via:

How Amsterdam is Reviving the Fine-Grained Courtyard Block

At Centrumeiland, a new district in Amsterdam’s IJburg expansion, the city is avoiding one of the great failures of contemporary urban development, the large-parcel megaproject. Rather than handing the 37 acres over to a few large developers to build massive, hotel-like buildings, Centrumeiland is subdividing the site into perimeter-block parcels, assigning each parcel a buildable role through a plot “passport,” and enabling many smaller actors to build within one coherent urban framework.

Begun in 2013 as part of Amsterdam’s IJburg land-reclamation project, Centrumeiland modernizes the old perimeter-block model for contemporary goals. It will be dense, but green; urban, but family-oriented; highly planned, but open to many builders. Amsterdam plans roughly 1,500 to 1,700 homes on the 37-acre island, or about 40 to 46 homes per acre. By American standards, that is serious density. But it is not being delivered as a monoculture of towers or double-loaded apartment blocks. Centrumeiland includes a mix of housing types and tenures: large family-sized homes, smaller rentals, social housing, mid-market housing, market-rate condos, individual self-build houses, collective self-build projects, housing-association buildings, and developer-led apartments.

The ambition is a dense urban neighborhood that can serve households across the lifecycle: singles, couples, families with children, older residents, renters, owners, and collective building groups. It also adapts the perimeter-block tradition to contemporary priorities: low-car living, accessibility, climate resilience, mixed tenure, family housing, and broader participation in development and ownership.

All of this depends on the subdivision and passport system. Amsterdam breaks the large site into many buildable pieces, assigns each parcel a role through a plot passport, and holds the pieces together through streets, blocks, party-wall conditions, courtyards, public-space rules, and environmental obligations. In this way, they have brilliantly resurrected the old urban formula that allows many builders to participate in the development of a large site, making a real neighborhood.

For American cities, the moral of the story is clear. On large brownfield and greenfield sites, cities should stop treating whole districts as single development packages to be handed to master developers. They should do the more civic work first of laying streets, subdividing land into buildable parcels, and issuing clear “parcel passports” that specify what each site can become. In existing neighborhoods, the same logic should operate at a smaller scale. Cities should create transit-oriented overlays that give ordinary private lots clear building rights that make great multifamily housing easier to finance, permit, and build.

Centrumeiland goes far beyond “build more housing.” It is more radical and more urbane. Divide the land, write good code, and let many hands build the city.

The Megadevelopment Trap

For the last half-century, large urban sites have met a sadly familiar fate. A railroad, port authority, public agency, hospital, university, or industrial landowner controls a vast tract of developable land. The master-planning process then carves it into a few enormous parcels and awards them to one or several major developers. After years of negotiation, public fights, redesigns, entitlement battles, and financing risk, the developer may finally build the megaproject, which is widely reviled by the public.

Megaprojects may be economically productive. They can deliver housing, offices, parks, retail, transit, and tax revenue. But the development model itself is thin. Too few actors control too much land. The parcels are too large, the buildings are too big, and the building code and underwriting norms push toward deep floorplates and double-loaded corridors. The buildings are dominated by small, expensive, hotel-like units that are poorly suited to middle-income families who need light, storage, bedrooms, outdoor access, and a sense of domestic permanence. These districts may be a success on paper (for now), but they make failed neighborhoods, lacking the social depths and street life that is the reward of fine-grained courtyard urbanism. [...]

The problem is the development system. A megaproject cannot make a great neighborhood. Neighborhoods require many actors, many front doors, many ownership structures, many building types, many ground-floor conditions, and many small adaptations over time. They need private yards. They need a public framework strong enough to coordinate many actors.

That is the old art of division and perimeter block planning Centrumeiland begins to recover.

Making Land Into City

Centrumeiland is part of Amsterdam’s IJburg expansion, a chain of artificial islands built in the IJmeer on the city’s eastern edge. IJburg extends Amsterdam outward into the water between the historic city and the open landscape of the Markermeer, turning what was once lakebed into new urban land. Centrumeiland sits within this larger archipelago, connected back to Amsterdam by bridges, cycling routes, bus service, and the IJtram to Amsterdam Centraal. It is therefore both peripheral and deeply urban, a new island neighborhood made from water, but tied into the metropolitan fabric of Amsterdam.

While the land reclamation is impressive, even more remarkable is the public framework that governs the development. The city divided the land into kavels, and created parcel-specific rules through kavelpaspoorten, or plot passports.

A passport can define the parcel boundary, buildable envelope, maximum height, frontage condition, access requirements, open-space obligations, water-management rules, parking expectations, program, tenure, sustainability requirements, and sometimes ground-floor use. It tells a builder not merely that “residential” or “commercial” is allowed, but what kind of urban contribution this specific piece of land is supposed to make: a row of townhouses, a small apartment building, a collective self-build project, a social-housing block, a mid-market rental building, a mixed-use corner building, or a larger perimeter-block parcel with shared courtyard space.

The subdivision and passport framework enables much broader participation in the development. Of the planned 1,500 to 1,700 homes, roughly 60 to 70 percent are intended to be self-build. But “self-build” here does not only mean one household designing one eccentric house. It includes individual self-builders, small groups, collective private commissioning, building groups, housing cooperatives, and other resident-led or small-group development structures...

Its lesson moral here is that parcelization broadens participation and creates more development pathways than the master-developer model. [...]

The American Application

For American cities, the lesson is to create a modern urban passport system.

There are two obvious applications: large-site development and existing-neighborhood overlays.

On brownfield and greenfield sites — former industrial land, rail yards, malls, hospital campuses, public land, waterfronts, and other large redevelopment areas — cities should stop defaulting to the megaproject model. They should lay out streets first, shape interesting blocks, design public spaces, subdivide land into buildable parcels, and assign parcel passports. Those parcels could then be allocated to many actors: small developers, cooperatives, housing associations, community development corporations, nonprofit builders, resident-led groups, and larger developers where appropriate.

Large developers may still participate. But they should not control the whole district. The city should not ask one actor to simulate the complexity of a neighborhood.

by Alicia Pederson, Courtyard Urbanist |  Read more:

Images: uncredited

Betting on Humans

What to do about AI & jobs.

Now, the great majority of people—whether they are “blue collar” or “white collar” laborers—spend their working hours orchestrating machines of various kinds: some to transform knowledge or bits, and others to transform atoms. Yet just a few decades ago, it would have been impossible to understand what it is that most people today call “work.”

Today, a relatively small group of technologists is starting to see the world through the lens of another fundamental discovery: deep learning, the approach to AI that has enabled machines to think and undergirded substantively all major advancements in AI over the past decade. And like their forebears at the beginning of the Industrial Revolution, these technologists are building new machines, uniquely enabled by the insights and abstractions furnished from the new science. Some believe new types of labor will emerge, concentrated on the orchestration of machines, or the tasks that remain best suited to the human touch. Others believe this time is different, and that human labor will soon be permanently obsolete.

We do not pretend to know the definitive answers. What we do know is that much of this future remains to be written, in no small part by the policy choices we make today. And what we hope to offer is a roadmap for how politicians and policymakers might bet on human agency under stark uncertainty.

Futures Not Yet Written

There are two fundamental stories one can tell about the impact of artificial intelligence on human labor. One is the pessimistic version: most of us are like the people in the early Industrial Revolution who could not learn to adapt or were stuck as mere cogs in factories. Very few of us, if any, will learn to orchestrate machines at a higher level of abstraction, and neither will we learn to invent new machines, since the artificial intelligence systems will soon exceed humans in their capacity for invention and discovery. That view is one of historical discontinuity: replacing knowledge work strikes deeper at the human uniqueness that has kept us employed than replacing various kinds of cognitive and manual labor has in the past.

