Dave Sharrock and Peter Maddison break down what's driving the shift to AI token economics, why the old "$20 per user" budget model is breaking down, and why usage alone is the wrong thing to optimize for. They dig into the pattern showing up across organizations, where a small share of users account for half the token spend, and why chasing that number down misses the real question: what value did that spend create? The conversation covers KPI traps, model selection tradeoffs, and how to build the kind of honest, open culture that lets you actually govern AI spend without punishing your best people.
This week's takeaways:
- Token usage by itself is a bad KPI once your organization has moved past early AI adoption, because it stops measuring exploration and starts driving the wrong behavior.
- The 10% of users driving 50% of the token spend aren't automatically the problem. Some are generating outsized value, and the only way to know is to ask them directly.
- Managing AI cost well means pairing spend visibility and caps with an honest conversation about the value that spend is producing, not just sorting a table by usage.
0:00 Welcome And Token Economics Setup
0:56 The Flat Fee Token Paradise
3:01 Why Vendors Shift To Consumption
3:37 The Water Meter Moment
4:44 More Tokens Do Not Mean Value
5:29 KPI Traps And The 10% Effect
6:50 Finding Impact In Complex Systems
8:57 Controls Caps And Spend Visibility
10:57 Build An Honest Culture Around Usage
12:14 Model Choice Guidelines And Tradeoffs
14:06 Budgeting Forecasting And Maturity Steps
15:35 Key Takeaways For CFOs And Teams
17:25 Closing And Subscribe Reminder
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