Meta is escalating its AI talent raid, moving from acquiring high-profile executives to surgically targeting specialized researchers and entire startup teams. The company has hired Trapit Bansal, an influential reasoning expert from rival OpenAI, and is in advanced talks to acquire PlayAI, a voice replication startup, according to sources familiar with the moves. These actions signal a new, more focused phase in Meta’s multi-billion-dollar campaign to plug critical gaps in its technology stack.
This strategic refinement follows our previous reporting on Meta’s broad ‘buy or poach’ playbook, a strategy born from repeated rejections in its attempts to acquire larger startups like Runway and Safe Superintelligence (SSI). The new hires demonstrate a deliberate effort to build expertise in specific, underdeveloped areas like AI reasoning and voice generation. This reveals the depth of the internal pressure on CEO Mark Zuckerberg to not only catch up to rivals but to build a complete, competitive AI ecosystem.
A Playbook Forged in Rejection
Meta’s current hiring frenzy was not the original plan. Instead, it represents a sharp tactical pivot forced upon the company after a previously unreported advance to acquire generative video startup Runway was rejected. That failure was part of a wider pattern of unsuccessful takeover discussions with key industry players, including AI-native search engine Perplexity and, ex-OpenAI CTO Mira Murati’s Thinking Machines Lab.
The company’s playbook became starkly clear following its failed bid to acquire the $32 billion startup Safe Superintelligence. Unable to buy the company, Meta executed a stunning escalation of its campaign. Meta entered talks to hire SSI’s CEO, Daniel Gross, and his partner, former GitHub CEO Nat Friedman. The deal also involves Meta acquiring a stake in their venture capital firm. This “buy or poach” approach, where leadership is hired after a buyout fails, has become Meta’s new modus operandi.
Internal Chaos Fuels External Aggression
Driving this external aggression is a firestorm of internal challenges. The company has been hemorrhaging talent, losing 11 of the 14 original authors of its foundational Llama research paper. That drain extends further, with other prominent researchers departing to found their own startup, Yutori. These personnel issues have been compounded by major technical setbacks, including the significant postponement of its most ambitious model, Llama 4 “Behemoth,” after it underperformed on key benchmarks.
Internal messages revealed in ongoing court proceedings underscore the competitive pressure. In an October 2023 message, Meta’s VP of Generative AI, Ahmad Al-Dahle, stated, “Honestly… Our goal needs to be GPT-4”, while dismissing French competitor Mistral as “peanuts”. This mindset helps explain reports from anonymous Meta engineers on the platform Blind, who described a “panic mode” inside the company, with one stating, “Management is worried about justifying the massive cost of GenAI org.”
Trading One Crisis for Another: The Scale AI Gambit
Nowhere is Meta’s high-risk strategy more evident than in its partnership with Scale AI. The colossal $14.3 billion investment for a 49% stake was primarily a vehicle to install its founder, Alexandr Wang, as the head of Meta’s new superintelligence lab. The startup was an attractive target, reportedly boasting a data annotation error rate of just 0.3% and the potential to significantly shorten training cycles for future Llama models.
However, the move immediately backfired. The deal ignited a crisis of confidence among Scale AI’s other Big Tech clients who feared its neutrality was compromised. The fallout was swift, with reports that Google, Scale’s largest customer, began planning to sever a contract worth hundreds of millions. While the Meta deal was a catalyst, insiders revealed OpenAI was already phasing out its work with Scale due to what one report called the firm’s own “limitations in handling increasingly sophisticated AI model requirements.”
Compounding the crisis, a bombshell report revealed a critical security failure at Scale AI that exposed confidential data from clients including Google and xAI. The security failure was perhaps unsurprising to some, with one contractor describing the company’s internal platform as “incredibly janky.” The discovery of such fundamental security flaws has turned a key strategic partnership into a significant liability.
Surgical Strikes in a Widening Talent War
This chaotic backdrop provides the crucial context for Meta’s current, more surgical strategy. The hiring of Trapit Bansal, an expert in the crucial field of AI reasoning where Meta currently lags, was confirmed by a person familiar with the matter to TechCrunch. His recruitment is part of a broader talent hunt that has also pulled in researchers from Google DeepMind and the startup Sesame. This followed the poaching of three other key researchers from OpenAI’s Zurich office, as first reported by The Wall Street Journal, a move that reportedly sent “There’s genuine shock,” through the rival company.
The hires directly contradict recent claims by OpenAI CEO Sam Altman that his “best people” were not leaving despite aggressive offers from Meta. While Altman accused Meta of offering nine-figure signing bonuses, one of the newly hired researchers, Lucas Beyer, called the claim “no, we did not get 100M sign-on, that’s fake news.” in a post on X. Meanwhile, Meta’s hunt continues, with a Bloomberg report detailing advanced talks to acquire PlayAI to bolster its voice replication technology.
While Meta is assembling an impressive roster of talent, its chaotic approach of spending lavishly to trade one crisis for another raises serious questions about its ability to build a stable foundation for AI leadership. Some analysts, however, see a deliberate method in the madness. Meta is making a calculated play to create a powerful, independent AI ecosystem. The ultimate question remains whether this costly gambit can fix the deep-seated issues plaguing its AI ambitions, or if it has simply purchased a new set of challenges.
