[D] Rebase for agents: why your AI workflows should use linear history
We’ve been working on agent workflows that write to Dolt (SQL database with Git semantics), and rebase has become a core part of the pattern.
The setup:
- Each agent gets its own branch
- Agent makes changes, commits
- Before merge to main, agent rebases onto latest main
- Conflicts = signal to the agent that something changed and it needs to re-evaluate
Why rebase over merge:
- Linear history is way easier for humans to review (and we’re swimming in agent-generated changes that need review)
- Conflicts surface early and force agents to reason about new information
- Agents don’t have the emotional baggage humans do with rebase—they just execute
The kicker: agents are surprisingly good at rebase because there’s so much Git documentation online. They’ve “read” all of it.
One-liner in SQL: CALL DOLT_REBASE('main')
Full writeup: https://www.dolthub.com/blog/2026-01-28-everybody-rebase/
Anyone else building agent systems with version control? What’s your branching model?
submitted by /u/DoltHub_Official
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