In the previous post we looked at hidden furnaces in agentic products. The example was the most common one, title generation. You type the first message, and the product quietly asks another model to name the conversation. Small and useful.
The most interesting AI workflow I have right now is not a coding workflow. It has code in it. It has a small Swift CLI, some auth state, a few JSON exports, a Codex automation, and way too much knowledge about how Discourse represents unread things. But it is not one of those fancy loops that will make you a product overnight.
Since I’ve been working with AI agentic tools, and especially since I’ve been working on the various incarnations of my own agent harness , there is something that is very clear to me.
A few weeks ago I read An Interpreter for Swift , from Cocoanetics, and I had that nice feeling of somebody else having already articulated the thing that was vaguely floating in your head.
Skills are everywhere right now. People talk about them as if they were some magical incantation that will make AI more powerful while also keeping it under control.
In the previous post we gave superpowers to the harness in the form of a bash tool. Even doing it just for the learning experience, it was already very eye-opening. It made this little Swift harness feel much closer to the real thing.
In the previous post, Have You Built an Agent Harness Yet? , we built a tiny harness in Swift. We gave it a loop, a prompt, and some tools, and with that it already had most of the features we are used to with modern AI. No magic. Just autocomplete, and a harness deciding what the model gets to see and do.
For years I have repeated a thing that I still believe. Every programmer should write a promise library once. I think agent harnesses are the 2026 version of that exercise.
I was migrating to a newer version of The Composable Architecture, which meant there was a list of deprecations to clean up. One of the things on that list was adding InferSendableFromCaptures as an upcoming Swift feature flag across all our package targets.
Today Mastodon has officially released their solution for a Share to Mastodon button . I was already using a third party service on this site, but I decided to give it a try because using officially supported tools seems easier to maintain in the future, especially for something I don’t work on every day.
Today I made an exciting discovery: the existence of AnchoredRelativeFormatStyle . An API that, as of the time of writing this, barely appears in search results other than Apple’s sparse documentation. And to my surprise, it’s exactly what I’ve been looking for over the past few years.
Recently, while watching a Tsoding stream , I saw something that piqued my curiosity. Alexey demonstrated how one of his applications could render a video just by calling into the ffmpeg binary directly, instead of using it as a source code dependency or even a static or dynamic library linked to his program.
Sometimes in command line tools we want to perform some cleanup final task before the process is killed. To detect this scenario we can hook to unix signals like an interrupt and perform the needed work before existing from the process.
Recently, I finished an almost final draft of my novel and decided it was time to refresh my online presence and website. Instead of starting my next novel, I dove into creating the next version of my site, what I call alejandromp4 . And, of course, you know what that means… using a new static site generator! Yes, I have a problem with focusing my hobbies; I’m working on it.
In my team, one of the things we always make sure of is keeping our dependencies up to date. We rarely add a dependency without a really good reason, and when we do, we assign an owner who is responsible for keeping it up to date.