Vibe coding

See also: Artificial intelligence terms

Introduction

Vibe coding is an AI-driven software development approach that emerged in early 2025, enabling users to create functional applications by describing their goals in natural language rather than writing code manually. Leveraging large language models (LLMs) and AI-powered tools, vibe coding allows both non-programmers and experienced developers to rapidly prototype and deploy software through an iterative, conversational process. Coined by AI researcher Andrej Karpathy, the term reflects a shift toward an intuitive, creative style of programming that blends the flexibility of traditional coding with the accessibility of no-code platforms.

Origins and Terminology

https://x.com/karpathy/status/1886192184808149383

https://x.com/karpathy/status/1886192184808149383

The term "vibe coding" was first coined by Andrej Karpathy in a tweet on February 3, 2025, where he described using AI tools like Cursor Composer to build software by casually instructing the AI, e.g. "halve the sidebar padding", without directly editing code. Karpathy noted how he accepted AI suggestions, ignored diffs, and fed errors back to the assistant, resulting in a codebase that grew “beyond his usual comprehension.” This playful remark sparked interest in AI-assisted development.

A structured framework built on three pillars: specification (defining goals), rules (setting constraints), and oversight (steering the process). Community contributions from platforms like Reddit and YouTube further refined vibe coding into a collaborative, repeatable methodology. It builds on the lineage of no-code and low-code platforms, distinguishing itself with natural language input and a modular rule-based system, powered by LLMs like ChatGPT, Claude, and GitHub Copilot.

Core Principles

Vibe coding is defined by the following principles:

• Natural Language Input: Users articulate project goals in plain English (e.g. "Build a note-taking app with save functionality") rather than writing code.
• Iterative Refinement: Development occurs through dialogue with AI, with users reviewing outputs and refining via prompts (e.g. "Add tests" or "Simplify the layout").
• Minimal Manual Coding: AI generates most or all code, often requiring no direct source edits—some users rely entirely on prompts.
• Rapid Prototyping: Projects materialize in minutes to hours, fostering experimentation and quick validation.
• Accessibility: Non-technical users can participate by clearly expressing ideas, no coding expertise needed.
• Rule-Based Control: Users set explicit constraints (e.g. "Use Python, keep it simple") to guide AI behavior, ensuring consistency and clarity.

Workflow

The vibe coding process typically follows these steps:

1. Initial Specification: The user provides a high-level goal (e.g. "Create a Twitter clone with login").
2. Rule Definition: Users establish preferences (e.g. "Use Python, prioritize simplicity") via a four-file framework (see below).
3. Code Generation: AI produces functional code—front-end, back-end, or both—based on prompts and rules.
4. Review and Oversight: The user tests the output, monitors logs (e.g. progress.md), and requests refinements (e.g. "Add error handling").
5. Iterative Execution: AI breaks tasks into stages, pausing for approval (e.g. "Backend done—proceed to frontend?").
6. Deployment: Platforms often enable one-click publishing for instant sharing or hosting.

A key innovation is the four-file framework (stored in a `.cursor/rules` directory or equivalent):

• Coding Preferences: Ensures clean code (e.g. "Keep files under 300 lines, document in /docs").
• Technical Stack: Locks tools (e.g. "Backend in Python, SQL storage").
• Workflow Preferences: Governs process (e.g. "Pause after major steps, log in progress.md").
• Communication Preferences: Sets interaction style (e.g. "Summarize changes as Small, Medium, or Large").

This structure tames AI chaos, enhances transparency, and scales from simple scripts to complex apps.

Comparison with Other Development Approaches

Aspect	Traditional Coding	Low-Code Platforms	Vibe Coding
Skill Required	Strong programming knowledge	Basic technical familiarity	Ability to describe ideas
Process	Manual coding and debugging	Drag-and-drop modules	Conversational AI prompts + rules
Flexibility	High, fully customizable	Limited by platform	High, within AI and rule constraints
Time to Build	Days to months	Hours to days	Minutes to hours
Main Benefits	Fine control, robust output	Ease of use, speed	Fast iteration, low barrier, guided AI
Key Drawback	Steep learning curve	Restricted customization	Potential quality/consistency issues

Vibe coding merges traditional coding’s flexibility with low-code’s accessibility, enhanced by AI and user-defined rules.

