In a move that signals both the maturation of artificial intelligence and the growing sophistication of its investment ecosystem, former OpenAI executives have quietly launched a new venture capital fund targeting $100 million. The fund, called Zero Shot, brings together five partners with deep ties to the AI pioneer, including three former OpenAI employees who played key roles during the company’s explosive growth period.
What makes this development particularly noteworthy isn’t just the fund’s size or pedigree, but what it reveals about the current state of AI investment. As Evan Morikawa, former head of applied engineering at OpenAI and now at robotics startup Generalist, told TechCrunch: “There is a real skill in knowing how to predict where these models will be going next, because it’s extremely not obvious. It’s not linear.” This insight from someone who helped launch DALL�E and ChatGPT through Codex suggests that even insiders see AI development as unpredictable, creating both opportunities and pitfalls for investors.
The Fund’s Strategy and Early Bets
Zero Shot has already made its first investments, backing Worktrace AI, a startup developing AI-based management software to help enterprises automate tasks, and Foundry Robotics, which is working on next-generation, AI-enhanced factory robotics. The fund’s approach appears to be selective and informed by their insider knowledge of AI’s trajectory.
Andrew Mayne, OpenAI’s original prompt engineer and host of The OpenAI podcast, explained the fund’s origin: “Maybe we should do our own fund, because we think we have a pretty good sense of where things are headed, and we have this great access to people who we think are incredible builders.” This insider perspective gives Zero Shot a potential edge in identifying promising AI startups while avoiding what they see as dead ends.
The AI Investment Landscape: Beyond the Hype
To understand the significance of Zero Shot’s launch, we need to look at the broader AI investment context. OpenAI recently raised a staggering $122 billion in funding at an $852 billion valuation, including $3 billion from retail investors for the first time. According to the Financial Times, this massive round was led by SoftBank, Amazon, and Nvidia with $110 billion, and OpenAI is now generating $2 billion in monthly revenue, with 60% coming from consumer business and 40% from enterprises.
This context reveals an important trend: while massive funding rounds for established AI companies continue, there’s growing interest in more targeted, specialized investment approaches. Zero Shot represents this second wave of AI investment – smaller, more focused funds led by technical experts rather than traditional venture capitalists.
What They’re Avoiding: Insider Skepticism
Perhaps more revealing than what Zero Shot is investing in is what they’re avoiding. Mayne is bearish on most iterations of “vibe coding” because he foresees that model makers, with their coding expertise, will quickly make subscriptions to such platforms feel unnecessary. Morikawa expresses skepticism about “ergo-centric video data companies right now in robotics,” noting that “there’s a lot of hoping and praying going on right now that someone in the research world will figure out how to transfer the embodiment gap, but that’s nowhere near possible.”
This insider skepticism extends to “digital twins” as well. Mayne has done due diligence on several such startups, including building a reasoning model to test them, and concluded that a regular large language model works just as well. These insights suggest that not all AI investment opportunities are created equal, and technical expertise matters in separating hype from substance.
The Competitive Landscape and Security Concerns
The AI investment space isn’t without its challenges. Anthropic, one of OpenAI’s main competitors, recently experienced a significant security incident when nearly 512,000 lines of TypeScript code for its Claude Code software package were accidentally leaked due to an exposed source map file. As reported by Ars Technica, this was the second security incident for Anthropic in a week, following an earlier leak of nearly 3,000 internal files.
While Anthropic described it as “a release packaging issue caused by human error, not a security breach,” the incident highlights the security vulnerabilities that can accompany rapid AI development. This context is important for understanding the risks that AI investors like Zero Shot must navigate – not just market risks, but technical and security risks as well.
Broader Implications for Business and Industry
The emergence of funds like Zero Shot signals several important trends for businesses and professionals:
- Specialization matters: As AI becomes more complex, investment decisions require deeper technical understanding than ever before.
- Insider knowledge is valuable: The Zero Shot team’s experience at OpenAI gives them unique insights into where AI is heading next.
- Selectivity is increasing: Rather than investing broadly across AI categories, sophisticated investors are becoming more selective about which technologies and approaches they back.
- The investment ecosystem is maturing: From massive corporate funding rounds to specialized VC funds, AI investment is developing multiple layers and approaches.
For businesses looking to implement AI solutions, this means they should be equally selective. The technologies that receive funding from technically sophisticated investors like Zero Shot may be more likely to deliver real value than those that simply ride the AI hype wave.
Looking Ahead: What This Means for AI Development
The launch of Zero Shot represents more than just another venture fund. It signals a maturation of the AI investment landscape, where technical expertise and insider knowledge are becoming increasingly valuable. As AI continues to evolve unpredictably, investors who understand both the technology’s potential and its limitations will be better positioned to identify truly transformative opportunities.
For professionals and businesses, this development suggests that the AI landscape is becoming more sophisticated and nuanced. The days of simply “investing in AI” are giving way to more targeted approaches that recognize the technology’s complexity and the importance of deep technical understanding. As the Zero Shot team demonstrates, knowing what not to invest in may be just as important as knowing what to back.