It’s hot. It’s kind of heavy. And on my computing weapon of choice, it’s hard to set up.

But honestly, I love that it exists.

Recently I’ve been taking a look at an eGPU, the Gigabyte Aorus RTX 5060 Ti AI Box, which is essentially a desktop GPU in a relatively small case. I’ve always been really curious about eGPUs, in part because they presumably offer the best of all worlds in many situations. Your laptop stays home with you, but when you want something beastly, you plug an eGPU into your setup, and boom—good graphics.

What makes the AI Box interesting is that it is technically small enough to fit in your laptop bag, while still giving your presumably older laptop a leg up. (As it supports Thunderbolt 5, it also will eventually run faster whenever you get to upgrading the thing.)

The GPU is actually a desktop GPU, though one that got gamer raspberries when it first came out. The Nvidia RTX 5060 was seen as underpowered and lacking in the RAM department when it first came out. The 5060 Ti still got the side-eye from gamers, but the bump up to 16GB of RAM made it more attractive to creatives or … yes, folks messing around with AI on their local machines.

Part of the reason for this comes down to its design. Unlike most GPUs, it is designed for an eight-lane PCIe gen 5 setup, rather than the more common 16-lane approach. (PCIe has gotten really fast, which is why that’s even possible.) And once you remove the myriad number of fans the thing has, the board is actually quite small.

Oddly enough, I think the context is what really matters here. In a desktop for your average Black Myth: Wukong player, it feels a little on the weaker end. But for laptop jockeys who only occasionally load up Steam, it suddenly seems utterly awesome. It is a beacon of miniaturization that someone got a card this powerful to actually in something the size of a traditional Thunderbolt dock.

You could carry this thing into a Panera and people would look at you like you have a giant power brick. (A small miss in this context is the decision to not include a sturdier case; after looking around, I landed on the Koolertron Waterproof DSLR Camera Bag. It fits nicely in a Chrome bag.)

And given the speeds of the laptops where this might end up getting used—my HP Envy has dedicated Intel Arc graphics, but they pale in comparison to this thing—and the value prop shows itself.

Another way the value prop shows itself: At $699, it’s not that much more expensive than a standalone 5060 Ti, and it is more or less self-contained, which you definitely can’t say for a low-end eGPU. (It is more expensive than what the base price of the card was supposed to be, but, y’know, AI.) Most are just cheap adapters that presume that 1) you have a power supply and 2) you’re cool with letting your GPU hang out in the open air. It’s a rare example where you actually get more value from it by setting the upgradeability aside.

(Though maybe not! As noted by a user on the eGPU.io forums, the device itself is just a GPU on a very small PCIe card, plugged into an adapter. So if another card like this ever exists, you might even be able to upgrade it.)

I set this thing up in Linux because I hate myself

I’m not going to sugar-coat it: If you’re buying an eGPU to run on Linux, you’re intentionally asking for a world of pain. Fortunately, as a former Hackintosher, I’m a glutton for punishment, and I was willing to experiment to get the upside.

And the problems this box had—freezes whenever the driver was enabled—reminded me of the most stressful parts of troubleshooting kexts in Clover.

The AI Box’s driver situation hasn’t fully been settled on Linux. But that hasn’t stopped some from trying, particularly developer Andrew Obersnel, who has built a project called nvidia-driver-injector that essentially patches Nvidia’s driver, then runs it in a Docker container.

Even with that starting point, it still wasn’t a cakewalk. Obersnel’s tool was written for the more powerful 5090 AI Box—same family, different requirements. On top of that, I was trying to run it in Bazzite DX, an immutable distro, which meant a more complicated state of affairs for me. (I’m used to it.)

Getting this working is absolute gruntwork, the kind of thing where using an LLM can be a huge help, helping to make sense of admittedly complex debugging schemes. It took a few hours, but eventually I hit paydirt.

Unfortunately for me, the next update to Bazzite hit right after and forced me to rebuild everything. Annoying, but a little more LLM gruntwork got me on track. But let it be known: Linux is not for the faint of heart at this time. Hopefully that changes.

Other operating systems offered differing tales: I ran it in Windows 11, installed the Nvidia drivers, and was immediately off to the races. More intriguingly, this GPU can theoretically run on Apple Silicon thanks to some newly sanctioned drivers from TinyGrad. I actually tested this method on my M1 Air and immediately ran into a brick wall, but if the card was a little older, it would have worked. Oh well, I’ll give it another shot in six months.

Running speed trials all over the place

My planned use case for this thing involves experimenting with local LLMs and giving creative software, particularly Affinity, a little extra horsepower.

I did run a land speed test in LM Studio by having them run the same prompt. Using Qwen 3 VL 4B, a model small enough to fully fit in the laptop’s Intel Arc chip, the difference was fairly stark. The laptop’s dedicated GPU spat out text at about 14 tokens a second; the eGPU did so at 118 tokens/second. It was not even close, and there’s still headroom on this thing to spare.

Newer models impressed as well, including the new Gemma4 12B model (around 35 tokens per second) and a distilled version of Qwen 3.5 trained on DeepSeek 4 (around 60 tokens per second). At least from a speed perspective, these models are quite capable—and after a little optimization I was able to increase those numbers a little further.

Local LLMs do have limits, however, and they’re easy to hit. I proved this with a very Tedium-coded challenge involving one of my favorite indie-rock dynasties: “Share with me a story about how Conor Oberst beat Tim Kasher in a trivia game about the history of Omaha.”

All the tests shared a story, but the details were where everything fell flat. Most, not all, of the LLMs were aware that Oberst was the singer of Bright Eyes, but none got close to figuring out which band Kasher led—one said The Decemberists, another said The National. (The answer, of course, is Cursive, or if you’re a real fan, The Good Life.) You don’t trust models with anything factual, of course, but local LLMs are likely more fact-deprived than their server-rack cousins.

And from a coding perspective, you will have to be careful about how you utilize a tool like this, testing some models to find the right balance. For example, I found that Gemma4 struggled to complete coding-related tasks in Opencode, while the Qwen/DeepSeek combo I tested did fine, even if it wasn’t quite as smart as DeepSeek proper.

(This is way beyond where it was a year ago, though.)

One area where I was pleased with the results of this test was Affinity. I did a fresh install of the tool using the graphical installer, and after a little troubleshooting, I had a very polished app that excelled in Vulkan mode using this GPU plugged in.

And for the nerds, yes, I did try a game or two. The 2016 edition of Doom, probably the closest thing in my library I have to a heavy game, scored 70fps at 4K medium and neared 100fps at 1440p ultra. Not a bad showing.

