Anthropic is on the greatest revenue growth run in the history of capitalism, going from $9B to $47B ARR in ~5 months. In that same window, the CTO of Workday, the co-founder of Instagram, and Andrej Karpathy all left their jobs to join Anthropic's technical staff. The revenue number is far more legible, but the talent gravity is what worries me.
My working definition of impressive talent gravity is hiring people who are making sacrifices to join you.
Peter Bailis became CTO of Workday in May 2025. He left less than a year later to take a role as a member of technical staff, focusing on reinforcement learning engineering. Mike Krieger co-founded Instagram, became Anthropic's chief product officer, then asked to step back to a technical role at Labs working on Claude Code. Bryan McCann left as CTO of You[dot]com for the same role in March.
They all gave up better titles for the opportunity to join Anthropic.
The best analogy I can come up with is a 5-star general choosing to serve as a private in a different army. You'd assume that person was either crazy or knew something you didn't.
The cynical read is that they've done the math on Anthropic equity and decided it beats whatever they're leaving behind. That's a plausible explanation for some of it. But it doesn’t hold as much water for Andrej Karpathy, one of the 11 co-founders of OpenAI and former director of AI at Tesla, who joined Anthropic's pre-training team in May.
In his announcement, he made his motivations clear: "I think the next few years at the frontier of LLMs will be especially formative." To me, that sounds like someone who wants to be where the work is happening.
The only historical parallel I can think of is Bell Labs in the 1950s, which pulled researchers away from academia because the resources and the mission made everything else feel small by comparison. Of course, US capitalism was much less intense back then. Today, the talent competition is much, much more intense. Anthropic’s talent gravity is simply stunning.
Everyone right now is focused on AI strategy: which layer wins or where the moat is. Strategy is much more legible than culture. But it’s the wrong focus area. Culture eats strategy for breakfast.
Today’s founders are inundated with thought pieces on moats and business models in the world of AI. This is largely noise. The more important questions are how to establish the most talent-dense culture and how to earn an insight to create an insanely good product.