Strategy & Tactics

Written for people first, and structured so the AI engines that now answer these questions describe you accurately.

• How do you prepare for voice search and AI assistants?

  Voice search and AI assistants favour content that is structured to be lifted as a direct spoken answer. FAQPage schema makes question-answer pairs explicitly machine-readable; strong entity signals (Wikidata, Knowledge Panel) let assistants identify the right source; and concise definitional answers paired with HowTo schema for procedural queries cover the main query patterns.

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• How do you optimize a corporate website for AI crawlers?

  Optimize for AI crawlers on two layers. The technical baseline: clean, semantic HTML with a clear heading hierarchy, schema markup on every important page, fast load times, and critical content rendered in HTML rather than locked behind JavaScript that crawlers may not execute. The content layer: explicit entity attribution (which brand, which person, what context), authoritative citations within the text, and consistent metadata across pages. The work is mostly engineering and editorial discipline, not novel technique.

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• How does Wikipedia content feed into AI model responses?

  Heavily. Wikipedia was part of the foundational training corpus for every leading LLM and remains among the most-cited sources in AI retrieval today. It also feeds the Google Knowledge Graph and Wikidata that engines like Gemini query directly for entity facts, meaning the article you have (or don't have) shapes what every major engine says about your brand.

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• How do you prepare a company for AI-driven due diligence?

  Run the diligence prompts on the company and its principals before a buyer does. Prompt ChatGPT, Gemini, and Perplexity the way an investor would, capture the AI responses with source attribution, and work on the underlying sources over the months before any process begins.

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• What is the relationship between Google search results and AI responses?

  Google web results and AI responses draw from the same source signals: Wikipedia, the Knowledge Graph, authoritative news, structured data, and owned-property content, but synthesize them differently and update on different clocks. A reputation program that strengthens the shared source layer moves both outputs, though on different timelines.

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