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headline economic figures have become less and less of a useful guide to how actual families are doing—something repeatedly noted by Democrats during the Obama recovery and the Trump years. Inequality may be declining, but it still skews GDP and income figures, with most gains going to the few, not the many. The obscene cost of health care saps family incomes and government coffers without making anyone feel healthier or wealthier.

To be clear, the headline economic numbers are strong. The gains are real. The reduction in inequality is tremendous, the pickup in wage growth astonishing, particularly if you anchor your expectations to the Barack Obama years, as many Biden staffers do.

During the Biden-Harris years, more granular data pointed to considerable strain. Real median household income fell relative to its pre-COVID peak. The poverty rate ticked up, as did the jobless rate. The number of Americans spending more than 30 percent of their income on rent climbed. The delinquency rate on credit cards surged, as did the share of families struggling to afford enough nutritious food, as did the rate of homelessness.

the White House never passed the permanent care-economy measures it had considered.

the biggest problem, one that voters talked about at any given opportunity, was the unaffordability of American life. The giant run-up in inflation during the Biden administration made everything feel expensive, and the sudden jump in the cost of small-ticket, common purchases (such as fast food and groceries) highlighted how bad the country’s long-standing large-ticket, sticky costs (health care, child care, and housing) had gotten. The cost-of-living crisis became the defining issue of the campaign, and one where the incumbent Democrats’ messaging felt false and weak.

Rather than acknowledging the pain and the trade-offs and the complexity—and rather than running a candidate who could have criticized Biden’s economic plans—Democrats dissembled. They noted that inflation was a global phenomenon, as if that mattered to moms in Ohio and machinists in the Central Valley. They pushed the headline numbers. They insisted that working-class voters were better off, and ran on the threat Trump posed to democracy and rights. But were working-class voters really better off? Why wasn’t anyone listening when they said they weren’t?

Voters do seem to be less likely to vote in their economic self-interest these days, and more likely to vote for a culturally compelling candidate. As my colleague Rogé Karma notes, lower-income white voters are flipping from the Democratic Party to the Republican Party on the basis of identitarian issues. The sharp movement of union voters to Trump seems to confirm the trend. At the same time, high-income voters are becoming bluer in order to vote their cosmopolitan values.

The Biden-Harris administration did make a difference in concrete, specific ways: It failed to address the cost-of-living catastrophe and had little to show for its infrastructure laws, even if it found a lot to talk about. And it dismissed voters who said they hated the pain they felt every time they had to open their wallet.

"The fog of war" is an expression that describes uncertainty about your adversary's capabilities and intentions while in the middle of battle. But it's also an appropriate way to describe our knowledge and understanding of history while living through it.

Everyone in the media seems to want this election to be about the issue they care most about, or to find a way to answer “why Trump won” or “what happened to the Democratic party” in a few sentences. I think that kind of quick summation is impossible. Elections are always decided by a confluence of several factors, some more important than others, and today I’m trying to lay out those factors I suspect were most relevant. That’s the goal: not to give a single, definitive answer, but a holistic and overarching one.

A lot of people, including Democratic strategists, have tried to explain to voters why they shouldn’t feel this way. They've pointed to low unemployment, inflation dissipating, and GDP growth — traditional metrics for measuring economic success — as proof that Bidenomics was working. But these macro numbers didn’t soothe the reality of what was happening at the granular level. Very few Democrats, and very few pundits, seem to have grasped this.

it turned out that Trump's 2020 performance (even in a loss) was the beginning of a new trend, not a fluke. While Democrats were focused on winning back white working-class voters, they actually lost support among their traditionally more multiethnic base.

I don’t think we were clear enough by saying fewer people came in under President Biden than came under Donald Trump. It’s clarity of the message, and if that’s what Bernie’s talking about, and that’s what Joe Manchin’s talking about, we weren’t clear in our message as to what things are, then I agree with that. And that was one of the concerns I expressed about saying we haven’t put forth what was done. It’s our legacy, too. [Pelosi bangs on the table.] The rescue package. [Pelosi bangs on the table.] Infrastructure Bill. [Pelosi bangs on the table again.] The CHIPS Act. But that didn’t come across as well as it should have. So I think if you’re talking about messaging, you’re talking about communications, that’s one thing. If you’re talking about what we stand for versus what they stand for, the public’s in for a big surprise.

I think that any vice president is, like it or not, tied to the record of the president. I think what Biden did was great, and being tied to his record is a great thing but not the way the record was perceived. This is a record of job creation. Sixteen million jobs as opposed to the record of her opponent who had the worst job-creation record since Herbert Hoover. Yes, 16 million jobs, turning around inflation, all the things that we did to build the infrastructure of America, reduce the cost of prescription drugs.

President Trump has promised to use the Justice Department and the attorney general to go after his perceived enemies. He has said that over and over again, and you’re one of them. Well, you would think that that would be enough reason for people not to vote for him. But that’s what he said. So when people say to me, “Why do you think our democracy is in danger?” I’ll say, well, let’s define our democracy. What is democracy? Free and fair elections? Peaceful transfer of power, independence of the judiciary, the rule of law, all of those kinds of things are part of a democracy. So if he’s going after those things, and thank God, the only, shall we say, peace of mind that we have today is that we don’t have the assault on the system that would have been there had Kamala Harris won. That isn’t right. It shouldn’t be that way. And that he would say — maybe thought it, might even want to do it, but to say it and the American people will say, “That’s OK with me ”?

In the beginning, VFA was an institution beloved by many of its fellows. “It was a wonderful way to leave college and enter the real world because you’re surrounded by a community and there’s support from the organization,” says Jamie Norwood, co-founder of feminine hygiene brand Winx Health. Norwood and her co-founder, Cynthia Plotch, are a VFA success story. They met as fellows in 2015 and VFA eventually helped them launch their company with a grant and advisement. “We always say, Winx Health would not be here without VFA,” Norwood says.

Norwood and Plotch went through the standard VFA admissions protocol, which was rigorous. It required two written applications, a video interview, and in-person interviews at an event called “Selection Day,” many of which were held in New York City and Detroit over the years. By the end of each university term in May, accepted fellows would get access to Connect, VFA’s job portal, and have until November to land a job. For each fellow hired in a full-time job, VFA received a $5,000 placement fee, paid by partner companies. This fee became a crucial revenue stream for the organization—effectively wedding the professional success of its fellows to its bottom line.

Selection Day interviews were conducted by judges who often pitted interviewees against each other. Candidates were told to organize themselves in order of least to most likely to be successful, or according to whose answers had the most value per word. The format felt ruthless. “People cried” during the interview process, Plotch remembers.

The problems with the business bled into the fellows’ experience in 2023 and 2024, leaving them disenchanted, financially struggling, or expelled en masse from the program for reasons they believe were beyond their control. Despite a multitude of financial red flags, VFA leadership still insisted on recruiting for the 2024 class. “The talent team was traveling nonstop, using prepaid Visa cards since the corporate cards didn’t work,” explains a former director who worked closely with fellows.

Onboarding fresh recruits became increasingly crucial if VFA was going to survive. The organization asked companies for placement fees upfront in 2023, according to internal VFA documents and conversations with former employees. The policy change gave companies pause. Fewer companies signed up as partners, meaning fellows weren’t getting jobs and VFA was losing money.

In the spring of 2023, “there were 15 jobs on opening day,” for a class that eventually grew to over 100 fellows, the former director explains. Gabriella Rudnik, a 2023 fellow, estimates that when training camp began in July 2023, less than half of her peers had jobs, “whereas in previous years it would be closer to like 80 percent.”

Fellows were made to pay the price for the shortage of companies partnering with VFA in 2023. “We weren’t getting more jobs on Connect, and that’s what led to so many fellows being off-boarded,” explains a former director who worked closely with fellows.

Traditionally, VFA gave fellows a deadline of November of their class year to find a job, which typically meant a few stragglers were given extra help to find a position if they were late. In those rare cases during earlier years, fellows were offboarded by the organization, a former director says.

In previous years, expulsion was a much more serious and infrequent occurrence. “Removal from the fellowship was not something done lightly. During my tenure, we instituted an internal investigation process, similar to an HR investigation,” says the former executive who worked at VFA from 2017-20.  In total, at least 40 fellows from the 2023 class were expelled for failing to get jobs that weren’t available, according to research by former VFA fellows who tracked the number of fellows purged from a Slack channel. Records of their participation were removed from the VFA website, the fellows say.

Many fellows had made sacrifices to be part of the highly selective and prestigious VFA, which cited acceptance rates of around 10 percent of applicants. “There were fellows who turned down six-figure jobs to be a part of this program, and were told that the program that Andrew Yang started would live up to its reputation,” says Paul Ford, a 2024 fellow.

Though internal documents show that VFA was slowly imploding for months, in all external communications with fellows, the nonprofit still maintained that 2024 training camp would take place in Detroit.

“From an ethical perspective, it does reek of being problematic,” says Thad Calabrese, a professor of nonprofit management at New York University. “You entered into an arrangement with people who don’t have a lot of money, who believed that you were going to make them whole. Then you’re going to turn around and not make them whole.”

Here’s a warning and an admonition written in January 2019 by author and organizer Jonathan Smucker: “If the Dem Party establishment succeeds in beating down the fresh leadership and bold vision that's stepping up, it will effectively enable the continued rise of authoritarianism. But they will not wake up and suddenly grasp this. It's on us to outmaneuver them and win.”

There are a million surface-level reasons for Kamala Harris’s loss and systematic underperformance in pretty much every county and among nearly every demographic group. She is part of a deeply unpopular administration. Voters believe the economy is bad and that the country is on the wrong track. She is a woman and we still have some work to do as a nation to overcome long-held biases.  But the real problems for the Democrats go much deeper and require a dramatic course correction of a sort that, I suspect, Democrats are unlikely to embark upon. The bottom line is this: Democrats are still trying to run a neoliberal campaign in a post-neoliberal era. In other words, 2016 Bernie was right.

