Operating manual
Tag: ai-governance
A focused reading path for ai-governance: related field notes, evidence trails, and operating questions from the archive.
- the-model-answer-is-not-accepted-knowledge.md
The Model Answer Is Not Accepted Knowledge
Valid JSON proves shape, not truth. Reliable AI extraction needs evidence, provenance, policy controls, and reversible claim acceptance.
open artifact → - your-ai-security-checklist-has-a-version-problem.md
Your AI Security Checklist Has a Version Problem
A practical control for pinning AI security guidance, preserving its source, and reopening reviews when that guidance changes.
open artifact → - system-prompts-are-product-policy.md
System Prompts Are Product Policy
When a prompt clause changes consequential AI behavior, it needs a release record—not an informal text edit.
open artifact → - the-governance-gap-after-ai-extraction.md
The Governance Gap After AI Extraction
An extraction model returns a candidate claim. A five-field governance record decides whether that claim can safely travel.
open artifact → - how-to-turn-nist-ai-rmf-into-operating-guidance.md
How to Turn NIST AI RMF Into Operating Guidance
Turn the voluntary NIST AI Risk Management Framework into an operating packet covering context, risks, practices, owners, evidence, and supplier requirements.
open artifact → - the-authority-envelope-every-agent-handoff-should-carry.md
The Authority Envelope Every Agent Handoff Should Carry
Agent handoffs do not become trustworthy because two systems can talk. They become trustworthy when every handoff carries authority, state, evidence, risk, and the next allowed action.
open artifact →