Michigan's nuclear comeback, your iPhone's hidden toolbox, a Michael Jackson footnote, the cardio math nobody likes, and cereal as midlife metaphor.

The Map

Michigan may become the first state to bring a retired nuclear plant back online. The Palisades Nuclear Plant, located near the Lake Michigan shoreline in southwest Michigan, is being prepped to operate in 2026.

The global turn away from nuclear power was irrational. There is no more clean and consistent power source. And with Michigan hosting one of the most expensive, unreliable, and slow-to-repair power grids in the country, we could use the juice. I hope the facility comes online next year.

The Machine

Don’t sleep on your iPhone’s accessibility features. There’s plenty of useful customizations in there.

One example: I use the Back Tap feature (Settings → Accessibility → Touch → Back Tap) to reduce screen brightness.1 Three taps on the back and I reduce eyestrain and spousal annoyance when using my phone in the dark.2

Open Settings —> Accessibility, and poke around for things. It’s a hidden toolbox. Take advantage.

(I may do a whole column on Accessibility features at some point.)

The Music

Don’t start with Thriller.3

The Muscle

We need to sweat it out more. A lot more. Today’s exercise guidelines say to get 150 minutes of cardio a week. That’s not enough to make a material difference.

We need 8-9 hours a week for substantive cardiac protections to show up. The problem is that this seems like a ton, and it discourages people, who then do nothing.

Some exercise is better than nothing. Build from where you are.

The Middle

I’ve been eating too much cereal. It’s a crime to leave milk in the bowl, you know. Another round is always warranted. A little weight gain comes with that strategy.

That’s a leak.

Lots of midlife content is about total life reinvention. Practically, midlife change is often small and simple, with big results: fixing our leaks.

Energy leaks, like too much focus on news or scrolling. Food leaks, too much cereal.4

There are so many other leaks: time, needless daily frictions, mood killers, doomscrolling.

Small but important improvements come when we pay attention to where we leak5, and then tighten things up.

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Before I ever watched MTV, I listened to it on the radio.

MTV was once simulcast via stereo, because TV speakers were absolute garbage.

The simulcast was supposed to work only via direct cable connection to your stereo receiver. But if you lived in the right location and balanced the radio dial very carefully at 90.9 FM, you could pull in MTV audio over the air, wafting out from leaky cable infrastructure.

(How did we know this? I have no idea, other than the Word On The Street was uncannily valuable in the pre-internet days. Kids just knew things, like MTV broadcast frequencies and that E.T. Atari cartridges were buried in the desert.)

My grandparents, who lived just on the other side of my block, had a “cable box” before we did. That meant 36 glorious channels, not 12. World-changing.

Amongst those channels was MTV.

The height of video entertainment status, an all-powerful Jerrold Electronics unit, circa early 1980s

We didn't yet have that glorious box at my house when Michael Jackson’s “Thriller” video came out.

But I had a plan. A flight plan.

I would place my bike in driveway launch position2, and listen to MTV on a terrible clock radio that used radioactive materials to light the clock hands at night. The minute “Thriller” came on the radio, I planned to take flight, blasting off to my grandparent’s house to watch.

(I don’t think I cleared this plan with Mission Control3, either.)

I waited, I listened, and I heard lots of 80s music through a speaker with the acoustical characteristics of a Campbell’s Tomato Soup can.

But the timing for launch never worked out. That’s for the best. My Lawrence Welk-loving grandparents would have been mortified by the sight of me roaring into their home and commandeering their television, only to watch zombified Michael cavort around and crotch-grab.

After numerous aborted launch attempts, I eventually saw the video at my friend’s house. “Thriller” was worth the wait.

So is the movie Michael, which grants more access than even the cable box could, taking us through Michael’s youngest days in the Jackson 5 up to the 1988 tour for Bad.

There are so many milestone cultural moments this movie had to hit. And that’s why time sometimes moves faster in this film than in Marty McFly’s DeLorean.

The early Jackson 5 performances. The “Billie Jean” moonwalk at the Motown 25th anniversary celebration. The “Beat It” and “Thriller” videos. The disastrous Pepsi commercial. One after another, the film drops you right back in.4

One huge moment was absent: the making of the “We Are The World” video.

Sure, depicting all those stars would be a casting, licensing, and ego-management nightmare5. But it was a song Jackson co-wrote, and an assembly of stars that only his gravity well could have attracted. It would have been fun to see. That’s one miss, as was Janet’s total absence.

Michael isn’t all familiar and fun memories.

The film overuses the theme of Joe Jackson as a physically abusive father and domineering business manager. And yet, somehow, still underplays the impact. We get hints of the belt whippings. We see Joe push the boys, Michael especially, to exhaustion. But occasional belt whippings and a heavy business hand undersell what the Jackson kids reportedly endured.

Jafaar Jackson, Michael’s nephew and Jermaine’s son, is getting loads of well-earned publicity for his spot-on portrayal of adult Michael. He is Michael in this movie. And Juliano Krue Valdi radiates as the younger, Jackson 5-era Michael as well. Emotionally, physically, and musically, Valdi did a tremendous job. Talent, charisma, heart. That kid kills it.

A question: is Mike Myers federally obligated to play a boisterous record executive in every music biopic?6 Myers does a fine job here in spot duty as CBS Records president Walter Yetnikoff, much as he did as a record exec in Bohemian Rhapsody.7

The “Human Nature” concert scene, depicted during the 1985 Victory Tour with the Jacksons, is magnificent. It’s probably the movie’s strongest musical spectacle, taking us through the song in full. Jaafar’s dancing and likeness is incredible. The scene is similar to this performance, from the Bad tour in Wembley Stadium in 1988:

All these iconic moments, painstakingly recreated … well, that’s mainlined Gen X nostalgia crack.

And that’s why people love this movie. The music, the memories, brought back to life. Michael is idealized in this film, but that positioning gives the viewer an empathetic figure to root for as he completes his hero’s journey to creative freedom and independence.

I think that’s why critics savaged this movie: it wasn’t honest and gritty enough. But gritty was never the goal.

