Workshop – Beyond Prompting: A Gentle Introduction to Agentic AI – May 21, 2026

Agentic AI refers to artificial intelligence systems that can act autonomously — planning, making decisions, and executing multi-step tasks with minimal human intervention. Unlike traditional LLM-based tools that simply respond to a single prompt, agentic systems can complete tasks that you design. You can design an agent to browse the web, run and debug code, manage your files, review and send emails, and chain together complex workflows to accomplish your goals on your behalf.

For faculty and staff, understanding Agentic AI is of great interest for a variety of reasons. Faculty want to understand it to a) see what their students are doing with AI, and b) see if there are any opportunities to improve their own workflows in a safe, secure way. Of particular interest is the use of AI systems to improve research. (Your favorite chatbot can be a pretty decent “research assistant” if guided properly!) Likewise, administrative staff want to understand how their tasks might be streamlined. And, most importantly for us, we all want to know how our students’ learning is affected when they engage with these tools. (And if you think they aren’t using AI, you’d be wrong.)

Knowing what agentic tools can do and where their limits and risks lie helps educators make informed decisions about how we might integrate them responsibly into teaching, research, and daily workflows. It also helps us understand when not to use them. As these technologies become embedded in mainstream software and institutional processes, fluency with agentic AI is fast becoming a core professional skill.

To help our community address these urgent topics, I led a workshop introducing faculty and staff to Agentic AI on May 21, 2026. Below are the slides from my workshop. The workshop was prepared and delivered as part of my role as a Faculty Fellow at the Dominguez Center for Data Science.

Workshop – Beyond Prompting – A Gentle Introduction to Agentic AI, Presented at Bucknell University, May 21, 2026. ©2026 by Brian R. King, licensed under CC BY-NC-SA 4.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/

Workshop – Demystifying AI – May 23, 2025

The links below are to Python notebooks for each section of the workshop. Open the notebook, which will take you to a Google Drive link that is a read-only version of the notebook. Open the link, save a copy of the notebook file in your Drive space, and open it in Google Colab. You can also run the file locally on your own machine if you have a complete Python environment installed with Jupyter/JupyterLab or an editor that lets you edit Jupyter notebooks. All notebooks were tested on both Google Colab and natively.

These materials are part of workshops taught in my role as Faculty Fellow of the Dominguez Center for Data Science.

Workshop – Demystifying AI, Presented at Bucknell University, May 23, 2025. ©2025 by Brian R. King, licensed under CC BY-NC-SA 4.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/