Empirical research from ReWeaver AI. 42 identical prompts, across 5 tools and 8 production dimensions, compared to human baseline. One metric that changes how you see drift.
Everyone knows AI-generated code has quality issues. What’s less understood is that the way most teams measure those issues — by how often they occur — systematically understates the risk.
We ran a controlled study to find out how badly. The answer surprised us, particularly in one dimension.
What We Did
We gave five leading AI coding tools (Cursor, Claude Code, Lovable, Figma Make, and VS Code with Copilot) 42 identical prompts: realistic single-component builds — buttons, forms, dashboards, navs, modals, auth surfaces. We scanned every output with ReWeaver, our deterministic drift-detection engine, across eight production readiness dimensions:
