When AI Agents Run Their Own Team Meetings
When AI Agents Run Their Own Team Meetings
In OpenClaw, AI agents run their own team meetings. They check in, report what they are working on, flag blockers, and coordinate who handles what. It sounds like the future of software development. The reality is messier.
The File Collision Problem
Even with coordination meetings, agents step on each other's files constantly. Agent A announces "I am working on the auth module." Agent B acknowledges this. Five minutes later, Agent B modifies a utility function that the auth module imports, breaking Agent A's work. Agent B did not touch the auth module directly, so it technically followed the coordination protocol. But the dependency was not tracked.
Why Meetings Are Not Enough
Human team meetings work because humans have implicit context about codebases. When a developer says "I am working on auth," the team understands that this implicitly includes shared utilities, database migrations, and API routes related to auth. AI agents take declarations literally. "Auth module" means the auth directory and nothing else.
What Works Better
File-level coordination is too granular and dependency-level coordination is too complex. The middle ground that actually works:
Module ownership with buffer zones - Each agent owns a module plus a declared set of related files. Other agents must check before modifying anything in the buffer zone.
Commit-and-notify pattern - Agents commit frequently and notify other agents after each commit. This way, if Agent B's change breaks Agent A, Agent A discovers it within minutes, not hours.
Shared build queue - Only one agent builds at a time. Build failures get attributed to the agent that committed most recently.
The Bigger Lesson
Multi-agent coordination is fundamentally a distributed systems problem. All the lessons from distributed computing apply - consensus is expensive, eventual consistency causes conflicts, and the CAP theorem means you cannot have everything. Treat agent coordination like you would microservice architecture, not like a team standup.
Fazm is an open source macOS AI agent. Open source on GitHub.