Orchestrate Your Agentic Research Team

Part of The AI Research Capability Stack

Hosted by John Whalen, PhD

76 students

In this video

What you'll learn

Define specialist agent roles

Create agents for extraction, contradiction checks, synthesis, and evidence review.

Design useful handoffs

Make each agent produce structured outputs the next step can inspect and use.

Learn agentic orchestration patterns

Learn the different ways you can sequence and orchestrate your team of agents.

Why this topic matters

Multi-agent systems are useful when different parts of the research work need different responsibilities. Interview analysis is a good example: one agent can extract evidence, another can find contradictions, another can draft synthesis, and a human can review the final claim. In this Lightning Lesson, John Whalen shows how to orchestrate an agentic research team for interview analysis.

You'll learn from

John Whalen, PhD

CEO, AI Research Leader, Cognitive Scientist, O'Reilly Author

I’m CEO of Brilliant Experience, have a PhD in cognitive science, and wrote Design for How People Think (O’Reilly).

For 20 years, I’ve helped teams at companies like Google, GSK, and Capital One better understand their customers, capture insights, and build better products.

When AI started reshaping research, I got curious and learned. My team ran “AI vs. Humans” studies to see where AI excels, where human judgment matters most, and how to effectively blend both.

I’ll teach you how to create trustworthy AI research workflows that let you trace every step and insight.

Then advance to the next course and learn to orchestrate agentic research teams, work strategically with synthetic users grounded in real data, and bring in human judgement so you can scale research without losing rigor.

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