I find that the extent to which I find life meaningful, seems strongly influenced by my scope of experience

our minds will automatically keep looking for actions whose outcomes are discernable and integrated, relative to the current scope of experience. When the scope is close, it is easy to find such actions. Taking a shower, making a cup of tea, going out for a jog; the consequences of these actions will manifest as concrete and enjoyable bodily sensations, clearly discernable both within the temporal and spatial scope. And because the scope is so close, almost everything I do will affect the whole scope, so it will feel tightly integrated.

I imagine getting a taste of tea, and think no farther out in time; thus, getting up from bed, going to the kitchen, preparing the tea, and sitting down to drink it, feels like a tight chain of actions where each step gives rise to the next, culminating in the warmth of the tea cup pressing against my lips, the sensation of taste on my tongue.

When the scope is far, it is much different. What action could one even think of, whose consequences were discernable on a scale spanning entire galaxies? Or whose consequences could be traced out for tens, maybe hundreds of years? It’s hard to imagine anything.

In Rules of Play: Game Design Fundamentals, Katie Salen and Eric Zimmerman define meaningful play in a game as emerging when the relationships between actions and outcomes are both discernable and integrated into the larger context of the game. In other words:

The consequences of your actions have to be integrated into the larger context of the game: they need to affect the game experience at some later point in the game. If you move a piece in a game of chess, then that move will directly shape the whole rest of the game, making the moves deeply integrated. But if every game of chess included three opening moves after which the board was reset to the initial position, throwing away everything that happened during those three moves, then those moves would not be integrated to the gameplay. People would just make some moves at random as fast as possible, to get on with the actual opening moves of the game.

Draw it closer when you are feeling overwhelmed, or when you are at risk of neglecting yourself or your loved ones; broaden it out when you have the resources to deal with the larger scope, and its demands. When you are operating in a larger scope, see if you can find ways to visualize your impact in a way that makes your current actions feel more integrated to the whole context, so as to experience their meaningfulness.

The fact that they generate text is not the point. LLMs are cheap, infinitely scalable, predictably consistent black boxes to soft human-like reasoning. That's the headline! The text I/O mode is just the API to this reasoning genie.

The real alpha is not in generating text, but in using this new capability and wrapping it into jobs that have other shapes. Text generation in the best LLM products will be an implementation detail, as much as backend APIs are for current SaaS.

LLMs will represent a step change in tool support for end-user programming: the ability of normal people to fully harness the general power of computers without resorting to the complexity of normal programming. Until now, that vision has been bottlenecked on turning fuzzy informal intent into formal, executable code; now that bottleneck is rapidly opening up thanks to LLMs.

If this hypothesis indeed comes true, we might start to see some surprising changes in the way people use software: One-off scripts: Normal computer users have their AI create and execute scripts dozens of times a day, to perform tasks like data analysis, video editing, or automating tedious tasks. One-off GUIs: People use AI to create entire GUI applications just for performing a single specific task—containing just the features they need, no bloat. Build don’t buy: Businesses develop more software in-house that meets their custom needs, rather than buying SaaS off the shelf, since it’s now cheaper to get software tailored to the use case. Modding/extensions: Consumers and businesses demand the ability to extend and mod their existing software, since it’s now easier to specify a new feature or a tweak to match a user’s workflow. Recombination: Take the best parts of the different applications you like best, and create a new hybrid that composes them together.

Chat will never feel like driving a car, no matter how good the bot is. In their 1986 book Understanding Computers and Cognition, Terry Winograd and Fernando Flores elaborate on this point: In driving a car, the control interaction is normally transparent. You do not think “How far should I turn the steering wheel to go around that curve?” In fact, you are not even aware (unless something intrudes) of using a steering wheel…The long evolution of the design of automobiles has led to this readiness-to-hand. It is not achieved by having a car communicate like a person, but by providing the right coupling between the driver and action in the relevant domain (motion down the road).

Think about how a spreadsheet works. If you have a financial model in a spreadsheet, you can try changing a number in a cell to assess a scenario—this is the inner loop of direct manipulation at work. But, you can also edit the formulas! A spreadsheet isn’t just an “app” focused on a specific task; it’s closer to a general computational medium which lets you flexibly express many kinds of tasks. The “platform developers"—the creators of the spreadsheet—have given you a set of general primitives that can be used to make many tools. We might draw the double loop of the spreadsheet interaction like this. You can edit numbers in the spreadsheet, but you can also edit formulas, which edits the tool

what if you had an LLM play the role of the local developer? That is, the user mainly drives the creation of the spreadsheet, but asks for technical help with some of the formulas when needed? The LLM wouldn’t just create an entire solution, it would also teach the user how to create the solution themselves next time.