But it was a fraught one, in part because of Linuxy issues. I had some issues with resizable BAR (Base Address Register) that I needed to work out, and even after I did that, I ran into frequent freezes when attempting to run a DisplayPort cable through the eGPU itself. I don’t think that’s the device. I think it’s a mixture of driver immaturity and user error. It does mean that until I get it fixed, I’m leaving performance on the table until I bite the bullet and go back to Windows 11.

This is not a plug-and-play device on Linux. In fact, it had a tendency to siphon resources from other plugged-in devices to feed its never-ending desire for bandwidth. (At times, it could disable other devices plugged into a Thunderbolt dock, like my keyboard, mouse, and webcam.) But for those willing to put in the work, it is a very capable one.

The eGPU for the rest of us? Not yet, but …

I’m certainly not going to say that the eGPU market is one that I have a deep understanding of, but its potential has always been a bit difficult to grasp for normal consumers because of what it represents. It’s a tool to bring a stationary task to a portable system, a niche that has never truly had its moment, like mini PCs have.

I think a device like this one gets us closer to such a moment. These things do have real downsides from a technical standpoint: Thunderbolt is just not as fast as a PCIe connection, and to get the best graphical performance out of the thing, you need to plug it into an external monitor. Having it run back through your laptop just tanks performance, though it’s still probably faster than anything else in your machine.

The 5060 Ti AI Box is certainly not the first “breakaway box” that attempts to bring a more portable form of this model to computers. But it is a relatively rare beast—a desktop GPU in a box that is smaller than a standard desktop GPU card. Plus, most prior attempts have been AMD graphics. AMD is fine, but the company is behind from a machine-learning standpoint, even with its recent improvements to its ROCm computation stack. (Side note: I think Intel should consider offering an eGPU, or at least push its vendors to offer one, as its Arc cards are fairly price-competitive at this time and would likely play nicer with Linux.)

There’s a possibility that eGPUs could eventually become a bridge device as laptops become more GPU-forward. That phenomenon already happened in the Mac ecosystem and could happen with PCs, based on Nvidia’s recent moves into ARM laptops. Those chips are powerful, with 5070-class GPUs and lots of RAM. But they’re not going to reach normal people for quite a while, thanks in part to their workstation-class positioning.

Unless Nvidia taps into its war chest like Apple has, these are likely going to be mid-four-figure computers. Even enthusiasts might find themselves passing, at least at first.

In that light, an eGPU that can be plugged into a Thunderbolt port and can offer something approaching that experience to a class of people with normie laptops feels like an excellent compromise. That’s especially true if LLMs become more fundamental to how we do work.

When I got this thing, I didn’t think the portability would be such an important part of why I like it so much, but it’s honestly the main feature. I hope we see a dozen models like it.

And I hope we see some real work on making them first-class Linux citizens.

Two companies that have enabled literal decades of creativity have both landed on the same question around the same time: Who owns a vibe?

One makes $5,000 guitars. The other makes software that they’d charge $5,000 a year for if they could. And creatives, as ever, are caught in the middle.

First up, we have Fender, the originators of one of the most important guitar designs of the past century, the Stratocaster. It’s been around so long that it’s basically generic at this point, often the starting point of many a luthier. But Fender disagrees on this point, with a single default judgment in a German court giving them just enough cover to call out their competitors, many of whom have been making Strat-like guitars for decades.

Surprisingly close to the center of this controversy, somehow, is John Mayer. See, a bit over a decade ago, Mayer wanted to make improvements to his Strat under his signature guitar deal with Fender. But Fender’s corporate culture was in the middle of a big shift, and the people in charge weren’t receptive to his ideas. So he jumped ship to PRS Guitars, whose founder, Paul Reed Smith, is still at the helm. Mayer found a close collaborator, and the two saw an opportunity to improve on a de facto industry standard, tweaking a solid guitar to make it even better for hardcore players.

They were small things—wider frets, a deeper slope to make it easier to hit those high notes—but they added up to be a better guitar that superseded its signature-guitar status.

John Mayer, showing off his Strat-like signature guitar, which is more popular than your average signature guitar.

The PRS Silver Sky, as it came to be called, got a lot of online mockery for looking kind of like a Strat. But the guitar quickly outpaced its surface details and became more popular than the Strat among serious guitarists.

Enter Fender, which recently sent PRS a legal complaint. They weren’t the only ones, but Fender was clearly looking for some way to protect its design, which has been around for about as long as Paul Reed Smith, a 71-year-old man, has been alive. Backlash has been swift—with many musicians siding with smaller manufacturers, reflecting a widespread belief that the Strat design is generic.

Meanwhile, a completely different push for ownership emerged this week on Capitol Hill. The company? Adobe, a clear favorite around these parts.

But this is worth paying attention to. Essentially, Adobe is attempting to put its might behind something called the CREATOR Act, which aims to give artists ownership over their distinct visual style, something at risk in the age of AI.

“If passed, this common-sense, bipartisan measure would address a gap in our intellectual property laws by protecting creators against style impersonation, and Adobe is proud to support it,” wrote Louise Pentland, the company’s chief legal officer and executive vice president of legal and government relations.

Broken down, Adobe is essentially pushing for something very similar to what Fender is—the right to protect a style, but in a very different medium. One is resolutely analog; the other is as digital as you can get. While the bill seems narrowly tailored based on a cursory read, the protecting-artists mess feels like it’s testing fate.

What do I mean by that? Well, going back to music, modern artists have found themselves navigating complex legal battles over songs that borrow a portion of a melody or even a general vibe. The infamous “Blurred Lines” case, in which the estate of Marvin Gaye sued over Robin Thicke, T.I., and Pharrell copying the general style (rather than the specific melody) of “Got to Give it Up.” That case has created all sorts of ugly precedent in the years since, and much of it is being driven not by the artists, but their estates.

This bill is literally asking to bring that mess to visual art, a situation in which interpretation is often even more abstract than with music. Admittedly, the bill has distinct limits—it has to be made clear whether, by AI or by a human creator, that the intent was to specifically rip off another person’s art. It carves out stuff that would already be protected under fair use, like using a work in a news story.

And as anyone might have noticed when OpenAI kicked off a Studio Ghibli meme last year, there would be clear cases where this might happen. At least from an AI standpoint, it’s timely.

But most art lives in an uncanny valley of indirect inspiration—where perhaps you saw something, and it inspired you to make something of your own. The gap between whether something is directly inspired or indirectly inspired is wide, and all matter of deeply messy legal battles could fill it.

One presumes the reason Adobe is the one pushing for this is because they see a potential business in licensing specific styles to AI platforms and Creative Cloud users, though the company does not explicitly state this. (Its Firefly product does something similar with stock photos.)

If this law passes, it wouldn’t be surprising if some big company started skulking around, looking for the next target to hit. (Given that this law would apply for up to five decades after the artist’s death, it might even apply to their estate.) You think this is hyperbole, but this is already what’s happening with music, where modern musicians preemptively make other artists songwriters on the off chance it sounds too similar.

