This demo presents the next-generation version of KimBilet.com, an educational platform that leverages generative AI to create adaptive, mastery-driven learning experiences. Building on last year’s personalized course generation, the new system introduces a fine-grained skill taxonomy and a feedback loop that evaluates and responds to learner performance in real time.

The adaptive algorithm begins with a user’s prompt to generate a topic and a taxonomy of skills needed to master that topic. For each skill, the system creates a focused lesson and a quiz. At the end of the course, learners receive a mastery profile displaying their performance across all skills. Based on these results, the system dynamically adapts: skills mastered with high accuracy are marked complete, while weaker areas trigger the generation of additional remedial lessons and quizzes until mastery is achieved.

This feedback loop transforms static AI-generated lessons into personalized, mastery-based learning pathways. The demo will showcase how KimBilet.com combines generative AI, adaptive skill assessment, and iterative content refinement to engage learners across domains such as standardized test preparation, academic coursework, and professional upskilling. Participants will explore how this approach supports scalable, individualized education and discuss its potential applications in diverse learning environments.