“When I was a data scientist at Airbnb, I compiled a list of requests I received. Some were certainly greenfield and necessary: e.g., can you help me with a query, can you create a new metric for X, etc. But the majority felt avoidable: e.g., requests for work that I’d already done before, a long tail of follow-up questions on work that I should’ve documented better, or work that I’d known others had done before. And the frustrating thing was that, in these cases, it shouldn’t have been necessary for me to be involved. I had somehow inadvertently made myself the gatekeeper of my own work by forgetting to include context or the query used for an insight. In other cases, because work was not centralized, I was simply operating as a human store of institutional knowledge.”xxxvi