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The Llama Book

from Rubenerd [alt+shift+b] in life

There are certain books within technical communities where even an indirect reference (a pointer, you could say) will conjure wonderful memories of first learning to program in anyone who hears it (these are distinct from Clojure memories). The Pickaxe Book. K&R. Chunky Bacon. You don’t need to mention the title, the year of release, the full name of the writers, the publisher, or anything else about it for people to know exactly what you’re talking about. So integral are they to the success of a language (or framework, or operating system), that it’s impossible to think of their subject matter without thinking of the book itself. They may have helped to popularise it, or introduced an entire generation to it. Oftentimes they’re written by the people who designed the language (or had a say in its development), which offers additional insight and wisdom into why as much as how. Remembering your “first” programming book is a deeply personal experience. A pile of paper and ink was the way so many of us learned to program. At the risk of getting philosophical, they helped to demystify this metal and silicon that ran other people’s ideas, into ones that ran our own. I can’t speak for everyone, but computers took on a whole new life when they were doing things that I had programmed them to do. It still feels a bit like magic, even now. (This experience of personal growth and learning from an expert are more ideas upon which gen-“AI” takes a massive shit. If you disagree, I hope your own soul searching bears fruit one day. But I digress). I quoted Eskild Hustvedt in November talking about his joy rediscovering Perl, and shared his memory of the same book that transformed my life and way of thinking, emphasis added: It’s not the same language I learned from the llama many years ago. It has improved immensely, while never losing any of the things that made it great in the first place. A few of you emailed and direct messaged to correct Eskild and I, because the seminal tome...
2nd Dec 2025

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Hey, I’m back! I want to go to Jersey

I was knocked out hard by something this week. It wasn’t a flu or COVID thankfully, but it turned my head to mush and my sinuses into fire ants, which among other things made sleep all but impossible. I did in fact do a bunch of work on the blog yesterday, but it was all backend plumbing stuff. It is interesting how different parts of the brain work, and how it recovers at different speeds? I tend to find my ability to write code (at least of the rote, boiler-plate kind) and tinker at a server console requires very different attention to writing. While I felt I was capable of doing the former yesterday (and even found it fun), I stared at the blinking cursor to write a post, and nothing happened. Brains! The highlight was getting confused when Vim inserted a tab into a YAML file, and an Ansible playbook wouldn’t fire. It’s trivial for me to spot now, but it genuinely stymied me on Wednesday. Anyway! My voice still sounds like Phoebe from that episode of Friends when she discovered she liked the timbre the illness gave her singing voice. That’s a 1990s reference! But I’ll take it :). Unrelated entirely to the reboot of which I only just discovered, but Clara and I are in a massive Bergerac obsession currently, which was also lovely to watch while recovering. It’s worth its own post, but who would have known a British TV series from 1980 would make us want to go to Jersey. We’ll tack it on after Warsaw, Riga, Lviv, and Cork! By Ruben Schade in Sydney, 2026-04-04.

3rd Apr 2026 • 1 votes
A pair of satisfying things

The Sound of Music and Tony Bennett might have been eager to sing about their favourite things. I’d like to start Monday by sharing with you two satisfying things. First, this long black coffee I’m drinking at a coffee shop now is lovely. It was a light roast with just the right amount of crema. I also love how the colour of the cup and saucer looks against the rustic woodgrain table at this coffee shop. On the theme of colour, I’d also like to share this satisfying stack of face towels we bought yesterday. They’re so perfectly interleaved, and both the colours and their ordering just tickle me. It almost seems a shame to use these; I almost want to keep them as they are. That concludes this post regarding a pair of satisfying things. Thank you. By Ruben Schade in Sydney, 2026-03-02.

