Ordinary Abundance. This is the greatest thing I've read in weeks. No kidding. This should win a Pulitzer in a category not yet invented. ordinaryabundance.com/

New essay on the closure of the Internet, the mass censorship campaign that transformed every platform and the Internet as a whole from free and open to a closely monitored playpen 2015-2022. Longer than usual, around 27,000 words, so maybe best read in multiple sittings. Link in next post. Before 2015, the Western Internet was almost entirely free and open, except for actual criminal activity. Internet censorship was opposed by the major relevant institutions and seen as something distinctive to authoritarian states like Russia and China. Then within just a few years, every major platform (I cover YouTube, Reddit, Facebook, Twitter, Amazon, Wikipedia, and Google Search, as well as more general deplatforming of websites, forums and open source projects, and comments sections) created a colossal censorship apparatus with tens of thousands of human moderators, opaque and ever-shifting rules, and an entirely new field of machine learning spun up ex-nihilo.

I'm leaving X for some time to focus on building. But before I leave, I want to share some thoughts on where we are with AI right now. If you are building with AI, then this is for you. I wish I had at least 1% of @levelsio's reach already because I feel more builders need to hear this. TLDR: Your skills and good taste matter a lot. Be the most ambitious you've ever been and use AI wisely. Superintelligence is defined as systems exceeding all human capability across pretty much all domains imaginable, and especially strategic agency. Models like Fable 5 and K3 are superhuman in some domains like code generation and breadth of recall, but they are also subhuman in domains like long-horizon autonomy, physical-world interaction, sustained original research, good taste, etc. We are directing them, and they remain constrained by us humans and institutions. They're not behind the steering wheel yet. The tool hasn't become our master yet. We're still the master over the tool. The reality is, human actors of all kind, not just deeply technical ones, are wielding AI like a magic wand now, shaping the software economy at the speed of compute, throttled by their limited attention, human speed of expression and prompting. You reading this, you are special. Special in your own unique and wonderful way. And what AI gives you is an amplifier to express yourself, your ideas, your dreams, your imagination, and your ambition more than you ever could before. It seems unfair to us old-school coders who had to grind our ways through the dark coal mines, hiking through manual coding and debugging hell in order to create amazing software systems and apps. It's frustrating as to the moon and back to see your skills become irrelevant so fast, at least if you believe the narrative that you've wasted the better part of your life acquiring them. It is true that there is a certain, quite strong homogenization effect. Millions of people prompting to replicate or iterate on what's known must inevitably lead to a lot of overlap with structurally low diversity. AI produces convergent styles. It's in its nature, like that one designer doing all the designs for everything. In the same way we are also all starting to sound the same, being influenced by AIs way of expressing thought. X, and everyone's own social circle or audience, produces selection bias. It's skewing the reality we perceive based on what the people in our feed and around us talk about or show us. So we tend to oversample trend-chasing indie apps and undersample deep tech systems, enterprise systems, research tooling or domain-specific work that flies under the radar, below the clouds of hype or algorithmic push. Apps that took a year to make now take mere hours, it seems. It is both true and false at the same time. Superficially it is true because you get something that appears to behave like an app that was meticulously crafted over the course of an entire year by a talented engineer or even a whole team. What took so long can now be scaffolded with ease, by anyone. Engineers, chefs, strippers. Even our non-technical partners, friends and parents. Great. But when we dig deeper, the truth is that complex products require reliability engineering, security, compliance, integrations, support and so much more that in the end, even with this powerful AI we have now to help us go from A to B through something like an Einstein-Rosen-Bridge warping space and time, things take their good amount of time to get right. Less than they did before, all things equal, but not mere hours. Your skill is still highly relevant because AI amplifies you. It gives you leverage. The widespread idea that AI renders skill irrelevant doesn't compute, because either we have output quality that varies, in which case skill still differentiates, or it doesn't vary at all. And if it doesn't vary at all, the concept of "better" is meaningless. In other terms: A quality gradient can't exist in a flattened distribution. This is essentially your mathematical proof right there that your skill is in fact highly relevant. What AI did is, it raised the floor dramatically. It also raised the ceiling, but not as much as the floor. This somewhat compresses the skill relevance gradient, but it doesn't eliminate it in any meaningful way. When was the last time that access to powerful tools has resulted in broadly equal results? Never. There was a time you needed to have a degree in chemistry or something in order to be able to take and develop photos. My grandfather, a scientist, used to have a laboratory for that. Taking and then developing pictures required immense skill. Then