Vibe Coding Problems are Popping Up
This is a summary of a video I published on YouTube. You can click on the link below to watch the full video.
The 80% Trap Is Where People Get Stuck
I keep seeing the same pattern with vibe coding. People move fast, generate a ton of code, and get something that looks like a working app. It feels like real progress.
Then they hit the wall.
That last 10–20%—the part that actually makes the software complete, stable, and usable—is where everything breaks down. And if you don’t understand how systems are put together, you’re not getting past it.
Half-built software has no value. It doesn’t matter if 80% works. If it crashes, leaks data, or can’t be extended, it’s useless in the real world.
Working Code Isn’t the Same as Good Code
There’s another version of this problem. Sometimes the app does “work.” You can click around, data saves, things happen.
But under the hood, it’s fragile, messy, and full of holes.
I’ve seen this before—early PHP days. Non-developers building real apps that technically worked, but were a nightmare to maintain and full of security issues. It took years for that ecosystem to clean itself up.
We’re seeing the same thing now with AI-generated code.
And companies are noticing.
Companies Aren’t Banning AI—They’re Controlling It
No, companies aren’t blocking vibe coding across the board. But they are tightening things up.
Why? Because a lot of AI-generated code fails basic security and quality checks. That’s not a small issue.
So the response is predictable:
- More code reviews
- Stricter guidelines
- Less tolerance for blindly shipping generated code
In many cases, AI is fine for prototypes or internal tools. But when it comes to core systems, developers are expected to understand every line they ship.
You own the code—even if AI wrote it.
The Real Divide: Mechanics vs Judgment
Here’s what separates people who benefit from AI and people who get stuck.
Experienced developers use AI to speed up execution. They already understand architecture, separation of concerns, and how systems behave under stress.
So when AI gives them code, they can evaluate it, reshape it, and fit it into a larger design.
Others rely on AI to make decisions for them—and that’s where things fall apart.
AI can generate code. It cannot replace judgment.
Where Vibe Coding Actually Fits
There is a place for this approach, and it’s a useful one if you stay within its limits.
- Quick prototypes
- Throwaway experiments
- Internal utilities
- Exploring ideas
That’s where it shines. Fast, loose, and low risk.
But if you’re building anything serious—especially systems handling real users or sensitive data—you need fundamentals. Structure, state management, API design, and clear logic.
Without that, you’re just stacking code you don’t fully understand.
The Takeaway
The issue isn’t AI. It’s how people are using it.
If you don’t understand how software is built, AI will take you far enough to get into trouble—but not far enough to finish the job.
And that’s where the wasted time really starts to hurt.
Learn how systems work. Then use AI to go faster.
Watch the video on YouTube here 👉 Vibe Coding Problems are Popping Up
Thanks for reading!
Stef