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This webinar explores the transformative world of Agentic AI and how it's changing intelligent systems. Dive into the fundamental components that define an AI agent, including memory, planning, and tool use capabilities. Compare the advantages of single-agent versus multi-agent systems across various applications. Examine different architectural approaches including Router-Tool, ReAct, hierarchical, and swarm-based designs. Learn about practical design patterns such as task routing, tool chaining, and role specialization that power effective agent implementations. Understand common failure modes like infinite loops and brittle planning that can undermine agent performance. Discover why improved evaluation methods, tracing, and observability are crucial for reliable agent systems. Watch a live demonstration of Arize Phoenix for agent tracing, evaluation, and debugging techniques. This 59-minute session from Data Science Dojo serves as the first installment in a community series with Arize AI, providing essential knowledge for anyone interested in the development and implementation of AI agent systems.