The lie that fueled the Iraq war destroyed confidence in the institutions that were the bedrock of this neoliberal order and in the idea that the U.S. could or should remake the world in our image. Even more devastating, the financial crisis left home owners destitute while banks were bailed out, revealing that there was something deeply unjust in a system that placed capital over people.

These events sparked social movements on both the right and the left. The Tea Party churned out populist-sounding politicians like Sarah Palin and birtherist conspiracies about Barack Obama, paving the way for the rise of Donald Trump. The Tea Party and Trumpism are not identical, of course, but they share a cast of villains: The corrupt bureaucrats or deep state. The immigrants supposedly changing your community. The cultural elites telling you your beliefs are toxic. Trump’s version of this program is also explicitly authoritarian. This authoritarianism is a feature not a bug for some portion of the Trump coalition which has been persuaded that democracy left to its own devices could pose an existential threat to their way of life.

On the left, the organic response to the financial crisis was Occupy Wall Street, which directly fueled the Bernie Sanders movement. Here, too, the villains were clear. In the language of Occupy it was the 1% or as Bernie put it the millionaires and billionaires. It was the economic elite and unfettered capitalism that had made it so hard to get by. Turning homes into assets of financial speculation. Wildly profiteering off of every element of our healthcare system. Busting unions so that working people had no collective power. This movement was, in contrast to the right, was explicitly pro-democracy, with a foundational view that in a contest between the 99% and the 1%, the 99% would prevail. And that a win would lead to universal programs like Medicare for All, free college, workplace democracy, and a significant hike in the minimum wage.

On the Republican side, Donald Trump emerged as a political juggernaut at a time when the party was devastated and rudderless, having lost to Obama twice in a row. This weakened state—and the fact that the Trump alternatives were uncharismatic drips like Jeb Bush—created a path for Trump to successfully execute a hostile takeover of the party.

Plus, right-wing populism embraces capital, and so it posed no real threat to the monied interests that are so influential within the party structures.

The Republican donor class was not thrilled with Trump’s chaos and lack of decorum but they did not view him as an existential threat to their class interests

The difference was that Bernie’s party takeover did pose an existential threat—both to party elites who he openly antagonized and to the party’s big money backers. The bottom line of the Wall Street financiers and corporate titans was explicitly threatened. His rise would simply not be allowed. Not in 2016 and not in 2020.

What’s more, Hillary Clinton and her allies launched a propaganda campaign to posture as if they were actually to the left of Bernie by labeling him and his supporters sexist and racist for centering class politics over identity politics. This in turn spawned a hell cycle of woke word-policing and demographic slicing and dicing and antagonism towards working class whites that only made the Democratic party more repugnant to basically everyone.

The path not taken in 2016 looms larger than ever. Bernie’s coalition was filled with the exact type of voters who are now flocking to Donald Trump: Working class voters of all races, young people, and, critically, the much-derided bros. The top contributors to Bernie’s campaign often held jobs at places like Amazon and Walmart. The unions loved him. And—never forget—he earned the coveted Joe Rogan endorsement that Trump also received the day before the election this year. It turns out, the Bernie-to-Trump pipeline is real! While that has always been used as an epithet to smear Bernie and his movement, with the implication that social democracy is just a cover for or gateway drug to right wing authoritarianism, the truth is that this pipeline speaks to the power and appeal of Bernie’s vision as an effective antidote to Trumpism. When these voters had a choice between Trump and Bernie, they chose Bernie. For many of them now that the choice is between Trump and the dried out husk of neoliberalism, they’re going Trump.

Maybe I will be just as wrong as I was about the election but it is my sense that with this Trump victory, authoritarian right politics have won the ideological battle for what will replace the neoliberal order in America. And yes, I think it will be ugly, mean, and harmful—because it already is.

Trump used these podcast appearances to both humanize and mythologize himself. He used them to launder his extremist positions through the pervasive can’t you take a joke filter that propels the Tony Hinchcliffes of the world to stardom. Most important of all, he used them to get out the vote.

in 2024, shouting to a few thousand true believers has nothing on being anointed by Elon Musk on X and a cadre of right-wing influencers with collective followings in the hundreds of millions.

What Trump and his team understood is that “the discourse,” to whatever extent that means anything anymore, no longer happens in op-ed columns or on The Daily Show or even on Breitbart, and hasn’t for years. Kamala Harris seemingly did not. She did appear on Call Her Daddy, a stratospherically popular podcast with an audience primarily comprising young women, and her campaign enlisted a number of influencers as surrogates. But she skipped Rogan, Lex Friedman, and other mainstream-adjacent marathon podcasts.

the world of conservative influencers dwarfs their liberal counterparts in both follower size and impact. In the same way Democrats never found their own Rush Limbaugh, they don’t have a Steven Crowder or a Ben Shapiro or even, so help us, a Tim Pool. There are Democrats with followings online, but the cumulative gap in people paying attention to what they say is several orders of magnitude wide.

what is the future of branding in the age of slop? The provocation for this particular stream of thought was a Tiktok video by brand strategist Eugene about branding in the era of brainrot. This video declares that the age of brands as stories has ended. There are no more ninety second spots that tell a tale, he argues, now there’s only vibe, something more like sentiment or affect – what's picked up in a crowded feed, two or three seconds between footage of catastrophic climate change and a monkey who’s learned to do makeup tutorials. He gives the example of a Twitch stream: it may be too hectic to read the individual posts, but you can monitor the sentiment. You can catch the vibe.

New things – brands, products, trends – are increasingly defined in relational terms to such an extent that they become devoid of any unique story, character, or essence.

Moodboarding as a practice is maxed out. It’s become a nearly absurdist consumer hobby, and it’s part and parcel of our algorithmic reality, targeted yet vague. Similarly, slop can’t be meaningfully curated because there are too many actors, algorithms, and microtrends being expressed simultaneously, in too many automated iterations.

When the brand is a person, an entity with a personality. The idea is that you can hone this personality in order to define your organization better and make more money out in the world. “All organizations have an identity whether they control it or not. A corporate identity programme harnesses and manages this identity in the corporate interest,” Wally Olins wrote.

Brand as story is the other conventional frame that’s been very popular, as mentioned in the Tiktok that kicked this off. This one is all about using things like narrative structure and the hero’s journey to structure the way a brand shows up and communicates, and also using stories as branding opportunities. Brand “lore” is an updated subset of brand as story.

These stories tend to coalesce around a charismatic founder (Tesla and Elon), a social cause (Patagonia and the environment), even a countercultural position (SST records and punk rock). The depth of the lore is directly correlated to brand value. Consumers can become pay-to-play characters of the story.

Brand as pattern is about creating something that shows up iteratively in the world, rather than repeating messages rotely. This has classic examples, like Absolut ads, and more mimetic ones, where users take on the pattern and create the brand themselves

Memes are an advanced form of this practice – everything from Pepe to Brat makes use of this repetition to create flexible and iterative meaning.  Brands that rely heavily on UGC are often related to brand-as-pattern.

Then there’s brand as world, the less eggheaded, more contemporary version of brand as story. Worldbuilding as a brand activity feels intuitively more digital and immersive, less linear than straight narrative.  Many luxury brands employ this practice to help us imagine a world of accessible wealth where people are more beautiful, more free, more actualized. Disney offers an accessible, albeit more fanciful version of this practice – creating an actual destination with its own culture and characters. In either case, the brand is a portal that gives you partial access to an alternative reality.

Brand as coherence is another more philosophical way of looking at brands, one that Nemesis-friend Michael Rock of 2x4 talks about a lot. In this world the brand is the je ne sais quois or x factor that makes everything fit together. It’s the systematic principle itself.  This coherence can be emotional… “When we talk about a strong brand, what we mean is that it consistently delivers the emotion it promises. The most successful brands, or at least the ones everyone emulates, have the knack for using design to produce an emotional coherence that spans from content to product to experience. Think Apple or BMW or Chanel. Not everything has to look alike, but it all has to feel alike. Whenever we encounter them we get that familiar brand sensation. That tingling tells you it's working.” (Michael Rock, Hooked on a Feeling) Or technical… “I know that [branding] is an incredibly distasteful term in cultural and academic organizations, but like it or not branding has become one of the major organizing principles of the world as we know it right now. States have brands, corporations have brands, people have brands, institutions have brands — everyone’s talking about that, and when they talk about brand, they may all be talking about different things, but I think it’s a way of thinking about this idea of assembly…I would say maybe that branding is this act of assemblage that creates seemingly coherent entities.” (Michael Rock, Berkeley design lecture)

there’s the brand as vibes. These are not just brands that have us asking what the there-there is. They’re also brands like Marc Jacobs’ Heaven, which has brought together disparate objects that fit a sort of dreamy Gen Z moodboard to great effect, creating new life for what was quickly becoming a legacy brand. Then there’s A24, perhaps one of the greatest vibe brands of them all.

vibes are something we feel, and have something to do with a sense of recognition or belonging.

In a sense, vibes are procedurally generated, created by following resonant patterns and associations rather than by directly expressing new ideas or unique sentiments. The value assigned to brands built on vibes is similarly transitive – if you like X you will probably like Y.  In the best cases, a brand can create and embody its own ineffable vibe that imbues all of its products and endeavors with a sense of magical value. Seeing the new A24 film is more about experiencing a new iteration of the brand than it is about the movie’s actual plot, cast, or story. Fans want to see a particular sensibility applied to the world around it.

When a brand is a person, you have an emotional connection with them (they also have rights: see Citizens United). When it's a story, it entertains you and holds your attention. When a brand is a world, there's immersion and escape. When it's a pattern, you can replicate it and play with it.

