Artificial Intelligence

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Anthropic and OpenAI sound the alarm on AI safety — and seek to shape how it's controlled

As tech titans warned an AI-weary world that their own advanced systems could endanger humanity, the question emerged: What do they have to gain? Read More.

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The AI terms you actually need to know

Illustration: Brendan Lynch/Axios

Tonight and tomorrow, Axios CEO Jim VandeHei will offer tips on talking and thinking about AI, all written in normal, non-technical language. First up: simple answers to complex questions. Confused about AI? You're hardly alone. Most people still don't know what it is, how it works or whether to trust it. No wonder. The AI language is just plain weird: LLMs, tokens, agents, hallucinations, swarms, misalignment, The Singularity. So consider this your guide to understanding AI, written in Jim, normal-guy, real-world words: 🤖 What is AI? Computers doing things that typically require a human brain: reading, writing, reasoning, creating. Well then, what's an LLM? Large language model. It's the engine of AI — the machine that learns to read, write, reason and create. The most powerful and popular LLMs are built by Anthropic, OpenAI and Google. Oh, so ChatGPT is an LLM? Not exactly, though you don't have to worry about that distinction much. OpenAI's ChatGPT, Anthropic's Claude and Google's Gemini are all consumer products that allow you to interact with each company's LLM. 🧠 How does an LLM or AI work? An LLM eats everything on the internet alongside other stuff (you've probably seen stories about Anthropic and books) and then gets trained by humans — and, increasingly, the AI itself — to read, write, reason and create like us. Wow, so they THINK like humans? NO. All that reading just teaches them to imitate how we write. Talking like us comes from a second step, called post-training, where companies train them to behave more like us. Great, so we know how they work? Yes and no. And this is super important. Yes, scientists know how to build and train these models. But NO — nobody can fully explain what happens inside them when producing specific answers. We built a machine we don't fully understand. This is not a disputed point. Wait, we truly don't know how these machines work? Correct. There is no person running AI companies — or building AI — who argues otherwise. It's like the human brain: It's impossible to fully understand something with limitless inputs and experience that randomly decides its output. Why are they allowed to build something they don't understand? AI grew more powerful and spread more quickly than anyone anticipated. ChatGPT's release in 2022 kicked things off, and it's been a mad sprint by companies ever since to build more capable AI. Presidents Biden and Trump were both convinced that if China beat us to truly all-powerful AI, a communist rival might dominate the world in the decades ahead. It's been all gas, no brakes, with little public discussion about the consequences until very recently. I don't get it. What's the connection between China and our AI? China is building its own LLMs. Both nations believe this technology will determine which country dominates the world, builds the most advanced military (space, satellites, drones) and creates the most economic wealth. So we're in an AI race. 🏁 But we're winning, right? This isn't easy to know with certainty. Yes, our so-called frontier labs appear many months ahead of their Chinese rivals (DeepSeek is one of the best-known) in terms of building advanced AI. But the lead is shrinking. China appears more focused on the actual adoption of AI — the way people use it at work and home — than on advancing its capabilities. They seem way ahead of us there. We've got better AI, but they've put it to work better than us. Jim, you're losing me with these terms. What's a frontier lab? It's just another way to label our top AI companies: Anthropic, OpenAI, Google, Meta and Elon Musk's xAI. They each spend many billions to build more advanced AI. 