The AI Coding Toolkit for Developers

Every developer today is using some form of AI to code, but the real question is whether you're using it well. Used badly, AI tools make you faster at shipping bugs you don't understand. Used well, they compress weeks of work into hours without you losing the ability to reason about your own code.

This is a practical, no-hype map of the current AI coding tool landscape (Cursor, Claude Code, GitHub Copilot, ChatGPT/Codex, v0, Amazon Q): what each is actually best for based on real projects, not marketing pages, plus the prompting habits that separate developers who get real leverage from AI vs. developers who just get more noise.

What's inside: a tool-by-tool breakdown with best use case and typical pricing for every major AI coding assistant, a simple framework for choosing autocomplete vs. agentic/chat tools for any task, prompting patterns that actually work including how to give context before asking for code and how to get a plan before code on non-trivial changes, and guidance on avoiding the over-subscribe trap with the 2-tool combo that covers 95% of real work.

Perfect for frontend/full-stack developers who want to move faster without sacrificing code quality, students prepping for interview questions about how they built something, and anyone using AI tools inconsistently who wants an actual system.