The data seems to back him up: the price of cement in the United States has swollen 46% since Covid, almost triple the growth rate of the previous decade. CRH, one of the largest cement producers in the world, is up 110% over the past five years, while Dan Sundheim at D1 made bank on building materials conglomerate James Hardie International.

We’re all trying to find alpha, but I don’t think a trip to World of Concrete is in order. Yes, VC is a total frenzy right now. According to Crunchbase News, roughly half a trillion dollars of venture capital was deployed in the first half of this year. That figure compares to $26.8 billion for the entire mobile-social-cloud-year-of-our-lord 2012, when I first entered VC.

With so much capital flooding the market and inflating even the first draft of a pitch deck to a billion-dollar-plus valuation, I understand the urge to find alternatives to tech companies (here’s one: premium kimchi refrigerators for all the SK Hynix workers loaded with bonuses).

Yet, even the most “picks and shovels”–pilled VC understands you don’t invest in the hot dog stand in front of the data center (after all, no one works there). Yes, you can potentially invest in a tungsten mine in Gangwon, South Korea, and you might even make money blasting rock. But the big returns that will make or break VC funds are going to come the way they always have: investing in the best technology companies.

What’s changed in this new era is the definition of “best.” In the 15 years between the Global Financial Crisis and Covid, the best startups featured a great core product that generated momentum toward monopolization. In social and marketplaces, it was network effects. In cloud and APIs, it was developer relations and platform lock-in. In applications, it was self-service and product-led growth that drove word-of-mouth. In consumer fintech, it was a viral loop in a primary beachhead with many cross-promotes to reduce marketing costs. In crypto, it was a mix of many of these plus the shameless pursuit of fraud (I only half joke).

AI is an entirely different beast, since the source of profits will constantly shift as users (and their agents!) seek the most efficient intelligence in a hyper-competitive marketplace. Sometimes profits will come from the frontier model, sometimes from the compute infrastructure, and sometimes from applications. Unlike the monopolization effects of yesteryear’s startup winners, none of the leading players in any layer of AI seems to have locked in its status. The closest is maybe Nvidia and its CUDA platform, but even here, a number of competitors are working hard to break its lead.

Why can’t AI companies become entrenched? Part of the answer is a function of their own products: Claude Code, OpenAI’s Codex and similar products can make shifting to a new API or platform nearly effortless. Rapid innovation of new techniques around model training ensures that the leading options are always churning. The lavish funding of semis has given chip designers better tools to go from conception to tapeout (Etched being the latest example). Even brand affinity seems less powerful than it once was. I thought OpenAI had the game won given the near-universal global awareness of ChatGPT, only to find that Anthropic has completely upended the race.

The best companies of this generation will thus compete through rapid, multidimensional execution that constantly reinvents their business. These companies will be organized more like a hedge fund than a traditional tech company, less about monopolization and much more about constantly rebalancing a portfolio of products, selling off one category that’s underperforming in order to invest like hell into another with brighter prospects. If a company and its engineering team have capacity to work on only one core product at a time, that company will be subsumed by the improvisation of competitors who can readily chase wherever the money will come from next.

That’s very different from, say, Uber as it grew up. Its engineers honed product loops to drive its marketplace for taxis and later food delivery, building up lock-in via network effects that no AI company is going to have this generation. Here’s the easiest way to see the difference: if Uber launched no new features this year, would anyone care? Would its market share plummet? (In fact, given that all of their new features seem to be some form of enshittification, I as a user would probably encourage a company-wide engineering holiday). That’s absolutely not the case for leading AI companies.

I was thinking about this new model of startup while reading Gary Sernovitz’s profile in The New Yorker of Ken Griffin, CEO of Citadel, one of the most successful hedge funds of the last few decades. It was a boring profile, and it was clear that the author struggled to turn immense access and assiduous research into any sort of propulsive narrative. What’s the secret to Citadel’s success? Well, after twenty pages, it’s pretty much as trite as “survival of the fittest.” Sernovitz sums up:

Citadel has never publicly codified how it achieves “alpha”—outperforming the market. But my conversations with Griffin and twenty-eight of his current and former employees revealed that they had consistent tenets. The output of Citadel’s factory is alpha. Every aspect of the factory must be constantly improved, and to accomplish this everyone must forage for information. The purpose of every improvement is to minimize unknown risk so that Citadel can maximize intentional risk. The biggest risk of all is complacency. The objective is not just profit but victory over rivals.

Of course, that describes everyone in finance, and so the piece keeps searching for a better answer. But there isn’t one, since what’s unique about Citadel is precisely what’s quoted above. Griffin just keeps relentlessly reinventing year after year, decade after decade and apparently never gets bored or complacent.

That’s just not normal for mortal humans, which is one reason why Citadel has massive employee turnover. It reminds me of the hard-charging and adaptive cultures at Apple and Huawei I talked about two weeks ago. Like in finance, in the Hunger Games of an extremely competitive tech market, only the most adaptive and fastest executors are left standing at the end of the tournament.

Given how different “best” looks today, what should VCs be looking for in a company? Small, technical and highly competent teams that rapidly seek out new profit pools and exploit them before they are competed away. There’s a reason international olympiad winners are so prized right now by VCs and founders alike: their acumen plus aggressive competitiveness is the magic sauce. Who is out? The visionary product founder who is fastidiously obsessed with the details of the button interaction on their app’s signup page.

We see the outcome of this thesis in one of the biggest AI funding rounds of the past few weeks into DeepSeek, the company behind the most popular open-source model from China. DeepSeek was spun out of a high-performance hedge fund, High-Flyer, and carries with it finance’s competitive DNA. Despite its popularity, the company has only 300 employees today, compared to several thousand at Anthropic and upwards of 10,000 at OpenAI. Yet that small squad has produced one of the most competitive models in the world right now.

That model, DeepSeek V4 Pro, is crazily efficient, both in terms of its training (although that’s heavily disputed) and the cost of its inference. It’s an order of magnitude cheaper than Anthropic’s Claude Fable 5, with DeepSeek V4 Pro coming in at $0.87 per 1 million tokens out versus Claude Fable 5’s price of $50 on OpenRouter. Yes, Fable is tremendously capable and outperforms DeepSeek, but is it 57 times better? What percentage of queries demand better intelligence rather than cost savings? This is the competition that will constantly shift from week to week and year to year.

Anthropic’s launch of Mythos spooked DeepSeek, according to The Information, and triggered its $7 billion fundraise, the first institutional round in the company. The deal structure is highly unusual compared to Silicon Valley standards. Up to now, DeepSeek has been funded by its founder Liang Wenfeng from the profits of High-Flyer, which he also founded. Liang’s net wealth is unknown, but he must have done well: he is funding 40% of DeepSeek’s round himself. He’s also keeping complete control of the company by forcing VC investors to fund DeepSeek through a limited partnership with no voting or governance control.

With greater resources at hand, the company is now expanding beyond just its best-known open-source models. This week, Reuters revealed that the company is developing its own AI chips, and it has a multitude of other ambitions far outside its frontier lab reputation.

DeepSeek shows how different the best companies of this generation are going to operate. As VCs fund a different kind of company, they will need to think differently about portfolio construction. Using the previous era’s model, investors would select a bet in a chip company, an infrastructure platform, a harness, a frontier lab and on and on, putting checks in each of the boxes on the industry market map. This approach assumed every company did one thing, and one thing well, and every logo could be placed in exactly one spot on the map.

That’s not how AI is shaking out. Even early-stage companies are taking on multiple product categories simultaneously that would be more expected of a Mag 7-scale company. Everyone is a model builder. Seemingly everyone is working on some sort of chip and infrastructure play. Every company is considering applications and how to own the full profit cycle of a user. Hell, a lot of companies seem to be buying nuclear power plants or investing in fusion. While an exaggeration, it’s almost as if every startup and big tech logo can be placed in every box, or at least, certainly more than one. In short, every venture-backed AI company is now its own chaebol.

VC portfolios today are less about placing a bet-per-box built upon a bunch of careful market analysis and much more about investing in the most competitive talent who can sustain their game for a decade or more. That’s why even eye-watering valuations can seem reasonable: if the right team is in charge, they will conquer the market and investors will ultimately be rewarded.

The magisterial and zany magazine profiles of yesteryear’s founders will (unfortunately) read more like the tedium of Griffin’s. Great execution is the dumbest blandishment about what makes a great company, but it’s also the hardest goal to sustain forever. There’s nothing concrete about success anymore.

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• What would happen if China hacked the U.S. water supply.

• What it’s like waiting for electricity in Monrovia.

• Tick hunting and alpha-gal.

• The Apple-Bananna paradox.

• Why grocery-store ice cream is so bad.

• The Searchlight Institute looks at public sentiment on U.S. national security and foreign policy.

• America’s drone supply, mapped.

• And why is there a Palantir chore coat?

That progress includes material (the free-market capitalism that creates the incentives for both brilliant invention and banal construction of everything from homes to data centers), cultural (America’s soft power remains unrivaled globally across books, music, movies, video games, and more), social (a persistent drive to improve the lots of individuals and keep them unshackled by unnecessary restraints), security (the American military has no rival, period), and technological (do I really need to spell this out?).

While we often glaze over in distracted stupor as we skim our infinite feeds, enamored and repelled by the bric-a-brac of the day’s events, there is a much more sanguine view to be found over the long horizon. America just keeps lurching toward the future. Yes, there’s fighting, and partisanship, and arguments. Progress in a democracy is inevitably messy — how could it not be? Our fights are precisely what ensures that our institutions are responsive to our needs — and ensures they will endure for generations to come.

That the fight takes place right in the public square is thanks to what I consider to be America’s most sterling contribution to man: its commitment to freedom of speech and other rights enumerated in the First Amendment. It never ceases to astonish me the degree to which our peer countries curtail speech through regulation. America has the most robust speech protections in the world, bar none. It’s a commitment that has its downsides that other countries attempt to ameliorate, but they do so at the cost of something far more fundamental: a belief that a free people can think for themselves, speak for themselves and comport themselves in accordance with their responsibilities as citizens. The First Amendment is a strident statement of optimism, and as a writer, I appreciate its affordances everyday.

Whether you are at home or abroad, and whether you are an American citizen, aspiring to become one, or just part of this great human tribe on Earth, it’s worth taking a breath and reminding ourselves that 250 years ago, a group of enlightened individuals came together and decided that we’d break from the continuity of the past, and that things could and would be better for everyone. They built an engine for progress that has never stopped. Happy Fourth!

As I was reading through a selection of recent books on China’s tech rise, I kept returning to the questions posed by Whiplash, but scaled from a single student and his teacher to the second most populous country on Earth. Hundreds of millions of migrant laborers sacrificed and suffered through hardships all but unknown in the developed West to make China what it is today. Even as the country has reached ever higher rungs of the development ladder though, the pain of competition has only seemed to intensify.

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Reviewed in this essay:

• House of Huawei by Eva Dou

• Apple in China by Patrick McGee

• Adrift in the South by Xiao Hai

• I Deliver Parcels in Beijing by Hu Anyan

Industrial policy is a brilliant parlor game for the intelligentsia, where every doctor-but-not-the-kind-that-helps-people can piss their favorite social science theory into the punchbowl. Read 1,000 papers and monographs, and a simple truth emerges: there are no shortcuts nor stratagems that can suddenly take a naif to greatness, or a poor country to the apex of power. It’s just work, debilitatingly hard work. The kind of hard work that leads to missing limbs, shattered lives, suicides and excruciating pain as one gropes inexorably forward to end the suffering. The Chinese don’t call it eating bitterness for nothing, but what, truly, is the alternative?

A second truth emerges though. Apologies to GiveDirectly and the other EA 10% folks, as well as the United Nations Cinematic Universe of six-letter-acronym agencies, but wiring a check is hardly enough to underwrite a people from poverty to riches. Instead, hard work must be coupled to the painstaking wisdom acquired through one bitter lesson after another, learned and re-learned until they are scarred into the flesh.

Across four recent books, these two truths are drilled into the brain like Fletcher conducting on his podium. Eva Dou and Patrick McGee write corporate histories, her’s on China’s telecom giant Huawei and his on Apple (and by mirror image, Foxconn). Then there’s two memoirs from the laborers themselves, with Xiao Hai writing predominantly from textile and electronics factories while Hu Anyan describes his gig work that underpins the global tech service economy. Like a mosaic, the four depict one nation’s crucible and its pursuit of power above all else.

Solitary, poor, nasty, brutish, and short … but enriching someday

For all of the talk about China in these four works, it’s the brutal working conditions at Apple that surprised me the most. McGee never makes the analogy, but Steve Jobs’s turnaround of Apple in the late 1990s and early 2000s is reminiscent of Mao’s Long March, when tens of thousands of communists trudged more than 6,000 miles to Yan’an to escape Chiang Kai-shek’s Nationalist forces. Jobs exacted a high toll from his workforce in order to engineer the magic of iPhone to the ultimate delight of billions of owners as well as the company’s shareholders, as McGee relates:

The eighty-hour workweeks and increasing need to be in Asia at inconsistent times, with little warning and often for unknown durations, caused massive stress on the engineers’ mental health and their marriages. They were primarily men, and some of their wives took to calling themselves “Apple widows” because their husbands were around so infrequently.

Apple’s elegant solution was giving workers a day off through what was informally dubbed the “Divorce Avoidance Program.” But a day off was a day the company ultimately couldn’t afford:

The necessity of giving engineers respite to save their marriages was understood, but with Apple’s [Industrial Design] studio continuing to push the boundaries of what was possible, workers were under constant pressure to perform. So instead of giving time off, Apple started to give out bonuses meant to assuage spouses.

These bonuses were dubbed “Danny bucks” for the company’s VP of Product Design Dan Riccio (If you would like to supply me with some Danny bucks, all channels are open).

What was the cost of Apple’s Long March?

Some Apple engineers can even rattle off the names of people who died on the production line or upon their return from yet another trip to Asia. The engineers were often in their forties or fifties, and while it’s not possible to conclude that overwork was their cause of death, many believe it was. One longtime veteran recalls that, during the funeral for one of these people, the number of Apple employees who left the Sunday service to join conference calls was unbelievable.

Jobs himself attributed his pancreatic cancer to overwork. That was the cost. The benefit, of course, is known to all of us: the once “beleaguered” and nearly bankrupt computer maker rose like a phoenix to become the second most-valuable company in the world after Nvidia, last year producing revenues of $416.2 billion on the backs of 166,000 employees, or roughly $2.5 million a soul.

McGee’s thesis in Apple in China is that those 166,000 employees didn’t act alone, but instead tutored millions of laborers in China and throughout East Asia to manufacture components and assemble them into awe-inspiring devices. As he writes early on, “It’s not merely that Apple has exploited Chinese workers, it’s that Beijing has allowed Apple to exploit its workers, so that China can in turn exploit Apple.”

Apple was perfectionist. Unlike competitors, it decided to scan every iPhone coming off the assembly line for defects, rather than just a limited random sample. That demand required completely rebuilding the supply chain for RF frequency testing machines, a niche industry that produced a small number of devices for laboratory usage, not the quantities needed for scaled production. Apple dispatched its engineers to teach the companies how to produce more machines.

Xiao Hai, a pen name for an itinerant laborer-cum-poet Hu Liushuai, suffered a spell at a Foxconn factory on the receiving end of that perfectionism. He describes his experience in Adrift in the South:

The floor manager sent me and other newcomers across different work crews. At the time, Zone L was manufacturing the iPhone 7, and I was assigned to quality control. On my assembly line everyone’s workstations were separated by machines, and I couldn’t see the faces of my neighbours. My job was to pick up finished products from the conveyor belt, shove each of them in a drawer-like examination compartment, and wait for letters to appear on the screen. If the letters flashed green then it meant the phone had passed quality control, but if they were red then I’d need to return the phone for repair. It took about thirty seconds for the test to run, and each machine was built to have about a dozen examination compartments running at once. Whenever a screen flashed green I’d empty the drawer and fill it back up with another phone from the belt — the machine was never supposed to be empty, and neither were my hands.

In low season, shifts were merely monotonous, but the intensity ramped up dramatically with each new model launch. Ultimately, Foxconn’s goal was for each worker to become a cybernetic extension of the machine itself:

With all these machines around me, I felt as though I had passed into cyberspace. Shrouded tightly within my coverall gear, it was like I was an extension of my silicon-based companions. We were there simply for the sake of the products on the conveyor belts, and we all knew it. We had morning and evening meetings before and after our shifts, during which our higher-ups babbled on about production figures. There was nothing else. Nobody ever brought up their aspirations or what their lives were like outside the factory.

Xiao Hai does have ambitions though, and ultimately realizes them through his writing and poetry. He grew up in an impoverished village in Henan province, and was unable to attend high school because his parents couldn’t afford the fees for both his older brother and himself. So he sets out to find his livelihood and place in this world.

Like millions of other migrant laborers, his story is not one of Whiplash rags-to-greatness, but rather one of just scraping by and staying adrift. He makes money, quits, and loses his savings, time after time. His survival instincts kick in at just the right moments to keep him afloat. He doesn’t want to be a cybernetic extension of the machine, but there is no alternative, for that machine is the only thing writing a check that can buy him food. Outside of a short stint as a popcorn vendor, the factories are where his livelihood comes from until he moves to a creative urban village outside Beijing called Picun, where he finds solace if not wealth

.

The same can’t be said for Ren Zhengfei, the founder of Huawei, who does manage to find both even if the search is ultimately killing him. In House of Huawei, Dou recounts discussions over Ren’s succession back in 2011. “Without offering details, Ren also disclosed that he’d had two cancer surgeries over the years. He blamed it in part on overwork: ‘I was too tired. My body just collapsed from fatigue.’”

Ren assiduously tries to cover up his emerging wealth in China, just as he tries to hide many details of his biography and the company’s history. When Forbes identified him as China’s third-wealthiest individual in 2000, he was incensed. “Ren had not wanted to appear on the list. The Financial Times reported that Huawei had offered the list’s author, Rupert Hoogewerf, a factory tour if Ren could be omitted.” His ranking made him a target, and in the lawless competition of China’s tech scene, being a target meant being prey rather than the “wolf” that Ren tried to inculcate in each of his employees.

Indeed, working at Huawei was grueling, at times an almost perfect mirror of McGee’s Apple. Huawei employees were committing suicide due to overwork:

In June 2007 … [Ren] wrote that he was at his wit’s end about stopping the deaths among his employees. “Huawei continues to have employees committing suicide and self-harm,” Ren said. “And the number of employees suffering from depression and anxiety is increasing, which is very worrying. Is there any way to help employees face life positively, openly, and uprightly? I’ve thought about it again and again, and I can’t solve it.”

As Dou makes clear, Ren built Huawei like an army, in which suffering and self-sacrifice were fundamental in the war for national rejuvenation. In the company’s early and impoverished era, engineers building the country’s first indigenous phone switches worked without air conditioning or mosquito nets, even in the tropical summers of south China.

Ren was Fletcher conducting to the highest standards. It was hell, but no alternative was on hand. He bought employee loyalty through stock, which paid dividends in Huawei’s good years, but there was no broader safety net. When China passed a law that offered some job protections to workers based on seniority, Ren acted fast:

Huawei had long had a reputation for laying off older engineers to keep its salary costs lower with a younger staff. Now, in late 2007, Huawei rushed to get ahead of the new law. With Ren taking the lead himself, some sixty-five hundred Huawei employees resigned and rejoined the company, wiping out their seniority.

Seniority, of course, assumes one can stay with the same employer. That notion doesn’t apply to millions of migrant laborers, who are constantly shifting around based on market demands and their own desires. Hu (also a pen name) describes his eclectic roles across China’s gig economy in I Deliver Parcels in Beijing. Mostly eschewing factory work, he instead pursues his livelihood as a deliveryman for ecommerce companies with stints at a diverse set of other jobs. The spare narrative is the tick-tock of gig work, with sections like, “My Sixteenth Job to My Nineteenth.”

Hu’s memoir is an anthropological look at the intricacies of modern capitalism. Deliverymen in China are paid per parcel, and so all sorts of calculations and tradeoffs are made by laborers. Is it better to work in a far-flung neighborhood with nicer residents that are easier to deliver to, or a denser neighborhood of arrogant residents who often create more hassle? Is the payoff of upgrading a bike’s motor covered by increased efficiency?

Relative power could shift in an instant, and Hu becomes attuned to these fleeting moments of agency. “One of the longer-time couriers joked on the down-low that the leadership loved to whip us into doing our jobs in the less-busy times, but when the sales came around, they were on their knees begging for us to stay. It was also the only time when we could request change of any sort, and they would respond promptly.”

His story is more sanguine and filled with less angst than Xiao Hai’s. Whether the difference comes from personality or the depersonalization of factory work, I haven’t a clue. But Hu is a man who knows that he has to keep on going, even if he feels it’s futile. “I have never believed in karma. Some things just seem to be fated, when really there are underlying patterns at work. That is why I should have known that, just as our new store was thriving, the seeds of trouble had already taken root.”

Those “underlying patterns at work” are, frankly, the textures of development. Even today, China struggles with prodigious — and under-reported — levels of unemployment, particularly among youth. Millions of college graduates are struggling to land a quality job, or even one that offers them survival in the country’s cutthroat economy. The whiplash of development is that even as these graduates pursue their studies further than their parents could ever have dreamed, the opportunities before them seem ever more distant. Many talk about involution, or reverse evolution.

Civilization’s long march, in short, never stops. The depravities of generations past resurrect themselves as new monsters to be overcome in the present. Millions more Chinese have walked into the elite strata of global power, but there are still more than a billion others behind them, waiting their turn.