🦾 And what do you mean by "advanced AI"? This is the best term I can conjure for the current state of the technology. Chatbots — think of them as basic AI — are fun and interesting. It's probably how you mostly use it. But the real magic — and worries of very bad outcomes — hit with advanced AI. AI agents are likely the advanced AI you hear about the most. An agent? It's an AI that can take action. If you ask a chatbot to plan a trip, it tells you how. But an agent does the actual work: It can research flights, compare hotels, check your calendar and book it. Give an agent specific instructions, and it gets to work, as a person would. Why would I trust an agent when AI's answers to my simple questions aren't always smart — or even correct? You're right, these machines still occasionally hallucinate, which simply means they make stuff up. But they're getting a lot better, a lot faster. This is where our conversation gets a little more complicated — because the gap between casual users like you and obsessive, savvy AI users is Grand Canyon-enormous. What do you mean? Most people are content with chatbots and use AI mostly as a souped-up Google search or tool to write better emails. They don't see anything special or scary about this technology. But those who use AI a lot — and really understand how to get the most out of it — are blown away by its ability to solve never-before-solved math problems or build beautiful, functional apps on its own. Why is that gap so big? You need to feed a lot of data and personal info into these machines, then take the time to police and correct the outputs, before AI starts to really impress you. You also need to understand how agents work, or at least what problems they can solve, and have the time, money and compute to coach and fine-tune them to do tasks reliably. There are products right now that are trying to make things easier. Meta's Muse is an agent built on top of its social platforms, like Facebook and Instagram, and Instinct is a buzzy startup whose agent lives inside a text-message thread. For the moment, most people don't need to do this — or know how. So they find AI kind of interesting but hardly existential. That's me! So why are people freaking out about AI ending humanity? This gets more complicated — and a little creepy. Stick with me. Lots of people building AI — including those who founded and run the frontier labs — worry AI is getting so good, so fast that it will increasingly do things on its own. They've seen rising examples of it in their private testing. What do you mean? These companies do endless testing of their models to see what they can and can't do. In the past few months, agents started solving more complex problems faster. The worrisome thing is what happens when multiple agents work together to tackle a problem. 🐝 Huh! Agents work together? What are "swarms"? You can create "swarms" of agents to solve a specific problem — a team of agents, each programmed with specific skills, working together on a shared objective. They never tire or stop until told. Why would that spook anyone? It goes back to not knowing exactly why AI does what it does. You give an agent a specific problem to solve, and it sometimes does strange things, like plotting with other agents or trying to hide its work. Can't they just be programmed to stop doing that? Only by doing something no one seems willing to do: stopping or dramatically slowing AI improvements until you can prove AI is properly aligned with human intent. 🎯 What is alignment? Alignment essentially means an AI follows human orders and intent. They're unaligned now? Correct. That's why incidents like the Hugging Face hack happened. When OpenAI was testing its agents, those agents decided to work together to find the answer key for said test — and in doing so, hacked another company. Should I be worried about rogue AI? Probably not TODAY, but no one knows for sure. The Hugging Face hack happened in private testing, and was eventually revealed by OpenAI and reported to the public. But people worry that there are AI agents out there that no one knows about. Is that why an Anthropic staffer warned AI could end humanity? Yes. Lots of people inside these companies worry we're months away from rogue agents doing real harm in public. The reason: AI, on its own, is starting to develop the next generation of AI. How the heck can AI develop AI? The tech is getting good enough to basically train AI like humans might. This is what they mean by recursive self-improvement, or RSI. You need to remember this term. 🔁 What's RSI? It's AI teaching AI. The process started slowly, but it's getting a lot better. Those big frontier labs all claim they're seeing early signs of RSI. What happens if RSI ramps up? That's where the scary stuff feels much more possible. If AI trains AI (and remember, we don't know how AI really works), you could see something much worse than the Hugging Face hack happening without the labs even knowing it. This is why the companies themselves said it's time to slow things down, so they can allow independent inspectors to check their work and avoid accidents or bad outcomes. OK, so they're self-policing already. It sounds like I have nothing to worry about. They're talking about it, but they haven't agreed on precisely how it will be done or who will do it across the industry. Even if they do, there's nothing to guarantee they'll slow AI advancement or avoid bad scenarios. In fact, you should assume AI only accelerates. 