Hello programmers! I’ve been making a living for a couple of decades figuring out stuff for people and coding whatever will make them happy. It’s fun. I’ve grown to prefer the people to the coding but I still get a kick out of the whole thing.
The problem is: at the job we’re being asked to pivot to vibe coding. At this point the order is to use it for all code, read the slop carefully, argue with the machine for way too long and only then open that PR. Massive productivity gains are expected. I’m appalled from an ethical, philosophical and professional standpoint. We’re a non-profit ngo ffs. My colleagues are fine with it. If I get even slightly critical the group goes awkwardly silent and I get comments on how all the programmers they know from other places don’t code anymore.
If this is how it goes from now on, I’m out. Is it really though? Are all businesses switching to vibe coding? Have some of you started switching career? I think I want to go to meatspace. Hand-made coding could make a cute hobby.
If you work for a company that prioritizes profit over quality - yes.
I no longer work in government IT, but from what I have heard from old colleagues, quality is still prioritized there and they are not forced to vibe code.
I read a retrospective from another team yesterday. They were preparing a demo for leadership and apparently it didn’t go so well. There were many reasons like last minute changes in requirements but one line was interesting for this discussion: The use of the LLM agents caused confusion about who is fixing which bug and taking on which tasks. The agents act like they’re alone in the codebase and keep adding and changing code broadly whenever they see an opportunity for improvement. And that often without specifically being prompted to do so. Now if you have multiple team members collaborating on a project with each their agents, chaos ensues because the agents are not coordinating and the diffs/commits become insane and the team doesn’t fully understand them.
This actually results in a necessity to test more and longer because nobody knows which bugs have really been fixed now and rapidly preparing for a release or a demo becomes more difficult than before.
In my opinion an LLM can be very useful to rapidly prototype something. Especially with an API or language you’re not familiar with. But for Production it’s still a huge risk to push code you don’t understand.
I have a co-worker that worked on a system with Kafka and some RDF inspired schema for the messages. He found a documentation page for an app using it telling bullshit about it and it is quite obvious made by AI without review. Even the first sentence was idiotic and wrong, so useless even for another LLM.
One question I have for the slop advocates in this thread is this - do you not like programming? Did you fall for the „learn to code“ meme and just learned the bare minimum to get a paycheque working on web dashboards?
Like why would you voluntarily cut out the most enjoyable part of the job, and go around scoffing at people who don’t want to do that?
Productivity is my boss’s problem, not mine, and I’d rather go and try and farm geese (I hate geese) than spend my whole day reading LLM generated code.
The responses to your question makes me fear for the future of products.
I use LLMs for scaffolding, boilerplate stuff, and basically things I can trust a junior with. For anything else, I have been forced to write it myself or rewrite it because the agents were so goddamn awful at it.
Reading that people even think programming has nothing to do with code and is just solving problems is just nuts to me. Code is a spec for a problem solution. If someone thinks the spec is neither important nor that being able to understand the spec is important… It’s like saying “I don’t care how this bridge is designed, it’s built”. Say that again and tell me it doesn’t sound nuts.
Writing code was never “the job”, that is just the trivial typing part you do when the thinking and designing ends. The job is solving problems (which I enjoy very much thanks.)
This is like people who refuse to program in another language because they are “a .NET programmer”. That just tells me you’re a coder not an engineer. In my career I’ve been paid good money to write C51 assembler, C, C++, Tcl, Limbo, Java, C# and Rust (roughly in order) - LLMs are just what’s next.
I do enjoy programming, but I prefer “getting stuff done”. While I enjoy programming, I’d rather just get it done and move on. I like the results of having programmed.
Productivity is my problem, because I build stuff for myself, not just for my boss.
I like to code. I like tools. There is a trap in using the LLM tool for everything. A Maslow’s hammer and everything looks like a nail type of trap.
I’m far from a slop advocate, so this is more of a devil’s advocate point: plenty of code writing is not enjoyable.
