When I started looking closely at products built heavily with AI, something felt off.
Nothing was obviously broken. Everything technically worked. But the experience felt like it was put together in a hurry. The seams were showing in ways that were hard to name but easy to feel.
The copy was fluent but generic. The features were coherent but not quite right for the problem they were meant to solve. The UX was functional but not considered. Everything had been built — but nothing had really been designed.
The Speed Trap
AI has made it dramatically faster to go from idea to working prototype. That's genuinely useful. But it's created a new failure mode that didn't exist at the same scale before: the cost of building the wrong thing faster is now much higher, because the wrong thing gets shipped much sooner.
The bottleneck used to be build time. You had to be reasonably confident before you started, because starting was expensive. Now starting is cheap, so the bottleneck has moved upstream — to clarity of thought, quality of problem definition, and depth of understanding of the person you're building for.
What Speed Hides
Speed hides weak thinking. When you can generate a working feature in an afternoon, it becomes easy to confuse activity with progress. The backlog grows. The product grows. But the core question — does this actually solve the problem in a way that people want? — gets deferred.
I've seen teams ship more in six months than they used to ship in two years, and still end up with a product that doesn't convert, doesn't retain, and doesn't grow. Because they built faster without thinking harder.
The constraint has moved. It's no longer about how fast you can build. It's about how clearly you can think before you do.