Code Comprehension Gaps in AI-Assisted Development: A Conceptual Framework for Knowledge Erosion Patterns — Patel et al. (2026)
The increasing adoption of AI-powered code generation tools has introduced a critical challenge in software engineering, the potential erosion of developer comprehension of codebases increasingly composed of AI-generated artifacts. Before examining this erosion, we establish that human code comprehension remains a functional requirement in AI-augmented development on four independent grounds: regulatory accountability obligations, the need for human oversight of AI failures, organizational resilience against tool unavailability, and the causal reasoning demands of incident response. This…
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