One change at work completely flipped my view on AI coding tools.

I’ll admit it — I wasn’t sold on AI coding tools.
Sure, I’d been using ChatGPT for content and brainstorming, but when it came to programming, I thought we were still years away from anything truly useful.
My early tests with GitHub Copilot didn’t help. The suggestions felt random, and I spent more time fixing its code than writing my own.
My takeaway? “Nice demo, but not ready for real work.”
The Corporate Catalyst
Everything shifted when my company rolled out Cursor for our dev team.
This wasn’t just another personal trial — we had enterprise licensing, training sessions, and teammates actively sharing tips and prompts.
So I went all in. Instead of dabbling, I committed to an AI-first workflow and made Cursor part of my daily development routine.
The Breakthrough Moment
Working with our massive, interconnected codebase, Cursor’s Agent Mode blew me away.
It:
Adapted to our coding style
Generated reliable unit tests
Tackled large-scale refactoring I’d normally avoid
When it got something wrong, the feedback loop was instant — I’d explain the issue, and it would fix it in minutes. That alone saved me hours every week.
Beyond the Day Job
That success led me to bring Cursor into my personal projects.
Whenever I tried a new framework or language, it became my on-demand mentor — explaining patterns, suggesting best practices, and helping me understand unfamiliar repos faster than docs or Stack Overflow.
The New Craft
Here’s what I’ve learned: AI coding tools are only as good as how you use them.
Prompting for code is a skill — just like writing clean tests or applying design patterns.
The trick? Treat the AI like a capable junior developer:
Give it context
Be specific
Let it handle structured, repetitive work
…while you focus on architecture and problem-solving.
I went from being an AI skeptic to having Cursor open in every dev session.
Not because it’s perfect — but because it’s now an essential part of my workflow.
💡 If you’ve tried AI coding tools before and given up — it might be time to try again.
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