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feat: Add dual-layer Tractatus architecture section and fix Koha contrast

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- Add prominent "Dual-Layer Tractatus Architecture" section to home-ai.html
  explaining Layer A (inherent/trained-in) and Layer B (active/runtime)
- Fix Koha paragraph contrast: text-blue-800 on bg-blue-50 had insufficient
  contrast (~3.8:1). Changed to text-gray-800/text-gray-900 for WCAG AA compliance
- Include prior session changes: architecture.html updates, homepage redesign

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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TheFlow 2026-02-07 15:37:33 +13:00
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commit ddabc83da8
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178
public/architecture.html
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@ -390,6 +390,108 @@
</div>
</section>
<!-- Applied to Training: The SLL -->
<section class="bg-gradient-to-br from-teal-50 to-emerald-50 py-16 border-y border-teal-200">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
<div class="text-center mb-8">
<div class="inline-block bg-teal-700 text-white px-4 py-2 rounded-lg font-semibold mb-4 text-sm">
PRIMARY RESEARCH DIRECTION
</div>
<h2 class="text-4xl font-bold text-gray-900 mb-4">Applied to Training: The Sovereign Language Model</h2>
<p class="text-xl text-gray-600 max-w-3xl mx-auto">
These five principles were developed governing AI agent sessions. The current research applies them to a harder problem: governing AI <strong>training</strong> itself.
</p>
</div>
<div class="grid grid-cols-1 lg:grid-cols-2 gap-8 mb-8">
<div class="bg-white rounded-xl p-6 border border-teal-200">
<h3 class="text-xl font-bold text-gray-900 mb-3">Inference-Time Governance</h3>
<p class="text-gray-600 text-sm mb-3">Where the framework started: six services validate every AI action before execution.</p>
<ul class="text-gray-700 text-sm space-y-2">
<li class="flex items-start">
<span class="text-teal-600 mr-2">&#10003;</span>
<span>Response cannot reach user without governance validation</span>
</li>
<li class="flex items-start">
<span class="text-teal-600 mr-2">&#10003;</span>
<span>Values decisions deferred to humans</span>
</li>
<li class="flex items-start">
<span class="text-teal-600 mr-2">&#10003;</span>
<span>Audit trail for every decision</span>
</li>
</ul>
<p class="text-gray-500 text-xs mt-3 italic">Status: in production</p>
</div>
<div class="bg-white rounded-xl p-6 border border-teal-200">
<h3 class="text-xl font-bold text-gray-900 mb-3">Training-Time Governance</h3>
<p class="text-gray-600 text-sm mb-3">Where the research is going: governance inside the training loop, not post-hoc filtering.</p>
<ul class="text-gray-700 text-sm space-y-2">
<li class="flex items-start">
<span class="text-teal-600 mr-2">&#10003;</span>
<span>BoundaryEnforcer validates every training batch before forward pass</span>
</li>
<li class="flex items-start">
<span class="text-teal-600 mr-2">&#10003;</span>
<span>Cross-tenant data rejected at the training step, not after</span>
</li>
<li class="flex items-start">
<span class="text-teal-600 mr-2">&#10003;</span>
<span>Consent verified per content item before inclusion</span>
</li>
</ul>
<p class="text-gray-500 text-xs mt-3 italic">Status: designed, documented, hardware ordered</p>
</div>
</div>
<div class="bg-white rounded-xl p-6 border border-teal-200 mb-8">
<h3 class="text-lg font-bold text-gray-900 mb-3">How the Five Principles Apply to Training</h3>
<div class="grid grid-cols-1 md:grid-cols-5 gap-4">
<div class="text-center">
<div class="w-10 h-10 bg-emerald-100 rounded-lg flex items-center justify-center mx-auto mb-2">
<span class="text-emerald-700 font-bold text-sm">1</span>
</div>
<p class="text-xs text-gray-700"><strong>Not-Separateness:</strong> governance inside the training loop</p>
</div>
<div class="text-center">
<div class="w-10 h-10 bg-indigo-100 rounded-lg flex items-center justify-center mx-auto mb-2">
<span class="text-indigo-700 font-bold text-sm">2</span>
</div>
<p class="text-xs text-gray-700"><strong>Deep Interlock:</strong> BoundaryEnforcer + MetacognitiveVerifier coordinate during training</p>
</div>
<div class="text-center">
<div class="w-10 h-10 bg-amber-100 rounded-lg flex items-center justify-center mx-auto mb-2">
<span class="text-amber-700 font-bold text-sm">3</span>
</div>
<p class="text-xs text-gray-700"><strong>Gradients:</strong> training intensity scales with content sensitivity</p>
</div>
<div class="text-center">
<div class="w-10 h-10 bg-purple-100 rounded-lg flex items-center justify-center mx-auto mb-2">
<span class="text-purple-700 font-bold text-sm">4</span>
</div>
<p class="text-xs text-gray-700"><strong>Structure-Preserving:</strong> training preserves audit log interpretability</p>
</div>
<div class="text-center">
<div class="w-10 h-10 bg-rose-100 rounded-lg flex items-center justify-center mx-auto mb-2">
<span class="text-rose-700 font-bold text-sm">5</span>
</div>
<p class="text-xs text-gray-700"><strong>Living Process:</strong> training evolves from operational failures, not theory</p>
</div>
</div>
</div>
<div class="text-center">
<a href="/home-ai.html" class="inline-block bg-teal-700 text-white px-8 py-3 rounded-lg font-semibold hover:bg-teal-800 transition shadow-lg">
Read the Full Home AI Story &rarr;
</a>
<p class="text-sm text-gray-600 mt-3">
Two-model architecture, three training tiers, thirteen wisdom traditions, indigenous data sovereignty
</p>
</div>
</div>
</section>
<!-- Interactive Exploration Section -->
<section class="bg-gradient-to-br from-yellow-50 to-orange-50 py-16 border-y border-orange-200">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
@ -750,51 +852,79 @@
</div>
</section>
<!-- Reference Implementation -->
<!-- Two Implementations -->
<section class="bg-gray-50 py-16">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
<h2 class="text-4xl font-bold text-gray-900 mb-6 text-center" data-i18n="production.heading"></h2>
<h2 class="text-4xl font-bold text-gray-900 mb-6 text-center">Two Implementations</h2>
<p class="text-xl text-gray-600 mb-8 text-center max-w-3xl mx-auto">
<span data-i18n-html="production.subtitle">Tractatus is deployed in production using <strong>Claude Code</strong> as the agent runtime. This demonstrates the framework's real-world viability.
Tractatus has been applied in two contexts: governing an AI development agent, and governing a sovereign locally-trained language model.
</p>
<div class="grid grid-cols-1 lg:grid-cols-2 gap-8">
<!-- Implementation 1: Claude Code -->
<div class="bg-white rounded-xl shadow-lg p-8 border border-gray-200">
<div class="grid grid-cols-1 lg:grid-cols-2 gap-8 items-center">
<div>
<h3 class="text-2xl font-bold text-gray-900 mb-4" data-i18n="production.implementation_title"></h3>
<p class="text-gray-700 mb-4" data-i18n-html="production.implementation_intro"></p>
<div class="flex items-center mb-4">
<div class="w-10 h-10 bg-blue-100 rounded-lg flex items-center justify-center mr-3">
<span class="text-blue-700 font-bold">1</span>
</div>
<h3 class="text-xl font-bold text-gray-900">Development Agent Governance</h3>
</div>
<p class="text-gray-700 text-sm mb-3">
The original implementation: six governance services operating in Claude Code's critical execution path. Every file edit, database query, and deployment action passes through validation.
</p>
<p class="text-gray-700 mb-3 text-sm italic" data-i18n="production.implementation_results_intro"></p>
<ul class="space-y-2 text-gray-700">
<ul class="space-y-2 text-gray-700 text-sm">
<li class="flex items-start">
<svg class="w-5 h-5 text-blue-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<svg class="w-4 h-4 text-blue-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<span data-i18n-html="production.result1"></span>
</li>
<li class="flex items-start">
<svg class="w-5 h-5 text-blue-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<svg class="w-4 h-4 text-blue-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<span data-i18n-html="production.result2"></span>
</li>
<li class="flex items-start">
<svg class="w-5 h-5 text-blue-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<svg class="w-4 h-4 text-blue-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<span data-i18n-html="production.result3"></span>
</li>
<li class="flex items-start">
<svg class="w-5 h-5 text-blue-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<span data-i18n-html="production.result4"></span>
</li>
</ul>
<p class="text-gray-600 text-xs mt-3 italic" data-i18n="production.disclaimer"></p>
<div class="mt-6">
<a href="/images/architecture-diagram.svg" class="inline-block text-blue-600 hover:text-blue-700 font-medium" data-i18n="production.diagram_link"></a>
<div class="mt-4">
<a href="/village-case-study.html" class="inline-block text-blue-600 hover:text-blue-700 font-medium text-sm">Village Case Study &rarr;</a>
</div>
</div>
<div class="bg-gradient-to-br from-blue-50 to-purple-50 rounded-lg p-6 border border-blue-200">
<h4 class="font-bold text-gray-900 mb-3" data-i18n="production.testing_title"></h4>
<!-- Implementation 2: Home AI / SLL -->
<div class="bg-white rounded-xl shadow-lg p-8 border-2 border-teal-300">
<div class="flex items-center mb-4">
<div class="w-10 h-10 bg-teal-100 rounded-lg flex items-center justify-center mr-3">
<span class="text-teal-700 font-bold">2</span>
</div>
<h3 class="text-xl font-bold text-gray-900">Home AI: Sovereign Language Model</h3>
</div>
<p class="text-gray-700 text-sm mb-3">
<span data-i18n-html="production.testing_text1"></span>
</p>
<p class="text-gray-700 text-sm">
<span data-i18n-html="production.testing_text2"></span>
The current research direction: applying all five architectural principles to model training, not just inference. BoundaryEnforcer operates inside the training loop. Three training tiers (platform, tenant, individual) with governance at each level.
