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Better Vector Clustering With Head Noun Extraction
Let’s do a mental exercise. Glance over the following list and group them in your mind: Most people arrive at the following clustering schema: Socks Laptops Bulldozers blue thermal socks cheap gaming laptops cheap diesel bulldozer cheap ankle socks blue lightweight laptops blue rental bulldozer used cushioned socks used touchscreen laptops blue compact bulldozer cheap…
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Advanced Prompting Techniques for AI SEO
Most marketers treat AI like a magic box: prompt goes in, content comes out. But AI models are more like highly skilled interns—they need clear instructions, context, and examples to do their best work. The quality of your AI output is directly determined by the quality of your prompts. Master prompt engineering, and you can:…
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To block or not to block? Bot is the question.
Are you accidentally slamming the door on helpful AI visitors while trying to keep your website’s content safe from being scraped for training data? Many site owners block bots to protect their intellectual property, but in doing so, they might be turning away the “good” AI traffic—like search engines and assistants that drive real visitors…
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Gemini 3 hallucinates fan-out queries
TL;DR: Gemini 3 made up the fan-out queries used to answer a prompt. Today I was testing the updated API response from Gemini 3 (thanks Mike!) and found it to be as unreliable as its predecessors when it comes to hallucinations. Not only did it lie to me, but it also attempted to cover up…
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AI SEO Deep Dive – Tom Critchlow & Dan Petrovic
I recently sat down with strategic SEO consultant Tom Critchlow for a deep-dive conversation about the mechanics of AI Search. We moved past the usual LinkedIn hype and “get-rich-quick” prompt engineering advice to look under the hood of Large Language Models (LLMs) like Gemini and GPT. We explored a fundamental shift in AI SEO industry: moving from Click-Through…
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OpenAI’s Sparse Circuits Breakthrough and What It Means for AI SEO
OpenAI recently released research showing that AI models can be built with far fewer active connections inside them. This makes them easier to understand because each part of the model does fewer things and is less tangled up with everything else. Think of it like taking a spaghetti bowl and straightening the noodles into clean,…
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How GPT Sees the Web
A Technical Walkthrough of Web Search, Snippets, Expansions, Context Sizes, and Sliding Windows Many people assume GPT “views” the web the way humans do: full pages, HTML, images, layout, and complete articles. Reality is very different. GPT doesn’t browse. It doesn’t load pages. It doesn’t ingest entire documents. What it sees is controlled, windowed, and…
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BlockRank: A Faster, Smarter Way to Rank Documents with LLMs
Large Language Models (LLMs) have revolutionized many areas of natural language processing, and information retrieval is no exception. A promising new paradigm called In-Context Ranking (ICR) leverages the contextual understanding of LLMs to re-rank a list of candidate documents for a given query. However, this power comes at a cost: the computational complexity of the…
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In AI SEO #10 is the new #1
Instead of sending a user to one “best” page, Google’s AI Mode assembles an answer from short text extracts (snippets) taken from multiple sources on the first results page. Our study compares those extracted snippets with their full source pages and checks where in the SERP those sources sit. AI tends to rely on several…
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How much of your content survives the AI Search filter?
But how much if your page content actually makes it to the model? About one third on average. Metric Value Total Characters Across All Pages 21,198 Total Characters Cited 6,818 Total Characters Not Cited 14,380 Overall Citation Coverage 32.16% Citation Analysis: owayo.com Source: owayo.com Citation Snippet Custom Running Shirts – owayo: owayo manufactures custom running…