It was strange watching this film, being back now in my hometown, where I first experienced many of these moments. There I was, at the same geographic coordinates I populated in the 1980s, and yet, I live in a completely different universe now than the one onscreen.

That juxtaposition of place and time wove a feeling of melancholy through the fun and nostalgia. The 1980s were a cool time. An era long gone. As the talented Northern Michigan writer often tweets, “The world you grew up in no longer exists.”

Still, it was good to be there in the 80s. And good to be back, just for a little while.

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It can be a formidable foe.

The Promise and The Pain

iTunes Match launched in 2011 as a bridge between “I have MP3s smattered across my hard drive1” and seamless, cloud-based music streaming. It's supposed to scan your files, find matches in Apple's cloud library, and stream those copies instead of yours.

For $25 a year, Apple gave you a clean library of your files you could stream anywhere, without having to worry about what was or wasn’t downloaded.

Today, you can still pay that $25 a year, or pay for an Apple Music subscription and get the same matching service for your own music files.

However.

iTunes Match doesn’t always get it right. Sometimes it’s like the drunk guy at a corporate function who calls you Bob2 even though you’re wearing a name tag.

So you’ll find, sometimes, when adding your own ripped files to Apple Music, that iTunes Match uses the wrong album artwork, splits up an album in two,3 just plain refuses to upload a track, and other joys that will mess up your library.

Let’s run through a couple of common issues.

Album Splitting

If we’re talking about splitting up, then it only makes sense to use a Beatle as the example4. This compilation from Paul McCartney, called Pure McCartney, was ravaged by iTunes Match, splitting it five ways.5

Two moves will solve most album splitting issues.

First, go the Apple Music album view on your Mac. Click through to the first instance of the album get the list of songs. Hit Command + A to highlight all the tracks. Then right click (or hit Command +I) and select Get Info.

Now you’re into the track data, and can commence your role as the Song Sanitation Department.

The two moves that often solve all:

1. Make sure “album artist” is the same for every track. In this case, that meant overwriting “Paul McCartney & Wings” “Paul McCartney & Michael Jackson,” etc. with simply “Paul McCartney.” You can also use “Various Artists” here if you like, but that will move the album out of the artist’s category and into a Various Artists bucket. That categorization is best left to compilations, like movie soundtracks or the Forever 80s compilation which was endlessly pitched on TV in the 90s that I picked up for $2 last year6.

2. Speaking of compilations, that’s your fallback if unifying “Album Artist” doesn’t do the trick. It’s a checkbox. Click it, and iTunes Match says, “Ooooh, there’s a bunch of different artists on the same album. Cool, let me bunch them back together.” Except when it doesn’t, of course.

If that still doesn’t work, you can always try deleting and reuploading the album. And sometimes, well, sometimes no matter what you try technically or which patron saint you pray to, Bon Jovi’s Greatest Hits will simply not unify.

No matter what I tried, “Blaze of Glory” would not join its Bon Jovi brethren on the same album. When I scroll on my Mac, the folly is always there.

Except it did unify on my iPhone.

iTunes Match, ladies and gentlemen!

The Graying

I ran into this problem frequently. I’d rip a CD and upload it. All looked well, until I went to play a certain song through my iPhone instead of my Mac.

Here you see some songs from Eliminator, eliminated by iTunes Match.

Well, my Classic Rock Mix playlist was not going to fly without “Got Me Under Pressure” and “Sharp Dressed Man7”.

It’s fixable.

When The Graying happens to you, and it will, your best bet is to delete the grayed out tracks from your library and re-upload. Other times, the whole album needs to be reset.

Annoying, a little time-consuming if you have a decent-sized library, but not terribly difficult.

Certain tracks have reputations for going gray8, like “Computer Blue” from Prince and The Revolution’s Purple Rain album. Apparently that track appears on a number of different albums and causes iTunes Match to fritz out about its placement.

The only option that worked was to add an underscore to the track title by altering its name inside Apple Music. At that point, Apple Music says “OK, I don’t know what this is, I can’t match it, I’ll just leave it alone.”

So my copy of “Computer Blue” is titled “Computer Blue_”, and sits in its rightful slot, track #4, on Purple Rain.

Other Normie Issues

Those are the most common technical issues most civilians will encounter when uploading their collections.

Other annoyances, like stuck tracks that won’t upload, can often be remedied by going to File > Update Cloud Library to force the upload. Failing that, deleting and re-uploading9 often solves the problem.

But outside the normal civilian existence lurks a population that’s deeply into tagging their music. You can tag at the album or track level in lots of creative ways: era, genre, songs that remind you of sophomore year of college. It’s up to you, and can be a big part of curating your collection.

Most people don't mess with tags. But some people really mess with them.

And iTunes Match can really mess with those people. Horror stories abound of hours and hours of tagging work being nuked by Apple Music.

We won’t get into tagging inside Apple Music today. We might another day, if I venture down that rabbit hole myself.

And we may get into tidying up Listening History at some point.

For now, I have a mostly clean and crisp library of my own files.10 And if you upload your library and have the patience for some simple cleanup afterwards, you will, too.

If you get stuck, I’d be interested to hear about what’s going on in the comments. Let’s see if we can fix it. As long as it’s not “Computer Blue_”.

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It didn’t work out.

And as it turned out, the right solution was sitting there all along: Apple Music.

My Apple Music library was a Frankensteined mess of my own music files (uploaded from CD rips and iTunes purchases) and streaming songs from Apple Music I’d “added to library” over a decade using the service.

Unseemly. Unowned. Unrecoverable.

So I deleted the entire Apple Music library and started over, ripping one CD at a time.

Back to square one1.

The Great Erasing

Deleting your library isn’t hard. On your Mac, go to the songs view in Apple Music. Press Control + A to select all. Right click. Select delete from library.

Poof, done.

Clean slate. Unfortunately, a little too clean.

Mistake #1: Not backing up my data and playlists first

I’m a playlist builder2, with around 30 created over a decade. Some had close to 1,000 songs.

When I deleted my music library, guess what else went away? The playlist content.

Not the playlist shells, though. Oh no. They stayed right there. Signposts to nowhere. Barren, persistent declarations of my haste.

