dispatching-parallel-agents

Parallel debugging works by orchestrating the concurrent execution of multiple independent AI agents to resolve distinct problem domains. Each agent operates within a focused, self-contained scope, preventing cross-contamination of state while handling unrelated bug reports or test failures simultaneously.

To set up parallel agent dispatch, clearly define the scope, constraints, and expected output for each sub-agent. Assign one agent per independent module, such as authentication, database, and UI, to investigate and fix failing test files simultaneously rather than sequentially.

Yes, you can use parallel agent orchestration for feature requests that do not share state or sequential dependencies. The skill handles multiple independent tasks concurrently, ensuring each agent operates within a focused, self-contained scope to prevent cross-contamination.

The best way to fix unrelated bugs across different modules is dispatching parallel agents. This method simultaneously triggers multiple specialized agents to handle unrelated failures or subsystems, accelerating debugging by enabling concurrent execution instead of sequential processing.

You should not use parallel agents for debugging when your tasks share state or have sequential dependencies. This approach requires clear definition of scope and constraints for each sub-agent, making it unsuitable for tightly coupled problems that require sequential resolution.