Zero Shot Fund: OpenAI Veterans Target Enterprise and Robotics with $100M AI VC Bet

Zero Shot Fund emerged from a core group of former OpenAI staffers who helped launch flagship technologies like ChatGPT and DALL·E. Founding partners Evan Morikawa (ex-head of applied engineering), Andrew Mayne (OpenAI's original prompt engineer and podcast host), and Shawn Jain (former researcher and GenAI founder) bring rich technical and practical experience honed during pivotal moments in OpenAI’s product growth ^[1][2][7]. The team is rounded out by Kelly Kovacs, with prior venture experience at 01A, and Brett Rounsaville, who previously worked at Twitter and Disney and now serves as CEO at Mayne’s consulting firm ^[4][8].

Their time at OpenAI granted them both unparalleled insight into generative model development and direct access to a network of researchers and potential founders. Following their tenure, frequent consulting requests from both VCs and startups seeking AI guidance underscored their value at the intersection of startup building and deep tech assessment ^[7][8]. This unique vantage point seeded their ambition: to allocate capital with the technical discernment often missing from generalist venture funds.

Zero Shot’s deployment has been swift and targeted. The fund participated early in Worktrace AI, led by ex-OpenAI product manager Angela Jiang, which crafts software helping enterprises pinpoint and automate operational tasks with AI ^[1][6][8]. Worktrace AI recently closed a $10 million seed round, drawing in capital from notable investors including OpenAI’s own fund and tech leaders like Mira Murati ^[8][9].

Another portfolio company, Foundry Robotics, exemplifies Zero Shot’s conviction in AI-driven physical automation. Foundry Robotics is developing next-generation factory robots tightly integrated with proprietary AI systems, and has already secured a $13.5 million seed round led by Khosla Ventures ^[1][4][8]. Both of these investments reflect the fund’s commitment to domains with clear, tangible pain points and defensible advantages from advanced AI, in contrast to ill-defined, speculative market bets.

Zero Shot’s partners have been explicit in their dismissal of certain overhyped sectors within AI venture investing. Market segments like “vibe coding” tools—subscription-based coding assistants—are seen as destined to be commoditized by the large model providers themselves, undercutting smaller point-solution startups ^[2][7][8]. Andrew Mayne, referencing his direct experience with model evolution at OpenAI, argues that any product directly addressable by base model improvements or API expansion from Big AI labs is fundamentally at risk ^[7][8].

Similarly, the team is skeptical of robotics companies primarily collecting ergo-centric video data for training and most digital twin startups. Evan Morikawa, coming from the applied engineering trenches, suggests that much of the embodiment gap in robotics (i.e., translating video to physical robotic action) remains unsolved, and that VC funding has frequently glossed over these persistent limitations ^[1][8]. They argue that model complexity does not smoothly translate to market value, and their due diligence process involves building reasoning models to test the claims of prospective investments.

The fund’s technical assessment is matched by attention to company-building fundamentals. Zero Shot co-founders cite both their access to a broad network of builders and their lived experience navigating AI’s non-obvious trajectory—where technical breakthroughs and commercial opportunities rarely align linearly ^[2][7][9]. This enables them to find and back founders with not just innovative ideas but credible plans for deployment and long-term defensibility.

To further support their thesis, the partners have assembled an advisory roster from OpenAI and the wider industry, ensuring startups gain mentorship from those deeply versed in both research and operations ^[6][8]. Their philosophy blends hands-on involvement and practical advice, rather than mere check-writing, helping portfolio companies navigate regulatory hurdles and continuously shifting technical baselines.

Zero Shot’s arrival signals a broader power shift in AI venture capital: operational insiders with domain knowledge are ascending as key early backers, setting a higher bar for technical rigor and evaluation in an overheated market. Their avoidance of popular but structurally flawed investment trends may insulate them from the high failure rate that plagues hype-driven bets ^[3][4][9].

For startups, Zero Shot offers capital coupled with unusually relevant guidance—potentially accelerating the translation of AI research into scalable, profitable companies. If successful, their approach could inspire other seasoned practitioners to pool resources and expertise, fostering a more technically sophisticated and sustainable AI innovation pipeline for the next decade ^[2][6][8].