APIs, initially designed for human developers, now face the challenge of AI agents lacking the intuition to navigate poorly designed contracts. Effective implementation of Model Context Protocols (MCP) requires a shift toward context-rich API specifications. Technology leaders must adapt their approaches, ensuring API specs provide comprehensive clarity and detail, as AI cannot infer context or intent. This includes precise descriptions, clear error codes, and robust operational definitions. Organizations should evolve their culture, seeing AI as a key collaborator and prioritizing API development like a product. Legacy design habits must be addressed, promoting concise specifications and efficient pagination. Additionally, moving to capability-based versioning can improve flexibility and stability. By embracing a specification-centered development philosophy and addressing existing code gaps, companies can successfully transition into an AI-driven landscape, where semantic clarity determines competitive advantage. Emphasizing this evolution is necessary for creating high-quality, AI-ready services that meet the needs of modern users.
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