Knowledge is useless if it can’t be discovered. If software is a good explanation, and that explanation can’t be investiated and the knowledge it encodes shared, what was the point of even writing it?
- Self-Validating Good Explanations
- Performer Metrics
Science and the scientific method is the most efficient way humanity has developed to systematically generate Discoverable Knowledge. The method centers around Feedback Loops of generating a falsifiable hypothesis and then putting those Theories Under Test. That falsifiable hypothesis is described as a Good Explanation by David Deutsch in his book “The Beginning of Infinity.”
- Empowering Environments
- Continuous Learning
However, it does make it hard to have Discoverable Knowledge.
Potential improvements would come not from prescribing any particular procedure or workflow; that would de-prioritize partition tolerance. Instead, giving more explicit effort towards avoiding unnecessary divergence would allow for more readily Discoverable Knowledge. This opens the door for propagating information across communication channels and making it easier to suggest strategies to optimize Feedback Loops.