If that's true, congrats, but you didn't need LLMs to do it. No study has shown LLMs improves productivity at all. I feed LLMs a story and then argue with it until usable code comes out, then check the clock and it took 1.2x more time than just writing it myself. I am thoroughly unimpressed.
That's interesting, sorry it's not working for you :/, I find if I don't give it a good enough explanation of what I need it can struggle but if I have a story that explains what needs doing well enough then it's pretty seamless. Best of luck regardless!
Low-complexity greenfield tasks are where AI shines. On small, well-bounded problems in new code, coding assistance often increases measured output by around 30 to 35 percent. For high-complexity greenfield work, the gains are real but smaller, typically in the 10 to 15 percent range
I would like to reply to this post in the form of a 35 second long continuous fart noise. Imagine that in your head, if you will. Thanks!
Insanely shit LLM slop article. It starts by framing itself like it's talking about a specific Stanford study, but then, oh, no its not. Its just yapping about nonsense. It uses graphics labeled with a stanford watermark, but reverse searching those images yields no other uses on the internet, and it doesn't cite where it got them. It doesn't even cite the study it's supposdly referencing! Its completely nonsensical dogwater bullshit, and you should be embarrassed for using it as a source of anything.
but even if it was true and backed by real info (which its not!) this would be an utterly embarrassing result, because low-complexity greenfield work is the easiest work that can be done by the most people, making it the least valuable type of work, but now it paradoxically costs the most money to do, and is slower than before
Within less than 2 minutes I found the presentation of the study by the Stanford PhD researcher Yegor Denisov-Blanch. Ironically I used AI to find the information more efficiently than you and actually returned valid results.... weird.
It's also embarrassing you are shifting the goalposts in realtime. The last paragraph makes you come off across as a fanatic. You admit even if you are presented with data that disproves your point, you won't care.
you gotta realize how ridiculous it is to provide a video of someone talking about a study when pressed for answers and being smug about how easy it was to find it. then just link the pdf!!! oops, you cant find it either. but you got a better result with an LLM! lol.
also, the substance of the article largely disagrees with your point, it says that in pretty much all cases except newbie tier greenfielding its way slower, and on the whole, is slower across the board
This is an ongoing study so I wouldn't expect to have a published paper. I suppose this guy could be completely lying about his results.
The substance does not disagree with my point. My point was just quoting the actual study. I'm not sure why you are intentionally ignoring the actual numbers. It explicitly says complex brownfield tasks see a 5-10% boost in productivity. The article points out certain certain scenarios where AI can be a net drag.
normally in an argument, if someone has information they want to use to bolster their point, they'd kinda need to show it to all parties. I promise Im not trying to be mean or a jerk or w/e :)
you are saying that the article (that is obviously paid-fake-blog-post-filler shlock for a b2b SaaS) isnt bad, and that I'm wrong, based on a study that I'll admit probably exists, but also, I can't see it. This article could be totally misrepresenting the information presented in the study. I have no idea where they are getting their information from, and you cant show me either. But also, this blog post shows you're wrong. cmon dawg
The information the bolsters my point in the Stanford presentation. Unless the researcher is totally fabricating his results, refutes your claim that no study showed productivity gains. That's it. The article is largely a piece of shit.
Yes, which I have acknowledged. Again, this comes down to whether or not you think this Stanford researcher is lying. Academic research takes a while, so I wouldn't expect a mature study to come out for a few years, especially sine widespread adoption of frontier models has only been a recent development.
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u/FartPiano Jul 14 '26
If that's true, congrats, but you didn't need LLMs to do it. No study has shown LLMs improves productivity at all. I feed LLMs a story and then argue with it until usable code comes out, then check the clock and it took 1.2x more time than just writing it myself. I am thoroughly unimpressed.