sadd:do-in-steps

Multi-agent orchestration decomposes complex tasks into sequential subtasks, dispatching parallel meta-judges and implementation agents for each step. It passes context between steps and uses LLM-as-a-judge verification with retry loops to ensure reliable outcomes.

To use LLM-as-a-judge for automated task verification, the orchestrator dispatches parallel meta-judges that generate evaluation specifications. Independent judges then verify each step's output, triggering retry loops if verification fails to ensure reliable outcomes.

Yes, you can run parallel meta-judges for step-wise task execution. The orchestrator dispatches parallel meta-judge and implementation agents per step, generating evaluation specifications and performing independent verification with controlled retries.

The best way to orchestrate sub-agents for complex automation tasks is using sequential task decomposition with parallel meta-judges. This approach selects optimal agents, passes context between steps, and handles retry loops without directly executing code.

No, multi-agent orchestration does not execute code directly during task decomposition. The orchestrator operates strictly through dispatched sub-agents, selecting optimal agents and passing context between steps while relying on independent verification for reliable outcomes.