Re:Speed at the cost of quality: Study of use of Cursor AI i...
by tabwidth on Monday March 16, 2026 @06:33PM
(#47405915)
The part that gets me is when it passes lint, passes tests, and the logic is technically correct, but it quietly changed how something gets called. Rename a parameter. Wrap a return value in a Promise that wasn't there before. Add some intermediate type nobody asked for. None of that shows up as a failure anywhere. You only notice three days later when some other piece of code that depended on the old shape breaks in a way that has nothing to do with the original change.
Re:Speed at the cost of quality: Study of use of Cursor AI i...
by chrisweekly on Monday March 16, 2026 @06:24PM
(#47405831)
> The study found "transient velocity increase" followed by "persistent complexity increase."
Companies facing this reality are of course typically going to use AI to help manage the increased complexity. But that leads quickly to AI becoming a crutch, without which even basic maintenance could pose an insurmountable challenge.
Re:Speed at the cost of quality: Study of use of Cursor AI i...
by galbar on Monday March 16, 2026 @06:27PM
(#47405852)
>The fix isn't "apply traditional methods"
I would argue they are. Those traditional methods aim at keeping complexity low so that reading code is easier and requires less effort, which accelerates code review.
I've been doing 10-12 hour days paired with Claude for months. The velocity gains are absolutely real, I am shipping things I would have never attempted solo before AI and shipping them faster then ever. BUT the cognitive cost of reviewing AI output is significantly higher than reviewing human code. It's verbose, plausible-looking, and wrong in ways that require sustained deep attention to catch.
The study found "transient velocity increase" followed by "persistent complexity increase." That matches exactly. The speed feels incredible at first, then the review burden compounds and you're spending more time verifying than you saved generating.
The fix isn't "apply traditional methods" — it's recognizing that AI shifts the bottleneck from production to verification, and that verification under sustained cognitive load degrades in ways nobody's measuring yet. I think I've found some fixes to help me personally with this and for me velocity is still high, but only time will tell if this remains true for long.