To determine whether documentation meaning changed, a raw HTML diff is insufficient. Snapshot an open URL, normalize noisy elements, compare extracted text and structure, then manually review candidate meaningful fragments. This item reports a methodology and pilot protocol, not a quantitative result: numeric observations must be collected by actually running the experiment.
Public documentation for seven surfaces describes different access and search modes but no shared source-selection formula. Measure accessibility, discovery, links, and citation as separate events.
A web-server log proves that a resource was fetched by a particular request. It does not prove retrieval, use of a fact, a displayed citation, or a user click. Each claim requires its own chain of preserved artifacts.
Google separates eligibility for AI answers from actual selection, different systems use different domains, and a scientific experiment shows reputation effects in a narrow task. Google Play adds a separate app-availability boundary, while Perplexity separates the model from the search surface. These are measurement boundaries, not universal promotion recipes.
Five signals this week show that AI visibility is several different events: Google may separate third-party content from a domain’s reputation, Alice can receive products through a commerce system, Grok Bot searches inside X, and large and field measurements separate citations from referrals. None is a universal recipe.
Google Preferred Sources is a personalized lever for an already interested reader, not a general ranking factor. Grok 4.6, GEO-text detection, Reddit decline, and connector errors show why measurements must be versioned and checked.
The week did not reveal a universal growth factor, but it established four practical limits: conversation context changes answers, one run does not cover all sources, more citations can reduce evidential quality, and page provenance is not a recipe for generating content.
Being included in an answer, ranking among named entities, evidential correctness, and a user action cannot be reduced to one metric. This week’s studies support measuring the stages separately and comparing page types within a specific intent.
A site-access policy should describe a specific crawler and purpose. Allowing or blocking one User-Agent does not establish a general result for search indexing, training, agent fetches, or advertising.
A row labelled only “Perplexity” or “Google” is not a reproducible experiment. Store surface, mode, answer model, device, personalization, repeat, and event type; citation, mention, paid presence, and traffic remain different outcomes.
An AI-bot visit does not prove that a page was retrieved for an answer, cited, or clicked. A useful measurement model needs separate artifacts for access, discovery, retrieval, mention, citation, and referral.