dispatching-parallel-agents

To dispatch parallel agents, you first identify independent problem domains without shared state, create focused prompts with clear goals and constraints for each, run them concurrently, and finally aggregate their outputs for review. This approach accelerates resolution by investigating unrelated tasks simultaneously.

You should use parallel agents when you need to investigate multiple unrelated failures or tasks that have no shared state and can be explored within clearly defined domains. This allows each agent to investigate an isolated problem concurrently before you review and integrate the findings.

You create focused agent prompts by assigning each agent a clear scope, goal, and constraints for its specific independent domain. This ensures that each parallel agent investigates its assigned problem without overlapping or relying on shared state during the dispatch.

No, parallel agent dispatch does not work for tasks with shared dependencies. It specifically applies when multiple failures or tasks are unrelated and can be explored without shared state, requiring clearly defined domains and isolated prompts to ensure non-conflicting fixes.

The best way to integrate outputs from parallel agents is to compare their findings, ensure the proposed fixes do not conflict with each other, and then integrate the non-conflicting results into the main workflow. This mechanism aggregates isolated agent outputs for final review.