In this paper, we report some challenges encountered in developing Prometheus, a software environment that supports the construction and revision of explanatory scientific models. Our responses to these challenges include the use of quantitative processes, to encode models and background knowledge, and the combination of AND/OR search through a space of model structures with gradient descent to estimate parameters. We report our experiences with Prometheus on three scientific modeling tasks and lessons learned from those efforts. We conclude by noting additional challenges that were not apparent at the outset of our work.