Vibe Coding

Vibe Coding Is a Myth

 

The most dangerous lie in tech right now is not that AI will replace developers. 

It is the quieter claim that thinking no longer matters.
 
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Vibe coding is sold as freedom. As evolution. As proof that we have finally escaped the “hard parts” of software engineering. You describe intent. The machine does the work. The friction disappears. You ship faster. You feel powerful.
 
But there is an assumption hiding underneath this story that nobody wants to say out loud.
 
That the act of thinking itself is overhead.
 
That reasoning is a bottleneck.
That struggle is inefficiency.
That understanding is optional as long as output exists.
 
This is not a tooling shift. It is a philosophical one.
And if it is wrong, the consequences are not small.
 
Because when a society decides that thinking is no longer required, it does not become more intelligent. It becomes dependent.
 
Vibe coding is not a new programming paradigm.
It is a rebranding of cognitive outsourcing.
And outsourcing always comes with a balance sheet.
 

Why vibe coding feels irresistible

 
We need to be honest before we can be critical.
 
Vibe coding feels incredible.
You bypass syntax.
You skip boilerplate.
You avoid the frustration that used to define early-stage development.
You go from idea to artifact in minutes.
 
Your brain loves this for very specific reasons.
 
First, it drops you straight into flow. No warm-up. No resistance. Humans are wired to seek flow because it feels like competence, even when the competence is borrowed.
 
Second, the feedback loop is instant. Prompt. Result. Prompt. Result. That rhythm is intoxicating. It mirrors the same neurological patterns that make slot machines and social feeds addictive.
 
Third, it validates a comforting belief. That intelligence is about intention, not execution. That if you can describe the idea, you deserve the outcome.
 
This is where the danger begins.
 
Because effort is not just a cost. It is a signal.
 
And when you remove effort entirely, you remove the signal that tells your brain something is worth encoding deeply.
 

Cognitive liquidation, not augmentation

 
Your brain is not a neutral observer. It adapts to how it is used.
 
Neuroplasticity is simple at its core.
The pathways you use strengthen.
The pathways you ignore weaken.
 
When you debug a system manually, you are not just fixing bugs. You are training your brain to hold complexity, reason across layers, and tolerate ambiguity.
 
When you consistently outsource that reasoning to a model, your role changes. You are no longer constructing mental models. You are selecting outputs.
 
Selection feels like intelligence.
But it does not build capacity.
 
This is what cognitive liquidation looks like. You trade long-term mental assets for short-term speed. Not because you are lazy, but because the system rewards it.
 
Over time, you still feel productive. You still ship. But your ability to operate without the tool erodes quietly.
 
The scariest part is not that you become slower without AI. It is that you become uncomfortable thinking without it.
 

The prompt engineering illusion

 

Prompt engineering is marketed as a new skill. A democratic one. Anyone can learn it. Anyone can build.

This is only half true.

Prompt engineering works when it compresses existing understanding. A good prompt is not magic language. It is architecture expressed in English.

A person who understands systems knows what constraints to specify, what tradeoffs matter, and what outputs to reject. A person who does not understand the system cannot do this, no matter how fluent they are in prompting.

Without architectural understanding, prompts become wishes. And wishes scale poorly.

The model will give you something that looks correct. It will often run. That is not the same as being safe, maintainable, or coherent under stress.

This is how we end up with developers who can generate code but cannot reason about failure, builders who can ship fast but cannot debug slow.

We are not creating engineers. We are creating operators of abstraction they do not own.

Where vibe coding actually works

 

This is not an argument for rejecting AI.

Vibe coding is powerful in the early stages. Exploration. Prototyping. Learning. Solo work. These are real gains.

AI lowers the cost of curiosity. That matters.

But here is the line nobody wants to draw.

The moment a system needs to be understood rather than demonstrated, vibe coding stops being a strength.

Production systems are not vibes. They are invariants. They are edge cases. They are failure modes.

And failure does not care how fast you shipped.

The cost nobody wants to price in

 

There is the obvious dependency problem. When the tool goes down, so does your confidence.

There is false competence. Shipping something that works feels identical to understanding it, until it breaks.

There is the environmental cost. Large-scale AI infrastructure consumes energy and water at a level we are still pretending is abstract. Every regenerate button has a physical footprint. At scale, this is not nothing.

But the deepest cost is psychological.

Struggle is how humans build judgment. When struggle disappears, judgment atrophies. You get faster, but shallower. More confident, but less capable under uncertainty.

This is not a moral failure. It is a design consequence.

The myth of vibe-coded success

 

You have seen the posts.

I vibe coded an app. Now it prints money.

What is rarely mentioned is the invisible foundation. Years of engineering intuition. Product sense. Distribution knowledge. Taste.

AI did not replace that. It hid it.

When an experienced developer vibe codes, they are still thinking. They are just thinking faster. When an inexperienced one does the same, they are skipping the thinking entirely.

These are not equivalent acts.

If a system requires an experienced engineer to make it safe after the fact, then the vibe was never the source of value. The human was.

How not to disappear inside your tools

 

If you are going to use AI, use it adversarially.

Ask it to critique your ideas before building. Force it to expose flaws, not just generate output.

Explain the code back to yourself. If you cannot explain most of it, delete it. Ownership begins with understanding.

Use AI as a sparring partner. Not a brain replacement.

And sometimes, deliberately choose friction. Write without assistance. Debug manually. Keep your cognitive muscles alive.

This is not about purity. It is about survival.

The part nobody wants to end on

 

Nobody knows where this goes.

Maybe software engineering becomes something else entirely. Maybe we adapt. Maybe new skills emerge that we cannot see yet.

But one thing is consistent across every technological shift in history.

What we stop practicing, we lose.

Vibe coding is not dangerous because it is powerful. It is dangerous because it convinces us that thinking is optional.

And once a generation internalizes that belief, no tool can bring the skill back.

So here is the question that actually matters.

If the tools disappeared tomorrow, would you still know how to reason your way through a hard problem? Or have you already sold that ability for speed?

That is not a technical question. It is a human one.

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