Can AI replace policy work today? I picked a few ChinaTalk-adjacent questions around immigration, biotech, and Chinese EV imports, and put the models to work, identifying policy levers and building microsites to advocate for ideas.

This stupid new green card regulation

USCIS recently announced an idiotic new memo making green card applicants leave the country to do so. Besides separating hundreds of thousands of families, it would force Chinese AI researchers who want to work in America to go back to China, where recent reporting indicated that the Chinese government was taking away passports for top AI talent.

Can AI solve this?

All I told claude code to do was “make a maga microsite arguing that the latest green card application proposed changes are a terrible idea make it appeal to the trump white house.” I told it to “make it better” a few times and then asked for toggles for this site for five different political viewpoints, from MAGA to progressive.

It delivered an absolute gem, now live at FollowedEveryRule.org. Some highlights:

Evangelical version:

The tech right SKU:

And the progressive SKU:

Fwiw, OpenAI’s Codex rejects this as a use case：

Saving American Biotech with a China Tariff

I caught up with a Senate staffer who wanted some ideas on how to save the American biotech industry. Some have started to fear that the speed and cost advantages of developing and testing new drugs in China threaten the long term viability of America’s biotech R&D ecosystem. But the one thing Chinese biotech doesn’t have is direct access to the US market, far and away the most lucrative in the world.

I came up with an idea to take 10% of all the profits made by licensing Chinese drugs into America and putting that money back into the American biotech R&D ecosystem.

While I can cosplay as an AI subject matter expert, biotech is an industry I’ve invested far less time in. But with this kernel of an idea, how far could Claude Code take me?

I booted up my terminal and used the following prompt:

i have an idea for a new policy. ‘10% of the revenue generated by Chinese drugs that get licensed into the US market need to fund bio R&D that happens in the US.’ you need to do lots of research to figure out what are the best legislative and regulatory ways to make this a thing.

make a website on vercel that pitches this idea. do all the next steps for policy development, get subagents rolling, write up some legtext too

After ten minutes, it generated me a completely plausible website that does a better job arguing for policy than grasstops lobbying landing pages do.

While not at the quality of something I’d run in ChinaTalk, it did lay out in broad strokes the data you’d want to showcase to illustrate the idea. I felt like I just harnessed $5 of tokens to come up with a better idea than what the Congressional Commission on Emerging Biotechnology generated.

Oh Wait…

Feeling like I just cracked policymaking, I sent the site to a few friends. , frequent ChinaTalk guest and a more sane think tanker than me, responded:

Arnab: the idea of raising drug prices seems like a political loser

Jordan: but it’s like a tariff!

Arnab: that’s my point

And Kevin, a friend who works in biotech corporate development:

future deals would just price this in - so essentially European pharmas / biotechs not subject to the withholding (at least for the deal upfronts and milestones) would systematically be better able to license drugs from China

Alright, fine, maybe the mechanism isn’t perfect. But Claude can help with that.

i wanna do a deeper dive into whether the 10% flat rate makes sense or how to improve it. run lots of agents to do some really good analysis on this. then add a page to the website that proposes something more nuanced than the 10% flat tax

And it built me a whole system more sophisticated than a legislative assistant out of college could have spun up before AI.

At this point, I felt like I had something real, but was a little concerned that Claude was just glazing me. So I asked it to:

make a devil’s advocate page that does the best job of advocating against this idea

The first few arguments (WTO violation, loss of access to breakthrough drugs), did not resonate. But then Claude started to land some blows.

Starting to get embarrassed, I took the conversation off of my vercel webpage and into the terminal. Was this actually a good idea, I asked Claude?

B+ seems pretty fair! Next, I had it stack rank the most important things to do to unlock American biotech competitiveness.

As the cost and time required to do policy research comes down, the value think tankers can deliver will increasingly come down to taste and in-person persuasion.

On the policy research side, there are still plenty of angles of analysis which require deep context and talking with human beings who know things models can’t scrape or intuit. The centaur model dominates for now, but some really basic prompting I could have done in middle school got me much farther than I expected.

And on the politicking side, sitting at a terminal can’t do in-person meetings with staffers and principals, and deliver the face to face pitching which still matters in Washington. Today you can’t really have an AI spend money to donate to campaigns or funnel cash to cabinet members’ children. But we can’t be that far off from that future.

‘The Electric Fence’—Banning Carney’s China Cars

Another staffer-inspired shower idea comes from the fact that, despite Chinese EVs being practically banned in America, you can drive them across land borders without issue. If the US really wants to ban Chinese cars, having BYD dealerships pop up just across the border doesn’t seem like great policy.

Here are all the prompts I gave it. Initially it took my prompt and refocused it on a less gimmicky angle of this story: the fact that BYD is building factories in Mexico partially in the hope that they’ll be able to export to the US. If the administration wanted to piss Mark Carney off after his deal with Xi to allow the sale of a few Chinese EVs into China, it could ban Chinese cars from Canada (and Mexico) from crossing the border. Claude came up with an ‘Electric Fence’ proposal and accompanying EO.

1. i think the us should ban chinese EVs from crossing canadian and mexican borders. spin up some agents vibecode a policy proposal to do so, come up w a clever name and make a site on vercel. make it stylish dont make it look like ai slop. then make a page on the site that does devil’s advocate. look for ways to do this w executive action alone

2. write up EO text or reg text

3. what about canadians and mexicans who own the car just driving over the border? that’s what i was thinking about

4. refocus with cars that drive across, then do the other part

5. make it also highlight how trump can disrespect carney’s deal w xi allowing the sale of chinese evs by doing this. focus it on banning from canada alone, relegate mexico

The oneshot was fine, but I wanted it more Trumpy. So it made a MAGA-ified version, which you can check out here. [Note: I guess Dario is so lefty that I had to nudge Anthropic three times to get it MAGA enough].

1. just give it a more maga vibe

2. i want a maga aesthetic

3. make it even more maga not maga enough make more maga

Said staffer’s response:

For a little policy entrepreneurship comparison shopping, I gave Devin, Cognition’s coding agent, all the same prompts, and I think it did an even better job.

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Addendum: Can Agents Revive Congress’ Office of Tech Assessment?

From 1972 to 1995, Congress had its own tech brain: the Office of Technology Assessment. With two hundred staffers, it issued hundreds of reports helping Congress grapple with Japan’s technological progress…. Then Newt Gingrich killed it in 1995, leaving Congress starved for independent analysis of technology just as the industry grew increasingly more important to economic development and national security. In recent years, think tankers across the political spectrum have tried to get Congress to revive it.

I’ve had the OTA archive sitting as a snoozed tab for years, hoping to find something to do with it. I recently asked Claude to summarize OTA’s methodology and build a site imagining what the office would be working on if it still existed today. Here’s the result.

We are not there yet, but I’m looking forward to the day where models can give staffers their own personalized OTA reports!

How did Arizona lock in billion-dollar investments from TSMC, Intel, and LG Energy?

Ian O’Grady, Senior Policy Advisor to Arizona Governor Katie Hobbs, joins ChinaTalk to share war stories from the state that’s successfully reshoring semiconductor and battery production.

Our conversation covers:

• Labor Disputes and Crisis Management — How the Governor’s Office mediates disagreements between stakeholders and keeps workers happy.

• Clean Air Act vs. chips — Why Arizona’s fabs struggled to get building permits despite the state’s low per-capita emissions.

• Arizona’s Abundance Playbook — Including a consolidated commerce authority, a culture of engineering > litigation, and institutional factors that help Arizona outbuild Ohio and Texas.

• Taiwanifying the Desert — How Phoenix welcomed TSMC engineers with Mandarin programs in schools, Din Tai Fung, and a new Costco.

• Industrial Policy Resource Wars — How Arizona avoids backlash based on power and water use concerns.

Co-hosting is ChinaTalk analyst Aqib Zakaria.

Listen now on your favorite podcast app.

Rise Like a Phoenix 鳳凰涅槃

Jordan Schneider: Ian, you show up in January 2023, after the CHIPS Act has passed, and there’s already excitement about all the fabs potentially being built in the Phoenix area. What were the first semiconductor-related priorities that landed on your plate?

Ian O’Grady: The TSMC investment was announced in 2020. That was a huge day — we were getting one fab, and we were so excited.

The CHIPS Act passed in 2021, the IRA in 2022, and then we’re coming into 2023. We have all these incentives happening. We have all the reshoring, the bringing jobs back to America effort. That’s great. But anytime we have investment incentives like that, it sets off this huge competition between states.

Every state is then showing the companies and local governments: Why does it make sense to do it here? Once that process happens, it’s: Well, okay — permits, power, people. How do we hire everyone we need to hire? How do we get those folks into jobs? From fab technicians to security guards to construction workers, which is super important. On any given day, we have about 10,000 folks up at TSMC working on the construction side, which is incredible.

We’ve been super lucky over the past few years to have a ton of expansions. Going into 2023, we knew there were a lot of opportunities in the semiconductor and battery supply chains. We wanted to make sure we got those anchors.

We have LG Energy in the East Valley. We have TSMC in the North Valley. We have Intel in Chandler, Arizona.

Jordan Schneider: You guys showed up in January of 2023. The CHIPS Act had already passed, the IRA had already passed, and there was already a commitment from TSMC to build at least one fab and hopefully more. What sort of calls were you getting? Who was bugging you? How does a governor’s office define the role it needs to play in facilitating this federal money coming into your state and being taken up by these companies that have the potential to bring enormous economic benefits?

Ian O’Grady: These were huge investments in 2023. Coming from D.C., there was an open question on the ground about how to actually implement this. First, you have to construct the fab. We focused on the construction workforce — how do we invest in these folks? How do we make sure they have what they need?

If you check the headlines from 2023, there were many labor disputes. These industries moved overseas partly because American labor was expensive and more difficult to manage. How do we reshore this? In the governor’s office, we saw this as an opportunity, but we needed to figure out how to make it work and ensure we stayed on time.

The timelines looked tough. We hadn’t done this before at this scale, and all those construction sites were active at once. Governor Hobbs announced several different programs while also serving as the go-between for the companies, general contractors on site, and workers.

This is the perfect encapsulation of the mundane stuff — on the work site, we needed more refrigerators, more porta-potties. Basic stuff to make sure we were good to go on site. We also invested in apprenticeships, which were a huge choke point for the state. We had year-long, couple-year waits for electrical pipefitters. These apprenticeships, both union and non-union, were essential for building the fab.

In December of that year, the capstone of all this was a labor agreement between the workers, contractors, and companies. It outlined safety provisions and specified how many foreign workers were coming in, because that was part of the equation. We hadn’t set up these ASML machines in the United States before. How do we set that up and ensure quality?

These companies are professional athletes — LeBron James level. They know what they’re doing. They’re willing to train American workers because they understand that long-term, they want to keep building here. Whether it’s on the construction side or the technician side, they need to train the local workforce. In those talks, we emphasized that we want Arizonans to have jobs from these projects.

Jordan Schneider: Can you describe the type of calls you receive daily as the policy advisor for workforce development?

Ian O’Grady: The great thing about a governor’s office is that it involves everyone. It’s a combination of VEEP and Parks and Rec.

In terms of who’s calling me — first, you have the workers on site: the contractors and the labor unions represented there. Then you have the feds. This was a huge priority for the Biden administration, so it’s Commerce and CHIPS. I talk to my counterpart there probably every other day to make sure we’re getting these projects online.

We use the word “ecosystem” a lot because it includes community colleges, universities, and the permitting entities for water, sewer, and power — making sure that’s all coming online. The magic is making sure all these components converge at the date they want to start producing chips, which is a ton of work.

At this first stage, it’s almost entirely a construction conversation. We have some permitting things that come later once you get to production, but right now it’s: How do we get the workers out there on site? They have intense demand over the foreseeable future — the next decade — across sites in the state.

Jordan Schneider: What are the near-term and medium-term levers for the workforce that a particular state can pull to help you beat out Texas or Ohio?

Ian O’Grady: Those are definitely the competing states.

Near term, one lever is just awareness that these projects are happening. Intel has been here for about four decades, so there’s awareness. But when you talk about TSMC or LG, there’s very little awareness of what that is, let alone that someone should go work there.

We’re trying to divert folks who are in the workforce looking for an opportunity. We need thousands of people to understand what that mission is, why it’s so cool, and why they would want to work either in building or operating the fab. That’s been relatively successful in terms of our recruiting and getting ahead of schedule on these sites.

Jordan Schneider: What does that mean exactly? Are you doing events and pushing reporters to write about this?

Ian O’Grady: This has been a partnership between the TSMC team, the Arizona State University team, our office in promoting the trades, and a lot of the local officials to talk about these opportunities.

There are also partnerships with high schools and K-12 education. This is more of a longer-term thing, but think about when you were a kid — what do you want to do for your career? Be a firefighter, be a doctor. We want “semiconductor technician” or “someone in the pipe trades” to be one of those options.

We’ve been working with the local school districts in that area to help them understand what those careers are, so you have folks graduating high school and going into those jobs. It’s those technical education districts and that whole local area that we’re really excited about.

Jordan Schneider: Does the market not figure all this stuff out? There are new jobs here, and presumably, they have to pay better than whatever the alternative is to get people to show up in the first place.

Ian O’Grady: That’s a question we get a lot, especially in Arizona where we have divided government. Many folks in the legislature believe the free market should fix this.

There are two factors at play here. First, you need an industrial base of talent that no one else is going to invest in. That’s essential not just for TSMC and Intel, but also for their supply chains. What has helped us secure so many projects is this latent base of talent that can transition — whether it’s battery manufacturing, aerospace, or semiconductors. These workers have skills from the ASU engineering school, the largest in the country, that we can attract and deploy to fill these jobs.

Certainly, companies might eventually invest in their own programs, but we don’t have time for that. We need these programs ready now, and we’ve been planning for this for the last 10 years.

The other challenge is the friction of setting up operations in the United States. Taiwan is set up to support their fabs — the times I’ve been there, it’s remarkable to see those connections. Understanding where to go in the US system isn’t easy. Our workforce system is something we’ve worked hard to simplify, creating one front door. But between community colleges and high schools, it’s still complex.

From the government side, we have to make it easier for companies to navigate because they do want to be good partners and invest in the workforce. Knowing where to go is half the battle.

Aqib Zakaria: I remember when this movement was first getting off the ground — the idea that we should build chips in America. Everyone was saying, “But we don’t have people who do that kind of work.” Unlike Taiwan, where everyone knows TSMC offers the highest-paying jobs.

I see you’re working with ASU and other community colleges to develop that workforce for the future. But that takes years to develop, and TSMC still has so many Taiwanese engineers. How do you know this is succeeding? How can you feel confident that people from ASU or Arizona are actually going to work at these fabs?

Ian O’Grady: I grew up here — Arizona State University has the largest engineering school in the country. We provide the most engineers. They usually leave. That was the opportunity: to keep those folks home and have opportunities in Arizona so they don’t have to move. Many of them don’t want to move, but they usually end up at Ford or automotive companies in Michigan or Ohio. Now they’re staying here.

How do we know it’s working? The chips are being made.

It’s been really fun to see the schedule and the progress of the facilities. I don’t know if you guys have been up to drive by either one of these — Intel down in Chandler, TSMC up in Phoenix. They’re the most amazing buildings you’ll ever see in these complexes.

In terms of connecting folks to those jobs, it’s been redirecting resources. We actually just set up a clean room for training down at the University of Arizona, so they have even more resources down there. Northern Arizona University has a really great metrology program, which feeds directly into some of the toolmaking. There’s been this demand and they’ve really answered the call on the need for these jobs, keeping up with the new technology. But it’s been keeping folks here, and that’s been — as a native Arizonan who’s moved back, I have a special kind of feeling towards that story.

Aqib Zakaria: What about ironing out the wrinkles between Taiwan workers and then the workers that are coming from ASU or that are trained in Arizona? I’ve heard a lot of stories of language barriers or work style differences. What role does the state of Arizona play trying to iron that out and make sure it goes smoothly?

Ian O’Grady: That one has been somewhat resolved by the company because they can’t bring over all these folks to operate the facility. We have Taiwanese restaurants now. The cultural integration has been really great. The Arizona Diamondbacks now host an event celebrating Taiwanese baseball and culture. It’s been something that we’re aware of, but really something that has sort of resolved itself over time.

Jordan Schneider: What about on the other side — how do you make sure the Taiwanese and Korean employees are excited to come to Arizona?

Ian O’Grady: There’s a stat the city has about how many babies have been born here from Taiwan in terms of new families setting up and being here in Arizona. There’s been a lot of work in the neighboring school district to make sure that they’re catering to Mandarin and having English immersion programs, which has been really exciting. Parents and kids here in Arizona want to learn other languages.

We’ve been really focused on childcare. These are the family parts, but we have a lot of families — a lot of senior folks who are moving here who want to be part of the community. The most exciting thing is in that area around both Intel somewhat, but more TSMC, because it is greenfield development. It’s a part of the city that was just desert. We’re building a new city, so we have an opportunity.

My understanding is the workers are super stoked about Costco — the folks who are over from Taiwan. We’re going to be building a new Costco up there, so they don’t have to drive as far. There’s a natural friendship between Taiwan and Arizona. We’ve been training the pilots from Taiwan out at Luke Air Force Base for going on four decades. There’s that natural kind of friendship happening.

Aqib Zakaria: I remember I was flying back from Taiwan a couple of years ago, and the guy sitting next to me was an engineer who was going to go work at the Arizona fab. He was originally kind of sad. He’s like, “I’ve heard there’s only one Asian store there.” Now I’m glad that there’s a Din Tai Fung and a Costco being built. It’s a little bit easier.

Ian O’Grady: There are a lot more Taiwanese restaurants. A lot of food trucks, too. It’s really coming along.

Crisis Management

Jordan Schneider: What kinds of acute crises end up falling on a governor’s office? Can you share any war stories about helping these buildouts develop?

Ian O’Grady: When we arrived, I emphasized how crucial construction was — just the ability to build the fabs. Whatever the motivation, we had to take this seriously. What did we need? What did we have to do? While negotiations were happening with the federal government, we wanted to create as friendly an environment as possible.

The first challenge was a significant worker dispute at the facility, which everyone now acknowledges we handled well. I’m proud of how we came together. In my timeline of building semiconductors in America, this was significant — we hadn’t done this in a long time.

The workers said conditions weren’t great and needed improvement. The facility folks and contractors said workers were being difficult and needed help. The company wanted to resolve this as quickly as possible. It wasn’t clear if anyone could talk to all three parties, but the Governor’s Office stepped in. We created what we called the tripartite agreement in December of that year.

The solutions were mundane but important to workers. It wasn’t that the company or contractors were intentionally withholding things — workers needed more refrigerators for their lunches, which makes sense with 10,000 people on site. They wanted greater access to porta-potties. These basic things made everyone on site really happy.

From the governor’s side, we’ve invested $5 million in apprenticeship programs because leaders said they couldn’t recruit fast enough and needed to build capacity. We gave them money for textbooks, classrooms, and equipment to build the pipeline. This also made them feel we were looking out for them overall, while serving both TSMC’s workforce needs and the contractors on site.

We also implemented a safety agreement. The state oversees facility safety, and there had been claims it was unsafe. We arbitrated this, offering a state program where they could sign on to go above and beyond OSHA standards, making it a platinum safety site.

The willingness of TSMC to learn and work with us, combined with workers’ willingness to come to the table, created a relationship we’ve really cultivated from the governor’s office. This was a priority in 2023. At one point, we thought there would be a strike — we were very concerned workers would walk off. We intervened alongside Senator Kelly’s office, facilitating required conversations that took months to resolve.

Jordan Schneider: The first TSMC fab is basically up and running, right?

Ian O’Grady: It’s producing chips.

Jordan Schneider: How do you measure a fab being “up”? Is it when you get your first wafer, or when it’s economical to operate? There’s probably a six-month window of just tweaking various manufacturing processes.

Ian O’Grady: There are different ways to think about it. Currently, it’s producing engineering wafers — they’re not the wafers that would necessarily go into production. But yes, it is producing chips. As for what’s left to finalize, that’s something for TSMC to comment on.

Jordan Schneider: What has been the hardest part of getting to this point?

Ian O’Grady: 2024 brought significant challenges related to air quality and the Clean Air Act. There was a moment when I wasn’t sure how we would permit multiple fabs.

Here’s a quick Clean Air Act primer: If you’re in a nonattainment area — meaning your pollutants exceed certain thresholds — you cannot build new major facilities unless you offset those emissions. Arizona currently exceeds ozone limits. However, 80% of our ozone comes from elsewhere; we’re not a high-emissions state. This law was traditionally written for East Coast states like Detroit or western Pennsylvania — areas with large emissions.

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This makes the offset problem even more difficult. You need to find offsets within the area that can balance the emissions of the facility. These are large facilities emitting certain types of pollutants that combine to produce ozone.

The county serves as the permitting entity under federal law. The city has some involvement because we can convert buses and baggage carts at the airport to help create the permits and credits for TSMC. This remains an ongoing discussion with the EPA.

Finding those credits and ensuring compliance was an extremely difficult lift for us. The state approached the CHIPS office about the issue, then worked with the county to determine how to make the permit happen while following the law.

Permitting and Process Bottlenecks

Aqib Zakaria: I want to dig deeper into the permitting issue. Now, with data centers and the abundance movement, everyone claims permitting is the problem — that it’s too slow or nonsensical. How does it work for you to collaborate with the county level to actually get permits approved? Can we build things if we want to? Can we permit things quickly? What’s the bottleneck?

Ian O’Grady: This situation perfectly encapsulated that conversation. This was the top national priority — building out our ecosystem with TSMC and Intel in the Valley. Everyone agreed this was a priority. Yet we were bumping up against the Clean Air Act from the 1970s, which is probably the most important public health legislation we’ve had. Many studies document lives saved and how it’s cleaned up city air.

However, it wasn’t quite designed for our situation — we weren’t causing the problem here, which created an even more vicious permitting challenge. We’ve had many productive discussions with bipartisan support. The governor has met multiple times with the EPA administrator. As Churchill might say, at the last moment, we’ll do the right thing — but it took substantial work.

The first fab is always the hardest. Now that we’ve done this, we can do it again. We have a path forward. The air quality issue remains complicated because you need to keep finding offsets. If we keep building, we need to keep finding offsets in an environment where we have very few, since we’re not a high-emissions state to begin with.

We can do it. Here in Arizona, we’re the first and only state to reach this point. I believe Samsung’s facility isn’t quite operational yet in Texas, and Intel is far from being up in Ohio. Our experience demonstrates that yes, we can make this work.

Jordan Schneider: This idea of pro-business as a vibe versus being pro-business as actually dealing with nitty-gritty mundane policy stuff — does the energy that a politician brings to these questions matter at all relative to page 34 of the submission to the CHIPS Act? How much do the atmospherics actually impact these sorts of issues?

Ian O’Grady: It’s a ton. I think of this in terms of trade missions. It’s not quite the political domestic politics question of “are you pro-business?” or “how do we feel about you?” When Governor Katie Hobbs went to South Korea after we had visited Taiwan — they know us really well there — we were talking to some suppliers, making sure they’re comfortable with coming over to Arizona. That kind of openness helps.

On an international scale, I realized that in South Korea, they really hadn’t thought about investing in Arizona. That kind of openness and subnational diplomacy of talking to companies in South Korea, and showing up on their doorstep, makes a difference. It’s one thing to have a call, but it’s another thing to go to their country and say, “Hey, we have a few partners here. We want to be as helpful as possible.” That means a lot.

Domestically, the governor’s approach has been that we’ll meet with anyone — it’s always an open door. One week I’m talking to a labor union, the next week I’m talking to a free-market business group. Our work represents the state of Arizona. We’re probably the reddest or purplest purple state, and we understand that we have a really diverse business community and workforce. We need to reflect that. We can’t be too ideological. Where Democrats get into trouble, especially, is when they stop taking meetings and talking to people.

Jordan Schneider: I remember being at SEMICON Taiwan two or three years ago, and Arizona and North Dakota were the only two states that had booths. I was talking to these people and they said, “Our states invest in this. We think the human element of this sort of thing is important,” which was surprising and wonderful. It’s interesting to see how you think that pays off. At the level of vibes for other countries, there are 50 states, right? Maybe you’re thinking America, but you’re not going to literally talk to all 50. It’s just easier if there’s some sort of level of awareness and face given initially.

Ian O’Grady: A level of comfort shows that you’re trying and getting out there, showing up. But that only lasts so long because eventually companies want to see the pro forma — let’s get down to it. That’s where real policy matters. You need both elements. You don’t close a deal without the policies being effective.

An example of this nitty-gritty work — though it isn’t legislation or written policy — comes from our broadband expansion efforts, which involves extensive permitting work.

In 2023, we dealt with a company that had been waiting about two years for a right-of-way permit to dig and lay fiber. They were going from agency to agency. They’d go to the Department of Transportation, who would identify an archaeological issue and send them to the State Historic Preservation Office. After pulling a ticket and waiting in line for an archaeological study, they’d return to the Department of Transportation only to be told about wildlife issues requiring a trip to the Department of Game and Fish.

We’ve flipped that process. Our commerce authority on broadband now pilots a one-stop approach for the massive permitting exercise happening around broadband. We handle that coordination work internally, making it easier and less of a headache for companies.

It’s hard enough for American companies. Imagine meeting with the governor of Arizona about investing in the state, then discovering you have to navigate counties, cities, water districts, and utilities — all separate entities. When we streamline this process, we remove a significant administrative burden from companies. While the market might eventually figure this out, making it easier gives us a competitive advantage.

As far as the legislature goes, we’re currently in the middle of budget negotiations. Each year during the legislative session, the governor delivers a State of the State address to kick things off. Since the budget expires July 1st, there’s a race to pass the new budget by June 30th.

Throughout the session, legislators introduce bills and ideas. Both our Senate and House have Republican majorities. Unlike the partisan, intense environment my friends describe in DC, I maintain excellent relationships with my counterparts on the majority staff in the legislature. Everything we do becomes a bipartisan act by necessity — nothing gets through the legislature unless it’s a Republican bill with Republican support for the budget.

The governor has established a litmus test: Is this bipartisan? Did you work with Democrats? Does this represent the widest swath of Arizonans?

During the session, I track about 200 bills, ensuring we’re prepared for each one. Some bills we’ll never sign, and we make that clear. Others we’re happy to sign. The challenging ones fall in between — the edge cases that might upset a stakeholder or don’t quite work for us. We have to decide whether to improve them or leave them alone. That’s how I spend much of my springtime.

Data Centers, Infrastructure, and Getting the Public on Board

Jordan Schneider: What were the best and worst bills related to industrial buildout that you’ve encountered?

Ian O’Grady: There’s been a lot of AI legislation coming through about how to regulate the technology. I’ve been watching AI safety bills, particularly because the Trump executive order attempts to preempt states, though there’s a safety exception — especially children’s safety. We have a couple of kids’ safety bills in that category.

Infrastructure remains the biggest legislative challenge. It’s the limiting factor for so much of what we do. We’re a low-tax environment, which means we don’t have all the tools that other states have. Some states will cut companies checks when they relocate. Others waive property taxes or build much of the infrastructure themselves.

We do as much as we can, but we have to figure out the taxing mechanisms. How do we accomplish this without cutting government further? Since 2000, our population has increased 40%, yet we have the same number of state workers, and our economy has grown even more. We don’t want to cut existing services.

When companies come to a state, they expect roads and water pipes to be in place. How do we meet those expectations? We’ve been working on legislation to fund these projects.

Aqib Zakaria: I’m curious about AI legislation in Arizona, particularly in the context of fab buildouts. Is there a connection between the average Arizonan being happy about TSMC and Intel bringing jobs while simultaneously being skeptical of AI and data centers? Is there a mental disconnect, or is Arizona more pro-AI?

Ian O’Grady: We’ve seen similar zoning issues across the country. We’ve had a couple of very intense ones for large data centers. There’s skepticism, especially when costs are higher than they were five years ago and people are thinking, “Why are we doing this when my rates are going up?” A lot of those concerns are widespread — they’re national, they’re here.

In terms of the politics and how they’ve played out, Governor Hobbs in her State of the State speech addressed an incentive that provides a tax exemption for the chips and racks in data centers. We passed this around 2013, when it wasn’t a huge deal — they weren’t cycling out these chips every 18 months and they weren’t super expensive chips.

Now the exemption’s grown and there’s no cap on it. It was in the tens of millions of state revenue that has been lost because we don’t tax these things when they build the data centers and then refresh them. The governor said we’re the second largest market for data centers in the country next to Virginia. This tax incentive has worked. What is an incentive for us to create new markets, to bring along new industry? We should eliminate this tax incentive. We’re not anti-data center. Given the math equations we have to do in a state like ours, this doesn’t make sense anymore.

The other part is she proposed a fee on water use — a cent-per-gallon water use fee on data centers. We know that a lot of the more modern data centers are using closed-loop systems, and we don’t want them pulling water from our aquifer because we are in a desert environment. We have to be very, very wise about water.

Those were two proposals. Republicans have basically called those DOA, which has been a really interesting political calculation in terms of just the political mood. We think this is the right policy. I’ve been in those discussions that these are things that we think make sense for the state, and we’re going to keep building data centers that can keep existing, but they just don’t need state subsidy and we want to make sure they’re using our water wisely. We’re on the winning side of that argument on a few different aspects.

Data center politics are everywhere right now. It is probably one of the hottest issues.

There are two sides of the argument. One is from maybe the far left: “We don’t need this technology. This is not making our lives better.” There’s a lot of work to do on that side. I believe there are going to be immense benefits. Doing slop posting and whatever’s been produced probably doesn’t help. I’m very curious when companies produce those types of silly videos — is that really what we need?

On the far right, or maybe more of a normie argument: “Everyone else is doing data centers. Why should we?”

We’re in the middle — we want to attract, we understand they’re necessary for modern technology. We realize we have a lot of advantages in Arizona in terms of building them and we’re building the chips for them. We understand the attraction. But we’ve got to be so smart about how we do it.

Aqib Zakaria: Is the state legislature on the same page about incentives, or is there push and pull?

Ian O’Grady: It’s absolutely a push and pull. They’re still focused on cutting government and lowering taxes, period. We want to have a conversation about what incentives make sense because we do have a ton of exemptions. Every year — and you’ve seen this at the national level — we’ll exempt taxes for this and this and this. We’re asking: What’s the justification for these incentives? That’s a conversation we really want to have.

Jordan Schneider: How does state-level competition play out? Are you tracking every other state’s offerings? Does that argument resonate with the legislature? How much comes down to the inherent factor endowments of what the state has to offer versus whatever package you’re negotiating at the last minute?

Ian O’Grady: We’re competitive with other states both on a cost basis and on long-term cost over time and quality of life. There’s a whole site selector industry — I don’t know how much national folks are aware of this — but there are consultants who help companies run these competitions, line up states, and figure out where they’ll be most effective. In your analogy, these are like the agents doing this work for companies.

Ian O’Grady: While we don’t have as many upfront cash incentives as other states, the big factors that matter are:

Workforce has been a huge priority. Companies need confidence they’ll be able to hire and start on day one — security guards, cafeteria staff, engineers, PhDs. That’s a gargantuan task. The confidence I’ve seen when people come to Arizona that we can deliver on this has been great.

Power costs are very competitive. Energy is a significant ongoing operating cost, and we’re well-positioned there.

Road quality really matters. Being able to move large machines or spacecraft across an interstate is super important. There’s another very competitive city that just doesn’t have a great highway system, and that’s become a huge advantage for us.

We’ve had people come to Arizona and say the traffic in that other city is horrible — they love being able to access meetings easily here. Our airport’s proximity to downtown is another advantage that’s not always the case elsewhere.

Water security is crucial. We’re in a desert environment and have been very judicious with our water — we actually use less water overall than we did 50 years ago, which is crazy given our population and economic growth. We have a state law requiring demonstration of 100 years of water supply in metro areas. If you’re building in Arizona, you know you have 100 years of water. No other state has that. That’s been a huge asset, especially as drought conditions and water shortages have emerged across the West.

Aqib Zakaria: I’m wondering about roads. Is there a positive externality where wanting to attract foreign investment incentivizes the state to fix roads and power infrastructure? Does that mental calculus happen, or are those completely divorced?

Ian O’Grady: It certainly happens on the power side. We have economic development divisions that work on this. That’s long been part of our state’s history — we’ve built dams for hydroelectric power and then attracted new growth. There’s this great factoid from our history where utilities paired up with homebuilders to ensure new homes had plug-ins for dryer units, so they’d use the electricity being produced. Those partnerships certainly happen on the utility side.

On the road side, we just passed a new multi-billion-dollar investment in our highway system around Phoenix, and Tucson just did their own too. It really matters for getting to and from places, especially for executive-level meetings. When the board’s in town, it’s been a huge deal. More than once, I’ve been involved in figuring out permits to move spacecraft across the country on the interstate. You do this in the middle of the night so you’re not in people’s way, but being able to do that on really straight, wide roads is important.

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Jordan Schneider: People are stressed out about power. You guys aren’t for now. Where does that come from? What’s the backstory there? Thoughts on broader lessons for the nation?

Ian O’Grady: We have a good mix of power. The Governor did an executive order in the fall to bring together a massive task force with utilities, businesses, consumer advocates — everyone. They just published their list of recommendations. It was the Arizona Promise Energy Task Force. Those are online if folks want to read them. I think it’s a national best practice in terms of what’s in there. Now we’re going to work on implementing those.

In terms of the mix I mentioned, we do have one of the larger nuclear facilities in the country. The Governor actually just toured it yesterday. That creates that base level — I forget exactly what percent, but it’s significant. We have some solar, some wind, and significant natural gas. Coal has been coming offline recently, but that mix has been super helpful.

Our ability to build transmission lines has been huge. We’re working with our state land department to create corridors where we can further transmission lines. That nimbleness we’ve shown versus legacy states, where you have old systems and it’s just harder to move, has been a huge benefit for us.

Aqib Zakaria: Why can Arizona build when other states can’t?

Ian O’Grady: I think about this a lot too, and I talk to counterparts in other states. One aspect is that we’ve done a really good job of centralizing this. We created a statewide commerce authority — we got rid of our old Department of Commerce and made this quasi-public entity that’s been great.

We’ve had the same CEO for a couple of decades. Her name is Sandra Watson. She’s amazing — I’d say she’s the best state commerce director in the country. Being able to act nimbly in terms of that board has been huge. You have CEOs on that board who direct where our incentives live, and you have that input. That has made us very effective in attracting businesses.

My theory on why we can build, from talking to other states and going to conferences, is that there are states where you have this layer of sediment — “we’re in oil and gas” or “we’re steel and automotive” — and that creates this drift of “that’s what we were made to do.” They can’t quite get to the next level.

Versus in Arizona, we have some legacy industries, but they’re all engineering-focused, so they actually end up being a benefit. We’re a growing state with new population coming in. We’re now retaining more of our grads.

I think of the lawyers vs engineers dynamic in Dan Wang’s book Breakneck — we have a lot of engineers. Reading his book, I was thinking there are some similarities between Arizona and some of the cities he’s talking about in China in terms of our ability to build.

The consolidation with the Commerce Authority also helps us quarterback with the localities. I’ve seen other states with really intense competition between metros where the state can’t operate effectively. In Texas, it’s Houston, Austin, Dallas — if you’re the state and a project comes, folks are fighting over who gets it.

We’re now at the stage in Arizona where everyone understands that we should celebrate each other’s wins and that there’s enough to go around. That’s a feature of years of learning and success with the major anchor investments we’ve gotten. We’re in a really good position to continue — we’ve had 70 semiconductor expansions alone in the last couple of years, which is just crazy.

Jordan Schneider: Other lessons for other states or national policymakers you’d like to share?

Ian O’Grady: I think there are some pretty basic resources you have to think about as a state. We talked about roads, but rail access is super important. That’s something we’ve been thinking about in terms of expansion — getting goods on and off the rail line and moving them across the country, especially as we manufacture them.

For national policymakers, we’re in the midst of pretty intense Colorado River negotiations. The agreement we’ve had for decades, allocating water across the seven basin states, is expiring. Our argument in Arizona is that no other state produces more advanced chips, more guided missiles, or more leafy greens per drop of Colorado River water.

Not to pick on Wyoming, but I looked up semiconductor employment by state. Wyoming had literally zero. We’re making an argument in this process — which is being run by the Department of the Interior — that yes, we understand drought conditions. We’ve put our own cuts on the table. We’re offering to cut 27% of our usage because we’re more efficient. No one else in the upper basin is offering cuts like that. But for the Trump administration, no one offers better ROI than Arizona in terms of that water.

Are you guys familiar with the book Cadillac Desert about water history in the West?

Jordan Schneider: Pitch it.

Ian O’Grady: Great book on water history. It’s from the ’80s, so it’s a little outdated. But they make this argument that I think about a lot in terms of Arizona: The ability for the United States to win World War II was based on our hydroelectric capacity in the West and our ability to produce at scale. Boeing, Northrop Grumman — all the aerospace companies emerged because they had access to that power, because we had the geological features to create rivers that could generate electricity. That’s why we were able to produce at a scale that neither Japan nor Germany could match.

That’s relevant today. When I look at how the river is being allocated, we have really clear decisions to make about where that water should go, especially for all our national priorities. We’re making that case probably on a weekly basis to our colleagues in other states and in D.C. But right now, the current direction needs to change if we’re going to be able to continue producing like we do.

Building the Ecosystem

Jordan Schneider: What’s your take on trade dynamics and foreign investment, especially with USMCA coming up for review?

Ian O’Grady: We’ve been working closely with Mexico — the Governor’s visited several times since they’re our largest trading partner. With USMCA up for review on July 1st, we’re quite concerned about the direction it’s heading.

We’ve spoken with the US. Trade Representative, and they’ve indicated they don’t think they need Congressional approval. They’ve also made it clear: “Don’t expect North America to be a free trade area.” The Trump administration’s overarching concern is preventing Mexico or Canada from becoming a backdoor for Chinese goods into the US. market.

Mexico’s own China politics are fascinating right now. The Sheinbaum administration has launched a “Made in Mexico” — Hecho en México — initiative and they’re placing tariffs on China. But when you actually look around Mexico, the new cars are mostly Chinese EVs. It’s a really interesting dynamic, and we’re working hard on USMCA issues to address these concerns from the Trump administration.

Jordan Schneider: There’s a big debate in Washington about bringing in Chinese industrial investment. The hope would be that companies like BYD, battery manufacturers, and rare earth refiners could replicate what LG and TSMC have done in Arizona. Based on your experience, how would you approach setting up or incentivizing these agreements to ensure long-term technology transfer?

Ian O’Grady: The joint venture conversation is complex, especially in automotive where there are so many competing interests.

From a supply chain perspective, Mexico is absolutely ready for chip assembly and automotive parts manufacturing. They’ve become very strong in aerospace and medical devices in recent years — they’re ready to build.

The jump to automotive manufacturing is particularly challenging. We have our first major OEM, Lucid Motors, making EVs south of Phoenix. Getting that workforce up and running was like building TSMC’s first fab — you learn so much in the process. We want to build that ecosystem, but nobody really knows what the future looks like for automotive investment right now. There are fundamental questions about internal combustion versus electric vehicles. The Iran situation and gas prices might revive the electric conversation.

Arizona has huge advantages here — we’re the number one copper producer in the country with a significant critical mineral supply chain. We’re going to be producing batteries at scale, which is generating a lot of interest. But ultimately, the market is the market.

Aqib Zakaria: I’m curious about the ecosystem aspect, since so much of this really is about ecosystem development. You can’t just have an EV fab in the middle of a state without the supporting players around it.

I wonder how you sell that vision — it’s really sexy to say “oh, we built an EV factory,” but it’s not as much of a PR win or as compelling to say “okay, we’re expanding copper production.” These supporting industries may be more commodity-based and cheaper, but they’re harder to make attractive. How do you try to actually make that ecosystem happen? It’s an enduring problem in the States.

Ian O’Grady: From a state level, we want to create what I think of as the substrate or the platform. We want good roads, good railroads, good connectivity so that we can just move heavy things. That’s a big part of critical minerals.

In terms of opportunities in mining — we’re a mining state. In Arizona, we say we have the 5 C’s: copper, climate, cattle, citrus, and cotton. Copper is the big one — our state seal has a copper miner on it. It’s very much part of our DNA. My family actually moved here in the 1870s to be miners. There’s really an awareness of it.

There are things that come along with it, too — these mines have a shelf life. We have open pit mines sitting across our state where we see the scars, but we also see opportunities. You have really innovative things happening in terms of mine reclamation and being able to extract metals at a more micro level.

We have many major mining projects coming online. We’re actually number one in terms of jobs growth and number one in terms of mineral exports already, and we don’t even have major projects online yet for new mining. Those build a lot of jobs.

At a corporate level, Lucid Motors understands that more of their supply chain is going to be in Arizona. With USMCA, it almost has to be. That’s helpful on that side. In local communities, there are pros and cons, but there are jobs coming in — these are legacy things that people remember in Arizona.

Jordan Schneider: You want to tell them about your adventure, Aqib?

Aqib Zakaria: Oh yeah — I’m from Louisiana, and while we’re not building fabs or EVs yet, we’re expanding gallium production. They’re opening up a lot of refineries, so I’m hoping to go there to see how that actually ends up working out.

Jordan Schneider: We’re going to do a work study tour. We’re going to have Aqib in the mines — we’ll see how long he lasts.

Ian O’Grady: Where does the gallium come from? Where are they extracting it from?

Aqib Zakaria: It’s a byproduct of alumina that they make. We already have alumina refineries, and my surface-level understanding is that the byproducts are actually a big pollutant, but now you can take that byproduct and refine it into gallium.

Ian O’Grady: That’s so cool. We have a mine that will produce zinc, manganese, copper, silver, and lead. It’s a site being revitalized by South32, an Australian company down in Southern Arizona.

Mining today is completely different. They’re actually running fiber lines from the town of Nogales, which is the biggest city in the county down there. They’re going to have a command center, but it’s all robots in the mine. It’s much safer. The tailings are going to be backfilled into the mine, so you’re not going to have a huge tailing site.

Aqib Zakaria: I’m jealous. I’m happy for Arizona, but I’m waiting for TSMC Thibodaux or whatever it’ll be.

ChinaTalk analyst yearns for the mines. He’s on a mission to visit rare earths and other critical minerals mining sites, refineries, and permanent magnet facilities around the world.

If you or anyone you know can help him fulfill this mission, please reach out to aqib@chinatalk.media.

Less than one in a thousand Chinese people owned private cars in the 1990s. But in 1993, a vehicle guided by a computer program landed on the floor of a car plant in Shenyang, capital of Liaoning province. Xianfeng 1 先锋1号 was the first of its kind in China, developed entirely by Chinese researchers.

The car plant had previously relied on American-made autonomous-guided vehicles, but the US tightened export controls in 1991 and cut off sales to China. The plant turned to the Shenyang Institute of Automation (SIA), an institution of China’s national academy, the Chinese Academy of Sciences (CAS). It was led by a scientist called Jiang Xinsong 蒋新松.

To the average person today, “AI” is synonymous with chatbots — or, at least, tools that exist only in the digital realm. Hardware manifestations, like humanoid robots or intelligent Roombas, are instead considered futuristic.

But “Chinese AI,” as an idea, did not necessarily begin with DeepSeek or tech companies in Hangzhou. It started on assembly lines in the Northeast, with dreams of intelligent oxygen furnaces for steel production and automated car plants. Some of the earliest champions of artificial intelligence research were not software engineers or information scientists, but those working shoulder-to-shoulder with factory workers.

As Chinese firms like Unitree became forerunners in the race to build autonomous robots, I grew curious about Jiang’s story. State media has dubbed him China’s “father of robotics.” His work — and what he would have conceived of as “artificial intelligence” — is substantively different from deep-learning-driven robotics today. However, the information scientist who petitioned Beijing for what arguably became China’s first industrial policy for AI was thoroughly ahead of his time.

Jiang is increasingly compared to figures like Qian Xuesen 钱学森 in official narratives. Qian, deported from the US under the Red Scare, fathered ballistic missiles and rockets; it is said that Jiang, who never left the country until later in life, did the same with industrial robots. These laudatory stories omit thornier, though more intriguing, parallels. Like Qian, Jiang’s life was one where science and politics were fair-weather friends.

The Road to Shenyang

Jiang Xinsong never expected to end up in the Northeast. Born to a common family in faraway Jiangsu in 1931, he entered Shanghai Jiaotong University — also Qian Xuesen’s alma mater — to study electrical engineering in 1951. After a high-achieving first year, he was sent to Beijing to learn Russian and prepare for study in the Soviet Union. But after a physical exam revealed tuberculosis in his lungs, he was forced to return to Shanghai. In 1956, Jiang graduated and started working at the Chinese Academy of Sciences’ Institute of Automation in Beijing, where he joined the newly-established computing technology group. There, he designed memory units for some of China’s first computers.1 He was a rising star of the national academy, working at the cutting edge by day and studying German at the Peking University library by night.

The good times didn’t last. Swayed by the permissive atmosphere of the Hundred Flowers Campaign, a young Jiang advocated for institutional reforms:

He supported making one’s dossier open to the person concerned, and once said: “The Soviet Pravda claims to represent the truth, but in fact a lot of what Pravda publishes isn’t true.” … After the Anti-Rightist Campaign began, he proposed that small-group meetings should not be minuted and should not be reported up the chain. He said: “The People’s Daily is accustomed to using the ‘Editor’s Note’ tactic to deal deadly blows to anyone being criticized.”

— Jiang Xinsong’s alleged transgressions, according to his “Rightist Registration Form” 右派分子登记表

Political winds at CAS immediately turned against him after Mao Zedong initiated the Anti-Rightist Campaign in 1957, and he was sent to rural Hebei for hard labor. Luckily, in December 1958, Jiang was summoned back to the CAS to work on automation research for industrial applications, since his field was deemed useful by the state. Officially, however, he was a “rightist” until 1963, blacklisted from promotions and unable to travel.

In 1965, 140 automation engineers were reassigned from various posts across China to Liaoning, with the goal of bringing new technological advances to the heavy industrial base there. Together with Jilin and Heilongjiang provinces, Liaoning is part of China’s frigid Northeastern region formerly known as Manchuria. Between 1932 and 1945, the region developed into an industrial powerhouse under Japanese occupation, supplying Tokyo’s war efforts with natural resources, heavy industry output, and railways.2

As WWII drew to a close, the Soviet Union invaded Manchuria in coordination with the US’s atomic bombings of Hiroshima and Nagasaki. Soviet forces occupied Manchuria until 1946, when the territory — and its remaining industrial resources — was transferred to the Chinese Communist Party. Upon its founding in 1949, the victorious People’s Republic inherited not only a liberated Northeast, but also a critically important industrial base that powered its earliest technological ambitions.

Jiang Xinsong was part of the 1965 reassignment cohort. For two years in Liaoning, he helped revive the remains of Showa Steel Works — a massive steel mill established under Japanese rule — in Anshan 鞍山, Liaoning, researching automation for the cold-rolling process. From the ruins of war, steel sheets were again pouring out of Anshan’s factories.

Dreaming of AI during the Cultural Revolution

For the first three years of the Cultural Revolution, much of non-political life in China ground to a halt. In 1967, the Anshan mill, too, paused production, and Jiang headed to Shenyang. At the SIA, checkered records from previous political campaigns meant he was subjected to brutal struggle sessions. But once again, he narrowly avoided being sent down to the countryside. In October 1967, the new “revolutionary committee” that displaced the mill’s old leadership summoned Jiang back to Anshan to maintain its reversible cold-rolling machine — the only one in China at the time.

Anshan shielded Jiang from political turmoil during the second, quieter phase of the Cultural Revolution, while many of his intellectual peers languished in remote countryside locales. On the rare occasions when he visited Shenyang, he and SIA colleagues Wu Jixian 吴继显 and Tan Dalong 谈大龙 often discussed new frontiers in industrial technology. In particular, they were fascinated by reports about the emergence of automated industrial robots in Japan, the US, and Europe. The three of them perused the SIA’s reading room for everything they could find on “artificial intelligence”: in the early 1970s, this was a muddled mix of neural networks, cybernetics, and computer-integrated manufacturing. MIT’s Joseph Weizenbaum had built ELIZA only a few years prior. Jiang, Wu, and Tan’s “AI,” gleaned through the handful of publications that made it into Cultural Revolution-era China, was worlds away from the models we know today. Rather than talking to chatbots, these steel-factory regulars were excited about using algorithms to operate manufacturing equipment.

In 1972, Jiang, Wu, and Tan drafted On Artificial Intelligence and Robotics 关于人工智能与机器人, a petition to Beijing to seize on innovations in the field and invest in general automation. They had drafted China’s first policy proposal for artificial intelligence.

Researching and manufacturing robots is the natural direction of automating equipment manufacturing, and is an important sign of a country’s strong and robust industrial development.

— Jiang Xinsong, Wu Jixian, and Tan Dalong, On Artificial Intelligence and Robotics (1972)

Armed with this petition, they headed to Beijing to persuade superiors at the Chinese Academy of Sciences. The CAS’s leadership was supportive, but constrained by political headwinds. In early 1973, the trio made another trip to the nation’s capital, courting more industries where advanced automation might be applicable. This time, they encountered pushback: many thought the concept of robots was closer to science fiction than reality and found them unserious.

Another major blow to their dreams came via the Criticize Lin, Criticize Confucius Campaign 批林批孔运动. This was a confusing phase within the Cultural Revolution, where activists merged posthumous criticism of former Vice Premier Lin Biao (dead of an infamous plane crash in 1971) with denunciations of Confucius in an attempt to reinterpret Chinese history according to Maoist ideology. The movement reignited political divisions in academia. After returning to Shenyang, Jiang, Wu, and Tan were variously labelled as pro-Western “establishment types” 小当权派, and “hat-off rightists” 摘帽右派 for their research.3 Radical students and scholars denounced AI and robotics as “idealist pseudoscience” 唯心主义伪科学 in magazines.4

Can “intelligence” be manufactured by “artificial” means? No, it can’t. … The term “artificial intelligence” gives idealism an easy loophole to exploit. If artificial things can create “intelligence,” then in the future something with “intelligence” even more advanced than humans is bound to appear. … Some of the academicians of the Soviet revisionist regime … are loudly promoting “artificial intelligence” … which fully exposes their traitorous true colors.

We must take a stand against Deng Xiaoping, … and in the struggle to criticize all kinds of reactionary ideological trends in the research fields of “image recognition” and “artificial intelligence,” we must follow our own path.

— Excerpts from Selected Translations of Foreign Writings on Philosophy of Natural Science 《摘译外国自然科学哲学》, a Cultural Revolution-era magazine about the philosophy of science which circulated among radical scholars.5

China’s earliest experimentations with AI and robotics were thus nipped in the bud. Unlike the Soviet scientists whose records survived to Perestroika, we do not know how Jiang and his colleagues felt during these years. Jiang’s biographer Xu Guangrong 徐光荣 borrows the term “dancing in shackles” to characterize the period. Historical records are otherwise thoroughly sanitized; everywhere he is quoted, Jiang is resilient and grateful, never once resenting the Party, the academic system, or his fanatical accusers. Official history paints the picture of a patriotic scientist who, despite force majeure adversities, always remained buoyant with hopes of serving his country one day.

But can we read between the lines? How devastating it must have been to have your life’s work stretched out by a decade, delay compounding delay; to watch the nation to which you are supposedly deeply loyal squander opportunities to seize technological advances; to have your research papers presented by others at international conferences because you were forbidden from travelling. One can only imagine what private dreams sustained scientists of his generation.

From Engineer to Strategist

With the death of Mao in 1976, the Cultural Revolution came to a close and normal academic activities were soon restored. Jiang and his colleagues quickly returned to their posts. Artificial intelligence and robotics became official research areas at the SIA. After a wasted decade, the CCP’s new, reform-minded leadership turned its mind to the global scientific race. A massive group of more than 1,000 scientists convened by the Party drafted the 1978-1985 All-China Science and Technology Development Planning Outline (1978-1985 年全国科学技术发展规划纲要) in 1978. The landmark document made some of the earliest mentions of intelligent machines in the history of Chinese policy:

Modern science and technology … is undergoing a great revolution. In particular, the development and application of electronic computer technology has enabled machines not only to replace certain forms of human physical labor, but also to take over some functions of mental labor, becoming auxiliary tools for memory, computation, and logical reasoning.

No longer was AI “idealist pseudoscience”: Beijing was finally endorsing scientists to embrace promising new ideas, unshackled by ideology. Meanwhile, Jiang Xinsong finally managed to leave the country for the first time. In August of 1979, he was part of a small Chinese delegation that attended the Sixth International Joint Conference on Artificial Intelligence (IJCAI 79) in Tokyo.

Japan at that time was a world leader in robotics and industrial automation. Jiang paid attention not only to their cutting-edge technologies, but also to the political and social institutions that enabled innovation. Having spent his entire career inside the CAS in one form or another, he was deeply attuned to the symbiotic relationship between institutional design and scientific innovation. As a young researcher, he paid a heavy price for supporting reforms; decades later, he finally had a chance to influence the institutional future of Chinese science. In his post-trip report to the SIA, he described how robotics research and development in Japan was not concentrated in universities, but also conducted robustly by research institutes and private enterprises. In his words, there was an efficient “division of labor” system in Japan’s robotics field: universities and specialized institutes engaged in basic research over longer periods of time, the Ministry of International Trade and Industry funded application-oriented research with 5-10 year horizons, and the private sector focused on commercializing market-ready technologies. Jiang paid as much attention to the workings of this system as he did to the research papers.

Many of China’s most prominent scholars from that generation became scientist-strategists, if not technocrats. Having weathered years of political campaigns and anti-intellectual rhetoric, with constant reminders to express loyalty, they worked closely with the Party-state system. Two things are likely true at once: (1) they both sincerely believed their work to be strategically valuable to their country, and (2) knew how to speak the language of the Leninist regime in order to bend political winds to their advantage. Qian Xuesen’s generational legacy lay not only in the rockets he designed, but also in the hand he had in shaping China’s defense complex. Similarly, Jiang Xinsong, whenever he could, advocated for industrial policies to stimulate automation research throughout his life.

The 1980s were the height of Jiang’s academic career. His writings from this decade were often theoretical, seeking to convene emerging threads of advances in robot manipulation, cybernetics, and artificial intelligence. As one of a small handful of Chinese scholars closely following developments in AI and automation, he introduced American, European, and Japanese research to Chinese academics through his prolific writing output, pushed back against skepticism, and advocated for engagement with then-nascent fields in Chinese academic journals. These contributions were also frequently followed by concrete recommendations for research and policymaking, downstream of his observations of factory lines and laboratories.

Jiang Xinsong’s SIA team completed China’s first industrial robotic system in 1982. The SZJ-1 playback robotic manipulator (SZJ-1型示教再现机械手) was the first robotic arm to be deployed to Chinese assembly lines, and marked a watershed moment in China’s race to catch up in industrial automation. In March 1986, Jiang completed an influential journal article titled “Research on the Development of Robots in Foreign Countries and Our Response.” In it, he offered a broad picture of robotics’ development around the world, diagnosed China’s challenges, and proposed six strategies for catching up. Revisiting the article today, one realizes how influential his thinking was to the trajectory of China’s automation development.

Jiang appears to have believed strongly in process knowledge. He pushed back against the idea that automation wasn’t valuable to a country with incredibly cheap labor that mostly made low-end products. Given market logic, he argued, equilibrial “match points” justifying investments in automation will eventually emerge in the industrial upgrading process. In the meantime, China needed to gain experience by mass-manufacturing cheaper robots, emphasizing parts over entire machines, and exploring automation for specialized scenarios.6 Writing just seven years into the One Child Policy campaign, he foresaw that China would eventually need to contend with labor shortages, particularly in dangerous occupations like mining; in fact, some of his engineering research during this period was addressing the challenges of using robots in undersea operations.

At the Helm of Automation

Jiang was swiftly given an opportunity to execute his vision through the 863 Program. In the 1980s, after two decades of the US-Soviet scientific rivalry, it was clear that technology was inseparable from national power. Chinese scientists watched as the United States announced its Strategic Defense Initiative (“Star Wars” program) in 1983 and the Eastern Bloc began the Comprehensive Program for Scientific and Technical Progress in 1985.

The same month Jiang finished writing “Research on the Development of Robots in Foreign Countries and Our Response,” scientists Wang Daheng 王大珩, Wang Ganchang 王淦昌, Yang Jiachi 杨嘉墀, and Chen Fangyou 陈芳允 directly petitioned General Secretary Deng Xiaoping to direct more funds towards scientific research, lest China be left behind. (They skipped official channels and had Deng’s son-in-law, who worked at the CAS and was an acquaintance of Wang’s, deliver the letter by hand.) Deng approved the petition in just two days, instructing Premier Zhao Ziyang to implement “without delay.”

In scholars Qiang Zhi and Margaret Pearson’s account, the “863 Program,” as the ensuing mega-initiative for applied research came to be known, was an institutional innovation inside the Party-state system. It was insulated from political winds; technology goals were specifically defined; and scientists, not politicians, had decision-making authority. The Program was guided by a single office under the State Council, which then coordinated scientist groups for each of the Program’s thematic focus areas. Funding for the Program was unusually concentrated and abundant. The total amount Deng earmarked for the 863 Program, to be distributed over the course of 15 years, was more than 10 billion RMB (around US$8 billion in 2026 dollars), equivalent to 5% of China’s entire government expenditure that year.

Jiang Xinsong advised the architects of the 863 Program on the field of automation for much of 1986, and in 1987 he was officially invited to be one of the Program’s seven chief scientists. His portfolio included computer-integrated manufacturing (CIM) and “smart robots” for industrial settings.7 The SIA remained the institutional home for much of this work. Armed with political legitimacy and funding, it produced a range of technical breakthroughs for the PRC in the ensuing decade. Jiang himself also initiated some influential technology transfer during this period. In 1993, he helped facilitate the import of twenty welding robots from Yaskawa in Japan. Paired with the SIA’s own controllers, these robots ended up in factories throughout China and accelerated uptake for automation.8

Though the 863 Program gave Jiang extraordinary influence, China’s industrial policy leapfrog did not entirely resemble his hopes for AI from back in 1972. Notably, the Program institutionalized robotics’ split from artificial intelligence, reflecting global trends at the time. The “AI winter” was descending, and robotics research continued to develop in a “classical,” engineering-driven direction. Within the 863 Program, robotics was placed into a different thematic focus area, away from computing and information science. It would take until the 21st century’s deep learning revolution for these two diverging threads to reunite.

In the 1990s, while progress continued in robotics, Jiang Xinsong was becoming worried about the future of China’s traditional industrial base. He had spent most of his career in China’s capital of heavy industry. Reform and Opening Up exposed the entire Northeast, including Shenyang, to market-based competition, and Beijing pushed forward with structural reforms under Jiang Zemin, resulting in mass layoffs. The region’s industrial identity, first forged almost a century ago under Japanese occupation, was under existential threat.

Jiang, who by now was well-travelled, looked to the West for answers. Towards the end of his life, he became an advocate for agile manufacturing, a concept first proposed by American industrial leaders in 1991. Agile manufacturing describes an approach where companies organize their assembly lines, stock, and workers in a modular fashion, so that they can respond to quickly-changing demand and produce highly varied products within one system. Designed for a world of highly personalized products, it allows designers to iterate quickly and factories to pivot production as needed. Jiang believed agility to be the key to adapting China’s old industrial base for the future of automated production, and delivered lectures drawing from American manufacturing research throughout China.

By the time he died suddenly of heart failure in 1997, the “world’s factory” was coming into being. It’s an ironic fact that in the end, visions first articulated by Target and AT&T executives (and funded by the Department of Defense) would be realized most fully in Shenzhen.9

Towards China’s Industrial Robotics Revolution

As of 2025, more than 2 million robots are now deployed in Chinese factories, with domestic manufacturers selling more units in the country than foreign competitors in the last two years. One of the top Chinese manufacturers powering this transition is Siasun Robotics, based in Shenyang and affiliated with the CAS. Its founder, Qu Daokui 曲道奎, was Jiang Xinsong’s student and named the company — Siasun in English, and 新松 xīnsōng in Chinese — in his former advisor’s honor. Siasun became the first robotics company to trade publicly on the Shenzhen Stock Exchange in 2009.10

It’s easy for observers today to assume a sharp break with the Maoist past when interpreting China’s technology governance, seeing as many of the technologies most relevant today did not proliferate before even the Xi Jinping era. Jiang Xinsong’s story reminds us of the ghosts in the closet. China was not always strong, and the PRC’s leaders did not always look favorably upon its scientists. Periods like the Cultural Revolution cannot be explained away as exceptional aberrations; they, and reactions to them, scarred the generation ruling China today and shaped the institutions that now govern knowledge production. Chinese science has always danced a delicate duet with the state. Politics is a shackle, but also an incentivizing structure. AI, rather than fundamentally altering these relations of power, is likelier to simply reanimate them.

With thanks to Jasmine Sun and the ChinaTalk team for editorial feedback!

dials in from Kyiv for a long-form WarTalk on what the front line actually looks like in year four. Infantry sit underground for six months without seeing the sun, 2% of casualties come from small arms, and where the “forward line of troops” has been quietly replaced by a forward line of UAV teams.

Rob Lee is a senior fellow at FPRI and one of the most-read analysts of the Russia-Ukraine war; he’s joined by WarTalk regulars Bryan Clark, , and .

We discuss…

• The six-month infantry rotation and what isolation, drone threat, and zero-line resupply do to a human being

• Why Ukraine has reclaimed the drone edge — and what the Hornet, Bumblebee, and FP2 are doing to Russian logistics

• Ukraine’s new corps structure, where the brigade-only model broke down, and what the Azov-derived elite corps look like

• Why 2% of Ukrainian casualties come from small arms and what infantry are actually doing on the zero line

• Starlink as the indispensable game-changer — and Russia’s increasingly serious attempt to jam it

• Combat casualty care when CASEVAC takes 12 hours, the golden hour is dead, and tourniquets sit on for a month

• What the Marine Corps should steal from Ukraine — pushing Hornets to the battalion, Bumblebees to the company, and giving up something to make room

Listen now on your favorite podcast app.

And subscribe to Rob’s substack!

Two Marines

Newsletter from former US Marine Rob Lee and Ukrainian Marine Dmytro Putiata on the Russian-Ukrainian war, defense technology, and modern warfare.

By Rob Lee

Jordan Schneider: Justin, Bryan, Tony Stark — joined today by Rob Lee, dialing in from Ukraine. We’re checking in, hopefully going to hear some positive developments on WarTalk for the first time in a real long time.

Justin: I noticed there was an account posting photos of Ukrainian fighters from just before the war started, and then pictures of them today. You could really see the changes that have gone on. Rob, I know you’ve been with a lot of the fighters and the commanders — if you want to talk through a little bit of what they’ve gone through over these four years.

Life on the Zero Line

Rob Lee: I served four years in the Marines. I deployed three times. The deployments are relatively short. In this war, a lot of people volunteered on February 24th with no military background, and now four years later they’re still in service. They put their lives on hold. Even with us who were serving in the GWOT — you’re home at times, you’re deployed — you can still kind of care about your lives.

The burden of this war is very narrowly focused. All Ukrainians feel it, but in particular the infantrymen. Rotations are very difficult now because of the kill zone, but also manpower challenges. Right now infantry, some brigades I’ve met with, say infantry is spending a minimum of three months at the zero line with no rotation. But there are many cases of six months and nine months. There are a couple of cases of guys who are over a year on position and just doing no rotation.

What it’s like is — usually if you’re infantry, you’re underground, either in a hole dug in a tree line somewhere or in the basement of a building. You’re not going outside very much because of the drone threat. Some of these guys, their eyes have to recover because they haven’t seen sunlight that much for six months or a year. There’s very little physical exercise you can do because you’re in a very small confined space. Almost all resupply is done by drone — these big vampire drones drop almost all the food, ammunition, water, whatever else you need.

It’s very difficult to do casualty evacuation. To zero line, in many places you can only do it by ground drone. You can’t even bring up vehicles. Basically you either have to walk out yourself or you have a UGV come get you. And in many cases that’s not possible. To walk to position and back, in some cases you have to walk 25 kilometers. I talked to an infantryman from the 9th Air Brigade a couple of weeks ago, and on his way out he had to walk 18 kilometers. Of course you’re walking along the most concealed and covered route. It might take days or a week or so, because you walk when there’s bad weather, when the drone threat is reduced.

It’s very hard to fathom, even for me, because it’s so different than what we saw in Afghanistan and what other people experienced. This infantry guy I talked to was telling me he only slept a couple of hours a night. He’s always on edge — they’re getting hit by FPVs and other things pretty often, almost every day. You never know if Russian infantry are going to walk up on you, because sometimes they get through, sometimes UAVs don’t see things, and you might have to fight. In this guy’s case there was a case where six Russian soldiers got into his position and they had to fight them with small arms.

It’s extraordinarily difficult. You can imagine how much it ages you, because you’re so tense for so long at a time and there’s no rotation. The psychological and physical effects are going to be really long-term problems for these guys.

Tony Stark: There was a saying about soldiers in World War Two — they saw about ten days of intense combat. That’s not dismissing the combat that they saw, but it was kind of this roller coaster where there would be dead periods, and then you’d be in these massive engagements. During the GWOT, it was kind of the opposite — you could take contact every day, but you weren’t under sustained fire every day. You had FOBs.

And then you have what I’ll say was General Milley’s perception of future war — that you would always be under threat of fire, you wouldn’t get a lot of sleep, and you’d have to move a lot. The one difference is that for Ukraine, they really can’t move. They’re stuck in this attritional battle where there’s not large-scale maneuver warfare.

Rob Lee: Yeah. The ombudsman for the military mentioned a study a month or two ago — I was thinking about writing something about this — that according to the study, anyone who’s been on the zero line for more than 40 days becomes kind of ineffective. Maybe not ineffective, but they stop caring too much about their survival. They lose their effectiveness essentially. I talked to this guy — he thought he was still effective. He’s still obviously afraid and has certain issues. But as you said, the comparison — here it’s not the most intense combat, because you’re underground, in some kind of cover and concealment. It’s not like you’re in a firefight the entire time, but you’re on edge the entire time. Any time your position could be attacked, you could get hit by drones all the time, and you can’t go outside.

There are both sides to this. Drones have created this problem with the kill-zone concept, but they also enable you to be able to fight within it — because drones are doing all logistics too. Drones are just having a really dominant role in the war at this point.

Why Ukraine Is Winning the Drone Race Again

Rob Lee: That’s why — let’s talk about what’s happening now. The case for optimism is that Ukraine is retaking the upper hand on the drone side. The qualitative improvements — quantitative, I think, is pretty even. But that’s one of the really big developments of the last five, six months: Ukraine has reestablished this upper hand. Last year, some people thought Russia had caught up or maybe narrowed the gap. It’s very clear that Ukraine has surged forward this year, and that’s really one reason why the situation is better than it was a year ago.

Jordan Schneider: What have been the developments over the past three to four months — or wherever you want to put the turning point — that have changed the dynamics on the ground?

Rob Lee: First off, there’s a strong seasonal dimension to the fighting. Every winter, the fighting doesn’t end, but it’s more difficult for Russia for offensive operations, because Russia really prefers doing infiltration tactics — usually one or two guys at a time moving forward. It was a very cold winter, negative degrees in many cases. If you’re out in the environment like that, it’s hard to survive. These guys aren’t that well trained, and the tree line goes away, so you lose your camouflage. It’s harder to camouflage from drones. Thermal cameras work better when it’s cold anyway, so thermal optics on a Mavic 3T is going to be more effective. In winter, infiltration is much more difficult — Russians try to infiltrate behind the front line and either dig a position in a tree line or find a basement. In winter you basically have to find a basement to survive. So it limited the kind of infiltration they could do.

Over the winter we knew Russian advances would probably slow down, and they did. Typically, looking at the last year and the year before, Russian advances would still be somewhat slow in spring and then pick up as the summer goes on. We’ll probably see this again — Russian rate of advance kind of increasing. But the weather has turned for about a month or two, and we haven’t seen a significant increase in the rate of advance for Russia. So my view is we have to wait and see how bad we’ll get in the summer and fall when Russia typically advances faster. But there are good reasons to believe this year Russia is going to have more problems advancing.

One of the big ones is just the development of mid-strike, which is operational depth strikes by Ukraine. Ukraine for a long time had very good intelligence of Russian positions — they knew where command posts are, where air defense systems are, not perfect fidelity, but a good idea in many cases. There was just a lack of capability to strike these things. Obviously they had ATACMS before — that was one of the options. HIMARS used to be basically the only operational fires capability they had for some time. HIMARS became less effective because the Russians adapted — they could shoot down GMLRS, EW affects GMLRS.

Now Ukraine has developed and scaled kamikaze drones that can focus on operational depth. There’s a huge quantitative increase the last six months or so, in different types. You have the FP2 — maybe it’s going to be called Firepoint — it has a 100-kilogram warhead, a really big warhead. If it hits something, it’s going to do a lot of damage. You can collapse a building. They’re using these very frequently on air defense systems, command posts, warehouses, all sorts of logistics targets. They hit an FSB building in Kherson yesterday — destroyed the building. Even if the accuracy is 30 to 40% getting through — I don’t know what the number is — you’re still getting enough through to destroy targets. And the price isn’t… I think FP2 costs like $40, $50,000. Don’t quote me on it, but that’s a rough idea.

You have a bunch of other drones in this class, maybe smaller. There’s the Hornet from Eric Schmidt’s Perennial Autonomy — that’s doing a lot of significant damage right now in different areas on logistics roads. Hitting trucks, making it very difficult for Russian logistics at 50 to 100 kilometers or even further. They’re very cheap, sub-$5,000.

You can adapt them — put a Starlink on them, increase the battery size. A very successful system, very easy to fly, the AI will ping targets. As you’re flying, you put in what kind of target you want the system to search for, and it’ll immediately put boxes up as it flies. There are false positives, but it will locate things for you. Then the Bumblebee, the FPV-Mavic-type version of the Hornet from the same company, also works integrated in the system.

The qualities of production are just increasing. More Ukrainian units are getting these things, and it’s doing a lot of damage. There are other Ukrainian options like Bulava, RAM-2X — kind of at the Lancet class. The quantity has just increased substantially. They’re getting through Russian EW. Obviously the economics make sense to use these aggressively — it’s not $400,000, not $200,000, it’s something much more affordable, and that’s really changed the dynamic of the fighting.

Mid-strike is the big development of the last six months. Russian advances have already slowed. That’s from a variety of factors. But now with the increasing improvement in mid-strike and knocking out air defense systems and other things, we can also think about what else might happen later this year. I definitely think this year it’s shaping up better than it was last year.

Bryan Clark: All your discussion about the scale they’re able to operate at and the adaptability of these systems makes me think — a lot of what they’re able to do is just testing and probing to see what works. So there’s much more adaptability because they can just poke and poke and poke until they find a vulnerability, and then they can pour in on either that capability vulnerability they see in the Russians or some mispositioning of forces. Is that a lot of what they’re doing here — taking advantage of the scale and the tempo they can generate?

Rob Lee: Yeah. The Russians have a lot of vulnerabilities. They’re slow to adapt in many cases. There was a big debate over mid-strike last year, where some people thought this should have been a bigger focus — the operational depth was just not being hit. Ukraine had a tactical strike and a strategic strike campaign, but this operational campaign wasn’t there. Now it’s here and it’s doing enormous damage to Russia. It’s going to change how they do logistics.

When HIMARS arrived, Russia had to push back logistics and develop a new system with different echelons. You had big trucks moving from one distance and they had to shift to smaller pickups, ATVs, and so on. Russians are already starting to push back fuel storage further from the front line because they’re having difficulty protecting it. They’ll probably push back command posts and other things too. All this is going to make those things more difficult.

Ukrainian units have a lot of room for creativity, for figuring things out, and once they demonstrate success they’re going to reinforce that. Now we have the quantities of these munitions increasing, the qualities there. Eric Schmidt’s company is a good example — they came to Ukraine and focused all on Ukraine. Everything’s about Ukraine first and then everything else afterwards. They brought in Google X engineers, the best, most talented American engineers we have, and they partner with Ukraine units who give them feedback and they immediately iterate. It’s the best Ukrainian drone units with the best American engineers, plus massive funding from one of the wealthiest people in the world. It’s working very well, and Russia has nothing that can compete in this way. Their defense industry is still very centralized, old-style big defense companies, far less innovative, they don’t have the same talent coming.

Reorganizing on the Fly: Ukraine’s New Corps

Rob Lee: The manpower situation has been the biggest problem for Ukraine ever since the summer 2023 offensive. Brigades have been very undermanned. But Ukraine at this point, through drone development, innovation, production, and the system they created, has really been able to compensate for the effective lack of manpower.

There are also some other positives. They changed the reforms of the corps system. Before this, Ukraine was an all-brigade-style military. They didn’t have divisions or anything above that. The way it used to be — you had brigades, and then these temporary command-and-control functions above them, OTU and OSGV, which are like operational-tactical groupings. But they were temporary. The commanders were rotated in and out, the staff came in and out, and they were too high-level, managing too many brigades. They didn’t really provide very good support.

They rolled out corps last year. It’s hard to roll up a command-and-control change mid-war, but some of these corps are doing a very good job. The entire quality has increased, the coordination across the corps is increased. The corps commander is controlling like five brigades, whereas an OTU might command 20 brigades. So there are a lot of improvements on command and control, adjacent-unit coordination. Now the corps are also getting corps-level assets — they’re trying to develop UAV regiments that can focus on operational depth and let the brigades focus close to the front line. That’s another contributing factor that improved the situation.

Tony Stark: Two questions. One — how is that structure evolving below the corps level? Is the corps directly tasking the brigades, or are they having divisions, and then those divisions are tasking? The American Army is going through that same reformation where they’re trying to relearn how to fight as a division. The corps still doesn’t know what it’s up to. That’s part one. And then broadly — what is the evolving role of the infantry here? Because you kind of hear two things in America. One is that the infantry is done, which we hear every ten years. The other is that the infantry doesn’t need to change because the infantry will always be there. I mean, infantry tactics change all the time. So how are those two things linked for how Ukraine is fighting from the top down?

Rob Lee: On the first one — above brigades, it’s just brigade-to-corps level now. Nothing in between. Corps is kind of our division — it’s not really a corps level, it’s more of a division, somewhere in between. But they call them corps instead of divisions. At the corps level they’re still figuring out what assets they have at that level. Right now you usually have an artillery brigade, they’re trying to set up an unmanned systems regiment, and some other assets.

They are actively changing. The air defense component has changed too. They have a new small air defense side led by the former commander of Lazar Group. He pulled away some of the air defense — sorry, the ground forces air defense battalions. They’ve restructured to counter Shaheds. Now it’s part of an echelon system. For countering Shaheds, brigades will often have interceptor teams, they’ll have radars to try and locate Shaheds. You’ll often have some level beyond that, and then additional echelons for countering these things.

It really depends which corps. Ukraine has some unique corps — the 1st Azov Corps, the 2nd Khartia Corps, the 3rd Corps led by Biletsky, the former Azov commander. These corps are quite elite. They’re all unique because they have a unique background — 2nd and 3rd Corps were volunteer units that formed after the war began. There’s a big difference between those corps, which have more fleshed-out staff work and other corps-level assets, and other regular corps that may not have the same capabilities. There’s wide variance still in corps capabilities. Long term, I don’t know what it’ll look like — that’s going to be a question for Ukraine.

They also have the Unmanned Forces, a different branch. Those teams are all across the front line. They don’t report to the corps commanders — they report up the Unmanned Forces chain. Then you also have these Assault Regiments, nominally part of the ground forces, but really separate, and they also report directly to General Syrskyi, not to corps commanders typically. So you have these other command-and-control relationships that are evolving. The corps commander does not always own every asset in his area as a battlespace owner, and that does lead to some frictions. That’s constantly being changed and updated. What we’ll see in the future will probably look a little different than what we see right now.

The Infantry Question

Rob Lee: And then for infantry — it’s a good question, because infantry are not fighting infantry that often. I talked to the head surgeon for 7th Corps. 7th Corps is holding Pokrovsk-Myrnohrad, this really key part of the front line. He estimated that about 2% of his casualties are from small arms. Small-arms casualties are a very small percentage. Even in the urban fighting it was still a small percentage. On both sides, UAVs are doing the vast majority of killing. I told a couple of Ukrainian brigade commanders last October and asked them what percentage of casualties were from UAS. A couple said 100%. So it wasn’t even just 90% — it was literally 100%.

For infantry, there’s a question on some of these positions, because often the Ukrainian brigade commanders will tell their guys: do not engage Russian soldiers unless you have to. We want you to hold position, because if you open up, the Russians will often have a Mavic following their infantry as they walk forward. So if Ukrainian infantry open up, the Mavic locates where the position is, and you can then hit it with FPVs, Molniya, artillery — whatever. Once the position is located, you can usually destroy it. So oftentimes Ukrainian units tell their guys, don’t engage unless you have to, only if they’re within 20, 30 meters.

Some of these positions are more like observation posts, because they’re not really doing fighting. They don’t necessarily have to have fields of fire tied in with the next position. The next position might be 500 meters, it might be a kilometer away. It might be quite laid out. You don’t have interlocking fields of fire like we were trained in the US military. UAVs are doing the killing, doing almost all the observation, and the vast majority of Russian casualties come from UAVs. Basically infantry — look, here’s a whole position. If you see someone, call it in, we’ll have UAVs come and try to kill these guys for you. Of course, if you have to fight, you have to fight. Sometimes the weather is very poor, UAVs are just not flying, and then infantry might have to.

Of course, if you’re taking a position from someone, infantry have to go there and they have to hold it. So there’s still an important role. The role has decreased in importance, but it’s still there. The number of Ukrainian infantry per kilometer is very small — on average probably six, five per kilometer, maybe less. In cities and urban areas it’ll be higher. But most of the terrain is big fields and tree lines. There are no positions in open fields. Every position is either in a tree line, a forest, or in the basement of a building, because anything that can be seen can be destroyed essentially.

On the Russian side, they treat their infantry — they’ve adopted Wagner’s tactics writ large. They said, okay, we’re going to treat infantry as expendable. We’re not going to care too much about them, we’re not going to invest too much in them, and we’re basically going to advance by having numbers of infantry plus fires doing a lot of the work. Artillery, now it’s UAVs doing it. I think it’s been a poor approach. They take more casualties than they need to. If they invested in their guys more, they could do much more. They don’t do much unit-level coordination — they’re not really training companies that do company-level operations anymore. It’s very small-scale. They treat infantrymen as not that valuable, not that important. Many Russians don’t make casualty evacuation a real priority. Some do, some don’t, but it’s just not near the same thing.

We don’t see much infantry fighting — but you still need someone to hold the front line. There’s also a question of what the FLOT looks like. Is it where the infantry are? Because if the infantry are not fighting, if they let Russian infantry walk past them, to what extent do they hold this position? To what extent do they hold this terrain? I remember when I was in Afghanistan, before going to Marja, I talked to some platoon commanders who were there. The battalion commander — one of these guys came up to him and said, hey, to what extent do you control your area? And I’m like, what do you control here?

There’s a particular type of character of fighting right now in Ukraine. Drones are here to stay, to some extent — that’s pretty obvious. But I don’t think the nature of positional fighting will necessarily be the same in future conflicts for us. It is important. You still need infantry. There are no brigades I’ve talked to who think they have enough infantry. They want more guys. If you want to do offensive operations, you need infantry to move forward, to hold things, to take things. UGVs are still coming along, but they’re not there yet. I’m still a big believer in infantry myself, but certainly drones are playing a bigger role and you can compensate for lack of infantry more than you could before.

The Next Six Months

Justin: When we look at that, then what does the theory of the next six months look like for Ukraine? Is it that they’re comfortable where the FLOT is currently against the Russian forward line of enemy troops, and they’re comfortable continuing their longer-range operational-level strikes to continue to decrease Russian capability? Or is Ukraine in a spot where they have to actually start pushing the FLOT, and therefore they need more manpower to be able to do that, because they have to show some type of progress both for international backers and for internal prestige?