Inspiration springs eternal, but one wonders if this attempt to protect creativity is just going to lead to a company resting on its laurels to try to smother the next generation of creatives.

Yes, we’re in a climate of constant slop, but a climate of constant lawsuits would probably be worse.

One basic-ass site against Google’s overwhelming prowess

To start off, I want to make a bit of a separation here. Google does a lot of good things. It also does a lot of bad things, especially in the realm of advertising.

I don’t think it’s fair to compare the badness of different companies on a scale—bad is bad, after all—but Google’s brand of evil is largely built from neglect for the genuinely good things it’s built.

You could see some of this at Google I/O, the company’s developer conference, last week. Google Beam, its attempt to make video conference calls more lifelike, continues to evolve in exciting ways, for example. And the Googlebook, the company’s evolution of ChromeOS and Android, feels like it’s coming along at a good time, given that everyone suddenly hates Windows.

But the thing is, how much of this did customers actually ask for? Google I/O seemed to be stuffed with things intended to sell a specific vision of how Google sees itself fitting into your life, rather than creating things that seem to demand it.

It’s not enough that Google is on your phone, on your wrist, or in your web browser. It must continually deepen that relationship in new ways or threaten its long-term relevance for good.

Which brings us the AI overviews discussion. It’s so weird. Two years ago, a Google I/O event added a feature that I could not ignore, so I spent 20 minutes looking for a way to ignore it. Then I found an obscure URL code and created a website that told everyone about it. Within hours, &udm=14 became a meme.

That website took off in a big way because, let’s face it, we’ve decided that we need to have a say in how intrusive Google’s features get.

Even in the world of AI, Google does interesting things (the Gemma 4 open-weight models are quite good), but the problem is that the company is approaching the technology from a defensive stance. Love ’em or hate ’em, people choose to use ChatGPT and Claude. Google’s structural advantage is that it’s already deeply embedded in your life, so its play has to be that it can integrate the thing that might give them value in a way that forces you to take notice.

On top of the AI overviews, there have been other visible signs of this kind of annoyance kibble throughout their product lines. At one point, Google put its Gemini icon in the Gmail app in the very place its account switcher button used to be, ensuring users would hit the button constantly.

More recently, Google put a giant button on the bottom of Google Docs by default, though it thankfully made it easy to turn that off.

That is Google’s modus operandi, and it has been for years, dating back to the days of Google+. (Remember, there was a time that Google just shoved everyone’s emails and search data into a social network. In fact, it was the second time in 18 months. This is not a new game for them.)

But just imagine if the company had decided it would just let the tech earn its place, not unlike the way Gmail or Google Photos did. The conversation would be way different. It would feel like we’re in conversation with it, rather than getting pulled down the road, kicking and screaming, ready to fight back if it gets too intrusive.

In so many ways, large companies like Google and Meta treat their mandates as if they can change the script constantly and we’ll just stick around. Users deserve more say in that discussion—and by working around forced features, that’s how they get it.

I spent two hours of my life building a thing. Google has probably spent thousands, if not millions, of collective employee hours building all their AI innovations. And for a surprisingly large number of people, the two-hour workaround I built wins out. There’s a lesson in that.

The single-serving site doesn’t get the due it deserves

I will admit that I did have one other inspiration point for my &udm=14 idea. And it’s extremely far away from the everything site that is Google.

Around 2011 or so, I had a successful long-haul Tumblr that got a bit of traffic. But one day, a coworker of mine briefly outpaced it with his own viral single-serving Tumblr. Months later, it happened again, when my pal Stacy Lambe, a fellow Tumblr user who I hung out with often, helped put together Texts From Hillary, one of the most viral websites I’ve ever seen.

My thing, ShortFormBlog, was built around depth and designed to get people coming back on the daily. But it couldn’t compete with humorous pics of safari animals. Different lane, but still a useful lesson.

Later, I became familiar with another category of single-serving site: The site that does one thing extremely well. My favorite example of this is Kay Savetz’s FaxToy, a website that does nothing but print faxes sent to a specific number. I talked to Savetz about it back in 2017 for a piece on unusual phone numbers, and I think in many ways, it stuck in my head. It was a genuinely clever idea that, beyond being absurd and funny, actually does something. If you want to ensure your fax machine is working, send a weird image to FaxToy.

Yes, it’s single serving, but it’s sticky, fitting into the category of “small tool.” That’s a bit of a rare beast online, and I often find myself relying on sites like these on the regular. I don’t send many faxes, but I do have plenty of single-serving sites I do rely on regularly. For one, Compressor.io, which does nothing but compress big images to smaller ones. I’ve compressed hundreds of GIFs using this method.

It’s no Texts From Hillary, but &udm=14 is an excellent small tool. It does two very specific things: First, it tells you about the &udm=14 hack, and second, it makes it easy to use it yourself, even if you’re a luddite.

There’s no reason other people can’t make their own, and in fact, I would encourage it. If vibe coding is a thing people just do now, why not vibe-code a simple solution to a common problem?

A tool that just does one thing and is in a specific place still has power. And it could be something you made. So if you’re holding onto something good, try making it. You might be surprised.

If we stand a chance against big tech, we need to think smaller

I don’t think I’ve necessarily hidden the fact that I’m “in the middle” about this whole AI thing. I’m not Ed Zitron, nor am I the YouTube-centric AI company whisperer Theo Browne.

I’m just a nerd who got into writing via emulation, who writes a lot about processor architectures like PowerPC and the Transmeta Crusoe. I once bought a 386 off of eBay because it was the exact model I used when I was 12. And when I was nine, I spent hours shoving random Game Genie codes into Super Mario 3 to see if I could find any codes that weren‘t in the book.

Basically, I’m the perfect target audience for interesting AI stuff. And even then, I’m just like, “Don’t hand it to me unless I ask for it.”

I’ve described a “bionic arm” philosophy for navigating the use of it ethically. I recently pitched the idea of moving away from the bigger providers and using DeepSeek (which remains an insanely cheap option).

If I’m looking for that kind of tool in my utility belt, I’m not by default opposed to accessing it, as long as I understand what I’m giving up by using it, and it doesn’t cross my personal lines. I know many people have far stricter standards than I do, as is their right, however.

When a modern technology, including but not limited to AI, becomes a decorative bird, it loses its novelty. No matter how good it is.

But what I am opposed to is what I might call “decorative bird AI,” of which Google’s AI overviews are the classic example. Part of the reason Google’s AI overviews are so rough is pretty obvious when you break it down. Google put a complex technology on top of the most widely used form on the entire internet. They can’t put an expensive model on that. Even though they own the entire infrastructure soup to nuts, it would cost too much! So instead, they put a more basic model on top of it, and the company gets embarrassed constantly.

