AI Vibe Coding: Engineers’ Secret to Fast Development

“Wait! Am I a vibe coder?”

That was my reaction to Andrej Karpathy’s viral post describing his new “vibe coding” workflow. On 2 February, Karpathy—a computer scientist and founding member of OpenAI—defined it as a style of programming where software engineers “give in to the vibes, embrace exponentials, and forget that the code even exists.”

I understood what he meant, because I’d already practiced it. In the fall of 2024, I decided to see for myself what large language models could do and used them to revamp my personal website. I’ve since used AI to code several personal projects, including a graphical user interface (GUI) for AI speech-to-text transcription on my Windows laptop and a JavaScript app for tracking initiative in tabletop games.

Though I’ve played with HTML and Python in the distant past, my knowledge of programming is limited, and I can’t explain in detail how the AI-generated code in these programs functions. But they work, and the ease with which I created them has implications for software engineering.

What Is Vibe Coding?

Prasad Naik, a licensed professional mechanical engineer, is feeling the vibes.

Naik works at Gripple, a company that builds wire joining and tension systems used to secure a variety of infrastructure, such as plumbing and gas lines in commercial buildings. Naik isn’t a software engineer, but he recently developed two software tools for internal use. They help teams outside of engineering, such as the sales team, understand which product is right for a use case.

He began by revisiting an iPad app he developed for the company over a decade ago. He programmed it in C for use on an iPad, but Naik wanted to convert it to a modern JavaScript web app. It was an intimidating project, as he’d never worked with JavaScript before.

“I remember that [the original app] took me almost a month, because I had to study a lot of things I didn’t understand,” says Naik. “To my surprise, I managed to [convert it to JavaScript] in just two hours, using step-by-step directions from ChatGPT.” Naik didn’t use the code exactly as generated, but estimates that more than 90 percent of the code he used was generated by ChatGPT.

After that success, Naik built a more complex app that connects to a server. The app accesses a database of spreadsheets containing information about hardware products, such as brackets and support systems used to hang pipes from ceilings in buildings. The entire development, including deployment, took about a week and a half, but Naik is doubtful he could have pulled it off without AI tools.

“It was fascinating. I never in my wildest imagination thought I would end up developing an app this complex,” Naik says.

Vibe Coding for Proof-of-Concepts

Jason Touleyrou, a data engineering lead who currently works for Corewell Health, uses AI-assisted coding to rapidly test new ideas. “Speed to ideation is critical,” he says. “If I have an idea, and my team isn’t on…