If I’m working on my own project, to my own standards, writing exactly what I want to write I’m usually going to get enjoyment out of it. That’s pretty commonly not the case when writing code for an employer. Maybe the tech stack sucks, the product is inane or worse, you think the feature is a dumb idea but have to do it anyway, you’re bending over backwards to work around tech debt that you’re not allowed by management to fix, or you have to appease incompetent/out of touch architects or tech leads who presume to tell you how to do your job. I personally don’t enjoy writing that code very much. At a certain point it’s almost like nails on a chalkboard if you genuinely enjoy programming for its own sake: you know what good would look like, you know how far away what you’re working on is from good, and you feel sad at all the organizational inertia you’d need to overcome to get to good or, choosing not to do that, at compromising your standards. That bugs me, at least, and at a certain point makes it hard to even start certain work projects.
LLMs can make this at least bearable. Rather than spending hours looking into the change yourself, writing all of the code, fighting the shitty test framework and swearing at the past engineers who made it so bad, you let the robot figure it out and review its work. The result may still suck, but it was going to suck if you wrote it by hand too, for reasons largely out of your control. You can’t be fully hands off, and you still have to deal with the things you don’t like to get a good result, but you put yourself a step away from what bothers you and by doing so make it a little more pleasant. And, when you find work that’s actually fun, interesting, or rewarding, you just cherry pick that for yourself. I’ve grown to appreciate them for this reason. I have a lot less dread for the nails on a chalkboard work than I used to, anyway.
When my AI fucks up code I sometimes think “I probably would have fucked that up too”. And then I make it write 50 more tests in 2 minutes so it doesn’t happen again. The ROI in time saving is too tantalizing for me to be a meat-only code monkey.
It does really need all those tests. But they probably should have existed anyway and I’m damn sure most devs out there weren’t going to be so obsessive with coverage.
Programming was never enjoyable to me.
Making things is. LLMs allow you to be extremely pragmatic and enjoy making things or troubleshooting things without tedious line by line nature.
Almost everyone in the industry worth their weight is using LLMs now. Top tier models create really solid code nowadays.
Almost everyone in the industry worth their weight is using LLMs now. Top tier models create really solid code nowadays.
This is not my experience. What worries me, is that I see posts like this all across the internet:
- All the good programmers are using LLMs. If you are not using agents for coding, you’re a bad programmer.
- Frontier LLMs are wonderful. You are just using the wrong model.
Anyway, if it works well for you, then I am happy for you. If you feel the need to evangelise, I think it would be more effective if you include some of your personal experience and include what is bad along with what is good.
Here is my personal experience from this Thursday:
- Gemini recommended a Kubernetes service to me (nice choice).
- The Helm config it gave had big problems. Settings were hallucinated and it used a feature that did not exist.
- After a day of doubling down on errors, I read a Github issue that said the Helm chart did not support the feature I needed.
- On Friday, I wrote my own Helm chart for the program from scratch. Thankfully, this is a skill that I have not lost. Its small, simple and I understand it.
- Total score this week: 1 day lost to AI.
We’re going towards a world where we can’t trust code anymore than we can trust images or videos. People all over the place are entrusting their entire jobs to AI and consumers have to deal with the output.
Work at a saas company in silicon valley, pretty much all the code being written is from an LLM here. Everything is still reviewed by humans, and a bunch of rounds of LLM reviews as well though.
Productivity has gone up as far as I can tell, we are shipping more features with a smaller staff. Support cases also seem to be going down, at least ones that reach an engineer like me since a lot are being resolved earlier in the escalation chain by a support technician, or just the customer talking to the built in helper LLM in the product.
Our token spend is pretty high though, looking like I’m at $1,200 on the month so far, so there’s that but don’t hear to many complaints from the finance department yet…
I’m liking the transition, as I have less work now. My day is a lot more waiting on the AI to complete a task or waiting for a human reviewer to do a pass on the code so I can spend more of my time doing important things, like scrolling on lemmy.
As for the future, I don’t think this is going away as much as everyone else in this thread seems to be wish casting for that to happen. The coding agents and models are only getting better, and tokens will only get cheaper as the data centers come on line. Long term I’ve been looking into becoming an electrician, but for now the economics don’t make sense with my current salary, so sticking with it until they lay me off…
I’m with you. Nearly same story, finance sector, east coast. It’s fun. It’s relaxing and I tinker with so many projects I never would have had the time for.
