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Agentic Hybrid RAG on SAP BTP: A Hands-On Guide with LangGraph, HANA Cloud, and Google Vertex AI
English | June 4, 2026 | ASIN: B0H1PD3SV5 | 399 pages | Epub | 3.32 MB
Build a production-ready AI agent on SAP BTP that answers complex questions using parallel hybrid retrieval - combining vector search and knowledge graphs, orchestrated with LangGraph. Step-by-step guidance covers SAP HANA Cloud, Google Vertex AI, CAP Node.js OData V4, Fiori Elements, and Cloud Foundry deployment - everything on free-tier resources.

Agentic Coding with Windsurf: Build, Refactor, Test, and Ship Multi-File Software Projects with Cascade, MCP, AI Workflows, and Production-Ready Developer Practices
English | May 5, 2026 | ASIN: B0GZCDZVDZ | 411 pages | Epub | 5.71 MB
Agentic Coding with WindsurfBuild, Refactor, Test, and Ship Multi-File Software Projects with Cascade, MCP, AI Workflows, and Production-Ready Developer Practices You've used AI to write code. It works... until your project grows.Suddenly, changes break across files. Context gets lost. Fixing one bug creates another. You spend more time managing the tool than building the product. Sound familiar?This book shows you a different way to work.Agentic Coding with Windsurf introduces a structured, real-world approach to building software with AI that actually scales. Instead of treating AI like a code generator, you learn how to operate it as a system-one that plans, edits, tests, and deploys across entire codebases with precision.Inside, you'll learn how to use Windsurf and Cascade to manage complex development workflows, coordinate multi-file changes, and ship production-ready software without losing control.What you'll gain from this bookBuild features across multiple files without breaking your systemPlan and execute changes using Cascade's Ask, Plan, and Code modesRefactor large codebases while keeping tests stableDebug issues faster with structured, test-driven workflowsRun parallel development streams using Git worktreesAutomate repetitive tasks with MCP tools and custom workflowsDeploy applications to the cloud directly from your development flowSet up secure pipelines with proper secret management and controlsMaintain full visibility with logging, monitoring, and rollback strategiesIf you've ever wondered:Why does AI struggle once projects get complex?How do you safely edit multiple files with confidence?Can AI actually help you ship production-ready software?This book gives you clear, practical answers-and shows you exactly how to apply them.You're not just learning a tool. You're building a system that helps you move faster, reduce errors, and ship with confidence.Get your copy now and start building software the way modern development demands.

Agentic AI with MCP, Second Edition: Build Real-World Multi-Agent Systems with Architecture Diagrams, LangChain Workflows, MCP Protocols, and Deployable LLM Agents
English | December 13, 2025 | ASIN: B0G6P3R63M | 289 pages | Epub | 1.95 MB
Build production-ready AI agents that don't just "chat" - they plan, use tools, collaborate, retrieve knowledge, and complete real tasks reliably.Agentic AI with MCP, Second Edition is a practical, beginner-friendly guide to designing and building modern multi-agent systems using the Model Context Protocol (MCP). You'll learn how to structure agents with clear roles, connect them to real tools and APIs, pass messages safely, and integrate memory and retrieval so your systems stay grounded, consistent, and useful. Every concept is taught with step-by-step explanations and working examples, so you can move from "I've heard of agents" to "I can build and deploy them" with confidence.This book stands out by showing you the full end-to-end path: from agent architecture diagrams and message pipelines, to RAG (retrieval-augmented generation) workflows, to tool-enabled agent design, to real-world projects like a Research Assistant system and a Developer Agent suite. You'll also learn how to deploy and scale agent systems using modern patterns such as FastAPI, Docker containerization, and cloud deployment strategies - with an emphasis on safety, reliability, and clean engineering practices.Written in a clear, mentor-like style, this Second Edition reflects the newest expectations of today's agentic ecosystem: graph-based orchestration, structured tool schemas, improved debugging workflows, and practical guidance for building systems that behave predictably under pressure. If you want a modern, hands-on roadmap for multi-agent engineering and MCP-based architectures, this book is designed to save you time and help you ship.

