About

What are Agentic Workflows?

Agentic workflows are AI-powered automation that can understand context, make decisions, and take meaningful actions—all from natural language instructions you write in markdown.

Unlike traditional automation with fixed if-then rules, agentic workflows use AI agents (like GitHub Copilot) to:

• Understand context: Read your repository, issues, and pull requests to grasp the current situation
• Make decisions: Choose appropriate actions based on the context, not just predefined conditions
• Adapt behavior: Respond flexibly to different scenarios without requiring explicit programming for each case

Natural Language to GitHub Actions

Imagine describing your automation needs in plain language instead of wrestling with complex YAML syntax and API calls. GitHub Agentic Workflows makes this possible by transforming natural language markdown files into GitHub Actions that are executed by AI agents (the AI that executes your workflow instructions).

Instead of writing intricate scripts to handle issue triage, code reviews, or release management, you simply describe what you want to happen. The AI agent understands your repository context, interprets the situation, and takes appropriate actions—all from a few lines of markdown.

Here’s a simple example:

---
on:
  issues:
    types: [opened]
permissions: read-all
safe-outputs:
  add-comment:
---
# Issue Clarifier

Analyze the current issue and ask for additional details if the issue is unclear.

The gh aw compile command transforms this markdown into a secure GitHub Actions Workflow (.lock.yml file) that runs an AI agent in a containerized environment whenever a new issue is opened.

Compilation (the process of converting markdown to GitHub Actions YAML) validates your configuration, applies security hardening, and generates the final workflow file that GitHub Actions can execute. Think of it like compiling code—you write human-friendly markdown, the compiler produces machine-ready YAML.

The AI agent reads your repository context, understands the issue content, and takes appropriate actions - all defined in natural language rather than complex code.

Workflows use read-only permissions by default, with write operations only allowed through sanitized safe-outputs (a security feature that enables creating issues, comments, and PRs without giving the AI direct write access). Access can be gated to team members only, ensuring AI agents operate within controlled boundaries.

More sample workflows can be found in the Agentics collection.