There are two stories about AI and code. One is the one everyone talks about: that language models write programs for us. The other is the one that is more important, but that almost no one talks about: that code keeps language models in check.
The two stories are the same story. But you have to tell them together to understand where the field is actually heading.
There's a difference between working with AI and working practically with AI.
The former is using ChatGPT from a browser. The latter is building something where AI is one step among many—where data needs to be fetched, validated, sent to a model, checked, transformed, and stored elsewhere. Almost all commercial AI work is of the latter kind.
And if you're doing the latter, Nushell should live in your terminal.
I recently wrote about how I automate my blog releases in one command — text in, article with image out. That flow runs in a shell most people have never heard of: Nushell. And it's not a random choice.
When I build what I call compound AI systems — meaning systems where eg. language models and image models are combined with other components to solve a real task — the most important question isn't "which model are we using?". It's "what do we surround the model with?".
And that's where Nushell comes in.
With one command in Nushell, you can view your knowledge base from the outside — and discover things you didn't know you didn't know.
It's all about overview.
I discovered something new today. Not in a note, not in a meeting — but in a terminal window.
Imagine being able to create graphics in all kinds of popular formats.
Directly from the command line!
I know, that is not the dream of everyone. But then again, you really should try the command line with Nushell.
So many things can be done faster and more consistently that way.
Anyway, here is a small Nushell module I made to work with Google's Gemini 3 pro image preview model. (Google, you gotta come up with a shorter name.)