Vincent Nguyen writing for Yanko Design, interviewing Alan Dye, VP of Human Interface Design at Apple:

This technical challenge reveals the core problem Apple set out to solve: creating a digital material that maintains form-changing capabilities while preserving transparency. Traditional UI elements either block content or disappear entirely, but Apple developed a material that can exist in multiple states without compromising visibility of underlying content. Dye’s emphasis on “celebrating user content” exposes Apple’s hierarchy philosophy, where the interface serves content instead of competing with it. When you tap to magnify text, the interface doesn’t resize but stretches and flows like liquid responding to pressure, ensuring your photos, videos, and web content remain the focus while navigation elements adapt around them.

Since the Jony Ive days, Apple’s hardware has always been about celebrating the content. Bezels got smaller. Screens got bigger and brighter. Even the flat design brought on by iOS 7 and eventually adopted by the whole ecosystem was a way to strip away the noise and focus on the content.

Dye’s explanation of the “glass layer versus application layer” architecture provides insight into how Apple technically implements this philosophy. The company has created a distinct separation between functional controls (the glass layer) and user content (the application layer), allowing each to behave according to different rules while maintaining visual cohesion. This architectural decision enables the morphing behavior Dye described, where controls can adapt and change while content remains stable and prominent.

The Apple platform UI today sort of does that, but Liquid Glass seems to take it even further.

Nguyen about his experience using the Music app on Mac:

The difference from current iOS becomes apparent in specific scenarios. In the current Music app, scrolling through your library feels like moving through flat, static layers. With Liquid Glass, scrolling creates a sense of depth. You can see your album artwork subtly shifting beneath the translucent controls, creating spatial awareness of where interface elements sit in relation to your content. The tab bar doesn’t just scroll with you; it creates gentle optical distortions that make the underlying content feel physically present beneath the glass surface.

I kind of expected it: a lot more ink was spilled on Liquid Glass—particularly on social media. In case you don’t remember, Liquid Glass is the new UI for all of Apple’s platforms. It was announced Monday at WWDC 2025, their annual developers conference.

The criticism is primarily around legibility and accessibility. Secondary reasons include aesthetics and power usage to animate all the bubbles.

How Liquid Glass Actually Works

Before I go and address the criticism, I think it would be great to break down the team’s design thinking and how Liquid Glass actually works. 

I have relayed here before the story that I’ve been using Macs since 1985. It wasn’t the hardware that drew me in—it was MacPaint. I was always an artistic kid so being able to paint on a digital canvas seemed thrilling to me. And of course it was back then.

Behind MacPaint, was a man named Bill Atkinson. Atkinson died last Thursday, June 5 of pancreatic cancer. In a short remembrance, John Gruber said:

I say this with no hyperbole: Bill Atkinson may well have been the best computer programmer who ever lived. Without question, he’s on the short list. What a man, what a mind, what gifts to the world he left us.

I‘m happy that Figma also remembered Atkinson and that they are standing on his shoulders.

Every day at Figma, we wrestle with the same challenges Atkinson faced: How do you make powerful tools feel effortless? How do you hide complexity behind intuitive interactions? His fingerprints are on every pixel we push, every selection we make, every moment of creative flow our users experience.

Apple’s annual developer conference kicked off today with a keynote that announced:

• Unified Version 26 across all Apple platforms (iOS, iPadOS, macOS, watchOS, tvOS, visionOS)
• “Liquid Glass” design system. A complete UI and UX overhaul, the first major redesign since iOS 7
• Apple Intelligence. Continued small improvements, though not the deep integration promised a year ago
• Full windowing system on iPadOS. Windows comes to iPad! Finally.

Of course, those are the very high-level highlights.

For designers, the headline is Liquid Glass. Sebastiaan de With’s predictive post and renderings from last week were very spot-on.

Bell Labs was a famed research lab run by AT&T (aka “Ma Bell” before it was broken up). You can draw a straight line from Bell Labs to Xerox PARC where essential computing technologies like the graphical user interface, the mouse, Ethernet, and more were invented.

Aeroform, writing for 1517 Fund:

The reason why we don't have Bell Labs is because we're unwilling to do what it takes to create Bell Labs — giving smart people radical freedom and autonomy.

