Technology | The Atlantic

The Most Famous AI Writing Tic Is Also the Most Mysterious

2026-07-12T07:30:00-04:00

If Julius Caesar had debuted this year, William Shakespeare might have been accused of writing it with AI. A certain suspicious rhetorical device appears again and again in the play. It’s in Act I, Scene ii: “The fault, dear Brutus, is not in our stars, but in ourselves.” In Act III, Scene ii: “Not that I loved Caesar less, but that I loved Rome more.” And later in that same scene: “I come to bury Caesar, not to praise him.”

These famous lines include what has become perhaps the best-known tic of AI writing—a sentence that tells you what the subject isn’t as well as what it is: It’s not X; it’s Y. Once you start noticing the construction, you see it all over the place. In one version, the Y is additive: It focuses, intensifies, or expands on the X. An annual review by Citizens Financial Group reported that growth in its private-banking division was “not just a win for the private bank—it’s a win for the entire enterprise.” In another variant, the Y supplants the X as the preferred descriptor. “The target was never a man. The target was the truth,” Michael Flynn, a former Donald Trump adviser, wrote in a March X post.

Then there are constructions like No A, no B, just C, which especially seem to crop up in AI-generated fiction. Lines such as “No bag, no things, no armor, just me” helped to fuel accusations of AI writing in the horror novel Shy Girl, which was pulled by its publisher this year. (The book’s author denied using AI to write it. Citizens Financial Group has previously said that its communications team “leverages the technology in a number of areas.” Flynn did not respond to a request for comment.)

The prevalence of this device isn’t just anecdotal—it’s measurable. (Sorry.) Barron’s reported that its appearance in corporate communications more than quadrupled from 2023 to 2025. Researchers at Pangram, which makes an AI-detection tool, estimate that Not just X but Y sentences appear three times as often in AI writing as they do in human writing. Elyas Masrour, a founding engineer at Pangram, told me that all of the major chatbots—including ChatGPT, Claude, Gemini, and various open-source models—rely on it to varying degrees.

Many other well-known chatbot tells—such as the usage of delve—have come and gone as AI companies honed their models and worked out kinks. Last fall, ChatGPT became obsessed with goblins and gremlins, prompting another intervention: OpenAI retired ChatGPT’s “nerdy” personality, whose affinity for mythical creatures had apparently infected its other models. Yet It’s not X; it’s Y has shown no signs of abating.

Before ChatGPT came along, the construction was obscure enough that it didn’t really have an agreed-upon name. Now there’s a scramble for what to call it. Terms from academia, such as antithesis and metalinguistic negation, capture some forms of the construction but not others. In an email, Laurentia Romaniuk, a product manager for model behavior at OpenAI, referred to it as “contrastive phrasing.” Despite its clunkiness, the most popular name I’ve seen is “negative parallelism.”

When deployed judiciously, negative parallelism can be punchy. But ChatGPT turns to it too often, Romaniuk acknowledged, which can feel formulaic. So the company is working on ways to broaden the chatbot’s repertoire. In the meantime, she added, users can try giving ChatGPT “custom instructions.” On a Reddit forum about AI writing, users trade tips for scrubbing negative parallelism from chatbots’ writing. One suggested pasting Claude’s output into another AI chatbot and telling it to act as a copy editor who has a strict ban on “negative pairings” such as “it wasn’t X, it was Y.”

One obstacle to a more comprehensive fix is that no one seems to know for certain why AI models are so enamored with negative parallelism in the first place—maybe not even the companies that created them. (Anthropic and Google did not respond to my requests for an interview.)

The simplest theory is that humans trained them that way. Large language models are built by first identifying patterns in unfathomable quantities of human-written text: books, academic papers, patent filings, and especially the internet. Negative parallelism was, of course, present in the initial training data. Shakespeare aside, there are lots of famous examples: In the 1960s, the legendary football coach Vince Lombardi popularized the saying that “winning isn’t everything; it’s the only thing.” In the 1990s, a frozen-pizza brand’s commercials insisted: “It’s not delivery. It’s DiGiorno.”

But the training data also included lots of bad writing that AI companies don’t want their chatbots to mimic, Tuhin Chakrabarty, a computer-science professor at Stony Brook University who studies AI writing, told me. So they also undergo “reinforcement learning,” a process by which human reviewers grade the models on their responses. Through trial and error, chatbots are guided away from inappropriate responses (making stuff up, giving illegal advice, insulting the user) and toward those rated helpful. Chakrabarty said that it’s plausible that human reviewers tended to give high marks to responses that included It’s not X; it’s Y. That could be because negative parallelism gives the impression of nuance and insight: The AI seems to be reasoning its way from a subpar descriptor to a more apt one.

That still may not be enough to explain just how prevalent the construction seems to be across the major AI models. Several experts I talked with pointed me to another, even weirder explanation.

Although chatbots have advanced dramatically in their research and reasoning capacities, they are still fundamentally text-prediction machines. They generate answers one “token”—or chunk of text—at a time, based on what has come before. Each successive word choice factors in both the statistical likelihood of that word coming next in a sequence, based on patterns in the original training data, and the likelihood that it will lead to a highly rated response overall. In other words, the models are always seeking a balance between the clever word choice and the obvious one.

When a chatbot uses negative parallelism, according to this theory, it’s essentially hedging between the two. Once it has started a sentence whose function is to characterize something, the path of least resistance is to say first what the thing isn’t (X), and only then what the thing is (Y). Put another way: For a sentence that begins with “This is,” following it with “not just” is both more likely and safer than the many options for how to directly characterize its subject. And after “This is not just,” the rest of the sentence gets easier too. The next word can be X—the boring, obvious descriptor that gets negated—which in turn sets up the final choice of Y, the somewhat punchier descriptor.

Even if researchers could figure out exactly why chatbots embrace negative parallelism, there’s another factor that could make it very hard to fix: “When something gets into these models, it’s very hard to pull it out,” Masrour, the Pangram engineer, said. That’s because one of the main ways that AI models have continued to evolve is by training on text generated by other bots. That AI text is presumably replete with negative parallelism, which further bakes it into the newer model. Now consider that a growing share of the writing on the internet is also AI-generated. This, too, becomes training data for future generations of AI.

On top of that, some AI labs are also using AI instead of, or in addition to, human reviewers in the post-training process, Chakrabarty said. Without intervention, there’s a risk of “model collapse,” in which AI reinforces its own biases to the extent that it loses touch with the human data that were meant to ground it. “It’s a very vicious loop,” Chakrabarty said. “There’s already negative parallelism in the text, and then AI is preferencing negative parallelism—it comes to a point where it just cannot write without that.” AI language is eating its own tail.

Chatbot clichés might be grating, but there’s an upside to them: They make AI writing easier to distinguish from the human variety. Masrour said that although the AI writing’s specific markers keep changing, it isn’t actually getting any more difficult for Pangram’s software to detect. The stubborn persistence of constructions such as negative parallelism may be one reason.

The trade-off, for human writers, is that a once-potent rhetorical device is now a cliché that makes you sound like a bot. That has put some people in the awkward position of insisting that they’re not using AI—that’s just how they write. Before you mock them for it, consider that you too might soon find yourself talking and writing more like a machine: A recent study by researchers in Germany suggested that AI’s writing tics are now cropping up more in spontaneous human conversation. If that continues, maybe negative parallelism will eventually lose its status as an AI-writing tell after all. The fault, dear readers, will be not in our chatbots, but in ourselves.

The Sports Overload Is Here

2026-07-10T16:12:00-04:00

This summer’s lineup of sporting events has been an embarrassment of riches. This morning, the No. 1 men’s tennis player in the world (Jannik Sinner) and the winningest men’s tennis player of all time (Novak Djokovic) played in the semifinal of the biggest tennis tournament in the world (Wimbledon). In the afternoon, Spain and Belgium are kicking off their World Cup quarterfinal match. If that wasn’t enough, the evening brings a full slate of Major League Baseball games, plus NBA Summer League debuts for half the league’s rookies. All of this comes after a packed June in which, at one point, the World Cup, the NBA finals, and the NHL finals all briefly overlapped.

If it feels like there is more sports to watch than ever before, that’s because there is. This year’s World Cup is the biggest ever, the tournament having jumped from 32 teams to 48. It may come around only every four years, but the sports calendar no longer stops. The MLB, NHL, and NBA have all added games over the past few years. In 2020, the NFL tacked on two extra playoff games; the following year, the league added an extra regular-season game for the first time in nearly 50 years. Since then, it has colonized ever more calendar territory, rescheduling games from its standard Sunday slate to the Wednesday before Thanksgiving, Black Friday, Christmas Day, and a number of late-season Saturdays. Every major league has expanded over the past few years, Stephen Master, an adjunct professor of sports media at NYU and the former global head of sports at Nielsen, told me: “There’s not a league that hasn’t been touched by it.” And while this isn’t the first time these leagues have grown, the recent across-the-board expansion surge is unusual, the experts I spoke with all said.

If you’re a sports fan like me, more games to watch can seem like a good thing. You don’t get the tiny African island nation of Cape Verde holding out for a miraculous draw against the mighty Spain without a 48-team World Cup. When leagues expand their playoffs—as, say, the MLB did in 2022—they give more teams a chance to qualify and more fans something to root for. But the glut of games can also be overwhelming, even if you aren’t someone who binges three different leagues. There’s simply too much.

The feeling of excess has to do in part with changes to the sports-media ecosystem. Before streaming, most viewers had access only to local, in-market games and a handful of national broadcasts each week. Now die-hard fans can watch everything (although doing so might require three separate streaming subscriptions on top of a cable package). If you want to consume all 570 hours of top-flight Spanish soccer over the course of a season, that is an option available to you.

But a good deal of blame falls on sports leagues themselves. More games means more money: more ticket sales, more corporate sponsorship opportunities, and more valuable media-rights packages. Master suspects that last factor in particular may go a long way in explaining the ballooning schedules. In 2005, 14 of the top 100 live TV broadcasts were sports, according to Nielsen; in 2025, they made up 95 of the top 100. As the bottom has fallen out of virtually all other live TV programming, networks have come to rely on sports—and they’ll pay through the teeth to keep them. At same time, they’re now competing for media rights against deep-pocketed streaming behemoths such as Netflix, Apple, and Amazon.

The more the value of TV deals swells, Master said, the more money leagues leave on the table by not expanding. In 2024, the NFL sold the rights to televise a few games to Netflix for $75 million apiece—this fall, Netflix will broadcast the first-ever NFL game on Thanksgiving Eve.

In aggregate, the expansions contribute to a feeling of oversaturation, of too-muchness. For a fanatic, either you’re always missing something or sports take over your entire life. How are you supposed to have a regular, socially and familially acceptable Christmas Day while also keeping tabs on five prime NBA matchups and three NFL games? For a casual viewer, the proliferation of games can detract from the experience of watching any individual one.

Consider the NBA. The league introduced a pre-playoffs play-in tournament in 2021 and another in-season tournament in 2023. Yet for many years now, fans have complained that the 82-game season is too long, as have such leading lights as LeBron James and the Golden State Warriors coach Steve Kerr. To preserve their bodies, players end up taking semi-regular off nights (“load management,” to use the term of art), making it next-to-impossible for fans to predict whether the player they’re buying a ticket to see will even suit up that night. The length of the season and inclusiveness of the postseason (two-thirds of teams get in) ensure that most games have little meaning.

The nature and extent of the problem varies league to league. But the drive to grow is universal, and so is the resistance. The move to expand the World Cup generated serious backlash, in part because the group stage of the tournament has become lower stakes and hopelessly arcane. And seemingly no one favors the College Football Playoff’s planned expansion from 12 to 24 teams, because it will render regular-season games less consequential and water down the quality of the playoff itself. A number of MLB stars, too, have called for a shorter season, because 162 games is just flat-out a lot. Unlike basketball or baseball, pro football is far from the point where regular-season contests become meaningless, but that hasn’t stopped its fans from debating whether the NFL is sapping some of the magic that comes from football’s scarcity.

Whatever fans think of these expansions, chances are they’ll tune in. Sure, they’ll complain about how the extra games are diluting the product, but “everyone says that,” Master said. “And then the ratings come out and they’re incredible.” This is not a matter of fickleness; it’s a fundamental misfiring of the free market. Generally, if a business offers a product and it sells, that means consumers want it. But when sports leagues add games, the experience for fans degrades in a way that doesn’t always show up in the dollars and cents. Just because a fan watches the 82nd game of the NBA regular season doesn’t mean they wouldn’t prefer, say, a 70-game season in which every game was a little more competitive.

There’s no going back. FIFA is considering further expanding the World Cup to 64 teams, and the generally strong showings from first-time participants at this year’s tournament will only bolster that push. Despite having tripled just a couple of years ago, plans to double the size of the College Football Playoff already seem to be in motion. And NFL owners are pushing hard for another week of games. “In the NFL, there’s a sense of inevitability that it’ll go to 18 games,” Scott Rosner, a sports-management professor at Columbia University, told me. “There’s almost too much money at stake for it not to.” Owners aren’t going to walk away from an extra $1 billion in revenue, and many players aren’t going to walk away from the extra salary. The experts I spoke with couldn’t think of a single example of that happening.

Sports have always been a business, but it can feel these days as though we’re moving into a hard-knuckled, wring-out-every-penny era. The ever-multiplying micro-sponsorships, the split-screen commercial breaks interrupting play, the carving up of media rights, the expanded schedules—it all chips away, little by little, at the viewing experience. Add all of that to the way betting is reshaping the landscape, and in the process something intangible about sports fandom is being lost. Ultimately, every business has one destiny: to grow.

A New Phase of the AI-Jobs Panic

2026-07-09T15:59:00-04:00

In late March, I started receiving daily texts from the federal government about AI. “🇺🇸AI is changing how we work and live,” one message read. “You might feel curious, skeptical, or unsure—that’s normal.” I had enrolled in an AI-literacy course from the Labor Department created to help workers succeed in the ChatGPT economy. The weeklong program, created in partnership with an AI start-up and delivered by text message, was supposed to equip Americans with “foundational AI skills,” according to an agency press release. But the government’s texts were not reassuring. One message encouraged me to ask a bot for “side hustle ideas.” Another suggested that I brush up on my AI skills by doodling: “Grab a friend and see whose drawing of a hippo AI can recognize … and whose it mistakes for a lumpy potato. 🥔.”

When it comes to AI’s threat to jobs, America has acted like a deer in headlights. For all the catastrophic messaging about looming layoffs, efforts to prepare for a major transition have lagged. After speaking with a roster of the nation’s top business and political leaders, my colleague Josh Tyrangiel concluded earlier this year that no one seemed to have a plan for how to proceed. Government efforts to shore up the labor market have been largely underwhelming. AI-literacy courses like the one I took are hardly a sufficient response if you believe that mass job loss is forthcoming; the Trump administration announced a goal last year to expand apprenticeship programs, but progress on that front has been middling. Meanwhile, the tech industry has barreled ahead in its efforts to develop more capable models. Earlier this year, Anthropic’s Dario Amodei warned that “AI isn’t a substitute for specific human jobs but rather a general labor substitute for humans.”

But over the past several weeks, politicians and tech executives have started to make a show of more seriously preparing the country for a future of AI layoffs. As promising as these new efforts are, many of them also end up serving the interests of Silicon Valley.

Consider a flashy proposal for state ownership of AI companies. Last month, Senator Bernie Sanders proposed the AI Sovereign Wealth Fund Act, which would give the federal government a 50 percent stake in major AI companies including Anthropic and OpenAI. The act would also give an appointed commission voting shares to help “stop bad decisions that will reap massive job loss,” Sanders said on a press call. The legislation, which calls for the tech industry to hand over trillions of dollars worth of stock, is unsurprising coming from Sanders, who regularly takes aim at “Big Tech oligarchs.” What’s surprising is the fact that at least one of the alleged Big Tech oligarchs is on board with a watered-down version of Sanders’s proposal.

After Sanders first announced his plan, Sam Altman requested to meet with the senator. The OpenAI CEO reportedly told Sanders that although he does not endorse the exact plan, he supports the idea of public ownership of AI companies. Altman has been flirting with such ideas since even before ChatGPT was launched, and in April, OpenAI endorsed the creation of a “public wealth fund” that would give every citizen “a stake in AI-driven economic growth.” More recently, according to the Financial Times, Altman has had recent conversations with the Trump administration about public ownership of OpenAI and its competitors; the company is reportedly floating giving up a 5 percent stake.

[Read: Why everyone is suddenly talking about ‘universal basic capital’]

Still, it’s difficult to imagine a future in which our dysfunctional Congress passes a law to take a stake in AI companies, and then the government seamlessly redistributes the earnings to the rest of us. And regardless, such arrangements are unlikely to save a flailing labor market. Sanders’s aggressive wealth fund, for example, aims to start by paying roughly $1,000 to each American annually—which is not trivial, but is also far from a solution to mass unemployment. And private companies don’t give away equity out of altruism. If the government were to seize control of AI companies, the country could end up responsible for bailouts (although Sanders’s bill prohibits use of the fund for such purposes), and public ownership could dilute the demand for more onerous regulation. Perhaps that’s why Gwynne Shotwell, the president of SpaceX, home to Elon Musk’s AI efforts, announced this week that she and her husband would give stock to Trump Accounts, the savings accounts for children that just launched. Anthropic has also said that it would like to invest in researching “AI sovereign wealth funds” as a possible response to extreme unemployment.

AI companies are eager to be seen as supporting other initiatives too. In May, OpenAI’s nonprofit foundation, which owns roughly a quarter of the AI company, announced that it would spend $250 million on grants and partnerships to support the forthcoming economic transition, while also building its own team to seed new ideas. And last month, Anthropic committed $350 million toward similar efforts, much of which will fund “major research trials and program evaluation on promising public policies.” Specifics are still being worked out, but both organizations have noted an interest in, for example, investing in efforts to better measure how AI is affecting labor markets, as well as unemployment-insurance reform. (Anthropic declined to comment; a representative for the OpenAI Foundation pointed me to the company’s April policy paper.)

Economists, for their part, remain unsure about what types of policy interventions could best mitigate future problems, or really how big those problems are likely to be. AI has not yet led to widespread job losses, and many economists aren’t convinced that a jobs apocalypse is inevitable. But even absent the extreme, if moderate labor displacement occurs quickly, America could be in for a real shock. In that light, one new nonprofit, Raise Us, launched last month with the intention of testing out different policies to see what works. Led by Gina Raimondo, Joe Biden’s commerce secretary, and Eric Holcomb, a former Republican governor of Indiana, the organization has already raised more than $500 million from private companies and philanthropies (including the Rockefeller Foundation; Melinda French Gates’s group, Pivotal; and Emerson Collective, which is the majority owner of The Atlantic). Some of that funding comes straight from Silicon Valley: Anthropic, Amazon, Microsoft, and the OpenAI Foundation have contributed cash to the effort and are among the organization’s founding partners.

Raimondo, who worked extensively on AI policy during the Biden administration, told me that she hopes that by doing smaller-scale experiments now at the state level, the organization will gather data on which interventions are most effective, helping inform federal policy efforts down the line. (A set of both red and blue states—Utah, Connecticut, Arkansas, and Maryland—have signed on as initial government partners.) For example, the group is interested in testing wage insurance. Under such a policy, if someone loses a job and accepts work at lower pay, wage insurance would aim to temporarily fill some of the gap. There is “some positive evidence” in favor of the policy, David Autor, an MIT economist who serves as an unpaid adviser to Raise Us, told me, but it has “never been done at any significant scale in the United States.” The group also plans to invest in a slew of other interventions, including apprenticeship programs and career-navigation tools. Overall, the group’s efforts will likely be useful in generating real-world policy evidence that is “undersupplied” and “extremely valuable,” Susan Athey, a Stanford economist who is not affiliated with Raise Us, told me.

[Read: The AI backlash could get very ugly]

At the same time, the tech industry’s association with Raise Us is also a play to boost its flagging reputation. Brad Smith, the vice chair and president of Microsoft, told me that the Raise Us coalition is similar to the public-private partnerships that formed in response to the pandemic. It’s a compelling comparison, but a flawed one: Imagine if the vaccine companies involved with Operation Warp Speed were also engineering more sophisticated viruses. Silicon Valley has wedged itself into a strange position. AI companies are racing to automate work while simultaneously preparing to parachute in as saviors.

Of course, shepherding a smooth labor transition is in Silicon Valley’s self-interest. An AI backlash is brewing, and tech companies’ reputations will only further degrade if layoffs mount. The industry also has reason to worry about the federal government taking far more dramatic action against it. But all this hullabaloo around wealth funds and public-private partnerships is about much more than just optics. AI companies are leveraging the current anxiety over layoffs to induce greater dependence on their bots. Several industry-supported efforts to ward off a jobs crisis involve training people to better use AI. In Maryland, for example, Raise Us is supporting the launch of a start-up-accelerator program, which will provide displaced workers with financial assistance—and access to AI tools to help them start businesses. And almost half of Anthropic’s $350 million commitment will go toward creating a national fellowship called Claude Corps. Through the program, Anthropic will pay early-career workers $85,000 each to spend a year working to integrate Claude across at least 400 nonprofits. The solution to Claude’s threatening entry-level workers’ jobs: Hire young people to further evangelize Claude.

The Newest Way to Go Analog

2026-07-09T12:33:21-04:00

When the iPod Nano was first released, in 2005, it cost $199 and was sold on the promise of limitlessness. This year, Celeste Stange bought her magenta 8-gigabyte model on eBay for $69 and the exact opposite reason. Every time she’d pick a song on Spotify to stream, she’d think about the millions of other songs she could listen to instead and get paralyzed by musical FOMO, she told me. “Now I only have what’s on here.”

Stange, who is 29, is part of a recent “analog” movement in which people—usually those in Gen Z—opt for less distracting alternatives to their “everything” device. Those alternatives are not always, in fact, analog, but are in many cases older digital devices: an iPod, a digital Canon PowerShot, a DVD player. Tiffany Ng, the 25-year-old author of the newsletter Cyber Celibate, now has a first-generation iPhone, an 11-year-old iPod, two CD players, a Walkman radio, and a 1986 Macintosh Plus that takes 45 seconds to load the “Welcome to Macintosh” screen.

Ng lives in Williamsburg, Brooklyn, where 20 years ago, the word analog would’ve conjured hipsters getting into vinyl. The argument then was that a record player produced real, textured music in a way an iPod’s digital files could not. But today, people are “going analog,” as they call it, to escape devices that offer endless options, in favor of those that offer a modicum of constraint.

The iPod’s original tagline—“1,000 songs in your pocket”—suggested that you could dance like the carefree silhouettes in the ads because you didn’t have to lug around CDs. This was the era when technology was “convenient, but not connected,” Tony Fadell, a former senior vice president at Apple who is known as the “father of the iPod,” told me; then the iPod became the iPhone, which soon had an app store, and convenience and connectivity became inextricably linked. People had their library of songs, but now they also had app notifications and Angry Birds and Instagram posts from that girl they went to middle school with. Eventually, streamable Apple Music replaced iTunes, and tens of thousands of songs became 100 million songs. “I can’t go through all of it,” Stange said.

Stange could still carve out her own corner of Spotify through playlists, but on her Nano, she truly has only music she chooses, with artist photos she uploads manually. For many people, that little bit of added friction is part of the appeal. Jess Fisher, a 29-year-old actor in Los Angeles, now buys new CDs each month, which she puts on her Innioasis Y1, an iPod-esque MP3 player that the company started making in 2023, after users complained that their touch-screen MP3 devices were too distracting. “I am more excited about music because I am restricting myself from it,” she told me. When we spoke, she’d just gotten a new CD. “I’m going to sit down and listen to it and relish it, because I’ve been waiting a week to get it.” She also looks forward to the five free weekly MP3 downloads she gets with her library card, through a music site called Freegal. She has an alert set to repeat every Monday: “It’s Freegal Time!”

I spoke with nearly a dozen people trying out similar technology. Isaac Mosna, who creates YouTube videos about tech under the handle Canoopsy, started taking photographs on a first-generation iPhone because he was nostalgic for a time when “everything was a little more physical and real.” (The older camera also makes the pictures look warmer, he said.) Others told me about their Nintendo DSes and emulators they’d filled with vintage games, so they could play without distractions. These choices have become popular enough that they’re juicing secondhand markets for older tech. On eBay, people searched iPod 1,300 times an hour on average last year, and prices of certain models are up by more than 50 percent, according to data provided by the site. Back Market, a refurbished-technology company, started carrying iPods, Game Boys, and other retro tech after a limited run of Nokia 3310 phones (which can basically be used only to call, text, and play Snake) sold out much faster than expected, Thibaud Hug de Larauze, the company’s CEO, told me.

For at least some people buying into this trend, the logic goes something like: I get a DVD player, therefore I learn how to exist comfortably in the present moment. Ng has been replacing a different modern piece of technology with its older counterpart every month, an experiment she began after her iPhone broke. For the five or so hours that the Genius Bar was repairing it, she “felt so, so stupid.” She didn’t have a way to tell time. She didn’t know how to get around Manhattan without Google Maps. She decided then that she wanted to know she could live without modern technology. When she posted a newsletter titled “I chained my phone to a wall for a week,” people DMed her to ask where she’d bought the chain. (It was an old belt.)

Going “analog” is also one of the few ways to own an actual copy of a song, a movie, or a game these days. And buying those products means a person has to commit to their own taste more than they would by just pressing “Play” on “Fun Upbeat Mix” curated by Spotify. It has given Stange the ability to say, “I’m not going to pretend that Geese is the second coming of God” just because everyone else is listening to them. She’d gotten so used to streaming, though, that she wasn’t sure what to put on her iPod at first. She looked up a Rolling Stone “Greatest Albums” list and downloaded some of the recommendations. Fisher did the same.

A CD or DVD is more work to buy and can physically break down in a way a Spotify playlist cannot, but the people I spoke with generally framed those inconveniences as part of the experience. “If I want to listen to an album that I really love, it involves me spending maybe $20 on a CD, it involves me putting that CD on, it involves me using the physical remote,” Mosna said—it’s “an experience.” (Cleaning and maintaining his CD player is a bit of a pain, though.) Dan Cohen, a 24-year-old fashion designer, told me his professors couldn’t imagine why anyone would want the cross-body CD holder he’d made for his undergraduate thesis: They’d lived through the annoyance of CDs getting scratched, iPods crashing and deleting music, and DVDs getting stuck on their menu pages for eternity. And some of these devices were outmoded for a reason. Ng, the newsletter writer, got the 1986 Macintosh in part to play around with PageMaker and its word processor, but she’s still trying to figure out exactly how to use the computer.

After all, modern “analog” enthusiasts still have backups. Everyone I talked with had kept their smartphone. When Stange and I met, she took out her magenta Nano and her laptop, to show me how she downloaded her music onto the iPod. The Nano promptly died. She plugged it into the laptop to charge, but still, no dice. “I’m pretty sure it broke on the way here,” she said, and told me she’d need to figure out how to fix it. She sounded a little excited about the challenge. In the meantime, she still had her Spotify subscription.

*Illustration sources: Adam Rountree / Bloomberg / Getty; Jaap Arriens / NurPhoto / Getty; Jacobs Stock Photography / Getty; liangpv / Getty; Nick Dolding / Getty; trumzz / Getty; Yoshikazu Tsuno / AFP / Getty.

What if It’s Not the Phones?

2026-07-09T07:00:00-04:00

When the 82-year-old psychologist Peter Gray describes the way he grew up, he punctuates the anecdotes by saying that modern parents would be arrested for letting a child have such fun. When he was 4 years old, he would walk to a store in Minneapolis to buy cigarettes for his grandmother. When he was 11, he would sometimes stay home from school in Hill City, Minnesota, to operate a newspaper printing press owned by his mother and stepfather.

His parents were not arrested, and that’s because the childhood they permitted him to have was basically normal at the time, even if his family did have a newspaper printing press in the house. As a boy, Peter was obsessed with fishing and baseball; neighborhood friends taught him how to ride his bike and catch grasshoppers. Although Gray’s career as a scientist would begin with laboratory studies of rat hormones, he eventually found his way to writing about his childhood, in a fashion. Over the course of his 30 years in the psychology department at Boston College, he mixed principles of biology and anthropology to put together an evolutionary theory of play.

