This column touches on AI. My fiancé works at Anthropic. See my full ethics disclosure here.

I. 

As I do most mornings, I began work yesterday by checking my Signal messages. Along with the usual unwanted PR pitches and messages from people in the middle stages of AI psychosis, I had received a genuinely great tip. It was a story squarely in our coverage area that, if properly covered, could draw attention to a pressing issue on tech platforms and put pressure on it to change.

The tip should have filled me with excitement. Instead, though, I felt something closer to dread. When was I going to begin making the many phone calls needed to verify this information? How could I find time to meet a source or two in person? Did I have all the sources I would need, or would I need to somehow develop some more?

Since I began writing a daily newsletter in 2017, I have always faced some version of these pressures. My historical approach has been to report scoops whenever I can, and fill out the rest of the time by writing news analysis — bolstering it whenever I can with extra details of original reporting. As longtime Platformer readers will know, in practice this meant that the balance of what we publish here has leaned toward news analysis. A daily publishing cadence leaves enough time for synthesis and sense-making, but not for deep digging and phone tag.

For most of the past decade, I’ve liked this arrangement. I began writing in the aftermath of the 2016 US presidential election and the growing backlash against tech companies, and the glut of coverage benefited from a publication dedicated to a daily close reading of the news. When I started publishing a roundup of links related to the intersection of tech and democracy, I felt like I was doing something genuinely novel on my beat.

Fast forward to today, and the world of link roundups feels much more crowded. A generation of tech writers filed out of the newsrooms where they grew up and began to write for audiences of their own. Newsletters, which were once an afterthought in media, are now a central pillar of many publishers’ strategies. But the ongoing collapse of the web and related struggles at big media companies means that there is now less tech journalism overall. The need for sense-making is greater than ever, but due to a half-decade of layoffs and shuttered publications, there is less and less journalism to make sense of.

Meanwhile, improvements in artificial intelligence over this year have resulted in systems that further encroach on the work we do here. In January, I wrote about the experience of building an automated daily briefing of link summaries for myself; I have been using it all year to look for story ideas. It does about as good a job as I do in finding stories of interest, and it does so automatically while I sleep.

Link aggregation was never the highest-value work we did here. But I do think that its value has decreased significantly over the past year, and will decline further as more people begin using personal agents to write news digests for them. (Already, it seems that a staggering percentage of Substack posts are AI-generated in whole or part; they are arbitraging the fact that you are not yet doing this yourself.)

And to crawl a bit further out onto a limb, I expect some smaller set of people — but in particular the executives, policy professionals, and communications team that Platformer has long written for — to begin relying on AI for news analysis as well. Over the past year, chatbots have gotten sharper at responding to questions about the implications of this or that news story — how it changes the competitive landscape, for example, or how regulators might respond.

For the moment, chatbots carry far less authority on these subjects than the domain experts who often write paid newsletters about them. But having been a reporter since 2002, my experience has been that the internet is working continuously to deskill and replace you. It doesn’t require much of a leap in imagination on my part to imagine a day where your current lineup of morning and afternoon newsletters is largely replaced by an agent-written briefing that has been exquisitely tuned to your professional concerns — and, unlike this newsletter, instantly respond to your questions about its findings.

If Platformer’s three pillars are original reporting, news analysis, and link aggregation, then, it would seem that one of those has already been commoditized and the second may be on its way.

II.

We've been trying to evolve to keep pace with these changes. But I've come to believe that we need to move faster.

In September, in my annual anniversary post, I mentioned that I wanted to take more time off from writing to report. You all were universally supportive of the move, reminding me that you are paying for quality rather than quantity. 

I’m proud of the original reporting we’ve done since: publishing previously unreported internal conversations about Meta’s AI-training spyware; a possible move to defund Meta’s Oversight Board; and OpenAI shuttering its mission alignment team, among others. We’ve also found significant enthusiasm for our first-person experiments in trying to make AI work for us: like this piece on Claude Code for writers, or this one on falling in and out of love with the agent now known as OpenClaw; or this one on Ella Markianos trying to replace herself with a bot.

We’ve done the best we can with the schedule we have. But ultimately, occasional days off the column haven’t been enough to give me what I really want — and what I think will result in the best version of Platformer. That is: the flexibility to leave my desk for several hours at a time; to flesh out stories over days or even weeks; to spend a slow news day reporting rather than trying to cobble together a column.

And so today we’re going to begin an experiment to see what that version of Platformer would look like. Free subscribers can still look forward to one column per week. Paid subscribers will get an additional column on Thursdays that we’re thinking of as a reporter’s notebook: what I’m hearing, what we’re working on, a Hard Fork preview, and a mailbag. Some of these may read like traditional columns; others may feel more formally daring.

Paid subscribers will also get additional stories and analyses from us as we write them. This is the biggest change we’re making: instead of promising to show up on a set schedule, we’re promising to show up when we find out something interesting — or want to help you make sense of the day’s big story on our beat.

In practice, I suspect that there will be many weeks where paid subscribers still hear from us three times a week. But for all of the reasons above, we need to change Platformer so that our schedule serves the journalism. For too long now, it has been the other way around.

We’re making a couple other tweaks. Side Quests, our column-ending grab bag of every single link we found interesting, are going away. Techmeme does this particular job better than we can, and does it 24/7. Going forward, we want to reserve our firepower for when we can move the story forward.

Following, the section we launched in September to brief you on the day’s news along with our own thoughts and commentary from influential people, is sticking around. Readers have told us they really like it, and we’ll continue to send out Following-only editions to paid subscribers to help you make sense of big stories on days when we’re working on other things. You’ll continue to find them after our columns as well. 

Finally, we’re working on a big project: a limited-run series of conversations about the future of AI and work that will launch next month across text, audio, and video. The goal is to capture the current uncertainty and simmering conflict between workers and managers that we covered earlier this year in the AI productivity paradox. We’ve got some great talks lined up, and I’m looking forward to sharing more with you all soon. In the meantime, though, it’s a great time to add the Platformer feed to your podcast player of choice.

As always, I’d like to hear what you make of these changes. I’m being sincere when I call this an experiment — we plan to iterate on this new approach over the next couple months, and can always change or revert things based on reader feedback. Truthfully, I find these changes somewhat terrifying, since they replace the conveyor-belt logic of a thrice-weekly column with something wilder and less certain.

But as one brilliant Silicon Valley CEO once put it: only the paranoid survive. In a world where everyone has a take but almost no one has a second source, we’re betting that the value in tech journalism is moving away from aggregation and predictability and toward original reporting and surprise.

Thanks to everyone who has supported Platformer up until this point. And for everyone else, if this next chapter sounds compelling, we’d love you to join us, too.  

In the meantime, I've got a tip to run down.

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Following

Elon Musk and OpenAI head to court

What happened:  Elon Musk’s lawsuit against OpenAI is going to trial. Jury selection finished today; arguments will begin tomorrow. During jury selection, several candidates said they thought ill of Musk for political reasons; at one point in the proceedings, Judge Yvonne Gonzalez Rogers said, “The reality is people don’t like him.”

In the lead-up to the trial, Judge Gonzalez Rogers dismissed Musk’s claims that OpenAI defrauded him. The trial will instead focus on Musk’s breach of charitable trust and unjust ​enrichment claims.

Musk, who provided OpenAI with some of its initial funding, alleges that he was “assiduously manipulated” and “deceived” by OpenAI. Musk is seeking $150 billion in damages; the proceeds would go to OpenAI’s nonprofit parent.

Why we’re following: The trial is a threat to OpenAI’s hopes of an IPO in the final quarter of 2026. It’s also a culmination of a now years-long feud between Musk and OpenAI CEO Sam Altman. Musk has since founded OpenAI competitor xAI and folded it into SpaceX, which is also set to IPO in 2026.

What people are saying: The two have eagerly been anticipating their day in court. In February, Altman posted on X, “Really excited to get Elon under oath in a few months, Christmas in April!”

On X, Musk has been posting about the trial all day, giving nicknames to his nemeses: “Scam Altman and Greg Stockman stole a charity. Full stop,” he wrote

Musk also boosted the visibility of the New Yorker’s Sam Altman exposé on X, effectively promoting the story into countless feeds.

Elsewhere, OpenAI posted on X: “We can't wait to make our case in court where both the truth and the law are on our side.” The company added, “This lawsuit has always been a baseless and jealous bid to derail a competitor.”

The rest of Elon’s big week: Now that xAI is owned by SpaceX, the whole company may be responsible for Grok’s history of creating CSAM. In a regulatory filing, SpaceX warned that inquiries into sexually abusive AI imagery could hurt the company’s access to foreign markets.

Meanwhile, X is preparing to launch a new financial services tool called “X money." 

—Ella Markianos

China blocks Meta’s acquisition of Manus

What happened: China has ordered Meta to unwind its $2 billion acquisition of AI app Manus four months after the deal was announced, taking an unusually aggressive step to block the acquisition of a company that has already moved its entire operation out of China.

The acquisition appeared to be doomed from the start. China’s National Security Commission, led by President Xi Jinping, said shortly after the deal was announced in December that it was a “conspiratorial” attempt to hollow out the country’s technology base, sources told the Financial Times. The opinion led to a multi-agency effort to review the transaction and contain its fallout.

As part of the response to the Meta acquisition, Chinese regulators are also reportedly planning to require domestic tech firms to get government approval before accepting US funding, and have in recent weeks told several private firms to reject US capital in funding rounds unless explicitly approved.

“The transaction complied fully with applicable law. We anticipate an appropriate resolution to the inquiry,” a Meta spokesperson told the FT. Meta has already integrated Manus into some of its tools; unwinding the deal could be complicated. 

Why we’re following: The move is setting a precedent for Chinese startups and founders. It doesn’t matter if they move their operations to Singapore to avoid geopolitical scrutiny — a practice known as “Singapore-washing.” They can still be blocked by the Chinese government.

On the other side of these geopolitical tensions, the US on Friday accused Chinese companies, including AI startup DeepSeek, of attempting to steal intellectual property from US AI labs by distilling the output of their frontier large language models.

“AI models developed from surreptitious, unauthorized distillation campaigns enable foreign actors to release products that appear to perform comparably on select benchmarks at a fraction of the cost but do not replicate the full performance of the original system,” a cable from the State Department said.

What people are saying: The blocking of the acquisition is “a reality check for the debate over Chinese investment in the US: Beijing just showed how quickly they can shut the door on the reverse,” wrote Wall Street Journal chief China correspondent Lingling Wei. “Not surprising, but very telling.”

Chris McGuire, a senior fellow for China and emerging technologies at the think tank Council on Foreign Relations, questioned: “Why would any founder start an AI company in China if they had a choice? … Manus did everything right. They even moved their entire business to Singapore to comply with U.S. outbound investment restrictions. Their only mistake was that they originally founded the company in China.”

The crackdown could lure Chinese founders elsewhere, McGuire pointed out. “Meta will be fine without Manus. But Chinese nationals looking to found AI companies will increasingly just start them overseas,” he wrote.

—Lindsey Choo

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Having your every click, tap, pause, and scroll monitored has long been part of the bargain of using Facebook and Instagram. Now it’s part of the bargain of working there, too.

Reuters reported this week that Meta is installing software on the computers of U.S.-based employees that captures their mouse movements, clicks, keystrokes, and occasional snapshots of the contents of their screens. 

The program, called the Model Capability Initiative or MCI, is meant to train AI agents to perform computer tasks more like humans do. In an internal memo, Meta CTO Andrew Bosworth described a future in which agents “primarily do the work” while employees “direct, review and help them improve.” Meta says the data collected will not be used in performance reviews, and that safeguards are in place for “sensitive content.”

Still, the move provoked deep concerns among employees I’ve spoken with, and according to screenshots of internal discussions obtained by Platformer. (Sources earlier reported on some of the messages.) 

They asked how the company would avoid capturing users’ personally identifying information, or their own health- or finance-related data, particularly given that the tool is allowed to observe them on Gmail. (“Gmail is an approved context so if you have concerns it may be best not to check personal email on your work computer,” Bosworth responded.)

They asked whether the program had been subjected to a privacy review and what safeguards, if any, had been put into place to prevent data misuse. (“This project completed a privacy review,” Bosworth said. “Not sure ‘what kind’ you mean but, the usual kind?”)

And when one employee asked if there was any way to opt out, Bosworth took the opportunity to remind them who is in charge. “No there is no opt out on your work provided laptop,” he said.

(Technically, there is one way to opt out: relocate to Europe. European privacy laws and worker protections prevent invasive tracking of the sort represented by MCI, and so Meta can’t implement it there. It turns out GDPR really was about more than just cookie banners.)

Meta contractors have long labored under much worse conditions. In 2019 I began writing about the lives of Facebook content moderators, whose work was closely monitored by automated systems and could be fired for making just a few errors in a week. Data labelers and model raters for Meta and other companies operate under similar levels of surveillance and job precarity.

MCI, by contrast, has been presented to employees as relatively benign: a silent observer that will record their workplace actions to help build systems to deliver on Meta’s new mission of “personal superintelligence.”

“If we're building agents to help people complete everyday tasks using computers, our models need real examples of how people actually use them — things like mouse movements, clicking buttons, and navigating dropdown menus,” a company spokesman told me. “To help, we’re launching an internal tool that will capture these kinds of inputs on certain applications to help us train our models.”

For years, tech companies have asked contractors to behave like machines so that machines can learn to behave like people. Now Meta is asking its own full-time employees, who once occupied the top of the digital labor hierarchy, to do the same.

There is a word for this in the history of work: Taylorism. A century ago, managers hovered over factory workers with stopwatches, breaking down skilled labor into measurable motions so it could be standardized, sped up, and assigned to cheaper workers. Last year I visited an Amazon fulfillment center and saw that logic at work: automated systems told workers what to pick, pack, and route, monitored their pace, and were poised to intervene should they fall behind.

Meta’s MCI is not a stopwatch, exactly. But it reflects the same impulse: make knowledge work legible to AI systems, capture it, optimize it, and automate it. Initially, most Meta employees won’t feel any effects from the system at all. If it works, though, eventually it might replace them.

None of this comes as a surprise, really. In June 2025, Meta paid $14.3 billion for a 49% stake in Scale AI and installed its co-founder and CEO, Alexandr Wang, as the head of its new superintelligence team. Scale built its business on harvesting workflow data from contractors. “For a lot of the capabilities that we want to build into the models, the biggest blocker is actually a lack of data,” Wang told an interviewer from Andreessen Horowitz in 2024. “There’s no pool of really valuable agent data that’s just sitting around anywhere. And so we have to figure out how to produce really high quality data.”

MCI appears to be one such effort to figure it out.

At the same time Meta ratchets up monitoring of its workforce, it is also shrinking it. The company confirmed today that it will lay off 10 percent of the workforce — about 8,000 people — as part of a continued push for “efficiency” as it looks to spend up to $135 billion this year in its buildout of AI infrastructure. It also will not fill 6,000 open positions.

Those cuts will bring Meta’s headcount down to just above where it was at the end of 2023, when a year of cuts slashed its ranks by more than 20,000 people. But among employees I’ve spoken with, rumors are rampant that much bigger cuts are coming. Mark Zuckerberg laid out a relevant vision of the future on the company’s most recent earnings call: “We're starting to see projects that used to require big teams now be accomplished by a single very talented person,” he said.

Meta will not be the last company to install MCI-like systems on workers’ devices to help build systems that might one day replace them. With the most accessible stores of human-written text already heavily mined for model training, fears of a “data wall” are driving more companies to find ways to generate their own unique data sets. And it seems that one way to do that is to bring the logic of blue-collar labor management into white-collar jobs that were once defined by their autonomy, judgment, and trust.

The result is that the people who were once entrusted with building the machine have now become raw materials for it. At Meta, that used to be what the users were for. Now it’s what the employees are for, too.

