Know exactly how much
code AI writes.

Not estimates. Not surveys. Real attribution from every commit. Tandemu measures AI vs manual code using Co-Authored-By tags — the same standard GitHub uses.

See the Dashboard

AI Attribution

Last 30 days

73%

AI Generated

27%

Manual

Per Developer

Sarah Chen

2,340 lines

78%

James Park

1,870 lines

65%

Alex Rivera

2,100 lines

72%

Mia Thompson

1,420 lines

54%

How it works

Claude Code automatically adds Co-Authored-By: Claude to every commit it helps write. Tandemu reads these tags during /finish and attributes lines to AI or manual — per file, per commit.

git log --oneline

a1b2c3d

feat: add webhook retry with exponential backoff

Co-Authored-By: Claude <noreply@anthropic.com>

e4f5g6h

fix: handle edge case in date parsing

(manual commit — no AI tag)

i7j8k9l

refactor: extract auth middleware into guard

Co-Authored-By: Claude <noreply@anthropic.com>

Measure what matters

AI attribution at every level — individual, team, and codebase.

Team AI Ratio

Overall percentage of AI-generated code across the team. Track adoption trends over weeks and months.

Per-developer breakdown

See who's leveraging AI heavily and who might need enablement. Not for judgment — for coaching.

AI effectiveness by file

Which files have high AI contribution that survives? Where does AI-written code get reverted or rewritten?

Investment allocation

How engineering time splits across features, bugs, tech debt, and maintenance — broken down by AI vs manual.

First-party data, not inference

Other tools estimate AI impact from external signals — installed extensions, survey responses, or API call counts. Tandemu measures it directly from the code. Every line attributed at the commit level. No guessing.

Know exactly how muchcode AI writes.