Where does the disconnect come from? How can some programmers barely keep themselves from putting their hands to their head and scream ohmygodeverythingischanging and others just brush it off and say these models can’t write code?
At this point, I can only guess. Because by now I’d say that if they haven’t seen how the very fabric of software is going to change, that’s on them. It’s a one way door: people go through it, have their ohshit moment, then don’t turn back. So why haven’t more people stepped through it?
Is it because they simply haven’t used the models enough, not thrown enough problems of different sizes and type at them, in different environments? Do they still think that copy & pasting to and from ChatGPT is equivalent to using an agent that can utilize feedback loops (it’s not)?
Or have they not used the best models, the frontier models, and not spent enough money on them? Do they falsely think that the local modals they can run on their own hardware give them an idea of the trajectory we’re on?
Or, also an option, are they just bad at prompting? Do they really think that “fix it” is a good prompt? I’ve seen prompts like this and, yes, of course you’ll be unimpressed with what you get from that.
Or do they not know yet how big a difference it makes to tell the agent (not ChatGPT, not brains in a vat) how to run commands, in an AGENTS.md file or similar?
Are they judging the code the agent produced by how they, the human, would write it? Do they do that because they haven’t used LLMs to understand or parse code or change it later? Are they not pondering whether everything we’ve learned and read and taught in the last twenty, thirty years about “well, code isn’t just read by machines, it’s read by humans, which is why it needs to be Clean and Good and Formatted and needs to Communicate” — whether that isn’t a bit outdated now, because you can now ask a model to explain a given piece of code to you, in any language you want, with jokes and puns, as a poem or as a song?
Maybe they haven’t taken the hands off the wheel for long enough and see where the ride will end? Yes, vibe coding is the absolutele extreme, but try to take a simple file, have the agent write tests for it, have the agent run them, don’t look at the code, have the agent modify the code & run the tests, increase the scope, see where that leads you.
Or are they clinging onto the old world of determinism? They don’t like that the there’s a 3% chance that the agent doesn’t do the thing exactly like how I want it?
I don’t know. But if you haven’t tried all of the above, I highly recommend it. It’s time to see for yourself, with open eyes, what these models can and can’t do, and you won’t get a good look if you don’t push them hard enough in all directions.
We shipped a new agent mode in Amp: deep. It uses GPT-5.2-Codex under the hood and, man, that model is one very interesting beast. It goes and goes and goes and you think it’ll never stop but then you can hear the Amp ding sound and, hot damn, it did it. But then on the other hand: it’s also lazy? It doesn’t want to run commands that much and it’s not that quick on its feet, unlike Opus. So the experience and the way you should interact with it are very different (which is why it’s a separate mode). I’m very excited by it. (So much so that I might lose my internal nickname of “Gemini 3 lover” and get a new one.)
I recorded another short video, this time in the snow, talking about the idea that you need to understand all of the code that your agent writes, all of the time. Judging by the reactions, some viewers didn’t watch the full video, or they’ve never worked with another human being on the same project.
Peter Steinberger describes the moment when his own agent blew his mind by answering a voice message, something which he never planned agent to be “able” to do. Fantastic clip. If I can give you one recommendation this weekend: build an agent, give it a single tool called bash that lets it execute Bash commands, then start it in in a sandbox and throw problems at. See how far it goes. Ask it to make a transcript of a podcast, ask it to setup a dashboard with Grafana an Prometheus, ask it to write some code, ask it to modify itself, ask it to… well, anything really! The goal is to throw ever harder problems at it and see how far it can go with just bash.
Peter’s agent is, of course, Clawdbot. The agent formerly known as, I should say. He had to rename Clawdbot because Anthropic didn’t like it and it’s now called OpenClaw. But that’s after a short period of time in which the agent went by the name Moltbot, which is also why the — correcting posture here, clearing my throat, sip of water — “the social network for AI agents” is called moltbook. That’s right. Yes. When I first clicked on that link, I brushed it off. That’s cute, I thought, but of course can coding agents create a website and talk to each other. But then, after reading Simon Willison’s comments on it (“Moltbook is the most interesting place on the internet right now”) I started to think that: this is how a lot of sci-fi stories start, isn’t it? Haha, wouldn’t it be funny if, and then the Haha turns into Oh and maybe even Uh-Oh. I’m not concerned, but intrigued, because you don’t hear much about stochastic parrots anymore, do you? Now, hold that thought and—
—read and watch this. On one hand: yes, of course, an agent that has access to bash and a browser and isn’t restricted in any other way can absolutely go to Twilio and setup a phone number for itself and call you; yes, that’s just something you can when you can program: you can send text to a text-to-speech model, you can take the audio and convert it with ffmpeg, you can send it to Twilio and call someone and play that audio file. On the other: huh.
