Hands-On with iOS and iPadOS 27, macOS 27 Golden Gate, and Siri AI

A return to form and function

Image: Apple.

In 2009, at Apple’s Worldwide Developers Conference, Bertrand Serlet walked onstage and presented an audacious claim: “Zero New Features,” the slide read.

Serlet, Apple’s then-senior vice president of software engineering, was introducing OS X 10.6 Snow Leopard, a release Apple claimed would emphasize small “refinements” and major updates to internal technologies. But to the public, it really was “Zero New Features” — a quote forever cemented in Apple’s modern history as one of its most notable. As Serlet later explained, OS X Snow Leopard had plenty of new features, most notably Grand Central Dispatch, which brought multithreading to OS X for the first time. OS X Snow Leopard established the architecture on which all personal computers, including the iPhone and the Apple Watch, would eventually rely. Its stability solidified Apple’s reputation for reliable, high-quality software, so much so that the coming decade of pervasive, sloppily thought-out user interfaces — beginning with OS X 10.10 Yosemite — was treated as an aberration.

In early June, Apple’s first real announcement at WWDC was neither novel nor revolutionary. It was not a coding agent that would put all white-collar workers out of jobs by 2030, augmented reality glasses, or even as much as a tab bar in the Photos app — it was a slider to adjust the translucency of Liquid Glass. Then came the stunning admission that macOS 26 Tahoe’s window corner radii were too inconsistent and radical: Apple would decrease and equalize all corner radii throughout the system in macOS 27 Golden Gate. Liquid Glass app icons would use new glass layers for a more polished, legible appearance. The central processing unit scheduler — the program that tells the CPU when to execute a process — was made more efficient. The Spotlight index was rewritten, and the Mail app’s search function was markedly improved. These were among the first “features” on which Apple spent the precious opening minutes of one of its most-watched presentations, and it was marvelous.

All of Apple’s releases this year converge on a single philosophy: returning Apple to its original promise of reliable yet innovative software. And much as OS X Snow Leopard — the company’s last true “cleanup year,” with hundreds of bug fixes and underlying performance improvements — became known for transforming personal computing for decades to come, so will iOS 27 and macOS Golden Gate. After a section of the keynote aimed, candidly, at regulators keen to scrutinize Apple’s child safety efforts, Apple introduced what I’d loosely call the Grand Central Dispatch of WWDC 2026: Siri AI, a completely reworked, large language model-powered version of Siri promised two years ago. After years of rumors, personnel changes, and bottlenecks, the “more personalized Siri” is finally here, and it’s both a Herculean reworking of the internals and a breakthrough consumer product.

I have spent over a month with all the new operating systems and Siri AI, and I can confidently report that Apple Intelligence, or at least this new version, has changed the way I use Apple products. It is the first artificial intelligence system that feels personal, like it knows me and is willing to use the decades of information I have stored on my Mac and iPhone. It sheds the gimmickry of current AI systems and, dare I say, makes you feel like you’re living in the future. Apple has proven that the answer to modern computing’s biggest questions comes not via the LLM alone, but via the cowling built around the model. Apple is a product company, and Siri AI is the best LLM product, engineered by people who astutely know what makes a great one. It’s an ice-cold glass of water in the hell of coding agents that will supposedly assume everyone’s jobs by the decade’s end.

But the “Snow Leopard” nature of this year’s operating systems leaves little to write about. There is, of course, Siri AI, coupled with some interesting changes to Liquid Glass, but there are almost no new features in this year’s releases. That’s OK — more than tolerable, in my book. I can ostensibly name dozens of features Apple announced in just a few years that occupied collective hours of keynote time, but hardly anyone uses: StandBy, Image Playground, tinted app icons, the Journal app, and Stage Manager, as pertinent examples. It’s not even that these features are useless, per se, but that they’re just too onerous to find. This was, in fact, the lede of my OS review from two years ago: Apple adds dozens of new, marquee features each year to go undiscovered and unused, while the core parts of the OS languish. Perhaps hundreds of millions of people search for emails in the Mail app, and it has been terrible for years. It isn’t anymore.

This is to say that my relative brevity in this year’s review should not be considered a gripe, but great praise. The adage of “comparison is the thief of joy,” begone — this year’s releases are a perfect replica of what made OS X Snow Leopard one of the most beloved Apple platform releases in history. They’re reliable yet teetering-on-the-edge-of-revolutionary pieces of software, and they’ll undoubtedly change the way millions of people use their devices in the fall. And I think a throwback to 2009 — a mélange between innovation and reliability — is the ideal place to be in a time of grave uncertainty and mistrust in the technology industry.

Siri AI

Siri AI is Apple’s marketing name for this year’s preeminent feature: a generative artificial intelligence-powered version of Siri that can search the web, perform actions in apps through App Intents, and peer into the personal context — a collection of personal data from first- and third-party apps. At its core, Siri AI uses a suite of on-device and cloud models to accomplish these three primary objectives. For more detail on how these models work in tandem, read my initial reactions to the Siri AI announcement from June. An on-device model, called the system orchestrator, chooses which model is best suited for the query and what information it needs, such as the personal context, an App Intent, or a web search. The model then uses the required tools to do the requested work and returns an answer.

