parallel-agents

To run independent tasks in parallel, you dispatch multiple problem-solving agents concurrently. This parallel processing approach reduces total resolution time when sub-tasks share no state and can execute simultaneously without dependencies.

Use concurrent agent dispatch when facing multiple independent tasks across subsystems. This parallel processing technique applies to workflows where no shared state exists between tasks and they can be executed concurrently without race conditions.

The best way to coordinate multiple agents is through non-blocking task dispatch. This method executes independent problems simultaneously and aggregates results with conflict-free consolidation, applying safeguards against hidden dependencies and race conditions.

No, you cannot execute parallel workflows if tasks have shared state or dependencies. This approach applies strictly to independent tasks with no shared state, using safeguards to prevent issues caused by dependencies and race conditions.

Result aggregation works by consolidating outputs from concurrently dispatched agents. After parallel processing completes, the system merges results in a conflict-free manner, ensuring that independent task outputs combine without race conditions or dependency issues.