I've closed my share of AI-generated PRs on some OSS repositories I maintain. These contributors seem to jump from one project to another, until their contribution is accepted (recognized ?).

I wonder how long the open-source ecosystem will be able to resist this wave. The burden of reviewing AI-generated PRs is already not sustainable for maintainers, and the number of real open-source contributors is decreasing.

Side note: discovering the discussions in this PR is exactly why I love HN. It's like witnessing the changes in our trade in real time.

> I wonder how long the open-source ecosystem will be able to resist this wave.

This PR was very successfully resisted: closed and locked without much reviewing. And with a lot of tolerance and patience from the developers, much more than I believe to be fruitful: the "author" is remarkably resistant to argument. So, I think that others can resist in the same way.

Has there been any posts where the AI-user goes "oh, that makes sense. Sorry. Carry on."?

Yes.

https://github.com/povik/yosys-slang/pull/237#issuecomment-3...

I was super excited about this PR and disappointed when it turned out to be AI generated.

Even if their AI says that for them, it doesn't mean they'll actually do it.

Successfully resisted, yes, but it also looks like a lot of actual human hours went into even replying to the PR in the first place. At what point do.l maintainers get overwhelmed with just politely rejecting PRs and throw their hands up because the time they allocated to the project they love has all been eaten up with rejecting slop?

Open-source maintainers will resist this wave even just because they don't want to be mocked on HN/Reddit/their own forums.

It's corporation software that we need to worry about.

OSS has always pushed back, just because of the maintenance burden in general, and corporate can just "fix it later" because there are literally devs on payroll. Or at least push through and then dump the project, the goal is just completely different, each style works in its context.

But I don't know if corporate software can really "push through" these new amounts of code, without also automating the testing part.

> It's corporation software that we need to worry about.

That ship has sailed..

> I wonder how long the open-source ecosystem will be able to resist this wave. The burden of reviewing AI-generated PRs is already not sustainable for maintainers, and the number of real open-source contributors is decreasing.

I think the burden is on AI fanbois to ship amazing tools in novel projects before they ask projects with reputations to risk it all on their hype.

To deliver a kernel of truth wrapped in a big bale of sarcasm: you're thinking of it all wrong! The maintainers are supposed to also use AI tools to review the PRs. That's much more sustainable and would allow them to merge 13,000 line PRs several times a day, instead of taking weeks/months to discuss every little feature.

The difference here of course is in how impressed you are by AI tools. The OCaml maintainers are not (and rightly so, IMO), whereas the PR submitter thinks they're so totally awesome and leaving tons of productivity on the table because they're scared of progress or insecure about their jobs or whatever.

Maybe OCaml could advance rapidly if they just YOLO merged big ambitious AI generated PRs (after doing AI code reviews) but that would be a high risk move. They have a reputation for being mature, high quality, and (insanely) reasonable. They would torch it very quickly if people knew this was happening and I think most people here would say the results would be predictably bad.

But lets take the submitter's argument at face value. If AI is so awesome, then we should be able to ship code in new projects unhampered by gatekeepers who insist on keeping slow humans in the loop. Or, to paraphrase other AI skeptics, where's all of the shovelware? How come all of these AI fanbois can only think about laundering their contributions through mature projects instead of cranking out amazing new stuff?

Where's my OCaml compiler 100% re-written in Rust that only depends on the Linux kernel ABI? Should cost a few hundred bucks in Claude credits at most?

To be clear, the submitter has gotten the point and said he was taking his scraps and going to make his own sausage (some Lisp thing). The outcome of that project should be very informative.

Does your own experience align with that of the maintainer who wrote:

> in my personal experience, reviewing AI-written code is more taxing that reviewing human-written code

Yes

I think he’s resume building.

Hi, author here.

I love reading the posts in this thread. It seems the waterfall vs Agile debate is still vivid in the HN community, which surprises me.

I know that developers have different experiences with SDD, and there is no one-size-fits-all methodology anyway. It's interesting to read the feedback of people who really like it, especially when they describe their background and the type of project they use it for.

In my experience, SDD doesn't bring any value as I'm already using Plan mode before going to implementation. I have also never seen instances of a coding agent doing exactly what I had in mind in the first try (except for very simple cases), so there must be iterations, which defeats the purpose of the Big Design Up Front.

