It's a bit strange that Karpathy's "vibe coding" ever gained traction as a concept, although perhaps only among those without enough experience to know better.

As I understand it, what Karpathy was referring to as "vibe coding" was some sort of flow state "just talk to the AI, never look back" thing. Don't look at the generated code, just feel the AGI vibes ...

It sounds absolutely horrific if you care even the tiniest bit about the quality of what you are building! Good for laughs and "AGI is here!" Twitter posts, maybe for home projects and throwaway scripts, but as a way of developing serious software ?!!!

I think part of the reason this has taken off (other than the cool sounding name) is because it came from Karpathy. The same idea from anyone less well known would have probably been shot down.

I've seen junior developers (and even not so junior), pre-AI, code in this kind of way - copy some code from someplace and just hack it until it works. Got a nasty core dump bug? - just reorder your source code until it goes away. At minimum in a corporate environment this way or working would get you talked to, if not put on a performance plan or worse!

From the jump, even without the emdashes, it was crystal clear that this post was written by Claude. I'm sure the OP put their own ideas into the prompt, provided some sources, etc. But reading some of these phrases provoked a pretty visceral sense that I'm just reading an LLM's output:

"The harsh reality" "he perfectly captured" "architectural decisions that make senior engineers weep" "fundamental issue"

It makes me wonder whether a whole class of writing is going to be deprecated because the cadence is just too similar to LLM outputs.

I have been taking on "rescue" projects for a while through my business. Previously, the barely-functioning code was usually being generated via outsourcing agencies but it seems the new source is now going to be LLMs.

I imagine it will be the same set of issues really. Just a different way of cost cutting measures. There can be good reasons to take shortcuts but, in my experience, the problems start when you're not mindful that there's a price to pay for taking these shortcuts. Whether it comes from managers, employees or outsourced personnel, it's the same result.

I haven't thought about advertising it as a separate type of service(for vibe coded platforms) yet but maybe I should. The Australian software market is small so haven't been hearing much about the results of those experiments.

> Startups save weeks getting to MVP with Vibe Coding, then spend comparable time and budget on cleanup. But that’s still faster than traditional development.

That's the core of situation as described in the article. I wonder how true that is, that it's faster overall than having developers build the MVP.

From what I've seen, I think developers can build just as fast, especially with AI assistance. They may not want to though, knowing full well the MVP/prototype will go directly into production.

Better to take some time to have a decent architecture early on. Product and management probably see that as a waste of time.

On the other hand, vibe coding allows the product team to make exactly what they want without having to explain it to developers. That's the real draw to this, basically a much better figma.

Perhaps there is a market for a product oriented vibe coding tool, that doesn't pretend to make code, but gives developers much better specifications while allowing the product and business side better input in the process.

I wonder if vibe coding is a bit like DIY plumbing. You can do it yourself a bit and then later when water starts gushing all over your bathroom you hire an emergency plumber at a high fee.

You learn a little more for next time.

Janitor Engineers [0] are already a thing? Damn. Also, all links in this article starting from the "Why AI code fails at scale" section are dead for some reason, even though it was written only 5 days ago. That raises some questions...

EDIT: Not trying to offend anyone with this [0], I've actually had the same half-joking retirement plan since the dawn of vibe coding, to become an "all-organic-code" consultant who untangles and cleans up AI-generated mess.

Vibe Coding is accelerating the death of documentation and architectural clarity. Companies are measuring success by tokens generated and time-to-prototype, ignoring the massive, hidden cost of cleanup/maintenance.

The real skill is now cleanup, not generation.

Vibe code has a lot in common with legacy code.

Low confidence to change it, low internal and external quality.

Also some differences: low age-to-quantity ratio, schedule pressure, inflated expectations.

It's most cost-effective to shift errors from runtime to compile time and from compile time to design time.

Unfortunately, AI rushes people to runtime as fast as possible.

Our company has been doing emergency fixes (system that are down, costing companies significant money and they cannot fix) for decades. We have been seeing a significant uptick in occurrences the past few years.

