Vibecoding: How AI is Changing the Way We Code

In software development, every decade brings a shift in how we work. First came compilers, then graphical interfaces, then the internet. Now, with the rise of large language models (LLMs), we’re seeing a new approach: vibecoding. Instead of writing every line of code, developers explain what they want in simple, everyday language – and let AI build it for them.
It’s not just a tech trick; it’s changing who can build software and how.

Where the Term Came From

The term vibecoding was coined and popularized in early 2025 by Andrej Karpathy, former head of AI at Tesla and co-founder of OpenAI. He first used the term as a joke on social media, describing it as “fully giving in to the vibes” – letting the AI handle the coding while you focus on describing the idea.

What began as a playful phrase quickly resonated with developers, especially as AI tools like ChatGPT and Claude became capable of building complete applications from plain-language prompts. Within months, researchers started treating vibecoding as more than a joke, seeing it as a potential new way to create software.

From Prompt to Product

With vibecoding you don’t need to write code yourself – you just describe what you want. For example, “a to-do list app that works offline, saves to the cloud and has a dark mode”. The AI creates the first version, you try it out, and then tell it what to change or add.

The process usually follows four simple steps:

1. Describe the goal – clearly explain what you want to build.
   
   

2. AI generates the code – a first draft or even a working app.
   
   

3. Test and refine – try it out and give feedback.
   
   

4. Iterate until ready – repeat the process until you’re satisfied.
   

Instead of writing every line yourself, you guide the AI step by step – more like a director shaping a film than a technician writing code.

Benefits and Risks

Vibecoding comes with clear advantages. Its biggest strength is speed – ideas that once took a week can now be turned into a working version in a single day. It also lowers the barrier to entry, allowing people without coding experience to create functional applications, while giving developers more time for creative work instead of routine setup.

But speed comes with responsibility. AI-generated code can be messy, contain hidden security issues, or use outdated libraries. The key is to treat it as a first draft – review, test, and clean it before using it in production. If you do that, vibecoding can be more than a quick demo tool and it can become a solid part of your work.

The Road Ahead

Vibecoding is not going to completely replace traditional coding, but it will change how we build software. In the near future, developers will probably mix both approaches – using AI to quickly create and test ideas, then using traditional coding to polish and secure the most important parts. As the tools get better, AI will become a normal part of every developer’s workspace, helping teams work faster without lowering quality.

Vibecoding isn’t the future – it’s already here. The question is, how will you use it?