Operating manual
Tag: AI Governance
A focused reading path for AI Governance: related field notes, evidence trails, and operating questions from the archive.
- scoring-definition-is-the-lever-in-agent-evals.md
Scoring Definition Is the Lever in Agent Evals
A 24.0%-57.0% consensus swing on identical held-out data is a property of the scoring definition, not the agents. Lock the definition before reading the number.
open artifact → - agent-depth-trades-yield-for-cheaper-context.md
Agent Depth Trades Yield for Cheaper Context
Depth is not automatically cheaper context. Treating finding yield, root-context exposure, and dollars per finding as three independent axes exposes the real trade, and a per-tier alignment check prevents promoting another tier on paper numbers alone.
open artifact → - 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 →