Learning from Failure
Learning from failure can be summarized as learning ‘what doesn’t work’.
Out of an arbitrarily large universe of possible things you could be trying (say 18,for the sake of this example), you have successfully accomplished narrowing down the scope of your next trial.
In practice, this can become problematic, because if you are looking to make an informed decision on what to try next, having only crossed one approach off your list (of the hundreds or many thousands of possible approaches to solving a problem), you are left only slightly more informed than where you started.
Learning from Success
Contrast this approach with a model of learning from success, where you have through a series of failed attempts hit upon something that is working and considered to be successful.
In this case, you well served to learn from this success and try to repeat it as much as possible, since success’s are fewer and far between.
Of course, most success come after a long string of successive failures, but in each failure there is some element of success (what actually worked) which can be far more informational than what didn’t work in terms of guiding your decision in what to try next.
Rewards vs Punishments by Jason Hreha of Dopamine.