Finally, I really think coding agents pave the path for a new way to develop digital products, more productive and closer to the users' expectations. But I doubt that SDD lies anywhere in this path.

Great feedback from the Etsy team about a real-world LLM usage that proved efficient.

This new browser mode is a robot that replaces visitors on websites. It can't be good news for website editors...

Should we (developers) start building websites for robots?

We already build websites for Googlebot so I don't really see much a difference. Maybe designers should be worried because if there's nothing to "look at" there's no point in making it look nice. This feels like XML/XHTML all over again.

Well, guess what we are doing when we say SEO?

AI is building websites for AI. Let the enshittification Olympics commence!

This looks similar to React application frameworks like react-admin [1] or Refine [2]:

    const App = () => (
      <Admin dataProvider={dataProvider}>
         <Resource name="posts" list={PostList} />
      </Admin>
    )
    
    const PostList = () => (
      <List>
        <DataTable>
          <DataTable.Col source="date" />
          <DataTable.Col source="title />
          <DataTable.Col source="author" />
        </DataTable>
      </List>
    );

The article mentions XML, but the true revolution is JSX itself, which lets you describe any piece of logic as a React element. This opens the possibility to create DSL for everything, just like in Python.

[1]: https://github.com/marmelab/react-admin [2]: https://github.com/refinedev/refine

Congrats! Now you need an entire datacenter to visualize a web page.

Couldn't this time reasonably well on a local machine is you have some kind of neutral processing chip and enough ram? Conversion to MD shouldn't require a huge model.

only if you use an API and not a dedicated distill/tune for html to MD conversion.

But the question of Javascript remains

This is nice, but I wonder about the actual use cases of such a service, given the very loose permissions:

1. Anyone can subscribe to a channel 2. Any registered user can publish to a channel 3. Only registered users can publish to their personal channel (@username)

The second point in particular is problematic. I don't want to add notifications to my app, only to have a script kiddie use is to spam my users.

The second point is solved with the 3rd point I think. In your case you need to create a user channel

From the FAQ:

> Ahey.io has two types of channels:

> Regular channels: Any authenticated user can publish to these channels.

> User channels: These channels are in the format @username, and only the user who created the user account can publish to it.

OP is making a decision about a complex problem using only back of the envelope calculation and without looking for scientific studies on the matter. We’re not obliged to take their advice. Typing “AI Carbon Footprint” on Google Scholar brings much better info than this post.

Evaluating the quality of the responses of AI agents used to be tricky. It required knowledge of eval criteria as well as third-party tools like promptfoo, ragas or prometheus. Now openAI makes it ridiculously easy with a new API endpoint. It can grade a completion against a reference response, assess its format and tone, and you can even promt the eval to add your own criteria.

It can solve sudoku. It took 119s to solve this easy grid:

_ 7 8 4 1 _ _ _ 9

5 _ 1 _ 2 _ 4 7 _

_ 2 9 _ 6 _ _ _ _

_ 3 _ _ _ 7 6 9 4

_ 4 5 3 _ _ 8 1 _

_ _ _ _ _ _ 3 _ _

9 _ 4 6 7 2 1 3 _

6 _ _ _ _ _ 7 _ 8

_ _ _ 8 3 1 _ _ _

I tried to have it solve an easy Sudoku grid too, but in my case it failed miserably. It kept making mistakes and saying that there was a problem with the puzzle (there wasn’t).

It seems to be unable to solve hard sudokus, like the following one where it gave 2 wrong answers before abandoning.

+-------+-------+-------+ | 6 . . | 9 1 . | . . . | | 2 . 5 | . . . | 1 . 7 | | . 3 . | . 2 7 | 5 . . | +-------+-------+-------+ | 3 . 4 | . . 1 | . 2 . | | . 6 . | 3 . . | . . . | | . . 9 | . 5 . | . 7 . | +-------+-------+-------+ | . . . | 7 . . | 2 1 . | | . . . | . 9 . | 7 . 4 | | 4 . . | . . . | 6 8 5 | +-------+-------+-------+

So we're safe for another few months.