By building a feature that competes directly with startups using its own API, Anthropic demonstrates the "platform risk" inherent in the AI ecosystem. Like Amazon with its Basics line, foundation model companies can observe usage, identify valuable applications, and integrate them, creating a kill-zone for dependent companies.

Building a business entirely on a closed-source API from a major provider like Anthropic or OpenAI is precarious. These platform companies can and do release new capabilities that directly compete with and subsume the functionalities of startups in their ecosystem, effectively erasing their business overnight.

Developers using OpenAI's API are warned that Sam Altman will analyze their usage data to identify and build competing features. This follows the classic playbook of platform owners like Microsoft and Facebook who studied third-party developers to absorb the most valuable use cases.

Startups building on OpenAI or Anthropic APIs face a major platform risk. Their usage data trains the underlying foundational models, enabling the platform owners to eventually absorb their features natively and make the startups obsolete.

Widespread anxiety from founders before OpenAI's Developer Day highlights a key challenge for AI startups. The fear is not a new competitor, but that the underlying platform (OpenAI) will launch a feature that completely absorbs their product's functionality, making their business obsolete overnight.

Startups building on proprietary AI platforms like Anthropic or OpenAI face significant risk. The platform can analyze token usage, identify successful applications, and then launch a competing, integrated feature, as Anthropic did to its partner Cursor with Claude Code.

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.

To avoid a future where a few companies control AI and hold society hostage, the underlying intelligence layer must be commoditized. This prevents "landlords" of proprietary models from extracting rent and ensures broader access and competition.