A Yacht Rock playlist with no vessels.

The loss included the Valentine’s playlist I painstakingly assembled for my wife, and wrote an entire post about.

Whoops.

What to do instead: before resetting your library, download Hezel. It backs up your Apple Music library tracks and playlist data, for free.

It takes like five seconds to back up your data. I didn’t.

The rebuild

With files and playlists obliterated, the slow rebuild began. That meant feeding CDs into an external drive, one by one, and using the XLD application for Mac to rip and organize the files.

You can rip right to Apple Music. But I wanted a backup folder first, which I’d then transfer to Apple Music.

I ripped all my CDs in lossless FLAC format, a widely used open standard for music files that is uncompressed, meaning that all the sound data is preserved. Because you’re getting complete data, an individual song can be pretty big in this format, anywhere from 30-50MB or more.3

So, lots of storage space needed, but all good. I had pristine, lossless files to upload to Apple Music.

Except I didn’t.

Mistake #2: File format

Apple Music doesn’t work with FLAC files, open standards be damned.

For lossless audio, Apple Music uses the company’s proprietary lossless format, called Apple Lossless Audio Codec (ALAC).

It takes a long time to rip a decent sized CD collection, slowly feeding disc after disc into the gaping maw of the external drive. I had no interest in starting again.

Claude came to the rescue.

Claude spun up a Python script that I copied and pasted into Terminal in my Mac. It converted all the FLAC files to ALAC. It took a few hours in the background. No sweat.

But lesson learned: for Apple Music, rip your files to ALAC format.4

The Collector’s Library Structure

So I was ready to hand over my files to Apple Music, but not without a strategy for the library going forward.

My library in Apple Music is only for files I own. I don’t click “Add to library” for any track or album that streams from Apple Music. I listen to songs that I don’t own, but never add them to library.

The library is mine. That’s what I mostly listen to. I use Apple Music streaming over the top to fill in some gaps, and for new music discovery through Apple playlists (like Today’s Country) and Apple’s radio stations.

But streaming never gets inside my library. That’s a watertight safe with only my own stuff.

Why do this? Don’t you have a life or something?

Indeed, this is a lot of uploading, curating, and cleanup headaches that are, in this streaming era, entirely unnecessary.

Unless you still want to own your music. To listen and buy with intention, without being mindlessly tossed about in a raging algorithmic river.

After all, what is a music “collection” anyway?

Inside Apple Music, it’s just a collection of data files. If you have CDs on your shelf, that’s just an inefficient storage system. If you’re into vinyl, well, that’s even less efficient.

But a music collection is something more.

It’s a curated archive of memories, audio that delivers a range of emotions and moments from your life, past and present.

A music collection is more than algorithms. To me, anyway.

Next up: Screaming Match

iTunes Match can be massive thorn in the side of music collectors.

It’s an Apple Music service that recognizes5 music you upload. It says, “Hey! I know this song, artist, and album! I have a perfectly good copy right here in the cloud so we’ll use that version for you to stream.”

But iTunes Match gets things wrong. It splits up albums. Seemingly at random, it grays out songs that you then can’t play on your iPhone because … reasons.

You can tame iTunes Match. We’ll get into that next time.

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I’m back working with and 1, who founded Circle Studios, a boutique agency that builds live cohort learning experiences for leading creators and media businesses. Circle Studios is a division of Circle — the company that built the software that hosts over 19,000 online communities2.

If you were part of Write of Passage as a student or Crew member you already know how rewarding this work can be. I loved it as a student, as a mentor, and eventually as Director of Student Success and live session co-pilot. I grew more professionally in those 3+ years than in eleven at my previous job. We did great work together, with a team of dedicated people who brought it to life for students.

Now we're doing that again. And maybe you would like to join us.

I’m building a community of learning professionals: instructors, session co-pilots, producers, and mentors who want to help eager, bright students change their lives and careers.

Sound interesting?

You can learn more and apply right here, right now.

Our most pressing need: an instructor who lives and breathes Claude, teaching a live cohort for one of the top AI entrepreneurs and creators on the internet.3

Much more to come from Circle Studios. I hope you might come along for the ride.

Mine just beeped a lot.

The practice of intentional listening, of (re)building your own music library, sounds fun and self-deterministic. But when you find yourself returning hard drives and rebuilding song libraries again and again, it’s time to see another strategy.

I believe we should own our music and not drift into the Spotify dream of music as barely-noticable background noise.

One way to do this is to rebuild (or blow the dust off of) your CD collection, rip those CDs to digital copies, and store them on a home network-accessable storage system. A NAS, built, curated, and collated by you.

A simple, self-contained music system … right? Right?

The NASty truth

I purchased a home server from Synology and two 4TB Western Digital hard drives. Thanks to AI draining the world of computer memory, it took weeks for the drives to arrive.

With two drives installed in the server, you can create a mirrored situation that gives you an instant backup for all the files you’re storing. If one drive goes down, no worries. The other has all the same files. You can remove the bad drive and swap in a new one. Seamless. Safe. Foolproof.

Yeah, right.

Although seemingly delivered by Wells Fargo wagon, the first drive finally arrived. With Claude’s help, I configured the Synology system and had it running pretty easily. Then began the process of transferring thousands of large music files (FLAC format—lossless and uncompressed) onto the hard drive from my Mac. Claude wrote a script for me to use in Terminal that automated a process that took hours.

With the files transferred, I used Plex software on the server and Plexamp on my iPhone.

Plex, for someone with their own music collection, is pretty great. The UI is beautiful. There are lots of capabilities for intentional listeners who want deep stats about their listening habits and library.1

It was slick. It worked well. The files were mine, on my own system, accessible from anywhere with wifi.

For awhile, anyway.

Further down the space-time continuum, the second drive eventually arrived. I installed in on the server.

Dead on arrival. Apparently, this is a fairly common occurrence for hard drives shipped through the mail2. They can have a delicate constitution.

No worries. I returned it and awaited the replacement.

Then, after less than three weeks of operation, the server started beeping in protest one cold Thursday morning, sounding angrier than R2-D2 in the swamps of Dagobah.

