Building AI Agents Platforms, Frameworks, and Real-World Implementations How to Build AI Agents Using LangChain, LangGraph [#1040625]

Building AI Agents: Platforms, Frameworks, and Real-World Implementations: How to Build AI Agents Using LangChain, LangGraph, CrewAI, LlamaIndex, Vertex AI, Google Opal, Copilot Studio, n8n, and More
English | December 16, 2025 | ASIN: B0G7BQT516 | 176 pages | Epub | 2.86 MB
AI agents are no longer experimental-they are becoming core building blocks of modern software systems. From document analysis and workflow automation to enterprise decision support, AI agents now operate at the intersection of reasoning, data, and action.Building AI Agents Using Modern Platforms and Frameworks is a practical, architecture-first guide to designing, implementing, and scaling AI agent systems across today's most widely used tools and platforms.Rather than focusing on a single vendor or framework, this book teaches you how to think like an AI agent architect. You will learn how to design agents that are reliable, governable, and production-ready-whether you are using developer frameworks, no-code platforms, or enterprise cloud services.What You'll LearnWhat truly distinguishes AI agents from chatbots and automationsCore agent design patterns, including reactive, role-based, workflow, and human-in-the-loop architecturesHow to implement the same real-world use case across multiple platforms and frameworksHow to choose the right agent platform based on risk, scale, governance, and complexityBest practices for security, compliance, and auditability in agent systemsHow to future-proof agent designs as tools and models evolvePlatforms and Frameworks CoveredLangChain and LangGraphCrewAILlamaIndexOpenAI Custom GPTs and experimental agent frameworksGoogle OpalMicrosoft Copilot StudioGoogle Vertex AI Agent Buildern8n, Zapier, and MakeA Real-World, End-to-End Use CaseThroughout the book, a single enterprise use case-document intake, analysis, and decision support-is implemented repeatedly across different platforms. This approach reveals what stays consistent in agent design and what changes depending on the tool.Who This Book Is ForSoftware engineers and solution architectsEnterprise IT and automation teamsTechnical product managersAI practitioners moving from prototypes to productionAnyone responsible for building AI systems that must be reliable and auditableThis is not a prompt collection or a vendor sales guide. It is a practical engineering reference for building AI agents that work in the real world-safely, responsibly, and at scale.If you want to move beyond experimentation and start building AI agents you can trust, this book is your guide.