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

De: Practicing Engineers Network

Narrado por: Virtual Voice

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 Learn

• What truly distinguishes AI agents from chatbots and automations

• Core agent design patterns, including reactive, role-based, workflow, and human-in-the-loop architectures

• How to implement the same real-world use case across multiple platforms and frameworks

• How to choose the right agent platform based on risk, scale, governance, and complexity

• Best practices for security, compliance, and auditability in agent systems

• How to future-proof agent designs as tools and models evolve

Platforms and Frameworks Covered

• LangChain and LangGraph

• CrewAI

• LlamaIndex

• OpenAI Custom GPTs and experimental agent frameworks

• Google Opal

• Microsoft Copilot Studio

• Google Vertex AI Agent Builder

• n8n, Zapier, and Make

A Real-World, End-to-End Use Case

Throughout 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 For

• Software engineers and solution architects

• Enterprise IT and automation teams

• Technical product managers

• AI practitioners moving from prototypes to production

• Anyone responsible for building AI systems that must be reliable and auditable

This 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.