Generative engine optimization (GEO)
Generative engine optimization is the practice of making a page likely to be quoted and cited by AI answer engines, which summarise sources rather than sending a reader a list of links.
Also called GEO, AI search optimization.
Generative engine optimization is making your content likely to be used and cited when an AI system answers a question. It matters because the shape of the result changed: an answer engine reads several sources and writes one response, naming a few of them. There is no page two, and being the fourth-best source often means not appearing.
Most of it is ordinary quality work, done with a different reader in mind. A model extracting an answer wants a passage that is true standing completely alone, because it will be lifted away from the page around it. That favours naming the subject rather than pronouning it, answering the question in the first sentence rather than building to it, and stating specifics a summary cannot blur. Definitional and comparative pages do disproportionately well, because they answer a question someone actually asked in a form that can be quoted.
The technical part is smaller than vendors suggest but not nothing: let AI crawlers reach the page, keep the substance in the HTML rather than behind interaction, so an accordion that holds one answer in the DOM at a time is a real problem, mark up structure so a machine can tell a definition from a navigation label, and describe your organisation consistently enough that a model resolves it to one entity.
What does not work is the thing SEO taught people to try. There is no keyword density to tune and no volume play, because there is no ranked list to climb. Thin pages produced at scale are worse than useless here: a model choosing between sources is choosing which to trust, and a page that says less than the others is simply not chosen.
In practice
- A glossary entry answering the question in its first sentence, quoted verbatim by an answer engine.
- An llms.txt file that gives models the definitions themselves rather than only a list of links.
- A page that loses citations because its answers sit inside an accordion that renders one at a time.
Questions
How is GEO different from SEO?
SEO competes for position in a list of links; GEO competes to be the source an answer is written from. That changes what wins. Ranking rewards matching a query and accumulating authority, so there is room for the fourth result. Citation rewards being the clearest, most self-contained, most trustworthy passage on the point, and there is usually no room for fourth place. The foundations overlap almost entirely, since a page a crawler cannot read cannot be cited either.
Does an llms.txt file actually help?
It is cheap and plausibly useful, and it is not a ranking mechanism. The convention is a plain-text file describing your site for language models. No major provider has committed to reading it, so treating it as a lever would be overclaiming. What makes it worth writing is that generating it from the same source as your pages forces the site's claims into one consistent form, and a version carrying the actual definitions rather than only links gives a model substance it can use without parsing HTML.
Can I make an AI recommend my product?
Not directly, and anyone selling that is selling something else. A model recommends what its sources support, so the work is making the sources say something true and specific about you: clear pages about what the product does, consistent naming so the entity resolves, and corroboration off your own site, since a model weights independent mentions more heavily than your marketing. What you influence is whether you are findable and describable. What gets recommended is decided by the evidence.
Related terms
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