Past event — This event ended 11 days ago.
September Meetup
About the event
Agenda: 18:00 doors open 18:20 doors close 18:20 Welcome 18:30 Debugging Class Loading with GDB - Marco Sussitz / dynatrace 19:30 break 19:55 Raffle 20:00 How to Become a Better Software Engineer with AI - Elias Erkinger / ActiveSolution 21:15 Networking @ Posedio
Debugging Class Loading with GDB Have you ever wondered why a particular class was loaded at that exact moment? Getting to the bottom of it can be surprisingly hard. I recently encountered a bug with a particularly nasty ClassCircularityError in which classes were loading unexpectedly, and I needed to figure out what triggered that. In this talk, I’ll walk through the steps I used to track it down. We’ll build a slowdebug JVM, attach GDB, and use breakpoints and inspection to identify the precise cause of the class loading. If you’re curious about how the JVM really works and want to peek under the hood, this talk is for you.
About Marco Sussitz Marco Sussitz is an engineer at Dynatrace who works at the boundary of Java and C++. He writes JVMTI agents, instruments bytecode, and digs into JIT, memory, and thread behavior. You’ll often find him sorting out class loaders or reading the spec longer than he should. Before Dynatrace, he worked on cloud video encoding with FFmpeg. In his off hours, he’s bouldering or in the mountains.
Becoming a Better Engineer in the Age of AI AI coding tools can produce code quickly, but developers still need to understand the problem, communicate intent, and judge the result. This talk explores how solid engineering practices help us work effectively with AI assistants. The first part focuses on thinking before coding: using pen and paper, clarifying requirements, and expressing intent through names, interfaces, and documentation. We’ll also discuss choosing the scope of a change and reviewing it critically. The second part brings these habits into practice through a Spring Boot demo application built with Codex. I’ll walk through a representative change, showing how I described the task, reviewed and corrected the generated code, and verified the result. Finally the demo serves a second purpose: demonstrating a simple Markdown structure for providing AI with guidelines, rules, and feature plans. Attendees will leave with a practical approach to organizing context, guiding implementation, and reviewing code, tests, and documentation together. Effective AI assistance starts with clear intent and engineering judgment - and developers remain responsible for the software they deliver.
About Elias Erkinger Elias Erkinger is a software engineer, consultant, and certified Java and Spring professional. He builds and modernizes enterprise applications with Java, Spring Boot, Angular, and relational databases. His interests include software architecture, clean code, and making complex codebases easier for developers and coding agents to understand. His experience with AI-assisted development spans early code-completion tools through to agentic coding with Codex. Along the way, he has built LLM-powered applications and agentic workflows using Spring AI, LangChain, and n8n. A regular attendee of developer meetups and conferences, including JavaOne in San Francisco, Elias enjoys exchanging ideas about practical AI engineering and how AI is changing the craft of software development.
