18.05.2026 –, Raum B
AI-powered autonomous agents are changing the way we interact with large language models (LLMs). In this hands-on workshop, you will learn how to build and customize AI agents using open-source models and frameworks. We will explore how these agents reason, plan, and execute tasks, and how they can be integrated with external tools.
This workshop is designed for developers, researchers, and AI enthusiasts who want to build intelligent LLM applications. No prior experience with AI agents is required—just basic Python knowledge and a curiosity to experiment!
--- After the workshop you will know... ---
✅ What AI agents are and how they interact with LLMs
✅ How to build AI-driven workflows using open-source frameworks
✅ How to integrate external tools and APIs using MCP
✅ How to secure your agents using guardrails
✅ How context engineering can be used to reduce hallucinations
AI agents allow large language models to go beyond simple text generation—they can think, plan, and take action. In this workshop, we will explore how to design LLM-powered agents that automate workflows, process information, and interact with external systems.
In this workshop you will be able to choose among many different cloud-based LLMs to gather hands-on experience with agentic AI. You’ll start by building a simple AI agent, then extend it with new capabilities, such as integrating APIs or working with structured data.
--- Key Topics Covered ---
✔ Understanding AI Agents: What they are, how they work, and common frameworks
✔ Hands-on Development: Building a simple agent from scratch
✔ Expanding Capabilities: Enhancing agents with plugins, APIs, or external tools
✔ Optimizing Agent Performance: Debugging, logging, and prompt tuning
✔ Guardrails: Securing your agentic workflows
✔ Context Engineering: How to reduce hallucinations
--- Who Should Attend? ---
👨💻 Developers interested in LLM-powered automation
📊 Data scientists & AI researchers exploring autonomous AI workflows
🛠️ Tech enthusiasts looking for hands-on experience with AI agent frameworks
--- Prerequisites ---
• Basic Python programming skills
• Familiarity with Git & working in a terminal
• Some knowledge of LLMs (not required but helpful)
• A laptop with Python 3.11+ installed, or the ability to use a cloud-based environment
I am a PhD student doing research in NLP. I am working on an interesting Sinergia project that aims to measure the level of sustainability in call for tender documents in the domain of public procurement. Previously I worked as a Senior Machine Learning Engineer at BSI, where I was focusing on the deployment and ethical use of Large Language Models within the BSI Customer Suite. Regarding my studies, I earned my masters's in Computer Science, specializing in Data Science, from the University of Bern. During my master's program, I contributed to the development of DiBB, a Python library aimed at distributed black-box optimization.
Outside of work, I keep a close eye on emerging trends in generative AI and human-centered technology. When I'm not exploring the digital realm, you'll find me delving into psychology, decoding escape rooms, and indulging in bicycle rides.