Despite daily use of an iPhone since they first became available—gasp—17 years ago this weekend, I still sometimes find myself flummoxed by some behavior or other. Today, it was this:

On iOS (or iPadOS) in Settings (assuming you’re signed into your iCloud account), you should see Your Name at the top of the screen, along with either your initials in a circle or an image you’ve selected.

Instead, it was “GU”, with the initials-in-a-circle default, but not my initials of “JG”. I tapped my name, and then the GU initials, and the name shown was “Guest User.”

Interesting… iOS doesn’t have a “guest user” mode. And it was happening on two devices signed into the same iCloud account.

Hm.

I struggled to find an answer, so I threw it out to Mastodon, and then in typical fashion, I answered my own question a short while after.

(If the best way to get a right answer is to give a wrong answer, the best way to answer your own question is to ask it.)

I knew the name was taken from the Contacts app, specifically the My Card setting. Sure enough, the Contacts app showed My Card was “Guest User”: first name Guest, last name User, with an otherwise empty Contacts entry. I have no idea how or why that contact card was created, nor why it was selected.

On macOS, I would select the contact I wanted to be My Card, then select Card > Make This My Card from the menu.

I couldn’t find a way to do this in the Contacts app on iOS.

That’s because it’s not in the Contacts app. It’s in Settings, under Contacts > My Info, from where you can then choose your contact card. Of course! iOS apps rarely have preferences within them; they’re usually in the Settings app.

(You can also change this in Settings under Siri & Search > My Information. I don’t know why it’s in two places, other than Siri uses this information.)

The Fix (in summary)

If your iCloud account name in Settings is unexpectedly incorrect, here’s how you fix it:

1. On iOS (or iPadOS), open Contacts and confirm My Card has the wrong name.
2. Optional: If the contact is otherwise empty, delete it: Tap the name, tap Edit, tap Delete (at the bottom).
3. Open Settings, scroll to and tap Contacts > My Info. (Alternatively: Siri & Search > My Information.)
4. Select the correct contact. Create a new one if necessary.

So, there you have it: a minor mystery solved.

I love a good mystery. As a little boy, I read Encyclopedia Brown, the Hardy Boys/Nancy Drew series, all of Agatha Christie’s works, and Sherlock Holmes. Solving mysteries probably goes a long way to explaining why I love computers.

I recently stumbled across a couple of very old books, gifts from my parents in 1985: Alfred Hitchcock’s Daring Detectives, a collection of eleven “Exciting Stories of Great Feats of Detection” featuring Ellery Queen, Dame Agatha’s Hercule Poirot, Perry Mason, and more; and an anthology of five of Agatha Christie’s Miss Marple novels.

You may be able to tell I read the snot out of these.

I also found 12 issues of Stanford University’s facsimiles of The Strand Magazine featuring Sir Arthur Conan Doyle’s “consulting detective.”

The Strand Magazine was a monthly publication which was, among other things, the first to publish the Sherlock Holmes stories. It also serialized The Hound of the Baskervilles in 1901. According to Wikipedia,

Readers lined up outside the magazine’s offices, waiting to get the next installment.

Can you imagine doing that in today’s binge culture? Even weekly episode drops bug me now.

Back in 2006/2007, as part of Stanford’s exploration of the Victorian era, they published these facsimiles and sent them monthly—for free—to anyone who requested them. I couldn’t resist.

They published 24 issues, but I foolishly only signed up for the first half. Fortunately, that half included The Hound of the Baskervilles, serialized and made available monthly just as they were to readers in 1901. I loved waiting for, and then devouring each issue.

They’ve long since discontinued publication, but they’ve kept the website up. You can download all the individual issues as PDFs, though it’s not obvious how to get to all of them, so as a public service, below are the direct download links for each issue.

If you’d like to save yourself two dozen clicks, I’ve compiled them all into a single zip file you can download. I also renamed the PDF files for consistency.

Series 1, 2006

Series 2, 2007

Try reading them one per month for the full experience!

Marques Brownlee (MKBHD) tackles the eternal product marketing question of “Product or Feature” when it comes to AI.

He highlights the Humane Ai Pin and Rabbit R1 as examples of “AI as a product,” that is, a standalone thing you buy that “does AI,” versus being integrated into existing products, such as a phone or smart home device.

Both the Humane Pin and Rabbit R1 require AI for them to be useful. Without AI, they are merely interesting hardware products that provide no meaningful functionality. Everything they do with AI can easily be (and perhaps already is being) done on a phone, either via an app or integrated into the system. The unique hardware bits they have exist solely because they’re not phones and need some mechanism for us to interact with them. A phone without AI is still useful. A Humane Pin without AI is… what? An attractive accessory?

