We have developed a technically innovative fusion of (1) dynamic SHERPA/HTA-based decision trees, (2) real-time CT-to-3D anatomical rendering, and (3) contextual, tool-triggered cognitive assessments. These components enable training not only of motor skills, but of real-time decision-making, error mitigation, and spatial awareness—essential competencies in endoscopic sinus surgery (ESS), which is anatomically complex and carries a steep learning curve. Using curated radiologic and clinical datasets, we will build case scenarios that incorporate disease progression, comorbidities, and diagnostic dilemmas. The AI engine will guide trainees through reasoning steps, linking imaging interpretation, pathology, and procedural choices. This cognitive scaffolding in VR does not currently exist in any ESS simulator.