Your opinion of AI is mostly a measurement of your own blind spots
Something I keep noticing and cannot unsee.
Before LLMs, maybe two percent of people could write code. That has not changed. What changed is that the rest can now produce something that looks like code, and they have no way to distinguish a working system from one that merely runs. So you get the confident version: developers are finished.
Move the same person one field over, into something they actually know, and the verdict inverts inside the same conversation. A lawyer on drafting. A doctor on a differential. An electrician on a load calculation. No, it makes far too many mistakes there, you cannot rely on it for that.
Everyone is an optimist about other people's professions and a sceptic about their own. That is not hypocrisy. It is the only honest reading of the evidence each of them has, because inside your own field you can see the errors and outside it you cannot. You count what you can see, and conclude there is nothing to count where you cannot.
Which means the enthusiasm is not measuring the model. It is measuring the gap.
The version of this I hit at work: generated code compiles, the demo runs, and that tells you nothing about what happens to a half-finished write when the network drops, or which of three plausible schemas falls over at forty thousand rows because the sort happens after the join. Those do not surface as errors. They surface as absences, and no model volunteers an absence. Someone who can read the code sees the absence. Someone who cannot sees a working demo.
I use it daily and it made me faster. But I have noticed my opinion of it is highest in the areas I know least, and I now treat that as a warning rather than a recommendation. The question I ask is no longer "is it good at this" but "would I notice if it were wrong". When the answer is no, that is not a green light, that is the whole risk in one sentence.
Curious whether people here see the same inversion in their own orgs, or whether there is a reading of it I am missing.