bro thought software engineering is just $20/mo chatgpt💀
I refuse to believe this post isn’t satire, because holy shit.
If I was 14 and had an interest in coding, the promise of ‘vibe coding’ would absolutely reel me in. Most of us here on Lemmy are more tech savvy and older, so it’s easy to forget that we were asking Jeeves for .bat commands and borrowing* from Planet Source Code.
But yeah, it feels like satire. Haha.
Lol I remember when I was around pre-school / kindergarten age and I was asking family members how to spell words so I could type into a Windows 3.1 “run program” dialog box “make sonic game”.
I feel you, and I agree that as a learning tool that’s probably how it’s being used (whether that’s good or bad is a different topic), but the fact that they immediately talk about having to pay a dev makes it sound like someone who isn’t trying to learn but trying to make a product.
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 /
They’re so close to actual understanding of how much they suck.
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.
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?
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.
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.
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?
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.
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
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?
What is good enough for the goose is good for the gander
Microplastics are stored in the balls.
I agree, the terminology used gives it away.
Obviously fake. Still funny though.
You should(n’t) watch Quin69. He’s currently “vibe-coding” a game with Claude. Already spent $3000 in tokens, and the game was in such a shit state, that a viewer had to intervene and push an update that dragged it to a “playable” state.
The game is at a level of a “my first godot game”, that someone who’s learning could’ve made over a weekend.
I better not watch this, it would make me angry. I hate people who could have hired someone like me for the same or even less money and get a working product. But no, they always throw money at fraudsters. Because wasting resources is their very nature.
I watched a bit out of curiosity and even vibe-coding aside, he is annoying as fuck. Couldn’t stand him 20 seconds.
That’s an issue on its own. He’s just a typical streamer. I already had enough from looking at thumbnails.
It’s strange, but I’ve seen lots of comments that are not aware this is fake. The ai hater crowd is using it as their proof, the other side saying he is using it wrong.
That’s depressing. This is so obviously fake because of how entertaining it is written and how the conclusion gets shoved in your face. No subtlety.
Is that what the weird extra width on some letters is, artifacts from some AI generating the post?
No, the phrasing makes it clear someone wrote a fictional account of becoming self aware that the output of vibe coding isn’t maintainable as it scales.
I’m entirely too trusting and would like to know what about the phrasing tips you off that it’s fictional. Back on Reddit I remember so many claims about posts being fake and I was never able to tease out what distinguished the “omg fake! r/thathappened” posts from the ones that weren’t accused of that, and I feel this is a skill I should be able to have on some level. Although taking an amusing post that wasn’t real as real doesn’t always have bad consequences.
But I mostly asked because I’m curious about the weird extra width on letters.
When something is too “on the nose,” for example, it’s written in exactly the way that would induce the most cheering and virality because it appeals so much to one group of people, it’s worth considering it may have been written to provoke exactly that reaction.
Thanks!
I really wish people did not do this. This isn’t something I was ever taught to look for, and I like to think I got a good education. I was taught to make sure my source is credible, to consider biases and spin and what things are facts and what is just opinion, but I wasn’t taught to look for a lot of deception people call out online. But I guess I have to live with this and gain the skill to look for deception. Genuinely, thanks for helping me, since I don’t think I ever would have figured out what raises “fake” flags in most peoples’ heads on my own.
AmidFuror’s description is on point and I see it as a variant of Poe’s Law. Instead of sarcasm being mistaken for a real belief, it is presenting a fictional account of someone being self aware that is mistaken for someone actually becoming self aware.
There are two lines that make me absolutely certain it is written by someone who it not a vibe coder and is leaning into the sarcasm.
- ‘pulling out my wallet for someone that knows what they are doing’ implies the poster knows they don’t know what they are doing
- ‘vibe coding is just roleplaying for guys who want to feel like hackers’ is a joke I’ve seen directed at vibe coders more than once
Keep in mind that not all deception is malicious, but most people see the word deception as having a negative implication. An actor/actress pretending to be someone else is technically deceptive the same way as whoever wrote this hilarious post. They are presenting a fictional account for an audience.
