DevNation DayDevNation Day
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INTERMEDIATE

How we made our team do stand-up on Minecraft (and you can too!)

The project transforms daily software stand‑ups by hosting them inside Minecraft. A custom server integrates with Jira and GitHub through locally run LLMs on Kubernetes, enabling in‑game updates via natural language. Using Java and LangChain4J, it demonstrates gamified, agentic collaboration tools that unify workflows and reduce context switching.

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Sawyer Bowerman
Sawyer BowermanRed Hat

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Thursday, May 7, 14:10-14:25
Room E
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Every day, millions of engineers join a well-known call to share progress, plans, and blockers. It's perhaps the most fundamental part of how software is built, but while the stand-up is collaborative, most of our tools aren't! They're fragmented across trackers, dashboards, and chat apps, turning what should be simple into context switching and "let me put some time on your calendar."

Our team's idea? Bring some fun to stand-up and Scrum by running them in Minecraft. Yes, your (or your child's) favorite sandbox video game, being used to review and ship code! We built a custom Minecraft Paper plugin that integrates GitHub PR reviews, Jira ticket management, project kanban boards, and AI-powered code assistance directly into the game. Using slash commands like /git pr-review or natural language with /ai-chat, players can create Jira tickets, review pull requests, search code, and get AI explanations, all without leaving their blocky world. You'll learn how you can maximize your own agentic capabilities using Java and custom tool definitions, and how with a bit of gamification and open source technology running on your own infrastructure, our team can't wait to join stand-up!

minecraft
gamification
standup
kubernetes
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Sawyer Bowerman

Sawyer Bowerman

Red Hat

United States of America

Sawyer Bowerman is an AI Engineer and Developer Advocate on Red Hat’s AI team based in Boston, MA. He specializes in high-performance model serving and inference, focusing on scaling open-source ecosystems like vLLM and llm-d to make large language models more efficient and accessible for developers. He is dedicated to bridging the gap between raw model performance and real-world developer productivity through open-source innovation.
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