Podcast Episode Details
Back to Podcast Episodes
Teresa Torres' Step-by-Step Guide to AI Product Discovery
In today’s episode, we have one of the two voices I wanted most when I started this podcast: Teresa Torres. Alongside Marty Cagan, she was in my top guests to have.
That’s because she has trained over 17,000 PMs in 100 countries.
And in today’s episode, she’s breaking down one of the most important elements of PMing: discovery.
She gives a masterclass on how to use the learnings from her smash hit book Continuous Discovery Habits for the AI age, covering both:
1. How to do discovery for non-AI features with AI tools
2. How to discovery for AI features
If you’ve ever wondered why your product ideas sometimes flop, even when the interviews and research looked promising… you’re about to find out why!
----
Brought to you by:
Miro: The innovation workspace
Jira Product Discovery: Build the right thing
Parlance Labs: Practical consulting that improves your AI
Product Faculty: #1 AI PM Certification (Class Starts: 15 Sep, get $500 off)
----
Timestamps:
Teresa's Background - 0:00
Story-Based Interviewing - 3:20
Fake Discovery Signs - 4:08
Assumption Testing - 4:39
Continuous Discovery Framework - 5:35
AI Changes Discovery - 8:01
AI Synthesis Concerns - 9:21
AI Prototyping Era - 12:45
Ads - 15:45
AI Prototyping Workflow - 17:32
Common Interview Mistakes - 22:24
Interview Synthesis - 24:26
OST Updates - 28:53
Discovery Theater - 30:52
Ads - 32:15
Real Product Management - 34:03
AI Product Discovery - 35:29
Context Engineering - 39:16
Orchestration Explained - 42:03
Error Analysis - 46:01
Observability & Traces - 46:05
Claude Code Demo - 49:15
Business Numbers - 52:56
----
Key Takeaways:
Takeaways:
01. Stop Shipping Blind. Your AI product isn't truly valuable until you validate it. Go beyond just building; understand user needs deeply with personas, journey maps, and jobs-to-be-done.
02. MOM Test = Your Secret Weapon. The "MOM Test" is about asking questions that even your most supportive friend can't lie about. Don't ask if users "would" use your AI. Ask about their past behaviors and real problems. This helps you define success metrics and avoid building a fancy toy nobody needs.
03. Evaluate Everything, Relentlessly. AI Evals are not just a technical task for engineers, but the most critical tool for Product Managers to build high-quality, trustworthy AI products. Use them to understand, refine, and continuously improve your AI.
04. Passion Won't Land the Job. Proof Will. "I'm passionate"...great I guess, but recruit
Published on 4 weeks, 2 days ago