Code Generation

# Introduction to Code Generation

Code generation is one of the most powerful capabilities of modern AI models. This guide will help you understand how to integrate code generation into your applications.

## Key Concepts

- **Prompt Engineering**: Crafting effective prompts for code generation
- **Context Management**: Providing relevant context to the AI model
- **Output Validation**: Ensuring generated code is safe and functional

## Getting Started

typescript
const prompt = "Write a function to sort an array of numbers"

const response = await generateCode(prompt)
console.log(response)


## Best Practices

1. Always validate generated code before execution
2. Use specific, detailed prompts
3. Provide relevant examples in your context
4. Test thoroughly in a safe environment

## Advanced Techniques

### Context-Aware Generation

By providing context about your project structure, you can get more relevant and useful code suggestions.

typescript
const context = {
projectType: "web-application",
framework: "react",
styling: "tailwind"
}


### Error Handling

Always implement proper error handling when working with AI-generated code:

typescript
try {
const code = await generateCode(prompt)
const validated = validateCode(code)
return validated
} catch (error) {
console.error("Code generation failed:", error)
}


## Conclusion

Code generation can significantly accelerate development workflows when used responsibly.