AIGuide

Why we included this project

Developers who want to build AI applications without first becoming machine-learning researchers will find a lot to work with here. The guide moves through the practical stack in a sensible order, starting with LLM fundamentals, then RAG for enterprise knowledge bases, AI agents with tool calling and memory, and finally production system design, where gateways, rate limits, fallbacks, cost, observability, and security all get covered. The author also runs the well-known JavaGuide site, so the material is tuned for backend engineers in Java or Go who want to transfer existing skills, though frontend, test, and product people can jump in through the prompt, RAG, and agent sections. The repo also carries a couple of installable agent skills, including a draw.io diagram generator and Java coding standards, which work with Codex, Claude Code, and Cursor. Topic-organized interview questions round it out, making it a practical companion for both learning and job hunting.