This comment condensed all the thoughts and emotions of an entire episode of Black Mirror into a few paragraphs
I write code. There is skill to being able to read documentation. I love tools like predictive IDE’s. Search engines augmented my ability to code with sites like stackoverflow. LLM’s are a continuation of that trend. Often the output is broad strokes that I need to refine. At my workplace, humans are required even with the tool improvements.
If AI becomes capable of assessing whether its proposed changes are actually the best decisions for a project, then it will become truly viable.
It’s not going away.
Everyone who complains about the quality of the code it produces is overlooking one important fact: 90% of the code developed by the software engineering profession is utter dogshit, pasted together by people whose understanding just about extends to typing in stackoverflow.com by banging their head against they keyboard.
LLMs are not replacing artisinal hand-crafted code developed by a skilled engineer from a top-10 university, it’s replacing the utter shite produced by the people with an NVQ from Timbuctoo Community College that actually powers the vast majority of websites and enterprise software.
And it’s fucking good at it.
Look, when I started my career I used to hand-write assembly code. I used to personally review the output of the Keil C51 compiler because its optimiser was objectively dogshit. Nobody is doing that any more - partly because the compilers are better than programmers at writing assembler these days, and partly because we have so much CPU and memory we don’t know what to do with, so who cares if they aren’t. Both apply to LLMs, and we will soom be at a stage where reviewing - or even caring - about the quality of LLM produced code is as anachronistic as thinking you need the check the compiler’s output. (TBF, Clang/LLVM for AVR still produces dogshit assembler, but that’s by the by.)
Just as assembler did before, high-level code is going to become just another intermediate representation that isn’t really important; what will matter are the prompts and context you give to the LLMs. And there’s still a hell of a lot of engineering skills that need to go into that.
Software Engineers - the real ones - have nothing to fear from LLMs, and in many ways it’s much more satisfying working with an LLM than a team of barely skilled “coders”. The barely skilled coders who wouldn’t know malloc from a semaphore though? They’re fucked.
Just as assembler did before, high-level code is going to become just another intermediate representation that isn’t really important; what will matter are the prompts and context you give to the LLMs.
Ah the old “LLMs are just a new layer of abstraction” argument. No they aren’t, and won’t be any time soon.
You mean that “write this service make no mistakes” executed with a LLM-as-a-service where the underlying model updates every week and the model itself is deprecated in 8 months isn’t a good idea for a source code representation?
Nah, it definitely is. It’s called job security.
On the first half, that’s not how it’s done; the input is a much more detailed description of design and architecture coupled with TDD.
On the second half - I happen to agree, that’s why I think the OpenAI/Anthropic business models are doomed to fail. But that’s where locally deployed models become key - predictable output.
They don’t need to be better than the best programmer in the world to change how 90% of code is written, they just need to be better than a junior dev from Timbuctoo. And feasably-deployable open models crossed that bar around Q1 this year and are only getting better (Qwen3.8-Flash-Next is another huge leap forward.) We may not be quite there yet, but the destination is now inevitable; adapt or find a new career.
On the first half, that’s not how it’s done; the input is a much more detailed description of design and architecture coupled with TDD.
Yes, I have these coworkers too. I’ve seen what they look like, and it doesn’t change my point.
But that’s where locally deployed models become key - predictable output.
Local controlled models help, yes. That isn’t what business do, though. And even for local models, the models are still stochastic as fuck. Maybe that changes in the future, in which case I’d reconsider that view (though natural language is still a terrible interface for telling a computer precisely what to do).
We may not be quite there yet, but the destination is now inevitable; adapt or find a new career.
How many years has it been now? Mythos was the end of the world, Fable had to be locked down by the US government, Astra is going to cause humanity to go extinct, and yet here we still are today with vibecoded, mass-produced slop.
God I have þoughts about your post, but I’m not typing all of it out on my stupid phone, so maybe if I remember when I’m at a computer þis comment will serve as a placeholder.
