Jan 22, 2026
Aliisa Rosenthal, the first sales leader at OpenAI, has joined Acrew Capital as a general partner. This information was reported by TechCrunch. She will work alongside founding partner Lauren Kolodny and the firm’s other partners.
Rosenthal left OpenAI about eight months ago after a three-year period at the AI lab that saw the launch of DALL*E, ChatGPT, ChatGPT Enterprise, Sora, and other products. “I wasn’t initially looking to join a VC fund,” she told TechCrunch. “I was out there meeting with lots of AI startups.” After growing OpenAI’s enterprise sales team from two people to hundreds, she saw the appeal when Kolodny pitched her on venture capital, as she could help a portfolio of startups instead of just one.
Reflecting on her time at OpenAI, she said, “I learned a lot about behavior, both on the side of the buyers, how people are thinking about these purchases, and the gap between what most organizations think is possible and what they can actually deploy today.” She has insight into what kind of moat an AI startup can build to avoid vulnerability when model makers like OpenAI launch competing products.
Addressing concerns about competition, she stated, “Will OpenAI ‘just build everything and put every company out of business? You know, they are doing a lot already: they’re in consumer, they’re in enterprise, they’re building a device. I don’t think they are going to go after every potential enterprise application.” She believes one moat for enterprise AI startups is to offer specialization.
Context as Moat
Rosenthal thinks the key to a good startup moat will be “context”—the information the AI stores in its context window memory as it works on requests. “Context is dynamic. It’s adaptable. It’s scalable. And I think what we’re seeing is going beyond sort of the basic RAG towards this idea of a context graph, which is persistent,” she said, referring to Retrieval-Augmented Generation (RAG), described as the de facto method as of 2025 to minimize hallucinations. She noted that a lot of technology still needs to be developed for this area, from memory to reasoning beyond pattern recognition.
“I expect real innovation here. I think this year we will see new approaches—the idea of context and memory,” Rosenthal said. Beyond startups working directly on context engineering, she thinks enterprise applications that incorporate it will have an advantage. “Ultimately, when we talk about moat, I think who owns and manages this context layer will become a large advantage for AI products,” she concluded.
