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I refuse to believe this post isn’t satire, because holy shit.
They’re so close to actual understanding of how much they suck.
I’m not a programmer by any stretch but what LLM’s have been great for is getting my homelab set up. I’ve even done some custom UI stuff for work that talks to open source backend things we run. I think I’ve actually learned a fair bit from the experience and if I had to start over I’d be able to do way way more on my own than I was able to when I first started. It’s not perfect and as others have mentioned I have broken things and had to start projects completely from scratch but the second time through I knew where pitfalls were and I’m getting better at knowing what to ask for and telling it what to avoid.
I’m not a programmer but I’m not trying to ship anything either. In general I’m a pretty anti-AI guy but for the non-initiated that want to get started with a homelab I’d say its damn near instrumental in a quick turnaround and a fairly decent educational tool.
This is the correct way to do it, use it, see if it works for you and try to understand what happened. It’s not that different from using examples or stack overflow. With time you get better, but you need to have that last critical thinking step. Otherwise you will never learn and will just copy paste hoping it works
As a programmer I’ve found it infinitely times more useful for troubleshooting and setting up things than for programming. When my Arch Linux nukes itself again I know I’ll use an LLM, when I find a random old device or game at the thrift store and want to get it to work I’ll use an LLM, etc. For programming I only use the IntelliJ line completion models since they’re smart enough to see patterns for the dumb busywork, but don’t try to outsmart me most of the time which would only cost more time.
lol it did save me from my first
rm -rf /
As a software developer, I’ve found some free LLMs to provide productivity boosts. It is a fairly hairpulling experience to not try too hard to get a bad LLM to correct itself, and learning to switch quickly from bad LLMs is a key skill in using them. A good model is still one that you can fix their broken code, and ask them to understand why what you provided them fixes it. They need a long context window to not repeat their mistakes. Qwen 3 is very good at this. Open source also means a future of customizing to domain, ie. language specific, optimizations, and privacy trust/unlimited use with enough local RAM, with some confidence that AI is working for you rather than data collecting for others. Claude Sonnet 4 is stronger, but limited free access.
The permanent side of high market cap US AI industry is that it will always be a vector for NSA/fascism empire supremacy, and Skynet goal, in addition to potentially stealing your input/output streams. The future for users who need to opt out of these threats, is local inference, and open source that can be customized to domains important to users/organizations. Open models are already at close parity, IMO from my investigations, and, relatively low hanging fruit, customization a certain path to exceeding parity for most applications.
No LLM can be trusted to allow you do to something you have no expertise in. This state will remain an optimistic future for longer than you hope.
I think the key to good LLM usage is a light touch. Let the LLM know what you want, maybe refine it if you see where the result went wrong. But if you find yourself deep in conversation trying to explain to the LLM why it’s not getting your idea, you’re going to wind up with a bad product. Just abandon it and try to do the thing yourself or get someone who knows what you want.
They get confused easily, and despite what is being pitched, they don’t really learn very well. So if they get something wrong the first time they aren’t going to figure it out after another hour or two.
In my experience, they’re better at poking holes in code than writing it, whether that’s green or brownfield.
I’ve tried to get it to make sections of changes for me, and it feels very productive, but when I time myself I find I spend probably more time correcting the LLM’s work than if I’d just written it myself.
But if you ask it to judge a refactor, then you might actually get one or two good points. You just have to really be careful to double check its assertions if you’re unfamiliar with anything, because it will lead you to some real boners if you just follow it blindly.
At work we’ve got coderabbit set up on our github and it has found bugs that I wrote. Sometimes the thing drives me insane with pointless comments, but just today found a spot that would have been a big bug in prod in like 3 months.
But if you find yourself deep in conversation trying to explain to the LLM why it’s not getting your idea, you’re going to wind up with a bad product.
Yes. Kind of. It takes ( a couple of days) experience with LLMs to know that failing to understand your corrections means immediate delete and try another LLM. The only OpenAI llm I tried was their 120g open source release. It insisted that it was correct in its stupidity. That’s worse than LLMs that forget the corrections from 3 prompts ago, though I also learned that is also grounds for delete over any hope for their usefulness.
It is not useless. You should absolutely continue to vibes code. Don’t let a professional get involved at the ground floor. Don’t inhouse a professional staff.
Please continue paying me $200/hr for months on end debugging your Baby’s First Web App tier coding project long after anyone else can salvage it.
And don’t forget to tell your investors how smart you are by Vibes Coding! That’s the most important part. Secure! That! Series! B! Go public! Get yourself a billion dollar valuation on these projects!
