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8 guides

SEO and AI Search Guides

AI search generated a large amount of advice very quickly, and a lot of it was published before anyone could test it. The guides in this cluster try to separate the parts that are documented by the platforms from the parts that are inference.

What is documented is narrower than the advice suggests. Structured data can make a page eligible for certain result types; eligibility is not selection, and Google removes support for result types periodically. llms.txt is read by some AI systems and explicitly not used by Google, which makes it cheap to publish and dishonest to sell as a lever. Content in server-rendered HTML is more reliably available to crawlers than content assembled by client-side JavaScript, and that has been true for a long time.

What is not documented is why any specific answer cited any specific source, and no one outside those systems can tell you. Anything written with confidence about citation mechanics, including anything here, is a description of observed patterns rather than of the rules.

The practical throughline is that content which answers a question directly, in HTML, with something in it the other sources do not have, is the part that survives every change to how results are assembled. The rest is hygiene worth doing and not worth overclaiming.

How we source, date, and correct what we publish is written up in our editorial and evidence policy.

Every guide in this topic

Past the reading stage?

These guides describe the decision. If you have made it and want the work scoped against your own site, the commercial terms, acceptance criteria, and exclusions are on one page.

See the editorial policy