Comment by mark242
1 hour ago
> Why do only the poor quality LLM code generation users make PRs to open source projects, and never the engineers that know how to really use it correctly?
It could be that the engineers who are extremely productive with LLMs are landing PRs that look indistinguishable from good, hand-written PRs.
If so, where are all the new features in the open-source projects I use? Why hasn't GIMP replicated Photoshop? Why hasn't CUDA been fully reverse-engineered as an open source toolchain? These are unreasonable expectations, but only in response to unreasonable claims of productivity. What before took ten years should now only take one, right?
It seems likely that the gains from generating tons of code are being offset by the debt incurred to understanding what you're doing. We see lots of greenfield projects one-shotted with GPT or GLM or whatnot, but very little on the side of projects with long-term maintenance goals. This is telling, to me, that the _effective_ gains are much lower than perceived (it's lots of fun to see the thing crank out code at breakneck pace, probably contributing to this). Still quite nice, and very useful, but not a totally new paradigm.
> Why hasn't GIMP replicated Photoshop?
My guess is that open source folks overindex on being anti-AI.
They don't though, very few people were anti AI in the early days. Open source projects were largely initially very interested in LLM usage, and generally had a pro AI contribution policy. This changed when it did not help their lives
Eg if you check out Godot, initially they were cool with LLM code, and then had to clamp down on it because it was not leading to anything good
Yeah, why hasn't AMD added every single CUDA feature lol
Why are Amazon and Walmarts mobile apps still janky crap that costs them money? Why does Meta still have four redundant, broken sign-up flows before you can give them money to advertise?
Wherever these “10000x” engineering gains are… I’m wondering why they’re only for shit nobody sees or touches.
If that were true, we'd expect to see massively accelerated velocity of open source projects by these engineers. They should be creating new open source projects at a truly astounding rate, with new tooling springing up every day that dwarfs the existing open source space as their productivity completely eclipses traditional development
Instead, software is plodding along exactly the same as it did prior to LLM code generation, and there's no evidence of superprogrammers making superprojects in 1/10th of the time. With a 10x productivity gain, what used to take a year should take a month
Github's Octoverse report kind of gives you that evidence, no? Pull requests landed in 2025 were up 30% over 2024. This year it's going to be much higher.
That's the point. Huge increases in pull requests. Virtually no increase in features or reliability.
LLM code is obvious to spot. If an LLM designed a screwdriver set it would make a screwdriver for each head instead of making a replaceable head.
LLMs are superhuman at short term coding such as debugging and writing tests though and you're missing out by not using them there.
So... basically an autocomplete to help you type faster and spot check if you did something unusual in the parts you wrote by hand?
> LLM code is obvious to spot. If an LLM designed a screwdriver set it would make a screwdriver for each head instead of making a replaceable head.
Commercial and industrial electricians are LLMs now?