this works fine for like 2-3 small instruction sets. once you start getting to scale of a real enterprise system, the AI falls down and can't handle that amount of context. It will start ignoring critical pieces or not remember them. And without constant review AI will start priotizing things that are not your business priority.

I don't agree they have solved this problem, at all, or really in any way that's actually usable.

What I'm saying is, don't get to thinking that the memory problem is some kind of insurmountable, permanent barrier that's going to keep us safe. It's already being addressed, maybe crudely at first, but the situation is already much better than it was - I no longer have to bring the model up to speed completely every time I start a new session. Part of this is much larger context windows (1M tokens now). New architectures are also being proposed to deal with the issue, as well.