{"product_id":"building-llm-agents-with-rag-mira-s-devlin-9798273159013","title":"Building LLM Agents with RAG, Knowledge Graphs \u0026 Reflection: A Practical Guide to Building Intelligent, Context-Aware, and Self-Improving AI Agent","description":"\u003cb\u003eTransform Large Language Models into Intelligent Agents That Reason, Retrieve, and Reflect\u003c\/b\u003e\u003cp\u003eIn \u003ci\u003eBuilding LLM Agents with RAG, Knowledge Graphs \u0026amp; Reflection\u003c\/i\u003e, AI systems architect Mira S. Devlin guides you beyond the surface of generative AI into the world of agentic intelligence-where LLMs evolve from reactive tools into dynamic collaborators capable of grounding responses in truth, understanding context, and improving over time.\u003c\/p\u003e\u003cp\u003eThis book doesn't just explain concepts-it helps you build them. Each chapter blends theory, diagrams, and applied examples to show how retrieval, reasoning, and reflection interact inside modern AI agents. Whether you're constructing a self-updating research assistant or a multi-agent workflow, you'll gain a deep understanding of how today's most advanced cognitive systems are designed.\u003c\/p\u003e\u003cbr\u003e\u003cb\u003eWhat You'll Learn\u003c\/b\u003e\u003col\u003e\n\u003cli\u003e\n\u003cp\u003eThe Cognitive Core of AI Agents\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cp\u003eUnderstand the architecture of transformers, tokenization, and attention.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eExplore the shift from static LLMs to adaptive, outcome-driven agents.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eLearn how retrieval, reflection, and reasoning form the four pillars of intelligence.\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003eRetrieval-Augmented Generation (RAG)\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cp\u003eImplement retrievers, rankers, and generators using open-source frameworks.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eEvaluate accuracy with metrics like Recall@K, Precision@K, and grounding quality.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eBuild a working RAG-powered knowledge bot capable of live data integration.\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003eKnowledge Graphs and Structured Reasoning\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cp\u003eDesign and query graph-based knowledge systems using Neo4j, ArangoDB, or GraphRAG.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eRepresent relationships between data entities for context-rich reasoning.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eCombine structured knowledge with unstructured language for explainable AI.\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003eReflection and Cognitive Loops\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cp\u003eImplement Plan → Act → Reflect → Revise cycles for self-improving intelligence.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eExplore short-term and long-term memory systems for continuous learning.\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003eMulti-Agent Collaboration\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cp\u003eArchitect intelligent teams of agents that can plan, delegate, and verify results.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eUnderstand communication protocols, cooperative memory, and role specialization.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eUse frameworks like CrewAI, LangGraph, and AutoGPT2 to orchestrate coordination.\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ol\u003e\u003cp\u003eEach chapter concludes with an \"Agent in Action\" section-hands-on projects and guided workflows that turn abstract concepts into working systems you can build, extend, and deploy.\u003c\/p\u003e\u003cb\u003eKey Features: \u003c\/b\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eEnd-to-end coverage: From LLM fundamentals to advanced RAG and reflection architectures.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eFramework-agnostic examples: Concepts applicable to GPT, Claude, Gemini, and open-source models.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003ePractical code labs: Step-by-step walkthroughs in Python with modular components.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eVisual clarity: Concept diagrams, data flow maps, and evaluation schematics throughout.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eDebugging insights: Identify hallucinations, reasoning gaps, and retrieval errors with real-world examples.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eScalable design patterns: Extend single-agent models into multi-agent collaborative systems.\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eAbout the Author: \u003c\/b\u003e\u003cp\u003eMira S. Devlin is an AI systems architect specializing in the intersection of language models, retrieval pipelines, and knowledge reasoning frameworks.\u003c\/p\u003e\u003cb\u003eWho This Book Is For: \u003c\/b\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eAI developers, data scientists, and engineers who want to move beyond simple LLM prompts.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eArchitects and product innovators building intelligent, explainable, and adaptive AI systems.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eResearchers and students seeking a structured understanding of retrieval-based reasoning and reflection.\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eTech leaders and educators integrating agentic AI into enterprise or academic zone.\u003c\/p\u003e\u003c\/li\u003e\n\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Mira S. Devlin\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9798273159013\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 11\/05\/2025\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 316\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.62lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 11.00h x 8.50w x 0.66d\u003c\/ul\u003e","brand":"Mira S. Devlin","offers":[{"title":"Paperback","offer_id":48175798550783,"sku":"9798273159013","price":24.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_c713c286-913a-4a0e-9713-632da7b6d9ce.jpg?v=1771335971","url":"https:\/\/www.whiterainbookhouse.com\/products\/building-llm-agents-with-rag-mira-s-devlin-9798273159013","provider":"WR Book House","version":"1.0","type":"link"}