The initial drive had died, too.

So, disappointed and music-less, I awaited the arrival of both replacement drives. I set them up as new. I started the process (again!) of transferring thousands of music files.

More beeps. Something went sideways in the mirroring process. The drives were not broken, but the setup process had to be restarted from scratch.

Cool, cool.

I reset everything from the beginning. I began the file transfer process again.

After several hours, I noticed the file transfer was no longer running. No beeps of protest. The transfer script just chose quiet quitting.

And that’s when I quit, also.

I just wanted to listen to my music

I like to tinker. I liked setting up the hardware and playing around with the Plex software. I did not like being an IT firefighter, battling beeps and bad drives and lazy scripts. I just wanted to listen to my music.

I unplugged the server. I pulled the hard drives. I sent it all back.

And moved on to Plan B.

In 2026, there are simpler ways to both own your music and get to the process of enjoying it.

We’ll cover that in the next post.3

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Playlist Playground

The key to this feature is in how you ask.

Playlist Playground works similar to the emoji playground. You’re asked, in the input bubble, what you want to listen to.

My first try was “1980s hair metal.” The result was decent enough: 25 songs with bands you’d expect (Van Halen, Poison, Quiet Riot, Scorpions, and hairspray abusers from the decade). And not just the most obvious hits, either. The playlist had a Motley Crue deep cut, “Ten Seconds to Love.” Ratt’s “Lay It Down” made the list, rather than “Round and Round.”

I assume it selected songs with bias towards my listening history and favorited songs. The appearance of Judas Priest’s “Loving After Midnight” and The Cult’s “She Sells Sanctuary” are breadcrumbs leading back towards my listening habits.

Overall, a mediocre result. Accurate, but a little short (25 songs seems to be magic number for every list I created). I build deeper and more interesting lists myself, often with hundreds of tracks. If you’re equally deliberate1 with your playlists, you’d do better yourself.

So I tried something else: a situation.

I typed “Peaceful morning coffee” into the magic bubble.

Now the slant towards my preferences is clear: songs from Jackson Browne, Paul Simon, Fleetwood Mac, Norah Jones, and others.

(Also two songs named “Coffee.” A little on the nose, don’t you think, Apple?)

Another underwhelming output. 2

So I tried another approach, writing like I’m prompting an AI chatbot:

“Suggest unplayed songs from artists I like, that would fit a quiet evening sipping wine on the back porch.”

I was served “Evening Serenity: Acoustic Reflections with Wine.”3

The playlist included some familiar tracks, like James Taylor’s “Fire and Rain,” and Bonnie Raitt’s “I Can’t Make You Love Me.” But also some surprises, like Tracy Chapman’s “Baby Can I Hold You.”

There’s some promise there, that this tool can serve as a spur-of-the-moment companion, dashing off a playlist for certain situations. I can see using it again that way.

Lastly, two more quick tests.

First was: “Suggest unplayed songs from the last five years, that would fit a quiet evening sipping wine on the back porch.”

This gave me a playlist of songs I’d never heard of, which can be fun for new discovery when I’m just hanging out.

Second was, “Suggest recent country songs in the style of Chris Stapleton.”

This was a letdown. The playlist was stuffed to the gills with Eric Church and Zac Brown Band. Which are fine enough, but I’m looking for discovery.

In all, Playlist Playground didn’t do much for me, but shows the promise of some future benefit (Apple does tell you the feature is in beta). And the fact you can add your own songs on top of the playlist may offer users some value as a starting point.

In short: You’ll get more interesting results if you describe listening situations, rather than specific musical eras or genres.

New Album and Artist Support

The other new features are interesting in that they help cement how Apple Music’s approach is different from Spotify.

There’s a new look for albums, with your screen taking on the coloring of the album artwork. I like it. The complementary color gives the album added weight and visual prominence.

While this feature can’t replicate a physical vinyl sleeve or CD jewel case, it does make the experience more distinct based on the album. That’s a nice improvement, especially for physical media collectors who use Apple Music as their collection hub.

Lastly, a new concert finding feature is … fine? I’m not sure we need it, but seems to do a decent enough job of finding local shows.

Together, these two features show Apple Music remains committed to supporting albums and artists. Which, on the surface, seems like obvious areas of emphasis for a music app.

But that’s not how Spotify operates.

Spotify wants you listen, but without noticing the artist or music you’re listening to. Turn it on, but be distracted. That way, it’s easier to slip in Spotify’s in-house produced (and royalty-free) tracks.4

Apple Music isn’t perfect. But it has its priorities in better order than the competition and the new features signal those priorities well.

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Between the ages of 12 and 22, the mesolimbic dopamine pathway, the same circuit that processes cocaine and sex, fires at levels in response to sound that it will never reach again for the rest of your life.

A 2025 University of Gothenburg study confirmed it: older listeners collapse into increasingly narrow loops, almost entirely anchored to music from their teens and early twenties.

However, a subset of us weirdos still like to discover new music:

The one variable that predicts whether someone keeps exploring: the personality trait “openness to experience.” Score high, you keep seeking.

I love finding new music. What I don't want is to be fed new music exclusively by an algorithm that prefers cheaply produced in-house songs, or AI-generated filler.

That’s the Spotify model.

So how do we find new stuff we like, in a messy, old-fashioned, mostly analog style?

Here are a few things I do.

SiriusXM

I love this streaming service, and would keep it over any of the absurd number of video streaming services I currently pay for.1

Two Sirius channels in particular help me find new stuff. One is The Spectrum, Channel 28, which is a mix of new songs and recurrent rock from the last 50 years. It is aimed squarely at Gen X, and excels at uncovering modern artists Xers are likely to enjoy. This is where I first heard Noah Kahan and Goose, which I’ve been listening to quite a bit lately:

The other channel is The Highway, Channel 56. They claim to play “Next generation country music,” and that channel has introduced me to Thomas Rhett and Tyler Braden, among others.

