Hardware
The iPhone’s Last Stand
Listen to this post : Apple fans would, for years and years, sneer at Microsoft’s penchant for talking about products that may or may not ship, deriding them as vaporware. After Apple’s bungled 2024 launch of Apple Intelligence and new Siri , however, vaporware is fair game, and just in time for this Article. Last week, at its annual Build developer conference, Microsoft put forth a vision for a new ecosystem of hardware devices under the banner of Project Solara : The concept — which isn’t entirely clear from that video, but was more fully explained on stage — is that in the future you will be surrounded by an ecosystem of devices, none of which stand alone, but are more like portals to interact with your agents, which live in the cloud. In other words, as I wrote in February, Thin Is In : This is even clearer when you consider the next big wave of AI: agents. The point of an agent is not to use the computer for you; it’s to accomplish a specific task. Everything between the request and the result, at least in theory, should be invisible to the user. This is the concept of a thin client taken to the absolute extreme: it’s not just that you don’t need any local compute to get an answer from a chatbot; you don’t need any local compute to accomplish real work. The AI on the server does it all. I made the case in that Article that server-side inference would dominate AI workloads, thanks in particular to increasingly high memory demands for agents. What I found intriguing about Microsoft’s vaporware, however, is that it showcased a use case wherein this thin client approach was compelling for reasons beyond KV cache. Specifically, for most of tech history computing has been indistinguishable from interacting ; that’s why we place so much value on new input methods, as they often set off new paradigm shifts. By the same token, the problem with wearables as the paradigm beyond the iPhone is that interacting with them generally sucks. Sure, you can imagine a future where voice interaction is completely seamless or where a device can “see” what you see, but anything longer than a few seconds is much less convenient than simply swiping on your phone. Agents, however, compute on your behalf, without any interaction necessary: a few seconds is all you need to get work done for hours — at least in theory. Apple, a company that can actually make devices, was under heavy scrutiny going into yesterday’s WWDC keynote for a different concern: can the company make AI? And, if your standards are the state of the art in AI circa June 2024, when Apple took their first crack at answering the question, they did quite well. The company’s pre-recorded keynote took great pains to show actual demos — spinning indicators and all — and they worked! Here was the first one of what Apple is calling “Siri AI”: What’s fascinating about this specific demo is that it also showed just how far behind Apple is. New head of Siri Mike Rockwell successfully used Siri to set a reminder to enter a lottery for concert tickets, demonstrating context awareness and the ability to interact with the Reminders app through Apple’s App Intents framework; what would have been state of the art would have been asking Siri to enter the lottery on his behalf when the time came. In other words, to act outside of the interaction paradigm that has traditionally defined computing, and which Apple has dominated. At the same time, the fact that Apple is behind the state of the art might not matter that much given Apple’s market and opportunity in that market. To start with the former, Apple is targeting consumers, for whom traditional chatbot functionality is probably sufficient for the vast majority of their AI needs. Siri will be able to give you recipes, tips on do-it-yourself projects, or generate images. Moreover, the fact that Siri will have access to your iPhone gives it all of the same advantages that made me optimistic about Apple Intelligence in the first place. From an Update after that initial June 2024 launch : The key part here is the “understanding personal context” bit: Apple Intelligence will know more about you than any other AI, because your phone knows more about you than any other device (and knows what you are looking at whenever you invoke Apple Intelligence); this, by extension, explains why the infrastructure and privacy parts are so important. What this means is that Apple Intelligence is by-and-large focused on specific use cases where that knowledge is useful; that means the problem space that Apple Intelligence is trying to solve is constrained and grounded — both figuratively and literally — in areas where it is much less likely that the AI screws up. In other words, Apple is addressing a space that is very useful, that only they can address, and which also happens to be “safe” in terms of reputation risk. Honestly, it almost seems unfair — or, to put it another way, it speaks to what a massive advantage there is for a trusted platform. Apple gets to solve real problems in meaningful ways with low risk, and that’s exactly what they are doing. Apple actually made this version of Siri much more capable in terms of accessing world knowledge and image generation, which should make the experience much more seamless, but the real differentiation will clearly be that access to your personal information. You can ask Siri about something you received in messages — or was it email, or a voicemail? — and it will actually find what you’re looking for; it can also “see” what you are looking at on your screen, and act on the information. And, to the extent that third-party apps offer up their data to the Spotlight semantic index, and make actions available via App Intents, Siri can actually operate across different services in a way other AIs can not, at least without making massive sacrifices in security on a local Mac or PC. These capabilities are genuinely useful, and there’s a good chance they’re enough, at least for now, and that’s because there is another aspect of the consumer market that is worth considering — beyond the fact that billions of consumers already have iPhones. Specifically, consumers don’t want to work, and don’t really care about being productive. This reality about the consumer market is a lesson that Silicon Valley has to re-learn every decade or so. Consider Dropbox, whose founder, Drew Houston, is in the process of stepping down . Dropbox was a category-defining product that had a viral hook — if someone signed up with your referral code, you got more storage — and grew extremely fast amongst consumers; the company then spent too long trying to actually build a business in the consumer space, before finally realizing that the only way to make money with what was ultimately a productivity product was by selling to enterprise. The reason is obvious when you think about it: enterprises are paying for their employees’ time, so of course they are willing to pay for tools that make those employees more productive; consumers, on the other hand, are mostly looking to waste time, which is why attention-harvesting advertising is the only software business model that works at scale for consumer services. The fact that Silicon Valley forgets this is downstream from Silicon Valley being a bubble; normal people aren’t looking for agents to buy them tickets to a concert. Still, the bubble was strong enough to convince OpenAI to make the exact same mistake Dropbox did: the company somehow convinced itself that it could make enough money selling subscriptions to consumers; Anthropic, meanwhile, realized that it was enterprises who were willing to pay for AI’s massive productivity benefits, even as OpenAI failed to capitalize on their consumer market penetration by refusing to build an advertising product . This is a long-winded way of saying that I don’t think that Apple’s agentic shortcomings are a big deal, at least for now. Agents help you do work and be more productive, and consumers don’t want to work or care about being productive. What they do want to do is watch short-form video, and an iPhone is simply much better at that than any other device ever will be; in that context, Siri being good enough is enough, and it appears that Apple crossed that bar. There are actually a lot of interesting technical details about how Apple rebuilt Siri, including expanding Private Cloud Compute to include Nvidia chips running in Google data centers, as well as a 20 billion parameter on-device mixture-of-experts model that selects the expert on a per-query basis (as opposed to on a per-token basis) so that it can run in an iPhone’s limited memory. The key strategic takeaway of these implementation details, however, is the centrality of the iPhone. Microsoft’s Project Solara obviously makes sense for Microsoft given the fact that the company missed out on mobile, but it also fits with the infrastructure of AI, which is in the cloud, and increasingly about compute happening without a human in the loop. Apple, in contrast, is heavily incentivized to preserve the iPhone’s importance, and by extension, to focus on use cases organized around human interaction. However, it’s too simplistic to reduce these approaches to a cynical analysis of incentives; both make sense in their own right. What makes me intrigued about Project Solara is the fact that Microsoft is positioning it as purely an enterprise play, which is important because an enterprise has context about the work being done, making it more viable to build long-running agents — which the enterprise is willing to pay for. That context would be far more difficult to build for consumers, given the need to tie together a huge number of services to get a coherent set of data over which to operate. Indeed, the only entities that can probably pull that off are Google and Apple via Android and iOS, respectively — and Google is always going to be focused more on its cloud services as the point of integration instead of the device. That leaves Apple as the only company truly — dare I say it? — thinking differently. And yes, the iPhone as the true core of Siri (which will work across your devices, but get its differentiated context first-and-foremost from your iPhone) just so happens to perfectly align with Apple’s business model and desire to not spend billions in capex, but that doesn’t mean it’s the wrong approach. You’ll be able to access all of that capex that other companies are building on your phone, you’ll just have to use an app; if you need to find something personal, or work across apps, Siri will be the only one who can pull it off — as long as it’s not vaporware (and it appears the second time is the charm).
AI
Cloud
Giving your Go apps Tigris superpowers
Tigris is S3-compatible, which means you can point the AWS SDK at it and most things just work. The catch is that the Tigris-exclusive features—bucket forking, snapshots, object renaming, and the like—need verbose workarounds because the AWS SDK doesn't know they exist. So we wrote a Go SDK that does. It comes in two flavors: the package is a drop-in replacement for the standard S3 client with first-class methods for the Tigris-specific operations, and is a higher-level client for the common single-bucket case that infers its configuration from the environment so you stop passing the same parameters over and over. You can adopt the Tigris features incrementally without refactoring your existing S3 code, and the simpler API still works against other S3-compatible providers. I wrote up how it works and why we built it over on the Tigris blog.
API
Programming
the beach episode
Whenever I descend into a mental health episode (often, but not always, triggered by cycle-related hormonal changes), there’s very specific signs both my wife and I pick up on. She usually notices it earlier than me, though. The pattern is always the same: Because it is all so repetitive (been happening for over a decade) and well-known to me by now, I see it for what it is and it doesn’t actually cause any harm, as I do not end up even close to making these drastic decisions. I am still in control. At worst, I used to unfriend people or exit groups, but even that has stopped. I wouldn’t say my opinions snd obsessions during that time have no leg to stand on; I have a high standard for what my apartment is supposed to look like, and it’s not always up to par. I really wanna switch jobs, move, or change some blog design things some time. But how I feel about it is dramatically amplified, and introducing a very unfitting level of urgency, life-or-death panic about it all. It almost feels like it’s taking a similar pathway to a phase of hyperfocus, but in a cursed way. It also feels like seeking validation and good feelings/a feeling of control from changing things or cleaning, which would make sense for my brain to wanna do when I feel depressed. Like it’s searching for anything that could help. Since some people might be wondering: It doesn’t fulfill the criteria for mania. My anxiety just gets elevated, and my brain decides to handle it in a weird way. I don’t feel happy or energized. Since it is hormonal, I imagine it is related to what some pregnant people go through with their sensitivity to their surroundings. As this is a largely offline thing, I can usually isolate it well and not say a peep about it happening online. I hope I don’t seem weirdly different in my blog posts during it, I genuinely can’t tell. I’m actually going through it again right now, since last week. Dienogest (hormone medication for this mood stuff, PMOD and endometriosis) bought me a while of stability when I tried it from March to mid of May, and I appreciate that; it showed me how often it happened and how bad it really was. I stopped taking it since then because it caused some excessive bleeding, but am restarting it now after a doctor’s appointment today. It’s not all bad. The things I am so inappropriately upset about are true/exist, it’s just my reaction that is a problem. I can harness the sense of urgency and tackle these issues in a constructive way and get things done that I have put off for too long. For example, the sneakers I wear the most have been falling apart so much that walking in them causes blisters and chafing and stuff to poke me while walking. Still, I kept procrastinating on buying new ones. Today, after a particularly exhausting morning in this mental health episode, I bought two new pairs of shoes and was able to discard the broken ones. I also lost my mind about the clutter so much that I ended up discussing new shelf units with my wife, who kindly measured everything out and had good ideas, so we ended up ordering some together and will pick them up tomorrow. It wasn’t a compulsive purchase I’d regret for something I don’t actually need, but instead, I used my tumultuous emotions to finally tackle the issue of needing to use my space more efficiently now, and the decision was made deliberately over the span of a couple hours. I need more storage for more hobbies I acquired over the last years, and things my wife keeps here that don’t yet have their own proper spot. The way things are right now was supposed to be a temporary state until we can move somewhere bigger, but I’ve accepted that this could take years, so I wanna invest into making it comfortable now. In the near future, I also wanna have more storage in the kitchen and bathroom, finally donate the clothes I decided to get rid of, and tidy up the basement. I also felt equally compelled to switch email providers and get 98% of account/newsletter email switching done, updated all saved passwords, and removed saved passwords for accounts that no longer exist. I’m happy that I was able to use my struggle for good today. I still hate everything else about it, and that it’s so uncomfortable and stressful in my head right now, but at least I got that. Can’t wait until I’m stabilized again. Reply via email Published 08 Jun, 2026 Issues falling asleep, feeling inexplicably sad and without energy, not finding joy in anything I usually like, or possibly sleeping almost all day. Getting up the next morning with a very, very low tolerance for clutter, or even owning anything more than bare necessities. Being extremely sensitive to dirt, smells, messes, crumbs and so on. The entire living space and my body starts to feel contaminated. This causing me to spiral and feeling overwhelmed, ranting about how the apartment is hopeless, that I wish I could just leave it or burn it down, that I wanna sell everything, what needs to be done etc. I start cleaning and tidying up for hours in a really tense way, maybe even decluttering, if I can manage and am not frozen in overwhelm. If you step in at that moment to tell me it isn’t even that bad or that I should keep whatever I wanna throw out in that moment, my laser eyes will turn you into dust (I wish). Everything feels very urgent, like I need to do it now or else something really bad will happen; as if I will lose control and this is the last moment to turn it around. Being able to do nothing to alleviate the situation makes me feel sick. My thoughts race and I am stuck in a loop. I’m coping with fantasizing about drastic decisions: Emigrating to a different country, quitting my job, booking a trip on a whim, suicide, selling everything, rearranging my apartment, ending relationships or friendships, deleting accounts, redesigning my entire website and blog from scratch, exiting groups, and so on.
Entertainment
Writing
Culture
“I’ve lost entire sentences of text to this incompetent implementation.”
