Agentic Ai Engineering With Generative Ai

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Agentic Ai Engineering With Generative Ai

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Author : PROCLUS. ZHIROV
language : en
Publisher: Independently Published
Release Date : 2025-09-23

Agentic Ai Engineering With Generative Ai written by PROCLUS. ZHIROV and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-23 with Computers categories.

This comprehensive guide provides a structured approach to engineering agentic AI systems powered by generative AI, covering design, development, and deployment. Key chapters include: Core Concepts and Technologies: Explore frameworks like LangChain and LlamaIndex, hardware requirements, and integration with external tools. Defining Purpose and Scope: Align agents with clear objectives, success metrics, and environmental constraints Choosing the Right Model: Balance fine-tuning and prompt engineering, manage token limits, and address cost considerations Development Environment: Set up testing, debugging, and frameworks like Hugging Face Transformers Prompt Engineering: Craft effective prompts, mitigate ambiguity, and refine iteratively for task automation Agentic Workflows: Integrate generative AI with APIs, manage state, and optimize workflows Autonomy with RL: Enhance agents with reinforcement learning for adaptive decision-making Multi-Agent Systems: Design collaborative agents with specialized roles and robust communication protocols. Testing and Safety: Evaluate outputs, ensure robustness, and implement ethical guardrails Deployment and Scaling: Deploy on cloud, on-premise, or edge, with monitoring and maintenance strategies Enhanced Capabilities: Incorporate multimodal inputs, real-time adaptation, and IoT integration for advanced applications like smart home control. Ethical Design: Mitigate bias, ensure transparency, and comply with regulations like GDPR and HIPAA. By combining LLMs, Stable Diffusion, and next-gen tools, this guide equips developers to build scalable, ethical, and autonomous agents that push the boundaries of AI-driven productivity and creativity.

Agentic Ai With Rag In Action

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Author : Ronald Taylor
language : en
Publisher: Independently Published
Release Date : 2025-02-16

Agentic Ai With Rag In Action 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 2025-02-16 with Computers categories.

Agentic AI with RAG in Action: Enhance AI Agents, AI Prompt Engineering, Generative AI and AI Edge Sales Strategies Systems Using Agentic RAG Step into the future of artificial intelligence with this groundbreaking guide that transforms how you build, scale, and deploy autonomous AI systems. This book is your comprehensive, step-by-step roadmap to mastering Agentic AI using Retrieval-Augmented Generation (RAG), a powerful approach that fuses dynamic data retrieval with cutting-edge generative models. Whether you're an AI engineer, entrepreneur, or business leader, you'll discover practical strategies for designing production-ready systems that drive innovation and unlock real-world value. Learn how to create self-directed, intelligent agents using Python and cognitive frameworks that revolutionize sales, customer engagement, and business decision-making. Explore advanced topics like multi-agent systems with RAG, agentic AI architecture, and iterative processes for building modern, future-proof AI solutions. With detailed case studies, code illustrations, and a focus on ethical, scalable design, this book equips you to develop AI systems that are not only intelligent but also agile enough to adapt to ever-changing digital landscapes. From practical guides to innovation in generative AI wealth engines to designing machine learning systems with foundation models, "Agentic AI with RAG in Action" covers everything you need to build self-directed AI systems that excel in real-world applications. Harness the power of autonomous AI to drive profitability and stay ahead in a competitive market-whether you're making money online with ChatGPT millionaire strategies or deploying intelligent systems for enterprise-scale transformation. Take your AI expertise to the next level with a practical guide that blends technical mastery with strategic insights. This is the definitive resource for anyone determined to lead the artificial intelligence revolution and create innovative, intelligent systems that transform industries.

Agentic Ai Engineering

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Author : Yi Zhou
language : en
Publisher: Argolong Publishing
Release Date : 2025-09-05

Agentic Ai Engineering written by Yi Zhou and has been published by Argolong Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-05 with Computers categories.

