You see a lot of discussion about how AI replaces people at work, but not as much discussion about how the same thing happens outside the office.

Have you noticed it, too? It seems to happen when we feel the pangs of loneliness, confusion, or, especially, insecurity. It's tempting to reach for the machine—ever patient and pliant—instead of peers and loved ones. The models offer what they can, but it mostly amounts to distraction. Echoes and shadows. It's hard to be vulnerable in front of other people because their judgement matters, but that difficulty is what tells us there's something worthy and real to be had.

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You grow tomatoes for the process, not just the product, to garden as well as to eat. To do as well as to have.

Silicon Valley is full of tyrants of the quantifiable. For decades, its oligarchs have preached that our criteria for what we do and how we do it should be convenience, efficiency, productivity, profitability. They have told us that to go out into the world, to interact with others, is perilous, unpleasant, inefficient, a waste of time, and that time is something we should hoard rather than spend.

The price of giving up many activities is the atrophy of the ability to do them.

Love is too often discussed as a sort of good you want to stockpile, harvest, collect, even extract, but to be loved without loving is a sad accomplishment, a miser's hoarding of someone else's wealth. The work of loving is also the work of forging a self and a life.

I want to praise difficulty, not for its own sake, but because so much of what we want, we get through endeavours that are difficult. The difficulty is why doing something is rewarding; you have accomplished something, exerted effort and skill, stayed with the trouble, tested your limits, realised your intentions – or sometimes failed at all these things, and that too can be important, as can learning to survive failure.

Among the things real friends can do and AI cannot: bake you a cake or drive you home, hold your hand or live through a crisis or a celebration with you. And because of that difference people need to have real friends. More than that, people need real communities and social support systems.

The solution to technology is not more technology. The solution to loneliness is each other, a wealth that should be available to most of us most of the time. We need to rebuild or reinvent the ways and places in which we meet; we need to recognise them as the space of democracy, of joy, of connection, of love, of trust. Technology has stolen us from each other and in many ways from ourselves, and then tried to sell us substitutes. Stealing ourselves back, alas, is not as easy as walking out the door. We need somewhere to go and, more importantly, someone to go to who likewise desires to connect.

The connections that matter to our humanity are not only to each other. They're with the whole natural and social world. Animals, wild and domestic, should be counted as part of the irreplaceable companionship that makes our lives meaningful and sometimes joyful. They remind us that there are many kinds of consciousness and that our species is itself not alone.

Keyana Sapp is the writer behind a publication/public accountability ledger called Worse on Purpose. I'm a fan of this kind of reviewing. It's the product of investigative journalism, not affiliate relationships. It's motivated by the most honest force we know of: care. Someone gives a shit about the topic and wants to understand what's going on. Not for riches, recognition, or attention, but for interest's sake. Because it mattered to them.

The topic at hand is quality, and because it's a bit of a slippery concept I appreciated that Keyana took the time to write out the site's definition of the term in this fantastic blog post. It manages to do two things: it translates our shared intuition about quality into something tangible, and it also explains how an incomplete definition leads to decline, particularly when companies try to industrialize quality in a superficial way.

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That is what every craft tradition is: a transmission system for the unnameable, carried in people rather than paper. It is why apprenticeship survives every technology invented to replace it: the judgment that produces quality transfers only by demonstration and correction, through thousands of supervised repetitions across years, from a person who has it to a person who does not yet.

Whatever resists definition resists measurement. Whatever resists measurement vanishes from the dashboard. And in a company run from dashboards, what vanishes from the dashboard vanishes altogether.

Each change is approved in isolation, and each is too small for any buyer to notice on its own. That is the trick. No test compares the product to what it was ten years ago. Each product version is measured against last quarter's, comes back as "no detectable difference," and ships. So the degradation compounds beneath the threshold of every individual measurement, invisible at each step and enormous in total.

It is by this mechanism that quality, the unmeasurable property, erodes as a company places a greater insistence on measurement.

Every measurement a company takes lands on one side of the objective/subjective divide or the other. Spec sheets, tolerances, and materials testing measure the object alone. Surveys, star ratings, and focus groups measure opinions alone. And they sample the opinion at the wrong moment. A star rating gets filed in the first week of ownership, while the surface still shines, and the failures arrive in year three, when almost nobody returns to amend it.

Nothing measures the relationship, because the relationship only exists in use, in the hand, on the road and across years. So when quality drains out of a product, it drains from the one place no instrument points at. Both sets of numbers can hold perfectly steady while the thing between them disappears. That is how a product gets worse without a single metric moving. That is also how the people doing it stay convinced that nothing was lost.

A good object is a fossil record of care. Thousands of small selections made by people who could tell the good facts from the bad ones and picked the good, even when not doing so was cheaper or easier.

When outside capital buys a great brand, nobody issues a decree that the product shall now be garbage. Instead, the people who previously made those thousands of selections either get laid off, retired out, or reorged into irrelevance, and the decisions migrate to a floor in an office building where nobody has ever actually used the product. Care cannot be exercised at that distance. Quality follows care out of the building, and the whole thing happens without any individual ever choosing badness directly.

That was 1968's confusion: good things that looked cheap. We industrialized the reverse. The heritage fonts, the small-batch copy and the unboxing moment engineered to simulate the exact feeling my Les Paul earned honestly. The surface has never been more perfected, wrapped around the glued joints and the plastic gears.

There are two ways to make money on quality. You can make a thing so good that people pay for it, keep it, and hand your name to their kids. That is the Miles road: quality found cheaper, profit as the receipt for care. Or you can buy the name after the caring is done, spend down four generations of accumulated trust, and be gone before anyone's memory catches up.

He calls it a return to the original promise of technology, which I grew up seeing as a force for widespread good. Something we can use to become more expansive and interconnected, not more paranoid and withdrawn.

What can I say? It's a great read. Co-signed.

Here's what I highlighted:

Over the past few years, I have found myself paying closer attention to my own instincts while working in technology, especially inside large organizations. Nothing dramatic happened. The work was solid. The people were smart and well intentioned. But something felt increasingly misaligned. The direction of the work, the incentives behind it, and the outcomes it optimized for no longer matched my own principles.

Small Tech is not anti-technology. It is not anti-progress. If anything, it is about taking technology seriously enough to ask who it serves, who controls it, and who benefits when it succeeds.

For me, Small Tech means principle-driven software. Software where the values come first, and everything else follows from that. Community ownership. Clear data control. Accountability. Limits. Not as marketing copy, but as design constraints. In Small Tech, principles are not aspirational. They are non-negotiable.

Technology itself is not the problem. Tools are neutral. Incentives are not. When powerful tools are applied with care, humility, and respect for context, they can genuinely help people who are often overlooked by mainstream platforms.

Small Tech is not about staying small for the sake of it. It is about staying accountable.

The goal is not to teach people technology, but to make technology quietly useful in the context of daily work.

This is why conversations about AI so often miss the point. They swing between hype and fear. Either AI is the future of everything, or it is an existential threat. The reality, for me, is more grounded. AI lowers the barrier to building software. That leverage can be used to build bigger platforms, or it can be used to build smaller, more focused tools for real communities.

We will never sell your data. You control your data. You can leave. These are not features. They are constraints. They shape what the product can become, and just as importantly, what it will never become.

When we always default to the biggest platforms and the most popular frameworks, we concentrate power whether we mean to or not. Choosing smaller tools is one way to keep that ecosystem diverse and resilient.

None of this is free. There are trade offs. Things can be slower. Some services cost more. You do not get infinite scale handed to you. But those trade offs are the point. They force you to be intentional.

Shall we?

**Walk off the Earth**
I'd like to introduce you to one of my favourite bands. They're Canadian, formed not far from where I grew up, and there's a decent chance you've heard their breakout hit: this cover of Somebody That I Used to Know. It's great, but let me show you the songs that built my appreciation for their range and spirit.

Stick Season was what caught my attention. It cemented my impression of the band as a source of witty lyrics, infectious energy, and a distinctive musical voice. The vibes are impeccable from the start, with uncomfortably self-aware lyrics steeped in a particular flavour of the suburban millennial experience that I suppose I'm primed to respond to.

But the way they play with rhythm and lyrics is more universally entertaining. Like how the end of "she forgot that I exist-ed" lingers like teenage hope, or how they paint a picture just specific enough—"Now you're just tire tracks and one pair of shoes" —to make you wonder.

When Sarah Blackwood takes over at 1:11, the darkness in the lyrics is offset by the bouncy-ball bassline underneath it, keeping things light and easy. The bass is doing a lot of work in general in this mix, with some unexpectedly prominent synth stabs and rhythmic handoffs that toe the line between aggression and levity in an interesting way.

