--- title: "Remove a redundant runner after verified cache delivery" description: "Once a trusted payload is already uploaded, let consumers start without waiting on another runner." url: https://starsling.dev/ci-playbooks/techniques/skip-warm-bundle-runner canonicalUrl: https://starsling.dev/ci-playbooks/techniques/skip-warm-bundle-runner --- # Remove a redundant runner after verified cache delivery Once a trusted payload is already uploaded, let consumers start without waiting on another runner. ## 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#skip-warm-bundle-runner)**: Use it when A warm preparation job produces the artifact, and a separate runner then only rechecks it. Check before adopting: An exact cache hit is not enough on its own: preparation and upload must succeed. Cold builds, platform proofs and release validation stay required. ## Apply this technique ````text Evaluate and apply this CI technique to my repository: Remove a redundant runner after verified cache delivery. Once a trusted payload is already uploaded, let consumers start without waiting on another runner. Read the technique and its source-backed company examples: https://starsling.dev/ci-playbooks/techniques/skip-warm-bundle-runner.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: Remove a redundant runner after verified cache delivery Codex Security's preparation job already restored and uploaded verified native payloads. The bundle runner now skips after a successful preparation with an exact cache hit; cold assembly and protected publication stay together. Evidence: Source PR/commit evidence 29 warm attempts spent a median seven seconds waiting for and running the redundant job ([Source](https://github.com/openai/codex-security/pull/2042)) Use it when: A warm preparation job produces the artifact, and a separate runner then only rechecks it. Before applying it: An exact cache hit is not enough on its own: preparation and upload must succeed. Cold builds, platform proofs and release validation stay required. [Read more in the OpenAI playbook](https://starsling.dev/ci-playbooks/openai#skip-warm-bundle-runner) [Primary source](https://github.com/openai/codex-security/pull/2042) ## 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. ### [Remove needs: dependencies that do not exist](https://starsling.dev/github-actions/optimizations/remove-unnecessary-job-dependencies) A needs: edge with no artifact, output, or side effect it depends on only serializes jobs. How to find and remove unnecessary GitHub Actions job dependencies.