It occurs to me that we can use LLMs to give better recommendations.
I want this for books.
The goodreads recommendations are crap.
The ton of “new hot books” newsletters I subscribe to are crap.
I want a daily email that makes highly specific recommendations made by an LLM based on:
- The books I am reading and have just read.
- The authors of those books.
- The genres of those books.
- The general areas of interest/study of those books.
- The specific details in my background.
I typically read on topics that interest me right now and I typically read a cluster of books on a topic.
I want to know about more/better books in the cluster.
I typically do this manually with an LLM and a ton of google/amazon/goodread searching, but it can be automated and made better.
Why stop at books?
I want LLM Recommended:
- podcasts and podcast episodes
- movies and tv shows
- bands, albums, songs.
- posts on socials
- websites.
Suck up the consumption exhaust and give me better LLM-based recommendations.
“Consumption Exhaust” sounds cool. And accurate.
I could probably hack this together for books as a cron-bot in Python that uses the Goodreads API and OpenAI API and some carefully tuned prompts.
I may do this.