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Shiro Automation: A portable, zero-infrastructure workflow orchestration runtime for CI/CD. AI-native, DAG-based execution, GitLab CI & GitHub Actions integration. Single binary, no servers.
👋 Hi everyone! I'm Rajit, the creator of Shiro.
I built Shiro after noticing a recurring pattern across engineering teams.
We automate builds and tests, but many workflows still involve manual steps:
Reviewing pull requests
Generating release notes
Requesting deployment approvals
Sending Slack notifications
Running deployment checklists
Existing workflow platforms are powerful, but they often require another service to deploy and maintain.
I wondered:
What if workflows simply ran inside the infrastructure we already have?
That's the idea behind Shiro.
Instead of deploying another orchestration platform, Shiro runs directly inside your existing GitHub Actions, GitLab CI, Jenkins pipeline, Kubernetes Job, or Docker container. It starts when your pipeline starts, executes the workflow, and exits—no always-on services or orchestration cluster required.
Today Shiro includes features like:
🤖 AI-powered PR reviews
💬 Slack notifications and approvals
📦 GitHub, GitLab, and Jenkins integrations
☸️ Kubernetes automation
🧩 Modular workflow components
🧠 Bring-your-own AI model (OpenAI, Gemini, OpenRouter, and more)
Everything is open source under the Apache 2.0 license.
I'm still actively building the project, so I'd really value your feedback:
Does the "run inside existing CI/CD" approach solve a problem for your team?
What workflow would you automate first?
Which integrations would you want to see next?
Thanks for checking out Shiro! Looking forward to hearing your thoughts and answering any questions. 🚀
Dropped the single binary into a test pipeline and it picked up my existing GitHub Actions yaml with almost no fuss. The DAG view finally makes job dependencies readable instead of a wall of YAML.
how does it handle state between DAG tasks across pipeline runs, especially if my runners get rotated mid-job?
The single binary approach is genuinely handy, I had a DAG pipeline running in under five minutes without touching any infra. The GitHub Actions bridge feels especially smooth for migrating existing jobs.
Tried running a multi-stage pipeline locally and the single binary just worked, no daemon or setup needed. The DAG approach made it way easier to reason about job dependencies than my usual GitHub Actions setup.
About Shiro Automation on Product Hunt
“Shiro – AI Automation That Runs Inside Your CI/CD”
Shiro Automation was submitted on Product Hunt and earned 5 upvotes and 6 comments, placing #74 on the daily leaderboard. Shiro Automation: A portable, zero-infrastructure workflow orchestration runtime for CI/CD. AI-native, DAG-based execution, GitLab CI & GitHub Actions integration. Single binary, no servers.
Shiro Automation was featured in Open Source (68.6k followers), Developer Tools (515.5k followers), GitHub (41.3k followers) and Tech (627.5k followers) on Product Hunt. Together, these topics include over 278.2k products, making this a competitive space to launch in.
Who hunted Shiro Automation?
Shiro Automation was hunted by Rajit. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Shiro Automation stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Rajit