Just have it do the tedious parts while you do the high-level planning. The interview with Matt Pocock on Pragmatic Engineer (podcast) discussed this approach in the latest episode. If I had to guess, I’d say that part of the conversation happened in the last 30 or 40 minutes of the interview, but the whole thing was interesting.
The problem with cast coding a bunch of vibe coded apps is you have to maintain the vibe coded apps.
As a developer of over two decades, ive seen ai aka llms good at:
- Creating small MVPs to prove something is possible as software
- Stealing and using other peoples code to make said apps.
- Quick very small directed scripts.
- Making up funny random shit. Such as aidungeon.
- Using up ram
And its mediocre at a lot of things.
And straight up bad at other things such as cooking and instructions that need to be followed to the letter.
it’s not gonna last. if you tune out of the hype and actually look at some hard data, vibecoding stops looking so hot: https://codemanship.wordpress.com/2026/08/12/ai-software-development-what-does-the-data-say/
the current token costs are unsustainable also. the only ones making bank right now are the shovel sellers: https://isaiprofitable.com/
personally i’m working on hand-rewriting several projects vibecoded out by a non-dev in a small shop. not only is a lot of this straight up broken nonsense, the amount of tech debt is staggering. previous job wasn’t better, i had to spend more time fixing slop from former coworkers than actually introducing new features. keep your skills sharp and persevere. we’ll get through this.
tl;dr: this, too, shall pass. but holy shit.
keep your skills sharp and persevere. we’ll get through this.
We’ll be the next generation that writes malware no one can stop
But being able to ship small, mildly broken, internal tools for my non-technical coworkers quickly is actually amazing.
Nobody cares if the internal tool code is nice, but when it shaves 50% of the work off of sales the sales team gets excited. So if I vibe up a shitty UI it’s still a net gain.
I’ve probably automated away like 60% of the ad hoc work I used to get into internal tools, and that has helped a ton with workload and budget.
Careful. You know how it goes with temporary workarounds? Suddenly, you find yourself maintaining slightly broken load-bearing slop.
That’s a fair concern, usually I only vibe the UI.
I’m not a front end guy, so as long as I know the backends is good I’m fine with it.
Yeah, it’s only the user’s experience fucked over when the UI is sloped together.
Although I agree with you…
That’s how the vast majority of software has been built for the past couple of decades. LLM’s aren’t different in that regard, just faster.
Ok, UI coding is messy either way.
I am a technician in the physics department for a major university. There are quick and dirty hardware hacks that I threw together 2 decades ago that are still in daily use. Quickly made mildly broken tools have a habit of lingering.
That’s exactly how a webpage that displays an excel spreadsheet nicely in different tables, turned into a gigantic monster of a project that nobody fully understand at my workplace.
Well, kinda, because that was BEFORE ai. I can’t even imagine what mockery of God himself they would have done with AI in their hands.
It’s absolutely going to last. IMO until Astra the models were not good enough to really be worth bothering with, but we’ve reached a tipping point.
And while I still do read the code they make and then fix things (or tell them to do things differently), it’s still waaaay quicker than doing it “by hand”.
Sorry but if you’re expecting this to be a temporary thing you’re going to be very disappointed.
IMO until Astra the models were not good enough to really be worth bothering with, but we’ve reached a tipping point.
People said the same about older models.
Yep. Every. Single. One.
I agree with you except for the Astra bit. The differences in day to day are marginal at best (compared to both Sol and Anthropic equivalents) and the paradigm shift came long before it.
It’s copium, which is understandable. I think it’s really important for people who want to have a reliable career in the industry 5+ years from now, to learn harness coding even if begrudgingly.
If vibe coding remains the norm and is actually sustainable, there won’t be a reliable career. You’ll be weavers being put out of work by the autoloom. You’re worthless to them. What can you do that someone with six weeks (or less) of training can’t?
You know the current state of IT security? It’s bad.
Aand here comes AI. It will not make it better, even though it finds some issues faster.
I’m still designing and writing all code by hand. I don’t know that any of my coworkers are and know that many definitely are not. Our company does have copilot reviews built into CI and, at least for now, requires human review as well.
