The ones I’ve stumbled upon seem to be: switch models based on task complexity, use tooling like ASTs and compression, disable unused MCPs, compact often, be verbose with input to give clear guidance…
I don't think compacting often is good for saving money. It generates more output tokens and then the input is no longer from cache, which is priced differently...typically very differently.
I don't think compacting often is good for saving money. It generates more output tokens and then the input is no longer from cache, which is priced differently...typically very differently.