What is LLM SEO, and how does it work?

LLM products use web content in two ways. During training, models learn associations between names, categories, and facts from large text collections. At answer time, many products retrieve current pages through search and write an answer from them, often with citations. LLM SEO targets both: being described accurately and consistently across the web, and being retrievable and quotable when an answer is written.

Typical tasks fall into four groups.

GEO, generative engine optimization, is the term from the 2023 research paper and is the most common synonym. AEO, answer engine optimization, emphasises being the direct answer, including in classic features such as featured snippets. SEO remains the foundation: LLM products mostly find current content through search indexes, so pages that cannot be crawled or indexed are invisible to them too. Choose one name for your team and measure both search and AI visibility.

This question from People Also Ask is about a different meaning: using an LLM to do SEO tasks. Any of the leading models can cluster keywords, draft outlines, and analyse exports when given real data; the choice matters less than providing accurate inputs and checking outputs. Our guide to using ChatGPT for SEO covers the workflow.

Check AI crawler access with our free checker, fix the opening paragraphs of your five most important pages so they state facts plainly, and write a prompt set to measure a baseline. Then read our guide to optimising content for LLMs for the writing techniques. SerionFlow builds new pages in this answer-first form behind quality gates; it does not replace the mention work, which happens on other sites.