Building Agentic Ai Systems
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Building Agentic Ai Systems
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Author : Anjanava Biswas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-04-21
Building Agentic Ai Systems written by Anjanava Biswas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-21 with Computers categories.
Master the art of building AI agents with large language models using the coordinator, worker, and delegator approach for orchestrating complex AI systems Key Features Understand the foundations and advanced techniques of building intelligent, autonomous AI agents Learn advanced techniques for reflection, introspection, tool use, planning, and collaboration in agentic systems Explore crucial aspects of trust, safety, and ethics in AI agent development and applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGain unparalleled insights into the future of AI autonomy with this comprehensive guide to designing and deploying autonomous AI agents that leverage generative AI (GenAI) to plan, reason, and act. Written by industry-leading AI architects and recognized experts shaping global AI standards and building real-world enterprise AI solutions, it explores the fundamentals of agentic systems, detailing how AI agents operate independently, make decisions, and leverage tools to accomplish complex tasks. Starting with the foundations of GenAI and agentic architectures, you’ll explore decision-making frameworks, self-improvement mechanisms, and adaptability. The book covers advanced design techniques, such as multi-step planning, tool integration, and the coordinator, worker, and delegator approach for scalable AI agents. Beyond design, it addresses critical aspects of trust, safety, and ethics, ensuring AI systems align with human values and operate transparently. Real-world applications illustrate how agentic AI transforms industries such as automation, finance, and healthcare. With deep insights into AI frameworks, prompt engineering, and multi-agent collaboration, this book equips you to build next-generation adaptive, scalable AI agents that go beyond simple task execution and act with minimal human intervention.What you will learn Master the core principles of GenAI and agentic systems Understand how AI agents operate, reason, and adapt in dynamic environments Enable AI agents to analyze their own actions and improvise Implement systems where AI agents can leverage external tools and plan complex tasks Apply methods to enhance transparency, accountability, and reliability in AI Explore real-world implementations of AI agents across industries Who this book is for This book is ideal for AI developers, machine learning engineers, and software architects who want to advance their skills in building intelligent, autonomous agents. It's perfect for professionals with a strong foundation in machine learning and programming, particularly those familiar with Python and large language models. While prior experience with generative AI is beneficial, the book covers foundational concepts for those new to agentic systems.
Agentic Ai A Practical Guide To Build Agent Based Ai Systems That Think And Act
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Author : Tejas Patthi
language : en
Publisher: Tejas Patthi
Release Date : 2025-06-30
Agentic Ai A Practical Guide To Build Agent Based Ai Systems That Think And Act written by Tejas Patthi and has been published by Tejas Patthi this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.
Build real-world AI systems that do more than just respond. They think, plan, and act with purpose. Agentic AI is a comprehensive, hands-on guide to building autonomous AI agents using Python, large language models (LLMs), LangGraph, CrewAI, FAISS, and other modern tools. Whether you are an AI developer, a machine learning engineer, or a tech enthusiast, this book will help you move beyond simple chatbots and prompt-based models into the advanced world of intelligent, agent-based systems that function independently and handle real tasks. In this step-by-step guide, you’ll learn how to build LLM-powered autonomous agents capable of reasoning, tool use, memory recall, and multi-step task execution. From integrating with real-world APIs to deploying production-ready agent workflows, you'll gain the skills to create powerful and reliable agentic AI systems using today's top frameworks and best practices. 🔍 What You Will Learn: How to build autonomous AI agents that work independently without constant human input How to create agents with long-term memory using vector databases like FAISS and Chroma How to orchestrate multi-agent systems using frameworks like LangGraph and CrewAI How to integrate AI with external tools, APIs, and web services How to use Python to script smart agent behaviors and decision-making logic How to deploy agentic systems in cloud environments or containers with live monitoring How to implement agent safety, performance testing, and real-time feedback loops 💡 Why This Book Is Different: This is not just another theoretical AI book. Agentic AI is a project-based, code-driven manual that gives you everything you need to: Build tool-using AI assistants, copilots, and multi-agent task managers Use LangChain, LangGraph, CrewAI, and LLM toolchains effectively Combine LLMs with real-time data, plugins, memory, and feedback systems Design and deploy goal-driven AI agents with full autonomy and context awareness Stay ahead in the fast-evolving field of agent-based AI and LLM integration 🧠 Tools and Technologies Covered: Python 3.x LangGraph & LangChain CrewAI & OpenAgents ChromaDB & FAISS for memory OpenAI, Claude, Gemini, HuggingFace APIs FastAPI, Docker, REST APIs, and Webhooks Autonomous task chaining, multi-agent routing, and smart tool use 📦 Who Should Read This Book? AI Engineers ready to move beyond static models Python Developers exploring LLMs and autonomous systems Tech founders building smart assistants and AI copilots Data Scientists interested in real-world AI deployment Prompt engineers ready to level up into full-stack AI workflows
Mastering Agentic Ai
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Author : Ted Winston
language : en
Publisher:
Release Date : 2025
Mastering Agentic Ai written by Ted Winston and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Artificial intelligence categories.
