Meta’s ambitious $14.3 billion investment in Scale AI and its CEO Alexandr Wang is already showing signs of strain, just months after the high-profile deal. The first major shake-up came when former Scale executive Ruben Mayer resigned from Meta less than two months into his new role. While Mayer publicly stated he was “part of TBD Labs from day one” and left for “a personal matter,” industry insiders suggest his exit reflects deeper friction within Meta Superintelligence Labs (MSL).
Despite the massive deal, Meta’s internal AI teams are reportedly relying heavily on Scale AI competitors such as Surge and Mercor. Several researchers have openly criticized Scale’s data quality, describing it as “low quality,” a claim Meta has pushed back against. The optics, however, are difficult to ignore — especially as OpenAI and Google have already ended their partnerships with Scale AI, resulting in layoffs for over 200 Scale employees.
The turbulence extends beyond partnerships. Meta is experiencing noticeable churn within its AI organization. New hires from OpenAI and Scale AI have reportedly expressed frustration with internal bureaucracy, while some long-standing generative AI staffers have chosen to leave altogether. Among them is MSL researcher Rishabh Agarwal, who announced his departure publicly, writing: “The pitch from Mark and @alexandr_wang to build in the Superintelligence team was incredibly compelling. But I ultimately choose to follow Mark’s own advice: ‘In a world that’s changing so fast, the biggest risk you can take is not taking any risk’.”
For Mark Zuckerberg, this moment is a critical test of his ability to retain the elite talent he has aggressively recruited from OpenAI, Google DeepMind, and Anthropic while keeping MSL on course. Meta is reportedly pressing ahead with the development of its next-generation AI model, but whether this $14.3 billion gamble cements its leadership in AI — or becomes a cautionary tale of overreach — is a question that remains unanswered.
