Overview
This example demonstrates the orchestrator-workers pattern, where a central AI agent dynamically breaks down complex tasks and delegates them to specialized worker agents. This pattern is particularly effective when tasks require multiple perspectives or parallel processing streams, with the orchestrator synthesizing the results into a cohesive output.
Example task
Our example task uses multiple LLM calls to extract claims from a news article and analyze them in parallel, combining source verification and historical context to assess their credibility. This task:- Uses
generateTextfrom Vercel’s AI SDK to interact with OpenAI models - Uses
experimental_telemetryto provide LLM logs - Uses
batch.triggerByTaskAndWaitto orchestrate parallel processing of claims - Extracts factual claims from news articles using the
o1-minimodel - Evaluates claims against recent sources and analyzes historical context in parallel
- Combines results into a structured analysis report
Run a test
On the Test page in the dashboard, select thenews-fact-checker task and include a payload like the following:

