In previous tech waves, proprietary technology was a key differentiator. Now, with powerful AI models widely available, the advantage shifts to deeply understanding customer problems. The question "Should we even build this?" is more critical to creating a moat than the technology itself.

In the fast-evolving AI space, traditional moats are less relevant. The new defensibility comes from momentum—a combination of rapid product shipment velocity and effective distribution. Teams that can build and distribute faster than competitors will win, as the underlying technology layer is constantly shifting.

Early-stage founders should not prematurely optimize for defensibility. The primary focus must be on solving a real problem and building something people want. Moats are a defensive strategy that only becomes relevant once a startup has created value worth protecting.

Founders shouldn't over-engineer a moat on paper. True defensibility is often discovered, not designed. By focusing on shipping a high-NPS product that users love, a moat will naturally develop over time through emergent properties like proprietary data traces, brand loyalty, or deep user workflow integration.

Investors obsess over moats, but in a rapidly changing AI landscape, a startup's ability to quickly build and ship products that unlock latent demand is a more reliable predictor of success than any theoretical defensibility.

During massive technological shifts like the early internet or today's AI boom, predicting where sustainable moats will form is nearly impossible. The industry structure is a complex, adaptive system with too many unknowns. Early, confident proclamations about moats are almost always wrong in retrospect.

With AI development becoming accessible, having an "AI product" is not a sustainable advantage. True defensibility comes from solving a specific customer problem better than anyone else, using AI as a tool, not the core value proposition. The challenge is no longer building, but deciding what to build.

With the underlying AI technology becoming more accessible, defensibility doesn't come from how hard the software is to build. Instead, founders must focus on classic, durable moats from business strategy: network effects, brand, scale advantages, and proprietary data. These fundamentals are more critical than ever.

Casado believes AI's novelty and power are so compelling that they naturally attract early users, overcoming the cold start problem. However, long-term defensibility still requires building traditional moats like network effects, integration, or workflow ownership.