With all this in mind, the key to successful brands after vibes may be in creating... something dense and irrefutable: a brand that flaunts itself as proof of work, that makes clear the amount of real information and human effort that went into creating it, that can’t become blurry. The brand is labor itself, a direct expression of the work that produces it. something exceptionally simple – logo only, that is, just one coordination point…or better yet, a ticker, a single letter, a point of pure speculative energy. Something so singular it can’t be spun off into iterations, but due to its singularity, can freely attach to and feed itself by anything and everything. The brand is an atom, a particle, a single-cell organism. something like dazzle, the makeup that helps a face escape facial recognition software: something so incoherent it can't be read by the model or algorithm, something that cannot be expressed as or compressed into a vibe.  In  this case, the brand is noise, something rule breaking that jams an orderly system of meaning / value.

In The Unaccountability Machine, Dan Davies argues that organizations form “accountability sinks,” structures that absorb or obscure the consequences of a decision such that no one can be held directly accountable for it. Here’s an example: a higher up at a hospitality company decides to reduce the size of its cleaning staff, because it improves the numbers on a balance sheet somewhere. Later, you are trying to check into a room, but it’s not ready and the clerk can’t tell you when it will be; they can offer a voucher, but what you need is a room. There’s no one to call to complain, no way to communicate back to that distant leader that they’ve scotched your plans. The accountability is swallowed up into a void, lost forever.

Davies proposes that: For an accountability sink to function, it has to break a link; it has to prevent the feedback of the person affected by the decision from affecting the operation of the system.

Another mechanism of accountability sinks is the way in which decisions themselves cascade and lose any sense of their origins. Davies gives the example of the case of Dominion Systems vs Fox News, in which Fox News repeatedly spread false stories about the election. No one at Fox seems to have explicitly made a decision to lie about voting machines; rather, there was an implicit understanding that they had to do whatever it took to keep their audience numbers up.

you could conclude that to be accountable for something you must have the power to change it and understand what you are trying to accomplish when you do. You need both the power and the story of how that power gets used.

an account is something that you tell. How did something happen, what were the conditions that led to it happening, what made the decision seem like a good one at the time? Who were all of the people involved in the decision or event? (It almost never comes down to only one person.)

After mulling over my bullet points, it occurred to me that the network problems I was dealing with—background cloud sync, editing across multiple devices, real-time collaboration, offline support, and reconciliation of distant or conflicting revisions—were all pointing to the same question: was it possible to design a system where any two revisions of the same document could be merged deterministically and sensibly without requiring user intervention?

It’s what happened after sync that was troubling. On encountering a merge conflict, you’d be thrown into a busy conversation between the network, model, persistence, and UI layers just to get back into a consistent state. The data couldn’t be left alone to live its peaceful, functional life: every concurrent edit immediately became a cross-architectural matter.

I kept several questions in mind while doing my analysis. Could a given technique be generalized to arbitrary and novel data types? Did the technique pass the PhD Test? And was it possible to use the technique in an architecture with smart clients and dumb servers?

Concurrent edits are sibling branches. Subtrees are runs of characters. By the nature of reverse timestamp+UUID sort, sibling subtrees are sorted in the order of their head operations.

This is the underlying premise of the Causal Tree. In contrast to all the other CRDTs I’d been looking into, the design presented in Victor Grishchenko’s brilliant paper was simultaneously clean, performant, and consequential. Instead of dense layers of theory and labyrinthine data structures, everything was centered around the idea of atomic, immutable, metadata-tagged, and causally-linked operations, stored in low-level data structures and directly usable as the data they represented.

I’m going to be calling this new breed of CRDTs operational replicated data types—partly to avoid confusion with the exiting term “operation-based CRDTs” (or CmRDTs), and partly because “replicated data type” (RDT) seems to be gaining popularity over “CRDT” and the term can be expanded to “ORDT” without impinging on any existing terminology.

Much like Causal Trees, ORDTs are assembled out of atomic, immutable, uniquely-identified and timestamped “operations” which are arranged in a basic container structure. (For clarity, I’m going to be referring to this container as the structured log of the ORDT.) Each operation represents an atomic change to the data while simultaneously functioning as the unit of data resultant from that action. This crucial event–data duality means that an ORDT can be understood as either a conventional data structure in which each unit of data has been augmented with event metadata; or alternatively, as an event log of atomic actions ordered to resemble its output data structure for ease of execution

To implement a custom data type as a CT, you first have to “atomize” it, or decompose it into a set of basic operations, then figure out how to link those operations such that a mostly linear traversal of the CT will produce your output data. (In other words, make the structure analogous to a one- or two-pass parsable format.)

OT and CRDT papers often cite 50ms as the threshold at which people start to notice latency in their text editors. Therefore, any code we might want to run on a CT—including merge, initialization, and serialization/deserialization—has to fall within this range. Except for trivial cases, this precludes O(n2) or slower complexity: a 10,000 word article at 0.01ms per character would take 7 hours to process! The essential CT functions have to be O(nlogn) at the very worst.

Of course, CRDTs aren’t without their difficulties. For instance, a CRDT-based document will always be “live”, even when offline. If a user inadvertently revises the same CRDT-based document on two offline devices, they won’t see the familiar pick-a-revision dialog on reconnection: both documents will happily merge and retain any duplicate changes. (With ORDTs, this can be fixed after the fact by filtering changes by device, but the user will still have to learn to treat their documents with a bit more caution.) In fully decentralized contexts, malicious users will have a lot of power to irrevocably screw up the data without any possibility of a rollback, and encryption schemes, permission models, and custom protocols may have to be deployed to guard against this. In terms of performance and storage, CRDTs contain a lot of metadata and require smart and performant peers, whereas centralized architectures are inherently more resource-efficient and only demand the bare minimum of their clients. You’d be hard-pressed to use CRDTs in data-heavy scenarios such as screen sharing or video editing. You also won’t necessarily be able to layer them on top of existing infrastructure without significant refactoring.

Perhaps a CRDT-based text editor will never quite be as fast or as bandwidth-efficient as Google Docs, for such is the power of centralization. But in exchange for a totally decentralized computing future? A world full of devices that control their own data and freely collaborate with one another? Data-centric code that’s entirely free from network concerns? I’d say: it’s surely worth a shot!

people mix up two very different types of pivots and that it’s important to differentiate which path you’re on: Ideation pivots: This is when an early-stage startup changes its idea before having a fully formed product or meaningful traction. These pivots are easy to make, normally happen quickly after launch, and the new idea is often completely unrelated to the previous one. For example, Brex went from VR headsets to business banking, Retool went from Venmo for the U.K. to a no-code internal tools app, and Okta went from reliability monitoring to identity management all in under three months. YouTube changed direction from a dating site to a video streaming platform in less than a week. Hard pivots: This is when a company with a live product and real users/customers changes direction. In these cases, you are truly “pivoting”—keeping one element of the previous idea and doubling down on it. For example, Instagram stripped down its check-in app and went all in on its photo-sharing feature, Slack on its internal chat tool, and Loom on its screen recording feature. Occasionally a pivot is a mix of the two (i.e. you’re pivoting multiple times over 1+ years), but generally, when you’re following the advice below, make sure you’re clear on which category you’re in.

When looking at the data, a few interesting trends emerged: Ideation pivots generally happen within three months of launching your original idea. Note, a launch at this stage is typically just telling a bunch of your friends and colleagues about it. Hard pivots generally happen within two years after launch, and most around the one-year mark. I suspect the small number of companies that took longer regret not changing course earlier.

ou should have a hard conversation with your co-founder around the three-month mark, and depending on how it’s going (see below), either re-commit or change the idea. Then schedule a yearly check-in. If things are clicking, full speed ahead. If things feel meh, at least spend a few days talking about other potential directions.

Brex: “We applied to YC with this VR idea, which, looking back, it was pretty bad, but at the time we thought it was great. And within YC, we were like, ‘Yeah, we don’t even know where to start to build this.’” —Henrique Dubugras, co-founder and CEO

Some people are great at giving gifts. The kinds of gifts that dig into your soul and make you feel seen. I'm trying to become one of those people

Simon conspired with a friend who owns a 3D printer and designed and created a little desktop bear that can hold all of the nice things people have written about Bear. He then wrote each of these entries by hand (suffering only minor carpel tunnel) on sticky notes which the bear now carries like a human bear directional.

These are the kinds of gifts I want to learn how to give. Ones that make the receiver feel like they've been listened to and understood. That don't cost much money but are priceless at the same time.

Things seemed to go well at the beginning. Due to the pandemic and the objective challenges of the traditional Brick & Mortar business, the business operated by Nike Direct (the business unit in charge of DTC) was flying and justifying the important strategic decisions of the CEO. Then, once normality came back, things slowly but regularly, quarter by quarter, showed that the separation line between being ambitious or being wrong was very thin.

In 6 months, hundreds of colleagues were fired and together with them Nike lost a solid process and thousands of years of experience and expertise in running, football, basketball, fitness, training, sportwear, etc., built in decades of footwear leadership (and apparel too). Product engine became gender led: women, men, and kids (like Zara, GAP, H&M or any other generic fashion brand).

Consumers are not so elastic as some business leaders think or hope. And consumers are not so loyal as some business leaders think or hope. So, what happened? Simple. Many consumers - mainly occasional buyers - did not follow Nike (surprise, surprise) but continued shopping where they were shopping before the decision of the CEO and the President of the Brand. So, once they could not find Nike sneakers in “their” stores – because Nike wasn’t serving those stores any longer -, they simply opted for other brands.

Until late 2010s, Nike had been on a total offense mode (being #1 in every market, in every category, in every product BU, basically in every dimension), a sort of military occupation of the marketplace and a huge problem for competitors that did not know how to react under such a domination. The strategic focus was only one: win anywhere. The new strategy determined the end of the marketplace occupation. Nike opened unexpected spaces to competitors, small, medium, or large brands (with exception of the company based in Herzogenaurach, that – as they usually do - copied and pasted the Nike strategy and executed it in a milder format).

