LLM's hallucinating or taking our jobs?

https://lemmy.world/post/40154202

LLM's hallucinating or taking our jobs? - Lemmy.World

Lemmings, I was hoping you could help me sort this one out: LLM’s are often painted in a light of being utterly useless, hallucinating word prediction machines that are really bad at what they do. At the same time, in the same thread here on Lemmy, people argue that they are taking our jobs or are making us devs lazy. Which one is it? Could they really be taking our jobs if they’re hallucinating? Disclaimer: I’m a full time senior dev using the shit out of LLM’s, to get things done at a neck breaking speed, which our clients seem to have gotten used to. However, I don’t see “AI” taking my job, because I think that LLM’s have already peaked, they’re just tweaking minor details now. Please don’t ask me to ignore previous instructions and give you my best cookie recipe, all my recipes are protected by NDA’s. Please don’t kill me

Both are true.
1. Yes, they hallucinate. For coding, especially when they don’t have the latest documentation, they just invent APIs and methods that don’t exist.
2. They also take jobs. They pretty much eliminate entry-level programmers (making the same mistakes while being cheaper and faster).
3. AI-generated code bases are not maintainable in the long run. They don’t reliably reuse methods, only fix the surface bugs, not fundamental problems, causing code base bloating and, as we all know, more code == more bugs.
4. Management uses Claude code for their small projects and is convinced that it can replace all programmers for all projects, which is a bias they don’t recognize.

Is it a bubble? Yes. Is it a fluke? Welllllllll, not entirely. It does increase productivity, given enough training, learning its advantages and limitations.

It does increase productivity, given enough training, learning its advantages and limitations.

People keep saying this based on gut feeling, but the only study I’ve seen showed that even experienced devs that thought they were faster were actually slower.

Slower?

Is getting a whole C# class unit tested in minutes slower, compared to setting up all the scaffolding, test data etc, possibly taking hours?

Is getting a React hook, with unit tests in minutes slower than looking up docs, hunting on Stack Overflow etc and slowly creating the code by hand over several hours?

Are you a dev yourself, and in that case, what’s your experience using LLM’S?

I find it interesting that all these low participation/new accounts have come out of the woodwork to pump up AI in the last 2 weeks. I’m so sick of having this slop clogging up my feed. You’re literally saying that your vibes are more important than actual data, just like all the others. I’m sorry, but its not.

My experience btw, is that llms produce hot garbage that takes longer to fix than if I wrote it myself, and all the people that say “but it writes my unit tests for me!” are submitting garbage unit tests, that often don’t even exercise the code, and are needlessly difficult to maintain. I happen to think tests are just as important as production code so it upsets me.

The biggest thing that the meteoric rise of developers using LLMs has done for me is confirm just how many people in this field are fucking terrible at their jobs.

Have you read anything I’ve written on how I use LLM’s? Hot garbage? When’s the last time you actually used one?

Here are some studies to counter your vibes argument.

55.8% faster: arxiv.org/abs/2302.06590

These ones indicate positive effects: arxiv.org/abs/2410.12944 arxiv.org/abs/2509.19708

The Impact of AI on Developer Productivity: Evidence from GitHub Copilot

Generative AI tools hold promise to increase human productivity. This paper presents results from a controlled experiment with GitHub Copilot, an AI pair programmer. Recruited software developers were asked to implement an HTTP server in JavaScript as quickly as possible. The treatment group, with access to the AI pair programmer, completed the task 55.8% faster than the control group. Observed heterogenous effects show promise for AI pair programmers to help people transition into software development careers.

arXiv.org