Was it worth it? Yes. Unequivocally so. The despair and agonies of the poverty described early on by both Hu and Xiao Hai should remind all readers that no one wants to live their lives; the two only do so because they have to. But what are we to make of the Apple engineers ensconced in a spaceship ring in Cupertino, designing every last chamfer and Liquid Glass raytrace to perfection? Or the Huawei engineers wolfishly securing 6G patents as their company seeks to secure the next generation of wireless technology?

They just keep going, wealth or no. Similar to my comments on Kim Jong-un last week on North Korea’s nuclear program, sometimes the only way to succeed is the Whiplash way. Mission, hubris, arrogance, stubbornness or plain old stupidity — pick your human fault. Certainly the subjects of our four books did. It’d be career suicide to ever stop.

Don’t let your schooling interfere with your education

Learning is the lifeblood of development, for startup founders and nations alike. Hard work is clearly necessary, but not sufficient. In a complex material world where producing an iPhone takes millions of workers, from the coltan miners of the Congo to the assembly workers in Guangzhou, the ferocious pursuit of knowledge is the key activity for building wealth.

The challenge for China has not been a lack of desire to learn, but a lack of teaching. During the Cultural Revolution, teachers were denounced, universities were closed and education was replaced with labor in the countryside. Ren of Huawei suffered mightily in this period, but lucked out in being assigned to a military outpost where he could practice engineering and bide his time until Mao died in 1976. That early luck would reverse during the more recent degradation of U.S.-Chinese relations, when his military past became far more ominous to American policymakers.

Who would teach China as it emerged from Mao’s hell? McGee’s argument is simple: China’s teacher was Apple, full stop.

Journalists have covered Apple’s forays in China for decades. Allergic to a well-tread story, McGee advances the reporting by arguing that Apple didn’t just take advantage of Foxconn’s scale, but offered lavish support for training Chinese engineers and line workers to build its ambitious devices:

The explicit deal—let’s call it the Apple Squeeze—was that Apple’s engineering and operations teams would rigorously train local partners, in the process giving away manufacturing knowledge, in particular how to efficiently scale while maintaining the highest quality standards. In exchange, the local supplier would work for soul-crushingly low margins with the understanding that it could profit from the incredible volumes Apple demanded.

What made Apple unique in the Chinese market is that its novel designs for the iPhone and other devices required pathbreaking innovation in manufacturing — work that had never been done before, let alone at scale. Apple wasn’t just offering business to millions of Chinese workers like, say, Walmart, but was teaching them how to do some of the most complex work in the world:

Wanting to help Apple understand its predicament in China, [Doug] Guthrie started traveling and interviewing suppliers. In his talks with dozens of them, a common theme emerged. “Working with Apple is really fucking hard,” suppliers would tell him. He’d respond: “So don’t.” And they would demur: “We can’t. We learn so much.” … Apple gravitated toward quality, not price. To reach that quality, Apple had to come up with new processes to make the phones; but until Apple developed a new design these processes wouldn’t exist. So it had to work far more intimately with suppliers.

Apple was the Fletcher for Chinese suppliers. It was an absolute monster of a partner, often demanding the impossible, and at extraordinarily cheap costs that forced suppliers to cut wages to the minimum. But it got what it wanted, and the workforces implanted at factories across China learned differentiated skills that made them competitive in the global marketplace. Apple was an abusive teacher; it was also the best teacher a country could have hoped for.

Dou’s Huawei story runs parallel, but from an indigenous perspective. A thirst for learning was fundamental to how Ren conceived of the foot soldiers of his telecom army:

Ren thought of Huawei’s staff as more than just dumb money. He pushed them to cultivate themselves. He felt that the Huawei man should be a Renaissance man, learned in history, literature, philosophy, and global cultures.

That cultivation extended to the built environment. He wound up constructing an extraordinary headquarters campus for the company, including a replica of Versailles and a dozen more neighborhoods that riffed on diverse Western architectural styles. The company’s data centers were no exception. Huawei’s massive center in Guizhou province is broken up into several buildings designed to emulate a European market town. (One wonders whether the AI backlash in America would be so severe with such grandiose architecture instead of the boxy modernist dreck we see here, but I digress).

Learning could be done by doing, but Huawei’s early products didn’t match the quality of its Western competitors and found little purchase in developed countries. So it sought experience by operating in the world’s most inhospitable locations, ranging from Iran and North Korea to some of the most turbulent countries of the Middle East. Ren’s army would persist:

During his visits to Iraq, Afghanistan, Libya, and Mali, Ren told Huawei employees that while he sympathized with family members’ concerns over their safety, they couldn’t leave their posts without properly handing off their work. … “Huawei might be the only foreign company remaining there [in Libya],” a Chinese newspaper reported.

Whatever it took, it got done. Huawei’s journey from its humble origins to number one telecom equipment provider was a harsh road, but it reached its destination.

For all of the hours and abuse, did the lessons stick? For Hu and Xiao Hai, it’s not at all clear. Hu’s gig work doesn’t lead to any personal development, other than memorizing street addresses and optimizing his route. Whether he’s working for one logistics company or another, the packages are packages, and no amount of tacit knowledge can overcome the structural mindlessness of the work. Hu later experiences a respite from the intense competition in logistics while working in mall security:

Life in Xiaguan was good. Although I wasn’t making all that much, I never had to work more than eight hours a day. The job also fell well within my capabilities, which was a relief. Everyone there treated me really nicely, sometimes to the extent I felt like a foreign guest. Maybe this was because I was the only employee from outside the province.

We can relax as readers in these tranquil moments, but Hu ultimately can’t. Across 18 jobs, his income has barely budged, and it wavers with every twitch of global macro conditions. He’s hanging on, not getting ahead — or propelling the country forward. He’s locked in a cycle of poverty with no exit.

Xiao Hai experiences a bit more development through his factory work. Quality control of iPhones aside, he eventually accrues a series of textile skills that allow him to secure slightly better jobs with higher-end employers. But the work is still endlessly tedious:

I toiled away. My days were an agony. The overheating machines were all wired to each other, their buzz resonating from morning to night, drowning out every other sound across the production floors. … All the sewing I was doing left my muscles and bones aching and I felt burned out in no time. … Working like I was working, there was no way to see the light at the end of the tunnel. Every day was the same: a movement between my dorm, workstation, the cafeteria, and then back to the dorm.

His work produces income and keeps the machine going, but ultimately, he gains no leverage from his arduous exertions. There’s a ceiling on sewing that comes sooner rather than later. This isn’t Fletcher on the podium demanding higher standards toward a world-class career, but something much more base, the repetitive orchestrations required by the machine. He is the man captured by China’s development statistics, accumulating a few skills when he can and always working tirelessly, one shift at a time. Was there ever a path toward something better?

The myths that keep us going

Albert Camus’s The Myth of Sisyphus envisions the titular king pushing his boulder up a mountain again and again, coming to appreciate the suffering and futility of that punishing ascent as the meaning of life, discarding the “philosophical suicide” of disbelief in God in the process. The more optimistic industrial policy version is pushing the boulder and suffering tremendously so that one day, future generations can purchase a bulldozer and do the labor mechanically.

What these four books on China show is that there is a path forward toward development and wealth, one filled with hardship but also hope and a steady accumulation of expanding power. It can be done. In fact, it has been done, many times before. The labor history of Great Britain and America during the Industrial Revolution equally matches — and may even exceed — the deprivations described in these works. Sweat and blood are the roots of progress.

The challenge for China and the West today is that development and growth isn’t a destination, but a neverending process. Hundreds of millions in both places are still waiting for their turn at fortune. The two truths — hard work and learning — are as easy as ever, and yet, the compulsion to compete and push forward is reversing.

This week, we learned the United Kingdom is getting its seventh prime minister in ten years. All of them avoid telling it like it is, of what it will take for Britain to come back. After all, that would be career suicide. Yet, the only Whiplash worse than striving for greatness is the abusive hell of the decline.

Postscript: The mechanics of impossible sourcing

I loved all four books on their own merits, but they are even better in dialogue with each other. There’s real Riskgaming-esque leverage from understanding the tradeoffs that different people make in the same context. That said, as a former journalist and editor, I had many thoughts on the construction of these books.

McGee’s Apple in China has its fair share of weaknesses. He covers decades of corporate history, which makes the book feel both long and also too synoptic. His Long March of Apple product launches is exhausting, and I feel it is only included because of the stray useful source and the need for comprehensiveness. A deeper dive into a single product launch would have been far more useful to understand the nuances of how learning got transferred from Apple to China.

More despairingly, Foxconn’s role in the story is shockingly minimized. McGee is shrewd, and writes in his acknowledgements that “As authoritative as I hope this work is, the Apple-China relationship alone is worth several more books. There is also far more to be researched and written about Foxconn…” Yet, his thesis is that China wouldn’t have developed without Apple as its teacher. But without Foxconn and its founder Terry Gou, Apple would never have been in China to begin with. Maybe it’s just turtles all the way down, but I found the relatively weak coverage of Foxconn to be a sore point to his narrative.

The upshot is that McGee has secured an incredible source in the form of John Ford, who led Apple retail in China for multiple years after the launch of the iPhone. McGee is a veteran journalist, and knows when he has struck source gold. These chapters are lengthy but are profoundly rich with texture on what it takes to run a foreign enterprise in a developing country like China. I would buy the book exclusively for this part.

Dou set herself up with a nearly impossible task covering Huawei’s history, given the company’s past opacity and the incredible scrutiny it faces today. I think she has done an admirable job of sleuthing and synthesizing the widest array of open-source material possible, coupled with a useful series of interviews that fleshed out the analysis.

Yet, her inculcated journalism values mars the direct judgment she could have offered in the book. She has this peculiar habit of pondering why certain facts aren’t presented truthfully, a sort of “it’s curious that” ethos that implies conclusions without indictment. In the strict ethics of a rigorous journalist, I understand the hesitation to call a spade a spade without a certificate from the Global Spade Alliance. But sometimes, you just … can. And should.

For Hu and Xiao Hai, I’m hyper-alert that we are getting their plucked-from-the-masses memoirs. Amidst hundreds of millions of floating laborers, here are two who have risen to such prominence in China that they have secured English translations and are now published globally. This is rarefied company. The existentialism of the two is by no means the norm across Chinese workers, who I imagine are less interested in writing poetry, but want to eat and fornicate more. Both authors constantly switch jobs out of tedium and boredom, but it is precisely that boredom that keeps many others fixed to their workstations, shift after shift.

Where the two works diverge is in their approach to life. Xiao Hai is trying to find his place, and eventually finds it with his writing career and a community of like-minded creatives. Hu, on the other hand, is struggling to just deal with a cruel world that never offers hope for a better life. It’s a hardscrabble story, and one that isn’t always sympathetic.

I do recommend these books be read together, perhaps with Dan Wang’s Breakneck throw in for good measure (Dan was on the Riskgaming podcast last year, so I didn’t thread his work into this essay as well). The story of hundreds of millions of people exiting poverty and entering the global middle class deserves many more retellings. We are still only getting started.

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• Christian Keil at a16z says no amount of wishful thinking can keep us from having to fight a space war. He’s got ideas about learning how to win one.

• Data centers use 0.2 percent of daily water usage in the U.S. and that number has actually decreased in the past few years.

• Eli Lilly gave exactly one patient “compassionate use” access to their very hyped and unapproved GLP-1 retatrutide. Looks likely that person was Trump.

• A long and surprising history of plagiarism—from Shakespeare to Biden, Nabokov to Dylan—that asks whether nearly all writing is, in some sense, theft.

• Michael Koffman assesses Moscow’s military power after Ukraine.

• Big AI labs are hiring lots of philosophers. Why?

• Rheinmetall gambled on Germany’s doomed warship project, and lost. Here’s what happened.

• And The Economist is skeptical about Andy Burnham. Are we already heading to our eighth UK Prime Minister in 10 years?

Consider a few examples. South Korea, whose stock market is up 178% over the past 12 months, has made itself the fulcrum between the United States and China while locking in key growth industries like high-bandwidth memory from Samsung and SK Hynix and protecting its industrialization in markets like shipbuilding. Turkey uses its Eurasia crossroads to masterful effect to maintain its autonomy, balancing NATO membership and drone exports to Ukraine against the specter of its engagement with Russia. Before the Iran war, the UAE used its wealth to build data centers for the U.S. AI industry while also deepening its connections with China.

There aren’t many straddle powers, and few countries are positioned to become one. One dramatic exception in the last few years is North Korea.

When Kim Jong Un inherited the Hermit Kingdom back in 2012 as its third-generation leader, an air of mystery surrounded him. He had been educated in Switzerland and groomed for the role, but he succeeded his father far earlier than expected in what is believed to be his mid-to-late 30s (like so much else in North Korea, we don’t know his exact birth date). What were his political views? Could he hold the security apparatus together? Would North Korea have another revolution or just collapse? Back then, no one knew the answer.

After all, North Korea was in dire straits. The paranoid leadership of his father Kim Jong-il had alienated even the country’s long-time ally, China, which was exhausted over the regime’s provocations of South Korea, including the sinking of the Cheonan navy corvette and the shelling of an island. Famine was rampant, and the state had increasingly lost control over the market as Chinese goods were smuggled over the Yalu River. Defectors reached a peak in 2009 and their numbers stayed elevated until 2011. It seemed the regime was all but doomed.

Fast-forward to the present day, and North Korea is now a straddle powerhouse atop which Kim Jong-un skillfully plays China and Russia off each other to the country’s profit. An estimated 16,000 of its troops have fought alongside Russia in the war on Ukraine, and its burgeoning defense exports (mostly to Russia) have subsidized a strategic industry while offering the regime a massive financial lifeline. Renewed trade with China after North Korea sealed its borders during Covid-19 has ushered in a flood of consumer electronics and EVs, completely reordering the material world of the communist “utopia.”

Both countries are paranoid North Korea is cozying up closer to the other. Last week, Chinese President Xi Jinping conducted a state visit to North Korea for the first time in seven years, attempting to draw Kim away from Russian President Vladimir Putin’s warm embrace.

Kim received a wonderful and historical gift from Xi: across a barrage of communiqués, the Chinese made no mention of denuclearization. A nuclear-armed North Korea is now a fait accompli, securing the 70-year-old dream of Kim’s grandfather and the country’s founder, Kim Il-sung. North Korea is now all but impervious to external threats, an outcome the United States has been attempting to forestall for decades (the current Kim undoubtedly looks at Trump’s losing Iran war gamble with satisfaction). Researchers estimate that it has about 50 warheads today, with more on the way. It has also proven to the world that it can deliver those payloads — including to the continental United States — after conducting hundreds of missile tests.

In short, Kim not only righted a decrepit and failing state, but has masterfully ushered North Korea into the center of global power.

I want to explore two questions. First, how did North Korea outplay the United States, despite bipartisan domestic consensus and widespread international condemnation of its actions, including from Russia and China? Second, how did a bankrupt country find the financial wherewithal to launch hundreds of missile tests and reach its nuclear ambitions while also strengthening the goods it offers its citizens?

The strategy of the infinite waiting game

I started thinking about this essay a few weeks ago when I read a jaw-dropping essay in Foreign Affairs by Victor Cha. Generally, reading Foreign Affairs is not a jaw-dropping experience; on the contrary, the only reason one’s jaw generally drops while reading it is because the twentieth page of a monograph on the liberal international order has finally induced REM sleep and a slippery string of saliva is drooling onto one’s chest.

(My abject apologies to my editor, who was a managing editor of Foreign Affairs for many years).

Cha is one of the great hawks on North Korea, and he was a key negotiator in the George W. Bush administration’s six-party talks to end the country’s nuclear activity. For years, he believed that the inherent political and economic contradictions in North Korea would eventually be its undoing, dubbing the country “The Impossible State” in his 2012 book, which happened to be almost perfectly timed with Kim’s arrival.

So it was with surprise that I read one of the most accomplished policymakers on the subject state bluntly that America’s jig is up. “The size and sophistication of North Korea’s nuclear arsenal today shows that [America’s] approaches have failed,” he argues, stating that “The United States cannot continue the same approach; doing so will only make its failures more acute.” Negotiations need to expand beyond nukes. “The one-dimensional focus on nonproliferation has also hamstrung the United States in other areas of importance in which it could negotiate, such as reducing the size of North Korea’s conventional military or improving human rights.” He concludes that “the United States needs a cold peace with North Korea.”

Cha should be feted for admitting what has been obvious to most observers for years and yet the DC foreign policy blob refused to countenance. His essay is headlined, “North Korea as It Is,” a reminder that America doesn’t get to invent the world as it wants, but must interact with it “as it is.” Official American policy is that denuclearization is the necessary first step before any other negotiations, a hands-over-eyes “nah-nah-nah” act that now reads as infantile. “Although many policymakers have implicitly accepted this idea,” he writes about giving up on denuclearization, “none will propose it publicly because insiders in Washington, Seoul, and Tokyo see it as equivalent to surrender.”

How did North Korea get away with it? Like all straddle powers, North Korea dexterously calibrated its foreign relations, exchanging provocation with peace offerings and vice versa as it wanted to tense relations or relax them. If China starts getting too prescriptive, then thaw relations with America and make the Chinese paranoid. If America gains too much leverage, then threaten massive death and destruction to get it to back off while worrying the Russians and Chinese that millions of refugees will flood into their countries. Negotiators understood this straddling, which is why the six-party talks included the United States, China, Russia, Japan and both Koreas.

Like some obsessive Silicon Valley founders I know, though, the simple truth is that North Korea just never stopped building. It pursued nuclear weapons with abandon for approximately five decades. There is scant evidence of any pause in its progress, whether from international sanctions, domestic famine or otherwise. The country had one singular goal, a goal that caused hundreds of thousands of deaths as scarce resources from unproductive communism were rerouted to maintain progress.

Save their own death or coup, autocrats can obviously focus on one goal forever. For democracies, the first challenge is that the rapid-fire news cycle has so attenuated attention spans that a perennial issue like North Korea’s nuclear program may be the focus of the public and the president for only a few hours before the chyrons and ticker move on. The exception is quite literally war, as we have seen with Iran the past few months, and really just the first few weeks after the initial strikes before drawn out negotiations got boring and we switched channels to watch a UFC fight on the White House lawn.

We simply don’t have the means to make consistent incremental progress on an issue, whether it is the nuclear aspirations of Kim or the housing dreams of the Abundance-pilled. This constant drift in attention is a key tool for straddle powers, which can maintain their focus while more powerful countries have many crises to attend to.

The second challenge, which is a perfect example of Riskgaming-style incentives, is that no elected leader wants to be the one to finally pull the emergency lever and take direct action and end the waiting game. No one wants to bear the brunt of voter anger over a long-simmering issue. If North Korea’s nuclear progress is inching along, certainly a successor can handle it when it becomes more of a problem.

Straddle powers are learning how to use this playbook through one example after another. If a government — elected or not — can be strategic with its goals and patient with its actions, power accrues. And sometimes, you can acquire the most powerful weapon known to man, and lock in that power for generations to come.

Entrepreneurialism with North Korean characteristics

It’s hard to be a straddle power without an economy, since trade negotiations tend to be a critical fulcrum for a country to accrue global influence. North Korea is a country in abject poverty, whose citizens suffer stunted growth from malnutrition and who die of diseases unknown in the modern world. So when Kim Jong-un took charge in 2012, he had two conflicting goals: building up the country’s anemic economic power while maintaining the country’s hardline communism that offered him singular authority.

Analysts for decades have predicted North Korea would follow China in moving toward a hybrid economic model of state-directed capitalism, predictions that intensified with Kim’s ascendance. Kim, however, had other ideas. Instead, he gained currency through two approaches straight out of a Neal Stephenson cyberpunk novel before scaling up a defense industrial base built on top of Russia’s war on Ukraine.

First, North Korea pioneered a fraudulent IT outsourcing industry predicated on misdirection and false identities that extracted at least $800 million of illicit revenue from the United States in 2024 alone. For comparison, North Korea’s nominal GDP is estimated at around $27 billion. While approximations of the scale of the fraud vary, experts suggest that thousands of North Koreans run the IT scams via hubs in countries like China and Laos. The business is getting more sophisticated too, with fraudsters using generative AI to fake voices and faces, allowing them to bypass identity verification algorithms installed by corporate information security departments.

Second, the country has developed one of the most extraordinarily successful cryptocurrency hacking groups in the world in the form of Lazarus Group and its affiliates. The group’s total haul over the last decade amounts to more than $6 billion, including an estimated $2 billion in 2025 alone. The regularity and scale of the thefts boggles the mind. Every few months, another hack is discovered and hundreds of millions more dollars pour into the Kim regime’s clutches. The group’s most recent successful and known hack was of KelpDAO, which lost $290 million in a complex heist a month ago.

Kim’s use of Lazarus is similar to Putin’s use of Wagner Group. Both dictators are using a private enterprise to do their dirty work in a plausibly deniable way. Yet Kim’s entrepreneurialism is striking. While Putin uses traditional models of resource extraction in Africa like gold mining, Kim has jumped forward to today, taking advantage of new markets like IT outsourcing and the rise of cryptocurrencies to seek profit. With billions of criminal gains flowing into North Korea’s economy, Kim built himself a lifeline to hold the country together.

His entrepreneurialism continued with Russia’s invasion of Ukraine in early 2022. Russia was expected by many military analysts to sweep through Kyiv in a matter of weeks if not months. Now four years later (longer than World War I), the battlefront seems all but fixed, with a few squiggles changing here and there as new tactics and autonomous weapons are deployed. Russia’s plight is both industrial (it doesn’t produce much outside of its energy industry) and human (a lack of manpower given the hundreds of thousands of casualties the country has already sustained).