AI is an enabling technology. People aren’t buying AI. They’re buying what AI can do for them. The question for any company selling an “AI product” is “to do what?”

If the what can be incorporated into another, more popular or widely used product, that “AI product” is in danger of being obsoleted, or at least becoming less relevant.

Marques uses the once-popular Clubhouse to highlight this transition. The enabling technology for Clubhouse was “live voice chatrooms”. However, the product was effectively obsoleted after other companies incorporated this feature into their own, more popular apps. People didn’t want Clubhouse, per se. They just wanted to chat with each other.

It’s likely we’ll see this happen a lot more for “AI products.” As Marques points out, Apple’s WWDC Keynote showcased many features powered by AI. In almost every instance, products that do “that thing” already exist today. Such products may soon become superfluous to a large number of Apple’s customers, because customers care about the feature, not the product.

One example: The next versions of iOS and macOS bring the ability to “rewrite, proofread, and summarize text,” directly integrated into just about every text field on the systems. This is huge for Apple customers. But if you’re, say, Grammarly, for whom “AI writing partner” is what you sell, you’re now competing with Apple in your only business. Feature, not product.

This isn’t to say Grammarly goes away. They provide some features not offered in Apple’s version, and as they noted to NPR:

Whenever new entrants come into our market, the reality is that we see increased demand for Grammarly.

OK, sure. But how many people will pay $12/month when they can get a basic “AI writing partner” for free?

As Apple demonstrated, it’s possible to build your own AI stack, and subsume AI-powered features, making them “just another bullet point” on a deck or press release.

Look at ChatGPT, for instance. Despite being the best-known, most popular AI chatbot, it was the last item mentioned in Apple’s two-thousand-word Apple Intelligence press release. And it won’t even be the only chatbot available on Apple’s devices. Eventually you’ll be able to replace ChatGPT with Anthropic’s Claude, Google Gemini, Microsoft Copilot, and who knows what else. Feature, not product.

And dollars to doughnuts, Apple already plans to Sherlock all of these chatbots, as they do with so many other features-pretending-to-be-products.

So is AI a Product or a Feature? Marques demurs:

Now there is no answer yet as far as is AI actually a feature or a product, which one will win, which one will lose, we don't know. But I think if history is any indication, I do think that more people in the long run are going to end up using this AI stuff as a feature, more than going to, like, a standalone thing.

I agree that for most people AI will simply be the technology that powers features they love. They won’t go seeking out AI, and won’t buy standalone “AI products”. In fact, most won’t think about AI at all.

The trajectory technology takes is to transition from a visionary product to an important feature of another product to a mundane feature used without thinking.

A great example comes from my friend Ron Lue-Sang: Biometric authentication.

In popular media, fingerprints, facial recognition, and retina scans once demonstrated just how advanced the civilization (or organization) was. Visionary.

Then biometrics were added to products like door locks as a key reason to buy them. Important.

Today we unthinkingly unlock our phones and computers with our fingers and faces. Mundane.

Companies will continue to sell “AI products” for as long as they can, and many of them will exist as foundational technologies and find ways to differentiate themselves, but most are on a glide path toward irrelevance. For me, and I think for most people, AI is absolutely a feature, not a product, and one we won’t even think of as AI.

So perhaps the question isn’t “is AI a product or a feature?”

Perhaps it’s “when will AI become mundane?”

As an Apple nerd, the week of WWDC is both a great and a terrible time to launch something new. Almost no one will pay attention to this new website, yet it gives me much to write about.

If you’re also an Apple nerd (and if you’re reading this, there’s an above-average chance you are), Apple’s annual Worldwide Developer Conference offers a ton to explore, learn, and generally obsess over. For many, it sets the direction for the rest of their year, acting as something of a launching pad, a new beginning.

For over two decades, WWDC was a major focal point of my year. I worked in Apple’s Worldwide Developer Relations organization (WWDR), which puts on the show, and the team I was on, Developer Technical Support (DTS), was an integral part of it.

Months of long days, sleepless nights, and endless planning meetings culminated with WWDC Monday. It was immensely gratifying to see the results of many months of hard work from the teams make it to the stage or screen. And while much of what was announced at any given show was a surprise to me, my excitement was generally tempered by having already spent a lot of time living on the new software.

Not so this year. It’s my first WWDC “on the outside” since 2001^[1], and my anticipation for what’s new was sky-high.

Restraint

Leading up to WWDC, there was much speculation about what Apple would do with AI, and its impact on the company’s fortunes.

Apple answered, but they sure took their time.

Monday’s Keynote (anchored by Craig Federighi) was effectively two events. The first sixty minutes was the normal annual updates of Apple’s software product lineup: All the new features coming in iOS 18, iPadOS 18, tvOS 18, watchOS 11, macOS Sequoia, and visionOS 2, with a surprisingly long Apple TV+ segment. Despite the hype, there wasn’t a single mention of “AI” or “artificial intelligence” in this first hour.

