2026-03-01 02:20:13
I’m a Six Colors Subscriber who likes to draw pictures of data. As in previous years, Jason Snell kindly asked me if I wanted to try drawing some additional graphs based on the 2025 Report Card. In prior years, I’ve looked at the questionnaire data in ways that a social scientist might, mostly focusing on how the answers cluster together across respondents.
This year, Jason’s discussion of the results here at Six Colors and on Upgrade highlighted not just this or that question but a more general feature of the data: the bad vibes. The vibes around Apple seem worse this year. Naturally, we want to know: what can … (here you should imagine me turning my head dramatically while the camera suddenly zooms in) … science … tell us about these vibes?
Well, if we were just relying on the survey, not that much. But when your panel of fifty or more also write tens of thousands of additional words of commentary, your polite attempts to dissuade them from doing so notwithstanding … Well, maybe that can be grist for our mill. Of science. It’s a science mill, OK? One that can be made to do a little sentiment analysis of the 2025 commentary to see how it compares to the vibes from 2024.
First, let’s just take a quick look at the survey questions. Non-response patterns are always worth looking at. Here’s a chart showing which questions were most likely not to be answered by panelists.
Everyone on the panel, or almost everyone, has an opinion on the Mac, Hardware reliability, and OS Quality. Last year, everyone had an opinion on the iPhone, too. In 2025, even more people than in 2023 had no opinion on the Vision Pro (over 35 percent of respondents). This is plausible, given that no one who doesn’t have a podcast owns a Vision Pro. Twenty of the 57 respondents have no views on Developer Relations, because they are not developers. This is also a consistent divide in the panel. While its membership shifts a little from year to year, it has a constituency of developers who have somewhat different preoccupations from their non-developer co-panelists. There’s also a steady group of people who have little to no interest in Home-related things.
The fact that the panel is not that big presents some appealing possibilities for visualization. Normally, when it comes to data, more is better. But the Report Card panel is, at its core, fifty or so people answering twenty or so questions. You can very nearly take it all in at once. Just not quite. Visualizations can help here. Here’s one of my favorite ways to try to see everything at the same time. The data is just a spreadsheet where the rows are the respondents and the columns are the questions. Each spreadsheet’s cell contains a particular respondent’s score for a particular question. It may be missing, but otherwise, all of them are on the same scale from 1 to 5. Now imagine you have some method for shuffling around the rows and the columns in a systematic way until both the respondents (in the rows) and the questions (in the columns) are as similar as we can make them in each direction. This is a way to see patterns of correspondence between the rows and the columns, i.e., between your cases and your variables.
One of my favorite ways to do this for data of this size is to make a Bertin Plot. Named for the French geographer Jacques Bertin, who developed it in the 1960s, plots like this involve permuting or “seriating” both the rows and columns of your table. They were originally done by hand using a matrix of Lego-like blocks that could be skewered in the rows and columns. Now we can make the computer do it for us. In this case, the result is easier to see if we flip the spreadsheet on its side and put the respondents in the columns and the questions in the rows.
The nice thing about this representation is that by coloring in only the “good” scores (4s and 5s) but still showing the “bad” ones (3s and lower), and keeping the non-responses, we get a very good sense of how both the questions and groups of respondents hang together. The result is that we get an immediate sense of the entire dataset at a glance, and see both which questions and which panelists tend to hang together.
So much for the questionnaire. What about the long-form textual responses? Now, perhaps, like Jason, you dutifully read every word of the complete commentary. But maybe your reaction was, as per the meme, “i ain’t reading all that; i’m happy for you tho; or sorry that happened”. For this bit of the analysis, I took everyone’s full-length responses (which Jason very helpfully labels and categorizes) for both this year and last year. The question at hand is: have the vibes shifted? And if so, how?
You already know the answer. The vibes are, in a word, bad. With about sixty thousand words of increasingly bad vibes to play with, we can do a little text-mining to contrast how panelists felt in 2025 and 2024. First, let’s get some overall sense of the keywords. To do that, we’ll construct TF-DIF scores for every word in the data. Some words appear often in the report card commentary just because they appear often everywhere: “a”, “the,” “really,” etc. Those aren’t very informative at all. Net of those, we want to pick out words that are relatively important compared to words in our corpus of text. TF-IDF downweights words that are common across our text groupings (e.g., if we divide it by year, or question, or both at once) and upweights words that are concentrated in particular groups. Here’s a picture of the most common words across all responses in 2024 as compared to 2025:
This gives us a very rough sense of how the focal topics have shifted from 2024 to 2025. We can do this by question, too, because that’s how Jason organizes the responses. Within the categories, many of the distinctive terms are what one would expect, like “MacBook” under Hardware Reliability or “HomeKit” under Home. We also don’t have to restrict ourselves to single words in an analysis like this. For instance, we can count up the most distinctive two-word phrases, or bigrams. Now, for many of the sub-categories, the most common bigrams are just the ones you’d expect, like “Liquid Glass”, “Mac Mini” or “Apple Watch”. So let’s just look at the open-ended “Anything else to say?” question and the “World Impact” question to get a sense of topical shifts from 2024 to 2025.
