Large language model assistants have shifted the center of brand visibility from retrieval surfaces to reasoning and recommendation layers. Traditional visibility metrics that rely on input-side optimisation no longer measure how models construct answer surfaces. The Answer Space Occupancy Score (ASOS) is a probe-based metric that quantifies the fraction of the observable answer surface occupied by a specified entity across independent runs of a controlled four-turn script. This document publishes the ASOS alpha protocol, scoring rules, validation commitments, and the first reference dataset.