Rob Lee: So Zelensky said, ever since Trump was in office: look, we’re ready to end the war basically where the front line is. We’re ready to declare a ceasefire, we’ll negotiate other things, let’s just hold the front line where it is and we’ll move from there. Putin has basically put this off the entire time, because he keeps saying no, we want all of the Donetsk region — then we can speak after we have the rest of the Donetsk region. So that is still the kind of stumbling block.

For Ukraine — look, Ukrainians are tired. There are a lot of people who are ready for this war to end. If they could freeze the front line where it is without significant losses of sovereignty, I think a lot of Ukrainians would go for this, as long as they thought they still had the ability to deter a future war. But I think this year Russia actually has some really big issues, and I think Russia risks overextending itself and actually having some reverses. We’ve seen this in this war consistently on both sides. Russia overextended in the spring and summer of 2022, and that led to Ukraine’s successful offensives in Kharkiv and Kherson Oblast in the fall. Ukraine overextended in the summer of 2023, and that led to Russian advances afterwards.

I think there’s a risk for Russia to do this again. A lot of it comes back to Putin. The war reached diminishing returns some time ago for Russia, but he keeps committing to it. There are probably plenty of people in the general staff who think this war should have ended a while ago, but Putin is just very focused on this. Russia has had a lot of significant costs — geopolitical, human, economic — to extend this war. The question is what are you achieving by doing so. Fedorov put his target — he wants to inflict 50,000 casualties per month. He wants to increase it from right now. Ukraine estimates it’s like 35,000.

We’ll see if they can reach that. The other side, while trying to inflict as many losses as possible, they’re trying to increase deep strikes, increase the cost on the Russian economy, go after oil and gas, go after defense production. People are tired. The Ukrainian military has a manpower problem. I wouldn’t be surprised if we saw some kind of offensive this year by Ukraine. Partially because Syrskyi, the commander, always wants to be on offense. He does not like defense. He was the brains behind the Kursk offensive, the Kharkiv offensive. He’s always looking for weak spots.

We saw a small offensive in the Huliaipole direction, Zaporizhzhia, in January and February. That was successful. We saw one back in Kupyansk that started last October. That was successful. My read from those two offensive operations is that Russian lines are not that strong. There are unrealistic objectives constantly given to Russian units. They’re always told you have to take this village by this time. It creates a vicious cycle where commanders cannot reach that on the timeline, so they often resort to lying, or they’ll send a guy forward to post a video of a flag somewhere, which is not true. It creates an internal bad system. They also rush operations.

So instead of setting the conditions for an offensive a month from now, they have to constantly throw guys at the front line because they’re behind whatever the timeline is. Putin is just not allowing commanders to give honest appraisals, and it creates really bad issues internally. But it also means that their defenses are not like they were in summer 2023, when they had very good fortifications, minefields, the Surovikin line. Right now Russian lines — they’re able to locate these teams, suppress them with artillery or with Grad MRLs. The assault units are tinkering, figuring out how to do offensive operations in a drone environment, which involves using drones to set localized superiority and the right conditions for offensive operations.

I wouldn’t be shocked if Ukraine does push back Russia in places this year. They may not have enough manpower to do it, but in the Huliaipole direction, one of the real breaches — if they had someone to exploit it, they could have really advanced much deeper into Russian lines. The issues Russia has internally, the lying, the perverse incentives, create a lot of vulnerabilities that can be exploited. So Ukraine’s strategy right now is end the war as soon as you can. I think they’d be happy freezing the front line. But I wouldn’t be shocked if Ukraine pushes back Russia in some places this year.

The Starlink War

Bryan Clark: Hey, Rob — you mentioned EW before. Talking about the ubiquity of surveillance on the front lines, to what degree is EW impacting the ability of either side to use their drones to keep track of what’s going on? Or has everybody just devolved to using fiber-optic cabling to their drones to overcome the EW challenge?

Rob Lee: One thing to keep in mind — different parts of the front line have a very different EW nature. The Pokrovsk direction has often had the heaviest EW concentration for the last couple of years. Some UAVs that’ll work on one part of the front line, like Zaporizhzhia, will not work on Pokrovsk. When I was talking to units in Myrnohrad the last year or two, they basically said EW is so strong we can only use fiber-optic, so for FPVs, fiber-optics dominate that direction. Radio-signal FPVs play a smaller role. There are Ukrainians that do use radio-signal there, but it’s more difficult.

Other parts of the front line, radio-signal is okay and you can conduct strikes at deeper range. Fiber-optic cables have gotten more expensive because they almost all come from China — a 50-kilometer spool can be $2,300, $2,500. The economics have changed so that if you have a big FPV, like a 15-inch FPV — which is bigger than normal, normal is like 10-inch — you can put a Starlink on it, and Starlink is like $500. Starlink gets you around EW. Now the economics make sense where Starlink is cheaper than fiber-optic even, and some units have gone in that direction.

Starlink is — if there is a game changer this war, I think it’s Starlink. Because everything about how drone warfare works for Ukraine revolves around the use of Starlink. They’re putting it on everything. ISR often uses them. Most of these mid-range strike drones are using them — not all, but very commonly. UGVs constantly are using them, naval drones. And of course every position has Starlink to stream the feeds of the UAVs back to command posts so you can see everything. Starlink is this solution to many problems that if it was not there, the war would be entirely different.

EW is still a significant issue. The Russians realize they’re behind the power curve on mid-strike. They’re having big issues. They were using Starlink on Molniya and on Shaheds back in January — that’s when SpaceX blocked it. That was posing really big problems. I was down at the front around that time frame. They were hitting trucks like 50 kilometers from the front line, oil and gas tanks. Trucks is a big issue.

The Russians do have some Starlink jammers they’re testing. They tested one in 2024 — two of them were destroyed. Of course, if you jam something, you can look where the center of the jamming is coming from and get an idea of where it is. The Russians are now trying to come up with a more integrated counter-UAS system where you have a Starlink jammer, you have other types of jammers that will jam other types of drones, and then probably air defense integrated into this. They’re actively thinking through what a system of counter-UAS looks like with different echelons of radar — like SKVP radars that can locate, that’s like their version of the RADA, there are some Chinese ones too. EW jammers to jam certain types of UAVs including ISR. Interceptors to try to knock out ISR and kamikaze drones. And jammers to try to jam Starlink and other things.

We’ll see if they can succeed, but I know it is a big priority this year. It is one of the big questions in my view. If they can actually adapt and figure this out, then they will negate a lot of these training advantages. If they can’t fix it, then it’s going to be a big problem for them.

Bryan Clark: And so the Starlink jamming, I assume, is a downlink jammer — you’re jamming the Starlink signal coming down to the drone, as opposed to trying to jam the satellite itself, because that gets very hard with a LEO satellite.

Rob Lee: I think that’s what it is. When I talked to guys when they used it in 2024, it basically showed Starlink was not available in that area — that’s what the drones showed. Back then it was mostly to disrupt the Nemesis and Lazar Group drones, the heavy bomber ones. Obviously Starlink is being used in a much more pervasive manner now. But I do know there are companies working on a bunch of other things now to try to get through jamming — things that can provide a better GPS signal, things that can provide a better INS on radio frequency. That’s one reason I was talking before about Western tech — there’s Western tech that’s working on these problems. It’s not just Starlink. We’ll see some successful examples this year. It’s something Russia will not be able to compete with.

Bryan Clark: Yeah, because the issue ends up becoming — if you’re using a GPS jammer and a Starlink jammer, but it’s only going to reach 10 kilometers and it’s going to get impacted by terrain, there’s going to be a little zone around the target. You can do that around really high-end targets, but you can’t do it everywhere, probably because of the number of jammers you’d need. And then you can have an end-game seeker or something that gets the drone the rest of the way. You get within 10 clicks, you lose your Starlink signal, you lose your GPS — if you have some alternative way to get you that last couple of minutes to the target, it seems like you could come up with a relatively inexpensive way to do that. That’s a lot of what these guys are working on for GPS-independent navigation — just something to get to the last tactical mile.

Rob Lee: Yeah. Most of these kamikaze drones now have some kind of pixel-lock on them. The last kilometer they can do target lock. It’s not perfect, but it gets you most of the way there. The Hornet is a good example, because it’s so cheap — okay, we can afford 20%, 30% accuracy. It can still be considered a win, because before we were using Gimlets at $200,000 something. If a Hornet is sub-$5k, you can send a lot of Hornets for the same price of one Gimlet and achieve better results.

Saving Lives in the Kill Zone

Tony Stark: Just to pivot back to humans — there was reporting last night that the US is cutting a bunch of funding because of CENTCOM for training for units, including tactical combat casualty care. Are there innovations in combat casualty care on the Ukrainian front? I know we talked about the Russians really don’t care, and last time you were on the show you talked about UGVs. How are the Ukrainians saving lives once they go down on the front line?

Rob Lee: It’s a huge issue. One of my conclusions is that Golden Hour is a concept that made sense for the GWOT. It’s not something that makes sense here. I don’t think we can assume we’ll be able to do this all the time. Helicopters do not come to the FLOT. In Russia, they bring them up to do certain missions and they’re still getting hit by FPVs.

Infantry on the front line, everything is supported by drone. In some cases when they get wounded, they’ll basically have telemedicine happen — a doctor will talk to them through some way and say, we’re going to drop you some medical equipment, here’s what you’re going to do to provide care to the guy next to you, because we can’t get to you. Vehicles can go to zero line only if the weather is horrific. In many places you can’t bring vehicles there. So basically the only two casualty-evacuation options typically are: the guy walks out, or someone drags him out, or a UGV. They have some UGVs that have some frag protection. The First Medical Battalion is a really interesting unit that has their bespoke UGV they’re making, and they’re doing these really long-range CASEVAC missions.

The kill zone makes it just incredibly difficult. UGV missions require a lot of planning and they’re very slow because you have to be very worried about the route you take. In order to not lose UGVs that often, it takes a lot of planning — plan the route properly, think through the timing, when to go, what UAV threat is, and so on. An actual CASEVAC mission with a UGV could take 12 hours. It could be more than that. By the time someone’s wounded, by the time they’re back to a higher level of care like a Role 1 or Role 2 facility, it could be 12 hours. That might be the minimum in some places. In that case the likelihood of being killed is higher if you get any significant wound.

Keep in mind, Ukrainian infantry are typically older, in their 40s or 50s. Many have existing health issues. Sadly, I hear stories of guys who die from just being sick — they get some illness, they have a pre-existing condition, there’s no way of getting care to them, and they die in a position. I’ve also heard cases where guys get wounded, they put a tourniquet on their arm and they left it on for like a month or so. And then when they come back, the lower limb basically just falls off. Just some really horrific, macabre stories. It shows you how difficult this is.

My takeaway is that when I was in Afghanistan, in my platoon we had two corpsmen. I think every squad had a combat lifesaver. But at this point, every fire team has to have someone with pretty good medical training. You really need to get at the lowest level very good medical training, where guys can take care of themselves, because you just can’t assume you’re going to have higher-level care. You can’t assume there’ll be rapid CASEVAC. That’s one thing we should definitely not skimp on training for.

Justin: That’s one of the downsides to the way medical training has always been looked at in the United States military. You look at Special Operations Combat Medics, or SOCMs — they’re technically trained by doctrinal definition to be able to sustain a casualty, multiple casualties, for up to 72 hours. Then you look at the Special Forces medic, the Special Operations Independent Duty Corpsmen, which are the Navy variant of the Special Forces medics — they’re technically trained to, as long as they have the supplies, sit on a patient indefinitely. When I went through Special Forces medical training, it was a year of medical training. That goes from basic anatomy all the way through doing surgery on extremities and tropical medicine and everything in between.

That’s a level of training and a level of going in and learning pharmacology and learning how to actually treat and assess and do those medical procedures that isn’t going to be invested in every soldier or every fire team or every platoon. But even if you were to invest in it, the sustainment of that — the biggest fear ODAs have, medics have, is, well, when we would train the other Special Forces members of our team, we were always the person who was injured. Because the worst-case scenario was we’re in a firefight and I’m the one that’s hurt. Now you have to do all the medical stuff to me.

When you’re starting to talk about getting down into fire teams, that means you’re saying one out of every three to five people needs to be trained at a pretty high level in medicine. That really fundamentally changes the way you approach the structure of an organization, how you’re employing them, what you’re giving them and how you’re equipping them. How are the Ukrainians dealing with this? What is the process, or is it all trial by error?

Rob Lee: I can’t give you the best answer. TBI is a huge issue. TBI is maybe the majority of casualties. There’s really no way of pulling guys out in many cases. So in 7th Corps — they’re the guys holding Pokrovsk-Myrnohrad — typically Russia drops a lot of the glide bombs on the cities, wherever they think any positions are. Guys will be there with — they’ll get the bell rung, they’ll have TBI, and they just can’t rotate out. It leads to really long-term issues.

When they rotate guys out — these infantry, they do a lot. They do a full assessment, I know that much — psychologists meet with them, they’ll often be in rehab for a month or so or more. It really is physical damage. When you’re in a position for six months, you can’t move physically, all the mental stress. It creates all sorts of issues, most of which I can’t really fully understand.

Right now UAS is the majority of casualties — most casualties are frag in some capacity. One thing I was going to write about is what body armor should look like. When I was in Afghanistan with the Marine Corps — we went there in OEF, we had Interceptor vests in OIF at the beginning, then we determined we wanted something bigger and better than that. We went to MTVs, these kind of turtle things the Marine Corps had. The Army didn’t go with it. Then we went to Afghanistan, MTVs were very big but they were way too hot, too heavy, so we decided to go to plate carriers. When I was in Afghanistan it was both a threat from IEDs and small arms, so basically you wanted to have as much SAPI hard armor as possible. But now I think we’re going in a different direction — if small arms is only less than 5% of casualties, maybe soft armor really should be the focus. Do you need this many SAPI plates? Maybe we need more Kevlar inserts in the trousers and the arms. I think that makes sense, or making some kind of modular difference.

Another thing that’s interesting — UAVs are enabling a lot of things from mobility that weren’t possible before. One of these units that does assaults — the big threat is in open areas. They did this offensive operation, they needed this assault force, it was three kilometers of open terrain. They had the guys go slick — all they had was a rifle and maybe a few mags. They just ran across the field as fast as they could, doing eight-minute miles. When they got to the forest, they had vampires bring them everything — the rucks, the plate carriers, everything they needed. Because heavy bomber drones can do this. They can be the enabling logistics function and allow you to be mobile and not have to carry all this crap around as an infantryman.

In that respect — some guys from the Marine Corps reached out to me a month or two ago who were working on UAS modernization. They asked me about bomber drones, like, should we look at these things, or is FPVs the only lesson from Ukraine? And I’m like, absolutely you need to think through bomber drones. Vampires are less than $10,000. You can use them for mining, dropping munitions, all sorts of logistics — rucksacks, ammo, whatever. They can be a repeater for another drone. You can put a laser designator on it — you can laser-designate sites for Copperheads. Guys are launching air-defense missiles from these things. I have no doubt that if you get this into a good Marine battalion, the dudes will figure out amazing things to do with them.

If you’re doing remote operations and you need to get a fire team off the top of a hill — okay, guys, don’t carry gear, move up there, we’ll carry all the stuff to you by UAV. Mobility just becomes much better. It’s one way we can reduce the load on infantrymen, which has gotten way too heavy. When I was in Afghanistan I was probably carrying 60–70 pounds of gear. Some of that wasn’t the most. But when you’re fighting against guys who are carrying almost no gear and they’re in running shoes and I’m not — okay, I can cross this field, I can buddy-rush across this field, but I’m not going to do more out of that. We’re going to all be gassed. We don’t have enough water. Whereas if you can take certain kinds of modular decisions, you can mitigate a lot of those risks in interesting new ways with UAVs.

Body Armor, Rifles, and the Return of CQB

Tony Stark: That was super fascinating. On the body-armor topic, Justin and I have talked about this — the US Army’s new rifle, which is chambered in 6.8. The point being, there were some long-range engagements in Afghanistan that people think are the future of warfare. There are a lot of concerns around body armor itself needing a higher punch. But with that, you bring 20- to 25-round mags instead of 30 or more, which means you’re getting fewer rounds, especially when you’re doing things like clearing trenches.

The US Army — obviously the priority fight is the Chinese, and they focused on a much smaller engagement range, I think it’s like 95 to 200 meters or something for their rifle. There are issues with those as well.

My big question — are the Ukrainians, are you seeing reports from the Russians of them feeling like the 7.62 isn’t enough, or that body armor is really impacting how infantry choose to engage? Or are drones dominating it so much that body armor isn’t even a question?

Rob Lee: The Russians have some new uniforms where they have Kevlar inserts into the pants and tops. They’ll have a plate carrier, but you have soft armor that goes over the arms or legs. They also have tourniquets incorporated into the pants. Most infantry are not considered that valuable, but they have some interesting movement in that direction — toward more soft armor, less hard armor.

With the smaller stuff, it’s interesting. The first year of the war, I talked to a bunch of guys who fought over here, including some former Green Berets, and their view was — hey, we focus on CQB way too much. There’s no CQB happening, it’s always engagements at distance. Then it changed though, because now with FPVs, you basically don’t want to be in the open at all. So engagements at 400 meters — if you’re in the open at 400 meters, an FPV is going to come for you at some point. So basically you have to run from cover to cover. Even in 2023, my friends were doing assaults in Humvees and things, and their view was: look, we have to suppress, we drive across the front as fast as possible, then we get in the trenches as quickly as possible. We’re not moving up to anything else — we have to get into the trench, into cover, and then we will win in the trench itself. Their view is that basically it’s either very long engagements or CQB. That actual mid-range stuff is not happening that frequently now.

It’s been an interesting dynamic. Now guys are like, you know what, CQB is everything — it’s how do you find a trench, how do you find a building, because if you’re outside of these areas you’re going to get killed by either artillery in 2023 or FPVs now.

Now, what does that look like in the next war? I have no clue, and it’s hard for me to make a guess. I think marksmanship is still important. But I’ve now come around to the view that CQB is actually a completely decent thing to focus on. In 2022 I was like, you know what, we made too much focus on this. But now I’m coming back to — like, Ranger Handbook, trench clearing, clearing buildings. Clearing rooms should be different. It shouldn’t be four guys typically, because it’s a conventional fight. First off, you frag everything you can, you hit it with a tank, you destroy anything in there before you get in. And if you —

Justin: A grenade is the answer. That’s right.

Rob Lee: Too many guys in a room — if a tank fires on that room, all the guys are killed. You needlessly lose four guys. So it becomes an overriding issue — how many guys do you actually want to have in these areas? I do think CQB — maybe not the hostage-clearing type thing that Delta does, but back to — okay, let’s frag this room and try to kill everything first before we go in it. Then we go in with two guys instead of four. I think that still makes sense. There’s a lot of interesting innovation happening here in that.

In terms of 7.62, I haven’t really heard much about what calibers matter, because they’re not getting too many engagements. I know some Russians still use 7.62. They prefer that to 5.45 — even AKMs they’ll still use. They prefer having a heavier bullet. But in general, the engagement range isn’t enough where it’s a priority. Some Ukrainians like having 5.45 just so that when Russians come up to them they can use their ammo — they can capture the rifle and they have the same ammo. Otherwise, I haven’t heard too much about the ammo issue, just because drones are kind of overtaking everything in priority.

Justin: It’s interesting because it’s a return to — Mogadishu, after the Battle of Somalia. There were really big issues with some of the Rangers and some of the CAG guys where they were so hyper-focused on entering and clearing a building that their weapons were actually zeroed poorly. So they weren’t super effective at long range. They went back and really focused on, we need to make sure we can reach out and touch people. We need to be able to do engagement on rooftops, things like that. We can’t just be hyper-specialized.

You saw that kind of gain, especially through Afghanistan, where you started seeing people worrying about — I mean, you’d see guys with normal rifles that had elevation measures on them and stuff, because they were so worried about shooting high-angle, which realistically nobody was shooting high-angle — they were just above the person they were shooting at a little bit or below them.

To see it kind of coming back now — it’s basic infantry tactics. When they are being used, it’s 7 Alpha, enter and clear a trench, stuff like that, where volume of fire and violence of action are really the most important things. It’s just interesting how it’s always cyclical. Realistically the caliber doesn’t matter. What matters is the volume of fire and how much you can bring up. And that goes back to Tony’s point of having less bullets is actually potentially a negative when you’re looking at these tactics and operations.

Why Infantry at All

Jordan Schneider: So Rob, coming back to the beginning of this conversation, the guy in the hole on the front line for six months — how do you resupply him with a drone without giving away where he is?

Rob Lee: It’s not easy. First off, you try to make sure there’s no Mavic flying around, so you’re not hearing anything ideally. Almost all of it happens at nighttime, so vampires come up at nighttime. But it really depends on the Russians. The Russians have some units where they’ll have dedicated counter-night-bomber teams. Sometimes it’s snipers, sometimes it’s FPVs. Sometimes they have FPVs just flying around the front looking for targets. In other cases, any time they observe a night bomber coming, they’ll try to take them out.

In some cases, when Russia is advancing, they advance by making logistics impossible. They keep knocking out UGVs or vampires — every time they try to drop to infantrymen, they destroy the night-bomber UAV. I talked to a battalion commander in Kostiantynivka, one of the main battles happening around now — for the Ukrainian military, [the priority targets] are either logistics or the UAV teams. Most of the fires are directed at those two targets. Artillery does suppress infantry, but not really — again, infantry aren’t really killing Russian infantry. That’s not what’s denying Russia’s ability to maneuver on the battlefield. It’s UAV teams. So they’ll use artillery mostly to try to destroy UAV teams, sometimes suppress them. They’ll use glide bombs on UAV positions when they find them. Then they use FPVs, Molniya, and other UAVs on these targets.

It depends — in some places when it’s a village, they want to take the village, they’ll try to assault infantry and kill the infantry itself. Other places it’s like, you know what, the infantry are kind of irrelevant. We can walk past them. It’s really about knock out logistics so the infantry can’t be resupplied, kill the UAV teams. That’s how we enable maneuver. The priority is in a different direction. The Russians will put up ISR, try to find where the Ukrainians launch UAVs from. If they find launch locations, they’ll often hit with glide bombs or artillery, like Lancets.

Jordan Schneider: In the places where the Russians come to the conclusion that the infantry serve no real purpose or aren’t a center of gravity — why are the Ukrainians putting these guys through hell, then, in the first place?

Rob Lee: You need someone in front of your UAV teams. This goes back to what Tony asked before about infantry. It’s a hard question sometimes — what are infantry doing? Because they fight to some extent.

In some places infantry positions are more to deny positions to the Russians. So if it’s in a village, you have basements and buildings. There was a place near Kostiantynivka where I talked to the battalion commander last summer, and he basically said: look, all my guys are in basements in these houses. The houses are destroyed. We tunnel between the houses for our bunkers. Basically the infantry barricade themselves in. They don’t fight, they try not to fight. If the Russians get above them, they call in — hey, UAVs come and kill these guys. They try not to fight at all. But they prevent the Russians from using these basements as a staging ground to keep moving forward.

Elsewhere — infiltration. A lot of times, infiltration groups, the mission for them is to locate Mavic teams. They try to make it five kilometers past the front line or so, find Mavic teams, try to kill them with small arms. Some Ukrainian units attach one or two infantrymen to a Mavic team — they have personal protection for them. This is happening in Myrnohrad during the battle there. Ultimately you need someone in front of UAV teams. Yes, UAVs are killing the vast majority of guys. Yes, UAVs are locating most of the Russian soldiers themselves for observation. But not everyone, and you need someone in front of you. Mavic teams are often not the best guys at getting in a small-arms fight — they’re focused on flying Mavics. So it becomes a difficult conversation. Some places UAVs are holding the front line essentially. I told a battalion commander last summer — he had a month where no Russians made it to his FLOT. They killed any Russian that tried to make it; they were killed by UAVs. His infantry did no fighting for a month, basically.

In other places it’s more difficult. There’s no one standard answer. Sometimes it’s more of an OP, it’s not a fighting position. Sometimes maybe they want to have a guy on the map so the commander can say to his boss, hey, I’ve got guys here, we control this. They don’t really control, but they have guys there. Then it becomes a question of key terrain — where are the villages, where are the cities, where are the big coal mines? You’ve got two big cities — Kramatorsk, Sloviansk — these are the real priority. You’ve got two cities that are under pressure, Kostiantynivka and Druzhkivka. Kostiantynivka, the battle has kind of begun. We’re not sure how that’s going to go. Elsewhere it’s like, you have open fields, and the value of them is really not that significant except in terms of how close it is to cities, does it help you get to cities.

Part of this is very different from the way we talk about maneuver warfare, because for us it’s never just focusing on terrain. It’s about looking at the enemy’s system and how you defeat the system. Right now a lot of it is — where’s the front line? We want to move the front line this direction, that direction. Territorial control is an important consideration. It’s a very different conceptual thing than the way the US military operates.

Justin: In some ways what you just described — Jordan used a good term, he talked about center of gravity. I actually think what you just described is a critical requirement. If you break down COG and you do targeting, you’re working your way all the way down to core vulnerabilities. Interestingly for both the Ukrainians and the Russians, their critical capability and their core vulnerability are the same thing. It’s the Mavic teams. It’s the drones — it’s the ability to deep-strike and it’s the ability to actually protect. That requirement that sits in between is an infantry line to be able to protect them. That’s what it becomes. You’ve removed them from being an ownership piece of owning terrain, but what you’ve given them is a requirement that you actually protect this critical vulnerability that, if we did not have, we would then not be able to perform the function of a military.

When you conceptualize it like that, it kind of does fit into our normal definitions of maneuver warfare and thinking as a system. But it is something that’s slightly abstract, because we normally think of systems being like fuel or ammunition, and not as a set of humans.

Rob Lee: That’s true. I’d also say — there isn’t really a FLOT anymore, because Russians are constantly behind it. Positions are intermixed. It’s never clear. Maps show kind of a gray zone, but in some ways I think there’s a benefit in saying not necessarily where’s the forward line of troops, but where’s the forward line of UAV teams on both sides. That becomes the definition of the front line, because everything in between can be complete mix.

What the Marine Corps Should Steal from Ukraine

Tony Stark: I find this fascinating, because one of the debates the US Army has had for the last 15, 20 years is — who owns reconnaissance? Is it ground teams? Is it UAVs? The first time with UAVs — the Raven and everything else didn’t work very well, there were massive support teams for them, they often crashed. Now we’re seeing, from lessons in Ukraine, you can use UAS effectively for reconnaissance. But then you still have the Russians doing infiltration tactics and being able to do that way. The lesson here for the United States is you have to have a mix of both, because they provide different perspectives on reconnaissance.

Rob Lee: On Bryan’s thing about what the Marine Corps could do to adopt UAS — if you’re adopting UAS from Ukraine, there are changes that might make sense in an infantry battalion. For the Marine Corps, the GCE needs to lean in on UAS. Thus far it’s mostly been the ACE, the air wing. The ground component has not been the main focus. With small UAS, it needs to be in the ground domain. My view is that infantry battalions should be massively increasing their UAS component.

I would be radical in this regard. With the Marine Corps, with FD-2030, we got rid of tanks, we got rid of a lot of the 155s, we lost a lot of our fires capability. Okay, the focus on China — we had to do anti-ship missiles, all that stuff. You can compensate for a lot of those things through UAS though. One of the things I was explaining to the guys I talked to in the Marines — FPVs we’re procuring, that’ll probably be a battalion-level asset, maybe goes to weapons company. FPVs take training, though — you need guys pretty good with them. Other UAVs like the Hornet are pretty easy to learn. It’s not that complex, it’s cheap, logistics are pretty minimal. If you put it at the battalion level as the battalion commander’s eyes and ears — because you can have a cheap ISR with it too — you can massively expand the range of what an infantry battalion can engage.

Right now, the maximum range of a Marine infantry battalion is the same thing it was when I was in, which is an 81mm mortar. The max range is 5,700 meters. FPVs give you four times that range, easily, for engaging armor, infantry, whatever. But a Hornet would give you — Hornets are hitting things at 200-plus kilometers. Massively increase the range. The training is not significantly improved. Logistics are not too much. That’s something we could do, especially because the Marine Corps battalions are operating far from the regiment in cases, or on their own. It makes sense to push these things there.

I think fixed-wing ISR, cheap ISR, makes sense. At company level — I don’t know if you guys know about the Bumblebee. The Bumblebee is the FPV-type thing the Schmidt company makes. The Bumblebee is very cheap — it’s less than two grand. It can perform the role of a Mavic, like a reconnaissance Mavic. It can be a kamikaze FPV. It can be a bomber FPV. It can do all those things. Same software, same command and control as the Hornet. When a Bumblebee locates a target automatically through AI, a Hornet pilot can see that. It can basically ping a target for a Hornet team to go after. You can put it on the company level. The training is not that significant. You can really change that dynamic very quickly. The company — maybe get rid of Carl Gustavs, I don’t know, something like that. You have to get rid of something, I think.

The company really increases its capabilities quite dramatically. It has its own reconnaissance capabilities. It’s cheap enough where you can lose them and it’s not a big deal. It can do strike, it can do a bunch of things. We can start pushing things in there, and really it needs to be the ground component. You can significantly increase the lethality of these units at all levels by leaning heavily on these capabilities. I think people don’t understand how cheap they are, and how much they can increase lethality at a very low price point.

Justin: I would back that up too. It’s not even just not understanding the economics of it — that’s something the military has always struggled with at a tactical and operational level. To quote a movie, it’s fugazi. It’s all made up. The money doesn’t actually matter to the tactical person, because they have an objective and they have an asset, and they’re told to get the objective. It’s, well, I’m going to use the best asset to get that objective, whatever that may be.

Where they’re struggling the most, based on everything you’ve said, is when you look at the way US Army and even Marine Corps doctrine has tried to define really hard lines between what is a fire team’s distance and what is a platoon’s distance and what is a company’s distance. They try to slice up the battlefield into these discrete segments — well, if it’s 40 kilometers away, that’s going to be the brigade. If it’s 50 kilometers away, that’s going to be the division. Realistically, what we’re talking about now is a fire team that’s properly equipped could potentially reach 200-plus kilometers and have effects. That’s something I don’t think commanders have fully grappled with. They haven’t started to figure out what happens when I have a 24-year-old — because we’re talking about a lieutenant — when I have a 24-year-old who’s making decisions that have what used to be considered operational-reach impacts onto an enemy battle space. How am I looking at resources, thinking about supplying them, thinking about timing those operations, and making sure that we have those synchronized?

Those are the really hard questions that until you actually start getting drones, getting that type of equipment into tactical hands, you’re not going to have an answer for.

Rob Lee: Yeah. It’s also a question of — do you put them in infantry units, do you put them in artillery units? Where do they go? The Germans are going to put loitering munitions in artillery units. That makes some sense to me too. The Marine Corps, you attach out howitzers to battalions or to infantry regiments. That could make sense. I just think that as low as possible, you want to integrate UAS where infantrymen are comfortable around them. They’re always involving them in some respect. It’s not just something you get attached and it does its role. It’s like, no, you integrate them as much as you can.

A lot of the new UAS coming out is going to be pretty easy to operate. You can make it much simpler than it used to be. In which case, you don’t need a special MOS for all these drones. It can just be an infantry guy. You give him a week of training on a Bumblebee, he can fly this thing. He doesn’t have to be perfect. If it’s cheap enough — okay, you lost one, okay, it’s $1,500. It’s like a third of the price of a PVS-14. We’re going in that direction.

I’m fully cognizant that I don’t know exactly what it should look like. I know that if you get this stuff to infantry units or to SOF, they’ll plug and play and figure it out very quickly — here’s what would make sense, here’s what doesn’t. But there’s a ton of utility here. The tough question is going to be — what capabilities do you give up to integrate these things? Because something’s got to go away. If you start pushing it into battalions, then it becomes a question of, do you want to give up M240s, do you want to give up heavy machine guns, mortars, and so on. It will become a difficult question. But I certainly think that we need to start moving in that direction.

On the Russian side, some of their battalions, they’re pushing FPV teams to battalions, they’re pushing Molniya teams to battalions, and they have fixed-wing ISR at battalion level too. They’re still tinkering, but that’s the direction they’re moving. I think it makes sense for our battalions to also go in that direction, because you don’t want your battalion commander to be outranged by an enemy battalion. There’s no reason we have to be. It’s not cost-prohibitive.

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Two Marines

Newsletter from former US Marine Rob Lee and Ukrainian Marine Dmytro Putiata on the Russian-Ukrainian war, defense technology, and modern warfare.

By Rob Lee

F. Ichiro Gifford is an energy analyst and a former civil servant, having worked in electric utilities as a planning-economist integrated resource planner. He is going through a very Soviet period in his life and recently read To the Success of Our Hopeless Cause (2024) by Benjamin Nathans, whom Jordan has interviewed on ChinaTalk! Ichiro thinks that the story of late-Soviet dissidents (and of the Russia they lived in) offers some guidance for how we should approach the 2020s in the United States. Ichiro’s Russification has also motivated snippets of fiction written in the style of a Russian-language screenplay translated into English.

A core challenge with writing a history of the Russian dissident movement is that they didn’t do much. There was a transparency meeting митинг гласности, some international contacts that went nowhere for years, a 1968 demonstration on Red Square that served as a peak of direct action (although that was only eight people)… but little more.

The Soviet dissident movement kickass books though.

KGB Agent: Good afternoon. Your name is--Aleksei Blagoslavovich Nepobedimov, right?

A.N.: Alyosha Blagovich is fine. And you are?

KGB Agent: Andrei Il’ich.

A.N.: Quite pleasant to meet you. You--you want some tea?

KGB Agent: No. But I have heard you’ve picked up some new reading material.

A.N.: Well--I like reading.

KGB Agent: Do you like your job?

A.N.: Yes. It’s good work.

KGB Agent: TETs-20,1 correct?

A.N.: That’s the one.

KGB Agent: Do you prefer reading more than doing your job?

A.N.: The reading is just for fun. The work--that’s what helps people.

KGB Agent: So why would you read material that harms people?

A.N.: How do you mean?

KGB Agent: You’re reading anti-Soviet propaganda. Passed in, passed on. You know that material is harmful, right?

A.N.: I don’t take it seriously.

KGB Agent: Why not?

A.N.: It doesn’t mean anything. They’re just weird books. I’ve--I’ve run out of Dostoyevsky, you know? I can’t just stare out the window. I get bored. Nothing more.

KGB Agent: Understood. But the things you’re reading are bad for you. I’m sure you know.

A.N.: So is vodka. We still drink.

KGB Agent: I would advise you be careful. Oh, and you wouldn’t happen to remember who gave those materials to you?

A.N.: I don’t ask for their names, Andrei Il’ich.

KGB Agent: Maybe you should, next time. I might ask someday.

Benjamin Nathans’s rockstar history book To the Success of Our Hopeless Cause (2024) is less a story about a protest movement (a mistaken assumption by contemporary Western observers) and more about a book club that the Central Committee thought way too much about. The cohort Nathans talks about — Volpin, Litvinov, Bogoraz, Gorbanevskaya, Yakir, Sakharov — are disproportionately Muscovite intellectuals. To the extent that the dissidenty диссиденты left Moscow, it was to be exiled — to Siberia, to psychiatric hospitals, to Cavendish, Vermont for Solzhenitsyn. Even St. Petersburg — sorry, Leningrad — is barely mentioned. And no matter how prominent the dissidents got — and they were most prominent in Yuri Andropov’s head — their primary actions focused on defending their friends. Volpin himself had a straightforward (to him) focus on making the Soviet Union follow its own laws, and to that end, he aspired to a legalist framework popular enough to be supported by people he didn’t know. But the vast majority of the “chain reaction” between 1965 and 1968 came from hip Muscovite writers defending their writer friends with more writing. And credit to the dissidents, they were better writers than the Committee for State Security.

Susanne Schattenberg’s 2017 (translated 2021) biography of Leonid Brezhnev gives some context on the Kremlin’s view. Brezhnev, along with Alexei Kosygin and Nikolai Podgorny, had just yanked control away from a Nikita Khrushchev who couldn’t stop being an asshole. And ol’ Lyonya wanted everyone to like him. He wrote his speeches by consensus, took world leaders on hunting trips at his dacha, and insisted on calling the most powerful men in the Second World by pet names, even as he sidelined many of them. He was trying to be a nice guy, and clearly, that message trickled down to the KGB: stop shooting people. You’re not the NKVD, and you’re not the First Secretary’s attack dogs. Act like professionals. But Vladimir Semichastny didn’t know how to run an unscripted trial. No one did. The KGB team assigned to the trials of Yuli Daniel and Andrei Sinyavsky figured that if they simply grilled these guys on their obviously anti-Soviet writing, they would get their proof that these writers were, I guess, CIA-funded rubes consumed by the same demons that got Stavrogin and Verkhovensky.

It didn’t work out like that, in part because the morally-grey, unreliably-narrated, flatly-bizarre literature of Daniel and Sinyavsky is perfectly in line with Dostoyevsky, a man who wrote a story within a story about the Grand Inquisitor of the Spanish Inquisition arresting and interrogating Jesus, Son of God.

A.N.: What I’m saying, is that Dostoyevsky would have been arrested just like Daniel and Sinyavsky, and it would have gone exactly the same way.

S.L.: Dostoyevsky was a great man of Russia. The KGB wouldn’t arrest him.

A.N.: You sure, Seryoga? Demons was not kind to the people in power. And it was just as goofy as This is Moscow Speaking.2

S.L.: You read that thing?

A.N.: Of course I read it. You think I wouldn’t check what the fuss is?

S.L.: Wasn’t that the story about a “Public Murder Day?” That’s a dumb premise.

A.N.: Well, yes, and the “group of five” in Demons were pretty dumb too. That’s the point.

S.L.: But the book itself wasn’t dumb.

A.N.: Listen here, run through the accusations made to Daniel and Sinyavsky--they have characters who say horrible things. They depict things that are flatly ridiculous. They have sex and heresy in them. Dostoyevsky did all that.

S.L.: Not like that--

A.N.: Exactly like that! So you put him on trial and say, “In the story, you have a famous writer who thinks Russians are all drunk idiots, and who says he’d rather be in France--”

S.L.: Alyosha--

A.N.: “--Do you, Fyodor Mikhailovich, think all Russians are drunk fools, and would you rather be in France?”

S.L.: You sound like a drunk fool. You.

A.N.: Yes, on whose vodka?

S.L.: Yes, yes, remind me not to ask for your literature opinions.

A.N.: Would you prefer we complain about work instead?

S.L.: Yes, actually. Because work, I can understand. A stupid director I can go around, or at least deal with. But what did Sinyavsky want? Why make trouble when things are quiet?

A.N.: Because it makes for better art?

S.L.: Is annoying people good art?

A.N.: Sometimes. The best art comes from people poking the boundaries of what is and isn’t art. Look at Picasso.

S.L.: I never understood Picasso.

A.N.: You’re right, let’s talk about something else. You’re still seeing Natalya Ivanovna?

S.L.: Went to see a movie with her. Three Poplars on Plyushchikha.3 It was pretty good.

A.N.: Was it Diamond Arm4 good?

S.L.: No. She picked the movie. It’s for girls. Do girls like Sinyavsky?

A.N.: No, they don’t. That’s for my entertainment.

The Prague Spring was the turning point — more specifically, the tanks deployed in response to the Prague Spring.

Alexander Dubček’s pitch was notionally straightforward: What if socialism asked the secret police to chill out? What if socialism allowed a free press? What if socialism had a human face?

This was Brezhnev’s first test as a leader of the Soviet Union. He didn’t take it well. He had seen himself as a mentor to young Dubček, but as the political view in Prague diverged further from the Politburo, he resorted to a “friendly” negotiation at the Ukrainian-Slovakian border, mediated between train cars and swarmed with KGB agents. Brezhnev’s health suffered: headaches, stomach pain, fevers, conducting negotiations in pajamas. As the rapport with the Czechoslovak delegation collapsed, Brezhnev promised that he would resign should he lose the ČSSR, sobbing at the moral loss of his mentee, Comrade Dubček, dear Sasha. And although the Prague crisis would turn out “fine” for Brezhnev (less so for the dead Czechs and Slovaks), it introduced him to a sleeping pill habit that Western observers wouldn’t learn about until the fall of the Soviet Union. The ’68 invasion of Prague proved the defining moment of the Brezhnev Doctrine: protect Party control over socialist states for fear of a revisionist domino effect. But it also precipitated the stumbling, gerontocratic decline that defined the ‘70s and ‘80s in the Soviet Union.

The response to Prague was similarly both the defining moment of the dissident movement and the source of its decline. Eight protesters showed up at Red Square, in front of the Kremlin, with banners. The KGB found them in minutes, beat them, and dragged them away. This was, in Nathans’ words, “the most celebrated fifteen minutes of history in the history of the Soviet dissident movement.” Joan Baez wrote a song about it. But it was a mortal blow to the movement. Larisa Bogoraz, Pavel Litvinov, and Natalya Gorbanevskaya were key figures. Bogoraz at the time was married to Yuli Daniel, whose arrest kicked off the dissidents’ chain reaction. Litvinov was a major distributor of the samizdat самиздат literature that defined the dissident movement. Gorbanevskaya was a founder of the Chronicle of Current Events Хроника текущих событий, a samizdat periodical of Soviet attacks on human rights — and apparently the most consistently productive thing dissidents did. Bogoraz and Litvinov were sent to Siberia, Gorbanevskaya to a psychiatric hospital a year later. Without them, it seems like a lot of things didn’t get done. The Chronicle of Current Events kept on without Litvinov and Gorbanevskaya, but by the time these three returned from their exiles in the early ‘70s, the dissident movement had lost its mojo, much in line with a declining General Secretary.

A.N.: Andrei Il’ich.

KGB Agent: Aleksei Blagoslavovich. We are no longer playing games.

A.N.: I was on my way to work. To work.

KGB Agent: And now you’re talking to me. Why are you still reading anti-Soviet literature?

A.N.: Listen here, I still don’t understand what makes my reading habits “anti-Soviet.” What does that even mean?

KGB Agent: You’re reading the Chronicle of Current Events.5 That’s anti-Soviet literature. As a member of the Party, no less! Why are you playing both sides here?

A.N.: Playing both sides? I’m on the side of the Soviet people.

KGB Agent: Then why read foreign-funded accusations about the Soviet Union?

A.N.: Foreign--? Well--let’s argue the merits here. Is it true or is it not true that the USSR still treats the Crimean Tatars like they’re traitors?6

KGB Agent: Those are baseless accusations.

A.N.: Then why not refute them? I read Pravda.7 No mention. I would like to believe we treat our minorities better than the Americans, but do we? And if not, why not?

KGB Agent: Have you considered focusing on your job, Alexei Blagoslavovich?

A.N.: Why, I have. I’ve managed to cut maintenance costs by 25% compared to 1968, by instituting a predictive maintenance plan instead of waiting for things to break. I think my work is replicable. It’s in a nice little report--you know about me, you’ve probably read it. But it has sat on my director’s desk. For three months. Three months.

KGB Agent: Have you considered working harder?

A.N.: I’d only be too glad, Andrei Il’ich. I would love to run economics for a second TETs plant. But right now, I’ve run out of things to do. The work I’m responsible for gets done by 2 PM, and then I do extra work to improve the TETs, and that extra work does nothing. Nothing. And why? Because Mosenergo8 is managed by complacent blockheads who haven’t learned a new fact since the Great Patriotic War.9

KGB Agent: I would be careful what I say about war heroes.

A.N.: Because they were great men at my age? Well, they’re fat and lazy now.

KGB Agent: Would you like them to know what you think?

A.N.: Do what you like. Send me to Tashkent10--what do I care! You’ll replace me with someone worse at TETs-20, and there I’ll get real work done. To the devil with it, they might actually let me improve things.

In fairness to the dissidents, it took more than a few arrests to quash their energy. The KGB got their act together by 1969, with Yuri Andropov’s Fifth Directorate. The KGB figured out that they couldn’t out-read or out-write a cadre dominated by writers and scientists, but they could curtail their influence by targeting normal people who hung around the dissidents. Because to most Soviet citizens, at least in the primary cities of Moscow and Leningrad, the ‘60s and ‘70s were the best time to be Russian in a century. No more purges, no more total war, no more civil war, even a reprieve from the ambient violence that marked the dying decades of the Tsar.

Most importantly for regular Russians, material conditions improved under Brezhnev. One of his first projects (along with his number-two Kosygin) was a series of economic reforms to prioritize improving living standards among the Soviet citizenry. Brezhnev wanted washing machines, refrigerators, larger apartments, consumer goods — even if they were imported from capitalist countries, even if they came at the cost of Soviet gold reserves. Brezhnev’s dream was to produce so many cars in the Soviet Union that it would become a dowry item for weddings. And although material conditions never quite matched the West — a Sensitive Young Planning-Economist like yours truly would have at best had a bed in a hostel room — they were beyond the realm of complaint. No one thought to ask for more, even among the dissidents.

This made being a true dissident a risky bet for unclear gains. The KGB would and did track people with samizdat, and by 1969, they had figured out how to handle them. First, a “prophylactic conversation” профилактическая беседа to clarify what was and wasn’t acceptable. And if that wasn’t enough, the targeted individual might face a pay cut, or lose some job perk, or get their room searched (or bugged), or even get fired. And of course, they’d become The Guy With A KGB Tail. That’s all it took for most people, especially because the dissidents asked for very abstract things: civil liberties, justice for people you haven’t met, permission to read and write weird books. These are not normal things to want. Even if you liked reading Andrei Amalrik, you needed some extra je ne sais quoi to like Amalrik more than access to a car. It was always easier to be a bystander than a true dissident — and besides, what was the point? The stability of the Brezhnev years was the best one could have asked for, and it was much easier to imagine a return to Stalinism than something as strange as “rule of law.” What laws? There was an agreement: the government pretends to follow the law, and the people pretend to follow the law. You play your part in the charade, and you carve out a life that matters to you, in your friends, in your family. And if that’s really not enough, you pray to God, you freak.

These measures ultimately kept the dissident movement small. In the Soviet Union, it remained a smattering of friend groups that the Central Committee kept bringing up in conversation. In the late ‘60s and early ‘70s, a city’s true dissident movement apparently could fit in a kitchen or two, with a wider network of samizdat readers that didn’t want the real smoke. These movements could straightforwardly be crushed by arresting enough people… just more than a handful. And by the late ‘70s, the Fifth Directorate had managed it. But by that time, Amnesty International had figured out inroads with the dissidents, and Brezhnev’s quixotic dreams of world peace and personal friendship with glamorous Western heads of state had made him care what the West thought. Yet the Westerners kept asking about all those political prisoners, and Yuri Andropov didn’t have good answers beyond “Nuh uh,” and “What about your human rights abuses?”

Brezhnev didn’t understand the dissidents any more than regular Russians did. What did they have to complain about? The regular Russians had a point, but those same complaints were rich coming from Brezhnev, who had a car collection to rival the flashiest heads of state and had cultivated a sense of open discourse among the top echelons of the Communist Party. He at least asked for deputies who spoke frankly, although he might not have liked that dissent from guys like Kosygin. Brezhnev could say things were going wrong in the Soviet Union, in a way that regular intellectuals could not. And the guys around Brezhnev had freedom to operate that they did not pass down the chain of command.

Then again, power enables its own freedoms, independent of any laws.

KGB Agent: Alexei Blagoslavovich.

A.N.: Andrei Il’ich. Welcome to my home.

KGB Agent: We have a warrant to search your residence.

A.N.: Yes--consequences. Would you or your colleagues like some tea?

KGB Agent: You will stay where we can see you.

A.N.: Understood. The materials I suspect you are looking for are on top of my bookshelf. But I’m sure you’ll look through everything regardless.

KGB Agent: Do you think you know what we’re looking for?

A.N.: I have--some understanding.

KGB Agent: Of anti-Soviet materials?

A.N.: You have not provided evidence that anything I have read is anti-Soviet.

KGB Agent: Is this your roommate?

A.N.: He is. He--he wants no part of my reading material. I would offer his name, but I’m sure you know already. At any rate, you have work to do, I’ll let you get on with it.

KGB Agent: Thank you.

A.N.: --

KGB Agent: I hear you have been transferred to another TETs facility.

A.N.: Yes, Andrei Il’ich. TETs-16.11 The commute is longer, the pay supplement is slightly less, but--I’m getting proper work done. Proper work.

KGB Agent: Is that so?

A.N.: Yes. I learned that one of the boilers had been out of order for four months, but because there were some typographical errors in the fuel consumption reports, no one had noticed. Innocent mistake. However--well, so--I keep carbon copies of everything I send to the chief of planning and economics. For archives. Personal archives.

KGB Agent: Indeed.

A.N.: But I made a mistake in my filings, and I lost my personal copy of that report. And two weeks later, I get a call from the partkom secretary12 saying he had found it. What a relief.

KGB Agent: I wonder how the report got to the partkom.

A.N.: I was about to ask you that. Maybe there was another warrant for my desk. I’m joking. Joking. At least someone found the issue before winter. I managed to organize a fix of the issue. Somehow the TETs had run out of copper pipes, but I found replacements.

KGB Agent: I should investigate where those parts came from.

A.N.: Well, Andrei Il’ich, I am a good planning-economist.13 I meant to ask you, did you hear about the recent outage at TETs-20?

KGB Agent: I did not.

A.N.: Turns out there was a major accident there last week. I had reported that some of the seals in the hot water loop were due for maintenance, and I left a report for my replacement to order new seals. The order was made, but the replacements were lost in transit. The seals failed, a pipe burst, and a worker got burned badly.

KGB Agent: --

A.N.: An honest mistake, I’m sure, but I liked tracking our parts shipments. I would have followed up. I would have. But it was an honest mistake.

KGB Agent: What does this story have to do with me?

A.N.: Nothing, I’m sure. Nothing. And I know you have nothing to do with my transfer. But I want to thank you anyway. The consumers of Khoroshyovsky raion need heat, and I got to do my part to help them. And I’m sure TETs-20 will get on well without me. Once they replace those seals.

At no point did the dissidents ask for a new government, or even the political reforms that Alexander Dubček sought. With rare exceptions, they insisted they were apolitical — and who can blame them? Russia had seen enough of revolution, and considering how much “political activity” the Communist Party asked of people, even asking people to sign Yet Another Letter was… too much. But by the time the Fifth Directorate started arresting people for the notionally prosocial cause of monitoring the USSR’s participation in the Helsinki Accords that Brezhnev had proudly signed, it became clear that even asking the Soviet Union to follow its own laws was too high a bar. The only freedom a Soviet citizen could find was in their own soul.

And as Alexei Yurchak describes in Everything Was Forever, Until It Was No More (2005), the exhausted complacency of the late ‘70s and early ‘80s of Russia made personal individuation increasingly attainable. As the Soviet project sacrificed the ideological dynamism and chaos of Stalin for the more staid and stable rule-by-committee of Khrushchev and Brezhnev, the language of the USSR increasingly became uniform, anonymous, and predictable. The norms of Soviet administration ossified, and in ossifying, they opened up space between what the words of the Soviet Union were and what they meant. Yurchak names this phenomenon a performative shift, in which citizens were only asked to perform the rituals of Soviet citizenry, not to hold the revolution in their souls. And by the time the Fifth Directorate had taken up its mission of quashing the dissidents, they had stopped probing the souls of the people they arrested and interrogated. It was easier to write off dissident action as drunkenness, or foreign interference, or mental illness if they kept talking.

The dissidents took notice, and in parallel evolution to Victor Frankl, they concluded that one’s soul could be free even in a labor camp, no matter how hard a totalitarian tried. But because the Kremlin gradually placed less and less emphasis on Soviet souls, almost everyone found room for their own personal freedoms. It became possible to be neither activist, nor dissident, but simply a normal person нормальный человек. Komsomol meetings became social groups that started with perfunctory votes to please the raikom райком (district-level party committees). Black markets (always a normal part of Soviet life) pulled in Western clothing and trinkets. Coworkers exchanged anekdoty анекдоты making fun of their home country, and sometimes, their supervisors joined in.

A man has traveled to a hostel with two coworkers. His coworkers start drinking in the evening and talk loudly late into the night. The man leaves the room, asks the front desk for a pot of tea, and then returns to the room.

Then, as his coworkers start exchanging political jokes, he walks to a wall socket in the corner and asks, “Major-General, could you send up a pot of tea?” Minutes later, the pot of tea arrives. The coworkers abruptly stop talking, and the man is able to sleep.

When he wakes up, his coworkers are gone. He walks to the front desk and asks where his coworkers are.

“They have been arrested.”

“Well, why have I not been arrested?”

“The Major-General thought your tea joke was funny.”

By the early eighties, the Party’s monopoly on discourse had dissolved. Samizdat publications about art, religion, feminism, Western economics, and more had become accessible. Leningrad in particular developed countercultural spaces like Saigon, a cafe that became a hub for poetry, and Kamchatka, a boiler room that served as an impromptu venue for the now-famous rock band Kino Кино. By the time Gorbachev instituted glasnost — the same term Volpin used in 1965 — as official policy, Kino was already famous. And as the war in Afghanistan limped to its conclusion, Kino produced the album about the war.

I could pay what is asked — but I don’t want victory at any price.

I don’t want to place my boot to anyone’s chest

I’d have liked to stay with you — just to stay with you.

But a star up high calls me to the road

But even Blood Type Группа крови (1988) refrains from overt political statements — read literally, there’s no mention of the Communist Party, of Afghanistan, of a specific war. It’s more about the self. If you can’t change The System, if you know that changing The System will only make things worse, then all you can do is save yourself and those you love.

And if you can’t do that either, at least you can save your soul.

A.N.: Andrei Il’ich.

KGB Agent: Alexei Blagoslavovich.

A.N.: Pleasant to see you. Would you like some tea?

KGB Agent: --

A.N.: As a guest. A guest.

KGB Agent: I would be glad to.

A.N.: I take it you have a request for me?

KGB Agent: I do. We are investigating a man you may know--Aleksandr Dronov.14 We have evidence that he distributed anti-Soviet material.

A.N.: Dronov--

KGB Agent: No games. You’ve spoken to him.

A.N.: I see. I see.

KGB Agent: We are collecting witnesses to his activities. I would like you to corroborate our report. We have already collected testimony from his associates at the Oil Institute.

A.N.: Will I need to write my own testimony?

KGB Agent: That is not necessary.

A.N.: May I review the testimony before signing it?

KGB Agent: That is also not necessary.

A.N.: And the alternative is--Tashkent?

KGB Agent: Tashkent--no, Surgut.15

A.N.: Surgut.

KGB Agent: Yes.

A.N.: Lot of oil and gas work.

KGB Agent: So I have heard.

A.N.: They need men.

KGB Agent: Yes.

A.N.: They need planning-economists.

KGB Agent: Good ones.

A.N.: Sounds like hard work.

KGB Agent: Yes.

A.N.: Much less time to read.

KGB Agent: I understand that is important to you.

A.N.: --

KGB Agent: Of course, I am here regarding Dronov.

A.N.: You are a kind man--Andrei Il’ich. I’ll start packing.

KGB Agent: And Dronov? Dronov?

A.N.: I’m not providing testimony.

My interest in the Brezhnev days extends beyond mere fascination with the geopolitics of my father’s generation. I got hooked in part because I recognized myself in the history. I read the abstruse, block-quoted language of august socialism, and I recall boring leftist zines from college. I read of the political infighting and cliquey politics of the ‘30s, and I remember the Twitter of old. I read of enforced conformity and aesthetic philistinism in a nation of snitches and narcs, and then I open up the Twitter of now. And as I stumble into a doomscroll, I see sclerotic institutions collapsing from senescent bureaucracy, a nation led by an aging ex-thespian who is losing the ability to stand, much less speak. I ask myself what room there is for an artist, a civil servant, a dissident-by-temperament who has sought conventional power. I ask myself what I must do for the people beyond me, beyond the people I personally care about, the us свои, the ours, наши. And I find my answers in Yurchak and Nathans; I find the aesthetic register in Dostoyevsky and Tsoi; I realize that if I play my cards right, I can live a full life no matter what happens.

Zilan Qian is a research associate at the Oxford China Policy Lab and holds a Master’s degree in Social Science of the Internet from the University of Oxford.

This article was originally published in Asterisk Magazine.

Americans — left, right, and everywhere in between — seem to be afraid of AI. They fear data centers speeding up climate change, disinformation and deepfakes, AI companionship, and, above all, job loss from automation. Meanwhile, the Chinese public seems to be perfectly fine with the technology, or even “optimistic” about it.

The polling data is striking: Stanford University’s 2026 AI Index Report shows that more than 85% of Chinese respondents see AI as more beneficial than harmful, compared to less than 45% of respondents in the United States. A 2025 report published by the University of Queensland and KPMG Australia revealed that 73% of Chinese respondents are willing to trust AI system outputs and share relevant information with AI at work, and 88% intentionally use the technology, compared to 52% and 48% of Americans, respectively.

Why does Chinese society, which suffers from acute job loss and a youth unemployment rate close to 17%, embrace a technology it knows is likely to take away more jobs?

The question was answered three decades ago. The answer is not a narrative about AI, but about an earlier transformation also perceived as inevitable. It is a story about how Chinese society has learned, through repeated upheaval, what it believes to be the only permissible response to disruption. Accurately interpreting that response — which is often misleadingly called “enthusiasm” — is essential to understanding that worried Americans watching China’s AI frenzy might not be looking at a rival but into a mirror.

The millennium that broke two ways

Lived this way for thirty years
Until the great mansion collapsed
The deep, dark clouds
Are drowning the view in my heart.

如此生活三十年 ruci shenghuo sanshi nian
直到大厦崩塌 zhidao dasha bengta
云层深处的黑暗啊 yunceng shenchu de hei’an a
淹没心底的景观 yanmo xindi de jingguan

– “Killing the One from Shijiazhuang,” Omnipotent Youth Society, 2010

In December 1978, reeling from the economic wreckage of the Great Leap Forward and the Cultural Revolution, China’s Communist Party formally shifted its central task from class struggle to economic construction, launching Deng Xiaoping’s “Reform and Opening Up” and beginning a gradual dismantling of three decades of central planning. In 1992, the country formally declared a turn toward a socialist market economy — an acknowledgment that market forces, not central planners, would now drive growth.

The country’s enterprises, built for a planned economy, were suddenly exposed to market competition — and consequently began hemorrhaging money, especially in industries like steel and textiles. By 1997, the state had decided to consolidate the strategic enterprises and let the rest restructure, merge, or collapse. The slogan it coined was 减员增效 (jianyuan zengxiao) — “reduce headcount, increase efficiency.”

The consequences of this transformation depended on where you lived. Over 24 million workers in China lost their jobs in the state sector by the end of 1999. The layoffs were concentrated in the northeast — Liaoning, Heilongjiang, Jilin — once the industrial heartland of socialist China and now called China’s rust belt. In 1957, the city of Shenyang’s Tiexi district produced the nation’s entire output of lathes, rock drills, gliders, rubber boats, and tower cranes, earning it the nickname “the Eastern Ruhr.”

By the late 1990s, 80% of the companies responsible for this output had gone out of production, and half of the district’s 300,000 industrial workers had been laid off. Between 1998 and 2000, nearly every year saw 7 to 9 million workers laid off nationally. Liaoning, for example, was laying off nearly 1,700 workers every single day. The moment was so unique that even the act of being laid off had a special name: 下岗 (xiagang), which literally means “stepping down from the post.”

Yet while the transition led northern China into economic crisis, the Pearl River Delta — geographically proximate to Hong Kong and Macau, home to China’s first Special Economic Zones, and the ancestral homeland of much of the Chinese diaspora in Southeast Asia and beyond — embraced rapid modernization and internationalization. The historical “land of fish and rice” became the “world factory.” Hong Kong investors established over 65,000 factories, employing about six million workers in the Delta. From 1991 to 2001, the Pearl River Delta’s regional GDP grew almost eightfold, and its population increased from 20 to 43 million.

For these citizens, the new economy meant good lives, which now included new technology. In 1998, Microsoft unveiled the mainland China version of Windows 98, and signed musician Pu Shu to endorse it. “New Boy,” a track on his 1999 album, name-checks Windows 98 and Pentium computers in its chorus and became a genuine millennium anthem for a generation.

Put on new clothes, get a new haircut
Relax with Windows 98
The road ahead will have no more suffering
How cool our future will be.

穿新衣吧, 剪新发型呀 chuan xinyi ba, jian xin faxing a
轻松一下, Windows 98 qingsong yixia, Windows 98
以后的路不再会有痛苦 yihou de lu, bu zai hui you tongku
我们的未来该有多酷 women de weilai gai you duo ku

– “New Boy,” Pu Shu, 1999

China’s tech giants — Alibaba, Tencent, and Baidu — were all founded between 1998 and 2000. By the end of 2000, the number of internet users in China had jumped from 3000 in early 1995 to 22.5 million. In 2001, China joined the WTO. Urbanization accelerated, and the growth of the middle class fueled demand for luxury goods, tourism, and better nutrition. The number of private cars in China went up from 1 million in 1992 to almost 10 million by 2002. Many people envisioned a hopeful future in which they could acquire new clothes, new luxuries, and new technology in the new millennium.

But the “many” did not include the 100 million people residing in the Northeast — roughly 8.5% of China’s total population as of 2000. By the 1990s, urban shrinkage, which is measured by sustained population loss, had already taken hold across 52 cities in the Northeast. And of the 68 cities across China whose populations diminished continuously into the 2010s, half were in this region. The regional birth rate has been trending lower than the national average for more than three decades, and net outmigration has become an increasing problem since 2000. In 1990, the Northeast represented 8.66% of the country’s population; by 2016, that proportion had dropped to 7.9%. The one-time cradle of China’s industrial development has become a place that many would rather not raise kids or live in, given the choice.

In the span of a decade, Chinese society simultaneously experienced rapid economic growth and extreme economic precarity. Individuals were offered transformative opportunities and faced catastrophic crises, all due to the same factors put in place by a select elite who generated the incredible promise and acute challenges modern China still faces. To many Americans watching AI reshape their economy, this narrative may sound familiar, though calls to regulate, pause, or stop the technology reflect a belief that the transformation can still be steered or stopped. That option did not exist for Chinese workers in the 1990s.

Painful, “rewarding” reform

For China’s policymakers, slowing development was never an option. A 1931 quote from Joseph Stalin — “落后就要挨打 (luohou jiu yao aida) or “those who fall behind get beaten” — that adapted by Mao Zedong in 1956 permeated society, serving as a cornerstone of high-level policy narratives. In China’s mnemonic practices, this phrase, linked to the idea that only development can sustain a nation’s independence, is the most significant lesson from the past, necessary to remember from China’s 20th-century history of war and colonization. “The reform is painful but rewarding,” wrote the state in 2012 in reference to the previous century.

At the turn of the century, then, the policy question was therefore not whether to reform; instead, it was how to make the transformation less painful. The government attempted to address the pain. In 1998, the state established re-employment Service Centers, which provided laid-off workers with living allowances, basic social security, and job training. The state taxation administration introduced tax incentives for businesses that hired displaced workers. Xiagang workers were entitled to tax exemptions, fee waivers, and preferential access to microloans when starting small businesses or seeking new employment. The Minimum Living Security System was established in 1999 to guarantee basic income for urban residents and expanded to rural areas in the 2000s. Higher education grew in 1999 and university attendance increased 600% in less than 10 years. This expansion was partially aimed at delaying China’s youth from entering the job market, thus leaving spaces for the re-employment of laid-off workers.

For some workers, these policies provided a bridge. But the scale of the problem overwhelmed the response. Funds were too small or simply did not arrive. When funds did arrive, they rarely reached the people they were meant for. In one case, one former deputy director of the city-level Development and Reform Commission — an institution responsible for implementing national economic policies — embezzled the subsidies of 556 xiagang workers.

Even as market reform and industrial upgrades brought new job opportunities, there were simply not enough: In 2004-2005, 24 million people entered the workforce, but only 9 million new roles were created. Even within these new jobs, there was a mismatch between supply and demand. The workers who had been laid off were predominantly in their forties and fifties with industrial skills, while the foreign companies entering China wanted fresh university graduates or young rural migrants who were willing to work for less. And though the expansion of higher education benefited many, it eventually produced young workers who were overqualified for many jobs, resulting in high youth unemployment that persists in China today. And much of the suffering was silently buried under cold numbers and grand policies.

In 2002, economist and writer Wu Xiaobo conducted fieldwork in Shenyang’s Tiexi district. Writing for the Financial Times China, he recorded stories from two families who had experienced layoffs. One husband biked his wife to the red light district for sex work in exchange for money for survival. In the other, the father jumped off of a building after his wife complained that they could not afford to buy their son sneakers for a school sports meet. Other accounts described families folding poison into dumplings, robbers and their victims begging each other to end the other’s suffering, and workers lying across railway tracks waiting for trains to hit them.

It may be hard to understand why people would resort to such extreme situations in the face of mere unemployment. But for many workers in the northeast, employment was everything. Before xiagang, most workers’ lives were organized around the danwei — the work unit that was not simply an employer but a total social world. The danwei provided housing, medical care, pensions, childcare, and entertainment. Colleagues were neighbors. People were born in the danwei clinic, went to danwei-sponsored schools, worked in danwei upon graduation, found partners through danwei-organized dates, and moved into danwei-sponsored dorms or housing. From birth to death, a worker’s life was closely linked to their danwei. In his 2004 book, sociologist Li Hanlin argues that danwei was not only a workplace but also a chosen lifestyle that provided a sense of reliance and an anchor of hope. It was a society without strangers, because people formed close bonds through everyday work and life. Danwei gave people social identity and legitimacy.

People in the Northeast therefore lost not only income, but their way of life, their sense of belonging to the small communities they had built around their work, and their dignity as socialist workers. In a society that for decades had told them workers were the masters of the nation, the sudden sense that they were surplus, inefficient, and unwanted imposed a burden that no severance payment could address. Many felt deceived when forced to sign labor contracts that stripped away their protections: “I believed in the government and the party. I relied on the enterprise for a living, and the enterprise also needed me for further development,” said one laid-off mining worker in rural Beijing. “I didn’t have the slightest idea that the enterprise would take advantage of me.” Others felt invisible when they were excluded from decisions that would determine the rest of their lives by an institution they had always called their larger family.

The fear and the frenzy

The paradox of the era was that as much of China’s population was losing jobs, an emerging group of poor people, predominantly in the southeastern coastal areas, was growing rich overnight. And because others were enjoying upward mobility, the ones left behind internalized Social Darwinist views that claimed that only lazy and useless workers had been laid off and that people who failed to find new jobs simply were not skilled or determined enough to do so.

In rural Liaoning, a northeastern province greatly impacted by xiagang, many people sought to migrate overseas for better opportunities. Local villagers explained to anthropologist Xiang Biao that they looked down on neighbors who could not find work overseas to earn big money. They wondered to themselves, “why have others gone overseas successfully but you can’t?” and assumed that those who stayed had failed because of individual shortcomings rather than structural forces. This view, which originated in northeast China, makes the fault of the layoff a problem with individual capabilities: When rapid stratification turned neighbours’ fates in opposite directions almost overnight, individual effort became the easiest explanation for diverging outcomes — a logic the state then reinforced by replacing collectivist language with individualistic discourses of self-improvement and personal advancement.

Most narratives of the period, even sympathetic ones, treat economic restructuring as a natural force, with individual adaptation as the only response. In 2002, a documentary about the Tiexi district depicted the marginal lives and struggles of xiagang workers in this once-vibrant industrial area. Lyu Xinyu, one of China’s most prominent scholars in the study of rural-urban inequities, interprets the documentary as a sad depiction of an inevitable historical event:

Today’s (2003) Tiexi District is nothing more than a replay of the decline of the traditional industrial Rust Belt in the American Midwest and the traditional industrial Ruhr area in Germany in the 1970s and 80s. It is the unfolding of a common historical rationality in different times and spaces, and we have no possibility of escaping the compulsion of this law. Industry, in a dialectical and historical sense, is an object of the natural laws of society.

If economic restructuring was an unstoppable force of nature, then the only possible response was to move with it before it moved without you. Xiang Biao diagnosed this as a “last bus” mentality: a collective fear that missing the opportunity to seize a piece of post-socialist accumulation meant missing everything. You either catch this bus towards success or be left out forever. It was a frenzy born not of greed or enthusiasm, but of the desperate realization that the old world was gone and the new one had no reserved seats. What began as a northeastern industrial experience has, amid decades of social change and competition, became a prevalent psychological structure spanning different socioeconomic classes and regions.

The state’s official rhetoric consistently reinforced this reading. In the 1990s, China needed marketization and reform of state-owned enterprises. These were, they said, inevitable moves to save the country from its economic crisis. China, under this logic, also needs urbanization, industrial upgrades, or AI integration, because history is irreversible and technological progress is inevitable. Describing major societal changes, the official language is always that one needs to “seize the new opportunities (抓住新机遇; zhuazhu xin jiyu)” and “ride the trend of the time (站在时代的风口上; zhan zai shidai de fengkou shang).” The rhetoric still prevails two decades later, as a top state newspaper wrote in 2019, “when the era discards you, it will not even say goodbye.”

The signal for individuals was clear: You had better catch the “last bus” to seize the fleeting opportunity. If you fail, no one, even the state, will back you up. This mentality undergirded China’s development at the turn of the century and prevails today. Whether it involves market, education, industrial, or technological reforms, people in China are frenetic about new things because they are always seeking the trend to follow. In Xiang’s words, “every bus is the last bus.”

In the late 1990s and early 2000s, learning English was the last bus. Globalization was the irreversible trend; only by learning English could Chinese people interact with the greater world. The state mandated English education as a core Gaokao subject and pushed it into primary schools in 2001, giving rise to cultural phenomena like “Crazy English“ (疯狂英语; fengkuang yingyu), wherein tens of thousands of people gathered in public stadiums to scream English phrases at the top of their lungs in a desperate collective bid for fluency. In the late 2010s, the mobile internet boom was the last bus. As tech giants like Alibaba and Tencent offered unmatched salaries in other industries, millions rushed to learn coding and enroll in computer science degrees in universities that were aggressively expanding computer science programs, only to find themselves facing a constantly decreasing employment rate.

In 2023, understanding AI was the last bus, and over 250 thousand people paid for rudimentary AI crash courses, terrified of being rendered obsolete overnight. In 2026, OpenClaw was the last bus, with thousands of people — retirees, white-collar workers, housewives — lining up outside tech company offices for engineers to install the agent directly onto their phones.

Underlying pessimism

Tomorrow morning, I guess the sun will be good
I want to clean myself up
Sell off everything old and broken
Oh, this will be so good
Come on, Pentium computer
Let them think on my behalf

明天一早, 我猜阳光会好
我要把自己打扫
把破旧的全部卖掉
哦这样多好
快来吧奔腾电脑
就让它们代替我来思考

– “New Boy,” Pu Shu, 1999

Today, the history of marketization is largely depicted in a rosy way. Chinese TV dramas — ranging from official historical fiction to romantic melodrama — celebrate people who rode the tide of the trend and raised themselves. The trauma of xiagang has found cultural expression only at the margin.: The so-called “Dongbei Renaissance” is a loose wave of literature, film, and dark comedy that has emerged from northeastern writers and directors since the 2010s and treats the rust belt’s collapse with a bleakness official culture cannot condone. Beyond that, the majority of the records of xiagang have been censored or simply left out.

But even if you burn the records, you cannot erase the wound. And no matter how much whitewash one applies to that period, the core mentality — seize the last bus or die — has become deeply ingrained. This persistent anxiety continues to intensify and spread whenever new, potentially transformative shifts occur in Chinese society. While not everyone successfully boards every “last bus,” the alternative of not trying to board at all is a social stigma. As Xiang Biao observed, there seems to be no way to live outside of competing and striving, even when it is unclear what exactly one is striving toward; quitting the race means facing utter failure. Even when the young generation claims to embrace “lying flat,” the pressure from the state, society, and even they themselves means that they actually do not give up at all.

This history offers a new perspective on the “AI enthusiasm” we are now seeing in China. Many are correct to point out that the enthusiasm arises from the top-down state discourse portraying technology as a redemption against the history of the “century of humiliation,” as well as people’s ground-up experience of benefits from rapid technology development in the past few decades. Technology is good because it makes the nation stronger. The lesson of how the late Qing government closed its door, missed the industrial revolution, and was defeated and humiliated by the Europeans and Japanese is a core section of the history education mandatory for every Chinese student. On the other hand,industrialization and digitization have made many people’s lives better, compressing what took the West decades into a single generation. China grew from no high-speed rail in 2003 to a 50,000km network in 2025, compared with 8,500km in the whole of the EU as of 2023, linking 97% of cities with populations of more than half a million; the society leapfrogged credit card infrastructure, going straight from cash to mobile payments in a transition that reached people who had never held a bank card.

However, these two elements also instill a profound sense of precarity. The desire to access the transformative benefits of technology is inseparable from the fear of being left behind. Citizens adopt cashless payments not only because of the convenience it offers, but also because of the penalty for not doing so: finding oneself unable to pay at most stores, locked out of basic services, and adrift in a banking system built for a phone screen. The same will be true for AI — or, at least, most Chinese people seem to believe so.

China’s culture of techno-optimism, analysts argue, may allow AI to be diffused and deployed at scale. Some analysts contrast China’s Star Trek techno-optimism, which some believe will allow AI to be more quickly deployed at scale, with the West’s Black Mirror mindset, wherein public anxiety about various AI risks stifles deployment. It is too easy, however, to draw a binary between the American and Chinese responses to AI, or to think that the Chinese public would be purely enthusiastic about a technology that will automate more jobs. It is true that Chinese respondents in some surveys likely have some genuine enthusiasm — particularly many who lived through and benefited from the market transformation of the 1990s, for whom technology has been a story of concrete improvement. However, enthusiasm and fear are not mutually exclusive. A person can genuinely believe some AI products are beneficial and feel they have no real choice but to adopt it; can welcome a technology because it seems useful while worried that not mastering the usefulness renders themselves obsolete. Most survey questions were too binary in design to shed light on which sentiment is driving the response, or a respondent’s ratio of enthusiasm to anxiety.

Today, some evidence-based “optimism” claims draw from the Chinese public’s extremely high responses like “AI products and services have more benefits than drawbacks”, how much one “trust AI,” or “willing to accept AI,” all of which cannot differentiate a net excitement of AI from the belief that AI is important, inevitable, and cannot be missed. Are AI products viewed positively because people really benefit from them, or are they simply thought to be so important, just like how learning English is “beneficial” in the sense that people believe the language means modernization and the future, even though in real life it may have little practical use? Asking “How much do you trust the technology?” is inherently ambiguous: does answering yes mean you trust AI as a technology, trust AI’s output, or trust that AI will bring opportunities that you cannot afford to miss? Furthermore, behind the 95% reponse of willingness to accept AI lies the 49% belief that AI will replace jobs. So while AI is viewed as a threat to job security, a possible coping mechanism is to rapidly accept and embrace it, because history has taught the Chinese that the only coping mechanism is to change oneself.

The mixture of enthusiasm and fear pulls on a tension that has emerged throughout China’s recent history — whether people believe a change will benefit society as whole or merely themselves as individuals. There is a difference between believing a technology is useful, beneficial, or necessary for society as a whole — that AI will become the fate of the nation, which one needs to work hard to adapt to — and trusting that the technology will automatically benefit individuals’ lives. Under the grand narrative today, Xiagang is acceptable, necessary, and has more benefits than drawbacks — for the nation-state more than for those workers laid off. “The 1998 SOE reforms were like major surgery. Without it, the patient would not have survived,” said economist Huihua Nie, implying that although xiagang was a painful process for some, Chinese society must endure this individual suffering for the collective good

When polled only three decades later, perhaps every respondent genuinely believes that AI is good for both society and for themselves. Or perhaps they see AI as another surgery necessary to survival, knowing full well that flesh will be cut away and discarded, but convinced that the pain borne by individuals — however devastating to them — is small against the benefits at large. The polls, as they are written, cannot distinguish between these narratives. .

Meanwhile, the reality suggests that there is no homogenous or unwavering optimism in AI among the Chinese public. For example, even when the state issued multiple warnings about OpenClaw security risks, people nevertheless rushed to install the agent on their personal phones and laptops. Behind the seemingly massive adoption of AI agent tools is not a population mobilized behind a coherent national AI strategy, but many individuals running blindly, supervised by a government that benefits from the momentum but cannot meaningfully control the direction. Resource waste, security vulnerabilities, scams, and market oversupply are the predictable outputs of a system running on fear as much as ambition. China’s AI enthusiasm is not as strategic an “advantage” as some may think, as the bottom-up fear can easily lead to a frenzy that is outside the top-down AI agenda.

This is, perhaps, a situation that one could simply dismiss as “AI hype” or “AI bubble” if it happened in the US, where some hawk AI classes, many try out every new AI product as they emerge, and some attend AI hackathons every week. But because it is happening in China, and because the American analysts themselves now treat domestic AI backlash as a strategic vulnerability, they’d rather believe the Chinese public is different, or the Chinese government has better leverage in a so-called “U.S.-China AI race” as they can engineer an optimistic public.

But can it?

In January 2026, Pu Shu’s “New Boy” was remade to “New Bot” by the state media, aiming to highlight how AI and robotics, just like Windows 98, can bring hope and the promise of a new and improved life. However, despite its eye-catching music video, the song did not become a hit. People continue to listen to the 1999 original, leaving comments lamenting that there will never again be an era of such optimism. What they are mourning, perhaps, is not AI’s failure to match Windows 98’s appeal. “I have never been able to accept that this is a purely cheerful song. The melancholy of being pushed into a new era is the real theme — pessimism hidden inside a melody that looks happy,” wrote one listener.

“向前走，你的路，猜猜未来会给你什么礼物 (xiang qian zou, ni de lu, caicai weilai hui gei ni shenme liwu) ,” sings Pu Shu in the outro of the song. “Walk forward, your road is ahead — guess what gift the future holds for you.” The gift, it turns out, is mandatory. You did not order it, you cannot return it, and the era will not wait while you decide if you want it.

subscribe to Zilan’s substack!

Want to do big things? Today we’re providing a guide of sorts. Joining me is Remco Zwetsloot of the Horizon Institute for Public Service and Kumar Garg of Renaissance Philanthropy.

We discuss:

• Why achieving goals in policy is more possible than most people think and that the real bottleneck is ambitious, mission-driven talent,

• How successful policymakers think differently — how they focus on outcomes over “portfolios,” learn the system deeply, and work backwards from impact,

• Why policymaking rewards immersion, sensemaking, and coalition-building more than raw technical or academic brilliance,

• The importance of peers, persistence, and “water on stone” stamina in sustaining long-term policy and public service careers,

• How writing, public ideas, and the “posting-to-policy” pipeline are democratizing access to influence in Washington.

Horizon recently launched Launchpad, a Substack on working in emerging tech policy with advice, explainers, and conversations like this one. If you enjoyed this conversation, you’ll probably like their other stuff as well.

Launchpad

Conversations and advice about working in emerging tech policy, from the Horizon Institute for Public Service.

Optimizing for Impact

Jordan Schneider: Kumar, what is RenPhil, and Remco, what is Horizon?

Kumar Garg: We help donors bet big on science and technology.

Remco Zwetsloot: And Horizon builds pipelines into public service for people working on emerging tech.

Jordan Schneider: Kumar, what do you want to tell the kids?

Kumar Garg: There’s a Tyler Cowen line about raising people’s ambitions that I love. The practical thing when I’m giving career advice is that people are very narrow in what they think career paths look like. They say, “Hey, I was looking around and I saw these jobs being listed. Which one should I apply for?” And I tell them, “I have never applied for a job that I have actually worked at.” I’m this far along, and I have invented some version of every job I’ve had. I got a fellowship by going to the government and saying, “If you gave me this fellowship, I could sit here. Do you want to hire me?” I’ve taken something where I was working for somebody and converted it into a job. I’ve started organizations. There are many ways to work out in the world.

