Artificial Intelligence applications are rapidly moving beyond simple question-answering systems. Modern enterprise AI assistants need to understand internal documents, retrieve accurate information, and provide reliable answers based on company knowledge.
I started building agentic AI systems from scratch — not to theorize about them, but to actually write the code, break it, and understand it from the inside out. This post walks through the second project in that journey: a Retrieval-Augmented Generation (RAG) system, what I built, what tripped me up, and where I'm taking it next.
What is RAG?
Retrieval-Augmented Generation combines two capabilities:
Retrieval: The system searches a knowledge base and finds relevant information related to the user's question.
