Yes. I started two projects with AI from scratch. Both abandoned, complete mess. Projects without AI are so easy to manage, maintain, add/remove features, etc. I use AI as a search engine on my projects instead of Google. I ask what's wrong with my code and change or improve it myself based on my experience.

People, especially those who don't do software development, often conflate coding and software development.

The models aren't good at architecture and design. But they take direction on architecture and design and design well and can refactor code quite effectively. AI agents can absolutely be used to clean up vibe coded code bases once you figure out if the investment is worth it. The mess can be avoided if you give them sufficient guidance on architecture and design upfront.

That said, doing so purely in text form doesn't feel great right now. I've been thinking about UML lately. The problem with that was the roundtrip after the code was generated and then the implenetation happened. I don't necessarily think UML is the solution, but neither is walls of dense text.

I've had the opposite experience. Spec driven development really makes things much easier to maintain. If you're just yolo'ing it and throwing prompts around things will fall apart fast.

Were you reading through the code it was generating to make sure the flow was intuitive and comprehensible for each PR? Projects only turn in to maintainable messes if you blindly merge in unmaintainable messy code.

As usual, when people post comments like this they never specify what model and when they used it. There is a huge difference between GPT 3 and 6 for example.

Late 2025 also had a step change when agents could largely code autonomously without handholding like previously, and to be honest it's not worth hearing opinions about AI from before that time, that's how significant the change was.

Oh my god. I am sad to have to acknowledge this even if the models have “theoretically” gotten better. I am not a programmer but I am super opinionated with the design and structure of the code and need to make sure whatever I write/ask to generate and use for my own tasks is understood by me at least once. I wasn’t this way in 2023. I am constantly reading/trying for an agent to help me write simple code without spending too much time. But so far nothing has worked. I wish someone figures it out otherwise, I personally would not be able to realize the AI agent productivity benefits that others are supposedly seeing.

I treat AI like an intern or junior team member. With enough guidance, they can contribute a lot but you can't let them loose without supervision or they usually will produce a big mess. As of now, you are still responsible for overall architecture. One strong indicator that something is going wrong are big pull requests where the AI has rewritten large sections of the code.

AI is a useful tool but it absolutely needs a lot of human guidance.

Unlike a compiler it won't give up at the first sign of trouble but that just means it left alone it will dig bigger and bigger holes.

Treat prompt engineering as a discipline and refine your technique. When it produces garbage throw out the work and start over until you figure it out.

Were you reviewing the changes? I've seen lots of projects with this problem. But if AI PRs have to pass the same review bar as any other PR then it shouldn't be an issue in theory (if you can actually maintain the discipline).

Vibe coding has always had and always will have one fundamental flaw: you didn't write the code it produced, therefore you don't have a good understanding/mental model of it.

On the other hand asking these clankers "review the feature branch I wrote" and "review my entire codebase for bugs" or "help me debug this" has saved me months of prospective work.

And more recently most major models have been getting _really_ good at RE, for example you can have OAI models (and maybe A/'s if they don't refuse) use idalib MCP and reverse-engineer stuff from start to finish, then follow up with GLM 5.3 for vuln assessment and exploit PoC.

Stuff that used to take weeks or months now just takes a few hours, or less.

I am not saying you are right or wrong, but I don’t think you can make such a broad conclusion simply because of your own experience.

You say you used AI and your projects turned into unmaintainable messes, so your conclusion is that it means AI is not living up to its promises.

I guess if the argument is “AI makes it so you always get a great result no matter how you use it”, then your argument is sound. Your projects not working out proves that AI doesn’t always work no matter what.

However, that doesn’t mean you can’t use AI to create sustainable and well organized code. Failing to do something doesn’t mean it’s impossible and anyone who thinks they can is not paying attention.

I can’t run a marathon. If I went out and tried to run one, I would get a few miles and collapse, failing completely.

I don’t think it would be reasonable, though, at that point to say “running a marathon is impossible, anyone who says they can do it clearly lying. I tried and didn’t even make it 5 miles!”

I wish people would stop assuming their experience with something is the only possible truth.

The people saying programming is solved couldn't program in the first place is what I've noticed. So to them it really does feel solved, things "work" and they don't have to learn what they don't know about programming.

I found your commit and your usage of AI seemed reasonable. It seems to me like your PR itself and the subsequent comments and correspondence was also human written.

I think a PR "in flight" shouldn't have been closed like that.

