AI Autonomous Agents with Python Programming

Par : Edgar Milvus
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  • FormatePub
  • ISBN8232432874
  • EAN9798232432874
  • Date de parution09/12/2025
  • Protection num.pas de protection
  • Infos supplémentairesepub
  • ÉditeurDraft2Digital

Résumé

Stop Building Chatbots. Start Building Digital Workers. The era of static "prompt-and-response" AI is over. The future belongs to Autonomous Agents-systems that don't just talk, but act, plan, debug, and collaborate to solve complex problems without human intervention. This book is the definitive handbook for senior developers ready to master the most advanced frontier of Generative AI. This is not a theoretical overview; it is a deep-dive architectural guide to building resilient, self-healing, and collaborative multi-agent systems (MAS).
From the OODA loop to production deployment, you will learn how to transform an LLM from a text generator into a reasoning engine capable of controlling web browsers, writing software, and managing financial portfolios. What You Will Master:- The Cognitive Architecture: Move beyond simple Chains. Master the OODA Loop (Observe, Orient, Decide, Act) and build agents that can plan and re-plan dynamically.- Multi-Agent Orchestration: Use CrewAI to build teams of specialized agents (Researchers, Writers, Analysts) that collaborate, delegate tasks, and review each other's work.- Cyclic Graphs with LangGraph: Break free from linear workflows.
Build complex, stateful loops that allow agents to self-correct errors, refine code, and iterate until success.- Memory & RAG: Equip your agents with a "Hippocampus." Implement Vector Stores and Retrieval-Augmented Generation so your agents remember facts and learn from past interactions.- Tool Use & Browser Automation: Give your agents hands. Teach them to browse the live web using Selenium, interact with APIs, and scrape real-time data.- Production-Grade Security: Protect your swarm from Prompt Injection and "Rogue Loops" (infinite resource consumption) with strict execution budgets and input sanitization.- Observability & Economics: Use LangSmith to trace complex debugging chains and master Token Economics to keep your AI costs under control.
The Capstone ProjectTie it all together by building a fully autonomous Software Development Agency Swarm. You will architect a Product Owner agent, a Developer agent, and a QA agent that work in a closed loop to write, test, and fix code automatically. Are you ready to architect the next generation of AI?