PyData June 11th 2026 Meetup

⭐️Agenda⭐️:

•⁠ ⁠18:00 - Open Doors
•⁠ ⁠18:30 - Short Intro
•⁠ ⁠18:40 -19:10 First Talk (Sahra Klünder) and Questions
•⁠ ⁠19:10 - 19:30 Break -Networking & food/snacks
•⁠ ⁠19:30 - 20:00 Second Talk (Artur Galstyan) and Questions
•⁠ ⁠20:00 - 20:45 Networking & food/snacks

First Speaker:

⭐️ Sahra Klünder
LinkedIn: https://www.linkedin.com/in/sahra-klunder/

The First topic: The AI Adoption Paradox: When Technology Moves at Internet Speed and Organizations Move at Paper Speed

Abstract: AI is evolving extremely quickly, with new models, tools, and workflows emerging all the time. Yet many large organizations struggle to turn AI excitement into real business value. While demos and pilots may look promising, practical adoption is often slowed by overlooked foundations such as limited data access, missing internal APIs, unclear ownership, legacy IT integration challenges, procurement barriers, compliance requirements, and risk management processes.
The talk argues that many organizations are not failing because they lack advanced AI capabilities, but because they have not built the basic conditions needed for AI to work reliably. Real value comes when AI is embedded into everyday workflows, supported by usable infrastructure, accessible data, clear responsibilities, and governance that helps teams move forward.
Expect fewer buzzwords, more reality, and concrete ideas you can apply on Monday morning.

Second Speaker:

⭐️ Artur Galstyan
LinkedIn:https://www.linkedin.com/in/galstyanartur/

The Second topic: Am I still a Good Coder?
Abstract: Six months ago, I barely used AI in my day-to-day coding. Today, roughly 95% of my code is written by an AI agent. This talk traces that transition, from early frustrations, to the moment I realized a colleague was shipping faster than me and I had to adapt or fall behind. While code was flying off the shelves, the uncomfortable realization kicked in: I was no longer writing code myself. In my opinion, coding is a muscle, and muscles atrophy! I'll share some of the exercises I do daily to keep my skills sharp, share some of the projects I code by hand (such as a LSP for Numpy matrix operations), and give you the decision tree that I apply to check when (and how) to apply AI during my work in order to maintain my skills while also shipping. This talk is for anyone who uses AI coding tools daily and has quietly wondered: am I still a good programmer?