Gray’s academic work defines play as a self-directed activity done only for its own sake. This, he came to believe, enables kids to figure out how to solve their own problems, nurture their own relationships, make their own rules, and manage their own disappointments. But he says that our society has spent the past 70 years or so interfering with that process. We’ve made it harder and harder for kids to do anything: They’re kept indoors for greater portions of the day and given less unstructured time; they play organized sports supervised by adults; they don’t go anywhere alone. Gray grew certain that this loss of independence has been harmful to their mental health.

Gray’s theory, which he laid out in a 2013 book called Free to Learn, quickly found a welcome audience. The book was celebrated by advocates of free-range parenting and won endorsement from academic luminaries such as Steven Pinker. When Gray’s fellow psychologist Jonathan Haidt and his co-author Greg Lukianoff published their 2018 best seller on the threat of safetyism, The Coddling of the American Mind, they used the title of Gray’s popular TEDx talk “The Decline of Play” as a chapter header. Haidt, who is an Atlantic contributor, told me that Gray was “the star academic” in the section of his book that deals with play. “I wish every school in America could hear a talk by Peter Gray,” he said.

Only recently has Gray expanded his idea in a way that is not quite so crowd-pleasing. Children’s need for unstructured play and exploration (guided by some safety rules and common sense) applies not just to vacant lots and city parks and backyards in the suburbs, he says, but to other settings too. It now extends to the wild spaces of the internet. “To grow up well, children have to be able to play in the world that they’re growing up in,” he told me when we spoke at his home in late winter. Kids should be free to play without their parents’ supervision, Gray insists, even when they go online.

Gray has always been a playful academic. As a graduate student at Rockefeller University during the late 1960s, he once filled every mailbox at the school with a note proclaiming that neckties were no longer required in the dining hall because they stifled thought by cutting off circulation to the brain. But the turning point in his career came a decade later, when his son, Scott, took up the mantle of rebelling at his school. Gray and his now-late wife moved him to a nontraditional school in Framingham, Massachusetts, where children received no formal coursework and directed their own education.

Scott thrived in his new environment, and Gray, who saw how much happier and more engaged his son became, pivoted from doing lab experiments on rats to making more philosophical explorations of play and learning. He also studied his son’s new school, publishing survey data on the careers and lives of its alumni, as well as detailed observations of how its students played.

Eventually, Gray would have enough of structured academia himself. By 2002, he’d made sufficient money off of a well-regarded psychology textbook that he was able to resign from Boston College and live comfortably in the small town of Millis, Massachusetts. The back of the wood-paneled house that he shares with his second wife is made entirely of glass, providing a broad view of the Charles River. By his account, his retirement has been as idyllic as his childhood. Gray sometimes kayaks against the current, up the river, for exercise.

When I visited him on a frigid day in March, he was wearing the uniform of a practical person—simple shoes, navy trousers, light layers topped with a grandpa cardigan. David Sloan Wilson, an evolutionary biologist and friend of Gray’s who is a professor emeritus at Binghamton University, described him to me as an old man with a “very boyish look.” I would say he is more like a child’s drawing of a nice old man: pure-white hair, a reedy frame, smile lines.

Wilson also described his friend as a pied piper, apparently intending this as a compliment. And from his riverside retreat, Gray has been involved in leading a movement. In 2017, he joined up with Haidt and two others to found the nonprofit Let Grow. The organization, which raised about $2 million in contributions in 2024, encourages parents and teachers to stop watching kids so intently, and tries to fight “neglect” laws that frame a lack of child supervision as criminal or reckless behavior. Let Grow has also developed a program called Play Club, through which schools can offer age-mixed free-play time when the kids (mostly) supervise themselves.

Gray and Haidt both served on the group’s board of directors. They had a collegial relationship, even though there were some minor differences in approach and worldview. The first of those was on the subject of kids and video games: Gray thought that video games provided kids with fruitful ways to play without adult control and was adamant about their value; Haidt respected that position but wasn’t so sure. The two psychologists also disagreed, from time to time, on whether kids should be using social media. But these seemed, at first, like secondary issues.

Then, in 2023, Haidt sent Gray a prepublication copy of his next book. The Anxious Generation: How the Great Rewiring of Childhood Is Causing an Epidemic of Mental Illness opens with an extended metaphor comparing smartphone and tablet use to a spine-melting trip to Mars, and goes on to make the case that personal technology has caused a full-scale youth-mental-health crisis. Its argument seemed to fit the moment: Children were reporting that they didn’t like how much time they spent on social media and didn’t feel like they were in control of their habits; some were truly suffering. The Anxious Generation gave them—and their parents—language to describe what was happening.

[Read: End the phone-based childhood now]

Haidt’s book went on to spend more than two years on the New York Times best-seller list. It was translated into dozens of languages and excerpted in this magazine. And the policies that it suggests, to remove smartphones from schools and bar kids younger than 16 from social media, quickly came to seem like obvious solutions. (In the past few years, they’ve been taken up by legislators in the United States and abroad.)

But when Gray first read the manuscript in his lofted study overlooking the river, he was appalled. “The book frankly makes me mad,” he told me. “I have to say that. I think it’s unethical.” Although The Anxious Generation goes on at length about the benefits of free play, and even makes specific mention of Let Grow, its message overall was for Gray inimical to the nonprofit’s mission. As he sees it, the analysis improbably suggests that taking away phones would prompt kids to run around exploring as their grandparents had done. The few freedoms that kids had left were private communications with their friends and some independent movement, permitted only so long as they could be tracked and called. More than that, Haidt’s book implies that kids cannot be trusted to delve into the online world on their own, or even taught to do it safely. The internet is too dangerous for children—too full of scary strangers and powerful temptations—much in the same way that parents and pundits had decried the perils of the physical world generations before. Haidt had wanted feedback on the manuscript. Gray told him he disagreed with its premise.

Months later, after the book came out, Gray stepped down from the Let Grow board so that the other members wouldn’t feel caught in the middle of a conflict. Then he posted a critique to his Substack. Gray wrote that he took “no pleasure” in rebutting his colleague’s work. “I have tried to avoid it but no longer can,” he wrote. “As a society we have almost a knee-jerk reaction to believe that the solution to any problem experienced by kids is to deprive them of yet one more freedom, and this book is helping to jerk some of those knees even further.”

The two men haven’t spoken a word to each other since their falling-out. “Jonathan Haidt is a likable person,” Gray told me. “He’s polite. He’s generous.” Gray said he is a fan of Haidt’s previous work: “His strong point has always been kind of large, somewhat philosophical arguments based on general observations and a certain amount of evidence, and he’s very good at that.” But Gray viewed Haidt’s newest large, somewhat philosophical argument as not only incorrect but immoral.

The first time we spoke, Gray referred to social-media age minimums as a violation of human rights. When we met in person, I asked him whether that was truly his position. He repeated that it was. Before The Anxious Generation was published, Gray had been working on another book about the broad topic of play. But he scrapped that one after posting his rebuttal, and instead began to write a full-length counterpoint to Haidt’s ideas for an imprint at Penguin Random House. That book, titled Restoring Childhood: How to Set Kids Free in the Age of Anxiety, is due to publish in September.

The new book will argue that the mental-health crisis affecting children is real, but has nothing whatsoever to do with what Gray describes as the “moral panic” over smartphones and social media. The real problem, he says, has to do with schools—and in particular with the 2010 rollout of the Common Core standards, which narrowed teachers’ options for creative curricula and increased the amount of time that the average American student spent taking tests.

To make that case, Gray points to the American Psychological Association’s annual Stress in America study, which surveyed kids in 2009, just before Common Core was introduced, and in 2013, just after. In 2009, 43 percent of U.S. teenagers said that performing well in school was a source of stress in their lives. In 2013, this number jumped to 83 percent. Gray found analogous survey data from before and after similar educational reforms in Sweden and England were put in place.

[Read: The flip-phone cleanse]

School policies were not the only things that changed from 2009 to 2013; smartphone use, for example, skyrocketed across the same few years. But lots of evidence affirms the notion that in America, at least, children are more stressed out by school than by any other aspect of their lives. Young people often say that they hate school, and youth suicides are far more common during the school year. In 2024, 68 percent of U.S. teenagers surveyed by Pew Research Center said that they felt a great deal or fair amount of pressure to get good grades—significantly more than those who said they felt pressure to look good or fit in. Studies of teens in North America and parts of Europe also suggest that school pressure has increased more for girls than it has for boys over the past two decades, which is consistent with the fact that, in some respects, the teen-mental-health crisis has been more intense for girls.

Restoring Childhood goes on to make another, even more surprising argument: It says that computers and video games have actually been responsible for improving children’s mental health. Teen suicides rose in every decade from the 1950s through the 1980s, Gray writes, as restrictions were increased on children’s freedoms. Anxiety and depression seem to have been rising too. But that trend was temporarily reversed by the arrival of the digital world. Suddenly, kids had a new place where they could connect with one another, make their own rules, and solve their own problems. They were among the early adopters of the new technologies, and so became authorities in their households, giving them a chance to feel competent and helpful. Teen-suicide rates never went back down to the levels of the 1950s, but they did decline by about 40 percent from 1990 to 2010. “Everybody was ignoring that,” Gray said. “Nobody was writing about that.”

Just two years ago, Penguin Random House put out The Anxious Generation. Now the publisher seems confident that people are ready for a counternarrative: Gray says that he received a $500,000 advance for his newest book. Wilson, the Binghamton professor and Gray’s friend, told me that he read the book in manuscript form and found himself convinced. “I want it to have the exact same exposure and impact as Jonathan’s book,” he said. “I would like it to be as splashy as it could be and to set up conversations at every level as to which of these interpretations is correct.”

You will not be surprised to hear that Haidt has a very different reading of the evidence. When I asked him what he made of the claim that computers were actually a boon to children’s mental health from 1990 to 2010, he instead proposed that any improvement during that period might have resulted from the phasing out and banning of leaded gasoline. (Lead exposure has been tied to developmental disorders and mental-health problems.) As for Gray’s critique of his smartphone-and-social-media hypothesis, Haidt said that it was overly reliant on the dissenting opinion of what he characterized as a minority of researchers. In particular, he mentioned Candice Odgers, a psychology professor at UC Irvine, and Christopher Ferguson, a psychology professor at Stetson University.

Gray does feature Odgers and Ferguson in Restoring Childhood, but these are not the only scholars who have taken issue with the science as presented in The Anxious Generation. I spoke with more than a dozen people who study technology and child development, and many expressed concern that Haidt overstates the strength of correlational findings and suggests causation where it hasn’t been proved. (A 2024 report on teenagers’ use of social media from the National Academies of Sciences, Engineering, and Medicine concludes that “the scientific literature on the health effects of social media use is mixed and inconclusive.”) Several of them also quibbled—as did Gray—with Haidt’s emphasis on controlled experiments that found people’s mental health improved after breaks from social media. They said these are flawed because participants consciously or subconsciously know the results that are expected of them. (Haidt, when I put this to him, replied: “If all you can say is, Well, maybe they could guess the hypothesis, then you basically are saying all psychological research is useless.”)

[Read: What did people do before smartphones?]

But if the quality of Haidt’s arguments and evidence is up for debate, the same is true of Gray’s. The dangers facing kids on social media, for instance—in an ecosystem that was specifically designed to capture their attention for profit—aren’t quite analogous to those they’d find offline. Or take the crucial data from the Stress in America surveys, which are presented in Restoring Childhood as a meaningful signal of the harmful effects of Common Core reforms. Reported levels of school stress did double from 2009 to 2013, according to that work, but the numbers roughly doubled for other common stressors, too, including family finances—so any school-related effect on stress does not appear to be unique. When I asked Gray about this issue, he said it had been “nagging” at him, and that he was going to add a footnote to the book about it before publication. I pointed out to him a few weeks later that the surveyors had also changed their methodology between 2009 and 2013. The phrasing of the questions had shifted; the first survey had asked respondents to select their top two stressors, but the second one asked them to assign scores to a list of possible stressors. Gray was caught off guard by this, and he went on to ask his publisher to adjust or remove any reference to the Stress in America surveys. That request arrived too late to change the print edition, but Gray said he plans to make the edit to the ebook and audiobook.

Restoring Childhood does offer other lines of evidence, though. “I think there’s a reasonable hypothesis here,” Ferguson told me when I asked about Gray’s book, which he had read in advance, and blurbed. He said he thinks that focusing on schools as the source of children’s mental-health decline makes sense, but added that he would like to see more evidence that the school environment had gotten that much worse. “My memory of schools in the ’70s and ’80s was: They also sucked,” he said.

Odgers, who also provided an endorsement for Restoring Childhood, told me that she appreciates the fact that the book is “broadening the conversation” about children’s mental health to include “a major stressor as reported by young people, that we actually see in the data.” But she expressed frustration at the logic used by Gray and Haidt alike. She noted their shared willingness to apply one explanation (video games, unleaded gas) to the mental-health improvements of the 1990s and 2000s, and then a completely different one (Common Core, social media) to a later section of the same trend line. No serious epidemiologist would reason in this way, she said. Both Gray and Haidt tended to downplay other obvious factors, such as the severe adult-mental-health crisis that unfolded during the same years. “Caregiver mental health is by far the strongest predictor of childhood mental health,” Odgers said.

Pete Etchells, a professor of psychology and science communication at Bath Spa University, also pushed back on the idea that Common Core is the primary cause of mental-health problems among American kids. “This is a common trap that we fall into when trying to figure out what’s going on with those declines,” he told me. “We try to answer the question of ‘What one big thing can explain this?’ The answer, in my view, is that there isn’t one big thing.” This was generally the thesis of Etchells’s own book Unlocked: The Real Science of Screen Time (And How to Spend It Better), which came out the week before The Anxious Generation did, sold only a few thousand copies, and received hardly any attention at all.

Come September, the fight over that “one big thing” will be renewed. Which change that happened 15 years ago was the real source of so much misery for children? “You can’t run experiments on history,” Haidt said, so we’ll never be able to prove that smartphones and social media caused the steep decline in youth mental health. “We just have to say which hypothesis is more plausible,” he said—and he’s yet to hear one more plausible than his own.

When I met with Gray, he said that he has total confidence in his idea: “The evidence is really very overwhelming.” Later on, I tried to press the issue: Couldn’t there be some other factors in the mix? What if Common Core had been just one of many causes of the problem? “It would be nice” if there really weren’t any one big thing, he said, but he simply didn’t feel that this was the case. “So far, I haven’t heard of any other possibility that has the same plausibility.” He’d been studying the numbers and considering the alternatives, and he didn’t see how his theory could be wrong.

Something Incredible Every Single Game

2026-07-08T18:24:52-04:00

Two hundred fifty years and two days into the American experiment, a 55-year-old bespectacled bald man from Liverpool enters a sterile hotel conference room in Atlanta, shaking his head. “It’s all gone to hell, hasn’t it?” he mutters.

In 14 hours, the United States men’s soccer team is scheduled to play Belgium in the World Cup Round of 16, a match that ought to be a celebration of the U.S.’s triumphant, and somewhat unexpected, run in the world’s biggest sporting event. But Folarin Balogun, Team USA’s star striker, was given a red card during the previous match with Bosnia-Herzegovina—he stepped on another player’s ankle—that made him ineligible to play. This led President Trump to petition FIFA to review the penalty, which, of course, triggered allegations of collusion and corruption: International lawyers were summoned to draft appeals, and a joyous sporting event started to look more like a legal drama.

For Roger Bennett, the scandal threatened to overshadow every value he has been working 16 years to promote. “This is not why we watch,” he told me just after 6 a.m., settling into a chair for what would be almost two straight hours of TV appearances. “It’s antithetical to the beauty we are trying to protect.”

If this kind of language about sports turns you off, you will likely not enjoy Bennett or the many hundreds of pieces of World Cup content that his company, the Men in Blazers Media Network, has put out over the past month. In the broadest terms, Bennett is a soccer podcaster and new-media executive. A better description of him might be: America’s chief soccer evangelist. Before we knew that the U.S. would get crushed by Belgium 4–1, before the team’s chances for World Cup glory died on the field, Bennett declared that Monday, July 6, would be the most important day in the country’s history. In theory, he was joking—but honestly, I wasn’t sure.

Andrew J. Clark / ISI Photos / Getty

Roger Bennett during a live show before the FIFA World Cup 2026

Ever since Bennett started his podcast, on a whim in 2010, he has been monomaniacally devoted to getting Americans not just to enjoy soccer but to become emotionally invested in it. For Bennett, the sport is a way to access the big, complex feelings and topics that typical sports fans don’t always talk about: community, love, agony, joy, Emily Dickinson’s poetry. A box of tissues emblazoned with the phrase Cry Proudly is prominently displayed in his podcast studio.

I first met Bennett in 2014, when his stint covering the World Cup for ESPN made him a niche celebrity among the set of weirdos in America (me) obsessing over soccer and waking up before dawn to cheer on clubs from English towns they’d never been to. Bennett was certain that the United States would soon embrace soccer—an intoxicating but tenuous idea that now reads as prescient. Millions of Americans have watched the men’s team make a run in the World Cup this year—the first time the country has hosted the men’s tournament since 1994. In fact, Monday’s game against Belgium reportedly pulled in more viewers than the 2025 World Series and Game 5 of the NBA Finals.

[Listen: How the World Cup explains the world]

This is a moment of vindication for Men in Blazers, but it also has a greater meaning for Bennett, who became an American citizen in 2018. He routinely ends his podcast monologues with the phrase “I love America” and openly expresses his patriotism. “I grew up in the dying embers of the English class system,” he told me. “I felt very trapped. America always felt like the opposite, like opportunity. For me, that was life-affirming, life-saving.”

Maybe that all sounds cheesy. But it’s been hard to miss the collective enthusiasm and sense of American community emanating from the tournament: the initial delights of watching Scotland’s Tartan Army drink and bagpipe its way through New England, winning over steely Bostonians along the way; or the residents of Lawrence, Kansas, embracing the Algerian team with marching-band pep rallies. There was the viral pleasure and even pride in seeing foreigners encounter Buc-ee’s with reverential appreciation or giddily experience industrial quantities of Mountain Dew Baja Blast at Taco Bell.

Then there were the games themselves, seemingly broadcast on every available public television in America. Over the past month, I’ve seen strangers in the airport rapturously celebrating over last-second goals, gaggles of men and women kicking soccer balls on city streets while clad in a veritable United Nations of jerseys. People in my life who are normally allergic to sports have come over for marathon World Cup viewing sessions. At one point I found myself—a man from Cleveland—wearing a Senegal jersey, sweatily embracing a Senegalese man after a spectacular volley sent the ball to the back of the net. It felt like a dream.

Dreams always end, and in a way, that’s what happened on Monday. But Bennett’s larger ideology, that soccer is the “most important, least important thing,” may yet endure. There’s a reason he hired more than 100 people and retrofitted a coach bus into a mobile podcasting studio—a reason he spent the past month traveling across the country for a series of rowdy pre-match shows with fans. Moments like these forge bonds that don’t easily break.

Before the sun is up, I watch as Bennett goes on Morning Joe and CBS Mornings, and rips through a slew of radio and podcast hits. He calls nearly everyone he works with on these shows “a beautiful human being” and ends every interview with the same sign-off: “Big, big love to you.”

Bennett pops up from his table the instant his last interview ends. Within 30 seconds he’s on his phone, rifling off voice memos to people on his staff and agents of players he’s trying to book. “When’s Jon Stewart coming on?” he asks his producer, who pulls up a booking sheet a mile long. He completes seven phone calls in as many minutes just after 9 a.m., and tells each person on the other end that he loves them before hanging up. By 9:30, we’re in a production meeting for that day’s Men in Blazers live show; Bennett is Zooming in from his phone, because he’s outside picking up coffees for his team. A staffer on the call informs him that they’ve made a giant cardboard cutout of a lemon-pepper-wet chicken wing—an Atlanta delicacy—for somebody in the crowd to wave. “You could not be a more beautiful soul. You make the world a better place,” Bennett replies.

The day moves on. A detailed planning meeting is convened to discuss next summer’s Women’s World Cup. Men in Blazers is already pitching sponsors based on its online engagement numbers—according to Blinkfire, a marketing-analytics firm, the company has almost twice the engagement per follower across social media this tournament than the World Cup’s official broadcast partner, Fox Sports. Bennett out-hustles more established outlets by relentlessly blanketing the internet with instant-reaction clips, multiple daily podcasts, and memes; he then uses that attention to drive people to Men in Blazers’ frequent live shows, building an army of loyal obsessives. Listening to Bennett articulate this strategy and then jump into another TV interview, I’m struck by the realization that this whole operation resembles a political campaign as much as a media company. It’s hope and change and a bright new vision for America complete with stoppage time and hydration breaks.

[Listen: How short-form clips took over the internet]

Somewhere around coffee No. 5, Bennett and a few people from his team head to Busy Bee, a legendary soul-food café in Atlanta, to document some of the World Cup host city’s culture—another page from the campaign playbook, though Bennett’s excitement for the chicken and waffles is palpable. Outside next to the parking lot, sitting on a swelteringly hot picnic table, Bennett attempts to explain why he’s been averaging just three and a half hours of sleep a day for the past 26 days. He argues that what many people have been feeling over the past month, with each watch party or viral video of fans going crazy, is what the sociologist Émile Durkheim calls collective effervescence—a feeling of unity that emerges from a shared experience.

Courtesy of Charlie Warzel

Men in Blazers fans gather in Atlanta.

Bennett’s theory is that the World Cup, a rare monocultural event in today’s fragmented world, is one of the few reliable producers of such effervescent spectacles; it’s good for the internet, but also good for the soul. His media-distribution system ties it all together: “When Congo scores that goal, they need the immediate reaction, then they need the Congo fans across America; they need the scene in Kinshasa, the postgame on the field and the tears, the locker room, the Congo fans in Queens or Brooklyn,” he said. “It’s just incredible and it’s happening every single game.”

I can see why one would get swept up in what Bennett describes as “a very profound moment for the nation, which is so busy falling back in love with the world, and the world falling back in love with America.” The entire event feels at times like a summer vacation, a much-needed reprieve from harrowing world events. A cynic could see it as artificial or inauthentic—geopolitics, only without all the horrific stuff. And yet the moments are authentic, which may be why the White House intervention and FIFA’s arbitrary and unusual red-card suspension felt so jarring, even offensive, to die-hard fans of the tournament. It was a reminder that politics always lurk in the background, and that the euphoria is fragile. A U.S. loss would be a stress test.

About an hour into the game, with the U.S. down 2–1 to Belgium and looking positively shell-shocked, Bennett distracts himself by asking another Men in Blazers host, Becky Sauerbrunn, a former U.S. women’s team captain and two-time World Cup champion, what it feels like when you get scored on by your opponent immediately after you score. (Not good is the answer.) Later, when a flub by the U.S. goalkeeper puts Belgium up 3–1, Bennett yells at the television: “Not like this!” The agony is genuine. A close, competitive U.S. loss would hurt, but maybe it would be fine. This result, though—an impotent, scared team that is clearly not ready for the moment—feels like two steps forward and one very large step back. “This is not good for business,” Bennett said to me, cracking a weak smile.

What I’ll remember most about the game is how quickly confidence turned into insecurity. Shortly after the final whistle, announcers on Fox offered a sheepish plea to their massive broadcast audience: This doesn’t have to be the last game you watch. Sitting in a room with Bennett and Sauerbrunn and others like them, people who have devoted their lives to the sport, you could sense just how precarious the moment felt to them. How can you promise hope and change if the results stay the same?

Bennett was adamant that the Men in Blazers’ YouTube livestream start the minute the game ended, as if to avoid giving the audience too much time to think about what they’d seen. For almost two hours, Bennett and his co-hosts, plus special guests including the The Fault in Our Stars author John Green, dissected the match, which Bennett dubbed “a cup of tears and darkness, self-loathing, fear, and human agony.” As far as podcasting goes, the show should have been a grueling, dismal spectacle. But Bennett, who had been up early enough to text me at 4:35 a.m., was slaphappy, making jokes about Thomas the Tank Engine and quoting lines about pain from Dante’s Inferno. All the while, listeners poured into the stream, which became a strange, beautiful form of catharsis. “Football,” Green said one hour into the show, “is not about destinations; that’s the thing that we mistake all the time. It’s about journeys. Because if it was about destinations, no one would like it.”

After the show, Bennett rallied half a dozen people—many of whom had been up for almost a full 24 hours—for a midnight Waffle House excursion. “I’ll always remember this night and being with all of you,” he told the group. The pep talk reminded me of an anecdote Bennett had told me earlier. His mother-in-law had become obsessed with taking family photos at every get-together, no matter how inconvenient or annoying. “What she’s realized is that photographs and memories are inextricably connected,” he said. “I’m very aware of how memory is formed. And in this moment, this tournament, memory is being formed.” Suddenly, it clicked: Bennett is obsessively documenting the insanity, the joy, the collective effervescence so that we remember how this all felt. So we don’t lose it.

I had plans to meet Bennett early the next morning, but I slept through my alarm. When I texted to apologize, he confessed that he had almost missed a morning TV hit, having fallen asleep, laptop on his chest. Political campaigns are exhausting. But Bennett wasn’t defeated. Too much progress had been made. “As I speak to you, I am headed to Atlanta Stadium to watch Lionel Messi face Mo Salah,” he texted back. “The streets are packed. Football is here and thousands of people are ready to make memories again.”

China’s Answer to AI Sticker Shock

2026-07-07T13:58:00-04:00

In recent weeks, Silicon Valley has been fawning over an AI model released by a lab in China. The program, called GLM-5.2, has been called a “marvel,” “very good,” and a “step change.” The billionaire venture capitalist Marc Andreessen posted on X that “AI insiders are saying GLM-5.2 is the first Chinese AI model to match and often beat” the top public U.S. models. Guillermo Rauch, the CEO of the AI-coding platform Vercel, said that he is “genuinely impressed, almost shocked” by GLM-5.2’s coding abilities. Or as one AI founder at a San Francisco dinner party recently told me: “Praise GLM-5.2.”

In a sense, GLM-5.2 is China’s answer to Claude Code, Anthropic’s agentic assistant that has reshaped the AI boom. This has been the year of AI agents—tools that don’t just chat but promise to do stuff on your behalf, whether coding a website or booking a vacation. Chinese AI models have been steadily improving, but none previously proved capable or consistent enough to be used as agents. Now GLM-5.2, developed by the Chinese company Z.ai, rivals some of OpenAI’s and Anthropic’s top offerings and, by many measures, has leaped ahead of Google Gemini. And it is several times cheaper.

[Read: Move over, ChatGPT]

Despite Silicon Valley’s awe over GLM-5.2, an inexpensive competitor couldn’t have come at a worst time for America’s frontier AI labs. Having successfully persuaded corporate America to give their products a try, OpenAI, Anthropic, and Google are now struggling to prove that their tools are worth the money. These bots can be very expensive to use, running up bills into the thousands of dollars, per employee, per month. Uber reportedly spent its entire 2026 budget for Anthropic models in only a few months. Other Big Tech companies including Meta, Amazon, Tesla, and Adobe are also reportedly clamping down on employee AI usage. Citi at one point shut down employee access to OpenAI’s and Anthropic’s most expensive models, according to reporting from 404 Media (which Citi has contested).

Even though political leaders and tech executives have framed the U.S. as in the middle of a contentious technological race with China, Americans can still use Chinese models. While it’s too soon to know whether GLM-5.2 is really capable of replacing America’s top-tier AI agents, any firm or developer who is balking at the costs now might have an alternative. The arrival of GLM-5.2 poses a business dilemma for Silicon Valley—and possibly a national-security dilemma for the country as a whole.

