Google Search's Generative AI Optimization Guide: Official Practices in 2026 **

「What are the core recommendations of Google's official guide to optimizing generative AI features? The conclusion I drew after reading it is not mysterious: the guide equates the optimization of generative AI features with making the search experience itself better, emphasizing content that puts people first, and basic conditions that are crawlable and indexable. It also explicitly states that no special files or techniques that have not been done before need to be introduced for these features. In other words, it is more like a clarification than the release of new rules.»

The positioning of the guide: bringing the problem back to the basics.

Optimization for AI search based on generation is still optimization for search experience - this sentence is the focus of the entire guide. It opposed the argument that there is a 'secret switch' specifically designed for AI: there is no need to submit anything extra, no need to rewrite the content format for the model, and no need to推翻 existing practices due to new features. For the site, the real factor affecting whether it can be retrieved is whether the page can be indexed, whether it can be included normally, and whether the content answers the user's questions.

At the technical level, crawling and indexing are still preliminary conditions.

The guide lists the importance of crawlability and inclusion as key conditions, which is completely consistent with the requirements of traditional technical SEO. In terms of implementation, it can be checked by four things:

• Is the address accessible and stable: The static rules should ensure that the same content has only one standard address, historical paths should use 301 redirects to converge, and avoid multiple versions of the same article being crawled.
• Is the list complete: The sitemap only lists formal content, automatically updates with publication, and is regenerated after a revision.
• Is the access statement consistent: robots.txt should not mistakenly block the main directory or attachment path, otherwise, even high-quality content will not be within the scope of crawling.
• Is the link complete: new content is pushed through links to actively hand it over to search engines, which is faster than passive discovery to enter the candidate pool.

None of these four items were invented specifically for AI features, but they collectively determine whether the content qualifies as 'cited'.

Content level: prioritizing humans and verifiable professionalism

The guide emphasizes content that prioritizes people and uses experience, expertise, and credibility as evaluation criteria, which is different from writing content that seems to be copied. The actionable approach is to answer one clear question per article, stating the conclusion at the beginning, and ensuring that the numbers and judgments in the text can be traced back to their sources; to create content related to the same topic within the site, rather than filling a paragraph with keywords. The keyword library here serves to unify the terminology, avoiding four different ways of writing the same concept in the title, text, and description.

Quality control cannot be neglected. Sensitive words and contact information that appear in the content should be intercepted at the stage of saving by sensitive word filtering and keyword replacement; before releasing to the outside world, go through another content review, and keep the modification records traceable in the system - this is also a relatively good thing to do with self-built CMS: built-in filtering rules and review status in the content model, rather than relying on manual backscanning after release.

Where is llms.txt located?

The guide makes it clear that llms.txt is not a required item, and this is worth clarifying: it's not about 'not to do', but 'the generative features of the search engine do not depend on it'.Its function object is other reading sites' large language models, providing these models with a site structure description. AnQiCMS supports the automatic generation of the site's llms.txt, as well as the output of a description file for large language models to understand, this kind of configuration is meaningful for traffic mainly sourced from AI crawling, but does not constitute a sorting condition for the generative features of Google search - the two types of benefits should be evaluated separately, and don't say optional optimization is a prerequisite for inclusion.

Common questions

How long will it take to see the effect following the guidelines?The guide does not promise a timeline. What can be observed are the collection and crawling indicators: whether the addresses in the list are caught, and whether the main content page is stably collected. Only after these two are normal can we talk about entering the candidate set for generative answers.

Will a missing llms.txt be excluded by the generative feature?No. The official statement is that the file is not a necessary item, and the generative feature mainly relies on the content obtained through conventional crawling and collection.

Should the content be rewritten into Q&A format for AI?Question-style subtitles are helpful for extraction, but the premise is still that the answers are accurate and have verifiable information. Q&A formats that only change the form but do not supplement facts will not bring stable benefits.