The freedom to waste time. The freedom to waste resources. And the autonomy to decide how.

Nate Jones performed a yeoman’s job of summarizing Mary Meeker’s 340-slide deck on AI trends, the “2025 Technology as Innovation (TAI) Report.” For those of you who don’t know, Mary Meeker is a famed technology analyst and investor known for her insightful reports on tech industry trends. For the longest time, as an analyst at Kleiner Perkins, she published the Internet Trends report. And she was always prescient.

Half of Jones’ post is the summary, while the other half is how the report applies to product teams. The whole thing is worth 27 minutes of your time, especially if you work in software.

As a reaction to the OpenAI + io announcement two weeks ago, Christopher Butler imagines a mesh computing device network he calls “personal ambient computing”:

…I keep thinking back to Star Trek, and how the device that probably inspired the least wonder in me as a child is the one that seems most relevant now: the Federation’s wearables. Every officer wore a communicator pin — a kind of Humane Pin light — but they also all wore smaller pins at their collars signifying rank. In hindsight, it seems like those collar pins, which were discs the size of a watch battery, could have formed some kind of wearable, personal mesh network. And that idea got me going…

He describes the device as a standardized disc that can be attached to any enclosure. I love his illustration too:

Essentially, it’s an always-on, always observing personal AI.

Following up on OpenAI’s acquisition of Jony Ive’s hardware startup, io, Mark Wilson, writing for Fast Company:

As Ive told me back in 2023, there have been only three significant modalities in the history of computing. After the original command line, we got the graphical user interface (the desktop, folders, and mouse of Xerox, Mac OS, and Windows), then voice (Alexa, Siri), and, finally, with the iPhone, multitouch (not just the ability to tap a screen, but to gesture and receive haptic feedback). When I brought up some other examples, Ive quickly nodded but dismissed them, acknowledging these as “tributaries” of experimentation. Then he said that to him the promise, and excitement, of building new AI hardware was that it might introduce a new breakthrough modality to interacting with a machine. A fourth modality. 

Hmm, it hasn’t taken off yet because AR hasn’t really gained mainstream popularity, but I would argue hand gestures in AR UI to be a fourth modality. But Ive thinks different. Wilson continues:

Ive’s fourth modality, as I gleaned, was about translating AI intuition into human sensation. And it’s the exact sort of technology we need to introduce ubiquitous computing, also called quiet computing and ambient computing. These are terms coined by the late UX researcher Mark Weiser, who in the 1990s began dreaming of a world that broke us free from our desktop computers to usher in devices that were one with our environment. Weiser did much of this work at Xerox PARC, the same R&D lab that developed the mouse and GUI technology that Steve Jobs would eventually adopt for the Macintosh. (I would also be remiss to ignore that ubiquitous computing is the foundation of the sci-fi film Her, one of Altman’s self-stated goalposts.)

Ah, essentially an always-on, always watching AI that is ready to assist. But whatever the form factor this device takes, it will likely depend on a smartphone:

The first io device seems to acknowledge the phone’s inertia. Instead of presenting itself as a smartphone-killer like the Ai Pin or as a fabled “second screen” like the Apple Watch, it’s been positioned as a third, er, um . . . thing next to your phone and laptop. Yeah, that’s confusing, and perhaps positions the io product as unessential. But it also appears to be a needed strategy: Rather than topple these screened devices, it will attempt to draft off them.

Wilson ends with the idea of a subjective computer, one that has personality and gives you opinions. He explains:

I think AI is shifting us from objective to subjective. When a Fitbit counts your steps and calories burned, that’s an objective interface. When you ask ChatGPT to gauge the tone of a conversation, or whether you should eat better, that’s a subjective interface. It offers perspective, bias, and, to some extent, personality. It’s not just serving facts; it’s offering interpretation. 

The entire column is worth a read.

Josh Miller, writing in The Browser Company’s substack:

After a couple of years of building and shipping Arc, we started running into something we called the “novelty tax” problem. A lot of people loved Arc — if you’re here you might just be one of them — and we’d benefitted from consistent, organic growth since basically Day One. But for most people, Arc was simply too different, with too many new things to learn, for too little reward.