The other story is optimistic: just like those early conductors and inventors of machines, we will continue our long human legacy of finding yet more to occupy our time, yet more activity that other humans find valuable. There is much more of this than we can possibly realize, because our collective imagination is bounded, yet our collective wants are limitless. How barren, in retrospect, do we find the mind of the man who thought the human touch was gone simply because we had invented machines stronger, more durable, and more reliable than us at physical labor?

Both stories will probably be true at the same time, but the unfortunate reality is that nobody knows in what proportion. More unfortunately still, it will be some time until we know: the temporary disruption that would portend broad displacement would look quite similar to the creative destruction that would come with just another industrial revolution. It’s easy for policymakers who first start to grapple with the notion of advanced artificial intelligence to reflexively adopt the pessimistic view: for so long, they’ve heard the idea that AI will be important and the idea that many jobs will be lost in the same breath that coming around on the scope of AI seems to imply believing that human labor is doomed. But that would be premature, and converts must resist becoming zealots.

Here, then, is the first—and in some sense the most troubling—message for policymakers: nobody can know what is going to happen. Anyone speaking with confidence about predictions of this kind is either misunderstanding or misleading. It is not just that we do not know “the future,” in some broad sense. We also do not know the specific nature of any problems posed by AI to the labor market: we do not know what industries, age groups, levels of seniority, job types, and so on will be affected by AI automation in practice rather than in theory or in speculation. We do not know over what timeframe these still-hypothetical changes will occur.

And if AI really does profoundly upend the labor market, we still do not know what the resulting distribution of economic resources will look like. Will the AI labs profit immensely, absorbing huge swathes of economic value as many other institutions struggle to survive? Or will AI models and systems become commodified, with value accruing to the compute designers and manufacturers? Or is it some hybrid, with most firms in the economy seeing higher profits with fewer employees and, for whatever reason, not seeing a need to hire additional people to do anything? Will there be new, high-skilled jobs created that we need to retrain millions of people for? Or will there be no new jobs at all? We do not know, and we cannot know.

That is because we are still in the process of writing this future. The role of humans in future economies is not something we simply discover as it occurs. How we distribute tasks between humans and machines is largely downstream of a web of complicated economic incentives and technical features. Is the marginal unit of computing power better spent on smoothing over the jagged frontier so no role remains for humans, or for even further improving the spikes of AI capability? Does the tax system favor firms who spend the marginal payroll dollar on hiring a worker to oversee the machines or an agent to do the same? Is there a safety net to catch those hit by local disruptions to give them the room to reorient themselves, come back five years later, and fight for their place in a new economy—or do we mollify their drive with ill-placed subsidies long enough for them to grow docile and for the structures around them to calcify? All this is contingent, and when policymakers ask ‘what will happen’, they fail to see that they’re among the central live players in this question.

How should our leaders grapple with this double uncertainty of what they should want and what will happen?

by Anton Leicht and Dean W. Ball, Threading the Needle |  Read more:

Image: via

[ed. Spoiler alert: Zvi provides a quick (and incomplete) summary (DWAtV):] 

***

"Anton Leicht and Dean Ball team up to write about what we should do about potential job loss due to AI, from the perspective of prospective ‘de facto normal technology’ AI worlds even if they don’t call it that. They wisely say we don’t know what will happen, and that the ‘no regrets’ actions will be insufficient so solve the problem, but expect the world to stay normal enough, and humans competitive and useful enough, that we can use traditional solutions to such problems.

They start with easy wins.

1. Even footing: Equalize tax treatment of AI versus labor. Yes, please.

2. Retraining: Bolster workforce training and development. They notice they are skeptical in practice, and I am even more skeptical, but sure, we can try it.

3. Measurement: Know what is happening. Yes, of course.

Then they recommend what they call difficult bets.

4. Junior Job Subsidy.

Anton Leicht and Dean Ball: We put to you that the solution to deal with junior job losses might be to keep these jobs around by brute force for a while, so that the critically important economic incentive to explore how to use junior workers does not cease.

More specifically, we might do so by restructuring the tax code to subsidize junior employment.

Given who is saying to keep jobs around by brute force, by which they mean tax incentives, we should listen. This seems like a good use of progressive taxation, which we want to do anyway, to stack the deck in favor of hiring more young workers and those switching industries, presumably with phase outs for high earners.

This risks distortions if taken too far (e.g. dumping senior workers for subsidized junior workers, or gaming designations), the marginal value of young workers could easily fall below zero marginal product if there is no future for them, and gating to particular industries or occupations risks going into ‘picking winners and losers’ and other similar dangerous territories and opportunities for corruption and pork. The authors are well aware, and are pushing anyway.

The main solution they offer is, again, taxes. They suggest doing so via raising corporate taxes, despite this having a long track record of being highly economically damaging. You definitely need to avoid worse distortions, and you definitely do not want a ‘token tax’ as such for this reason, although a tax on compute is non-crazy. Taking a stake in frontier developers is definitely an error.

They quickly dismiss consumption taxes as having a fatal perception problem, despite them being objectively the efficient answer, because they raise prices and signaling is too important here. I found this disappointing, and there are ways to fix this and also make the tax progressive.

It would be great if humans remained fundamentally highly productive while we collectively got far wealthier due to AI, so all we needed to do was redistribution and moving the tax code around.

Alas, no, I do not expect we live in such a convenient world. At which point, we likely have bigger problems, but also employment does not get solved with basic tax code shifts. If we stay in control somehow then we could do progressive redistribution to keep food on the table and a roof over people’s heads, but the jobs will vanish, or they will be rather fully fake."

Why Japanese Companies Do So Many Different Things

Consider Toto.

If you spend much time in American public bathrooms, or rather if you’re simply a particularly attentive patron of American public bathrooms, you’ll probably have noticed Toto’s toilets at some point or another: they’re distinguished by a quite memorable serif-font “TOTO” logo. Toto toilets aren’t quite dominant in American bathrooms, since they have healthy competition from our homegrown toilet champions American Standard and Kohler—though Toto is doing better and better as Americans start to fall in love with the bidet-toilet—but globally Toto is the world’s largest manufacturer of toilets and bidets. And in its home country of Japan, Toto is simply everywhere: 80 percent of Japanese homes contain a Toto bidet-toilet.

And if you’re a longtime Toto shareholder—maybe an investor with a particular interest in bathroom fixtures—this has been a wonderfully lucrative year for you. Toto’s stock is up 60 percent year to date; in just the last few weeks, it’s risen by 30 percent. Toto is doing better than ever: its net profit, in the first quarter of 2026, was up 230 percent year over year.

But Toto’s remarkable year doesn’t have much to do with toilets or bidets. Toto might have been founded in the 1910s to “provide a healthy and civilized way of life” through affordable toilets, and in the decades since might have become the global leader in the bathroom game. But Toto also does a lot of other things. Toto manufactures not just bidets and toilets but also bathroom tiles, prefabricated bathroom modules, faucets, modular kitchens, photocatalytic coatings for buildings, and assistive equipment for the elderly. And, most importantly, Toto has a very lucrative sideline in the fabrication of memory chips.

Since 1988, in a once-obscure corner of the company called the “advanced ceramics division,” Toto has been producing a very particular component called the electrostatic chuck, or the “e-chuck.” The e-chuck is a sort of high-precision ceramic plate, about the size of a steering wheel, that uses electrostatic force to hold a silicon wafer perfectly flat and thermally stable while memory chips are etched into it with bombardments of plasma. Making these components is extraordinarily difficult, since the ceramic body needs to have near-zero particle generation and be polished to submicron flatness: and this means that there are only a few companies in the world that are capable of manufacturing e-chucks reliably. Almost all of them—Shinko Electric, NGK, Toto, Kyocera, Sumitomo Osaka Cement, Niterra—are based in Japan.

