What is Vibe Coding?
Vibe coding is an informal term used to describe a relaxed, creative approach to programming where the focus is on experimentation, flow and results rather than strict theory or perfect technique.
In plain English, it means:
You’re coding in a way that feels intuitive and exploratory. Instead of starting with heavy planning, complex diagrams or deep mathematics, you learn by trying things out, adjusting as you go, and seeing what happens. The “vibe” part refers to the mindset — curious, playful and hands-on — rather than rigid or overly technical.
In the context of AI, vibe coding usually involves:
• Using existing tools and libraries rather than building everything from scratch
• Writing small bits of code and quickly seeing visible outcomes
• Tweaking inputs, prompts or data and observing how the AI responds
• Learning concepts through doing, not just reading or listening
• Accepting trial and error as part of the process
It does not mean coding without thinking. Good judgement, ethics and understanding still matter. The difference is that the learning path feels more like creative exploration than formal computer science.
You could describe it simply as:
“A practical, experimental way of learning to code with AI, where you build, test and refine ideas in real time.”
Read: “Vibe Coding: Beginning a New Era” (LinkedIn article)
In vibe coding, AI is not just the topic you study — it becomes a tool you actively work with while you code.
Here’s how a person typically uses AI in this approach:
AI as a coding assistant
You use AI tools to help write, explain or improve code. For example, you might:
• Ask AI to generate a small piece of Python code
• Request an explanation of what a block of code does
• Debug an error message by pasting it into an AI tool
You stay in control, but AI speeds up learning and problem-solving.
AI as a building block
Rather than creating complex systems from scratch, you plug into existing AI models or services. A learner might:
• Use a text-generation model to build a simple chatbot
• Use an image model to create visuals from text prompts
• Use a pre-trained machine learning model to classify data
You’re assembling intelligent features into your project.
AI as something you experiment on
You change inputs and see how AI behaves. This is a big part of the “vibe”:
• Adjust prompts and observe different outputs
• Feed in different data and compare results
• Tweak settings and see how performance changes
Learning comes from observing cause and effect.
AI as a creative partner
AI helps you prototype ideas quickly:
• Generating sample content, data or scenarios
• Helping brainstorm project ideas
• Producing rough outputs you refine
This lowers the barrier between idea and working demo.
AI as a learning environment
Instead of memorising theory, you learn concepts by interacting with real systems:
• Seeing how bias appears in outputs
• Noticing where AI is confident but wrong
• Understanding limits through use, not just lectures
So, in vibe coding, AI is assistant, toolkit, experiment subject and creative collaborator all at once. The person is still thinking, deciding and guiding — AI simply makes it faster to explore, build and understand.