One of the empiric laws of business says that online, the main lever of competition is “price” (as the organic consumer funnel is built on price comparison). The proverbial ability of Nike to leverage the power of the brand to sell sneakers at 200$ began to be threatened by the online appetite for discounts and the search for a definitive solution to the inventory issue. Gross margin – because of that – instead of growing due to the growth of DTC business, showed a rapid decline due to a never-ending promotional attitude on Nike.com

Nike has been built for 50 years on a very simple foundation: brand, product, and marketplace. The DC Investment model, since Nike became a public company, has been always the same: invest at least one tenth of the revenues in demand creation and sports marketing. The brand model has been very simple as well: focus on innovation and inspiration, creativity and storytelling based on athletes-products synergy, leveraging the power of the emotions that sport can create, trying to inspire a growing number of athletes* (*if you have a body, you are an athlete) to play sport. That’s what made Nike the Nike we used to know, love, admire, professionally and emotionally.

What happened in 2020? Well, the brand team shifted from brand marketing to digital marketing and from brand enhancing to sales activation.

shift from CREATE DEMAND to SERVE AND RETAIN DEMAND, that meant that most of the investment were directed to those who were already Nike consumers

as of 2021, to drive traffic to Nike.com, Nike started investing in programmatic adv and performance marketing the double or more of the share of resources usually invested in the other brand activities

the former CMO was ignoring the growing academic literature around the inefficiencies of investment in performance marketing/programmatic advertising, due to frauds, rising costs of mediators and declining consumer response to those activities.

Because of that, Nike invested a material amount of dollars (billions) into something that was less effective but easier to be measured vs something that was more effective but less easy to be measured.

To feed the digital marketing ecosystem, one of the historic functions of the marketing team (brand communications) was “de facto” absorbed and marginalized by the brand design team, which took the leadership in marketing content production (together with the mar-tech “scientists”). Nike didn’t need brand creativity anymore, just a polished and never stopping supply chain of branded stuff.

He made “Nike.com” the center of everything and diverted focus and dollars to it. Due to all of that, Nike hasn’t made a history making brand campaign since 2018, as the Brand organization had to become a huge sales activation machine.

Last fall, while reporting Esquire’s “Future of Books” predictions, I asked industry insiders about trends they’d noticed in recent years. Almost everyone mentioned that debut fiction has become harder to launch. For writers, the stakes are do or die: A debut sets the bar for each of their subsequent books, so their debut advance and sales performance can follow them for the rest of their career. For editors, if a writer’s first book doesn’t perform, it’s hard to make a financial case for acquiring that writer’s second book. And for you, a reader interested in great fiction, the fallout from this challenging climate can limit your access to exciting new voices in fiction. Unless you diligently shop at independent bookstores where booksellers highlight different types of books, you might only ever encounter the big, splashy debuts that publishers, book clubs, social-media algorithms, and big-box retailers have determined you should see.

BookTok—er, TikTok—is still considered the au courant emergent platform, but unlike Instagram and Twitter before it, publishers can’t figure out how to game the algorithm. “It’s a wonderful tool, but it’s an uncontrollable one,” Lucas says. As opposed to platforms like Twitter and Instagram, on which authors can actively post to establish a following, the runaway hits of BookTok (see: The Song of Achilles) grew from influencer videos.

These days, “in order to get exposure, you have to make the kinds of content that the platform is prioritizing in a given moment,” Chayka says. On Instagram, that means posting videos. Gone are the days of the tastefully cluttered tableaux of notebooks, pens, and coffee mugs near a book jacket; front-facing videos are currently capturing the most eyeballs. “A nonfiction author at least has the subject matter to talk about,” Chayka says. (Many nonfiction writers now create bite-size videos distilling the ideas of their books, with the goal of becoming thought leaders.) But instead of talking about their books, novelists share unboxing videos when they receive their advance copies, or lifestyle videos about their writing routines, neither of which convey their voice on the page. Making this “content” takes time away from writing, Chayka says: “You’re glamorizing your writer’s residency; you’re not talking about the work itself necessarily.”

“Energy tends to attach itself to wherever energy is already attached,” Lucas says. “Fewer debuts have a chance of really breaking through the noise in this climate, because all of the energy attaches itself to the ones that have made it past a certain obstacle.” In some cases, the energy starts building as early as when a project is first announced.

Because staff publicists at publishing houses must split their workload among several authors, there is an expectation that an author will now spend untold hours working as their book’s spokesperson.

The agent at the talent firm describes a “one strike and you’re out” mentality, with some authors getting dropped by their agents if their debut doesn’t sell well.

But one positive development amid this sense of precarity is the rise of the literary friendship. “On social media,” Isle McElroy wrote for this magazine in September, “writers are just as likely to hype their peers as they are to self-promote: linking where to buy books, posting photos of readings, and sharing passages from galleys.” There is now an all-ships-rise mentality among authors at every career stage, but particularly among first-time novelists. Now networks of writers are more important than ever.

When it was time to ask other writers for blurbs for The Volcano Daughters, Balibrera had friends who were excited to boost the book, but she could also rely on other writers who remembered her from Literati. “There was goodwill built up already,” Gibbs says.

The thing I most worry about using anti-perfectionism arguments is that it begs a vision in the first place—perfectionism requires an idea of what's perfect. Projects suffer from a lack of real hypotheses. Fine, just build. But if you're cutting something important to others by calling it too perfect, can you define the goal (not just the ingredients)? We tend to justify these things by saying, we'll iterate. Much like perfectionism can always be criticized, iteration can theoretically always make a thing better. Iteration is not vision and strategy, it's nearly the reverse, it hedges vision and strategy. This is a slightly different point, but when we say we don't need this extra security or that UX performance, you're setting a ceiling on the people who are passionate about them. Those things really do have limits (no illusions!), but you're not just cutting corners, you're cutting specific corners. That's a company's culture. Being accused of perfectionism justifiably leads to upset that the company doesn't care about security or users. Yeah, maybe it's limited to this one project, but often not.

Perfection can be the enemy of the good. It's that it's not a particularly a helpful critique. To use the article’s concept, it’s the wrong scale. It might be helpful to an individual in a performance review, but it doesn’t say why X is unnecessary in this project or at this company. Little is added to the discussion until I describe X relative to the goal. Perfectionism is indeed good to avoid—it's basically defined as a bad thing by being "too". But the better conversation says how X falls short on certain measuring sticks. At the very least it actually engages X in the X discussion. Perfectionism is more of a critique of the person.

It takes effort to understand the person's idea enough to engage it, but more importantly it takes work that was supposed to (but might not) have gone into developing good projects or goals in the first place. Projects well-formed enough to create constraints for themselves.

I agree with the thesis of this article but I actually think the point would be better made if we switch from talking about optimizing to talking about satisficing[1]. Simply put, satisficing is searching for a solution that meets a particular threshold for acceptability, and then stopping. My personal high-level strategy for success is one of continual iterative satisficing. The iterative part means that once I have met an acceptability criterion, I am free to either move on to something else, or raise my bar for acceptability and search again. I never worry about whether a solution is optimal, though, only if it is good enough. I think that this is what many people are really doing when they say they are "optimizing", but using the term "optimzing" leads to confusion, because satisficing solutions are by definition non-optimal (except by luck), and some people (especially the young, in my experience) seem to feel compelled to actually optimize, leading to unnecessary perfectionism.

Perfectionism is sort of polarizing, and a lot of product manager / CEO types see it as the enemy. In certain contexts it might be, but in others “perfectionism” translates to “building the foundation flawlessly with the downstream dependencies in mind to minimize future tech debt.” Of course, a lot of managers prefer to pretend that tech debt doesn’t exist but that’s just because they don’t think they can pay it off in time before their team gets cut for not producing any value because they were so busy paying off tech debt.

kthejoker2 3 months ago | prev | next [–] Not sure you can talk about perfectionism without clarifying between "healthy" perfectionism and "unhealthy" perfectionism. Both exist, but often people are thinking of one or the other when discussing perfectionism, and it creates cognitive dissonance when two people thinking of the two different modes are singing perfectionism's praises or denouncing its practice.

looking at these comments, it seems perfectionism is ill-defined. it seems to be positive - perfectionism is not giving up, it is excellence, it is beyond mediocre. it also seems to be negative - it is going too far, it is avoiding/procrastinating, it is self-defeating. I wonder what the perfect definition would be?

Cloud apps like Google Docs and Trello are popular because they enable real-time collaboration with colleagues, and they make it easy for us to access our work from all of our devices. However, by centralizing data storage on servers, cloud apps also take away ownership and agency from users. If a service shuts down, the software stops functioning, and data created with that software is lost.

In this article we propose “local-first software”: a set of principles for software that enables both collaboration and ownership for users. Local-first ideals include the ability to work offline and collaborate across multiple devices, while also improving the security, privacy, long-term preservation, and user control of data.

This article has also been published in PDF format in the proceedings of the Onward! 2019 conference. Please cite it as: Martin Kleppmann, Adam Wiggins, Peter van Hardenberg, and Mark McGranaghan. Local-first software: you own your data, in spite of the cloud. 2019 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (Onward!), October 2019, pages 154–178. doi:10.1145/3359591.3359737

To sum up: the cloud gives us collaboration, but old-fashioned apps give us ownership. Can’t we have the best of both worlds? We would like both the convenient cross-device access and real-time collaboration provided by cloud apps, and also the personal ownership of your own data embodied by “old-fashioned” software.

In old-fashioned apps, the data lives in files on your local disk, so you have full agency and ownership of that data: you can do anything you like, including long-term archiving, making backups, manipulating the files using other programs, or deleting the files if you no longer want them. You don’t need anybody’s permission to access your files, since they are yours. You don’t have to depend on servers operated by another company.

In cloud apps, the data on the server is treated as the primary, authoritative copy of the data; if a client has a copy of the data, it is merely a cache that is subordinate to the server. Any data modification must be sent to the server, otherwise it “didn’t happen.” In local-first applications we swap these roles: we treat the copy of the data on your local device — your laptop, tablet, or phone — as the primary copy. Servers still exist, but they hold secondary copies of your data in order to assist with access from multiple devices. As we shall see, this change in perspective has profound implications.

