[lifeslogit]

There are layers of each problem space that benefit from optimization and good design more than others, however, most solutions still need all the other layers to be useful. I've had extreme success being a data generalist at a mid-sized analytics company because I was able to be the one to fill in all the gaps of a project, e.g if there are 10 steps that need to be completed, the generalist can do 7 of them and the specialists can do a great job on those other 3. This is the magic of human collaboration after all! On the flip side, I've found that working alone I miss having the specialists. While I know I can technically achieve all the steps, what I really want is the context the specialists can add. Those bits of code or math that turn a vanilla engineered solution into a nuanced piece of software. My conclusion is that collaboration between generalists and specialists is important but asymmetric. Generalists need context and information from specialists so they can become semi-specialists, while specialists simply need generalist infrastructure to power their ideas.