But I think that probably puts the utility of llms at a much lower level — at the level of syntax, or at least functionality. Naming functions is crucial to developing a nomenclature for a project, so LLMs can't really be useful at that level or higher (except for functions that you don't care about — in which case, why not just write a big procedural blob).
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Yes... correct? I'm much more AI-skeptic than most people here apparently, so I'd agree with the implied premise here that LLM's shouldn't be deployed for any kind of higher-level reasoning than things that are very rote, procedural, and where there's a clear "manual" or "spec" for what they're writing.
For instance, while LLM's are very useful for certain things in science, their utility from my perspective is mostly limited to synthesizing large bodies of literature, occasionally making relevant connections between disparate fields (which can be very valuable), and of course writing code for simulations or math models etc.