As a follow-up to yesterday’s item on how Google’s AI overviews are curtailing traffic to websites by as much as 25%, here is a link to Nielsen Norman Group’s just-published study showing that generative AI is reshaping search.

Kate Moran, Maria Rosala and Josh Brown:

While AI offers compelling shortcuts around tedious research tasks, it isn’t close to completely replacing traditional search. But, even when people are using traditional search, the AI-generated overview that now tops almost all search-results pages steals a significant amount of attention and often shortcuts the need to visit the actual pages.

They write that users have developed a way to search over the years, skipping sponsored results and heading straight for the organic links. Users also haven’t completely broken free of traditional Google Search, now adding chatbots to the mix:

While generative AI does offer enough value to change user behaviors, it has not replaced traditional search entirely. Traditional search and AI chats were often used in tandem to explore the same topic and were sometimes used to fact-check each other.

All our participants engaged in traditional search (using keywords, evaluating results pages, visiting content pages, etc.) multiple times in the study. Nobody relied entirely on genAI’s responses (in chat or in an AI overview) for all their information-seeking needs.

In many ways, I think this is smart. Unless “web search” is happening, I tend double-check ChatGPT and Claude, especially for anything historical and mission-critical. I also like Perplexity for that fact—because it shows me its receipts by giving me sources.

Jessica Davies reports that new publisher data suggests that some sites are getting 25% less traffic from Google than the previous year.

Writing in Digiday:

Organic search referral traffic from Google is declining broadly, with the majority of DCN member sites — spanning both news and entertainment — experiencing traffic losses from Google search between 1% and 25%. Twelve of the respondent companies were news brands, and seven were non-news.

Jason Kint, CEO of DCN, says that this is a “direct consequence of Google AI Overviews.”

I wrote previously about the changing economics of the web here, here, and here.

And related, Eric Mersch writes in a LinkedIn post that Monday.com’s stock fell 23% because co-CEO Roy Mann said, “We are seeing some softness in the market due to Google algorithm,” during their Q2 earnings call and the analysts just kept hammering him and the CFO about how the algo changes might affect customer acquisition.

Analysts continued to press the issue, which caught company management completely off guard. Matthew Bullock from Bank of America Merrill Lynch asked frankly, “And then help us understand, why call this out now? How did the influence of Google SEO disruption change this quarter versus 1Q, for example?” The CEO could only respond, “So look, I think like we said, we optimize in real-time. We just budget daily,” implying that they were not aware of the problem until they saw Q2 results.

This is the first public sign that the shift from Google to AI-powered searches is having an impact.

I enjoyed this interview with Notion’s CEO, Ivan Zhao over at the Decoder podcast, with substitute host, Casey Newton. What I didn’t quite get when I first used Notion was the “LEGO” aspect of it. Their vision is to build business software that is highly malleable and configurable to do all sorts of things. Here’s Zhao:

Well, because it didn’t quite exist with software. If you think about the last 15 years of [software-as-a-service], it’s largely people building vertical point solutions. For each buyer, for each point, that solution sort of makes sense. The way we describe it is that it’s like a hard plastic solution for your problem, but once you have 20 different hard plastic solutions, they sort of don’t fit well together. You cannot tinker with them. As an end user, you have to jump between half a dozen of them each day.

That’s not quite right, and we’re also inspired by the early computing pioneers who in the ‘60s and ‘70s thought that computing should be more LEGO-like rather than like hard plastic. That’s what got me started working on Notion a long time ago, when I was reading a computer science paper back in college.

From a user experience POV, Notion is both simple and exceedingly complicated. Taking notes is easy. Building the system for a workflow, not so much.

In the second half, Newton (gently) presses Zhao on the impact of AI on the workforce and how productivity software like Notion could replace headcount.

Newton: Do you think that AI and Notion will get to a point where executives will hire fewer people, because Notion will do it for them? Or are you more focused on just helping people do their existing jobs?

Zhao: We’re actually putting out a campaign about this, in the coming weeks or months. We want to push out a more amplifying, positive message about what Notion can do for you. So, imagine the billboard we’re putting out. It’s you in the center. Then, with a tool like Notion or other AI tools, you can have AI teammates. Imagine that you and I start a company. We’re two co-founders, we sign up for Notion, and all of a sudden, we’re supplemented by other AI teammates, some taking notes for us, some triaging, some doing research while we’re sleeping.

Zhao dodges the “hire fewer people” part of the question and instead, answers with “amplifying” people or making them more productive.

Yesterday, OpenAI launched GPT-5, their latest and greatest model that replaces the confusing assortment of GPT-4o, o3, o4-mini, etc. with just two options: GPT-5 and GPT-5 pro. The reasoning is built in and the new model is smart enough to know what to think harder, or when a quick answer suffices.

Simon Willison deep dives into GPT-5, exploring its mix of speed and deep reasoning, massive context limits, and competitive pricing. He sees it as a steady, reliable default for everyday work rather than a radical leap forward:

I’ve mainly explored full GPT-5. My verdict: it’s just good at stuff. It doesn’t feel like a dramatic leap ahead from other LLMs but it exudes competence—it rarely messes up, and frequently impresses me. I’ve found it to be a very sensible default for everything that I want to do. At no point have I found myself wanting to re-run a prompt against a different model to try and get a better result.

It's a long technical read but interesting nonetheless.

Jay Hoffman, writing in his excellent The History of the Web website, reflects on Kevin Kelly's 2005 Wired piece that celebrated the explosive growth of blogging—50 million blogs, one created every two seconds—and predicted a future powered by open participation and user-created content. Kelly was right about the power of audiences becoming creators, but he missed the crucial detail: 2005 would mark the peak of that open web participation before everyone moved into centralized platforms.

There are still a lot of blogs, 600 million by some accounts. But they have been supplanted over the years by social media networks. Commerce on the web has consolidated among fewer and fewer sites. Open source continues to be a major backbone to web technologies, but it is underfunded and powered almost entirely by the generosity of its contributors. Open API’s barely exist. Forums and comment sections are finding it harder and harder to beat back the spam. Users still participate in the web each and every day, but it increasingly feels like they do so in spite of the largest web platforms and sites, not because of them.

My blog—this website—is a direct response to the consolidation. This site and its content are owned and operated by me and not stuck behind a login or paywall to be monetized by Meta, Medium, Substack, or Elon Musk. That is the open web.

Hoffman goes on to say, “The web was created for participation, by its nature and by its design. It can’t be bottled up long.” He concludes with:

Independent journalists who create unique and authentic connections with their readers are now possible. Open social protocols that experts truly struggle to understand, is being powered by a community that talks to each other.

The web is just people. Lots of people, connected across global networks. In 2005, it was the audience that made the web. In 2025, it will be the audience again.

For my series on the Design Talent Crisis (see Part I, Part II, and Part III) 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.