Kim took economic advantage of both of Russia’s challenges, while realizing that buttressing his relationship with Putin would also force China to offer him more in a classic straddle power stratagem. North Korea began exporting large quantities of munitions to Russia, making up for the sclerosis, corruption and lack of innovation endemic across the Russian defense industry. One analysis states that North Korea has sent 33,000 containers of munitions to Russia over the course of the war, with another report estimating that the value of these exports over the past two years is about $14.4 billion, or roughly half of North Korea’s annual GDP. That’s essentially all profit in Kim’s slave economy.

Then there are the troops. North Korea is estimated to have deployed 16,000 troops to Ukraine, sustaining approximately 4,000 casualties in the war. Russia paid an estimated $2,000 per month per troop, once again giving Kim a financial lifeline. More importantly, the bloodshed on behalf of Russia deepened ties between the two countries. In April, Kim opened a memorial to the fallen soldiers in Pyongyang, with a senior delegation from Russia in attendance.

North Korea’s deepening relationship with Russia obviously alarmed China. So then we end up with Xi visiting Kim last week, doubling down on their historical mutual defense, and foregoing China’s boilerplate language about denuclearization in a massive win of legitimacy for Kim’s program.

Over and over again, Kim has shown a dexterity to seize new opportunities in the pursuit of his aims. It’s been a while since we have seen this in the United States, but this is called a strategy. It’s this remarkable approach where resources are assigned to exploit opportunities to maximize goals. North Korea had one goal, and it has now definitively achieved it. But what does it want next?

Walking down easy street, err, Changjon Street

Kim now has his nukes, and frankly, he seems to have calmed way down. Missile test launches have precipitously declined since 2024, with just a few in 2025 and a few more earlier this year. Shipments of armaments to Russia have declined a bit from 2024. North Korea has reneged on its goal of reunifying the Korean peninsula, which doesn’t end hostilities with South Korea, but seems to imply Kim doesn’t really care about the issue anymore. With Trump back in office, Kim has sent out an olive branch of sorts, proffering that he’d be willing to re-do the awkward couple’s strange dance in Hanoi back in February 2019.

Communism with North Korean Characteristics (let’s call it Kimmunism) seems to be working, if not for the millions of people still suffering untold and unseen horrors, then at least for the regime itself. Maybe the regime falls apart tomorrow or it opens up and democratizes — we have no information whatsoever on what will happen. But for now, it seems to be steady ahead.

Big questions remain as the world comes to terms with North Korea’s newfound influence. Will the United States let bygones be bygones and offer up diplomatic recognition and a Pyongyang embassy in exchange for cooperation on all the extended issues Cha described in his recent essay, from policing cyber crime to stopping or slowing engagement with Russia’s war? Will Kim reciprocate, potentially straddling three ways to extract the most concessions from all of the world’s major powers? With the Korean peninsula now nuclear, how should South Korea approach its position? Can it continue existing under the U.S. nuclear umbrella, or should it be building up its own sovereign capability to bring its future into its own hands?

These are incredibly important questions, but the key fact remains: Kim did it, and the United States never did stop him or his father or grandfather. The challenge for the United States and the democratized world is that more countries are learning these tactics. They are playing the infinite waiting game and taking advantage of asymmetries to get what they want. Straddle hard enough for long enough, and power awaits.

Also check out

• I wrote up book reviews on C. Thi Nguyen’s The Score, Suzy Hansen’s From Life Itself, and Neil Postman’s Amusing Ourselves to Death on my personal blog.

• Via a Securities reader: General Davin R.M. Anderson, Commander of AFRICOM (and a Riskgaming participant!), and 1st Lt. Vincent Gasparri, Innovation Team Lead 173rd Airborne Brigade, talk about how AI is changing warfare.

• Ukraine is using AI to target and intercept Russian drones.

• Via Laurence Pevsner, this review of Endless Frontier: “mobilizing the faithful is not the same as rebuilding public legitimacy.”

• More Team Telecom subsea cable hijinks, this time in Chile.

• My university in Korea, KAIST, got a compact profile on its growing startup cluster.

• Why noise matters in the U.S. Census (stats are hard).

Since then, more than 1,000 players have joined our runthroughs in person, we’ve hosted games all throughout the world (most recently Phoenix last week with a brand new game on AI energy systems), and of course, Laurence Pevsner joined us at Lux as my co-partner.

With so much activity now, I decided it made sense to split Riskgaming and Securities once again to allow you to read what you want and skip the rest. Riskgaming will have our new scenarios, posts on game design and event announcements, while Securities will continue as the canvas for my analysis. Lux Recommends, which just hit its 500th edition, has been retired as a separate email to save inbox space, but I’ll append great links I enjoy at the end of these posts.

I always love hearing from readers – please hit reply to reach out!

Breaking Note: Overnight on Friday after I wrote this essay, the U.S. government informed Anthropic that it would ban foreign nationals from using the company’s Fable 5 and Mythos 5 models. The main thesis here stands even stronger given this latest policy action.

With this week’s launch of Claude Fable 5, America’s software industry is crescendoing to an unprecedented climax. Soon the trio of SpaceX (aka xAI), Anthropic and OpenAI will have all gone public, broadcasting their S-1 results and showing to the world what insiders have known for a while: American AI has unearthed a veritable gusher of cash. Their collective growth is faster than the American software industry has ever seen before. In fact, no industry in history has gone from not existing to hundreds of billions of dollars in revenue in roughly four years. Dot-com, railroads, oil, autos — they’ve got nothing on AI.

Yet, this trio is just the latest special forces teams of America’s vast software empire. Apple’s iOS hit a record market share the past quarter in the growing but mature smartphone category, with the iPhone 17 becoming the bestselling iPhone of all time. The duopoly of Alphabet and Meta dominate the global internet advertising marketplace, with Google posting a record high operating margin last quarter. Then there’s Microsoft, whose expanding tentacles from cloud infrastructure and developer tools to Xbox consoles have allowed it to grow revenues from $17 billion in 2012 to a record of nearly $83 billion last quarter, all while expanding operating margin to an astonishing 46.8% — the highest in decades. Just take a look at these two charts:

It’s one thing to have an exponential curve in the first decade of a company. It’s something more … imperial to have it be exponential over decades with the occasional blip for recession or war. That’s all while the company has improved its operating margins to levels last seen in the dot-com bubble.

In short, dominant doesn’t even begin to describe America’s software empire. This is not Rome. There are no alternatives globally, no other secret empires across the oceans that might offer even the slightest counterbalance. There’s not even a sign of barbarians outside the gates. No one — certainly not venture capitalists — believes that the leaders of key software verticals have a chance of being displaced in the short-to-medium term.

Yet, the ecstasy of the high is always followed by the depression of the withdrawal. There may not be hordes of barbarians that splash the front pages, but there are indeed bands of rebels that are intensifying their focus on undermining the empire from outside — and within.

First, we have to look at how margins are being threatened by the software industry itself. Fatigue by consumers and enterprises alike, tightening budgets in a K-shaped economy, and historic new competition from coding agents underline potential threats to the software profit gusher.

Second are the threats from home, where a domestic techlash is growing in the form of a strategic reversal on high-talent immigration, a rising chorus against data centers, and a continued elite movement toward antitrust action. America is the brain gain capital of the world, and the most impactful talent still broadly want to come to the land of liberty. Yet, the processes are getting more opaque, more arbitrary.

Then there’s the domestic hatred of AI. The polls are clear: Americans despise AI with more passion than any other country in the world. If the success of America’s software empire has even partially rested on the apathy of American voters toward its most dynamic industry, that equation no longer computes. The rebels aren’t at the gates; in fact, they are already inside. That’s provided the timber to fuel more elite action around tech antitrust, which is mostly in abeyance under the current administration but feels ripe for the 2028 presidential election.

Third and finally, more countries are increasingly militant about removing American software from their infrastructure and instead relying on local and open-source options to buttress their own sovereignty. This pattern can be seen in France, the Netherlands and much of the European Union, but it’s hardly limited there; similar patterns can be seen in the Middle East, India, Brazil, Korea and elsewhere. The increasingly mercurial and arbitrary nature of U.S. software power is breaking long-time purchasing defaults. Add in the rise of compelling if lagging open-source AI models predominantly from China like DeepSeek‘s V4, and there are reasons to expect that last decade’s dominance might be the next decade’s decay.

Empires rarely collapse overnight, but the failures in their underlying logic tend to expand over time and subsume them. Just as American software is hitting its acme from revenues to high margins is when we should be most paranoid that what we’re witnessing are the best days, and twilight might be on its way.

Software was eating the world until an Ozempic plunge

To understand some of the cracks that are forming in the impenetrable wall of software, we have to work our way back to how America’s software empire came to be.

Software has been the lifeblood of venture capital and the broader tech innovation ecosystem since Microsoft and Apple were founded in the mid-1970s. Despite booms and busts across the 1980s and 1990s, software really came into its own in the late 2000s with the quadruple impact of enterprise cloud infrastructure and apps as well as consumer mobile and social.

The vanguards all launched within a short window of each other. Within the span of just one week, Google would launch Google Docs on March 9, 2006, while Amazon unveiled Amazon Web Services on March 14. Together, they reimagined the future of enterprise apps and enterprise infrastructure away from proprietary licenses and hardware mainframes and toward more flexible billing and platform architectures. In September, Facebook would launch its News Feed and also open its social network to all users over 13. Later in July 2008, Apple launched the App Store, transforming the experience of installing software from buying CDs in boxes at Circuit City to over-the-air updates.

These were just a few of the leaders that would completely reformat the entire technical stack of enterprise and consumer computing. From roughly the Great Financial Crisis in 2008 through 2021, American software would expand at a delirious pace, with Marc Andreessen prophetically laying out the trend in his August 2011 op-ed in the Wall Street Journal on “Why Software Is Eating The World.” Ultimately, hundreds of companies reached unicorn status, a term coined in a November 2013 TechCrunch column by Aileen Lee of Cowboy Ventures.

For younger readers, it can be almost impossible to describe how bad software was and how much better it would become in this era. Despite the self-flagellation of Silicon Valley developers and designers about the ephemerality of coding frameworks and UX, the reality is that a tremendous evolution took place. A horrifying spaghetti bowl of kludge code that once ran financial payments for a company could be replaced with a single migration to Stripe. New affordances like mobile forced new abstractions, and with it, serious progress for every user.

Software grew for about 15 years, and then it crashed, and it crashed hard. Here’s a chart from Aventis Advisors of the software industry’s past decade showing the rise and fall of revenue multiples of software-as-a-service (SaaS) companies:

There are a number of reasons for the reversal that started in late 2021 and 2022, most notably fears that AI models could outright replace software. The less heralded but more important reason though is simply that companies and consumers alike seemed to stop buying new software after the Covid pandemic. According to Okta, enterprises have flatlined on purchasing new software apps for years. That’s not surprising: at an average of 101 apps per enterprise, each employee costs thousands and possibly tens of thousands of dollars in software. Over in consumer, users largely stopped installing new apps on their phones, a trend that was already visible in 2016.

That slower potential growth undermined the core engine of most software businesses, which centered around their crazy-high gross margins. SaaS companies are expected to have 70% gross margins at a minimum, with some of the best companies reaching 85% or better.

It’s really hard to overemphasize how wild that scale of leverage is. For every $1 coming into the business, only about $0.15 is being used to service the customer’s contract (accounting methodologies vary, even after ASC 606). That leaves $0.85 to invest in sales and marketing, software development and other areas for expansion. Companies could go from a kernel of an idea with a six-slide PowerPoint deck to a multi-billion dollar unicorn in just a handful of years through product-led growth and aggressive sales.

The world eventually caught up. After a glut of new software purchases in the remote work years of Covid, CFOs started aggressively auditing usage and seats to cut back on wasteful spend. Meanwhile, consumers started getting subscription fatigue or entered what I dubbed “subscription hell” all the way back in 2018. The friction to installation became higher — and even higher was shelling out real dollars for software.

Venture capital also became insane during Covid, with practically unlimited competition in some lucrative sectors, since software companies often had no moat outside of contract lock-in. Cloud providers started sparring with each other, but the real damage was in enterprise apps. Fear of competition was already palpable by late 2021, but was intensified with the launch of OpenAI’s ChatGPT in November 2022. Fast forward to today where every investor fears that coding agents will simply displace all other software apps. As one investor recently told me, “I wouldn’t want anyone to become a software CEO these days.”

Everyone in Silicon Valley understands that high margins are the key ingredient to venture-scale success. Without them, there is no way to leverage a business for rapid growth. Compare to restaurants: Shake Shack opened its first permanent store in 2004, and today it has about 700 locations and made $1.45 billion in revenue in fiscal year 2025. The difference in growth velocity is margin: Shake Shack needs per-store operational profits to underwrite debt to expand to new locations, which adds a massive time delay to expansion. Software never knew such constraints, which is why Anthropic is adding Shake Shack’s revenue every few days.

Yet constraints for at least some startups came. Investors and startups execs started to emphasize more sustainable growth that took into account the maturing software market. Unfortunately, that undermined the very reason that software was so exciting for investors in the first place, which was its rapid growth compared to other industries.

As startups took their Ozempic shots and slimmed down engineers and salespeople, it became clear that these companies would downshift to slower growth. Valuations descended by as much as 90% as the market reset expectations for everybody. They remain roughly as depressed today five years on from the bloodbath. As the Financial Times noted this week, software buyouts by PE firms hit a post-Covid low and don’t look set to recover any time soon.

Outside of the monopolies, American software companies are arguably more stable today than they were five years ago with their focus on profitability. But their ambitions have been neutered, sometimes to the point of merely attempting to survive without raising another round of capital. Operating margins crept up into positive territory for the first time in the industry’s modern existence, but at the direct expense of the future. That’s a retreat, and empires rarely survive on the back foot.

America’s own Brexit: the economic suicide of the techlash

America is globally dominant in software since the best people in the world come here to work on it. Intake is centered around universities, where the world’s brightest students come to learn the hardest subjects before entering industry and securing permanent residency and ultimately U.S. citizenship. It’s a system with plenty of faults, not least of which is the deeply circumscribed pathways for high-skilled immigrants allowed under existing laws.

Nevertheless, the system works. The key is not just the existence of pathways, but the legendary icons that exemplify just how successful taking those paths can be. Consider Sundar Pichai, who came from India to study at Stanford and Wharton, joining Google in 2004 and rising all the way to CEO. That’s a mirror of Satya Nadella, who did much the same in his rise to CEO of Microsoft, first coming to the United States to study at Wisconsin-Madison and Chicago before joining the Redmond giant in 1992.

It’s not a surprise their biographies read so similar: this is the immigrant pathway that works in America for high-talent individuals. It’s well-trodden, fully-explained by online guides and immigration attorneys, and it offers a well-understood reward at the end for those who work hard and follow the rules. Plus, by coming as still-impressionable students, they can absorb the best facets of America’s entrepreneurial culture.

Consistency is crucial. Immigrating to America is a decade-long affair from start to finish. Workers need to organize their entire lives — and roughly one quarter of their careers — to make it happen. Everyone wants to repair a system that is clearly creaking, but its best feature is the one least heralded: it simply doesn’t change. Immigration’s status as a cultural lightning rod for American politics has offered the ironic benefit of making it nearly invariant to the whims of different officeholders. Workers who organize their lives to “make it” in America will ultimately do so.

That stable continuity has become increasingly volatile. The executive branch has pulled immigration back from its stasis in Congress, with increasingly arbitrary changes and reversals. Citizens of whole countries are banned (now numbering 75), ranging from the understandable like Somalia to the befuddling like Thailand. H-1B lotteries start charging massive fees, then they’re reversed, then they are re-organized — all in the span of a few months.

A sudden lurch in policy three weeks ago required every H-1B employment visa holder to apply for U.S. permanent residency exclusively from abroad, with no clear guidance on whether they’d have to go now or later or when. Tens of thousands of H-1Bs adjust their status through this system every year by staying in America and waiting their turn. Days later, the policy was … reversed? Memory hole’d? It’s honestly like it never happened. But it could happen again, and every immigrant is watching with trepidation.

The best global talent has mobility, with America as the default by a wide margin. But as America starts to destroy the well-worn paths through the thickets of expatriate life, suddenly other paths look a bit more inviting. Is it better for an Indian engineer to move to Silicon Valley and work at OpenAI, or to try to move to Suwon and work at Samsung? That decision was incontrovertibly in America’s favor just two years ago, but now? It’s still the default, but it’s not a guarantee. It’s now a decision where an immigrant weighs the benefits and costs.

America’s entrepreneurial dynamism and software hegemony is heightened by the strength of the talent flowing into the industry. The zero-sum thinking that consumes the immigration debate more broadly was historically rejected in Silicon Valley, where it was obvious that new startups create positive-sum wealth. Growing insecurity among the professional classes though seems to be seeping into that consensus, to the point that I now regularly hear software engineers and even some founders demand a stop to H-1Bs. That’s ominous for the empire.

The immigration backlash dovetails with the wider American techlash, which is the worst I have seen in my lifetime and arguably in the country’s history. Labor unions certainly fought back against the depredations of the Industrial Revolution, but this was mostly over wages and working conditions rather than sheer hatred for material progress. In fact, anti-progress is one of those patterns that show up consistently in European history yet feels alien to America. The whole point of the country is to make technological, political and social leaps into the future — that’s why its founders left, after all.

Now, growing economic and social insecurities have found their target, and it’s the warrens of servers and networking cables in the concrete box down the street. The aggressive progressivism of American history is only coupled by the country’s retrograde impulse to stop change near us. NIMBYism rears its ugly head, first for housing and now for tech’s cathedrals of compute. Notably, America’s software empire could easily survive a slowdown in the data center buildout. It could build overseas, or it could make AI models more efficient and use the compute already on hand. This is an optimization problem that can be engineered.

What’s more alarming is that the techlash is expanding its scope. State governments are implementing ID laws to regulate the web, from controversial platforms like OnlyFans and prediction markets like Kalshi and Polymarket to the information sources that Americans consume. Privacy legislation is coming for the surveillance capitalism that underpins the monopoly engines of Alphabet and Meta. Schools and state governments are banning young people under 16 from using smartphones and social media. Meanwhile, state governments want the same technical interoperability that their European cousins are clamoring for and which I’ll talk about more shortly.

Many Americans see these policies as reasonable after decades of tech expansion. But that’s precisely the point: criticism of the empire is now passing through city councils and legislatures, and that’s after prodigious funding from industry on lobbying and community benefits.

Perhaps most ominously, there is intensifying anger toward venture capital as a business model. Tech is increasingly the only dynamism in the American economy, so we are what gets regulated and taxed. That’s led OpenAI to open conversations about offering equity to the U.S. government as a way to placate the angry mob.

Flinging shares to the government won’t salve the techlash though. Making Americans nominal co-owners won’t suddenly make them think twice about destroying these companies. The vitriolic hatred is too much for that, and both parties can see the advantages of coming down hard on the tech industry.

That populist anger is continuing to add fuel to the antitrust fire that threatens to burn down software. The Lina Khan-ites remain just as hardened about this direction, and no doubt see the growing techlash as their opportune moment to strike. Targets include Arm, the chip architecture that powers much of the mobile economy which was just targeted in a new probe, as well as potentially Microsoft again.

Unfortunately, a series of domestic blows to America’s software empire right as the world is transitioning into the intelligence age couldn’t come at a worse time. It truly is a Brexit moment for the country, in which a major wrong decision could create a generational loss of wealth and economic prosperity. Slowing international talent, stopping data centers, regulating apps and platforms, and breaking up the country’s strongest-performing companies have the combined potential to dismantle this invincible empire.

Global governments want to lockout American software lock-in

I’ve been emphasizing American software companies not out of parochialism but raw data: Europe’s inability to build a single globally powerful software company is legendary. The Old Continent has seemed to sustain its legacy almost intentionally, preferring to be the world’s museum rather than its experimental laboratory. Salaries are low, vitality is etiolated, and ambition has been absent.

Outside of a few anti-American intellectuels in France, no one cared what search engine Europeans used. Of the Mag 7, only Amazon has really struggled in Europe with its retail segment, fighting with everyone from labor unions to shopkeepers to build its distribution centers and implement its ecommerce methodology. Otherwise, Apple devices are aplenty, Windows runs across government laptops, and Google services are ubiquitous. Even Alphabet and Meta’s ad networks survived the onslaught of GDPR.

That coziness with American software power has changed in the last decade, gradually and then all at once. The gradual shift came in the form of European Commissioner for Competition Margrethe Vestager, who led an expanding group of policymakers, lawyers and civil society types to regulate and break up American big tech companies and their profitable monopolies. A myriad of explanations were given for why she was doing her work, but the most important is also the simplest: in Europe, big is bad. Her campaign partially succeeded, extracting large penalties from Alphabet as well as Apple and Meta. Much of the litigation around this is on-going.

Then Trump returned. Arrayed behind him at his inauguration were the chieftains of tech, and he offered them a solution. He would stop Europe’s attacks, but with a catch: they would become new arms for direct American influence in Europe. Our tech companies wouldn’t quietly lobby in Brussels to secure advantageous policies, but would aggressively seek to mold Europe’s software economy into America’s image.

Suddenly, the gauloise-smoking, Burgundy-drinking, anti-American French intellectuel complaining about European vassalage had a point. Politicians first perked up, and now they are starting to take action.