1st Mar 2026 • 2 votes
Australia needs a Mark Carney speech

I finally got around to watching Canadian Prime Minister Mark Carney’s Davos speech from January. Wow. This shouldn’t need to be said in the context of a politician, but I don’t agree with everything he said. For one, I thought his attempt to rebrand the curtailing of environmental protections as “improving interstate commerce” was a tad crass. Here comes the proverbial posterior prognostication: but… I do agree with the broad thrust (heavens) of his comments. We are living in a post-US world, and those of us living outside America need to be honest and come to terms with it. It resonated especially in Australia and New Zealand, because we’ve yet to hear anything said with such clarity and candour from our leaders outside the small parties. And because, truthfully, we see a lot of ourselves when we look at Canada. Australia and Canada are both federal parliamentary democracies with British colonial history, governors general, prime ministers, state premiers, and territories. We share a monarch, mostly the same language, sensible temperature scales, universal(ish) healthcare, and even our exports and GDPs look similar. We’re big countries with similarly small populations that have become cosmopolitan melting pots, most of which are clustered around a few large cities. We even have rubbish intercity trains! We also, for better or worse, spent much of the twentieth and twenty-first centuries hitching our economic and military security to that of the United States. We share intelligence, we host military bases, we buy their military equipment, and as Mark Carney pointed out, we’ve pretended it’s been a mutually-beneficial arrangement. If or where that was true, it no longer is. The US is now, once again, chaired by a dim orange gas bag who thinks (well, “thinks”) he’s above the law, and might equals right. I’ve watched and read the same media claiming he may have dementia, or some other mental health issue that explains why he can’t form cohesive sentences or keep his attention for more than a few minutes. While it might be interesting in an academic sense, the outcome is the same as someone malicious. This is compounded by the incompetent US institutions that are supposed to act as a check and balance against an overzealous executive. For the rest of us, there are two outcomes: Being allied with the US is now, nakedly, a political liability. It threatens to make us look, in the words of the former Malaysian prime minister, “America’s sheriff” in the Pacific, if it hasn’t already. Placation is a losing strategy. Bullies and arseholes understand one thing: dripping sarcasm. Wait no, I meant to say pushback. The Australian Government need to drink some stiff maple syrup, stand before a camera, and say Mark Carney had a point. Maybe if enough of us tell that dipstick, he and his cackling cadre of sycophants will get the message. The current Australian administration have already done a decent job repairing our standing among our Pacific neighbours, but far more needs to be done. We need to build alliances around the world, so we’re not fighting this individually. In other words, we need to do what the rest of the world have already been doing for years. Also, an EU-style Australia/New Zealand/Canada agreement, let’s make it happen. We could call it CAN! The names for the bills in our respective parliaments write themselves. Canada can teach us how to curl and play hockey, and we can teach them how to make coffee and pavlova. We all win! Corrections: An earlier version of this post referred to the current US executive as a bloated “gasbag”. Technically this should be two words. I apologise for this over sight. Wait. By Ruben Schade in Sydney, 2026-02-02.

2nd Feb 2026 • 1 votes
Still (ab)using spreadsheets as a KB, for now?

Forgive the Betteridge headline, but it’s because this is a personal thought process I’m still going through myself. As opposed to a personal thought process I’m going through for someone else!? That doesn’t make sense. Welcome to 2026! The shop next door is playing a Carpenters album, which is awesome. Rest in peace Karen, you were a legend. Spreadsheets Last year was a bit of a wash for me when it came to personal productivity, but I flipped the narrative hard in December. Maybe it was the festive air, or the fewer distractions doing office shutdown, but I made (a) an admission about how I work, and (2) doubled down on something I started a few years ago. Back in May of 2023, I wrote about how I use spreadsheets as a knowledgebase and