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iOS and iPadOS 27: The MacStories Review

After years of relentless building, it’s good to see Apple sweat the details again.

In the 11 years I’ve been writing annual iOS and iPadOS reviews every summer, I don’t think I’ve ever struggled to find an “angle” for my story as much as I did this year. The reason was twofold: I wasn’t particularly enamored with Siri AI and Apple’s belated chatbot efforts; and, as I realized during the summer, it can be challenging to write about an OS update that is largely focused on performance improvements and refinements.

“Everyone wants a so-called Snow Leopard year until it actually happens,” I thought to myself on several occasions over the past few months. Think about it: on paper, we all love a good ol’ basket of bug fixes that just make our phones better without changing much about the overall design and experience of iOS. It’s a commendable effort, and there’s no denying that iOS 27 is the snappiest (insert meme here), most stable version of iOS I’ve ever tested – and it has been since the first developer beta. In practice, though, it turns out that considering a major iOS update merely through the lens of improvements and fixes can be…a little boring.

So I’ve been sitting on this review for a while. I let it simmer. Then, a month ago, as I was sunbathing with my girlfriend Silvia down south in beautiful Vieste, Puglia, it hit me: iOS 27 is a geographically ambiguous update. Stay with me here. Depending on where you are in the world, this update can either be a little boring or pretty exciting.

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The iPhone 18 Pro Camera: Apple Reference Image and Tyler Stalman’s Review

In the wake of last week’s Surprise and Shine event, Apple published a post on its Security Research blog about Apple Reference Image, a way to verify that a photograph taken with an iPhone hasn’t been altered. As Apple explains, AI offers helpful features like one-touch removal of distractions from an image, but that can make knowing what is real difficult.

This is not a simple problem to address. Modern cameras rely on sophisticated image-processing algorithms to produce the final viewable image, so certifying that an image accurately reflects what a real camera sensor captured requires a chain of trust covering the sensor as well as the computational photography software that interpreted the capture. Industry approaches to this problem, based on the C2PA standard, attach provenance metadata after capture and certify the history of image edits from that point forward. This approach, however, is vulnerable to compromise at any point in the editing chain, and a viewer has no way to detect such a failure. It can also create privacy risks for photographers working in dangerous conditions by tying the image to a public identity, either to a particular device or to an individual.

Apple’s solution is a:

…new, opt-in camera mode lets a photographer create a securely timestamped reference image that accurately reflects what was captured by the iPhone’s camera sensor. Dedicated secure hardware on the device protects the integrity of this reference image, and Private Cloud Compute protects the privacy of the image data during processing.

The entire post is well worth reading because the solution is both clever and a great showcase of what Apple’s control over its chipset and Private Cloud Compute architecture can achieve for its customers. Apple also supports Google DeepMind’s SynthID watermarking technology.

Also, don’t miss Tyler Stalman’s review of the iPhone 18 Pro and Pro Max on YouTube. Tyler always does a fantastic job with his reviews, and this year’s review doesn’t disappoint, covering features like the camera hardware’s new variable aperture and what this year’s software updates mean for iPhone 18 Pro and Pro Max users.


Chance Miller on the Apple Watch Series 12 and Ultra 4

Apple Watch reviews are out and Chance Miller at 9to5Mac has an excellent, in-depth look at both the Series 12 and Ultra 4. One of the things that Chance points out that might not be immediately obvious to many people is that the inclusion of an always-on chip as part of the S11 system on a chip allows Apple to fill meaningful gaps in both Watches’ data collection:

They will capture your heart rate every five seconds, regardless of whether you’re moving or stationary. Having such frequent and accurate heart rate readings unlocks new levels of data and insight.

When measuring your heart rate once every five minutes while stationary, previous Apple Watch models had an inherent blind spot. They either didn’t capture moments where your heart rate increased while not working out, or they captured one or two arbitrary readings somewhere in the middle of those moments.

That always-on component, combined with the Secure Exclave, is what Apple will also use to keep microphone data private and secure for features like Live Rewind and Siri Recap that are coming later this year.

