Cognitive debt is emerging as a critical concern for engineering teams, paralleling traditional technical debt. Senior engineering leaders are increasingly discussing the implications of AI adoption in their organizations.

Cognitive debt refers to the gap between a system's evolving structure and a team's understanding of its functionality and adaptability. Generative and Agentic AI may exacerbate this cognitive debt, prompting discussions within various communities about its implications.

Cognitive Debt is a metaphor for the loss of understanding within a team regarding a system's functionality. Margaret-Anne Storey identifies three layers of system health: technical debt in code, cognitive debt in people, and a third unspecified layer.

Shipping multiple features rapidly can lead to cognitive debt, where understanding and maintaining the code becomes challenging. High velocity in development may result in a lack of comprehension about the code's architecture and interactions, complicating future modifications.