When LLM's write code to accomplish a task, that code has to actually run somewhere.

And right now, the options aren't great.

You can spin up a sandbox container and you're paying the full second of cold start overhead,

plus the complexity of another service.

Let the LLM loose on your actual machine, and well, you better keep an eye on it.

On this episode, I sit down with Samuel Colvin, the creator of Pidentic now at 10 billion

downloads, to explore Monty, a Python interpreter written from scratch in Rust, purpose-built

to run LLM generated code.

It starts in microseconds, is completely sandboxed by design, and can even serialize its entire state to a database and resume later.

We dig into why this deliberately limited interpreter might be exactly what the AI agent error needs.

This is Talk Python to Me.

Episode 541 recorded February 17th, 20206.

Talk Python to me, yeah, we ready to roll.

Upgrading the code, no fear of getting old.

They sink in the air.

New frameworks in sight, geeky rap on deck.

Quark crew, it's time to unite.

We started in pyramid, cruising old school lanes, had that stable base. Yes, sir.

Welcome to Talk Python, a me, the number one Python podcast for developers and data scientists.

This is your host, Michael Kennedy. I'm a PSF fellow who's been coding for over 25 years.

Let's connect on social media. You'll find me and Talk Python on Macedon, Blue Sky, and X. The social links are all

in your show notes. You can find over 10 years of past episodes at Talkbython.fm. And if you

...