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Autor(en): 
  • Robert J Godwin
  • Mastering Microsoft AutoGen: The Complete Guide to Building, Scaling, and Orchestrating Multi-Agent AI Systems with Python 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Mai 2026  
    Genre:  EDV / Informatik 
     
    COMPUTERS / Artificial Intelligence / Generative AI / COMPUTERS / Programming Languages / Python
    ISBN:  9798197332813 
    EAN-Code: 
    9798197332813 
    Verlag:  Independently Published 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 254 mm / B 178 mm / D 10 mm 
    Gewicht:  321 gr 
    Seiten:  178 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Stop Prompting. Start Orchestrating.The era of the simple chatbot is over. Welcome to the age of the autonomous
    digital workforce.
    In just a few years, we have moved from asking AI to "write an email" to
    requiring AI to "run a company's research department." Single-prompt
    interactions are no longer enough. To solve the complex challenges of 2026, you
    need a team of specialized, collaborative, and self-healing AI agents.
    Mastering Microsoft AutoGen is the definitive, code-rich guide for developers,
    data scientists, and AI architects ready to lead the next revolution in software
    engineering. Whether you are building a self-improving coding suite, a real-time
    financial analyst, or a global supply chain swarm, this book provides the
    professional blueprint for autonomous intelligence.
    What's Inside the Laboratory?
    This book takes you through a proven Dialogue-to-Deployment (D2D) framework,
    moving from basic agent construction to industrial-scale orchestration. You will
    master:
    - The Core Architecture: Go deep into the DNA of ConversableAgent,
    AssistantAgent, and the vital UserProxyAgent.
    - Self-Healing Code: Build agents that write, test, and debug their own
    software in secure Docker sandboxes.
    - Advanced Orchestration: Move beyond simple chats into Sequential Workflows,
    Nested Conversations, and Graph-Based (DAG) decision trees.
    - Grounded Memory (RAG): Connect your agents to the real world using Vector
    Databases like ChromaDB, Pinecone, and Qdrant.
    - Skills & Tool Use: Teach your agents to use the web, query SQL databases,
    and interact with any API.
    - Production-Grade LLMOps: Scale your swarms with Redis caching, monitor
    "agent thoughts" with LangSmith and Phoenix, and deploy using FastAPI and
    Kubernetes.
    - Safety & Governance: Protect your budget and your infrastructure with prompt
    injection defense and economic circuit breakers.
    In-Depth Professional Case Studies
    Theory is nothing without application. This book culminates in the design of two
    massive, real-world projects:
    1. The Autonomous Financial Analyst: A multi-agent "War Room" that synthesizes
    market data, performs quantitative math, and drafts investment memos.
    2. The Digital Software House: A self-improving department where Product
    Managers, Coders, and QA Engineers build and test software 24/7.
    Who Is This Book For?
    - Python Developers looking to transition into Agentic Workflows.
    - AI Architects designing scalable multi-agent systems for enterprise.
    - Tech Leads who need to implement secure, cost-effective LLM solutions.
    - Innovation Managers ready to replace static chatbots with autonomous digital
    workers.
    Lead the Agentic Revolution
    The world is moving from "AI as a tool" to "AI as a teammate." By mastering the
    AutoGen framework, you aren't just learning a library-you are learning how to
    architect the "Society of Mind" that will define the future of computing.
    Don't just chat with the future. Build it.
    Keywords: Microsoft AutoGen, AI Agents, Multi-Agent Systems, Python AI, LLMOps,
    RAG, Autonomous AI, GPT-4o, Llama 3, Vector Databases, Docker for AI, FastAPI,
    LangChain, CrewAI, Agentic Workflows.

      



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