Why it matters
The talk's own numbers, latency down ~23%, cost down about a fifth, scaling oscillations cut 5x, are exactly the infra-cost tradeoffs tokenmaxxing readers track for any always-on AI or agent service.
The tokenmaxxing angle
Not about LLM tokens directly, but the same optimization problem: predicting load instead of reacting to it. The approach (add capacity ahead of the spike) maps directly onto right-sizing agent infra spend.
From the organizers
Speaker is Shalini Sudarsan, DevOps Engineering Leader at KinderCare Learning Companies; she reports latency down ~23%, cost down about 20%, and oscillations cut from 15/hour to 3/hour.