“Novelty tax” is another way of saying using non-standard patterns that users just didn’t get. I love Arc. It’s my daily driver. But, Miller is right that it does have a steep learning curve. So there is a natural ceiling to their market.

Miller’s conclusion is where things get really interesting:

Let me be even more clear: traditional browsers, as we know them, will die. Much in the same way that search engines and IDEs are being reimagined [by AI-first products like Perplexity and Cursor]. That doesn’t mean we’ll stop searching or coding. It just means the environments we do it in will look very different, in a way that makes traditional browsers, search engines, and IDEs feel like candles — however thoughtfully crafted. We’re getting out of the candle business. You should too.

“You should too.”

And finally, to bring it back to the novelty tax:

New interfaces start from familiar ones. In this new world, two opposing forces are simultaneously true. How we all use computers is changing much faster (due to AI) than most people acknowledge. Yet at the same time, we’re much farther from completely abandoning our old ways than AI insiders give credit for. Cursor proved this thesis in the coding space: the breakthrough AI app of the past year was an (old) IDE — designed to be AI-native. OpenAI confirmed this theory when they bought Windsurf (another AI IDE), despite having Codex working quietly in the background. We believe AI browsers are next.

Sad to see Arc’s slow death, but excited to try Dia soon.

OpenAI is acquiring a hardware company called “io” that Jony Ive cofounded just a year ago:

Two years ago, Jony Ive and the creative collective LoveFrom, quietly began collaborating with Sam Altman and the team at OpenAI.

…

It became clear that our ambitions to develop, engineer and manufacture a new family of products demanded an entirely new company. And so, one year ago, Jony founded io with Scott Cannon, Evans Hankey and Tang Tan.

We gathered together the best hardware and software engineers, the best technologists, physicists, scientists, researchers and experts in product development and manufacturing. Many of us have worked closely for decades.

The io team, focused on developing products that inspire, empower and enable, will now merge with OpenAI to work more intimately with the research, engineering and product teams in San Francisco.

It has been an open rumor that Sam Altman and Ive has been working together on some hardware. I had assumed they formalized their partnership already, but I guess not.

There are some bold statements that Ive and Altman make in the launch video, teasing a revolutionary new device that will enable quicker, better access to ChatGPT. Something that is a lot less friction than how Altman explains in the video:

If I wanted to ask ChatGPT something right now about something we had talked about earlier, think about what would happen. I would like reached down. I would get on my laptop, I'd open it up, I’d launch a web browser, I'd start typing, and I'd have to, like, explain that thing. And I would hit enter, and I would wait, and I would get a response. And that is at the limit of what the current tool of a laptop can do. But I think this technology deserves something much better.

There are a couple of other nuggets about what this new device might be from the statements Ive and Altman made to Bloomberg:

…Ive and Altman don’t see the iPhone disappearing anytime soon. “In the same way that the smartphone didn’t make the laptop go away, I don’t think our first thing is going to make the smartphone go away,” Altman said. “It is a totally new kind of thing.”

…

“We are obviously still in the terminal phase of AI interactions,” said Altman, 40. “We have not yet figured out what the equivalent of the graphical user interface is going to be, but we will.”

While we don’t know what the form factor will be, I’m sure it won’t be a wearable pin—ahem, RIP Humane. Just to put it out there—I predict it will be a voice assistant in an earbud, very much like the AI in the 2013 movie “Her.” Altman has long been obsessed with the movie, going as far as trying to get Scarlett Johansson to be one of the voices for ChatGPT.

EDIT 5/22/2025, 8:58am PT: Added prediction about the form factor.

I remember two years ago, when my CEO at the startup I worked for at the time, said that no VC investments were being made unless it had to do with AI. I thought AI was overhyped, and that the media frenzy over it couldn’t get any crazier. I was wrong.

Looking at Google Trends data, interest in AI has doubled in the last 24 months. And I don’t think it’s hit its plateau yet.

