LLM SEO | Definition

Publisher note

All ten sites in this network are published by Bay Area AEO. They cover answer engine optimization in the Bay Area from ten angles and link to one another so readers can move between related topics.

The model-facing practice. Work aimed at the language model itself: what it has absorbed about a business, and what it can find when it searches.
The source-facing practice. Work aimed at the sites a model reads and cites, on the reasoning that a business described well in those sources will be described well in answers.

What a language model is, for this purpose

A large language model is the program that writes an assistant's reply. It has learned patterns of language from a large body of text, and when it answers it produces new sentences one piece at a time. For a local business the model matters in two ways. It may already carry some general impression of the business from what it learned in training. And, more often for local questions, the assistant pairs it with a search step that fetches current pages, so it can write from fresh sources.

The two routes into an answer

LLM SEO is named for the model, but most of its work happens upstream, in the sources. The definition Bay Area AEO gives says so outright: the large language models behind AI assistants, and the sources they learn from and cite. The two routes look like this.

Table. Two ways a business reaches a language model's answer.
Route	How it works	What helps
Learned	The model absorbed facts about the business during training.	Long-standing, consistent descriptions across many reputable sites.
Retrieved	The assistant searches, reads current pages, and writes from them. Most local recommendations come this way.	Readable pages, accurate listings, recent reviews, mentions in sources the assistant trusts.

The retrieved route moves faster. Bay Area AEO's published timeline reflects that: listing and data fixes can start showing up in AI answers within a few weeks, because many assistants pull live information, while content and reviews build over two to four months, as do third-party mentions.

Learning from and citing

The phrase “learn from and cite” names two different relationships. A source a model learns from shapes its general sense of a topic. A source it cites is one it read for this answer and credits, sometimes with a visible link, as Perplexity does with numbered citations. LLM SEO tracks the second closely because it is observable. When Bay Area AEO runs a client's prompt panel each month it records which sources the AI cites, which tells the owner which directories, guides or pages the models are leaning on for that question. See listing citation vs AI citation for the two senses of “citation”.

Letting the models read

A practical first check in any LLM SEO work is whether AI crawlers can fetch the site at all. Each AI company runs its own crawler, such as GPTBot, ClaudeBot or PerplexityBot, and a site's robots.txt file decides which may read it. Bay Area AEO's own guidance is that a new website is usually unnecessary; it works with the existing site and adds what AI needs. Where a site blocks AI crawlers or is very hard to read, the agency says so and recommends the smallest fix.

What an owner can check in an afternoon

Some of LLM SEO is technical, but its first questions are not. Ask two or three assistants the question a customer would ask, in the customer's words, and note whether the business appears and how it is described. Read the description against the business's own facts: the services named, the neighborhood, the hours. Where an assistant shows its sources, note which sites it used. Then look at those sites. If a directory the model leans on carries an old phone number or a retired service, that is the fix with the shortest path into the answer.

Bay Area AEO turns that afternoon exercise into its free AI visibility check: the questions customers ask, what ChatGPT and Gemini, Perplexity and Google's AI say today, and a walkthrough of what AI currently says about the business and its competitors. The paid work then repeats the same questions monthly, so the owner can see which fixes reached the models.

Usage

LLM SEO is the most technical of the five names and the most common among people who build with these models, which fits a region where many of them work. Bay Area AEO's South Bay page notes that the South Bay is where a lot of the AI tools now recommending local businesses were built. For a Cupertino orthodontist or a Mountain View electrician, the name matters less than the result: a model that can find the practice, read its facts and cite a source that vouches for it.

Within this dictionary LLM SEO is treated as a synonym of answer engine optimization with a technical accent. Use it when the conversation is about how the models read and retrieve; use AEO when it is about the customer's question and the answer that comes back.