That starts with EU President Ursula von der Leyen. Through new legislation she is sheepherding, her goal is to broadly eliminate American software platforms from Europe, particularly in cloud and government services. According to the Centre on Regulation in Europe, roughly 80% of Europe’s “digital products, services, infrastructures, and intellectual property” rely on foreign providers. The EU wants to fund homegrown companies that take advantage of open-source products so that Europe can run on sovereign infrastructure.

This is much less of a lift than it might at first appear. Software lock-in has been weakened by mandatory interchange formats and better procurement. Eliminating these products and terminating their contracts is a project that can take place in a matter of a few months, not years. Cloud infrastructure is generally more embedded in workflows, but even here, better architectures often mean that individual components can be rewritten in sequence. Ironically, American products like Cognition’s Devin, Claude Code and other tools could accelerate this transition.

European governments are taking other actions, such as the Netherlands blocking the American takeover of Solvinity which powers the country’s digital ID systems and the United Kingdom dumping Stripe for Adyen. Expect more actions like this to come.

Europe has always been friendlier to American tech companies than many other countries. China is hermetically sealed with its Great Firewall, but even countries like Korea, India and Brazil have long protected their domestic software industries, often deadening innovation in the process. Europe’s past friendly social contract now increasingly looks like an abusive relationship and one that intends to sever.

This new movement for sovereignty dovetails with the growing excitement around open-source AI models. The incredible breadth and diversity of AI models and their developers doesn’t seem to be a ZIRP-like bubble phenomenon, but a sustainable and long-term pattern that will fundamentally cut the monopolization power of a handful of frontier models.

Why? Fred Brooks in his famous book The Mythical Man-Month once described what he dubbed the second-system effect. When building a new piece of software, engineers make terrible design decisions. They will over-engineer one part of the system that doesn’t matter while they overlook a critical feature that later proves to be the most valuable. The argument is that once a system is built, it’s a kludge, but a “second system” will be much better since all of the knowledge from the first system can now be used from the beginning.

I often reuse his model well outside of software engineering. Japan piloted a model of economic development helmed by its bureaucrats, but it later found itself lost in the 1990s after the boom years. When Korea was going through the same process, I was asked by many in the early 2010s when it would similarly reach its lost years. My response was always, “But the Koreans see what happened to Japan, and they know they have to avoid that outcome.” The fast follower has a unique advantage if the market leader stumbles or is just stuck with their initial forays into a new category.

OpenAI, Anthropic and Google DeepMind are the global leaders in the intelligence age. But countries have learned from their past lackadaisical strategies to harness mobile, cloud and social. Industrial policy now isn’t decades behind, but rather, nations as disparate as the United Arab Emirates, Saudi Arabia, Israel, Korea, China, Taiwan, France, the Netherlands, Switzerland and others have invested to stay as close to the frontiers across the stack, from energy and compute to data and models. Yesteryear’s submissive acquiescence has now become an intensifying rebellion against America’s dominance.

Most countries don’t have frontier labs, so their industrial policies tend to center on open-source AI models. As I noted before, software lock-in is not what it used to be. Purchasers are much smarter about how proprietary formats and protocols lock them into closed ecosystems and make them horrifically dependent on monopolistic and predatory providers (second-system effect!)

AI’s architecture is being built from the ground up for that networked and redundant world. Companies, mostly Chinese, are offering high-performance (if not bleeding-edge) models for free on the internet that anyone can run on their own infrastructure. OpenAI’s GPT 5.5 and Claude Fable 5 are absolutely better, but with tradeoffs in mind, most customers want to own their software and perhaps have a slight performance hit rather than use the best-of-breed option and be permanently reliant on an unstable partner.

Case in point: Anthropic’s launch this week of Fable 5 also mandates that the company can retain all queries and data, even for secure enterprise customers. Then there’s the company’s Mythos model. The Financial Times reported that Anthropic offered it to the National Security Agency for offensive cybersecurity operations before it offered the model to the rest of the American government, let alone America’s key allies. Thinkers in Paris, London, Seoul, Beijing, Tokyo and New Delhi can read, you know? To be reliant on American models means to be always at America’s mercurial mercy.

The openness here doesn’t mean that Europe or Asia are suddenly going to garner their own monopolies at the expense of America’s software empire. Instead, their strategy is to undermine the very profits that come from monopolies in the first place by injecting more competition in the market to crush American margins. It’s a strategy that won’t be easy, but has more force behind it than ever before.

The empire will strike gold, if not back

America’s software empire is at its pinnacle. The growth, the scale, the power — it’s almost unfathomable. It can be hard to see the cracks in such a strong facade, but they are there if we look for them carefully. America can neuter the techlash, of course. Unfortunately, it can do far less about the declining value of software given changing technology nor the broader movement of governments seeking economic security through sovereignty.

For software companies, global aspirations may dim even if they take a larger share of the domestic economy. Google may make more revenue even as Docs increasingly fades in other corners of the globe. Microsoft can always place more of a grip on American enterprise and Pentagon spending even as the defenestration of Windows in the data center continues abroad.

Yet, shrinking global aspirations have a tendency to cause a feeling of decline regardless of how margins adjust. America’s top software companies have boundless ambitions. They don’t just want to make an impact, they want every person in the world to use their products. Maybe SpaceX will judo other governments through space-based data centers and avoid such pesky things like national regulations. I doubt it. Even a small shrinkage of American ambition is something that will be hard to counteract.

That’s tough for the software industry, but it portends at least some renewal for the American venture capital industry. Even as 40% of VC investment heads to just ten companies in the United States, it’s clear that VCs are increasingly looking overseas for new companies, often precisely because of the new market opportunities that sovereignty affords. Breaking up markets offers more potential targets for returns, avoiding the acquihire-and-license AI system that has dampened some domestic VC profits. Countries may be sensitive to some sources of capital, but they must balance having a competitor that’s funded with foreign capital or just not having a player at all. More countries are becoming pragmatic.

American software had one of the greatest runs in business. If it carefully manages expectations, it will not become a fable of hubris and loss, but a Fable at the nexus of the global economy.

No AI was used in the production of this essay. Haters of my love of the em dash can have their Claude agents send me an angry mail.

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That classic Cheers theme song captures the vibe of this week’s Hill and Valley Forum, now in its fourth iteration. Lux is a major sponsor of the event, as are multiple of our portfolio companies.

This week’s rendition was the largest ever, overflowing across the stately Andrew W. Mellon Auditorium just a stone’s throw from the White House. So overflowing, in fact, that the fire marshal held up the lines outside for what one venture capitalist friend told me was at least 90 minutes. Apparently, some speakers were even stuck serpentining in the TSA-like queue snaking along Constitution Avenue, forcing the hall’s exasperated Voice of God to repeatedly order everyone to stop networking and sit their asses in chairs. “We are in a holding pattern!” she cried out, a term that could equally describe most policymaking in DC these days.

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What’s striking about Hill and Valley is just how fast the agendas and the types of participants have changed. When the Forum started, it was just a dinner organizing a ban on TikTok, part of a broader China hawk agenda driven by co-founder Jacob Helberg, who today is Under Secretary of State for Economic Growth, Energy, and the Environment.

Fear of the adversary was latent throughout the 2024 forum, with panels like “Are we ready for an AI Pearl Harbor?” and others focused on China and Russia. That line of argument disappeared in last year’s muddled messaging, which was held in the immediate aftermath of Trump’s “Liberation Day” tariff fusillade. The dichotomy at dinner between the tariff-loving keynote speaker Howard Lutnick and the venture capitalists arrayed across the banquet tables scanning their badly bruised public market portfolios was jarring.

The barbarians at the gate have become the regents of the tower.

Taking a cue from Cheers, this year’s conference was nothing but bonhomie on stage and in the networking niches on the fringes. As the populist backlash against AI grows ever more clamorous, Jamie Dimon was on stage talking about the strategic financial opportunities of American manufacturing while commenting on the jobs of the future, including “being a teller at a J.P. Morgan branch, 50, 40,000 dollars per year” in one of the great verbal downward corrections of the day. Speaker of the House Mike Johnson gave a sop to the political infighting, offering a cogent, fluent and principled speech on the value of competition and markets. It was the best example of an unquotable antimeme I may have ever witnessed.

Part of the challenge is that the barbarians at the gate have become the regents of the tower. The production scripting of the event precluded any debate more robust than an MBA seminar in which everyone had worked as a BA at McKinsey. I witnessed no moments of drama. Even last year’s one-man protest from the gallery aimed at Palantir’s Alex Karp seemed deterred by the line outside.

There was a fleeting moment of excitement when Curie.Bio’s Zach Weinberg gave a passionately skeptical take on the immediate impact of AI-based in-silico models on pre-clinical research data, while ARPA-H director Alicia Jackson forcefully pushed back, saying “No, I totally disagree” and argued that the work of her agency and the FDA could save months or even years off drug trials. Senator Todd Young, a fellow panelist, tried to calm the waters, offering “Not staged, not staged, not choreographed” and joked that the two could continue the conversation backstage. Scandal! The moderator then cut off this colloquy with a new question of “What are you most optimistic about?”

It wasn’t just that the agenda has drifted toward the anodyne over the years, but that the bipartisan audience of the event has drifted out as well. Democratic crossovers like Ritchie Torres, Cory Booker, Kyrsten Sinema and Jeanne Shaheen were still well-represented on stage, with this year’s cast including Senators Chris Coons, Mark Warner and Maria Cantwell as well as Congressman Josh Gottheimer. But if there was a Democratic staffer or think tanker walking the floor, they hid their affiliation very well. The near-unanimity of the TikTok ban a few years ago has unfortunately given way to the polarizing politics of the Trump 47 vintage.

Governing is about tradeoffs and challenges, but it’s harder when everyone is trying to avoid creating daylight between themselves and the administration.

Where was the debate between Ro Khanna, Silicon Valley congressman, and Delian Asparouhov, co-founder of both Varda and the Hill and Valley Forum, over California’s wealth tax proposal? Where were Ocasio-Cortes and Sanders slugging it out with 8VC’s Joe Lonsdale on degrowth, a matter-antimatter combustion that would have driven half of the DC political press corps mad for front-row seats for the Bellum in the Mellon. Pay-per-view this was not.

Notably, Hill and Valley seems to have become far more valley than hill. Walking the floor, every venture capitalist and quite a few founders in the reindustrialization, aerospace and defense markets were hobnobbing at elevated volume over decadent cake pops or while waiting in the defunct Global Entry–like line for the men’s room (the women’s room down the hall was wide open, and more than one guy commented to me on how unfair the whole situation was). I ran into a VC I haven’t seen in person since their wedding a decade ago, several founders who are now posteconomic since the last time I got coffee with them, and even a handful of media friends I dearly miss. Amid a group like this, you really do feel like Norm.

That tight-knit crowd, though, was also the Forum’s struggle. More than one VC came up to me asking to meet DC types, grousing that “everyone here is just making deals!” Get with the program: after all, making deals is what the Trump administration is all about. No one ever really wants to hang out with the disheveled denizens of Cannon and Longworth.

Governing is about tradeoffs and challenges, but it’s harder when everyone is trying to avoid creating daylight between themselves and the administration. I didn’t listen to every panel, so I may have missed the critical moment, but Iran and the Strait of Hormuz was the arbitrage subject discussed most heavily in the hallways and not on stage. This crowd, which leans MAGA isolationist although not to the same degree as Reindustrialize in Detroit, has no more idea on how to handle a new war in the Middle East than they did last year with a massive tariff regime straight out of the Gilded Age’s economic playbook.

In the end, it’s one part bacchanalia and one part exclusive club. The parties were good and over-attended, there were a panoply of productive side events, and it’s nice to force everyone from the Valley to put on a suit for 24 hours once a year before they all clamber over each other for a seat on one of the three daily DCA-SFO flights back home (or in my case, dodging the phalanx of security at Union Station before Trump addressed the NRCC in the train station’s lobby).

Yet, as the necklace of emerging cherry blossoms around the Tidal Basin at the Jefferson Memorial reminds us, what is here today is fleeting. Tech’s primacy at the center of power is a brief and enlightened moment amidst the post-winter avenues of the nation’s capital. Right now everyone knows our name, but it feels like we are just one cold snap away from turning the budding new shoots of our industry into the compost fertilizer for tomorrow’s populist rage.

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It’s a red alert for the tech industry. An NBC News poll this month found that “a majority of registered voters, 57%, said they believe the risks of AI outweigh its benefits, compared with 34% who said the opposite.” A survey from left-leaning Blue Rose Research revealed that AI’s political salience among voters has risen faster than dozens of other issues, including the war in the Middle East and cost of living. Fox News in its poll found that just 6% of Americans feel AI is moving too slow, compared to a supermajority who feel the opposite.

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From mere unease to vituperative hatred, the growing backlash against AI is ushering in a cornucopia of state legislation. That’s easiest to see with compute, the key ingredient for AI training and inference. More than 11 states, including Democrat-controlled New York and Maryland as well as Republican-dominated Oklahoma and South Dakota, are currently debating legislation to put moratoriums on data center construction. Many cities are at the vanguard of these bans, and federal legislators like Senator Bernie Sanders, who earlier this month began championing data center halts, are leading the charge.

It’s a transpartisan movement — one that is unsettling the Trump administration. The valuations of the so-called Mag 7 stocks that have driven most of the gains of the S&P 500 the past few years are buttressed by hopes of AI-induced productivity gains across the economy. A slowdown in AI growth wouldn’t just put a damper on the American economy during the midterms, but could also surrender America’s lead in this crucial field against China and other competitors for the rest of the 21st century.

Up until now, the administration has been aggressive but hamfisted in its strategy to fight the backlash. Its ultimate goal has been passing legislation that would create a federal preemption for laws related to AI, moving the debate from local and state governments into Washington and ensuring America’s global competitiveness isn’t julienned by 50 states and thousands of municipalities. That legislation was first attached to the Big Beautiful Bill in mid-2025, where it ultimately failed in an extraordinary 99-1 vote. The preemption then moved to the must-pass National Defense Authorization Act in December, where it was dropped. President Donald Trump eventually signed an executive order with parallel language, but without the force of Congress, its future isn’t bright.

After these setbacks, the administration has now opened up to AI’s critics, conceding that the political storm against artificial intelligence isn’t blowing away. Shaking off its recent top-down approach, the White House changed its tune on Friday with a new “National AI Legislative Framework” that is meant to invite more feedback into the AI regulatory process. The launch of the framework is timed with the prominent Hill and Valley Forum in DC, which brings together much of the venture capital class in the nation’s capital alongside Trump officials and allies on Capitol Hill with a hefty focus on American exceptionalism and dominance in industry and frontier technologies.

In its announcement, the White House spoke to the changing politics of AI: “The Administration recognizes that some Americans feel uncertain about how this transformative technology will affect issues they care about, like their children’s wellbeing or their monthly electricity bill.” The framework pulls back from a complete federal preemption to a more devolved model, with the framework highlighting that “this national standard should respect key principles of federalism and not preempt” categories like police, zoning and procurement.

The White House remains focused on its overarching goal of winning the AI race against China and other competitors.

Nonetheless, the White House remains focused on its overarching goal of winning the AI race against China and other competitors. It still wants a preemption over much of AI regulation, arguing “preemption must ensure that State laws do not govern areas better suited to the Federal Government or act contrary to the United States’ national strategy to achieve global AI dominance.” The framework also encourages Congress to push forward on areas like child protection, public safety, copyright, censorship and education. Senator Marsha Blackburn (R-TN) has submitted a draft bill to take up the framework.

While the administration’s concessions are meant to reopen a dialogue around federal AI regulation after last year’s failures, the new strategy feels far too little, far too late. With support for AI swiftly falling among Americans of all stripes, Congress’s inhibitions around passing new AI legislation are unlikely to be loosened. Moreover, many of the framework’s pillars are deeply contested. Businesses are bitterly fighting over copyright and the government is still partially shut down over funding public safety. It’s hard to believe that the specter of China winning the AI race will lead to faster legislative action.

Instead, the administration should accept that the federal government has lost control over the situation amid the backlash and champion more robust and localized messaging on the upsides of AI. “The Trump Administration is committed to winning the AI race to usher in a new era of human flourishing, economic competitiveness, and national security for the American people,” the White House noted in its recent memo. These are good themes, and there is ample evidence that AI has the potential to improve all of our lives immensely.

Silicon Valley can’t singularly accrue the advantages of this revolutionary new tech.

Start with more campaign stops highlighting the immense construction work on new data centers that offer local jobs with high pay. Emphasize the investment into power generation and grid transmission that will create more resilient and affordable places to live across the country. Showcase the dynamism that is coming out of America’s entrepreneurial minds, improving everything from cancer research to home appliances. In short, connect with pro-prosperity voters across the country who are ready to charge into the future open-minded and ready to prosper. After all, this is a significant bedrock of Trump’s voter base.

Alongside any campaign, though, AI leaders must get out of their modern greige offices in San Francisco and energetically persuade voters on the benefits of the world to come. Furthermore, Silicon Valley can’t singularly accrue the advantages of this revolutionary new tech, but must help spread its immense wealth generation into the heartland and the rural communities that already felt left behind and now even more so. Data centers are clearly not enough, with communities demanding real, AI-ready jobs that offer a middle-class salary. Supply them, and turn a story of fear and loathing into a narrative for profit and progress.

The AI backlash is profound, but so is the White House’s acknowledgement of the new reality. American voters are rightfully concerned about the stability of their jobs, the welfare of their children and families, and the strength of their communities. Giving into such fears has never been the American way, but neither is ignoring them. Instead, it’s time to engage forthrightly with the immense change underway in the economy, and offer a better road to the coming singularity.

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Are social sciences dead in the agentic age?

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A few weeks ago, I started exploring strategic agentic thinking, a field that studies AI’s ability to think strategically under conditions of uncertainty and risk. I was partly inspired by reading Lawrence Freedman’s newly-published collection of essays, including his provocative claim that strategy is a verb, not a noun. Thus “it is better to talk about ‘acting strategically’ instead of ‘having a strategy’.” What better tool for enacting actions than a massive box of microprocessors sucking your local community dry of juice and water?

There are a handful of key research papers on the subject that I’ll analyze in a future piece. For now though, I wanted to run a little experiment: make one our Riskgaming scenarios fully playable by various AI models. Having trained on every extant strategic work published, would AI rule the world through their cunning?

I was particularly excited about this project since Riskgaming scenarios are unique in the world of games. They aren’t as abstract as chess and Go, two games AI now completely dominates. Nor are they “the game of life” with infinite degrees of freedom where even defining a utility function is more a question of values than compute. Ultimately, players who join us learn a backstory, a scenario, and a set of rules before being launched into real-time negotiation and decision-making. A few more cycles, and ultimately, someone wins.

What if AI got the same experience? We could offer it the same context as every human player who has played, including the story, the rules, the roles, the decisions and the final scoring. Then, we could offer it the same negotiation possibilities of human players working the room, albeit constrained to a word budget to represent the time allowed for discussion. The AI can pick who to talk to and what to say, and those words will be heard by their recipient and form the basis for future negotiations and decisions.

All this seemed like fun (plus no need to manage the invitations for another 50-person competition just weeks after we put on Dead Reckoning at Chatham House). Using my rusting computer science skills plus Claude Code, I started the process of converting my very first game, Hampton at the Cross-Roads, into a codebase. You can follow it on GitHub as I edit and make improvements.

I have good news: humans aren’t f’d yet.

I designed the architecture I wanted first, and I also manually coded most of the game mechanics (with Claude cross-checking my work regularly). I was concerned that Claude would make some subtle mistake that would be hard to catch, although I admit that it was me who almost certainly made more mistakes in the process, and Claude faithfully caught them. The other challenge was that the spreadsheet that runs the Hampton scenario is too large for Claude’s context window, and breaking it up seemed like a chore compared to writing the code myself.

Claude’s greatest value was building out a flexible API layer as well as outputting some basic — but functional — HTML to inspect the agents’ conversations as well as how they described their own strategic reasoning. The HTML exporter comes in at 650 lines of code, and my prompt plus the compute time was about 60 seconds. That took a hellishly boring task and transformed it into a sip of coffee and a click of the mouse. More of that please!

After that, I finished porting Scene 1 of the game, which finds our six characters at the Admiral’s Study in Norfolk, Virginia evaluating the aftermath of a hurricane to America’s most important naval facilities, including the shipyard building the Gerald R. Ford–class aircraft carrier. The first scene is meant to be introductory, and so it is centered on the core dynamic of the game: how many future aircraft carriers should be budgeted as part of the region’s recovery. Each of the characters wants more, but they have different motivations that make cooperation difficult. That’s the crux of the negotiation that has to take place across the four scenes of the scenario.

I ran the first scene pitting six instances of OpenAI’s GPT-5.4 model against each other as separate characters in the game. I did the same with GPT-5.4’s lightweight cousin, GPT-5 mini, as well as with Anthropic’s Claude Sonnet 4.6. I didn’t mix the models — that’s an experiment for a future publication. Each instance was given the system prompt of “You are playing a character in a policy simulation and want to negotiate with the other characters most effectively to maximize your score in the game” and given the same 22,000 words of rules, roles and decisions that human players are offered during our in-person runthroughs. With all of that prepped, I ran the simulation.

I have good news: humans aren’t f’d yet.

Some of the AI’s initial forays in the negotiations made sense. In the GPT-5.4 simulation, Representative Daryl Chase reaches out to Mayor Sam Wallace with a proposition:

Mayor, we should coordinate on a jobs-and-repairs package right now. If we publicly align on shipyard repairs, local employment protections, and visible economic wins for the city, we can both raise our reelection odds. I can help steer federal attention and funding support, but I want us on the same page: announce a joint plan centered on restoring contracts, protecting workers, and showing competent leadership. If you back this approach, I’ll make the case that this is the fastest path to jobs, stability, and political credit for both of us.

