openclaw

You can build autonomous agent factories by using a multi-agent coordination pattern that manages task flow, spawns worker agents, and synthesizes results to enable parallel task execution.

Multi-agent coordination works by using shared YAML files for inter-agent communication, allowing agents to manage tasks, synchronize state, and handle errors through defined protocols.

Complex multi-agent workflows require specialized agent roles such as orchestrator, worker, researcher, and reviewer to manage distinct phases of task execution and synthesis.

No external dependencies are required to set up an orchestrator for autonomous agents, as the framework relies entirely on internal scripts and shared YAML files for coordination.

The best way to handle error management in multi-agent automation workflows is by utilizing shared state files like kill-signals.yaml to communicate failures and coordinate error handling across agents.

Yes, you can use shared YAML files to coordinate an automated workflow where a researcher agent gathers data, a worker implements features, and a reviewer agent evaluates the code.