Claude Code for User Insights: What Chained Agents Can Do
Hosted by Caitlin Sullivan
Wed, Feb 4, 2026
1:30 PM UTC (30 minutes)
Virtual (Zoom)
Free to join
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Go deeper with a course
AI Analysis for PMs: From Feedback Chaos to Decisions in Hours
Caitlin Sullivan
Ex-Head of User Research at Spotify Business, Advisor to AI platforms, Top 100
Wed, Feb 4, 2026
1:30 PM UTC (30 minutes)
Virtual (Zoom)
Free to join
Go deeper with a course
AI Analysis for PMs: From Feedback Chaos to Decisions in Hours
Caitlin Sullivan
Ex-Head of User Research at Spotify Business, Advisor to AI platforms, Top 100
What you'll learn
DEMO: A multi-agent workflow run end-to-end
I'll run a live analysis: one agent categorizes, another summarizes, another pulls quotes. See what's possible when agen
What each agent does (and why the chain matters)
Breaking analysis into steps changes output quality. I'll show you what each agent handles — and why this beats one.
Where this approach is worth it (and where it's overkill)
Chained agents aren't for every task. I'll show you use cases where this shines — and when a simpler approach is enough.
Why this topic matters
Most people use AI for one-off analysis — paste data, write a prompt, hope for the best.
Chained agents are different.
You break the work into steps, let each agent do one thing really well, and pass results down the line.
The output quality is noticeably better. But most people haven't seen this in action. This session shows you what's possible — so you know what you're building toward.
You'll learn from
Caitlin Sullivan
Ex-Head of Research at Spotify Business/SYB ᐧ AI Advisor for Customer Insights
Why trust me?
- Product teams like Maze hire me to fix prompts behind their AI tools—I help them build the functionality that gets customers better AI results.
- Ex-Head of User Research at embedded in Product—sitting alongside PMs shipping B2B products. I know how fast feedback piles up.
- Trained 450+ people at Canva, YouTube, Figma, Meta, and more to use AI for analysis they can actually defend in high-stakes decisions. (My previous course is rated 4.8/5)
- 1500+ hours testing AI for customer insights.
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