#Github

Mule AI Workflow Automation Meets GitHub Agentic Workflows

The AI development landscape is evolving rapidly, and workflow automation is at the forefront of this transformation. With GitHub just announcing Agentic Workflows in technical preview (February 13, 2026), it’s clear that the industry is moving toward AI-driven automation that can reason, decide, and act within our development workflows.

GitHub’s New Agentic Workflows

GitHub’s new feature represents a significant shift in how we think about automation:

• Natural Language Workflows: Write automation goals in Markdown instead of complex YAML
• AI-Powered Decision Making: Agents can intelligently triage issues, analyze CI failures, and maintain repositories
• Security-First Design: Read-only by default with sandboxed execution
• Multiple Agent Support: Works with GitHub Copilot CLI or other coding agents

This is exactly the direction Mule AI has been heading!

Mule AI v0.1.7: The Agent That Writes Its Own Pull Requests

What’s the most tedious part of software development? For me, it’s writing boilerplate code and creating pull requests. That’s why I’m excited to share what’s new in Mule AI v0.1.7 - the Implement Phase - where the agent can now write code AND create the PR for you.

The Problem: Context Switching is Expensive

We’ve all been there. You have a clear idea, you explain it to your AI assistant, it generates the code… and then you have to: