HOW TO FIGHT CLICKBAIT: META, LINKEDIN, & YOUTUBE CASE STUDIES

Summary from the TLDR Marketing newsletter

Feed ranking is quietly moving from rewarding what gets clicked to rewarding what a post is actually about, and the three largest platforms landed on three different architectures for it. LinkedIn replaced five separate retrieval systems with a single language-model dual encoder that serves its whole feed through nearest-neighbor search. Meta went the other way on Instagram, keeping over a thousand specialized models in a staged funnel so engagement, diversity, and integrity stay independently tunable. YouTube's PLUM system skips a search index entirely, generating a video's identifier straight from a language model.