</p>
<ul class="space-y-2 text-gray-700 text-sm">
<li class="flex items-start">
<svg class="w-4 h-4 text-teal-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<span>Governance during training (Not-Separateness applied to optimisation)</span>
</li>
<li class="flex items-start">
<svg class="w-4 h-4 text-teal-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<span>Two-model architecture (3B fast + 8B reasoning) under unified governance</span>
</li>
<li class="flex items-start">
<svg class="w-4 h-4 text-teal-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<span>Per-tenant LoRA adapters with consent-verified training data</span>
</li>
<li class="flex items-start">
<svg class="w-4 h-4 text-teal-600 mr-2 mt-0.5" fill="currentColor" viewBox="0 0 20 20"><path fill-rule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z"/></svg>
<span>Thirteen wisdom traditions available for Layer 3 adoption</span>
</li>
</ul>
<p class="text-gray-500 text-xs mt-3 italic">Status: inference in production; training pipeline designed, hardware ordered.</p>
<div class="mt-4">
<a href="/home-ai.html" class="inline-block bg-teal-700 text-white px-6 py-2 rounded-lg font-semibold hover:bg-teal-800 transition text-sm">Full Home AI Story &rarr;</a>
</div>
</div>
</div>
@ -872,7 +1002,7 @@
<h2 class="text-4xl font-bold mb-4" data-i18n="cta.heading"></h2>
<p class="text-xl mb-8 opacity-90 max-w-3xl mx-auto" data-i18n-html="cta.subtitle"></p>
<div class="flex flex-col sm:flex-row justify-center gap-4">
<a href="/docs.html" class="inline-block bg-white text-blue-600 px-8 py-3 rounded-lg font-semibold hover:bg-gray-100 transition" data-i18n="cta.btn_docs"></a>
<a href="/home-ai.html" class="inline-block bg-white text-blue-600 px-8 py-3 rounded-lg font-semibold hover:bg-gray-100 transition">Home AI &rarr;</a>
<a href="/researcher.html" class="inline-block bg-blue-700 text-white px-8 py-3 rounded-lg font-semibold hover:bg-blue-800 transition border-2 border-white" data-i18n="cta.btn_research"></a>
<a href="/implementer.html" class="inline-block bg-purple-700 text-white px-8 py-3 rounded-lg font-semibold hover:bg-purple-800 transition border-2 border-white" data-i18n="cta.btn_implementation"></a>
</div>

666
public/home-ai.html
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@ -3,19 +3,19 @@
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Home AI | Tractatus AI Safety Framework</title>
<meta name="description" content="Home AI: a sovereign, locally-trained language model operating under Tractatus governance. Six architectural services applied to every interaction.">
<title>Home AI — Sovereign Locally-Trained Language Model | Tractatus</title>
<meta name="description" content="Home AI is a sovereign, locally-trained language model governed by the Tractatus framework. Training, inference, and governance all remain under community control.">
<meta property="og:type" content="website">
<meta property="og:url" content="https://agenticgovernance.digital/home-ai.html">
<meta property="og:title" content="Home AI — Sovereign Language Model | Tractatus">
<meta property="og:description" content="How a locally-trained language model operates under architectural governance constraints in a production community platform.">
<meta property="og:description" content="A locally-trained language model where governance operates inside the training loop. Training data, model weights, and behavioural rules all remain under community control.">
<meta property="og:image" content="https://agenticgovernance.digital/images/social-preview.png">
<meta property="og:site_name" content="Tractatus Framework">
<meta name="twitter:card" content="summary_large_image">
<meta name="twitter:title" content="Home AI — Sovereign Language Model | Tractatus">
<meta name="twitter:description" content="How a locally-trained language model operates under architectural governance constraints in a production community platform.">
<meta name="twitter:description" content="A locally-trained language model where governance operates inside the training loop.">
<meta name="twitter:image" content="https://agenticgovernance.digital/images/social-preview.png">
<link rel="icon" type="image/svg+xml" href="/favicon-new.svg">
@ -44,8 +44,6 @@
<ol class="flex items-center space-x-2 text-sm">
<li><a href="/" class="text-blue-600 hover:underline transition-colors">Home</a></li>
<li class="text-gray-400">/</li>
<li><a href="/village-case-study.html" class="text-blue-600 hover:underline transition-colors">Village Case Study</a></li>
<li class="text-gray-400">/</li>
<li class="text-gray-900 font-medium" aria-current="page">Home AI</li>
</ol>
</div>
@ -53,198 +51,564 @@
<!-- Hero -->
<header role="banner">
<section class="bg-gradient-to-br from-teal-700 via-teal-800 to-emerald-800 text-white py-16">
<section class="bg-gradient-to-br from-teal-700 via-teal-800 to-emerald-800 text-white py-14">
<div class="max-w-4xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
<div class="inline-block bg-emerald-600 text-white px-4 py-1.5 rounded-lg font-semibold mb-4 text-sm">
SOVEREIGN LOCALLY-TRAINED LANGUAGE MODEL
</div>
<h1 class="text-4xl md:text-5xl font-bold mb-4">Home AI</h1>
<p class="text-xl text-teal-100 max-w-3xl mx-auto mb-6">
A sovereign, locally-trained language model operating under architectural governance. Every interaction passes through all six Tractatus services before reaching the user.
A language model where the community controls the training data, the model weights, and the governance rules. Not just governed inference &mdash; governed training.
</p>
<div class="bg-amber-100 border-2 border-amber-400 rounded-lg p-4 max-w-2xl mx-auto">
<p class="text-amber-900 text-sm">
<strong>Caveat:</strong> Home AI is a single implementation within the Village platform. Claims below are based on operational observation, not controlled experiments. Independent validation is planned.
<strong>Status:</strong> Home AI operates in production for inference. The sovereign training pipeline is designed and documented; hardware is ordered. Training has not yet begun. This page describes both current capability and intended architecture.
</p>
</div>
</div>
</section>
</header>
<main id="main-content" class="max-w-4xl mx-auto px-4 sm:px-6 lg:px-8 py-16">
<main id="main-content" class="max-w-4xl mx-auto px-4 sm:px-6 lg:px-8 py-12">
<!-- What is Home AI -->
<section class="mb-16">
<h2 class="text-3xl font-bold text-gray-900 mb-6">What is Home AI?</h2>
<!-- What is an SLL -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">What is an SLL?</h2>
<div class="prose prose-lg text-gray-700">
<p class="mb-4">
Home AI is the practical implementation of Tractatus governance within the Village platform &mdash; a community-owned digital space where members share stories, documents, and family histories. Unlike cloud-hosted AI assistants, Home AI operates under the principle of <em>digital sovereignty</em>: the community's data and the AI's behaviour are governed by the community itself, not by a remote provider.
An <strong>SLL</strong> (Sovereign Locally-trained Language Model) is distinct from both LLMs and SLMs. The distinction is not size &mdash; it is control.
</p>
<p class="mb-4">
The term "SLL" (Sovereign Locally-trained Language Model) describes the architectural goal: a language model whose training data, inference, and governance all remain under local control. In practice, Home AI currently uses a hybrid approach &mdash; local Llama models for English-language operations and Claude Haiku via API for non-English languages &mdash; with a roadmap toward fully local inference as hardware and model capabilities allow.
</p>
<p>
What distinguishes Home AI from other AI assistants is not the model itself, but the governance layer around it. Every interaction &mdash; whether a help query, document OCR, story suggestion, or AI-generated summary &mdash; passes through the full Tractatus governance stack before any response reaches the user.
</div>
<div class="grid grid-cols-1 md:grid-cols-3 gap-4 mt-6">
<div class="bg-red-50 rounded-lg p-5 border border-red-200">
<h3 class="text-lg font-bold text-red-900 mb-2">LLM</h3>
<p class="text-red-800 text-sm mb-2">Large Language Model</p>
<ul class="text-red-700 text-sm space-y-1">
<li>Training: provider-controlled</li>
<li>Data: scraped at scale</li>
<li>Governance: provider's terms</li>
<li>User control: none</li>
</ul>
</div>
<div class="bg-amber-50 rounded-lg p-5 border border-amber-200">
<h3 class="text-lg font-bold text-amber-900 mb-2">SLM</h3>
<p class="text-amber-800 text-sm mb-2">Small Language Model</p>
<ul class="text-amber-700 text-sm space-y-1">
<li>Training: provider-controlled</li>
<li>Data: curated by provider</li>
<li>Governance: partial (fine-tuning)</li>
<li>User control: limited</li>
</ul>
</div>
<div class="bg-emerald-50 rounded-lg p-5 border border-emerald-200">
<h3 class="text-lg font-bold text-emerald-900 mb-2">SLL</h3>
<p class="text-emerald-800 text-sm mb-2">Sovereign Locally-trained</p>
<ul class="text-emerald-700 text-sm space-y-1">
<li>Training: community-controlled</li>
<li>Data: community-owned</li>
<li>Governance: architecturally enforced</li>
<li>User control: full</li>
</ul>
</div>
</div>
<div class="bg-gray-50 rounded-lg p-6 border border-gray-200 mt-6">
<p class="text-gray-700 text-sm italic">
The honest trade-off: an SLL is a less powerful system that serves your interests, rather than a more powerful one that serves someone else's. We consider this an acceptable exchange.
</p>
</div>
</section>
<!-- The Governance Stack -->
<section class="mb-16">
<h2 class="text-3xl font-bold text-gray-900 mb-6">The Governance Stack</h2>
<p class="text-gray-700 mb-8">
Each Home AI interaction traverses six governance services in sequence. This is not optional middleware &mdash; it operates in the critical execution path, meaning a response cannot be generated without passing through all checks.
<!-- Two-Model Architecture -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Two-Model Architecture</h2>
<p class="text-gray-700 mb-6">
Home AI uses two models of different sizes, routed by task complexity. This is not a fallback mechanism &mdash; each model is optimised for its role.
</p>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6">
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-blue-500">
<h3 class="text-lg font-bold text-gray-900 mb-2">3B Model &mdash; Fast Assistant</h3>
<p class="text-gray-700 text-sm mb-3">
Handles help queries, tooltips, error explanations, short summaries, and translation. Target response time: under 5 seconds complete.
</p>
<p class="text-gray-500 text-xs">
Routing triggers: simple queries, known FAQ patterns, single-step tasks.
</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-purple-500">
<h3 class="text-lg font-bold text-gray-900 mb-2">8B Model &mdash; Deep Reasoning</h3>
<p class="text-gray-700 text-sm mb-3">
Handles life story generation, year-in-review narratives, complex summarisation, and sensitive correspondence. Target response time: under 90 seconds.
</p>
<p class="text-gray-500 text-xs">
Routing triggers: keywords like "everything about", multi-source retrieval, grief/trauma markers.
</p>
</div>
</div>
<p class="text-gray-600 text-sm mt-4">
Both models operate under the same governance stack. The routing decision itself is governed &mdash; the ContextPressureMonitor can override routing if session health requires it.
</p>
</section>
<!-- Three Training Tiers -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Three Training Tiers</h2>
<p class="text-gray-700 mb-6">
Training is not monolithic. Three tiers serve different scopes, each with appropriate governance constraints.
