I keep seeing "vibe coding." WTF is vibe coding? ELI5
this post was submitted on 15 Sep 2025
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Vibe coding is asking gpt for code, copying it into your code environment, then telling gpt about any errors or issues. The problem is that it actually works a significant amount of the time, let's be generous and say 80%. Another 15% of the time it cannot solve a problem itself. And finally the worst possible outcome is the last 5%, where it creates a seemingly working solution that actually breaks on edge cases or has potential security issues.
A security nightmare waiting to happen.
A day will come when I get to know what vibecoding is. Or maybe this word will die out sooner. You never know.
That picture accompanying the article is backwards. Why is it portraying the AI as the babysitter and not the baby that needs to be supervised by a human?
You're absolutely right!
I completely messed up the picture. It should be the other way around. Do you want me to correct my mistake and generate a new picture?
/s
Carla Rover once spent 30 minutes sobbing after having to restart a project she vibe coded. Rover has been in the industry for 15 years, mainly working as a web developer. She’s now building a startup, alongside her son, that creates custom machine learning models for marketplaces.
Using AI to sell AI, infinite money glitch! /s
“Using a coding co-pilot is kind of like giving a coffee pot to a smart six-year-old and saying, ‘Please take this into the dining room and pour coffee for the family,’” Rover said. Can they do it? Possibly. Could they fail? Definitely. And most likely, if they do fail, they aren’t going to tell you.
No, a kid will learn if s/he fucks up and, if pressed, will spill the beans. AI is, despite being called "intelligent", not learning anything from its mistakes and often forgetting things because of limitations - consistency is still one of the key problems for all LLM and image generators
If you bring a 6yo into office and tell them to do your work for you, you should be locked up. For multiple reasons.
Not sure why they thought that was a positive comparison.
This feels like one of those paid fluff pieces companies put out so that smaller ones feel like they’re “missing out”
Currently, I write all production code at work without any AI assistance. But to keep up with things, I do my own projects.
Main observation: When I use it (Claude Code + IDE-assistant) like a fancy code completion, it can save a lot of time. But: It must be in my own area of expertise, so I could do it myself just as well, only slower. It makes a mistake about 10 - 20 % of the time, most of them not obvious like compile errors, so it would turn the project into disaster over time. Still, seems like a senior developer could be about 50% - 100% more productive in the heat of the implementation phase. Most important job is to say "STOP" when it's about to do nonsense. The resulting code is pretty much exactly how I would have done it, and it saved time.
I also tried "vibe coding" by using languages and technologies that I have no experience with. It resulted in seemingly working programs, e. g. to extract and sort photos from an outdated data file format, or to parse a nice statistics out of 1000 lines of annual private bank statements. Especially the latter resulted in 500 lines of unmaintainable Python-spaghetticode. Still nice for my private application, but nobody in the world can guarantee that there aren't pennies missing, or income and outcome switched in the calculation. So unusable for the accounting of a company or anything like that.
I think it will remain code completion for the next 5 years. The bubble of trying more than next-gen code completion for seniors will burst. What happens then is hard to say, but it takes significant breakthroughs to replace a senior and work independently.
In real code, so after the first week of development, typing really isn't what I spend most of my time on. Fancy autocomplete can sometimes be right and then it saves a few seconds, but not nearly 50-100% added productivity. Maybe more like 1-2%.
If I get a single unnecessary failed compile from the autocomplete code, it loses me more time than it saved.
But it does feel nice not having to type out stuff.
That's why all research on this topic says that AI assistance feels like a 20-30% productivity boost (when the developers are asked to estimate how much time they saved) while the actual time spent on the task actually goes up by 20-30% (so productivity gets lost).
I find it also saves a certain "mental energy".
E. g. when I worked on a program to recover data from the old discontinued Windows photo app: I started 2 years ago and quickly had a proof-of-concept: Found out it's just sqlite format, checked out the table structure, made a query to list the files from one album. So at that point, it was clear that it was doable, but the remaining 90 % would be boring.
So after 2 years on pause, I just gave Gemini 2.5Pro the general problem and the two queries I had. It 1-shot a working powershell script, no changes required. It reads directly from the sqlite (imagine the annoyance to research that when you never ever use powershell!) and put the files to folders named by the former albums. My solution would have been worse, would probably have gone with just hacking together some copy-commands from SELECT and run them all once.
That was pretty nice: I got to do the interesting part of building the SQL queries, and it did the boring, tiring things for me.