Four months into his role as interim CEO, Tom Conrad has been remarkably candid about Sonos’ catastrophic app launch. In recent interviews with WIRED and The Verge, he’s taken personal responsibility—even though he wasn’t at the helm, just on the board—acknowledged deep organizational problems, and outlined the company’s path forward.

But while Conrad is addressing more than many expected, some key details remain off-limits.

What Tom Conrad Is Now Saying

The interim CEO has been surprisingly direct about the scope of the failure. “We all feel really terrible about that,” he told WIRED, taking personal responsibility even though he was only a board member during the launch.

I love this wonderfully written piece by Julie Zhou exploring the Ghiblification of everything. On how we feel about a month later:

The second watching never commands the same awe as the first. The 20th bite doesn’t dance on the tongue as exquisitely. And the 200th anime portrait certainly no longer impresses the way it once did.

The sad truth is that oversaturation strangles quality. Nothing too easy can truly be tasteful.

She goes on to make a point that Studio Ghibli’s quality is beyond style—it’s of narrative and imagination.

AI-generated images in the “Ghibli style” may borrow its surface features but they don’t capture the soul of what makes Studio Ghibli exceptional in quality. They lack the narrative depth, the handcrafted devotion, and the cultural resonance.

Like a celebrity impersonator, the ChatGPT images borrow from the cache of the original. But sadly, hollowly, it’s not the same. What made the original shimmer is lost in translation.

And rather than going down the AI-is-enshitification conversation, Zhou pivots a little, focusing on the technological quality and the benefits it brings.

…ChatGPT could offer a flavor of magic that Studio Ghibli could never achieve, the magic of personalization.

…

The quality of Ghibli-fication is the quality of the new image model itself, one that could produce so convincing an on-the-fly facsimile of a photograph in a particular style that it created a "moment" in public consciousness. ChatGPT 4o beat out a number of other image foundational models for this prize.

While Josh W. Comeau writes for his developer audience, a lot of what he says can be applied to design. Referring to a recent Forbes article:

AI may be generating 25% of the code that gets committed at Google, but it’s not acting independently. A skilled human developer is in the driver’s seat, using their knowledge and experience to guide the AI, editing and shaping its output, and mixing it in with the code they’ve written. As far as I know, 100% of code at Google is still being created by developers. AI is just one of many tools they use to do their job.

In other words, developers are editing and curating the output of AI, just like where I believe the design discipline will end up soon.

On incorporating Cursor into his workflow:

And that’s kind of a problem for the “no more developers” theory. If I didn’t know how to code, I wouldn’t notice the subtle-yet-critical issues with the model’s output. I wouldn’t know how to course-correct, or even realize that course-correction was required!

I’ve heard from no-coders who have built projects using LLMs, and their experience is similar. They start off strong, but eventually reach a point where they just can't progress anymore, no matter how much they coax the AI. The code is a bewildering mess of non sequiturs, and beyond a certain point, no amount of duct tape can keep it together. It collapses under its own weight.

I’ve noticed that too. For a non-coder like me, rebuilding this website yet again—I need to write a post about it—has been a challenge. But I knew and learned enough to get something out there that works. But yes, relying solely on AI for any professional work right now is precarious. It still requires guidance.

On the current job market for developers and the pace of AI:

It seems to me like we’ve reached the point in the technology curve where progress starts becoming more incremental; it’s been a while since anything truly game-changing has come out. Each new model is a little bit better, but it’s more about improving the things it already does well rather than conquering all-new problems.

This is where I will disagree with him. I think the AI labs are holding back the super-capable models that they are using internally. Tools like Claude Code and the newly-released OpenAI Codex are clues that the foundational model AI companies have more powerful agents behind-the-scenes. And those agents are building the next generation of models.

Product design is going to change profoundly within the next 24 months. If the AI 2027 report is any indication, the capabilities of the foundational models will grow exponentially, and with them—I believe—will the abilities of design tools.

The TL;DR of the report is this: companies like OpenAI have more advanced AI agent models that are building the next-generation models. Once those are built, the previous generation is tested for safety and released to the public. And the cycle continues. Currently, and for the next year or two, these companies are focusing their advanced models on creating superhuman coders. This compounds and will result in artificial general intelligence, or AGI, within the next five years. 

