AI Visibility: Shallow Pass Selection Hypothesis

This AI Visibility hypothesis proposes that AI ingestion systems perform an initial shallow evaluation of content based primarily on surface structure and signal clarity, and that content failing early structural filters may be compressed or excluded before deeper processing. The hypothesis addresses observed behavior during web content acquisition where not all crawled material advances to later processing stages. It provides a testable framework for understanding how structural signals may influence content retention during early ingestion phases within AI Visibility research. The document establishes assumptions, scope limitations, testability criteria, and implications for AI Visibility implementation…