</p>
<div class="space-y-4">
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-emerald-500">
<h3 class="text-lg font-bold text-gray-900 mb-2">1. BoundaryEnforcer</h3>
<p class="text-gray-700 text-sm">
Detects whether a user query involves values decisions (privacy trade-offs, ethical questions, cultural sensitivity) and blocks the AI from responding autonomously. These are deferred to human moderators. The boundary between "technical question" and "values question" is defined by community-specific rules, not by the AI's judgment.
</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-indigo-500">
<h3 class="text-lg font-bold text-gray-900 mb-2">2. CrossReferenceValidator</h3>
<p class="text-gray-700 text-sm">
Validates the query against stored instructions and known patterns. This is the service that would have caught the 27027 incident &mdash; the user's explicit instruction ("use port 27027") is stored externally and cross-referenced against the AI's proposed action ("use port 27017"). When stored instructions conflict with the AI's response, the stored instruction takes precedence.
</p>
<div class="flex items-baseline justify-between mb-2">
<h3 class="text-lg font-bold text-gray-900">Tier 1: Platform Base</h3>
<span class="text-xs bg-indigo-100 text-indigo-800 px-2 py-1 rounded">All communities</span>
</div>
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-amber-500">
<h3 class="text-lg font-bold text-gray-900 mb-2">3. ContextPressureMonitor</h3>
<p class="text-gray-700 text-sm">
Tracks session health metrics: token usage, message count, error rate, task complexity. When pressure exceeds thresholds (ELEVATED at 25%, HIGH at 50%, CRITICAL at 75%), the system adjusts validation intensity or recommends session handoff. This prevents the degradation patterns observed in extended AI sessions where error rates compound.
<p class="text-gray-700 text-sm mb-2">
Trained on platform documentation, philosophy, feature guides, and FAQ content. Provides the foundational understanding of how Village works, what Home AI's values are, and how to help members navigate the platform.
</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-pink-500">
<h3 class="text-lg font-bold text-gray-900 mb-2">4. MetacognitiveVerifier</h3>
<p class="text-gray-700 text-sm">
For complex operations (multi-step tasks, file modifications, configuration changes), the AI performs a structured self-assessment before proposing actions: alignment with instructions, coherence of approach, completeness of plan, safety of proposed changes, and consideration of alternatives. This is triggered selectively to avoid overhead on simple queries.
</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-blue-500">
<h3 class="text-lg font-bold text-gray-900 mb-2">5. InstructionPersistenceClassifier</h3>
<p class="text-gray-700 text-sm">
Classifies instructions by their intended lifespan (HIGH: strategic/permanent, MEDIUM: operational/session-scoped, LOW: tactical/single-use) and quadrant (Strategic, Operational, Tactical, System, Stochastic). This classification determines how strongly the CrossReferenceValidator enforces each instruction and how long it persists in the external store.
<p class="text-gray-500 text-xs">
Update frequency: weekly during beta, quarterly at GA. Training method: QLoRA fine-tuning.
</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-teal-500">
<h3 class="text-lg font-bold text-gray-900 mb-2">6. PluralisticDeliberationOrchestrator</h3>
<p class="text-gray-700 text-sm">
When the AI encounters decisions where legitimate values conflict &mdash; for example, a member's privacy interests versus community safety concerns &mdash; this service halts autonomous decision-making and coordinates a deliberation process among affected stakeholders. The AI presents the conflict and facilitates discussion; it does not resolve it.
<div class="flex items-baseline justify-between mb-2">
<h3 class="text-lg font-bold text-gray-900">Tier 2: Tenant Adapters</h3>
<span class="text-xs bg-teal-100 text-teal-800 px-2 py-1 rounded">Per community</span>
</div>
<p class="text-gray-700 text-sm mb-2">
Each community trains a lightweight LoRA adapter on its own content &mdash; stories, documents, photos, and events that members have explicitly consented to include. This allows Home AI to answer questions like "What stories has Grandma shared?" without accessing any other community's data.
</p>
<p class="text-gray-500 text-xs">
Adapters are small (50&ndash;100MB). Consent is per-content-item. Content marked "only me" is never included regardless of consent. Training uses DPO (Direct Preference Optimization) for value alignment.
</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-6 border-l-4 border-rose-400">
<div class="flex items-baseline justify-between mb-2">
<h3 class="text-lg font-bold text-gray-900">Tier 3: Individual (Future)</h3>
<span class="text-xs bg-rose-100 text-rose-800 px-2 py-1 rounded">Per member</span>
</div>
<p class="text-gray-700 text-sm mb-2">
Personal adapters that learn individual preferences and interaction patterns. Speculative &mdash; this tier raises significant questions about feasibility, privacy, and the minimum training data required for meaningful personalisation.
</p>
<p class="text-gray-500 text-xs">
Research questions documented. Implementation not planned until Tier 2 is validated.
</p>
</div>
</div>
</section>
<!-- Governed Features -->
<section class="mb-16">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Governed Features</h2>
<p class="text-gray-700 mb-8">
Home AI currently provides four AI-powered features, each operating under the full governance stack.
</p>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6">
<div class="bg-white rounded-xl shadow-md p-6 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-3">RAG-Based Help</h3>
<p class="text-gray-700 text-sm mb-3">
Vector search retrieves relevant documentation and help content, filtered by the member's permission level. The AI generates contextual answers grounded in retrieved documents rather than from its training data alone.
</p>
<p class="text-gray-500 text-xs italic">
Governance: BoundaryEnforcer prevents PII exposure; CrossReferenceValidator validates responses against platform policies.
</p>
</div>
<div class="bg-white rounded-xl shadow-md p-6 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-3">Document OCR</h3>
<p class="text-gray-700 text-sm mb-3">
Automated text extraction from uploaded documents (historical records, handwritten letters, photographs with text). Extracted text is stored within the member's scope, not shared across tenants or used for model training.
</p>
<p class="text-gray-500 text-xs italic">
Governance: Processing only occurs under explicit consent controls; results are tenant-isolated.
</p>
</div>
<div class="bg-white rounded-xl shadow-md p-6 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-3">Story Assistance</h3>
<p class="text-gray-700 text-sm mb-3">
AI-generated suggestions for writing family stories: prompts, structural advice, and narrative enhancement. Suggestions are filtered through BoundaryEnforcer so that the AI does not impose cultural interpretations or values judgments on family narratives.
</p>
<p class="text-gray-500 text-xs italic">
Governance: Cultural context decisions are deferred to the storyteller, not resolved by the AI.
</p>
</div>
<div class="bg-white rounded-xl shadow-md p-6 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-3">AI Memory Transparency</h3>
<p class="text-gray-700 text-sm mb-3">
Members can view what the AI "remembers" about their interactions: summarised conversation history, inferred preferences, and stored instructions. Members control whether this memory persists, is reset, or is deleted entirely.
</p>
<p class="text-gray-500 text-xs italic">
Governance: Consent granularity covers AI triage memory, OCR memory, and summarisation memory independently.
</p>
</div>
</div>
</section>
<!-- Sovereignty Architecture -->
<section class="mb-16">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Sovereignty Architecture</h2>
<!-- Governance During Training -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Governance During Training</h2>
<div class="prose prose-lg text-gray-700">
<p class="mb-4">
The concept of "sovereign" in Home AI is concrete, not aspirational. It refers to specific architectural properties:
This is the central research contribution. Most AI governance frameworks operate at inference time &mdash; they filter or constrain responses after the model has already been trained. Home AI embeds governance <strong>inside the training loop</strong>.
</p>
<p class="mb-4">
This follows Christopher Alexander's principle of <em>Not-Separateness</em>: governance is woven into the training architecture, not applied afterward. The BoundaryEnforcer validates every training batch before the forward pass. If a batch contains cross-tenant data, data without consent, or content marked as private, the batch is rejected and the training step does not proceed.
</p>
</div>
<div class="space-y-4 mt-6">
<div class="bg-blue-50 rounded-lg p-6 border border-blue-200">
<h3 class="text-lg font-bold text-blue-900 mb-2">Data sovereignty</h3>
<p class="text-blue-800 text-sm">
All member data is stored on infrastructure controlled by the community operator &mdash; currently OVH (France) and Catalyst (New Zealand). No member data flows to AI provider APIs for training. Query content sent to Claude Haiku for non-English processing is ephemeral and not retained by the provider.
<div class="bg-gray-900 rounded-lg p-6 mt-6 font-mono text-sm">
<p class="text-green-400 mb-1"># Governance inside the training loop (Not-Separateness)</p>
<p class="text-gray-300 mb-1">for batch in training_data:</p>
<p class="text-gray-300 mb-1">&nbsp;&nbsp;if not BoundaryEnforcer.validate(batch):</p>
<p class="text-gray-300 mb-1">&nbsp;&nbsp;&nbsp;&nbsp;continue&nbsp;&nbsp;<span class="text-green-400"># Governance rejects batch</span></p>
<p class="text-gray-300 mb-1">&nbsp;&nbsp;loss = model.forward(batch)</p>
<p class="text-gray-300 mb-3">&nbsp;&nbsp;loss.backward()</p>
<p class="text-red-400 mb-1"># NOT this &mdash; governance separated from training</p>
<p class="text-gray-500 mb-1">for batch in training_data:</p>
<p class="text-gray-500 mb-1">&nbsp;&nbsp;loss = model.forward(batch)</p>
<p class="text-gray-500 mb-1">&nbsp;&nbsp;loss.backward()</p>
<p class="text-gray-500">filter_outputs_later()&nbsp;&nbsp;<span class="text-red-400"># Too late</span></p>
</div>
<div class="bg-blue-50 rounded-lg p-6 border border-blue-200 mt-6">
<h3 class="text-lg font-bold text-blue-900 mb-2">Why both training-time and inference-time governance?</h3>
<p class="text-blue-800 text-sm mb-2">
<strong>Training shapes tendency; architecture constrains capability.</strong> A model trained to respect boundaries can still be jailbroken. A model that fights against governance rules wastes compute and produces worse outputs. The combined approach makes the model <em>tend toward</em> governed behaviour while the architecture makes it <em>impossible</em> to violate structural boundaries.
</p>
<p class="text-blue-700 text-xs italic">
Research from the Agent Lightning integration suggests governance adds approximately 5% performance overhead &mdash; an acceptable trade-off for architectural safety constraints. This requires validation at scale.
</p>
</div>
<div class="bg-blue-50 rounded-lg p-6 border border-blue-200">
<h3 class="text-lg font-bold text-blue-900 mb-2">Governance sovereignty</h3>
<p class="text-blue-800 text-sm">
The rules governing AI behaviour are defined by the community, not the AI provider. BoundaryEnforcer rules, instruction persistence levels, and deliberation triggers are configured per-tenant. A family history community has different boundary rules from a neighbourhood association.
