What this means
Finding candidate information or documents for an AI response.
Historical record
Perplexity introduces Q2D-Web for large-scale retrieval evaluation in agentic RAG
The visible user prompt is not necessarily the query a source competes for. AI visibility therefore depends on several distinct stages: query reformulation, first-stage retrieval, ranking, evidence selection, and eventual citation.
Google expands AI Mode and Deep Search using query fan-out
Topical completeness, subtopic relevance and retrieval across multiple intents become central to AI search visibility.
Anthropic launches web search on the Claude API
AI discoverability extends beyond consumer search interfaces into embedded enterprise and developer workflows.
Google introduces AI Mode and describes query fan-out
Visibility is no longer tied only to the user’s literal query; sources can be discovered through hidden subqueries and related retrieval paths.
ChatGPT web browsing begins rolling out in beta
Website discoverability became directly relevant to ChatGPT answers and later evolved into a dedicated search product.
OpenAI WebGPT demonstrates browser-based answering with citations
The retrieve-read-cite pattern closely anticipates later AI answer engines and modern citation optimization concerns.
Retrieval-Augmented Generation (RAG) is formalized in research
RAG is one of the core technical patterns behind modern AI search, source retrieval and citation behavior.