Julia Kordick
Sr. Software Global Black Belt @ Microsoft
Köln, Germany
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Julia is a Software Global Black Belt at Microsoft, helping large-scale organizations accelerate dev workflows through pragmatic, end-to-end platform engineering. With a background as a Software Engineer, Dev Lead, and Cloud Solution Architect, she speaks fluent developer and management—and knows how to bridge the gap without losing either side in translation.
She’s a big-picture thinker who also loves to understand the details. Web and frontend will always have a place in her ❤️.
Outside work, Julia is a gamer, a proud fahrradmaus, and a former quarterback for a women’s American football team (yes, really).
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A (short) guide to Platform Engineering and Agentic DevOps
Platform Engineering helps organizations manage the growing complexity of cloud-native software development. As DevOps practices mature, a new evolution is emerging: Agentic DevOps.
This session explores how Platform Engineering provides the foundation for introducing AI-assisted and agent-driven workflows in a controlled, scalable way. Using GitHub as a central DevOps and orchestration platform, we will show how automation, governance, security, and developer experience come together to enable agentic capabilities without sacrificing engineering rigor.
Teaching GitHub Copilot COBOL: A Practical Guide to Agentic AI Legacy Modernization
Everyone talks about modernizing legacy systems. Few people actually open a COBOL codebase and do it. In this session, I will. Using real mainframe applications, I'll walk through how GitHub Copilot's agentic capabilities can help you understand, plan, and extend COBOL code you've never seen before. We'll start where every modernization project actually starts: figuring out what the code does. Using structured prompt workflows, we'll reverse engineer modules, discover data structures, trace transaction flows, and build a knowledge base that turns tribal knowledge into something an AI agent (and your team) can actually work with. Then we'll go further: planning and implementing a new feature, end to end, with Copilot doing the heavy lifting while we stay in the driver's seat. This isn't a "replace your mainframe overnight" talk. It's a grounded, hands-on look at what's possible right now when you combine spec-driven development with agentic AI. You'll leave with a repeatable approach to legacy discovery and modernization, and a realistic sense of where AI helps, where it struggles, and where you still need to know your stuff.
Spec First Development: Building and Modernizing Apps with Agentic AI
Agentic AI is moving fast from hype to hands on reality. But most teams still struggle with the same questions:
- How do I prompt agents effectively?
- How do I control context and tools?
- And how do I use agentic AI in real brownfield and greenfield projects without creating chaos?
In this full day masterclass, we start by grounding participants in what they actually need to know about agentic AI. We cover practical prompting strategies, context engineering, and MCP, with a clear focus on what works in real projects. No buzzwords. No magic thinking.
Bring your own project and your own agentic AI setup. Participants can work on their own ideas or systems, or follow along with provided examples.
I will use examples with GitHub and Azure as this is my personally preferred tech stack, but the learnings and patterns apply everywhere.
From there, we go fully hands on. Using spec kit, participants work through a choose your own adventure style journey. You decide whether you start from a greenfield idea or a brownfield application. Step by step, we turn specifications into working code and cloud ready artifacts using agentic workflows.
This is not a slide heavy workshop. You will write specs, guide agents, debug outcomes, and learn where agentic AI shines and where it clearly does not.
You will leave with concrete patterns and mental models you can apply immediately in your own projects.
No prior experience with agentic AI is required.
Basic software development experience is highly recommended.
AI Won't Fix Your Engineering Culture
AI doesn't fix broken systems. It amplifies them. And right now, most organizations are learning that the hard way. This talk reframes the conversation: engineering culture is the real constraint, not tooling. DevEx is the signal. Platform Engineering is the lever. You need both before humans and agents can operate effectively. Agentic workflows don't wait for you to get your house in order. They expose weak foundations at speed and scale. Strong DevEx and platform capabilities become a multiplier. Everything else just gets louder.
Azure Community Day 2026 Sessionize Event Upcoming
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AgentCon Cologne Sessionize Event
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