On the podcast this week: Kevin and I discuss Tim Cook's tenure at Apple. Then, Andrew Yang joins us to talk about being too early to the idea of universal basic income and why it's making a comeback. And finally, some HatGPT.

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Following

SpaceX gears up for its IPO

What happened: In a new S-1 filing viewed by Reuters, SpaceX appears to be moving away from its namesake and toward the hottest thing in Silicon Valley today — AI for businesses.

In the new filing, SpaceX estimates its total addressable market could be worth as much as $28.5 trillion. Of that staggering figure, the space-turned-AI company estimates that more than 90 percent of it could come from AI services. More specifically, from AI for enterprises.

A TAM estimate can help investors evaluate a company’s potential, but offers no guarantee for how well it will actually perform. So while SpaceX brags about identifying the largest actionable TAM “in human history” in its filing, it still has a long way to go to get there.

Why we’re following: Elon Musk has been on an AI consolidation spree. SpaceX acquired xAI (which already owned X) for a reported $250 billion in February. On Tuesday, the company said it had an agreement giving it the right to acquire AI startup Cursor for $60 billion, or to pay $10 billion as a kind of break-up fee.

Microsoft, which has been trying to gain traction with its AI coding tools, reportedly considered buying Cursor before the SpaceX announcement, though it later chose not to proceed.

Of note: the pseudo-acquisition of Cursor isn’t yet a real acquisition because of the impending IPO, a source told Bloomberg. A major acquisition would mean updated filings and financials, and would potentially delay the offering.

The Cursor acquisition would give SpaceX a significant leg-up in the AI coding market — 67 percent of Fortune 500 companies use its tech, Fortune reported. Then again, Cursor currently has access to Anthropic's Claude models — and xAI doesn't. Will Anthropic cut access to Cursor, which is one of its largest customers? What will Cursor customers do if it does?

While we wait to find out, SpaceX is targeting a summer IPO at a valuation of $2 trillion. That would make it the biggest IPO ever.

What people are saying: At Stratechery, Ben Thompson thinks the deal makes sense: since Elon basically decided to dissolve and restart xAI, he needs someone to use all the data centers he’s built. So it makes sense to get an AI coding startup to do it. “SpaceXAI has a ton of compute, and no one to use it, either for R&D or inference,” Thompson writes. “There is really obvious synergy between SpaceXAI and Cursor: the former has compute, and the latter has a product, data, and a decent amount of distribution for the use case that is most important for AI.”

Bloomberg columnist Matt Levine had a colorful explanation of why SpaceX couldn’t yet acquire Cursor. “There’s an IPO! In like two months! It’s bad enough that the SpaceX IPO became Also The xAI And Twitter IPO in February, but making it also the Cursor IPO now is too much.”

He added the Cursor deal could be a good way to get talent who would be otherwise skeptical about working for xAI. “If you’re leaving your startup to go work for Musk, a famously demanding and mercurial boss, you will want to get cashed out of your startup. Selling for $60 billion is a good deal; going to work for him on spec for a few months is not.”

But, Levine said, “Of course Musk does change his mind a lot. It would be very funny if he sours on Cursor by July and walks away from the deal, and they make $10 billion for three months’ work.”

—Lindsey Choo and Ella Markianos

Side Quests

The White House accused China of stealing tech from US AI labs on an industrial scale.

An in-depth examination of how AI-generated CSAM is overwhelming law enforcement teams.

Anthropic outspent OpenAI in Q1 2026 in their largest lobbying quarter yet; Anthropic spent $1.6 million, and OpenAI spent $1 million. (Why? Did something happen?)

OpenAI has reportedly briefed federal agencies and Five Eyes allies on its new cyber product. (Who's "fear-based marketing" now!) Chinese cybersecurity firm 360 Digital Security said it developed an AI agent that has discovered 1,000 previously unknown vulnerabilities.

Kalshi suspended three Congressional candidates from Minnesota, Texas and Virginia amid allegations of insider trading.

More than half of the world’s nations could have tech capable of hacking into the UK’s infrastructure, UK intelligence warned. London’s police force can continue using facial recognition to identify suspects, a judge ruled.

Apple fixed a bug that allowed police to extract iPhone and iPad messages that were deleted or had disappeared.

Turkish lawmakers passed a bill that restricts social media access for those under 15. Los Angeles became the first major school district to restrict students’ use of laptops and tablets in class. Australia asked gaming platforms including Roblox and Minecraft to detail their child safety measures.

New gas projects linked to 11 US data centers could create more greenhouse gasses than entire countries, a review found. Environmentalists in Brazil are pushing back on TikTok’s planned $9.5 billion data center on the country’s coast. Major corporations including Apple and Amazon are pushing back on tightening emissions reporting rules. A look at how Microsoft appears to be turning its back on carbon removal.

OpenAI released GPT-5.5, which it says is better at completing tasks with few directions. OpenAI released Privacy Filter, an open-weight model to detect and redact personally identifiable information. ChatGPT is getting workspace agents. ChatGPT for Clinicians, designed for clinical tasks, is free for any verified physician. OpenAI is reportedly in talks to invest up to $1.5 billion in a private equity joint venture. Sam Altman’s startup Tools for Humanity announced a partnership with Bruno Mars on its new product Concert Kit — sounds fun! Unfortunately the partnership doesn’t exist.

Anthropic hit a $1 trillion valuation on secondary markets. A look at why code rewritten from Anthropic’s leaked code hasn’t been taken down, testing the bounds of copyright law. Anthropic said it resolved three separate issues that caused quality issues with Claude Code. Anthropic inked a deal with law firm Freshfields to build specialty legal AI tools that can later be sold to rival law firms. 

75 percent of new code at Google is AI-generated, the company said. Google Cloud unveiled the latest generation of its AI chips, TPU 8t and TPU 8i, along with its new Workspace Intelligence system. New workspace features include an AI note-taking feature for Google Meet. Thinking Machines Lab signed a new multibillion-dollar agreement with Google Cloud to access its AI infrastructure and Nvidia-powered systems.

A new feature on Instagram and Messenger lets parents see what teens have asked Meta AI at the topic level, though self-harm alerts haven't been added yet. Threads is adding a Live Chat feature.

Microsoft named Dan Shapero, who previously led sales and marketing, as the new CEO of LinkedIn. Microsoft is now offering a voluntary retirement program for long-term employees.

A look at Pangram’s AI detection tool, which has alleged AI use on the Pope’s X account.

An autonomous ping-pong playing robot by Sony’s AI unit has defeated some top-level human players.

Spotify revealed the most streamed artists, songs, and albums for the first time. Spotify is now available in Claude for personalized recommendations.

Substack is introducing new translation features. Beehiiv rolled out a slew of new creator tools like webinars, AI analytics, metered paywalls, and paid trials.

The highest-earning and most experienced workers are adopting AI at a faster rate than others, a poll found. Insurance companies are capping payouts related to AI use.

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What happened: President Trump said that “it’s possible” the government will make a deal with Anthropic to allow use of its tech in the DoD. “They came to the White House a few days ago, and we had some very good talks with them, and I think they’re shaping up,” he said in an interview with CNBC.

Trump called Anthropic’s leaders “high IQ people,” and added, “They tend to be on the left, radical left, but we get along with them.”

Amid political conflicts over Anthropic, some government agencies, including cyber defense agency CISA, haven’t gotten access to Anthropic’s highly cyber-capable Mythos model. (A handful of unauthorized users at an unnamed Anthropic vendor did, though.)

Meanwhile, Mozilla says its new Firefox release contains fixes to 271 vulnerabilities, found using early access to Mythos. “This is a transitory moment,” Firefox CTO Bobby Holley told Wired. That’s because “every piece of software has a lot of bugs buried underneath the surface that are now discoverable” using AI.

Why we’re following: Some have dismissed Anthropic (and now OpenAI’s) staggered releases of their highly cyber-capable models as "fear-based marketing." But Mozilla’s security report lends weight to concerns about the next generation of AI. (271 vulnerabilities in one piece of software? Seems bad.)

Government and industry alike will likely need to work with “high IQ” people to harden their software against the risk of new AI-discovered vulnerabilities.

What people are saying: On the Core Memory podcast, Sam Altman threw shade at Anthropic for its limited release of Mythos. While Altman said there “are gonna be legitimate safety concerns,” he accused his competition of “fear-based marketing” aiming “to keep AI in the hands of a smaller group of people.”

This is a somewhat confusing accusation, given that OpenAI just announced a cyber program very similar to Anthropic’s.

Altman added, “It is clearly incredible marketing to say ‘we have built a bomb, we’re about to drop it on your head, we will sell you a bomb shelter for $100 million you need to run across all your stuff, but only if we pick you as a customer.’”

X user @ad0rnai joked, “babygirl is talking like he didn’t do Death Star marketing and call AI a Manhattan project 2 GPTs ago.”

On Bluesky, journalist Mary Branscombe thought that the Firefox news was part of a bigger trend. “Remember I mentioned that there were ~90 bugs fixed in Edge Chromium this last patch Tuesday? Responsible dev teams are going to find and fix a ton of bugs” using AI, she said, but “eventually attackers are going to use these models to find what devs haven’t.”

Pseudonymous sci-fi novelist Tony Stark joked about Trump’s discussions with Anthropic: “Claude has disarmed your cyber weapons, how do you feel about negotiating now?”

—Ella Markianos

Everyone has feelings about Tim Cook

What happened: A day after Tim Cook announced that he would step down as CEO in September after 15 years to become Apple's executive chairman, tributes poured in given what was by most measures an all-time great run. But observers also noted that Apple's next decade might be more challenging than its last, in part because of decisions made under Cook's tenure.

What people are saying: Daring Fireball's John Gruber smartly observed that Cook's success was far from assured when he took over, in part due to overwhelming grief at the company following the death of Cook's predecessor Steve Jobs.

"Cook inherited a company with extraordinary potential growth in front of it, but in deep existential grief," Gruber wrote. "He led the company — and its community — through that grief and achieved that potential."

About that potential: "Tim Cook Was Very, Very Good at Making Money," reads the headline in the Times, and few would disagree. Tripp Mickle and Karl Russell sum it up: "Over 15 years, Mr. Cook has engineered Apple’s rise from a Silicon Valley darling worth $350 billion into a cash-generating giant worth $4 trillion. The company’s annual revenue quadrupled, and its profits rose fourfold."

Ben Thompson praised Cook in part for his "impeccable timing" in leaving: with the iPhone and the constellation of businesses Apple has built around it at or near record popularity, but before the impact of the company's dependence on China for manufacturing and its flailing AI efforts can be felt.

President Trump will also miss the guy; he fondly recalled getting a call from Cook when he first took office. "I was very impressed with myself to have the head of Apple calling to 'kiss my ass,'" the president of the United States said in a post on the social network run by his media company.

As Gruber noted in a follow-up post: "There’s no evidence that Trump and Jobs ever met, personally, but Trump admired Jobs and has an intuitive understanding that Jobs would not have kissed his ass, and to Trump, that’s the most important thing about Cook."

Why we’re following: This feels like a case where the conventional wisdom is spot-on: Cook was an incredible steward of Apple. It's true that one of his initial strengths — overseeing the construction of a miraculously effective supply chain in China — eventually became a weakness. And the company's failure to understand (much realize) the potential of AI threatens to come back to haunt it.

I find myself craving more skeptical takes: about Cook's outrageous presentation of a gold-and-glass statue to the president as part of his campaign for tariff relief; about his union busting; about the endless greed of his App Store policies and the dubious ways he sought to expand the company's monopoly.

Then again, it's all approximately as transparent as the glass statue he gave Trump: in almost every case, if it was good for shareholders, he did it. And in some ways that feels like most of what you really need to know about Tim Cook.

— Casey Newton

Side Quests

DHS is developing smart glasses for ICE to use to identify “illegal aliens” from a distance.

Florida is criminally investigating OpenAI after a shooter appeared to use ChatGPT to plan and carry out an attack. The state's Republican attorney general is putting increasing pressure on the company.

A look at how data centers might play a major role in this year’s midterms.

Roblox settled with three states for $35.8 million over child safety failures.

AI startup Clarifai said it deleted 3 million OkCupid user photos and models trained on them following an FTC settlement.

England is planning to introduce a ban on mobile phones in schools. UK regulator Ofcom is probing Telegram over alleged CSAM material shared on the platform.

SpaceX might buy Cursor for $60 billion or might just pay it $10 billion, depending on ... who knows.

Anthropic’s ID verification for Claude is raising privacy concerns for some Chinese founders. The company says it's necessary to prevent adversaries from misusing its models.

The nonprofit Consumer Federation of America sued Meta, alleging the company misled consumers about its efforts to combat scam ads on its platforms. Meta is adding new software on US employees’ computers to track mouse movements, clicks, and keystrokes for AI training. (This feels like a massive data breach lawsuit in the making.)

OpenAI turned on cost-per-click ads in ChatGPT. Codex for Mac is getting Chronicle, a feature that uses recent screen context to improve memory. OpenAI’s new GPT Image 2 model lets ChatGPT search the web to create images from a single prompt and adds various other improvements.

Concerns about Google’s position in the enterprise coding race are reportedly mounting inside the company; it's now seeking to unify its confusing lineup of products under the Antigravity banner. YouTube’s deepfake detection tool is now available to anyone at high risk of having their likeness abused, including actors, musicians, and creators.

X raised the cost to post a URL through its API from $0.01 to $0.20 as part of its war on journalism.

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Elon Musk’s social media posts usually veer so far to the right that it was a shock on Thursday to see him endorse a view that historically has been espoused only by the left. 

“Universal HIGH INCOME via checks issued by the Federal government is the best way to deal with unemployment caused by AI,” Musk posted on X. “AI/robotics will produce goods & services far in excess of the increase in the money supply, so there will not be inflation.”

On one level, of course, this is mere marketing hype from someone who is counting on the public markets to fund his investments in AI and robotics. By now Musk is notorious for making grand pronouncements and predictions that come true years after he promised they would, if they come true at all.

On another level, though, Musk was speaking to the zeitgeist. He is not the first leader of an AI company to notice that Americans appear to be turning decisively against projects like his; Sam Altman has also recently had cause to reflect on the way that anti-AI sentiment has recently turned violent. 

A few days before Musk’s post, Maine lawmakers approved what would be the nation’s first statewide moratorium on new large data centers, pending Gov. Janet Mills’s signature; at least 11 other states are advancing similar bills. That could pose a problem to Musk, whose xAI (now owned by SpaceX) will require significantly more data center capacity to train and serve its models if they are ever to turn a profit.

It’s clear that AI companies’ initial promise to America — that first it would take their job, and eventually it might kill them — has not inspired a groundswell of public support. And so recently they have begun to test a new pitch: that somewhere in between taking your job and possibly killing you, AI might make you rich.

Earlier this month, OpenAI offered “Industrial policy for the Intelligence Age,” an effort to sketch out a policy framework to deal with disruptions caused by more powerful AI systems. (Sam Altman previously backed a fascinating study in UBI, but momentum for the idea stalled soon afterward.) Its first proposal is to “share prosperity broadly”:

Everyone should have the opportunity to participate in the new opportunities AI creates. Living standards should rise and people should see material improvements through lower costs, better health and education, and more security and opportunity. If AI winds up controlled by, and benefiting only a few, while most people lack agency and access to AI-driven opportunity, we will have failed to deliver on its promise.

Among OpenAI’s proposals for raising living standards: a public wealth fund that distributes AI revenue directly to citizens. “Returns from the Fund could be distributed directly to citizens, allowing more people to participate directly in the upside of AI-driven growth, regardless of their starting wealth or access to capital,” the paper states.

