Organizations incur substantial friction when guessing recipients' need profiles and pushing outputs toward those guesses. This paper develops an information-theoretic theory treating alignment friction as endogenous to specification codification. Architecture decomposes into three layers: a codified specification substrate encoding commitments across six ontological tiers, an interface layer defined by recipient-class perception-weight vectors, and a function layer whose headcount and spend constitute a measurable tax on specification gaps. In push regimes, energy loss scales with cross-entropy between guessed and actual need profiles. In pull regimes, consumption-layer AI lets recipients query the specification directly, collapsing misalignment toward zero as codification completeness rises. Recipient classes are architectural primitives whose distinct perception geometries impose coherence conditions across interfaces. Four contributions follow. First, push-pull cost asymmetry is formalized as a structural analog to Shannon's cross-entropy. Second, geometric machinery links specification to interface rendering. Third, functional friction is a consequence of specification investment rather than governance choice. Fourth, specification readiness is the critical moderator of AI returns, distinguishing Substrate-Operator execution (specification-constrained, coherent across interfaces) from Surface-Operator execution (locally fluent, globally inconsistent). Specification codification is architecturally prior to governance and capability deployment; the theory generates predictions distinct from transaction-cost economics, stakeholder theory, and existing AI-augmentation scholarship. Includes paper.yaml (Paper Spec v0.1.0) – a machine-readable specification of the paper's claims, assumptions, and dependencies. See https://github.com/spectralbranding/paper-spec for the standard.
Dmitry Zharnikov (Mon,) studied this question.
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