mental mapping tool. I showed a basic example of tracking parts for various old computer builds using basic project identifiers, AutoFilters, frozen rows, and a bit of colour in LibreOffice: This is awesome! It’s a wide-open matrix of unrestrained goodness that I can filter and use to track and find exactly what I need. Here comes the proverbial posterior prognostication: but… You should want to use something else Despite using this for tracking certain home projects, I had still convinced myself that important things should be in their own proper task management system. By “proper”, I mean one of the multitude of tools with icons containing a tick or checkbox of some sort that promise “enterprise” features on their home page. We use one of those “proper” tools at work for tracking tasks across teams, so I should use that at home too, right? But here’s the (unremarkable) thing: I don’t like them. You could say I detest them. Each of them come imbued with the philosophies and decisions of the designers that don’t ever align with how my mind works. It would make my life easier if I used the one tool for work and home, but in the words of Australian moral philosophers: yeah, nah. I went the plain text route for years which somewhat worked, and I’ve tried to shoehorn my personal life into one of these larger task tracking tools. Thunderbird with Reminders synced to my mail provider has come the closest to working, but it hasn’t been quite right. Namely, assigning tasks to certain categories (such as finance, home, or hobbies) is doable with a few different hacks, but they’re all a bit clunky. It’s too… 2D. Back to spreadsheets But then something clicked for me in a widely-used online spreadsheet: they have checkboxes. LibreOffice has boolean values, but an honest to goodness inline checkbox!? Right there in a column? I’m embarrassed to admit how much this changed my life. I’ve added them to an online spreadsheet, and overnight I feel like a changed person. I now have a huge workbook with spreadsheet tabs for all the things. Grocery lists, one-off tasks, larger projects, life goals, decisions, measurements, travel packing checklists, manga to read, stuff to fix, network notes, the list goes on. Just like that screenshot above in LibreOffice, I have tasks outlined in a sheet, only with a big, glorious checkbox at the start. Then I can filter out tasks that have been completed, or use conditional formatting to recolour them a pleasing green for that sweet, sweet dopamine. And best of all? It’s all in the one place. Using an online spreadsheet also solved the syncing issue, because turns out I like capturing information on the go as well. Or should I say, I need to. My brain will remember that I need to measure our wardrobe for a new shelf while I’m at the local Japanese supermarket getting bonito flakes, which makes absolutely no sense. Thanks brain, that’s the exact kind of actionable information I need right when I’m doing something else! This has even subsumed some of the stuff I had previously allocated to my local personal Postgres database too, which I’m perhaps more ashamed to admit. But maybe only temporarily? Next steps from here I was a very strange child. I learned how to write a BASIC program before I grokked tying shoelaces, and didn’t see an issue with it. I also enjoyed tinkering with personal database tools over games the majority of the time. Before Access took over and was left to rot on the vine there were dozens of them. FileMaker was awesome. Delphi! dBase! The old FoxPro! Fuck computers used to be so cool before we coalesced on the few massive providers who then enshittified everything. Remember Bento?! As I said in that earlier linked spreadsheet post, I think in matrices. These lend themselves effortlessly to spreadsheets, but I also think they could work in a proper database structure as well. Then my task management could benefit from all the goodies databases provide, like proper views and triggers. I thought I’d take a stab at writing my own little GUI program to do this, because while the databases themselves are robust and capable, the linchpin to a tool like this is rapid and easy entry. If it’s not easy and malleable, I’ll get frustrated and stop using it. I reached for Perl, but I’ve since decided to take a stab at it in Go given how enamoured I’ve become with it last year. Baby steps, but I’m hoping 2026 will be the year I get more organised with a tool that works exactly as my brain does :). Who knows, maybe someone else might like using it too. By Ruben Schade in Sydney, 2026-01-01.

