AI Governance
Governance Under Scale — Part IV: Model Selection, NAIC, and the Crosswalk
The NAIC AI bulletin, NIST AI RMF, ISO/IEC 42001, the EU AI Act, and SR 11-7 all require a compliant system, not a compliant model. The crosswalk shows they are one control problem.
Governance Under Scale — Part III: Revocation and the Reachable Decision Surface
If governance requires the ability to constrain authority, then the critical question is not how a system behaves, but what it remains permitted to do.
When AI Systems “Dream”: A Failure of Architecture, Not Models
Many AI failures labeled as hallucinations are actually coherent systems operating without sufficient grounding or constraint. The fix is architectural, not model-based.
Governance Under Scale — Part II: Monitoring Is Not Control
Monitoring provides visibility into system behavior. Governance requires the ability to constrain it.
Governance Under Scale — Part I: Human Override Is Not Governance
Human-in-the-loop is commonly treated as a safety guarantee. Under scale, it becomes a delegation surface, and one of the primary vectors of governance drift.
AI in Regulated Systems: Where Architecture Becomes Governance
In regulated systems, the primary AI risk is not hallucination. It is allowing probabilistic inference to directly mutate deterministic state.
AI Is Increasing Your Delivery Velocity While Moving Your Problems Downstream
AI speeds up delivery. In many teams, it also delays the moment where real structural problems surface.
AI Is a Delivery Tool, Not a Strategy
AI accelerates delivery when governed; without standards it creates fragility.