That raises the question if LLM-generated code is going out of fashion in general. The article seems to assume it will always exist and always need clean-up. But what if it's not worth it and instead you should (mainly) return to the world where humans write code? Simply because salary < LLM-credits + cleanup costs.

Would be interesting to see an in depth breakdown on a project that has went through the vibe code to cleanup pipeline in full. Or even just a 'heavy LLM usage' to 'cleanup needed' process. So, if the commits were tagged as LLM vs human written similar to how it's done for Aider[0]: At which point does the LLM capability start to drop off a cliff, which parts of the code needed the most drastic refactors shortly after?

[0]: https://aider.chat/HISTORY.html

This mirrors exactly what we learned from outsourcing over the past two decades. The successful teams weren’t those with the best offshore developers - they were the ones who mastered writing unambiguous specifications.

AI coding has the same bottleneck: specification quality. The difference is that with outsourcing, poor specs meant waiting weeks for the wrong thing. With AI, poor specs mean iterating indefinitely on the wrong thing.

The irony is that AI is excellent at helping refine specifications - identifying ambiguities, expanding requirements, removing assumptions. The specification effectively IS the code, just in human language instead of syntax.

Teams that struggled with distributed development are repeating the same mistakes with AI. Those who learned specification discipline are thriving because they understand that clear requirements determine quality output, regardless of the implementer.

As a freelance developer, I've already had one job that was essentially vibe coding cleanup - though I ended up recommending that I just rewrite the whole codebase (I reused one tiny piece). It's definitely a new world.

I've seen some new vibe coding websites that now come with shipping support by a dev as part of the package like https://sparkedby.ai

In the long term, software development is about theory building more than coding. And these are theories that need wrestle with wholly imperfect external systems, as well as business departments whose desires and needs are in conflict with each other and with themselves from day to day.

LLMs are still too sycophantic. The ideal agent needs to say no increasingly as time moves on, explaining why new requirements would conflict with existing commitments, and grunt awkwardly and emit enough noxious fumes so that business people only come forward with their most pressing needs rather than wavering whims.

I wonder how many of these vibe coding build apps will grow to massive apps/be really popular (I imagine a lot of them will)... and what kind of security vulns we'll see everywhere because of how it was initally built...

i can only imagine that services like described in this article will become a very common part of getting proof of concepts built with AI into production.....

I'm pretty good at getting LLMs to write well-tested, production-ready code. I think it's a matter of knowing the right tools and techniques to use and steering the project in the right direction. Type-checking, linting, and a solid test suite go a very long way. It would be a nightmare to work on any project without these.

It could be interesting to take on a consulting project. I haven't done any contract work for many years but I'm curious to see if I could provide some value. Let me know if you need help with making a project more maintainable: refactoring, linters, writing tests, setting up CI/CD pipelines, etc.

In Spanish we have the saying: "Lo barato sale caro". So in order to save, you turn to "AI", and then you immediately need to turn to a real developer or a development team. If I were in this business, I would charge hefty amounts too, because I can imagine the type of disaster that will have to deal with.

this article doesn't add much; it's a thin advertorial for their services. It also just seems like typical maintenance programming, which has existed for about 1 day less than the entire time we've been writing software. I guess even this most unattractive of all programming work is also looking for a little AI sauce to spice up the offerring, and justify increased rates (maintenance work: $100/hr; vibe-coding cleanup: $200/hr)

I use Elixir in production. So, it's already a pretty unique language with very low marketshare in the first place and not many developers are attracted to it because of that and the opportunities. And rarely, I do take on some existing codebases that would smell of code rot from vibe coding. Elixir is one of those languages where it's actually hard to make something look complex. But, vibe coders somehow manage to pull it off. There are usually all these modules all over the place - running Genservers instead of just using something simplified, lot of Javascript like patterns all over the place.

And so, I dug deeper, I tried Claude, GPT-5 and Gemini. While each have their own merit, they all seem to be flawed when it comes to keeping things simple. Having said that, there are a lot of times I'm stuck in these codebases and the AI knows exactly what's happening if you give it the right context (within VS Code). So, definitely you can just setup a small shop to "De-vibe" coding with AI. Ironically.

