Mastery is the state of genuinely knowing a concept, not merely having encountered it. It implies you can apply the idea in a new situation, explain why it works, and anticipate where it breaks — the difference between recognizing a caching strategy and being able to design one under real constraints.
For measuring engineering understanding, mastery must be evidence-based and conservative: it is earned through demonstrated understanding across real work, not claimed from a single correct answer, and it can fade if unused. A responsible model of mastery is slow to award and honest about uncertainty, precisely because overstating what someone knows is worse than admitting a gap.
This is why Engineering Intelligence grounds mastery in accumulated evidence from an engineer's actual changes and comprehension checks, rather than self-report.