What this means
Optimization aimed at how LLM-based systems understand, retrieve, cite, or recommend entities and content.
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.
The llms.txt convention is proposed
It reflects growing demand for content representations optimized for machine readers, although it is not an established web standard.