The practice of reducing the number of tokens consumed by an agent's configuration and instruction files, so that more of the available token budget is preserved for the actual task, improving output quality and reducing cost.
"You want it to be as token efficient as possible, aka have less text involved. So you wanna shrink down everything that we've just done and set up, get rid of everything you don't need that's in there. There'll be things that are left in there that you don't need. There'll be things that are wordy. Again, you can use AI to do this. You can take your configuration file, give it to an AI, and say, "I'm trying to make this more token efficient, but I still want all of these, all these configurations, measures that I put in place to be in place for this agent. How can I provide this in a more efficient way?""
