AI Meet-Up: A Framework for Choosing the Right AI Building Blocks
Join us for talks and drinks, and connect with the artificial intelligence community of the AI Innovation Center!
“Agent”, “Skill”, “Harness”, “Workflow”: the vocabulary around AI is exploding, and it’s getting harder to tell what’s genuinely new from what’s just a rebranded API call. We are happy to welcome Samer Albadry from Snowflake to the stage. Together, we’ll cut through the noise and build a practical framework for understanding how modern AI systems are put together and how to choose the right AI building blocks for the job.
Register here- Date 10 September 2026
- Time 15:30 to 18:30
- Location AI Innovation Center, HTC 5
- Organization AI Innovation Center
- Contact ai@hightechcampus.com
We’ll unpack what agents, skills, harnesses, and workflows really are, how they differ, and when each becomes the right building block instead of defaulting to “just add an LLM.” Along the way, ideas come to life with live demos, showing how the pieces fit together in practice.
Drawing on Snowflake’s work with some of the most innovative startups around the world, he’ll share what the sharpest teams are actually building today, the patterns that separate hype from real value, and the lessons you can steal for your own projects. Expect concrete examples and an honest look at where this is all heading.
Whether you’re building AI into production today or just trying to keep your bearings, you’ll leave with a practical framework for choosing the right AI building blocks, knowing when to use them, and understanding why.
Event details
Date: 10 September 2026
Location: AI Innovation Center, High Tech Campus Eindhoven (HTC 5)
Program:
15:30 – 16:00 Walk-in
16:00 – 16:15 Welcome and update on AI Innovation Center by Philipp Werle (HTCE)
16:15 – 17:00 Talk and Q&A by Samer Albadry (Snowflake)
17:00 – 17:15 Open mic
17:15 – 18:30 Drinks and networking
Our speaker
Jaïro Martha (Snowflake) is a Solution Engineer who works with organizations looking to turn their data and AI ambitions into real implementations. This gives him a close view of what teams are building, where they tend to get stuck, and which patterns make the difference. He is particularly interested in how companies can build AI agents that combine flexibility with the predictability needed in production.