For several years the Offline First movement has been encouraging developers of web and mobile apps to improve offline support, but in practice it has been difficult to retrofit offline support to cloud apps, because tools and libraries designed for a server-centric model do not easily adapt to situations in which users make edits while offline.

In local-first apps, our ideal is to support real-time collaboration that is on par with the best cloud apps today, or better. Achieving this goal is one of the biggest challenges in realizing local-first software, but we believe it is possible

Some file formats (such as plain text, JPEG, and PDF) are so ubiquitous that they will probably be readable for centuries to come. The US Library of Congress also recommends XML, JSON, or SQLite as archival formats for datasets. However, in order to read less common file formats and to preserve interactivity, you need to be able to run the original software (if necessary, in a virtual machine or emulator). Local-first software enables this.

Of these, email attachments are probably the most common sharing mechanism, especially among users who are not technical experts. Attachments are easy to understand and trustworthy. Once you have a copy of a document, it does not spontaneously change: if you view an email six months later, the attachments are still there in their original form. Unlike a web app, an attachment can be opened without any additional login process. The weakest point of email attachments is collaboration. Generally, only one person at a time can make changes to a file, otherwise a difficult manual merge is required. File versioning quickly becomes messy: a back-and-forth email thread with attachments often leads to filenames such as Budget draft 2 (Jane's version) final final 3.xls.

Web apps have set the standard for real-time collaboration. As a user you can trust that when you open a document on any device, you are seeing the most current and up-to-date version. This is so overwhelmingly useful for team work that these applications have become dominant.

The flip side to this is a total loss of ownership and control: the data on the server is what counts, and any data on your client device is unimportant — it is merely a cache

We think the Git model points the way toward a future for local-first software. However, as it currently stands, Git has two major weaknesses: Git is excellent for asynchronous collaboration, especially using pull requests, which take a coarse-grained set of changes and allow them to be discussed and amended before merging them into the shared master branch. But Git has no capability for real-time, fine-grained collaboration, such as the automatic, instantaneous merging that occurs in tools like Google Docs, Trello, and Figma. Git is highly optimized for code and similar line-based text files; other file formats are treated as binary blobs that cannot meaningfully be edited or merged. Despite GitHub’s efforts to display and compare images, prose, and CAD files, non-textual file formats remain second-class in Git.

A web app in its purest form is usually a Rails, Django, PHP, or Node.js program running on a server, storing its data in a SQL or NoSQL database, and serving web pages over HTTPS. All of the data is on the server, and the user’s web browser is only a thin client. This architecture offers many benefits: zero installation (just visit a URL), and nothing for the user to manage, as all data is stored and managed in one place by the engineering and DevOps professionals who deploy the application. Users can access the application from all of their devices, and colleagues can easily collaborate by logging in to the same application. JavaScript frameworks such as Meteor and ShareDB, and services such as Pusher and Ably, make it easier to add real-time collaboration features to web applications, building on top of lower-level protocols such as WebSocket. On the other hand, a web app that needs to perform a request to a server for every user action is going to be slow. It is possible to hide the round-trip times in some cases by using client-side JavaScript, but these approaches quickly break down if the user’s internet connection is unstable.

As we have shown, none of the existing data layers for application development fully satisfy the local-first ideals. Thus, three years ago, our lab set out to search for a solution that gives seven green checkmarks.

Thus, CRDTs have some similarity to version control systems like Git, except that they operate on richer data types than text files. CRDTs can sync their state via any communication channel (e.g. via a server, over a peer-to-peer connection, by Bluetooth between local devices, or even on a USB stick). The changes tracked by a CRDT can be as small as a single keystroke, enabling Google Docs-style real-time collaboration. But you could also collect a larger set of changes and send them to collaborators as a batch, more like a pull request in Git. Because the data structures are general-purpose, we can develop general-purpose tools for storage, communication, and management of CRDTs, saving us from having to re-implement those things in every single app.

we believe that CRDTs have the potential to be a foundation for a new generation of software. Just as packet switching was an enabling technology for the Internet and the web, or as capacitive touchscreens were an enabling technology for smartphones, so we think CRDTs may be the foundation for collaborative software that gives users full ownership of their data.

We are often asked about the effectiveness of automatic merging, and many people assume that application-specific conflict resolution mechanisms are required. However, we found that users surprisingly rarely encounter conflicts in their work when collaborating with others, and that generic resolution mechanisms work well. The reasons for this are: Automerge tracks changes at a fine-grained level, and takes datatype semantics into account. For example, if two users concurrently insert items at the same position into an array, Automerge combines these changes by positioning the two new items in a deterministic order. In contrast, a textual version control system like Git would treat this situation as a conflict requiring manual resolution. Users have an intuitive sense of human collaboration and avoid creating conflicts with their collaborators. For example, when users are collaboratively editing an article, they may agree in advance who will be working on which section for a period of time, and avoid concurrently modifying the same section.

Conflicts arise only if users concurrently modify the same property of the same object: for example, if two users concurrently change the position of the same image object on a canvas. In such cases, it is often arbitrary how they are resolved and satisfactory either way.

We experimented with a number of mechanisms for sharing documents with other users, and found that a URL model, inspired by the web, makes the most sense to users and developers. URLs can be copied and pasted, and shared via communication channels such as email or chat. Access permissions for documents beyond secret URLs remain an open research question.

As with a Git repository, what a particular user sees in the “master” branch is a function of the last time they communicated with other users. Newly arriving changes might unexpectedly modify parts of the document you are working on, but manually merging every change from every user is tedious. Decentralized documents enable users to be in control over their own data, but further study is needed to understand what this means in practical user-interface terms.

Performance and memory/disk usage quickly became a problem because CRDTs store all history, including character-by-character text edits. These pile up, but can’t easily be truncated because it’s impossible to know when someone might reconnect to your shared document after six months away and need to merge changes from that point forward.

Servers thus have a role to play in the local-first world — not as central authorities, but as “cloud peers” that support client applications without being on the critical path. For example, a cloud peer that stores a copy of the document, and forwards it to other peers when they come online, could solve the closed-laptop problem above.

These experiments suggest that local-first software is possible. Collaboration and ownership are not at odds with each other — we can get the best of both worlds, and users can benefit. However, the underlying technologies are still a work in progress. They are good for developing prototypes, and we hope that they will evolve and stabilize in the coming years, but realistically, it is not yet advisable to replace a proven product like Firebase with an experimental project like Automerge in a production setting today.

Most CRDT research operates in a model where all collaborators immediately apply their edits to a single version of a document. However, practical local-first applications require more flexibility: users must have the freedom to reject edits made by another collaborator, or to make private changes to a version of the document that is not shared with others. A user might want to apply changes speculatively or reformat their change history. These concepts are well understood in the distributed source control world as “branches,” “forks,” “rebasing,” and so on. There is little work to date on understanding the algorithms and programming models for collaboration in situations where multiple document versions and branches exist side-by-side.

Different collaborators may be using different versions of an application, potentially with different features. As there is no central database server, there is no authoritative “current” schema for the data. How can we write software so that varying application versions can safely interoperate, even as data formats evolve? This question has analogues in cloud-based API design, but a local-first setting provides additional challenges.

When every document can develop a complex version history, simply through daily operation, an acute problem arises: how do we communicate this version history to users? How should users think about versioning, share and accept changes, and understand how their documents came to be a certain way when there is no central source of truth? Today there are two mainstream models for change management: a source-code model of diffs and patches, and a Google Docs model of suggestions and comments. Are these the best we can do? How do we generalize these ideas to data formats that are not text?

We believe that the assumption of centralization is deeply ingrained in our user experiences today, and we are only beginning to discover the consequences of changing that assumption. We hope these open questions will inspire researchers to explore what we believe is an untapped area.

some strategies for improving each area: Fast. Aggressive caching and downloading resources ahead of time can be a way to prevent the user from seeing spinners when they open your app or a document they previously had open. Trust the local cache by default instead of making the user wait for a network fetch. Multi-device. Syncing infrastructure like Firebase and iCloud make multi-device support relatively painless, although they do introduce longevity and privacy concerns. Self-hosted infrastructure like Realm Object Server provides an alternative trade-off. Offline. In the web world, Progressive Web Apps offer features like Service Workers and app manifests that can help. In the mobile world, be aware of WebKit frames and other network-dependent components. Test your app by turning off your WiFi, or using traffic shapers such as the Chrome Dev Tools network condition simulator or the iOS network link conditioner. Collaboration. Besides CRDTs, the more established technology for real-time collaboration is Operational Transformation (OT), as implemented e.g. in ShareDB. Longevity. Make sure your software can easily export to flattened, standard formats like JSON or PDF. For example: mass export such as Google Takeout; continuous backup into stable file formats such as in GoodNotes; and JSON download of documents such as in Trello. Privacy. Cloud apps are fundamentally non-private, with employees of the company and governments able to peek at user data at any time. But for mobile or desktop applications, try to make clear to users when the data is stored only on their device versus being transmitted to a backend. User control. Can users easily back up, duplicate, or delete some or all of their documents within your application? Often this involves re-implementing all the basic filesystem operations, as Google Docs has done with Google Drive.

If you are an entrepreneur interested in building developer infrastructure, all of the above suggests an interesting market opportunity: “Firebase for CRDTs.” Such a startup would need to offer a great developer experience and a local persistence library (something like SQLite or Realm). It would need to be available for mobile platforms (iOS, Android), native desktop (Windows, Mac, Linux), and web technologies (Electron, Progressive Web Apps). User control, privacy, multi-device support, and collaboration would all be baked in. Application developers could focus on building their app, knowing that the easiest implementation path would also given them top marks on the local-first scorecard. As litmus test to see if you have succeeded, we suggest: do all your customers’ apps continue working in perpetuity, even if all servers are shut down? We believe the “Firebase for CRDTs” opportunity will be huge as CRDTs come of age.

