Summary

The article discusses the evolution of generative AI applications into agentic AI systems at Amazon, highlighting the need for a comprehensive evaluation framework. It emphasizes the importance of assessing not just individual model performance but also the emergent behaviors of the entire system. The authors present a detailed evaluation methodology that includes automated workflows and a library of metrics tailored for agentic AI applications. Best practices and lessons learned from real-world implementations are shared to guide developers in evaluating and deploying these complex systems effectively.

Data Problems Addressed

Technologies Referenced