If it feels like Meta has been in the news a lot lately, you’re not imagining things. Just weeks after unveiling Meta Superintelligence Labs (MSL), the tech giant is restructuring again, carving the new division into four separate teams and placing a hard stop on all hiring, per the Wall Street Journal. 

It’s the latest twist in what has been nothing short of a whirlwind summer for Meta’s artificial intelligence operations. MSL was billed as a moonshot — an ambitious bid to deliver “personal superintelligence” that surpasses human intelligence in every way. To get there, the company embarked on an aggressive hiring spree, shelling out massive signing bonuses to lure top talent away from rivals like OpenAI and Google DeepMind. It also brought on heavy-hitters like former GitHub CEO Nat Friedman and Alexandr Wang, who joined in June after Meta entered into a $14 billion deal to invest in his company Scale AI. 

But the road has been far from smooth. Meta’s new Llama 4 language models landed with a thud back in April, reportedly prompting CEO Mark Zuckerberg to “handpick” MSL’s team himself. And tensions have started mounting between the new hires and Meta’s veteran AI researchers, some of whom have threatened to quit (a few are already gone).

“This is not a sign of being lost, it is a sign of being intentional. The reality is this technology is still relatively new, and even the biggest players are learning in real time how best to deploy it.”

Now, with news of yet another massive reorg and total hiring freeze, it’s tempting to read Meta’s moves as signs of panic, a scramble to stay relevant in an AI arms race it was already losing. But the shake-up may also be part of a much larger strategy. It’s the messy reality of a company willing to upend itself in pursuit of what is shaping up to be the most consequential technology of our lifetimes.

“Meta is entering a new phase of its AI push. They went full steam on hiring the top talent they wanted, and now the focus is on figuring out how those people and teams fit together,” Luke Pierce, founder of Boom Automations, told Built In. “This is not a sign of being lost, it is a sign of being intentional. The reality is this technology is still relatively new, and even the biggest players are learning in real time how best to deploy it.”

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What We Know About Meta’s AI Restructure

According to a since-leaked internal memo written by Wang, who is now Meta’s Chief AI Officer, the company organizing its AI efforts into four dedicated teams — all of which are housed under the umbrella of Meta Superintelligence Labs:

1. TBD Lab: A small team headed by Wang that is focused on training and scaling Meta’s largest models, with the ultimate goal of achieving superintelligence.
2. FAIR (Fundamental AI Research): Meta’s long-standing AI research arm led by Director of AI Research Rob Fergus and Chief Scientist Yann LeCun.
3. Products and Applied Research: Headed by former GitHub CEO Nat Friedman, this team is in charge of weaving Meta’s Llama models and other AI research into its consumer products.
4. MSL Infrastructure (Infra): Led by former VP of engineering Aparna Ramini and former AGI Foundations head Amir Frenkel, this team is responsible for the infrastructure (GPUs, data centers) needed to power Meta’s AI research and development.

Wang’s memo also revealed the following:

• TBD Lab and FAIR will work together on research: FAIR will serve as an “innovation engine” for MSL, feeding its research directly into TBD Lab’s training runs. This is a major shift for FAIR, which has always functioned more like an independent academic lab than a tightly integrated part of Meta.
• TBD Lab is exploring an “omni” model: TBD’s work will involve exploring “new directions,” potentially including an “omni model.” While the memo does not explain what exactly an “omni model” is, it would likely operate similarly to a multimodal system that would handle text, visual, audio and other data types — which makes sense given MSL’s recent hires in those areas.
• Meta is dissolving AGI Foundations: Born out of Meta’s old GenAI division, AGI Foundations was created in May to continue developing the Llama language models. But the team drew criticism from executives after Llama 4’s lukewarm reception. Now, its members will be dispersed across MSL’s product, infrastructure and FAIR divisions. Notably, TBD was not mentioned as a destination for ex-AGI Foundation members.
• Almost everyone reports to Wang: FAIR heads Rob Fergus and Yann LeCun will report to Wang. As will MSL Infra leads Aparna Ramini and Amir Frenkel. The same goes for Nat Friedman, head of Products and Applied Research, which is interesting given that Friedman was originally positioned as leading MSL alongside Wang, not reporting to him. The only person not mentioned as reporting to Wang is ChatGPT co-creator Shengjia Zhao, who is now MSL’s chief research scientist.

