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

In the realm of search engine optimization (SEO), businesses are constantly trying to navigate a complex landscape. While some strategies can genuinely enhance visibility, many popular tips circulating online often lack substantial backing. One such trend, known as "content chunking," has recently come under scrutiny. In a recent episode of Google’s 'Search Off the Record' podcast, experts John Mueller and Danny Sullivan discussed the pitfalls of this method, specifically when it comes to tailoring content for large language models (LLMs) like Gemini. The practice involves breaking down articles into smaller, bite-sized sections, which some believe will make the content more appealing to AI bots. However, this approach may not yield the desired results. Sullivan highlighted that the notion of creating short paragraphs and numerous subheadings formatted as questions for LLMs is fundamentally misguided. He stated, "One of the things I keep seeing over and over in some of the advice... is that turning your content into bite-sized chunks is beneficial because LLMs prefer it that way. So… we don’t want you to do that." This discussion, which starts around the 18-minute mark of the podcast, emphasizes the importance of prioritizing human readers over algorithms. Sullivan revealed that he has consulted with Google's engineers to confirm that the key to ranking well on Google remains focused on producing valuable content for people, not just machines. Ultimately, human behavior—what users choose to click on—plays a significant role in Google’s ranking algorithms, reinforcing the idea that quality content will endure in the long run.