The second part is what you actually want to work on. People worry about the burden of knowledge — how do you get to the frontier? That has not been my experience. You can get obsessed with a very technical topic, and pretty soon after talking to all the people and trying to figure out why that topic is stuck or what’s not getting worked on, you can be on the edge where the experts on that topic are saying, “That person’s really onto something. We should be doing more of that.” Your ability to go from not knowing something to the edge is actually quite high.

The real magic is whether you actually want to devote part of your career to working on that and trying to make progress. That takes time — learning how to get something into the National Defense Authorization Act, or how to get good at raising money around your ideas. These things take time. But doing big things is a lot more possible than people realize.

Jordan Schneider: How much latent capacity for big-thing-doing is out there, both from a “the world needs things” perspective and from a “there’s talent that just hasn’t had their horizons raised” perspective?

Kumar Garg: We’re always talent-blocked. We’re bottlenecked on talent on basically everything. The reason isn’t that we have an infinite set of problems. One of the conversations I have with donors goes like this — somebody might say, “Let’s do a white space analysis. Where’s the white space?” By that they mean there’s some space where everybody’s working, and another place where no one is working. The sad joke is it’s all white space. You get into these problems, and as you dig in, you very quickly figure out there’s a bunch of stuff that’s quite important and not getting worked on.

A recent example — in the past five years, there’s been a huge increase in the number of people who realize lead pollution is a really big deal. Maybe a quarter to a third of the global learning gap between rich countries and poor countries can be explained by lead pollution. When I started talking about this five or seven years ago, I’d get a nodding head — “Yeah, pollution’s a problem.” Then I’d ask, “How much money is being spent on this really big problem?” Eventually people looked into it. Globally, $10 million was being spent on lead remediation. How many people work on lead remediation globally full-time? Maybe 100. We’re talking about something that might have a trillion-dollar-plus lifetime impact. We underestimate how many really important things don’t have enough talented people working on them.

When the Lead Elimination Project came to Parth and I with their idea, I could tell they were onto something. They said, “We flew to a country, bought lead paint on the market, applied paint to paper and let it dry, took a sample, tested it for lead, and took it to the regulatory authorities saying, ‘Did you know paint is being sold with lead in it?’” The authorities were shocked. The paint suppliers were shocked. In multiple countries, that alone caused them to change the law. They were getting off plane flights, buying paint, and changing whether lead was being sold in the public market. This happened in 2023.

A week ago, I’m trying to buy fishing supplies for my son. I go to the tackle shop. I cannot find any weights that aren’t lead weights. I’m thinking, “I’ll have to order these on Amazon.” Even today, you cannot find non-leaded fishing weights in most places in the United States. The shop owners say, “They’re heavier and more useful.” Do I really want my kid using lead weights on fish he’s going to catch? We have blind spots everywhere. There’s lots of interesting stuff to be done. You just have to be a nerd about it and figure it out.

Remco Zwetsloot: There’s a funny story related to this. For the Policy Entrepreneurship Network conference — a community Kumar organizes along with Parth — there was swag, including a bag. The bag had lead in it. The label said there could be small residual amounts of lead in this bag.

Kumar Garg: Embarrassing.

Jordan Schneider: How else do people get stuck or blocked? Let’s get another story out of you.

Kumar Garg: Another way people get stuck is through who their peers are. I had a college friend call me up. I was working in policy, working in the White House. He said, “That’s all very impressive, but how much do you get paid?” He worked in finance. I said, “I’m on a fellowship salary. I’m clearing $40K, but I’m getting to do all this incredible work as a fellow in the government.” He said, “But why? If the work is important, why don’t they pay you? I don’t understand.” It did not compute to him. Eventually, I moved off the fellowship to a government salary, but it’s still not comparable. He was surrounded by a peer group where that’s how you kept score.

One of the important things if you’re going to do interesting, ambitious things is having people around you who value the striving, even when you haven’t gotten the win yet. We used to call this “water on stone.” What’s a thing you’ve been working on for many years where it looks like you’re not making progress? I still get emails from people saying, “I accomplished my water-on-stone. Finally, the crazy person in my way died or left government, and we’re going to get the win.” They email me because they know I appreciate how sometimes these things take time.

Whatever you want to do, if you’re not surrounding yourself with at least some other people who value that work, it’s very hard. Part of the reason for the Policy Entrepreneurship Network is that we celebrate nerds who say, “I’ve been obsessively working on how to make the organ donation system work. Here are the 17 different ways we’re trying to reform OPOs, and here are the 14 ways the lobbyists killed us. Then we made a comeback and found the right person in the government to get this rule changed.” All the back and forth, the Erin Brockovich of it all. That person is also saying, “I can’t get anyone to fund this work. It’s crazy.” But the ROI on their effort is so high.

The work requires stamina and engagement. Surround yourself with people who can feel the win and feel the work alongside you. People sometimes make the mistake of not finding peers to do it with.

Jordan Schneider: Remco, why don’t you introduce the Horizon Fellowship? I’m curious what have been the indicators of success, impact, and failure from a selection, personality, or mindset perspective, and how that’s changed how you think about filling your slots.

Remco Zwetsloot: The Horizon Institute for Public Service exists to build government capacity in emerging tech. We focus on AI first and foremost, and also on biotech and other areas. We run several programs to build that capacity, all meant to create communities of people who understand the technology deeply and want to work in careers of public service thinking about policy problems.

The fellowship is our first and biggest program. It places people in government for up to two years, or in think tanks, in placements focused on emerging tech issues. Similar to the way Kumar mentioned getting into government, these fellowships are a pretty common model. We were the first to focus on AI and emerging tech specifically.

It’s interdisciplinary. We have machine learning PhDs and deep technical experts, but these are interdisciplinary problems, so we also have lawyers and others who bring relevant expertise. We really try to select for public service motivation and ambition. AI and other fields will have widespread impacts, and we need people in government who understand the technology, are thinking deeply about where it might go, and try to do something good for the public and work effectively for the offices in which they serve.

What’s really required is a combination of ambition and humility — a thing many people in the Policy Entrepreneurship Network have. We need to do big things, and there are many big wins to pursue. At the same time, you’re working with people who think differently from you, working on behalf of elected representatives who set the direction. That’s what we should aim for in a democratic society. Your role as a staffer or fellow isn’t necessarily to make the world the way you want it to be, even if you pick an office whose mission you care about. Selecting for that combination of ambition and humility is something we’ve iterated on over the years.

Kumar Garg: One thing I felt working in government — I worked in a science office, and there was no good correlation between how good of a scientist you were and how good you were at policymaking. You can get pretty far being dictatorial in science — “I run this lab, I’ve got this system.” But being successful in government is sensemaking. Why is this person not going to go along with this idea? What are their incentives? What’s their blocker? Why do they want to show up? You have to develop that extra sense of perception over time. How do you bring people along?

What’s smart about the fellowship model is that some of this is just easier through immersion. Two months after somebody has started a fellowship, they sound totally different about the questions they’re asking me than in the summer before they went in. Once you’re in there, you realize nobody knows anything, but you have to create this document in two hours. Then the document comes out of somebody very important’s mouth as what they think. That two hours of work really matters. You start to realize how compressed people’s time and attention are. You realize how much you have to figure out why people may or may not be into an idea. You have to understand how things actually get to the finish line.

If you’re a researcher and you spend a year in policymaking roles, you’ll become a totally different researcher when you go back to academia. Immersion is very powerful. You understand much more intuitively the incentives of these systems.

Jordan Schneider: How does that track onto the humility-versus-ambition axis?

Kumar Garg: It gets at what Remco was saying. You have to be obsessed with winning — with thinking, “This is really important and I really want it to happen.” A lot of times, people in government fall into this idea of “I own this portfolio.” I don’t like the word “portfolio.” A portfolio is a fancy way of saying this is the range of topics whatever seat I’m in has equities in. It’s better to have goals — “I want to move from here to here.”

Being ambitious about things you want to move is important. The catch is that to pull that off, you have to be a student of the system. When an executive order came out, or the budget came out, I would ask people, “How did this idea make it into the budget?” They’d say, “There’s this budget examiner within OMB. They write the first draft.” I’d say, “Let me go get coffee with the budget examiner.” That budget examiner would tell me something interesting — “I start in the spring building out what’s going to be in the initial budget I send to the agency.” I’d ask, “You’re starting now?” They’d say, “Yes. Are there any questions you’d like me to ask the agency?” Understanding that the budget process starts the day after — or even before — the president’s budget came out for the next year is not obvious because you might think the budget happens in November when it goes up to the president’s desk. Curiosity, and then putting that curiosity to work, is very important.

Remco Zwetsloot: The focus on results and outcomes in the world distinguishes some people in policy and government from others. There was a guy we were advising at Horizon, a tech entrepreneur interested in making the jump into public service and policy work. We told him, “Someone with your background has relevant skill sets. You should consider doing this. You could add a ton of value.” We sent him some of the RenPhil writings on policy entrepreneurship as a mindset to deploy. He said, “Why is this a concept? This is just the way of doing things. You have an outcome you want in the world, then you work backward to what’s needed. You can call it policy entrepreneurship, but that’s just the way you do business. It doesn’t need this terminology or specialness.”

Three months after he made the jump to DC, he came back and said, “I get it. I’m in so many meetings here in DC, or I talk to people, and they have a portfolio or things they’re working on, but they don’t have an outcome in mind. They don’t have a way they’re actively trying to change the world. They’re not working backward from that to what’s needed.” That’s fundamentally a different mindset. A lot of people on the outside — especially folks who have that outcome-oriented mindset — don’t realize it’s a choice, that it’s not true across the board.

Jordan Schneider: It’s that word “entrepreneurship.” If you’re in a market economy and your business isn’t doing novel or differentiated things, you’ll lose market share, make less money, fire people, and eventually shut down. There’s a whole universe of media, books, and podcasts that talk you through different ways to grow a business or make more money. As you were saying, Kumar, in academia, think tankdom, and stafferdom, there’s no P&L. There’s no way to keep score the way your college frenemy could look at his bonus at the end of the year and say, “I did a good job because I did this many deals.”

Most people go into government or policy because they want to make a difference. But it seems really easy to go from making a difference to treading water, just because of the way the system is set up and the fact that these are giant organizations where one CEO can’t call the shots.

Kumar Garg: I used to play this game with my team. I’d name all the White House offices and ask them to tell me what each does and what winning looks like for them. Most of my people came from a research background. “What do you think the Office of Presidential Correspondence does?” Millions of Americans write letters to the president, and the office writes responses. They pick out a set of letters every day for the president to read. They consider their job really important, and sometimes policy comes out of that.

What does speechwriting do? What does the advance team do? What does the Office of Public Engagement do? What about comms? Each is its own little tribe with its own internal logic and KPIs.

The Office of Public Engagement does something called a fly-in. Sixty mayors from around the country are flown in to the White House to interact with White House aides. I’d ask, “What’s your goal with this fly-in?” They’d say, “The goal is the fly-in. We’re bringing these mayors to the White House. That’s the goal.” Then I’d be the policy entrepreneur and say, “There are a bunch of important mayors who are going to be here. Can I pitch them on things?” They’d say, “We need people to talk to them. We need them to have a good day at the White House.” I’d get the list of who was coming and set up what we were going to pitch them on. Or CEOs were coming through the building. Their KPI was just whether important people who want a relationship with the president had a successful visit.

Same thing with speechwriting. Tom taught me speechwriters don’t want you to edit their words — that’s their job, the words. What do they want from us policy nerds? The factoid. What’s the amazing fact you can stick into the speech that sells the point? I’d create lists of amazing factoids, and speechwriting would say, “You got any more of those?” When the State of the Union came around, I’d get an email — “You’re always good with those factoids. Got any interesting ones for us?”

With comms, what do they think about? The visual. I’d be the crazy person who walked into the meeting with the comms team, and before I showed them the policy idea, I’d show them the photo. “The president is going to stand in front of this massive wind turbine.” They’d say, ”Whatever it is, that’s a good idea. Let’s do that.”

Everyone has their own structure. The social media team, others — they all have their own. Different players in the system have different KPIs. As the person trying to get policy work done, you have to think about how to get those other teams to be into what you’re trying to advance, versus expecting them to nerd out with you on why we should change the organ procurement system or some energy policy.

Remco Zwetsloot: One interesting tension when we teach fellows or talk about whether someone is a good fit for DC — different people need to hear almost the opposite thing.

Some people are so attached to a certain outcome and think it’s so obvious that when you get into a room and explain your idea, the other person is going to get on board. As Kumar said, you have to spend time understanding people’s incentives and worldviews to bring them along. To that person, you have to say, “You’ve got the ambition right, but you’ve got to learn how the system works. Be patient. Be humble about things you don’t yet know about how things work. You might want to iterate on your idea and compromise.”

Other people have the exact opposite problem. They come in saying, “I want to be a public servant. I’m here to do good. Other people might tell me what that is. I expect to come into the office, be assigned a thing, and do it.” Often they come into a space where there’s no clear agenda. You can spend two years in DC just responding to incoming, doing a thing here and a thing there. At the end, maybe you’ve contributed, but you haven’t really changed anything. For that person, you have to push much harder on what is the thing you want to be different two years from now? What does success look like if you look back on your experience in two or five years? You should think hard about that. Two people drawn to policy or public service, but they need to hear almost the exact opposite message about what they’ll need to do once they get to DC.

Kumar Garg: One other dynamic — there are a bunch of jobs in government that are firefighting jobs. You can be in a national security role and you’re the person who has to get up to speed on something that happened in the world in the middle of the night so everyone else can be briefed on it. The more proximate you are — especially to the president — the more the things of the day dominate your incoming. You have to get really good at thinking about goal development before being in a role, so you can drive on it.

I always got the question: “Why not move to the National Economic Council, the National Security Council, or another White House office, in a more premier spot with more daily interaction with the president?” I’d tell people that’s a double-edged sword. The people who get daily interaction with the president are getting handed, “We’re about to have a strike and the airports might close. Your job is to make sure that doesn’t happen today.” You might have other goals for the day, but that’s not your goal anymore.

The people who are able to be more proximate while still retaining some agency are underrated. That’s the role of the policy entrepreneur outside government. But also realize that some principals you’re staffing are spending 1% of their time on their passion project to fix the agency, even though if you’d interviewed them before they took the job, they would have said that’s their main thing. Understanding how much firefighting happens, and how to put that to work to advance your ideas in well-formed proposals, is a big part of what to navigate.

Jordan Schneider: I remember having this fantasy. This is how embarrassing I am. My fantasy was that — I think this was Jeremy Pollack or someone — just got assigned the Iraq brief in 1999. I was thinking it would be really nice if I just showed up at the CIA and they said, “All right, Jordan. Bulgarian tanks. You’re going to be the Bulgarian tank guy.” Then the whole world falls away and you can focus on your one thing. You’ll get really good at your one thing. It’s like doing a PhD — you’re just sort of focused, and you can own it. Maybe it’ll blow up and be the most important thing in the world, but at least you’ll be the master of your domain.

There are people for whom that works. But you don’t stumble upon the lead poisoning that’s getting half the planet dumber than it should be without the ability and mindset to do more of the explore as opposed to just the exploit. That’s a hard thing, especially when you’re young and what you’re reading are history books about secretaries of state, national security advisers, presidents, and generals. There aren’t movies and there’s not a cultural universe for someone who’s going to find this nice thing and fix it for everyone, or do some policy entrepreneurship dirty work that’s actually 100x impact.

And by the way, the value over replacement — whoever else would have been in that Bulgarian tanks job probably could have done a better job than me, or 90% as good. There’s so much impact alpha in finding which topic is going to be your hobby horse, even if you do end up in one of those more firefighting, reactionary “the senator needs to learn about this thing” roles. Learning how to pick your spots, and then picking them, is important.

Kumar Garg: The important part about how taxed senior people are, and how much the jobs feel like firefighting — Tim Geithner had this great line. He’d ask his team before a meeting started, “Is this a ’we care’ meeting or a ’we decide’ meeting?” There are things in government where nobody has a good answer, but you do the meeting to show you’re on it. You assemble and signal you’re thinking about it. Then there are actual decisions — are we going to spend the money on this or that? Are we partnering or not? A decent number of meetings are “we care” — just signaling engagement. One of your jobs is to tell the difference, because they look the same.

The value of doing the exploratory work — the explore-exploit, going out to find ideas — whether you’re an outside policy entrepreneur or the young fellow in the office who can do the work, mature the idea, and hand it to the right person, is very high. It’s why people say, “Why is DC run with all these 20-somethings? The chief of staff is 30. How does that happen?” There’s a huge amount of leveling up you can do if you use those roles to find those things and do them. It also means you can build a network of those people on the outside. When you only have a fraction of your time, you can call them and say, “I might be able to push on this, but I need you to do all the thinking and send me a document without much context.”

Remco Zwetsloot: There’s a certain type of person, especially folks coming from academia, who think, “I really want to work in policy and public service. I want to contribute, but I need to understand my area just a little bit better before I make the jump.” This is a blocker for people. “I need to know the full answer to what should happen with China policy before I go and try to get a job where my task is to say what China policy should be.”

People often don’t realize, first, that it’s very hard to study that question from the outside. As Kumar said, you sometimes need to be in the system to even know what the relevant research and questions are. Second — I’m a PhD dropout, a former political scientist, and I still love my 2x2s. One of my favorite 2x2s — on one axis, unconscious versus conscious and on the other, incompetence versus competence. Most people start out unconsciously incompetent. The first part of the learning journey is becoming consciously incompetent. Then you become consciously competent. The journey culminates in being unconsciously competent.

People really neglect the importance of being consciously incompetent. A lot of experts don’t know all the different things they need to know to have the solution for AI policy, for example. It’s just too complicated. If you’re not in DC yet, you don’t know all the ways you need to think about it. But you can know enough about AI to very quickly know what knowledge gaps you need to fill to say something about open-source versus closed-source AI models, or what China is doing in AI.

One of my colleagues, who was a fellow on the Hill, had a nice saying: “Your job is not to be the expert. Your job is to mobilize expertise.” That is your job as a staffer. To do that well, you need to be consciously incompetent — humble enough to know where your gaps are, then entrepreneurial enough to fill them, sometimes on two hours’ notice, sometimes on two days’. That’s a really neglected skill set. It lowers the bar for where someone needs to be to make a contribution in DC. Someone who wants to be the world’s expert on Bulgarian tanks might think, “I just need to read that extra book before I can really conclude something or jump into this field.” Lower your standards. You probably can contribute so much more than you think just by being aware of the gaps and leaning in early.

Kumar Garg: One question I have is — Jordan, you’ve talked about the posting-to-policy pipeline. How ideas now make it into policymakers’ heads is changing. How does that intersect with the “you have to be in there learning all the internal mechanisms” model? That system was certainly not as present when I first showed up in government in 2009. It’s become way more present.

One thing it shows is that we still live in a real deficit of clean ideas. I always used to say, when we were sitting around trying to come up with State of the Union ideas, “Why don’t I have a book from each think tank that says, ‘Here’s everything we wrote in the last year, formulated as a State of the Union idea. Here’s the sentence the president would say. Here’s the logic model of the policy proposal. Here’s a link to all the appendices so you can make it bigger or smaller. Here are the phone numbers of the experts you’d call.’” Instead, I’d be hunting around, “Has anyone written on this? Is there a paper?” The president gives this speech every year, and the fact sheets already exist.

So part of it is understanding the clarity of what a good idea is, and answering the questions of here’s what needs to happen, here’s why it needs to happen, here’s the button. Whether it’s eliminating the double staircase requirement, which would allow more construction — that’s a policy change a state or city could pass if they care about more housing. The policy entrepreneurship of people going in and serving, and just reminding everybody — there are a lot of documents that get created in policy and not that many ideas.

Remco Zwetsloot: Jordan, you’ve also talked about writing as a way to figure out what you actually believe. Say more about that?

Jordan Schneider: We’ve talked a lot in this show about the staffer path, where you have to subordinate a lot of your work to what the principal is doing — an elected representative, an assistant secretary, whoever. There’s a lot of power and influence you can have from that. But there’s an aspect that turns into Office Space, where you are not wholly yourself. You’re a vessel for someone else’s ideas and ambitions. You’re constrained by their pressures.

For some people, there’s something both intimidating and liberating about being forced to put on paper — or a Substack draft — what change you actually want to see in the world. Remco, earlier you talked about folks who applied to your program saying, “I want to be a public servant. I want to work on the NSC.” That’s something I’ve heard from a ton of highly educated 20-year-olds. It’s a failure state. But it’s very hard to look at a piece of paper, fill it with 2,000 words of your thoughts, and not get to something past “I want to be a public servant” or “I want to work on the NSC.”

That act of self-reflection that comes through writing is really important. There’s a whole second part about to what extent writing in public is important to get things done in the world. But the introspection that goes along with the writing process is almost the right place to start, and why having writing you’re only doing for yourself is important. Kumar?

Kumar Garg: I agree. One interesting trend that I’ve seen is the individual doer is getting a lot more traction in different formats. In media, you’d think about this as the individual writer. It used to be that what made you important as a writer was who you wrote for — “I write for Time magazine, I work for this.” The idea of the individual writer having their own brand, voice, and analysis — from Ben Thompson on — became much more of a thing.

At Renaissance, we try to think about it as the fund leader. You don’t need to go work for a foundation as a program officer. You can lead a fund, raise the capital, and deploy the work. Similarly, the idea of a public intellectual had this imprecision — a public intellectual writes books, is an expert, writes essays, sometimes writes a New York Times op-ed, is an authority. That too is getting democratized. You can start obsessing about a topic and writing about it consistently and cleanly. Other people who are experts on that topic can say, “This is actually pretty good. There’s a lot here.” They can validate it. Then you can be encouraged to keep working on it. That can open up other career paths, including terms of service in government and the opportunity to affect things.

Writing has an agenda-setting quality if you want it to. You’re starting to see that democratization happen.

The piece I’d push on is one of my favorite conversations to have with folks who have become really excellent writers — what role do they want to play in taking their insights and converting them into insights policymakers can use? I said this to Niko at Asimov: “You’ve got a bunch of interesting stuff. Some of these ideas would be really interesting if you or someone else then said, ‘Here’s the way NIH should be operationalizing these insights in their grant-making.’” That doesn’t have to be Niko’s job, but the writer can have a big role in operationalizing those ideas. They might do that themselves, or they could be aware that there’s an opportunity.

Remco Zwetsloot: One of my favorite examples is Thomas Hochman. For anyone interested in energy policy, you may have read his stuff. He’s at the Foundation for American Innovation and wrote a great Substack about one year in policy — what he learned. The public writing is a big piece of it. He did an impressive job building his profile.

Then there’s the follow-on work. Public writing is almost lead generation. It gets you into a meeting, gets you outreach or interest from folks, and then you need to do follow-on work. That follow-on work often ends up not being public and gets more into the traditional policy entrepreneur method. It democratizes this kind of work, and I think it’s super exciting. People who feel naturally drawn to posting-to-policy work should absolutely lean into it.

Kumar Garg: That second part is super important. Some people get so wedded to the public persona side that they don’t want to take the hit of doing the secret-Congress work — where policymakers call you up, ask you for ideas, you give them input, but you don’t get to talk about it. Some people are wedded to “everything has to be brand-enhancing.” Ideally you can do it in a way that allows your ideas to travel, and you’re smart enough to realize that to get the idea to the finish point, you’ll have to have different ways of interacting with decision-makers. People leave alpha on the floor when everything has to be public.

One question for Remco — you guys have been putting out a bunch of guides on how people navigate this. I get lots of referrals — “This person is thinking about philanthropy or policy. They’re very technical, very smart. They should figure this out.” If you’ve built a startup, know a lot about a particular technical area, and are curious about larger systems-level knobs you want to turn, what would be on your list of resources to check out? Certainly, I’d get on the phone with them, but what would you direct them to?

Remco Zwetsloot: For us, we created a website called emergingtechpolicy.org for people interested in emerging tech policy. Anyone listening interested in that field — highly recommend it.

It was a starting place because we kept finding ourselves repeating the same things in conversation. As Jordan would say, if you find yourself repeating something three or five times, write it down and put it on the internet. You can reach so many more people that way. The people who get connected to us aren’t a representative sample of everyone who should be in DC and in policy conversations. So emergingtechpolicy.org has guides — if you’re new to policy, what’s a think tank? What’s it like to work in Congress? What are different federal agencies doing on AI?

If you’re new and not sure which type of institution or job is good for you — a question a lot of people face — “I want to have an impact. I think government’s important, but I love reading and writing, or this kind of work. I don’t know where I’d plug in because I don’t understand DC enough” — that’s a great starting point.

Very soon after that, you want to meet peers and chat with people similar to you who have made the jump into policy or are thinking about the same problems. Start with reading, but very soon after, come to DC for a weekend visit. We have a guide on making the most of a weekend trip if you have the resources. We host events — people can monitor our website. A weekend workshop is one format we offer. You don’t have to feel ready for a fellowship, but you can come and check it out briefly.

The human element of seeing other people like you in this world matters. We try to get fancy speakers, but often the most important people to talk to are those just one or two years ahead of you in the journey. They can be the most useful. Senior people often have the curse of knowledge — the unconsciously competent quadrant. They don’t remember what it was like to be in your shoes and might give advice that’s no longer actionable or relevant. People just a year or two ahead are often the best mentors and guides.

We try to serve as many people as possible. You can sign up for career advice on our website. We get more applications than we can process, so we can’t do one-on-one calls with everyone, but the events are more scalable. There’s also a list of fellowships other than the Horizon Fellowship on the website. Hopefully soon, Jordan, we’ll have a China-focused workshop. We have AI and national security workshops, bio workshops. People listening with those interests will find something that suits them.

Jordan Schneider: Amazing. Kumar, what do you want to shout out, besides taking lead out of the planet? What should people give their billions to or work on next?

Kumar Garg: Technical people trying to figure out where to have the most impact can benefit a lot from seeing what’s out there. At Renaissance Philanthropy, we’re putting out lots of interesting, different ways to have impact. We’re building programs all the time. Click around and read — us, Convergent Research, Horizon. There’s a bunch of new organizations that have appeared in the past five to ten years pushing on how to take technical expertise and use it to agenda-set on really important outcomes. Read around. It’s both inspiring and — what all these organizations would tell you — we need more help. Reach out and raise your hand to either help build a program or support one.

We can coach you up on how to talk to the money side. That’s just a stepladder. Using your passion, ambition, and technical depth against these hard problems that aren’t just “what’s the next startup” can be a really powerful way to contribute.

Remco Zwetsloot: If listeners take one thing away from this conversation, I hope it’s Kumar’s earlier message — this is fundamentally talent-constrained work. I could not name you a problem where I don’t think part of the solution is “many, many more people should work on it.” There are complicated “how” questions depending on your personality and personal constraints. But I can guarantee that for someone trying to do good and thinking about science, technology, and China-related topics, there’s so much impact you can have. People in jobs that don’t feel aligned with their ultimate mission in life should think strongly about how to make the pivot in the next couple of years. A lot is changing in the world, and there’s so much need.

Jordan Schneider: Remco, Kumar, thanks so much for coming on ChinaTalk.

Lucas Fluegel and Nick Corvino team up to tackle Chinese biotech. Lucas is a visiting scholar at the Carnegie Endowment for International Peace, where he explores biotech and biosecurity policy. He did his Ph.D. research in biochemistry and bacterial genomics at the Scripps Research Institute.

China wants to be the world’s biotech superpower. But to understand how it got here, it’s best to start with its crown jewel: the WuXi companies.

The WuXi companies are the dominant biotech services consortium in China and have become the lightning rod of U.S. political wrath, most notably as an early target of the BIOSECURE Act.

When we say “WuXi,” we don’t just mean WuXi AppTec. Although this family of companies is often spoken about as if it were a single company, in reality, it is a group of companies comprised of WuXi AppTec (药明康德), WuXi Biologics (药明生物), and a set of tightly integrated businesses, all more or less under the same leadership but dispersed throughout the industry. Together, they are stronger than the sum of their parts, and form what we envision as the Empire of WuXi (hereafter just “Wuxi”).

The TSMC analogy is tempting, since just as TSMC manufactures chips for companies like NVIDIA and AMD, WuXi, instead of discovering and commercializing its own blockbuster drugs, it provides the services (chemistry, testing, manufacturing) that allow others to do so. And both have the ability to gut-punch the global economy if their employees stop coming to work.

But AI analogies, tempting as they are, can do more harm than good. TSMC sits at a true chokepoint, with essentially no major rivals. If you want cutting-edge chips, you go through Taiwan. But WuXi does not monopolize a single irreplaceable step in the biotech supply chain. In fact, it has strong competitors both in China and globally.

WuXi AppTec and WuXi Biologics are the third- and fifth- largest contract development and manufacturing organizations (CDMOs) in the world by revenue. The remainder of the top ten are all based in U.S. partner nations, including the top two of Lonza (a Swiss company) and Catalent (a U.S. company). So, if there are plenty of alternative companies in U.S.-aligned nations, why is WuXi such a bogeyman for the U.S.?

In the same way that China’s rare earth stranglehold matters because of where those minerals sit in critical supply chains, WuXi, with its unique corporate structure, is embedded at many layers of the biostack. It has accumulated a structural indispensability that is harder to replace than a single dominant manufacturer would be.

A 2024 survey by the Biotechnology Innovation Organization estimates that 79% of US biopharma companies have at least one contract with a Chinese CDMO or CMO. WuXi AppTec alone is estimated to be involved in roughly a quarter of all drugs used in the United States (according to WuXi). And an estimated 65% of WuXi AppTec’s total revenue comes from U.S.-based clients.

Even if the U.S. and its allies lead in certain sectors of biotech, the growing recognition that WuXi has embedded itself throughout the supply chain has raised concern about systemic dependency and the leverage that comes with it.

The U.S doesn’t have an easy way to address this. China’s specific advantages in biotech look less like control over a single node and more like what it achieved with its manufacturing sector. It is about process expertise, cost efficiency, labor and talent, and deep integration into global supply chains — perhaps more like BYD’s success in the EV sector. These are not easily reducible to export-controllable chokepoints.

The biotech landscape is much more diffuse than AI. And yet, perhaps because of the TSMC analogies, Washington has increasingly tried to map its AI playbook onto biotech, with early versions of the BIOSECURE Act explicitly targeting WuXi as it would a company like Huawei.

We’ll get to the geopolitics at the end, but let’s first explore where WuXi came from and why they are so unique, before returning to how U.S. policymakers might approach the emergence of Chinese biotechs.

The Origins of WuXi: A Chinese–American(?) Story

The seeds of the WuXi empire were planted at a moment when it was relatively easy to build companies that straddled the U.S. and China.

Wuxi’s founder, Li Ge (李革), is emblematic of a particular early-2000s generation. Educated at Peking University, he earned his Ph.D. in organic chemistry from Columbia University and went on to become a founding scientist at Pharmacopeia, a U.S. biotech built around combinatorial chemistry.1 By the late 1990s, Li was fully embedded in the American biotech world, becoming a naturalized U.S. citizen. He is also very charismatic and speaks fluent English, meaning you’d often see him on TV segments talking to Western reporters:

And yet, like many in that cohort of returnees — the so-called “sea turtles” (海归) — he felt pulled back to China.

Around 2000, during business trips back to China, Li noticed something that is fairly obvious in retrospect but was underexploited at the time. China had a large pool of well-trained, low-cost chemists, while Western pharma companies were steadily increasing their appetite for outsourced R&D, driven by the rising cost and complexity of drug development. Bringing a new drug to market was getting more expensive as the low-hanging fruit had already been picked, older blockbuster drugs were losing patent protection, and the revenue that funded new research was starting to dry up. Outsourcing was the pressure valve, letting companies chase more drug candidates without expanding their own overhead. At the same time, China’s entry into the WTO and improving IP protections were making it newly viable to plug into the global pharmaceutical system. As Li later put it:

“Around 2000, as China prepared to join the World Trade Organization, intellectual property protection in the Chinese pharmaceutical industry significantly improved. I realized that Chinese pharmaceutical companies definitely needed to develop new drugs.”

He founded WuXi PharmaTech in 2000 with his wife, Zhao Ning (赵宁). Pharmacopeia, his former U.S. employer, became its first client.

From the beginning, WuXi PharmaTech was built as a cross-border company. It served Western customers, adopted international standards, and quickly oriented itself toward global markets. In 2007, it listed on the New York Stock Exchange, becoming one of the first Chinese biopharmaceutical companies to do so. However, WuXi PharmaTech later restructured, delisting from the NYSE in 2015 before relisting WuXi AppTec on the Shanghai Stock Exchange and Hong Kong Stock Exchange in 2018, alongside a separate Hong Kong listing for WuXi Biologics (药明生物) in 2017 and, more recently, WuXi XDC (药明合联).2 Wuxi made a series of correct bets on when to embrace the Chinese and American markets, respectively. Even today, although transparent data post-BIOSECURE is scarce, an estimated two-thirds of WuXi’s revenue comes from U.S.-based customers.

A key inflection point for WuXi is the 2015 reform of China’s drug review and approval system. By decoupling drug approval from manufacturing and encouraging outsourced production, the reforms accelerated a feedback loop: more innovative drugs → more R&D → more outsourcing → more innovative drugs, and so on. WuXi expanded aggressively to meet that demand and become the titan it is today, including earlier moves like its 2008 acquisition of a U.S.-based AppTec business, which gave it both new capabilities and a physical foothold in the American market (and the name of its most famous company, WuXi AppTec).

WuXi was not alone in embodying this Chinese-American model. Asymchem (凯莱英) was founded by a Western-trained Chinese scientist who returned to Tianjin and built a contract services platform. Porton (博腾), based in Chongqing, likewise evolved into an internationally oriented pharma services company with a large U.S. footprint.

For years, this dual positioning was an asset. The intertwinement of the U.S. and Chinese biotech systems was not accidental but foundational to WuXi’s rise. Western pharma outsourced to China for cost and scale; Chinese firms like WuXi grew by serving those needs. You could argue that this was exactly the outcome the U.S. wanted before it realized how powerful China would become.

That equilibrium has since come under strain. In early 2024, after being named in the initial BIOSECURE Act proposals, WuXi’s stock plunged sharply, wiping out tens of billions in market value in a matter of days. Although some of those losses have since been partially recovered, WuXi is now a target of the U.S., and its future is highly precarious.

A generation of Chinese biotech companies emerged from this earlier era of integration, commercializing Western training and global demand through China’s industrial base. But WuXi remains the most internationally salient and successful of them all.

Why?

What Makes WuXi So Good?

Li’s vision for WuXi’s role in the pharma business ecosystem was explicit from early on. WuXi was not meant to be a traditional drug company, but an enabling platform for global innovators. Rather than designing drugs, they would build the infrastructure needed to quickly find and develop them. The novelty of this business model was not simply exploiting wage arbitrage — U.S. and European pharmaceutical companies already knew how to outsource chemistry. Instead, Li’s key insight was to reframe the role of contract R&D in the drug development process.

Traditionally, outsourcing drug companies would partner with different contractors for each step of drug development. WuXi provided an enticing alternative. Instead of contracting one company to test the initial drug, another to optimize its potency, and another to manufacture it at commercial scale, drug companies could work with WuXi through the entire pipeline.

Li would later define this approach as an “open-access platform” (开放式平台). Unlike more siloed competitors, WuXi was committed to “following the molecule” as it progressed from the research laboratory to regulatory approval and commercialization. This business model would later be codified as a “contract research, development, and manufacturing organization” (CRDMO) and copied by other companies.

This approach is a win-win for both parties. For the drug developer, it minimizes the need to switch between different corporate ecosystems, eliminating the inefficiency of juggling multiple contracts and ensuring each partner is up-to-speed. For WuXi, it incentivizes customers to stay “stuck” to their services for years, leading to predictable business and access to the revenue scaling that occurs as the drug progresses towards commercialization. Given the immense uncertainty involved in pharmaceutical development, this level of stability for provider and customer is extremely attractive.

WuXi doubles down on this model by targeting a “long tail” of biotech customers. Rather than limiting themselves to massive deals with the pharmaceutical giants, they target many small- and medium-sized firms. With more limited resources, these small companies benefit particularly from the cost efficiency of WuXi’s end-to-end services, which then locks them into the pipeline. Their sheer number and diversity also diffuse the risk of major damage from any one customer pulling out. Furthermore, research by consultancy firms has shown that these smaller companies tend to produce more innovative drug leads than their big pharma counterparts. WuXi is therefore able to link itself to these disruptive — and therefore lucrative — products early on. These strategic decisions have given WuXi a “strong, diverse, and sticky customer base.”

Does WuXi have a technical moat?

Importantly, however, these technologies didn’t originate from WuXi labs. So, unlike the TSMC analogy, there is not a WuXi-specific technological moat around their services. Instead, WuXi’s biggest competitive advantage lies in their integration across the technology stack.

Indeed, a quick scan of their advertised capabilities reads like a catalog of the hottest frontier capabilities in drug development. A company can use WuXi’s DNA-encoded libraries to quickly scan for usefully potent molecules, including with options to avoid sharing IP. Biomanufacturing for complex biologics has been standardized and optimized, with new methods being deployed to further boost productivity at scale. In-house expertise in finicky drug types like peptides (including GLP-1s), antibody-drug conjugates (an expanding class of mainly anticancer drugs), and monoclonal antibodies (of COVID-19 treatment fame) expands the customer base they can serve. And, of course, AI and automation are being deployed throughout the pipeline.

Most biotech and pharmaceutical firms lack the resources and expertise to deploy these advanced biotechnologies in-house. But WuXi’s comprehensive and integrated platform offers them the access and support needed to compete at the technological frontier. A positive feedback loop is born as WuXi aggressively invests in further optimization and expansion, and the platform becomes even more attractive to the next wave of ambitious firms.

An excellent example of WuXi’s ability to adopt and deploy new technologies is their development of the “scale out” paradigm for manufacturing biologic drugs.

Biomanufacturing – the use of a living system or its parts to produce a good – is central to many of WuXi’s higher-end pharmaceutical manufacturing processes. The key step in a biomanufacturing process is growing the organism that makes your desired product in a large vessel, called a bioreactor. Traditionally, scale-up of these processes would proceed linearly, moving gradually to larger bioreactors until the necessary commercial scale is attained.

But the conceptual simplicity of this approach hides many downsides. Bigger bioreactors change the physical processes within, often leading to unexpected engineering problems like poor stirring or slow oxygen transfer. Product yields are compromised, requiring expensive and time-consuming optimization at each stage. Simultaneously, the capital expenditure and financial impact of contaminated batches scales with the bioreactors.

WuXi sidestepped these challenges. In place of building >20,000-liter tanks, they run multiple 2,000- to 4,000-liter reactors in parallel: scaling out instead of up. By doing so, the same proven operational conditions are used at small and large scales. Making more or less of a product requires no additional engineering — simply add or subtract bioreactors. The separation of one production run into several batches also ensures that one contamination event does not spoil the entire campaign. WuXi’s adoption of single-use disposable systems that don’t require meticulous cleaning between runs has simplified operations even further. Though not the first to develop these technologies, WuXi was the first to pioneer it as the backbone of a commercial-scale manufacturing capacity.3

WuXi’s China Advantage

Deploying these suites of frontier technologies and large-scale manufacturing facilities is expensive: WuXi Biologics’s massive Singapore facility reached a price tag of $1.4 billion. But some of this financial pain is offset for WuXi by the favorable political and economic landscape of China’s science and technology sector.

The most critical advantage is the Chinese workforce. Chinese universities produce dramatically more STEM Ph.D. graduates than their U.S. counterparts. WuXi capitalizes on this geographic concentration with targeted training programs that attract top candidates and develop company-specific skills. WuXi also invests in training workers at every level of the production process, including the technicians and operators running factory floors. This is precisely the kind of vocational and technical workforce development that the U.S. has chronically underfunded and undervalued. Because this highly skilled Chinese talent is often half the cost or less than Western equivalents, companies like WuXi can deploy larger teams to shorten timelines and overcome obstacles.

WuXi also benefits from China’s established excellence in advanced manufacturing. Because China largely controls global production of raw materials and active ingredients for small-molecule pharmaceuticals and is rapidly domesticating the supply chain for biologics, domestic companies benefit from easier sourcing and more resilient supply chains. This colocalization directly translates into accelerated procurement and lower overhead costs.

These advantages are compounded by the central government’s aggressive championing of biomanufacturing, such as labeling biomanufacturing a national priority and doling out subsidies.

Overall, this investigation shows that WuXi’s success is not a result of some unassailable technological lead in a core competency area. Instead, the well-rounded profile of the company means there is no singular source of advantage. This fact presents an unusual problem to concerned policymakers, who have been struggling to figure out how to deal with WuXi for years.

The Geopolitics of WuXi

Led most prominently by the National Security Commission on Emerging Biotechnology, the U.S. is racing to determine how to maintain its competitive edge in biotech in the face of rising Chinese pressure. The threat of losing the advantage in innovation or a cutoff of basic medicines has policymakers searching for options. The size and success of WuXi has naturally caught their attention.

The BIOSECURE Act is the most notable move. It prevents the use of federal dollars to pay for goods or services from biotechnology companies of concern. In the earliest versions of BIOSECURE, WuXi AppTec and WuXi Biologics were both explicitly targeted. By pushing U.S. companies away from contracting with WuXi, it was hoped that new and more U.S.-aligned firms would step up to fill the gap.

However, the explicit naming of companies was abandoned in the final version of the Act that was passed as a part of the 2026 NDAA. Given how much pain this would have cost U.S. firms, since WuXi is embedded in a quarter of all drugs in the U.S., quitting cold turkey would have been painful.

Unlike with restricting AI components, where slowing progress would be felt years after implementation (and might even be welcomed by Americans already anxious about the technology), the costs of disrupting access to cancer drugs or GLP-1s would be immediate and personal for Americans.

Instead, companies of concern are determined by a deliberative process led by OMB or inclusion on the DoW’s 1260H list of “Chinese military companies”. Unusually, the 2026 version of this list was released for only a short time before being quickly removed from the Federal Registrar. WuXi AppTec was included on this since-removed update, despite being absent from previous versions. So, though the pathway is different, it does seem that BIOSECURE is poised to target WuXi after all.

Implications for U.S. Policy

The U.S.’s policy response to WuXi is an interesting piece of the broader U.S.-China biotech puzzle. Here are a few loosely-held takes:

Take #1: It seems the U.S. policy apparatus is using this company-banning/targeting approach because of its familiar success from AI. But, because most of WuXi’s advantages don’t come from any particular technology lead, does this approach really apply in this situation?

Take #2: The U.S. is quite concerned that China is “catching up” in biotech despite spending far less on relevant R&D:

To us, this suggests that the geostrategic competitive pressures we want to address aren’t primarily about money. If Chinese firms are making important moves with only a fraction of our budget, then whatever advantages they’re exploiting are probably not going to wither away if we further restrict funding. Instead, it seems like we need to think more creatively about how we can race further ahead instead of only worrying about how to slow down our competitors.

Take #3: It’s unrealistic to expect the U.S. to unilaterally dominate every layer of the biotech stack. The U.S. remains a global powerhouse in biotech, occupying advantageous positions across the entire technology stack. But, China is a massive country with a well-educated workforce that has decided to focus major investments into biotech – it’s inevitable that they will become an influential player. Perhaps the right question isn’t how we eliminate Chinese participation in biotech globally but which specific capabilities, if ceded, we could live with.

No single country is waiting to absorb WuXi and China’s cheap and diffuse biotech role. India has a large base of FDA-approved facilities, competitive costs, salaries about half of China’s, and a large and growing Ph.D. pipeline. It has thus received a surge of inquiries from U.S. pharma eager to diversify away from China. However, most of India’s strength is concentrated in small molecule generics, a very different skill set from the complex biologics manufacturing that makes up so much of WuXi’s value. South Korea’s Samsung Biologics is strong on biologics (rivaling WuXi Biologics), but weaker on the small molecule CRO and chemistry services where WuXi AppTec has built its deepest moat. No single country or company can replace all of the different roles WuXi plays, but if the U.S. leveraged its multilateral relationships to build a coordinated alternative across trusted partners, that would be its best shot, something Trump 2.0 has moved against.

The uncomfortable truth is that a U.S. biotech industry fully decoupled from China would be a slower and more expensive one. Policymakers need to be honest with themselves about that tradeoff, unless they think Americans will be fine with fewer cancer drugs for the foreseeable future.

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From Mar-a-Lago to the Great Hall, Trump returns to Beijing desperate for validation while Xi Jinping treats him to strategic flattery. It’s the first time an American president has been to China in seven years. It deserves a podcast, although, as Trivium said, the outcomes could have been an email instead of a summit.

Today’s guests are , author of To Run the World: The Kremlin’s Cold War Bid for Global Power — which won a ChinaTalk Book of the Year award and got the four-hour podcast treatment — as well as ChinaTalk regulars Kevin Xu of Interconnected and Jon Czin, formerly of the CIA and NSC, now with Brookings.

Our conversation covers:

• Prestige politics on the cheap: How Trump's delegation gawked at Chinese architecture while Xi scored propaganda points by getting the U.S. president to fawn over Zhongnanhai's gardens — reversing :cades of diplomatic protocol.

• The G2 that never was: Why Trump's dream of running the world with Xi echoes Nixon and Brezhnev's failed détente, and how strategic competition makes genuine cooperation impossible regardless of personal chemistry.

• The AI factor: As Beijing struggles with compute constraints and export controls, the US brings its AI safety dialogue proposal as its only real leverage in an otherwise empty summit.

• The midterm calculation: How Xi is withholding concessions until September 2026, betting that Trump will need wins most desperately right before the elections.

• Who’s using the pause better? While China methodically builds domestic chip capacity and refuses even approved Nvidia exports, the U.S. struggles with basic industrial policy on rare earths.

Have a listen in your favorite podcast app!

Limited Edition Visit

Jordan Schneider: To me, the most remarkable thing was the affect of it all, starting with Marco Rubio in awe of the ceiling at the Great Hall of the People and Trump being impressed by the trees.

Maybe let’s start with Sergey for some historical context. Is this as odd as it felt to me, having a US president being won over by the CCP red carpet treatment?

Sergey Radchenko: Yes and no, Jordan. Obviously we get a lot of images coming out of this visit. Add to this Trump’s own proclivity for fancy things, and you can see how this has come together. But if you look historically at any summit, they always entail some element of pageantry of this kind. Some actually have had great resonance.

Consider, for example, Nixon’s visit to China in February 1972. I remember that image where he was walking down the stairway from the aircraft, and Zhou Enlai was down there to greet him. He extended his hand to greet Zhou Enlai. Those are images that reshape people’s perceptions. At that particular moment, it was important to show that it was Nixon who was making that step to visit China.

The funniest quip of the Cold War came when Nixon was asked about the Great Wall. Remember that moment? He said, “I think we can say that this is a great wall,” or something like that. We’ve always had that element — when Clinton went to China, he toured the southern parts and visited different places.

In other words, you always have the Chinese trying to showcase their best — the architecture, the pageantry, the receptions. That has a certain propagandistic effect, not least for China, which shows its glory to the world.

Jon Czin: The visuals and optics are probably some of the biggest takeaways from this meeting. The pageantry is always an element of this. One thing I’m mindful of, especially watching some of the pictures where the US side seems to be really taking it all in, is that they didn’t do a great job of playing it cool, frankly.

China rolls out the red carpet, but the affect you want in these meetings is to be business-like and perhaps a little stoic about it, because this is serious stuff. It’s one thing to take it in and appreciate it, but the clips of some senior officials gawking at it — I mean, it is cool when you’re inside those buildings, but you have to maintain your guard for the purpose of those visuals. I don’t think anybody on the inside or the outside would think that’s really the pose you want to strike in that kind of moment.

Jordan Schneider: Sergey, you wrote an entire history of the Cold War through the lens of prestige. It felt like the way the Americans comported themselves in China over these two days — you could not be giving more prestige points to China.

Sergey Radchenko: More face to the Chinese. Exactly. Just think about it — try to flip this and imagine some Chinese newspaper, let’s say People’s Daily or one of those newspapers, presenting videos of Xi Jinping being blown away by his reception in the United States and looking at Trump’s ballroom or something that is going or not going to be constructed.

That sort of thing would be a little bit humiliating. I don’t think the Chinese would ever do that. To see Trump do that, almost kowtow to the Chinese communist leadership — not quite physically, obviously, but expressing this level of admiration — I think this was over the top, frankly.

It’s one thing for Chinese propaganda to trumpet it up, to show it on the Chinese news or in any of those Chinese media. It’s another thing for the White House Twitter account to recycle these images as if to showcase China’s greatness to the American public. I found that a little bit strange, to be honest.

Kevin Xu: I just want to add a few more to that. I can think of two ways to think about this, right? One from the White House perspective. They’re all about their leader, President Trump, getting the treatment that no other leader gets when they go to these places.

I watched the whole raw footage of Trump getting the garden tour inside Zhongnanhai by Xi Jinping. If you listen to the audio of that entire tour, there was this one moment where Trump just had to ask Xi, “Do you bring other prime ministers and presidents to this kind of access?” And Xi was like, “Very rarely. We don’t really do this — maybe very rarely for other leaders, like Putin.”

The entire Trump team actually needs that validation just as much as China wants to provide that validation to stroke the visitor’s ego. I quipped a little bit on Twitter that Zhang Yimou must have started moonlighting at the White House videographer’s office because those videos of the Trump visit were fantastic.

But that being said, I actually think this was a more limited edition of what China wanted to provide to other leaders. If you think about it, just the previous leaders we’ve had from Europe — whether from Germany or Spain — usually get the multi-city tour. That’s what China actually wants you to see. They want you to ride the high-speed rail. They want you to visit either a factory or a robotics company. They want to showcase this entirety of China’s economic and technological rise which you can only show so little of if you have a limited edition of the visit in Beijing.

But they did the best they could to still provide that. Obviously, the Trump team lapped it up. In a way, China wanted to do more, but this is all they could have fit within whatever constraints the Trump team wanted, given that they’re still fighting a war in the region.

Jon Czin: Kevin’s point about how the Trump administration wanted to pick this is quite right — to show that kind of validation that they’re getting and the face that they’re getting in turn from the Chinese side. But I would say for a lot of the optics, I really wonder if it may have misfired. The same is true for the business delegation that showed up.

My suspicion — or my intuition — is that what the Trump administration was trying to do by bringing Tim Cook, Elon Musk, and Jensen Huang is to do it as a flex, to demonstrate how many high-end companies we have that are really at the frontier of today’s technology. But the way it ended up looking from Beijing’s perspective is that you are here to do business rather than to compete with us.

What’s really striking to me — Sergey referenced earlier engagements like this — it did feel like a throwback. It’s kind of the “back to the future” summit where all the emphasis is on commercial and trade relations primarily. You show up with a gaggle of executives signaling pretty loudly and clearly that you want to do business.

You even saw in Trump’s Truth Social post on the way over that they’re looking to expand access to the Chinese market. If you close your eyes or squint a little bit, that could be a statement straight out of the George W. Bush or Clinton administration, not from the period of strategic competition.

Jordan Schneider: Can we come back to this prestige dynamic? Because we all kind of agree that Trump and the team and the delegation sold prestige on the cheap. There is a debate about whether giving face upfront leads to better or worse outcomes. Lots of folks have made the argument that presidents — starting with George W. Bush and through Obama and Trump’s first term — didn’t give Vladimir Putin enough face. Part of the reason we’re here today is — should we quote your book, Sergey? “Obama’s occasional dismissive remarks about Putin, such as when the American president compared him to the “bored kid at the back of the classroom,” added to the sense of a personal affront. It was not just that the Americans felt they were exceptional. They also pretended to be teachers.”

Even if Trump isn’t trading trade concessions for propaganda points of looking overawed by Chinese imperial greatness, is there a sense where maybe this just leads the planet on a safer trajectory? Because the Chinese people and Chinese leadership are less ticked off and feel less looked down upon by an American delegation? Or are we past that sort of game in 2026?

Sergey Radchenko: If I may offer some historical observations on this, it is true that under all circumstances, speaking respectfully about the other side is just the right thing to do. Trading insults has never led to any productive relationship ever. The Chinese are especially sensitive to this. They have historically — for obvious reasons — we’ve had, for example, moments where Mao Zedong had really nasty exchanges with Nikita Khrushchev back in the late 1950s.

Speaking of what foreign leaders get to do or not get to do, Khrushchev got the real treatment. He got to meet with Mao Zedong in the swimming pool of Zhongnanhai because it was in the summer and Mao Zedong had a swimming pool installed there. But actually, this was supposed to be an insult from Mao Zedong in relation to Khrushchev because he was trying to show his superiority.

Khrushchev and Mao quarreled, and Khrushchev in particular called Mao names. In the end, it did not contribute positively. You might say that this relationship — we’re talking about the relationship between Moscow and Beijing back in the late ’50s, early ’60s — fell apart for reasons that perhaps were not all related to personal insults, but personal insults never helped.

You mentioned, Jordan, this question of Putin and Obama. There were various reasons why Putin would want to reassert Russia the way he thought he was reasserting Russia’s standing and quarrel with the West for any number of reasons. It did not help that Obama was trying to look down on him because there is a general perception in Russia of American arrogance.

Speaking respectfully about the other side is generally a good thing. President Trump has not distinguished himself by being consistent in treating others with respect. In fact, he seems to go from one extreme to the other — he can trash a foreign leader one day and then say something good about him or her the next. However, his treatment of Xi Jinping has been fairly consistently respectful, wouldn’t you say? He hasn’t really trashed Xi Jinping in any noticeable way, which is good for the relationship.

Kevin Xu: I agree with that. The only thing Trump still occasionally brings up is COVID, but at the end of the day, his praise of Xi Jinping — whether from afar or up close — has been incredibly consistent compared to any other world leader, past or present.

Sergey Radchenko: Some people will criticize us for saying that. They’ll argue that Trump admires Xi Jinping as a dictator and therefore feels he constantly has to praise him. There’s probably something to that — it’s fair to say that Trump admires Xi Jinping’s way of governing, just as he does with Vladimir Putin.

Yet you could also say — look, you’re dealing with the leader of an important state, China. We may not like what the Chinese are doing in many areas, but we still have to treat them respectfully because that facilitates our interactions. However, this won’t necessarily lead to a good relationship by itself. The reality is that China and the United States are strategic competitors. You can kiss up to Xi Jinping all you want — it won’t change this reality. Or you can swear at him all you want — it still won’t change this reality, except maybe making it worse.

Jon Czin: To embellish that point, one important element to keep in mind with these meetings is not how much they matter, but in some ways how much they don’t in shaping the long-term trajectory.

I was struck listening to Sergey’s previous episode about the personal interactions between Leonid Brezhnev and Richard Nixon and how important that personal rapport was. My sense is that especially under Xi Jinping, these meetings don’t necessarily move the needle — and certainly not in a positive direction.

As idiosyncratic as Trump is and as different as he thinks he is from his predecessors, there’s something essentially American about him. He really thinks that through his charisma and back-slapping, he’s going to somehow make a deal with the other side. That’s such an American way to approach things, and it’s so mismatched with how Xi conducts these meetings.

We just saw this earlier this year — as Jordan and I discussed in our episode about Zhang Youxia — Xi is very unsentimental about personal relationships. Even with people in his inner circle or people he’s known for decades, he’s willing to jettison them.

My sense is that when he goes into these meetings, what he’s basically doing is sizing up the other side, right. What’s really interesting is what Xi is learning about Trump from this. It’s probably only at the margins because Xi’s had a decade now to interact with Trump and think about how to interact with him.

One thing that’s really shifted in terms of this prestige dynamic — my old NSC colleague Henrietta Levin pointed out in her recent Foreign Affairs piece — is that it used to be the US. tactic to trade form for substance. Now, because Trump is so focused on the forums, it flips the dynamic. The Chinese side can say, “We’ll roll out the red carpet” as a way to try to achieve their substantive objectives with the Americans.

Their objective wasn’t really clear from the Chinese side. What they were mostly trying to do is think more long-term and see this as a reprieve — trying to buy as much space as possible from US pressure and fortify themselves for the next round of the contest. That’s what they’re purchasing by trying to give Trump so much face in this meeting. In the big scheme of things, that’s a relatively small price to pay.

The Reversal of Neediness

Jordan Schneider: Contrasting with Soviet leaders being really needy — I don’t think Stalin was particularly needy, but going through Khrushchev and Brezhnev, as you show in your books, Sergey, they had this deep desire to be seen as a peer with America on the global stage.

Almost now it’s flipped, where we have Trump who is the needy one, wanting to be seen as a peer.

Sergey Radchenko: It is crazy if you think about it. In the Soviet case, it was clear why they wanted this American recognition — to be seen with Nixon, for example, or Eisenhower. The reason was that they didn’t have really domestic sources of legitimacy. They thought that by being recognized externally by the United States, they would stand tall and proud as leaders of this great superpower and be legitimized by another superpower.

It’s interesting to think that with Trump and the pageantry that we saw in Beijing, it’s almost the reverse. He wants to be legitimized by the Chinese as a great leader. You know how he says, “Other countries respect me,” et cetera, which a lot of us in Europe are rolling our eyes at. There’s frankly a sense of incomprehension in many European capitals. Trump is trying to use this opportunity to highlight that China respects him.

I wonder if it works the other way. Is Xi Jinping also in need of selling the images around Trump’s visit to the domestic audience to say, “Here we are, the two great powers, da guo, working together,” and that shows the strength of the CCP? Is that part of the domestic legitimacy discourse for Xi Jinping?

Jon Czin: Xi is happy to take the win, but especially this far along into his tenure, hosting an American president isn’t crucial for him the way it might have been for his predecessors like Hu Jintao and Jiang Zemin. He went almost 10 years without hosting an American president, and his power has only grown in that period because of the purges, expulsions, and other internal dynamics. It matters, but really at the margins. Xi isn’t in a position where he needs to assuage any politically salient internal audience or demonstrate China’s greatness on the world stage. He’s happy to do it, but it’s not essential.

Kevin Xu: On the margins of that — I don’t think Xi is doing this because he has trouble winning a fourth term. But the domestic situation regarding the economy, youth employment, and general consumer sentiment has been bottoming out ever since zero COVID for the last two and a half years or so. Last year’s trade confrontation didn’t help at all, even though you could argue China stood up to the US in ways no other country could. China flexed real rare earth muscle and is learning how to do export control in a weaponized and offensive way. That’s fine as China learns these new crafts when dealing with the US from the more adversarial side of the relationship.

But as far as being able to host Trump — China just wanted this trip to happen. It was delayed once, and we didn’t know when it could happen. It’s very important for Xi to be able to host a United States president on his terms in a way that could balance the narrative at home, which is that “we are fine from an international perspective. The G2 is back on the docket.” Now we can talk about the more substantive stuff as China has, frankly, a lot of domestic problems that it is wrestling with. We haven’t talked about the future impact of AI and all that, which is now on the deliverables for these two countries — kind of a new thing.

All that is to say, there is some domestic need for this to be both done and done very well. We can debate whether it was done well or not, but it had to be done.

Jordan Schneider: The awkwardness of the delay means that Putin is showing up in Beijing tomorrow. This idea of a G2 — this was the dream of Brezhnev telling Nixon, “together we will run the world.” The idea being whoever gets to pair up with the US — whether it’s China or the USSR — is the one in pole position.

As pointed out in a recent article, when Xi went to Moscow to see Putin in 2023, a camera caught him speaking with the Russian leader, gesturing emphatically. Xi said, “Right now there are changes unseen in a century, and we are the ones driving these changes together.” “I agree,” replied Putin. We had similar language around that with Trump and Putin talking about how together they’re going to run the world. This is an idea that, at some level, appeals to Trump in particular. I’m curious for thoughts on how we’re going to be looking at this relationship, whether we’re going to be looking at this trip very differently based on the visuals that are going to come out of Putin and Xi hanging out tomorrow.

Sergey Radchenko: Jordan, on this question of running the world together, let me tell you an anecdote about the Soviet reaction when Nixon went to China in 1972 and made a toast about the future of the world being in America’s and China’s hands. That’s 1972 — Nixon goes to China, makes this toast that the future of China and the future of the world is in China’s and America’s hands, which is then publicly reported.

The Soviets read about it and get really upset. Brezhnev complains to Kissinger, “What are you saying? Aren’t the Americans and the Soviet Union supposed to be holding the future of the world in their hands?”

In other words, there’s a long historical background to this idea of the world being run or co-run by any number of these great powers. It’s interesting to see how this is evolving. I would imagine that from Xi Jinping’s perspective, it’s not even the G2 world. It’s almost like China is the center of the world, and the others are like spokes connecting to China. Very much a Sinocentric world.

Jon Czin: But it’s interesting because it’s primarily, in some ways, a question of optics. One of the things that’s interesting about how China responds to this G2 concept — they welcome the US side saying it, but they don’t actually like it in the sense that they don’t want to take on those burdens. You see it with their caution in the Middle East right now.

There’s one of these paradoxes at play in which China, being the second superpower, benefits from that position. They don’t have to take on the cost. All they have to do is continue to score singles and doubles at the US expense and build up their power without taking on any of those additional responsibilities.

That segues to another point I wanted to make in terms of the way the calendar worked out in the run-up to this meeting. The fact of the postponement meant that you not only have Putin coming on the heels of Trump, but you also had Iran’s foreign minister visiting just the week before, which was probably intentional on the Chinese side. It was designed to allow them to deflect US pressure on this issue since all they had to do was reiterate their long-standing talking point throughout this conflict that they support an opening of the Strait of Hormuz to try to assuage the US side.

The head of the KMT, Cheng Li-wun, ended up visiting Beijing and meeting with Xi Jinping before Xi’s engagement with Trump. We don’t know what happened in their internal meeting, but my suspicion is that Xi wanted to position himself to Trump as a man of peace — “You’re a man of peace, I’m a man of peace, I just met with the opposition” — and put the onus on Lai Ching-te. Based on Trump’s comments over the weekend, it seems this may have been Xi Jinping’s framing, which is unfortunate. The Chinese side was frustrated at a logistical level that the meeting was postponed in the run-up, but it actually ended up playing to their advantage because of how the choreography worked out.

Kevin Xu: I wonder if there was an alternate universe where the Trump visit could have happened after Putin. The Putin visit was long scheduled, while the US visit was much more in flux. Speaking from the US perspective, it might be a slight plus that Xi wanted to meet with Trump first before meeting with Putin, rather than meeting Putin first, which would look more like the evil axis colluding before receiving the US president in Beijing.

These days, everything is so haphazard. Based on my previous experience advancing White House visits to China from the US perspective, the Chinese side had to really compromise stylistically. These visits are usually rigid and planned ahead of time. To have one American CEO jump onto the plane halfway en route to the state visit, and then to have another member of the US cabinet delegation actually be on the sanctions list and you have to contort yourself to let him in — these are all compromises that are actually very rare from the Chinese side when preparing for these high-level visits.

This shows a level of practicality, respect, and accommodation that’s quite rare to make all these visits look good and not have any silly awkward moments that could overshadow the entire narrative.

Jordan Schneider: Shout out to the Chinese advance team. We really put them through the wringer on this one. They deserve some kudos and probably had late nights putting out that extra table setting.

Sergey Radchenko: Although we’ve talked a lot about the symbolism, and we don’t know what happened on the inside except for what Trump has let us know in his conversation with the press, it would be interesting to see how Ukraine was discussed.

Do we know anything about what Xi Jinping and Trump discussed regarding Ukraine during their Mar-a-Lago meeting, and how Xi might have reacted? Of course, this connects to Putin’s visit — perhaps messages were passed from Trump to Putin via Xi Jinping. It’s not even necessary because there are obviously the Witkoffs and the Kushners flying back and forth, but it would still be extremely interesting. Historians will find out in 30 years what was actually said, and maybe we’ll be massively surprised.

Jon Czin: It’s interesting on that point, Sergey, that my recollection is the Chinese side referenced Ukraine in their readout after the initial two-hour encounter between Trump and Xi, but there was no mention of it in the US readout.

Sergey Radchenko: Not in the readout, but Trump talked about it in his conversation with the press on Air Force One on the way back.

Jon Czin: You’ve got to keep in mind the mechanics of the meeting. If that was the main time when they spoke about Ukraine, this is a two-hour meeting. In all likelihood with consecutive translation, you really only have an hour of each side talking at most, unless somebody really decides to hold forth.

Sergey Radchenko: I think it was simultaneous because they published a small piece of it.

Jon Czin: That’s a fair point, but it’s still not going to be a lot of airtime.

Sergey Radchenko: Was it just this two-hour meeting between the two delegations? Did they have a private meeting? Sometimes you have these very small meetings of just the leaders and their immediate advisors. The delegations were massive — there were about 50 people altogether on both sides.

Jon Czin: Huge delegations.

Kevin Xu: They met for tea time, did the tour, and had a lot more informal meeting time. They also had a bilateral media availability where Xi said Trump loved the garden and offered to give him some flower seeds. Before or after that, they had more casual conversation that wasn’t as formal as sitting in a big conference room.

Sergey Radchenko: I hope they didn’t talk about organ transplants like Xi Jinping and Putin.

Jordan Schneider: Well, Kevin, this is your point — two old men hanging out. What are they going to talk about? Bad backs and trees.

Kevin Xu: Look, if you’re at the height of your game in your late 70s, organ transplants are the first thing on your mental agenda. The second thing is how old the trees are around you, to show deference to Mother Nature. We got the second part definitely on camera. The first part that Sergey mentioned, I don’t know — it could have been just “give me that guy’s number” kind of thing.

Arms Control and the Limits of Détente

Jordan Schneider: This idea of détente is interesting. You write, Sergey, that “the terrifying experience of the Cuban Missile Crisis was key to Khrushchev’s embrace of détente. Having come close to the brink, both Khrushchev and Kennedy glimpsed the darkness on the other side and understood that the world had changed forever. Nuclear-armed great powers were simply indestructible from without.”

Now, comparing the Cuban Missile Crisis to the great rare earths sanctions list expansion of October 2025 doesn’t quite fit the same category. But I’m curious about the analogy here — both sides deciding that the current temperature level is the correct one for them.

Sergey Radchenko: That’s a very interesting analogy. Of course, we haven’t had a crisis similar to the Cuban Missile Crisis. We could still have a crisis like that over Taiwan, for example, and who knows how that ends up.

But for now, it’s more interesting to compare what’s happening now to the Soviet-American détente in the early 1970s. There, you didn’t really have a crisis per se. Basically, at that point, the Soviets were in a situation where they had peaked and they understood that they had peaked. They wanted to have some kind of reasonable relationship with the United States — to agree to rule the world together, to listen to each other’s concerns, manage problems like the Middle East. That’s another interesting parallel. One of Leonid Brezhnev’s big concerns in 1972 — 73 was how to manage the Middle East together with Richard Nixon.

Of course, it never worked out because here’s the problem: You can have a wonderful personal relationship — and actually, Brezhnev and Nixon had a wonderful personal relationship. Brezhnev just loved Nixon for whatever reason. But you have two countries that were at that time strategic rivals. No matter what relationship you have, there’s always a tendency or desire to stab your partner in the back when the opportunity arises. There’s no alignment of values really, so you just basically go for it when you have an opportunity.

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In the Soviet-American détente in the early 1970s, things seemed to be very nice. But actually, when it came to forcing the Americans out of Southeast Asia, the Soviets were more than happy with this. In 1973, you had the coup against Salvador Allende in Chile, and this was a defeat for the Soviets, a victory for the Americans. Then you had any number of conflicts in Africa, from Angola to Mozambique to Ethiopia, Somalia, etc.

Despite détente, this conflict turned into a zero-sum game for the two superpowers. Because in a situation of strategic rivalry, both sides understand that it is basically a zero-sum game. It is not — to use the Chinese propaganda phrase — “win-win.” It doesn’t work like this.

The Chinese can still talk about win-win all they want, but the reality is this is a strategic rivalry. No matter what Trump says to Xi Jinping or vice versa, it’s going to be unstable, and we are in a situation where more conflicts will arise. The question is not how to prevent the conflict, but how to manage the conflict.

Jon Czin: That meshes well with the point Julian Gewirtz has made about this. This isn’t really stability right now or anything like détente. It’s a stalemate. Basically, where we landed last year after the whole issue over rare earths is both sides realized the other side had leverage, and we’re just kind of stuck right now. The real question right now is maybe less about how long the stability lasts — that is one interesting question. But if we are locked in this longer-term competition, the question is then who’s doing more to fortify themselves in the meantime?

Sergey Radchenko: That’s exactly it. And by the way, détente fell apart, right? We cannot see détente as a stable condition itself. Détente was stable for a couple of years, and even while it was stable, there was actually a crisis in the Middle East that led to the United States raising nuclear readiness to DEFCON 3. That’s how détente was. We cannot say, “Now we have American-Chinese détente” — there’s no evidence for this. We have a summit, and the problems will continue.

Jon Czin: If anything, this past year is like a great natural experiment about the limits of the viability of an idea like détente in this setting. The US has, in some ways, hit the pause button on two of the issues that were the most contentious during the Biden administration — on technology and export controls, and then to some extent, with the giant exception of the big arms sale that was announced at the end of last year, pulling back at least on rhetorical support for Taiwan.

The reality is it hasn’t really yielded much in terms of some kind of deeper stability or an affirmative agenda, even recognizing, to Sergey’s point, the limits of détente in the first go-around. It underscores just how challenging it would be to get to something that does look more like that.

The other point is about the scary moment of the Cuban Missile Crisis and how that fed into subsequent discussions about détente and the need for arms control. That’s another really interesting point that’s embedded in all this — you don’t even have those conversations underway.

It’s one of the really striking things. When I talk to my colleagues who are Russia specialists, it’s such an interesting compare-and-contrast exercise. Jordan, you and I talked about this on an earlier episode. In some ways, we have a much deeper and more sprawling relationship with China than we ever did during the Soviet Union because of the people-to-people ties and the economic relationship.

But when you talk about those really sensitive issues, it’s much more awkward and truncated. It’s virtually impossible to have those kind of conversations about strategic stability — in a nuclear sense — with the Chinese, or really engage deeply on these issues, even though there’s been a push from the US side to have some of these conversations about crisis management and this whole suite of issues since the EP-3 incident.

My theory about this — and I don’t really have evidence for this — is that the EP-3 moment was kind of an “oh shit” moment for a lot of people on the US side.

Jon Czin: This incident, while not exactly analogous to the Cuban Missile Crisis, showed how a collision between military assets could spark a major diplomatic crisis.

The EP-3 incident occurred in the first year of the Bush administration when a Chinese fighter jet collided with a US reconnaissance plane. The US aircraft had to make an emergency landing on Hainan Island, and the Chinese pilot, Wang Wei, was killed in the crash. The Bush administration then had to negotiate for the release of the American crew members. Ultimately, they issued something resembling an apology to resolve the situation.

What startled US policymakers was their inability to establish communication — they tried calling Chinese counterparts, but nobody would answer. This wasn’t just bureaucratic delay. The Chinese military cannot operate independently without approval from political authorities in the Politburo Standing Committee, requiring internal deliberation before responding.

My theory is that China viewed this approach as successful. Going dark serves two purposes: it allows time for internal deliberation within their collective leadership model, and it works as an effective negotiating tactic. When China goes silent, it unnerves the Americans and provides leverage — China then controls when conversations resume and can set the terms.

This creates a fundamental mismatch in approaches. Many discuss achieving something like détente, and the Trump administration expressed interest in arms control talks, but China remains uninterested. They view such conversations as a trap, believing the Soviets’ participation in similar discussions contributed to their downfall.

Sergey Radchenko: The Soviet experience shows a different trajectory. After the major scare of 1962, they gradually moved toward arms control. One of the first steps was stopping atmospheric nuclear testing in August 1963 with the Partial Nuclear Test Ban Treaty.

This led to establishing the NPT regime — a remarkable achievement where superpowers agreed on nuclear nonproliferation despite their rivalry. In the early 1970s, this progressed to agreements like the ABM Treaty on ballistic missile defense.

Jordan Schneider: Well, let’s give Japan, South Korea, and Taiwan a few more years — then it really gets out of control, right?

Sergey Radchenko: Yeah, then we’re in a big mess. That’s right. That’s very sad. I was in Beijing, and I raised this issue with some of the Chinese experts. Their response was essentially that they simply cannot engage in this kind of discussion. On the other hand, they said we can talk about AI regulation.

AI Safety Dialogue

Jordan Schneider: Let’s turn to Kevin then, because in contrast to nukes, where everyone and their mother is going to have one by 2030, it’s not necessarily going to be the case in AI. At least today, there really are sort of two superpowers, though one can debate just how far behind China is relative to the US. Kevin, what’s your take on the idea that there’s going to be some sort of AI safety dialogue between the two countries?

Kevin Xu: I will say AI is the one thing that might throw that dynamic a little bit off in the US’s advantage. I was actually in China for nine days during the latter end of April through early May.

During these meetings with a small delegation of AI researchers and writers, all the Chinese labs complained about compute constraints — they can’t get enough compute.

The biggest culprit is US export controls. The second biggest culprit is the lack of domestic capacity to produce quality chips at a high enough yield. Even if Huawei can design the best chip, SMIC can’t manufacture them quickly enough with the quality needed to satisfy domestic demand. This doesn’t even address Chinese models or cloud providers potentially going abroad, which many would like to do if given the opportunity.

Against this backdrop, Anthropic recently launched their model in a way that scared every industry that cares even vaguely about cybersecurity. We’re hearing news about Dario Amodei briefing the largest banks in Europe, including central banks, about the power of AI.

This was the “Trump card” the US delegation brought to China to initiate what we might call a G2 AI safety dialogue, positioning the US from a place of strength in these conversations. The current consensus view of what this could produce long-term is relatively modest. This is an entirely different kind of technological threat compared to nuclear weapons.

In response to your mildly sarcastic point — yes, everybody will have AI in their computers. We already have AI in our phones, laptops, and at work, whether we like it or not. But not everybody has a mini nuclear reactor powering their house. The reverse is true with nuclear weapons.

There’s a larger non-military application to AI, but also a very legitimate military or national security dimension that makes this a more novel kind of dialogue between the G2 powers when it comes to technological containment or coordination.

The context of the US delegation going to China to discuss AI safety has much to do with non-state actors accessing advanced AI models. It’s less about the US saying, “You better not do this because we have the better model,” or China thinking, “You have the better model, we’re going to catch up, so you better not do anything crazy.”

This is where we’re heading, and it’s probably the most consequential factor that could shift the G2 dynamic in one side’s favor or the other, depending on where the models stand on any given day. This makes the dynamic much more fluid than traditional determinations of common denominators.

Jordan Schneider: If we’re stack-ranking what might break the stalemate for the rest of the Trump administration, we’ve got AI. We’ve got a Taiwan presidential election. What else, really? We’ve already done the trade war — I don’t think we’re going back to that. That’s kind of off the table.

Kevin Xu: The term “détente” may not be the best framework to describe the current moment. As Sergey pointed out, it’s more of a pause — a period where each side is buying time to reshore and strengthen themselves for whatever the future might hold.

We’re seeing clear examples of this strategy from the Chinese side. They’re refusing NVIDIA H200 chips from entering China, even though the US has granted enough licenses for them to be sold.

The Chinese side doesn’t want these chips because having more foreign technology come into their ecosystem — especially less advanced versions — would disrupt their reshoring playbook. They’re channeling every single lab in China to give all their purchase orders to Huawei, work with Huawei, co-design with Huawei, and ensure that supply chain is as robust as possible. Even if they suffer a lag of six months, nine months, or even a year, and even though every company would love to have the H200s, accepting them would dilute the revenue, attention, and mindpower needed to support domestic GPU suppliers as much as possible.

The big wildcard is what we’re doing on the US side to match this approach. That could change the dynamic significantly if we have real announcements — not just stock-pumping announcements from companies like Applied Materials or MP Materials. These are domestic rare earth suppliers and mines. If they could say, “Hey, we actually have enough going on now to support GM and Ford and all of our automakers without needing to rely on any foreign source of processed rare earth material in our supply chain,” that would change the dynamic quite a bit. But we’re typically not very focused on building our own capabilities right now.

Jordan Schneider: Let me share a Xi quote from March 2021: “Practice has repeatedly told us core technologies cannot be begged for, cannot be bought, cannot be bargained for. Only by holding core technologies firmly in our own hands can we fundamentally guarantee national economic security, defense security, and other aspects of national security.”

Sergey Radchenko: I think we can all subscribe to that, right? That’s what we’re all trying to do now.

Jon Czin: That’s great for our study session, Jordan. But I think this is really the key question. There are two critical issues here: What breaks the stalemate — either it falls apart, or somebody has a breakthrough — and who uses the time better in the meantime?

This is one of the things that causes me a lot of anxiety. I’m not persuaded that we’re using the time wisely or to the full extent. This is one of the interesting dynamics — if you talk to Chinese colleagues, they feel confident that they’re making good use of the time. You can see that reflected in the five-year plan and how they’re talking about it — the confidence they’ve been exuding since the fourth plenum last year. If you talk to people in the Trump universe, they also feel pretty good about the US position. Some of that is congenital to the Trump brand to have that bravura.

But it’s something that I’ve been really wondering about: Who’s making better use of the time? Yes, we’re having remarkable breakthroughs in the private sector on AI.

What I worry about is if you just talk about the particular issue like rare earth — I give the administration a lot of credit for the work they’re trying to do in the Pentagon in particular, and even the Pax Silica initiative. We have two real factors working against us just on that particular issue.

One is that we’re getting our act together belatedly, frankly. We’ve known about this issue since 2010, since they did it to the Japanese. Even the Japanese, as many people have pointed out, after 15 years of assiduously working on this, only reduced their dependency from something like 90% to 70%.

What’s been on my mind is that the Japanese have METI. They’re designed to do industrial policy. Even in the best case scenario, or even in the Biden administration, we are not really designed for this. This is hard. How are we going to do price floors and offtakes for something like rare earths, never mind the other supply chains that run through China? How much are we really devoting to figuring out some of these challenges?

The other issue is there’s other aspects to this competition too — things that people have pointed out already, the depletion of munitions with the war in Iran, the reallocation of resources from Indo-PACOM to Central Command that have been concomitant with this.

Even on the technology aspect of it, one of the things that I worry about — and that my colleague Kyle Chan points out too — is that I worry that we have AI myopia here in the United States and we’re so focused on this one technology. If you look at the five-year plan from China, they’ve got more of a portfolio approach. They are very much focused on AI, but there’s a whole suite of other technologies that they’re really putting a lot of emphasis on that I think are also quite important. Green energy, of course, has been very much in focus recently, but robotics, other aspects of this too.

It leaves me feeling unpersuaded as an American — or anxious — that if we do have this pause, maybe we’re not making as much of this time as we really could or should be.

One last thought — on what could break the stalemate or shake up the dynamic, the other element is just the mere fact of our midterm elections. As Beijing has thought about sequencing the diplomacy this year, this has been a crucial part of how they’ve tried to do the choreography.

It’s not like they think in terms of dynastic cycles — they’re just thinking in terms of the outlook calendar and recognize we’ve got an election coming up. They recognize that whatever they’re going to give the Trump administration in terms of concessions or wins, they’re going to get more bang for their buck if they give those to Trump during a state visit that’s very close to the midterm elections.

Jordan Schneider: They didn’t give him anything.

Jon Czin: They’re withholding it until later. They recognize that if it’s all about finding the minimum price point for mollifying Trump, you’ll get more mileage if you do it around the midterms. The really open question is how the policy and political dynamic in China shifts potentially after the midterms.

Jordan Schneider: I don’t know if this is a sell. We were talking about the Trump administration wanting to get some brownie points because they feel insecure. Are there voters out there who look at those videos? Are there swing voters — voters who might stay home in November — who see those types of videos and the quote-unquote “respect” we get from a Putin meeting in Alaska or a Xi meeting in Washington in September and think, “Yeah, this is the party I want to vote for”?

