The field of programming education is undergoing significant changes with the integration of AI tools, leading to a shift in the way programming is taught and learned. Researchers are exploring the impact of AI code assistants on novice programmers, highlighting both the benefits and challenges of these tools. The need for pedagogical strategies that integrate AI meaningfully while reinforcing foundational programming skills is becoming increasingly apparent. Studies are also investigating student perceptions of assessment practices and the effectiveness of different learning activities, such as lab assignments and projects. Furthermore, the use of reflective homework and dual-submission homework is being explored as a way to foster reflection and discourage reliance on online answer repositories. Noteworthy papers include: Between Tool and Trouble: Student Attitudes Toward AI in Programming Education, which highlights the need for pedagogical strategies that integrate AI meaningfully. Teaching Introduction to Programming in the times of AI: A case study of a course re-design, which provides a review of the state-of-the-art AI tools available for teaching and learning programming. Reflective Homework as a Learning Tool: Evidence from Comparing Thirteen Years of Dual vs. Single Submission, which found that dual-submission significantly improved outcomes in a majority of cases.