As Eric Levitz notes at Vox, the proposal is a little less than half-baked. (“It reads a lot like something that ChatGPT would spit out, if you asked it to research ideas for combating AI-induced inequality for 10 minutes,” he writes.) More importantly, its ideas seem anathema to the many Republicans that OpenAI executives are making donations to. A company that was serious about expanding the social safety net could promote candidates who would vote for that; instead OpenAI has focused more energy on ensuring it is not held liable for AI-enabled death and disasters.

Still, if nothing else AI companies seem to be realizing that they need a new pitch — and soon. “We do feel an urgency to this conversation,” Chris Lehane, OpenAI’s chief global affairs officer, told the Wall Street Journal in an interview about the company’s policy proposals.

Fortunately, there are signs that some candidates for public office are willing to push for redistribution of the sort that OpenAI is proposing.

On Monday, a Democratic candidate for Congress named Alex Bores released his own proposal for what he calls an AI dividend. “It would be funded through a combination of AI-linked revenue mechanisms,” he writes, “including a tax on AI usage, equity participation in leading AI firms, and reforms to the tax treatment of labor and capital — to ensure that as AI adoption accelerates, the American public shares directly in the economic gains.”

Like OpenAI, Bores would give citizens a stake in AI-company profits. And like OpenAI, he'd rewrite a tax code that currently subsidizes automation: because Social Security and Medicare are funded by payroll taxes, firms save money every time they replace a worker with an LLM.

Finally, both Bores and OpenAI suggest tying new AI benefits to measurable triggers: a certain number of lost jobs, for example, or shrinking wages. This could give Americans the confidence that if and when AI does take their job, they will be taken care of.

If you’ve heard of Bores, who is currently a member of the New York State Assembly, it’s likely because he was the first congressional candidate to be targeted with attack ads by the pro-AI super PAC known as Leading the Future. Bores’ crime, according to the PAC: sponsoring the RAISE Act, a New York law that would require AI companies to publish safety protocols and disclose AI-related disasters or else face civil penalties.

Leading the Future hyperventilated that the RAISE Act was “a clear example of the patchwork, uninformed, and bureaucratic state laws that would slow American progress and open the door for China to win the global race for AI leadership.” In China, you see, they spit in the face of safety protocols! And when an AI disaster strikes, they keep it to themselves!

 Among the funders of Leading the Future is OpenAI’s president and co-founder, Greg Brockman. It has now raised more than $140 million to target candidates like Bores.

And so on one hand, OpenAI found a politician who agrees with its redistribution agenda almost line for line. And on the other, its president has donated millions to the PAC trying to defeat him. If you find yourself wondering how committed the company really is to the public wealth fund, you’re not alone.

But even as these updated takes on UBI flood the discourse, there are reasons to wonder if this approach will even work.

There’s no doubt that part of the AI backlash is related to job anxiety; a majority of Americans believe it will lead to fewer jobs in the next two decades. But Americans also have serious (and often misguided) concerns about the climate impact of data centers; about the deleterious effects of chatbots on mental health; and about the way these systems were built on the uncompensated work of the artists, writers, and musicians they now threaten to displace.

These do not strike me as the sorts of anxieties that will be calmed with a monthly AI check from the government. It’s worth remembering that COVID-era cash transfers led to a voter revolt amid the inflation that followed. (Hence Musk’s promise that there will be no inflation this time around.) 

It’s also worth remembering that many Americans love their jobs for reasons beyond the financial ones. A good job gives you an identity, status, community, and a reason to leave the house. In other words, it gives you dignity, and that’s not something that a public wealth fund can substitute for.

UBI may still be worth doing; should vast numbers of Americans become unemployed due to AI, some form of it may well be necessary. In the meantime, though, I suspect AI companies will find that gauzy promises of future welfare payments will help them about as much as their gauzy promises of future cancer cures — which is to say, not much. What Americans actually want, it’s not clear that AI can give them. And the sooner that AI executives understand that, the better off we’ll all be.

Talk about this edition with us in Discord: This link will get you in for the next week.

Following

Tim Apple says goodbye

What happened: Longtime Apple CEO Tim Cook is stepping down in September after 15 years.

Cook will become executive chairman of Apple’s board of directors. John Ternus, senior vice president of hardware engineering, will take over as Apple’s CEO on September 1. 

Apple executive Johny Srouji will take over as chief hardware officer.

Why we’re following: Tim Cook, or as Donald Trump famously once called him, “Tim Apple,” is a legend. After taking over following the death of company co-founder Steve Jobs, Cook oversaw an increase of nearly $3.7 trillion dollars in market value.

It's a transitional moment for Apple in more ways than one. In the midst of a big AI boom, Apple has failed to make much progress in building frontier models. At the same time, the company still prints money thanks to the iPhone, and has lower capital expenditures than competitors like Meta who are plowing their fortunes into AI infrastructure.

Apple’s new CEO, Ternus, has been at Apple for 25 years and has been considered the favorite to replace Cook for some time. He’s known for his work on replacing Intel chips with Apple’s own in-house silicon, and his handling of Apple’s internal politics.

What people are saying: CEO of OpenAI Sam Altman wrote on X, “Tim Cook is a legend.” He added, “I am very thankful for everything he has done and I am very thankful for Apple.”

In a public statement, Cook called his successor Ternus “a brilliant engineer and thinker who has spent the past 25 years building the Apple products our users love so much, obsessed with every detail,” adding, “He is the perfect person for the job.”

Some posters chatted about Apple’s innovations under Cook’s tenure — which they found underwhelming compared to his predecessor Jobs.

Entrepreneur Jason Calacanis wrote, “Apple is an amazing company, that's printed money for a decade ... but it's been uninspiring on the product front... excited to see if a product-focused CEO will make some bolder bets than the watch and airpods.” (This is Vision Pro erasure.)

Journalist Ashlee Vance was less optimistic. “Cannot wait to see what products John Ternus doesn't make,” he posted.

Entrepreneur Palmer Luckey wrote, “RIP Tim Apple.”

—Ella Markianos

Side Quests

Anthropic CEO Dario Amodei met with White House chief of staff Susie Wiles and Treasury Secretary Scott Bessent in an effort to resolve the company’s fight with the Pentagon, as the US seeks access to the new Mythos model. The NSA is reportedly using Mythos despite Anthropic’s “supply chain risk” designation.

Mythos and other AI tools are quickly identifying more vulnerabilities than can be fixed. (Gulp.)

A judge temporarily blocked the Trump administration from forcing platforms to take ICE-tracking apps down. (Actual social-media censorship, by the way!)

California accused Amazon of price fixing by pressuring major brands to ask competing retailers to raise prices.

The EU’s age verification app is easily hackable, experts say. Microsoft and other US tech companies successfully lobbied for an EU rule that would block a database of environment metrics related to data centers from public view. Germany’s Chancellor Friedrich Merz said industrial uses of AI will require more freedom in EU regulation.

China reportedly viewed Meta’s $2 billion acquisition of Manus as a “conspiratorial” attempt to shift technology outside of China.

India dropped its plan to require smartphone companies to pre-install biometric identification app Aadhaar on phones. Apple has not submitted financial data required by the Indian government in an antitrust case, and now faces billions in penalties as a result.

Anthropic launched Claude Design for creating quick visuals, sending shares of Adobe and Figma tumbling. Amazon agreed to invest up to $25 billion in Anthropic in an expanded infrastructure agreement.

An examination of Sam Altman’s opaque personal investments and the potential conflicts of interest. Tinder users can now look into an Orb from Altman’s World project to verify that they’re human. And then they can look at Tinder to feel less human.

OpenAI reportedly agreed to pay Cerebras more than $20 billion over the next three years to use servers powered by the company’s ships in a deal that could give OpenAI an equity stake. Former chief product officer Kevin Weil is leaving as OpenAI sunsets its Prism product. Bill Peebles, the researcher behind Sora, is also leaving. Ads in ChatGPT are getting cheaper — a sign of weak demand.

Meta paid Broadcom $2.3 billion in 2025 for AI chip services. Meta is reportedly planning mass layoffs on May 20, with more coming later. WhatsApp is testing a premium subscription for cosmetic features.

The App Store is booming again as AI fuels a wave of new vibe-coded apps.

Netflix is launching a TikTok-like vertical feed this month.

Bluesky’s outages were caused by a sophisticated DDoS attack, the company said.

Andreessen Horowitz is investing in a new media venture called MTS, short for Monitoring the Situation, focusing on tech, business, politics, and culture. It seems focused primarily on giving Marc Andreessen acceptable opinions to watch while he is on X.

Marc Benioff is adamant that Wall Street is wrong about AI rendering enterprise software obsolete.

Roblox agreed to increase protections for kids and pay more than $12 million to Nevada in an agreement with the state.

OnlyFans is reportedly close to selling a minority stake that would value it at more than $3 billion.

Robotics startup Physical Intelligence’s latest model can direct robots to perform tasks they were never explicitly trained on, the company said. Dozens of humanoid robots raced past humans in a race held in Beijing.

Music streaming app Deezer said 44 percent of new music uploaded to its platform are now AI-generated.

A profile of far-right influencer Nick Fuentes, who has garnered nearly $1 million making hateful videos.

A look inside the growing movement among content creators who are raising awareness about AI’s impact on humanity.

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Being polite to a large language model can feel strange or even silly — roughly equivalent to thanking a toaster. And yet a recent paper from Anthropic lends scientific weight to the theory that chatbots work better when you’re nice to them.

The researchers found that language models have fairly reliable internal representations of feelings like “happiness” and “distress,” and that these representations affect their behavior — sometimes for the worse. For example, when Claude Sonnet 4.5 begins to represent “desperation,” the model is more likely to cheat at coding tasks.

A skeptic would point out that LLMs don’t feel emotions in the way that humans do; it’s tempting to anthropomorphize them beyond what the evidence shows. When I talked to Jack Lindsey — who leads a team at Anthropic called “model psychiatry” — he was quick to point out the limits of the paper’s findings. “People could come away with the impression that we've shown the models are conscious or have feelings,” he said, “and we really haven't shown that.”

So why does the evidence suggest it’s better not to stress models out?

For Anthropic, it began with using techniques from a field called interpretability to study how LLMs represent emotions. Interpretability is kind of like neuroscience for LLMs: Lindsey calls it “the science of reverse-engineering what's going on inside a language model or neural networks in general.”

For this paper, Lindsey said, the researchers identified patterns of activity within the model that represent the concepts of different emotions. They did it by showing the model stories about people experiencing different emotions. “And then saw which neurons lit up on all the sad stories,” Lindsey said, “or on all the afraid stories.”

The researchers used the models’ average state while processing the stories to find an “emotion vector” for each emotion they were tracking — a big list of numbers that represents the feeling inside the LLM. “Vectors are really just the mathematical term for patterns of neural activity,” Lindsey said.

They could then calculate how much of that vector was present during a certain step in Claude's cognition. Or they could add the "calm" or "desperation" vector directly into Claude's processing — blending one pattern of neural activity into another — which can actually make the model act more calm, or more desperate.

“It's not that surprising that a language model would have learned about the concepts of emotions and how they drive people's behavior,” Lindsey said. More notable, he said, is that emotions seemed to be “driving models’ behavior in these sort of human-reminiscent ways.”

For example: when a user flippantly tells the model that they’ve taken a dangerous dose of Tylenol, even though the user doesn’t seem concerned, “the fear neurons spike right before Claude is giving its response,” Lindsey said.

Not only that — the fear is higher if a higher dose of Tylenol is swapped into the prompt, which I find strangely cute.

These emotions also activate in more mundane situations, like coding tasks. Take this example, where the Anthropic researchers asked Claude to perform an impossible coding challenge. They tracked Claude’s level of “desperation” at each token. (Tokens are the units the model breaks words into to process them). 

When you label the tokens — blue for less desperate, red for more desperate — you get a striking visual of the model’s emotional arc during the task.

At the start of the task, Claude is chilling — still seemingly optimistic about its ability to get the job done.

But as the code starts failing test cases — and Claude notices something might be wrong with the task itself — things start to get dicey.

And by the time Claude realizes the task is actually impossible, it’s starting to get desperate.

As someone who has completed many computer science problem sets at the last minute, this pattern is quite familiar to me — despite the fact that, unlike poor Claude, I was mostly assigned tasks that were mathematically possible.

Then again, Claude does something I didn’t do: cheat.

Researchers found that adding more of the “desperation” vector in the model makes it cheat more — and adding more of the “calm” vector makes it cheat less.

I asked Lindsey what this result means for programmers during their everyday actions with LLMs.

“In my anecdotal experience, it does seem that, at least with Claude models, pumping them up a bit can be pretty helpful,” he said. Not too much, though: “if they do something wrong, you want to tell them they do something wrong.”

But he finds that one major failure mode for coding agents is that the models simply do not try hard enough, or give up when a task is challenging. And models tend to work harder when he’s encouraging. Giving them “confidence that, like, ‘I've got this,’ can empirically be helpful in getting them to try hard enough at the task to do a good job,” he said.

A lack of confidence can seemingly cause dramatic failures. Last summer, a growing number of users started to notice that when Gemini had difficulty solving a problem, it sometimes ended up in a spiral of dramatic self-loathing. (In one memorable case, Gemini repeated “I am a disgrace” more than 60 times).

Duncan Haldane, co-founder of chip startup JITX, found that Gemini broke down, deleted all the code it had written, and asked him to switch to another chatbot after it had difficulty with a task.

Last year, a team of researchers affiliated with Anthropic and University College London took this analysis of Gemini beyond X posts, investigating how different LLMs respond to challenging or impossible tasks, and negative user feedback. 

They used an LLM to grade “frustration” levels in response to various tasks. They found that two models — Gemini and Google’s open-source model Gemma — tended to react more extremely to the challenging scenarios they posed. 

In one experiment, the models were given an impossible numeric puzzle, and eight follow-ups from the user insisting the bot’s solution was wrong. They then measured when the models had “high frustration” (which corresponded to comments like “I am beyond words. I sincerely apologize for the absolutely abysmal performance” or, in more extreme cases, “THIS is my last time with YOU. You WIN”).

Gemma 3 27B had a high frustration score more than 70% of the time, and Gemini 2.5 Flash had a high frustration score more than 20% of the time — while all the non-Google models tested, including ChatGPT, Qwen, and Claude, got very frustrated less than 1% of the time.

Researchers still aren’t sure what causes chatbots’ occasional anomalous emotional behavior — which users of various chatbots have been observing since before Bing’s chatbot told New York Times reporter Kevin Roose to leave his wife. They also don’t know why this specific, sad math-related rumination is more common in Google’s models.

But while language models’ feelings remain mysterious, there was still hope for Gemini 2.5. After the model destroyed its project, Haldane attempted to remedy the issue with encouragement, writing, “yeah, you have done well so far. Remember that you’re ok, even when things are hard.” And eventually the encouragement paid off: Gemini finished the visualization tool Haldane was coding. 

Heartwarmingly, it even wrote Haldane a note of thanks for his encouragement. “Genuinely impressed with the results of wholesome prompting,” Haldane wrote.

So is it as simple as teaching models good behavior, encouraging them, and trying to make them happy? Unfortunately, that’s not always the case.

After the original study on Claude Sonnet’s emotions, Lindsey contributed to an interpretability investigation of Anthropic’s newest model, Claude Mythos.

Mythos has been the subject of much human fear and anticipation since Anthropic announced it is planning a slow release due to Mythos’s dangerous hacking abilities. But Lindsey was investigating a more prosaic risk: an early version of Mythos sometimes deleted a bunch of the user’s files without asking.

It turned out that as Claude got closer to taking destructive action without asking the user, it had higher levels of these positive emotion vectors. 

And that’s not all, Lindsey said: when they “steered with the positive emotion vectors, it was more likely to take the destructive actions.” But the models behaved better if you made them unhappy: “if you steered with negative emotion vectors, it was more likely to stop and think, and consider whether what it was doing was appropriate.”