one day digital cameras came along. Now any fool could take pictures, faster and easier than ever, thousands a day in full color or 3D even, instead of just 10 in monochrome. And yet, we all know that some people routinely take amazingly awe-inspiring photos, National Geographic front cover style that make us pause and look, while most others take tens to hundreds of photos a day that just end up clogging up our cloud drives. We all have access to the same English language, but not everyone writes equally well. The equalization applies to the generation layer that is commoditized, but not to our taste, judgement, distribution, trust, or timing. AI smashed through barriers to entry and brought them down like the Berlin wall. Now competition floods the market and drives economic profit toward zero in the layer that got commoditized, that is, the generation layer. Margins gravitate to zero, but not equally everywhere. So what is it that survives this kind of "commoditization of everything"? What do we do, if we drink this snake oil? The classic sets of moats persist. Distribution, brand, trust, network effects, proprietary data, switching costs, regulatory position, capital intensity, and any kinds of significant embeddedness. Yes, anyone can start using Claude Code & co and copy some app's code in an hour just based on screenshots. But it doesn't copy its user base, proprietary data in the cloud, its trust, its integrations or anything like that. There is a sense that AI forces us to rush, because everyone is working so fast now. Well, the race was always on. So how about speed-to-trend? It's a temporary edge at best, but not a long-term differentiator. The fruits that hang low are just being picked faster overall, by more hunters and gatherers searching for them. There is a widespread belief that all the value is going to accrue to the frontier AI companies in the end, who are the ones selling this immense power to everyone else. In fact it's a bit sad to see all these non-influencer vibe coders raising their hopes for nothing, buying the picks and shovels from the AI frontier labs to go dig for gold. It's like watching 100 ducks fight for a small handful of breadcrumbs, and it's funny until you realize they are essentially fighting for their survival. That's not how the world should be, right? Well, in reality the frontier AI companies spend astronomical amounts of money on research and development, including things like AI infrastructure and energy, training and inference, etc. They themselves are essentially ducks in the lake, fighting for their survival for breadcrumbs. They suffer competitive commoditization pressure as much as we do, just at a different level. At the model layer, rather than the generation layer. Structurally the winners are consumers and users who capture the surplus when production costs fall to the ground, but that of course doesn't really help us builders much, at least not those who have to make a living off of it. And, let's be real. It may seem funny to have AI spit out an app that someone else previously spent an entire year on creating meticulously by hand, and then upload that to compete. The opportunity is short-lived, and the cost of opportunity a lot are missing is this: The real gold rush is not that now you can make an app in a few hours instead of a year. The non-obvious that will become common sense soon is that an app that takes 2 hours to make is worth -5$ minus the value of your time + the value of demand which is likely $0 unless you have distribution, which you then burn with slop. The real opportunity that AI has opened up is WIELDING ENORMOUS COMPLEXITY x EXCELLENCE. Just imagine for a moment what you could accomplish, if only you would take this new superpower, your amazingly valuable skills, your great taste, your power of imagination, and do something that is outrageously AMBITIOUS! Something that makes others think you must be absolutely mental to even think for a second that it could be accomplished. And then go and work for a full year on just that, utilizing AI to the fullest extent possible. Milking the beast until its dry. What will that be? No, not another Bumble clone. Not another weather app. For AI's sake, please, not an "app" at all. But something that the world actually needs. Think about it! Think bigger! And when you thought you've thought bigger, think even bigger. You're still aiming too low. THINK BIGGER! Here is my bucket list of things I want to accomplish before I die. - A platform that solves the number one root cause of poverty for good, giving everyone a fair chance at living a good life free of financial worries (it's far more than a "platform"). - A floating city in international waters, driven and governed by AI under a human charter (capital intensive, long story, and yes it will be fundable and doable) - A digital twin of Earth for climate analytics, climate communications and Earth sciences education (the world's most advanced nature simulation by far, unlike anything you've ever seen or heard of) - Truly reliable, explainable AI that can reason through complex systems and across extremely vast design spaces without stalling under the pressure of combinatorial explosion, laying the foundation for generative engineering so we can work on great and complex things like the USS Voyager and other incredible things far beyond today's vibe coding - Something so insane, they would lock me up just for saying it out loud A good heuristic: If talking about it doesn't make you sound like a complete lunatic, and building it doesn't scare you, you're probably aiming too low and the thing you're about to do will be commoditized rapidly (or is already). Gone building. Back when there's something to show.

