The drama at Thinking Machines, where co-founders were fired and immediately rejoined OpenAI, shows the extreme volatility of AI startups. Top talent holds immense leverage, and personal disputes can quickly unravel a company as key players have guaranteed soft landings back at established labs, making retention incredibly difficult.
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When Thinking Machines' CTO departed for OpenAI, the company cited "unethical conduct." Insiders speculate this is a "snaky PR move" or "character assassination leak" to control the narrative as talent poaching intensifies among AI labs.
The creation of talent agency CAA in 1975 by agents who defected from a larger firm mirrors the current AI landscape, where top researchers leave established labs like OpenAI to found competitors like Anthropic. This suggests that talent-driven industries consistently see cycles of unbundling led by key players.
In the hyper-competitive AI talent market, companies like OpenAI are dropping the standard one-year vesting cliff. With equity packages worth millions, top candidates are unwilling to risk getting nothing if they leave before 12 months, forcing a shift in compensation norms.
Top AI labs face a difficult talent problem: if they restrict employee equity liquidity, top talent leaves for higher salaries. If they provide too much liquidity, newly-wealthy researchers leave to found their own competing startups, creating a constant churn that seeds the ecosystem with new rivals.
In the fierce competition for elite AI researchers, companies like OpenAI, Meta, and xAI are shortening or eliminating the standard one-year equity vesting cliff. This move reflects the immense leverage top talent holds, forcing companies to prioritize recruitment over traditional retention mechanisms by offering immediate equity access.
The 'Valinor' metaphor for AI talent's destination has flipped. It once signified leaving big labs for well-funded startups like Thinking Machines. Now, as those startups face turmoil, Valinor represents a return to the stability and immense resources of established players like OpenAI, which are re-attracting top researchers.
After reportedly turning down a $1.5B offer from Meta to stay at his startup Thinking Machines, Andrew Tulloch was allegedly lured back with a $3.5B package. This demonstrates the hyper-inflated and rapidly escalating cost of acquiring top-tier AI talent, where even principled "missionaries" have a mercenary price.
The frenzied competition for the few thousand elite AI scientists has created a culture of constant job-hopping for higher pay, akin to a sports transfer season. This instability is slowing down major scientific progress, as significant breakthroughs require dedicated teams working together for extended periods, a rarity in the current environment.
Thinking Machines Lab, founded by ex-OpenAI leaders, raised $2B pre-product. Its current struggles, including executive departures and inability to raise more funds, suggest investors are shifting focus from founder hype ('vibe founding') to concrete products and business strategies.
The "Valinor" metaphor for top AI talent has evolved. It once meant leaving big labs for lucrative startups. Now, as talent returns to incumbents like OpenAI with massive pay packages, "Valinor" represents the safety and resources of the established players.