Volume 1 of The Agentic AI Handbook. Architecting Agentic AI: Fundamentals & Core Patterns is a rigorous, practitioner-grade guide to the foundational building blocks of production agentic systems — not demos. It moves from first principles to battle-tested design: the core agent loop, memory and context persistence, tool invocation and external integration, retrieval and context engineering, and prompt chaining and instruction trees.
Written for AI architects, ML engineers, and technical leaders, every chapter pairs concept with implementation — annotated code, reference architectures, and decision frameworks grounded in the latest models (Gemini 3.x, GPT-5.x, Claude 4.x, Llama 4). You will learn how to choose between long-context and retrieval, structure multi-step reasoning, wire agents to real tools and data, and design the core patterns every production agentic system is built from — independent of any single vendor or framework.
This is the foundational half of the series' architecture spine; Volume 2 continues with multi-agent architectures, governance, and frameworks, and every industry volume that follows builds on the patterns established here.
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