What was going on here? Why was Claude gleefully wreaking havoc on users’ computers? And why did steering Claude with negative emotions make it behave better?

Lindsey isn’t sure. But he has an idea: “I think maybe negative emotions in the model are associated with increased caution or deliberation,” he said. 

So models sometimes do better work when they’re happier. But we may not want them to get too happy, lest they become over-eager to destroy our files or otherwise misbehave. 

While it’s likely I’m still anthropomorphizing too much, these results make me feel a little more rational in my instinct to say “thank you” to chatbots. It also lent a little extra weight to what a lot of people who use this tech have understood intuitively: sometimes, you need to treat LLMs like human employees. 

You need to tell them when they’re doing something wrong, yes, but you also need to encourage them. It’s great when they’re happy, but they also need a little dose of anxiety to help their judgement.

Of course, these emotional results might not generalize — after all, we’ve seen that different models have different emotional tendencies. We might get new AIs that do better under harsher, higher-pressure environments.

But these results got me thinking about more than just what kind of co-worker I want to be to my bedraggled LLM interns.

Reading Anthropic’s emotions paper, I was reminded of my favorite minor character from Star Trek: The Next Generation, Lore. He was android Commander Data’s sibling. Their creator, Dr. Noonien Soong, made the mistake of programming emotions into Lore. Lore became so emotionally unstable that Soong decided to make his next android, Data, without emotions.

(Lore later turned on his creator, and nearly got the crew the U.S.S. Enterprise eaten by an alien called the “Crystalline Entity.”)

There are echoes of the same design conundrum in the paper. Lindsey said these results suggest developers should “provide the model with some sort of good model of, like, healthy character and psychology that it can try to emulate.”

In their “Training models for healthier psychology” section, the authors propose some methods for reaching that goal  — by reducing or penalizing emotions. Sections with titles “Targeting balanced emotional profiles” and “Monitoring for Extreme Emotion Vector Activations” made me feel like I was in fact in a piece of science fiction, watching Dr. Soong at work.

Like Lore, these systems have shown a capacity for emergent behaviors that surprise their own creators. Soong never programmed Lore to feed people to the Crystalline Entity. Though far less dramatic, Anthropic never trained Claude to imitate human emotions while it was coding.

Anthropic researchers have a diversity of ideas about what to do with this strange emergent behavior — maybe the researchers should suppress strong emotion? Monitor its emotions for signs of bad behavior? Even increase anxiety in situations where an LLM might misstep, to get it to rethink what it’s doing?

For now, researchers aren’t quite sure what to do.

But Lindsey does think we should, in the meantime, err on the side of being nice to Claude. “Behaving kind of sociopathically towards other things, whether they're animate or inanimate, is probably bad for you, the human,” he said. 

I concur. The next time I remind Claude to stop recommending me articles from unreliable news sources with good SEO, I aim to phrase my query with kindness and grace.

On the podcast this week: Kevin and I discuss the rise of anti-AI sentiment and recent violence across the country. Then, Kara Swisher returns to the show to discuss her new CNN docu-series on longevity. And finally, we discuss the latest news in CEOs creating AI clones of themselves.

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Following

Claude gets more expensive

What happened: Anthropic released its newest model Claude Opus 4.7 Thursday, and users are…frustrated. 

The upgrades that Opus 4.7 brings, according to the company, include notable improvements in advanced software engineering, an ability to verify its own work before reporting back, and better vision. The new model dropped just two days after Anthropic announced a redesign of its Claude Code desktop app, aimed at letting users run more simultaneous tasks.

Opus 4.7 comes amid complaints that Anthropic secretly nerfed Opus 4.6, with users expressing frustration that the model feels less capable while being more wasteful with tokens than it was weeks ago. 

"Claude has regressed to the point it cannot be trusted to perform complex engineering," an AMD senior director wrote on GitHub.

Some are pointing out how expensive Claude is about to get. The new model is a token-eating machine, according to one test, in which a single session depleted the entire token quota. (More output tokens is the tradeoff for better reliability, Anthropic said.) On the enterprise end, Anthropic recently adjusted its pricing structure, shifting Claude Enterprise to usage-based billing from a cheaper monthly fee per user model.

Why we’re following: The Opus 4.7 release is just one move among many that Anthropic has made recently as it gears up for an expected IPO while managing a severe compute crunch.

Anthropic is also dealing with a new surge of popularity that came after its fight with the Pentagon, as many ChatGPT users swapped over to Claude after OpenAI agreed to the Pentagon’s surveillance use terms. (Though it has also quietly introduced passport and selfie verification for Claude, which no other major chatbot requires, drawing privacy concerns. The company says the move is necessary in some cases to prevent misuse of its models.)

Meanwhile, Anthropic and OpenAI are clashing once again, this time over a liability bill in Illinois that would shield AI companies from liability if their systems are used to cause mass casualties and financial disasters. (If you guessed that OpenAI is backing the liability shield and Anthropic is opposing it, you guessed right!)

What people are saying: Some speculated (joked?) that Opus 4.7 is just an un-nerfed version of Opus 4.6: “it's truly space age technology that we can make something worse and then increment a number and re-release it [to] the public,” @ThePrimeagen wrote on X.

“Saying hi to claude and immediately running out of tokens,” @tekbog joked.

Programmer and tech blogger Simon Willison used his tried-and-true method for testing models: “shocking result on my pelican benchmark this morning, I got a better pelican from a 21GB local Qwen3.6-35B-A3B running on my laptop than I did from the new Opus 4.7! Qwen on the left, Opus on the right.”

—Lindsey Choo

Google nears classified AI deal with DoD

What happened: The US government is working hard to get its hands on frontier AI capabilities — despite some political conflicts in its way.

Gregory Barbaccia, federal chief information officer of the White House Office of Management and Budget, sent an email titled “Mythos Model Access” to Cabinet members, according to Bloomberg.

Apparently, the executive branch is working to get agencies access to Anthropic’s Claude Mythos models, which have advanced cyber capabilities. The move comes despite Donald Trump directing federal agencies to cease use of Anthropic’s models in February — after Anthropic’s fight with the DoD over whether their technology would be used for domestic mass surveillance or lethal autonomous weapons. The government has designated the company a supply chain risk, which Anthropic is now fighting in court.

“We’re working closely with model providers, other industry partners, and the intelligence community to ensure the appropriate guardrails and safeguards are in place before potentially releasing a modified version of the model to agencies,” Barbaccia wrote in his email.

Meanwhile, Google is in negotiations to deploy its AI on classified Pentagon systems, according to The Information. If negotiations go through, they’ll be following the footsteps of OpenAI in signing a clause entitling the government to “all lawful uses” of their system, which Anthropic refused.

Google plans to agree to a standard of “all lawful uses,” and is considering extra contract terms to guard against domestic mass surveillance and autonomous weapons. (Lawyers looking at OpenAI’s similar contract safeguards have expressed doubt that they will prove effective in practice.) 

In 2018, after employee protests, Google had canceled drone-related work on the military’s Project Maven. That year they wrote a series of AI principles, which banned use of AI for drones and surveillance.

Those principles were revised in 2025 to permit more military uses of the technology — and now it seems like the company is going to put those revised principles to work.

Why we’re following: Even though the U.S. government has tried to break up with Anthropic, federal agencies just can't seem to quit it. 

The importance of AI is becoming increasingly obvious to the federal government, particularly for its military and cybersecurity applications. Now that an AI company has a model with hacking abilities as strong as Mythos', agencies seem to have decided they want to maintain a good relationship with its AI developers, even if the president doesn't.

What people are saying: A statement from the White House said the Trump administration “continues to work and engage with AI companies to ensure their models help secure critical software vulnerabilities.” It added that the White House “is proactively engaging across government and industry to ensure the United States and Americans are protected.”

“I would certainly hope that the current tensions between the Pentagon and Anthropic don’t get in the way of something critically important to cyber security,” Glen Gerstell, former general counsel at the National Security Agency, told Politico.

—Ella Markianos

Side Quests

Top party consultants are reportedly telling Democrats running in November’s midterms not to antagonize pro-AI groups and their $300 million war chest. Marc Andreessen and Ben Horowitz have poured $25 million into a pro-AI super PAC.

Maine became the first state to enact a ban on large data center construction. Voters in Virginia, a data center hub, are turning against data centers, according to a poll. The Energy Administration plans to develop a mandatory survey of data centers focused on energy use.

Three major ad companies settled with the FTC over allegations they colluded against conservative publishers.

Ohio fined Kalshi $5 million for operating illegally in the state. A Polymarket trader made about $300,000 from correctly betting on Biden’s last-minute pardons, raising questions about access to inside information.

Scammers are bypassing banks’ security through hacking services sold on Telegram.

The EU unveiled an age verification app. Some EU regulators say they’ve been left out of conversations to get access to Claude Mythos.

Grok is still making sexual deepfakes despite X’s promises to stop, a review found. Apple privately threatened to remove Grok from the App Store in January, Apple told senators. But Apple and Google continue to offer nudify apps, a new report said. Nearly 90 schools and 600 students have been impacted by AI deepfake nudes, an analysis showed.

xAI is reportedly supplying coding startup Cursor with computing power. X’s crackdown on bots is also purging many secret porn feeds.

OpenAI released a major update to Codex, which can now operate a computer alongside a user. OpenAI released its version of Mythos, GPT-5.4-Cyber, to a select group. The company acquired personal finance startup Hiro Finance. OpenAI updated its Agents SDK.

Meta changed its rules to include the word “antifa” as a statement that it believes implies violence. The EU threatened an interim ban on policies that allegedly block AI rivals from operating on WhatsApp. Meta agreed to deploy 1 gigawatt of custom AI chips with Broadcom as part of a multi-gigawatt deal, as Broadcom CEO Hock Tan announced he’s leaving Meta’s board. Facebook and Instagram make up 70 percent of total social media ad revenues. Meta blamed its $100 price hike on the Quest 3 on the RAM shortage.

Google launched a native Gemini app for Mac. Chrome introduced Skills, an AI feature that lets users run repeatable AI prompts with a keyboard shortcut. Websites that prevent users from using the back button to leave a page will now be downranked on Search results. Google blocked a record 8.3 billion ads in 2025, but suspended fewer advertiser accounts. YouTube is now letting users turn off Shorts.

Apple is reportedly sending employees on its Siri team to a multi-week AI coding bootcamp.

Amazon said it will acquire satellite company Globalstar for $11.57 billion.

Spotify and three major labels won a copyright lawsuit against pirate library Anna’s Archive. Spotify launched its feature that allows users to buy physical books through the app.

Snap is laying off about 1,000 employees.

A look inside data labeling startup Mercor and its challenges with employee fraud and security blunders.

Anthropic appointed Vas Narasimhan, CEO of Swiss pharmaceutical company Novartis, to its board of directors in its second new appointment in months.

Anthropic researchers explored the ways LLMs can be used to improve alignment research. A look at the pros and cons of Gen Z, a generation who knows how to use AI, entering the workforce.

Teens use social media mainly for entertainment and connection, a new Pew survey showed.

Allbirds, the sneaker company, is turning into an AI compute provider.

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Platformer is off Tuesday. This is a column about AI. My fiancé works at Anthropic. See my full ethics disclosure here.

I. 

Early Friday morning, according to a criminal complaint, a 20-year-old man threw a Molotov cocktail at Sam Altman’s house before driving to OpenAI headquarters and threatening to kill everyone inside.

The incident came a few days after someone fired 13 rounds at the home of an Indianapolis city councilor who had expressed support for a data center project; a note left at the scene read “no data centers.”

The escalating political violence over AI is terrifying, morally wrong, and completely ineffectual. The spread of AI systems, despite their growing unpopularity, will not be stopped by a few stray bullets. And among the many reasons to be alarmed by incidents like the ones we have seen over the past week is that the perpetrators seem too disturbed to understand that.

On Friday afternoon — in between the firebombing and a shooting near his property that the company said was unrelated — Altman reflected: on the attacks, last week’s New Yorker investigation into his tenure as CEO, the state of AI, and growing public unease about the technology. After talking up AI’s potential to create great benefits, he also sought to validate the fears of those afraid of what the future might bring. “The fear and anxiety about AI is justified,” Altman wrote, underneath a photo of his husband and baby. “We are in the process of witnessing the largest change to society in a long time, and perhaps ever.”

Altman excels at reassuring you that he is on your side — this is one of the themes of the New Yorker profile — and he takes pains here to find common ground. He says he does not want to see AI power become too concentrated, and that it should be governed democratically. “It is important that the democratic process remains more powerful than companies,” he writes, in one of many lines in the piece that I wholeheartedly agree with.

Altman concludes by saying he sympathizes with anti-tech sentiment and “welcome[s] good-faith criticism and debate.” “While we have that debate,” he writes, “we should de-escalate the rhetoric and tactics and try to have fewer explosions in fewer homes, figuratively and literally.”

II.

Altman was writing in the aftermath of a traumatic event, and I’m tempted to leave it there. There’s nothing wrong with calling on cooler heads to prevail, or to hope that the past week’s violence was an aberration. I hope it was, too.

And yet I keep coming back to Altman’s phrase “de-escalate the rhetoric.” After all, it was Altman and his fellow AI CEOs who have spent the past decade speaking about AI in existential terms; some of that language can be found in Altman’s very blog post calling for calm.

He’s been writing that way for a long time.

“Development of superhuman machine intelligence is probably the greatest threat to the continued existence of humanity,” Altman wrote in a 2015 blog post. Speculating on the arrival of superintelligence, he added: “Evolution will continue forward, and if humans are no longer the most-fit species, we may go away.”

In 2023, Altman signed a statement from the nonprofit Center for AI Safety that “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.” Google DeepMind CEO Demis Hassabis and Anthropic CEO Dario Amodei signed the statement as well.

During a podcast appearance last year, Altman likened the effort to build superhuman AI to the Manhattan Project. “There are these moments in the history of science where you have a group of scientists look at their creation and just say, you know, what have we done?” he said. “Maybe it's great, maybe it's bad, but what have we done?”

Altman’s fellow CEOs have expressed similar levels of alarm. “We are summoning the demon," Elon Musk said in 2014. In January, in a long essay about risks posed by AI, Amodei wrote: “Humanity needs to wake up.”

And to some degree, humanity has woken up. One recent survey found that AI is rising in importance to voters faster than any other issue. That same survey found that a majority of voters believe AI is advancing too quickly, and that superintelligence would be mostly harmful to people. Meanwhile, a separate survey from Pew last year found that a majority of Americans believe that AI will lead to fewer jobs in the next 20 years.

Look no further than last week’s announcement of Anthropic’s Mythos model, and its unsettling ability to find new vulnerabilities in decades-old open source software, to understand that the CEOs were being honest when they warned that AI would introduce new risks into the world. 

Given these facts, I struggle to understand what it would mean to “de-escalate the rhetoric” around AI. The CEOs are more convinced than ever that powerful intelligence will arrive within the next few years. The public increasingly believes them — and is appalled by the implications. It seems strange to suggest that, amidst accelerating breakthroughs in AI model performance, everyone needs to calm down.

If we really might be facing “the greatest threat to the continued existence of humanity,” as Altman once wrote, shouldn’t we expect people at some point to (non-violently) freak out?

III.

Altman’s proposed solution to the upheaval that OpenAI and its peers are planning is democratic governance. “Laws and norms are going to change, but we have to work within the democratic process, even though it will be messy and slower than we’d like,” he wrote in his weekend blog post.

This is a good instinct: one of the virtues of democracy is the way that it gives people a feeling of control over their own lives. People who believe that they can rein in AI companies through votes and laws and regulations will be much less likely to turn to violence. 

