Martin Monperrus argues that coding agents have crossed a capability threshold that renders traditional human code review obsolete. Since Fagan formalised code inspection in 1976, teams have relied on manual scrutiny before merges. Now large language model‑based autonomous systems can read, write, test, and repair code at lower cost and higher throughput. These agents also detect edge cases that humans often miss in complex codebases, reducing bugs before release significantly.

Monperrus claims that every goal of code review—validation, defect detection, knowledge transfer—can be met by agents, and that pairing agents with human reviewers creates a bottleneck. He stresses that a naive model where humans merely sign off on AI‑generated code offers little assurance and fails to scale with the rapid throughput of automated systems across development pipelines everywhere worldwide today.

If coding agents truly outperform humans, the industry may shift from review gates to continuous integration cycles powered by AI. Companies will need to invest in tooling that integrates LLMs with version control, automated testing, and deployment pipelines. Until then, the debate over human oversight versus machine autonomy will shape software quality standards for years in the tech sector today.