Discover how Software Engineering is transforming into Agentic Engineering, the new discipline for building Production-Grade, Enterprise-Grade, and Regulatory-Grade intelligent systems. Most AI agents shine in controlled demos but collapse in production. They hallucinate confidently, drift off tasks, or fail silently without explanation. The problem is not intelligence but fragility. Agentic AI Engineering delivers the missing discipline, showing how to build systems that are resilient, auditable, and trustworthy across real-world environments. At its heart, the book reveals how software engineering evolves into agentic engineering. Where traditional software aimed for deterministic correctness, agentic systems must reason under uncertainty, adapt across shifting contexts, and continuously prove alignment. This evolution demands new foundations, new practices, and new roles. The central framework, the Agentic Stack, shows how to take agents from fragile prototypes to systems that can stand up to audits and scale without breaking. It demonstrates how to move deliberately up the maturity ladder: first to production-grade, where agents are contained and observable, then to enterprise-grade, where they integrate safely across organizations, and ultimately to regulatory-grade, where they can withstand external scrutiny and prove compliance in motion. The book goes beyond technical mechanics to address the organizational transformation required. It reframes product management around the economics of cognition, redefines operations as AgentOps, and advances quality assurance into the practice of proving not just outputs but reasoning itself. It shows how traditional agile squads must evolve into agentic teams, designed with architects, context engineers, and cognitive reliability leads who engineer not only systems but trust. The journey closes with the future horizon. Agents will not remain isolated utilities but will interconnect into adaptive ecosystems and, eventually, operating fabrics of intelligence. In this world, every application becomes an agent, and every system becomes accountable by design. Agentic AI Engineering is written for AI engineers and architects, yet it also provides vital perspective for executives, product leaders, and investors. More than a manual, it is a manifesto for the next era of technology.

Data Engineering With Generative And Agentic Ai On Aws

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Author : Justin J. Leto
language : en
Publisher: Apress
Release Date : 2026-04-11

Data Engineering With Generative And Agentic Ai On Aws written by Justin J. Leto and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-04-11 with Computers categories.

Unlock the future of cloud data engineering with generative and agentic AI on AWS. This hands-on guide shows you how to build intelligent, responsive data platforms using cutting-edge AI capabilities and modern AWS services. Learn to design next-generation data architectures—from data lakes and data mesh to scalable pipelines and real-time analytics. Discover how generative AI and agentic automation are transforming every aspect of enterprise data work: ingesting unstructured data, enabling semantic search with Retrieval-Augmented Generation (RAG), building autonomous data agents, and using natural language interfaces to turn business questions into instant insights. Author Justin J. Leto, PE, MBA, PMP, is a Principal Solutions Architect at AWS with over 20 years of experience in data engineering and AI. He doesn't just teach today's techniques—he prepares you for the future disruptions reshaping the field. His book is essential reading for current and aspiring data engineers, data analysts, data architects, engineering managers, CTOs, CDOs, and data-focused entrepreneurs looking to gain an edge over the competition. What You Will Learn: Master the core principles and practices of data engineering to build a long, successful career in the field. Accelerate your impact using AWS cloud services for scalable, modern data solutions. Explore how the role of the modern data engineer is evolving to support generative and agentic AI use cases. Develop a modern data strategy by working backwards from business goals to gain buy-in from CxO-level leadership. Design and deploy modern data architectures—including data lakes, data mesh, and data marts—and understand when to use each. Apply generative and agentic AI to enhance every stage of the data engineering lifecycle. Evaluate emerging data and AI technologies using proven methodology to separate real value from hype. Prepare for the future of data engineering powered by autonomous agents that scale enterprise impact. Who this Book Is For: Data engineers, analysts, architects, and tech leaders seeking practical guidance on AWS data engineering and generative AI, with or without prior cloud experience.

Ultimate Agentic Ai With Autogen For Enterprise Automation

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Author : Shekhar Agrawal
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-06-30

Ultimate Agentic Ai With Autogen For Enterprise Automation written by Shekhar Agrawal and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.

