> 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.
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
Scaling AI use in highly-collaborative environments, which open source projects are, is very challenging. I totally understand the apprehensiveness around it.
How is it challenging for open source projects? You just write a PR, and try to get it to meet the maintainer's quality bar. That's exactly how all code is written in any environment - you do code review and refine a PR until its good enough to be merged
With AI and how a lot of people use it, the quantity of written PRs goes up, but the quality goes down, and the maintainers of the project, who are often volunteers, now have to deal with this in addition to the standard work they've been doing before.
Just my experience, but the relatively few fully AI-generated merge requests we've received that were "big features" were all really bad.
For instance, we had one person submit a merge request to convert the entire GIMP codebase into Python, and it was just tons of files with stubcode implementations.
Another person submitted a fix for our OpenEXR plug-in to load YCbCr images, and when I reviewed it, they'd "imported" a non-existent version of the library that had an imaginary "OpenYCbCrOpenEXR ()" function. :)
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.
Those websites are janky despite having all the (non AI) solutions available already. They suck for reasons independent of the quality of LLMs. I have not worked inside a megacorp but my understanding is they suck because of what are essentially political roadblocks within the organisation.
Ok, let’s assume that’s the case and we’d never see those improve under any circumstances.
Where are all the killer new things? All we see are glorified hobby projects (guilty as charged) and an unimpressive pace of equally unimpressive feature additions to all the same old stuff.
Businesses with resources out there should tackling huge things we all want, that they never could have undertaken. But I’m not seeing it. Everything is just… more or less the same. And this tooling didn’t arrive last Wednesday.
Or did we get magical AI at a time when we’re also completely out of ideas? That seems unlikely.
This shit just isn’t adding up. We’re not seeinganything that isn’t more “here’s some more ai tools and services… they’re basically the same as the ones you saw last month.”
I agree they are over-hyped. Maybe the problem is that all the things LLMs are great for are essentially quality of life improvements. There are a dozen killer apps worth of functionality I get out of LLMs - near instant proofreader, one-shot code bugfixer, excellent cursory research tool, bibtext generator, etc. All of these things extend what I can do a bit but none of them instantly result in me being able to generate category killing apps. They still make stupid mistakes, they don't reduce my workload, but they reduce cognitive load on mundane tasks.
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
I think what you're missing is that there are new open source projects being created at a very fast rate.
But that doesn’t mean they stick.
And the core issue isn’t AI, it’s that… a successful, highly adopted project requires time for people to know it exists, adopt it, and also time by the maintainer growing community and ensuring reliability. The people factor is more important. I see tons of new projects, but I’m not going to pick a brand new project that has high odds of being abandoned. I’m going to pick the one that consistently maintains it and has some adoption already.
I have seen engineers create very successful internal projects fairly quickly. And yes, a project that would have taken a year taking a month. And offering a lot of extra bells and whistles that you just wouldn’t have time for.
But these are greenfield internal projects, and the bar is much, much lower for those.
I have seen multiple internal incidents root-caused by an agent faster than the humans responding. Just because it can go up and down rabbit holes a lot faster.
The problem is that AI solves one bottleneck, but not others. One team member produces a huge amount of new PRs. (Like 12 solid enhancements and big fixes in a couple hours.) Now I have less time because I’m reviewing that. And we’re all context switching a lot more.
On top of that, I find AI workflows continue to be deeply immature, even though certain models are very effective and very good at troubleshooting.
The story around testing is not really improving for example. AI can write tests, but are they good? I don’t think we have much actually ensuring product quality and reliability automatically. Unit tests are not enough.
Collaboration is very poor too. Coworkers agent creates PR, and now I’m reviewing it, and now he sends my comments back to his agents… really clunky workflow especially since I’m ACTUALLY just prompting his agent.
Plus, certain models (Opus) are getting much worse at writing. I will not use Opus any more because the writing style is so horrible.
The constant change means approaches that worked well a couple months ago don’t work well today. And there are no real experts, because no one’s been doing this for long. And half the posts and learning out there are outdated, or straight up blogspam.
This makes it hard for people to learn and get better, despite the fact that models like Sol 5.6 are effective troubleshooters, and write decent code.
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 point was specifically addressed in the article.
Given that a compiler doesn't include a statistical model likely to create one's written Rust code, the compiled bytecode is quite clearly an expression of said writing.
If you go to a coffee shop and ask for extra ice, whole milk, double espresso latte - did you make the coffee or did the Barista make it. You gave him some specific directions didn’t you?
When I'm building, and get approached by large customers who have specific needs for them, those needs go at the end of our backlog. There's a hard and fast rule that unless it's an issue with authentication or accepting money, nobody gets to jump the line. We re-evaluate our backlogs periodically, and treat large-customer requests similarly to small-customer requests; who is this going to serve, what additional revenue could this generate, will this increase retention. If there are other projects that, combined, will move the needle more than doing one project for one enterprise client, guess what, that enterprise client doesn't get to jump the line.
"If a local district starts losing funding, then it would have to close / shrink schools, and people from outside the educational system would be allowed to establish independent (secular) charter schools within the district."
There is zero incentive for "people outside the educational system" to do this. Kids will absolutely suffer because of this plan.
The answer to this, like always, is that teachers need to be paid more.
If "we will opt everyone in because otherwise we won't get enough data because we know users won't opt in" is your business model, maybe it's time for a rethink.
Agreed but "it's always been shitty" isn't a reason to do nothing about it.
For much of human history slavery was fine too, but thankfully that's been dealt with in many nations. I know some folks argue that capitalism is just the next iteration of slavery but that's different.
not sure why you think stating facts implies nothing should be done about it
slavery is still fine in the US as long as you're incarcerated, and the US still does business with countries that regularly use the old fashioned kind — hell, some people still want to bring chattel slavery back here and still proudly display the confederate flag
these are just very slow things to change... in the timespan of centuries if you're lucky, but in the case of wealth bringing privilege we haven't cracked the issue for thousands of years
I'd recommend at least doing a short spike to see if you can build your own in some way. We did that for the purpose of experimentation and now we've built our own metrics platform that we completely own.
I sincerely hope this never comes to pass, but you or your loved ones may someday find themselves in the position of wishing more people were opted in for organ donation.
The same cannot be said for some random corporation training AI models off your data to make a buck or two.
I think it might be better to get rid of the organ *donation* system entirely.
Organ transplant surgery costs hundreds of thousands of dollars, yet donors get zilch, which is completely unfair when everyone else in the value chain gets paid.
If instead it was "allow my organs to be sold for my estate" I think the supply of organs would greatly increase, which would be win/win.
there are a number of problems with people selling their organs for profit, it's a perverse incentive — the people in the chain who otherwise get paid don't get paid for the organs, they get paid for the labor of doing their jobs
If you keep commenting like this, we'll have to ban you. We've asked you before, not to do this, and you've been using HN long enough to know that this is unacceptable. If you keep it up, we'll have to assume that you want to be banned.
Off topic but I'm curious what's evil about that article. Bizarre, sure, but evil? They took a brain (an organ) from a dead person who had previously given consent to use their organs for that purpose.
I think most people, and definitely myself, when they sign up to be an organ donor, they think of the liver, kidney, and heart. Things that will help other people.
Not the brain, the center of conscience, being kept in some sort of horror-movie half-alive state. I do not think we understand consciousness enough to rule out what those brains are experiencing.
That's fair. Personally I wouldn't mind, but when you put it that way it makes sense people would be wary. Kind of reminds me of the series Pantheon, which is amazing but also kinda disturbing for similar reasons.
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