---
title: "Keep blocking merge gates minimal and follow flakes with a rerun"
description: "Gate merges on the checks that guard correctness and handle a flake with a follow-up run."
url: https://starsling.dev/ci-playbooks/techniques/minimal-merge-gates
canonicalUrl: https://starsling.dev/ci-playbooks/techniques/minimal-merge-gates
---

# Keep blocking merge gates minimal and follow flakes with a rerun

Gate merges on the checks that guard correctness and handle a flake with a follow-up run.

## How to choose an approach

This technique currently has one documented company example. Validate its prerequisites, tradeoffs and original CI environment against your repository before adapting it.

- **[OpenAI](https://starsling.dev/ci-playbooks/openai#minimal-merge-gates)**: Use it when Required checks hold merges on results that a follow-up run clears. Check before adopting: The team describes this as a trade that fits a high-throughput repository where corrections are cheap. Keep required the checks that guard changes a follow-up commit cannot undo.

## Apply this technique

````text
Evaluate and apply this CI technique to my repository: Keep blocking merge gates minimal and follow flakes with a rerun.

Gate merges on the checks that guard correctness and handle a flake with a follow-up run.

Read the technique and its source-backed company examples: https://starsling.dev/ci-playbooks/techniques/minimal-merge-gates.md

Inspect this repository’s CI workflows, build and test commands, dependencies, and recent run timings. Identify where this technique applies and explain the expected benefit using this repository’s evidence.
Measure a baseline from recent comparable runs: elapsed time, queue time, runner minutes and failures where available. If data is unavailable, say what cannot be measured.
Compare relevant company approaches, checking prerequisites, platform differences and tradeoffs. Rank applicable options by evidence, fit and measurable opportunity; do not present company results as predictions for this repo.
Recommend the smallest safe change, show what checks and fallback paths remain, and ASK ME WHICH CHANGE TO APPROVE BEFORE EDITING ANY FILES.
Only after approval, work on a new feature branch, make one reversible change, and open a reviewable pull request. Never merge or push to a default or protected branch.
Keep required checks, test coverage, deployment and release behavior intact. Validate the change and compare equivalent runs where possible; report limitations and what should be monitored after merge.
````

## How OpenAI used this technique

Read what OpenAI changed and follow the original sources.

### OpenAI: Keep blocking merge gates minimal and follow flakes with a rerun

OpenAI's agent-first team runs its repository with minimal blocking merge gates and short-lived pull requests. A test flake gets a follow-up run, so progress continues while the flake is handled. The team reasons that when agent throughput far exceeds human attention, corrections are cheap and waiting is expensive.

Evidence: Company-reported result or observation

In a system where agent throughput far exceeds human attention, corrections are cheap, and waiting is expensive. ([Source](https://openai.com/index/harness-engineering/))

Use it when: Required checks hold merges on results that a follow-up run clears.

Before applying it: The team describes this as a trade that fits a high-throughput repository where corrections are cheap. Keep required the checks that guard changes a follow-up commit cannot undo.

[Read more in the OpenAI playbook](https://starsling.dev/ci-playbooks/openai#minimal-merge-gates)

[Primary source](https://openai.com/index/harness-engineering/)

## CI optimization is continuous work.

Apply this technique yourself, or use StarSling Runners for faster GitHub Actions and optional agent-driven optimization PRs, which teams on eligible paid plans can turn on.

[Get self-improving CI](https://starsling.dev/products/runners)

## Company Playbooks

### [Anthropic](https://starsling.dev/ci-playbooks/anthropic)

Run only affected tests

### [DoorDash](https://starsling.dev/ci-playbooks/doordash)

Run build and test in parallel, sharded across CI agents

### [Linear](https://starsling.dev/ci-playbooks/linear)

Benchmark the same job on faster hardware

### [Mastra](https://starsling.dev/ci-playbooks/mastra)

StarSling runners for the slowest test workflow

### [OpenAI](https://starsling.dev/ci-playbooks/openai)

Rank CI fixes by the minutes they save

### [Ramp](https://starsling.dev/ci-playbooks/ramp)

Move a CPU-bound test suite to a faster CPU

### [Shopify](https://starsling.dev/ci-playbooks/shopify)

Let an agent iterate against one CI metric

### [Spotify](https://starsling.dev/ci-playbooks/spotify)

Build arm64 on native arm64 runners

### [Stripe](https://starsling.dev/ci-playbooks/stripe)

Run only the tests a change can reach

### [Uber](https://starsling.dev/ci-playbooks/uber)

Build the merge-queue speculations most likely to be needed

## Related guides

Implementation guides for this technique.

### [Keep non-required checks off the GitHub Actions critical path](https://starsling.dev/best-practices/github-actions/keep-advisory-checks-non-blocking)

A slow, non-required check on the PR critical path is pure wait. How to narrow or async advisory checks in GitHub Actions, without disabling real tests.