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Parallel task execution fires multiple agents at once to handle independent subtasks like builds, tests, and deployments concurrently. This reduces total completion time and improves throughput in complex automation scenarios.

Agent orchestration for concurrent execution is a lightweight coordination layer that delegates independent subtasks to multiple agent executors simultaneously. It provides parallelism without persistence, optimizing throughput while preserving control.

Model routing orchestration allows you to select appropriate agent tiers for different tasks during parallel execution. This explicit routing optimizes throughput by matching task complexity to the right execution model.

The lightweight orchestration layer works with higher-level modes like ralph and autopilot to provide parallelism without persistence. It integrates into existing automation workflows to accelerate independent task completion.

Use parallel execution when you have multiple unrelated subtasks that can run simultaneously, such as parallel builds, tests, deployments, or data processing pipelines. It applies to scenarios with independent operations that do not require sequential processing.

Optional background execution is supported to optimize throughput while preserving control. This allows parallel tasks to continue running without blocking the main workflow, improving overall automation efficiency.