AI understands the problem. It just can't be trusted to execute it.

Been thinking about this a lot lately. Newer models are genuinely good at reasoning through hard problem, they get the logic, the structure, the WHY. Ask them to explain a complex system and they'll usually nail it.

But hand that same model actual execution. The real input, real constraints, no room for a rounding error or a dropped edge case, and it starts to wobble. Wrong units. A broken format. A fix that quietly creates two new problems.

It's less "the model is dumb" and more "understanding a domain and being reliable inside it are two completely different bars."

Feels like most of the AI conversation right now is stuck on the first bar. Curious how others are thinking about the second. Has an AI tool ever nailed the reasoning but completely fumbled the execution for you?