Pulse
2026-09-18-v3.0
Dataset
2026-09-18-v3.0
Ruleset
b2e8889c66f7
Scanned
2026-09-16
Window
February–September 15, 2026
Local to this browser
pydantic/pydantic-ai ↗

pydantic/pydantic-ai AI coding statistics: 17.2%

of 1,278 commits in February–September 15, 2026 were committed by an AI agent — a floor, not an estimate
17.2% agent · top contributor 31.4%69 contributors
org-wide

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

220
agent commits
1,058
other considered commits
69
agent contributors
31.4%
largest contributor

What shapes this result

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

Assisted or autonomous

217assisted
3autonomous

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. Across the whole index, 96% of agent commits are assisted.

Agent share by month

Agent-attributed commit share by month
MonthAgent shareConsidered commits
2026-0233%103
2026-0350.5%93
2026-0447.6%124
2026-058%137
2026-062.3%129
2026-0717.4%327
2026-082.9%245
2026-091.7%120

Peak month: 50.5%. Bars are scaled to that peak, not to 100%.

Which agents

AgentVendorCommitsShare
Claude CodeAnthropic21216.6%
DevinCognition90.7%
Cursor AgentAnysphere40.3%
GitHub CopilotGitHub40.3%

Inspect the matches

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

Matched commit samples

  • 86b250f3 on GitHubAdd a Comparisons section covering 10 agent frameworks (#8260)Claude Code
  • 0c91425f on GitHubInstall `strict-no-cover` only in the coverage job and authenticate CI's GClaude Code
  • 8c5838dd on GitHubStop rebuilding unmanaged models in durable capability operations (#7972)Claude Code
  • d55a2115 on GitHubAdd `list_prompts` and `get_prompt` functionality to `McpServer` (#3889)Devin
  • f0b19471 on GitHubAdd anthropic speed, `fast` mode for opus 4.6 (#4300)Devin
  • 3b8246a7 on GitHubbug: Warn about Azure OpenAI completions file-incompatibility (#4048)Devin
  • 86b250f3 on GitHubAdd a Comparisons section covering 10 agent frameworks (#8260)Cursor Agent
  • b6798f7e on GitHubfeat(openrouter): add `CachePoint` and prompt caching support (#4604)Cursor Agent
  • f0b19471 on GitHubAdd anthropic speed, `fast` mode for opus 4.6 (#4300)Cursor Agent
  • b25c8b3b on GitHubdocs(models): show how to inspect model capabilities via `model.profile` (GitHub Copilot
  • 4e50e598 on GitHubReject duplicate deferred tool call IDs (#6241)GitHub Copilot
  • 666bfcba on GitHub[docs] Add reference for third-party agent skills capabilities in Coding AGitHub Copilot

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 window1,342
Merge commits removed−2
CI / dependency bots removed−62
Considered1,278

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

Pinned to a source state

This observation names the repository state, release, and detector that produced it. Use these identifiers when reproducing or citing the result.

Dataset release
2026-09-18-v3.0
Scan date
2026-09-16
Ruleset
sha256:b2e8889c66f72c18a61839f0bf1a9f77b5481ba2def044dba33c797b2f2bdcae
Canonical repository
pydantic/pydantic-ai
Default branch
main
Resolved
2026-09-16
Measurement window
February–September 15, 2026
Download observation JSONDeterministic export · same values as this page

Position among comparable repositories

The cohort uses the same release and measurement window, then narrows to the repository’s ecosystem and removes low-activity observations.

CohortPython · 247 eligible repositories · at least 100 considered commits2026-09-18-v3.0 · February–September 15, 2026 · 145 of 392 ecosystem repositories excluded
Agent-commit share position74th percentile

Midrank percentile; equal shares split the tied positions.

Repository
17.2%
Cohort median
6.3%
Share rank
64 / 247
0th50th100th

Percentile = (repositories below + half of 1 tied repository) ÷ 247.

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 pydantic/pydantic-ai

Scan another repository