If open models on local hardware were more cost effective and competitive, it would be obvious that this is such a superficial approach. (I mean, it still is obvious but what are ya gunna do?)
We would be doing the same general loop, but fine tuning the model overnight.
I still think the current LLM architecture(s) is a very useful local maximum, but ultimately a dead end for AI.
Time will tell. I find the transparency of explicit memory systems paired with the perfect-forgetfulness of LLMs a very pleasurable toolkit. I guess a black-box memory could work too, but at the very least I'd want to be able to rewind and branch. My memory systems are currently git controlled, so it's fairly straightforward.
That's kinda what I mean by the "very useful" part of my description. For all the flaws of the LLMs of today, in some ways context management - nominally a weakness - can be leveraged as a tool.