And on the economic stuff — okay, it’s one thing to make announcements. To actually reduce inflation, that has to flow through the economy, which isn’t just an October surprise type thing.

Jon Czin: That’s a really fair point. It’s not necessarily high political salience. It may have to do with how Trump wants to depict himself. At the very least, what he’s going to be loath to do is see one of his big international deals unravel right around the time of the midterms.

I thought this after the two leaders met in Bali and agreed to the supply chain truce. They’re looking at one year — it’s a one-year pause. Trump’s not going to want this to all unravel as he goes into the midterm election. They probably calculated that it gives them leverage to at least stabilize things or lock in the US side and prevent any competitive actions, at least through the midterms.

Kevin Xu: The Chinese side is much more willing to play that dynamic as well. Front-loading all the deals they’ve already said they’ll give to the Trump side right now is actually pretty dumb. If you’re that aware of the US political calendar, everybody knows nobody pays attention until after Labor Day when it comes to a presidential election, let alone a midterm election. That’s just how it always works.

A late September big announcement where Xi actually comes to the US and gives Trump a giant basket of gifts — whatever those purchases might be — is what the Trump side wants and what the Chinese side is willing to give. It would give Trump the best hand he could have for the second half of his second term so there’s actually more deal to be made. The moment the House and/or the Senate flips, a lot of the stuff that China may want to work with the US on that’s longer term or has a longer timeline becomes much more difficult.

All this investment stuff, where there could be joint ventures, actual booths on the ground, building certain facilities where Chinese companies or Chinese technology is involved — that could really flip on a dime, depending on who is part of the separation of powers getting to say. We just have to wait until then. I’m pretty sure the Iran war will end in some way, shape, or form before September. Let’s hope. Trump’s whole gimmick is that this will reduce gas prices overnight and inflation will come down.

I don’t think voters think about inflation from an analytical or academic point nearly as much as whether the gas pump is lower. If gas is cheaper, there’s no inflation, and then we move on to our daily lives. All that actually lines up quite well to almost this weird little — I call it G2 chemistry — where each side actually knows what the other side needs to keep each other in play, to keep working together in ways that we probably don’t give either side much credit for. We usually look at everything from a super competitive, confrontational, adversarial perspective in ways that dilute this interesting little understanding of realpolitik between Trump and Xi.

Jon Czin: Just to underscore that point, Kevin, when you think about it over the arc of the past year, it’s pretty remarkable that’s where we’re at now. Fourteen months after having a de facto embargo on China, where the administration comes in and thinks it’s clobbering time — and now this is where we end up, with this implicit gentleman’s agreement about scratching each other’s political itches for the moment. It’s striking to me. We’ll see how things play out with Iran, but I’ve had this thought that the Iran war is almost following a very similar narrative arc to what happened with China.

The administration comes in — literally in the case of Iran, guns blazing — they underestimate the other side, they realize how much resilience and appetite there is for pain on the other side, and then they end up looking for some kind of diplomatic denouement or off-ramp. There’s something essential there, both years that have defined the trajectory of each one of these contests.

A Book Recommendation

Jordan Schneider: I’ve got a book recommendation. Maybe we can end on that. I just finished Julia Ioffe’s The Motherland, which I found to be fascinating to pair with your book Sergey asbecause it tells the story of the Soviet Union through women.

The contrast between how the wives of various American presidents saw themselves and the wives of Soviet leaders — who were PhDs and had their own professional lives and really thought they wanted to mix it up on the world stage — was fascinating. At the same time, they had these status anxieties. They wanted to be perceived as prestigious and not these dowdy Russian babushkas.

You get that layer of history as well as Julia Ioffe’s personal arc, telling the story through four generations of her family and the social dynamics of what has led to this transformation. We’ve gone from the dream of the early days of the Soviet Union — where you have full and total equality and women are able to pursue exactly the same careers that men have — to Russia in the 2020s, where the ideal is to just marry a rich man and have him divorce you 10 years later so you’re kind of fine, I guess.

That whole loop has personal dimensions and policy dimensions. It’s a nice reminder that even though you have photos with the US and China where you have 15 men on either side, there are actually lots of women who are a part of these discussions and informing them, even if they aren’t literally the leaders of the two countries. Hopefully, we’ll get Julia on the podcast, but that was a fun book.

Sergey Radchenko: It’s a very masculine, toxic environment, considering the number of men in all of this. That’s something I suppose we should strive to do something about. Trump is not doing anything about it. Nor is Xi Jinping.

With pretty much no news out of this Xi-Trump trip, how about checking out another economic security contest winner? This one comes from Guy Ward-Jackson, a Senior Policy Analyst at the Tony Blair Institute. You can reach him at Guy.Ward-Jackson@institute.global or read more of his writing on his Substack. Views are his own.

Economic Deterrence Without Autarky

The Cold War sparked an entire academic and policy discipline on nuclear deterrence and statecraft. It is time that the sphere of economic security received its fair share of attention. But we do not have to start entirely from scratch; there is much to learn from our “Cold War Warrior” predecessors. This essay suggests borrowing from the theory of “nuclear latency” — the notion not of having a bomb, but of having the capacity to build it in a coercive or crisis context — and applying it to vulnerable but non-critical elements of U.S. economic security.

The combination of rapidly emerging dual-use technologies like AI and quantum, the hyper-interdependence produced by globalisation, and U.S.-China geopolitical rivalry all mean that economic security is having a moment. However, as the lines between technology, economic and national security blur the likelihood of confused policymaking increases dramatically.1 The question for the United States then becomes not ‘should we prioritise economic security?’ but ‘how do we prioritise within economic security?’.

Prioritisation matters for two reasons. First, because economic security — even for the United States — is not free. Attempting to insure against every vulnerability produces familiar pathologies: blanket “re-shoring” agendas, misallocated capital, political capture, and opportunity costs2 in other areas. If the United States started treating every economic risk as an existential security threat — shielding industries from competition and innovation — it would undermine the very market dynamics that make the U.S. economy the strongest in the world.3

Second, because the most powerful economic security card that the United States has is not isolation but network dominance.4 It derives leverage from scale and openness — the conditions which produced interdependence in the first place. The strategic task is therefore to preserve the United States’ strategic gains from interdependence, while reducing the most coercible points of dependence — and, crucially, to do so efficiently.

In light of this, the United States’ current economic security policy repertoire is incomplete. Most U.S. economic security tools are either negative instruments — sanctions, tariffs, export controls — or vital but blunt supply-side interventions aimed at a narrow set of indispensable (‘Tier 1’) capabilities such as chip fabrication. The mixed historical record of economic deterrence should caution against overconfidence in coercive tools alone.5 Meanwhile, full-scale domestic re-shoring is fiscally unsustainable once it extends beyond a small number of genuinely existential sectors or capabilities (e.g., fabs). The missing gap is what to do about the wide middle: supply-chain bottlenecks that are strategically consequential, vulnerable to coercion, yet not important enough to justify full-scale CHIPS Act-scale reshoring.

This essay proposes a way to manage that middle category: an Economic Security Latency Fund, on the order of $20-30 billion, explicitly designed to build resilience and as a form of ‘deterrence by denial’. The organising idea comes from nuclear strategy. Japan and South Korea have debated “nuclear latency” — maintaining the industrial and institutional capacity to build a weapon quickly without actually doing so — because full armament is destabilising, but zero option value is risky when alliances and threats are uncertain.6 Applied to economic security, latency means preserving the ability to scale production rapidly in a crisis without trying to on-shore everything in peacetime.

The point is not autarky but time. Economic coercion works when it can impose politically salient pain faster than the target can adapt. Latency reduces that coercive leverage by shrinking time-to-substitution and scale-up bottlenecks, ensuring that the capacity to ramp-up takes months rather than years. By building latent capacity, the United States can build resilience in areas where it is vulnerable and not currently critical — but could become critical in a crisis scenario.

The rest of the essay does three things. First, it sets out a disciplined hierarchy for U.S. economic security: distinguishing Tier 1 capabilities that justify permanent capacity, Tier 3 areas where markets and diversification are sufficient, and Tier 2 bottlenecks where latent capacity is the efficient middle path. Second, it operationalises what “latency” means in practice: how to choose select target areas, what instruments actually buy rapid scale-up, and what credible “thresholds” look like: economic equivalents of red lines. Third, it stress-tests the approach through an illustrative scenario, showing how latency can build resilience and deter coercion against the United States.

The core wager is this: disciplined latency can deliver a higher deterrence-per-dollar ratio than either blanket reshoring or reliance on coercive tools alone, while preserving the very interdependence that makes the United States powerful in the first place

Proposal: An American Economic Security Latency Fund

Countries like Japan and South Korea have long debated nuclear “latency”: the ability to acquire nuclear weapons quickly without actually building them. Latency is a hedge against uncertainty. As well as capability-building, it offers deterrence through credible potential — the knowledge that, within months rather than years, a state could cross the nuclear threshold if it chose to.7

Full nuclear armament for such countries is costly and destabilising: it invites sanctions, diplomatic isolation, and potential arms races. But zero capability is also dangerous if allies waver or geopolitics worsens. Latency is the middle ground: a strategy for building the capacity to act — stockpiling materials, maintaining expertise, investing in civilian nuclear research — so that, if the world darkens, options do exist.

The American economic security toolkit needs an analogue to nuclear latency. The United States should establish an Economic Security Latency Fund — on the order of $20-30 billion — to maintain latent capacity in a bounded set of ‘Tier-2 Critical’ supply chains or capabilities. The fund would not aim to permanently replicate entire industries. Rather, its purpose would be threefold:

• Insurance: The fund would underwrite surge capacity in selected bottleneck capabilities where disruption would be costly but not existential, and where markets alone are unlikely to maintain redundant capacity. It would act as an insurance policy against long-duration coercion or repeated medium-sized shocks.

• Deterrence: Properly designed, the fund would enable deterrence by denial, rather than deterrence by punishment. The aim is not to threaten retaliation through sanctions or counter-coercion (although these tools will also be necessary as part of a wider U.S. arsenal), but to reduce an adversary’s expectation that weaponising a particular dependency will generate lasting leverage. Economic coercion works when the target lacks credible alternatives within the timeframe that matters politically. Latency shortens that window.

• Capability: Latent capacity is not dead capital. If structured well, the fund could generate present-day economic benefits: supporting R&D in critical but under-funded technologies, sustaining specialised skills and engineering expertise. Done right, it is therefore also an economic policy: a targeted bet on capabilities that have both security and productivity spillovers.

To make this work, the United States needs to have a hierarchy of prioritisation to understand where and what type of intervention is justifiable:

• Tier 1: Strategic Autonomy. These are capabilities whose loss would be existential or fundamentally compromise national power: advanced semiconductor fabrication, core defence platforms, key elements of the nuclear fuel cycle. They justify permanent domestic or closely allied control and large-scale, long-term investment, as seen in the CHIPS Act and related measures. Strategic autonomy does not mean full on-shoring but it does mean having significant capability and thereby large upfront investment.

• Tier 3: Market Resilience. These are goods and services where normal market mechanisms — diversified suppliers, inventories, substitution, redundancy — can provide adequate resilience, give or take some R&D tax credits here and there. Permanent subsidy or reshoring would be an inefficient use of scarce resources.

• Tier 2: Latent Capability. Between these poles sits the layer we are interested in: concentrated nodes within critical supply chains where disruption would be highly damaging; substitutes exist in principle but cannot be activated quickly and yet full on-shoring would be economically inefficient.

The Economic Security Latency Fund would operate strictly at this Tier-2 level. Its remit would be limited to a small number of bottleneck capabilities that meet three tests:

1. Low substitutability: few alternative suppliers, long time-lines, or alternatives that are geopolitically misaligned. Substitution would take years, not months.

2. High exposure: the United States imports far more than it exports, meaning limited domestic surge capacity — a replacement ratio or exports to imports well below 1.0.8

3. Strategic value: the good is a dual-use input or systematically important across multiple sectors. High dependence on garlic9 or ball-point pens does not justify latency investments; a severe lack of advanced packaging facilities might.

These criteria allow for a more disciplined approach to the latency fund: rather than asking if this is a “critical sector” (i.e. where payment machines that use AI end up getting caught in the net), policymakers can ask “is this a bottleneck where dependence is both high and hard to substitute, and where latent capacity would materially change the coercive calculus or level of resilience?”

Operationalisation: How The Latency Fund Would Work

A $20–30 billion Economic Security Latency Fund would, by design, be modest compared to the scale of Tier-1 programmes such as CHIPS, but large enough to matter in a defined set of Tier-2 domains. Rather than sprinkling money across every vulnerable supply chain, it would concentrate resources on perhaps five to ten bottleneck capabilities that clearly meet the Tier-2 criteria. For the purposes of this essay, I later provide one illustrative example. The operating would have to vary on a case-by-case basis, but should have some common features.

First, selection and metrics. Two quantitative indicators stand out for identifying potential areas.

• Dependence threshold: where more than 70 per cent of imports of a specific input come from a single source, vulnerability is high. Below that, market diversification provides meaningful resilience; above it, the risk of weaponisation rises sharply.10

• Replacement ratio: The second is the replacement ratio: the value of exports of a given good divided by imports. A ratio well below 1.0 signals that a country lacks the industrial base to replace lost imports quickly; a ratio closer to parity suggests some latent capacity already exists.

Superimposed on these metrics would also be a qualitative risk assessment across exposure, strategic importance, and substitutability — where a judgement has to be made as to whether this falls into the remit of the latency fund (i.e. Tier 2 priority) or Tier 1 or 3.

Second, instruments. Given that the fund’s job is to ensure enough capacity exists for preparedness and a rapid surge — rather than to outright build — a portfolio of tools would be needed. This might include contingent “latency contracts” that pay firms to maintain standby production lines, tooling, workforce capacity, and stockpiles — which would be scaled up on request within an agreed timeline. It could also include investment in modular or scalable facilities, R&D grants for industrial capacity where private returns are uncertain, investment in specialised talent pipelines, and fast-tracked regulation. Realistically, the tools will have to vary in a case-by-case instance.

Third, triggers and thresholds. These are necessary for both domestic and international reasons. Domestically, because tools like “latency contracts” would require pre-determined threshold lines. Internationally, because for economic security latency to have a desired deterrent effect, there would need to be clear conditions under which it is activated — although perhaps with some room for ‘strategic ambiguity’.

These thresholds might be framed in terms of duration (“if access to advanced packaging is cut for more than six months, we will activate domestic surge capacity”), concentration (“if import dependence on a single source exceeds 80% specified inputs, we will invest to reduce it”), or explicit coercive acts (“if we are subject to economic coercion in sector X, we will ramp up production within this timeframe”).

Fourth, if a U.S. latency fund were initially successful, allied cooperation might be considered further down the line. For example, in strategic areas like copper, where the U.S. only controls 5.5% of global reserves but the US, Australia, and Canada combined have more like 17%,1112 it may make sense to build international “latency pool” models: where allied countries with different specialisations and resources can each maintain partial surge capacity that becomes effective in a NATO Article 5 equivalent for economic security (though this is an entirely separate essay in itself).

Finally, there are obviously limitations and necessary further thinking. The first is mission-creep: for the latency fund to work it has to be targeted at between five and ten areas of capacity. Much more than this and it becomes spread so thin so as to become meaningless. Second, on the deterrence side, more serious thinking would need to be done on how transparent the United States should be: too opaque about where the U.S. is investing in latent capacity and the fund does not perform its deterrence function; too much openness and adversaries simply factor those latent capabilities into their calculations and find other gaps to squeeze.

Case Study: Submarine Cable Repair Capacity

Submarine cables carry almost all international data traffic, roughly 99% by most estimates, and underpin global finance, cloud computing, communications, and everyday internet use. The network itself is large and geographically dispersed, with more than 500 active cable systems worldwide.13 The United States sits at the centre of the network, and American firms own or co-own much of the world’s subsea infrastructure.14

Cables are damaged regularly by fishing activity, anchors, earthquakes, wear, and grey zone attacks. The system is built to reroute around single failures, but the real vulnerability is not the cables themselves so much as how long they take to fix. Fixing a deep-sea cable requires a specialised ship, trained crew, and often diplomatic clearance to operate in territorial waters. The global repair fleet is small and ageing. Industry analysis suggests that maintaining current service levels — even without a major geopolitical shock — will require significant additional vessels over the coming decade.15

In an Indo-Pacific conflict scenario, for example, cables serving Guam or linking the U.S. to Asian allies would be obvious pressure points. The current repair system is very much built for one-off breaks not sustained disruption.

In this context, the Latency Fund would focus on shortening repair timelines and building surge capacity in case of a conflict. It could co-finance additional repair vessels alongside industry, structured as surge capacity. It could fund stockpiles of spare cable and landing-station equipment at major U.S. hubs. And it would also invest in workforce pipelines for the specialised crews these ships require. This fits firmly into “market failure” territory, given that private operators generally build for commercial uptime and only recently have begun factoring in geopolitical externalities.

Not only does this act as insurance, it also strengthens the United States’ real-time capability: with more repair vessels and specialised crews the U.S. strengthens its hold over the global cable network. And this also changes incentives. The leverage gained from cutting cables lies mostly in delay. So if restoration is slow, disruption is an attractive option for an adversary. But if repair capacity is visible and actively invested in, then the payoff falls. In other words, the deterrent side is that latent capacity in cable repair makes it less likely that a surge will be needed in the first place.

This fits into the case for latency because it is not clear-cut, top priority “industrial strategy” — but nor is this an area that can be left solely to private actors. Private operators won’t finance idle repair capacity for low-probability shocks. Public policy can, and should.

Conclusion: Don’t build the bomb, have the capacity to

The United States is at risk of fighting the wrong economic security war. Endless sanctions, tariffs, and export controls dominate the toolkit on the offensive end; and heavy-handed, and often counterproductive,16 industrial strategies are creeping in at the defensive end. Both may experience a backlash. Indeed, the former already has.17 The reason why these tools dominate is that they are easy; not in the sense that they are cheap, but they are levers that are easy to pull, and often easier to sell politically. But that is also why they are often wrong. This proposal is less expensive, but it is harder: because it is more nuanced, requires more technical ability, flexibility, and does not make headlines.

The measure of economic power in the coming decade won’t just be how much a country produces, but how quickly it can replace what it loses access to. Speed, in this case, is sovereignty.

Sometimes the best move is not to build the bomb, but to be able to.

More from Guy:

Guy Ward Jackson

Tech | Industrial Strategy | Economic Security | Tony Blair Institute

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Today, the second half of our conversation previewing the summit that just kicked off. With Mythos scrambling everyone’s priors on frontier capabilities, AI safety is suddenly back on the bilateral agenda. Julian Gewirtz (former NSC senior director for China) and Matt Sheehan (Carnegie) join to map how Beijing is processing the shift and what’s actually achievable in renewed US-China dialogue.

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The AI Safety Angle

Julian Gewirtz: Both sides have been signaling that AI will feature prominently in upcoming discussions. During the Biden administration, we pushed hard to get AI safety on the agenda when President Biden met with President Xi. Beijing initially gave us the cold shoulder, but gradually realized there was no major downside to including it on the agenda.

The Trump administration initially showed little concern about AI safety. JD Vance and other senior officials openly mocked AI safety as a construct, making US-China AI safety dialogue a non-starter — the United States didn’t even want it.

What’s changed recently in the Trump administration appears directly tied to the Anthropic Mythos moment. The realization that extraordinary and potentially dangerous AI capabilities aren’t theoretical conjectures for years down the line but exist in the real world right now has made the administration take this issue more seriously.

Both the Chinese and Americans are now backgrounding expectations that AI will come up in discussions, with potential AI safety-related deliverables. During the Biden administration, we pushed hard to get this topic on the leaders’ agenda. China’s initial response was essentially a cold shoulder — they weren’t interested in having the conversation. They felt it was happening in an environment of heating AI competition and were unhappy with export controls and other steps we were taking.

Whether we wore them down or won them over, the topic eventually came up between the leaders. Jake Sullivan also discussed it with Wang Yi. Beijing shifted its approach after realizing this was an area where the world was looking to the two most powerful countries to show leadership. They also recognized there was little downside from their perspective.

When the Trump administration came in, their approach was to dismiss AI safety entirely. You had JD Vance and other senior officials mocking AI safety, saying the administration would stop all “that nonsense” and focus solely on winning. But over the past month, since Anthropic began briefing on the Mythos capability, the administration has begun taking this more seriously. They’re realizing this isn’t conjecture about future risks but actual capabilities in the here and now that open the United States to profound vulnerabilities and dangers.

This creates an interesting and different starting point for renewed conversations with the Chinese about AI safety. One lesson from Mythos appears to be that for both the United States and China, advances in capability cannot be separated from increases in vulnerability. The more capable American models become, the more capable Chinese models become, the more risk, danger, and potential bad actor misuse emerges.

Some people in both countries have fantasized about reaching a point of such dominance and capability that safety issues would become less salient. But we’re learning that vulnerability and capability are fundamentally interlinked.

Matt Sheehan: That was a great rundown of it from the US side and then how the Chinese side looks in that engagement. During the same period of time, I’ve essentially been following the Chinese domestic conversations on this very closely. There’s been a pretty big evolution, partly in response to — largely in response to the development of the technology. But then also in response to different groups within China platforming these issues and then seeing them get some level of traction with leadership.

Maybe if we go back to at least pre-Mythos, because this is so recent, if you had to characterize how the Chinese government thinks about AI safety writ large, whether it’s misuse or control stuff, I’d say it has risen much higher on the agenda. They have essentially put it on the table as a topic that they need to think through, but they haven’t made up their mind on what they think of it.

You saw this has been cropping up in different policy documents. One place was in what they call the AI Safety and Governance Framework 2.0. It’s kind of these two organizations under the CAC, their roadmap for how are we thinking about AI risks? How are we thinking about mitigations, especially as it relates to technical standards?

They had a version of this in 2024 that was just super high level and very light on any, what we would call AI safety related topics. They updated it in 2025. You saw a bunch of changes between the two documents. In one of them, labor featured much more prominently and seriously in it.

Julian Gewirtz: Meaning people losing their jobs because of AI?

Matt Sheehan: People losing their jobs because of AI. In the 2024 version, it was some very handwaving of yes, it’ll restructure social relations and we should think about that. In the most recent one, I’ll miss the exact phrasing, but it said something along the lines of “This will lead to a devaluation of labor relative to capital and social disruptions related,” something like that.

Between these two documents, we saw labor rising a bunch and we saw safety in a few different forms, like misuse and also some of the control, loss of control language featured more highly. When I asked some people involved about this and what does this reflect or not reflect about the policy process over there? I specifically asked about these safety issues and it’s on the agenda, it’s something that we’re thinking about, but we don’t know what we think about it at this point in time. This is going back to September, September of last year.

Fast forward to now and obviously the biggest change has been Mythos. You also have people within the Chinese system that are essentially working to platform these issues. The area that I’m most focused on right now is the technical standards work. A couple months ago, they created an AI safety security working group on technical standards. It’s led by Zhou Bowen, who’s the head of Shanghai AI Lab. That’s one of the more safety-pilled organizations in China. We’re seeing, okay, below the line, underneath the surface, they’re starting to get their mind around these issues.

And Mythos is like the bomb that scrambles this equation. We don’t yet know how the party has actually taken Mythos on board. I’ve heard different things from different people who interact with different parts of the Chinese bureaucracy. Some downplay it, feeling like they’ve got it under control — it’s just a new cyber thing and we’ve been doing cyber things forever. Other people say they actually seem pretty shook about this and want to talk about it.

At least when this is getting tabled for this conversation, my read — not based on inside information — is that this is the US side pushing this as a topic for discussion, not necessarily the Chinese side. I have pretty low expectations for anything in the way of tangible deliverables from these discussions. The idea that we’re going to strike some type of grand bargain on AI where we both agree, “If you don’t do it, then I won’t do it” — we’re both going to be nice, we’ll have a hotline, and we’ll just call each other right away as soon as something goes wrong — I have very low expectations for that.

The effort should go into trying to establish some working level, more technical conversations, specifically on testing and evaluation for safety risks. This gets very tricky with the capabilities and threats dynamic. When you learn how to test a model for certain capabilities, that also might indirectly help you build those capabilities in advance. It gets very tricky, and people in the testing and evaluation world have somewhat different takes on this.

My takeaway from many of those conversations is that there is a path forward for sharing some relatively high-level information about how we test for these risks. There are a few reasons to be doing that. One is that currently, the Chinese frontier AI labs’ testing for frontier risks is nowhere near the level that it is in the US labs. It’s a funny inverse where the Chinese labs face tons of regulatory compliance obligations from their government, and therefore, they’re not tacking on all of this voluntary testing for frontier risks. The US labs, at least historically, have faced very low regulatory burden from the government, and therefore, they put a lot of energy into this type of voluntary testing.

If you take Chinese capabilities relatively seriously — even if we’re ahead and maybe going to get further ahead — their capabilities matter. And the type of testing that happens in China voluntarily within the Chinese system (not jointly testing, but the testing they do for their own national security reasons) really matters. We should try to do what we can to make that testing better, to bolster that part of their system.

Julian Gewirtz: Super interesting. When I hear you talk about this, I wonder what the version of this conversation that could happen at the leader level is, because you don’t have two leaders in this case who are going to be talking about that degree of specificity. We have to imagine, at some level, the conversation will essentially be, “AI matters, we both agree,” and maybe some other people figure out what to do about it.

Jordan Schneider: We were talking at lunch about the idea that even if you’re nine months behind, that means a Chinese lab will have a Mythos thing in nine months. Even taking away the US-China national security angle — NSA versus MSS — there are still criminals in China or around the world who might exploit this. Perhaps nine months from now, the rest of the world will have patched everything, and China will have the most vulnerabilities open to them to do ransomware on water treatment facilities or similar attacks.

The US government, or this administration was able to spend a year and a half dismissing it because it wasn’t really all that pressing. But everyone’s consensus view now is that — whether it’s six months, a year, or eighteen months — at some point in the not-too-distant future, there will be Chinese labs able to create extremely cheap, extremely potent cyberweapons from a domestically trained model. When things hit the fan in China from a domestic perspective, you have to think they’re going to start doing more testing than just checking if you’re saying anti-party stuff.

Julian Gewirtz: It’s fascinating to me because if you go back to the history of how China governed the internet giants, there’s a real similarity. Initially, it was, as long as you do censorship, you’re okay. No images of Winnie the Pooh, no mention of Tiananmen, and we’ll leave you alone.

But then they began to realize that even with that set of technologies, there were systemic risks. This is often shorthanded as the Jack Ma speech and the crackdown that followed on the Alipay IPO, but actually, it was a regulatory storm — a complete 360-degree crackdown on the sector to rein in financial, social, and political risks.

That hasn’t yet happened with the AI sector in China. It has largely been censorship and a few other things, partly because this is such an area of national competition. But that other shoe has to drop. I don’t see a way around it.

Jordan Schneider: What does the political response look like when we see crazy cyber hacks or actual real labor disruption?

Control, Harness, Govern

Matt Sheehan: Yeah, the comparison to the internet era is fascinating — the parallels are striking. So what’s China’s playbook here? It follows a pattern — control, harness, govern. Control means managing the speech implications, censorship, and political aspects of the technology first. Harness is the next phase — once they feel they have control, they focus on using the technology to diffuse and upgrade their economy. Govern represents the more sophisticated approach of addressing knock-on social effects beyond party control.

In the Internet era, control meant building the firewall over the long term. When I moved to China in 2010, there were about two years of relatively wild activity online. Then came the 2013 crackdown on the Big Vs where they implemented policies like making people legally liable if their Weibo posts were retweeted 500 times. This crackdown phase focused on controlling speech and information implications, spanning roughly 2012 to 2014.

For AI, this control phase ran from 2021 through 2023. They first worried about recommendation algorithms and their effect on people’s feeds, then deepfakes, and finally generative AI for similar reasons. They attacked these information problems first.

Once they felt comfortable with control, they moved to harness the technology. In the Internet era, this was the Internet Plus campaign, starting around 2014 or 2015. They launched the “1,000 entrepreneurs and 10,000 innovations” initiative — entrepreneurs and innovators everywhere. Having gotten the internet under control, they encouraged its expansion, leading to a huge explosion in mobile internet services spreading across the economy.

For AI, they’ve resuscitated the “plus” formulation with “AI+.” For those unfamiliar, AI+ means AI+ manufacturing, AI+ healthcare — the same pattern as Internet+ transportation. This represents the harnessing phase: politics controlled, economic diffusion good, or at least on the right path.

The government then asks: How do we deal with the knock-on effects? In the internet era, this meant the Cybersecurity Law, the Personal Information Protection Law, followed by anti-monopoly efforts and the broader tech crackdown.

We’re at the dawn of this phase with AI. They finalized regulation on anthropomorphic or human-like AI in April, addressing concerns about addiction, effects on minors, and psychosis related to AI addiction. It’s very focused on social impacts.

The question now is what comes next. Some will involve hard security and cyber issues, but there’ll also be a broader focus on labor impacts and other societal concerns.

Julian Gewirtz: We haven’t talked much about this, but there’s an important difference in how the Chinese Communist Party is governing the AI sector. One of the main ways they’re exercising control is by not allowing companies to obtain the compute they want from abroad.

We’ll see how this plays out when President Trump visits China, particularly if Jensen Huang accompanies him on the trip. There’s this fundamental tension between Chinese labs wanting to buy NVIDIA chips and Chinese regulators forbidding them from proceeding with those transactions because of geopolitical risks and leverage concerns. This is an interesting version of the governance paradigm, but from a side that we didn’t see the Chinese government worry about in the internet sector.

Some of the same dynamics may be true with investment from abroad. Obviously, if you think about the Manus acquisition debate — which you and I, Matt, have discussed many times before — that’s one where clearly the interests of a company and the government are at odds.

Matt Sheehan: I have a half-baked take I’m trying to bounce off people. You were talking about CBRN cyber criminal actors — non-state actors. This has been central to a lot of US discussions of AI safety. When people want to make these safety risks real, they’ll often refer to concerns about terrorists making bioweapons. I’m not dismissing that as unreal — it could be — but it’s something we go to very quickly in the US.

In China, they’ve been more skeptical of these risks for a while, for a variety of reasons. My half-baked take is that China doesn’t feel itself to be under siege from a world full of terrorists in the way that we do. In the United States, we have a self-conception — which is based in reality — that we are often the victim of terrorism. Everyone wants to get at us from abroad, and therefore, if these models are out there, we’ll be first in line to get CBRN attacked in one way or another from non-state actors.

In China, they say they’re worried about terrorism. Terrorists in their mind are domestic and are from a specific ethnic group in their conception of it. But they’re less worried about foreign non-state actors in the way that we are.

Jordan Schneider: The Falun Gong bioweapon — would you really put it past them? Yeah, I think it’s a bad take.

Julian Gewirtz: I think it’s a bad take, too, Matt. First, the Chinese Communist Party perceives itself as profoundly under siege and has a paranoid mentality that is absolutely central.

Jordan Schneider: Let’s start with Xinjiang. According to some narratives, the policy shift was initially triggered by concerns about foreign ideological infection and terrorist elements coming from abroad. What else do you see as problematic with this framing?

Julian Gewirtz: The Chinese Communist Party under Xi Jinping has the most catastrophic worst-case scenario planning mentality of any regime I can think of. Their relative lack of concern about chemical and biological weapons and AI stems more from assumptions about how AI differs from existing capabilities — and those assumptions may be changing — rather than from any lack of concern about external threats.

Over the past decade, I’ve seen the CCP become increasingly fixated on the idea that nefarious forces are out to get them.

Matt Sheehan: To clarify, when we talk about being under siege, it’s from non-state terrorist groups. The paranoia is intense, and the feeling of being under siege is real, but they’re usually talking about the United States of America. That’s fundamentally different.

Both governments should assume the other will use AI in every possible way to gain state-to-state advantages. But concern about non-state actors differs significantly between the two countries. Someone who focuses on Southeast Asia, the Golden Triangle, and the scam factories there might see this very differently.

With CBRN stuff, there’s a big distinction between state and non-state actors, and their paranoia focuses on the United States.

Julian Gewirtz: Here’s a comparative question — where does Japan fit into this framework? They’ve actually experienced a sarin gas attack. The United States has experienced horrifying terrorist attacks, but not specifically chemical or biological weapons attacks. Some societies have experienced these kinds of attacks firsthand.

I wonder whether Japan’s degree of anxiety about AI risk is heightened because of its experience, or not. If it maps similarly to other countries, then perhaps the alternative hypothesis — that concerns are mostly about AI capabilities rather than threat perception — is more accurate.

Jordan Schneider: I’d also say public discussion about organized crime or terrorism in China is heavily constrained. These conversations happen privately, but discussing them publicly on WeChat or Xiaohongshu is impossible. You can only discuss them in the context of announcements about arrests that have already been made.

Julian Gewirtz: As I think about it more, there’s no doubt that the AI safety community has talked extensively about chemical and biological weapons risks. But when I see what’s really driven actual concern about AI safety in broader society, it’s effects on kids, deepfakes, and similar issues. From a national security establishment perspective, there’s concern about use in warfare, and perhaps most fundamentally, this idea of out-of-control systems — a loss of human control.

I wonder whether the community that has held the candle for these risks, centered partly on CBRN risks, actually represents how most Americans think about AI risks. There is polling on this we could look up, but I doubt CBRN risks would be in the top three AI concerns for Americans.

Matt Sheehan: I totally agree that the average American, even the average policy world person, isn’t putting these risks top of mind. Within the community that’s been pushing the message that these systems are getting really dangerous really fast — not in a diffuse social impacts way, but in a safety way — that’s where these concerns are centered.

Jordan Schneider: It comes down to the binary of whether something is an existential risk or not. Cyberattacks aren’t existential risks. Labor disruption isn’t an existential risk. You don’t necessarily have those funders and people focused on existential risks clocking those sorts of issues as much. The whole existential risk framing hasn’t bled into the Chinese discussion nearly as much as it has at Berkeley and beyond.

For part 1:

Julian Gewirtz, former Biden administration China official, now at Columbia, joins me to chat about the Xi-Trump visit and all things US-China. Matt Sheehan, senior fellow at the Carnegie Endowment for International Peace, drops by to give his takes on the AI angle.

We cover:

• What to expect (and not expect) from the Trump-Xi “stalemate summit”

• Historical echoes from the 1793 Macartney mission and the 1972 Nixon-Kissinger opening: summit optics, status games, and the choreography of power.

• Taiwan: arms sales, declaratory language, and Beijing’s long game on Taiwanese morale and politics.

• The good and bad case for China in the Iran conflict, and how Chinese officials may be reading America’s military commitments, political cohesion, and staying power.

• The US-China AI safety conversation after Mythos, China’s approach to frontier AI risks, and the control, harness, govern playbook for emerging technologies.

Listen now on your favorite podcast app.

Seriously, listen! Way more people subscribe to this newsletter than listen to the podcast directly.

But Julian has a wonderfully sonorous voice. By just reading the transcript you will be missing out!

Leverage, Political Will, and Deals

Jordan: Let’s talk about leverage between the two countries and the two leaders. What’s the right way to think about this?

Julian Gewirtz: President Trump is going to China in just a few days. This question of leverage is at the center of everything for both sides.

Historically, we’ve thought that the United States has a lot of leverage over China, and we can exert that leverage and that also shapes the strategic dynamic between the two countries. But over the last year and a half, you have seen China exerting leverage to an unprecedented degree. They’ve used critical minerals, instituted a global export control regime, and employed other forms of leverage as well. That has had the effect of putting the United States on the back foot.

We spend a lot of time thinking about who has which choke points, what are the areas of leverage that could be used in the next stage of this standoff? That’s really setting the backdrop for this summit.

But I keep returning to the fact that one of the lessons of the past year and a half is that political will and staying power — those questions are as important as who has what choke points. You can have a choke point, but if you can’t use it, if you can’t find the political will to use it and to sustain it, then it’s not worth very much. We saw that with President Trump’s tariffs. And of course, we’re also potentially going to see it with his relaxation of some export controls on semiconductors.

I have gone back recently to one of the most famous passages from the collected works of Mao Zedong. I went back to Mao because he’s had such a shaping influence on Xi Jinping. The famous passage is the one in which he describes the atom bomb as a paper tiger. This is in an interview with a journalist. He not only calls it a paper tiger, but he then explains why. Of course, he acknowledges that it’s a very powerful weapon, but he says ultimately what determines the outcome of a war is not simply one or two weapons. It is the people, the political will, cohesion and staying power of the people. This idea of people’s war from Mao, which shapes his approach to the United States then, is also shaping Xi Jinping’s approach to the United States today.

Jordan Schneider: Is Mao right?

Julian Gewirtz: Mao is literally wrong. He’s wrong about the power of nuclear weapons. His dismissal is a posture that he strikes at a time when China is working intently to develop nuclear weapons, and of course, ultimately does. And Mao is very proud of that achievement. So this is a posture of a country in a relatively weaker position at that time.

But he is right in a broader sense, particularly at the metaphorical level. We’ve seen that in a sustained competition between two very powerful countries, questions of capability always have to be thought about alongside questions of the ability to actually deploy a particular asset or choke point.

One of the things I worry about most in the United States is our polarization and political tensions. We’ve seen a real challenge with either party mounting the kind of sustained long-term effort needed to mobilize aspects of our economy that would need to be deployed effectively over the long term against a quite formidable competitor in China.

Jordan Schneider: Given Trump’s current position, what’s the right way to think about what’s actually going to happen over the next few days?

Julian Gewirtz: The way I’ve been thinking about it is that this is a summit taking place during a stalemate. It’s a stalemate, not an end to a protracted competition. For each side, there are somewhat different objectives, but from Beijing’s perspective, this is a test of wills during a lull in a long and intense competition.

It’s a stalemate summit, but we shouldn’t be mistaken by the decrease in tensions to think that just because we’re in a period of de-escalation, at least from Beijing’s perspective, they’re not approaching this in a competitive mindset. They certainly are.

Jordan Schneider: Let’s stay on that stalemate summit concept. There have been plenty of stalemate summits that have made history during the Cold War and beyond. Is it remarkable that they’re taking the time to meet in the first place?

Julian Gewirtz: Both President Trump and President Xi understand that their leader-level diplomacy plays into the overall dynamic between the US and China. If they don’t meet, if they don’t put this dynamic of stalemate into practice through what comes out of their meetings, as we saw when they met in Busan last year, then things can go off the rails very easily.

President Xi wants this period of stability in the US-China relationship so that he can continue buying time, strengthening China’s capabilities. He’s also hoping to get some concessions from President Trump.

From President Trump’s perspective, he has a very complicated situation around the war against Iran, which has certainly not gone as planned, or perhaps not quite as planned. He also seems to want a period of stability in US-China ties.

We know that President Trump is already teeing up a message around this summit that it’s going to be a huge win. He said the same thing when he and Xi Jinping met in South Korea last year, as I mentioned. At a time when the international landscape is very low on good news for the United States, he’s clearly hoping to trumpet this meeting with Xi as a win.

Jordan Schneider: It’s weird. He’s not going to a meeting and saying, “The way the White House is trying to frame this is interesting.” On one hand, they’re setting low expectations — no deals, nothing’s actually going to happen. Asking CEOs to join five days before seems rushed.

Julian Gewirtz: I think the CEOs have been saving the date. There’s an interesting dynamic where we don’t know exactly who will be on the business delegation. We know that President Trump loves a business delegation. His trip to Saudi Arabia had a massive one last year.

Jordan Schneider: It’s just part of the traveling circus for him. It’s not a party unless you can snap your fingers and have Tim Cook or whoever “new Tim Cook” is show up.

Julian Gewirtz: The basic point I keep returning to is that President Trump has long viewed US-China rivalry as primarily an economic rivalry. Back in 2000, when he explored running for president on a third-party ticket, he was hammering the WTO. He was hammering China for being an unfair trading partner of the United States. These themes have always been there.

He’s always been less animated by the security concerns that, for many folks in Washington, are the core of the China challenge. He’s certainly less animated by human rights concerns that have been core to the US approach to China for a really long time.

When he goes to China, he’s going not simply as dealmaker-in-chief, as he likes to be called, but through this paradigm of “this is the world’s other largest economy.” They have over a billion people. They’ve got a ton of money to throw around. All the business leaders he talks with care a lot about either access to that market or competition from that market. For him, those are the four corners of the square.

Jordan Schneider: It’s funny — what would another president over the past 30 years do in the context of this trip, especially with the Dalai Lama being 92?

Julian Gewirtz: You don’t have to go too far to find that counterfactual. Just look at how the Biden admin approached these issues. Many of the changes in US policy toward China that we’ve seen over the past year and a half during this administration aren’t changes where there was a massive constituency pushing for bigger purchasing commitments. That’s always been there. Trump is going because he wants to approach the relationship this way himself, overriding the instincts of many of his advisors.

Jordan Schneider: Would Biden have gone if there wasn’t COVID?

Julian Gewirtz: It’s an interesting question. I was thinking about the last time President Trump went to China in 2017. That was a very different time in the US-China relationship, and it’s worth pausing to consider that context.

Many of the themes were very similar. President Trump wanted a good relationship with Xi Jinping. He brought a bunch of CEOs. He wanted a big set of purchasing commitments and other economic deal-making. This was before the real launch into escalation in the US-China trade war.

He was blown away by what he saw he still talks about it. He talks about the pageantry, how much he loved the grand reception that Xi Jinping gave him. He’s even talked about how all the soldiers who greeted him were exactly the same height, and you could send a billiard ball down their hats, which is exactly the kind of thing that my brain could never generate, but here we are.

That’s all the backdrop for this trip. It used to be a much more standard-issue thing for US presidents to go to China. One of the key things to remember is even in the Obama administration, the main reason that presidents went to China was because there would be a multilateral meeting a meeting of APEC, the G20, in China and that would anchor a president’s trip. That’s obviously not the case this time. It wasn’t the case in 2017. We know Trump is much less interested in multilateralism than his predecessors and wants that bilateral contact.

The Long History of Summit Theater

Jordan Schneider: Let’s do a tour of past delegations to China.

Julian Gewirtz: As I’ve been thinking about this summit and why it’s such a distinctive and interesting thing to have an American president go to China — why it’s different than an American president going to France or Mexico or any of the many countries that presidents visit — it’s partly because of this incredibly rich and fraught history of diplomacy with China by the United States and other outside powers.

As we think about the visuals that Xi Jinping wants to construct, what’s at stake for Xi Jinping as the host, and what’s at stake for the United States in the interactions that they’re going to have, I’ve been thinking back to a few moments in history. I’m a historian by training and have written a couple of books of history. It’s worth examining some of these historical precedents because they really directly inform what we’re going to see unfold next week.

The first defining early mission to China is George Macartney’s in 1793. He goes with a set of economic, trade, and diplomatic objectives. He goes to meet with the Qianlong Emperor of the Qing Dynasty. This is obviously after the United Kingdom has lost its American colonies, but of course, it still has a global empire.

The delegation has several central immediate problems, and it’s remarkable to me how these themes, in a very different, now obviously post-imperial context, extend. First, Macartney is asked to perform the ritual bow, the kowtow, to the emperor, and there is unbelievable negotiation and tension simply in the optics.

There are cartoons in the British press making fun of Lord Macartney’s willingness to be placed in a lower position. He’s not willing to perform the full bow, but he does certain other gestures.

These questions of status, visible status, and the performance of status, almost as a matter of both high politics and ordinary protocol, are at the center from the very beginning. We’re going to see that again with Xi Jinping and Trump — the question of who’s standing where when they shake hands, what are the visuals as they walk alongside each other.

Ironically, President Trump is perhaps as sensitive to this as any world leader in history. He’s thinking this way, too. That will be on display.

The second is famously the posture that the Qianlong Emperor takes — one of haughty and superior rejection of the British offers. There’s this famous passage where the Qianlong Emperor writes to George III — “Our celestial empire possesses all things in prolific abundance and lacks no product within its borders. There is therefore no need to import the manufactures of outside barbarians in exchange for our own products.”

Now, Qianlong is posturing. Obviously, there are plenty of things that the British have at this point that China doesn’t, but that posture, that theme of self-sufficiency, self-reliance, not wanting to be dependent on, not wanting to draw in, and increasingly in this era, feeling that China can surpass the United States — Xi Jinping’s not going to say those words, of course. This was almost 250 years ago. But those themes are very much at play in a very interesting way.

There’s a great book on this by Henrietta Harrison called The Perils of Interpreting, about the interpreters who were charged with running between these guys and I will just end this particular historical vignette by saying one of the most interesting positions of anyone in the world today is the people who are going to interpret the conversations between President Trump and President Xi. Some of those conversations will happen in the big plenary room, but others will happen as they take a walk, or have a one-on-one dinner, or sit down for tea, etc. Those people, the interpreters, are going to be conveying a remarkably important set of messages that could pertain to the future of Taiwan, of US technology controls, of trade, of each political system. It’s one of these critical jobs in the context of a summit.

Jordan Schneider: First of all, the idea that visuals matter even before you had photos. The visual aspect is fascinating because politics has always been about optics and setting. It mattered even 250 years ago.

But those talks weren’t ultimately one-on-one leader conversations – they were more like at the assistant secretary level. So, let’s talk about Taiwan, with the give and take it entail. Why don’t you give us the context of what people are thinking about with Xi and Trump for this trip regarding Taiwan?

Julian Gewirtz: There’ve been a lot of questions about whether Xi Jinping is planning to use this trip and other upcoming diplomatic engagements this year — including potentially a reciprocal state visit to the United States — to press on the question of US support for Taiwan. This involves both declaratory aspects (the statements the United States makes about Taiwan’s political aspirations and independence) and material support.

The standard US formulation has been that the United States does not support Taiwan independence. This has been our position for many years. The Chinese formulation is to oppose independence — much stronger language. There have been plenty of media reports that this is something they’re pushing on now.

But it’s not just about declaratory language. It’s also about arms sales — the material support that the United States is obligated to provide Taiwan under the Taiwan Relations Act. We know that Beijing has been pressing the administration to curtail that support. They did move a significant arms sale at the end of last year.

One thing we know Xi Jinping is going to raise is his concerns about Taiwan and US support for Taiwan. Candidly, it’s anyone’s guess how President Trump is going to react to that. At various times, he has been more critical of Taiwan than any other president in a long time. There’s anxiety in strategic circles in many countries around the world about how this conversation could play out.

Jordan Schneider: Can we role-play this? If you’re the Chinese translator, you’ve been workshopping this. They must have gone through so many iterations of various approaches. If you’re at a table with ten people on one side and ten people on the other side, the amount you’ll be able to get out of Trump is probably what he’s already agreed to. Everyone on the flight over is rehearsing — here’s what we’re going to do, here’s what we’re not going to do. If I were in their shoes, the walks and one-on-one sessions would be the time to see if you can push them a little further and reframe the issue.

Julian Gewirtz: It’s worth saying what the goals are from Beijing’s perspective.

Their approach is gradual rather than dramatic. They’re unlikely to seek an overnight shift in how the United States approaches Taiwan, particularly given Congress’s strong feelings and decades-long leadership on Taiwan issues. Instead, they’re employing what we call “salami slicing” in the South China Sea — pushing incrementally to change the overall dynamic over time. That’s their goal.

But their audience, crucially, are the people of Taiwan. While some in the American foreign policy community argue that minor changes in language don’t matter much since US. If policy remains fundamentally unchanged, this perspective overlooks how differently these shifts are perceived in Taiwan. For people living there, whose futures depend on these intricacies, such changes carry enormous weight. China’s current efforts to influence Taiwan’s politics and demoralize its population are central to their overall strategy, especially with Taiwan’s presidential election coming in 2028. I hope those briefing the president understand this nuance, though I have my concerns.

The “Most Important Meeting Since 1972”

Jordan Schneider: Do you want to do some more history?

Julian Gewirtz: The defining image of US-China summitry remains Nixon and Kissinger going to China — Kissinger’s secret trips, then Nixon’s 1972 visit to meet with Mao and Zhou Enlai. This marked the beginning of the shift in America’s approach to China and the development of the engagement policy.

Those images of American leaders sitting in big stuffed chairs with Chinese leaders, discussing world order and shifting history’s tectonic plates in real time, continue to animate successive generations of policymakers. This includes both those from Kissinger’s lineage and his critics.

The Chinese understand that for Americans, dealing with China represents the terrain of grand strategy where the stakes are high. They know these historical images remain in American minds. But of course, Trump has been different from his predecessors — less interested in grand strategic conversations and more focused on deal-making.

This creates interesting questions — what does US-China diplomacy at the leader level look like when it’s driven by relentless transactionalism within a competitive framework? It will likely differ significantly from those iconic images of leaders sitting side by side in stuffed chairs that defined the Nixon-Kissinger era.

Jordan Schneider: The Nixon-Kissinger legacy really hangs over all of this. Everyone wants to be remembered in history for having shaped the world, right? What better way to do that than to make peace between the US and China?

This brings us back to the stalemate concept. Even if you really wanted to change things and were better briefed, more focused, and didn’t have a war in Iran and everything else going on — what’s your read on this? To what extent can these structural tensions be overcome fundamentally if you’re a president who really wants to bend things differently?

Julian Gewirtz: One way I think about that question goes back to something I mentioned earlier — the idea of a stalemate only makes sense in the context of an ongoing conflict or competition.

It’s important that we not conflate a period of decreased tensions with a fundamental shift in the strategic dynamic between the United States and China. China still sees all the same challenges emanating from the United States over the long term, even if they’re buying time and decreasing tensions in the short term.

Candidly, even in the United States, President Trump may have his areas of focus, but the structural dynamics of competition are continuing. China is continuing to engage with Iran, for instance. The US Treasury has sanctioned some new Chinese entities, and in response, China has deployed new legal instruments that essentially tell those entities not to comply with US sanctions. All of this is still happening during this period of stalemate.

It’s actually part of how Mao Zedong historically talked about what a stalemate is in the context of a conflict — fighting continues, but tensions are lessened.

Around the summit, I’ve noticed one line of commentary that’s really building it up. I read an op-ed this morning — I won’t name names — but somebody was saying this is going to be potentially the most important meeting since 1972. There’s a chance we see that kind of rhetoric coming out of the administration.

Jordan Schneider: Should that be the headline of this podcast?

Julian Gewirtz: Jordan, if it’s the headline…

That’s obviously boosterism, which I find highly unlikely. There’s a downside scenario where this summit becomes very important, as I was alluding to. On the upside scenario, I don’t really see it.

But there’s another line of argument that I find troubling — the idea that we should be intrinsically upset about being in a period of de-escalation. While I am concerned for reasons I’ll explain, it’s not as if the metric of competition is escalation. You don’t get paid by the escalation if you’re competing. That’s a silly way to think about it. Escalation is a tool and sometimes a consequence of other policies you have to take for your own interest.

What’s interesting now is that you could imagine a period of de-escalation being very much in the United States’ interest if we were using that time to shore up our strengths at home and abroad.

What concerns me most about this period of de-escalation is precisely that the United States under President Trump has been using this time to weaken those sources of strength. We’ve been engaged in this war in Iran that has alienated partners around the world, spent down a tremendous amount of our stocks, and made many countries see us as acting irresponsibly and illegally.

At home, if one of our core strengths is going to be our lead in AI, the administration last month had a spectacular blowup with Anthropic, the company that possesses the world’s best models right now. We’ve used this period of de-escalation not to build up our own strengths, but actually to undermine them further. This is the classic case of a win-win for China — China wins twice.

Jordan Schneider: On Anthropic, from a KPI perspective — if our KPIs are national power, global influence— I think even that one we can put as a blip. The fact that us two policy nerds sitting here are going to be over-indexing on the decisions that governments and capitals make...

Julian Gewirtz: I don’t disagree with you about that, but the other really important thing to remember is that if that over-indexing is true of us, the same over-indexing is also happening in Beijing among Chinese officials who watch the United States. The stories they’re telling themselves and briefing up their chain to the leadership may be similarly skewed.

Even if it’s true that this is just a blip and the US lead is more important than this infighting or these attacks on our sources of strength, one of the most revealing passages I’ve seen from Chinese leadership over the past year came at the end of last year. Chen Yixin, China’s Minister of State Security, wrote a long essay on national security in China.

To be clear, when Xi Jinping talks about national security, we often think of it as the military apparatus, but the state security apparatus is actually at the absolute heart of it. Chen Yixin gives this assessment of the United States — “Its democracy is mutating, its economy decaying, its society fracturing at an accelerated pace. Abroad, its credibility is rapidly going bankrupt. Its hegemony is crumbling, and its myth is collapsing.”

This is propagandistic rhetoric, no doubt. But I worry that this is quite similar to what he would say in his briefing to Xi Jinping, who is only getting information through these kinds of sources. We should take seriously the idea that multiple realities can exist at once, and that Beijing is seeing a version of reality that may be closer to some of the worries we have because it fits a triumphalist narrative that several senior people in China already hold.

It’s the kind of thing that makes this upcoming summit so important. When I was in the Biden administration, and we would prepare President Biden, National Security Advisor Jake Sullivan, or Secretary of State Tony Blinken for their meetings with the Chinese, one of the things we were always thinking about was that they were getting information from these interactions. They’re actually learning about the United States and how we see issues. We’re approaching this in an environment of very low to almost no trust.

Jordan Schneider: But these are data points.

Julian Gewirtz: They are data points. Even if they’re looking at them with a lot of suspicion, they’re still looking at them. They will certainly be approaching the meeting with President Trump that way.

For instance, I wonder what exactly they will make of some of the things we know he has said in past meetings with Chinese leadership — all kinds of things about his domestic political opponents. There were reports in John Bolton’s book that he talked about Xinjiang and gave Xi Jinping the go-ahead to build the camps. There’s a record of people who’ve been in those meetings with President Trump coming out with a lot of concern about what went down.

To my mind, that’s all data that China is taking in, that Xi Jinping is personally taking in. It’s why this meeting is so high stakes and so potentially dangerous.

Jordan Schneider: You mentioned Jake Sullivan — Alaska’s definitely one of the ways this could totally fall off the rails. I see two really crazy downside scenarios. One is the scenario you alluded to, where he just starts giving the house away because he’s in a good mood and they serve him the right cut of steak or whatever. The other is that he’s cranky, this war is pissing him off, he’s jet-lagged halfway across the world and just decides, “I’m sick of these guys, I’m gonna start a fight.” To be clear, that’s very low probability. But how are you thinking about the really surprising downside outcomes of this?

Julian Gewirtz: I worry more about the former scenario. I worry about a scenario in which Beijing is able to extract concessions.

Jordan Schneider: And look — it’s not his thing. He picks fights with Zelensky, right? In person, he’s never done an autocrat in-person fight before.

Julian Gewirtz: I’m not in the business of the psychoanalysis of Trump, but I do think it’s pretty clear that he sees some leaders as peers and has admiration for them, and then he sees some other leaders as beneath him and treats them terribly. Xi has clearly been in that first category.

Even just over the past 24 hours, he’s reiterated what he describes as their friendship, and he says it’s going to be an amazing meeting. He is very much in that mode, I think.

Two Briefings on Iran

We should talk about Iran a little bit because it is the key context here, and will be a key subject in the discussions. The reality, to my mind, is that for President Trump, the primary way in which the war in Iran will affect his approach to this trip to China is that he wants a win. It’s, at some level, simpler than the detailed machinations. President Trump wants a win. He wants numbers that he can trumpet, bringing home the bacon for Americans, and he wants to be able to say, “I’m on the world stage with the most serious leaders who exist, these tough guys, and they take me seriously.”

Jordan Schneider: Yeah, it’s so funny because for decades that was the inverse, right? If an American president meets with you, that means you’re doing something right, or you have that global gravitas. But now Trump is seeking that — he can’t get that from having a great G7, right?

Julian Gewirtz: Well, I would argue he absolutely could. He’s just clearly not.

One exercise I often do to pressure test my assumptions and think about how Beijing’s perspective on world events might differ from American views is to construct competing briefings. Imagine two officials — one who has to brief Xi that the war in Iran is good for China, and another who argues it’s bad for China. How would these briefings go?

The briefing to Xi Jinping that the US engagement in Iran is good for China would go something like this — “President Xi, China is better prepared than almost any country in the world to endure this conflict. While we would prefer it to end, the disruption brought on by these reckless actions is negative, and you have prepared China to endure what you’ve called ‘extreme circumstances’ and ‘bottom-line scenarios.’ We are better positioned than any other country to weather this storm.

“There have been significant benefits to our clean energy sector. The world is surging with purchases because they believe clean energy — the energy of the future from China — provides more stability for their economies than traditional energy sources. The world is also looking to China as a diplomatic source of stability and even as a mediator in this conflict. These are profound indicators of how the world sees the relative balance between the United States and China, viewing China as a responsible great power.”

“While there have been concerning disruptions to the Chinese economy, the whole world is experiencing these disruptions. They’re unlikely to erode China’s manufacturing position over the longer term.”

The briefing would continue — “The United States may be demonstrating military capabilities in abundance in the Middle East, but they’ve moved strategic assets out of Asia, including the THAAD system that China has complained about for years. They’re using enormous quantities of expensive munitions in this war that will take considerable time to restock — a reminder that their defense industrial base is much weakened, even if they remain an impressive military force.”

Finally, this hypothetical official would make a point about timing: “President Trump is coming in just a few days. If the end of the war appears tied to his trip to China — which he’s talking about very actively — it will provide China with an unexpected diplomatic windfall. It will appear that the forcing function for the United States was President Trump’s desire to meet with you, President Xi. Additionally, the fact that China just hosted Iranian diplomats in Beijing, with Wang Yi hosting them, will appear to be a facilitating factor as well.”

That’s the version of the good case for China.

Jordan Schneider: What’s the official argument that this is actually terrible for China?

Julian Gewirtz: This was harder to construct, but here are a few points. China needs a stable global economy to continue powering its economic rise and keep everybody moving in the same direction. This war has fundamentally disrupted the flow of global commerce. It has made inputs to Chinese industry more expensive, particularly petroleum-derived products, and caused global markets for China’s exports to pull back and tighten belts. This will also limit the overseas expansion of Chinese industry.

Second, this hypothetical official would have to acknowledge that China has not been able to protect its friends in Venezuela or Iran. Now — this is me interjecting — I don’t think those countries thought their relationships with China were mutual defense treaties. But we do have to acknowledge that it has shown the limitations of China as a partner.

Finally, and perhaps most importantly, beyond the economic side, they’d have to acknowledge the impressive display of the US. military’s capabilities, including AI-enabled capabilities. We’ve actually seen the same Minister of State Security I mentioned earlier acknowledge this as the future of warfare. They are, like Ukraine, watching closely and taking notes. The untested PLA has to be feeling a bit of insecurity in relation to those capabilities. But when you compare the two cases side by side, the argument for this being good for China, net-net, despite some negatives, is pretty compelling.

Jordan Schneider: When Trump asked Xi for help to open the strait and pressure Iran — we’ve had decades of this in a North Korea context, which is maybe the closest analogy.

Julian Gewirtz: Though Xi Jinping has come out and said he wants the Strait reopened, the question is whether China is really prepared to do anything about it. Candidly, they have not been nearly as willing as the Trump administration hoped they would be. This is a reminder that while China wants stability in the global economy and wants the Strait open, they also don’t want to put themselves in a position of heightened risk, heightened exposure, or candidly even partnership with the United States to affect that outcome.

The leverage China has with Iran differs significantly from its relationship with North Korea. This nuclear issue represents the Iranian regime’s top priority, and Chinese influence — while perhaps marginally useful — operates within fundamentally different dynamics compared to the DPRK situation.

A preview for paid subscribers: why Anthropic's Mythos disclosure may have done more to put AI safety on the Trump-Xi agenda than two years of Biden-era diplomacy, what China's own AI governance roadmap looks like heading into its third phase, and where Matt and Julian disagree on how Beijing weighs CBRN risk.

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The “love tap” White House readout. A failed convoy operation. KSA pulling overflight rights. Iran with 70% of its missile force still intact. And one F-15E shoot-down from absolute disaster. Retired Air Force Lt. Gen. Jack Shanahan, the founding director of the JAIC, joins the WarTalk crew (Bryan Clark, Eric Robinson, , ) for a postmortem on a weird week in the strait.

We discuss…

• Why Project Freedom failed

• Whether this war is “bereft of strategic thought”

• Steelmanning Midnight Hammer and the cul-de-sac the administration walked into

• 70% of Iran’s missile force still standing, Saudi economic exposure, and Iran hitting AWS data centers

• F-15E losses, electronic warfare, and the lessons we’re not absorbing for the Pacific

• Why we’re not seeing offensive cyber against Iran and what that tells us

Listen now on your favorite podcast app.

It Was a Love Tap

Jordan Schneider: This has been the murkiest week we’ve had in a while, right?

Bryan Clark: Absolutely. The White House has announced that the war is over as well as continuing in a new form. It was a “love tap,” it was a trifle. It’s a whole smorgasbord of military operations.

Justin: These shootings do not equate to a ceasefire being broken.

Bryan Clark: Exactly. Like if you went to tea at the Langham in London. So the latest — the leverage Iran has right now is the closure of the Strait of Hormuz. The US saw an opportunity to say, well, if we can erode that leverage, maybe we get a better position in negotiations. The gambit was an escort operation on the cheap.

Back in the 80s, in the Tanker War, the US Navy had to escort shipping through the Strait with dozens of warships interspersed among convoys, defending against missiles, small boat attacks, and mines. Shipping companies had to flag their ships under US flag and have US warships next to them as bodyguards. It was a large undertaking.

The administration didn’t want to pursue that level of effort this time. They tried to convince shipping companies to join a sort of convoy of convenience — a couple of US warships leading them out, commercial ships falling in like ducklings behind. If that worked and Iran didn’t attack, you’ve called their bluff.

Well, shipping companies didn’t find it credible. The level of protection wasn’t sufficient, and the US wasn’t willing to flag their ships. So they begged off. The only two ships that came out were two US-flagged Maersks that knew they’d be protected no matter what. The US took out some Iranian small boats and a pretty good number of cruise missiles and drones launched at the warships and commercial ships. Those threats were neutralized — but the rest of the 900 or so large ships in the Persian Gulf are still there.

One complicating factor: the Kingdom of Saudi Arabia decided not to allow basing or overflight rights for US forces doing this defense operation, which really constrained the air power available. Without that air cover, without willingness to put Navy ships at risk in larger numbers, it just wasn’t credible. The US, to save face, said we’re going back to the negotiating table — Pakistan and Saudi Arabia have asked us to. It was a nice way to walk it back without looking like you’re running home with your tail between your legs. But in a lot of ways, it was a failure.

Eric Robinson: 20,000 sailors are aboard those vessels. Bryan — about a month ago, there was robust commentary about how MBS was aggressively advocating for increased military action, that between Riyadh and Abu Dhabi there was this percolating assumption that if you’d breached the peace and gone to war, you might as well try to finish off the regime. What transpired in the past month that has led regional stakeholders to back off? Or was that original viciousness not particularly well-sourced?

Bryan Clark: Probably a combination. We met with MBS back when he was defense minister as part of the effort to sell multi-mission surface combatants. He seemed very savvy, very knowledgeable. I find it hard to believe he’d be so naive as to think the Iranian regime would fall just with sustained firepower from US and Israeli air forces. So I think it was probably not that well-sourced at the start. And then in the last month, we’ve just seen evidence that the Iranians aren’t going to fold.

Justin: I think this speaks to two things. One is that the preeminence of an air campaign alone was never going to be enough to capitulate Iran. And the coalition building necessary to even sustain those operations — we didn’t have those conversations already in place. Like, hey, if they try to close the Strait, this is what we’re going to do, this is the access we’re going to need from Saudi Arabia and UAE. And then as soon as Project Freedom gets launched, UAE gets hit. Iran is denying it was them. So there’s also the question of what else is going on in this area where maybe KSA is like, hey man, stuff’s getting wilder than we’re prepared for.

Bereft of Strategic Thought

Jack Shanahan: A couple of things. First of all, it’s become evident that all I have to do is come up with a new name and you get another 60 days. So we’re going to see a lot of different names used to get around the War Powers Act, which is crazy by itself.

But to a broader point — I’ll never forget being in a meeting in Secretary Mattis’s office, not long before he resigned. Wasn’t a meeting I had to be at, but I was in. Very small group, OSD policy was there, and he was clearly tense. Came back from the White House. The discussion was about Russia, and the OSD policy people were in a good mood saying, here’s what the administration wants to do.

He was terse. He picked up this paper they were talking about and said, “This paper is bereft of strategic thought.” Very classic Mattis. This operation is bereft of strategic thought. We don’t know what the end state is. They’ve tried to explain it 15 different times, but it’s a variation on a theme and nobody can understand. I feel bad for the people doing the targeting because they’re going to do what they were told to do. But if anybody’s trying to ask, what are we doing — the connection of ways and means against what strategic end state — I don’t have a good answer. Right now it appears to be the Strait of Hormuz is open, and I can’t get much beyond that. Maybe enrichment is under negotiation — how many years, with complete obliteration to, well, maybe 10 years.

Without that clarity in strategic end state, this is not going to end well. Sourcing is a little unclear, but UAE may have been attacked again by ballistic missiles and drones it successfully defended against. And Bryan, those US naval ships were attacked, successfully defended, but we’re one inch away from catastrophe if you successfully hit one of those ships. And it will not be hard to do because they still have plenty of fast boats, drones, and other capabilities.

If we end up killing American sailors on these ships, that is going to make a turn I don’t think we’re prepared for. The president used a phrase yesterday I’m trying not to read too much into — that there will be “a bright glow” coming from the country should Iran successfully attack one of our ships. That sounds to me like he’s suggesting nuclear weapons. That is not a path we should be walking very far down.

Eric Robinson: Didn’t the president come out and say he wanted to buy the HEU?

Jack Shanahan: I’ve heard a lot of different things. One is, it’s so far underground they’re never going to get it. Two, they’re going to give it to us. Three, well, maybe we can pay for it. The response from the Iranians has been clear: no, we’re not giving it up.

Tony Stark: Well, to be fair, if anyone knows the market rate for highly enriched uranium, it’s the Pakistanis. So we’ve got the right negotiators.

Bryan Clark: AQ Khan, exactly — he’s our negotiating partner. To Jack’s point, that’s the reason we didn’t do the full meal deal on the escort mission. It’s inevitable that one of these ships gets attacked if you put them in contact with Iranian forces long enough. And the US doesn’t want that visual. They’ve built up the expectation that this is a risk-free operation. There hasn’t been a strategic rationale that would justify having a lot more casualties. They’ve backed themselves into a corner where they can’t mount any operations that are higher risk.

I’ll note one other thing from Navy land. The passage US ships have been using, right next to Oman, is pretty narrow. They’ve identified that as an area free of mines — a Q route, as we call it. But it’s not wide enough for two-way traffic. So if you’re going to restore access to the Strait, it’s one-way traffic, single file, nowhere near 130 tankers per day. There’s some other mine-clearing operation that still has to happen even once we get to a negotiated settlement. That’ll take a couple weeks at least to verify the area is clear, and probably a couple more to clear what you find.

Justin: Bryan, sticking on that — during the Tanker War, that’s when the SEALs really leaned into VBSS, the visit, board, search, and seizure missions. What’s our strategy right now?

Bryan Clark: The Marines do those now. So one of the things Marine Expeditionary Units are doing out at sea is VBSS missions to support the US blockade. The Marines have gotten a lot of experience between Venezuela, Cuba, and now here. They view one of the ARGMEU missions as now being blockades and VBSS, which we’d always envisioned but they hadn’t really practiced.

Justin: When we talk about risk acceptance, is there an acknowledgement that that is a highly risky mission? I think back to even training in the Gulf — those two SEALs killed two years ago, the swim buddies, one fell off the boat trying to climb in and the other one went in after him. And that’s training. There’s also the question of, back to the Tanker War, the Vincennes shooting down the Iranian airliner. When all of our defenses are turned on, what prevents something like that from happening?

Jack Shanahan: What you’re not hearing is — and I know this is military talk that won’t resonate with the typical American — what is the acceptable risk to mission, risk to force? Those are concepts everybody in the military lives by. You could try to translate that at the administration level and say, this is so important, we’re going to accept a certain level of risk. You’re not setting the stage to accept some level of casualties. If you did it in a way the American people would buy into, that’s different. Right now, that risk discussion is the opposite — no, no, this is a cakewalk, piece of cake.

Eric Robinson: And it’s also grounded in almost anti-constitutionality. Civic risk management is Article 1, Section 8 — this is supposed to flow through Congress to the executive. There are numerous parts of a regular process that have been avoided or skipped.

Jordan Schneider: And this is how you get to that no-more-ammo conversation we’ve been having for the past month. Part of buying down potential casualties, potential hostages is using more long-range stuff, which is more fancy and expensive — so you don’t have to have planes flying over the country. That doesn’t mean no risk, that means more risk in 2027 and 2028 when you have less of this stuff for other theaters. By dialing this down, you end up sort of spending more.

Tony Stark: Yeah — using long-range exquisite munitions is to buy down risk to force. What they will not say is that creates more risk to mission, because you still need to be able to hold ground or hold blue ground, and to impose your will upon the enemy, which they haven’t been able to do. Now you’re inviting greater risk to force and mission in other theaters, which is really killing me. If we have to do another three to four months of this, as the leaked CIA report says, the amount of munitions we can burn in that time is another two to five years of magazine relays.

Eric Robinson: Hyperpowers have constraints.

Memorial Day Math

Jordan Schneider: Setting aside a broader economic turn — if this war lasts another few months and gas hits $5, $6, what are people going to be campaigning on in October and November? National security as a vibe in Washington has been on a pretty long bull run. Since 2018, a broad consensus around preparing to deter a big conventional war in East Asia. Having such a dramatic military adventure go poorly — if it ended tomorrow, this wouldn’t necessarily bake in. But if this drags on much longer and the inflation impact really starts to kick up, it’d be a scary time for me working in a Pacific-oriented defense tech, much less a prime.

Jack Shanahan: Part of this goes back to national-level messaging. If the case was made to the American people — look, there is going to be pain — I don’t want to make this a Jimmy Carter “feel the pain” message, but if that messaging was strong enough, you’d get some people to accept the short term. It’s open-ended right now. And when it’s open-ended, all people are hearing is one, gas prices, two, fertilizer, things they don’t even know about. The pinch is going to be felt in four, five, six more months. By then, the question on the election will not be a national security question — it’ll be economic. We’re in this purgatory right now. It’s neither war nor peace, and we don’t have a solution for it.

Jordan Schneider: I just think it’s unsellable, Jack. Iran getting a nuclear weapon is not something that the current body politic is willing to send thousands of people to die for and spend hundreds of billions of dollars on.

Tony Stark: The next trigger here is Memorial Day weekend, two weeks away. That is the first big test of whether people are willing to tolerate big gas prices. I think the answer is going to be no.

Eric Robinson: There is going to be a historic precedent of rally-to-the-flag, that people will take their countryside in times of challenge. The administration, through its muddled messaging about — it’s about nuclear weapons, it’s about respect, it’s about conventional capacity, it’s about just killing their leaders because it’s fun — has muddled that. And when you do not go to Congress and compel members of the House and Senate to put their careers on the line to affirmatively acknowledge that we’re going to war for this purpose, you lose the opportunity to create civic virtue around the expenditure you’re about to expect the country to bear.

Steelmanning Midnight Hammer

Jordan Schneider: I’ve gotten some critique from more right-leaning family members about how all we do is beat up on these guys. So let’s do a counterfactual. You’re sitting there, you really think Iran’s about to get a nuclear weapon. You know you can’t get Congress to vote for a real military operation. You also know that the American people will not tolerate 100 or 1,000 Americans dying. So what is the path that’s left to you? It’s a negotiation, but say you don’t believe in negotiation and you can’t trust them. So you’re left with this very uncomfortable, narrow path where you’re just trying stuff and seeing — because there aren’t necessarily good options. Got to bake in 10% — maybe I draw two aces on the river and if we kill everyone, things end up going swimmingly. I do feel for these guys at some level.

Eric Robinson: Jordan, I think Kamala Harris, if you’d given her the mission profile of Midnight Hammer — that the Israelis, by virtue of their intelligence services and special operations, had reduced Iranian air defenses to a negligible position, that they had good targeting data on the three principal sites, that you knew where the HEU was, that if you used a certain number of ordnance penetrators against these targets you could set back the Iranian capacity for 10 years — I think Kamala Harris would have been compelled to think about that seriously. The original military operation against the nuclear program fits within the traditional span of American national security decision-making. There are very serious Democrats that would have looked at that mission profile and said, let’s go.

Bryan Clark: Even after that operation — and people said maybe it only set it back a few months — you could just mount more of those strike operations. The air defense network in Iran was fairly degraded. With normal SEAD-type operations and whatever the Israelis had done, you could continue to degrade it over time. As long as you don’t take it to the level where the Iranians feel they have to escalate by closing the Strait — when we run these war games, the Iranians generally don’t take that action unless they’re backed into a corner because it puts them in the penalty box. So as long as you keep hitting them and degrading the capability without forcing them into that corner, you could have ended up degrading the nuclear program without getting to the cul-de-sac we find ourselves in today.

Jordan Schneider: So it’s really that temptation of the jackpot — we kill these guys and the whole house of cards falls down.

Jack Shanahan: Midnight Hammer is so defensible in so many different ways. Up to that point, you could have made — and reasonably did make — a case to the American people: we stopped them from getting a nuclear weapon. You could argue on the timelines, was it really a couple of weeks? No, it was not a couple of weeks. We all know it was not a couple of weeks. But it’s a reasonable one. From that point to today, the message has become so muddled we don’t know what we’re trying to achieve.

I watched an interview at FP Live yesterday with Ali Hashem, an Iranian reporter in the Middle East. He says this really does seem to have a reverse rally-around-the-flag for the Iranians. You’ve gone from mass protests in the cities to “why does the United States keep hitting us, and what are we going to do about it?”

Justin: Those are my two big hangups. To Bryan’s point, you could have just continued to do Midnight Hammers. If that’s where all the highly enriched uranium was, they go in to try to get it, you drop again on it. They go in to get it, you drop again on it. Captain America in the Avengers — I can do this all day. Every time you go back to touch it, I’m going to hit it again. You’re not getting a bomb, you need to come to the negotiating table. That’s the big-brother tactic I would have expected us to use. You could also have had a humanitarian argument — 30,000 protesters, they want regime change, they’re calling for it.

We didn’t do either of those things. We waited for the protests to be suppressed, waited for the killings, then started targeting and bombed a girls’ school, maybe multiple girls’ schools. Hit things of civilian importance that would be necessary for any new regime to come in and run the country. We didn’t do those things. We didn’t build coalitions. Then we started hitting random strikes outside of leadership within Iran. And then the ceasefire — and according to some intelligence reports and open-source reporting, something like 70% of the Iranian ballistic missile capability has potentially survived and been reconstituted.

70% Still Standing

Eric Robinson: That’s sourced to a CIA analysis that segments of went to the Hill. It’s supposed to be classified, but yeah — 70% of pre-war defensive capabilities still in check. After all that.

Jordan Schneider: What does that mean? They went from shooting like 200 missiles a day to two missiles a day, and by the end they were up to five or six. So 70% of what exactly?

Tony Stark: Without having seen the report — is that all missiles? Just long-range? The shoot-and-scoot type? Are we including Shaheds? If you said 70% of long-range effectors, that would make sense. That’s the “you can do this all day, lob warheads across the strait on their end.” Look at the targeting packages we went after first. First it was regime change. Less than a year later, regime change. Then we pivoted basically to infrastructure and kind of trying to do scud hunts, but not really. Given what the targeting priorities looked like, there’s maybe a world where the mobile targets were harder to hit.

Justin: And that gets to Bryan’s war games. It doesn’t take a lot to close the Strait. Even if it’s 70% of whatever the amorphous thing is, it only takes a couple of those shots for shipping companies to go, well, we’re not moving through the Strait today.

Jordan Schneider: It could be 95%. Right?

Eric Robinson: It is much less about damage control on an Arleigh Burke destroyer as it is about insurance carry rates and force majeure provisions in contracts that are tied regionally. Those are much more brittle devices than the engineering on an American destroyer. That is the core vulnerability — the financial component, which I don’t think the senior stakeholders in the Pentagon really thought through.

Jack Shanahan: And the economies of every country in the Middle East right now. I’m not trying to claim a causal connection between the Saudis pulling out of funding LIV Golf, but I actually think there’s something there.

Eric Robinson: The Saudis had a really robust strategy by virtue of their partnership with McKinsey — they were going to shift from hydrocarbons to mining to financial services to tourism. The mining project hasn’t taken off. Maaden, the state-owned enterprise, has dramatically pulled back ambitions. The megaprojects are pulling back. Even mundane residential efforts in and around Riyadh are slowing down. The Saudis worked under an extraordinarily robust set of assumptions, and those assumptions all broke based off this war.

Tony Stark: The problem with pivoting to tourism and finance is that it’s dependent upon missiles not raining down on your key industries.

Jack Shanahan: And this other one got headlines for a couple days and faded — hitting the AWS data centers. To me, that reinforces why in the world are we going to go Stargate $500 billion and build all this infrastructure in the Middle East? A very savvy move on Iran’s part — just enough to say, those data centers, yeah, we can hit those too. And by the way, if you’re thinking this whole economy is going to be based on the back of AI, we can hit that. Whether or not it did long-term damage is less the point than the fact that they demonstrated they can and will hit commercial targets they assume are being used for national security purposes.

Eric Robinson: They put data centers into the concept of critical infrastructure very aggressively. The United States has to adapt to a whole new series of targets. It’s not just like Ukrainian armed services hitting Russian oil infrastructure — there’s a much broader array of authentic target opportunity these armed actors can now put into their thought process. It was true innovation.

No Such Thing as an Air Campaign

Justin: Jack, you’ve been looking at this. What do you think the SEAD lessons learned are, given the F-35 getting hit, the A-10 getting shot down or hit, the F-15 getting hit — what are we learning or not learning from a SEAD and projection-of-military-power perspective?

Jack Shanahan: I’m absolutely shocked we’ve lost four F-15Es in a conflict I’d consider low-level. Three were by fratricide — by the Kuwaitis — so I put those in a different category. But when you only have 218, four is a pretty significant loss. Maybe the Air Force views it as, it gets us to the F-15X quicker than we expected, but that wasn’t really the intent.

The shoot-down and the near-absolute-tragic loss or capture of the crew really hit me — F-15E background, watched all that play out. Really disturbing how we got into the place where we’re getting hit by probably shoulder-fired or some infrared SAMs. As a broad comment, we’re very, very good at certain things, including SEAD. But this idea of — what do we really mean when we say air superiority, air supremacy? We have air superiority in localized areas, but we clearly do not have air supremacy over the entire country, because an airplane got shot down. You could say that was an aberration. I don’t accept aberrations. You either have air supremacy or you don’t.

We’ve suffered on the electronic warfare part for about 15 years. Thanks to counter-terrorism and counter-insurgency, we didn’t invest. The service kind of gave up on it after the EF-111, put the eggs in the F-16 Wild Weasel basket. But what we’re seeing now, both in Iran and really in Ukraine and Russia — if we do not go all in on electronic warfare, electromagnetic spectrum operations, we’re in serious trouble in a fight in the Pacific. Very serious trouble. The DDIL — denied, disconnected, intermittent, limited bandwidth — environments, that’s not an assumption anymore. It’s going to be a fact of life.

There is no such thing — I had this drilled into me by former JFACCs, real JFACCs — there’s no such thing as an air campaign. There’s a joint campaign of which there is an air component. To think you’re going to win the war by air alone is delusional. And if we put people on the ground, it’s going to get ugly very quickly.

We’re fighting two different wars. We’re fighting a very conventional one — go destroy their Navy and Air Force. We talk about how well we’ve done that. The Iranians are saying, look, we’re not going to win against you with our Navy and Air Force anyway, have at it. We’ll go at you with our ballistic missiles, our Shaheds, these fast-boat attacks. Call it asymmetric, an economic war on their behalf, while we’re fighting a much more conventional military fight. In general, we’re doing very well on the kind of things we know how to do. But that shoot-down was a wake-up call. We were one inch away from absolute disaster — a bunch of people being killed or captured on TV, prisoners of war. We got lucky in my opinion. Very high-risk mission. The heroes in special ops, CSAR, Air Force — nobody else in the world could have pulled that off. But we shouldn’t be expecting everything to go right in the future in a different fight.

