01 - AI Agents: Introduction, What They Are and When to Use Them
What are AI Agents, how they differ from traditional chatbots and when to adopt them. Complete overview of the autonomous agent paradigm with LLMs.
AI agents: architetture ReAct, tool use, planning, multi-agent systems, orchestrazione e deployment di agenti AI autonomi per compiti complessi.
What are AI Agents, how they differ from traditional chatbots and when to adopt them. Complete overview of the autonomous agent paradigm with LLMs.
The fundamental patterns of AI Agents: OODA cycle, ReAct framework (Reasoning + Acting) and the Tool Calling mechanism for interacting with external systems.
Building AI Agents with LangChain and LangGraph 1.0: from AgentExecutor to stateful graphs. Tools, chains and the new production standard for LLM agents.
CrewAI for orchestrating AI agent teams with roles, goals and coordination. Crew patterns, task delegation and multi-agent collaboration in practice.
Microsoft's AutoGen (now AG2) for emergent multi-agent conversations. GroupChat, conversational patterns and the new Microsoft Agent Framework.
The 5 multi-agent orchestration patterns for production: Sequential, Concurrent, Group Chat, Handoff and Plan-First. Scalable and fault-tolerant architectures.
Memory systems for AI Agents: short-term, long-term and episodic memory. Vector stores, knowledge graphs and the Mem0 framework for persistent memory.
Advanced tool calling techniques: creating custom tools, integrating REST APIs, web scraping and function calling. Composition patterns and robust error handling.
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