Incentives are more likely to elicit desired outcomes when they are based on accurate models of agent behavior. A growing literature---from behavioral economics, as well as online user studies---suggests, however, that people do not quite behave like standard economic agents in a variety of environments, both online and offline. What consequences might such differences have for the optimal design of these environments? In this note, we summarize our results from Easley and Ghosh [2015] which explores this question of behavioral design---how departures from standard economic models of agent behavior affect mechanism design---via the problem of the optimal choice of contract structure in crowdsourcing markets where workers make decisions according to prospect theory preferences [Kahneman and Tversky 1979] rather than classical expected utility theory: we show that a principal might indeed choose a fundamentally different kind of mechanism---an output-contingent contest versus a 'safe', output-independent, fixed-payment scheme---and do better as a result, if he accounts for deviations from the standard economic models of decision-making that are typically used in theoretical design.