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Agentic AI Foundations: Build Intelligent Autonomous Systems with Python (Agentic AI Mini-Series Book 1)
English | May 9, 2026 | ASIN: B0GY1ZSB7Y | 166 pages | Epub | 282.91 KB
Build the next generation of intelligent AI systems - one real project at a time.Agentic AI for Developers is a complete hands-on series designed for developers, engineers, researchers, and AI builders who want to move beyond simple prompts and learn how to create autonomous AI agents that can reason, plan, use tools, collaborate, and operate in production environments.In this book, you will learn:* ReAct-based reasoning agents * Tool-using AI systems * Memory-driven conversational agents * LangChain and LangGraph workflows * Claude MCP-powered systems * OpenAI Agents SDK applications * Multi-agent systems using AutoGen and CrewAI * Enterprise-grade production AI infrastructure What Makes This Series Different?✔ Python-first learning approach ✔ Research-grounded explanations ✔ Production-focused architecture patterns ✔ Real-world case studies ✔ Step-by-step implementations ✔ Modern frameworks used in 2025-2026 Whether you are building your first AI agent or designing enterprise-scale autonomous systems, this series provides a structured roadmap from fundamentals to production deployment.If you want to understand how modern AI agents actually work - and build them yourself - this book was written for you.

Agentic AI For Beginners: From Concept To Digital Co-Worker: Build Intelligent AI Agents that Think, Plan, and Act in the real world.
English | May 6, 2026 | ASIN: B0GZM3MBMF | 647 pages | Epub | 0.3 MB
Agentic AI is changing how software gets built, automated, and used.For years, most people interacted with AI as a chatbot: ask a question, get an answer, repeat. But the next major shift is already here. AI systems are moving beyond simple prompt-and-response interactions into agents that can reason through goals, create plans, use tools, remember context, and move multi-step work forward.Agentic AI for Beginners is a practical, beginner-friendly guide to understanding and building AI agents without needing an advanced machine learning background.This book explains agentic AI as a system, not magic. You will learn how language models, prompts, tools, memory, orchestration, approval gates, evaluation, and security work together to create useful AI agents.Inside, you will learn how to:Understand what makes an AI agent different from a chatbotBreak goals into plans, tasks, and workflowsConnect agents to tools such as search, files, APIs, databases, email, calendars, and code executionDesign memory without creating confusion or privacy risksBuild safe approval gates for higher-risk actionsEvaluate whether an agent is actually workingAvoid common beginner mistakes with tool use, memory, and autonomyApply agents to founder workflows, developer workflows, business operations, and automation tasksBuild a complete beginner business automation agentContinue learning with a practical 90-day roadmapThis book is written for developers, automation engineers, founders, technical beginners, business operators, and anyone who wants to understand how practical AI agent systems are designed.You do not need to be an AI researcher. You do not need to train your own model. You do not need to understand advanced AI mathematics.You only need curiosity, basic technical comfort, and a desire to build useful systems.If you want to move beyond prompting and start understanding how AI agents actually work, this book will give you the foundation.

Agentic AI For Beginners: Build Intelligent AI Agents That Think, Plan, and Act Autonomously
English | May 20, 2026 | ASIN: B0H2FCZ11W | 270 pages | Epub | 697.34 KB
Agentic AI is transforming how we work, but most people are still stuck building basic chatbots that need hand-holding for every task.What if you could create intelligent AI agents that operate like digital employees - breaking down complex goals, using tools, remembering context, adapting to feedback, and executing multi-step tasks completely autonomously?This guide shows you how.Whether you are an entrepreneur looking to automate your business operations, a marketer wanting to scale content and research, a developer expanding into AI automation, or simply curious about the technology powering the next wave of productivity tools, this book provides a clear, beginner-friendly roadmap from concept to deployment.Inside, you will discover:* The core architecture of agentic AI systems - how agents differ from chatbots and why that matters* Reasoning loops and goal decomposition - teaching agents to plan, act, observe, and iterate* Tool integration patterns - connecting agents to APIs, databases, search engines, and real-world systems* Memory systems - short-term, long-term, and episodic memory for context-aware agents* Error handling and safety - building reliable agents that fail gracefully and stay on track* No-code and low-code approaches - accessible entry points for non-developers* Code examples and frameworks - for those ready to build with Python, LangChain, AutoGPT, and more* Real-world use cases - research automation, content generation, data analysis, customer support, competitive intelligence* Deployment strategies - moving from prototype to production-ready autonomous systems* Monitoring and optimization - ensuring your agents improve over timeNo PhD required. No enterprise budget needed. Just practical steps and proven patterns.This book strips away the jargon and focuses on what actually works. You will learn the mental models, architecture blueprints, and implementation workflows that let you design AI agents that work while you sleep - handling tasks that previously consumed hours of manual effort.Readers report deploying their first functional agent within 48 hours and automating 10+ hours of weekly work within the first month.Stop being a prompt writer. Become an architect of intelligent systems.Whether you want to multiply your personal productivity, build AI-powered products, or simply understand the technology reshaping every industry, this guide gives you the foundation to move from concept to working digital co-worker.Perfect for: Entrepreneurs, solopreneurs, marketers, content creators, developers, product managers, consultants, students, and anyone ready to master the future of AI automation.Get your copy today and start building agents that think, plan, and act autonomously.

