← All issues

AEO/GEO RADAR · 5 October 2026

Google put numbers on how slowly it notices a change: about 30 days to re-read a page it already knows.

Reported, not confirmed

Google gave typical timings for crawling, indexing and recovery

On the last day of Google's three-day Search Central event in Barcelona, Gary Illyes showed a table of how long Google's steps usually take. The figures, as carried by all three write-ups: a new URL is discovered in about 20 hours; a known URL is refreshed about every 30 days; a sitemap is processed in about 24 hours; a robots.txt change is picked up in about 24 hours; indexing end to end takes about 1.5 hours once a page is fetched; a title or snippet change shows in 1 to 2 days. Each row has a slow case, and for discovery and refresh the slow case is "weeks to never". Recovery after a core update is given as 3 to 6 months. Search Engine Journal states the limits: "Reported ranges are reference points, not deadlines", with no sample size, no measurement period and no definition of "typical". The source is an agency's recap of slides, not a Google document. The table is about Google Search. It does not mention AI Overviews, though the same recap records Illyes saying "AI results are built on SEO infrastructure".

ROAST, "Google Search Central Live Deep Dive, Barcelona, Day 3 Recap" (John Campbell), event of 2 October 2026, read first-hand 5 October 2026; Search Engine Roundtable (Barry Schwartz), 5 October 2026; Search Engine Journal (Matt G. Southern), 2 October 2026
Reported, not confirmed

Google on spam updates: scaled content, and "months" as the slow case

The recap records Illyes saying "Google filters out 40 billion spam pages a day" and "Scaled content is now becoming more of a problem than link spam". It records Duy Nguyen of Google's search quality team saying "There have been more spam updates recently because there is so much more new content" and "The point is the quality, not who wrote it. Low quality content can be human or AI generated." The timing table gives a spam update as "1 to 2 weeks" in the usual case and "months (batch refreshes)" in the slow one. None of this names the September 2026 update. Google's incident for that update still shows one post, the 24 September launch, on day twelve of a rollout Google said "may take up to two weeks".

Same ROAST recap; Search Engine Roundtable, "Google Search Spam Updates Use AI To Find AI Spam & More" (Barry Schwartz), 5 October 2026; Google Search Status Dashboard, read first-hand 5 October 2026
Reported, not confirmed

A second Claude model in the engine is near its earliest retirement date

The table lists `claude-haiku-4-5-20251001` as Active with a tentative retirement date of "Not sooner than October 15, 2026". It is not deprecated, and Anthropic promises at least 60 days' notice, so nothing fails this month. It is worth a line because the same pattern played out last week: Claude Sonnet 4.5 passed its "not sooner than" date on 29 September and was formally deprecated on 30 September. In the engine, `src/extract.ts` line 129 sets `NER_MODEL = "claude-haiku-4-5"`. That is the step that pulls the names of other businesses out of each answer. Sonnet 4.5 is unchanged: deprecated, retirement 30 November 2026, replacement `claude-sonnet-5-5`. The engine's `main` is still `06233ce`.

Anthropic model deprecations page, read first-hand 5 October 2026; engine source checked the same day
Confirmed at source

Standing items: Perplexity

Unchanged. The migration page still says Sonar requests "are being reformulated as Agent API requests, rolling out gradually by model" and names no model. No October changelog entry.

Perplexity migration page and changelog, read first-hand 5 October 2026
Reported, not confirmed

Otterly: German AI answers cite German sources about two times in three

Otterly counted 3.95 million citations on German prompts across 16 industries and seven assistants, from 16 August to 28 September 2026. Verbatim: "64.9% of German AI Search citations point to a domain that carries a local region or language signal". Association sites take 8.9% of German citations against 5.3% in its US data, and Reddit 0.60% against 1.79%. The local share runs from 75.2% on Perplexity to 57.7% on Claude. This is vendor data, it counts cited pages and not named businesses, and the period sits partly inside Google's spam update.

Otterly blog, "AI Search in Germany Plays by Different Rules. Here Is the Data." (Rick Tousseyn), 5 October 2026, read first-hand

The Radar is free to read and always will be. If you want to know whether AI names your business when a buyer asks, the free check asks ChatGPT 25 real buyer questions and emails you the answer within the hour.

Get the Radar by email →