Agentic Engineering

What happens when AI agents stop working alone and start working as a team?Artificial Intelligence is entering a new phase in which intelligent systems can do more than respond to individual instructions. Multiple specialized agents can collaborate, divide complex tasks, communicate with one another, use tools, evaluate results, and coordinate their actions toward a shared objective.Multi-Agent AI Systems: The Complete Handbook for Building Intelligent, Scalable, and Autonomous Agent Teams provides a practical roadmap for understanding this emerging paradigm.The book begins with the fundamentals of multi-agent systems and explains why collaboration between specialized agents can be valuable for complex workflows. Readers will learn about hierarchical, peer-to-peer, and hybrid architectures, along with roles such as manager, planner, worker, critic, and supervisor agents.It then moves into modern frameworks and technologies, including CrewAI, AutoGen, LangGraph, MetaGPT, LLMs, vector databases, and agent memory systems. Practical chapters explain how to design agent teams, decompose tasks, establish communication protocols, manage shared memory, coordinate workflows, integrate tools and APIs, and recover from failures.Readers will also explore advanced concepts such as dynamic replanning, parallel execution, swarm intelligence, agent debates, self-organizing systems, human-in-the-loop workflows, and multimodal agents.The book goes beyond experimentation and addresses the challenges of deploying multi-agent systems in real environments. Cloud deployment, Docker, Kubernetes, monitoring, logging, scaling, evaluation, benchmarking, testing, and cost optimization are included.Real-world applications demonstrate how agent teams can support software development, research, customer service, content creation, and business operations.Equally important, the book examines AI safety, privacy, security, transparency, governance, alignment, and responsible AI development.Whether you are a student discovering agentic AI, a developer building your first agent team, a researcher exploring collaborative intelligence, or a professional preparing for the next generation of AI applications, this book provides a foundation for moving from individual AI agents toward coordinated intelligent systems.Understand the architecture. Design the team. Build the agents. Coordinate the intelligence.

The first thing many people hit with an AI coding assistant is a plateau. A correction made on Monday is gone by Thursday. This book is about the operating model above the prompt, where truth lives, how a correction becomes a standing rule that holds, and which judgments stay in human hands.

一本面向有一定 AI 基础的工程师、技术负责人与产品人的实战手册。它回答一个被大多数 AI 内容回避的问题：为什么大多数 AI 项目止步于 Demo，而少数能真正跑进生产？

Move Beyond Simple Prompts. Build Reliable, Autonomous AI Systems.Connecting an LLM to an API is easy; building an AI agent that works reliably in production is hard. Mastering AI Agents gives you the exact architectural frameworks, workflows, and engineering practices needed to design, deploy, and scale intelligent agents that solve real-world problems.Practical Engineering: Master memory systems, tool integration, multi-agent orchestration, and system security.Production-Ready Focus: Learn how to evaluate, monitor, and maintain agents so they remain controllable and safe.Evergreen Principles: Built on core software architecture principles that stay valuable even as frameworks and models evolve.Grab your copy today and start building the next generation of intelligent software!

Short Description of the BookSecuring Modern AI Applications is a practical guide to securing LLM-powered applications, RAG systems, AI agents, and modern AI development environments.The book explains AI-specific threats such as prompt injection, data leakage, RAG poisoning, insecure tool use, agent abuse, and AI supply-chain risks while also covering traditional application security, privacy, governance, secure development, monitoring, testing, and red teaming.Designed for developers, AI engineers, cybersecurity professionals, architects, and technology leaders, the book focuses on practical principles that remain useful as AI technologies continue to evolve.Build AI. Secure AI. Govern AI.

Build real-world web applications faster with Claude Code by your side. This hands-on guide takes you from web development fundamentals to production-ready full-stack engineering with React, Next.js, TypeScript and PostgreSQL. Learn practical AI-assisted workflows while building, testing, securing and deploying applications that are ready for real users.

This book presents a modern, unified, and language-agnostic workflow for creating analytical pipelines that are truly reproducible, from environment to execution.

