Show HN: An AI collaboration playbook(AGENTS.md and code map and template) (www.privydrop.app)

A new open-source initiative, showcased in an HN post, offers an AI collaboration playbook intended to improve the quality and reliability of AI-assisted coding. Named "AGENTS.md," this framework provides a structured approach to using AI as a collaborator rather than a simple tool, addressing common pitfalls such as code divergence and quality drop-offs. The playbook includes essential documents like a project snapshot, code maps, and collaboration rules, designed to streamline the engineering workflow, ensuring clear boundaries and expectations for AI interactions. By implementing this approach, the team behind the project, PrivyDrop, experienced faster and steadier feature shipping and bug fixing. This playbook's significance lies in its practical methodology for enhancing AI collaboration in software development. By incorporating hard constraints and clear documentation right into the repository, teams can mitigate risks and avoid costly rework. Key components of the playbook include a repository-wide AGENTS.md that outlines core principles, a high-signal index for quick navigation, and structured plans for code changes, which help ensure that AI maintains the necessary context throughout its interactions. The adoption of such frameworks marks an evolution in how developers can leverage AI tools, promoting sustainability and efficiency in coding practices.