Pushpak Chhajed writes about the evolution of project rule systems for AI coding agents, explaining why Laravel Boost moved away from complex semantic search layers in favor of a simple markdown-based approach. To prevent instruction files like `CLAUDE.md` from becoming bloated and consuming excessive context, the team implemented a system using `.ai/rules` containing specific Markdown files linked by a generated two-column index. This "progressive disclosure" method allows agents to efficiently locate relevant project conventions without overwhelming their prompt window or requiring complex vector databases for small rule sets.
- The system uses an automatically updated `index.md` file to help agents map current file paths to specific rule files.
- Agents are encouraged to use a combination of index matching and `grep -rin` to find rules that span multiple directories.
- This approach aligns with advice from the Anthropic Claude Code team regarding progressive disclosure in agentic workflows.
- The solution avoids "staleness" risks associated with maintaining separate vector embeddings for small collections of files.
- The system uses an automatically updated `index.md` file to help agents map current file paths to specific rule files.
- Agents are encouraged to use a combination of index matching and `grep -rin` to find rules that span multiple directories.
- This approach aligns with advice from the Anthropic Claude Code team regarding progressive disclosure in agentic workflows.
- The solution avoids "staleness" risks associated with maintaining separate vector embeddings for small collections of files.
