Product management fundamentals are timeless. But the tools? Completely transformed.

Every PM needs to master new workflows in 2025:

AI Prototyping - From text to live prototype in minutes

Design Collaboration - Working with designers in the AI age

User Research - Systematic validation that actually works

Problem Definition - The only bottleneck that matters

Team Dynamics - Escaping the "Jira jockey" trap

So, in today's episode, I bring you the definitive guide to product management in the AI era:

I’ve teamed up with Dan Olsen - author of The Lean Product Playbook and one of the most respected voices in product management for over 15 years.

Dan has seen it all: from the early days at Intuit to consulting with hundreds of startups.

He's been through the internet wave, mobile wave, and now the AI wave.

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Timestamps:

Introduction - 0:00

Lean Product Playbook Origins - 1:49

AI's Real Impact on PMs - 3:44

The Prototyping Revolution - 5:18

Ads - 12:02

Solution Space Risks - 14:18

When Designers Become Bottlenecks - 22:49

AI Tool Recommendations - 26:37

Ads - 32:21

Design Process Evolution - 34:07

User Research Hierarchy - 42:32

Testing Methods Explained - 44:34

Running User Sessions - 53:05

Avoiding Interview Mistakes - 1:01:15

Systematic Feedback Capture - 1:03:23

Escaping Jira Jockey Trap - 1:08:46

Current BS Trends - 1:11:55

Dan's Revenue Breakdown - 1:13:34

Where to Find Dan - 1:18:33

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Key Takeaways:

1. AI hasn't changed the fundamentals. You still need to understand customers, identify problems, and prioritize opportunities. AI can't tell you about your customers or validate market needs for you.

2. Prototyping is the biggest unlock. What used to take weeks (text → sketches → wireframes → Figma → code) now happens in minutes (text → live prototype). This is where AI truly transforms PM work.

3. Start with Lovable/Bolt, graduate to Cursor. Lovable and Bolt are perfect for quick prototyping without code. Cursor gives you more control and learning opportunities for serious AI PMs willing to touch code.

4. The design gap is closing. AI tools have moved every team up 1-2 levels in UX maturity. Teams without designers can now create professional prototypes, but still need humans for breakthrough innovation.

5. Match research method to uncertainty. New product/market = in-person research. Existing product usability = remote unmoderated. The more uncertain you are, the more human interaction you need.

6. Use the three-bucket system. Categorize all user feedback into: Feature Set, UX Design, and Messaging. Test in waves of 5-8 users, track percentages, fix issues, repeat.

7. Good usability ≠ product-market fit. Always ask "How likely are you to use this?" at the end. Dan learned this the hard way - zero complaints doesn't mean people want your product.

8. Protect discovery time. If your PM-to-dev ratio is above 1:8, you're probably a Jira jockey. Use Dan's 4 D's: Discover → Define → Design → Develop. Spend meaningful time in all four.

9. Collaborate, don't replace designers. Be upfront: "This prototype is directional, not pixel-perfect." Use AI for quick validation, bring designers in for differentiated experiences and innovation.

10. Stop sprinkling AI everywhere. AI is a solution looking for problems. Start with real customer pain points, then figure out if AI solves them better than existing approaches.