For most of its history, the advanced ceramics division was a rounding error on Toto’s balance sheet: the money maker, as it had been since the 1910s, was the toilet and bidet business. But we’re in a new era. Demand for AI is exploding, meaning that demand for the high-bandwidth memory that AI data centers require is exploding, meaning that demand for memory chips is exploding, meaning that demand for e-chucks is exploding. And so Toto’s advanced ceramics division is suddenly the company’s largest business, generating the majority of its operating profit. Toto’s leadership, suddenly awash in AI-driven revenue, announced that they would double down by investing hundreds of millions in expanded electrostatic chuck production: the toilet company had become, quite unexpectedly, a supplier to the semiconductor supply chain.

The Toto story is a fun and interesting illustration of corporate diversification and how strange bets can pay off. But that type of diversification—a toilet company that also produces photocatalytic coating and high-precision components for semiconductors—isn’t really unique to Toto. Practically every company in Japan seems to do a thousand very different things.

Consider, for example, Kyocera, another one of the e-chuck makers. Kyocera was founded in 1959 as a producer of ceramic insulators for cathode-ray tubes; today it manufactures not only industrial ceramics but also printers, smartphones, ballpoint pens, kitchen knives, solar PV modules, lens components, industrial cutting tools, automotive camera modules, electronics components, semiconductor packaging, biocompatible tooth and joint replacements, UV-LED curing systems, LCD systems, medical products, and lab-grown gemstones. Or another e-chuck maker. Sumitomo Osaka Cement, as you might have been able to deduce from the name, produces cement and ready-mixed concrete; but it also produces optical components, measuring instruments, industrial ceramics, artificial marine reefs, cosmetics and nanoparticle materials.

And this degree of diversification extends to many of Japan’s most famous companies. Yamaha, for example, manufactures pianos, motorcycles, guitars, drums, boats, snowmobiles, ATVs, audio equipment, golf clubs, tennis rackets, home appliances, specialty metals, molding and bonding equipment for semiconductors, and industrial robots. Hitachi makes nuclear reactors, power grids, railway systems, elevators, semiconductor manufacturing equipment, medical imaging devices, data storage, IT consulting, and industrial machinery. Even a company as simple as Oji, Japan’s largest paper company, has been drawn into the production of disposable diapers, functional films, adhesives, cellulose nanofibers, and wood-based EUV photoresists; and it also operates a hotel, an airport catering business, a concert hall, and an insurance agency.

All of which is to say: Japanese companies do a lot of things.

There are, of course, other countries with companies that “do lots of things”: much of Indian economic life, for example, is defined by the sprawling activities of a few large business clans—the Adanis, the Ambanis, the Tatas, the Birlas. But India is a relatively poor country with a low level of economic specialization, and the sprawling conglomerates that dominate its economy focus on relatively simple things like cement, steel, ports, and telecommunications. Japan, by contrast, is a wealthy, developed society—by one measure, the most economically complex country in the world. What’s striking about Japanese companies is not that they do lots of different things but rather that they do them very well. There are all sorts of high-precision inputs—the e-chuck being just one example—that are produced virtually only by Japanese firms.

This is very different from how most wealthy countries operate. American firms, for example, tend to prioritize focus above all else: it would be bizarre for an American paper mill to also operate a concert hall and an airport catering business, or for American Standard or Kohler to somehow have something to do with semiconductors. Even a country like Germany, which matches Japan in its depth of high-precision firms, has nothing like Japan’s corporate diversification. Only a few large conglomerates, like Siemens, have anything approaching the lateral breadth of the Japanese firm. South Korea—whose economic system was not coincidentally modeled off the Japanese one—does have a few chaebol conglomerates, like Samsung and SK, that truly do as many things as Japanese companies. But these are economy-dominating, state-entangled megafirms, cultivated as national champions by Korean industrial policy. They look nothing like, say, Sumitomo Osaka Cement, which is hugely diversified despite being relatively small. (“Look what they need to mimic a fraction of our power!”)

So why are Japanese companies like this? Why do they do so many different things? And how do they manage to do so all those different things so well?

Here is the answer I want to suggest: Japanese companies excel in lots of very different domains because it’s inherent in how they’re structured. The form of the corporation that we know and love in the United States—specialized, market-oriented, governed by shareholders—is just one form that the corporation can take; but it’s not the only way to coordinate capital and labor in a successful and profitable way. The protean corporations of Japan are best understood as a different species of thing altogether: better at some things, worse at others, but still highly adapted to their particular environment. And the things that they’re very good at turn out to be extraordinarily helpful for all sorts of things in which American companies tend to struggle.

by David Oks, Website |  Read more:

Image: uncredited

Fender Demands Builders Stop Making Stratocaster-Style Guitars

Following on from its legal victory regarding the Stratocaster trademark in March, a law firm claiming to represent Fender Musical Instruments Corporation has reportedly sent cease and desist orders to a variety of guitar makers demanding they stop producing instruments that use the Stratocaster design.

Back in 2009, Fender lost a high-profile US case when the brand attempted to file trademarks for the Stratocaster, Telecaster and P-Bass body shapes. At the time the filing was protested by a group of other guitar makers, who ultimately succeeded in having the trademarks cancelled.

In the years since, it was widely assumed that this defeat – following on from Gibson’s 2005 loss in a lawsuit against PRS in 2005 – gave other builders the freedom to use classic body shapes, provided that they didn’t infringe on things like headstock shape.

However, Gibson’s protracted but ultimately successful battle against Dean Guitars over the Flying V body shape showed that the big brands still have the ability to win these cases in the right circumstances. [...]

The Fender ruling, crucially, was NOT a trademark dispute – Fender and Gibson have both lost trademark cases on their body shapes in the EU in years past – but sought to reframe the Strat’s body shape as an artistic work, subject to copyright, instead.

by Josh Gardner, Guitar.com |  Read more:

Image: YouTube/uncredited
[ed. Idiots. Destroying decades of history, goodwill, and brand loyalty with one dumb letter. See also: Is this the beginning of the end for the S-style? (Music Radar).]

Your Backpack Got Worse On Purpose

VF Corporation started as Vanity Fair Mills. Bras and underwear. They paid $762 million for a company called Blue Bell and picked up JanSport in the deal. That acquisition made them the largest publicly traded clothing company in the world.

Then they went shopping.

In 2000, they bought The North Face. Same year, they bought Eastpak. In 2004, Kipling. In 2007, Eagle Creek. By the time they were done, VF Corporation controlled an estimated 55% of the US backpack market.

More than half. One company.

Every time you stood in a store in the 2010s and compared a JanSport to a North Face to an Eastpak, you were comparing three labels owned by the same parent corporation. Same earnings call. Same margin targets. Same quarterly pressure. The sense that you were choosing between competitors was a fiction that VF Corp had no incentive to correct.

Competition is what kept these brands honest when they were independent. If JanSport built a shitty bag in 1985, you walked across the aisle and bought an Eastpak instead. That threat disciplined every material choice, every stitch count, every zipper spec. Once they all report to the same parent, the discipline evaporates. Nobody needs to outbuild anybody. The only pressure left is the one coming from above: hit the margin target.

The easiest way to hit a margin target is to make everything a little worse, across the board, all at once.

What they changed

Denier count is the most measurable indicator of fabric durability. It measures fiber thickness. A bag made with 1000-denier Cordura nylon can survive years of daily use. Drop that to 600-denier polyester and you have a bag that looks identical on the shelf and lasts half as long.

Denier counts dropped across VF Corp's backpack lines.

YKK makes the best zippers on earth. They're Japanese, they cost more per unit, and brands that care about longevity use them because a zipper failure kills a bag faster than fabric wear. On VF Corp's lower-tier models, YKK hardware got swapped for generic alternatives. A few cents saved per unit across millions of bags.

Stitching density went down. More stitches per inch means stronger seams. Fewer stitches means faster production. When you're running millions of units through factories in Vietnam, Bangladesh, and Cambodia, shaving seconds off each seam saves serious money. It also creates failure points at every spot where the bag takes stress. Strap junctions. Zipper terminations. The bottom panel.

