On May 19th and 20th, the Dynaimix team headed to the Crowne Plaza in King of Prussia, Pennsylvania for a two-day Intro to AI training with Yale Electric Supply Company. The session brought together a wide range of participants from across the organization, each at different points in their AI journey, and that range turned out to be one of the strengths of the room.
Yale Electric has been serving the electrical and lighting distribution industry since 1940. With eight locations across central and eastern Pennsylvania, Delaware, and New Jersey, they have built a reputation for exceptional service and deep product knowledge. That kind of operation runs on people who know their business well, and the training was designed to meet them exactly where they were.
Dan Callahan, Dynaimix AI trainer, led both days.
The training centered on ChatGPT as the primary platform, with practical guidance layered in on Copilot within Outlook and Excel. Yale Electric had already been actively using and evaluating several LLM platforms before the training, including ChatGPT, Copilot, and Claude, which made for a more substantive conversation throughout the two days. Participants weren’t starting from zero. They had real experience to draw from, real questions to ask, and in some cases real opinions about what was working and what wasn’t. That created a learning environment where the discussion moved quickly past the basics and into the kinds of comparisons that actually matter when you’re deciding how to use these tools at work.
One of the more practical segments covered Copilot’s standard version inside Outlook and Excel. While the basic version has real limitations, the training focused on where it delivers immediate, tangible value. Summarizing long email threads and quickly editing or reorganizing spreadsheet data were among the use cases that landed with the group, because they connect directly to tasks people are doing every day. Small time savings in the right places add up fast.
The capstone exercise on the afternoon of day two was where the training came together. Participants split into five departmental groups and spent the afternoon designing and building their own custom GPTs. Each group worked through the process of refining prompts, testing outputs, and applying the tools to business scenarios specific to their own team’s work. By the end of the session, every department walked away with a functioning proof-of-concept custom GPT and a set of implementation ideas they can continue developing and deploying on their own.
That outcome matters. A training that ends with participants holding something they built themselves, something connected to their actual work, is a training that has a chance of continuing past the last day in the room. The custom GPTs Yale Electric’s teams built aren’t just exercises. They are starting points.
It was a well-run two days with a sharp, engaged group, and a strong example of what happens when a company decides to bring its people along intentionally rather than waiting for AI to figure itself out on the floor.
