The Harsh Truths
1. Your Expertise Still Matters (More Than Ever)
- Can’t guide AI without knowing SOLID principles
- Can’t review AI code without understanding performance implications
- Can’t prompt AI without architectural vision
- Garbage prompts = garbage code
2. Style Guides Become Critical
AI can generate volumes of technically correct but unmaintainable code. Your style guides and coding standards are the guardrails preventing AI from creating technical debt at scale.
3. Code Review Is Non-Negotiable
- AI writes plausible-looking bugs
- AI copies patterns without understanding context
- AI optimizes for “works” not “maintainable”
- You’re still responsible for what ships
4. The Junior Developer Problem
If your team uses AI without foundational knowledge, you’ll inherit a maintainability nightmare. AI amplifies both good and bad practices.
What Actually Works
The Sweet Spot: Amplifying Expertise
- Boilerplate acceleration: Tests, migrations, config files - let AI handle the tedious stuff
- Rapid prototyping: Generate 3 approaches, cherry-pick the best patterns
- Architecture-guided prompting: “Implement this following our existing error handling patterns”
Non-Negotiables
- Review ruthlessly: AI code gets the same scrutiny as human code
- Enforce standards: Your linters and tests catch what humans miss
- Know your domain: AI doesn’t understand your business logic
- Prompt with precision: Specify constraints, patterns, edge cases
The Reality Check
AI is a powerful tool, not a replacement for engineering judgment. It’s like giving a junior developer superpowers - they can build faster, but they still need guidance.
Your value isn’t decreased by AI. It’s amplified.