The agent wrote the code. The tests are green. The linter is clean. You can't explain what changed.

说明与用途

当开发者依赖 AI 代理时，即使代码通过所有自动化检查，也可能在一个月内失去对代码的理解。实施理解检查并为架构维护分配时间，可保持调试和演进代码的能力。

问题

When developers rely on AI agents to write code, they can lose the mental model of the code within a month, leading to a situation where the code passes all automated checks but the author cannot explain its intent or debug it when issues arise.

结果

Implementing a comprehension check and dedicating time for mental model maintenance prevents the loss of understanding that can occur after a month of agent-driven development, ensuring developers can still debug and evolve the codebase.

工作流

• 1. Review every line of the agent-generated diff initially.
• 2. Within a week, skim the diff and rely on the agent’s summary.
• 3. Approve based on green tests and auto-LGTM after two weeks.
• 4. After a month, developers cannot explain the code’s intent during reviews.
• 5. When the agent fails to fix a bug, developers cannot step in due to lack of understanding.
• 6. Implement a comprehension check: close the diff, write a brief explanation of what changed, why, and what breaks if reverted.
• 7. If explanation fails, set a breakpoint, observe variables and call stack, and try again.
• 8. If still unclear, do not merge the PR.
• 9. Allocate one day a week for architecture review and mental model maintenance.

证据

Two independent custdevs reported the same timeline: a month of agent-driven development, and the developer can no longer explain the code they are shipping.

来源

Compilation, green tests, and auto-LGTM — the three signals most pipelines use to accept a change — can all pass on code nobody understands.

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If you can close the diff, describe what changed, why it changed, and what breaks if it reverts — you own the change. If you can’t, the diff owns you.

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