It's the same punk/folk intersection that other bands inhabit, but the musical and lyrical wit sets them apart for me. It's evident in other songs like Catching Feelings, or Mom's Old Car, both of which paint a vivid picture with the same electronic-infused instrumentation and production polish that keeps things feeling modern.

Other times, they're just having fun. Social commentary with a wink, as in Bless the Telephone. And just to bring things back to where we started, they're still fucking amazing at doing covers. Take a listen to Take On Me, or my latest obsession, Enter the Sandman, each of which further showcases this band's talents.

**Soleil Bleu**, Bleu Solei & Luiza
Shannon's been learning French, and one of my favourite things about it is that it means we've suddenly got French radio, French books, and—you guessed it—French music in the house. She discovered this song a few weeks back and we've both been listening to it a bunch ever since.

Besides its poetic, dreamy lyrics, this song is just so damn groovy. Reggae-leaning rhythms bop along with an unreasonable amount of swagger. Wispy ping-pong delays toss percussion around your head, echoing like fun memories when you've had one too many.

This is carefree summer in a song.

**Recuerdo de Ti**, Geoffroy
Speaking of unreasonable swagger, this song is something else.

Geoffroy Sauvé, who I'd never heard of before, unleashes devastation with this one. And it's done without relying on flashy production tricks or tons of layers. Simple ingredients, expertly combined. Laidback singing comes in over the plucked arpeggio. Suddenly we get bucket percussion, and then the bassline. That bassline! Punctuated by a perfectly dry and beefy kick and a mix drowning in lush delays.

Makes for a heady sonic cocktail.

**ARC Raiders**, Patrik Andrén & Johan Söderqvist

If you're aware of videogames at all, you've likely heard of ARC Raiders. I haven't been able to try the game yet, but when I saw who was on composing duty I knew I had to take a listen.

These two talented gents are known for their superb work on a number of the recent Battlefield games, which themselves boast enjoyable scores. Actually, you know what—

**Battlefield V (Original Soundtrack)**, Patrik Andrén & Johan Söderqvist
Before we even get to ARC Raiders, I'm going to linger on Battlefield for a moment. You might hear that name and think "ok, mindless shooter franchise, probably not fertile ground for musical expression".

Allow me to change your mind.

You know how every good war movie has That Theme™? The rousing, soaring, spirited melody that sends goosebumps dancing over your arms when you hear it over the end credits? Here's *Under No Flag*. Like many of its kind, this theme introduces itself with quiet, aching strings, but the woodwinds give it wings, and by the time you reach the final statement it feels noble and inspiring.

Fans of the series will immediately jump a few tracks down to see what these two did with the iconic Battlefield theme, a 12-note motif that's showed up in every game in the series. What can I say? They do it justice. But in fact it's *Spitfires*, a few more tracks down the list, that's my favourite rendition of the Battlefield theme on this album. It spins the familiar melody into the slightly off-kilter 5/4 time signature, which gives it a fleet-footed, propulsive feel that almost makes the original march feel ponderous.

Just goes to show how flexible a good melody can be in the hands of a good composer. It's always a treat when you get both.

**ARC Raiders**, Patrik Andrén & Johan Söderqvist
Okay, back to ARC Raiders.

Now that you've heard what they can do, you have a richer perspective coming into this most recent major work of theirs. ARC Raiders is a bigger album all around. This game has a different voice, it feels more grand, more otherworldly (as it should).

*Speranza* is one of my favourite cues on the album. I'm always a fan of a satisfying build, and boy do we ever get one here. And then—wait for it—just as things seem to be reaching a climax, we get a synth handoff that takes your breath away. It's unexpected but satisfying gestures like that one that set this soundtrack apart for me.

Speaking of rousing themes, we have *City of Toledo*. It's not easy to find fresh ways to revisit familiar territory. This isn't the first sci-fi shooter game, after all. But they manage it, and they weave together some very interesting instrument combinations to do it, including delicate bells, a large hybrid orchestra, a Bulgarian choir, and some masterfully-programmed and performed synth lines. What a feast for the senses, this album is.

Alright, enough about these two. You'd be forgiven for thinking I'm sponsored by them or that I even know them, but no, I just like their work. And now maybe you do, too!

**Edge of the Earth**, Skott
I guess I'm drawn to unusual origin stories because Pauline Skött's certainly counts. She was born in a remote village in the Swedish forest, surrounded by her community's musical traditions but entirely cut off from the rest of the world's.

Those woods cultivated a hell of a talent, with a voice that mixes breathy intimacy with a purity and control that stops me in my tracks. She harnesses that voice to great effect to create vivid harmonic layers.

The first song of hers that I heard is called *Overcome*, which also describes my reaction to hearing it for the first time. When all the layers of her voice come in for the first time around the 0:48 mark, and especially when we slide down to that warm hug of a sub-bass note at 0:54, it felt as if I'd just been planted into the ground like a tree.

Whatever she's yearning for, I feel it too.

OK that's plenty for this batch. I hope you found something you enjoyed in there! And if you've had a song stuck in your head lately, share it with me. I'm always happy to get new music recommendations. 😊

An important read, especially for those of us working in tech.

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If you want to meaningfully oppose AI in a way that lasts, you should speak loudly with your dollars in the market and your attention online, and you should speak loudly with your votes. You should participate in a democratic regulatory and political process. Anything else will get dismissed and perpetuate the cycle.

I also think it's incredibly important for our politicians and tech executives to make sure our political process makes people feel empowered, not helpless, which is a specific kind of nihilism they have all greatly contributed to. The violence is a result of that helplessness and nihilism. And the most powerful people in our society ought to reckon with that, especially as they run around saying AI will wipe out all the jobs.

It feels like someone just needs to say this clearly, so I'm just going to do it. AI doesn't have a marketing problem. People experience these tools every single day. ChatGPT has 900 million weekly users, trending to a billion, and everyone has seen AI Overviews in Google Search and massive amounts of slop on their feeds. You can't advertise people out of reacting to their own experiences. This is a fundamental disconnect between how tech people with software brains see the world and how regular people are living their lives.

People are constantly trying to issue commands to society at large like it's a computer that will obey instructions.

But law isn't actually code, and society and courts aren't computers. I have to remind our fairly technical audience on Decoder and at The Verge all the time that the law is not deterministic. You simply cannot take the facts of a case, the law as written, and predict the outcome of that case with any real certainty, even though the formality of the legal system makes people think it works like a computer, that it's predictable.

But not everything is a business, not everything is a loop, and the entire human experience cannot be captured in a database. That's the limit of software brain. That's why people hate AI. It flattens them. Regular people don't see the opportunity to write code as an opportunity at all. The people do not yearn for automation. I'm a full-on smart home sicko; the lights and shades and climate controls of this house are automated in dozens of ways. But huge companies like Apple, Google and Amazon have struggled for over a decade now to make regular people care about smart home automation at all. And they just don't.

AI isn't going to fix that. Most people are not collecting data about every single thing that they do. And if they're collecting any at all, it's stored across lots of different systems — your email in Gmail, your messages in iMessage, your work schedule in Outlook, your workouts in Peloton. Those systems don't talk to each other and maybe they never will, because there's no reason for them to. And asking people to connect them all freaks them out.

Even taking the time to consider how much of your life is captured in databases makes people unhappy. No one wants to be surveilled constantly, and especially not in a way that makes tech companies even more powerful.

I've reviewed a lot of tech products over the past decade and a half, and all I can tell you is that it is a failure when you ask people to adapt to computers. Computers should adapt to people. And asking people to make themselves more legible to software, to turn themselves into a database, is a doomed idea. It's an ask so big, I can't imagine a reward that would make it worth it for anyone, even if the tech industry wasn't constantly talking about how AI will eliminate all the jobs, require a wholesale rethinking of the social contract and — oops — also the latest models might cause catastrophic cybersecurity problems that might lead to the end of the world.

Does this sound like a good deal to you? Can you market your way out of this?

And so the tech industry is rushing forward to put AI everywhere at enormous cost — energy, emissions, manufacturing capacity, the ability to buy RAM — and locked into the narrow framework of software brain without realizing they are also asking people to be fundamentally less human. They then sit around wondering why everyone hates them.

This post covers a lot of ground, but it does a great job of highlighting that while AI has been developing intelligence quickly along one axis, there's another branch of intelligence that current methods still haven't conjured in these models.

This is one reason skeptics think the approach the frontier labs are pursuing is unlikely to lead to Artificial General Intelligence (or the Singularity, or Superintelligence, or whichever label and loose definition you prefer).