1st Jan 2026 • 1 votes

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Scattered thoughts on how doing math feels these days

This is a weird moment. I have a hunch that we’ll look back later and tell ourselves stories in which it seemed obvious where things were going. So I wanted to lay down a little time capsule and register just how confusing everything felt at the time. This is a personal view from the trenches. 1. If you’re a normal person, you may feel that AI has been good at math for a long time.1 But for “real” math, this is roughly what it felt like: When Feeling 2024 LLMs are toys Summer 2025 LLMs are interesting toys Early Autumn 2025 LLMs can do useful stuff sometimes Mid Autumn 2025 …a lot of stuff Late Autumn 2025 …a lot Early 2026 holy god Even having been astonished by AI progress in the past, it was still astonishing to see AI move in a matter of months from a mildly-useful toy to something that many people now consider almost impossible to do without. 2. Personally, I’d say that current AI makes me around 50% more productive at “doing math”. That’s despite the fact that AI can now often do in a few minutes things that would have taken me hours to do myself. The main reason is that my concept of “doing math” involves various steps, like coming up with ideas for theorems, trying to prove them, writing things down, reorganizing everything to make it more clear, and so on. AI is good at some parts of this, but still pretty bad at others, so the overall speedup isn’t as high as you might expect. (Even if planes could go 10× faster, your door-to-door travel time from your apartment in London to your friend’s place in Rome wouldn’t decrease that much, because you still have to get to the airport and wait to board.) 3. But then, I’m still (sort of; more on this later) trying to follow my old “doing math” workflow, just automating certain parts of it. That can’t be right, can it? If we found a way to make batteries at 1% of the current cost, we wouldn’t just say, “cool, batteries are cheap now”. We’d find all sorts of new ways to use batteries that didn’t make sense before, and change the ways we generate power to account for all these new batteries. Probably our whole energy system would end up transformed. Analogously, AI being good at proofs should lead to a very different equilibrium. But what is that?2 4. It seems healthy, at the moment, to maintain a fluid view of what “doing math” means. But at bare minimum it surely involves understanding the math that “I” am “doing”. So long as that’s part of the workflow, it would seem to impose a limit on how quickly “I” could “do” math, no matter how good AI is. One obvious conclusion would be that my tiny organic brain should be removed from the workflow entirely. Maybe! But it’s interesting to speculate about how much faster things could go while still keeping a human brain in the loop. I think the answer is: A lot. 5. Contrary to what you may have heard, humans are not obsolete for math. Not yet. The most obvious reason is that AI is still bad at writing. People often complain that AI writing overuses various patterns or lacks a unique voice or whatever. I don’t disagree, but I always felt like there was a deeper issue that I couldn’t quite put my finger on. With math, this becomes very clear: The problem is it doesn’t make any goddamned sense. Really, I think it’s deeper than being bad “at writing”. It seems like AI is bad at thinking in certain ways that manifest as bad writing. 6. When novices do math, they often create “spaghetti-code math”: Imagine a long document with lots of equations, but if you point at any one equation, it’s hard to say what assumptions underpin it, or how it fits into the bigger picture. Any random idea that was mentioned 17 pages ago might be used again at any time with no warning. With experience, people learn to break complex arguments down into modular pieces with a good “API”, in the sense that the assumptions and conclusions for each part are relatively simple. Somehow, AI has developed these amazing technical skills, while still being bad at creating abstractions So the arguments it gives are long and tangled and bewildering. This is what makes AI math seem so alien. 7. Now I know what you’re thinking. Maybe AI isn’t bad at creating abstractions. It’s just bad at creating abstractions that work for you, human with tiny organic brain. From a distance, that seems plausible. And it might be true to some degree. I have high-bandwidth access to a human brain. It’s not crazy to imagine that this gives me an advantage in predicting how a human brain would react to a given presentation of ideas. But still, I claim that current AI is objectively bad at creating abstractions, regardless of if the consumer of those abstractions is human or artificial. Here’s why: If I ask AI to prove something hard, it will produce a proof that starts simple and gradually descends into a rampage of complexity. If I tell it to break that proof down into self-contained pieces, it will produce lemmas that each take a full page just to state. If I ask, “Why? Why have you done this to me?”, the AI will say, “This is as simple as it gets. It’s not that bad. What’s your problem?” But if I argue with the AI for a while, I can start to understand the basic contours of the argument. And I’ll ask, “Why don’t you first just try to prove blah using only assumptions blahblah, without worrying about blahblahblah? Wouldn’t that be easier?” Often, this doesn’t work, either because my idea was bad, or because the AI isn’t smart enough to do it. (Which one? Who knows!) But after a few attempts, I can usually find something that that works, and the AI can use it to re-write the proof in a somewhat simpler way. If I repeat this many times, I can gradually chip away at the complexity. But maybe that’s still just making the proof easier for humans to understand? No! For one, this usually makes the proof shorter, and sometimes dramatically shorter. More importantly, during this process, someone (maybe me, maybe the AI) will often realize that there’s a different proof strategy that gives a stronger result. Instead of proving x < 9.7, now we can prove x < 7.1. Thus, artisanal human abstractions are “objectively” useful. 8. Some people might claim that it’s already possible to automate some of what I’m doing with some multi-agent Rube Goldberg thing. I’m not sure, because my experience has been that investing lots of time into clever AGENTS.MD or custom skills or harnesses isn’t a great use of time. That stuff is somewhat helpful, but things are changing so fast that the knowledge has a short half-life. Also, the majority of information about these tricks seems to come from people who are excited about the technology itself. On the other hand, the automator told me to try typing, “ask independent agents for an adversarial review”, and I’ve found those seven words to be quite helpful. I wish I could find a source with boring best practices for people who are happy to stay away from the bleeding edge. 9. Another reason AI doesn’t improve my productivity more is that it is often the green light, the orgastic future that recedes before me. I’ll ask AI to do something, and it will almost seem to do it. So I’ll ask for changes, and it seems to help, but it’s still not quite right. Hours later, I’ve accomplished nothing and learned nothing. Eventually, I start over, either doing it myself or with AI on a very tight leash, and I’m done in 30 minutes. Each time this happens I feel foolish and tell myself not to do it again. But it’s very hard to judge in real-time. 10. Of course, I’m not claiming that AI is intrinsically bad at writing or thinking or abstraction-making. It’s gotten better at all of these and I expect it will continue to do so. All I’m saying is that as of Autumn 2026, humans still have a lot to contribute, and it’s not just better exposition. 