As AI Writes and Reviews Code, the Traditional Pull Request Model Faces Collapse

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The rise of large language models and autonomous coding agents is fundamentally disrupting the pull request (PR) workflow that has long governed software development. Traditionally, PRs served three roles: quality control, knowledge transfer, and establishing team ownership of code. When AI both generates and reviews code, a verification paradox emerges — two models trained on similar data may reinforce each other's blind spots rather than catch meaningful errors. The loss of human narrative in code reviews also threatens institutional memory, as AI agents make probabilistic choices with no documented reasoning behind them. Industry analysts are now calling for a new paradigm based on semantic verification and property-based contract testing to address these gaps.

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