I think you might be fooling yourself with AI

foxyv

I've noticed that you can either move very fast with AI, or very slow. Moving fast, you place a lot of trust in the agent and let it proceed and create something very quickly that works at a surface level and that you don't understand at all. Moving slow you take the time to ask questions and understand every part of the application and learn more about how to code it yourself and make changes as necessary. One thing I've noticed is, that coding manually is exponentially more stressful than the slow AI approach. I'm not going any faster than I normally would, but the burnout doesn't show up on the fifth day of the week. The hyper-focus is kind of fun but utterly exhausting. With the fast approach I can create impressive demos and POCs that are nowhere near ready for production. But sometimes that's exactly what I need.

hmokiguess

Both things can be true.

xyzsparetimexyz

I think it's very productive in areas that aren't economically impactful. Reverse engineering old windows games for example. Doing absurd ports between languages.

zuzululu

tired of this one dimensional articles that paint a wide brush, there are wide variety of AI uses and it absolutely has a productivity multiplying effect.

aogaili

These articles are so off from reality to the point that it can't be taken seriously at all. I keep wondering how they keep popping at HN. At least the author admit he is biased..

dcow

AI costs aren’t going to stay this high. They will go down. Nobody is going to turn off AI, but they will care about making sure that we are reasonably efficient when using it. Compute that can happen locally will. Communities that responsibly want to build data centers are. Climate implications will be addressed by policy. People said the same about the internet 30 years ago… It’s not about raw productivity. It’s about perceived effort. If a job feels easier with AI assistance we’ll demand it. If AI checking a human’s work is more reliable than a human checking AI’s work (it is) that’s what we’ll deploy.

x3haloed

I think you might be fooling yourself. Personal-plan subscription subsidies do not equate to "it's not viable, and all of it is about to be shut off." If that were true, then Kilo Code, Claude Code, Cline, Pi, and Command Code would not be occupying 5 of the top 10 apps using OpenRouter. People have purchased 20 trillion tokens this month already for coding on OpenRouter alone at full-price market rates. Would you commission a study about whether cars are really a faster form of locomotion before deciding to purchase one? There is empirical data right in front of your face. You're just choosing to exclude it because of where you already stand. That's exactly what Feynman was warning about.

Narciss

Many improvements have come to AI that have reduced costs of inference and training, like sparse attention, and many more will arise in the future. To talk about the cost of AI right now versus the future is to talk about the first IBM computers versus the personal computing that appeared years later. The cost will go down. In fact that is what the major labs are definitely banking on.

jldugger

> And I'm also standing by my own idea that AI will run out of money and just be turned off due to the huge operational cost. Thats a pretty strong outcome. It implies that not only are GPUs that power AI too expensive long term, but they cost too much to operate even if they were free. Seems to me the more likely outcome is a wave of dotCom style bankruptcies wiping out equity holders for companies who contracted to buy chips and datacenters at MSRP, and a second wave for the groups that step in after to operate whats left without the absurd financing charges and lower capex.

pwillia7

Now imagine if this was written about the first steam engines being used inefficiently to pull coal up out the ground and pump out the water. It's so expensive -- is this really more effective than just hiring 50 men? We all know how that ended up...

chilmers

This is the perfect archetype of an intellectually lazy anti-AI post. The author ends with his admission of bias, but he'd be better off starting with it, as it's clear that his reasoning flows entirely from it. AI is bad for productivity, says this single study from 2025. AI is unsustainable, says this article I found. AI will all just disappear one day... because I hope so? Ironically, the author would have been better asking an LLM to write the article. At least it would have found better sources and developed more convincing arguments.

duendefm

I think it really depends on your knowledge and skill, and the kind of work you are using it for. It's hard to measure because the more you use it the more you lose some skills. But I have to admit that I can do much more parallel work when using the best models. It's messy, because sometimes I feel that I get lazier and just prompt them and go do some random stuff and sometimes even skip the part of verifying what they actually did meanwhile. But you can command AI to do massive stuff, you can get smart non developers to do useful work with them, it's really a new paradigm. One funny thing that I think people should consider more is pride in the code. If I code something by hand, like fully developing a service, I will get proud of seeing it work, I will attach to it like if it's my creation. That hardly happens if I use AI a lot.

ChicagoDave

These people keep citing that survey from 2025. That kills all arguments from the article instantly. December 2025 through today GenAI has become massively better. I’ve built things with Claude in contracted spans of time that would have been man-years in the before times.

hsuduebc2

These AI sceptics always omit the possibility that running LLMs could become much cheaper in the future, which it almost certainly will. This is largely an infrastructure problem, and it will be solved just as similar problems were solved with storage, network capacity, and computing power. There will be bankruptcies, but the technology will prevail, just as the web did after the dot com bubble. Personally, I see the loss of craft and practical skill, which can only be built through doing, as a much greater danger. I still practise LeetCode from time to time so I do not lose the ability to write code myself.

kalkin

> Meanwhile, a study (late 2025) seems to report that although participating developers felt they completed tasks faster using AI, they where around 19% slower. METR reran the study early this year and, while they caveat it, this time they found a speedup, which is consistent with subjective estimates of productivity also having increased -- the simplest explanation is that subjective estimates exaggerate, but there's still a speedup with current models: https://metr.org/blog/2026-02-24-uplift-update/#wider-adopti... (Nobody seems to cite the followup since it's not such a fun counterintuitive finding.)

podgorniy

Author does not draw full enough picture (by linearly projecting current trends). But still has good points. I liked the one where perceived "productivity" is compared against unsubsisdized token prices.

simonw

I read this headline and thought "METR study"... and sure enough, a few paragraphs in: > Meanwhile, a study (late 2025) seems to report that although participating developers felt they completed tasks faster using AI, they where around 19% slower. I think you might be fooling yourself if you build your entire worldview concerning the productivity benefits of AI-assisted programming around that one study from one organization that confirms your priors.

rorykirchner

I think you might be fooling yourself with stale data.

lordnacho

Zitron might be right about the economics of it, maybe it really does come crashing down. But we won't be forgetting about it. Even if AI stopped progressing today, it will still be massively, undeniably, insanely useful. I could use current models forever. LLM does things for me that couldn't be done in 2023. I don't want to go back to a world without it, but I'm also ok with progress stalling right here. As for the productivity benefits, I find there is a kind of skeptic that just has his eyes closed. Open an AI page, ask it to write you an app that renames all your scientific papers so they have their title as the filename instead of the weird long number. Without AI you could easily waste an hour looking for the right PDF library and working out how to use it. Or fiddling with the file search mechanism so that you only get the articles and not every file in your downloads. Now you will have the files renamed in a few minutes, and a tool that keeps them correct every time you have download some more. How is this not a productivity win? It clearly is. Do we really need a double blind test to check this kind of thing? Whether it gets squandered in modern orgs is another matter, but the core win is clear for everyone to see.

lowbloodsugar

Quotes study from early 2025. Same group redid study now shows opposite result. “Fooling yourself” indeed. Anybody actually using AI in anger (to get paid) will tell you AI was pretty bad early 2025. It wasn’t usable till June. By December it was writing most of my code - with significant reviews by me. Now it’s basically getting it right. YMMV.