Give an agent the last mile: watch CI, rebase and retry flaky checks

Let an agent shepherd each change through CI to the merge.

Prompt

Evaluate and apply this CI technique to my repository: Give an agent the last mile: watch CI, rebase and retry flaky checks.

Let an agent shepherd each change through CI to the merge.

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

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How OpenAI used this technique

Read what OpenAI changed and follow the original sources.

Give an agent the last mile: watch CI, rebase and retry flaky checks

Translated to GitHub Actions

What OpenAI built: OpenAI's Symphony gives each ticket's agent the gh CLI and skills to watch CI, rebase and retry flaky checks.
Your GitHub Actions version: An agent that watches CI on its pull request, rebases when needed, resolves conflicts and retries flaky checks.

OpenAI's Symphony gives each ticket's agent the gh CLI and skills to read CI logs. In a large monorepo, where the last mile of landing a pull request is slow and fragile, the system watches CI, rebases when needed, resolves conflicts and retries flaky checks. By the time a ticket reaches Merging, the team has high confidence the change will land without human babysitting.

Use it when: Landing a pull request takes repeated manual rebases, conflict fixes and reruns of the same flaky checks.
Before applying it: Bound the retries and record each flake so a retried check still leaves a trail to fix, and leave required checks and approvals in force.
GitHub Actions adaptation: Compare the source system with your own workflow before applying this translation.

How OpenAI used this technique

Give an agent the last mile: watch CI, rebase and retry flaky checks

Company Playbooks