title: Who believes in vibe-coding?
author: u/bigbott777
contenttype: redditpost
publication: r/programming
published: 2026-02-27T07:51:10+00:00
sourceurl: https://www.reddit.com/r/programming/comments/1rg0jju/whobelievesinvibecoding/
word_count: 835
[removed]
Link: https://medium.com/ai-in-plain-english/who-believes-in-vibe-coding-1796fdd27b43?sk=790fbf5e16a80ddc825ea3e9750dc451
Score: 208 | Comments: 312 | Subreddit: r/programming
Top Comments
u/thehairof_aenarion (304 pts):
My boss does I can tell you that. So I have to or I'd be failing in my job. My opinion on the subject does not matter as all engineers are being forced to utilise ai more in their work flow.
I personal do not like using code that I don't understand. I do not mind using ai to generate code and then to learn about it. Very different to tab tab tab tab.
But yeah even then I'm not learning at the rate I was before because there's so much more code being produced now. I can learn what I use and then I'll receive 3 or 4 massive merge requests and can't spend the same energy learning those. I used to get one or two of these a week and now it's one or two a day.
u/AvidCoco (146 pts):
The thing with vibe-coding is that it misses the vital “Refactor” step of the classic “Red, Green, Refactor”.
I occasionally vibe code things, but since I’ve been programming for 10+ years I also always go in and refactor the generated code to meet my standards.
Same way that Junior developers used to just copy-paste from stackoverflow without actually reading and understanding the code, while seniors would still copy-paste but then refactor.
u/deceased_parrot (121 pts):
I believe in vibe-management: the idea that AI can replace the average manager, including CEOs. In fact, we had the technology to do it for awhile now, but it was considered inhumane to raid the local zoo for chimps and put them into suits.
u/seweso (110 pts):
This getting downvoted seems weird given the sentiments of every actual programmer on the subject of AI.
Who downvotes this? Is that organic?
u/ratttertintattertins (39 pts):
The article certainly has some truth although I’ll say one thing. We’ve got a god class in our code which has been there for decades, since the inception of our pretty old code base.
We’ve never been able to get rid of it because it’s simply too large to refactor and it’s horrendous legacy C++ spaghetti code that’s thousands of lines long. The risk of touching it is very high and it has 0% test coverage.
As an experiment, I set my Claude opus the problem of refactoring it and it spent all afternoon doing so. It has refactored it into testable, organised modern c++ code, that’s much more well documented, and the unit test coverage figure is now 40%. It still passes our extensive automated regression test.
Will that PR get through? No of course not, it’s too risky. However, it is clear that this machine can potentially do something that we human have been unable to do for 20 years and might just facilitate us finally moving to a better code base, with the right level of supervision and quality assurance.
None of that really disagrees with the article but it does show the sheer power of these tools and what they can potentially achieve in the right hands.
u/CondiMesmer (21 pts):
that's not what vibe coding means. Vibe coding is when you don't even follow what's going on and let the LLM do everything for you, including the architecture. Of course it's assumed you're not reviewing the code either. Why not when the AI can do that for you instead of killing ur vibe.
u/FrenchieM (26 pts):
Vibe coding is like DIY products. Now you can do it yourself without the hassle but if you need something stable and battle tested, you'll need a professional.
Im a programmer/engineer with 20 years of experience and even for me the treasure trove of AI allows me to do things that would have taken months or years of research. It opens the door for things you wouldn't have thought possible unless you're someone with a strong vision and/or wanting to revolutionize the field.
But it's also allowing anybody to do it, which means even people with no clue deploying stuff to everyone. It's like being cured by your neighbor.
u/datNovazGG (14 pts):
I'm getting a bit tired of "vibe-coding" being both the original "vibe-coding" where you don't even look at the code and whenever a developer prompt for code.
There's a big difference and yes I believe it's viable to prompt for code.
u/mpanase (8 pts):
Vibe coding totally works, if what you are building is somethign you could easily build yourself.
If it's something you wouldn't know how to build, it's a clusterfuck.
u/TikiTDO (5 pts):
Starts off strong, but very quickly falls into the same trap as many other such articles.
To start off, this list is mistaken:
- Big bosses — CEOs and such of companies used to hire programmers.
- General public.
- Programmers.
There are actually 4 distinct groups:
- Big bosses — CEOs and such of companies used to hire programmers.
- General public.
- Programmers that do not understand ML
- Programmers that DO understand ML
You described Big bosses and the general public accurately, but you missed the final distinction.