John Gruber at Daring Fireball talks about a problem in SwiftUI-based macOS and iOS apps where undo is completely broken during text editing : Basic stuff that’s worked reliably for decades — some things that heretofore had worked forever — are dangerously broken. If you’re running MacOS 26 Tahoe, open Journal and make a new dummy entry. Type something like “The quick brown fox.” Then double-click on the word “brown” and delete it. Now invoke Undo. What you expect is for the word “brown” to reappear. What happens is ... the whole sentence disappears . Gone. Invoke Redo and you only get back to “The quick fox.” The word “brown” is just gone forever. It’s nowhere in the Undo stack. That’s just profoundly fucked up. I couldn’t believe it, but I reproduced it myself just now on my phone (my backup Tahoe-running Mac is in a closet not responding to pings, I am now assuming out of embarrassment): Gruber adds: Apple’s developer message used to be that it was not just easy to develop apps for their platforms, but that it was easy to develop good idiomatically native apps. You got the correct complex behavior — for things like Undo/Redo — out of the box. That’s still true for AppKit and UIKit, but it’s never been true for SwiftUI, and SwiftUI is now seven years old . That’s too long for any excuses to hold water. I don’t want to automatically assume that this problem has existed for seven years (vs. being a more recent deterioration), and I don’t know exactly which native apps use SwiftUI, but either way, this reflects very poorly on Apple. Software engineering typically has some categories of bugs and failures that result in immediate action – a night shift, a war room, “sevs,” and so on. Those are, in my experience, things like: Depending on what you work on, this list will also likely include security problems, regulatory considerations, privacy-leaking bugs, and so on. In a more mature organization, these are all well documented, but even in early startups there is some shared understanding that some bugs are bigger than life and they take immense priority over pretty much anything else. At any company, a version of this list needs to exist for front-end and user-experience problems, and undo problems should be on top of that list. If you break undo, you drop what you’re doing to fix it . #apple #process #undo the app crashes, the site doesn’t load, there is data loss.
iOS
Swift
Test Coverage Won't Save You
Forestwalk’s CTO Jenn Cooper shares what she’s been learning about tests , after a couple years of increasingly coding with agents: Most discussions about AI-native development jump from this problem – agents’ tendency to accumulate tech debt – directly to tests. … Tests verify that code does what it did before. Whether what it did was even the right way to do it is a separate question. She argues that while agents make it easy to have rigorous traditional test coverage, at best unit tests maintain local code cohesion. At worst, they can actually make it harder to improve what agents are worst at: the wider coherence of the entire codebase. So far I’ve been impressed with how effective the broader automated checks she describes can be to guard against agentic nonsense.
Testing
ppclp.ai announces 100x Productivity Gains
ppclp.ai, North America's third-largest AI-native manufacturer of premium wire-formed office fasteners, formerly known as Paper Clip Company, announced a landmark 100x improvement in its proprietary Organizational Productivity Index (OPI™), cementing what leadership is calling "a new era of operational excellence" and "a little bit of a miracle." The breakthrough follows an 18-month company-wide initiative called Project Streamline, during which all 340 employees completed mandatory efficiency training, adopted a new Jira-based workflow system powered by Rovo, and attended a two-day offsite in Scottsdale where a consultant named Derek asked everyone to "think about how they think about work." "I used to open fourteen browser tabs and just stare at them. Now I open fourteen browser tabs, and AI agents are looking at them for me. I've never felt more in control." — Sandra K., Senior Clip Assembly Coordinator, 11 years at ppclp.ai Central to the transformation is Rovo, Atlassian's AI, which the ppclp.ai Jira Center of Excellence team has deeply integrated into the company's ticket lifecycle. Rovo now autonomously opens tickets when it detects workflow friction, assigns them to the appropriate team, and, in what the Center of Excellence calls "the closed-loop moment", it closes them upon determining that sufficient time has passed. Ticket velocity has increased by 340% as a result. "Rovo doesn't wait for humans to decide a problem is solved," explained the Head of Delivery Operations, in a blog post titled We Taught Our Tickets to Heal Themselves. "It senses resolution. It acts. And then it documents the action in a follow-up ticket, which it also closes." The OPI™, aggregating over 200 signals including ticket velocity, standup attendance, emoji reaction latency in Slack, and what the methodology document calls "ambient focus energy," now shows a number in the top-right corner of the dashboard that is very large and going up. The dashboard itself, prominently themed in dark mode (naturally), required six months to build and is, by all accounts, extremely beautiful. "We are incredibly proud of this number," said CEO Bob Realman in a statement prepared by the communications team and reviewed by legal. "It represents the dedication, the hustle, and the genuine passion of every single person at ppclp.ai. And of Rovo, who we consider an honorary team member and who closed 1,400 tickets last Tuesday alone." When asked by a reporter at the earnings call whether the 100x productivity improvement had resulted in a corresponding increase in paperclip output, CFO Melissa Tran paused, smiled warmly, and said the question "reflected a pre-transformation mindset." She then advanced to the next slide, which was a photo of the team at the Scottsdale offsite. "Volume is a very legacy way of thinking about a fastener business. We've moved beyond units. We're measuring what matters: Agentic motion." — Bob Realman, current and former CEO, ppclp.ai The company did acknowledge, in a footnote on page 34 of the supplemental earnings materials, that paperclip production had declined approximately 20% year-over-year. The footnote attributed this to "macroeconomic headwinds, a challenging staple-adjacent market, and notable seasonality in Q2 clip demand," adding that the trend was "well within the range of normal paperclip seasonality" and "expected to self-correct, eventually." Analysts who requested a definition of "paperclip seasonality" were directed to a separate FAQ document that had not yet been written. A Rovo ticket to write it was opened and closed the same afternoon. ppclp.ai says it expects the OPI™ to continue improving through the end of the fiscal year. They are already exploring an OPI™ 2.0, an open source model that will incorporate biometric data, walking pace between meetings, and what the roadmap calls a "vibe coefficient." Production guidance was not provided, but the company noted that the dashboard remains, in their words, "extremely actionable," and that Rovo has already opened a ticket about it. OPI™ was developed in collaboration with Proxy Ai™ . ProxyAi, so you don't have to. About ppclp.ai: ppclp.ai has manufactured precision wire-formed fasteners since 1987, and rebranded as an AI-native company in 2024. The company serves offices, government agencies, and one very loyal stationery shop in Duluth. ppclp.ai employs 340 humans and Rovo, and is headquartered in a building with a lot of glass. More information is available at a website that is currently being redesigned by an agent. Forward-looking statements contained herein involve risks and uncertainties, including but not limited to: continued ambiguity about what productivity means, the possibility that Rovo opens a ticket about this press release and then closes it, and the risk that someone in finance eventually opens a spreadsheet unassisted. OPI™ is a trademark of ppclp.ai. "Seasonality" is used here in the broadest possible sense. Rovo is a product of Atlassian and is referenced here with the full confidence that it would autonomously resolve any objections. Past dashboard performance is not indicative of future paperclip output.
Business
An open letter to office suite users, just before the Euro-Office announcement
by The Document Foundation The Document Foundation shares its history to rebuke claims made by Euro-Office about being Europe's first open-source office suite. They argue that by hiding its code provenance and defaulting to Microsoft's proprietary format, Euro-Office actually undermines European digital sovereignty rather than supporting it. Read post ➡ All this post does is make The Document Foundation sound petty and butthurt, especially this part: Euro-Office defaults to the fully proprietary OOXML document format, developed and controlled solely by Microsoft. This makes it a de facto ally of Microsoft in its content lock-in strategy, with control remaining firmly in Redmond and far from Europe. Saying that Euro-Office are an ally of Microsoft is a bit of a stretch. I assume they defaulted to MS format because that's what 99.9999% of the world uses, like it or not. If Euro-Office are going to be successful, they need to be compatible with MS out of the box. That's just a fact. Maybe that's why LibreOffice has never been able to eat Microsoft's lunch? I dunno. But this isn't a good look for TDF in my opinion. Sometimes it's just better to say nothing, yanno? Thanks for reading this post via RSS. RSS is ace, and so are you. ❤️ You can reply to this post by email , or leave a comment .
Open Source
Media
changed email address!
Just letting you know that my email address has changed from @pm.me to @tuta.com . The change is reflected in the footer and post template already. I don't know what I will do about the 400+ old posts that have the old email address attached yet; email forwarding has been set, but it will apparently run out next year as my subscription to Proton lapses. Currently in the process of exporting and importing mails, transferring files, and changing newsletters and accounts to use the new email address(es). I respect what Proton is trying to accomplish with their product suite, yet I feel like they are spread too thin, releasing unpolished product after unpolished product, and not putting enough effort into adequately supporting what they already have. On top of that, their questionable approach to politics as well as their recent sponsorship of a far-right French YouTuber was the final nail in the coffin for me. Their responses about this matter didn't cut it for me, as they evade the actual problem and responsibility. Personal politics (and the fact that I don't want my money to go benefit people who want to take away our rights) aside: If you lose sight of who you are sponsoring and where your money goes, and you cannot even clearly tell your customers what you have changed so that will not happen again, that is mismanagement I can't ignore. Reply via email Published 08 Jun, 2026
Fitness challenge underway
A few weeks ago, I was at my brother’s place, watching NBA, and amongst other things, I was teasing him about the fact that he’s putting up weight. Which is just a fact. But he’s also in his 40s, so that’s understandable. He pointed out that I’m also gaining weight (but I’m not in my 40s), and since it was a long time since I weighed myself, I decided to hop on a scale, and the number that came out was 89.6kg. Now, I’m 190cm tall, so being almost 90kgs isn’t really a tragedy but I told him «I’m gonna get back into shape» just so that I can keep continue teasing him and he won’t be able to say shit back. Isn’t brotherly love wonderful? I gave myself the “extended” whole summer (so till the end of September) to reach two goals. The first goal is to be lighter than I was 10 years ago. I had a smart scale for more than a decade, and the oldest measurement I have logged is 85.3kg, recorded on December 21st 2015. So I need to be below that by September 30th. The second goal is to be in better shape than I was 10 years ago. Now, this is a bit harder to quantify, but I’ll let my brother determine if I reached this goal or not. I did take a “before” picture at the beginning of June. It’s my intention to take an “after” one on September 30th, and we’ll compare and see if I made any progress whatsoever. Do I have a concrete plan for how to achieve these two goals? Absolutely not. Do I have a personal trainer guiding me through a training program? Hell no. Am I following a diet prepared by a nutritionist? Nah, what’s the fun in doing that! We’re in the “vibe” era, so I’m gonna vibe training and vibe dieting, meaning I’m doing things my way, trying random shit, going for silly walks, training however I want, and having fun in the process. Gonna be a fun summer. And since we’re talking losing weight, I’m gonna mention two of my blogging pals here, one mr Kev and one mr Luigi , both of whom are going through a similar challenge (for more sane and normal reasons, unlike myself, who is fueled by spite). I believe in you guys! Thank you for keeping RSS alive. You're awesome. Email me :: Sign my guestbook :: Support for 1$/month :: See my generous supporters :: Subscribe to People and Blogs
Sports
Bureaucracy is Eating the World
Disclaimer: This is an opinion piece. It is also a long one, because the subject is too tangled to compress without losing the thread. I have tried to look at the matter from different perspectives and include the strongest counter-arguments where I saw them. As this write-up had been in the works for a very long time, some of the referenced data isn’t the absolute latest data available today, which however does not impact the underlying message. As usual, summary at the end. A few weeks ago I sat down with a friend who, after twenty years in a steady job, had decided to start a small business in the European Union. Nothing exotic, just a one-person operation, selling a thing they had been making in their spare time for years and that other people kept asking to buy. By the time we were done, we had identified the trade register filing, the tax office registration, a separate VAT registration with its own threshold rules, the obligation to issue invoices in a specific format, the e-invoicing mandate, the beneficial-ownership disclosure under the EU’s AML regime, the bank’s own KYC questionnaire, the data-protection obligations under GDPR even though the operation collected practically no personal data, the CE marking requirements, the extended-producer-responsibility packaging registration, the WEEE registration, the social-security contributions for self-employed individuals, the mandatory professional liability insurance for the relevant guild, and the local trade-tax filing. None of these are illegitimate and most of them, taken in isolation, sound reasonable. Together, however, they constitute a mountain that my friend, who is a competent adult with a real product, was now expected to climb before they sold the first unit. That is when it occurred to me that the story I had been telling myself for years, that it has always been like this and every generation thinks the system is rigged , might not actually be true, and this post is the result of that thought. I want to walk through roughly three and a half centuries of how easy or hard it has been, in the western world, to simply do something economically. From the period when an Englishman with a ship and a bond could legally attack Spanish merchants for a living, through the early 1900s when an entrepreneur could incorporate a company on four pages, to the present, when the same kind of operation requires a stack of filings most people will never finish reading. I am going to argue that we have drifted, slowly and with the best intentions, into a regulatory state where the friction of doing anything new is high enough that the people best positioned to absorb it are no longer the small operators that once founded the today’s behemoth companies. I want to be clear up front that I am not writing a “libertarian manifesto” . There are regulations I am glad exist, including most of the worker-safety, environmental, and consumer-protection regimes that the post-war west put in place. The argument is narrower than abolish the rules , and it is roughly that the cumulative weight of three centuries of mostly well-intentioned rule-making (almost none of which was ever repealed, btw) has reached a point where it disproportionately punishes the small and rewards the large. That, I think, is a problem regardless of where you sit politically. Let me repeat: This post is not about political ideology and I urge you to read it as apolitical as humanly possible and focus on the real-world implications rather than some abstract political ideas. Also: While I’m no historian, I tried my best to investigate and find reliable information, which I linked where necessary. Anyhow, let me start with one of my favorite periods to dwell on, which is the time … Of course, we’re talking about the era historians loosely refer to as the Golden Age of Piracy (roughly 1650 to 1730). Back then, the relationship between private business and the state in the Atlantic world was so different from ours that it can feel almost like science fiction. If you were an English merchant in 1690, and you wanted to make money by attacking Spanish (or French) shipping, you did not have to do it in secret. You could go to the Lord High Admiral , or one of the Commissioners acting on his behalf, and apply for what was called a letter of marque . The application named your vessel, its tonnage, its armaments, the owner, and the intended crew. You posted a bond promising to observe the laws and treaties of England, and you got, in return, a piece of paper that legalised an activity that, without the paper, would have made you a pirate . The captures were later judged in admiralty courts, the Crown took a percentage (usually 10%, though Queen Anne later waived even that tiny bit of tax as an incentive ) and you kept the rest. This was not an obscure backwater of business, but in