Keep me in the good wine and the nice car! I love vibes coding.
Kinda hard to find jobs right now in the midst of all this but looking forward to the absolutely inevitable decade long cleanup.
Also, don’t waste money on doctor visits. Let Bing diagnose your problems for pennies on the dollar. Be smart! Don’t let some doctor tell you what to do.
IANAL so: /s
Not me, I’d rather work on a clean code base without any slop, even if it pays a little less. QoL > TC
I’m not above slinging a little spaghetti if it pays the bills.
I’m sure it’s fun to see a series of text prompts turn into an app, but if you don’t understand the code and can’t fix it when it doesn’t work without starting over, you’re going to have a bad time. Sure, it takes time and effort to learn to program, but it pays off in the end.
Yeah, mostly agreed. In my experience so far, an experienced dev that’s really putting time into their setup can greatly accelerate their output with these tools, while an inexperienced dev will end up taking way longer (and they’ll understand less) than it would have if they worked normally
Clearly satire
I agree, the terminology used gives it away.
It’s kind of hard for me to tell on this one. Maybe the boomer lead is seeping into my brain.
Nah, it’s the microplastics.
Why not both ™?
With a pinch of PFAS for good measure?
Microplastics are stored in the balls.
So there are multiple people in this thread who state their job is to unfuck what the LLMs are doing. I have a family member who graduated in CS a year ago and is having a hell of a time finding work, how would he go about getting one of these “clean up after the model” jobs?
I’ve been an engineer for over a decade and am now having a hard time finding work because of this LLM situation so I can’t imagine how a fresh graduate must feel.
Has he tried being a senior developer? He should really try being a senior developer.
He needs at least a decade of industry experience. That helps me find jobs.
It would be nice if software development were a real profession and people could get that experience properly.
It was. Wall St is destroying it, along with everything else in its insatiable drive for more profit. Everything must be sacrificed to the golden idol.
It makes me so mad that there are CS grads who can’t find work at the same time as companies are exploiting the H1B process saying “there aren’t enough applicants”. When are these companies going to be held accountable?
Never, they donate to get the politicians reelected.
This is in no way new. 20 years ago I used to refer to some job postings as H1Bait because they’d have requirements that were physically impossible (like having 5 years experience with a piece of software <2 years old) specifically so they could claim they couldn’t find anyone qualified (because anyone claiming to be qualified was definitely lying) to justify an H1B for which they would be suddenly way less thorough about checking qualifications.
It’s so much worse than it was. AIs have absolutely murdered entry-level positions
Yeah companies have always been abusing H1B, but it seems like only recently is it so hard for CS grads to find jobs. I didn’t have much trouble in 2010 and it was easy to hop jobs for me the last 10 years.
Now, not so much.
After they fill up on H1B workers and find out that only 1/10 is a good investment.
H1B development work has been a thing for decades, but there’s a reason why there are still high-paying development jobs in the US.
No idea, but I am not sure your family member is qualified. I would estimate that a coding LLM can code as well as a fresh CS grad. The big advantage that fresh grads have is that after you give them a piece of advice once or twice, they stop making that same mistake.
Where is this coming from? I don’t think an LLM can code at the level of a recent cs grad unless it’s piloted by a cs grad.
Maybe you’ve had much better luck than me, but coding LLMs seem largely useless without prior coding knowledge.
What’s this based on? Have you met a fresh CS graduate and compared them to an LLM? Does it not vary person to person? Or fuck it, LLM to LLM? Calling them not qualified seems harsh when it’s based on sod all.
The difficult part is going to be that new engineers are not generally who people think about to unfuck code. Even before the LLMs junior engineers are generally the people that fuck things up.
It’s through fucking lots of stuff up and unfucking that stuff up and learning how not to fuck things up in the first place that you go from being a junior engineer to a more senior engineer. Until you land in a lofty position like staff engineer and your job is mostly to listen to how people want to fuck everything up and go “maybe let’s try this other way that won’t fuck everything up instead”
Tell your family member to network, that’s the best way to get a job. There are discord servers for every programming language and most projects. Contribute to open source projects and get to know the people.
Build things, write code, open source it on GitHub.
Drill on leet code questions, they aren’t super useful, but in any interview at least part of the assessment is going to be how well they can do on those.
There are still plenty of places hiring. AI has just made it so that most senior engineers have access to a junior engineer level programmer that they can give tasks to at all time, the AI. So anything you can do to stand out is an advantage.
Answer is probably the same as before AI: build a portfolio on GitHub. These days maybe try to find repos that have vibe code in them and make commits that fix the AI garbage.