Tim Cook dominates both these categories in both years, as one might expect. One thing that’s worth noting is that, because of the timing of the Report Card survey, the Trump Administration was already very much on the minds of panelists when they were answering the 2024 version. By the time they were reflecting on Apple in 2024, it was already early 2025 and not only had the U.S. Presidential election already happened, but Tim Cook had attended Trump’s inauguration, and also personally donated a million dollars to the Trump campaign. Still, the additional shift from 2024’s “carbon neutral” and “environmental impact” to “24k gold” and “bottom line” is notable.
Now, what about people’s feelings around these terms? I used two tools from computational text analysis to characterize the tone and emotional content of the long-form responses. Both work on the same principle: they match individual words in each response against a pre-built dictionary (or “lexicon”) of words that have been scored or tagged by human raters. The results are statistical summaries. They capture broad patterns across many responses rather than close-reading any single one. On a corpus this size—-too big for someone to immediately digest, but in the grand scheme of things really rather small—-they’re not going to do a whole lot better than the sense you’d get from using your own ability to read, one of many remarkable capacities that the lump of watery cholesterol sitting between your ears somehow possesses.
First, the AFINN lexicon is a list of about 2,500 English words, each rated on a scale from -5 (very negative) to +5 (very positive). The ratings were originally compiled by Finn Arup Nielsen. Words like “outstanding” or “love” score positively; words like “terrible” or “hate” score negatively. Most everyday words are not in the list at all and just get skipped. To score the 2024 and 2025 full reports, I find every word in them that appears in the AFINN list and take the average of their scores. A response whose matched words average out to, say, +1.2 is mildly positive in tone; one averaging -0.5 is mildly negative. I then aggregate these scores by topic and compare them between years. Here’s what that looks like:
Again, this method works purely at the word-level. It does not understand sarcasm, or even simple negation (“Not great, Bob”), let alone more sophisticated things like context or irony. A sentence like “I can’t believe how great every new Mac is” will score positively because of “great,” even though “can’t believe” might signal surprise more than straightforward praise. Averaging the scores has its costs, too. Scores near zero can mean either genuinely neutral language or a mix of positive and negative words that just cancel out.
Let’s try a different approach. The NRC lexicon, developed by Saif Mohammad and Peter Turney at the National Research Council of Canada, tags about 14,000 English words with the emotions they tend to be associated with. The system uses eight categories of emotion based on Plutchik’s wheel of emotions. This is a model of general emotional responses, not a game show, relationship experience, or torture device. The emotions are anger, anticipation, disgust, fear, joy, sadness, surprise, and trust. A single word in the NRC lexicon can have more than one tag. “Abandoned,” for instance, is tagged with both fear and sadness.
Like with AFINN, we match every word in the panelists’ long-form responses against the NRC list, count how many times each emotion category appears, and convert those counts to proportions. If 20% of all emotion-tagged words in the 2025 responses are tagged “trust” and 8% are tagged “anger,” that tells us something about the overall emotional texture of the commentary that year. Here’s an overall comparison of the differences in the vibe between 2024 and 2025:
The same caveats apply here as with AFINN: the method is wholly context-free and works at the word-level only. It is better at pinning down vibes from a largeish body of text. Its context-free character can also pollute the analysis in unexpected ways. For example, “trust” and “anticipation” tend to appear as “emotions” in English-language writing about technology, but that is because the relevant vocabulary (words like “support,” “reliable,” “expect,” and “update”) is prevalent in this domain for reasons that often have little to do with the emotion of trust as such. Relative differences between years or topics are probably more informative than absolute proportions. We can see that joy and fear were ahead in 2024, relatively speaking, with anger and disgust being more prominent in 2025 than in 2024, relatively speaking. We can also break this out by topic area. Let’s look at four:
We can see distinct shifts in emotional valence in the categories. In the open-ended “Anything else to say?” prompt, there are notably more joy flips in 2024 than in 2025. Sadness, anger, and disgust flip in the opposite direction, with relatively more of them in 2025 than in 2024. Once again, it’s quite tricky to quantify the scope and meaning of these shifts with tools as crude as these. Breaking things out by category makes it clear that the nature or meaning of one’s anger may be quite different across contexts. Panelists in 2025 are comparatively much more angry about Apple Software than they were in 2024, for example. But this anger might not have the same character as that expressed in the “Anything else to say?” category. Still, crude as our vibesometer is, it does seem to register the shifts Jason was feeling in the responses.