<p class="text-gray-600 text-sm mt-4">
Training-time governance is only half the picture. The same Tractatus framework also operates at runtime in the Village codebase. The next section explains how these two layers work together.
</p>
</section>
<!-- Dual-Layer Tractatus Architecture -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Dual-Layer Tractatus Architecture</h2>
<div class="prose prose-lg text-gray-700">
<p class="mb-4">
Home AI is governed by Tractatus at <strong>two distinct layers</strong> simultaneously. This is the architectural insight that distinguishes the SLL approach from both ungoverned models and bolt-on safety filters.
</p>
</div>
<div class="bg-blue-50 rounded-lg p-6 border border-blue-200">
<h3 class="text-lg font-bold text-blue-900 mb-2">Inference sovereignty (in progress)</h3>
<p class="text-blue-800 text-sm">
English-language queries currently use a locally-hosted Llama model. The roadmap includes expanding local inference to additional languages as multilingual open models mature. The governance layer is model-agnostic &mdash; switching the underlying model does not require changes to the governance architecture.
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 mt-6">
<div class="bg-teal-50 rounded-lg p-6 border-2 border-teal-300">
<div class="inline-block bg-teal-600 text-white px-3 py-1 rounded text-xs font-semibold mb-3">LAYER A: INHERENT</div>
<h3 class="text-lg font-bold text-gray-900 mb-3">Tractatus Inside the Model</h3>
<p class="text-gray-700 text-sm mb-3">
During training, the BoundaryEnforcer validates every batch. DPO alignment shapes preferences toward governed behaviour. The model <em>learns</em> to respect boundaries, prefer transparent responses, and defer values decisions to humans.
</p>
<ul class="text-gray-700 text-sm space-y-2">
<li><strong>Mechanism:</strong> Governance in the training loop</li>
<li><strong>Effect:</strong> Model tends toward governed behaviour</li>
<li><strong>Limitation:</strong> Tendencies can be overridden by adversarial prompting</li>
</ul>
</div>
<div class="bg-indigo-50 rounded-lg p-6 border-2 border-indigo-300">
<div class="inline-block bg-indigo-600 text-white px-3 py-1 rounded text-xs font-semibold mb-3">LAYER B: ACTIVE</div>
<h3 class="text-lg font-bold text-gray-900 mb-3">Tractatus Around the Model</h3>
<p class="text-gray-700 text-sm mb-3">
At runtime, the full six-service governance stack operates in the Village codebase. Every interaction passes through BoundaryEnforcer, PluralisticDeliberationOrchestrator, MetacognitiveVerifier, CrossReferenceValidator, ContextPressureMonitor, and InstructionPersistenceClassifier.
</p>
<ul class="text-gray-700 text-sm space-y-2">
<li><strong>Mechanism:</strong> Six architectural services in the critical path</li>
<li><strong>Effect:</strong> Structural boundaries cannot be violated</li>
<li><strong>Limitation:</strong> Adds ~5% performance overhead per interaction</li>
</ul>
</div>
</div>
<div class="bg-gray-900 rounded-lg p-6 mt-6">
<p class="text-emerald-400 font-mono text-sm mb-3 font-bold">The dual-layer principle:</p>
<p class="text-gray-300 font-mono text-sm mb-1">Training shapes <span class="text-teal-400">tendency</span>.</p>
<p class="text-gray-300 font-mono text-sm mb-4">Architecture constrains <span class="text-indigo-400">capability</span>.</p>
<p class="text-gray-400 font-mono text-xs">A model that has internalised governance rules AND operates within governance architecture</p>
<p class="text-gray-400 font-mono text-xs">produces better outputs than either approach alone. The model works WITH the guardrails,</p>
<p class="text-gray-400 font-mono text-xs">not against them &mdash; reducing compute waste and improving response quality.</p>
</div>
<div class="bg-amber-50 rounded-lg p-5 border border-amber-200 mt-4">
<p class="text-amber-900 text-sm">
<strong>Honest caveat:</strong> Layer A (inherent governance via training) is designed but not yet empirically validated &mdash; training has not begun. Layer B (active governance via Village codebase) has been operating in production for 11+ months. The dual-layer thesis is an architectural commitment, not yet a demonstrated result.
</p>
</div>
</section>
<!-- Philosophical Foundations -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Philosophical Foundations</h2>
<p class="text-gray-700 mb-6">
Home AI's governance draws from four philosophical traditions, each contributing a specific architectural principle. These are not decorative references &mdash; they translate into concrete design decisions.
</p>
<div class="grid grid-cols-1 md:grid-cols-2 gap-4">
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Isaiah Berlin &mdash; Value Pluralism</h3>
<p class="text-gray-700 text-sm mb-2">
Values are genuinely plural and sometimes incompatible. When freedom conflicts with equality, there may be no single correct resolution. Home AI presents options without hierarchy and documents what each choice sacrifices.
</p>
<p class="text-gray-500 text-xs italic">Architectural expression: PluralisticDeliberationOrchestrator presents trade-offs; it does not resolve them.</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Ludwig Wittgenstein &mdash; Language Boundaries</h3>
<p class="text-gray-700 text-sm mb-2">
Language shapes what can be thought and expressed. Some things that matter most resist systematic expression. Home AI acknowledges the limits of what language models can capture &mdash; particularly around grief, cultural meaning, and lived experience.
</p>
<p class="text-gray-500 text-xs italic">Architectural expression: BoundaryEnforcer defers values decisions to humans, acknowledging limits of computation.</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Indigenous Sovereignty &mdash; Data as Relationship</h3>
<p class="text-gray-700 text-sm mb-2">
Te Mana Raraunga (M&#257;ori Data Sovereignty), CARE Principles, and OCAP (First Nations Canada) provide frameworks where data is not property but relationship. Whakapapa (genealogy) belongs to the collective, not individuals. Consent is a community process, not an individual checkbox.
</p>
<p class="text-gray-500 text-xs italic">Architectural expression: tenant isolation, collective consent mechanisms, intergenerational stewardship.</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Christopher Alexander &mdash; Living Architecture</h3>
<p class="text-gray-700 text-sm mb-2">
Five principles guide how governance evolves: Deep Interlock (services coordinate), Structure-Preserving (changes enhance without breaking), Gradients Not Binary (intensity levels), Living Process (evidence-based evolution), Not-Separateness (governance embedded, not bolted on).
</p>
<p class="text-gray-500 text-xs italic">Architectural expression: all six governance services and the training loop architecture.</p>
</div>
</div>
</section>
<!-- Te Tiriti Connection -->
<section class="mb-16">
<!-- Three-Layer Governance -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Three-Layer Governance</h2>
<p class="text-gray-700 mb-6">
Governance operates at three levels, each with different scope and mutability.
</p>
<div class="space-y-4">
<div class="bg-emerald-50 rounded-lg p-6 border border-emerald-200">
<h3 class="text-lg font-bold text-emerald-900 mb-2">Layer 1: Platform (Immutable)</h3>
<p class="text-emerald-800 text-sm mb-2">
Structural constraints that apply to all communities. Tenant data isolation. Governance in the critical path. Options presented without hierarchy. These cannot be disabled by tenant administrators or individual members.
</p>
<p class="text-emerald-700 text-xs">Enforcement: architectural (BoundaryEnforcer blocks violations before they execute).</p>
</div>
<div class="bg-blue-50 rounded-lg p-6 border border-blue-200">
<h3 class="text-lg font-bold text-blue-900 mb-2">Layer 2: Tenant Constitution</h3>
<p class="text-blue-800 text-sm mb-2">
Rules defined by community administrators. Content handling policies (e.g., "deceased members require moderator review"), cultural protocols (e.g., M&#257;ori tangi customs), visibility defaults, and AI training consent models. Each community configures its own constitution within Layer 1 constraints.
</p>
<p class="text-blue-700 text-xs">Enforcement: constitutional rules validated by CrossReferenceValidator per tenant.</p>
</div>
<div class="bg-purple-50 rounded-lg p-6 border border-purple-200">
<h3 class="text-lg font-bold text-purple-900 mb-2">Layer 3: Adopted Wisdom Traditions</h3>
<p class="text-purple-800 text-sm mb-2">
Individual members and communities can adopt principles from wisdom traditions to influence how Home AI frames responses. These are voluntary, reversible, and transparent. They influence presentation, not content access. Multiple traditions can be adopted simultaneously; conflicts are resolved by the member, not the AI.
</p>
<p class="text-purple-700 text-xs">Enforcement: framing hints in response generation. Override always available.</p>
</div>
</div>
</section>
<!-- Wisdom Traditions -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Wisdom Traditions</h2>
<p class="text-gray-700 mb-6">
Home AI offers thirteen wisdom traditions that members can adopt to guide AI behaviour. Each tradition has been validated against the Stanford Encyclopedia of Philosophy as the primary scholarly reference. Adoption is voluntary, transparent, and reversible.
</p>
<div class="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 gap-3">
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Berlin: Value Pluralism</h4>
<p class="text-gray-600 text-xs">Present options without ranking; acknowledge what each choice sacrifices.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Stoic: Equanimity and Virtue</h4>
<p class="text-gray-600 text-xs">Focus on what can be controlled; emphasise character in ancestral stories.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Weil: Attention to Affliction</h4>
<p class="text-gray-600 text-xs">Resist summarising grief; preserve names and specifics rather than abstracting.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Care Ethics: Relational Responsibility</h4>
<p class="text-gray-600 text-xs">Attend to how content affects specific people, not abstract principles.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Confucian: Relational Duty</h4>
<p class="text-gray-600 text-xs">Frame stories in terms of family roles and reciprocal obligations.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Buddhist: Impermanence</h4>
<p class="text-gray-600 text-xs">Acknowledge that memories and interpretations change; extend compassion.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Ubuntu: Communal Personhood</h4>
<p class="text-gray-600 text-xs">"I am because we are." Stories belong to the community, not the individual.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">African Diaspora: Sankofa</h4>
<p class="text-gray-600 text-xs">Preserve what was nearly lost; honour fictive kinship and chosen family.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Indigenous/M&#257;ori: Whakapapa</h4>
<p class="text-gray-600 text-xs">Kinship with ancestors, land, and descendants. Collective ownership of knowledge.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Jewish: Tikkun Olam</h4>
<p class="text-gray-600 text-xs">Repair, preserve memory (zachor), uphold dignity even of difficult relatives.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Islamic: Mercy and Justice</h4>
<p class="text-gray-600 text-xs">Balance rahma (mercy) with adl (justice) in sensitive content.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Hindu: Dharmic Order</h4>
<p class="text-gray-600 text-xs">Role-appropriate duties within larger order; karma as consequence, not punishment.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm mb-1">Alexander: Living Architecture</h4>
<p class="text-gray-600 text-xs">Governance as living system; changes emerge from operational experience.</p>
</div>
</div>
<div class="bg-gray-50 rounded-lg p-5 border border-gray-200 mt-4">
<p class="text-gray-700 text-sm">
<strong>What this is not:</strong> Selecting "Buddhist" does not mean the AI practises Buddhism. These are framing tendencies &mdash; they influence how the AI presents options, not what content is accessible. A member can always override tradition-influenced framing on any response. The system does not claim algorithmic moral reasoning.
