Developer builds self-documenting repo system to give AI agents persistent project memory

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A software developer grew frustrated with AI coding agents losing all project context between sessions, forcing repeated re-explanations of architecture and decisions. To solve this, he restructured his codebase into a living knowledge base centered on two components: an AGENTS.md entry-point file and a modular agent-sitemap directory of Markdown documents. Most modern AI agent tools automatically read AGENTS.md on launch, giving any new agent or model instant access to project overviews, rules, data flows, and conventions. A built-in Documentation Sync Loop requires agents to detect, update, and confirm documentation changes before completing any task. The result is a stateless-AI workaround that lets developers switch models or open fresh sessions without losing accumulated project knowledge.

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ProgrammingDEV Community ·

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