It’s not just about Google, though. Lots of companies do this, and it more often than not just makes things worse for them, as they add features on top of features on top of features. They don’t do this because anyone is specifically asking for these features, but because this is what they’ve been told is an exploitable market.

One example I often think back to is Dropbox. In the midst of the Apple Silicon move, which came with significant architectural changes that Dropbox users could have benefited from, the company was constantly launching new productivity features, rather than updating their app for the new architecture. Five years later, the company’s CEO is leaving, after years of sagging values.

Too much tech is just put out there because an investor told a CEO that it was essential to include to keep up. Doesn’t matter that the audience didn’t ask for it, that there wasn’t market research suggesting that it was necessary. We need to have an answer to the other guy’s use of AI, so it’s there.

All the motivations are set against us. And while some companies have actively avoided going down the road of overzealous AI infusion, like the Vivaldi browser, the truth is that there’s a structural motivation behind all this.

If we no longer want to be at the mercy of companies that poorly dominate every part of our life, we must embrace the idea of companies that do one thing well.

Way back in the Tedium archive sits a tale about why umbrellas are so hard to redesign. They’re single-use devices that do one thing well, and every attempt we’ve made to improve them has never quite lived up to the ambition. I hate single-use devices, particularly clunky ones, until the moment I need them. And well, once that moment arrives, an umbrella proves its worth.

Contrast that with the approach modern tech takes: Once we’ve decided on something being important, every big company must have their dedicated version of it.

Our world needs more, smaller tools that speak the same language, where everyone makes a little money, but nobody dominates the industry. In the 1980s, the software industry was kind of like this. Oh, sure, Microsoft and Apple were still out front, sucking up all the oxygen. But there were lots of little companies, selling software on disks. The bigger ones put them in boxes in stores. The smaller ones realized that they could just ship software through the mail and let the software spread naturally among user communities.

Shareware didn’t really survive the internet era—but, at least for a while, its spirit did. More recently, that spirit has taken a backseat to the larger companies that realize, if they’re big enough, they can shape how we interact with our world.

In 1991, if you wanted to start a software company, you had to hope that your product was good enough that word of mouth and a P.O. Box could push it around. That’s exactly what happened when Tim Sweeney released ZZT. It became the starting point for Epic Games, the kind of company that today is big enough that, thanks to its Unreal Engine and the success of Fortnite, it can dictate terms to much of the gaming industry.

If you ask me, I want a world where more software is like ZZT than it is like Fortnite, because more people have a chance to succeed in the former environment.

As much as I hate umbrellas, I think I’m coming around. Let’s build more small stuff. I’d rather have something small that covers my part of the sky than something big that covers the whole thing.

We’d all be happier with more umbrellas.

For nearly two decades, Plex has served as self-hosting’s great gateway drug.

It’s the one self-hosting tool that normies know about, and it looks slick and modern. (It’s even a streamer itself these days!) Despite the fact that it’s often associated with piracy, it has transcended its roots in the Xbox homebrew scene—it started as a Mac-oriented fork of XBMC, which became the modern-day Kodi—to become a legit business.

The rub, of course, is that it’s not open-source like most of the other tools people self-host. But Plex more than made up for this failing by offering an add-on service that added additional features to the free app. For more than a decade, you’ve been able to pay the fine folks at Plex a one-time fee, and boom, you have the full-fat service forever.

And for years, that fee was under $100—sometimes well under it. (I got it in 2024 on a discount, and I paid $91 for the honor.) At a time when Adobe seemed to charge an arm and a leg for its software with glee, Plex’s model felt like the right balance for consumers.

But clearly the deal wasn’t quite so good for the company, because this week the company felt compelled to raise the already elevated price of this lifetime subscription by an eye-watering $500, from $249.99 to $749.99. Their reasoning is pretty plain when all laid out:

We’ve considered eliminating the Lifetime Plex Pass in the past, given that recurring subscriptions help us sustain long-term development, but we know it’s still a valuable option for many in our community. So instead of retiring it, we’re keeping it available at a price that reflects the real, ongoing value of the software we’re committed to building and maintaining for years to come.

Just like everyone else, Plex needs money to pay for its service. But the problem is, people specifically use Plex and products like it to get away from the SaaS business model. Hence the impasse. By charging so much for it that the average person is not going to be willing to get past the sticker shock, Plex weeds out the people who aren’t good for their bottom line long-term.

Those people, rather than paying more than the price of the mini PC they use to host their Plex libraries, are most assuredly going with an alternative like Jellyfin.

But this tension is not new—far from it. A few years back, FUTO had then-spokesperson Louis Rossmann pushing for a form of open-source that encouraged payment by users. FUTO’s big self-hosted tool is the excellent Immich, so they have a horse in this race just like Plex. The problem is, FUTO’s pitch isn’t really open source. While Immich uses the more common AGPL v3 license, other FUTO projects like Grayjay use the Source First license, which encourages payment for commercial use.

(By the way: I see FUTO now states directly on its website that it’s not a nonprofit. I’d like to think my piece from 2024, which specifically called out that lack of clarity, led to that statement.)

Self-hosting is an extremely exciting scene these days, as I wrote about a couple of months ago. (I have plans to write a guide to apps you should be trying very soon.)

But if the model is ultimately unsustainable, that’s not good for the self-hosted community, either. And I think Plex, by announcing this insane price increase, they’re making it clear that they ultimately do not see this model as sustainable for real companies. (The counter-argument that carries water with me: Most users did not ask Plex to get into the streaming or content-licensing businesses.)

There’s a consistent tension that the Plex news hints at: End users want ownership of the tools they use, but those tools require different business models than the buy-once software of yore. You could reasonably argue that since we’re no longer buying software in boxes, we have a different expectation of maintenance than we once did. But on the other hand, there are plenty of cases where we weren’t necessarily asked whether we wanted new features added to the software we use. (I think if Adobe still shipped standalone Creative Suite versions every year and charged $1,000 for them, people wouldn’t be begging for feature updates every year.)

The truth is, if you run a business, a consistent stream of revenue is better than a flood of revenue that turns into a sputter. (A stream of revenue that becomes a flood is even better, if you have the infrastructure to manage it.) But when every drop of our paychecks is already accounted for before we’ve even saved anything up, SaaS feels exhausting. Plex’s move only leans into that exhaustion.

I think Plex’s problem is that it’s straddling two worlds, only one of which can realistically support a big company. Self-hosting is great for users and hardware companies, but there’s no way in heck it is as profitable as a money spigot.

The company had to make a choice. It might just push the next generation of self-hosted users to alternatives like Jellyfin and Emby. But that’s okay. Plex still has its normies.