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Some problems have clear boundaries and verifiable solutions, like "What's the cube root of 38,126?". These problems require objective intelligence. Other problems are vague and squishy and it's not clear whether you've solved them, or whether they exist at all, like "How do I live a good life?". These problems require subjective intelligence. Objective intelligence can be trained, reinforced, and validated. Subjective intelligence cannot.

It's unfortunate that people use one word to refer to both of these capabilities, when in fact they have nothing to do with each other. It is also, ironically, a case of objective intelligence overshadowing subjective intelligence: these skills are obviously and intuitively different, but a century of psychological research has "proven" that only one of them exists.

The problem is that any test of intelligence is only ever a test of objective intelligence. "How do I live a good life?" is not a multiple-choice question. "Discovering" the g-factor again and again is like being surprised that you find the same patch of sidewalk every time you look under the same streetlight.

AI is pure objective intelligence. That's why each new model comes with a report card instead of a birth certificate

The promise of artificial superintelligence is based on the idea that objective intelligence is the only intelligence. Or, even if there are multiple forms of intelligence out there, that they are fungible. To be an AI maximalist is to believe we are playing under Settlers of Catan rules, where if you have enough of any one resource, you can trade it for any other resource. If you have infinite objective intelligence, then you have infinite everything.

It's hard to describe exactly what the machines are missing. Have you ever loved someone who once loved you back, then didn't anymore? Did you notice how their eyes dimmed? Did you note the disappearance of that subtle wrinkle in the temples that distinguishes a real smile from a fake one? Did you catch it when you stopped being cared for and started being humored? The moment you realize what's happening, you age out of your enchantment—one day you're crawling through a wardrobe to Narnia, and next day you open up the wardrobe and there's nothing but hangers. Talking to an AI feels a bit like that, except without the nice part at the beginning.

The words themselves don't contain that feeling—they are a recipe for creating that feeling inside your own head, to assemble the right set of emotions out of the experiences you have at hand. If I do a good job, the subjective experience that results inside you might resemble the one that originated inside me, but it will never be identical, because we're working with different ingredients.

The computer doesn't know any of this. It can't know any of this. It can only read the cookbook; it can't taste the meal. Objective knowledge can make your sentences true, but it can't make them alive. Without access to subjective knowledge, you quickly hit a wall. And unlike all previous walls that AI has surmounted, you can't overcome this one by scaling—either in the literal or metaphorical sense—because it's a wall with a width you cannot describe and a height you cannot see.

The fact that it's hard to describe how to improve AI writing is, of course, the exact problem. You can't put a number on the things it does wrong, and you can't minimize what you can't measure. That's the wall.

I find this very fortuitous, of course, but I also find it pretty funny, because me vs. the machines should be no contest at all. I have not read the entire internet or even that many books. I do not have a team of Stanford PhDs working round the clock to make me better at my job. Nobody has invested $2.5 trillion in me. I should be lying dead somewhere in West Virginia, my heart burst open after losing to Claude Opus 4.6 in a John Henry-style showdown. Instead, I get to write my little posts because nowhere, in all those data centers, are the specific thoughts that happen to occur in the dumb hunk of meat ensconced in my skull.

I think all of us suffer from this bottleneck blindness : we assume our current bottleneck is our only bottleneck. When you're strapped for cash, you think all of your problems are cash problems. But once you've got some money in you pocket, you realize that what you really need is time. Free up some time, and you discover that you're actually lacking motivation . Acquire some motivation, and you realize what you're missing is ideas . Then you need direction , then you need discipline , then you need buy-in, and so on, forever.

Well, once you get access to an infinite Madame Stats and Mr. Encyclopedia, you realize they can't get you very far. For one thing, you can't rely on Madame Stats and Mr. Encyclopedia entirely, because if you can't do any stats and you never read any papers, you're probably not going to have many interesting ideas yourself.⁵ Plus, while the Stats/Encyclopedia duo can tell you whether your experiment has been done before and whether you've run the numbers correctly, they can't give you the single most important piece of feedback: they can't tell you whether your idea is boring.

The most important thing I learned during my PhD was how to be bored correctly. Novices think everything is exciting, or they think everything is boring. Only masters are bored by the right things.

I don't say this as someone who is allergic to the idea of AI, or who has only spent 15 minutes screwing around with a single model, hoping it will do something stupid so I can go tattle on it. If the talking computers said lots of fascinating things, I don't see any point in trying to tell a noble lie about it. And if AI can cure cancer and end all wars, I'm all for it, even if it means I'm personally out of a job.

I have several family members in academia, so the phenomenon being discussed in this piece was already familiar to me, but Dr. Karamanis paints an evocative picture of the underlying structural problem.

I see a lot of parallels in the tech industry, and I'm trying to quash any nascent tendencies toward this in my own life.

Well-meaning workers are trying their best to be useful as they watch their colleagues fall away around them. They're inheriting roles and responsibilities they may not be qualified for or equipped to do justice to. Thanks to the same AI that's bedazzled their leaders, these folks can produce the work...but not substantiate it. Unable to understand the model's output enough to polish it into worthiness, they lean too much on the model's expertise.

Except models don't have expertise, they have statistics. Statistics are valuable, but on their own they can only mimic expertise. The missing ingredient is instinct, which is honed through experience. For now, those qualia are beyond the reach of LLMs.

And so those workers find themselves handing in artifacts they're unable to fully explain, maintain, or improve upon. When corporate culture confuses volume with impact to justify their AI investments, it creates a hidden liability. That knowledge gap remains buried right up until a crisis makes it suddenly and painfully obvious.

On the other hand, there's a parallel phenomenon. One I also see plenty of, thankfully.

You know how some videogames make a big deal out of you dying, while others do their best to get you back in the game as quickly as possible? Which one are you more motivated to keep playing? In this way, AI can make learning faster, and therefore more fun. Nothing teaches faster than fun.

It's a way of using these tools to accelerate the building of expertise. Not by skipping the drudgery, but by shortening the time between tries. Lowering the cost of experimentation. And, I suppose, by providing an infinitely patient professor (who's only sometimes high on mushrooms). One who you can appeal to for answers, without fear of meaningful judgement or being made to feel stupid.

While I'm fairly sure this process doesn't produce equivalent expertise to previous methods of learning, I do think it's a valuable improvement on not caring enough to learn at all.

By the way, this seems to be Minas' blogging debut! Great new blogs are always an exciting find. Go read **The machines are fine. I'm worried about us.** and then add the website to your feed reader.

Here's what I highlighted:

The majority of PhD students will leave academia within a few years of finishing. Everyone knows this. The department knows it, the funding body knows it, the supervisor probably knows it too even if nobody says it out loud. Which means that, from the institution's perspective, the question of whether Alice or Bob becomes a better scientist is largely someone else's problem. The department needs papers, because papers justify funding, and funding justifies the department. The student is the means of production. Whether that student walks out the door five years later as an independent thinker or a competent prompt engineer is, institutionally speaking, irrelevant. The incentive structure doesn't just fail to distinguish between Alice and Bob. It has no reason to try.

The models are already powerful enough to produce publishable results under competent supervision. That's not the bottleneck. The bottleneck is the supervision. Stronger models won't eliminate the need for a human who understands the physics; they'll just broaden the range of problems that a supervised agent can tackle. The supervisor still needs to know what the answer should look like, still needs to know which checks to demand, still needs to have the instinct that something is off before they can articulate why. That instinct doesn't come from a subscription. It comes from years of failing at exactly the kind of work that people keep calling grunt work. Making the models smarter doesn't solve the problem. It makes the problem harder to see.

The real threat is a slow, comfortable drift toward not understanding what you're doing. Not a dramatic collapse. Not Skynet. Just a generation of researchers who can produce results but can't produce understanding. Who know what buttons to press but not why those buttons exist. Who can get a paper through peer review but can't sit in a room with a colleague and explain, from the ground up, why the third term in their expansion has the sign that it does.

The failures are the curriculum. The error messages are the syllabus. Every hour you spend confused is an hour you spend building the infrastructure inside your own head that will eventually let you do original work. There is no shortcut through that process that doesn't leave you diminished on the other side.

Schwartz can use Claude to write a paper because Schwartz already knows the physics. His decades of experience are the immune system that catches Claude's hallucinations. A first-year student using the same tool, on the same problem, with the same supervisor giving the same feedback, produces the same output with none of the understanding. The paper looks identical. The scientist doesn't.

The crisis of meaning he talks about is something that worries me, especially at global scale. Then again, the tendency to associate identity with work is a 20th-century, North American thing. It's a bubble I'm immersed in, and my creative background doesn't help. Still, we're going to see a lot of people with a lot of extra time on their hands. And chances are, I'll end up among them.