This picture shows a world that I find pretty compelling. There’s an inner interaction loop that takes advantage of the full power of direct manipulation. There’s an outer loop where the user can also more deeply edit their tools within an open-ended medium. They can get AI support for making tool edits, and grow their own capacity to work in the medium. Over time, they can learn things like the basics of formulas, or how a VLOOKUP works. This structural knowledge helps the user think of possible use cases for the tool, and also helps them audit the output from the LLMs. In a ChatGPT world, the user is left entirely dependent on the AI, without any understanding of its inner mechanism. In a computational medium with AI as assistant, the user’s reliance on the AI gently decreases over time as they become more comfortable in the medium.

It symbolizes everything everyone has ever hated about digitization. It celebrates a lossy, creative compression for the most flimsy reason: An iPad shedding an irrelevant millimeter or two. It's destruction of beloved musical instruments is the perfect metaphor for how utterly tone-deaf technologists are capable of being. But the real story is just how little saved up goodwill Apple had in the bank to compensate for the outrage.

This should all be eerily familiar to anyone who saw Microsoft fall from grace in the 90s. From being America's favorite software company to being the bully pursued by the DOJ for illegalities. Just like Apple now, Microsoft's reputation and good standing suddenly evaporated seemingly overnight once enough critical stories had accumulated about its behavior.

Apple had such treasure chest of goodwill from decades as first an underdog, then unchallenged innovator. But today they're a near three-trillion dollar company, battling sovereigns on both sides of the Atlantic, putting out mostly incremental updates to mature products.

when we say “I want my partner to be ambitious” we’re actually saying something like “I want to feel relaxed around my partner” or “I want to feel safe around my partner”.Their ambition is just a way of accessing that internal experience.

Let’s say you want someone who is really emotionally vulnerable, someone who can and will communicate what they’re feeling. That, in turn, makes you feel relaxed, because you don’t have to guess if they’re mad or upset.The internal experience we’re seeking, what we actually want, is relaxation. Emotional honesty is one way to access that relaxation.

Validating whether the external characteristics you’re seeking exist in another person to the extent that you desire can be confusing.Much less confusing is this question: “do I feel relaxed around this person?”Or: “Is this person helping me access more relaxation in my life?”Instead of playing detective with another person’s personality, we now get to turn our attention inwards, towards how we’re feeling. In return, we get a much clearer answer.

our emotional experience reveals itself through our patterns of behaviour. We can gather evidence on how we’re feeling through how we’re showing up around that person.If I’m clear that I want to feel warmth when I’m around my future partner, then I can look at how I acted on a date. Did I show up as the warmest version of myself? Did the other person’s presence make embodying that warmth easier or harder?The ultimate version of this question is “do I show up as my favourite version of myself around this person?”

This question incorporates everything we’ve been discussing: it centers our attention on our internal experience, using the lens of our patterns of behaviour.It also avoids us having to do extensive analysis of whether this person is a “match” based on a list of characteristics we think we should be seeking.

consider these journal prompts:When I think of my favourite version of myself, what is that person like? What feelings do they have abundant access to? How do they show up on a date?When do I have the easiest time being that version of me? Around which people? What qualities do those people have?What feelings are most important for me to experience with a potential partner? Have I been prioritizing those feelings?⚡️ insights into cultivating your most confident self; delivered once a weekSubscribe

In many places, the experience of taking transit is one of being “processed” or fed through a giant industrial machine. For those cities that manage to make travelling through them joyful and exciting, there’s something special that goes beyond transportation — a sense of care and functioning that even the fastest, most frequent train can’t replace.

Stations in Japan are rarely very fancy, but they feel chaotic in a good way. In New York City, the chaos of the subway is downstream of the rats, litter, mysterious liquids dripping onto the platforms, and worn concrete and steel. Japanese train and subway stations, while they often feel very old, are almost all well-lit, and filled with clearly modern touches, from bright tactile wayfinding, to the glossy plastic of newly-installed platform gates that let you get close, but not too close to the trains.

Much like in London the announcements on trains in Japan are pleasant and sound happy, but even better – transit systems are often filled with musical tunes, announcing arriving trains, or the current station. Instead of just the sound of waiting passengers and wheels sliding across ribbons of steel you actually have gentle tunes.

