Why a Lunch Break Can Change the Cost of an AI Conversation
In this Short, I use a long conversation and a lunch break to explain prompt caching.
The example compares one roughly 150,000-token request with warm cached input against the same input after the cache has expired. The headline's “11x” comes from that API-price example. It is not a promise about a subscription bill or a universal multiplier for every model.
The useful distinction is between reusing unchanged input and processing it fresh. If a service can reuse part of the context, the next request may be handled differently from one arriving after that reuse window has closed.
My practical takeaway is to notice the handoff point. After a long break, ask whether the whole old conversation is still needed. A short summary of the goal, decisions, and next step can be a cleaner starting point.
Cache lifetimes and billing rules vary by product and date. Treat the video as an explanation of the tradeoff, and check the service's current rules before turning its example into a cost estimate.