Autonomic Safety as Missing Infrastructure

Despite sustained progress in clinical interventions for depression, long-term outcomesremain fragile at scale, with relapse and functional stagnation persisting across settings.This paper argues that the limitation lies not primarily in therapeutic effectiveness but in astructural omission: systems of care often behave as if feasibility for change were constant,while it is in fact variable and largely shaped outside clinical encounters. We advance aconstraint-based conceptual theory in which autonomic safety and temporal predictabilityare necessary—though not sufficient— preconditions for the feasibility of sustained recovery. The framework introduces no new treatments, diagnoses, or biological mechanisms.Instead, it formalizes a missing infrastructural layer linking individual physiology, home environments, family dynamics, and resource-constrained public care. Operational guidanceis provided for AI systems, explicitly bounded to feasibility preservation (GO/NO-GO), notclinical decision-making