It is a time-consuming and difficult task for an individual, a group, or an organization to systematically express and organize their expertise so it can be captured and reused. Yet the expertise of individuals within an organization is perhaps its most valuable resource. Q&A attempts to address this tension by providing an environment in which textual representations of expertise are captured as a byproduct of using the system as a semiautomatic question-answering intermediary. Q&A uses its experience referring questions to expert users to answer new questions by retrieving previously answered ones. If a user’s question is not found within the collection of previously answered questions, Q&A suggests the set of experts who are most likely to be able to answer the question. The system then gives the user the option of passing a question along to one or more of these experts. When an expert answers a user’s question, the resulting question-answer pair is captured and indexed under a topic of the expert’s choice for later use, and the answer is sent to the user. Unlike previous work on question-answering systems of this sort, Q&A does not assume a fixed hierarchy of topics. One of the main contributions of this work is a set of techniques for managing the emerging organization of textual representations of expertise over time by mediating the negotiation of shared representations among multiple experts.