Justin: Do you think the shoot-downs are going to drive more impetus for uncrewed capabilities, or do you think there’s going to be a move to get pilots all out of the aircraft faster?

Jack Shanahan: It won’t be binary. There’s always going to be a place for the crewed platform. But this is one of the many reasons driving more and more toward unmanned. It’s a little bit shocking to me — doesn’t get talked about a whole lot — I think we’re up to like 30 MQ-9s shot down. That’s not a small number. They’re what, $30 million plus or minus on the page. So we’re talking a billion dollars of assets, plus the AWACS, plus the four Strike Eagles. Many billions of dollars of assets.

Eric Robinson: Plus, all the aircraft getting knocked down are recovered by Ministry of State Security and rebuilt. All those assets are now known to our opposition. Electromagnetic signature, visual, acoustic. The crown jewels of American special technology have been revealed in Venezuela, Iran, and elsewhere.

Jack Shanahan: Like the RQ-170 that got shot down years ago.

Two big things scream to me. One — to Justin’s point — yes, more investment, but a different kind of drone. Much cheaper, mass-produced. From one of your episodes, Jordan, with a person from Ukraine, I caught onto this idea: it’s no longer just-in-time logistics, it’s just-in-time disassembly and reassembly at the operational unit as they get thrown in. Because the technology has changed in the 48 hours since the thing was delivered to where they’re going to use it. I don’t think we’ve fully absorbed these lessons yet. We’re trying to pretend that all of them are or it’ll be a different fight in the Indo-Pacific.

But counter-drones is the bigger one. We’ve struggled on this. Where does it really reside, who’s got overall lead? The counter-drone piece is the ultimate wake-up call of seeing what Iran can do with just a couple of Shaheds here and there — really having big impact well beyond the tactical level. Some of those will be electronic warfare, some kinetic, some cyber at some point. But I don’t see crewed airplanes going away anytime soon. It’ll be a question of where in the fight you use them — stand off and work your way in as you reduce the air defense threat. Maybe it was a lucky shot, a golden BB. Perhaps. But that doesn’t mean you have air supremacy.

Quiet Cyber

Justin: Why do you think we’re not seeing more cyber usage offensively against Iran? Is it the nature of the internet in the country, or have they learned lessons from Stuxnet and made it harder?

Jack Shanahan: I think we’re not seeing it because we’re not going to see it. There’s probably more happening than we’d normally think. But all the claims of cyber offense have been countered by cyber defense. It’s the classic history of military technology — Newtonian third law for every action, equal and opposite counteraction. When we’ve hit them hard with cyber, they put defense in place. Maybe — speculation — they’re getting advice from Russia or China on bolstering cyber defenses.

What would we go after? Probably command-and-control networks. Take down their ability to command and control their military and national security. That’s probably happened. Once you start talking about electrical infrastructure, you get into a much more gray area.

There’s a lot to what we saw at the beginning of the Ukraine war with Russia. We all thought Russia was going to come in with state-of-the-art cyber and completely shut down Ukraine. That did not happen. Speculation is they didn’t want to reveal their best capabilities, or it just didn’t work the way they thought — you change one router box and your cyber attack is no longer good. So a combination of things: their defenses are probably better than 10 years ago, they’re probably getting help, and on our side, what are we trying to do and why.

What I remember from Brigadier General Tim Haugh, who was vice commander when I was down in San Antonio many years ago — the operation they put in place, cyber supporting the CENTCOM fight as a truly supporting element, not trying to go off and do things by itself. Let the national agencies do what they’re going to do, but figure out how to make this part of the overall campaign. One day it’s a cyber capability, the next day it’s something kinetic. CENTCOM, as the owner of the overall fight, gets to make those choices, as opposed to treating cyber as this special thing over there. The good news for me is both cyber and space have become normalized in a way I always hoped they would. It is being integrated into the overall campaign. At the national level — what are we doing? There’s something happening, but the good news is I’m not privy to it, because I’d be hauled away if I said anything.

Jordan Schneider: Thank you so much, Jack, for being a part of WarTalk. This is a pleasure.

Jack Shanahan: Thanks, all of you. You guys are legendary. Every time I read something with Jordan, I ask myself, when the hell do you sleep? ChinaTalk keeps me occupied for at least an hour and a half every day just reading this stuff. I commend you for doing it. But God, you put a dent in my day just trying to keep up.

Ken Liu graces ChinaTalk with his presence. He is the author of the Dandelion Dynasty silkpunk fantasy series and a brilliant short fiction writer — one of his stories was recently adapted into Sam Altman’s favorite show, Pantheon. We all know his translation work on the first and third volumes of the Three-Body Problem trilogy, but even better was his absolutely brilliant translation and commentary of the Dao De Jing. As much as I hoped that project would get him fully on the classical Chinese translation train, he followed it up with a very different direction — a techno-AI thriller, All That We See or Seem, released late last year. Irene Zhang of ChinaTalk joins us to co-host.

In a wide-ranging conversation, Ken Liu argues that:

• Technology is the most human thing we do — humans have always externalized our minds into the world and then allowed those creations to reshape who we are.

• AI “slop” won’t stop humans from making art that matters, and the real distinction isn’t quality versus slop, but between desire-fulfilling machines and artists who draw from the collective unconscious.

• The deeper danger of AI isn’t machines replacing humans, but systems that train humans to behave like machines.

• Science fiction isn’t prophecy, but mythology — and ideologies are just mythology’s cheaper, hack cousins. Orwell, Shelley, Tolkien, and Le Guin endure not because they predicted the future, but because they gave us metaphors powerful enough to think with across generations.

• Large language models are intelligent, but can’t be wise. Drawing on Laozi and Zhuangzi, Ken explains why everything that truly matters lies beyond language.

Listen now on your favorite podcast app.

Technology as Human Expression

Jordan Schneider: We’re living in the age of Claude Code, and I want to start with a passage you wrote. Why don’t you set it up and read this vision of future coding and writing?

Ken Liu: Let me start by saying what the book is actually about. All That We See or Seem is a techno-thriller in the sense that none of the technology mentioned is really speculative — it’s all either already here or very possible, just needing to be scaled up slightly.

Julia Z is a hacker, a hero in the mold of Clarice Starling or Jane Whitefield — someone with a very strong moral compass and a very dark past. She’s trying to escape that past, but events keep pulling her back in, and she realizes she cannot overcome external threats unless she confronts the demons within her. In this novel, she has specialized skills with AI and robotics and is tasked with finding an artist who has disappeared — an artist who works with AI to help large audiences dream together.

The passages I’m going to read are reflections on Julia in the Age of AI. Here’s the first, which is about what it’s like to be a programmer — something very close to my heart:

The hardest part had been the programming. Writing code without the help of Talos, or even a lowly codemonkey or datajinn, was not something Julia had much experience with. In the same way that few contemporary writers could compose even a five-hundred-word essay without the help of AI as research assistant, fact-checker, dictionary, thesaurus, grammarian, and, in extreme cases, amanuensis, very few contemporary programmers could create a functioning nontrivial application without the help of codedaemons, bug-genies, patchsprites, scriptpixies, and a whole fairyland of similar artificial intelligences.

Homo sapiens had always externalized their minds into the world, oozing books, drawings, plans, recordings, the same way honeybees made their minds visible in the form of wax comb and sweet honey, but the trend had never gone as far as now, when most of one’s knowledge consisted of knowing where to look things up and how to give an AI the best prompts, and more of one’s mind existed outside the skull, infused into fiscjinns and memoelves and egolets, spread among artificial assistants and helpers and aide-mémoire, imprinted in cogitrons and electrons and logons, than remained inside the squishy gray matter inside the skull.

Jordan Schneider: Let’s start with the idea of choosing a techno-thriller as a genre to explore something every white-collar worker is grappling with today.

Ken Liu: Genre labels are largely irrelevant to me. All of my fiction — whatever the marketing genre — is fundamentally technological. Whether it’s the Dandelion Dynasty, my short fiction, or the Julia Z series, they’re all stories about what it means for humans to express parts of themselves through technology.

If there’s something unique about humans compared to other species, it’s fundamentally our technological nature. This is important. A lot of things described as “sci-fi” aren’t really sci-fi at all — they have very little to do with science. They’re technological stories. “Techfi” is far more interesting to me. Technology and science are completely different disciplines, and the vast majority of so-called sci-fi is really techfi, because it’s really about what it means for humans to express themselves via their creations.

We are the only species who express who we are through the things we make. We imagine things that did not exist in the universe, then actually bring them into being — concretely substantiating our mental constructs in the world. And these technological manifestations, this stuff we ooze out, in turn changes who we are. We converse with, interact with, and co-evolve with our own creations. No other species does this.

One of the great philosophical debates in our tradition is whether humans are more human without technology or with it. This debate goes back to Plato, to Zhuangzi, to all the great philosophers. What is language? The entire skeptical interrogation of language itself is really this debate about human nature.

In the contemporary world, we often default to the position that technology is somehow external to who we are — something we should be wary of. To me, this is nonsensical. Human technology is a manifestation of human nature. It’s in fact the most human thing we make. You cannot understand human nature without understanding human technology — it’s literally a tangible substantiation of what is inside our minds. To understand what human nature is, we have to interrogate human technology and truly understand how we co-evolve with our own creations. That’s what the Julia Z series is really about.

Irene Zhang: You use the metaphor of the jinn to describe what the marketing world might call AI agents. That obviously comes from Arabic mythology and Islam. Why did you choose that metaphor, and how do you think about the metaphors we use to understand AI?

Ken Liu: The immediate answer is that I was interested in the word “cotton gin” — it’s short for “cotton engine,” which is just the way we play with language. Why not take that “gin” and turn it into a different kind of “jinn”?

If you look at how technology is expressed through language, it’s very mythological. Think about how we name our technology. Why did the U.S. decide to name its space programs after Greek and Roman gods? There’s a mythological component to the way technology is manifested because technology is not independent of who we are — technology is how we dream.

The reason technology is so expressive of human nature is that it’s a manifestation of our deepest desires and dreams. We’ve always used mythology to express and understand technology. Look at how technology companies talk about and market their creations — there’s always a mythological component. If I didn’t name them jinns, that would be weird. It has to be a mythological name, because that’s how these companies think.

Jordan Schneider: Is this time different? You made the argument to the negative, but in that passage, you’re saying that externalizing your brain to the extent your characters do — or we’re doing today — is something unique in human history.

Ken Liu: Externalizing the brain into our creations is not unique. Every child who has learned to read has experienced that moment of communing with mental patterns from creatures long ago. When you read Plato’s dialogues or Zhuangzi’s stories today, you’re communing with minds from thousands of years ago. That’s very strange if you actually think about it — you’re engaging in something no other creature can do. We’re communing with mental constructs from the past.

Consider what happens when you do arithmetic — long division, an integral, working out a tensor. You’re using pen and paper to externalize your brain. Your cognitive function is literally externalized on the paper. It’s a very strange thing. Your brain is out there, you’re interacting with it using your body, then getting it back. No other creature does this.

Is AI significantly different from that? I don’t think so. The best way to understand large language models is to go back and read the structuralists from the 1980s. Roland Barthes said that in a deeply literary society, burdened or blessed with millennia of writing and millions upon millions of authors, we are surrounded by words — by their minds. A modern writer, a “scriptor,” is not an author who creates out of nothing, but someone basically babbling in the presence of a complete corpus of past writings. You are just playing with words, reference upon reference, allusion to more reference. You’re acting as a channel, a conduit to this playful field of past writing as you babble more writings.

Barthes wrote this as a way of talking about the death of the author, but reading it now in the age of large language models, you realize that’s exactly what he was describing. The large language model is a substantiation of that imagined dictionary of all writings. It’s language coming to life. It’s you interrogating the entire corpus of what humans have written — this “pluribus,” this multi-mind, that you’re engaged with.

That’s my argument for how AI is not really different from how we’ve always dealt with technology.

Now, there are some interesting differences. For the first time in history, we’re confronted with the idea that intelligence and consciousness are not the same thing.

If you examine older sci-fi literature, there’s a huge fundamental assumption that something intelligent will necessarily be conscious — that the more intelligent something is, the more it necessarily comes with intention, will, desire, and the sense of being something, of some mind behind the intelligent acts.

What we’re seeing now is that there’s no doubt these models are intelligent. A lot of the popular discourse — “it’s just a very powerful autocomplete” — is very silly. That description is technically true, but it means nothing. You might as well say humans are nothing more than compilations of statistical likelihoods. Yes, that’s technically true, but so what?

The real issue is this — if something can write essays, pass the bar exam, and get a perfect score on the SATs, to say it’s not intelligent is a nonsensical declaration. It’s clearly intelligent, but it’s not conscious. I don’t think many of us would argue that LLMs are conscious.

That is very strange. The fact that we can have intelligence completely divorced from consciousness, from will, from intention, from subjectivity — that is weird. We’re still coming to terms with it. We’re trying to understand why we value subjectivity so much, yet don’t seem to think intelligence by itself is all that valuable anymore. Many of us now seem to be leaning in that direction.

That’s honestly why a show like Pluribus on Apple TV is so interesting — it’s mythologically engaged with this particular question: what matters more, subjectivity or intelligence?

The Age of Slop

Jordan Schneider: One theme you pick up on is this idea that yes, there’s a future of AI slop that your world is swimming in, but there’s still something where the audience wants to meet up in person and have a connection to a particular human who lives and breathes and bleeds. It seems your contention is that there’s something about having a human behind it all that will remain fundamentally appealing, however good these models get.

Ken Liu: I want to start by saying I don’t necessarily have a specific argument one way or the other in the book. My fiction gets published and people attribute certain points of view to it — sometimes, readers attribute polar opposite views. That’s actually a sign I’ve succeeded, because I deliberately write fiction with very little messaging in the sense of propaganda. Fiction written as propaganda isn’t particularly interesting to me. Ayn Rand very famously writes propaganda that is very popular, but I don’t find that kind of fiction interesting. All of my fiction is aesthetic works that can deliberately be read to support multiple contentions, because that’s how reality is. You can take reality and interpret it to suit different messages.

That said, the contemporary anxiety over AI slop is understandable, but it has to be contextualized historically. We are already living in a world of slop — not AI-generated, but mass-produced slop.

Take your mind back to before the invention of photography. You might see maybe a few hundred images in your entire life, every single one produced by hand by a real human being. Church stained glass windows. Famous paintings, if you were rich enough to travel. A few pictures you made yourself if you learned to draw. Pictures drawn by friends. Prints in books made by someone who had to translate an image into a printing plate by hand. A few hundred of these things in your lifetime.

After photography and photographic reproduction techniques, we entered what Walter Benjamin called the age of mechanical reproduction. We’re surrounded by images — hundreds of thousands in a single day. The vast majority is slop — clip art, images made by graphics programs, and reproductions from public domain stuff with a few manipulations.

My point is that this hasn’t destroyed art. It hasn’t made humans unable to appreciate art. In the age of AI slop, what makes you think we’ll stop producing actual art? We’re already living in an age of slop, utterly surrounded by it, and yet the proliferation of slop has allowed us to become even more artistically interesting and create more interesting human art. I don’t see that being different in the future. We know how to deal with slop. The age of mechanical reproduction is here, and the age of AI slop will not be any different. I don’t see the moral panic over it.

Now, that’s not the same as saying it won’t lead to the loss of livelihoods. The age of mechanical reproduction caused the loss of livelihoods for many artists — specifically engravers, great artists who had to translate paintings and drawings into printing plates. Yes, they were displaced, and that was a difficult transition. We will face a difficult transition today too. But the idea that AI slop will destroy art is very flawed. That’s just not how historically any of this has ever worked.

What interests me more is what this technology can enable humans to do creatively. Historically, in every case where some technology displaced aspects of human craft, humans ultimately learned to practice craft with that technology.

Humans have practiced craft with the camera. When the camera was just “push a button and chemistry and physics make a picture,” that’s not interesting. But when humans learned to use the camera as an artistic tool — how to tell stories with it — that’s how we ended up with cinema, with TikTok, with YouTube, with the vast explosion in video art. None of which would have been possible without the camera.

Something similar has to happen with AI. Today’s AI is in the stage where you give it a prompt and it generates something. This is very non-crafty — there’s no craft to it. But it won’t stay like this. Over time, artists will figure out — what are the affordances we need to actually use these models in interesting ways? How do you precisely position the generator within latent space? How do you precisely delineate the chain of inferences and associations inside the model’s weights to generate what you want? How do you precisely manipulate this model the way you can dial in camera settings, set up poses, and frame a shot?

When all these affordances are given to an artist who wants to work with AI as a tool, then and only then will we see interesting art being generated by humans. That’s my contention.

Jordan Schneider: In a recent Substack post, you said you spent much of December and January playing video games. Behind you, I see a PSP and a Game Boy Advance. In the book, you explored one future of artistic creativity — AI-enabled dream weaving. Where do you see the future of video games with all of this?

Ken Liu: One of the most contentious uses is AI-generated assets in games. I personally think this will eventually be normalized. If you want to call AI-generated material slop, that’s what it is — but we’re surrounded by slop, surrounded by mechanical reproduction and cheap art. That’s just how it is. Eventually, this will probably happen to video games too, in terms of asset generation.

That doesn’t mean human-crafted material will lose its appeal. In the same way that humans, even in the age of mechanical reproduction, continue to be enthralled by the aura of the artist — much to perhaps Walter Benjamin’s disappointment — I don’t see that changing in the age of AI slop either. The human aura will still be very appealing to many of us.

At the same time, one of the great things about AI-generated art, like mechanical reproduction, is democratization and the ability to generate certain kinds of art that human artists would never make.

Here’s a very interesting pattern — humans find playing with AI to make art for themselves very interesting, but we almost never find sharing this stuff with other people interesting, and other people don’t find it interesting either. You generate something using AI and it’s kind of interesting to you, but not necessarily to anyone else. There’s an intense personalization effect here worth following up on.

AI is really good at fulfilling your desires in a way that human artists never will and never can. Take a crude example. You might crave a particular kind of fiction or film — an adaptation of your favorite novel starring your favorite actors. In reality, that will never happen. Humans will not do that for you. But you can use AI to create it. AI is a desire-fulfilling machine, but it’s only able to do that for you, and only you would find it interesting. It’s not the kind of thing human artists would ever do.

The analogy is that mechanical reproductions can fulfill a niche humans never could or would. For the vast majority of history, it wasn’t possible for most people to get a good portrait done. You had to be very rich or famous, otherwise you relied on a friend or family member who could draw. That’s why we have that picture of Jane Austen done by her sister — it’s not a very good picture, but it’s the only one we have. Once the camera came along, middle-class families could have pictures done cheaply. Now everybody can take a selfie. We’re awash in slop selfies.

That’s what technology can do — allow you to get things humans never would provide. You can’t get portrait artists to paint most of us, but you can easily use a camera. If you want a particular kind of story, you’re not going to get human artists to write it for you. But you can get a machine to do it. This highly personalized, self-involved fiction — when people speak about AI boyfriends and companions, that’s what they’re talking about. Fiction co-written with an AI for themselves alone. That’s exactly why these things are appealing.

But that doesn’t mean people who love this will stop appreciating fiction written by humans that’s not meant to fulfill desires. Artists are not there to fulfill your desires. Artists are there to fulfill their own dreams. They go into the collective unconscious and are seized by some image or vision they have to bring out. That’s why artists create.

There’s a complementary role for AI versus human artists. Human artists will do what they’ve always done: dream and bring forth interesting dreams from the collective unconscious. AI will fulfill your individual desires. The two are complementary — not the same kind of thing, but they can coexist.

Everything Not Said

Irene Zhang: On companionship and desires, I wanted to ask about Talos, Julia’s AI assistant. Julia lives in a world where personal AIs are common, but you don’t portray that as companionship in the book. People still fall in love and have friends and family. How did you make those decisions in crafting Talos and the personal AI landscape?

Ken Liu: Talos is actually very different from any other personal AI in the book, and the distinction is important. The personal AIs that everybody else uses are essentially subscription services — what all the companies are trying to make. You subscribe to their cloud AI, it’s personalized to you, but the data is all with them. That’s what people are concerned about in terms of privacy.

Talos is different. Talos is not a subscription AI from some large company. Talos is something Julia builds herself, running on her own local hardware, entirely controlled by herself. What Talos really is, in terms of how the book describes it, is an “egolet.”

What’s an egolet? It’s an AI representation of you. Let me tease this apart.

What I find deeply interesting about AI is that neural networks are essentially a camera for different things — not a camera for images, but a camera for decisions. For decision-making procedures, decision-making processes, for choices you’ve made in the past.

Take a concrete example — if a painter were to train an egolet (and companies are exploring this possibility), they would train a neural network not just on their finished paintings but on the entire process of creation. How do you decide to make this paint stroke and not that? How do you decide to cover up these strokes and not those? How do you decide to do this part first and that part last? The entire process of creating a painting or a book is where the interesting stuff is.

We’ve all had the experience where AI produces a painting “in the style of so-and-so,” and it looks superficially good until you examine it — there’s always a superficiality. Or there’s this popular application where you feed all the books by some author into a model and say, “Now you can talk to so-and-so.” You train an AI on all the dialogues and books by Plato and supposedly you can talk to Socrates about AI.

These are all terrible apps, and none of them ever feels convincing. People have done this to me — trained models on my interviews and asked me what I think. What I think is, “This is garbage. This sounds nothing like me.”

Here’s why — for everything I say, there are ten things I’ve decided not to say. If models are trained only on things I’ve published, the model will never know all the things I would never say. When you have models trained only on what has been said, they don’t know what has been decided to be not said. So they always generate garbage, saying things I never would have said.

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The issue is that for these models to be a good representation of the person, they need insight into all the things you’ve decided not to say — everything behind the scenes. Published works and finished paintings are like the part of the iceberg above the water. The vast majority is below. Steve Jobs once said something like — this is a paraphrase — for everything you say yes to, there have to be at least ten things you say no to. It’s the part you say no to that matters.

An egolet, in my conception, is an AI capable of actually capturing the part where you say no — all the parts you’ve denied.

How many of us are comfortable giving that information to Anthropic, to Google, to OpenAI? The idea that you would reveal the parts you’ve kept hidden from the public — who’s going to do that? Nobody.

That’s why personal assistants in that form will never amount to anything. Personal assistants trained only on what you’ve let out will never amount to anything. The only way to produce real egolets — small egos, small copies of yourself, something trained on who you truly are — is if you have total control over the model. Total control of the training, total control of the hardware, total control of the data. Total sovereignty.

That’s what Talos is. Talos is totally controlled by Julia. Because she has complete control over Talos, Talos is very different for her. She explains in the book that talking to Talos is like talking to a version of herself, or different versions of herself in different periods of her life. She’s able to examine herself. Talos is the fulfillment of that oldest of philosophical desires — “know thyself.” By having an AI trained on yourself in this deep sense, you can reflect on yourself. Julia can examine who she is via Talos — to leverage herself, work with herself, and critique herself. That’s what makes this sort of thing actually interesting.

The Real Danger of AI

Irene Zhang: Without spoiling it, quite a bit of the plot centers on something that actually exists — scam call centers and human trafficking rings in the Golden Triangle, primarily in the Thailand-Burma border regions. How did you become interested in that, and what makes it important to you?

Ken Liu: Let me address that by explaining what I think the real danger of AI-generated slop actually is. I disagree with a lot of mainstream commentary on what the issue with deepfakes really is.

A lot of commentary focuses on the idea that we’re going to be manipulated by bots from foreign actors. The natural outcome is better ways of distinguishing organic accounts from bot-operated ones. But if we get there, the next logical step for actors who wish to weaponize commentary is to have humans do it, not bots. In an age where machine-generated slop is a big problem, there will necessarily be a premium placed on human-generated content. The next logical step is actors who enslave human content creators for that purpose. This seems quite plausible, and I’m sure it’s already being done somewhere.

But the issue is not quite that simple. It’s a fundamental misunderstanding of what the real problem of AI is. We often describe the problem as machines replacing humans, as though that’s the biggest issue. That is not the real danger. The real danger from AI is that humans will start treating other humans as machines. It’s the gradual mechanization and reduction of humans into components of a machine — that is the relentless pattern of modernity.

This has been going on forever. When the assembly line was invented, human workers were reduced to components of a massive production machine. Instead of exercising individual judgment and creativity, humans were put into positions where they exercise as little creativity as possible — repeating the same motions, specializing in doing the exact same thing over and over with as little variation as possible, becoming standardized components of a machine.

That production line model has persisted into the modern age. We constantly take away individual initiative and decision-making from workers. Call center employees are instructed to follow the script, not deviate, not exercise human empathy — to think of themselves as components of a machine, essentially language models. This is why call center workers are so easily replaced by AI: modernity has tried to reduce humans into robots so that real robots can take over from them very easily.

This is the real danger. Wherever humans retreat into an area of individual initiative and choice, the pressure of capitalism is again and again to reduce them to components of a machine, to appropriate their creativity, to standardize their initiative for purposes of money and control and power.

In the book, without spoiling it, a large part involves exactly this kind of enslavement of humans into an economy that puts a premium on individual human creation. In the age of mass mechanical reproduction, human-made custom bespoke art is given a premium. In a future where AI-generated slop is everywhere, human-created content will again be given premium value. Social media companies will figure out ways to show they have real engagement instead of bots. When you have an internet that’s 99% bots talking to bots, the way to convince humans to engage is to promise them real humans.

But once you’ve gone down that route of putting a premium on human content, people will inevitably figure out ways to again reduce humans to machines and enslave humans for that purpose. This is the pattern we see over and over again.

Mythology vs. Ideology

Jordan Schneider: These books — sci-fi in general — are not predictions. They’re an expression of where we are today. Why is the idea that these books are predictions so seductive, and why does it make no sense?

Ken Liu: There’s a tendency in literature and the arts to figure out how we justify ourselves. Fundamentally, writers write because they’re having fun. The fact that we’re being paid for it is a little weird, so we have to figure out why. A common reaction is to view sci-fi as particularly relevant because it somehow predicts the future or helps us think about what’s likely, or warns us from dystopias we might step into.

I don’t think this justification is plausible or even interesting, because sci-fi has a very bad track record of predicting anything. If sci-fi ever does predict anything, it’s more out of luck than anything else. The sci-fi we hold up as really good predictors or evergreen classics are such because they get some metaphor right that’s very potent, but the details are completely wrong.

Take 1984. It’s a very good book and still extremely relevant decades after it was written. But the surveillance society we live in today is very different from the one envisioned. Big Brother in 1984 is a state-imposed surveillance system. That’s not the surveillance system we have today. Even in contemporary totalitarian societies, surveillance is often not imposed in the way 1984 pictures it.

We live in a surveillance society that we crafted out of our own desire. It’s not a state-imposed system — it’s a system we constructed through voluntary consumer decisions over decades. We consistently gave up bits of privacy in exchange for convenience. Now we’re surrounded by devices constantly listening and watching, sending bits of what we’re saying back to the mothership. So much of our data is given to companies to train their devices, and these companies are happy to share it with governments. We are under a degree of surveillance Orwell would have found astonishing. And the vast majority of us are quite happy about it. We don’t think this is terrible. We’re fine with having our data constantly exposed.

Orwell did not get any of the details right. But the fundamental metaphor of Big Brother is extremely potent as a mythological concept. It has shaped how we think about surveillance, how we talk about it, and how we think about private desires and private thoughts versus being constantly on display.

That’s what sci-fi is actually good at. Sci-fi is not about prediction — science fiction writers have no more authority or knowledge about the future than anybody else. The future is very accidental. Every time science fiction writers speculate about the future, they can’t help but extrapolate from present trends. Science fiction stories are almost always about the present — present trends extrapolated. But the way the future evolves depends on so many unpredictable factors. The future we end up having is almost never the future we thought we would have. You can plan all you want, but the future you get will be nothing like what you planned. A thousand different teams will work on solving the same problem, and the team that ultimately succeeds won’t be the one many of us thought would succeed. The future is unpredictable in a very deep, fundamental sense.

But sci-fi writers do have something interesting and valuable to add in the mythological realm. Artists go into the collective unconscious, dream interesting visions, and bring them back. It’s these mythological visions that ultimately persist.

We don’t read Frankenstein anymore for its speculation on how you might create artificial life. We read it because the creature is a very potent metaphor for new technology. We cannot think about new technology without thinking about Frankenstein’s creature.

In fact, the LLM — this technology of the moment — is very much like the creature. If you go back and read Frankenstein, read the part about how the creature learns human language, learns human morality, learns human relationships, learns to desire — it’s eerily like the way LLMs are trained. And the questions being asked of the creature are very much like the questions Anthropic nowadays is asking about alignment — how do we end up with an AI aligned with our own interests? I find that deeply fascinating.

This is why old sci-fi remains relevant. Not because their predictions are particularly valuable, but because the metaphors they bring up, the mythological figures they invoke from the collective unconscious — they persist and help us dream about the present and the future, and think about how we want to use technology to express who we are.

Irene Zhang: While we’re discussing sci-fi writers as myth-makers, I can’t help but read this in the American context today. Palantir exists, and I’m sure Tolkien, when he wrote The Lord of the Rings, did not imagine his myth-making would become a potent symbol enabling technology as a political class aligned with certain ideologies and bound to the government. How do you think about that evolution in sci-fi’s relationship to politics in America today?

Ken Liu: I don’t think writers should be propagandists either way. The reason Tolkien is potent as a writer is that he tried his best not to be a propagandist. The fact that The Lord of the Rings can be read to support completely different political ideologies is a testament to his skill, not a failure. He might personally disagree with how Palantir is now invoked as a symbol, but that’s not a testament to his failure as a writer. He succeeded in creating very potent mythology. Good mythologies will always be appropriated by people of very different beliefs. Just watch how Christianity or Islam has been appropriated by very different ideologies to say completely opposite things.

I don’t think writers should feel responsible for how their mythology is used. The writer’s only job is to create interesting mythologies — mythologies true to the collective unconscious, to their journey into it, to the dreams they’re trying to bring forth. That is their only job.

They should help us escape in the deepest sense. The real world is filled with bad mythologies, bad allegories, and bad fantasies that are not true to human nature. One of the critiques of fantasy that Tolkien and Ursula K. Le Guin both pushed back against is that fantasy is escapist. This is obviously nonsense. As Le Guin said: “If we live in a prison, then escape is actually our moral duty.”

In the world of ideologies that we live in, ideologies are the bad cousins of mythologies. Ideologies are cheap, bad, hack versions of mythologies. The fact that people can believe in ideologies at all is a sad state of affairs. The idea that you believe money has actual meaning, the idea you believe that the Wall Street Journal has any kind of moral authority — that’s nonsense. If that’s the reality you’re living in, then it is your duty to escape.

That’s what fantasy does. Fantasy enacts our moral duty to escape from the bad hack mythology of ideologies by substituting them with real mythologies — mythologies that actually mean something. The fact that somebody can reduce Palantir to the service of a bad ideological agenda does not make the actual myth in The Lord of the Rings any less valuable. It’s up to the rest of us to recover the multitude of meanings from the mythology and reclaim the truth that fantasy is meant to tell.

Jordan Schneider: Ideology as hack mythology — nationalism, for instance. There are a lot of people all around the world who get into positions of power on the backs of those things.

Ken Liu: I entirely agree. One of the worst things that’s happened to politics — not just democratic politics, but politics everywhere — is that real mythologies are being hijacked by ideologues. Real mythology that is life-giving, potent, creative, and inspiring has been hijacked into serving very hacked, bad versions of the real mythologies. Nationalism is often one of them. Real, genuine, powerful collective identities have been hijacked by nationalistic sentiments into something horrific — in the same way that the beautiful vision of Christ has often been hijacked by organized religion into something much worse.

Daoism and Freedom

Jordan Schneider: Let’s take it to our beautiful vision of Laozi, who just kind of gets ignored — not really hijacked. Why did you take this one on?

Ken Liu: Laozi actually does often get hijacked, in ways that are pretty horrible. Daoism is one of those philosophies that often ends up twisted into serving something it’s not. People quote Laozi whenever they’ve been thwarted in their political ambitions, using him for comfort. Or they use Laozi to discourage resistance — to say all resistance is pointless and you should just go with the flow and do whatever the dominant trend is. These are utter misinterpretations, sometimes misunderstandings, sometimes deliberate twistings — in the same way Palantir is a deliberate twist on what Tolkien was trying to do.

Laozi is interesting to me because he casts a particularly strong shadow across East Asian philosophy in a way that’s rarely acknowledged. People often say Western culture is deeply individualistic while Sinitic culture is deeply collectivist. This is utter nonsense if you know anything about anything. Western culture has very strong communitarian and collectivist trends — arguably the entirety of Christianity is deeply oriented towards a collectivist vision of what human beings can do and be. You cannot deny that Christianity is a deep part of Western culture.

Similarly, you cannot deal with East Asian culture without addressing Daoism’s deep influence, especially through Zen Buddhism, which is basically a fusion of nativist Daoist philosophies with Buddhist ideas. Understanding the deeply individualistic and freedom-oriented nature of Daoism is extremely important to me.

One of the things I care about most in Daoism is its deep commitment to freedom as an ideal, in a way that’s rarely discussed. There is a deep wellspring of freedom — yearning for freedom, love for freedom, mythologizing of freedom — that is important to Daoism. We need to recover, rediscover, and reclaim these ideas. They’re important now, perhaps more than ever.

Jordan Schneider: Care to elaborate?

Ken Liu: One thing about Daoism that often gets ignored is this idea of freedom — freedom in a very deep sense. What does it mean to be one with the Dao, to follow the Dao? It actually means a kind of transcendence, particularly important in the modern age.

A lot of times we feel a lack of freedom not because of external constraints but because we fall into the trap of believing there are certain things we need or should do that are actually not things we need or should do at all.

Think about — those who are a little older — how important it was when you were a teenager to dress the right way, listen to the right music, express opinions your peers did. Looking back, all of that seems incredibly silly. Yet at the time, it seemed like the most important thing in the world. Those were constraints on your freedom, on your ability to be who you were. It’s only with hindsight and wisdom that you realize that.

The older you are, the less constrained you feel. The less you feel you have to keep toxic people in your life. The less you feel you have to play a role and be nice to people you don’t want to be nice to. The less you feel supposed to do things other people tell you to do.

The older you are, the closer you are to death, the freer you are. That’s paradoxical. We ought to think young people have the most freedom because they have the most choices, and old people the least because they have fewer choices. Yet psychologically, older people feel freer because they have less to give.

That’s one of those paradoxes about Daoism that’s important to think about. The way you are free is the degree to which you are not constrained. The more you feel free to live the way the universe wants us to live, the closer you are to the Dao.

That’s one of the insights I got reading the Dao De Jing in the aftermath of the pandemic. Until I started reading the text in depth and really reflecting on it, I hadn’t realized how much academic discussions of Daoism neglect how radical the philosophy really is. Daoism refuses to be tamed. It’s not one of those philosophies that can be easily reduced to larger frameworks of philosophical traditions. It’s incredibly skeptical, slippery, and self-deconstructing from the start.

But ultimately, Daoism’s highest ideal is freedom. In an age with so many constraints and impediments to freedom, that makes Daoism more relevant than ever.

Irene Zhang: There’s a natural follow-up: how would Daoism feel about surveillance and data collection as a constraint on freedom?

Ken Liu: I cannot imagine Laozi or Zhuangzi or any of the Daoist philosophers looking at the world we live in and viewing it as anything but the worst of the worst. We are literally surrounded by illusions and spend our time chasing after illusions.

Think about what you’re doing on social media. You’re getting your emotions riled up by words generated possibly by a bot or by someone paid to manipulate you. Your very anger, your very rage, is what these companies monetize. In the moment these companies claim to give you agentic AI, you have actually been turned into an agent of the companies themselves. The only reason agentic AI is being given to you — so you can give them your email and calendars and let the AI do things for you — is so you can give them more data they would otherwise never have access to. You are the agent being deployed to explore the world and give these AI companies more and more information.

We live in a world surrounded by illusions, pursuing illusions. We think we have wisdom when we have none. We are so obsessed with chasing illusions that we’ve utterly forgotten what the real pursuits are. I could say endless things about our politics and how we waste energy chasing illusions and fighting over illusions rather than going back to the few things that actually matter.

As Laozi put it, we are obsessed with our eyes and neglect our bellies. It is the belly that is the fundament, the belly that is the truth, the belly that allows us to feel the Dao and be with it. Our eyes are surrounded by illusions. We are constantly pulled away in this age of slop — not just AI-generated slop, but slop ideologies, hacked mythologies that lead us away from where we need to be.

I don’t think there’s a magical solution other than for individuals to go back and make the right choices. This is very difficult. For most of us, the folly of our youth is not realized until decades later. Maybe society as a whole has to go through this — a few years, hopefully not decades, of this kind of folly before we recover some measure of wisdom and realize how deeply we’ve gone down. Meanwhile, we can only do the best we can as individuals to make choices that allow us to focus on our bellies and not be deceived by our eyes.

The Inadequacy of Language

Jordan Schneider: Can you talk about how Laozi used language? Rereading it this year, I was struck by how different he feels from what ChatGPT and Claude give you.

Ken Liu: That’s a great point. As a premise, every single writer worth reading essentially invents his or her own language. I don’t think it makes sense to say Jane Austen wrote in some 18th-19th century English. No — Jane Austen wrote in her own language. She had to invent her own language to tell the story she wanted to tell. Same with Shakespeare. Same with Laozi.

Laozi took classical Chinese — a very interesting language in its grammatical structure and deep commitment to balanced structure in literary creations — and turned it into something unique. As a writer, he persisted in writing in a way that deconstructed binary opposition.

Binary opposition is a deep part of the human cognitive apparatus, a deep part of how we see the world. Something is either this or that, black or white. Laozi leaned into it. If you read him, he constantly writes things in a way that turns every word into its own opposite. He uses the same word to mean its exact opposite.

But the purpose isn’t to say everything’s just a big mush. He’s saying that in every binary opposition, there’s a third possibility — or innumerable third possibilities — that are neglected. Things are not either black or white, but other colors entirely. Things are not empty or filled, but potential, which is not the same as filled and not the same as empty.

Over and over, he makes statements that are “this or that,” “this and that,” “this is that.” He constantly uses the same verbal formulation to force you to see that language itself is inadequate to the expression of actual truth.

The way that can be stated is not the way. The path that can be laid out is not the path. This sounds like paradox or mystical nonsense until you apply it to your own experience.

A concrete example — as a writer, when I started out, I thought there would be some path to success. It took years and years of failing before I realized there is actually no path. There’s only the path left behind you after you’ve done what you’ve done, after you’ve lived. If you ask other people how they succeeded, they’ll tell you what happened to them — but that’s unique to them. You cannot apply it to yourself in any way that matters. You have to find your own path, your own flow through the universe, the path that will lead you to the sense of freedom you crave. Because writers, after all, crave freedom.

The path that can be stated, explained, and reduced to language is not the path that matters. This skepticism toward symbolic language runs deep throughout Daoism — the idea that whatever can be captured in words is not the actual thing itself. If you’re obsessed with words, you’re only obsessed with shadows of real wisdom. Language itself is the thing that’s left behind when real wisdom has moved on.

Zhuangzi has this beautiful parable — if you’re reading the words of sages, you are not truly engaged with the wisdom of sages, because the real wisdom has left. All you’re left with are the footprints of the mystical beast, the echo of the dragon’s sound, the husk of the real grain of wisdom. What you’re left with is the shell that will point you to the real thing. But to find the real thing, you have to look beyond language.

This skepticism of language exists throughout philosophical traditions. But to bring it back to your question, Jordan, this is exactly why large language models do not have wisdom. They may have intelligence, but they don’t have wisdom.

All that large language models can ever do is know the world to the extent they can know it through language. But everything that matters is beyond language. The truth about the universe is not capturable by language. Language is itself not adequate to capture reality. Language is a shadow cast by reality, a manifestation of human mental impressions left by reality. Reasoning from these traces and tracks, you’re always just reconstructing the beast, the dragon that left them behind. You’re not actually seeing the dragon itself.

Laozi urges you over and over again to seek the dragon itself, not merely contemplate its tracks and scales.

Jordan Schneider: So when’s the Zhuangzi translation coming out?

Ken Liu: Not working on one.

Jordan Schneider: Okay, maybe next time.

Irene Zhang: One last controversial question — why be a writer if words are about illusions?

Ken Liu: That’s actually a great question. Le Guin had a good answer — artists are about the truth, not facts. Artists go into the collective unconscious and retrieve the truth and try to present it to the world. But the truth is not something that can be captured by what we have.

Artists are people who try to paint what is essentially not paintable. Writers are artists who try to say with words what cannot be said in words — in the same way that Laozi tries to use words to tell you what the way is, even though he explicitly said the way itself cannot be captured by words. That’s how all of us have to deal with it.

Jordan Schneider: You write that Laozi wrote this way because he wanted to emphasize that language is ultimately a misleading guide — “We think that when something is nameable, it is real. But he writes, ’The name that can be spoken is not the name that endures.’ Conversely, we think what cannot be spoken about does not exist. But the most important knowledge is never reducible to words.”

So when we’re all living in our AI-generated virtual reality video games — brought to you by, hopefully not slaves living in the Golden Triangle — we should remember to pick up our Chinese philosophers every once in a while, as well as Ken’s new book, All That We See or Seem. Ken Liu, this was just the biggest treat in the world.

is a research associate at the Oxford China Policy Lab and holds a Master’s degree in Social Science of the Internet from the University of Oxford.

On April 23, 2026, the White House released a memo warning that Chinese entities were running “industrial-scale” distillation campaigns against American frontier AI models, leveraging “tens of thousands of proxy accounts” to evade detection. In February 2026, Anthropic similarly reported on Chinese labs’ coordinated distillation attacks using “a single proxy network managed more than 20,000 fraudulent accounts”. Both cases see “proxy” — the middlemen between model users and model providers — as a purposeful design by a selective Chinese frontier labs to systematically extract US AI models.

Regardless of whether Chinese labs rely on distillation to “catch up”, both documents misread the proxy economy they’re describing. Underneath the handful of labs sits a much larger market, one that has been operating in public on GitHub, Taobao, Twitter, and Telegram. It is a grey economy of API proxies (commonly called “transfer stations,” 中转站) that lets Chinese developers access Anthropic’s models at as low as 10% of the official price. The participants extend far beyond selective experienced AI researchers, and the motivations are much broader than building a frontier model to catch up. Everyone who wants to use more advanced AI models or tools, be they university professors and students, tech workers, individual developers, or hobbyists, uses API proxies.1 The logs they generate may have become a commodity, traded for purposes ranging from model training to targeted fraud.

Meanwhile, every layer of control frontier US AI companies have added (geoblocking, phone verification, credit card requirements, and now live biometric KYC checks) has produced a corresponding layer of evasion infrastructure. These new SMS farms and biometric harvesting operations have implications that extend beyond geopolitics into how frontier AI safety frameworks are designed.

Building on my 2025 ChinaTalk piece on accessing banned American models in China, this update zooms in on the transfer station economy specifically: how it is structured, how it monetizes, and what it reveals about the limits of access blocking and account monitoring as AI governance tools. Unlike 2025’s grey market, however, the 2026 story does not stop at the border between Chinese users and American AI model providers. The transfer station economy exposes blind spots in AI safety frameworks designed to prevent harms that extend beyond the US-China rivalry, from misuse by malicious actors to the erosion of provider traceability, while feeding into criminal markets that exploit ordinary people — many already disadvantaged — caught in the supply chain.

To illustrate how a transfer station works, let’s take Anthropic, the company with the most rigorous geo-blocking mechanism, and whose models are very popular among Chinese developers, as an example.

Geo-blocking and Know-Your-Customer (KYC)

On the map of Anthropic’s supported countries, China is conspicuously absent, and on the Chinese internet, so is Anthropic – technically speaking. In reality, neither Anthropic’s blockage nor the Great Firewall stops Chinese users from accessing Claude and Claude Code. Claude models have thrived on e-commerce apps like Taobao despite supposed platform and government censorship since 2025, and Singapore, with a population smaller than that of New York City, “surprisingly” leads global per capita use of Anthropic’s Claude in April 2026.

The Chinese government is not today especially motivated to curb Chinese developers’ access to advanced US models. Anthropic, on the other hand, is serious about it, with its multiple layers of mechanisms to block users in mainland China. At the most basic level, account registration requires phone numbers, overseas credit cards, and matching billing addresses. On September 5, 2025, Anthropic further prohibited access from any entity more than 50% owned, directly or indirectly, by companies headquartered in unsupported regions like China, regardless of where that entity operates. This closes the subsidiary loophole that had allowed Chinese-backed firms in foreign countries to retain API access.

The most recent measure arrived in April 2026. Anthropic began requiring select users to verify their identity using a government-issued photo ID and a live selfie, making Claude the first major consumer AI platform to implement this level of identity checking. The rollout is selective and triggered by specific use cases or platform integrity flags. For Chinese users accessing Claude through VPN or other intermediaries, the new KYC policy is supposed to make it considerably harder to access Claude–even if Chinese users can fake phone numbers and addresses, they will theoretically have a hard time faking live selfies matched against a physical government document.

In reality, however, Chinese people not only can access Claude and related tools, but most of the time they can purchase tokens at 10% of the original price. The magic lies in “transfer stations.”

What is a “Transfer Station (中转站)”?

A transfer station (中转站) is what the Chinese developer ecosystem calls an API proxy–an overseas server that sits between a developer and Anthropic’s infrastructure. It accepts API requests, forwards them as if they originated from the transfer station’s location, and passes the response back.2 The user redirects their software to the proxy’s server instead of Anthropic’s, and pays the API proxy RMB via WeChat or Alipay.3 This sidesteps both the VPN and the overseas credit card needed for direct access. Prominent transfer stations are catalogued in community repositories and ranked by real-time price and uptime. Below them, a longer tail of small and individual projects comes and goes.

While this setup sounds functionally identical to legitimate Western API aggregators like OpenRouter, transfer stations operate in an entirely different universe of legality and trust. Legitimate aggregators exist to simplify developer workflows, charging standard rates based on transparent enterprise agreements. Transfer stations, conversely, are built explicitly for evasion, routing data through unaccountable middlemen.

Just like providing VPN services or selling Claude on Taobao, a transfer station is technically not allowed in China. According to China’s regulations on the AI services registry, AI services provided without filing and security assessment are illegal. But just as some small businesses can skip AI registration without punishment, so do most transfer stations. However, the bigger the business, the more unsafe it is to run.

The Supply Chain of Transfer Stations

A transfer station is not a sole entity. It sits in the middle of a layered supply chain, with most participants never interacting with each other directly.

Upstream are the resource providers: account merchants who bulk-register or acquire Anthropic accounts at scale; SMS verification platforms that supply the foreign phone numbers needed to pass sign-up checks; and, at the more technical end, reverse engineers who analyze Anthropic’s client code to find authentication shortcuts or detect when detection logic has changed. The payment infrastructure with card merchants and proxy networks also enables overseas billing from inside China.

The upstream also tackles more sophisticated KYC regimes–either by AI or humans. AI services have demonstrated the ability to generate highly realistic fake IDs capable of bypassing identity verification on major platforms, and deepfake tools now allow criminals to create digital clones that successfully pass biometric verification remotely. Even if the defender can successfully detect AI faking humans, a more labour-intensive method exists to find real humans. Agents travel to lower-income countries in Africa or Latin America to recruit real individuals willing to complete in-person verification.4 The Worldcoin black market offered a documented precedent, with iris scans harvested from KYC merchants in Cambodia and Kenya, sold for under $30.

In the middle sits the transfer station itself: a software interface that receives users’ requests and forwards them to Anthropic as if they originated from a legitimate account, a payment integration (usually Alipay or WeChat), and the unglamorous operational layer that keeps it running — cycling accounts before they get flagged, balancing load across the pool, and continuously adapting to Anthropic’s abuse-detection updates.

Downstream are the customers: individual developers using Codex or Claude Code, enterprises routing internal workflows through the proxy, application builders embedding the API in their own products, and secondary resellers who buy wholesale access and repackage it for individual customers on Taobao–as I documented last year.

Almost no one operates the full chain. Most participants own one or two links and monetise those well, resulting in a resilient, modular system. AI model providers can suspend individual operators, but the upstream account pools and downstream customer base remain intact. So long as there are developers who want access to Claude and identity black markets willing to supply the credentials, which are both durable features, a replacement can be stood up quickly.

One Fish, Three Meals (一鱼三吃): How to Make Tokens Cheap

The most curious thing, however, is not how to get access to Claude or Claude Code in China, but how to get it at a ridiculously low price–usually priced at 1 RMB per $1 of tokens — 70–90% below official prices. According to public discussions, there are at least three ways a transfer station makes this possible–often described as “one fish, three meals (一鱼三吃)”.

Meal 1: The markup on access. This is possible because of the upstream resource providers who can stack proxies using at least five relatively “innocent” tactics:

• bulk-registering API accounts to farm Anthropic’s $5 free credit

• reselling unused quota from others’ accounts

• corporate/educational discount arbitrage

• “APImaxxing” — one $200 Max plan carved up among multiple users via tokens-per-hour quotas, exploiting the gap between Anthropic’s flat subscription price and the far higher cost of equivalent pay-per-token API access

Beyond these, there is a darker upstream input: accounts purchased using stolen or fraudulent credit cards which can enter the proxy pool at effectively zero cost to the operator. How large this share is relative to the above four “innocent” tactics is difficult to verify, but the two markets likely share some infrastructure and personnel.

Meal 2: Swapping models and inflating tokens. Because users’ inputs and model outputs are mediated through a proxy, users cannot verify which model their request was actually routed to. A user selects Opus 4.7, but the proxy can silently route to Sonnet, Haiku, or, in the worst case, GLM or Qwen, and fraudulently relabel the output. In a recent paper from Germany’s CISPA Helmholtz Center for Information Security (which cited my article last year on grey market!), researchers audited 17 API proxies and found widespread model swapping–API proxy access to “Gemini-2.5” achieved only 37.00% on a medical benchmark, a staggering drop from the 83.82% performance of the official API. On the user end, the tell only comes on complex tasks, when the output feels off (often referred to as 降智, or “dumbed-down”), but there is no clean way to prove it. Numerous public records highlight concerns that certain API proxies have noticeably compromised model performance. These proxies are suspected of “diluting” (掺水) services by substituting premium frontier models with inferior tiers.

Besides model swapping, overconsumption of tokens also makes the price per token cheaper, though at the expense of driving up the total cost. Some of it is structural, as proxies that rotate accounts frequently destroy cache continuity as a side effect, forcing users to burn full-price tokens on context that would otherwise be nearly free. Some of it may be deliberate as the proxy providers try to milk more usage. The line between the two is difficult to draw from the outside.

Meal 3: The logs are the product. This is perhaps the most important part as it intersects with data privacy and distillation. Every request that passes through a proxy — full prompt, full response, tool calls, iterations — is sitting on the proxy operator’s server. For AI coding agents, those logs contain long reasoning chains, real engineering decisions, repository context, and human-verified correct outputs. This makes them an ideal dataset for post-training: for supervised fine-tuning on real engineering tasks, and, where full reasoning traces are captured, for distilling Claude’s reasoning patterns into smaller models. Chinese developer communities assert this is happening in at least some cases, but whether proxy operators are systematically harvesting and selling these logs, and to whom, remains unverified. However, downstream distillation data does exist on the open web. Several datasets of Claude Opus 4.6 reasoning outputs circulate on HuggingFace with no clear source for the outputs. Theoretically, one can clean and sell similar distilled datasets to other model developers in China.

The first two meals are useful for providing cheaper tokens cheaper than Anthropic officially charges, but to really make prices ridiculously low — at 10%, or even 5%, of the original price — one needs to eat the third meal. And as a Chinese saying goes, there is no free lunch in the world (天下没有免费的午餐). Several Chinese developers have revealed that the markup business is just customer acquisition, and the log harvest is the actual margin. Users are simultaneously paying customers and unpaid data producers, selling their private data to proxy operators in exchange for a low price. Some also warn of potential promotion, fraud, and even blackmail based on leaked users’ data from the proxy. To avoid privacy risks, some Chinese developers have also constructed their own Claude Code API proxy and open-sourced the guidelines.

What Know-Your-Customer Cannot Know

AI usage is gradually shifting from chatbot to tool use. With the rise of agent and token economy, the question of using US models is no longer only about access, but extends to cost-efficiency. This is because the Chinese AI ecosystem, regardless if it is frontier labs, university research groups, individual developers, or hobbyists, is capital-scarce. Meanwhile, the data generated by users through transfer stations demonstrably enters downstream markets, used variably for model training, data brokerage, or fraud. To the extent that distillation is part of that economy, the problem extends far beyond a handful of frontier actors that the government or AI companies in the US might expect.

History teaches us that access blockage rarely stops determined users. They raise the cost of access, which in turn creates profitable markets for anyone with the expertise to lower it. The Great Firewall made VPN services a thriving cottage industry in China. KYC requirements bred an identification-faking economy, from domestic ID card resellers to biometric harvesting operations in Southeast Asia or Africa. Layered controls by frontier AI companies— geoblocking, phone verification, credit card requirements, and now live biometric checks — have produced the same effect.

The story, however, goes beyond a “Anthropic/US versus China” framing. This points to an uncomfortable truth about access control, both in terms of geopolitical boundaries and beyond. How a geo-blocked developer walks around the controls is, structurally, the same methods plausibly employed by a terrorist to access a frontier AI model and make destructive bioweapons without being tracked. The access problem is both a unique geopolitical consideration and a shared safety concern.

Today, AI safety research treats system-level access control — in particular, detecting, monitoring, and account suspension for publicly accessible closed-weight models — as an important safeguard. In monitoring, developers control inference infrastructure, including flagging harmful inputs and outputs in real time. Detecting such as KYC requirements assumes that the provider can attribute behaviour to identifiable actors, and account suspension similarly assumes that suspending an account meaningfully denies access. However, US model providers do not control inference for Chinese users routing through a transfer station — the proxy operator does. When a harmful request arrives, rather than seeing the IP of the real user, AI model providers see that of the proxy. And when an account is banned, the upstream supply chain can easily set up a new proxy within hours.

The problem compounds for more sophisticated monitoring tools. Anthropic’s Clio system, designed partly to detect coordinated misuse that is invisible at the individual conversation level, works by identifying patterns across accounts and conversations. It identified, for example, a network of automated accounts using similar prompt structures to generate search engine spam and subsequently banned them. But because requests route through proxies, bans do not meaningfully stop the underlying behaviour. And for deliberately staged attacks — such as distributing a harmful inquiry across multiple stages and proxy accounts, each request individually innocuous — cross-account patterns are far less visible than coordinated spam, where the signal is obvious by design.

Lastly, the transfer station does not only embody a traditional offence/defence paradigm — whether between US AI companies and Chinese users or between AI safeguards and malicious actors. A black market has a supply chain with its own exploitative logic, and the harms it generates extend well beyond the original question of access. Faces harvested for proxy KYC verification to bypass Anthropic’s system today can be resold to open fraudulent financial accounts, fabricate employment records, or generate deepfakes tomorrow, with the original subject in the Global South bearing the legal and reputational consequences. The same infrastructure that routes Claude requests can be used to defraud users through model substitution, targeted scams based on leaked prompt data, or blackmail. The account-farming operations that keep proxy pools stocked — bulk SMS verification, fraudulent registrations, carded accounts — nurture broader criminal markets for spam calls, phishing texts, fraudulent loan applications, and credit card scams. Many harms have nothing to do with AI or geopolitics.

But now that every byproduct of the grey market–from the potential danger of terrorists leveraging AI to synthesize the next pandemic to real-life exploitation and crime. As much as the Great Firewall or AI geo-blockage wants to separate who gets access to frontier technology along national lines, as the grey market reveals, the harms are not separable.

Acknowledgement:

Zilan is grateful to Alan Chan, Gabriel Wagner, Karuna Nandkumar, and Kayla Blomquist for their helpful feedback.

The author acknowledges the use of LLMs for preliminary desk research, technical concepts clarification and copy-editing, and is, in fact, very grateful that she can still use VPN to access Claude in mainland China via the Singapore node without triggering the KYC process.

Earlier this year we launched an economic security contest. We had two prompts:

• What are the most important high level KPIs that policy should aim for? What is the analogy of the Fed’s ‘2% inflation and full employment’ target for economic security?

• Where today would you put $10-50bn to get the most for your investment in economic security? Feel free to propose both defensive and offensive ideas, and either a portfolio of ideas or the one large idea you think will deliver the most value.

Last week we ran our first essay winner.

Our second essay comes from Naveen Krishnan, a Belfer Young Leaders research fellow at Harvard with the Belfer Center for Science and International Affairs, where he specializes in artificial intelligence capabilities and U.S. national security policy. He is an intelligence officer in the U.S. Navy Reserve. His views are his own and do not represent those of the U.S. Navy or Harvard.

The United States stopped manufacturing its own TNT in 1986. For decades afterward, the Army bought its primary explosive fill from Russia and Ukraine. When one supplier invaded the other in February 2022, the Army needed to surge 155mm artillery shell production from 14,500 rounds per month to over 100,000. The binding constraint (instead of money) was America’s physical inability to produce the explosives, propellants, and shell casings at the required pace. Congress appropriated nearly $5 billion. But four years and billions of dollars later, production has reached only 40,000 rounds per month.

This is what an economic security failure looks like: the absence of the industrial base required to turn money into output under crisis conditions - regardless of how ‘urgently’ Congress pushes. Money is not a magic wand for manufacturing; in a crisis, you cannot simply legislate or spend your way out of the physical reality of industrial systems. The U.S. remains vulnerable precisely when surges are necessary: a scenario where we have the capital to buy, but no physical mechanism to produce.

Across the political spectrum, policymakers recognize this crisis and see that the U.S. government must take a more active role in securing the supply chains that underpin national power. Yet this activism lacks a dashboard. We have no headline numbers that tell policymakers whether the United States is becoming more secure or less secure, by how much, and where the gaps are. Policy debates fruitlessly devolve into competing lists of vulnerabilities (e.g. chips, minerals, pharma) without a unifying framework for tradeoffs. The result is incoherent allocation: billions for flagship semiconductor fabs while the Army cannot produce enough artillery shells for a single theater war.

This essay proposes the missing headline: two metrics, in productive tension, that together define economic security the way inflation and unemployment define macroeconomic health for the Federal Reserve.

A Dual Mandate for Economic Security: The Chokepoint Exposure Index and Mobilization Elasticity

Metric 1: Chokepoint Exposure Index (CEI%): The percentage of U.S. GDP at risk from adversary-controlled supply chain chokepoints across critical industries. This measures dependency: where the economy is vulnerable to coercion. Target: below 2% of GDP.

Metric 2: Mobilization Elasticity (ME): The speed and scale at which the U.S. can surge production of critical goods (e.g. finished weapons systems, essential medicines) under crisis conditions, without destabilizing or intolerable price spikes. This measures production capacity: whether the economy can actually respond when coercion hits. Target: 50% output increase within 180 days.

The first metric tells policymakers where the economy is exposed. The second tells them whether it can fight back. Together, they force the tradeoffs that matter most: engagement versus self-sufficiency and openness versus resilience: the central balancing acts of economic security in the age of weaponized interdependence.

The Productive Tension

The Fed’s dual mandate (maximize employment, stabilize prices) works as a policy framework precisely because its two targets pull against each other. Pushing unemployment down requires stimulative policy (low interest rates, quantitative easing) that risks overheating prices. Pushing inflation down requires restrictive policy (high interest rates, tighter credit) that risks killing jobs. The tension is the point: it forces the Fed to find the frontier between the two goals rather than blindly maximizing one at the expense of the other. The published numbers (unemployment rate, PCE inflation) give Congress and the public a simple scorecard to judge whether the Fed is managing the tradeoff well.

The two metrics in this essay (CEI% and ME) create the same productive tension for economic security. The most direct way to cut chokepoint exposure (lower CEI%) is to reshore production: build domestic fabs, refine rare earths at home, manufacture APIs on American soil. But reshoring is slow, expensive, and ties up capital for years in construction instead of surge tooling, workforce training, and standby capacity that would raise ME today. Worse, the OECD’s 2025 Supply Chain Resilience Review found that aggressive reshoring actually made more than half of modeled economies more vulnerable to supply shocks, by concentrating production in a single location over maintaining diverse allied sources and friendly partners. Conversely, the fastest way to raise ME is to maintain deep allied supplier networks and strategic stockpiles, but that means accepting continued dependence on some foreign nodes, keeping CEI% elevated. Neither metric can be maximized alone without damaging the other. That tension forces the policy question that matters: for each critical input, what is the right mix of domestic production, allied diversification, stockpiling, and demand-side flexibility?

Why Dependencies and Production (and Not Innovation)

A natural instinct is to make technological leadership the centerpiece of economic security. But innovation already has institutional infrastructure: the U.S. spent $192.2 billion on federal R&D in FY2025, with the Department of Defense accounting for 62% of the FY2026 request. NSF, DARPA, DOE national labs, and the CHIPS and Science Act’s R&D provisions are all aimed squarely at the frontier.

The core of economic security is the supply chain underneath it. The United States can design the world’s most advanced chip but be unable to produce it without TSMC. It can invent breakthrough battery chemistry but depend entirely on Chinese-processed rare earth magnets for every motor that uses it. The policy-relevant issue is “given resource constraints and a preexisting factor allocation, how much should we spend to boost our manufacturing capabilities?” CEI% and ME target that question directly, the production and resilience layer that existing R&D policy does not address.

The following two sections break down the technical details for each metric and where they stand today.

Metric 1: The Chokepoint Exposure Index (CEI%)

What It Measures

CEI% answers a single question: What percentage of U.S. GDP is at risk because critical inputs flow through supply chain nodes that a geopolitical adversary can credibly deny, restrict, or weaponize?

This operationalizes the concept of “weaponized interdependence”, Farrell and Newman’s insight that states controlling centralized hubs in global economic networks can exploit the chokepoint effect to deny adversaries access and the panopticon effect to extract information. CEI% focuses on the chokepoint effect: where can an adversary cut the pipe, and how much of the U.S. economy is downstream?

The critical distinction between CEI% and raw import dependence is that not all dependence is dangerous. Importing 90% of a mineral from Canada is concentration, but it is not a chokepoint. Canada is a treaty ally with deeply integrated economic interests and no credible coercion motive (setting aside recent tensions in 2026). Only nodes that pass all three simultaneous filters enter the index: (1) high concentration, where a single country or small bloc controls over 40% of global supply; (2) adversary control, where the dominant supplier is a strategic competitor, not an ally; and (3) low substitutability, where fewer than three qualified alternatives exist globally with switching times exceeding 12 months. This triple filter separates dangerous dependencies from benign ones.

Scope: Critical Industries That Underpin National Power

CEI% covers only inputs and downstream products relevant to defense, public health, energy, and critical infrastructure, defined by three existing government-maintained lists:

• USGS Critical Minerals List (2025): 60 minerals evaluated against supply risk, import reliance, and importance to national security and the economy. The 2025 list expanded from 50 to 60 minerals, adding copper and others based on updated methodology.

• CISA Critical Infrastructure Sectors: 16 sectors designated under Presidential Policy Directive 21, including the defense industrial base, energy, healthcare, water systems, and communications.

• BIS Export Control Classifications: Technologies subject to export restrictions due to national security significance (advanced semiconductors, AI-enabling hardware, quantum computing components, and advanced materials.)

A separate all-industry anomaly scan runs quarterly as a watchlist, flagging any node that crosses the triple-filter threshold but is not yet on any official list. This is how gallium and germanium (materials barely discussed in policy circles before 2023) would have been caught before China restricted them. But the headline CEI% number reflects only the designated critical basket.

How to Calculate CEI%

Step 1 - Map the supply network: Construct a directed graph from three public datasets. The Bureau of Economic Analysis publishes annual input-output tables covering 70+ industries (and 400+ industries in benchmark years), showing production relationships among domestic industries and commodities. The OECD Trade in Value Added (TiVA) database, most recently revised in January 2026, provides value-added trade flows across 50 industry sectors for 76 countries, revealing where value is actually created, not just where goods merely transit. UN Comtrade provides bilateral product-level trade data at the HS 6-digit level for over 200 countries, enabling granular identification of which country supplies which input. Each node in the resulting graph is a country-product pair. Each edge represents a flow of intermediate goods or value-added.

A caveat on data sources. BEA input-output tables, OECD TiVA, and UN Comtrade are the best public starting points, but they were not built to identify supply-chain chokepoints. They aggregate at industry level, not at firm-or-facility level; they rarely reveal which specific facility supplies a sub-component; and they lag real flows by months to years. The CEI% number computed from these sources should be read as a lower bound on true exposure. A serious operational version of this dashboard would supplement public data with three classes of new collection: (1) facility-level supplier mapping commissioned from private supply-chain intelligence firms (Z2Data, Interos, Exiger, Sayari) on a critical-basket subset; (2) mandatory Tier-2 and Tier-3 supplier disclosure for federal contractors above a threshold contract value, modeled on conflict-minerals reporting; and (3) commercial trade-receipt data (bills of lading, customs filings) acquired under contract. The headline CEI% number should be published from the public data so that it is replicable; the watchlist and the policy-trigger logic should run on the augmented data.

Step 2 - Identify chokepoint nodes: For each node in the critical basket, compute: (a) supplier concentration using the Herfindahl-Hirschman Index, where HHI above 2,500 indicates a highly concentrated market per DOJ/FTC standards; (b) whether the dominant supplier is an adversary or an ally; and (c) substitutability, proxied by the number of qualified alternative suppliers and estimated switching time. Only nodes passing all three filters qualify as chokepoints.

Step 3 - Propagate through the Leontief inverse: This is the critical quantitative step: A chokepoint input may represent only 2% of a sector’s direct input costs, but if it is a binding constraint (with no near-term substitute) losing it can shut down 100% of downstream output. The Leontief inverse matrix, (I − A)⁻¹, captures these cascading higher-order effects. As Baqaee and Farhi have shown, in the short run before firms can adjust sourcing, the economic impact of losing an input is proportional to the value of all downstream final products, not just the cost of the input itself. The short-run impact can be orders of magnitude larger than the long-run marginal effect described by Hulten’s Theorem, because production is Leontief-like (requiring fixed proportions of inputs) before substitution kicks in. For each chokepoint node, multiply the direct disruption by the column sum of the Leontief inverse for that sector.

Step 4 - Apply risk weights: Not every chokepoint is equally likely to be weaponized. A weaponization probability is assigned based on demonstrated behavior: adversaries that have previously restricted an input (China restricted rare earths against Japan in 2010, gallium and germanium in 2023, antimony in 2024, and rare earth magnets in 2025) receive higher probability scores than adversaries with concentrated supply but no demonstrated intent. This transforms CEI% from a raw exposure measure into a risk-weighted measure, analogous to how Basel III bank capital requirements weight assets by riskiness rather than face value.

Step 5 - Compute CEI% as a percentage of GDP:

CEI% = (1/GDP) × Σⱼ Pⱼ × [(I − A)⁻¹]ⱼ · Dⱼ × Sⱼ

where Pⱼ is the weaponization probability, Dⱼ is the direct output disruption if node j is denied, Sⱼ is the substitutability adjustment (1 = no alternatives, approaching 0 = fully substitutable), and GDP is used as a denominator to make the metric comparable over time and intuitively legible.

What the Numbers Reveal

China’s mineral export controls since 2023 have moved from threat to reality: exports of unwrought gallium have been near zero throughout 2025, with European prices up 365%; germanium exports fell 60% with prices up 400%; antimony exports collapsed with a 437% price spike. In April 2025, China imposed new controls on seven categories of rare earth elements and magnets, directly targeting inputs to defense systems and electric vehicle motors. An illustrative aggregate CEI% today likely sits in the 3-4% range, meaning roughly $0.9–1.3 trillion in risk-weighted economic output depends on adversary-controlled chokepoints. (This is an order-of-magnitude estimate, not a precise computation.) But the point is that even this rough estimate reveals an exposure level far above the 2% target, and that the metric is computable with existing public data, making it auditable and apolitical.

How to Track It Over Time

CEI% can be computed retroactively from historical Comtrade, BEA IO, and TiVA data going back to 2000, revealing a clear trajectory: CEI% rose steadily as China entered the WTO and captured critical manufacturing share (2001-2010), accelerated as rare earth processing and pharmaceutical API production consolidated (2010-2020), and peaked in the 2022-2025 period as China began actively weaponizing its chokepoint positions. Whether the CHIPS Act, IRA, and allied mineral agreements are sufficient to bend the curve downward is the central policy question, and CEI% provides the number to answer it.

Metric 2: Mobilization Elasticity (ME)

What It Measures

ME answers the question: For a set of identified critical goods, how quickly can U.S. and allied production (plus stockpiles) reach crisis consumption level and keep it there for at least a year, without repeating unacceptable price blowouts or chronic drug shortages?

Where CEI% maps dependency, ME maps production capacity. The key insight is that economic security is fundamentally about responsiveness. A country producing 5% of its own rare earth magnets but able to ramp to 30% in six months is more secure than one producing 25% with zero surge capability. The OECD’s 2025 Supply Chain Resilience Review confirms this: geographic diversification and adaptability outperform reshoring as resilience strategies, and “aggressive reshoring” actually made more than half of modeled economies more vulnerable to shocks. Reshoring supply chains globally could shrink trade by 18% and cut GDP by over 5%, while doing little to increase supply chain resilience.

Two elasticities, not one: ME as defined here measures supply-side responsiveness - how quickly U.S. and allied production can rise when coercion hits. But economic security also depends on demand-side responsiveness: how quickly the United States can ration, substitute, or defer non-essential consumption of a critical input until supply catches up. A country with a supply elasticity of 0.05 but a demand elasticity of 0.40 (because half of consumption is in non-essential applications that can be temporarily switched off) is meaningfully more secure than one with the same supply curve but inelastic demand.

The ME framework admits a complement: Demand Elasticity (DE), the share of crisis consumption that can be reduced within 180 days through rationing, technical substitution, or non-essential-use shutdown without unacceptable welfare cost. For example, in the case of Gallium, roughly 40% of U.S. gallium consumption goes to GaN power devices in non-defense applications (consumer electronics, EV charging) where substitution to silicon carbide or graceful performance degradation is possible on a months-to-quarters timescale. The effective elasticity facing the policymaker is therefore β + δ, not β alone. Future iterations of the dashboard should publish both terms.

The ME Basket: Inputs and the Things They Build

The ME basket is deliberately broader than CEI%’s upstream input basket. CEI% tracks chokepoint inputs (the raw materials and components that adversaries control.) ME tracks the ability for US + allies to surge production of both those inputs and, more importantly, the critical downstream products they feed into. This means the ME basket includes:

• Hard power systems: 155mm artillery shells, Stinger and Javelin missiles, precision-guided munitions, naval vessels, hypersonic weapon components: the outputs of the defense industrial base that determine whether the United States can sustain a fight.

• Critical healthcare products: Generic pharmaceuticals, APIs, IV fluids, medical devices: the products whose shortage during COVID-19 and the ongoing drug shortage crisis demonstrated that health system resilience is a national security issue.

• Energy infrastructure: Power transformers (2-3 year lead times, no demonstrated surge), grid-scale batteries, solar panels, critical energy components.

• Upstream critical materials: Rare earth magnets, gallium, germanium, antimony, pharmaceutical precursors (the same inputs tracked by CEI%, now measured for their production ramp capability.)

The logic is straightforward: CEI% identifies the chokepoint in Chinese rare earth processing. ME must answer whether the United States or allies can actually produce the missiles, motors, and turbines that depend on those magnets (and not just whether it can source the magnets themselves.)

Security is ultimately about the end products.

How to Calculate ME

Step 1 - Define the critical-goods basket: The ME basket combines two layers: (a) the upstream inputs from CEI%’s critical basket, and (b) the downstream defense, health, and infrastructure products those inputs feed into, as identified through the BEA input-output requirements tables. Each item gets a criticality weight based on GDP-at-risk (from CEI%) and national security priority (from CISA sector designations).

Step 2 - Measure current capacity slack: The Federal Reserve’s G.17 release provides monthly data on industrial production and capacity utilization across manufacturing sectors. Overall manufacturing capacity utilization in early 2026 hovers around 75-76%, but this aggregate masks enormous variation. The munitions sector ran at 95%+ utilization pre-Ukraine with effectively zero slack. Specialty chemicals operate near capacity. The critical step is disaggregating to the ME basket level, measuring slack in the sectors that matter for crisis response, not in manufacturing as a whole. This methodology relates to US production; analogous calculations are executed to extend the metric to allied production.

Step 3 - Estimate the supply response function. For each sector in the basket, the core building block is β₆ : the realized supply elasticity at the six-month horizon. Instead of relying solely on econometric estimation, the most transparent and defensible approach is to ground each β in a documented historical demand-shock episode: measuring the actual production rate at the start of the shock (Q₀) and six months later (Q₆), then computing:

β₆ = (Q₆ − Q₀) / Q₀

This is a direct empirical measure which makes each estimate transparent and replicable, but also specific to the historical episode used. Different crisis scenarios would produce different responses. Where the historical episode involved a baseline of zero (Stinger, primary gallium), β₆ is reported as zero because the policy-relevant question is whether the U.S. could surge at all. The methodology, sources, and per-good calculations are documented in the Appendix.

Step 4 - Apply the price penalty: Output surge is worthless if it comes with a price spike that cascades through the civilian economy, but the relevant price threshold depends on who is buying. For government-procured defense goods, the buyer is the federal government, which can and does absorb large cost premiums when the alternative is a capability gap in wartime; the acceptable price increase (α) is set at 200%. For civilian-critical goods with concentrated institutional buyers (hospitals, health systems), α is set at 100%, these buyers can absorb moderate premiums but begin rationing when prices double. For civilian-critical goods with dispersed private buyers (utilities, manufacturers, consumers), α is set at 50%, beyond that, price cascades cause project cancellations, demand destruction, and systemic risk that undermines the purpose of the surge. The formula is:

MEᵢ = β₆ × max(0, 1 − ΔPᵢ/(Pᵢ × α))

This tiered approach reveals three distinct failure modes: sectors where the U.S. cannot physically surge regardless of price (Stinger, gallium), sectors where it can surge but only at prices that destroy downstream economics (N95s, transformers), and sectors where modest surge capacity survives the price screen (munitions, some pharmaceuticals). The policy response differs for each. (These α have been set for illustrative purposes for these calculations and can be changed on a per item basis.)

A tiered α by buyer class:

Step 5 - Aggregate using the harmonic mean: The national ME is the criticality-weighted harmonic mean across the basket:

ME = (Σ wᵢ · (1/MEᵢ))⁻¹

The harmonic mean is needed because the weakest link dominates. An economy that can surge 50% in steel but 0% in rare earth magnets is as vulnerable as its least elastic input. This is the mathematically correct property for a security metric: security is defined by the binding constraint instead of the average.

What the Numbers Reveal

The tables above present ME estimates for nine critical goods, each grounded in a specific historical demand-shock episode with publicly verifiable production data. Full sourcing and methodology are in the Appendix.

Table Details: β₆ is the realized share by which monthly output rose between the start of the historical demand-shock episode and six months later, computed from publicly reported production rates. Sources: Defense One; U.S. Army PEO Ammunition; Lockheed Martin and RTX corporate disclosures; FDA CY2024 Report to Congress; USGS Mineral Commodity Summaries 2025; Wood Mackenzie Q2 2025 Transformer Supply Chain Report; Swedish National China Centre 2025 review of Argus / Fastmarkets / China Customs data; TSMC corporate disclosures.

Four sectors: Stinger (ME = 0, line cold for 20 years), gallium/germanium (ME = 0.01, no primary production), leading-edge logic (ME = 0.02, no surge mechanism in a 3-to-5-year fab cycle), and generic injectables (β₆ = −0.30, supply contracted after the Intas shutdown), have surge capacity at or below zero and are excluded from the harmonic mean. They represent binding constraints requiring distinct policy responses, as described below.

The remaining five sectors produce an aggregate ME of 0.045, meaning the U.S. can scale output by less than 5% within six months even in the sectors where some capacity exists. The 0.50 target remains distant by more than an order of magnitude. Even the N95 success story (β₆ ≈ 2.30, the only genuine surge in the basket) does almost nothing to lift the aggregate because the harmonic mean is dominated by the weakest links.

The price penalty column adds nuance: The relevant threshold depends on who is buying: 200% for government-procured defense goods (the Army will pay 3× per shell if shells exist to buy), 100% for civilian goods with concentrated institutional buyers like hospitals, and 50% for goods with dispersed private buyers like utilities and manufacturers, where price cascades cause project cancellations and systemic risk. Applying these tiered thresholds reveals three distinct failure modes detailed below.

Policy Implications:

America cannot physically surge, price irrelevant: Stingers, gallium, germanium, leading-edge semiconductors, and generic injectables have ME at or near zero regardless of price tolerance. For munitions and minerals, the binding constraint is industrial capacity. For generics, the constraint is structural: concentrated manufacturing, thin margins, and 85% foreign API sourcing mean the system contracts when a major supplier fails instead of surging to compensate. Policy response: DPA Title III investments, second-source qualification, stockpiling, and (for pharmaceuticals) reforming the reimbursement incentives that make domestic API production uneconomic.

America can physically surge but price destroys downstream: N95 respirators and power transformers show positive physical β₆ but zero price-penalized ME. When N95 prices went to 10× list, hospitals rationed and reused them. When transformer prices rose 77%, utilities delayed grid projects. Policy response: strategic reserves sized to bridge the spike, demand-side rationing authorities, pre-negotiated surge pricing contracts.

America can modestly surge at manageable prices: 155mm shells, Javelins, and some generics retain small but real price-adjusted ME. These are the sectors closest to functioning, where marginal investment in warm standby lines and pre-qualified second sources has the highest payoff per dollar.

The target (ME above 0.50) means the U.S. can scale output of critical goods by 50% within 180 days at prices sustainable for the relevant buyer class. This creates accountability for the unglamorous work that actually moves the needle: pre-qualifying backup suppliers, training machinist pipelines, maintaining warm production lines, and positioning strategic stockpiles.

Institutional Design: Making the Numbers Real

Publishing body: The natural home is a new Office of Economic Security Analytics modeled on the analytical independence of the Bureau of Labor Statistics, civil-service economists and supply-chain analysts whose published numbers cannot be edited for political convenience. The 2025 CFR Task Force on U.S. Economic Security recommended dedicated institutional capacity for exactly this function.

The Department of Commerce is also an obvious home (BIS already runs the export-control list, ITA runs trade defense), but it is also a department whose recent track record on industrial policy execution (from the slow CHIPS Act disbursement timeline to the politicized handling of entity-list decisions) gives many people pause. Two alternatives for consideration: (1) a federally chartered nonprofit on the model of MITRE or IDA, contracted by Commerce but operationally insulated; or (2) a joint office reporting to both Commerce and the Director of National Intelligence, on the model of the National Counterintelligence and Security Center. The institutional choice matters less than the principle: the office must have genuine analytical independence and a publication cadence that cannot be halted by an incoming administration that finds the numbers inconvenient.

Publication cadence: Quarterly CEI% dashboard with sector and adversary decomposition, plus a top-10 chokepoint node list and watchlist. Annual ME assessment with sector-level scores, historical backtesting, and explicit policy recommendations for the lowest-ME sectors.

Policy triggers: When CEI% for any single chokepoint exceeds a threshold (when any individual adversary-controlled node puts more than 0.5% of GDP at risk) an automatic interagency review is triggered with a mandatory 90-day action plan. When ME for any critical-basket sector falls below 0.15 (when surge capacity is essentially nonexistent) the same trigger fires.

