Implicit.js, a way for agents to do 3D design with math

Implicit.js is an open source library that lets agents generate CAD with code + mathematical functions representing surfaces. No CAD kernels, no STEP files — just agents using math + code to directly generate 3D models.

This is: 1. A small library of SDFs with a browser-native renderer: https://github.com/earthtojake/implicit.js 2. A demo that renders 3D models from code in realtime: https://www.implicit.sh/ 3. A set of skills to write code to generate 3D models with agents: https://github.com/earthtojake/text-to-cad

Some awesome things about implicit CAD: • No CAD kernels (Parasolid, OpenCascade, etc.): the math + code is the model. • They are FAST: the https://www.implicit.sh/ demo compiles and renders models from GLSL in the browser in realtime. • Representations are small: implicit code can be 100x smaller than STEP files.

Implicits are great at: • Manipulating complex geometry • Producing high resolution, scaled CAD models • Boolean / offset operations

But they are really hard for humans to intuit, which is why we prefer vanilla CAD that works more like LEGO: faces, edges, holes, cuts, fillets, etc., with human-readable topology.

Agents, on the other hand, are very, very good at coding and math — the two key ingredients for implicits.

The third ingredient is visual / spatial reasoning. While lacking today, I believe for many reasons (including robotics) this will be the next frontier that labs pursue.

To caveat: agents aren’t great at implicits today. Frontier models are still pretty blind, so implicits break down on complex parts/assemblies with visual feedback (code → model → screenshot → repeat). There is also no easy toolchain to inspect implicits because they lack topology.

That said, 6 months ago the models couldn’t write reliable code. Things are changing fast, and I think 2026 will be the year the models solve 3D design.

I also think it’s possible (and even probable) that implicit CAD becomes the preferred way for models to do 3D design.

Special thanks to Blake Courter and the Gradient Control team for teaching me about implicits and sharing the Python primitives used to build this library. Blake is the GOAT of implicit CAD and gave an excellent talk on this exact topic at Kinetic a few weeks ago.