4/8/2026 Jeanie Chung
For National AI Literacy Day, 27 high school students came to DPI to learn about generative AI, ending the day by building their own workflows.
Written by Jeanie Chung
It’s easy to think about the future of computing in terms of hardware and software, qbits and processors, and lines of code. But of course, the future of computing, and of the tech workforce, is really the people who create and work with all that technology.
That was the idea behind DPI’s second annual observation of National AI Literacy Day, a chance for area high school students to play around with AI tools outside the pressure of a class or internship.
Program Coordinator Kenyanna Sanders said that, as with any DPI program, the organization’s National AI Literacy Day activity was grounded in DPI’s investment in students’ understanding and feeling comfortable with trends in Chicago’s tech ecosystem.
“This allows them to get some trial and error under their belt, get comfortable, and honestly feel safe exploring,” she said, “and feel like they can actually apply this in the future to a real tech career.”
Under the direction of instructor Ian Heraty, DPI’s software development educator, the 27 students in the workshop began with an overview: What is AI? What is a model? What are hallucinations and how do you deal with them?
“I was really impressed by how many AI tools they already use,” Heraty said. “They are AI natives.”
With the foundation set, students dug into workflows and prompts, and how to use them
Heraty walked them through n8n as a workflow development tool, showed them how to connect their workflows to generative AI, and then had them develop their own. At the end students shared the workflows they created around the assignment: creating a product using AI to address a real-world problem.
Shriya created a video featuring a superhero who could save a city from a giant donut. Naturally it was Homer Simpson.
(No one said they had to be serious problems.)
Harish and Dhishant built a workflow to simulate the 2026 World Cup, focusing on how logic, inputs, and decision paths can model outcomes instead of relying on surface-level predictions.
Harish, who has already founded a startup, posted about the workshop to LinkedIn. “Most people attend AI events and leave with notes,” he said. “I left with a working system.” But he said what stood out for him was less what he built than the environment in which he built it.
“A room full of people building, testing, and challenging ideas instead of passively listening,” he said. “This is what AI education should look like.”