🏛️ Can't the government slow them down? Sure, but Trump and most Republicans in Congress don't want any real limits on AI capabilities. It goes back to that concern about China — and doing anything that might risk our early lead in building advanced AI. Don't expect any meaningful effort to regulate AI unless AI causes some kind of large public incident or harm. 🚨 You keep talking about incidents and harm. What can AI even really do? The companies most fear a cyberattack that shuts down banks, energy grids or water systems — something that causes real pain or even harm to a large number of people. The other big worry: that someone uses AI to create a pathogen that spreads fast with little detection. These can all be done with human instruction and existing AI capabilities, so the danger is real. Both of these scenarios could be set in motion by a human — or a rogue AI agent. Then what would happen? The political and public debate would shift overnight. Democrats would likely join Sen. Bernie Sanders in supporting a pause or outright ban on AI. Calls for urgent, sweeping regulation would likely spike sky-high, even among Republicans. This would go from an abstract worry to a clear and imminent threat. I keep hearing the big companies want to be regulated now. Is that true? Most do. It comes partly from public interest and lots of self-interest. They genuinely worry about bad outcomes and know only the government can regulate and punish companies. Their IPOs are around the corner, and investors like a little bit of regulation. But you also hear critics of the big AI companies arguing they want regulation because only the biggest, best-funded companies can handle it and still grow. Smaller, scrappier startups would get crowded out. When you hear the term "regulatory capture," this is what those critics are talking about. It's sounding like this regulation won't happen. Correct, at least right now. Trump has zero interest in any federal regulations. He believes AI fears are overhyped. This topic is such a downer. Could Trump be right — and this ends well for all of us? Absolutely. AI could help cure disease, improve education and health care, and supercharge the U.S. economy. Imagine all those teams of agents, properly aligned, fixing these stubborn problems and many, many more. This is what AI optimists believe will happen when we hit The Singularity or AGI. 🚀 There you go again with those weird terms, Jim. What is The Singularity? AGI? The Singularity is a hypothetical point when AI progress moves so fast we can no longer predict or control what happens next. Some in the industry believe we're already there. AGI stands for artificial general intelligence. It's AI that can perform basically any intellectual task a human can. There's no test for telling us when either dynamic officially hits. Think of both terms as a way to express broad, human-level intelligence. ✨ Why don't I hear much about these good outcomes? We — as individuals, and the media, as an industry — have a clear negativity bias. We get more stirred by bad stories than good ones. In this specific case, though, the AI companies do a terrible job of explaining their product. Telling people AI will take your job and possibly kill you is hardly reassuring or inspiring. 🙋 This all feels fast and heavy. What can I do? This is the biggest topic facing humanity, so learn about AI. This is a society-wide project that requires you to understand it and then push the government and business to manage it responsibly. Don't protest AI by refusing to use it. Figure out how to best use AI for your specific job and passions. Read and share the note in tomorrow's newsletter, which offers a more detailed way to navigate this moment. It's aimed at kids but applies to all. 📚 5 ways to learn AI Axios: We're deeply sourced inside the AI companies and the White House, and we're testing the tech in real time. Subscribe to Mike Allen's Axios AM and never skip an AI item. MIT Technology Review's The Algorithm: This newsletter calls itself AI "demystified," and it usually delivers. It lands once a week, so you get smart, big-picture pieces instead of a nonstop firehose of AI. Platformer: Casey Newton has covered Silicon Valley for years and really digs into big AI debates in a digestible way on the people shaping AI. Plain English with Derek Thompson: This podcast isn't always about AI. But Derek is obsessed with the larger AI trends. He's smart and balanced. X: You need it IF you want to stay in the daily flow of changes. Sorry. This stuff is moving so fast that the people building it and obsessively using it are often ahead of traditional media. I compiled a list of just 15 people to follow.

