{"product_id":"ai-agents-pocket-guide-patterns-for-building-autonomous-systems-with-llms-9798258950147","title":"AI Agents Pocket Guide: Patterns for Building Autonomous Systems with LLMs","description":"\u003cp\u003e • Author(s): Gabriel Anhaia\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Machine Theory\u003c\/p\u003e\u003cp\u003e\u003cb\u003eBuild AI agents that actually work - without being locked into any framework.\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eMost tutorials teach you a specific library. This book teaches you the \u003ci\u003epatterns\u003c\/i\u003e. Whether you use LangChain, CrewAI, AutoGen, or raw API calls, the architecture behind reliable AI agents is the same. \u003cb\u003eAI Agents Pocket Guide\u003c\/b\u003e gives you framework-agnostic blueprints you can apply anywhere. \u003cp\u003e\u003c\/p\u003eAcross \u003cb\u003e14 chapters\u003c\/b\u003e, you will learn how to design, build, and deploy autonomous systems powered by large language models: \u003cp\u003e\u003c\/p\u003e- \u003cb\u003eTool Use\u003c\/b\u003e - Give your agents hands. Call APIs, query databases, and execute code safely.\u003cbr\u003e- \u003cb\u003eMemory\u003c\/b\u003e - Short-term, long-term, and episodic memory patterns that let agents learn and recall.\u003cbr\u003e- \u003cb\u003eRAG (Retrieval-Augmented Generation)\u003c\/b\u003e - Ground agent responses in your own data with vector search and hybrid retrieval.\u003cbr\u003e- \u003cb\u003ePlanning \u0026amp; Reasoning\u003c\/b\u003e - ReAct, chain-of-thought, tree-of-thought, and task decomposition strategies.\u003cbr\u003e- \u003cb\u003eMulti-Agent Systems\u003c\/b\u003e - Orchestrate teams of specialized agents with delegation, routing, and consensus patterns.\u003cbr\u003e- \u003cb\u003eGuardrails\u003c\/b\u003e - Input validation, output filtering, and safety layers that keep agents from going off the rails.\u003cbr\u003e- \u003cb\u003eEvaluation\u003c\/b\u003e - Measure agent quality with deterministic and LLM-as-judge evaluation pipelines.\u003cbr\u003e- \u003cb\u003eDeployment\u003c\/b\u003e - Take agents to production with observability, error handling, cost control, and scaling strategies. \u003cp\u003e\u003c\/p\u003eEvery pattern comes with \u003cb\u003eclear Python code examples\u003c\/b\u003e you can adapt to your stack. No filler, no hype - just the engineering decisions that separate toy demos from production-grade agents. \u003cp\u003e\u003c\/p\u003e\u003cb\u003eWho this book is for: \u003c\/b\u003e Software engineers, ML engineers, and technical leads who want to build AI agents grounded in solid architecture - not framework lock-in. \u003cp\u003e\u003c\/p\u003e\u003cb\u003eOther books in Pocket Guides for Developers\u003c\/b\u003e (standalone, no reading order): \u003cbr\u003e- \u003ci\u003eSystem Design Pocket Guide: Fundamentals\u003c\/i\u003e\u003cbr\u003e- \u003ci\u003eSystem Design Pocket Guide: Interviews\u003c\/i\u003e\u003cbr\u003e- \u003cb\u003eThis book\u003c\/b\u003e - \u003ci\u003eAI Agents Pocket Guide\u003c\/i\u003e\u003cbr\u003e- \u003ci\u003ePrompt Engineering Pocket Guide\u003c\/i\u003e\u003cbr\u003e- \u003ci\u003eDatabase Playbook\u003c\/i\u003e\u003cbr\u003e- \u003ci\u003eLLM Observability Pocket Guide\u003c\/i\u003e\u003cbr\u003e- \u003ci\u003eEvent-Driven Architecture Pocket Guide\u003c\/i\u003e\u003cbr\u003e- \u003ci\u003eRAG Pocket Guide\u003c\/i\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47883345199255,"sku":"9798258950147","price":2155.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798258950147.webp?v=1781101296","url":"https:\/\/atlanticbooks.com\/products\/ai-agents-pocket-guide-patterns-for-building-autonomous-systems-with-llms-9798258950147","provider":"Atlantic Books","version":"1.0","type":"link"}