Pulse
2026-09-18-v3.0
Dataset
2026-10-27-catalog-ai-v2
Ruleset
b2e8889c66f7
Scanned
2026-10-27
Window
February–September 15, 2026
Catalog tracking observation. This repository is measured with the same fixed window and ruleset, but it is not part of the published benchmark or its aggregate claims.

PyTorch native quantization for training and inference

01Result

pytorch/ao ↗

pytorch/ao AI coding statistics: 4%

of 498 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate
4% agent · top contributor 45%11 contributors
org-wide

Adoption is broad. Many contributors are committing agent-authored work, which is what a real organisational rollout looks like.

20
agent commits
478
other considered commits
11
agent contributors
45%
largest contributor

02Drivers

What shapes this result

Mode, timing, and detected signatures show whether the result reflects broad adoption or one concentrated workflow.

Assisted or autonomous

20assisted
0autonomous

Assisted — a developer’s identity authored the commit and the agent added itself as co-author. Autonomous — a bot identity authored the commit without a human identity attached.

Agent share by month

Agent-attributed commit share by month
MonthAgent shareConsidered commits
2026-020%91
2026-034.2%119
2026-048.8%91
2026-053.5%57
2026-0611.1%27
2026-070%41
2026-083.6%56
2026-090%16

Peak month: 11.1%. Bars are scaled to that peak, not to 100%.

Which agents

AgentVendorCommitsShare
Claude CodeAnthropic102%
GitHub CopilotGitHub91.8%
Cursor AgentAnysphere10.2%

03Evidence

Inspect the matches

Public commit samples let you inspect the signatures behind the aggregate result.

Matched commit samples

  • 46e106b8 on GitHub[nvfp4_training] Support NVFP4 GroupedExperts on Blackwell (#4598)Claude Code
  • 5647df97 on GitHub[PT2E][X86] Fall back to plain linear annotation for reused nn.Linear withClaude Code
  • 9467cd8a on GitHub[mxfp8] Fix mx_mm backward crash on non-contiguous grad_output (#4470)Claude Code
  • b506da55 on GitHub[X86] multi-ISA portable kernel compilation and runtime dispatch (#4159)GitHub Copilot
  • 5cc2ef9e on GitHub[PT2E][Docs] Calibration is a must for both static and dynamic quantizatioGitHub Copilot
  • 92dcc961 on GitHub[X86] Fix correctness bug of DA8W4 linear kernel on certain platforms (#43GitHub Copilot
  • 96dd8fc7 on GitHub[ROCm][CI] Update to ROCm version 7.14 (#4755)Cursor Agent

04Method

What entered the denominator

The result begins with commit history, removes merges and routine automation, and reports literal agent signatures as a lower bound.

Exclusion ledger

Commits in window499
Merge commits removed−0
CI / dependency bots removed−1
Considered498

Bots are excluded from the denominator entirely. Agent attribution requires a literal supported signature; no code-style inference is used.

Continue exploring

Claude Code commitsBrowse repositories with detected Claude Code signatures →GitHub Copilot commitsBrowse repositories with detected GitHub Copilot signatures →Cursor Agent commitsBrowse repositories with detected Cursor Agent signatures →Python AI coding statisticsCompare evidence across Python repositories →GitHub AI commit analyzerInspect another repository with the same evidence model →
Reproduce this observation

Run the same detector locally.

Deterministic signature matching; no code-style inference. Squash merges can remove trailers, so this result remains a measured floor.

npx qmmit-cli pytorch/ao

Scan another repository

Try