Most systems do not reveal their truth directly. You infer them from signatures — shadows, feedback, distortions, response curves.
The Sundog Project is a framework for turning those indirect signals into actionable software control. Where conventional approaches demand complete world state, Sundog asks whether the partial signal — the shadow, the torque, the occlusion — already contains enough structure to act.
In the core experiment, a controller aligns a reflected beam without target coordinates, using only sparse photometric feedback. In product systems, the same pattern informs procedural agents acting under occluded state, cheaper physical-feeling simulation, and softbody motion made interpretable through graph signatures.