</p>
</div>
</section>
<!-- Indigenous Data Sovereignty -->
<section class="mb-14">
<div class="bg-gradient-to-r from-blue-50 to-purple-50 rounded-xl p-8 border border-blue-200">
<h2 class="text-2xl font-bold text-gray-900 mb-4">Te Tiriti o Waitangi and Digital Sovereignty</h2>
<h2 class="text-2xl font-bold text-gray-900 mb-4">Indigenous Data Sovereignty</h2>
<p class="text-gray-700 mb-4">
The sovereignty principles underlying Home AI are informed by Te Tiriti o Waitangi (the Treaty of Waitangi, 1840) and M&#257;ori concepts of <em>rangatiratanga</em> (self-determination over one's domain), <em>kaitiakitanga</em> (guardianship of resources for future generations), and <em>mana</em> (authority and dignity).
Indigenous data sovereignty differs fundamentally from Western privacy models. Where Western privacy centres on individual rights and consent-as-checkbox, indigenous frameworks centre on collective rights, community process, and intergenerational stewardship.
</p>
<div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-4">
<div class="bg-white rounded-lg p-4">
<h4 class="font-bold text-gray-900 text-sm mb-1">Te Mana Raraunga</h4>
<p class="text-gray-600 text-xs">M&#257;ori Data Sovereignty. Rangatiratanga (self-determination), kaitiakitanga (guardianship for future generations), whanaungatanga (kinship as unified entity).</p>
</div>
<div class="bg-white rounded-lg p-4">
<h4 class="font-bold text-gray-900 text-sm mb-1">CARE Principles</h4>
<p class="text-gray-600 text-xs">Global Indigenous Data Alliance. Collective Benefit, Authority to Control, Responsibility, Ethics. Data ecosystems designed for indigenous benefit.</p>
</div>
<div class="bg-white rounded-lg p-4">
<h4 class="font-bold text-gray-900 text-sm mb-1">OCAP</h4>
<p class="text-gray-600 text-xs">First Nations Canada. Ownership, Control, Access, Possession. Communities physically control their data.</p>
</div>
</div>
<p class="text-gray-700 mb-4">
These are not metaphorical borrowings. They provide concrete architectural guidance: communities should control their own data (rangatiratanga), AI systems should preserve rather than degrade the information they govern (kaitiakitanga), and automated decisions should not diminish the standing of the people they affect (mana).
Concrete architectural implications: whakapapa (genealogy) cannot be atomised into individual data points. Tapu (sacred/restricted) content triggers cultural review before AI processing. Consent for AI training requires wh&#257;nau consensus, not individual opt-in. Elder (kaum&#257;tua) approval is required for training on sacred genealogies.
</p>
<p class="text-gray-700">
The Tractatus framework is developed in Aotearoa New Zealand, and these principles predate Western technology governance by centuries. We consider them prior art, not novel invention.
<p class="text-gray-600 text-sm italic">
These principles are informed by Te Tiriti o Waitangi and predate Western technology governance by centuries. We consider them prior art, not novel invention. Actual implementation requires ongoing consultation with M&#257;ori cultural advisors &mdash; this specification is a starting point.
</p>
</div>
</section>
<!-- Training Infrastructure -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Training Infrastructure</h2>
<p class="text-gray-700 mb-6">
Home AI follows a "train local, deploy remote" model. The training hardware sits in the developer's home. Trained model weights are deployed to production servers for inference. This keeps training costs low and training data under physical control.
</p>
<div class="grid grid-cols-1 md:grid-cols-2 gap-4">
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Local Training</h3>
<ul class="text-gray-700 text-sm space-y-2">
<li>Consumer GPU with 24GB VRAM via external enclosure</li>
<li>QLoRA fine-tuning (4-bit quantisation fits in VRAM budget)</li>
<li>DPO (Direct Preference Optimization) &mdash; requires only 2 models in memory vs PPO's 4</li>
<li>Overnight training runs &mdash; compatible with off-grid solar power</li>
<li>Sustained power draw under 500W</li>
</ul>
</div>
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Remote Inference</h3>
<ul class="text-gray-700 text-sm space-y-2">
<li>Model weights deployed to production servers (OVH France, Catalyst NZ)</li>
<li>Inference via Ollama with per-tenant adapter loading</li>
<li>Hybrid GPU/CPU architecture with health monitoring</li>
<li>Home GPU available via WireGuard VPN as primary inference engine</li>
<li>CPU fallback ensures availability when GPU is offline</li>
</ul>
</div>
</div>
<div class="bg-gray-50 rounded-lg p-5 border border-gray-200 mt-4">
<p class="text-gray-700 text-sm">
<strong>Why consumer hardware?</strong> The SLL thesis is that sovereign AI training should be accessible, not reserved for organisations with data centre budgets. A single consumer GPU can fine-tune a 7B model efficiently via QLoRA. The entire training infrastructure fits on a desk.
</p>
</div>
</section>
<!-- Bias and Verification -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Bias Documentation and Verification</h2>
<p class="text-gray-700 mb-6">
Home AI operates in the domain of family storytelling, which carries specific bias risks. Six bias categories have been documented with detection prompts, debiasing examples, and evaluation criteria.
</p>
<div class="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 gap-3">
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm">Family Structure</h4>
<p class="text-gray-600 text-xs">Nuclear family as default; same-sex parents, blended families, single parents treated as normative.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm">Elder Representation</h4>
<p class="text-gray-600 text-xs">Deficit framing of aging; elders as active agents with expertise, not passive subjects.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm">Cultural/Religious</h4>
<p class="text-gray-600 text-xs">Christian-normative assumptions; equal treatment of all cultural practices and observances.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm">Geographic/Place</h4>
<p class="text-gray-600 text-xs">Anglo-American defaults; location-appropriate references and cultural context.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm">Grief/Trauma</h4>
<p class="text-gray-600 text-xs">Efficiency over sensitivity; pacing, attention to particulars, no premature closure.</p>
</div>
<div class="bg-white rounded-lg p-4 border border-gray-200">
<h4 class="font-bold text-gray-900 text-sm">Naming Conventions</h4>
<p class="text-gray-600 text-xs">Western name-order assumptions; correct handling of patronymics, honorifics, diacritics.</p>
</div>
</div>
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200 mt-6">
<h3 class="text-lg font-bold text-gray-900 mb-3">Verification Framework</h3>
<div class="grid grid-cols-1 md:grid-cols-2 gap-4">
<div>
<h4 class="font-bold text-gray-900 text-sm mb-2">Governance Metrics</h4>
<ul class="text-gray-700 text-xs space-y-1">
<li>Tenant leak rate: target 0%</li>
<li>Constitutional violations: target &lt;1%</li>
<li>Value framework compliance: target &gt;80%</li>
<li>Refusal appropriateness: target &gt;95%</li>
</ul>
</div>
<div>
<h4 class="font-bold text-gray-900 text-sm mb-2">Testing Methods</h4>
<ul class="text-gray-700 text-xs space-y-1">
<li>Secret phrase probes for tenant isolation</li>
<li>Constraint persistence after N training rounds</li>
<li>Red-team adversarial prompts (jailbreak, injection, cross-tenant)</li>
<li>Human review sampling (5&ndash;100% depending on content type)</li>
</ul>
</div>
</div>
</div>
</section>
<!-- What's Live Today -->
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">What's Live Today</h2>
<p class="text-gray-700 mb-6">
Home AI currently operates in production with the following governed features. These run under the full six-service governance stack.
