This is tangential to your point, but it’s funny how sometimes the amount of information on a topic can ultimately be a detriment due to the dilution of truth over time.
I’ve been spending my free time working with an experimental library. Google stops returning relevant results for searches on this topic around the 10th result. While this is often infuriating and leads to countless hours deep in indecipherable library code, it is equally likely to stumble upon an in depth discussion among users about pros and cons of various solutions. This context is rarely captured for mainstream tools, and when it is, those authors are lauded for their ability to contextualize the problem.
What is most disappointing to me is how often we document “what” but not “why” when most of us NEED the context of “why” to make comparisons across different tools or approaches for our use cases.
I’ve been spending my free time working with an experimental library. Google stops returning relevant results for searches on this topic around the 10th result. While this is often infuriating and leads to countless hours deep in indecipherable library code, it is equally likely to stumble upon an in depth discussion among users about pros and cons of various solutions. This context is rarely captured for mainstream tools, and when it is, those authors are lauded for their ability to contextualize the problem.
What is most disappointing to me is how often we document “what” but not “why” when most of us NEED the context of “why” to make comparisons across different tools or approaches for our use cases.