2026-06-09 –, Maschinenhaus
The LLM ecosystem changes faster than most teams can adapt. This talk shares our experience and the practical lessons we’ve learned while building an intelligent search product in a world where models, tools, and best practices constantly evolve.
Working with LLMs today means operating in an environment where models, APIs, capabilities, and costs change constantly. What works today may become obsolete in months, creating technical and organizational pressure on teams.
In this talk, we share our experience working in an intelligent search company in this environment. We will share the good, the bad, and the ugly: the rollercoaster of realizing that something which took hours of code can suddenly be achieved with a simple prompt. We discuss how we evaluate new models without destabilizing production, stay updated without losing our minds, and separate the wheat from the chaff in the constant stream of LLM news.
Beyond technical architecture, we reflect on the human side of constant change. The goal is not to predict where LLMs will go next, but to share strategies for building systems and teams that adapt without losing sanity.
I’m a computer scientist working in ML and NLP, with a soft spot for fairness, linguistics, and trying to make the world a bit better, or at least not worse.
I’m also passionate about making the tech world more inclusive and thoughtful, one system (or conference talk) at a time.
Machine Learning Engineer at Progress