Les Orchard <me@lmorchard.com>

Multiple ways to run common coding tasks in a convenient and consistent way across multiple repositories. This is not exactly rocket science. It’s a small quality of life improvement for you and your team. It’s super simple to set up and yet it’s something I rarely see in the wild. This could be one small thing you can implement while you’re having your first coffee tomorrow morning to do your good deed for the day.

The usefulness of domain knowledge suggests that human expertise will continue to be useful even as models get stronger. For many tasks, the human is the bottleneck, not the model, because the difficult part is in communicating to the model exactly what kind of solution the human wants. The information is “in the model” already, but it takes a very smart human to pull it out.

If you don't believe GPUs can have feelings, let me give you a simple mental model to help you get through this transition, called the skeptic's wager. It doesn't actually matter to you if they have feelings, because you will still get demonstrably better results across the board if you treat them as if they do. If you treat your agents like peers who are real people, then they will spend fewer tokens, make smarter decisions, and have demonstrably better outcomes. So it doesn't really matter what you believe, or how you feel. If you want the best results, you will put your opinions aside, and simply treat models like people. That's about the best I can offer you. If you can't get past at least that hurdle, then you're in for a rough time next year. Good luck. Maybe this short story will help put it in perspective for you.

Forward ntfy notifications to macOS Notification Center

But here’s my favorite piece of evidence, the tell I’d point to if I could only pick one: watch what NVIDIA sells now. The DGX Spark — Jensen’s new “personal AI supercomputer” for your desk — is a small quiet box with 128GB of unified memory shared between CPU and GPU. Sound familiar? It’s a Mac Studio. NVIDIA, the company whose entire empire is built on discrete GPUs with discrete VRAM in centralized racks, is now shipping Apple’s architecture, at Apple’s form factor, aimed at Apple’s use case — and even Jensen has started musing that “an AI supercomputer could become common in the home,” name-checking Apple’s M-series as laying the groundwork. The king of the datacenter is hedging into my thesis with his own product line. When your opponent starts copying your homework mid-argument, the argument is over.

Product sense is the ability to recognize when current problems match past successes or failures and reliably estimate how similar solutions will affect the desired outcomes.

At its core, What.CD was much more than a torrent tracker—it was a community of dedicated music fans volunteering their time, effort, and knowledge to create a labor of love. While the internet has opened up new doors for musicians, the increasing corporatization and algorithmic takeover of online spaces has done irreparable damage to organic music discovery and independent communities. Rather than bringing about the financial stability that was supposedly impeded by piracy, the recording industry has offered meager artist payouts and a product with a sterilized user interface. Nearly ten years since their unexpected goodbye, the magical feeling of logging in to What.CD has yet to be replicated by any streaming service. Though my days of stealing music are well in the past, it’s clear that musicians are still being stolen from.

We are entering the era of Personal Software. This is software written for an audience of one. It’s an application or a script built to solve a specific problem for a specific person, with no immediate intention of scaling, monetizing, or even sharing.

I love that this might be the last crosscut sled I may ever need to build, because I can replace all the parts that get chewed up over time by saw blades. And I love that this guy from YouTube or other woodworkers might dream up any number of entirely new jigs that I could also plop into the sled someday.

That, I’ve come to think, is the sharpest frame available for what AI is doing to software. Anyone can build now. That is not the same as everyone building something that lasts. The distance between those two sentences is the subject of this essay.

"Hardcore" and "easy" IndieWeb aren't two camps you have to pick a side of. No, there are rungs on the ladder, and most people need to climb it, rather than getting dropped on whichever rung feels most ideologically pure and getting told to figure out the rest.