For my series on the Design Talent Crisis (see Part I and Part II) I interviewed five recent graduates from California College of the Arts (CCA) and San Diego City College. I’m an alum of CCA and I used to teach at SDCC. There’s a mix of folks from both the graphic design and interaction design disciplines. 

Meet the Grads

If these enthusiastic and immensely talented designers are available and you’re in a position to hire, please reach out to them!

Benedict Allen

Luke Wroblewski, writing in his blog:

Across several of our companies, software development teams are now "out ahead" of design. To be more specific, collaborating with AI agents (like Augment Code) allows software developers to move from concept to working code 10x faster. This means new features become code at a fast and furious pace.

When software is coded this way, however, it (currently at least) lacks UX refinement and thoughtful integration into the structure and purpose of a product. This is the work that designers used to do upfront but now need to "clean up" afterward. It's like the development process got flipped around. Designers used to draw up features with mockups and prototypes, then engineers would have to clean them up to ship them. Now engineers can code features so fast that designers are ones going back and cleaning them up.

This is what I’ve been secretly afraid of. That we would go back to the times when designers were called in to do cleanup. Wroblewski says:

Instead of waiting for months, you can start playing with working features and ideas within hours. This allows everyone, whether designer or engineer, an opportunity to learn what works and what doesn’t. At its core rapid iteration improves software and the build, use/test, learn, repeat loop just flipped, it didn't go away.

Yeah, or the feature will get shipped this way and be stuck this way because startups move fast and move on.

My take is that as designers, we need to meet the moment and figure out how to build design systems and best practices into the agentic workflows our developer counterparts are using.

In many ways, this excellent article by Kaustubh Saini for Final Round AI’s blog is a cousin to my essay on the design talent crisis. But it’s about what happens when people “become” developers and only know vibe coding.

The appeal is obvious, especially for newcomers facing a brutal job market. Why spend years learning complex programming languages when you can just describe what you want in plain English? The promise sounds amazing: no technical knowledge required, just explain your vision and watch the AI build it.

In other words, these folks don’t understand the code and, well, bad things can happen.

The most documented failure involves an indie developer who built a SaaS product entirely through vibe coding. Initially celebrating on social media that his "saas was built with Cursor, zero hand written code," the story quickly turned dark.

Within weeks, disaster struck. The developer reported that "random things are happening, maxed out usage on api keys, people bypassing the subscription, creating random shit on db." Being non-technical, he couldn't debug the security breaches or understand what was going wrong. The application was eventually shut down permanently after he admitted "Cursor keeps breaking other parts of the code."

This failure illustrates the core problem with vibe coding: it produces developers who can generate code but can't understand, debug, or maintain it. When AI-generated code breaks, these developers are helpless.

I don’t foresee something this disastrous with design. I mean, a newbie designer wielding an AI-enabled Canva or Figma can’t tank a business alone because the client will have eyes on it and won’t let through something that doesn’t work. It could be a design atrocity, but it’ll likely be fine.

This can happen to a designer using vibe coding tools, however. Full disclosure: I’m one of them. This site is partially vibe-coded. My Severance fan project is entirely vibe-coded.

But back to the idea of a talent crisis. In the developer world, it’s already happening:

The fundamental problem is that vibe coding creates what experts call "pseudo-developers." These are people who can generate code but can't understand, debug, or maintain it. When AI-generated code breaks, these developers are helpless.

In other words, they don’t have the skills necessary to be developers because they can’t do the basics. They can’t debug, don’t understand architecture, have no code review skills, and basically have no fundamental knowledge of what it means to be a programmer. “They miss the foundation that allows developers to adapt to new technologies, understand trade-offs, and make architectural decisions.”

Again, assuming our junior designers have the requisite fundamental design skills, not having spent time developing their craft and strategic skills through experience will be detrimental to them and any org that hires them.

Sonos announced yesterday that interim CEO Tom Conrad was made permanent. From their press release:

Sonos has achieved notable progress under Mr. Conrad’s leadership as Interim CEO. This includes setting a new standard for the quality of Sonos’ software and product experience, clearing the path for a robust new product pipeline, and launching innovative new software enhancements to flagship products Sonos Ace and Arc Ultra.

Conrad surely navigated this landmine well after the disastrous app redesign that wiped almost $500 million from the company’s market value and cost CEO Patrick Spence his job. My sincere hope is that Conrad continues to rebuild Sonos’s reputation by continuing to improve their products.

In case you missed it, there’s been a major shift in the AI tool landscape.