Build the Next Generation of Enterprise AI SystemsCloud-Powered Agentic AI is a practical guide to designing, developing, deploying, and operating production-ready AI applications using Large Language Models (LLMs) and modern cloud-native technologies.From prompt engineering and Retrieval-Augmented Generation (RAG) to AI agents, multi-agent systems, Model Context Protocol (MCP), FastAPI, Docker, Kubernetes, and LLMOps, this book provides a complete roadmap for building scalable, secure, and maintainable AI solutions.Through hands-on examples, architecture diagrams, case studies, and a comprehensive capstone project, you will learn how to move beyond prototypes and engineer enterprise-grade AI systems.Inside this book, you'll learn how to:Build LLM-powered applications from scratchDesign Retrieval-Augmented Generation (RAG) pipelinesDevelop AI agents and multi-agent workflowsIntegrate tools using the Model Context Protocol (MCP)Deploy AI services with FastAPI, Docker, and KubernetesApply LLMOps for monitoring, evaluation, and continuous deliverySecure and govern AI applications in enterprise environmentsBuild a complete cloud-native AI platform from development to productionWhether you are an AI engineer, software developer, cloud architect, or machine learning practitioner, this book will equip you with the practical skills needed to build reliable and scalable AI systems in the era of generative AI.

Artificial Intelligence is no longer the future—it is transforming the way we work, learn, create, and innovate today. Whether you're a student, professional, entrepreneur, freelancer, educator, or software developer, understanding Generative AI is becoming an essential skill.Generative AI Mastery is your practical guide to unlocking the full potential of AI. From mastering prompt engineering and boosting productivity to enhancing business operations, software development, research, writing, creativity, and decision-making, this book provides the knowledge and real-world strategies you need to use AI with confidence.Inside, you'll discover:How Generative AI works and why it mattersEffective prompt engineering techniquesPractical AI applications for work, business, and educationAI tools for writing, coding, research, and creativityEthical AI, privacy, security, and responsible useFuture career opportunities in the age of AIPractical prompts, templates, and implementation strategiesRather than focusing on a single AI tool, this book teaches timeless principles and transferable skills that remain valuable as AI continues to evolve.Whether you're just beginning your AI journey or looking to maximize your professional potential, Generative AI Mastery will help you work smarter, innovate faster, and thrive in the age of Artificial Intelligence.

Build AI agents that go beyond conversation._ AI Agents Mastery_ is a practical guide to designing, building, deploying, and scaling autonomous AI agents for real-world applications.Learn how to combine LLMs with tools, APIs, workflows, memory, state, retrieval, automation, security, monitoring, and human oversight to create capable and reliable AI agent systems.From the fundamentals of agent architecture to production deployment and responsible autonomy, this book provides an end-to-end framework for turning AI-agent ideas into practical applications.Learn the principles. Build the systems. Deploy with confidence.

AI agents don’t fail because they forget everything. They fail because they remember badly. This book shows you how to engineer memory that stays accurate, efficient and useful over time. From SQLite and PostgreSQL to vector indexes and multi-agent systems, you’ll learn what it takes to build agents that can run for days without losing the plot.

Turn a small language model into an AI agent that runs on your own hardware. This practical guide takes you from choosing a base model to fine-tuning, tool use, evaluation and deployment. With reproducible code and real configurations throughout, you'll learn how to build specialized local agents that are capable, efficient and truly yours.

Specification Engineering turns complex ideas into clear, workable specifications. This practical guide takes you from core principles to advanced methods for defining, validating, managing and evolving requirements across products, software, systems and services. Built for real-world use, it gives you the tools to create specifications that people can understand and act on.

They say AI is coming for junior developers first. This is a junior's honest case for the opposite: how driving agents well, on real legacy code, makes you level up faster instead of getting left behind. The failures are left in.

Domine a arquitetura de sistemas de IA autônomos. Um guia completo cobrindo motores de raciocínio, memória de longo prazo, orquestração multiagentes, otimização de custos e o Model Context Protocol (MCP). O livro definitivo para arquitetos e desenvolvedores.