Excited to introduce GEO Wiki geo.wiki, an encyclopedia I created for the AI search community📈 If you are researching Generative Engine Optimization, I compiled deep, "paper-level" tutorials and the most cutting-edge global GEO developments into one place. High-quality insights, and entirely free. Would love to hear your feedback!

Search Generative AI performance reports is coming！

Interesting Growth😂

GEO Wiki: The Wikipedia of Generative Engine Optimization producthunt.com/products/geo… via @producthunt

AI visibility scores swing ±15-20% within 30 days. You can get recommended by ChatGPT today and vanish next week. Without continuous tracking, you're flying blind. This is why I use a framework called RADAR for GEO ops: Record — build your baseline Analyze — find gaps, figure out why you're losing Deploy — fix and create content Accumulate — systemize what works Review — measure results, start the next cycle Rinse and repeat.

1/ LLMs don’t retrieve truth; they predict the next token. Fluent answer ≠ correct answer.

Research found that 44.2% of AI citations are extracted from the first 30% of an article. Tracks with what I've seen — AI doesn't read your page top to bottom like a person. It scans, grabs, and moves on. So put your most important takeaway up front. Don't write like an academic paper with the conclusion buried at the end. In AI search, if the answer isn't at the top, it doesn't exist.

One stat I keep coming back to: Brands are 6.5x more likely to get cited through third-party sources than their own website. Basically, AI cares way more about what others say about you than what you say about yourself. So optimizing just your homepage isn't enough. G2 reviews, Reddit threads, press coverage, industry directories — that's where AI actually pulls from. Brand building IS GEO building. More true every month.

1/ AI can read your 5,000-word article and still cite a rival’s 800-word post. Readable ≠ quotable; context window is input, output tokens are the real budget.

Ran the same query across 5 AI search tools last week. ChatGPT cited a Reddit thread and a TechCrunch article. Google AI Overviews cited the brand's own website. Perplexity cited a niche industry blog. Claude cited a research paper. Same question. Completely different "witnesses." If you're only creating content for one platform, you're invisible on the others.

🔍 The "One Giant, Many Challengers" Landscape As of early 2026, the AI search market has a clear structure: ChatGPT holds 64.5% market share with 800M weekly active users — but notably down from ~75% at the start of 2025. Competitors are closing the gap fast. Google AI Overviews now covers 25% of search queries, reaching 1.5B users monthly. Its new AI Mode is eliminating blue links entirely for some queries. Perplexity processes 435M monthly queries with an $18B valuation. Gemini has 650M monthly active users. Copilot holds ~7.2% share.