The short version: X wants your friends back in your feed
X has quietly started pushing a fix for one of the most complained-about feelings on social media: the sense that everyone in your replies is a stranger. The platform is now boosting posts from mutuals — accounts that follow you back — so they show up more often in feeds and conversations.
Nikita Bier, X’s product head, announced the change on the platform itself. He said the algorithm was missing relationship data, which made familiar accounts fade into the background whenever reply sections filled up with randoms.
It’s a small tweak, Bier said. But it could shift how the whole network feels.
What exactly is X changing?
In a post on July 13, 2026, Bier explained: “We’re rolling out a small tweak to boost visibility of your posts to your mutuals (people who you follow back). We noticed this data was missing from the algo and it made your friends appear less in your replies.”
The result, he said, was that reply sections felt more like a battleground than a conversation. With this adjustment, posts should reach mutual followers more reliably. And when those people jump into a thread, their replies should be easier for the original poster to spot among the noise.
Bier thinks this could help groups form around shared interests. That’s basically how social networks worked a decade ago — you followed people, and you saw them. But modern feeds are built on predicted behavior, not deliberate choices. An angry response from a stranger still counts as activity, even when it makes the whole experience feel hostile.
Giving existing connections more weight could redirect some of that attention. Whether you’ll notice the difference depends on how much influence this signal actually gets inside the ranking system.
Why did the AI need help finding friends?
Here’s the strange part. X’s published algorithm code already includes tools for understanding mutual relationships. A May 2026 release added mutual-follow graphs to user context, along with scores attached to posts being considered for recommendation.
So the data was there. The announcement implies it wasn’t reaching the ranking process that mattered, or it wasn’t affecting results the way it should. X hasn’t explained where the disconnect happened — whether it was an omission, a weighting problem, or something else entirely.
That gap matters because X’s recommendation engine leans heavily on Grok-based engagement predictions. The model estimates whether a post will earn replies or clicks. Those predictions can surface content that keeps people active, but activity doesn’t tell you whether a conversation is welcome. An algorithm can learn that arguments generate reactions without ever understanding why everyone involved is miserable.
The engagement trap
This is the core tension. Social platforms optimized for engagement will always find that outrage performs well. It’s not that the algorithm hates you — it’s that it doesn’t know the difference between a heated debate and a toxic dumpster fire.
By weighting mutuals more heavily, X is trying to reintroduce a signal that used to be foundational: the social graph. It’s a small acknowledgment that raw engagement numbers aren’t the same as meaningful interaction.
Will X actually feel friendlier?
Too early to say. X hasn’t disclosed how strong the boost is, whether it extends beyond replies and feeds, or how success will be measured. The company has described the desired outcome without demonstrating it.
Recognizable names in your replies could make conversations feel less random. But a ranking adjustment won’t remove outrage bait or hostile users. It just tilts the odds slightly in favor of people you already know.
Teaching an algorithm who your friends are is relatively easy. Teaching it that every argument isn’t valuable engagement — that’s the hard part, and no single tweak fixes that.
For now, the change is worth watching. If it works, other platforms might follow. If it doesn’t, X will quietly move on to the next experiment. Either way, the fact that a major social network is admitting its algorithm lost track of friendship is a telling moment.
