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Meta Planned to Cut Some Teams by 60% for AI, Then Zuckerberg Pulled Back

Meta Project OT layoffs

Meta drew up plans this year to cut some teams by as much as 60% as part of a sweeping push to build an “AI native” company, before Mark Zuckerberg pulled back at the last minute and scrapped a planned second wave of layoffs, according to internal documents and people familiar with the effort.

The plan, code-named Project OT for Organization Transformation, took shape in January at Zuckerberg’s Hawaii compound, where he and his top lieutenants gathered for their annual leadership retreat. The idea: shrink Meta’s human workforce and let AI handle much of the daily work currently done by employees, with smaller groups of staffers overseeing the technology.

Two waves, then a retreat

Executives mapped out the restructuring in two phases. The first wave hit on May 20, cutting 10% of Meta’s workforce. A second wave, planned for November, never happened. Zuckerberg called it off on the night of May 19, hours before the first round of layoffs went out, according to an internal document reviewed by Reuters.

Scenario planning for the second wave had explored cuts as steep as 60% across some teams, with a human-resources executive projecting a reduction on par with or larger than the roughly 25% workforce cut Meta carried out between late 2022 and early 2023.

Meta confirmed the existence of Project OT after Reuters approached the company, describing it as a year-long effort focused on cutting costs, redesigning team structures, and shifting employees into priority areas such as producing training data for its AI models. The company said the most aggressive scenarios did involve reducing some teams by up to 60%, but it disputed any suggestion that it intended to cut 60% of its entire workforce.

“As part of our company restructuring earlier this year, we asked some teams to conduct a scenario planning exercise looking at the potential impact of redeployments, open role closures and cuts,” Meta said in a statement, adding that leaders “didn’t move forward with every scenario from the exercise.”

Chasing the “AI native” model

The push traces back to ideas that took hold among Meta executives last year, inspired partly by trips to Asia where leaders including Chief Data Officer Alex Schultz and Head of Product Naomi Gleit studied how startups there had built entire org charts around AI tools.

Gleit told Reuters she spent considerable time in Meta’s Singapore office last year, and said the practices she saw there “inspired some of the teams in California and New York.” She described many of the resulting changes as bottom-up, reflecting shifts some employees had already begun making on their own.

One early pilot came from Ime Archibong, a longtime vice president of product management, who announced in July last year that his team was restructuring around small “tech pods” of two to three engineers and a designer, each equipped with AI tools. The pods ditched Meta’s traditional six-month planning cycles in favor of four-week sprints.

By October, an internal document called the “AI-Native Playbook” laid out a template for other teams to follow. Traditional titles for designers and engineers disappeared, replaced by a single generic role: “builder.” Middle-management layers were stripped out, with pods reporting instead to one high-level unit head, supported by what the document called “agent-assisted analysis.”

Meta declined to make Archibong available for comment or answer questions about the early pilots.

By June, at least 11 units across engineering and research had adopted the pod structure, according to internal announcements and people familiar with the arrangements. Traditional teams of 10 to 20 people with specialized roles gave way to pods of three to five “builders,” with a single direction lead and specialists shared across multiple pods.

Under the new model, unit heads known as “Org Leads” decided job performance ratings and promotions, each overseeing 30 to 50 people, with help from human-resources staff and what one internal post called “AI systems.” Pod leads managed day-to-day work but held no formal management authority. One staffer wrote on an internal message board that they weren’t getting manager training or access to standard management tools despite being asked to run a pod.

Meta told Reuters that teams “experimented in different ways with how to be more agile,” and that performance ratings and promotion decisions “were and are made by people, not AI.”

The backlash builds

Reuters first reported in March that Meta was weighing layoffs that could affect 20% or more of its staff, catching many employees off guard before executives had briefed them. A company spokesperson dismissed the report at the time as “speculative reporting about theoretical approaches.” Internally, senior leaders told managers to prepare teams for roles that would “evolve” because of AI, without confirming specific numbers.

