Imagine designing complex 3D mechanical parts not by painstakingly clicking and dragging in CAD software, but by simply describing what you want in plain English. That's the ambitious goal researchers are tackling by combining the power of Large Language Models (LLMs), like the ones powering ChatGPT, with the precision of Constructive Solid Geometry (CSG). Traditionally, AI-powered 3D model generation has relied on meshes – collections of interconnected triangles – which work well for visuals but lack the precision needed for engineering. Meshes are approximations; a circle becomes a polygon, and smooth curves become a series of flat surfaces. This makes them difficult to modify and unsuitable for the demanding world of mechanical design. This new research takes a different approach. Instead of meshes, they generate code that defines the 3D part using CSG. CSG represents objects as combinations of basic shapes (cubes, spheres, cylinders) joined together through Boolean operations (add, subtract, intersect). This allows for exact representations of complex shapes, perfect for engineering applications. To achieve this, researchers created a specialized dataset. They started with existing 3D models in a standard CAD format (BREP) and converted them into Python code representing the equivalent CSG construction. Then, they used GPT-4 to generate natural language descriptions of these parts, creating a link between the code and human-readable text. This dataset was used to fine-tune a code-generating LLM. Given a partially completed 3D part and a textual description of the desired addition, the LLM generates the missing code to complete the design. The results are promising, demonstrating the model's ability to grasp geometric concepts and generate plausible, often accurate, completions based on both the existing part and the textual instructions. While still in its early stages, this research opens exciting possibilities. Imagine a future where engineers can rapidly prototype designs using natural language, or where non-experts can create custom parts without needing CAD expertise. Although challenges remain, particularly in accurately describing complex shapes with text, this approach represents a significant step towards a more intuitive and automated future for 3D design.