AI agents are becoming more sophisticated. They are evolving from answering questions to autonomously executing multi-step complex tasks. But before these agents can be trusted to book trips or conduct financial analysis on behalf of users, model providers and the startups building such agents want to ensure that they perform reliably across a vast range of scenarios. AI labs often use benchmarks to show off their model’s prowess, but a high score, even on an agent-oriented benchmark, doesn’t ac...