This marks the fourth overhaul of Meta’s AI operations in less than six months, raising doubts about whether all this reshuffling will be enough to propel the company to the forefront of the industry — especially given that most other key players have managed to sustain far greater organizational stability over the years. But Wang seems confident.

“I recognize that org changes can be disruptive,” he said in the memo. “But I truly believe that taking the time to get this structure right now will allow us to reach superintelligence with more velocity over the long term.”

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What We Know About Meta’s Hiring Freeze

Meta imposed its hiring freeze on MSL around the same time as the restructure, halting both external hires and internal transfers unless they’ve been personally approved by Wang, according to the Wall Street Journal. The company has not said how long the freeze will last.

The pause comes after a months-long hiring spree led largely by Zuckerberg himself. As of mid-August, Meta has poached more than 50 AI researchers and engineers, including more than 20 from OpenAI, at least 13 from Google, three from Apple, three from Elon Musk’s xAI and two from Anthropic, the WSJ, reports. Now, the New York Times says Wang and the team he and Zuckerberg assembled are scrapping Meta’s old frontier model, Behemoth, and starting anew. They’re also considering making this new model “closed,” a sharp break from the company’s long-standing practice of open-sourcing its model weights. The shift has reportedly intensified tensions between these newcomers and the old guard.

Internal squabbles aside, this influx of fresh talent has also cost Meta a fortune. Several of the new researchers received nine-figure pay packages to come aboard, and the company even offered to buy a stake in Nat Friedman’s venture firm to woo him and co-founder Daniel Gross. Zuckerberg reportedly offered Thinking Machines Lab co-founder Andrew Tulloch $1.5 billion to join, but Tulloch turned it down. During an investor call in July, Meta said its capital expenditures could be as much as $72 billion in 2025, with the bulk of it going toward building new data centers and hiring researchers. 

Now, the company seems to be pumping the brakes. The Wall Street Journal says a Meta spokesperson characterized the hiring freeze as “basic organizational planning” — a way to build a “solid structure” for its superintelligence efforts after a surge of hiring and “yearly budgeting and planning exercises.”

“The freeze is less about saving money, and more about pausing the game of musical chairs,” Cat Valverde, founder of Enterprise AI Solutions, told Built In. “When you’ve restructured four times in six months, throwing new hires into that chaos just compounds the mess. My read is that Meta wants to stabilize reporting lines, prove the new org design actually works and only then start layering on fresh talent.”

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What Does All of This Mean for the AI Industry?

News of MSL’s restructure and hiring freeze is coming at a time of rising scrutiny over the entire artificial intelligence industry, with experts warning that Big Tech’s rampant spending may not be sustainable for much longer. After all, Meta isn’t the only one burning billions of dollars to secure the talent and resources they need to keep their AI operations afloat. Every major player seems to be locked in the same costly battle.

In August, analysts at Morgan Stanley reportedly cautioned that the hefty, stock-based compensation packages being offered by companies like Meta are could “dilute shareholder value without any clear innovation gains.” Around the same time, MIT released a report claiming that 95 percent of organizations were seeing “zero return” on their AI investments — a data point that helped incite a massive selloff of tech stocks on the very day news of MSL’s hiring freeze broke. Even Sam Altman, the CEO of OpeAI, says he sees an AI bubble forming (though he is still confident in the technology’s long-term future).

All things considered, every AI company seems to be at a turning point right now, not just Meta. Whether it’s a sign that the bubble is on the verge of bursting or simply a necessary period recalibration depends on who you ask. What’s clear is that the AI industry appears to be reaching a moment of truth. And Meta is right in the thick of it.

“Investors aren’t wowed by flashy demos anymore, they want to see revenue. Meta’s turbulence is a symptom of that shift,” Valverde said. “In AI, everyone’s experimenting in real time. Even the giants are guessing their way forward, which makes it feel a bit like the blind leading the blind. Meta’s missteps just highlight that nobody has cracked the code on how to turn breakthrough research into durable, scaled products.”