Meanwhile, leading AI labs are playing high stakes and talent playing a never-ending game of musical chairs. The latest shuffle began three weeks ago, when OpenAI announced it was re-hiring several researchers who left less than two years ago to join Mira Muratti’s startup, Thinking Machines. At the same time, Anthropic, itself founded by former OpenAI employees, is poaching talents from the ChatGPT creator. In return, OpenAI appointed a former Anthropic security researcher as its “head of preparedness”.
As Dave Munchiello, an investor at GV, says, the hiring churn happening in Silicon Valley represents the “great unbundling” of tech startups. In earlier eras, tech founders and their first employees often stayed onboard until either the lights went out or some major liquidity event occurred. But in today’s market, where generic AI startups are growing fast, armed with lots of capital, and prized especially for the strength of their research talent, “you invest in a startup knowing that it could go broke,” Munchiello told me.
The early founders and researchers of the hottest AI startups are moving on to different companies for a variety of reasons. Of course, a big incentive for many people is money. Last year Meta was reportedly offering compensation packages in the tens or hundreds of millions of dollars to top AI researchers, giving them not only access to cutting-edge computing resources but also… generational wealth.
But it’s not all about becoming rich. Sayash Kapoor, a computer science researcher at Princeton University and a senior fellow at Mozilla, says the broader cultural shifts that have shaken the tech industry in recent years have made some workers worried about committing to one company or institution for too long. Employers could safely assume that workers would stay for at least four years when their stock options are typically scheduled to vest. In the high-minded era of the 2000s and 2010s, many early co-founders and employees also sincerely believed in their companies’ stated missions and wanted to help achieve them.
Now, Kapoor says, “people understand the limitations of the institutions they’re working in, and founders are more practical.” For example, Windsurf’s founders may have calculated that their impact could be bigger at a place like Google, which has lots of resources, Kapur says. He further said that similar changes are taking place in the education world also. Over the past five years, Kapur says, he has seen many PhD researchers leave their computer-science doctoral programs to take jobs in industry. He says that at a time when AI innovation is growing rapidly, there is a high opportunity cost associated with staying in one place.
Investors, wary of collateral damage in the AI talent wars, are taking steps to protect themselves. Max Gazor, founder of Stryker Venture Partners, says his team is screening founding teams “more than ever for chemistry and cohesion.” Gazor says it has become increasingly common for deals to include “protective provisions that require board consent for content IP licensing or similar scenarios.”
Gazor says some of the biggest acquisition-appointment deals recently involved startups founded long before the current generative AI boom. Scale AI, for example, was founded in 2016, at a time when the kind of deal Wang struck with Meta would have been unimaginable to many. However, now these potential outcomes can be considered in the initial term sheet and “managed creatively,” explains Gazor.
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