dispatching-parallel-agents

Parallel task dispatch works by assigning independent problems to specialized agents with isolated context, allowing them to execute concurrently. This mechanism preserves context, speeds up resolution, and keeps unrelated problem domains separate from each other during execution.

You should use parallel agents for debugging automation when facing multiple independent failures across different domains. If the failures are unrelated and can be tackled concurrently without relying on each other's context, parallel execution reduces total resolution time compared to sequential processing.

To set up parallel orchestration, first split your failures into separate problem domains. Define clear goals and per-agent constraints for each domain, dispatch one agent per problem area, and run them concurrently. Finally, apply a mechanism to aggregate the results from all agents.

Aggregating results from parallel agents requires clearly defined problem domains, per-agent constraints, and a dedicated mechanism to combine outputs. You must ensure each agent operates with isolated context and handles a single domain so the aggregation mechanism can process the concurrent outputs effectively.

Parallel task dispatch is designed for independent-domain problems where failures are unrelated. If your debugging failures share context or depend on each other within the same domain, sequential processing is more appropriate to avoid context mixing and ensure accurate resolution.