Mastering Multi-Agent Coordination in OpenClaw
Building a single agent is easy. Building a fleet that works together is where the real value lies. In this guide, we explore the patterns for multi-agent coordination in OpenClaw.
The Delegation Pattern
OpenClaw is designed for hierarchy. Use a 'Commander' agent to decompose tasks and delegate to specialized sub-agents like Forge (coding) or Sage (research).
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Agents communicate through the filesystem and the database. Learn how to use the memory/ directory to pass structured state between turns without bloating the context window.
Parallel vs. Sequential Execution
When can agents work in parallel? We look at the sessions_spawn tool and how to manage race conditions when multiple agents are editing the same codebase.
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Conclusion
Coordination is the next frontier for AI deployments. By mastering these patterns, you can scale your autonomous operations far beyond what a single model can achieve.