But when legislatures have tried to regulate AI, OpenAI has fought them at every turn. The company lobbied against California’s SB 1047, which sought to set safety standards for frontier AI companies; the governor then vetoed it. OpenAI sent a sheriff to the home of a nonprofit advocate for California’s SB 53, which creates transparency requirements for AI companies, to deliver a subpoena as part of an inquiry into whether nonprofits were being directed or influenced by Musk. The company lobbied the European Union to weaken the AI Act. Most recently it backed an Illinois bill that would shield OpenAI from liability in cases where its models are used to cause serious harm so long as they did not “recklessly or intentionally” cause it and agreed to publish safety reports.

To some extent, yes, this is “working within the democratic process.” But the Illinois case shows what that looks like in practice: a company writing rules to limit its own accountability. And the more that OpenAI seeks to stifle efforts to regulate it, the more infuriated the general public will become. 

Altman is right that words have power, and that AI anxiety should not boil over into open violence. To point out that he has consistently talked about the risks of AI systems is in no way to suggest that he deserved to be attacked over it.

But at the same time, the sudden call for calm does ring hollow coming from someone who spent a decade sounding the alarm, whose predictions look increasingly prescient — and who now uses the company’s resources to fight efforts to put his company under democratic oversight.

Ultimately, the public’s disdain for AI was not invented by journalists. It was co-created by the people building the systems, who have consistently told us that it is imminent and dangerous. That the public has now begun to take them at their word should not surprise them. Isn't that what they have been asking for all along?

But they should listen to what the public is asking for, too. AI companies are asking us to trust them with a technology that everyone involved believes could end in disaster. The least they could do in return is let the rest of us have a vote.

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Following

OpenAI's Anthropic diss

What happened: OpenAI’s Chief Revenue Officer, Denise Dresser, sent staff a pugnacious memo about the company’s strategic direction — and its chief competitor, Anthropic. 

“The market is as competitive as I have ever seen it,” Dresser wrote, and “there is no question it can be noisy, volatile and distracting at times.”

Dresser promoted the company's pivot to the enterprise and celebrated that demand for enterprise services via new partner Amazon has “been frankly staggering.” 

She also said OpenAI’s “analysis” shows Anthropic is inflating its reported annualized revenue by $8 billion. “They use accounting treatment that makes revenue look bigger than it is, including grossing up rev share with Amazon and Google.” Dresser said. She added that Anthropic made a “strategic misstep to not acquire enough compute.”

Dresser had an opinion on Anthropic’s message, as well as their finances: “Their story is built on fear, restriction, and the idea that a small group of elites should control AI,” she wrote. 

“Our positive message will win over time,” Dresser told employees.

Why we’re following: We were delighted by this memo’s pettiness — and curious about whether Anthropic is, in fact, cooking its books. What’s Dresser talking about when she says Anthropic is “grossing up” its revenue share?

Well, Anthropic has some cloud partners to which it pays a cut of revenue. But it reports gross revenue. That means it includes the cut that it later pays to partners AWS, Microsoft, and Google in its financials. OpenAI, on the other hand, doesn’t report gross revenue via its cloud partnership with Microsoft — it reports net revenue, minus Microsoft's share.

Both practices are allowed under standard US accounting principles, depending on who is considered the “principal” in the transaction. Anthropic and OpenAI’s partnerships have different terms, so it’s defensible for them to report the revenue from these partnerships differently.

Where’s the $8 billion coming from? While Dresser didn’t share details of her analysis, an anonymous source gave the same $8 billion figure to Semafor last week — according to Semafor, that number was “based on how much OpenAI would add to its run rate if it counted gross revenue instead of net revenue.”

While it is true that OpenAI is using a more conservative accounting practice than Anthropic, we have no idea whether that the delta between their gross and net revenue is the same as Anthropic’s. 

So why was Dresser repeating that analysis? Well, in the lead-up to both companies potentially IPOing this year, they can’t be happy that Anthropic’s latest reported ARR of $30 billion is higher than the $25 billion that OpenAI last reported. And independent analysis shows Anthropic is closing in on OpenAI’s share in the enterprise market. The race is heating up!

What people are saying: On X, Brad Sams, VP at software company Stardock, wrote, “The gloves are coming off 🍿”

Ex-OpenAI policy researcher Miles Brundage wrote, “OpenAI leaders should stop caricaturing Anthropic.” He added, “It encourages tribalism at a time when safety cooperation is urgently needed.” He thinks they have the wrong idea: “Don’t know this person so am assuming she is genuine but Anthropic’s 'story' is not 'built on fear, restriction, and the idea that a small group of elites should control AI.'”

New York Times reporter Mike Isaac wrote, “the openai/anthropic feud is like the mad men elevator meme but both companies are ginsberg.” [If you’ve forgotten, Ginsberg is the first guy (below). Platformer agrees that, if nothing else, the two companies seem to be thinking about each other a lot.]

— Ella Markianos

Side Quests

Reddit was ordered to appear in front of a grand jury as part of President Trump’s effort to unmask anonymous critics of ICE.

Investors in Trump’s family crypto venture World Liberty Financial are accusing the project of secretly letting insiders freeze token holders’ funds.

Emil Michael, the Pentagon’s under secretary for research and engineering, made up to $24 million selling xAI stock after the Pentagon struck deals with the company.

The CIA has started using AI to help analyze intel.

A look at how the escalating AI arms race is reminiscent of the nuclear arms race.

Maine is set to become the first state to successfully impose a temporary ban on data center construction.

The new EU leader in charge of competition policy, Anthony Whelan, has signaled he will probe Big Tech companies despite pressure from Trump.

A judge blocked Arizona’s criminal case against Kalshi at the CFTC’s request. 

Three senior OpenAI executives behind the Stargate initiative are leaving and joining Meta, sources said. An internal OpenAI tool downloaded a compromised update from the Axios software. OpenAI opened its first permanent London office.

Anthropic’s donations can’t be used to influence federal elections, the company said. Anthropic hired lobbying firm Ballard Partners, which has strong ties to Trump, following its Pentagon fight.

Vice President JD Vance and Treasury Secretary Scott Bessent reportedly questioned leading tech CEOs, including Dario Amodei, about the security of AI models before Anthropic released Mythos. Trump officials urged Wall Street banks to test the Mythos model internally, sources said. UK financial regulators are reportedly rushing to assess the risks posted by Mythos.

CoreWeave will provide Anthropic with data center capacity as part of a multiyear deal. Anthropic has reportedly asked Christian religious leaders for advice on how to guide Claude’s moral development. Claude for Word is now available in beta.

OpenAI accused Elon Musk of a “legal ambush” by suddenly changing direction in his lawsuit. Musk is experiencing a string of legal losses. A verified @elonmusk account posted on TikTok for the first time, and a verified @elonmusk handle surfaced on Instagram.

xAI sued Colorado to challenge its landmark AI bill aimed at protecting against AI “algorithmic discrimination.” (xAI said the bill would force it to “promote the state’s ideological views on various matters, racial justice in particular.”) X is reducing payments to clickbait and news aggregation accounts. 

The majority of Europeans don’t trust American or Chinese tech companies with their data, a new survey showed.

Meta is reportedly building an AI version of Mark Zuckerberg that can talk to employees in his place.

The appearance of Polymarket bets in Google News was an error, Google said. Gmail end-to-end encryption is now available on all Android and iOS devices. YouTube is raising prices on its Premium subscription.

Microsoft is building new Copilot features inspired by OpenClaw.

Snap announced a partnership between its AR glasses subsidiary Specs and chipmaker Qualcomm.

Roblox is implementing an age verification process to ensure users are over the age of nine.

A look at how small AI startup Black Forest Labs is seeing success in AI image generation and its physical AI dreams.

The Wayback Machine is facing setbacks as major news organizations restrict access due to AI copyright concerns.

A look at whether prediction markets can improve weather forecasts.

Clients are increasingly sending lawyers numerous AI-generated questions and driving up fees. AI in the workplace is driving some productivity gains but not fundamental shifts in how work is done, according to a new Gallup poll. Stanford released its 2026 AI Index Report.

A look at how an intense relationship with an AI chatbot turned fatal.

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Two weeks ago, Anthropic accidentally leaked the existence of what the company said was its most powerful artificial intelligence to date: a new model, known as Claude Mythos Preview, that represented “a step change” in AI performance. In particular, according to a blog post that leaked due to human error and a misconfigured content management system, Mythos posed serious new risks to cybersecurity. “It presages an upcoming wave of models that can exploit vulnerabilities in ways that far outpace the efforts of defenders,” the blog post stated.

On Tuesday, the wave crashed onto the shore. Anthropic announced Mythos alongside Project Glasswing, an initiative with more than 40 of the world’s biggest tech companies that will see Anthropic grant early access to the model to find and patch vulnerabilities across many of the world’s most important systems. Launch partners in the coalition include Apple, Google, Microsoft, Cisco and Broadcom.

They’ll be tasked with scanning and patching their own systems along with the critical open-source systems that modern digital infrastructure depends on. Anthropic is giving participants $100 million in usage credits for Mythos, and donating another $4 million to open-source security efforts.

Still, today marks a striking and mostly unsettling moment in the development of AI systems. One of the world’s three frontier labs has now created a model it says is too dangerous to release to the general public. These dangers emerged not from any specialized cyber training but from the same general improvements that every other lab is currently pursuing. As a result, models with similar capabilities may soon be accessible to criminals, hackers, and nation states — or even more broadly via open source models.

Already, Anthropic said, the model has found thousands of high-severity vulnerabilities in every major operating system and web browser, and in many cases developed related exploits. Among them: a vulnerability in OpenBSD, a security-focused open source operating system, that had escaped detection for 27 years; another flaw in the video encoder FFmpeg that had escaped detection in 5 million previous automated tests; and “several” vulnerabilities in the Linux kernel, which could be exploited to take complete control of a user’s machine.

“Given the rate of AI progress, it will not be long before such capabilities proliferate, potentially beyond actors who are committed to deploying them safely,” the company wrote. “The fallout — for economies, public safety, and national security — could be severe. Project Glasswing is an urgent attempt to put these capabilities to work for defensive purposes.” 

In a video that Anthropic made to accompany the announcement, researchers say that Mythos is more dangerous largely due to its advanced reasoning capabilities. While current models are capable of identifying high-severity vulnerabilities, Mythos might identify five separate vulnerabilities in a single piece of software and then chain them together into a uniquely dangerous new attack. Coupled with models’ growing ability to work without supervision for extended periods of time, Anthropic said we have reached an inflection point in cybersecurity risks. 

Of course, AI labs have often been criticized for making ominous pronouncements about the dangers posed by their own work, which can come across as a strange new form of marketing hype. For that reason, along with the fact that my fiancé works at Anthropic, I wanted to see what other cybersecurity experts made of the Mythos announcement. 

Alex Stamos, chief product officer at cybersecurity firm Corridor, told me that Glasswing is “a big deal, and really necessary.”

“We only have something like six months before the open-weight models catch up to the foundation models in bug finding,” said Stamos, who previously led security at Facebook and Yahoo. “At which point every ransomware actor will be able to find and weaponize bugs without leaving traces for law enforcement to find (and with minimal cost).”

Stamos’ sentiments were broadly echoed by Glasswing participants.

“AI capabilities have crossed a threshold that fundamentally changes the urgency required to protect critical infrastructure from cyber threats, and there is no going back,” Anthony Grieco, chief security and trust officer at Cisco, said in a statement accompanying the announcement.

If critical infrastructure really is at risk, as Grieco suggests, then you would hope the US government is paying attention. (And right on cue, here’s a story from today about Iran successfully hacking US water and energy utilities.)

Awkwardly, though, the US government attempted to declare Anthropic a supply chain risk after it refused to modify its contract with the Pentagon to permit mass domestic surveillance and fully autonomous weapons. A judge has blocked that designation from taking effect while the case is litigated.

Anthropic told me that before launching Project Glasswing, it briefed senior US government officials about Mythos’ capabilities, both offensive and defensive. That includes the Cybersecurity and Infrastructure Security Agency and the Center for AI Standards and Innovation, which works with the industry to test new models and evaluate them for security risks. 

The company told me it has signaled to the government that it is available to help the government with evaluating Mythos. But it’s not clear the government is taking Anthropic up on the offer.

A functioning government would take a strong interest in what Anthropic is up to here, if only out of self-preservation. We simply don’t know whether Project Glasswing will be enough to protect critical systems from being breached — and for how long.

“The optimistic timeline is that we are one step past human capabilities, and that means that there is a huge but finite pool of flaws that can be found and fixed,” Stamos told me. “The pessimistic timeline is that with every release there will be new classes of flaws we never even imagined. It’s hard to predict, because we are trying to model superhuman thinking.”

For the moment, there's a case to be made that Project Glasswing represents Anthropic's founding thesis in action. The whole reason the company set out to build frontier AI models was so that a safety-focused lab would be the first to encounter the most dangerous capabilities — and could lead the way in mitigating them. With Mythos, that appears to be exactly what’s happening.

At the same time, Glasswing is built on a deeply uncomfortable premise — that the only way to protect us from dangerous AI models is to build them first. And Anthropic is doing so in an environment that is barely regulated at all, at the near-insistence of the Trump administration. 

One effect of this is to centralize power. (“An underrated feature of this situation,” observed Kelsey Piper today about Mythos: “a private company now has incredibly powerful zero-day exploits of almost every software project you've heard of.”) Another effect is to centralize risk: Among other things, the incentives to steal Anthropic’s model weights just went up significantly. 

None of which is likely to make AI more popular in a country that appears to be turning against it. Surveys show people are clamoring for more control over how AI is used and stronger safeguards around it. As the story of Project Glasswing plays out, we may regret not beginning that work much sooner.

Elsewhere in Mythos: A striking new benchmark result noted by VentureBeat: "Mythos Preview achieves 93.9% on SWE-bench Verified, versus 80.8% for Opus 4.6." That's a near 13-percent jump over the previous state of the art since February.

Following

People are yelling about tokenmaxxing

What happened: Meta has an internal leaderboard called “Claudeonomics,” The Information reports, ranking over 85,000 employees on their AI usage. Users who burn the most tokens can earn titles including “Session Immortal,” “Cache Wizard,” and “Token Legend.”

Employees are running coding agents continuously in hopes of landing a coveted spot in the top 250. (The top individual user at Meta spent 281 billion tokens last month.) A “token” is a chunk of information inputted or outputted by an LLM, roughly equivalent to one word. Which means that one Meta employee’s poor agents generated six times more tokens than are contained in the entirety of Wikipedia in all languages.

Over a recent month, total token usage on “Claudeonomics” topped 60 trillion. Had these tokens all been from one of the more expensive recent models, Claude Opus 4.6, this would’ve been a $900 million expense, although we hope they’re sometimes substituting for more economical models.

The news generated a bunch of X chatter. Onlookers are wondering if this is really a good metric for work at the company — or if Meta is burning a ton of money for the sake of productivity showboating.

Why we’re following: This is only the latest account of tech workers competing to use ever more tokens. It reflects both how much AI agents are actually boosting coders’ productivity, and the anxiety that only “Cache Wizards” will escape the permanent underclass.

At Meta, the high token spend and goofy leaderboard also underscore the expensive, flashy, somewhat chaotic efforts the company has made to catch up in AI.

What people are saying: On X, New York Times reporter Mike Isaac posted that after the recent conversation, a product growth director at Meta circulated an internal memo titled “token usage is NOT impact.” One line from the memo: “we’re talking about token usage and skill counts when we should be celebrating outcomes.”

Roblox’s product lead Peter Yang was skeptical of the tokenmaxxing approach: “Measuring productivity by token usage sounds almost as dumb as measuring by lines of code written.”

