In order to make machine learning algorithms more usable, our community must be able to design robust systems that offer support to practitioners. In the context of classification, this amounts to developing assistants, which deal with the increasing number of models and techniques, and give advice dynamically on such issues as model selection and method combination. This paper briefly reviews the potential of meta-learning in this context and reports on the early success of a Web-based data mining assistant.