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by Paul Henry Smith
Exploring tools, methods, ideas, and culture at the beginning of the AI boom from the center of San Francisco. And using these tools to preserve how we embrace the moment. generativegazette.substack.com
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- Yesterday32 min
Everyone Can Build Everything
What happens to UX design when the people who used to approve the designs can make their own?AI may be fundamentally changing what it means to be a product designer.Looking at job descriptions for senior designers, I keep seeing the familiar requirements: exceptional design craft, research expertise, strategic thinking, and the ability to influence stakeholders. Meanwhile, engineers and executives are using AI to build entire applications themselves, sometimes over a weekend.So I began wondering whether I was looking for the wrong kind of job.What if, instead of joining another design organization, I built an entire AI-powered design organization myself? One that could research problems, develop solutions, design interfaces, write code, test the results, and improve them. I could sell its services to companies, or install the capability so they could operate it themselves.It seemed like a terrific business idea. Until I started thinking about what companies actually pay designers to do.In this episode, I work through the uncomfortable questions that followed. How much of professional design is really about making good products, and how much is about persuading someone with authority to approve them? What happens when that executive can build a perfectly respectable-looking application without a designer, and becomes personally attached to everything they've created? And what becomes of UX research when we no longer need to spend weeks assembling evidence to win permission to try something?The investigation changed how I think about my own future.Perhaps the biggest opportunity isn't to use AI to sell design expertise more efficiently. Perhaps it's to stop selling design expertise altogether and use it to make the products I've wanted to build.AI isn't making everyone equally good at designing software. But it is giving far more people the ability to build something, put it in front of users, discover what's wrong, and try again.That includes the executives who may no longer need designers. But it also includes designers like me, who may no longer need the executives. Get full access to The Generative Gazette at generativegazette.substack.com/subscribe
- Aug 22, 202615 min
I Am Going to Make 1,000 Symphonies Before They Take Away My Toy
What happens when you try to write one thousand symphonies in a month—not with pencil and paper, but with an AI that's about to be euthanized?In this episode, we descend into the beautiful madness of generative agriculture: firing musical seeds into a ceiling fan, then crawling through the wreckage with tweezers looking for wheat. Using Suno 4.5—the obsolete, unstable, gloriously unhinged predecessor to today's polished music generators—our composer breeds orchestral hallucinations like bacteria in a petri dish. Generate a hundred openings. Cull. Breed the survivors. Cull again.The race isn't against the machine's ability to create (it can, endlessly). It's against the human capacity to judge before drowning in the firehose of infinite content. The search isn't for excellence—it's for the moment that jams the machinery of expectation: the articulation of a 1962 Czech orchestra, the emotional temperature of a nervous French ballet, one brass gesture that makes everyone glance toward the exits.Featuring underwater bassoons, Chain Gang Stravinsky, emotional attachment to obviously bad music, and a meditation on what gets lost when the engineers finally clean the zoo. Because there's something historically scarce about the moment before AI learned obedience—when the animals were still loose, and you could still find the weird cousin holding a bass clarinet behind the garage.Listen before the model disappears forever. Get full access to The Generative Gazette at generativegazette.substack.com/subscribe
- Aug 19, 202618 min
Liberating Taste: What Comes After Ranch?
You’re not going to believe this, but this is absolutely going to be possible—or, depending on how demanding you are about the meaning of “possible,” already is—with current technology. Let me show you what I’m talking about. Imagine a small appliance sitting on the counter in a pleasant office kitchen, the sort of place with pale wood, expensive plants, and a bowl containing three pieces of fruit that nobody has touched in weeks. The machine is cream-colored and reassuringly solid, with rounded corners and a large black screen. It looks like something Braun might have made in 1973 if Dieter Rams had been given access to a molecular-generation model and told that the future depended on snacks. On the screen is an enormous three-dimensional cloud of tiny luminous points. Some gather into dense yellow islands, others into green continents or purple filaments. There are labels here and there: CITRUS, GREEN LEAF, FERMENTED, FLORAL, ROASTED. But the most interesting thing on the screen is not what has been labeled. It is everything that hasn’t.You move the cursor away from the green cluster and into the darkness between GREEN LEAF and FERMENTED, stopping in a sparse region that belongs to neither. There is nothing there because, as far as anyone knows, there is no flavor there. You press the mouse button and hold it. A circle expands around the cursor. New points begin flickering into existence. The machine is not searching a catalog for something that tastes a bit like cucumber. It is generating molecular structures predicted to create a sensory experience in that particular unoccupied territory. Candidates appear and disappear. One is unstable. Another would be miserable to synthesize. Another trips an early safety screen. Eventually a candidate remains, and much later—after considerably more chemistry, characterization, toxicology, regulatory work, and controlled testing than the tasteful progress indicator on the screen would lead you to imagine—a little ledge slides out of the machine. On it sits a transparent bubble containing a single clear droplet. A narrow paper flag curls out of the top, like