What is LLM Optimization (LLMO)?
LLM Optimization (LLMO) is the practice of improving how large language models describe, cite and recommend a brand, both through live retrieval and through what the models learned in training.
By the AIO Automatic team · Last updated
What does LLMO mean?
LLMO, or LLM optimization, focuses on what large language models know and say about your brand. It covers live retrieval, where the model searches the web, and model memory, where it relies on training data. The work is consistent brand descriptions, broad third-party mentions, crawlable content and correcting inaccurate information wherever it appears.
How do you influence what an LLM says about you?
Make your brand easy to retrieve and hard to misdescribe. Allow AI crawlers, publish a clear llms.txt, use one brand sentence everywhere, and earn mentions on sites the models already trust. Over time, consistent information across many sources shapes both live answers and future training data.
| Path | How it works | What you control |
|---|---|---|
| Live retrieval | Model searches an index at answer time | Crawler access, content, indexing |
| Training data | Model learned from past web crawls | Consistent, widespread mentions over time |
Frequently asked questions
Is LLMO different from GEO?
Mostly a different name for the same goal. LLMO stresses model knowledge; GEO stresses generative search results.
Can you edit what ChatGPT says about your company?
Not directly. You change the sources it retrieves and learns from, then measure the shift across repeated prompts.