fact an arrangement that some of the most celebrated figures in English history operated under. Sir Francis Drake , whose 1577–80 circumnavigation predates the Golden Age proper but established the template, gave investors a return on capital that contemporary sources placed in the order of forty-seven pounds for every pound invested , with Elizabeth I ’s share alone reportedly enough to retire the Crown ’s debt. The exact figures are deliberately obscured in the surviving records ( Elizabeth had diplomatic reasons not to be specific), but I don’t think any historian disputes that the venture was extraordinarily profitable, and that it was funded by something close to a venture-capital syndicate of nobles and merchants. A century later, in 1695, William Kidd received a privateering commission from the Admiralty Commissioners , plus a special commission under the Great Seal , to seize French ships and pirates. His subsequent hanging in 1701, however, was less about the business model than about the fact that he attacked the wrong ships. Whoops , I guess. Note: It wasn’t only privateering that was comparatively easy to establish and run. In one of my favorite books, Moby-Dick , Herman Melville roughly describes how the economics of whale hunting worked at the time. The capital for the endeavour came from the town. A vessel like the Pequod had a couple of principal owners, the retired Captains Peleg and Bildad in the novel, but the rest of the ship was parcelled out among ordinary Nantucket citizens, a crowd of old annuitants; widows, fatherless children, and chancery wards , each one owning the value of a timber head, or a foot of plank, or a nail or two in the hull . A widow could put her late husband’s savings into a sliver of a whaler the way one might today buy a few shares of an index fund, and when the ship came home three years later heavy with oil, she retrieved her portion of the proceeds, minus the owners’ cut for fitting her out. The crew, meanwhile, drew no wages at all. Every man from the captain down to the greenest hand was paid in what was called a lay , a fixed fraction of the voyage’s total net profit, the size of the fraction set by his skill and rank. The smaller the number, the larger the slice, so a seasoned harpooner like Queequeg was signed at the ninetieth lay, while Ishmael , who had never so much as touched a whale, was first offered the seven-hundred-and-seventy-seventh by the pious and tight-fisted Bildad before Peleg talked it up to the three-hundredth. Nobody was paid for showing up, you were paid, if at all, only when the casks were full and sold, which meant every soul aboard owned a piece of the outcome and bore a piece of the risk, no payroll department required. This was not merely a novelist’s imagination, but it was how the real Nantucket and New Bedford fisheries actually worked. Ships were financed by pooling fractional shares among the townsfolk, every hand from captain to greenhorn took a lay instead of a wage, and historians today describe the whole arrangement as a precursor to modern venture capital, obviously with significantly less bureaucracy involved. Looking at the possible growth and power, the chartered companies of the same era operated on a scale that no modern private corporation could legally match. The English East India Company , chartered by Elizabeth I on the last day of 1600, was eventually granted the right to acquire territory, mint coinage, command fortresses and standing troops, form alliances with foreign powers, make war and peace, and exercise civil and criminal jurisdiction over its holdings. The Dutch East India Company ( VOC ) , chartered in 1602, went further and was given an explicit twenty-one-year monopoly, the right to wage war, sign treaties with sovereign powers, build forts, appoint governors, and mint its own coins. At its peak the VOC employed roughly twenty-three thousand people in Asia, fielded somewhere between one hundred and fifty and two hundred and fifty ships at any one time, kept a standing army of around ten thousand soldiers, and over its life sent close to a million Europeans to Asia on nearly five thousand ships. The Hudson’s Bay Company , chartered by Charles II on May 2, 1670, was granted absolute Lords and Proprietors status over Rupert’s Land , an area of roughly 3.9 million square kilometres, or about 40% of modern Canada, again with monopoly trade rights, lawmaking, civil and military jurisdiction, and the authority to wage war. For the ordinary merchant, who was neither a Drake nor a director of the VOC , the bureaucratic environment was correspondingly easy to navigate. There was no income tax, since Britain’s first income tax was a Napoleonic-era invention from 1799 , and there was no business registration in the modern sense. There was no payroll tax, no compliance officer, no insurance mandate, no occupational licensing, and certainly no equivalent of GDPR or beneficial-ownership reporting. The state extracted revenue mostly through customs and excise on specific goods, the Land Tax on real property, the Hearth Tax from 1662 to 1689 (two shillings per fireplace), and the Window Tax from 1696 onwards. In the American colonies in particular, enforcement of even the limited Navigation Acts was famously weak under what historians call salutary neglect , to the point that the Hoover Institution notes colonists in the late seventeenth century killed three customs officers, imprisoned two others, tried one for treason, and persuaded one to join them . That’s a level of “customs compliance” that would definitely not pass a modern audit. :-) Note: Of course there is a romanticised version of this period that isn’t as rosy as it first seems. For example, within chartered English boroughs (London especially), domestic trade was seemingly gated by guilds and the Freedom of the City . The 1562 Statute of Artificers required a seven-year apprenticeship for most trades, which was apparently the only national apprenticeship law in pre-modern Europe, and admission fees in the 16th and 17th centuries ranged from under one pound to twelve pounds and more, which was a substantial sum at the time. Guild monopolies were seemingly a real form of bureaucracy, just not a state-run one. So the open a shop with no paperwork framing is more accurate for rural England, the frontier American colonies, and overseas trading ventures than for established urban commerce. It was the commercial ventures specifically (the ships, the colonies, the trading expeditions) that operated with the kind of low-friction freedom we no longer have, not the neighbourhood bakery in seventeenth-century London, although that bureaucracy was still well below what we are facing in today’s world. The point I want to draw from this period is not that we should bring back privateering or massive chartered companies that can wage wars , which would be both impractical and politically unattractive, but that the basic relationship between private enterprise and the state was, at least for novel ventures, permissive by default . You could simply go ahead , and the state involved itself only when you crossed a specific line that had been drawn in advance. Yet, despite the lack of all modern bureaucracy, regulation and compliance, civilization evolved and societies developed, maybe at times even at a faster pace than we’re seeing it today. Skip forward two and a half centuries, and the world is unrecognisable in almost every way except that starting and running a business is still extraordinarily light on paperwork, even by modern standards. In 1896, New Jersey passed the first enabling general incorporation statute, allowing a company to be formed by simple administrative filing rather than by a special act of the legislature. Delaware followed on March 10, 1899 , and the modern American corporation was born. Before then, every incorporation in the United States required its own legislative act, but after it, you just mailed a form , figuratively speaking. The cleanest illustration of how thin that paperwork was is the document that incorporated the Ford Motor Company on June 16, 1903 . Henry Ford and twelve co-investors signed a four-page Articles of Association in Detroit . The document covered the name of the corporation, its purpose, its place of operation, its capital stock ($28,000), its term, and its stockholders. It was notarised, mailed to the Michigan Secretary of State , and the company was legally constituted by June 17, 1903. The same Ford Motor Company would go on, over the next four decades, to produce the Model T , build the Highland Park assembly line, employ tens of thousands of workers, and become one of the largest industrial enterprises on the planet, all without anyone needing to file beneficial-ownership disclosures, complete a Customer Due Diligence questionnaire, or commission a Data Protection Impact Assessment . The tax environment was also correspondingly simple. The 16th Amendment to the U.S. Constitution was ratified in 1913, and the Revenue Act of 1913 introduced a federal income tax with a 1% normal tax on net income above $3,000 (single) or $4,000 (married), with a graduated surtax topping out at 7% on income above $500,000. Approximately 3% of the U.S. population was even subject to the tax, and under 1% paid anything at all. In Britain, income tax averaged 2% to 3% of GDP from 1900 through 1913, and the super-tax , the precursor to surtax, was only introduced in Lloyd George ’s 1909 People’s Budget . Value-added tax, the workhorse of modern European public finance, did not exist anywhere in the world until Maurice Lauré’s reform was signed into French law on April 10, 1954, and was not mandated EEC-wide until two directives in April 1967. Note: If these are too many numbers and dates and words and you only want to remember one single thing from this chapter, then remember the following: Taxes, as we know them today, did not exist around a hundred years ago, and many of them only go as far back as ~70 years. It is also worth noting that even the way taxes were collected was different. Tax withholding at source, the now-ubiquitous mechanism by which your employer hands a slice of your salary to the state before you ever see it, was introduced in the United States only in 1943 with the Current Tax Payment Act , as a wartime measure to fund the war effort and to broaden the tax base from the wealthy to ordinary workers. Before 1943, Americans calculated their taxes annually and wrote a cheque, which is why tax-day filing was, for most of history, a relatively low-frequency interaction between citizen and state. Many EU member states introduced their withholding tax regimes only between 1952 and 2013. The withholding mechanism is, in many ways, the backbone of the modern administrative state. It works only because there is a persistent identity attached to every worker, a bank account they are paid into, and a payroll system that can route the deductions automatically. Banking, in the same period, was also fairly accessible. There was no formal Know Your Customer regime in the sense we now use it. The Bank Secrecy Act , which is the foundation of the modern American anti-money-laundering regime, was passed in 1970. KYC as a structured set of rules was not codified federally until the U.S.A. PATRIOT Act of 2001 introduced the Customer Identification Program under Section 326 . The Foreign Account Tax Compliance Act ( FATCA ) , which today shapes the experience of Americans abroad and the willingness of foreign banks to serve them at all, was only enacted in March 2010. If you were a working person in 1920 and you wanted a bank account, you walked into a bank, gave your name and address, signed a card, and received an account. There was no requirement to hand over a utility bill, to document the source of your funds, no electronic identity verification, no sanctions screening, and no algorithmic suspicious activity detection. De-banking , in the modern sense of having a financial institution close your account because of who you are or what you do, was not really a phenomenon at all in the early twentieth century. The Oxford English Dictionary records the verb debank as far back as 1929 , but the meaning that contemporary readers will recognise is essentially post-2014. This matters because the people who built the post-war economy did so in exactly this environment. The men and women of the GI Generation (born roughly 1901–1927), the Silent Generation (1928–1945), and the Baby Boomers (1946–1964) came of professional age in a regime where you could open a bank account in an afternoon, file a four-page incorporation document, hire and fire on a handshake, pay relatively low effective taxes, and grow a business through several decades without anyone asking for a beneficial-ownership statement, a tax-residency certificate, a data-protection impact assessment, or a sustainability report. This is not a moral observation about that generation, it is an observation about the environment they built businesses in. Before I move on to what changed, I want to take one short detour east, because it is the cleanest case I know of how much the regulatory environment can matter to outcomes. In 1953, at the end of the Korean War , South Korea had a GDP per capita of roughly sixty-seven U.S. dollars, which made it one of the poorest countries in the world , poorer than most of sub-Saharan Africa and on a par with Haiti. Seoul, its capital, had a population of about one million people and had been substantially flattened during the war. The country had no significant industrial base, no natural resources to speak of, and no obvious path forward. Seventy years later, South Korea’s GDP per capita is roughly thirty-three thousand dollars, the Seoul Capital Area is home to roughly twenty-five million people, and the country is a global leader in shipbuilding, steel, electronics, automobiles, semiconductors, and increasingly cultural exports. This is one of the most extraordinary economic transformations in recorded history. The popular story of Korea being a free-market miracle, however, is half right at best. The serious academic literature, particularly Alice Amsden’s Asia’s Next Giant and Robert Wade’s Governing the Market , makes clear that the Park Chung-hee regime (1961–1979) was an authoritarian developmental state , not a libertarian paradise. It directed credit, picked sectors, suppressed labour, and tolerated heavy chaebol concentration. What the regime did not do, however, was load new ventures with the kind of compliance and regulatory machinery that the modern OECD economies were already accumulating. New industries could be built quickly, factories could be thrown up, ports expanded, ships launched, because the bureaucratic overhead was thin and the political will to remove obstacles was high. I am definitely not holding Park -era Korea up as a model, as the political costs were severe. What I am pointing at is how fast a country can transform when the regulatory friction on building things is set close to zero. It is much, much faster than people who have only experienced modern OECD economies typically realise. The generations that built the post-war west ( GI , Silent , Boomer , and to a lesser extent early Gen X ) accumulated (or inherited) their wealth in this lighter regulatory regime. The generations that came after (later Gen X , Millennials , Gen Z , …) are trying to do the same thing in an environment that has significantly changed under their feet. The U.S. Federal Reserve’s Distributional Financial Accounts are the authoritative source, that shows, that as of late 2024, Millennials and Gen Z together represented 35.1% of U.S. households but owned only 10.1% of total household wealth , roughly 71% less than their household-share would predict. By contrast, Boomers in 1989, at a roughly comparable average age, held 19.5% of wealth while making up 42.2% of households. In other words, younger Americans today are more under-represented in wealth than Boomers were at a comparable point in their lives. Pew Research similarly found that the median net worth of households headed by Millennials aged 20–35 in 2016 was roughly $12,500, compared with $20,700 for Boomers at the same age in 1983, in constant dollars. That is, the Millennial household had about 60% of the inflation-adjusted net worth that the Boomer household had at the same stage of life . Homeownership data tells the same story. Apartment List ’s analysis of homeownership rates at age 30 finds that 55% of Silents owned a home by that age, falling to 48% of Boomers , 42% of Gen X , and just 33% of Millennials . In the United Kingdom, the Office for National Statistics reports that in 2024 the median home in England (£290,000) cost roughly 7.7 times median full-time annual earnings (£37,600), and the Resolution Foundation has shown that it now takes a typical young first-time buyer roughly 18 to 19 years to save a deposit from disposable income, compared with about 3 years in the mid-1990s . The Joint Center for Housing Studies at Harvard reports that in 2022 the U.S. median home price reached 5.6 times median household income, the highest ratio on record going back to the early 1970s. Note: I want to recognize that the wealth-comparison story is more nuanced than the Millennials are screwed narrative that I’m partially presenting here. For example, the St. Louis Fed has also found that, on a per-household basis, Millennials and Gen Z have been catching up rapidly since 2019. Critics, including New America and others, point out that this relies on average rather than median wealth and is heavily skewed by a thin slice of high-earning younger households. Both stories are simultaneously true, depending on which slice of the distribution you look at. The median younger household is materially behind, the average younger household less so. I am framing the argument around the median because that, in my view, is the more relevant indicator of broad opportunity. In addition, the crises that bracketed Millennial , Gen Z and later generation’s lives were not randomly distributed across generations. Those generations experienced the post-9/11 wars in Iraq, Afghanistan, and the broader counterterrorism campaign , the 2008 Global Financial Crisis , the COVID-19 pandemic , the Ukraine war , and the recent war in Iran with all its economic impact slowly unfolding. The cost of these, in the form of debt, inflation, and asset-price inflation through quantitative easing , has fallen disproportionately on the people who were/are not yet old enough to own assets when these events occurred. In fact, the Bank of England ’s own analysis of the distributional effects of quantitative easing acknowledged that a large share of the wealth gains flowed to households that already owned assets, and a 2023 Oxford Bulletin paper found that the asset-price channel of QE increases wealth inequality across most countries studied. There is a counter-argument from central banks that the alternative (a deeper recession) would have hit younger workers even harder through unemployment, and I think this counter-argument is partially correct, but the cumulative effect, on top of the housing-supply story documented by Glaeser and Gyourko , is a generational asset-price gap that compounds. I’m trying to be careful not to slide into a Boomers caused this framing, because that doesn’t appear to be what the data ultimately says, despite everything visually pointing towards this narrative. Boomers themselves appear to be highly stratified, with the median Boomer being noticeably less wealthy than generational averages seemingly suggest. The Urban Institute ’s research on the Great Inequality Transfer emphasises that policy regimes, not generational malice, are the proximate cause. What is true, however, is that the policy choices of the past several decades, made disproportionately by people who were already established in the post-war environment, accumulated into a stack of rules, asset prices, and compliance requirements that the people coming up behind them now have to navigate. In that sense, the current environment can in fact be attributed to the decisions made by Boomers , as well as the generations in their immediate proximity. Which brings me to the actual point about how big that stack of rules has become, and what its distribution of cost is. The U.S. Code of Federal Regulations , which is the codified body of federal regulatory rules, was a thin pamphlet at its origin in 1938. It is now, depending on how you count, somewhere north of 190,000 pages . The Mercatus Center ’s RegData project, which counts regulatory restrictions defined as instances of words like shall , must , and may not , finds that the federal CFR contained roughly 835,000 such restrictions in 1997, rising to over 1.08 million by 2019 and continuing to climb. The Federal Register , which is the daily journal in which new federal rules are first published, totalled 9,562 pages in 1950 across 15 volumes, and hit 86,356 pages in 2020 , the second-highest count ever recorded. Meanwhile, the European acquis communautaire , the body of cumulative EU law, has followed a similar trajectory, with estimates of the active acquis range from an 80,000-page figure to over 170,000 pages, depending on how you count, with more than 100,000 of those pages produced in the prior decade alone . The cumulative legislation since 1957 is on the order of 666,879 pages. The cost of complying with all this is, as you might have guessed, not evenly distributed. The widely cited 2010 SBA Office of Advocacy study by Crain and Crain estimated that U.S. small firms with fewer than 20 employees paid about $10,585 per employee per year in regulatory compliance, compared to $7,755 for firms with more than 500 employees, which is roughly a 36% gap. A more recent 2023 National Association of Manufacturers study put the total federal regulatory cost at $3.079 trillion in 2022 (about 12% of GDP), with small manufacturers paying $50,100 per employee per year compared to $24,800 for large manufacturers , which is roughly a 100% gap. Note: The Crain and Crain methodology has been criticised by the Congressional Research Service and others as including economic-impact estimates rather than just direct compliance costs, and using a cross-country regression that some economists consider unreliable. The NAM is an industry association with an obvious incentive to report large numbers. However, even if we discount both estimates substantially, the basic shape (that smaller firms pay disproportionately more per employee to comply with the same rules) is consistent across studies and across methodologies. A fixed cost of compliance simply hits a smaller firm harder, in per-employee terms, than a larger one. A few specific recent regulations are worth naming, considering their (cost-)impact: I will stop the list there, but the pattern is clear, and adding DAC6 , DAC7 , the DSA , the DMA , the CSRD , the CSDDD , UKCA marking, REACH , MDR , IVDR and the rest does not improve the picture. Each of these has a defensible rationale, and most of them addressed a real problem, but the cumulative burden, however, is significant . Sadly, there is no agency anywhere whose job is to look at the total weight of regulation on a small business and ask whether it is still proportionate. However, there are agencies, in many jurisdictions, whose job is to add to it. Tax complexity has followed the same arc. The U.S. Internal Revenue Code runs to roughly 2.4 million words, or about 10 million if you include Treasury regulations and IRS guidance. Wolters Kluwer ’s Standard Federal Tax Reporter , the practitioner’s reference, has grown to roughly 80,000 pages from a thin volume in 1913. The U.K.’s Tolley’s tax handbooks have grown from about 5,000 pages in 1997 to over 21,000 pages in current editions. The IRS Taxpayer Advocate , who is statutorily independent of IRS political leadership, has reported that Americans spend roughly several billion hours per year complying with the federal tax code. Meanwhile, the OECD ’s tax-to-GDP statistics show that the average tax-to-GDP ratio across member countries rose significatnly from 1965 to 2022. For example, France went from ~33% to ~46%, Denmark from ~29% to ~42%, the U.K. from ~30% to ~35%, Germany from ~31% to ~38%, Spain from ~14% to ~36%, and the U.S. from ~23% to ~28%. In other words, across most of the developed world, the share of economic activity passing through tax authorities has grown by roughly a third over six decades, and the complexity of the path it takes through those authorities has grown by considerably more. The crucial point, for my argument, is not about whether taxes are too high in some absolute sense, or whether taxation as such is actual theft , as that is a separate political question on which reasonable people disagree, but the point is that the complexity has grown to the level where it is itself a significant input cost, and that cost is again non-linear. A small business that needs to interpret 80,000 pages of tax guidance has to either hire someone to do it, or do it themselves at the cost of not running their business for the time that it takes. A multinational has a tax department, and frequently has the resources to make the complexity work in its favour. Which brings me to the most important part of the picture, which concerns tax *cough* planning . The Institute on Taxation and Economic Policy documented in its 2021 study, that 55 of America’s largest corporations paid $0 in federal income tax on $40.5 billion of pre-tax income in 2020. A 2024 update found 109 large profitable U.S. corporations paid 0% federal income tax in at least one year between 2018 and 2022, with an average effective rate of about 14.1% against a statutory rate of 21%. A 2022 study from the U.S. Government Accountability Office on large profitable corporations found an average effective federal rate of about 9% over the period 2014 to 2018, well below the statutory rate of the time. The mechanisms by which large multinationals (and wealthy individuals) achieve these rates are well-documented, largely legal and, most importantly, only available to companies (and individuals) of equal size and accounting firepower , and definitely not to your mom-and-pop-shop next door. The Double Irish with a Dutch Sandwich , used by Google , Apple , Facebook and others, was estimated by economist Gabriel Zucman to have shifted more than $100 billion per year at peak. Ireland closed it in 2014 with a phase-out completed by 2020. The European Commission ruled in August 2016 that Apple owed €13.1 billion in back taxes to Ireland, and the Court of Justice of the European Union finally upheld this on September 10, 2024 in Commission v. Ireland (C-465/20), eight years after the original ruling. The Tax Justice Network ’s State of Tax Justice 2023 report estimates that countries collectively lose roughly $472 billion per year to tax abuse, of which about $311 billion is corporate. It’s worth mentioning that the TJN’s methodology is contested by the IMF and others, and that the figure should be treated as an upper bound, but even at half that figure, the disparity is striking. The OECD’s BEPS Pillar Two , the global minimum corporate tax of 15% beginning in 2024, is estimated to raise corporate income tax revenue by roughly $155 to $192 billion per year, but it does nothing for the structural disparity between a small business (or regular individuals) that cannot relocate its profits and a multinational (or wealthy individuals) that can and, on the contrary, is likely to introduce even more bureaucracy for small businesses in future iterations of the code. There are honest reasons the system has ended up where it has, including the difficulty of taxing economic activity that crosses borders, but the lived effect is that a self-employed plumber in Paris or a small bakery in Chicago pays a higher effective tax rate than Apple or Amazon does on income shifted through the right holding structure. There is one more thread that I want to pull on, because it has changed character significantly in the past decade and is, I think, undertreated in the broader conversation, which is the slow conversion of banks from financial-services providers into compliance gatekeepers. One (in)famous exampale for this is Operation Choke Point , a U.S. Department of Justice initiative running from 2013 to 2017, that pressured banks to drop high-risk merchants, including payday lenders, firearms dealers, and adult-industry workers. The program was officially terminated in August 2017 after the FDIC settled lawsuits and pledged to cease informal or unwritten suggestions to banks, but the label Operation Choke Point 2.0 has since been applied to alleged debanking of crypto firms after the March 2023 collapse of Silvergate , Signature Bank , and Silicon Valley Bank . However, the evidence for a coordinated Choke Point 2.0 operation remains contested , and the framing has been used by politically interested parties on both sides. Less contestable, on the other hand, is the Nigel Farage / Coutts case, in which the U.K. private bank Coutts closed Farage ’s account, and an internal 36-page Reputational Risk Committee dossier from November 2022 cited his political views as “at odds with our position as an inclusive organisation” . The CEO of parent group NatWest resigned in July 2023, and the U.K.’s Financial Conduct Authority subsequently reviewed account closures across multiple banks, finding roughly 343,000 personal and business accounts were closed in 2021 to 2022 alone. Banks self-reported that few were for political views, but the FCA also noted significant data-quality problems. Disclaimer: I have no skin in the U.K.’s political game and I do not care about Farage as a political figure or even as an individual. However, the Farage / Coutts case is one of the most prominent cases, which is why I picked it up to give an example. Make no mistake to believe that de-banking is solely an issue on one side of the political spectrum , as it is clearly not. The volume of Suspicious Activity Reports filed by U.S. financial institutions to FinCEN has risen from about 1.3 million in 2014 to roughly 3.6 million in 2022 , and Currency Transaction Reports run at about 20.5 million per year. The European Banking Authority ’s 2022 opinion on de-risking is even explicitly acknowledged that AML rules are causing unwarranted account closures across NGOs, money-service businesses, and correspondent banks. To understand the real world implications of how these account freezes and closures impact even regular people on a day to day basis it’s enough to look at individual institutions’ bad ratings on any unbiased review site, e.g. for (Transfer)Wise on ConsumerAffairs . The mechanism here is, again, one I think is poorly understood. Banks are one part malicious, injecting their own policy and beliefs into their decision-making, and one part cautious, as they face fines for AML failures. For example for laundering $881 billion, the HSBC paid $1.9 billion in fines in 2012. But don’t worry, nobody at HSBC went to jail. Similarly, the U.S. Treasury Department settled with the Standard Chartered for $1.1 billion, for violations of multiple sanctions in 2019. On the other hand, however, AML over-compliance effectively carries no penalty at all, e.g. for closing the account of a legitimate small business or unbanking an innocent individual. The economically rational response is to weight profit vs. risk and to interpret risk conservatively for any account that does not pay enough to justify the regulatory exposure . The result is that the marginal small business, the freelancer with an unusual revenue pattern, or the person whose work happens to fall in a politically sensitive category, finds banking impossible, without any of this being written into any law as such. It is the emergent behaviour of a stack of regulations, none of whose authors probably intended this outcome. Add to this the ever changing regulatory environment and banking suddendly becomes yet another bureaucratic burden for small and medium businesses, let alone lower- and middle-class private individuals. The deeper irony is that this regime consistently fails at the very thing it was built to do. The list of major money-laundering scandals over the past two decades, including HSBC ’s settlement for laundering Mexican cartel money , Credit Suisse ’s Suisse Secrets leak revealing accounts held by criminals and corrupt politicians, the 1MDB scandal in which billions of dollars flowed through major Western banks, the CumEx tax fraud in which European treasuries lost an estimated €150 billion, and the Wirecard collapse in which one of its senior executives simply vanished, all happened despite KYC, AML, beneficial-ownership disclosure, and the rest of the modern compliance stack, without any of the involvement of cryptocurrencies or any other modern technologies, that are usually politically vilified for enabling these sort of schemes. The people the regulatory regime is supposedly catching are, with rare exceptions, not being caught. The people most affected are those who do not have a tax planner, a private banker, a trust fund, or a corporate structure that can absorb the friction and make issues simply go away . Take the popular case of Flipper Devices , the small hardware company behind the Flipper Zero , a multi-tool aimed at hardware hackers, penetration testers, and electronics hobbyists. The product’s Kickstarter campaign in 2020 was extraordinarily successful, raising nearly five million dollars from tens of thousands of backers. In late 2022, the company publicly reported that PayPal had frozen approximately $1.3 million of its funds, applying the platform’s standard 180-day review hold and citing only generic suspicious activity as justification. After significant media attention the funds were eventually released, but for a small hardware company in the middle of manufacturing and fulfilling international orders, going six months without access to over a million dollars of customer money is plainly a near-fatal event. Flipper survived because the tech press noticed and because they had alternative revenue streams, but the experience is far from unique. Most small companies that find themselves on the wrong side of a payment processor’s algorithmic risk score do not have a public profile large enough for anyone outside maybe their accountant or, ultimately, their lawyer to care. I believe that what is happening here is important and underappreciated. The bureaucratic delegation of compliance enforcement to private financial institutions has handed banks, payment processors, and similar gatekeepers a degree of power over private economic life that, historically, simply did not exist at this scale. A bank has the unique ability to create a business, by extending it credit on terms no ordinary lender would offer, or to destroy one, by freezing or even closing its account. If a major institution decides a particular firm is strategically valuable, it can throw virtually endless money at it through revolving credit facilities, underwriting commitments, intra-day liquidity, and market-making support, propping up balance sheets that, on the merits, would have folded years earlier. The opposite operation is just as easy, and considerably faster, as a compliance officer flagging a customer as inconvenient can, overnight, sever that customer from the payment rails on which essentially all modern economic activity runs. There is no court, no due process, and no meaningful right of appeal, and the customer typically receives a single boilerplate letter that does not even state the reason. This is a degree of power over individual livelihoods and corporate existences that, in democratic societies, used to require a court order. It is now exercised routinely by salaried risk officers operating under regulatory pressure that strongly incentivises closing first and asking questions later never. The same dynamic falls, sometimes even more starkly, on individuals, where a debanked person can find themselves locked out of housing, employment, and even the ability to receive their own salary, with no agency, court, or ombudsman that they can effectively appeal to. It’s this exact same financial-control infrastructure that has been used for instance by the Canadian government in response to the Freedom Convoy protests , or by the German government in response to Antifa . By freezing bank accounts associated with protest participants and