AI Can Write Code. But It Can't Build a Business
Everyone is talking about AI.
The instant answers. The lightning-fast code generation. The feeling that you can build a whole app over a weekend.
But almost no one is talking about the trap.
The huge, invisible one that's luring founders and developers into a dead end.
It's a practice I call "vibecoding."
You’ve probably seen it. Maybe you’ve even done it.
It's the act of prompting, copying, and pasting AI-generated code until something looks like it works.
No deep understanding. No real engineering. Just vibes.
And honestly? It’s a disaster waiting to happen.
This isn't an article bashing AI.
It’s a warning that some of the most powerful tools can become the most dangerous crutches.
If you care about building a product that lasts longer than your next demo, keep reading.
Here's why vibecoding is killing your startup — and what to do about it.
Your "Fast" MVP is Actually Just Fragile
Have you ever seen a house of cards?
Looks great. Until you breathe on it.
That’s a vibecoded product. It creates the illusion of speed, but the foundation is pure sand.
Your impressive-looking MVP? It’s a black box. A tangled mess of code that nobody on your team actually understands.
It might work for one user in a demo.
But it will shatter under the weight of a thousand real customers.
And when you need to pivot? Good luck. Trying to change one feature causes a domino effect of failures you can’t predict or fix.
Here's your actionable: stop measuring speed by how fast you can generate code.
Start measuring it by how fast you can confidently change it.
If your team can't explain the code, they can't own it. And if they can't own it, you don't have a product — you have a liability.
You're Taking Out a Loan You Don't Even Know Exists
We all know about technical debt. You cut a corner to move faster, and you plan to pay it back later.
That’s a conscious choice.
AI-driven vibecoding creates something far worse: unconscious debt.
The AI made a decision for you — it picked a certain algorithm, it skipped some error handling, it chose a less-than-optimal path for the sake of simplicity.
And you have no idea what trade-offs were made.
This debt is invisible. It lives in the gap between what the code does and what you think it does.
When the bill comes due — and it always does — you won't even know where to start paying it back.
Want to apply this? Start demanding the "why."
For every piece of AI-generated code, ask: Why this way? What are the other options? What could go wrong here?
If you can't answer those questions, you've just taken out a loan with a truly vicious interest rate.
You're Outsourcing the Most Important Job: Learning
The biggest risk of vibecoding isn't to your code. It's to your people.
By offloading the hard work of thinking to a machine, your team misses the single most important part of building things: the struggle.
Struggle is where the learning happens.
Debugging isn't a chore to get rid of. It’s a workout for the engineering brain.
The process of hunting down a bug, forming a theory, and fixing it builds a deep, unshakable understanding of the system.
Asking an AI to "just fix it" is like asking a calculator to pass your math test.
You get the answer, but you learn nothing.
You're not building a learning culture. You're building a prompting culture.
Tip for you: celebrate the debug.
Treat a tough bug not as a roadblock, but as a masterclass in how your system really works.
The pain of fixing it is the price of admission for genuine expertise.
The Fix: From Code Monkey to Code Master
So how do you use these powerful tools without becoming a mindless prompter?
You get disciplined. You treat the AI not as a vending machine for code, but as a sparring partner for your brain.
Here’s the framework.
1. Generate Like You Mean It.Don't ask vague questions. "Write a login function" is a rookie move. Get specific. Demand certain technologies, error handling, and structure. Force yourself to think like an architect before you even see a line of code.
2. Grill the AI. Relentlessly.This is the game-changer. Take the AI's output and interrogate it.
"Explain line 5. What is this 'bcrypt' thing? Why is it here?"
"You used
async/await. Why not something else? What’s the trade-off?""What are three ways this function could fail in the real world?"
Treat the AI like a tutor you're paying by the hour. Don't let it off the hook until you understand everything.
3. Get Your Hands Dirty.Now, take the code and make it yours. Refactor it. Rename variables. Break it on purpose and then fix it manually. Don’t just feed error messages back into the AI. That’s the lazy way out. Use your own brain. This is where the knowledge sticks.
4. Zoom Out.Once you've mastered the piece, figure out how it fits into the whole puzzle. How does this module talk to the others? Does it create a security risk? You need to be a system builder, not just a component assembler.
This isn't just a process. It's a mindset.
And it’s creating a new kind of superstar.
Meet the AI-Native Engineer
This new approach is giving rise to a different kind of developer.
They might not have a fancy degree. But they have meta-skills that are becoming way more valuable.
They learn insanely fast.
They are expert critics, able to spot flaws in code they've never seen before.
They use AI for the grunt work, saving their brainpower for architecture and strategy.
Want a real takeaway? Audit your hiring.
Stop asking people to write code on a whiteboard. Instead, give them a flawed piece of AI-generated code.
Then ask them to critique it, fix it, and explain it.
You’ll learn more about their real skills in 10 minutes than in a 2-hour-long traditional interview.
Conclusion
AI is a tool. A powerful one.
But it’s not a substitute for thinking.
Vibecoding is easy. Building real, lasting value is hard.
The choice is yours.
So, what are you building? A team of prompters, or a team of problem-solvers?