The initial resistance
When AI coding tools first emerged, I was skeptical. Would they make us lazy? Would they erode the deep understanding that comes from struggling with problems? Would we become dependent on autocomplete for everything?
Some of those concerns were valid. Some were not.
What I've learned
After months of building with AI assistance, here's what I've found:
AI excels at:
- Boilerplate and repetitive patterns
- Explaining unfamiliar codebases
- Suggesting alternative approaches
- Catching obvious mistakes
AI struggles with:
- Novel architecture decisions
- Understanding business context
- Maintaining consistent style across a project
- Knowing when to break the rules
The craft question
Does using AI diminish craft? I don't think so—if you use it right.
The craft isn't in typing code. It's in:
- Knowing what to build
- Understanding the tradeoffs
- Maintaining quality over time
- Solving problems that haven't been solved before
AI can help with execution, but the thinking is still yours.
My current approach
I use AI as a thoughtful collaborator:
- I explain what I'm trying to achieve
- I evaluate its suggestions critically
- I modify and adapt rather than accept blindly
- I stay curious about how things work underneath
The goal isn't to write less code. It's to spend more time on the parts that matter.
Looking ahead
AI tools will keep improving. The best response isn't resistance—it's adaptation. Learn to collaborate with these tools while maintaining the judgment that makes you valuable.
The future belongs to those who can think clearly and leverage tools effectively. That's always been true. AI just makes it more obvious.