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Inter-disciplinary, multi-disciplinary, cross-disciplinary research is much lauded and encouraged in academia. The reasonfor this  is clear: cross-fertilization of ideas is undeniably a good thing. One obvious example of this Interdisciplinary research allows for disciplines and cultures to borrow research methods, practices, approaches, and results from one another. After all, scholars do not do research in a vacuum \cite{Pepe}. And as the boundaries separating departments and disciplines fade, collaboration among them naturally increases. While interdisciplinary research  is indeed a \textit{good} thing for academia, I would like to argue that it is a \textit{bad} choice to jumpstart an academic career.  As Here's my story, for example. Since my undergraduate degree and all  the boundaries separating departments and disciplines fade, collaboration among them naturally increases. While this way through my graduate studies and my postdoc, I was pushed to take classes in other departments. My undergraduate degree was in \textbf{Astrophysics} and I took two or three classes in Computer Science. This  is rather normal. A lot of physicists are (and need to be) good at computers. I liked these classes enough to apply for a Masters in \textbf{Computer Science} which I completed right after my Bachelor. I then worked two research jobs. The first at CINECA, Italy, where I did Astronomical Data Visualization (a great way to blend Astrophysics and Computer Science). The second one at CERN, Switzerland, where I worked with data repositories, digital libraries, natural language processing, Open Access. In my years at CERN, I started getting more and more interested in data and information science. I applied and got into a Ph.D. program in \textbf{Information Studies} at UCLA. Anything that falls under the umbrella of Data Science and Information Science is intrinsically interdisciplinary and the classes I took at UCLA where as interdisciplinary as it gets. During my first two years as a Ph.D. I took classes such as \textit{Computational Social Science, Critical studies of architecture, Geographic thought and the concept of belonging, Thinking, Formal Modeling and Simulations in Social Sciences,} and \textit{Data and media arts}.  Since my undergraduate degree and all the way through my graduate studies and my postdoc, I was pushed to take classes in other departments,  to apply research methods