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AI Power Hour Morning Session - Bigger Stronger Faster Date: March 31, 2026 Host: Kyle Bartlett Participants: Kyle Bartlett, Heather Bartz, Michael Falvo [00:00:00 - 00:06:30] Chapter 1: Introductions and Session Format Discussion Kyle Bartlett welcomes everyone to the AI Power Hour morning session. The session is titled Bigger Stronger Faster. Kyle is joining from Houston, Heather Bartz is joinin

to accomplish. She has seen her manager Ray's Staples sales dashboard and wants to replicate something similar for other retailers. The current process of manually formatting weekly sales reports into presentable formats takes too much time for her team. She describes the typical workflow: every week they receive sales reports from retailers like Staples, and someone has to manually copy the data,

dashboard as an example of what they will build. He shows the dashboard on screen and walks through its features including charts, category breakouts, and partner comparisons. He then explains the two main methods for keeping dashboards updated with fresh data each week. Method 1 is Google Drive folder sync. You can connect a Google Drive folder directly to your dashboard. When you drop a new data

step by step, showing everyone how to start a brand new dashboard project from scratch. First tip: if the MOPA interface appears in Chinese, you can switch it to English by clicking the Open in Browser option. This opens it in your web browser where it defaults to English. This is an important first step that many people miss. Kyle explains how to create a new project in MOPA. You start by describ

partner or retailer names, geographic locations, product categories, and timeline or date ranges. Specifying these dimensions upfront helps MOPA create a more accurate dashboard on the first try. Heather asks about whether she should plan her data structure upfront or just start building and iterate. Kyle says both approaches can work, but planning upfront saves significant time. He recommends spe

same dashboard? Yes, you share the project link with team members. Once they access it, their permissions persist long-term. Multiple people can modify and sync data through the shared project. The collaboration link persists over time. Once someone has accessed your project, they maintain access without needing to be re-invited. This makes it easy for teams to jointly maintain dashboards. Kyle di

need (totals, averages, comparisons to prior period). Kyle agrees with Michael and adds that you can even use the AI agent as a planning partner. Before building anything, you can have a conversation with the AI about your data structure, describe what reports you receive, and ask it to help you design the optimal dashboard layout. This planning conversation with the AI can save hours of rework la

stores by the 13th and then, and to the store, not the warehouse, but all the way to the store. And then if there, if it's a top store and they unload their truck that same day, it could be getting sold by the 14th. And so that's literally nine days only. So it can go from anywhere from like a week all the way up to a month. And so where it makes it hard planning wise in to where you, that's why w

reporting works is we're not gonna get that information until the following Monday, so the 18th. And the that data that we get on the 18th is as of the 16th, so Saturday. So we're already now two full weeks'worth until we, on our end, are even able to see that it only took 3 days for it to get to the store. So it's, the timing issue is also something that you have to take into effect, and that's o

able to track everything at a real time. It, or almost it would it be updated hourly. And so literally we would be able to, you know, I'm sitting here, my best guess is the 4 weeks. And a big part of it, honestly, though, is the fact that we don't get access to the data except once a week. It because if we, if I, like I said, if it arrives on a Monday or Tuesday, I'm not gonna know until the follo