What I do definitely falls into the broad category of "cognitive labour", so I've been thinking: what part of that would AI replace? Cognitive labour can be measured in terms of volume (how many projects), or impact (how successful the projects are). Garg's vision seems rooted in the idea that AI can help a company making 1,000 widgets per month do so with 10 people instead of 50. That's likely true, but why would the company do that when it could use those 50 people to make 5,000 widgets instead? This is Jevon's Paradox, and we don't yet know how it will play out for cognitive labour.

That's one of a few additional factors Garg didn't get into that would influence the outcomes he's considering. Here are three more:

• The last mile is the hardest. For as long as AI agents remain terrific at the first 90% of a task but require human interaction, ingenuity, or intuition to cross the finish line...the difficulty and importance of that final 10% will be underestimated and understaffed.
• Resource constraints are real. Some of these timelines are incompatible with the geopolitical reality of what it takes to establish and sustain the necessary infrastructure for this imagined future.
• Regulation moves slowly, but it does move. For the transitions in this piece to play out as quickly as Garg proposes, there would have to be no pesky interference from the likes of professional guilds, labour unions, and governments.

I don't know how this will impact my career, but I do know that I'm not interested in optimizing for volume of output. Employers typically don't care how many plates you're spinning, they care how many of those initiatives deliver what I like to call "happy graphs"—up and to the right. They also care how much your efforts cost them, because only the difference matters. How efficient are you at translating company resources into company profits?

Here's what I highlighted:

This is a remarkable change. I now view my intelligence as a commodity on tap. The primary skills I have left are my ability to synthesize different AI-generated perspectives into a combined whole that's better than what the AI produces on its own, my ability to judge what I like and don't like, and my ability to identify what I care about. Taste, direction, synthesis. Not raw cognitive horsepower. For someone whose whole identity was predicated on that horsepower, this is a significant transformation, and it's one that millions of knowledge workers will go through in the next few years whether they're ready for it or not.

It helps to think about human labor as falling into two broad categories. The first is cognitive labor: knowledge work and emotional work. Analysis, writing, coding, design, legal reasoning, financial modeling, medical diagnosis, therapy, coaching, project management. This is the category being automated right now. The second is physical labor: construction, manufacturing, agriculture, logistics, plumbing, electrical work, maintenance. This requires robotics and physical automation, which follows a different timeline.

If physical labor automation arrives on a ten-year timeline, it means we cannot treat physical labor as a permanent refuge for displaced knowledge workers. Unlike the Industrial Revolution, where one type of human labor (manual agricultural work) was replaced but another type (factory and later knowledge work) grew to absorb the displaced population, this transition has no obvious next category of labor for humans to move into. All three categories (knowledge work, emotional work, physical work) are converging toward automation within a single generation.

Economics doesn't break down. But a good chunk of capitalism might. Capitalism operates on the basis of prices aggregating information to coordinate production and consumption. When the cost of producing many goods and services approaches zero, that price mechanism stops functioning for those goods. There's no price signal to send when the marginal cost of one more unit of legal advice, or software, or medical diagnosis is effectively nothing. It's an open question which parts of capitalism break down and which adapt.

Within three to five years, the majority of cognitive jobs will be substantially automated. This doesn't mean every knowledge worker loses their job overnight. It means the number of humans needed to produce a given unit of cognitive output drops by an order of magnitude. One person with AI does what twenty did before. The math is simple: most knowledge workers become redundant.

This hits the upper-middle class hardest, which is counterintuitive. The truly wealthy have diversified assets and capital reserves. Working-class people doing physical labor still have scarce skills. It's the $80,000-to-$400,000 household (the lawyer, the software engineer, the financial analyst, the radiologist) that gets caught. Their skills are the most directly substitutable by AI, and their lifestyle is built on continuous high income rather than accumulated capital. They lose their income, and the value of their primary asset (typically a home in an expensive knowledge-work city) declines as demand in those cities contracts.

A software engineer's identity is as tied to their cognitive ability as a steelworker's was to their trade. "I'm smart, I solve hard problems, I build things" is not just a job description. It's a self-concept. When AI can solve harder problems and build things faster, that self-concept shatters.

The technology changes. Human nature does not. The drives that define us (status-seeking, hierarchy, competition, the desire to be valued relative to others) are not products of capitalism or knowledge work. They predate both. These dynamics existed before knowledge work was important to society, and they will continue after knowledge work is automated. What changes is the terrain on which these drives play out, and the social contracts that channel them.

What people actually seem to need is not work specifically but four things that work happens to provide: agency (the sense that you're making choices that matter), contribution (the sense that you're valued by others), mastery (the sense that you're getting better at something), and connection (belonging to something larger than yourself). Work can provide all four, but it's not the only thing that can. The challenge is building new structures that provide these when work no longer does.

In a world where AI can produce any material good, conspicuous consumption becomes meaningless as a status signal. So status migrates to whatever remains scarce: physical excellence, social and relational capital, creative originality, governance influence, spiritual attainment.

In this article, Dan Williams frames today's anti-intellectual movements as a matter of social dynamics. We've known for a long time that the simplest story wins. It's as true in politics as it is in marketing. Unfortunately, reality is nuanced and often inconvenient. Being wrong or, even worse, not knowing is experienced as failure, not opportunity. Moreover, it's scary.

Consider this against a backdrop where fewer and fewer people hold more and more power over everyone else, and it's not hard to understand the rise of conspiracy theories, alternative medicine, cults, and similar systems. All these fringe positions offer an escape valve for the pent-up fear, frustration, and exhaustion of living in a complicated world without easy answers. Their simpler, more comforting narratives affirm what we wish was true.

The role of education emerges as an obvious focal point, not only for where the problem starts but for how we can hope to address it.

Here's what I highlighted:

We are social creatures, and almost everything puzzling and paradoxical about our species is downstream of this fact.

For one thing, we rely on complex networks of cooperation to achieve almost all our goals. Given this, much of human behaviour is rooted not in ordinary material self-interest but in the need to gain access to such networks—to win approval, cultivate a good reputation, and attract partners, friends, and allies. Human decision-making occurs within the confines of this social scrutiny. We evaluate almost every action, habit, and preference not just by its immediate effects but by its reputational impact.

In well-functioning human societies, individuals advance their interests not by bullying and dominating others but by impressing them. These high-status individuals are admired, respected, and deferred to. They win esteem and all its benefits. Their lives feel meaningful and purposeful.

Surprisingly, one of the psychological traits that reliably correlates with a conspiratorial mentality is narcissism. It is obvious why paranoia would drive people to posit nefarious hidden plots. Why would tendencies towards grandiosity and entitlement have similar effects?

One reason is that conspiracy theories offer an intoxicating status inversion. By rejecting the "official knowledge" disseminated by society's elites, the conspiracy theorist rejects their claim to intellectual superiority. It is the conspiracy theorist, not the elites, who knows things that others—the gullible sheeple—do not. Through their bravery and insight, they have seen through society's lies and uncovered what is really going on. To someone who craves feelings of status and self-importance, there is something delicious about such a worldview.

When voters are asked to "trust the experts" or "follow the science", these requests have symbolic significance. They ask some humans to grant prestige to other humans—to acknowledge that others know better than they do.

Given this, the populists' rejection of expertise does not liberate them from bias and error. It guarantees bias and error. Gut instincts, intuition, and "common sense" are fundamentally unreliable ways of producing knowledge.

You cannot fact-check your way out of status competition. And as long as the acceptance of expert guidance is experienced as an admission of social inferiority, there will be a lucrative market for demagogues and bullshitters who produce more status-affirming narratives.

Did you know that one Mac can be used to "revive" a second Mac that's had its system firmware damaged? I didn't.

I found out this evening, when Shannon and I discovered first-hand that system firmware can be damaged in "rare circumstances" like...clicking accept on the system prompt asking her to install an update to the operating system. A simple software update completely bricked her work computer.

Luckily, there's a hidden jumpstart utility built into Finder that pops up when you connect your healthy Mac to a struggling one via USB-C cable. Like all things Apple, it just works. And by "just works" I mean works when using a specific port, after performing the needlessly-complex keyboard shortcut incantation required to lull it into DFU mode. The tool then offers to either "revive" or "restore" the connected Mac.

I'll spare you the details: it failed.

Now, Shannon is tech savvy and keeps no files locally that aren't backed up elsewhere. So all she's really losing here is time—which is bad enough. But it should not be possible for a normal user in normal circumstances to cause catastrophic system loss through the installation of a routine system update.

That's what makes this so appalling. This wasn't a big upgrade from Sequoia or a beta or anything like that, we're talking about a simple point to point update of Tahoe. This machine was literally provisioned last week and set up from scratch with no betas or cruft from old backups. You couldn't ask for a cleaner set of circumstances. If Tahoe falters here, what's it doing elsewhere?

As someone who's always struggling to convince friends and family to keep their software up to date so they can benefit from the latest security and usability improvements, all I can do is shrug and laugh at how profoundly Apple's latest software releases undermine my efforts.

I suppose it's our fault for expecting that "software update " implies "software improvement". Good grief.

Change is often good, but not always. Not all advancement is progress. And when it comes to something as important as thinking, it seems like any changes are worth keeping an eye on.

When we look back at AI's impact on our ability to focus, think, and make independent judgements, will we feel good about those changes? If they herald a new dependency, are we prepared to take on that collective responsibility? We've come a long way powered by the steadfast engine of the scientific method. But that engine requires people who think for themselves, take calculated risks, cooperate openly, and engage with problems in good faith. It doesn't run if people stop wanting to verify information, or lose the ability to discern reality from fiction. Where AI worries me is that it seems to be making us less invested in the difference between the two.

Given how important communication is to us, it seems short-sighted to have focused so much of our AI efforts on building tools that undermine the trust we can have in our means of connecting with one another: language, written knowledge, imagery, sounds. None of this was inevitable.

Here's what I highlighted:

When every paragraph has a metaphor, you stop noticing metaphors. When every code block is wrapped in exception handling, none of them feel exceptional. AI deploys communication tools and rhetorical devices not because the content requires them, but because they pattern-match on what "good writing" or "robust code" looked like in the training data.

...if consumers can't comprehend complex ideas or notice errors, they're easier to manipulate. This isn't just about misinformation in the dramatic sense. It's more mundane than that. If I can't tell whether a piece of code is actually robust or just looks robust, I might ship something broken. If I can't tell whether a literature review is accurate or just plausible, I might build on work that doesn't exist. The inability to verify compounds over time. And I think this is an underrated safety issue. There's a lot of discourse about AI safety in terms of catastrophic outlier risk, i.e., dramatic scenarios where someone develops a bioweapon in their garage. But one of the biggest safety problems might be happening right under our noses: en masse, people are losing the ability to comprehend and verify the information they consume.

Taste—in any domain—depends on a feedback loop: you notice when something is good, you notice when something is bad, and over time you develop judgment. But if you stop being able to notice the difference, you stop developing that judgment. This matters even for things that seem low-stakes. Take restaurant recommendations. If the people making recommendations can't tell the difference between a good meal and a mediocre one—or if they're just parroting what an LLM scraped from Yelp—then the recommendations become worthless. I stop trusting them, and I lose access to a source of judgment I used to rely on.

The tools for communication and verification are how we build on each other's work. When they erode, we become a society that can't tell what's true, can't recognize quality, and can't coordinate on hard problems. This is how societies get dumber.

The model's role is to surface what's in the grounding space, not to claim the experience.

I was listening to a podcast recently where the hosts were discussing their favourite technology purchases of the year.

As they listed off computers and smartphones and cameras and the like, I found myself thinking about what I would pick. Despite being someone who loves technology, my answer is something that I bet those hosts would barely even consider "technology".

It's a watch. Not some fancy, expensive one either. It's a humble Casio I picked up earlier in the year, and it represents the kind of technology I'm most drawn to these days.

Casio makes a lot of watches, including the best-selling wristwatch of all time, but this particular Casio is one of several models in their lesser-known "Wave Ceptor" series. These watches typically share a few key attributes:

• They're solar powered, so you never need to wind them, charge them, or change their battery.
• They set themselves automatically each night via a global radio signal so they're always accurate.
• They have analog dials but include a small display that can show you the day of the week and date, a digital time readout, or another timezone.
• They include multiple alarms, world time, stopwatch, and countdown timer functions.
• You can press a button to illuminate the dial for easy visibility in the dark.
• They can withstand immersion in about 50m of water, which is considered mediocre but nevertheless means you don't have to worry about them while showering, swimming, or wandering in the rain.
• They typically cost less than $200, but if you're willing to spend a little more they also have a "Lineage" series that packages the same capabilities in nicer materials for an extra hundred or so.

What more could I ask for in a watch?

The model I bought, the WVA-M630B-1AJF, cost me a little over $100 CAD. It's one of the more affordable models in the range, and the only compromise is that it's primarily made of plastic instead of metals. After replacing the strap it came with, I ended up with a lightweight, comfortable, versatile watch that makes me happy whenever I wear it.

This is one of the few pieces of technology in my life that doesn't demand my attention. I don't have to worry about it for any reason. It's always working, always up to date, always accurate, and never disruptive. If I lose it or break it, I can replace it without hurting my wallet or worrying about what sensitive data on it might fall into the wrong hands.

This kind of thing isn't for everyone, but I'm glad companies like Casio are around to remind us that using technology doesn't have to entail convenience tradeoffs, Faustian privacy bargains, subscription fees, or brain rot. Here's a piece of technology that's in my life without being in my way.

Now that I no longer own an Apple Watch, something about the simplicity of my Casios is profoundly appealing. I still wear a Garmin for tracking health metrics or when I want some of the smarts of a smartwatch, but I'm always looking for excuses to wear my Casio collection.

What sort of music are you into? Me too. One of the side effects of writing music for games and films is that I've ended up learning to appreciate every genre. Occupational hazard. But being up for anything makes music discovery fun!

Oh sure, I'm happy to pick the first one...maybe something peaceful? I get the sense we could both use a little escape, and I know just the place.

**Landscape to Light**, James Ross & Maxwell Quartet

There's something indescribably comforting to me about music inspired by classic Celtic traditions. It's a sound that's contributed to countless modern music genres, and tracing those influences back to their roots can be calming.

Scottish composer and pianist James Ross invites us to experience a full spectrum of feelings in this album. Performed with exquisite sensitivity by the talented Maxwell Quartet, Landscape to Light is an album of tone poems, a book of stories about the grandeur of his north coast home.

I could point to so many moments, but I'll pick a few that I think you'll appreciate. Start from the top, with the title track. Let's press play. You'll have to give it a second—this kind of music isn't in a hurry.

At 0:46 we're introduced to the main melody, but you won't fall in love with it until it comes back, having explained itself. Do you notice the quartet using the space to bounce a note back and forth between our ears at the 1:30 mark? It's just before the cello steps in with a soaring countermelody, building a bridge of beautiful harmonies for us.

Remember I said you'd fall in love with the melody? Here it comes, at 2:18, to carry us into a satisfying conclusion.

Tracks 2 and 3 are sublime—especially 3, though its captivating melody takes its time appearing—but if you only have time for one then I recommend Fairy Hill. It seems to be the most popular track on the album, and I can see why. It's difficult not to be transported to a sunny hillside, wind blowing through the grass. Whether it's the piano or the violin carrying it, the lilting melody meanders brightly through a landscape of pizzicato rhythms and pulsing arpeggios. I can't help but smile.

Whatever I was worried about when I started listening was long forgotten by the time I reached the end of this album. I hope that's the case for you as well.

**Descensus**, Zedd, Dora Jar, Mesto

Shall we dial up the energy? This one is ear candy. There's a lot going on in this mix, and it rewards close attention and the best listening environment you can give it.

Nestled near the end of an incredible album, this song sounds like what might happen if you took a solid dose of classic dance, added some gothic flavour, and seasoned it with symphonic metal and some dubstep tendencies.

Try to pay attention to all the ways it's playing with our attention. The variety of sounds, the unexpected interruptions, the careful interplay of intensity and restraint. Once it gets going you'll probably think it sounds like chaos, but see if you can close your eyes and notice how all those moments, those microscopic gestures, are both harmonically and rhythmically locked in. There is method to this madness.

Those sorts of details are what I find myself appreciating when I'm lost in the music. Kudos to the artists and engineers who breathed so much life into this one.

This whole album, by the way, is great to pull out when your friend is trying to convince you that better headphones/earbuds/speakers really do sound better but you're skeptical. Listen to it on what you've got, then listen to it on what they've got and I bet you'll notice some things you didn't pick up on the first time around. Especially over the course of an album as eclectic as this one.

Descensus isn't even my favourite song on the album. I can't decide which I like best, but it's one of these: Tangerine Rays, Shanti, No Gravity, Dream Brother, or this one.

How about you?

**Broken Step**, AV On Decks & SamBeazy

Last one for today? Okay, let's take things in a different direction. Remember when I wrote about how you can learn to appreciate minimalism through music and vice-versa? This track is a perfect one to practise with.