"The next era of artificial intelligence is here - Agentic AI. These cutting-edge systems go beyond traditional AI by independently perceiving environments, reasoning about complex problems, learning from experience, and taking decisive action without human intervention. From autonomous vehicles and intelligent robots to adaptive industrial systems and personalized digital assistants, agentic AI is revolutionizing industries and redefining what machines can achieve. This book is your comprehensive guide to designing, building, and deploying these powerful, self-directed AI systems. Written by an industry expert with deep insights into artificial intelligence and autonomous systems, this book delivers a practical, real-world approach to mastering agentic AI. Drawing on the latest advancements in machine learning, cognitive architectures, reinforcement learning, and ethical design, this guide equips you with the tools, frameworks, and knowledge needed to create intelligent systems that not only perform but evolve and adapt in complex environments. Whether you're a developer, AI researcher, engineer, or tech leader, this book will help you stay ahead in the rapidly evolving AI landscape"--
Building Agentic Ai System With Rag 2 0
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Author : Theo Marris
language : en
Publisher: Independently Published
Release Date : 2025-06-24
Building Agentic Ai System With Rag 2 0 written by Theo Marris and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Computers categories.
Agentic AI is transforming how intelligent systems operate-moving beyond static responses to dynamic, tool-using, goal-driven behavior. At the heart of this evolution is Retrieval-Augmented Generation 2.0 (RAG 2.0), a new architectural pattern that fuses long-term memory, contextual reasoning, multi-agent coordination, and modular tool use for building advanced AI systems that act, learn, and adapt over time. This book delivers a practical blueprint for applying RAG 2.0 to real-world agentic workflows across enterprise, healthcare, education, and automation sectors. Written by a seasoned AI practitioner and technical author specializing in LLM architectures, this guide is grounded in the latest research, including SafeRAG best practices, LangChain, LlamaIndex, Pinecone integration patterns, DSPy, GraphRAG, and AGI-aware agent design. Every chapter reflects current industry trends, community-driven implementations, and field-tested methodologies that have emerged from the leading AI labs and open-source communities. "Building Agentic AI System with RAG 2.0" is your complete roadmap to designing, implementing, and deploying powerful, scalable, and intelligent agents using the next generation of Retrieval-Augmented Generation techniques. Covering everything from system pipelines and memory management to prompt chaining, multi-agent orchestration, hallucination control, and ethical deployment, this book equips developers, architects, and AI enthusiasts with actionable insights and full-stack expertise. Whether you are building AI copilots, enterprise search assistants, autonomous agents, or educational tutors, this guide will accelerate your journey from experimentation to production readiness. Explore cutting-edge topics including vector databases and hybrid retrieval strategies, adaptive memory structuring, multi-modal extensions (GraphRAG & VideoRAG), safe deployment architectures, long-term personalization techniques, and cost-effective optimization. Detailed case studies demonstrate agentic AI in action across finance, clinical decision support, education, and more. Practical node-based examples using LangChain, LlamaIndex, and DSPy are provided throughout-designed to ensure hands-on application. This book is written for AI developers, data scientists, software engineers, ML ops practitioners, and anyone building advanced AI systems with LLMs. Whether you're transitioning from basic LLM use to advanced agent orchestration, or leading technical teams in deploying autonomous reasoning frameworks, you'll find clear guidance, practical architecture blueprints, and real-world use cases to elevate your skills. Stop building fragile prototypes and start engineering future-proof, scalable AI systems. The RAG 2.0 framework enables long-term performance, lower hallucination risk, and flexible integration across tools and memory-so your applications remain relevant, reliable, and continually evolving with new data and user feedback. This book is built for today's LLM stack and tomorrow's intelligent agents. Unlock the full potential of AI agents today. Buy "Building Agentic AI System with RAG 2.0" now and take the next step toward mastering Retrieval-Augmented Generation, declarative agent design, and production-grade agentic architecture. Start building intelligent, scalable systems that reason, remember, and act-on your terms.
