LLMO (Large Language Model Optimization)
Definition
LLMO, short for large language model optimization, is the practice of improving how large language models describe and recommend a brand in their answers. It is a synonym for generative engine optimization (GEO) and answer engine optimization (AEO).
The name emphasizes the models rather than the products built on them: ChatGPT, Claude, and Gemini are interfaces to large language models, and LLMO frames visibility work as influencing what those underlying models say when they compose an answer.
The mechanics do not change with the name. Models describe brands from what they can read: their training material plus whatever the live retrieval layer fetches. LLMO therefore reduces to the same jobs as GEO and AEO: correct the facts, be present on the sources engines lean on, structure your own pages so machines can quote them, and measure the answers continuously so you can see whether any of it moved.