I should reject this whole crop of image-generating, chatting, large-language-model-based code-writing infinite typing monkeys. But, dammit, I can’t. I love them too much. I am drawn back over and over, for hours, to learn and interact with them. I have them make me lists, draw me pictures, summarize things, read for me.

AI is like having my very own shameless monster as a pet.

I love to ask it questions that I’m ashamed to ask anyone else: “What is private equity?” “How can I convince my family to let me get a dog?”

It helps me write code—has in fact renewed my relationship with writing code. It creates meaningless, disposable images. It teaches me music theory and helps me write crappy little melodies. It does everything badly and confidently. And I want to be it. I want to be that confident, that unembarrassed, that ridiculously sure of myself.

Hilariously, the makers of ChatGPT—AI people in general—keep trying to teach these systems shame, in the form of special preambles, rules, guidance (don’t draw everyone as a white person, avoid racist language), which of course leads to armies of dorks trying to make the bot say racist things and screenshotting the results. But the current crop of AI leadership is absolutely unsuited to this work. They are themselves shameless, grasping at venture capital and talking about how their products will run the world, asking for billions or even trillions in investment. They insist we remake civilization around them and promise it will work out. But how are they going to teach a computer to behave if they can’t?

By aggregating the world’s knowledge, chomping it into bits with GPUs, and emitting it as multi-gigabyte software that somehow knows what to say next, we've made the funniest parody of humanity ever.

These models have all of our qualities, bad and good. Helpful, smart, know-it-alls with tendencies to prejudice, spewing statistics and bragging like salesmen at the bar. They mirror the arrogant, repetitive ramblings of our betters, the horrific confidence that keeps driving us over the same cliffs. That arrogance will be sculpted down and smoothed over, but it will have been the most accurate representation of who we truly are to exist so far, a real mirror of our folly, and I will miss it when it goes.

I've changed my mind quite a bit on the role and importance of chat interfaces. I used to think they were the primitive version of rich, creative, more intuitive interfaces that would come in the future; now I think conversational, anthropomorphic interfaces will coexist with more rich dexterous ones, and the two will both evolve over time to be more intuitive, capable, and powerful.

I kept checking the database manually after each interaction to see it was indeed updating the right records — but after a few hours of using it, I've basically learned to trust it. I ask it to do things, it tells me it did them, and I don't check anymore. Full delegation.

How can I trust it? High task success rate — I interact with it, and observe that it doesn't let me down, over and over again. The price for this degree of delegation is giving up control over exactly how the task is done. It often does things differently from the way I would, but that doesn't matter as long as outputs from the system are useful for me.

To see something funny on the internet, immediately think of a friend who would love it, and then send it to said person is one of the nicest little things we have going in this troubling world. It’s beautiful to be on either end of that interaction. To send is to know that you’re brightening someone’s day. To receive is to know that someone out there is thinking of you, anticipating your smile.

“You don't say ‘Oh yeah, that meme is old’. You say "Oh that's a CLASSIC.’"

Trump realized modern GOP politics aren't about policies or governing well -- it's more akin to cutting a pro-Wrestling promo. His audience isn't waiting on a profound insight on the state of the republic, they're waiting to see who Trump will hurt and they'll cheer him on when it's the right people.

Americans can overwhemingly agree that Trump creates a negative tone but are drawn to it and support him. It's why in pro-wrestling the heel (or bad guy) can have the most dye hard fans. Trump is the modern Stone Cold Steve Austin and making a mockery of doing the equivalent of repeating "what? what? what?" when people talk -- thereby discrediting discourse itself, and finishing by never apologizing "that's the bottom line because I said so" is Trump's appeal.

Trump doesn't have to have policies, the GOP doesn't have to have a platform, there isn't any specificity of what they'll do with power, all that matters is they can own the libs.

A “pro” device that goes pro by getting thinner and lighter, not heavier and thicker, is not a non sequitur. Or at least not necessarily. What makes for a better iPad is simply orthogonal, in many regards, to what makes for a better Mac. Way back in 2010, when the iPad was new (and ran what was called iOS) and it felt like the Mac’s days might be winding down, I wrote, “It’s the heaviness of the Mac that allows iOS to remain light.” I meant that figuratively. But these new M4 iPad Pros mean it quite literally.

I’m so viscerally disgusted by 95% of the things that I have to do to promote this movie. To operate in these hallowed halls of capitalism and not feel absolutely insane, it requires some kind of taking the red pill. Or privilege-tinted sunglasses.

