Agentic Engineering & ToolingBuilding Autonomous AI Agents with Spring
This workshop teaches building autonomous agentic AI systems with Java, Spring AI, and MCP. It covers prompting, chat memory, RAG, tool integration, and agentic patterns, plus production concerns like observability, security, and reliability. Attendees will create a multi-agent system for complex tasks.
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Software development has rapidly evolved from explicit, instruction-based programming to integrating the non-deterministic reasoning capabilities of Large Language Models.
Now, we face the next massive paradigm shift: moving from passive AI tools to Agentic AI.
In this workshop, you will learn everything you need to build these autonomous systems using Java, Spring AI, the Model Context Protocol (MCP) and more. We will move beyond basic prompting to master chat memory, RAG, tool integration, and agentic patterns. Most importantly, we address the "day two" challenges of production: ensuring your agents are observable, secure, and reliable. By the end of the session, you will have built a multi-agent system capable of solving complex, high-level tasks.
Join us and transform your applications from simple interfaces into proactive digital colleagues.
Timo Salm
Timo Salm is a Principal Solutions Engineer at VMware Tanzu by Broadcom with over a decade of experience in customer-facing roles, modern applications, DevSecOps, and AI. In his roles, he ensures that the most strategic customers in the EMEA region achieve their goals with VMware Tanzu's Spring, developer platform, AI, and data products. Another essential part of his role is continuously learning through experimenting hands-on with innovations and sharing the outcomes with colleagues, customers, and the community via, for example, conferences. Before Timo joined Pivotal, which VMware and now Broadcom acquired, he worked for consulting firms in the automotive industry as a software architect and full-stack developer.
Sandra Ahlgrimm
As a leader in the tech community, Sandra actively contributes to the Berlin Java User Group (JUG) and the Berlin Docker MeetUp. Her expertise extends beyond coding; she focuses on LangChain4j integrations and serves as the primary point of contact for developer feedback related to Java in Visual Studio Code (VS Code) and GitHub Copilot in IntelliJ. Additionally, her interest in performance and event-driven architectures led to her involvement with native images. Therefore, Sandra represents Microsoft on the GraalVM Program Advisory Board.