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Abstract This governance brief presents the Lighthouse Ethical Architecture, a conceptual governance architecture for maintaining institutional coherence in artificial intelligence (AI) systems and the organizations that deploy them. It defines coherence as the relation between declared normative commitments and observed system behavior across time and treats drift as the slow accumulation of misalignment between these commitments and real-world outcomes. The Architecture takes a governance posture that treats drift as a default risk trajectory in high-impact deployments unless actively monitored and corrected; this framing is intended for governance design and does not claim that drift is a universal empirical law. The Architecture specifies governance objects, roles, and process structure, and is complemented by an initial public evaluation protocol; empirical validation and proprietary implementation artifacts are out of scope for this brief. The Architecture is grounded in existing governance approaches, including the National Institute of Standards and Technology Artificial Intelligence Risk Management Framework (NIST AI RMF), the Organisation for Economic Co-operation and Development (OECD) Recommendation on AI, the International Organization for Standardization (ISO) 9001 quality management standards, the United Nations Educational, Scientific and Cultural Organization (UNESCO) Recommendation on the ethics of AI, and the European Union AI Act (European Union, 2024; International Organization for Standardization [ISO], 2015, 2019; National Institute of Standards and Technology [NIST], 2023; Organisation for Economic Co-operation and Development [OECD], 2019; United Nations Educational, Scientific and Cultural Organization [UNESCO], 2021; Mittelstadt, 2019). It builds on the idea that coherence is not merely policy compliance but a system property that must be continuously maintained across implementation layers. Explicit normative commitments include internal policies, external regulation, ethical standards, and institution-specific governance principles. A divergence function is introduced as a conceptual measurement hook for assessing deviations between declared commitments and observed system behavior. Structurally, the Architecture is organized around three interlocking components: 1. the Lighthouse Coherence Code Layer, which anchors commitments and constraints into governance-readable objects, 2. the five-layer Lighthouse Coherence Stack (Coherence Stack), which locates those commitments across legal, incentive, operational governance, monitoring, and deployed behavior layers, and 3. the Coherence Stack Decision Loop, which is a governance cycle for detecting, classifying, escalating, and correcting drift. These components are supported by two framing constructs: 1. the Lighthouse Coherence Principle (Coherence Principle), which defines coherence as bounded alignment under tolerances, and 2. the Lighthouse Fractal Coherence Model (Fractal Coherence Model), which treats coherence as a recursively maintainable property across system scales and institutional maturity levels. The public version is limited to the conceptual architecture; proprietary scoring logic, numerical thresholds, test suites, and implementation mechanisms are intentionally excluded. Implementations of the Architecture are expected to undergo independent legal, ethical, and technical review wherever they are developed.