dispatching-parallel-agents

Dispatching parallel agents is used to coordinate multiple autonomous agents to tackle independent tasks concurrently. It accelerates debugging or data gathering by assigning one agent per problem domain to avoid context bleed.

You investigate multiple independent failures by dispatching dedicated agents to each independent failure domain in parallel. This allows work to proceed concurrently without shared state, isolating the context for each agent.

You should use parallel agents for debugging when you have 3 or more failures across different subsystems that can be explored independently. This approach allows concurrent investigation to accelerate the process without interdependence.

You merge results from concurrent agents by collecting the outputs from each isolated investigation and reassembling them into a coherent plan. This approach ensures minimal coordination overhead and minimal conflict risk.

Yes, you can run analyses in parallel across different subsystems by dispatching parallel agents. Each agent operates with an isolated context and a focused prompt to prevent context bleed during concurrent investigation.

The main limitation of coordinating multiple autonomous agents is that tasks must proceed without interdependence. If failures or tasks span subsystems that require shared state, dispatching parallel agents with isolated context is not suitable.