donors, without conventional court orders, these individuals were cut off of modern life in an instant. Regardless of the underlying political debate and whatever you think of each of these cases individually, the precedent (specifically, a government using existing AML infrastructure to remove citizens from the financial system as a form of political pressure) is now established, in a world in which even the everyday use of cash, which is the official government-issued currency , has been recoded as suspicious in many jurisdictions. Large-cash deposits trigger reports, jewellers and car dealers face mandatory reporting thresholds, and several EU member states have explicitly capped what can be paid in cash at all. Going back to the more general topic of bureaucracy , especially in the context of business activity, I think the outlook is worrying when we project forward on the current curve. The U.S. Census Business Formation Statistics show that applications surged after 2020 from roughly 3.5 million per year to about 5 million per year, which is generally a welcome thing. But the underlying business dynamism has been declining for decades. Decker, Haltiwanger, Jarmin and Miranda ’s Brookings work documents that the U.S. startup rate fell from roughly 13% of all firms in the 1980s to about 8% by the 2010s. Additionally, multiple studies show that the share of employment at firms with fewer than 20 employees fell significantly in the past fourty years, and the OECD ’s Entrepreneurship at a Glance series finds similar declining startup rates across most member economies. So the recent surge in applications is encouraging, but it is seemingly happening against a multi-decade trend of declining small-firm employment and declining new-firm formation relative to incumbents. One plausible end-state, which I do not think is inevitable but which is clearly the trajectory we are on, might look something like this: Large incumbents accumulate the regulatory, tax, and compliance machinery (at their scale, the per-employee cost of compliance falls). Small entrants either do not start, start under the radar in regulatory grey zones (if even possible, see below), or get acquired before they can scale. The marginal new business is increasingly a side-hustle on a platform owned by an incumbent (think Amazon FBA , TikTok Shop , etc.), where the platform absorbs the compliance burden in exchange for a (hefty) cut, but also sets the terms unilaterally. The number of independent businesses falls, the share of actual, as well as paractical employment in incumbents rises, and the regulatory state both causes and justifies this concentration, on the grounds that fewer, larger firms are easier to oversee, while simultaneously likely to be corrupted bought lobbied by these exact firms. For most of the past century, the infrastructure of compliance was built and operated by bureaucrats , namely people sitting in offices, processing forms, applying judgement within the limits of their statutory remit. The friction generated by that arrangement was high, but the friction was also a feature, in a way, as it built in a small reserve of leeway , in the form of a human who could lose a form, mark a case as borderline, or exercise discretion. The trajectory we are now on is the replacement of that human by a system, with the bureaucratic structure inherited intact and made fully queryable . The bureaucrats built the cathedral, and the techno-/algocrats are now installing the 24/7 surveillance and the “AI” . Decades of beneficial-ownership filings, KYC records, CRS and FATCA exchanges, DAC7 platform reports, payment-service-provider data, e-invoicing pipelines, real-time VAT reporting (Italy’s SDI , Spain’s SII , Hungary’s RTIR , the impending EU-wide ViDA regime), property and Land Registry records, vehicle registries, customs data, and social-security feeds, all sitting in databases that, for most of their existence, were used in isolation, as data-silos. The techno-/algocratic project, broadly speaking, is to wire those databases together, to make them fully searchable, and to layer pattern-detection and “AI” on top. Make no mistake in believing that this is only hypothetical. The U.K.’s HMRC Connect , which is operational since 2010 and built for the tax authority by BAE Systems Applied Intelligence at a reported cost in the tens of millions of pounds, already cross-references dozens of distinct sources, including bank statements, social media, Land Registry filings, DVLA vehicle records, Companies House data, PayPal transactions, and offshore-account exchanges. On September 8, 2023, the U.S. IRS announced a major expansion of audit activity targeting large partnerships and high-income individuals, with Inflation Reduction Act funding and an explicit reliance on “AI” to identify return patterns that human reviewers would not have spotted. The OECD ’s forum on tax administration has, for years, been pushing member states toward real-time compliance and data-driven audit as the operating model of choice. With all of this the direction of travel is clearly set, and the technical capacity to act on it has now finally caught up. The cautionary tales of what happens when this approach is rolled out at scale, without the institutional caution that has historically slowed bureaucratic overreach, are already with us. For example Australia’s Robodebt scheme , which was in operation from 2016 to 2020, used automated income-averaging to issue hundreds of thousands of debt notices to welfare recipients on the basis of data-matching alone. The scheme was found unlawful by the Federal Court in November 2019, the government settled a class action for AUD 1.8 billion, and the Royal Commission that reported in July 2023 concluded the programme was crude, cruel, and produced disproportionate harm, including contributions to suicides . Also, the Netherlands’ toeslagenaffaire , in which the Belastingdienst ’s self-learning risk model wrongly accused tens of thousands of mostly immigrant-background parents of childcare-benefits fraud, demanding repayments that drove families into bankruptcy and, in over a thousand documented cases, the loss of custody of their children, was serious enough to bring down the third Rutte cabinet on January 15, 2021. Finally, the Dutch SyRI system , a separate algorithmic fraud-detection tool deployed in low-income neighbourhoods, was struck down by the District Court of The Hague in February 2020 for violating Article 8 of the European Convention on Human Rights on grounds of opacity and disproportionality. AlgorithmWatch ’s Automating Society reports have catalogued dozens of similar cases across European member states, in welfare, policing, education, and employment. What unites these cases, and what should worry anyone trying to run a small business or live a private life, are the integral features of the techno-/algocratic arrangement, which are that the system acts at machine speed, that the cost of being wrongly flagged is borne entirely by the citizen, and that the institutional pathway for appeal is essentially the same slow, human bureaucracy that has now been deprioritised in favour of the system that flagged you. The political-philosophy literature on algocracy , or governance by algorithm, has been making this point for over a decade, but has only recently moved it from academic concern into operating practice. The borderline situation, namely the small business that took a contested deduction, the freelancer with an unusual revenue mix, the side-hustle whose VAT return is six weeks late, or the consultant whose payment patterns trip an unexplained risk score, that, twenty years ago, would have been quietly tolerated, mis-filed, or simply missed becomes discoverable instantly. Once discovered, it is sanctionable with no human in the loop, and the same asymmetry that already shapes the regulatory landscape applies here, as large multinationals have the budget to deploy their own AI , hire armies of tax engineers, and structure around the algorithmic detection, while small businesses inherit the algorithmic enforcement without the means to defend against it. The leeway that used to exist in the system, a function of human inattention, finite processing capacity, and occasional judgement, is being engineered out as a deliberate goal, and sold as efficiency and fairness . The people who lose the most when that leeway disappears are precisely the ones who needed it most. I think this is sadly where we are headed if nothing changes, and I think it should worry people across the political spectrum, in every developed and developing nation. Probably the strongest argument against this is, that the reason 1700 looked deregulated is, that it was also worse on almost every dimension of human welfare. Workers had no protection, children worked in mines, the seas were full of slaves, rivers were poisoned, and banks collapsed routinely and took depositors’ savings with them. The reason the modern regulatory state exists is that the previous arrangement was actively killing people, and the slow accumulation of rules is the price of a society in which most people “no longer” die at work , drink contaminated water , or lose their savings to a bank’s bad bets . That’s at least what the bureaucrats , and technocrats , and algocrats keep telling us. In principle, cumulative regulation is not a flaw of the system, it is a record of every preventable disaster the system has tried to prevent from recurring, and removing the rules in aggregate would remove the protections in aggregate. And don’t get me wrong, I am glad when workers have meaningful safety protections, when consumers can sue over defective products, when depositor insurance exists, when environmental externalities are at least partially priced in, and when a small number of bad actors no longer get to externalise their costs onto everyone else. I do not think that the counterfactual world in which we kept the freedom of 1700 and added the income from 2026 is a world I or anyone else would probably want to live in. What I do think, however, is that there is a meaningful difference between essential protections (that actually work) and accumulated regulatory drift . The basic worker-safety rule that says you have to provide fall protection above a certain height is essential. The 47-page guidance document about how to file your beneficial-ownership disclosure for a single-member LLC is drift. The basic principle that consumers should be told what is in their food is essential. The 200-page set of EU labelling rules covering every permissible variation of free-range is drift. And the regulatory process, almost everywhere, is asymmetric, as rules are added much more easily than they are removed. The U.K.’s one-in, two-out initiative was an attempt to rebalance this, and was quietly abandoned. The EU’s REFIT programme was modest in ambition and modest in delivery. The basic dynamic, that political incentives strongly favour adding rules in response to any given incident and very weakly favour removing them in response to cumulative drift, is the big issue here. If you can grant me that distinction, between essential protection and accumulated drift , then I think the current state of the western regulatory system contains a lot more drift than its defenders are willing to admit, and removing some of that drift would not actually require dismantling any of the protections that make modern life better than in 1700. To wrap this up with something approaching constructive thoughts, I think we should want a regulatory state that protects against catastrophic externalities (pollution, fraud, systemic financial collapse, occupational deaths) while making it easy to start the kind of small, independent business that built post-war prosperity. I think we should want a tax system that is fair and simple enough that a person running a one-person operation can comply with it in an evening, and graduated enough that a multinational cannot escape it through accounting geography . Speaking of which, I also think that we should want a levelled playing field, in which accounting geography is either impossible, or possible for anyone regardless of the depth of their pockets or the political and economical influence they might have. I think we should definitely want banking that is open to anyone who has not been individually adjudicated to have done something wrong, and not closed to people on the basis of category-level reputational risk. And we should almost certainly want this lifeblood of our modern life to require a lot more effort to be simply turned off in an instant than it does today. I think we should want a habit, in the political class, of asking what should we remove this year , with the same energy we currently bring to the question what should we add . None of this is a return to 1700, but it is more like a return to the economic environment of, say, the 1950s, 60s, 70s and maybe even 80s, in which the post-war west had built a real welfare state and meaningful worker protections, but had not yet loaded on top of that the accumulated drift of seventy further years of rule-making. That is not a libertarian fantasy, and it may in fact be living memory for some of the people reading this. It was the environment in which their parents or grandparents started shops, opened bakeries, built small factories, and made middle-class lives. None of the rules that I think constitute drift were added in bad faith and probably each of them was a response to a real problem, designed by people who (in most cases) meant well, and voted for by representatives whose constituents wanted that specific problem solved. The cumulative effect was nobody’s intention, it is just what happens when a system has a stronger tilt towards adding than towards removing, and that runs on such an imbalance for several decades. Therefor, I think the next political project that is worth caring about, more than most of the noise that currently passes for debate, is the project of deciding what to keep, what to remove, and how to build an institutional habit of asking that question regularly. I do not have a clear policy proposal for how to do that, as I am far from being truly politically and economically knowledgeable, but I am reasonably sure, that the current trajectory ends somewhere I would rather not arrive at, and that the people who will pay the highest price for arriving there are the people who were not yet born when most of the drift was added. If you take only one thing from this post, take this: The bureaucratic weight that we treat as an immovable feature of modern life is, in fact, a very recent construction. It was built in living memory, by people we can name, in response to problems we can list, with consequences they did not entirely foresee or willfully ignored. It can be rebuilt, lightened, simplified, and reformed, in the same way it was built up. The question is whether we have the political stomach to treat accumulated rules with the same scepticism we currently treat proposed rules , and to remember that every line of regulation, however well-intentioned, is also a small tax on every future person who has to read it before they are allowed to do something useful. I would like to think we still have that stomach, but I am not certain we do. Footnote: The cover artwork is a real painting by Heather Castles . Sarbanes-Oxley ( SOX ) from 2002 added 3,000 to 10,000 compliance hours per company per year, with average direct cost of $1.7 million for accelerated filers, and average annual SOX cost for a small public company rose from about $1.5 million in 2001 to over $2.8 million by 2007. This is a significant part of the reason that the number of U.S. publicly listed companies has roughly halved since the 1990s. Dodd-Frank from 2010 required, at peak, around 398 distinct regulatory rulemakings, and the American Action Forum estimated cumulative compliance burden at over $36 billion and 73 million paperwork hours by 2016. The 2018 Economic Growth, Regulatory Relief, and Consumer Protection Act rolled back some of this for regional banks, but the substantive bulk remained. MiFID II from January 2018 cost the financial industry roughly $2.1 billion in first-year implementation costs and several hundred million in ongoing costs, with the top ten sell-side firms each spending more than $50 million. A documented side-effect, perhaps an unintended one, was a substantial fall in EU sell-side research analyst headcount over the following two years. The General Data Protection Regulation ( GDPR ) , in force from May 2018, has been one of the most consequential pieces of EU legislation of the past decade. Industry surveys at the time put average Fortune 500 GDPR spend in the mid-eight-figure range, with substantial recurring annual costs thereafter. More than a thousand U.S. news sites blocked European users entirely after GDPR came into effect, including major publications like the Los Angeles Times and the Chicago Tribune , and many of those blocks remain in place years later. GDPR was a serious response to a real problem, but the way the cost falls is itself an externality of how the rule was designed. Strong Customer Authentication ( SCA ) under PSD2 , enforced from 2021, made online payments in the EU more secure but, by Stripe ’s estimate, also lost European e-commerce roughly €57 billion in sales in the first year. The U.S. Corporate Transparency Act , effective January 1, 2024, requires beneficial-ownership disclosure on roughly 32.6 million existing entities plus another 5 million new entities annually, at first-year compliance cost estimated by FinCEN itself at approximately $22.7 billion . The constitutionality is currently in litigation, but the regulatory intent tells you a lot about where the trajectory is. The EU AI Act , passed in 2024 and phasing in through 2027, will impose high-risk AI compliance obligations whose cost the Commission estimated at roughly €29,000 per system, but which independent analyses (such as CEPS ) suggest could run closer to €400,000 for a small company deploying a high-risk system. The order-of-magnitude disagreement is itself a sign that nobody really knows what this is going to cost yet, which is not a reassuring property of a major piece of legislation.
