Definition
LLMO (large language model optimization) is the practice of improving how large language models such as ChatGPT, Claude and Gemini describe and cite your brand. No official body defines it, and it is generally used as another name for GEO and AI SEO.
Is LLMO the same as LLMOps?
LLMO is not the same as LLMOps, although both show up when you search for the acronym. LLMOps is an engineering term for running language models in production: deploying, monitoring and updating them. LLMO is a marketing term about how those models talk about you.
How does LLMO work?
LLMO works through two routes into an AI answer: what the model learned in training, and what it fetches live. The levers are different for each, so the first job is working out which route produced the answer you are looking at.
The live route is where most of the practical work sits, because it responds to changes you make now. It depends on the search bots being allowed to fetch your pages and on those pages answering clearly. The training route moves slowly and rewards being described the same way in many places.
What do people get wrong about LLMO?
- Blocking every AI bot at once. Training bots and search bots are separate, so a blanket block can remove you from live answers you wanted to appear in.
- Treating it as separate from SEO. The live route runs on search, so the SEO fundamentals still decide what gets fetched.
Sources
- OpenAI: Overview of OpenAI crawlers
- Anthropic: Does Anthropic crawl data from the web?
- Google Search Central: AI features and your website
Last checked against these sources on 17 September 2026.