AI is now part of my daily workflow, but I learned quickly that speed is not the same as progress.
At first, I used AI like overpowered autocomplete. I shipped faster, but I also reviewed less carefully and sometimes approved code that looked fine while violating boundaries.
The fix was simple: keep clear guardrails.
Core principle
AI can generate options. Engineers still own decisions.
- AI drafts implementation.
- Engineers own architecture.
- AI suggests tests.
- Engineers define quality.
If I cannot explain why a change exists, I do not merge it.
My workflow (short version)
- Define constraints first: behavior, non-goals, performance, security.
- Ask for options with trade-offs, not one-shot code.
- Generate in small slices I can fully review.
- Verify with the same quality bar every time.
That is it. No magic, just discipline.
Common mistakes with AI
- Premature abstraction.
- Boundary leaks between domains.
- Weak edge-case handling.
- Tests that check implementation, not behavior.
Final thought
The advantage is not typing faster. The advantage is keeping strong judgment while moving quickly.
Use AI as force multiplication, not decision outsourcing.
