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As AI agents generate code at exponentially increasing volume and size, traditional human code review is becoming untenable. PR review time has increased 91% for teams with high AI adoption, while the number and size of changes scale beyond human capacity to read. The proposed alternative is shifting human checkpoints upstream: humans define specs, acceptance criteria, and constraints before code is generated, rather than reviewing diffs afterward. A layered trust model replaces the single review gate, including competing agent outputs, deterministic guardrails (linters, type checks, contract verification), BDD-style acceptance criteria authored by humans, narrow permission scopes for agents, and adversarial verification agents. The conclusion is that 'good code' in an agentic world means code that satisfies machine-verifiable specs, and human judgment is most valuable when defining what correct means, not when reading implementations.

How to Kill the Code Review

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