Ruby
Career
AI Is Slowing Down
If you liked this piece, you should subscribe to my premium newsletter. It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5,000 to 18,000 words, including vast, detailed analyses of NVIDIA , Anthropic and OpenAI’s finances , and the AI bubble writ large (updated to version 3.0 last week). My Hater's Guides To the SaaSpocalypse , Private Credit and Private Equity are essential to understanding our current financial system, and my guide to how OpenAI Kills Oracle pairs nicely with my Hater's Guide To Oracle . Over a three week period in May , I published an exhaustive three-part guide to how the AI bubble might collapse, the events that might trigger it, and the consequences. For something lighter, check out last week’s premium, where I re-introduce you to the antagonists of the AI bubble (and their fatal weaknesses) in caustic, slightly sweary terms. Subscribing to premium is both great value and makes it possible to write these large, deeply-researched free pieces every week. Last week I went on Bloomberg and discussed the state of the AI bubble with a clarity that rattled even the sweatiest boosters, mostly because I spoke with clarity about an investment frenzy whipped up through hype, deceit and mythology. Some were equal parts frustrated and angry that I don’t have money in the market, or, as they’d put it, “skin in the game.” I get it! When your entire worldview is dictated by what a series of venture capitalists and psuedo-journalists on Twitter want you to believe, it must be difficult to imagine someone having “morals” or “beliefs” or that one might hold a position that wasn’t entirely based on greed or tribalism. It must be confusing — upsetting, even! — to hear that somebody is willing to accurately and vociferously tear into a tech industry largely controlled by people with no regard for their users or workers, who are willing to bathe their products in mediocrity all because it’s the thing that everybody else is doing. This is a hysterical era perpetuated by liars, cowards, imbeciles, craven boosters and the easily-fooled. Those excited about generative AI are either the victim or the perpetrator of a con centered around a technology to ingratiate at the highest cost possible. I also think that everybody is a little flippant about what has to happen for me to be wrong. Whatever obtuse fantasies you have about the current state of generative AI are irrelevant to a much larger problem: that the infrastructure being built and compute commitments being made are being done so at a level that demands that generative AI and AI compute generate over $2 trillion in annual revenue by 2030. When I say that, I mean it absolutely has to do that otherwise none of the data center capex makes sense, and neither Anthropic nor OpenAI can pay their commitments. OpenAI expects to spend $50 billion on compute in 2026 , and I wouldn’t be surprised if Anthropic spends anywhere from $30 billion to $50 billion. Between them, Anthropic and OpenAI represent the vast majority of all AI compute demand — at a minimum 70% , if not 80% to 90%. Put another way, there’s barely a few billion dollars of demand outside of two companies that lose billions — or tens of billions — of dollars a year. Let’s break down these numbers a little further: This is not hyperbole! Every single thing I have stated here precisely maps to the projections and promises of the AI industry. No matter how horny or flaccid you are for the potential of AI, it must grow at an astonishing, unstoppable rate from here until the end of time to be anything close to worthy of its costs. Actually, sorry, let’s put judgments aside for a second, because this isn’t about judgment , but rather the promises that have been made by the software and hardware companies associated with AI. NVIDIA’s place atop the stock market and its ridiculous projections depend on both the continued flow of data center debt and the continued belief that AI services will have the revenue to back it up. AI cannot, under any circumstances, slow down. In a year, Anthropic and OpenAI’s businesses have to be roughly twice the size they are today, and then double again basically every year until 2029 or 2030. In that time period, they must also both raise hundreds of billions of dollars or, alternatively, turn deeply unprofitable businesses into profitable ones while also doubling their revenues. Alternatively, both must severely reduce their costs… except if they do that, they won’t have any need for all that compute capacity, which will deprive Oracle, Google, Microsoft, SpaceX, Cerebras, CoreWeave, TeraWulf, Cipher, and Hut8 of the $1.1 trillion in remaining performance obligations. Also, if OpenAI can’t afford — or doesn’t want — its compute, Oracle will simply run out of money . It is spending anywhere from $340 billion to $700 billion (depending on whether you believe Jensen Huang in September 2025 or May 2026) on the 7.1GW of data centers it’s building for OpenAI. These, again, are not hyperbolic statements, but the actual costs associated with Oracle’s massive buildouts in Michigan, New Mexico, Wisconsin and Texas. I didn’t agree to do this! Larry Ellison did! Apparently, Salesforce is planning to spend $300 million on Anthropic in 2026, to which I say “that’s not nearly enough”! Everybody has to be spending even more than that in the next few years, without fail, no ifs, ands, or buts. It is non-negotiable. Anthropic needs to be making over $100 billion in two years or it can’t afford its commitments, so you filthy token-hogs better slurp up your slop this instant, or Dario Amodei gets made part of the permanent underclass! But seriously folks, the combined compute demand of every single AI company in the world doesn’t currently reach $100 billion — and it needs to be ten times that by 2030 or all those data centers got built for no reason! And for that to happen, both Anthropic and OpenAI need to be making about $400 billion a year in annual revenue, which means there needs to actually be that much demand for AI services! Right now, Anthropic and OpenAI’s combined projected revenues for 2026 sit somewhere in the region of $60 billion — so, you know, they only need to grow by 496% by the end of 2029! To make matters worse, it doesn’t seem like anyone else in the AI industry is going to help with the whole “demand for AI services or compute” thing. As The Information reported a few weeks ago, OpenAI and Anthropic make up 89% of all AI startup revenues . We could include hyperscaler revenues, but that wouldn’t help very much. Microsoft’s $37 billion in AI annual run rate — these fucking cowards never share actual AI revenues! — is predominantly made up of OpenAI’s compute, with the rest of it (maybe $8 billion in annual revenue at best) from Microsoft harassing its permanently-abused customer base into installing Copilot. Ah, shit, there’s another problem with Microsoft — Microsoft AI CEO Mustafa Suleyman just said that Anthropic’s models were too expensive, and he intended to reduce Microsoft’s use of them to zero ! You can’t do that Mustafa! We need every cent of demand, otherwise everything falls apart! Anyway, eager math-knowers among you might also notice that even if Anthropic and OpenAI spent $500 billion a year in annual compute — an amount that they can’t afford even if they combined both their unsustainable asses — we’d need at least another $250 billion or more in annual compute revenue to justify it. In other words, they need everybody to be “doing agents” at such a scale that basically every third dipshit you run into on the street is sinking $50 or more a day into them. I sure hope that’s happe- OH MY GOD! As I discussed last week , you can’t measure the cost of a particular task with AI, nor can you measure its return on investment. The only reason that we’ve been “doing AI” with such ferocity and veracity is that most companies are beholden to Business Idiots disconnected from production who have no real understanding of their underlying firms’ outputs, and thus have very little way of measuring them. These multi-millionaire midwits have been “doing AI” because everybody else is doing it, burning millions of dollars to turn their code into slop ( see: Zillow ) or have their engineers compete to see who can spend the most money ( see: Meta and multiple other companies ). In one case, a company spent $500 million on Anthropic’s models in a month because it didn’t set up spend controls . In Uber’s case, it burned through its entire annual token budget in a single quarter , which led to its COO saying it was harder to justify spending money on AI tokens because it couldn’t show a link between that spend and a meaningful increase in useful features on Uber . Now Uber has capped its employee spend at $1,500 a month per user , with T-Mobile temporarily following at $2,000 a month per user with the intent to move to a tiered system. Over at Brex , engineers are limited to $500 a week in tokens, with non-engineers getting an astonishingly-low $5 a week. These are signs that AI’s revenue growth is slowing, and it’s likely going to slow further, because we currently live in an era where Anthropic and OpenAI are straight-up abusing its clients, providing limited-to-no visibility into spend, per the Wall Street Journal : How utterly ridiculous! Only in the frothiest, most-disconnected economy in history could we have companies spending millions (or tens or hundreds of millions) of dollars on a service without having any visibility into costs until after billing. This is not a sustainable revenue stream under any circumstances, and anybody who says that it is is either ignorant, a mark or a con artist. This is revenue made entirely by convincing your customers that something is true (AI is the most revolutionary thing ever!) and keeping them in the dark as long as humanly possible as they run up ridiculous bills, all in the hopes that you’ve brainwashed the executives /paypigs well enough that they’ll never stop. And really, “paypig” is the accurate term for these cretins: Russell, you may as well let Dario Amodei put a cigarette out on your forehead! This is pathetic! What a fucking loser! Oohhh, I sure hope that the company I pay all this money to lets me see how much I’m spending! I thought Silicon Valley was meant to be all about meritocracy ! Boosters will say that it’s “hard to measure productivity for any job outside of sales,” but that’s simply not true! If you let your engineers spend $1500 or more a month on a service, surely you must have some way of measuring how much actual new stuff went out — new features, customer tickets reduced, projects completed, I don’t know, I’m not the fuckwit spending $1,500 a month per person on this garbage! You’re the one that has to justify it! But, fundamentally, these are all signs that AI is slowing down. Remember: Anthropic and OpenAI only moved their customers to token-based billing in Q1 2026 . It only took two or three months for us to get headline after headline of big , serious business publications saying “AI costs a lot of money and companies aren’t sure if there’s a return on investment.” If things were going well, these stories would be inverted — companies would be boasting about their remarkable token spend and pointing to all the new, incredible things they were shipping. Their products would be spotless, their features sublime, their engineers sliding entire new stacks of impressive software out the door so fast that it would be changing the very nature of software. I mean… someone would be, right? Let’s check out the cha AHHH ! What’s actually happening is that these tools are — at a remarkable price — shoving a lot of stuff out the door. Is the stuff good? No. Do people like or use it? No. Does it make money? Also no. While we’ve discovered the shovelware , that’s all that LLMs have given us — “more” apps, with the vast majority being useless, insecure slopware. This is meant to be the era of agentic coding! This is meant to be the era where any dickhead with a Codex or Claude Code account with $1,000 of free API credits should be able to create the next Salesforce or whatever it was that dimwit Citrini talked about a few months ago. I’m sorry to be a little surly and dismissive, but the AI industry has burned over a trillion dollars and I’ve spent two years being told I’m a luddite and an ape for not celebrating it. I don’t care! I’m not impressed! I’m not coddling this mediocre, expensive crap! Like I said earlier: isn’t the tech industry meant to be a glorious bastion of meritocracy? Isn’t this meant to be a cold, harsh community of rationalists? If so, why are we coddling AI like it’s the kid from that episode of the Twilight Zone ? Has Silicon Valley become so decidedly whipped by the forces of capitalism that it can’t see that none of this makes sense? Or was this always just a culture of lemmings drawn in whatever direction venture capital waved a dollar bill? To make matters worse, both OpenAI and Anthropic are speeding as fast as they can toward IPO — which means that both will have to start looking like real companies , which means both will, inevitably, start charging their customers more and very likely moving the vast majority of them to token-based billing and either kill or vastly limit their subsidized subscriptions . In a mysterious confluence of events, both Claude Code chief Boris Cherny and OpenAI-owned OpenClaw televangelist Peter Steinberger have both said that their users need to be “designing loops for their agents,” meaning “creating ways to make their agents burn a bunch of tokens doing stuff,” I imagine as part of the ongoing campaign by both Anthropic and OpenAI to make people spend lots of money on tokens to keep their enterprises afloat. I expect that “loops” will become the next thing that journalists pick up on and start oinking about. To be clear, “loops” already exist, in that you can make an LLM decide to keep taking actions whether or not a user prompts it for as long as you’d like. Whether the output works at the end isn’t Peter or Boris’ problem, as both of them are allowed to burn anywhere from $130,000 to $1.3 million a month in tokens . As I’ve argued before (though referring to subsidized subscriptions): To be clear, this is both OpenAI and Anthropic’s representative stooges actively suggesting that you “shouldn’t be prompting coding agents anymore,” instead letting LLMs that hallucinate the more they “reason” (IE: make plans for themselves, which is how agents work) do as much reasoning as possible without user input. These men have complete contempt for their users and customers. They do not give a shit that their models break so often that Notion had to cut access to Anthropic’s for several hours or that the costs are so severe that CFOs are a few bad bills from a trip to Budd Dwyer’s Favorite Lunch Spot. You must burn more tokens, because otherwise you won’t be doing AI coding right, whatever that means. And please, god, stop trying to convince me this shit is impressive. You all sound like you’re in an abusive relationship trying to explain why a guy who rifles through your pockets and half-asses everything he does at an incredible cost is actually super sweet behind closed doors. I’m distinctly unimpressed! After hearing a particularly colourful story from Kevin Smith , I came up with the perfect way to explain the AI bubble. Okay, perfect might be a stretch, but I think this gets my point across, and hell, it’s a free newsletter, what’re you going to do? Kill me? Run me over with a truck? Good luck with that, I’m a huge homebody. Anyway, imagine, if you will, a smaller version of the giant mechanical spider from Wild Wild West — a portable one that you sit in like a chair with big arms and big legs. The giant metal spider costs $1 million, and takes up about $40,000 of fuel every time you use it, but it can sometimes pick stuff up and make you dinner. The problem, however, is that it’s a giant metal spider — sometimes it precisely grabs a diet coke from the fridge, and sometimes it punches a hole clean through it, requiring both a brand new fridge and for me to pay $40,000 regardless. The good news is that the companies that make the giant metal spider from Wild Wild West also subsidize the giant metal spiders at around $200 a month with free insurance, though businesses are forced to pay for its actual costs. As I march it around my apartment, the giant metal spider leaves horrible scratch marks on my floor, it sometimes makes a terrible noise, but I, as the user, barely have to do anything — the spider does everything for me, even though whatever it “does” is incredibly costly, convoluted, and often takes far longer than it should. Every update to the spider widens what it can allegedly do, but each time I use it it’s just as expensive. Can the spider make me a cup of coffee? Yes. It takes five minutes, which is longer than I’d take, and occasionally it throws the coffee in the air or simply fills the cup full of oil, but most of the time I get a cup of coffee. Isn’t that good? We love the giant metal spider. When I turn on the news, I see a headline about how “THE GIANT METAL SPIDER FROM WILD WILD WEST WILL CHANGE EVERYTHING.” 