The 10x Rule: Turning a Research Paper into an AI Company

About this episode

The episode discusses how a research paper evolved into a venture-backed AI company and the challenges faced in building a deep-tech startup.

Most startup advice assumes the biggest challenge is finding customers. But what happens when the demand is obvious and the real question is whether the technology can actually work at scale? In this episode of Fund/Build/Scale, I sit down with Stanford professor and Inception Labs founder and CEO Stefano Ermon to discuss how a breakthrough research paper evolved into a venture-backed AI company serving enterprise customers. Stefano explains why his team believed they needed a 10x advantage in speed, cost, or quality to compete with industry giants, and how they convinced investors to back an idea that was still largely unproven. We explore the realities of building a deep-tech startup, including raising capital before product-market fit, assembling a world-class founding team, learning enterprise sales as a first-time CEO, pricing a new category of technology, and competing with companies like Google, OpenAI, and Anthropic. Along the way, Stefano shares practical advice for technical founders trying to transform research into a business, de-risk ambitious ideas, and create evidence that investors can believe in before the market fully understands what they're building. In this…

People in this episode

Host: Walter Thompson

Guest: Stefano Ermon

Topics covered

• AI startups
• venture capital
• deep-tech
• enterprise sales
• research commercialization
• technical risk

Keywords

• 10x advantage
• venture-backed
• capital raising
• product-market fit
• founding team
• enterprise customers
• technical founders

Mentioned in this episode

Organizations: Stanford, Inception Labs, Google, OpenAI, Anthropic

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