You are right about the thespian thing, but when you watch TV/film/theatre everyone is in on the “joke” and we all know they’re not really falling in love, getting murdered, or whatever dramatic happening. I’m not sure if OOP is just trying to entertain and expects everyone to realize they’re joking, which would stick them on the thespian side, or if they have other motives. But hey, interesting point to bring up!
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Interesting. Curious for a point of comparison how The Onion reads to you.
(Only a mediocre point of comparison I fear, but)
That’s a bit difficult because I already go into anything from The Onion knowing it’s intended to be humorous/satirical.
What I lack in ability to recognize satire or outright deception from posts written online, I make up for by reading comment threads: seeing people accuse things of being fake, seeing people defend it as true, seeing people point out the entire intention of a website is satire, seeing people who had a joke go over their heads get it explained… relying on the collective hivemind to help me out where I am deficient. It’s not a perfect solution at all, especially since people can judge wrong—I bet some “omg so fake” threads were actually real, and some astroturf-type things written to influence others without real experience behind it got through as real.
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r/thatHappened was the worst thing to happen to Reddit and I sincerely hate whoever created that sub
No, the text itself. No vibe coder would write something like that. The artifacts you mentioned are the result of simple horizontal and vertical upscaling. If you zoom in you can see it better.
Thanks!
You’e welcome!
I don’t really care about vibe coders but as a dev with just under 2 decades in the field:
- Your vibe coding shit will not go to prod until humans fully review it
- You better review it yourself first before offloading that massive mental drain to someone else (which means you still need to have some semblance of programming skills). Don’t open a PR with 250 files in it and then tell someone else to validate it.
- Use more context. Don’t give it vague ass prompts.
- Don’t use auto-accept. That’s just lazy asshole shit.
I can’t stress this enough: if you give me a PR with tons of new files and expect me to review it when you didn’t even review it yourself, I will 100% reject it and make you do it. If it’s all dumped into a single commit, I will whip your computer into the nearest body of water and tell you to go fish it out.
I don’t care what AI tool wrote your code. You’re still responsible for it and I will blame you.
When I see a sloppy PR I remind people “AI didn’t write that. You wrote it. Your name is on the git blame.”
Love it, I have a vibe coding colleague I will use this with.
I like this mentality. I might start telling people the same thing
If it’s all dumped into a single commit, I will whip your computer into the nearest body of water and tell you to go fish it out.
I’m going to steal this for an update to an internal guidance document for my dev team. Thank you.
Lmao glad I could help! I hate those big commits. They’re so much harder to traverse and know what’s going on. Developer experience has been big on my mind lately. Working 5 days a week is already hard, but there are moments when we can make tiny bits easier for each other.
I have never used an AI to code and don’t care about being able to do it to the point that I have disabled the buttons that Microsoft crammed into VS Code.
That said, I do think a better use of AI might be to prepare PRs in logical and reasonable sizes for submission that have coherent contextualization and scope. That way when some dingbat vibe codes their way into a circle jerk that simultaneously crashes from dual memory access and doxxes the entire user base, finding issues is easier to spread out and easier to educate them on why vibe coding is boneheaded.
I developed for the VFX industry and I see the whole vibe coding thing as akin to storyboards or previs. Those are fast and (often) sloppy representations of the final production which can be used to quickly communicate a concept without massive investment. I see the similarities in this, a vibe code job is sloppy, sometimes incomprehensible, but the finished product could give someone who knew what the fuck they are doing a springboard to write it correctly. So do what the film industry does: keep your previs guys in the basement, feed them occasionally, and tell them to go home when the real work starts. (No shade to previs/SB artists, it is a real craft and vital for the film industry as a whole. I am being flippant about you for commedic effect. Love you guys.)
I think storyboards is a great example of how it could be used properly.
Storyboards are a great way for someone to communicate “this is how I want it to look” in a rough way. But, a storyboard will never show up in the final movie (except maybe fun clips during the credits or something). It’s something that helps you on your way, but along the way 100% of it is replaced.
