9 karma · joined July 5, 2025
The idea of parameterizing geometric problem spaces and learning from how different kernels handle them is strikingly similar to what compiler researchers have done in CS: generating corner cases, analyzing compile errors, and training AI to self-correct. AI coding is used widely in the industry currently, with tools like cursor gaining huge popularity.
And the move to a text-based representation is what makes this all tractable — binary formats never gave us that level of observability or editability. With source-level CAD, it becomes much more realistic to analyze failures, share test cases, and eventually integrate AI tools that can reason about geometry the same way they reason about code.
Although building such engine requires tons of work, but the engine we’re having is indeed a bit of old. Except for the problems I mentioned, you also mentioned they’re still single threaded. That’s why I think it’s still worth building a new one, especially when there’s no good open sourced one currently.
I’m a big supporter of open source. If we have something like that in the future, we should of course make it open source like Linux kernel and allow everyone to enjoy the benefit of it.