This one is different.
It gathers content through Superfeedr, stores the content in an ArangoDB database, processes it with scikit-learn, huggingface transformers and all that. The user interface is written in Python w/ aiohttp and is all SSRed. It runs as fast as a desktop application, is accessible on my tablet from anywhere through Tailscale, and doesn't have any loading spinners because it is too fast for that.
The primary interface looks like TikTok for text (it shows me one thing at a time that I classify) but there are some other rudimentary screens for viewing lists of classified content. It scores 73% on a metric that TikTok gets 80% on with a very simple model so I feel like I am not doing so bad.
On a good day it ingests 1200 articles, proposes to show me 300, maybe I really see 200.
If there was one glaring deficiency it's that Superfeedr is only cost effective for high volume feeds (say arXiv CS papers or The Guardian newspaper), I couldn't afford to subscribe to 2000 blogs that publish once a week.
There are many directions to improve it but the most interesting ones are to move away from the "non-social social media" use case and towards ones that support "filter 5000 abstracts from PubMed", "filter through a huge number of profiles looking for sales prospects/possible employees/etc."
I'm using my own RSS-to-Email service https://feedmail.org but I've also used https://blogtrottr.com/ in the past.
After Google Reader I used Feedly for years, even ponying up for a Pro subscription. But I was forced out as they capped on sub total (even as a Pro customer) and I was unable to add new feeds & the tools to identify and prune "dead" feeds (even there, I treat my RSS pool as a stream to wade in when needed / desired and didn't want to delete even inactive feeds, just feeds that got hijacked by spam farms). So I wrote my own.
Initially had grandiose vision of opening it up to anyone but it needs some UX work 1st (and a better DB model than a SQLite DB on a shared host lol).
I don't read every entry
I don't hit it every day
But it's what I use