People and businesses are outsourcing their tasks to AI agents everywhere across the economy for increasingly high stakes responsibilities. How can they know which agents they should trust among the endless sea of grand promises and black-box operations? Agent users need more effective ways of evaluating the performance and reliability of these autonomous systems. Traditional methods such as benchmarks and A/B testing provide a starting point, however exposing agents to real-world conditions ...