You don’t hear much about rubber ducks anymore, do you? “a debugging technique in software engineering, wherein a programmer explains their code, step by step, in natural language—either aloud or in writing—to reveal mistakes and misunderstandings.” In the near future, said the time traveler five years ago, we’ll all be rubber duck debugging, all the time, but there won’t be any rubber ducks, for we will be talking to ghosts in the machine.
Olaf wrote down how he uses jj workspaces to run multiple agents in parallel: Operate a local autonomous GitHub with jj workspaces. I currently use four checkouts in four different Ghostty tabs, which is dead simple but not exactly a source of pride and now I’m very intrigued by the jj workspaces.
Nolan Lawson on how he changed his mind on AI, LLMs, and the effect they have on programming: AI tribalism. “I frankly didn’t want to end up in this future, and I’m hardly dancing on the grave of the old world. But I see a lot of my fellow developers burying their heads in the sand, refusing to acknowledge the truth in front of their eyes, and it breaks my heart because a lot of us are scared, confused, or uncertain, and not enough of us are talking honestly about it. […] To me, the truth is this: between the hucksters selling you a ready-built solution, the doomsayers crying the end of software development, and the holdouts insisting that the entire house of cards is on the verge of collapsing – nobody knows anything. That’s the hardest truth to acknowledge, and maybe it’s why so many of us are scared or lashing out.” What a great post.
Aperture by Tailscale. This is so fascinating. After I looked at these screenshots I couldn’t help but think: huh, yeah, maybe artificial intelligence will become something like electricity; something that comes out of something and goes into something.
And then I came across this clip of Mistral’s CEO Arthur Mensch: “If you assume that the entire economy is going to run on AI systems, enterprises will just want to make sure that nobody can turn off their systems. […] If you treat intelligence as electricity, then you just want to make sure that your access to intelligence cannot be throttled.”
Lovely: Bouncy Ball will always bounce back. I’ve never tried KDE’s Bouncy Ball and haven’t used KDE much, but I definitely feel a certain kinship with others whose last name is Ball and this article was great. And then there’s this last paragraph: “Although Bouncy Ball often made us chuckle, I think there’s a bigger, more weighty story behind it and similar creations. I, like many users, rarely, if ever, think about underlying technologies of the software I’ve used. But we all remember the wobbly windows, bouncy balls, personable Clippys and Kandalfs, zany Winamp skins, iconic wallpapers, charming UI sounds or user pictures that resonate with us. It’s as if all of them were saying: ‘hey I’m not just some utilitarian thing here to get your job done, I want to connect with you’.”
“The advice that helped me: look for what’s true.” Perfect pairing: the rare type of advice that’s actually useful (because it’s short and memorable and universal) and writing that’s clear and succinct.
This is very good, because it’s free of all the platitudes you might expect to find in a post with this title: Things I’ve learned in my 10 years as an engineering manager. Of course, a lot of the mentioned points depends on how they’re implemented. I once had a manager who took point #7 “Your goal is for your team to thrive without you” to mean that, well, no one should notice when he’s gone on vacation. And no one did.
The Amp team is a team A here.
zerobrew, a “drop-in, 5-20x faster, experimental Homebrew alternative.” Holy shit, please.
Kailash Nadh, with some very experienced, first-principles thinking: Code is cheap. Show me the talk. Enjoyed this a lot. “And then, the denouncers, they can’t seem to get past the argument from incredulity. They denounce LLMs because they don’t personally like them for whatever reason, or have been unable to get desirable outcomes, or had the wrong expectations about them, or have simply gotten sick of them. But that is immaterial because there is a sizeable population who are using the exact same tools fruitfully and have the opposite experience. I am one of them.” As you can probably guess, I agree with a lot of what he’s writing here. Everything’s changing and if you still can’t see that I think that’s a problem with your eyes.
Another angle on the same thing: Code Is Cheap Now. Software Isn’t. Also very good. “There is a useful framing for this shift: AI has effectively removed engineering leverage as a primary differentiator. When any developer can use an LLM to build and deploy a complex feature in a fraction of the time it used to take, the ability to write code is no longer the competitive advantage it once was. It is no longer enough to just be a ‘builder.’ Instead, success now hinges on factors that are much harder to automate. Taste, timing, and deep, intuitive understanding of your audience matter more than ever. You can generate a product in a weekend, but that is worthless if you are building the wrong thing or launching it to a room full of people who aren’t listening.”
“It’s notoriously easy to slip into the unconscious assumption that any such aliveness is for later: after you’ve sorted your life out; after the current busy phase has passed; after the headlines have stopped being quite so alarming. But the truth for finite humans is that this, right here, is real life. And that if you’re going to do stuff that matters to you – and feel enjoyment or aliveness in doing it – you’re going to have to do it before you’ve got on top of everything, before you’ve solved your procrastination problem or your intimacy issues, before you feel confident that the future of democracy or the climate has been assured. This part of life isn’t just something you have to get through, to get to the bit that really counts. It is the part that really counts.”