Human legacy code turns into machine-generated legacy code; the nature of work remains, more or less, the same

In my experience vibe coding is useful at the very beginning of a project (especially if the tooling selected does not have a boiler late generation) and at the very end when a lot of the work is refactoring.

YMMV but I’d rather build the MVP without much AI but then clean it up using it.

Just a few days ago, I had to "clean up" a vibe-coded prototype:

1) generate API tests using AI

2) refactor the app manually

3) make sure the tests passed

Took me a few hours or so. The app was pretty small, though.

I've done a fair amount of vibe coding cleanup, ironically using a fair about of LLMs, a lot of leadership are under the false impression that more code means better product, their ignorance is my gain.

Need an MCP server that can do this.

10x the productivity measured by lines of code written, but 1/100th the quality measured by pain in the ass to clean up.

While this was inevitable, I must say I’m a little surprised it has become a thing this _quickly_.

A while ago, I was having an intense and heated argument with a good friend in the Finance sector about whether AI would replace jobs. I informed him that AI can only do something repeatable, "already solved problems", or what I call "shit kicking work". His response was something to the effect that I was underestimating how many people's jobs were _entirely_ shit kicking work.

To be fair to him, my partner who works in Healthcare has the same concern, and for quite precisely the same reason: if the kind of work normally done by juniors who are training/building their skills is done by machines instead, where do the next generation of seniors come from?

My response to both was that I was confident the market would fix this problem itself - people will not pay for garbage. There is a reason books are still printed by established publishers. Why buy a book when you can just print a book on printer paper yourself? Because reading a book on printer paper sucks.

I cannot imagine that machines will ever replace any work where there is any meaningful threshold for "correct". I am so intrigued to see how this plays out across the broader economy.

Just vibe clean it when GPT-6 comes out.

I feel like there should be a term that's like "MVP," but instead of a "minimum viable," it's a FULL FEATURE SET but just super sloppy and not really usable for production.

FSV = full slop version

Talk about sloppy seconds

Where are the apps created with vibe coding? I haven't seen any so far...

Many of the links from this article don’t exist. Is it AI generated slop?

What I've been witnessing in the recent time is that people who have no coding experience but great ideas, get into coding and due to the cheap and fast way of generating this code, have no issues with sharing it.

Other people who have more or a lot of experience with coding, help them and everybody profits in the end.

I understand that it becomes a problem with some businesses but others may profit too.

It's not all bad.

Insufficient context is definitely a major hurdle for LLMs when coding, but I think an even bigger hurdle is their inability to synthesize ideas and to resolve logical conflicts.

They don't seem to have a 'cohesive worldview'; additional context can easily sway them from one conclusion to the opposite conclusion. A large part of coding is about decision-making and prioritization; it's difficult to perform well at either of these tasks unless your worldview is internally consistent.

"vibe coding" is 20% initial prompting, and 80% doing exactly this (with more prompting). At some point we'll have to recognize that there are good and bad coders, and good and bad vibe coders.

Where reality seems to be heading:

Company hires a bunch of young MBAs from prestigious universities who don't know how to code; pay them large salaries to produce a massive pile of junk which doesn't work. Pay some engineer with 10+ years of experience to be a 'code janitor' to clean up the mess to actually make it work.

Quite dystopian considering that the experienced engineer could probably build the whole thing in 1/10th of the time from scratch.

This would align with the trend of companies imposing an increasing number of arbitrary and counter-productive constraints on engineers whilst simultaneously expecting them to be more productive.

Cool sister article on their site, the other side, using AI to cleanup AI slop:

> How Senior Engineers Clean Up Code and Scale Products with AI

> Partnering with us means investing in quality, not just speed. We leverage AI to accelerate development and testing,

https://donado.co/en/articles/2025-08-02-prototype-to-mvp/

I just take some kitchen paper and one of these small thin plastic bags to clean up after my own dog's shit. No need to pay for a service.