Technical Product Management Course · by Stanislav Belyaev
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AI-Generated Code %

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AI Tools

AI-Generated Code %

AI-Generated Code Percentage tracks the share of production code that was originally authored or substantially generated by AI coding tools. It provides visibility into how much of the engineering output is AI-assisted and helps teams understand their evolving relationship with AI tooling. This metric must be interpreted alongside quality indicators to ensure that increased AI contribution does not come at the cost of maintainability or correctness.

Percentage of production code authored by AI. Brex benchmark: 45%. >60% indicates a critical need for automated QA guardrails.

Scale Impact
👤 Solo / Pair (1–3)
0.5
👥 Team (4–15)
0.6
🏢 Department (15–100)
0.7
🏛️ Organization (100+)
0.8

AI-generated code percentage matters more at scale where quality control is harder. Brex: 45% of changes from Cursor. Risk compounds with codebase size.

0
Influences
2
Influenced by

← Influenced by

AI Code Acceptance Rate

Higher acceptance directly translates to more AI code in the codebase.

Direct correlation
GitHub Accenture Study
Documentation Quality

Better docs = better AI suggestions. AI learns from existing patterns.

AI learns from docs
AI Code Generation Research
Metrics map by Stanislav Belyaev · Analysis powered by Anthropic Claude Opus 4.6 · All data validated by human experts