I must applaud Apple’s restraint here. I speculated last week,

What if Apple announces “Siri AI” and says it’s “Advanced Interactions” or “Apple Intelligence”?

“Edit your photos using your voice. Powered by Siri AI….”

“Xcode 16 helps you write code twice as fast using Siri AI.…”

“In the newly improved Developers Forums, you can quickly find answers to your code-level questions thanks to Siri AI….”

They get to utter “AI” a bunch of times, but make it distinct from “artificial intelligence”.

It would be very Apple to try to redefine what AI means.

🤔

What I expected was a presentation littered with “AI” droppings to satisfy those carping about Apple falling behind in AI. Instead, Apple stuck to their usual language as they highlighted new features enabled by “intelligent capabilities”, “machine learning”, and “powerful new algorithms”, just as they have for years.

It was in the back forty minutes that we finally got what for many people was the main attraction: The introduction of “Apple Intelligence”, Apple’s name^[2] for their on-device, privacy-focused, and deeply integrated take on artificial intelligence.

Apple Intelligence

Tim Cook introduced Apple Intelligence this way:

At Apple, it’s always been our goal to design powerful personal products that enrich people’s lives, by enabling them to do the things that matter most, as simply and easily as possible.

We’ve been using artificial intelligence and machine learning for years to help us further that goal. Recent developments in generative intelligence and large language models offer powerful capabilities that provide the opportunity to take the experience of using Apple products to new heights.

So as we look to build in these incredible new capabilities, we want to ensure that the outcome reflects the principles at the core of our products. It has to be powerful enough to help with the things that matter most to you. It has to be intuitive and easy to use. It has to be deeply integrated into your product experiences. Most importantly, it has to understand you, and be grounded in your personal context, like your routine, your relationships, your communications and more. And of course, it has to be built with privacy from the ground up. Together, all of this goes beyond artificial intelligence. It’s personal intelligence, and it’s the next big step for Apple.

I include the entire quote^[3] because I see this as Apple’s AI thesis. Their privacy-first approach to AI is all about experiences and functionality, not data collection. Technology as Infrastructure, not as a business model. Apple Intelligence gives Apple (and developers) the ability to craft experiences that are relevant to you, using the extraordinarily personal information available on your device, and without compromising your privacy.

This is the right approach. People care about what technology lets them do—or can do for them—not the technology itself. They buy a new iPhone because it “takes better photos” not because it has an “ƒ/1.78 aperture.” The technology enables the feature, but it’s not the feature.

For Apple, it’s not about AI, it’s about what AI enables.

What sets Apple Intelligence apart from other offerings are Siri’s deep integration with the system, on-device processing, and new cloud server infrastructure.

With Siri’s improved integrations, better natural language understanding, and awareness of my personal contexts, my iPhone, iPad, and Mac—which already know more about me than my wife or mom—will be able to use that knowledge even more directly.

It’ll do this without needing to go to the cloud. Much of Apple Intelligence will be processed locally, which is a massive win for both speed and privacy. (It does require devices with the latest Apple silicon: iPhone 15 Pro, or any M-family iPad or Mac. One can presume any new phones announced this year will work.)

For requests too complex to process locally, Apple’s new cloud server infrastructure adds scalability. Private Cloud Compute uses Apple silicon-powered servers created specifically for this task. Limited data is sent to those servers, the data is used only for your requests (not to train models for others), and then the data is deleted once the task is complete.

As Craig said,

You should not have to hand over all the details of your life to be warehoused and analyzed in someone’s AI cloud.

This is what differentiates Apple from everyone else doing AI, and why Apple remains one of the few companies I trust with vast amounts of my personal data. Apple Intelligence is built, as Tim noted, “in a uniquely Apple way.” They aren’t trying to monetize your data, so there’s no need to hold onto it. It’s a solution “only Apple” could make.

Siri

There were several demos showcasing the capabilities of Apple Intelligence. Many were tied to generative writing and images, done locally, and constrained to specific contexts. I found them interesting, but not exciting.

