One of the biggest threats to a company's focus is a bored founder. Convinced of their own intelligence, they chase new, shiny opportunities, which dilutes resources and distracts from the core mission that made them successful in the first place.

With AI commoditizing technology, the sustainable advantage for startups is the speed and discipline of their experimentation. Founders who leverage AI to operate 10x faster will outcompete those with static tech advantages, as execution velocity is far harder to replicate than a feature.

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.

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.

With traditional moats gone, the only way to stay ahead is to move faster. Defensibility now comes from the speed at which a team can ship new value and deeply understand its customers, ensuring the product is always one step ahead of a crowded field.

Instead of chasing trends or pivoting every few weeks, founders should focus on a singular mission that stems from their unique expertise and conviction. This approach builds durable, meaningful companies rather than simply chasing valuations.

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.

While moats like network effects and brand develop over time, the only sustainable advantage an early-stage startup has is its iteration speed. The ability to quickly cycle through ideas, build MVPs, and gather feedback is the fundamental driver of success before achieving scale.

In a space like AI where everyone uses the same models and tech moats are rare, competing on technology is futile. The winning strategy is to ignore the competition, focus intensely on a narrow ideal customer, and build an amazing product vision tailored specifically to their needs.