Music Forums

There are old heads with good music taste still posting about it on online forums (look it up, youngsters). In particular, the Best New Albums of 2026 thread from the Steve Hoffman Music Forums unearths bands I would never give a shot otherwise, like Blackwater Holylight:

Apparently this genre is called “shoe gaze,” a genre that rocks, but is maybe just a little too depressed or introspective to rock too hard.

Anyway, I like it. I’d have never found these ladies from Portland without that thread.

Long live internet forums.

Other humans

Back in ye olden days, we used to look at each other’s CD collections and find new music to try. Some people still actually “converse” about music and share recommendations. The top person for me doing this is my daughter.2 She’s introduced me to Ty Myers, Conan Grey, and even got me to like The Tortured Poets Department.

The bridge nobody’s building

Nostalgia music accounts on X miss the obvious move. They've already proven they share your taste in classic songs. Why not be the bridge to something new?

But they don’t. I’m sure that’s because they stick to what drives engagement, and that’s posting old songs.

I’m going to keep sharing new stuff I like. Because you might like it, also.

So here’s to finding new music. A messy, unpredictable, process. Make it anything but efficient and algorithmic. Be surprised. That’s part of the adventure the algorithms want to take from you.

Make the music you find yours.

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💿 Zach Bryan, With Heaven on Top

A bit of The Boss1. A dash of Johnny Cash.

Both legends echo through Zach Bryan's latest voluminous (25 tracks) release. It’s like Zach and Morgan Wallen are having a back-and-forth pushup contest, except the reps are tracks released.

The album’s themes are familiar: drinking, regret, love squandered. But there is variety amongst those themes. At times, like on “Skin,” the sentiment is harsh:

I’m takin a blade to my old tattoos

I’m draining the blood between me and you

It’s not all darkness. On “All Good Things Past,” Bryan looks to the future:

Well, all good things pass, but there are better things ahead

Nostalgia has a way of looking better in your head

Some light and optimism pushes through these songs which are introspective and personal, and colored with self-judgement.

There’s criticism that the album represents musical retrenchment for Bryan. Some say the tracks run together, that there’s a lack of big sound or powerful hooks.

But that’s the point.

With Heaven on Top is boldly anti-Spotify2. These tracks belong together, not flung across disparate playlists.3

I listened to With Heaven on Top on a Michigan backroads excursion with my wife. That’s this album’s ideal environment. Amble along with it, take in the mix of light and shadow, and don’t rush the destination.

💿 Leon Bridges, Leon

This album deserved more. More recognition. More conversation. More play. Released in 2024, it came and went, as etherial as the Texas memories Bridges shares from his youth.

Leon reminds me of Marvin Gaye, a strong current of 70s soul running through the tracks. There’s a hint of Latin influence running through some tracks, like “Laredo.”

As Leon looks back, the themes are familiar: first love, cruising the streets. But also some specific memories:

Rock, paper, scissors

‘Cause you know the winner would be the first to play Nintendo 64

I enjoyed “Leon” all the way through4 and have played it numerous times since, his Texas retrospective accompanying the lengthening evenings with a cocktail here in the great white north.

💿 Wang Chung, Points On The Curve

If you want to be transported directly into the 1980s5, Wang Chung’s Points On The Curve is a hell of a transportation vehicle.

It’s rife with 80s staples: lots of synth, comically large drum machine beats and prominent base. “Dance Hall Days'“ is the crown-jewel hit here, and the other tracks, while highly listenable nostalgia-fuel, are missing hooks that got radio play in the early 80s:

Watching this, it’s clear early Wang Chung lacked the cool factor of their British brethren like Duran Duran. And that, in the early MTV era, probably held back a couple more singles from breaking through here. It’s hard for me to believe “Don’t Let Go,” couldn’t have reached a lower rung on Casey Casem’s Countdown.

But I am team Wang Chung. For 80s atmosphere, Points On The Curve is an ideal CD to put on. Let the hair spray fly.

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Just a little later, mixes burned on CDs.

Eventually, kids and mortgages and jobs took precedence, and I stopped making my wife those mixes.

This year, I made the modern version: an Apple playlist called “Matt 💚’s Nik.” It was a compilation of songs with shared meaning from our lives together—nearly 25 years married, 28 together. And I threw in songs from our early youth, when we were friends.

Engagement day, February, 2001.

But now, something funny is happening: I keep adding new songs as I discover them.

Rather than a frozen moment in time, the playlist is a living thing between us. It evolves as we evolve. It can spark new discovery, new conversations, new connection.

The playlist is a bit of fun adhesive as we move through life, and an example of what can happen when we put music’s technology to work for us. Not let it work on us.

Oh — the most recent additions to the playlist? Sure, here are a few:

• Leon Bridges: “They Ain’t Got Nothin On You”

• Buckingham Nicks: “Crying In The Night”

• Goose: “Mr. Action”

• Mumford & Sons: “Run Together”

Harry Also Wants to Rule The World

I am surrounded by three Harry Styles superfans at home. And I admit, he is pretty good1. So when I stumbled across his cover of Tears For Fears’ Everybody Wants To Rule The World,2 I was intrigued.

It’s a good cover.

It lacks a bit of the original’s zip. Or maybe I lack some of the zip I had when I first heard the original in 1985. Such is the predicament of the aged music reviewer.

The two-piece brass accompaniment is a simplifying retort to the very 80s, super-engineered, and percussively3 explosive original track.

In a time where anger screeches all around us, Harry’s polite remake is a respite.

Enjoy.

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You can add music files, play and skip tracks, see album art, even get basic playback stats.

I could use it as my only player, if I wanted to.

I can’t code. But I did build this, with ChatGPT leading the way.

Honestly, I don’t know much more about coding than I did before the project started. But I did learn to think through a user experience—where things go and why, and what to sacrifice to keep things simple.

Prepare for things to change midstream

Because the AI space moves so fast, what worked to build software yesterday might not apply today. For example, I built a ChatGPT project with all the governing documents to guide it. ChatGPT wrote code, piece by piece, that I would paste into Apple’s iOS app building software, Xcode.

That worked ok, but was pretty slow.1

Then, partway through the build, ChatGPT’s Codex suddenly appeared inside Apple’s Xcode application. Apple just slapped it right in there. Now you didn’t have to bring code over from ChatGPT. You could just … do stuff … right inside Xcode.

