What is Vibe Coding? A New Era of AI-Driven Coding
What is Vibe Coding?
What in the world is vibe coding? Is it just being lazy and letting AI write all your code for you? Or is it about chilling out while manifesting the next big B2B SaaS idea?
Let’s break it down.
Vibe Coding Explained
Vibe coding is basically the practice of leaning on AI tools and agents to handle most of the heavy lifting when it comes to writing code. Instead of grinding through every line yourself, you focus more on the bigger picture:
- How the app works
- What features it should have
- The overall functionality and outcome
In other words, vibe coding frees you up to be more of a manager or director of your project, while AI handles the repetitive coding side.
Where Did the Term Come From?
The phrase “vibe coding” was coined by Andrej Karpathy who is a super early member at OpenAI and just a really famous guy and a thought leader in the AI ecosystem. He introduced the term vibe coding in February 2025. We all know I think everyone in the AI community knew that something was up for the past few months seeing people almost build entirely with AI and share their sort of experience online. But he was the first one to put the term to the name. Since then it started getting associated with like this Rick Rubin where he’s like you know the sort of vibing to some music and after it really blew up when Rick Rubin came out and did not acknowledge the term vibe coding.
How Vibe Coding Has Evolved
At the core, vibe coding simply means using AI agents and editors with built-in AI features to build applications through natural language—or even voice commands.
What’s striking is the pace of progress: about every 7 months, the scope of what AI can do on its own has been doubling.
- A few years back, GitHub Copilot could only autocomplete a line.
- Six or seven months later, it could write full functions.
- Soon after, it was generating parts of files and features in apps.
- Now, AI agents are capable of creating entire applications.
This trend has been observed, measured, and appears to follow a pretty reliable trajectory.
How It Works
- Describe Your Goal
Write a clear prompt in plain English for the AI agents, outlining the app and features you want. - Generate Code
The AI tools process your request and generate the code based on your instructions. - Refinement
Run the code, observe how it behaves, and give natural language feedback to fix bugs or improve results. - Outcome
Repeat this loop until the output meets your requirements, keeping the focus on achieving your application’s goal.
Key Characteristics :
- Conversational Interaction
Development becomes more like dialogues rather than manual coding.
- Natural Language Prompt
You use plain English to communicate with AI agents to understand AI to achieve your application goals, not any programming languages or syntax.
- Focus on Ideas
Developers spend less time on code implementation and more time on creative ideas for software development.
- Primary Coder
The AI handles writing of code, fixing bugs and enhancing application, freeing the human to guide and direct the project.
Limitations
- Quality Of Code
Vibe coding has raised concerns about understanding code and complexity. Developers may use AI-powered tools to write code and develop applications without understanding it. This often leads to hidden bugs and errors. AI often generates complex code that is hard to understand, as in development a deep understanding of the code is crucial for debugging, maintenance,
- Security Concerns
AI generated code has a lot of vulnerabilities that lead to security issues and should increase the chane of cyberattacks. Due to complex programming and not understanding lead to security vulnerabilities.
- Task Complexity
AI is capable of handling simple tasks and basic algorithms. However such AI systems struggle with complex code problems like handling multiple files, poorly documented libraries, and real world problems.
- Challenges with Debugging
AI generates code dynamically, since the developer did not write code they may struggle to understand code which leads to poor debugging and can’t figure out bugs, errors.
- Loss of Flow
Instead of coding daily, you depend on AI. You may be stuck in a loop of prompting, checking and refining, which can reduce your productivity and momentum.
- Less Productivity
Relying too much on AI and spending extra time on prompting, fixing and waiting for AI generated code that doesn’t match your need, can actually slow you down and hurt productivity.
- Learning Curve
For beginners, vibe coding may feel easy and smart at the start but if you don’t understand the core of the code, can’t make further updates and fix bugs later then it’s just a waste of time and can become a bottle-neck.
Who use Vibe Coding
Non-Technical Creators:
Entrepreneurs, students and other non-technical professionals can develop applications and prototypes.
Experienced Developers
Experienced developers use it to work faster and smarter. To automate repetitive tasks and update their existing projects.
Tools And Technologies
Ai Coding Assistances: Github copilot, Amazon CodeWhisperer, Lovable, V0 and Replit.
Large Language Models : GPT-4, Gemini and Sonnet.
