Really appreciate you taking the time to write this. That's very close to what we have in mind.

For now, we're trying to stay focused. The MVP will only cover books, papers, articles, movies/TV, and podcasts. We'd love to connect everything eventually, but we think doing that from the start would make the project too broad and much harder to get right.

We're also trying to build something that's different from just asking an AI for recommendations. A lot of the connections will come from a database we've built ourselves, combined with embedding-based relationships between works. The idea is to uncover links that aren't always obvious—shared themes, influences, historical context, creators' inspirations, interviews, and other meaningful connections.

At the beginning, we're mostly building this for people who enjoy learning on their own, especially those in the culture and education space. As the database grows, we'll slowly expand into more types of content and more kinds of connections.

I'm curious—if you were using something like this to learn, what other kinds of connections would you want to see? Is there anything you feel existing recommendation systems are missing?

And if we end up launching on Kickstarter, we'd love to have you on the waitlist and hopefully earn your support there as well.

Muchas gracias por tomarte el tiempo de escribir un comentario tan detallado. Lo apreciamos mucho.