In part one of our conversation with Julia Silge, astronomer-turned–data-science leader, we explore why data science needs a different kind of IDE. Julia takes us inside Positron, Posit’s next-generation, data-scientist-first environment, and unpacks the day-to-day realities that make data science work unlike software engineering. Along the way, we get a first-hand account of a legendary pineapple-pizza protest and how to juggle multiple projects at once.

Episode Notes:

A behind-the-scenes tour of Positron and the workflows it’s built for, plus the stories, trade-offs, and team choreography required to ship an IDE on a living substrate. We talk extension ecosystems, upstream merges, data viewers, and more. Plus, Julia shares why applied systems (and messy, real-world data) are her happy place.

What’s Inside:

• The pineapple-pizza story that unexpectedly went viral — and what “context collapse” feels like from the inside
• Why Positron is a data-science-first IDE, optimized for analysis, not general software engineering
• Iteration vs. reproducibility: the central tension in data science workflows and how tooling can honor both
• Hadley’s cold-turkey move from RStudio, muscle memory, and finding the new ergonomic groove
• How Julia measures success by smoothing the boundaries between tools and teams
• The applied, people-and-process side of data science that keeps Julia energized