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 workbench and product systems, the same pattern informs guarded three-body control under partial local signals, procedural agents acting under occluded state, verb-field NPC behavior, and softbody motion made interpretable through graph signatures.