One thing worth emphasizing with ServiceNow AI agents is that a successful response doesn't always mean the workflow completed correctly. At IT Path Solutions, we see the importance of verifying the actual record changes, approval states, and downstream actions rather than relying only on the agent's final message. A useful safeguard is to define the expected postconditions for each action and check them before reporting success. This makes failures easier to detect and prevents an agent from presenting an incomplete workflow as a completed task.
Kartik N V J K
AI Developer | Making AI reliable, trustworthy & accessible to everyone | Active community contributor
Mistake 8 is the one I run into most, where a single clean run in the test console gets treated as proof. Building eval datasets from the execution logs of earlier runs is what finally helped my own agents, because real requests carry ambiguity I never think to write myself. Of those 100 scenarios, how many of yours end up being multilingual or hostile-text cases?