Operating manual
Tag: ai-agents
A focused reading path for ai-agents: related field notes, evidence trails, and operating questions from the archive.
- population-monitoring-as-an-agent-warning-signal.md
Population Monitoring as an Agent Warning Signal
Individual agent checks can miss collective drift. Here's how to evaluate a population-level warning signal without mistaking it for a safety guarantee.
open artifact → - 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 → - skill-libraries-need-an-optimization-budget.md
Skill Libraries Need an Optimization Budget
Skill evolution is a billed optimization loop. A production skill library declares iterations, sampling, and validation cost up front, then treats overshoot as failure.
open artifact → - a-model-upgrade-is-a-memory-migration.md
A Model Upgrade Is a Memory Migration
Copied records do not prove an agent kept its memory. Model upgrades need directional tests, clean index rebuilds, repair evidence, and rollback.
open artifact → - compile-agent-experience-into-skills-not-memory.md
Compile Agent Experience Into Skills, Not Memory
A six-check promotion contract for turning repeated agent experience into scoped, tested, versioned, observable, and reversible skills.
open artifact →