As Goodhart's law states, "When a measure becomes a target, it ceases to be a good measure". From an organizational management perspective, one way to partially work around that problem is by simply adding more measures thus making it harder for a bad actor to game the system. The Balanced Scorecard system is one approach to that.

https://balancedscorecard.org/

This extends beyond AI agents. I'm seeing it in real time at work — we're rolling out AI tools across a biofuel brokerage and the first thing people ask is "what KPIs should we optimize with this?"

The uncomfortable answer is that the most valuable use cases resist single-metric optimization. The best results come from people who use AI as a thinking partner with judgment, not as an execution engine pointed at a number.

Goodhart's Law + AI agents is basically automating the failure mode at machine speed.

Agreed, Goodhart’s Law captures the failure mode well intentioned KPIs and OKRs may miss, let alone agentic automation