What is LLM Optimization (LLMO)?
LLM optimization is the practice of structuring a website's content and metadata so language models can accurately understand, summarise and represent it. It covers machine-readable facts, consistent entity data, extractable writing, and files such as llms.txt that give models a curated summary of a site.
Understanding LLM Optimization (LLMO)
The problem LLMO addresses is misrepresentation as much as absence. A model asked about a company assembles an answer from whatever it retrieved, and if the site never states plainly what the company does, where it operates and what it charges, the model infers — and inference produces confident, wrong summaries that then circulate.
The fixes are unglamorous. State the facts explicitly somewhere machine-readable: structured data with a stable entity identity, an about section that defines the business in one sentence, service pages that name the service rather than gesturing at outcomes. Keep those facts identical across the site and off it, because contradiction between two sources is resolved arbitrarily.
llms.txt is an emerging convention: a markdown file at the site root giving models a curated, plain-text map of what the site contains and what the organisation does. Adoption is not universal and it is not a ranking factor, but it costs almost nothing and it is the only place you get to state your own summary in the model's preferred format rather than hoping it infers a good one.
Key points
- Prevents misrepresentation, not just absence, in AI answers
- Explicit machine-readable facts beat inferred ones
- Entity consistency across the site and off it is foundational
- llms.txt offers a curated site summary in a model-friendly format
- Contradictory facts across sources get resolved unpredictably
Where this gets oversold
llms.txt is a convention, not a standard, and support is inconsistent. Treat it as cheap insurance rather than a strategy — the structured data and entity consistency underneath it do the real work.
Related terms
LLM Optimization (LLMO) — related questions
What is llms.txt?
A markdown file at a site's root that gives language models a curated summary of what the site contains and what the organisation does. It is an emerging convention rather than a standard, and support varies, but it costs little to publish.
How do we stop AI from describing our business incorrectly?
State the facts explicitly in structured data and plain page copy, keep them identical everywhere the brand appears including third-party profiles, and remove outdated descriptions. Models infer when facts are missing, and inference is where wrong summaries come from.
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