The internet is losing its mind over vibe coding. Managers are ecstatic. Non-technical founders are spinning up startups in a weekend. Everyone's an architect now — just ask Claude to build your SaaS and deploy by Friday.
But here's the uncomfortable truth nobody wants to hear: vibe coding is the new technical debt factory, and most people celebrating it have never shipped anything that needed to survive past a demo.
We at Gerus-lab have built 14+ production systems — from Web3 protocols to AI-powered SaaS platforms. We've seen the vibe-coded prototypes land on our desk with a note that says "just clean it up a bit." Spoiler: "a bit" means rewriting everything from scratch.
Let's talk about why.
The Illusion of Productivity
The core argument for vibe coding goes like this: "I described what I wanted in plain English, and the AI built it. Why do I need developers?"
This is like saying, "I told my friend to build me a house, and he stacked some bricks. Why do I need an architect?"
Sure, you got bricks. But do you have load-bearing walls? Plumbing? Electrical that won't burn the place down? A foundation that handles the local soil conditions?
The gap between "it works on my screen" and "it works in production under load with real users doing unpredictable things" is enormous. And that gap is exactly where professional engineering lives.
A recent Habr article titled "Vibe Code Quieter, Please!" made waves in the Russian-speaking dev community with a simple observation: everything AI coding tools do today was already possible before. We had pandas for data analysis. We had CMS platforms and no-code builders. We had Stack Overflow. The difference isn't capability — it's accessibility wrapped in hype.
The Real Cost of "Free" Code
Let's do some math that vibe coding evangelists conveniently skip.
Scenario: You prompt an AI to build a customer dashboard. It generates 2,000 lines of React code in 20 minutes. You're thrilled.
Week 1: You realize it doesn't handle edge cases — empty states, error boundaries, loading states for slow connections. You prompt more fixes. The codebase grows to 5,000 lines.
Week 2: A user reports that the dashboard breaks on mobile. The AI-generated CSS is a maze of absolute positioning and magic numbers. You spend 3 days prompting fixes that break other things.
Week 3: You need to add authentication. The AI bolts on a solution that stores tokens in localStorage (a security vulnerability). You don't know this because you're not a security engineer.
Month 2: You have 15,000 lines of code that nobody — including the AI — fully understands. You hire a developer to "just clean it up." They estimate 3 months to rebuild it properly.
We've seen this exact pattern at Gerus-lab across a dozen client engagements in 2025 alone. The "free" vibe-coded prototype ends up costing 2-3x what a proper build would have cost from day one.
Why Managers Love It (And Why That's Dangerous)
Here's an observation that resonates deeply with our experience: the people most excited about vibe coding are almost always non-technical.
Why? Because they see code being generated and think value is being created. More lines = more progress. It's the same cognitive bias that made people think blockchain would revolutionize everything from supply chains to voting systems.
Managers love vibe coding because:
- It feels like control. They can "see" the code being written.
- It eliminates the knowledge gap. They no longer need to trust engineers' estimates.
- It's fast. Speed feels like productivity, even when it isn't.
But here's what they miss: the hardest part of software engineering was never writing code. It's understanding the problem, designing the architecture, handling failure modes, planning for scale, and maintaining the system over years.
As the old saying goes: a sufficiently detailed specification IS the code. If you can describe your system precisely enough for an AI to build it correctly, congratulations — you've just done the hard part of programming. You've simply used English instead of Python.
The Spam Generation Problem
One of the most alarming side effects of the vibe coding movement is the flood of low-quality software hitting the market.
Think about it: if anyone can build an app in a weekend, everyone will. And most of those apps will be terrible. Not because AI is bad at coding, but because the people building them don't understand:
- User experience design — Why does this button go here? What happens on a 320px screen?
- Data modeling — How does this scale from 100 to 100,000 users?
- Security — Is this SQL injection proof? Are API keys exposed in the frontend?
- Accessibility — Can a screen reader navigate this? Does it meet WCAG standards?
- Performance — What happens when the database has a million rows?
