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Vibe Coding Cleanup: The Birth of a New Tech Side Hustle Ecosystem
Haebom
There is a saying that is secretly being passed around among developers these days.
"AI writing code for you? That's great. But ultimately, it's people who organize it."
This is where a new service category called "Vibe Coding Cleanup" emerges. What started out as a simple joke—"We clean up your AI-damaged code"—has now become a clear business opportunity.
In my recently published book, I personally wrote that Vibe coding requires a tremendous amount of debugging.
The explosive spread of Vibe Coding
In early 2025, Andrej Karpathy first coined the term 'Vibe Coding'.
A method of generating entire functions as if having a conversation with AI, instead of developers typing out each line of code.
This approach to programming in natural language seemed to promise a tenfold increase in productivity.
In fact, according to GitHub, 92% of developers worldwide use AI coding tools, and Copilot alone generates billions of lines of code every month.
But behind the flashy numbers lies a less obvious problem.
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According to GitClear analysis, AI-assisted codebases experience a 41% increase in code churn (the rate of reverts and rewrites).
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A Stanford research team found that AI-assisted developers wrote more vulnerable security code, but mistakenly believed it was secure.
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Lack of input validation, use of outdated libraries, architectural collapse… these problems make senior developers sigh.
The Cleanup Economy Really Exists
Now, there are companies specializing in fixing AI-written code. 404 Media calls this "AI Spaghetti Code," and numerous freelancers and consulting firms are already touting this cleanup as a core service.
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A consultant may work on 15 to 20 "cleaning projects" at a time and receive a premium fee.
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Ulam Labs even formalized the service category name "Vibe Coding Cleanup."
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A dedicated marketplace called VibeCodeFixers.com even sprang up, connecting 300 professionals with dozens of projects within weeks of its launch.
A typical client looks like this:
"I poured $5,000 into OpenAI credits, and I'm left with a half-functioning prototype. And I need to somehow get it into production."
Even among Silicon Valley startups, 25% of Y Combinator batches have over 95% of their codebases generated by AI, so the scale of this "cleaning market" is staggering.
Why AI Code Is Breaking Down
Actually, the problem is simple.
It's not that AI "can't write code," but rather that it doesn't understand the overall context of the system and only produces locally optimized code.
According to Stack Overflow's analysis, AI is strong at implementing small features, but it falls short when it comes to architectural decisions. Ultimately, each prompt adds new technical debt.
Moreover, according to a Georgetown University study, more than 48% of AI-generated code contains security vulnerabilities.
They expose secret keys in your code, pull in outdated libraries, and create race conditions that only surface under load.
What's more serious is that even developers themselves don't fully understand the code written by AI.
Thoughtworks calls this “competency debt.”
As reliance on AI increases, teams lose the ability to maintain their own codebases.
Market Opportunities
So is this simply a temporary phenomenon?
No. Gartner predicts that by 2028, 75% of all enterprise software engineers will use AI coding assistants.
If only half of these needed cleaning, it would create a huge market.
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Startups can get to an MVP in a matter of weeks with AI, but end up spending the same amount of time and money on cleanup.
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Still, it's faster than traditional development methods.
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Meanwhile, organizing professionals are creating new carriers for $200 to $400 an hour.
Some even expand into packaged services.
In productized forms such as "flat-rate cleanup packages, AI code security audits, and vibe-to-production pipelines."
A new division of labor in software development
This is the view we see.
AI writes the draft, humans design, and humans finish editing.
It was a little different from what I expected, but this is how reality works.
Expert Gergely Orosz offers this analogy:
"AI is like a junior developer who works very hard. But the problem is that this junior never grows into a senior."
Ultimately, this means that there will continue to be a need for organizing experts.
This change creates new career paths.
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A junior developer who is good at cleaning up AI code can earn a senior-level salary in just two years.
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Seniors who understand both the pros and cons of AI will become key personnel for companies.
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A company's competitiveness depends on how well it establishes its cleanup process.
My perspective
I believe this phenomenon is not a simple coincidence, but a fundamental shift in the software ecosystem in the AI era.
There's no better tool than AI for rapid prototyping. But bringing it to production level still requires human intervention.
Ultimately, what matters is how smartly we utilize AI and how strategically we design cleanups .
To those who readily claim that AI will replace developers, I have this to ask:
"Okay, but who's going to clean up that code?"
That's the most exciting opportunity right now, and it's the next market we need to look at seriously.
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I post articles related to IT 💻, economy 💰, and humanities 🎭.
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haebom@kakao.com
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I post articles related to IT 💻, economy 💰, and humanities 🎭.
If you are curious about my thoughts, perspectives or interests, please subscribe.
haebom@kakao.com
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