PS5 Linux lead quits as open-source projects have become “a bunch of noobs using LLMs” that “they don’t even understand”

[u/Wargulf]

https://frvr.com/blog/news/ps5-linux-lead-quits-as-open-source-projects-have-become-a-bunch-of-noobs-using-llms-that-they-dont-even-understand/

[u/Veggies-are-okay]

TL;DR there is a skill gap with AI usage and it sucks that it’s both noobs to computer science AND AI that are ruining it for the rest of us. It’s supposed to replace your fingers, not your brain!

I mean yes do not one shot but there is a grey area here. I use LLMs to drill into specs and clarify all those things that you mention. Naming conventions is a trivial thing to build into the workflow. Give it a bulletproof list of jira-style tickets and an mcp server to GitHub and you can get a very solid and well-documented project.

My workflow got me my job. I had the best solution to their exercise (albeit admittedly not very difficult at all… optimizing a backend to make an ml model realistically scalable/deployable). Took an hour of chatting with Claude and boom off to the races. Took less than an hour to get the 10 PRs in and reviewed.

Now you may absolutely complain about having to extensively review code you did not manually write. I like to round-robin a few writing style based skills so that there’s some variety in syntax style. It’s pretty neat.. I’ve even gotten to the point where I request little grammar errors so I feel like it’s coming from a human 😅

I’m one of the minority that is more attracted to the high level meta of prompting self-checking systems and finding reusability there than the rote boilerplate coding. Watching a system play with jira tasks and have agents interacting is kind of magic. It’s like being the manager of little workers that listen to every directive like a monkey paw.

[u/bastiVS → u/Veggies-are-okay]

It actually is supposed to replace your brain. And its partially already there.

The "partially" however is the problem. Any AI can still spit out the most insane nonsense, so you still need to have an idea of what the AI was supposed to be doing to spot when it didn't do that.

Lots of people dont get that, but are trying to use AI to make a quick buck by flooding everything with shit apps that will never recieve any proper support.

[u/MCRN-Gyoza → u/Veggies-are-okay]

Honestly most of the problems people say they have with AI generated code just comes from not knowing how to use the AI.

It's hilarious that there are some people in this thread who think they are better at coding than LLMs while working their shitty job at a legacy non-tech company, meanwhile high level people in big tech and academia all admit they don't write code anymore because the model does a better job at that than they do.

It's the epitome of Dunning-Kruger.

The only thing better are the people who go on a pedantic tirade about how it's just autocomplete or not really intelligent. Who the fuck cares? I care that it makes my job 10x easier.

[u/fell_ware_1990 → u/Veggies-are-okay]

It’s not really a problem. I do use a lot of AI, but i can also explain what my code does, why it fails, what should be different.

I have a ‘new’ senior developer coworker, the first 2 months i gave him the benefit of the doubt, after that i knew he sucks. He can’t verbally explain the tiniest bit of code. Can’t do git, i ended up with PR’s which started with 5 commits go to 50 and the code went back and forth. Told him to sqaush, PR removed > recreated.

Just this week he managed to upload his whole AI workflow, even that really sucks…..50 skills, random orchestration agent, MCP’s all over the place. And then only about 10% even matched the file type, even less matched our preferences and such.

He was suddenly getting more done, so i checked his usage. Trough the roof, 30/35k agent starts, complete orchastration flows, 10 commits and only a i think 50 LO(c) cause half is still .md . So i didn’t bother, send out a deepseek with a harness. Basically all code was wrong, so i checked by hand and it was right.

[u/Veggies-are-okay → u/fell_ware_1990]

I think it’s important to learn when you’re veering into the realm of “vibing.” I was concerned about this until I 100% vibed out my first complex react app as a backend data science guy. That feeling of “this is cool but I can’t really say anything about it” is worlds different than imposter syndrome on rapid progress. I always tap into that feeling as a litmus of slowing down/taking a break from computer work. Glaze-y eyes means finish up the task and go touch grass.

[u/fell_ware_1990 → u/Veggies-are-okay]

Yeah, well i’m a DevOps guy. So i manage complex infra, kubernetes, openshift, iac and a lot more.

99% is done in code. So i also use AI a whole lot, for all kinds of different stuff. But i won’t let it build or touch a very important module with my git keys wide open ( as he does ).

I have a complete system around it, red build? It notifies my system, it starts collecting the logs, identical pipelines, checking knowledge RAG, tickets, creates a new ticket with all the information. Hit’s up an other agent picked by the ticket subject ( one of the many specialized agents ) > Creates an isolated space, gets a few specific tools, cant commit. For most part’s of the repositories there are guidelines, rules, hooks, linters ( partially custom made so it handles it how i want ) .

The end result could be 2 things, i get code delivered i can review or i at least get a suggestion what’s happening or that it is a big change that needs planning.

Worst comes to worst i at least have a very up to date ticket complete with everything i need. Best case, the code’s good. I approve, it already created a commit + PR message, tooling tracks PR down to a green build in PRD.

So i am really pro AI, it saves me a lot of time. But dumping a few skills in, burn tokens, dont know what you create….yeah well….