Building Generative Ai Agents
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Building Generative Ai Agents
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Author : Tom Taulli
language : en
Publisher: Springer Nature
Release Date : 2025-06-15
Building Generative Ai Agents written by Tom Taulli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-15 with Computers categories.
The dawn of AI agents is upon us. Tech visionaries like Bill Gates, Andrew Ng, and Vinod Khosla have highlighted the monumental potential of this powerful technology. This book will provide the knowledge and tools necessary to build generative AI agents using the most popular frameworks, such as AutoGen, LangChain, LangGraph, CrewAI, and Haystack. Recent breakthroughs in large language models have opened up unprecedented possibilities. After years of gradual progress in machine learning and deep learning, we are now witnessing novel approaches capable of understanding, reasoning, and generating content in ways that promise to revolutionize nearly every industry. This platform shift is as significant as the advent of mainframes, PCs, cloud computing, mobile technology, and social media. It’s why the world’s largest technology companies – like Microsoft, Apple, Google, and Meta – are making enormous investments in this category. While chatbots like ChatGPT, Claude, and Gemini have demonstrated remarkable potential, the years ahead will see the rise of generative AI agents capable of executing complex tasks on behalf of users. These agents already exhibit capabilities such as running test suites, searching the web for documentation, writing software, answering questions based on vast organized information, and performing intricate web-based tasks across multiple domains. They can autonomously investigate cybersecurity incidents and address complex customer support needs. By integrating skills, knowledge bases, planning frameworks, memory, and feedback loops, these systems can handle many tasks and improve over time. Building Generative AI Agents serves as a high-quality guide for developers to understand when and where AI agents can be useful, their advantages and disadvantages, and practical advice on designing, building, deploying, and monitoring them. What You Will Learn The foundational concepts, capabilities, and potential of AI agents. Recent innovations in large language models that have enabled the development of AI agents. How to build AI agents for launching a product, creating a financial plan, handling customer service, and using Retrieval Augmented Generation (RAG). Essential frameworks for building generative AI agents, including AutoGen, LangChain, LangGraph, CrewAI, and Haystack. Step-by-step guidance on designing, building, and deploying AI agents. Insights into the future of AI agents and their potential impact on various industries. Who This Book Is For Experienced software developers
Generative Ai Llms A Hands On Guide To Building Ai Agents A Practical Guide To Building Fine Tuning And Deploying Ai Agents With Large Language Models Learn Prompt Engineering Rag And Autonomous Systems
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Author : Anshul Saraf
language : en
Publisher: Anshul Saraf
Release Date : 2026-01-06
Generative Ai Llms A Hands On Guide To Building Ai Agents A Practical Guide To Building Fine Tuning And Deploying Ai Agents With Large Language Models Learn Prompt Engineering Rag And Autonomous Systems written by Anshul Saraf and has been published by Anshul Saraf this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-06 with Computers categories.
Unlock the Future of AI Development: Your Complete Guide to Building Intelligent Agents Master Generative AI & Large Language Models (LLMs) with this definitive, project-driven handbook. Whether you’re a software developer, data scientist, product manager, or tech entrepreneur, this book transforms you from an AI user into an AI architect—capable of designing, building, and launching sophisticated autonomous systems. What You Will Build & Learn: ✅ Prompt Engineering Mastery: Move beyond basic chats. Learn advanced prompting techniques—including few-shot learning, chain-of-thought (CoT) reasoning, and persona patterning—to reliably control LLM outputs. ✅ Build AI Agents with Memory: Implement RAG (Retrieval-Augmented Generation) systems to give your agents long-term knowledge, overcome hallucinations, and ground responses in your private data using vector databases. ✅ Create Autonomous AI Agents: Design and code agents that execute the Think-Act-Loop. Build systems that can reason, plan, and take action using tools and APIs to complete complex tasks without constant human input. ✅ Develop Multi-Agent Systems: Orchestrate teams of specialized AI agents that collaborate, debate, and delegate to solve problems no single agent could handle. ✅ Fine-Tune LLMs: Go beyond prompting. Learn how to fine-tune models like GPT and open-source LLMs on your custom data to create domain-specific experts with a unique voice and superior performance. ✅ Real-World Deployment: Navigate the complete pipeline from prototype to production. Learn deployment strategies, monitoring, logging, safety guardrails, and cost optimization for scalable AI agent applications. Inside This Practical Guide: Step-by-Step Tutorials with clear explanations and conceptual diagrams. Hands-On Projects including a Research Agent, an Autonomous Scheduling Assistant, and a Multi-Agent Marketing Team. Production-Ready Code Patterns using Python, OpenAI API, LangChain, and vector databases. Ethical Framework & Best Practices for building responsible, transparent, and safe AI. Perfect For: Developers ready to build AI-powered features and products. Engineers and ML practitioners expanding into applied LLMs and agentic AI. Tech leaders and founders who need to understand the capabilities and roadmap of autonomous AI. Anyone tired of theoretical hype and eager for practical, buildable skills in generative AI. Stop just using AI. Start building it. Your journey to becoming an AI Agent architect begins here.