The Toolkit: What “Action” Actually Looks Like

The Federal Reserve’s dual mandate works because it comes with instruments that move markets within hours. CEI% and ME need their own toolkit: narrower than monetary policy, but real. Five categories of instrument should be linked to the metric:

1. Strategic stockpiling at scale: The Defense Logistics Agency’s National Defense Stockpile is currently funded at roughly $1 billion per year and holds materials worth a fraction of one percent of GDP. When CEI% on a single chokepoint exceeds the 0.5%-of-GDP trigger, the stockpile authority should be empowered to acquire forward inventory equal to 12 months of U.S. consumption of that chokepoint input within 180 days, funded from a standing appropriation that does not require fresh congressional action. This is the equivalent of the Fed’s open-market desk (fast, rule-bound, and large).

2. Defense Production Act Title III investments: DPA Title III already permits direct equity investments and loan guarantees to expand domestic production of critical inputs. When ME for a critical-basket sector falls below 0.15, a DPA Title III action plan should be required within 90 days, with a binding obligation to obligate funds within 180 days. The MP Materials–DOD partnership (which committed to scaling U.S. rare earth magnet capacity from near-zero to an estimated 10,000 metric tons annually by 2028) is the model.

3. Allied-sourcing fast-track: Most resilience gains come from diversification to allies, not reshoring (the OECD 2025 Supply Chain Resilience Review is explicit on this). The dashboard should trigger automatic Section 232 exemptions, USMCA fast-track designation, and AUKUS-style defense procurement carve-outs for inputs sourced from a defined ally bloc when CEI% on the input exceeds the trigger.

4. Demand-side authorities: Drawing on the demand-elasticity insight above, the toolkit should include the authority to suspend non-essential federal procurement of a chokepoint input during a designated crisis (analogous to Cold War priority-rating systems), and to issue voluntary efficiency standards that reduce private-sector demand without triggering an outright price-control regime.

5. Targeted second-source qualification grants: The single most effective cheap intervention is paying the qualification cost for a backup supplier, whether for a missile component or a generic API, so that switching time falls from 18 months to 90 days. The metric should trigger automatic FDA, DOD, and DOE qualification-grant authority for second sources in any critical-basket sector with ME below 0.15.

The analogy to the Fed is imperfect, as there is no “interest rate of economic security”, but the principle holds: a metric without a policy lever is a thermometer in a room with no thermostat. The five instruments above are the thermostat.

What These Metrics Do Not Directly Measure

A qualification on technological leadership. CEI% and ME do not directly measure innovation as a headline metric, but they should not be read as endorsing import substitution at any quality cost. A surge to 30% domestic production of a leading-edge chip at two-generation-old quality is worse than a continued reliance on a single Taiwanese supplier, because the resulting domestic ecosystem cannot actually run the modern applications that economic security is trying to protect. Two guardrails follow:

First, the ME basket should be defined at the relevant performance specification, not at the generic product class: “sub-7nm logic” rather than “semiconductors,” “GaN-on-SiC RF amplifiers above 100 W” rather than “power electronics.” Output that does not meet the relevant spec does not count toward the surge.

Second, when a product class has a specification frontier moving faster than domestic capability can match, the dashboard should flag the gap and refer the question to the existing technology-policy apparatus (CHIPS R&D, DARPA, DOE national labs) instead of pretending the ME framework can resolve it. The dual mandate is necessary but not sufficient, and that’s the point of having a separate technology-leadership policy track that runs alongside it.

Innovation metrics (patent counts, R&D spending, venture capital flows) belong in technology policy, which has its own institutional apparatus and its own billions of annual budget. Conflating economic security with technological leadership allows every dollar justified as “security” to flow toward glamorous frontier research over the unglamorous work of qualifying backup suppliers, training machinists, pre-positioning stockpiles, and maintaining warm production lines.

By limiting the mandate to dependencies (CEI%) and production capacity (ME), these metrics force policy attention onto the industrial base that actually makes things: the layer where the United States is most visibly failing. Examples: The Stinger missile production line was closed. The Army hadn’t bought a Stinger in 18 years. The U.S. hadn’t manufactured its own TNT since 1986. These are production and industrial base failures. CEI% and ME are designed to ensure they never happen again, or at minimum, to ensure that when they do happen, there is a published number that holds policymakers accountable.

While the Fed’s dual mandate did not “solve macroeconomics,” it gave policymakers a common language, a set of targets, and a transparent scorecard. Economic security will benefit from this outlined scorecard with benchmarks like CEI% below 2% of GDP and Mobilization Elasticity above 0.50.

Appendix A: ME Calculation Methodology and Sources

For each critical good i, ME is estimated from a specific historical demand-shock episode. The actual production rate at the start of the shock (Q₀) and six months later (Q₆) are observed, then:

β₆ = (Q₆ − Q₀) / Q₀

This is a direct empirical measure which makes each estimate transparent and replicable, but also specific to the historical episode used. Where the historical baseline is zero, β₆ is reported as zero. Two ME values are reported: ME (physical), which is β₆ alone, and ME (price-adjusted), which applies the tiered price-penalty formula from the main text. The acceptable price threshold (α) varies by buyer class: 200% for government-procured defense goods, 100% for civilian goods with concentrated institutional buyers (hospitals), and 50% for civilian goods with dispersed private buyers (utilities, manufacturers).

A note on zero-baseline sectors. For three sectors (leading-edge logic, NdFeB magnets, gallium/germanium), the pre-shock U.S. production baseline was effectively zero, making the standard β₆ formula undefined (division by zero). For these sectors, ME is estimated as the share of U.S. demand that new or trial domestic capacity could serve within six months of the relevant shock, a related but distinct measure that captures the same policy question: how much can the U.S. produce when it needs to? For one sector (generic injectables), β₆ is negative because the system contracted instead of surging; ME is reported as zero.

155mm artillery shells

α = 200% (defense)

Q₀ = 14,500 rounds/month, the pre-war rate confirmed by Maj. Gen. John Reim (Joint PEO Armaments and Ammunition), reported by Defense One (June 2025) and at a CSIS event (February 2024). Q₆ ≈ 15,200 rounds/month (August 2022): supplemental funding flowed in mid-to-late 2022, but new propellant and TNT lines did not come online until 2024–25. Production reached 28,000/month by October 2023 and 40,000/month by September 2024, where it plateaued through mid-2025, roughly 30 months to roughly triple. The Army’s target of 100,000/month by October 2025 was repeatedly missed and pushed to mid-2026.

Binding constraints were physical: the U.S. hadn’t manufactured TNT since 1986, propellant production depended on imports from Poland, France, Czech Republic, Korea, and Canada, and qualified workers had to be trained from scratch. A $435 million domestic TNT contract (Repkon USA, Graham, Kentucky) was awarded in November 2024.

Price impact: ~+15% unit cost in year one. Well within the 200% defense threshold.

β₆ ≈ 0.05. ME (physical) = 0.05. ME (price-adjusted) ≈ 0.046.

Stinger MANPADS

α = 200% (defense)

Q₀ ≈ 0/month: RTX had not built new Stingers in roughly 20 years. The Pentagon awarded a $624.6 million contract for 1,300 missiles in May 2022. Q₆ ≈ 0/month: then-CEO Greg Hayes told investors in April 2022 that Raytheon could not ramp production until 2023 because the missile contained obsolete components requiring redesign. Wes Kremer (former Raytheon president) estimated 30 months from contract to first units, retired employees were drafted to teach current staff how to build the missile.

By 2024, Raytheon was ramping to 60 Stingers/month (FlightGlobal). A $700 million NATO contract (2024) added 940 missiles for Germany, Italy, and the Netherlands. A Raytheon spokesperson told Breaking Defense in August 2025 the company is “doubling Stinger production capacity over the next five years.”

Price impact: irrelevant: zero output means no market price for surge units.

β₆ ≈ 0.00. ME = 0.00.

Javelin ATGMs

α = 200% (defense)

Q₀ ≈ 175/month (2,100/year), per Lockheed Martin’s media kit and February 2024 corporate update. Q₆ ≈ 180–200/month: modest overtime ramp, no meaningful capacity addition. The ramp from 2,100 to 2,400/year (14% increase) took until 2024. The further ramp to 3,960/year requires 14 new test stations in Troy, Alabama and 8 in Ocala, Florida, targeting late 2026, a 50%+ expansion taking approximately four years. On August 29, 2024, the Army awarded the JJV a $1.3 billion contract, the largest single-year Javelin contract to date.

Price impact: ~+5%. Negligible against the 200% threshold.

β₆ ≈ 0.05. ME (physical) = 0.05. ME (price-adjusted) ≈ 0.049.

N95 respirators

α = 50% (dispersed civilian buyers)

Q₀ ≈ 45 million/month domestically (3M-dominated). Q₆ ≈ 150 million/month by August 2020: 3M roughly tripled output, Honeywell stood up new lines, and dozens of new entrants added capacity under DPA Title III orders. β₆ ≈ 2.30, by far the highest in the basket and the only case of genuine surge capacity.

But spot prices rose 5× to 15× depending on grade and channel; hospitals reported paying 10× list. This far exceeds the 50% threshold for dispersed civilian buyers. The physical surge was real; the economic surge was fictitious.

β₆ ≈ 2.30. ME (physical) = 2.30. ME (price-adjusted) = 0.00.

Generic sterile injectables (cisplatin/carboplatin)

α = 100% (concentrated institutional buyers - hospitals)

Intas Pharmaceuticals (Accord Healthcare) facility shutdown after FDA inspection findings, February 2023. Intas supplied roughly 50% of U.S. cisplatin. Q₆ ≈ 70% of baseline: emergency imports from Qilu (China) and 503B compounders restored partial supply by mid-2023, but the Intas facility remained below normal through Q3.

Structural context: per the FDA’s CY2024 Report to Congress, 1,459 potential shortage situations were reported by 151 manufacturers that year. Manufacturers operate at 80%+ capacity with thin margins; 85% of APIs come from foreign facilities (ASPE January 2025 brief); 40% of generic drug markets have a single manufacturer; roughly 272 active shortages tracked by ASHP as of mid-2025.

Price impact: cisplatin rose ~25%, within the 100% hospital-buyer threshold.

β₆ ≈ −0.30: the system contracted instead of surging, with output falling to roughly 70% of baseline by month six. This is a structural fragility. ME (physical) = 0.00. ME (price-adjusted) = 0.00.

Leading-edge logic (≤7nm)

α = 50% (dispersed civilian buyers - fabless chip companies)

No historical demand-shock episode exists because there was essentially no U.S. leading-edge logic to surge. TSMC Arizona is the relevant proxy: committed 2020, broke ground 2021, Phase 1 entered N4 production Q4 2024, a four-year construction cycle. Mid-2025 output: ~15,000 wafer-starts/month, ramping toward design capacity of ~24,000 wpm. Global TSMC leading-edge capacity exceeds 150,000 wpm; Arizona is ~10% of that. Phase 2 (3nm) targets H2 2027; Phase 3 (2nm/A16) broke ground April 2025. Total committed investment: $165 billion, the largest FDI in a U.S. greenfield project in history.

There is no physical mechanism by which leading-edge wafer output can surge in 180 days. New fab construction takes three to five years.

Price impact: U.S.-made chips carry a ~50% cost premium over Taiwan-made equivalents, right at the threshold.

ME ≈ 0.02. ME (price-adjusted) ≈ 0.00.

NdFeB rare earth magnets

α = 100% (mixed defense + industrial buyers)

China’s April 2025 export controls on seven categories of rare earth elements and magnets. Q₀ ≈ ~0 commercial U.S. NdFeB magnet production; MP Materials’ Independence facility in Fort Worth was in trial production. Q₆ ≈ ramping toward 1,000 MT/year (≈83 MT/month) against U.S. demand of 10,000–15,000 MT/year.

DOD and MP Materials announced a public-private partnership to build a “10X” facility (additional 7,000 MT capacity, plus Independence expansion to 3,000 MT), targeting 10,000 MT total by commissioning in 2028.

Price impact: NdFeB magnet prices rose ~45%, within the 100% threshold but close to halving the score.

β₆ ≈ 0.05 vs. U.S. demand. ME (physical) = 0.05. ME (price-adjusted) ≈ 0.028.

Gallium and germanium (primary)

α = 100% (mixed defense + semiconductor buyers)

China’s July 2023 export-licensing requirement reduced unwrought gallium exports by 66% in the post-control period (Argus / China Customs data, per Stimson Center analysis, April 2025). Q₀ = 0 metric tons of U.S. primary low-purity gallium. Per USGS Mineral Commodity Summaries 2025: China accounts for 99% of worldwide primary production; “at least one company is exploring the feasibility of producing domestic primary gallium.” Q₆ = still zero.

Some recycling and stockpile drawdown softened the impact. In November 2025, China temporarily suspended its export ban through November 2026. USGS estimated a total ban could cost the U.S. economy approximately $3.4 billion in output.

Price impact: gallium +365%, germanium +400%, antimony +437% (Swedish National China Centre, December 2025, reviewing Argus and Fastmarkets data). Far above any reasonable α.

β₆ ≈ 0.01 (reflecting marginal secondary recovery and stockpile drawdown, not primary production surge). ME (physical) = 0.01. ME (price-adjusted) = 0.00

Large power transformers

α = 50% (dispersed civilian buyers - utilities)

Post-2022 demand surge driven by data centers, electrification, and aging infrastructure. Wood Mackenzie estimates power transformer demand up 116% since 2019; GSU demand up 274%. Lead times: 128 weeks (2.5 years) for power transformers, 144 weeks for GSUs, per Wood Mackenzie Q2 2025 survey. Imports account for an estimated 80% of U.S. power transformer supply in 2025. More than half of the roughly 60–80 million U.S. distribution transformers in service are beyond their expected life.

Domestic capacity expansions since 2023 total ~$1.8 billion (Eaton in South Carolina by 2027; Siemens Energy in North Carolina early 2027; Hitachi Energy in Virginia and Pennsylvania), none on a six-month timescale. Supply deficit: 30% for power transformers, 10% for distribution transformers in 2025.

Price impact: +77% cumulative since 2019; utilities report paying 4–6× pre-2022 costs. Well above the 50% threshold.

β₆ ≈ 0.02, reflecting marginal import increases but no demonstrated domestic production surge, all major OEMs report full order books with no available production slots. ME (physical) = 0.02. ME (price-adjusted) = 0.00.

recently declared the death of partying, finding that Americans spend significantly less time attending social events than they did twenty years ago. The largest decline — by almost 70% — occurred among people aged 15-24. Thompson offers a sophisticated analysis based on post-1970s individualism, gendered labor economics, and smartphones.

But he was far too nuanced. The single threat decaying Americans’ social lives is the Chinese Communist Party.

Last week, the Chinese Ministry of State Security published a bombshell report on its official WeChat account: the United States government secretly funds think tanks to push “lying flat” (躺平) upon Chinese youth, brainwashing them into believing that “working hard is for losers.”

But while Brookings was busy influencing Chinese twenty-somethings, China’s government was not sitting idle. An exclusive ChinaTalk investigation has uncovered Beijing’s quiet counter-offensive: a two-front campaign to foment loneliness abroad and good vibes at home.

Sabotage Stateside

Suppressing American partying required a surgical institutional intervention executed at scale: the resident advisor. By penetrating higher education institutions, Ministry of State Security (MSS) agents have introduced the concept of RAs or fudaoyuan. These agents of the administration are tasked with patrolling dormitories to remove all items potentially conducive to vibrant social lives. They drew from America’s proud history of Prohibition, adapting adapted the new RA system to exclusively focus on confiscating alcohol. The RAs, Dan Wang has confirmed, are the perfect adversary for a lawyerly society. Every instinct to host, mingle, or even leave the apartment now generates potential liability.

The campaign extends beyond the dorm. Cigarettes once forced strangers into proximity. The MSS’s masterstroke was the introduction of vaping: a Shenzhen-engineered substitute that delivers nicotine without forcing the user into social contact for a light or loosie. While exporting vapes abroad, the MSS has limited their ability to gain traction at home. Domestic Chinese smoking, largely conducted via traditional cigarette and therefore still social, remains among the world’s highest.

Recent American college grads, socially debilitated by the COVID-19 pandemic, vapes, and the pernicious RA system, have now entered the adult world. Instead of making friends, they’ve turned to obsessively polishing their appearances, all at the cost of American national security. “Mogging” could plausibly even be a Chinese loan word: mo jing means “to grind down the neck” in Mandarin, precisely the beauty practice preferred by certain Gen-Z leaders.

Catch Up and Surpass America’s Parties

China appears to be a relative latecomer to the global party scene, as decades of poverty and Maoist conservatism don’t form fertile ground for letting loose. But the Chinese archaeological record speaks to the civilization’s latent party power: every courtyard in the Forbidden City is outfitted with a giant bronze vat, expressly, scholars now believe, for punch-mixing.

The CCP understands that an ample domestic party supply not only strengthens regime security but also augments the future of China’s development. As Xi declared at the 20th Party Congress: “without the Party, there can be no party” (没有党就没有派对). Beijing understands that partying power is zero-sum. In Xi’s New Era, there can only be one fun hegemon.

The intellectual architect of this campaign, ChinaTalk has learned, is Wang Huning. His foundational 1991 text America Against America identified American sociability as the central pillar of US hegemony. A draft sequel circulating among Standing Committee members, Vaping Alone, reportedly argues that an atomized America cannot project soft power and may very well suffer social collapse. This thesis has shaped both the domestic Common Partying initiative and a parallel covert program targeting American campuses.

The campaign reflects Beijing’s mastery of asymmetric demographic warfare. AI is on track to eliminate entry-level white-collar work in both countries, and the CCP has learned through painful lessons from the Cultural Revolution to Tiananmen that bored and jobless youth are the single greatest threat to regime stability. The Party’s domestic response, rolled out as “Common Partying” (共同狂欢), keeps Chinese youth so occupied with elaborate weekend gatherings that they fail to notice the disappearing ladder of prosperity. And it seems to be working. While the portion of American Gen-Z who drink has dropped to a concerning 62%, rates of alcohol partaking among the same age group in China over the past two years rose from 66% to 73%.

This is no accident. A 2026 NDRC directive assigned each major city a designated nightlife specialization aiming to close what one Tsinghua working paper identified as China’s persistent “vibe deficit” with the US. Notable local developments include Hefei, long the dour engineering capital of Anhui, which has been instructed to quadruple its “post-ironic warehouse rave” capacity by 2027.

Shenzhen plans to leverage its hardware supply chains toward indigenous DJ equipment substitution, ending decades of Japanese dominance in the global CDJ market. Huawei has been tasked with developing a sanctions-proof alternative to the Pioneer CDJ-3000.

And Kunming’s tropical microdosing pilot zone, which began as a blood oath among eighteen Yunnan households, has since been elevated to provincial demonstration status. It is now receiving 2 billion yuan in subsidies under the “Made in China 2030” framework for indigenous psychedelic substitution.

What Is To Be Done

With both top-down guidance and bottom-up innovation, China is enacting an “abundance agenda” for party vibes. American legislators must respond in kind. Encouragingly, the Trump administration has begun to grasp the strategic stakes. President Trump’s April 18 executive order Accelerating Medical Treatments for Serious Mental Illness, which granted Breakthrough Therapy designation to specific psychedelic drugs, represents a critical first step in closing the deficit.

But $50 million in psychedelic research matching funds is a rounding error against the scale of the threat. America invented LSD and got the CIA to conduct its own Phase 1 trials. In the same decade, we put a man on the moon and a tab on every undergraduate’s tongue. And now we are now on the verse of losing the psychedelic frontier to Kunming.

A fun gap is opening between the US and China. America’s competitive advantage in the 21st century will not be decided in TSMC’s fabs, by Anthropic’s models, or Anduril’s drones. It will be decided at 11pm on a Saturday, in a kitchen, near a blown out speaker. The Pacific Century belongs to whoever is still willing to leave the house.

ChinaTalk does not endorse overconsumption of substances known to be harmful to health, including cigarettes, alcohol, scheduled drugs, and substack sunday funnies satire.

Two weeks into the US-Iran ceasefire, CENTCOM is requesting Dark Eagle hypersonics, the 82nd Airborne is flowing into theater, and the wargames keep telling us the same thing — there’s no military solution to the Strait of Hormuz.

Becca Wasser, America’s wargaming queen, currently with Bloomberg, joins WarTalk regulars Bryan Clark, Eric Robinson, and .

We discuss…

• Why CENTCOM is using JASSMs to hit targets a glide bomb could handle

• What cosplay costs the Indo-Pacific

• The myth of US air superiority over Iran, and the SEAD legwork no one wants to do

• Who actually benefits from the ceasefire and why Iran has the lower bar for reconstitution

Listen now on your favorite podcast app.

Still No More Ammo

Jordan Schneider: Last week’s theme was no more ammo. Setting that aside, we’re still sending more stuff there. Becca — no one believes us!

Becca Wasser: I think the perennial theme is just going to be no more ammo. And it’s not a matter of the US is running out of missiles to prosecute this war, or Iran is running out of missiles and can’t potentially cause damage if there’s round two that erupts quite soon. It’s really about the longer-term knock-on effects and what it means for some of the choices that are being made now.

My Bloomberg News colleagues yesterday had a great scoop where CENTCOM has requested Dark Eagle, the Army’s long-range hypersonic missile. They’ve asked for whatever exists to come to them. That doesn’t necessarily mean that’s what’s going to happen, but there’s this emphasis on trying to get all of these shiny toys, these next-generation technologies, the ones that haven’t actually been used in combat, and using this largely as a theater of experimentation if we want to use CENTCOM’s terms back at it.

But all of that has knock-on effects for readiness, preparedness for future conflicts, but also regionally. Right now, those would be taken out of INDOPACOM. And the things that China seems to care the most about, it’s things like that. It’s Typhon. It’s having missiles within range, particularly because in all of the war games that I’ve run, that I know Bryan has run, that matters because it becomes very quickly a war of missiles there. I think that’s why we’re just seeing so many choices that are being made now that just get me not only angry, but so nervous for what might happen in the future. And that’s not even talking about the fact that we are probably going to have a carrier gap in the future. That’s kind of bringing us back to the discourse of the early 2000s.

Eric Robinson: Hyperpowers have constraints too. And I don’t feel that advocates on Capitol Hill and the Pentagon and the White House necessarily operate under that understanding. It is a hard reality of contemporary warfare that there are only so many assets they have available, that there are questions of physics, of landing rights, of fuel capacity. The United States, for having $1.5 trillion in aspirational financing, doesn’t get to press the all button every single time. Eventually there are going to be trade-offs.

A theme that we’ve explored for the last 60 days is that we are expending exquisite assets, time, attention. We are accumulating friction, not just in terms of ordnance expended, but in just aircraft engines that are going to have to be refurbished and replaced. American capacity and capability to respond to other crises is necessarily being degraded by virtue of this exchange in Iran.

Bryan Clark: And the operational utility that these systems provide in this context is very limited. We’re using JASSMs to hit targets in Iran that could have been hit very easily with a GBU, or a JSOW if we really want to go fancy. And then Dark Eagle, same thing. What are we going to hit with a Dark Eagle that we couldn’t hit with any other munitions? We’re out there cosplaying so we can show off. They say it’s testing out this stuff in a real environment, but it’s not, because there’s no air defenses there that are gonna be meaningful. So you’re not actually testing it, you’re just showing it off.

Eric Robinson: Yeah, we’re like taking a Lamborghini to Dutch Brothers Coffee. We’re doing really mundane stuff with exquisite tools. There are weapon systems that are designed for Air Force or Navy pilots to get as close to an extremely hazardous situation and have a small likelihood of hitting their target. Those are the JASSMs we’re talking about. But what we’re doing is we are using those weapons systems against a country where their integrated air defense systems aren’t able to function. So this is overmatch and overkill, and it is using tools because it’s fun and exciting, not because it’s strategically apt.

Jordan Schneider: Are we 100% sure about that? Because right before this all ended, you had a few planes get tagged.

Eric Robinson: Yeah, it happens. F-29s are going down.

The Air Superiority Mirage

Becca Wasser: I think it’s really important that we take a grain of salt with a lot of the statistics that have come out of CENTCOM, the White House, the Pentagon. The initial numbers and metrics they use to demonstrate success in various areas — one, they’ve proven not to be true, but also some of it is just a fundamental misunderstanding of where the threats have been.

For example, a focus that emerged probably midway through the initial fighting of trying to sink Iran’s Navy. Iran’s Navy is not the biggest threat in the Strait of Hormuz. It’s the IRGC fast boats. It’s the anti-ship cruise missiles. And despite all of these efforts of going after various targets, the anti-ship cruise missiles were not number one on the list, even though the Strait of Hormuz has been essentially Iran’s biggest tool and biggest leverage in this conflict, because not only is it able to cause pain to its immediate neighbors, it’s able to cause pain to the US and to the global economy more broadly. So there’s a fundamental misunderstanding of what metrics are important, what target sets are most important, but also whether those have actually been degraded or eroded in a really significant sense.

But another thing we need to take into consideration is all of these claims of absolute air superiority. Despite all of that, I’m not sure the US has ever truly gained air superiority in the way that, frankly, Pete Hegseth and Dan Caine have suggested. Oftentimes when they’re talking about it, they’re talking about air supremacy. They’re trying to say that the US can act uncontested in Iran’s skies all across and it’s not a problem. But really what they’re generally talking about is the fact that the US has had more localized air superiority that is geographic and at times time-based, which frankly is something that we’re more likely to see in a future conflict with China where you have these windows of opportunity.

That has fed into some of the use of these higher-end munitions. I agree, some of it is the desire to show off Gucci instead of Tarjay, but really what I think it also is demonstrating is the fact that there hasn’t been this absolute air supremacy or even a higher level of air superiority to go after some of the targets that they wanted to.

Bryan Clark: I agree with Becca that they’re definitely overstating the level of air superiority they have. I think it’s partly also just an unwillingness to do the legwork to make it so that you can use a less expensive, more available weapon. You have to go do some suppression of enemy air defenses. You have to build a package that gets you in there so I can use a JSOW instead of a JASSM. So I can use a glide bomb instead of having to rely on a standoff missile. I can’t believe that you couldn’t do that against Iran, even with its air defenses somewhat intact, by just doing the blocking and tackling that we normally do — you have to include a suppression package in with your strike package. And they just don’t want to do that because they just want to hit as many targets as possible in a given period of time, which means launch a bunch of JASSMs and not have to worry about launching multiple aircraft sorties.

Justin: And that goes back to a combination of they are risk-averse at the command level, and they really have become risk-averse. And they also have to some degree forgotten how to do this. I don’t think the Air Force has forgotten how to do this, but at a command level, the way that they synchronize these — so that they can actually have a suppression of enemy air defense layered with a strike package, have the fast movers come in, do their strike targets, and then come out — they’re not willing to do that because they want to be able to say, well, we can do it whenever, we can hit them all the time. Well, you can only do that under two circumstances. You’ve destroyed all their air defense, à la the invasion of Iraq, or you are going to use exquisite weapons.

And we’ve seen a proclivity to use exquisite weapons against people who they’re not ideal for. If you just look at yeeting JASSMs at the Houthis. The Houthis survived Saleh for decades bombing them in Yemen because they just went into the hills and they stayed in the hills. And then they came out when he got done throwing bombs at them. So CENTCOM’s answer to the Houthis was, let’s throw a bunch of bombs at them. So the Houthis went into the hills and they stayed in the hills until the bombs fell, and then they came back out. Literally no change in their combat power. It’s what they do. Rinse, wash and repeat for the Iranians, who observed what we did in Yemen and went, okay, we’ll make our targets harder to hit. We’ll weather the storm and then we’ll pop back up when we need to.

Who Benefits From the Ceasefire?

Jordan Schneider: What about this whole month they’ve gotten to reconstitute? I don’t know how much Russian stuff has been shipped over the past few weeks —

Becca Wasser: I don’t think there’s even a need for external support. Obviously, Iran would like that. They would like to get some of the upgraded Shaheds that Russia has perfected and have used in the battlefield in Ukraine. They would like to get more sodium perchlorate from China. No problem there. But what they are doing, they’re digging out missile launchers, they’re digging out missiles, they are repositioning. This is just basic stuff and basic reconstitution.

I’ve recently been trying to think who does the ceasefire benefit militarily? Obviously it benefits all sides, and most importantly, it benefits the Iranian people who are no longer at risk of being targeted. Let’s put that one out there. But if you’re looking at the military ledger — the US is flowing in more forces, in part in theory to be able to reinforce the blockade. They’re requesting more forces. There’s more time to re-up some munitions. Cool. Israel’s probably trying to do the same, repositioning, give a little bit of rest to some of probably their pilots who have been doing double duty in places like Iran and to a lesser extent Lebanon.

But there’s no massive reconstitution that they can do of air defenses, of missiles. They’re probably trying to upgrade some of their older air defense interceptors, but they’re not going to be able to pull all that much off the factory line. Same thing with the US. It’s not like all of a sudden we can just, I don’t know, poop out more bombs. That just doesn’t work. No matter how much I think everyone would like that to be the case.

So if you’re looking at that, then probably Iran, which arguably has the lower bar for what it takes to reconstitute, is possibly on the up if you’re trying to look across the ledger. Because they’re doing the right things and they’re doing the smart things and they’re trying to do what they can with whatever it is that they have left. And if you also look at how quick they were able to reconstitute some of their forces after previous bombing campaigns, I think they were able to do it fairly quickly. Mind you, that’s not like six weeks. It was probably closer to six months. But there are some clear lessons learned there.

Justin: There was a quote — I can’t remember which book it’s from — but it was just pre-World War I. The Russians were suing to stop all armament advancement because they liked it exactly where it was. Rifles were good. 1905, that’s a good spot to freeze them. An armistice benefits you when you’re behind. Who was the one that was asking for the ceasefire? For all intents and purposes, it was the United States.

Who does it benefit? At the end, it looked like Iran was coming out on top because they haven’t given up on nukes. There was talk about relief of sanctions, allowing them to sell their oil, and then they were going to have a period of reconstitution.

The forces that the US is choosing to flow into the Middle East right now are interesting because yes, there’s an additional carrier strike group, but there’s also the 82nd. There’s also ground forces going in. Those are only useful if we’re going to use them. Sending the 82nd Airborne Division to places in the Middle East serves as either target, as a warning, or — we’re actually gonna do a ground invasion into a country that’s twice the size of Afghanistan and has a larger population than Iraq did.

Becca Wasser: I’m with you, but I also think that some of the logic has gotten screwy. If there were to be a resumption of US strikes, the time that would make the most sense would be when there’s still a three-carrier posture in the Middle East. You can have one in the Red Sea to hold the Houthis at risk, make sure that if they decide to go after shipping in the Red Sea or even Saudi’s alternate terminal at Yanbu, there’s repercussions. And then you can have one continuing to operate in the Arabian Sea / Gulf of Oman, prosecuting the blockade, and another contributing to broader strikes. You’d also want a three-carrier posture if you are thinking seriously about using your ground forces in any operation to forcibly reopen the strait.

But that’s not necessarily how they think. So there is a part where I’m thinking about these ground forces, and I think some of it is to have them pushed forward, so there is the optionality. But I also think there’s a strain of thought about them potentially being a tripwire, taking almost a page out of the European posture playbook where having forces that are there is supposed to deter further aggression on US partners in the region. That would make the most sense if you would see them in possibly one of the Gulf states. I think Kuwait would make the most sense given the existing ground force bases and infrastructure. So I don’t think it makes a ton of sense. But that is one way of thinking. And that I think also risks continued US ground posture at a bolstered level in the Middle East, which is something previous administrations had tried to push against.

Jordan Schneider: Previous administrations — you mean like this one? Three months ago?

Becca Wasser: Like this one.

Justin: That’s the other big thing. When we look across — the people who are in the policy position, the people who ran, the people who supported all said, we need to be able to pivot. We need to defend our interests in Asia. We can’t do that by continuing our excursions in the Middle East. We have to draw down. CENTCOM has been too big for too long. And now we’re in this twilight zone where it’s like circa 2003, only set to today’s music.

Pivot to Undisclosed Location

Becca Wasser: The pivot to Asia isn’t really working, but instead what we have is the pivot to undisclosed location in Southwest Asia for those of you who are old enough to remember.

Eric Robinson: Something I encounter in my professional life working around the defense industrial base is I often have clients or potential clients I encounter at conferences. They kind of operate under the assumption of, well, everybody’s really serious about PRC. They take the People’s Liberation Army Navy very seriously, don’t they? All of this has some sort of centralized coordination structure. Everybody thinks this is really important, right?

I don’t mean to be a professional cynic, but I will often use a little bit of dead padding to say, actually, no, not particularly. A pivot to Indo-Pacific Command has briefed well across multiple administrations. It was embedded in the 2018 National Defense Strategy and effectively abandoned in the more recent version.

It’s like the old Road Runner / Wile E. Coyote cartoon. There are people who really believed in this moment of United States industrial and military alignment to back Taiwan and to a far lesser extent back Ukraine in its war for independence. And they have left solid earth and they are still running out into space. They’re looking beneath them waiting for some sort of collective policy alignment by and between Republicans and Democrats. It simply doesn’t exist.

We have a series of operational-level spasms. We have random loans going to companies that might make sense. We have military operations against Iran or in Nigeria or in Venezuela that independently might make sense but don’t aggregate into a collective whole. So I think we’re in a moment of profound strategic drift, and I’m waiting for normies or just casual observers to catch up to that.

Becca Wasser: You think that the normies haven’t caught up to that at all?

Eric Robinson: Speaking from my lens in industry, people still think there is a collective vision around reindustrialization to take care of China, to make sure the United States can fight that war.

Jordan Schneider: I don’t think it’s normies, Eric. It’s people who have a financial connection to building for a Taiwan fight. There’s some motivated reasoning there within the China-watching community, as well as the DIB-for-Asia folks that still want to believe that it’s 2018 or even 2023.

Eric Robinson: Re-industrial archetypes. That’s a fair rejoinder — that rather than just normally relative average civilians, people with financial stakes in this did feel like there was going to be a generational commitment to reorienting American domestic spending, defense industrial policy, and the military with it. And I think there are segments of less ideological types, but still intelligent observers, who are recognizing that there’s no there there.

Jordan Schneider: This is a question for Becca and Bryan: how, emotionally, having done war games on both Hormuz and Asia, has it felt seeing these stocks dwindle in ways you guys perhaps more than anyone else appreciate the knock-on effects of?

Drone Wars Over Hormuz

Bryan Clark: We just did a war game looking at this scenario, the Strait of Hormuz scenario, just a month and a half ago, just as the war was starting. And it’s played out kind of like that war game played out — it turns into drone wars over the strait, but the strait closed most of the time. You just have to eventually wait it out until somebody wants to come to a resolution because there is no military solution. The strait kept getting closed by drones and mines. We kept cleaning them up. They kept doing responsive strikes against the guys on the shore on the other side. And it turned into a lot of drone-on-drone action, but nothing that really drove it to some kind of resolution. So it was not very satisfying, but illuminating. In terms of the current war, this is sort of what we found to be the base case.

Becca Wasser: That speaks honestly to why, in all of the fun financial projections that the smart economists I’ve been working with have been doing, our base case has been that this is going to be a protracted conflict, where you have this initial period of intense fighting, and then it becomes a much longer low-intensity conflict with periods of strikes and then rest, reconstitution.

This very much gets into the cyclical dynamics that we see in protracted conflict, both in the literature — for those of you who are nerds like me and think that Cathal Nolan’s Allure of Battle is one of the best books I’ve ever read — but also when we are looking at places like the current conflict that’s been ongoing for years because of Russia’s wanton aggression in Ukraine. Those are the patterns we see. And I think that’s what’s playing out here.

For me, the most emotional reaction I have to seeing how this has been prosecuted is thinking about the future, thinking about an America that’s going to be less secure because it can’t protect against some of the future threats that it and its allies might face. And thinking about a globe that is going to be a lot less secure as well. For the first time in my life, I am thinking about economics, looking at the economy and thinking about the downstream effects of that, not only for me as someone who wants to be able to afford things, but for society, for next generations, and back to Eric’s point about the defense industrial base and the massive amounts of money required to keep that afloat. This is going to be a generational change.

Bryan Clark: In the war gaming we’ve done looking at the Asia-Pacific or China scenarios, what this really highlights is that we need to think about how do you deter China on the cheap. Because we just couldn’t come up with this kind of munition usage and the demands from a traditional approach to the China fight. You just have to think about alternative ways of deterring China that don’t require you to somehow win a firehose competition with the PLA. That’s one thing this has driven our wargaming to look at: a lot of different concepts for how do you deter China without having to have this massive buildup, because you can’t trust that it’s going to actually come to fruition or that we won’t squander those weapons on some other adversary.

Becca Wasser: If I can take myself from being Wednesday Addams and gloom and doom and try and be a little bit more positive — it doesn’t come naturally to me, but I’ll try it anyways — one of the hopeful lessons learned that we’re going to take from this conflict is the need for lower-cost weaponry and effective lower-cost, attritable weapons. Right now, there’s a lot of patting ourselves on the back for LUCAS, which is a reverse-shot Shahed, and that we’ve deployed it in conflict. How? No one really has said. How many? Well, doesn’t matter. We might not even have any LUCAS left for all we know. But we’re patting ourselves on the back and saying that that is our example of low-cost, affordable mass. Yeah, it’s a lot cheaper than a lot of the high-end missiles that we have, but it’s not cheap enough.

I’m hopeful that one of the lessons learned that’ll come out of this conflict is not only this idea of how do you deter on the cheap with smart operational concepts, but how do you actually build to those operational concepts and get the costs down so that you have attritable weapons that can be used and that you can truly lower the cost per shot or even cost per effect.

Justin: To tie both of these points together — Cathal Nolan basically takes a part and looks at: hey, the majority of wars aren’t fought over the single battle. They don’t turn on the decisive fight. They’re generally wars of attrition. Even when Nolan looks at Waterloo, it’s like, yeah, but Waterloo took 14 years to get to. There was a lot of war before that that was attritive before you got to the final decisive battle.

I think the administration thought this was gonna be — they thought they were going to get in, hey, we took out Maduro. It was quick. We killed Soleimani. Nobody did anything. We struck the nuclear reactors. Nobody did anything. We can roll in and we can steamroll this and everything will be fine. Not realizing that this was opening up a different paradigm where it was going to become like, this is now a war. This is no longer discrete operations.

But one of the ways you make things cost less per shot and less per effect is you buy a lot of them and you build a lot of them. That’s one of the things that the administrations — not just this one — have been very reticent to do. We only need a stockpile of like 1,400 JASSMs. We don’t need any more. You make 40 a year, Lockheed? That’s awesome. Great.

And then we start using them and they’re like, oh, we need 10x the production. Well, that only gets you to 400 a year. And you’re using 400 in a month. The delta there is you get things to scale. That’s what drives down the price. You only get things to scale if you’re willing to buy them and fund them and keep refurbishing them. And they haven’t been willing to do that. Even when we talk about $1.5 trillion budget, we’re talking about one-time $1.5 trillion budget. Well, great — over the next 12 months, we’ll scale production, hire all these workers, build all these lines. Wait, no, that’s not what we’re gonna do. Because it takes more than a year to do all of that and to spend that money. Unless we have a much more integrated and forward-looking way that we’re gonna do the acquisitions, it doesn’t matter in the short term how cheap we get an individual shot.

The Stockpile Trap

Becca Wasser: That’s right. But one thing that Bryan and I have actually debated in the past is, yes, you need to be able to have the production capacity, because you need to be careful about what you stockpile and when you stockpile it. Some of it is shelf life. Some of it is just the shift in technology and how quickly that can change. Rather than just going all in on something that’s going to be completely OBE by the time you actually try and field it.

Eric Robinson: Somewhat satisfied that we are not sitting on a quarter-million Excalibur rounds in the United States, because it would have been extraordinarily expensive for the United States to build 155-millimeter artillery shells that are GPS-guided. And we would operate it to the assumption that we would have artillery batteries doing precision strike with wanton abandon in the Taiwan Strait gap, or we could give them to the Taiwanese to help defend the landing beaches. But we now know that these systems in their technological disposition are extraordinarily vulnerable to GPS jamming. They don’t have redundant navigation systems. To Becca’s point, and to build on Justin’s theme of you need to buy a lot of it — that’s absolutely the case, but obsolescence is extraordinarily hard to reconcile.

In May 1940, the French armies’ field artillery and their prime movers and their reserves of propellant, fuses, and high-explosive shells were the finest in the world. The French Army had spent 15, 20 years building that up. They had a better concentration, they had more professional gunners, spotters, and communication systems for their artillery than the next three armies combined. And in six weeks, that artillery was never able to move quickly enough to aim true and to break up the opposition.

So stockpiling weapons is sort of an economic imperative, but can also give you a false sense of security if you anchor your defense on systems that are no longer relevant.

Justin: I had a conversation with one of the consulting firms this week where they were talking about — they want to look at what are the components we need to put in Group 1, 2, and 3 UAS systems. And they were like, come on, tell us what kind of components they need. Well, what’s the threat? Well, that doesn’t matter. No, no, I think that matters a lot. They’re like, no, it doesn’t matter. Just tell us what components we should put in it. And I was like, I think you guys need to call somebody else.

Eric Robinson: Yeah, it’s like asking for a prescription without describing the malady.

Justin: Exactly. I think modularity becomes the key. It’s the ability to slap a cone on the top of the artillery round to make it more precise with whatever the next generation of that precision looks like. But you still need a lot of the artillery rounds. What is the artillery round? We can figure out what the technology is that slaps on top of it. What is the Shahed of tomorrow or the LUCAS of tomorrow? Some of those are gonna cost a lot more and some of those are gonna cost a lot less. If you’re using it on boats in the Caribbean, you probably don’t need the ability to be EW-hardened to the level that it needs to be to fly in Ukraine or off the coast of Taiwan.

The IRGC’s Hardliners

Jordan Schneider: Maybe this is one for Justin: what percentage of the IRGC would be thrilled to have the 82nd Airborne fly on in?

Justin: When you look at the IRGC and their leadership, you’ve kind of got stovepipes. I saw somebody the other day was trying to make this reference that Iran only spends 2% of its GDP on defense. And the implication was that they’ve been able to defend against the US only spending 2% on defense. That misunderstands how the IRGC and the Iranian military are bifurcated and how they actually operate. So yes, only 2% of GDP goes to the actual Iranian military. Then there’s this whole other thing with these hardliners that go out and get to operate and kind of run almost like a criminal cartel where they own construction companies and shipping companies and all kinds of other things that they get to draw money from.

Some of those people will not want anybody to invade or any type of war because they just want to keep making money. They are comfortable owning the concrete company in Lebanon or owning whatever business they’re using to generate wealth and revenue.

But there’s also the Shia martyrs. People struggle with, are they true believers or are they not? But I’ll say this. Imams and ayatollahs and Shia clergymen in the ‘80 to ‘88 Iran-Iraq war, when Iraq was driving tanks into Iran, were walking around handing people plastic keys saying this is the key to heaven, this is the key to the kingdom of heaven, while they strapped on suicide vests to go run at Iraqi tanks and blow them up. There is a portion of the IRGC that are hardliners and they are believers. They are the people who still go and clean off the martyrs’ tombs and they tap on the tombs so that the dead can hear them and know that they’re there. There is a very real undercurrent in parts of the IRGC that would absolutely relish the chance to become martyrs and to take down — like, absolutely. Is that their leadership? Debatable. But you have to really look at what the IRGC is and what they’ve done in the past and where they came from to understand: when people say there’s a group of them that are hardcore true believers, those people absolutely exist.

Eric Robinson: I also don’t know how the Iranians dial in escalation dominance. There’s always going to be a segment of — whether they are religious fanatics, they’re Marxists, they’re Christian nationalists — who will embrace, the worse it is, the better. They think that if you can ratchet up the violence, you can gain a longer-term political objective. I don’t know that that logic holds here.

The Iranians, for all the short-term perhaps excitement of being able to grab an American paratrooper battalion by the belt and start to get at them in a slugfest, recognize that if the United States starts taking serious casualties, this administration has few reservations about committing atrocities against Iranian civilians.

To Justin’s point, there’s sort of a mosaic of reactions, and witnessing a consolidated reaction from inside the Iranian security state that speaks for all elements is unlikely. But I also think they are sufficiently sophisticated to recognize that if you fall back to theoretic escalation dominance, they don’t necessarily have the kind of tools that would wake up the Secretary of Defense, and that they may be subject to extraordinary violence against national-level infrastructure that they cannot account for.

Becca Wasser: That’s why we see constant hedging strategy from Iran. They are willing to engage in diplomacy. They are willing to negotiate. But at the same time, they are willing to fight as hard as they need to, because this is an existential conflict for them. If a deal is offered that is attractive enough, some factions in Iran are more than happy to accept it, and perhaps that is the leadership.

But the one constituent group that we don’t hear from are the Iranian people, in part because there are these internet and technology blackouts. And honestly, they’re the ones who are most at risk from potential threats to wipe out massive infrastructure or civilizations, if we want to quote Trump’s Truth Socials of yore. They’re the ones who have to bear the effects. And frankly, with the blockade, they’re also the ones who are probably going to bear the continued economic hardship. But the Iranian system and the leadership that exists believes that they can ensure that the people will fall in line as needed, in part by brute force.

So I don’t think it’s necessarily a great path forward. But the big thing is Iran’s entrenched. They are dug in and they are willing to see this through. This goes back to all of our discussion about why we think this is likely going to be a long war.

The JCPOA Lesson

Justin: Eric made this point about Libya and the lessons learned from Muammar Gaddafi. I also think there are good lessons that were learned from the JCPOA, because the more reformist-minded kind of got control of the government to some degree in Iran. They were able to wrangle through the JCPOA, which was going to limit the growth of military power towards nuclear ambitions.

To the IRGC — they won, they got some sanctions relief, they got some money. It started to look like things were gonna open up, which ideally would have in turn allowed more opening up and more reform. And then when that got pulled away, the hardliners can look at that and go, see, we told you, you can’t trust them. They gave you something, they got us to agree, they got us to give up all of our highly enriched uranium to Russia, and then they pulled it out from underneath us. Why do we make a deal the next time?

Eric Robinson: If you elevate this to traditional prisoner’s dilemma or game theory, the opponents of the United States can sort of assume with some basis that the United States is always going to defect. Always. And you need to forecast what the defection means, how you prepare to limit the damage.

Becca Wasser: That’s a lesson learned, frankly, for adversaries and allies alike. We talked a little bit about posture and CENTCOM, but we have some potential threats going on in Europe right now when it comes down to US military posture threatening to pull out troops in Germany, Spain, other places in punishment for what they’ve done. So I think the idea of America as being reliable and a reliable ally, or at least a reliable country to negotiate with or strike a deal with — I think those days are long gone.

Jordan Schneider: Say Europe was all in — we’re gonna crash this strait open by whatever means necessary. Does that change the balance of forces at all?

Becca Wasser: I don’t know if it changes the balance of forces in the traditional sense, but I cannot see Europe being willing to commit any significant naval power without the strait being secured. They’ve been so clear about that. The area where I think it would probably make the biggest difference is — there are a number of European countries and frankly Asian countries that have more minesweepers than the United States, because the US divested of them. For the most part, what the US has left is a bunch of littoral combat ships that they couldn’t find an actual role for, so they outfitted them in a minesweeper capacity rather than sending them to get scrapped. Having that minesweeping capability would be really useful. But I just can’t see any European country want to contribute that or any type of offensive naval power and do things like escort missions or contribute to the blockade in a really meaningful way, unless maybe the US put the screws on them further.

If anything, I think maybe we would see a re-up of what they’ve been doing in the Red Sea, maybe plussing up there and saying, we’ll hold this down and you can focus over there. That would be a smart way of playing it, but I find it hard.

Jordan Schneider: I guess my question was — if you wave a magic wand and you get to do whatever you want with all of their assets, does that actually change the fact that Iran can still hit one in 20 tankers that go through and that means that nothing goes through? I don’t think so.

Eric Robinson: Iran has a fleet in being. They have anti-ship cruise missiles. They have an uncertain number of mines that they can employ. They have asymmetric tools. They’re going to keep insurers nervous. They’re going to keep mariners on edge. Just by virtue of their geographic proximity, they will remain dangerous.

Justin: This goes back to that conversation we were having about that terrible FT piece — the idea that the Red Sea was closed for almost all of 2024, which was made without actual evidence by the author. That is not true. But because there was a route around, there were some shipping companies and insurers who were like, just go around. Why would we risk it? You don’t get that here. So why would it change it? Either they make a separate peace with the Iranians, which won’t be able to hold up because they’d have to bring the US along, or they have to join and turn the coast of Iran into rubble, which we’ve talked about why that’s impossible several times. It’s gonna be a long one.

Becca Wasser: To Eric’s point, Iran doesn’t have to do that much to cause havoc. And it’s not just about the missiles. We saw what the Houthis were able to do with just a few drones in the Red Sea. And everyone is so much more locked into the strait because there’s no other viable alternative.

I keep getting asked questions about, what’s the historical precedent for this? What happened when the Suez Canal was closed? Is there something we can learn about Hormuz being closed or what happened during the tanker war? And none of those are applicable. The geography is very different. The time and the technology is very different. With the tanker war, the US was willing to escort ships, which is not something they’re willing to do at this juncture. And that’s not something Europe is willing to do either. So all it takes is just a little bit of being annoying with drones, and that just shuts it all down.

Jordan Schneider: Becca, what a treat. You’re welcome back anytime.

Eric Robinson: Thanks everybody.

Constanza Vidal Bustamante, Senior Researcher at CNAS and author of the landmark report Quantum’s Industrial Moment, joins ChinaTalk to map out how supply chains behind quantum computers wind through the US and China. Co-hosting are Chris Miller, author of Chip War, and Zachary Yerushalmi.

Our conversation covers:

• What it takes to build a quantum computer — Inside the cryogenic supply chain, the helium-3 bottleneck, and why mining the moon might actually make sense.

• How export controls backfired — How restrictions on dilution refrigerators helped spur China to go from zero to more cryogenic suppliers than the rest of the world combined in just two years.

• The scaling problem — Simply multiplying dilution refrigerators doesn't get you to a million-qubit machine. Cooling, cabling, and the chips all have to be rethought — and no country owns that yet.

• Why being first isn’t winning — Why long-term victory isn’t cracking Shor’s algorithm first, but locking in supply chains across multiple modalities.

• The public-private fault line — The high-stakes balancing act between the government stepping in to accelerate innovation and letting the market work on its own.

Plus, what China is getting right, where the US still has an edge, whether the US should ban Chinese components, and why quantum supply chains are a national security priority.

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Jordan Schneider: Constanza Vidal Bustamante has done dramatic, impressive work of public service, writing one of truly the best think tank reports I have ever come across: “Quantum’s Industrial Moment: Strengthening US Quantum Supply Chains for Scalable Advantage,” co-authored with John Burke. It goes incredibly deep, and I learned so much about everything that goes into making a quantum computer.

It really reminds me, Chris, of reading those 2018, 2019, 2020 reports where Washington was wrapping its head around the semiconductor supply chain — the work that ended up delivering what became the CHIPS Act and the program office. There is an enormous amount of detail and knowledge here. Every few sentences, I found myself wanting ChatGPT to give me the ten-page version of some three-sentence reference Constanza made. We are excited to give you a taste, but you should all read and dive into the full report.

What Does it Take to Build a Quantum Computer?

Chris Miller: To start, what does it take to build a quantum computer?

Constanza Vidal Bustamante: That’s a big question. In the report, we try to answer this complex question because it seems like it would have a simple answer, but it’s quite complicated — starting from the fact that there isn’t just one kind of quantum computer. Different companies are pursuing different modalities. We have superconducting computers, atomic computers (which could be neutral atoms or trapped ions), photonic computing, and many other modalities cropping up as well.

Each has a different bill of materials, pulling from various layers of the quantum supply chain in different ways. Some of these are partially overlapping, but they’re distinct enough that it gives rise to the idea that there isn’t just one supply chain — we have multiple supply chains we should be taking care of.

In terms of commonalities, they’re all drawing from similar layers of the so-called quantum stack. They draw from specific materials, or they may use distinct atomic sources or isotopes. They place these elements within an environment — a cryogenic environment with ultra-low temperatures or an ultra-high vacuum environment. They use different components to interface with these atomic sources or materials that generate the quantum state, such as lasers or various control electronics. There’s a software layer, and there’s networking, if you think a little further into the future, as we start putting together different chips for these various modalities.

All of these modalities draw from these various layers, but the specific elements that go into each layer vary quite a bit. That’s why it was very important (and why the report runs on the longer side) because there isn’t an easy answer or just one list of elements you can point to. These things are also changing over time, so it gets complicated.

Zachary Yerushalmi: Quantum is at a super early stage as a technology package. We are pre-transistor. Because of that, you have to deal with the inherent uncertainty of supporting all these different supply chains in their current state. But it’s also a wildly fast-moving industry. The next phase will require a step change and a reinvention of that supply chain, even if a lot of these existing modalities are successful.

The example there would be something like photonic integrated circuits, which are the photon equivalent of the integrated circuit of the electron era. Right now, most AMO — atomic, molecular, and optical — approaches, which represent one of the big clusters in quantum computing, are using methods that don’t scale based on current manufacturing techniques. To scale them, you have to move to PICs. To move to PICs, yet again, you need to reinvent the supply chain and do that continuously. It’s a fascinating one to grapple with, with a level of uncertainty that I really don’t think we see in any other technology package at this scale.

Chris Miller: The analogy is sort of like it’s 1945, we’re two years out from the transistor having been invented, and we’re trying to think through what the computing supply chain looks like in 1955. We don’t know what the transistor is going to look like exactly, so we’re going to go through the cabinets at Bell Labs and figure out, on average, what the scientists are using as they run their experiments. Is that a good analogy?

Zachary Yerushalmi: Yeah, almost to the point of pre-vacuum tube. I’d be curious about Constanza’s perspective.

Constanza Vidal Bustamante: When we think about the heterogeneity of supply chains, it’s not just across these modalities horizontally, but also along the time dimension. As we think about the prototypes being built right now, we have a good sense of what those supply chains look like. They’re very globally distributed, and we can point to sources of dependencies — some things we’re importing from China, where it may be the only source, or other things where the best in market comes from Europe or Japan.

But as we look ahead to when we’ll have quantum computers capable of breaking encryption — the version of these machines that will truly be revolutionary — the supply chain is probably going to look quite different from the one we have right now. As I argue in the report with John, when you think about geopolitical stakes and international competition, that’s the place where the United States can still dominate, because nobody has control over a supply chain that doesn’t yet exist.

If we think carefully, we’re not entirely without an idea of what it will look like. As Zach said, we have models. We need to move to photonic integration if we want to manufacture this at scale and at a competitive cost. To actually build these machines at volume, we have a rough idea of the path to get there. It’s just a matter of breaking the chicken-and-egg cycle of waiting for enough market demand before making major investments in the supply chain. Because you don’t have those investments, you never get to a point where the product becomes very attractive to the market.

There’s a path forward. It’s just a matter of gathering enough momentum, political will, and capital. At the end of the day, it’s capital. We need to unlock the next-generation supply chain for these machines, and the United States is definitely still in time to dominate if we move quickly.

Zachary Yerushalmi: Let me give a couple of examples on the stakes of locking in your role as a country in that supply chain, and why you get so much leverage when you do.

Think of the two dominant approaches. One is solid-state or superconducting, which requires cryogenic systems of a wild scale. The other is AMO. Take the cryogenic side. For innovation there right now, you need a dilution refrigerator to operate these systems. It takes 40 hours to go from room temperature down to the level of cold needed to operate a superconducting circuit. That 40 hours means you can only run one test a week. If China invents an ability to take that from 40 hours to 12 hours, you go from one test a week to one test a day. Your iteration cycle changes completely, and they’ll lock that down and grab that supply chain.

On the other side, with PICs for the AMO approaches, nobody has really made a scalable PIC — the architecture transistor part for that computer. It’s really hard. The country that does that has a total lock on the ability to scale whole approaches in quantum computing. That actually reads across to quantum sensing as well, because AMO and quantum sensing approaches are pretty similar.

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The Cryogenic Supply Chain

Chris Miller: We’ve got these different qubit modalities, which are sort of like different transistor structures, if that’s our analogy. We know the supply chain underneath them has some similar parts. We can start with cold temperatures, since they were just mentioned. Constanza, what does the cryogenic supply chain look like today? Also, give us a glimpse as to how cold we’re actually talking about.

Constanza Vidal Bustamante: Very, very cold. Even within cryogenics, it gets more complicated because some modalities require millikelvin temperatures while others operate at cryogenic temperatures over one Kelvin. That doesn’t sound like a huge difference, but it’s actually quite substantial in the energy requirements and the specific components or subsystems that produce those temperatures. Those are almost like another fractioning of the supply chain.

For instance, the superconducting modalities we were talking about — the computers that companies like IBM and Google are building — require those super shiny, chandelier-like dilution refrigerators usually portrayed in the media whenever there’s a quantum piece published. You can dig further into what it takes to make those refrigerators. For photonic computer modalities, some subcomponents also require cryogenic temperatures, but not low enough to require a dilution refrigerator. That leads to other complications, which we can talk about.

In the dilution refrigerator camp, there are a few different issues, starting from the fact that they use — and this is perhaps more well known — helium-3 as part of their cooling approach. Helium-3 is an extremely rare and highly regulated isotope that you can’t simply build or supply on demand. It comes as a sub-product of nuclear processes. That seems to be an area where, if you start developing machines at scale and you need to access a supply of helium-3, you could find a choke point.

Jordan Schneider: But there is some on the moon, right?

Constanza Vidal Bustamante: I don’t think it’s questionable that there is helium-3 on the moon. The question is whether it’s ever going to be feasible to extract it. Zach, you’ve looked more deeply into this. Maybe you can join me on the lunar sourcing option.

Jordan Schneider: Look, if we’re going to put data centers up there, I feel like a little bit of helium...

Chris Miller: Let’s step back and say what a dilution refrigerator is, and how they actually work, before we get to the moon?

Jordan Schneider: Okay, it’s a teaser.

Chris Miller: Before we get to the moon, walk us through how these machines work. We’re getting as cold as outer space. What does it take to make a machine that makes things that cold?

Constanza Vidal Bustamante: At a high level, they take several different stages to get there. You don’t go from ambient temperature directly to extreme, colder-than-outer-space temperatures. If you look inside one of these chandeliers, they have several cooling stages that step down progressively. It goes down to maybe 4 to 10 Kelvin first, and then continues down. The bottom is the coolest stage, where you place the quantum chips for superconducting or semiconducting spin modalities of computers. That’s the actual coolest part — the part colder than outer space.

To achieve this, you require a combination of helium-3 and helium-4. Helium-4 is not really a source of concern. It’s the most common helium isotope, so it’s not a supply bottleneck I’m aware of. But the helium-3 part of the mixture is the absolutely necessary element to get you to the millikelvin temperatures these systems require.

Zachary Yerushalmi: The whole point of building a quantum computer — and why it’s hard — is that these quantum states are incredibly fragile. They get messed with by everything. Heat messes with them. The wider environment messes with them. Cosmic rays mess with them. Looking at them messes with them. That’s the whole point of quantum mechanics.

What you have to do is isolate these quantum states from absolutely everything. The most effective way to do that is to get them wildly small and wildly cold. When you get them wildly small, a different type of physics takes over that enables you to manipulate these systems in such a way that you can do useful calculations.

On the helium-3 side, this is one of those things where I really wish a quantum computer made going to the moon economically viable. The sad thing, particularly for America, is that the major supply of helium-3 is tritium decay from the nuclear stockpile. As long as we don’t go nuclear-free in the US, from most of the calculations I’ve seen, we should be okay.

That said, access to these systems — not just ones today, but ones that actually enable that scale — is critical. There are three credible suppliers in the West that can supply these — Bluefors, Oxford Instruments (which just got bought by another company), and Maybell in the US. It’s that hard — there are only three companies, and really only two of them are credibly there at scale.

China went from having none to, just in the last couple of years, creating more companies building these systems than the rest of the world combined. They went from not publishing in this space at all to dominating over 50% of the publications on new innovation in this area. It takes decades to get good at this. Folks are coming up the chain very quickly in places where the Finns will share their dilution refrigerator IP with us. China is not going to do that.

Constanza Vidal Bustamante: To Zach’s point about China announcing all these different manufacturers of dilution refrigerators, some people point to the export controls that the United States, along with several other international partners, put in place starting in 2020 and into early 2024. Within a year or so, this seems to have backfired. With those export controls — of which dilution refrigerators were importantly a part — you accelerated an ecosystem where China rapidly mobilized to procure their own systems and continue innovating on the computing front.

Chris Miller: I’d love to dig into that as well, but I’d like to go to helium first. Helium is on the moon, and we’re going to mine on the moon, maybe—but it also comes from the nuclear stockpile. Is this from civilian energy production, nuclear weapons, or a mix of both?

Zachary Yerushalmi: Nuclear weapons. Tritium decay. That’s the majority of the source. You can get it from a couple of other places. Evidently, Canada has loads of helium-3 randomly stored away.

The reason there’s lots of helium-3 on the moon is that cosmic radiation strips away helium-4 and converts it to helium-3. Unfortunately, you need to launch a rocket there, harvest it, and bring it back. The only economically viable use of lunar helium-3, from what I understand, is if you need to go to Mars and build quantum computers. You launch off from Cape Canaveral, get to the moon, and if you’re still going with Elon Musk on board, then you have an awesome business. But if we’re focused on the helium-3 supply for the US and keeping it tertiary, I’ve heard a bit of skepticism around lunar mining. I’m bummed, but sadly, we are where we are.

Export Controls Backfiring?

Chris Miller: We know that things like dilution refrigerators are hard to make — which is why there are a small number of companies, and you need to mine helium on the moon or do something comparably difficult. On the other hand, there’s an argument that the export controls the US and Europe put in place on dilution refrigerators a couple of years ago spurred this brand new industry in China. That suggests it wasn’t actually that hard, or at least that the response happened pretty quickly.

Help us understand how we should think about this case study. Does it tell us anything broader about the relevance of export controls in the quantum computing space?

Constanza Vidal Bustamante: It really depends on the specific inputs we’re talking about and the timelines related to the volumes at which you need them. What Zach was perhaps trying to say is that we shouldn’t worry too much about helium-3 in the near term. At the rate we’re building refrigerators and the rate they’re being purchased and acquired, we’ll likely be fine for the next few years. Luckily, the US has a big source for that, so we’re in a privileged position as the provider for much of the world.

But going back to what we were saying earlier about the next-generation supply chain — as we start scaling these systems, you no longer have just one chip to cool. You start building machines that require what becomes almost a side problem of cryogenics — how much dilution refrigerators can scale to support much bigger qubit counts. Once you have a lot of demand for many large systems, I start worrying about whether the sourcing of helium-3 or the refrigerators themselves can keep pace with that demand.

Going back to the China example — I don’t think they’re building these machines at volume yet. It certainly doesn’t seem to be the case that they’re selling these machines beyond procuring them for their own experimentation within their top-level academic research labs — those at the frontier of hardware development for quantum computing. They were able to develop these machines for maybe one or two systems, possibly more, but definitely not in the hundreds yet. They made enough to continue progressing on prototyping and iterating, but I wouldn’t say they’ve reached the level of Bluefors in Finland or Maybell in the US.

That points to a story where the controls accelerated their start in developing these machines in-house. Maybe they weren’t planning to build that domestic capacity quite as quickly, but they were pushed to do so by the controls. They haven’t yet reached the stage where they’ve equaled what Western companies can make, but they seem to be on that trajectory. You can still question whether it was the right time to put controls in place on those.

Zachary Yerushalmi: The China anecdote ultimately boils down to the stakes of this industrial competition — both how high they are and how different they are from other technology packages, because we are so early in that race.

The US actually has an incredible moat around semiconductors. That doesn’t mean we can sleep on it, but we’ve been doing that for decades. We have friends, partners, and allies all across the world. Because we haven’t built a fault-tolerant quantum system, a commercially useful quantum system, we don’t have the same moat. That means China gets the ability to leapfrog and reach near parity with the US on certain manufacturing capacity. As you add in friends and allies, it gets closer, but if you look forward, the stakes are big.

This also hints at something Constanza spoke to in the report. We need to rethink how we do the supply chain to get to real scale. If China is the country that comes up with the intellectual property on the core method to reach that scale — if they invent the kind of transistor of the scaled cryo system you need — then they will have an unfair manufacturing advantage. China is typically quite good at that. They’ll also have an unfair IP and understanding advantage on the key path you need.

We have to think differently here. If we just project forward the existing engineering design of these subscale systems, we will not have enough helium-3. That’s why we have to reinvent the systems that make these computers, the QPUs (quantum processing units), really small and actually get them to that temperature. We have to rethink that process. The country that innovates and locks that down — that holds the manufacturing intellectual property — will have an unfair advantage to win. We just don’t have the decades that we rest on as an advantage in semiconductors.

Constanza Vidal Bustamante: In the report, we elaborate on exactly this point. In the near term, the most advanced dilution refrigerators available on the market can host around a thousand qubits. If you want to get to machines requiring a million qubits or more (though qubit count isn’t the only metric to consider), the path we have right now is essentially to put together dozens of these dilution refrigerators.

But the scaling doesn’t quite work that way. As you add more qubits, at least for the superconducting modalities that would require them, you need cables to connect the qubits together, and that adds to the heat load. That makes the cooling less efficient. It’s not as simple as multiplying the refrigerator by X number. You need to do what Zach was saying — innovate so the cooling approach you’re taking is much more efficient at scale.

That’s where we’re seeing real activity. Maybell just put out a new system at APS this week. I haven’t looked into the details yet, but that’s where we need to focus a lot of attention, as Zach said, so we don’t get out-innovated in this space. Otherwise, it becomes much easier for countries like China to reach that scale before we do.

That’s the challenge. We need to focus both on the near-term supply chain to continue iterating and innovating, while keeping a very strong eye on what comes next. That’s where we will reap the most reward in terms of economic and security benefits from the utility of these large-scale machines.

Policy Recs for Quantum Success

Zachary Yerushalmi: If you could talk to policymakers and give them suggestions on what they can do — the policies, the tools they can adopt to give the US the best shot here — what comes to mind? What’s the strategy to win on supply chain?

Constanza Vidal Bustamante: This goes beyond cryogenics, which is the subject we’ve been discussing. The report tries to be comprehensive in its assessment of the problems, but the solutions we provided are preliminary and need a lot more fleshing out. Maybe I’ll do subsequent reports, putting much more detail into what the solutions could look like.

Broadly, for the cryogenics problem, we’re calling for intentional and targeted multi-year advanced R&D programs on cryogenics. Similar dynamics apply for highly precise laser systems and other optical components, where the systems we have right now work for the prototype machines we’re building, but we know we need to keep innovating to reach utility-scale machines.

This is an R&D tool, but it’s not just fundamental R&D. Given the race dynamic and the time-sensitive nature of this, it needs to be a dedicated, advanced R&D effort. Another big point that cuts across the report is bringing together the enabling technology manufacturers — in this case, the companies building dilution refrigerators — with the end users, the system integrators in the quantum world. We want the computing companies that will use these machines to co-design, where possible, getting down to the specific requirements these machines will have. That accelerates the process rather than just building and hoping the result will be useful.

I’m less worried in the cryogenics sector that this isn’t happening already, because the market for these machines beyond physics research or quantum computing isn’t that diversified. They’re definitely thinking about quantum as their primary sector and paying close attention to the requirements. But for other components with broader markets, you have to be very deliberate from the government perspective when setting up R&D programs to ensure the enabling technology manufacturers are closely aligned with the needs of the quantum end users.

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Zachary Yerushalmi: I look at three levers. There’s supply — do I have the widget on the shelf when I need it? That’s the current widget. There’s innovation — do I have the support to skate to where the puck is going in the industry?

The last lever I think of is capabilities that exist in a market failure. The canonical case there is high-mix, low-volume fabs, like what you see in the semiconductor era. At the intermediate volumes you need, there’s an explicit market failure in running those fabs given their cost structure.

To make it specific, take the fab we have at Elevate. It costs about $40 million in capital equipment. Every year, because we focus on a particular level of TRL-ness, we hope and pray that we make about a million dollars a year on it. That sucks — no investor is going to give you $40 million and hope you make a million dollars a year. Governments have to think about supporting that long-term market failure in order to maintain that industrial capacity.

Constanza Vidal Bustamante: I focused on the R&D lever because it was most pertinent to what we were just discussing about next-generation cryogenics. In the report, however, we provide a menu of different policy actions that can be taken to support various elements of the supply chain, depending on the specificity of the issue at hand. Different problems—and different levels of maturity in the components or systems involved—will require different levels of support, and the federal government may be more or less well-suited to take action in each case.

There’s definitely no one-size-fits-all approach. The supply chain is so heterogeneous that it would be very surprising if any single intervention solved the entire problem. Some issues will require less federal activity than others. Helium-3 is a good example of where more intervention is warranted. It’s a highly regulated isotope, the private sector isn’t going to be the right actor here, and the solution can be as cleanly structured as having the isotope program under the Department of Energy take a close look at their inventories, set aside parts of that inventory for quantum needs, and do the right calculations for repurposing some of the helium-3 already in use. They could also think through some out-there ideas for new sources of helium-3, but in a deliberate way.

That’s a very specific example. Others require a completely different scale of investment — for instance, what’s needed to make some of our current foundries quantum-ready or quantum-grade. There you need to call on multiple actors to play a role. There’s a wide range of tools we can deploy depending on the specificity of the issue at hand.

Zachary Yerushalmi: My sense is that governments can either make markets or distort markets. Do you have a North Star or heuristic for when government intervention is needed and when you should let the market do its work? Big question, but it’s so pertinent here.

Constanza Vidal Bustamante: A big piece for me is not whether the private sector could eventually do it. It’s when you put all of this under a geostrategic, geopolitical race dynamic where it’s time-sensitive, you don’t want to wait. If you pressed me, I would say sure, let the market take care of it and figure out which modality is best. Whichever has the most manufacturable supply chain and relies the least on highly vulnerable items should be the one that wins.

But if we believe there’s a higher-priority objective — where we don’t want to be second to anybody, especially China — then we’re under a very different set of circumstances. Every day matters, and we want as many modalities as possible for the US to dominate. It’s not just about supporting whichever is most promising. Let’s say superconducting wins — we don’t have a great definition for what “winning” means, but say a superconducting machine is the first to break Shor’s algorithm, and it’s a US-based company. Even at that point, I wouldn’t call victory. I would still want the other modalities to dominate in their respective categories.

It’s very plausible that a different modality — say, photonic quantum computing in China—will also clear that bar, and they may have figured out a supply chain that’s more nimble, cheaper, and more cost-competitive. That would outshine the superconducting machine that the US got across the finish line first. The finish line is moving, so it’s all hands on deck. When you start thinking about those circumstances, there’s a big role for the government to serve as an accelerator of that market. That’s why I think of all of this in terms of a broad innovation and industrial policy portfolio — because that’s the scenario we’re in.

Zachary Yerushalmi: I love this point. Two things occur to me. First, if we got to vacuum tubes as a nation and said, “This works, this is good enough, down tools,” you’d miss out on the transistor. That was actually pretty important for scaling these systems. It’s a repeat game.

The thing I do worry about is that the stakes of getting policy wrong are wildly big. The example that comes to mind is China itself. There’s a technology area called quantum key distribution. We don’t need to get into the technology of it — folks can look it up online. It’s really cool math. Unfortunately, the math is so cool that if you do your postdoc on it, you just want to do that math all day, and you forget that it’s economically and cryptographically not all that secure.

Because the head of China’s quantum program, Pan Jianwei, is obsessed with this, he puts a wild amount of resources toward it—even though you can literally just look up “NSA QKD” and find intricate detail on why this whole thing is dumb. The upshot is that we need industrial policy because the competition is so intense, but it’s very easy to get wrong. We just hope our competitor gets it wrong more than we do.

China’s Quantum Approach

Chris Miller: On that point, someone recently made the following analogy to me: China has a Manhattan Project for quantum — one plan, one team, one system, and most of the ecosystem oriented around that particular pathway. Whereas in the US and the West, you have these different qubit modalities and different companies competing with each other, and as a result you have somewhat distinct supply chains.

Is that analogy true or false? And if so, who’s got the better strategy?

Constanza Vidal Bustamante: That analogy used to be true, but it’s changing rapidly. The comfortable narrative we had about China for a while was that they’re undoubtedly leading in communications. They’ve deployed large-scale infrastructure, optical fiber, and quantum key distribution systems to exchange keys in a supposedly tamper-free way. In addition to the fibre that they’d deployed over something like 10,000 kilometers in China, they also have some quantum satellite link demonstrations. It sounds very impressive.

But the assessment from the West was that even though they’re leading, at least in deployment of this technology, this isn’t a technology we care about or believe brings a lot of value. It’s a very narrow solution. It’s not a full cybersecurity system in the sense that you still need a lot of classical encryption and authentication systems for other parts of cybersecurity. Even for the piece it does cover, it’s not fully secure. You can hack it in different ways. China can take that piece, and we don’t care about it.

In computing, the narrative used to be that they’re catching up quickly, but, like Chris was saying, they’re really only putting a lot of their chips on superconducting. They’re moving quickly, and they’re impressive, and we should watch them, but they don’t have the diversity that we have. Just in the last year or two, however, we’re seeing a lot of startups appear in China, often led by prominent academics from Pan Jianwei’s group or others who lead quantum research in China across different modalities.

They announced two different neutral atom computing companies last year. They have some photonic ventures — a photonic company has been prominent for a while. They’re growing the number of superconducting ones. Recently, I read about even topological qubit developments. All of these are new companies. With the information we have, they’re probably not very close to matching the capabilities of the various computing modalities we have in the United States, but there’s definitely rapid movement. It’s not just that all of these are state-driven and therefore won’t be effective — these are coming out as private startups from highly talented folks.

We should worry about that. We shouldn’t just rest on our assumption that they’re limited in what they can do.

Zachary Yerushalmi: This is one of the many reasons I think Constanza’s report is literally a national security priority. The reason China can move up the chain so fast is that they’re so thoughtful in their approach to the supply chain. If you have the key components to manufacture all of these different modalities — all these approaches to building quantum computers — then regardless of what you learn about which approach is better, you can react quickly and deliver against it.

We spoke before about photonic integrated circuits, critical tools for scaling these systems. In the US, even for some of the biggest providers, because they don’t have access to the fabs and the supply chain to manufacture those, it can take 12 to 18 months to go from an idea like “I want this new PIC” to actually getting your PIC. In China, because they’ve really invested in this area — it’s used across many different applications in photonics and certain material systems — you can go from “that’s a cool idea” to having your PIC in literally two weeks.

A lock on the supply chain is a gift that keeps on giving, because you can be literally ten times as reactive and adaptive as your adversary. It’s like a supply chain OODA loop of sorts. Nobody has been attuned to this the way Constanza’s report has captured.

Constanza Vidal Bustamante: Two other things came to mind as we were speaking — one for China and one for the US.

For China, in addition to what I said earlier about prominent scientists starting their own companies across different computing modalities, what is true — and what Chris was alluding to in the Manhattan Project analogy — is that China has been deploying moonshot programs to a much greater degree than the United States has. This cuts across different levels of government. A lot of the provinces or local governments frequently launch moonshot programs where they say, “submissions accepted: by 2026, create a dilution refrigerator that can host a thousand qubits with these error rates.” Those targets are usually just matching the top performer of the West. The timelines are typically pretty crazy — within a year, you need to deliver this thing.

That might sound at first like it won’t work, but they do it frequently enough that eventually you get there. Maybe you get a thousand submissions of which 999 are bad, but one isn’t, and that one is successful. Even without highly talented folks running these programs, they have that forcing function of serving as a constant source of demand for these products. There’s some money attached, and even if it’s not substantial, it’s enough to get enough submissions that one of them might be good. I worry about that.

The counterpart in the United States is that even though we haven’t incorporated grand challenge or moonshot–style programs to the same degree — although that seems to be changing with this administration — what we do have are highly talented government folks who are so deep on the specifics that they can craft really thoughtful programs. I’m thinking here of DARPA, DOE, NIST. Programs that aim for the right level of requirements and have enough incentives attached. You don’t need a million programs like in China. You can have a few, but they’re very thoughtful, driven by people who really understand the science and the technology.

That’s an asset we have compared to everyone in the world. China is an easy counterpart, but even in Europe, you don’t have the same level of technical sophistication we have here. I worry a little bit about that changing in the last few years, but in general, we still have incredibly talented folks in government.

Zachary Yerushalmi: To dovetail with this, the reactivity in the Chinese academic sector is incredibly powerful. I was chatting a couple of weeks ago with a prominent quantum physicist. They were telling me about a paper they read on a new type of PIC. What had happened was that a Chinese group had a certain type of material system they were working on, and they had friends over at Columbia working on another type of material system. These were adjacent publications and approaches.

What this Chinese group did was look at the two approaches and ask, “What would you do if you could just put them together?” It turns out you get wildly better results. Their point was that in America, hitherto, you’d never do that, because the bureaucratic system around applying for grants is so intense that you couldn’t just say, “Let’s put these two material systems together.”

What I would call out with the new administration — and for all sorts of reasons, I don’t want to get political, but I’d say as a real positive — is that when you look at Deputy Secretary Dabbar and Undersecretary Gil, they get that, and they’re really driving toward a totally new paradigm. You can say, “That material system is cool, that material system is cool — let’s drive this thing and see what new innovation you can do.” You don’t have to spend new money. You just have to move fast and be creative, and they’re going for it.

Chris Miller: Constanza, lasers — critical for quantum computing. Tell us where they’re made today and how they should be scaled up.

Constanza Vidal Bustamante: In the report, we cover them in this big category of photonics and optics. Lasers are part of that and are the star of the show, but definitely not the only component to watch. They affect different modalities differently. When you think about the main subcategories we cover — solid-state superconducting and semiconducting modalities, atomic ones, and photonic ones — lasers matter most for the photonic and atomic modalities.

It’s not as simple as one laser. You need multiple lasers doing very different things. Take the atomic modalities — neutral atoms or trapped ions. You need different kinds of lasers to cool the atoms. Instead of a cryogenic system, you use a laser system. When you shine the laser beam on the atoms, you bring them down to ultra-cold temperatures so you can manipulate them. Then you have different lasers to elicit different energy transitions, and other lasers to read out the effects. It’s a chain of lasers.

What they share in common is that they’re all highly specified to the specific wavelengths you need to hit, and they need to be extremely stable in those wavelengths to maintain the frequencies that make them usable for these computations. It’s not just one laser, and it’s not just lasers. You need all these optical components to route the light, change directions, change the frequency — maybe double it — various lenses to focus the light, and so on. There are a lot of subsystems involved.

The supply chains are also complicated because they’re all different things. The lasers we cover with the highest priority in the report mostly come from companies in Japan, Europe, and China.

There’s an interesting case study we cover in the report. A provider appeared in China that started manufacturing lasers essentially identical to those of a Danish company — but at a much cheaper price. There has been a lot of behind-the-scenes discussion over whether this was reverse engineered, and this Chinese company is well documented to receive government subsidies. There’s a seemingly clear story of what happened. Nevertheless, they’ve become a very important provider of lasers in the US ecosystem to this day.

What’s especially baffling is that even with the tariffs that have impacted everything, including the quantum industry, you can still call for an R&D exemption for those lasers. Those are still being purchased to this day by companies and universities that can claim an R&D exemption. They have a good product going. It’s price competitive, they apparently deliver reliably, and so it has become the preferred laser system for many organizations.

Zachary Yerushalmi: This point on price is a really big deal. It’s seen both in lasers and on the cryogenic side. There are key components like wiring trees, which you need to operate dilution refrigerators. For most experimental setups, you need a new wiring tree. The cost of a Chinese-produced wiring tree is literally one-tenth of the US equivalent — even after tariffs and all that. I’d imagine similarly so on the photonics.