Agentic AI for Solopreneurs: Build Smart No Code Systems with AI Agents to Save Time and Scale Your Business | Beginner Friendly | Includes No Code ... No-Code Automations to Save Time and Money)
English | November 1, 2025 | ASIN: B0FXH5RY7F | 227 pages | Epub | 3.57 MB
Learn Agentic AI, and Start Automating Your Business in 5-Minutes or Less.⭐ Beginner-Friendly. No Code. No Technical Skills Required. ⭐You don't need to be a developer-or even "techy"-to harness the power of Agentic AI. This book shows any solopreneur how to build smart, time-saving systems using simple, no-code tools.This isn't another hype-driven AI book - it's a clear, step-by-step guide designed for busy professionals who value independence and efficiency.Inside, you'll discover how to:Launch your first automation in minutes - plug in the included JSON templates and have workflows running in 5 minutes or less. ⌛Simplify every part of your business - connect your email, CRM, invoicing, and calendar tools without touching a single line of code. 🏢Understand Agentic AI in plain English - learn what it is, why it matters, and how it can transform how you work and earn. 🧠Master the Three-Pillar Framework - Develop your system, Engage your clients, and Sustain your growth automatically. 💪Future-proof your business - stay ahead as AI evolves with adaptable, scalable workflows that grow with you. 💎You'll also get: Free plug-and-play automations Access to numerous free 5-minute courses designed to get anyone (and we mean ANYONE) going fast Real solopreneur case studies proving what's possibleIf you can click, copy, and paste, you can build your own AI-powered business systems with our proven framework.Stop trading time for tasks. Upgrade Your Life Now 🤓 .⭐ Agentic AI - Made Simple. ⭐

Agentic AI for Developers: Build Autonomous AI Systems That Plan, Execute, and Deliver Real-World Results Using Modern AI Agents
English | May 8, 2026 | ASIN: B0GXLP6PM3 | 222 pages | Epub | 542.61 KB
Agentic AI is changing how modern software is built. Instead of relying on single prompts or isolated model responses, developers are now designing autonomous AI systems that can plan, reason, use tools, manage memory, execute workflows, and adapt across multi-step tasks. As AI agents become central to automation, research systems, enterprise workflows, and intelligent applications, the ability to build reliable agentic systems is quickly becoming one of the most valuable skills in modern software development.Agentic AI for Developers is written for technical readers who want more than theory. This book focuses on practical architecture, production-ready control, real-world implementation patterns, and the engineering discipline required to move from experimental AI prototypes to reliable autonomous systems. It aligns with today's best practices in AI system design, including structured workflows, tool calling, retrieval-augmented generation, state management, observability, guardrails, evaluation, cost control, and scalable deployment.This book gives you a clear, implementation-driven path to building AI agents that do more than generate responses. You will learn how to design systems that understand goals, break tasks into steps, coordinate tools, preserve context, recover from failures, and deliver useful results under real-world conditions. From foundational agent loops to multi-agent coordination and production deployment, every chapter is designed to help you turn intelligent models into dependable software systems.What's Inside* Discover how to move from basic prompting to goal-driven AI systems that plan and execute with purpose.* Learn the core architecture of agentic AI systems, including perception, planning, action, reflection, memory, and workflow orchestration.* Build agent workflows that use APIs, external tools, databases, function calling, structured inputs, and secure execution patterns.* Explore planning and reasoning strategies such as task decomposition, adaptive execution, tool-augmented reasoning, and controlled autonomy.* Master memory systems, RAG pipelines, vector stores, long-term context, state propagation, and context management for complex AI applications.* Design real-world agents for research, content generation, workflow automation, business operations, and enterprise AI integration.* Understand multi-agent systems, role-based coordination, planner-executor-reviewer patterns, communication protocols, and conflict resolution.* Learn how to debug, evaluate, monitor, optimize, and scale agent systems while controlling latency, token usage, cost, reliability, and production risk.This book is for developers, software engineers, AI builders, automation specialists, technical founders, and professionals who want to build practical AI agent systems instead of simply experimenting with prompts. If you already understand APIs, software architecture, Python, backend systems, or automation workflows, this book will help you add the missing layer: turning AI reasoning into controlled, reliable, production-ready execution.You do not need months of scattered research to understand agentic AI development. With a structured, step-by-step approach, this book helps you build clarity quickly and apply modern AI agent concepts with confidence. In weeks, not months, you can move from basic LLM usage to designing autonomous AI systems that plan, execute, recover, and scale.If you are ready to go beyond simple AI prompts and start building autonomous systems that deliver real-world results, Agentic AI for Developersis your practical guide. Get the book today and begin mastering the architecture, workflows, tools, and production strategies that will define the next generation of AI-powered software.

