OpenClaw Multi-Agent Configuration: Architecture and Production Patterns

Originally published at heyuan110.com Your single OpenClaw agent worked great for two weeks. Then it started hallucinating project context into unrelated conversations, confusing coding tasks with writing tasks, and taking 15 seconds to respond because its memory index had grown to 200MB. The problem is not the model. The problem is architectural: one agent cannot hold unlimited context domains without degradation. The solution is multiple specialized agents with isolated workspaces. This guide covers: Why multi-agent (the single-agent ceiling) Agent creation and model routing configuration Binding-based routing (most-specific-wins priority) Agent-to-agent communication via sessions_send Four production patterns: Supervisor, Router, Pipeline, Parallel Cost optimization strategies Read the full article → If you found this useful, check out my blog for more AI engineering guides.