Platforms like the massively popular (and still growing) TikTok and YouTube put far less emphasis on friends and social graphs in favor of carefully curated, magical algorithmic experiences that match the perfect content for the right people at the exact right time. This is recommendation media, and it’s the new standard for content distribution on the internet.

In social media, creators have the programming power. As a result, social media is effectively a competition based on popularity, not on quality of content.

the bigger the following, the bigger the potential for distribution and influence.

Built-in distribution for content to social networks has meant that people can share and spread problematic content just as easily as they spread good-natured content.

because content is primarily distributed to clusters of connected people, there is huge potential for echo chambers of groupthink on social media. Diversity of thought is, by design, at a disadvantage in social networks.

Just because people can easily distribute content to their friends or friends of friends doesn’t mean that that content will be interesting or relevant to the consumer.

no platform has been better at exploiting the weaknesses of social media than TikTok, the platform which popularized algorithmic content distribution and gave birth to what I call, recommendation media.

In contrast to social media, recommendation media is not a competition based on popularity; instead, it is a competition based on the absolute best content.

In recommendation media, the best content for each consumer wins.

in recommendation media, content distribution is optimized for engagement. This results in very little waste in a feed, and consumption patterns are highly efficient.

on a platform like YouTube or Instagram which contains billions of pieces of potentially programmable content, programming can occur across a multitude of dimensions, such as any user’s interests, demographic, or location.

in recommendation media, the algorithm is understood to be the final decision maker about what gains traction and what doesn’t.

Where do they turn for that engagement? Other platforms. This is why you often see so much TikTok content being shared to platforms like Instagram, Twitter, and Facebook. Creators are sharing content to networks where they already have audiences.

social networks are simply no longer defensible because the underlying data that powers them, the social graph, has become commoditized.

In recommendation media, the platform with the best machine learning wins.

in order to be able to match the exact right content with the exact right person, a platform needs an ocean of content, including extremely niche content for every person on the planet. The only way to have that much content is to be an open creation platform where users of the platform are able to create on the platform.

As the cost of AI content-creation solutions come down, I expect platforms to create more synthetic media over time to create even more perfect fit content for the right users at the right time.