Building Trusted AI Engineering

AI is changing how we build software. But how do we build systems we can trust? Join Open Source Singapore Meetup to explore AI-native engineering, open-source frameworks for production AI, and real-world lessons from LLM performance. Discover how to build faster, more reliable software with AI while maintaining engineering discipline and control. \\Signup at this link:\\ https://luma.com/rbz02r24 Agenda: 6:30 PM: Registration 6:50 PM: Welcome and opening remarks 7:00 PM: Building AI-Native Engineering Teams Without Losing Engineering Discipline 7:25 PM: LLM4S 1.0: From Idea to Production AI in Scala/JVM 7:50 PM: Fast Models, Slow Systems: Lessons from Benchmarking an LLM 8:15 PM: Networking 8:30 PM: Event Ends 1\. Building AI\-Native Engineering Teams Without Losing Engineering Discipline Speaker: Ilya Verbitskiy Ilya Verbitskiy is a software engineer and architect with over 20 years of experience building cloud platforms, security systems, and developer tools. His current work focuses on AI products, agent-based software, and practical approaches to reliable AI-native engineering. AI-native engineering is not about replacing engineers with prompts. It is about redesigning the delivery system so humans and AI work together with clear intent, strong constraints, and rigorous verification. This talk shows how small, senior teams can use AI to ship products in weeks without accumulating architectural debt. We will explore why faster code generation makes engineering discipline more important, not less, and how teams can avoid the common failure mode of plausible but incoherent AI-generated code. 2\. LLM4S 1\.0: From Idea to Production AI in Scala/JVM Speaker: Kannupriya Kalra Kannupriya Kalra is the Co-Founder of the LLM4S Foundation and creator of LLM4S, an open-source generative AI framework for Scala and the JVM. From an open-source idea to a production-ready AI framework, LLM4S has evolved rapidly over the past 18 months. Kannupriya will share the journey towa