From the middle In the past year, there have been at least three major AI “acqui-hires” in Silicon Valley. Meta invested more than $14 billion in Scale AI and brought in its CEO, Alexandr Wang; Google spent a cool $2.4 billion to license Windsurf technology and wrap its founders and research teams at DeepMind; and Nvidia bet $20 billion on Groq’s inference technology and hired its CEO and other employees.
Frontier AI labs, on the other hand, have been playing high stakes and a seemingly endless game of musical chairs with talent. The latest change began three weeks ago, when OpenAI announced it would rehire several researchers who had left less than two years earlier to join Mira Murati’s startup, Thinking Machines. At the same time, Anthropic, itself founded by former OpenAI employees, was poaching talent from the maker of ChatGPT. OpenAI, in turn, recently hired a former Anthropic security researcher to be its “head of preparedness.”
The employment churn occurring in Silicon Valley represents a “massive fragmentation” of tech startups, as Dave Munichiello, a GV investor, puts it. In earlier times, tech founders and their early employees often stayed on the board until the lights went out or there was a big financial event. But in today’s market, where productive AI startups are growing fast, armed with a lot of funding, and highly valued for the power of their research talent, “you invest in a startup knowing it can fall apart,” Mnichiniello said.
Early founders and researchers at popular AI startups jump to different companies for a number of reasons. Of course, the biggest incentive for many is money. Last year Meta was reported to be offering AI researchers compensation packages in the tens or hundreds of millions of dollars, giving them not only access to high-end computing resources but also … wealth generated.
But it’s not just about being rich. A broader cultural shift that has shaken the tech industry in recent years has made some employees wary of committing to a company or institution long-term, said Sayash Kapoor, a computer science researcher at Princeton University and a senior partner at Mozilla. Employers used to safely assume that employees would stay at least until the four-year mark when their stock options are usually scheduled to vest. In the high-concept era of the 2000s and 2010s, most founders and former employees also sincerely believed in the stated missions of their companies and wanted to be there to help achieve them.
Now, Kapoor says, “people understand the limitations of the institutions they work in, and innovators work harder.” The founders of Windsurf, for example, may have calculated that their impact would be greater in a place like Google with more resources, Kapoor said. He adds that a similar change is happening in education. In the past five years, Kapoor says, he has seen many PhD researchers leave their computer science doctoral programs to take jobs in industry. There are high opportunity costs associated with staying in one place at a time when AI innovation is accelerating rapidly, he says.
Investors, wary of becoming collateral in the AI talent wars, are taking defensive measures. Max Gazor, founder of Striker Venture Partners, says his group is exploring teams that create “more chemistry and cohesion than ever before.” Gazor says it’s more common for deals to include “security clauses that require board approval of key IP licenses or similar conditions.”
Gazor notes that some of the biggest acqui-hire deals that have happened recently involve startups that were founded long before the current AI boom. Scale AI, for example, was founded in 2016, a time when the kind of deal Wang negotiated with Meta would have been incomprehensible to many. Now, however, these potential consequences can be considered in the original time sheets and “handled constructively,” Gazor explained.
