As my title suggests, this position paper focuses on the relevance of linguistics in NLP instead of asking the inverse question. Although the question about the role of computational linguistics in the study of language may theoretically be much more interesting than the selected topic, I feel that my choice is more appropriate for the purpose and context of this workshop. This position paper starts with some retrospective observations clarifying my view on the ambivalent and multi-facetted relationship between linguistics and computational linguistics as it has evolved from both applied and theoretical research on language processing. In four brief points I will then strongly advocate a strengthened relationship from which both sides benefit. First, I will observe that recent developments in both deep linguistic processing and statistical NLP suggest a certain plausible division of labor between the two paradigms. Second, I want to propose a systematic approach to research on hybrid systems which determines optimal combinations of the paradigms and continuously monitors the division of labor as both paradigm progress. Concrete examples illustrating the proposal are taken from our own research. Third, I will argue that a central vision of computational linguistics is still alive, the dream of a formalized reusable linguistic knowledge source embodying the core competence of a language that can be utilized for wide range of applications.