Project Workflows & Best Practices
Sustainable AI-Assisted Development
4 min read
AI tools are powerful, but overreliance creates risks. This final lesson covers sustainable practices for long-term success with vibe coding.
The Sustainability Balance
┌─────────────────────────────────────────────────────────────┐
│ AI Assistance Spectrum │
├─────────────────────────────────────────────────────────────┤
│ │
│ Under-use Balanced Over-reliance │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌───────┐ ┌───────┐ ┌───────┐ │
│ │ Slow │ │Optimal│ │Fragile│ │
│ │ Work │ │ Flow │ │ Code │ │
│ └───────┘ └───────┘ └───────┘ │
│ │
│ • Miss productivity • AI handles • Can't debug │
│ gains repetitive • Blind spots │
│ • Slower delivery • Human handles • Technical debt │
│ • Fatigue complex • Skills atrophy │
│ • Skills grow │
└─────────────────────────────────────────────────────────────┘
Maintaining Core Skills
Skills to Practice Without AI
Weekly practice (even if AI could do it):
├── Write a function from scratch
├── Debug using console.log or debugger
├── Read and understand unfamiliar code
├── Write tests before implementation
└── Design a data structure
The 80/20 Rule
Use AI for (~80%):
├── Boilerplate code
├── Repetitive patterns
├── Documentation
├── Test generation
├── Refactoring
Do manually (~20%):
├── Architecture decisions
├── Complex debugging
├── Performance optimization
├── Security implementation
├── Critical business logic
Technical Debt Management
AI Can Create Technical Debt
Common AI debt sources:
- Over-engineered solutions
- Inconsistent patterns
- Unused code generated "just in case"
- Missing tests for edge cases
- Poor error messages
Debt Prevention Practices
Before accepting AI code:
├── Is this the simplest solution?
├── Does it match existing patterns?
├── Will future me understand this?
├── Is everything generated actually used?
└── Are error messages helpful?
Regular Debt Audits
# Schedule regular code health checks
# Find unused exports
npx ts-prune
# Find code complexity issues
npx eslint --rule 'complexity: ["error", 10]'
# Find duplicate code
npx jscpd ./src
# Check test coverage
npm test -- --coverage
Cost Management
Monitoring AI Costs
// Track AI tool costs
interface MonthlyCosts {
cursor: number; // $20-60/month
anthropicApi: number; // Variable
copilot: number; // $10-39/month
devinAcu: number; // Pay per use
}
// Calculate ROI
function calculateROI(costs: MonthlyCosts, hoursSaved: number, hourlyRate: number): number {
const totalCost = Object.values(costs).reduce((a, b) => a + b, 0);
const valueSaved = hoursSaved * hourlyRate;
return ((valueSaved - totalCost) / totalCost) * 100;
}
Cost Optimization Tips
Reduce costs:
├── Use cheaper models for simple tasks
├── Batch similar requests
├── Cache common prompts/responses
├── Use free tiers strategically
└── Monitor token usage
Long-term Maintainability
Documentation for AI Code
/**
* Calculates user engagement score.
*
* @ai-generated Cursor Composer, 2026-01-06
* @ai-reviewed Human review completed
*
* Logic: Weighted average of activity metrics
* - Login frequency: 40%
* - Feature usage: 35%
* - Session duration: 25%
*
* @param user - User object with activity data
* @returns Engagement score 0-100
*/
function calculateEngagementScore(user: User): number {
// Implementation...
}
Future-Proofing
Make AI code maintainable:
├── Add comments explaining "why"
├── Use descriptive variable names
├── Keep functions focused and small
├── Write tests that explain behavior
└── Document edge cases
Avoiding Anti-Patterns
Anti-Pattern 1: Cargo Cult Coding
// ❌ Using AI code you don't understand
const result = await someLibrary.complexOperation({
options: { flag: true, mode: 'advanced' }
});
// "It works, I don't know why"
// ✅ Understand before using
// First: Ask AI to explain the code
// Then: Understand each parameter
// Finally: Use with confidence
Anti-Pattern 2: AI Dependency
// ❌ Can't code without AI
"I need AI to write even simple functions"
// ✅ AI enhances, doesn't replace
"I can write this, but AI makes it faster"
Anti-Pattern 3: Blind Trust
// ❌ Accept without review
await ai.generate("Create user auth")
// Click "Apply All" immediately
// ✅ Review everything
await ai.generate("Create user auth")
// Read each line
// Check security implications
// Test edge cases
// Then apply
Building Healthy Habits
Daily Practices
Morning:
├── Review yesterday's AI code with fresh eyes
├── Run tests before starting new work
└── Update .cursorrules if patterns emerged
During work:
├── Commit frequently
├── Take breaks from AI (manual coding time)
└── Document decisions as you go
End of day:
├── Review all AI code generated
├── Clean up unused generated code
└── Note any patterns for tomorrow
Weekly Practices
├── Code review without AI assistance
├── Practice debugging manually
├── Update prompt library
├── Review AI costs
└── Share learnings with team
Monthly Practices
├── Audit technical debt
├── Review and update AI configurations
├── Assess skill maintenance
├── Evaluate tool effectiveness
└── Plan training/learning
Course Conclusion
Congratulations on completing Vibe Coding Fundamentals!
What You've Learned
Module 1: AI Coding Landscape
└── Tools, trends, and choosing wisely
Module 2: Cursor Deep Dive
└── Composer, Agent, Tab completion
Module 3: Claude Code & CLI
└── Terminal workflows, checkpoints, MCP
Module 4: Effective Prompting
└── CRISPE framework, advanced techniques
Module 5: Debugging AI Code
└── Review, common bugs, strategies
Module 6: Project Workflows
└── Git, teams, sustainability
Your Path Forward
Next Steps:
├── Practice daily with real projects
├── Build your prompt library
├── Experiment with different tools
├── Contribute to team standards
└── Stay current with AI developments
Final Wisdom
The Vibe Coder's Mindset:
AI tools are like power tools in a workshop. A master carpenter doesn't just know how to use a power saw—they know when to use hand tools, how to maintain their equipment, and most importantly, how to craft something beautiful.
Vibe coding at its best is not about generating code fast. It's about amplifying your creativity, eliminating tedium, and shipping better software. The human remains the craftsperson; AI is the best apprentice you've ever had.
Thank you for completing this course. Now go build something amazing! :::