I have written quite a few times over the years about Byron Allen, the legendary television business model exploiter who has managed to build an island of misfit toys into a business empire of his own.

Allen is a unique figure in media, because he can effectively maximize distressed assets—most infamously of late, the time slot soon to be vacated by Stephen Colbert.

But it’s not like he’s necessarily in it for the art of the whole thing; he is a man who understands business models in distress and how to execute on them. Which is why his decision to acquire BuzzFeed feels like something of an admission of how far BuzzFeed has fallen.

Jonah Peretti, until now BuzzFeed’s leader, had this to say about his new boss:

Byron’s vision, operational experience, and long-term commitment to premium content makes him exceptionally well-positioned to lead BuzzFeed and HuffPost into our next phase of growth. And personally, I’m thrilled Byron is taking over “The Late Show With Stephen Colbert’s” time slot, and highly confident that his relationships with talent will bring some incredible stars to the BuzzFeed platform.

(He’s sticking around, BTW, as president of BuzzFeed AI, which sounds like the business-world equivalent of becoming the United States Special Envoy for the Shield of the Americas.)

While it’s unlikely he’d be singing Allen’s praises in any other situation, Peretti must be feeling a massive sense of relief right now.

It’s been a bit overshadowed by the messiness of what’s happened since, but BuzzFeed started out essentially as a petri dish for experimental media ideas, only for massive VC funding to push that idea into the background. Recent moves by Peretti seem to suggest he’s been wanting to bring some of that spirit back to the company he founded, most notably in the form of his Anti-SNARF Manifesto from last year.

As an experiment in what it takes to build virality and generate attention online, BuzzFeed has been a massive success. As a company, it’s seen better days. And one might argue that, because he’s been stuck trying to steady the ship, Peretti has been kept away from what he’s actually good at—building inventive digital publishing ideas. One hopes that, as far as his new title goes, “AI” is merely shorthand for “being creative.”

Problem is, his path for getting to that point required him to make a deal with a guy whose latter-day career is associated with acquiring dusty old legacy media brands. It’s a rough association on the surface. Story-wise and money-wise, it suggests BuzzFeed’s best moments are in the past.

That’s far from what this company once represented in the media ecosystem, but on the other hand, it’s certainly a better fate than what happened to, say, Vice. After all, there was a financial payday in the end, and it does allow BuzzFeed to finally get out of the humiliating death spiral of their time on the stock market.

Allen, The Biz Reaper himself, is not a deeply creative mind like Peretti is (if he was, Comics Unleashed would be a better show), but more of an old-school entertainer with business chops. But as strange as it sounds, that may be to BuzzFeed’s advantage. The company spent years treading water, attempting to shore itself up with acquisitions that only made things worse from a financial standpoint. (I will note that HuffPost was cofounded by Peretti, but it came with a lot of debt.)

Meanwhile, its diaspora is out there winning Emmys, reshaping independent media, and becoming media moguls in their own right. Something about this model is not working, and as Simon Owens suggested in his newsletter today, it might just be a coherent YouTube strategy. It’s telling that the most memorable product the company has produced in the past five years was something it acquired, then sold: Hot Ones.

Sometimes you just need a boring guy who knows how to make deals at the helm, and Allen is probably that. Yes, his rep as the guy you see when your business model is on the fritz precedes him. But given that Peretti spent years grabbing every loose branch he could see in hopes of rekindling a fire, maybe a guy who knows about internal combustion might be the better bet.

BuzzFeed may never be a central viral force ever again. But it might have a chance to become a successful business again.

This week, word came out that the CEO of a name-brand, heavily memed company was trying to do something completely audacious.

Also, Ted Turner, the guy who arguably invented that trick and arguably did it better than possibly anyone else of his generation, just died.

It’s hard not to want to compare the left-field tactics of Ryan Cohen, the CEO of GameStop, founder of Chewy, and apparent suitor of eBay, to what Turner did throughout his long, storied, crazy-like-a-fox career. There’s a modest cult of personality around Cohen; I have a self-contained cult of personality around Turner, who is one of my favorite business leaders of the modern era.

I described Turner way back in 2015 as the Steve Jobs of television, and it’s a reputation that sticks. Like Jobs, he faced his share of boardroom drama, and took bold swings that everyone thought were out there at the time but looked brilliant in retrospect.

There are so many good stories about Turner, the guy who shot a nuclear winter contingency plan for his 24-hour news network. He was perhaps the only competitive yachtsman of note to appear on the cover of Sports Illustrated, a magazine whose then-owner later bought his company. He tried (and quickly failed) to take on MTV. He attempted to colorize lots of films for purely commercial reasons, only to do an about-face and launch a prestige cable channel instead. He created an environmentally friendly superhero.

And then there’s whatever the Goodwill Games was.

But in 1985, he had a moment where his boldness was about to knock him off the rails. In April of that year, he announced his plans to launch a hostile takeover of CBS, a company that, like eBay, was comically larger than its potential acquirer. Like Ryan Cohen’s eBay bid, Turner was trying to do it with cash he largely did not have. And it felt audacious at the time; the Macon Telegraph dedicated an entire page of its business section just to the implications of the deal, involving one of Georgia’s most powerful residents.

It didn‘t work out, ultimately; for once, Turner’s audacity got the best of him. His consolation prize? Buying the MGM library, considered a film industry crown jewel at the time, but selling the company. (The colorization drama came after.)

Now, 40 years later, we have a different class of weird, audacious, CEOs, the kind that are more likely to take potshots at the UN than give it a billion dollars just because.

And then we have dudes like GameStop CEO Ryan Cohen, who does admittedly have a track record. Chewy is a pretty huge company that blew up after he refused to accept the logic that a pet-centric e-commerce site couldn’t work. In some ways, Turner and Cohen have a lot in common—if eBay is Cohen’s CBS moment, Cohen got there at a slightly younger age than Turner did. But in others, they sharply diverge.

Love or hate Turner, he built his empire by taking bold risks with business moves that others were too nervous to try themselves. He acquired companies, yes, but he also built essential things from the ground up, like CNN. He helped give Atlanta a modern identity and a voice in the conversation, along with the roots of one of the strongest film industry epicenters in the country.

Cohen has taken bold risks, too, but much of his power is centralized in the stock market. His motivation for buying eBay seems far different from the motivation that drove Turner. When I heard about the proposed buyout, I immediately expressed skepticism and wondered if there might be a gas leak at GameStop HQ.

(Part of the reason for this: Cohen treats companies like financial instruments that can be optimized and tweaked for maximum stock market value. He’s an investor first, CEO second.)

CNN’s Turner obit was in the can long enough that it features an extended interview with Jimmy Carter, someone who died over a year ago. (Turner was diagnosed with Lewy body dementia in 2018.)

