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Title: Thomas Thornton - Azure Blog - Empowering Developers with Azure, Azure DevOps, GitHub & Terraform Insights

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When I first built my Diagram Agent Skill with Draw.io MCP, the focus was Azure. That was deliberate. I wanted to solve one problem properly before broadening it. If you have ever tried to create a cloud architecture diagram that is both accurate and easy to read, the trade-off is familiar enough: manual drawing gives you precision but takes too long, while auto-generation is...


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Terraform provider upgrades often turn into a manual research exercise. You check the registry, read changelogs, scan the codebase for deprecated resources, update the provider version, add blocks, run a plan, and hope nothing breaks. Using GitHub Agentic Workflows, a Terraform MCP server, and reusable agents and skills, much of that preparation can be automated safely.

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If you’ve ever tried to create a cloud architecture diagram that’s both accurate and easy to read, you’ll know the challenge: Recently, I wrote about my experience using Draw.io MCP for diagram generation – why it’s worth adopting and how it changes the way teams produce diagrams. If you haven’t read that post yet, start there for broader context: Draw.io MCP for Diagram Gene...


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I started using Draw.io MCP to generate diagrams from structured input and keep them tied to code and infrastructure. Instead of dragging boxes around by hand, I can spit out a draft in minutes, tweak it intentionally, and commit it to Git. That turns diagrams into living assets instead of throwaway slides. Instead of manually arranging every shape, I can now generate a solid...


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In my a previous blog post, I shared my early experience getting started with GitHub Agentic Workflows. I’ve known about GitHub Agentic Workflows for a few months, after spending more time using them, what stands out isn’t just the AI capability – it’s the operating model: You keep the reliability and visibility of Actions, while gaining adaptive problem-solving for tasks tha...


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