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Agentic AI Systems: Multi-Agent Orchestration, RAG, and Memory Architectures for Intelligent Workflows
Paperback
Series: The Agentic AI Engineering, Book 3
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ISBN13: 9798186440444
Publisher: Independently Published
Pages: 198
Weight: 0.78
Height: 0.42 Width: 7.00 Depth: 10.00
Language: English
Publisher: Independently Published
Pages: 198
Weight: 0.78
Height: 0.42 Width: 7.00 Depth: 10.00
Language: English
Single agents can only take you so far. Learn to build the systems that power real production AI: teams of agents, grounded in real knowledge, that remember. Most multi-agent tutorials are really just one model wearing different prompts. Most RAG tutorials stop at a basic vector search with no idea why retrieval quality actually matters. And almost none of them show an agent that genuinely improves over time, rather than starting from zero in every session. AGENTIC AI SYSTEMS is a 17-chapter, hands-on guide to the three subjects real production agentic systems need together: multi-agent orchestration, retrieval-augmented generation (RAG), and long-term memory. You'll build Nexus, a complete system that coordinates specialized agents, grounds every answer in real, cited documents, and remembers what it learns across sessions. What you'll actually build:
Developers who've completed Book Two in this series - or have equivalent hands-on experience with LangChain, LangGraph, and structured output - and are ready to build the kind of sophisticated, production-grade agentic systems that single-agent tutorials never touch. Written by Dave Malhotra, with the same commitment throughout this series: real, working code over slideware, every concept explained before it's automated, every chapter building toward something you can actually run. A free companion package - full source code for Nexus, OnboardHub, StudyMind, and every supporting module - is available for download, no registration required. This is Book Three, the final volume in the Agentic AI Engineering series - completing the arc from hand-built fundamentals, through the professional toolchain, to fully unified multi-agent, retrieval-grounded, memory-capable systems. Build the systems that actually power production AI.
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