Vibe coding

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 a more intuitive, creative style of programming that blends the flexibility of traditional coding with the ease of no-code platforms.

Origins and Terminology

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

The term "vibe coding" originated from a tweet by Andrej Karpathy in February 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 himself. Karpathy humorously dubbed this process "vibe coding", noting how he accepted AI suggestions, ignored diffs, and fed errors back to the assistant, resulting in a codebase that grew “beyond his usual comprehension.” Though initially a playful remark, the phrase resonated with a growing community experimenting with AI-assisted development.

Vibe coding builds on the lineage of no-code and low-code platforms, which abstracted programming into visual interfaces. However, it distinguishes itself by using natural language as the primary input, powered by advances in LLMs like those behind ChatGPT, Claude, and GitHub Copilot. These tools had become adept at generating boilerplate code and handling repetitive tasks, inspiring a cultural shift toward faster, less rigid development practices.

Core Principles

Vibe coding is defined by the following principles:

Natural Language Input: Users describe their project goals in plain English (e.g. "Build a website that tracks daily deals") rather than writing syntactically precise code.
Iterative Refinement: Development unfolds through a dialogue with AI, where users review outputs and request adjustments (e.g. "Add a login page" or "Fix the layout").
Minimal Manual Coding: The AI generates most or all of the code, reducing the need for hands-on editing—some users never touch the source files directly.
Rapid Prototyping: Projects can be built and tested within hours, encouraging experimentation and quick iteration.
Accessibility: Non-technical users can participate, as the approach requires only the ability to articulate ideas clearly, not programming expertise.

Workflow

The vibe coding process typically follows these steps:

Initial Prompt: The user provides a high-level description (e.g. "Create a web app to calculate podcast script recording time").
Code Generation: The AI produces functional code, often including front-end and back-end components, based on its training and context.
Review and Testing: The user runs the code, evaluates its performance, and identifies areas for improvement.
Refinement: Through additional prompts (e.g. "Add error handling" or "Make it mobile-friendly"), the AI updates the code iteratively.
Deployment: Many platforms offer one-click publishing, enabling instant sharing or hosting.

This workflow emphasizes speed and adaptability, often yielding usable prototypes in minutes to hours.

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
Flexibility	High, fully customizable	Limited by platform	High, with AI limits
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
Key Drawback	Steep learning curve	Restricted customization	Potential quality issues

Vibe coding bridges traditional coding's flexibility and low-code's accessibility, powered by AI's interpretive capabilities.

Benefits

Empowerment: Non-developers, such as marketers or educators, can build custom tools without coding skills.
Speed: Prototypes emerge in hours, accelerating idea validation for businesses and creators.
Creativity: By automating tedious tasks, users focus on design and functionality rather than syntax.
Cost Savings: Reduced reliance on professional developers lowers the financial barrier for small projects.

Limitations

Code Quality: AI-generated code may lack optimization or scalability, requiring expert review for complex applications.
Security Risks: Novices might overlook vulnerabilities, especially in data-sensitive apps, if security isn’t explicitly requested.
Understanding Gaps: Users who don’t inspect the code may struggle to debug or maintain it long-term.
Complexity Limits: Highly specialized or intricate logic can challenge AI, necessitating traditional coding.

Tools and Platforms

Several platforms support vibe coding as of 2025:

Replit Agent: A web-based IDE with AI assistance for code generation and deployment (from $20/month).
Cursor: An AI-enhanced editor built on Visual Studio Code, ideal for iterative refinements (free tier; paid plans available).
GitHub Copilot: Suggests code inline or via chat, popular among developers ($10/month individual plan).
Bolt.new: Browser-based prototyping with Netlify integration (free with usage limits).
Rosebud AI: Focuses on creative apps and games, with AI image generation (free tier; $10/month+).
Databutton: Business-oriented, with database support and AI task management ($20/month+).

General-purpose LLMs like ChatGPT and Claude also remain popular for generating code snippets outside dedicated environments.

Real-World Examples

Podcast Script Timer: A podcaster used Replit Agent to build a tool estimating script recording time, adding features like PDF export in under an hour.
Content Genie: A marketer created an app in 30 minutes via Cursor to draft LinkedIn posts from YouTube links, showcasing vibe coding’s accessibility.
JustBuildThings.com: Rasit, a non-developer, built 100 web utilities with Cursor, launching a site that ranked on Product Hunt in early 2025.
Multiplayer Flight Simulator: Indie developer Pieter Levels crafted a basic simulator in one day using AI prompts, proving vibe coding’s prototyping power.

Impact and Criticism

Vibe coding has democratized software creation, enabling rapid innovation and reducing barriers for non-technical creators. However, critics—particularly seasoned engineers—warn of:

Technical Debt: Unreviewed AI code can become unmaintainable over time.
Security Oversights: Novices may deploy insecure apps without realizing it.
Skill Erosion: Overreliance on AI might hinder learning core programming concepts.

Supporters counter that vibe coding enhances productivity for professionals and empowers amateurs, with its flaws mitigated by oversight and education. As of March 2025, the community remains cautiously optimistic, with forums like X buzzing with both success stories and cautionary tales.

Future Outlook

In the futurr, vibe coding is expected to evolve with:

Smarter AI: Models will generate more secure, efficient code, reducing quality concerns.
Voice Integration: Speech-driven coding (e.g., “Build a quiz app”) may become standard.
Enterprise Adoption: Businesses could use vibe coding for internal tools, pending improved security features.
Education Shift: Coding curricula might incorporate vibe coding to teach problem-solving over syntax.

While unlikely to replace traditional development for critical systems, vibe coding is poised to dominate prototyping and small-scale app creation.

References

Karpathy, Andrej. "Personal Tweet on Vibe Coding," February 2025.