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 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 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 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) is shaping your content and presence so AI systems favor them in generated responses — one route to AI Visibility.

AI SEO is optimizing your content and brand so AI systems surface them when answering questions — the broad practice behind AI Visibility.

GEO (Generative Engine Optimization) is optimizing for LLM-powered search and chat so your brand and pages appear in generated answers.

AEO (Answer Engine Optimization) is optimizing to be the answer that AI assistants and answer engines give to a question.

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.

AI Visibility is the outcome of AI-centric SEO, focusing on being cited and recommended by AI systems through brand mentions and source citations in answers.