Vibe Coding - Creating Code with Natural Language

1. Vibe Coding

  • The term “Vibe Coding” first appeared in a post by Andrej Karpathy on X (Twitter) in February 2025.
    • He is a co-founder of OpenAI and previously served as the Head of AI at Tesla.

"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."

[Source] X - Andrej Karpathy

  • The core idea of “Vibe Coding” is a development approach where instead of manually writing code, developers describe requirements in natural language and let AI generate the code.
  • Just like creating music by following rhythm, coding is performed by riding the “vibe,” progressing based on flow and atmosphere.

In summary, Vibe Coding is an AI-driven development paradigm where you build by requesting tasks from AI, focusing more on outcomes and flow rather than the code itself.

2. Code Assistant

  • A Code Assistant is an AI tool that generates or modifies code based on natural language instructions.
  • Examples include GitHub Copilot, Claude Code, OpenAI Codex, and Gemini Code Assist.
  • These tools support Vibe Coding by helping developers focus more on “what” to build rather than “how” to implement it.

Code Assist Provider Base Model
GitHub Copilot - GitHub
- Microsoft		 Supports multiple models including GPT (GPT-mini, GPTCodex), Claude (Sonnet, Haiku), Gemini, etc.
Claude Code - Anthropic Claude Opus, Claude Sonnet, Claude Haiku
OpenAI Codex - OpenAI Based on OpenAI GPT, GPT-mini, GPTCodex models
Gemini Code Assist - Google
- Google DeepMind		 Gemini family models (Flash, Pro)

3. Prompt

  • A prompt is a sentence used to instruct an AI Code Assistant on what task to perform.
    • There is no strict format, but in practice, structured instructions using Markdown are commonly used.
  • The more clearly you specify what to build, how to build it, and under what conditions, the better results you can achieve.
    • This is because prompts are the key element that allows AI Code Assistants to accurately understand user intent and generate appropriate outputs.
    • The methodology and experience of crafting effective prompts become valuable know-how in real-world development.
  • Programming languages have evolved to become more human-friendly over time.
  • Initially, there was machine code, which was difficult for humans to understand. This led to the emergence of Assembly language, which represents instructions in a readable text form.
  • Later, higher-level languages such as C and Java, which are closer to human language, became widely used.
  • Now, we have entered an era where simply describing desired functionality in a prompt allows AI to generate code.

  • Regardless of the programming method used, all code is ultimately translated into machine code and executed by the CPU.

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