In summary: Meta has hired five founding members of Thinking Machines Lab, the artificial intelligence startup created by former OpenAI CTO Mira Murati, after she rejected a $1 billion acquisition offer. The most expensive individual hire, co-founder Andrew Tulloch, reportedly received a $1.5 billion package over six years. The talent raid is part of a broader AI shakeup that includes the $14.3 billion investment in Scale AI, the appointment of Alexandr Wang as chief AI officer, the departure of Yann LeCun after 12 years, 600 FAIR research cuts, and the creation of Meta Superintelligence Labs, whose first closed-source model, Muse Spark, was released on April 8.
Meta has now hired five of the founding members of Thinking Machines Lab, the artificial intelligence startup Mira Murati built after leaving her position as CTO of OpenAI. The most recent departure, founding engineer Joshua Gross, joined Meta Superintelligence Labs in March after creating Tinker, the startup’s core API product. His departure follows that of co-founder Andrew Tulloch, who left for Meta in October with a compensation package reportedly worth $1.5 billion over six years, a figure that, if accurate, would make it the most expensive individual talent acquisition in the history of the tech industry.
The pattern is not subtle. After Mark Zuckerberg reportedly offered approximately $1 billion to acquire Thinking Machines Lab outright and was rejected, Meta went on to recruit the founding team one by one. Several media outlets have described the strategy as a “large scale raid.” It has been effective. Of the startup’s original founding group, five left for Meta, three returned to OpenAI, and one joined Elon Musk’s xAI. Murati’s company, which raised $2 billion at a $12 billion valuation in a seed round led by Andreessen Horowitz in July 2025 and was reportedly in talks for a new round at a $50 billion valuation in November, has lost most of the team it was built around.
Who left and where did they go?
Tulloch and Gross are the two departures whose fates and roles are most clearly documented. Tulloch, an AI researcher who had previously worked at OpenAI, joined Meta Superintelligence Labs and now works with Alexandr Wang, the 28-year-old former CEO of Scale AI whom Meta installed as its first AI director in June 2025. Gross, who had previously worked at both OpenAI and Meta, now leads engineering teams within the same division.
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The other Thinking Machines defections followed different paths. Barret Zoph and Luke Metz returned to OpenAI in January 2026, along with Sam Schoenholz. Murati reportedly fired Zoph for what the company described as “unethical behavior” before immediately rejoining OpenAI. Devendra Chaplot left xAI in March. The departures have left Murati with a significantly reconstituted leadership team: she remains as CEO, Soumith Chintala, the creator of PyTorch who joined from Meta’s own FAIR laboratoryserves as chief technology officer and John Schulman continues as chief scientific officer.
Meta’s new AI hierarchy
The talent acquisitions are part of a broader restructuring that has transformed Meta’s AI organization over the past year. In June 2025, Meta paid $14.3 billion for a 49% non-voting stake in Scale AI and hired Wang to run a new division called Metasuperintelligence laboratoriesalong with Nat Friedman, former CEO of GitHub. Zuckerberg called Wang “the most impressive founder of his generation” in an internal memo.
The restructuring has not been easy. Yann LeCun, Meta’s chief AI scientist for 12 years and one of the most influential figures in deep learning, departed in November 2025 after being asked to report to Wang.You don’t tell an investigator what to do. You certainly don’t tell a researcher like me what to do,“LeCun told the Financial Times in January. He called Wang”young and inexperiencedand warned that “many people have left, many people who have not left yet will leave.” LeCun later raised a billion dollars found AMI Labs in Paris, integrating the founding team “almost entirely of Meta’s AI research organization.”
As of August 2025, Meta Superintelligence Labs had split into four groups: the TBD Lab for large language models, led by Wang; fundamental research FAIR; a products and applied research division led by Friedman; and an infrastructure unit headed by Aparna Ramani. The AGI Foundations team, which had been responsible for the Llama family of models, disbanded after the lukewarm reception of Llama 4. LeCun publicly stated that the AI team had “manipulated” some of the results. In October 2025, approximately 600 positions were eliminated from the FAIR and AI infrastructure units.
The economics of the talent war
Compensation figures circulating in the AI talent market have reached a scale that distorts normal hiring dynamics. OpenAI CEO Sam Altman has acknowledged that signing bonuses of up to $100 million have been offered to attract top researchers. OpenAI chief scientist Mark Chen described Meta poaching as “similar to someone breaking into our house.” Altman’s response was that Meta “had to come pretty low on their list,” a characterization that five departures from a single startup’s founding team would seem to contradict.
The competition extends beyond Meta and OpenAI. Anthropic is winning what Fortune described as a “one-sided talent war” against OpenAI, which retains 67% of its researchers, and Google DeepMind, which retains 78%. DeepMind responded by imposing non-compete clauses of six to twelve months with full salary. The talent market for cutting-edge AI researchers has become a zero-sum contest in which every hire by one lab is a direct loss to another, and the compensation needed to move individuals has risen from millions to hundreds of millions and, in the case of Tulloch, potentially billions.
Meta can afford the climb. The company reported $201 billion in revenue for 2025, up 22% year over year, with $43.6 billion in free cash flow. It is spending between $115 billion and $135 billion in capital expenditures on AI infrastructure this year, including a $27 billion joint venture with Nebius for a gigawatt-scale data center. He 8,000 layoffs starting May 20 are explicitly framed as a reallocation: shedding roles in Reality Labs, recruiting, sales and global operations to fund the AI pivot that Wang’s division represents.
What Meta has to show
The first result from Meta Superintelligence Labs came on April 8 with the release of Muse Spark, a native multimodal reasoning model that Meta described as the first step toward “personal superintelligence.” Now powering Meta AI on Facebook, Instagram, WhatsApp, Messenger and Ray-Ban Meta AI glasses. The model is closed source, breaking with Meta’s open-source Llama tradition and signaling that the intellectual property produced by the researchers Meta is hiring at extraordinary expense will not be shared freely.
A second model, internally called “Avocado,” is supposedly in development under tighter control within the TBD Lab. Its progress has been uneven: internal benchmarks showed it fell short of Google’s Gemini in some evaluations, contributing to the dissolution of the AGI Foundations team and the consolidation of model development under Wang.
The question for Meta is whether the talent it has assembled, at a cost that includes $14.3 billion for Scale AI, $1.5 billion for a single engineer, the departure of one of the field’s most respected scientists, and the systematic dismantling of another company’s founding team, will produce AI capabilities that justify the investment. Thinking Machines Lab, for its part, has survived the exodus with new leadership, a $12 billion valuation, and the distinction of having produced a team so valuable that the world’s largest social media company was willing to spend more to acquire its members individually than it offered to buy the entire company.
