You gotta use AI like it's a new guy you're training at work where every single thing you tell them to do they'll probably do wrong but you have to pay attention and learn their specific fucked up brain so you can anticipate their path of fuck up
technology
On the road to fully automated luxury gay space communism.
Spreading Linux propaganda since 2020
- Ways to run Microsoft/Adobe and more on Linux
- The Ultimate FOSS Guide For Android
- Great libre software on Windows
- Hey you, the lib still using Chrome. Read this post!
Rules:
- 1. Obviously abide by the sitewide code of conduct. Bigotry will be met with an immediate ban
- 2. This community is about technology. Offtopic is permitted as long as it is kept in the comment sections
- 3. Although this is not /c/libre, FOSS related posting is tolerated, and even welcome in the case of effort posts
- 4. We believe technology should be liberating. As such, avoid promoting proprietary and/or bourgeois technology
- 5. Explanatory posts to correct the potential mistakes a comrade made in a post of their own are allowed, as long as they remain respectful
- 6. No crypto (Bitcoin, NFT, etc.) speculation, unless it is purely informative and not too cringe
- 7. Absolutely no tech bro shit. If you have a good opinion of Silicon Valley billionaires please manifest yourself so we can ban you.
Only little bits and pieces for projects I have so many backups I'd laugh if the LLM fucked it up, noticed they're heavily trained on python but near nothing on pascal. I use glm (deepseek, kimi etc) mostly for coding, I get banned just looking at chatgpt. I've abandoned google like a one way time capsule to 1997.
have you considered that computers are very clever and maybe deleting sys32.dll would work
I'm using AI for the first time to make simple numbered lists with names. The lists vary from 100 to several hundred entries.
I have to repeatedly ask chatgpt to double and triple check its work and then end up manually counting, editing and doing a lot of the work anyways. Frustrating
why are you doing that?
Anything that is even remotely a novel problem AI can't solve. It doesn't have the training data for your specific problem. At best it'll do a web crawl for you and summarize its findings.
If you want to really pull your hair out take a look at AGENTS.md or SKILLS.md. State of the art agentic coding practices: glorified README.md files. (the ai frequently doesn't bother to read them).
I will say one thing nice about LLMs: they are fairly "human" in the sense that they error in familiar ways. In a way AI is automated human error.
I've used it to create some simple scripts to do some tedious shit that I didn't feel like coding myself but nothing serious or professional. For example:
"Here is a big file that has a bunch of data in it but I only need points X,Y,Z, formatted in a JSON which I have provided an example of. Write me a simple python script to do that."
Works okay for that stuff. Always desk check it with edge cases.
They do. Most programmers think they're above average (there were actual statistics on this, maybe from stackoverflow survey) and are mediocre enough that they find it useful/faster long term.
I'm statistically likely to be mediocre myself, but I would rather try to improve than relying on LLMs. Every single coworker I work with who is actually above average hates the forced AI usage.
hmmm maybe user error. deepseek is really useful in helping with troubleshooting and linux stuff
One of the only positive things I can say about AI is that it's helped me troubleshoot computer and technology issues. That's basically all I use it for anyone.
It can help with tedious but relatively non complex work or maybe speed up some exploratory work, anything else and it's going to make ridiculous mistakes. It's a useful tool occasionally but nothing I'd lose sleep over if it disappeared.
I'm absolutely baffled by it as someone who started their college career in computer science before switching majors. I was never the best programmer, yet it seems so ass-backwards to me modern programmers aren't writing pseudo-code and working things out on paper. I wasn't in school that long ago. Did things really change that fast? Are people not doing formal logic anymore? Do they even learn binary and hex? Just what the fuck is happening to this field.
My impression is that the people who are most excited about these tools are people like tech journalists and "solopreneurs" (gag), who have been tech adjacent but never formally learned to code and now think that they don't need software engineers to achieve their vision anymore.
this. llm code is the silver bullet for "idea guys"
I'm imagining a comedy with this dialog...