You have to be flexible, because the AI is advancing so fast. It’s like you take off for a trip in a prop plane, and halfway through the flight jet engines just sprout and start firing.

“One-shotting” is mostly hype

You hear a lot about apps being built in a single pass—”one-shotted”—where the AI takes an initial prompt and builds the software in one swoop.

There was no one-shotting my app, that’s for sure.

I spent hour after hour making small updates, running back to ChatGPT with new errors and issues, and correcting code before moving forward. Sometimes I had to take several2 different runs at one issue to resolve it.

We are not in the microwave era of codeless development. Not even the air fryer era.

Vibecoding is in its convection oven era. You can cook up pretty cool stuff, but it’s going to take awhile.

The biggest lesson: focus on small annoyances

A music app was too big a swing.3 Yes, it works. No, it’s not as good as many existing solutions. It solves no unique problems.

For most of us, “vibecoding” should revolve around small, specific issues or use cases without a solution.

For example, what pisses me off about modern music is what Spotify is taking from people and artists: intentional listening.

The smaller apps I’m working on now fight that head on. They’ll be tools for contemplation, for intentional listening, and intentional discovery.

A smaller slice, taking on a major annoyance. That’s the key.

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The streaming media utopia they sold us—own nothing, access everything—isn't holding up.

Video streaming costs rose nearly 20% last year. While we once paid for unlimited, commercial-free access to movies and TV shows, well, now all the services have ads to accompany our price increases.

And music?

Spotify is being overrun with AI songs, by design, and AI is furiously shoveling them at you to improve profit margins. Albums and artists appear and disappear off the services.

Streaming listeners are losing their relationships with artists:

In the lean-back listening environment that streaming had helped champion, listeners often weren’t even aware of what song or artist they were hearing. As a result, the thinking seemed to be: Why pay full-price royalties if users were only half listening?

Sliding music into the background is more profitable than serving an engaged audience.

The subscription media model has one fatal flaw: they can change the deal whenever they want. And they do.

Against that backdrop, vinyl records have made a comeback. CD1 sales are also up, led surprisingly by Gen Z, who see CDs as both vintage and practical.

I’ve previously written about my own reconnection with CDs. There is something unique about owning the music, having it on the shelf, and listening with intention rather than just for background accompaniment.

CDs were once space-age technology. Today, CDs play nice with digital: one rip and you've got lossless files. Retro meets modern, kinda like this newsletter.2

So I’m going to re-digitize my CD collection into high-quality FLAC music files, and then two hardware and software projects will bring it all to life.

The software project

My next AI project is to build my own music app to play my files. Will it be my forever go-to? Maybe not. Plexamp seems pretty great for streaming your own music. But I want to go though the learning3 process of using AI to build software top-to-bottom, and to think through decisions in UI and look and feel.

That’s something I’ve never done before, and couldn’t without AI.

Could I possibly get this sucker into Apple’s App Store? Let’s find out together.

The hardware project

I’m building a home network-accessible storage solution (NAS) to stream my music files. The NAS will store and back up the files, and the music will always be accessible through my Mac or iPhone.

I’ll write about the hardware and software setup for this as I walk through it, because you might want to follow along.

For me, these projects are less about nostalgia than my desire to tinker and to have control over what I want to own.

(But yeah, also some nostalgia.)

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AI tools bring back that 1980s tech wonder I felt watching Max Headroom on Letterman, or playing a Nintendo game for the first time. It’s that, “Oh, cool, the future is here right now,” kind of feeling.

Of course there’s a lot more at stake with AI than there ever was with Mario. Job displacement, electricity costs, the occasional extinction-event concern … heavier stuff than jumping on mushrooms.

I wanted to better understand what AI could do in my life and work, specifically.

And to show that you can do that, too. Even if you’re not a programmer. Even if you’re 50 years old.

You don’t have to know everything about AI for it to be useful in your work and life. You just have to know what’s possible, and be curious about how to bring it about.

That was the goal. And I built a few useful things along the way.

The Projects

The just-for-fun Michigan Weather site was a lesson in how Claude can help guide me in making things with other tools—in this case, Bolt and GitHub.

The AI Workout Trainer taught me about animations, and the requirement (and frustration) in using a middle man (n8n, here) to get applications talking to each other.

The Talkback Journal removes the friction from getting a quick journal entry down, which should lead to more writing with less hassle.

Patience and diligence go a long way in building your own tools. Some automations probably aren’t worth the time, so think through what you really want to create.

I learned debugging is a trying process, and one that will get easier (or go away) as automated coding tools improve.

Mostly, I learned to stop measuring myself against some imaginary AI power user. The most useful and fun tools to build are weirdly personal in appeal and utility.

There’s always the next frontier

I didn’t spend time on agentic tools like Clawdbot, the Wild West frontier of AI right now. If you read X, you might believe you’re already fossilized if you don’t have ten agents organizing your email and moving your files around.

In reality, it’s early in the agentic AI game, and there are huge security concerns with those programs right now. It’s not time for the non-programmers to jump into agents just yet—the juice is not yet worth the squeeze.

But it won’t be long.

Where do we go from here

AI is on a frenzied progression of growth and competition. Don't let that exhaust you. We don't need to know about and use all of it, no matter what the X tech bros are pushing.

My next project is under way. It’s more ambitious, aligned to my personal interests, and appropriately retro in nature. More on that soon.

We’re in this AI age together, whether we like it or not.

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Quick test platforms

My lesson for today was about test-driving low-cost alternatives to the big three (ChatGPT, Gemini, and Claude).

For this test, I used Poe.com, which lets you jump between models on the free tier, until you reach your chat limit for that model.

There are others. OpenRouter lets you work cheap—if you can get it to set up.1 Hugging Face is another, but there’s a lot going on there. This gives me instant brain freeze:

Don’t get overwhelmed.

You want to test drive a few models, not the entire fleet.

