In Episode 162 of the AIAW Podcast, we’re joined by Göran Sandahl, Co-Founder of Opper AI, to explore the future of building reliable AI systems at scale. Göran shares his journey from observability engineering to co-founding Opper AI, a company tackling one of the most urgent challenges in enterprise AI: making LLM-based features predictable, testable, and production-ready.

We dive into Opper’s structured API approach, the strategic vision behind their recent acquisition of FinetuneDB, and how combining dynamic prompt engineering with fine-tuning workflows strengthens reliability in AI agents. Along the way, we unpack the nuances of context engineering vs. prompt engineering, debate whether open-source AI models will gain or lose momentum, and examine how enterprise AI and data sovereignty shape the path to trustworthy integrations.

From “specification-first” design to real-time tracing, Göran offers a sharp look at the skills developers will need in the AI era—and how to build systems that don’t just work, but can be trusted. A forward-looking conversation on what it takes to create harmony between humans and machines, one integration at a time.

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