"Am I a programmer? A lowly programmer? Of course not! I'm an ideas guy." As the plot unfolds - it turns out the guy has no idea how to do anything. All he does is enter AI prompts and then lie that he has yet another fantastic idea.
I was self-taught programming before I started my college career similarly (also switched majors except I dropped out) and I don't usually do pseudo-code. I guess I kinda do in my head or write out a plan for how it should work. I also don't usually do very big projects either. I've tried OS dev, but I have a hard time expanding beyond the tutorials on the wiki and keeping things organized and actually working. Mostly now I just write. (switched majors to literary studies)
I was never the best programmer, yet it seems so ass-backwards to me modern programmers aren't writing pseudo-code and working things out on paper
Not a programmer, but as someone whose master's degree is filled with "write 30 pages worth of documentation before starting a project" when you are actually working in the real world, half that shit goes out of the window. So, I can definitely see how a lot of people are not writing pseudocode and instead brute forcing a bunch of things.
The free models are much worse than the $500 per user/month enterprise ones. I have seen these be able to generate working features first hand at work, and I cannot deny that certain models are capable of implementing features when appropriate requirements are provided. To claim anything else would be to deny what I have seen with my own eyes.
However, therein lies the trap. Just because it is capable of achieving the provided task in one instance, doesn't mean that it always provides an appropriate answer or solution in all cases.
But those who have initially used it successfully tend to start believing its output uncritically. I've noticed this on myself when I tried it at work, and I think this is basic human, heck, even animal condition. You are naturally inclined to trust an entity that initially provides you with beneficial output. You become less critical, as the output often sounds informed and convincing, and in many cases provably works as well (especially when a robust testing framework exists inside the project. its only through unit and integration tests that these AIs can even reliably implement features).
But this leads to an increasing reliance on the tech, and you stop being capable of arguing why the solution it generated works. You have to put in active effort to question what it's doing, and you have no way of knowing whether it's telling you the truth or lies, because it has no motive, and researching the facts can take so long that it completely defeats the point of automation. So it ends up being rather self-defeating in many cases, and can leave you less capable of solving problems yourself.
I think the most useful application for it personally is to use it for debugging -- feed it a cryptic error message, and it will usually generate an answer that, while not necessarily accurate, can give you more pointers to find the true answer, much better than most search engines can.
I mean deepseek will make you working programs for 20 cents of tokens sometimes if the requirements are straightforward and it's nothing too exotic.
It's probably related to the reason why your Start button took a vacation lol

The thing is, our entire field is bad at what we do. For most of the software the cost of error is very low, and for a long time it was a very lucrative field that attracted a lot of people who were really bad at coding. So coding with AI is not significantly different from coding without AI, it’s just that there’s now a much faster, and much less ethically acceptable way of producing code.
50% of developers have less than 5 years of experience and the number of new developers just keeps growing too. We’re a profession of amateurs with companies poaching the oldheads out from underneath each other.
With coding it's easier to deceive yourself that the AI is doing a good job. There are tons of tools out there that can detect various kinds of problems in code and the AI can call those tools and change stuff until the warnings go away. So the code might look alright on first glance. Then half the time people don't even understand the code they wrote themselves so they just look at changes across 50 different files and be like: fuck it, how much do I really care if this company goes up in flames?
i said this before but it's very good at making you feel like you're accomplishing something, but you will inevitably hit a wall with any ai project where it just can't meaningfully contribute anymore. you can work around this issue to an extent by getting really good at you know like project management and splitting your thing up into smaller and smaller chunks but eventually you'll then cross the second wall which is where you're putting in way more effort prompting the AI than you would have spent just doing it yourself
I found that in coding same as with creative writing the best use for the AI is as a parrot because you know if you're hitting writer's block or if you're trying to flesh out an idea all you need is something to like kind of spit your own words back at you to kind of help you shake yourself out of that so using an AI as like a sounding board for your ideas I think is somewhat valuable use or using it as a search engine but even the search engine use is only there because search engines have gotten so shitty
I have a very close friend who is an engineer for programming(idk what the title is rn) at a very large company.
