As development using AI agents progresses, concerns have been raised that decisions regarding refactoring—the restructuring of system architecture—are decreasing.
Concerns Over the Lack of Refactoring Decisions Due to the Use of AI Agents
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In traditional development, the point at which humans can no longer grasp the complexity of the code has served as a critical indicator for executing refactoring. Design methodologies such as modularization and encapsulation were also means of addressing the limitations of human working memory.
However, AI agents are not subject to human constraints. Agents can decipher intricately intertwined functions and branches, and can appropriately add new processing even within code that has become so cluttered that it is incomprehensible to humans.
Agents do not "get lost" within the code. Consequently, they may fail to sense signals that a system is falling into an unmanageable state, potentially continuing to pile up exception handling without ever correcting the underlying structural issues.
Source: AI Agents and the Refactoring That Never Happens (Hacker News Frontpage, 2026-09-03)