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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'model'}) and 1 missing columns ({'family'}).

This happened while the csv dataset builder was generating data using

hf://datasets/whyamas/ai-commit-census-reverse-engineering/models.csv (at revision 6c73e249ddb09867574197f440496a55e45a7778), ['hf://datasets/whyamas/ai-commit-census-reverse-engineering@6c73e249ddb09867574197f440496a55e45a7778/families.csv', 'hf://datasets/whyamas/ai-commit-census-reverse-engineering@6c73e249ddb09867574197f440496a55e45a7778/models.csv', 'hf://datasets/whyamas/ai-commit-census-reverse-engineering@6c73e249ddb09867574197f440496a55e45a7778/projects.csv', 'hf://datasets/whyamas/ai-commit-census-reverse-engineering@6c73e249ddb09867574197f440496a55e45a7778/weeks.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1856, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 811, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 822, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              model: string
              commits: int64
              projects: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 612
              to
              {'family': Value('string'), 'commits': Value('int64'), 'projects': Value('int64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'model'}) and 1 missing columns ({'family'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/whyamas/ai-commit-census-reverse-engineering/models.csv (at revision 6c73e249ddb09867574197f440496a55e45a7778), ['hf://datasets/whyamas/ai-commit-census-reverse-engineering@6c73e249ddb09867574197f440496a55e45a7778/families.csv', 'hf://datasets/whyamas/ai-commit-census-reverse-engineering@6c73e249ddb09867574197f440496a55e45a7778/models.csv', 'hf://datasets/whyamas/ai-commit-census-reverse-engineering@6c73e249ddb09867574197f440496a55e45a7778/projects.csv', 'hf://datasets/whyamas/ai-commit-census-reverse-engineering@6c73e249ddb09867574197f440496a55e45a7778/weeks.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

family
string
commits
int64
projects
int64
Claude
183,907
675
GPT / Codex
10,022
34
GitHub Copilot
1,639
33
Cursor
1,110
21
Open models
304
10
Other agents
220
4
Gemini
69
5
Devin
22
3
null
106,567
509
null
29,962
164
null
13,126
126
null
10,333
123
null
9,713
34
null
9,511
136
null
8,754
52
null
4,280
93
null
4,170
51
null
3,063
80
null
2,391
7
null
1,639
33
null
1,515
47
null
1,110
21
null
866
37
null
97
null
null
67
null
null
188
null
null
74
null
null
59
null
null
377
null
null
42
null
null
20
null
null
254
null
null
3
null
null
2,243
null
null
3,858
null
null
40
null
null
307
null
null
479
null
null
19
null
null
13
null
null
221
null
null
43
null
null
355
null
null
6
null
null
4
null
null
180
null
null
6
null
null
313
null
null
31
null
null
466
null
null
135
null
null
1,188
null
null
1,822
null
null
4,246
null
null
48
null
null
30
null
null
20
null
null
22
null
null
10
null
null
3,041
null
null
36
null
null
23
null
null
13
null
null
131
null
null
24
null
null
562
null
null
259
null
null
823
null
null
15
null
null
871
null
null
166
null
null
324
null
null
66
null
null
131
null
null
1,139
null
null
117
null
null
48
null
null
87
null
null
6,853
null
null
26
null
null
56
null
null
146
null
null
772
null
null
105
null
null
17
null
null
1,239
null
null
26
null
null
72
null
null
140
null
null
5
null
null
1,428
null
null
4
null
null
2
null
null
297
null
null
1,050
null
null
202
null
null
1
null
null
32
null
null
493
null
null
39
null
End of preview.

AI commit census for reverse engineering projects

Version 2026-11-10. Measured on 10 Nov 2026 (snapshot captured 2026-11-10T08:52:25Z).

This dataset counts how many commits in public reverse engineering projects credit an AI tool as co-author or author. At the snapshot, 190,658 of 450,474 commits (42%) across 838 public projects credited an AI. Claude is credited on 183,907 commits and GPT / Codex on 10,022. The census covers every kind of project, games included.

The census is published on the web at https://reversedwithai.com/ai-commit-census, and this dataset is the same data as a file. I run it, and I rerun it about once a week. Each listed project has its own page at https://reversedwithai.com/p/, with the same figures.