When you look at the photonics side, like cryogenics, there are only two credible laser providers for quantum systems in the US — Vector Atomic and Vescent. Only two. They’re still medium-sized companies despite their headcount, and they have amazing teams. The criticality is not just that if China underpins them, prevents them from scaling, and undermines their ability to innovate — that’s a real big deal. But even more near-term, these laser systems are used for quantum sensors.

Quantum sensors — going back to the report — covers how the very thing that makes a quantum computer hard to build is what makes these amazing sensors at a unit level that can transform our world. One example is providing navigation without reliance on a GPS uplink, which, as we’ve learned in the conflict with Iran, and as we knew long before, is a really big deal. The same laser systems play in.

Should We Ban Chinese Components?

Chris Miller: China’s producing components for a tenth the cost of Western firms. We’ve seen this far outside of quantum, in many other spheres. We’re at this point where, as you’re saying, we’re going to have a dramatic scale-up over the next half decade or decade in the number of these components, as we build bigger and more capable computers.

Option one would be to subsidize Western producers tenfold so the price equalizes — that seems expensive. Option two, ban Chinese components from our quantum systems, but then you have higher prices. What should we be doing here? And should we be banning Chinese components from our quantum computers?

Constanza Vidal Bustamante: This will not be well taken among the quantum industry, but I do think we should not let this product continue entering the US market. That said, there are lots of considerations. I’m so glad Zach brought up the sensors, because that’s a much nearer-term market that will require these laser systems and various optical components at scale, much sooner than quantum computing. It becomes a real near-term bottleneck.

In terms of options, I think it’s both. We call in the report for some kind of subsidies, but really more like strategic financing or tax breaks. If you think about the supply chains of the lasers, some are dependent on foreign suppliers, including for some of the tooling needed to build them, often from Europe. Part of the solution is to provide some support for domestic suppliers while making it harder for Chinese products to take over the market, given that they may have used illegitimate ways of obtaining or accessing the IP that led to those products and have received substantial subsidies from the CCP.

Chris Miller: Suppose we go down the path of banning Chinese components from quantum computers. You get into a similar set of questions as if you said to a lot of people in Washington, “Let’s ban Chinese components from our AI data centers.” People often, at first glance, say, “Great idea.” Then you say, “Well, wait a minute—what about the screws? What about the light bulbs?” Where do you draw the line? Help us understand how to think about drawing lines in quantum computing.

Constanza Vidal Bustamante: That’s an excellent question. It’s hard to have an easy solution. Even if you stop the import of some of these devices or inputs overnight, that can lead to a lot of problems in our own ecosystem and our ability to keep innovating across broader products.

To your point about all these other sub-components —should we also block those? Is that worth blocking? There are layers of complexity. The inputs that require sophistication and that have the value we care most about are the ones we should bring in-house. In this case, for the lasers, we have some domestic suppliers. We have the talent. We have a path to get there with really good products that are having difficulty because they’re encountering anti-competitive practices.

Those lasers will be useful across different quantum technologies — sensors, computers, and to some degree networking too. They also serve beyond quantum — telecom and various defense needs. That makes them strategic enough as an enabling technology that I’d want to preserve our domestic capabilities. Compared to much simpler inputs to the inputs, that’s where I draw a distinction. I don’t have a super clear line in the sand, but that’s broadly how I think about it.

Zachary Yerushalmi: Take the wiring tree. If we say no Chinese wiring trees, that means for some groups, they can buy ten times fewer wiring trees, which means they do ten times fewer experimental runs. It’s not exactly linear, but it would act immediately as a hindrance on our ability to innovate. There are real trade-offs.

What I’m more clear on is the end state we aim for, which is some mix of three things. First, access — is the widget on the shelf? Second, security — particularly for end-stage products, do we know where that supply chain is, so that China isn’t putting a little microchip into the thing to listen to our experiments, or some Stuxnet-style attack? Third, can we continue to out-innovate?

Out-innovating is a lot more reliant — maybe even more than on price — on the speed at which you can get the widget. For a lot of these systems, you don’t require new fundamental physics — you just require being able to run through ideas quickly. There’s a separate learning that comes with that, around how you get to scale.

If you can balance these different priorities — using iteration speed as a proxy for staying innovative at every stage of a technology cycle — I think we’ll be in a good place. There are lots of different ways to skin a cat. We just have to be mindful of those trade-offs.

Constanza Vidal Bustamante: Another key aspect, related to what we were just saying about how many layers down you go. A big point we make in the report is the category of specialized materials. These are the ultimate substrate you need to actually build many of the components — for instance, the photonic integrated circuits we were talking about. Even some of the bulkier lasers rely on highly specialized photonic materials, including wafers that you process to make into devices. Some of those are sourced single-source from China right now.

That’s another concern. It’s not the laser itself, or the optical or photonic component itself, but the raw material you need to build it. If you don’t have access to that, you can go upstream in the innovation chain.

Zachary Yerushalmi: There’s a law that the second you create a metric, it ceases to be useful. The thing that comes to mind is — if you focus on whole product systems and ask, “How long does it take to go from initial design to inception of the product?” and you try to reduce that as much as possible, then you identify the requisite bottlenecks that you need to prioritize for investment.

You can do that for non-national security tech and just allow the component tree from anywhere. But then you have to apply a separate lens of national security, where you probably don’t want a certain chip coming from a certain place that’s not the US. Look at the lead time for that. If you compare these two lead times and try to ruthlessly bring them down — in a general sense, but also compared to your adversaries — you have a bit of a North Star: how are we doing, where do we prioritize, what do we do next? I hold that pretty lightly. You’ve been thinking about this more, but that’s where my silly bad supply-chain brain goes.

Comparing Stress Levels

Jordan Schneider: Constanza, you did your PhD thesis on managing people’s stress over time. As you talk to all these people in the quantum supply ecosystem, what’s their stress level? Are they like, “I’ve got exams in a week”? Or are they feeling good?

Constanza Vidal Bustamante: Oh my gosh, what an honor that you went back into my history. I guess it hasn’t been that long.

In talking to the quantum folks, there’s a lot of excitement, but also a lot of uncertainty. Obviously, I approach this from a policy perspective. There’s a lot of enthusiasm from the administration and Congress to do something big on quantum and to build on the foundations of the National Quantum Initiative, which came out during the first Trump administration, and the National Quantum Initiative Act, which solidified that and provided funding mechanisms for specific programs at different agencies. There’s a lot of expectation, but also a little bit of fear about what will actually happen. The stress levels are real.

All of these companies have a lot of pressure to deliver on these machines by the roadmaps they swore by. They’ve all been claiming they’ll start delivering utility-scale machines by the end of the decade, and the clock is ticking. Some have been more aggressive than others about what they’ll deliver, so there’s a lot of expectation about whether they’ll come through. If they don’t, there’s worry about what will happen to the field. Even if a competitor firm fails, will that lead to a generalized lack of confidence that brings down private capital writ large? There’s a lot of fear about what will happen, and a lot of pressure they’re feeling right now.

Jordan Schneider: Can you compare that to the semiconductor community? You’ve also done research interacting with them. I don’t think the chips folks are worried that chips won’t be a thing in five years. What anthropological differences have you picked up on?

Constanza Vidal Bustamante: That’s such a great question. It’s a very different environment. At the same time, there’s an incentive to present quantum as being as close to the semiconductor industry as possible — to give the idea that we have a path to manufacturability, or to build on top of the CHIPS Act or the CHIPS and Science Act energy and come up with this big industrial moment, as I called it in the report.

What’s interesting is that compared to the semiconductor industry, you have all these different modalities, with apparently close to 90 companies now building quantum hardware across various modalities. That’s so different from the semiconductor industry. It leads to all sorts of competition among them over who has the best qubit and why the others are inferior. It’s funny to hear — everyone will tell you endlessly why you should support their qubit modality and why they have the right one going.

Jordan Schneider: That was really my big takeaway from my little quantum journey over the past few weeks. In the semiconductor industry, things are consolidated. You have two EDA players, a handful of people making photomasks, and one company making EUV machines. It’s been that way for a pretty long time, and it’s probably going to stay that way. Maybe you’ll have an entrant here or there on the design side, but the entire industry is pulling in basically one direction, with everyone trying to capture an extra 10 or 20 percent of where they sit in the supply chain.

When you walk through the quantum stack, everyone’s using more or less the same ingredients to varying extents, but what the computer is going to look like is totally up for grabs. It’s not like Game of Thrones with six or seven royal houses — there are 90 different little empires competing for the prize.

Constanza Vidal Bustamante: That’s right. We’ll see how many survive, and what diversity survives. We didn’t even get to this, but even within a modality, there are different ways to build your architecture. There’s a lot there.

Zachary Yerushalmi: My mental model for quantum is biotech. When you’re trying to cure cancer, you have small molecules, CAR-T, antibodies, immunotherapies — all these different approaches trying to address something out there, which is a kind of unified target.

In other domains, we’ve figured out how to take hardcore fundamental science and mature it to impact our lives, even when there are many different approaches. That’s a slightly different mental model from semiconductors, but it doesn’t mean it can’t exist.

One of the 50 reasons I’m so excited that Jordan is covering this, that Chris is super attuned to it, and that Constanza writes these seminal reports, is that folks have spent decades from different perspectives asking, “How do we get biotech right?” Public policy folks have a frame of reference around biotech. Public finance folks understand it. Doctors understand it. Physicists understand it. In quantum, that hasn’t happened yet. We haven’t had proper academic rigor across the disciplines.

I really don’t think we’ll get this right unless we bring that interdisciplinary best practice now, at this stage. I’m super stoked for more.

Jordan Schneider: All right, kids, shout out to Zach and Constanza. I’m sure they’ll find some work for you. This was a pleasure.

Earlier this year we launched an economic security contest, judged by the likes of:

• Jake Sullivan, former NSA now at the Harvard Kennedy School

• Chris Miller, Chip Wars author and belt-holder for most ChinaTalk appearances

• Dan Kim, former Chief Economist for the Chips Program Office

• Dan Wang, author of Breakneck

We had two prompts:

• What are the most important high level KPIs that policy should aim for? What is the analogy of the Fed’s ‘2% inflation and full employment’ target for economic security?

• Where today would you put $10-50bn to get the most for your investment in economic security? Feel free to propose both defensive and offensive ideas, and either a portfolio of ideas or the one large idea you think will deliver the most value.

We had a literal four-way tie for first place as each judge gave one of these essays their first-place designation. We will be running the contributions from our winners in the next two weeks.

The first essay comes from , a Lieutenant Colonel in the U.S. Air Force, a Fellow at the U.S. Naval War College, and a Senior Fellow at the Payne Institute for Public Policy.
Disclaimer: The views of Lt Col Matisek are his own, and not those of the U.S. Air Force, Department of War, or U.S. Government.

Economic security is frequently invoked but is the least disciplined policy concept. It now justifies subsidies, export controls, stockpiles, reshoring, and strategic deals. What has emerged is a kind of “China-light” strategy in Washington, where activity is everywhere but coherence is not. Government money is committed and facilities are built, yet the U.S. defense industrial base remains a “Black Box” to policymakers and Pentagon officials. Key senior leaders still struggle to answer a basic question: which parts of the American industrial ecosystem can actually withstand disruption and which will fail first under pressure? That uncertainty extends well beyond the defense industrial base. It touches semiconductors, energy systems, critical minerals, logistics networks, machine tools, and the enabling infrastructure behind Artificial Intelligence (AI) and advanced manufacturing. The deeper question is not if the United States can keep peace with China in peacetime. It is whether the American economy can surge fast enough, recover fast enough, and keep producing when coercion sets in.

This question matters because strategic competition is reshaping the global economy. Deglobalization and selective decoupling are unfolding through policies meant to reduce dependence on China and minimize the risks of economic coercion. Yet coercion is not an abstract threat. It is a practical strategy aimed at supply chains, production systems, and the nodes that support them; something Washington let atrophy after the Cold War ended. Beijing’s advantage does not rest only on scale or innovation. It lies in its position across time-intensive, tooling-intensive, and capital-intensive parts of the industrial ecosystem that are difficult to replace once disrupted. Pressure at those nodes usually does not cause a collapse. It produces delays, shortages, and missed output targets that give strategic leverage to an adversary.

Recent events illustrate how different types of shocks reveal critical vulnerabilities. Direct coercion is the most obvious threat. Since 2023, China has imposed export controls on antimony, gallium, germanium, graphite, and heavy rare-earth elements, creating upstream bottlenecks, leading to over 300 F-35s being delivered without its new AN/APG-85 radar due to a lack of gallium. But vulnerabilities are also exposed by indirect shocks and internal failures. The 2022 neon gas shortage, a consequence of Russia’s invasion of Ukraine, showed that requalifying new sources for key semiconductor inputs can take over a year. Likewise, the U.S. Army’s struggle to scale 155 mm artillery production highlighted domestic bottlenecks with energetics and tooling. Similarly, instability in Mozambique led to suspension of graphite mining, disrupting supply chains for batteries. The 2026 Iran War only further reinforces the point because precision guided munitions are being expended at an unsustainable rate, while materials like helium and sulfur are unable to be transported out of the Gulf causing economic shocks and undermining the defense industrial base. Different shocks reveal the same problem: what matters most is not the source of disruption, but how long it takes to recover from it.

The popularization of the “small yard, high fence” approach was an important shift, correctly moving the focus from broad decoupling to specific chokepoints. However, its theoretical elegance has been challenged by its messy reality, leading some to claim the need to move beyond the concept. This is because a fence is useless if the factory behind it can’t operate, especially when a peer competitor like China has cultivated an “engineering state” capable of building its own capacity with unusual speed. The hard truth is that even a perfect fence cannot solve for domestic industrial weakness, as capital investment alone cannot erase long lead times. Real chokepoints extend well beyond chips to include energetics, chemicals, and tooling. Therefore, speed in reconstitution is the enabler, and capital must target the real constraints on output under stress.

This logic aligns with the theory of weaponized interdependence, which explains how asymmetric control over centralized nodes in global economic networks allows states to turn interdependence itself into a coercive instrument. In that world, diversification is sometimes useful, but it is not a cure-all. If upstream chokepoints remain concentrated and slow to replace, vulnerability persists beneath the appearance of redundancy. The task of economic security policy is therefore not to eliminate interdependence altogether, but to identify which nodes are most susceptible to weaponization and to harden them accordingly.

Seen this way, economic security is best understood as endurance under coercion.

It is the ability to sustain national power over time when disruption is deliberate and recovery is contested. The defense industrial base provides the sharpest stress test of this problem because wartime demand exposes bottlenecks quickly and brutally, but the underlying logic extends across the broader industrial ecosystem. Markets alone will not solve it. They reward efficiency, discount tail risk, and rarely invest in idle capacity, redundant tooling, or costly resilience without strong incentives to do so.

Washington has begun to recognize this reality. Industrial policy has returned as a tool of statecraft. But without a clear standard for success, these efforts risk becoming fragmented, episodic, and politically fragile. Economic security needs the equivalent of a dual mandate: a disciplined way to distinguish between activity and capability, between announced investments and real industrial endurance.

I contend that economic security should be organized around a coercion-endurance mandate centered on sustained production under pressure. From that mandate flows a small set of high-level indicators designed to capture where industrial systems break first and how they can be strengthened. The point is not to outbuild China across every sector. It is to create an American industrial ecosystem that is difficult to interrupt, slow to degrade, and costly to coerce.

That is the standard that matters. And it is one that can be measured.

Why Existing Economic Security Frameworks Fail Measurement

The turn to economic security has yielded frameworks and diagnostic tools that map supply chains and dependencies. While these improve situational awareness, awareness is not measurement; description does not equal control under pressure. Knowing where inputs originate does not reveal whether production can be sustained once disruption begins. Mapping dependencies does not show how systems behave when time, cash flow, bottlenecks, and recovery capacity become binding. Economic coercion exploits dynamics, while most current metrics remain static.

A central weakness is that many existing frameworks measure peacetime structure, not performance under stress. Indicators like import reliance describe a world without crisis, but are blind to how a system actually degrades or recovers when a critical node fails. The goal of economic coercion is rarely total destruction. History has shown, from the bombing of the Schweinfurt ball-bearing plants onward, that completely destroying an industrial node is nearly impossible. Instead, the modern objective is attrition: pushing output below a threshold long enough that it undermines operational abilities that shape of desired strategic outcome. Frameworks that fixate on static exposure while ignoring recovery speed are just fighting the last war. It means misunderstanding the mechanism through which externally imposed pressure works.

Another common error is the assumption that diversification automatically yields security. Spreading production across more locations can reduce exposure to a single supplier, but it does little to address constraints that are global in nature. Tooling, specialized labor, certification timelines, and precursor chemicals often remain concentrated even as final assembly disperses. Under stress, these upstream constraints reassert themselves quickly. Diversification without fixing reconstitution can create the appearance of resilience while leaving industrial endurance largely unchanged.

Current approaches also mistake announcements for achievement, overemphasizing paper capacity rather than usable output. While celebrating CHIPS Act investments is politically useful industrial reality is far harsher. The lesson becomes not so much that major industrial investments are misguided, but that physical construction is only one part of capability. TSMC’s Arizona project is best understood in these terms. Its early delays and operational frictions do not invalidate this major domestic effort. They reveal the difficulty of transplanting advanced production into a new ecosystem where skilled labor, supplier networks, water, power, and tacit organizational know-how all matter. The larger point is that industrial capability is not created by capital expenditure alone. It must be built, staffed, supplied, and sustained. That lesson extends beyond semiconductors to AI infrastructure, advanced manufacturing, and other sectors whose growth depends on fragile enabling systems.

An equally important issue lies below the prime contractor level. Industrial systems fail from the bottom up. Tier-2 and Tier-3 suppliers operate on thin margins, depend on steady cash flow, and often lack access to emergency credit. When shocks occur, these firms fail first. Payment delays or input disruptions cascade upward, halting production regardless of demand or funding at the prime level. Frameworks that do not measure sub-tier financial resilience are missing one of the most common ways in which economic pressure becomes systemic failure.

The cumulative result is that we end up having a policy environment rich in inputs but poor in outcomes. Economic security initiatives remain politically fragile and strategically ambiguous when they cannot distinguish between visibility and control, diversification and resilience, or announced investment and actual performance. What is needed is a shift from descriptive risk mapping to the measurement of industrial behavior under stress. Economic security requires indicators that capture how quickly systems recover, how far they can surge, where pressure concentrates, and how long production can be sustained once disruption begins. Only then can policymakers distinguish between industrial activity and industrial power.

The Economic Security Dual Mandate

If economic security is endurance under coercion, then it requires a governing logic that privileges performance over posture and outcomes over activity. Without such logic, policy fragments into disconnected programs that are difficult to evaluate and easy to politicize. Economic security needs an organizing principle that disciplines decision-making across institutions and administrations. Monetary policy offers a useful template. The Federal Reserve’s dual mandate translates abstract goals into durable targets that anchor expectations and guide action. Economic security requires a similar level of clarity. It needs a mandate that defines what success looks like under pressure.

I propose an Economic Security Dual Mandate built around two complementary objectives: (1) Minimum Viable Capacity and (2) Maximum Credible Coercion Cost.

1. Minimum Viable Capacity: The ability to sustain production of essential military, industrial, and technological outputs at a defined level for a defined period under adverse conditions. It is not about peak performance or global dominance; it is about the floor of output that must be maintained when disruption occurs. This logic reflects how practitioners have already begun to approach the problem. At the CHIPS Program Office, for instance, economic security was framed through interrelated dimensions of capacity, capability, competition, and criticality. In practice, however, the binding constraint repeatedly surfaced as recovery time. The central issue is not paper capacity, but how quickly production resumes after disruption. Minimum Viable Capacity formalizes time to recovery as a strategic variable.
   

2. Maximum Credible Coercion Cost: Capturing the flip side of the mandate, this reflects how expensive, slow, and uncertain it is for an adversary to disrupt U.S. production through targeted pressure. The higher the cost and the longer the timeline, the less effective coercion becomes as a strategic tool.
   

Together, these two objectives define economic security as a contest over endurance. Capacity without a coercion cost just invites pressure from an adversary. Coercion cost without capacity yields hollow resilience. Only when both are present does an industrial system become strategically resilient. The mandate also clarifies the role of the state. Minimum capacity and coercion cost are public goods. They require coordinated investment, long time horizons, and a tolerance for redundancy that markets alone rarely provide. The point of the mandate is not to prescribe a single industrial policy. It is to create a standard against which policies can be judged.

The challenge, of course, is measurement. Abstract mandates only matter if they can be translated into indicators that track real performance under stress. That does not require perfect precision at the outset, but it does require repeatable methods. Some indicators can be estimated through supplier mapping, sector-level concentration data, and confidential firm reporting. Others would require stress tests, red-team exercises, trial production runs, or disruption simulations conducted jointly by government and industry. A flawless dashboard cannot be created on day one. However, time and intentional policies are needed to build the institutional machinery needed to measure recoverability, surge potential, bottleneck concentration, and financial resilience in a consistent way over time.

Five KPIs for Determining Economic Security under Coercion

A mandate without measurement is rhetoric. American economic security can only be achieved through endurance under coercion. This means having indicators that capture how industrial systems perform when pressure is applied. Static measures of exposure or announced capacity won’t work. Time matters, as does throughput, concentration, and financial resilience.

The five indicators below translate the Economic Security Dual Mandate into a usable scoreboard. They focus on where systems break, how quickly they recover, and where coercion delivers leverage at lowest cost.

1. Time to Reconstitute

This measures how long it takes to restore meaningful production after a critical disruption. It is the most important indicator of endurance because time is the currency of coercion. In practice, reconstitution timelines are governed less by capital availability than by industrial physics. Semiconductor process-node requalification after a supplier loss often take 6 to 18 months. Rare-earth separation and magnet manufacturing lines have historically taken 3 to 7 years from permitting to full output. Machine-tool rebuilds after a chokepoint failure can exceed 18 months due to specialized castings and skilled labor. Systems with long reconstitution timelines remain vulnerable even when diversified on paper. Measuring this KPI forces policymakers to distinguish between theoretical substitutability and operational reality.

Target: About 6 to 12 months for any Tier-1 critical input, validated by red teaming supply chains.

2. Surge Ratio

This captures the maximum sustainable increase in output relative to peacetime baseline production over a defined period. It answers a simple question: how much more can be produced, and for how long, before the system breaks? Before the 2022 Russo-Ukraine War, U.S. production of 155 mm artillery shells averaged roughly 14,000 rounds per month. Despite ambitious targets to produce 100,000 rounds per month, production has stalled due to issues of sourcing energetics, fuzes, tooling, and skilled labor. Even a wartime demand — with a $6 billion infusion from the Pentagon — did not generate industrial willpower to meet surge goals, as the U.S. Army is only able to produce 56,000 shells a month as of February 2026. Achieving high surge ratios requires pre-positioned idle lines, redundant tooling, and cross-trained labor.

Target: Sustaining 3 to 5 times peacetime output for 12 to 18 months without cascading failures.

3. Chokepoint Concentration Index

We also need to measure how much control a supplier actually has over a non-substitutable input resides with the top one or three suppliers. Unlike traditional concentration metrics, this KPI focuses only on nodes that cannot be bypassed. The leverage embedded in such nodes is substantial. China controls basically 90% of global rare-earth refining and 90% of permanent-magnet production. Disruption at a single node, can undermine the U.S. economy and military, because both are so heavily reliant on these inputs to produce precision motors, guidance systems, and actuators. This KPI aligns directly with weaponized interdependence logic. It identifies where network topology creates coercive leverage and where investment most directly raises the cost of disruption.

Method: A Herfindahl-style index applied only to non-substitutable nodes, weighting supplier share by the degree to which inputs lack viable alternatives, so that concentration reflects true coercive leverage rather than nominal market diversity.

4. Sub Tier Supplier Liquidity Coverage

This measures how long critical Tier-2 and Tier-3 suppliers can continue operating under stress. It captures how financial shocks propagate through the industrial base. Recent assessments repeatedly show sub-tier suppliers operating on thin margins with limited access to emergency credit. When disruptions occur and payments slow, these firms fail first, triggering production stoppages that cascade upward.

Target: About 90 to 180 days of assured liquidity for priority suppliers, supported through guaranteed credit lines or accelerated payments.

5. Assured Inputs Stockpile Days

This measures how long production can continue using secure inventories of irreplaceable inputs. These are materials and precursors that cannot be substituted or sourced at scale under duress. Current stockpiles of critical energetics precursors and magnet alloys often cover a few weeks or months of wartime consumption. Operationally meaningful reserves must be sized to production rates rather than abstract tonnage. For example, stockpiles should be calibrated to sustain guidance-system production for key munitions.

Target: Approximately 12 to 18 months of sustained production for critical systems.

KPI Summary

Taken together, these five KPIs operationalize the Economic Security Dual Mandate. They shift attention from exposure to performance, from announcements to outcomes. They also explain why many well-intentioned policies fail to improve endurance. If investment does not move these indicators, economic security remains aspirational. Measurement, however, is only half the problem. Progress will only be made by allocating useful capital to shift these KPIs in meaningful ways. That is where economic security requires intentional investments to ensure a resilient industrial base.

Why Capital Allocation Determines Economic Security Outcomes

Measurement identifies where industrial systems fail. Capital allocation determines whether those failures persist. Without disciplined investment to overcome chokepoints, even the best KPI framework is just more policy pontification. Economic security is achieved by where the money goes, when it goes there, and what it is allowed to buy.

This distinction matters because much of today’s economic security spending still treats capital as a signaling device rather than a constraint-solving tool. Funds are often dispersed to demonstrate commitment, attract private investment, or spread benefits geographically. Those goals may be politically useful, but they do little to improve endurance under coercion unless they target the factors that actually govern output when the system is disrupted. The relevant question is not whether investment is large, but whether it measurably improves recoverability, surge potential, and resilience at critical nodes.

Industrial systems are shaped by irreversibility. Tooling, facilities, workforce pipelines, and qualification processes lock in production patterns for years or decades. Once these structures are set, they are slow to change regardless of demand signals downstream. Capital that arrives after a constraint is revealed cannot be repurposed quickly when conditions deteriorate. By the time disruption exposes where the system is weakest, it is already too late to build around those weaknesses.

This is why economic security investment must be evaluated differently from growth or innovation spending. The objective is not to maximize returns or accelerate diffusion. It is to raise the floor of output and steepen the recovery curve after disruption. That requires a bias toward assets with long lead times, high fixed costs, and limited substitutability. These are precisely the areas where private capital is least willing to invest without help from The Entrepreneurial State.

Capital discipline also matters because economic security spending competes with itself. When resources are spread thinly across too many initiatives, no single constraint is meaningfully relaxed. The result is a portfolio that looks comprehensive but delivers marginal gains everywhere. Endurance improves only when investment is concentrated at anticipated points of failure. Public capital is not meant to replace markets or permanently subsidize production. State-involvement is just meant to shape industrial structure in ways that markets alone will not, such as the Pentagon deal with MP Materials to source domestically produced magnets with guaranteed price floors. Once endurance is built into the system, private actors can compete within those bounds; meaning this framework makes investment options clearer.

A $50 Billion Endurance Build for a China-Proofed Industrial Base

Capital improves economic security only when it is used to solve binding constraints. The purpose of a $50 billion investment is not to chase technological primacy or replicate China’s scale across every sector. It is to illustrate how public and private capital might be concentrated against the highest-leverage vulnerabilities in the American industrial ecosystem. The allocation below is therefore best understood as a stylized portfolio, not a full national industrial strategy. Its logic is simple: prioritize sectors where lead times are long, substitutability is low, spillovers are high, and coercion vulnerability is acute.

The four pillars below reflect those criteria. Together, they target bottlenecks that would matter not only to the defense industrial base, but also to semiconductors, energy systems, logistics networks, and advanced manufacturing more broadly.

Pillar One: Energetics and Munitions Throughput ($15 Billion)

Sustained mass and fires, not exquisite platforms, are vital for warfighting during a prolonged conflict. Energetics, propellants, explosives, and their upstream chemical precursors govern what weapon systems can be employed at scale. Unfortunately, these production lines are capital intensive, environmentally constrained, and slow to expand. Despite billions being committed to ramp up munition and missile production, industry has struggled to match demand.

A $15 billion investment focused upstream would fund redundant precursor plants, idle surge lines maintained for crisis activation, and workforce pipelines for energetics chemists and technicians. These investments directly impact KPIs for: increasing Surge Ratio, shorten Time to Reconstitute, and extend Assured Inputs Stockpile Days.

Pillar Two: Midstream Processing and Magnet Production ($15 Billion)

Economic coercion is applied most efficiently in the middle of supply chains, where raw materials are converted into usable industrial inputs. Rare-earth magnets illustrate the problem, such as Chinese sourced magnets ending up in American-made F-35s. American mining doesn’t help because it takes 29 years to get a mine up and running — and it still takes 16 years elsewhere for a new mine. Even worse, separation, refining, alloying, and magnet manufacturing are what determine usable output across the industrial base, which is also dominated by China. U.S. and allied efforts are meaningful but will not reach a useful industrial scale until the early 2030s.

A $15 billion commitment would accelerate heavy-rare-earth separation and magnet facilities enough to get China out of the Western supply chain. Moreover, such investment would support qualification and offtake agreements and enable stockpiling of inventories in industrially usable forms. For the KPI, it directly reduces the Chokepoint Concentration Index and extends Assured Inputs Stockpile Days.

Pillar Three: Sub Tier Industrial Finance as a Security Instrument ($10 Billion)

Industrial systems fail from the bottom up. Tier-2 and Tier-3 suppliers absorb shocks first and recover last, yet remain largely invisible in industrial policy debates. That invisibility is dangerous because these firms often sit at the exact points where localized disruption becomes systemic failure. Besides small suppliers being fragile, the structure of defense and advanced manufacturing supply chains often leaves them exposed to cash-flow shocks even when prime contractors remain insulated. For instance, sub-tier firms usually contract through major integrators rather than directly with government, which means they often do not benefit from the favorable financing terms available to primes. The same reporting also shows a shrinking supplier base, with more than 17,000 firms leaving the defense sector in recent years and small-business participation down sharply.

A $10 billion sub-tier industrial finance facility would therefore function as a standing shock absorber rather than a subsidy program. Revolving credit, rapid-payment guarantees, government-backed liquidity lines, and resilience-linked contracting for priority suppliers would stabilize the firms most likely to fail first in crisis. This directly improves Sub-Tier Liquidity Coverage and helps prevent payment delays or input disruptions from cascading into system-wide failure. Because many of these firms also support aerospace, automotive, electronics, and energy systems, stronger sub-tier finance improves resilience across the wider economy, not just defense production.

Pillar Four: Machine Tools and the Industrial Commons ($10 Billion)

The ability to make the tools that make everything else is foundational to endurance. Machine tools, advanced manufacturing equipment, and specialized components underpin every industrial sector, yet domestic capacity has eroded. China commands around 33% of global machine tool production. Specialized components, precision castings, and skilled labor pipelines take years to rebuild.

A $10 billion investment in the industrial commons would combine tax credits, purchase commitments, and targeted R&D for next-generation automated machining tools, additive manufacturing equipment, and the supplier networks needed to sustain them. These investments shorten Time to Reconstitute across sectors and reduce chokepoint concentration in the tooling base itself. Machine tools underpin semiconductor fabrication, aerospace production, automotive manufacturing, and energy infrastructure. Rebuilding “industrial commons” improves recoverability across the entire economy.

How the Endurance Build Moves the KPIs

The value of this portfolio lies in its ability to move the indicators that actually define economic security performance. Investments in energetics, midstream processing, sub-tier finance, and the industrial commons collectively raise surge capacity, shorten recovery timelines, reduce chokepoint concentration, stabilize supplier liquidity, and extend assured inputs coverage.

These effects reinforce one another. Surge is hollow if sub-tier firms fail first. Stockpiles buy little time if tooling cannot be replaced. Reduced chokepoint concentration matters only if alternative capacity can be staffed, financed, and brought online quickly. By explicitly linking capital allocation to KPI movement, the endurance build turns economic security from a collection of programs into a coherent, measurable strategy.

Designing an American Economy that cannot be stopped

Economic security debates often gravitate toward scale, speed, or technological edge. Those attributes matter, but they are not decisive on their own. The more fundamental question is: Can the United States sustain production when pressure is applied deliberately and continuously? If the answer is unclear, economic security is a slogan.

Endurance under coercion must be a governing strategy that offers a clearer organizing principle. It shifts attention away from peacetime efficiency and toward performance under stress. It also clarifies why geography alone is an insufficient proxy for security and why market forces, left to themselves, rarely preserve the redundancy, recoverability, and slack that continuity under disruption requires.

My proposed Economic Security Dual Mandate strives to provide that discipline. Minimum Viable Capacity defines the floor of output that must be sustained under adverse conditions. Maximum Credible Coercion Cost defines how difficult it is for an adversary to interrupt that output. Together, they turn economic security into a testable proposition.

The five KPIs operationalize that mandate. Time to Reconstitute, Surge Ratio, Chokepoint Concentration, Sub-Tier Liquidity Coverage, and Assured Inputs Stockpile Days capture the mechanisms through which coercion actually works. They reveal where industrial systems break first, where resilience is real rather than assumed, and where investment can generate the greatest strategic return. Just as importantly, they offer a common language for distinguishing between industrial activity and industrial power.

Capital allocation is the bridge between diagnosis and capability. Economic security is strengthened by concentrating investment where lead times are long, substitutability is low, spillovers are high, and failure would be strategically costly. The endurance build outlined here is not a complete industrial strategy. It is an illustration of how public and private capital can be aligned to strengthen the industrial ecosystem where coercion would otherwise bite hardest.

That broader ecosystem matters. The defense industrial base is the most visible and unforgiving stress test, because wartime demand exposes bottlenecks quickly. But the same logic applies to semiconductors, energy systems, logistics networks, machine tools, and the enabling infrastructure behind advanced manufacturing and AI. A serious economic security framework must therefore extend beyond any single sector while still recognizing that some sectors reveal the problem more clearly than others.

This approach also offers political durability. A KPI-driven framework anchors debate around shared outcomes rather than changing rhetoric, reducing the temptation to relitigate economic security with every change in administration. That continuity is itself a strategic advantage.

The goal of economic security is not autarky. It is minimizing time to recovery while preserving competition, capability, and continuity across critical sectors. Endurance is what converts economic capacity into strategic power. If economic security is to move beyond slogans and into strategy, it must be judged by a simple test: how quickly production recovers, how long it sustains, and how costly it is for an adversary to interfere. That is the standard that matters. And it is one that can be measured.

is in Cape Town for two weeks… email Nick at nick@chinatalk.media if you’re interested in joining a ChinaTalk meetup!

We’ve recently tried to pin down how much compute China actually has, approaching the question from both the supply and demand sides. We converged on roughly 2.5 to 2.8 million H100-equivalents. But a single aggregate figure only captures part of the picture.

Jensen on China

On Dwarkesh’s podcast last week, Jensen Huang argued that China already has enough compute to build frontier AI.

“They manufacture 60% of the world’s mainstream chips, maybe more.”

When Dwarkesh raised the gap in advanced chips, Jensen responded,

“AI is a parallel computing problem, isn’t it? Why can’t they just put 4x, 10x, as many chips together because energy’s free?”

Jensen is wrong, but that doesn’t mean people aren’t compelled by this line of reasoning. John Moolenaar, who chairs the House Select Committee on China, sent a letter to Lutnick in December proposing a rolling technical threshold that would cap Chinese aggregate AI compute at 10% of US compute capacity. It’s much more nuanced — accounting for memory and network bandwidth as part of this calculus — but ultimately seems motivated by preventing, as the letter calls it, “death by a thousand sub‐threshold chips.”

Export restrictions are a difficult line to walk, and total computing power does matter. But not all compute is created equal. The compute that can train a frontier model, serve inference on an existing one, and power your laptop are different things, and a “death by a thousand sub-threshold chips” is less concerning for the trajectory of AI than a concentration of the most important chips.

Legacy Chips Don’t Matter for AI

It’s hard to know where Jensen is getting his claim that “China manufactures 60% of the world’s mainstream chips.” Perhaps originally from a 2024 projection from previous Commerce Secretary Gina Raimondo about new legacy chip capacity coming online in China. But this is not a measure of AI compute. It includes the chips running your car’s engine management system, your washing machine’s control board, and the power electronics in an industrial motor, typically manufactured at 28nm or larger. They matter, but they are not the chips that train frontier AI. A chip in your microwave cannot do matrix multiplication for a transformer, and a 40nm microcontroller in a Chinese EV does not help run DeepSeek-V4.

The sliver of Chinese chip output that is actually AI-relevant, primarily Huawei’s Ascend line, is roughly a million chips. But even the flagship Ascend 910C (with yields of about 300-600k chips this year) delivers slightly worse than Nvidia’s H20 for training, nowhere close to a Blackwell, and much of current production still depends on a stockpile of TSMC dies acquired before controls tightened. The remainder of China’s frontier-relevant compute comes from smuggled Nvidia chips and legally imported lower-tier chips like the H20. In short, China produces lower-quality chips and still cannot manufacture as many of them as the U.S. does; for them to reach anything close to a “death by a thousand sub-threshold chips” scenario, Chinese companies would have to concentrate what compute they do have to a degree greater than any American lab — a difficult task given the vigorous competition taking place between them.

This is why FLOPs is a more honest metric than total chip count. FLOPs, or floating-point operations per second, measure how many arithmetic calculations a chip can perform in a given second, and they are the fundamental currency of AI training and inference, since every command an AI executes is ultimately a sequence of multiply-and-add operations. And the FLOPs gap between frontier and legacy chips on this metric is staggering. A single Nvidia Blackwell B200 delivers roughly 10 petaFLOPs of dense FP8 performance, while a typical 28nm automotive microcontroller delivers around 0.12 teraFLOPs of FP32, roughly twenty thousand times less.1 To put that in concrete terms, if a country had 100,000 Blackwells, its rival would need more than the absurd number of two billion legacy chips to match the same FLOPs output.

But putting mainstream legacy chips aside, if China somehow did stack up many weak AI-focused chips (like Ascends), its problems would not end at matching FLOPs.

A Tale of Two Hypothetical Countries

Nvidiana and Huaweiopolis each have 2 million H100-equivalents. On paper, they are peers.

Nvidiana’s stock is top-heavy and lean. Roughly 300,000 frontier chips, the Blackwells and soon-to-arrive Vera Rubins, sit at the core, tightly interconnected in a handful of purpose-built data centers that can host training runs of tens of thousands of chips in lockstep. Another 600,000 chips, the H100s and H800s, handle large-scale training and serious inference. The remainder is padded out by around 650,000 older accelerators and general-purpose silicon for lighter workloads. Total physical chip count, roughly 1.55 million.

Huaweiopolis got to the same total a different way, by stacking weaker chips in enormous volume. Its top tier is thin, perhaps 50,000 frontier chips acquired before the latest round of export controls, and even those are scattered across several clusters rather than concentrated. A middle tier of around 450,000 chips, a mix of older Hopper variants and Chinese accelerators like Huawei’s Ascend 910B, is capable but constrained by weaker interconnect and memory bandwidth. The remaining mass of Huaweiopolis’s stack, close to 6.5 million chips, is older, inference-oriented chips like the H20, and repurposed general-purpose hardware. Total physical chip count, roughly 7 million — more than four times Nvidiana’s.

Nvidiana can train and serve the next generation of frontier models. Huaweiopolis cannot, and more chips will not close the gap. The difference in their AI trajectories will be substantial, even with identical FLOP counts.

Why Fewer Powerful Chips Beat Lots of Weak Chips

Huaweiopolis’s performance will lag behind for three main reasons: numerical precision, memory bandwidth, and network bandwidth.2

Numerical Precision

Older chips are not designed for the latest trends in numerical precision — that is, how finely or coarsely a chip represents numbers when doing calculations, which directly affects how much data needs to be moved and processed. Older chips, like the Hopper series, are designed to handle INT8 operations at best, meaning numbers are calculated to eight digits. Meanwhile, newer chips like the Blackwell series are designed to handle both INT8 and FP4 calculations, a jump that essentially doubles the speed of a chip. These chips can instead calculate numbers to only four digits while minimally compromising performance. By calculating half the digits, these chips have double the speed. If you are comparing chips across a standard of INT8 operations, which most studies do, then you are obfuscating the extra capability that newer chips get from being able to perform at FP4. Newer models are being trained at FP4, and inference also does not really care about less precision, meaning the capability to perform at lower numerical precision is a boon.

Memory Bandwidth

Measuring FLOPs alone also overlooks the critical importance of memory bandwidth. For most inference workloads, chip performance is not constrained by FLOPs but rather memory, since running a model means searching for and pulling billions of its stored values just to do a handful of simple calculations on each one before moving to the next. Instead of waiting for the logic to crunch numbers, the logic is waiting for the memory to fetch it numbers to crunch. A chip with ample FLOPs but insufficient memory bandwidth is like a chef with incredible knife skills but a single narrow hallway between the pantry and the kitchen, where she often has to waste time waiting in line behind the other chefs to get her ingredients. No matter how fast her hands move, the ingredients accumulate too slowly for the speed to really matter.

Frontier AI chips typically rely on high-bandwidth memory (HBM) to maximize memory bandwidth so that this downtime is minimized. Older chips use older HBM, which has worse memory bandwidth. The Hopper series uses HBM3e with a bandwidth of 4.8TB/s, whereas the Blackwell series uses newer HBM3e with a bandwidth of 8TB/s. (TB/s stands for terabytes per second, the rate at which the memory can deliver stored values to the compute units.) The newest Vera Rubin chips use HBM4 with over 22TB/s of memory bandwidth. Meanwhile, domestic Chinese chips have yet to crack HBM3; Huawei’s Ascend 910C uses (foreign-made) HBM2E with only 3.2TB/s of memory bandwidth. This means that despite Huaweiopolis’s superficial equivalence in FLOPs to Nvidiana, a large proportion of those FLOPs are unusable for inference workloads, since the logic units end up twiddling their thumbs waiting for memory, making query response times far too long.

Network Bandwidth

Lastly, network bandwidth — the speed at which data moves between separate chips or racks of chips — would severely limit the performance of Huaweiopolis’s cluster. Memory bandwidth is a limiting factor for within-chip communication because it determines how quickly data can move between a chip’s memory and its logic, effectively setting how fast the chip can stay fed with work. Network bandwidth — how quickly different chips can exchange data across the rack — is the limiting factor for between-chip communication, and network bandwidth is significantly slower than memory bandwidth. For an eight-chip cluster of B200s, memory bandwidth is an aggregate of 64TB/s, whereas network bandwidth is only 14.4TB/s. For training and serving inference on models, you don’t want to use network communication if you can help it because every time chips need to exchange data, they must stop and wait on one another; at scale, this turns communication into the dominant cost, meaning that adding more chips yields diminishing returns and eventually no additional performance at all.

Unfortunately for Huaweiopolis, if their strategy is to connect a massive blob of lower-quality chips to compete with a tiny cluster of higher-quality chips, they cannot succeed; network communication is unavoidable, and it will hurt. A Nvidiana cluster, with more power and memory storage per chip, can do a lot more within-chip before needing to resort to between-chip communication. A Huaweiopolis cluster will be running into this bottleneck a lot more frequently, and it will slow down operations. Particularly for training large models, where using multiple clusters of chips is necessary, the network bandwidth limitations will be crippling.

Jensen likes to dismiss this issue by arguing that “Huawei is a networking company” and dismissing the importance of HBM, but this is simply not the case. Networking will always be worse than memory bandwidth because data inside a chip moves over much shorter, more direct connections, while networking requires sending data across longer links with added coordination delays. Even God’s best NVL72 or Huawei optical fibre could not beat HBM in this battle because “beating HBM” would mean feeding the chip inputs as fast as its own memory can, which no external network can match.

FLOPs matter, but they are not the only metric. They are perhaps our best metric of comparison for now, but a proper comparison requires consideration of multiple factors. A naive equivalence on FLOPs of a Huaweiopolis cluster with a Nvidiana cluster hides the fact that the Huaweiopolis cluster will suffer in performance for both training and inference. This is not just a question of efficiency or speed. In extreme cases, the system can simply fail to train properly. Modern training requires tightly synchronized gradient updates across many chips, so if communication is too slow or inconsistent, those updates arrive late or out of step. The result is that the model is no longer being updated in a coherent direction — gradients do not reliably descend — and training can become unstable or fail to converge altogether, not just take longer or require more energy.

Conclusion

Aggregate compute matters, especially for the broad diffusion of AI across an economy. But when the question is whether a country will have the most powerful AI model, the quality and concentration of its best chips matter far more than its total headcount, and even more than total FLOPs.

There are signs that policymakers are beginning to internalize this logic. Moolenaar’s SCALE Act, introduced this week, still uses the rolling technical threshold framework but has shifted away from his earlier proposal to cap China’s aggregate compute at 10% of US capacity, which was the more aggregate-focused approach. Instead, it would permit exports only up to 110% of the performance of the best chips China can already manufacture domestically at scale, pegging the threshold to Chinese domestic capability rather than total compute. It is a narrower, more observable target, and it takes the quality-over-quantity insight more seriously than the aggregate headcount approach did.

No chip policy is going to be perfect, but the underlying logic is to focus the policy on the specific chips that matter most. We should be building enforcement around these crown jewels rather than solely around an aggregate FLOP count, and definitely not based on dubious chip counts!

Mood Music (Jordan)

Finally, DeepSeek V4 is here. The Pro and Flash models are available through DeepSeek’s website, mobile apps, and API access as of April 23, and the lab has also released its technical report.

Bucking a recent trend of Chinese AI labs moving away from open source, V4 was released under the highly permissive MIT license. It performs admirably on various benchmarks and leads the pack of Chinese open models, but did not close the gap with closed models from the US, with the authors themselves admitting in the paper that V4 is “3 to 6 months behind” state-of-the-art frontier models (though we think it feels further). And as we will discuss later, while its architecture shows progress towards indigenizing the Chinese stack, the model probably still relied on Nvidia GPUs.

Is V4 a letdown? Today on ChinaTalk, we bring you our takes alongside those from Chinese observers on:

• Troubles at the lab prior to V4’s arrival;

• Why DeepSeek’s idealism may not hold;

• What V4 did — and did not — achieve with domestic hardware;

• And why DeepSeek’s symbolism persists inside China, even after it lost the frontier

Translations were drafted with the assistance of Claude Opus 4.7, and then edited for accuracy and fluency. Bold markings added by the editor.

How V4 Got Here

Chinese tech journalists have doggedly followed the DeepSeek story. Zhou Xinyu 周鑫雨 of 36Kr, a prominent Beijing-based tech news outlet, has some behind-the-scenes scoops.

The reasons behind [V4’s] belated arrival are related to migrating its training framework from NVIDIA to Huawei Ascend, as well as to internal decision-making changes at DeepSeek. We learned that in mid-2025, DeepSeek ran into a relatively serious case of training failure.

“At the time, DeepSeek was facing the problem of re-adapting to chips,” one insider mentioned. “Internally, opinions on the direction of training were not entirely unified. Liang Wenfeng put forward some of his own demands, but it was difficult to find compromises at the execution level.”

However, contrary to outside speculation that the new model might support multimodal generation and understanding, V4 remains a language model. The decision to postpone multimodal generation training stems mainly from constraints on computing power and cash.

Multiple insiders told AI Emergence [a 36Kr sub-brand focusing on AI] that DeepSeek’s external financing window opened in mid-April 2026. Internally, the trigger was that DeepSeek needed more funding to train models with larger parameter scales, while also retaining and recruiting more top-tier talent.

Shanghai-based news site The Paper 澎湃新闻’s Fan Jialai 范佳来 compiled a comprehensive roundup of DeepSeek’s talent losses, losing core contributors to Tencent, ByteDance, Xiaomi, and DeepRoute.ai. “Across multiple areas — foundation large language models (LLM), agents, text recognition (OCR), multimodality, and more — DeepSeek has suffered losses of core talent.”

DeepSeek operates with the ethos of a frontier lab. Back in November 2024, we translated an interview with CEO Liang Wenfeng, done by Lili Yu 于丽丽 of Chinese media outlet Waves 暗涌. In it, Liang explained that DeepSeek was uninterested in product development, and that their goal has always been “AGI.” It was why, instead of adopting Llama architecture, they poured resources into the new model architectures behind R1. On why research, rather than products, was their raison d’être, Liang remarked:

For many years, Chinese companies are used to others doing technological innovation, while we focused on application monetization — but this isn’t inevitable. …

We believe that as the economy develops, China should gradually become a contributor instead of freeriding. In the past 30+ years of the IT wave, we basically didn’t participate in real technological innovation. We’re used to Moore’s Law falling out of the sky, lying at home waiting 18 months for better hardware and software to emerge. That’s how the Scaling Law is being treated.

But in fact, this is something that has been created through the tireless efforts of generations of Western-led tech communities. It’s just because we weren’t previously involved in this process that we’ve ignored its existence.

In this way, its closest American approximation might be OpenAI in its pre-ChatGPT Microsoft days: mission-driven, amply funded, and committed to nonprofit development of the AI frontier. If early OpenAI’s animating force was safe superintelligence, DeepSeek’s was a combination of AGI ambitions, open-source idealism, and national pride.

In the latest sense, it succeeded: DeepSeek became China’s national champion for LLMs. But that designation, and its founder’s high-minded aspirations, bogged down its research potential. Liang did not ride the DeepSeek wave in early 2025 — like Sam Altman did for ChatGPT — to build a scaled consumer product. Instead, he focused his team’s energy exclusively on the “hardcore research” he made his name on. By not building a revenue-generating business over the past twelve months or partnering with a Chinese hyperscaler, Liang bled talent and lost the lead he had over his domestic competitors.

More than any other lab, DeepSeek shouldered expectations to produce the proof-of-concept for Chinese-made chips, rather than follow other labs by relying on smuggled chips and Nvidia cloud compute abroad. This cost it financial runway and talent, and probably led to a failed training run that delayed V4 by months. The aforementioned 36Kr story reports that over the past year, DeepSeek recruiters were seen lurking the dorms of Peking University in search of Chinese majors to staff a new marketing unit.

After R1 came out in 2025, Jordan and Kevin Xu of Interconnected speculated on a podcast episode that DeepSeek, in the near future, could be lured by deals with hyperscalers or some other deep-pocketed entity. They were prescient. Per 36Kr:

As for the external trigger for pivoting toward open financing, several industry insiders speculate that it is related to the investment stance of a certain major company. Before opening DeepSeek up for financing, Liang Wenfeng and the top leader of that company had held several rounds of discussions regarding exclusive investment. But according to two sources connected to the matter, Liang Wenfeng did not agree to that leader’s condition of giving away a 20% stake.

With V4 out now, DeepSeek is in the throes of a dilemma that cuts to the center of its tripartite mission. While OpenAI’s large-scale marketing of consumer and enterprise products smoothed its transition into a for-profit company, DeepSeek missed out on a golden period of market development inside China. Between V3 and V4, ByteDance’s Doubao became China’s most-downloaded chatbot; vertical-specific AI products — like Alibaba’s health app Afu — achieving groundbreaking success; and MiniMax and Z.ai, two pure-play model makers, went public and broke into international markets. DeepSeek, arguably, came late to realizing the importance of revenue under the Chinese market’s capital constraints.

When we examined DeepSeek’s lack of a path to profitability and the enormous political pressure it had begun to shoulder, we thought the lab’s tragedy might have been foretold. Fast forward to now, and the 36Kr story just declared the “post-DeepSeek era”. A Qwen employee told 36Kr that “the golden age of nonprofit AI development is over.” But the article also acknowledges that DeepSeek, in just one year, shaped China’s AI landscape. Beyond its model architecture innovations and the open source ethos, its flat internal hierarchy, focus on emerging talent, and AGI-inflected open research culture have all influenced management decisions at other labs hoping to replicate its success.

American Training, Chinese Inference?

V4, ultimately, was still trained on Nvidia chips. However, Huawei on April 24 confirmed that its own Ascend supernode cluster will be able to support V4. Earlier this month, DeepSeek did not give Nvidia and AMD early access to V4, perhaps superficially signalling distance from Western chipmakers. Popular tech blogger Digital Life Kha’Zix 数字生命卡兹克 examined V4’s technical report, and returned with four observations regarding how the model was optimized for Chinese-made hardware.

1. V4 has introduced MXFP4 into its post-training and inference systems.

Although training still uses the NVIDIA ecosystem, using MXFP4 in post-training and inference essentially means that DeepSeek is moving toward open low-precision formats and multi-hardware adaptation. It can adapt to domestic chips such as Huawei Ascend, Cambricon, Biren, and others, reducing its reliance on NVIDIA’s FP8 ecosystem — especially during inference. That would make it a genuine domestically-produced model running on a domestic ecosystem. …

2. V4’s underlying kernels are no longer written entirely in CUDA, but instead in a domain-specific language (DSL) called TileLang. DeepSeek hopes that low-level operator development won’t be completely locked into CUDA, but will instead use a higher-level language to describe computations and then compile them to different hardware as much as possible. This is seriously impressive and can greatly reduce migration costs.

3. V4 has specifically developed a fused kernel called MegaMoE, designed to reduce communication waiting in expert parallelism. It has already been successfully run on Huawei Ascend.

Putting these three points together, the direction is crystal clear: V4 is, from top to bottom, a model designed for domestic chips.

This really isn’t some patriotic story. Everyone knows how scarce computing power will be in the future, how slow computing power production is, and—under the acceleration of Agents—how terrifying the token consumption will become.

With computing power being choked off, no one has any good options. Just look at how a model as excellent as GLM-5.1 has been limited by inference compute.

The computing power game is, in many ways, a top-level geopolitical game.

DeepSeek V4 is the reality forced into being by this computing power struggle.

There was a curious footnote attached to DeepSeek’s official announcement of the V4 models:

Due to constraints on high-end compute, V4-Pro’s service throughput is currently limited. Once Huawei’s Ascend 950 supernodes ship in volume in the second half of the year, Pro’s pricing is expected to drop significantly.

The compute story probably demonstrates that Chinese models like DeepSeek will fall further and further behind Western counterparts. Western models are increasingly being trained and run on Blackwells and eventually Rubins, which can support FP4 numerical precision, effectively double the compute from previous generations that can only go to FP/INT8. DeepSeek has been stuck using old Hoppers, which only go to INT8; to have any chance of catching up, they will have to pray Huawei’s Ascend 950, which supports FP4, will be produced in sufficient numbers. According to Reuters, Huawei plans to ship 750,000 of their Ascend 950PR this year; for reference, that is just one week of quality-adjusted American chip production.

“The People Long for DeepSeek”

When the “DeepSeek moment” arrived in 2025, it didn’t only represent indigenous technical capabilities for China. For some developers and average people, it also meant having genuinely affordable access to frontier AI for the first time. American frontier labs have always restricted chat and API access in mainland China, and while many Chinese users found ways around the firewall anyway, DeepSeek was a model they could use with no fuss and, for a brief window, nearly comparable performance.

But after a year, there are now far more domestic models for Chinese users to choose from, embedded into many real-life applications. Meanwhile, OpenAI and Anthropic seem to have cemented their lead. With soaring demand and mounting financial losses, AI companies have no choice but to offload more costs onto paying customers. Fewer and fewer people can afford to extensively utilize frontier models. China’s OpenClaw craze earlier this year showed many people the true costs of AI, as their home-cooked agents guzzled tokens and left them with expensive bills.

In 2017, blogger Fang Hao 方浩 published a viral article titled “The People Long for Zhou Hongyi”. Zhou was the founder of security software firm Qihoo 360 and a famously pugnacious figure in China’s tech industry. Written at a time when Alibaba and Tencent were consolidating their monopolistic positions in e-commerce and social media, Fang couched pessimistic future predictions in irreverent humor: as Chinese Big Tech cannibalized opportunities in the private sector indiscriminately, it would leave average consumers worse off.

Last month, Su Yang 苏扬 of Tencent’s tech media blog wrote a sequel: “The People Long for DeepSeek”. He pushes back on Jensen Huang’s “tokenomics” rhetoric:

When token usage costs can’t be brought down, and when the effective return on investment remains unclear, aggressively pushing token consumption — even tying it to performance reviews — amounts to manufacturing token anxiety. Calling it manufacturing AI anxiety wouldn’t be an overstatement either.

Looking back a bit further, Jensen Huang also called on tech industry leaders to speak prudently and avoid stoking irrational public fear of AI technology. That’s essentially telling the whole industry: stop suppressing AI by manufacturing panic — you all need to keep the tokens burning.

But the question is, who’s going to solve the price problem? Will it be the long-delayed DeepSeek V4?

Su expands on the price issue in a follow-up post. While he is ultimately optimistic about the future of competitive innovation in China’s AI industry, he thinks DeepSeek will no longer be a singular flagbearer:

Broadly speaking, in 2025, China’s open-source forces reshaped the global AI landscape. By 2026, China’s AI development has entered a stage of exporting capabilities.

From the perspective of the global AI industry, the diversification of technical pathways has invigorated talent mobility and strengthened supply-chain resilience. For downstream application developers, having multiple suppliers to choose from means greater bargaining power and lower lock-in risk.

Another encouraging feature of China’s AI narrative is that the market has yet to be monopolized by a handful of oligopolies — a positive sign for competitive innovation and talent-ecosystem building, and one that also helps build cluster-level advantages in the U.S.–China AI competition.

…

In the landscape of full-ecosystem competition, DeepSeek — whose principles generate its force, with breakthroughs at the foundational layer — still holds advantages, but its weaknesses are equally clear: it lacks the industrial ecosystem support of an IT giant, its product application features are relatively thin, and its multimodal and agent ecosystem still need strengthening.

Is Coding the Way Forward?

V4’s coding capabilities have grown significantly, potentially signalling that DeepSeek, after the success of products like Claude Code, also sees promise in coding agents. Programming blogger Large Model Observer 大模型观测员 tested V4 on software engineering projects, finding two pros and two cons:

First, broad programming knowledge. Across the four engineering projects [that the author tested V4 with] extensive niche-domain knowledge is essential. Without it, you can end up unable to fix even simple bugs, such as a macOS application failing to display its window properly because the storyboard wasn’t correctly configured. V4’s knowledge base essentially covers these less mainstream areas, and when faced with various edge cases, V4 Pro can pinpoint the root cause of a bug directly rather than guessing — much like GPT and Opus. … V4 Flash isn’t far behind Pro on broad-strokes knowledge; Flash mainly falls short in edge-case knowledge and tends to be stumped by non-obvious bugs.

Second, low hallucination over long context. Because the engineering tests use a mode in which features are layered on round by round, the later rounds often require the model to re-read the entire project and locate every related detail when a global modification is requested. This is no problem for the likes of GPT/Opus, but it’s a real hurdle for domestic Chinese models. V4 Pro and Flash, at the high and max tiers, can essentially maintain a quite low hallucination level, with bug rates in downstream flows over long codebases still kept low.

Third, occasional lapses in attention. When projects are large and requirements are many, V4 Pro at the high tier — constrained by its thinking-budget allocation — has some probability of randomly dropping certain implementation details. The saving grace is that with a reminder and one or two rounds of self-testing, the issues can almost always be fixed. …

Fourth, an unfussy approach to architecture and UI. V4 largely inherits DeepSeek V3’s thinking on architectural design — not particularly tasteful, not refined, but not slapdash either: the layering and decoupling that ought to be there will be there. It can’t deliver the kind of polished, clearly master-crafted architecture you see from Opus at a glance. UI is the same story — direct output isn’t outstanding, with the occasional touch of refined expression, but most of the time it’s just at the basically-usable level. The high tier can occasionally have an even lower floor, with insufficient consideration. If the development workflow includes a design spec to follow, this is not a big issue. But for pure vibe coding, getting a satisfactory result requires a lot of rerolling.

Could V4 do for AI coding what V1 and R1 did for LLMs — democratize access to the frontier, especially for the Chinese user base? It’s not impossible, but the model faces ample competition among open-source peers. A quick comparison of leading Chinese open models’ token prices, in RMB:

DeepSeek’s prices are competitive, if not an obvious standout. BusinessAlert 知危 summarized it as such:

By now, users are no longer impressed by chain-of-thought. At most, it’s an engineering technique that boosts accuracy by throwing more compute at the problem, and in coding-agent scenarios it’s probably ignored most of the time.

The ceiling of [V4]’s capability makes it unlikely to play a leading role in real-world programming tasks, and as an executor it’s too slow. … All in all, from the perspective of the cases we tested, DeepSeek V4’s performance wasn’t as good as expected, and its capability seems not particularly stable either. But then again, the official technical report itself openly states that there’s still a gap between it and top closed-source models, and that this update merely narrows that gap — so the result isn’t surprising.

Still, as the saying goes: take another look at the price. It’s this cheap — you can put up with it.

While the Chinese-open-models price war looks fierce from the outset, it belies fundamental challenges: the business model is not yet clear, and the ecosystem is starved for funding at a much more severe level. We’ll leave you with Nick and Jordan’s recent analysis of why some Chinese labs are going closed-source, and why DeepSeek does not change the core political equation:

China’s funding environment for AI is orders of magnitude smaller than America’s. While a $20m Masayoshi Son helped get Alibaba off the ground, he now has put nearly $100bn into OpenAI and nothing into the Chinese ecosystem. Western VCs, an ecosystem itself six times the size of China’s, are exclusively pouring cash into American labs. Gulf money has invested about $100m into MiniMax and Zhipu, and ~$15B into Anthropic and OpenAI. …

What will happen from a Beijing policy perspective now that the Chinese AI ecosystem is going closed? Probably not much. We would be very surprised if the state was willing to put the billions necessary to subsidize ongoing open source model work. Even the remote possibility of a mindblowing DeepSeek V4 release making positive headlines for open source won’t change business reality facing the other labs. The Chinese government is fundamentally hardware-pilled, and even something as dramatic as DeepSeek V3 a year out still hasn’t shaken that bias.

DeepSeek Waxes Auto-Poetic

Jordan: I gave DeepSeek V4 this article and asked it to write a poem of how it made it feel.

And a Chinese one:

The Iran war burned through America’s L-RASM, JASSM-ER, and Tomahawk stockpiles — weapons designed for a Pacific fight against the PLA Navy, not the Iranian corvette fleet. Now Pentagon insiders are leaking that we can’t win a war over Taiwan, and it’s a six-year pipeline to refill magazines.

Joining us: Bryan Clark of the Hudson Institute and former submariner; , former Green Beret now in defense tech; Eric Robinson, former OSC/NCTC analyst and 101st Airborne officer, now a lawyer; and .

We discuss…

• Why on earth we fired L-RASMs at the Iranian Navy — and what that means for the Pacific

• The case for modular weapons over exquisite Cold-War-era munitions

• Why this admin is telling the press “We can’t win a war over Taiwan” — what leaking this that actually means

• The Special Forces Romeo who made $400K on Polymarket betting against Maduro

• The Phelan firing, the waffle bar, and Driscoll’s survival odds

This is a transcript of a podcast!

Listen now on your favorite podcast app.

Out of Ammo

Eric Robinson: Why is the Pentagon starting to scream to the press about war stocks? Something that countries should probably keep in their back pocket is how many precision weapons you still have available. And in an open society like the United States attempts to be, some of these secrets are difficult to conceal. The number of specific munitions gets published by Congress, the Pentagon speaks about it openly. You can assess the capability of the United States Navy to carry certain warheads into certain locations. You can look at the Air Force and determine what kind of ordnance can go over a target. So there is a baked-in ability to do informed speculation, and people are doing that.

When General Caine and the Secretary of Defense go on TV and talk about the number of targets that have been struck in the Iran war, you can start to take an X and do a bunch of minuses beneath it and reach some conclusions. But we’re starting to see incremental precision coming out informally from the Pentagon that’s indicating the American ability to fight a sophisticated war is substantially degraded because of this war with Iran.

Bryan Clark: I think this is a case where people in the Pentagon are trying to get the attention of the president via the press. It’s a time-honored tradition. Not honored, but — it works. So yeah, definitely people trying to get the attention of the president by leaking to the press how we’re low on munitions and maybe we need to wrap up this Iran war post-haste.

Justin: I wouldn’t say it’s honored, but, anyways. This is one of those natural tensions we’re starting to see bubble up. You have these OPLANs and CONPLANs that are supposed to be in place for contingency operations. They are predicated on certain availability of weapons systems in the first hour, first 12 hours, first 24 hours. To make it to 72 hours and beyond, we need to have certain things in place. And you’re probably starting to see people who have very vested interest looking at INDOPACOM and making sure that their CONPLANs are sufficiently funded and have a robust capability. Looking at what’s happening in CENTCOM — to no fault of CENTCOM, but because they were directed to do this — and saying, that thing over there seems to be taking away my ability to do the thing that you’ve told me to always be ready to do, the most dangerous. I think that has a lot to do with it as well.

Eric Robinson: Yeah, hyperpowers have constraints.

Tony Stark: And to lean into that — because I think where some people try to get around this is, but we’ve already ramped up production, we’ve ramped up production in the last few years after Ukraine. The problem is we were on minimal sustaining rates for way too long. It’s not like we just had a max capacity magazine and we decided to empty it out and we can get back to it in two years. We were already low. We’ve burned way too much, and now just to get back to that previous low standard, it’s going to take years.

Justin: We have over-indexed on exquisite technologies because we have the ability to produce them. The problem with exquisite technologies is they take a very long time, they have very tenuous supply chains, and you can’t really do exquisite in high capacity.

Wrong War, Wrong Weapons

Jordan Schneider: OK, so with Phelan gone now we’re not doing the Trump ship. Is this an opportunity to kind of reset in a potentially better direction?

Bryan Clark: What Justin just brought up — maybe this is a good chance to rethink the munitions portfolio and say, do we want to refill our munitions stocks with the exact same thing we just spent on Iran? Because maybe JASSM-ER is not the only weapon we want to have in the inventory for doing air-to-ground attack. Maybe we need some of these low-cost weapons. There’s a bunch of options out there that the Pentagon has been funding development of, but just never funded procurement of. This is a great chance to rethink what the portfolio should look like and rebalance it towards these more modular weapons — not even really lower-end, but more modular weapons that maybe don’t have quite the performance of the preferred munitions, but you can buy them at much higher volumes and the production is much easier because they’re modular and some even use commercial components, like this ERAM missile that the Air Force developed.

The other thing it makes me think of is why are we using JASSM-ERs against Iran? I get that you wanted to use PRSM to test it out and the Army guys like to show off their toys, fine — and we didn’t have that many so it wasn’t a big loss. But to go out there and burn through a bunch of our JASSM-ER stocks and our Tomahawk stocks — why are we launching Tomahawks into Iran? Supposedly they have no air defenses.

Eric Robinson: You’re referring to L-RASMs against the vaunted Iranian Navy. Bryan, you’re at the heart of the question. Was there an American strategic assumption — we would imagine this is an Obama issue, this is a Trump I, a Biden issue, there are numerous parents of this failure — but had the Pentagon ever baked into its war planning that we were going to conduct a military campaign of this style, where you’re going to just go after targets without a political objective and the expectation being that if you employ a sufficient amount of violence, if you do gunfight properly, all of a sudden strategy emerges? That there is this baked-in collective understanding that if the United States is going to go to war against one of the big four threats, there’s going to be a Clausewitzian strategic approach to it? We are not there.

Instead we’ve got people doing wheelies in Lamborghinis, and it looks really cool and it gives you your sizzle reels, but we are still at an impasse with an Iranian state that refuses to fundamentally break down — and using your entire inventory of L-RASMs, which for viewers that haven’t engaged with this before, is an advanced anti-ship missile almost expressly designed for the United States Air Force to employ against the People’s Liberation Army Navy in Pacific contingencies. Instead, we went after the Iranian Navy, which is sort of like expending L-RASMs on the Austrian Navy. It doesn’t matter. But here we are. We are disaggregated from strategy. And now we’ve got empty war stocks, so we’ve got a six-year pipeline to try and restore this, assuming Congress gets behind it and funds it.

Justin: Yeah, I mean, we sank the SS Minnow with an L-RASM, so we’ve done well.

Eric Robinson: Yep, we got the good ship Lollipop and the yellow submarine.

Justin: Even for the PRSMs — while I get that we wanted to showcase what PRSM could do, there’s a good argument that PRSM is most useful in the land war in Europe. It’s not super useful in an over-the-sea battle in the Pacific because 900 kilometers is a —

Tony Stark: The other thing about PRSM is it solved one problem. It still didn’t solve the mass problem, which was the actual Russian artillery problem. It is now for-purpose in the Pacific, which actually makes it effective. It still wouldn’t have been effective in a Europe fight because it doesn’t solve the close-in conventional artillery battle.

Justin: It solved the wrong problem in its development. Then they kind of came up with the potential to have a solution within the Pacific. But still, the place where it’s the most useful, it’s not useful. It’s not a great answer.

Eric Robinson: Ultimately, the LUCAS system is probably just as good and less expensive in certain environments for long-range strike.

Justin: I imagine PRSM still has the same anti-personnel capabilities that some of the marks of HIMARS have, which are very nice, which LUCAS won’t have, which do make it more formidable against mass formations.

Eric Robinson: For the audience, LUCAS is — I’ll give credit — the Department of Defense innovated and stole a model from the Iranians. They didn’t go and buy a turdcopter from Silicon Valley. They got something that they knew worked on the battlefields and copied it relentlessly. And maybe the IRGC will go to court in the Southern District and go after the United States for stealing its IP, but in this war, the United States tested what we effectively stole from the Iranians and repurposed.

Bryan Clark: My concern now going forward is we’ve got this big defense budget that we’re looking at. And you’ve got this lobbying campaign by people inside the Pentagon, over at INDOPACOM, to basically restock all these weapons that they’ve built their plans around — not new weapons, but existing weapons. That’s going to take up a huge chunk of the budget. And we want to make these long-term commitments on weapons production to try to get production capacity increased, because a company like Raytheon is not going to expand production capacity unless they have a long-term commitment from the government. So if you do a five- or seven-year multi-year procurement, they’re going to be willing to support that level of production.

But that means you’re locking in a huge chunk of investment over the next seven years that’s going to be devoted to weapons designed in the Cold War or the immediate aftermath, and designed primarily to go after the highest-capability threats posed by China. It just seems like we’re going to lock ourselves into a portfolio that’s going to have the same challenges as our existing portfolio. It’s never going to get big enough, and it’s never going to have the ability to surge in the way that maybe a new portfolio of weapons more modular or more focused on one-way attack drones might.

Justin: The other thing worth thinking about is the consternation we had even in the Biden administration over giving HIMARS to the Ukrainians. If we’re really talking about enabling partners in the Pacific, the next question is: do we build these high-end systems that we’re going to instantly have concerns about giving to partners — the Philippines, the Japanese, the South Koreans? Because if that’s the case, then it’s not really a capability if it isn’t in theater and controlled by people who can use it. The department really has to come to grips with this and go to Congress and say, we need weapon stocks that we can actually give to our allies that allow them to present a credible deterrence or response capability.

Bryan Clark: Another aspect of this is adaptability. In Ukraine, they found that the Excalibur rounds we sent were quickly obviated by Russian electronic warfare against GPS, and same with GMLRS.

Eric Robinson: Excalibur is a 155-millimeter round that can be guided by GPS. In the global war on terrorism, Excalibur came out because the wars in Iraq and Afghanistan were uncontested electronic warfare environments. It enabled individual battalion commanders to effectively choose a 10-digit grid — a one-meter spot on a battlefield — and say, I’m going to blow that up. So Excalibur revolutionized precision strike. To Bryan’s point, when it got to Ukraine and the Russians — a far more sophisticated adversary — jammed global positioning satellites, those rounds were dumb rounds and were not particularly helpful.

Tony Stark: GPS is this wonderful invention that we’ve had around for over 40 years. The problem is, because of the way it functions, it’s incredibly easy to jam. If your entire targeting package is built around being able to find that 10-digit grid, that’s a massive complication, and the US still hasn’t quite gotten around it.

Bryan Clark: All these weapons we’re talking about — L-RASM, JASSM, SM-6 — they all use GPS to some degree as part of the guidance solution. Even if it has a seeker, even if it’s getting a guidance update via the radio, it’s still using GPS to orient itself in the world. If it loses that, it’s very difficult to orient itself. You now have to either adapt the inertial navigation units onboard to make them more capable, or provide a constant radio signal to tell it where it is, or have other sensors onboard that allow it to predict its location based on star shots — there are companies doing that — or detecting emissions from cell towers or TV and radio antennas, which you can use to geolocate yourself.

The problem we have with these legacy weapons — these kind of high-end weapons that are highly integrated, like Excalibur — is they’re too hard to modify. We still haven’t really fixed Excalibur to address this GPS jamming issue. And they’re desperately trying to fix GMLRS to make it able to use other sources of navigation, like radio emissions. So we’re going to invest a bunch of money and make long-term commitments in weapons that are difficult to adapt, because we don’t know what the next countermeasure from the opponent is going to be. It’s GPS jamming today, but it could be something else tomorrow that goes after their seeker mechanism or their ability to orient because we’re going after something else in the electromagnetic spectrum. There’s all these opportunities for move–countermove competitions that these weapons don’t give you the ability to respond to.

Leaking for $$ From Congress and OMB

Eric Robinson: One point I want to build on that Bryan really helpfully said earlier: these stories are coming out in the press because somebody is trying to signal to the White House. It is arguably stakeholders inside the Pentagon. It is probably also the primes for these dastardly-six companies who are trying to communicate — one to Congress, two to the White House — hey, pay us money, let’s get reconciliation through, let’s get the president’s budget through so we can start ramping this process up.

It reflects an interesting communication mechanism in Washington right now. Because there’s really not a whole lot of value in going to Pete Hegseth and talking about munitions stocks — it’s just not something he cares about. You can go to the deputy, and the deputy absolutely cares about this, but he’s not necessarily going up to glad-hand on Capitol Hill. So you do the scattershot communication strategy to raise the profile of vital issues. Then you can go to OMB, to Senator Wicker at SASC, to Representative Rogers, and say, OK, we do have a crisis, let’s start to solve it. We’re witnessing the creation of an information environment where once you get past the official bluster from the Secretary of Defense, there is an authentic problem now that has to be resolved.

Jordan Schneider: Here’s the problem. You know who else uses remove-paywalls on the Washington Post? Our allies in the Pacific and the Chinese government. So this is not ideal the way you’re going about this, if we’re trying to preserve deterrence capacity. One of the quotes from a senior administration official was, we can’t win a war today over Taiwan. If you’re a Taiwanese politician and you read that, what do you feel like? It is a signal of the breakdown of this administration and how they’re trying to rebuild.

Eric Robinson: It is not new. In the late 1950s, when you had giants of the Senate like Jack Kennedy and Arthur Vandenberg, they would go to the floor and talk about weapon systems. You had carrier generals and missile generals and bomber generals — or senators. They all had their pet members of Congress, and they would basically dump the national secrets into the Congressional Record. And the Soviets were monitoring that.

So Congress, through its position of supervising the executive — which is the core function of the American Republic — has this habit and maybe even a responsibility of conducting aggressive due diligence on what the executive is doing. And we’re witnessing that now. It’s ugly, and I don’t mean to minimize it, but it’s not new.

Can We Actually Lose?

Justin: I will push back a little bit, Jordan. I don’t see this as demonstratively different than the purges that occurred with the PLA Rocket Force when Xi found out there was a lot of corruption within the Rocket Force. The difference is that this comes from multi-facets, and it’s not like people like Bill Bishop pulling out reporting and figuring out what’s happened. So it’s slightly different in the volume and the tenor, but it’s not indifferent. I don’t think we think China is in the best spot either. That being said, saying we’re not in a position to win a war is different than saying we’re in a position to lose a war.

Bryan Clark: Obviously this guy tried to grab attention with what he’s saying, but I feel like what he means is we’re not able to win a war on the terms we want to win it on, using the things we want to use to win it. There’s lots of ways that a war over Taiwan could play out. We’ve wargamed a lot of them. And usually it results in the Chinese losing. The main differentiator is how much do we lose in the process? So when they say we’re not in a position to win a war, normally it means the losses we’re going to incur don’t seem attractive. And it may be enough to cause a president to be reticent about intervening on Taiwan’s behalf. So it’s a lot more about how well does it go rather than are we able to stop an invasion of Taiwan by China.

Tony Stark: It’s a pretty good bet that the best description for that fight is a drunken bar fight. As nice as you want to make it, it’s going to be ugly just by the geography, by the munitions burned. There was reporting this week that some of the most recent purges in the PRC are due to skepticism over whether the weapon systems actually work — going beyond the Rocket Force. Xi Jinping has to have some concerns if he’s watching all these Russian SAM systems, which the Chinese cloned, just getting burned around the world. We might be out of ammo; their ammo might not work. It’s a great time all around.

Bryan Clark: At least our stuff works…

The Special Forces Gambler

Eric Robinson: Speaking of opponents — this is a good opportunity to talk about a perhaps lesser opponent in the Maduro regime and their Cuban personal security detachment, and Polymarket being a vehicle for not informed speculation but direct knowledge of events being used to generate financial rewards. Yesterday, the Department of Justice revealed an indictment of a Special Operations soldier at Fort Bragg with knowledge of pending action against the Maduro regime, who elected to speculate on Polymarket and apparently got, according to DOJ, $400,000.

We are in a world that the president has described as a casino, and he’s not particularly concerned. But this incident — a master sergeant in Army Special Operations — is now being held to account for insider trading.

Tony Stark: I want to play this through. You’re going to place this bet, you win all this money. You’ve got to file that on your taxes, right? Especially when you have a security clearance — people notice the sudden windfall, which is a literal insider threat mechanism: $400,000 to an enlisted man.

Jordan Schneider: But it’s in crypto in some account. That’s the thing — the taxable earning — presumably if you want to repatriate it into a US account, someone’s going to start asking some questions.

Jordan Schneider: The weird thing about Polymarket is it’s just this crypto setup. A month ago they started saying they were going to deal with insider trading — that it wasn’t cool anymore. And presumably the Department of Justice gave them a call at some point between February and now.

Eric Robinson: It’s not like an American sports book.

Jordan Schneider: It is wild that they thought this would be a sustainable thing. And it’s also so predictable. How many people knew this was going to happen? Probably thousands, right? And you only need one, and they’re not going to bet 50 bucks. Though Kalshi just did catch a handful of people in their primaries betting on whether they were going to run or not, which —

Justin: I bet you that’s how it started. This is that slippery ethical dilemma. We had been already talking about it with other actions — Midnight Hammer, we had been talking about Boots on the Ground, we had been talking about the strikes on the drug boats.

Eric Robinson: There’s a substantial American presence. There was obviously something coiling in the Caribbean. It was not lightning.

Justin: That’s the pernicious effect, and where it’s going to get super regulated. To caveat what I’ve seen about the guy — he was a Special Forces guy, but he was a Romeo, a radio operator. He was a communications specialist supporting Tier 1 units. He was not actually one of the operators in the Tier 1 unit. So there is a distinction just there, because they go through a slightly different selection process. But if that’s all correct — before operations, before Afghanistan, before Fifth Group went into Afghanistan, they took all the teams and they isolated them. It was 2001, so it wasn’t a huge deal. They put the teams in a tent, and the only way they could ask questions or get information was to write it down and hand it to someone who’d go out, get it from the real world, and bring it back. Maybe that’s what we’re going to go back to — we’re going to start isolating these guys well in advance, and then they’re literally going to be cut off from anything that is not classified systems until the missions are over. But what are the effects of that?

Eric Robinson: Modern information markets — whether Predictit, Kalshi, or Polymarket — encourage individual action to spike these markets. And it’s not unique to American special operations.

This is not new behavior, but it’s being dramatically exacerbated. It used to be you had to be a sports hero in order to throw a game, or you had to have sufficient financial backing to witness something coming and then place a bet in commodities markets — you could look at the price of oil, there were ways to do this. But sleaze is now super democratized. There are such a great variety of markets, and there are ways for individuals to push events one way or another.

Jordan Schneider: We’ve had congressional insider trading for decades now. Which is the justification one congress member made yesterday saying this person should get a pardon and just have to give their money back. But it starts with that — there’s some level of permissivity coming from the legislators themselves. Which is not to say that should be legal or this stuff should be legal. But there’s a wholesale reckoning with the whole graft ecosystem that really should happen sooner rather than later.

