dispatching-parallel-agents

To run parallel AI agents, you provide a list of independent tasks and the system dispatches one agent per non-overlapping domain. This concurrent execution reduces investigation time when multiple unrelated issues have no shared state across files or subsystems.

Use parallel task dispatch when you have three or more unrelated failures across different files or subsystems. It allows concurrent work across domains, preventing cross-contamination between investigations and reducing context switching.

To dispatch independent tasks, structure your prompt to assign one agent per domain with clear task separation and non-overlapping scopes. For example, list the files or modules and instruct the system to investigate them in parallel and report findings.

No, parallel agents require clear task separation and non-overlapping scopes. This approach applies only when multiple issues are unrelated and have no shared state, ensuring the concurrent execution does not cause cross-contamination.

Parallel task dispatch is a technique that allocates one AI agent per independent problem domain to work concurrently. By separating unrelated investigations into non-overlapping scopes, it reduces context switching and significantly cuts down overall debugging time.