Core Ai Agent Design
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Author : Tristin Reed
language : en
Publisher: Independently Published
Release Date : 2025-09-15
Core Ai Agent Design written by Tristin Reed and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-15 with Computers categories.
Core AI Agent Design is a practical introduction to building AI agents that reason, act, and adapt beyond simple prompts. Written for beginners in agentic AI, it explains the fundamentals of autonomy, planning, action, and feedback loops, showing how agents differ from plain LLM applications. The book guides readers through the perception → planning → action → reflection cycle and provides a clear understanding of goal-directed behavior and the current limits of AI reasoning. With frameworks such as LangChain, CrewAI, and AutoGen, readers see how today's tools make it possible to create agents with real functionality. Practical examples inspired by building AI agents, building generative AI agents, and LangChain programming for beginners connect concepts to implementation. A step-by-step walkthrough of a simple functional agent demonstrates how to set up APIs, define purpose, and test interactions. By the end, readers will have created their first working system, gaining clarity on generative AI with LangChain and confidence to continue. For anyone searching for agentic AI or AI agents for business, this book delivers a strong foundation for intelligent agent design.
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.
Building Ai Agents With Crewai Langchain And Langgraph
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Author : NATHANIEL. CROSSFIELD
language : en
Publisher: Independently Published
Release Date : 2025-04-04
Building Ai Agents With Crewai Langchain And Langgraph 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 2025-04-04 with Technology & Engineering categories.
Building AI Agents with CrewAI, LangChain, and LangGraph: Automating Workflows with Multi-Agent Systems and Generative AI AI-powered automation is revolutionizing industries, and multi-agent systems are at the forefront of this transformation. CrewAI, LangChain, and LangGraph enable developers to build sophisticated, autonomous AI agents capable of handling complex tasks, orchestrating workflows, and making intelligent decisions. As businesses and developers race to integrate AI-driven solutions, mastering these tools is essential to staying ahead in the rapidly evolving AI landscape. This book is written by Nathaniel Crossfield, a recognized expert in AI automation, large language models (LLMs), and AI agent orchestration. With years of experience in AI development and real-world applications, Nathaniel provides in-depth insights, practical examples, and best practices to help developers harness the full potential of CrewAI, LangChain, and LangGraph. Building AI Agents with CrewAI, LangChain, and LangGraph is your ultimate guide to mastering AI agent development and automation. This book takes you from the fundamentals to advanced implementations, providing hands-on projects and real-world case studies. Whether you're building chatbots, AI-driven assistants, or complex automation workflows, this book equips you with the knowledge and skills to design, deploy, and optimize AI agents effectively. What's Inside: Introduction to AI agent frameworks: CrewAI, LangChain, and LangGraph Step-by-step guide to building and deploying multi-agent AI systems Techniques for improving AI reasoning, memory, and decision-making Integration with LLMs, APIs, and real-world data sources Advanced strategies for AI collaboration, automation, and scalability Real-world applications, case studies, and best practices This book is for AI developers, software engineers, data scientists, and tech entrepreneurs looking to leverage AI automation for productivity, efficiency, and innovation. Whether you're a beginner exploring AI agents or an experienced developer seeking advanced techniques, this book provides actionable insights and practical implementations to help you succeed. AI is evolving faster than ever, and those who master AI automation now will lead the future of intelligent systems. Companies are rapidly adopting AI-driven workflows, and understanding multi-agent systems is a game-changer. Don't get left behind-stay ahead of the AI revolution with this book. Get your copy of Building AI Agents with CrewAI, LangChain, and LangGraph today and start building the next generation of AI automation. Whether you're creating AI-powered chatbots, streamlining enterprise workflows, or developing autonomous AI systems, this book will give you the expertise you need to succeed. Start building intelligent AI agents now!