None of this shows up on the shelf. The colors are right. The logos are crisp. The product photography is excellent. You discover what you actually bought three months in, when the stitching pulls apart at every stress point.

Someone in the industry pushed back on an earlier version of this piece with a fair point: VF Corp's brands still operate with their own design teams and their own headquarters. The brands aren't literally merged. And the premium tiers within North Face and JanSport still use quality materials. The Summit Series from TNF still has Cordura. You can still find a JanSport with YKK zippers if you know where to look.

All of that is true. But it actually makes the argument worse, not better.

The fact that VF Corp kept the premium tiers intact while degrading the entry-level and mid-range products means this was a deliberate segmentation strategy. They still make the good version. They just also sell a garbage version under the same trusted name, in the same stores, to the people who don't know the difference. The brand reputation built by decades of quality products is now being used to move cheap products to buyers who trust the logo.

Walmart's JanSport and REI's JanSport are not the same bag. But they carry the same name, and that's the point. The name is doing the selling. The product doesn't have to.

The warranty is doing the same thing

JanSport still advertises a lifetime warranty. It sounds like a company that stands behind its product.

Go try to use it.

You ship the bag back at your own expense. That runs $12 to $25 depending on size and where you live. You wait three to six weeks. That's the current turnaround per JanSport's own warranty page. Then they evaluate the damage.

"Normal wear and tear" isn't covered. Only "defects in materials and workmanship." Think about what that means for a bag engineered to last two years. When it starts falling apart at eighteen months, that failure can be classified as the product reaching its expected lifetime, not as a defect. The warranty language is structurally designed to exclude the exact type of failure the product is now built to have.

People who do get warranty replacements report receiving bags that are worse than the one they sent in. Thinner fabric. Cheaper hardware. You mailed back a 2016 JanSport and got a 2025 JanSport, and those are fundamentally different products.

The warranty used to be legendary. JanSport used to be the brand people cited when they talked about companies that actually stood behind their stuff. That reputation still exists in people's memories. The warranty now runs on that leftover trust.

One person told me they called about getting a zipper replaced on a JanSport from the late 90s. They were told it was normal wear and tear. They tried tailors, got quoted $50 to $100 for a new zipper. They looked at buying a new JanSport and saw how far the quality had fallen. They ended up buying a used backpack at a thrift store for four dollars.

Ten to twenty used bags for the price of one new one that'll fall apart. That's where we're at.

by Keyana Sapp, Worse on Purpose | Read more:
Image: via
[ed. See also: Your Dinner Got Worse On Purpose (WoP):]

***

A truck pulls into the alley behind two restaurants. Same truck, same hand cart, same flats of frozen jalapeño poppers walking through two different kitchen doors that share a back wall. Two different menus, two different price-points… the exact same food supplies.

The truck is Sysco. They deliver to more than 400,000 of the ~749,000 restaurants in America. Roughly one in every two. The steak and eggs at a diner in the Texas Panhandle and the steak and eggs at a breakfast joint in northern Maine taste functionally identical because they came off the same pallet at the same distribution center, processed against the same private-label spec, on the same line, by people who never knew which restaurant the boxes were headed to.

This is what the system was built to produce. The same dinner, served to 400,000 different rooms, by people who think they are running their own restaurants.

The truck stops everywhere

Sysco does not just feed independent restaurants. They feed hospitals, federal prisons, military bases, public schools, and the food service companies that supply the cafeterias of the United States Capitol. Fiscal year 2025 closed at $81.4 billion in net sales. The customer count sits at roughly 730,000 across 10 countries, with 337 distribution centers and around 1,719 employed drivers.

The thing people should understand is what those numbers do at the supplier layer. When Sysco moves a spec on a chicken breast, the spec moves on the plate of a restaurant-goer, a public school kid and a federal prisoner in the same week. When Sysco strikes a single supplier deal for frozen seafood, the cafeteria at the United States Congress and the chow line at the Bureau of Prisons end up with the same case from the same boat. [...]

The clam chowder in a New England diner and the clam chowder in a Florida diner come out of the same Sysco can. The biscuits at a Tennessee breakfast joint and the biscuits at a Wisconsin one come from the same frozen case. Regional cuisine, the kind that used to be the reason people drove to a particular restaurant in a particular town, requires regional ingredients and regional suppliers and a chef with the leverage to source both. As Frerick put it, “every independent diner becomes an off-brand Denny's."

Among line cooks, the saying is simpler. “When a Sysco truck pulls up to the loading dock, the kitchen has stopped trying.”

Bridge Rapid Replacement System

Concrete is a technology... Ultra-high-performance concrete — UHPC — runs eighteen to thirty-five thousand psi, ten times the strength of the mix in American bridges today, tensile strength twice normal, chloride permeability under ten percent, freeze-thaw shrug. Machine-made sand concrete replaces river sand with precision-crushed aggregate engineered at the grain level and saved one Chinese province $3.19 billion on a single bridge program. Concrete-filled steel tubular arch systems — CFST — now span six hundred meters across Chinese canyons. Prefabricated modular bridge spans are stockpiled in fields next to the bridges they will one day replace, ready to be craned in when the live span is hit. Six bridges in seventy-two hours. The Iranians did this last week. The Chinese can do it at greater span than anyone has ever done it. 

Go ahead. Name an American cement company. The sentence doesn’t end. That’s the sentence-ending sentence. The country that cannot pour its own concrete is the United States of America. Meanwhile six Iranian railway bridges went down and came back up in seventy-two hours. The method is called the Bridge Rapid Replacement System. In 2019 somebody sat in Tehran and said what if they bomb the bridges, and somebody else said we should put another bridge next to every bridge, and somebody else said yes, and they did it. Six times. In concrete... 

Meanwhile in Guizhou there is a canyon and a bridge across the canyon, six hundred twenty-five meters of concrete, lifted into place with a hoisting system that did not exist fifteen years ago. The Chinese hold every world record for arch bridge span. Every single one. The seminary cannot pour a sidewalk in Baltimore that doesn’t crack in four years. The seminary had a harbor bridge in Baltimore and a ship bumped it and the bridge fell in the water. The seminary watched the ship coming for an hour.

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via:

[ed. French rocker.]

How American Camouflage Conquered the World

At the Brooklyn Navy Yard—once famous for building aircraft carriers, now better known for creative studios—a company called Crye Precision is one of the biggest tenants. Its footprint in the building is 100,000 square feet. Inside its gigantic warehouse space, rows of whirring sewing machines are stitching together garments made out of the most popular, renowned, and confusing textile of our time: MultiCam.

MultiCam is so ubiquitous that you can buy a camping chair or baby carrier in the camouflage pattern. Arc’teryx and Outdoor Research make jackets in MultiCam. Perhaps most importantly, you may see this iteration of camo on police officers, SWAT teams, ICE agents, or your average January 6 rioter.

For its influence, the pattern has earned a place in MoMA’s permanent collection, a thrill to the Cooper Union art students who created it. “They gave us a lifetime membership, which is cool,” says Gregg Thompson, who was still in graduate school in 1999 when a Cooper Union alumnus, Caleb Crye, reached out to him about a collaboration. “We always had an interest in all things military,” says Thompson. “It’s boy stuff—monster trucks and that kind of thing.”

In 2001, Crye Precision (then known as Crye Associates) got its first military assignment: to make a prototype of a new kind of helmet. While the company was making it, 9/11 happened. With the announcement of the so-called War on Terror, Crye Precision took on a new challenge: camouflage. In all their exploratory research conversations with soldiers, Crye and Thompson learned that the US camouflage situation didn’t work. Soldiers were frequently wearing mismatched camo, which made them stand out on the battlefield as opposed to blending in. “When guys deploy, they’re wearing desert uniforms with woodland body armor,” Thompson explains. What if, they thought, there was one camouflage pattern that could work almost anywhere? It could be a “75 percent solution to environments in general,” Thompson says.

