Python, Go, Rust, TypeScript and AI with Armin Ronacher

The Pragmatic Engineer

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Python, Go, Rust, TypeScript and AI with Armin Ronacher

For an AI startup today, what language would be the best choice? Flask creator and former Sentry engineer Armin Ronacher discusses this, and how AI is changing how he now builds software.

Gergely Orosz

Oct 08, 2025

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In this episode

For an AI startup today, what language would be the best choice: Python, TypeScript, Go or Rust?

Armin Ronacher is the creator of the Flask framework for Python, was one of the first engineers hired at Sentry, and now the co-founder of a new startup. He has spent his career thinking deeply about how tools shape the way we build software.

In this episode of The Pragmatic Engineer Podcast, he joins me to talk about how programming languages compare, why Rust may not be ideal for early-stage startups, and how AI tools are transforming the way engineers work. Armin shares his view on what continues to make certain languages worth learning, and how agentic coding is driving people to work more, sometimes to their own detriment.

We also discuss:

Why the Python 2 to 3 migration was more challenging than expected
How Python, Go, Rust, and TypeScript stack up for different kinds of work
How AI tools are changing the need for unified codebases
What Armin learned about error handling from his time at Sentry
And much more

Jump to interesting parts:

06:53. — How Python, Go, and Rust stack up and when to use each one
30:08 — Why Armin has changed his mind about AI tools
50:32 — How important are language choices from an error-handling perspective?

Interesting quotes from the episode

On how Armin uses AI tools (at 28:05)

“Over the years, many of my projects didn’t go anywhere because the legwork needed to build this bespoke tooling to be able to pull this project off was too much.
One of the big changes I’m noticing for myself is that I have so many better tools around now. For example, I moved from Terraform to Pulumi for one of the services just to see how that goes. I had Claude build me a perfect control system to get my logs and visualize what’s going on in production. I would never have done this before [Claude Code] just because it wouldn’t have worked.”

Why Armin wants to hire more engineers at his startup, despite using an “army of AI interns” until now (at 33:48:)

Now there’s an argument to be made that maybe systems like Claude will help you, and maybe you can even bootstrap a startup around it. But if you fully delegate everything that you’re doing to a machine, then the person who doesn’t do that has an edge on you.
This is one of the reasons I want to hire more people now. It’s just because Claude is not a human. There’s energy to a well-running company and to motivated people that just a computer can’t replace. So a big part that sticks with you as an engineer is understanding how to create your systems, and understanding when the code it produces is more right versus more wrong. I don’t think much of this has changed [since AI].

Why Armin doesn’t believe strongly typed languages like TypeScript meaningfully reduce errors — based on his experience observing this at Sentry (at 52:42:)

There was a large-scale realization in JavaScript ecosystem that type checkers could get rid of a whole class of errors, because at the very least you have to explicitly check if this thing is nullable or not.
I never got the feeling that the adoption of TypeScript dramatically changed anything about JavaScript error rates. None of that adoption had any meaningful impact. If there was an impact, it’s immeasurable.
I remember that the adoption of more and more complex things in the React ecosystem has just dramatically increased the types of errors. For example, hydration errors were not a thing for many years. And then all of sudden, there’s a whole class of new errors coming in because of this [because of the wider adoption of React.]