4 ms·
OT but its interesting that none of the harnesses today use embeddings but just simple grep. I would not have predicted this
by simianwords 2mo ago
OT but its interesting that none of the harnesses today use embeddings but just simple grep. I would not have predicted this
- imtringued 2mo agoOk? I'm not seeing how that is interesting, you're exclusively focusing on coding which requires precise substring locations. Google is basically almost entirely driven by embedding models now.
- simianwords 2mo agoAnd why do you think coding didn’t benefit from embeddings? It was attempted many times and the industry gave up. I find this interesting because practically no one is doing RAG on thier personal data which is something I wouldn’t have expected.
- owen-hill 2mo ago[flagged]
- marginalia_nu 2mo agoA lot of this is due the size of the corpus. Grep falls apart for severely underspecified queries, which is the difficult part of web search. For any given query in web search there can be several millions of candidate results. You can get good results with FTS as well, but just finding phrase matches is inadequate, you need more ranking signals to find relevant results. When Claude is looking for a function in your code base, it needs to sift through dozens of matches. This is not hard, and anything beyond grep is likely not worth the effort.
- anthonypasq 2mo agocursor still uses embeddings and theyve found it works better than just grep https://cursor.com/blog/semsearch https://cursor.com/blog/semsearch
- simianwords 2mo agothey don't use it anymore which adds to my point that people tried it and largely gave up
- anthonypasq 2mo agosource? nothing im seeing on the internet agrees with you https://cursor.com/data-use https://cursor.com/data-use their data use policy from july 2026 explicitly mentions embeddings