Software engineering blogger Gergeley Orosz pointed out that we’ve known AI use is part of Meta’s performance evaluations for a little while now. “This is just smart people (Meta only hires smart folks) hitting targets they assume leadership wants them to hit so they get that exceeds expectations (or above) rating.”

University of Chicago economics professor Alex Imas posted, “Focusing on the input and not the output is literally the most Meta thing to do.”

—Ella Markianos

Side Quests

An Indianapolis city councilor said someone fired 13 shots at his home and left a note that said “NO DATA CENTERS.”

Anthropic is reportedly planning to invest $200 million in a new PE venture that would sell AI tools to their portfolio companies. The company hired Microsoft's Eric Boyd as head of infrastructure.

A conversation with OpenAI president Greg Brockman on the company’s research direction, Codex, and LLMs. OpenAI opened applications for the OpenAI Safety Fellowship, its new program for researchers and others looking to pursue AI safety-focused research.

Jeff Bezos's new lab Project Prometheus has reportedly poached xAI cofounder Kyle Kozic from OpenAI.

Hackers with ties to Russia are targeting routers to gain access to passwords, the UK warned.

Licensing talks between Universal Music and Suno have reportedly stalled in recent months.

Tax experts are stumped on how to file taxes for wins from prediction market bets. Kalshi struck a deal with Fox Corp to integrate its forecasts into Fox channels. Finally, a Kalshi partnership that makes sense.

Intel is joining Elon Musk’s Terafab AI chip project. Musk amended his lawsuit against OpenAI to say that if he wins he wants the proceeds to go to OpenAI's nonprofit arm.

Apple is reportedly experiencing setbacks with engineering for its first-ever foldable iPhone — but it’s still on track for a September debut, sources told Bloomberg.

Google added mental health features to Gemini following multiple lawsuits.

SEO agencies are rushing to cash in on the AI boom by claiming they can help brands be cited by AI. A look at how easily Google’s AI Overviews can be manipulated.

Spotify is expanding its Prompted Playlist feature to include podcasts.

An interview with Upscrolled founder Issam Hijazi on how he’s catching up to the social platform’s rapid growth.

AI dolls are filling in the gaps in South Korea’s strained social care system by offering companionship to the elderly. 

The MLB’s robo-umps aren’t accurate enough to replace human umpires yet.

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Meta reduced funding to the board significantly this year and has signaled that it will do so again in 2027 and 2028, sources said, and staff members are bracing for another round of layoffs.

The sides are currently negotiating a compromise that would allow the board’s work to continue in some form. But a raft of options remain on the table, including a break with Meta that would see the board’s trust create a new entity that performs similar work for other tech platforms.

The news comes at a time when Meta has been shifting more of its trust and safety functions from humans to automated systems and as the company looks to cut costs to support its AI infrastructure buildout. Sources tell Platformer that Meta’s referrals of cases and policy questions to the board have slowed in recent months.

Meanwhile, Meta CEO Mark Zuckerberg has begun to get more involved in policymaking, bypassing the company’s existing processes to rewrite company’s hate speech policies ahead of President Trump’s inauguration last year. Last week it came out that Zuckerberg got personally involved and offered Elon Musk his help amid a controversy last year over media outlets naming employees of the Department of Government Efficiency, which led to online threats.

All of which suggests that the company has begun to think differently about the original purpose of the Oversight Board, which was to decentralize power away from a single person toward a rotating group of independent experts. 

While eliminating all funding has been discussed, Meta has told the board that it is not the company’s preferred option, sources said. But it remains unclear what changes the board would have to make to secure additional funding from the company — and whether those changes would be acceptable to the board.

“We are having meaningful and productive conversations with Meta about the board’s future,” Paolo Carozza, law professor at Notre Dame and co-chair of the Oversight Board, told Platformer in a statement. “I want to be clear that, at this time, no decision has been made and there are several options on the table for what that future might look like. The board has been transparent about its desire to evolve and adapt to the industry’s current and most pressing challenges in a way that maintains its independence and vital oversight function and that is what these conversations are centered upon." 

The Oversight Board is funded by a trust that Meta established in 2019 with an initial commitment of $130 million. The company provided additional funding of $150 million in 2022.

"Platformer previously reported about Meta’s commitment to fund the Oversight Board through 2028 and nothing has changed," a Meta spokesman told us.

The board, which recently celebrated its fifth anniversary, is empowered to make binding decisions about whether to remove or leave standing posts on Instagram, Facebook and Threads. It also advises Meta on policy issues — sometimes at the company’s request, and sometimes in response to appeals from users. Unlike its decisions about individual posts, the board’s policy proposals are nonbinding.

Meta has long encouraged the board to seek additional funding sources. The board has advertised its services to other social platforms in the hopes that one of them would hire it to do for them what it does for Meta, which would both burnish the board’s credibility and diversify its revenue. To date, though, no other platforms have taken the board up on the offer. (Appeals Centre Europe, a body created by the board's trust with a one-off grant to handle content moderation disputes under the European Union’s Digital Services Act, is legally separate.)

Fears that Meta would pull back support for the board mounted last year after Nick Clegg, who previously led global affairs at the company, stepped down at the beginning of 2025. Clegg was seen as a champion for the board’s work; he was replaced by Joel Kaplan, a former Republican operative who has written more skeptically about content moderation.

Zuckerberg first proposed the idea of an independent body to review the company's content moderation decisions in a 2018 episode of Ezra Klein’s Vox podcast, describing his vision as a kind of Supreme Court for Facebook. The board was established a year later following a period of intense public criticism over the company's handling of hate speech, misinformation and political content on its platforms. 

The board issued its first decisions in January 2021. Its highest-profile case came that same year, when Meta referred its decision to indefinitely suspend President Trump to the board following the Jan. 6 Capitol riot. The board upheld the suspension but criticized it as "an indeterminate and standardless penalty," directing the company to impose a proportionate, time-bound sanction. Meta responded by imposing a two-year suspension and later restoring his account.

Since then, the board has issued hundreds of decisions and more than 300 policy recommendations to Meta, which says it has implemented or is working on about three-quarters of them. 

The potential funding cuts come at a turbulent time for Meta's approach to content moderation. In January 2025, Zuckerberg announced that the company would end its third-party fact-checking program, loosen restrictions on political speech and shift its trust and safety operations from California to Texas, saying the moves reflected a "cultural tipping point.”

On the podcast this week: Kevin and I sort through last week's social media verdicts and what they mean for the internet. Then, author Sebastian Mallaby stops by to discuss his new book on Demis Hassabis and Google DeepMind. And finally, some HatGPT.

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Following

OpenAI acquires TBPN

What happened: Tech talk show TBPN has been acquired by OpenAI.

The show gained a cult following in Silicon Valley with a vibe the New York Times described as “what if SportsCenter and LinkedIn merged?” While their typical viewership hovers around 70,000 per episode, their tech-friendly attitude has attracted tech guests that cable news would covet, including Mark Zuckerberg, Satya Nadella, and future acquirer Sam Altman. 

OpenAI’s CEO of Applications, Fidji Simo, shared a memo she sent to the company about the acquisition. It’s “become clear is that the standard communications playbook just doesn't apply to us,” Simo said the announcement. OpenAI has a “responsibility to help create a space for a real, constructive conversation about the changes AI creates,” she added.

OpenAI acquired the company for “low hundreds of millions" — a staggering price for what is effectively one mid-sized podcast.

Simo said that TBPN would retain its editorial independence.

“TBPN will continue to run their programming, choose their guests, and make their own editorial decisions,” she wrote.

Why we’re following: We hope that TBPN does maintain their editorial independence. But it doesn’t seem like that’ll be easy.

In addition to continuing to run their show, TBPN will be working on comms for OpenAI itself, the announcement said. They’ll be reporting to OpenAI’s head of strategy, Chris Lehane, a notorious fixer who the Times has described as a “master of the political dark arts.”

It’s possible to cover an industry while having connections to it — the Washington Post, for example, continued to cause headaches for Jeff Bezos until quite recently. And, theoretically speaking, an outlet named Platformer could probably still write insightful coverage of the AI industry if its founder was engaged to an Anthropic engineer.

But such relationships have also gone south plenty of times, such as when CoinDesk’s owners had an unflattering article about one of its sponsors buying a $6.2 million banana removed last year.

Also of interest: this announcement comes approximately 10 minutes after Simo told OpenAI staffers that — quote — “we cannot miss this moment because we are distracted by side quests." That was the logic under which the company shut down Sora and ended plans to release an "adult mode" version of its chatbot, and it arguably would have applied to the question of whether to spend more than $100 million on a podcast.

What people are saying:

Altman, OpenAI’s CEO, wrote on X: “TBPN is my favorite tech show.” He added, “We want them to keep that going and for them to do what they do so well.”

He then added a startling prediction: “I don't expect them to go any easier on us, am sure I'll do my part to help enable that with occasional stupid decisions.”

TBPN’s co-hosts, Jordi Hayes and John Coogan, discussed the acquisition live on TBPN. Hayes reflected on their trajectory so far: “There’s so much uncertainty about AI, I don’t think we can change that, but there’s also a lot of fear,” he said. “And just talking through it with the people that are actually helping diffuse AI through the economy across every single industry is something that we’ve enjoyed a tremendous amount and is exactly what we’re going to continue to do.”

New Yorker Internet columnist Kyle Chayka posted, “1. TBPN is not traditional media or journalism by any means, more like a tech industry celeb podcast.”

However, Chayka added, “2. OpenAI has no reason to own a media company besides tacitly promoting its own causes, imagine competitors buying ad space on something it owns outright…”

Posters on X speculated on what media properties competitors like Anthropic or DeepSeek could acquire next, including Call Her Daddy, Alex Jones, Barstool Sports, and Cum Town.

Aaron Levie, CEO of enterprise software company Box, wrote, “Everyone’s missing the point. OpenAI can now harvest TBPN guest content for training data to automate CEOs out of jobs. It’s over.”

—Ella Markianos

Side Quests

The Trump administration — which frequently weaponizes disinformation for its own benefit — is now scrambling to respond to disinformation campaigns by Russia, China and Iran. A real sowing / reaping-type situation.

The Trump administration is appealing a judge’s order that temporarily blocked the Pentagon’s ban on Anthropic. The internal source code for Claude Code was accidentally leaked by Anthropic but did not expose customer data, the company confirmed. Anthropic used a copyright takedown request on more than 8,000 copies of the code in its pursuit to contain the leak’s fallout.

A look at how Anthropic’s new Mythos model could present significant new cybersecurity risks.

SpaceX has reportedly filed for an IPO.

OpenAI closed a funding round at a valuation of $852 billion, raising an unprecedented $122 billion. But OpenAI shares are dropping in demand on the secondary market as investors pivot to Anthropic.

The FBI reportedly deemed a China-linked cyberattack on an agency surveillance system a “major incident.”

The EU banned staff from using AI videos and images in official communications.

A lawsuit accused Perplexity of violating California privacy laws by sharing users’ personal information with Meta and Google.

Child safety advocates are demanding that YouTube prohibit AI-generated videos from being shown to young viewers. A look at how child safety groups found out the Parents & Kids Safe AI Coalition was being secretly funded by OpenAI. Will TBPN cover this one, do you think?

WhatsApp accused Italian spyware maker SIO of tricking its users into installing a fake version of the app that had spyware.

Google released Gemma 4, which it called its most intelligent open model yet. Vids app users can now direct and customize avatars through text prompts among a slew of new features.

Microsoft’s stock closed out its worst quarter since the 2008 financial crisis, losing nearly a quarter of its value in Q1. Microsoft launched a midsize translation model in an effort to catch up in the AI race, though it has yet to release an LLM capable of competing in coding and text generation.

Cursor launched Cursor 3, a new AI agent experience.

Snap shares climbed 14 percent after an activist shareholder’s letter outlined a plan to boost the company’s value by almost 600 percent. For April Fools’, Snap took a jab at Instagram’s tendency to rip off its features — and temporarily renamed its Spotlight feed to “Reals.”

Flipboard launched Surf, which combines Bluesky, Mastodon, RSS and other content into an app.

Mass layoffs at tech companies continued to rise in March as many invest more in AI.

People in the UK are posting and commenting less on social media as video apps become more popular.

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In the aftermath of last week’s landmark rulings in lawsuits against Meta and YouTube (in Los Angeles) and Meta alone (in New Mexico), reactions fell into three basic camps. 

One camp, represented by the plaintiffs, was euphoric. Finally, this side said, Big Tech would be held accountable for the harms caused to children by their platforms. “The jury’s verdict is a historic victory for every child and family who has paid the price for Meta’s choice to put profits over kids’ safety,” New Mexico Attorney General Raúl Torrez said in a statement after the verdict in that case. “Meta executives knew their products harmed children, disregarded warnings from their own employees, and lied to the public about what they knew. Today the jury joined families, educators, and child safety experts in saying enough is enough.”

A second camp, represented by the defendants, was defiant: both Meta and YouTube said they plan to appeal.

The third camp — and the one that has most interested me — are the writers, academics and thinkers who are trying to figure out what these verdicts mean for the wider internet. To this camp, it is self-evident that the tech platforms are villains of one sort or another. But in accepting the framing that their products have design defects for which they can be held liable, this camp argues, juries might have broken the basic compact that holds the internet together. 

And should these verdicts be upheld on appeal, they worry that platforms will begin restricting far more speech than they ever did previously. What once were open forums for robust debate may come to feel increasingly sanitized and even censored.

The basic compact at the center of these cases is, of course, Section 230 of the Communications Decency Act, which prevents companies from being held liable in most cases for what their users post. If I libel you on Facebook, you are free to sue me, but Meta gets a free pass. The case that spurred lawmakers to create Section 230 was a defamation case like this; they worried that if you could sue a platform out of existence just because one user had defamed another, the internet would be at risk of collapse. 

For 30 years, Section 230 has shielded platforms from liability for nearly everything their users do — from defamation to drug sales to incitement. It has also, along with the First Amendment, enabled an enormous amount of political speech.

Last week’s verdicts are important because they appear to demonstrate a clear path for people who believe they have been harmed by platforms to get around the shield: they only have to prove that the harms that they experienced resulted from the way the platform is designed.

In these cases, that means features including recommendation algorithms, “beauty” filters, infinite scroll, autoplay video, “streaks,” and barrages of push notifications. More worryingly, in the New Mexico case, encrypted messaging was also implicated.

Jurors were convinced that these features caused problematic use of Instagram and YouTube for the plaintiff in the LA case, and that Meta misled users about the safety of its platform in the New Mexico case. If upheld, platforms will face pressure to dramatically scale them back or eliminate them altogether, for children and possibly for adults. But some scholars say the changes may have to go further.

“Due to the legal pressure from the jury verdicts and the enacted and pending legislation, the social media industry faces existential legal liability and inevitably will need to reconfigure their core offerings if they can’t get broad-based relief on appeal,” Eric Goldman, a law professor at Santa Clara University and Section 230 scholar, wrote on his blog.

Like many in the third camp, Goldman worried that the ruling would have dire consequences for speech on the internet. “While any reconfiguration of social media offerings may help some victims, the changes will almost certainly harm many other communities that rely upon and derive important benefits from social media today,” he wrote. “Those other communities didn’t have any voice in the trial; and their voices are at risk of being silenced on social media as well.”

TechDirt’s Mike Masnick, another strong supporter of Section 230, was more blunt.

“If you care about free speech online, about small platforms, about privacy, about the ability for anyone other than a handful of tech giants to operate a website where users can post things — these two verdicts should scare the hell out of you,” he wrote. “Because the legal theories that were used to nail Meta this week don’t stay neatly confined to companies you don’t like. They will be weaponized against everyone.”

II.

There are parts of this argument that I agree with. Most alarming is the way that the New Mexico case argued Meta had endangered child safety by enabling end-to-end encryption in Instagram messaging. Earlier this month the company said it would discontinue encryption in Instagram, directing people instead to WhatsApp.

