Interesting data point from the other direction — while CEOs see no productivity impact, engineers are feeling the pressure of AI regardless of actual output gains. In our burnout survey, AI pressure to do more has emerged as a top 4 burnout driver in 2026. That finding didn't exist two years ago.
So even if AI isn't delivering the productivity CEOs expect, it's still extracting a cost from engineers in the form of heightened expectations and stress.
If anyone wants to add their data:
https://docs.google.com/forms/d/e/1FAIpQLSdu-1Sa6oPvhDtFtBuK...
Live results:
rechargedaily.co/state-of-burnout-2026
There’s alway a bit of that going on, but ironically if AI does result in mass labor replacement India and the Philippines are likely going to be ground zero where workforces get wiped out first. They’re ripe with the kind of things that AI is, in theory, getting very good at.
I've always held the view that successfully using AI requires more knowledge and skill, as the burst radius of poor engineering decisions or lack of domain knowledge is way larger. I just cannot see WITCH doing this without exponentiating the usual problems with outsourcing. I've seen some horrors. Can't wait for contractors wielding unprecedented chaos.
Good point, successfully using AI takes skill. If you'll please pardon me, I don't think your average GenZ knows how to properly use it. It takes someone who grew up with technology, who understands the fundamentals of technology, who understands the fundamentals of computational decision-making, that can really make use of ChatGPT etc. Someone raised on App Tap culture just isn't equipped to fully appreciate the technology. Not that they can't, it's just… The vast majority of them are hopeless with this.
I wish anytime someone used the word "productivity" there was an accompanying definition.
its because its all vibes
i think its too hard to separate the noise from the signal unless there is some huge differential like 2x profits immediately following ai adoption or a real deep longitudinal study (which no-one pushing this at companies seems to want to do)
AI isn’t going away, but it’s also clear the much promised impacts aren’t there and aren’t coming anytime soon. A bit like the claims a few years back that we’d all have self driving cars by now. The most likely outcome is an AI bubble correction that will be somewhat painful and wipe out many/most AI startups, followed by AI settling into day to day in a way that’s useful and found in many places, but not world-as-w…
> the much promised impacts aren’t there and aren’t coming anytime soon at least according to industry analysts, the thesis at the moment is that reasoning models (which loop over their own output and backtrack if necessary) will bring fidelity close to 100% and find novel solutions not present in the training dataset. but they consume more tokens, they require more computing and the infra for it is still being built…
> fidelity close to 100%
what is fidelity meaning here? creating perfectly lifelike images and video or code that is "perfect" even with imperfect inputs? or something else...?
This article is underlining the stark contrast between the viewpoints of “AI Enthusiasts” and everyone else. Don’t get me wrong, I use these tools daily. That being said I’m having a very hard time finding where the productivity gains are. I imagine I’m far from alone in that search and when you pair that with the constant marketing and glowing “analysis” from some of the enthusiasts about how this technology is “sol…
I think a lot of the disconnect in the programming world is we treat all programming as equivalent and it's not. There really are many programming jobs that are rote and I have no problem believing that an LLM based tool can learn the pattern and regurgitate with the tweak de jour. In those jobs LLMs probably do increase productivity. But there are other programming jobs that are not rote and there is no pattern to l…
> forces the engineer to spend a moment to actually think about what they're doing and make some kind of plan
i thought so too, until i observed the exact opposite at $job
basically i see people just jump into claude and tell it to do x, then x is wrong or not quite right, so they go down a rabbit-hole fixing up things again and again burning tokens like a bonfire till it sort of works... i see very little upfront planning from where im at but maybe this is just my bubble...