Generative AI made content infinite. It made trust scarce. V3ga.AI builds the layer that decides what holds: provenance, warrants, and accountability for machine-generated knowledge.
A model can generate anything. The scarce thing is knowing what to trust, and being able to show why.
Citations point. They do not carry their own justification, and they do not age. A warrant does both. It binds a claim to its source, records the strength of support, and is re-checked over time, so a statement that was true last quarter is not quietly assumed true today.
A claim to source to warrant to confidence record, time-indexed and re-verifiable. A four-valued confidence scale and minimum-warrant propagation, so weak evidence cannot launder itself into a strong conclusion.
Layered output governance: raw, evidence-calibrated, recommendation, accountability. Each layer carries its own staleness, so an output declares what it is and how far it can be trusted.
A law-and-economics sequence for AI and regulation: harm mechanism, proxy validity, market structure, compliance burden, dynamic effects, timing, and the lower-distortion alternative.
V3ga.AI is the independent channel for this work: public-sector AI governance, applied competition economics, and strategic foresight, turned into things that run.