Agentic AI Engineering with Microsoft Foundry: Design, Build, Evaluate, Monitor, and Deploy Enterprise AI Agents That Solve Real Business Problems
English | May 23, 2026 | ASIN: B0GZL31GZ9 | 266 pages | Epub | 6.42 MB
Agentic AI Engineering with Microsoft Foundry: Design, Build, Evaluate, Monitor, and Deploy Enterprise AI Agents That Solve Real Business ProblemsBuild AI agents that do more than answer prompts. Build agents that solve real business problems with structure, reliability, evaluation, monitoring, and production discipline.Many developers can create a quick chatbot, but turning that chatbot into a useful enterprise AI agent is a different challenge. How do you connect agents to trusted business data? How do you give them tools without creating risk? How do you evaluate quality, monitor behavior, control cost, and deploy systems that teams can actually depend on?Agentic AI Engineering with Microsoft Foundry gives you a practical, step-by-step guide to building enterprise-ready AI agents with Microsoft Foundry, Azure AI services, retrieval-augmented generation, custom tools, evaluation workflows, tracing, and production monitoring.This book is written for builders who want clear implementation guidance, not vague theory. You will learn how to design agentic AI systems around real business needs, connect models to documents and data, add safe tool use, build code-first agents, create multi-agent workflows, evaluate performance, and prepare agent systems for deployment.Inside, you will learn how to:Set up Microsoft Foundry projects for agent developmentBuild code-first agents with practical Python and .NET workflowsConnect agents to files, Azure AI Search, tools, APIs, and Azure FunctionsDesign retrieval-augmented agents that answer from trusted sourcesCreate structured outputs for tickets, reports, reviews, and decisionsBuild workflow-based and multi-agent systems with clear responsibilitiesEvaluate groundedness, relevance, tool behavior, safety, and task completionTrace, debug, monitor, and improve agents after deploymentUse checklists, templates, and production-readiness practices to reduce guessworkWhat makes this book different is its engineering-first approach. Instead of treating AI agents as impressive demos, it shows how to build them as maintainable software systems with configuration, testing, observability, governance, human review, and measurable quality.This book is ideal for software developers, AI engineers, cloud engineers, solution architects, enterprise IT teams, technical leads, and anyone responsible for building practical AI applications with Microsoft Foundry and Azure.If you want to move beyond simple prompts and build enterprise AI agents that can retrieve knowledge, use tools, support workflows, and operate with confidence, get this book and start building agentic AI systems the right way.

Agentic AI Engineering with LLMs: Designing Multi-Agent Systems and Building LLM Applications That Reason, Plan, and Act in Real-World Environments | A Practical Guide to AI Agent System Design
English | April 27, 2026 | ASIN: B0GXV89GF5 | 154 pages | Epub | 819.20 KB
Build AI Agents That Think, Plan, and Act on Their Own.Software is being rewritten. Large language models are no longer passive tools waiting for prompts. They now power autonomous systems that pursue goals, make decisions, use tools, and complete real work. The engineers who understand how to design and ship these systems are building products that were impossible two years ago.Agentic AI Engineering with LLMs is the complete, hands-on guide to designing multi-agent systems and building LLM applications that operate in real-world environments. This is not surface-level theory or another framework tutorial. It is a deep, structured walkthrough of the engineering discipline behind every reliable AI agent in production today.What you will learn:How large language models actually work, from tokens and transformers to alignment and inferenceThe shift from passive language models to autonomous AI agentsThe full anatomy of an agentic system and the role of every componentReasoning frameworks like ReAct, Chain of Thought, and Tree of ThoughtPlanning, decision-making, and task decomposition strategies that scaleTool use, function calling, and how agents extend their capabilities through APIsMemory architectures, state management, and retrieval-augmented generationMulti-agent collaboration, coordination patterns, and orchestration frameworksProduction deployment, evaluation, observability, and safety guardrailsCost optimization, scaling strategies, and proven industry use casesWho this book is for:Software engineers building AI features, architects designing agentic platforms, technical leaders guiding teams through the AI transition, researchers translating ideas into systems, and advanced students who want a serious foundation in this fast-moving field.Why this book is different:Most AI books either drown you in math or hand you a toolkit walkthrough that is outdated within months. This one teaches the underlying principles that survive every framework update. Tools change. Principles endure. By the final chapter you will have a working mental model for every layer of a modern agentic system, plus the confidence to make architectural decisions in production.The window to master AI agent system design is narrow. Engineers who learn the discipline today will lead the next decade of software.Scroll up, click "Buy Now," and start building autonomous AI systems that actually work.

