# Prompt orchestration

**Source:** https://promtable.com/glossary/prompt-orchestration

> Prompt orchestration is the discipline of coordinating multiple LLM calls — routing, chaining, branching, retrying — to compose a reliable end-to-end workflow from individually less-reliable steps.

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Prompt orchestration is the discipline of coordinating multiple LLM calls — routing, chaining, branching, retrying — to compose a reliable end-to-end workflow from individually less-reliable steps.

Single-prompt apps don't survive contact with diverse real users. Prompt orchestration adds the missing infrastructure: router LLMs to dispatch to the right specialist prompt, chained calls for multi-step tasks, branching on intermediate outputs, retries on failure, structured fallback. The 2026 frameworks (LangGraph, OpenAI Agents SDK, Mastra, Pydantic-AI) treat orchestration as the primary concern. Best practice: keep individual prompts focused, enforce structure between them, and instrument the whole pipeline with traces and evals.

## When to use

- Any production LLM feature with diverse inputs.
- Multi-step workflows where reliability matters.

## Common mistakes

- Treating each prompt as independent — orchestration is where the system reliability lives.
- Skipping eval of the orchestration layer — chains hide where quality fails.

## Related terms

- [agent](https://promtable.com/glossary/agent)
- [prompt-chaining](https://promtable.com/glossary/prompt-chaining)
- [agent-loop](https://promtable.com/glossary/agent-loop)
- [model-router](https://promtable.com/glossary/model-router)

*Last updated: 2026-06-01*
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Original page: https://promtable.com/glossary/prompt-orchestration
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