GitLake: Git-for-data for the agentic lakehouse

We present GitLake, a Git-for-data design for an agent-first lakehouse.

The system lifts single-table Iceberg snapshots into lakehouse-wide commits, branches, and merges, letting agents work on isolated branches while humans review and publish changes.

Pipelines run on temporary branches and publish through a final merge, so all outputs become visible atomically or none do.

Finally, we report production lessons as well as correctness insights from a preliminary Alloy model of our core abstractions.