ServiceNow's Tara Bogavelli discussed AgentArch, a new benchmarking tool developed to evaluate AI agent architectures within real-world enterprise workflows, aiming to move beyond traditional static Q&A benchmarks. Unlike synthetic benchmarks, AgentArch measures agent performance in environments that reflect actual enterprise conditions, emphasizing task completion, adaptability, tool calibration, and long-horizon coherence. This approach helps identify how agents interact with systems, APIs, and people, addressing challenges like maintaining coherence over multiple steps and recovering from workflow disruptions. AgentArch is designed to be modular and model-agnostic, allowing it to assess diverse architectures in workflow contexts, and it plans to expand to measure collaborative capabilities among agents. By focusing on real-world performance rather than isolated task accuracy, AgentArch provides insights into an agent's robustness in dynamic enterprise environments.