Overall, I remain sceptical as you do. There is definitely a massive bullshit-bubble, and it's not clear yet where it ends. I keep it out of production code for now, but will keep experimenting on the side with an "it's just code completion" approach, which I think might be viable.
Yours is pretty much the best-case scenario for AI:
- Super small project, maybe a few dozen lines at most
- Greenfield: no dependencies, no old code, nothing to consider apart from the problem at hand
- Disposable: once the job is done you discard it and won't need to maintain it
- Someone most likely already did the same thing or did something very similar and the LLM can draw on that, modify it slightly and serve it as innovation
- It's a subject where you are good enough that you can verify what the LLM spits out, but where you'd have to spend hours and hours to read into how to do it
For that kind of stuff it's totally OK to use an LLM. It's like googleing, finding a ready-made solution on Stackexchange, running that once and discarding it, just in a more modern wrapping. I've done something similar too.
But for real work on real projects, LLM is more often than not a time waster and not a productivity gain.
It makes a mistake about 10 - 20 %
Anecdotally, Copilot does the reverse for me.
Copilot leads me on flights of fanciful code that is absolutely not possible, and the joy turns to tragedy when I find out it lied insidiously about a particular niche function the entire time.
That will make Taco very angry
Looks like every senior developer is building vibe coded startup and their children are selling machine learning models on marketplaces. Anyone know of such marketplace or it's fake as much as the article ?
I've noticed nary a thing except vapid media and social buzz. I've tried the tools themselves and they seem to waste time too often to be worthwhile
This headline made me a little nauseous.
If you are wondering how it could possibly be “worth it” the end of the article has this.
The Fastly survey found that senior developers were twice as likely to put AI-generated code into production compared to junior developers, saying that the technology helped them work faster.
So vibes. Vibe coding is “worth it” because people got good vibes.
The research shows that - while engineers think AI makes them more about 20% more productive - it actually causes an approximate 20% slow-down.
AI cannot use logic or reason. Everything it outputs is a hallucination, even if it’s sometimes accurate. You cannot trust anything it outputs.
The research shows that - while engineers think AI makes them more about 20% more productive - it actually causes an approximate 20% slow-down.
AI cannot use logic or reason. Everything it outputs is a hallucination, even if it’s sometimes accurate. You cannot trust anything it outputs.
Research shows that - while people think having more people in the household gets the housework done faster - babies actually cause an approximate 100% increase in time spent on housework.
Children cannot use logic or reason. Everything they output is brabbling, even if it sometimes resembles actual works. You cannot trust anything they say. Parents are stupid for having them. (/s)
Developers see AI as a "child" that might need many years to grow up, but it's still worth all the trouble they go through. It's an emotional choice, not a rational one.
If I try to get it to do more than predict the next two lines of code it's gonna fuck something up. A nervously laughable thing I saw at work was someone using a long spec file to generate a series of other files and getting high praise for it. It was the equivalent of mustache templates but slower and with a 30% chance of spitting out garbage. There was also no way to verify if you were in that 30% zone without looking through the dozens of files it made.
As someone right there in the trenches getting hired specifically to clean the slop up, I don't buy this survey at all and I'd be very suspicious of any "senior dev" that participated in it cause...where are they? I'm not seeing them when I go in to my clients offices because they all got axed. I do see a lot of junior prompt monkeys though.
I'm a senior dev and I want nothing to do with AI. By the time I understand what I want well enough to describe it in a complete sentence or paragraph, I can just write the fucking code myself. I figure it out as I go.
The whole point of having devs under you that is to be able to trust them to get the job done and do it right. You want to be able to delegate tasks to them and not have to peek over their shoulder every five fucking minutes to be certain they're not making a mess of things.
I seriously doubt AI will ever be able to replace that. Not until they figure out how to make it afraid of fucking up.
As a senior dev I have found AI useful for auto completion (where you see beforehand what it wants to write directly in Visual Studio) and code analysis (as it does find some bugs and can give good hints for code structure). I would never trust it with anything even remotely complex though.
It kinda scares me that people trust it enough for "agent mode", as giving it direct access to change stuff directly has simply put never worked.
Yes. It's extremely helpful when I'm doing a refactor and can just go TAB TAB TAB TAB Oops not that TAB TAB done. Saves me a lot of time with the boilerplate, but is very bad at the logic portions.
You do refactoring with auto complete?
senior developers were twice as likely to put AI-generated code into production compared to junior developers, saying that the technology helped them work faster
Perhaps senior devs are more likely to use more granular, step-by-step, controlled prompting. Asking it do write specific functions in specific ways and following specific approaches and conventions instead of just "do me an app, robot bro".
