During a major technology shift like AI, the most valuable initial opportunities are often the simplest. Founders should resist solving complex problems immediately and instead focus on the "low-hanging fruit." Defensibility can be built later, after capitalizing on the obvious, easy wins.

While not in formal business frameworks, speed of execution is the most critical initial moat for an AI startup. Large incumbents are slowed by process and bureaucracy. Startups like Cursor leverage this by shipping features on daily cycles, a pace incumbents cannot match.

Incumbent companies are slowed by the need to retrofit AI into existing processes and tribal knowledge. AI-native startups, however, can build their entire operational model around agent-based, prompt-driven workflows from day one, creating a structural advantage that is difficult for larger companies to copy.

The historical advantage of being first to market has evaporated. It once took years for large companies to clone a successful startup, but AI development tools now enable clones to be built in weeks. This accelerates commoditization, meaning a company's competitive edge is now measured in months, not years, demanding a much faster pace of innovation.

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.

In a gold rush like AI, the shared 'why now' forces many founders into a pure speed-based strategy. This is a dangerous game, as it often lacks long-term defensibility and requires an incredibly hard-charging approach that not all teams can sustain.

AI tools drastically reduce the time and expertise needed to enter new domains. This allows startups to pivot their entire company quickly to capitalize on shifting investor sentiment and market narratives, making them more agile in a hype-driven environment where narrative alignment attracts capital.

An enterprise CIO confirms that once a company invests time training a generative AI solution, the cost to switch vendors becomes prohibitive. This means early-stage AI startups can build a powerful moat simply by being the first vendor to get implemented and trained.

ElevenLabs' CEO sees their cutting-edge research as a temporary advantage—a 6-12 month head start. The real, long-term defensibility comes from using that time to build a superior product layer and a robust ecosystem of integrations, workflows, and brand. This strategy accepts model commoditization and focuses on building durable value on top of the technology.