This admittedly oversimplified description may be reminiscent of a chatbot, like ChatGPT, Claude, or — especially — Gemini. But over my weeks with Siri AI, I think the product is far closer to an interactive assistant than to a chatbot. Products like ChatGPT have taught us over nearly four years that natural-language input is the future of computation. Older virtual assistants, like the non-AI Siri and Google Assistant, used a limited understanding of human language to provide deterministic, reliable answers. They could neither process language naturally nor generate language of their own; they were instead hand-trained to recognize certain phrases like “What’s the weather tomorrow?” They were handed a predefined set of tools and were essentially told to match certain queries to them. In Siri’s case, the assistant only generated preprogrammed outputs, handwritten by Apple employees for different scenarios.

All of this is to say that those assistants were only useful for a handful of tasks, usually ones performed on-device. Siri — to this day, in non-beta versions of the operating systems — types almost all knowledge-based queries into Bing. It has virtually no knowledge of its own. Chatbots lie on the opposite end of the virtual-assistant spectrum: They claim to hold the world’s knowledge and have such a grasp on it that they can write complex computer programs from scratch or solve problems that have stumped mathematicians for decades. They’re mathematical models of human language, designed to predict the answer to a question nondeterministically. Siri AI lands somewhere in the middle of the spectrum, still unquestionably best suited, like its prior versions, for personal commands, yet with the breadth of knowledge that inherently comes from an LLM foundation. Siri AI merely leverages an LLM to realize the original product’s vision from 2011 — it is unapologetically not a chatbot, despite using the same underlying technology.

I say this for two reasons: the models and the interface. The former is straightforward: The models are nothing like GPT-5.6 Sol from OpenAI or Claude Fable 5 from Anthropic. AI enthusiasts use terms like “big model smell” to refer to the breadth of knowledge these frontier models have, and it’s immediately apparent upon interacting with Siri AI that “big model smell” was never Apple’s intention. Siri AI speaks organically, in short sentences, and uses little formatting. It prefers to quote much of the source material, such as when searching the personal context or the web. The model seldom launches into long reasoning traces and usually generates laconic responses. It’s lightning-fast — almost latency-free, to my delight — in nearly every interaction, choosing to process most queries on-device. Those are not characteristics of frontier-level models, which write with a certain cadence that Siri AI cannot match. Siri AI would clearly struggle to answer first-year calculus problems, let alone discover novel mathematics or write code; it is neither amusing nor particularly useful as a conversational partner.

The latter reason is, broadly, the rest of this section. People can open Siri AI on iOS in four ways: pressing and holding the Side Button to launch voice mode, using the Siri app, swiping down from the center of the Home Screen to open Spotlight, or swiping down from the top center of any app to launch the same Spotlight interface. The point is that Siri AI is available everywhere, including in apps. On macOS, people can use Spotlight or the “Hey Siri” wake word. Spotlight and Siri are not the same; rather, Spotlight leads to Siri. Spotlight works normally without any AI features unless the query no longer matches any results, in which case it offers to send it to Siri. If you prefer to talk to Siri directly, the voice mode bypasses Spotlight entirely, and so does the new, bespoke Siri app, which aggregates Siri conversations across devices through iCloud. Searching for “Siri” in Spotlight launches the Siri app.

Siri AI across modalities.

All of Siri AI’s new modalities use a beautiful semitransparent gradient; the traditional voice mode uses a new glassy orb. When using Siri AI from anywhere but the Siri app, it initially displays a short answer no longer than a paragraph. Manually swiping down on the initial result opens a mini window with a longer answer and, for select queries, web images. You can open the conversation in the Siri app from this window using a button at the top trailing edge. This reveals how Apple envisions Siri AI: It’s for direct answers, not long chats. People don’t even need to interact with the Siri app at all if they don’t want to — the app functions more as a place to recall past conversations than to start new chats. It is, of course, still possible to start chats and voice conversations from the Siri app — because anything else would be unintuitive — but that’s clearly not the app’s primary purpose. The Siri app is not a competitor to ChatGPT and isn’t a place where people will spend significant time.

The Siri AI app in iOS 27.

In practice, I start almost all of my Siri conversations on iOS through voice mode1 — when I’m not in public, at least — and on macOS through Spotlight, just because speaking to a desktop computer seems daft. I scarcely even open the Siri app because it’s quite barebones, at least for now. It is neither as visually appealing nor as useful as the ChatGPT app, and offers only basic file uploads and search. I especially love all of the new animations and sounds when Siri is working: a circle of dots rotates as Siri reasons through an answer, and results drop down gracefully from the Dynamic Island on iOS. Resu

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