Understanding psychosis benefits from experience sampling methodology (ESM), repeated self-reports collected in real life, to capture its dynamic, context-dependent nature as it unfolds naturally in daily life. In this seminar, I will present a series of studies using ESM to demonstrate how fluctuations in affective and social-cognitive processes contribute to the development and maintenance of positive and negative symptoms and their subclinical expressions. I will also discuss how integrating passive sensing and experimental tasks provides complementary insights into behavior, physiology, and cognition beyond subjective self-report in psychosis research. Together, findings from these studies highlight the value of multimodal, ecologically valid assessment strategies for advancing understanding of the psychopathological mechanisms underlying psychosis and informing digital, personalized interventions.