Vibe-Coding Limits No One Can Avoid: Cleanup Specialists On Rise

Vibe coding is when AI quickly puts together the first version of a program. You get something working in a few hours. It is an easy way to test an idea and show the result right away. Many startup founders use AI "vibe-coding" platforms (Lovable, Replit, etc.) to build early versions of their apps. You type a plain-language description of what you want, and the tool produces the code (and sometimes a runnable app). This lets non-technical people with no programming experience create a working prototype quickly and at low cost. About 25% of new startups now use AI for 95% of their code. AI writes more than 30% of Google's new code.

The Promise: Speed and Cost Savings

Jobs that used to take weeks can now be finished in a few days - about two to five times faster than with traditional approaches, in my experience. AI coding tools let startups build and launch a basic product very quickly - sometimes even from a single prompt. This helps them test ideas and reach users sooner.

Founders can build a prototype without hiring a team because AI coding tools take care of the routine code. This can significantly reduce further development costs. A project that once required 1,000 development hours can now be completed in 200. For a startup, that is a major saving.

From the outside, you look very productive - one day's work now leads to a week's worth of code.

The Hidden Problems

With vibe-coding you can quickly assemble a prototype, but such code usually doesn't work properly. Founders quickly run into errors. LLMs write code that looks fine, but it often has problems that beginners don't notice.

Architecture and Scalability Issues

Founders want code fast and cheap. They use AI to build something that works right now and skip what they see as not important. There is no testing to make sure it is reliable, and no plan for how different parts of the code should fit together. This is only suitable for a demo. Without a good plan for how your code is organized, the app might work but will not scale well. Nobody knows what needs to change when things get bigger. When more customers start using your app or you want to add new features, you may have to rebuild most of it.

Security Vulnerabilities

When you ask an AI tool to write code, you may not think to request checks on user input, password hashing, or access checks, so the AI may ignore it. Tests show that, for example, asking an AI to build a login page with no extra details on security produces code that allows SQL injection. Code built this way often breaks company rules and industry standards. Experienced developers can spot these problems right away.

Performance and Reliability Issues

When AI writes code, it often works slowly - pages load for a long time, database queries take too long, the application is "heavy". If you don't configure and optimize such code, the application will start to "crash" or slow down when many people log in simultaneously.

Small home-grown projects often lack thorough tests. A founder may assume that code from an AI will work, but rare cases, and error handling will be missing. Unit tests, docs, and helpful error text show up only when someone creates them. Without them, the program can break with little provocation.

Teams that code this way in-house often end up with shaky programs lacking solid structure or security checks. They then need experienced engineers to review, rewrite, and prepare the software for day-to-day use. The prototype may run, but it does not meet the standards of a safe, and efficient app, so founders bring in experts.

The Solution: AI Code Cleanup Specialists

When writing the first version, everything is done quickly just to show how the idea works. Then they usually call in experienced programmers or specialized teams to prepare the product for launch. A quick draft and a real product are completely different things.

Now there are companies that specialize in this. Vibe coding cleanup specialists are in high demand to fix poorly-written code with issues generated by AI. They close security holes, write tests, set up automated builds, connect logs and monitoring.

Companies increasingly turn to such specialists to rescue projects where AI code is raw, without proper architecture and security. Those who made demos now call in seniors to make the code stable and secure. Investors and product managers often call such teams before launch to avoid surprises.

Before, everyone was happy that AI could write code in a couple of minutes. Now everyone understands: without experienced programmers, the product won't work for real users.

How Cleanup Specialists Work

In the beginning, startups often write code themselves - just to get something working. But such code is usually unstable, with errors and without proper structure. Then they call in experienced developers to fix bugs, build proper architecture, create protection from hacking, write tests and documentation. They know how to make a stable and secure product from such a prototype. Products stop falling apart and are ready for launch.

Founders come to Belitsoft with first versions of their software products coded by AI agents. Our vibe coding cleanup specialistsmake the products ready for customers: ensure proper architecture, fix bugs, patch security holes, and perform testing. You get a reliable application faster and cheaper than with traditional development.

The Cleanup Process

Experienced programmers look at all the code and search for where hackers might break in. They look for bugs too. Then they decide what's better to rewrite from scratch. There's usually plenty of problematic code. Next they write tests so nothing breaks and check that all parts of the program work normally with each other. In the end, they make it so that customers can use it without problems.

The best AI cleanup companies have a special process for working with AI. Senior engineers plan out how the app should work before any AI writes code. This way the AI-generated code fits the plan better. They build one piece at a time and test each piece as they go instead of building everything at once.  Sometimes they use different AI tools for different jobs. Senior developers put all the pieces together, run tests on the whole app, and fix any problems before anyone sees the code.

AI plus Senior Engineers

These companies have senior programmers and neural networks. Artificial intelligence writes the first version of the code in a few hours. Then senior developers review that code and make it reliable.

By pairing experienced engineers with AI "co-pilot" tools and well-honed processes, these companies can do more with fewer billable hours – savings that get passed to the client.

Instead of an engineer spending a day writing rote code (like writing tests, converting one data format to another, etc.), an AI model can generate most of that code in minutes. The senior engineer's role then shifts to reviewing and refining the AI-generated code. Far fewer human hours are needed for a given scope of work.

AI has freed senior engineers to resolve higher-level issues ten times faster than before. By letting the AI handle the grunt work, a single senior developer can produce the output that might have taken several developers in the past.

These firms assign senior engineers to oversee each step of the AI-assisted development process. AI-generated code serves only as an initial draft. Every line is then tested, reviewed and refined by an expert before it becomes part of the final product. This human oversight catches and corrects bugs, design flaws and security vulnerabilities in the AI code. As a result, clients receive reliable, well-built software more quickly and at lower cost.

The New Economics: Professional Vibe-Coding Software Development

A key reason entrepreneurs seek out these AI-savvy development companies is also the cost. They want the expertise of senior developers, but at a price closer to what they might pay less-experienced coders. The good news for them is that the top cleanup firms have figured out how to dramatically boost senior developer productivity using AI, which in turn lowers the cost of their services.

AI makes coding faster, so projects cost less. You pay for fewer hours of work and get your product out sooner. Projects that used to take six months now take two or three. The quality stays just as good. A project that once cost $200,000 and took six months? Now it's done in two to three months for much less money.

This requires fewer senior developers and less time. The clients get a working product quickly and at a lower cost.

Startups used to need a large team of programmers. Months of work cost a lot of money. AI writes code fast, but the code usually has bugs. Company employees can't fix these problems themselves. So they hire outside experts to clean it up. After that, you need real programmers. They find the bugs and fix them, patch security holes so hackers cannot break in, and make the code stable. Now there are entire teams who take what the neural network has written and turn it into a working product.