That’s actually how I am using AI for my work (web dev, pls don’t hate me). If I am stuck or have some tiny function missing for a task I ask AI, check their output - if it’s garbage I continue on my own again or if it’s usable I review the output and continue from there. Also, I think AI can be neat for „rubberducking“ when I am debugging some stupid shit and point me in directions I haven’t looked before.
Similar to how I have found success with it. Is it revolutionary? No, not at all. But it's a variable sized (big for some use and nonexistent for other use) incremental tool that requires a new skill set to use effectively.
Mix in all of the hype and its easy to see why people are confused and why some get different results.
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I have never tried to use AI to develop software, just looked at the output that sometimes shows up in google searches. Noises are starting to come from on-high about an AI 'push', so I may need to show some basic awareness. Any suggestions on how to get started or should I just ask the AI?
I've been using copilot. Potential is there but getting a result is more art than science. I've found it helpful to document desired workflows in readmes and ask for unit tests then run unit tests until it works out.
- use a premium model like sonnet and put it in agent mode
- Ask it to review the project
- ask it to review the ticket/requirements
- ask it to research existing solutions and write a design document that meets the requirements with high certainty
- Let it write the document and make sure it stays on task
- review the output and send build errors back, roll forward or undo the code and re-submit
- identify what works and reduce scope
I will say Claude Code may be at the fore front of AI coding assistants. It runs in your terminal. Try loading it on one of your side projects and see what you can accomplish.
Is there a difference between claud in the vscode extension and Claude code? I mostly use chat mode but will sometimes try agent and neither really make me happy. Id say if a task could be given to a high school programmer the AI agents can do it about 30÷ of the time.
I feel like the experience is different and it feels more integrated with the project than simply running a claude model with Cursor which is a vscode fork. Right now I had it working on a long running cli app task in Rust and its been implementing feature after feature consistently.
I'd suggest Cursor. I was somewhat anti-AI-coding until my job encouraged it, and Cursor (using Claude 4 Sonnet) gave me that "ohh, now I get it" moment.
It's still plenty capable of generating bad code, so it can take a bit of practice to get a feel for how to use it productively.
I'm well aware the plural of "anecdote" isn't "data", but literally no dev I know (senior or otherwise) thinks this. Give me a junior work with - most of them at least actually learn.
Yeah it’s the same skillset I use with Junior devs except I don’t have the hope AI will grow out of its bad habits
Amen. I've tried the vibe coding thing but it's frustrating because a) too often the AI output has some profound problems and it gets annoying 'babysitting' it; and b) I usually prefer the challenge of figuring out syntax and implementation issues myself.
If something is taking too long I'll ask the LLM. But I feel like if I do this too much my skill set will atrophy and I'll lose my sharpness. So it's a balancing act.
But this brings up another wider question: where is the line between "occasionally getting AI help" and "vibe coding"? Surely it's subjective.
The definition may have changed but I feel like originally it was only vibe coding when the “dev” did not know what they are doing. When some one with little to no programming background is able to build and app on “vibes” alone.
Also applies when the dev could know what they're doing, but just doesn't care to.
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Senior devs love vibe coding because they have the knowledge and skills to recognize and fix errors. They hate it because it makes morons think they don't need the knowledge and skills to recognize and fix errors.
As a senior dev I hate vibe coding. I can write code an order of magnitude faster than I can review it, because reviewing code forces you to piece together a mental model for something made by someone else, whereas when I write the code myself I get to start with the mental model already in my head.
Writing code is never the bottleneck for me. If I understand the problem well enough to write a prompt for an LLM, then I understand the problem well enough to write the code for it.
I'm a junior and even I feel the same way, reading and understanding someone else's code not only takes me longer but is far less rewarding than just writing it myself. There's also the issue as a junior that if I read AI code with issues that maybe I don't notice or recognise, but it compiles fine, it could teach or reinforce poor practices that I may then put into my own work.
I understand how to turn the results of a select statement into an update statement, but the AI does it a hell of a lot faster.
I find if you give it small enough chunks, it's easy enough to review. And even if you do have to correct, it's generally easier to correct than it would be to write it all by hand.
Outside of my own specialty I can people in the software industry bogged down by managing excessive boilerplate. I think this happens most often in web dev and data science.
In my opinion this is an indication that the software tools for those ecosystems need improvement, but rather than putting in the design effort to improve the tools in the ecosystem, these Big Data companies see an opportunity to just throw LLMs at it and call it a commercial product.
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