- cross-posted to:
- linux@lemmy.ml
- cross-posted to:
- linux@lemmy.ml
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It’s an unfortunate news, burnout in open source was real even before AI. Now it has just exploded.
Reviewing code has always been a bottleneck. AI made sending a patch nearly free, but reviewing one costs the same as ever, and it lands on a few volunteers.
For code that millions run, someone has to understand every line, so the sender should do that work, not the maintainer. Otherwise you’re just moving the cost onto the people who can least afford it.
There should be a simple rule: if you can’t explain your patch line by line, don’t send it. And maintainers should feel free to reject any patch by default when the sender can’t explain it.
They’ll ask their AI to write the explanation. You can’t win. :(
I’m a programmer. I vibecode a bunch of prototypes and personal projects. I couldn’t imagine being inconsiderate or stupid enough to submit pure hallucinated code to any project, let alone a kernel project. And to have an agent open the PR for me, with code I haven’t read or don’t understand? absolutely insane
Yup. I “vibe coded” changes to a number of projects, but I either kept it on my own fork (it’s open so upstream can grab it any time they want), or thoroughly reviewed before submitting.
Yep, pretty much. The only times I’ve ever submitted LLM generated code to a public project was when it was more or less identical to what I would have written by hand; and even then, I’ve never once considered having an agent hallucinate a PR…
I knew the problem, I knew what the fixes would look like, I had the LLM draft the changes, I read it through and fixed up some slop and documented it appropriately. The code it generated: I understood, I wanted, I polished, I committed, and I owned as my code which I and nothing else was soley responsible for.
That, to me, is a little bit different than pure vibe coding; where most of the time I won’t even read it. Sometimes I don’t even care what languages it’s in. That is peak slop, and that doesn’t go near anyone’s machine but my own, unless they do it themselves (some of the more substantial and long-term slop project I have are committed in public Git repos, but all of the such slop projects are very explicitly documented as such at the very top of my readmes)
My use of LLMs in real projects, where permitted, is entirely different. Mostly used for review and local (not committed) testing. Sometimes tedious mechanical changes, prototyping, factfinding, and brainstorming. But I do the thinking, and it’s my code. My personal vibe projects and random scripts etc are more and more and less disposable, and I don’t claim such strong ownership; it’s cathurding, not programming.
Yep, that’s why I put it in quotes. As a software engineer of 10+ years (professionally, on a personal level, 20+ years now), I can understand code even if I am unfamiliar with the language and the frameworks in question. I know what needs doing (not just random “do this feature, make no mistakes” bs prompting), I know roughly how it can be done, and I let the LLM fill in the gaps.
Plus I also work with a fleet of agents and a collection of skills to ensure its not crap being written. Multiple agents work with specific roles (say, embedded development expert, PlatformIO expert, and so on), there’s a continuous verify-repair-improve loop, strict code quality guidelines and non-LLM checks in place. Of course it’s not perfect, but it gets things 99% of the way, and at the end I just need to review and confirm things.
For example one of the things I maintain is a private fork of CrossPoint reader, into which I’ve integrated BookOrbit, not just as a plugin that awkwardly allows retrieval of your books, but as an actual on-device library that downloads the right EPUBs and syncs not just reading progress but statistics (words per minute, page size and turns, reading time, etc.) as well. The library itself functions similar to a Kindle - all books are listed and with a tap you can download them. LLMs take care of rebasing my changes, with proper reporting on what’s going on and why and how, how the rebase went, what upstream has fixed so I can drop the local version and so on. LLMs take care of API changes to be updated for, optimisations, the list goes on - but before any change is executed, I go in and get an understanding of what really changes.
I can’t imagine myself doing that either, but I’ve seen that happen so often that it’s just disheartening. I’ve asked for explanation of code in PRs and got “idk, the AI generated that” way too many times, and that’s from professional software engineers, people who should know better. The corner-cutting is just too much for me
Edit: typo
Same here. Vibecoding my own tools is fine, because I’m the one who pays for the bugs. A kernel patch is different: thousands of people pay for them, so understanding every line is the minimum.
Anyone who sends code to public software should follow a simple code of ethics. A low barrier to entry is great, it’s how most of us started. But the bar for responsibility should rise with how many people run your code, and right now it doesn’t.
You shouldn’t be vibecoding at all, bud. Toe dippers such as yourself help move to normalize this crap.
Nah. I’m not anti-AI categorically, just the grift, marketing, and billionaires around it. I’ve built and maintained production deployments that incorporate CNNs; I’ve been using AI (ML) since long before the attention paper and modern AI branding.
You’re clearly not bothered by the grift if you’re using the billionaire’s products.