Most people that you refer to as "vibe coders" fall into group 2 and 3. It's essentially the people trying to use an AI like a person. Also in group 3 are people that seem to think the only valid use for AI is trivial translation and research tasks. Essentially the unifying theme; to people like this "AI" is a black box that you can treat as a singular object. It's something you use, and then you stop and do something else.
On the other hand, programmers that do understand machine learning treat AI tools like any other tool or lib that is omnipresent in our lives. I'm never just "using an LLM," just like I'm never just using "glibc," or just using "linux," or just using "python." These are all just tools that are constantly active. I might refer to them directly sometimes, but even if I'm doing something totally unrelated they are still there facilitating operations.
It's not too different with ML. During the course of work I might be using any number of LLMs, classifiers, embedders, filters, processors, and transformers, all as individual tools that facilitate my work. It's rarely just one either. I might have multiple tasks going in the background at once as I review and validate the results of one. It's about understanding how to use your toolkit effectively.
As part of it I am constantly making decisions about things like how much to review (a test needs much less attention than auth code), and conversely, how much time to spend before implementation to plan out the entire thing (If it knows exactly what files to change, and how to change them, it's far less likely to make uninformed changes) . For instance, the idea that LLM code needs to be refactored (well, all code really. Would you ever actually ship your first draft?) is pretty well known, so at the very least you probably shouldn't be reviewing your code until you've had the LLM iterate over it a few times with an eye towards cleanup, refactoring, and normalising the code to your style (which you've obviously described in extensive detail for the AI in your docs, right?)
The challenge here is that none of this is obvious or implicit. If you don't understand that you must take on all these extra tasks to make AI development effective... Well, then you just won't be effective. Then when scientists are studying simplify it all down to a simple soundbite (no gains in performance when using a tool that takes many years to fully master, a couple of years after that tool's release).
It's also where you get the people thinking that just because an AI can write code now that makes them software engineers. Software engineering isn't "writing code," that's just being a code monkey. A software engineer understands why software is designed the way it is, and can make informed decisions about the structures and abstractions that a codebase will need not just tomorrow, but also in two years. This is why the most senior devs and engineers have always spent more time in meetings than at the keyboard. The meetings is where the hard stuff with no clear answers gets solved. The keyboard is where the technical challenges with an obvious solution you haven't found yet get solved. One of those is actually much harder.
An AI will happily make generic, uninformed decisions about your codebase if you let it, and your task as the person doing the development is to not let it do that.
Some programmers report (I am one of them, honestly) that they lost the fun of coding and the feeling of a “flow”.
I find this has more to do with how much you're learning, and how challenging it is, rather than how exciting the profession is. As you master a profession, it will often stop being fun, because you will stop encountering projects that challenge you. With AI this is a very easy state to reach, because AI makes a lot of previously challenging tasks much easier.
This makes sense if you know anything about flow state though. Flow is a mix if skill and difficulty of a task. If a task is too simple, you will not enter a flow state. Obviously if you make a task easier, you will have trouble entering flow.
The solution is that is actually quite simple though. Take on more challenging tasks. Have the AI help you understand fields you don't understand at all, but have always wanted to. Use it to write code in totally new environments, doing things you've never done before. Start projects that have always seemed too impossible and too insurmountable to even start. It's quite easy to regain that bright-eyed excitement when you're exploring a totally new realm that you thought was denied to you.
As an example, I did not really need an AI driven home assistant box capable of tracking me across all my camera, parsing voice from any of them in order to respond to my requests, and I most certainly didn't need to design my own PoE powered box pi5 ML inference box, and I absolutely didn't need to do fluid dynamics simulations to track how the air would flow in that box. I could have just bought one of the stupid pre-made assistant boxes, or just bought a micro-PC and used that and spent far less time and money. I didn't though; instead I hammered at it for a while with AI, and now I have a 3D model generation scaffold, a fluid dynamics simulation environment, and nearly have a talking smart house that can operate even without internet. None of those were things I thought I'd reasonably be able to get to in this lifetime. All were, and continue to be really fun.
u/redmera (15 pts):
There is time and place for vibe-coding. Sometimes a person or a company just needs a draft for something very fast to test if the idea and UI are viable. Once they have a nice prototype, it's much easier and cheaper call the real developers and tell them "we would like one like this, please".
u/diesuke (7 pts):
Vibe coding should get you vibe salary
u/MayBeArtorias (5 pts):
Managers who consume PR promises of AI companies 24/7
u/smirk79 (6 pts):
What a joke of an opinion article. I’d love to see how strong a programmer the author is. I have serious doubts.