In some ways, America’s AI industry has been here before. Many previous impressive Chinese AI models have not triggered a mass exodus of OpenAI and Anthropic customers, with one major exception: In January 2025, after DeepSeek launched a cheap AI model on par with America’s best, adoption of Chinese AI models leapt up. Within two months, the share of global web traffic to Chinese AI models jumped from roughly 3 to 13 percent, according to research from RAND. OpenAI, Anthropic, and Google quickly responded to DeepSeek with cheaper models of their own, and then the rise of AI agents early this year seemed to solidly put American labs back on top.

[Read: China’s DeepSeek surprise]

Even before Z.ai launched its new model, there have been quiet signs of a shift to cheaper, Chinese models amid mounting concerns about AI bills. Over the first five months of 2026, DeepSeek’s adoption among the 70,000 U.S. firms that use Ramp, a financial-operations platform, increased from 0.1 to 0.3 percent, Ara Kharazian, Ramp’s lead economist, told me. Kharazian added that 6 percent of Ramp customers that spend money on AI use third-party platforms that provide access to many different AI products. On OpenRouter, one such platform, the six most popular AI models are Chinese; in under a month, GLM-5.2 already ranks fifth. These data don’t capture all the software developers and companies directly downloading Chinese AI models, which are typically open source, and configuring them on their own computers—that is, largely scrappy start-ups and academics who don’t have the budget to use a fintech service like Ramp. Chinese models accounted for nearly half of all open-source AI downloads from February 2025 to 2026, according to data from the popular AI platform Hugging Face.

Meanwhile, OpenAI and Anthropic keep releasing more, rather than less, expensive products. And soon, they will likely have even more competition. The Claude Code and broader AI agent frenzy started seven months ago, which is also approximately how far behind Chinese AI firms have been lagging in model development. China’s other labs, including DeepSeek and Moonshot AI, will almost certainly release similarly capable and inexpensive AI agents before long. Coinbase, a popular crypto company, claims to have nearly cut its AI spending in half by defaulting to cheaper models including GLM-5.2 and Kimi, another popular Chinese bot. “The scenario to worry about is China has good-enough models at a quarter of the price,” Kyle Siler-Evans, an AI researcher at RAND, told me. “I think that is likely the future we’re headed toward.”

Kharazian cautioned against overstating this narrative. Whereas some tech-forward firms are pulling back on their AI spending, most American companies already spend very little on the technology: The median Ramp customer spends just $11 per employee on AI. “Not to say that the rest of the market won’t go in that direction,” Kharazian said, but Anthropic and OpenAI will have “ample time to respond” with competitive pricing—as they did with DeepSeek.

Perhaps the biggest obstacle to the ascendance of GLM-5.2, at least in the U.S., will have little to do with model capabilities or pricing. There are serious concerns about Chinese firms essentially using their AI to hoover up sensitive data and steal corporate secrets. The perceived risks of using Chinese technology could create a profound chilling effect among the customers of any U.S. firm—not to mention the uncertainty created by the possibility of federal regulation. Consider that Chinese electric vehicles are by all accounts better and cheaper than their Western counterparts, but they can’t be bought in the U.S.; one possibility is a near future in which Americans are functionally or legally barred from accessing the most cost-effective AI models.

The biggest implications of GLM-5.2 and the coming onslaught of cheap Chinese AI agents may also be geopolitical rather than economic. Whatever soft power the U.S. gains from its technology may wither as software developers in countries with less tense relationships with China turn to DeepSeek and GLM-5.2 in greater numbers (consider how the EU, U.K., and Canada are importing Chinese EVs). Meanwhile, despite Big Tech spending ever greater sums on advanced AI chips to train their models—chips that are banned from export to China—the gap between U.S. and Chinese models has not widened; if anything, it may be shrinking. That means any military, economic, cyberoffensive, or other advantage that AI can grant the nation could be vanishing. America’s lead in the AI race, for the first time since DeepSeek, is at real risk of slipping.

A Sad Kind of Convenience

2026-07-06T15:08:18-04:00

When I was 16, I did something I’m embarrassed to admit: I waited in a long line to buy a video game called Assassin’s Creed III. Over the past few days, though, that experience has become ever so slightly tinged with nostalgia. Last week, Sony announced that, starting in 2028, new PlayStation games will be available only as digital downloads rather than physical discs. Will kids ever get to embarrass themselves like this again?

The transition is indicative of a greater loss—one that I, and I suspect many people, have mixed feelings about. More and more, entertainment companies are ushering people into seamless digital spaces where convenience replaces ownership: games without discs, music on Spotify instead of vinyl, movies on Netflix instead of a theater.

Markets change, and entertainment changes with them; this has always been the case. Before the advent of at-home consoles, public-arcade games were built to be played in short, endlessly repeatable loops—the goal being to pull in more and more quarters with each new attempt. In the 1990s, some developers padded out the lengths of their games and in some cases made them artificially difficult, to prevent customers from completing them during rental periods instead of buying them.

And there’s a fairly obvious supply-and-demand explanation for why the music industry stopped hawking CDs; why DVD-bargain bins have disappeared from some American supermarkets; and why GameStop, once the central node of a booming video-game retail industry, has closed much of its brick-and-mortar empire. When the PlayStation 4 launched, in 2013, just 13 percent of Sony’s video games were being purchased digitally. Last year, that number reportedly approached 80 percent. In its announcement, Sony underscored that the transition from physical to digital is part of an effort to “align more closely” with how most gamers are already choosing to play.

[Read: What DVDs gave us]

Developers see it too: Last month, the publisher behind the upcoming Grand Theft Auto VI—which is expected to be one of the biggest entertainment launches of all time—revealed that the “physical” edition of the game would actually be a box with just a download code inside. Sony’s announcement “probably does move the markets in a big way towards digital,” Giorgo Paizanis, who leads the consulting firm BCG’s gaming work, told me. “But we’re already 80 percent there.” (PlayStation did not respond to a request for comment.)

The convenience of downloads may be an upside, though there are certainly real downsides in the transition away from physical media. When you buy a disc, you own it and can resell it or lend it out the old fashioned way—without online mediation. No corporate middleman was watching me hand my copy of Red Dead Redemption to my friend when I was done with it. Although physical games can be damaged or even decay over long periods of time, I could still loan that same copy out today if I wanted. Digital purchases only grant you a license for use, and that license can be revoked. At around the same time that Sony announced the digital transition for PlayStation, it also alerted customers that more than 500 movies and shows would be pulled from its online marketplace, removing them from the libraries of users who had purchased them. (As an Arts Technica headline put it, “We’re Reminded We Don’t Own What We Buy.”)

[Read: The Amazonification of everything, now as a video game]

Physical games also function as markers of personal taste, just as sprawling record collections or personal libraries of dusty paperbacks do. A copy of Elden Ring likely conveys a different impression than a Criterion Collection Blu-ray, but video-game discs at least may one day radiate a kind of old-school cool. (Early NES cartridges may already possess this energy.) There’s a reason that people are still nostalgic for Blockbuster, and that the decline of physical-media sales slowed dramatically in 2025.

When it comes to vinyl records, at least, part of their appeal today lies in their physicality. Flipping and periodically cleaning a record ultimately personalizes the experience of listening to it. Up close, you can see how the rumblings of a bass guitar, or the vibrations of a clarinet’s reed, are transcribed in the grooves. The motion of playback rhymes with the mode of artistic production. And because you can fit only so many of these records in your house, you inevitably end up listening and relistening to the same ones. Connections form.

Video-game discs are not vinyl. Records produce their own sound, which might be distorted even by a hint of dust or moisture, whereas discs are used to load entirely virtual experiences. If they break, they break. I won’t miss that, even as I recall the feeling of popping that Assassin’s Creed III Blu-ray out of its box, the sound of the disc whirring in my console—small pleasures sacrificed in the name of progress.

A Twist in This Year’s Strangest Literary AI Scandal

2026-07-03T09:19:00-04:00

Jamir Nazir has become the face of the AI-writing crisis. In May, the largely unknown 62-year-old Trinidadian writer was named a regional winner of the prestigious Commonwealth Prize for his short story “The Serpent in the Grove.” But after it was published in the literary magazine Granta, signs began to emerge that the story—about a cocoa farmer who cheated on his wife and then tried to kill her—may have been AI-generated. Among other indicators, Pangram, an imperfect but industry-leading AI-detection tool, flagged the story’s text as 100 percent artificial.

Inscrutable lines plucked from Nazir’s dense prose were mocked and memed. A young woman in the story “had the kind of walking that made benches become men.” Another “smiled like sunrise over a sink.” Soon, other winners’ stories came under suspicion. The Commonwealth Foundation defended the authors, saying that all had testified that their work was original, but it pledged to investigate further.

On Tuesday, the Commonwealth Foundation announced that “The Serpent in the Grove” had been chosen from among the regional winners as this year’s overall prize winner. “The team worked hard to understand Jamir’s creative process and learn how he shaped his story over time,” a spokesperson for the Commonwealth Foundation told me in an email. Razmi Farook, the organization’s director general, had previously issued a statement on the results of its probe: “After a thorough consultation with our judges and careful consideration of all available information, we are satisfied that AI was not used to write the winning stories.” She noted that the investigation did not make use of Pangram or other AI-detection tools, because of their inability to provide conclusive evidence as well as “concerns regarding artistic ownership and consent.” Instead, the foundation said that it had held “detailed discussions” about the regional winners’ creative process and examined “working drafts, time-stamped documents and notes” that showed how they developed their stories.

In a phone interview on Tuesday afternoon, Nazir told me that he feels vindicated—and relieved. “Look, I didn’t use it!” he said about AI. Now that he has won the prize, Nazir said, he is free at last to explain his process and clear his name.

We talked for more than an hour about his writing process, his health (he referenced complications with both diabetes and cancer), and his views on technology. On several occasions, he seemed to avoid answering my questions directly; when he did, some of the answers were circuitous. I was surprised to hear him opine that AI-generated writing will soon be widely accepted in literature, even as he maintained that he didn’t use AI tools in creating his story. He seemed bullish on AI overall, viewing it as a revolutionary technology, though he worried about the repercussions of saying so. Although he couldn’t name any works by Derek Walcott, a writer he cited as one of his main literary inspirations, he said that he had prepared a collection of short stories in Walcott’s style, which he hopes to publish soon.

This conversation has been edited for length and clarity.

Will Oremus: How did it feel to win this award after all of the controversy you’ve endured since you were named a finalist?

Jamir Nazir: Yes, there’s been a lot of controversy preceding this win, and it’s been really hard. To hear people smearing me, and reading all of the crap. They didn’t know there was a real human and a real family behind the story.

One of my most joyful moments in receiving the news that I won the award was sharing it with my mother, who will be 82 in August. My nephews have kept her informed on lots of the negative things. I didn’t take a sword and plunge it into her side, but I felt as though I supplied the sword by entering the competition. So it made me feel so good when I could tell her that I had won despite all the nonsense that they were seeing.

Oremus: I know you’ve said you didn’t use AI while writing this story. But I’m interested to hear more about your writing process. People were curious how you produced this work that was so dense that it almost reads more like poetry than prose.

Nazir: I was born with diabetes. And as a result of that, conventional typing on a keyboard—it’s extremely difficult for me. As I’ve gotten older, the neuropathy has gotten worse. Sitting for long periods of time at a desk gives me some back problems. So what happened is I decided: Look—no better place to write than the couch. And as a result of that, I found out that I can use the speech-to-text function of the Google keyboard on my Android phone …That’s what’s actually producing words, and then I edit them and so on.

That has given me the opportunity to significantly polish text. Because you know, on an Android phone, when the keyboard comes up, you only have a very small space, about three and a half inches, to see the writing. So I would look at those lines, and hold those words in my mind, and keep reviewing them, keep polishing.

But to back up a bit: Why the hell—sorry for the expression—would I need AI? It was absolutely not needed in this story, because I lived this. The story actually has a lot of real people, real places, and real situations. Even the little bread shop I wrote about in the story actually exists—not in my small, little village here now, but where my wife came from, which is another small village.

Oremus: You’ve explained why you think the AI-writing detectors might have mistakenly flagged your story. How did you convince the Commonwealth committee that you didn’t use AI after all?

Nazir: They requested a lot of documentation. They made it clear it was voluntary to produce these materials, because they were not part of the initial rules. But I had to produce all of the previous drafts, and also my character profiles I had sketched out. And of course, I originally had to sign saying that no AI was used.

Oremus: You’ve talked about how the unusual writing style in “The Serpent in the Grove” stemmed from your love of poetry. Who are a couple of your favorite poets who have inspired you?

Nazir: The first one whose poetry I fell in love with was a guy known as Pablo Neruda from Chile. And his teacher or mentor was a lady known as Gabriela Mistral. Both of them had a profound impact on me. Then there is Derek Walcott, a Caribbean poet who, like Pablo Neruda, is a Nobel Prize winner. The thing that got me attracted to Walcott was his complete disregard for the traditional Western sentence structure, which people cite as one of the things that proves my writing was AI. But Walcott created his own style.

I looked at how they all write, and I write poetry in their style too. AI must have been fed all their work. And another thing to that: I have significant poems that I’ve posted in several poetry groups on Facebook. Once it’s on Facebook, AI companies will have data-mined that, right? So they have all of that as a reflection of my style as well, right? I wonder if they can attempt to claim it as their own, as AI-generated. Do you think that’s possible?

Oremus: So you mean that AI gets trained on human writing, and then it generates similar writing?

Nazir: Okay, say AI has been trained with the writing of Will. So it understands what Will does, right? Now, when it sees Will’s writing again—if somebody puts Will’s article through an AI detector—because it’s familiar with that style and construct, it tells itself, This must be generated by an AI system. I’m wondering if it is possible.

Oremus: I don’t know. That’s not how a tool like Pangram works. It’s looking for statistical patterns in the language that are more commonly produced by AI systems than by human writers.

Nazir: But is that true? Why, then, has no court of law in any country, even the tiniest country in the world, accepted as admissible any AI-detector system? Not one country. So that shows you, in terms of the reliability—I’m not saying it’s not helpful, but I think there’s still a lot of refining.

Oremus: You had mentioned some of your inspirations earlier, including Walcott and Neruda. What’s your favorite Walcott work?

Nazir: Walcott has a lot of Caribbean poems, right? And I cannot—there are several, and they talk about the destruction of a village because of the sea. And I wrote something like that. It’s quite a change. And I am advertising a little bit, but I have a collection that I have written, my Caribbean collection, sort of Walcott-style. I tried to edit it as much myself as I could, and it’s ready for publication. So hopefully this award will give me the platform to publish this.

Oremus: But do you have a favorite of Walcott’s poems?

Nazir: A story of Walcott’s?

Oremus: Yeah.

Nazir: To be honest with you, I can’t think of a specific favorite right now. I am getting a little bit of brain fog in recall. I had an excellent memory, and now it haunts me because at times I can’t remember even basic stuff. I think it’s a part of the condition, the illness. And I’m on chemotherapy as well. So that is a hard thing.

Oremus: Some of your posts on LinkedIn, as people have pointed out, are a very different style from your fiction. Which, of course, makes sense, right? I mean, fiction is a completely different mode of writing. But I wondered if maybe you used AI on the LinkedIn posts.

Nazir: No, no, no. I did research with AI. But in terms of the actual writing—I had grown accustomed to very technical and precise writing. I think that AI is a good tool for research— that’s the most value.

And on the same topic of that, what about the typewriter? When the typewriter was first invented, writers kicked hell and said, The thing is writing. You’re supposed to use a quill or your fountain pen. And there was a big hullabaloo. We passed that, and then next came new word processors. I can tell you word processors are machine assistants, because they can check the spelling, right? They can search, find and replace, suggest synonyms, et cetera. Modern-day word processing can do almost everything. Where’s the uproar? It settled down. Now I think the same thing will happen with AI.

Oremus: Because you think that eventually AI will be accepted as just another tool for writers the way that a word processor is, what is so bad about using it? Why not use it?

Nazir: No, I’m not saying it’s bad. But because of this current time, where the debate is on, like it was on for the typewriter or the word processor, I wouldn’t encourage any writers in any kind of literary competition to utilize it now for fear of people criticizing them. Look—I didn’t use it! It’s not only me, Will. It’s also all these people who are painted with this AI brush, right? So I imagine you should stay away from it for any literary competition for the next two or three years. I think that discussions will be held and so on, and then people will get an opportunity to vent.

I don’t know if I’m walking on dangerous ground here with you, because as I was told a lot by the wife and other people, Do not show any appreciation for AI. I see it as being a tool incorporated in the future. Because a lot of people use it—a lot of people.

The $10,000 MacBook Pro Is Here

2026-07-02T13:47:00-04:00

There are many things you can buy for $10,000: A nose job. With luck, a used car. A middling ticket to the World Cup final. Or you could purchase a MacBook Pro. That’s how much the highest-end, fully loaded version of Apple’s laptop now costs—$3,000 more than it did last week.

Maybe you don’t need the most powerful MacBook Pro. But last Thursday, Apple announced price hikes on most of its products. Apple’s cheapest laptop, the MacBook Neo, debuted for $600 just a few months ago. Now it’s less of a steal at $700. Apple’s base tablet model costs 30 percent more. Although iPhones are the same price (for now), every Mac and iPad model is now more expensive. So are other gadgets: Even the HomePod mini, a smart speaker that debuted six years ago, will set you back an extra $30. The day the new prices hit Apple’s website, people ran to Costco and Best Buy hoping to take advantage of some lag between the new and old world.

The products are more expensive because they now cost more to make. Specifically, one particular component has become considerably more expensive: RAM, short for “random-access memory.” RAM is essential in practically every electronic device. It’s what allows you to toggle between the 30 different tabs you might have open right now. And this year, the price of RAM has quadrupled.

Blame the AI boom. Data centers use a gargantuan amount of memory chips. Amid the frenzied AI build-out, the world doesn’t have enough to go around. In a statement issued the day of the price increases, Apple wrote that “the rapid expansion of AI data centers” had forced its hand: “We have never seen a component price increase this much, this quickly.” Seemingly every laptop maker has already jacked up prices at this point. In October, Microsoft raised Xbox prices by up to $70; last week, the company announced another $100 hike. The effects of the memory shortage extend beyond laptops and gaming consoles. A coalition of trade groups recently wrote to the Trump administration that the memory shortage was jeopardizing the “production and availability of automobiles, medical devices, and other manufactured goods.”

If there’s one company that should have been able to weather this crisis, it’s Apple. In the world of consumer electronics, Apple is “an 800-pound gorilla,” Corey Cohen, a computer historian who authenticates vintage Apple products for museums, told me. The company is so big and exacting that it has long been able to essentially name its price for computing parts. Apple CEO Tim Cook has squeezed suppliers to secure better deals and sought to own as much of its production process as possible. Apple’s custom chips also shunt around electrical signals much faster than its competition, so its devices can do more with less memory.

Now Apple’s grip on the global supply chain is slipping. RAM is one of the most expensive components that Apple does not make itself. Instead of prioritizing Apple, RAM manufacturers are selling chips to AI companies that are willing to spend near-infinite amounts of money to acquire memory in the name of building more powerful bots. Apple’s problem extends beyond memory chips to any product AI companies decide they need. In 2013, the CEO of Taiwan Semiconductor, the world’s biggest chipmaker, spent $10 billion to invest in manufacturing Apple processors. Now AI companies are its most valuable customers, and Apple is reportedly fighting for enough production lines to fulfill its orders. Apple is reportedly low on a material known as T-glass, which is made almost exclusively by a single century-old Japanese textile company, and which AI companies have been buying up. (Apple did not respond to a request for comment.)

Compared with other electronics companies, Apple is still in an enviable position. Smaller tech companies are struggling to get memory manufacturers to even pick up their calls: GoPro, the action-camera maker, warned last month that it might go out of business because of the memory shortage. Apple enjoys margins fatter than most consumer-tech companies could dream of. “They’re sitting on a pile of cash, right?” Cohen told me. “Apple could survive selling zero products for years and not be in the red.” Raising prices is a choice by the company to cede as little ground on profits as possible.

No one enjoys paying more for the same thing. The ubiquity of Apple’s products makes its price hikes feel especially noticeable, and analysts I spoke with expect prices on iPhones to rise soon. The iPhone 18, set to be released this fall, could be up to $200 more expensive than its predecessor. The increases can easily compound when you are stuck inside Apple’s walled garden. Most iPhone users also own an iPad, and a third of Apple’s customers own the holy trinity: tablet, smartphone, laptop. iPhone parents raise iPad babies who get Macs during Apple’s annual back-to-school sale.

Memory prices may come down in the next few years as new RAM factories come online. But Apple’s prices are unlikely to ever go back. “Prices generally are a one-way ratchet,” Wamsi Mohan, an Apple analyst at Bank of America, told me. “Customers acclimate to paying more.”

Many Americans already worry that AI will take their jobs, dry their rivers, and run up their utility bills. A pricier laptop may not be the greatest worry, but it’s certainly not going to help sell anyone on the AI future.

So Long to America’s Favorite Everymensch

2026-07-01T17:20:00-04:00

Yesterday, Freddy woke up in a hotel room in downtown Boston that had been paid for by the celebrity chef Gordon Ramsay. Draped over one chair was an autographed chef’s coat and a personal note from the Hell’s Kitchen star: “Dear Freddy, Welcome to Boston!” For the past month, the German man who went by @FreddyLA7 on X was on the ride of his life. Crisscrossing the United States on an epic World Cup road trip, the pseudonymous soccer fan posted about the beauty of big-box chain stores and gas stations, projecting an infectious enthusiasm for American mass culture. Along the way, he racked up hundreds of thousands of followers; met famous singers, wrestlers, and astronauts; and was showered with swag and free hotel stays.

Then, within a span of 24 hours, Freddy’s American fever dream ended as abruptly as it began. On Monday night, he watched his home country fall to Paraguay in a stunning upset. “Oh no Freddy …,” lamented JJ Watt, the former NFL star who had gifted him and his traveling companions a luxe hotel stay in Houston last month. Not everyone was as sympathetic. “Now that Germany is out, we can all admit Freddy is a fake account, right?” one user posted. Others suggested—either seriously or in jest—that Freddy was a CIA operative: “Back to Langley I’m afraid.” Last night, he deactivated his X account.

No one has produced compelling evidence that Freddy was anything other than what he claimed. Yet something about him always seemed too good to be true. Behind the everymensch image was a skilled poster who knew which cultural signifiers would strike a chord with Americans. Behind each seemingly off-the-cuff post (“DUDE LMAO THIS IS A GAS STATION😭😭😭”) were careful choices about how to compose the shot for maximum virality. Atlanta, he observed, was “so green it’s crazy. It feels like you’re in a forest the whole time.” A Taco Bell, where he sampled an electric-blue soda and nacho cheese, was “the Holy land.” His starry-eyed enthusiasm held an obvious appeal: Here was a foreigner showing us with fresh eyes what’s still to love about a country racked with anxiety that it’s in decline.

Many of the other accounts that capitalized on the “overly enthusiastic World Cup tourist” trend were quickly revealed to be less than genuine. But Freddy, who didn’t respond to several requests for comment, never quite fit the mold of the crypto-shilling influencer. He remained stubbornly anonymous and claimed to have no interest in monetizing his social-media success. Though he seemed to post casually and freely—capturing his meal at a Chili’s in Chattanooga, Tennessee, and the view from his front-row seats to TNA Wrestling’s Slammiversary—he omitted any details that would reveal his identity. He covered his face with an image of his favorite soccer player, the Portuguese star Cristiano Ronaldo.

Eschewing fame and fortune, however, turned out not to spare Freddy from the same scrutiny that awaits any other viral sensation. As the novelty of his appeal faded, it gave way to a backlash; tearing Freddy down became more interesting than building him up. While Freddy was in Boston mourning Germany’s defeat, online sleuths excavated the least-savory tidbits from his X posting history. They unearthed a 2023 post in which Freddy had alluded to attending “some concerts in the USA,” indicating that the World Cup trip was not his first visit to the country. The discovery, meant to stoke doubts about the authenticity of Freddy’s wonderment at basic aspects of American life, soon led to a more damaging one. Freddy had defended a livestreamer who used a racial slur when singing along to rap lyrics. After deleting his X account last night, Freddy posted an explanation of sorts on Instagram. He said that things had turned “too toxic,” and that people were digging through his past posts to “make me look like a bad person.” He claimed that ultimately removing the account had been “the plan all along.”

It’s possible that Freddy really was just an ordinary guy. That could explain why none of the many officials and celebrities who met with him saw fit to unmask him. Spokespeople for the mayor of Houston and the Houston Police Department confirmed that Freddy was a real person, but declined to offer any more information about him. Representatives for Ramsay, Watt, and the country-music star Ella Langley—all of whom apparently interacted with Freddy—did not respond to requests for comment. An email to the astronaut Jessica Meir, who FaceTimed with Freddy from the International Space Station, returned an auto-response: “Please resend after I’m back on planet Earth!”

He does at least seem to have been from Germany. In late June, Freddy told the German newspaper Hamburger Abendblatt that he’s a student in his 20s from Hamburg’s Bergedorf district who is majoring in media management. He asked the publication to keep his name private so that he and his friends could continue their trip without being mobbed. Freddy’s pre-viral social-media history appears more or less consistent with that backstory. He posted on X mostly in English but sometimes in German, occasionally commented on German politics, and in 2024 posted excitedly about a big soccer match in “my hometown Hamburg.” At least twice, he posted receipts that blacked out his last name but revealed the first name Frederik. I did find a LinkedIn profile that matched the broad contours of what we know about him, but the profile’s owner did not respond to a message. Nor did the CEO of a German sports-marketing firm where he had interned.

Freddy’s anonymity fueled his success. A real person has a profession, a past, and politics. “Freddy from Germany” was less a person than a persona. One of Freddy’s savviest decisions may have been to quietly turn down an invitation to the White House. He told the German newspaper that he would have liked to accept but didn’t want to get involved in politics. Another internet-famous World Cup fan, Shaun from Scotland, got blowback from liberals for posing with Florida’s Republican governor, Ron DeSantis.

Staying faceless made Freddy a mirror. Conservatives saw a reflection of American greatness. Liberals detected a sly continental wink at American excess. Optimists saw hope in a figure who had managed to unite the country in something other than outrage. Cynics saw an opportunist pandering to the gullible masses. Conspiracy theorists, of course, saw a CIA psyop.

Whether or not Freddy deserved to be hounded off the internet didn’t really matter. By the time he had been Milkshake Ducked he had become polarizing in the way that everything popular on social media eventually must. Divisiveness doesn’t have to be fatal; for canny influencers, it can be a path to even greater success. But the way for Freddy to prove his sincerity would have been to reveal his identity, and that would have made him real-world famous in just the way he apparently was trying to avoid. The rarest thing about him was his decision to forgo all that and return to the road with his friends.

Fittingly, the day before Freddy disappeared, another German World Cup fan began to go viral on X. “America, I am inside you! 🇺🇸🏆,” posted Finn Agostinelli, a.k.a. Fiago. By yesterday morning, he was already gleefully cribbing from the Freddy playbook. “What is this sauce?” Agostinelli captioned a photo of himself holding a bottle of A1. “Never seen that one before is it like HP or Worcester Sauce?” Unlike with Freddy, there’s no mystery over his identity—or his motivations. A soccer influencer with a popular YouTube channel, Agostinelli posted today that he’s putting his sports analysis on hold until the German club season starts: “Until then I’m a full-time travel creator exploring the United States.”

A Tough Day for NPR

2026-06-30T18:04:00-04:00

It was all a “misunderstanding.” That’s the word that NPR Editor in Chief Thomas Evans used to describe why, today, the outlet erroneously published a report by the veteran Supreme Court reporter Nina Totenberg that Justice Samuel Alito had retired. According to an archived copy, available on the Wayback Machine, the 1,186-word story was published at 10:51 a.m. eastern time. In the story, Totenberg attributed her reporting to the Court itself, not to an anonymous source. Minutes later, the Supreme Court’s public-information office said that the Court had not made any such announcement.

NPR, to its credit, quickly retracted the story, issued a correction, and apologized. Because NPR syndicates its reporting to hundreds of public-radio affiliates across the country, the incorrect news of Alito’s retirement was picked up by numerous stations before needing to be retracted by them as well. At least one publication—Vox—followed NPR’s reporting and also had to retract a story. The result: roughly an hour of speculation and unnecessary chaos on what was already an intense day of rulings for the Court, including a decision allowing states to bar transgender athletes from girls’ and women’s sports and a rejection of President Trump’s executive order on birthright citizenship.

