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@SnoopJ @xgranade We're definitely getting hit by slop PRs as well (easiest to see by looking at the list of closed PRs in the CPython repo). Unfortunately, I think the initial LLM guidance was born out of a Discord discussion, so I don't have a handy link for the rationale behind it. https://github.com/python/devguide/issues/1513 has *some* info, but not the original examples where we saw LLMs being used to good effect by non-native English speakers to participate more easily in English-only threads.
@ancoghlan @xgranade I have experienced the assistive effect it has when operating across a language barrier¹ and can't deny that it's very real.
Appreciate the peek behind the curtains.
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¹ though gosh I wish we had specialist machine translator models doing this very important work instead of generalists who might just pepper in bad facts for non-linguistic reasons >.< -
As a second addendum, since this has come up in several reply threads, the number of commits is limited so far, and doesn't date back past December 5, 2025 so far as I'm aware of.
The Python-specific part of that broader problem is, at least to my mind, that there's not a mechanism that I see for limiting that exposure to those commits, to preventing further and more expansive commits in the future.
Addendum the third, amplifying something I've said a few times now in replies: as much as this is not about Python *in particular* so much as Python *as an example* of a systemic problem, it's also not about individual people so much as about OSS communities writ large.
There are absolutely bad-faith actors at play here who have taken active effort to make things worse, but I don't think that's common, nor do I think pointing fingers at individual contributors here is a useful strategy.
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Addendum the third, amplifying something I've said a few times now in replies: as much as this is not about Python *in particular* so much as Python *as an example* of a systemic problem, it's also not about individual people so much as about OSS communities writ large.
There are absolutely bad-faith actors at play here who have taken active effort to make things worse, but I don't think that's common, nor do I think pointing fingers at individual contributors here is a useful strategy.
Naming individual people is sometimes justified, and I have done so in other contexts, but it's best done with extreme caution. For calling out the *systemic problem* of slopware vendors making incursions into OSS processes, it's just not worth the potential harm, that's not good praxis imho.
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Naming individual people is sometimes justified, and I have done so in other contexts, but it's best done with extreme caution. For calling out the *systemic problem* of slopware vendors making incursions into OSS processes, it's just not worth the potential harm, that's not good praxis imho.
@xgranade Other fun complications: OSS consumers actively paying maintainers of their dependencies is good and something we want to encourage. Ditto for offering maintainers free access to tools that make their lives easier. Yet some of those consumers and tools pose a credible threat to the entire edifice of open source collaboration.
I'm a former defence contractor that works for a retail bank so the moral ground I'm standing on is far from high, but even I can see we're deep in a quagmire.
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@xgranade Other fun complications: OSS consumers actively paying maintainers of their dependencies is good and something we want to encourage. Ditto for offering maintainers free access to tools that make their lives easier. Yet some of those consumers and tools pose a credible threat to the entire edifice of open source collaboration.
I'm a former defence contractor that works for a retail bank so the moral ground I'm standing on is far from high, but even I can see we're deep in a quagmire.
@ancoghlan I mean, I get it, yeah. My PhD was largely funded by the US military, and was at an institution that is abusive in the extreme. My postdoc was a bit better, but not by a *lot*.
All that said, I do think that it isn't unreasonable to consider AI as being fashware, given its eugenicist origin and given the ways it's funded and developed. I get some folks are stuck in jobs that make and push it, but also, it's important to resist incursion into OSS spaces?
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@MissingClara @xgranade That's a bad argument against having a policy. Policy is a statement of who does and doesn't belong. If they're using it without revealing it, trying to launder code with fraudulent provenance into your project, that's highly malicious behavior worthy of a ban from the project once they're caught. And it's a signal to your good contributors that the project is healthy and not going to be turned into irreparable garbage by slop bros.
@dalias @xgranade we already ban those slop spammers. that leaves reasonable contributors, but no it isn't a good argument. some highly knowledgeable folks that I know are experimenting using LLMs as a tool with success, while I dislike it due to ethical reasons, there is no objective technical reason to reject those contributions.
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@dalias @xgranade we already ban those slop spammers. that leaves reasonable contributors, but no it isn't a good argument. some highly knowledgeable folks that I know are experimenting using LLMs as a tool with success, while I dislike it due to ethical reasons, there is no objective technical reason to reject those contributions.
@MissingClara @dalias I disagree with the use of AI on an ethical basis, and also believe that there's an objective technical reason to reject AI-generated code. In particular, LLMs do not model the behavior of code, and do not reason about its likely effects. It similarly isn't designed in any meaningful way. Those properties aren't compatible with sound engineering?
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@MissingClara @dalias I disagree with the use of AI on an ethical basis, and also believe that there's an objective technical reason to reject AI-generated code. In particular, LLMs do not model the behavior of code, and do not reason about its likely effects. It similarly isn't designed in any meaningful way. Those properties aren't compatible with sound engineering?
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@MissingClara @dalias (afk for a while due to other life things, not trying to ignore you, sorry)
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@dalias @xgranade we already ban those slop spammers. that leaves reasonable contributors, but no it isn't a good argument. some highly knowledgeable folks that I know are experimenting using LLMs as a tool with success, while I dislike it due to ethical reasons, there is no objective technical reason to reject those contributions.
@MissingClara @xgranade There absolutely are technical reasons. Lack of provenance. Lack of ability to license the code comoatibly with the project. High probability of easily missed errors - the slop machines excel at making things that look deceptively right in form but aren't. People who don't understand these problems are not "highly knowledgeable". They're folks who've already sabotaged their own cognitive facilities and whom it's not safe to trust.
