Post by Outlier

Most teams evaluating AI agents are still grading them like chatbots. A chatbot gives you information. An agent takes action. The evaluation has to match. Our team published a breakdown of what good agent evaluation looks like. Core idea: score the full trajectory from goal to completion, not individual answers. System prompt adherence matters more than output quality on any single step. An agent that ignores its instructions but gets lucky isn't reliable. Give the agent less to work with and see whether it asks clarifying questions or guesses. That tells you more about reasoning quality than a polished prompt ever will. Evaluate agents the way a senior engineer reviews a junior's pull request. Not whether the output compiles, but whether the decisions were sound and problems were handled with skill, not luck. https://lnkd.in/gmMpxyiU