AI Skill 1 of 5

Translate Organizational Goals into Agent-Actionable Specifications

Autonomous agents optimize for whatever metrics they are given, which means poorly specified goals produce confidently wrong outcomes at scale. A proficient practitioner defines strategic objectives qualitatively before selecting quantitative measures, specifies constraining metrics that balance each other, and builds health metrics and stop rules that detect divergence from intent. This is the entry point for the entire alignment chain because every downstream capability depends on goals being specified correctly.

Proficiency Level

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Measurable Behaviors

Each behavior is directly observable and can be assessed through manager observation. In Admire, these drive evidence-based skill tracking.

Define Strategic Objectives Qualitatively Before Quantifying

Articulates what the organization is trying to achieve in qualitative terms before selecting quantitative metrics, ensuring goal-setting starts with intent rather than numbers.

Specify Constraining Metrics That Balance Each Other

Defines multiple metrics that constrain each other, preventing agents from maximizing one dimension at the expense of others.

Anticipate Perverse Incentives in Agent Specifications

Proactively identifies ways an agent could technically satisfy objectives while violating the spirit of the goal through red-team thinking applied before deployment.

Establish Trade-Off Priorities Across Competing Objectives

Defines explicit priority rankings for situations where objectives conflict, giving agents clear guidance on which goals to favor.

Build Health Metrics and Stop Rules for Intent Divergence

Creates health metrics and automatic stop rules that detect when agent behavior diverges from organizational intent and trigger human review.

This is a preview of how behavior tracking works in Admire

Mastering Agent-Actionable Goal Specification

A practitioner who excels here starts every goal-setting conversation with qualitative intent before selecting metrics. They routinely red-team their own specifications by asking how an agent could technically satisfy the objective while violating its spirit. Their specifications include constraining metrics, explicit trade-off priorities, and automatic stop rules that trigger human review when behavior diverges from organizational intent.

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