Verbal working memory (WM) tasks typically involve the language production architecture for recall; however, language production processes have had a minimal role in theorizing about WM. A framework for understanding verbal WM results is presented here. In this framework, domain-specific mechanisms for serial ordering in verbal WM are provided by the language production architecture, in which positional, lexical, and phonological similarity constraints are highly similar to those identified in the WM literature. These behavioral similarities are paralleled in computational modeling of serial ordering in both fields. The role of long-term learning in serial ordering performance is emphasized, in contrast to some models of verbal WM. Classic WM findings are discussed in terms of the language production architecture. The integration of principles from both fields illuminates the maintenance and ordering mechanisms for verbal information.