Abstract The theory of Self-Preserving Flow (SPF) proposes that stability in long-horizon intelligent systems cannot be sufficiently guaranteed through local transition validity, behavioral consistency, or stationary constraint enforcement alone. SPF introduces a continuity-centered framework in which systemic identity is understood as an epistemic property: the historically reconstructible continuity of semantic evolution across recursive adaptation. This framework distinguishes between first-order adaptive evolution within established interpretive constraints and second-order governed revision of those constraints under historically accountable transformation. The central contribution of SPF is the introduction of a layered conceptual architecture consisting of the Semantic Consistency Layer (SCL), Dynamic Pattern Adaptation (DPA), and a higher-order meta-governance regime that preserves continuity across semantic self-reconstruction. SPF provides a conceptual basis for diagnosing semantic erosion, recursive drift, and interpretive collapse in advanced autonomous systems while remaining non-intrusive at the execution layer.
Ali Mofradi (Mon,) studied this question.