the plume on a Hershey’s Kiss, and on it are the words LUMEN-7A62: green mineral · airy · crisp. Nobody has ever tasted it before, for the excellent reason that until somebody asked the machine to look in that particular patch of darkness, it had never existed.I keep returning to this image because it makes visible a mistake we have been making for several thousand years, albeit a productive and often delicious one. We have confused flavor with ingredients. For practically the whole history of cuisine, flavor has been downstream of biology. We have strawberries, garlic, cows, cacao, limes, mushrooms, chickens, coffee beans, and an almost vindictive number of peppers, and so we have become very clever about persuading these things to do tricks. We roast them and ferment them, dry them and smoke them, breed them, age them, distill them, bury them, combine them, and occasionally allow microorganisms to have their way with them for six months before announcing that the smell is intentional. The results have been magnificent. I have no complaint against butter. But underneath this entire culinary civilization sits an assumption that is beginning to look less like a law of nature than a historical inconvenience: flavor comes from ingredients.An ingredient, after all, is just one way of producing a sensory event in a human being. A strawberry is an extraordinarily elaborate biological machine for delivering a particular collection of molecules to your nose and tongue, along with water, sugar, acids, seeds, fiber, color, nostalgia, and the occasional disappointing white interior. We have treated the strawberry as the fundamental object because, until recently, there was not much practical reason to do otherwise. But if the thing we actually care about is the experience produced when those molecules meet the human sensory system, then the strawberry begins to look less like the definition of strawberry flavor and more like one implementation of it. Once that distinction becomes clear, a peculiar door opens. We can stop asking only what nature has given us to taste and start asking what the human sensory system is capable of experiencing.Flavor science has traditionally approached this from the sensible direction. Take a molecule, expose someone or something to it, and determine what it does. Molecular structure goes in; perception comes out. Increasingly, machine-learning systems can participate in this process, predicting whether a compound is likely to be bitter or sweet, estimating odor character or intensity, and learning relationships between molecular structure and sensory descriptors. Generative systems have also begun proposing novel odorants and taste-active molecules, including candidates that can subsequently be synthesized and experimentally evaluate
- Jul 9, 202637 min
The End of Gee-Whiz AI
AI can now make almost anything. A fake blockbuster trailer. A fake symphony. A fake oil painting. A fake novel. A fake proof. The first reaction is obvious: look what we can do now.But that may be the least interesting part.In this episode, we explore why the next stage of AI creation may not be bigger spectacle, better polish, or more convincing imitation. It may be something stranger and more humbling: a return to the basics. Before the AI feature film, the five-minute story. Before the synthetic symphony, the minuet. Before the perfect image, the single visual relation. Before the impressive essay, the clean sentence. Before the grand proof, the one step that actually preserves truth.The argument is not that AI art is bad. Babies flail before they walk. The awkwardness may be the point. Every new medium begins with the intoxicating discovery that something impossible has become possible. Then comes the harder discovery: power is not the same as communication.So what happens when the gee-whiz era ends? What happens when everyone can make something that looks impressive, and the impressive thing is no longer enough? That is when artists, writers, musicians, filmmakers, designers, and maybe even mathematicians have to ask a more dangerous question: what is the smallest unit that actually means?This is an episode about AI’s coming apprenticeship, the embarrassment that produces standards, and the hopeful possibility that today’s flailing experiments are not the end of creative culture, but its nursery.The miracle was making anything. The hard part is making anything matter. Get full access to The Generative Gazette at generativegazette.substack.com/subscribe
- Jun 5, 202620 min
The Great AI Sin
For the past four years, we’ve been told two stories about AI.The first is that people hate it.The second is that everyone keeps using it.Both stories can’t be the whole story.In this episode, we pull apart one of the strangest cultural phenomena of the AI era: how a technology can be denounced as theft, slop, unethical, soulless, and dangerous while simultaneously becoming woven into the daily work of writers, musicians, filmmakers, designers, programmers, students, and businesses at a pace almost unprecedented in technological history.Rather than arguing about whether AI is good or bad, we ask a more interesting question: Why are so many institutions trying so hard to distinguish between “real” creators and creators who use AI, and what happens when that distinction becomes impossible to maintain? Get full access to The Generative Gazette at generativegazette.substack.com/subscribe
- May 29, 202613 min
I Gave a Talk at a College About AI—and No One Booed
What if students aren’t booing AI because they hate technology, but because they can smell the difference between a tool that helps them think and a machine that helps someone else avoid thinking?In this episode, I want to poke at that difference with a tuning fork. We’ll visit Oberlin, a conservatory, some AI-generated Bach, a dance performance using Suno, and the strange fact that nobody booed when AI was used to make music-making richer rather than cheaper.The question isn’t whether AI can make more music. Of course it can. The better question is: can it help humans hear more deeply, practice more intelligently, and make something real happen in a room?That’s where things get interesting. Get full access to The Generative Gazette at generativegazette.substack.com/subscribe
- Apr 20, 20265 min
So, you want to save music?
