Cluster
Orchestration
The orchestration cluster covers principles that help teams represent delegated workflows as systems — with clear nodes, boundaries, and review points — rather than as opaque conversational flows.
Key Facts
- Cluster
- Orchestration
- Principles
- 1
- Linked examples
- 6 implementation library examples
- Principle titles
- Represent delegated work as a system, not merely as a conversation
Principles in this cluster
Implementation examples
- Level 1: Augmented LLM — Single API CallOne model call with structured output, system prompt, and context. No loops, no tools.script · advanced
- Level 2: Prompt Chains & Routing — Deterministic DAGsMultiple LLM calls in a fixed sequence. Code controls the flow, not the model.script · advanced
- Level 3: Tool-Calling Agent — Scoped AutonomyThe agent decides which tools to call and in what order, but only within a fixed set of well-defined capabilities.script · advanced
- Level 4: Agent Harness — Full Runtime AccessGive the agent a full runtime via the agent runtime SDK. It can search files, read docs, and reason through problems autonomously.script · advanced
- Level 5: Multi-Agent Orchestration — Delegated AutonomyAn orchestrator delegates to specialized subagents defined via the agent runtime SDK. Each subagent has its own prompt, tools, and model. The orchestrator coordinates.script · advanced
- Get Single PageRunnable example (intermediate) for script using docling, openai.script · intermediate