Technical debt is the metaphor for choosing a faster, less-clean solution now and paying for it later through harder changes, more bugs, and slower development. Some debt is deliberate and sensible; the danger is debt taken on unknowingly and never repaid.
AI-assisted development introduces a newer, subtler form: understanding debt. When code is generated and merged without anyone truly comprehending it, the team owes future interest not just in messy structure but in missing knowledge. The bill comes due during incidents, security reviews, and refactors — exactly when reasoning about the code is most needed and least available.
Managing technical debt in an AI-native workflow therefore means tracking comprehension, not only code quality: the cheapest debt to avoid is the code no one understood in the first place.