> The consequence in this model of not being an early AI adopter is that unless you're a rock star performer already, you're going to fall behind the curve and get ejected from the game of software engineering early.
This is assuming that AI _currently improves productivity_. There's little empirical evidence for this (there is evidence that it causes people to believe that they themselves are more productive, but that's not very useful; _all sorts_ of snake oil cause people to believe that they themselves are more productive).
My baseline assumption right now would be that AI does not, in aggregate, improve productivity (at least in software engineering; it may in some other fields); if it ever _does_, then sure, I'll probably start using it?
AI 100% does currently improve productivity when used correctly. You can say that's a no true Scotsman, but you can look at my company GitHub page to see that I'm delivering.
AI delivers results when you understand its characteristics and build a workflow around it designed to play to its strengths. AI doesn't deliver huge results when you try to shoehorn it into AI unfriendly workflows. Even if you took the Stanford 95% study on its face (which you shouldn't, there are a lot of methodological issues), there are still 5% of projects that are returning value, and it's not random, it's process differences.