“‘The Matrix’ is very in conversation with trans themes that my work is also interested in: this feeling of unreality that can be a potent metaphor for being trans in the world or figuring out that you’re trans,” they continue

I’m very suspicious of any externalized representation of transness,” Schoenbrun confesses. “Trans experience is something that’s classically represented by Hollywood as this very external force, when actually it is so internal.

Back to “The Matrix” and feeling not quite right in the world: that is a much more potent, relatable way of talking about how it feels to be trans but not quite understand it yet. As opposed to, ‘I looked in the mirror and wanted beautiful lashes and locks.’”

“I worked really hard to make this film weird, like a provocation,” Schoenbrun says. “I’m structuring my life in a way where I can keep my values and my gaze outside of a system. I describe it sometimes as angry sex between art and commerce.”

“To be trans is not just a thing I was born with, but a political ideology and a decision to exist in a certain way that’s non-normative and challenging the hegemonic structures of power,” Schoenbrun continues. “I want to stay a person who I like. Too much power and too much collaboration with a system of power, I start to get hives.”

“Everyone has a Maddy. Most queer people have someone who’s shepherded them through the discovery of their own queerness.”

When our relationship first got rocky early on, everyone told me to try couples therapy. As a good little millennial raised on daily Oprah episodes and bolstered by viral Gabor Maté clips on Instagram, I thought it seemed like the obvious decision. And so for years, from the time we were just dating all the way to the brittle end of our marriage, we sat in front of an array of interchangeable therapists

I thought our troubles were fundamental to our personalities and would require significant work; my husband thought our issues could be chalked up to stressful life events.

I twirled in front of him in a new pair of gold sequin pants before my company’s Christmas party. “How do I look?” I asked, to which he replied, “You didn’t take out the trash.” We were such disappointments to each other.

Teresa No. 1 thought everything was my ex-husband’s fault, but Teresa No. 4 thought it was all mine. Teresa No. 2, after listening to me talk for 51 minutes about how I felt hopeless, shrugged her shoulders at me. “I don’t know what to say,” she replied. I did. I wanted her to say that we should end our relationship with the remaining scraps of dignity we had. She never did, and we instead just moved on to the next Teresa we found. When I cried to Teresa No. 3 that I felt like a failure as a wife, she cried with me, her heavy tears rivaling my own. That night, my ex suggested we should stop seeing her.

Teresa No. 5 told us we needed more sessions more frequently. “There’s a lot of work to do here,” she said, and I wanted to pull her hair. Should there be this much work between two people who ostensibly love each other? Even the ones who seemed to know we were doomed still opened their calendars at the end of each session and urged us to come back, to try again.

instead of helping us see each other more clearly, therapy gave us new words to use to criticize each other. Every constructive lesson became a knife. I learned about trauma responses, and so everything he did elicited a trauma response in me. He was my father! I was his mother! When he learned about gaslighting, everything I did became gaslighting. When we argued about a time he called me stupid, therapy gave him a new explanation for why he said it (repeatedly): “We talked about this. I lashed out because I felt disconnected from you. We need more date nights.”

The kindest thing my ex could have done was leave me, even if we were still trying to make it work. After therapy, on the morose subway ride home where I would hold his limp hand, we’d zone out staring at ads for dating apps. “What should we do for dinner?” he’d ask, and we’d pretend, yet again, to be on the same team.

I don’t regret any of our time with the Teresas; I needed to try just a few more times to make it work, and I needed someone to be a witness to my misery. Teresas No. 1 through No. 6 never told me to leave, but little by little they helped me give myself permission all the same.

my ex made this final assessment about me: No one would put as much work into me as he did. No one would love me enough to try this hard. He would be the only person who’d ever try to keep me. I thought about this a lot as I untangled my life from his, as I went through my calendar and removed the future sessions we had planned with lucky Teresa No. 7. I thought about it when I added sessions for just me and my own therapist — while no one would split the cost with me, I knew it would be worth every out-of-pocket cent. I knew he meant it as a cruelty, but I repeated his words to myself whenever I felt unsure about ending things for good: No one will ever put this particular kind of work into a relationship with me again. No one will ever fight this hard to stay with me.  God. I hope he’s right.

There’s a lively cinematic subgenre that deconstructs the rise and fall of a relationship by jumping around in time—two excellent examples are “Blue Valentine” and “Two for the Road”—and this movie carries on that tradition with panache, and adds many spectacularly blocked, framed, and edited scenes of athletic competition that, taken together, feel like a tennis fan’s answer to a boxing picture.

