Whether you’re streaming a show, paying

bills online or sending an email, each of these actions

relies on computer programs that run

behind the scenes. The process of writing computer programs is known as coding. Until recently, most computer code was written, at least originally, by human beings. But with the advent of generative artificial intelligence, that has begun to change.

Now, just as you can ask ChatGPT to spin up a recipe for a favorite dish or write a sonnet in the style of Lord Byron, you can now ask generative AI tools to write computer code for you. Andrej Karpathy, an OpenAI co-founder who previously led AI efforts at Tesla, recently termed this “vibe coding.”

For complete beginners or nontechnical dreamers, writing code based on vibes – feelings rather than explicitly defined information – could feel like a superpower. You don’t need to master programming languages or complex data structures. A simple natural language prompt will do the trick.

How it works
Vibe coding leans on standard patterns

of technical language, which AI systems use to piece together original code from their training data. Any beginner can use an AI assistant such as GitHub Copilot or Cursor Chat, put in a few prompts, and let the system get to work. Here’s an example:

“Create a lively and interactive visual experience that reacts to music, user interaction or real-time data. Your animation should include smooth transitions and colorful and lively visuals with an engaging flow in the experience. The animation should feel organic and responsive to the music, user interaction or live data and facilitate an experience that is immersive and captivating. Complete this project using JavaScript or React, and allow for easy customization to set the mood for other experiences.”
But AI tools do this without any real grasp of specific rules, edge cases or security requirements for the software in question. This is a far cry from the processes behind developing production-grade software, which must balance trade-offs between product requirements, speed, scalability, sustainability and security. Skilled engineers write and review the code, run tests and establish safety barriers before going live.

But while the lack of a structured proces

s saves time and lowers the skills required to code, there are trade-offs. With vibe coding, most of these stress-testing practices go out the window, leaving systems vulnerable to malicious attacks and leaks of personal data.

And there’s no easy fix: If you don’t understand every – or any – line of code that your AI agent writes, you can’t repair the code when it breaks. Or worse, as some experts have pointed out, you won’t notice when it’s silently failing.

The AI itself is not equipped to carry out this analysis either. It recognizes what “working” code usually looks like, but it cannot necessarily diagnose or fix deeper problems that the code might cause or exacerbate.


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