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After a two-year absence from running a digital publication, namely Minimalissimo, I’m returning with a new project. Just when I thought I was out... Okay, no Pacino impressions. I definitely needed that break from curation and probably also from the constraints of minimalism for that matter. Over the past few years I’ve focused a lot on making digital tools and the odd experimental physical object. The latter still interests me hugely, and I’m casually working on a design for FFF, which I’ll cover in greater detail another time. Yet I became pretty disillusioned with the former: digital tooling in the age of AI. The sheer pace of development, replicas, slop, and hype just killed my enthusiasm for building. And I thought, “What do I actually enjoy doing?” The short and simple answer to that was “curation”. The longer and more complex answer is building a respectable publication that features journalistic deep dives, meaningful conversations, and tasteful curation. All presented and exhibited in a way that makes you appreciate the web experience over any social media feed or RSS reader. My new project is called MOUTHPRINT, which I’m building with my cofounder George Kroustallis, aka Minorstep. Together, our approach is to look closely at visual culture across art, fashion, and product design, tracing the people, processes, and choices behind the work. We’ll be publishing case files, which might sound a bit odd, but what the hell. These will examine individual projects through research and conversations with the people behind them. Ultimately, it’s about acknowledging and recording the many people who contributed to these projects and helped shape them. Alongside that, we’ll be publishing exhibitions that bring works together around a theme, making connections across disciplines and time. I’m under no illusions about how difficult it is to build a publication from the ground up. We’re totally up against it, but the web is a big place, we’re locked in, and we want to be heard. I’d now like to invite you to subscribe to our newsletter for the latest developments ahead of our official launch. We’d love to have you along for the ride. → mouthprint.com
Never did I imagine myself getting into running, especially as a middle-aged man. It always seemed a bit boring to me. Cycling is what I thought I‘d inevitably venture into, especially because I love watching that sport. But here I am, roped in by a couple of friends, fully embracing the running trend. Well, kind of. I have zero aspirations to run a marathon, or even a half for that matter. But I’m thoroughly enjoying doing short stints a couple of times a week, ranging from 5k to 8k, with a goal of consistently running 10k. Why? First and foremost for my health and cardio fitness, but also because I‘ve signed up for a 10k charity run in October that I’m determined to complete in under an hour. It was actually late last year that I first got a bit of the so-called runner’s high. I went on a 3-week remote work trip to the beautiful island of Lanzarote, which is filled with volcanic landscapes. Well, it turns out circling some of those under the sun makes for great trail runs, which I discovered over the course of that trip. And it was a lot of fun, if not a challenging way to introduce my body to running. Anyway, I’m returning to Lanzarote for another 3-week trip in November, and I intend to pick up where I left off, but hopefully in much better cardio condition. If you want to follow my progress, you can find me on Strava. Experimenting with a running photo aesthetic P.S. You’ll never catch me on a treadmill. It’s outdoors in the fresh air, invariably battling a Scottish headwind, or nothing. P.P.S. I still much prefer rock climbing to running as a form of exercise, so you’ll still find me bouldering on plastic or real rock a couple of times a week.
At the risk of sounding melodramatic, it feels like the end of an era. Or at least the end of the familiar formula that indie businesses relied on to build, launch, and grow over the past decade. Something has quietly changed. It’s probably been happening for a couple of years, to be fair. But recently it feels impossible to ignore. The reasons are pretty obvious. What’s less obvious is what comes next. And maybe every generation of builders feels like this. The tools available today have probably never been better, although I‘m also wading through plenty of sewer shit. We’re building software and shipping feature updates at an absurd pace, and at a much lower development cost, at least in the short term. Yet unless you’ve managed to build an audience, every product launch these days feels harder than it used to. Not because a product necessarily lacks quality or value in its own right, but because we’re drowning in software. You either have a million competitors, or your potential customers now have the tools to build a rough version themselves, whether they have technical skills or not. SaaS is far from dead, but the abundance is staggering. And the old assumptions around product roadmaps, paid advertising, and organic discovery no longer feel reliable. We can now build more refined products with fewer resources. But each improvement to a product seems to have less influence on whether anyone discovers or buys it. I’ve been feeling this most directly through 099 SPLY. We started by making digital assets and mockups for designers. More recently, we built a browser-based 3D editor that lets people create still and animated product mockups without specialist software. It‘s comfortably one of the most capable things we’ve made. But the editor has also been one of the hardest things to get people to care about. I knew it was a risk, though. Browser-based mockups are very niche, but it‘s an experiment I have zero regrets about. Maybe the positioning is wrong. Maybe we simply haven’t found the right audience. It‘s tough to know. But I also don’t think our experience is unusual. Plenty of small teams are now discovering that being able to build something is no longer much of an advantage in itself. Cutting through the noise has always mattered. It just feels much more pertinent now. For years, SEO offered some kind of safety net. You could publish a useful product, write about it, optimise content, and gradually find an audience through search. It was never easy and it tested your patience, but there was at least a recognisable path. But search today is dog shit. Results are crowded with ads, aggregators, AI summaries, and content written primarily to occupy space. An increasing number of searches end without anyone clicking through to an external site, and taken to their logical extreme, they point towards what some call “Google Zero”. There’s a label for everything, isn‘t there? Then we have social media, which tends to favour founders who are comfortable performing in public, have the time to publish constantly, or already have enough attention to generate more of it. The product can start to feel secondary to the content wrapped around it. Each release needs its own miniature marketing campaign, and even then the response can disappear within a day. But I also respect the grind and energy some founders put into making that work. Distribution has always required effort. So where does that leave indie hackers? Honestly, I’m not sure. I don’t think the answer is to stop making software, and I certainly don’t think small digital businesses are finished. But relying on the same combination of product quality, SEO, launch platforms, and occasional social posts feels increasingly naive. Maybe the next phase is less about finding another universal playbook and more about building in ways that are harder to replicate or make interchangeable. Or maybe it‘s about building a stronger rapport between founder and customer. I’m trying to think more experimentally myself, with less attachment to any particular format. And more willingness to test strange ideas, abandon weak ones, and follow whatever appears to have genuine energy around it. None of that makes the current landscape less frustrating. But if your launches feel quieter, your growth has stalled, or a project that once looked promising is beginning to decline, I doubt you’re alone. It might not mean the work is bad. It likely means the conditions around it have changed. For the time being, I‘ll keep listening, learning, and adapting. Maybe I‘ll even start a YouTube channel or something. If any of this resonates, feel free to continue the discussion over email or DMs with me.
