No rules, just vibes! What is vibe coding?
In February, OpenAI cofounder and former Tesla AI director Andrej Karpathy coined a phrase that quickly sparked fascination, debate, and even a small cultural shift in the world of software development: vibe coding.
What began as just a post "There’s a new kind of coding I call ‘vibe coding,’ where you fully give in to the vibes, embrace exponentials, and forget that the code even exists" – has snowballed into a new way of thinking about human-AI collaboration in programming. Today, developers, tech influencers, and even companies like IBM are taking a closer look at what this experimental style of coding means for the future of software development.
Vibe coding describes an emerging practice where developers use AI tools not just for assistance, but as co-creators, or, more provocatively, as the ones driving the development process. Instead of meticulously planning out and controlling every aspect of a program, vibe coders interact with large language models (LLMs) like ChatGPT, Claude, or specialized code assistants like GitHub Copilot and Cursor. They describe what they want, accept AI suggestions with minimal intervention, and simply see what happens.
Karpathy's own process involved copy-pasting error messages back into the AI, rarely questioning outputs, and trusting the system to “fix its own mistakes.” It's a relaxed, improvisational approach that prioritizes speed, spontaneity, and intuition – almost the opposite of traditional software engineering.
The appeal of vibe coding lies in its simplicity and efficiency. Developers can focus on broader design concepts and user experience rather than getting bogged down in technical details. Vibe coding seems to serve two very different groups: experienced developers who can catch and fix errors when needed, and total beginners who are looking to bring an idea to life without writing much (or any) code themselves.
The practice has already proved its worth in prototyping small games, apps, and websites. It drastically lowers the barrier to entry, making it possible for someone with no background in programming to spin up functional, if basic, software.
Experts caution that while vibe coding might work for hobby or pet-projects, it isn’t yet reliable or secure enough for serious systems. AI-generated code can include bugs, inefficient logic, or even dangerous security vulnerabilities – issues that require an experienced human to detect and resolve.
For now, the consensus is that vibe coding shines in the early stages of experimentation and ideation, but shouldn’t be relied on for mission-critical codebases.
Will AI eventually take over the bulk of software development? Possibly. But even as automation advances, many believe human developers will continue to play a crucial role in debugging, architecture, optimization, and integrating business logic. As Joshua Noble, a technical strategist at IBM, puts it: “Challenging software engineering will always require a human at some point in the process.”
As LLMs continue to improve, and AI coding assistants gain real-time integration into development environments and cloud platforms, the nature of software creation may shift permanently. The line between coder and non-coder is already blurring.
Vibe coding may have started as a meme, but it’s quickly become a mirror reflecting our changing relationship with AI. It’s chaotic, imperfect, sometimes silly – and very human. Maybe that’s the point.