Managing understanding and intent has always been important in software engineering. AI has been changing the landscape.
Generative AI is dramatically accelerating software development, allowing teams to generate and modify code faster than ever before. For decades, software engineering has focused on managing technical debt—how code structure and implementation make systems harder to change. But in the age of AI, technical debt might no longer be the most important constraint. This article argues that the real risks are shifting toward two less visible forms of debt: cognitive debt and intent debt. Cognitive debt is the erosion of shared understanding across a team where no one can confidently explain how a system works or predict the impact of a change. Intent debt is the absence of clear goals, constraints, and rationale that explain what the system is for and guide how it should evolve, for both humans and AI agents. These debts have always existed, but GenAI accelerates their accumulation while hiding their effects. I propose how these forms of debt can be recognized in practice and suggest strategies teams can use to mitigate them.
From Technical Debt to Cognitive and Intent Debt – Rethinking software health in the age of AI, by Margaret-Anne Storey.
I will not yet go as far as claiming that intent debt and cognitive debt will become seen as more important than technical debt. Certainly though as risks, they are becoming more highlighted, since AI usage is increasing their probability.