The week in AI search, pulled together from the posts published since the last recap.
This week’s analysis separates measurable AI-search signals from broad claims about traffic, visibility, publisher economics and business impact.
Read more: AI search this week: evidence, economics and the limits of easy conclusionsThis week’s posts separate signals from proof: AI adoption, crawler access, attribution and litigation all need evidence before they support a marketing decision.
Read more: AI Search’s Evidence Problem, From Crawlers to CourtroomsThis week’s posts separate useful signals from overstated conclusions—and pair better measurement with the operational work needed to act safely.
Read more: AI search, measurement and delivery: the week’s operating gapsThis week’s posts put the focus on reliable signals: from campaign taxonomies and attribution tests to AI referral reporting, structured data and dependency review.
Read more: Weekly recap: measurement discipline meets AI search realityThis week made AI search less theoretical: policies are being published, visibility is harder to measure, and browser and dependency changes demand operational checks.
Read more: AI policy, measurement and browser operations moved closer to productionThis week’s posts show GEO becoming an operational discipline: teams must govern the tools, packages, crawlers, markup and rendering paths that shape AI-facing experiences.
Read more: Weekly recap: GEO moves from visibility to operational controlThis week’s posts show GEO becoming less about isolated visibility tactics and more about technical standards, rights, evidence, interface design and delivery planning.
Read more: AI Search Moves From Visibility Tactics to Operational Decisions