AI-generated code creates "cognitive debt"—code produced faster than humans can understand it. The author proposes a ledger system with microcertifications tracking who understands what code, verified by domain experts. Every line of code would be cognitive debt until certified as part of a living mental model.
AI-generated code creates "cognitive debt"—code produced faster than humans can understand it. The author proposes a ledger system with microcertifications tracking who understands what code, verified by domain experts. Every line of code would be cognitive debt until certified as part of a living mental model.
Cognitive debt in software development is as harmful as technical debt but lacks an accounting system to track it. Without measurement, teams unknowingly accumulate mental strain that reduces productivity and code quality. The author calls for formal methods to record and address cognitive debt.
Software teams need a formal system to track "cognitive debt"—the mental burden from complex code, poor abstractions, and unclear logic. Like technical debt, it slows development and causes errors and burnout. The article calls for explicit measurement and management of cognitive load in codebases.
Simon Willison reflects on a talk by Geoffrey Litt at AIE, who argued that when collaborating with coding agents, developers must understand the code deeply enough to remain active participants in the creative process, avoiding cognitive debt from drifting understanding.
AI-generated code creates "cognitive debt"—code produced faster than humans can understand it. The author proposes a ledger system with microcertifications tracking who understands what code, verified by domain experts. Every line of code would be cognitive debt until certified as part of a living mental model.
In a July 2026 talk at the AI Engineer conference, Geoffrey Litt, a Design Engineer at Notion, argues that understanding code remains critically important even when using AI coding agents, presenting the idea that comprehension—not generation—has become the new bottleneck in software development.