In this poster, I outline how I chose to be on only some of the bandwagons (Rex Bernardo 2016) to rebuild Purdue’s soft red winter wheat breeding program since 2015. Wheat breeding programs in KY, OH, IL, MI, NY, and IN created a genomic selection (GS) consortium in 2020. In this project, we increased the capacity of stage-1 testing outside of the state of origin, referred to as sparse testing. We also use genomic prediction besides phenotypic selection to increase the confidence of selection from the single-replicated stage-1 trials. Genotypic data were produced after planting of 600 stage-1 Purdue lines. After harvest, genomic estimated breeding values (GEBVs) based on current season “raw yield” and “relative yield” data were predicted. Across 5-fold cross-validation with 20 iterations, the averages and ranges of accuracies, in terms of correlation of true phenotypes and GEBVs, were 0.53 (0.37-0.63) for “raw yield” and 0.57 (0.38-0.69) for “relative yield”. The stage-1 lines used in 2020-21 were progeny of 2015 crosses and breeding populations that were developed in large field plots to allow natural and breeder selection for multiple years. I avoided speed breeding because it is associated with the risk of small size breeding populations, lack of natural in-field, and lack of breeder selection during the early generations. In our line production pipeline, lines are extracted from F4 bulk generation plots, head rows are planted as F5, and stage-1 testing are planted as F6 generation. For incorporating genomic prediction, I used a combination of phenotype and GEBVs as selection criteria to advance from stage-1 testing. Those that showed highest phenotypes and highest GEBVs received highest priority for advancing. We are now able to produce much more lines than our capacity to place them in stage-1 testing. Maybe genomic prediction of untested lines can be used as a strategy to pre-select what should go for testing. We collaboratively continued NorGrains under a new brand of BIG6. The key change is massively increasing the number of advanced lines testing in multiple locations.