How I Use AI for Rapid Prototyping and MVP Development

Speed is seductive in startups. But speed without direction just gets you to the wrong place faster. When I use AI for rapid prototyping and MVPs, the goal isn’t “build quickly.” The goal is learn quickly, with minimal waste and maximum signal. AI is not my shortcut to shipping. It’s my multiplier for thinking, testing, and iterating. Here’s how I actually use it, end to end. 1) I Start With the Problem, Not the Prototype Before a single screen or API exists, I force clarity on: who the user is what job they’re trying to get done what “success” looks like what failure would look like what constraints matter (time, cost, risk, trust) I use AI here as a thinking partner: to challenge assumptions to list alternative framings to surface edge cases to propose simpler versions of the problem If the problem isn’t crisp, a fast prototype is just a fast distraction. 2) I Use AI to Explore the Design Space, Not Just One Solution Instead of committing early, I ask AI to: sketch 3–5 different appr