Working with Claude: An AI Pair Programming Experience

Introduction 
Working with AI has transformed how we approach software development. In this post, I share my experiences using Claude as an AI pair programming partner, covering real-world use cases, best practices, and lessons learned.
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Disclaimer: I am not affiliated with, employed by, or sponsored by Anthropic. I am a paying Claude Pro subscriber and receive no compensation or endorsement for mentioning Claude in this article. All opinions and experiences shared are my own.
What is Claude? 
Claude is an AI assistant created by Anthropic. Unlike traditional code generation tools, Claude excels at:
- Understanding context and intent
 - Explaining complex code and concepts
 - Suggesting architectural improvements
 - Writing production-quality code
 
My First Project with Claude 
This very website is a testament to AI-assisted development. Let's walk through how Claude helped build the BANCS blog.
Setting Up the Tech Stack 
We chose a modern stack:
- VitePress: Fast, Vue-powered static site generator
 - TypeScript: Type safety and better developer experience
 - Tailwind CSS: Utility-first styling framework
 
Here's how we configured VitePress with TypeScript:
// docs/.vitepress/config.ts
import { defineConfig } from 'vitepress'
export default defineConfig({
  title: 'BANCS',
  description: 'Professional software development and consulting',
  base: '/',
  themeConfig: {
    nav: [
      { text: 'Home', link: '/' },
      { text: 'Blog', link: '/blog/' }
    ],
    socialLinks: [
      { icon: 'github', link: 'https://github.com/bancs' }
    ]
  }
})TIP
Check out the full configuration in the examples directory: examples/working-with-claude/vitepress-config.ts
Best Practices for AI Pair Programming 
1. Clear Communication 
Just like with human colleagues, clear communication is key:
// ❌ Vague request
"Make it better"
// ✅ Specific request
"Refactor this function to use async/await instead of promises,
and add proper error handling with try-catch blocks"2. Iterative Development 
Break down complex tasks into smaller steps:
// Step 1: Define the interface
interface BlogPost {
  title: string
  date: string
  author: string
  content: string
  tags: string[]
}
// Step 2: Implement the parser
function parseBlogPost(markdown: string): BlogPost {
  // Implementation here
}
// Step 3: Add validation
function validateBlogPost(post: BlogPost): boolean {
  // Validation logic
}See the complete implementation in examples/working-with-claude/blog-parser.ts.
3. Code Review Everything 
Always review AI-generated code:
- Check for security issues
 - Verify edge cases are handled
 - Ensure it matches your coding standards
 - Test thoroughly
 
Real-World Example: Custom Theme Integration 
Let's look at how we integrated Tailwind CSS with VitePress:
// docs/.vitepress/theme/index.ts
import DefaultTheme from 'vitepress/theme'
import './custom.css'
import type { Theme } from 'vitepress'
export default {
  extends: DefaultTheme,
  enhanceApp({ app, router, siteData }) {
    // Custom app enhancements
  }
} satisfies ThemeThe custom CSS file leverages Tailwind:
/* docs/.vitepress/theme/custom.css */
@tailwind base;
@tailwind components;
@tailwind utilities;
:root {
  --vp-c-brand: #6366f1;
  --vp-c-brand-light: #8b5cf6;
}
.custom-button {
  @apply inline-flex items-center px-6 py-3 rounded-lg;
  background: linear-gradient(135deg, #6366f1 0%, #8b5cf6 100%);
}View Full Theme Configuration
For the complete theme configuration, see examples/working-with-claude/theme-config.ts.
Lessons Learned 
What Works Well 
- Architecture Planning: Claude excels at suggesting project structure
 - Boilerplate Generation: Quickly scaffold common patterns
 - Documentation: Generate comprehensive docs and comments
 - Debugging: Explain complex error messages
 
What to Watch Out For 
- Context Limitations: Break large projects into smaller chunks
 - Outdated Patterns: Verify that suggested approaches are current
 - Over-Engineering: Sometimes simpler is better
 - Testing: AI may not catch all edge cases
 
Code Quality Metrics 
Here's a comparison of code written with vs. without AI assistance:
| Metric | With Claude | Without AI | 
|---|---|---|
| Time to MVP | 2 hours | 6 hours | 
| Lines of Code | 500 | 450 | 
| Test Coverage | 85% | 70% | 
| Documentation | Comprehensive | Minimal | 
Advanced Techniques 
Prompt Engineering 
Effective prompts lead to better results:
// Example: Complex type transformation
type DeepPartial<T> = {
  [P in keyof T]?: T[P] extends object ? DeepPartial<T[P]> : T[P]
}
// Ask Claude: "Explain this TypeScript utility type and
// provide 3 practical use cases with code examples"Context Management 
Keep conversations focused:
- Start new chats for different features
 - Provide relevant code context
 - Reference previous decisions when needed
 
Conclusion 
AI pair programming with Claude has significantly improved my productivity and code quality. The key is treating it as a collaborator, not a replacement for critical thinking.
Key Takeaways 
- ✅ Clear communication leads to better results
 - ✅ Always review and test AI-generated code
 - ✅ Use AI for boilerplate, but think critically about architecture
 - ✅ Document your processes and decisions
 
What's Next? 
In upcoming posts, I'll dive deeper into:
- Deploying to GitHub Pages with automated releases
 - Advanced TypeScript patterns with AI assistance
 - Building reusable component libraries
 
Resources 
- Full code examples: 
examples/working-with-claude/ - VitePress Documentation
 - Anthropic Claude
 - TypeScript Handbook
 
Have questions or experiences to share? Contribute to this blog or reach out on GitHub.
