AI Models & Assistants / Knowledge library
Orchestrator-Worker Loop
Lets a coordinator create subtasks, assign workers, inspect results, and synthesize an answer
Why learn Orchestrator-Worker Loop?
It handles tasks whose useful decomposition cannot be fully specified before execution.
The problem it solves
It dynamically divides complex work while retaining one place for integration and quality control.
Where it came from
Unlike fixed parallelization, an orchestrator determines subtasks from the input and can request additional work after reviewing results. The coordinator becomes a bottleneck and must track ownership, dependencies, and completion.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Define Orchestrator-Worker Loop and identify its place in an agent architecture.
- Choose a task where Orchestrator-Worker Loop improves an agent system.
- Diagnose one failure caused by misusing Orchestrator-Worker Loop.
- Interpret a trace or state transition involving Orchestrator-Worker Loop.
- Explain one operational tradeoff of Orchestrator-Worker Loop.
Documentation and sources
- Building Effective AI Agents (www.anthropic.com)