In the pursuit of better tools we moved many applications to the cloud. Cloud software is in many regards superior to “old-fashioned” software: it offers collaborative, always-up-to-date applications, accessible from anywhere in the world. We no longer worry about what software version we are running, or what machine a file lives on. However, in the cloud, ownership of data is vested in the servers, not the users, and so we became borrowers of our own data. The documents created in cloud apps are destined to disappear when the creators of those services cease to maintain them. Cloud services defy long-term preservation. No Wayback Machine can restore a sunsetted web application. The Internet Archive cannot preserve your Google Docs. In this article we explored a new way forward for software of the future. We have shown that it is possible for users to retain ownership and control of their data, while also benefiting from the features we associate with the cloud: seamless collaboration and access from anywhere. It is possible to get the best of both worlds. But more work is needed to realize the local-first approach in practice. Application developers can take incremental steps, such as improving offline support and making better use of on-device storage. Researchers can continue improving the algorithms, programming models, and user interfaces for local-first software. Entrepreneurs can develop foundational technologies such as CRDTs and peer-to-peer networking into mature products able to power the next generation of applications. Today it is easy to create a web application in which the server takes ownership of all the data. But it is too hard to build collaborative software that respects users’ ownership and agency. In order to shift the balance, we need to improve the tools for developing local-first software. We hope that you will join us.

I think she enjoys treating her boyfriend like a chore because her relationship with her parents acclimated her to the feeling of being depended on. She likes the feeling of parenting and babying someone because her child-self had to do that to stay on her parents’ good side. In other words, her psyche felt like, in order to keep her parents’ love and protection, she needed to turn herself into a caretaker, going above and beyond what she knows she should be doing.

Patterns that are formed out of necessity in an earlier stage of life determine what you look for for the rest of your life. The behaviors you were forced to do when you were younger become the behaviors you itch to do when you’re older.

Like making a tie-dye T-shirt, the twists and turns of childhood shape the way we’re colored as adults.

The AI trust crisis 14th December 2023 Dropbox added some new AI features. In the past couple of days these have attracted a firestorm of criticism. Benj Edwards rounds it up in Dropbox spooks users with new AI features that send data to OpenAI when used. The key issue here is that people are worried that their private files on Dropbox are being passed to OpenAI to use as training data for their models—a claim that is strenuously denied by Dropbox. As far as I can tell, Dropbox built some sensible features—summarize on demand, “chat with your data” via Retrieval Augmented Generation—and did a moderately OK job of communicating how they work... but when it comes to data privacy and AI, a “moderately OK job” is a failing grade. Especially if you hold as much of people’s private data as Dropbox does! Two details in particular seem really important. Dropbox have an AI principles document which includes this: Customer trust and the privacy of their data are our foundation. We will not use customer data to train AI models without consent. They also have a checkbox in their settings that looks like this: Update: Some time between me publishing this article and four hours later, that link stopped working. I took that screenshot on my own account. It’s toggled “on”—but I never turned it on myself. Does that mean I’m marked as “consenting” to having my data used to train AI models? I don’t think so: I think this is a combination of confusing wording and the eternal vagueness of what the term “consent” means in a world where everyone agrees to the terms and conditions of everything without reading them. But a LOT of people have come to the conclusion that this means their private data—which they pay Dropbox to protect—is now being funneled into the OpenAI training abyss. People don’t believe OpenAI # Here’s copy from that Dropbox preference box, talking about their “third-party partners”—in this case OpenAI: Your data is never used to train their internal models, and is deleted from third-party servers within 30 days. It’s increasing clear to me like people simply don’t believe OpenAI when they’re told that data won’t be used for training. What’s really going on here is something deeper then: AI is facing a crisis of trust. I quipped on Twitter: “OpenAI are training on every piece of data they see, even when they say they aren’t” is the new “Facebook are showing you ads based on overhearing everything you say through your phone’s microphone” Here’s what I meant by that. Facebook don’t spy on you through your microphone # Have you heard the one about Facebook spying on you through your phone’s microphone and showing you ads based on what you’re talking about? This theory has been floating around for years. From a technical perspective it should be easy to disprove: Mobile phone operating systems don’t allow apps to invisibly access the microphone. Privacy researchers can audit communications between devices and Facebook to confirm if this is happening. Running high quality voice recognition like this at scale is extremely expensive—I had a conversation with a friend who works on server-based machine learning at Apple a few years ago who found the entire idea laughable. The non-technical reasons are even stronger: Facebook say they aren’t doing this. The risk to their reputation if they are caught in a lie is astronomical. As with many conspiracy theories, too many people would have to be “in the loop” and not blow the whistle. Facebook don’t need to do this: there are much, much cheaper and more effective ways to target ads at you than spying through your microphone. These methods have been working incredibly well for years. Facebook gets to show us thousands of ads a year. 99% of those don’t correlate in the slightest to anything we have said out loud. If you keep rolling the dice long enough, eventually a coincidence will strike. Here’s the thing though: none of these arguments matter. If you’ve ever experienced Facebook showing you an ad for something that you were talking about out-loud about moments earlier, you’ve already dismissed everything I just said. You have personally experienced anecdotal evidence which overrides all of my arguments here.

One consistent theme I’ve seen in conversations about this issue is that people are much more comfortable trusting their data to local models that run on their own devices than models hosted in the cloud. The good news is that local models are consistently both increasing in quality and shrinking in size.

Through this strategy, Dotdash Meredith allegedly identifies small sites that have cemented themselves in Google results for a specific (and valuable) term or in a specific topic, with the goal of pushing them down the rankings by publishing vast amounts of content of their own.

“IAC’s vision for Dotdash Meredith — to be a flywheel for generating advertising and commerce revenue — is finally starting to pan out.  […] More than 80% of Dotdash Meredith’s traffic and digital revenue come from its core sites, such as Food & Wine, Travel & Leisure, and Southern Living, that deliver a form of what one might think of as commerce-related service journalism.” — Allison Schiff, managing editor of AdExchanger

To give the pet insurance affiliate section of Forbes the best chance to succeed, the Forbes Advisor team pumped out A LOT of content about pets and built A LOT of links around the topic with statistics round-ups designed to obfuscate the original sources in order to increase the chances of people linking to Forbes.com when using the stats

All this hard work paid off in the form of an estimated 1.1 million visitors each month to the pet insurance section of Forbes Advisor

This happened at the expense of every site that has produced content about dogs, cats, and other pets for many years before Forbes.com decided to cash in on pet insurance affiliate money.  They successfully replicated this model again and again and again across the huge variety of topics that Forbes covers today.

Step one: buy the site. Step two: fire staff. Step three: revamp the content strategy to drive new monetizable traffic from Google

“As a journalist, all of this depresses me,” wrote Brian Merchant, the technology columnist at the Los Angeles Times. He continued, “If journalists are outraged at the rise of AI and its use in editorial operations and newsrooms, they should be outraged not because it’s a sign that they’re about to be replaced but because management has such little regard for the work being done by journalists that it’s willing to prioritize the automatic production of slop.”

Here’s a recap so far: Digital media conglomerates are developing SEO content strategies designed to out-publish high-ranking specialist independent publishers. Legacy media brands are building in-house SEO content teams that tie content creation to affiliate marketing revenue in topics that have nothing to do with their original areas of expertise. Newly created digital media companies are buying once successful and influential blogs with the goal of driving traffic to casino sites. Private equity firms are partnering with companies like AdVon to publish large amounts of AI-generated content edited by SEO-focused people across their portfolio of media brands. And here’s the worst part: Google’s algorithm encourages all of them to rinse and repeat the same strategies by allowing their websites to rank in top positions for SEO-fueled articles about any topic imaginable. Even in cases when the articles have been written by AI and published under fake authors.

Women spend twice as much time as men, on average, on childcare and household work. All groups experience a free-time gender gap, with women having 13% less free time than men, on average. Mothers spend 2.3X as much time as fathers on the essential and unpaid work of taking care of home and family Young women (18-24) experience one of the largest free-time gender gaps, having 20% less free time than men their age Working women spend 2X as many hours per week as working men on childcare and household work combined Mothers who work part-time spend 3.8X as much time on childcare and household work as fathers who work part-time Married women without children spend 2.3X as much time as their male counterparts on household work Among Latinos, mothers spend more than 3.6X as much time as fathers taking care of children and doing household work

The unequal division of unpaid work in the home, such as cooking, cleaning, and shopping for food and clothing, is a powerful testament to the tenacity of old gender norms. Women do significantly more of this work than men do, even when there are no children living in the home. This holds true for women regardless of their marital status, their employment status, or their level of education.

Among all adults without children, women do twice as much household work as men, dedicating 12.3 hours per week to these tasks, on average, compared to 6 hours for men. Similarly, among all single people without children, women do nearly twice as much household work as men, spending 10.6 hours per week on household tasks compared to 5.7 hours for men.

getting married seems to exacerbate the burden of household work on women. Married women do substantially more household work than their single women peers, while married men spend just a few minutes a day more than their single peers. Married women without children do 2.3 times as much household work as their male counterparts (14.3 hours per week versus 6.2 hours).

Working women spend significantly more time than working men on unpaid work in the home. This is the case whether they work full-time or part-time. It is the case whether they have children or not. Take household work like cooking, laundry, and the like. Women who work full-time do 1.8 times as much as men who work full-time; they spend 9.7 hours per week on it compared to 5.4 hours for men. Women who work part-time do 2.5 times as much household work as men who work part-time.

Across every group studied, men spend more time than women socializing, watching sports or playing video games, or doing similar activities to relax or have fun. Women overall have 13% less free time than men, on average. The gap balloons among some groups, with women having up to one-quarter less free time than men.

