Abstract: How would an A.I. do statistics? Fitting a model is the easy part. The other steps of workflow—model building, checking, and revision—are not so clearly algorithmic. It could be fruitful to simultaneously think about automated inference and best practices in statistical workflow, moving beyond inference for a single model toward statistical problem solving. These same issues arise when a human research team designs and analyzes quantitative data. We discuss in the context of examples from many different application areas.