On Friday, OpenAI’s $3 billion offer to acquire AI coding tool Windsurf expired. Windsurf is the Pepsi to Cursor's Coke. They're both IDEs, the programming desktop application that software developers use to code. Think of them as supercharged text editors but with AI built in.

On Friday evening, Google announced that it had hired Windsurf's CEO Varun Mohan, co-founder Douglas Chen, and several key researchers for $2.4 billion.

On Monday, Cognition, the company behind Devin, the self-described “AI engineer” announced that it had acquired Windsurf for an undisclosed sum, but noting that its remaining 250 employees will “participate financially in this deal.”

Why does this matter to designers?

The AI tools market is changing very rapidly. With AI helping to write these applications, their numbers and features are always increasing—or in this case, maybe consolidating. Choose wisely before investing too deeply into one particular tool. The one piece of advice I would give here is to avoid lock-in. Don’t get tied to a vendor. Ensure that your tool of choice can export your work—the code.

Jason Lemkin has more on the business side of things and how it affects VC-backed startups.

Geoffrey Litt, Josh Horowitz, Peter van Hardenberg, and Todd Matthews writing a paper for research lab Ink & Switch, offer a great, well-thought piece on what they call “malleable software.”

We envision a new kind of computing ecosystem that gives users agency as co-creators. … a software ecosystem where anyone can adapt their tools to their needs with minimal friction. … When we say ‘adapting tools’ we include a whole range of customizations, from making small tweaks to existing software, to deep renovations, to creating new tools that work well in coordination with existing ones. Adaptation doesn’t imply starting over from scratch.

In their paper, they use analogies like kitchen tools and tool arrangement in a workshop to explore their idea. With regard to the current crop of AI prompt-to-code tools…

We think these developments hold exciting potential, and represent a good reason to pursue malleable software at this moment. But at the same time, AI code generation alone does not address all the barriers to malleability. Even if we presume that every computer user could perfectly write and edit code, that still leaves open some big questions.

How can users tweak the existing tools they’ve installed, rather than just making new siloed applications? How can AI-generated tools compose with one another to build up larger workflows over shared data? And how can we let users take more direct, precise control over tweaking their software, without needing to resort to AI coding for even the tiniest change? None of these questions are addressed by products that generate a cloud-hosted application from a prompt.

Kind of a different take than the “personal software” we’ve seen written about before.

This post has been swimming in my head since I read it. Elena Verna, who joined Lovable just over a month ago to lead marketing and growth, writing in her newsletter, observes that everyone at the company is an AI-native employee. “An AI-native employee isn’t someone who ‘uses AI.’ It’s someone who defaults to AI,” she says.

On how they ship product:

Here, when someone wants to build something (anything) - from internal tools, to marketing pages, to writing production code - they turn to AI and... build it. That’s it.

No headcount asks. No project briefs. No handoffs. Just action.

At Lovable, we’re mostly building with… Lovable. Our Shipped site is built on Lovable. I’m wrapping hackathon sponsorship intake form in Lovable as we speak. Internal tools like credit giveaways and influencer management? Also Lovable (soon to be shared in our community projects so ya’ll can remix them too). On top of that, engineering is using AI extensively to ship code fast (we don’t even really have Product Managers, so our engineers act as them).

I’ve been hearing about more and more companies operating this way. Crazy time to be alive.

More on this topic in a future long-form post.

John Calhoun joined Apple 30 years ago as a programmer to work on the Color Picker.

Having never written anything in assembly, you can imagine how overjoyed I was. It’s not actually a very accurate analogy, but imagine someone handing you a book in Chinese and asking you to translate it into English (I’m assuming here that you don’t know Chinese of course). Okay, it wasn’t that hard, but maybe you get a sense that this was quite a hurdle that I would have to overcome.

Calhoun was given an old piece of code and tasked with updating it. Instead, he translated it into a programming language he knew—C—and then decided to add to the feature. He explains:

I disliked HSL as a color space, I preferred HSV (Hue, Saturation, Value) because when I did artwork I was more comfortable thinking about color in those terms. So writing an HSV color picker was on my short list.

When I had my own color picker working I think I found that it was kind of fun. Perhaps for that reason, I struck out again and wrote another color picker. The World Wide Web (www) was a rather new thing that seemed to be catching on, so I naturally thought that an HTML color picker made sense. So I tackled that one as well. It was more or less the RGB color picker but the values were in hexadecimal and a combined RGB string value like “#FFCC33” was made easy to copy for the web designer.