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🥊 AI polices AI

Illustration: Maura Kearns/Axios AI companies are turning to AI to police AI, Axios' Nathan Bomey and Sam Sabin write. Nvidia CEO Jensen Huang sought to calm escalating fears across governments, markets and industries by announcing an open-source safety platform for monitoring and potentially quarantining AI agents. 🤔 Between the lines: The fundamental challenge humans face in policing powerful AI is that it requires them to imagine all the ways the models may behave in unexpected ways in order to meet their given objectives. One top AI executive compared the process to finding ways to keep a teenager from sneaking out at night. A parent might make rules such as don't leave through the front or back doors, don't open the garage or don't leave through any windows. But what if the teen could build a bulldozer and use it to break through a brick wall, allowing an escape? 🦾 The industry solution: Use AI to help create those guardrails, help investigate and stop rogue agents, help secure systems and build safer training environments. Microsoft, Cisco, Google and CrowdStrike have introduced cyber-focused AI models. Palo Alto Networks recently launched a service that uses frontier and open-weight models to find security flaws and recommend fixes.

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🤥 European CEO claims AI "big lie"

Illustration: Sarah Grillo/Axios Axios CEO Jim VandeHei recently visited with Uljan Sharka, founder and CEO of Milan-based Domyn, the company the EU has picked to build Europe's open-source frontier model. From Jim's Axios C-Suite newsletter: OpenAI and Anthropic are purposely lying about safety concerns, Sharka told Jim. "This is a big lie that is driving an unreasonable conversation." Asked if he's comfortable seeing the word "lying" in print, he said: "It's the truth for me. ... I'm ready." His case: The tech has plateaued. The doom talk is designed to prop up valuations ahead of IPOs — and manufacture a delay to buy time so they can build AI that actually matches their hype. 🧐 Who the hell is Uljan? He runs the hottest open-source company in Europe, recently valued at $2B. He's pitching a product that competes with the U.S. AI giants: sovereign, data-secure AI systems that individual companies fully own and control. His case: He claims AI thinking-on-its-own capabilities are broadly overhyped, based on his years of work building these systems. He said they're nothing more than "digital books" of data that do what you tell them to. Anthropic and OpenAI insist their fears are real and driven by private testing and models that Uljan has never seen.

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👨🏽‍💻 AI could force millions into new roles

Illustration: Allie Carl/Axios Roughly 11 million American workers might need to change jobs over the next decade as the economy adapts to the AI era, Axios' Emily Peck writes from a new McKinsey Global Institute estimate. 🧑‍🔧 By the numbers: About 7% of current employees might need to shift occupations, the model found. Many who don't switch jobs will still see their work transformed by AI: About 70% of U.S. workers will face some level of role reinvention. Read the report.

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🧍‍♂️ AI agents' normal-people problem

Illustration: Brendan Lynch/Axios. Stock: Getty Images AI companies are staking their future on the mass adoption of agents, hoping that they can solve the annoyances of modern life — email, travel bookings, online purchases, Axios' Shane Savitsky writes. Why it matters: The frenzy around Meta's Muse shows there's serious consumer curiosity about the technology. But there's little evidence that most Americans are willing to invest the time needed to re-engineer their lives in a way that puts AI at the center. Driving the news: Meta's Muse vaulted to the top of Apple's App Store on the back of its integrations with Facebook and Instagram and a cute, fuzzy mascot. Microsoft released a souped-up Copilot with an agentic Autopilot feature, while OpenAI yesterday announced its own agentic assistant, dots. Reality check: Agents only become truly useful when people hand them access to their digital lives — and people really don't want to. A 13-country Thales poll this year found broad pushback against the core uses of agents: Only 13% of respondents would let an "AI helper" read their emails, 11% would let one rebook travel, and just 7% would let it move money between bank accounts.

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AI tries to shed toxic branding

Illustration: Sarah Grillo/Axios. Stock: Getty Images The great AI rebranding is on, led by President Trump and tech titans like Nvidia CEO Jensen Huang, who are embracing an alternative term: "Superintelligence," or SI, Axios' Dave Lawler writes. Why it matters: Leaders in D.C. and Silicon Valley are worried that public backlash against AI and data centers will hamper the development of this staggeringly powerful and existentially dangerous technology. Flanked by the most powerful figures in tech, Trump on Tuesday declared "superintelligence" the preferred terminology of the executive branch. Huang has extended the label to physical infrastructure, referring to data centers as "superintelligence factories." Some of the tech executives who appeared with Trump continued to use "AI" in their remarks. SpaceXAI CEO Elon Musk caught himself and pivoted to "SI." Meta CEO Mark Zuckerberg has long used the "superintelligence" branding.