TAGLINE Empowering Enterprises with Scalable, Intelligent AI Agents. KEY FEATURES ● Hands-on practical guidance with step-by-step tutorials and real-world examples. ● Build and deploy enterprise-grade LLM agents using the AutoGen framework. ● Optimize, scale, secure, and maintain AI agents in real-world business settings. DESCRIPTION In an era where artificial intelligence is transforming enterprises, Large Language Models (LLMs) are unlocking new frontiers in automation, augmentation, and intelligent decision-making. Ultimate Agentic AI with AutoGen for Enterprise Automation bridges the gap between foundational AI concepts and hands-on implementation, empowering professionals to build scalable and intelligent enterprise agents. The book begins with the core principles of LLM agents and gradually moves into advanced topics such as agent architecture, tool integration, memory systems, and context awareness. Readers will learn how to design task-specific agents, apply ethical and security guardrails, and operationalize them using the powerful AutoGen framework. Each chapter includes practical examples—from customer support to internal process automation—ensuring concepts are actionable in real-world settings. By the end of this book, you will have a comprehensive understanding of how to design, develop, deploy, and maintain LLM-powered agents tailored for enterprise needs. Whether you're a developer, data scientist, or enterprise architect, this guide offers a structured path to transform intelligent agent concepts into production-ready solutions. Start building the next generation of enterprise AI agents with AutoGen—today. WHAT WILL YOU LEARN ● Design and implement intelligent LLM agents using the AutoGen framework. ● Integrate external tools and APIs to enhance agent functionality. ● Fine-tune agent behavior for enterprise-specific use cases and goals. ● Deploy secure, scalable AI agents in real-world production environments. ● Monitor, evaluate, and maintain agents with robust operational strategies. ● Automate complex business workflows using enterprise-grade AI solutions. WHO IS THIS BOOK FOR? This book is tailored for AI/ML engineers, software developers, data scientists, solution architects, enterprise tech leads, product managers, innovation strategists, and CTOs. It’s also valuable for business leaders and decision-makers seeking to understand and leverage LLM-powered agentic systems for scalable, intelligent enterprise solutions. TABLE OF CONTENTS 1. Introduction to LLM Agents (Foundation and Impact) 2. Architecting LLM Agents (Patterns and Frameworks) 3. Building a Task-Oriented Agent using AutoGen 4. Integrating Tools for Enhanced Functionality 5. Context Awareness and Memory System 6. Designing Multi-Agent Systems 7. Evaluation Framework for Agents and Tools 8. Agent-Security, Guardrails, Trust, and Privacy 9. LLM Agents in Production 10. Use Cases for Enterprise LLM Agents 11. Advanced Prompt Engineering for Effective Agents Index

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 Free with your book: PDF Copy, AI Assistant, and Next-Gen Reader 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 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.

Enterprise Guide For Implementing Generative Ai And Agentic Ai

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Author : Shakuntala Gupta Edward
language : en
Publisher: Apress
Release Date : 2025-12-10

Enterprise Guide For Implementing Generative Ai And Agentic Ai written by Shakuntala Gupta Edward and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-10 with Computers categories.

Generative AI and Agentic AI together are revolutionizing the technology landscape, with profound and far-reaching impacts across industries. Organizations are increasingly adopting these technologies to drive innovation, enhance unstructured content management, and improve problem-solving capabilities. With Agentic AI, enterprises are moving towards the development of intelligent systems that can plan, reason, and act with autonomy. While early proof-of-concepts (POCs) demonstrated the potential of these technologies, the current shift is toward responsible and scalable production implementations that leverage both generative and agentic capabilities. This book begins by guiding you through the technological evolution of AI, from early machine learning to today’s large language models (LLMs) and agentic systems. It then explores a wide range of use cases across industries, highlighting how LLMs can support decision-making, and how Agentic AI enables dynamic, collaborative systems that act with autonomy and intent. This is followed by Design Patterns across the lifecycle of AI solution development, deployment and monitoring. Readers will then gain insights into the methodologies for developing and deploying Generative and Agentic AI solutions at an enterprise level. A featured implementation demonstrates how Agentic AI can be effectively put into action. The book also introduces essential concepts such as MLOps, LLMOps, and Responsible AI principles which are critical for transitioning the AI solutions from experimentation to production. These principles ensure that AI deployments are scalable, secure, ethical and compliant. The book concludes with key takeaways and best practices for developing, evaluating, deploying and scaling AI applications responsibly and effectively within enterprise settings. You Will: Understand key design patterns to develop, deploy and monitor a Generative AI solution effectively. Learn how to develop and implement a production-ready Agentic AI use case. Discover best practices for building scalable, secure, and enterprise-grade AI solutions. Understand how to assess and mitigate risks using Responsible AI principles and LLMOps best practices. This book is for : Enterprise Software Engineers and Architects

Agentic Ai Playbook

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Author : Tommy M Mayer
language : en
Publisher: Independently Published
Release Date : 2025-11-07

Agentic Ai Playbook written by Tommy M Mayer and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-07 with Computers categories.

