As startups build on commoditized AI platforms like GPT, product differentiation becomes less of a moat. Success now hinges on cracking growth faster than rivals. The new competitive advantages are proprietary data for training models and the deep domain expertise required to find unique growth levers.

The ideal founder archetype starts with deep technical expertise and product sense. They then develop exceptional business and commercial acumen over time, a rarer and more powerful combination than a non-technical founder learning the product.

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.

Early in a technology cycle like the web or AI, successful founders must be technical geniuses to build necessary infrastructure. As the ecosystem matures with tools like AWS or open-source models, the advantage shifts to product geniuses who can build great user experiences without deep technical expertise.

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.

In a rapidly evolving space like AI, being the first mover can be a disadvantage if you bet on the wrong technical approach (e.g., fine-tuning vs. application logic). Second movers can win by observing the market, identifying the first mover's flawed strategy, and building a superior product on the correct technical foundation.