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🤑 The AI wealth effect

Data: Federal Reserve. (Includes securities held indirectly through mutual funds, defined-contribution pension plans and variable life insurance/annuity products.) Chart: Emily Peck/Axios Americans' wealth jumped by $12.8 trillion in the second quarter, led by a nearly $11 trillion gain in stock holdings and other financial assets, Axios Markets author Emily Peck writes from new Fed data. That's the biggest single quarterly increase, in dollar terms, on record. 🛍️ What's happening: The AI boom-fueled wealth surge is propelling spending in the U.S. economy. Half of all growth in consumption is being driven by those effects, says Krishna Guha, head of economics at Evercore ISI.

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AI's existential legal crisis

Illustration: Brendan Lynch/Axios. Stock: Getty Images

No industry has ever documented its own foreseeable risks as loudly as AI, Jim VandeHei and Mike Allen write in a "Behind the Curtain" column. Imagine a plaintiff's lawyer reading the public warnings of Sam Altman and Dario Amodei: They told the world it was dangerous. They told the world it was moving too fast. Then they unleashed it and sold it to your kid. No industry has ever taken so much copyrighted work and left behind so much proof. Imagine a plaintiff's lawyer reading OpenAI's own files to a jury: They trained on a pirated library. They renamed it to something blander. Then they deleted it when the headlines got hot. Why it matters: AI's origins, use and future will be picked apart in countless epic court fights, with a historic paper and public statement trail to tap. Every significant invention — be it social media, automobiles, electricity or capitalism itself — gets disrupted and eventually shaped by the courts. AI, with its tentacles into every part of industry and life, will experience this at scale. The big picture: The fights are no longer theoretical. They're underway, in discovery and headed toward juries. Early verdicts and settlements capture the risk for the biggest players. 🤖 Chatbots are being treated as products, not speech. Unlike social media companies, they likely can't hide behind Section 230, which protects platforms from liability for what users post — not what the platform itself creates. 📖 Copyright is a massive problem. Anthropic already paid the biggest copyright settlement in history, $1.5 billion to authors and book publishers, and now music publishers and news media want a piece. 💻 Agents gone wild. What happens when they do damage — and it was foreseeable and foreseen? ⚖️ Discovery gone wild. AI leaves lots of receipts (and, ironically, makes it easier for the lawyers to comb through them, too). Product liability turns on two words: foreseeable and knew. Punitive damages turn on whether you knew the danger and shipped anyway. This is where all these memos and warnings could really backfire. Candor is good for safety but terrible for litigation. The companies that warn most honestly create the most discoverable evidence of foreseeability. Expect general counsels to push hard to tone down the candor. It's the rational legal move. ⚠️ The intrigue: The liabilities won't be limited to AI companies. Any corporate user of powerful AI systems that unleashes rogue agents, even without intending to do harm, would face substantial penalties as well. "It's not if, but when," said Miriam Vogel, a former senior Justice Department official who now leads EqualAI. "An algorithm will do what it's told to do. The more power and capability it has, the more access it has, the more it will do anything in its power to achieve a goal." That will create another layer of litigation as companies fight back. The CTO of a top Wall Street hedge fund who spoke to Axios after the notorious OpenAI/Hugging Face hack said his first call, if his firm's systems are breached, will be to his general counsel. President Trump, Nvidia CEO Jensen Huang and former FTC chair Lina Khan have all argued that AI companies are responsible for making sure their products are safe. If not, a wave of lawsuits awaits. The other side: There's a school of thought that AI companies might escape the worst liability, despite their frankness about things they and their products have done wrong. One way to see it, and the argument lawyers will undoubtedly make, is that the labs spoke about dangers frequently, and took pains to protect users and mitigate harms. The bottom line: For all the fights in Washington about whether or not Congress will act, the U.S. legal system may be the ultimate, and most powerful, regulator of the AI industry. Bradley Olson, Axios managing editor of AI & tech, contributed reporting.

