agent-orchestrationlisted

# Agent Orchestration Orchestration is the runtime layer: taking agents as workers and running them as a system — routing tasks, scheduling execution, handling parallelism, aggregating results, and supervising the whole fleet. Architecture designs the team; orchestration runs it. ## Overview An orchestrator owns the task lifecycle: intake (validate and normalize requests), planning (decompose into subtasks), dispatch (assign to agents with briefs), supervision (track progress, handle stalls), aggregation (combine results), and delivery. Underneath: queues, worker pools, retries, timeouts, and rate limits. The orchestrator is also the policy enforcement point — budgets, permissions, and escalation all live here. ## When to use - Running many agent tasks concurrently: batch jobs, user-facing agent fleets, background processing. - Workflows where tasks have dependencies and need scheduling, not just parallel blasting. - Production agent systems needing reliability: retries, failover, backpressure. - When you need visibility: what's running, what's stuck, what's costing money. ## Core concepts - **Task model**: tasks as structured objects — id, type, payload, priority, deadline, retry policy. Everything the orchestrator touches is a task. - **Routing**: matching tasks to agents by capability, load, and cost. Simple round-robin to start; capability-aware routing as the fleet diversifies. - **Scheduling**: ordering with dependencies (DAGs), priorities, and deadlines