- Update glossary (v1.1) with value pluralism terminology
- Update case studies with value pluralism examples
- Update core concepts to include foundational pluralism
- Update introduction with 6th core service
- Update technical architecture and comparison matrix
- Update implementation guide with value pluralism sections
All markdown reflects 6-service production architecture
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Added 21 public-facing PDFs for research organizations and implementers:
**Core Framework Documentation (7):**
- Introduction to the Tractatus Framework
- Core Concepts of the Tractatus Framework
- Glossary of Terms
- Implementation Guide
- Implementation Guide: Python Code Examples
- Case Studies: Real-World LLM Failure Modes
- Technical Architecture Diagram (NEW)
**Research Papers (7):**
- Structural Governance for Agentic AI (Inflection Point Study)
- Executive Summary: Tractatus Inflection Point
- Organizational Theory Foundations
- Research Foundations: Scholarly Review and Context
- Research Scope: Feasibility of LLM-Integrated Framework
- Concurrent Session Architecture Limitations
- Rule Proliferation and Transactional Overhead
**Implementation Resources (4):**
- 24-Month Implementation Roadmap
- Tractatus Framework Enforcement for Claude Code
- Claude Code Framework Enforcement
- AI Governance Business Case Template
**Case Studies (4):**
- Real-World AI Governance: Framework Failure and Recovery
- When Frameworks Fail (And Why That's OK)
- Framework in Action: Detecting AI Fabrications
- Framework Governance in Action: Pre-Publication Security Audit
**Content Review:**
✓ All materials reviewed for confidential information
✓ No internal credentials, API keys, or sensitive data
✓ No session handoffs or internal project planning
✓ Research-grade materials suitable for academic outreach
✓ Implementation materials for production deployment
**Purpose:**
Enable research organizations to evaluate Tractatus framework with
comprehensive documentation, empirical studies, and implementation guides.
**Target Audience:**
- AI safety researchers
- Academic institutions
- Industry implementers
- Policy organizations
- Standards bodies
**Total Size:** ~7.3 MB of public research materials
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