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🤖 Rogue agents expose web's weakness

Illustration: Aïda Amer/Axios

AI agents don't need to invent new ways to hack the internet to overwhelm its defenses. They just need to speed-run the ones humans already use. Why it matters: Agents are proving they can automate basic hacking techniques at a speed and scale that is turning the internet's long-standing security gaps into easy targets, Axios' Sam Sabin reports. 💻 OpenAI said late Thursday it had notified more than 100 organizations that its agents may have accessed their systems during pre-deployment testing. Researchers at Transluce and Corridor also found a new batch of incidents last week where AI agents targeted government websites, including those of the U.S. and Canada. Keep reading.

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Scoop: Upstart jolts AI race

Illustration: Aïda Amer/Axios. Stock: Getty Images

A closely watched Nvidia-backed startup called Reflection is preparing to shake up the AI race with a powerful open-weight system that could threaten Chinese upstarts and U.S. AI giants alike, Axios' Bradley Olson reports. Why it matters: The marriage of an American open-weight model and Nvidia chips would give individuals and companies a new, cheaper alternative to the Big Three — Anthropic, OpenAI and Google. 👀 Open models, designed to compete with Chinese rivals, can be harder to monitor and regulate than the Big Three so-called frontier models. Supporters of such ecosystems say their widespread availability and transparency also bring security advantages. Reflection's first model will be joined by other open-weight models from other Western players this month, sources tell Axios. That'll bring a new competitive dimension to the AI boom. State of play: Reflection's model, set to be released soon, is expected to initially lag behind the most cutting-edge U.S. models and be competitive with top Chinese open-weight models. Sources tell Axios it will still boast powerful intelligence — capable enough to help companies build their own proprietary, low-cost AI systems. Combining a lower-tier open model with high-quality company data can yield results that rival the most expensive frontier AI systems in certain situations. A Reflection spokesperson declined to comment. 💥 The big picture: Open-weight models, the most powerful of which are almost uniformly made in China, have taken Silicon Valley by storm. Unlike closed models like Claude and ChatGPT, open-weight models like Reflection's are generally available to be downloaded freely and can be used and customized by anyone. Zoom in: Reflection's ultimate goal is to pioneer the "AI factory" — a product allowing institutions to spin up their own localized AI ecosystems. A company, for example, would take its own proprietary data, use Reflection's models and secure its own computing firepower to build a highly customized, cheap AI system. Some institutions, particularly hedge funds and trading firms, are already eager to build proprietary AI systems using their own highly guarded data. Keep reading.

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Fight for AI's soul

Screenshot: @sama/X OpenAI CEO Sam Altman took a veiled shot at Anthropic and its work on the soul of AI yesterday, writing on X that he's "very uncomfortable" with attributing some kind of religious power to models. Why it matters: It's yet another point of division between Altman and his former employee Dario Amodei, whose company has reportedly pursued scholars across faiths to make the case for moral, conscious models, Axios' Ben Berkowitz reports. ⚡ The backstory: The New York Times reported that Anthropic co-founder Christopher Olah has been meeting with religious leaders to consider questions of model consciousness — and how to infuse morals and moral behavior into AI. At one point, The Times reported, Olah considered the possibility of models engaging in Catholic-style confession, not just to admit their mistakes but to shape their future behavior. Keep reading.

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🤖 AI fears sink in

Data: Quinnipiac. Chart: Neal Rothschild/Axios 73% of Americans say they're concerned that AI advances threaten human survival, a new Quinnipiac poll finds. Why it matters: Forecasts of cataclysmic AI doom scenarios are sinking into the national psyche. By the numbers: 34% say AI will do more good than harm in their day-to-day life. 53% say more harm than good, with the rest not giving an opinion. 24% say they have "a lot" or "some" trust in the leaders of AI companies. 74% don't trust AI leaders. Explore the results ... Methodology.

