Vibe Coding

Welcome to the Vibe Coding documentation. This section covers the modern approach to software development using AI-powered code generation and conversational programming.

What is Vibe Coding?

Vibe Coding refers to a software development approach where developers use large language models (LLMs) to generate code based on natural language prompts. It's characterized by a more relaxed and conversational style, where developers provide high-level directions and the AI handles the low-level implementation details.

Key characteristics of vibe coding:

  • Natural Language Prompts: Describe what you want in plain English
  • AI-Generated Code: Let LLMs handle the precise coding details
  • Conversational Development: Iterate through dialogue with AI assistants
  • High-Level Direction: Focus on the "what" rather than the "how"
  • Rapid Prototyping: Quickly generate working code from ideas

Core Principles

1. Prompt Engineering

Master the art of communicating with AI:

  • Be specific about requirements and constraints
  • Provide context about your tech stack and preferences
  • Use clear, unambiguous language
  • Break complex tasks into smaller, manageable prompts

2. Iterative Refinement

Develop through conversation:

  • Start with a basic implementation
  • Refine through follow-up prompts
  • Ask for specific improvements or modifications
  • Build complexity gradually

3. AI as a Coding Partner

Leverage AI effectively:

  • Use AI for boilerplate code generation
  • Get help with complex algorithms and logic
  • Generate documentation and comments
  • Explore different implementation approaches

4. Human Oversight

Maintain quality and control:

  • Review and understand generated code
  • Test thoroughly before deployment
  • Validate security and performance implications
  • Maintain architectural consistency

Getting Started with Vibe Coding

1. Choose Your AI Tool

Popular tools used by the vibe coding community:

Primary AI Assistants:

  • Claude.ai: Advanced reasoning and code generation
  • ChatGPT: Versatile AI assistant for coding
  • DeepSeek Chat: Specialized coding AI
  • Poe: Access to multiple AI models
  • v0.dev: AI-powered UI component generation

Integrated Development Tools:

2. Learn Effective Prompting

// Instead of: "Make a function"
// Try: "Create a TypeScript function that validates email addresses using regex, returns boolean, and handles edge cases like empty strings"

3. Start Small

Begin with simple tasks:

  • Generate utility functions
  • Create basic components
  • Write test cases
  • Generate configuration files

4. Build Complexity

Progress to larger tasks:

  • Implement full features
  • Create API endpoints
  • Build complete components
  • Generate entire modules

Best Practices

Effective Prompting

  • Be Specific: Include exact requirements, tech stack, and coding standards
  • Provide Context: Share relevant existing code or architecture
  • Set Constraints: Mention performance, security, or style requirements
  • Ask for Explanations: Request comments or documentation alongside code

Code Quality

  • Always Review: Never blindly accept generated code
  • Test Thoroughly: AI-generated code needs comprehensive testing
  • Refactor When Needed: Clean up and optimize generated code
  • Maintain Standards: Ensure consistency with your project's patterns

Security Considerations

  • Validate Inputs: AI might not always consider security implications
  • Review Dependencies: Check any suggested libraries or packages
  • Audit Sensitive Code: Extra scrutiny for authentication, data handling, etc.
  • Test Edge Cases: AI might miss unusual scenarios

Advanced Techniques

Multi-Turn Conversations

Build complex features through dialogue:

1. "Create a React component for user authentication"
2. "Add form validation to the login component"
3. "Implement password strength indicator"
4. "Add social login options"

Test-Driven Development Workflow

A proven pattern used by the vibe coding community:

1. "Write tests first, then the code, then run the tests and update the code until tests pass"
2. "I have got some build errors, run 'nr build' to see the errors, and then fix them"
3. "Run build until build passes"

Cursor AI Optimization Hack

Save Requests and Money with the 10x Tool Calls Technique:

When using Cursor AI's paid plan ($20/month with 500 requests), every message counts as a full request, even simple ones like "Hello". This can drain your quota quickly.

Solution: Use the userinput.py script

  • From the open-source 10x Tool Calls project
  • Creates an interactive terminal-like interface
  • Each command within the interface counts as a Tool Call within the same request
  • Build entire projects step-by-step while using only one request
  • Up to 25 Tool Calls per request limit

Setup:

  1. Add the userinput.py script to your project
  2. Configure according to the setup guide
  3. Use the interactive interface for all AI interactions
  4. Complete multiple development steps within a single request

Code Explanation and Learning

Use AI to understand existing code:

  • "Explain what this function does"
  • "How can I optimize this algorithm?"
  • "What are potential issues with this implementation?"

Debugging Assistance

Get help with troubleshooting:

  • "Why isn't this function working as expected?"
  • "Help me fix this error message"
  • "Suggest improvements for better performance"

Tools and Resources

Community Recommended AI Tools

Based on the awesome vibe Discord community recommendations:

Primary AI Assistants:

  • Claude.ai: Advanced reasoning and code generation
  • ChatGPT: Versatile AI assistant for coding
  • DeepSeek Chat: Specialized coding AI
  • Poe: Access to multiple AI models
  • v0.dev: AI-powered UI component generation

Development Tools:

Learning Resources

Community Best Practices

  • Next.js Best Practices: Adapt globs depending on your project's specific structure and file types
  • Test-Driven Development: Write tests first, then code, then iterate until tests pass
  • Build Error Resolution: Run build commands to identify and fix errors systematically

Prompt Engineering

  • Learn effective prompt patterns
  • Study successful examples from the community
  • Practice iterative refinement
  • Understand model limitations
  • Use specific, detailed prompts for better results

Integration

  • Set up AI tools in your existing workflow
  • Configure preferences and settings
  • Learn keyboard shortcuts and commands
  • Integrate with version control
  • Implement cost-saving optimization techniques

Common Patterns

Component Generation

"Create a reusable Button component in React with TypeScript that accepts variant, size, and disabled props, follows shadcn/ui patterns, and includes proper accessibility attributes"

API Development

"Build a REST API endpoint in Express.js for user management that includes CRUD operations, input validation, error handling, and follows RESTful conventions"

Test Creation

"Generate comprehensive unit tests for this utility function using Jest, including edge cases, error scenarios, and proper assertions"

Function Development with TDD

Community-proven workflow:

"Create a function that [specific functionality]. Write tests first, then the code, then run the tests and update the code until tests pass"

Build Error Resolution

"I have got some build errors, run 'nr build' to see the errors, and then fix them, and then run build until build passes"

Vibe coding represents the future of development - where human creativity meets AI capability. Focus on the big picture and let AI handle the details.