Why AI Moats Still Matter (And How They've Changed)

In a panel discussion, David Haber and Alex Rampell explore the evolving nature of moats in the age of AI, emphasizing that while AI serves as a powerful tool for differentiation, traditional moats like owning end-to-end workflows, becoming a system of record, and deep customer embedding remain critical for defensibility. They discuss how the ease of software creation due to AI increases competition, making it harder to achieve the scale necessary to demonstrate a moat, and debate whether incumbents are more or less defensible in the AI era, considering factors like pricing models and the potential for vibe-coded competitors. The conversation also covers the Goldilocks zone of pricing, Greenfield opportunities, and the importance of momentum in achieving gravitational scale, while also addressing the question of whether major AI players like OpenAI will overshadow smaller companies.