# How to compare parallel and sequential refinement on the same task with harness2

Repo: [google-research/harness2](https://github.com/google-research/harness2) | Difficulty: Intermediate | Time: 2 hours | Basis: From the README

Run the same benchmark task in both recursion modes to pick the cheaper or stronger refinement strategy.

**Who it is for:** ML engineer deciding how to spend an agent-refinement compute budget on a recurring task type

**The problem:** It is unclear whether exploring many candidates at once or refining step by step gives better results per dollar for your task.

**The outcome:** Two reports for the same task, one per mode, that you can compare side by side to choose a strategy.

## Steps

1. Run parallel mode: harness2 --bench lab --k 2 --mode parallel --only-domains antitrust-competition --max-tasks 1
2. Run sequential mode: harness2 --bench lab --k 2 --mode sequential --only-domains antitrust-competition --max-tasks 1
3. Judge each run: harness2-judge --bench lab --k 2 --mode parallel and harness2-judge --bench lab --k 2 --mode sequential
4. Report each run: harness2-report --bench lab --k 2 --mode parallel and harness2-report --bench lab --k 2 --mode sequential
5. Compare the two reports and the adopted harnesses.

## Prompt to paste into your agent

```text
Using google-research/harness2, run LAB on one task with --k 2 in both parallel and sequential modes, judge and report each, and tabulate the scores side by side. Verify both runs used the same task selection and seed before comparing.
```

## Caveat

A single task is a very noisy comparison, and the README ties each judge and report call to its own mode, k and seed, so run the full command set once per mode.

Dual-use notice: only use this on software, sites and systems you own or are authorized to test.

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URL: https://dedupedai.com/use-cases/google-research-harness2/compare-parallel-vs-sequential-recursion/