Turn prompts into finished work with a playbook that teaches you how to design reliable agentic ai for real tasks. This book shows how ai agents think through goals, plan steps, and call tools so your team ships outcomes, not drafts. You will see how llm agents combine reasoning, memory, and action, and you will learn how to build ai agents that follow clear rules, respect limits, and report what they do. Practical examples walk through langchain agents and langgraph agents, while grounding results with retrieval augmented generation (rag) for accurate, source-aware output. You will discover where autonomous ai systems shine and how multi-agent systems llm patterns divide work across specialists for speed and consistency. If you care about measurable gains, you will appreciate the chapters on ai workflow automation that reduce manual clicks and errors. The book explains how to package agentic ai services that act as real ai value creators, and how to stand up an instant ai agency inside your company. New builders can learn ai step by step, from policies to prompts, while advanced readers sharpen ai agent engineering skills and tune ai for llm orchestration. Clear diagrams connect ai and llm roles with classic ai engineering practice so teams can align on design choices. You will also see how llm and ai work together in pipelines that you can share with peers and learn with ai using repeatable tests. For those scaling production tasks, the guide links ai machine learning llm concepts to operations that matter, including cost, latency, and quality. Founders will find a path to ai & automation for entrepreneurs, including patterns for an ai sales agent that qualifies leads and writes follow-ups. Builders get hands-on methods for ai agent build while they build ai skills in safe sandboxes. You will map a clean ai agent workflow from intake to review, understand where plain ai is enough, and know when building generative ai agents pays off. Teams responsible for ai agents development will adopt checklists that support audits and uptime. Engineers can deepen agentic ai engineering practice, apply ai for engineering tasks like documentation and testing, and tie projects to outcomes that speak the language of ai & money. Across use cases, the goal stays simple. Design for clarity, verify with tests, and scale with discipline so every agent earns trust, saves time, and delivers results your users can measure.

Azure Ai Engineer Associate Ai 102 Study Guide

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Author : Renaldi Gondosubroto
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-09-09

Azure Ai Engineer Associate Ai 102 Study Guide written by Renaldi Gondosubroto and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-09 with Computers categories.

With the GenAI boom showing no sign of letup, the demand for AI skills will only increase with time and innovation. Microsoft Azure leads the pack with services for developing and deploying AI solutions, so professionals looking to break into this field should consider pursuing certification as an Azure AI Engineer Associate. Azure's AI-102 exam isn't a piece of cake, but author Renaldi Gondosubroto makes it a great deal more approachable with this comprehensive study guide. Packed with expert guidance, it covers everything you'll need to know to pass the exam. You'll dive deep into all the phases of AI solutions development, from requirements definition and design to development, deployment, and integration, along with maintenance, performance tuning, and monitoring throughout. The book also takes you through practical implementation of these systems, covering decision support, computer vision, natural language processing, knowledge mining, document intelligence, and generative AI solutions. Understand the core concepts of Azure AI services Develop and deploy AI solutions within Azure's environment Explore integration and security practices with Azure AI services Optimize and troubleshoot AI models on Azure Gain knowledge about building GenAI solutions on Azure and put it into practice

Ai Revolution Research Ethics And Society

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Author : Hamid R. Arabnia
language : en
Publisher: Springer Nature
Release Date : 2026-01-01

Ai Revolution Research Ethics And Society written by Hamid R. Arabnia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Computers categories.

This book constitutes the proceedings of the International conference on AI Revolution: Research, Ethics and Society, AIR-RES 2025, held in Las Vegas, Navada, USA, during April 14–16, 2025. The AIR-RES Conference received 620 submissions, of which 131 papers were accepted, resulting in a paper acceptance rate of 21%.