How do you generate your charts? They're very nice

Useful read. One thing I add for engineers at any level: ladders describe scope, but promotions are mostly evidence. Keep a short win log every month so you have real examples when it matters.

I sometimes wonder if some folks who hate AI use it poorly to show that it "fails half the time".

The AI has access to roughly the same resources as you - if you can't find docs or anything then it doesn't either. So yeah - for incompletely documented APIs it will perform poorly. It isn't magic (despite some marketing claims)...

But if you don't want to spend 20 mins digging through AWS's API docs to figure out how to list all EC2 instances and their volume mounts to tally disk usage or something it will produce workable code very quickly.

This matches my experience when I've used midsize models connected to read-only tools.

It does not match my experience using a big model in an environment where it can generate and execute code when given instructions to base its answer on that. That pattern almost always results in a factual answer, and often, but not always a good one. The downside is you need to set up such an environment or pay a provider for one, and it's slow. If you have something else to do while you wait, it may improve your efficiency. If you don't, you might as well do the experiment yourself.

Sadly I'm noticing this.

I imagined that, since this is a federated group, people would be more interested in discussing, or at least reading each other's essay. But looks like I was wrong.

"I can see my code from 3 years ago, was already slop!"

• Myself

Funny how often I can see that people haven't read a single phrase in the post. And are probably just going by the headings and title.

Honestly fuck capitalism for taking us down this road.

Capitalism has nothing to do with this. It's corruption, incompetent politicians, and a lazy populace who would rather bitch online than go out and vote (something I'm definitely guilty of, but am actively working to change)

The direction things are going are to concentrate wealth and power into the hands of a very small group of assholes. There is no economic or political system that can fix the problems those assholes have been exploiting to pull this off. The only thing that can prevent that is an informed and energized population of voters.

Like, we all want to see Trump, Musk, Zuckerberg, etc in prison. It feels like they're untouchable, but literally all it would take to do that is to spend a few minutes filling out a ballot to get rid of the career politicians who have been in office too long (and thus are more likely to be corrupt). Even local elections matter.

“NoT eVeYtHiNg Ai Is SlOp”

Did you fully read the blog post? Because your critic is somewhat far from the discussion on the post.

“will you still think I’m cool if I use AI???”

That's is not the case, and if you read the post I'll strongly discuss about the usage and quality and how heavy usage decrease quality.

I see you're deep into AI psychosis, so you're brain isn't working at its full capacity.

Slop means “high volume, low effort garbage,”

and

Slop is a measure of quantity (and to a certain extent, effort), not of quality

Are saying the same thing. Your last paragraph is also incoherent, so I won't even go into that.

Turn off the AI waifu. It isn't real.

Most of Lemmy is not interested in nuance.

This has been my observation outside “AI,” on any other topic. TBH I think you are wasting your breath.

The answer to that question is Tech Bros.

Altman, Modi, Musk; those are the people that benefit from the binary view, because they are quite intentionally turning it into a “it’s us or nothing” wedge issue.

I disagree strongly.

Slop means “high volume, low effort garbage,” and it was a term even before LLM/diffusion proliferated.

“Anything AI generated is slop” was not the original definition, and it cannot be applied consistently. You’re probably on a computer filled with “slop” right now, if that’s your definition. You’re using it in nearly every website you visit regularly, you were touching it in media well before Stable Diffusion or ChatGPT were even out.

This is tiring. Any AI generated thing is slop. Slop is a measure of quantity (and to a certain extent, effort), not of quality. Why? Because quality is subjective, and thus a useless point of comparison. You might think those AI generated studio ghibli rip offs are ugly/disgusting, but my mom thinks they're "cute".

So stop with this tiring "NoT eVeYtHiNg Ai Is SlOp" cope. The question people like this really want to ask is "will you still think I'm cool if I use AI???", and that's also subjective, and thus pointless. I personally will never think anyone who uses generative AI is cool, especially when they reveal how pathetically desperate for approval they are by making posts like this.

[...] avoid having humans do any of that work [...]

You are stepping to close to the S word, the only word that makes the capitalism fear. So are you sure that you want to pull this topic on this community?

It's also good for generating boilerplate, one-use scripts where maintainability doesn't count, suggesting solutions, parsing log files, writing test cases (especially if you have templates)...

Funny that I'm seeing negative view on this post, and it's also closer to what I've found in the wild. Often (in special outside of the web/rest api world), the LLM fails far more often, like at least 3 in 10 is pure garbage, while the other 7 is maybe correct, but still needs refactor to be in the shape to use in the codebases that I've.

[...] latest models are capable of non-slop code and tolerable prose [...]

We may disagree on this. It can help, but "good" quality you are stretching the point. I would argue that if you stay in the comments section only, any LLM generated text is "good quality", but when you look for good writers, and gets familiar with quality essay, LLM isn't even close to "good".

[...] Anthropic has a slight edge on code quality [...]

As a engineer with some years in my back (enough to have back pain when wake up, if you catch my drift)... The quality level of code is "bad" to "ok-ish"... But far from "good". When you work in good codebases you can see what an good abstraction is. But the LLM can only produce "ok-ish" at best, and this won't save the industry.

If this code generation were "good", we should be surfing in new features for every single product, instead we have more bugs. So I ask the question, did it have a productivity boost?

And I get back to my original question on the post, "Who benefits from this binary view on the topic?"

Had a similar experience with a question about google's googleads python lib. It told me how to do it, didn't work and it turns out it was impossible todo because of how it is structured so it just wasted 2-3 days of work.

Windows 11 is getting reverse engineered. Hilarious.

I tested REA with Qwen 3.8 27B with a narrow solver capability from some commercial 3d software and it was quick to extract 20,000 lines of Ghidra C-like pseudocode, but painfully slow to turn it into actual C++. It struggled interpreting all the matrix math and making something that actually worked. I stopped after a couple days of it churning, figuring it could spend a couple weeks and end up with worthless slop. I’m a software engineer and don’t have a background in RE, so maybe someone with more experience would do better.

The opinion I'm starting to settle on is that expecting people to read LLM output is rude.

That means at the point something is released for public consumption, the documentation should be human-written. At the point an open source project solicits collaborators, the code should at least be human-reviewed and probably human-refactored. I've read enough LLM-generated code to know it isn't very good at picking abstractions.

There are, of course business school types in industry who want to avoid having humans do any of that work because it's expensive. This leads to the same kind of problems any other decision to reduce quality to save money does.

• https://de.wikipedia.org/wiki/Artcraft
• https://getartcraft.com/
• https://github.com/storytold
• https://en.wikipedia.org/wiki/Clean-room_design

And plenty coverage from all the tech news outlets, Reddit etc.

De-obfuscation is probably one of the few ok uses for a ethically trained LLM

That won't be a sustainable option for most software, as they need to work offline, plus a majority of customers still live in areas where reliable high bandwidth internet (a requirement for streaming software at any usable rate) isn't really available.

The latest models are capable of non-slop code and tolerable prose (OpenAI is much better than Anthropic on the prose but I think Anthropic has a slight edge on code quality). It's really just pre-Astra models that are super sloppy. Annoyingly you get what you pay for.

Also the benchmarks don't really seem to capture this at all. I guess it is difficult to have a benchmark for code quality or writing style.