AI Made Your MVP Cheaper, But It Didn't Lower The Main Risk

AI collapsed the cost of building an MVP. It did nothing to lower the risk of building something nobody needs. The expensive mistake was never the code.

I wrote before that an MVP is a scientific experiment designed to reduce uncertainty, not a small product. That claim gets sharper, not weaker, now that a model can produce the code in an afternoon. If the MVP was always an instrument for answering a question, then making the instrument cheaper to fabricate changes nothing about whether you asked the right question.

I built the wrong thing, and cost was never the reason

I started a startup with a former colleague. We had a vision we believed in, and we lost money and time before it ended. The signals that people did not care showed up early. We read every one of them as a communication problem. The idea was fine, we told ourselves, we just were not pitching it well enough. That story lasted far longer than it should have. It took someone outside the team, someone not living inside our bubble, to point out that we were doing the whole thing backwards.

Here is the part that matters for this post. If we had built that product with today’s tools, it would have been cheaper, faster, and better instrumented. And it would have failed for exactly the same reason. We were attached to the solution in our heads while the market kept telling us it did not want it. No coding agent on earth fixes that. The waste was never the engineering hours. The waste was aiming them at the wrong target.

What AI actually lowered

AI lowered the cost of producing the code. That is real and I am not minimizing it. Work that used to take three developers three months now takes a fraction of that. You can even afford the boring parts you used to skip: logging, analytics, automated tests, a real A/B setup. The floor of what a small team can ship went up.

What AI did not touch is the distance between what you believe about your market and what is actually true. That distance is the thing an MVP exists to measure. A model does not know whether anyone wants your product. It cannot run the experiment for you, because the experiment was never the code. It was the decision about which assumption to test and what result would change your mind.

Cheap construction makes it easier to build the wrong thing faster

There is a new trap, and it is subtle. When building was expensive, the cost itself forced a pause. Nobody committed three months of a team’s time without at least a nervous conversation about whether the thing should exist. The friction was accidental, but it forced people to think before they committed.

Remove the friction and the pause goes with it. Building is cheap now, so the question of whether to build at all quietly disappears. You skip straight to construction because construction is the fun, visible, satisfying part, and because you can. The result is that you reach a polished, working, fully-featured wrong answer in a week instead of a quarter. You have not reduced your risk. You have just paid for it faster.

Producing code got cheaper. Doing the correct thing did not.

This is the whole point. Writing software was never about typing. The goal was always to turn an idea in someone’s head into something real that solves an actual problem. AI made producing the code cheap. It did not make it any easier to know the correct thing to produce.

Deciding what to build is still hard. Talking to real users is still hard. Naming the one assumption that kills the business if it is wrong, and designing the cheapest honest test of it, is still hard. None of that got automated, because none of it was ever the mechanical part. It was always the judgment, and judgment is the one thing the model hands back to you unchanged.

Where the effort should move

If building is nearly free, then the only scarce resource left is knowing what to build. That is where your attention, your best people, and your remaining budget should go. Spend the hours you just saved on construction figuring out whether construction was the right call.

The founder who wins in this era is not the one who ships fastest. It is the one who still asks, before anything gets built, what would have to be true for this to work, and how do I find that out for the least possible cost. That question was always the hard part. It just used to be hidden behind the cost of code. Now that the code is cheap, there is nowhere left for it to hide.