As coding agents continue to improve, I've noticed that the hardest problems are no longer about generating code. Claude Code, Codex, Gemini CLI, Cursor, and other agents are already capable of implementing features, refactoring applications, writing tests, and navigating large repositories with very little guidance.
The real challenge begins when multiple autonomous workers need to collaborate on the same project.
Most development tooling was designed around humans. Git records history, GitHub manages collaboration, CI systems automate builds, and editors provide an interface for writing code. Those tools work extremely well because humans naturally communicate outside the system. We discuss implementation details in Slack, leave comments on pull requests, create tickets, and coordinate work through meetings.
AI agents don't have those implicit communication channels.
Every agent starts from its own context window. It doesn't know whether another worker is already implementing the same feature, whether a file is currently being modified, which decisions have already been made, or what work remains after another agent terminates unexpectedly. As more autonomous workers participate in software development, coordination becomes a systems problem rather than a prompting problem.
