A Nostr client with an integrated Small Language Model to handle timeline recommendations would be elite.

It would read through and tag content posted to relays and populate a ‘For You’ feed, without exporting user data to a third-party for profiling. It could also work across nsecs and if the user’s preferences were stored as a .json then it could be shared between the user’s devices. It would need to be sufficiently lightweight to run on local hardware or an iPhone’s neural engine to handle everything privately. Ideally, you would be able to tweak its recommendation via natural language conversations.