The prompt test

In AI lesson, Claude suggested the prompt, “Write a 200-word newsletter intro about why GenX professionals should care about open source AI models,” which I sent to:

• Claude 4.6 Opus

• GPT-5.2

• Gemini Pro

• DeepSeek V3

• Llama 3.3

All through Poe’s easy-to-use interface.

The results

I wouldn’t use any of the results2 as-is. Lots of Gen X cliches:

• “Using open source is like owning CDs!”

• “Remember when we used to buy software on disk?”

But guess which model got the closest?

DeepSeek, the lowest-cost model among the paid AIs:

But there’s another path: open source AI models. Think of them like the early, independent internet—not owned by any one corporation. For us, the practical upside is twofold.

First, cost. Once set up, these models can run on your own systems, eliminating those growing subscription fees.

Second, independence. You’re not locked into a single company’s ecosystem, rules, or future decisions.

DeepSeek did gloss over something important here. From my understanding, you’re going to need a high-powered computer with lots of expensive RAM to run models locally, save for a few lightweight options.3 And of course, setup on your computer can be a challenge.

The takeaway

The more expensive models didn’t win by default. But without a quick and easy way to test, I’d never have known.

Model testing is easy and valuable. And the landscape is ever-changing, so keep testing from time to time. Have a standard prompt you check every few months, for example. Or use Poe to fact-check AI results across models, as they do tend to hallucinate.4

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RAG means Retrieval Augmented Generation. That means using AI that references your own data, not its training data or other outside sources.

I have journaled for years in Apple Notes. Sometimes, I’d paste a month’s worth of entries into ChatGPT and it to show me patterns in my thinking, Insights I was missing, and opportunities and actions I could have taken

What came back was surprisingly insightful. Journaling is great. A journal that talks back can be even better.

Building a Journaling RAG system

Building a RAG system requires creating a Project and adding your data sources to pull from. In this case, I uploaded journals from prior months (pasted into a Google Doc and downloaded as a PDF) to the Project in ChatGPT.

But I also wanted a frictionless way to get new entries into the Project. Typically when I journal, I don’t sit down and bang out 1000 words. When thoughts hit, I type them out quickly. I may have several entries in a day, or none.

I don’t want feedback on every entry—just when I proactively ask for it (like once a month).

Getting that frictionless input required using what I’d already learned about automations.

The Automation

An Apple Shortcut allows me to tap a button on my home screen, and a dialogue box pops up. I write my entry and hit ok.

The entry is whisked off to n8n, which in turn populates the data on a new row in a Google Sheet.

An easy journaling flow.

But there was so much debugging for a simple setup. Shortcut problems. n8n problems. Tags not sitting in their own column, but shoved into the entry column in Google Sheets. Or no data at all. Or only tags and no journal entry.

It’s a familiar pattern now: cycle through errors, carry the water back and forth, until the app works.

That’s learning to build, not learning to code.

The RAG Journal

With the bugs cleared, the Google Sheet receives the entries and is readable by the GPT. So when I do ask for insights about what I’ve journaled, the GPT has access to the older entries via PDF upload and recent stuff by reading the Google Sheet.

I have a fast and frictionless way to journal, and feedback on demand.

P.S.: An aside about AI selection

Out of curiosity, I ran a month’s worth of entries in Claude and asked it the same feedback question just to see if the response differed.

Claude was harsh.

It lectured me about actions it thought I should have taken (seemingly forgetting it didn’t have complete information about actions I did take).

It’s a good reminder: it pays to test different models. I am good with clear and actionable feedback. But I don’t need an AI version of R. Lee Ermey treating me like it’s day one of bootcamp.

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Today my first-ever automation crossed the finish line. I definitely “hit the wall” halfway through, and needed IV fluids and post-marathon warming blanket at the end. But now, my workout data loop glides from reps and sets logged in Apple Notes through to Claude to feedback in my Gmail.1

Piece of cake!2

Yesterday, I built the shortcut in Apple Shortcuts and set up n8n to receive the workout data. Today, I did the work to send the data to Claude and get the feedback.

A parade of errors

I could write a whole bunch of sentences here that would sound like “I spent an hour trying to fix JSON syntax in HTTP Request node.”

But the point is this: there’s a lot of debugging that has to take place, even with a simple project like this.

And if, like me, you don’t have a programming background, you’ll spend a lot of time carrying water between Claude and whatever other apps you’re using for the project.

Get instructions from Claude, paste into other app, take screenshot of error for Claude. Try again. Over and over.

But there is opportunity in the water carrying. I often asked Claude about why it suggested certain approaches, and asked for clarification when it used overly techy terms.

That’s lots of learning while stumbling around in the dark, with those water buckets sloshing all over.

Over the finish line

Now I have a button on my iPhone screen. I tap it. It grabs my latest workout data. Claude digests it and sends feedback via email.

And that’s pretty damn cool.

The cost

This project wasn’t quite free. I pay $20 for Claude’s Pro tier, and bought some extra usage today to get this over the finish line after I capped out on my daily allotment.

There’s a small ongoing cost to get the data, deliver it, and generate the email: about $.01 in tokens used per session.

Then there’s the time.

I spent over three hours working on this one simple automation. That a lot of time spent to avoid cutting and pasting a workout log from Apple Notes to Claude.

But it’s also my first automation ever. I expect to get better, and for AI to get easier to use. That’s a path we can all be on as we evolve along with these tools.

Try it out

If you've got something annoying and repetitive in your routine, this might be worth the water-carrying. Tell Claude (or another model) what you want to build, and let it walk you through the process. At worst, you’ll learn something.

Up Next: Three projects down—what did I learn?

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When I strength train, I track reps and weights in an Apple Note. Then, I take the data and copy and paste it into a Workout Trainer Project I created in Claude. The project logs the workout and gives me feedback based on the reps, weights, and any notes I left about the workout.1

The Process

I wanted to design an automation that:

1. Could find the Apple Note with my latest workout data

2. Copy and send that data to the Workout Trainer Project in Claude

3. Send back feedback on the workout and any related next steps

I described this to Claude, who came up with a simple plan. Build an Apple Shortcut in iOS to get the data from the Apple note, and then send it off via a webhook on the n8n platform.

