Containment Is Lying to You: Measuring AI Agents Like Employees — Druid AI

This post introduces a performance review framework for AI agents that goes beyond containment rate. It proposes a seven-pillar scorecard covering configuration, runtime, and governance, with 26 components scored and weighted by business impact. This framework aims to provide a more accurate measure of agent performance by considering factors like error tolerance, risk, compliance, drift, hallucination, tone, mandate, scope, business case, budget, platform, and outcome validation. It also discusses answering ROI questions and setting industry-specific targets.