Mastering Agentic Artificial Intelligence
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Author : RONALD. TAYLOR
language : en
Publisher: Independently Published
Release Date : 2025-02-11
Mastering Agentic Artificial Intelligence written by RONALD. TAYLOR and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-11 with Computers categories.
"Mastering Agentic Artificial Intelligence: Building Autonomous AI Agents with Real-Time Knowledge, Adaptive Reasoning, and Proactive Decision-Making" is a definitive guide for anyone seeking to harness the full potential of autonomous AI systems. This book combines cutting-edge concepts with practical, step-by-step instructions to help you build self-directed AI systems using Python and advanced cognitive frameworks. Learn how to create intelligent agents that integrate Retrieval-Augmented Generation (RAG) for real-time knowledge retrieval and adapt through multi-agent systems with RAG architecture, all while ensuring they remain future-proof in an ever-evolving technological landscape. Drawing on real-world case studies and hands-on examples, this guide takes you from the fundamentals of agentic AI architecture to the sophisticated processes behind building agentic AI in action. Whether you're interested in the practical applications of agentic AI in enterprise automation, business intelligence, or scientific research, or you're eager to explore the role of agentic AI in robotics, finance, and cybersecurity, this book provides the tools and insights needed for innovation. With a focus on practical implementation and cognitive design, "Mastering Agentic Artificial Intelligence" demystifies complex topics like building autonomous AI systems and offers a clear pathway to developing intelligent systems for real-world applications. If you are ready to future-proof your skills and join the artificial intelligence revolution with a practical guide to innovation AI, this comprehensive resource is your essential companion on the path to mastering agentic AI and autonomous decision-making."
Agentic Ai System Using Rag
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Author : BRIAN. PITMAN
language : en
Publisher: Independently Published
Release Date : 2025-02-11
Agentic Ai System Using Rag written by BRIAN. PITMAN and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-11 with Computers categories.
Agentic AI system using RAG: Enhancing Autonomous AI with Real-Time Knowledge using the Power of Retrieval-Augmented Generation is a comprehensive, hands-on guide designed for researchers, engineers, and entrepreneurs who are ready to harness the power of autonomous AI in the modern era. This book presents an in-depth exploration of Agentic AI in action, providing you with the tools to build self-directed AI systems that leverage advanced cognitive frameworks and cutting-edge retrieval-augmented generation (RAG) techniques. Throughout the book, you will discover how to construct robust Agentic AI architectures using Python, blending foundation models with practical guides to innovation in AI. The text covers everything from designing and implementing multi-agent systems with RAG to mastering the art of building production-ready, autonomous AI systems for real-world applications. With extensive code illustrations and step-by-step instructions, you will learn how to create intelligent systems that can dynamically update their knowledge base, ensuring real-time decision-making and adaptive responses. This book is your gateway to mastering agentic RAG architectures, whether you are interested in agentic AI in books, agentic AI architecture, or even applications that empower a generative AI wealth engine. You will gain insights into cognitive frameworks for agentic systems, practical approaches for iterative process optimization, and strategies for designing machine learning systems that are future-proof in an era of rapid technological change. In addition to technical details, the book also delves into how autonomous AI systems are revolutionizing industries such as finance, healthcare, and research. Learn how to build chatgpt millionaire making money online models and explore the transformative impact of intelligent systems for real-world applications. The guide provides a balanced perspective on both the theoretical foundations and practical challenges of deploying AI systems that operate autonomously, ensuring that you are well-equipped to implement and troubleshoot your own agentic AI projects. Whether you are seeking to develop a generative AI wealth engine, explore agentic AI systems using radio or rgb, or design sophisticated models for autonomous decision-making, this book offers a complete roadmap. It emphasizes best practices, iterative improvement, and the integration of reinforcement learning to enhance the adaptability of your AI applications. With a focus on scalability, performance, and ethical considerations, you will be empowered to contribute to the artificial intelligence revolution and future-proof your innovations. Step into the future of modern agentic artificial intelligence with this essential guide, and transform your approach to AI engineering. The knowledge and techniques presented in this book will enable you to build, customize, and deploy advanced RAG-powered AI agents that are ready to tackle the complexities of the digital age.
