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> I've had manually written, well thought through, well conceived, rough around the edges code get called "AI slop" by a colleague (who I very much respect and have a good relationship with) who admittedly hadn't had a chance to thoroughly understand the code yet.

This is the core problem with AI that makes so many people upset. In the old days, if you get a substantial submission, you know a substantial amount of effort went into it. You know that someone at some point had a mental model of what the submission was. Even if they didn't translate that perfectly, you can still try to figure out what they meant and we're thinking. You know the submitter put forth significant effort. That is a real signal that they are both willing and able to do so to address going forward to address issues you raise.

The existence of AI slop fundamentally breaks these assumptions. That is why we need enforced social norms around disclosure.

We need better social norms about disclosure, but maybe those don't need to be about "whether or not you used LLMs" and might have more to do with "how well you understand the code you are opening a PR for" (or are reviewing, for that matter). Normalize draft PRs and sharing big messes of code you're not quite sure about but want to start a conversation about. Normalize admitting that you don't fully understand the code you've written / are tasked with reviewing and that this is perfectly fine and doesn't reflect poorly on you at all, in fact it reflects humility and a collaborative spirit.

10x engineers create so many bugs without AI, and vibe coding could multiply that to 100x. But let's not distract from the source of that, which is rewarding the false confidence it takes to pretend we understand stuff that we actually don't.

  but maybe those don't need to be about "whether or not you used LLMs" and might have more to do
  with "how well you understand the code you are opening a PR for" (or are reviewing, for that matter)

AI is a great proxy for how much someone has. If you're writing a PR you're demonstrating some manner of understanding. If you're submitting AI slop you're not.

I've worked with 10x developers who committed a lot of features and a lot of bugs, and who got lots of accolades for all their green squares. They did not use LLM dev tools because those didn't exist then.

If they had used AI, their PRs might have been more understandable / less buggy, and ultimately I would have preferred that.

  If they had used AI, their PRs might have been more understandable / less buggy, and ultimately I would have preferred that.

Sure, and if they had used AI pigs could depart my rectum on a Part 121 flight. One has absolutely nothing to do with the other. Submitting AI slop does not demonstrate any knowledge of the code in question even if you do understand the code.

To address your claim about AI slop improving the output of these mythical 10x coders: doubtful. LLMs can only approximate meaningful output if they've already indexed the solution. If your vaunted 10x coders are working on already solved problems you're likely wasting their time. If they're working on something novel LLMs are of little use. For instance: I've had the pleasure of working with a notoriously poorly documented crate that's also got a reputation for frequently making breaking changes. I used DDG and Google to see if I could track down someone with a similar use case. If I forgot to append "-ai" to the query I'd get back absolutely asinine results typically along the line of "here's an answer with rust and one of the words in your query". At best first sentence would explain something entirely unrelated about the crate.

Potentially LLMs could be improved by ingesting more and more data, but that's an arms race they're destined to lose. People are already turning to Cloudflare and Anubis en masse to avoid being billed for training LLMs. If Altman and co. had to pay market rate for their training data nobody could afford to use these AI doodads.

>> but maybe those don't need to be about "whether or not you used LLMs"

The only reason one may not want disclosure is if one can’t write anything by themselves, thus they will have to label all code as AI generated and everyone will see their real skill level.

> Normalize draft PRs and sharing big messes of code you're not quite sure about but want to start a conversation about. Normalize admitting that you don't fully understand the code you've written / are tasked with reviewing and that this is perfectly fine and doesn't reflect poorly on you at all, in fact it reflects humility and a collaborative spirit.

Such behaviors can only be normalized in a classroom / ramp-up / mentorship-like setting. Which is very valid, BUT:

- Your reviewers are always overloaded, so they need some official mandate / approval to mentor newcomers. This is super important, and should be done everywhere.

- Even with the above in place: because you're being mentored with great attention to detail, you owe it to your reviewer not to drown them in AI slop. You must honor them by writing every single line that you ask them to spend their attention on yourself. Ultimately, their educative efforts are invested IN YOU, not (only) in the code that may finally be merged. I absolutely refuse to review or otherwise correct AI slop, while at the same time I'm 100% committed to transfer whatever knowledge I may have to another human.

Fuck AI.

> The existence of AI slop fundamentally breaks these assumptions. That is why we need enforced social norms around disclosure.

Exactly! The code used double as "proof of work". Well-formed language used to double as "proof of thinking". And that's what AI breaks: it speaks, but doesn't think. And my core point is that language that does not originate from well-reasoned human effort (i.e., from either writing the language directly, or from writing such code manually that generates the language deterministically, and for known reasons/intents), does not deserve human attention. Even if the "observable behavior" of such language (when executed as code) looks "alright".

And because I further think that no code should be accepted without human review (which excludes both not reviewing AI-generated code at all and having some other AI review the AI-generated code), I conclude that AI-generated code can never be accepted.

I get it. But it’s ultimately up to the maintainer here.

Of course. I don't actually think the maintainer guidelines here are entirely unreasonable, even if I'd personally modify them to reduce reactive panic.

My little essay up there is more so a response to the heated "LLM people vs pure people" comments I'm reading all over this discussion. Some of this stuff just seems entirely misguided and fear driven.

You should not just be open to being transparent, you need to understand that there will be times you will be required to be transparent about the tools you’ve used and the ultimate origin of your contributions, and that trying to evade or even push back against it is a huge red flag that you cannot be trusted to abide by your commitments.

If you’re unwilling to stop using slop tools, then you don’t get to contribute to some projects, and you need to be accept that.

Your blanket determination that the tools themselves are slop generators is an attitude I'm definitely not interested in engaging with in collaboration.

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