Generative AI is accelerating software development, but may quietly shift where the real risks lie. As AI generates code faster than teams can understand it, two under appreciated forms of debt accumulate: cognitive debt, the erosion of shared understanding across a team, and intent debt, the absence of externalized rationale that both developers and AI agents need to work safely with code. This article proposes a Triple Debt Model for reasoning about software health built around three interacting debt types: technical debt in code, cognitive debt in people, and intent debt in externalized knowledge. Cognitive debt concerns what people understand; intent debt concerns what is explicitly captured for humans and machines to use. We discuss how generative AI changes the relative importance of these debt types, how each can be diagnosed and mitigated, and surfaced points of debate for practitioners.

翻译：生成式人工智能正在加速软件开发，但可能悄然改变了真正风险的所在。当人工智能生成代码的速度超过团队理解能力时，两种尚未充分认知的债务正在积累：认知债务——团队共同理解的侵蚀；以及意图债务——缺乏外化的理由，而这些理由对开发者和人工智能代理安全操作代码都不可或缺。本文提出了一个三重债务模型，用于推理软件健康，该模型围绕三种相互作用的债务类型构建：代码中的技术债务、人员中的认知债务以及外化知识中的意图债务。认知债务关乎人们理解的内容；意图债务关乎为人类和机器使用而明确捕获的内容。我们讨论了生成式人工智能如何改变这些债务类型的相对重要性、每种债务如何被诊断和缓解，并提出了供从业者辩论的议题。