
Agentic AI is moving from prototypes to production and everybody must balance speed of adoption and reliability. Due to their dynamic task executions, the behavior of agentic AI is even more unpredictable than in regular AI system where ML/AI models - large or small - are utilized in predefined workflows. Nevertheless, going forward all the AI and product teams will be dealing with agentic AI sooner or later.
What does it take to build and operate the agents as productized software solutions?
Let's hear it from forerunners that have been living through the latest regarding advanced agent cases in enterprises or as technical founders.
🎤 The talks and the panel:
Case Story from WithSecure - Seamus Moloney, Data & AI Team Lead, Principal Data Architect / WithSecure Corporation
From Prompt to Product: Managing AI Agents in Production - Pasi Vuorio, Founder, CEO / ModernPath
Panel Discussion
Choosing the Right Approach for Agentic AI: Where It Fits and What It Demands
📍 Haaga-Helia University of Applied Sciences (Pasila campus next to Pasila railway station)
📅 May 19th
🕠 17:00 - 21:00
Beverages & snacks
Haaga-Helia University of Applied Sciences - Pasila campus
TrasaHaaga-Helia University of Applied Sciences - Pasila campus
Trasa