Hussein Loubani
AI Vision and Robotics Researcher
Montbéliard, France
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I am an AI researcher at the CIAD Laboratory at UTBM in France, working on computer vision, robotics, and applied AI. My work focuses on deploying vision-based and intelligent robotic systems in real industrial environments, with a strong emphasis on robustness, scalability, and seamless integration into existing systems. My research spans perception for robotics, multi-sensor fusion, and deep learning for visual inspection.
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Agentic AI Patterns Developers Can Use Today
Agentic AI is everywhere in 2026, but most examples are either toy demos or huge research systems. This session focuses on practical patterns developers can use right now to add agentic behavior to their applications in a controlled way.
We will walk through simple architectures for LLM-based agents that call tools, work with context, and coordinate steps, while still fitting into normal services, APIs, and UIs. The focus is on what is realistic for a small team, how to keep things observable, and how to avoid agents “going rogue”.
Attendees will learn:
- Core building blocks of an agentic AI system (tools, memory, orchestration)
- Simple patterns to integrate agents into existing backends and workflows
- How to keep agent behavior debuggable and predictable
- Pitfalls to avoid when moving from a chatbot to real agentic features
Dutch AI Conference 2026 Sessionize Event
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