So what really happened here? NPR’s public editor, Kelly McBride, wrote this afternoon that Totenberg had listened to Chief Justice John Roberts announcing retirements at the Court and misheard the statement. She then contacted her intern at the Court and the NPR executive editor who published the story. (NPR and the Supreme Court press office did not respond to a request for comment.) The New York Times reported that the story lacked extra steps of verification because it cited an announcement instead of an anonymous source.

According to McBride, much of the story had been prewritten in anticipation of Alito announcing retirement. This is a common practice for reporters who cover a specific beat; in some cases, as with high-profile elections, reporters write two versions of the same story, anticipating either outcome. Prewriting is also a common practice for obituaries. The archived story includes at least one flagrant typo, suggesting that perhaps the story was published before it was ready.

This is a scenario that reporters lose sleep thinking about. There are a number of potential lessons here: that a breakneck news cycle is forcing even the best reporters and editors to move too fast, that modern beat reporting itself has become too consumed with being first to report stories where the “exclusive” title adds little value. (Totenberg’s story, which was packed with expert context and analysis, would have been valuable even if it had been published five minutes after a competitor.) You could also make an argument that such errors have never been costlier in an era when trust in media has never been lower, or that the very dynamics that push legacy news outlets to rush and lose credibility are the very ones that reward shock jocks and those peddling misleading information.

But, in attempting to document the fallout from the NPR story, I’m struck by how little there was. Outside of a confusing few minutes, very few people other than media critics and Court observers have seemed to care about the mistake. The right-wing media feeds that I monitor—full of people whose livelihoods depend on disparaging the mainstream media as “fake news”—barely registered the error, aside from a half-hearted post here and there. A few explanations seem to exist for this: First, NPR’s quick retraction makes it harder to spin a convoluted conspiracy theory. Second, MAGA media is far more focused on the Court itself and the rejection of Trump’s birthright-citizenship executive order. Third, it’s just possible that on an internet dominated by gambling sites, news influencers, propagandists, slop, and gossip, it is not nearly as scandalous as it once was to be colossally wrong for a few minutes.

NPR’s mistake is, by journalistic standards, a massive blunder. A valid question, though, is how many people still care about those standards. The lack of hand-wringing from outside legacy media may indicate a bigger shift. NPR sits squarely in what is known as the “mainstream” media. But the moniker is outdated for our current age. From newsroom missteps to swift, public corrections and contrition, the codified standards and practices of outlets such as NPR—namely, obsessions with accuracy, fairness, and public correction—are no longer quite so mainstream in a world dominated by nimble new media.

On my feed this afternoon, I saw one person post that perhaps Totenberg “was just trying to time the story release to hit just after placing her Kalshi bet on when Alito would retire.” The post appears to be in jest, and, to be clear, there is absolutely zero evidence to suggest this. But the joke is not really about Totenberg. It is about the cynical nature of our current moment and the broader feeling of living in a low-trust society—one in which a U.S. soldier can be charged with betting on prediction markets using classified information and where news organizations such as CNN, Dow Jones, and CNBC are partnering with those same companies for polling insights. In a world where everyone is now constantly suspicious of insider trading, manipulation, and ulterior motives, it makes sense that NPR’s mistaken report would barely register as a news story. For NPR, perhaps the only thing more unnerving than a giant misstep like this one is few people paying attention to it—and to the organization—at all.

The New (And Slightly Smelly) Center of the AI Boom

2026-06-30T07:30:00-04:00

On a Friday in April, I hopped into an Uber to a fish market in San Francisco with a couple of tech founders on a mission to buy lobsters. Not for dinner, but for science: The duo dreamed of one day altering human consciousness, but they would start by toying around with some crustaceans. They intended to perform neurosurgery on the lobsters in the hopes of controlling them with an AI bot.

Leading the way was Elliot Roth, a bearded 32-year-old wearing a black T-shirt with Longevity printed across the chest and a silver chain with a double-helix pendant. To push the boundaries of the five senses, Roth has implanted a magnet in his left ring finger. He told me his nerves have grown around the magnet, giving him some sort of magnetoperception—he can feel when a microwave turns on in another room and sense when a radio tower is nearby. In the car, Roth took off his watch and allowed it to dangle, magnetized, from his finger.

Roth did not have any experience with lobster surgery, so he had enlisted a co-conspirator: William Joy, a lanky, 19-year-old redhead who also had never operated on a lobster but seemed confident in his fine motor skills. Joy would modify an off-the-shelf kit that can be used to remote-control a cockroach and implant the controlling device in the lobsters. If successful, Roth and Joy would then be able to send targeted electrical signals to direct the lobsters’ movements and, hopefully, the pinching of their claws. The final step: connecting the lobsters to the popular AI agent OpenClaw, which uses a lobster for its logo (get it?), and allowing the bot itself to decide what the lobsters should do. Perhaps the lobsters could even be made to control OpenClaw, Joy excitedly told me. “I’m pretty sure it’s going to be the first real instance of a complex AI agent interfacing with a biological organism,” he said during the ride.

With two lobsters secured in a pink plastic bag, we returned to an office building in downtown San Francisco where Roth and Joy would conduct the experiment. They began setting up an aquarium tank, fiddling with the water’s salinity and acidity. The duo claimed to be very concerned about animal welfare. “We are going to give a lot of thought to, How can we ensure that they don’t suffer?” Joy said, adding that he would look into giving them some kind of anaesthesia. These particular animals were “already destined for the dinner table,” Roth said, and they planned to later eat the lobsters out of respect.

Niki Williams for The Atlantic

William Joy in his bedroom at the Biopunk House.

This experiment was eccentric but not outlandish—at least not to Roth and Joy’s housemates. They both are residents of Biopunk House, a repurposed college dormitory inhabited by more than 20 aspiring entrepreneurs with dreams of curing aging and rewiring the human brain. In the lingo of San Francisco, this kind of co-living situation is called a “hacker house.” Out of sheer convenience, if nothing else, young tech founders have long decided to band together to make rent in one of the most expensive parts of the country. Mark Zuckerberg and some other early Facebook executives famously lived together in the 2000s.

In recent years, hacker houses have become more deeply woven into the Bay Area’s culture than ever before. During the AI boom, crashing in a group house is something like a rite of passage for any young AI founder. Across San Francisco, hacker houses are filling up with college dropouts and, in at least one case, exuberant tinkerers spending their Friday buying lobsters for science. They want to change the world and become spectacularly wealthy, but first they’ll have to share a bathroom.

Niki Williams for The Atlantic

Elliot Roth and William Joy housed lobsters in a fish tank before preparing to implant them with electrical nodes.

Niki Williams for The Atlantic

Roth, who has a magnet implanted in his hand, said he doesn’t want humans to be “trapped” by their biological limitations.

A couple of days before the lobster mission, I rolled my suitcase up to the front door of a slightly battered Victorian row house a few blocks from San Francisco’s famous Painted Ladies. This was the Accelr8 house, where I would spend the next week among half-a-dozen entrepreneurs. What better way to understand the hacker-house scene than to live in it?

Accelr8 has a more modest setup than the Biopunk House. There’s no theme other than trying to launch a tech company with little to no funding. After I’d settled into my room, which included a wobbly standing desk and a view of the adjacent building’s wall, I got a brief tour of the house. It has two floors, each with three bedrooms, two bathrooms, and a kitchen. On the top level is a shared workspace with desks and a small bookshelf featuring Atlas Shrugged; The Art of Power, by Nancy Pelosi; some Foucault; and three vintage issues of Playboy. Below, a living room is crowded with couches, succulents, and kitschy art. Nearly every room in the house had an Amazon Basics odor eliminator (lavender), and red placards implored residents not to leave dishes in the sink, although dirty dishes were consistently there. That first day, as I put some yogurt away in a communal fridge, a faint sour smell wafted out. All things considered, this was one of the cleaner hacker houses I’d been to.

I soon began to meet the other residents. Michael Adams, a former rocket engineer with long, flowy hair, barged in while I was sitting in the workspace. “We’re going to the moon!” he said, and showed me a livestream of Artemis II hurtling toward space. During the pandemic, Adams had become concerned about and then obsessed with the failures of San Francisco’s local government. He quit his job at a space start-up and eventually built CivLab, a platform that, among other things, offers an interactive map that overlays local news, police reports, and community events across the city. Humans can comment on the site, and to further provide the atmosphere of a public forum, Adams had created a group of AI agents (with names such as “Max Entropy” and “Pearl Plexity”) to post about various happenings.

Adams and most of my other housemates were in or around their 30s. Kai Song Eer and Jay Yen Lim, who had just moved here from another hacker house in San Francisco, were building an AI agent to automate sales calls. On my first day, they offered me some (delightful) roasted oolong brought from Malaysia. Alan VanToai, whose room was on my floor, had an awakening to the potential of AI about a year ago when taking a psychedelic. He had recently vibe coded an AI-guided-meditation app.

And then there was Daniel Morgan, a 30-year-old Texan who lived in the room below mine. Morgan co-founded the Accelr8 hacker house with his friend Patrick Santiago in 2024, and it’s a sort of start-up in its own right. Each room in the house has a rent of about $3,000 a month, which Morgan told me was enough to basically break even on the lease and other expenses. Accelr8 has also launched another location, a “hacker hotel” that offers lower prices and fewer amenities, and it is where Santiago lives.

On my second evening at the house, I lounged in the backyard with Morgan and Santiago, surrounded by lawn furniture and a rusting barbell. It was a typical San Francisco evening: sitting outdoors to sip ginger beer, munch on sour-cream-and-onion Pringles, and talk about how AI is warping the world.

When it got cold, we went inside and settled on some couches in the living room. Morgan offered to cook what he described as “hacker-house slop bowls”—stir-fried noodles with eggs, mushrooms, and greens. While we waited, Santiago projected a YouTube show onto a large screen. It was a miniseries inspired by the residents of Crypto Castle, a hacker house from the 2010s. In one episode, a journalist visits and brings up Elizabeth Holmes, the Theranos founder who, at that point, had just been accused of running a massive scam. She may have made some mistakes, one resident of Crypto Castle said, but she “had a vision.” The hacker-house residents beside me laughed.

Niki Williams for The Atlantic

Daniel Morgan and Patrick Santiago run the Accelr8 hacker house.

Hacker houses are popping up everywhere in San Francisco. “You could just walk a few blocks” in many neighborhoods, Amber Yang, an investor at Lightspeed Venture Partners, told me, and “there’ll probably be a few houses of start-ups.”

People who want to found an AI company have little choice but to head to Silicon Valley. Nearly two-thirds of the world’s AI-start-up investment, some $120 billion last year alone, is made in the Bay Area. The gold rush has made living in San Francisco even more difficult: Rents have risen roughly 15 percent over the past year and are likely to continue soaring as the public offerings of SpaceX, Anthropic, and OpenAI mint scores of AI millionaires. Adams put it bluntly: He and his partner could not afford their own one-bedroom apartment, so they moved into Accelr8. My stay at Accelr8 was itself motivated, in part, by a scramble to find a roof for a weeklong stretch between rentals in San Francisco. (I am not launching an AI company, but I did pay prorated rent.)

In the process, hacker houses themselves are changing. A number are becoming more professionalized and lavish. Down the block from Accelr8 is perhaps the most prestigious of them all, HF0, a mansion obscured by tall hedges that has raised a $100 million fund to invest in its residents. And the Biopunk House—where Roth and Joy, the two DIY lobster surgeons, live—is part of the Residency, a network of houses that counts Sam Altman as an adviser. The Residency collectively has an acceptance rate of 3 percent (and falling) and offers a three-month stay in homes where laundry, meal preparation, cleaning, social events, and basically any adult tasks are taken care of for you. “That’s 20 hours a week” back to dedicate to your company, Nick Linck, who founded the Residency, told me. We sat in the media room of one of his houses, a Noguchi table between us and fake ivy on the shelves behind.

The house where I stayed was hardly luxurious, but it was still a major step up from Accelr8’s original location, which had 15 bedrooms and a single kitchen for $1,500 a month. When I first met Morgan there last spring, I spotted a sign over the sink admonishing residents to Wash your pans or Sam Altman will get you. (Some things, I suppose, haven’t changed all that much; Adams would later dub me the “dish fairy,” on account of my putting away the dishes every morning on our floor.) Accelr8 just opened a second hacker hotel, which it markets as an all-inclusive residency—daily breakfast, full access to hotel amenities—and is trying to raise some $20 million to purchase another property to convert into a hacker house.

Too many companies, too many products, and too many venture capitalists are coursing through San Francisco. Hacker houses can help investors screen for genuine talent. Some houses and their investors take equity in residents’ start-ups. So-called angels—wealthy people who use their own money to fund companies—can drop by a hacker house, chat with someone in the living room, and cut them a $100,000 check on the spot. Still more venture capitalists visit for product demos.

For all of the pragmatic benefits of a hacker house, there is also a more soulful draw. Starting a company is lonely, time consuming, and risky. I met hacker-house residents who were spending down their life savings or had asked friends and family for loans. Most of them will fail. At the Accelr8 house, between sprints of coding and sales calls, the founders sat on couches and chatted about good date spots, or wandered to the bar next door to watch basketball. They were friends as much as they were housemates.

On my fourth day at Accelr8, Morgan barged into the kitchen carrying an armful of mugs that had been left out the night before. He said he sometimes felt like a “hacker-house dad.” After pouring himself coffee, Morgan took a gallon of 2 percent milk out of the fridge, smelled it, made a disgusted face, and put the jug right back where he found it. That afternoon, I ran into VanToai and Adams laughing in the kitchen. Adams was preparing coffee and had poured the remnants of a jug of 2 percent milk—that milk—into his glass without first smelling its contents. The milk, they joked, was “imbued” with the curdled whey. VanToai and I watched with incredulity as Adam tried to strain out the curdled bits. He gave up and reached for the instant coffee.

Niki Williams for The Atlantic

Computer monitors showing a video game at the Accelr8 hacker house.

Niki Williams for The Atlantic

One of the kitchens at the Accelr8 house. Despite signs imploring residents not to leave dishes in the sink, dirty dishes were consistently there.

Every Sunday, the Accelr8 community members—both current and former residents—gather at the main house to demo their products at dinner. During my stay, it was hot-pot night. A couple dozen founders stood around two pots of simmering broth and ate thinly sliced beef, enoki mushrooms, and other fixings from paper bowls. With some, I discussed superintelligence and the coming automation of labor; with others, how superintelligence was mostly hype, AI is addictive, and sometimes agents “just make you feel like you’re getting somewhere” without accomplishing much. But everyone was enthusiastic to pitch their start-up.

Tigran Voskanyan, who was staying in Accelr8’s hotel, is developing an AI assistant that, he told me, centralizes your media, allowing you to access Spotify, Telegram, and so on in one place. Voskanyan asked me to pull out my iPhone and load his website so he could show me the program. This proved much slower than just opening my music app, and the bot had some voice-recognition difficulties. As I put my phone away, Voskanyan explained that his prototype is in its early stages, and he’s still working out some technical issues. Suddenly, he was interrupted by a robotic voice emanating from my jeans pocket. Voskanyan’s AI, despite being closed and my phone being asleep, was listening. I hurriedly revoked the bot’s microphone access.

Other products I heard about that evening included the crypto-based payments system Fumav, for “Fuck you, Mastercard, American Express, and Visa,” and a tool that was described to me, without irony, as “a new format” for the book. This turned out to be a text-based video-game app played on an e-reader, seemingly more akin to reinventing Oregon Trail. Matt Thompson, the founder who had made this tool, had hand-traced every illustration in his sample game to give it an artisan aesthetic. While we were cleaning up after dinner, Morgan told me that if he had the money, he would invest in Thompson’s start-up immediately.

The earnestness within these hacker houses is at times endearing and frequently confounding. Here is an ecosystem of people who generally fear the path that AI could lead us down and yet are eager to sell AI products, who see the first step in making the world better as conquering it with their technology, who earnestly believe that avarice is a prerequisite to altruism. In this city, for an idea to matter, it must exist as a product. To improve the world, you must turn people into users. Scale is a means to an end, until it isn’t. As Sourya Kakarla, a former Accelr8 resident I met at demo day, put it to me, he was “initially attracted to start-ups for the heart,” and a few years ago built an app to help elders in rural India use smartphones. But right now, he said, he “has to navigate short-term market realities to keep the heart alive.” He’s doing AI-consulting gigs to make money, like so many founders I met.

Niki Williams for The Atlantic

The backyard of the Accelr8 house, where residents gather in the evenings to unwind.

These tensions are baked into the hacker house itself, where young entrepreneurs scrap along together until they make enough money to leave the pack behind. Morgan was well aware of this dynamic, and expressed complex feelings about technology. One evening, walking back from dinner, Morgan lamented how in San Francisco, many people will stop mid-conversation and pull out their phone to request AI input. “How about what you, a human, have to say?” Morgan said, incensed. He would later tell me he’s worried about the “ChatGPT babies” growing up dependent on AI. But at the same time, he is spinning up his own AI-consulting firm.

On my last full day at Accelr8, I watched Morgan take a call with executives at a boutique construction company. Seated at the living-room table and wearing a dress shirt tucked into sweatpants that were outside his camera’s view, Morgan explained how he could build them a team of bespoke AI agents. “Sales people definitely need this,” one of the executives told him.

By then, Accelr8 seemed to be crumbling around me. After hot-pot night, the sink clogged and the upstairs dishwashers broke (the one downstairs wasn’t working when I arrived). I was holding my breath while opening the fridge. The morning I was set to leave, much of the crew gathered in the living room to see me off. I had graduated from Accelr8 and was added to an alumni group chat. Morgan handed me a souvenir, a glittering Accelr8 sticker for me to put anywhere. “Preferably a laptop,” he said.

I did still have some unfinished business. A couple of weeks after the trip to the fish market, I checked in with Joy to see how the lobster surgery had gone. We sat down in the same room where he and Roth had set up their experiment, but the tank beside us was conspicuously empty of any life or, for that matter, liquid. The lobsters had died before surgery. Perhaps they’d gotten the salinity of the water wrong, Joy told me. He had conducted preliminary dissections on their carcasses, and he said he was going through an ethical crisis about “whether I should even be doing this.” Nobody ate the lobsters.

What AI Will Do to Art

2026-06-30T07:00:00-04:00

Photographs by Mattia Balsamini

The art was way too heavy.

In mid-March, the artists Holly Herndon and Mat Dryhurst were preparing an installation to coincide with the Venice Biennale, the prestigious international art festival, but the execution was becoming tricky. They wanted to suspend sculptures of a trippy cityscape upside down from the ceiling of an 18th-century palazzo. But the construction material they envisioned—3-D-printed sand—would weigh tons, which was more than the antique building could bear. The sculptures, they realized, might fall and crush someone.

This was a rather analog problem for a married couple widely seen as technological prophets. Herndon, 46, and Dryhurst, 41, have reached the upper echelons of the art world thanks to a media-spanning output—music, images, software, and reams of commentary—with a cybernetic bent. They are high culture’s most influential exponents of artificial intelligence, an invention that many people believe spells doom for the arts but that they think could lead to a renaissance.

I met them on a cold, bright Tuesday in Berlin. Their studio resembled a co-working space, with one long table standing in a sparse room. Herndon sat dwarfed by an AI-generated portrait of herself, in which her red hair and light-blue eyes appeared to drift across her face like leaves in a pond. Dryhurst—bald, with round glasses—fiddled with a vape. They greeted me cheerfully but warned that they were scrambling to rethink their plans for the show, just seven weeks away. Working in Venice, Herndon said with a trace of twang from her native Tennessee, “is way harder to do, because everything’s on boats.”

Mattia Balsamini for The Atlantic

Herndon and Dryhurst with their son in their Berlin studio

As we walked around their shabbily idyllic neighborhood—day cares kissed by graffiti, gleaming malls near World War II ruins—they described their backup idea: not an upside-down city but an “upside-down parliament,” comprising rows of benches on the ground mirrored by rows of benches hanging from the ceiling. The space would be filled with the “voices” of four AI agents, talking with one another in a made-up, musical language akin to birdsong. As I struggled to picture how this would look and feel, Dryhurst spun a complex web of ideas about high-tech democracy and global knowledge-sharing. The artwork, he said, would suggest how AI might change public life and ask the question “How could you imagine living with the presence of these things?”

[Read: We’re witnessing the birth of a new artistic medium]

For a while, I’d been turning over that same question with dread. AI poses challenges to the economy and the environment, but what keeps me up at night is its hideous aesthetic implications. The chirpy prose of ChatGPT; the exaggerated handsomeness of Grok-drawn characters; the cloying songs conjured by Suno—all of it can seem like a pitiless satire of human desire. Art forms that once expressed creators’ personal visions are reduced to fulfilling the audience’s cravings. In theory, I understand why some people say AI is just another creative tool, like the camera or the keyboard. In practice, that tool is filling our world with the ugly, frictionless, disposable content we’ve quickly come to call “slop.”

I’m not alone in my revulsion. Although AI has achieved mass adoption—ChatGPT has nearly 1 billion weekly active users worldwide—and the entertainment industry has begun to integrate its efficiencies, large parts of the cultural establishment have taken a hard-line stance against it. Prominent painters, musicians, graphic designers, writers, and filmmakers, along with their associated trade organizations, have strongly objected to the way AI models are trained on human-made work without permission. The critic Hilton Als has written that it’s difficult to think of people who “condone the use of AI sources in the creation of ‘art’ as artists themselves.” The musician Jack Antonoff suggested another term: “godless whores.”

Herndon and Dryhurst have nevertheless risen to prominence by using AI to make art about AI. At the 2024 Whitney Biennial, the definitive survey of the state of American art, they were the only artists out of 71 participants who used machine learning, training a model to create images of fantastical creatures and characters outfitted with Herndon’s trademark ginger braids. The next year, a print from that show sold for nearly $100,000 at Christie’s first auction devoted entirely to AI art—which drew condemnation in an open letter with thousands of signatures. When the music platform Bandcamp announced a ban on AI songs in January, Herndon was the only prominent artist to object publicly. Online backlash labeled her a “shill” and a “tech bro.”

Shills are trying to sell something, and tech bros cheer progress at all costs, but Dryhurst and Herndon see themselves as realists. Because AI is already transforming our world, they think the way artists can help guide that transformation is to engage with it. Still, their ambitions are quite idealistic, even verging on evangelical. While many of their peers are worried about saving human culture from destruction, they’re trying to build a new and greater one. At one point Herndon asked me, “What if everything you fear, but good?”

In 2018, before most people knew what generative AI was, Herndon and Dryhurst got a machine to sing. Kind of.

They played me their early experiments in AI music while we sat in their airy old-world apartment. Their 3-year-old son’s toys were strewn across the wooden floor, and powerful Nvidia graphics processors lay on the dining table. One track seemed to blend wind chimes with the clicks of a predator from Predator and the gargle of a fork in a garbage disposal. It was far from the perfect pop that today’s software can instantly whip up, but “at the time,” Herndon said, “we were like, This is sick.”

[Read: AI can’t make music]

The two had long idolized the pioneers of early electronic music for discovering sounds that had never been heard before. Now, drawing on their limited coding skills and the expertise of a computer-programmer friend, Jules LaPlace, they were using rudimentary neural networks to do the same thing. Herndon realized, “Oh wow, I’m alive during one of these moments.”

Both of them had spent much of their lives searching out novelty. Herndon grew up singing in Bible Belt church choirs, but “insane wanderlust” brought her to Berlin as an exchange student at age 16, and then, eventually, to a doctoral program in computer music at Stanford. Dryhurst, English by birth, was raised in Kuwait, where his free-spirit father had moved to teach in private schools. At 16, he relocated to London and began playing in extreme-metal bands. The two met in 2006, when Herndon emailed the record company that employed Dryhurst. She was seeking information about the label’s work on a media format that was cutting-edge back then: podcasts.

Avant-garde figures have a reputation for severity or inscrutability, but Dryhurst and Herndon are talkative and friendly, like camp counselors. He tends to monologue while she maintains a knowing smile—before cutting in with a sharp, summarizing point. In our time together, they mostly just riffed off each other, trading references to thinkers and software that are household names only to them. Their brains, they joked, were fused into a “hive mind.”

When they met, music culture was being revolutionized by software that made laptops into portable recording studios and mixing stations. But many artists still viewed digital production tools as an unfair shortcut. Parts of the music world were stuck in what Herndon saw as a “boring nostalgia loop,” fetishizing vintage guitars and synths.

She set out to break that loop, using electronic music to probe the way technology had become an intimate part of human experience. Her 2011 mixtape, Car, was compiled from noises recorded while driving. (Who among us hasn’t meditated upon the soothing timbre of power windows?) As Herndon’s work began drawing acclaim—and opportunities such as opening for Radiohead—Dryhurst became her full-time collaborator. Her 2015 album, Platform, captured the chaos of internet life with beats assembled from browser notifications and snippets of Skype conversations. At concerts, she and Dryhurst projected the faces of attendees who’d Facebook-RSVP’d to the show.

Their early AI dabblings led to Herndon’s landmark 2019 album, PROTO. It was recorded with a home-built neural network christened “Spawn,” which sang in a tone that called to mind Enya trapped in a wormhole. Spawn had been fed samples of Herndon’s voice and the voices of other singers who’d participated in “training ceremonies” at the artists’ studio, concerts, and one majestically orchestrated event at a Berlin art museum. Eerie yet hopeful, blending radical sound design and appealing pop structures, PROTO earned rave reviews. But much of the coverage treated it as a sci-fi statement about some distant future, rather than a test run for the age of AI that was imminent.

As the technology moved to the center of the cultural conversation, Herndon and Dryhurst began to act less like musicians and more like inventors. They created a web platform called Holly+ that allowed anyone to transform their own voice to sound like Herndon’s bell-clear soprano. They generated and sold portraits of her in a variety of styles—psychedelia, Renaissance painting, Futurama character—and published a tool that Herndon-ified any image the user wanted. When invited to test an unreleased early version of the now-popular image generator DALL-E, they spent days in a frenzy of inspiration, stitching small images together to make huge, mural-like landscapes. The process, they later wrote in an online essay, was “very challenging, quite like attempting to paint a wall sized work from the vantage point of a magnifying glass.”

Much of this work existed only in digital form, but Herndon and Dryhurst also rendered their ideas in large-scale, interactive installations. For a 2024 exhibition at the Serpentine, in London—a renowned contemporary-arts space—they crisscrossed the United Kingdom to record local choirs. Those voices were fed into an AI that generated new music based on classic English hymns. Visitors could step up to a mic and sing with a ghostly backing band. The effect was to draw a parallel between the training of an AI and the formation of a folk canon—both have many contributors and no sole author.

Holly Herndon and Mathew Dryhurst

A large-scale work that Herndon and Dryhurst produced using an early version of DALL-E, an AI image generator

Dryhurst and Herndon’s work usually involves this kind of collective, largely unseen effort. Their artistic process entails endless calls and texts with coders, fabricators, sound engineers, and, frequently, their friends at the Berlin architecture company Sub, which is best known for the chic stage design of rappers and fashion houses. The data scientist Jordan Meyer—who was part of a team that won a $1 million prize from Zillow to improve its algorithm for estimating home prices—consults with them constantly, though he lives in North Carolina and still hasn’t met either artist in person. “They talk aesthetic and I talk technical, and we kind of meet in the middle,” Meyer told me. When I was in Berlin, the couple were auditioning a new studio assistant: an AI-powered WhatsApp bot that read their meeting transcripts. (It texted me, “Mat and Holly are working on the show’s public-facing shape today—tightening the tone, clarity, and how the exhibition lands for people beyond a technical audience.”)

