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Credits of the image to Anthropic

Overview

In the orchestrator-workers workflow, a central LLM dynamically breaks down tasks, delegates them to worker LLMs, and synthesizes their results. The key difference from parallelization is its flexibility—subtasks aren’t pre-defined, but determined by the orchestrator based on the specific input.

When to use

This workflow is well-suited for complex tasks where you can’t predict the subtasks needed (in research, for example, the specific sources to investigate and the nature of analysis required depend on what information is discovered along the way).

Using orchestrator-workers in Latitude

Research Intelligence Report
Note the use of isolate steps in all of the steps. Doing this we have a clean final synthesis of the workers’ results, without any interference from previous steps. This is crucial in orchestrator-workers workflows, as each worker’s output needs to be treated independently before the final synthesis.
This pattern is particularly effective when you have complex research questions that require different types of expertise and where the specific information sources can’t be predetermined, allowing the orchestrator to adapt the research strategy based on what information is discovered during the investigation.