tl;dr: As AI agents write more code, humans still need to understand it—not just to verify (agents are getting good at that), but to participate meaningfully in the ongoing creative loop and avoid "cognitive debt." The author proposes three techniques borrowed from education: rich explanations (structured "literate diffs" with background, intuition, and quizzes to check comprehension), micro-worlds (interactive tools and debuggers that let you explore how code works), and shared spaces (collaborative environments where teams build mental models together). The broader point: AI's real promise is augmenting human understanding, not just automating it away.