Six months ago, I decided to go all-in on AI coding assistants. Not just for fun — I used them on real production projects, real deadlines, and real bugs. No benchmarks, no marketing fluff. Just my honest experience as a backend developer.
What I Used
I tested three main tools across different scenarios:
- GitHub Copilot — daily driver for autocomplete and small functions
- ChatGPT/Claude — for architectural questions and debugging
- Cursor — for larger refactoring and new feature generation
The Good Stuff
Let me be honest — some things genuinely saved me time.
1. Boilerplate disappears. Writing CRUD endpoints, database schemas, middleware — Copilot nails this in seconds. It’s not perfect, but it’s 80% there.
2. Debugging got faster. Paste an error, ask Claude “why is this happening,” and more often than not, you get a solid explanation. Way faster than Stack Overflow.
3. Learning new stuff. I needed to work with Redis caching recently. Instead of tutorials, I asked an AI to explain it in context of my codebase. Game changer.
The Bad Stuff
Here’s where I got burned:
1. It writes confident wrong code. The worst part? The code looks good. It passes linting. But it silently does the wrong thing. I shipped a bug where a query was fetching all users instead of filtered ones. AI made it look correct.
2. Context blindness. AI doesn’t know your team’s conventions, your legacy code quirks, or your business logic. It’ll suggest solutions that work but don’t fit your system.
3. I stopped thinking. This is the scary one. When AI handles the easy stuff, I sometimes just accept what it writes without understanding it. That’s a recipe for disaster in production.
What I Learned
After six months, here’s my current approach:
- Use AI for exploration, not execution. Let it explain concepts, draft solutions, or find bugs. But review every line before committing.
- Don’t trust it with security or data logic. Anything related to auth, payments, or data validation — I write from scratch. Too many hidden risks.
- Keep your skills sharp. I make sure I could solve the problem without AI. The tool should make me faster, not dependent.
Final Verdict
AI coding assistants are useful. I’m not going back to not using them. But they’re not replacing me — they’re augmenting me. The developers who thrive will be the ones who learn to work with AI while keeping their fundamentals strong.
The danger isn’t AI getting too good. It’s us getting too comfortable.