It was these more frequent heart rate and HRV readings, along with the larger, more accurate sensor on the rear of the Apple Watches, that led me to order an Ultra 4. So I was also glad to see this observation from Chance after his first week with the new Watches:

In my one week with the Apple Watch Series 12 and Apple Watch Ultra 4, I’ve found that added data very insightful. I’m learning more about how little things I do throughout the day impact my heart rate. For example, I can visualize the impact of a late afternoon cup of coffee, or the impact of a stressful moment at work.

That’s the sort of feedback that you can act on and the kind of data that I expect developers will be able to use to make even more meaningful apps across the health and wellness spectrum.

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ChatGPT Is Surprisingly Thorough at Planning Running Routes

Every now and then, I go looking for new running routes to mix things up, which was why I was intrigued by this post by Simon Willison, who gave ChatGPT Work his address and asked it to find 5K and 10K routes, using OpenStreetMap data:

It worked for 27 minutes and produced exactly what I’d asked for, as both an embedded visualization and downloadable GPX file and GeoJSON files. Here’s that 5K route:

I decided to give the same thing a try and was impressed by the results. ChatGPT spent a similar amount of time, poring over OpenStreetMap data, but it didn’t stop there. The model consulted my town’s website to account for road construction and the availability of sidewalks. Then, it visited the county’s website to review maps of greenways that aren’t part of the local road system. The final results were within 100m of exact 5K and 10K routes with notes on where to be careful to verify safe pathways and road crossings.

What I love about this sort of experiment is that it’s not something I’d ever have thought to ask ChatGPT myself. In hindsight, it’s obvious that all the data is there, ready to assemble. However, it just goes to show the many ways that I, and I’m sure many others, are still just scratching the surface of what LLMs make possible.

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Our Favorite Indie Apps for iOS 27, Vol. 1

With our annual OS reviews out of the way, Federico and I will be covering our favorite indie apps that take advantage of Apple’s latest OS features. We have hundreds to draw from and instead of one big sweeping roundup, we’re going to do a bunch of smaller ones as we work our way through our lists.

To start with, we have six excellent apps that make use of Siri AI, Apple Intelligence, extra-large widgets, and more. There’s a lot of innovation packed into this group, so let’s dive into the details, and check back soon for more roundups.

Things

Cultured Code’s beautiful task manager is no stranger to supporting major Apple OS releases: while the company is keeping quiet on their plans for a possible Things 4 (Things 3 was released in May 2017), for the past nine years Things has regularly received support for new versions of iOS, iPadOS, and macOS on day one. The app’s iOS 27 update is no exception, and it makes for a great demo of some of the new features of Siri AI as well as XL widgets for iPhone. It also serves as an example of the limitations of Siri AI – and not because of Cultured Code.

The updated Things app integrates with Siri AI and Spotlight, allowing you to retrieve and open tasks from anywhere on iOS and iPadOS, as well as manage tasks with the assistant using its several input methods. In my tests, Cultured Code’s integration worked well, but Apple’s slow on-device indexing was the problem. Soon after installing the app, I was able to ask Siri to create a reminder, and it prompted me to pick a destination app again because I’d installed a few more task managers since I last confirmed my previous choice. After picking Things, I was able to create a task, which landed in the inbox, and then follow-up with Siri AI by saying “make it due at 3 PM”, and it worked.

The issues I ran into, which are outside of Cultured Code’s control, are due to how long it takes iOS 27 and Siri AI to build an index of the app’s capabilities and data structure. For instance, I created an ‘iOS 27 Review’ list in Things, but, after three hours, Siri AI still can’t find it. As I noted in my review, I believe this is going to be a major challenge for most third-party apps in the short term as users download them, expect them to work with Siri, but the indexing isn’t going quickly enough.

Regardless of Apple’s technical problems, Things’ integration with Siri AI shows the path forward for third-party task managers on iOS. I also recommend reading the developers’ guide on how to prompt Siri AI for the app.

