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Mike King argues that search now works on meaning while many SEO tools still lean on BM25 and TF-IDF, and goes on to relevance engineering and fan-out queries.
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Fan-out queries are at the centre of Nik Ranger's AI visibility study for a travel platform, where seven million synthetic queries produced 110 Google citations and just 2 from ChatGPT.
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What does each part of E-E-A-T mean in practice? Lily Ray explains, and says AI search raises the stakes, with a look at what brands often get wrong about credibility.
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Krishna Madhavan traces the steps from a search query to an AI answer on Bing, including the index, annotation, fan-out queries and the engineering choices that affect which brands get named.
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Trust has replaced rank in AI visibility measurement, according to Kevin Indig, who presents a study of link metrics and a second one following 50 people across AI Mode and classic search.
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Dawn Anderson explains what the AI era changes for crawling, indexing and technical SEO, and argues RAG works from a web index rather than live data.
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Structured data does not need every schema type, says Jarno van Driel, who argues for clean HTML and good content and a clear sense of what markup is for.
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What is behind generative AI in search? Fabrice Canel of Bing talks it through with Jason Barnard, from Bing Chat to the different ways people search.
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