GEO Blog
Analysis, insights, and strategic guidance for SEO pros navigating AI-driven search.
EEAT and Beyond: How Generative Engines Judge Your Content
Why EEAT still matters — and what goes further for generative engines
Sep 21, 2025
Search engines care about EEAT, but generative engines like ChatGPT, Claude, and Gemini are rewriting the rules of visibility. Learn what still matters — and what goes beyond EEAT.
Read articleWhy GEO Matters in 2026 — and What SEO Teams Need to Know
Hallucinations, misinformation, and why visibility in AI answers matters
Sep 19, 2025
How AI hallucinations create visibility and accuracy risks for SEO teams — and what to do about it.
Read articleEchoTune — Content Tuning at the Snippet Level
How content is analyzed and tuned for generative engine interpretation.
Aug 05, 2025
How EchoTune evaluates, tunes, and validates content so it can be accurately extracted and reused in AI-generated answers.
Read articleUnderstanding GEO: The Next Shift in Search Visibility
A foundational overview of how generative engines change search visibility.
Aug 01, 2025
How GEO extends traditional SEO when visibility depends on how AI systems interpret and summarize content.
Read articleFrom Rowana to GEOsync: What Early LLM Diagnostics Revealed
How early generative diagnostics shaped GEO optimization.
Jul 28, 2025
What early experiments revealed about how generative engines interpret content — and why diagnostics alone weren't enough.
Read articleWarning: Traditional SEO Won't Save You From AI Search
Why rankings alone don't guarantee visibility in AI-generated answers.
May 01, 2025
How AI systems interpret, summarize, and sometimes misrepresent content—and why traditional SEO signals aren't enough.
Read articleBeyond llms.txt:
Is your website 'really' ready for AI search?
Apr 30, 2025
llms.txt is a starting point; true readiness means optimizing your content for comprehension.
Read articleThe Unseen Interpretation Layer
How AI systems interpret web content beyond human intent.
Apr 20, 2025
This article explores the gap between human intent and how AI models interpret web content — the unseen interpretation layer that shapes how generative engines 'see' the web.
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