Foraging research aims at describing, understanding, and predicting resource-gathering behaviour. Optimal Foraging Theory (OFT) is a sub-discipline that emphasises that these aims can be aided by segmenting foraging behaviour into discrete problems that can be formally described and examined with mathematical maximization techniques. Examples of such segmentation are found in the isolated treatment of issues such as patch residence time, prey selection, information gathering, risky choice, intertemporal decision making, resource allocation, competition, memory updating, group structure, and so on. Since foragers face these problems simultaneously rather than in isolation, it is unsurprising that OFT models are ‘always wrong but sometimes useful’. I will argue that a progressive optimal foraging research program should have a defined strategy for dealing with predictive failure of models. Further, I will caution against searching for brain structures responsible for solving isolated foraging problems.