Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Building Agentic AI System with Rag 2.0: A Practical Guide to Engineering RAG-Based AI Agents with Long-Term Memory and Tool Use

Building Agentic AI System with Rag 2.0: A Practical Guide to Engineering RAG-Based AI Agents with Long-Term Memory and Tool Use

Marris, Theo

Paperback

General Computers

ISBN13: 9798289498601
Publisher: Independently Published
Published: Jun 24 2025
Pages: 152
Weight: 0.61
Height: 0.33 Width: 7.00 Depth: 10.00
Language: English

Agentic AI is transforming how intelligent systems operate-moving beyond static responses to dynamic, tool-using, goal-driven behavior. At the heart of this evolution is Retrieval-Augmented Generation 2.0 (RAG 2.0), a new architectural pattern that fuses long-term memory, contextual reasoning, multi-agent coordination, and modular tool use for building advanced AI systems that act, learn, and adapt over time. This book delivers a practical blueprint for applying RAG 2.0 to real-world agentic workflows across enterprise, healthcare, education, and automation sectors.

Written by a seasoned AI practitioner and technical author specializing in LLM architectures, this guide is grounded in the latest research, including SafeRAG best practices, LangChain, LlamaIndex, Pinecone integration patterns, DSPy, GraphRAG, and AGI-aware agent design. Every chapter reflects current industry trends, community-driven implementations, and field-tested methodologies that have emerged from the leading AI labs and open-source communities.

Building Agentic AI System with RAG 2.0 is your complete roadmap to designing, implementing, and deploying powerful, scalable, and intelligent agents using the next generation of Retrieval-Augmented Generation techniques. Covering everything from system pipelines and memory management to prompt chaining, multi-agent orchestration, hallucination control, and ethical deployment, this book equips developers, architects, and AI enthusiasts with actionable insights and full-stack expertise. Whether you are building AI copilots, enterprise search assistants, autonomous agents, or educational tutors, this guide will accelerate your journey from experimentation to production readiness.

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