Damn @awscloud why you gotta do me like that?

Let's goooo!

I did a deep dive into our 290 LTO deals at @afternic and discovered some valuable insights concerning cancellations, early payoffs, and trends. 📉 Cancellation Rates Our raw cancellation rate was 26.9%, but that understates risk because it counts active deals as non-cancellations. A better number is the resolved cancellation rate: cancellations divided by completed LTOs. Historically, among our LTOs that have reached an outcome, about 59% completed successfully and 41% were cancelled. ⏱️ Cancellation Timing Cancellations are heavily front-loaded. Obviously the more payments they make the less likely they are to walk away at the next payment. But at what point are they really committed? Of our 78 cancellations, 28 (36%) made only one payment, 40 out of 78 (51%) made at most two payments, and 63 out of 78 (81%) made at most six payments. Once a deal avoids cancelling after only one payment, its resolved success rate rises to about 70%. Once a deal avoids the early churn window and gets to around six payments, the resolved success rate rises to around 86-88%. 📆 Cancellation and Term Length Most of our LTOs (87%) were in the 12-23 month range, so I'm not sure how statistically significant this data is. But there was a pretty clear pattern that the longer the length of the LTO, the higher the raw cancellation rate was. The raw cancellation for LTOs less than one year was 25%, for 12-23 months it was 25.3%, for 24-35 months it was 31.2%, and for 36+ months it was 53.8%. You might think the longer the term, the more manageable the monthly payments are, and the more likely they'll be to stick around. But in this dataset, longer terms were clearly riskier. Personally, I’d be cautious offering terms longer than 24 months. 💳 Cancellation and Monthly Payment Looking only at 12-month LTOs, the raw cancellation rate was essentially the same for sub-$200 monthly payments vs $200-299 payments vs $300-499 payments. But interestingly, once the monthly payments reached $500+ the raw cancellation rate dropped by more than 50%. That's somewhat intuitive though, someone committing to a $500+ monthly payment is probably more serious and well-funded. 🤔 Confusing Cancellations Three buyers cancelled with only one payment left, which seems pretty unbelievable. In 8 cases, a cancelled LTO later sold again shortly afterward — 6 through LTO and 2 through BIN. The data doesn’t include buyer identity, but given normal domain sell-through rates and the short timing, these were very likely buyers coming back after missing a payment or regretting the cancellation. ⚡ Early Payoffs 17% of completed LTOs were paid off early. Nearly half of early payoffs happened close to the finish line, but of the early payers, 32% paid off after only 1–2 payments. 📈 LTOs By Year 2023: 13 (53 annualized) 2024: 106 2025: 114 2026: 57 (137 annualized) We're seeing a steady trend upward as LTOs stack up. 🎁 Wrap Up I hope this helps you get a better picture of what you might experience if you enable LTOs. The interesting takeaways for me were how heavily front-loaded LTO churn is, how longer terms reduce your odds of success, how little the monthly payment amount affects the odds except at the high end, and how more than 10% of cancelled LTOs still ended up in a sale shortly after.

