Learn runtime governance.
Concepts, comparisons, and reference for teams building runtime governance into AI agents. Grounded in the KYA paper and adjacent literature.
Start here.
What is runtime governance for AI agents?
The definition. The four responsibilities. The five-verdict pipeline. The three-layer AI governance stack. Grounded in the KYA paper.
What is AI agent analytics?
Continuous analysis of agent actions, governance decisions, delegation, and cost — with signed evidence attached to every row.
Observability vs runtime governance
Observability logs what happened. Runtime governance decides what happens. Side-by-side with the money-shot visual.
Agent analytics vs observability
Observability describes. Agent analytics attributes, verifies, and feeds signals back into policy. When to reach for each.
Agent analytics
The continuous analysis of AI agent actions, governance decisions, authority, delegation, cost, and outcomes.
Tamper-evident agent audit trail
A cryptographically chained record of every AI agent action. Verifiable offline, without contacting the vendor.
Browse by category.
Glossary
Definitions of the terms that make runtime governance a discipline.
Guides
Long-form pieces on concepts, patterns, and mechanisms.
Compare
How runtime governance differs from adjacent disciplines.
Research
The KYA paper on arXiv. Runtime governance formalized.