•Resting-state fMRI biomarkers in psychiatry often lack disorder specificity.•Transdiagnostic study designs allow direct assessment of biomarker specificity.•p-factor models reveal biomarkers common across most diagnostic axes of psychiatry.•The functional connectome develops into an individualized fingerprint.•Delayed individualization is a biomarker that may be characterized using networks. Searching for biomarkers has been a chief pursuit of the field of psychiatry. Toward this end, studies have catalogued candidate resting-state biomarkers in nearly all forms of mental disorder. However, it is becoming increasingly clear that these biomarkers lack specificity, limiting their capacity to yield clinical impact. We discuss three avenues of research that are overcoming this limitation: (i) the adoption of transdiagnostic research designs, which involve studying and explicitly comparing multiple disorders from distinct diagnostic axes of psychiatry; (ii) dimensional models of psychopathology that map the full spectrum of symptomatology and that cut across traditional disorder boundaries; and (iii) modeling individuals’ unique functional connectomes throughout development. We provide a framework for tying these subfields together that draws on tools from machine learning and network science.