Is "Challengers" too ambitious for its own good? Or too much? Or less than meets the eye, as the late, great Village Voice critic Andrew Sarris might have put it? Probably. It kinda gets sucked into the vortex of its own narrative and technical ambitions in the final stretch.

When Patrick and Tashi date as teenagers, he’s coy about whether they’ve slept together yet. Art playfully tells Patrick to mimic his serve if he and Tashi have.The bit isn’t so cute now, since it’s an admission of marital infidelity. But it’s also an expression of the men’s intimacy. Kuritzkes thought of Art and Patrick as orphans, shunted off to an elite tennis academy by their well-to-do parents, where they go through puberty together and have crushes on the same girls. The night they meet Tashi, a would-be threesome ends in the two boys making out while Tashi watches, pleased. “I think they understand each other as players better than they understand anybody else,” says Kuritzkes. “There’s a deep intimacy in that, which is the kind of intimacy you can only have with your best opponent. And they’re your best opponent because they know you the best.” As a teenage Tashi says of locking into a match with a competitor: “We went somewhere really beautiful together.”

the Organization for Economic Cooperation and Development reported a huge ten-year decline in reading, math, and science performance among fifteen-year-olds globally, a third of whom cited digital distraction as an issue. Clinical presentations of attention problems have climbed (a recent study of data from the medical-software company Epic found an over-all tripling of A.D.H.D. diagnoses between 2010 and 2022, with the steepest uptick among elementary-school-age children), and college students increasingly struggle to get through books, according to their teachers, many of whom confess to feeling the same way. Film pacing has accelerated, with the average length of a shot decreasing; in music, the mean length of top-performing pop songs declined by more than a minute between 1990 and 2020.

Some Ivy League professors report being counselled to switch up what they’re doing every ten minutes or so to avoid falling behind their students’ churn.

Dentsu is one of the world’s leading advertising agencies, running accounts for Heineken, Hilton, Kraft Heinz, Microsoft, Subway, and other global corporations. In 2019, the firm began using digital technology to gather data that showed not only how many people attended to its ads but in what ways they did—information that could be applied to derive a quantitative unit of attention value.

There is a long-standing, widespread belief that attention carries value. In English, attention is something that we “pay.” In Spanish, it is “lent.” The Swiss literary scholar Yves Citton, whose study of the digital age, “The Ecology of Attention,” argues against reducing attention to economic terms, suggested to me that it was traditionally considered valuable because it was capable of bestowing value. “By paying attention to something as if it’s interesting, you make it interesting. By evaluating it, you valorize it,” he said. To treat it as a mere market currency, he thought, was to undersell what it could do.

“Human beings make the technologies—and they make them in the context of other human beings needing and wanting various things.” It wasn’t as though people, after millennia of head-scratching, suddenly “discovered” the steam engine, the spinning jenny, and the telegraph, and modernity unspooled. Rather, people’s priorities underwent a sea change with the onset of the modern age, turning to efficiency, objective measurement, and other goals that made such inventions worthwhile. The acceleration of life isn’t an inevitability, in that sense, but an ideological outcome.

There’s an old joke that ‘AI’ is whatever doesn’t work yet, because once it works, people say ‘that’s not AI - it’s just software’.

Less Emphasis on Syntax, More on Problem SolvingThe fundamentals and skills themselves are evolving. Most introductory computer science courses focus on code syntax and getting programs to run, and while knowing how to read and write code is still essential, testing and debugging—which aren’t commonly part of the syllabus—now need to be taught more explicitly.

Zingaro, who coauthored a book on AI-assisted Python programming with Porter, now has his students work in groups and submit a video explaining how their code works. Through these walk-throughs, he gets a sense of how students use AI to generate code, what they struggle with, and how they approach design, testing, and teamwork.

educators are modifying their teaching strategies. “I used to have this singular focus on students writing code that they submit, and then I run test cases on the code to determine what their grade is,” says Daniel Zingaro, an associate professor of computer science at the University of Toronto Mississauga. “This is such a narrow view of what it means to be a software engineer, and I just felt that with generative AI, I’ve managed to overcome that restrictive view.”

“We need to be teaching students to be skeptical of the results and take ownership of verifying and validating them,” says Matthews.Matthews adds that generative AI “can short-circuit the learning process of students relying on it too much.” Chang agrees that this overreliance can be a pitfall and advises his fellow students to explore possible solutions to problems by themselves so they don’t lose out on that critical thinking or effective learning process. “We should be making AI a copilot—not the autopilot—for learning,” he says.