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Increasingly convinced that high-res metrics, when used as a proxy for some other thing, are almost always worse than fuzzy rules of thumb that deal with the thing directly. It's VERY difficult to get people to intuit that a weak measure can have extremely high apparent precision
Basically: it is not the end of the world if your tools are a bit wonky, messy, or hard to point, BUT they should **look** wonky/messy/hard to point. It should be obvious. "This is wonky" does not belong in the 3rd paragraph of the implementation document nobody reads
You can get much better feedback from a rough sketch than a drawing that looks 'finished'
Reminds me a little bit of the Fence paradoxhttps://twitter.com/visakanv/status/1110799562560528384?s=21 …
The market won't let experts be honest about their ignorance. Nobody wants to hear: "I don't know how much energy X will use since A and B are impossible to predict. If someone tells you they can predict X, they are lying."
They should be presented to the user as wonky absolutely agree, but in derivation take advantage of as much precision as your inferences can support, even if with wide error bands.
Similar to sw prototypes: they should look as unrefined as the underlying code is.
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