Unlocking Data with Generative AI and RAG: Learn AI agent fundamentals with RAG-powered memory, graph-based RAG, and intelligent recall , Second Edition

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Key benefits

Build next-gen AI systems using agent memory, semantic caches, and LangMem

Implement graph-based retrieval pipelines with ontologies and vector search

Create intelligent, self-improving AI agents with agentic memory architectures

Description

Developing AI agents that remember, adapt, and reason over complex knowledge isn’t a distant vision anymore; it’s happening now with Retrieval-Augmented Generation (RAG). This second edition of the bestselling guide leads you to the forefront of agentic system design, showing you how to build intelligent, explainable, and context-aware applications powered by RAG pipelines. You’ll master the building blocks of agentic memory, including semantic caches, procedural learning with LangMem, and the emerging CoALA framework for cognitive agents. You’ll also learn how to integrate GraphRAG with tools such as Neo4j to create deeply contextualized AI responses grounded in ontology-driven data. This book walks you through real implementations of working, episodic, semantic, and procedural memory using vector stores, prompting strategies, and feedback loops to create systems that continuously learn and refine their behavior. With hands-on code and production-ready patterns, you’ll be ready to build advanced AI systems that not only generate answers but also learn, recall, and evolve. Written by a seasoned AI educator and engineer, this book blends conceptual clarity with practical insight, offering both foundational knowledge and cutting-edge tools for modern AI development. *Email sign-up and proof of purchase required

Who is this book for?

If you’re an AI engineer, data scientist, or developer building agent-based AI systems, this book will guide you with its deep coverage of retrieval-augmented generation, memory components, and intelligent prompting. With a basic understanding of Python and LLMs, you’ll be able to make the most of what this book offers.

What you will learn

Architect graph-powered RAG agents with ontology-driven knowledge bases

Build semantic caches to improve response speed and reduce hallucinations

Code memory pipelines for working, episodic, semantic, and procedural recall

Implement agentic learning using LangMem and prompt optimization strategies

Integrate retrieval, generation, and consolidation for self-improving agents

Design caching and memory schemas for scalable, adaptive AI systems

Use Neo4j, LangChain, and vector databases in production-ready RAG pipelines

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Shipping Details

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Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

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Unfortunately, due to several restrictions, we are unable to ship to the following countries:

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Unlocking Data with Generative AI and RAG: Learn AI agent fundamentals with RAG-powered memory, graph-based RAG, and intelligent recall , Second Edition

What do you get with Print?