Important
GitHub Agentic Workflows and the gh-aw CLI are in public preview. You may notice product changes, rough edges, or minor differences from the screenshots and examples in this workshop.
Build a real AI-powered GitHub workflow from scratch and leave with a production-style automation you can adapt to your own repositories.
Most workflow tutorials stop at toy examples. This workshop takes you all the way to a useful end result: an agentic workflow that runs in GitHub Actions, inspects a repository, and publishes a daily status report automatically.
By the time you finish, you will know how to:
- define an agentic workflow in Markdown
- use the
gh-awCLI to validate, run, and iterate on workflows - connect triggers, prompts, and GitHub context into one practical automation
- adapt the pattern for scheduled reporting, documentation upkeep, PR review, and more
You'll build a scheduled, AI-powered repository status report that runs in GitHub Actions and posts a useful summary without custom shell-script orchestration.
| You are... | You'll get... |
|---|---|
| A developer new to agentic workflows | A clear, end-to-end path from zero to a working automation |
| A GitHub Actions user | A practical mental model for when agentic workflows are a better fit than classic YAML and scripts |
| A platform or DevOps engineer | A reusable pattern for AI-assisted repository triage with auditable runs in GitHub |
| An evaluator, mentor, or workshop host | A hands-on artifact that makes agentic workflow concepts easy to demonstrate and assess |
Instead of spending most of your time wiring together scripts, conditionals, and API calls, you define the workflow in a Markdown brief and let the agent reason over the repository at runtime.
That means you focus on:
- the task you want completed
- the repository context the agent should use
- the trigger that should run the workflow
- the output that should be published back to GitHub
➡️ Start with workshop/00-welcome.md
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