I don't think this line of reasoning holds. The only thing people should look at are peer reviewed studies, lots of them ideally, and with no conflict of interest. Who's getting productivity gains? What kinds of work are they doing? What doesn't work so well? All of these questions should be investigated by studies. People feeling productivity gains doesn't imply the gains exist.
Otherwise it sounds like "many people have had their lives changed by {insert philosophical/religious movement}, so if you're not finding it true you should look into what's wrong with you."
> The only thing people should look at are peer reviewed studies, lots of them ideally, and with no conflict of interest.
"Ignore your own direct experience, only research papers matter" is certainly a take.
The beautiful thing about the current generation of tools is that they are so incredibly cheap relative to historical tools intended to improve engineering productivity. You can't just run out and pick up CASE tools for less than ~$CAR to ~$HOUSE. A pro subscription to whichever AI tool you want to try is $20.
Ignore research, try them, if you have success, use them. There's no dogma here. Just empiricism.
> When developers are allowed to use AI tools, they take 19% longer to complete issues—a significant slowdown that goes against developer beliefs and expert forecasts. This gap between perception and reality is striking: developers expected AI to speed them up by 24%, and even after experiencing the slowdown, they still believed AI had sped them up by 20%.
Maybe you just think you're being more productive ;)
Otherwise it sounds like "many people have had their lives changed by {insert philosophical/religious movement}, so if you're not finding it true you should look into what's wrong with you."