> At the slightest touch of the reins, he felt a familiarity that shook him...
Ah... Some good, old, pre-AI journalism slop.
Oh the countless times a universities press release has been turned into four pages describing the smell of coffee some scientist inhales on their way through campus...
Not sure if this is the right abstraction: The recall seems to need a search term.
But would it not be more sensible to assume that the full conversation (+ system parts) CAN inform the recall and some neural network picks the right memory bits?
So my fear would be that something like this, if adapted, drags the development into a local optimum that is hard/impossible to get out of.
Good point. I think you’re right. We need more rigor for the AI, which would actually help code generation, I suspect. Included batteries are for humans and AIs don’t need convenience.
From my experience what domain experts are often missing - and at least currently this is also an area where LLMs fail - is the ability to model data and interfaces in a sustainable way and factor in team and domain boundaries.
This is a failure mode that senior engineers have seen a few times throughout their career: They know how certain choices will play out over time... and the kind of problems and roadblocks these choices might cause.
(To state it in AI lingo:)
It's not about the best measure for "amount of code".
It's about wether "amount of code" is a good metric to begin with.
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