30 different guys on Twitter write 800-word-long screeds about how we must redesign apartments and office buildings to cater to the spider, that “it’s inevitable that the metal spider from Wild Wild West will be how everybody does everything in the future,” and one guy even suggests that it’s alive because, after adding a $500,000 add-on, the giant metal spider can be scheduled to get up on its own and make the coffee. Sometimes it does so successfully. Sometimes it smashes the coffee maker up into tiny little pieces. Sometimes it mashes its legs through the kitchen island. Sometimes the spider opens up my Amazon packages with ease. Sometimes the spider rips them in two. Thankfully, the companies behind the giant metal spiders subsidize them, so the average person only experiences the occasional act of destruction, but they also lose billions of dollars a year on training the spiders and the constant maintenance required to run them. There are some workplaces full of the giant metal spiders and they’re absolutely insufferable. Everywhere I go, somebody is telling me the spider is the future. “The giant metal spider from Wild Wild West will eventually stop destroying stuff! Future innovations in giant metal spiders will make them cheaper and more-reliable! Look, we’ve done a study, and the giant metal spider’s ability to complete a task of a certain length 50% of the time has increased !” Every time they add a new feature to the giant metal spider from Wild Wild West, it requires several hundred million dollars, and it isn’t always clear whether the giant metal spider learned anything new. It’s really good at opening Amazon packages, so they thought it might be able to make a bed, and spent $100 million training it to do so, only to find it kept karate chopping the bed in half approximately 20% of the time. Another time, the giant metal spider from Wild Wild West showed promise at playing Texas Hold ‘Em, successfully getting through an entire game 50% of the time. Unfortunately, the other 50% of the time it smashed the cards into the table. After another $100 million, they were able to reduce that number to 30%. A day later, The Atlantic ran a story: “ Vegas Is Scared Of The Giant Metal Spider From Wild Wild West .” Technically, the giant metal spider is productive, at least in some households where they give it significant room to maneuver and only give it tasks it’ll excel at. Across the world, private credit funnels billions into giant metal spider factories powered by NVIDIA chips, assuming that everybody will be paying to rent one of them. When you criticize the giant metal spiders, you’re told that you use them in the wrong scenarios, ones where they’re guaranteed to fail. Young graduates are encouraged to learn how to move the giant metal spider, and that if they fail to, they’ll be unable to explore the giant-sized future that will be built for them. Year after year, more people insist that the giant metal spider from Wild Wild West will get cheaper, but the costs only seem to increase along with the vast amounts of damage it causes. It’s undeniable that the giant metal spider from Wild Wild West can do stuff. Sometimes it even does the stuff as well as a person. For some reason, it’s impossible to tell when it’ll get things wrong, and despite everybody saying that the giant metal spider from Wild Wild West is “smart,” it seems to occasionally do things the user didn’t ask for. If you say that the giant metal spider from Wild Wild West isn’t going to be the future of anything due to its massive, unsustainable costs, or suggest that its inconsistencies make it unreliable in some way, you’re told you’re a doomer, a skeptic, a luddite and a rube. One day, someone using one of the giant metal spiders from Wild Wild West steps on your car. Futurism writes an article laughing at you . You scream so loudly that one of your neighbors calls the police. No matter how much you dress up whatever AI service has gaslit you into believing it’s sentient, generative AI is inherently limited, impossibly expensive and economically unviable. Its services cost too much to run, its progenitors have no path to profitability, and no amount of rigged benchmarks and anecdotal examples of theoretical engineering teams that are “10x’d” can make up for the fact that you can’t measure the cost of an LLM-driven task or its return on investment . Anyone claiming that you have to “measure AI’s ROI differently” is attempting to con either you or themselves. While it’s tough to measure the ROI of a particular worker or project, most workers and projects don’t increase your operating expenses by anywhere from 10% to 100% under the vaguest of promises that you might be “doing the future. ” AI is calamitously expensive and, despite years of promises of it getting cheaper for both those running AI services and its customers, costs have only ever increased. I think that’s by design. AI labs want their costs to be high so that they can continue growing at ridiculous rates, all so that they can keep feeding money to their hyperscaler compute partners who then invest that money right back into them , creating further reasons to keep buying NVIDIA GPUs, so that NVIDIA can then invest that money back into either AI compute providers (who OpenAI and Anthropic pay) or the AI labs themselves. Concepts like “efficiency” or “cost reduction” run counter to the greater narrative of AI’s voracious sprawl of data center capex and still-theoretical AI revenue. If OpenAI or Anthropic were to seek profitability or sustainability (assuming these things were possible), that would create less demand for AI compute, which would mean less demand for Azure or Google Cloud or Amazon Web Services or CoreWeave or Oracle Cloud Infrastructure , which would in turn mean less demand for NVIDIA GPUs. The problem with this marvelous plan is that at some point there had to be an honest transaction — real, honest, sustainable demand based on a reliable product that people liked paying for because they understood its value. Right now, AI revenues are either chaotically experimental or so thoroughly-subsidized that labs are giving away hundreds of dollars a user in the hopes that at some point said user might want to pay even more money for measurably less value , the kind of proposition you make when you think your customers are fucking idiots. It only took a few months of token-based billing for the AI conversation to go from “our magical, beautiful agents” to “hmm, are we sure this is worth it?” and I believe it only gets worse from here. AI labs do not have some super secret trick up their sleeves — no, not even Mythos, that was bullshit I’m afraid — that will suddenly provide the kind of ROI that’s impossible to ignore, nor do they have some magical way to bring down their costs while also spending just as much on compute. From here, we basically need to 10x every part of the AI stack based on the projections and commitments made by effectively every AI firm. Anthropic and OpenAI must grow faster than any company has ever grown before in the space of a few years, and suddenly become profitable, all while somehow raising hundreds of billions of dollars. On top of that, we need at least another $250 billion in annual AI compute demand, which likely means at least two other OpenAI or Anthropic-scale companies. If this all sounds unreasonable, don’t blame me. I’m not the stupid fucker that agreed to build 100GW+ of data centers or mortgaged the future of Oracle on the off chance that Sam Altman and Dario Amodei, two craven manipulators , somehow work out how to create Google 2 and Amazon 2 in the space of four fucking years. I won’t tip my hand too much, but I have a story coming out in the next two weeks that will likely confirm the absolute worst fears of the AI industry. Many have been incredibly brazen about the potential losses of particular AI labs to the point that I made it my mission to talk to as many people in the tech industry as humanly possible, in part because some who have suggested that I “don’t speak to people who work in the tech industry.” In truth, I speak with tech workers every single day of the week, and they’re in fucking agony. If you are someone in the executive team of any major tech company, know that your employees are, for the most part, completely and utterly miserable. Your endless death march of “do as much AI as possible or we’ll fire you” and forcing them to use these tools day-in-day-out has radicalized them against you. Every day I hear from someone who is dealing with the wrath of a different Business Idiot who doesn't do anything other than demand more deliverables in a smaller timeframe with less people because you keep laying people off. If you are a worker at a tech company, I fucking see you. I feel your pain. I hear your sadness. I am enraged and disgusted at the way you are being treated. Reach out to me at ezitron.76 on Signal with anything you’d like to share. I’ll protect your identity, listen to your stories, and if you share something with me that warrants publishing, I’ll make sure I do it justice by understanding the subject matter and reporting it in a way that it never gets back to you. I’ve done this again and again, and will continue to do so, because I love my sources, I treat them with dignity, respect and empathy, and they, like me, find the current state of the tech industry wretched, its leaders worthless, its road maps directionless and its works mediocre. Even if I don’t run with the story, I am here to listen, because I hate what you are going through. I feel your pain. So many of you truly love making good software and want to do good things in the world and feel impeded by the Business Idiots and mocked by the boosters who seem to care more about your bosses than anything to do with software or innovation. It sickens me what the industry has done to you and continues to do to you. You deserve better. I write this newsletter because I deeply enjoy writing and I deeply hate what is being done to the computer. I hate that many people like me are suffering at the hands of the scumbags and freaks birthed from the guts of McKinsey and various MBA programs. I don’t do this because of a short position. I don’t have one. I don’t hold any stocks, securities, or CFDs. I do it because it’s my job and because I give a shit. If it’s impossible to comprehend why somebody would do something without a short position, you need to think long and hard about why you bother waking up every morning. One of my sources has come forward and brought me a story that will possibly burst the AI bubble. The reason they brought this to me is that I’ve shown — and will continue to show — that I actually give a shit about this industry and the people in it. If you’re wondering what the story is, know that it’s the information I’ve wanted for years, delivered as I have always wanted it, and I will treat it with the reverence it deserves. Imagine what the worst possible thing for me to get would be and you’re probably close. I expect it to be out in the next two weeks, and you’ll know exactly when it runs. There’ll be a podcast and a newsletter, and very likely follow-on coverage elsewhere. I can guarantee you it’ll be worth it, and you’ll be stunned by what I report. If you liked this piece, you should subscribe to my premium newsletter. It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 10,000 to 18,000 words, including vast, detailed analyses of the biggest events and companies in the AI bubble. If we take Sightline Climate’s data from February at face value , there are 190GW of data centers planned. If we take NVIDIA CEO Jensen Huang’s statement that data centers will cost $80 billion to $100 billion a gigawatt at face value, this means that said data centers will cost anywhere from $9.5 trillion to $15 trillion. Bloomberg incorrectly states that this is a “$3 trillion” buildout . This money will have to come from somewhere. The Financial Times reported in May that banks are concerned they might “choke” on data center debt when I estimate there’s barely $250 billion a year being issued. They will, to actually make these data centers happen, have to start issuing anywhere from $500 billion to a trillion a year. Jensen Huang has also said that NVIDIA projects a trillion dollars worth of revenue through the end of 2027 . 54% of NVIDIA’s revenue comes from three clients , which means that NVIDIA’s future largely depends on three unnamed companies — likely Taiwanese ODMs building servers for Microsoft, Google and Meta — and their counterparties’ ability to raise debt on a near-perpetual basis, as the number of firms that can afford to buy thousands of $7.8 million racks of Vera Rubin GPUs is dwindling. Even then, every part of this puzzle requires more and more debt or at the market dumps like Google’s $85 billion equity sale or Meta’s planned multi-billion dollar dump . The fact that hyperscalers are doing equity sales is, as economist Paul Kedrosky raised in our conversation on my show last week , a sign that debt is becoming harder to acquire. Anthropic has made $330 billion in compute and chip commitments between Google, Amazon, and Microsoft , another $30 billion with CoreWeave and another $15 billion with SpaceX. To pay for this compute, Anthropic must meet its projected revenue of $174 billion a year by 2029 . Anthropic has raised $95 billion across rounds in February , April (from Google and Amazon ), and May . These funds will be insufficient to cover Anthropic’s costs, as will Anthropic’s cash flow, meaning that it will have to raise at least another $200 billion in the next year. OpenAI has projected to burn at least $852 billion through the end of 2030 , and has made over $770 billion in compute commitments across Microsoft, Amazon, CoreWeave, Cerebras, and Oracle. The $122 billion funding round from March will be insufficient to cover these costs, and it will require, at the very least, another $250 billion in funding by the end of the year. 190GW of data center capacity assuming a PUE of 1.35 suggests a critical IT load of around 140GW, which, charged at around $12.5 million per megawatt, works out to around $1.75 trillion in annual revenue. If we assume that half of that gets built, that’s still $875 billion in annual revenue that will be needed to keep these data centers from running out of money as their margins are atrocious and they’re all paid for with onerous debt. OpenAI and Anthropic project to make $184 billion and $174 billion in revenue in 2029, for a total of $358 billion in annual revenue. While Anthropic claims it will be profitable by then, I do not believe it will be, nor is it profitable at this point outside of financial engineering . At present, there are no other major purchasers of AI compute outside of NVIDIA, hyperscalers (who are selling it to Anthropic and OpenAI, or they’re Meta, which has no AI strategy ), OpenAI, and Anthropic. None. I can’t find a single one outside of Jane Street spending more than a few hundred million. We need a few hundred billion. That’s already a huge problem, but the other problem is that we also need companies to spend dramatically more on AI services than they already do. While journalists are currently gooning over OpenAI and Anthropic making $6 billion or $10 billion in a given quarter, that’s just not enough! Both Anthropic and OpenAI need to be making $10 billion or more in monthly revenue by Q1 2028, or their growth rates aren’t going to support their compute commitments.
