dispatching-parallel-agents

To run parallel agents for independent tasks, you dispatch multiple autonomous agents to investigate failures concurrently. This approach prevents cross-domain interference by ensuring each agent works on a problem solvable without shared state or cross-task dependencies.

You should dispatch parallel agents when you have 3 or more unrelated tasks or failures. This pattern applies when each task is independent, solvable without shared state, and can benefit from concurrent execution to save time and avoid cross-domain interference.

To synthesize results from multiple autonomous agents, you review, reconcile, and integrate their findings into a single consolidated report. The process includes guardrails to create focused tasks, run them concurrently, and integrate findings without conflicts.

Parallel task coordination is not suitable for AI pipeline failures with shared dependencies. The dispatching pattern requires that each task or failure is solvable without shared state or cross-task dependencies to avoid conflicts during concurrent execution.

The best way to coordinate multiple autonomous agents investigating independent failures is to assign a focused agent to each problem domain. You dispatch them to run in parallel and synthesize results without overlapping state, integrating findings into a single report.