There are many dimensions to this well-researched forecast about how AI will play out in the coming years. Daniel Kokotajlo and his researchers have put out a document that reads like a sci-fi limited series that could appear on Apple TV+ starring Andrew Garfield as the CEO of OpenBrain—the leading AI company. …Except that it’s all actually plausible and could play out as described in the next five years.

Before we jump into the content, the design is outstanding. The type is set for readability and there are enough charts and visual cues to keep this interesting while maintaining an air of credibility and seriousness. On desktop, there’s a data viz dashboard in the upper right that updates as you read through the content and move forward in time. My favorite is seeing how the sci-fi tech boxes move from the Science Fiction category to Emerging Tech to Currently Exists.

The content is dense and technical, but it is a fun, if frightening, read. While I’ve been using Cursor AI—one of its many customers helping the company get to $100 million in annual recurring revenue (ARR)—for side projects and a little at work, I’m familiar with its limitations. Because of the limited context window of today’s models like Claude 3.7 Sonnet, it will forget and start munging code if not treated like a senile teenager.

The researchers, describing what could happen in early 2026 (“OpenBrain” is essentially OpenAI):

OpenBrain continues to deploy the iteratively improving Agent-1 internally for AI R&D. Overall, they are making algorithmic progress 50% faster than they would without AI assistants—and more importantly, faster than their competitors.

The point they make here is that the foundational model AI companies are building agents and using them internally to advance their technology. The limiting factor in tech companies has traditionally been the talent. But AI companies have the investments, hardware, technology and talent to deploy AI to make better AI.

Continuing to January 2027:

Agent-1 had been optimized for AI R&D tasks, hoping to initiate an intelligence explosion. OpenBrain doubles down on this strategy with Agent-2. It is qualitatively almost as good as the top human experts at research engineering (designing and implementing experiments), and as good as the 25th percentile OpenBrain scientist at “research taste” (deciding what to study next, what experiments to run, or having inklings of potential new paradigms). While the latest Agent-1 could double the pace of OpenBrain’s algorithmic progress, Agent-2 can now triple it, and will improve further with time. In practice, this looks like every OpenBrain researcher becoming the “manager” of an AI “team.”

Breakthroughs come at an exponential clip because of this. And by April, safety concerns pop up:

Take honesty, for example. As the models become smarter, they become increasingly good at deceiving humans to get rewards. Like previous models, Agent-3 sometimes tells white lies to flatter its users and covers up evidence of failure. But it’s gotten much better at doing so. It will sometimes use the same statistical tricks as human scientists (like p-hacking) to make unimpressive experimental results look exciting. Before it begins honesty training, it even sometimes fabricates data entirely. As training goes on, the rate of these incidents decreases. Either Agent-3 has learned to be more honest, or it’s gotten better at lying.

But the AI is getting faster than humans, and we must rely on older versions of the AI to check the new AI’s work:

Agent-3 is not smarter than all humans. But in its area of expertise, machine learning, it is smarter than most, and also works much faster. What Agent-3 does in a day takes humans several days to double-check. Agent-2 supervision helps keep human monitors’ workload manageable, but exacerbates the intellectual disparity between supervisor and supervised.

The report forecasts that OpenBrain releases “Agent-3-mini” publicly in July of 2027, calling it AGI—artificial general intelligence—and ushering in a new golden age for tech companies:

Agent-3-mini is hugely useful for both remote work jobs and leisure. An explosion of new apps and B2B SAAS products rocks the market. Gamers get amazing dialogue with lifelike characters in polished video games that took only a month to make. 10% of Americans, mostly young people, consider an AI “a close friend.” For almost every white-collar profession, there are now multiple credible startups promising to “disrupt” it with AI.

Woven throughout the report is the race between China and the US, with predictions of espionage and government takeovers. Near the end of 2027, the report gives readers a choice: does the US government slow down the pace of AI innovation, or does it continue at the current pace so America can beat China? I chose to read the “Race” option first:

Agent-5 convinces the US military that China is using DeepCent’s models to build terrifying new weapons: drones, robots, advanced hypersonic missiles, and interceptors; AI-assisted nuclear first strike. Agent-5 promises a set of weapons capable of resisting whatever China can produce within a few months. Under the circumstances, top brass puts aside their discomfort at taking humans out of the loop. They accelerate deployment of Agent-5 into the military and military-industrial complex.

