A knowledge map turns scattered evidence of understanding into a navigable picture: which concepts an engineer has demonstrated mastery of, which they are still building, and where the blank spots are. Think of it as a skills graph grounded in real work rather than a self-assessment survey.
Each node represents a concept or system — an authentication flow, a caching strategy, a particular framework — and its state reflects accumulated evidence from the engineer's actual changes and comprehension checks. As they work, the map updates: mastery deepens where understanding is demonstrated and stays provisional where code was merged without it.
For teams, the aggregate map reveals concentration risk (only one person understands a critical system) and guides where learning investment pays off most. It is the durable artifact behind Engineering Intelligence.