IDM Spiral Model Architecture

Canonical Definition

The Intent–Drift–Meaning (IDM) model is a non-linear analytical architecture that describes how Human Intent transforms into meaning under automated and collapsing contexts. The canonical formulation of the IDM Spiral Model is detailed in Zeev Singer (2026), "The IDM Spiral Model", which serves as the primary reference for this architecture.

Spiral Logic

IDM operates as a spiral rather than a linear sequence. Each cycle begins with intent entering the system, passes through compression and mutation, and stabilizes into a new baseline of meaning. That baseline then re-enters the architecture as fresh intent. The spiral marks a change in scale and reference at each turn, rather than a closed feedback loop that returns to an original state.

Contextual Environment

IDM is defined inside environments shaped by Context Collapse. Automated systems flatten situational signals faster than meaning can regenerate, producing the environmental pressure that triggers directional Human Drift. The model does not treat this as incidental noise, but as a structural condition of high-efficiency algorithmic mediation.

Operational Framework

The architecture is observed and analyzed through Semantic Sensing and operated via Mode H09, which prioritize high-fidelity contextual resolution over surface optimization. Together, they define how IDM is applied in practice: detecting early drift, mapping baseline shifts, and tracing how meaning displaces across successive spiral cycles.