This demo paper presents Emora STDM (State Transition Dialogue Manager), a\ndialogue system development framework that provides novel workflows for rapid\nprototyping of chat-based dialogue managers as well as collaborative\ndevelopment of complex interactions. Our framework caters to a wide range of\nexpertise levels by supporting interoperability between two popular approaches,\nstate machine and information state, to dialogue management. Our Natural\nLanguage Expression package allows seamless integration of pattern matching,\ncustom NLP modules, and database querying, that makes the workflows much more\nefficient. As a user study, we adopt this framework to an interdisciplinary\nundergraduate course where students with both technical and non-technical\nbackgrounds are able to develop creative dialogue managers in a short period of\ntime.\n