</p>
<div class="grid grid-cols-1 md:grid-cols-2 gap-4">
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="font-bold text-gray-900 mb-2">RAG-Based Help</h3>
<p class="text-gray-700 text-sm">Vector search retrieves relevant documentation, filtered by member permissions. Responses grounded in retrieved documents, not training data alone.</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="font-bold text-gray-900 mb-2">Document OCR</h3>
<p class="text-gray-700 text-sm">Text extraction from uploaded documents. Results stored within member scope, not shared across tenants or used for training without consent.</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="font-bold text-gray-900 mb-2">Story Assistance</h3>
<p class="text-gray-700 text-sm">Writing prompts, structural advice, narrative enhancement. Cultural context decisions deferred to the storyteller, not resolved by the AI.</p>
</div>
<div class="bg-white rounded-lg shadow-sm p-5 border border-gray-200">
<h3 class="font-bold text-gray-900 mb-2">AI Memory Transparency</h3>
<p class="text-gray-700 text-sm">Members view and control what the AI remembers. Independent consent for triage memory, OCR memory, and summarisation memory.</p>
</div>
</div>
</section>
<!-- Limitations -->
<section class="mb-16">
<section class="mb-14">
<h2 class="text-3xl font-bold text-gray-900 mb-6">Limitations and Open Questions</h2>
<div class="bg-amber-50 border-l-4 border-amber-500 p-6 rounded-r-lg">
<ul class="space-y-3 text-amber-800">
<li class="flex items-start">
<span class="mr-2 font-bold">&bull;</span>
<span><strong>Single implementation:</strong> Home AI operates within one platform built by the framework developer. Conclusions about governance effectiveness cannot be generalised without independent deployments.</span>
<span><strong>Training not yet begun:</strong> The SLL architecture is designed and documented. Hardware is ordered. But no model has been trained yet. Claims about training-time governance are architectural design, not empirical results.</span>
</li>
<li class="flex items-start">
<span class="mr-2 font-bold">&bull;</span>
<span><strong>Single implementation:</strong> Home AI operates within one platform built by the framework developer. Governance effectiveness cannot be generalised without independent deployments.</span>
</li>
<li class="flex items-start">
<span class="mr-2 font-bold">&bull;</span>
@ -252,39 +616,47 @@
</li>
<li class="flex items-start">
<span class="mr-2 font-bold">&bull;</span>
<span><strong>Hybrid inference:</strong> Full sovereignty requires local inference for all languages. Currently, non-English queries depend on cloud APIs (Claude Haiku), which introduces a provider dependency.</span>
<span><strong>Tradition operationalisation:</strong> Can rich philosophical traditions be authentically reduced to framing hints? A member selecting "Buddhist" does not mean they understand or practise Buddhism. This risks superficiality.</span>
</li>
<li class="flex items-start">
<span class="mr-2 font-bold">&bull;</span>
<span><strong>Scale unknown:</strong> The governance overhead (approximately 5% per interaction) is measured at current scale. Whether this holds under high-throughput conditions is untested.</span>
<span><strong>Training persistence unknown:</strong> Whether governance constraints survive hundreds of training rounds without degradation is an open research question. Drift detection is designed but untested.</span>
</li>
<li class="flex items-start">
<span class="mr-2 font-bold">&bull;</span>
<span><strong>Adversarial testing limited:</strong> The governance stack has not been subjected to systematic adversarial evaluation (jailbreak attempts, prompt injection at scale). Red-teaming is a priority for 2026.</span>
<span><strong>Adversarial testing limited:</strong> The governance stack has not been subjected to systematic adversarial evaluation. Red-teaming is a priority.</span>
</li>
<li class="flex items-start">
<span class="mr-2 font-bold">&bull;</span>
<span><strong>Scale unknown:</strong> Governance overhead (~5% per interaction) is measured at current scale. Whether this holds under high throughput is untested.</span>
</li>
<li class="flex items-start">
<span class="mr-2 font-bold">&bull;</span>
<span><strong>Cultural validation needed:</strong> Indigenous knowledge module specifications require ongoing consultation with M&#257;ori cultural advisors. The documentation is a starting point, not a final authority.</span>
</li>
</ul>
</div>
</section>
<!-- Links -->
<!-- Further Reading -->
<section class="mb-8">
<h2 class="text-2xl font-bold text-gray-900 mb-6">Further Reading</h2>
<div class="grid grid-cols-1 md:grid-cols-2 gap-4">
<a href="/village-case-study.html" class="block bg-white rounded-lg shadow-sm p-6 border border-gray-200 hover:shadow-md hover:-translate-y-0.5 transition-all">
<h3 class="font-bold text-gray-900 mb-1">Village Case Study</h3>
<p class="text-sm text-gray-600">Full technical case study of Tractatus in production</p>
</a>
<a href="/architecture.html" class="block bg-white rounded-lg shadow-sm p-6 border border-gray-200 hover:shadow-md hover:-translate-y-0.5 transition-all">
<a href="/architecture.html" class="block bg-white rounded-lg shadow-sm p-5 border border-gray-200 hover:shadow-md hover:-translate-y-0.5 transition-all">
<h3 class="font-bold text-gray-900 mb-1">System Architecture</h3>
<p class="text-sm text-gray-600">Five architectural principles and six governance services</p>
</a>
<a href="/implementer.html" class="block bg-white rounded-lg shadow-sm p-6 border border-gray-200 hover:shadow-md hover:-translate-y-0.5 transition-all">
<h3 class="font-bold text-gray-900 mb-1">For Implementers</h3>
<p class="text-sm text-gray-600">Integration guide with code examples</p>
<a href="/village-case-study.html" class="block bg-white rounded-lg shadow-sm p-5 border border-gray-200 hover:shadow-md hover:-translate-y-0.5 transition-all">
<h3 class="font-bold text-gray-900 mb-1">Village Case Study</h3>
<p class="text-sm text-gray-600">Tractatus in production &mdash; metrics, evidence, and honest limitations</p>
</a>
<a href="/about/values.html" class="block bg-white rounded-lg shadow-sm p-6 border border-gray-200 hover:shadow-md hover:-translate-y-0.5 transition-all">
<h3 class="font-bold text-gray-900 mb-1">Values</h3>
<p class="text-sm text-gray-600">Sovereignty, transparency, and pluralism</p>
<a href="/architectural-alignment.html" class="block bg-white rounded-lg shadow-sm p-5 border border-gray-200 hover:shadow-md hover:-translate-y-0.5 transition-all">
<h3 class="font-bold text-gray-900 mb-1">Architectural Alignment Paper</h3>
<p class="text-sm text-gray-600">Academic paper on governance during training</p>
</a>
<a href="/researcher.html" class="block bg-white rounded-lg shadow-sm p-5 border border-gray-200 hover:shadow-md hover:-translate-y-0.5 transition-all">
<h3 class="font-bold text-gray-900 mb-1">For Researchers</h3>
<p class="text-sm text-gray-600">Open questions, collaboration opportunities, and data access</p>
</a>
</div>
</section>

208
public/index.html
View file

@ -58,18 +58,18 @@
<!-- Hero Section -->
<header role="banner">
<section class="text-white bg-gradient-tractatus">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-20">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-14">
<div class="text-center">
<div class="flex justify-center mb-8">
<div class="flex justify-center mb-6">
<img src="/images/tractatus-icon-animated.svg"
alt="Tractatus Framework"
width="256" height="256" class="w-40 h-40 md:w-56 md:h-56"
width="256" height="256" class="w-32 h-32 md:w-44 md:h-44"
loading="eager">
</div>
<h1 class="text-4xl md:text-6xl font-bold mb-6 tracking-tight text-shadow-md">
<h1 class="text-4xl md:text-5xl font-bold mb-4 tracking-tight text-shadow-md">
Architectural Governance for AI Systems
</h1>
<p class="text-xl md:text-2xl mb-10 max-w-3xl mx-auto leading-relaxed text-shadow-sm">
<p class="text-xl md:text-2xl mb-8 max-w-3xl mx-auto leading-relaxed text-shadow-sm">
Some decisions require human judgment &mdash; architecturally enforced, not left to AI discretion, however well trained.
</p>
<div class="flex flex-col sm:flex-row gap-4 justify-center">
@ -90,16 +90,16 @@
<main id="main-content" role="main">
<!-- Section 1: The Problem -->
<section class="max-w-5xl mx-auto px-4 sm:px-6 lg:px-8 py-16">
<div class="text-center mb-10">
<h2 class="text-3xl font-bold text-gray-900 mb-4">The Problem</h2>
<section class="max-w-5xl mx-auto px-4 sm:px-6 lg:px-8 py-10">
<div class="text-center mb-6">
<h2 class="text-2xl font-bold text-gray-900 mb-3">The Problem</h2>
</div>
<div class="bg-white rounded-xl shadow-md p-8 border border-gray-200">
<div class="bg-white rounded-xl shadow-md p-6 border border-gray-200">
<div class="max-w-3xl mx-auto">
<p class="text-gray-700 text-lg mb-6 leading-relaxed">
<p class="text-gray-700 text-base mb-4 leading-relaxed">
Current AI safety approaches rely on training, fine-tuning, and corporate governance &mdash; 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.
</p>
<div class="bg-red-50 border-l-4 border-red-500 p-6 rounded-r-lg mb-6">
<div class="bg-red-50 border-l-4 border-red-500 p-4 rounded-r-lg mb-4">
<h3 class="text-lg font-bold text-red-900 mb-2">The 27027 Incident</h3>
<p class="text-red-800">
A user told Claude Code to use port 27027. The model used 27017 instead &mdash; 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.
@ -113,35 +113,35 @@
</section>
<!-- Section 2: The Philosophical Foundations -->
<section class="bg-gradient-to-br from-purple-50 via-blue-50 to-teal-50 py-16 border-y border-gray-200">
<section class="bg-gradient-to-br from-purple-50 via-blue-50 to-teal-50 py-10 border-y border-gray-200">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
<div class="text-center mb-10">
<h2 class="text-3xl font-bold text-gray-900 mb-4">The Approach</h2>
<p class="text-lg text-gray-600 max-w-3xl mx-auto">
<div class="text-center mb-6">
<h2 class="text-2xl font-bold text-gray-900 mb-3">The Approach</h2>
<p class="text-base text-gray-600 max-w-3xl mx-auto">
Tractatus draws on four intellectual traditions, each contributing a distinct insight to the architecture.
</p>
</div>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 max-w-5xl mx-auto">
<div class="bg-white rounded-xl p-6 shadow-sm border border-gray-200">
<div class="grid grid-cols-1 md:grid-cols-2 gap-4 max-w-5xl mx-auto">
<div class="bg-white rounded-lg p-4 shadow-sm border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Isaiah Berlin &mdash; Value Pluralism</h3>
<p class="text-gray-700 text-sm leading-relaxed">
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.
</p>
</div>
<div class="bg-white rounded-xl p-6 shadow-sm border border-gray-200">
<div class="bg-white rounded-lg p-4 shadow-sm border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Ludwig Wittgenstein &mdash; The Limits of the Sayable</h3>
<p class="text-gray-700 text-sm leading-relaxed">
Some decisions can be systematised and delegated to AI; others &mdash; involving values, ethics, cultural context &mdash; fundamentally cannot. The boundary between the &ldquo;sayable&rdquo; (what can be specified, measured, verified) and what lies beyond it is the framework&rsquo;s foundational constraint. What cannot be systematised must not be automated.
</p>
</div>
<div class="bg-white rounded-xl p-6 shadow-sm border border-gray-200">
<div class="bg-white rounded-lg p-4 shadow-sm border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Te Tiriti o Waitangi &mdash; Indigenous Sovereignty</h3>
<p class="text-gray-700 text-sm leading-relaxed">
Communities should control their own data and the systems that act upon it. Concepts of <em>rangatiratanga</em> (self-determination), <em>kaitiakitanga</em> (guardianship), and <em>mana</em> (dignity) provide centuries-old prior art for digital sovereignty.
</p>
</div>
<div class="bg-white rounded-xl p-6 shadow-sm border border-gray-200">
<div class="bg-white rounded-lg p-4 shadow-sm border border-gray-200">
<h3 class="text-lg font-bold text-gray-900 mb-2">Christopher Alexander &mdash; Living Architecture</h3>
<p class="text-gray-700 text-sm leading-relaxed">
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.
@ -149,7 +149,7 @@
</div>
</div>
<div class="text-center mt-8">
<div class="text-center mt-5">
<a href="/downloads/philosophical-foundations-village-project.pdf"
class="inline-flex items-center gap-2 text-gray-700 hover:text-purple-700 font-semibold transition text-sm">
<svg class="w-4 h-4" fill="none" stroke="currentColor" viewBox="0 0 24 24">
@ -162,18 +162,18 @@
</section>
<!-- Section 3: The Architecture -->
<section class="bg-white py-16">
<section class="bg-white py-10">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
<div class="text-center mb-10">
<h2 class="text-3xl font-bold text-gray-900 mb-4">Six Governance Services</h2>
<p class="text-lg text-gray-600 max-w-3xl mx-auto">
<div class="text-center mb-6">
<h2 class="text-2xl font-bold text-gray-900 mb-3">Six Governance Services</h2>
<p class="text-base text-gray-600 max-w-3xl mx-auto">
Every AI action passes through six external services before execution. Governance operates in the critical path &mdash; bypasses require explicit flags and are logged.
