Relying solely on a chronological feed of followed accounts limits growth. The "For You" page, despite its pitfalls, is a powerful discovery tool. The ideal strategy involves using both: a curated feed for engagement and a discovery algorithm for finding new, compelling voices.

Social media algorithms amplify negativity by optimizing for "revealed preference" (what you click on, e.g., car crashes). AI models, however, operate on aspirational choice (what you explicitly ask for). This fundamental difference means AI can reflect a more complex and wholesome version of humanity.

Unlike platforms like YouTube that merely host user-uploaded content, new generative AI platforms are directly involved in creating the content themselves. This fundamental shift from distributor to creator introduces a new level of brand and moral responsibility for the platform's output.

The next evolution, the Generative Ads Recommendation Model (GEM), aims to fully automate ad creation. Marketers will simply provide an image and a budget, and the AI will generate the entire ad library. This shifts the marketer's primary value from ad creation to optimizing the post-click customer journey and offer.

Gary Vaynerchuk argues that platforms have evolved beyond a follower-based model ("social media"). Now, algorithms dominate, creating an "interest media" landscape where content is surfaced based on a user's demonstrated interests, regardless of whom they follow. This makes the content itself paramount over follower counts.

Platforms are moving beyond engagement metrics like clicks and watch time. The next frontier is optimizing for a user's entire lifespan (LTV) by showing content that increases their long-term value as a consumer, such as educational material that leads to higher-paying jobs and greater purchasing power.

The future of media is not just recommended content, but content rendered on-the-fly for each user. AI will analyze micro-behaviors like eye movement and swipe speed to generate the most engaging possible video in that exact moment. The algorithm will become the content itself.

The future of search is not linking to human-made webpages, but AI dynamically creating them. As quality content becomes an abundant commodity, search engines will compress all information into a knowledge graph. They will then construct synthetic, personalized webpage experiences to deliver the exact answer a user needs, making traditional pages redundant.

AI struggles to provide truly useful, serendipitous recommendations because it lacks any understanding of the real world. It excels at predicting the next word or pixel based on its training data, but it can't grasp concepts like gravity or deep user intent, a prerequisite for truly personalized suggestions.