The MVP Myth That’s Breaking Product Teams with Chuck Moxley and Nick Paladino
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Join hosts Chuck Moxley and Nick Paladino as they tackle one of product development's most polarizing debates: the Minimum Viable Product. Drawing insights from companies like Duolingo and referencing their previous conversation with Nakul Goyal from Carfax, Nick and Chuck explore whether MVPs encourage smart learning or just create a culture of half-finished products.
They dissect the difference between "low minimum" and "high minimum" approaches, expose how "finding the green" leads to cherry-picked data, and reveal why product bloat happens when teams try individual valuable features without measuring what they displaced. Most importantly, they argue that the real problem isn't MVPs themselves—it's whether your culture is built around making customers happy or making the wrong people happy.
Key Actionable Takeaways:
- Redefine "minimum" based on customer value, not developer speed - The developer defines what's technically achievable fastest, but minimum should prioritize what creates viable user value, not just "does it work"
- Use production data to guide iteration, not cherry-pick success metrics - Avoid "finding the green" by searching for any positive indicator; instead, let real user data guide your vision and be willing to kill 6 out of 7 tested features
- Measure diminished value when adding new features - Product bloat occurs when you validate each new feature individually without assessing how it reduces the value of existing features it displaces or pushes down the page
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Nick Paladino's LinkedIn: https://linkedin.com/in/npaladino
Chuck Moxley's LinkedIn: https://linkedin.com/in/chuck-moxley
Chapters:
(00:00) Introduction - The MVP controversy
(01:00) Defining minimum viable - What does it really mean?
(02:00) Minimum lovable vs minimum viable - Nakul Goyal's approach
(03:00) Who defines minimum and how?
(05:00) Product bias and "finding the green"
(08:00) Product bloat - When features cannibalize each other
(10:00) Low minimum vs high minimum approaches
(12:00) Revolut case study - When testing breaks the experience
(16:00) Duolingo's approach - Getting streaks wrong then right
(19:00) How to measure "lovable" - The data question
(21:00) Culture matters more than methodology
(23:00) Conclusion
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