Distortion Geometry and the Deflationary Threshold: Why Construction Resists Intelligence—and When It Will Not

Residential construction is the only large-scale production system that has resisted the deflationary intelligence that reduced computation cost by a factor of ten trillion and genome-sequencing cost by fifteen million within a single generation. We argue this resistance is not coincidental: it is a structural consequence of a geometric compound of environmental distortions (D = exp(∑wₖ·ln(dₖ))) whose six channels have remained simultaneously elevated — a configuration that no single-channel intelligence intervention can overcome. We formalise distortion axiomatically, derive the geometric formula by necessity (not empirical fit), and introduce the Channel Synchronization Index (CSI) as an operational predictor of deflationary inflection: when CSI ≥ 3 channels compress simultaneously, a nonlinear phase transition in construction cost becomes likely. We calibrate a six-channel D_urban model against OECD, ILO, World Bank, and Eurostat data (2010–2026), compare current AI systems (GPT-4o, Claude 3.5/4, Gemini Ultra, agentic frameworks) by their D-compression capacity, and run a 10,000-scenario Monte Carlo simulation (Deucalion HPC, FCT Grant 2025.00020.AIVLAB.DEUCALION). Central estimate for sustained deflationary inflection: 2031–2035. Under a coordinated agentic AI scenario (CSI ≥ 5 by 2032), a 90% real price decline from peak becomes structurally achievable by 2050–2060. We provide eight falsifiability criteria. Definitions, axiom proofs, and full methodology are in the Appendix.