August 20, 20262026-08-20
When I first started using AI, model quality was what mattered most. I compared which model wrote better code, read long documents more accurately, and reasoned more deeply. But once AI became part of my actual work and my usage grew, my attention shifted. Using AI well now matters as much as being able to keep using it sustainably.
August 5, 20262026-08-05
I knew prompt caching reduced costs. My understanding went about as far as: when you send the same system prompt repeatedly, it gets cheaper from the second request onward.
But the more I thought about it, the stranger it seemed. If caching happens in some relay layer outside the model, then from the model’s point of view nothing is saved. And yet the savings are said to reach 90%. Would that mean most of the cost of using an LLM (Large Language Model) comes not from the model itself but from the layer around it?