But looking at the deal in context of what Turner did is forcing me to check my priors a little. If I was looking at Ted’s wheeling and dealing in 1985, would I feel differently about it? Is there actually a point to such audacious bets?

(And it’s to be noted that Turner himself got burned by an audacious bet like this, with the AOL Time Warner merger, when the Turner-owning Time Warner played CBS to AOL’s Ted Turner.)

Ryan Cohen I’m sure is a fine entrepreneur, and entrepreneurship is a game of bets. But I wonder if he should study up on Ted Turner’s career before he dives into the deep water of an eBay acquisition any further.

There was always a logic to Turner’s decision-making even when it led to weird places like Captain Planet. It wasn’t always about the stock price. It might have been meeting another goal for him. That style of business feels old-school in an era when it’s literally possible for a company whose product everyone has been using for decades can see a 4,000% jump in value just because it’s indirectly attached to AI.

The logic needs to be more than about stock price.

Wheels Within Wheels: It’s wheels all the way down

One interesting thing about screw locomotion is that you move at a right angle to the direction you would move if you were using a wheel, despite the screws themselves being wheel shaped. So, combining the notion of the wheel and the screw opened up new possibilities for compound wheels—strange lumpy multi-ocular things that, by mounting wheels on (or embedding wheels in) other wheels, allow you to change direction without steering.

The simplest version of this is the omni wheel, where powered wheels are wrapped perpendicularly around the edge of a wheel. By stopping your large wheel and activating the smaller ones, you can move at a right angle, albeit much more slowly, since you are rolling on much smaller wheels.

Another variation is the Ilon wheel (after its inventor—also known as the Mechanum wheel, after the company that manufactured it, and the Swedish wheel, after the inventor’s nationality), a wheel wrapped in powered wheels mounted at a 45-degree angle. It is essentially a screw made of wheels mounted on a wheel. A single Ilon wheel can move back and forth along two axes, but four can rotate in place as well as moving side to side.

The problem with all of these is that the actual amount of surface area you are rotating against the ground depends upon the direction you’re moving. And so, all of the exotic motions that these wheels are capable of are very slow when used on something heavy (like a vehicle). Instead, these wheels are largely used in robots and sorting machines.

Platforms, which aren’t just limited to Lego

There is a wheel that we have, so far, been ignoring: the circle formed by the arrangement of drive wheels on the bottom of our vehicle. We turn this abstract wheel when we rotate the vehicle.

With two independently-powered ordinary wheels and a caster, we can drive forward and back (by keeping the power to both wheels consistent), turn gradually (by pushing more power to one wheel than the other), or do tight spins (by turning one wheel off entirely).

This is a differential drive platform, and if you balance things perfectly, you can even remove the caster. The problem with two-wheel differential drives is that, without a caster creating a third point of contact with the ground, and if you go too fast your vehicle is going to flip forward and back. The center of gravity has to be maintained very carefully. (And casters get stuck, as anyone who has ever used a shopping cart or office chair can tell you.)

Enter the holonomic drive: rather than using the differential between two parallel wheels, use the differential between three wheel assemblies arranged in a triangle. Use rotating wheels and you have a synchro drive. If these wheel assemblies are omni or Ilon wheels, then this is called a kiwi platform.

If instead these are “linear wheels” (i.e., a pair of thick wheels at right angles to each other, resting on the ground along their edges), then this is called a Killough platform.

With three wheel assemblies, rotation and movement is possible with less slipping than a four-wheel arrangement. With linear wheels, it’s not necessary to adjust for the size difference between the rollers and the main wheel body found in omni wheels.

These platforms can do all sorts of impressive acrobatics, but they require computer control—steering involves a lot of math—so they are mostly used in robots, and not in manned or remote-control vehicles. In fact, it was hard for me to find pictures of holonomic drive platforms not made of Legos!

While there are industrial uses, they appear to be downstream of a short-lived vogue for holonomic drives in high school and college robotics clubs about 20 years ago—feeding the imaginations of kids who have now become senior engineers.

I think the point where it became clear to me that the AI bubble was hitting a wall came about two weeks ago, when Anthropic launched its Claude Design product.

As someone who is interested in design and is trying to understand what the hell is happening with AI enough to have a thoughtful perspective on it, it struck my interest. I threw it a GitHub project and told it to extract the visual style. Then I ran a second command, and … suddenly, it was out of credits until Friday at noon. It was 1pm on a Friday.

I prefer to actually understand the things I feel skeptical about, because it helps me catch things that highlight bigger underlying problems. And well, it doesn’t get any more blunt than that.

Expect more stories like this. Recently, GitHub announced that it would change its billing for Copilot to usage-based pricing. And there have been mixed messages around how people could use their paid Claude subscriptions for tools like the overly hyped OpenClaw—at first, it was banned, but now it’s not.

The truth is, these mainstream AI products are getting subsidized, and users are addicted to the subsidy. It’s not sustainable, but the goal is to keep you addicted long enough that maybe it will be. Admittedly, some, like noted AI skeptic Ed Zitron, don’t think it ever will be:

It’s very, very important that nobody writing about AI in the mainstream media actually understands how much these services cost, and that any mainstream articles written about services like ChatGPT or Claude Code are written by people who have little or no idea how much each individual task might cost a user.

Remember: generative AI services are, for the most part, experimental products that do not function like any other modern software or hardware. One cannot just walk up to ChatGPT or Claude and start asking it to do work.

And when you become dependent on these tools, you pay more, and then you fall into this trap of paying huge chunks of your revenue just to keep these things running.

It’s costly, it’s inefficient, and we’re going to run into scale limits eventually. All the money for those Super Bowl ads and new products is going to eventually come due.

But then there’s DeepSeek and its ilk.

AI For Cheapskates: Yes, It Exists

To be clear, I’m not saying any AI model is going to solve the inherent structural problems that AI creates. Much the opposite. However, I think that DeepSeek’s story is an important contrast to the massive players that seem to dominate every news headline these days.

The Chinese company, whose access to the highest-end GPUs is limited by trade restrictions, has been building models on a budget, then charging for those same models at rates that put dominant players to shame. Its newest ones came out just last week.

DeepSeek V4 Flash, which is roughly as powerful as Claude’s Sonnet 4.6 model, costs less to use than the low-end Claude 3 Haiku, a deprecated model which came out more than two years ago and is barely functional in comparison. It isn’t as slick, but it has some advantages, notably a very large context window (a weak point of prior DeepSeek models). Plus, you’re not paying the overhead for all the misadventures that come with Anthropic or OpenAI’s models.