It’s normalized now but I don’t see it lasting. I’m retiring at the end of this year cause I’ve had enough of it and I don’t want to wait anymore for companies to finally figure it out. I’ve told so many what needs to change, what they need to do in order to fix their builds (mainly consisting of rebuild it, rehire the devs you laid off, use AI as a rubber duck only) and none of them listen. They thank me for my time, cut a cheque, and send me on my way. I had the idiotic notion of trying to change things, hopefully make some people see the light but they’ve all drunk the kool-aid and have all pushed all their poker chips in and are currently hoping it works out. it won’t.
Any dev worth their salt can look at what’s been produced and everything is garbage. everything. I’ve yet to meet a single developer of any level that has looked at something that’s been vibe coded and said “hey, that’s not bad!” It’s all crap. the ONLY things that would ever work is if the AI somehow managed to churn something out to be 100% complete and working on the first attempt. something that will never need to be upgraded or scaled or something that would never interact with the user space. Name me something that does that.
The issue as it stands right now is it’s taking too long to fail. it will fail, I guarantee you that, but it’s taking too long. Developers and programmers and engineers can’t wait anymore. They’re not keeping their skills up because many just don’t see a point. Many have been unemployed from the field for so long now they’ve taken different career paths. We’re simply losing developers due to time.
It should have happened by now, should have happened months ago. the gaps in training data are increasing. you get way more hallucinations than solutions. the tool is absolutely worthless but the problem is the people utilizing the tool don’t know any of this. thus token use increases.
Basically what I feel like, except I’m too young and I’m not even close to not needing a salary. I’ve been pushing back; I bought some time. I’ve spent all my willpower on this now and the cancer is still growing. I’m pretty much done. The uncertainty that comes with career change doesn’t look so bad anymore compared to whatever this “work” feels like.
It’s honestly a shame and on behalf of other devs my age and older I apologize. We let you down. I’d say start looking into FOSS projects or contributing to them but man even I’m getting out of those as most are also drinking the AI Kool-Aid especially in the Linux FOSS space. it’s gotten REALLY bad for Linux based projects within the past year. they’re actively killing any progress made on “The year of the linux desktop” I don’t see that happening, ever.
I’ve switched to Linux on my personal computer a few years back and I was so happy I did. Seeing pillar distributions like Debian open up to the slop is immensely depressing. As you’ve said FOSS is unfortunately not a sanctuary.
OS maintenance, like Debian, is tons of tedious busywork, most of it is quite literally just pulling from upstream packages, making sure there is no conflicts or certain types of labeled bugs, and that it meets the licencing and policy standards. So long as they are checking the code, I could see open-source projects benefiting substantially from LLM usage. The one thing that FOSS projects have is a lack of manpower.
What are your thoughts for using AI to colour in & do the tedious bits? So you plan out the structure of what you’re trying to do, work out the individual pieces and get the AI to do a bunch of the (well specified) leg work. I’ve found it fairly reliable like this, especially for things that involve looking up function parameters in unfamiliar APIs. But this does depend on a thorough look over what comes out as well. No doubt there’s still issues that can pop up but generally have found it to be useful overall
If the API is unfamiliar how do you know what it puts out is the best way to use the API without going and reading the docs anyway?
Sure if you need it to work with that level of detail/efficiency then you’ll need to understand the code thoroughly as well. If you need it to draw a dashed line and you get a dashed line then that is fine by me. Looking up the argument differences between matplotlib plt.plot and plt.scatter for example can take quite a bit of time for fairly trivial things
It is heavily normalized in industry now.
I quit a job that added AI use to performance reviews super early. That was pure bureaucratic cancer and most of my good coworkers burned out and left. I don’t think I’ll ever work for a big corp again, I actually like my work so much more now.
At work I’m expected to use it, our clients want it, my boss likes that he can feel technical when writing tickets (they’re mostly wrong though, and the tickets solution instead of report and request). It genuinely can do some useful tasks that make sense to use it for.
There are real pros and cons, but there’s no putting this back in the bottle. Philosophically I do hate it and everything it stands for, but practically it has allowed me to do a lot that I couldn’t (and wouldn’t) before.
