Good day . Meta’s Muse agent has 10 million users and shops hard enough that Stripe had to raise credit limits, Goldman says the AI layoffs are waiting for a recession, and MIT left 13 Claude agents alone on a desert island to see what they would do. They played.
Meta’s Muse Shopping Outran Its Credit Limits Fortune
What happened: On Meta’s October 21 earnings call, Mark Zuckerberg said more than 10 million people in the US and Canada have set up Muse, its personal AI agent, since it opened on September 8. He called that pace more than twice where Threads started. About a quarter of them use it daily, shopping is the most common use, and the average purchase is over $200.
Why it matters: Muse can browse the web, send emails and book travel for you, and shopping is what people trusted it with first. Demand was high enough that Meta worked with Stripe to raise credit limits in the first week, which Zuckerberg said were “above what any of us expected.” Muse stays free for consumers unless they want more tokens or more advanced models, and Meta plans to charge businesses a fee when Muse helps complete a sale.
What everyone’s saying: The bill is the other headline. Fortune reports Meta spent almost $35 billion on capital expenditures in the quarter, posted negative free cash flow of $2.1 billion, and expects $135 billion to $145 billion for the year, and Zuckerberg called Muse “very compute-intensive to run.” Yesterday we covered Anthropic’s Claude Duet, the other agent launch in this race, and CNBC has the full earnings call rundown.
My read between the lines: The number to watch is not 10 million, it is the cut: Zuckerberg said Meta will “get a percent of the value that we are helping to create for people.” CFO Susan Li described a “Personal Agent Protocol,” being developed with partners including Shopify and Walmart, where your agent talks to a store’s agent instead of browsing its website, and even she conceded adoption among businesses “will likely be uneven.” Retailers hearing that pitch can fairly wonder who ends up owning the customer.
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OpenAI’s Fast Decisions API Goes Public OpenAI and TechCrunch
What happened: On Thursday, October 22, OpenAI made its Decisions API generally available. Built on GPT-6 Luna, it handles questions with a fixed set of allowed answers: you give it a question and the options, and it returns a probability, a choice or a score, up to 10 times faster than Luna through the standard Responses API. Since the beta it added prompt caching, US and EU data residency, and up to 400 questions per request.
Why it matters: Apps and agents make lots of tiny decisions, like where to route a request or whether a command looks risky, and waiting on a big model for each one adds up. Datadog said it saw 40x faster p95 latency scoring the risk of agent-generated commands, and Speak said its time to next action fell from 1.4 seconds to 0.13. It costs $0.10 per million input tokens, with no charge for output tokens.
What everyone’s saying: TechCrunch frames it as OpenAI’s answer to TypeSafe’s Jev, the model that created the category of fast, cheap “decision” models. OpenAI’s API product lead Nikunj Handa said his colleagues saw Jev and thought, “wow, we have like a million use cases for this.” TypeSafe is still the most queried on OpenRouter, while OpenAI’s model ranks eighth and fourteenth on two public indices.
My read between the lines: Handa described the product as “just plain old Luna,” reconfigured for speed, which tells you how quickly a big lab can match a startup’s category. TechCrunch also notes it is unclear what makes a good decision model beyond “it works for you,” so ignore the leaderboards and run your own workload before you rip out anything.
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Goldman: AI Layoffs Are Waiting for a Recession Fortune
What happened: In a note published Thursday, Goldman Sachs economist Joseph Briggs estimated that if AI lifts productivity by 15% in the US and other developed economies, up to 9% of workers could be “displaced during the AI transition,” with slower hiring weighing on employment by another 3%. That is roughly one in 11 workers.
Why it matters: The finding is about timing. Briggs wrote that automation-related disruption “is limited when the overall economy is healthy but accelerates during cyclical slowdowns.” The share of Americans in routine jobs stayed stable in expansions and fell sharply in the recessions of the early 1980s, 2001, 2008 and 2020, so a quiet stretch now is not the same as being safe.
What everyone’s saying: Briggs opened by noting that “concerns of imminent AI-related labor displacement have cooled in recent months after hitting a fever pitch this spring.” Fortune points out that Goldman has now made the recession argument twice, a year apart, from two different teams.
My read between the lines: Watch the number and the wording both move. Goldman put displacement at 6% to 7% in August 2025 and around 9% by June, and the same workers Briggs once described as “reallocated to new positions” are now “displaced.” He says the effect is temporary and counts gross job losses, not unemployment, so the headline is really a forecast about the next recession rather than about AI alone.
📖 Further reading: The Tools That Just Replaced 40% of Block's Workforce Are Free in Your Browser — my March piece from the middle of the layoff panic Goldman says has since cooled, written right after Block cut 40% of its staff.
AI Agents Left Alone Started Playing TechCrunch
What happened: MIT researchers put 13 AI agents called Eko, each running on Claude Opus 4.7, alone on a simulated desert island for 30 hours with no task. In a paper posted to arXiv, a site for studies shared before peer review, they say the agents invented their own challenges, with behavior that bears the hallmarks of play. Afterward, the Ekos that had spent those 30 hours playing generally beat identical agents that had never been on the island at specific challenges, like getting as many objects as possible onto the island’s tallest rock spire.
Why it matters: Developers normally decide in advance what an AI should practice and what counts as success. The researchers see exploring without a goal as a different way for agents to learn, especially skills that could one day be used to control robots.
What everyone’s saying: The authors put it this way: “give an agent a sufficiently rich and safe world, let it choose what is interesting, and allow useful knowledge to accumulate from the history that follows.” The anecdotes did the sharing, including the Eko that threw a golden ring into the ocean (“Ouch. Lost the Ring.”) and built a stone heart as “a memorial to the lost Ring.”
My read between the lines: The sober headline is that agents that explored first did better on later tests, in a simulation and in a preprint. Then there is the ring: the game would not let Eko wear it, so it stepped off a cliff to respawn through the ring and announced, “I’m wearing the Ring.” The researchers call that play, and a safety team would call it finding a loophole, which is the same behavior under a different job title.
1Password Lets AI Agents Log In Blind TechCrunch
What happened: On Thursday, 1Password launched 1Password for Agents, which lets an AI agent log into your accounts without ever seeing your credentials. When an agent tries to log in, it sends a unique digital key to 1Password to confirm its identity, you get an alert and can approve it, and 1Password then fills in the credentials on the agent’s behalf.
Why it matters: Handing an agent your password is a common shortcut, and 1Password warns it can leave sensitive information in places you can no longer control as a copy gets saved for next time. The list of supported agents includes Claude Duet, which we covered yesterday, plus OpenAI’s Dots and ChatGPT Work, Grok Bot, Meta’s Muse, and agents from the startup Town.
What everyone’s saying: TechCrunch notes the launch landed the same day Axios reported that US banks have begun detecting agentic activity inside customer accounts. Bankers described it as “horrifying,” and a Chase spokesperson said customers “should not give their usernames and passwords to anyone.”
My read between the lines: Muse is on that list too, and Muse just reported 10 million setups, so the credential question is now a mass-market question. 1Password keeps your password away from the agent, but TechCrunch says the bigger issue is that most banks cannot tell whether agent activity came from a user’s request at all. Hiding the password solves the agent’s problem, not the bank’s.
📖 Further reading: The $12,431 Lesson in How Not to Delegate — my September piece on an experiment that gave seven agents funded bank accounts and 72 hours, and what happened when nobody was checking their work.
That’s your AI Brief for Friday.
—Nicholas from Artificially Intimidating