Using SwiftUI to Build a Mac-assed App in 2026
Link: https://pfandrade.me/blog/mac-assed-swiftui-app/ Paulo Andrade , creator of Secrets and Shopie : There was a time when Mac apps felt unapologetically Mac. Panic, Omni, Cultured Code, Bare Bones, Sofa. The years just before the iPhone SDK were probably peak Mac-assedness. Then Apple's center of gravity shifted toward the iPhone. Now we have Electron, Catalyst, and iPadOS apps on the Mac. And even Apple's SwiftUI apps often sand off the very behaviors that made Mac software feel great in the first place. SwiftUI was announced at WWDC in 2019, almost exactly 7 years ago now. It was meant to be a unified toolkit that would allow you to build apps for Mac, iPhone, iPad, Apple Watch, and any future platforms Apple might release. Most Apple developers would agree that SwiftUI has failed to deliver on that promise. In fact, Paulo's post is not the first I've read about SwiftUI's various inadequacies. Michael Tsai recently made a list of grievances professional SwiftUI developers have with the framework . I've been personally interested in getting back into building native Mac apps since at least the COVID lockdowns. But every time I've asked for advice on whether I should learn SwiftUI or AppKit, I've been met with the same answer: learn both. For somebody who has a full-time job and somewhat of a social life, this is untenable. It's just not possible for me to learn two new UI frameworks just as a cost of entry into the Apple developer ecosystem, no matter how motivated or skilled I might be. Meanwhile, long-time Mac users complain that nobody builds native apps anymore. To be fair, diehard Mac users have always complained about this, but I believe this time their complaint has legs. I don't see too many native Mac apps being built in 2026. The old stalwarts are still going strong—BBEdit, Things, Transmit, iA Writer, and all the rest—but pretty much every recent app I've used is built on top of Electron. It's easy to point the finger at Electron and React, or at CXOs that want to hire cheap frontend developers over expensive native developers, or at developers themselves, but I feel Apple is at least partially to blame for the state of the ecosystem today. I don't want to invest my time in an incomplete and buggy UI framework, and I certainly don't want to learn two UI frameworks just to try my hand at building a native app. I suspect most developers feel the same. Paulo ends his post with: You can see the result everywhere. SwiftUI is productive, modern, and often delightful, right up until you try to make a really good Mac app. Then suddenly you're fighting the framework for things the Mac solved 20 years ago. WWDC starts in two hours from the time I'm writing this post. Perhaps today we'll see some announcements that address some of these issues? Perhaps the Apple of 2026 will finally catch up with the Apple of 2006 in terms of software quality? Whether Apple cleans up their mess or not, Electron exists today and works fine . It lets you get your work out the door and into the hands of your users. It lets you build your business without worrying about what Apple will or will not do. As does React, which hasn't changed significantly since SwiftUI was announced.
Tutorial
“I am skeptical it achieves what Apple intends.”
Nick Heer’s analysis of Apple’s Pages interface over time is a nice counterpart to the recent post about Sinofsky doing the same for the early years of Microsoft Office . Here is the key comparison, 2011–2025: = 2x) and (width >= 700px)" srcset="https://unsung.aresluna.org/_media/i-am-skeptical-it-achieves-what-apple-intends/1.2096w.avif" type="image/avif"> = 3x) or (width >= 700px)" srcset="https://unsung.aresluna.org/_media/i-am-skeptical-it-achieves-what-apple-intends/1.1600w.avif" type="image/avif"> = 2x) and (width >= 700px)" srcset="https://unsung.aresluna.org/_media/i-am-skeptical-it-achieves-what-apple-intends/2.2096w.avif" type="image/avif"> = 3x) or (width >= 700px)" srcset="https://unsung.aresluna.org/_media/i-am-skeptical-it-achieves-what-apple-intends/2.1600w.avif" type="image/avif"> = 2x) and (width >= 700px)" srcset="https://unsung.aresluna.org/_media/i-am-skeptical-it-achieves-what-apple-intends/3.2096w.avif" type="image/avif"> = 3x) or (width >= 700px)" srcset="https://unsung.aresluna.org/_media/i-am-skeptical-it-achieves-what-apple-intends/3.1600w.avif" type="image/avif"> = 2x) and (width >= 700px)" srcset="https://unsung.aresluna.org/_media/i-am-skeptical-it-achieves-what-apple-intends/4.2096w.avif" type="image/avif"> = 3x) or (width >= 700px)" srcset="https://unsung.aresluna.org/_media/i-am-skeptical-it-achieves-what-apple-intends/4.1600w.avif" type="image/avif"> I’ll let you read the whole excellent analysis and Heer poking at the notion of “content over chrome” which feels dogmatically attractive, but needs deeper thinking which usually doesn’t follow. The interesting thing to me about that last screenshot above is that the team didn’t want a toolbar separated from content – and yet, they walked themselves into recreating a de facto toolbar anyway, just uglier and with more problems. (Just like designers who use all-white for complex surfaces , and arrive at visual hierarchy challenges that now require more work.) We’re a few hours away from WWDC. I don’t imagine we will see any direct response to the criticism of Liquid Glass as Apple doesn’t work that way , but it will be interesting to spot any indirect signs of reactions or course corrections. #apple #nick heer
Design
📝 2026-06-08 14:22
So I've been listening to #Spotify most of the day while working. Instead of playing my liked songs, I've just let it play whatever. This is the way! It's been banger after banger, and lots of great news tracks. Thanks for reading this post via RSS. RSS is ace, and so are you. ❤️ You can reply to this post by email , or leave a comment .
Music
“Each one of these buttons has four distinct purposes.”
A nice blog post by Nathan Manceaux-Panot on Pending Design about the subtle design of the tabs underneath the search results in the programming editor Nova: Through buttons right below its text field, the bar also lets you filter results: only show files, only show symbols, or only show symbols in current tabs. Here’s the thing, though: each one of these buttons has four distinct purposes . They’re not just for clicking. The tabs are clickable as they normally are, but they’re also a treasure map (to tell you something is possible), a cheat sheet (to remind you how to do it again), and an onramp for faster keyboard navigation. I’d add two more things to the celebration: = 2x) and (width >= 700px)" srcset="https://unsung.aresluna.org/_media/each-one-of-these-buttons-has-four-distinct-purposes/2.2096w.avif" type="image/avif"> = 3x) or (width >= 700px)" srcset="https://unsung.aresluna.org/_media/each-one-of-these-buttons-has-four-distinct-purposes/2.1600w.avif" type="image/avif"> = 2x) and (width >= 700px)" srcset="https://unsung.aresluna.org/_media/each-one-of-these-buttons-has-four-distinct-purposes/3.2096w.avif" type="image/avif"> = 3x) or (width >= 700px)" srcset="https://unsung.aresluna.org/_media/each-one-of-these-buttons-has-four-distinct-purposes/3.1600w.avif" type="image/avif"> The search pop-up always has a nice contrasty appearance: dark when the background is light, or vice versa. Many modern interfaces go for white background for every UI element and surface. This seems like solely an aesthetic choice, but has more consequences when it comes to visibility of things, and even hierarchy. I am personally always excited when I see a duochrome app these days, because it feels like the team knows what they’re doing and isn’t just chasing visual trends. (Below is an example from Bear.) = 2x) and (width >= 700px)" srcset="https://unsung.aresluna.org/_media/each-one-of-these-buttons-has-four-distinct-purposes/4.2096w.avif" type="image/avif"> = 3x) or (width >= 700px)" srcset="https://unsung.aresluna.org/_media/each-one-of-these-buttons-has-four-distinct-purposes/4.1600w.avif" type="image/avif"> #bear #coding #keyboard #onboarding #search I myself often forget onboarding is not just about the first run, but also about reinforcement . Here, this UI does a lot of reinforcing over time, helping you build the habit. Pressing the key highlights the tab. Clicking on the tab adds a key as if you pressed it, and so does using an advanced shortcut (e.g. ⌃⌘O instead of ⇧⌘O). Even slash as a symbol comes from path names, so you might naturally associate it with files. The search pop-up always has a nice contrasty appearance: dark when the background is light, or vice versa. Many modern interfaces go for white background for every UI element and surface. This seems like solely an aesthetic choice, but has more consequences when it comes to visibility of things, and even hierarchy. I am personally always excited when I see a duochrome app these days, because it feels like the team knows what they’re doing and isn’t just chasing visual trends. (Below is an example from Bear.)
Web Development
The Decline of Search Engines is an Opportunity
Enshittifcation is a blessing in disguise.
Google Buys Compute From SpaceX, Broadcom’s Outlook, Apple’s AI Politics
Google's deal with SpaceX, and Broadcom's earnings, both seem bullish for Nvidia. Then, what I'm looking for at WWDC.
Why I Didn’t Buy a New MacBook (Yet)
I currently use three laptops: a work-issued Windows machine that I use every day, a personal 17-inch Windows laptop that I used at my previous job (and subsequently bought from my employer when I left the company more than five years ago), and my trusty MacBook Air. My Mac is a 2017 MacBook Air - Intel i7, 8GB of RAM, and a 500GB SSD. It’s almost nine years old now. The battery gives me a few hours at best, it’s occasionally sluggish, and it doesn’t support multiple external monitors the way newer Apple Silicon Macs do. That’s particularly annoying because both of my Windows laptops connect to my home setup through a single dock. I have two home desks with almost identical setups because I work from home a lot, and my son and husband also use the docking stations to connect their laptops - it’s literally a case of plugging in one cable and you’re away. It’s seamless. My Mac doesn’t do that, but throughout its entire life with me I’ve mostly used it as a literal laptop on my lap - for writing, browsing, and general personal use. And of all the laptops I own, my old MacBook Air still feels the nicest to use. It’s light, comfortable, quiet, and just plain elegant. Despite its age and limitations, I still reach for it when I want to sit on the couch and write. So recently I started thinking that maybe it was time to update that experience with a new MacBook. The laptop I’ve been looking at is a 13-inch MacBook Air M5 with 16GB of RAM. On paper, it’s a massive upgrade. Better performance, all-day battery life, support for multiple monitors through a single dock., and a machine I could probably keep well into the mid-2030s. It would fit seamlessly into my existing home setup (apparently). The problem is that my current one still works. Pretty well. It’s not frustrating. The battery isn’t great, but I mostly use it at home or in a coffee shop for an hour. The more I sat with the decision, the more I got annoyed with myself. This has happened before. A few years ago bought an iPad Air and an Apple Pencil. I spent a huge amount of time on that decision - comparing models, watching reviews, mapping out use cases. I bought it. Then a few months (of agonizing over it) later I decided it would probably be even more useful with a keyboard, so I bought that too. I barely use either of them now. The problem was that I’d been buying a future version of myself - someone who would take notes in meetings or while reading, journal on an iPad, and create things. And for a while, I did. But it was never as seamless or friction-free as I’d imagined. At least not like it was in my head during those hours and hours of research. Or my new Kindle Paperwhite. I bought it to replace my very old Paperwhite, and yet I still use the old one most nights because it performs better in bed, in the dark, which is when I use it most. It’s smaller, the light is gentler in the dark, and somehow it just does the job better. What I’ve come to understand - and never really articulated to myself before - is that research creates its own momentum. The more time I invest in a decision, the more I start to feel like I should buy something, if only to justify all the effort I’ve already put into researching it. The MacBook Air replacement conversation was starting to feel very familiar. And exhausting. I don’t need a new MacBook. Not yet. I want one. I can afford one. I could even frame it as a reward for all my hard work or whatever. But should I? Round and round it goes until eventually I buy the thing and then feel disappointed because the purchase never solved the problem I thought it would. My MacBook is old, but it’s still good enough. Whatever I’d gain from a new one doesn’t feel like enough to justify the cost (and effort). If the battery or performance eventually gets bad enough that it genuinely gets in the way, I’ll replace it without guilt. Maybe I’ll replace the battery now and get another year out of it. It still feels great to use. I’m typing this on it now. What I keep coming back to is the difference between wanting a device and wanting the life you imagine you’ll have with it. In my case, I wasn’t really buying a MacBook. I was buying the fantasy version of myself who would finally finish that novel. The person who would take advantage of 18 hours of battery life to write for hours in cafés, on planes, or on top of some mountain somewhere. Never mind that my actual life doesn’t really allow for 18-hour writing sessions in the first place. Maybe I get an hour. Maybe two if I’m lucky. But would I use them for writing anyway? If I don’t on one of the three laptops I already own, why would I on a new MacBook Air?
I Love F1
by Gordon McLean Gordon has been hooked on F1 for 45 years, from childhood memories of Murray Walker to booking a trip to the Madrid GP. It’s a great look at how much the sport has changed and why he's still obsessed. Read post ➡ I discovered Gordon's blog after he commented on my recent note about F1 . I always check people's sites when they comment, as it's a great way to discover new blogs. Gordon's blog didn't disappoint - lots of great content on there, including this gem all about his love of the sport of F1. I've been following F1 for around 25 years now, and have similar memories as Gordon when it comes to thinking about some of the great drivers from the past. His post has me thinking about booking some ticket's to next years practice sessions for my wife and I (who's also a big F1 fan). Anyway, fun read. Thanks, Gordon. Thanks for reading this post via RSS. RSS is ace, and so are you. ❤️ You can reply to this post by email , or leave a comment .