Rebecca Barter, senior data scientist at Arine and adjunct assistant professor at the University of Utah, refuses to work on things she doesn’t care about. Lucky for us, she cares about a lot, most of all impact. In this episode, Rebecca joins The Test Set to talk about learning fast, building better tools, and staying motivated and adaptable.

She shares how moving between R, Python, SQL, and dashboards reshaped how she thinks about expertise. Plus a reflection on her recent posit::conf talk, “AI: Hype, Help, or Hindrance.”

Episode Notes

Rebecca digs into what it’s really like to work with AI every day and why humans still rule, especially in exploratory data analysis. She explains how tool building can be the fastest way out of busywork and how teaching beginners sharpened her ability to communicate clearly. The conversation circles a bigger question too: As AI keeps improving, are we headed toward a future where code looks completely different … or maybe disappears altogether?

What’s Inside

Why motivation matters even more than productivity
Escaping busywork by building better tools
From R to Python to dashboards: Learning fast as a survival skill
Reality check on AI in the IDE
Why exploratory analysis still needs human intuition
The 80/20 of coding: Automate the boring, protect the judgment
Teaching beginners and earning trust
The uncertain future of code

Rebecca Barter: Persistent learning, tool building, and ‘Will code even exist?’