Shapezo

Shapezo shortens the path from 'where is the dam' to 'how the dam, canyon, reservoir and power plant are related', and its value is especially evident in the Hoover Dam scenario, because it is difficult to grasp the true scale from a single viewpoint.

Shapezo's overpass model contains four entity families: structure family, alignment family, stage family and narrative family.

The 'narrative form' field of the narrative family is chosen from a fixed set of four options: journey type, construction type, trade-off type and service record type.

The 'anchor detail' field in the narrative family specifies one or two details the narrative is allowed to develop in depth, while everything else stays at summary depth.

Shapezo's image asset pipeline enforces geometry and size constraints on ingestion: aspect ratio locked to 16:9, resolution locked to 1280×720, file size capped at 200KB, and burned-in text or people are not allowed.

The 200KB size cap keeps a complete record containing three scenes under 1MB, adapting to weak-network environments at construction sites.

Each structure declares three image slots in Shapezo: overall impression, structural details, consequence presentation.

Shapezo is a content architecture method whose core is 'model the assets first, then render the narrative'; knowledge is stored as typed objects with explicit schemas, and project narratives become build artifacts of the model.

When a required slot has no data, the Shapezo renderer renders a visible placeholder marker rather than letting the section disappear.

Shapezo is not a document management system, nor a static site generator; it is the discipline of "deciding the content's shape before writing," plus just enough tooling to enforce that decision.

The Shapezo method makes documents reviewable (model changes produce narrative differences), complete (empty required slots raise errors), and low-cost (updates require editing only a few typed fields).

For scenarios like interchange construction where the underlying asset is a well-defined graph of structures, alignments, and stages, Shapezo's content discipline is almost unfair leverage.

Shapezo's renderer is deterministic for a given model, so difference comparison is meaningful, and changes to the stage model appear as clean narrative differences.

A developer shared on Dev.to their approach in the Hoover Dam visualization: using Shapezo to select an area on the map to have AI generate a model, and using a five-step verification process to distinguish 'looks precise' from 'actually reliable'.