Imagine effortlessly designing complex building models just by chatting with your design software. What if you could simply describe your design intent in plain English, and have an AI copilot translate your words into intricate BIM models? This is the future of Building Information Modeling (BIM), as envisioned by researchers at the Technical University of Munich, who have developed an LLM-based agent that acts as a virtual copilot within BIM authoring tools. Modern BIM software, while incredibly powerful, can be overwhelming to learn and use efficiently. Designers often find themselves wrestling with software complexities, distracting them from the creative process. This research aims to bridge that gap by allowing users to interact with their BIM software using natural language. The AI copilot acts as an intermediary, understanding user instructions, figuring out the necessary software commands, and executing those commands automatically. This research team implemented a prototype within Vectorworks, a popular BIM authoring tool. The prototype copilot responds to both text and voice commands, allowing users to create walls, move objects, and even generate entire building structures by simply describing their vision. This innovation is made possible by integrating large language models (LLMs), the same technology that powers AI chatbots like ChatGPT, with the software's core functionality. The copilot doesn't simply execute pre-programmed commands. It actually interprets user intent, plans the required steps, and interacts with the underlying software APIs to generate the desired design. The researchers also incorporated a memory module, enabling the copilot to remember previous instructions and design choices, further streamlining the design process. This research is more than just a cool demo—it offers a glimpse into the future of design and human-computer interaction. While still in its early stages, this technology could significantly democratize access to advanced BIM modeling, freeing designers to focus on creativity and innovation, rather than software intricacies. However, challenges remain, including designing comprehensive toolsets for the AI copilot, handling complex design scenarios reliably, and optimizing the performance of open-source LLMs for this specialized task. The future of design looks increasingly collaborative, with AI copilots augmenting human creativity and simplifying the design process in powerful new ways.