Review At The End Because AI Erodes Quality Quietly
AI does not fail loudly. It fails by accretion, one plausible shortcut at a time, and the damage shows up in the codebase months later. GitClear analyzed 211 million changed lines from 2020 to 2024 and found the signature of that erosion.
Refactored code, the lines that get moved and consolidated when someone reshapes a system, fell from 25% of changes in 2021 to under 10% in 2024. Copy-pasted lines rose from 8.3% to 12.3%, and 2024 was the first year on record that copy-pasted code outnumbered moved code. Duplicated blocks rose roughly eightfold.
Read that as a pattern, not a verdict. The study is correlational, and other things changed over those years. But the mechanism is familiar to anyone who has watched a fast tool meet a tired team: the machine makes adding easy and reusing hard, so people add. The result passes every test and still weakens the foundation, because duplication and drift do not announce themselves in a green build.
A test suite tells you the code runs. A review tells you the code belongs.
This is why the review at the end is not optional ceremony. It is the one checkpoint positioned to catch what the machine hides: the third copy of a function that should have been shared, the pattern that broke from your system, the shortcut that works today and costs you four times over by year two. A test suite tells you the code runs. A review tells you the code belongs.
The review also has to change to match the tool.
Reviewers should know which parts were AI-assisted and read those parts harder, not softer. The instinct to trust fluent output is exactly the instinct a good review exists to correct. You are not reviewing only for whether it works. You are reviewing for whether it should stay.
Action items
- Add an end-of-work review gate. Check for duplication and drift, not just passing tests. A green build is necessary, not sufficient.
- Flag the AI-assisted sections. Label them so reviewers apply extra scrutiny where fluent output is most likely to hide a shortcut.
- Hunt the third copy quarterly. Once a quarter, look for anything duplicated. If a function or pattern exists in three places, consolidate it before it becomes five.
Resources
Conclusion
Return once more to the typesetters. The ones who struggled were not the least talented; they defined themselves by the part of the job the machine took.
The ones who thrived had decided, before the beige computer arrived, that their craft was never the metal. It was the judgment the metal carried.
AI is handing you the same decision on a shorter clock. The production layer is leaving and not coming back. You can defend the artifacts, the polished screens, hand-built components, or follow craft to its new address.
That address has seven rooms. Choose the right problem first. Keep research a weekly habit, not a phase. Describe your craft, so the machine applies your standards, not its defaults. Build the scaffolding to hold that description. Keep a human in the loop, and a user after them. Evaluate what the machine hands you, and build that judgment into the system. Put a real review at the end, where erosion hides.
None of this is nostalgia. It is where the leverage moved. The tools got faster, judgment got scarcer, and scarce is where craft has always lived. Name it clearly and the machine carries it, amplifying your judgment, not replacing it.