Decomposing CAD generation into discrete operations that an LLM selects sequentially, rather than generating full code at once, dramatically improves structural correctness (82.7% success rate) and works with any language model without retraining.
This paper presents GOPR-CAD, a system that generates CAD models from text by having an AI agent progressively build a graph of operations rather than directly writing code.