This report documents the program and the outcomes of Dagstuhl Seminar 23332, which focused on automated algorithm design (AAD) for optimization. AAD aims to propose good algorithms and/or parameters thereof for optimization problems in an automated fashion, instead of forcing this decision on the user. As such, AAD is applicable in a variety of domains. The seminar brought together a diverse, international set of researchers from AAD and closely related fields. Especially, we invited people from both the empirical and the theoretical domain. A main goal of the seminar was to enable vivid discussions between these two groups in order to synergize the knowledge from either domain, thus advancing the area of AAD as a whole, and to reduce the gap between theory and practice. Over the course of the seminar, a good mix of breakout sessions and talks took place, which were very well received and which we detail in this report. Efforts to synergize theory and practice bore some fruit, and other important aspects of AAD were highlighted and discussed. Overall, the seminar was a huge success.