A new mechanistic interpretability study reveals that large language models handle emotional affect reception — detecting whether something is positive or negative — through circuits distinct from those performing emotion categorization, such as labeling a feeling as 'joy' or 'anger'. The research suggests these are dissociable cognitive-like processes, not a single unified mechanism. The findings have implications for how we audit and trust AI systems deployed in emotionally sensitive contexts.