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practical-tutorials/project-based-learning
36.4%
of 22 commits were committed by an AI agent — a floor, not an estimate
Too little recent activity to publish. Only 22 commits landed in this window, so the percentage is noisy. Repositories below 100 are excluded from the index for this reason.
36.4% agent · top contributor 100%1 contributor
individual

One person is driving this. The headline number reflects a single contributor's workflow, not a project-wide shift.

8
agent commits
14
human commits
1
agent contributors
100%
largest contributor

Assisted or autonomous

8assisted
0autonomous

Assisted — a developer’s identity authored the commit and the agent added itself as co-author. The agent ran git commit during a working session, with a person there. Autonomous — a bot identity is the author, no human in the loop. Across the whole index, 93.7% of agent commits are assisted.

Which agents

Claude CodeAnthropic836.4%

Verify it yourself

Sample commits that matched. Every one links to GitHub — check the trailers.

  • f55fe25bAdd Networking from Scratch to C/C++ Network programming (#864)Claude Code
  • 25df2892Remove dead 'Write a NoSQL Database in Python' entry (#850)Claude Code
  • 25546408Remove two dead Medium links from JavaScript section (#849)Claude Code

What was excluded

Commits in window32
Merge commits removed0
CI / dependency bots removed10
Considered22

Bots are excluded from the denominator entirely. Counting dependabot as “AI-written code” is the fastest way to produce a meaningless number.

How this was measured

Measured over February–August 2026, cloned directly. Detection is deterministic string matching against signatures agents write about themselves — no heuristics, no style analysis. Merge commits and CI bots are excluded from the denominator. The figure is a floor: squash merges strip trailers, so real usage is higher. Contributor counts are aggregate — no individual is named.

Run it yourself: npx qmmit-cli practical-tutorials/project-based-learning

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