A simple working system creates tight feedback loops: you can measure outcomes quickly, attribute them to specific choices, and adapt. That learning loop is often more valuable than any single feature, because it turns uncertainty into information.
As the system grows, those loops can slow down; therefore, starting small isn’t merely a convenience—it’s how you preserve learning while the stakes are low. In practice, this is why prototypes, pilots, and “minimum viable products” are not buzzwords but mechanisms for converting ideas into tested knowledge. [...]
