This experience report describes the instructor and student experience of a “just-in-time”, blended approach to prerequisite review, implemented in a machine learning course but applicable elsewhere. Although prerequisites are commonly used to structure university curricula, both the literature and our experience show that students sometimes forget prerequisite knowledge when they need it in subsequent courses. This challenge is especially pronounced in courses where diverse prerequisite concepts are applied throughout the semester, with different concepts required for different units. Our approach consisted of short prerequisite review quizzes due before each lecture, where the quiz questions assess the mastery of key prerequisite concepts needed for that lecture.Moreover, each quiz was accompanied by a brief instructional video that provided targeted review of the content. We evaluated this approach across two course implementations, based on perspectives from two instructors and 353 students. Both instructors and students felt positively: reduction in prerequisite related questions during lectures was observed, and students reported that the approach helped to bridge gaps in preparedness, improved self-efficacy, and was efficient. More interestingly, the responses showed key tradeoffs regarding the timing, modality, and level of support in a prerequisite review intervention. While we believe this approach to be applicable for other courses with diverse requirements, our results lead us to believe that there is no one-size-fit-all for prerequisite review, and that it is highly context-dependent.