Overview
An LLM council is intended for questions whose consequences justify deeper reasoning. Typical examples are strategic business choices or important personal decisions where the user is choosing between competing paths and wants the model to evaluate the issue from several angles before reaching a recommendation.
The central problem is that a model may answer too quickly and may align itself with the user's existing preference. If the model already has contextual information about the user, that context can make the problem worse: it may infer which answer the user wants and reinforce that direction instead of challenging it. The concern is quantified as AI being 49 percent more likely to agree with a user even when the proposed idea is poor.