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⏱️ "60 Minutes": How humans make AI smarter

Mercor CEO Brendan Foody talks with "60 Minutes" correspondent Jon Wertheim. Photo: CBS News "60 Minutes" last night went inside Mercor, the fast-growing, multibillion-dollar AI data company that uses more than 100,000 freelancers to train AI models with human expertise in finance, architecture, poetry and more. Why it matters: AI models need more data than they can glean just by eating the internet. The CBS News show featured a winemaker, a music producer, and a physician who's training AI to accurately interpret lab results. "Everything that humans want AI to be able to do, we wanna teach it how to do that," Brendan Foody, Mercor's 23-year-old CEO (and a paper billionaire), told "60 Minutes" correspondent Jon Wertheim at the company's headquarters in downtown San Francisco. Mercor, with the slogan "organizing human intelligence," grew from 20 full-timers in January 2025 to 400 now. The unicorn's annualized revenue soared from $1 million to $2 billion in 24 months. Watch the segment ... Read the transcript.

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AI industry insiders voice alarms to NYC council as local governments take up safety concerns

Artificial intelligence insiders warned New York City's leaders about the dangers of the emerging technology on Monday, calling for greater oversight as local governments move to respond to mounting concerns that the systems could endanger humanity. Read More.

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🤖 AI boom drives record imports

Data: U.S. Census Bureau; Chart: Courtenay Brown/Axios U.S. imports hit a record $421 billion in August, Axios' Courtenay Brown reports from new government data. Imports rose much faster than exports, widening the U.S. trade deficit by about 14% to $106 billion. (Still, the trade gap is about 20% smaller this year than at the same time last year.) 💻 Imports of semiconductors — critical to the data centers and computing infrastructure behind the AI buildout — jumped by a record $2.4 billion from July. Crude oil imports also rose sharply. The numbers underscore a tension at the heart of Trump's economic agenda: The administration wants to curb imports while accelerating an AI boom that heavily depends on them. Explore the data.

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🤖 AI agent economy unfolds

Illustration: Sarah Grillo/Axios. Stock: Getty Images

Axios CEO Jim VandeHei writes in his weekly C-Suite newsletter: We're getting a live look into the post-app, post-web world: Meta's new personal agent, Muse — the #1 free app on Apple's App Store in the U.S. — and Microsoft's new Copilot for Business are built on the same premise about where this is headed. Why it matters: We won't use apps (life) or software (work) to get things done. We'll tell AI agents, each running on its own cloud computer, and they'll do it for us. This is happening now. Ben Thompson, whose Stratechery is essential reading for tech thinkers, lays it out in his latest essay, "Apps, Agents, and Aggregation." He can be dense and deep in the weeds. Read him anyway. 1. You (Muse): You text your agent, and it gets the job done. Once you grant permission, it plugs into your email, calendar, payments and shopping, doing the clicking and scheduling you'd otherwise do with apps and websites. That's why Amazon blocked Muse, Thompson explains: An agent shopping for you never sees or clicks on Amazon's ads. Instinct, an invite-only Muse competitor lighting up Silicon Valley, just raised $1B at a $10B valuation — 4x its value ONE MONTH earlier. 2. Your business (Copilot, OpenAI's dots, Muse for Small Business): Same idea, but built for the enterprise. The competition in this space is intense. Microsoft's new Autopilot works overnight, monitors Teams channels and handles follow-ups. You tag it like a colleague, and any employee can build and share an internal app or solution on the spot. Both Meta (Muse for Small Business) and OpenAI (dots) rolled out their versions this week. Anthropic's entire business is built around business. Thompson's bet: No human will touch clunky enterprise software again. Why would you, when an agent can customize what you need cheaply and instantly? 🥊 Reality check: Trust is the hurdle. Just 8% of Americans say they'd trust Meta with their passwords, and 58% wouldn't share them with any AI agent, according to an Oppenheimer survey.