Articles on Google & AI Search.
Practical playbooks written by Brian Ho, from technical setup to content strategy.
Shenzhen SEO Conference 2026, in one visual guide
32 talks, 7 diagrams and a 90-day checklist.
The 12-Layer Technical GEO Stack & 7-Step AI Search Funnel from Discover to Mention: Why You Must Audit Bottom-Up
Many teams rush to publish llms.txt or rewrite content while their WAF silently blocks OAI-SearchBot or critical pages rely on client-side JS. Here is why bottom-up engineering is mandatory.
AI Training Bots vs. AI Search Bots: Stop Accidentally Erasing Your Brand from ChatGPT
Many webmasters block all AI user-agents to protect training data, inadvertently blocking OAI-SearchBot and ChatGPT-User and wiping out their live search citations.
4-Entity Model, EEAT-A & Internal Wikipedia: Turning Your Site into AI’s Primary Grounding Source
On-page GEO differs fundamentally from classic On-page SEO. Instead of keyword density, you must engineer unambiguous entity graphs and an Internal Wikipedia structure.
Turning Claude, ChatGPT, and Cursor into Technical GEO Specialists with BHM-MCP
Instead of pasting fragmented prompts, Model Context Protocol (MCP) lets your AI assistant dynamically invoke Brian Ho’s verified technical skills and audit checklists.
From Link Building to Brand Mentions: In-App Memory & Entity Satellite Networks
Classic SEO revolves around backlinks to a domain, whereas GEO focuses on cross-web brand entity corroboration and in-app AI memory layers.
Lessons from 22+ Singapore GEO Projects & 6 Global Markets: SG, KR, JP, CN, US & UK
Every market relies on a different mix of AI engines and grounding authorities, from Microsoft Copilot in Japan and Singapore to DeepSeek/Doubao/Kimi in China and AI Overview in the US.
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