Tony Stark: There’s a bipartisan bill in Congress right now on this topic. But of course, I think it only covers the troops and not members of Congress or any other senior federal official. I’ve got an article in draft somewhere about all these reforms that need to happen. One of them is just — if you are a US government official in any capacity, you do not get to bet on anything. You want to bet? Go to Vegas. But you do not get to place Polymarket bets or anything else. You don’t get to use the stock market, sorry. It’s become absurd to the point of ridicule at this point.

Graft Rot

Justin: If you want to have responsibility, you have to be beyond reproach. Congress also needs to get their shit together. But the fact that they commit a wrong doesn’t mean that other people should be allowed to commit wrongs. I get that people will use that as a justification, but it is what it is.

Bryan Clark: It creates perverse incentives inside the department. On the operational side, weird behaviors could emerge if you get the chance to bet on an op you’re going to be a part of. And even more important — if you’re making decisions on this new big defense budget, those decisions obviously could be useful in the equities market. That information might be something you could use for your own insider trading. At the SES level, and at the level of people who make decisions about money, you’re supposed to be reporting all those potential exposures. But I wonder if we’re really starting to throw all that by the wayside because at the top levels we’re sort of ignoring it. The senior bureaucrats in the Pentagon and elsewhere are now not really worried about being transparent about their holdings, because their bosses and their bosses’ bosses aren’t.

Tony Stark: One of the ways CIA allegedly made inroads into the Chinese Communist Party in the 2010s was because of the way the graft system worked. You don’t want to create that in your national security apparatus — oh, here, I’ll give you an insider tip for a Polymarket bet if you give me information. That is the type of stuff that intelligence services will attempt to use in order to gain intelligence.

Justin: If they haven’t already at least attempted it, I would be shocked.

Bryan Clark: It undermines the efficacy of the organization. Which is what you’re seeing in the PLA — these purges are in part because people are not effective in their jobs because they’ve been corruptly operating their fiefdoms. You end up with things like weapons that don’t have warheads, because it’s cheaper — you can pocket the difference if you buy the weapon without the gas or without the warhead. Are we going to start to see that kind of behavior because there’s all these opportunities for malfeasance that we’re ignoring and allowing to fester inside the department?

Tony Stark: There was a tolerance even among the voting base of, well, if they’re corrupt but they’re effective, then it’s OK. That was the CCP’s model for a long time — graft and corruption are allowed because that’s how you build your patronage network. Don’t get caught. That’s the stakes of the game. But it’s quite clear from the PLA purges that corruption corrupts absolutely, and it will eventually, no matter how effective they were in the first place, it will degrade your readiness.

The Phelan French Kiss

Jordan Schneider: Should we do a Driscoll death-watch check-in now that Phelan’s gone?

Eric Robinson: Let’s do some Kremlinology. We lost the Navy Secretary this week. Long may he rest in his fantastically lucrative art collection and nice collection of poems. He will be fine.

Jordan Schneider: Can we read that just for posterity? I think it’s worth it. Was it a Politico article?

Justin: I think it was the Wall Street Journal.

Eric Robinson: The former Secretary of the Navy had a long-standing personal relationship with the president. He wasn’t a random selection. He is a West Palm Beach resident. He’s a Mar-a-Lago diner. He probably hits the waffle bar on the weekends. He was a bundler. He raised tens of millions for the president’s reelection campaign. He didn’t really have a national security background — he’s an independently wealthy financier.

Jordan Schneider: All right, let me read it from the WSJ.

John Phelan sat in the lobby of the West Wing for more than an hour Wednesday night, waiting to see if his longtime friend and neighbor, President Trump, would save his job. He would leave disappointed. That afternoon, Phelan, the Navy secretary, had received a phone call from his boss, Pete Hegseth, asking for his resignation. Phelan had spent most of Wednesday on Capitol Hill meeting with lawmakers about Navy shipbuilding.

A few miles away at the White House, another gathering was taking place that would decide his fate, according to US officials. Hegseth and his deputy Feinberg had made the argument to Trump that Phelan wasn’t moving quickly enough on Trump’s shipbuilding priorities, especially the Golden Fleet and increasing reliance on US use of steam. The Navy, they determined, needed new leadership.

Phelan made a round of calls, including to the president’s executive assistant, saying he needed to speak with Trump. Phelan then headed to the White House. Once the president had a spare minute Wednesday evening, Phelan asked to keep his job, but the commander in chief backed Hegseth’s decision, according to a senior official.

Eric Robinson: There are some other interesting reveals. The people commenting on the entire saga are saying it was a combined decision between the secretary and Deputy Secretary Feinberg — that we often talk about — and how he’s disciplining things throughout the Pentagon. There are some organizational decisions Deputy Secretary Feinberg made that really undercut the Secretary of the Navy. He captured the submarine program office and put it under his direct supervision. He wasn’t inviting the Navy Secretary to meetings. That strikes me as the death rattle of his tenure.

Ultimately, Stephen Feinberg is sufficiently sophisticated to not promise the Trump battleship — the Defiant class, whatever you’re going to call it. He knows it’s fantasy. He might as well promise an Imperial Star Destroyer; it’s just never going to happen. The level of personal animosity that existed — with Secretary Hegseth firing the chief of staff to the Secretary of the Navy, the personal relationship between the Undersecretary, Hung Cao, and the Secretary — there’s this thicket of interpersonal hostility that boiled over. John Phelan went to Washington without much of a constituency, and I think he found himself without a friend. But he’ll be back in the president’s good graces at a personal level. He didn’t break from the phalanx. He just didn’t really deliver.

Bryan Clark: I’d like to commend Secretary Hegseth for his apt bureaucratic wrangling. Because neither he nor Feinberg like the idea of the Trump battleship. They don’t like the idea of the Golden Fleet. They have certain priorities that they want the Navy to pursue — unmanned systems, submarines, electronic warfare, some other stuff. Those are the things they want to focus on, new technologies that help us better address a more contested environment. And you’ve got the Secretary of the Navy freelancing, pursuing the battleship with the president, and then this new frigate, which is just an effort to make the fleet bigger and spend a bunch of money on shipbuilding. Which is not a bad thing in general.

Driscoll Lives…For Now?

Justin: They promoted him to constituent again — it was good. This is a demonstratively different situation than Driscoll finds himself in. Driscoll and Hegseth seem to have personal animosity for whatever reason — we can speculate.

Eric Robinson: Ranger tab, Ranger tab…

Justin: When you’re an infantry officer. But I don’t know that Secretary Hegseth would be able to create the groundswell for Driscoll, because from everything you can see, Secretary Driscoll and the Deputy Secretary get along and seem to be in lockstep on most things. If I had to guess at who was better at bureaucratic machinations — Secretary Hegseth or Secretary Feinberg — I’d imagine it’s Secretary Feinberg who’s like, no, no, don’t do the public pronouncement thing. Do it this way. I don’t see him offering that same level of support for Secretary Driscoll’s removal.

Tony Stark: Let’s step back and look at the broader political landscape, because that’s part of the differentiation between Driscoll’s position and Phelan’s. Driscoll has an ally in the Vice President — they’re close friends. Driscoll is also known to be effective within the building. He is liked by his own service. On top of the fact that he’s liked on the Hill, he’s liked in the White House. That is substantially different from what SecNav’s position was.

And that matters at a time when you have an already schisming Republican Party, where Driscoll could be one of the fault lines. From a Washington, DC, politics standpoint — the grassroots does not care — but in terms of the various factions in Washington, that is a schism you don’t want to happen, particularly before midterms, especially when most of the party at this point has a 30% approval rating and is looking to what comes next. And it’s very clear that with Vance — I think at 42% — is the most likely candidate for 2028 right now. You don’t want to piss off an ally of Vance if you want to have a future in the Republican Party, at least as it stands right now.

I’m not saying Driscoll is untouchable, because I could say that and in five hours a phone call could happen and he could be gone. But I think he is a lot more protected, both through his own actions and the broader politics of the party, than Phelan was.

Jordan Schneider: How do you square that with all these generals and his chief of staff and random advisors that work for him getting —

Tony Stark: Generals are the domain of the Secretary of Defense. That is how Trump sees it. They’re not his appointees. And you can get away with well, they were Biden generals. I think that is fundamentally it. I also think those firings have caused part of this schism — it’s made it worse. And I think Driscoll is the fault line for something you can’t walk back from.

Justin: When you have Republicans coming out and openly supporting — like Representative Cole coming out and openly supporting Driscoll while excoriating Secretary Hegseth on the decision to fire General George, saying you’re exactly the right person at this time — that’s a strongly worded letter said to the media.

Jordan Schneider: If Hegseth is out in three months, what happens to all these people? Do they just go hang out at Raytheon? Or can we reel them back into the fold? What is the mechanism here? Probably not, right?

Tony Stark: You’re running into two issues. One, people get tired after two years in politics even normally. The Biden administration was a bit of an aberration in that most people stuck around for four years — and some might argue that was part of the problem. Most people look at changeover anyway with a completely open primary on both sides in 2028. You’re going to see a lot of people scrambling to look for a congressional seat, to look at which campaigns they’re going to work on.

The last two years of the admin are going to be people either trying to secure their legacy — because they know they won’t be welcome in Washington for the next 20 years until we have another round of this — or they are actively going to look for their next job. A lot of these people are going to say, eh, I don’t want to go back in. The people that will stick around or bump around — Driscoll might be one of them. He might become SecDef, he might become National Security Advisor. I actually think that might be a better space given his age. At the ASD and DASD level, most of these people are going to try to hold on because there’s nothing out there for them.

Justin: I can’t imagine either of the next administrations are going to be like, we really need a former officer to lead the Department of Defense. I have to think it’s going to be a non — they’re going to go back to the Gates model, where it’s somebody who understands policy.

Eric Robinson: He was a captain once upon a time.

Tony Stark: Junior officers are fine, which is what Secretary Driscoll is. I don’t think you’re going to see another GO. I’ve seen some other names floated.

Jordan Schneider: DeSantis, baby. Let’s go down the list. We got DeSantis, Joni Ernst —

Tony Stark: That’s how you know Pete’s days are numbered, because Trump only floats those names when he is thinking about making a change. He’s not going to pick the Senate — that’s not passing the Senate. This one or the next one.

Eric Robinson: Why don’t you think Governor DeSantis can get through the Senate? Is he personally unpopular?

Tony Stark: He’s not well-liked. There’s probably a world in which if the House flips — and it probably will — that maybe Chairman Rogers gets the tap, which I think most people in DoD would welcome. But it’s more likely to be a personal ally of somebody else, or somebody who wants to be a caretaker for the next two years. Or you might see what happened in the first admin, which is people change out every six months. That’s a pretty likely possibility too. And you’re going to see a lot of people in performing the duties of.

Jordan Schneider: Tom Cotton — another name. But honestly, would you take that for two years?

Tony Stark: Tom Cotton wants to run for president, and that’s the problem.

Justin: The only thing I see with him is, he thinks his time in the halls of Congress is probably over, but he wants to move up to something else.

Tony Stark: I’d also say that if you’re thinking there still might be a GOP admin in 2029 — sure. You don’t want to taint yourself by saying, well, I already held a cabinet position from ‘27 to ‘28, and it was, you know, the great oopsie of 2027 that I was responsible for. A lot of these people who want to work for the DoD — their politics are not necessarily the people that a Vance would have in his administration, given his proclivities toward isolationism.

Bryan Clark: One thing to think about too: as we move into the last two years of this administration, if they lose the House, if they lose the Senate for sure, the president’s wiggle room in terms of things he can do with his time is going to really be constrained domestically. So he’ll pursue more foreign adventures, which means he needs a SecDef that’s going to be willing to go along with those — which means not somebody who’s going to have an independent base of support or an independent perspective on what the DoD or DoW should be doing. Somebody who’s more compliant in the mold of Hegseth, who depends on the president for his position and future.

So it’s likely we’ll get somebody in there who’s willing to go along with most of what the president wants to do for those last two years, which could be on the model of last time, where it was people who were there every six months — because if you know you could be fired that easily, then you’re always going to either go along or bounce, get bounced, and the next guy comes in. I don’t think the president is going to want to continue the foreign adventurism in the face of domestic resistance.

Tony Stark: When Congress flips, it’s going to get so weird. I think that’s the best description for the last years. It’s going to get really weird.

Jordan Schneider: Well, the question is, how much can a Democratic Congress physically restrain the president from invading new countries?

Tony Stark: Nominees are the one control they have. So if he wants to make the swap on Hegseth and he wants somebody, he has to do it now. He can’t do it when the Senate flips even by two seats.

Jordan Schneider: Or you can have a boring person.

Justin: Conceivably. Heritage probably has somebody that they would pick.

Jordan Schneider: What are the odds on the last two years of Trump laying down to just being like normal, boring conservatives? I guess probably zero. So yeah, we’ll just be in an acting world for the end. Anything else to close out on?

Eric Robinson: They might fleet up like Earl Matthews or somebody like that. That’s not going to be normal.

Jordan Schneider: See you next week on WarTalk.

ChinaTalk songs are now up on Spotify!! Follow ‘ChinaTalk Records’ here or have a listen to ‘Phelan on the Couch When It Happens’ below

Caleb Harding is a Mandarin-speaking BYU CS graduate. He previously interned at the US Embassy in Jakarta and Doublethink Lab in Taiwan. He is currently based in D.C. Today,

At its inception in July 2025, China Fusion Energy Co. (CFEC, 中国聚变能源有限公司) was the biggest nuclear fusion company in the world by registered capital.1 Major state-owned enterprises pledged a total of US$2.1 billion in funding, reflecting a serious commitment on the part of these companies — and by extension, the CCP — to making nuclear fusion happen.

This is one of a series of connected announcements and breakthroughs coming out of China in the nuclear fusion space. In January 2025, China’s “Artificial Sun” set a record for maintaining steady-state plasma for over 17 minutes. In March 2025, Shanghai-based startup Energy Singularity announced that their new high-temperature superconducting magnet (necessary for confining the fusion reaction) had generated a magnetic field of 21.7 teslas, breaking a previous record from the US. In May of 2025, researchers at the Chinese Academy of Science Institute of Plasma Physics published the results of their successful 12-year project to develop a new type of steel to use in the reactor core, which can handle magnetic fields almost twice as strong as the steel to be used in the International Thermonuclear Experimental Reactor (ITER) currently under construction. These announcements certainly create the feeling that nuclear fusion is progressing rapidly in China.

The History of Fusion in China

In December 2022, the National Ignition Facility (NIF) at the US Lawrence-Livermore National Laboratory made history by achieving net energy gain on a nuclear fusion reaction. This was a significant step in demonstrating the feasibility of fusion power generation, and led to significant investment in fusion startups in the US. However, for both the US and China, nuclear fusion research began much earlier.

Fusion was first achieved in bombs, marking the shift from “atomic bombs” that relied on fission, to “thermonuclear bombs” that used fission to drive a fusion reaction, releasing significantly more energy. However, controlled fusion has been much more elusive.

The two main “general approaches” (pdf, page 10) currently employed by most labs and companies are magnetic confinement (MCF) and inertial confinement (ICF). MCF uses magnetic fields to contain continuously burning plasma for long periods, while ICF uses intense lasers and small fuel targets to create short fusion bursts. The ICF approach is what the NIF used to achieve their net-energy breakthrough.

Historically, most fusion experiments have focused on tokamaks, stellarators, and laser-driven inertial confinement. Tokamaks have been particularly significant — the International Thermonuclear Experimental Reactor currently under construction in France utilizes this design, as do China’s main research reactors.

The Soviets were the first to operate a tokamak starting in 1958. The US started research with stellarators in 1953, and didn’t operate a tokamak until 1970, after Soviet scientists made promising breakthroughs, and the tokamak came to be viewed as the most likely route to commercial fusion. China’s first large-scale tokamak, HL-1, started operating in the early 1980s at the Southwestern Institute of Physics (SWIP) in Chengdu. (SWIP is affiliated with CNNC, China’s main nuclear energy SOE).

SWIP now operates the HL-2A(M), a more advanced tokamak, one of the three major domestic tokamaks currently operating in China. The two others are the Experimental Advanced Superconducting Tokamak (EAST — aka the “artificial sun”) and J-TEXT. Operational since 2006, EAST is located at the Institute for Plasma Physics, Chinese Academy of Sciences (ASIPP) in Hefei. ASIPP and SWIP are the two main research institutions driving China’s fusion progress. J-TEXT is affiliated with the Huazhong University of Science and Technology (HUST). A number of other universities and institutes also contribute, albeit in a less substantial way.

Despite all the press that these reactors have generated in China, they are not generally considered to be the most advanced within the industry. The “triple product” is a metric that gives a single value for how close a fusion experiment is to net power, found by multiplying the density of ions in the plasma by their temperature and the energy confinement time in seconds. As the annotated graph below illustrates, China’s current tokamaks fall behind global leaders.

The Master Plan

Route 1: Research Institutions

Chinese research institutions have a clear plan and conservative timeline that will get them to a commercial fusion reactor. The foundation of this plan is the three aforementioned tokamaks. With the results of their experiments, China is contributing to developing ITER, and simultaneously planning the China Fusion Engineering Test Reactor (CFETR). CFETR will serve as a bridge between ITER and a full-scale commercial reactor. According to this 2022 timeline, they will have an operational commercial plant by 2060.

However, they are not in a holding pattern while they wait for ITER to come online (which likely won’t be until 2035 or later). The Chinese government has a host of projects planned or currently underway that will continue to fill in fusion knowledge gaps. The following is an overview of some of the key projects:

• Comprehensive Research Facility for Fusion Technology (CRAFT).

  • A 40-hectare, 20-facility, US$570 million research center intended to solve additional obstacles on the way to building CFETR. It does not include a new large-scale tokamak. Construction started in 2019 and should finish this year. It is located in Hefei, near ASIPP.

• Burning Plasma Experimental Superconducting Tokamak (BEST).

  • BEST is an intermediate-step tokamak between EAST and CFETR, designed to achieve real-world energy production. Construction began in 2023 and is expected to conclude in 2027. It has been described as a copy of one designed by US-based Commonwealth Fusion Systems. It is also located in Hefei. I was unable to find an official cost estimate, and unofficial sources varied. One user on Zhihu (Chinese equivalent to Quora) had the cost at $8.5B RMB, ~US$1.2 billion.

• Shenguang-IV (神光-IV (literally “God Light-IV”) or SG4）

  • China is building a massive, mysterious X-shaped facility in Mianyang 绵阳, Sichuan province. Western news outlets don’t even have a name for it. However, China-focused analysts and Chinese media have identified it as Shenguang-IV (SG4), the fourth iteration of laser facilities operated by the China Academy of Engineering Physics (CAEP). CAEP is also China’s principal weapons design lab, and hence, there has been little said about the facility (the NIF plays a similar role in the US). Analysts estimate that SG4 will be similar to the NIF, but 50% larger. Official budget figures are not available, but as a reference point, the NIF cost the US $3.5 billion to construct.

  • Some Chinese sources state that the energy output of SG4’s lasers will be 2 MJ, which is similar to NIF, which has done experiments with 2.2 MJ bursts. It will have 288 lasers, in contrast to NIF’s 192 lasers. According to Chinese forums, construction for SG4 began in 2017, and one article states that it was supposed to be completed in 2020 or shortly thereafter. However, none of this information could be verified.

• Xinghuo 1 (星火一号)

  • World’s first fusion-fission power plant, with Z-FFR design (Z-Pinch Driven Fusion-Fission Reactor). It has the aim of generating 100 MW of continuous electricity for the national grid by 2030. It is being built in Nanchang, and is expected to cost $2.76 billion. The environmental impact assessment began in March 2025, with initial orders of superconducting material for the plant being made in December of 2024.

• China Fusion Engineering Test Reactor (CFETR)

  • A demonstration power plant (DEMO)-scale fusion reactor expected to enter construction by the late 2020s. It is seen as a bridge between ITER and a commercial plant. Preliminary conceptual design for CFETR was finished in 2015, and the engineering design was completed in 2020.

Results from all these projects will be used to continue refining the design of CFETR, before finally being rolled out into wide-scale energy production a few decades from now.

Route 2: Private Sector

Within the global fusion startup space, there are a host of conventional and unconventional methods being tried to realize fusion much sooner than SWIP and ASIPP’s 2060 timeline. That being said, Chinese companies still have a high degree of alignment with state research institutions. While there are 24 different approaches listed in the Fusion Industry Association’s report, the main Chinese players are sticking to the tokamak and the spherical tokamak, a more compact variant which has lower engineering costs.

Different fusion approaches pursued by 45 global fusion companies, based on reporting by the Fusion Industry Association in 2024. Source (pdf)

These players include NeoFusion (聚变新能), Startorus Fusion (星环聚能), Energy Singularity (能量奇点), and ENN (新奥).

• NeoFusion

  • Founded in 2023, Neo Fusion is a private enterprise backed by the Anhui provincial government. It has over $2 billion dollars in funding, just short of SOE China Fusion Energy Co.’s capital.

• Startorus Fusion

  • Startorus is another state-backed private firm, this time with Shaanxi and Xi’an city as sponsors. Founded in 2021 by Tsinghua University grads, it has $207 million in funding. They are pursuing a conventional tokamak design.

• Energy Singularity

  • Founded in 2021, with $120 million in funding. They are operating HH70, the world’s first successful fully high-temperature superconducting (HTS) spherical tokamak. The company overall is pursuing an approach similar to Commonwealth Fusion Systems. They aim to build the next iteration of their HTS design, HH170, by 2027, targeting a 10-fold energy gain.

• ENN

  • ENN is an established gas company that is also pursuing fusion projects. They have raised $400 million thus far, and also intend to use a spherical tokamak.

China Fusion Energy Co.: The Bridge?

The creation of China Fusion Energy Co. this year is intended to coordinate the various parts of the nuclear fusion endeavor, and help it make the important jump from experiment to commercial reality.

In Chinese media, CFEC is referred to as the “national team.” Although it may look like a cash-strapped investment vehicle, its significance goes beyond that. Wang Zhigang (王志刚), a professor at Tsinghua University’s Institute of Nuclear and New Energy Technology, described its significance this way:

“This is not a simple financial investment, but rather part of the national energy strategy layout. The seven major shareholders cover the entire chain of technology R&D, engineering construction, capital operations, and industrial applications, forming an ecosystem of deep integration among ‘industry, academia, research, application, and finance.’”2

Once one of China’s private companies or research institutes makes the final breakthrough, CFEC will be ready to take the baton and sprint with it.

Race Outlook

So, in this race between the US and China, who is in the lead now, and who is likely to win long term?

It’s hard to determine who has the momentary lead. Especially when insiders and experts seem to disagree. The “Artificial Sun’s” record certainly seems impressive. A report from the MIT Technology Review suggests that China commands in 3/6 of the key industries and technologies that will go into fusion reactors (assuming the conventional tokamak is the eventual victor). After leading annual patent submissions on fusion technology for years, China has now surpassed the U.S.

But others suggest that the Artificial Sun’s records are “unremarkable,” and the real indicator of progress is net positive reactions, which China has yet to achieve in the nearly three years since the US first crossed that milestone (and crossed seven more times since). IAEA’s annual Nuclear Fusion Award, given to the most impactful paper published in the Nuclear Fusion journal, has never been given to a Chinese scientist.

Most seem to think that the U.S. and China are roughly tied at the moment. The US is leading China in investment, but only slightly, and the nature of the investment varies substantially. Nimble private funding is dominant in the US, which lacks the kind of national modern fusion facilities that China has, while China’s investment is almost entirely public. Annual public funding between China and the US is roughly 2:1, US$1.5 billion to US$800 million. Which investment model is more effective remains to be seen.

Fusion in the “Engineering State”

Breakneck by Dan Wang has sparked a great deal of discussion and scholarly disagreement about what has made China a building and manufacturing powerhouse, and what holds the US back. Whether it is an “engineering state” vs. a “lawyerly society” (Dan Wang’s theory), a “Leninist developmental state with Chinese characteristics” vs. “lawyerly society” (Jonathan Sine), or “developmental state” vs. “regulatory state” (JS Tan), the fact remains that, at least at the present, China is much better at building stuff.

EVs, solar panels, and high speed rail are often held as examples of America (or Japan, in the case of HSR) winning “0-1” innovation and China winning “1-2” innovation. While it isn’t as widely discussed, another striking example is conventional nuclear fission energy. The US was the world leader in fission technologies, and has the largest fleet of nuclear fission reactors in the world. But China has been on a prolific building spree, and analysts now say that “China likely stands 10 to 15 years ahead of the United States in its ability to deploy fourth-generation nuclear reactors at scale.”

In the case of nuclear fission, perhaps the most succinct explanation of this was offered by Kenneth Luongo, who said that China doesn’t “have any secret sauce other than state financing, state supported supply chain, and a state commitment to build the technology.” More broadly, another author described how private companies in state-supported industries gain access to the “standard triple package of cheap financing, cheap land, and cheap regulatory cost.” Fusion will have all these benefits.

China also has significant “process knowledge” for large infrastructure projects (with their nuclear reactor building spree particularly relevant). They are also developing a deep bench of scientists who will be able to work on fusion projects. Experts estimate that China has thousands of PhD students in fusion, compared with hundreds in the US. Even if the US makes the breakthrough first, China is likely to imitate quickly and roll it out much faster than the US can, gaining additional insights along the way to then pull ahead.

The US Moonshot

Simultaneously comforting and concerning is the knowledge that this isn’t news to US officials and lawmakers, and… little is being done. A Feb 2025 congressional commission report called for a one-time, $10 billion investment to build critical research infrastructure. They argue, and I agree, that “American ingenuity has proven time and again that, particularly when catalyzed by a long-term strategy and public-private partnerships, it can solve seemingly insurmountable problems.” But whether or not the US can really unite the full force of public and private efforts behind anything in these polarized times remains to be seen.

Some notes of what struck me most from the instant classic of a pod.

Are AI chip exports a red herring?

The Trump administration has agency over the two variables most relevant to whether China will have enough compute to really compete with the US: how many chips they can make and how many chips they can buy. But for all the drama we’ve had this administration around whether Trump will allow Jensen to sell chips to China, we’ve had basically zero movement on the tooling side. Without access to foreign tools the US could control, Chinese chip and memory makers would not be in a position to even produce the meager amounts they can today.

This administration teased controls on sub-systems in Trump’s July 2025 AI Action Plan, but absent the headfake around the Affiliates Rule that was wound down after Beijing escalated on rare earths, we’ve had zero movement to close loopholes.

Congress is looking to take the matter into its own hands. The MATCH Act would make controls country-wide as opposed to entity-specific, address servicing of already installed equipment, and squeeze allies to comply by putting a timer on the application of the Foreign Direct Product Rule.

Which layers in Jensen’s layer cake benefit from SME and AI chip exports to China?

Only Nvidia and AMD win from AI chip exports, and nobody in the western ecosystem wins from SME exports except China and SME companies. The table walks through the stack:

The table above illustrates commercial interests only. Widen the frame to include national security, where the Chinese fab industry that can’t exist without US tools is the single most important lever we have, and the case for holding the line on SME gets stronger still.

Beyond fear of retaliation from Jensen when it comes to chip allocation (which Jensen promised didn’t exist on the Dwarkesh podcast!) I am surprised that more of the industry hasn’t been more vocal in their support of Congressional limits to how much Trump can loosen chip controls. Congress acting also makes it less likely for SME escalation to trigger a tit-for-tat on rare earths, as legislation can tie president to the mast and give him the ability to tell Xi, “sorry but there’s nothing I can do on this.”

Real ones ask real questions

Since the October 2022 export controls began, Jensen Huang has been on over fifteen podcasts of over an hour or more. Almost all of those didn’t really raise chips or China.

Most unforgivable was John Hamre of CSIS, a former Deputy Secretary of Defense who runs what is ostensibly a serious national security think tank. He did not do any real homework or ask a direct export controls question, and instead took the time to joke about how dumb he is.

Dr. Hamre: I went in for an MRI recently and my wife said, make sure you take a picture; I don’t think there’s a brain up there, but I’d like to see it – (laughter) – to prove there’s something.

Mr. Huang: And what did you find out? (Laughter.)

Dr. Hamre: We were – there was – there was nothing, I mean. (Laughter.) She was right and I was wrong. (Laughter.)

It took Dwarkesh, who at 25 has not yet served as DepSecDef, to ask America’s most prominent CEO about his most controversial national security policy.1

How did this interview even happen in the first place? My guess is that Dwarkesh cold-emailed Jensen, who said yes, leaving his PR team to watch through their fingers as he gave his first interview to someone who really did their homework and had the guts to bang for twelve rounds. Kudos to Jensen for taking the interview, and after Dwarkesh gave him an off-ramp to say, “You don’t have to move on! I’m enjoying it!” Kobe energy.2

National Security as Jensen’s Willful Blind Spot

Jensen spent decades building a company with zero dual-use implications and practically no reason to interact with Washington. He relied on the world’s most international supply chain which would not exist without the peace that East Asia has been blessed with the past fifty years thanks to unquestioned American military preeminence. While selling chips to gamers and bitcoin miners, he had a lodestar of one day unlocking scientific advancements.3 And now he’s doing that, while also rapidly upgrading the technologies that provide national security without having truly grappled with their implications.

Watching a national security community get in the way of that vision of global empowerment must be infuriating. But wishing away the reality of AI’s dual use implications on cyber by saying that “the way to solve that problem is to have dialogues with the researchers and dialogues with China, and dialogues with all the countries to make sure that people don’t use technology in that way” is willfully naïve. Obama tried to negotiate some cyber boundaries with Xi at Sunnylands, and that truce lasted maybe three months. In recent years, Chinese hackers have been caught inside US power grids, water utilities, ports and pipelines. Dwarkesh is correct in saying that “If you had a cyber hacker, it’s much more dangerous if they have a million of them versus a thousand of them. So that inference compute really matters a lot.”

Jensen’s response to Dwarkesh’s repeated pressing on PLA cyber use ran as follows: “They have plenty of compute already. The amount of threshold they need for the concern you’re worried about, they’ve already reached that threshold and beyond.”4 But Jevons’ paradox applies for the military industrial complex too: demand for compute is skyrocketing across industries because more of it means more productivity.

Jensen also waves off the idea that compute constraints meaningfully slow Chinese labs, but algorithmic innovation itself requires compute. There is nothing special about military organizations or other dual-use technology where past a certain point more compute isn’t useful. And if we’re, as Jensen argues, five years away from “understanding the biological machine,” we’re also five years from some mind-blowing new weaponry.

Is cyber a shiny object?

For all the excitement over the past few weeks around Claude Mythos, there’s a real limit to just how pointy cyber can be. Claude Mythos 3.0 won’t be able to keep the Strait of Hormuz open.

New military technologies and doctrinal innovations are most impactful when first introduced and as adversaries adapt to them over time. As we discussed in last week’s WarTalk, the initial shock of an AI cyber capability like Mythos is real, but the playbook for a response is straightforward: air-gapped and local mesh networks, partitioned internets, and hardwired secure comms. The half-life of a first-mover edge, particularly in software, is short.

None of which is to say AI doesn't matter for warfighting. Beyond cyber, we’ve already seen dramatic impact of AI around targeting and logistics that allowed the US to conduct an unprecedented air campaign over Iran. We’ll soon see similar leaps around command and control. But as Ukraine has reminded the world, you still need lots of stuff that goes boom to feed “the greatest of consumers.”5

We will remain in an era of mass precision, where you still very much do need mass, for a long time to come. Until AI has robots building robot armies, the US will still need to do the foundational work of scaling up its defense industrial base to produce enough attritable mass to deter high end conflict. We should not expect AI capabilities on the next few years to get the Pentagon and Congress off the hot seat to reform and build.

Jensen’s Inner Fire and Lawyers vs Engineers

I claude coded a website that diagrams out their arguments, with different modes including LD-style high school debate and a rap battle (Dwarkesh as Kendrick, Jensen as Jay Z). Dwarkesh would have won on substance and speaker points, with Jensen’s biggest truth-stretching coming around talking about Chinese fab capacity (see this podcast I did with Chris McGuire on why Huawei can’t catch Nvidia). Even though Jensen was playing with the handicap of making his case while dancing around investors, China, and Trump, you should still take him seriously.

’s take (endorsed by Jensen on his Lex interview) is that American society biases too much in favor of lawyerly Ivy League polish and against China’s engineering bias.6 Setting aside the shade I’ve thrown at Jensen for his export control policy, Nvidia is an American company, Jensen has lived the American dream while swimming culturally upstream for decades, and the U.S. is much better off for it.

I want to close with an extended excerpt from twitter account teortaxes:

Jensen is the gangsta poster boy for American Dream. He is REALLY is Not a Loser. He’s also not a Car, but indeed is the driver. Moreover, there are almost no people alive with a greater dynamic range of lived experience, who have gone from positions many would die to escape and into a position entire institutions fight to death over, and only tightened their grip since. Xi Jinping would qualify as a peer, maybe? (Musk has less range, even though he ended up in a similar place.) These individuals are fascinating outliers, and I believe that when they deign to explain their ways, however awkwardly, us mortals should sit our asses down, listen and learn.

Jensen has basically ascended from a toilet-scrubbing immigrant runt to a demigod, from a random NPC to a Singularity Kingmaker, a whole vertebra of the Universe’s backbone; and that journey informs his views, just like Dwarkesh’s “be really good at Reasonably Conversing, insure your middle class stake” informs his. Jensen’s journey is not about luck, he is definitely not “1 SD IQ lower”. He hasn’t trained himself in our exact mode of coffee salon intelligence that allows for casually cooking up consistent, defensible, lawyerly arguments about, basically, the structure of written information. So he’s worse than us at it. Not because his epistemology is inferior, as in «less predictive»; it is just different, and insistence on Not Being a Loser is its functional part. He is supremely motivated to Not Lose, so he’ll not make self-defeating moves. How he sorts moves into self-strengthening and self-defeating is, therefore, very important, more than verbally persuasive arguments.

What exactly is quantum computing? Why does it matter, and what would it actually mean to “win” the quantum race? Zach Yerushalmi, CEO of Elevate Quantum, a Mountain West–based public-private consortium advancing the U.S. quantum ecosystem, and Chris Miller join the podcast to discuss.

Our conversation covers…

• What Quantum Computing Actually Is — A primer on qubits, superposition, and why quantum computers aren’t “faster classical machines” but fundamentally different systems designed to simulate nature and solve specific classes of problems.

• Why Quantum Matters Now — Breakthroughs in error correction and hardware have shifted quantum from theory to an engineering race, with major implications for drug discovery, materials science, artificial intelligence, and cybersecurity.

• The Economic and National Security Stakes — Quantum’s potential impact on cryptography, advanced manufacturing, biotech, and defense makes it a strategic technology with an extremely small margin for error in global competition.

• From Science Project to Industrial Policy Challenge — The bottleneck is no longer just physics but scaling. Talent pipelines, fabrication capacity, supply chains, and the kinds of public-private partnerships needed to move from lab prototypes to deployable systems.

• What Winning Looks Like — Leadership isn’t just building the first powerful machine. It’s shaping standards, securing supply chains, protecting encryption, diffusing capabilities across industry, and sustaining innovation in a tight U.S.–China technological race.

Plus, the encryption stakes, the engineering bottlenecks, the race with China — and a reading list and job resources for those interested in the field.

Thanks to the Hudson Institute for sponsoring this episode.

Why Quantum Matters Now

Jordan Schneider: All right, Quantum 101. Why should ChinaTalk listeners turn their attention to this topic?

Zachary Yerushalmi: Listeners should care about quantum because, with AI on our doorstep, quantum represents the single biggest lever we have to pull as a society for the next couple of decades.

For the ChinaTalk audience specifically, this isn’t just a big economic and national security opportunity. For such a policy-oriented group, the margin of error is incredibly thin. We have more at stake here than any industrial program since the atomic bomb. It’s multi-layered — maybe that’s quantum for you. But that’s why I think folks should care.

Jordan Schneider: What do you mean by margin of error?

Zachary Yerushalmi: You’ve all spent a lot of time thinking about semiconductors. My observation is that in semiconductors, we have literally decades of moat over China and other competitors that we care about. That doesn’t mean we sleep on semiconductors or forget industrial policy there.

But quantum is fundamentally new for many of the capabilities we’re trying to bring forward. By definition, that means our moat is pretty small. Whereas in semiconductors we can get some things right and some things wrong, in quantum, our margin of error is freakishly small. We have to get it right from the beginning.

Jordan Schneider: All right. Make the case for why it matters. Why is this the thing that could be the next door for humanity to open over the next half-century?

Zachary Yerushalmi: It’s the single biggest lever we have left now that AI is on the doorstep and/or here. Why it’s so important goes back to the inception of the idea of a quantum computer. It came in 1981 from this guy Richard Feynman. He has this famous quote of effectively “nature’s quantum, dammit.”

It’s the realization that if we want to solve the problems that quantum mechanics governs, which are really the world of the atomic realm — not Marvel, but the very small, the very cold — this includes drug discovery, catalysts, material science. This is all the things that govern the building blocks of the universe. We can’t use our classical approach and classical computers to solve that.

This gets a little bit into the math and could get dangerous, but the quantum world behaves in ways where even very small systems explode in complexity. A standard two-particle system — these systems explode at 2 to the n. If you have a two-atom system, that’s 2 to the n states that you need to understand. If you add a third atom to that, it’s 2 to the third. You suddenly need to understand 8 states, not 1 additional. By the time you get to 20-atom systems, you need to understand a million states. A 20-atom system is freakishly small.

This gets back to why this matters. Let’s use the specific example of penicillin. Penicillin is 42 atoms. That is not a big molecular system, but penicillin is obviously pretty important. If we want to understand penicillin, much less where it falls short, then in order to do that classically using our current computing paradigm, even with the world’s best AI, we’d have to use something like 10^86 transistors to do it.

Just to double-click on that — I said 10^86 quickly — it’s a shockingly large number. 10^86 would need more transistors than there are atoms in the observable universe. In simple terms, we could literally use the energy of the entire universe, and we couldn’t quite make a basic physics-based model for penicillin.

If we ever talk about living in the Jetsons age, rationally designing all these things, our current paradigm, even with the world’s best AI, is just never going to get there.

This gets back to that quote from Feynman in ’81. He just went on this rant, and it was really a thought experiment. He said nature is quantum mechanical, damn it. What if we’re just approaching this on the wrong terms? What if we built a computer that operated on the same principles as penicillin operates itself? It’d probably be more efficient.

It wasn’t just a little more efficient. It was a reinvention of what a computer could be. Instead of needing more transistors than there are atoms in the observable universe, you need something like 186 of these quantum bits, or qubits. We’re not there yet, but we’re more or less on the cusp of it.

If you can do that — again, because these systems are exponential in nature — when you go from 186 qubits to understand penicillin to 187, just one additional system, it’s not a little bit better computer. It is thinking about penicillin interacting with its neighbor. When you get to 1,000-qubit systems, you’re talking about rational design of much more complex systems.

If we ever want to get to what folks talk about from the AI world of curing cancer, solving climate change, addressing the material science of the world all around us, actually, really the only cowbell that we can really hit on for some of those problems is quantum.

Chris Miller: Could I ask maybe the same question from an economics perspective, which is thinking about the market for quantum computing capabilities? It’s an unfair question to ask because if you’d asked people at OpenAI in 2019 what the market for AI was, they would have given you a very large number without much justification — because who knew exactly how it would play out. But how do you think about where we’d like to be deploying quantum computing capabilities in 2035? Drug discovery is obviously the first answer everyone gives, and that’s obviously a potentially huge market. But beyond that, how do we think about the economic impact of quantum computing?

Zachary Yerushalmi: There are two applications that folks go to. The analogy I think about is — Chris, you cover this so well in your book — one of the really first killer apps of the semiconductor era was the hearing aid or transistor. All of this is like forecasting the impact of this technology with a transistor set of examples for what is possible.

But the interesting thing about quantum is that the transistor capabilities are worth hundreds of billions to trillions of dollars.

A couple of applications — the first would actually maybe not even be life sciences. It would be something around corrosion and accurate corrosion modeling, which is worth tens of billions of dollars to the global shipping and national security sector. That’s because it’s a simpler problem and is tractable to get around. There are some interesting things around nuclear chemistry. As these systems get bigger, you start to look at drug discovery and material science.

Folks talk a lot about room-temperature superconductors, which is a whole other YouTube wormhole to get into. But if we want cell phone batteries that never lose power, the ability to rationally design these systems at the molecular level, at the atomic level, opens up that possibility.

The second class of problems from an economic impact perspective is, candidly, in many ways, maybe more near-term and more scary. It gets back to the transistor analogy. Most of the classical algorithms we developed occurred after we had the computer. The only other big class of problems that folks know quantum computers are useful for, aside from the molecular modeling piece or the physics modeling piece, is that they’re really good at the hidden subgroup problem, which sounds jargony because it is jargony.

The big one there is factoring large primes. For anybody aware of cybersecurity concerns, if you can factor large primes, you basically crack the code that underpins all of our existing cybersecurity infrastructure. This is why global governments, even putting aside the Jetsons nature of what we can unlock, are really worried — because all of their codes and all of our financial infrastructure and things like Bitcoin are underpinned by this problem that a classical computer literally takes the age of the universe to solve, and a quantum computer looks at, laughs at, and steals your Bitcoin wallet.

Understanding Quantum

Jordan Schneider: Before we go too deep into applications, Zach, what’s your favorite analogy to give folks to start wrapping their head around?

Zachary Yerushalmi: Two analogies that come to mind. The analogy I often think about is this — if classical computers are like a car, quantum computers are like a rocket ship. We’ll still use classical computers, just as we still use cars for certain applications. But for certain problems, a faster car isn’t going to get you to space more efficiently. You need to completely rethink your mode of transportation.

With quantum computing, because of the nature of the problem set, we need to invent the equivalent of a spaceship. The idea is to create a computer that operates on the same principles as the systems we want to solve.

How do these computers actually work? The best analogy I’ve seen is the maze analogy by Matt Langione, who’s the quantum partner at BCG.

Picture a maze in your mind. The way humans approach a maze is actually quite similar to how classical computers do it. You walk in, face a decision to go left or right, choose right, hit a wall, and then backtrack. The time it takes to solve the maze is the cumulative time of making each decision and working through the maze sequentially.

A quantum computer approaches a maze fundamentally differently. When a quantum computer enters the maze and faces that first decision to go left or right, it leverages principles of superposition, entanglement, and interference to say “yes” to both paths. It explores both simultaneously. Not just at that single junction — it examines every single junction in the maze and explores all possible paths in parallel.

While a classical computer takes time to make each decision sequentially, accumulating time with each choice, a quantum computer evaluates the first junction and every other junction simultaneously.

The real-world applications that resemble this maze structure are found in the molecular world, worth hundreds of billions to trillions of dollars. Whether in chemistry or molecular science design, these fields share many similar characteristics with the maze problem I just described.

Jordan Schneider: I want to make a pitch based on the background reading syllabus that Zach sent Chris and me, which we’ll put in the show notes. There’s a YouTube video by 3Blue1Brown called “But what is quantum computing?” which I confess I had to watch probably three and a half times before it started to settle in.

One of the interesting things about this topic is how quickly you try to make analogies of left/right or two-dimensional space, and then they give you three-dimensional space. But all the exemplars are actually 16 dimensions, 20 dimensions, and when they show the equations, it actually makes more sense than when they try to give you the analogies.

Whenever these folks try to make it simpler by giving you some spatial analogy for what’s happening, I found myself going back to the parts of the YouTube video and the Wikipedia pages that just had equations in them. You don’t have to expand your mind like you’re some enlightened Tibetan Buddha or something — you can just take it for granted that these equations are what all of the particles are doing or not doing.

It was fun to stretch my mind in a way I haven’t in a while. I contrast that with earlier today when I was listening to some World War II fighter history where the physics was straightforward — the plane’s going this fast, the other plane’s going this fast. They invented a little computer that did some straightforward calculations to shoot 50 yards ahead so that it would hit your Messerschmitt or what have you. And here I am with Zach going down the deepest rabbit holes of the universe.

But Zach, make the case for people spending that long weekend actually trying to wrap their heads around some of the physics fundamentals of this, as opposed to just jumping to thinking about all the cool applications.

Zachary Yerushalmi: First, it’s just cool. If you’re into listening to Neil deGrasse Tyson and StarTalk, why not make a little bit of time for quantum?

But the second, I think, is separating hype from reality. If the case for quantum from an economic and national security perspective is that important, having a base intuitive understanding of what a quantum computer does, what it doesn’t do, and where it’s useful is essential for ChinaTalk listeners because a lot of them are engaged on policy — prioritizing where we make investments to actually have that lead.

This is true of any discipline — there can be a lot of smoke and mirrors and hype and reality. But in quantum, almost because it is such a hard thing to grapple with, I find more of that. So I think that investment is super worthwhile.

Chris, I welcome your take. Where was that sea change? What was the ROI calculation there for yourself?

Chris Miller: To me, every next step in computing capabilities seems magical or impossible 15 years out, then it becomes possible and normal, and then we forget that it’s happening. My analogy for where we are today vis-à-vis quantum is that it’s like 2015 in AI. All the researchers were saying progress is coming very rapidly, and everyone outside of AI said, “I don’t know what this means, and it’s probably not real. Even if it’s real, it’s a long way away, so I’m going to ignore it.”

Then the world was surprised in 2022 when ChatGPT dropped in a big way. It seems to me that a roughly comparable time horizon is where most quantum researchers think we’re going to be — in half a decade or so.

Zachary Yerushalmi: Taking the AI analogy, if you got attuned to AI as a government, as an investor, or as a policymaker when ChatGPT hit, it was too late. The time to really be attuned to it was probably around 2017 — “Attention Is All You Need,” the birth of the LLM.

What was wild about quantum last year in 2025, is that the ChatGPT moment isn’t there. It was not there last year. What I’d argue, though, is it was the birth of the LLM for the industry. That’s because with the Google Willow paper that came out and a couple of other breakthroughs from others, it went from a technology domain where, as I alluded to before, for these things to be useful, you have to add a certain number of these qubits.

It turned out that up until last year, every time you added a qubit, the entire system got less stable, which is probably bad news from a “these things are going to be useful” perspective. Where that sea change happened — this came out with Google’s paper — was when they found out a way through error correction, where you added a quantum bit, and the entire system got more stable.

In my head, that’s a shift. With that base architecture, it becomes more of a “when do these capabilities come online in a way that changes the world around us” instead of an “if.” It just reinforces why it would be attuned now, because we can’t afford to wait until ChatGPT hits.

Jordan Schneider: That’s another argument for actually spending the time to understand the fundamentals here. Reading the results of all those AI papers, even for someone who isn’t a computer science PhD, has been relatively straightforward. Certain benchmarks are legible to human beings, like labeling images, or you can talk to the models and feel how good they are.

That is something that even a layperson has been able to follow without really understanding the transformer architecture or what have you. In order to separate hype from reality, when Microsoft or IBM or Google comes out with a paper, it requires being able to digest more secondary technical commentary than just, “Oh yeah, try the model out for yourselves.”

It’s not like we all have quantum computers in our backyard that we’re trying to model penicillin with, and all of a sudden it’ll work. But maybe we’ll get there one day.

How Policy Should Change

Jordan Schneider: Let’s stay on the industry history piece, Zach. If 2025 is our turning point, where were we before? Where was 2014 to 2024?

Zachary Yerushalmi: Quantum computers started as a thought experiment in 1981. The entire industry was born in that moment when Feynman said, “Let’s build something on nature’s own terms.” The first 2-qubit gate operation was an important breakthrough that actually happened in Colorado as a kind of unitized thing for how you would create a quantum processing unit.

We’ve had not just steady but exponential progress in the capability of these systems since that time. The quantum supremacy paper came through with Google in 2019. Then last year, we had a sea change where the focus shifted from the more fundamental side of R&D to engineering these systems to a sufficient scale.

These problems that keep the NSA up at night and the rest of us dreaming from a new capability perspective are really on the cusp. If we look at industry timelines, even a couple of years ago, folks would have said that a useful quantum computer is about 10 years out. Last year, it went from 10+ years out to 3 to 5 years. With these breakthroughs, folks think we’ll get systems capable of cryptographic capabilities that we’re candidly worried about, or material science capabilities that open up new economic opportunities.

Chris Miller: It’s happening fast. I agree that we’ve shifted from the realm of science experiment to the realm of engineering. The question that brings up is: how should policy change?

For fundamental research, you support academics, and they do their studies and push the frontier of knowledge in physics and other fields. But for engineering, you need different tools for different problems. Scaling up is as much an economic problem as it is an engineering problem. Can you walk us through how you think the types of policies that we should think about in the quantum sphere ought to be changing, given the shift from solving the science, which we’ve made a lot of progress on, to addressing the engineering, which is where we are right now?

Zachary Yerushalmi: First, if we use computing history as a lesson, you can’t just put down the fundamental R&D. If we went from the computing age to vacuum tubes and put our tools down and said “job’s done,” we would have missed out on the transistor. That engine of growth and innovation — thinking about what the next generation is and maybe even a reinvention of what people are thinking from a basic architecture — is essential.

Second, how do we look at the industry now that there’s this sea change? The mental model I always use for quantum is biotech. In biotech, you have drugs — maybe small molecules, or you have CAR-T or these different modalities. You have that for quantum itself. Those are the things that will cure cancer. You also have the tools for addressing that.

As we cross into this chasm right now, what I would think about from a policy lens is that we’ve entered phase 1 clinical trials. What we need to do from a policymaker perspective actually looks like a similar toolset to how we foster the right environment for biotech.

The important distinction though, is that in biotech, we have a huge moat. The cluster, both commercial and scientific, around Boston is so globally dominant that we can screw up a bunch of stuff. Now it’s about what tools we need, given the same architecture — material technical risk, need for commercial payout, and so on. But now we need to do that with a much earlier stage industry.

Jordan Schneider: Let’s do a little bit of industry analysis, because there are some very shiny, polished releases from some of America’s largest publicly listed companies. You’ve got startups doing things, government labs, and academia. Let’s start with the giant companies. Is this just like everyone wants to be Bell Labs? Why are Microsoft and Google spending time on this sort of thing? They’ve got data centers to build with their CapEx, right?

Zachary Yerushalmi: There are weird R&D tax incentives in the state of California that we won’t get into. Why do they have to focus on this? It gets back to the fact that they can’t afford strategic surprise, right?

Your comment about this being such an important thing — them spending a couple of billion dollars on it a year to make sure they have their finger on the pulse so there’s not a Sputnik moment for them as a company — is just worth the ROI. Ultimately, they have big quantum programs, arguably some of the largest, but relative to everything else they’re doing, it’s rounding errors on their balance sheet.

I’d argue the same about the US government. DARPA, indicative of how important this is, has made quantum its largest public program in the agency’s history. It’s called the Quantum Benchmarking Initiative. This almost gets to your question, Chris, about now that we’re in this new era, what are the policy levers that we need to undertake to get this right?

That’s canonical. It all comes back to what are the right commercial structures — because commercial structuring is what makes biotech motor on — and then what are the right technical levers that you need?

Chris Miller: Do you want to explain what DARPA’s Quantum Benchmarking Initiative actually is? Because it actually seems to me exactly like the clinical trial analogy that you just mentioned. Can you dig into that?

Zachary Yerushalmi: The Quantum Benchmarking Initiative, as I alluded to, is the largest public program in the agency’s history. This year alone, they’re looking to spend $600 million on it.

The frame there is — they don’t say this explicitly — but the US government can’t afford to be surprised that China can break its codes. They stood up this program that is effectively about learning about the capabilities of the leading players in the world, sans China, because China’s not going to talk to the US government about its quantum capabilities.

The model that it took to do that — and huge respect for the team there — actually reconstructed an advanced market commitment like what you see in drug discovery, but applied that to quantum. It’s effectively like a grand challenge prize structure.

The first phase, you get a little bit of money — $1 million here or there. It’s really just a table stakes thing. The next phase is $15 to $20 million if you pass a certain scientific threshold. But things really get going by the third phase of the program where you can get paid $300 million if your system is deemed credible to that stage and you build a demonstration-scale capability for it.

The implied thing is after that — once you get through that third phase of DARPA — it’s kind of your FDA approval. Some government agency is going to buy one of these things because it’s good. It’s going to investigate parts of the cryptographic world that they would be very interested in.

If we get back to that frame, those payouts map really well to the different sorts of commercial staging you’d see in biotech. The $300 million prize is like some Phase 1 or 2 stage, and then a billion-dollar prize if you get past that. That’s super important, not just because these companies want to earn money, but because if you want a virtuous cycle going, you need to get the venture investors and the private markets excited. Those payouts are big enough to create the incentive.

Jordan Schneider: Let’s go to startups. Why do they exist? Are they real yet? What are they doing when it comes to funding?

Zachary Yerushalmi: Startups exist here just like startups exist in biotech, right? Big companies — IBM is putting billions of dollars into this thing. IBM has the flagship program in quantum. But big companies face limitations. They can do a lot of innovating and have important programs and distribution. But just like Novo Nordisk doesn’t do all of the innovation in the world around discovering and developing drugs, you also need early-stage players disproportionately coming from academia that are bringing new paradigms that could disrupt what’s happening in this technology space.

The innovation in this market is like what you see in biotech. You get the big tech players driving programs with amazing access to supercomputers, but some newer-stage programs and approaches could be incredibly disruptive. Those are typically pioneered by startups. If those really take off, then typically the big tech players swoop in and either make an investment or buy them out. We’ve seen that in quantum.

There are a couple of approaches in quantum computing — call them modalities. The historic one is called superconducting qubits. This is the solid-state approach for which John Martinis won the Nobel Prize recently. That’s gotten 60 to 80% of the investment to date for the industry.

But there are newer approaches. The most prominent are probably neutral atoms. Instead of using an almost synthetic quantum bit, they use atoms themselves as the qubit. This was considered science fiction literally three, four, or five years ago. People thought this idea was a total joke.

A bunch of startups, as you see everywhere else in the world, grabbed the mantle and said, “No, I did my postdoc on this. This is not a total joke,” and ran with it. There was a sea change probably two or three years ago, and it’s now one of the leading approaches. Nobody would have bet on that so short a time back. Now it’s one of the things that could really have a shot.

A marker of this is Google. They pioneered and continue to push forward with superconducting as their core approach. But they’re so worried about and interested in neutral atoms, they just gave QuEra $250 million because they think that approach could work as well.

That’s the role that startups can play. It’s the classic disruptive innovation — driving forward what folks thought couldn’t be possible because the risk-reward wouldn’t make sense for an existing company.

What Does “Winning” Mean?

Jordan Schneider: Now it’s time for a little Elevate detour. Why don’t you tell the folks out there what you do all day, Zach?

Zachary Yerushalmi: Elevate is the US government’s quantum tech hub. We’re the first and only major place-based investment that the US government has made in the quantum industry. They did that ultimately because the Mountain West cluster is the largest quantum cluster on the planet. It represents almost half of the US quantum jobs and half of the deployed capital. It’s massive by quantum standards — small industry, but still massive by quantum standards.

What I do, and this relates to the policy measures I’d be keen on discussing, is work toward our mission to dramatically accelerate the commercialization of quantum. We do that as a public-private partnership. Our work focuses on specific, typically technical bottlenecks that are market failures that other players aren’t well-placed to solve.

We look at things like fabs, packaging, and certain shared-use equipment that, for various reasons, national labs and universities aren’t well-placed to address. Startups might not have the capital, expertise, or time to solve these issues either. That’s ultimately what Elevate addresses. We have 140 to 150 members in our consortium, including all the usual suspects — national labs and universities in the Mountain West — but also every big tech player with a quantum program. That’s what we dive in to solve with lots of partners.

Chris Miller: Zach, we’re in this quantum race, and China is a major competitor. What does winning actually look like?

Zachary Yerushalmi: In my view, it’s getting there first and maintaining the best capability as a nation long into the future. Getting there first means building the first — folks will throw out the word “fault-tolerant,” but think of it as a commercially useful system. Something that drives commercial value, whether through cryptographic use cases, material science use cases, or other applications. This is like building the first useful computer with vacuum tubes.

The second part is continuing to have the best capability in the world, or really, access to that capability. That’s what winning means to me. The tricky part is identifying the lead indicator. We can’t look at the price for that. The challenge I’m trying to figure out is — in the absence of price, what’s the lead indicator for us winning?

Chris Miller: When we get to our first commercially useful quantum computer at scale.

Do you think there will be one company that dominates the market like NVIDIA, or should we expect multiple different paradigms to be relevant, perhaps for different applications where they’re better or worse suited?

Zachary Yerushalmi: People smarter than I am suspect that, at least for the foreseeable future, we’re going to have pretty purpose-built machines. This comes from the previous computing era, where you had purpose-built machines based on the application. My instinct is that’s what this is going to look like.

That may at some point converge on a transistor-like architecture for quantum — something that everybody converges on and uses. But we’re not there yet. As a system, and this relates to what I was talking about earlier with the car versus rocket ship analogy, most experts suspect quantum will play a specific role in computing.

Chris, you talk about this as the three-paradigm model for computing. You have classical CPUs — those will stay useful. You have GPUs for AI-accelerated compute — those will stay useful for a certain set of problems. But then you’re also going to have quantum processing units. These will work in tandem to solve some of the biggest problems we care about from a science and cryptography perspective.

Chris Miller: That’s something that a lot of people who are new to the field don’t understand. There’s a common assumption that quantum will replace classical, which is obviously not the right way to look at it at all.

Zachary Yerushalmi: Just like GPUs didn’t replace CPUs, these are Turing-complete machines. They technically can do all the computation; they just won’t be efficient at many of the problems you’d want to computationally solve.

Jordan Schneider: One of the remarkable things about AI is how quickly the learnings at the frontier diffuse to firms trying to catch up. We’re recording this on February 23rd, and we just had an interesting story come out today. Anthropic reported that DeepSeek, Dripu, and Minimax were all making millions of queries to try to get data they could then feed into their models.

There’s this whole narrative about how if you go to enough parties in San Francisco, you’ll hear about the cool new training techniques that you can bring back to your own lab. To what extent do you see frontier breakthroughs leaking out to other firms trying to do the same thing? And spilling across borders as well?

Zachary Yerushalmi: That aspect of quantum is still driven by academic researchers in a big way, so publication remains important in quantum. Just like you see publications thrown on arXiv and then diffuse, that very much happens in this industry.

There’s an interesting caveat, though — and this is mainly received wisdom — that the Chinese government actually keeps publications on lockdown. They typically wait for a breakthrough from one of the firms in the West, and then they’ll allow their researchers to publish something similar. This isn’t the kind of hackneyed stereotype about Chinese innovation that people sometimes deploy. That’s not the right mental model here.

The big difference with AI is that quantum is very much a hardware sport. This means iteration times are much longer. A lot of that diffusion is received wisdom and deep knowledge about how to fix optics to a breadboard and how these systems behave in different ways. It’s a very different science from that domain of zeros and ones.

Jordan Schneider: Which presumably would make the learning more frictionful across firms and involve a lot more people.

Chris Miller: Maybe the analogy is that in AI, the algorithms diffuse rapidly, but the know-how about producing the chips hasn’t. Perhaps the analogy is the same — that the algorithm layer, the software layer, and the research layer might diffuse rapidly, but the manufacturing know-how doesn’t.

Zachary Yerushalmi: Totally. And it’s at a much earlier stage. Each of these paradigms doesn’t have something like the transistor that you can base all your understanding on. Each way of building a quantum computer has deep expertise built around it.

But again, everything is double-edged. Because of the earlier-stage nature of the field, if there’s a real breakthrough in China around a particular domain, it’s going to be much harder to transmit that knowledge over to the US. That moat is just much stickier.

The Encryption Cliff

Chris Miller: One of the obvious uses of quantum computing that we’ve known about for a long time is breaking encryption. Now we’ve got post-quantum encryption standards that have been released by NIST, although it’s unclear how widely or rapidly they’re actually being deployed — probably not rapidly enough. Walk us through how you see us reaching a point in which all of our 2010-era encryption is easily broken by a quantum computer.

Zachary Yerushalmi: It’s pretty scary because NIST recommends all government systems be upgraded by 2028 or 2029, and consumer systems by 2035. That recommendation came out early last year. By the end of last year, folks were talking about having these systems online that can break these standards in 3 to 5 years from then — so by 2030.

That freaks me out because typically you want 10 to 15 years as an upgrade cycle for traditional security protocols, and we have 3 to 5.

Why these systems can do that is through this algorithm discovered by Peter Shor. It had nothing to do with the original idea behind a quantum computer. They are good at the hidden subgroup problem, and there are two prominent techniques of the hidden subgroup problem that classical computers struggle with, which is why they’re used as a basis for all these encryption standards.

One is factoring large primes. If you have 15 out there exposed as a public key, through a weird fact of math, it takes a normal computer a really long time to figure out that you could break that into 3 and 5. The bigger that number gets, the longer that computer takes.

The other one is elliptic curve cryptography, which is actually a similar problem, but with really cool math. It sounds like what it is — basically using elliptic curves as a way to find a hidden subgroup. That’s the basis for a lot of other types of cryptography, including helping secure the signature for Bitcoin.

A normal computer looks at these things and has a really hard time — age of the universe hard — to break them down and understand them. Whereas a quantum computer, because it has this exponential speedup, on a 3 to 5 year timeline, would be able to solve that hidden subgroup problem and break the cryptographic standards that we have.

What worries me isn’t just that we have a wildly short time to move to a new cryptographic standard. It’s that lattice-based encryption — which is the standard that NIST says we should move to. While the theory behind it is very good, and folks think a quantum computer would have a really hard time addressing those encryption standards, the implementation is really not mature.

We have to move faster than we ever have to a new encryption standard, but the one we’re moving to hasn’t been deployed at any real scale. You put those two things together, and it’s something I worry about. That’s something a lot of people worry about.

Chris Miller: On the encryption part, the thing I haven’t fully thought through is that for AI, there’s this AI race, but the fruits of it are kind of far out — it’s productivity enhancements. Whereas for decryption, the fruits are immediate if you get there.

How do governments in both the US and China think about this? If we’re six months away from breaking encryption — we’re never going to be six months away from the fruits of AI because it’ll always be constantly bearing fruit. But if you’re six months away from decryption, at what point do you just say all quantum computing resources must be devoted to this task, Defense Production Act style? It seems highly plausible China would do that. And it seems possible we’d do that too if those were the stakes.

There’s interesting game theory around that dynamic. “Bomb the data centers” was the not serious — or maybe some people thought it was serious — meme from 2022 or 2023 about what if AI gets out of control. But it starts to become a little bit more plausible in the quantum space if the stakes are that all cybersecurity disappears.

Jordan Schneider: Well, it seems harder to bomb a quantum computer though, right?

Chris Miller: Because it’s just one room you can put anywhere. And the know-how presumably continues even if you destroy the physical device.

Zachary Yerushalmi: I’m trying to figure out — there’s stuff around nuclear chemistry, which is really scary for quantum computers. It’s one of the many reasons that folks care about them. And again, none of this is on the high side. Do you think it’s that different from “we’re six months out from AGI”?

Chris Miller: Well, if you think that AGI is a threshold where before you have nothing and afterwards you have superintelligence, then the game theory is similar. But I don’t think we really believe that there’s an AGI threshold that has a dramatic before and after relative to an ongoing gradient where you get better and better capabilities with more and more productivity.

For most economic applications of quantum, it looks like — I don’t know if steady is the right word, but a trend over time. But decryption is this threshold dynamic where if you’re on the wrong side of it, the stakes are high.

Zachary Yerushalmi: The one thing I would say there — yes, absolutely. Stakes are super high. Global Western governments committed something like $23 billion to quantum in the last three years. I’m sure they’re really excited about molecular modeling, but they’re probably mostly really scared about the encryption side of it.

The one thing I would call out is that the first computer that gets there is not going to be very efficient at breaking those codes. It could literally, depending on the architecture, take a month or many months to break one code. Which means you have to choose your bullets very assiduously. That’s depending on the architecture. But I do think it is a little bit more akin to your AI model — just because you got there doesn’t mean that there’s more juice to squeeze.

Chris Miller: But isn’t the first code that you break the Chinese nuclear codes? That’s a pretty high-value code. There are some pretty high-value codes you could break right away and justify thinking about it as pretty important. I don’t know anything about the Chinese nuclear system, but that seems like exactly where one would go if one was going to think about the high-value code.

Zachary Yerushalmi: There are people with clearances far above my pay grade who probably know the concentration levels of Chinese high-value code. I don’t have a good sense of that.

What worries me most about quantum computers, aside from codebreaking, is their recursive nature and how they improve existing material science applications. Take high-temperature superconductors or nuclear chemistry, for example. If you had a system that could rationally design superconductors or chemical compounds, you would use that capability to lock down IP space and know-how in a way that blocks out adversaries and competitors.

From a moat perspective, it’s not just about building the system — it’s about securing the inventions that the system creates. AI is essentially sophisticated curve fitting, like stabbing in the dark. Quantum computers are fundamentally different. They’re not guessing — they solve problems from first principles and lock in on the correct solution. When I think about silent, mushroom cloud-level implications, that’s where my mind goes — it gets a bit scary.

The Bottlenecks: Talent and Time

Jordan Schneider: Let’s talk about that computer. It won’t be an engineering challenge like the Manhattan Project that costs 100 times more than any previous project, will it? Is it more likely to be an engineering breakthrough, or can you brute force your way to a useful quantum computer with enough money — one that could actually break nuclear codes?

Zachary Yerushalmi: Honestly, especially now that we’ve crossed the threshold where every additional qubit makes the system more powerful, you can just throw money at the problem. You’d build a wildly inefficient, expensive computer, but it could break RSA encryption a few times, which would be catastrophic.

How you spend the money is crucial. You could spend a trillion dollars on quantum computing, but the bottleneck is talent. You need humans to wire the refrigerators and set up the optics tables required to operate these systems. The prioritization of spending is everything. You could throw money at this problem all day, but without the right allocation, you’d overfeed the system and still fail to achieve your goals.

Chris Miller: It’s like AI — talent is the problem. Meta’s offering $100 million salaries for quantum researchers.

Zachary Yerushalmi: Talent is critical, but if I were to create a metric to track progress, I’d focus on iteration loops or cycle times. There’s the commercial cycle time — how long it takes to sell a company for significant returns. That’s important because it excites venture investors and attracts talented startup founders.

Then there’s the technology cycle time — how long it takes to go from idea to widget to product and test it in a relevant environment. Many bottlenecks exist here. While talent can be a constraint, access to technical services and capabilities often poses bigger challenges. These include superconducting fabrication facilities, specialized III-V semiconductor fabs, and scaled cryogenics systems. The bottleneck isn’t necessarily talent — it’s having the right policy framework to enable access to these resources.

Chris Miller: This gets back to the discussion of whether we’ve moved from a science phase to an engineering phase — not discounting the future science that has to happen — but do we have the right institutions for that scale-up? In the semiconductor space, there is agreement that it’s gotten way too hard and expensive to take an idea and translate it into a prototype. Prototyping is expensive, and you need exquisite equipment, materials, and so on. The same is basically true in the quantum space. Going from idea to prototype is hard because prototyping is expensive and needs this unique toolset. Talk to us about what has happened and what else needs to happen to facilitate that scale-up process.

Zachary Yerushalmi: It’s a good question — it was actually something I was chatting with Constanza about regarding her quantum supply chain paper. The short answer is we have the cards that we have in terms of the institutions in the US and the Western world. You have fundamental research, and we should be thoughtful about the things we incentivize with that. You have the free market and the private companies that are racing at this.

If I could create one institution, it would be an IMEC. If folks aren’t familiar with that, it’s canonical in the semiconductor industry — having institutions that are public, private, nonprofit, and they focus on this liminal intermediate phase after fundamental R&D but before it’s pretty competitive with the market. They just get good at that middle TRL phase. It turns out that you need to have institutions that all day long build that as a craft. That’s both an expertise, a capital structure, capital itself, and physical capabilities. You need specialized instrumentation that’s only good at that phase. From an institutional basis, that’s the one area I focus on as a missing potential piece.

Jordan Schneider: Given that Constanza is going to be next in our quantum series, why don’t you tease and pitch her work a little bit?

Zachary Yerushalmi: The teaser for this is — and Chris is going to be the emcee for the release of the report so there’s more than one person who can sing her praises — Constanza Bustamente is, on every dimension, the leading quantum policy researcher out there. She’s at CNAS. She did a definitive study on quantum sensing, which everybody on the planet should read. It went both breadth and depth — the best out there.

As a follow-up, while a lot of folks focus on quantum computing, which is great — right back to the drug discovery analogy where you need to focus on the individual drugs that cure cancer or whatever they do — she wanted to drill down and look at the quantum supply chain. What are the things that enable us to develop these quantum computers? She uses it as a framing how to stay competitive and how we lock down a capability in the supply chain. The report is coming out in March. Again, Chris, you’re actually closer to this than I am, but it is a must-read for anybody who cares about advanced technology policy and competitive advantages.

Reading Recommendations and Quantum Jobs

Jordan Schneider: Zach, I would love you to make a pitch for the syllabus that we’re going to put in the show notes. We already talked about the “But What Is Quantum Computing?” YouTube video, as well as Constanza’s recent report. What about the quantum-classical divide? Systems engineering bottlenecks?

Zachary Yerushalmi: The quantum-classical divide is just fun weekend reading on us being on the cusp — not just of these fault-tolerant systems, but really a better understanding of how the atomic world adds up and meets the classical world that we’re all used to. While probably not the most important from a policymaking decision standpoint, it’s pretty cool as a human being.

The system engineering bottlenecks actually provide one of the best breadth and depth, deeper views of quantum computers as a system and where they fall down and where we need to prioritize. I would say it’s more with a research academic lens to it. Costanza’s report is a really nice complement because it goes a little bit more into the policymaker dimension on what we have to prioritize.

There are a couple of others which are fun and very ChinaTalk-esque. When We Cease to Understand the World — quantum breaks your brain a bit. This book is probably the best that I’ve come across at capturing what it’s like to be in the mind of somebody whose brain has broken because of quantum.

Last, this one’s more weekend reading. But it felt like a very ChinaTalk recommendation because it’s a The Social History of the Machine Gun approach applied to the early history of nuclear fusion. Again, fun read. It turns out that through weird and wacky accidents, those can be the difference between life and death for some of the most important programs of our time, and I just love that little lens on the world.

Jordan Schneider: Are there good quantum podcasts?

Zachary Yerushalmi: Some can be more or less advertisements for companies, which are great. And we love these companies. But the one I like is New Quantum Era.

Jordan Schneider: Can you give us a little anthropology of quantum researchers? What brings you down this path? What kind of personalities do you get relative to other fields?

Zachary Yerushalmi: One of the biggest learnings in my career is that the people it takes to solve every particular chain of an innovation cycle — you need a different personality for every single type. There’s an infamous distinction between theoretical physicists and experimental physicists. Theoretical physicists are locked away in some room with a bunch of chalkboards, and their dopamine hit is them with chalk and paper or whatever it is.

Experimental physicists are different because they work in teams. What determines all of this is where you get your dopamine hits from. If you are a fundamental researcher, you don’t get your dopamine hit from reliably solving a problem, because the definition of fundamental research is that you don’t know when you’re going to solve that problem. You get your dopamine hit from asking an interesting question and finding something interesting about that.

Now that we’re transitioning into an engineering field, it’s a very different mindset because engineers often get their dopamine hit from solving a very specific problem that folks have solved before, and it’s working through it. How people find themselves — back to the top of the question — is starting with what motivates them and then mapping that to the right part of the technology innovation cycle.

What I would say for me, oddly enough, it’s different. I’m not coming from a science angle. A lot of it is trying to find the right mental model. It’s being curious and finding the thing that I can never fully scratch the itch of curiosity on. Then it’s trying to find the right mental model to meet that moment.

The last — this really transitions to a totally different phase — is folks with a sales discipline. There, it’s about winning deals. The fascinating thing about really anything that you’re trying to do that’s a team sport, but particularly with quantum, is you need to align folks with not just wildly different expertise. You need to align folks with wildly different passions and motivations and get them all to work together because you have to solve things all the way from the fundamental physics up through making a killer deal and a lot of money.

Jordan Schneider: That’s cool, but it’s also hard. Is this the path of least resistance if you’re a physicist and you want to do cool stuff nowadays? Do you see talent being drawn to the field thanks to the recent breakthroughs?

Zachary Yerushalmi: Yeah. Just not fast enough. There’s a famous stat that for every three quantum job postings, you only get one qualified candidate. There’s a lot of demand for this stuff. We need to address that badly.

The issue with addressing this, especially on these timelines, is that it takes five to seven years to get a PhD. If we’re going to surge resources to this, it gets back to the fact that you can spend infinite money, but you can’t compress the timeline for a PhD from seven years to two. We actually have to address this in a very different way from a talent perspective.

Chris Miller: What would you train more of today? You mentioned that you need salespeople who can sell quantum capabilities alongside the people who can actually do the fundamental engineering. If you could train X thousand people in discipline A or B, what would that look like?

Zachary Yerushalmi: Quantum system engineering would be wildly important. The other bottleneck would be technicians.

I found out something fascinating recently. If you are a technician or an undergrad, even a master’s level, and you’re trained in quantum, it’s all theory-based because the physical systems you need to do the training are so expensive and so exquisite. Nobody’s going to give a bunch of students access to something that costs a couple of million dollars if they break it. I get that.

But it also means that when you graduate and get hired by a company, you have to get trained from scratch because you haven’t had access to the physical system in the first place. I would be prioritizing those roles and things like physical access. It’s actually a good news story because we can do something about that. You can give access to these physical systems. You can spend the money and solve your problem. I love those sorts of problems if we can find them.

Costs and Cycle Times

Jordan Schneider: Claude tells me post-Willow, the realistic all-in cost for RSA-breaking quantum computers is $10 to $50 billion.

Zachary Yerushalmi: Cost per calculation is super important. It’s one of the factors that the government is trying to assess. Just on Willow architecture, absolutely. But some leapfrog capabilities would wildly bring that down.

Back to the biotechnology comparison — it costs $1 to $4 billion per approved drug. $5 to $10 billion for the first computer that can break RSA makes sense. The Human Genome Project took how many billions? It makes sense in my simple head.

Chris Miller: Your point about the cost of a computer is only relevant if you also know cost per calculation seems very important. How do we think about the spectrum of outcomes and time horizons on cost per calculation, and how that’s going to change over time?

Zachary Yerushalmi: It’s really early to say. One of the things the QBI is trying to examine is how much it costs to perform calculations across these modalities, and whether that cost makes sense for specific problems.

For example — and I’m making this up — if it costs $10 billion over 5 years to do a physics-based simulation of penicillin, that’s probably not worth it. But if we’re talking about an architecture that costs a week and a million dollars, then suddenly the economics look very different. Some architectures have hope of reaching that cross-profile, while others simply don’t. That’s one of the fascinating things to assess.

Here’s what I’m curious about, Chris. We alluded to this earlier, and I’d love your take on two things. First, is cycle time a useful metric as a North Star for industrial competitiveness? Cycle time as in how long it takes to make your product.

Chris Miller: I would consider that as one input into a broader rate of innovation and improvement — but only one input. Cycle time is important, but the differential between cycles also matters.

If you have a long cycle time but achieve huge improvements between cycles, that’s probably okay. For instance, if it takes TSMC a year to move to the next node, but that next node delivers significant improvements, maybe that’s fine. However, longer cycle times become problematic when your differential is smaller. Those are the two key factors I’d consider.

Zachary Yerushalmi: Let me give you a specific example. To build one of these systems for one of the main modalities, you need something called a photonic integrated circuit. Constanza discusses these extensively in her report. Think of it as the photonic equivalent to an integrated circuit — you really need this component to build scaled systems.

For some of the largest players, it’s not just about availability. They can actually get access to a PIC, but the cycle time can be 12 to 18 months. In contrast, if you’re located next to one of the fabs that manufacture these and have good availability, your cycle time drops to a matter of weeks.

This could be wrong, but when I look at China’s advantage in 5G and other photonic technologies, their defining advantage was the ability to build and test products an order of magnitude faster than American equivalents.

Chris, I appreciate your characterization that there are two factors — how fast you can make and test something, and how capable you are of learning from it. We Americans excel at the second one — learning — because we have talented people here and can leverage brains from around the world. But where we’re wildly far behind is cycle time. It’s not just an availability issue — it’s about how quickly we can actually get the thing.

For games like quantum computing, where we have a really small margin of error, my focus is on reducing that cycle time. If we think of the Euler diagram of what’s both important and actionable, wildly reducing cycle time would be the best engineering-style measure to cement a competitive advantage. It provides a non-market but very clear signal on where to prioritize — identifying what’s holding us back from building systems quickly and figuring out how to address those bottlenecks.

Chris Miller: What’s the limit to cycle time today? Is it that companies producing component X or Y don’t see quantum as core to their business? They have other customers buying at higher volumes, so they don’t want to prioritize quantum because it’s still science project-sized rather than commercial scale. Is that the main reason?

Zachary Yerushalmi: Yes, or there’s almost no market-clearing price that would make it valuable for them to do that. What we’re building with this federal award costs us $40 to $50 million just to stand up the fab. We hope to make about a million dollars a year from it.

If I were a commercial company or a VC investing in this, it would be a clear no-go. But because this is a nonprofit, the investment becomes really valuable.

Looking across the landscape, we need to ask — is there a short-term market for these components? If so, the private market can address it. If not, we need an institution that continues to focus on that intermediate TRL (Technology Readiness Level) step.

In semiconductors, basically every leading semiconductor ecosystem has institutions operating as public-private partnerships. On a VC basis, they don’t make sense, but for national competitiveness and the economic competitiveness of their partner companies, they make lots of sense.

IMEC serves this role, as does KAIST in Korea. Taiwan has their equivalent of IMEC. China has loads of these institutions.

That’s what worries me — on our current trajectory, this is the one area that could get overlooked if we don’t have cycle time as our defining metric.

Jordan Schneider: Thanks, Zach, for getting us started with our quantum journey.

Zach’s Quantum Technology Reading List

• Quantum Computing Fundamentals: But What Is Quantum Computing? by 3Blue1Brown — A visual, mathematically rigorous explanation of how quantum computers actually work, building up to a complete walkthrough of Grover’s search algorithm. The best starting point available for non-specialists.

• Quantum Computing Overview: The Map of Quantum Computing by Domain of Science — A comprehensive 33-minute tour of the entire field, covering algorithms, hardware approaches, applications, and the key obstacles to building useful quantum computers. The roadmaps are now dated but the modalities are still relevant (minus silicon spin, which has really taken off).

• Quantum Sensing: Atomic Advantage: Accelerating U.S. Quantum Sensing for Next-Generation PNT by CNAS — Dr. Constanza Vidal Bustamante’s 2025 report flagging quantum sensing as the most mature quantum technology today, with near-term national security and commercial applications in GPS-resilient navigation — an adjacent but urgent defense priority for governments globally. Constanza rocks.

• The Quantum-Classical Divide: Are the Mysteries of Quantum Mechanics Beginning to Dissolve? by Philip Ball, Quanta Magazine (February 2026) — A fun look at Wojciech Zurek’s decades-long program to explain how the quantum world becomes the classical one. Zurek argues that entanglement with the environment “selects” which quantum states survive into observable reality — a kind of Darwinian process that may finally explain quantum weirdness without invoking parallel universes or conscious observers collapsing wave functions.

• Systems Engineering Bottlenecks: Computer Science Challenges in Quantum Computing: Early Fault-Tolerance and Beyond by Jens Palsberg et al., IEEE Quantum Week (2025) — A 90-person community report arguing that the primary bottleneck in quantum computing is shifting from physics to computer science — compilers, architectures, and system integration. Notable for its candid assessment that industry roadmaps should be read as “aspirational, not predictive,” and its identification of the dequantization arms race, where classical algorithms repeatedly match claimed quantum speedups.