Production Memory Engineering for Agentic AI

As LLMs transition from static text generators to autonomous agents, the biggest bottleneck is memory. Standard RAG (injecting documents into a flat context window) is no longer enough. To build agents that can plan, personalize, learn from mistakes, and persist context across weeks of conversations, you need a Memory-Augmented Architecture.

This book is a comprehensive, production-first guide to building state-of-the-art cognitive memory engines. It bridges the gap between theoretical cognitive science and practical software engineering by leveraging FastAPI, LangGraph, and Ollama in a fully local stack.