How It Started
I was skeptical at first. Another AI hype cycle? But six months in, AI assistance has genuinely transformed how I work — not by replacing my thinking, but by amplifying it.
What I Use Claude For Daily
First Draft Generation
I no longer stare at a blank file. I describe what I need, get a first draft, and refine from there. It is faster than starting from scratch, even when I rewrite 80% of it.
Rubber Duck Debugging
Explaining a bug to Claude often helps me find the answer myself before it even responds. The act of articulation clarifies thinking.
Documentation
Writing docs is tedious. Claude drafts them from code and I edit. What took an hour now takes 10 minutes.
Learning New Technologies
"Explain Terraform workspaces to someone who knows Docker" — this kind of contextual learning is where Claude excels over generic documentation.
What Does Not Work Well
- Complex business logic with deep domain knowledge
- Anything requiring real-time data
- Long-term architectural decisions without full codebase context
The Skill That Matters Most
The highest-leverage skill is not prompting — it is knowing when AI output is wrong. Critical evaluation of AI suggestions requires deep technical knowledge. AI raises the floor but humans still set the ceiling.
Conclusion
AI is a force multiplier, not a replacement. The developers who thrive will be those who learn to collaborate effectively with AI tools while developing the judgment to know when to trust them — and when not to.