He says he has managed to keep one or two codebases "AI free" but when I asked if he has to review any AI code he said it's completely unavoidable and everyone uses it now. He's proud of the fact that they still require the coder to actually review the AI generated slop before passing it off to him.
It's bleak
This, except in my case there's no reviewer, I either review or do the rest of my work. Someone in my team is really a broker with the AI and he has such a bad grasp on the core of our codebase that I've had to spend several days refactoring the AI's vomit just to get something mildly performant (it's graphics-related code). It's clear when making new things that he just doesn't plan for the future and every new piece of code is just a hack to deliver the feature, instead of discussing the code with the others at least. Worst part is that there is seemingly no end to this
yes, people are writing code with AI. I use claude code and it has built a couple of things for me. But they are nowhere near production level.
The AI is right. Just delete that shit and install freeBSD.
for what it's worth i'd rather program a filesystem from scratch than troubleshoot someone's cursed computer and the janky setup they need to barely run a video game but that's besides the point, AI is abysmal dogshit, yes
Last time I used it, for some fluids problem, it couldn’t even do simple calculations correctly. It the final number was off by two significant digits lol
For the love of god never ask an LLM to do math. That's the exact opposite of their function.
This is such a key point you make—quality of search results and available info to use to solve a problem have degraded so far that you almost have to rely on web search enables AI to do what you used to be able to do on your own, and in both cases now you have to engage a lot of extra effort in trying to discern if the information is at all useful.
And like you say, the situation will only recursively get worse as the two feed on each other further destroying informational value.
People are going to learn about Socialism from these tools. Having websites with easily laid out information debunking the common talking points is more important than ever.
Very much this - I used to rely a lot in tutorials, devlogs etc to learn new patterns etc, but now search is so bad that LLMs are basically the only game in town
If it's not new tech (never use new libs) just add "before:2022" or such to the search
We use AI at my coding job and our codebase has a lot of safeguards to make sure the AI isn’t spitting out garbage. Every time it makes a commit, it runs the linter, the static analysis tool, and the unit test suite which is pretty extensive. Every time it makes a mistake in spite of these things being present, we update our agents file until it can consistently get that thing right (this is sometimes limited by the overall capabilities of the model).
In other words, it has a good set of default instructions that tells it what we expect of it, we all share tips on how to prompt it in ways it will respond well to, and when it inevitably slops out some shit anyway, it has a lot of automatic tooling to tell it to fuck off instead of us having to review every intermediate step. We also have a requirement of signing off that you’ve read and understand the code it writes before opening a PR. It’s not perfect but it’s a lot more reliable than a naked chat bot
My coworkers range from "Claude can find errors in my code" to "Yeah I just copy-paste everything from chatgpt". Those like the former at least can still submit legible code (for now). Those like the latter submit random gibberish and have no idea how it works.
Those like the latter submit random gibberish and have no idea how it works.
That's ok because neither do they!
Its fine for boilerplate simple programs. However, it will often make mistakes even for those, so you have to know what you are looking at. Still saves time, though idk if the actual energy usage etc., is actually saving you time and money without free money existing.
However, I have seen people write big programs with it and then be surprised that they don't work. Even more worrying though is when they do work, but then I walk through whoever wrote it and they cannot explain how or why it is working.
Its real engineering logic.
It's not that different than using Stack for parts or boilerplate code (since AI probably just stole from that anyways). So you still need to know what's going on unless you literally just keep throwing prompts at every error for 3 hours until it magically works.
I use AI mostly to troubleshoot all of the vague errors that come out of python or SQL, not to write my entire code. It's a [relatively shitty] tool, not an 'I Win' button that everybody claims it is.
Similarly, I like having it summarize search results and I can click into the actual relevant links. But yea it's pretty garbage most of the time. I'm definitely on team 'fuck ai'; I lived without it before, I can live without it again
