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.

A PyTorch native platform for training generative AI models

01Result

pytorch/torchtitan ↗

pytorch/torchtitan AI coding statistics: 1.5%

of 1,089 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate

1.5% agent · top contributor 18.8%12 contributors

org-wide

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

agent commits

1,073

other considered commits

agent contributors

18.8%

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

16assisted

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

Peak month: 2.5%. Bars are scaled to that peak, not to 100%.

Which agents

Agent	Vendor	Commits	Share
Claude Code	Anthropic	14	1.3%
Cursor Agent	Anysphere	1	0.1%
OpenAI Codex	OpenAI	1	0.1%

03Evidence

Inspect the matches

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

Matched commit samples

d263ca0a on GitHub[rl] Pin renderers 0.1.11, render with TorchTitan's tokenizer, take the reClaude Code
0ff24646 on GitHub[New Model]Add DeepSeek V4 model support (#3634)Claude Code
5fecad92 on GitHub[kimi k3] add eager reference model with FSDP2 (#4025)Claude Code
1c40dd26 on GitHubFix AMD 8-GPU-feature CI (#3896)Cursor Agent
046fdbbe on GitHubSupport mark_unbacked in minimal_fx_tracer (#3046)OpenAI Codex

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 window	1,100
Merge commits removed	−0
CI / dependency bots removed	−11
Considered	1,089

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 →Cursor Agent commitsBrowse repositories with detected Cursor Agent signatures →OpenAI Codex commitsBrowse repositories with detected OpenAI Codex 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/torchtitan

Scan another repository

Try

Month	Agent share	Considered commits
2026-02	0%	55
2026-03	2.5%	120
2026-04	1.5%	195
2026-05	0.8%	118
2026-06	1.9%	213
2026-07	1.5%	65
2026-08	1.1%	178
2026-09	1.4%	145