This document defines the NAIM (Natural AI Interface Modeling) framework, a canonical semantic intermediate representation between natural language descriptions and YANG data models (RFC 7950). NAIM addresses a recognized gap in the YANG authoring and network management workflow: direct conversion from natural language to YANG is error-prone because essential modeling semantics -- including configuration versus state distinction, list key identification, constraint expressions, operational preconditions, and cross-module relationships -- are routinely absent or ambiguous in natural language input. NAIM makes these semantics explicit, structurally consistent, and machine-verifiable. This document defines: the NAIM Document format (Canonical JSON and derived Markdown View); the LLM Context View for AI prompt context distribution; the three-layer architecture (Specification, Skill, Tool); Skills A-D for conversational modeling, summarization, YANG generation, and reverse engineering; and the Validation-Reflection- Retry mechanism for AI output quality control. The NAIM Document format is designed to serve two roles: as the intermediate representation for design-time YANG authoring, and as the runtime semantic authority against which AI-generated operation intents are validated. The runtime validation usage is specified in [NAIM-OP]; this document defines the format, derived views, and design-time workflows.