How it was measured

  • I count the AI co-author credits that coding tools write into each project's public git history. A commit counts only if it names an AI as co-author or author, typically through a Co-authored-by trailer.
  • The repositories are the 859 that my discovery had found on GitHub by 10 Nov 2026: 508 listed in the directory and the rest awaiting review.
  • Each commit counts once. Commits are matched by hash. Forks repeat their parent's history, so forks are grouped into one project by their first commit.
  • A commit crediting two models counts once for each model.
  • Figures for individual projects are published only for the 508 listed entries. The corpus totals (838 projects) include the unlisted projects, which have no per-project rows in this dataset.

Limits

These limits are copied from the census page.

It is a minimum. A commit counts only if it names an AI as co-author or author, and many tools and people leave that out.

Commit counts measure activity. An agent that commits every few minutes counts for far more than a person who squashes a week of work, and the 10 busiest projects account for 39% of AI-credited commits.

It doesn't show whether the result works. For that, see each project's reported outcome.

Each commit counts once. Forks repeat their parent's history, so commits are matched by hash and forks are grouped into one project by their first commit.

The repositories are the 859 that our discovery had found on GitHub by 10 Nov 2026: 508 listed in the directory and the rest awaiting review. Recently active repositories are easier to find, so recent weeks can look busier than they were. Figures for individual projects are published only for listed entries.

The page footer adds: "Figures are reported by project authors and not measured by this site."

Notes from checking the files against each other (these are not on the page):

  • The weekly series starts on 18 May 2026. Its aiCommits sum to 175,941, which is 14,717 short of the corpus total of 190,658. The JSON does not explain the gap. Some listed projects have a first AI commit before 18 May, so the gap is probably older commits, but I have not confirmed that.
  • The last week row (starting 9 Nov 2026) is partial, because the snapshot was taken on 10 Nov.
  • projects.csv covers only the 508 listed projects: 292,189 commits and 135,180 AI-credited commits. The remainder of the corpus (158,285 commits and 55,478 AI-credited commits, derived by subtraction) belongs to the unlisted projects, whose per-project figures are not published.
  • In families.csv and models.csv the rows overlap, because one commit can credit two families or two models. Their sums (197,293 and 207,000) are therefore larger than the 190,658 AI-credited commits.
  • For 29 listed projects the model rows add up to fewer commits than the project's aiCommits. The JSON does not say why.
  • For 15 listed projects two models tie for the most commits. top_model takes the first one in the order used in data.json.

Files

File Contents
data.json The full snapshot as published by the census. Keys: version, capturedAt, corpus, families, models, weeks, projects (an object keyed by slug), license, attribution.
models.csv One row per model name as credited (15 rows). Columns: model, commits (commits crediting that model), projects (projects crediting it).
families.csv One row per family (8 rows). Columns: family, commits, projects.
weeks.csv One row per week, 26 rows from 18 May 2026 to the week of 9 Nov 2026. Columns: week (the Monday, YYYY-MM-DD), aiCommits (AI-credited commits that week), activeProjects (projects with AI-credited commits that week; the page does not define this, so this is my reading), newProjects (projects whose first AI-credited commit falls in that week, the page's "First AI commit that week" column).
projects.csv One row per listed project (508 rows). Columns: slug, commits (all commits in the project after de-duplication), aiCommits (AI-credited commits), aiDays (days with an AI-credited commit), firstAi and lastAi (first and last AI-credited commit dates, YYYY-MM-DD, as given in data.json), top_model (the model with the most commits in that project; blank when no model is credited). 83 listed projects have no AI credit and so have a blank top_model.

The CSV files are UTF-8 with a header row and LF line endings. data.json is the source, and the CSVs are flattened from it with a short Python script.

Citation

Reversed with AI, "AI commit census for reverse engineering projects", measured 10 Nov 2026, https://reversedwithai.com/ai-commit-census

Licence

CC BY 4.0. You may reuse the data if you credit Reversed with AI and link to https://reversedwithai.com/ai-commit-census.

Link to the census: https://reversedwithai.com/ai-commit-census

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