AI & Tools
Top AI Tools for Developers
AI tooling for developers goes well beyond autocomplete now -- here's the landscape by category, not just a list of product names.
The Main Categories
- AI coding assistants -- inline code completion and chat-based pair programming inside your editor
- AI code review tools -- automated first-pass review flagging potential bugs, security issues, or style problems before a human reviewer looks
- AI-assisted documentation -- generating and keeping API docs/comments in sync with actual code
- AI-powered test generation -- suggesting unit tests based on existing code paths
- AI-assisted debugging -- explaining a stack trace or error message in plain language and suggesting likely causes
Example: Using an AI Assistant Well vs. Poorly
Poor use: accepting a generated function wholesale without reading it, then being unable to explain what it does or debug it later when something breaks. Good use: asking the assistant to generate a first draft of a repetitive but well-understood piece of code (a DTO mapper, a standard CRUD endpoint), then reviewing it line by line the same way you'd review a teammate's pull request -- catching the edge cases it missed, and understanding exactly what it produced before it ships.
Frequently Asked Questions
Not in any near-term, wholesale sense -- they change what a developer spends time on (less boilerplate typing, more reviewing, architecting, and debugging), similar to how earlier tooling shifts (IDEs, frameworks, package managers) changed the job without eliminating it. The skill that matters most now is being able to critically evaluate AI-generated code, not just accept it.
Depends entirely on the specific interview's stated rules -- some explicitly allow it (and evaluate how you use it), most traditional live-coding interviews still don't. Always ask directly rather than assuming either way.