OpenAI Alumni Launch $100M AI Venture Fund That Is Already Writing Checks
A group of former OpenAI insiders has quietly launched a new venture capital fund called Zero Shot, and it has already made its first close toward a $100 million target. The founding team has roots deep inside the AI lab that built ChatGPT, and they are already deploying capital into startups they believe the broader market has missed.
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| Credit: Bryce Durbin |
Who Is Behind the Zero Shot Fund
Zero Shot is co-founded by five partners, three of whom are OpenAI veterans. Evan Morikawa served as head of applied engineering during the landmark launches of DALL-E, ChatGPT, and Codex. Andrew Mayne was the original prompt engineer at OpenAI and now hosts a widely followed AI podcast while running an AI deployment consultancy called Interdimensional. The third OpenAI alum is Shawn Jain, an engineer and researcher who later became a venture capitalist and founded his own generative AI startup, Synthefy.
Rounding out the founding team are Kelly Kovacs, a former founding partner at a prominent growth-stage venture firm, and Brett Rounsaville, formerly of Twitter and Disney, who currently serves as CEO of Interdimensional. Together, the five bring a rare combination of technical depth, product experience, and venture capital know-how that is genuinely hard to replicate.
How a Podcast and a Consulting Company Turned Into a VC Fund
The origin story of Zero Shot is less boardroom strategy and more organic convergence. After leaving OpenAI, the founders found themselves constantly fielding calls from venture firms wanting technical advice on emerging AI tools, and from founder friends who wanted a gut check before building. That informal advisory role became a pattern nobody planned for.
Mayne launched his consulting company partly as a response to that demand. But as more people from OpenAI began leaving to start companies, the team saw a clear gap. Established VCs were funding AI startups at a furious pace, yet many of those investors lacked the insider knowledge to distinguish transformative technology from clever marketing. The Zero Shot founders believed they could do better. After conversations with institutions and family offices, they closed their first twenty million dollars and set their sights on the full hundred million dollar target.
The AI Startups Zero Shot Is Already Backing
Zero Shot has already written checks to at least two companies, with a third still operating in stealth mode.
The first investment went to Worktrace AI, founded by Angela Jiang, an early OpenAI product manager. Worktrace AI is building an AI-powered management software platform designed to help enterprises figure out which tasks should be automated before actually automating them. The startup raised a ten million dollar seed round that included backing from notable names in the AI investment world.
The second bet is on Foundry Robotics, a startup focused on next-generation factory robotics enhanced by artificial intelligence. Foundry recently closed a thirteen and a half million dollar seed round led by one of Silicon Valley's most respected deep technology investors. Both picks reflect a consistent thesis: back the builders who understand where AI is genuinely going, not where it appears to be going from the outside.
What Zero Shot Is Deliberately Avoiding
Perhaps more interesting than what Zero Shot is funding is what the partners are choosing to skip entirely. Their insider knowledge of AI model development gives them a sharp lens for spotting ideas that sound compelling but are likely to be disrupted or made irrelevant by the model makers themselves.
Mayne is skeptical of most vibe coding platforms. His reasoning is pointed: as AI model companies develop increasingly powerful coding tools, standalone subscriptions to vibe coding products will feel redundant to users. The model makers are moving too fast and have too much coding expertise for most standalone platforms to hold their ground.
Morikawa is equally cautious about what he calls ego-centric video data companies in the robotics space. These are startups collecting embodiment training data for robots, betting that someone in the research world will eventually close the gap between video observation and physical action. Morikawa sees that as a high-risk gamble with no clear timeline for a payoff and a lot of hope baked in.
Mayne has also done deep due diligence on digital twin startups, even building a reasoning model to stress-test their value propositions. His conclusion is blunt: a standard large language model performs just as well. He sees most digital twin offerings as a layer of complexity that simply does not justify the investment.
Why Timing and Trajectory Matter More Than Hype
One of the most revealing insights from the Zero Shot founders is their warning that predicting where AI models are heading is extremely non-linear. It is not a smooth upward curve that any outside observer can safely extrapolate from quarterly announcements and product demos. The people best positioned to make those calls are the ones who spent years watching the models develop from the inside.
That is the central pitch of Zero Shot. The fund is not just another generalist technology vehicle that has pivoted toward AI because the market demands it. It is a purpose-built vehicle whose edge comes from people who were in the room when the most consequential AI milestones of the past decade happened. Their pattern recognition is not theoretical. It is earned through direct experience.
An Advisor Bench That Adds Institutional Credibility
Beyond the founding partners, Zero Shot has assembled a group of advisors who bring additional weight to the fund. The advisor network includes the former head of people at OpenAI, the company's former head of communications who also held a senior role at a major global technology company, and a former senior product leader from OpenAI. Advisors will receive a share of the fund's carried interest, aligning their incentives directly with its long-term performance.
The combination of seasoned operators, technical founders, and a tightly curated advisor bench positions Zero Shot as a serious institutional player rather than a celebrity-adjacent side project.
What This Means for the Broader AI Investment Landscape
The launch of Zero Shot signals something meaningful about where the AI venture market is heading. As the first wave of general-purpose AI excitement matures, investors with genuine technical fluency are beginning to separate themselves from the crowd. The era when any startup with AI in the pitch deck could raise at sky-high valuations is giving way to something more discerning and more demanding.
Funds like Zero Shot are a product of that maturation. They exist because the founders understand that not every AI application is worth building, not every category is defensible, and not every technical bet will survive contact with the model makers' own roadmaps. That kind of selective conviction, grounded in firsthand experience building and deploying AI systems at scale, is becoming a genuine competitive advantage in venture capital.
For founders building in AI, getting a check from Zero Shot likely means more than the capital itself. It means having partners who can tell you honestly where your product fits in the model roadmap, which adjacent threats you may not have considered, and whether the category you are entering will still be relevant in three years.
That kind of guidance is increasingly rare. And in a market moving this fast, it may turn out to be worth more than the money.