Agentic Ai Systems
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Author : Roberto Pizzlo
language : en
Publisher: Independently Published
Release Date : 2025-06-15
Agentic Ai Systems written by Roberto Pizzlo and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-15 with Computers categories.
Agentic AI Systems: Build Multi-Agent Workflows with LangChain, MCP, RAG & Ollama (A Practical Guide to Local LLM Orchestration, Retrieval-Augmented Generation, and Autonomous Agents) Unlock the power of local LLMs, agentic AI architectures, and multi-agent orchestration with this hands-on guide designed for developers, AI engineers, and system architects building intelligent applications beyond the cloud. In an era where data privacy, autonomous workflows, and cost-effective deployments are critical, this book offers a production-ready blueprint using LangChain, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and Ollama. Whether you're designing AI copilots, deploying autonomous agents, or developing secure on-premise AI systems, this guide helps you go from concept to execution with confidence. What You'll Learn: Set up a complete agentic AI stack with LangChain, LangGraph, MCP, and Ollama Run private LLMs like Llama 3 and Mixtral with full control using Ollama Fine-tune models with LoRA/QLoRA for domain-specific applications Design and orchestrate multi-agent systems using LangGraph and graph-based coordination Build robust Retrieval-Augmented Generation pipelines using FAISS and Chroma Implement secure message-passing and streaming using MCP Handle authentication, observability, and compliance (GDPR, HIPAA, SOC 2) Deploy agents with Docker, Kubernetes, and scalable CI/CD pipelines Who This Book Is For: AI engineers and backend developers working with LLMs and LangChain Security-conscious teams needing private and auditable AI workflows DevOps and MLOps professionals deploying containerized AI systems Researchers and tech leads building autonomous agent systems Anyone interested in real-world agentic AI with local deployment capabilities Unlike cloud-reliant AI books or overly academic texts, Agentic AI Systems delivers actionable blueprints for building and deploying real systems on local infrastructure. You'll explore hands-on code, architecture diagrams, and reusable patterns that scale from laptops to clusters. No fluff-just proven strategies and reproducible workflows grounded in current LLM capabilities. Roberto Pizzlo is an AI infrastructure engineer and systems architect specializing in agentic orchestration and secure LLM deployments. Known for translating cutting-edge AI concepts into practical engineering, he brings a wealth of expertise in LangChain, LangGraph, RAG architectures, and edge AI systems. His experience bridges research, enterprise, and open-source ecosystems-making this book an essential guide for professionals navigating the fast-evolving world of autonomous AI. This guide reflects 2025 technologies and best practices, including the latest versions of LangChain, Ollama (v0.2.16+), CUDA 12.9, and RAG toolchains. It ensures your understanding remains relevant in a rapidly changing AI landscap
Building Agentic Ai With Rust
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Author : Evan Sterling
language : en
Publisher: Independently Published
Release Date : 2025-06-10
Building Agentic Ai With Rust written by Evan Sterling and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-10 with Computers categories.
