Jarosław Śmietanka
Senior Software Engineer in the Commodities Risk Technology team at Balyasny Asset Management, working on large-scale, long-lived Python systems in a high-stakes financial environment.
Previously a Technical Team Lead at Growbots, where I spent nearly a decade designing and evolving microservice-based data platforms, leading engineering teams, and improving the maintainability of complex production codebases.
With over ten years of professional experience across finance, data engineering, and backend architecture, my work focuses on reducing system complexity, improving changeability, and helping teams deliver faster in real-world Python environments.
Session
Some codebases let you ship a change in minutes. Others turn a one-line fix into weeks of investigation.
The difference is often not skill, tooling, or even architecture—it’s cognitive load.
In this talk, we’ll look at real examples from long-lived Python systems to understand how inheritance, deep nesting, excessive abstraction, microservices, and over-applied DRY silently increase the cost of change.
You’ll learn practical heuristics to recognize high cognitive load early and concrete strategies to reduce it—so your team can move faster without rewriting everything.
This is a pragmatic engineering talk for developers who work in real production code, not greenfield demos.