u/sjia

We rewrote the printed parts of Open Duck Mini v2 as CadQuery (Python) programs. Then we changed three values in one file. The leg and neck parts aren't copies. They run the Duck's own programs with the new values, so the servo pockets and screw holes stay where the STS3215 needs them and only the length between them changes. We added wings and a small bird head, and the result is the Flamingo.

The repo also has SO-101 and the LeRobot humanoid as code (Apache-2.0.

https://github.com/yotown/gym

We generated this simplified White House scene using a single reference image, then exported the individual parts as STEP and imported them into Fusion 360. The scene contains 16 separate parts, including the building, columns, entrance door, flag, gates, fountain, trees, and Washington Monument.

I have been building YoCAD, a tool that turns a text prompt or a photo into a real parametric CAD model instead of a static mesh. Working joints, live dimension sliders, animation, all from one prompt. The demo is an unofficial concept of the OpenAI x Work Louder macropad. Every keycap presses on its own slider joint, the knob spins, the joystick tilts. The generator named the keys as musical pitches, so pressing them plays actual piano notes.

The output is a program, not a blob: dimensions are draggable parameters, and you can pin any part and type a change to edit just that part. An LLM writes the model, an analytic CAD kernel verifies geometry, joints, and collisions.

  Still needs more work for manufacturing, it is a concept and a starting point today.

I’ve been experimenting with a different workflow for AI-generated 3D models.

Instead of generating a mesh, an LLM writes Python CAD code, and our geometry kernel executes that code to build the B-Rep model. This articulated violin is defined by about 500 lines of Python.

To edit it, I clicked different locations on the model, pinned notes there, and described the changes step by step. The system used each pinned location to focus the edit on the selected area instead of regenerating the entire model.

Afterward, I exported the parts as STEP, imported them into Fusion 360, added the assembly motion, and created the video.

Not a mesh or a render. It wrote parametric CadQuery code: parameters at the top, one section per part, joints at the end. A physics loop checks interference through the joint motion before it ships. It's not perfect, there are still a couple of collisions if you push the joints to their limits, but this went photo to moving, articulated, editable CAD in one shot. Full source code in a comment

Fed it one photo of a toaster. It came back with a parametric model, every part named, every joint working. I pinned a note on one part ("chamfer the top edges") and watched it edit just that part, re-check the geometry, and hand back the result.

It exports to a real STEP file too, not a mesh, so it opens straight into Fusion 360 with a proper feature tree if an engineer wants to keep going from there.

Still early and free to try. Happy to answer questions about how it works if anyone's curious.

The whole model is generated from one self-contained Python/CadQuery script — no external assets. It includes the rocket body, fins, launch tower, base platform, support arms, and a few simple mechanical details.

This is our first Fusion 360 tryout with a scripted CAD workflow. We built a small gear train demo using CadQuery-style Python, exported each part as a separate STEP file, then imported the parts into Fusion 360 for assembly and animation.

The workflow we tested:

Python script → STEP parts → Fusion 360 assembly → revolute joints → motion animation

It appears that many people on Reddit enjoy gears.

We built a small gear train emo with CadQuery-style Python and tested the full workflow in Onshape. We will be sharing the Python code, STEP files, Onshape assembly setup, and animation result at https://maker.yotown.com/cad.

The workflow is:

Python script → STEP parts → Onshape assembly → revolute mates + gear relations → animation

The goal is to test whether script-based CAD can cleanly hand off to a real CAD assembly workflow.

Would love feedback from Onshape/CAD users.

We’ve been working on smoother mesh segmentation for 3D printing. Curious how other modelers would approach this: would you prefer automatic segmentation, manual cut guides, or a hybrid workflow?

We had to adjust parameters a few times, so the pins smooth enough to slide.

We’ve been experimenting with parametric cutters for adding functional joints to 3D models.

This one is a threaded connector cutter. The idea is to keep the control surface small, with only a few key parameters like radius, depth, pitch, and clearance, then use it to generate printable screw-fit geometry.

Quick follow up on our cutter tools, we’re turning threaded joints into something you can control with just 4 parameters instead of a long list, generated from code and ready to print as screw fit parts, still tuning it so curious if this feels like the right level of control and what you’d change.

We’ve been improving on a small set of cutters that add joints directly into models, so they can actually move after printing./ Right now we have 5 types:

• hinge style joints
• snap fit
• dovetail
• slot interlock
• flexible link style

The goal is simple: take any mesh → split it → add joints → make it printable and usable. Still early, but it’s already working on toys and simple mechanical parts.

Curious what people think, what kind of joints or use cases would you want to see?