What is Vibe Coding? The Next Evolution in AI-Assisted Programming Techniques

You must have heard of the popular Gen Z term 'Vibe', which describes the overall feeling or atmosphere of a person, place, or situation. But what if we told you that this term has taken over the field of AI and computing? Would you believe it?

Vibe Coding, yes, that's right! It is a new concept where you tell the AI your problem in a prompt form, and then the LLM writes the computer code for you. 

For instance, you provide a prompt stating, "Write a function that takes two numbers as input and returns their sum," and the AI provides you with Python code (or code in another programming language) defining a function that performs addition.

Therefore, rather than focusing on the how, the AI translates that description into the actual code. This left the programmer with the role of evaluating whether the code matches its requirements or not. 

But do you know where this term came from? Who invented it? And how can it revolutionise the LLMS we use? Let's understand!

What is Vibe Coding?

The term ‘Vibe Coding’ was introduced by the renowned computer scientist Andrej Karpathy, co-founder of OpenAI and former AI leader at Tesla. This term became widely known in February 2025. 

To put it simply, Vibe Coding is a coding approach that relies on LLMs and allows programmers to generate working code by providing natural language descriptions rather than manually writing it.

He described his approach as conversational, in which voice commands are used while AI generates the code. "It's not really coding – I just see things, say things, run things, and copy-paste things, and it mostly works."

Additionally, he also added that vibe coding has its own limitations and that AIs are not always reliable to fix or understand bugs, so he is always experimenting with unrelated changes until the problems are resolved. 

He concluded that he found the technique "not too bad for throwaway weekend projects" and described it as "quite amusing".

How Vibe Coding Works: A Step-by-Step Guide

Vibe coding leverages the capabilities of large language models (LLMs) to generate code from natural language descriptions. Here's a step-by-step guide to understanding the process:

Problem Definition:

• Clearly define the problem you want to solve with code. This involves understanding the requirements, inputs, and expected outputs of the software.
• Example: "Create a function that sorts a list of numbers in ascending order."

Prompt Creation:

• Craft a concise and clear prompt that describes the problem to the LLM. The prompt should include enough detail for the AI to understand the task.
• Key elements: specify the desired functionality, input parameters, and expected output.
• Example Prompt: "Write a Python function called sort_numbers that takes a list of integers as input and returns a new list with the integers sorted in ascending order."

LLM Code Generation:

• Input the prompt into a coding-tuned LLM (e.g., Codex, GPT-4). The LLM processes the prompt and generates the corresponding source code.
• The LLM uses its training data to predict the most likely code that satisfies the prompt.
• The generated code may include comments and explanations based on the prompt's context.

Code Testing:

Thoroughly test the generated code to ensure it meets the requirements. This involves creating test cases that cover various scenarios, including edge cases and error conditions.

Use testing frameworks (e.g., unittest in Python) to automate the testing process.

Example Test:

assert sort_numbers([3, 1, 4, 1, 5, 9, 2, 6]) == [1, 1, 2, 3, 4, 5, 6, 9]

assert sort_numbers([]) == []

assert sort_numbers([-1, 0, 1]) == [-1, 0, 1]

Refinement and Iteration:

• If the code does not perform as expected, refine the prompt and regenerate the code. This iterative process involves analysing the errors and adjusting the prompt to guide the LLM towards the correct solution.
• Modify the prompt to provide more specific instructions or constraints.
• Example: "Write a Python function called sort_numbers that takes a list of integers as input and returns a new list with the integers sorted in ascending order. The function should use the quicksort algorithm."

Code Integration:

• Once the generated code passes all tests, integrate it into your project. This may involve adapting the code to fit the existing architecture and ensuring it works seamlessly with other components.
• Follow coding best practices for readability and maintainability.
• Add comments and documentation to explain the purpose and functionality of the code.

Monitoring and Maintenance:

• Continuously monitor the performance of the integrated code and address any issues that arise. Regularly update the code to incorporate new features, improve efficiency, and fix bugs.
• Use version control systems (e.g., Git) to track changes and collaborate with other developers.
• Implement logging and error tracking to identify and resolve issues quickly.

Benefits of Vibe Coding: Efficiency and Innovation

Vibe coding involves describing a problem to an AI, which then generates the code. You test the code, refine your description if needed, and integrate the working code into your project. Here are some of its useful benefits:

1. Increased Efficiency: Vibe coding significantly reduces development time by automating repetitive coding tasks. AI-powered tools generate code quickly, allowing developers to focus on refining and optimising rather than starting from scratch. This leads to faster project completion and quicker iterations.
2. Enhanced Accessibility: Vibe coding lowers the barrier to entry for software development, making it accessible to individuals with limited programming experience. Non-technical stakeholders can contribute by providing natural language instructions, fostering better collaboration between technical and non-technical teams.
3. Accelerated Prototyping: Vibe coding enables rapid prototyping, allowing developers to quickly create and test new ideas. AI assistance reduces the time and resources required to build functional prototypes, facilitating faster innovation and experimentation. Startups can bring minimum viable products (MVPs) to life more quickly, validating concepts and gathering feedback efficiently.
4. Focus on Innovation: By automating routine tasks, vibe coding frees up developers to concentrate on creative problem-solving and strategic thinking. This shift in focus allows teams to explore new approaches, experiment with cutting-edge technologies, and develop innovative solutions that drive business value .
5. Improved Code Quality: While it requires careful oversight, vibe coding can improve code quality by providing instant suggestions, highlighting errors, and even writing tests. AI tools help ensure code adheres to best practices and reduces the risk of vulnerabilities, leading to more robust and maintainable software.

In summary, vibe coding enhances efficiency by automating tasks, increases accessibility for non-technical users, accelerates prototyping, fosters innovation by freeing up developers' time, and can improve code quality with proper oversight.