Show HN: Context.md – A proposed standard for AI project context (github.com)

Pavel Kerbel, an independent researcher, has proposed the Repository Context Layer, a new standard aimed at enhancing AI project development by providing a structured, version-controlled context for AI agents. Currently, while source code and documentation are versioned, the critical knowledge about decisions made during the development process often remains undocumented or lost in informal communications. The Repository Context Layer aims to fill this gap by creating a human-readable store that agents can consult before planning tasks, thereby preventing repetitive mistakes and architectural drift. This innovation is significant for the AI/ML community as it establishes a framework that allows AI agents to learn from past experiences and decisions in a systematic manner, rather than starting each session with a blank slate. The proposed implementation, a simple Markdown file named context.md, will reside alongside the codebase, ensuring that context evolves with the code through a clear process of consultation, execution, updating, and committing. By utilizing established version control systems like Git, this layer not only enriches the operational context for agents but also improves safety and review processes, ultimately enabling more effective and informed AI development.