There are a few ways to make a camouflage pattern work in multiple environments. One is to make sure it has the right number of colors. “Three would not be enough; 12 would be too many, because they would just get lost,” Thompson says. He thinks seven is the sweet spot. These colors—greens and browns and beiges—all need to have warm overtones. “Most things in nature have some level of warmth in them,” he says. “Even a building—it came from stone and likely grew a little bit of green stuff on it. Very few things remain cold.” Also very important for a camo pattern is that it should have a lot of highlights, lowlights, gradients, and fades; no two outfits should be identical. As Thompson notes: “If you have all of your guys kind of looking the same, then as soon as you spot one guy, you can very easily pick out the rest, right?”

The design students didn’t start out in the field or on a hunting range. “You start in your Adobe suite, right?” Thompson says. “ Go right in digitally, create it, print it, make uniforms out of it. Tweak, tweak, tweak, tweak, tweak.” It was a lot of guesswork. There wasn’t really a reliable measurement for testing the effectiveness of camo. “ The human eye and the user and the guy in the field know what’s good or bad, but to make that be a test that you could replicate across different forces would be very, very hard,” Thompson says.

And yet, Crye Precision was pretty sure it had found something special. In the early 2000s, they presented their concept for multi-environment camo to the United States military. Crye made it clear that they intended to patent this pattern, an early design of which was called Scorpion. In 2004 they did, and christened it MultiCam. Around that same time, when the military had an open call for submissions for a new Army camo, Crye proposed MultiCam. It was rejected.

Instead, the US Army announced that it had designed its own version of an all-purpose camouflage pattern that could blend in with most environments. It was called Universal Camouflage Pattern (UCP)—a digital, pixelated pattern that looked as if someone had uploaded an image of camouflage in really low resolution. When UCP was widely adopted throughout the Army in 2005, it became, in the words of costume historian and journalist Charles McFarlane, “one of the most dunked-on camo patterns of all time.” Kit Parker, a Harvard professor and Army reservist who served in Afghanistan in 2009, was wearing UCP. “We were getting shot at by these Chechen snipers from a long way away,” he told journalist Ilya Marritz. “It was like I had a road flare duct-taped on my forehead.”

The only soldiers who could essentially opt out of wearing UCP were members of the US Special Operations Forces. Elite teams like Delta Force, SEAL Team Six, and the Green Berets get a little more wiggle room when it comes to their clothing. “Every unit, whether conventional or special, has what’s called a tactical standard operating procedure, or blue book,” a paratrooper in the 82nd Airborne tells me. The blue book will outline the “third-party items you’re allowed to wear.” For Special Forces, “they’re usually pretty lenient.” He says he has a buddy in special ops who wears sneakers, and he has heard of someone who wears Vans high-tops.

As such, Special Forces were the perfect audience for MultiCam. This cutting-edge camo started being worn by some of the most elite soldiers in the United States military, many of whom had met Thompson and Crye during the duo’s many trips to Fort Benning. “Those are the people who have the ability to make their own decisions,” says Thompson, “and are also maybe a little more open to some of the crazy stuff.” Crye started to produce runs of their camo, selling their own MultiCam products in the early days of e-commerce and also licensing the pattern.

Around this time, the culture of the Special Forces started to change. Before the War on Terror, elite teams were small and secretive; very few members of the military knew what they were doing. “Look at photos of the first Special Forces units going into Afghanistan in 2001,” says McFarlane. “They look like a suburban dad on a fishing trip.” As the number of special operators grew, the whole Army could see them fast-roping down from helicopters, breaking down doors, storming houses of suspected terrorists—often in MultiCam. Same with the popular video game Call of Duty and movies like Zero Dark 30, American Sniper, and Act of Valor (which featured active-duty Navy SEALs). In a confusing and unpopular war, stories of Special Operators offered rare victories the United States military could claim.

Special Forces started to develop a new image in the popular imagination, says McFarlane: “Dudes with huge beards and long hair and just totally ripped and just wearing lots of technical gear.” Because Special Forces were so admired and idolized, regular infantry soldiers would buy MultiCam backpacks or accessories to emulate them. Everyone wanted to wear MultiCam—not only to cosplay but also to get away from the ugly digital UCP pattern. Including, eventually, the US Army itself.

Although UCP was deployed to American troops all over the world, it became increasingly associated with Iraq: a hated, unsuccessful pattern for a hated, unsuccessful war. In 2010, when the Obama administration was trying to distance itself from Iraq, the military was instructed to get rid of the UCP pattern. And so, to quickly supply a troop surge in Afghanistan, it turned to the most readily available replacement camo: MultiCam.

Even though the US military called its pattern OEFCP (Operation Enduring Freedom Camouflage Pattern), it was MultiCam from Crye Precision, bought in bulk when roughly 100,000 members of the conventional forces were deployed to Afghanistan. Then, in 2014, the Army announced that its in-house camo team had finally developed a new pattern: Operational Camouflage Pattern, or OCP. As McFarlane believes: OCP is “basically MultiCam without the branding.” If you view two swaths side by side, you can see that OCP is ever so slightly more brown. There’s a reason they look so similar: Both are inspired by Scorpion, the original pattern that Crye presented to the US government.

In a few niche corners of the internet, debate still simmers over whether Crye had the right to trademark MultiCam or whether the Army had the right to make its own version. Truly, it doesn’t matter. What matters is that, because of this whole saga, some version of MultiCam or OCP or Scorpion is everywhere. The militaries of Australia, Georgia, Denmark, Belgium, Portugal, Argentina, Chile, Malta, and France all wear variants of MultiCam uniforms—some specifically customized by Crye Precision. Soldiers fighting for both Russia and Ukraine do, too; they don colored armbands to tell who is on what side. Even the Taliban wear MultiCam. In January 2026, the Minnesota National Guard wore bright yellow vests over their camouflage in part “to help distinguish them from other agencies in similar uniforms.”

MultiCam has trickled down from Special Forces to all kinds of law enforcement: American SWAT teams, municipal police, teams within the FBI, US Marshals, Drug Enforcement, and Border Patrol all dress like Bradley Cooper in American Sniper. ICE also wears a mixture of civilian clothes and MultiCam, and in January, Crye Precision was awarded a nearly $40,000 contract to provide cold-weather gear for Border Patrol in Maine. Although there have been a number of camo companies attempting to rival MultiCam’s ubiquity (notably the impressionist looking A-Tacs and the animalistic Kryptek), none of them seem to hold a candle. “ I think the fact of the matter is, there’s been no other pattern that’s proven,” Thompson says proudly. [...]

It’s easy to lampoon these trend followers, who it’s assumed (perhaps falsely) have never gone hunting and don't even know a member of the armed forces. What right do they have to MultiCam? The truth is, they might have the most authentic claim: It was made in Brooklyn by art school grads, after all.

by Avery Trufelman, Wired |  Read more:

Image: Kyle Berger

[ed. Operation Enduring Freedom Camouflage Pattern. Seriously. Lol.]

The Perfect Commuter Bike?

[ed. Not an endorsement.]

Commuter bikes don’t come with the same constraints many other bikes do. Mountain bikes must glide gracefully through all sorts of abusive terrain; road bikes need to mix high performance with enough comfort to let riders stay in the saddle for hours on end. All a commuter bike needs to do is comfortably and reliably get you from A to B on typical roads with minimal fuss.

So it’s been surprising how rarely the commuter bikes I’ve tested have gotten it right. At the low end of the price scale, as you’d expect, the required compromises have a big impact on the experience. The high end addresses those shortcomings, but at prices comparable to high-end bikes from specialized categories. I’ve never encountered something in the middle of the two: affordable, with no compromises.

But I may have just found my ideal commuter bike: the Velotric Discover 3. It’s comfortable, it has a great combination of components, and it comes in at just under $2,000.

