There is a longstanding dispute concerning the structure of the psychological realm. ‘Representational realists’ maintain that the best explanations of human behaviors must mention the truth-conditional contents of relevant mental states. ‘Psychological deflationists’ maintain that such contents are not needed, since the required explanatory work can be done by less problematic notions like (non-semantic) computation and indication/information. Developing some ideas by Hartry Field and Frances Egan, Sanchez Gomez presents a deflationist strategy for replacing truth-conditional notions with indication-based analogues in canonical computational explanations, and argue that it undermines a standard abductive argument for representational realism. She then draws on the 'resource rational analysis' framework in computational cognitive science (Lieder & Griffiths, 2020) to motivate an alternative argument for representational realism. This alternative argument is more promising, since it isn’t threatened by similar deflationist paraphrases. But it relies on a potentially controversial assumption about the connection between reliability and learning.