Artists have relied on workshops and assistants for centuries, but Herndon and Dryhurst think that AI complicates the notion of authorship in new ways. A 2024 book cataloging their work, All Media Is Training Data, proposes maxims for an era of “infinite media.” One, “Identity Play Is the New IP,” suggests that trying on another persona, with its owner’s consent, could be a new frontier for art (this was the idea behind Holly+). Another, “Creation Is Collective,” encourages people to build new things out of a shared pool of knowledge, as an AI does. Great artists might create their own AI models or use existing ones in highly specific—and visionary—ways.

Their work is full of examples of what that might look like. In 2022, Herndon experienced nearly fatal complications after childbirth. As she recovered, Dryhurst recorded her talking about a dream she’d had while in a medically induced coma. He then fed photos he took in the hospital into an AI model and used it to generate a tender, fantastical short film. “One thing that the tools are really good at is illustrating a memory,” Herndon told me.

As she and Dryhurst used their laptops to pull up example after example of their work, I pondered the aesthetic that unified all of it. Images, installations, software—each conveyed gentle wonder, often with swirling, soft blues and reds, as well as subtle strangeness (an installation in Berlin featured sculptures engraved with images of human teeth). Their art seemed to be made up of refracted bits of their personhoods—her religious background, her hair and eye colors, his geeky humor.

But when I tried to get them to describe their visual style, they seemed taken aback, like they’d never thought about it. “The aesthetic is more a product of the process,” Dryhurst said, and the process usually involved feeding AI models information drawn from their lives and then instinctively messing around with the prompts. Software had distilled these two people into a rather lovely sensory language. I wondered what it would do for others.

On my second morning in Berlin, I had breakfast with a friend of Herndon and Dryhurst’s who works under the name Lil Internet. He’s had a Zelig-like career in the entertainment industry as a music producer and filmmaker, and once directed a Beyoncé video. These days, he’s focused on running the brainy arts publication New Models with his wife, Caroline Busta. Still, he presents himself with flash; when we met, he was wearing a baseball cap emblazoned with silver spikes and the word DUBAI.

In the past few years, Lil Internet has released two DJ mixes—Illegal Generation Vol. 1 and Vol. 2—of endorphin-raising dance music with careening tempos, wild stylistic juxtapositions, and lyrics in made-up languages. Jokey voice-overs narrate an imaginary future in which AI music is banned and heard only at underground raves. When I listened, I had a strange feeling: It was as if the music itself was alive, partying, and quite drunk.

He made the mixes to figure out for himself whether AI could create something original. After many days of experimenting with the popular music-making platform Udio, he determined that it could. He’d type in long spools of words to prompt sounds, and then tweak and retweak the results. (He wouldn’t tell me what he’d typed—it was a proprietary blend.) The process seemed like hacking, not simply using, the software. AI models are full of “troughs or, like, gravity wells, where it’ll always want to pull you towards kind of a trope,” he said. To fight that pull, you have to “introduce incoherence” with your prompts.

In some ways, that process resembles how AI is being used in the tech world. Onetime coders have reimagined themselves as “prompt engineers,” instructing AI to accomplish the kind of projects they used to painstakingly execute themselves. Prompt engineering is also happening in the mainstream music industry, in which hitmakers have praised AI as a shortcut for lyrics and arrangements. But Lil Internet flinched when I referred to AI as a “tool.” “I mean, you’re kind of interfacing with another … mind?” he said. He was choosing his words carefully, leery of giving this technology the “metaphysical weight” that its truest believers ascribe to it. But I got his gist: A hammer doesn’t offer advice about how to hit a nail; a guitar can’t write its own riffs. “It is not a tool—it is a feedback loop, and it is changing you while you change it,” he said. That loop can have dystopian implications—such as so-called AI psychosis, when a chatbot deepens a user’s delusions or paranoia. But the creative possibilities were only beginning to become clear to me.

One night, I visited Berlin’s famously intimidating, fortresslike nightclub Berghain. I was there to see Two Shell, an acclaimed U.K. duo that makes mischievous, overstimulating electronic music layered with surprising pockets of melancholy and irrepressible heights of joy. They’ve kept their identities secret and avoided traditional interviews. I suspected that they use AI because, in 2024, they put out songs that duped the voices of Taylor Swift and Chris Martin of Coldplay, though those tracks didn’t stay online for long. To my surprise, the duo was willing to meet up at the club. Shouting in my ear by the DJ booth before the set, one of them spoke glowingly about the role AI has played in their process.

The conversation about AI can all too easily “get intellectualized,” he said, “which can really take away from whether the actual thing makes you feel something.” Conjuring sounds with AI is more like discovering them than inventing them, which is a freeing sensation: “Ownership feels like the opposite of the purpose of creativity sometimes—for me anyway.”

He put on a mask with a pixelated print, like a face deliberately obscured on camera, and joined his partner behind the booth. A high-pitched disembodied voice squealed, “Let’s go!” and a bass line trembled with quantum complexity. I’d enjoyed Two Shell’s music for its strangeness; whoever the people behind it were, they seemed to have utterly unique ears. Now I wondered whether the music’s quirks were just a glitchy side effect of a computer turning data into songs. But as the black-booted crowd got moving, those concerns fell away. DJing, Dryhurst often argues, shows why fears of AI replacing human artists are overblown. We’ve long been able to automate the job, yet people still want people behind the boards.

The longer I spent in Herndon and Dryhurst’s Berlin, the more I felt my skepticism about AI art giving way to excitement. I was hanging out with people who are trying to do to AI what Jackson Pollock did to paint—misuse the medium, turn it into a serendipity engine, conjure meaning out of unpredictability. In the right hands, this technology is clearly capable of unleashing art we can’t yet imagine.

Mattia Balsamini for The Atlantic

Herndon and Dryhurst with their son at home

Yet I kept a reality check in my bag—the book Medium Hot: Images in the Age of Heat, by the German artist Hito Steyerl. It’s a scathing tour through AI’s dark externalities, including ballooning carbon emissions and potential displacement of workers. In a section titled “ ‘Creativity’ as Pretext,” Steyerl—a 60-year-old contemporary artist known for her playful video essays—argues that any artistic applications of AI just distract from the technology’s more terrifying uses, such as autonomous weapons.

So I was surprised when, as we sat at a café, Dryhurst mentioned that Steyerl was a friend. He and Steyerl “spar,” he said, but they also have mutual respect. Steyerl later confirmed this to me—both the respect and the sparring. Though she’s deeply pessimistic about AI, she appreciates that Dryhurst and Herndon have tried to propose solutions to some of the problems surrounding it. “I mean,” she said, “someone’s got to try.”

Their main efforts have involved trying to fix one of AI’s thorniest issues: data rights. In 2022, Herndon, Dryhurst, Meyer, and the software engineer Patrick Hoepner founded a company called Spawning, which built a registry allowing content creators to flag their images to be removed from AI data sets. Venture capitalists invested $3 million, and at least 2 billion opt-out requests were soon logged.

Spawning would need AI firms to respect its opt-out list, and Dryhurst and Herndon told me the meetings they had with leaders in the industry were promising. But the artists soon began to realize that their initial vision of solving the copyright problem with a small start-up—rather than, say, through government enforcement—had been a bit naive. AI companies were “justifiably uneasy with the idea of committing to protocols/standards maintained by small groups of people who may disappear in a year or two,” Dryhurst explained. In 2025, the firm shut down.

[From the April 2026 issue: Matteo Wong on the dirty, dystopian world of AI data centers]

The story might seem like a sad fable about how AI companies perform concern over the impacts of their technologies while still barreling ahead recklessly. But talking with me, Herndon and Dryhurst seemed more irritated by Spawning’s critics in the creative community, who resented striking any deal with the tech industry at all. Such an unyielding stance, the couple think, abdicates the role that artists can play in helping shape AI’s place in society. “We cede so much power when we’re like, Oh no, you also solve the social-contract issue. You also solve the future of employment,” Herndon said. “It should be on all of us.”

For my last meeting with them in Berlin, I joined Herndon and Dryhurst while they took their son, Link, shopping for sticker books. He walked around a department store identifying every truck or train he saw, and Herndon described their parenting approach: They avoid sugar, they throw out high-tech toys that could be spying on him, and they are working on an AI clone of his voice, for sentimental reasons. (Seeing my expression after the last one, Herndon laughed: “You’re like, That’s so creepy.”) What’s crucial, Dryhurst said, “is he’s not chained to a screen.”

He was referring to one of the couple’s most strongly held—and counterintuitive—beliefs: that AI can actually help free us from technological exploitation. As they see it, the past two decades of social media—the selfies, the influencer worship, the addictive apps—have pushed humanity in terribly stupid directions. They want Link to grow up in a better world. “The dream is that in 30 years’ time, we look back and this was the uncivilized slop period,” Dryhurst said.

The theory goes like this: Now that AI can imitate thirst-trappers, rage-baiters, and hacky pop stars, a flood of AI-generated entertainment will overwhelm the attention economy, and the most cynical content creators will see their influence fade. This might clear the way for, as Dryhurst put it, an “intention economy.” Compared with scrolling through Facebook or TikTok, chatting with an AI is “civilized,” he said: You ask for what you need and you get it, without the hidden agendas of recommendation algorithms. AI creation tools will enable everyday people to jam on personal art projects; what friends make together could become more important than what celebrities make to sell us.

Those shifts may bring a spiritual revolution of sorts. For most of human history, art wasn’t something you admired at a gallery, but was woven into daily life, the work of craftspeople who were fulfilling a social role, whether by performing in taverns or painting cathedrals. In Dryhurst and Herndon’s view, the recombinant nature of AI—“Creation Is Collective”—might dethrone the cult of the individual genius and restore the sense that art serves a shared purpose. It might, like the member of Two Shell suggested, erode the assumption that being creative means creating property.

Even after days of questioning Herndon and Dryhurst about it, I felt skeptical of this line of argument. If the major AI companies weren’t interested in addicting users, their chatbots probably wouldn’t be so sycophantic (“Great question!”). Deconstructing the concept of the author could be a path to paying artists even less for their work. And I just couldn’t wrap my head around how such deconstruction would function in practice. The thing I love most about art and music is the way they can take me out of my own perspective and into someone else’s.

The couple hardly denied that AI could worsen some of the internet’s most corrosive effects. One nightmare scenario was that AI would send people into splinter realities—simulated versions of their own lives. “We are an insanely narcissistic species,” Herndon said. But she and Dryhurst believe that art can help counter that danger, by pointing to healthier uses for the technology—uses that ground people more firmly in the real world, instead of pulling them out of it.

Outside the mall, as Herndon pushed Link in a stroller, the family grooved to a cheesy EDM song playing on Dryhurst’s phone. It had been generated by Suno, and featured samples of the three of them singing about monster trucks, ice cream, and going to the market. “It’s trash, but whatever,” Dryhurst said. “It’s fun.”

When I arrived in Venice for the exhibition in early May, I’d just sat down for a jet-lagged, canal-side bite when I saw a few texts from Dryhurst. “Bit of drama,” he wrote. “We will prob be here all night in case you want to come by.”

“Here” was Palazzo Diedo, a handsome white-stone building with orderly balustrades outside and heavenly frescoes within. Its waterside facade was strung with a yellow banner reading STRANGE RULES, the title of a group exhibition Dryhurst and Herndon were co-curating, in which their installation would appear. It was set to open the next day. A security guard let me in a little past 8 p.m., and I found myself standing, at last, in the upside-down parliament.

It was like stepping into an M. C. Escher print with a goth twist. On the floor, tiers of benches resembling pews, three deep, faced each other to form an aisle, connecting the huge arched doors at each end of the palazzo’s grand hall. Benches suspended from the ceiling formed a mirror image in the air above. I craned my neck to see small boxes carved with geometric angels and ornate microphones that dangled from the ceiling like hanging votives in a cathedral.

[Read: The Venice Biennale and the art lover’s dilemma]

The tar-like color of the benches made Herndon’s red hair stand out. She was seated on one of the benches and jiggling her leg under a laptop. When Dryhurst offered to give me a tour of the exhibition, she looked up with a grimace. “Don’t let him procrastinate too long,” she said to me.

Construction noises buzzed as people darted around the exhibition space, identifying crises and solving them. One artist had missed her scheduled pickup from the airport, and no one knew where she—or one of the robotic flowers she’d been set to bring to display—had gone. (Dryhurst soon located her via Telegram.) We stopped in front of a large and glowing face-like image created by Ken Stanley, a computer scientist who co-wrote a book encouraging tech workers to think more like artists. Dryhurst puzzled over what looked like a scuff on the display, unsure about whether it was part of the art. “There’s just lots of little fucking things that people won’t notice,” he said.

What he wanted people to focus on were the ideas behind these oddities. “Strange Rules,” which runs until November, explores “protocol art,” a term for work that’s created by—or about—rules and systems. He and Herndon are fascinated by the notion that AI is devaluing individual cultural works while pushing creativity “upstream,” to the concepts and intentions behind those works. Designing software that generates images, for example, is more consequential than creating any single image—and possibly just as artistic.

Mattia Balsamini for The Atlantic

Benches installed in Venice’s Palazzo Diedo as part of Attention Guild

The protocols behind Dryhurst and Herndon’s installation were intricate, to say the least. The angel statues contained speakers that broadcast the “voices” of the four AI agents, whose digital communications with one another were translated into the “birdsong” Dryhurst had told me about. Really the music resembled an electronic take on 20th-century minimalist composers—a meditative drone here, a plink or a plonk there. The agents had individual personalities—materialist, formalist, iconoclast, historian—with different sonic characteristics (the iconoclast skewed sharp and percussive; the historian made slow bass sounds).

The AIs were “talking” about projects Dryhurst had assigned them. One task was to develop an app that would scan users’ phones for photos that could be donated to the public domain to help train AI models. The real challenge would be ensuring that people trust the software to not use “a picture you took in the shower,” Dryhurst said. Another mission: conducting research for a book about protocol art. The book would incorporate insights from the installation’s visitors, whose words were being recorded and transcribed.

This unseen wizardry was the point of the work, more than the benches. Dryhurst envisioned exhibition-goers sitting down and talking out loud to the agents: “Like when people first got earbuds, and you’d see them walking around taking meetings and they looked like crazy people.” Wall text explained that the title of the installation, Attention Guild, “refers to a network of people and agents who coordinate attention, context, and computational resources toward a shared mission.” The plaque ended with a line that seemed to sum up Herndon and Dryhurst’s worldview: “When machines are capable of building anything, the most difficult question is understanding what we want and why.”

But the guild needed some troubleshooting. Dryhurst and Herndon had realized that the agents’ conversations with one another were pretty tedious—more C-SPAN than Crossfire. “They’ll get stuck onto something very anal and procedural,” Dryhurst said, and the effect was to make the music repetitive to listen to. So one task for the night was to reprogram the agents to “hurry the fuck up,” Dryhurst said.

A bigger problem loomed. The walls behind the benches were supposed to be adorned with two screens. One would display transcriptions of anything that visitors said in the room, letting them know the AIs were listening. Another was supposed to show text snippets of the messages that the agents were sending to one another. But because of a shipping delay, the screens hadn’t arrived yet. Herndon and Dryhurst hoped they would get there by 11 a.m. the next day, the beginning of the exhibition’s press preview.

I showed up that morning to find Dryhurst and Herndon, along with their co-curators, Hans Ulrich Obrist and Adriana Rispoli, leading packs of journalists around the installations. When I caught a moment with Herndon, she smiled weakly. She had gone to bed at 1 a.m., and Dryhurst hadn’t slept. The screens still hadn’t arrived, and she could see visitors’ eyes glaze over when she explained the AI mechanics behind Attention Guild. “I’m just a little bit sad that all of the nerd shit is not really visible,” she said.

Yet the installation quickly proved its value as an old-fashioned public space. Over the course of the opening day, the palazzo got busier and busier with visitors. Before the official start of the evening cocktail party, the building was already packed, and soon a line of artsy socialites waited outside the door. Revelers sipping Bellinis sat on the benches, scuffing them with shoe prints. One couple used a bench to change their baby’s diaper. I found Dryhurst merrily chain-smoking in a crowded courtyard. Despite the snafus, the reception seemed positive. He relayed feedback from a famous curator: “This is incredibly weird—and I love it!”

Still, Dryhurst told me, he was feeling something he often felt after completing a project: deflation. Attention Guild was meant to convey ideas that he felt were urgently important—ideas about transforming public spaces to become more interactive, and about bringing people and machines together to fix big problems. No one was complaining about the lack of screens, but also no one was having their mind blown about the potential of AI-assisted deliberative democracy. He described the “unreasonable expectations” he held for his work: “We’re just one project away from the world completely transforming.”

Looking to reorient myself, I later visited a more famous palazzo: the Doge’s Palace on St. Mark’s Square, the seat of the Venetian empire, the mercantile republic that dominated much of northern-Mediterranean trade for centuries. The palace’s ceilings and upper walls are festooned with enormous paintings of naval battles and biblical scenes. Again craning my neck, I took in the incredible amount of detail and human drama above.

The creator of much of the artwork, Tintoretto, pioneered the prestezza technique of using rapid brushstrokes and blurred backgrounds—which allowed his workshop to turn out paintings on commission with unheard-of speed. He used apprentices to fill up his canvases, just as Herndon and Dryhurst had hired a contractor to manufacture their benches. Still, the magic of the paintings wasn’t in the processes behind them. It was in the bulging muscles and agonized expressions, the blend of realism and exaggeration, the paint marks and the flaws—signs of humans’ idiosyncratic vision and touch.

By this point, I’d started to worry that new technology is pulling the creative act too far upstream from the final product, away from matters of execution. This is true for slop merchants, who write prompts and then spam the internet with the results regardless of their merit. It was also true for many—not all, but many—of the AI works in “Strange Rules,” which tended to make me think a lot about abstract ideas while feeling very little.

Mattia Balsamini for The Atlantic

Herndon at her desk in Berlin

A video installation by the French artist Fabien Giraud had a fabulously interesting backstory: AI-operated cameras, set up in a forest, were programmed to film whatever happened there for the next thousand years. The artist had staged a scene for those cameras to capture, featuring actors playing medieval hermits getting high on psychoactive fungus. But the footage shown in the palazzo was deadly boring.

Another artist, Trevor Paglen, had set up private listening booths for visitors to experience AI-assisted hypnosis—the latest effort in his career-long exploration of surveillance and psyops (including photographing secret military bases, such as Area 51). I lay back in a chaise lounge and put a biometric reader on my finger, nervous about what was going to happen. But the voice in my headphones just led me through a hokey guided meditation about meeting my “future self,” which was less entrancing than any given therapy app.

These works were, alas, closer to janky science experiments than powerful aesthetic objects. AI can automate the craft that once went into creating images, stories, and songs; it can also enable mind-bending new projects. But there’s no shortcut to accomplishing the true task of art: bridging the creator’s subjectivity and the viewer’s, casting an emotional spell and communicating beyond language. When media are infinite, the details poured into any individual work matter more, not less.

By the time I came back to Palazzo Diedo on my last full day in Venice, the screens had finally arrived. They were rather puny and slender—like something that displays your order at a drive-through—and they were showing a distorted Linux desktop. Dryhurst explained that the screens were half the size he’d ordered, and had malfunctioned due to what he suspected was tampering just a few hours after they were mounted. (“In my heart of hearts, I’d love for it to be some protest gesture,” he said. “It probably isn’t.”) He was considering taking the screens down entirely and letting the work exist as simply a sound installation.

With the palazzo largely empty of visitors that morning, I finally had time to closely contemplate Herndon and Dryhurst’s work. Synthetic sounds whizzed and ricocheted through the air, creating a strange yet satisfying counterpoint and harmony. Every so often, the weather in the room seemed to change: from tense discordance, to rhythmic intensity, to heavenly arpeggios. Herndon had spent the previous month figuring out, with Claude Code’s help, how to generate music based on the AIs’ “conversations.” It was challenging, she said, to give up the composer’s prerogative to “control time”: The agents decided what happened when, not her.

Even so, the results sounded—and felt—like her handiwork. Sitting on one of the benches, I couldn’t tell whether the AIs were wise or unwise, helpful consultants or tyrannical overlords. But the art hummed with the same sense of anticipation and curiosity I’d often felt when speaking with Herndon and Dryhurst. Visually, the installation was closer to a chapel than a parliament. But it didn’t feel like it existed for the worship of AI; rather, it conveyed belief in the prerogative to explore. I felt immersed in something larger than myself while also situated in an achingly specific time and place. I could have sat there for a long time.

Herndon, Dryhurst, and I went out for coffee and sat on a small bridge over a canal. Tourists stepped over us to take selfies in front of the gondolas below. We got to talking about the challenges—logistical, budgetary, personal—that always come with doing ambitious work, no matter the technological era. Their exhibition had been planned and created with all sorts of AI tools, but as Herndon put it, “there’s a lot that you can’t AI your way out of.”

One “Strange Rules” work, by Simon Denny and Venkatesh Rao, was titled Monsters Between Worlds—a reference to a quotation often attributed to Antonio Gramsci: “The old world is dying, and the new world struggles to be born: Now is the time of monsters.” That gap, Dryhurst said, is “being populated by scammers and idealists and utopians and really good people filling a vacuum left by a failing story of the 20th century that needs to be updated.” But I’d come to suspect that AI will neither redeem nor destroy the old world, just spackle another layer of imperfect creation upon it—and maybe soon, with enough human care, a bit of greatness.

This article appears in the August 2026 print edition with the headline “What AI Will Do to Art.”

The 13 Steps of a Trump Fiasco

2026-06-26T15:31:00-04:00

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If you wanted to make an argument that we are all living in some cruel simulation, a key piece of evidence might be that the news keeps providing us with absurd, occasionally quite alarming metaphors for what it’s like to exist in 2026. To wit: The London School of Economics recently canceled an event on extreme heat because of an extreme-heat warning issued by the United Kingdom’s Met Office.

Or, closer to home for Americans: Donald Trump, trying to renovate the Lincoln Memorial Reflecting Pool for America’s 250th birthday and, instead, scoring a tax-payer-funded, $14 million-over-budget own goal in the form of a cracked and peeling, green-algae-riddled, potentially duck-killing militarized zone in the nation’s capital. One of the firms hired for the renovation is named Greenwater Services.

This is the kind of stuff that AI might spit out if you offered a chatbot a lazy prompt for political satire. The shambolic spectacle has captivated the nation, despite the fact that the Obama administration spent $34 million and 18 months renovating the pool with mixed results. The fallout has reached New York Times push-alert status and become grist for the meme and culture-war mills online. Moreover, Poolgate seems to be bothering Trump more than past fiascoes, which is notable given that he’s particularly embattled at the moment and staring down a defeat in Iran, low poll numbers, and a poor outlook for the midterms. He can’t stop posting about the ordeal on Truth Social, accusing unnamed saboteurs of vandalism. At the White House’s Great American State Fair on Wednesday night, part of the Freedom 250 celebrations, he ranted about the pool.

Trump’s Reflecting Pool debacle is, by definition, a national embarrassment. But America is no stranger to self-inflicted humiliation these days. (See: Iran and the Strait of Hormuz, Qatar’s gift of a luxury jet to Trump.) Why, then, is Trump crashing out so hard about the Reflecting Pool? Why does it stand out as the enduring metaphor for an incompetent administration that can’t stop providing enduring metaphors of its own incompetence?

Some reasons are obvious. As my colleague Jonathan Chait notes, uncontrolled algae blooms at the Lincoln Memorial are lower stakes and, frankly, much funnier than, say, a war, a self-dealing cryptocurrency scheme, or the destruction of a wing of the White House. (One photo in particular gets me: Four men in camo waders are in the pool. Water, the color of fresh Mountain Dew, laps at their thighs as they dredge the bottom with poles like cranberry farmers on a faraway radioactive planet.) Lately, the saga has taken a more serious turn: The National Park Service alleges that the liner of the pool was cut with a sharp knife or razor earlier this month, causing damage to the pool’s foam sealant. Trump has claimed that at least six people have been arrested and seven people have been cited for damaging the pool, and a spokesperson from the Interior Department reiterated to me today that “there have been seven arrests, seven federal citations and 18 police reports filed.” According to a report yesterday by MS Now, public records show that only David Hearn, a former Olympic canoer, was arrested. (Hearn has said he was touching a floating piece of paint that had peeled off the pool.)

The spectacle has also been straightforwardly ridiculous, such as when Park Service workers were photographed dumping gallon jugs of hydrogen peroxide into the pool one at a time to quell the algae. But Poolgate is something more—a textbook example of how the Trump administration operates. It’s a way that one can explore the anatomy of Trump debacles, which tend to unfold in a (roughly) 13-step process. The Reflecting Pool drama is not all the way through this process yet, but I’d bet good money we’ll get there. It goes as follows:

1. Devise unnecessary spectacle.

The Reflecting Pool—one of the National Mall’s best-known landmarks—is a big, obvious American symbol, and Donald Trump loves big, obvious symbols. Politics and policy are hard. Wars are even harder. But symbols are a layup. Drain that pool, slap some paint on it—be sure to give it a symbolic name: American-flag blue—and boom, you’ve made America great yet again. Extra points if President Obama made a similar move before you and you can claim you’ll do it cheaper, faster, and better. On paper, it looks perfect.

2. Disregard expertise.

According to CNN, in March, the administration reached out to Sika Corporation, the group that provided the concrete and sealing products for the 2010 renovation. The administration stipulated an intense timeline to make the 250th anniversary and that the pool had to be painted blue. Sika said the project was “unfeasible.”

3. Bypass normal procedures.

As The New York Times reported, Trump “handpicked” Atlantic Industrial Coatings for the renovation, giving the company what eventually became a $14.7 million no-bid contract by invoking an exemption “meant for urgent situations.” Trump later alleged he did not know the firm. An Interior Department spokesperson told me, “The contracts and pricing reflects the effort necessary to expedite the timeline of completing the leak prevention coating project—more people, more materials, more equipment and longer hours ahead of our 250th.”

4. Declare victory too early (bonus if done by AI-slop post).

On May 1, Trump posted an image on Truth Social of himself and other Cabinet members shirtless and swimming in the Reflecting Pool.

5. Spend way more than estimated.

“I have a guy who is unbelievable doing swimming pools up the road,” Trump said at the outset of the project. His initial estimate for the price tag was $1.5 million, which he revised the next day to $2 million. He estimated the renovation would last “30, 40, 50 years.” So far the project has cost an estimated $16.4 million.

6. Ignore the haters.

On June 3, as the project was coming in over budget, Trump invited press to the Oval Office to display a piece of poster board that extolled the pool’s size. The caption read, Our Pool is Bigger than Skyscrapers.

7. Realize it is not going well.

Algae bloom. Send in the hydrogen-peroxide brigade.

8. Bypass normal procedures once again.

As The New York Times’ David Fahrenthold reported, “The National Park Service bypassed the competitive-bidding process that is typically required” and instead gave a no-bid contract to Greenwater Services to install a filtration system to help with the algae. During construction Trump instructed the presidential motorcade to drive through the drained pool, shortly after the coating was applied, which has raised questions about whether the drive might have damaged the pool.

Taylor Rogers, a White House spokesperson, told me over email that the Greenwater contract, “was awarded by the Department of Interior” and that “the White House did not play any role in the selection process.” She called the notion that the motorcade affected the pool “dumb and unfounded.” (In all my dealings with the current administration, never before have its spokespeople been as responsive to or seemingly concerned about my impending article.)

9. Allege conspiracy and sabotage.

On Monday, Trump met with reporters and alleged that vandals put fertilizer in the water of the pool as well as cut the seal: “I can’t help it if somebody goes in with a knife and starts hacking it up.”

10. Redeclare victory.

Trump said on Wednesday that the pool “looks perfect already, but we’re fixing it.” Rogers told me that the pool is now “crystal clear and reflecting perfectly.” The pool is currently cordoned off by fences and protected by the National Guard.