The build is patient but gripping, the chords few but soulful, laced with yearning. Let it wash over you. There's restraint in the execution—this kind of piece could easily have ended up with too many layers too soon, but instead we get a carefully considered handful.

It's an interesting blend of genre elements, too. We get some traditional percussion instruments from around Africa delivering a foundation for more jungle-flavoured digital drums. Delicate plucks and processed vocal samples drift overtop, and an escalating assortment of synths deliver another layer of modern flavour.

Even 4 minutes in there are still significant sonic novelties being revealed. That takes skill and taste to deliver. For me, the payoff here is sweeter because of how carefully it's been prepared for us.

Let's do this again sometime

Discovering new music, talking about it, trying to appreciate all the details the artists worked to include...I have a lot of fun doing it.

Would there be any interest in me sharing recommendations, in a format like this, every couple of weeks or so? Write me a note if you'd be into it. If you use Scribbles like I do, you can even try out this fun new feature that was added recently.

Happy listening!

It's the only one I fully agree with, but unfortunately it's also the scariest. Especially from a security and privacy angle (a view I am predisposed to, given my workplace).

Here's what I highlighted:

Atlas is a browser, but it is not a web browser. It is an anti-web browser.

In the new-era command-line interface of Atlas, though, we're not just facing the challenges of an inscrutable command line. There's the even larger problem that, even if you guess the right magic words, it might either simply get things wrong or completely make things up. Atlas throws away the discoverability, simplicity and directness of the web by encouraging you to navigate even through your own documents and search results with an undefined, unknowable syntax that produces unreliable results.

In the marketing materials and demonstrations of Atlas, OpenAI's team describes the browser as being able to be your "agent", performing tasks on your behalf. But in reality, you are the agent for ChatGPT.

Those Google Docs files that your boss said to keep confidential. The things you type into a Facebook comment box but never hit "send" on. Exactly which ex's Instagram you were creeping on. How much time you spent comparing different pairs of shoes during your lunch hour. All of those things would never show up in ChatGPT's regular method of grabbing content off the internet.

But by acting as ChatGPT's agent, you can hold open the door so that the AI can now see and access all kinds of data it could never get to on its own. As publishers and content owners start to put up more effective ways of blocking the AI platforms from exploiting their content without consent, having users act as agents on behalf of ChatGPT lets them get around these systems, because site owners are never going to block their actual audience.

Their robots need humans to guide them around the gates that are quickly being erected around the open web, and if they can use that to keep their eyes on everything the humans are doing at the same time, so much the better. The "agent" story really only works in one direction, and that direction is anti-web.

I really, really want there to be more browsers! I want there to be lots of weird new ways of going around the web. I have my own LLM that I trained with my own content, and I bet if everybody else could have one like mine that they control, that had perfect privacy and wasn't owned by any big company, and never sent their data anywhere or did anything creepy, they'd want the benefits of that, too. It would even be awesome if that were integrated with their browser — with their web browser.

We need to have fewer things in the world that make us wonder whether everything is just made up bullshit.

In it, Jenny (a fellow Torontonian!) wonders what's underneath modern technology's promise of "convenience". She's pointing at artificial intelligence, but AI is just the neon lights version of the same story this industry has been telling for decades. In it, "convenience" means "productivity", which serves the people selling the widgets but doesn't always serve the rest of us in the ways we expect.

I think about what, exactly is becoming more convenient. Is it companionship with fellow people? Not really. The ability to focus my time and energy on things that enrich my life and contribute to those around me? That hasn't been my experience.

On paper, this productivity means we get our work done faster and can deploy the time saved in other ways. In reality, finishing our work early means our employers can assign more work. And even if they didn't, the extra time is a precious resource that we're getting rusty at spending on the things that move society forward. These tools help us become better workers, not necessarily better people. We look inward, shielding ourselves from the inconvenience of others. But that friction, Jenny argues, is central to the human experience.

While I agree with the broad strokes of this characterization, I still believe AI is fundamentally a technology, therefore a tool, and therefore subject to the imperfect whims of its operators. The challenge is to look past the marketing and manipulation and find ways to apply this technology for good—like we've had to with every other technology that came before it. If AI can save us time (which in my experience it can), then it still falls to me to use the time saved in constructive ways. It's not AI's fault if I choose to use it for doomscrolling, workaholism, or social isolation. That's on me.

A lot of anti-AI sentiment seems to wish for a world in which the technology didn't exist. We don't live in that world. In this world, my goal has been to explore and encourage more creative ways of applying this new force. It can do more than just make work more efficient. Shareholder value isn't the only thing we can build with these bricks.

Here's what I highlighted:

"all destination and no journey" is a pretty good explanation for why using AI to create art is mainly compelling to people who think about creativity in terms of producing content and generating intellectual property. They just want the thing they can market and sell for money or clout; they don't care how they got there.

I quite like thinking, and I think humans should do more of it, and I think the less we do it the more our thinking muscles will atrophy. This seems bad for everyone except for authoritarians who wish we were easier to control.

My refusal is a philosophical position more than it is a practical one, in the same way that my decisions not to use Amazon or Netflix or Spotify do more to introduce friction into my life in service of an abstract ideal than it does to actually engender pain for the corporate oligarchs I despise. I harbour no delusion that my individual refusal will slow AI's death drive to destroy societal trust and goodwill any more than I believe that Jeff Bezos is personally mourning money I'm not spending in his little shoppe. But if I am not capable of withstanding even this small amount of friction in my otherwise materially comfortable life for my ideals, what discomfort would I be able to endure when it matters more?

It is not virtuous to suffer, and discomfort is not noble. But everything in my life that is worth having, love and friendship and art and community, I found by fighting my way through discomfort. Pain does not mean growth, but growth does require pain. It is so easy in our rotten modernity to choose convenience and ease, to avoid friction at all costs and tell ourselves it is self-care. I choose the friction of refusal because I worry that if I forget how to be uncomfortable, I will forget how to grow. Refusal, like acquiescence, is habit-forming.

There are probably tasks that generative AI could help me do more quickly, if I can get over my fundamental moral disagreement with the technology. Maybe I would be able to fit more things into my life if I embraced it. But more does not always mean better, and abundance is not an uncomplicated good. We express our values and identities in what we choose to make time for, and the act of being forced to give some things up so you can prioritize other things, the realization that we cannot in fact have it all, that is what gives our choices meaning in the first place.

The problem with AI "art" is that it was not the expression of a mortal being choosing to spend its one wild and precious life clawing its way through mediocrity to try and imperfectly communicate a feeling with other mortal beings who, by definition, can never fully comprehend it, and therefore it is fundamentally uninteresting to me.

If you can push a button and get a screenplay or a symphony or a painting at the cost of a nominal subscription fee that does not begin to cover the true expense of this technology to the world, if you did not have to at least subconsciously face your mortality and decide that the pursuit of this piece of art is what you want to spend your finite time on, if your desire to speak is not strong enough to overcome the friction of learning how to speak, is it something that needed to be said?

The friction that the political project of AI promises to remove is, by and large, the same friction that authoritarianism promises to remove: other people.

That's one of many things Shannon, my wife, has taught me about love and life in the 16 years we've been together so far.

Here are a few more:

Friendship is gardening, not painting.
Relationships can't be set up and admired from afar; they must be nurtured to thrive.

Anger is a disguise for truer feelings.
If you're mad at others, it's often hunger. If you're mad at yourself, it's often exhaustion. If you're mad at the world, it's often fear. Look deeper and deal with the real feeling.

Related: always pack snacks. Hanger sneaks up and wreaks havoc.

The line between perseverance and stubbornness is thin but not invisible. Perseverance is the pursuit of a clear vision, no matter the obstacles. Stubbornness is a way to avoid admitting that we've lost our way.

If you're reading between the lines, make sure the lines actually exist. You can drive yourself mad looking for hidden motives and subliminal meaning where none exist.

Care is an activity, not an aspiration.
If you care about something, participate in its care. Donate your time, money, and energy to uplift the things that bring you joy.

If it looks insurmountable, you're standing too close.
The bigger the problem, the further back you need to stand to see the path through.

Accumulate experiences, not things.
Don't rely on objects to encode memories.

People usually want their problems heard, not solved.
Often the solution is already clear to them, it's just hard to confront the challenge alone.

How someone cares for you reveals how they want you to care for them.
Paying attention to how others show their love equips you to reciprocate.

Love people even when they don't love themselves.
Especially then.

The technology industry went from being a mechanism for dismantling silos to one that manufactures them. From a diverse and competitive jungle of hungry innovators, we've found ourselves in a beige desert, where enormous corporate interests quarrel in the distance like Kaiju while the rest of us seek shelter in the dust.