Finally, on Upgrade this past week, Jason wondered if being angry about Apple’s World Impact might cause people to downgrade the company on other dimensions. It’s a good question. There are several more and less complicated ways to assess it, but with data like this, none of them is really decisive. Here is a very simple way to just look at the association between the two.
A low impact score is reasonably strongly associated with lower scores on other questions, on average, but we’re not really in a position to say that it caused people to assign those lower scores.
So there you have it. You had a sense that the vibes were bad; now you know that the numbers maybe kinda confirm it. Pinning down exactly how people feel using only descriptive numerical methods is quite tricky. But that, I suppose, is the nature of vibes.
2026-02-27 06:38:27
It’s almost time for the green flag.
After lengthy rumors, last October Apple announced it had bought the U.S. rights to the Formula One racing circuit. Next week, the races begin, and Apple has now detailed the viewing experience for the season.
First, the basics: Every Apple TV subscriber has access to all the video feeds from live races, practices, and qualifying. There’s no separate package to buy, and all the video will be available within the TV app on all of Apple’s platforms as well as many other smart TVs and connected devices.
According to Apple SVP of Services Eddy Cue, race video will be in 4K HDR with 5.1 audio, and will offer reduced levels of compression that make the image quality of Apple’s other sports broadcasts look better than the competition.
The TV app supports Multiview, which allows for the display of up to four video feeds at one time. To make it easier on users who might be uncomfortable building a custom Multiview layout, the app will be able to build different combinations of multiview with just one click—for example, if you click the Red Bull multiview option, you’ll get a large view of the race feed with smaller onboard views from the two Red Bull cars. (You can also set up custom Multiviews and even edit the ones created by the presets.)
Every session will be presented in both English and Spanish audio, and Apple is using the F1 TV feed as its primary feed—but also offering the very popular Sky Sports video feed as an option, and either feed can be used with Multiview. There are 30 extra feeds, including a race tracker; driver data; “podium channels” that show the video of whichever cars are in first, second, and third place; and all 22 driver cameras.
Users of Apple’s Vision Pro won’t get a 3D race map (yet—though that would be amazing, wouldn’t it?), but they can add a fifth camera view to the multiview for an even more immersive experience.
According to Cue, Apple was inspired to become a Formula One broadcaster after working with the circuit on “F1: The Movie.” “What it really did is it let our teams work together for years, and what I discovered is we shared the same vision, in the sense of being innovative and focused on providing the best fan experience,” he said.
Perhaps the most surprising announcement on Thursday was that Apple and Netflix, which have had a rather stand-offish relationship when it comes to video programming, have struck a deal to swap some Formula One-related content. Formula One’s growing popularity in the United States is due, perhaps in large part, to the high-profile success of the Netflix docuseries “Drive to Survive.” The latest season of that series, debuting Friday, will premiere simultaneously on both Netflix and Apple TV. Presumably, in exchange for that non-exclusive, Apple will also non-exclusively allow Netflix to broadcast the Canadian Grand Prix in May. (Insert obligatory wish that Apple and Netflix would bury the hatchet and enable Watch Now support in the TV app for Netflix content.)
Netflix isn’t Apple’s only F1 content partner. The company said it would be providing free streamer Tuby with “exclusive alt-casts for multiple races.” An alt-cast is an alternative version of the main broadcast, like the Manning Brothers doing a sort of live podcast during a Monday Night Football game or Nickelodeon’s animated take on live NFL broadcasts. It’s unclear what the Tubi alt-cast will actually be, but I love the idea of Apple embracing the alt-cast concept—and using it to find a different audience with a partner.
Since Apple’s rights are limited to the U.S., I assume most of these partnerships will involve races that take place during waking hours, since many races do tend to start in the middle of the night over here. On that note, Apple did emphasize that it’s working hard not to spoil the results of races in the TV app, since many American fans will watch on a time-delayed basis.
Other partners Apple announced Thursday were IMAX (select World Championship races will be shown on IMAX screens in the U.S., again presumably ones taking place during waking hours), Comcast, Everpass, Prime Video, and DirecTV. Some of those may just offer resold versions of Apple TV, and others (like Everpass and DirecTV) will make races available to commercial establishments like bars and restaurants.
