Why it matters
AI programs fail when teams optimize for what gets counted. Shifting from usage metrics to outcome metrics reduces waste, lowers token spend, and makes it easier to prove (or disprove) AI ROI to finance and leadership.
Tokenmaxxing read
Tokenmaxxing is a symptom of missing governance: define one workflow, pick a measurable business result, then track cost per successful outcome. That turns 'more tokens' into 'better unit economics'.
Source takeaway
The article proposes swapping leaderboards for feedback loops: pick a specific AI-assisted workflow, measure downstream results, and tie adoption to a concrete business goal instead of broad 'everyone must use AI' targets.
