Google: Don’t make “bite-sized” content for LLMs if you care about search rank (arstechnica.com)

In a recent episode of Google’s Search Off the Record podcast, Google representatives John Mueller and Danny Sullivan made a crucial statement regarding search engine optimization (SEO) strategies for content aimed at large language models (LLMs). They advised against the increasingly popular practice of "content chunking," which involves breaking information into bite-sized paragraphs and sections. This method aims to make content more appealing to AI systems like Gemini but, according to Sullivan, is based on a misunderstanding of how Google evaluates content for search ranking. The significance of this discussion lies in its reaffirmation that creating content for humans—rather than aiming for algorithms or AI ingestion—is the most effective way to achieve good search rankings. Sullivan emphasized that Google’s ranking signals are closely tied to user engagement and behavior, such as what users choose to click on, rather than adhering to trending SEO gimmicks. This reinforces the idea that thoughtful, human-centric content remains key to long-term visibility and success in search engine rankings, urging content creators to prioritize quality over adherence to fleeting trends.