It boils down to information loss in compaction driven by LLM's. Either you could carefully design tools that only give compacted output with high information density so models have to auto-compact or organize information only once in a while which eventually is going to be lossy.

Or you just give loads of information without thinking much about it, assuming models will have to do frequent compaction and memory organization and hope its not super lossy.