Cognition targets tokenmaxxing with AI efficiency grading system

Cognition, the startup behind the autonomous coding agent Devin, built an internal system that grades engineers on how efficiently they use AI. The best performers then get higher spending limits. How the grading actually works Cognition converts each completed Devin session into an estimate of equivalent human engineering hours. Those estimates were validated against feedback from 126 users across 258 sessions. On held-out data, meaning sessions the model had not been trained on, the estimates showed a log correlation of 0.74 with what users reported. The efficiency score comes from basic division. Take the human-equivalent hours a session produced, then divide by what that session cost in tokens and spend. Spending limits that work like credit lines Engineers who hit defined productivity quotas see their spending limits rise dynamically. That flips the logic of tokenmaxxing on its head. Under the old approach, heavy token use was the signal of a power user. Under Cognition’s model, heavy token use with little to show for it is a red flag. The system went live with customers in mid-2026. It was publicly detailed in reports published on October 15 and 16, 2026. Alongside the gradin...