Executive Summary AI observability is the practice of monitoring the behavior, performance, quality, cost, security, and reliability of AI applications in production. Unlike traditional application monitoring, it must trace what happened inside the AI system—including model calls, prompts, retrieved context, tool calls, agent decisions, workflow steps, token usage, latency, errors, and final outcomes. This distinction […]