We're entering an era of software doorways — remember those SEO spam pages from the 2000s? Vibe-coded apps are the software equivalent. A flood of barely functional products that clutter app stores and GitHub repos.
At Gerus-lab, we've started seeing clients come to us specifically because they tried the vibe-coding route first. They have a "working" prototype that crashes under 50 concurrent users, has no test coverage, and is built on architectural decisions that make no sense. The rebuild cost? Always higher than building correctly from scratch.
When AI Coding Actually Works
Before you think we're anti-AI — we're absolutely not. We use AI tools daily at Gerus-lab. The difference is HOW we use them.
AI coding tools are genuinely powerful when used by people who already understand what they're building:
1. Boilerplate Acceleration
Need a standard CRUD endpoint? An API client? A database migration? AI can scaffold these in seconds, and an experienced developer can review and refine them. This saves real time.
2. Documentation and Testing
AI is surprisingly good at generating test cases and documentation for existing code. At Gerus-lab, we use AI to generate initial test suites that cover edge cases our developers then refine.
3. Code Review Assistance
Having AI review pull requests catches trivial issues — typos, missing null checks, inconsistent naming — freeing human reviewers to focus on architecture and logic.
4. Exploration and Prototyping
When you're exploring a new library or API, AI can generate quick examples that help you understand the interface. This is genuinely useful.
5. Translation Between Languages
Need to port a Python script to Go? AI does this remarkably well for straightforward code. An engineer still needs to review it, but the starting point is solid.
The pattern is clear: AI amplifies existing expertise. It doesn't replace it. A skilled developer with AI tools is a force multiplier. A non-developer with AI tools is a liability with a GitHub account.
The Uncomfortable Parallel: Crypto and NFTs
Remember 2021? Everyone was going to be a millionaire minting NFTs. Artists who spent decades honing their craft watched as procedurally generated apes sold for more than their life's work.
Two years later? The NFT market collapsed. The artists remained. The craft remained. The get-rich-quick crowd moved on to the next shiny thing.
Vibe coding is following the exact same trajectory:
- Hype cycle: "Everyone can code now! Developers are obsolete!"
- Reality check: Production systems built by non-developers start failing
- Correction: Companies realize they still need engineers, but now with AI skills
- New normal: AI becomes another tool in the professional toolkit
We're currently between phases 1 and 2. The correction is coming, and it will be painful for companies that bet everything on vibe coding.
What This Means for Your Business
If you're a founder or manager reading this, here's our honest advice from building production systems for 14+ clients:
Don't skip the engineering. Use AI tools to accelerate development, but invest in people who understand what they're building. The cost of doing it right is always less than the cost of doing it twice.
Prototype fast, but rebuild properly. There's nothing wrong with using AI to validate an idea quickly. Just don't mistake the prototype for the product.
Hire engineers who use AI, not AI that replaces engineers. The best developers in 2025-2026 are the ones who leverage AI as a power tool, not the ones who are being replaced by it.
Be skeptical of \"10x productivity\" claims. If someone tells you AI made them 10x more productive, ask them: 10x more productive at what? Writing code that nobody reviewed? Shipping features with no tests? Generating technical debt faster than ever before?
The Bottom Line
Vibe coding is real. AI coding tools are genuinely useful. But the narrative that "anyone can build software now" is as dangerous as "anyone can perform surgery now because we have YouTube tutorials."
The tools changed. The fundamental challenges of building reliable software did not.
At Gerus-lab, we embrace AI in our workflow every single day. But we also understand that the value we bring isn't typing code faster — it's making the right architectural decisions, anticipating failure modes, and building systems that work reliably for years after deployment.
The future isn't developers vs. AI. It's developers WITH AI vs. everyone who thought they could skip the "developer" part.
And if you're sitting on a vibe-coded prototype that needs to become a real product? We've done this before. Let's talk.
Gerus-lab is an engineering studio specializing in Web3, AI, SaaS, and automation solutions. With 14+ delivered projects, we help teams build software that actually works in production. Visit gerus-lab.com to see our cases.
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