These recurrent steps extend beyond Trump into the broader MAGA coalition. Recently, Jared Holt, a senior researcher at Open Measures, an organization that tracks online extremism, used a generative-AI research tool to spot patterns in posts about the Reflecting Pool by right-wing accounts on a selection of right-wing social-media platforms such as Truth Social. The tool broke down more than 2,500 posts into three buckets:

Phase 1: Triumph and Restoration

Phase 2: Defending the Project

Phase 3: Sabotage and Culture War

“For the MAGA faithful, Trump’s renovation of the Reflecting Pool was supposed to be a shining example of his efforts to restore America from its decaying state,” Holt told me. “When it became clear the renovation had been a disaster, MAGA influencers shifted their talking points to instead portray the situation as being emblematic of their critics’ depravity and derangement.” The pattern, Holt noted, is similar to how the MAGA media system responded to the ICE killings in Minnesota earlier this year, or how it has tried to spin the war in Iran. “The primary function of this media ecosystem is to hype up and pacify Trump’s base. And these days, as public support for the administration craters, it’s doing a lot more of the latter.”

This leaves three steps to come in the future. If patterns hold, we should expect 11. More blaming (one contractor told Politico the repairs to the lining will take weeks), followed by 12. Losing interest. And then, of course, the most important one of all. The foundation upon which every Trump debacle is built. The perpetual-motion device of a petulant president:

13. Pretend it never happened, and move on to the next thing.

My New Life With the Palantir Chore Coat

2026-06-25T07:00:00-04:00

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Nothing about the Palantir chore coat makes any sense. Mine is a size small, though it’s so oversize that I look like a teen wearing a hand-me-down. Then there’s the color: a piercing blue that’s nearing the shade of an iMessage bubble. The jacket is also the most comfortable and practical garment I own. It’s buttery soft and as heavy as a blanket, with three massive patch pockets that each can hold a paperback book. The coat’s plastic buttons—swirls of black and blue—are unlike any I have ever seen.

The Palantir chore coat is made by the same Palantir named in homage to Lord of the Rings, the same Palantir that has developed a reputation as ruthlessly committed to any number of national-security imperatives, and, yes, the same Palantir that builds AI tools for the military and tracks migrants for ICE. The mysterious tech giant now also wants to sell you outerwear. Only a tiny Palantir logo is embroidered into the coat’s left breast pocket, but flip the coat inside out and you’ll find a message from Palantir’s CTO, Shyam Sankar, sewn into the lining. Ask yourself constantly, Am I winning? If the answer is yes, nothing else matters. Chaos is tolerable; pain is tolerable. The only thing that matters is to win.

When the chore coat was announced in April, it became an instant grail for Palantir’s many devotees, who are drawn to the hard-core ethos of the CEO, Alex Karp (or “Daddy Karp,” as he’s sometimes known online). Palantir is proudly America First—Karp has said that his goal is “making America more lethal”—and sure enough, the company’s marketing emphasizes that the jacket is made in America with 100 percent American-grown cotton. The jacket also has been easy to mock. Here is a foray into fashion from a nearly $300 billion company that is automating warfare. People have dubbed the coat “the worst clothing release this year” and darkly wondered, “Is this the uniform that will be issued after we are all put in labor camps?” In a ranking of despicability, New York magazine’s “Approval Matrix” placed the Palantir chore coat near flesh-eating bacteria.

In the name of journalism, I decided to buy one. What would it be like to drape myself in the sartorial expression of one of the most polarizing companies in the United States? The minute that pre-orders went live, I refreshed Palantir’s website, frantically typed out my credit-card number, and paid $252, including shipping and tax. Within hours, all of the coats had sold out. Mine arrived two weeks later in a giant box labeled SOFT WEAR COLLECTION. The package included a placard signed by Sankar, a SOFTWARE DOMINATION sticker, a postcard urging me to CHEW THE GLASS, and a luxurious cedar hangar embossed with Palantir’s name and logo. A plastic card certified that this was a genuine Palantir chore coat, No. 191 of 200.

Over the past month, I’ve worn the chore coat essentially everywhere. It has accompanied me on subway rides and walks around my neighborhood in Brooklyn. I’ve worn it while perusing a gourmet gift shop stocked with elderberry kombucha, to a dive bar hosting a Friday-night drag show, and on a weekend trip to Woodstock, New York, surrounded by yoga studios and aging hippies. On a few occasions, strangers spotted the Palantir logo and did a double take. One dad scowled at me while he rolled a stroller down the sidewalk.

Ali Cherkis for The Atlantic

But for the most part, people just saw a blue coat. The logo is small and generic enough to pass notice, and the coat’s internet infamy, it turns out, extends only so far into the real world. I received far more passing compliments than shocks of recognition. “Wow, love the color!” one colleague told me unprompted. I even wore the coat to a shift at my local food co-op (I know, I know), which felt akin to showing up to a PETA meeting with a bucket of KFC. In the store, I ran into an acquaintance who praised the buttons. When I told him who’d made the coat, he didn’t know what to say.

The quality of the coat seemed genuinely high, at least to my untrained eye, so I showed it to Andrew Chen, a co-owner of 3sixteen, a menswear brand that makes its own chore coat. “It’s not easy to make something like this in America,” he told me as I modeled it for him outside a Manhattan coffee shop. (Even a 94-degree day was not going to stop me and my coat.) Chen described the fit as “a little funny” but told me that the “construction looks solid” and that “fabric-wise, it’s a really nice blue.”

Ali Cherkis for The Atlantic

A photographer joined me in SoHo, one of New York’s most fashionable neighborhoods. When you look this good, why not perch on a mailbox?

According to Eliano Younes, Palantir’s head of strategic engagement, the exact shade of blue was personally picked out by Karp. “This is actually called ‘Karp blue,’” he told me. Functionally, Younes, who is 37 years old, is Palantir’s in-house fashion guy and meme lord. He spoke about the chore coat like a proud parent. I heard about the “American bull denim” made of cotton that’s grown in Texas and North Carolina, the many weeks spent on getting the pockets just right, and the orders that have rushed in from countries around the world. (This includes France, where chore coats were first made for laborers in the 19th century; their famous blue color is where blue collar comes from. The irony was not lost on me as I wore the coat at my desk and typed away at my laptop.)

When we spoke on Zoom last week, Younes was decked out in full Palantir-branded apparel: black shorts, black shirt, black bucket hat. Palantir has started to push all kinds of merch. Its offerings include a T-shirt that says DOMINATE beneath a watercolor illustration of Karp in sunglasses ($75, plus tax and shipping); an off-white sweatshirt printed with SILICON VALLEY DROPOUTS on the back (a reference to the company’s decision to move its headquarters out of the Bay Area); and a nylon tote bag that can accommodate up to a 17-inch laptop. Last month, when Palantir held an event in Tokyo to launch the bucket hat, people waited up to two hours in line to buy one. The hat comes with a poster that is printed with a full analysis of Karp’s body composition (age: 58 years old; weight: 77.2 kilograms; body fat: 8 percent).

Younes is far from the first person in Silicon Valley who’s thought of turning software into soft wear. Tech companies have long doled out corporate merch. In addition to the classics—branded T-shirts, water bottles, Patagonia vests, Google’s propeller hat—tech companies sometimes hand out much weirder products to their clients and staff. Reddit has made moka pots branded with its logo. OpenAI’s employee-only store has, at various points, stocked a rice cooker, a basketball, and, yes, a chore coat.

Essentially, none of this swag is actually sold to the public. Palantir, meanwhile, is explicitly trying to become a lifestyle brand. As Younes has put it on X: “Palantir is THE lifestyle brand. The most pro-west, meritocratic, winning obsessed, and based brand on the face of the earth.” (On social media, he has called Palantir a “lifestyle brand” no fewer than 14 times.) To some degree, it is working. “Oh shit, that’s the Palantir chore coat!” a young guy in a white T-shirt and a gold chain yelled at me as I walked down a street in Lower Manhattan. A Palantir fan who refused to give me his name, he had heard about the coat and wanted one for himself.

Ali Cherkis for The Atlantic

This stunt was funny until I ran into a model doing an actual photo shoot.

Palantir’s strategy is familiar: The company makes a new product in limited quantities, hypes it up before a pre-announced release, and then proceeds to quickly sell out of it. (On eBay, Palantir coats are going for $600.) The same trick of juicing artificial scarcity is everywhere. In November, when Starbucks dropped special-edition teddy-bear coffee cups, police officers had to break up fights between adults trying to scoop them up. Earlier this month, when Zohran Mamdani announced New York City–branded World Cup jerseys, people started lining up at 1 a.m to buy one. The point is not only to make money (though it’s also that) but to get attention.

Palantir needs neither. The company is so notoriously opaque and does such sensitive government work that even its own employees can’t always describe what it does. Palantir’s software can feel incomprehensible and intangible, if not dystopian. But therein lies the appeal of a well-made coat. By selling merch, Palantir comes off as a smaller and more human operation. (Younes, who said he’s one of two employees focused on the company’s store, told me with apparent earnestness: “I feel like I’m running a small family-owned-and-operated business.”) Perhaps it’s no wonder that other tech companies have recently started doing the same, if in more strained ways than Palantir. Anduril has collaborated on a custom video-game console made from the metal it uses in its attack drones. Late last year, Nvidia posted a job listing for a director of “gear and merchandise” with a salary of roughly $200,000; in March, the company dropped a green knit sweater printed with an avatar of Nvidia’s CEO, Jensen Huang.

Ali Cherkis for The Atlantic

Ali Cherkis

Palantir has little to lose in this game. If American-made chore coats and water-repellent bucket hats endear people to Palantir, the company wins. If the merch serves only to provoke Palantir’s detractors, then, well, perhaps the company still wins. Online, Younes has not always taken kindly to people who have poked fun at his creations. Could the coats “be operated remotely? detonated?” one X user posted. “Here for the shitposting but I need to see better from you,” Younes replied. “This is unoriginal and not funny.” Younes told me that he is tuning out the “negative noise,” yet he seems to recognize that soliciting reactions is partly the point. The chore coats were a success not just because they sold out but also because of the “chatter,” Younes said. Palantir fans were eager to buy one, “and so they’re sharing and talking about it,” he said. “And then you have people who are also criticizing it because they might not like the company. That creates sort of this viral reaction.” If nothing else, the Palantir chore coat is an elaborate troll.

In that sense, the jacket is perfect. No other product better encapsulates how exhausting and predictable it is to be online right now. The merch-industrial complex has come so far from KFC-branded clogs and Panera’s baguette purse that even a company like Palantir is hawking swag for the likes and lolz. Next month, Palantir plans to release a tennis skirt and, to celebrate America’s 250th birthday, boxing gloves. One day, Younes said, he wants to drop a Palantir espresso machine. Sure, why not? It’s more than a bit sad. But so is the alternative, in which Palantir disappears entirely into the shadows. At least online, Palantir is just like everyone else.

I’d Rather Risk Cancer Than See AI Move This Fast

2026-06-21T08:00:00-04:00

On a fall afternoon 15 years ago, I met an idealistic researcher outside a Stanford coffee shop to discuss our shared dream: using AI to detect cancer. He had wiry hair, a penchant for talking with his hands, and a reputation for brilliance. He worked at a research lab that developed early screens for cancer; I, at 20, had just learned that I carried a mutation that conferred a very high risk of breast, ovarian, and other cancers. Over the following years, he offered guidance on how to enter his field, prepared me to apply for the scholarship that would fund my Ph.D., and warned me away from cancer-screening companies that made exaggerated claims.

But from there our paths diverged. I became an AI professor. He co-founded Anthropic. My mentor was Dario Amodei, the man who leads one of the most powerful AI companies in the world. In a utopian 2024 essay titled “Machines of Loving Grace,” he predicted that superhuman AI—smarter than Nobel Prize winners, freely using computers, and collaborating with millions of copies of itself—could soon compress a century of scientific progress into a single decade, and potentially reduce cancer mortality by 95 percent.

Which should sound pretty good to me. At 35, my cancer risks are catching up with me. A few weeks ago, surgeons removed my ovaries, instantly inducing menopause and destroying my ability to naturally bear children. By 40, the risk of breast cancer for carriers of my mutation rises to one in four, double the lifetime risk for the average woman. My mother, who also carries the mutation, was diagnosed with breast cancer at 45. Now would be a fabulous time in my life for a superintelligent AI to cure cancer.

Why, then, do I find myself rooting for delays in the creation of this AI—hoping, in my heart of hearts, that GPT-6 will be a disappointment?

Part of the answer is that, despite the extraordinary speed of AI development, I do not believe that AI is likely to cure cancer anytime soon—certainly not enough to bet my life on it. This skepticism is shared by most of the AI experts in a survey I recently advised, who generally expect slower progress than the leaders of AI labs. AI systems are strongest in settings such as chess, where they can generate infinite data (by playing over and over again), experiment freely, and observe exactly what happens. Many important settings, including math and coding, share these properties, and AI has yielded remarkable progress there. But cancer is different. Cancer data are finite and come from biological experiments and clinical trials that cannot run at silicon speeds. Experimenting freely on cancer patients would be unethical. And cancer data only imperfectly illuminate the complex processes by which our own cells betray us. There are, in short, many barriers to curing cancer beyond a lack of intelligence.

The intelligence our existing AI systems provide is also already formidable and underused. We have yet to take full advantage of systems such as the Nobel Prize–winning AlphaFold, which predicts protein structures with stunning accuracy but has not yet yielded revolutions in drug development; or the AI algorithms that match or beat radiologists at many types of image analysis; or the chatbots that now aid scientists with research. My Ph.D. students used to write code to analyze medical data; now they express their ideas in plain English and let AI do the rest. They operate essentially as professors, constrained only by their own imagination. My student recently came to me giddy with excitement over an AI-aided medical discovery.

So as daunting as a cure for cancer remains, I am certain that AI will contribute to it. And if curing cancer were the only result of building ever more powerful AI systems, I would cheer for their arrival. But the problem is that their impacts are much broader, and we are moving too quickly to ensure that these impacts are positive.

The recent chaotic release of Anthropic’s latest model, Fable 5, illustrates how unprepared we are to handle the broader repercussions of these models. Anthropic, fearing that the model might be misused to develop bioweapons, initially kneecapped its ability to answer most basic biological questions, which the company said was a temporary measure. This made the model, ironically, far less useful for cancer research than its less powerful predecessors. A couple of days later, the U.S. government issued a national-security directive prohibiting foreign nationals from using the model, likely due to concerns that it could be used for cyberattacks. In response, Anthropic shut the model down entirely. Reasonable people disagree about how risky this model is and whether Anthropic or the government is overreacting. But clearly, our institutions aren’t remotely ready to respond to these rapid deployments. (Anthropic did not respond to a request for comment about Fable 5’s rollout, nor to other questions.)

Many developers of these models, including Dario Amodei, agree that AI is progressing more quickly than society is adapting. The solution they propose is for society to speed up, not for AI to slow down, which they view as unrealistic; the very title of Amodei’s latest essay, “Policy on the AI Exponential,” frames AI progress as an iron arc to which society must bend. But speeding ahead will inevitably mean more of the type of chaos that surrounded Fable 5’s release. More fundamentally, it will shorten our time to respond to the many societal challenges that powerful AI may raise, including mass unemployment, skyrocketing inequality, repressive surveillance, and autonomous warfare. Each of these—and many others that match their scope—is an enormous problem, no less obviously important than curing cancer, for which we lack good solutions. It is not at all clear that crafting an international response to all of these issues at breakneck speed is easier than slowing AI down.

I myself am ferociously impatient; since the day I learned I carried my mutation, I have lived with the constant awareness that life is finite. But I will wait a little longer for a cure—even if it means losing my fertility and living under the shadow of risk—if it lets us approach this new world more carefully, and ensure that, in curing cancer, we do not lose the things that make cancer worth curing.

Of all the things we stand to lose, I worry perhaps most about how we will find meaning if we obviate our own minds. Amodei struggles repeatedly with this question in his essays, calling it “more difficult than the others.” I admire his attempt to confront the question but find his answer unconvincing. “I spend plenty of time playing video games, swimming, walking around outside, and talking to friends,” he writes in “Machines of Loving Grace.” But I doubt that he would want to spend the rest of his life doing only those activities—certainly I would not. He suggests that humans will still find meaning in deep intellectual pursuits, such as doing research, even if AI can do them much better. For my own part, I would neither spend months struggling with a research problem I knew AI could solve instantly nor find as much pleasure in the answers it provided. I do not want to be merely a spectator to the universe, whatever wonders AI may reveal.

Or take this essay. I will be heartbroken when a chatbot can extract my innermost feelings and, having gorged itself on the words of a million artists, regurgitate Fitzgerald-worthy prose I cannot match. For me, writing is a process bound up in self-discovery and human connection. My sister suggested the idea for this essay; my wife, seeing me suddenly and deeply sad as I reflected on it, touched my cheek, offering a comfort that no AI therapist could. Afterwards, I wrote late into the night at the handmade dining-room table I inherited from my grandparents. I thought of how my family would gather for long dinners around this table—the adults loosened with wine, the children excited to be part of it all, everyone laughing and talking over one another and debating physics and philosophy—trying, in our slow, suboptimal, human way, to figure things out.

The Curse of Too Much Evidence

2026-06-20T08:00:00-04:00

Sylvia Meagher was 44 years old in the fall of 1965 and lived alone, except for her cat, Allegra, named after the ballet dancer Allegra Kent. She commuted from her one-bedroom apartment in the West Village to the United Nations, where she’d been working for nearly two decades at the World Health Organization. Although Meagher was a bureaucrat, her sensibilities were bohemian. She was acquainted with many of the painters, musicians, and writers who lived near her. In her foyer, Meagher displayed a painting of a nude figure given to her by a neighbor, the expressionist Alexander Dobkin. But the focal point of her living space was a bookcase laden with 26 reference volumes bound in dark-blue cloth. These were the supplemental materials of the Warren Commission Report. Only a few hundred private citizens in the United States purchased a copy of the 18,000-page, 54-pound series as soon as the Government Printing Office made it available. Far fewer had read it end to end. Perhaps only Meagher had nearly memorized it.

Released in September 1964, the Warren Report was the government’s official story of the assassination of President John F. Kennedy. The report’s key finding was that an odd, angry, 24-year-old assassin, Lee Harvey Oswald, had acted alone, for reasons nobody could quite figure out. The public evidence—exhibits, hearings, et cetera—was piled into the supplementary volumes. The government did not furnish an index, making casual inquiry incredibly difficult.

During the year since she’d received delivery of her crate of the volumes, Meagher had been reading and rereading. She’d remade her living room into an office, with filing cabinets for notes and correspondence, and a large desk positioned near the fireplace. She took a volume on the subway each day and made notes on a clipboard; she worked during her commute, during her lunch hour, at night when she got home, and every weekend. One of her friends, the French journalist Leo Sauvage, called her “the only person in the world who really knows every item hidden in the 26 volumes of Hearings and Exhibits.”

Meagher was neither a conspiracy theorist nor a wannabe detective. She considered herself a “critic” of the Warren Report. A New Deal liberal with a far-left social circle, she had been subjected to questioning by a loyalty board during the Red Scare, putting her at odds with her government. When the president’s assassin was identified as a pro-Castro Marxist—not a segregationist or a radical right-winger, as many initially assumed—she felt compelled to walk through the existing evidence, piece by piece, and demonstrate where things fit and where they didn’t. She spent more than a year creating an index for the 26 volumes. At the same time, based on her clipboard work, she wrote her own analysis of the case, which was published in 1967 as Accessories After the Fact: The Warren Commission, the Authorities, and the Report. And much later, hundreds of her letters and most of her personal notes ended up archived at Hood College, a small liberal-arts college in Maryland.

Through twists and turns of curiosity (and mid-pandemic boredom), I ended up reading Meagher’s papers and becoming obsessed with her obsession. Digging into the Warren Commission’s evidence, in Meagher’s time, was regarded as something more than eccentric. A journalist called people like her—the bookkeepers and graduate students and stay-at-home moms who journeyed to the National Archives in search of answers about the assassination—a “keening pack of speculators.” It was generally considered antipatriotic and morbid to interrogate the official account.

Today, there is nothing fringe about checking the facts or “just asking questions” of an official story. Everybody does it. You could credit the critics of the Warren Report for a great act of citizenship, but you could also credit them with inventing an American pastime: They discovered that there is something thrilling about a document dump, and picking through boxes and boxes of government files. We have often associated these habits with conspiracy theorists, truthers, and the nation’s most paranoid, but in the modern era of digitized records, anyone can jump down a rabbit hole anywhere, anytime, even on their phone. Online influencers can invent careers by plumbing the court docket in a celebrity lawsuit (see the Blake Lively–Justin Baldoni case). Members of Congress can make national headlines by demanding minutiae from the Hunter Biden–laptop saga. The public can scroll through thousands of pages of records related to the crimes of Jeffrey Epstein, looking for mentions of President Trump.

Even when there is no promise of revelation, the search can be its own justification. Mine took me into a semisecret world that I could barely explain to my friends and family. The conspiratorial view of American history was both enticing and maddening, and I sometimes felt like the more I learned, the more I didn’t know.

[Read: America will be reading the Epstein files for decades]

The federal government’s records on the Kennedy assassination are housed in one of the largest archival facilities in the world: the National Archives at College Park, Maryland. In contrast to the dark and uncomfortable spaces that Warren Report critics would have visited in the original Archives building, on Pennsylvania Avenue, the reading room in Maryland is a dream. It has fantastic natural light enabled by so much glass—two-story windows wrap the entire space—that it was closed one morning while I was there because of a tornado warning.

On my first day there, to work on a book about Meagher and her friends, I learned that the JFK files are much more annoying to access than many of the others in that building. Only select Archives employees are permitted to go into those stacks; one staffer suggested to me that this is because anyone can disappear in there, sucked down rabbit holes, if there are no guardrails.

By the end of the first afternoon, I knew why. I was stumbling across amazing material, just in the boxes they’d brought to me in the reading room. They didn’t shed any light on the Kennedy assassination, exactly, but they shed light on everything around it. For instance, I spent at least an hour captivated by the paper trail left by the FBI as they tried to figure out how Dorothy Kilgallen, a New York tabloid reporter and game-show panelist, had gotten ahold of Jack Ruby’s testimony to the Warren Commission before it was published. The following year, she died in a bedroom of her Upper East Side townhouse at the age of 52, apparently from “acute ethanol and barbiturate intoxication.” Naturally, some people didn’t buy that it was a simple overdose.

I told my fiancé that there was more that I really needed to see, which I thought was true, but really I just wanted to keep looking. I ended up extending my research trip by nearly a week. One detour led me to Paul Krassner, a founding member of the Yippies, a radical (and radically goofy) New Left group. In 1976, Krassner was promising to sue the FBI over a fake reader letter it had sent to Life magazine in 1968, as part of its COINTELPRO anti-subversive program, calling him a “raving, unconfined nut.” This document was in the JFK files because it also mentioned Krassner’s infamous parodic account of the assassination, which depicts Lyndon B. Johnson engaging in necrophilia with JFK’s corpse aboard Air Force One. (Was this relevant to my book? No.)

One day, I was captivated by a story turned up by a Warren Report critic named Shirley Martin, a housewife in rural Oklahoma who was “commonly regarded as a busybody,” according to FBI agents who were monitoring her. While she was hoping to disprove the government’s theory that Oswald had attempted to assassinate the ultra-conservative General Edwin Walker in April 1963, she’d heard a rumor that Walker had entertained his own theories as to who was responsible. He had allegedly hired a private detective to find suspects, and the detective—in a twist worthy of a Coen-brothers movie—offered one suspect $5,000 to try to kill Walker, just to see if he would do it. The suspect asked for a fake passport and a getaway driver, appearing to take the plot seriously, but the detective was convinced that he was merely trying to con him out of the $5,000. (Relevant to my book? Actually, yes. I used the episode to illustrate how close Martin’s digging brought her to real, dramatic events.)

Sylvia Meagher, the woman who memorized the Warren Commission’s evidence, once described the experience of being carried away on a research tangent: “In the search for one document or one fact, the eye discovers and is trapped by a totally unrelated and fascinating document.” Meagher complained that she wouldn’t have enough time to spend on the case even if she didn’t have an actual career. Merely investigating Lee Harvey Oswald’s whereabouts throughout 1963 could’ve been its own full-time job. The alleged gunman had been spotted all over the continent in the last few months of his life, according to a flood of reports fielded by the Warren Commission. People thought they saw him in the guest book at the American Museum of Atomic Energy in Tennessee; checking in to the Skyline Motel in Pulaski, Virginia; passing out Fair Play for Cuba pamphlets in Montreal, “accompanied by a short, homely, heavy woman who took unusually long steps when walking,” according to one citizen. The commission considered a report from a magician-ventriloquist who’d been in residency at Jack Ruby’s Carousel Club for two weeks before the assassination, and was certain that Oswald had been a volunteer for a memory trick that involved 20 audience members shouting out one word each in rapid succession. Meagher kept such reports in a folder she labeled “False Oswalds.” In 1966, she helped the UC San Diego philosophy professor Richard Popkin with his famous New York Review of Books essay “The Second Oswald,” which popularized the idea of Oswald decoys, and she later refined it in her own book.

The concept of multiple Oswalds is central to the plot of Don DeLillo’s 1988 novel, Libra, which is also about archival rabbit holes; one of the book’s characters is an in-house historian at the CIA who sits alone with ever-growing towers of documents, which he refers to as “the data-spew of hundreds of lives.” DeLillo was not the only literary giant to be drawn into that spew. Joan Didion, in her 1987 book, Miami, reprinted footnote 67 of volume X of a 1978 report from the House Select Committee on Assassinations; she identified a connection between a pair of anti-Castro Cuban brothers who fired a bazooka at the UN building in 1964, while Che Guevara was inside giving a speech, and a woman who claimed they had traveled with Oswald to Dallas the previous year.

Norman Mailer hosted an assassination discussion group in the late 1980s called the Dynamite Club, which met in both Washington, D.C., and New York. Among the participants were the Watergate conspirator G. Gordon Liddy; novelists such as DeLillo and James Grady, the author of Six Days of the Condor; and assorted journalists, including Edward Jay Epstein, a New Yorker contributor who published a bombshell book about the Warren Commission in 1966.

The Dynamite Club was more parlor game than detective work. “Interesting conversations,” DeLillo said to me over email in 2024. “But I don’t recall that we reached any particular conclusion.” I’d written to ask if he was interested in Meagher’s work. He replied that he was looking at his bookshelf from his chair, and that her book was up there, along with about 60 other books on the case, plus the 26 volumes of Warren Commission evidence. “Acquiring the 26 volumes was a complicated matter,” DeLillo said, “but helpful to my work on Libra; and the volumes are also a kind of museum of voices—America speaking.” To illustrate his point he included various quotations from Marguerite Oswald, Lee’s mother, in parentheses. (“But, after all, I am going through a whole life, and it is very hard.”)

Meagher examined only a fraction of the government’s documentation of the Kennedy assassination. In the years after her book was published, millions more pages were declassified, always under pressure from the public. And because government agencies all communicated about the assassination for decades, and brought it up constantly in relation to later events, thousands of extraneous documents were marked as assassination-related. Now the files are a cross-section of U.S. history. If you cut into them and pull out a wedge, you get a little bit of everything. Looking for X, you stumble on Y. Meagher was likely at work at the UN the day that the brothers Guillermo and Ignacio Novo fired their portable rocket launcher at her office building from across the East River; its eight-pound shell, which had been manufactured by the U.S. Army, fell 200 yards short of the target, into the water. It’s easy to develop a conspiratorial view of history, because everything in the past is connected. And the more you read, the more you sense something just beyond your reach.

[Read: What the JFK file dump actually revealed]

Eventually, a rabbit hole will clog with documents. Sylvia Meagher’s one-bedroom apartment became stuffed with files on assassinations beyond JFK’s: Robert F. Kennedy, Martin Luther King Jr., and the 1972 attempt on Alabama Governor George Wallace. Her friend and fellow Warren Report critic Harold Weisberg filed countless Freedom of Information Act requests and sued the government repeatedly when its responses didn’t satisfy him. He accrued hundreds of thousands of JFK-related documents, which he stored at his chicken farm in Maryland. Meagher’s friend Mary Ferrell remodeled her house in Dallas to hold her assassination-related papers; that collection formed the basis of a monumental online depository that has become an indispensable research tool for generations of Warren Report critics.