I want to recapture the spirit of cooperation and mutual benefit that paved the way for today's distorted takes on technology's true potential. Technology should be a force for connecting and providing, not segregating and exploiting. It's those positive manifestations that I admire and enjoy, so it's what I tend to look for when I explore.

My goal right now is to keep my tech stack nimble enough to pivot seamlessly as these giants grumble and quake around us. I want to be able to take my business to the highest bidder (in terms of delight, productivity, innovation, philosophy, etc.) in any given category without feeling beholden to their predecessor. I'm willing to weather some discomfort, change some habits, and explore some new paradigms along the way.

Nothing I do is so critical that it can't survive a bit of disruption, and I find that occasionally shaking up my patterns helps me grow.

Here's what I highlighted:

We now exist in what people call "late-stage capitalism," where meaningful competition only occurs among those with the most capital, and their battles wreck the landscape around them. We scatter and dash amidst the rubble like the unseen NPCs of Metropolis while the titans clash in the sky.

The much-lauded "democratic" technology of the early internet has given way to systems of surveillance and manipulation so comprehensive they would make 20th century authoritarians weep with envy, not to mention a fear-induced appeasement to the destruction of norms and legal protections that spreads across our entire culture like an overnight frost of fascism.

AI accelerates this process. It centralizes power by centralizing the capacity to process and act upon information. It creates unprecedented asymmetries between those who own the models and those who are modeled. Every interaction with an AI system becomes a one-way mirror: you see your reflection, while on the other side, entities you cannot see learn about you, categorize you, and make predictions about you.

Liberty in the age of AI requires more than just formal rights. It demands structural changes to how technology is developed, deployed, and governed. It requires us to ask not just "what can this technology do?" but "who benefits from what this technology does?"

To think about AI without thinking about capitalism, fascism, and liberty isn't just incomplete — it's dangerous. It blinds us to the real stakes of the transformation happening around us, encouraging us to focus on the technology rather than the systems that control it and the ends toward which it's deployed.

As AI advances, we face a choice: Will we allow it to become another tool for concentrating power and wealth? Or will we insist upon human dignity and liberty? The answer depends not on technological developments, but on our collective willingness to recognize AI for what it is: not a force of nature, but a product of flawed human choices embedded in vulnerable human systems.

Apple products have become familiar to the point of monotony. And, having spent weeks using the betas of the upcoming version of iOS, I can't shake the feeling that Liquid Glass is a design language at war with itself, contradicting its own mandate to put your content first by drawing attention to itself at every turn.

So what, it's a phone—just change it. You're right, and I did. Twice, actually. I spent a bit of time with the Google Pixel 9 Pro XL a few months back and the OnePlus 13 a little after that. But...at the time, RCS was just rolling out, and since most of my social life relied on iMessage, the friction was too great—if not for me, certainly for my friends and family who I had no desire to inflict turmoil upon.

Even so, to call the experience a breath of fresh air would be putting it lightly. It's so refreshing to see a fundamentally different take on the same promises Apple makes with its iPhones. Same form factor, same capabilities, yet governed by different philosophies and priorities.

I relish the changes to my routine.

The price of platform loyalty

Those attempts helped me realize there's plenty of innovation happening in the smartphone space, it's just not happening within Apple's walled garden. This means that many folks—myself included—have lost sight of those advances, discrediting them as if they're forbidden, veiled in a fog of platform war.

And for what? Ecosystem ties? What does that even mean?

Why should the tools we buy be allowed to strategically influence how we use them? How did we become convinced that innovation requires isolation? If these companies were as invested in broad human flourishing as they purport to be, we'd have a lot more interoperable, cooperative technology than we do.

Also worth asking: what do we gain in exchange for submitting to our ecosystem bonds? And are we sure the reasons given for these restrictions are demonstrably impactful to the average user? I find it hard to reconcile given that the global majority isn't bound by these limitations and yet manages to live, work, and play through these devices all the same. Android users outnumber iPhone users nearly three times over. Only in North America are iPhones dominant, which is another thing that's easy to lose sight of if you spend most of your time there.

I don't think we ought to accept the notion that technology has to be proprietary to be pleasing, polished, and purposeful. The fact that in some categories that appears to be the case doesn't mean it must or should be that way. It's on me to advocate for the kind of technology I want to see more of. When we've fallen into a well, we should ask for a ladder not a shovel.

All these thoughts came to a head for me recently. The thought of spending another autumn pining for the next incremental step, seeking wonder in mediocrity, suddenly felt exhausting. What I love is technology , not products. Brand should be one of many criteria, not the primary one.

Apple hasn't been earning my loyalty lately, and I'm all out of excuses. What better way to put my money where my mouth is than by changing the single most significant piece of personal technology in my life?

My old new phone

And so, after two false starts, I have switched my mobile computing platform to Android.

Just to be clear, I'm not dual-wielding here; my old iPhone 15 Pro Max is in a drawer, turned off. My Apple Watch Ultra 2 is keeping it company. Both will be sold or traded in toward their ultimate successors.

For now, I'm using a Samsung Galaxy S22 Ultra (2022's flagship) that I have for uninteresting reasons related to work. Over the next few weeks, manufacturers like Apple and Google will be unveiling their flagship hardware for the year, and I'd rather wait and see what they're bringing to the table before I decide on my next phone.

This way, I get to spend some time fully using Android as my mobile OS, and I won't be swayed by fancy cutting-edge hardware. If I miss iOS, I'll have been away just long enough for the iPhone 17 family to arrive on the scene and lure me back in. If not, extraordinary flagships from Google, Samsung, OnePlus, and more are vying for supremacy. And any one of them would feel like the biggest change to my phone experience in years.

Heck, even a three-year-old phone does! This thing has a pen built into it. It has four cameras. The screen is curved. These things aren't necessarily better, but I get the opportunity to find out. And no matter what I decide is important to me, I have options available.

There's not much point reviewing a three-year-old phone, so I'll just offer a few comparative thoughts. While this S22 Ultra is beginning to show its age, most notably in terms of its battery health, this has felt like more of a sidegrade than a downgrade.

Both it and my outgoing iPhone 15 Pro Max have spacious 120Hz OLED displays. On the Samsung, the display is slightly dimmer at max brightness, but it's higher resolution than my iPhone's—and I notice the resolution more. On the other hand, the Samsung is less responsive, with less consistent animations. You can feel the slower processor and sluggish storage speeds holding it back. I prefer the main camera from the iPhone, but I'd rather take selfies with the Samsung. They're way better. Biometrics differ too, face vs fingerprint. I haven't decided yet which I prefer, but I know I'd rather not have to choose.

There's not much more to say about the hardware, so let's talk about the most contentious difference: Android vs. iOS.

What it's like to switch to Android

You may be expecting a harrowing account of how challenging it was to detach myself from the Apple ecosystem, but it all turned out to be more of a mental barrier than a real one.

All my core apps are already cross-platform. Email is with Fastmail, calendars with Google, tasks with Todoist. Notes are in Obsidian, journals are in Day One, RSS is in Feedly, reading is in Readwise Reader. Thoughts, inspiration, bookmarks, products, watchlists, and games to play are all in MyMind. Podcasts are in Pocket Casts, Plex streams my personal media collection, and Apple Music is actually better on Android because you get access to better Bluetooth codecs. Secrets are, of course, in 1Password.

As for messages? I turned off iMessage, and after waiting a few hours for its tendrils to wither and fall away, I was pleased to discover that RCS (now fully rolled out) had taken over all my conversations, giving me the typing indicators, reactions, read receipts, and replies I appreciate in a daily messaging app. Only two group chats had issues, and me sending a new message manually to the same people fixed them both. No wonder Apple is dragging its feet with implementing the latest RCS functionality—this protocol strikes at the heart of their most powerful lock-in lever.

Alongside RCS messaging, there's Signal and Telegram, WhatsApp and Messenger...each with its own benefits and drawbacks. I'm on all of them, and while I certainly admire the makers of some of those apps more than others, there are more impactful ways for me to rebel against them. Besides, I'm not interested in policing the way people want to communicate with me. I'm just glad they do. And if that means keeping a few more messaging apps installed so folks can reach me, I'll take it. It's a good problem to have.

When it comes to the Android experience itself, it's terrific.

First of all, the universal back gesture? They were right all along. I'm not a big fan of Samsung's aesthetic with OneUI, but since this is Android I mostly don't have to see it if I don't want to. I've also replaced their system apps with Google's equivalents because I prefer them. Beyond that, I use Niagara launcher and a custom icon pack, which replaces the entire home screen and app launching experience with a completely different paradigm. To me, it feels both fresh and faster, more helpful than mainstream mobile OS interaction models. If I get tired of it, there are tens of other launchers and thousands of icon packs I could turn to for help refreshing and reinvigorating my enthusiasm—without having to change the hardware.