Answer is probably the same as before AI: build a portfolio on GitHub
You really think that using GitHub falls in the usual vibecoding toolbox? As in: would they even know where/how to look?
You think vibe coders don’t love the smell of their own shit enough to show it to the world?
My path was working for a consulting firm (Accenture) for a few years, making friends with my clients, and then jumping to freelance work a few years later when I can get paid my contract rate directly rather than letting Accenture take a big chunk of it.
Working with Accenture
I am so sorry…
It was a wild ride
No idea, but I am not sure your family member is qualified. I would estimate that a coding LLM can code as well as a fresh CS grad. The big advantage that fresh grads have is that after you give them a piece of advice once or twice, they stop making that same mistake.
a coding LLM can code as well as a fresh CS grad.
For a couple of hundred lines of code, they might even be above average. When you split that into a couple of files or start branching out, they usually start to struggle.
after you give them a piece of advice once or twice, they stop making that same mistake.
That’s a damn good observation. Learning only happens with re-training and that’s wayyy cheaper when done in meat.
God bless vibe coders, because of them I’m buying a new PC build this week AND I’ve decided to get a PS5.
Thank you Vibe Coders, your laziness and and sheer idiocy are padding my wallet nicely.
Hope are you finding work right now? Shits rough out here haha.
But I thought armies of teenagers were starting tech businesses?!
My boss is literally convinced we can now basically make programs that take rockets to mars, and that it’s literally clicks away. For the life of me, it is impossible to convince him that this is, in fact, not the case. Whoever fired developers because ‘AI could do it’ is going to regret it.
Maybe try convincing him in terms he would understand. If it was really that good, it wouldn’t be public. They’d just use it internally to replace every proprietary piece of software in existence. They’d be shitting out their own browser, office suite, CAD, OS, etc. Microsoft would be screwing themselves by making chatgpt public. Microsoft could replace all the Adobe products and drive them out of business tomorrow.
Yea, it’s that lack of critical thinking that is the reason why MLMs, and get rich quick courses still exist
I mean … the first moon landings took a very low number of clicks to make the calculations, technically speaking
Lots of clacks, though.
it is impossible to convince him that this is, in fact, not the case
He’s probably an investor.
The tech economy is struggling. Every company needs 20% more every year, or it’s considered a failure. The big fish have bought up every promising property on the map in search of this. It’s almost impossible to go from small to large without getting gobbled up, and the guys gobbling up already have 7 different flavors of what you’re trying to make on ice in a repo somewhere. There’s no new venture capital flowing into conventional work.
AI has all the venture capitalists buzzing, handing over money like it’s 1999. Investors are hopping on every hype train because each one has the chance of getting gobbled up and making a good return on investment.
These mega CEO’s have moved their personal portfolios into AI funding and their companies pushing the product will line their pockets indirectly.
At some point, that $200/pp/m price will shoot up. They’re spending billions on datacenters, and eventually those investments will be called in for returns.
When they hit the wall for training-based improvement, things got slippery. Current models are costing exponentially more, making several calls for every request. The market’s not going to bear that without an exponential cost increase, even if they’re getting good work done.
Like trying to write a book just using auto complete
Vibe coding tools are very useful when you want to make a tech movie but the
hollywoodcommand just does not cut it.Vibe coding is useful for super basic bash scripting and that’s about it. Even that it will mess up but usually in a suler easily fixed way
I don’t think it has much to do with how “complex or not” it is, but rather how common it is.
It can completely fail on very simple things that are just a bit obscure, so it has too little training data.
And it can do very complex things if there’s enough training data on those things.
Yes exactly.
“Implement a first order lowpass filter in C”
LLM has no issue.
“Implement a string reversal function in Wren”
LLM proceeds to output an unholy mix of python and JavaScript.
Even though the second task is trivial compared to the first, LLMs have almost no training data on Wren (an obscure semi-dead language).
I’ve also found it useful for simple Python scripts when I need to analyze data. I don’t use pandas/scipy/numpy/matplotlib enough to remember the syntax and library functions. With vibe coding it, I can have a script in minutes for reading a csv with weird timestamps, scale some of the channels, filter out noise or detrending, perform a Fourier transform, and do a curve fit towards a model.
But then obviously I know every intermediate step I want to do.
When I want to be lazy and make some simple excel macros is about the most iv trusted it with that it manages to do with out fucking up and taking more time then just doing it my self.
No way. Youtube ad told me a different story the other day. Could that be a… lie? (shocked_face.jpg)
