The Dark Side of “Vibe Coding”: Why AI-Generated Code Is a Trap

There’s a seductive illusion spreading through the tech industry right now. Executives announce layoffs claiming AI can handle the work. Developers share stories of building “10x faster” with AI coding agents. Conference talks extol the virtues of “vibe coding”—the art of prompting AI to generate vast quantities of complex code without actually reading it yourself.

It sounds revolutionary. It’s actually dangerous.

What Is Vibe Coding, Really?

Coined (or at least popularized) in the AI era, vibe coding refers to creating large quantities of highly complex AI-generated code with the intention that the code will never be read by humans. You describe what you want, the AI writes it, and you move on. The promise is seductive: why waste time learning programming when an AI can do it for you?

But here’s what happens in practice. Renowned developer Armin Ronacher recently documented his experience with AI coding agents in a post titled “agent psychosis.” After two months of “excessively prompting the thing and wasting tokens,” he found himself with a ton of tools he didn’t actually use, many of which didn’t work as intended. He described feeling really great about tools he built, only to realize later they were useless.

This should sound familiar to anyone who’s spent hours gambling.

The Slot Machine Metaphor

Psychologists have studied a phenomenon called “dark flow”—a corrupted version of the positive psychological state known as “flow.” Originally formalized by Mihaly Csikszentmihalyi in the 1970s, flow describes that optimal state where your skills are perfectly matched to the challenges at hand. It’s when you’re fully absorbed in productive work and performing at your best.

But there’s a darker version. Modern slot machines are engineered to create flow-like states while actually draining your resources. They use “Loss Disguised as Win”—when you gamble 20 cents and receive 15 cents back, the machine celebrates like you won. This creates a false positive feedback loop that keeps players absorbed even while losing money.

Vibe coding works the same way. The AI produces hundreds of lines of code. It “works.” You feel productive. But months later, you discover hidden bugs, can’t make simple modifications, or find the entire program crashes unexpectedly. The celebratory noise of code being generated masks the actual loss of productivity.

The Productivity Mirage

A study from METR found something startling: when developers used AI tools, they estimated they were working 20% faster. In reality, they worked 19% slower. That’s nearly a 40% gap between perceived and actual productivity. Developers genuinely believed AI was helping them—they just couldn’t accurately judge their own work.

This aligns with what Jeremy Howard warned: “People who go all in on AI agents now are guaranteeing their obsolescence. If you outsource all your thinking to computers, you stop upskilling, learning, and becoming more competent.”

The Failed Predictions

Tech CEOs have been promising AI would replace developers for years. Geoffrey Hinton predicted AI would replace radiologists by 2021. Google executives predicted neural architecture search would automate data science by 2023. Anthropic’s CEO predicted AI would write 90% of all code by late 2025.

None of these materialized. The predictions continue because they serve a purpose—scaring companies into investing in AI tools and pressuring developers to adopt them. But the gap between promise and reality remains vast.

What AI Actually Can’t Do

AI coding agents can produce syntactically correct code. But they don’t create useful abstractions or meaningful modularization. They don’t value conciseness or improve code organization in large codebases. We’ve automated coding, but not software engineering.

Similarly, AI can produce grammatically correct text. But it doesn’t sharpen your ideas or help you identify the heart of what you’re trying to say. It produces plausible-sounding output, not genuinely useful thought.

The Path Forward

AI is genuinely useful. I’ve seen it accelerate work when used thoughtfully—as a tool that augments human expertise rather than replacing it. The key distinction is whether you’re using AI to enhance your skills or to avoid developing them.

If you’re vibe coding because you want to avoid learning, consider what happens if the predictions are wrong. What if, a year from now, you haven’t developed your skills but AI “Agents” still can’t handle complex software engineering? You’re left with code you don’t understand and abilities you never built.

The alternative is to use AI as a multiplier for skills you already have. Let AI handle the boilerplate while you focus on architecture, design, and understanding. Stay in control. Keep learning. The AI tools will improve—but so should you.

Based on analysis of “Breaking the Spell of Vibe Coding” – fast.ai