We sat down with Pat Cooney, Head of Platform Engineering, to talk about what Platform Engineering means here and where agentic AI fits into the picture. Pat has spent over a decade at Optiver across markets, regions, and roles.

When people talk about developer productivity, they often jump straight to tools: powerful coding agents, faster compilers, smarter automation. These things matter, but they are not the whole story.

In most systems, the database acts as a boundary. You write data into it, and other systems read from it. If you need something more dynamic, like reacting to changes as they happen, you usually introduce something alongside it, whether that is a service layer, a queue, or a stream.

Large language models (LLMs) are getting surprisingly good at learning the basics of trading. Consider that the latest models are able to perform tasks like pricing simple scenarios, reasoning through rules and even outlining basic strategies.

Leanne Fok is a Senior Infrastructure Engineer in Amsterdam with 15+ years at Optiver. She previously led the Infrastructure Platform team responsible for our internal Infrastructure-as-Code stack and is now leading the Infrastructure Kubernetes project.

If a UI doesn’t feel instant, it feels broken and users start to question what they’re seeing. A grid lags, values don’t update when expected, or a filter that used to feel instant starts to slow down. In high-demand systems like a trader’s workstation, a single desktop may be running many latency-sensitive applications at once, all competing for CPU, memory, and network bandwidth, so issues can show up quickly.