Growing Your App: From MVP to MLP
The episode discusses the distinction between MVP (Minimum Viable Product) and MLP (Minimal Lovable Product), using a golf score-tracking app as a case study. The hosts argue that building too many features due to AI-enabled development can complicate products unnecessarily, and emphasize the importance of user feedback, gut instinct, and resilience when determining what features actually make a product worth using.
Summary
The hosts explore the concept of MVP versus MLP in product development, distinguishing between a product that is technically viable and one that people genuinely want to use and share. Using a golf app as an example, they illustrate how an MVP might be a simple score recorder, while an MLP would include features that make people fall in love with the product—such as score history, course comparisons, and casual multiplayer tournaments.
They identify a modern problem: AI and improved development tools have made it easier to build 30-50 features quickly, leading developers to over-engineer products rather than focus on core functionality. This results in bloated applications where users typically only engage with 1-2 features despite many options being available. The hosts argue this is counterproductive and that the saved development time should instead be invested in marketing, user research, or refining key features.
The discussion covers how to gather meaningful feedback, particularly the challenge of testing with friends who may not be in the target market and whose muted responses can actually signal disinterest. They emphasize that consensus among multiple users indicates potential success, and that single one-off feature requests shouldn't drive development decisions.
A significant portion addresses resilience and trusting your instincts. Using Alex Warren's song 'Ordinary' as an example, they illustrate how an artist's belief in their work despite initial rejection led to eventual viral success when shared on BookTok. They argue that successful product development requires balancing this resilience with the wisdom to recognize true failure and pivot when necessary.
The hosts conclude by emphasizing that product development is multi-faceted, involving technical performance, marketing, user feedback, gut instinct, and personal resilience—making it one of the hardest aspects of entrepreneurship.
About this episode
We discuss the difference between an MVP and an MLP, why AI has made feature creep easier than ever, and how developers can validate ideas, prioritize features, and build products people genuinely enjoy using.
Key Insights
- The hosts observed that their own released app with 30-50 features saw users engaging with only 1-2 features, indicating that excessive feature development actually reduces rather than increases product value.
- Modern AI-assisted development has lowered the technical barrier to building, causing developers to add 15 features in the time previously required for 2-3 features, leading them to misjudge what actually matters to users.
- Friend feedback is inherently unreliable as market validation because friends are often outside the target market, responses tend to be muted regardless of actual product quality, and lack of follow-up questions signals genuine disinterest rather than politeness.
- The speakers argue that MVPs do not need to be MLPs immediately—releasing a simple MVP can still be valuable as proof of concept, and some early users may find the MVP sufficient while others indicate the direction needed for an MLP.
- Product success requires resilience paired with intuition: developers must persist through initial rejection while also recognizing when a product genuinely isn't working, making the judgment call between these states the most difficult and least teachable aspect of product development.
Topics
Transcript
All righty, everybody. This is another edition of the web news and we have sort of an interesting one, very sort of active and relevant to us right now. So we've talked over the years about MVP, which is a minimum viable product, which is sort of like, let's just use mobile app as an example, your, your most, or your minimum viable mobile app. So if you're going to be making a golf app, you know, can the thing record scores? And if it can, then that's the minimum viable product as an example. But then there's another version of MVP, which is sort of a level up, if you will, which is the MLP, which is the minimal…
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