LLM, RAG, MCP, A2A... OMG! Decoding the Alphabet Soup of Modern AI
Join Sarah and Jan for a live session transforming AI alphabet soup into practice.
Format: Michi introduces core concepts with clear explanations, then Sarah immediately demonstrates implementation in code. Watch abstract ideas become working functionality.
Journey: We'll build through essential AI components - local LLMs with Ollama, RAG, tool calling, AI agents, and MCP standard.
Twist: The application isn't just a demo – it's designed to help attendees. Leave with both deep understanding AND the practical skills to build your own AI app
Target Audience: Developers, DevOps Engineers, Software Architects
Prerequisites:Knowledge in a programming language (Python, etc.), AI interest
Level: Introductory
Extended Abstract:
Key takeaways:
- Demystify the AI acronym soup: Understand LLMs, RAG, Agents, MCP beyond the buzzwords
- Experience the building blocks: Learn how AI technologies stack together from basic queries to intelligent agents
- Get hands-on confidence: Leave with practical knowledge and working examples to kickstart your own AI projects
- Bridge the gap: Move from "knowing about AI" to "knowing how to build with AI"
Solution Architect
Sarah Matthies worked as a developer for 10 years before she decided to join GitLab. She is now part of the Solutions Architect team and enjoys teaching others about best practices and sharing tips and tricks. If not at work you'll find Sarah in a makerspace tinkering with something.
Solutions Architect
Jan Kunzmann has more than two decades of experience in DevOps — from a time when the word hadn't even been invented yet. As a Solutions Architect at GitLab, he helps organizations integrate AI into their DevSecOps practices. Jan is interested in everything related to science and technology, with a particular focus on security, privacy, and AI — and how these technologies are reshaping society.
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