No one should be surprised to hear that iOS and Android are more alike than not, especially these days. They trade blows. Being able to have the number row on the keyboard in Android? Great. Not being able to tap the clock to scroll back to the top of a view? Less great. Being able to connect my iPad to an external display? Good. Being able to do the same thing from my phone? Better.

In other areas, Android is clearly ahead, in my estimation. Separate volume controls for alerts vs media vs ringtones vs. system sounds is fantastic. Native clipboard history is handy. Being able to control animation speed system-wide makes it easy to tune the interface responsiveness to suit your preferences. And many of the core features are just smarter; for example, auto-rotate uses the front-facing cameras to check which orientation your face is in relative to the screen, so if you're lying down and looking at your phone, it doesn't switch orientations on you unnecessarily. When you take a group photo, it takes multiple shots so you can later choose the best facial expression for everyone, overcoming the typical challenge of getting that perfect moment where no one is blinking or looking elsewhere.

There's a lot more to explore, and I'm excited by the sheer breadth of choices available to me, both in software and in hardware. I'm going to have to learn some new ways of doing things, and unlearn some old ones.

But unlike the previous times I've tried this, this time it feels easy .

Between RCS (replacing iMessage), Find Hub (replacing Find My), Blip (replacing AirDrop), KDE Connect (replacing Continuity), and a growing ecosystem of web-first and cross-platform apps, this is proving to be a smoother transition than I thought.

A new chapter

This doesn't mean I suddenly hate Apple.

I love my Mac, and I'll continue to purchase Apple products when they legitimately serve my needs better than other options, but I hope to start making my purchase decisions with more care and a more open mind. Gadgets aren't only important to me as a hobby, but also as a matter of professional interest.

One way I contribute to the world is by finding and sharing ways to use technology for good, which I believe requires it to be built on foundations that are distributed, interoperable, and humane. Never has this felt more important to me than now.

If I don't want technology to exclude, I shouldn't exclude entire branches of technology myself. At least not without trying them.

So here we are, in a season where I, a staunch Apple user of over a decade, should be debating nothing but the colour and size of iPhone I'll upgrade to (for no good earthly reason), or at least "iOS or Android this time?"—but I'm not. Instead, I'm mostly asking myself...slab or foldable?

Technology is fun again!

The pendulum continues to swing, from the post-war grit of our parents' values, to the easy-going idealism of our own upbringing, perhaps back now, toward a more measured perspective on what it takes to succeed.

Here's what I highlighted:

We tell them that if they just find their passion, work will magically transform into endless joy, as if difficulty is just a symptom of being in the wrong job rather than an inevitable part of doing anything worthwhile.

We've convinced an entire generation that if work feels hard, they must be doing it wrong.

Everything worth having lives on the other side of effort. Everything good requires tending. Everything beautiful demands maintenance.

The people who understand this most deeply are often the happiest, because they've made peace with the beautiful burden of nurturing. They know that the dishes exist because they've been eating good meals all week. The laundry piles up because they've been living a life worth getting dressed for.

And to extend this: I see people online constantly lamenting that they can't make or keep friends in adulthood, as if friendship is something that just happens to you rather than something you actively create. This, too, requires intentional effort. Want to get invited to dinner parties? Start throwing them. Menu planning, grocery runs, washing dishes until midnight while your guests laugh in the next room. Want good friends? Be the one who texts first, who remembers birthdays, who shows up with coffee when someone's having a terrible week. Be the person who helps with moves even when you'd rather stay home in your pajamas, who plans the group trips that everyone will remember years later.

We cannot keep buying the fallacy that everything meaningful should feel effortless, including the relationships that make life worth living.

We've made "work" synonymous with suffering, when it should be synonymous with building. Tending a garden requires effort, but you get to eat the tomatoes.

Our cultural obsession with finding passion has obscured a more fundamental truth: discipline matters more than motivation.

Motivation is weather: changeable, unpredictable, often absent when you need it most. Discipline is climate: the steady, reliable conditions you create for yourself regardless of how you feel on any given day.

This is why the influencer dream is so seductive and so dangerous. It promises intensity without consistency, passion without discipline, reward without work. It's the lottery ticket approach to career planning, and like most lottery tickets, it's a tax on not understanding probability.

What kind of life do you want to build? What values do you want your work to reflect? What skills do you want to develop? How do you want to contribute to the world around you? What kind of people do you want to work alongside? What are you willing to sacrifice for those things? What discomfort are you willing to endure? What would make you proud to be tired at the end of the day? If you want flexibility, are you willing to trade some security? If you want creativity, are you prepared for financial uncertainty? If you want to help people, can you handle seeing them at their worst? If you want to build something, are you ready for the loneliness of starting from zero?

Good work should do at least one of these things: fund the life you actually want to live, align with values you can defend at dinner parties, surround you with people who challenge you to grow, or teach you skills that compound like interest over decades. Great work does several of these at once.

Life is modular, not linear. You don't choose a career at twenty-two and stick with it for forty years like some kind of professional arranged marriage. Instead of hunting for the mythical perfect tree, follow your curiosity. What ideas make you pause while scrolling? What conversations do you find yourself returning to days later? When a friend mentions something interesting at dinner, what makes you want to know more?

In nature, adversity isn't the enemy of growth. It's the condition for it.

Ultimately, here's what I think we should tell young people about work: it will be harder than you expect and more rewarding than you can imagine, sometimes on the same day.

...hard work isn't the tax you pay for living, it's the tuition for a life worth having. Everything good requires work. Discipline trumps motivation. Meaning emerges not from avoiding struggle but from choosing struggle that serves something larger than yourself.

I read it some years ago, but its central ideas have stuck with me, and in times of trouble I find myself thinking back to the lessons it contains.

Here's what I highlighted:

When you love someone, you have to offer that person the best you have. The best thing we can offer another person is our true presence.

The main affliction of our modern civilization is that we don't know how to handle the suffering inside us and we try to cover it up with all kinds of consumption.

Part of the art of suffering well is learning not to magnify our pain by getting carried away in fear, anger, and despair. We build and maintain our energy reserves to handle the big sufferings; the little sufferings we can let go.

Happiness is not an individual matter; it has the nature of interbeing. When you are able to make one friend smile, her happiness will nourish you also. When you find ways to foster peace, joy, and happiness, you do it for everyone.

Happiness is impermanent, like everything else. In order for happiness to be extended and renewed, you have to learn how to feed your happiness. Nothing can survive without food, including happiness; your happiness can die if you don't know how to nourish it.

Being able to enjoy happiness doesn't require that we have zero suffering. In fact, the art of happiness is also the art of suffering well. When we learn to acknowledge, embrace, and understand our suffering, we suffer much less. Not only that, but we're also able to go further and transform our suffering into understanding, compassion, and joy for ourselves and for others.

To love is, first of all, to accept ourselves as we actually are. That is why in this love meditation, "Know thyself" is the first practice of love. When we practice this, we see the conditions that have caused us to be the way we are. This makes it easy for us to accept ourselves, including our suffering and our happiness at the same time.

If there is anything to be aware of, it's that an emotion is only an emotion, and that you are much more than one emotion. You are body, feelings, perceptions, mental formations, and consciousness. The territory of your being is large. One emotion is very little. An emotion is something that comes and stays for a while and eventually goes away. If during the time of the emotion, you have that insight, that insight will save you.

Walking in walking meditation is walking just to enjoy walking. You don't have any desire to arrive anywhere. Walking and not arriving, that is the technique. And you enjoy every step you make. Every step brings you home to the here and the now. Your true home is the here and the now, because only in this moment, in this place, called the here and the now, is life possible. Every step you take should bring you back to peace, to the present moment.

When you look at a tree in a storm, if you focus your attention on the top of the tree, you'll see the leaves and branches blowing wildly in the wind, and the tree will look so vulnerable, as though it could be broken at any time. But when you direct your attention down to the trunk of the tree, there's not so much movement. You see the stability of the tree, and you see that the tree is deeply rooted in the soil and can withstand the storm.

We don't understand ourselves. In our body there are conflicts and tensions, and we can't resolve them. Instead of stopping and looking deeply, we are running as far away as possible from the loneliness, grief, sadness, anger, and emptiness that we feel we can't bear. If we're in this situation and we find ourselves unable to communicate well with others, that's normal. They aren't communicating with themselves, and we aren't communicating with ourselves, so is it any wonder we have difficulty communicating with each other?