Arthur, question from your GitHub + essay:

In GitHub you show stats that say a "cache hit" is 200ms and a miss is 1-2s (LLM call).

I don't think I understand how you get a cache hit off a novel tweet. My understanding is that you

1) get a snake case category from an LLM

2) embed that category

3) check if it's close to something else in the embedding space via cosine similarity

4) if it is, replace og label with the closest in embedding space

5) if not, store it

Is that the right sequence? If it is, it looks to me like all paths start with an LLM, and therefore are not likely to be <200ms. Do I have the sequence right?