Using revision to produce extended natural language text through a series of drafts provides three significant advantages over a traditional natural language generation system. First, it reduces complexity through task decomposition. Second, it promotes text polishing techniques that benefit from the ability to examine generated text in the context of the underlying knowledge from which it was generated. Third, it provides a mechanism for the interaction of conceptual and stylistic decisions. Kalos is a natural language generation system that produces advanced draft quality text for a microprocessor users’ guide from a knowledge base describing the microprocessor. It uses revision iteratively to polish its initial generation. The system performs both conceptual and stylistic revisions. Example output of the system, showing both types of revision, is presented and discussed.