The "AI wrapper" concern is mitigated by a multi-model strategy. A startup can integrate the best models from various providers for different tasks, creating a superior product. A platform like OpenAI is incentivized to only use its own models, creating a durable advantage for the startup.

Michael Burry's comparison of OpenAI to Netscape is apt regarding market share erosion due to intense competition. However, the AI market is expanding exponentially. Unlike the browser market of the 90s, OpenAI can lose market share percentage yet still see massive absolute revenue and usage growth.

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.

Startups are becoming wary of building on OpenAI's platform due to the significant risk of OpenAI launching competing applications (e.g., Sora for video), rendering their products obsolete. This "platform risk" is pushing developers toward neutral providers like Anthropic or open-source models to protect their businesses.

The choice between open and closed-source AI is not just technical but strategic. For startups, feeding proprietary data to a closed-source provider like OpenAI, which competes across many verticals, creates long-term risk. Open-source models offer "strategic autonomy" and prevent dependency on a potential future rival.

As competitors like Google's Gemini close the quality gap with ChatGPT, OpenAI loses its unique product advantage. This commoditization will force them to adopt advertising sooner than planned to sustain their massive operational costs and offer a competitive free product, despite claims of pausing such efforts.

Large platforms focus on massive opportunities right in front of them ('gold bricks at their feet'). They consciously ignore even valuable markets that require more effort ('gold bricks 100 feet away'). This strategic neglect creates defensible spaces for startups in those niche areas.

OpenAI has seen no cannibalization from its open source model releases. The use cases, customer profiles, and immense difficulty of operating inference at scale create a natural separation. Open source serves different needs and helps grow the entire AI ecosystem, which benefits the platform leader.

Despite its early dominance, OpenAI's internal "Code Red" in response to competitors like Google's Gemini and Anthropic demonstrates a critical business lesson. An early market lead is not a guarantee of long-term success, especially in a rapidly evolving field like artificial intelligence.