I went for a personal newsfeed, agent pulls news form ~100 feeds related to my interests. Then reads all articles for me and orders them by how interesting they might be for me. I specifically asked for vector embeddings, up/down votes (-2..+2), visited status, LLM content evaluation. Probably there are some other mechanisms I didn't even bother to check. It's a work in progress but I can see myself replacing most of my news reading with it. For many news the AI summary, which contains main idea behind the item is enough for me. As a bonus it resolves clickbait and is quite good at it. Also no ads, ever. For sure I need to implement some grouping because when the popular story breaks I have many stories about the same thing with mostly overlapping details. AI merging them would be quite cool.
I also asked AI to extract my interests from my browsing/watching histories of my all accounts. V2 of my newsfeed might utilize that somehow for better results.
Silly thing is I made it in one afternoon with my only motivation of being slightly more annoyed with the web on that day.
When I move it to the server I might consider waking it up periodically to pull and analyze new stories and perhaps notify me if something absolutely great shows up.
There are so many possibilities for tuning it. And I don't need to think how to make it secure (beyond the basics), ultra performant, fitting other people's tastes and so on because this program has audience of one.
How do the vector embeddings fit into the picture?
When I touched it the last time I was a fan of gemma4 https://ollama.com/library/gemma4
Since then I grew really fond of Qwen3.6 (it's super capable in coding against the DOM) so I'll probably try to move to it with the next iteration. https://ollama.com/library/qwen3.6