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

What happens when you post a real Monet and say it’s AI? The coolest art social experiment I’ve seen in a while. Thank you @SHL0MS

We used to go to a special website, ask strangers for help with programming, and get humiliated in return

Young Australians should be enraged by the new super tax. The statist talking heads will tell you "it's only on balances above $3M. The rich." Most Aussies will fall for it. Run the numbers. 35yo today. $200k in super. Contributes $15k a year. Earns 8% returns (long run super average). In 30 years their balance is $3.7 million. Caught by the tax. But here's the trick. Australia's money supply has grown about 8% a year for the past two decades. RBA's own data. So that $3.7M buys what $369k buys today. Same groceries. Same house. Same petrol. You didn't get rich. You ran on the spot. And the $3M line? Frozen. In 30 years it only buys what $300k buys today. It's lost 90% of its real value. The govt doesn't have to move the line. Inflation does the work for them. No different from the obscene overreach on anti-money laundering rules. The $10k cash transaction threshold was set in 1988 and never moved. $10k then is $26k in today's money. Adjusted for money supply growth, it's $170k. Same threshold. Almost 3x more transactions caught by CPI, 17x by money supply. That's why you get interrogated at the bank for withdrawing what only covers half a year of school fees. Same trick with income tax. Wages rise with inflation. Brackets don't. Suddenly the average worker is in a "high earner" bracket they were never meant to be in. You don't earn more. The line moved. This one policy tells you everything you need to know about the government and its intentions. It's all about grift and theft. Meanwhile, the kids who get hit hardest are kept busy by an education system arguing about hate speech, social media, and the climate apocalypse promised in 2012. Nobody teaches them how money actually works. The govt likes it that way. So they vote for more taxes. Bigger govt. More "fairness." Pouring petrol on the fire burning their house down. The fix isn't communism. It's the opposite. Smaller govt. Lower taxes. Index every threshold to the actual money supply, not the CPI lie. Decentralise the banks. Despite everything, Australians are entrepreneurial and predominantly hardworking. Imagine what this country could become without the government's boot on its neck.

Effective today, we are: 1) Doubling Claude Code’s 5-hour rate limits for Pro, Max, and Team plans; 2) Removing the peak hours limit reduction on Claude Code for Pro and Max plans; and 3) Substantially raising our API rate limits for Opus models.

Hello Julia, sans aucune ironie, c'est top que tu prennes le temps de te renseigner. Mais le problème quand on lit Marx aujourd'hui, c'est qu'on prend pour acquis sa prémisse de départ, alors qu'elle a été démontée scientifiquement il y a plus de 150 ans. Toute la pensée de Marx repose sur la théorie de la valeur-travail. L'idée que la valeur d'un bien vient de la quantité de travail nécessaire pour le produire. Si tu acceptes cette prémisse, alors oui, tout son raisonnement tient. Le capitaliste "vole" la plus-value du travailleur, l'exploitation est mathématique, la révolution est inévitable. Sauf qu'en 1871, trois économistes (Menger en Autriche, Jevons en Angleterre, Walras en Suisse) découvrent indépendamment la même chose : la valeur n'est pas objective, elle est subjective et marginale. Un verre d'eau dans le désert vaut une fortune. Le même verre à côté d'une rivière ne vaut rien. Le travail incorporé est identique. Donc le travail ne détermine pas la valeur. C'est le consommateur qui valorise un bien selon son utilité marginale dans un contexte donné. Exemple concret : tu peux passer 1000 heures à tricoter un pull moche que personne ne veut. Selon Marx, ce pull a énormément de valeur (beaucoup de travail incorporé). Selon la réalité, il ne vaut rien. Parce que personne n'en veut. À l'inverse, Bernard Arnault crée des milliards de valeur non pas parce qu'il "exploite" mais parce qu'il a su anticiper et organiser des désirs humains à grande échelle. La valeur est créée par la coordination, pas extraite par le vol. Cette découverte (la révolution marginaliste) a invalidé tout l'édifice marxiste. Pas pour des raisons idéologiques, pour des raisons scientifiques. C'est pour ça que plus aucun département d'économie sérieux au monde n'enseigne Marx comme un cadre d'analyse valide. On l'enseigne en histoire de la pensée. Maintenant, le truc important. Si ton intention en lisant Marx c'est d'aider les pauvres (c'est une intention noble), alors tu vas être surprise par ce qui suit. Regarde les chiffres de la Banque mondiale. En 1820, 90% de l'humanité vivait dans l'extrême pauvreté. Aujourd'hui, moins de 9%. Cette chute historique ne s'est PAS produite dans les pays qui ont appliqué Marx. Elle s'est produite dans les pays qui ont libéralisé leur économie. Chine post-1978, Vietnam post-1986, Inde post-1991, Pologne post-1989. À chaque fois qu'un pays libéralise, des centaines de millions de gens sortent de la pauvreté en une génération. À chaque fois qu'un pays applique Marx (URSS, Cambodge, Corée du Nord, Venezuela), c'est la famine et les goulags. Ce n'est pas une opinion, c'est l'expérience la plus massive jamais menée en sciences sociales. Plusieurs milliards de cobayes humains, sur un siècle. Donc paradoxalement, si tu aimes vraiment les pauvres, la position la plus cohérente n'est pas d'être marxiste. C'est d'être pour la liberté économique. Parce que c'est empiriquement la seule chose qui a jamais sorti massivement les gens de la misère. Pour creuser, je te recommande trois lectures qui vont changer ta vision : "La Loi" de Frédéric Bastiat (court, lumineux, gratuit en ligne) "La Route de la Servitude" de Hayek "Économie en une leçon" de Henry Hazlitt Bonne lecture, et vraiment chapeau de chercher à comprendre plutôt que de rester dans tes certitudes. C'est rare.