So an engineer decided, all on his own, that he'd add a couple extra features. Including the fun crayon picker:

On a roll, I decided to also knock out a “crayon picker”. At this point, to be clear, the color picker was working and I felt I understood it well enough. As I say, I was kind of just having some fun now.

And Calhoun makes this point:

It was frankly a thing I liked about working for Apple in those days. The engineers were the one’s driving the ship. As I said, I wrote an HSV picker because it was, I thought, a more intuitive color space for artists. I wrote the HTML color picker because of the advent of the web. And I wrote the crayon picker because it seemed to me to be the kind of thing Apple was all about: HSL, RGB — these were kind of nerdy color spaces — a box of crayons is how the rest of us picked colors.

Making software—especially web software—has matured since then, with product managers and designers now collaborating closely with engineers. But with AI coding assistants, the idea of an individual contributor making solo decisions and shipping code might become de rigueur again.

Let's continue down Mac memory lane with this fun post from Basic Apple Guy:

With macOS 26, Apple has announced a dramatically new look to their UI: Liquid Glass. Solid material icon elements give way to softer, shinier, glassier icons. The rounded rectangle became slightly more rounded, and Apple eliminated the ability for icon elements to extend beyond the icon rectangle (as seen in the current icons for GarageBand, Photo Booth, Dictionary, etc.).

With this release being one of the most dramatic visual overhauls of macOS's design, I wanted to begin a collection chronicling the evolution of the system icons over the years. I've been rolling these out on social media over the past week and will continue to add to and update this collection slowly over the summer. Enjoy!

I was in London last week with my family and spotted this ad in a Tube car. With the headline “Humans Were the Beta Test,” this is for Artisan, a San Francisco-based startup peddling AI-powered “digital workers.” Specifically an AI agent that will perform sales outreach to prospects, etc.

I’ve long left the Bay Area, but I know that the 101 highway is littered with cryptic billboards from tech companies, where the copy only makes sense to people in the tech industry, which to be fair, is a large part of the Bay Area economy. Artisan is infamous for its “Stop Hiring Humans” campaign which went up late last year. Being based in San Diego, much further south in California, I had no idea. Artisan wasn’t even on my radar.

Here we go. Figma has just dropped their S-1, or their registration for an initial public offering (IPO).

While a lot of the risk factors are boilerplate—legalese to cover their bases—the one about AI is particularly interesting, “Competitive developments in AI and our inability to effectively respond to such developments could adversely affect our business, operating results, and financial condition.”

Developments in AI are already impacting the software industry significantly, and we expect this impact to be even greater in the future. AI has become more prevalent in the markets in which we operate and may result in significant changes in the demand for our platform, including, but not limited to, reducing the difficulty and cost for competitors to build and launch competitive products, altering how consumers and businesses interact with websites and apps and consume content in ways that may result in a reduction in the overall value of interface design, or by otherwise making aspects of our platform obsolete or decreasing the number of designers, developers, and other collaborators that utilize our platform. Any of these changes could, in turn, lead to a loss of revenue and adversely impact our business, operating results, and financial condition.

There’s a lot of uncertainty they’re highlighting:

• Could competitors use AI to build competing products?
• Could AI reduce the need for websites and apps which decreases the need for interfaces?
• Could companies reduce workforces, thus reducing the number of seats they buy?

These are all questions the greater tech industry is asking.

In a dual profile, Ben Blumenrose spotlights Phil Vander Broek—whose startup Dopt was acquired last year by Airtable—and Filip Skrzesinski—who is currently working on Subframe—in the Designer Founders newsletter.

One of the lessons Vander Broek learned was to not interview customers just to validate an idea. Interview them to get the idea first. In other words, discover the pain points:

They ran 60+ interviews in three waves. The first 20 conversations with product and growth leaders surfaced a shared pain point: driving user adoption was painfully hard, and existing tools felt bolted on. The next 20 calls helped shape a potential solution through mockups and prototypes—one engineer was so interested he volunteered for weekly co-design sessions. A final batch of 20 calls confirmed their ideal customer was engineers, not PMs.

As for Skrzesinski, he’s learning that being a startup founder isn’t about building the product—it’s about building a business:

But here’s Filip’s counterintuitive advice: “Don’t start a company because you love designing products. Do it in spite of that.”

“You won't be designing in the traditional sense—you’ll be designing the company’s DNA,” he explains. “It’s the invisible work: how you organize, how you think, how you make decisions. How it feels to work there, to use what you're making, to believe in it.”

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.