Create an AI Interview Analysis Pipeline

Part of The AI Research Capability Stack

Hosted by John Whalen, PhD

Wed, Jul 8, 2026

4:00 PM UTC (30 minutes)

Virtual (Zoom)

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AI for Customer Research: Deliver Trusted Insights at Scale
John Whalen, PhD
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What you'll learn

Map the analysis pipeline

Break interview analysis into intake, extraction, synthesis, review, and reporting steps.

Define handoffs and artifacts

Specify what each step reads, produces, and passes to the next step.

Place human review gates

Decide where AI can run automatically and where research judgment must inspect the output.

Why this topic matters

Interview analysis is not one task. It is a chain of steps: transcript intake, cleaning, extraction, tagging, theme development, contradiction checks, synthesis, and stakeholder communication.In this Lightning Lesson, John Whalen shows how to create an AI interview analysis pipeline that keeps the work visible. You will see how to decompose the workflow, define handoffs, and make work transparent.

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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