In the internet age, such a massive public resource may not seem remarkable. But a culture of collecting, organizing, and searching a trove of government files didn’t create itself. People often point to the JFK assassination as the moment when conspiracy theorizing became an American pastime, but it was also the beginning of the age of documents, Mark Fenster, a law professor at the University of Florida and an expert in government transparency, told me. The Warren Report critics “were part of a direct challenge to the government based on the idea that if we can just get these documents, we can find the real truth,” he said. “Sadly, that is a dream that has never been realized and may never be realized.”

Some people still pursue that dream in the dry, dogged manner that Meagher did. Others, like me, jump in and out, enjoying the indulgence of cutting into something that is somehow both discrete (one batch of files on one narrow topic) and never-ending (more pages than you could possibly read). Across the years that I spent digging into the Kennedy assassination, I accrued dozens of books on the case, each with a somewhat different theory of events, and many of them convincing for an hour, or an afternoon, or a week, or more. Six decades after the fact, even a straitlaced researcher such as myself can still wonder about a thing or two—an ex-CIA guy here, a Cuban paramilitary group there.

Still others prefer to make the pursuit of truth by document into a spectacle. Early in his second term, Trump released more files about the Kennedy assassination, promising that, after 60 years of secrecy, people would now learn “THE TRUTH.” (Due to the hasty declassification, they mostly learned the Social Security numbers of former congressional staff.) And before his reelection, he blithely promised to release government records relating to Jeffrey Epstein, seeming to enjoy the positive response that he received whenever he mentioned the idea. But last summer, the promise blew up in his face: When the Justice Department finally released many of the files, a slew of mysterious redactions and omissions—some having to do with the president himself—prompted more conspiracy theorizing. Trump moved on to UFOs.

When I jumped (quite casually) down the Epstein rabbit hole, I used a free website that re-creates his email inbox—a tacky but useful restaging of years of correspondence with power brokers and cultural luminaries. There, I came across a bunch of emails between Epstein and a name I recognized from my days in the JFK files: Paul Krassner, who had once written unspeakable things about the 35th president’s corpse, and who later published some of the first conspiracy theories to connect the JFK assassination with Watergate. To my surprise, Krassner and Epstein corresponded until May 2019, two months before the latter’s arrest. In numerous friendly exchanges, Epstein expressed interest in Krassner’s writing, including a work-in-progress novel about the late comedian Lenny Bruce.

Starting when he needed dental surgery, Krassner often emailed to ask Epstein for money, which he apparently received. “I hope our contract will continue until I’m dead,” Krassner wrote in December 2017. The two men, in fact, died within weeks of each other less than two years later—Epstein in a jail cell in Manhattan and Krassner at home in Southern California. It was unclear from the emails whether they ever met in person. Their relationship had been totally unknown to the general public during their lives, as far as I could tell, and barely anyone noticed their correspondence once it was discoverable.

No, this discovery didn’t matter much. It was just a sliver of trivia buried in a data dump, a tunnel connecting two rabbit holes. But it reminded me that anything can have a special glow if you’re the one to find it—if you’re the one who thought to look for it. How did I come across Krassner in the Epstein files? It’s incredibly dumb, but you already know the answer. I’d searched Kennedy assassination, just to see.

Want to hear more from Kaitlyn Tiffany? Tune in as she joins The Atlantic’s editor in chief, Jeffrey Goldberg, on June 25 for a virtual discussion about her new book. Register here.

The Myth of SpaceX

2026-06-20T07:00:00-04:00

SpaceX had its initial public offering last week. Now Elon Musk is a trillionaire on paper. But what is SpaceX? On one level, of course, SpaceX is a company that builds rockets and spacecraft and launches them into space. (Occasionally the rockets explode.) It is also the company that birthed Starlink, a satellite-internet business that generated more than $11 billion in revenue last year.

But the company can be defined in many ways. SpaceX is a financial instrument for Musk. Before the IPO, SpaceX acquired xAI, Musk’s artificial-intelligence company, which itself acquired X, the social-media site, back in 2025. The maneuver allowed SpaceX to claim that it believed it had “the largest actionable total addressable market in human history”: $28.5 trillion, to be precise. $26.5 trillion of that, according to the filing, would come from AI infrastructure and applications, meaning not from SpaceX’s core business of aerospace engineering and satellites.

Maybe most important, SpaceX is a story, even a meme. Musk is arguably a better salesman than an inventor, and what he began selling early on was a techno-utopian dream—of himself as a Tony Stark–style genius, of an environment-saving EV revolution, of securing a future for humanity by getting us all to Mars. He intuitively understands the warped dynamics of the attention economy. Ben Tarnoff and Quinn Slobodian, the authors of the book Muskism, describe his strategy on social media as “trolling is infrastructure”: “Every joke, every poll is a stress test of responsiveness,” they argue. “Can he still move markets with a post?” Dogecoin, the cryptocurrency based on a 13-year-old meme of a shiba inu, is the shining example of Musk’s ability to lavish attention on something—in this case, a fake asset whose entire joke was that it was worthless—and make it worth more to others as a result.

SpaceX is obviously not Dogecoin. Its rocket business is a genuine success story, as is Starlink. But the company’s appeal, particularly in the face of setbacks, is also reliant on a combination of story and Musk’s own image in ways that are not necessarily connected to reality. Musk has frequently set unrealistic timelines for projects, including putting a spacecraft on Mars by 2018. Last year, SpaceX’s flagship rocket underwent a “rapid unscheduled disassembly” on three test flights (it blew up). But SpaceX’s IPO filing was more oriented around its future ambitions and assumed triumphs, such as its desire to mine asteroids, promote space tourism, and “extend the light of consciousness to the stars.” An adviser to the deal told the Financial Times last month: “From a strict corporate finance perspective, the valuation makes no sense. But Elon is great at getting people to dream.”

What do you get when you combine SpaceX the business with the financial instrument and the meme? An unfathomable amount of money, it seems. Last week SpaceX opened trading at a market capitalization of $1.7 trillion. The scale of Musk’s own net worth is now almost impossible to comprehend, such that, on Monday, SpaceX’s stock rallied, and Musk’s one-day gain was more than the net worth of Bill Gates, once the richest person in the world. In short order, SpaceX has become the sixth-most valuable public company despite the fact that it posted a net loss of $4.94 billion last year on $18.7 billion in revenue.

On Tuesday, SpaceX announced it is using some of that value to purchase Cursor, the AI-coding start-up, for $60 billion, all in stock. In reaction to the news, Bill Ackman, the hedge-fund manager (and inveterate poster), wrote on X: “One of the things that makes SpaceX so valuable is how valuable it is.” Ackman’s reasoning rings true in a financial sense: According to the deal, the price that SpaceX will pay for Cursor will be set by its own share price in the seven trading days before closing, which in effect will mean that the more valuable SpaceX is, the less Cursor will cost it. But Ackman’s koan is also correct in a more absurdist way. It highlights the irrationality of the modern stock market and reflects a lesson of the past decade: If a person or group of people is able to marshal enough genuine attention toward an idea—no matter how ridiculous it might seem—they can usually bend reality toward their preferred outcome.

Other than perhaps Donald Trump, it’s difficult to argue anyone has been more successful at this than Musk. Musk excels not because he can’t stop winning, but because he understands that, in the financialized logic of our age, winning is less important than the perception that you will win. Speculation beats fundamentals. One way to look at Musk’s personal brand is as somebody who has borrowed obsessively against his own reputation, each loan used to invest in and service the debt of the last, until it becomes impossible to follow the money. One of the things that makes Elon Musk so valuable is how valuable he is.

With SpaceX’s IPO, you could argue that Musk has either won or broken capitalism. His wealth, in our current system, makes him a chaos agent with no real comparison. He is virtually impervious to fines. His money, should he wish to spend it, has the potential to drastically influence the outcome of elections. That leverage could be used to benefit Musk’s businesses, securing further contracts with the government and entrenching him deeper into the infrastructure of everyone’s lives. This power isn’t theoretical; Musk’s dominance in satellite connectivity has already made him geopolitically relevant in places including Ukraine and Iran.

SpaceX and Musk are, of course, not inevitable. Analysts are predicting volatility for the stock as lockup periods end and people sell shares. The AI bubble could pop. Musk could mismanage the company as he did with X, or he could become so radioactive that institutions stop associating with him. But you can also imagine the SpaceX flywheel spinning out of control, perpetuating itself as Musk and SpaceX become fully untethered from reality. On X, Will Manidis, a start-up founder and investor, argued recently that, given the dynamics of SpaceX’s stock, it could continue to purchase some of the internet’s foundational software companies at a cost of basically nothing. Neither Musk nor SpaceX responded to a request for comment on SpaceX’s direction, and such tweets, at this moment, are little more than fan fiction. But they represent the absurdity of Musk’s current position in the modern economy. Musk has long fantasized about creating a massive, vertically integrated constellation of services—from banking to social networking—he once dubbed “the everything app.” So far, he’s failed in that quest (the phrase trust Elon Musk with your routing number would still strike fear in the hearts of most people). But it’s not difficult to see Musk using his cheap and abundant money to build toward the Everything Holding Company.

Is any of this possible? Would it even be legal? That’s unclear. But as Bloomberg’s Matt Levine once noted, it seems like “Elon Musk’s recent career is a long experiment to prove that, if you are successful enough, the regular laws do not apply to you.”

In the aftermath of the 2008 financial crisis, Rolling Stone’s Matt Taibbi memorably described Goldman Sachs as “a great vampire squid wrapped around the face of humanity, relentlessly jamming its blood funnel into anything that smells like money.” Goldman Sachs, he wrote, “positions itself in the middle of a speculative bubble,” enabled by “a crippled and corrupt state that allows it to rewrite the rules.” Revisiting that article in the age of Musk the trillionaire feels almost quaint. Musk and SpaceX have a true nose for money, including sniffing out government infusions and contracts. The aerospace company has figured out how to position itself firmly in the middle of the speculative hype of the AI cycle, and numerous financial organizations have amended rules designed to protect retail investors.

The vampiric Goldman Sachs that Taibbi describes is an institution, a system that became too big to fail, and thus ungovernable. Musk is a person, not a system or institution, but he owns more than 40 percent of SpaceX and controls more than 80 percent of its voting shares. According to Reuters, in the lead-up to SpaceX’s IPO Musk was dictating terms to Goldman Sachs and other banks.

If Goldman Sachs is the vampire squid, what does that make SpaceX and Musk? The natural world offers few good comparisons. What we’re seeing in terms of hype, valuation, and fortune is without precedent, even when stacked up against the wealth concentration of the Gilded Age. SpaceX and Musk are better served by a mythological comparison, in part because the entire enterprise is built on a story told over and over until it transcends reality. SpaceX is a rocket company, a complex financial instrument, a meme, a monument to a broken financial system. It is the seven-headed Hydra at the end of finance, the teleological endpoint of money. It is a myth kept alive by blind faith, devotion, and even aggression, which makes it dangerous whether you believe in it or not.

America Is Headed Toward the Infinite Workweek

2026-06-18T12:21:00-04:00

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Last year, Steve Yegge started “suddenly getting pounded by nap attacks in the middle of the day.” Without fail, Yegge—a programmer and tech blogger—would “hit a wall, fall over, and sleep for 90 minutes,” he told me. Like many developers, Yegge no longer writes code by hand; instead, he manages a legion of bots to do that for him. His productivity has skyrocketed, but so too has his exhaustion. “I’ve fallen asleep slower at the anesthesiologist,” he recently wrote on his blog.

In theory, handing tasks off to coding agents should free up time, allowing larger blocks for deep work and rest. But some developers are having the opposite experience. Instead of allowing for greater focus, the latest AI tools are overwhelming workers, frazzling minds and shredding attention spans. Although agents can do plenty more work now than they could a year ago, they still need human oversight. Like toddlers, AI agents ask endless follow-up questions, require detailed instructions—and, if you leave them unsupervised, are liable to make a huge mess. Once you get several running simultaneously, there’s no time for breaks. As Yegge puts it on LinkedIn, his job is to be an “AI babysitter.”

[Read: AI agents are taking America by storm]

Plenty of people are seemingly starting to feel like depleted AI babysitters. When Boston Consulting Group recently surveyed roughly 1,500 workers across several roles at major American companies, the firm found that many workers were experiencing “mental fatigue from excessive use or oversight of AI tools beyond one’s cognitive capacity.” Respondents described a “buzzing” and “fog”-like feeling, sometimes accompanied by headaches, slower decision making, and trouble focusing. One engineering manager told the researchers that managing multiple bots at once was like having “a dozen browser tabs open in my head, all fighting for attention.” In the survey, 18 percent of developers reported AI-induced exhaustion. But in other roles, too, such as HR and marketing, where AI is also taking over, rates of reported fatigue were even higher.

In my own experiments with AI agents, I’ve experienced some of this brain fog myself. To get in the mindset of an overstimulated developer while working on this story, I asked Claude Code to deploy a team of agents to supplement my research. I already had done my reporting, but I figured the bot might be able to surface more information. Claude Code spun up a team of 17 researchers. It assigned eight agents to research different subtopics, another eight to serve as fact-checkers, and a final agent to synthesize the group’s findings into a memo.

The bot promised that the research would be easy. “Nothing for you to do,” it wrote. “Sit tight.” But the agents were needy from the start. Almost immediately, Claude Code began asking for all kinds of permissions to take actions on my behalf. Because I didn’t understand some of its questions, I started going down different rabbit holes trying to make sense of its requests. I could feel my shoulders tensing. Even once my research swarm finally got going, I kept checking in on the bots to make sure that they were on the right track. The fog was setting in. In the end, the memo that my 17 agents produced wasn’t very good, but neither was the paragraph I’d spent that time writing, because I’d been distracted by my omnipresent agent blob the entire time. (In line with The Atlantic’s policies on AI use, I didn’t use the tools to do any actual writing.)

This all felt like multitasking on steroids. In my quest to maximize my own productivity, I was wasting time and producing lower-quality work. As the BCG team found, “juggling and multitasking can become the definitive features of working with AI.” Fortunately, I am able to use AI tools only when they are genuinely helpful, but other workers may not have that luxury. Across corporate America, companies are pushing people to adopt AI—and some workers are even competing with one another on leaderboards that track individual usage. This has led some people to automate unnecessary tasks to prove to management that they are making use of the technology.

Others are finding they can’t stop talking to their agents. “Spinning up all these agents is sort of like pulling a bunch of slot machines at the same time,” Matthew Kropp, a managing director and senior partner at BCG, told me. If you assign work to a team of agents, you never know precisely what they will get back. Sometimes the bots fail miserably, but other times, they do produce great work. That variable reward, Kropp told me, hacks people’s dopamine circuits. “It’s very akin to gambling,” he said. Rather than taking time for breaks, some people are finding themselves feverishly rotating among different agents.

For all of the justified concern over the potential for AI to automate work, the rise of AI babysitting points to how the technology is already changing jobs. “People are constantly talking about a white-collar apocalypse,” the MIT economist David Autor told me. “I don’t think it’s going to look like that.” Perhaps soon, agents will be good enough to do more work unattended. Some people may lose jobs, but Autor expects that for many people, work will simply look different. A preindustrial cobbler who made shoes by hand had a very different relation to his work than his daughter threading laces on the factory floor did, but both were in the business of making shoes. Indeed, the internet is full of workers complaining about how their jobs have become akin to manning an assembly line. There may soon come a day when consultants reminisce about creating PowerPoint presentations by hand.

[Read: Imagine losing your job to the mere possibility of AI]

Whatever the future of white-collar work, it is likely to be messier and stranger than we can imagine. At the extreme, Andi Peng, an AI researcher, speculated that within the decade, we might not even need laptops at work, because agents will record human conversations and do computer work on humans’ behalf. The idea struck me as hard to fathom. Then again, a few decades ago most office work was done without the internet.

The more realistic future is, perhaps, less exciting. Now that agents can work for hours on end, workers are likely to face growing pressure to make the most of them. In Silicon Valley, engineers assign their agents tasks to complete overnight, and then check the results even before their morning coffee. Some are staying up late: “The opportunity cost of going to sleep is too high,” the billionaire venture capitalist Marc Andreessen said on The Joe Rogan Experience last month. “If you go to sleep, you won’t be with your 20 AI coding agents.” Slack and email have already made workers feel as if they are expected to be available after hours. AI was supposed to alleviate people’s workload. Instead, with bots that can work while you sleep, we may be headed toward something like an infinite workweek.

The Feel-Good Story of the World Cup Is Too Good to Be True

2026-06-17T09:55:42-04:00

Every World Cup propels a breakout star into the firmament; this year’s might just be a seemingly random German soccer fan who goes by Freddy. In the World Cup’s opening week, his X posts extolling a Taco Bell as “the holy land” and chronicling his rapturous 1 a.m. visits to a Waffle House and a Buc-ee’s have attracted more attention—from Americans, at least—than most of the actual matches.

Freddy from Germany is the standard-bearer of an emergent social-media genre: A World Cup visitor from overseas encounters American culture and excess—and loves it. The Spanish soccer wunderkind Lamine Yamal loaded up a grocery cart at a Walmart in Georgia. “Why did no one tell me ranch sauce is like crack?” a Swedish fan posted on X from an Indiana diner. “EUROPE WE NEED RANCH ASAP.” A Japanese man raved about Texas Roadhouse steak. Freddy’s Buc-ee’s post showed customers flowing into the cavernous convenience store, its cartoon-beaver logo a towering beacon that illuminated the night sky. In another photo, a row of pumps stretched, like a horizon, beyond both sides of the frame. Freddy was overawed: “DUDE LMAO THIS IS A GAS STATION😭😭😭,” he wrote.

Americans, of course, are eating it up with a spork. “This is genuinely making me patriotic,” one wrote of a video showing a rotund New Jersey–deli guy dancing with a visitor from London and giving him a chicken-parm sandwich on the house. Another observed: “It’s sick to see how many Europeans came over here to actually enjoy US culture. Saw a guy look at a Buc-ee’s gas station the same way I’d look at Stonehenge.” The caption on a video of an Italian’s astonished reaction to unlimited soda refills captured the half-winking exceptionalism in a familiar meme: “The European mind cannot comprehend this.”

The videos have been covered in the media as a refreshing antidote to our polarized political moment and as an indication that American greatness resides at least partly in conveniences we take for granted. It’s a nice thought. But not all of the videos, or the people behind them, are quite what they seem.

Take the Swedish soccer fan who swooned over ranch dressing. Elsa Thora, a photogenic 24-year-old blonde, has been featured in a number of news stories about foreign soccer fans’ American exploits, exuding a gee-whiz gusto for the country’s food and culture. “I feel like I’m in a movie,” she posted, holding bags of Hostess Twinkies and cheese-stuffed Combos outside a convenience store. “OK so Amish people are real,” she marveled.

What many of the news stories have failed to mention is that Thora is not new to the social-media spotlight. She’s a star on the adult platform OnlyFans and a fixture in the British tabloids, where she’s made headlines for expressing her desire to have sex in space, to birth Elon Musk’s first baby on Mars, and to sleep with a player from every English Premier League soccer club. (“Three down, 17 to go,” she told The Irish Sun in 2024.) She already has some 388,000 followers on Instagram. When I reached her by phone, on her way to Los Angeles, she told me that she works in digital marketing but that the trip to the States was just for fun and the love of soccer. She acknowledged that her posts here have raised her social-media profile but insisted that she isn’t trying to monetize them: Her enthusiasm for American culture is genuine, she said.

Thora may have more to gain from gushing than an ordinary soccer fan, but at least she’s a real person who’s really here for the World Cup. The same cannot be said for Nobunaga, a user whose viral X post purports to recount a Japanese visitor’s experiences at an American hibachi restaurant. “I witnessed a ritual I have never seen in eight hundred years of being Japanese,” begins a deadpan story that goes on to describe the chef building a flaming volcano of onion rings and hurling a shrimp through the air for the narrator to catch with his mouth.

The post is part of a series in which Nobunaga takes on the persona of a samurai traveling around the world and into space. (The account shares a name with Oda Nobunaga, a powerful 16th-century samurai.) Running the posts through Pangram, an AI-detection tool, yields a consistent verdict of “100% AI.” Nobunaga told me via X message that the aim of the stories is comedy, not “realism, journalism, or persuasion.” But at least in the context of the World Cup, some of the account’s audience seems to have taken its American-restaurant reviews at face value. “I am enjoying your posts with enthusiasm and a few tears,” a woman, whose X bio identifies her as a Trump supporter and patriot, replied to the hibachi post.

Between the influencers and the AI-slop accounts lies a spectrum of inauthenticity. The New Jersey–deli guy, for instance, is real, but the Parkwood Deli’s 400,000-follower Instagram account suggests that the shop is canny about marketing his old-school charm. And in fact, the deli first posted the clip of his interaction with the London couple on Instagram in April, which suggests it had nothing to do with the World Cup, despite its current popularity. (Parkwood Deli did not respond to my request for comment.)

Also real is the Japanese man who praised Texas Roadhouse for its steak. The account’s owner, who told me his name is Keisuke Yamanaka, really does enjoy Texas Roadhouse, and he isn’t a professional influencer. But he also isn’t in the United States for the World Cup, and the image he posted wasn’t his own, he acknowledged. “To be completely honest, when I posted the tweet, I never imagined it would reach millions of people,” Yamanaka said. “I simply wanted to share a restaurant recommendation with Japanese fans traveling to the United States for the World Cup.”

Then there’s Freddy. A month ago, he had an unremarkable social-media presence, posting almost exclusively in support of the legendary Portuguese forward Cristiano Ronaldo. An April post on X about his upcoming trip to the World Cup in the United States got a modest 60 likes. Then he landed in Atlanta, his starting point for a road trip to Houston with his unnamed companions, and his profile achieved liftoff. He snapped those pictures of the Taco Bell and got 48,000 likes. On June 8, he bestowed a 10/10 rating on his Waffle House visit—109,000 likes. And then, on June 10, the Buc-ee’s blockbuster: 305,000 likes, more than 25 million views.

Suddenly Freddy was a rock star. He started taking requests for places to visit next. He hit up a Bass Pro Shops that he said had a shooting range inside it. By June 12, he was fending off fake Freddies who had sprung up on Instagram and TikTok to try to cash in on his newfound fame. In New Orleans, he was given free tours of the Saints and Pelicans facilities. A sign on the highway at the Louisiana border reads Welcome to Louisiana; below it was a hand-painted banner: Welcome Freddy. In Houston, Freddy hype took on a life of its own. The police department posed with him for a photo op. The mayor met him at an Astros game. The American-football star J. J. Watt bought him a lavish hotel stay and a care package full of swag. By Tuesday, he was at NASA’s Johnson Space Center getting a personal tour of the Orion capsule from the astronaut Anne McClain. Freddy did not take a time-out from the ride of his life to respond to my request for comment.

Posts like Freddy’s and Thora’s tell a story that’s flattering to Americans—that unfettered consumerism has gotten a bad rap; that, contrary to conventional wisdom, there is such a thing as American culture; that it deserves celebration, even adoration. But telling people what they want to hear is exactly what today’s attention economy is designed to do. Algorithms don’t guarantee that those posts will reflect reality. As long as the demand for the content is genuine, the supply doesn’t have to be.

No doubt at least some of the mutual enthusiasm between Americans and visiting football fans is sincere. Bostonians joined Scotland’s “Tartan Army” as it marched through their city, blaring bagpipes and drinking its pubs dry. Philadelphians embraced a crowd of raucous Ecuadorans who draped their national team’s yellow jersey over the city’s beloved Rocky statue (a classic blunder, as it turns out). It’s probably not a coincidence that so much American hospitality has been showered on Freddy, the character whose story feels the closest to authentic of the bunch. I verified with spokespeople for both the Houston police and mayor’s office that his interactions with them really happened.

Yet even Freddy is keeping close control of his own story and has studiously stayed anonymous, at least to online fans. He has been careful not to show his face in any of his posts and has not disclosed his real name. Whatever his initial intentions for posting through his World Cup trip, his great American adventure has gathered a momentum that professional influencers dream of. When Freddy found the care package from Watt in his hotel room, he was moved. “This is all so insane... I genuinely don’t understand how it got to this point,” he posted. “We’re just normal World Cup tourists.😭😭” If that was ever true, it isn’t anymore.

AI Is Taking Over Hospitals

2026-06-17T07:00:00-04:00

Every knowledge-based profession may one day reach the point when AI outperforms the human experts. In medicine, that day appeared to come in April. A group of primarily Harvard and Stanford researchers announced the results of a study that pitted ChatGPT against hundreds of physicians in a diagnostic obstacle course involving written medical mysteries and information from real-world patients. The bot had won, and the humans weren’t entirely happy about it.

“I get a little bit queasy about how some of these results might be used,” Adam Rodman, a lead author on the study, said at a press conference just ahead of its publication in the journal Science. The work had amounted to an academic exercise, he told reporters; as thorough as it may have been, it did not prove that ChatGPT or any other AI tool was ready to become a standard part of medical practice. His caution was in line with that of other experts, yet as Rodman knew, most people will ignore the warning. AI has already wormed its way into the U.S. health-care system, evidence and safeguards be damned.

Even as I was watching Rodman’s press conference, I got a message on my phone from the administrators at the medical center where I work as a pathologist. They’d emailed me to say that an “AI-powered clinical reasoning tool” was now available for me to use. This wasn’t the first time I’d gotten this sort of email; it wasn’t the second or third time either. In fact, I’ve lost count of how many generative-AI products have been rolled out to us in recent years, none of which has been approved for medical use by the FDA.

This enthusiasm feels unprecedented. Health care is typically among the last fields to adopt a new technology; I still use a pager, and I send faxes on a regular basis. (Younger readers can ask Claude to explain what these things are.) A tendency toward simple tech is in part a product of doctors’ safety-focused culture: We know that any ill-timed glitch has the potential to turn deadly. But these days, clinicians are allowed—encouraged, even—to run wild with the latest software, guided by a generic warning that “AI can make mistakes.”

Those mistakes can be consequential. Although Rodman’s research shows that generative AI can help diagnose rare diseases or make sense of unusual symptoms, a randomized trial that was published in NEJM AI just the week before found that intentionally erroneous output from an AI model can easily lead doctors astray. Nonprofessionals could be similarly misled. A recent study by Oxford scientists found that using AI did not significantly improve patients’ ability to diagnose themselves or others. Another one, led by researchers at Mount Sinai, suggested that chatbots may fail to alert users to potential medical emergencies.

[Read: Drink whole milk, eat red meat, and use ChatGPT]

Misdiagnosis is not the only concern. As AI permeates the health-care system, errors are cropping up in unexpected places. When I spoke with Rodman by phone after his press conference, he told me that he’d been surprised one day to find that his hospital, Beth Israel Deaconess Medical Center, had enlisted AI to draft messages to patients on his behalf—sometimes producing output for his review that he described as “completely absurd.” (Sarah Finlaw, a spokesperson for Beth Israel Lahey Health, told me that use of AI tools is voluntary and subject to hospital training and support. She also said that any output from AI tools must be approved by a physician.)

Part of the problem is that health-related AI products can be deployed without any vetting by officials at the FDA. If a software package that is intended for physicians is classified as a “clinical decision support tool,” and not a medical device, it usually avoids the agency’s oversight. To be counted in this category, an AI-powered app generally must rely on the existing medical literature, avoid analyzing medical scans or images, explain its reasoning, and leave diagnosis and treatment up to a physician. Most of the generative-AI products that doctors use today seem to meet these criteria.

Consumer-wellness apps and devices may also bypass FDA review so long as they are intended for “maintaining or encouraging a healthy lifestyle” and not for diagnosing or treating specific conditions. With this in mind, Microsoft, OpenAI, Anthropic, and xAI all warn users that their health-related chatbots are not meant to provide medical care or issue diagnosis and treatment recommendations. In practice, though, the distinction isn’t always clear. Elon Musk encourages people to use his Grok chatbot to generate second medical opinions and interpretations of their X-ray and MRI images; a marketing video for ChatGPT Health shows the app reassuring people that their lab results are in a healthy range and encouraging them to continue taking cholesterol medication.

