# AI-Native CAD Workflow

ForgeCAD is an AI-native CAD workflow for turning product ideas into editable, manufacturable parametric models. The core loop is simple: describe the goal, let an AI agent edit `.forge.js` source, validate the model with the CLI, inspect visual and manufacturing evidence, then revise or fork the next iteration.

The important distinction is that ForgeCAD does not stop at a pretty mesh. The model remains code. A hole can move, a wall can thicken, a fastener can change, and a product variant can branch from the same source instead of starting over.

## What AI-Driven CAD Means Here

AI-driven CAD should produce a model that can survive feedback. In ForgeCAD, the agent works with normal files, not a hidden binary state:

- `.forge.js` files express dimensions, parameters, assemblies, connectors, materials, and export intent.
- `forgecad run` catches syntax errors, import problems, invalid geometry, collisions, and verification failures.
- `forgecad render` and `forgecad inspect` create visual evidence for design review, fit checks, wall thickness, sections, masks, depth, and normals.
- `forgecad export` sends the same source toward STL, 3MF, STEP, reports, cutting layouts, robot packages, or G-code depending on the job.

This makes the AI useful after the first answer. You can ask for changes in natural language, but the artifact being changed is still an editable engineering object.

## Manufacturing Feedback Loop

A manufacturable model needs feedback before fabrication. ForgeCAD gives agents a concrete loop:

```text
prompt -> edit source -> run -> render -> inspect -> fix -> export
```

That loop is where quality improves. The agent can inspect collision reports, check thin walls, render multiple camera views, test parameter ranges, and produce evidence for the user instead of relying on a single screenshot.

## Parallel Product Idea Iterations

Because ForgeCAD models are source files, parallel product exploration is cheap. An agent can create several variants in separate files or branches:

- one concept optimized for 3D printing
- one concept aimed at sheet metal or laser cutting
- one concept with purchased hardware and service access
- one simplified blockout for proportion and motion review
- one production-facing version with clearer tolerances and export targets

Each variant can keep the same validation contract: run it, render it, inspect it, compare it, and decide whether it deserves more detail.

## Where ForgeCAD Fits

ForgeCAD is useful when you want AI-assisted CAD that remains inspectable and editable:

- founders exploring physical product ideas
- makers iterating 3D printed parts and fixtures
- engineers prototyping mechanisms, enclosures, brackets, and assemblies
- teams that want version-controlled CAD source and reproducible exports
- AI agents that need a deterministic toolchain instead of a purely visual prompt-to-mesh path

The goal is not to hide CAD behind a chatbot. The goal is to let AI do more of the modeling work while ForgeCAD keeps the result grounded in readable source, validation evidence, and manufacturing outputs.
