Launch HN: Adam (YC W25) – Open-Source AI CAD
Hey HN! I'm Zach from Adam (https://adam.new/). We're building AI agents for mechanical CAD software. We’ve built the company on two fundamental beliefs: - AI will be the primary medium for creating mechanical designs just like it is in software today. - The best paradigm for CAD generation is to generate CAD as code (text -> code -> CAD). We’re building CADAM, an open source Text to CAD platform. It's a React app (TanStack Start) with a Supabase backend for auth, database, and file storage. Think of it like AI TinkerCAD. Demo: https://www.youtube.com/watch?v=iESOr7EGWqk Try it: https://adam.new/cadam/ What it does: - Generates parametric 3D models from natural language, with support for both text prompts and image references. - Outputs OpenSCAD code with automatically extracted parameters that surface as interactive sliders for instant dimension tweaking - Exports as .STL or .SCAD (plus OBJ, GLB/GLTF, FBX, and DXF) Under the hood: - One agentic endpoint with two modes that swap system prompts and tools: a parametric mode that writes/edits OpenSCAD via a build_parametric_model tool, and a mesh mode that generates 3D textured meshes. - Simple parameter tweaks bypass the model entirely; adjusting a slider does a deterministic regex update on the SCAD source, requiring no LLM call. - Model-agnostic via the Vercel AI SDK: Anthropic (Claude), Google (Gemini), and OpenAI/others through OpenRouter, with adaptive thinking auto-enabled on newer models. Surprisingly, in our evals Gemini 3.1 Pro is the top model. - Runs fully in-browser by compiling OpenSCAD to WebAssembly (in a Web Worker, so the UI never blocks) and rendering with Three.js via React Three Fiber - Supports BOSL, BOSL2, and MCAD libraries, plus custom font support (Geist) for text in models Future improvements: - Support both build123d and CadQuery. This will allow us to move beyond CSG primitives to constraint-driven modeling and provide direct comparisons to other code-as-CAD primitives. - Better spatial context: UI for face/edge selection and viewport image integration to give LLMs spatial understanding You can clone the repo and run it locally! Contributions are very welcome.
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It did a great job with this prompt. Got it done in about the time it would take me to login and load Fusion. I forgot to include the wire diameter but it made a reasonable assumption and included it in the params for edits "Make a grommet seal for a hole in an aluminum pipe where a cable goes through. The hole is 0.48 inches in diameter. The wall of the pipe is .25 inches thick. Make the seal split so it can be installed with the cable in place. Make a circular cover lip that is .2 inches across on the outside, and an inner lip to secure it that is smaller. It will be printed in flexible tpu"
Can it work from photos? I'm specifically thinking about stuff like this: https://www.tooltrace.ai/
Congratulations on the launch. The propeller demo looks good :) BTW, customising gears (which are then laser cut from sheet metal) is also a common request from untechnical people who need CAD help. How do you differentiate from other open source AI CAD solutions? I’ve also had a good experience with Claude Code and CadQuery, which is a Python toolkit for generating CAD designs based on OpenCascade. I.e. what’s your moat? And given that you’re YC funded .. what’s your plan for millions in MRR? I’m asking because I would like to launch some useful open source tools myself (but for PIM, not CAD) and I just can’t figure out how to make open source sustainable, let alone profitable enough for hockey stick revenue growth. Any tips? Book recommendations?
I'm pretty skeptical of AI products, but your onboarding and first design experience has been pretty awesome. I will definitely spend a bit more time experimenting with this
Is CADAM also what's used for the commercial product adam.new? How did you manage to write all those plugins? If it is also CADAM isn't stuff getting lost in the Fusion/Solidworks/Onshape -> OpenSCAD -> back process? Do constraints and everything just seamlessly import/export? Some comments here mention tolerances/functional requirements. Do you think the LLM/screenshot loop will scale to that too? Maybe rendering subassemblies individually until they make sense? Still feels like a full functioning V8 engine block needs _a lot_ of ghost-view screenshots to verify it works. What's your thoughts on a "simulation" approach, since it's not aligned with your bitter-lesson-blog-post? Are you able to reveal more about what kind of traction you have? 10s/100s/1000s of companies? Very cool open source project, and thanks for sharing so much!