[yen223]

Their autocomplete experience is decent, but I've gotten the most value out of Cursor's "chat + codebase context" (no idea what it's called). The feature where you feed it the entire codebase as part of the context, and let Cursor suggest changes to any parts of the codebase.

[skp1995]

ohh inserting.. I tried it on couple of big repos and it was a bit of a miss to me. How large are the codebases on which you work? I want to get a sense check on where the behavior detoriates with embedding + gpt3.5 based reranker search (not sure if they are doing more now!)

[yen223]

Largest repo I used with Cursor was about 600,000 lines long

[skp1995]

that's a good metric to aim for... creating a full local index for 600k lines is pretty expensive but there are a bunch of huristics which can take us pretty far

- looking at git commits - making use of recently accesses files - keyword search

If I set these constraints and allow for maybe around 2 LLM round trips we can get pretty far in terms of performance.