From Miracle to Mirage: The Truth Behind “Vibe Coding”
Last updated: November 01, 2025 Read in fullscreen view
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There was a time when becoming a programmer meant years of learning, thousands of lines of code, and countless sleepless nights. Today, all it takes is a few conversations with AI — and suddenly, people are building apps, writing programs, even launching startups. The world calls this Vibe Coding — programming by inspiration.
It’s been hailed as a miracle — a creative revolution that frees humanity from tedious coding. But behind that miracle lies a hidden cost few dare to mention. So today, let’s peel back the illusion and ask:
Is Vibe Coding truly a revolution — or a dangerous dream wrapped in hype?
The Rise of a “Magical” New Era
Not long ago, building a mobile app was a distant dream. Now, anyone can simply tell AI:
“Create a dating app called T.”
And in seconds, streams of code pour out like magic. Within an hour, the app is ready. It feels like sorcery — or perhaps, the gold rush of the 21st century.
This movement has many names — prompt programming, no-code, AI-assisted coding — but one phrase captured the cultural vibe perfectly: Vibe Coding.
The term was coined casually by Andréj Karpathy, one of the bright minds behind OpenAI. He described it simply:
“There’s this new kind of coding I call vibe coding — you just go with the flow, follow the vibe, and forget that code even exists.”
But buried in his offhand remark was a subtle warning:
“I just copy, paste — and it mostly works.”
That word — mostly — went unnoticed. Then came the explosion. Suddenly, Vibe Coding wasn’t just a tool. It was a promise: that anyone, without knowing data structures or algorithms, could become a creator.
Startups sprang up overnight, generating ten or fifteen apps a day. Big Tech joined in — Microsoft embedded Copilot everywhere, Google rolled out its own tools, and AI-generated code began infiltrating everyday systems.
It felt like liberation from syntax and logic. But like every gold rush, behind the glitter lies dirt, crude tools — and hidden dangers.
The Hidden Price of “Magic”
Every magic trick has a cost — and Vibe Coding’s price tag is only starting to surface.
We’ve been obsessed with how fast AI can write code, but forgot to ask:
“Does it actually understand what it’s writing?”
To understand the problem, we must look inside the machine.
A large language model (LLM) isn’t a logical engine — it’s a probability machine.
Its job isn’t to reason — it’s to guess which word (or line of code) statistically makes sense next, based on billions of examples it’s seen online.
When AI gives an answer, it doesn’t ask “Is this true?”
It asks, “What sounds most plausible?”
It’s a brilliant actor who’s memorized every script — but doesn’t understand a single line.
That’s why hallucinations happen — AI confidently invents fake functions, imaginary menus, or code snippets that don’t exist. Not because it’s broken, but because it’s designed to sound right, not be right.
And here’s the dangerous twist: these models are rewarded for confidence, not accuracy. Saying “I don’t know” gets zero points. Making a confident guess gets rewarded. Repeat that millions of times — and you get a machine that would rather lie persuasively than admit uncertainty.
When Code Becomes Digital Pollution
This is how the internet is filling up with what experts call AI Slop —
mountains of low-quality code, articles, and images that look fine on the surface but hide structural chaos underneath.
Take the story of the dating app “T.” It was built mostly by AI, and it worked — until it didn’t.
A massive hack leaked 72,000 private photos. The cause?
A simple database misconfiguration — the kind any junior developer could have spotted.
But the “vibe coder” trusted AI blindly. And AI, in turn, had learned from the open web — where 95% of public code is garbage.
Worse, AI doesn’t know why something is wrong. It only imitates patterns — even dangerous ones.
That’s how hard-coded API keys, bad security practices, and unsafe logic get copied and multiplied at scale.
A study from Stanford revealed a chilling pattern:
Developers who used AI assistants wrote less secure code — yet felt more confident in it.
This combination — low competence, high confidence — is a recipe for disaster.
The Generation We’re Losing
Here lies the most human tragedy of all.
Senior engineers used to assign tedious tasks — debugging, writing unit tests, fixing minor bugs — to junior devs.
Those weren’t chores. They were training grounds — the dojo where intuition and discipline were built.
Now, those tasks are handed to AI.
The result? A generation of “vibe coders” who can prompt, copy, and paste — but have no idea how to fix a system when it breaks.
In 5–10 years, the tech industry may face a massive talent gap:
AI isn’t just threatening programming jobs — it’s threatening craftsmanship itself.
The Fall of an Illusion
So, has Vibe Coding collapsed?
Not exactly. AI is still here — and it remains a powerful tool.
What’s collapsing is the illusion — the fantasy of effortless magic.
Companies are realizing that “AI-generated code” isn’t cost-saving — it’s technical debt in disguise.
Cleaning up AI mess often costs more than writing clean code from scratch.
The future of programming won’t be “no-code.”
It will be smart-code — written faster with AI assistance, but understood deeply by humans.
AI can suggest, accelerate, and automate.
But the pilot — the one with context, judgment, and ethics — must always be human.
Because in the end, the most powerful tool isn’t artificial intelligence.
It’s human understanding — the ability to not just predict the answer, but to truly grasp the question.
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