If I were to write ip a quick history of the Warpcast feed algo, what would you be most interested in?

Technowatermelon. Elder Millenial. Building Farcaster. 

nf.td/varun

How does algo react to “breaking/just-in” trends changes?
I am a noobie at ranking but can assume that in a non-ML algo you introduce time decay and while the “topic” has not even started decaying and more and more people engage with it, it rank skies up to the roof.

But in ML-based feed algos I assume “feeds” are prepared beforehand- “feed_1”, “feed_2” etc.
And if so, is there some kind of extensive workload that the algorithm is experiencing when a “just-in” trending cast shows up that must be seen?

As an example, in the “other” platform news about an “earthquake” or “missile attack” appear almost instantly, at nearly at the first three posts.
Is it simply because lots of people post about it?
Thanks!