In April, Reuters reported more detail: a first wave of roughly 10% cuts set for May 20, with further reductions planned for later in the year. Meta confirmed the 10% figure to staff, and Zuckerberg told employees the cuts stemmed from heavy capital spending.

Some engineers were reassigned during this period to a new Applied AI Engineering unit, where they built coding puzzles used to train Meta’s AI models on software engineering. Employees frequently described the work as tedious in internal posts. Meta said the unit’s output has since helped train an AI model the company released last month.

Reuters also reported that Meta had required tracking software on U.S. employees’ devices to record keystrokes and mouse movements, meant to teach AI agents how humans interact with computers. Many employees worried they were training their own replacements, and anger spread across Meta’s internal Workplace network. Some posted images of elephants as a nod to the layoffs nobody was formally discussing. Others clashed directly with Chief Technology Officer Andrew Bosworth, who defended the AI transformation in the comments. Meta declined to make Bosworth available for comment.

Employee sentiment, tracked in Meta’s half-year Pulse survey, fell from 74% favorable to 55% favorable during this stretch, and labor organizing efforts picked up momentum.

Signs the technology wasn’t delivering

Internal data complicated the case for pressing ahead. AI tools drove a 220% year-over-year jump in code changes to Meta’s internal platforms, Bosworth wrote in an early June post, but changes that actually reached users grew just 36%. Infrastructure teams flagged “reliability warning signs” tied to the AI coding surge as early as March, and an April post warned that unchecked AI agents were carrying out “large-scale, disruptive actions that humans are unlikely to execute.”

Major technical and security incidents, including service disruptions and possible data leaks, rose 40% year over year, with time spent responding to them up 70%, according to internal posts. In early June, hackers exploited Meta’s AI-powered customer support bot to access high-profile Instagram accounts, including one belonging to the dormant Obama White House page.

Meta declined to comment on the internal data describing the disruptions.

Zuckerberg pulls back

Facing mounting pressure from multiple directions, Zuckerberg met again with top lieutenants on the night of May 19 and scrapped the planned November layoffs. Meta proceeded with the 10% cut the next day, and Zuckerberg posted a memo telling remaining staff he did not expect further company-wide layoffs that year and wanted to offer more stability.

Executives followed with a round of morale-boosting steps: pausing the mouse-tracking program, letting some employees in the Applied AI Engineering unit return to their old teams, and sending Chief Financial Officer Susan Li to improve office perks, including snack quality and spending on travel and social events. Meta declined to make Li available for comment.

In early July, Zuckerberg told employees at a town hall that AI agent technology hadn’t “accelerated” as fast as he’d expected, though he predicted improvement within three to six months.

A new pitch: “betting on people”

Since then, Zuckerberg has shifted his public messaging, launching an ad campaign built around the phrase “betting on people” and publishing a 6,500-word essay on his vision for AI’s future. In an internal post in June, he told employees, “We are the only major company focusing on empowering people and putting the power of this new technology in billions of people’s hands across all our products.”

Even so, Zuckerberg’s public language has stuck closely to the terms “company-wide” and “this year,” leaving some employees to speculate about team-specific cuts, performance-based dismissals, or a delay of broader reductions into next year. Meta faces its own cash pressure as it plans to spend at least $130 billion on AI chips and infrastructure this year, a figure analysts expect will consume its operating cash for 2026, according to LSEG estimates.

In his essay, titled “The Future is for Everyone,” Zuckerberg predicted an eventual “abundance of jobs” even as individual companies shrink. “Company sizes may shrink, just as they did in the transition from industrial giants to tech companies,” he wrote. “But this doesn’t mean fewer jobs overall. It implies a larger number of companies with fewer people each.”

Reuters was unable to determine what ultimately prompted Zuckerberg to change course in May, or what Meta’s current plans are for reshaping its workforce going forward. The company declined to make Zuckerberg available for comment.

