AI @ AP Meetup

We are excited to invite you on December 18 for the next AI @ AP meetup, this time with a special focus on AI & Software. Join us on campus for inspiring talks, live discussions, and plenty of networking opportunities!

Program

19:00 – Tom Cools (DevRel at Timefold, Java Champion, BeJUG organizer, (Keynote) Conference Speaker)

Tom has a decade worth of experience delivering systems and loves to share not only knowledge but also passion for our craft. You can read more at his blog (http://www.tomcools.be) or follow him on Bluesky (@tomcools.be).

Talk: LLMs can't optimize schedules
LLMs have made remarkable progress, which might suggest they’re the answer to everything. However, when it comes to everyday tasks like creating work schedules they tend to fall short. As a result, humans often end up creating a schedule manually, which is usually far from optimal.
Fortunately, there’s a lesser-known branch of AI that excels at complex scheduling. In this talk, we’ll discuss Timefold, a Java based open-source AI solver, and you’ll discover how it leverages magic (aka math) to generate optimized schedules.

19:40 – Kristof Michiels (AP Hogeschool)

Kristof Michiels teaches Python, web development, and cybersecurity at AP University College in Antwerp. He guides IT students as they take their first steps into professional practice and explores the latest AI tools in both education and industry.

With a background spanning technology and the humanities, he blends analytical precision with a creative, human-centered approach. His mission is to empower people to use AI with confidence and insight as a force that amplifies their expertise.

Talk: AI-assisted coding: superpowers, tradeoffs, and the skills that still matter

AI-assisted coding is transforming how we build software. Tools like Copilot, Cursor and Claude can generate boilerplate, scaffold entire projects and refactor code at remarkable speed. But if AI handles the easy work, how do developers still grow from beginner to expert?

In this talk, we explore what AI is truly good at, where it falls short, and the concrete practices that make AI-assisted coding reliable: problem decomposition, context curation, reviewing AI-generated diffs and keeping security front and center.

Drawing on classroom experience and real-world development, we zoom in on the skills that matter most in an AI-native world - system thinking, debugging, communication and the human judgment no model can replace.

You’ll walk away with a clear, practical roadmap for thriving as a developer with AI: faster, smarter, and still fully in control of your expertise.