Building with AI without losing your mind
How I use AI as a coding assistant without letting it replace the thinking. Lessons from six months of daily use.
AI coding assistants are genuinely useful. But there's a failure mode nobody talks about: you stop thinking, and the code starts thinking for you.
I've been using AI assistants daily for six months. Here's what I've learned about keeping the balance right.
The trap
When you're stuck, it's tempting to hand the whole problem to the model. You paste in a function, ask it to fix the bug, and it does — sometimes. But when you don't understand the fix, you've only deferred the confusion. The bug comes back in a different form, and now you have even less to work with.
What actually works
Use AI for the mechanical parts — boilerplate, type definitions, repetitive transforms, documentation lookup. Keep the architecture, the data model, and the tricky logic decisions to yourself.
Ask it questions, not for answers. "What are the tradeoffs between X and Y?" produces more useful output than "Write me a function that does Z."
The rule I follow
If I can't explain what the generated code does line by line, I don't commit it. This sounds slow. It's not — it forces me to read carefully, and that reading is where I actually learn.
Final thought
AI doesn't replace the thinking. It replaces the typing. Keep the thinking.