With the million-context-window models we never hit compaction, observed over hundreds of sessions. What are you doing that has you hitting compaction regularly?

For me logs can chew through a lot of tokens. And when the agent is trying a bunch of different experiments and then it may need to refer to what happened previously.

Million context models also are still not effective for the entire context size.