Hi HN, I’m releasing WLM (Wujie Language Model) — a structural language for AI that treats meaning as geometry, tension, and boundary instead of tokens, narrative, or emotion. This release includes the Shadow Layer v1.1, a fully public, non‑executing architectural description of WLM. It exposes the dimensional structure and reasoning framework without revealing any protocol‑level execution logic. What WLM is WLM is not a model, dataset, or training method. It is a high‑dimensional structural protocol for: - reasoning - world modeling - subject/world separation - boundary formation - dimensional alignment It defines how meaning stabilizes across 0D–27D structural layers. What’s included in this release This release contains the public half of WLM: - Shadow Layer v1.1 The complete architectural outline of WLM. Non‑executing, safe, and version‑frozen. - 0–27D Dimensional Physics A separate repository describing the generative physics of structure: how worlds appear, how subjects stabilize, and how meaning emerges. Why release this The goal is to provide: - a transparent structural reference - a stable interface for research - a shared language for high‑dimensional reasoning - a foundation for alignment work that doesn’t rely on behavioral heuristics This is not a teaser or partial disclosure. It is the full public architecture. Links Shadow Layer v1.1: https://github.com/gavingu2255-ai/WLM-Open-Source/blob/main/... Dimensional Physics (0–27D): https://github.com/gavingu2255-ai/WLM-Paradox-Dimensional-Ph... Happy to answer technical questions about the architecture, dimensional stack, or structural reasoning model.