Longer term it gets more interesting.
Assuming we can solve long (approaching infinite) context, and solve the issues with reasoning over long context that LangChan correctly identified[1] then it becomes a cost and performance (speed) issue.
It is currently very very expensive to run a full scan of all knowledge for every inference call.
And there are good reasons why databases use indexes instead of table scans (ie, performance).
But maybe we find a route forward towards adaptive compute over the next two years. Then we can use low compute to find items of interest in the infinite contest window, and then use high compute to reason over them. Maybe this could provide a way forward on the cost issues at least.
Performance is going to remain an issue. It's not clear to me how solvable that is (sure you can imagine ways it could be parallelized but it seems likely there will be a cost penalty on planning that)