From Generic Evals to Specific Monitors: The Annotation Queue Bridge

How to turn generic evaluation metrics into a useful starting point for AI Reliability. It's common now with all the talk about AI reliability to come to a bit of a conundrum: you know quality matters, but you don't yet know which failures matter most. You deploy a handful of broad evaluations like toxicity, hallucination, response length, and hope they catch the important stuff. Often what you find is that either you get no triggers because your prompt already passes them (models are being cons