Explanatory context for the Versioned Markdown Entity Manifest (vMEM) As AI systems transition from passive retrieval toward synthesis and decision-adjacent operation, interpretation ceases to be an implicit human activity and becomes an explicit operational cost. Ambiguity now consumes compute, introduces probabilistic error, and creates downstream exposure when automated outputs are reviewed, challenged, or reused. This article explains the motivating conditions behind the Versioned Markdown Entity Manifest (vMEM), a minimal, declarative interface for publishing entity scope, explicit non-claims, authoritative references, and versioned change history in a human- and machine-readable format. vMEM is designed to externalize interpretation costs by making boundaries explicit and replayable, rather than inferred from prose, marketing material, or fragmented documentation. This work does not propose a ranking signal, compliance mechanism, governance framework, or enforcement layer. It does not assert correctness or truth of declared information. Instead, it articulates why undeclared scope has become a structural liability in AI-mediated environments and why replayable declarations may be necessary where misinterpretation carries material cost. The article includes illustrative, non-normative examples and appendices clarifying how vMEM relates to existing mechanisms such as llms.txt and structured data. Adoption is voluntary and decentralized; no platform behavior or outcome is implied. This work is explanatory and non-normative. It does not define requirements, standards, compliance obligations, or enforcement mechanisms. No reliance, adoption, or platform behavior is implied.