How AI answers pick sources · Official documentation
Google's own AI search guide lists 5 "GEO" tasks you don't need to do
Google says optimizing for generative AI search is still SEO. In its official guide, one section names 5 things site owners don't need to do for Google Search: llms.txt and special markup, chunking content, rewriting for AI, seeking inauthentic mentions, and overfocusing on structured data.
A whole service category now sells "AEO" and "GEO": writing llms.txt files, splitting articles into AI-sized chunks, adding more schema. Buyers are rarely shown what Google itself says about that work.
We opened the document where Google says it: Google Search Central's guide to generative AI features, last updated 2026-07-10.
Finding 01
Google treats generative AI search optimization as SEO, not as a separate discipline
From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO.
The guide explains that AI Overviews and AI Mode run on Google's core ranking and quality systems. Crawling, indexing and good content remain the standard, so a GEO proposal that skips them is selling a different product.
Finding 02
Files, chunking, rewriting, mentions and schema: Google addresses each one for Google Search
Each line uses Google's own heading. The verdict after "Google:" restates that line's original sentence, shown in the table below.
| Google's heading | Original sentence |
|---|---|
| LLMS.txt files and other "special" markup | You don't need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search (including its generative AI capabilities), as Google Search itself doesn't use them. |
| "Chunking" content | There's no requirement to break your content into tiny pieces for AI to better understand it. |
| Rewriting content just for AI systems | This means you don't have to worry that you don't have enough "long-tail" keywords or haven't captured every variation of how someone might seek content like yours. |
| Seeking inauthentic "mentions" | However, seeking inauthentic "mentions" across the web isn't as helpful as it might seem. |
| Overfocusing on structured data | Structured data isn't required for generative AI search, and there's no special schema.org markup you need to add. |
Finding 03
What the guide expects to last longest is content nobody else could have written
Creating content that people find unique, compelling, and useful will likely influence your website's presence in generative AI search in the long run more than any of the other suggestions in this guide.
The guide calls content built on common knowledge "commodity content" and contrasts it with content only someone with first-hand experience could write.
There is no word count or uniqueness ratio in the guide. The standard it states is the insight and experience a page gives its reader.
Commodity content (for example, something like "7 Tips for First-Time Homebuyers") is often based on common knowledge, which could originate from anyone, and typically adds little unique insight for readers.
So what should change in an AI search proposal?
- List llms.txt and schema under their own purposes, such as agent-facing files and rich result eligibility, not as requirements for Google's AI features.
- Measure the engagement by whether crawling, indexing and snippet eligibility are in place, not by a count of mentions.
- Build pages around what only your company can say: original data and processes you ran yourself.
Methodology
- Google Search Central, "Optimizing your website for generative AI features on Google Search" (updated 2026-07-10) · checked 2026-09-13 · https://developers.google.com/search/docs/fundamentals/ai-optimization-guide
- Google's sentences are quoted verbatim. Only the short verdicts in the figure are our wording.
- The guide is about Google Search. Rules for ChatGPT, Naver and other services are checked separately.