The new stuff in the Twitter algorithm is wild.

"author_is_elon", "author_is_republican", "author_is_democrat", etc., are explicit terms that are special cased.

https://github.com/twitter/the-algorithm/blob/7f90d0ca342b928b479b512ec51ac2c3821f5922/home-mixer/server/src/main/scala/com/twitter/home_mixer/functional_component/decorator/HomeTweetTypePredicates.scala

the-algorithm/home-mixer/server/src/main/scala/com/twitter/home_mixer/functional_component/decorator/HomeTweetTypePredicates.scala at 7f90d0ca342b928b479b512ec51ac2c3821f5922 · twitter/the-algorithm

Source code for Twitter's Recommendation Algorithm - twitter/the-algorithm

GitHub
I'm a bit surprised at how many "well, actually, these are just metrics" replies I'm getting that seem to find the spirit of this comment plausible after (just for example), Elon asked why his engagement was dropping and then fired Twitter's most senior remaining engineer for telling him it's not a bug, which was followed by people seeing a lot more Elon in their feed and people also report seeing way more Republican stuff in their feed.

@danluu

I think rank and file engineers don't always have visibility into the fact that metrics are the product goals.

If you have a metric that wants to keep two groups balanced, then software will be written and models will be trained to achieve that goal. Especially if they are a metric tracked by leadership.

The launches that try to achieve this goal often aren't visible in the code base, because the only visible change is a parameter changing from 0.6 to 0.7.