Why Traditional Observability Falls Short for AI Agents

The discussion centers on the evolution of data observability in the age of AI agents. Lior Gavish, CTO and co-founder of Monte Carlo Data, describes how data teams are increasingly building and deploying AI agents to automate tasks and enhance user experiences across various industries. A key shift involves the need for more granular telemetry and traces to monitor agent behavior, along with new techniques to interpret unstructured data generated by these systems. The conversation highlights challenges in security, compliance, and measuring the quality of agent outputs, emphasizing the importance of specialized tools for agent observability and governance.