Since catalytic activity can be extracted from a reaction network including the reactants and potential catalyst candidate, many groups (including us) have worked to develop methods for automated reaction discovery for the generation and exploration of reaction networks. This in principle provides a way of discovering completely novel catalysts for reactions with no prior knowledge of catalytic activity. Some proof-of-principle papers have been presented using these methods to discover the mechanism of a catalytic cycle. Specifically the cobalt-catalyzed alkene hydroformylation has been a popular example, since the system consists of only 18 atoms. A more widespread application of these reaction discovery methods is mostly hindered by the vast computational cost of freely growing several reaction networks. In order to move from hypothesis-testing to discovery, the methods need to be efficient enough that screening of different potential catalyst candidates is possible.