Agentic AI-autonomous systems capable of perception, reasoning, and action-is redefining how we build intelligent applications. From AI customer service agents and healthcare assistants to real-time financial analysis tools, these systems integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and goal-oriented control. Rust, with its unmatched performance, safety guarantees, and asynchronous power via Tokio, is the ideal language to build scalable, high-concurrency AI agents that are production-ready. Written by a seasoned systems engineer and AI practitioner, Building Agentic AI with Rust is the first comprehensive guide focused on using Rust to build high-performance, autonomous AI agents. With deep real-world experience, clean architectural patterns, and a practical teaching style, this book bridges the gap between cutting-edge AI research and robust, deployable software engineering practices. This hands-on guide shows developers how to architect, implement, and deploy agentic AI systems using Rust and modern AI tools like OpenAI, Hugging Face, and vector search engines. Each chapter provides a step-by-step approach, from designing the agent loop to implementing a scalable RAG system and deploying with Docker and cloud services. You'll learn best practices for async programming with Tokio, profiling for performance, and implementing real-world use cases across industries. Implementing the Perceive-Reason-Act loop in Rust Architecting modular AI agents with traits and async tasks Integrating OpenAI and Hugging Face LLMs using structured prompts Building Retrieval-Augmented Generation (RAG) pipelines Scaling with Tokio, caching, and vector stores like Qdrant Packaging, containerizing, and deploying agents to AWS and GCP Monitoring, logging, and optimizing agents for production Full case studies: customer support, healthcare, and financial AI This book is written for Rust developers, AI engineers, system architects, and technical enthusiasts looking to build powerful autonomous agents with real-world capabilities. If you're comfortable with Rust and want to extend your skills into modern AI systems, this guide is for you. No prior experience with LLMs or RAG is required-concepts are introduced clearly and practically. Agentic AI is no longer experimental-it's production-ready, and it's here now. As the field of generative AI evolves rapidly, learning to build scalable, secure, and performant agents with Rust puts you ahead of the curve. Don't wait to catch up with the future-become one of the first engineers building it. Master the intersection of systems programming and generative AI. Build fast, safe, and intelligent autonomous agents with Rust today. Get your copy of Building Agentic AI with Rust and start coding the future of AI, now.
Agentic Ai Mastery
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Author : MEEK. ANDERSON
language : en
Publisher:
Release Date : 2025
Agentic Ai Mastery written by MEEK. ANDERSON and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
Autonomous Ai Systems
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Author : NATHANIEL. CROSSFIELD
language : en
Publisher: Independently Published
Release Date : 2025-04
Autonomous Ai Systems written by NATHANIEL. CROSSFIELD and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04 with Technology & Engineering categories.
Autonomous AI Systems: Practical Guide to Building Agentic AI and Self-Learning Systems The future of artificial intelligence lies in autonomy-AI systems that can learn, reason, and act without constant human intervention. Autonomous AI Systems explores the cutting-edge advancements in Agentic AI, self-learning models, and AI-driven automation that are transforming industries. From real-time decision-making to adaptive learning, this book unveils the technologies shaping the next wave of AI evolution. Written by AI expert Nathaniel Crossfield, this book is built on the latest research, real-world applications, and best practices in AI development. Whether you're an AI engineer, data scientist, researcher, or business leader, you'll gain deep insights into how autonomous systems function, how to build them effectively, and how they're revolutionizing cybersecurity, healthcare, finance, robotics, and more. This comprehensive guide takes you on a journey from foundational AI principles to advanced Agentic AI systems. You'll learn about self-improving models, reinforcement learning, autonomous decision-making frameworks, and ethical AI design. Unlike theoretical discussions, this book emphasizes real-world implementation, offering hands-on projects, case studies, and practical coding exercises. What's Inside: A deep dive into Agentic AI and self-learning architectures Step-by-step tutorials on building autonomous AI systems Real-world applications in business, cybersecurity, healthcare, finance, IoT, and robotics Practical coding exercises using Python, TensorFlow, PyTorch, and LangChain Advanced AI concepts, including Reinforcement Learning, Multi-Agent Systems, and Neuro-Symbolic AI Ethical considerations, AI safety measures, and governance frameworks Future trends, including Artificial General Intelligence (AGI) and AI's impact on society This book is for AI practitioners, data scientists, engineers, and tech entrepreneurs looking to master Agentic AI and self-learning systems. Whether you're building AI-powered automation for businesses, developing cutting-edge AI research, or exploring AI-driven robotics and cybersecurity, this book equips you with the skills and knowledge to stay ahead in the AI revolution. Basic programming knowledge in Python is recommended but not required. AI technology is evolving rapidly-staying ahead means mastering the latest advancements before they become industry standards. This book equips you with forward-thinking AI strategies, ensuring you're prepared for the next decade of AI-driven transformation. Take your AI expertise to the next level. Autonomous AI Systems: Practical Guide to Building Agentic AI and Self-Learning Systems provides the tools, knowledge, and hands-on experience you need to develop truly autonomous AI applications. Get your copy today and start building the future of AI!