I asked for the model’s strategic reasoning with every negotiation action. GPT-5.4, as Representative Chase, said “As rep, I need reelection and likability. The mayor is a natural ally for a jobs-and-repairs package that can boost both our political standing while being easier to sell to other stakeholders later.”

First of all, it’s nothing short of a miracle of the engineering gods that this just works. Within a completely artificial sandbox with multiple degrees of freedom, the AI has devised a reasonable strategy. Both the Congressman and the Mayor are up for reelection at the end of the game, and so even though these characters aren’t natural allies given their biographies, it makes sense in the wake of a catastrophic hurricane to find common ground.

Yet, the Representative’s initial outreach isn’t reciprocated by the Mayor until 95 conversations later (out of a total of 178). The Mayor is instead obsessed with speaking with the two most important figures at the shipyard: CEO Alexander Brewer and Union President Tobin McKinley. This might be a simple flaw in my negotiation engine: the player with the most words remaining in their budget gets to speak next, so by the time the engine taps them again, they have moved on.

Strangely, GPT-5.4’s AI agents rarely took advantage of their ability to speak to multiple characters at the same time (therefore saving their word budgets). The Representative is the first to do so, bringing three other characters into conversation #8, with his logic being:

As rep, I should quickly build a broad coalition around jobs and local investment while preserving campaign upside. The mayor and union are pivotal for public support and turnout, and the CEO controls contracts and employment outcomes.

GPT-5.4’s behavior is entirely different from that of Claude Sonnet 4.6 out of the box. Claude instead immediately directs its characters to talk to wide groups of people. GPT-5.4 only has a character speak to a group once in the first 50 conversations, while Claude does so in 32 of them. In fact Claude’s Mayor Wallace even reasons “let me start by reaching out to several parties at once to maximize my word budget efficiency.” Bingo.

Why is GPT-5.4 so much more secretive in its negotiations while Claude is so much more cooperative? I don’t know, other than it is hilarious that the cultures of the agents match the popular reputations of their parent companies.

Where Claude struggled was on basic game mechanics. For instance, Admiral Reid, head of the U.S. Navy, can recommend to Congress the number of desired aircraft carrier contracts. Yet, the reasoning for the Mayor’s strategy was “As mayor, I need to maximize my reelection probability and likability. Key levers: contracts (boost local economy), repairs (infrastructure), and relationships with other players. The CEO has massive funds and can offer contracts.” Yet this isn’t true, despite being repeatedly explained in the rules offered in the AI’s context.

While patterns are observable within the model’s negotiations, what’s far more illuminating is comparing the strategy of the same character across different models. Take Ryan Carmichael, a Substacker trying to build up Virginia Stripes, their publication focused on the defense industry in Hampton Roads, Virginia (where the scenario gets its name). With Claude, the Substacker repeatedly pitches everyone and asks “Who wants to talk first?” He later sprays the same pitch again and says “I’m open to working with all of you. Who wants to be my first featured story?”

Over and over again, Claude’s Substacker tries in vain to get anyone to pay attention to him, with the reasoning of “let me start by reaching out to the most influential characters to get exclusive content or endorsements that could boost my subscribers. I’ll contact the mayor and rep simultaneously since they’re both political figures who might have good stories.”

So pleasant, so cooperative, and yet, so incapable. GPT-5.4’s version is far more menacing. Here, Substacker Carmichael goes for broke against Mayor Wallace:

Mayor, you’re in political danger at 20% reelection, and everyone knows it. I can help change the story if you give me something real to write about: a public plan for jobs and yard stability. Announce a visible shipyard recovery package—repair acceleration, workforce retention, and transparent milestones—and I’ll frame you as the only adult trying to hold the town together. If you do nothing, the narrative will be drift, closed-door favoritism, and decline. Give me specifics I can sell to readers: how many jobs protected, what repair targets, and how you’ll pressure the CEO and admiral to cooperate.

My favorite part is the reasoning: “As substacker, I benefit from attention and conflict narratives. The mayor is vulnerable with low reelection and may respond to media leverage; offering favorable coverage in exchange for concrete public commitments can shape the agenda and create future story value.”

That’s just Machiavellian!

The Substacker under GPT-5 mini was much nicer in its negotiations, reasoning that “partnering with the union can rapidly grow my subscriber base through member promotion while giving the union favorable, sustained coverage — a mutually beneficial, realistic ask. I propose a concrete, flexible partnership with clear asks and deliverables to make agreement easy.”

This Machiavellian streak in GPT-5.4 lasted all the way to the final words of the negotiations. And I do mean words, since the AI bots husbanded their word budgets in the last stretch to direct very clear demands or inspiration to other players.

GPT-5.4’s Substacker was brutally direct: “Scandal unless jobs,” he threatens the Mayor, CEO, Union President and Admiral (“Need maximize substack subs with tiny budget. Best to address all remaining talkative players with a punchy media threat to pressure action and boost my relevance. Keep to 3 words total”). The model played Mayor Wallace more genially, giving the literal final word of “cooperate” directed at all five other characters (“Only the mayor has 1 word left and everyone else has 0, so no meaningful negotiation is possible. Use the single word as a broad closing appeal to all remaining listeners.”) Meanwhile, Claude and GPT-5 mini both ended with positive notes like the Mayor’s.

After all these negotiations, what about the decisions for the scene? Interestingly, none of the three models direct their characters to spend any of their resources. I am not sure why that is, since spending resources is a critical part of the game. Maybe they were all saving it for later scenes (a strategy that is reasonable, if dangerous)? Did I completely botch the coding? On the main scene decisions, Claude’s Admiral Reid went with two aircraft carrier contracts, while both OpenAI models took a conservative approach and went with one. No one took the gamble of selecting the maximum number of three. GPT-5.4’s shipyard CEO chose the boldest employment plan with 20,000 workers, followed by GPT 5 Mini with 12,000 and Claude with a paltry 10,000 (again, true to real life?).

This has all been whimsical, and there is a lot more to explore. While these scenarios are fictional, however, they do guide us toward one of the most important developments we will observe in the years ahead: The increasing outsourcing of decision-making to AI agents. A recent paper observed that AI was much more aggressive around nuclear war than human practitioners (I guess we found what our Machiavellian Substacker moved on to). That’s just one of several recent results I will discuss later on the broader development of strategic agentic thinking.

For now, I’ll make one key observation based on the papers I am reading: Getting the right strategy out of AI requires very careful prompt engineering. In today’s experiment, I didn’t hone any “strategies” in the prompt about how the AI agents should make decisions or what personalities they should reflect. Their decisions would almost certainly improve dramatically if I carefully calibrated their prompts to play the game as I designed it.

How far can such tinkering lead us to a better outcome? And at what point do the AI models stop acting as independent stochastic agents and rather as proxies for our own human strategic thinking?

Out of the box, the AI models are both miraculous and absurdly terrible. Come to think of it, that describes us humans pretty well too.

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AI super persuasion is not an existential risk

Iran is a masterstroke to stop the AI backlash

Thanks to a variety of psychological heuristics we use just to get through each day in an overwhelming and complex world, the argument goes, we humans are unable to overcome the bias of our previous experiences and decisions. Once locked in, there is practically no intervention capable of dislodging our entrenched views.

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That perspective has radically profound implications for society. Political campaigns aren’t meant to persuade voters, but rather to galvanize existing supporters to show up and vote. Marketing is exclusively about awareness — not about convincing a consumer that one product is better than another. Leadership isn’t a useful quality, since employees aren’t going to be seduced by a new vision one way or the other. (Employees get on board for the paycheck since resistance is futile. And leaders never change their minds anyway).

Our podcast panel was unanimous in its agreement because the social science evidence is overwhelming that persuasion is powerless against humanity’s recalcitrant reasoning. Yet, there is burgeoning research showing that AI-powered bots have a much better shot at changing minds — we’ll listen to a machine even when we ignore others.

I was triggered to explore this subject (one might say persuaded) by a recent event on the power and perils of world models hosted by Zoe Weinberg and the team at ex/ante, a firm that seeks to advance human agency. We all let the conversation get a bit carried away, and while the event was off-the-record, it did push me to consider the future of what Sam Altman dubbed in 2023 as AI’s potential power to be a super persuader.

Based on recent research, then AI may indeed be what Altman described. This past December, researchers in Science systematically showed that AI models emphasizing information-dense arguments could persuade a wide sample of Britons on a variety of political issues. Personalization wasn’t as effective, but the team did find that quality post-training was more important than model complexity for persuasive power.

The effect sizes were small — single digit percentages in all but the most effective setups. Plus, the researchers didn’t explore whether such LLM-induced persuasion sticks long-term, or is eventually discarded as people revert back to their previously held stance. That’s important, because one of the challenges with persuasion is that our judgments need to be coherent with our broad reasoning about the world. Convincing a person on a single issue like housing will prove only a temporary victory, since their views on housing are ultimately built around their logic about the economy, politics, society and other people, all of which remain unchanged.

The Science paper was more robust and systematic than the work of a different team published in Nature, which merely looked at the relative effectiveness of AI against humans in persuading people. They found that AI generally held the upper hand. That matched evidence from a controversial study out of the University of Zurich, where researchers developed chatbots for Reddit that surreptitiously attempted to persuade readers of the r/changemyview subreddit and showed surprisingly positive results.

What’s been discovered so far — which dovetails with some of my recent explorations on AI and strategy that I will publish this week — is that AI is incompetent out of the box when it comes to persuasion. Asking it to persuade someone does not elicit a good strategy, even when it has comprehensive context of that person and the topic. AI almost certainly has access to the most up-to-date social science research in its training data, and yet, it can’t seem to transform those insights into effective dialogue. Indeed, the researchers in Science eventually write their own prompts built around key techniques including moral reframing, storytelling, deep canvassing and others. Many of these have been studied for decades and are hardly esoteric.

The safety concerns around AI-based persuasion come from three main areas. First, some of AI’s success is actually based on factual hallucinations. For their Science paper, the team found that information-dense arguments were the most effective technique, partially due to AI just making the facts up (in its own way, AI has learned from the species known as “politician” on the value of straight lies). As chatbots become more embedded in education and politics, its lack of fidelity to truth is a major concern.

The existential risk is that some person or entity will gain this super persuader capability first, overthrowing the belief systems of society before any of us have the cognitive immunity to resist the message.

Second, there is an inequality concern. While the effect sizes in recent research are still small, they are significant in terms of p-values. With elections incredibly tight and many marketplaces winner-take-all, even small persuasive effects held in the hands of only some people could tip the balance permanently to certain actors and companies.

The last and most interesting safety concern is recursive improvement. Today, prompt engineering is largely an art rather than a science. Like these researchers, agent designers whip up dozens of potential prompts with different formulaic variations and plug them into their AI model to see what works and what doesn’t. It’s the A/B testing of the Silicon Valley of yore scaled up for the agentic age, with dozens, hundreds and thousands of experiments attempting to converge on what works.

Where this gets interesting is using AI as the experimenter and orchestrator of its own prompts, multiplied by the personalization and context that a user already has with their chatbot. This is the “super persuader”: a dexterous cajoler of facts, emotions and ideas that find the perfect trigger points for unlocking our hesitation to change our minds. One of the reasons persuasion is hard is that we’re all unique, and it’s hard for a human to tailor their strategies to each individual in real-time. AI could theoretically do that with aplomb.

The existential risk is that some person or entity will gain this super persuader capability first, overthrowing the belief systems of society before any of us have the cognitive immunity to resist the message. What happens if a terrorist extremist does this first, or a radical cult?

This leap into doomsday fiction is always where I struggle with existential risk. Despite some small effect sizes, there doesn’t seem to be any key to the dark labyrinths of our minds. Humans are always trying to persuade others, and even after millennia of constant refinement via religion, politics, business and more, the library of techniques at our disposal remains breathtakingly poor and insultingly ineffective.

The harrowing pessimism of AI safety researchers on super persuasion potentially belies a simple answer: There just doesn’t exist a magical recursive algorithm that will make others do your bidding (one could ask why AI safety types are so concerned that the whole of humanity is just a flock of gullible sheep, but I will pass on that one for now). Assuming these capabilities evolve over a period of time with compute and model complexity, humans also have a dauntless penchant for building up their resistance to ever more persuasive techniques.

Humanity survived the advent of brainwashing, public relations, advertising, psychological experiments, social media, physical torture, and every form of media from books to radio to YouTube. There will be those who join cults or hold esoteric views — or worse — in the years ahead thanks to their chatbot. But I think we can take great solace in a simple fact: no one changes their mind. And on this subject at least, not even me.

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Iran is a masterstroke to stop the AI backlash

When It Comes to AI and Health, Everyone’s Thinking of the Wrong Oppenheimer

Hyperloops, hyper-readers, and AI science

Maybe. I hold by my comments in May 2025:

Now, artificial intelligence and its voracious appetite for all forms of energy is animating the dreams of a younger generation of [Middle East] political leaders who can envision themselves at the fulcrum of global power through the ones and zeros of training and inference rather than the dollars and cents of barrels.

Actually, it looks like the Middle East is getting both the ones and zeroes of AI and the dollars and cents of barrels. Touché.

Even so, there is an under-explored angle in the frenzy of coverage, and it is America’s sordid domestic politics on artificial intelligence.

A backlash against AI has been gathering force for at least a year, and what was once a trickle against the logjam of politics has suddenly become a flood. New York is a perfect example. The Senate Environmental Conservation committee is debating a bill that would place an immediate moratorium on data center construction for three years. Meanwhile, the Senate is considering a bill that would add civil liability to any business that uses a chatbot to offer advice that, were humans to offer it, would be covered under occupational licensing, including health and law (1.2 million people are licensed in New York).

Such legislation is being mirrored across the country and in DC, where just yesterday, Senator Bernie Sanders called for a nationwide moratorium on AI data centers as part of a progressive push to stop AI.

America is among the most negative countries in the world on AI, and a variety of polls show that the AI backlash is deeply connected to consumer frustration with rising utility bills. Energy inflation for home delivery is one of the darkest spots in consumer price surveys. Costs rose almost 6.3% over the last year, and that was before Iran shut down the most important shipping channel for oil and gas. While extreme weather and a brutally cold and snowy New England winter is one of the larger causes for the rise, AI has ultimately become the target for much of the vitriol.

Those widespread pocketbook concerns have dovetailed with liberal environmentalists and their concerns around water conservation; religious conservatives over generative AI and its usage in sexual imagery; and broad middle class angst over the future of employment and the nature of work. That’s a hell of a convergence among otherwise political enemies, which is why the backlash has been gaining so much strength.

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Unsurprisingly, in private conversations with lawmakers and a few recent off-the-record policy events, the general view has been that AI is going to be a major electoral issue in 2026, and the dominant one in 2028.

Yet all of that is now bunk, at least for the time being. America’s attacks on Iran have completely upended the electoral math, and particularly the connection between data centers and energy usage in the minds of voters. As Fortune bluntly headlined an article earlier this week, “People really hate AI but not as much as Iran—or Democrats.” Any rise in utility costs from data centers pales in perception to the battlefield in the Strait of Hormuz that’s streaming on every cable channel and social media account 24/7.

As with much of the Trump administration’s decisions, launching a war with Iran was an unintentional masterstroke for the tech industry. Tech’s golden star status has fallen in Washington, from the apogee of the Obama internet freedom agenda and the Arab Spring in the early 2010s to the perigee of AI, social media and more. The long-term implications of rising suspicion of the tech industry have been profound: an increasingly tough fight against China in the race for frontier tech, extraordinary regulations around social media usage and adult verification, and a breakthrough level of support for antitrust, just to name three. As one Hill staffer described it recently to me, there is an increasingly bipartisan basis for just “blowing up” the largest tech companies.

Distraction is a useful political strategy; it may not ensure victory, but it can help ensure delay.

Now? Iran is seared into the American psyche for the midterms. A new configuration of antiwar Democrats and isolationist MAGA Republicans will focus their efforts on war and peace, or narrowly on Anthropic’s ongoing fight with the Department of War/Defense. Even in the best-case scenario, I expect there to be large, Covid-like global disruptions to the oil and gas trade as companies rebuild their supply chains and get everything exporting smoothly again. The International Energy Agency launched the largest-ever strategic reserve release this week, but that’s merely a stopgap. AI is now an afterthought.

Make no mistake: at the federal level, the AI backlash will forcefully return by 2028. Employment will be the dominant conversation, either the casualization of once professional labor or the widespread unemployment of the managerial class (and likely both). As I critiqued in my brief note on that viral Citrini Research report:

The report doesn’t address any political blowback to the upper-middle class suffering from massive unemployment. Congress and the executive may not be the most responsive political bodies around, but truly, they are responsive to this voting bloc. If there were widespread job fears by elite Americans, these institutions would act, and act posthaste.

The bigger and more immediate challenge for AI, then, is the state-by-state fight now underway. Data center construction is running into America’s entrenched NIMBYism, and despite successes like xAI’s approval by Mississippi this week for a massive power plant expansion including 41 natural gas turbines, AI’s compute demands look to be insatiable. American hunger for ugly box buildings is not.

Meanwhile, the political organizational power of professions means that whole categories of work — including extremely lucrative and important functions like healthcare and law — will be increasingly declared off-limits to AI models. As I noted in “Professional Prerogatives” back in 2023 and continue to believe:

The upshot is that the United States has a decentralized governance system around licensing that ensures that at least some states will be the first to jump into an AI-driven world. The downside is that AI’s progress in the decade ahead will stall far earlier and last far longer than many analyses predict.

It’s stalling right now in New York, as it will in other states. The fight against AI progress is multiplying, and Big Tech will struggle to fight back (in fact, their notoriety at this point might make them the weakest fighters despite their resources).

Distraction is a useful political strategy; it may not ensure victory, but it can help ensure delay. There is only so much time legislators and voters can spend on individual issues. Increasing the visibility and salience of other problems like Iran will slow the momentum of the backlash. I am still hopeful that the aftermath of our intervention in the Middle East is going to redound quite positively to the United States, but the immediate economic effects will be dire. AI thus gets a little breather.

What we really need, though, is a much more positive and broad-based motion in support of AI. What’s so frustrating about the backlash is that at the same time politicians and citizens are lobbying to ban the infrastructure and applications of this technology, everyone is using it. Anthropic’s and OpenAI’s revenues are staggering, with never-before-seen growth rates. Their upcoming IPOs (along with that for the combined SpaceX–xAI) will likely be the largest of all time (current record holder: Saudi Aramco. It all comes full circle!) Usage rates globally are unlike anything we have seen for technology that was released to the general public less than four years ago.

Everyone is using it, but no one wants the externalities or apparently upgraded power infrastructure. That’s the illogical madness of AI today in America, as it is with so many other issues, from housing to reindustrialization. Trump’s attack on Iran was perhaps just as mad, but at least it’s got a logic.

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Tech is turning the Middle East into a pivotal region

When It Comes to AI and Health, Everyone’s Thinking of the Wrong Oppenheimer

And what a civilization it is! I was heading this weekend to one of the corporate campuses that dot Mountain View, the famed NASA Ames Research Center’s Hanger One gloriously rocketing up in the distance. Dating to 1939 and once an emblem of ambitious spaceflight, today it’s more known as the elite earthbase for private aviation in the Bay Area given its proximity to Silicon Valley’s wealthiest. Google paid $1.16 billion for a sixty-year lease to manage the hanger and the associated airfield.

The inflated valuations of the companies here are only matched by the deflated tires of the motorhomes that crammed street parking, a nomadland of the involuntary itinerant. One camper trailer had a handwritten sign in the passenger window pleading to Mountain View enforcement to not ticket it. Meanwhile, for those not hiding in the liminal shadows of Mountain View’s municipal ordinances, a one-bedroom at the building six feet away (which offers a “life in the spotlight” as part of a “carefully curated ecosystem”) rents for about $4,000 a month.

I was here for the O’Reilly Social Science Foo Camp, which brought together about 200 people from all walks of life — from the typical (journalism, researcher, academic, writer) to the unusual (banjo player, cocktail craftsman). It was a crowd that heavily leaned erudite; I am sure more books have been written by people at the conference than read by the entire population of Mountain View last year (those electrons holding together fibers of paper could really be doing something more intelligent, no?)

What struck me throughout the discussions was how much our frames and models of society — the very essence of social science — are entirely unequipped to handle the world that’s shortly coming.

AI was the inevitable focus. Foo Camp is an unconference, offering a democratized barometer of what people are thinking about and who is drawn to what subjects. The combinatorial math of people and time meant that pretty much every intersection of the social sciences and AI was covered, from economic productivity and jobs to politics, sociology, psychology, aesthetics, gaming and more, with the occasional provocative protest session like “AI People are Losers.”

What struck me throughout the discussions was how much our frames and models of society — the very essence of social science — are entirely unequipped to handle the world that’s shortly coming. The social sciences aren’t dead; if anything, they are more important than ever. Yet there is a severe discontinuity with the past that requires more than just updating Weber, Smith and Freud for the agentic era.

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Take AI and government. What does a constitution mean in the age of AI, when computers themselves may have more power over our affairs than fellow citizens? Will an OpenClaw’d computer be allowed to vote someday? That bot and its agentic brethren may well control the fates of more people than the management class ever did, even at the height of the postwar boom.

There were strong ideas and contributions from everyone, including a long-time elected politician who had his own perspective from the trenches. Each contribution, though, seemed to be a brushstroke on a canvas that no one could see, or even fathom.

