This too should be questioned, at least a couple studies at this point suggesting many feel like they are going faster with AI when, by some metrics, they are going slower (e.g. https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...), and then there are e.g. admissions from major CEOs publicly admitting e.g. Copilot doesn't "really work" (https://ppc.land/microsoft-ceo-admits-copilot-integrations-d...).

And, again, this is ignoring all the technical debt of produced code that is poorly understood, weakly-reviewed, and of questionable quality overall.

I still think this all has serious potential for net benefit, and does now in certain cases. But we need to be clearer about spelling out where that is (webshit, boilerplate, language-to-language translation, etc) and where it maybe isn't (research code, legacy code, large codebases, niche/expert domains).

This Stanford study on developer productivity found 0 correlation between developers assessment of their own productivity and independent measures of their productivity. Any anecdotal evidence from developers on how AI has made them more or less productive is worthless.

https://youtu.be/tbDDYKRFjhk?si=gF4EN4ilogoam3hG

Agreed.