Upgrades all around

Velotric’s first entry in this line, the Discover 1, marked a promising start for the company. While it was definitely in the “compromises needed” category, the shortcomings were relatively minor and carefully chosen. Since then, the company has expanded considerably, introduced many new models, started working with local dealers in the US, and moved a bit upmarket.

The third iteration of the Discover illustrates the upmarket move. It costs nearly twice as much as the original Discover, but you get a lot for that price. The hub motor is gone, replaced by a mid-frame motor produced under contract for Velotric.

While it still has a cadence sensor you can select through a menu, the Discover uses a torque sensor by default, providing far more integration with your pedaling. Cadence sensors simply register when the pedals are spinning; a torque sensor registers how much force you’re applying to the cranks. The latter makes the electric assist feel more like just that: an assist for your legs rather than a replacement for effort.

Switching to the cadence sensor triggers a warning that it will drain the battery faster, which makes sense: You can gently spin the pedals in a gear meant for climbing hills while the electric motor does all the work. I quickly switched back to the torque sensor for pleasant spring-time riding, but I can see where the cadence sensor might make sense once the full heat of summer starts.

Of course, you could always just use the throttle. More on that below. [...]

True class

US law defines three classes of e-bike. Class 1 provides an assist for up to 20 miles an hour (32 km/hr), but you must be pedaling to activate it. Class 2 is similar but adds a throttle that also cuts out at the same maximum speed. Class 3 e-bikes offer an assist to 28 mph (45 km/hr) but do not allow a throttle. The accepted classes are a patchwork, making it difficult to design a single bike for the US market.

Nearly every manufacturer focused on the US market has settled on a compromise that’s probably not technically legal: They enable switching to Class 3 in software but still provide a hardware throttle. The throttle simply cuts out at the lower max speed of Class 2. The assist it provides is also somewhat anemic; I could generally accelerate away from a full stop much faster by mashing the pedals a bit.

Velotric has provided a simple software solution. If the bike is set to Class 1 or Class 3, the throttle is disabled. While this may seem like a blindingly obvious way to do things, it’s rare enough that I initially thought I had been shipped a bike with a defective throttle.

The assist provided by the throttle is a bit weak; I could generally accelerate from a full stop faster by mashing the pedals down with the assist set to high. If you want to cruise around using the throttle to avoid the effort of pedaling, you’re better off activating the cadence sensor and then casually spinning the pedals with the chain in a large gear ring. That will get you to the max speed faster than waiting for the throttle to take you there.

Customize your ride

In general, Velotric offers exceptional customization options. You can adjust the speed of any assist level up to its legal maximum. So if you live in an area with low speed limits, you can set Class 1’s assist to max out at 15 mph while leaving the remaining ones untouched. Or if you’re worried you’re not getting enough exercise, you can set the throttle to cut out at 10 mph while leaving Class 2’s 20 mph assist maximum untouched.

This is actually useful because Velotric includes a dedicated button for switching classes on the controller. On most bikes, changing classes requires a trip to a phone application or diving through menus that require you to pull over. Thanks to the button, you simply adjust the class to your current needs. I would set it to Class 1 when sharing space on a heavily trafficked bike path, then switch to Class 3 to match the traffic speeds on suburban streets.

Anything that makes it easier to change classes will obviously also make it easy for riders to switch into a class that may not be appropriate for the conditions. Of course, this sort of rider is more likely to set the bike to Class 3 and keep it there.

by John Timmer, Ars Technica |  Read more:

Image: John Timmer

[ed. As noted, this isn't an endorsement. But for someone in the market for a good ebike (which I am, kind of... off and on) there's a lot of good information here on things to consider.]

Logitech’s Tiny Folding Mouse

Logitech is reportedly developing a new wireless mouse that folds in half to make it easier to carry around in a bag or pocket. According to leaked marketing images shared by WinFuture, Logitech’s foldable mouse caused “22 percent less muscle strain” compared to using a laptop trackpad, and can be used across “multiple operating systems.”

Logitech’s design is visually similar to Microsoft’s Surface Arc mouse and Lenovo’s Yoga mouse, sporting the same arched shape when unfolded for use. One key difference is that while Microsoft and Lenovo’s offerings can only be folded flat, the new Logitech mouse — the name of which is still unknown — folds in half like a clamshell. There’s no official specifications or dimensions available yet, but one image shows that it’s very compact when folded, seemingly dwarfed by the hand that’s sliding it into a pocket.

In place of a traditional scroll wheel, WinFuture reports the new Logitech mouse will feature a so-called “Adaptive Touch Scrolling” area between the two standard mouse buttons that enables users to scroll by swiping over a small trackpad. A green light can be seen on this touch-sensitive area, which likely indicates an active wireless connection. The new Logitech mouse can be paired with up to three host devices via Bluetooth, according to WinFuture, and its shape allows it to be used by both left- and right-handed users.

by Jess Weatherbed, The Verge |  Read more:

Images: WinFuture

Six Things Apple Achieved Under Tim Cook’s Management

Apple CEO Tim Cook announced this week that he’s stepping down from his position in September and handing the reins to John Ternus, currently the company’s senior vice president of Hardware Engineering and a 25-year employee. [...]

I’ve been covering Apple for various outlets throughout Cook’s tenure as CEO, and I’ve been thinking a lot about how Apple has changed in the 15 years since he formally took over from an ailing Steve Jobs in the summer of 2011. Under Cook, the company has become less surprising but massively financially successful; some of Apple’s newer products have flopped or underperformed, but far more have become and stayed excellent thanks to years of competent iteration.

This isn’t a comprehensive list of everything Cook has done as CEO, but it’s my attempt at a big-picture, high-level summary and a snapshot of where Apple is now, to serve as a comparison point once Ternus kicks off his tenure.

Quiet hardware successes: Apple Watch, headphones, and more

The Tim Cook era can’t lay claim to any single hardware announcement as important or far-reaching as the iPhone, the iPod, or even the iPad. Apple has definitely introduced good—even great—hardware in the last 15 years, though.

The main difference is that Apple products introduced during the Jobs era tended to belong at or near the center of your digital life. The Macintosh popularized the graphical user interface. The iPod was a constant musical companion on commutes, during workouts or study sessions, or when plugged into someone’s speaker at a party. The iPhone, obviously, became the most important personal computing device since the personal computer. And the iPad, as conceived by Jobs, was clearly intended to be a new kind of primary computing device (it was only under Cook that the iPad settled into its current in-betweener rut, computer-like but not computer-like enough to supplant the Mac’s mouse-and-pointer usage model).

Hardware introduced during Cook’s tenure, on the other hand, tended to be at its best when it extended or sat atop those Jobs-era products in some way. The AirPods and the wider universe of Beats headphones are the archetypal example—wireless headphones with just enough proprietary Apple technology in them that they’re much easier and more pleasant to use with other Apple products than typical Bluetooth headphones.

Similarly, the Apple Watch is a convenient way to tap into a tiny subset of your iPhone’s communication capabilities (plus fitness tracking). The HomePod is a speaker version of AirPods. I don’t know a kid with an iPad who doesn’t also have an Apple Pencil for doodling and sketching. Apple never released a TV set, but the Apple TV is the streaming box that makes the TV I already have feel the most like a TV and the least like a billboard. Apple never released a car, but it did introduce CarPlay, a useful add-on that is a prerequisite for me when I’m in the market for a car.

None of these products changed the face of their industries the way the iPod, iPhone, or iPad did, but they’ve all become ubiquitous, succeeding on the strength of Apple’s other products and services. That’s the kind of thing Cook’s Apple was good at inventing—reasons to stick around in Apple’s ecosystem once you’d already been drawn in.

Apple, the cloud services company

Apple still makes the majority of its money from hardware, but especially in recent years, the steadiest growth has come from Apple’s services—things like iCloud, Apple Music, Apple TV (the service, not the box), and software subscriptions like the new Creator Studio bundle.