On Thursday, both parties pitched their relationship as not being between Apple TV and Formula One, but between Apple and Formula One. Following last year’s Monaco maps tied to the Grand Prix, Apple added fancy Melbourne maps in advance of next week’s race, and I’d expect more fancy racing-focused maps in the future. Apple Music, Fitness, Podcasts, Sports, and even its retail stores will be part of a larger Formula One push. It’s clear that the playbook Apple used to push “F1: The Movie” will continue with this wider relationship, at least in the U.S.
Last November, I got to experience watching a Formula One race with my pal Myke Hurley, who is an avid F1 fan. It was a pretty good time, and I’m looking forward to seeing how Apple’s implementation of all these features works out during next week’s race. It won’t be so fun to watch without Myke, though. Maybe I’ll FaceTime him during the race.
2026-02-26 05:05:11
Over the past several months, I’ve been on a bit of a quest to refine and enhance the essential automations on my Mac. While I’ve relied on a hodgepodge of tools over the years, the primary impetus for this bout of self-improvement was the introduction of automations for Shortcuts in macOS Tahoe—a long-awaited feature that has been around for many years on iOS and whose lack I’ve repeatedly decried during that time.
Many of the tools I previously used were totally fine—good, even—but I am a big believer in using first-party options where possible, both to figure out the extent of their capabilities, as well as to reduce dependence on other tools that might not offer full cross-platform support or might use non-sanctioned methods that could go away. It’s hard enough to get most people to start trying automations, without having to refer them to third-party apps.
One place that I’ve relied on automation over the past several years is in managing my podcasts. Jason and I have, of course, collaborated on a podcast notes workflow, but most of my needs are more mundane. To wit, recording podcasts requires managing a lot of files, and dealing with all of that manually was something I didn’t really want to have to spend time thinking about.
My previous solution relied on Hazel, an excellent Mac automation tool that can watch folders and carry out actions based on what happens in them. Apple itself has long offered a similar capability called Folder Actions, though it’s somewhat hidden these days and requires using AppleScript to at least bridge over to Shortcuts, something that I didn’t want to have to deal with.
So I set out trying to get two of my major podcast file management workflows into automations.
The first task is dealing with the files that I record. I’ve long had a Podcast Sorter shortcut that helps put files into sub-folders, based on the show I’m recording. Initially, this was a shortcut that was triggered by Hazel; later on I adjusted it to be fired off by Audio Hijack’s built-in automation features. The annoyance there was that I maintain different Audio Hijack sessions for each show I regularly record, and that meant having each of them set up to trigger those shortcuts. But Shorcuts’s automation feature allowed me to centralize this functionality. Especially once Apple added the much-needed ignore subfolders criteria.
The shortcut itself is largely the same as the earlier version I linked above, with a few minor refinements from over the years.1 I did run into one thing that I thought was going to be a challenge, but ended up being fine, if surprising: because this automation watches for changes in the In Progress folder where Audio Hijack keeps the files it’s actively recorded, the shortcut is actually triggered right when the recording files first appear. Thus, those files are instantly moved to the correct sub-folder…while the recording is still happening. To my 1980s/90s-trained brain, I thought for sure this would cause some huge corruption errors with the recordings, but apparently modern file systems can handle it without, if you will, missing a beat. Wild, but true. I’ve been using this for weeks now with nary a problem.
The second podcast file management task I had automated was archiving old recordings to my Network Attached Storage. This was previously another Hazel workflow that would watch my local folder of podcast recordings, take any episode folder that was more than two weeks old, compress it into an archive, and move it to the corresponding folder on my NAS.
I figured replacing that with a Shortcuts automation would be relatively simple and it was…with some caveats. First off, instead of using the Hazel technique of watching the folder, I just have this automation run every day at 3am. That’s plenty efficient for me; there’s no need it needs to be alerted as soon as a folder is two weeks old—and in fact, the old Hazel routine timing meant it often started doing the archiving right as I was recording the current episode of the same show. Schedules!
While the shortcut itself is fairly straightforward, the challenges came—surprisingly enough—in terms of dealing with the file system.