There were three examples which delighted me. All were tied to Siri’s deeper integration into and across the system:

1. You’re filling out a form and it requires your driver’s license. If you have a copy of your license in Photos, Siri will be able to find that photo, copy your license number, and type it into the form for you. I had this exact need just a few days ago. I had to launch Photos, search for “driver’s license”, tap on the text icon, and copy and paste the number. It was quite handy, as I didn’t have to leave the couch to grab my wallet, but I can’t wait until I can say “Siri, paste in my driver’s license number.”
2. A friend sends you a Message with his new address. You say to Siri “add this address to his contact card”. Siri knows what’s on your screen, what an address is, how to get and format an address, what “this” address refers to, what a “contact card” is, who “his” means, what it means to “add to contact card”, and how to add it to the Contacts app.
3. You’re picking your mom up from the airport. You ask Siri “when is my mom’s flight landing?” Siri knows who “my mom” is, what flight she’s on (because of an email she sent earlier), and when it will land (because it can access real-time flight tracking). You follow up with “what’s our lunch plan?” Siri knows “our” means you and your mom, when “lunch” is, that it was discussed in a Message thread, and that it’s today. Finally, you ask “how long will it take us to get there from the airport?”. Siri knows who ”us” is, where “there” is, which airport is being referenced, and real-time traffic conditions.

I’ve been dreaming about these types of interactions since first seeing Apple’s Knowledge Navigator concept video, where—among other futuristic things—an “intelligent agent” has such deep contextual knowledge about a professor, it jumps in—unprompted—with the answer to a forgotten appointment time.

History

The WWDC video opens with Phil Schiller flying an airplane filled with Apple executives^[4]. Craig is pumping them up ahead of the show, then they all parachute out above Apple Park. The airplane, the jumpsuits, and the parachutes themselves are all liveried in the six colors of the classic Apple logo. It’s a lovely callback to Apple’s history.

Ninety minutes later, toward the end of the event, Craig gives us the tag line for Apple Intelligence: AI for the rest of us.

This is another callback to the earliest ads for Macintosh, the computer for the rest of us, and I think it encapsulates everything about how Apple envisions their place within the broader AI ecosystem.

The original series of ads compared the graphical user interface and one-button mouse of Macintosh to DOS-based PCs where you typed in cryptic, text-based commands to get things done. In one ad, a Macintosh is removed from a zippered bag:

It’s more sophisticated, yet less complicated.

It’s more powerful, yet less cumbersome.

It can store vast amounts of yesterday, or tell you what’s in store for tomorrow.

It can draw pictures, or it can draw conclusions.

It’s a personal computer from Apple, and it’s as easy to use as this.

The ad ends with a finger pressing a mouse button, highlighting the simplicity of using a Macintosh.

With new visuals, and some minor changes to the narration, this could be an ad for Apple Intelligence.

It can’t be coincidence that a Keynote that opens by evoking the early days of Apple computing, ends with one too. Apple is saying there’s Artificial Intelligence, which is all about LLMs and models and prompt engineering, and which requires specialized knowledge and lots of typing to accomplish anything, and there’s Apple Intelligence, which uses context and relevance and personal knowledge to make it easy to be creative and productive.

The pundits worry Apple has fallen behind.

Apple is telling us this is just the beginning.

After 22 (and a half!) years at Apple, I’ll be going on an extended, open-ended sabbatical.

That is, I’m retiring.

I’ve spent my entire career at Apple in Developer Technical Support (DTS), part of Worldwide Developer Relations (WWDR). In my time, I've been fortunate enough to be a (small) part of every OS launch, hardware transition, and WWDC since April of 2001.

I’ve helped developers move from Carbon to Cocoa, Objective-C to Swift, PowerPC to Intel to Apple silicon, a “sweet solution” to native development. I’ve helped them ready apps for the introduction of iPhone, iPad, Apple TV, Apple Watch, and now Vision Pro.

I worked closely with App Review from its initial launch, and helped launch and lead the Mac App Review team.

I partnered with Inclusion and Diversity and University Recruiting to help bring focus to the hiring, retention, and growth of female and Black engineers across Apple, and I was honored to be on the leadership team for Women@Apple-Tech for two years, and Co-chair of Black@Apple (formerly African-American Employee Association) for seven years.

All of which is to say:

I’ve had the great good fortune to work with hundreds of the smartest people across Apple in pursuit of things that mattered.

Whether it was addressing an issue affecting thousands of developers; crafting and polishing a talk for WWDC, Grace Hopper or NSBE; or exploring race and gender in the industry, every day I was part of remarkable, thought-provoking, insightful discussions with people from across this amazing company.

Those discussions have educated me, challenged me, comforted me.

Steve said “the journey is the reward”. To all of my colleagues past and present, thank you for being a part of my journey, for making it rewarding beyond measure.

What’s next?

For the first couple of months, I plan to relax and recharge, to “drain my brain”. After that, I’ll be reconnecting to some long-dormant hobbies, including photography, podcasting, and perhaps some writing.

Sometime next year I plan to launch an organization for the next generation of tech leaders of color. The focus will be on building important non-tech skills, facilitating conversations that go beyond pure engineering and technical discussions, and strengthening networks and community. I’m excited to use my experience and skills in different ways, to be a mentor and coach, to open doors, and show a path upward.