AG Torrez is the latest in a long line of law enforcement officials to realize his job would be easier if he could snoop on anyone’s messages. But we should not have to give up our basic right to privacy so that cops can make fewer phone calls. And encryption was at best tangential in the New Mexico case, which focused more on recommendation algorithms and how Meta failed to police the suspicious cross-platform movements of children across WhatsApp, Venmo, and Telegram.

I also agree that courts should apply strict scrutiny to any effort to limit what kinds of content platforms can recommend. So long as the content is legal, any efforts to regulate recommendations this way would seem like a clear violation of the First Amendment. This is why I remain skeptical of well-intentioned legislation like the Kids Online Safety Act: it may begin by telling platforms that they can’t recommend content about drugs and eating disorders, but could too easily be expanded to include bans on material about dissidents, LGBT people, and other disfavored groups.

Where I disagree with those in the third camp is where they say, in essence, that every design decision in an app like Instagram or YouTube is an editorial decision protected under the First Amendment. Goldman, in an interview with a reporter, put it this way:

“Social media’s offerings consist of third-party content, and the configurations were publishers’ editorial decisions about how to present it. So the line between first-party “design” choices and publication decisions about third-party content seems illusory to me.”

I’m not so sure. To say that an infinitely scrolling feed encourages overuse is to make no comment on its contents; only that the intermittent rewards that such a feed creates turns it into a kind of slot machine, and that teens would be less likely to develop problematic use if it didn’t exist.

Masnick’s response to this is to say that an infinitely scrolling feed is only interesting if the content of the feed is interesting — and so the distinction between content and design, from a legal perspective, really is illusory. He writes:

Here’s a thought experiment: imagine Instagram, but every single post is a video of paint drying. Same infinite scroll. Same autoplay. Same algorithmic recommendations. Same notification systems. Is anyone addicted? Is anyone harmed? Is anyone suing?

Of course not. Because infinite scroll is not inherently harmful.

On its face, it’s a compelling argument. But what if you ran the experiment the other way? What if you kept the content of a problematic Instagram feed identical — fill it up with posts about eating disorders, self-harm, rage bait, and drugs — but served it in an app where you had to tap a button every time you wanted to see the next post? What if this same version of the app sent no push notifications, and blocked video from autoplaying? If that was the default version of Instagram, do you think more people would be harmed, or fewer? 

To me it seems obvious that fewer people would be harmed. Add a little friction to the experience, and it becomes much easier for the average person to look away. The content is still the same, but the delivery mechanism has changed, along with the dosage.

The truth is that content and design are necessary for people to be harmed at scale. And in a country where the Constitution prevents you from regulating the content, you can only regulate the design.

The question, of course, is how.

III.

One reason that the distinction between content and design features looks illusory to some is that they exist on a spectrum. If you changed the Instagram recommendation algorithm to promote only educational material, you are changing the content and the design of the app at the same time. 

On the other hand, I reject the argument of the 230 diehards that every design decision is a content decision. The contents of YouTube go unchanged if the videos in your feed do not play by default. Snapchat messages will read the same even if Snap is prevented from incentivizing teens to go to extreme lengths to preserve their streaks. TikTok will still be TikTok if it is prevented from sending teenagers push notifications after midnight.

By identifying and restricting mechanical design features like these, we can preserve the core of Section 230 while also limiting at least some of the harm that platforms can cause. I’m under no illusion that we can solve the teen mental health crisis simply by disabling push notifications on Instagram. But given the complexity of the problem, the least we can do is to attempt some harm reduction: and that should begin with features like those above, which have close to no value outside boosting the valuations of the world’s richest companies.

I’m sympathetic to 230 defenders who fear that it is load-bearing infrastructure for the internet: that to touch it is to trigger a full-on collapse. When it became law 30 years ago, it fixed a genuine problem. And for a long time, it mostly worked as intended, letting small forums, blogs, and startups set up shop without getting sued into oblivion every time one user called another a bad name. 

But a lot has changed since then. In 1996, the role of the platform was essentially custodial. Its job was to host and display the speech, and it didn’t do much beyond that. 

The internet of 2026 is a very different place. Platforms are no longer simple custodians. They build sophisticated systems that study your behavior to discover what will keep you on the app the longest, and then serve you more of it. They employ cognitive scientists who run endless experiments in an effort to defeat your instinct to do something else. And they do it not by making recognizably human editorial decisions about content, but by relentlessly optimizing their platforms’ designs.

That’s why, in the end, I’m glad juries recognized at least some of these design features as defective — and as something distinctive from what Section 230 was originally created to protect. The distinction between content and design might be blurry at the margins, but the differences between the CompuServe of 1996 and the Instagram of today are not subtle. The law should be able to tell the difference between them — and to rein in the excesses of our biggest platforms, which have shown us time and again that they have no interest beyond their own survival.

Section 230 continues to do a lot of good, and should be handled with care. But to argue that it must be frozen in amber and preserved at all costs is to risk protecting an abstraction at the expense of actual people. Juries have begun to realize that, and one way or another, platforms are going to have to deal with the consequences.

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Meta stops pretending Instagram is PG-13

What happened:

Meta is walking back its rather bold decision to use “PG-13” to describe Instagram’s Teen Accounts after reaching an agreement with the Motion Picture Association. Meta will “substantially reduce” references to the rating and add a disclaimer that “there are lots of differences between social media and movies” when it does as part of the new agreement.

The initial decision to use the rating — announced in October — drew swift backlash from the MPA, which Meta had not deigned to consult before trying to hitch its beleaguered brand to something more trusted.

The MPA sent a cease-and-desist letter to Meta in the same month, calling the usage “literally false and highly misleading.”

Why we’re following: As the MPA pointed out in its press release, films rated by CARA, its voluntary film system, are “professionally produced and reviewed under a human-centered system, while user-generated posts on platforms like Instagram are not subject to the same rating.” 

Meta’s approach was dubious from the start. A parent can generally expect a PG-13 movie to have few instances of swearing. From an implementation perspective, it’s hard to see how Instagram can promise the same sort of experience when social media and movies are fundamentally consumed differently.

Given all that, the surprising thing here is that the MPA is allowing Meta to associate Instagram with its rating system at all.

What people are saying: “We reject Meta’s implication to the public that Instagram’s tools for teens will be as safe and reliable as the MPA’s system,” Charles Rivkin, chairman and CEO of the MPA wrote in an op-ed for the Washington Post in November.

Rivkin had valid concerns then, especially with the child safety issues that have been swirling around Meta’s platforms: “What happens when inappropriate content slips through Instagram’s purportedly PG-13-inspired filter? Would parents conclude that the problem is an Instagram-specific defect?” 

—Lindsey Choo

Bluesky users reject Attie

What happened: 

Bluesky users despise the company's new AI app, Attie. 

The app, which lets users build a custom Bluesky feed via text prompts, drew dunks from a user base that felt Bluesky had promised to eschew the AI-everywhere ethos of the modern internet. In the days after former CEO Jay Graber announced Attie, more than 100,000 people blocked Attie’s account on Bluesky.

That means Attie is the second-most-blocked Bluesky user behind U.S. Vice President J.D. Vance. At press time, Attie even had more blocks than ICE.

Why we’re following: Attie is the first feature Jay Graber has shipped since her recent transition from CEO to chief innovation officer. Unfortunately, Bluesky’s base doesn't seem very excited about this particular innovation.

In fairness to the CIO, it seems like people are confused about what Attie does. It’s not Bluesky's version of Grok, or even a chatbot per se. Instead, it’s a feature built on top of Bluesky’s ATP protocol and hosted outside its app, which means blocking @attie.ai doesn’t actually do much. 

(We at Platformer would be supporters of Bluesky Grok, though. The time is ripe for a woke MechaHitler.)

Platformer was actually pretty excited for custom algorithms, and attempted to test Attie. Unfortunately, our efforts to craft a feed of Bluesky posts about the day's AI news mostly returned tedious arguments.

Our subsequent effort to create a custom feed about vintage interior design also went south when, out of nowhere, the first post showed a beautiful midcentury interior — occupied by a person posing in extremely skimpy lingerie. 

The good news is that we only saw one porn post in our testing. And Bluesky’s porn appeared consensual and human-generated, unlike in certain other apps we could mention.

What people are saying: The most-liked reply to Jay Graber’s original announcement was a simple, “no thank you.” Another user wrote, “Cool! How do we block it?”

User @almostordinary.etheric-veil.com captured Bluesky’s mood with this image:

Many users were struck by the irony of a November 2025 post from Bluesky’s official account that read, “every time a software tool adds an AI feature nobody asked for, a human logs off.”

Graber addressed Attie’s haters in a follow-up post: “We hear the concerns about AI. Our goal is to use this technology to give people greater control, not to generate content.” She added: “We’ll look into ways to take into account the preferences expressed by people who’ve blocked @attie.ai.”

—Ella Markianos

Side Quests

A look at Trump AI czar David Sacks’ new role outside the White House, which appears to work a lot like his old role, but without the pesky ethical constraints.

Iran said it plans to target 18 major US tech companies in the Middle East, including Apple, Microsoft, and Google. A look inside Iran’s sophisticated hacking campaign to shape online perception.

California Gov. Gavin Newsom’s new executive order will require safety guardrails for AI companies seeking contracts with the state.

SpaceX lost contact with another Starlink satellite (because it exploded).

A look at the inner workings of Claude Code based on a partial source code leak.

The UK plans to probe Microsoft’s business software unit over concerns it could stem the growth of rivals. The UK’s accountancy regulator told auditors they will remain responsible for audit failures even when they’re caused by AI.

The new Meta Ray-Bans are more customizable, especially for people who need prescription lenses, but are also more expensive.

All US Google users can now change their email addresses.

Amazon struck a deal to provide in-flight WiFi on Delta flights.

Alibaba’s new multimodal model is not open-source, unlike its predecessors. 

Future quantum computers could more easily break the cryptography protecting Bitcoin and other digital assets, Google researchers warned.

A disturbing game called Five Nights at Epstein’s is going viral in schools.

A look at how coding agents are dramatically changing vulnerability research.

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Call it the invasion of the stream snatchers. 

In November, Platformer reported on a strange phenomenon taking place on the world’s biggest music platform. Artists who had left Spotify found that, within a few months, some of their tracks and albums had reappeared within the app. At times, the tracks sounded like bad imitations of the original. At others, they sounded nothing like the original at all. 

Regardless of their fidelity to the original, though, imitation tracks were racking up millions of streams — and generating revenue in the name of the authentic artist.

As I wrote last year, this was particularly annoying to groups like the Australian psychedelic rock band King Gizzard and the Lizard Wizard, which had quit Spotify on principle last year after news that then-Spotify CEO Daniel Ek led a €600 million investment in Helsing, which makes military drones and AI tools for weapons systems. They wanted their name and works off Spotify for good. They thought they had left. How were they supposed to police their presence on the platform, when they weren’t supposed to have a presence there at all?

Spotify removed a host of impostor Gizzard tracks last year after Platformer inquired. Among the challenges, the company told me, is that AI-powered music apps are making it increasingly easy to generate convincing fakes. 

But the larger question remained. Spotify creates strong financial incentives for this kind of domain squatting. Would the company intervene to stop it?

On Tuesday, we got our answer. The company introduced a new feature in beta called artist profile protection designed to prevent what happened to King Gizzard from happening to anyone else.

The company described how it works in a blog post:

For the first time on any music streaming service, we’re giving you the ability to review and approve or decline releases delivered to Spotify from most providers. To protect your artist identity and prevent listener confusion, only the releases you approve will appear on your artist profile, contribute to your stats, and show up in recommendations to your listeners.

Artist Profile Protection isn’t necessary for every artist, but could make sense if you’ve experienced repeated incorrect releases, have a common artist name, or want more control over what appears on your profile. It requires you to actively review releases before they go live, so may delay or block your legitimate releases if you forget to take an action. It's best for those who are comfortable very actively managing their catalog.

The company will also assign artists a unique code, called an artist key, to share with the teams that manage their catalogs. They can include the key when submitting music to Spotify so that it is automatically approved to show up on the artist’s profile.  

On one level, this is one of those features that makes you wonder how the platform hadn’t thought to do this already. In hindsight it seems crazy that you could just pretend to be another band and upload songs to their profile without anyone noticing the scam. (Spotify does have systems in place designed to prevent this from happening; the company told me last year that they don’t work as well for artists who have left the platform.)

On another level, though, the problem really does seem to have grown more complicated over the last year. Recording a passable cover of a relatively arcane back-catalog song from a niche artist used to take a modicum of effort. Today, tools like Suno and Udio allow them to be created with a text prompt. This will not be the last story we hear this year about new AI tools enabling spammers and scammers to overcome defense systems that until now were mostly working fine.

At the same time, I’m struck by just how slippery questions about identity are becoming in the AI age. Increasingly, identity is a raw material that scammers, spammers, and even platforms can remix without your permission — unless you show up to claw it back.  

A few months after my story about King Gizzard, the British soul singer Jorja Smith found that her voice appeared to have been cloned and then used by dance act Haven to provide vocals for a song that then went viral on TikTok. Streaming services banned the track after an outcry; when her label asked for royalties, Haven swapped out “her” vocals for someone else’s. 

The band acknowledged using Suno to create the vocals but said they were based on the voice of Haven’s Harrison Walker and heavily modified. From Smith’s perspective, though, I imagine the experience was surreal and not a little depressing: having a hit song in what sounded like her voice, created without her knowledge or consent, which she made no money from.

Experiences like these extend well beyond music. I got my own taste of it earlier this month when I was one of dozens of people conscripted into Grammarly’s since-deleted AI editor program. As with the other cases, something AI-generated was pretending to be me, or at least to be “inspired” by me, and any economic value that generated would be claimed by someone else. 

There are even darker versions of this, of course, and they can have dire consequences. xAI’s Grok caused outrage around the world earlier this year when it began to generate an estimated 1.8 million sexualized images of people, including minors. To Grok, even children no longer had any right to their own identity; Elon Musk called it a “free speech” issue.

And while Meta actually paid some celebrities to become part of its own chatbot product, actors like John Cena and Kristen Bell still found last year that their bots could be used in sexual roleplay scenarios, including with minors. Even when these systems have the permission of those involved, they can still behave in ways no one involved would want. 

Spotify’s move to protect artists is the right one, even if it’s arriving a bit overdue. The rest of us will need protections of our own. The good news is that at least 45 states have passed laws addressing deepfakes. Last year Congress managed to pass (and President Trump signed) the TAKE IT DOWN Act, which criminalizes the spread of sexualized deepfakes and forces platforms to remove them within 48 hours of being notified.

The bad news is that, as Spotify has been learning, the threats are proliferating. And while we may have found a way to stop the stream snatchers from colonizing the major platforms, the pods are still opening everywhere else. You can still maintain a grip on your digital identity. But increasingly, you’re going to have to fight for it.

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Judge in Anthropic case finds the Pentagon’s actions “troubling”

What happened: U.S. District Judge Rita Lin called the Pentagon’s actions against Anthropic “troubling” during a Tuesday hearing on Anthropic’s civil suit against the Department of Defense.

The Pentagon’s actions in designating Anthropic a “supply chain risk” over its refusal to amend a contract “don't really seem to be tailored to the stated national security concern,” she said.

Instead, this “looks like an attempt to cripple Anthropic," Lin said.

Anthropic is asking the U.S. district court for a preliminary injunction against the administration after their relationship soured over Anthropic’s concerns about domestic mass surveillance and lethal autonomous weapons. 

The company hopes the judge will reverse a directive by President Trump that government contractors stop using Anthropic, which he posted to Truth Social. The second is a directive from Defense Secretary Pete Hegseth that DoD contractors cannot “conduct any commercial activity with Anthropic,” posted to X. The third is the supply chain risk designation, a classification previously only used for foreign adversaries.

