How about (3): that in-house utility that you want to re-use across projects because it scratches one itch in precisely the way you want it scratched. Its raison d'être does not disappear from the appearance of LLM, it arguably gets stronger. You want the decisions that went into the library to be encoded in immutable form from the perspective of the contexts working on library dependents.

In the old days, both the investment in the library and the additional cost you'd want to sink on it to consider it publishing quality incentivised to keep it truly internal. LLM code however? It might be slop, but it's accurately groomed slop. Prompting the model to roleplay a public library author might even improve the output when it's in fact not published at all. The investment is low, the extra cost of sharing is low, worst that could happen is others actually picking it up and that would not be bad at all.

Is that spamming the public information universe on the faint hope that perhaps future models might come pre-trained with understanding of your library? Sure. But it's a very different thing from the scenarios described in (1).