Similarly, the way I think of generative AI is that it’s basically a really good props department.
In the past, if a props / graphics / FX department had to generate some text on a computer screen that looked like someone was Hacking the Planet they’d need to come up with something that looked completely realistic. But, it would either be something hand-crafted, or they’d just go grab some open-source file and spew it out on the screen. What generative AI does is that it digests vast amounts of data to be able to come up with something that looks realistic for the prompt it was given. For something like a hacking scene, an LLM can probably generate something that’s actually much better than what the humans would make given the time and effort required. A hacking scene that a computer security professional would think is realistic is normally way beyond the required scope. But, an LLM can probably do one that is actually plausible for a computer security professional because of what that LLM has been trained on. But, it’s still a prop. If there are any IP addresses or email addresses in the LLM-generated output they may or may not work. And, for a movie prop, it might actually be worse if they do work.
When you’re asking an AI something like “What does a selection sort algorithm look like in Rust?”, what you’re really doing is asking “What does a realistic answer to that question look like?” You’re basically asking for a prop.
Now, some props can be extremely realistic looking. Think of the cockpit of an airplane in a serious aviation drama. The props people will probably either build a very realistic cockpit, or maybe even buy one from a junkyard and fix it up. The prop will be realistic enough that even a pilot will look at it and say that it’s correctly laid out and accurate. Similarly, if you ask an LLM to produce code for you, sometimes it will give you something that is realistic enough that it actually works.
Having said that, fundamentally, there’s a difference between “What is the answer to this question?” and “What would a realistic answer to this question look like?” And that’s the fundamental flaw of LLMs. Answering a question requires understanding the question. Simulating an answer just requires pattern matching.
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See, I agree with everything up to the end. There you are getting into the philosophy of cognition. How do humans answer a question? I would argue, for many, the answer for most topics would be "I am repeating what I was taught/learned/read. An argument could be made that your description of responding with “What would a realistic answer to this question look like?” is fundamentally symmetric with “This is what I was taught.” Both are regurgitating information fed to them by someone who presumably (hopefully) actually had a firm understanding of the material themselves. As an example: we are all taught that 2+2=4, but most people are not taught WHY 2+2=4. Even fewer are taught that 2+2=11 in base 3 or how to convert bases at all. So do people “know” that 2+2=4 or are they just repeating the answer that they were told was correct?
I am not saying that LLMs understand or know anything, I am saying that most humans don’t either for most topics.
How do humans answer a question? I would argue, for many, the answer for most topics would be "I am repeating what I was taught/learned/read.
Even children aren’t expected to just repeat verbatim what they were taught. When kids are being taught verbs, they’re shown the pattern: “I run, you run, he runs; I eat, you eat, he eats.” They’re are told that there’s a pattern, and it’s that the “he/she/they” version has an “s” at the end. They now understand some of how verbs work in English, and can try to apply that pattern. But, even when it’s spotting a pattern and applying the right rule, there’s still an element of understanding involved. You have to recognize that this is a “verb” situation, and you should apply that bit about “add an ‘s’ if it’s he/she/it/they”.
An LLM, by contrast, never learns any rules. Instead it ingests every single verb that has ever been recorded in English, and builds up a probability table for what comes next.
but most people are not taught WHY 2+2=4
Everybody is taught why 2+2=4. They normally use apples. They say if I have 2 apples and John has 2 apples, how many apples are there in total? It’s not simply memorizing that when you see the token “2” followed by “+” then “2” then “=” that the next likely token is a “4”.
If you watch little kids doing that kind of math, they do understand what’s happening because they’re often counting on their fingers. That signals that there’s a level of understanding that’s different from simply pattern matching.
Sure, there’s a lot of pattern matching in the way human brains work too. But, fundamentally there’s also at least some amount of “understanding”. One example where humans do pattern matching is idioms. A lot of people just repeat the idiom without understanding what it really means. But, they do it in order to convey a message. They don’t do it just because it sounds like it’s the most likely thing that will be said next in the current conversation.