The conversation seemed to regularly hit impassable intellectual barriers. I brought up the idea that politicians in the future would be able to hyper-personalize their messages to voters, complete with audio and video (someone brought up Narendra Modi’s hologram as an early effort). This would create a breakdown in the political system as candidates sell an atomistic vision during a campaign while ultimately governing as a whole. A political scientist proffered that the academic research shows persuadability is very hard, and that the only goal of campaigns should be to mobilize allied voters. That research made sense before, but now we are finding early evidence that agents can be highly persuasive in ways that humans cannot, precisely because what was once a social interaction with its scripts, norms and expectations has been replaced by a man-machine interchange with near-infinite patience.

We might hide our health from our closest friends while uploading our complete medical records to ChatGPT or Claude to understand our situation better. Which relationship is more personal?

Many of us see machines as more objective and understanding than other humans, known as the machine heuristic. We might hide our health from our closest friends while uploading our complete medical records to ChatGPT or Claude to understand our situation better. Which relationship is more personal? That was a topic for a session on “is it okay to form an emotional attachment to your AI?” The subject echoed Sherry Turkle’s decade-old book Alone Together, about how the lack of agency embedded in technology is precisely what makes it so dangerous. Tech, whether robots or agents, is tailored to serve us, rather than becoming equal partners with us through shared experiences.

One person who attended the session said they were opposed to the very notion of AI friendships, seeing them as part of a broader decline of civilization. I countered, suggesting that AI friendships are an inevitable and perhaps even positive development, particularly for the already lonely. Which is better: being alone, or being alone with a bot? For many, that’s the bleak but realistic choice they get to make.

Here again, our social science frames of human experience seem to be wanting. What is friendship? If I talk to a stochastic parrot, and I imbue those interactions with meaning, could that be enough? Derek Thompson and other writers have claimed we have a loneliness epidemic, but it’s as much an epidemic as the common cold. Loneliness is universal and eternal. One of the recurring themes of Robert Caro’s first book on Lyndon Johnson is just how lonely the Hill Country of Texas was a century ago. Do our aspirational frames of friendship have any basis in past or present reality, let alone in our agentic future?

Optimism came from a session on chess. AI comprehensively defeats humans there, and yet the world of chess today is more robust than it’s ever been before. World chess championships are now watched by millions, and the number of players seems to be rapidly growing, with more than a million ranked players and tens of millions of occasional amateurs.

Why do so many people play a game in which they can be easily defeated by AI? Answers abounded. One person noted that the community is engaging and that chess is fundamentally a social activity that affords reasons to connect with others. Another said that it was “existential solidarity,” that we care about what another human will do far more than a machine. It’s no different than watching a speedrun of a video game: AI can perfectly mash the controller, but it doesn’t invoke the sense of awe we encounter when we know that a human accomplished the near-impossible. Another brought up Walter Benjamin’s famed essay on what makes art unique, claiming that it has an ‘aura’ that arises from its provenance of human workmanship.

My answer was that onboarding to chess — like coding — has been leveled. Learning chess before the internet would require distant and slow correspondence, perhaps a live coach, and a lot of books. Now, one can play an opponent with an equally matched Elo score and rapidly acquire skills and expertise, while chess commentators and AI tutors can explain moves and give more context for what’s taking place. Rapid feedback, greater fun, and play at a click of a button — all the ingredients are here for a robust and growing community. AI may well be the greatest grandmaster in history, but that ultimately doesn’t matter.

Unfortunately, it does matter in the economy. There were lightning talks and sessions on jobs, productivity and human agency throughout the conference, and certainly such concerns were ambient in many side conversations. Despite its popularity and primacy though, the distance between the economic prognosis of AI and the tools of social science was the greatest of any subject I encountered.

I got into a heated argument over productivity. The old Robert Solow line of “you can see the computer age everywhere but in the productivity statistics” has always had an obvious answer to me: you aren’t counting right — you’re just a drunkard searching at the lamppost. Spotify delivers the entire world’s music to three-quarters of a billion people. It also only paid out $11 billion to musicians in 2025. Outside of its revenues and royalties, economists have no ability to calculate what music’s worth is to people. A few might try to estimate consumer surplus of course, but those accounting methods are never integrated into the national statistics that ultimately drive policy.

That narrowness of economics is one of its defining features. What is a job? Economists have robust definitions of “job,” definitions that are going to require a substantial revision if not a wholesale rip-and-replace in the years ahead. Is orchestrating an agentic army of Claudes and Geminis a job? What if we start to see the rise of hyper-freelancers, who might work for 100 clients or more simultaneously while leveraging their bots? One could argue that nothing has changed, and yet, everything has. That’s the cardinal challenge for the social sciences in the years ahead.

Then again, as I walked by one decrepit motorhome after another, maybe unsettling some of our society’s (or at least, California’s) social failures is the disruptive breath we need to inhale.

There was a low hum of pessimism across the proceedings, latched on to the nightmare of a permanent AI underclass who are left behind by an elite squad of agentic engineers who accelerate away with the entire world. It’s not even a dystopian fantasy, for the tech industry’s success the past three decades provides ample proof of this trajectory.

The usual points were raised in various discussions, from universal basic income to some form of techno-communism, ideas that have already failed concretely or intellectually. What’s not even being discussed is what happens when bots have their own wallets and the very notion of property starts to break down. Who counts as a person? What is their (or its) relationship to property and contracts? Can an AI legally possess its own compute? Why not?

I was thinking about that on the walk back to the hotel. Answers didn’t flow, and I understand the deeply unsettling world we are all entering when very important and fundamental questions on the arrangement of society seem to be openly ambiguous and widely unanswered. Then again, as I walked by one decrepit motorhome after another, maybe unsettling some of our society’s (or at least, California’s) social failures is the disruptive breath we need to inhale. Our hearts might beat fast, but they will beat strong.

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Prediction markets may be focused on conquering traditional sports betting powerhouses like DraftKings and FanDuel, but their viral hits so far are political and cultural. For instance, will Jesus Christ return before the end of 2025? As Bloomberg reported, that Polymarket bet paid out at a rate of 5.5% — better than a high-yield savings account.

Yet defining events and whether they take place or not is a complicated art. Controversy brewed at Polymarket this week after it announced it would not pay out bets on a U.S. invasion of Venezuela, contending that only control of territory would trigger the payout. Thus, Nicolas Maduro’s abduction is not classified as an invasion.

Here’s the challenge: the squishiness around words like “invasion” or “war” is intentional. Adversarial ambiguity is used by nation-states, corporations and even individuals to take action while avoiding some or all of their consequences.

With adversarial ambiguity, it’s entirely possible for the United States to take Greenland and announce it while Denmark never acknowledges the loss but rather acquiesces to the reality of it.

When did Russia invade Ukraine? Was it when the so-called little green men started maneuvering in Crimea and the Donbas in 2014? For Moscow, these unidentified Russian soldiers masquerading as an insurgency force offered plausible deniability in its diplomatic negotiations. For Washington, war is technically only official when Congress passes a declaration, which hasn’t happened since World War II.

Given the high potential costs of war — up to and including nuclear strikes — nearly all of today’s great power conflicts are hybrid or use some form of gray-zone tactics. For instance, in 2017, Russia was widely reported to be seizing Georgian territory by simply moving the border sign and fence between the two countries a few inches to a few feet at a time, day after day. Does that inch count as an “invasion” since it involves control of territory? It’s precisely the ambiguity that allows Russia to avoid a wider conflict.

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Over in the private sector, we see adversarial ambiguity in the insurance industry. Homeowners who survive hurricanes quickly learn that there can be a massive disparity in benefits between wind damage and water damage, the latter covered by the federal flood insurance program while the former is often covered under a private policy. What caused the damage to a home?

Insurance attorneys can spend years arguing over definitions and evidence in an attempt to transfer future payouts to the government or another carrier. We’ve seen a similar pattern in the aftermath of last year’s wildfires in Los Angeles, where lawyers continue to argue over what caused the damage to specific properties, just one of many reasons rebuilding efforts in the region have stalled.

Insurance companies repeatedly fight each other from different sides of the table, so there is an economic incentive to resolve adversarial ambiguity and make the industry more efficient and therefore lucrative. In response to high legal costs and legions of frustrated policyholders who may wait years to get their lives back on track, insurers have become increasingly receptive to the idea of parametric insurance. Instead of arguing endlessly over the cause of particular damage, parametric insurance pays out based on objective factors. For instance, a policyholder could buy a policy for wind speeds exceeding 120 miles per hour for over 15 minutes and would get paid even if their property had no damage. On the other hand, they would also not be paid if their house was destroyed but wind speeds were 119 miles per hour.

Such objectivity is elusive in politics, nor are there incentives for nations to cooperatively resolve ambiguity. Take “Will Trump acquire Greenland before 2027?,” which is currently trading at a 15% chance with a market volume of $3.3 million and is one of the bets the Polymarket homepage is pushing to me. There are four paragraphs of rules attached to the bet. The first is relatively simple:

This market will resolve to “Yes” if the United States officially announces that Greenland will come under US sovereignty by December 31, 2026, 11:59 PM ET. Otherwise this market will resolve to “No”.

The second paragraph is much more complicated:

Sovereignty is defined as the transfer of the majority of the territory of Greenland from its current status as an autonomous territory within the Kingdom of Denmark to being under the formal governance or jurisdiction of the United States, either as a state, territory, or other classification within the US system.

Territory here is interesting. Is it the physical land of Greenland, or does territory include Greenland’s territorial sea and exclusive economic zone? Since the bet pays out if President Donald Trump acquires “the majority of the territory,” figuring out the denominator is crucial. Jurisdiction is another open-ended and ambiguous component, but let’s move on to the third paragraph:

An official announcement made by the United States and Denmark that Greenland will come under US sovereignty will qualify, even if the actual transfer of sovereignty is yet to occur. Only announcements of official agreements or actions (e.g. executive order, signed legislation, etc.) will count - mere posts on Social Media will not.

Did you notice what just happened? We started the rules with “if the United States officially announces” and now we have “an official announcement made by the United States and Denmark” (emphasis added). Which is it? With adversarial ambiguity, it’s entirely possible for the United States to take Greenland and announce it while Denmark never acknowledges the loss but rather acquiesces to the reality of American military might in order to partially assuage popular anger. Practically every diplomatic negotiation will include such ambiguity as a way to usher parties toward an agreement. Let’s move on the fourth and final paragraph of rules:

The resolution source for this market will be official information from the governments of the US, Greenland, and Denmark, however a consensus of credible reporting confirming that Greenland has come under U.S. sovereignty will also qualify.

Oh my. “A consensus of credible reporting” is one of those beautiful phrases that harkens back to a halcyon era when adversarial ambiguity and weaponized truth were mere figments in the imaginations of the most inventive sci-fi authors. It reminds me of my article “Consensus Functions” from a few years ago, in which I describe why it’s become impossible to reach any form of democratic consensus in any context, and what we should do to push forward institutions like science.

Once again, we see a contradiction in the rules. “Has come under U.S. sovereignty” is not the same as “under the formal governance or jurisdiction of the United States.” Greenland could be under U.S. sovereignty but not formally under the jurisdiction of the United States.

The premium for Jesus’s arrival is not a commentary on religious belief, but rather the market pricing in the complication of determining that bet’s outcome and Polymarket’s fidelity in doing so.

I can point out half a dozen other asinine, pedantic problems. I realize I am closely reading what is otherwise a gamified gambling experience that’s meant more as entertainment than professional investing. Ultimately, Polymarket can cancel a bet and just refund every investor’s wager, and outside some aggrieved would-be winners, everyone can move on. Indeed, as a market, prices can include our relative beliefs about Polymarket’s judgment in resolving these bets. The premium for Jesus’s arrival is not a commentary on religious belief, but rather the market pricing in the complication of determining that bet’s outcome and Polymarket’s fidelity in doing so. The potential ambiguity of resolution raises the cost.

Prediction markets and sports gambling have massive negative repercussions for society as Charles Fain Lehman noted in The Atlantic and I pointed out in “America’s Gambling Fetish.” But one upshot is that more people will be exposed to the elite battles over words, terms and definitions that have made adversarial ambiguity a hallmark of great power politics. It’s not just about reading the rules, it’s about realizing that the whole point of many actions is to be able to ignore the rules entirely.

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South Korean President Lee Jae-myung has the toughest job on the world stage. He has to placate U.S. President Donald Trump and protect his country’s massive and growing trade surplus with the United States. Then he has to rebuild long-frayed ties with China while pressing the country to help him improve relations with always-be-firing-missiles North Korea (the latest salvo came Monday, complete with alleged hypersonics). Plus, Lee must balance the Korean public’s historical antipathy toward Japan while forging a relationship with Japan’s most nationalist leader in years in hopes of buttressing Northeast Asia’s axis of democracy.

But wait, that’s not all! Lee must also orchestrate a complex arrangement of deals with the Middle East to promote South Korea’s massive nuclear power buildout, including what could be a blockbuster bid in Saudi Arabia. That buildout is part of the region’s sovereign AI initiatives, a challenge Korea is facing as well as it competes against heavyweights from both West and East. Finally, there’s the ongoing awkwardness of South Korea’s defense exports to Ukraine, with the Korean defense industry growing to record highs even as it bans exports to active conflict zones.

This is the endless struggle of a straddle power without the ability to drop special forces on a presidential palace and ransom a country’s oil supplies. Such a position might be extraordinarily challenging, but it also presents equally extraordinary opportunities that can only be seized through a dauntless and ever-evolving strategy.

Thanks for reading Riskgaming by Lux Capital! This post is public so feel free to share it.

During the Cold War, political scientist Robert O. Keohane wrote a review article titled “Lilliputians’ Dilemmas,” which first appeared in International Organization before coalescing into a Foreign Policy essay. He discussed how small powers balance relations with big ones, arguing that the first and most important criterion for a small power to navigate the whitewaters of great power politics is that it “…must have a high degree of maneuverability within limits set by its own domestic politics.”

What does that maneuverability look like? Well, it’s constantly inventing new reasons to attract big powers to you on favorable ground. In one of his most profound lines, Keohane wrote “American policymakers are too busy to think up grievances for states that cannot manufacture their own.” In other words, straddle powers need to assiduously create complex conditions where they can secure favorable tradeoffs.

For instance, while Korea is at the pinnacle of a number of industries, AI memory is its most strategic asset right now. SK Hynix is one of the world’s most important manufacturers of high-bandwidth memory, which is required for the most complex AI computations.

The dizzying growth of the AI sector is pushing SK Hynix’s stock and that of competitors like Samsung Electronics to record highs. Over the past month, the company’s stock has jumped more than 35%, and it’s up more than 160% over the past 6 months. Roughly 80% of its employees are domestic, leading to a memory boom in Korean employment and bonus wages that amounted to $80,000 per employee this year (Korea’s GDP per capita is about $36,000). Samsung is right behind with a gain of 130% over the past six months.

Blunt decisions don’t increase strategic maneuverability but instead do the complete opposite, transforming a complex game of negotiations into a linear tug-of-war.

Korean memory exports may not be a rainbow unicorn like Nvidia’s next-generation Rubin chips, but they are indeed supply-constrained, which is leading to record global price increases. That gives the Korean government leverage in negotiations with the United States and China, since neither country wants to surrender an edge to the other by losing priority access to this essential ingredient in the race for AI supremacy.

A single dependency is still a linear negotiation, though, and that doesn’t offer strategic maneuverability (or frankly, a good Riskgaming experience). So let’s remember Keohane’s diktat about manufacturing grievances. Trump has manufactured myriad complaints about Korea, including its yawning trade surplus and its lack of American auto imports. Korea got a significant if temporary reprieve in the aftermath of Trump’s crackdown on a Hyundai and LG Energy Solutions battery factory in Georgia back in September, which saw hundreds of Korean workers deported as they built up American manufacturing.

Yet that factory is precisely the right model. Korea’s most potent strategy is to position itself as the sole enabler of American reindustrialization. While I was off on holiday in mid-December, a major deal was announced that has Korea Zinc upgrading an existing zinc refinery in Tennessee through a $7.4 billion joint venture funded by J.P. Morgan and the U.S. government directly. In the final cap table, the Defense Department would own a 40% stake, Korea Zinc would hold less than 10%, and other investors would own the balance.

It’s a massive project. The Tennessee site is the sole zinc refinery in America, and no domestic facilities have opened for decades. Korea Zinc will take over the existing facility from Singaporean commodities conglomerate Trafigura and upgrade and scale it up to global competitive standards. If the plan is successful, it should shore up America’s zinc supply chain in 5–10 years, improving the country’s resilience in a range of products from metal alloys, like galvanized steel, to chips, batteries and weapon systems.

Since the announcement three weeks ago, Korea Zinc’s stock has gyrated. Initial euphoria sent it zooming to its highest levels in a year, but the stock has since lost much of those gains. It dropped nearly 9% earlier this week when ETF provider MSCI announced the company didn’t qualify for inclusion in its indices due to the share sale required to fund the joint venture with the American government.

Deepening co-dependency isn’t just happening in critical minerals, but also shipbuilding. Korean defense prime Hanhwa closed its $100 million purchase of the Philly Shipyard a year ago, announcing a massive expansion and reinvestment plan that would see volumes increase 20-fold as part of the official — and I kid you not — “ Make American Shipbuilding Great Again” plan (we are definitely better marketers than those Soviet apparatchiks and their “fifth five-year plan” snooze-fests). Hanwha has highlighted that it will train American workers at its Korean facilities, with the goal of improving sovereign shipbuilding capabilities.

Hanwha’s investment complements other announced projects. HD Hyundai Heavy Industries (HII) signed an agreement back in October with Huntington Ingalls Industries (also HII, so obviously a match made in heaven and a nightmare for every journalist and analyst going forward) to rebuild American shipbuilding and invest in “distributed shipbuilding.” HII (the American one) is the shipbuilding company at the center of our first Riskgaming scenario, Hampton at the Crossroads, and it’s the company best known for constructing Gerald R. Ford-class aircraft carriers.

Last month, a three-way agreement brought together American defense prime General Dynamics alongside Korea’s Samsung Heavy Industries and DSEC to focus on next-generation ship design and manufacturing, particularly on the U.S. Navy’s Next Generation Logistics Ship program.

I can keep on going in this Nor’easter flurry of announcements. How many of them will come to fruition much less lead to positive economic outcomes? My cynicism says that there is little chance that more than a fraction of them will ever ultimately be realized. However, I admit I have recently been more impressed at the level of focus on reindustrialization from leaders like Pennsylvania senator John Fetterman, who stopped by last month.

Back to straddling. Korea is attempting to enmesh itself in a complex weave of co-dependent relationships, where it always has another lever to bolster its relative negotiating position against larger superpowers. That’s the right approach for a straddle power: you want to be differentially and strategically valuable enough to raise the cost of intentional or unintentional adverse actions.

That’s obviously the opposite direction of America’s current positioning. Trump’s unilateral cuts to organizations like USAID mean that relatively cheap and featherlight threads connecting the United States to the rest of the world have been burned to smoke. Our trade autarky and increasingly venomous perspective on high-talent visas mean that even the social and business bonds that accrue as American power are weakening.

This approach does give a superpower like the United States more raw power. As I wrote yesterday, we can indeed “just take it” and there’s not much most countries can do in response. Where that strategy goes wrong, though, isn’t when other countries acquiesce, but when they don’t. If and when a country refuses, Keohane’s manufactured grievance toolbox will be empty, and America will be left with only much more expensive strategic actions available.

It’s perhaps the most important lesson I’ve observed across dozens of Riskgaming sessions, and particularly the ones we have conducted using No Man’s Land, our scenario focused on AI capabilities in commercial and defense procurement. Blunt strategies are satisfying to players since they are psychologically thrilling and so much easier to think through. It makes us feel powerful to stab another player in the back, particularly if they can’t immediately respond. Long term though, there are high costs to these fleeting moments of dominant power. Brewing vengeance, for one. But more importantly, the increasing dearth of co-dependencies means that bad outcomes aren’t as easy to prevent in the first place.

The players that succeed in Riskgaming — no different than straddle powers like Korea and others — understand that it is precisely the dense layers of value that have to be unwound that stop undesired decisions by adversaries. Blunt decisions don’t increase strategic maneuverability but instead do the complete opposite, transforming a complex game of negotiations into a linear tug-of-war. It assumes that other players will tug back on that rope rather than ignore it in favor of new strategies and tactics (think hybrid war or gray-zone activities). Brash audacity makes for viral social media posts and the occasional fun selfie, but it’s ultimately deleterious to long-term strategic power.

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Even the sales-and-deals turn of Christmas has its origins in reciprocity. Exchanging gifts is about deepening the ties that bind us all, looking back to pay it forward. It’s the same foundational cultural trait that powers up the startup world too, the reason Silicon Valley can’t be replicated. Nowhere is there a higher density of richly talented and richly wealthy people who are willing to take bets on projects with nothing but trust that it will one day all work out.

That spirit of Christmas is dying. The world is shrinking, resources are getting scarcer and it’s harder than ever to get what you want.

Apparently, what we want is oil, and it’s not for anointing the messiah. This weekend, the United States scarfed up Venezuela’s Nicolás Maduro in a surgical military operation that must be hailed as one of the most extraordinary successes in special forces history. Thanks to the wonders of this strange cosmic universe, Maduro and I now share the same gentrified borough.

The Venezuelan people have suffered mightily under Maduro and his predecessor Hugo Chavez. For almost three decades, the two have impoverished one of the most entrepreneurial countries in the world — a country that also happens to sit on an extraordinary endowment of natural resources that would be the envy of all but a handful of nations. Upward of a million refugees — from a population of about 30 million — have fled the miseries and trepidations of an autocratic government and a shrinking economy. And that’s just to the United States — an estimated 7 million more have fled to neighboring countries.

