dispatching-parallel-agents

Dispatch parallel agents by assigning one agent per independent problem domain to avoid contention. This approach enables background execution and focused exploration for distinct tasks without sequential dependencies.

Use parallel agent orchestration when you have 3 or more distinct problems with no shared state or sequential dependencies. It reduces total execution time by allowing autonomous agents to tackle separate tasks simultaneously.

Coordinate background execution using non-blocking monitoring to track long-running agents. This allows you to dispatch multiple autonomous agents for separate tasks while waiting for their structured results to converge.

Integrate parallel agent results through structured review and convergence. As each autonomous agent completes its independent task, monitor and combine their outputs to form a coherent, integrated plan.

Dispatching parallel agents is designed for tasks with no shared state or sequential dependencies. If your problems require shared data or sequential steps, this parallel orchestration approach is not suitable.

Parallel agent dispatching works well for data collection and research synthesis. By assigning one autonomous agent per problem domain, you can gather and synthesize information from multiple independent sources simultaneously.