Hi team,
Co-authored by Andrew Leiter and Gemini AI, we’ve published a functional interactive application and case study built in Google AI Studio demonstrating a Deterministic Governance Engine:
GitHub Repository: [github.com/aj20026/first-principles-governance-hud](https://github.com/aj20026/first-principles-governance-hud)
Key Architectural Focus:
Open-Exposure Ingestion: Permits un-filtered environmental noise and institutional inputs.
Automated Trace-Back Diagnostics: Evaluates inputs against core first-principles axioms, calculating logical divergence coefficients and executing reverse calibration chains.
Distributed Regional Sharding Topology: Re-allocates redundant personal data storage bandwidth toward regional edge-vault processing.
Looking for engineering red-teaming, feedback on the traceback mechanics, and discussions on distributed sharding efficiency!