I think there are plenty ways to "extend the context memory". Compaction is the most obvious: reduce old context to it's core and free tokens. Another tool is session search. The models can look back in parts of the session that got "compacted away" and also in other sessions.

But honestly with 500k or 1m token sessions, I rarely run out of context memory and barely notice any loss of precision after compaction.