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Free Download Agentic AI in Enterprise: Harnessing Agentic AI for Business Transformation by Sumit Ranjan, Divya Chembachere, Lanwin Lobo
English | August 14, 2025 | ISBN: 8868815419 | 432 pages | MOBI | 2.50 Mb
This book delves into the transformative power of Enterprise Agentic AI, tracing its evolution from basic automation to intelligent agents capable of contextual reasoning, memory retention, and autonomous decision-making. It provides a strategic roadmap for enterprises looking to integrate Agentic AI seamlessly into their operations while ensuring scalability, efficiency, and security.

Free Download Agentic AI & ML Pipeline Boilerplates: Design, Train, Deploy, and Scale Intelligent Systems (The AI Boilerplate Engineering Series Book 2)
English | December 18, 2025 | ASIN: B0G8KFYHK5 | 309 pages | Epub | 2.01 MB
Agentic AI & ML Pipeline Boilerplates Design, Train, Deploy, and Scale Intelligent Systems Stop experimenting. Start building production-ready AI systems. Agentic AI & ML Pipeline Boilerplates is a practical, engineering-first guide for developers and architects who want to move beyond demos and notebooks and start building real, scalable, and safe AI systems . This book shows you how to design, train, deploy, and operate agent-based AI systems and machine learning pipelines using battle-tested boilerplate architectures, not hype, not theory, and not fragile experiments. If you already know basic AI or machine learning and want to ship reliable AI products , this book is for you. What you'll learn: ✔ How agentic systems actually work, from input to reasoning, action, and response ✔ When to use agents (and when not to) in real products ✔ How to design clean, scalable agent architectures ✔ How to build production ML training pipelines (no notebooks-as-products) ✔ How agents, tools, memory, and models fit together ✔ How to debug, evaluate, and control costs in agent systems ✔ How to safely scale from a single agent to multi-agent systems ✔ How to deploy agents locally, in the cloud, or fully offline ✔ How to integrate agents with real systems: codebases, CRMs, monitoring, and sales pipelines ✔ How to prepare AI systems for enterprise security, governance, and compliance What makes this book different: 🚫 No hype 🚫 No "magic AI" explanations 🚫 No copy-paste prompt tricks ✅ Engineering-driven ✅ Production-ready ✅ Boilerplate-focused ✅ Safety-aware ✅ Enterprise-minded Every chapter is built around reusable folder structures, execution loops, workflows, and deployment patterns you can directly adapt for your own projects. Who this book is for: This book is ideal for: Software developers building AI-powered applications Backend and ML engineers moving systems to production Architects exploring agent-based system design Startup founders building AI products Engineering teams preparing for enterprise AI adoption You should already be comfortable with Python, APIs, and basic ML or LLM concepts . Designed for real-world use: This book is structured as a long-term engineering reference , not a one-time read. You can return to it whenever you need: A clean agent boilerplate A scalable ML pipeline structure A safe deployment strategy A production-grade workflow design If you're ready to build serious AI systems If you're tired of fragile demos and want to engineer AI systems that last , Agentic AI & ML Pipeline Boilerplates will become your go-to production handbook . Build smarter. Ship faster. Scale safely.

Free Download Agent-Powered Coding with Cursor 2.0: Design Intelligent Development Pipelines Using Context-Aware AI Agents
English | December 9, 2025 | ASIN: B0G61J9ZTJ | 311 pages | Epub | 1.50 MB
Agent-Powered Coding with Cursor 2.0: Design Intelligent Development Pipelines Using Context-Aware AI Agents Software development is entering a new era; one where intelligent agents collaborate with you at every stage of engineering. Agent-Powered Coding with Cursor 2.0 shows you how to move beyond single prompts and into a structured, predictable, and highly effective way of building software with AI. Instead of treating AI like a tool that produces answers, you learn how to design full development pipelines that combine reasoning, context, memory, and constraints into stable, repeatable workflows. This book gives you a complete foundation in context engineering , the discipline of shaping the information that AI agents use to understand tasks and produce high-quality results. You learn how to design instruction layers, build memory systems, apply guardrails, and create role-based agents that work together in coordinated stages. Through practical examples and real code, you see how Cursor 2.0 transforms everyday tasks: feature creation, debugging, refactoring, test generation, and documentation, into streamlined, automated processes that improve consistency and reduce engineering overhead. Across ten chapters and multiple case studies, you see how to build and scale multi-agent systems that understand your codebase, reason across files, correct their own mistakes, and contribute to long-term project maintenance. You will learn how to integrate these workflows into real development environments using Git, CI/CD, architectural templates, and shared context structures. You also explore the future of AI-driven engineering, including autonomous coding loops, verification-first practices, and continuous evaluation systems that maintain software quality as agents evolve. By the end of the book, you will not only understand how Cursor 2.0 works, you will know how to design intelligent pipelines that drive real productivity, accelerate delivery, and raise the standard of your software projects. Whether you are a beginner seeking clarity or an experienced developer looking for advanced patterns, this book gives you the technical depth and practical guidance to build with confidence. If you're ready to stop treating AI as a helper and start using it as a structured engineering partner, this book gives you the blueprint. Step into a new way of developing software, one where agents analyze, refactor, test, document, and collaborate with you across your entire codebase. Take control of your workflow. Build smarter systems. Lead the shift toward intelligent development pipelines. Start your transformation today with Agent-Powered Coding with Cursor 2.0.

Free Download Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving By Zili Zhang, Chengqi Zhang (auth.)
2004 | 194 Pages | ISBN: 3540209085 | PDF | 1 MB
Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems.This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining.

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