Agentic AI Systems in Production: Architecting, Orchestrating, and Scaling Autonomous Workflows
English | May 11, 2026 | ASIN: B0H1DN82J7 | 426 pages | Epub | 507.03 KB
AGENTIC AI IS NO LONGER EXPERIMENTAL - IT IS NOW INFRASTRUCTURE.Most AI books stop at prompts, demos, or toy projects. This one does not.Agentic AI Systems in Production is a deep technical field manual for engineers, architects, and infrastructure teams building autonomous AI systems that must survive real-world production environments. This book goes beyond hype and explores what actually happens when probabilistic AI agents collide with distributed systems, GPU bottlenecks, orchestration failures, latency cascades, memory constraints, and enterprise-scale reliability demands.Inside, you will learn how to architect production-grade autonomous workflows using modern infrastructure patterns including Kubernetes, Kafka, Redis, Celery, vector databases, observability stacks, and multi-agent orchestration frameworks. The book treats AI systems as volatile distributed systems requiring rigorous engineering discipline - not magic.Through detailed architectural breakdowns, production incidents, operational tradeoffs, and implementation examples, this guide equips readers to build scalable, fault-tolerant AI infrastructure capable of handling real-world enterprise workloads.WHAT YOU WILL LEARN:* Production Agent Architecture - Design resilient multi-agent execution systems with deterministic orchestration patterns.* Inference Infrastructure - Deploy and scale GPU inference workloads using modern serving architectures and batching strategies.* Memory & Retrieval Systems - Engineer high-performance RAG pipelines, vector search systems, and context management layers.* Distributed Systems for AI - Handle latency, backpressure, concurrency, retries, partitions, and failure recovery in autonomous environments.* Observability & Reliability - Implement tracing, telemetry, monitoring, and incident-response strategies for AI-native systems.* Kubernetes & Autoscaling - Operate agentic systems under burst traffic and enterprise-scale concurrency demands.* Security & Governance - Harden AI infrastructure with guardrails, RBAC controls, sandboxing, and compliance strategies.WHO THIS BOOK IS FOR:This book is designed for backend engineers, AI architects, platform engineers, DevOps teams, SREs, infrastructure engineers, and advanced developers building serious AI systems in production. It assumes familiarity with Python, APIs, distributed systems, and cloud-native infrastructure.If you are responsible for reliability, scalability, orchestration, or operational resilience in AI systems, this book was written for you.Build autonomous systems that scale beyond prototypes - and survive production.

Agentic AI Systems Design with Claude Code and MCP: Engineer Autonomous Solutions Through Modular Planning Techniques And Resilient Infrastructure Models ... for Beginners and Developers Book 2)
English | May 7, 2026 | ASIN: B0GZVLMT7P | 508 pages | Epub | 14.91 MB
What if your AI systems could do more than respond? What if they could plan, adapt, collaborate, recover from failure, and operate with the kind of structured autonomy modern software environments now demand? Have you been wondering how developers and architects are building intelligent systems that can reason through tasks, coordinate tools, manage workflows, and continuously improve outcomes without constant human supervision?This book invites you into the evolving world of agentic AI design, where autonomous systems are no longer experimental ideas but practical engineering solutions shaping the future of software development. Whether you are a developer exploring advanced AI orchestration, a systems engineer searching for resilient infrastructure patterns, or a curious technologist eager to understand modular planning frameworks, this guide challenges the way you think about intelligent applications.Have you ever asked yourself why some AI systems fail the moment complexity increases? Why certain architectures collapse under scaling pressure while others remain flexible, adaptive, and reliable? What makes one autonomous workflow efficient while another becomes difficult to maintain? These are the kinds of questions explored throughout this engaging and practical journey into agentic AI systems.Through conversational explanations and real-world engineering perspectives, you will discover how Claude Code and MCP can support the creation of organized autonomous environments capable of decision-making, task delegation, memory handling, modular coordination, and resilient execution. Instead of treating AI as a simple chatbot layer, this book encourages you to approach intelligent systems as evolving ecosystems built upon planning logic, communication structures, recovery models, and scalable architectural principles.Are you trying to understand how modular agents cooperate within larger infrastructures? Curious about how planning chains influence reliability and execution flow? Wondering how resilient infrastructure models reduce operational risks when autonomous systems encounter uncertainty or incomplete information? This book walks beside you through those challenges with clarity and purpose.As you move deeper into the material, you will begin exploring how modern AI agents interact with tools, APIs, memory systems, and distributed services while maintaining operational consistency. You will see how intelligent workflows can be designed for adaptability rather than rigidity. You will also gain insight into creating systems that remain maintainable even as complexity expands across teams and environments.But this is not just about theory. It is about practical thinking. How do you engineer AI systems that developers can trust? How do you prevent fragile automation patterns from becoming liabilities? How do you create architectures that allow autonomous reasoning while still preserving observability, control, and long-term sustainability?Perhaps you are building next-generation applications, modernizing enterprise infrastructure, or simply trying to understand how autonomous AI ecosystems are transforming software engineering. Wherever you stand, this book offers a pathway into the foundations required to navigate this rapidly advancing field with confidence.The future of intelligent systems belongs to those who understand not only how AI responds, but how AI plans, coordinates, recovers, and evolves. Open this book today and start building the resilient, modular, and agent-driven AI architectures shaping the next era of innovation.

