---
title: "Rank fixes by the minutes they save"
description: "Price every CI fix in minutes saved per day before writing any YAML."
url: https://starsling.dev/ci-playbooks/techniques/rank-by-minutes
canonicalUrl: https://starsling.dev/ci-playbooks/techniques/rank-by-minutes
---

# Rank fixes by the minutes they save

Price every CI fix in minutes saved per day before writing any YAML.

## 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#rank-by-minutes)**: Use it when You have CI run history and want to choose a first optimization. Check before adopting: Estimates depend on the history window and run frequency. Rank total CI minutes separately from time waiting for a merge.

## Apply this technique

````text
Evaluate and apply this CI technique to my repository: Rank fixes by the minutes they save.

Price every CI fix in minutes saved per day before writing any YAML.

Read the technique and its source-backed company examples: https://starsling.dev/ci-playbooks/techniques/rank-by-minutes.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: Rank fixes by the minutes they save

The team asked its agent to read the repository's CI run history, list ideas to relieve CI load, and rank them by estimated CI minutes saved per day. Following up on that ranked list produced about 30 CI optimization PRs.

Evidence: Company-reported result or observation

About 30 CI optimization PRs landed after ranking ideas by CI minutes saved. ([Source](https://developers.openai.com/blog/maintaining-software-with-the-gpt-6-family#other-ideas-to-try))

Use it when: You have CI run history and want to choose a first optimization.

Before applying it: Estimates depend on the history window and run frequency. Rank total CI minutes separately from time waiting for a merge.

[Read more in the OpenAI playbook](https://starsling.dev/ci-playbooks/openai#rank-by-minutes)

[Primary source](https://developers.openai.com/blog/maintaining-software-with-the-gpt-6-family#other-ideas-to-try)

## 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.

### [Make GitHub Actions faster](https://starsling.dev/fast-github-actions)

Make GitHub Actions faster two ways: faster Ubuntu runners, and less workflow waste from caching, sharding and path filters. How to tell which one wins.