The Test Set by Posit

In this conversation, Mine Çetinkaya-Rundel, data science educator at Duke University and Posit, joins Michael, Hadley, and Wes to talk about teaching data science in a time when AI can write the code for you. Mine shares her journey from actuarial science to academia, the teaching philosophy behind the “whole game” approach, and her experiments using LLMs for instant student feedback. Along the way, the group dives into the joys and risks of coding by hand, the role of open source in the classroom, and what it’s like to work across both the R and Python communities.What’s Inside:How a career in actuarial science led Mine to the world of data science and teachingThe “whole game” approach to learning and how it helps students stay motivatedBuilding an LLM-powered feedback tool for low-stakes assignmentsBalancing AI assistance with the need for hands-on coding experienceThe shared DNA of R and Python scientific computing communitiesThe hidden value of live coding, pair programming, and seeing the process — not just the output

In part two of our conversation with Wes McKinney, we dig into the challenges and realities of sustaining open source development. Wes shares how funding actually works (or doesn’t), why corporate buy-in is essential, and what it’s like building tools across languages, communities, and IDEs. We also talk about the Apache Software Foundation’s role in open governance and the origin of the Positron IDE.What’s Inside:Why passion isn’t enough for open source to scaleApache Arrow’s origin story and how it was pitchedHow open governance enables trust between competitorsThe thinking behind Positron, Posit’s next-gen IDEPolyglot programming – Designing tools that bridge the R/Python divideLLMs and data UX: Why modern IDEs need to serve both humans and modelsDay-to-day coding, advising, investing, and context-switchingMetalheads unite

Wes McKinney’s fingerprints are all over the modern data stack — from inventing Pandas to co-creating Arrow. But before all that, Wes was organizing speedrun communities and hacking together better ways to wrangle datasets in finance. In this conversation, he shares his origin story and what makes good tools good. Stay tuned for part 2, coming soon.What’s Inside:How frustration with data work led Wes to build pandas (and leave a PhD)A nostalgic dive into the GoldenEye speedrunning sceneWhy read_csv performance is a deeply personal crusadeLessons from convincing friends to quit finance and go open sourceFounding startups, launching Arrow, and the Ibis origin storyThe beauty of letting contributors take the reinsShout-out to Philip Cloud, pandas’ resident pun masterWhy open communities win — and what it takes to build them

Hadley Wickham, Chief Scientist at Posit and creator of the Tidyverse, shares his journey from a spreadsheet-loving teen to a major figure in data science. He reflects on how messy Excel sheets led to the tidy data revolution and discusses the challenges of developing R packages. The conversation touches on maintaining focus amidst burnout, his fascination with integrating LLMs into data workflows, and how writing books helps tidy ideas. Fun anecdotes, including a custom bike inspired by his Shiny textbook, add a personal touch to his insights.