This study investigates the integration of Generative AI (G-AI) into the FLIP learning methodology, particularly focusing on the "Fail" phase of Manu Kapur's "Productive Failure" approach. Building on our previous study with G-AI in enhancing entrepreneurship education within IT courses, this research explores how these tools can help students identify their knowledge gaps and enhance their learning while also promoting entrepreneurship skills.

In this study, we focus on using productive learning to enhance entrepreneurship education in IT courses. Students interact with AI simulations of well-known figures in their field or their future selves. These interactions challenge their understanding of course concepts, pushing them to confront and understand their misconceptions. By embedding entrepreneurship education into the course, we aim to develop entrepreneurial thinking and skills alongside technical knowledge.

The goal is to assess how G-AI can facilitate productive failure, identify student challenges, and enhance self-directed learning and problem-solving skills. By focusing on the "Fail" phase, students are encouraged to confront their misconceptions early, leading to deeper learning through targeted instruction. The challenges presented in this phase trigger students' entrepreneurial thinking. This approach personalizes learning, increases engagement, and deepens understanding of complex topics. Through these AI interactions, students gain a clearer awareness of their knowledge limits and areas needing improvement, resulting in more effective and meaningful learning experiences that also cultivate entrepreneurial skills.

Keywords: Generative AI, FLIP Learning, Productive Failure, Entrepreneurship Education, entrepreneurial thinking, personalizes learning.