So far I've turned off automatic memory creation in every harness I've used. Claude Code sometimes creates some anyway, and I probably delete 95% of them. The memories it creates are almost always relevant only to the specific task that it is currently working on. If it's a task I'll need to do again, then yeah, maybe that's useful. But that isn't the case most of the time, so I delete them to avoid cluttering context.

So the main improvement to memories I'd like to see is better judgment on which ones to create.

The parts about "dreaming" make me think of how agent transcripts contain a ton of information, which I think is currently under-utilized. I'll repeat advice I've seen here a few times: ingest your own transcripts into duckdb (claude code will build that pipeline in about 10 minutes) and do some data analysis on them. Some ideas if you don't know where to start: look at tool call failures to see if you can prevent common ones, check out if you have large cache misses and what causes them, look at various efficiency metrics over time (tokens per $, lines of code per tokens, etc.) with main thread vs sub-agents, etc. I started with this sort of things, and ended up following some threads to interesting insights. For example, I found indications that I tended to make Opus 5.5 / Sol 6.1 divide their work into units that were too small. They have the capacity to work on more stuff at once than older models, and I wasn't really taking advantage of that.