The only good solution I’ve found is that you have to get your hands dirty and stay in the weeds. You cannot let it run off and do what it wants, you have to drive and then tag it in. When you vibe code something you’ll find yourself in three weeks resolving an issue and going “wait, it does what?!”, and of course, arguing with the gibberish Claude or GPT claims is English but is actually the first stage of model collapse as the models reinforcement train on ever more distilled data. Plus, skill atrophy is real. Decide which skills to allow to atrophy carefully.
AI code review is good and useful. I used to use it as a first wave for obvious stuff, but it is actually decent and high trust now. Saves me some time on that.
It’s good at finding bugs and security issues, and one thing I actually really like is having it model a system as a state machine and enumerate all the possible states to find bugs — especially concurrency bugs. I don’t work in a provable language, so this is hugely helpful.
I would be very hesitant to take a role where they push vibe coding or “agentic fleets” or loops or whatever. If you’re babysitting 6 Claude code sessions you aren’t working and you’re not in the loop on any of them. That will accumulate as tech debt and bog you down over time. It’ll suck your soul dry. It’s miserable.
Reading the slop and reviewing it “software factory” style is a very bad sign to me.
Some code is throwaway or disposable, vibing that makes sense to me. But the core work is more important than ever. Maybe the disposable code is the new part, I look at it like installing an IKEA kitchen, it’s slop, but it looks nice, the important part is the foundation and level flooring that enables the slop to stand up.
I actually like my work so much more now.
You hiring any managers? 😅
arguing with the gibberish Claude or GPT claims is English
You’re right to push back on that – I’ve been using Claudish the whole time and this actually changes everything. If we use English instead, each one of these comments could be a single, concise line. One thing worth knowing: This is not a minor boost to understanding, but a complete game changer. Understanding my bullshit has been gated behind speaking LLMese.
Nah, really, I’ve been able to get fairly decent code out of the newer models since I work with a very popular language. Not one-shotted of course, but after some change requests or manual changes. But the language these models speak (including the Chinese ones, it seems) is infuriating and they seem to insist on tons of super long comments in places where the code itself feels self-explanatory. My philosophy is to write “why” comments, not “how” comments, but not a single model seems to agree with me.
I look at it like installing an IKEA kitchen, it’s slop, but it looks nice
Are IKEA kitchens really that bad? I’ve been looking to remodel my ancient kitchen and it comes to 5-6k EUR, appliances included (minus the fridge, I upgraded that a while ago), from IKEA. If I ask a carpenter to do a proper one, that’s going to be more like 10-20k and I don’t wanna spend that kinda money lol
IKEA kitchens are great?! We’ve had ours for a long time now. And even moved once and took the kitchen with us. It’s easier to assemble than their competition, the surface of my cupboards has higher quality than some other kitchens I’ve seen. There’s no silly salesman in the process who tells you it’s 17,000€ but you get a special discount and only need to pay 10,000€ if you order it today… You can just grab additional cabinets 12 years later…
I didn’t buy the appliances at IKEA, though. And I found nicer alternatives for the sink, plumbing, countertop as well. But the rest is from IKEA and I’m A-okay. Also like my IKEA wardrobe.
Only downside is if you don’t assemble it yourself. I had a look at their price table for assembling it, and that service was a bit expensive, I think. At least where I live.
I think IKEA has different price points
The ones installed when I moved in were those cheap particle board counter tops and cabinets, so when my dishwasher leaked everything expanded and cracked and can never be fixed. A real wood or high quality MDF would have been okay with a one time water event (if dried properly)
It stood up for years, worked fine, wasn’t awful. Just was cheap and not resilient.
Absolutely hate the “how”, that’s comment garbage.
But it perfectly matches what you’d get in annotated data or intro medium blog style writing.
one thing I actually really like is having it model a system as a state machine and enumerate all the possible states to find bugs — especially concurrency bugs. I don’t work in a provable language, so this is hugely helpful.
Could you elaborate on that at all, finding bugs with a state machine approximating the system, how does that work?