Agentic AI Engineering: Build Autonomous AI Systems from Scratch
English | May 26, 2026 | ASIN: B0H3223418 | 63 pages | Epub | 6.24 MB
Agentic AI Engineering: Build Autonomous AI Systems from ScratchLearn MCP, LLMs & system designBuild real-world AI agentsUnderstand deployment & scalingMove from user → builder

Agentic AI Engineering 2026
English | 4 Jun. 2026 | ASIN: B0H483SMKZ | 134 pages | EPUB (True) | 115.08 KB
The era of passive chatbots is over. The systems that matter now don't just respond-they pursue goals, execute tasks, and adapt to reality. Welcome to the era of Agentic AI.In Agentic AI Engineering 2026, veteran systems practitioner Harvey Webber moves past temporary hype and superficial product demos to deliver a definitive, code-agnostic masterclass in building production-ready autonomous systems. Written specifically for software engineers, ML practitioners, and technical architects, this practical book isolates the durable design patterns that allow AI agents to plan, reason, and safely act in the real world.Frameworks will shift and APIs will change, but the engineering principles established in this book are designed to last. Webber breaks down the architectural anatomy of successful agents, providing a step-by-step scaffold around the unique strengths and stark limitations of modern Large Language Models (LLMs).Inside this comprehensive guide, you will master:The Beating Heart of Agency: A deep dive into the perception-decision-action cycle and the foundational ReAct (Reasoning and Acting) pattern.Core Building Blocks: How to architect precise tool schemas, implement multi-layered memory (short-term, long-term, episodic, and semantic), and deploy robust Retrieval-Augmented Generation (RAG).Advanced Orchestration & Planning: Designing deterministic chains, adaptive graphs, and multi-agent hierarchies utilizing supervisor-worker, delegation, handoff, and debate collaboration models.Production-Grade Guardrails: Critical engineering strategies for input/output validation, least-privilege permissions, sandboxed execution, and mitigating the persistent threat of prompt injection.Operations & Scaling: Practical math for token cost reduction, model routing, latency mitigation, asynchronous concurrency, and state persistence over long-running tasks.Real-World Deep Dives: Architectural blueprints for building state-of-the-art coding assistants, research synthesis engines, customer-facing agents, and workflow automation systems.Complete with production checklists, evaluation datasets guidelines, and a comprehensive glossary of agentic terminology, this text bridges the gap between clever prototypes and resilient, auditable enterprise software.Stop prompting. Start engineering. Build AI systems you can actually trust with real users and real money.

Agentic AI Development: Build Autonomous Systems and Intelligent AI Agents That Plan, Execute, and Deliver Real-World Results
English | May 8, 2026 | ASIN: B0H133JHWJ | 376 pages | Epub | 562.41 KB
What if your AI applications could think, plan, use tools, remember context, recover from failures, and execute complex workflows autonomously just like a real digital workforce?Agentic AI Systems is a practical, hands-on guide to building intelligent AI agents that go far beyond simple chatbots and prompt engineering. This book takes you deep into the rapidly evolving world of autonomous AI systems, showing you how to design, orchestrate, deploy, and scale production-ready agentic applications capable of real decision-making and task execution.Instead of focusing on theory-heavy explanations, this book emphasizes modern architectures, real-world workflows, and implementation-focused learning. You will learn how to build agents that can reason iteratively, use external tools and APIs, manage memory, coordinate with other agents, automate workflows, handle failures gracefully, and operate reliably in production environments.From foundational agent loops to advanced orchestration systems, this book guides you step-by-step through the complete lifecycle of intelligent system development. Whether you are building autonomous research assistants, AI-powered development tools, workflow automation systems, or enterprise-grade multi-agent platforms, this book provides the architectural knowledge and practical skills required to build them correctly.Inside this book, you will learn how to:Build task-oriented AI agents from scratchDesign Plan → Act → Observe and ReAct workflowsIntegrate APIs, databases, vector stores, and external toolsImplement memory systems for contextual reasoningBuild scalable multi-agent collaboration systemsCreate event-driven orchestration pipelinesHandle retries, failures, observability, and monitoringDeploy and scale agent systems in production environmentsDesign secure, maintainable, and reliable AI architecturesBuild complete end-to-end real-world AI projectsWhat makes this book different is its strong focus on practical engineering. Rather than teaching isolated prompts, it teaches how modern AI systems are actually built in production. Every major concept is reinforced with complete code examples, architectural walkthroughs, deployment strategies, and real implementation patterns that developers can apply immediately.This book is ideal for software engineers, AI developers, architects, technical founders, automation engineers, and anyone who wants to move beyond basic LLM experimentation into building fully operational intelligent systems.The future of software is autonomous, adaptive, and agent-driven. The developers who understand how to build these systems will shape the next generation of technology.If you are ready to master the architecture, workflows, and engineering principles behind modern agentic AI systems, then this book is your roadmap.Start building intelligent systems that do more than respond - build systems that think, act, collaborate, and execute.

