Just yesterday, humanity feared that AI would take programmers’ jobs.
Today, humanity fears a financial app built by someone who asked ChatGPT yesterday:
“So… what exactly is a backend?”
Welcome to the era of vibe coding — a development approach where architecture is replaced by intuition, testing by hope, and the phrase “it kinda works” is considered a complete QA process.
Vibe-coding enthusiasts confidently proclaim:
“Now anyone can build software.”
And technically, they’re right.
In the same way that anyone can buy a scalpel — but that still doesn’t make them a neurosurgeon.
Vibe Coding: When MVP Becomes MMP
(Minimum Maintainability Problem)
The concept of vibe coding is beautifully simple:
- Open an AI assistant.
- Type: “Build me Uber, but for capybara walking.”
- Hit Accept All.
- Get an application.
- Discover a week later that your database is publicly accessible with no authentication.
Modern LLMs are indeed impressive at generating code quickly.
But there’s one small issue:
They generate code, not engineering.
Recent industry analyses repeatedly show that AI-generated code often suffers from:
- technical debt accumulation,
- security vulnerabilities,
- poor scalability,
- lack of architectural consistency,
- and catastrophic long-term maintainability.
In simpler terms: AI can help you build a house.
Nobody promised it would have a foundation.
“I’m Not a Programmer, but AI Built Everything”
This is the favorite sentence of vibe coders.
It’s usually spoken about 15 minutes before the first SQL injection attack.
The problem isn’t AI itself.
The problem is that:
- without understanding architecture, you cannot evaluate solution quality;
- without database knowledge, you cannot design reliable systems;
- without security expertise, you cannot identify vulnerabilities;
- without engineering experience, you cannot maintain a growing product.
AI does not tell beginners why a solution is bad.
It simply suggests the next one with tremendous confidence.
That’s why studies increasingly highlight a paradox: developers using AI tools often produce less secure code while simultaneously becoming more confident in its reliability.
It’s like a GPS occasionally suggesting you drive into a river — but doing so with such confidence that you start questioning whether bridges are real.
Scalability? Never Heard of It
Vibe coding works wonderfully… while the project is small.
The problems begin approximately when:
- a second developer joins,
- the number of files exceeds the number of browser tabs,
- business logic needs to change,
- traffic appears,
- real users arrive,
- someone mentions the word “compliance.”
That’s when everyone discovers:
- business logic is scattered across 47 files,
- the same code is duplicated six times,
- the API somehow calls itself,
- authentication is checked “somewhere in the frontend,”
- and changing one button breaks the payment system.
AI is exceptionally good at generating local solutions.
It is significantly worse at maintaining long-term system architecture.
Which is why many AI-generated prototypes resemble garage startups built entirely on energy drinks and panic-driven deadlines.
Low-Code: Boring, Reliable, Predictable
Now comes the truly ironic part.
While vibe coders proudly “build SaaS products overnight,” low-code platforms have quietly been solving actual business problems for years:
- rapidly building applications,
- ensuring maintainability,
- preserving scalability,
- enforcing security,
- and standardizing architecture.
Yes, low-code is less glamorous.
You rarely hear someone say:
“Bro, I vibe-coded a CRM for an oil corporation overnight.”
But what you usually do get is:
- architectural governance,
- standardized patterns,
- access control,
- integrations,
- compliance tooling,
- CI/CD pipelines,
- proper database management,
- and maintainable codebases.
Low-code does not attempt to replace engineering with “good vibes.”
It automates repetitive work within engineering constraints.
Which is precisely why enterprises choose low-code platforms for production systems instead of hiring “Senior Prompt Engineer Fullstack Visionaries.”
The Most Expensive Line of Code Is the One Generated for Free
The biggest problem with vibe coding is the illusion of cheapness.
At first, everything appears free and instantaneous.
Then reality arrives:
- endless refactoring,
- vulnerability hunting,
- architectural rewrites,
- database migrations,
- performance degradation,
- scalability limitations,
- and a complete rewrite six months later.
Industry experts increasingly note that AI-generated code may pass immediate tests, yet gradually deteriorates as the project evolves and becomes progressively harder to maintain.
It resembles buying an ultra-cheap suitcase:
- it looks fantastic in the store,
- its wheels fall off at the airport,
- and eventually you carry everything by hand.
Vibe Coding Is Not Replacing Low-Code. It’s the New Excel.
And here lies the key conclusion.
Vibe coding will not destroy low-code.
For the same reason Excel never replaced accountants.
AI is excellent for:
- prototyping,
- generating templates,
- automating repetitive tasks,
- accelerating development,
- building MVPs,
- and creating internal tools.
But production software development is not about “making it work.”
It’s about:
- reliability,
- maintainability,
- security,
- architecture,
- scalability,
- and accountability.
And until neural networks start taking responsibility for:
- data leaks,
- production outages,
- compliance violations,
- and 3 AM client calls,
software engineering is not going anywhere.
Final Thoughts
Vibe coding is a fantastic tool.
Right up until people begin treating it as a replacement for system engineering.
Because:
- an application is not merely a collection of screens;
- backend systems are not “magic behind APIs”;
- architecture is not a mood;
- and security is not a vibe.
Low-code automates development.
Vibe coding automates technical debt generation.
And honestly, that may be one of the most impressive technological achievements of recent years.