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Learn how to effectively debug and evaluate AI agents through structured tracing in this 15-minute conference talk. Discover why traditional logging methods fall short when dealing with complex, multi-step autonomous AI systems and explore how comprehensive traces can capture the complete narrative of an agent's execution, including chains of thought, tool calls, and model interactions. Understand practical applications for using these traces to rapidly identify and fix failures, construct robust evaluation frameworks, and develop golden datasets for regression testing. Gain insights into building more reliable and predictable AI agents by implementing proper tracing methodologies that provide complete visibility into agent behavior and decision-making processes.
Syllabus
AI traces are worth a thousand logs
Taught by
MLOps.community