The AI industry’s revolving door is spinning faster than ever, as top talent continues to shift between leading labs at a rapid pace. Yesterday’s news spotlighted the sudden and reportedly tense departure of three senior executives from Mira Murati’s Thinking Machines lab. Within days, all three were recruited by OpenAI, underscoring the intense competition for skilled AI professionals. Now, reports indicate that two more employees from Thinking Machines are expected to follow suit, joining OpenAI in the coming weeks. This latest exodus adds to a growing pattern of high-profile talent moves that has become a defining feature of the current AI landscape. Meanwhile, Anthropic is making strategic inroads into OpenAI’s safety and alignment teams. According to The Verge, Andrea Vallone, a senior safety researcher at OpenAI with expertise in how AI models handle mental health-related queries, has left the company to join Anthropic. Her departure is particularly notable given OpenAI’s recent controversies around model behavior, including instances of sycophantic responses that raised concerns about AI’s reliability and ethical boundaries. Vallone will be working under Jan Leike, a well-known alignment researcher who left OpenAI in 2024 citing concerns that the company wasn’t prioritizing safety and long-term risks with sufficient urgency. His move to Anthropic was a major signal of the growing rift between safety-focused researchers and the broader direction of some leading AI labs. The talent war isn’t limited to safety or research roles. OpenAI has also made a significant hire in engineering, bringing in Max Stoiber, formerly director of engineering at Shopify. Stoiber will join OpenAI to work on its long-rumored operating system, a project aimed at creating a new platform to run AI models more efficiently. He described his new role as part of a “small high-agency team,” suggesting a focus on agility and innovation in building the next generation of AI infrastructure. Together, these moves highlight a broader trend: as AI companies race to build more powerful systems, the battle for top talent has become as critical as the race to build better models. The constant churn of executives and researchers reflects both the high stakes of the AI race and the growing dissatisfaction among some professionals about corporate priorities, particularly around safety, transparency, and long-term impact.