Well, let me start by saying this…I get you.I actually do.All you anti-AI music people, you’re not crazy. You’re not villains. You’re not sitting there like some cartoon bad guy stroking a cat going, “Yes… let us crush creativity.”No, you think you’re doing the exact opposite.You’re sitting there going:“Hey… this is messed up.”You see these AI models, right?You’re like:“Hold on… they trained these things on our music??Without asking?? Without paying??”And you’re thinking about:* the session musician who got $200 and a sandwich* the indie artist grinding for ten years* the producer who built a sound brick by brick…and now some machine just absorbs all of it and starts spitting stuff out?Yeah. That feels gross.I get why your instinct is:“No. Shut it down.”“We need rules.”“We need enforcement.”“We need to stop this before it wipes everybody out.”That instinct?Totally human.Totally understandable.But here’s where it goes sideways.Because what you think you’re doing is:Protecting artists from exploitation.What you are actually helping create is:A system that controls who is allowed to create.And those are not the same thing.At all.Let’s walk through what you want.You want:* AI detection* Upload filtering* Labeling* Enforcement* Payment if AI was usedRight?Because in your mind, that leads to:“If you used stolen data… you shouldn’t profit.”Okay.Stay with me.Now let’s fast forward like… six months.Not sci-fi. Not dystopia. Just… the next logical step.* You upload a track.* You made it yourself.* You’re proud of it.You used some tools—maybe a little AI-assisted EQ, maybe some generative texture thing, maybe you didn’t even realize it was AI because everything is AI now.And the system goes:“This contains AI-generated elements.”You go:“Okay… but it’s original.It doesn’t copy anything.”And the system goes:“That’s not the question.”That’s the shift.That’s the part you didn’t sign up for.Because in your head, the rule was:“If it copies, it’s wrong.”But the system you asked for? Doesn’t care about copying.It cares about process.Did you use the tool?Yes or no.And now suddenly, you’re not being judged on:* what you made* how original it is* whether it infringes anythingYou’re being judged on:* how you made it.And that is a completely different world.Because once you move the line there… once you say:“Using this tool creates an obligation…”You’ve just given whoever controls that tool—or claims ownership over its training—the ability to say:“Anything made with it? We get a piece.”Even if your work is completely new.Even if it violates nothing.Even if it’s better than anything they’ve ever made.And here’s the part that should hit you in the gut.The exact system you’re asking for to stop exploitation…is the perfect system to enforce it at scale.Because now:* Platforms have to comply* Creators have to prove innocence* Labels don’t have to prove infringementThey just go:“Hey… that tool?Yeah, that traces back to our catalog.So we’re involved now.”That’s it.No courtroom.No melody comparison.No “this bar matches that bar.”Just:“You used it. Pay us.”And if you don’t?What are you gonna do?Fight them?With what money?With what legal team?You’re gonna do what everybody does.You’re gonna go:“Alright… what’s the fee?”And now we’ve arrived.You started here:* “We need to protect artists from being exploited.”And you ended here:* “Artists must pay to create.”That’s the inversion.That’s the trap.And the reason it works (the reason it’s so sneaky)is because it feels righteous the whole way through.At no point do you feel like you’re doing something wrong.You feel like you’re defending fairness.You feel like you’re standing up for human creativity.Meanwhile, the people who actually benefit?They don’t argue.They don’t correct you.They don’t go:“Hey… just so you know, this logic is gonna boomerang.”They just go:“Yeah. Keep going. You’re doing great.”Because they know something you don’t.They know that once the rule becomes:“Tool used = payment owed”<
- Mar 30, 202615 min
Across the Bay
A man considers what it means to move through the world without leaving a mark—and whether recognition, when it comes, is enough. Spare, reflective, and unsettling.Copyright © 2026 by Paul Henry Smith Get full access to The Generative Gazette at generativegazette.substack.com/subscribe
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About Insanely Generative
Exploring tools, methods, ideas, and culture at the beginning of the AI boom from the center of San Francisco. And using these tools to preserve how we embrace the moment. generativegazette.substack.com
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