Chapter 7: Important Reminders

Essential Guidelines for AI Development

This chapter consolidates critical reminders and best practices for AI-assisted development. These points represent essential considerations that should be regularly reviewed and maintained throughout the development process.

What You'll Learn

  • Critical documentation maintenance practices
  • AI model awareness and limitations
  • Development best practices and guidelines
  • Context management strategies
  • Safety and verification procedures

Quick Start

  1. Review documentation maintenance checklist
  2. Verify AI model configurations
  3. Implement verification processes
  4. Set up regular review schedules

Why This Matters

Regular review of these critical points helps ensure project success and maintainable code quality. Think of these reminders as your pre-flight checklist - they help ensure nothing important gets missed and keep your project running smoothly.

Documentation Maintenance

# Documentation Maintenance

## Daily Updates
- Update cursor.rules daily
- Maintain specialized .md files
- Review process documentation
- Keep technical docs current
- Document all changes

## Quality Check
- Comment-to-code ratio (1:3)
- File headers complete
- Complex logic documented
- Cross-references valid

AI Model Awareness

# AI Model Awareness

## Model Limitations
- Knowledge cutoff dates
- Version compatibility
- Context window limits
- Response variations

## Version Management
- Track model versions
- Document behaviors
- Update patterns
- Maintain compatibility

Development Best Practices

# Development Guidelines

## Implementation Approach
- Start with MVP (Minimum Viable Product)
- Break changes into steps
- Test incrementally
- Document decisions
- Keep code clean and readable

## Technical Debt Prevention
- Understand code thoroughly
- Avoid complexity
- Keep implementations focused
- Regular refactoring
- Maintain documentation

Essential Daily Checklist

# Essential Daily Checks

## Documentation
- [ ] Documentation updates completed
- [ ] Code changes tested
- [ ] Comments maintained
- [ ] Technical debt addressed

## Code Quality
- [ ] Security considerations verified
- [ ] Performance impacts assessed
- [ ] Context windows managed
- [ ] Tool configurations checked

## Communication
- [ ] Team updates shared
- [ ] Knowledge base maintained
- [ ] Learning outcomes documented
- [ ] Process improvements noted

Context Management

# Context Management

## Session Management
- Monitor window usage
- Create new sessions when needed
- Maintain clear boundaries
- Document session states

## File Management
- Tag relevant files explicitly
- Maintain clear structure
- Document relationships
- Update file headers

Verification Process

# Code Validation

## Testing Requirements
- Test changes thoroughly
- Validate edge cases
- Check error handling
- Verify security implications
- Document test coverage

## Review Process
- Code review checklist
- AI-generated code verification
- Documentation accuracy
- Implementation validation

Maintenance Schedule

# Maintenance Schedule

## Daily Tasks
- Update documentation
- Review code changes
- Check tool status
- Monitor performance

## Weekly Tasks
- Validate workflows
- Review model configs
- Update templates
- Check integrations

## Monthly Tasks
- Comprehensive review
- Major version updates
- Security audit
- Team training

Common Pitfalls and Solutions

Inconsistent Reviews

Don't skip regular reviews and maintenance tasks. Establish a routine and stick to it to prevent technical debt and documentation drift.

Neglecting Updates

  • Keep documentation current
  • Monitor AI model versions
  • Update tooling regularly
  • Review security practices

Quick Tips

Regular Reviews

  • Schedule daily checks
  • Maintain checklists
  • Document findings
  • Follow up on issues

Proactive Maintenance

  • Address issues early
  • Keep tools updated
  • Monitor performance
  • Review security
Previous ChapterHome