UNCONFERENCE: Engineering AI Together #11
Join us for the 11th edition of the Unconference: Engineering AI Together.
A no-hierarchy gathering for software engineers, AI/ML practitioners, and technical builders to spend an evening exchanging ideas, pressure-testing approaches, and going deep on the problems they are actually working on.
Unlike a traditional conference, there is no preset agenda and no speaker lineup. The sessions are proposed and shaped by the people in the room. Bring a technical question, a problem you are stuck on, something you have learned recently, or simply join a discussion that catches your attention.
Previous sessions have explored topics including:
AI Coding Tools
Can fully generated codebases deliver secure, scalable architectures, and where does human design still matter?
Model Hosting & Reliability
How do we make increasingly complex models reliable and cost-efficient in production?
AI Agent Orchestration
What does coordination between multiple agents actually look like, and how do we design systems that produce useful emergent behaviour?
Meta Prompting for Code Generation
Which meta-prompting techniques meaningfully improve code quality, structure, and maintainability?
The event is deliberately curated for people who are actively building in software and AI, so the conversations stay technical, practical, and useful. If you are not currently hands-on in full-stack, ML, or AI development, this one may not be the right fit.
Doors close at 6:30 PM sharp.
About your hosts
Merantix AI Campus: In the heart of Berlin, the Campus brings together 80+ AI teams and hosts 300+ events a year. Part of Merantix, it is a meeting point for founders, engineers, researchers, operators, industry leaders, and investors building the next generation of AI infrastructure and applications.
Hacker Room: A four-month residency at the AI Campus for technical builders working deeply on AI projects. It brings together engineers and researchers developing beyond the API layer in a collaborative environment outside the usual constraints of academia, accelerators, or company KPIs.