A few days ago, I sat down to do something I've done a hundred times: write documentation for a library I made. The project is called binarystruct —a Go library that helps serialize and deserialize binary data using struct tags. With tools like Claude Code, Cursor, and Gemini by my side, I had finally updated the library after years of neglect. Satisfied with the code, I prepared to write the docs. And then, I had a sudden realization: No human is ever going to read this. Almost every developer using my library today would not read my documentation; they are copying my repository URL, pasting it into a coding agent, and saying: "Implement a ZIP encoder using this library." So I decided to adapt my repository for these new AI consumers. I read the community standards, scaffolded the emerging llms.txt and llms-full.txt files, wrote a detailed agent-facing manual, and prepared for a future of frictionless AI integrations. Then I actually measured it.…