Gaussian Splatting has made it easier than ever to create beautiful, detailed 3D models of buildings, cities, and infrastructure. Yet for most teams, these models still require specialized tools, manual inspection, and significant effort to extract insights. This session explores an emerging paradigm: turning image captures automatically to interactive 3D Gaussian Splat environments using simple prompts. Instead of navigating complex software, users can begin to ask questions like: “Construct a Guassian splat using these images,” “Identify where vegetation is encroaching on power lines,” or “Extract machines on this factory floor as separate 3D models?” These interactions point toward a new layer - often described as spatial agents - where AI systems can interpret 3D environments and help surface insights such as measurements, risks, or areas of interest. Through examples across industries, we will explore how prompt-driven interaction could shift 3D models from static visualization toward more conversational systems, and what this may mean for the future of digital twins.