A developer explains why AI agents need an evaluation hierarchy to understand users better. The framework helps builders move beyond surface-level interactions to model what users actually believe and want, improving how AI systems represent and respond to people.
All down to the recommendations. We've talked about belief systems. We talked about why creating representations of the self, the user and belief systems and an engine to evolve that over time is very useful to get to the causal structures and to approximate reality as perceived by that user. And in the context of your AI experience or agent or element, application or chatbot, I kind of think of this eval hierarchy of needs or hierarchy of eval needs for an agent to really understand a user starts at the foundation models, then the application evals, and then user centric and belief centric, and that's epistemic evals.