Agentic AI Systems Architect 2026: Design, Build, and Deploy AI Agents for Real-World Automation
English | May 24, 2026 | ASIN: B0H2SK6JR5 | 184 pages | Epub | 180.75 KB
Design, build, and deploy AI agents for the next era of real-world automation.Artificial intelligence is moving beyond simple chatbots. The next breakthrough is agentic AI - intelligent systems that can follow goals, use tools, retrieve knowledge, remember context, work through multi-step workflows, and help automate real tasks.But building useful AI agents takes more than random prompting.Agentic AI Systems Architect 2026 gives developers, entrepreneurs, freelancers, technical beginners, and ambitious professionals a practical guide to understanding how AI agents are designed, built, tested, and deployed for real-world automation.Inside this book, you'll learn how to:Understand how AI agents actually workDesign agentic workflows from scratchUse LLMs as the brain of an AI agentBuild stronger prompts for agent systemsUnderstand tools, function calling, and external actionsUse RAG systems and knowledge retrieval to reduce hallucinationsDesign memory systems for smarter AI agentsBuild multi-agent workflows and digital AI teamsExplore no-code, low-code, and Python-based agent automationApply AI agents to business, software, support, research, content, and operationsTest, monitor, and deploy agents with real-world reliabilityUse security, governance, guardrails, and human oversight responsiblyThis is not a hype book about AI replacing everyone.This is a practical builder's guide for people who want to understand the architecture behind AI agents and use that knowledge to create smarter systems.Whether you are a developer, founder, creator, consultant, student, freelancer, or professional preparing for the future of work, this book will help you move from casual AI user to confident AI systems thinker.Stop using AI one prompt at a time.Start designing intelligent systems.Agentic AI Systems Architect 2026 is your practical guide to building AI agents, real-world workflows, and automation systems for the agentic AI era.