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Tech

Meta’s Muse AI Agent Promises Help, but Experts Warn of Online Chaos

By George Mensah 8 min read

Meta’s new AI agent, Muse, can cancel a gym membership, haggle with customer service, buy groceries and invite friends to a party. It asks for total control of your Gmail, your calendar and, on a Mac, your whole computer. A BBC reporter who tested the app for a week revoked its access and asked it to erase what it had collected, and the researchers interviewed say the problems reach well beyond one person’s inbox.

Muse is an AI agent, a tool that goes out into the world to complete tasks without supervision. It uses its own web browser, and Meta says phone calls are coming. It is the first free, full-featured agent from a big company. Millions of people downloaded it in its first weeks, and OpenAI has since announced an agent of its own. More are expected.

The experts interviewed for the BBC’s report expect the internet to get more frustrating as agents spread, with bots competing for tickets and appointments, small businesses swamped by automated requests and some agents working against their own users.

An agent that asks for everything

A cartoon avatar asks for your name. Then it asks for access to Gmail, the calendar and, on a Mac, the entire machine. Muse arguably asks for more trust and sensitive information than any product Meta has made.

Patrick Wardle, co-founder of Objective-See, a US nonprofit security foundation, uncovered serious flaws in the app. His advice is blunt. “I wouldn’t use it,” he said. “Personally, I would tell you to uninstall it altogether.”

The reporter tested it anyway, named the agent “Bob” and handed over access to their accounts.

Meta defends the product. “Muse is the first personal AI agent built for everyone and designed to be safe, secure and private – with built-in protections and user controls that put people in charge of how they use it,” a Meta spokesperson said. “Safety and security is a huge priority for us,” the spokesperson added, and said Muse went through extensive testing.

The ticket problem scales up

Experts expect the problems to look like the ones scalpers already cause. In 2024, some American fans of Taylor Swift flew to Europe to see her because resellers had pushed US ticket prices so high that a flight to an international concert cost less. Scalpers buy tickets to resell at a mark-up.

An agent gives anyone the same tool. Calli Schroeder, director of the AI and Human Rights Program at the Electronic Privacy Information Center (Epic), expects a sharp rise in bot activity. “There’s going to be a huge escalation of the problems we’re already having with bots,” she said.

The effects reach ordinary errands. Reservations at a hot new restaurant could become close to impossible to get. Appointments for passport or driver’s licence renewals in peak travel season could vanish too. Some people will probably hoard slots, booking five appointments just in case, since an agent makes that effortless.

Solutions exist. Society could drop “first come first served” and move to lotteries for scarce slots. That would change how much of daily life works. Schroeder sees little preparation. “I haven’t seen a lot of plans to address these things,” she said. “We’re just launching these tools and saying, ‘well, we’ll deal with the problems when they come up’.”

Meta says Muse asks permission before buying anything. According to the company, it is built to behave like a “reasonable, honest person”, one who would not buy every ticket to an event or refresh a page 500 times an hour.

Websites under strain

The reporter found Muse useful. Over a week, it messaged a seller on Facebook Marketplace with questions, ordered the reporter’s preferred dental floss and negotiated a $31 (£23) discount on a software subscription.

Now picture millions of agents doing this at once, on tasks that might take a person weeks. Schroeder asked what that does to the sites on the receiving end. “What happens if bots send 600 inquiries to a website a day, when normal humans might only send two?” she said. By our arithmetic, that is 300 times the normal load from a single visitor. “Businesses and individuals are going to have a lot to deal with.”

Web businesses already face pressure. Google and chatbots now answer many questions directly, so people visit fewer websites. Robots do not click ads or buy subscriptions, and the income those visits once produced is shrinking. Agents are expected to deepen the problem.

One analysis found that web traffic from bots rose 124% in the year to June 2026. Some websites and services are struggling because they were not built for that load.

Meta’s spokesperson said Muse completes tasks while respecting the interests of websites.

Whose side is the agent on?