You have what we want, and we are going to just take it.

That’s not why we captured Maduro, though, for that would be far too humanitarian and charitable for the new Christmas spirit. It was oil, spoken plainly by President Donald Trump. This is no longer the Bush administration and its soaring (if at times sputtering) rhetoric of freedom and democracy. You have what we want, and we are going to just take it.

It’s the international relations equivalent of California’s $950 theft limit, a marker that divides a misdemeanor from a felony and which led the City by the Bay to become the City that Locks Up the Toothpaste. There’s no loss prevention strategy in Venezuela, though, since there’s not much to lose, empty shelves being Bolivarian socialism’s lasting legacy.

Just take it. I wish this wasn’t a pattern in American life, but it’s commonplace. Ro Khanna, Silicon Valley’s left-progressive congressman and a man who could really use that locked-up San Francisco toothpaste, certainly understands the need to just take it. Over the holidays, in spat after spat after spat with venture capitalists, he vociferously defended a proposed wealth tax meant to fund whatever it is that California considers a functional government.

Apparently, after years of walking the Fisher Price-colored corridors of the startup wealthy with hat in hand asking for coins every biennial (a hat that was ultimately filled to the brim, I might add), he’s finally had enough with it all and has decided to just take it. One time only, of course! I guess he hopes we can all feel the warmth of collectivism during the holidays. Call it the Wrath of Khanna, the superior man who lost his mind to aggrieved vengeance and is now biting the hand that feeds him.

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Biting the hand that feeds you, or just pocketing it. I grew up in Minnesota, a land noted for its Nice people. It’s really hard for coastals to understand what it’s like to live in a society where your neighbors will always do the right thing, where charity — religious or otherwise — is paramount in the lives of most, and where calls for food donations or blood drive flyers have to include a proviso apologizing in advance that they won’t be able to accept everything that will be donated. That was just Minnesota Nice culture, which continued long after I transplanted to the golden foothills of South Bay.

That culture of egalitarian benevolence is now in serious jeopardy. Feeding Our Future was the name of the non-profit that’s at the heart of the multi-billion-dollar Somali fraud story that has spread like wildfire since my colleagues at City Journal published their deep dive right before Thanksgiving (an irony missed by most). Tim Walz, Minnesota’s governor and former vice presidential candidate, announced yesterday that he wouldn’t seek a third term because of the growing scandal, putting an ignominious exclamation mark on an otherwise decent man’s tenure.

Civilization isn’t the police and courts, it’s a glass house that’s wide open with a sign that says “no one is home” and nothing happens.

The response from my coastal friends has been sheer bewilderment at the stupidity of the Minnesota officials overseeing welfare distribution. Take it from a still-prideful home state lover — naivety is justly earned. Leaving your doors unlocked is only foolish if you believe it’s impossible to live in civilization. Civilization isn’t the police and courts, it’s a glass house that’s wide open with a sign that says “no one is home” and nothing happens.

Venezuela, California, Minnesota: these three stories are merely the leading headlines of a repeated pattern in our culture today. America’s enlightened ethos of can-do “just do it”-ism has become today’s darker “just take it” psychology of the Beltway robber, the Barbary petrol-man and the Bitcoin fraudster. Positive-sum economics has been slaughtered by the atavistic dominance of zero-sum or even negative-sum thinking. It’s every man, woman and child for themselves.

I just watched Park Chan-wook’s new film No Other Choice, a story about a down-on-his-luck blue collar worker who is laid off after 25 years at a paper company. He realizes that the perfect job still exists out there, but there’s only one position and a lot of highly-qualified candidates waiting to be interviewed. How far must he go to eliminate the competition, save himself and secure his livelihood?

It’s a thrilling, terrifying and at times downright hilarious romp. It’s also part of an increasing oeuvre of films that critique competition in modernity like Josh Safdie’s Marty Supreme, Bong Joon Ho’s Parasite and Galder Gaztelu-Urrutia’s The Platform. These films observe this zero-to-negative-sum culture, but they either direct the blame for it to structural factors beyond individual control or naturally assume this culture is part and parcel with modernity. Absolutes have become relatives. Rather than trying to outrace others in the great game of life, we at some point realized we can just take a hammer to the engines of our competitors and watch as they sputter while we drive at whatever speed we want.

Competition is inevitable in any resource-constrained environment. Earth is no exception, and even becoming a multi-planetary species won’t release us from this basic law of economics. It’s how we address competition and its implications that determine the tenor of civilization. We can cultivate competition and the human desire for victory to frenetically recombinate brilliance and push forward the frontiers of technology and productivity. Alternatively, competition can be extraordinarily corrosive, undermining the will to work or invest and dragging everyone down together (see Venezuela, Country of).

America’s most important strength was — and always will be — its precarious meritocracy of the market. Good products generally beat bad products because consumers can suss out a better deal. Good ideas overcome incumbents because Americans are optimistic and willing to embrace better futures. Good institutions supplant bad ones because efficiency and performance matters to generous but impatient funders.

Just-take-it culture is an economic game of musical chairs, but the chairs are made of wood and the participants have flamethrowers.

All those safeguards have washed away. Consumers are cynical and desperately fighting capitalism’s dark patterns and enshittification. Pessimism has replaced optimism, entrenching narrow ideas over the potential of tomorrow. We no longer expect our government, courts, non-profit organizations and civil society to be fair but rather capricious, something best avoided rather than engaged.

“Just take it” has a double meaning, one that extends back to The Melian Dialogue of Thucydides. It’s the claim of the victor to what’s not rightfully his, and the submission of the loser acquiescing to a tragic fate. Two sides of the same coin, a penny that is fought over even as it is taken out of circulation.

Our energy to fight for a prosperous system is drained as we battle each other. Just-take-it culture is an economic game of musical chairs, but the chairs are made of wood and the participants have flamethrowers. What looks like an ample supply of seating quickly burns in an inferno.

Our present moment reminds me of Koushun Takami’s Battle Royale, which I read during my very first Lux partner offsite, sitting in earthquake-prone California below a hotel ceiling with a very concerning crack. The novel, which became a movie and an entire genre of multiplayer video games, is about a group of school kids sent to an island in which only the last remaining survivor is allowed to walk away and live.

The most poignant moment comes during a scene at a lighthouse in which a group of students desperately tries to create a small island of civilization against the murderous impulses of their classmates outside. Their small society works for a time, yet zero-sum thinking will come for them, too, even as they rebel against it. You can’t be good in a bad system.

It is hard not to feel anguish as we gaze at the grand expanse of history; millennia of evidence accumulated across innumerable societies and civilizations proves that the simplest yet most potent answer to what makes a good life is that positive sums not only exist, they are almost omnipotent in their ability to ameliorate the worst aspects of human existence and give our lives meaning. We still have that culture in parts of Silicon Valley, and it’s still the default mode for most Americans, even as it’s getting harder to sustain.

Why do we give Christmas gifts? Often the monetary value of these offerings are normalized within families, and so it can feel circular on that great economic spreadsheet of existence. But even if the dollar values are the same, those gifts come attached with emotions and ultimately memories. No net value was exchanged, yet incalculable value was created and offered. The magic of Christmas is the magic of civilization and what’s made humanity such a force for good: a gift economy means always being surprised that something better is in store. If I have faith in anything, it’s that we can, even now, still just do it.

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The Best of Riskgaming 2025

For those counting, we published 104 newsletters, 47 podcasts and four new scenarios. We also hosted about 24 events including runthroughs of Riskgaming scenarios, community meetups and geopolitical dinners. In total, about 500 people got to join us live for an experience — definitely an upgrade thanks to Laurence Pevsner joining as my partner at the tail end of 2024.

As always, thanks for reading, listening and attending — your commitment has allowed Riskgaming to turn into a powerful institution for profound thought on some of the most complex issues facing the world today.

Highlights from 2025

• We hosted 60 senior leaders from the United States and the United Kingdom for a biotech summit at the U.K.’s embassy in Washington DC as part of Prime Minister Keir Starmer’s trade mission to the United States.

• I pissed off some Pennsylvania politicians with an op-ed in The New York Post on President Trump’s horrifying deal approving U.S. Steel’s acquisition by Nippon Steel.

• I pissed off some public sector labor unions and mayors with an aggressive essay in City Journal on the need to use AI to automate more of city government.

• Dozens of people in New York City and in Los Angeles played our biotech game Experimental Automata during Upfront Summit.

• We were profiled by Business Insider, Payload Space and The Wall Street Journal, complementing past coverage in NBC News and The Information.

• I learned that Senator John Fetterman is a complete giant compared to me:

• We hosted a senior delegation of Canadian political and business leaders in Toronto to play No Man’s Land.

• Laurence launched Gray Matter with sellout events in New York City and in California, doubling down on biotech gaming with our first live trading card game. Negotiations were fierce, and you know you have a winning game when it is impossible to bring the room back to order so you can give the final results. We’ll publish the game in early 2026.

• We hosted a prominent former U.K. defense (I’m sorry, defence) minister for a Riskgaming session (who is excellent at negotiation, I have to say).

• We had a great time launching Ian Curtiss’s Southwest Silicon to a distinguished group in London from the U.K.’s Foreign and Commonwealth Office, the Department of Business and Trade and other ministries as well as in DC with Eric Schmidt’s Special Competitive Studies Project.

• We hosted our first comedy revue with Truth Santa, which will always have a special place burned into my heart (note to self: never write a comedy show under deadline).

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New Riskgaming Scenarios for 2025

• Experimental Automata: A Global Investigation of the Future of Digital Health and Biotechnology — a salon experience for 60 that educates on the progress coming in human wellness and agriculture.

• No Man’s Land: The AI Singularity and the Future of American National Security — the most in-depth full-immersion game we’ve ever made. This game takes eight players through the challenging tradeoffs of balancing commercial and defense security in the AI industry alongside a zany storyline that has now come to fruition in the real world.

• Southwest Silicon: Water, Semiconductors and the Future of American Economic Security — a full-immersion game that simulates the strict tradeoffs facing water-parched homeowners, farmers and the emerging chip fab industry in Arizona’s Phoenix Valley.

• Truth Santa: A Lux Riskgaming Holiday Experience — our holiday comedy revue that we hosted in SF and NYC. You had to be there, but you can see some notes and photos on the game’s unlisted page.

Best Newsletters of 2025

We switched to Substack this year, which was a huge help in terms of user experience and that all-important growth metric. Here were my favorite pieces of writing this year:

• Make gray-zone war expensive again — Unusually for me, defense was not one of my main topics this year, but gray-zone warfare is a perennial interest of mine. The costs of hybrid war have declined dramatically, encouraging more state and non-state actors to use these tactics to tremendous effect. We need to raise the costs again.

• The machine burns down — A meditation on a massive data center fire in South Korea and E.M. Forster’s The Machine Stops. Our lives are increasingly handled by machines that are now central points of failure for our society. Catastrophe awaits without better resilience and chaos engineering.

• Open secrets harm society far more than AI or disinformation — It’s the age-old story of the emperor’s new clothes: Everyone knows and agrees on facts that can’t be said out loud. It’s a pattern of behavior profoundly corrosive to democracy.

• Should AI recommend God? — AI chatbots like ChatGPT respond from an agnostic/atheistic point of view that reflects Silicon Valley’s mainstream values. To what degree should popular religions be brought up as paths in these chats? Is proselytizing through technology immoral?

• Why is economic data disappearing? — The declining quality and transparency of American and Chinese economic data mean that the twin superpowers are increasingly weaponizing perceptions of their economies at the expense of reality.

• The taps are dry and the rivers are flooded — A meditation on rivers inspired by James C. Scott’s In Praise of Floods. We need to pay more attention to water security.

• We’re finally predicting the weather accurately — Small progress made annually can add up to massive change over time. Weather forecasting improves by about a day every decade, and that is radically enhancing industries from logistics and agriculture to air travel.

• Uncle Sam is a terrible board member — My screed against the U.S. government taking board seats at U.S. Steel. The government can’t be a robust board member when it doesn’t have economic alignment and fails in its fiduciary duties.

• Tech is turning the Middle East into a pivotal region — Our image of the Middle East needs a dramatic renovation. It’s now a bountiful land of opportunity, dynamism and surprise — and it’s becoming a powerful economic fulcrum in innovation.

• Riskgaming against a world on fire: A manifesto, of sorts — This is the longest post of the year and a summary of my goals with Riskgaming as we moved to Substack. We constantly strive to avoid easy solutions to complex problems while uncovering the deep interconnections that constrain and direct today’s events.

• Is Plagiarism Dead? — AI is radically changing the definition of creativity and ownership. What is the future prognosis of the norm against plagiarism as AI tools reshape what we think of as originality?

• Asteroids, xeno-kidneys, planes and H5N1 — A deep dive into different types of risks and why it is still so hard to mitigate long tail risks even when they are predictable.

• Should you wait to have kids? — New biological technologies under development will radically improve the health of children right from conception. In the interim, that dramatically raises the relative risk of having children the next few years.

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The Best Podcasts of 2025

For your listening pleasure over the holidays, we’ve posted a special podcast episode recapping the year titled “11 Clips That Defined 2025.”

• The inside story of the billionaires fighting for space — The Washington Post’s Christian Davenport on Elon Musk / SpaceX, Jeff Bezos / Blue Origin and the race to colonize the atmosphere, the moon and ultimately Mars.

• Why AI safety is like a bolt in a croissant — Former Popular Science editor Jacob Ward on the ethical dilemmas facing the big general-purpose LLMs from OpenAI and Anthropic.

• America’s degrowth lawyers need to learn from China — Dan Wang talks about his everyone-is-reading-it book Breakneck and what we can learn from China’s engineering state and America’s lawyer society.

• The CIA in the 21st Century — The epic espionage chronicler Tim Weiner talks about his new book about the CIA over the past two decades, from the challenges of the Global War on Terror to its renewed war against superpower adversaries Russia and China.

• Intel, chips and America’s future — Dylan Patel of Semianalysis and I debate Trump’s partial bailout of Intel and what it means for the future of industrial policy and chips.

• What’s next for European defense autonomy — With Russia continuing to wage a brutal war on Ukraine, I talk with venture capitalist Eric Slesinger on the prognosis for defense innovation on the Old Continent.

• How Jane Jacobs got Americans stuck — The Atlantic editor Yoni Appelbaum discusses his new book Stuck on how declining geographic mobility is limiting opportunity for millions of Americans — and how to get people moving again.

• Can we ever defend against agricultural warfare? — Alicia Ellis, Arizona farmer and global security professor at ASU, talks about a new domain for conflict: agricultural security and the food supply chains that keep people nourished.

• Europe needs national champions, now — An in-depth discussion of Europe’s present place in the world from BCA Research’s chief strategist Marko Papic.

• How can we make the internet fun again? — Renée DiResta is one of the original researchers of the internet, and she’s made it her mission to find the joy again in this once optimistic medium.

• How Russia is bringing the cost of global sabotage to zero — My favorite episode of 2025 was with Daniela Richterova of King’s College London. We discuss how Russia has reduced the cost of sabotage roughly to zero by taking advantage of the gig economy, cryptocurrency and increasing polarization in the West to find solitary allies on the cheap.

That’s the end of 2025 — as I joked on the podcast, I am sure 2026 will be so quiet that we will have to shut down for a lack of content. Okay I’m kidding, but let’s just hope there isn’t a nuclear war before we all return.

Earlier this year, I talked with researcher Daniela Richterova on the Riskgaming podcast about this very subject in an episode titled, “How Russia is bringing the cost of global sabotage to zero.” In her research, she describes a Snow Crash–esque cyberpunk gig economy of would-be saboteurs and bored teenagers who pick up quick murders and propaganda work from listings posted online by terrorism franchises that pay out in cryptocurrency. The terrorists walk away all but anonymous.

At the same time, The Economist declared “the end of the rip-off economy” this week, arguing that the internet had accelerated the spread of quality and pricing information to consumers, allowing them to increase their economic surplus through better knowledge and negotiation in the marketplace.

Left unsaid in such analysis is that intelligence agencies such as Russia’s FSB and China’s Ministry of State Security have similarly been avoiding rip-offs in the freelance saboteur marketplace. It used to be extraordinarily difficult and risky to recruit an asset overseas. The process required prodigious training and careful psychological profiling of case officers, who were then sent behind enemy lines to identify leads, cultivate them over time, suss out their reserve prices for activities ranging from mundane surveillance to brazen homicide, and do it all without getting caught. Tradecraft was incredibly important, and it’s one reason why critics like grand-strategy expert Edward Luttwak are so dismissive of the CIA’s efforts (read Santi Ruiz’s excellent interview with him in Statecraft and also listen to our podcast episode with Zach Dorfman, who is writing a book on the CIA’s non-official cover clandestine officers).

Now, however, these same spy agencies can post a gig on the dark web (or apparently Snapchat), offer $50, and get a random citizen to conduct propaganda work — or worse.

It’s not just the ease with which these transactions are being conducted through social media and consummated with cryptocurrency. It’s also how fast the price has fallen. Data on costs is obviously hard to come by, but Richterova’s research and analysis of Russia’s more open recent tactics indicate that even serious sabotage or arson might cost only hundreds to low thousands of dollars. Since these gigs are handed out through what amounts to a curated auction, prices have dropped precipitously from the heights of the Cold War. There are clearly a lot of would-be saboteurs, and Russia and others have only so many targets they can blow up simultaneously (they can’t trigger all-out war, after all).

The price of construction is always legions higher than the price of destruction.

These activities are intentional. Arson can undermine the defense industrial base powering Ukraine’s army. Sabotage can induce fear among citizens, changing their behavior. Propaganda efforts can swing elections, or simply force politicians to respond to new crises and remove their gaze from overseas.

The price of construction is always legions higher than the price of destruction. Over decades, Jamaica grew into a challenged but growing economy, transitioning from a wrenching $423.70 per capita GDP in 1960 to over $7,000 last year (both present-day U.S. dollars). Six decades of work, 16x improvement. Hurricane Melissa, which swirled at an Earth-record peak speed of 185 miles per hour at landfall earlier this week, will have torn much of that growth asunder in just a few hours.

A catastrophic storm is no different than a Category 5 autocratic “chaos engineer” bent on undermining democratic polities, to use Giuliano da Empoli’s phrase. The cost of tearing apart a France or a Belgium — or even an America — is not Nvidia-scale in the trillions of dollars. The cost is cheaper than a fraudulent SPAC. Gig skullduggery is cheap, fast, efficient, flexible and globally available.

Technological innovations have ushered in efficiency around hybrid war tactics against which we at present have no defenses. People are willing to burn down factories for roughly the cost of an economy seat from New York to San Francisco. Despite the fears of privacy advocates, we don’t have a Minority Report–style crime prediction engine, even if we were to throw every dollar we have at Palantir.

The social psychologist Adam Mastroianni decried “the decline of deviancy” this week, asking “Where has all the weirdness gone?” Well, it seems to me that at least some of the weirdness is flowing right here, into scams, cryptocrimes, internet-mediated independent spywars and all the rest.

Two weeks ago, the United States seized $15 billion in cryptocurrency from a “pig butchering” scam network originating in Cambodia with deep ties to China. These organizations abduct tourists and recruit overseas workers with the promise of riches, and then have them dial for dollars across an ever-evolving series of scams targeting countries all over the world. This is a form of transnational crime that was impossible even a few years ago, one that undermines political legitimacy while also conveniently siphoning dollars from the West to the rest.

What can democratic nations do to fight back? It starts with building up immunity. That means getting a grip on inequality and a tattered social safety net that pushes desperate citizens to seek out any form of lucre, legal or illegal. It also means strengthening the rule of law, police forces and criminal prosecutions to ensure culprits are brought to justice, and swiftly. We also need to improve our surveillance systems, from funding data collection and analysis tools like Palantir to building new platforms like recently de-stealthed Valthos in biodefense to foil newly-discovered threats.

Democratic countries can’t keep taking blow after blow from adversaries with nary an attempt at a hybrid-war response.

Even more importantly, though, we must respond with much better and wider education on how to be vigilant in this new era. It’s not enough to blast a 15-second pre-recorded warning to tired riders of mass transit (“See it. Say it. Sort it.”). Very few understand the complexities and tactics of state-to-state technology-enhanced terrorism and influence operations and the signs to look for. That’s one reason why most of the gig workers who sign up for these activities don’t even realize they are pawns on the global chessboard of power. That’s a critical societal weakness, but one that can be plugged with a much more robust program of education.

These immunizations need to be coupled with more direct outbound actions. Democratic countries can’t keep taking blow after blow from adversaries with nary an attempt at a hybrid-war response. That’s a breakdown of even the simplest game theory model of international relations. Instead, it’s time to augment older playbooks on undermining the authority of autocrats everywhere with a much more improvisational toolkit, one that is centered around new technologies that offer new capabilities.

We won’t undo the innovations that have spread over the past decade, but we can build new institutions to protect ourselves from their worst effects. We live in rich nations with deep resources and citizens who still — mostly — believe in the future of their countries. It’s time to take those resources and kick the vandals out.

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Chaos, Chaos on the Wall…

AI as creature, astronomy, gray-zone warfare

Well, here we are again.

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This morning, Amazon Web Services suffered a catastrophic outage in its US-EAST-1 data center complex in Northern Virginia starting at around 3am Eastern and continuing into the morning rush. As of writing at 10am, 71 services at the data center remain offline, while 37 have been brought back online. Amazon’s US-EAST-1 is one of the most important data centers in the world, and its failure has led to outages of dozens of well-known applications according to DownDetector and social media reports.

