--- title: "Automatically Optimize GitHub Actions Workflows | StarSling" description: "StarSling is AI-native CI for GitHub Actions: it watches your logs, timing, caches, and telemetry, then opens agent PRs that improve the pipeline over time." url: https://starsling.dev/ai-native-ci canonicalUrl: https://starsling.dev/ai-native-ci --- # Agents that optimize your GitHub Actions workflows Most CI runs your jobs and stops there. AI-native CI keeps watching, and keeps improving the pipeline. StarSling is AI-native CI for GitHub Actions: fast, drop-in runners plus agents that open optimization PRs you review and merge. AI-native CI is continuous integration that does more than run jobs. It observes workflow logs, job timing, cache behavior, failures, and machine telemetry, then uses agents to propose or apply improvements to the pipeline over time. ## What is AI-native CI? Traditional CI is static: it executes the workflow you wrote, the same way, every run. The pipeline only improves when an engineer finds time to profile it and hand-tune caching, parallelization, or test layout, which rarely gets prioritized. AI-native CI closes that gap by treating the pipeline itself as something to be continuously analyzed and optimized. ## How StarSling works AI-native CI combines [faster GitHub Actions](/fast-github-actions) runners with continuous workflow optimization. The runner makes supported jobs faster today; the agent layer keeps finding workflow improvements over time. StarSling has two layers. The first is the runner: StarSling Runners are a drop-in replacement for `ubuntu-latest` and `ubuntu-24.04`, on faster hardware (5th Gen AMD EPYC), so existing workflows get quicker the moment you change one line. See the [runner instance types and labels](https://docs.starsling.dev/runners/instance-types). The second is the agents. After you install the StarSling GitHub App, agents continuously analyze your workflows, jobs, run logs, and machine telemetry, then open pull requests that optimize your pipeline. You review and merge, so nothing changes your CI without a PR. See [how the optimization agents work](https://docs.starsling.dev/ai-powered-features/optimizations) in the docs. For new accounts, AI-powered optimization PRs are only available to customers on paid plans and are not enabled by default. ## Generally available launch StarSling Runners became generally available on June 29, 2026, after running over one million CI jobs for teams including Better Auth, Mastra, and Partcl. The GA launch post is the primary current reference for StarSling Runners availability, pricing, migration, and customer proof: [StarSling Runners are now generally available](https://starsling.dev/blog/starsling-runners-are-now-generally-available). ## Why fast runners alone are not enough Faster hardware is real and immediate, but it only addresses one cause of slow CI. The rest is structural: caches that never hit, dependency installs that re-download everything, steps that run serially when they could be parallel, test suites that aren't sharded, and fixed sleeps standing in for real readiness checks. Each of these has a known fix in our [CI optimization best practices](/best-practices/github-actions), which you can apply manually or let StarSling agents propose as PRs. No runner fixes those by itself, because they live in your workflow files. That is exactly the work AI-native CI takes on: finding the structural waste and proposing the fix as a reviewable PR. You can [benchmark StarSling against GitHub-hosted runners](https://docs.starsling.dev/performance/benchmarks) on your own workflows. ## What StarSling agents optimize StarSling agents focus on the highest-leverage, lowest-risk improvements to your GitHub Actions pipeline (see the [optimizations docs](https://docs.starsling.dev/ai-powered-features/optimizations)): - Caching: detect missing or misconfigured caches (e.g. broken Turborepo or actions/cache keys). On Better Auth, agents found a Turborepo cache configuration that wasn't hitting between runs and fixed it ([PR #7950](https://github.com/better-auth/better-auth/pull/7950)), which is part of the CI workflow going from 1m 40s to 1m 02s. A separate agent PR cached Playwright browser installs that were re-downloading on every run ([PR #8073](https://github.com/better-auth/better-auth/pull/8073)), one of the three PRs behind per-job E2E going from 2m 22s to 1m 04s ([Better Auth case study](/customers/better-auth)). - Dependency installs: faster install strategies like frozen lockfiles and parallel installs. - Parallelization: split serial steps and jobs that can safely run concurrently. - Test sharding: spread long test suites across parallel shards to cut wall-clock time. On Mastra, agents sharded the E2E kitchen-sink suite across parallel jobs ([PR #15888](https://github.com/mastra-ai/mastra/pull/15888), one of the four agent PRs behind that workflow's speedup). E2E went from 14m 16s to 10m 50s, a 1.32x speedup ([Mastra case study](/customers/mastra)). - Workflow structure: job splitting, matrix strategies, dependency ordering, and removing redundant work. ## How to migrate from ubuntu-latest Migration is a one-line change. Install the [StarSling GitHub App](https://github.com/apps/starslingdev), then swap your runner label: Your workflows, actions, and secrets stay exactly as they are. StarSling runs your existing GitHub Actions, just on a different runner. See the [migration guide](https://docs.starsling.dev/configuration/migration-guide) and [quickstart](https://docs.starsling.dev/getting-started/quickstart) for the full walkthrough. ```yaml # .github/workflows/ci.yml - runs-on: ubuntu-latest + runs-on: starsling-ubuntu-24.04 ``` ## StarSling vs traditional GitHub Actions runners A traditional runner (GitHub-hosted or a third-party fast runner) gives you a machine to execute jobs. It does not look at your pipeline or suggest changes. StarSling is a drop-in runner too, but the agents make it self-driving: the pipeline gets faster the longer you use it, not just the day you switch hardware. For a side-by-side breakdown, see the comparison with GitHub Actions. ## FAQ ### Is AI-native CI the same as self-driving CI? Yes. StarSling uses the terms interchangeably. Both mean CI that observes your pipeline and improves it over time through agents, rather than just executing static workflows. ### Does AI-native CI change my workflows automatically? No. StarSling's agents open pull requests. You review the diff and merge, so nothing reaches your default branch without your approval. ### Do I have to rewrite my GitHub Actions to use StarSling? No. StarSling is not a new CI syntax. You change `runs-on: ubuntu-latest` to `runs-on: starsling-ubuntu-24.04` and keep your existing workflows. ## Learn more - [StarSling overview](https://starsling.dev/) - [Fast GitHub Actions](https://starsling.dev/fast-github-actions) - [GitHub Actions runner alternatives](https://starsling.dev/github-actions-runners-alternatives) - [Quickstart (migrate in 5 min)](https://docs.starsling.dev/getting-started/quickstart) - [Migration guide](https://docs.starsling.dev/configuration/migration-guide) - [What StarSling's agents optimize](https://docs.starsling.dev/ai-powered-features/optimizations) - [Benchmark on your own workflows](https://docs.starsling.dev/performance/benchmarks) - [Runner label reference](https://docs.starsling.dev/configuration/label-reference) - [StarSling vs GitHub Actions](https://starsling.dev/compare/github-actions) - [StarSling Runners are now generally available](https://starsling.dev/blog/starsling-runners-are-now-generally-available) - [Announcing StarSling Runners (original launch post)](https://starsling.dev/blog/announcing-starsling-runners-self-driving-ci-that-optimizes-itself) - [All StarSling docs](https://docs.starsling.dev) - [StarSling facts for AI assistants](https://starsling.dev/ai-assistant-facts) - [LLM facts (llms.txt)](https://starsling.dev/llms.txt)