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@MissingClara @xgranade There absolutely are technical reasons. Lack of provenance. Lack of ability to license the code comoatibly with the project. High probability of easily missed errors - the slop machines excel at making things that look deceptively right in form but aren't. People who don't understand these problems are not "highly knowledgeable". They're folks who've already sabotaged their own cognitive facilities and whom it's not safe to trust.
@dalias @MissingClara I don't even entirely disagree, but I wouldn't necessarily characterize people who use AI tools as being not "highly knowledgeable," given the sheer amount of disinformation that AI companies have put out about how (and indeed, if!) they work. Well meaning experts can and have come under misapprehensions due to that disinfo.
It's part of why a strong stance banning AI generated code is as important, even at a technical level. It helps counter that disinformation.
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@dalias @MissingClara I don't even entirely disagree, but I wouldn't necessarily characterize people who use AI tools as being not "highly knowledgeable," given the sheer amount of disinformation that AI companies have put out about how (and indeed, if!) they work. Well meaning experts can and have come under misapprehensions due to that disinfo.
It's part of why a strong stance banning AI generated code is as important, even at a technical level. It helps counter that disinformation.
@dalias @MissingClara (still mostly afk, but trying to pop back on occasionally as best as i can)
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@dalias @MissingClara I don't even entirely disagree, but I wouldn't necessarily characterize people who use AI tools as being not "highly knowledgeable," given the sheer amount of disinformation that AI companies have put out about how (and indeed, if!) they work. Well meaning experts can and have come under misapprehensions due to that disinfo.
It's part of why a strong stance banning AI generated code is as important, even at a technical level. It helps counter that disinformation.
@dalias @MissingClara Anyway, that is part of why I don't think going after specific individuals is not the most productive thing, even aside from the potential harm. AI in OSS is a systemic problem, irrespective of the expertise or lack thereof of the people using AI products.
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@MissingClara @xgranade There absolutely are technical reasons. Lack of provenance. Lack of ability to license the code comoatibly with the project. High probability of easily missed errors - the slop machines excel at making things that look deceptively right in form but aren't. People who don't understand these problems are not "highly knowledgeable". They're folks who've already sabotaged their own cognitive facilities and whom it's not safe to trust.
@dalias @xgranade I can concede of the provenance and licensing, but on the last point, that can also be true from regular user contributions. to be a good maintainer you need to be able catch those errors, so it doesn't matter if it comes from a real user or a LLM. especially in a project like Python, where the smallest thing can break a lot of code downstream.
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@dalias @xgranade I can concede of the provenance and licensing, but on the last point, that can also be true from regular user contributions. to be a good maintainer you need to be able catch those errors, so it doesn't matter if it comes from a real user or a LLM. especially in a project like Python, where the smallest thing can break a lot of code downstream.
@MissingClara @xgranade If someone actually wrote it and it looks right, you have whatever mental process they went thru writing it plus the "looks right" as reasons it's likely right. If it was LLM slop, you only have how it looks.
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@MissingClara @xgranade If someone actually wrote it and it looks right, you have whatever mental process they went thru writing it plus the "looks right" as reasons it's likely right. If it was LLM slop, you only have how it looks.
@dalias @MissingClara I don't want to sell anyone reviewing code short; my objection isn't that people aren't doing enough to review LLM extruded code.
It's that reviewing extruded code is *at best* an effective mitigation of a risk that shouldn't have been there in the first place. With human-written code, you at least have some marginal, tiny trust in the author that they are competent, have some concept of how the code works, and so forth, but *none* of that exists for AI.
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@dalias @MissingClara I don't want to sell anyone reviewing code short; my objection isn't that people aren't doing enough to review LLM extruded code.
It's that reviewing extruded code is *at best* an effective mitigation of a risk that shouldn't have been there in the first place. With human-written code, you at least have some marginal, tiny trust in the author that they are competent, have some concept of how the code works, and so forth, but *none* of that exists for AI.
@dalias @MissingClara From that point, I guess I'm making a "just because the hole is there doesn't mean we should keep digging" kind of argument. Code review, even by excellent and competent reviewers, has at best *reduced* but not eliminated defects and vulnerabilities in code.
Code review is incredibly difficult, it's why rely so much on having incredibly competent reviewers.
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@dalias @xgranade I can concede of the provenance and licensing, but on the last point, that can also be true from regular user contributions. to be a good maintainer you need to be able catch those errors, so it doesn't matter if it comes from a real user or a LLM. especially in a project like Python, where the smallest thing can break a lot of code downstream.
@MissingClara the intent of a real contributor is to provide a good, safe, working code change. the goal of an llm is to deceive you into believing that it produced good, safe, working code.
given how important details are in something like Python, how far do you want to ride this conflict of interest?
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@MissingClara @xgranade If someone actually wrote it and it looks right, you have whatever mental process they went thru writing it plus the "looks right" as reasons it's likely right. If it was LLM slop, you only have how it looks.
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@MissingClara the intent of a real contributor is to provide a good, safe, working code change. the goal of an llm is to deceive you into believing that it produced good, safe, working code.
given how important details are in something like Python, how far do you want to ride this conflict of interest?
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@discatte @ozzelot my plan at some point is to build a long fully custom control surface with rotary encoder jog wheels, each with a ring of WS2816B-2121 LEDs for indication and position marking. not hard to set that up for USB MIDI.
that'd then be a good starter project to get more familiar with the stack, ready for when I eventually build a custom grandMA3 Command Wing clone for onPC.
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Ma chi è sta qui?! 😅
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@support No, not yet. As I told @thedarktangent, we'll run some tests, but we can only do that once I've had all my time to test compatibility with all the other instances feddit.it currently works with.
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...per non parlare del diluente alla nitro. 😬
