Everyone is shipping fast right now, really
You describe a feature in plain English, Lovable or Bolt or Cursor spits out a working Next.js app in 20 minutes, you deploy to Vercel, share the link, and it looks genuinely good. The UI works. The buttons click. The forms are submitted. The demo is clean.
And then six weeks later, you are sitting across from a founder who can’t figure out why their app went down, why their users’ data is leaking, or why nobody can touch the codebase anymore without breaking three other things.
I’ve been in this situation more times than I want to count. Not as the person who built the broken thing. As the person called in after.
This is what vibe coding actually costs. And almost nobody is talking about it honestly.
The 80/20 wall is real, and it’s brutal
Here is what the tools don’t tell you: AI gets you to 80% very fast. The UI looks right. Core features work. You can demo it to investors, clients, and your co-founder. Everyone impressed.
The last 20% is where the architecture either succeeds or fails. Edge cases. Concurrent users. Real data that doesn’t behave the way your test inputs did. Third-party APIs that go down. Authentication flows must be airtight. Payment logic that can’t have a bug at 2am.
That last 20% requires someone who actually thought through the system before building it. Not someone who prompted their way to a working screen.
AI writes code that solves the immediate problem in front of it. It doesn’t reason about how that code sits inside everything else, how it will behave under load, or what breaks three layers down when an edge case hits. That is not a tool limitation. That is a fundamental difference between generating code and engineering a system.
What’s actually happening in production
The numbers are not theoretical anymore.
Around 45% of AI-generated code contains vulnerabilities from the OWASP Top 10 cross-site scripting, broken authentication, SQL injection, and the basics. Not exotic attack vectors. The stuff every developer is supposed to catch before shipping.
A startup called Enrichlead built its entire lead generation platform using Cursor. The UI was polished. The product worked. But the AI had put all security logic on the client side, which means users could change a single value in their browser console and get free access to all paid features. Within 72 hours of launching, the exploit was found. The founder was staring at 15,000 lines of AI-generated code he couldn’t audit. The company shut down.
In early 2026, a vibe-coded app exposed 1.5 million API keys and 35,000 user email addresses through a misconfigured database. The founder had not written a single line of code manually.
These are not cautionary tales from careless developers. These are what happens when the architecture layer gets skipped because nobody thought it was necessary.
The technical debt nobody sees coming
Here is the quieter version of the same problem.
Vibe-coded projects accumulate technical debt roughly three times faster than traditionally written ones. Not because the code looks wrong, it usually looks fine. Because there is no documentation, no test coverage, and no architectural coherence. Nobody designed the system. The AI improvised it, component by component, prompt by prompt.
The codebase works until someone needs to change something. Then they discover that nothing is separated properly, business logic is tangled into UI components, API calls are happening in the wrong places, and the database schema makes sense only if you trace every prompt that created it.
At that point, the cost of maintenance starts exceeding the cost of a rebuild. And the rebuild is expensive because half the logic exists only in a series of chat sessions nobody kept.
Industry analysts are projecting $1.5 trillion in accumulated technical debt by 2027 from AI-generated code. That number is going to be real money that real companies have to spend cleaning up things that looked fine on launch day.
The actual problem is not vibe coding
I want to be clear about something: I’m not against AI-assisted development. I use it. It’s genuinely changed what a single developer can output. The speed is real.
The problem is the removal of architectural thinking from the process entirely.
Vibe coding as a prototyping tool is excellent. You get from idea to testable thing faster than any other method available. That’s valuable. Use it.
Vibe coding as a production methodology, where the system architecture is whatever the AI decided to generate, security is whatever the AI remembered to include, and the data model is whatever made sense for the first prompt, that’s where the failures are building up
The developers who are actually winning with these tools right now are not the ones who fully gave in to the vibes. They are the ones who use AI for the heavy lifting but never stop thinking about the system underneath. They design first. They prompt second. They review before they ship. The AI writes the code, but a human decides what the code needs to do and how it needs to sit inside everything else.
That distinction is not obvious when you’re watching a demo. It’s extremely obvious when something breaks.
What I have been doing differently
Every project I take on, whether it’s a full AI implementation, an automation infrastructure, or a web application, starts the same way: mapping the system before writing a single line.
Not a Notion doc with bullet points. An actual architectural map. What data goes where? What happens when it fails? What the load looks like at 10x current usage. Where the security boundaries are. How each component talks to every other component.
This process is not exciting. It doesn’t make a good demo. Nobody posts about it on LinkedIn because there’s nothing to show. But it’s the reason the things I build don’t fall apart after the initial excitement wears off.
If you are a founder or a technical lead who is sitting on a vibe-coded product that you already know is held together by good luck and a deployment that has not hit anything unexpected yet, the time to look at the architecture is now. Not when something breaks. Not when a user finds the vulnerability. Now.
Because the cleanup after is always more expensive than the review before.
If this hit close to home
I work with startups, agencies, and businesses that are either building AI-powered systems from scratch or cleaning up ones that were built fast and are now showing cracks. If you are in either situation, I’m happy to talk, not a pitch, just a technical conversation about where things actually are.
You can reach me at hi@hanzala.co.in or just message me directly.