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.
Building Generative Ai Applications With Langchain And Google Cloud
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Author : David S Richard
language : en
Publisher: Independently Published
Release Date : 2025-09-08
Building Generative Ai Applications With Langchain And Google Cloud written by David S Richard and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-08 with Computers categories.
Building Generative AI Applications with LangChain and Google Cloud: A Hands-On Guide to Vertex AI, RAG, and AI Agents in Python Are you ready to turn the hype of Generative AI into real, production-ready applications? This book is your complete roadmap to mastering LangChain, Google Cloud Vertex AI, and cutting-edge techniques like Retrieval-Augmented Generation (RAG) and AI agents-all through practical, hands-on projects in Python. Inside, you'll discover how to: Build powerful AI applications that go beyond simple prompts Harness the full potential of LangChain to connect large language models with real-world data and APIs Leverage Google Cloud Vertex AI to train, deploy, and scale AI systems with enterprise-grade reliability Implement RAG pipelines to deliver accurate, context-aware responses from custom data Create intelligent AI agents that can reason, plan, and act autonomously Apply best practices in scalability, security, and cost optimization for cloud-based AI solutions This is not just another theory-heavy AI book. Every chapter is designed to give you immediate, practical skills that you can apply in your projects, whether you're a developer, data scientist, or technology leader. By the time you finish, you'll have the confidence and technical know-how to: Build generative AI systems that solve real business problems Integrate cutting-edge AI into existing applications and workflows Future-proof your career with one of the most in-demand skill sets of the decade If you're serious about becoming a leader in Generative AI, this book is your one-stop solution. Don't just watch the AI revolution-be the one building it.
Generative Ai Agent In Practice
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Author : Clifford C Sowders
language : en
Publisher: Independently Published
Release Date : 2025-06-25
Generative Ai Agent In Practice written by Clifford C Sowders and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-25 with Computers categories.
Generative AI Agent in Practice: A Developer's Guide to Building Intelligent, Self-Learning Assistants with LangChain and Transformers Are you ready to move beyond chatbots and start building real, intelligent agents? Imagine transforming your codebase into a dynamic, problem-solving assistant-one that can search, reason, interact with APIs, and adapt to new data automatically. In a world powered by generative AI, mastering these next-generation tools isn't just an advantage-it's essential. This book is your hands-on blueprint for building production-ready AI agents. Inside, you'll discover step-by-step guides for deploying agents that truly understand, remember, and act. From environment setup to advanced multi-agent workflows, every chapter delivers concise explanations, practical code, and expert insights drawn from real-world deployments. What sets this guide apart? End-to-End Workflows: Learn to build, test, and scale agents using proven frameworks like LangChain and Hugging Face Transformers. Retrieval-Augmented Generation (RAG): Combine semantic search, vector databases, and custom tools for agents that go beyond static knowledge. Prompt Engineering and Memory: Master the art of reusable prompt templates, context management, and versioning for reliable, robust performance. Tool and API Integration: Empower your agents to search the web, process files, call custom APIs, and automate entire workflows. Observability and Security: Gain production confidence with strategies for logging, monitoring, error handling, and security best practices. Practical Case Studies: Follow real-world examples, from customer support bots to developer assistants, that illustrate both pitfalls and successes. Are you building for the future of AI? Whether you're an engineer, data scientist, or AI enthusiast, this guide gives you a toolkit you can use today-no theory without code, and no code without real use cases. Take the next step: Supercharge your development workflow, launch smarter assistants, and future-proof your AI skill set. Grab your copy of "Generative AI Agent in Practice" and start building intelligent, self-learning agents that make a real impact.
Ai Agent Architecture
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Author : Domenic D Wood
language : en
Publisher: Independently Published
Release Date : 2025-08-25
Ai Agent Architecture written by Domenic D Wood and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-25 with categories.
