The pull request outlived its obituaries and got a bigger job

As AI agents and automation rapidly increase pull request volume, commentators debate whether traditional code review can survive, but the central challenge is ensuring that generated changes remain understandable, validated, and accountable before reaching production. GitHub reports major growth in merged pull requests and commits, while platform strain and maintainer workloads illustrate how automated contributions can overwhelm existing review processes. The proposed response is not to eliminate pull requests but to expand their function beyond displaying code diffs, incorporating prioritization by risk, independent testing and security validation, contextual explanations of agent activity, and clear records of human approval. GitHub, open-source projects, and tools such as CodeRabbit are adding controls and review workflows intended to help maintainers manage high volumes of AI-generated work, particularly from contributors unable to explain or defend their submissions. Under this model, pull requests become richer checkpoints where humans assess evidence, understand consequences, and accept responsibility for software produced partly or largely by agents.

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