“We investigate classic diffusion with the added feature that a diffusing particle is reset to its starting point each time the particle reaches a specified threshold. In an infinite domain, this first-passage resetting is non-stationary, and its probability distribution exhibits rich features. In a finite domain, first-passage resetting leads to a nontrivial optimization problem in which a cost is incurred whenever the particle is reset and a reward is given when the particle stays near the reset point (maximal performance). We derive the condition to optimize the net gain (reward-cost). We also explore simple consequences of first-passage resetting in a toy model of wealth sharing.”