Women overall have 13% less free time than men, on average. The gap balloons among some groups, with women having up to nearly one-quarter less free time than men.

there is a wide gulf between our ideals and our realities, as we have seen in this report on how Americans divide the work of taking care of home and family. One reason for the persistence of these gender disparities is that the U.S. has failed to modernize its public policies to fit 21st century economic realities. Even though 78% of American women are in the labor force, the nation’s social infrastructure is still largely premised on the assumption that mothers will be at home with children.

Every high-income nation in the world provides for paid leave for new parents—except the United States. Most provide ample financial and institutional support for childcare and preschool. Our peers devote a substantial share of public spending to family benefits, but the U.S. invests only minimally in supporting families. For instance, family benefits account for 2.4% of GDP in Germany compared to 0.6% in the United States.

Even when young children enter school, typical American school hours are grossly misaligned with the workday, forcing families to either spend money on after school care or reduce their work hours.

Public policy alone will not entirely eliminate these deeply rooted gender disparities. Cultural change is needed too. But smart policy can nudge along positive behavioral change that ultimately advances equity and equality. For example, several countries include mechanisms in their family policy to encourage fathers to take paid parent leave. Many Nordic nations have a ‘use it or lose it’ provision for fathers. Other countries, like Canada, provide extra paid weeks of leave to families if both parents use the time.

The unequal division of care work, particularly, affects women’s opportunity and well-being in ways that cannot be measured solely in dollars and cents.

One way Americans deal with the housing affordability crisis is to move to distant suburbs and exurbs, where housing is cheaper than it is in central cities and job hubs. The tradeoff, however, is typically a long commute to and from work. But for women who are caring for children or elderly relatives, long commutes are often not feasible. Children and elderly parents get sick and need to get to doctors in the middle of a workday. School hours begin too late and end too early to accommodate a commute to a 9-to-5 job.

when schools close due to climate-driven events, mothers might have to take unpaid time off of work or pay for childcare. As Americans experience more dangerous heat waves, wildfires, and floods driven by climate change, the caregiving demands on women can increase, as they are more likely to be the ones responsible for helping children and elderly adults stay out of harm’s way.

Earlier this month, the Gender Equity Policy Institute released a new analysis of the 2022 Time Use Survey, administered by the U.S. Bureau of Labor Statistics. The Time Use Survey is not perfect or granular, but it’s widely understood as the best and broadest data set of how Americans allocate their time. The survey asks respondents where and how they worked, how much time they allocated to childcare and/or domestic tasks, and how many hours were dedicated to “leisure.” You can take a closer look at the survey methodology and results here — and while they do breakdown results by race, age, income, education level, marital status, occupation, and number of children in the household, they do not distinguish between heterosexual and queer relationships (and also divide gender as male or female)….which means this analysis does not account for how queer relationships, in so many meanings of the word, fit into this larger analysis. With that said — the findings are stunning.

women spend more than twice as much time allocated to household work than men, even when they are single or do not have children. And getting married doesn’t split the load for women, as it theoretically would, but increases it: married women without children still do 2.3 times as much housework labor as their husbands.

men just had to hunt, but women back at the cave had to tend fires and care for kids and tan animal hides blah blah blah etc etc etc. These narratives make the nonsensical make sense: how else would you explain dramatically different approaches to cleanliness that seem to be fairly neatly divided by gender? It has to be biological, otherwise, well, women have just been caring about things that ultimately matter very little for centuries.

this particular argument falls apart when you consider women who aren’t “naturally” good at cleaning, or multi-tasking, or even caregiving — or just don’t like it. (Hello, all the ADHDers in my DMs also responding to these stats). Within this framework, the only way to conceive of these women is as faulty specimens: people who would be weeded out by natural selection. And yet somehow these people are still here, being women!

“Everything we call a sex difference, if you take a different perspective — what’s the power angle on this — often explains things,” neuroscientist Lise Eliot tells Darcy Lockman in All the Rage. “It has served men very well to assume that male-female differences are hard-wired.”

cleaning can be pleasurable the same way that popping a zit is pleasurable. It’s gross but oddly cathartic to erase abjection and mess, or to create order out of chaos. But you cannot separate the pleasures of degreasing the stove top from the pleasures of successfully meeting the demands of proper performance of womanhood. It’s like people who say they “just like being thin.” So much of why you like it is because it grants you societal power.

men can clean! I know men who are good at it, who take pleasure in it, who are also excellent noticers and multitaskers — and almost all of them were either 1) raised by single mothers or 2) spent time in the military. They were socialized, over an extended period, to understand cleanliness and multi-tasking as essential — with personal and social consequences if they did not.

“When people come over and our house is a mess, I feel this reflects badly on me as a person, adult, wife, and mother. My husband doesn't feel that at all,” a reader named Leah told me. “My father-in-law once told my husband he wished our house was cleaner when he comes to visit (don’t get me started). So now I scour the place top to bottom. My husband just shrugs and says: whatever, my dad can deal with it. The same applies to our kid. My husband can send him to school in ripped, dirty, or too-small clothes and not worry what people will think of him and his parenting skills. Me? I’m worried they are about to call CPS on us.”

if you’re “safe” being bad at womanhood — you can blow off societal repercussions. But a messy or dirty domestic space intersects with so many other stereotypes of class, race, education level, body size, and marital status. “My grandma grew up extremely poor in the South and I’ve always felt there was a strong class element to her standard of cleanliness,” a woman named Aimee told me. “Like even if you had no money, get a broom and a rag because you at least need a clean house.”

Or: a single woman can have a dirty apartment if she’s a hot, dirty mess; take away the hot thinness and she’s just a slovenly cat lady spinster.

I don’t think most people believe this! Yet these understandings endure, asking women to feel like failures or oddities, setting up shop in our relationships and slowly festering.

It is tremendously hard to divest from a way of understanding your own value in the world — and, by extension, others.

Men are socialized to see their spaces as utilitarian, spaces that serve them. Women, we serve our spaces.”

We can attempt, as a society, to socialize boys and men to be more clean, to notice more, to multitask more, to spend more time on domestic tasks and to allocate less time to leisure. We can teach men that their value (and their morality) is also rooted in their capacity to maintain a clean home: that they should also serve their spaces.

some of this work has happened: men in their 30s and 40s today do more domestic labor than their grandparents or great-grandparents did. But the gender discrepancy in domestic labor closed and closed and then….got stuck at a 65/35 split, and hasn’t budged in years.

The math just doesn’t math when it comes to domestic labor. When dads start allocating more time to parenting, it doesn’t subtract from the time moms spent parenting. When women leave the home to work for pay, the number of hours they allocate to domestic tasks doesn’t decrease, as one might assume, but goes up. If men do more, women still…..do more.

If you feel bound by these expectations: what would it take to free you? Because when I survey the hundreds of responses that arrived in my DMS when I posted the stats above, what I felt most was fatigue. Just look in the fucking drawer, is that where the bras go??? one woman wrote. God I’m so tired.

I’m always suspicious of arguments that ask anyone who’s subjugated, in some way, to do more. But in this case, the work is difficult, particularly for bourgeois women, because the work feels like something we’re so rarely asked to do: less.

At my grandmother's funeral, literally every single speaker talked about how much she loved her...house. How much care she put into it, how it was the joy of her life and source of her identity. When I was a kid, there was "clean" and there was "grandma clean". And after my mother died and I was rocked by grief, my grandmother attempted to console me by suggesting it wasn't that big of a loss because my mom (her daughter-in-law) wasn't a good housekeeper. (My mom was working full time, had four kids at home, and was literally dying.) I was so angry with my grandmother I barely every spoke to her again, and then at her funeral listening to everyone talk about her love of her house (!!) drove home what a waste of a life that was. She could have been kind. She could have been kind to my mom, who'd lost her own mother and was struggling. She could have been kind to me, her grand-daughter who was grieving. She could have had a life that meant something, but instead she focused on her house, which she saw as an extension of herself, and serviced her own pride and vanity. What a WASTE.

I feel like I am constantly drowning in a sea of paperwork/phone calls/emails - fighting with our health and dental insurance, calling contractors/plumbers/etc to do things for our house, filling out new tax paperwork. Not to mention fielding the barrage of spam emails/calls. I feel like this kind of stuff has expanded exponentially and I can’t tell if it’s just me, but it feels like every single one of these is a fight - someone sent the wrong paperwork to us, so I have to fill it out again; the insurance company makes a mistake on the claim and I have to file an appeal and follow up on it; contractor says they’re going to do something, doesn’t do it completely, and I have to fight to get them to come finish the job they agreed to. I get that we are all stretched so thin & distracted, but I am exhausted by trying to keep up with the apparently “essential” stuff of modern American adulthood

When you’re enmeshed with someone, both their flaws and their positive qualities become your whole life. This is, I guess you could say, the downside of intimacy. Seen from afar, someone might look like a house you’d like to promptly move into—pretty, spacious, great wood floors. But when you’re actually living inside them the sound of construction coming from the upstairs window and the leaky ceiling make you crazy.

some people prefer to be bored in intimate relationships, and others prefer to be annoyed. I was noodling on it this morning, wondering why I'd always rather prefer to be annoyed.

would you rather be far enough away from someone to feel peace, or would you like to have your psyche entwined with theirs, with the downside of constantly being exposed to all their flaws?

In relationships, there’s some kind of balance you have to strike that’s personal to you—you want to be able to tolerate significant annoyance, because every person you can be truly intimate with is going to come with their own particular set of downsides, but you don’t want to end up in a state of permanent exasperation.

But people who are more organized and structured have a far greater number of internal partitions. It can hard for them to be as present, as soft and consuming and close.

Generally, the people who are most capable of expressing love are soupy, gushy, and disorganized. Their structurelessness can be unsettling—when I’m around them, I feel like I’m submerged in a warm and comforting swamp. But nevertheless a swamp!

When I was younger, I thought that love occurred as a result of comprehensible, desirable qualities. Like, I fell in love with him because he’s tall and beautiful and kind. In reality, I find that there’s some of that, but mostly we fall in love for reasons that have little to do with our partner’s virtue. It’s more that something about their way of being hooks onto us—their attachment style is similar to our mother’s, or the way they listen makes us feel deeply understood.

