AI Visibility

Mentioned in

• Why we don't do prompt tracking.
  Instead of infinite prompt variations, this measurement framework tracks canonical core entities across AI models to score brand visibility over time.
• Semantic Image Optimizer
  An overview of an e-commerce image optimization method using Google's AI models and vector embeddings to iteratively generate and score product alt text.
• Google, Anthropic and OpenAI crawlers fetched dejan.ai's robots.txt 1,150 times and its llms.txt 4 times in 30 days
  In a 30-day server-log census of dejan.ai's three machine files, the big-three AI crawlers fetched robots.txt 1,150 times combined, llms.txt 4 times, and the OKF content bundle 23 times.
• Gemini picks whichever web page it reads first 92% of the time. Only pages rewritten to its measured preferences ever beat that.
  Shown two web pages, Gemini picks the first one 92% of the time. Pages rewritten to 31 measured text preferences win 15% from the second slot. Ordinary pages: 0%.
• No, AI doesn't prefer Reddit. Search does.
  Analysis of citation mining data shows Reddit has a 99.39% rejection rate from OpenAI, zero citations from Anthropic, and heavy usage by Google.
• The Paradox of Average and AI Visibility
  A study by DEJAN AI examines how AI rankers prioritize prototypical content over brand authority, suggesting a dual strategy for SEO and human conversion.
• Content Optimization Engine Insights by DEJAN AI
  We spent 2.71 Billion tokens teaching a machine to reverse-engineer how AI search ranks pages. What it found overturns the usual SEO playbook: structure and intent beat every credential you've been told to add, and the engine that proved it reached #1 in 1,554 of 2,246 runs.
• Grounding Source ≠ Citation ≠ Mention
  Being a cited grounding source does not mean your brand was mentioned in the answer, and being mentioned does not mean you were cited. They are correlated but distinct events produced at different stages of the AI answer pipeline — and conflating them is the source of most AI-visibility measurement
• Primary Bias
  Primary bias is what an AI model already believes about your brand before it searches: an ungrounded confidence baked into training that becomes the biggest factor in whether your content is selected in AI answers.
• Grounding Snippets
  Grounding snippets are the short, extractive sentences AI systems pull from your page to build their answers: the atomic unit of AI-search visibility, where most of your page never makes the cut.
• Selection Rate Optimization
  Selection Rate Optimization is the AI-search counterpart to click-through-rate optimization: improving how often AI systems choose your content as the source they ground and cite their answers on.
• Relevance Engineering
  Relevance Engineering is the practice of building a page's semantic relevance to a query with embeddings and vector math, treating search visibility as an engineering problem rather than keyword optimization.
• AIO (AI Optimization)
  AIO (AI Optimization) is shaping your content and presence so AI systems favor them in generated responses — one route to AI Visibility.
• AEO (Answer Engine Optimization)
  AEO (Answer Engine Optimization) is optimizing to be the answer that AI assistants and answer engines give to a question.
• GEO (Generative Engine Optimization)
  GEO (Generative Engine Optimization) is optimizing for LLM-powered search and chat so your brand and pages appear in generated answers.
• The Open Knowledge Format (OKF)
  Google Cloud's Open Knowledge Format is an open, vendor-neutral way to package the context AI systems need, as plain markdown files any model or agent can read.