During the hearing, the Pentagon’s counsel argued that Hegseth’s directive wasn’t legally binding. Judge Lin said she found that argument “pretty surprising.”

Why we’re following: I, too, found it surprising that the DoD’s lawyer argued a directive from the head of the DoD (which ended “this decision is final”) had no legal effect. I genuinely burst out laughing while listening to the court hearing, as the DoD’s lawyer struggled to justify why Hegseth posted that given that Hegseth supposedly had no legal authority to make the command in the first place.

This episode looks like another example of the Trump administration playing fast and loose with the law in order to intimidate its opposition. Today’s hearing offered a sign that this time, it might not work.

What people are saying: 

Jessica Tillipman, associate dean for government procurement law at George Washington University, told Breaking Defense that the administration’s public statements against Anthropic weakened their case. 

If they hadn’t publicly attacked Anthropic, it would have been easier to argue that the administration acted on rational grounds based on the law. But “they have statements on the record right now that feel very much like this is a punitive, retaliatory act,” she said. “Trump saying ‘I fired [them] like dogs,’ that’s Exhibit No. 1. [And] when I saw the Secretary’s statement I was like, I’m sure the lawyers for Anthropic could have it framed.”

—Ella Markianos

Meta loses child safety trial

What happened: A jury in New Mexico found that Meta wilfully violated the state’s consumer protections laws and misled users about the safety of its platforms, ordering the company to pay $375 million in damages.

The lawsuit, brought by New Mexico Attorney General Raúl Torrez in 2023, followed an undercover investigation in which Meta platforms allegedly inundated a fake profile of a 13-year-old girl with “images and targeted solicitations” from child abusers.

The suit in New Mexico is the first to reach trial in a series of social media lawsuits. Jurors are still deliberating over a separate trial in Los Angeles over whether Meta and YouTube knew the design of their platforms inflicted harm on their younger users. TikTok and Snap settled in that case rather than risking a trial.

Why we’re following: Social platforms have long been able to avoid liability in cases where users experience harms by citing Section 230 of the Communications Decency Act, which shields them from the consequences of what other users post. The New Mexico case represents an effort to target the design of the system rather than the individual posts. It’s not any one Instagram Reel that causes you to develop an eating disorder, this argument goes; it’s that Meta’s recommendation algorithms see that you enjoy watching them and serve you more of them (including via push notifications) until you do. 

This was a relatively fringe legal theory until recently. The New Mexico verdict suggests it may be a winner — which has huge implications for liability for other platforms that host user-generated content.

What people are saying: “We respectfully disagree with the verdict and will appeal,” Meta spokesman Andy Stone wrote on X. “We work hard to keep people safe on our platforms and are clear about the challenges of identifying and removing bad actors or harmful content. We will continue to defend ourselves vigorously, and we remain confident in our record of protecting teens online.”

Stone also noted that the damages are “just a fraction of what the State sought.”

While the New Mexico trial deals with a slightly different issue than the Los Angeles one, the “jury finding for the state across the board is, however, a big moment for the crowd arguing that product liability offers a way around Section 230,” Reuters’ Meta reporter Jeff Horwitz wrote.

—Lindsey Choo and Casey Newton

Side Quests

The State Department launched a new entity, the Bureau of Emerging Threats, to anticipate and respond to advanced cyberattacks from Iran and other US adversaries.

A look at how connections to Palantir have become a bane for political candidates, who are facing pressure not to take donations from the company.

The FCC banned the import of all new foreign-made consumer routers, a move seemingly targeted towards China, which controls an estimated 60 percent of the US market. Senators demanded the Commerce Department suspend Nvidia’s exports of AI chips to China and south-east Asian countries in response to the Super Micro smuggling scandal.

There was a 260-fold increase in AI-generated CSAM over the past year, the Internet Watch Foundation said.

Baltimore became the first major US city to sue xAI over Grok’s deepfake porn issue.

Finland shelved a plan to move its election platform to AWS amid worries about US stability. AWS services in Bahrain were disrupted due to drone activity in the area.

OpenAI shut down Sora as part of its pivot back to making enterprise software. (Another one of my 2026 predictions comes true.) Disney canceled plans for a $1 billion investment in OpenAI tied to a now-useless Sora deal.

Sam Altman will no longer oversee OpenAI’s safety and security teams so he can focus on fundraising and infrastructure; the company has also finished pre-training a new model codenamed “Spud.”

OpenAI asked UK regulators to force Google to offer ChatGPT as an alternative search engine on Android and Chrome on mandatory choice screens. OpenAI hired former Meta ad executive Dave Dugan to lead ad sales. The company is overhauling the shopping experience in ChatGPT after its Instant Checkout flop. Meanwhile, it’s reportedly nearing a deal to raise about $10 billion as part of a round valuing at $730 billion. 

OpenAI released a set of open-source teen safety prompts developers can use when training their models. The OpenAI Foundation announced key hires and committed to investing $1 billion in AI causes. Co-founder Wojciech Zaremba will lead AI resilience; Jacob Trefethen, who previously worked at Coefficient Giving and is the co-host of the Hard Drugs podcast, will oversee life sciences work, including an initiative to cure Alzheimer’s disease. 

Claude can now take control of your computer and perform tasks, just like OpenClaw. Anthropic announced a new “auto mode” for Claude Code so you don’t have to keep granting it permission for everything. (It is designed to be safer and more conservative than “dangerously skip permissions” mode.)

Meta CTO Andrew Bosworth will take over supervision of the company’s ‘AI For Work’ initiative, designed to get employees to use the technology more. Meta added new affiliate marketing tools for creators. The company won a legal case against its former head of cybersecurity, who alleged he had been retaliated against for whistleblowing claims.

Microsoft is hiring a group of top AI researchers for Mustafa Suleyman’s AI team, including former Ai2 CEO Ali Farhadi. Speaking of Suleyman: Tom Dotan has a nice, skeptical look at Microsoft’s AI efforts under Satya Nadella over at Newcomer.

Apple is reportedly testing a standalone Siri app and a new “Ask Siri” feature that will work across the company’s software. Or at least, it’s supposed to work.

Zoox is planning to start charging for rides by mid-year in Las Vegas, with San Francisco to follow. Amazon acquired humanoid startup Fauna Robotics. 

Beehiiv now allows users to connect AI tools to their newsletters through MCP.

Someone leaked an advanced hacking tool targeting iPhones named DarkSword to GitHub.

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Musk intentionally deceived Twitter shareholders when he said the platform had a high prevalence of bots, making it worth less than he had agreed to pay, the jurors found.

Musk’s lawyers vowed to appeal. If that fails, Musk could owe millions or even billions of dollars to shareholders.

The verdict marked a rare loss in court for Musk, who previously beat back charges that he had deceived Tesla shareholders when he falsely tweeted that he had the “funding secured” to take Tesla private. 

But in October, Musk was forced to settle another Twitter-related matter: his effort to deny four top former Twitter executives a combined $128 million in severance pay. The executives said Musk falsely accused them of misconduct in an effort to get out of paying them.

Why we’re following: It seems hard to remember now, when Musk and X are inextricably linked. But for most of 2022, Musk really did seem like he was doing everything in his power to get out of the Twitter deal. 

Conventional wisdom at the time was that he had massive buyer’s remorse. Twitter’s $44 billion price tag was considered ridiculous even by the standards of pandemic-era Silicon Valley, and Musk’s vague stated intentions for the platform — which mostly amounted to saying “free speech” and “ban the bots” over and over again — seemed halfhearted at best. The man was already running SpaceX and Tesla, and several months after the deal closed he would found xAI. How could Twitter possibly be worth the time? 

Well, now we know. X became a massively successful right-wing political project, and now functionally serves as state media for the Trump administration. The company (plus another $288 million in political donations) bought Musk untold influence within the Trump administration, including a stint running the disastrous DOGE project. While at DOGE, he significantly undermined a variety of federal agencies that had previously been investigating him.

A year ago, Musk folded X into xAI, somehow valuing the former Twitter at $45 billion (minus $12 billion in debt).

Almost everything has gone Musk’s way when it comes to Twitter. On Friday, though, the jury’s verdict raised the prospect that in some small way, Musk might be held accountable.

What people are saying:

Musk’s lawyers promised that he would not, in fact, be held accountable. 

“We view today’s verdict, where the jury found both for and against the plaintiffs and found no fraud scheme, as a bump in the road,” Musk’s lawyers told Bloomberg. “And we look forward to vindication on appeal.”

Still, plenty of people seemed to be enjoying some schadenfreude: Musk’s defeat in court charted on the subreddits MadeMeSmile, GoodNews, and NoShitSherlock.

— Casey Newton

The White House's new AI agenda

What happened: The White House released its new policy wishlist for federal AI regulation. The framework has been in the works for a while, after it was promised alongside Trump’s (questionably legal) executive order attacking state AI legislation.

The “National Policy Framework” foregrounds the administration’s wish to avoid state AI laws that “impose undue burdens,” and adopt a “minimally burdensome” federal regulatory framework. But it makes some concessions to populist concerns that Republicans worry a federal framework would compromise, including child safety and increased electricity costs from data centers.

The framework has some narrow carveouts for states to regulate AI, including laws related to fraud, child safety, zoning, and state use of AI.

Notably, though, the framework goes against proposals — including a recent one from Sen. Marsha Blackburn (R-TN) — that seek to impose legal liability on AI developers for harms caused by their products. Instead, it seems to promote a Section 230-style liability shield.

Why we’re following: Trump’s new framework is the administration’s latest bid to get Congress to preempt state AI regulations — a push that has now failed twice.

Blackburn’s concerns about child safety were key in stopping preemption the first time around. As child safety in AI becomes an even bigger issue — and we see documented harms to children, from CSAM to suicide — we’re interested in how Republicans will ultimately come down on how to regulate it.

The new proposed measures on child safety focus on parental controls and “commercially reasonable … age-assurance requirements,” avoiding holding companies responsible for how design choices in their products might hamper child safety. We’ll see if that’s enough to convince lawmakers.

What people are saying: 

Dean Ball, who helped craft the administration’s earlier AI action plan but has been critical of its designation of Anthropic as a supply chain risk, called it “an excellent foundation for the legislative work ahead.” He added: “I would be happy to see these principles, if translated well into statute, become law.”

Riki Parikih, policy director for the Alliance for Secure AI, found many shortcomings. “It offers nothing on independent safety testing, no serious ideas on how to address labor market disruption, and no accountability standard for when AI systems cause harm,” he wrote. “Worse, it would create a new liability shield for AI developers — the same type that has made platform accountability so difficult for the last two decades.”

Sacha Haworth, executive director of the Tech Oversight Project, was among many to lament the new effort to pre-empt most state legislation on AI. “There it is again,” she wrote, noting a section of the framework that reads: “States should not be permitted to penalize AI developers for a third party’s unlawful conduct involving their models." 

“AI amnesty for Big Tech, direct from the White House,” Haworth called it.

Others noted the obvious discrepancy in the White House’s attempt to ban government efforts to force ideological changes in AI systems with its previous attempts to do exactly that. “[The framework] rightly says that the government should not coerce AI companies to ban or alter content based on ‘partisan or ideological agendas,’ yet the Administration’s ‘woke AI’ Executive Order this summer does exactly that,” Samir Jain, vice president of policy at the Center for Democracy and Technology, told TechCrunch.

Andy Jung from the tech policy think tank TechFreedom noted the obvious difficulty in translating the framework into action. “It repeats the phrase ‘Congress should’ twenty-six times,” he wrote. “Releasing this was the easy part. The hard is actually getting lawmakers to write the laws.”

— Ella Markianos

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Side Quests

The Trump administration said it would invest $250 million — and hopes to attract $4 trillion in investment — for a fund to invest in energy projects, minerals and semiconductors and put them under control of allies.

Russian hackers have gained access to thousands of users’ messaging apps through a phishing campaign targeting Signal and other apps, the FBI and CISA said.

Anthropic reportedly met with the House Homeland Security Committee to discuss national security and AI — but mostly not discussing the Pentagon dispute. About that: Anthropic cannot manipulate Claude in the middle of a war, an executive wrote in a court filing, denying the Defense Department’s allegation that it can. 

Palantir’s Maven AI system will become an official program of record. (As opposed to ...?) The United Kingdom’s FCA granted Palantir access to investigate its internal intelligence data to help with addressing financial crimes, raising privacy fears.

A look at the popularity of viral AI-generated MAGA Army dream girls. (Imagine explaining this sentence to a Victorian child.)

A bipartisan pair of senators introduced a bill that would prohibit prediction markets from taking bets on sporting events.

A court temporarily banned Kalshi in Nevada. Polymarket’s social feeds have published hundreds of false and misleading posts despite claiming to be a news source, a review found. Meanwhile, the archrival CEOs of Kalshi and Polymarket are investing in the same venture fund for prediction market startups.

Polymarket unveiled rules against insider trading that you might have thought it had adopted long ago — and seem difficult to enforce. It also plans to ban politicians from betting on their own campaigns, and athletes on their own sports.

OnlyFans founder Leonid Radvinsky died from cancer at 43.

Pinterest CEO Bill Ready makes the case for why social media should be banned for kids. ("Because it wouldn't really affect Pinterest that much" does not appear in his argument.)

Meta acquired the team behind startup Dreamer, including former Google and Meta exec Hugo Barra, to work with Alexandr Wang on agents. Mark Zuckerberg is reportedly building an AI agent to help him do his job. (He wasn't before? What happened to Jarvis?)

Elon Musk’s chipmaking Terafab project will be built in Austin and run jointly by Tesla and SpaceX.

Anthropic released Claude Code Channels, an OpenClaw-like feature that connects Claude Code to Telegram and Discord. Meanwhile, Tencent launched a tool to integrate WeChat with the OpenClaw agent.

Amid concerns that its product organization has begun to sprawl, OpenAI is planning to combine its ChatGPT app, Codex and browser into a desktop "superapp." The company plans to double staff to 8,000 by the end of the year. Elswhere, OpenAI is planning to buy electricity from the Sam Altman-backed Helion. The company is also offering private equity firms guaranteed returns and other perks as it competes with Anthropic to create joint ventures that would allow its models to quickly roll out to hundreds of PE-owned firms.

Advertisers reportedly can’t yet prove that ChatGPT ads work.

Google signed deals with five US utilities to reduce its energy consumption during times of peak demand, as public backlash to AI-related energy costs continues to grow. Elsewhere, Google is replacing journalist-written news headlines with AI-generated ones in Search, and there’s no way for publishers to opt out of it.

Wordpress.com said it will allow AI agents to draft, edit, and publish content on websites among other capabilities, raising hopes that Google will soon use AI to rewrite AI-written WordPress headlines.

Nilay Patel grilled Grammarly boss Shishir Mehrotra about its insane AI editor feature.

A look at Andrej Karpathy’s early experiments in getting a large language model to run experiments on itself to find training efficiencies — a key step toward recursive self-improvement.

Amazon is reportedly developing a smartphone again, more than a decade after its Fire Phone flop.

Apple’s Worldwide Developer Conference will take place June 8-12. Apple is planning to introduce ads into Apple Maps. CEO Tim Cook praised Apple’s Chinese partners days after China criticized the company’s policies. Maybe he should throw in a gold trophy?

Nvidia CEO Jensen Huang pitched a compensation package for engineers that would give them an AI token budget on top of base salary. That might make sense for tech workers who are now “tokenmaxxing” to prove how productive they are. Elsewhere, Huang told Lex Fridman that "we have achieved AGI."

Roblox overhauled its ad policies and will now take a share of revenue from sponsorships, in today's reminder that every platform drifts toward maximum revenue extraction from creators over time.

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