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Troubleshooting AI Development: Complete Guide

Learn how to identify, debug, and fix common issues in AI-generated applications. From prompt problems to deployment challenges.

January 22, 2025•17 min read

Quick Diagnosis Checklist

  • ✓ Is the prompt clear and specific?
  • ✓ Are all dependencies properly installed?
  • ✓ Is the environment configured correctly?
  • ✓ Are there any console errors?
  • ✓ Is the generated code syntactically valid?
  • ✓ Are API keys and credentials set up?

Common AI Generation Issues

1. Incomplete or Partial Generation

Problem

AI generates only part of the application or stops mid-generation.

Solutions

  • • Break down the prompt: Generate in smaller chunks
  • • Use continuation prompts: "Continue building the [feature]"
  • • Increase context: Provide more specific details
  • • Check token limits: Ensure prompt isn't too long

2. Wrong Technology Stack

Problem

AI uses different frameworks or libraries than requested.

Solutions

  • • Be explicit: "Use Next.js 14 with App Router, NOT Pages Router"
  • • Specify versions: "Use React 18.2.0 and TypeScript 5.0"
  • • Exclude alternatives: "Do NOT use Vue, Angular, or Svelte"
  • • Reference examples: "Use shadcn/ui components like in [example]"

3. Styling and Layout Issues

Problem

UI looks broken, unstyled, or doesn't match expectations.

Solutions

  • • Check CSS imports: Ensure styles are properly imported
  • • Verify Tailwind config: Check tailwind.config.js content paths
  • • Clear cache: Delete .next folder and rebuild
  • • Specific design refs: "Make it look like Stripe's dashboard"

Database and Backend Issues

4. Database Connection Errors

Common Database Errors

Error: Connection refused to localhost:5432

Fix: Ensure PostgreSQL is running or use cloud database

Error: relation "users" does not exist

Fix: Run migrations: npx prisma migrate dev

Error: Invalid DATABASE_URL

Fix: Check .env file format and credentials

5. Authentication Problems

Auth Troubleshooting Steps

  1. 1. Check environment variables:
    NEXTAUTH_URL=http://localhost:3000 NEXTAUTH_SECRET=your-secret-here
  2. 2. Verify OAuth callbacks:

    Ensure redirect URLs match in provider settings

  3. 3. Test with different providers:

    Try email/password if OAuth fails

  4. 4. Check session configuration:

    Verify session strategy and expiry settings

Frontend and UI Issues

6. Component Not Rendering

Debugging Checklist

7. State Management Issues

Common State Problems

State Not Updating
// ❌ Wrong - mutating state
state.items.push(newItem);

// ✅ Correct - creating new state
setState([...state.items, newItem]);
Stale Closures
// ❌ Wrong - using stale state
useEffect(() => {
  setTimeout(() => {
    setCount(count + 1); // Uses old count
  }, 1000);
}, []);

// ✅ Correct - using function update
useEffect(() => {
  setTimeout(() => {
    setCount(prev => prev + 1);
  }, 1000);
}, []);

API and Integration Issues

8. API Request Failures

API Troubleshooting

CORS Errors:
  • • Add proper CORS headers to API routes
  • • Use API routes as proxy for external APIs
  • • Configure allowed origins correctly
401 Unauthorized:
  • • Check API key configuration
  • • Verify authentication tokens
  • • Ensure headers are sent correctly
Rate Limiting:
  • • Implement request throttling
  • • Add caching layer
  • • Use webhook for async operations

9. Third-Party Service Integration

Integration Checklist

Stripe Integration
  • ✓ API keys in .env
  • ✓ Webhook endpoint configured
  • ✓ Webhook secret set
  • ✓ Test mode for development
  • ✓ Product/price IDs correct
Email Service
  • ✓ SMTP credentials
  • ✓ From email verified
  • ✓ Templates configured
  • ✓ Rate limits considered
  • ✓ Spam folder check

Performance Issues

10. Slow Loading Times

Performance Optimization

Quick Wins:
  • • Enable Next.js Image optimization
  • • Implement lazy loading for components
  • • Use dynamic imports for heavy libraries
  • • Enable gzip compression
  • • Optimize database queries with indexes
Advanced Optimizations:
  • • Implement Redis caching
  • • Use CDN for static assets
  • • Enable ISR for dynamic pages
  • • Optimize bundle size with tree shaking
  • • Use Web Workers for heavy computations

Deployment Issues

11. Build Failures

Common Build Errors

TypeScript Errors

Fix: Add // @ts-ignore temporarily or fix type issues

Module Not Found

Fix: Check package.json and run npm install

Environment Variables

Fix: Add all required vars to deployment platform

Memory Limit Exceeded

Fix: Increase build memory or optimize imports

12. Production-Only Issues

Production Debugging

  1. 1. Enable detailed logging:
    DEBUG=* npm run build
  2. 2. Check production environment:

    Verify NODE_ENV=production settings

  3. 3. Test locally with production build:
    npm run build && npm run start
  4. 4. Monitor with error tracking:

    Use Sentry or LogRocket for production errors

AI-Specific Troubleshooting

13. Prompt Not Working as Expected

Prompt Debugging Techniques

1. Add Constraints:

Instead of "create a form", use "create a form with email and password fields, validation, error messages, and submit handling"

2. Provide Examples:

"Style the button like GitHub's green 'Create repository' button"

3. Specify What NOT to Do:

"Do NOT use class components, only functional components with hooks"

4. Break into Steps:

Generate core functionality first, then add features incrementally

Debugging Tools and Techniques

Essential Debugging Tools

Browser Tools

  • • React DevTools
  • • Redux DevTools
  • • Network tab for API calls
  • • Console for errors
  • • Lighthouse for performance

Code Tools

  • • ESLint for code quality
  • • TypeScript for type safety
  • • Prettier for formatting
  • • Jest for testing
  • • Postman for API testing

Prevention Strategies

Best Practices to Avoid Issues

  • ✅ Start Simple: Build MVP first, add complexity later
  • ✅ Test Incrementally: Verify each feature as you build
  • ✅ Use Version Control: Commit working states frequently
  • ✅ Document Issues: Keep notes on fixes for future reference
  • ✅ Review Generated Code: Understand what AI created
  • ✅ Set Up Monitoring: Catch issues before users do
  • ✅ Have Rollback Plan: Be ready to revert if needed

Getting Help

When You're Stuck

  1. 1. Check Documentation:

    Read framework/library docs thoroughly

  2. 2. Search Error Messages:

    Copy exact error into Google/Stack Overflow

  3. 3. Use AI for Debugging:

    Prompt: "I'm getting [error]. Here's my code: [code]. How do I fix this?"

  4. 4. Community Support:

    Discord servers, Reddit, Stack Overflow

  5. 5. Create Minimal Reproduction:

    Isolate the issue in a simple example

Conclusion

Troubleshooting AI-generated code is a skill that improves with practice. The key is to approach problems systematically, understand the underlying technologies, and know where to look for solutions. Remember that AI is a tool—it generates code based on patterns it has learned, but it's up to you to ensure that code works correctly in your specific context.

Most issues have straightforward solutions once you identify the root cause. Use this guide as a reference, and don't hesitate to regenerate or refine your prompts when something isn't working as expected.

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