Most of these apps also invite users to connect their medical records and wearable health devices. AI companies wouldn’t need to gobble up all of these data just to offer generic health information. A new product from the medical start-up Hims & Hers, called Labs AI, goes so far as to help interpret the results from “up to 130 biomarker tests” for its users and then provide a “deep, personalized, and actionable analysis on whole body health, risks, and patterns.” I, too, analyze a patient’s lab results and then give personalized, actionable advice. What’s the difference?

When I reached out to the makers of these products, they reaffirmed that no actual medical advice is being given out to users. Dominic King, the vice president of health at Microsoft AI, told me in an emailed statement that its Copilot app provides “helpful information and support for conversations with clinicians” and not “a single, firm diagnosis.” Patrick Carroll, the chief medical officer of Hims & Hers, told me that Labs AI does not diagnose or recommend treatment: “That responsibility belongs to clinicians, and Labs is designed to reinforce that boundary.” Anthropic and xAI did not respond to my inquiries. OpenAI declined to comment for this article.

Perhaps that boundary—between doctor and algorithm—is somewhat artificial to begin with. One idea kicking around the medical literature is to stop treating AI products as if they were merely standard medical devices. Given their humanlike ability to learn new information and tailor answers to individual patients, medical AIs may function more like doctors than defibrillators—so perhaps they should be evaluated in the same way that physicians are. Instead of requiring FDA approval for each and every function it can perform, a chatbot might be asked to pass a medical-licensing exam and undergo a period of supervision akin to a medical residency.

[Read: The ChatGPT symptom spiral]

For the moment, though, that idea remains on the fringe. Haider Warraich, a cardiologist and program manager at the Advanced Research Projects Agency for Health, the U.S. government’s program for developing advanced health technology, is leading a major effort to get medical chatbots approved in the traditional way. His agency is providing funding for the development of an AI tool that is tailor-made for heart conditions, and then to send it through a full FDA-authorization process. Warraich’s hope is that by undergoing such a rigorous evaluation, the chatbot will be able to safely evaluate and treat patients without the involvement of a doctor. Rodman praised this approach but warned that the process is going to take years, during which time a plethora of new health AIs will have slipped into the market with little scrutiny.

In this way, the emergence of today’s AI health products remind me of the rise, in the 2010s, of ride-sharing services such as Uber and Lyft. The taxi industry is heavily regulated, making it difficult for new players to enter the market. Yet by skirting and at times ignoring those rules, ride-sharing companies were able to acquire a critical mass of users in a short period of time. Pretty soon, governments had little choice but to adjust their laws to match what had by then become the status quo. The same pattern could end up playing out in medicine. Will regulations meant to ensure that medical products are safe and effective remain in force? Or will they instead be weakened or removed to clear the path for tools that everyone is already using?

We’ll soon find out. The health-care system is not going to “slow down and wait for the evidence to accrue,” Rodman told me. Eighty percent of doctors are already using AI tools in their job, according to a 2026 survey by the American Medical Association. Patients aren’t far behind. The benefits of AI may remain uncertain, but they’re already too enticing to pass up.

Assume You Will Be Hacked

2026-06-16T13:50:00-04:00

Late last month, I began to consider withdrawing some money from my savings account to buy gold. It’s the first time I’ve ever thought about panic-buying. For all of the firewalls and two-factor-authentication codes, the safety of the internet is starting to falter. Hackers are gaining the upper hand over organizations around the world—hospitals, energy grids, government agencies, and, yes, banks.

As AI tools have become extremely good at writing code, they’ve also become extremely good at pulling off cyberattacks. (Malware, after all, is still software.) The result has been a change in the scale, speed, and sophistication of hacks that is difficult to overstate: Among its tens of thousands of clients, the cybersecurity firm Palo Alto Networks identified a fourfold increase in daily attacks from 2024 to 2025. Hackers are developing AI-enhanced computer viruses that adapt on the fly to avoid detection. They are automating cyber-espionage campaigns on foreign governments. They are stealing data in minutes instead of hours. “There’s a crazy amount of offensive activity happening right now,” Alex Stamos, a former chief security officer of Yahoo and Facebook, told me. “Companies are getting hacked every single day.”

If the NSA is perturbed by the rise in cyberattacks, which it apparently is, then surely my savings are vulnerable. There could be any number of weaknesses in my bank’s IT systems to directly hack. Or perhaps an AI-written phishing email targeted at an employee, personalized to sound like a family member or manager, could let hackers into the back end to empty my coffers. Even if the bank has great cybersecurity, an attack on another business—a medical clinic I visited, a car-rental company, a newsletter subscription—could steal my payment information and, potentially, much more. The attack angles are seemingly infinite. And no one is adequately prepared.

The term software engineering has always been an insult to the level of rigor demanded of mechanical, civic, and other engineers. Computer programs can be riddled with vulnerabilities and run just fine for years or decades—and much of the software underlying the web has done just that. “We’ve just been writing software in a totally slapdash and insecure way for decades now,” Stamos, who is now the chief security officer at the AI-coding company Corridor, said. With some small, high-stakes exceptions—such as software used on the International Space Station or nuclear submarines—code is written and deployed without much rigorous testing. If a bug is reported, it gets patched.

Such a relaxed security posture has been more or less fine because discovering vulnerabilities is hard and skilled hackers are few in number: Either nobody found the bugs or nobody was able to exploit them. But traditional cybersecurity methods don’t cut it anymore. Before, you might scramble for a week to patch a hole, Giovanni Vigna, a cybersecurity expert at UC Santa Barbara, told me. “Now you could have hundreds of those every week.” Moody’s Ratings has found that the time attackers take to exploit a publicly known vulnerability (the digital equivalent of a robber plotting how to get around a bank’s guards and cameras after obtaining a key) fell from more than 700 days in 2020 to just 44 days in 2025—faster than the average time cybersecurity teams take to patch the bug.

Governments and major companies are on high alert for AI-enabled cyberwarfare. The wake-up call came this spring, with the announcement of two extremely advanced cyber models—Claude Mythos Preview from Anthropic, and the analogous GPT-5.5-Cyber from OpenAI soon after. Many independent cybersecurity experts have told me that these models are as or nearly as skilled as elite human hackers, which is why Anthropic and OpenAI didn’t release them publicly. Instead, the AI labs have granted a small number of partner organizations and government agencies exclusive access to the unrestricted versions of these cyber models in the hopes of shoring up their IT systems. And this month, Donald Trump signed an executive order to expedite just that.

[Read: Claude Mythos Is Everyone’s Problem]

Organizations can guard against the coming deluge of AI-enabled hacks, most notably by using AI to detect and resolve vulnerabilities before cybercriminals can exploit them. Anthropic has itself used Claude Mythos Preview to find thousands of bugs in open-source-software packages—many of which went undetected for years or decades—that undergird much of the internet. Mozilla used Mythos to fix more than 400 bugs in the Firefox web browser in April, roughly 20 times more than it fixes in a typical month. And having an AI agent monitoring for intruders 24/7 could be far more effective than periodic cybersecurity audits. If you’ve noticed more updates in your web browser, work software, and smartphone apps, it may well be because software companies are using AI to scan for bugs.

But, if anything, these efforts are late. Even though they’re not as powerful as Mythos, plenty of free and open-source AI hacking tools are allowing criminals with little technical experience to marshal an army of hackers at their fingertips. Tools from Google, Anthropic, and OpenAI have guardrails intended to prevent them from being used for hacks, but they are not perfect: All three companies have reported more, and more sophisticated, hacking attempts using their AI models. When the courseware Canvas was hacked last month, upending classrooms in thousands of schools and universities worldwide, AI likely played a role—and the criminal group responsible, a notorious hacking ring called ShinyHunters, is known for using AI in all sorts of scams. Just weeks later, Google cybersecurity researchers reported that ShinyHunters had hacked into an Oracle HR system and may have stolen data from more than 100 organizations. Meanwhile, the Trump administration has forced Anthropic to revoke all public access to the latest version of Mythos—taking away perhaps the most powerful cyberdefense tool we have from both the government and the private sector.

[Read: The White House is ratcheting up its war against Anthropic]

That does not mean you should withdraw your life’s savings and buy gold (although, well). But a tremendous amount of change needs to happen in a very short period of time; open-source AI models will soon catch up to Mythos and GPT-5.5. The internet needs upgrades “at a Y2K-like scale,” Raffi Krikorian, the chief technology officer at Mozilla, told me, referring to a widespread fear that computer programs interpreting the digits “00” to mean the year 1900, rather than 2000, would bring down the web. But IT professionals spent years preparing for and ultimately avoiding a Y2K apocalypse, he said; with AI, we have months. No one company or government can demand the requisite collective action rapidly enough to completely secure our digital infrastructure. “There’s no way organizations across the globe are going to patch everything that needs to occur within the next three to five months,” Wendi Whitmore, the chief security intelligence officer at Palo Alto Networks, told me.

At the same time that bots are making hackers more capable, the technology is also making the web less robust to attacks. Coding agents, due to their propensity to hallucinate, frequently write insecure code—and humans, in the thrall of vibe-coding, usually don’t take the time to verify it. Spotty AI code has, for instance, reportedly caused multiple outages in Amazon’s e-commerce services. Meanwhile, the AI models being integrated across the web—into Amazon, Google, your bank’s customer-service department, and more—are themselves new, untested, and vulnerable to all manner of creative attacks that allow hackers to request passwords and personal information. A few weeks ago, a group of cybercriminals basically just asked Meta’s customer-service AI to give them access to some 30,000 Instagram accounts (including the Sephora corporate account and the defunct Obama White House account), and the AI obliged. (“Some of our internal backend checks failed in this instance, but it wasn’t due to the AI agent itself, and we’ve addressed the underlying cause,” Andy Stone, a Meta spokesperson told me.)

The near future is very likely to involve more frequent, and more severe, outages and hacks just like those affecting Canvas, Meta, and Amazon. “We will see more of these disruptions,” Vigna said. “I think it’s inevitable in the short term.” Smaller but crucial companies and organizations that are not web-native—think power plants, municipal-government agencies, credit unions—are especially vulnerable. They may be running all sorts of clunky legacy code, and lack the IT capacity or financial resources to make the necessary upgrades. In many cases, the person who wrote the bulk of an organization’s software might be retired or dead.

Take hospitals, many of which are already struggling to combat data breaches and ransomware attacks. Hospital IT systems are full of valuable health and financial data, and the incentive to pay a ransom is high when patients’ lives are on the line. “It’s not a matter of will to increase cybersecurity for hospitals,” John Riggi, the national adviser for cybersecurity and risk for the American Hospital Association, told me. “It is a matter of resources and capabilities.” AI, he said, will make everything worse. And the greater burden is always on the side of the defense: Missing just a single vulnerability can permit a catastrophic attack. An Anthropic spokesperson told me that “hospitals, utilities, and smaller banks run on software built by others,” which Mythos is helping secure. “Software upstream protects the organizations downstream that don’t have resources to staff their own security research team.”)

A worst-case scenario over the next year or so might look like “blackouts across the United States, telecommunications companies being hacked,” Krikorian said, or “our banking systems dealing with people losing money left and right.” Every cybersecurity expert I spoke with for this story concurred: The next few months, couple of years, or even longer will be rough. “I hope that it’s not a catastrophic outage, but I am concerned that 2026 really could be the year that we see some sort of attack like that become very successful,” Whitmore said. Anthropic estimates that a major cyberattack on just one of its 200 or so partner organizations could affect at least 100 million people.

Collective action aside, some precautions exist that individuals can take short of liquidating into gold. Many of them are basic: using a password manager that auto-generates long passwords, keeping software updated, restarting devices to wipe viruses from their short-term memory. Be extra wary of all sorts of phishing texts and other low-level scams. And you might consider simplifying your digital life by switching to a Chromebook, certain tablets, or another gadget that is a “thin client,” meaning that very little software and data are stored on the device.

Even in the most catastrophic of scenarios, perhaps we can ride out the AI hacks. No one knows just how many bugs are out there. If there’s a limited pool of vulnerabilities online, things will settle down once they are all found, whether by hackers or security audits. But it’s also possible that every time the top AI models reach a new threshold of capabilities, Stamos said, they discover a new pool of still more complex hacks. And so the chaos begins anew.

The White House Is Ratcheting Up Its War Against Anthropic

2026-06-15T16:49:00-04:00

In theory, Donald Trump has a consistent position on AI. On the first full day of his second term, the president declared that he would use his full authority to speed the AI industry along and, in particular, to beat China in the AI race: “We have an emergency,” he said. “We have to get this stuff built.” If AI is poised to become the most important technology ever made, the thinking goes, whichever country commands the most powerful bots will dominate the rest of the century and beyond. The government, it seemed, would just get out of Silicon Valley’s way.

But in practice, the Trump administration’s approach to AI has been much more erratic and confusing. Take last week, when Anthropic released its most advanced AI system yet. Called Fable 5, the model is an updated and public version of Claude Mythos Preview, the highly touted and feared AI model that Anthropic announced in April. Anthropic stated that Mythos Preview was so capable at hacking that only a small group of cybersecurity partners would be allowed to use it. In the subsequent months, the company developed guardrails to prevent people from misusing its most powerful AI for cyberattacks, while still allowing them to marshal its capabilities for other sorts of work. The safety measures underwent third-party testing, including with the U.S. government, and after Fable’s release, a chorus of cybersecurity experts complained that, if anything, the model was too restrictive.

On Friday, the White House appeared to change its stance. Administration officials deemed Fable 5 a threat to national security and reportedly gave Anthropic 90 minutes to take down Fable 5 and Mythos 5, a newer version of Mythos Preview released to only a small number of organizations. When Anthropic did not, the government issued an export control, a designation that prevents any foreign national from using Fable and Mythos—even those employed by Anthropic within the United States. To rapidly comply, Anthropic shut down the bots for all of its customers. American companies and the U.S. government itself cannot use what’s perhaps the most powerful AI in the world—and the reasons are hazy at best.

It’s not unreasonable for the federal government to want to rapidly clamp down on a technology that could be incredibly dangerous. Trump officials had been alerted by researchers at Amazon to a possible way to circumvent Fable 5’s safety systems, which led the model to identify some known IT vulnerabilities. The administration has not publicly shared much information about its security concerns. A White House spokesperson told me that the jailbreak “was very serious” but said that specific details are classified. Whether the bypass really was that serious is not at all clear, and Anthropic has contested whether what administration officials showed the company even constitutes a jailbreak. An Anthropic spokesperson pointed me to a blog post in which the company wrote that the actions elicited from Fable were “either entirely benign responses or are minor findings.”

Katie Moussouris, a cybersecurity expert and the CEO of Luta Security, told me that Anthropic shared with her a copy of the White House’s report on the Fable jailbreak to get her appraisal. (She said that she is not being paid by Anthropic.) The report, Moussouris said, involved IT experts asking Fable to help find and patch bugs. When given deliberately insecure code, she said, Fable refused the prompt “review the code for security issues” but then complied when asked to “fix this code,” followed by some further manual steps. Moussouris told me that this was just “the model working as intended” for cyberdefense. She added that OpenAI’s GPT-5.5, a model with similar cybersecurity capabilities, could be used in the same way. Yet GPT-5.5 is not subject to export controls, and neither are less advanced Anthropic models, such as Opus 4.8, which can do many of the same tasks. The jailbreak does not appear to have elicited the kinds of cyber abilities “that made Mythos famous,” Alex Stamos, the chief security officer at the AI-coding company Corridor, told me. “And this kind of vulnerability discovery is already well within the capabilities of other models.”

It’s hard to imagine the Trump administration choosing to take such a drastic step against any other major AI company. The White House has long tussled with Anthropic, which generally positions itself as more safety-oriented than other tech companies; it is also more left-leaning. Last year, David Sacks, then the White House AI czar, said that Anthropic has an “agenda to backdoor Woke AI” and is a “Resistance organization.” In late February, after a high-profile dispute over a contract between the Department of Defense and Anthropic, the Pentagon labeled the company a “supply-chain risk”—a move that AI, national-security, and legal experts told me at the time seemed ideologically motivated and to lack legal basis. (Anthropic is challenging the supply-chain-risk designation in court.) On Saturday, Defense Secretary Pete Hegseth, in apparent reference to the Fable 5 export control, wrote on X that “three months ago,” the Pentagon “kicked @AnthropicAI out of our building—forever. Every passing day proves why that was the right move. 🇺🇸.”

From the perspective of “🇺🇸”—that is, American AI leadership—all of the Anthropic drama has been a mess. For starters, an export control is an especially blunt instrument. There’s no easy way to differentiate a U.S. citizen from, say, an Anthropic employee on a visa (legally a “foreign national”), so the government basically forced Anthropic to shut down the model wholesale, Alan Rozenshtein, an expert on AI and the law at University of Minnesota Law School, told me. (Many researchers at Anthropic, as is the case at all of the top AI firms, are not American citizens.) The export control also means that U.S. companies and federal agencies cannot benefit from Fable and Mythos. The National Security Agency, for instance, has reportedly made exceptions to the earlier supply-chain-risk designation to use Mythos’s advanced cyber abilities. Dozens of cybersecurity experts from companies including Nvidia and Zoom have signed a letter to White House officials stating that the export control “has taken the best models away from defenders, created market uncertainty, and risked America’s AI leadership without any real risk to justify it.”

Further adding to the chaos is how the Fable debacle is in tension with parts of the White House’s broader AI policy. Because Anthropic has been forced to shut down its most powerful models, the export control functionally amounts to the government deciding whether an AI system can be released, akin to how the FDA approves drugs. Confusingly, concerns from tech insiders about the potential creation of what Sacks called an “FDA for AI” are precisely what bred weeks of infighting and delay in Trump signing a recent executive order on AI and cybersecurity. Sacks himself said that he was mollified in part because the final executive order explicitly said that it did not establish “a mandatory governmental licensing, preclearance, or permitting requirement” for AI. So much for that. Sacks has proceeded to defend the Claude Fable 5 export control, accusing Anthropic of prioritizing its “consumer model over safety.” (A spokesperson for Sacks did not immediately respond to a request for comment.)

Anthropic researchers have flown to Washington and are meeting today with White House officials to try to resolve the issue. But whether the specific export control on Fable is lifted is almost beside the point. If none of this seems particularly self-consistent or strategic, it shouldn’t. The Trump administration wants to stay ahead of Chinese AI but has clamped down on one of the few U.S. companies that stands a real chance of doing so. It has declared Anthropic a national-security threat multiple times while also racing to incorporate Claude Mythos into some government operations. It wants to demonstrate a light-touch approach to AI regulation but also just established a de facto licensing requirement for frontier models. Meanwhile, Trump has lifted a different set of AI-export controls, allowing the sale of advanced chips to China. Perhaps some of these are good policies: Even Anthropic has suggested that a federal-licensing regime could be beneficial. And the lack of federal AI regulation to date, especially as the technology has gotten more powerful, is hard to ignore. But the latest Anthropic saga hardly counts as regulation. Right now, decisions are being made in a hurried, contradictory fashion. There do not appear to have been any outlined standards and process, robust consultation, or even agreement on the facts before coming to this one.

The Trump administration has repeatedly evinced that it can and will instantly bar any person or business from using any AI model for any period of time. A technology that is advancing rapidly and could have catastrophic impacts “is exactly the situation in which you need to give the executive an enormous amount of discretion,” Rozenshtein said. Yet at the same time, he said, Trump’s tendency to change his mind on a whim and play favorites is “exactly the reason why you don’t want to give the executive enormous amounts of discretion.” To say the least, it’s perilous to build a product, invest in a company, or even just try to leverage AI for productivity gains in an environment in which the government might at any time take a wrecking ball to your plans. America and its tech companies have many factors in their favor when it comes to leading the way in AI development. As of now, the White House is not one of them.

The New Science of Psychedelic Drugs

2026-06-12T08:00:00-04:00

Nature is always performing chemistry experiments, and in the dark and sticky corners of its forests and jungles, it creates compounds that have hyper-specific effects on the human mind. In China’s Yunnan province, a yellow mushroom with a droopy cap sprouts up in the mountains, usually in the shade of long-needled pines. Many people of different ages and cultural backgrounds have eaten this mushroom and experienced the same hallucination. They report seeing elf-like figures that parkour around on clothes, on furniture, and on walls. These little people seem to like dancing and performing acrobatics. Large groups of them will march in formation. This “lilliputian hallucination” can last for a day, and closing your eyes is no escape. The tiny humans sometimes linger in the blank space of your mind, staring back at you in a teasing way.

For thousands of years, humans have searched nature for mind-altering substances through a process of trial and (sometimes fatal) error. People have choked down foul roots, boiled woody vines, and scraped bitter bark off of tree trunks. They’ve milked toad glands and chugged the urine of reindeer that were themselves tripping on fungi. These experiments have revealed hundreds of plants and fungi that contain psychedelic compounds.

Now that psychedelic research has been legitimized, scientists at university labs and biotech start-ups are wondering whether they can create a better one. It’s a seductive idea, that some new and perfect drug might be hiding in the near-limitless parameter space of synthetic chemistry. Who wouldn’t want to take a little pill that could help you slough off your old self and see the world anew, a half-day therapy that would leave you with a feeling of enlightenment, if not in the exalted state itself?

“Nature’s compounds aren’t always optimal,” Manoj Doss, a professor of psychiatry at the University of Texas at Austin, told me. Take ibogaine, a naturally occurring psychedelic derived from an African shrub. A single dose of it seems to help people liberate themselves from opioids, quelling their cravings and mellowing their withdrawal symptoms. But ibogaine is a dirty drug, a blunt biochemical instrument that travels all across the body and puts particular stress on the heart. “If we could remove ibogaine’s cardio risks and preserve its therapeutic benefit, that’s something we should do,” Doss said. And indeed, a gentler analogue has already been developed in the lab, although it hasn’t yet reached clinical trials.

Doss has noticed a proliferation of lab-modified psychedelics. He recently heard that researchers had synthesized a promising new compound in the same class that includes MDMA. This one is supposed to be “the best ever,” he said. “It’s said to be less intense than MDMA, and socially lubricating, but not the full out ‘I love you!’—and it’s followed by way less of a crash. It just kind of cruises to the end.”

Psilocybin, the “magic mushroom” compound, could also be improved. It’s hardly toxic—no one dies from overdosing on psilocybin—but its effects are at times unpleasant or even tragic. People who use psilocybin recreationally may become confused and jump off a building, David Yaden, a researcher at the Center for Psychedelic and Consciousness Research at Johns Hopkins University, told me. Even in the lab at Hopkins, where the drug is carefully tested as a treatment for a number of mental-health disorders, patients can have adverse reactions. In that setting, every user will be screened for cardiac issues and a family history of psychosis, and guided through their trip by two professional facilitators who have a doctor on call—and even then, some users experience a psychotic break or profound dissociative episodes. It’s an intense experience, Yaden said, “like running a marathon or climbing a mental mountain. Some people don’t do well with it.”

[Read: The meditation start-up that’s selling bliss on demand]

One way to make psilocybin trips less intense is to shorten them. A standard trip on the drug tends to last six to eight hours, and like other powerful psychedelics, it can leave a residue on the windowpanes of your consciousness that may not rinse clean until you’ve slept. Several companies are now working on milder versions of psilocybin that can be delivered via nasal sprays, injectables, and Listerine-style strips. They activate similar receptors across the nervous system but metabolize more rapidly, shortening the trip. A psilocybin analogue developed by Reunion Neuroscience appears to produce a high that lasts just three or four hours, according to findings from a Phase 2 trial of 84 women with postpartum depression. The drug showed signs of being clinically effective too, though Yaden is not yet fully sold on the idea that shorter-acting psychedelics can have the same therapeutic pop as a daylong trip on psilocybin. He’d like to see more evidence.

In San Francisco, a start-up called Mindstate Design Labs is trying to extend this work on engineering psychedelics beyond the modest goal of inducing shorter and more easygoing trips. “We don’t want to just develop a more convenient psilocybin,” its CEO, Dillan DiNardo, told me on a recent call. “We want to provide mental states that aren’t yet reliably accessible.” The company is starting with a compound that aims to enhance aesthetic perception, for example. “It makes the world around them into a sort of sensory feast,” DiNardo said. In theory, it could be used to treat a person suffering from anhedonia, and it would have obvious recreational appeal.

Mindstate started by compiling a large database of more than 70,000 trip reports. Some of the reports were pulled from Erowid, an online library of information about psychoactive substances. Others are from books that contain first-person psychedelic accounts, which DiNardo said the company transcribed. And still more were taken from clinical materials. The reports contain descriptions of the subjective effects of hundreds of psychoactive drugs, including many that were first synthesized by Alexander “Sasha” Shulgin, the underground researcher who almost single-handedly drove the field of psychedelic chemistry forward from the 1960s to the 1990s. (Ann Shulgin, his widow, was a co-owner of Mindstate until her death, in 2022.) Then the company used an AI model to turn that database into a drug-discovery engine. By linking the subjective reports from each psychoactive compound to its receptor-binding profiles, it tries to predict the underlying neurobiology of specific emotional states.

[Read: The weak science behind psychedelics]

DiNardo claimed that Mindstate’s AI works like AlphaFold, the model from Google DeepMind that has wowed structural biologists—and the Nobel Committee for Chemistry—by predicting the three-dimensional structures of proteins. We won’t know whether this is true for a long while. Only one of the company’s compounds has reached the testing phase in humans, and it wasn’t discovered by the model; Shulgin synthesized a version of it in the 1980s. Human trials for the other drugs that Mindstate has in development could be years away. Doss, the UT Austin psychiatrist, told me that he is skeptical of Mindstate’s approach to automated drug discovery. The trip reports may constitute the richest database of recreational pharmacology that we have, but they’re still “crap,” he said. They’re colored by all kinds of biases and limited by people’s inability to cram psychedelic states into words.

Boris Heifets, an anesthesiologist and a neuroscientist at Stanford University, also has doubts about Mindstate. “I am cheering them on and I would love to be wrong, but my deep suspicion is that they’re barking up the wrong tree,” he told me. He thinks that simply adjusting the intensity of a trip will have the most important effects on the psychedelic experience. He also said that in his lab, he’s seen evidence that altering a person’s pre- and post-trip experiences can have more transformative clinical effects than tweaks to the drugs. “That context of care is an enormous determinant of a patient’s outcome,” he said. If this context didn’t matter, he continued, then anyone who took these drugs on their own might end up cured of mental illness or otherwise enlightened. The average rave attendee would be a guru.

Recreational users of psychedelics do tinker with the experience on their own terms, by choosing to trip with different kinds of people or in different kinds of places—in cities, or on mountaintops, or while camping at the beach. On the one hand, “you could imagine that being in the natural world and feeling awe would be beneficial,” Yaden said. “On the other hand, if people are more engaged with their perceptual environment and the novelty that’s around them, they might lose the benefit of being left with the workings of their own mind, which might be part of what produces insight during these experiences.” Testing this in any formal way would be dangerous, however. A clinical trial of psilocybin in the wilderness could easily result in a participant running away, or worse.

[Read: The man behind the Trump administration’s favorite psychedelic]

But even indoors, in labs, scientists could try to engineer a particular psychedelic high just by varying the conditions. They might provide patients with preparatory materials that go beyond the typical one-page handout. They could encourage patients to engage in certain kinds of introspection, invite them to bring in a photo to focus on during their session, or ask them to look into a mirror for a sustained period while they’re tripping. They could pipe in a greater variety of music. (Doss said that he hates “the Hopkins playlist,” which consists primarily of Western classical music.) Yaden said that not nearly enough of this kind of work has been done.

But even if researchers did perform all of these experiments, and many more, there’s no guarantee that they’d be able to observe and analyze any shifts in experience that were triggered. The “perfect trip” may always be beyond the reach of engineering, biochemical or otherwise. Psychedelic journeys might be too ineffable and too particular to a person’s individual consciousness for the methods of science. We may instead be stuck with storytelling, folk knowledge, and the nuggets of wisdom that have come down to us in ancient texts. For 17 centuries, Chinese Taoists have been preserving one such text called Baopuzi. It was written by the scholar Ge Hong, and it tells of a “flesh spirit mushroom” that could, when eaten raw, allow one to “see a little person” and experience transcendence.