Locally AI

I covered the differences between Apple’s two flavors of local Foundation models (AFM 3 Core and 3 Core Advanced) in yesterday’s review, but there’s no better way to actually take the model for a spin than Locally AI.

The app, which is now part of the LM Studio family of products and can connect to a remote Mac using LM Link, now offers an ‘Apple Foundation Advanced’ model that, assuming you have a compatible device, lets you prompt Apple’s new on-device model.

A good way to prompt this model is to give it an image: for the first time, a local Foundation model comes with vision capabilities, and I’ve found Core Advanced to be surprisingly strong at describing things like iPhone screenshots, selfies with different facial expressions, and more. Obviously, it comes with limits: Locally AI’s harness doesn’t expose tools to the model, which means it can’t fetch web content and, say, summarize articles for you in the app. Its knowledge and creativity are also quite limited, as you can see from the non-joke it created in the screenshot above.

Still, despite the limitations of the model itself, Locally AI is an excellent utility for running local models on iPhone and iPad, and if you’re curious to see what Apple’s bigger models feels like outside of Siri AI with your own prompts, I recommend checking it out.

Dark Noise

Charlie Chapman’s Dark Noise has long been my favorite utility to play white noise and other sound effects to relax or focus, and the app has received a substantial update for iOS 27 worth checking out.

First, there’s a good-looking new Liquid Glass player that fluidly morphs on-screen from a mini-player docked at the bottom of the app into a full-screen view that lets you control playback, volume, and set a sleep timer. On the Home Screen, there’s a (customizable) XL portrait widget for iPhone that lets you configure any combination of up to 24 distinct sounds and mixes that you can play with a single tap without opening the app.

As you can imagine, the app also integrates with Siri AI now. Using Apple’s assistant, you can ask to play specific sounds from the app (make sure to add “…from Dark Noise” to your request) and you can also leverage on-screen awareness inside the app itself. While looking at your list of favorites and mixes, for instance, you can say something like “play the second mix”, and since Chapman has properly annotated the app’s views, Siri AI and Dark Noise will know what you mean.

If you, like me, struggle to get work done with music in the background but also do not appreciate complete silence, I recommend installing Dark Noise and creating a few mixes of your own.

AskPlay

I first covered Francisco Cantu’s AskPlay when it debuted on the Mac earlier this year in the App Radar for Club members, where I wrote:

Created by indie developer Francisco Cantu (a name that should be familiar to longtime MacStories readers!), AskPlay is one of the best new Mac apps I’ve tried in a long time, and we will properly review it on MacStories in the near future. The idea is simple: AskPlay gives you natural language control over Apple Music to play or queue songs. The app, which lives in the menu bar but can also be invoked with a system-wide hotkey, brings up a Spotlight-like floating search box where you can type or say things like, “Queue some ‘90s hip-hop,” or, “Play something like Oasis,” and have an AI carry out the request.

The app can build mixes for a mood or era, start stations, manage the queue (you can ask to move songs up or down), control playback, and add songs to your library or playlists, and it also answers questions such as, “Who sings this?” You can either type your requests or set a voice hotkey that summons the app already listening, pausing your music while you speak. AskPlay is a bring-your-own-key app, so you’ll need an API key from OpenAI, Anthropic, or OpenRouter in addition to an Apple Music subscription (and a subscription to the app itself).

AskPlay is now on iPhone too, and thanks to iOS 27, it’s become one of my favorite showcases of Apple’s Cloud Pro Foundation model running in Private Cloud Compute. Unlike the original version, AskPlay now lets you hand off prompt processing to a reasoning model in the cloud at no cost thanks to Apple’s PCC framework for third-party developers. And not only that, but AskPlay is also the first app I’ve seen that lets you choose between the three reasoning modes supported on PCC: light, moderate, and deep.

In my experience, I’ve had the best results with the PCC model set to “moderate” reasoning. What this means in practice is that with AskPlay for iOS 27, we now have a way to generate Apple Music-based mixes using natural language with a quality that I find superior to Apple Music’s own playlist generation feature.

AskPlay remains one of the best app debuts of the year, and if you want to demo the capabilities of Private Cloud Compute for third-party apps, you should start here.

