According to Flexport's CEO, large incumbents hold significant AI advantages over startups. They possess vast proprietary data for model training, the domain expertise to target high-value problems (features, not companies), and instant distribution, allowing them to deploy AI solutions to thousands of customers overnight.

In the AI era, where technology can be replicated quickly, the true moat is a founder's credibility and network built over decades. This "unfair advantage" enables faster sales cycles with trusted buyers, creating a first-mover advantage that is difficult for competitors to overcome.

While AI agents could shift sales away from traditional retailers, companies with extensive physical infrastructure and forward-positioned inventory have a defense. AI agents prioritizing speed and efficiency for physical goods will likely still favor these established networks, preventing full disintermediation in the new agentic commerce landscape.

When asked if AI commoditizes software, Bravo argues that durable moats aren't just code, which can be replicated. They are the deep understanding of customer processes and the ability to service them. This involves re-engineering organizations, not just deploying a product.

AI capabilities offer strong differentiation against human alternatives. However, this is not a sustainable moat against competitors who can use the same AI models. Lasting defensibility still comes from traditional moats like workflow integration and network effects.

The long-held belief that a complex codebase provides a durable competitive advantage is becoming obsolete due to AI. As software becomes easier to replicate, defensibility shifts away from the technology itself and back toward classic business moats like network effects, brand reputation, and deep industry integration.

While many see autonomous vehicles as a threat to Uber's ride-hailing, its delivery segment may be more important and defensible. Automating last-mile delivery of goods from varied locations is significantly more complex and less economical than automating passenger transport, providing a durable moat.

Creating a basic AI coding tool is easy. The defensible moat comes from building a vertically integrated platform with its own backend infrastructure like databases, user management, and integrations. This is extremely difficult for competitors to replicate, especially if they rely on third-party services like Superbase.

Service company CEOs believe strong brand loyalty is their primary defense against the "DoorDash Problem." Lyft's CEO argues that users are more likely to ask an AI specifically for "a Lyft" rather than a generic "ride." They are investing in brand to ensure they are requested by name, preventing them from being disintermediated and reduced to the cheapest commodity option.