I’m sharing a research deposit that explores an alternative AI governance model: non-decision systems.

Instead of optimizing outputs or replacing human judgment, the system constrains AI to structural verification, explicit stop conditions, and third-party auditability.

The goal is not performance, but preventing interpretative drift and authority transfer from human to system.

This is not a book or manifesto, but an operational framework derived from real deployment constraints and observed failure modes in current AI systems.

I’m interested in technical and governance feedback, especially from people working on safety, alignment, or infrastructure-level controls.