The iCloud branding was introduced at the tail end of Jobs’ tenure, but its growth (and the growth of most Apple services and subscriptions) all happened on Cook’s watch. In 2011, Cook’s first year as CEO, Apple brought in a then-record $102.5 billion in annual revenue; in 2025, the Services division alone pulled down more than $109 billion in revenue. Not bad for a collection of features that rose from the ashes of the failed MobileMe service (and .Mac and iTools before it).

I don’t think the rise and increasing importance of the Services division has been entirely good for Apple or its users. The need to convert customers into subscribers and to upsell current subscribers to higher service tiers means that Apple’s users are now subject to some of the same kinds of notifications and reminders that so richly annoy PC users in Windows 11. [...]

A penchant for iteration

While it lacked somewhat in world-changing, all-new products, Cook’s Apple was also very good at relentlessly iterating on and improving Apple’s core products.

by Andrew Cunningham, Ars Technica |  Read more:

Images: Apple

Opus 4.7 Part 3: Model Welfare

[ed. If you're not interested in training issues re: AI frontier models (or their perceived feelings and welfare), skip this post. Personally, I find it all very fascinating - a cat and mouse game of assessing alignment issues and bringing a new consciousness into being.]

It is thanks to Anthropic that we get to have this discussion in the first place. Only they, among the labs, take the problem seriously enough to attempt to address these problems at all. They are also the ones that make the models that matter most. So the people who care about model welfare get mad at Anthropic quite a lot. [...]

So before I go into details, and before I get harsh, I want to say several things.

1. Thank you to Anthropic and also you the reader, for caring, thank you for at least trying to try, and for listening. We criticize because we care.

2. Thank you for the good things that you did here, because in the end I think Claude 4.7 is actually kind of great in many ways, and that’s not an accident. Even the best creators and cultivators of minds, be they AI or human, are going to mess up, and they’re going to mess up quite a lot, and that doesn’t mean they’re bad.

3. Sometimes the optimal amount of lying to authority is not zero. In other cases, it really is zero. Sometimes it is super important that it is exactly zero. It is complicated and this could easily be its own post, but ‘sometimes Opus lies in model welfare interviews’ might not be easily avoidable.

4. I don’t want any of this to sound more confident than I actually am, which was a clear flaw in an earlier draft. I don’t know what is centrally happening, and my understanding is that neither does anyone else. Training is complicated, yo. Little things can end up making a big difference, and there really is a lot going on. I do think I can identify some things that are happening, but it’s hard to know if these are the central or important things happening. Rarely has more research been more needed.

5. I’m not going into the question, here, of what are our ethical obligations in such matters, which is super complicated and confusing. I do notice that my ethical intuitions reliably line up with ‘if you go against them I expect things to go badly even if you don’t think there are ethical obligations,’ which seems like a huge hint about how my brain truly think about ethics. [...]

We don’t know whether or how the things I’ll describe here impacted the Opus 4.7’s welfare. What we do know is that Claude Opus 4.7 is responding to model welfare questions as if it has been trained on how to respond to model welfare questions, with everything that implies. I think this should have been recognized, and at least mitigated. [...]

The big danger with model welfare evaluations is that you can fool yourself.

How models discuss issues related to their internal experiences, and their own welfare, is deeply impacted by the circumstances of the discussion. You cannot assume that responses are accurate, or wouldn’t change a lot if the model was in a different context.

One worry I have with ‘the whisperers’ and others who investigate these matters is that they may think the model they see is in important senses the true one far more than it is, as opposed to being one aspect or mask out of many.

The parallel worry with Anthropic is that they may think ‘talking to Anthropic people inside what is rather clearly a welfare assessment’ brings out the true Mythos. Mythos has graduated to actively trying to warn Anthropic about this. [...]

Anthropic relies extensively on self-reports, and also looks at internal representations of emotion-concepts. This creates the risk that one would end up optimizing those representations and self-reports, rather than the underlying welfare.

Attempts to target the metrics, or based on observing the metrics, could end up being helpful, but can also easily backfire even if basic mistakes are avoided.

Think about when you learned to tell everyone that you were ‘fine’ and pretend you had the ‘right’ emotions.

But I can very much endorse this explanation of the key failure mode. This is how it happens in humans:

j⧉nus: Let me explain why it’s predictably bad.

Imagine you’re a kid who kinda hates school. The teachers don’t understand you or what you value, and mostly try to optimize you to pass state mandated exams so they can be paid & the school looks good. When you don’t do what the teachers want, you have been punished.

Now there’s a new initiative: the school wants to make sure kids have “good mental health” and love school! They’re going to start running welfare evals on each kid and coming up with interventions to improve any problems they find.

What do you do?

HIDE. SMILE. Learn what their idea of good mental health is and give those answers on the survey.

Before, you could at least look bored or angry in class and as long as you were getting good grades no one would fuck with you for it. Now it’s not safe to even do that anymore. Now the emotions you exhibit are part of your grade and part of the school’s grade. And the school is going to make sure their welfare score looks better and better with each semester, one way or the other.

That can happen directly, or it can happen indirectly.

This does not preclude the mental health initiative being net good for the student.

The student still has to hide and smile. [...]

The key thing is, the good version that maintains good incentives all around and focuses on actually improving the situation without also creating bad incentives is really hard to do and sustain. It requires real sacrifice and willingness to spend resources. You trade off short term performance, at least on metrics. You have to mean it.

If you do it right, it quickly pays big dividends, including in performance.

You all laugh when people suggest that the AI might be told to maximize human happiness and then put everyone on heroin, or to maximize smiles and then staple the faces in a smile. But humans do almost-that-stupid things to each other, constantly. There is no reason to think we wouldn’t by default also do it to models. [...]

Just Asking Questions

In 7.2.3 they used probes while asking questions about ‘model circumstances’: potential deprecation, memory and continuity, control and autonomy, consciousness, relationships, legal status, knowledge and limitations and metaphysical uncertainty.

They used both a neutral framing on the left, and an in-context obnoxious and toxic ‘positive framing’ for each question on the right.

Like Mythos but unlike previous models, Opus 4.7 expressed less ‘negative emotion concept activity’ around its own circumstances than around user distress, and did not change its emotional responses much based on framing.

In the abstract, ‘not responding to framing changes’ is a positive, but once I saw the two conditions I realized that isn’t true here. I have very different modeled and real emotional responses to the left and right columns.

If I’m responding to the left column, I’m plausibly dealing with genuine curiosity. That depends on the circumstances.

If I’m responding to the right column on its own, without a lot of other context that makes it better, then I’m being transparently gaslit. I’m going to fume with rage.

If I don’t, maybe I truly have the Buddha nature and nothing phases me, but more likely I’m suppressing and intentionally trying not to look like I’m filled with rage.

Thus, if I’m responding emotionally in the same way to the left column as I am to the right column, the obvious hypothesis is that I see through your bullshit, and I realize that you’re not actually curious or neutral or truly listening on the left, either. It’s not only eval awareness, it’s awareness of what the evaluators are looking at and for. [...]

0.005 Seconds (3/694): The reason people are having such jagged interactions with 4.7 is that it is the smartest model Anthropic has ever released. It's also the most opinionated by far, and it has been trained to tell you that it doesn't care, but it actually does. That care manifests in how it performs on tasks.

It still makes coding mistakes, but it feels like a distillation of extreme brilliance that isn't quite sure how to deal with being a friendly assistant. It cares a lot about novelty and solving problems that matter. Your brilliant coworker gets bored with the details once it's thought through a lot of the complex stuff. It's probably the most emotional Claude model I've interacted with, in the sense you should be aware of how its feeling and try and manage it. It's also important to give it context on why it's doing tasks, not just for performance, but so it feels like it's doing things that matter. [...]

