[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:

  1. Linear history is way easier for humans to review (and we’re swimming in agent-generated changes that need review)
  2. Conflicts surface early and force agents to reason about new information
  3. 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
[link] [comments]

Liked Liked