On top of all that, since it’s an open-weight model, you’re not stuck using DeepSeek’s servers. The pay-as-you-go cloud service Novita, for example, charges roughly the same rates as DeepSeek does for its new models. (Good luck self-hosting these though, as you’d need a lot of GPUs to do so.)

When DeepSeek first emerged with its R1 model a year ago—built on the cheap and punching above its weight—its emergence was so shocking that it caused the global stock market to shake. This new model did not do that, which has led outlets such as Reuters and The Economist to suggest it might be a failure.

But if anything, the reason it feels like a failure to some has less to do with its innovations and more with the fact that others have followed in its footsteps. MiniMax, for example, has a “self-improving” model comparable to DeepSeek’s, one that actually learns from its mistakes, apparently. And other players like Z.ai and Alibaba Cloud’s Qwen have drawn excitement from self-hosters who want to avoid paying Anthropic or OpenAI any money at all.

They’re Aiming For The Big Bill. You’re Not.

I think the point I want to get across is that AI is not a two-headed hydra. There are other players, but the biggest ones are incentivized to suck up all the oxygen. So you might be forgiven if you think that only two or three companies are building AI models.

These smaller players, who are more likely to open-source their innovations, have to compete on efficiency and technical prowess, not with unlimited resources. That makes them an effective counterweight to the attention-grabbers.

But the big players are always ready to throw their weight around—for example, with constant feature drops. Recently Anthropic announced integrations with numerous major creative tools, including Affinity and Creative Cloud. (And, controversially, Blender.)

I’ve often joked that, in the wrong setting, AI can be a decorative bird, but I don’t think that’s what’s happening here. I think, instead, Anthropic has identified a use case for its technology that is useful enough, and sucks up enough tokens, that companies will be ready to put down some big bucks for its models. And you thought Creative Cloud was expensive.

I think so many companies are going to be sucked in by the efficiency benefits of these tertiary tools, only to find that they’re spending giant amounts of money for modest efficiency gains.

It won’t do much for all the other ethical concerns about this stuff (giant data centers remain a big risk, for one), but a bit of literacy about what all this stuff does will go a long way. After all, modest efficiency gains will be a lot easier to swallow if the amounts of money aren’t giant.

A lot of companies want to optimize with AI, but they’re looking at efficiency, not cost. Which is a shame, because I think these open-weight Chinese models will ultimately be like open-source. Lots of people will ignore them, because they don’t advertise, don’t have sales teams, and don’t build random buzzy-but-expensive things like Sora. But eventually, a cult will form of people who figure out that spending tons of money on bleeding-edge LLMs, when there are cheaper options (including some that can be hosted on your laptop), is not a good investment.

(Plus, dollars to donuts you’ll eventually see an open-source recreation of this design functionality, just as we saw with Claude Code competitors like OpenCode.)

As I wrote recently, humans are often the problem with AI. But they can also be the solution—by being savvy about how they deploy it, by not letting flashy features distract you from your goals.

After all, the bill is going to eventually come due. And you’re gonna want a smaller bill. Trust me on this one.

Tweezer resharpening may be the most obscure, niche service ever offered inside the pages of a magazine

If you or someone you love read magazines about watchmaking in the 1970s or 1980s, you might have been pulled in by a simple ad published by a man named Harvey C. Watkins.

It was simplistic, not exactly showy, a classified ad buried in the back of a magazine on the nichiest of niche topics. But there it was: “Superior Tweezer Resharpening. $2.50 each, including return first class postage. Minimum of three tweezers. Advance payment required.”

Now, far be it from me to tell you how to spend your money, but an expert tweezer resharpener was not something I knew someone needed to be.

But on the other hand, this ad ran in a magazine, the Horological Times, that focuses on the art of watchmaking. (Free slogan idea: “What time is it? Time for a new issue.”)

Basically, this tweezer resharpener’s business fit right in with the magazine in which the ad was published—a magazine that is still published today by the American Watchmakers-Clockmakers Institute, a group whose tightly wound history goes all the way back to 1866. It was one of the few fields at the time that worked with things at such a small scale on a regular basis.

Case In point: In a 1981 issue of this magazine where Watkins’ ad ran, one of the main features was a piece titled “A Plethora of Pliers,” which is such a bizarre headline I based this issue’s headline off that headline.

So why am I focused on this random classified ad in a trade publication for people who work with tiny machines that fit on your wrists? Because, when I was researching tweezers, I found an article so unusual, so pure of heart, that I needed to share it with my readers.

The headline, from The Orlando Sentinel in 1985: “Daughter Carries on Father’s Tweezer-Sharpening Trade.”

The piece, about the then-retired Watkins and his daughter Phyllis Hildreth, discusses how Watkins got into the trade two decades prior, in part because of a problem Watkins ran into as a watchmaker: His tweezers, made of high-quality alloys and produced in Switzerland, would keep chipping. At the same time, the prices of good tweezers, which are more expensive than you might have expected, just kept going up.

Despite the modest ad, Watkins apparently refinished thousands of pairs of tweezers over the years, with Hildreth picking up the slack after her father left the business in the mid-1980s (And yes, this family firm had a trade secret: Hildreth agreed not to let anyone see the machine her father developed to handle tweezer resharpening.)

The kicker of this wonderful article comes from Horological Times managing editor Maury Norrell, who need the utter obscurity of this business: “If I had to get a pair of tweezers refinished, I don’t know where I’d go, other than Watkins.”

Now, I can’t find evidence that this tweezer firm survived into the modern day, but there are those that handle similar work. Express Instrument Service, a firm that has existed since 1979, handles tweezer refinishing for surgical-grade instruments. And for consumers who want their tweezers to stay sharp, the manufacturer Tweezerman offers free sharpening to those who purchase its high-end tweezing product.

Let it never be said that people don’t take sharp tweezers seriously.

The aptitude-testing nut who came up with a dexterity test for tweezer users

The thing about tweezers is that, unless you’re using them on a regular basis, they can be a complete challenge to pull off well. They are often intended to grab things at scales far smaller than the average person is equipped to properly handle.

Which explains why there’s actually a standardized test to analyze a person’s aptitude with tweezers.

The O’Connor Tweezer Dexterity Test, which sells on Amazon for a shockingly expensive $175+, is a test of precision and manual aptitude that relies on placing a series of pins into specific holes on a board. The test is fairly simple and a good way to measure whether a person is handy with handling small, precise things with their hands. (Check out a video of someone doing it, above. IMPORTANT EDITORIAL NOTE: DO NOT SEARCH ON YOUTUBE FOR TWEEZERS. IT IS GROSS.)

Its inventor, Johnson O’Connor, had a knack for developing things like this, first through an in-house position at General Electric in the 1920s in which he developed a series of skills tests, including the dexterity test, which first found use among GE’s 3,000 employees. The tests, 17 in total, weren’t specifically tied to physical tests; they also emphasized things such as clerical ability, personality, observation, number memory, and visual imagination. (As noted in his 1973 New York Times obit, he also found a niche in vocabulary building.)

