OpenAI embraces the 'platform paradox' by selling API access to startups that compete directly with its own apps like ChatGPT. The strategy is to foster a broad ecosystem, believing that enabling competitors is necessary to avoid losing the platform race entirely.

Synthesia initially targeted Hollywood with AI dubbing—a "vitamin" for experts. They found a much larger, "house-on-fire" problem by building a platform for the billions of people who couldn't create video at all, democratizing the medium instead of just improving it for existing professionals.

Intense competition forces companies to innovate their products and marketing more aggressively. This rivalry validates the market's potential, accelerates its growth, and ultimately benefits the entire ecosystem and its customers, rather than being a purely zero-sum game.

For companies with jaw-dropping technology, it's easy to chase 'wow moments' and PR instead of solving real problems. Synthesia instills a core value of 'utility over novelty,' obsessing over delivering value for enterprise customers rather than getting lost in the novelty of their own tech.

Small firms can outmaneuver large corporations in the AI era by embracing rapid, low-cost experimentation. While enterprises spend millions on specialized PhDs for single use cases, agile companies constantly test new models, learn from failures, and deploy what works to dominate their market.

The AI industry is not a winner-take-all market. Instead, it's a dynamic "leapfrogging" race where competitors like OpenAI, Google, and Anthropic constantly surpass each other with new models. This prevents a single monopoly and encourages specialization, with different models excelling in areas like coding or current events.

AI drastically accelerates the ability of incumbents and competitors to clone new products, making early traction and features less defensible. For seed investors, this means the traditional "first-mover advantage" is fragile, shifting the investment thesis heavily towards the quality and adaptability of the founding team.

The founders, not being PhD AI researchers, knew they couldn't rely on being acqui-hired by a tech giant. This perceived weakness became a strength, forcing them to relentlessly focus on finding customers and building a sustainable business from day one, unlike many research-led AI startups of that era.

Conventional venture capital wisdom of 'winner-take-all' may not apply to AI applications. The market is expanding so rapidly that it can sustain multiple, fast-growing, highly valuable companies, each capturing a significant niche. For VCs, this means huge returns don't necessarily require backing a monopoly.