Overview
If you can’t measure it, you can’t improve it. But measuring the wrong things is worse than
measuring nothing—it actively drives bad behavior. These metrics define how we evaluate
whether our AI systems are truly succeeding at their mission.
Key insight: Metrics are indicators, not goals. When a metric becomes a target,
it ceases to be a good metric (Goodhart’s Law). Use these to guide improvement, not to
game performance.
A Living Document
These metrics are not static. As the system evolves, as new challenges emerge, as understanding
deepens, these measurements will need to adapt. Regular review ensures they remain meaningful.
Review Schedule
- Weekly: Technical performance metrics (automated dashboards)
- Monthly: Collaboration quality and ethical compliance review
- Quarterly: Impact assessment and metric framework review
- Annually: Full framework audit and update