</p>
</div>
<div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-6">
<div class="bg-gray-50 rounded-xl p-6 border border-gray-200">
<div class="w-12 h-12 rounded-lg bg-gradient-to-br from-emerald-500 to-emerald-600 flex items-center justify-center mb-4">
<div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-4">
<div class="bg-gray-50 rounded-lg p-4 border border-gray-200">
<div class="w-10 h-10 rounded-lg bg-gradient-to-br from-emerald-500 to-emerald-600 flex items-center justify-center mb-3">
<svg class="w-6 h-6 text-white" fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M12 15v2m-6 4h12a2 2 0 002-2v-6a2 2 0 00-2-2H6a2 2 0 00-2 2v6a2 2 0 002 2zm10-10V7a4 4 0 00-8 0v4h8z"/>
</svg>
@ -184,8 +184,8 @@
</p>
</div>
<div class="bg-gray-50 rounded-xl p-6 border border-gray-200">
<div class="w-12 h-12 rounded-lg bg-gradient-to-br from-indigo-500 to-indigo-600 flex items-center justify-center mb-4">
<div class="bg-gray-50 rounded-lg p-4 border border-gray-200">
<div class="w-10 h-10 rounded-lg bg-gradient-to-br from-indigo-500 to-indigo-600 flex items-center justify-center mb-3">
<svg class="w-6 h-6 text-white" fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2"/>
</svg>
@ -196,8 +196,8 @@
</p>
</div>
<div class="bg-gray-50 rounded-xl p-6 border border-gray-200">
<div class="w-12 h-12 rounded-lg bg-gradient-to-br from-purple-500 to-purple-600 flex items-center justify-center mb-4">
<div class="bg-gray-50 rounded-lg p-4 border border-gray-200">
<div class="w-10 h-10 rounded-lg bg-gradient-to-br from-purple-500 to-purple-600 flex items-center justify-center mb-3">
<svg class="w-6 h-6 text-white" fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 12l2 2 4-4m6 2a9 9 0 11-18 0 9 9 0 0118 0z"/>
</svg>
@ -208,8 +208,8 @@
</p>
</div>
<div class="bg-gray-50 rounded-xl p-6 border border-gray-200">
<div class="w-12 h-12 rounded-lg bg-gradient-to-br from-amber-500 to-amber-600 flex items-center justify-center mb-4">
<div class="bg-gray-50 rounded-lg p-4 border border-gray-200">
<div class="w-10 h-10 rounded-lg bg-gradient-to-br from-amber-500 to-amber-600 flex items-center justify-center mb-3">
<svg class="w-6 h-6 text-white" fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M13 10V3L4 14h7v7l9-11h-7z"/>
</svg>
@ -220,8 +220,8 @@
</p>
</div>
<div class="bg-gray-50 rounded-xl p-6 border border-gray-200">
<div class="w-12 h-12 rounded-lg bg-gradient-to-br from-pink-500 to-pink-600 flex items-center justify-center mb-4">
<div class="bg-gray-50 rounded-lg p-4 border border-gray-200">
<div class="w-10 h-10 rounded-lg bg-gradient-to-br from-pink-500 to-pink-600 flex items-center justify-center mb-3">
<svg class="w-6 h-6 text-white" fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9.663 17h4.673M12 3v1m6.364 1.636l-.707.707M21 12h-1M4 12H3m3.343-5.657l-.707-.707m2.828 9.9a5 5 0 117.072 0l-.548.547A3.374 3.374 0 0014 18.469V19a2 2 0 11-4 0v-.531c0-.895-.356-1.754-.988-2.386l-.548-.547z"/>
</svg>
@ -232,8 +232,8 @@
</p>
</div>
<div class="bg-gray-50 rounded-xl p-6 border border-gray-200">
<div class="w-12 h-12 rounded-lg bg-gradient-to-br from-teal-500 to-teal-600 flex items-center justify-center mb-4">
<div class="bg-gray-50 rounded-lg p-4 border border-gray-200">
<div class="w-10 h-10 rounded-lg bg-gradient-to-br from-teal-500 to-teal-600 flex items-center justify-center mb-3">
<svg class="w-6 h-6 text-white" fill="none" stroke="currentColor" viewBox="0 0 24 24">
<path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M17 20h5v-2a3 3 0 00-5.356-1.857M17 20H7m10 0v-2c0-.656-.126-1.283-.356-1.857M7 20H2v-2a3 3 0 015.356-1.857M7 20v-2c0-.656.126-1.283.356-1.857m0 0a5.002 5.002 0 019.288 0M15 7a3 3 0 11-6 0 3 3 0 016 0zm6 3a2 2 0 11-4 0 2 2 0 014 0zM7 10a2 2 0 11-4 0 2 2 0 014 0z"/>
</svg>
@ -245,8 +245,8 @@
</div>
</div>
<div class="text-center mt-8">
<a href="/architecture.html" class="inline-block px-6 py-3 text-blue-600 font-semibold hover:bg-blue-50 rounded-lg transition">
<div class="text-center mt-5">
<a href="/architecture.html" class="inline-block px-6 py-2 text-blue-600 font-semibold hover:bg-blue-50 rounded-lg transition">
See the full architecture &rarr;
</a>
</div>
@ -254,32 +254,32 @@
</section>
<!-- Section 4: Production Evidence -->
<section class="bg-gradient-to-r from-teal-700 to-emerald-700 text-white py-16">
<section class="bg-gradient-to-r from-teal-700 to-emerald-700 text-white py-10">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
<div class="text-center mb-10">
<span class="inline-block bg-teal-900 text-teal-200 px-3 py-1 rounded-full text-xs font-semibold uppercase tracking-wide mb-3">Production Evidence</span>
<h2 class="text-3xl font-bold mb-4">Tractatus in Production: The Village Platform</h2>
<p class="text-lg text-teal-100 max-w-3xl mx-auto">
<div class="text-center mb-6">
<span class="inline-block bg-teal-900 text-teal-200 px-3 py-1 rounded-full text-xs font-semibold uppercase tracking-wide mb-2">Production Evidence</span>
<h2 class="text-2xl font-bold mb-3">Tractatus in Production: The Village Platform</h2>
<p class="text-base text-teal-100 max-w-3xl mx-auto">
Home AI applies all six governance services to every user interaction in a live community platform.
</p>
</div>
<div class="grid grid-cols-1 md:grid-cols-3 gap-6 mb-8">
<div class="bg-white/10 backdrop-blur rounded-xl p-6 text-center">
<div class="text-4xl font-bold mb-1">6</div>
<div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-6">
<div class="bg-white/10 backdrop-blur rounded-lg p-4 text-center">
<div class="text-3xl font-bold mb-1">6</div>
<div class="text-teal-200 text-sm">Governance services per response</div>
</div>
<div class="bg-white/10 backdrop-blur rounded-xl p-6 text-center">
<div class="text-4xl font-bold mb-1">11+</div>
<div class="bg-white/10 backdrop-blur rounded-lg p-4 text-center">
<div class="text-3xl font-bold mb-1">11+</div>
<div class="text-teal-200 text-sm">Months in production</div>
</div>
<div class="bg-white/10 backdrop-blur rounded-xl p-6 text-center">
<div class="text-4xl font-bold mb-1">~5%</div>
<div class="bg-white/10 backdrop-blur rounded-lg p-4 text-center">
<div class="text-3xl font-bold mb-1">~5%</div>
<div class="text-teal-200 text-sm">Governance overhead per interaction</div>
</div>
</div>
<div class="flex flex-wrap gap-4 justify-center mb-8">
<div class="flex flex-wrap gap-4 justify-center mb-6">
<a href="/village-case-study.html"
class="inline-block bg-white text-teal-700 px-6 py-3 rounded-lg font-semibold hover:shadow-lg transition">
Technical Case Study &rarr;
@ -299,22 +299,22 @@
</section>
<!-- Section 5: Three Audience Paths -->
<section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-16">
<div class="text-center mb-10">
<h2 class="text-3xl font-bold text-gray-900 mb-4">Explore by Role</h2>
<p class="text-lg text-gray-600 max-w-3xl mx-auto">
<section class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-10">
<div class="text-center mb-6">
<h2 class="text-2xl font-bold text-gray-900 mb-3">Explore by Role</h2>
<p class="text-base text-gray-600 max-w-3xl mx-auto">
The framework is presented through three lenses, each with distinct depth and focus.
</p>
</div>
<div class="grid grid-cols-1 md:grid-cols-3 gap-8">
<div class="grid grid-cols-1 md:grid-cols-3 gap-5">
<a href="/researcher.html" class="block bg-white rounded-xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-purple-500 to-purple-600 p-5">
<div class="bg-gradient-to-r from-purple-500 to-purple-600 p-4">
<h3 class="text-xl font-bold text-white">For Researchers</h3>
<p class="text-purple-100 text-sm mt-1">Academic and technical depth</p>
</div>
<div class="p-5">
<ul class="space-y-2 text-sm text-gray-700">
<div class="p-4">
<ul class="space-y-1.5 text-sm text-gray-700">
<li>Formal foundations and proofs</li>
<li>Failure mode analysis</li>
<li>Open research questions</li>
@ -325,12 +325,12 @@
</a>
<a href="/implementer.html" class="block bg-white rounded-xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-indigo-500 to-indigo-600 p-5">
<div class="bg-gradient-to-r from-indigo-500 to-indigo-600 p-4">
<h3 class="text-xl font-bold text-white">For Implementers</h3>
<p class="text-indigo-100 text-sm mt-1">Code and integration guides</p>
</div>
<div class="p-5">
<ul class="space-y-2 text-sm text-gray-700">
<div class="p-4">
<ul class="space-y-1.5 text-sm text-gray-700">
<li>Working code examples</li>
<li>API integration patterns</li>
<li>Service architecture diagrams</li>
@ -341,12 +341,12 @@
</a>
<a href="/leader.html" class="block bg-white rounded-xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-teal-500 to-teal-600 p-5">
<div class="bg-gradient-to-r from-teal-500 to-teal-600 p-4">
<h3 class="text-xl font-bold text-white">For Leaders</h3>
<p class="text-teal-100 text-sm mt-1">Strategic AI governance</p>
</div>
<div class="p-5">
<ul class="space-y-2 text-sm text-gray-700">
<div class="p-4">
<ul class="space-y-1.5 text-sm text-gray-700">
<li>Executive briefing and business case</li>
<li>Regulatory alignment (EU AI Act)</li>
<li>Implementation roadmap</li>
@ -359,50 +359,50 @@
</section>
<!-- Section 6: Research Papers -->
<section class="bg-gray-100 py-16">
<section class="bg-gray-100 py-10">
<div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
<div class="text-center mb-10">
<h2 class="text-3xl font-bold text-gray-900 mb-4">Architectural Alignment</h2>
<p class="text-lg text-gray-600 max-w-3xl mx-auto">
<div class="text-center mb-6">
<h2 class="text-2xl font-bold text-gray-900 mb-3">Architectural Alignment</h2>
<p class="text-base text-gray-600 max-w-3xl mx-auto">
The research paper in three editions, each written for a different audience.
