Beyond Models: Reflections on Engineering AI-enabled Systems in a Project-Based Course

The paper discusses the design and implementation of a project-based master's course on AI-enabled systems, where students developed a movie recommendation system while addressing architectural design challenges, including scalability and deployment. A mixed-methods study revealed persistent difficulties in early architectural decisions and integration of machine learning components, highlighting the need for improved educational approaches in teaching software engineering for AI systems. This work emphasizes the importance of system-level reasoning and data-centric practices for practitioners involved in building robust AI-enabled applications.