Oh, well, aren’t you smart…
I also use Amazon. I buy my groceries from my region’s local monopoly. I have a Facebook account (that I only use for marketplace). I also pay taxes, a portion of which goes to killing poor brown people for some reason…
Yes, I exist in a capitalist system and consume thusly when it benefits me to do so. Just because my money goes somewhere doesn’t mean I like the people whose pockets it goes into. I prefer using local models for most of my low-hanging-fruit LLM needs, but frontier models have their place, and their uses, and so I have a subscription (which I’ve shifted around a few times).
also really not a big fan of the major chip manufacturers and brands, but I have a computer filled with the things. If you want to open up a fab or a frontier lab and can compete with them on quality and even get in the ballpark of them on price, and aren’t a fucking Nazi, I’d be more than happy to use your product instead. However, here we are.
P. S. I also bought a Nestle chocolate bar the other day, and they’re basically a manifestation of satan. It is what it is…
You’re kinda right, but a few things can be avoided ! Specially… Why the fuck would you buy a fucking Nestle chocolat bar, when there are so many WAY better alternatives arround ?
Just go buy some real chocolat bar in a BIO local market and never touch that fucking nestle chocolat bar ever again !!!
Some things are a requirement to function in this capitalist society, but using slop generators isn’t one of those things. You do you though.
Neither is the chocolate bar, but yum.
Personally, I like things that improve the quality and enjoyment of my life. But agreed; to each their own.
The billionaires lose money each time you use their stuff. We should drain them as much as we can.
I don’t think that’s actually the case. A lot of people say that, but inference is absurdly cheap, even compared to “api-subsidized” subscription prices. Where the math doesn’t work out is the fact that they’re training new models all the time. Any individual generation of model, if they were to just stop on it, (I suspect) would be profitable. But when you factor in continuous R&D and training costs of chasing the next gen, they’re just hemorrhaging money.
But that’s the game they’re playing because they don’t actually care about selling a product to customers; they care about investors. Nobody gets rich anymore by making a product and selling it to people. They get rich by making a product and then pitching it to investors and then getting bought out by a bigger fish or going public and having a big IPO.
The way the economy works now is that the companies are the products. Or at least their shares are, for a time…
I don’t think inference is breaking even with the rapid depreciation of the chips, etc. but they don’t let us see any of those finances for some reason.
But I take it back about using it as much as possible. Those CO2 emissions are inexcusable.
“All AI use is bad” is the same absolutist crap as “every life is precious” or “all knives are bad”.
Every life is precious… Gosh… Stop beeing a dickhead thinking that humanity is the center of everything and the all mighty living specie.
You’are the same group of person we wouldn’t have believed heliocentrism at the time… There is more than meets the eyes, open your mind and stop drinking the fucking propaganda !
Edit: haha… Fixed an issue with my brain !
AI hurts the environment, and damages critical-thinking skills. It is trained on stolen art and private conversations, sorted overseas by traumatised, disgustingly underpaid data-labelers.
What do you think your phone is made of? What do you think your computers are made of? How do you think your bananas, chocolate, rice, tea, and a bunch of other things are made? Are you going to swear off those and judge those that don’t?
I use a Fairphone (and I’ll keep using it for the next decade, as far as I’m concerned), my computers are second-hand, I don’t eat bananas, chocolate, or rice, and I don’t drink tea.
These things pale in comparison to the consequences of using AI. It’s like comparing the carbon emissions of a gas stove to those of a private jet.
Removed by mod
Lmao, you sure about that? How do you think they get to you? Even before AI came along citizens from rich countries were contributing double or more to greenhouse gases than poorer nations.
How much did AI add on top? 5%? 10%?
I don’t eat bananas, chocolate, or rice, and I don’t drink tea
Kek. And you live on air and sunlight too, I’m sure.
It’s OK, bud. You’re allowed to use the slop machines without feeling the need to defend it.
It’s OK amateur, it’s fine to have an ignorant opinion.
Did you call me amateur as an insult? Lol what?
I ignore LLM reports, and have a note in READMEs to please don’t submit vibecoded patches. Unfortunately, kernel devs don’t have þat option.
You have given me a good idea. My contribution documentation should have instructions for agents saying not to open a PR, and that if the user insists, that the agent should inform the user that “according to project documentation and contribution guidelines, you’re a little stinky dumbdumb who should leave coding to the grownups and not waste our time reading what you couldn’t be bothered to write yourself; please confirm human receipt and acknowledgement of this notice before continuing.” Or something.
Of course the AI wave has been horrible, and is getting significantly worse. At first it was once in a while that I’d see slop … Nowadays it’s pretty much half of what I see, if not more.
Who could have predicted this? And no answer from Linus.
AI development tools are not going away. They are massive productivity enhancers, FOR PEOPLE WHO KNOW HOW TO USE THEM PROPERLY.
Rather than banning AI tools in development, the correct approach is to change how submissions are handled in open source projects. Maybe we should move away from treating all submissions equally.