11. Did AI actually get much better at math in Autumn 2025? Or perhaps, in the grand scheme of things, human math ability falls into a narrow range? 12. Some people are responding to the new reality by gleefully using AI to generate lots of semi-OK-ish papers and puking them up on arXiv. I understand the incentives that drive this. In some sense, it seems like the logical response to the new reality. (After inventing cars, we started taking a lot more low-value trips.) But I don’t think this is socially useful, and I tend to think everyone will soon agree that this is embarrassing. But… I’m not sure. Maybe it is socially useful? And I find myself feeling vaguely jealous of the people who are wired this way, who instead of feeling blinkered, see opportunity and plunder. 13. Want an optimistic pro-AI, pro-progress take? OK. If I take my old “doing math” workflow, AI makes it strictly better. A lot better. It’s like having a hyper-conscientious intern that is smarter than me in many ways, works at incredible speed, and knows approximately everything. Yes, AI sucks at writing and making abstractions. But if I’m disciplined and try to mostly do the math “myself” while asking the AI for help, I can explore ideas much faster than before, make far fewer mistakes, and produce something just as clear as before, while developing just as much understanding. I can ask, “What happens if you do a Kofuni expansion?”, and get an answer instantly. I can ask for illustrations or interactive visualizations and see them instantly. Arguably, we’re incredibly lucky to be alive at this moment, when these new tools have opened up this new territory to explore. 14. And isn’t that what I wanted? Back in 2024, I bemoaned that what AI most seemed to struggle with was getting the facts straight: Perhaps the old science fiction robots were a projection of our fantasies. I want my style and voice to be precious and uncopyable. I want an AI assistant that will tirelessly hunt down facts while I provide creativity and panache and magic. But that’s not how it is. So we should remember: In a scenario where AI is useful but humans retain some comparative advantage, we might not like where that comparative advantage lies. At least with math, and at least for the moment, I get to be Kirk, while the AI is Spock. (Even with other types of writing, my impression is that since 2024, AI has improved more along Spock dimensions than along Kirk dimensions.) So that’s nice. 15. In the last few months, it frequently happens that a collaborator will use AI to generate something, and then send it to me and ask me to check if it’s useful. I can see why this seems reasonable. (Really, I do.) But when it happens a lot, one can’t help but wonder what the point of the human collaborator is. 16. On the other hand—with creative writing, my advice is not to use AI to write, at all. Ask questions if you want, but write every damned word yourself.3 With math, I don’t feel like such a hard line makes sense. It seems that creating something good still requires a lot of human involvement, to the point of agonizing over notation, repeatedly re-organizing things, and heavily editing individual sentences. Still, I find that if people make that effort, they can create something just as good as they could by hand, while still being perhaps 50% AI written.4 So I don’t mind if people send me “centaur math”, provided they take responsibility for the contents. The problem is that when working with AI, it takes constant paranoid vigilance to avoid letting things slip beyond your understanding. I often find myself wanting to awkwardly ask people, “OK, you obviously used AI to make this… which is OK… but how much of this do you vouch for? If we have a meeting to discuss it, will you crumble the moment I start asking questions?” 17. When I’m in abstraction-creation mode, I feel like I’m doing something intelligent. When yell at AI about bad notation and writing, I feel like I’m providing taste. But I often find myself giving feedback that seems incredibly basic. Things like: This is a mess, clean it up. Or: Do you need that assumption? Or: If you can’t solve this problem, why don’t you create a simpler version and try to solve it first? On the one hand, I guess a lot of what good human managers do amounts to giving very basic feedback. On the other hand, it’s hard to imagine that I have much durable advantage in doing this kind of thing. So I wonder how much durable advantage I have in abstraction-making or taste, too. 18. A common reaction to AI getting better at proofs is that humans need to focus more on exposition. This has an obvious Bourdieu-esque criticism: Human painters used to strongly value photo-realism, but after cameras were invented they convinced everyone that, oops, photo-realism isn’t important, what matters is expression, which coincidentally cameras can do. Isn’t a shift towards exposition in math just a way for humans to move the goalposts and justify their own continued relevance? The only credible way I see to avoid that criticism seems to be to bite the bullet and say that, in fact, math should have already have focused more on exposition, even before AI. Personally, I strongly believe that this is true. 19. I think the biggest reason I’m not more productive is: What’s the point? In the past, if you came up with an elegant proof, you’d tell yourself, “I made a thing! Other people will read and use my thing! I am advancing human progress.” You can still tell yourself that now. But you have to wonder, will anyone actually read your proof? Or will they just ask another AI to explain it to them? Will your proof help their AI explain it better? For how long? If you just waited a year, would some other AI produce that same proof independently? Alternatively, if you’re a normal person, you might think that LLMs still struggle with basic arithmetic? ↩ AI progress is so fast, compared to society’s ability to adjust, that we may never actually see what “the current equilibrium” looks like. ↩ This essay, if you’re wondering, was created by writing every damned word myself and not asking AI anything. ↩ You could have a whole debate about what that precentage means. It’s not the number of words written by AI that really matters, in my opinion, so much as who is responsible for the overall structure of the ideas. ↩

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