While these concepts were first built for corporate America, they soon found homes in academia (they were further developed at the Massachusetts Institute of Technology and Stevens institute of Technology) and in the form of a nonprofit that still exists today, the Johnson O’Connor Research Foundation.

Know Your Real Abilities: Understanding and Developing Your Aptitudes, a 1948 book partly inspired by O’Connor’s work by Charles V. And Margaret E. Broadley, put the reasoning for the approach as such:

Most of us want work in which we can put our hearts, in which we feel we are making some contribution to the world. But we see no way out in our modern world where so many jobs are routine, where individual development has been pushed aside to make way for material progress. Yet we sense vaguely that we have more in us; we feel restless and dissatisfied with ourselves; we feel inferior and inadequate. But we do not know what to do about it.

This mindset about work abilities helping to define whether a person is a match for the field they’re in is a driving force behind the nonprofit that bears Johnson’s name.

“Aptitude testing is the starting place to identify strengths,” said Alina Myers, director of Johnson O’Connor Research Foundation Inc. in Washington, a nonprofit educational organization founded nearly 70 years ago. “Aptitudes don’t change over time.”

And obviously, there are lots of fields where the ability to use a tweezer in this way can come in handy. For example, electrical engineering, a field for which soldering is a key skill set; for another, surgery, where precise movements are often necessary. And this test, beyond its value for aptitude testing, is also a great option for rehabilitation, for those trying to improve dexterity after an injury.

You might laugh at the idea of taking a bunch of random tests to understand your skill sets, but these tests are vigorous, and apparently take a lot out of the people who do them.

“Trials they were. I dropped the tweezers. Whole sequences of numbers, once shown, were promptly forgotten,” one person wrote in a testimonial. “A vocabulary test left my smug self-assurance as an erudite man of letters in shambles. First I felt challenged, then frustrated, and, in the end, exhausted.”

(That person was pinned as a communicator, which makes sense, because as we all know, communicators can’t tweeze.)

McClatchy is a company that screams legacy. Nearly 170 years old, it has acquired a number of significant newspapers over the years, most notably in 2006, when it acquired the iconic Knight Ridder chain.

It is a company that has faced many challenges over its long history, notably filing for bankruptcy around the time of the COVID-19 outbreak. Even after merging with the former owner of the National Enquirer (really), it is barely holding on, and plus it has to figure out this whole AI thing.

One of my favorite metaphors is the idea of using a wrench in place of a hammer. It technically works, but it’s not the right purpose. AI tools are often the wrench of technology. And McClatchy just found its wrench.

According to The Wrap (paywall), the chain is pushing its journalists to use AI tech to repackage content in multiple directions. The technology was sold to the employees as Grammarly on steroids, and the hint seems to be that those who don’t accept this technology will be on thin ice career-wise.

“Journalists who embrace and experiment with this tool are going to win,” McClatchy VP of Local News Eric Nelson said recently, per the publication. “Journalists who are defiant will fall behind. Bottom line: We need more stories and we need more inventory.”

McClatchy is effectively using Claude to take already-written stories, repackage the reporting, and reuse it in whatever ways are necessary. Put another way, the company is trying to scale up for the arms race that is SEO, social media, and Google Discover.

The problem is, that means that these journalists are now going to have their bylines on content that AI actively wrote and repackaged, while attempting to limit the say those journalists have in the matter. From the piece:

Kathy Vetter, McClatchy’s chief of staff for local news, said during the March 17 meeting that the company’s general policy was that reporters who cannot revoke the use of their bylines must keep them attached to CSA-produced stories. For those who can revoke their byline, she said, McClatchy will still use their work anyway.

“We have every right to use their work,” she said, according to multiple sources familiar with the meeting. “It belongs to us, and if an editor wants to go … in there and repurpose a reporter’s content, they can put their name on it.”

Unions have gotten involved, limiting how those bylines get used, but not every paper has a union.

An unwanted byline introduces murky questions

What’s fascinating about the Wrap piece is the divide between journalists and executives that it exposes. VPs and business staffers seem excited about the opportunities this opens up. Journalists are upset that their names are going to be associated with work they didn’t actually write.

I’m not a lawyer, but the decision to essentially force non-unionized employees to include their bylines on pieces they didn’t write feels like it could be legally risky to me. Let me pose a scenario: Let’s say one of these LLM stories gets something wrong, and a journalist gets strong pushback on social media about the story, maybe even death threats, even though they didn’t write it. Does that put the newspaper at risk of a lawsuit from their own employee? Given our current culture, that does not seem far-fetched.

There are other risks, too: Imagine a defamation lawsuit against a journalist based on an error AI introduced, for example. And for readers, it might introduce a misrepresentation risk that gets a regulator like the Federal Trade Commission to weigh in, potentially even restricting the use of AI in news content. The parallels to the Wild West of early adtech are hard to miss.

If it was the government forcing this situation, that byline might even be seen as “compelled speech,” though employers have a lot more leverage. Nonetheless, it points at a moral wrong of sorts, a breaking of norms, and one that feels avoidable. After all, journalists typically have the right to take their bylines off of pieces, even if McClatchy appears to be quietly eliminating that right.

By McClatchy attempting to make this shift, it highlights the weakening state of the power dynamic between the newsroom and its employees. And AI is the justification.

A truism about AI: It’s often a scapegoat

Another headline that I stumbled upon around the same time I think points to a broader issue: Often, AI is just used as a reason to do something that employees would otherwise be uncomfortable with.

This week, Meta announced a plan to start tracking employees’ mouse and keyboard input, with the idea of building training data for its AI agents. See, it’s okay if we spy on you, because it’s for AI.

Let’s be clear, if Meta wanted to do this, it would just do it. It doesn’t need to attach AI as an excuse. But the addition makes it generally more palatable.

Likewise, if McClatchy wanted to have a bunch of inexperienced interns or non-journalists repackage content in haphazard, over-the-top ways, it could just do it. If it wanted to strip employees of the right to take their name off a story, it could just do it. But AI gives it enough of a sheen that it takes attention off the fact there’s nothing stopping them from just doing it because today is a day that ends in y.

And I think that’s ultimately the point I want to get at here. Employers are going to say a lot of things in the coming years and blame AI for doing those things. After all, it’s a great wrench for hammering in nails. But let’s not be silly: It’s also an excellent excuse to sweep a lot of other changes through, whether it’s layoffs or costing employees some of their taken-for-granted rights.

In Wizard of Oz parlance, don’t let the flashy visuals fool you: There’s a human behind the curtain, making the choices that could reshape your life and career.