Field note
From ShapesXR to WorldAgents
ShapesXR helped spatial teams design, prototype, and validate immersive products before production. WorldAgents carries that same principle into AI agents that need to operate in real places.
Field note
ShapesXR helped spatial teams design, prototype, and validate immersive products before production. WorldAgents carries that same principle into AI agents that need to operate in real places.
The shift
ShapesXR was built around a simple idea: spatial work should be reviewed spatially. Teams designing for XR, smart glasses, immersive interfaces, events, training, and real-world 3D need to understand scale and context early.
WorldAgents starts from a related problem. AI agents are leaving the chat window and entering stores, warehouses, venues, campuses, and field work. They need to understand the place, the workflow, the user's current situation, and the device being used.
That is why WorldAgents is built around simulation and the Spatial Intelligence Engine. The goal is to test the agent in context before it becomes part of an operational workflow.
Trusted by teams using ShapesXR



These testimonials are about ShapesXR and the spatial product experience behind the WorldAgents team.
What carries forward
Spatial products become easier to evaluate when teams can see scale, position, attention, and context directly instead of arguing from flat documents.
The cost of a wrong assumption rises once a team starts building. The faster path is to test the workflow before production hardens around it.
Physical and spatial decisions need shared context. Teams move faster when designers, operators, and decision makers can review the same simulated environment.
AI agents for physical work need more than chat. They need place models, workflow rules, visual context, device constraints, and evaluation loops.
WorldAgents
The Spatial Intelligence Engine (SIE) turns spaces into context an agent can use: environment, tasks, policies, visual input, and device constraints.
