Fundamental Principles in AI

10 KEY PRINCIPLES:

1. NEVER SKIP PLANNING
AI amplifies your plan. Vague plans produce vague results.
Detailed plans produce quality software.

2. ALWAYS SET UP FOUNDATION MANUALLY
You must understand the base of your application.
Don't let AI create mystery infrastructure.

3. ONE STEP AT A TIME
Small, incremental steps lead to better code and easier debugging.
If something breaks, you know exactly what changed.

4. TEST BEFORE COMMITTING
Every commit should represent a working state.
Never commit broken code (except with [WIP] prefix).

5. COMMIT FREQUENTLY
Small, focused commits make it easy to:
- Understand what changed
- Roll back if needed
- Review code history
- Collaborate with others
Aim for 5-10 commits per day.

6. ALWAYS REVIEW AI CODE
Don't blindly trust AI output. You are responsible.
You're the senior developer. AI is your junior developer.

7. WRITE REAL TESTS
Tests are not optional. They're your safety net.
Focus on integration tests and critical E2E paths.

8. KEEP CONTEXT UPDATED
Update context files when you make architectural decisions.
3 days from now, you'll forget why you made that choice.

9. MANUAL EDITING IS EXPECTED
AI is a tool, not a replacement for your skills.
Good developers: 60% AI-generated, 40% manually refined
Poor developers: 100% copy-paste without understanding

10. STAY IN CONTROL
You are the lead developer. AI is your assistant.
Never let AI drive architectural decisions without approval.
Red flag: "I don't understand what the AI built, but it works!"