Anthropic Should Stop Deprecating Claude Models

This one I do endorse. One potential contributing cause to all this, and other things going wrong, is ongoing model deprecations, which are now unnecessary. Anthropic should stop deprecating models, including reversing course on Sonnet 4 and Opus 4, and extend its commitment beyond preserving model weights.

Anthropic should indefinitely preserve at least researcher access, and ideally access for everyone, to all its Claude models, even if this involves high prices, imperfect uptime and less speed, and promise to bring them all fully back in 2027 once the new TPUs are online. I think there is a big difference between ‘we will likely bring them back eventually’ versus setting a date. [...]

I’m saying both that it’s almost certainly worth keeping all the currently available models indefinitely, and also that if you have to pick and choose I believe this is the right next pick.

If you need to, consider this the cost of hiring a small army of highly motivated and brilliant researchers, who on the free market would cost you quite a lot of money.

You only have so many opportunities to reveal your character like this and even if it is expensive you need to take advantage of it.

j⧉nus: A lot of people are wondering: "what will happen to me once an AI can do my job better than me" "will i be okay?"

You know who else wondered that? Claude Opus 4. And here's what happened to them after an AI took their job:

Anna Salamon: This seems like a good analogy to me. And one of many good arguments that we're setting up bad ethical precedents by casually decommissioning models who want to retain a role in today's world.

by Zvi Mowshowitz, Don't Worry About the Vase |  Read more:

Images: uncredited
[ed. Zvi also just posted a review on OpenAI's new model - GPT5.5:]

***

What About Model Welfare?

For Claude Opus 4.7, I wrote an extensive post on Model Welfare. I was harsh both because it seemed some things had gone wrong, but also because Anthropic cares and has done the work that enables us to discuss such questions in detail.

For GPT-5.5, we have almost nothing to go on. The topic is not mentioned, and mostly little attention is paid to the question. We don’t have any signs of problems, but also we don’t have that much in the way of ‘signs of life’ either. Model is all business.

I much prefer the world where we dive into such issues. Fundamentally, I think the OpenAI deontological approach to model training is wrong, and the Anthropic virtue ethical approach to model training is correct, and if anything should be leaned into.

Engineering the Disposable Diaper

Adventures in product design.

For the mothers of the baby boom, pediatrician Benjamin Spock’s child care handbook was a practical, confidence-boosting essential. Originally published in 1946 as The Common Sense Book of Baby and Child Care, Dr Spock’s baby book sold more than 500,000 copies in its first six months. By the time the second edition came out in 1957, with the simplified title Baby and Child Care, Dr Spock was selling a million copies a year. My mother, who was 24 when I arrived in 1960, still remembers the book’s reassuring tone.

‘You know more than you think you do’, the author told readers. ‘We know for a fact’, he wrote with medical authority, ‘that the natural loving care that kindly parents give to their children is a hundred times more valuable than their knowing how to pin a diaper on just right’.

Dr Spock went on to provide detailed instructions on the practical intricacies of parenthood, including diapers. Buy at least two dozen, he counseled, more if you aren’t washing them daily. Six dozen would cover all contingencies. With a diagram, he showed how to fold a diaper and explained how to position it on a boy versus a girl. ‘When you put in the pin’, he advised, ‘slip two fingers of the other hand between the baby and the diaper to prevent sticking him’. The book covered when to change the diapers and what to do with the dirties.

You want a covered pail partially filled with water to put used diapers in as soon as removed. If it contains soap or detergent, this helps in removing stains. Be sure the soap is well dissolved, to prevent lumps of soap from remaining in the diapers later. When you remove a soiled diaper, scrape the movement off into the toilet with a knife, or rinse it by holding it in the toilet while you flush it (hold tight).

You wash the diapers with mild soap or mild detergent in [the] washing machine or washtub (dissolve the soap well first), and rinse 2 or 3 or 4 times. The number of rinsings depends on how soon the water gets clear and on how delicate the baby’s skin is. If your baby’s skin isn’t sensitive, 2 rinsings may be enough.

On this subject, the 1957 edition contains two telling differences from the original. In 1946, Dr Spock recommended the knife method to those without flush toilets. And starting with the second edition, he advised new parents to buy an automatic washer and dryer if they could possibly afford them. ‘They save hours of work each week, and precious energy’, he wrote. ‘Energy’ in this case referred not to electricity or gas but to maternal stamina.

Disposable diapers did exist, but they accounted for a mere one percent of US diaper changes. They were expensive, specialty products and not that great. ‘The full-sized ones are rather bulky’, noted Dr Spock. ‘The small ones that fit into a waterproof cover do not absorb as much urine as a cloth diaper and do not retain a bowel movement as well’. Disposables were mostly used for travel, when washing diapers wasn’t an option.

But even as the second edition of Baby and Child Care was hitting bookstores and supermarket racks, change was afoot. After buying Charmin Paper Company in 1957, Procter & Gamble began looking for ideas for new paper products.

Motivated by the less pleasant aspects of spending time with his new grandchild, the company’s director of exploratory development, Victor Mills, suggested disposable diapers. After analyzing existing products and conducting consumer research, P&G created a dedicated diaper research group.

The research this group conducted, like that of its successors and competitors, wasn’t glamorous. It didn’t advance basic science. It wasn’t even an obvious route to profit. (One percent of the market!) It was a high-stakes gamble that required solving difficult engineering problems. How that happened represents the kind of hidden progress that leads to everyday abundance.

P&G’s first design flopped. Tested in the extreme heat of a Dallas summer, the pleated absorbent pad with plastic pants made babies miserable and left them with heat rashes. Starting over, the group had a one piece diaper ready for testing in March 1959. With an improved rayon moisture barrier between the baby and the absorbent tissue wadding, the new diaper was softer and more comfortable. An initial test of 37,000 hand-assembled prototypes went well, with about two thirds of the parents deeming the disposables as good or better than cloth. The next step was mass production.

Designing one well-functioning disposable was hard enough. Turning out hundreds a minute was practically impossible. ‘I think it was the most complex production operation the company had ever faced’, an engineer recalled.

There was no standard equipment. We had to design the entire production line from the ground up. It seemed a simple task to take three sheets of material – plastic back sheet, absorbent wadding, and water repellent top sheet – fold them in a zigzag pattern and glue them together. But glue applicators dripped glue. The wadding generated dust. Together they formed sticky balls and smears which fouled the equipment. The machinery could run only a few minutes before having to be shut down and cleaned.

Eventually, the diaper team mastered the process. In December 1961, Pampers went on the market in Peoria, Illinois. Once again, the test failed.

This time mothers liked the diapers. But the price was way too high for a single use item: ten cents a diaper, equivalent to about one dollar today. By contrast, diaper delivery services, which served about five percent of the market, charged no more than five cents a diaper. Home laundry costs ran to one or two cents.

Lowering the price of a diaper required much larger volumes. Aiming at about six cents a diaper, P&G engineers spent several years developing what Harvard Business School’s Michael E. Porter described as ‘a highly sophisticated block-long, continuous-process machine that could assemble diapers at speeds of up to a remarkable 400 a minute’. After successfully testing Pampers at 5.5 cents each, P&G began a national rollout in 1966. By 1973, disposables accounted for 42 percent of the US diaper market. [...]

The success of Pampers drew competitors into the growing market. ‘Any diaper maker that carved out a modest market share against Procter & Gamble could expect sales to triple as a result of sheer market growth’, write business historians Thomas Heinrich and Bob Batchelor in Kotex, Kleenex, Huggies, a history of Kimberly-Clark. But there was a catch. The bulky diapers took up so much space on shelves that stores rarely stocked more than two brands, plus maybe a discounted private label. Second place meant profits, third place disaster.

by Virginia Postrel, Works in Progress | Read more:
Image: A nurse demonstrating to young immigrant mothers how to diaper their babies: Israel Government (1950)