Reading up on documentation

The article examines why developers often avoid native web platform features, citing historical gaps, familiarity, documentation, enjoyment of building, and AI's influence on code choices.

A developer describes a build system that auto-captures screenshots from a live web app via Markdown comments, ensuring documentation images never go stale.

Developer portals should optimize for AI coding agents by structuring documentation with llms.txt, token-efficient formatting, and capability signaling via skill.md.

Mintlify built a multi-agent system that auto-generates production-ready documentation sites from any public GitHub repo by planning structure first, then writing pages in parallel within sandboxed AI agents.

Tool description quality and specificity, especially when not to use a tool, significantly influence whether AI agents select it over alternatives.

SuperDocs uses AI to generate searchable documentation sites from code repositories by analyzing types, flows, and dependencies.

Large software products are so complex and rapidly changing that even engineers often cannot answer basic questions about them without investigative research.

Google's Code Wiki uses Gemini to automatically generate and maintain interactive documentation, diagrams, and AI chat for code repositories, staying synced with every PR merge.