Benefits

• Empowerment: Non-developers (e.g., marketers, educators) build custom tools without coding skills.
• Speed: Prototypes emerge in hours, accelerating idea validation.
• Creativity: Automation of tedious tasks shifts focus to design and functionality.
• Control: Rules ensure AI aligns with user intent, reducing scope creep.
• Maintainability: Documentation and logs (e.g. /docs, progress.md) support long-term viability.

Limitations

• Code Quality: AI-generated code may lack optimization or scalability without expert review.
• Security Risks: Novices might overlook vulnerabilities if not explicitly addressed in rules.
• Context Limits: LLMs (e.g. Claude’s 200k token cap) may lose coherence in large projects unless managed (e.g. via context-summary.md).
• Complexity Challenges: Intricate logic or edge cases may require traditional coding.
• Oversight Dependency: Success hinges on clear specifications and active user guidance.

Tools and Platforms

As of 2025, vibe coding is supported by:

• Replit Agent: Web-based IDE with AI code generation and deployment ($20/month).
• Cursor: AI-enhanced editor with rule-based support, built on Visual Studio Code (free tier; paid plans).
• GitHub Copilot: Inline/chat-based code suggestions ($10/month individual plan).
• Bolt.new: Browser-based prototyping with Netlify integration (free with limits).
• Rosebud AI: Creative apps and games, with AI image generation (free tier; $10/month+).
• Databutton: Business tools with database support ($20/month+).

General-purpose LLMs like Claude and ChatGPT also power vibe coding, especially with custom rules.

Real-World Examples

• Note-Taking App: Using Cursor, a user built an app with save functionality in 45 minutes (Python backend, SQL storage, documented in /docs/notes.md).
• Content Genie: A marketer created a LinkedIn post generator from YouTube links in 30 minutes via Cursor.
• JustBuildThings.com: Non-developer Rasit launched 100 web utilities with Cursor, ranking on Product Hunt in 2025.
• Multiplayer Flight Simulator: Indie developer Pieter Levels prototyped a simulator in one day using AI prompts.

Advanced Techniques

For complex projects:

• Coding Quality: Enforce SOLID principles, ban mock data in production, and use emojis (e.g. 🐙) to verify context retention.
• Workflow Mastery: Add tests for edge cases, summarize context at 100k tokens, and adjust checkpoint frequency.
• Communication Precision: Classify changes (Small <50 lines, Large = architecture shift) and prioritize urgency cues (e.g. “This is critical!”).

Impact and Criticism

Vibe coding has democratized software creation, fueling rapid innovation. Critics, including seasoned engineers, highlight:

• Technical Debt: Unreviewed AI code may become unmaintainable.
• Security Oversights: Novices may deploy insecure apps without rule-based safeguards.
• Skill Erosion: Overreliance might hinder learning core concepts.

Supporters argue it boosts productivity and empowers amateurs, with flaws offset by oversight and education. As of March 2025, forums like X and Reddit buzz with success stories and refinements.

Future Outlook

Vibe coding may evolve with:

• Smarter AI: Enhanced models will produce secure, efficient code.
• Voice Integration: Speech-driven prompts (e.g., “Build a quiz app”) could dominate.
• Enterprise Use: Businesses may adopt it for internal tools with stronger security.
• Education Shift: Curricula might prioritize problem-solving over syntax.

While unlikely to replace traditional coding for critical systems, vibe coding is set to lead prototyping and small-scale development.

See Also

• No-Code Platforms
• Low-Code Development
• Generative AI
• GitHub Copilot
• Replit

References

1. Karpathy, Andrej. "Personal Tweet on Vibe Coding," February 3, 2025. https://x.com/karpathy/status/1886192184808149383
2. Vibe Coding Manual March 2025 https://www.reddit.com/r/ChatGPTCoding/comments/1j5l4xw/vibe_coding_manual