How AI Agents Can Coordinate Across Multiple Repositories

As AI coding agents become more capable, developers are discovering they struggle when features span multiple repositories—each agent optimizes locally while breaking end-to-end product flows. This article proposes a lightweight, file-based coordination layer that lets multiple AI agents work independently while staying synchronized. The approach addresses a critical gap in AI-assisted development: maintaining system coherence when changes touch multiple codebases.