LookUp 13

LookUp 13 from Vidit Bhargava has been released with a wide variety of features that make use of iOS and iPadOS 27. The app, which is available on the iPhone, iPad, Mac, Apple Watch, and Vision Pro, makes great use of Siri AI, allowing you to quickly ask Siri things like “Search the word plethora in LookUp,” which opens the app right to that word. Siri can also be used to find LookUp’s word of the day or a random word.

LookUp 13.

LookUp 13.

Beyond Siri, Vidit has added support for Apple Intelligence in the notes that can be tied to a word and combined Apple’s Foundation Models with the Vision framework and hand-pose tracking to let you scan a printed page for a word. Point at a word and the app’s scan mode uses your device’s camera to see which word you’re pointing at. It took a little practice to figure out the right distance from the camera to the page, but once I got that down, it felt like magic. The same feature can pick out other nearby words that might be difficult for the reader, too.

LookUp 13 also offers a Reading Mode that looks up words you speak as you read. The feature uses a Live Activity that listens to you speak, and returns a definition. Initially I ran into some trouble with Reading Mode, but when I tried again later, it worked every time. Also included in the latest release are interactive flash cards that ask for word definitions that are graded by Private Cloud Compute and new extra-large widgets for the word of the day and a shuffled word of the day.

LookUp is an excellent app. I love how Vidit continues to push the boundaries of Apple’s technologies every year, and while I hit a few rough spots in testing, which struck me as issues with Siri AI, not LookUp, I’m impressed by how much depth LookUp’s new Apple Intelligence features add to the app.

Play

The latest update to Play, the watch-it-later app from Marcos Tanaka that works on the iPhone, iPad, Mac, Vision Pro, and Apple TV, includes a bunch of great touches. There’s a new Channels Inbox for navigating saved videos by source. Play has also added Siri AI support allowing you to search for and open videos. Onscreen content is made available to Siri, so you can do things like ask it to remind you to finish a video later, and it knows what you mean. In my testing, all three features work well.

Also, on an individual video’s detail view, you can use Apple Intelligence to create a summary of a video. There are options ranging from a concise summary to a simple explanation. I ran into a roadblock when I tried to create a summary of a fifteen-year-old YouTube video, but more recent videos all worked well. Apple Intelligence can also suggest tags and icons for videos and lets you ask questions, with the answers drawn from the video’s transcript.

Beyond Siri AI and Apple Intelligence, Play adds an extra large widget, a refreshed Liquid Glass design that I love, and Spotlight search. It’s a fantastic update to my favorite way to save videos for later.


TestFlight Fixes and Wishes

Just as I was heading into the final stretch of review season, TestFlight was updated to reverse an update I wrote about in July. That update added search, which was one of my longstanding wishes for TestFlight. However, for some users, the update also changed the sorting of betas from reverse chronological order to alphabetical, including active betas alongside expired ones. As someone who reviews a lot of apps, that made TestFlight barely usable.

With the latest update, I’m happy to report that the sorting order has been restored to reverse chronological order. The most recently updated betas appear at the top of the list, and when you want to find something older, search is a great option. Returning to reverse chronological order may seem like a small thing, but it’s made a world of difference in keeping up with the apps I test.

Search was near the top of my list of TestFlight wishes for years, and its addition made a meaningful difference to the app’s usability. But I’ve had a lot of TestFlight wishes over the years that are scattered across multiple articles, so I thought I’d share what else I’d like Apple to tackle with TestFlight:

