Text prompts can be used to manipulate the artificially generated outputs, such as images and videos, creating unique content with every run. This paper explores how Vector Quantized Generative Adversarial Network and Contrastive Language–Image Pre-training (VQGAN+CLIP) outputs can be used as idea generation for functional 3D product design. By taking inspiration from the Neural Radiance Field (NeRF) and photogrammetry processes, using a video panorama of an object could eventually create a system for 3D objects using a trained VQGAN+CLIP collab.