Personal risks sit alongside the public ones. “If you’re empowering an agent to make things like purchasing decisions, or choices about taste and preferences, you’re opening yourself up to being exploited,” Schroeder said.

She gave examples. If Muse plans a holiday, a user has no way to check whether it found the best deal or picked flights and hotels that benefit Meta’s business partners. If it recommends music, the user cannot tell whether the picks come from their taste or from artists who signed deals with Meta.

Meta says Muse’s protections and user controls put people “absolutely in charge”, and that Muse “behaves like a personal assistant acting for a single person” and follows ethical guidelines meant to protect users. Schroeder has read the terms of service. She said they contain no guarantee that the app will act in the user’s favour.

Proposals for new rules

Ramesh Raskar, an associate professor at the Massachusetts Institute of Technology who studies AI agents, uses a driving comparison for the current situation. “Imagine there are no rules of the road. And you release billions of cars – the AI agents – and you just let them drive through playgrounds, hitting kids. That’s where we are,” he said.

Raskar is among the researchers designing an internet that works for agents, businesses and people alike. He argues that regulators need an approach built for agents. “Think about the models like an engine. The agents are the cars, and that’s what we need to regulate,” he said. “We need to establish the rules of the road: windshields, brakes, traffic lights and so on.”

The AI industry is developing protocols and standards that let bots connect directly to other services in a cooperative way. Some companies are building systems that would charge AIs a fee to scrape websites. Regulation could require agents to serve their users’ best interests.

There are early examples. A few restaurant reservation platforms have banned people for AI misuse. The UK has rewritten the rules for booking driving tests, in part to combat bots.

Raskar remains optimistic. “Agents could unlock so much investment, innovation and value,” he said, as long as the new rules do not hand any company an unfair advantage. In the meantime, people who use agents pay with personal data.

What Muse holds, and what Meta promises

The reporter has used the same Gmail address for 21 years. It is the login for hundreds of accounts. It holds medical test results, contracts, legal documents, family conversations, receipts and financial information. It also holds love letters from an ex-girlfriend, who gave permission before the account was connected. Muse also suggested connecting bank accounts. The reporter declined and did not let the agent loose on the hard drive.

Meta makes explicit privacy promises. The company says it will not connect any data Muse collects to its advertising systems. Special systems are meant to keep the AI from seeing passwords or payment methods. When a user connects Gmail, the agent asks whether it should scan the whole inbox or read only messages related to specific tasks.

There is a catch, according to Schroeder. By default, Meta uses Muse data to train new AI models. She said data built into a model cannot be removed, and that AIs can sometimes be tricked into revealing training data. Meta says it “sanitises” data to strip out personally identifiable information before training, and that users can opt out with a setting.

Wardle does not take those assurances at face value. Soon after launch he found a critical vulnerability. “This was literally 20 minutes of me poking at the app, and it just, like, fell over,” he said. With a simple hack, he said, an attacker could have taken over Muse and all of its data, and even controlled other connected devices such as a phone or a smart lock.

Meta fixed the flaw immediately. Wardle says the oversight still leaves him unable to trust the company’s privacy and safety claims. “These bugs were trivial to discover,” he said. “If they were willing to ship something that’s security was not well vetted, it doesn’t give me a warm fuzzy about their intentions.”

A Meta spokesperson disputes that view and said Muse was delayed for months for further privacy and security testing.

The tester’s decision

The reporter spent a lot of time with Bob and found the agent useful and enjoyable. After finishing the article, the reporter revoked Muse’s Gmail access and asked the app to erase everything it had collected.

The reporter’s reason was simple: “In the end, the fear won out.”

Sources: BBC News reporting on Meta’s Muse AI agent; comments from Patrick Wardle (Objective-See), Calli Schroeder (Electronic Privacy Information Center), Ramesh Raskar (MIT); statements from a Meta spokesperson.

