Something structural has changed in social media. The platforms have shifted from interest graphs — showing content from accounts you follow — to recommendation systems that show you content based on what the algorithm predicts you will engage with, regardless of source.

TikTok built this model. Instagram, Twitter/X, YouTube Shorts, and LinkedIn have all followed with increased recommendation feeds.

The follower count driving creator economics for a decade is becoming less relevant. A creator with 500 highly engaged followers whose content consistently triggers the algorithm now reaches more people than one with 50,000 followers whose content performs averagely.

The old model: post consistently, grow followers, reach grows with them. The new model: post content that performs well algorithmically, and reach scales with performance regardless of follower count.

The algorithm-over-followers model reduces the follower disadvantage that previously made breaking through nearly impossible. A new account can generate significant reach if the content performs well. The bottleneck is no longer followers — it is algorithmic performance.

Algorithmic reach is decoupled from relationship. A viral recommendation builds momentary reach without the durable relationship a follower represents. The spike of views does not translate to a stable audience unless there is a conversion mechanism — an email sign-up, a specific reason to follow.

For creators building sustainable businesses, algorithmic reach is the top of a funnel that needs a bottom. The email list is that bottom.

Social platforms are becoming television with personalised channel guides. The strategy that worked when they were friend networks — grow followers, rely on follower reach — is being supplanted by content quality and algorithmic optimisation. The direction is clear enough to plan around now.