That's a fair point and I agree. It's just sometimes difficult to beat automated exploration; as a standard company you probably don't have access to top-end researchers/practitioners, just average ones, and those might get a significant boost by trading smartness for brute force and run many models in parallel in evolutionary fashion.
When you e.g. look at how Google's internal system constructs loss functions and how many combinations do they try, one has to have an unexpected idea to beat their results, and that idea can be usually quickly incorporated into their platform, raising the bar for individual researchers. At Facebook they basically press a few buttons and select a few checkboxes, then wait until best model is selected, leading to frustration among researchers.