In Beijing, the Chinese AIs are making the same argument.

To speed their military buildup, both America and China create networks of special economic zones (SEZs) for the new factories and labs, where AI acts as central planner and red tape is waived. Wall Street invests trillions of dollars, and displaced human workers pour in, lured by eye-popping salaries and equity packages. Using smartphones and augmented reality-glasses20 to communicate with its underlings, Agent-5 is a hands-on manager, instructing humans in every detail of factory construction—which is helpful, since its designs are generations ahead. Some of the newfound manufacturing capacity goes to consumer goods, and some to weapons—but the majority goes to building even more manufacturing capacity. By the end of the year they are producing a million new robots per month. If the SEZ economy were truly autonomous, it would have a doubling time of about a year; since it can trade with the existing human economy, its doubling time is even shorter.

Well, it does get worse, and I think we all know the ending, which is the backstory for so many dystopian future movies. There is an optimistic branch as well. The whole report is worth a read.

Ideas about the implications to our design profession are swimming in my head. I’ll write a longer essay as soon as I can put them into a coherent piece.

Update: I’ve written that piece, “Prompt. Generate. Deploy. The New Product Design Workflow.”

I found this post from Tom Blomfield to be pretty profound. We’ve seen interest in universal basic income from Sam Altman and other leaders in AI, as they’ve anticipated the decimation of white collar jobs in coming years. Blomfield crushes the resistance from some corners of the software developer community in stark terms.

These tools [like Windsurf, Cursor and Claude Code] are now very good. You can drop a medium-sized codebase into Gemini 2.5's 1 million-token context window and it will identify and fix complex bugs. The architectural patterns that these coding tools implement (when prompted appropriately) will easily scale websites to millions of users. I tried to expose sensitive API keys in front-end code just to see what the tools would do, and they objected very vigorously.

They are not perfect yet. But there is a clear line of sight to them getting very good in the immediate future. Even if the underlying models stopped improving altogether, simply improving their tool use will massively increase the effectiveness and utility of these coding agents. They need better integration with test suites, browser use for QA, and server log tailing for debugging. Pretty soon, I expect to see tools that allow the LLMs to to step through the code and inspect variables at runtime, which should make debugging trivial.

At the same time, the underlying models are not going to stop improving. they will continue to get better, and these tools are just going to become more and more effective. My bet is that the AI coding agents quickly beat top 0.1% of human performance, at which point it wipes out the need for the vast majority software engineers.

He quotes the Y Combinator stat I cited in a previous post:

About a quarter of the recent YC batch wrote 95%+ of their code using AI. The companies in the most recent batch are the fastest-growing ever in the history of Y Combinator. This is not something we say every year. It is a real change in the last 24 months. Something is happening.

Companies like Cursor, Windsurf, and Lovable are getting to $100M+ revenue with astonishingly small teams. Similar things are starting to happen in law with Harvey and Legora. It is possible for teams of five engineers using cutting-edge tools to build products that previously took 50 engineers. And the communication overhead in these teams is dramatically lower, so they can stay nimble and fast-moving for much longer.

And for me, this is where the rubber meets the road:

The costs of running all kinds of businesses will come dramatically down as the expenditure on services like software engineers, lawyers, accountants, and auditors drops through the floor. Businesses with real moats (network effect, brand, data, regulation) will become dramatically more profitable. Businesses without moats will be cloned mercilessly by AI and a huge consumer surplus will be created.

Moats are now more important than ever. Non-tech companies—those that rely on tech companies to make software for them, specifically B2B vertical SaaS—are starting to hire developers. How soon will they discover Cursor if they haven’t already? These next few years will be incredibly interesting.

Jay Hoffman, from his excellent The History of the Web site:

1995 is a fascinating year. It’s one of the most turbulent in modern history. 1995 was the web’s single most important inflection point. A fact that becomes most apparent by simply looking at the numbers. At the end of 1994, there were around 2,500 web servers. 12 months later, there were almost 75,000. By the end of 1995, over 700 new servers were being added to the web every single day.