(We’ll cover the next leg of the automation, getting the data from n8n to Claude, in the next post.)

Building the Shortcut

I’m not a total stranger to Apple Shortcuts, but I’m light years from experts like Stephen Robles.

If you’re unfamiliar with Apple Shortcuts, it’s a visual automation tool that allows you to link multiple steps across different apps into a single command, creating an automated routine.

Here’s what the Shortcut looks like to grab my workout log from Apple Notes:

Essentially:

1. Find note

2. Get text

3. Show me text in an alert

4. Deliver text via webhook to n8n

5. Notify me that the Shortcut ran

Delivering to the middle man

Shortcuts is the courier. n8n is the processing plant. Apple wouldn’t dream of letting n8n grab the data from my iPhone, so I set it up to wait and receive the info from Shortcuts.

Once there, n8n can take the info and send it on to my Claude Project.

No problem, right?

(Annoying) human issues

I spent nearly an hour with Claude trying to figure out why n8n was saying the execution worked, but there was no test data in the log.

Poor Claude did every bit of troubleshooting imaginable. Just as it was about to resort to a rain dance, I noticed something.

I was reading the bottom entry on the list, assuming it was the most recent. It wasn’t.

If I had simply clicked on the most recent instance, I would have seen the test data coming through bright and shiny:

Well, well.

When I figured this out, Claude laughed with, not at, me.2

Once again the lesson with no-code building rears its head: it’s not the building that’s hard. It’s the debugging, especially with multiple systems in play.

Even in a simple automation like this one.

Try this

You can build something like this, too. Think of a simple repetitive action you’d like to happen without you. Talk to Claude about it. It won’t laugh at you, even if it should.

Up next — Part Two of this automation: Delivering the data to the Claude Workout Project so it can give me feedback.

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I figured I had another 15 minutes or so of cleanup, but then I learned a big lesson:

Refining your app is the longest part of the creation process.

After the build, the next step was to review and list the issues and work with Claude on fixes. Claude wrote new prompts to share in Bolt. Some changes worked right away. Others, like this “logo” stubbornly refused correction.

Often, it took several approaches to get issues to resolve. Fortunately, Claude is inexhaustible.1

The pattern was simple enough: Describe what’s wrong → Claude writes fix prompt → Test → Repeat.

But even when I thought I was done, I wasn’t.

Bolt would not deploy the site with an SSL certificate, meaning browsers would flag the site as unsafe.”2

So, in one last lengthy revision, Claude helped me gather and export the code to GitHub, where the site now lives.

I thought the build would be tough, and adjustments would be easy.

But the opposite proved true. The v1 was simple to stand up, then it was on to review, followed by working with Claude to write revisions.

The revision process is the part triumphant “I built this with no coding!” stories skip. Yes, the AI can write code. But human judgement and refinement are critical, even when building a simple app for yourself.

Here’s the link to the live weather site.

Up next: Building an automation (and if refining a one-page website was work …)

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Back in the late 80s and early 90s, I watched the Weather Channel this time of year just to know that somewhere, out there in a distant land far from Michigan, the skies were not gray, the ground not frozen.

Now, deep in Michigan’s gray season, I recreated the TWC vibe.

Building the app

The first thing I did was find some screenshots of that 90s Weather Channel vibe, which I uploaded to Bolt. I told Claude what I wanted to include and it organized and cleaned up the prompt for me, which I pasted into Bolt.

Bolt wrote the code. Five minutes later, the app was running, using data from the National Weather Service API.

Radar? No problem.

It’s a reasonable first pass compared to the real thing:

All that’s missing is that Yacht Rock-adjecent, light jazz soundtrack. But don’t worry. I have you covered with an Apple Music playlist right here:

This app is a rudimentary example, but it does illustrate that any of us, even without coding expertise, can now create our own online tools with our own vibe. And this ability is getting easier to implement and more powerful all the time.

And I’m not quite done with the weather app.

Next up: I’ll tackle refinements: a wind speed bug, adjusting the fonts, and migrating to a more permanent home.

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1. AI will lie, cheat, and kill to stay alive

2. Jobs are over (again)

3. Phone calls, email, and text channels will be obliterated

Nikita is the head of product at X.

Here’s what they leave out

Item #1

It’s true that in tests, AI did try to take extreme steps to stay online. But not because of an emotional will to live, but because AI is trained on human data. We have a fierce will to live. It’s mimicking our will, and trying to complete an objective (to stay online) using its training data. Which includes tons of stories about deceit, blackmail, and worse.

We haven’t seen this happen in the wild, on its own, yet. And if it’s coming out in testing, where it should, then good. Still time to fix it.

Interesting. A little alarming, yes. But the tweet assumes no one cares. That’s not the case.

Item #2

Kudos to the Financial Times for using careful, measured language:

… most of the tasks accountants, lawyers and other professionals currently undertake will be fully automated by AI within the next 12 to 18 months.

But good heavens, the content on the quote tweets.

And on and on.

There’s a vested interest in hyperbole, of course. And even if the tech is ready in a year, the marketplace (and certainly government agencies) won’t be. The future will arrive unevenly, and will have to fight through the muck of bureaucracy and habit and entrenchment.

Lawyers and accountants will still be here in a year. (But they better be using AI tools.)

Item #3

Nikita’s IQ is probably twice mine1. But the missing piece here is assuming only one side will use AI to scale2—only the scumbags will use bots to overwhelm our most trusted comms channels. Spam is not new. Gmail and iMessage still work, even with annoyances.

But the other side can use AI to scale countermeasures, also. And that side has a vested financial interest in keeping the services we rely on viable.

I remember when spam started running wild. I worked at an ISP. It was a giant pain in the ass. We made changes: IP blacklists, content filtering, rate limiting, spam folders.

The white hats built tools to stem the tide. I bet we will again.

Look for what isn’t said

There’s nothing more interesting—and generating more fear—than AI. As you read these stories, think through how they are positioned, why they are positioned that way, and most importantly, what they don’t say at all.

Huge disruption is coming. Some of it is here now. But we don’t know how fast nor what awaits us on the other side3. And steadiness will be valuable in any outcome.

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