Andrew Tulloch Leaves Meta for Anthropic Less Than a Year After Joining, Exposing Limits of AI Talent War

Andrew Tulloch Exits Meta After Less Than a Year

Andrew Tulloch, the AI researcher whose reported $1.5 billion offer from Meta became a symbol of the AI talent war, is leaving the company after less than a year1

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. According to Semafor, Tulloch timed his departure for the day after Meta launched Muse, its new AI assistant capable of handling tasks like sending emails and making purchases2

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. The Wall Street Journal reports he is joining Anthropic's inference and performance team, though neither company has confirmed the move3

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Tulloch's exit comes at an awkward moment for Meta. The company spent heavily to rebuild its AI bench, including a talent raid on Thinking Machines Lab that brought over five founding members this spring1

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. Now it loses the best-known name from that effort just one day after its biggest consumer AI launch. No outlet has reported why Andrew Tulloch is leaving Meta, but the timing raises questions about how long money alone can hold a lab together1

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The $1.5 Billion Question and Meta's Recruitment Push

Tulloch spent 11 years at Meta before leaving in 2023 for OpenAI, where he helped train GPT-4o, GPT-4.5 and o31

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. He then co-founded Thinking Machines Lab with Mira Murati, OpenAI's former chief technology officer. His return was a prize for Mark Zuckerberg, who reportedly recruited him in person1

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Meta had first tried to buy Thinking Machines Lab outright, an approach Murati rejected1

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. Last year the Wall Street Journal reported that Meta's compensation package could have reached $1.5 billion over six years, assuming bonuses and stock paid out in full3

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. Meta spokesperson Andy Stone called that figure "inaccurate and ridiculous," and the company has always disputed the number2

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. Tulloch turned the offer down at first and joined months later in October 20244

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. Nobody has disclosed the sum he finally accepted.

Working at TBD Lab on Superintelligence

At Meta, Andrew Tulloch worked inside TBD Lab, the small team at the center of Mark Zuckerberg's AI strategy focused on superintelligence5

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. Scale AI founder Alexandr Wang leads Meta's broader Superintelligence Labs organization2

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. According to Semafor, Tulloch held off leaving until Meta had shipped Muse AI, the personal AI agent it launched on Tuesday1

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. His work focused on large-scale machine learning systems and advanced AI research and development4

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Why Andrew Tulloch Joins Anthropic Matters

If the Wall Street Journal is right, the timing is awkward for Meta. For Anthropic, it would be a marquee hire in the same week it lost a researcher in public. Jacob Coxon quit on Tuesday, warning that AI labs are gambling with our lives1

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. Anthropic already pays the biggest salaries in the industry and can bid for people few others can afford1

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Tulloch will focus on AI model performance and efficiency at Anthropic's inference and performance team4

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. This shifts attention toward operational excellence rather than headline model releases. Better efficiency can reduce computing costs while improving speed and large-scale product performance4

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. The move gives Anthropic another highly experienced researcher as leading labs compete for scarce talent4

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The Broader AI Talent War and Retention Challenges

The departure exposes the limits of massive compensation packages in retaining AI specialists. Research autonomy, technical influence, computing access and team direction can shape senior researchers' decisions more than money alone4

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. Meta, Anthropic, OpenAI and Google continue competing for the same small pool of elite AI talent.

The churn is wider than two labs. Google chief scientist Jeff Dean left last month with three other senior researchers to start a company1

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. Only a small group of people have trained frontier models. Each move between labs carries that experience to a rival1

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. The escalating AI talent war now extends beyond salaries into technology, research culture and strategic influence4

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. Even extraordinary offers cannot guarantee long-term loyalty when researchers have several powerful career options.