Interactive notebooks were popularized by the Jupiter Project and have since become a core tool for

data science, research, and data exploration. However, traditional imperative notebooks often break down

as projects grow more complex. Hidden state, non-reproducible execution, poor version control

ergonomics, and difficulty reusing notebook code in real software

systems make it hard to move from exploration to production. At the same time, sharing results

often requires collaborators to recreate entire environments, limiting interactivity and slowing feedback.

Marimo is an open- source, next-generation Python notebook

designed to address these problems directly. Akshay Agrawal is the creator of Marimo, and he

previously worked at Google Brain. He joins the show with Kevin Ball to discuss the limitations

of traditional notebooks, the design of reactive notebooks in Python,

how Marimo bridges research and production, and where notebooks fit in an increasingly agentic

AI-assisted development world. Kevin Ball, or K-Ball, is the vice president of engineering

at Mento and an independent coach for engineers and engineering

leaders. He co-founded and served as CTO for two companies, founded the San Diego JavaScript

meetup, and organizes the AI inaction discussion group through latent space. Check out the show

notes to follow Kball on Twitter or LinkedIn or visit his website, Kball.LC.

Okay, Kevin.

It's great to be here.

Yeah, I'm excited to get to talk to you. Let's start out with a little bit about you. So can you give a quick background of who you are and how you got to our topic today where you got to with Marima? Sure, happy to. So my name's Akshay. I've got a background in computer systems, but also machine learning research.

I spent a little bit of time at Google Brain.

This was a while ago, back when Google Brain existed before it was taken over by DeepMind.

So this was 2017 to 18.

...