I wasn’t attempting to attack what you said, merely pointing out that once you cross the line into philosophy things get really murky really fast.
You assert that LLMs aren’t taught the rules, but every word is not just a word. The tokenization process includes part of speech tagging, predicate tagging, etc. The ‘rules’ that you are talking about are actually encapsulated in the tokenization process. The way the tokenization process for LLMs, at least as of a few years ago when I read a textbook on building LLMs, is predicated on the rules of the language. Parts of speech, syntax information, word commonality, etc. are all major parts of the ingestion process before training is done. They may not have had a teacher giving them the ‘rules’, but that does not mean it was not included in the training.
And circling back to the philosophical question of what it means to “learn” or “know” something, you actually exhibited what I was talking about in your response on the math question. Putting to piles of apples on a table and counting them to find the total is a naïve application of the principals of addition to a situation, but it is not describing why addition operates the way it does. That answer does not get discussed until Number Theory in upper division math courses in college. If you have never taken that course or studied Number Theory independently, you do not know ‘why’ adding two numbers together gives you the total, you know ‘that’ adding two numbers together gives you the total, and that is enough for your life.
Learning, and by extension knowledge, have many forms and processes that certainly do not look the same by comparison. Learning as a child is unrecognizable when compared directly to learning as an adult, especially in our society. Non-sapient animals all learn and have knowledge, but the processes for it are unintelligible to most people, save those who study animal intelligence. So to say the LLM does or does not “know” anything is to assert that their “knowing” or “learning” will be recognizable and intelligible to the lay man. Yes, I know that it is based on statistical mechanics, I studied those in my BS for Applied Mathematics. I know it is selecting the most likely word to follow what has been generated. The thing is, I recognize that I am doing exactly the same process right now, typing this message. I am deciding what sequence of words and tones of language will be approachable and relatable while still conveying the argument I wish to levy. Did I fail? Most certainly. I’m a pedantic neurodivergent piece of shit having a spirited discussion online, I am bound to fail because I know nothing about my audience aside from the prompt to which you gave me to respond. So I pose the question, when behaviors are symmetric, and outcomes are similar, how can an attribute be applied to one but not the other?
I think this is great. I like hearing about your experience in the VFX industry since it’s unfamiliar to me as a web dev. The storyboard comparison is spot on. I like that people can drum up a “what if” at such a fast pace, but vibe coders need to be aware that it’s not a final product. You can spin it up, gauge what works and what doesn’t, and now you have feasibility with low overhead. There’s real value to that.
Edit: forgot to touch on your PR comment.
At work, we have an optional GitHub workflow that lets you call Claude in a PR and it will do its own assessment based on the instructions file we wrote for it. We stress that it’s not a final say and will make mistakes, but it’s been good in a pinch. I think if it misses 5 things but uncovers 1 bug, that’s still a win. I’ve definitely had “a-ha” moments with it where my dumb brain failed to properly handle a condition or something. Our company is good about using it responsibly and supplying as much context as we possibly can.
I like your previs analogy, because that’s how I’ve been thinking of it in my head without really knowing how to communicate it. It’s not very good at making a finished project, but it can be useful to demonstrate a direction to go in.
And actually, the one time I’ve felt I was able to use AI successfully was literally using it for previs; I had a specific idea of design I wanted for a logo, but didn’t know how to communicate it. So I created about a hundred AI iterations that eventually got close to what I wanted, handed that to my wife who is an actual artist, told her that was roughly what I was thinking about, and then she took the direction it was going in and made it an actual proper finished design. It saved us probably 15-20 iterations of going back and forth, and kept her from getting progressively more annoyed with me for saying “well… can you make it like that, but more so?”
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
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.
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.
My entire IT career has been funded by morons like this. This is just the latest moronic idea that is going to pay my bills. Cleaning up after vibe coders has guaranteed my income until I die. You see, posts like this focus on the code that is broken and requires another dev to fix it enough to get it going. There is a long road from “finally working” to “production ready” to “optimized”, and we get paid along every inch of the way.
