Stop Making TUIs — Quarrelsome

Our field has a weird relationship with terminal and command line interfaces. The time has come to re-evaluate it.

I’m on a kick lately getting my friends to try building native user interfaces. I built my first serious Mac application a few months ago, and since then I’ve built more native UI thingies than in my entire career prior to that. Let’s take a quick tour.

This is MDV.app, the greatest Markdown viewer in the world until someone else writes a serious markdown viewer. I’ve already written a bunch about MDV and won’t wear you down with more advocacy for it. It is great, though.

I had almost no hand in writing this UI code. Why would I? Like most user interfaces, MDV doesn’t break any new ground. It’s not a challenging problem. But building good UI is very hard: this kind of code is tedious, repetitive, exacting, and gated by platform conceptual knowledge. It takes years to get good at this kind of work. Which is why I would never hand-write this program. Instead, I summoned it.

Moving along:

I spent the last year doing Math Academy, from Foundations I through Machine Learning, which you can shorthand as “I taught myself calculus”. I like Math Academy a lot and have a bunch to say about it, but here it’s just the set-up to another SwiftUI app I willed into being: a native calculator-style frontend for SageMath, which is the default math system for cryptographers.

Three big things this app does for me: it automatically renders Sage output in LaTeX, which gets handier the deeper you get into multivariable calc, it point-and-click exposes Sage methods on objects like vectors, matrices, and expressions (which is much nicer than typing trig_simplify over and over again), and it provides a “little language” of shorthand inputs that make common operations (like “take the gradient of this expression”) quick to type. [1,2;3,4] is a matrix in this system; you should already be sold on it.

I’m not packaging this application up. If you want it, just screenshot this section of the post and give it to Claude. It’ll build something useful. You see where I’m going with this.

(it would be more useful if I cleaned up all my genre labels, most of which date back to the first MP3 rips I did back in 1997).This is DJ Roomba, my Apple Music player. The genre map is a dubious feature. What isn’t dubious is the embedded LLM agent, which has tool calls to read my library, my last played list, and my upcoming tracks. “I’m going to the basement shop to build a picture frame; give me a no-skips playlist to fit the mood”. Turns out the mood is “lots of Kurt Vile and Tom Petty”. No notes.

It’s backended by a SQLite database, a sane one with a reasonable schema, which was also a surprisingly useful feature.

I don’t really know what to think about programs like this. It’s an AI-assisted music player that includes 90% of the interface of Music.app. Music.app. My ever-present personal computing nemesis. This is the personal computing equivalent of slaying a dragon. But I didn’t write a single line of code in it. Am I developing software, or just configuring my computer?

Hold that thought.

This is my LLMwiki. Somebody should write a popular, widely-shared piece on how valuable a self-driving wiki is, where you feed it source material and ask it questions and it writes the wiki for you. Wildly useful idea, I’m glad I thought of it.

Self Driving Wiki.app was fun to write. Unlike DJ Roomba, which directly embeds a Responses API client, this app drives claude -p under the hood. Because I assume that agents work better with a filesystem to grovel, I summoned a macOS virtual filesystem extension, which reflects a read-only view of the backing SQLite database as a mounted filesystem inside the app’s sandbox.

Was this probably unnecessary? Does it make the app more annoying to install, for instance by requiring it for some reason to run out of /Applications/? Yes, and also yes. But these kinds of yak-shaving excursions were the joy of software development in the pre-LLM era and I’m glad to discover that I can still experience them today.

(hyper-responder at 2.5 with zero side effects, this shit is choice)Here’s something I use constantly: a semiautomated food macro tracker. I’m glipping balls like everybody else. The app is another simple agent fronting GPT5, taking very short meal descriptions like spitball a guess on the calories ingested tasting cake batter and cream cheese frosting (but I didn't eat any cake) and translating them to intake estimates.

Here’s a menu-bar application that tracks temperatures around my house using these cheap little TP-Link temperature sensors that are giving the Chinese Communist Party access to my Apple TV. Normally after putting something like this together I’d be able to tell you a lot more about the protocols and HTTP APIs these things use to communicate, but I did none of the work to figure that out, so all I can tell you is that there are two different...