slug: supapechakucha

Discover how The Epic Programming Principles can transform your web development decision-making, boost your career, and help you build better software.

In a fit of frustration, I wrote the first version of Kamal in six weeks at the start of 2023. Our plan to get out of the cloud was getting bogged down in enterprisey pricing and Kubernetes complexity. And I refused to accept that running our own hardware had to be that expensive or that convoluted. So I got busy building a cheap and simple alternative.  Now, just two years later, Kamal is deploying every single application in our entire heritage fleet, and everything in active development. Finalizing a perfectly uniform mode of deployment for every web app we've built over the past two decades and still maintain. See, we have this obsession at 37signals: That the modern build-boost-discard cycle of internet applications is a scourge. That users ought to be able to trust that when they adopt a system like Basecamp or HEY, they don't have to fear eviction from the next executive re-org. We call this obsession Until The End Of The Internet. That obsession isn't free, but it's worth it. It means we're still operating the very first version of Basecamp for thousands of paying customers. That's the OG code base from 2003! Which hasn't seen any updates since 2010, beyond security patches, bug fixes, and performance improvements. But we're still operating it, and, along with every other app in our heritage collection, deploying it with Kamal. That just makes me smile, knowing that we have customers who adopted Basecamp in 2004, and are still able to use the same system some twenty years later. In the meantime, we've relaunched and dramatically improved Basecamp many times since. But for customers happy with what they have, there's no forced migration to the latest version. I very much had all of this in mind when designing Kamal. That's one of the reasons I really love Docker. It allows you to encapsulate an entire system, with all of its dependencies, and run it until the end of time. Kind of how modern gaming emulators can run the original ROM of Pac-Man or Pong to perfection and eternity. Kamal seeks to be but a simple wrapper and workflow around this wondrous simplicity. Complexity is but a bridge — and a fragile one at that. To build something durable, you have to make it simple.

One rabbit hole I can never resist going down is finding the original creator of a piece of art. This sounds simple, but it’s often quite difficult. The Internet is a maze of social media accounts that only exist to repost other people’s art, usually with minimal or non-existent attribution. A popular image spawns a thousand copies, each a little further from the original. Signatures get cropped, creators’ names vanish, and we’re left with meaningless phrases like “no copyright intended”, as if that magically absolves someone of artistic theft. Why do I do this? I’ve always been a bit obsessive, a bit completionist. I’ve worked in cultural heritage for eight years, which has made me more aware of copyright and more curious about provenance. And it’s satisfying to know I’ve found the original source, that I can’t dig any further. This takes time. It’s digital detective work, using tools like Google Lens and TinEye, and it’s not always easy or possible. Sometimes the original pops straight to the top, but other times it takes a lot of digging to find the source of an image. So many of us have become accustomed to art as an endless, anonymous stream of “content”. A beautiful image appears in our feed, we give it a quick heart, and scroll on, with no thought for the human who sweated blood and tears to create it. That original artist feels distant, disconected. Whatever benefit they might get from the “exposure” of your work going viral, they don’t get any if their name has been removed first. I came across two examples recently that remind me it’s not just artists who miss out – it’s everyone who enjoys art. I saw a photo of some traffic lights on Tumblr. I love their misty, nighttime aesthetic, the way the bright colours of the lights cut through the fog, the totality of the surrounding darkness. But there was no name – somebody had just uploaded the image to their Tumblr page, it was reblogged a bunch of times, and then it appeared on my dashboard. Who took it? I used Google Lens to find the original photographer: Lucas Zimmerman. Then I discovered it was part of a series. And there was a sequel. I found interviews. Context. Related work. I found all this cool stuff, but only because I knew Lucas’s name. Traffic Lights, by Lucas Zimmerman. Published on Behance.net under a CC BY‑NC 4.0 license, and reposted here in accordance with that license. The second example was a silent video of somebody making tiny chess pieces, just captioned “wow”. It was clearly an edit of another video, with fast-paced cuts to make it accommodate a short attention span – and again with no attribution. This was a little harder to find – I had to search several frames in Google Lens before I found a summary on a Russian website, which had a link to a YouTube video by metalworker and woodworker Левша (Levsha). This video is four times longer than the cut-up version I found, in higher resolution, and with commentary from the original creator. I don’t speak Russian, but YouTube has auto-translated subtitles. Now I know how this amazing set was made, and I have a much better understanding of the materials and techniques involved. (This includes the delightful name Wenge wood, which I’d never heard before.) https://youtube.com/watch?v=QoKdDK3y-mQ A piece of art is more than just a single image or video. It’s a process, a human story. When art is detached from its context and creator, we lose something fundamental. Creators lose the chance to benefit from their work, and we lose the opportunity to engage with it in a deeper way. We can’t learn how it was made, find their other work, or discover how to make similar art for ourselves. The Internet has done many wonderful things for art, but it’s also a machine for endless copyright infringement. It’s not just about generative AI and content scraping – those are serious issues, but this problem existed long before any of us had heard of ChatGPT. It’s a thousand tiny paper cuts. How many of us have used an image from the Internet because it showed up in a search, without a second thought for its creator? When Google Images says “images may be subject to copyright”, how many of us have really thought about what that means? Next time you want to use an image from the web, look to see if it’s shared under a license that allows reuse, and make sure you include the appropriate attribution – and if not, look for a different image. Finding the original creator is hard, sometimes impossible. The Internet is full of shadows: copies of things that went offline years ago. But when I succeed, it feels worth the effort – both for the original artist and myself. When I read a book or watch a TV show, the credits guide me to the artists, and I can appreciate both them and the rest of their work. I wish the Internet was more like that. I wish the platforms we rely on put more emphasis on credit and attribution, and the people behind art. The next time an image catches your eye, take a moment. Who made this? What does it mean? What’s their story? [If the formatting of this post looks odd in your feed reader, visit the original article]