Agentic AI Harness Pattern: The Top 15 Patterns Learned from Leaked Claude Code and Hermes Agent
English | May 9, 2026 | ASIN: B0H13XWS8W | 447 pages | Epub | 20.92 MB
Most AI tutorials teach you prompts. This book teaches you patterns.Production AI engineering - the discipline of turning a language model into something reliable, safe, auditable, and shippable - is mostly undocumented. The libraries churn every quarter. The patterns endure.Agentic AI Harness Pattern distills 15 of those patterns by reading two mature production codebases side by side: Claude Code, Anthropic's TypeScript CLI for agentic coding, and Hermes, a Python agent built to run across messaging platforms. The two systems make different language choices, different concurrency choices, and different deployment choices - but the harness pattern they implement is the same.Every chapter follows the same rhythm:Name the pattern. What problem is the harness solving?Show Claude Code's implementation in real TypeScript.Show Hermes's implementation in real Python.Compare them as a table. Where do they diverge, and why?Recommend when to use which. A decision rule, not a hot take.Apply the pattern to a defensive cyber-security agent. A worked example that shows the pattern under operational pressure. Inside the 15 patternsThe Harness Paradigm - why a model alone is not a productTool Architecture and the Tool Contract - the boundary between reasoning and consequenceThe Query / Agent Loop - what happens between the model's tool call and the next turnPermission Systems and Safety Guardrails - gating the destructive setTool Orchestration and Execution - partitioning safe vs. serial workContext Management at Scale - the five strategies before compactionMulti-Agent Coordination - when one agent isn't enoughMemory Systems and State Persistence - three tiers, one cacheObservability and Debugging - distributed tracing for non-deterministic systemsProduction Deployment Patterns - SDK-first vs. gateway-firstHook / Event-Driven Automation - the layer above the loopThe Skill System Pattern - capabilities as content, not codeMCP Integration - connecting agents to the worldModel Routing and Provider Abstraction - falling back without falling overStructured Output and Schema-Constrained Generation - when free text isn't enough Who this book is forEngineers building AI products who keep hitting the same architectural questions and want vetted answers.Architects and tech leads making the build-vs-buy-vs-wrap decision for an agent platform.Security and compliance reviewers who need to understand how a production agent enforces a destructive-action gate, an audit trail, and an iteration budget. Each chapter stands alone. Read what you need; read end-to-end and the patterns compound. Either way, you'll close the book with a working mental model of how to design an AI agent that survives contact with production. About the authorsKen Huang is CEO of DistributedApps.ai, advising organizations on production-grade agent deployment at the intersection of AI, distributed systems, and security.Grace Huang is a Product Manager and AI Engineer at PIMCO, where she ships AI features for the world's largest fixed-income asset manager. Her focus is the engineering rigor that makes AI products trustworthy in regulated environments.The model is intelligence. The harness is the system.Start here.

Agentic AI: From Zero to Advanced Level: Build Autonomous AI Agents with Python, LLMs, LangChain & Real-World Use Cases
English | April 27, 2026 | ASIN: B0GY1JCCLG | 143 pages | Epub | 4.23 MB
AGENTIC AI: FROM ZERO TO BUILDERLearn * Build * Automate * Scale * Earn With AIArtificial Intelligence is changing everything-but most people are still stuck using AI only for basic prompts and chatbot conversations.The real future is Agentic AI.Agentic AI systems don't just generate answers. They can think, reason, plan, remember, use tools, connect APIs, automate workflows, collaborate with other AI agents, solve real-world problems, and even help build businesses.This book is designed to help you understand and build Agentic AI systems from absolute zero-even if you are a beginner.Whether you are a student, entrepreneur, freelancer, developer, creator, business owner, or someone who wants to stay ahead of the AI revolution, this book gives you a practical roadmap to go from learning AI concepts to building real-world AI systems.This is not a boring theory book.This is a practical implementation guide designed for real-world execution.Inside this book, you will learn how modern AI agents work behind the scenes and how businesses worldwide are using them to automate operations, reduce costs, increase productivity, and create new revenue opportunities.What You'll Learn Inside:✔ What Agentic AI is and why it matters✔ How AI agents think and make decisions✔ Memory systems and how agents remember✔ How tools give agents powerful capabilities✔ How APIs help agents communicate with external systems✔ Frameworks used to build advanced agents✔ How to build no-code AI agents✔ How to build AI agents using Python✔ How to create AI art tools✔ How to build automation agents✔ Multi-agent systems and collaboration✔ Real business use cases in India and globally✔ How to earn money with Agentic AI✔ AI ethics, safety, and risks✔ The future of Agentic AI--What You Get In This Book:✅ 15 powerful chapters✅ 50+ ready-made AI systems✅ 75 powerful prompts(5 prompts included in every chapter)✅ Step-by-step practical examples✅ Real-world use cases✅ Business opportunities✅ Automation workflows✅ No-code + coding approaches✅ Beginner-friendly explanations--Who This Book Is For:BeginnersDevelopersEntrepreneursFreelancersStudentsBusiness ownersContent creatorsStartup foundersAnyone who wants to build with AI--Most AI books only teach theory.Most prompt books only teach how to chat with AI.Most technical books are too complex for beginners.This book combines all three:Learning + Building + Automation + Business + FutureYou'll go from:Zero Knowledge → AI Builder → Automation Creator → Business Opportunity CreatorThe AI revolution has already started.The biggest winners will be those who learn how to build intelligent systems instead of simply consuming AI tools.If you want to build AI agents, automate workflows, create products, generate income, and prepare for the future of intelligent systems-this book is your roadmap.Your journey from zero to builder starts here.