Romance is annoying. It exposes our vulnerabilities, our worst qualities, the patterns we like to pretend we’ve outgrown. Romance teaches you that what you claim to value is not what you actually value.

Their bad habits disturb any semblance of peace you once had. It’s relatively easy to remain calm around a pet or a child, because we don’t expect them to know better. But an adult knows better! How can it be that they are intelligent, capable, fully possessed of free will… and yet they use their free will to be annoying?

We are given aphorisms like “No one is perfect” and “relationships are hard.” We are given diagnoses like codependent and avoidantly attached and “the day-to-day entanglement of marriage is fundamentally opposed to the mystery that sustains sexual attraction.” Well, in trying to come up with my own theory of love, I’d like to submit: closeness is fundamentally annoying.

Closeness is annoying because it’s about the surrender of control.

I believe everyone could benefit from a personal website. Its form encourages you to look inward, whereas every social platform on the internet encourages you to look outward. A personal website has affordances which encourage you to create something that you couldn’t otherwise create anywhere else, like YouTube or Reddit or Facebook or Twitter or even Mastodon. Why? Because the context of those environments is outward looking. It’s not personal, but social. The medium shapes the message.

Additionally, a personal website and a social platform are two different environments: one I’ve cultivated, the other I’ve been granted.

Like dancing or singing, you don’t have to be skilled to do them. Personal websites should be the same. They’re for everyone. Like dancing and singing, their expression can be as varied as every individual human.

My problems were too complex and modern to explain. So I skated across parking lots, breezeways, and sidewalks, I listened to the vibration of my wheels on brick, I learned the names of flowers, I put deserted paths to use. I decided for myself each curve I took, and by the time I rolled home, I felt lighter. One Saturday, a friend invited me to roller-skate in the park. I can still picture her in green protective knee pads, flying past. I couldn’t catch up, I had no technique. There existed another scale to evaluate roller skating, beyond joy, and as Rollerbladers and cyclists overtook me, it eclipsed my own. Soon after, I stopped skating.

the end point for the working artist is to create an object for sale. Once the art object enters the market, art’s intrinsic value is emptied out, compacted by the market’s logic of ranking, until there’s only relational worth, no interior worth. Two novelists I know publish essays one week apart; in a grim coincidence, each writer recounts their own version of the same traumatic life event. Which essay is better, a friend asks. I explain they’re different; different life circumstances likely shaped separate approaches. Yes, she says, but which one is better?

we are inundated with cold, beautiful stats, some publicized by trade publications or broadcast by authors themselves on all socials. How many publishers bid? How big is the print run? How many stops on the tour? How many reviews on Goodreads? How many mentions on Bookstagram, BookTok? How many bloggers on the blog tour? How exponential is the growth in follower count? Preorders? How many printings? How many languages in translation? How many views on the unboxing? How many mentions on most-anticipated lists?

A starred review from Publisher’s Weekly, but I wasn’t in “Picks of the Week.” A mention from Entertainment Weekly, but last on a click-through list.

There must exist professions that are free from capture, but I’m hard pressed to find them. Even non-remote jobs, where work cannot pursue the worker home, are dogged by digital tracking: a farmer says Instagram Story views directly correlate to farm subscriptions, a server tells me her manager won’t give her the Saturday-night money shift until she has more followers.

What we hardly talk about is how we’ve reorganized not just industrial activity but any activity to be capturable by computer, a radical expansion of what can be mined. Friendship is ground zero for the metrics of the inner world, the first unquantifiable shorn into data points: Friendster testimonials, the MySpace Top 8, friending. Likewise, the search for romance has been refigured by dating apps that sell paid-for rankings and paid access to “quality” matches. Or, if there’s an off-duty pursuit you love—giving tarot readings, polishing beach rocks—it’s a great compliment to say: “You should do that for money.” Join the passion economy, give the market final say on the value of your delights. Even engaging with art—say, encountering some uncanny reflection of yourself in a novel, or having a transformative epiphany from listening, on repeat, to the way that singer’s voice breaks over the bridge—can be spat out as a figure, on Goodreads or your Spotify year in review.

And those ascetics who disavow all socials? They are still caught in the network. Acts of pure leisure—photographing a sidewalk cat with a camera app or watching a video on how to make a curry—are transmuted into data to grade how well the app or the creators’ deliverables are delivering. If we’re not being tallied, we affect the tally of others. We are all data workers.

In a nightmarish dispatch in Esquire on how hard it is for authors to find readers, Kate Dwyer argues that all authors must function like influencers now, which means a fire sale on your “private” life. As internet theorist Kyle Chayka puts it to Dwyer: “Influencers get attention by exposing parts of their life that have nothing to do with the production of culture.”

what happens to artists is happening to all of us. As data collection technology hollows out our inner worlds, all of us experience the working artist’s plight: our lot is to numericize and monetize the most private and personal parts of our experience.

We are not giving away our value, as a puritanical grandparent might scold; we are giving away our facility to value. We’ve been cored like apples, a dependency created, hooked on the public internet to tell us the worth.

When we scroll, what are we looking for?

While other fast fashion brands wait for high-end houses to produce designs they can replicate cheaply, Shein has completely eclipsed the runway, using AI to trawl social media for cues on what to produce next. Shein’s site operates like a casino game, using “dark patterns”—a countdown clock puts a timer on an offer, pop-ups say there’s only one item left in stock, and the scroll of outfits never ends—so you buy now, ask if you want it later. Shein’s model is dystopic: countless reports detail how it puts its workers in obscene poverty in order to sell a reprieve to consumers who are also moneyless—a saturated plush world lasting as long as the seams in one of their dresses. Yet the day to day of Shein’s target shopper is so bleak, we strain our moral character to cosplay a life of plenty.

(Unsplash) Technology The Collapse of Self-Worth in the Digital Age Why are we letting algorithms rewrite the rules of art, work, and life? BY THEA LIM Updated 17:52, Sep. 20, 2024 | Published 6:30, Sep. 17, 2024 W HEN I WAS TWELVE, I used to roller-skate in circles for hours. I was at another new school, the odd man out, bullied by my desk mate. My problems were too complex and modern to explain. So I skated across parking lots, breezeways, and sidewalks, I listened to the vibration of my wheels on brick, I learned the names of flowers, I put deserted paths to use. I decided for myself each curve I took, and by the time I rolled home, I felt lighter. One Saturday, a friend invited me to roller-skate in the park. I can still picture her in green protective knee pads, flying past. I couldn’t catch up, I had no technique. There existed another scale to evaluate roller skating, beyond joy, and as Rollerbladers and cyclists overtook me, it eclipsed my own. Soon after, I stopped skating. Y EARS AGO, I worked in the backroom of a Tower Records. Every few hours, my face-pierced, gunk-haired co-workers would line up by my workstation, waiting to clock in or out. When we typed in our staff number at 8:59 p.m., we were off time, returned to ourselves, free like smoke. There are no words to describe the opposite sensations of being at-our-job and being not-at-our-job even if we know the feeling of crossing that threshold by heart. But the most essential quality that makes a job a job is that when we are at work, we surrender the power to decide the worth of what we do. At-job is where our labour is appraised by an external meter: the market. At-job, our labour is never a means to itself but a means to money; its value can be expressed only as a number—relative, fluctuating, out of our control. At-job, because an outside eye measures us, the workplace is a place of surveillance. It’s painful to have your sense of worth extracted. For Marx, the poet of economics, when a person’s innate value is replaced with exchange value, it is as if we’ve been reduced to “a mere jelly.” Wait—Is ChatGPT Even Legal? AI Is a False God How Israel Is Using AI as a Weapon of War Not-job, or whatever name you prefer—“quitting time,” “off duty,” “downtime”—is where we restore ourselves from a mere jelly, precisely by using our internal meter to determine the criteria for success or failure. Find the best route home—not the one that optimizes cost per minute but the one that offers time enough to hear an album from start to finish. Plant a window garden, and if the plants are half dead, try again. My brother-in-law found a toy loom in his neighbour’s garbage, and nightly he weaves tiny technicolour rugs. We do these activities for the sake of doing them, and their value can’t be arrived at through an outside, top-down measure. It would be nonsensical to treat them as comparable and rank them from one to five. We can assess them only by privately and carefully attending to what they contain and, on our own, concluding their merit. And so artmaking—the cultural industries—occupies the middle of an uneasy Venn diagram. First, the value of an artwork is internal—how well does it fulfill the vision that inspired it? Second, a piece of art is its own end. Third, a piece of art is, by definition, rare, one of a kind, nonfungible. Yet the end point for the working artist is to create an object for sale. Once the art object enters the market, art’s intrinsic value is emptied out, compacted by the market’s logic of ranking, until there’s only relational worth, no interior worth. Two novelists I know publish essays one week apart; in a grim coincidence, each writer recounts their own version of the same traumatic life event. Which essay is better, a friend asks. I explain they’re different; different life circumstances likely shaped separate approaches. Yes, she says, but which one is better? I GREW UP a Catholic, a faithful, an anachronism to my friends. I carried my faith until my twenties, when it finally broke. Once I couldn’t gain comfort from religion anymore, I got it from writing. Sitting and building stories, side by side with millions of other storytellers who have endeavoured since the dawn of existence to forge meaning even as reality proves endlessly senseless, is the nearest thing to what it felt like back when I was a believer. I spent my thirties writing a novel and paying the bills as low-paid part-time faculty at three different colleges. I could’ve studied law or learned to code. Instead, I manufactured sentences. Looking back, it baffles me that I had the wherewithal to commit to a project with no guaranteed financial value, as if I was under an enchantment. Working on that novel was like visiting a little town every day for four years, a place so dear and sweet. Then I sold it. As the publication date advanced, I was awash with extrinsic measures. Only twenty years ago, there was no public, complete data on book sales. U