Technical SEO for AI search: access, indexing, and structured data

Diagnose the actual failure

Discovery, crawling, indexing, retrieval, and citation are different steps. An accessible page may not be indexed; an indexed page may not be retrieved for a particular question; a retrieved source may not receive a visible citation.

Use the Google technical SEO documentation as a reference for search diagnostics. Record evidence for the step you checked rather than labeling every missing AI mention a technical failure.

A practical handoff for your developer

Check	Evidence to request	Common repair
Public access	HTTP response and visible page content	Resolve server errors, login walls, or accidental blocks
Indexing directives	Rendered robots meta and HTTP headers	Remove unintended noindex from public pages
Canonical URL	Canonical tag on the actual page	Point to the intended public URL
Internal discovery	A real link from a relevant public page	Add useful navigation and contextual links
Sitemap	Important canonical URLs in the generated sitemap	Include new routes and remove retired URLs
Content parity	Visible facts compared with markup	Correct outdated or contradictory values

A sitemap lists URLs for discovery. It is not an instruction to rank them. A canonical tag is a signal about the preferred URL, not a tool for making unrelated pages equivalent.

Check crawler policy by purpose

OpenAI documents separate controls for OAI-SearchBot and GPTBot. Decide search access and potential training access deliberately. Do not assume one setting controls both.

Perplexity’s crawler documentation describes its bot and published IP ranges. If the site uses a firewall or bot challenge, check those layers as well as robots.txt.

Ask your developer to verify legitimate crawler traffic using the provider’s current instructions. A user-agent string alone can be spoofed. Do not disable a site’s security protections broadly just to test a crawler hypothesis.

Use structured data to describe visible content

For an educational guide, Article markup can describe the headline, author, publication date, and modification date. Google’s Article documentation explains supported properties and validation.

The values should match the page. Do not invent an expert author, a review score, or a recent update date. When a business detail changes, update both the visible copy and its structured representation.

Validate the generated HTML, not just the template source. A correct template can still receive missing or malformed content.

Do you need llms.txt or special GEO markup?

Google says it does not use llms.txt and does not require special AI markup. That statement applies to Google Search. Other services may have their own documentation or uses for such files.

Our recommendation is to prioritize working pages and useful evidence before optional files. If someone proposes an AI-specific implementation, ask which system consumes it, where that behavior is documented, and how the change will be verified.

What should be visible without an interaction?

Make the main answer, service facts, headings, links, and source notes available on the page. Search and filtering can improve navigation, but visitors should not need a search query to discover every guide.

For a resource library, give each guide its own URL, link related material, include meaningful metadata, and keep the sitemap aligned with published pages. Avoid producing many near-identical pages simply to cover keyword variations.

Verify after release

Check the live canonical domain after deployment. Confirm status codes, robots rules, generated metadata, sitemap URLs, and any CDN or firewall behavior that a local preview cannot reproduce.

Then use the relevant webmaster tools to investigate indexing. Technical validation establishes that an implementation behaves as intended; it does not establish future visibility. The measurement guide covers that separate observation process.