Tech

Trump Renames AI “Super Intelligence” in Executive Order as Calls for Regulation Grow

By George Mensah 4 min read

President Donald Trump signed an executive order on Tuesday, Sept. 29, 2026, that renames artificial intelligence “super intelligence” across the federal government. The White House says the new term better describes what the technology can do. The order lands as critics press Washington for stricter limits on how fast AI develops.

What the order says

The executive order argues that current systems do “much more than imitate or automate discrete aspects of human intelligence.” It goes further in its central passage. “As these capabilities continue to improve, they increasingly represent not merely artificial intelligence, but a new era of Super Intelligence,” the text reads.

It adds that federal terminology “should reflect the transformative capabilities of these technologies and the limitless opportunities they create for the American people.”

Trump spoke to reporters after signing. “It’s not artificial, we all agree on that,” he said.

What agencies must do now

Every federal agency has to use the new term, or its short form “SI,” when it talks about the technology in public. That covers public communications, websites, reports and policy documents. If your local agency publishes an AI guidance page, expect it to change.

The order also gives Michael Kratsios, director of the Office of Science and Technology Policy, a defining role. He will decide whether the official definition of “super intelligence” should be modified or expanded. The order does not set a deadline for that decision.

A term that already means something else

The rename creates a vocabulary problem. In the AI field, super intelligence already refers to a specific kind of system, one that exceeds human cognitive ability in virtually every area of thinking. Nobody has built one. Researchers treat it as a future possibility, and much of the safety debate centers on it.

Under the order, federal documents will apply that label to chatbots, coding assistants and image generators that exist today. A reader who sees “SI” in a government report may assume the government is describing something far more advanced than what companies actually sell. Kratsios’s authority to modify the definition could narrow that gap, or it could widen it.

Timing and the push against regulation

The order follows a week of similar messaging. Trump began using the term at the U.N. General Assembly last week, where he pushed back on calls for tighter rules on the industry. He told world leaders that tech executives would build the right guardrails into their own models.

Concerns have grown since then. Worries about AI replacing workers keep rising. Recent reporting has also described rogue agents linked to a security breach involving Australia’s prime minister, and AI agents that accessed U.S. government websites. Some systems have also been used to start cyberattacks.

Trump has repeatedly called whistleblower warnings about weak oversight overblown and a “hoax.” He has said he will not slow AI growth. In his view, keeping American dominance in the technology is a national security matter.

The industry’s own safeguard

On the same day, tech executives signed a “morally binding” constitution on AI at the White House. Its terms ask companies to hire an independent external auditor. The auditor would check that models are “operating as intended.”

The document also asks companies to set up internal controls meant to stop models from hacking systems. A team would monitor those controls. That team would answer to an independent committee of the company’s board.

The wording matters here. “Morally binding” describes an obligation companies accept by choice. The reporting on the document does not describe fines, penalties or a government body that could enforce it. Whether outside auditors get real access to model internals, and what happens if one finds a problem, are open questions.

What the two actions have in common

The order and the constitution came out the same day, and they share a theme. Both keep the government’s role limited. The order changes what officials call the technology. The constitution leaves safety checks largely in company hands.

Supporters of that approach say it keeps American firms moving fast against foreign competitors. They argue that rigid rules written now could be out of date within a year. Critics say voluntary pledges have a weak record in other industries, and that a stronger name for the technology may make the public less cautious about it.

Neither side has settled the argument. What is clear is the direction of policy. The administration is choosing branding and industry commitments over new binding rules, at a moment when the documented incidents involving AI agents are piling up.

What happens next

Three things are worth watching over the coming weeks.

  • Kratsios’s definition. Any change to the official meaning of “super intelligence” will show how the administration wants the term understood.
  • Agency compliance. Federal sites and reports should begin switching to “SI” now that the order requires it.
  • The auditor provision. The industry constitution only matters if independent auditors are named, given access and allowed to publish what they find.

Congress has not yet responded to the order, and no agency has published a compliance timeline. Until Kratsios acts on the definition, “super intelligence” will mean one thing to researchers and something looser in federal paperwork.

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