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fix: clarify multi-agent orchestration description #34

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fix: clarify multi-agent orchestration description #34

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2 changes: 1 addition & 1 deletion docs/multi_agent.md
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Expand Up @@ -27,7 +27,7 @@ This pattern is great when the task is open-ended and you want to rely on the in

## Orchestrating via code

While orchestrating via LLM is powerful, orchestrating via LLM makes tasks more deterministic and predictable, in terms of speed, cost and performance. Common patterns here are:
While orchestrating via LLM is powerful, orchestrating via code makes tasks more deterministic and predictable, in terms of speed, cost and performance. Common patterns here are:

- Using [structured outputs](https://platform.openai.com/docs/guides/structured-outputs) to generate well formed data that you can inspect with your code. For example, you might ask an agent to classify the task into a few categories, and then pick the next agent based on the category.
- Chaining multiple agents by transforming the output of one into the input of the next. You can decompose a task like writing a blog post into a series of steps - do research, write an outline, write the blog post, critique it, and then improve it.
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