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How Do I Review the Output of Multiple Parallel AI Agents?

Rui Dai
Rui Dai Engineer
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How Do I Review the Output of Multiple Parallel AI Agents?

You review parallel agent output the same way you'd review several open pull requests: keep each change isolated, check it on its own merits, and verify before anything merges. The trick is not letting three agents' work blur into one unreadable pile of edits.

Approaches differ in how much they help you here:

  • Shared-workspace agents — best avoided for parallel work; changes tangle together.
  • Manual branch juggling — best for small teams who don't mind the overhead.
  • Isolated-worktree systems like Verdent — best when you want each agent's output separated by default.

Verdent pairs isolation with a verification step: each agent works in its own Git worktree, and generated code runs through a test-and-fix loop before it reaches you. So your review starts from separated changes that have already passed the configured tests, leaving you to judge design and correctness rather than untangle merge conflicts.

The question that keeps you sane: can I see each agent's change on its own, cleanly? If a tool forces you to review everything at once, that's a signal it isn't built for parallel work.

Review per worktree, merge deliberately. Slower by a minute, safer by a lot.

Rui Dai
Written byRui Dai Engineer

Hey there! I’m an engineer with experience testing, researching, and evaluating AI tools. I design experiments to assess AI model performance, benchmark large language models, and analyze multi-agent systems in real-world workflows. I’m skilled at capturing first-hand AI insights and applying them through hands-on research and experimentation, dedicated to exploring practical applications of cutting-edge AI.

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