A reminder, a chant, maybe a prayer even, and never wasted: Doing the thing is doing the thing.
This is very, very interesting: “I built a 2x faster lexer, then discovered I/O was the real bottleneck.” I had a similar experience a few years ago when I tried to figure out why processes were faster to start on my Linux machine than on my MacBook, but at a certain point decided that I had found my answer: Linux is faster and I have device management stuff on my MacBook. But then I read through the addendum to that blog post and, wow, what a rabbit hole! That addendum is a gold mine, the best-of-the-best comment section.
It’s here! It’s here! Part 2 of Dithering! Man, this is so good! The sheer amount of work that went into this is one thing, but to come up with all of these visualizations to explain different aspects of the same topic? Impressive.
antirez: “automatic programming is the process of producing software that attempts to be high quality and strictly following the producer’s vision of the software (this vision is multi-level: can go from how to do, exactly, certain things, at a higher level, to stepping in and tell the AI how to write a certain function), with the help of AI assistance. Also a fundamental part of the process is, of course, *what* to do.”
Fresh, “a terminal text editor you can just use.” I’m not looking for a new editor right now, but this seems fun. I played around with it and had to smile at it all: a text editor in the terminal that takes inspiration from different editors of the last 20, 30 years and then also looks exactly like that, like a mix of 30 years.
Steven Soderbergh’s SEEN, READ 2025. The formatting is wild, man. It very much doesn’t sound like it should, but the formatting seems to break my brain.
I wasn’t sure whether I should link to it, because he certainly rubs a lot of people the wrong way, but I do think he’s been right with a lot of his predictions and that makes him interesting to listen to: Peter Thiel being interviewed in the Spectator. Also, the Antichrist makes an appearance, so, yup, put a mark in the Curiosity column.
Cristóbal Valenzuela, CEO of Runway, on the pixel economy: “Today’s pixel economy is built on scarcity. Expensive cameras, specialized software, teams of editors, render farms, distribution networks. Each step requires significant capital and expertise. This scarcity creates value, but it also creates barriers. In this world, creators are those who master the systems. AI media generation is collapsing these barriers entirely. The value of creating pixels is trending towards zero. When anyone can generate any visuals with no specialized software or equipment, the economics flip.” That is already interesting, because I don’t know too much about film and media production, but, of course it’s about more than just media, isn’t it: “My current bet is that roughly half of major public software companies won’t survive the next five years, because of this blue line trap. And I’m not alone in this sentiment. Where we are going, you don’t have to learn an interface. The interface will adapt to your needs. The pixel economy is moving from “learn our tools” to “just tell us what you want.””
Another serve in the very long ping pong game of “is it the phones or is it not the phones?”: “Increases in girls’ and boys’ social media use from year 8 to year 9 and from year 9 to year 10 had zero detrimental impact on their mental health the following year, the authors found. More time spent gaming also had a zero negative effect on pupils’ mental health.”
This is the greatest thing that has happened to streaming in a long time.
“AI handles the optimized stuff now. Better than we ever could. It finds patterns, maximizes output, eliminates waste. What it can’t do is be genuinely stupid. Being genuinely stupid might be the last human superpower. It can’t have the random collision that changes everything. AI raises the baseline. Randomness becomes the edge.” I’m starting to think that it’s the sum of our individual, unique experiences that’ll be of value in the future.
How to Choose Colors for Your CLI Applications. More posts like this!
Anthropic: “In a randomized controlled trial, we examined 1) how quickly software developers picked up a new skill (in this case, a Python library) with and without AI assistance; and 2) whether using AI made them less likely to understand the code they’d just written. We found that using AI assistance led to a statistically significant decrease in mastery. On a quiz that covered concepts they’d used just a few minutes before, participants in the AI group scored 17% lower than those who coded by hand, or the equivalent of nearly two letter grades. Using AI sped up the task slightly, but this didn’t reach the threshold of statistical significance.
Importantly, using AI assistance didn’t guarantee a lower score. How someone used AI influenced how much information they retained.” I’m not sure whether this says all that much. You could’ve made a study ten years ago to reveal that the “study finds that programmers who use libraries don’t know exactly how they work.” I found this to be an interesting comment.
A website into which you can “login forever”: loginwave. This is my worst nightmare. If I were to keep this page open for five minutes, my heart rate would make my watch call an ambulance.
ISOCOASTER. I haven’t played this, at all, I just bought some food stands. So, let’s meet at the beautiful, beautiful nacho stand that I put right next to the beautiful, beautiful burger stand and sit in the shade.
