COPD

On Thursday, April 16, 2026, we will meet at the 700N Conference Room at 700 N Hurstbourne Pkwy. Doors will open at 6:00 p.m., and the presentations will begin sharply at 6:30 p.m. Along with an excellent presentation, TEKsystems will provide food. Please RSVP so we know how much food to order. Afterward, we will go to Brick House Tavern for drinks and food to continue the conversation. The session will also be broadcast at https://twitch.tv/TaleLearnCode. ### What If Your AI Could Be a Team? GitHub Copilot is powerful, but what if you could scale from a solo AI assistant to an entire team of specialized agents working in parallel? This session introduces Squad: an open-source framework for multi-agent orchestration that lets you define teams of AI agents with specific roles, responsibilities, and expertise. We'll progress from Copilot basics to the Copilot CLI, explore how Agents add autonomy, and see how Instructions and Skills let you customize agent behavior. Then, the climax: a live demo where a Squad team of 3 agents (Lead, Developer, Tester) stands up and builds a working application in real-time, showcasing true multi-agent collaboration. Whether you're new to AI or exploring how to scale your use of Copilot, this session will show you what's possible when agents work as a team.

Let’s walk the gardens and enjoy what has spring has on display.

This trail is a meandering path through the woods. There will be some overlooks and a couple stops at the creek as well as time along a waterway. It will not be a fast paced hike. There is some elevation change and uneven terrain. I will be using poles just to be safe! Will aim to get in about three miles. Optional lunch after if there is an interest.

Meet at Wolfe Park parking lot by tennis courts. We willl walk along Alum Creek trail, through Jeffrey Mansion Park then along Bexley neighborhood and back. Optional lunch at Trolley District.

The Fellowship of the Star Schema: Transforming OLTP Data for Power BI One does not simply build reports on OLTP data. Join us on an epic journey from the depths of raw, normalized tables to the shining halls of a well-modeled star schema fit for Power BI greatness. We will demystify the differences between OLTP and OLAP, walk through star schema vs snowflake (and why Power BI has a clear favorite), and show you the compression differences between normalized and columnar storage that will make you never look at an OLTP model the same way again. We will cover the different types of dimensions, when to use them, and how to handle Slowly Changing Dimensions without losing your mind. You will leave knowing exactly how to identify a bad model, how to convert OLTP data into a clean star schema, and how to forge relationships that rule them all. Whether you are a data wizard, a curious hobbit, or somewhere in between, your models will never be the same.