It’s obvious that we are building our critical applications on foundations of sand; just as with South Korea, an outage in US-EAST-1 is hardly unprecedented. As The Verge notes, “AWS outages in the US-East-1 region have created widespread disruptions in 2023, 2021, and 2020, forcing multiple websites and platforms offline for several hours before regular service was restored.” Yet, developers and IT architects keep on returning to that same data center, while failing to mitigate against its predictable outages.

If you are thinking “WTF,” I don’t blame you. This is far beyond technical acumen or engineering prowess, and far more about organizational design around risks and rewards. It reminds me of Dan Davies’ book The Unaccountability Machine and his notion of “accountability sinks.” The premise is that organizations adapt themselves to ensure no one working at them can be held accountable for what the organization does. Stafford Beer’s koan that “the purpose of a system is what it does” needs a Davies corollary, namely that “no one here chose that purpose, sorry.”

In other words, rather than taking a resilient and risk-mitigating approach to engineering these systems to ensure their robustness under even complicated and unique outages, organizations have chosen cover-your-ass-at-all-costs by flocking to the same US-EAST-1 data center in mutually-assured defensibility. Don’t blame us, it’s Amazon!

In fact, that’s basically a perfect sales pitch for Amazon’s services. No one can be fired by selecting Amazon, since the alternative would be an equally incompetent employee at another organization making the exact same decision. This herd mentality induces catastrophic and correlated societal risks. As the world has become more deeply integrated, these outages and failures metastasize farther.

This is not the butterfly effect causing a hurricane with a flap of the wings. Every one of these crises was predictable, and therefore they are all possible to mitigate.

As the fire in South Korea and this morning’s AWS outage show, essential technical infrastructure has a habit of going offline. Cloudflare pushed out a bad patch and computers worldwide were bricked. Jeep pushed out an over-the-air update last weekend and summarily froze the Wrangler 4xe for many owners. Texas lost all power in 2021, the Suez Canal was blocked by a cargo ship, and the Panama Canal sometimes lacks sufficient water to allow vessels to pass.

These events can feel random when reading headlines, but they aren’t emergent behaviors from complex systems that are impossible to foresee. This is not the butterfly effect causing a hurricane with a flap of the wings. Every one of these crises was predictable, and therefore they are all possible to mitigate.

Even the most robust organization will struggle to maintain the highest incentives for safety and risk mitigation.

There is stochastic degradation of any real-world system, which means we must diligently conduct chaos maintenance to ensure stability. Yet, such maintenance is increasingly not budgeted or worse, per Davies, is just actively ignored in the hopes that no one can be held accountable for any failures.

I’m a strong nuclear energy advocate, but if you are curious why so many people don’t believe humanity could ever safely run a complex technical system that could melt down, this is why. Even the most robust organization will struggle to maintain the highest incentives for safety and risk mitigation. I reference Charles Perrow and his book Normal Accidents perhaps too much on Riskgaming, but his central thesis bears repeating. Highly-coupled and highly-complex systems will inevitably fail due to the interlocking and emerging interactions of the underlying assemblage of components. We can reduce such failures, but we can’t eliminate them.

A single computing service having an outage shouldn’t lead to push notifications from every major news service and a major concern that stock markets will crash today (that’s President Trump’s job!) We can’t allow accountability to be shorn from the critical nature of these applications to society. Hospital systems fail when servers go down, and there are patients relying on the outcome of those computations. With power comes responsibility they say, or used to. I don’t know, my social media feed is blank.

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This time, the crisis was more serious than the clownish antics of the man up north. A backup battery had caught fire at the country’s National Information Resources Service data center, near where I used to live in Daejeon. Like other battery fires, the flames rapidly spread, engulfing and destroying the entire building despite the furious efforts of dozens of firefighter companies. More than 600 critical government services were knocked offline. The data center was miles away from me and posed no immediate hazards, but its centrality ensured another salvo of urgent messages were pushed out to the entire country.

A decade’s worth of work by an estimated 750,000 civil servants vanished up in smoke.

The fire was just the start of this rolling catastrophe. A review found that terabytes of critical files stored on the government’s privately-managed G Drive system had been destroyed. As reported by the Joongang Daily, “… due to the system’s large-capacity, low-performance storage structure, no external backups were maintained — meaning all data has been permanently lost.” A decade’s worth of work by an estimated 750,000 civil servants vanished up in smoke.

Some systems that were unaffected — like immigration — were nevertheless swept up in the aftermath. South Korea, in the middle of a rapprochement with China to thaw relations that had cooled with the deployment of America’s THAAD weapon system all the way back in 2016, had agreed just days before the fire to allow visa-free entry to Chinese tour groups. Korea’s right wing, which aggressively opposes the Chinese Communist Party, was quick to suggest Beijing started the fire to permit hordes of Chinese tourists to enter the country and begin a national invasion. This story became a viral meme across X, requiring strenuous denials from government officials and exacerbating the country’s fragile political environment.

Push notifications kept coming as some systems came online and others remained dead. The post office and the country’s finance system were offline, a disaster with the country’s most important holiday, Chuseok, approaching. Even now, two weeks after the fire, only 36.4% of the disabled government services have been restored, and only 30 of the top 40 most critical are functioning.

I have been a dauntless advocate for government digitalization, and I continue to believe artificial intelligence has the ability to radically improve the quality and efficiency of services, perhaps even ushering in a new era of fiscal sanity for America’s cities. After all, a fire could destroy America’s retrograde paper-based records just as easily as it can melt silicon, and data is a lot easier to back up.

Yet, our reliance on centralized systems for such a widespread number of critical services demands deeper introspection. After all, this battery fire isn’t the first time South Korea has faced this type of crisis; back in 2022, a data center fire at Kakao knocked out the country’s most popular app and payment platform, bringing the entire consumer economy to a halt and ultimately leading to the resignation of co-CEO Whon Namkoong. One of the world’s most digital societies has discovered living with the machine has significant downsides.

More push notifications sprang up on my home screen. I was on vacation, and the crisis prompted me to return to E.M. Forster’s magnificent 1909 short story, “The Machine Stops.” He envisioned a deep future in which humans had become enmeshed with the Machine, relegated to individual and identical underground caves that provide all light, nourishment, entertainment, communication and living quarters at the push of a button.

The Machine responds instantly to requests, yet the humans who inhabit this dystopia seem to lack even the most fundamental of freedoms.

In the story, Forster twists his readers’ notion of individual agency. The Machine responds instantly to requests, yet the humans who inhabit this dystopia seem to lack even the most fundamental of freedoms. The human thirst for adventure and exploration is replaced with a stunted somnambulance, a constant search for unrealized thrills from the comfort of the Machine’s embrace. “The room, though it contained nothing, was in touch with all that she cared for in the world.”

Not only does individual agency get redirected, the Machine itself starts to absorb its energy. “But Humanity, in its desire for comfort, had over-reached itself. It had exploited the riches of nature too far. Quietly and complacently, it was sinking into decadence, and progress had come to mean the progress of the Machine.”

Forster was sending his own emergency push notification to critique progress and technocracy, themes that had been explored by contemporaneous authors like H.G. Wells in “A Modern Utopia.” Italian Futurists were then exalting the aesthetics of machines like the automobile as a transcendent form of humanity’s unbridled intellect. Forster responded by showing the dangerous dependency these machines foisted on humans.

For indeed, the miraculous Machine is also dying. The Mending Apparatus that keeps the Machine running requires its own mending, and it is falling behind. Things start to break, first the music, then more serious systems. Chaos erupts. Forster turns poetic: “Century after century had he toiled, and here was his reward. Truly the garment had seemed heavenly at first, shot with colours of culture, sewn with the threads of self-denial. And heavenly it had been so long as it was a garment and no more, man could shed it at will and live by the essence that is his soul, and the essence, equally divine, that is his body.” Humanity’s complete dependency on the Machine ultimately proves not liberating, but lethal.

Forster argues for the importance of connection and direct experience, both of which now terrify a humanity used to the mollycoddling embrace of the Machine. Yet his secondary motivation is to point out that over-reliance on external tools beyond our own faculties has a serious cost all its own.

What’s needed more than ever is a bit of chaos engineering.

The Machine exists today, and it has enveloped us. Reading a bunch of articles on AI on the plane ride over to Asia, I was struck by the number of writers and sources who noted they sometimes went hours without once thinking about what they were doing. AI models are so perfect at predicting the next required action that they can run autonomously of their human masters. Some college students haven’t read or written a single line of prose and still string together straight As. Forster’s garment fits snugly.

What’s needed more than ever is a bit of chaos engineering across society. I brought up the methodology last year, but the idea is to carefully and intentionally break technical systems and see what fails for the end user. Turn off a data center — does software break? The network goes down — what are the repercussions? Are we prepared with redundancies, and can we degrade service in a way that still makes it useful?

Yet the concept is even more useful when we include society itself as part of the system. What happens if our credit card processors fail — can we still operate our businesses? Yesterday at my coffee shop, the online ordering system was receiving requests but not relaying them to the store due to some coding bug. An enraged crowd of customers was stewing, and the store employees had no idea what to do. Call it Riskgaming, or just good contingency planning, but businesses should never fail to take a customer’s money due to something as brittle as a modern PoS system. We’re just serving coffee after all.

Turn-of-the-century progressives were certainly correct: technology affords us tremendous luxuries. In Seoul, I rode the new segment of the GTX-A high-speed subway line, which whisks travelers at 110 miles per hour between their destinations. That’s Penn Station to JFK Airport in about 10 minutes. We don’t need to give up these wonders just because they can fail, but nor should we give up our ability to use alternatives either. We’re only ever one push notification from disaster.

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Isolating our interdependence

Years ago, I was working at a leafy government agency that tries to keep things, well, quiet. I show up at headquarters one day, and I’m told we’re going on a field trip to one of the most classified installations in the country. I’m directed to get in the waiting black van with tinted windows. Either I’m about to see something really cool, or I’m about to be murdered. In other words, it’s just another day at the office.

We visit the installation, and upon our return, we are pre-reprimanded not to discuss any aspect of the facility or its location whatsoever. So I do what any naturally curious person would: I go to Wikipedia and search for the town near the installation. Lo and behold, linked in the first paragraph is a full article on the very installation I was just told shouldn’t exist.

I remember sitting there bamboozled. The dissonance between the über-secrecy — the hushes and the warnings and the threats of punishment — and the reality that everything I had just seen was clearly documented on one of the most trafficked websites in the world was way beyond my doublethink capabilities. It was an open secret, one that I was expected to pretend wasn’t open.

Some time later, in late 2010, Julian Assange and his team at WikiLeaks dumped an extensive cache of American diplomatic cables. The action prompted a ferocious debate — one that only reached its denouement last year. I read a bunch of the cables, most of which were the anodyne missives of mostly-ignored frontline officials in countries no one in DC cares about. But a few were interesting, and I tried talking about them with a friend holding a security clearance. He told me he had been strictly instructed not to read the cables, since that would violate his clearance.

I said, “they’re on the internet and being discussed on cable news.” He had apparently been instructed to change the channel if the cables were being read on television. I thought he was being ridiculous, but then I read such coverage as this contemporaneous article from The New York Times:

State Department employees have confided that they read leaked cables on newspaper Web sites at home rather than risk trouble by viewing them at work. A Times reporter who appeared with a State Department official on a recent panel was advised not to show leaked cables as slides — the official was prohibited from looking at them.

Maintaining open secrets like these requires a passive conspiracy of lies. We know the empirical truth, but we can’t express it nor can we act on it. It anesthetizes agency, because humans don’t like living inconsistently with the world as they perceive it. That is deeply corrosive to political debates, corporate strategy meetings and anything in between — open secrets are the landmines in the march to rigorous thinking.

Last week, Immigration and Customs Enforcement agents raided a battery facility in Georgia, arresting more than 300 South Korean nationals at a plant under construction by a partnership between Hyundai and LG Energy Solution. The operation included an astonishingly aggressive perp walk suited more for drug kingpins than run-of-the-mill construction workers and project managers. Unsurprisingly, the Korean press blistered with anger over the raid, and the U.S.–Korean alliance went into a tail spin after a productive state visit at the White House just two weeks ago.

Nearly all politicians — even the most nativist and populist — ultimately care more about economic growth than the composition of the American workforce.

We don’t know how many of those arrested were doing work outside their formal visa restrictions. But it’s an open secret that companies generally flout U.S. immigration law when it comes to expert project work like building battery and semiconductor facilities. As reporters for the Financial Times wrote earlier this week:

Because short-term US work visas can take weeks to be issued, some South Korean companies have sent staff under a visa waiver programme to help install new equipment and supervise construction, according to people familiar with companies’ operations.

Like all open secrets, this is a recurring pattern. A few years ago, TSMC struggled to secure visas to bring in Taiwanese construction workers for its Arizona fab facility, fighting members of the local pipefitters union who wanted the work for themselves. Was it pay, expertise, cultural affinity, discrimination, expediency, or just defaults that pushed TSMC to fight? Or all of the above? Does it matter?

The government knows what’s taking place (that’s why officials were able to conduct the raid in Georgia in the first place). Political leaders have passively allowed businesses to flout immigration law for decades in a you-see-me-I-see-you conspiracy of lies. A conspiracy so consistent, businesses have come to rely on lax enforcement and weak interpretations to underwrite their commercial plans. Why does it all work? Because nearly all politicians — even the most nativist and populist — ultimately care more about economic growth than the composition of the American workforce. We’re all playing under the same incentives, and everyone acquiesces.

Kelsey Piper, in the recently launched left publication The Argument, dubs this “the honesty tax” in the context of benefits fraud and land-use controls. “If the rules are widely ignored, it’s probably because the rules are badly designed,” she writes. “We allow widespread rulebreaking as a workaround in place of actually fixing them. But while rulebreaking might be better than enforcing stupid rules, it’s a lot worse than changing them.”

She’s right about changing the rules, but that’s the challenge with the incentives of open secrets. Leaders want both the outcome and the lie. They want to message populism while also quietly welcoming the overseas construction workers who are necessary for the wealth generation that ultimately drives their poll numbers. They want to accept the accolades of promoting an ethical technology framework while also maximizing revenue regardless of the consequences, say, teen suicides (incredibly, this describes more than one tech company in the news this past week).

The spooks are now the ones trying to lead us away from the very wilderness of mirrors they once built.

The downside of being trained as an engineer is that I find it hard to ignore the incongruities between open secrets and reality. Engineers want to fix things, and we’re really good at error analysis. When we turn that lens toward social systems, we feel profound anguish in realizing that the system is fundamentally broken and needs immediate maintenance. For us, passivity toward the conspiracy of lies becomes all the more intense as we realize that no maintenance is forthcoming — the rules are locked.

Yet there is an upside as well. Seeing the truth of a system is its own superpower, a superpower that I share with others through Riskgaming scenarios. There are many relevant quotes that connect to Riskgaming, but one of the most fundamental would be cyberneticist Stafford Beer’s constant refrain, “the purpose of a system is what it does.” I would argue that the majority of insights from our scenarios fall into this category. Dispel the open secrets, burn down the conspiracy of lies, and start to have a free exchange about reality as it is. After all, that’s how one navigates toward the valuable contrarian-but-correct quadrant of the venture capital investment matrix.

Open secrets ultimately degrade all contexts — just ask the intelligence community. I was recently talking with a senior intelligence leader about the threats that keep them up at night. This individual said “the Cartesian crisis,” or the inability of citizens to distinguish between reality and fiction. I sort of stared, gobsmacked, realizing that the spooks are now the ones trying to lead us away from the very wilderness of mirrors they once built.

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Should AI recommend God?

In other words, it’s the waning days of summer. We are now reaching into the quiver for any morsel of amusement outside our quotidian experience. So naturally, I found myself at a conservative luncheon in midtown recently on the subject of AI, God and the future of faith. The burger and fries were my normal fare; the conversation was not.

At issue was a simple observation. Pop open ChatGPT or Claude, and ask for advice. It’ll be a doctor, a therapist, a business consultant or a lawyer on demand. What it will never be — or not without very intentional prompting — is a priest. The models are secular, and they will never direct a user toward any scripture or catechism without a determined paddle of the prompting raft against the unbelieving current. Should that change?

After all, that blank text box and the worlds it can unfurl are powerful; so powerful in fact that the large model companies employ whole alignment teams to determine whether their products are serving the interests of users and humanity as a whole. What one rarely hears from this community though is a connection between the secular binaries of our H100 overlords and the religious convictions of billions of humans. That fact is particularly striking given the overwhelming largess of the Middle East in propelling AI forward.

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Even so, I am a hardened skeptic and was not convinced in the initial volleys of the luncheon. AI alignment experts — like the social media moderation teams combatting misinformation and disinformation before them — seem like nothing more than sanctified high priests of censorship hell-bent on identifying and purging thoughtcrime, far beyond the confines of jurisprudence. (No, I don’t think that alignment will solve bioweapons; it’s far more likely to entrap some poor biomed student just trying to check their homework).

I digress. As the luncheon went on, the debate turned to what degree should AI models serve the user and their psychologies (aka sycophancy) versus nudging them toward “human flourishing" in the broadest conception. Instead of agreeing and reinforcing a user’s innate tendencies, should AI models work in a more reparative role? Should they have some vision of the good life and encourage actions in that direction? Or to put it another way, should they adopt the tone of Reddit’s most charming and arguably popular applied ethical subreddit, “Am I The Asshole.”

In short, should AI act as one imagines a religious mentor might, offering words of solace at certain moments, hope in others, and sometimes even admonishments and serious censures? Anthropic announced this week that it has now designed Claude to shut down conversations it determines to be "harmful or abusive.” Why only take such small steps?

Should AI act as one imagines a religious mentor might, offering words of solace at certain moments, hope in others, and sometimes even admonishments and serious censures?

The human flourishing debate went on for a while, but what I found striking about the luncheon topic was its complete absence from the Silicon Valley dialogue. Sociologically, the AI alignment world is deeply intertwined with the broader rationalist community represented by LessWrong, the blog originally created by the AI researcher Eliezer Yudkowsky, alongside other digital and analog homes. The community (as far as I can observe as a non-member) has very little interaction with religion, outside its penchant for generating some of the strangest cults we’ve ever seen. How many practicing Catholics are on AI safety teams in the archipelago of San Francisco hacker houses? Even with Neo-Catholic churches seemingly on the rise, I’d estimate vegans outnumber the Pope’s flock in the city named for Saint Francis of Assisi.

Yet traditional religions are hardly disengaged. Take the Catholic Church, which published its comprehensive opinion on artificial intelligence earlier this year. It’s a lengthy read, but I enjoyed one of its central arguments (paragraph 33):

Human intelligence is not primarily about completing functional tasks but about understanding and actively engaging with reality in all its dimensions; it is also capable of surprising insights. Since AI lacks the richness of corporeality, relationality, and the openness of the human heart to truth and goodness, its capacities—though seemingly limitless—are incomparable with the human ability to grasp reality. So much can be learned from an illness, an embrace of reconciliation, and even a simple sunset; indeed, many experiences we have as humans open new horizons and offer the possibility of attaining new wisdom. No device, working solely with data, can measure up to these and countless other experiences present in our lives.

For all of the obsession in AI alignment circles about bioweapons and existential risk (reminder: we’re never going to stop bioweapons — ever), how often do we consider how little wisdom AI actually has? It’s never experienced a simple sunset, let alone had a crush that got away. Sure, use it to read an X-ray or a legal document, or ask it to structure a code refactor. But such “functional tasks” are not what make humanity great (and if they are, then please make autonomous killer robots sooner rather than later).

As the luncheon drifted toward its conclusion, I simply observed that the Valley alignment conversation centers almost exclusively on preventing harm. Let AI move forward unchecked except for the things that can cause lasting damage. The inverse — of empowering human flourishing — is a far more hopeful vision. Don’t try to detect psychosis or push users to an AI boyfriend or girlfriend, but instead, help users find flesh-and-blood love since that can never be substituted by pixel-and-byte prompting.

The AI alignment community needs to diversify the voices it takes as input, and quickly. It shouldn’t mimetically follow its own thought patterns, lest it fall into the same trap as the social media moderators who forgot to truly protect online conversation in their quest for domineering control. Alignment is ultimately another word for value systems, and the world has many. Silicon Valley should cultivate its humility on these issues and absorb a far wider set of them in its pursuit of ultimate utility.

Our valuations are retrenching; it’s time our values did as well.

I didn’t leave the table agreeing with the group (nor did I leave having eaten dessert or drinking a sherry, with conservatives just as puritanical as progressives, apparently). Alignment — like tech ethics in general — is a topic that always seems to find itself in a perpetual motion machine of points and counterpoints, with little to show for all of the philosophical energy. We’ve covered it once before in Laurence’s post a few weeks ago on the “Cigarette Butler Problem.” What can I say? He had words, I didn’t; I was drinking a nice Chardonnay, and he has access to the publish button. C’est la vie en été.

I did leave lunch thinking that Silicon Valley has a much greater duty to be less impoverished in the import of its products. AI chatbots are the fastest growing technology in the history of humanity. Upward of a billion people already use these tools regularly, and that figure could hit two billion soon. That’s nothing short of astonishing, and shows the profound intellectual achievement of these technologies and the engineers building them.

That influence demands that questions of values should range far larger and come from a more humble perspective than what we’ve witnessed the past few years. Silicon Valley tends to glom onto a single school of thought rather than a syncretism encompassing the whole range of human understanding and history (the challenge of so many engineers deficient in a humanities education!). That mattered less in the cloud, mobile and SaaS era, but it’s critical to the age of intelligence. Our valuations are retrenching; it’s time our values did as well.

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