  • Performance. I test a lot of apps, which slows TestFlight down on every Apple platform. The issue isn’t as severe today as it was when I wrote about it in 2023, but the slowness is still bad enough to make the app hard to use. Whatever the issue is, I’d love to see the list loading time reduced and scrolling through a list of apps become as smooth as it is in the App Store.
  • Add filtering, sorting, and folders. Search is a step in the right direction, but allow me to sort by date, developer, category, and other metadata. I’d also like to be able to filter by installation status, so I can just see the betas I’ve installed or haven’t installed yet. User-defined folders for organization would be a nice bonus too.
  • Hide inactive and expired betas. I’ve thought about TestFlight’s expired betas section a lot and can’t think of a single reason it exists from a tester’s perspective. Let me hide or exclude expired and withdrawn betas.
  • Fix TestFlight emails and automatic updates. TestFlight email notifications can only be turned on or off on a per-beta basis. Adding a global switch would help a lot with managing these messages. Also, automatic updates of betas have never worked on my iPhone, and I’ve talked to others who have the same problem.
  • Restore usable betas after a device migration. Apple’s migration from one device to another has gotten much better over the years, but it still does not migrate TestFlight betas, leaving me with a bunch of broken apps on my iPhone every fall.
  • Indicate when a beta has been released on the App Store. This strikes me as easy to request, though I’m sure is difficult to implement, but I’d love to know when a beta has been superseded by an App Store version, so I can grab the stable release if I want and know I can publish a review about an app without having to check the App Store repeatedly myself.

The bottom line is that while TestFlight is once again usable, it could be much better. I recognize that TestFlight isn’t an app used by most people, but like Apple’s own OS beta testing program, TestFlight betas are an important part of developers’ workflow. They provide QA feedback and a promotional channel that the friction encountered by TestFlight users undermines.

I’m glad TestFlight continues to get meaningful updates. I just hope it gets more attention going forward.


watchOS 27: The MacStories Review

I haven’t been this excited about an Apple Watch in a long time. Last week, Apple introduced the Apple Watch Series 12 and Apple Watch Ultra 4, which will be available at the end of the week. The new Watches feature the S11 chip, which enables a bunch of new features, some of which won’t debut until later this year. At the same time, Apple is dropping support for more Watches than usual.

What we’re witnessing is a reboot of the Apple Watch and watchOS forced by advances in AI. The Apple Watch and its OS found their niche years ago, freeing us from pulling out our iPhones for notifications, tracking our health and fitness, and enabling the occasional Siri request. It was a good and comfortable spot for what by all accounts has been one of the most successful wearables to date, but watchOS also felt stuck in a rut.

Every year we got a few new workout types, a new watch face, and a few other features, but the OS didn’t advance much. What’s different this year is that watchOS 27 is breaking with slower hardware and looking forward to the substantially more powerful S11 chip, which will allow the Apple Watch to expand into all-new areas.

What this transition also means is that there is not just one set of features to track in watchOS 27 this year but three:

  • those that arrive today for anyone with a compatible Apple Watch,
  • those that arrive at the end of the week that are exclusive to the new Apple Watch Series 12 and Ultra 4, and
  • those that are coming later this year.

That makes this more than just a review. It’s also a preview of things to come and a roadmap for where the Apple Watch is heading.

There’s more than usual to cover this year, so let’s dive in and check it out.

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macOS 27: The MacStories Review

Every OS update has a story to tell. With macOS 27 Golden Gate, that story captures a moment when Apple is faced with multiple challenges, many of which are tied to the rise of large language models.

One of those challenges is obvious. Apple was caught off guard by chatbots, overpromised a response at WWDC in 2024, and has been playing catch-up ever since.

But this isn’t simply a story of missteps or wasted opportunities. There’s more to it than that.

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Our OS 27 Review Extras: eBooks, Shortcuts, and the Making of the iOS and iPadOS 27 Review

Today we published not one, but three reviews covering four OSes:

The reviews cover design, new app features and more, which kicks off a big week here at MacStories that includes extra special perks for Club MacStories members. Here’s what we have planned.

For Club MacStories members, we’ve got some exciting perks to help you get more out of the reviews:

  • An eBook edition of Federico’s iOS and iPadOS 27: The MacStories Review that you can download and read on your favorite device or app
  • 20 additional ready-made shortcuts for iOS 27
  • An eBook edition of John’s macOS 27 Golden Gate review
  • An eBook edition of John’s watchOS 27 review.

If you’re not already a member, you can join Club MacStories for $5/month or $50/year using the buttons below:

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