Building Agentic Ai From Scratch Pdf
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Building Agentic AI Systems
Author: Anjanava Biswas
language: en
Publisher: Packt Publishing Ltd
Release Date: 2025-04-21
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
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
Agentic Artificial Intelligence
Author: Pascal Bornet
language: en
Publisher: Irreplaceable Publishing
Release Date: 2025-03-17
A practical, non-technical guide for business leaders, entrepreneurs, and curious minds "Agents are (…) bringing about the biggest revolution in computing since we went from typing commands to tapping on icons." — Bill Gates "AI agents will become the primary way we interact with computers in the future.” — Satya Nadella "The age of agentic AI is here"— Jensen Huang In a world where ChatGPT took us by storm, a far more powerful revolution is unfolding: AI Agents. Like Jarvis in Iron Man or Samantha in Her, these intelligent systems can execute actions, learn from experience, and orchestrate digital interactions with minimal human supervision. They promise to redefine business and society. However, behind the excitement lies a crucial reality: a significant gap between promise and reality. This comprehensive guide on agentic AI cuts through the hype and offers a clear, jargon-free strategic roadmap to understanding and applying this technology. The authors bring a rare perspective, having implemented agentic AI across diverse organizations—from global enterprises to agile startups—witnessing both remarkable successes and sobering failures. Through illuminating case studies and hands-on experiments, the authors reveal: - A step-by-step method for identifying high-value agentic opportunities and building impactful agents in your business, work, and personal life - The secrets behind today's most successful agentic transformations at scale: cutting costs by over 25% while boosting customer satisfaction by over 40% - Approaches to seize the new opportunities of the Agent Economy—new business models, Agentic-driven startups, rapid scaling, and game-changing revenue opportunities. - Hands-on guidance to navigate common pitfalls such as workflow integration, error handling, data quality, agent control, and user adoption - The new mindset and skills required to lead effectively in a world where humans and AI agents need to work seamlessly together The profound impact of agentic AI on society, employment, education, and our personal lives AI agents create what the authors call "compounding intelligence advantages"—the more they're used, the smarter they become, creating an accelerating gap between early adopters and laggards. Hence, those who understand and leverage AI agents today will define the next business era. The question isn’t whether AI agents will transform your industry—it’s how you will lead that change. Every revolution demands foresight and responsibility. This book challenges you to not just adopt agentic AI, but to shape it with purpose and integrity.