All this will do is push out developers like you that honestly disclose, and instead people will now just lie.

What is actually the meaning of “handcrafting” here?

It's not. Read the article, they have a good reason for banning it and it's not because they hate LLMs.

It also doesn't answer the question of how they might even recognize LLM generated code in contributions to PopOS directly.

I have yet to understand how maintainers can't distinguish beyond (1) PRs that literally include Claude co-author notes or (2) low quality code contribution regardless of the creator.

I agree.

PopOS is Ubuntu with extra problems. Ubuntu itself is fine, but then PopOS adds weirdness.

Cosmic has been in beta for how long ?

I don't think it's performative.

They aren't saying that AI produces bad code or is terrible for the world in some way.

It's mainly just resulting in a lot of PRs that they don't have enough time to review or features they don't plan to add.

It sounds like what they are primarly aiming for is introducing backpressure in their own review pipelines.

This is a good idea, we should start a blacklist of open-source projects that are known to have used LLMs. There should be two universes of code, one for hand-typed code used by people who care about quality and one for slop used by those making trash.

Probably because pop_os and Cosmic are so niche and their market share so insignificant, that they're irrelevant to attackers and bad actors, when those now have much bigger fish to fry to make their time and effort worth it. See the Arch AUR attacks, for perspective.

I think even amongst the HN and Linux userbase, pop_os is still niche, let alone amongst normies who never heard about Linux. So they can afford take the high road and treat it like their personal sandbox, accepting only human written code.

But larger and more important projects like Fedora and Debian are more pragmatic with the fact that they'll have to accept AI written(but human reviewed) code, if they wish to keep up with the real world development and threats, as expressed by Linus Torvalds himself.

The thing is, the cat's out of the bag on this one now, especially in the field of pen-testing and reverse-engineering. AI can brute-force its way into projects in ways that beat even experienced researchers, so your only choice to keep up is to accept the use of AI generated fixes as a counter defense.

So you took every single line of open source code you could possibly get your hands on (using scrapers so violently dumb that they amount to a permanent low-grade DDoS) and spent billions of dollars to tune trillions of parameters, and the value you can offer is… “let us inundate you with bad code or else we’ll generate exploits for your software”.

Using AI to find vulnerabilities doesn’t mean that you need to use AI to generate the code that fixes them. And you can still ask AI whether it thinks the fix is okay, as a second opinion.

AI finds a lot of "vulnerabilities" but most are fake, untested, or not actually vulnerabilities.

Reminder that AI is quite stupid.

Irony is that they will get the benefits from upstream projects (like the Linux kernel) that does accept AI inputs.

The issue is “ai generated code” using ai to find bugs/0 day and manually writing a fix would (I assume) be allowed under the new rules.

I'm assuming they still use AI to find vulnerabilities, just not fix them?

Issue is entrenchment in the old SWE world that ceased to exist somewhere in August this year, and using AI to mechanize the traditional workflows. Also people with "I need to eyeball each char in PR diff" attitude, which is fucking unproductive at this point.

Feels like AI on autopilot running OSS projects is the dream everyone is trying to get to. Tokens will never be free. Anthropic needs to go IPO. You make an interesting point about personal spend, but bad PRs are unlikely to be on purpose. But the discipline to review/clean up the slop might not be there?

A 100kloc PR is unacceptable regardless of the source. That needs to be broken down into reviewable chunks.

There are a whole lot of people (in tech) who truly hate AI and want nothing to do with it. Those people will flock to projects who take a stand against it.

Reasonable, although I've taken a different approach. Either closing such PRs, or treating them as very detailed issues and having my own LLM build the actual fix.

My repos probably don't see as much traffic as SQLAlchemy though.

> If I'm going to have a small fix or improvement coded by an LLM (which I do all the time), I want to prompt the LLM directly, rather than having someone trying to pad their resume forward my communications onto their LLM via PRs. What's the point of that?

Which is why LLM PRs should just be issues (if there isn’t one already). Make the issue author a co-author on the PR. But let the maintainer actually oversee the LLM generated solution.

rejecting low quality ones should be the norm regardless of whether an AI or a human wrote them. the question is what would happen if you were swamped with high quality PRs? what will happen once you are? (that's probably a 2027 question!)

Maybe the policy should be: no AI PRs except from established contributors who have been vetted?

So basically you're saying you reject drive-by PRs.

It might get millions in founding.