When the iPhone first appeared in 2007, Microsoft was sitting pretty with their mobile strategy. They'd been early to the market with Windows CE, they were fast-following the iPod with their Zune. They also had the dominant operating system, the dominant office package, and control of the enterprise. The future on mobile must have looked so bright! But of course now, we know it wasn't. Steve Ballmer infamously dismissed the iPhone with a chuckle, as he believed all of Microsoft's past glory would guarantee them mobile victory. He wasn't worried at all. He clearly should have been! After reliving that Ballmer moment, it's uncanny to watch this CNBC interview from one year ago with Johny Srouji and John Ternus from Apple on their AI strategy. Ternus even repeats the chuckle!! Exuding the same delusional confidence that lost Ballmer's Microsoft any serious part in the mobile game.  But somehow, Apple's problems with AI seem even more dire. Because there's apparently no one steering the ship. Apple has been promising customers a bag of vaporware since last fall, and they're nowhere close to being able to deliver on the shiny concept demos. The ones that were going to make Apple Intelligence worthy of its name, and not just terrible image generation that is years behind the state of the art. Nobody at Apple seems able or courageous enough to face the music: Apple Intelligence sucks. Siri sucks. None of the vaporware is anywhere close to happening. Yet as late as last week, you have Cook promoting the new MacBook Air with "Apple Intelligence". Yikes. This is partly down to the org chart. John Giannandrea is Apple's VP of ML/AI, and he reports directly to Tim Cook. He's been in the seat since 2018. But Cook evidently does not have the product savvy to be able to tell bullshit from benefit, so he keeps giving Giannandrea more rope. Now the fella has hung Apple's reputation on vaporware, promised all iPhone 16 customers something magical that just won't happen, and even spec-bumped all their devices with more RAM for nothing but diminished margins. Ouch. This is what regression to the mean looks like. This is what fiefdom management looks like. This is what having a company run by a logistics guy looks like. Apple needs a leadership reboot, stat. That asterisk is a stain.