dispatching-parallel-agents

To execute independent tasks in parallel without interference, delegate each task to a specialized sub-agent that operates in strict context isolation. This ensures no session data leaks between tasks, requiring only a final integration step to merge the isolated results into a single output.

Parallel agent delegation is the distribution of 2 or more unrelated issues to independent agents for concurrent execution. You should use this orchestration model when tasks have no shared state dependencies, clear individual scopes, and no sequencing constraints, allowing them to run simultaneously.

No, parallel sub-agents require strict task isolation and cannot handle sequencing constraints. If your tasks depend on a specific execution sequence or share state between operations, this concurrent delegation model will fail because each agent operates independently without cross-task communication.

The best way to orchestrate concurrent agents is assigning each independent issue to a dedicated sub-agent with isolated context, then coordinating their outputs in a single final integration step. This simple orchestration model scales effectively with the number of tasks without shared-state dependencies.

Yes, you need a final integration step to manually merge results after dispatching parallel agents. While the sub-agents execute their isolated tasks concurrently, the orchestration model requires you to coordinate and combine their independent outputs into a unified final result.

Parallel agent execution requires clear per-task scope and context isolation to prevent cross-task interference. Each sub-agent must receive only its own data to ensure safe, independent operation, preventing session context leaks that could corrupt the concurrent execution of unrelated issues.