The era of simple large language model (LLM) prompts is over. We are at the dawn of agentic systems-autonomous, tool-using AI entities capable of complex, multi-step problem-solving. This book introduces the Model Context Protocol (MCP), a groundbreaking architectural standard that transforms unstructured LLM interactions into structured, production-ready workflows. It is the definitive guide to moving beyond basic generative AI and mastering the principles of agent architecture, AI orchestration, and multi-agent frameworks. Authored by a team with extensive experience in deploying high-stakes, production-grade AI systems, this book is built on real-world insights and battle-tested strategies. We move past theoretical concepts to provide you with the practical, hands-on knowledge required to build, monitor, and deploy reliable AI agents. This is the playbook for serious builders, a direct result of solving the very engineering challenges this technology presents. AI Agent Architecture is your end-to-end masterclass on designing and building intelligent, autonomous agents. This practical guide takes you on a complete journey from foundational architectural design to final production deployment. You will learn to break down complex problems, integrate external tools, manage a multi-agent team, and create custom user interfaces that build trust. By the end, you won't just understand the theory of AI agents; you will have a working blueprint and the skills to build your own. What's Inside: The Model Context Protocol (MCP): A deep dive into the architectural pattern that defines modern AI agents. Multi-Agent Systems: Step-by-step tutorials on building collaborative teams of specialized agents for complex problem-solving. Practical Tool Integration: Hands-on examples for creating and managing tools, from simple APIs to sophisticated databases. Trust Factor Design: Learn to build user interfaces with real-time feedback, status, and transparent agent tracing. Production Deployment: A full final project walks you through containerizing your agent, building a web API with FastAPI, and deploying to the cloud. The Future of AI: Expert commentary on emerging standards, the evolution of multi-agent systems, and where the technology is headed. This book is for software developers, AI engineers, data scientists, and product managers who are ready to move beyond basic LLM prompts and build real-world AI applications. If you have a foundational understanding of Python and want to master the next generation of artificial intelligence, this guide is your essential resource. It's for anyone who wants to future-proof their skills and become a leader in the rapidly evolving world of AI engineering. The next major wave in AI technology is here, and it's driven by agents. The skills you need to build these systems are becoming the new standard for serious developers. The time to master this technology is now. Don't get left behind by the pace of innovation. This book provides a clear, practical path to becoming an expert in a field that is redefining software development. Unlock the power of autonomous AI. Master the architecture that makes it all possible. Get your copy now and start building the future.
Building Ai Agents
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Author : AJIT. SINGH
language : en
Publisher: Independently Published
Release Date : 2025-07-16
Building Ai Agents written by AJIT. SINGH and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-16 with Computers categories.
"Building AI Agents" is a comprehensive, practical, and modern guide designed to empower the next generation of AI developers. This book demystifies the complex world of Artificial Intelligence by focusing on a single, compelling goal: teaching you how to build intelligent agents from the ground up. It provides a structured path from foundational principles to the cutting-edge technologies that are defining our future. Key Features: 1. Real-World Capstone Project: A final chapter guides students step-by-step through building a practical AI agent (a customer service chatbot), providing invaluable hands-on experience. 2. Updated & Relevant Content: Includes dedicated, easy-to-understand sections on the latest breakthroughs, including Large Language Models (LLMs), Generative AI, and Transformers. 3. Simplicity and Clarity: Complex concepts are broken down into simple, digestible parts. The language is accessible, and examples are chosen for their intuitive nature (e.g., solving mazes, playing simple games, classifying reviews). 4. Progressive Learning Path: The 10-chapter structure provides a logical and seamless progression from basic agent definitions to advanced architectures, ensuring a solid and comprehensive understanding. 5. Focus on Ethics: Integrates the critical conversation about AI ethics, bias, and safety as a core component of AI development, not an afterthought. 6. Online Companion Resources: The book will be supported by a publicly available GitHub repository containing all code examples, datasets, and additional exercises, facilitating a hands-on learning experience. Who Should Read This Book? 1. B.Tech/B.E. Students in Computer Science, Information Technology, and AI & Machine Learning. 2. M.Tech/M.E. Students seeking a strong, practical foundation in AI agent design. 3. Software Developers and IT Professionals looking to transition into the field of AI. 4. Hobbyists and Self-Learners who want a structured, all-in-one guide to building AI. 5. "Building AI Agents" is more than a textbook; it's an invitation to become a creator in the age of intelligence. This book stands out by prioritizing intuition and application. We consciously avoid overly dense mathematical notation, instead using clear explanations and relatable analogies to build a strong conceptual foundation. The learning journey is carefully curated to mirror the historical and logical evolution of AI itself-starting with classical search and reasoning, moving to data-driven machine learning, and culminating in the powerful deep learning and reinforcement learning techniques used to build today's most sophisticated agents.