Yeah sloppers I know went from “see it proved new math! that totally clears us of plagiarism accusations we get when we repost that someone ai generated a frogger and a WoW clone” to “tried to use it for coding and it didn’t do a good job”.

The math stuff is mostly using Lean proof verifier and all that, by the way, the only use of LLM that they found that is actually legit because it doesn’t matter if its slopping, and you want your attempts randomized.

Anyone who would have tried the kind of bullshit he’s trying, a century ago, would have died of radium poisoning or something equally dreadful. The only reason this idiot is still alive is regulations; however he’s pretty good at risk compensating greater safety of quack treatments in 21th century with the sheer number of quack treatments he’s doing.

I’m going to prognosticate that he’ll die through some combination of the sheer brute force effort he’s putting into finding a lethal quack treatment, and the weakening of regulations and corresponding societal norms relating to quack treatments.

Fucking knew it. I follow some idiot slopper thread and they are all always going on about their prompting and absolutely none of them ever even considered measuring the effects.

Having actually done optimizations including professionally once upon a time, its so ridiculous to see people thinking they optimize a stochastic process [when they don’t even formally measure anything]. It is just gambling.

In addition to shoving absolute piece of shit “products” into everything. Prompt injectable “assistants”, worthless search overviews, shoveled out without any QA or security reviews or anything.

Take those doctor transcriotionists that make up whole sentences. Why in the fuck is there even an LLM in there? Oh it lowers word error rate? That’s because nobody expected having to benchmark bad faith efforts where coherent sentences can be completely made up, so nobody thought it necessary to disqualify for it.

They are still trying to prompt inject the robot god into turning us all into paperclips, I see.

There’s a slopper at the other end of it who believes that asking AI to find the best place to buy bitcoin is something that AIs are good at. Or perhaps asking AI to summarize the article and getting a penis enlargement ad as a summary.

“But I thought chatbots were great at security! They hacked huggingface and also fable will fix all security bugs in firefox”.

I think even if development at an instant is some % faster to start with, it writes the same functionality in more lines of code which will rapidly lead to a cumulative slowdown.

Imagine you are traveling the oregon trail in a wagon and a devil offers you an extra horse but all of its manure has to go into the wagon. Initial speed up followed by a cumulative slowdown. If you keep accepting devil’s deals as your wagon keeps slowing down to a crawl, the progression is governed by a horseshit version of Tsiolkovsky’s equation.

Well, the big issue is that there’s only this much demand. How many web browsers is there genuine end user demand for, worldwide? Probably just 1. Several are made thanks to other demands by large corporations. How much value does a web browser provide, to billions of people who use it? What ever the number may be, it’s orders of magnitude more than it costs to develop.

Why is software observably hard for companies? When 90% of people are working on projects that are going nowhere, that creates a situation where competence is quite rare. Because in most projects it is objectively unnecessary (would make no difference). Where majority of software engineers never seen a successful project all the way from the start to the finish line.

Then there’s startups, these are (predominantly) mere vehicles for moving money from the coffers of large publicly traded corporations into pockets of VCs (who sell startups to said corporations). Whole world of pretend software engineering.

Then there’s large corporations, where CEOs want to get paid more and to be able to get paid more they need to add more layers to the hierarchy underneath them, which they need to fill somehow, and they can’t fill on merit because they just don’t have enough stuff happening that they could measure merit in.

edit: basically the management always wants to do the equivalent of having hired a dozen heart surgeons to work on one heart and a “heart surgery architect” as well, the more layers the better because the more layers the higher is the pay their layer can get.

As a software engineer, all of the free portion of the article is 100% correct about software engineering dysfunction.

There’s another reason why it is that way, though. A software engineer who is competent and productive and working under competent leadership making an useful product, would make a very large multiple of their salary in profits.

That permits all sorts of utter dysfunction while still breaking even on the average. You can have incompetent leadership in 90% of projects, you can saddle your developers with any kind of bad practices, you can impose all sorts of productivity damaging nonsense and yet still break even.

The dysfunction can be presented as relentless innovation and pursuit of new, uncertain opportunities, as a shrewd strategy.

If you fall below break-even, the consequences will not be visible for many years. And up until it becomes impossible to recover, on the technical level it is extremely cheap to recover: it’s easier to do nothing than to convert your OS’s start menu to React. Tech companies don’t fail because of tech.

This also relates to using AI to write code. You already can have a human write your code and pay them $1 for $10 you would make from it - or $0 you would make if you fucked up. You want it to become $0.5 with AI coding tools? Then you’re multiplying your probability of success by what’s left after the probability that you get some unmaintainable slop . It’s simply not worth it.

Into a black hole.

Who needs cures when you can instead simply replace doctors with chatbots?

Yeah I have to admit I don’t have the energy to gaze into that particular idiotic abyss. How do they even write that kind of fiction, in a world where AI companies routinely use critihype to obtain more investments? The least unhinged CEO: “we caught our AI trying to start a nuclear war, it’s almost skynet, please give us another trillion dollars”, the least unhinged investors: “shut up and take our money”.

I thought it was 2027. What, the timelines slip or something?

Yeah… I think the core point is, LLM’s shit is generated artifacts, which need to be kept separate from sources. That you can’t actually re-generate the same artifacts, is just a dingleberry on top of the shit pile.

Perfect for when your workplace will fire you if you dont use enough tokens, I’m sure.

I think there’s something to the compilers analogy, in the sense that if you used a C compiler through a chat interface with one liners to insert snippets into assembly without keeping the source code in source files as such, it would probably be slower than just writing in assembly yourself.

That LLMs have a number of extremely undesirable properties as “compilers” (from nondeterminism to plagiarism) does not make the dumb ass chat interface any less fundamentally shit. It just makes them shit in other ways too.

I just love how they are adding the absolutely fucking most stupid exploits ever to everything, and then trying to whitewash it with all that bs about Fable or whatever the fuck.

There could be but it would be difficult to implement - something a bit like putting together a shredded paper, heh.

It’s a perfect example of how “using LLMs for test coverage” can also be harmful. He expected the tests to to prevent introduction of said regressions, probably based on a combination of the quantity of tests and their style (they look like what decent human written tests look like). But the tests are AI slop, and so they give a lot less value per line of code than he expects, hence a significant regression.

It is literally useful to call these tests AI slop, and the problem is in part caused by not calling them AI slop, and having consequent inflated expectations. LLMs are not any better at writing tests than at writing other code! It is merely that the bar for tests can, legitimately, be a lot lower (in projects where there would otherwise be no tests at all). Making an exception to calling AI generated tests “slop” is thus counter productive, because it leads people to act as if LLMs are actually better at writing tests than at writing other code, and not just because the bar for tests is frequently very low.

edit: actually scratch that I looked at the PR and those tests even look like dogshit and worse than the tests I seen claude write at a workplace that was into vibecoding (which i since quit).