LLM Optimization (LLMO)

LLM Optimization is an umbrella term for influencing what large language models say about a brand. It covers two different routes into an answer. One is retrieval: an assistant searches the web, reads pages and quotes them, which is where GEO and AEO work applies. The other is what a model already carries from training: whether it associates your brand with a category, describes your product accurately, and puts you on a shortlist when nobody has named you.

The term has no single authoritative origin and is used loosely, often interchangeably with GEO. The useful distinction is scope. LLMO asks about your presence across every way a model forms an answer, including the parts no single page controls, such as how consistently the wider web describes you.

The two routes are governed separately, and the controls are now explicit. OpenAI runs one crawler that gathers training data and a different one that surfaces sites in ChatGPT search, and a site can allow one while refusing the other. Treating AI crawlers as a single on or off switch can remove a brand from live answers by accident.

Retrieval-side work has evidence behind it: research on generative engines found that making content more quotable measurably raised its visibility in their responses. Google, for its part, says there is no special optimisation needed to appear in its AI features beyond sound search practice, which keeps LLMO grounded in fundamentals rather than tricks.

• OpenAI says OAI-SearchBot is used to surface websites in search results in ChatGPT’s search features, and sites opted out of OAI-SearchBot will not be shown in ChatGPT search answers.OpenAI, Overview of OpenAI crawlers, 15 Sept 2026
• OpenAI says GPTBot crawls content that may be used in training its generative AI foundation models, and disallowing GPTBot indicates a site’s content should not be used for that training.OpenAI, Overview of OpenAI crawlers, 15 Sept 2026
• Up to 40%The GEO paper reports that its methods can boost visibility by up to 40% in generative engine responses.Aggarwal et al., GEO: Generative Engine Optimization (KDD 2024), abstract, 15 Sept 2026
• Google says there are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary.Google Search Central, AI features and your website, 15 Sept 2026

1. 1

   Ask the assistants your buyers use to describe your company and to recommend tools in your category, and record where the answers are wrong, vague or missing you.

2. 2

   Decide your crawler policy agent by agent: which bots may use your content for training, and which may fetch pages for live answers. Write it into robots.txt deliberately.

3. 3

   Fix the sources models learn from and retrieve: your own product, pricing and about pages first, then consistent descriptions on review sites, directories and partner pages.

4. 4

   Publish the specific facts assistants get wrong in plain, quotable form on a page you control, with the date they were last checked.

5. 5

   Re-run the same prompts on a schedule and track how often you are named, rather than judging from one answer.

• Blocking every AI crawler to protect content, then wondering why the brand never appears in ChatGPT search. Training and search crawlers are separate choices.
• Chasing a single prompt. Model answers vary between runs and between users, so a one-off win or loss is weak evidence either way.
• Assuming training data can be edited quickly. What a model learned changes only with new training, so the fast lever is usually retrieval, not the model’s memory.

Generative Engine Optimization (GEO)

GEO concentrates on the content generative engines retrieve and quote. LLMO includes that and also what models say about you from training, without fetching anything.

Answer Engine Optimization (AEO)

AEO is about pages being extracted as the direct answer by search features and assistants. LLMO is the wider question of how a brand is represented across language model outputs.

1. 1OpenAI, Overview of OpenAI crawlers read 15 Sept 2026
2. 2Aggarwal et al., GEO: Generative Engine Optimization (KDD 2024), abstract read 15 Sept 2026
3. 3Google Search Central, AI features and your website read 15 Sept 2026