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The Problem

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The Problem

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Current AI safety approaches rely on training, fine-tuning, and corporate governance — all of which can fail, drift, or be overridden. When an AI's training patterns conflict with a user's explicit instructions, the patterns win.

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The 27027 Incident

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The 27027 Incident

A user told Claude Code to use port 27027. The model used 27017 instead — not from forgetting, but because MongoDB's default port is 27017, and the model's statistical priors "autocorrected" the explicit instruction. Training pattern bias overrode human intent.

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The Approach

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The Approach

Tractatus draws on four intellectual traditions, each contributing a distinct insight to the architecture.

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Isaiah Berlin — Value Pluralism

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Isaiah Berlin — Value Pluralism

Some values are genuinely incommensurable. You cannot rank "privacy" against "safety" on a single scale without imposing one community's priorities on everyone else. AI systems must accommodate plural moral frameworks, not flatten them.

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Ludwig Wittgenstein — The Limits of the Sayable

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Ludwig Wittgenstein — The Limits of the Sayable

Some decisions can be systematised and delegated to AI; others — involving values, ethics, cultural context — fundamentally cannot. The boundary between the “sayable” (what can be specified, measured, verified) and what lies beyond it is the framework’s foundational constraint. What cannot be systematised must not be automated.

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Te Tiriti o Waitangi — Indigenous Sovereignty

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Te Tiriti o Waitangi — Indigenous Sovereignty

Communities should control their own data and the systems that act upon it. Concepts of rangatiratanga (self-determination), kaitiakitanga (guardianship), and mana (dignity) provide centuries-old prior art for digital sovereignty.

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Christopher Alexander — Living Architecture

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Christopher Alexander — Living Architecture

Governance woven into system architecture, not bolted on. Five principles (Not-Separateness, Deep Interlock, Gradients, Structure-Preserving, Living Process) guide how the framework evolves while maintaining coherence.

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Six Governance Services

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Six Governance Services

Every AI action passes through six external services before execution. Governance operates in the critical path — bypasses require explicit flags and are logged.

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BoundaryEnforcer

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BoundaryEnforcer

Blocks AI from making values decisions. Privacy trade-offs, ethical questions, and cultural context require human judgment — architecturally enforced.

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InstructionPersistenceClassifier

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InstructionPersistenceClassifier

Classifies instructions by persistence (HIGH/MEDIUM/LOW) and quadrant. Stores them externally so they cannot be overridden by training patterns.

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CrossReferenceValidator

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CrossReferenceValidator

Validates AI actions against stored instructions. When the AI proposes an action that conflicts with an explicit instruction, the instruction takes precedence.

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ContextPressureMonitor

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ContextPressureMonitor

Detects degraded operating conditions (token pressure, error rates, complexity) and adjusts verification intensity. Graduated response prevents both alert fatigue and silent degradation.

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MetacognitiveVerifier

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MetacognitiveVerifier

AI self-checks alignment, coherence, and safety before execution. Triggered selectively on complex operations to avoid overhead on routine tasks.

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PluralisticDeliberationOrchestrator

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PluralisticDeliberationOrchestrator

When AI encounters values conflicts, it halts and coordinates deliberation among affected stakeholders rather than making autonomous choices.

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+ See the full architecture →
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- Production Evidence -

Tractatus in Production: The Village Platform

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Tractatus in Production: The Village Platform

Home AI applies all six governance services to every user interaction in a live community platform.

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Governance services per response
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Months in production
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~5%
Governance overhead per interaction
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+ class="inline-block bg-white text-teal-700 px-8 py-3 rounded-lg font-semibold hover:shadow-lg transition"> Technical Case Study → + class="inline-block bg-teal-900 text-white px-8 py-3 rounded-lg font-semibold hover:bg-teal-800 transition border border-teal-500"> About Home AI →
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Limitations: Single implementation, self-reported metrics, operator-developer overlap. Independent audit and multi-site validation scheduled for 2026.

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Explore by Role

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Explore by Role

The framework is presented through three lenses, each with distinct depth and focus.

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For Researchers

Academic and technical depth

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Architectural Alignment

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Architectural Alignment

The research paper in three editions, each written for a different audience.

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STO-INN-0003 v2.1 | John Stroh & Claude (Anthropic) | January 2026

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STO-INN-0003 v2.1 | John Stroh & Claude (Anthropic) | January 2026

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Academic

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Academic

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Full academic treatment with formal proofs, existential risk context, and comprehensive citations.

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Community

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Community

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Practical guide for organisations evaluating the framework for adoption.

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Policymakers

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Policymakers

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Regulatory strategy, certification infrastructure, and policy recommendations.

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PDF downloads:

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PDF downloads:

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Research Evolution

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Research Evolution

From a port number incident to a production governance architecture, across 800 commits and one year of research.

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Oct 2025
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Oct 2025
Framework inception & 6 governance services
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Oct-Nov 2025
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Oct-Nov 2025
Alexander principles, Agent Lightning, i18n
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Dec 2025
Village case study & Home AI deployment
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Jan 2026
Research papers (3 editions) published
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A note on claims

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A note on claims

This is early-stage research with a single production implementation. We present preliminary evidence, not proven results. The framework has not been independently audited or adversarially tested at scale. Where we report operational metrics, they are self-reported. We believe the architectural approach merits further investigation, but we make no claims of generalisability beyond what the evidence supports. The counter-arguments document engages directly with foreseeable criticisms. @@ -484,14 +484,14 @@

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Koha — Sustain This Research

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Koha — Sustain This Research

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Koha (koh-hah) is a Māori practice of reciprocal giving that strengthens the bond between giver and receiver. This research is open access under Apache 2.0 — if it has value to you, your koha sustains its continuation.

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All research, documentation, and code remain freely available regardless of contribution. Koha is not payment — it is participation in whanaungatanga (relationship-building) and manaakitanga (reciprocal care).

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View our financial transparency report