alt Hacker NewsThe real takeaway here -- also corroborated by the DORA 2025 report https://dora.dev/research/2025/ -- is that more than anything, AI amplifies your current development culture. Organizations with strong quality control discipline enjoy more velocity, those with weak practices suffer more outages.
Expecting AI to magically overcome your development culture is like expecting consultants to magically fix your business culture.
Furthermore, by various estimates, engineers only spend 10 - 60% of their time on actual code. So, given that currently AI is largely used only for coding activities, 10% is actually considerable savings.
Also this is the result of retro-fitting AI into existing workflows; actual "AI-native" workflows would probably look very different, likely having refactored in other parts of software engineering. Spotify's "Honk" workflow is probably just a starting point.
I'm pretty sure it has to do with the individual as well as the culture. Juniors/new hire use AI to multiply by two their wrong/unsafe output, and seniors then have to spend more time correcting it.
I'll be honest: I piss poor code, each time I come back to an old project I see where I could have done better. New hires are worse, but before AI (and especially Opus) they didn't produce that much code before spending like 6 months learning (I'm on a netsec tooling team). Now, they start producing code after two weeks or less, and every line have to be checked because they don't understand what they are doing.
I think my personal output was increased by 15% on average (maybe 5 on difficult projects), but our team output decreased overall.