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The Agentic AI Security & Systems Engineering Series explores the cutting edge of autonomous large language models (LLMs), multi-agent coordination, and secure system deployment in enterprise environments.
Each volume dives deep into the design, protection, and governance of agentic AI, blending the disciplines of cybersecurity, distributed systems, and applied machine learning.
Written by experts for professionals, the series provides actionable architectures, real-world security frameworks, and rigorous implementation guides built on LangGraph, LangChain, and modern AI orchestration stacks.
From adversarial threat modeling to schema-bound reasoning and compliance enforcement, these books equip engineers and architects to build AI systems that are not only intelligent-but resilient, verifiable, and secure.
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