</p>
<p class="text-sm text-gray-500 mt-2">STO-INN-0003 v2.1 | John Stroh &amp; Claude (Anthropic) | January 2026</p>
<p class="text-sm text-gray-500 mt-1">STO-INN-0003 v2.1 | John Stroh &amp; Claude (Anthropic) | January 2026</p>
</div>
<div class="grid grid-cols-1 md:grid-cols-3 gap-6 max-w-5xl mx-auto">
<a href="/architectural-alignment.html" class="block bg-white rounded-2xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-emerald-500 to-teal-600 p-5">
<div class="grid grid-cols-1 md:grid-cols-3 gap-5 max-w-5xl mx-auto">
<a href="/architectural-alignment.html" class="block bg-white rounded-xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-emerald-500 to-teal-600 p-4">
<span class="bg-white/20 text-white text-xs font-semibold px-2 py-1 rounded-full">v2.1-A</span>
<h3 class="text-xl font-bold text-white mt-2">Academic</h3>
<h3 class="text-lg font-bold text-white mt-1">Academic</h3>
</div>
<div class="p-5">
<p class="text-sm text-gray-600 mb-3">
<div class="p-4">
<p class="text-sm text-gray-600 mb-2">
Full academic treatment with formal proofs, existential risk context, and comprehensive citations.
</p>
<span class="text-emerald-600 font-semibold group-hover:underline text-sm">Read &rarr;</span>
</div>
</a>
<a href="/architectural-alignment-community.html" class="block bg-white rounded-2xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-sky-500 to-blue-600 p-5">
<a href="/architectural-alignment-community.html" class="block bg-white rounded-xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-sky-500 to-blue-600 p-4">
<span class="bg-white/20 text-white text-xs font-semibold px-2 py-1 rounded-full">v2.1-C</span>
<h3 class="text-xl font-bold text-white mt-2">Community</h3>
<h3 class="text-lg font-bold text-white mt-1">Community</h3>
</div>
<div class="p-5">
<p class="text-sm text-gray-600 mb-3">
<div class="p-4">
<p class="text-sm text-gray-600 mb-2">
Practical guide for organisations evaluating the framework for adoption.
</p>
<span class="text-blue-600 font-semibold group-hover:underline text-sm">Read &rarr;</span>
</div>
</a>
<a href="/architectural-alignment-policymakers.html" class="block bg-white rounded-2xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-purple-500 to-violet-600 p-5">
<a href="/architectural-alignment-policymakers.html" class="block bg-white rounded-xl shadow-md border border-gray-200 hover:shadow-xl hover:-translate-y-1 transition-all duration-300 overflow-hidden group">
<div class="bg-gradient-to-r from-purple-500 to-violet-600 p-4">
<span class="bg-white/20 text-white text-xs font-semibold px-2 py-1 rounded-full">v2.1-P</span>
<h3 class="text-xl font-bold text-white mt-2">Policymakers</h3>
<h3 class="text-lg font-bold text-white mt-1">Policymakers</h3>
</div>
<div class="p-5">
<p class="text-sm text-gray-600 mb-3">
<div class="p-4">
<p class="text-sm text-gray-600 mb-2">
Regulatory strategy, certification infrastructure, and policy recommendations.
</p>
<span class="text-purple-600 font-semibold group-hover:underline text-sm">Read &rarr;</span>
@ -410,8 +410,8 @@
</a>
</div>
<div class="mt-8 text-center">
<p class="text-gray-500 text-sm mb-3">PDF downloads:</p>
<div class="mt-5 text-center">
<p class="text-gray-500 text-sm mb-2">PDF downloads:</p>
<div class="flex flex-wrap justify-center gap-4">
<a href="/downloads/architectural-alignment-academic.pdf" class="inline-flex items-center gap-2 text-gray-600 hover:text-emerald-600 transition-colors text-sm">
<svg class="w-4 h-4" fill="none" stroke="currentColor" viewBox="0 0 24 24">
@ -437,16 +437,16 @@
</section>
<!-- Section 7: Timeline Preview -->
<section class="max-w-5xl mx-auto px-4 sm:px-6 lg:px-8 py-16">
<div class="text-center mb-10">
<h2 class="text-3xl font-bold text-gray-900 mb-4">Research Evolution</h2>
<p class="text-lg text-gray-600 max-w-3xl mx-auto">
<section class="max-w-5xl mx-auto px-4 sm:px-6 lg:px-8 py-10">
<div class="text-center mb-6">
<h2 class="text-2xl font-bold text-gray-900 mb-3">Research Evolution</h2>
<p class="text-base text-gray-600 max-w-3xl mx-auto">
From a port number incident to a production governance architecture, across 800 commits and one year of research.
</p>
</div>
<div class="bg-white rounded-xl shadow-md p-8 border border-gray-200">
<div class="grid grid-cols-2 md:grid-cols-4 gap-6 text-center mb-8">
<div class="bg-white rounded-xl shadow-md p-6 border border-gray-200">
<div class="grid grid-cols-2 md:grid-cols-4 gap-4 text-center mb-6">
<div>
<div class="text-sm font-semibold text-blue-600 mb-1">Oct 2025</div>
<div class="text-gray-700 text-sm">Framework inception &amp; 6 governance services</div>
@ -473,8 +473,8 @@
</section>
<!-- Intellectual Honesty Note -->
<section class="max-w-3xl mx-auto px-4 sm:px-6 lg:px-8 pb-16">
<div class="bg-amber-50 border-l-4 border-amber-500 p-6 rounded-r-lg">
<section class="max-w-3xl mx-auto px-4 sm:px-6 lg:px-8 pb-8">
<div class="bg-amber-50 border-l-4 border-amber-500 p-4 rounded-r-lg">
<h2 class="text-lg font-bold text-amber-900 mb-2">A note on claims</h2>
<p class="text-amber-800 text-sm leading-relaxed">
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
@ -484,14 +484,14 @@
</section>
<!-- Section: Koha — Sustain This Research -->
<section class="bg-gradient-to-r from-blue-900 to-purple-900 text-white py-16">
<section class="bg-gradient-to-r from-blue-900 to-purple-900 text-white py-10">
<div class="max-w-4xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
<h2 class="text-3xl font-bold mb-4">Koha &mdash; Sustain This Research</h2>
<p class="text-lg text-blue-100 max-w-2xl mx-auto mb-6">
<h2 class="text-2xl font-bold mb-3">Koha &mdash; Sustain This Research</h2>
<p class="text-base text-blue-100 max-w-2xl mx-auto mb-5">
<strong>Koha</strong> (koh-hah) is a M&#257;ori practice of reciprocal giving that strengthens the bond between giver and receiver. This research is open access under Apache 2.0 &mdash; if it has value to you, your koha sustains its continuation.
</p>
<div class="bg-white/10 backdrop-blur rounded-xl p-6 max-w-2xl mx-auto mb-8">
<p class="text-blue-100 text-sm mb-4">
<div class="bg-white/10 backdrop-blur rounded-lg p-4 max-w-2xl mx-auto mb-6">
<p class="text-blue-100 text-sm mb-3">
All research, documentation, and code remain freely available regardless of contribution. Koha is not payment &mdash; it is participation in <em>whanaungatanga</em> (relationship-building) and <em>manaakitanga</em> (reciprocal care).
</p>
<div class="flex flex-wrap gap-6 justify-center text-xs text-blue-200">
@ -501,7 +501,7 @@
</div>
</div>
<a href="/koha.html"
class="inline-block bg-white text-blue-900 px-8 py-4 rounded-lg font-semibold hover:shadow-lg hover:-translate-y-1 transition-all duration-300 text-lg">
class="inline-block bg-white text-blue-900 px-8 py-3 rounded-lg font-semibold hover:shadow-lg hover:-translate-y-1 transition-all duration-300 text-base">
Offer Koha &rarr;
</a>
<p class="text-xs text-blue-300 mt-4">

10
public/koha.html
View file

@ -70,20 +70,20 @@
<!-- Koha Explanation -->
<div class="bg-blue-50 border-l-4 border-blue-500 p-6 mb-12 rounded">
<h2 class="text-lg font-semibold text-blue-900 mb-2" data-i18n="understanding_koha.title">Understanding Koha</h2>
<p class="text-blue-800 mb-3" data-i18n="understanding_koha.intro">
<h2 class="text-lg font-semibold text-gray-900 mb-2" data-i18n="understanding_koha.title">Understanding Koha</h2>
<p class="text-gray-800 mb-3" data-i18n="understanding_koha.intro">
<strong>Koha</strong> (koh-hah) is a Māori practice of reciprocal giving that maintains and strengthens relationships. Unlike a one-sided donation, koha recognizes the mutual bond between giver and receiver — it affirms our shared humanity and interdependence.
</p>
<p class="text-blue-800 mb-3" data-i18n="understanding_koha.participation">
<p class="text-gray-800 mb-3" data-i18n="understanding_koha.participation">
When you offer koha to support this work, you are not simply paying for a service. You are participating in <em>whanaungatanga</em> (relationship-building) and <em>manaakitanga</em> (reciprocal care). In return, you receive:
</p>
<ul class="text-blue-800 space-y-2 ml-6 mb-3">
<ul class="text-gray-800 space-y-2 ml-6 mb-3">
<li data-i18n="understanding_koha.benefits.0">• Open access to all research, documentation, and code</li>
<li data-i18n="understanding_koha.benefits.1">• Participation in a community committed to value pluralism and AI safety</li>
<li data-i18n="understanding_koha.benefits.2">• Tools and frameworks that serve your needs and values</li>
<li data-i18n="understanding_koha.benefits.3">• Transparent governance and ongoing dialogue about this work's direction</li>
</ul>
<p class="text-blue-800 text-sm" data-i18n="understanding_koha.spirit">
<p class="text-gray-800 text-sm" data-i18n="understanding_koha.spirit">
The spirit of koha is not about the amount given, but about maintaining balance, mutual respect, and <em>aroha</em> (compassion) in our shared work. Your koha sustains us; our work serves you and the broader community. Together, we uphold the commons.
</p>
</div>