JCTheDenthog

Poe's law is making it hard to tell if your comment is sarcasm or AI-induced psychosis.

I’m curious if that matters if humans are never going to even read this code?

If by never even read you don't include attaching a debugger to solve an issue. 1,000 global mutable variables would make debugging anything an absolute nightmare.

Thanks!

Got any specific examples? I believe you, I'd just like some concrete examples to show my coworkers.

Dude, stop with “slop”.

No.

It's a useful term, just like "clickbait" was 10 to 15 years ago (and still is). Trying to police other people calling it slop is reminiscent of Microsoft autobanning anyone using the term "Microslop" on their Discord, it's idiotic language policing and I'm not going to do it, simple as.

I hear a lot of complaints about bun but nothing concrete about what broke in the migration.

Because it hasn't been released yet (at least not outside of some unstable branches). You can find some criticism of the actual slop here though: https://old.reddit.com/r/rust/comments/1t4033y/buns_rewrite_...

Given that even the unsafe audit article appears to be written by AI that doesn't seem like much thought to me.

Given that LLMs are capable of generating code from open source projects verbatim (and entire books like Harry Potter verbatim) and no one gives a damn it seems like copyright is essentially a dead letter, legally speaking at least And the courts (in the US and elsewhere) haven't decided to intervene at all. Still a scummy thing to do morally though, I agree.

Assuming it all works 50k scanners running nonstop at 60 seconds a scan is 2.1 billion scans a month. Assuming they aren't lying/exaggerating about anything, and assuming there is no downtime/setup/etc. in between. In other words, reeks of massive bullshit.

Actually good quality stuff is more affordable than ever. People just don't want to pay for quality and things that last.

You might want to read *A Market for Lemons".

For me, the painful banging my head against the wall to figure something out is usually the most rewarding sort of learning experience.

https://www.tomshardware.com/news/why-most-roms-are-illegal,...

https://answers.justia.com/question/2025/08/04/is-downloadin...

https://www.howtogeek.com/262758/is-downloading-retro-video-...

etc. etc. etc. etc.

citing that it's illegal even though I own the games

In the. US at least it is actually illegal to download ISOs/roms of games, even if you own a physical copy. It's a stupid law and as a downloader (as opposed to the people hosting the files) your chances of getting into any kind of actual legal trouble are effectively 0, but it is still against the law.

Libraries like Guidance guarantee that the output of an LLM will be syntactically correct (i.e. it will be valid JSON or whatever output format you are wanting). They do not, and fundamentally cannot guarantee that the data contained in them is actually correct, and cannot make the actual behavior of the LLM "well-specified". Or, as you put it, trumps voice wrong.

rather than giving it in a well-specified and tested form

So, code?

At my employer (megacorp with tens of thousands of employees) daily use is mandated. Our annual bonuses and pay raises for our performance reviews were explicitly tied to this.

How much of that use is driven by corporate mandates to use AI anywhere and everywhere (even when it's a terrible fit)?

Or just write it yourself?

Aren’t human coders non-deterministic?

Sure, but LLMs are non-deterministic in ways that no sane human ever would be. See the "Is it better to drive or walk to the carwash" scenario from a few months ago as one of many, many examples. Or a personal example I encountered just a week ago: I asked Claude (Opus 4.8 in case any of the "you aren't using the latest model that totally fixes that issue" types are interested) to convert a bunch of DB calls that currently use raw ADO.NET calls to use Dapper instead.

The projects in this repo were on .NET 4.8.1 and were still using the older format for the .csproj file instead of the newer (and far better) "SDK-style" format that Microsoft introduced a few years ago. It tried to use the dotnet CLI to add references to Dapper, even though the older format of .csproj doesn't work with that. The dotnet CLI returned errors about trying to add the package references for Dapper, which Claude completely ignored while continuing to try and convert the ADO.NET calls to Dapper. And at the end it tried building the project, which of course failed, and then it confidently informed me that the conversion had been completed successfully and that the build completed successfully and all tests were passing successfully, even though the output from the build it had done immediately prior clearly told the LLM otherwise.

