Archetypes as Enterprise Primitives

Abstract

Large language models are increasingly capable of meeting the functional requirements asked of them — the code works, the feature ships. Enterprise adoption of AI-assisted development, however, is not bottlenecked by function; it is bottlenecked by form: repeatability across teams, consistency across releases, auditable boundaries between generated and hand-written code, and the governance that accumulates around them. This paper argues that declarative archetypes — in the AgentGuard sense — are a minimum-viable primitive for enterprise AI development, because they convert implicit prompt-level intent into an explicit, version-controlled artefact that scales to organisational size. The argument is theoretical and draws on contract programming, specification-driven development, and software architecture. It is the closing paper of a four-part series that describes the mechanism, measures it empirically, and documents the implementing architecture.

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