AI coding assistants can write boilerplate, explain unfamiliar code, generate tests and suggest fixes in seconds. Used well, they're a huge productivity boost. Used carelessly, they can quietly add bugs, outdated patterns or security problems.
Give context, get better code
Tell the assistant the language version, framework, existing conventions and constraints. Paste the relevant code and error messages, not just a description. “Using Laravel 11 and our existing Repository pattern” produces far better output than “write a PHP function”.
Review every line
Treat AI output like a pull request from a fast but junior teammate. Read it, understand it and question it. Watch for:
- Missing input validation and error handling
- SQL built with string concatenation instead of parameters
- Hard-coded secrets or credentials
- Deprecated functions or libraries that don't exist
- Edge cases: empty input, nulls, very large values
Let tests be the judge
Ask the AI to write tests along with the code, including edge cases, and run them. If you're refactoring, write or generate tests before changing the code so you can prove behaviour didn't change.
Protect sensitive code and data
Check your company's policy before pasting proprietary code into any external tool. Never paste API keys, passwords, customer data or production database dumps. Replace them with placeholders.
Use it to learn, not just to ship
Ask “why” as often as “how”. Requests like “explain this regex token by token” or “what are the trade-offs of this approach?” make you a better developer and help you spot when the AI is wrong.