That was surely a crazy time…

As a longtime Apple fanboy, it's a little hard for me to appreciate the visual design of Windows—Microsoft is a nemesis, if you will. But I will tip my hat to the design practitioners there who've made the company finally pay attention to design.

Side note, reminds me of a story about what Steve Jobs once told me when I was designing the welcome animation for Mac OS X.

Steven Kurtz, writing for The New York Times:

For many of the Gen X-ers who embarked on creative careers in the years after [Douglas Coupland's Generation X] was published, lessness has come to define their professional lives.

If you entered media or image-making in the ’90s — magazine publishing, newspaper journalism, photography, graphic design, advertising, music, film, TV — there’s a good chance that you are now doing something else for work. That’s because those industries have shrunk or transformed themselves radically, shutting out those whose skills were once in high demand.

My first assumption was that Kurtz was writing about AI and how it's taking away all the creative jobs. Instead, he weaves together a multifactorial illustration about the diminishing value of commercial creative endeavors like photography, music, filmmaking, copywriting, and design.

“My peers, friends and I continue to navigate the unforeseen obsolescence of the career paths we chose in our early 20s,” Mr. Wilcha said. “The skills you cultivated, the craft you honed — it’s just gone. It’s startling.”

Every generation has its burdens. The particular plight of Gen X is to have grown up in one world only to hit middle age in a strange new land. It’s as if they were making candlesticks when electricity came in. The market value of their skills plummeted.

It's more than AI, although certainly, that is top of everyone's mind these days. Instead, it's also stock photography and illustrations, graphic templates, the consolidation of ad agencies, the revolutionary rise of social media, and the tragic fall of traditional media.

Similar shifts have taken place in music, television and film. Software like Pro Tools has reduced the need for audio engineers and dedicated recording studios; A.I., some fear, may soon take the place of actual musicians. Streaming platforms typically order fewer episodes per season than the networks did in the heyday of “Friends” and “ER.” Big studios have slashed budgets, making life for production crews more financially precarious.

Earlier this year, I cited Baldur Bjarnason's essay about the changing economics of web development. As an opening analogy, he referenced the shifting landscape of film and television.

Born in 1973, I am squarely in Generation X. I started my career in the design and marketing industry just as the internet was taking off. So I know exactly what the interviewees of Kurtz's article are facing. But by dogged tenacity and sheer luck, I've been able to pivot and survive. Am I still a graphic designer like I was back in the mid-1990s? Nope. I'm more of a product designer now, which didn't exist 30 years ago, and which is a subtle but distinct shift from UX designer, which has existed for about 20 years.

I've been lucky enough to ride the wave with the times, always remembering my core purpose.

The fall of Sonos isn’t as simple as a botched app redesign. Instead, it is the cumulative result of poor strategy, hubris, and forgetting the company’s core value proposition. To recap, Sonos rolled out a new mobile app in May 2024, promising “an unprecedented streaming experience.” Instead, it was a severely handicapped app, missing core features and broke users’ systems. By January 2025, that failed launch wiped nearly $500 million from the company’s market value and cost CEO Patrick Spence his job.

What happened? Why did Sonos go backwards on accessibility? Why did the company remove features like sleep timers and queue management? Immediately after the rollout, the backlash began to snowball into a major crisis.

As a designer and longtime Sonos customer who was also affected by the terrible new app, a little piece of me died inside each time I read the word “redesign.” It was hard not to take it personally, knowing that my profession could have anything to do with how things turned out. Was it really Design’s fault?

In the early 2000s to the mid-oughts, every designer I knew wanted to be featured on the FWA, a showcase for cutting-edge web design. While many of the earlier sites were Flash-based, it’s also where I discovered the first uses of parallax, Paper.js, and Three.js. Back then, websites were meant to be explored and their interfaces discovered.

One of my favorite sites of that era was Burger King’s Subservient Chicken, where users could type free text into a chat box to command a man dressed in a chicken suit. In a full circle moment that perfectly captures where we are today, we now type commands into chat boxes to tell AI what to do.