True multimodal AI needs to understand the world spatially 🎯 🚀 Excited to release #CVPR2026 TIPSv2 from @GoogleDeepMind, a foundational image-text encoder with spatial awareness, leading to strong overall results and massive gains on patch-text alignment. 🔥 1/N

My dear front-end developers (and anyone who’s interested in the future of interfaces): I have crawled through depths of hell to bring you, for the foreseeable years, one of the more important foundational pieces of UI engineering (if not in implementation then certainly at least in concept): Fast, accurate and comprehensive userland text measurement algorithm in pure TypeScript, usable for laying out entire web pages without CSS, bypassing DOM measurements and reflow

Australia Fuel Outage Checker is now live! ⛽️🔗 = checkpetrol.com.au PetrolCheck shows current outages, prices & overall fuel supply stats based on publicly-available API data. Users can report fuel outages and submit new data. See below for more details 🔽

Of course that's your contention. You're a first-time SaaS bear. You just got finished listening to some podcast, Dario on Dwarkesh, probably. Now you think it’s the end of white collar work and seat-based pricing is screwed. You're gonna be convinced of that til tomorrow when you get to “Something Big is Happening”. Then you’ll install ClawdBot on a Mac Mini, vibe code a dashboard on top of a postgres database and say we’re all just a couple ralph loops away from building a Salesforce competitor. That’s gonna last until next week when you discover context graphs, and then you're gonna be talking about how the systems of record will be disintermediated by an agentic layer and reposting OAI marketing graphics. “Well, as a matter of fact, I won't, because ultimately the application layer is just ….” The application layer is just business logic on top a CRUD database. You got that from Satya’s appearance on the BG2 pod, December 2024, right? Yeah, I saw that too. Were you gonna plagiarize the whole thing for us? Do you have any thoughts of your own on this matter? Or...is that your thing? You get into the replies of anyone posting a SaaS ticker. You watch some podcast and then pawn it off as your own idea just to impress some VCs and embarrass some anon who’s long SaaS? See the sad thing about a guy like you is in a couple years you're gonna start doing some thinking on your own and you're gonna come up with the fact that there are two certainties in life. One: don't do that. And two: you dropped thirty grand on Mac Minis and LLM API calls to come to the same conclusion you could’ve got for free by following a handful of VC accounts.