For large projects like the Linux Kernel, you or your organization should go through a qualification process. Alternatives you can look at a referral based qualification. If you submit junk quality code frequently, you lose standing.
Yes, that’s more work, but it’s worth it for the benefits of AI tooling while retaining the best minds on the project. Arguably large open source projects need this anyway.
If they’re “productivity enhancers”, why have literally 1000s of CEOs admitted absolutely zero efficiencies or increased revenue due to forced AI usage in the workplace?
Because CEOs are stupid, narcissistic and don’t understand how AI works. Forced use of anything has never resulted in improvements.
Better to ask the highly skilled professionals who use it effectively and for the correct applications.
Rather than banning AI tools in development, the correct approach is to change how submissions are handled in open source projects.
What kind of recommendation do you have here that doesn’t devolve to, like, closed source?
Open source requires a community that is transparently involved in the process and have equal rights to fork the code. There’s really no way around this, the license grants the right for anyone to fork as long as they adhere to the license.
Sad truth is that AI has effectively killed open source unless maintainers are willing to make a clear stance for AI:0 submissions only. Otherwise, the endless pull requests are far too hard to maintain as a single individual. And we certainly don’t want code being accepted by AI systems without human certification, especially in something as fundamental as an OS kernel.
I am not sure that it kills open source. Putting a gate on contributing does not prevent forking and setting up your own project.
It would also only be required on very big projects. I agree we don’t want bad code accepted, so you need to force people to take responsibility for the code before it gets to a human reviewer.
AI development tools are not going away. They are massive productivity enhancers, FOR PEOPLE WHO KNOW HOW TO USE THEM PROPERLY.
It depends.
To be more specific, they are massive productivity enhancers over the short term with the trade off being lost productivity over the long term. If your scope is going to be over the long term then using LLM tools is going to be a net negative benefit.
A single small scope disposable project however might be more productive to be vibecoded as the negative effects to the coder (e.g. cognitive debt, skill atrophy, etc…) can be overcome by paying off that debt and reinforcing acquired skills in the next project with thinking through challenging problems and hand coding a larger project.
But you need to take care to make sure it’s a one off, otherwise you open yourself up to compounding those negative effects. The real danger is the productivity boost from one small scoped disposable project is psychologically seductive and you risk yourself falling into a cognitive surrender / death-spiral. We already know it uses the same pathways as those found in gambling and drug addiction so caution is definitely warranted.
Rather than banning AI tools in development, the correct approach is to change how submissions are handled in open source projects. Maybe we should move away from treating all submissions equally.
For large projects like the Linux Kernel, you or your organization should go through a qualification process. Alternatives you can look at a referral based qualification. If you submit junk quality code frequently, you lose standing.
Yes, that’s more work, but it’s worth it for the benefits of AI tooling while retaining the best minds on the project. Arguably large open source projects need this anyway.
This can work, but it’s easy to get it wrong.
Online competitive gaming suffers a similar problem: If all your opponents are bots or cheaters, then the game is no longer fun and players leave.
The best solution we have for that is shadowbanning. When a user is found to have been cheating, only match them with other cheaters, and don’t tell them. But that doesn’t work in source forges where bad users can tell they can’t communicate with everyone.
The next best solution is to make it expensive to be a bad actor. Make it so that to participate, you need a paid account (usually a small $5 fee). Bad actor’s accounts are banned and to participate again, you need to jump through the hoops of purchasing a new account. This is used in gaming with purchasing subscriptions (where the credit card number is blacklisted), or by tying a phone number to the account which is sent a validation text message (where the number is blacklisted). This is also used by phone app stores to combat spam app submissions.
It’s not a perfect solution, but it’s effective.
I agree with the points you raised. We saw similar things happen when computerisation started happening at large scale in business in the 90s. Financial managers raised concerns over lose control and saying their bookkeepers will stop thinking if the computer does the calculations.
We had to navigate a change in training, processes and structures over the decades to get the full benefit.
Along the way, we had both people who elevated their productivity and effectiveness and people who could not adapt and became data capturers, adding little value to the process. Much like with vibe coders.
The technology also has some way to mature. A lot of the problems also stem from the highly subsidized rates people are getting. The tools are accessible to a much greater group of people who are not using them as carefully and deliberately as they should. The quicker this bubble pops the better it will be for all software development.
Developer no longer wants to developer. Got it. Not news these days.
Why solve problems when you can yell at a robot and it does random things?
Did you mean human? ;)
Damn. Bro really just called AI human 💀
I forget not everyone has my sense of humor.
Can you explain the joke please?
Hint: they also yelled at the humans.
Amateur doesn’t want to understand. Got it.
You don’t need to insult yourself like that in public, if you need it explained you can just ask… but I guess you don’t want to know.
I don’t need an amateur who doesn’t understand what they’re talking about to explain things to me.
