dispatching-parallel-agents

To run independent tasks in parallel, you dispatch each task to a dedicated agent without shared state. This isolates context to prevent cross-talk and aggregates outputs for final coordination.

Use parallel agent dispatch when you have 2 or more independent problems that can be addressed without cross-task dependencies, allowing them to run concurrently and reduce total turnaround time.

Orchestrating concurrent agents without shared state requires defining isolated agent prompts and assigning each independent problem to a dedicated agent, then aggregating the results into a cohesive coordination summary.

No, parallel task distribution applies only when you have 2 or more independent problems that can be addressed without cross-task dependencies or shared state to ensure reproducibility.

You aggregate outputs from multiple parallel agents by collecting the isolated results from each dedicated agent and providing a cohesive coordination summary after all concurrent tasks are complete.

Yes, dispatching parallel agents reduces total turnaround time by decoupling independent tasks into separate domains and running them concurrently without shared state or sequential dependencies.