My podcast file organization, which the shortcut needs to traverse, is structured like so:
Podcasts/ ├── In Progress ├── Show Folder/ │ ├── Show Name - Date/ │ │ ├── Recording File │ │ ├── Recording File │ │ └── ... │ ├── Show Name - Date/ │ │ ├── Recording File │ │ ├── Recording File │ │ └── ... │ ├── show asset file │ └── ... ├── Show Folder/ │ ├── Show Name - Date/ │ │ ├── Recording File │ │ ├── Recording File │ │ └── ... │ ├── Show Name - Date │ ├── show asset file │ └── ... ├── ... ├── Miscellaneous/ │ ├── Recording - Date/ │ │ ├── Recording File │ │ ├── Recording File │ │ └── ... │ ├── Recording - Date │ └── ... ├── asset file └── asset file
First, there is—amazingly to me—no way to identify a given file as a folder. Let’s say you’re using Shortcuts to iterate through the contents of a folder and you just want to identify each sub-folder. The very powerful Filter Files action lets you add a bunch of criteria, pulling out files with a certain extension, path, date, name, etc. In the olden days, you probably could have filtered by kind2, but “kind” is not a criteria in Shortcuts’s Filter Files action, only file extension. And folders apparently neither have an extension nor are regarded as having no extension.3 Which I believe is a bug, but doesn’t really help me.
In the end, the most reliable method I found of isolating folders was to Filter Files where file size is less than 1KB. It is, of course, not impossible that I would have another file that small there, but it is enough of an edge case that I’m not worried about it.4
My next challenge came from a similar source. Once I identify all the Show Folders, I need to identify the archivable episode folders. Again, I filtered by the 1KB rule to just pull out folders, as well as by the date modified to find the old episodes, buuuuut I ran into another issue. Some of my folders contain Logic or Garage Band projects as show assets (either as templates or for other utility reasons). And guess what? Those are technically packages, which are basically folders…which make them files that are less than 1KB. So I had to specifically filter out files where the file extension was logicx or band. Once again, a problem that could be solved if I was able to just filter out specifically folders.
Now that I’ve identified the files that need to be archived, let’s get to it. First step, compress the folder into an archive. Easy enough, as Shortcuts offers the Make Archive action, but that feature has a quirk. When it creates an archive, it exists…in the ether. Well, not strictly true, but it’s not the same behavior as if you select files or folders in the Finder and choose Compress: there the archive just pops into being, right next to the file you’ve compressed. In Shortcuts, that archive doesn’t stick around unless you subsequently use the Save File action to put it somewhere. Otherwise, it happily makes the archive, and then just tosses it in the dumpster.5
Second point, I had to be sure to give the archive an explicit name. When you compress files in the finder, the archive is by default the same name as the item being compressed, just with a ZIP at the end. Not so when you do it in Shortcuts. (I found this out/remembered the hard way, after I started seeing files on my NAS show up with long and random alphanumeric strings.)
The last challenge was to ensure that the archives were moved to the correct corresponding sub-folder on my NAS. In Hazel, I’d accomplished this via a feature that copies the directory structure and by having my NAS’s archive folder essentially mirror the hierarchy of my Podcasts folder. Shortcuts doesn’t really have a corresponding capability, so I had to come up with my own solution. So, I got the name of the parent directory for the folder being archived (which is the name of the show) and then used the Save File feature’s subpath parameter to specify the folder structure within the Podcasts folder on my NAS.
The original is then deleted from my local machine6, and a notification sent that says the folder has been archived.
To my delight, this has all generally worked pretty well. Most of the technical issues were limitations with what Shortcuts lets you do, but the automation itself has been solid once those bugs were worked out. While it took way too long for macOS to get Shortcuts automation as a feature, the actual results have been great and, as per my above goals, allowed me to rely more on first party tools for most if not all of the automation workflows I’ve relied on.
I’ve also continued to use automation to push forward another repetitive task: keeping track of my finances. But that’s another post altogether, so stay tuned.
2026-02-26 04:51:47
The imminent Apple products we’re most interested in, our weather tech suggestions, how we remember things, and our cities’ transit payment options.
2026-02-26 00:00:00
The Mac mini is gonna be made in Amurica, we talk about our levels of comfort letting AI Jesus take the wheel and some people have snow while others do not.
2026-02-25 05:34:22
Cool Hunting’s Josh Rubin spoke to Apple’s Yuri Imoto and Matt Dessero about building immersive environments for the Apple Vision Pro:
Designing for outer space presents a fundamentally different problem. There is no weather window to wait out, no fog delay, no permit to secure—but there is also limited to no ground truth. The moon environment was built from limited imagery captured during the 1972 landing. And for the Jupiter environment, the team had to construct a plausible world from almost nothing.
I appreciate the idea that these are less photorealistic recreations of the environments than idealized versions. The kind of sheen that your memory puts on something, editing out the things that you weren’t paying attention to. Immersive environments remain one of the best parts of the Vision Pro experience, the only downside being that there aren’t more of them. But from what you can glean from this interview, it’s clear the reason there are so few of them is the amount of attention and detail that they put into making them.