I've worked with Photoshop for an age. Back in 2022, I created a small business called 099, offering a focused collection of minimal PSD mockups and web tools for creatives. Although I still appreciate the demand for PSDs, especially among seasoned designers, I wanted to explore a different way of generating mockups: directly in the browser, without subscriptions, licences, or heavyweight software. Because I feel a newer generation of creatives expects tools to be fast, focused, and accessible. Focused browser-based tooling has been gaining momentum across the digital design industry, even if it still sits in a comparative niche. But that doesn’t make it any less worth leaning into. And that’s exactly what we’ve done with the new version of 099.supply. the new 099.supply site using the MacBook Pro 3D model We’ve built a 3D mockup editor around a simple pay-as-you-go model, with enough customisability to be useful and enough restraint to avoid becoming something it’s not. At the same time, we’ve kept our PSDs available. That’s the point of 099 now: two modes of making, side by side. PSDs for those who want control, familiarity, and layered files. Browser exports for those who want speed, simplicity, and a finished mockup in seconds. This all might feel like a stepping stone before everyone is exclusively using AI to build mockups and web components, but not everyone is comfortable with moving at the same pace. Nor should they be. For now, I want to see where this goes. So, I invite you to try the tool. You can export for free, or pay a small one-off fee for higher-quality output, including 5-second animated mockups. Are the editor features sufficient? What feels missing? Is the pricing fair? Please get in touch and share your feedback. the 099 editor in action, customising the cap model
It recently dawned on me that, as a digital designer, I had yet to make a macOS or iOS app. So I wanted to give the former a try while also experimenting with a coding agent to bring it to life. While it’s easy to feel overwhelmed by the constant stream of AI tools and announcements, I think it’s enough to explore a couple properly and find your own way through the noise. Keeping up with the industry is one thing. Feeling pressured to try every new tool is another. Anyway, for this project, my agent of choice was Codex. It felt like the logical option given my existing subscription to ChatGPT. So I ran with it, and it didn't disappoint. I vibed, nay, context engineered my way to a beautiful little Mac app in just a week. Local Log is a minimal open-source journaling app that lets you record both text and video entries in one quiet, focused space, with everything stored locally on your Mac for privacy and simplicity. No accounts, no cloud dependency, no clutter — just a clean archive of your thoughts, searchable and always yours. With autosave, editable entry titles, keyboard shortcuts, and light and dark mode support, Local Log is designed to stay out of the way so you can get straight to logging. Local Log app icon in dark mode Why a journaling app? I’ve always loved the notion of blogging and thinking in public, but there’s always been a layer of restraint to it. I wanted to create a digital space where you can be unapologetically honest with yourself. A private space to recalibrate, reflect, and reset. Where each entry becomes a small record of your mind that you can revisit whenever you like. The design was inspired by the irreplaceable iA Writer and the open-source app Freewrite, which gave me the idea of adding vlogs. The typeface felt important to me, and I had no desire to offer multiple choices to the user. I made a decision and I stuck with it. And that font was Geist Mono by Vercel. And a shoutout to Manu for the clever app icon, which mirrors the UI itself. You can view the GitHub repo and download directly for free. Local Log app icon in light mode Default screen in light mode Entry example in dark mode Entry example with collapsed sidebar Select actions in the entry archive
More in life
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. ↩
I always liked stories about eccentric royals doing mad things. Queen Christina of Sweden reportedly had a miniature cannon made for firing tiny cannonballs at fleas in her bedroom. Louis XIV made a proto-reality-show of his daily routines, allowing an audience of courtiers the honor of watching him dress, bathe, and use the toilet. Peter the Great famously returned from […]
The (Re)insurance AI Landscape
to become the version of yourself needed in the next chapter
