Michael King: "12 Strategies to Dominate AI Search in 2026" — Moz

Michael King (iPullRank) published a comprehensive tactical playbook on Moz covering 12 specific strategies for AI search visibility across ChatGPT, Perplexity, Claude, and Google AI Overviews. Key findings: JavaScript rendering gap (AI crawlers see raw HTML only — SSR is mandatory), 499ms TTFB timeout (AI crawlers drop pages slower than ~500ms entirely), atomic content blocks (AI retrieval uses cosine similarity on passage-level vectors — each content block must stand alone as a potential AI citation), Digital PR over links (AI models cite brands in earned media, not just linked pages), three-bucket measurement (Brand Awareness, Consideration, Conversion).

High — AI retrieval is fundamentally different from SEO; review sites must restructure for passage-level retrieval and sub-500ms TTFB

• Restructure review pages for atomic content blocks — each section (rating summary, pros/cons, feature breakdown, price assessment) must be a self-contained semantic unit with clear H2/H3 headings that can stand alone as an AI citation
• Measure TTFB for top 50 review pages — AI crawlers drop pages >500ms entirely; prioritize edge caching for review templates and lazy-load non-critical elements
• Pitch review data to journalists for Digital PR — gobii.reviews data shows [product] rated 4.2/5 by 500+ users is a narrative hook; earned media mentions = AI citations even without links