Insights

How AI Decides
Who to Recommend.

Search stopped being a list of links. Now a buyer asks an assistant who to trust, and it names two or three businesses. This is the library on becoming one of them: every track below maps to a layer of the AI Visibility Stack, so the order you read them in is the order you build.

The spine

Understand. Trust. Recommend.

An AI assistant can only recommend a business it understands, trusts, and has seen vouched for elsewhere. That is the whole game, and it is the reason the tracks are ordered the way they are. Start with the AI Visibility Stack if you want the full methodology first.

Five tracks

Layer 1: Foundation

SEO Foundation

The technical base and structured data every recommendation is built on. Crawlability, schema markup, Core Web Vitals, internal linking, and E-E-A-T basics.

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Layers 3 to 4: Authority and Extraction

AI Discoverability

How ChatGPT, Perplexity, and Gemini decide who to recommend. Entity clarity, bot directives, llms.txt, quotable answers, and the signals that actually move the machine.

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Layer 5: Recommendation

Earned Visibility & Reputation

Roughly 85 percent of what AI recommends comes from off your own site. Review platforms, listicles, press coverage, and community mentions, and how to earn them.

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Channel

Social SEO

Social platforms are search engines now. Optimizing profiles and content for discovery on TikTok, Instagram, YouTube, LinkedIn, and Pinterest, and inside Google.

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The business case

ROI & Business Impact

The real return on search and AI visibility. What it costs to ignore, how it compares to paid ads, and why it compounds. The dollars and sense behind visibility.

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The Book, Serialized