Agentic AI Architecture: Visual Blueprints for Designing Secure AI Agents, MCP Tool Workflows, A2A Collaboration, and ReACT Reasoning Systems
English | June 5, 2026 | ASIN: B0H2BYFT2R | 426 pages | Epub | 300.81 KB
Agentic AI Architecture: Visual Blueprints for Designing Secure AI Agents, MCP Tool Workflows, A2A Collaboration, and ReACT Reasoning SystemsBuild AI agents that are structured, secure, explainable, and ready for real workflows-not just impressive demos.AI agents are moving fast, but many developers and teams still struggle with the same problem: how do ReACT loops, MCP tools, A2A collaboration, safety controls, and production workflows actually fit together?Agentic AI Architecture gives you a practical visual blueprint approach for designing agentic systems before they become messy, risky, or hard to debug. Instead of treating AI agents as black boxes, this book shows how requests move through coordinators, tools, specialist agents, approval gates, observability layers, and deployment boundaries.Inside, you will learn how to design secure AI agents that can reason, call tools, pass tasks between agents, handle errors, preserve traceability, and stay within safer automation limits. The book covers ReACT reasoning systems, MCP tool workflows, Agent-to-Agent collaboration, human-in-the-loop approval, testing, observability, FastAPI packaging, Docker deployment, and production-readiness checks.You will gain practical confidence in:Mapping agent workflows with clear visual blueprintsDesigning reliable tool schemas and MCP serversBuilding multi-agent collaboration patterns with A2A conceptsAdding safety rules, permission boundaries, and approval pointsTesting, tracing, evaluating, and deploying agentic AI systemsThis book is for developers, AI engineers, solution architects, automation builders, technical founders, and product teams who want a clearer way to design agentic AI systems for real applications.

Agenti AI con n8n (Serie AI Agents & MCP)
English | June 11, 2026 | ASIN: B0H4WN4Q49 | 199 pages | Epub | 596.97 KB
Scopri il potenziale degli agenti AI autonomi - senza bisogno di programmare!Agenti AI con n8n è la tua guida completa per progettare, creare e monetizzare workflow intelligenti utilizzando la piattaforma di automazione open-source n8n. Scritto per sviluppatori, imprenditori individuali e appassionati di tecnologia, questo manuale pratico chiarisce il concetto di agenti AI e ti mostra come sfruttare gli strumenti low-code per risolvere problemi aziendali reali.Inizierai con i fondamenti degli agenti AI e scoprirai perché i workflow visivi di n8n rappresentano una svolta decisiva per l'automazione:contentReference[oaicite:39]. Passo dopo passo, configurerai il tuo ambiente di lavoro, creerai il tuo primo agente e padroneggerai il prompt engineering con LangChain. Quindi collegherai i tuoi agenti a fonti di dati esterne, progetterai la memoria, orchestrerai sistemi multi-agente e dimensionerai le tue soluzioni con sicurezza. Nel corso del libro troverai esempi pratici - dagli assistenti di supporto ai bot di ricerca, dalla qualificazione dei lead alla pianificazione vocale - insieme a checklist operative e strategie di monetizzazione.Imparerai a:Comprendere l'anatomia degli agenti AI e cosa li rende autonomi:contentReference[oaicite:40].Configurare n8n nel cloud o sul tuo server, connetterti agli LLM e impostare credenziali sicure.Creare agenti che si integrano con Google Sheets, CRM, provider email e qualsiasi REST API.Padroneggiare il prompt engineering e le catene di ragionamento con LangChain per produrre risultati affidabili.Implementare la memoria con vector store e progettare sistemi multi-agente utilizzando pattern gatekeeper:contentReference[oaicite:41].Monetizzare i tuoi agenti attraverso servizi in formato prodotto, offerte SaaS e guadagni di efficienza interna.Distribuire e dimensionare i tuoi agenti in modo responsabile, con attenzione a sicurezza, etica e conformità:contentReference[oaicite:42].Che tu voglia automatizzare attività ripetitive, creare un nuovo flusso di entrate o rimanere all'avanguardia nella rivoluzione dell'AI, questo libro ti fornisce le conoscenze e la sicurezza necessarie per avere successo. È il momento di trasformare le tue idee in workflow autonomi che lavorano per te e per i tuoi clienti.Sei pronto a costruire il tuo futuro con gli agenti AI? Inizia a leggere oggi!