Right from the start of this essay I must dispense with the royal “we” to make it clear for the readers: what comes next is the product of a personal gedankenexperiment (thought experiment). Pulmonary vascular disorders, which frequently lead to pulmonary hypertension, are complex and multifactorial. One glance at the pulmonary hypertension classification list, which is revised every decade, makes this clear. According to Daniel Kahneman,1 complexity reduces the validity of a forecast, claim, or hypothesis—hence our need for algorithms and large databases, which help us in making decisions. Both diagnostic or treatment algorithms and databases are hypothesis-free. These tools, which are based on statistical information gathered from large but sometimes not homogenous cohorts, are used for forecasting and prognostication. As the clinical pulmonary hypertension community is surviving the 6-minute walk crisis in search of new end points, it has occurred to many in this community that hypothesis testing first requires hypothesis generation. According to Kahneman, this gets us into the territory of uncertainty and unpredictability—in his words, into “low-validity environments.” Depending on your degree of risk aversion, you may not be comfortable in such an environment. However, comfort comes from the testing of the hypotheses, which is the step that follows the hypothesis-generating first step. There are many ways to skin a cat and many ways to generate a hypothesis. For this particular exercise, my approach is to identify the spokes—and I will need to explain why I call a spoke a spoke, and I will need to declare to what degree the identification or recognition of a spoke may be biased. Similar to the level or validity of evidence rating, I will rate my bias the following way: little bias (A), moderate bias (B), and probable high bias (C). My hope is that the reader will enjoy this exercise as much as I did.