Beyond MVP: AI and “Minimum Useful Product”
This week I explored a concept that emerged from a client conversation: the “Minimum Useful Product.” It’s not just another buzzword to add to our lexicon—it’s a recognition that AI has fundamentally redrawn the economics of software development.
AI Summary
This talk examines how AI is forcing us to rethink the traditional MVP (Minimum Viable Product) approach. When a successful podcast client shared that “being useful” was their guiding principle over years of evolution, it sparked a deeper reflection on how we scope and ship software today.
The traditional binary choice—ship something scrappy fast or take time to polish it—is dissolving. AI enables us to build functional, aesthetically appealing, brand-aligned software much faster than before. This shifts the economic trade-off space that engineers have navigated for the past 15 years. The “Minimum Useful Product” concept acknowledges that simply having digital software that works is no longer enough in a world saturated with SaaS tools. We need to deliver something genuinely useful from day one, but we can now do so without the traditional time penalty.
The implications extend beyond product development: pure IC (Individual Contributor) roles may become less viable as AI handles more heads-down coding, pushing engineers toward deeper business integration and cross-functional collaboration—something agile practices have advocated for years, but economics are now forcing.
Chapters
(00:00:01) - Introduction: Minimum Useful Product
(00:00:10) - The Evolution from MVP to MLP
(00:02:23) - When “Useful” Becomes the North Star
(00:03:40) - Why the Bar Has Changed: SaaS Saturation
(00:04:29) - AI Blurs the Binary Choice
(00:06:37) - Hard Agile vs. Soft Agile
(00:08:26) - The “We’ll Come Back to It” Problem
(00:10:19) - Reassessing Our Trade-Off Paradigms
(00:13:06) - The Cost of “Making It Look Better” Has Collapsed
(00:13:45) - My First Fractional AI-Assisted Coding Work
(00:15:39) - The Future: No More Pure ICs?
(00:17:08) - What’s Coming Next
Key Moments
The Guiding Principle (01:41) - “The kind of guiding principle in her words was that they always wanted it to be useful. The actual format actually where they did that would always change might change but that core kind of value of being useful kind of remained.”
The Blurring Binary (04:59) - “I think that binary choice or what felt like a binary choice is increasingly getting blurred. It is much more possible to ship prototype features much faster. You can incorporate brand guidelines much more easily.”
Software’s Economic Reality (09:47) - “Software is completely bound to the economics both of the industry and the company that we’re operating in. It’s not as much as it can be nice to kind of be removed from it and just be able to treat software as this kind of abstract entity—it’s deeply embedded in the economics of the situation we’re operating in.”
The Trade-Off Space Redrawn (11:32) - “AI just completely, you know, this is an economic trade-off space... AI just like really rejigs, makes this trade, drawing this trade-off space way more difficult. And obviously every time some new model gets released, every time new capability of the frontier models changes, that redraws it.”
The Context Switch Revolution (14:32) - “Traditionally as an engineer, what I’d have to do is I need half a day, I need a day to really get into the problem. And now, you know, certainly for like simpler problems, I can spin up the agent, ask it... I’ll go do something else, come back. It’s given me some options. I can review them. And so suddenly I’m able to actually write relatively productive code.”
The End of Pure IC (15:36) - “I think the idea of a pure IC is going to go away. I just don’t think there’ll be enough value there for someone to be a pure IC... and being much more deeply ingrained with the business, working much more closely with other functions.”
Sharing is caring
If you found this useful (see what I did there?), please consider sharing it with two friends navigating similar questions about building in the AI age.
Also, drop a comment below—I’d love to hear how you’re thinking about MVP vs MLP vs MUP in your own work.