A real human, despite being non-deterministic, would have caught the issue at multiple stages. They would have seen the error when trying to add the reference. If they ignored that then they would have seen the red squiggly lines all over the (deterministic) IDE telling them there was something wrong, along with autocomplete for Dapper calls not working. And if they continued to ignore those and managed to keep going anyways, they would have clearly seen that the build failed, with tons of errors specifically about references to Dapper failing to resolve. An LLM keeps going on its merry way in ways that effectively 0 humans would.

what "sense of rigour"? it's way too soon to put those rose-tinted glasses on.

I don't think OP is claiming that prior to LLM coding everything in the software development world was super rigorous (I assume that's effectively what you mean with the "rose-tinted glasses" comment). But rigor was actually possible and in a deterministic way too, which is fundamentally impossible with LLMs. You can build all kinds of guardrails and processes around LLMs that make it somewhat approach rigor again, but it's still fundamentally based on a bunch of statistical probabilities instead of deterministic, repeatable results.

All of the methods I see to mitigate the fundamental and inherent issues of LLMs seem roughly equivalent to the kind of crap you see in astrology groups or palm reading etc. You need Venus and Mercury to be in alignment while Mars is retrograde if you want to be able to get the right results from your token predictor.

Then why did it take Anthropic over a year just to fix the flickering issue in one of their main products when they have internal access to the latest and greatest models?

I think we're going to see a big scramble to pick up the pieces in a few years when a bunch of vibe-slopped houses of cards come crashing down. I imagine it will be like the demand for COBOL developers but on a much more massive scale.

All else being equal, and assuming you are building the right thing, being able to deliver more correct lines of code is a good thing.

Why? If you can deliver the same thing in fewer correct lines of code wouldn't that be preferable? At a bare minimum if you're still insisting on using AI to slop out your project, having it do things in fewer lines of code means you can fit more into your LLM's context window.

The entire Linux kernel is about 40 million LoC, and only something like 16 million LoC after you remove drivers. I have a hard time imagining whatever OpenAI was talking about there having anywhere close to 6% as much utility as the Linux kernel, despite having 6% as many lines of code. And I have a hard time imagining it's anywhere close to maintainable, regardless of how powerful their LLMs might be.

If this works and passes all of the tests

Only if the existing tests were actually useful in what they tested and covered.

I'm not expecting them to know it ahead of time, I'm expecting them to understand it when it is explained to them.

Seeing as my Russian, Ukrainian, Belarusian, Mexican, French Canadian, and Brazilian coworkers don't seem to have these issues with me I don't think the issue is with my explanations.

What if I'm hiring someone specifically to work at a Spanish language news outlet?

Having actually worked at a Spanish language news outlet before (1 of 4 tv and radio stations in the office I was doing IT help desk work in), I can tell you that every single employee spoke English somewhere on the level of very good to near native fluency. As it turns out, knowing English (or the native language of whatever country you're in) is an incredible value-multiplier for almost every job position imaginable.

As far as language issues at my current job goes, it turns out once you hire a manager that speaks both Hindi and English (or Marathi and English, or Bengali and English, you get the picture) it doesn't matter much if the H1Bs he hires barely speak English because he can just start shouting at them in Hindi if they don't understand (even if several native English speakers are in the meeting too).

There are much simpler mechanisms to making that would make the enforcement mechanism more effective without destroying the economy, like prioritizing them by salary instead of randomly.

The Trump admin already did that too:

https://www.uscis.gov/newsroom/news-releases/dhs-changes-pro...

Rigorous examinations for English fluency and for competency in their alleged field of expertise would be a good start. I have several H1B coworkers in the US who barely speak intelligible English, and who barely understand normal conversation let alone anything technical. A blatant example of this that I experienced recently being that several of them could not understand that just because a method in C# is asynchronous does not mean it executes out of order.