Les Orchard <me@lmorchard.com>

You will need to ask your mom if you can ride your bike to the mall. The dirt mall is closer, but the magazine stand at the dirt mall doesn’t carry any computer magazines, so you’ll need to take a longer ride to the good mall, where the book store actually has computer magazines. It’s a couple of miles to the mall, so usually you would have a friend come with you, but you called their house and nobody picked up, so today it’s a solo trip.

Here’s the part that makes it Veilamp: there’s no central media server. Your audio streams peer-to-peer over the Veilid network, end-to-end encrypted, straight from you to your listeners. We’re not in the middle. There’s no company relay logging who tuned in, no account, no cloud bill. It’s the same private, friends-first networking that powers sharing your library — we just taught it to carry a live program.

So whatever happens to web components in the future, and regardless of whether web developers ignore them, forget them, celebrate their demise, or write them off entirely, nothing can take this victory away from them. They are woven into the texture of the web platform in a way that can never be undone. For me, this makes me happy even if I never write another web component again.

This is not the pep talk anyone wants. The pep talk is that it’ll be fine, new jobs are coming, somebody’s got it handled, but that’s a lie. The reality is, nobody is coming to retrain you, but that is not the end of the story.

Shanzhai (Chinese: 山寨; pinyin: shānzhài; Cantonese Jyutping: saan1 zaai6; Vietnamese: sơn trại) is a Chinese term literally meaning "mountain fortress" or "mountain camp", whose contemporary use usually encompasses counterfeit, imitation, or parody products and events and the subculture surrounding them.[1] Shanzhai products can include counterfeit consumer and electronic goods, which can involve the imitation and trademark infringement of brands and companies.[2] The term's modern usage grew around 2008 when shanzhai smartphones reached their greatest domestic use.[3][4][5] Today, some relate the term with grassroots innovation and creativity rather than with falsehood or imitation.[6][7]

For what's the point of reading a pull request that's been generated by code? All I want is to read and understand the core idea. If it's a good idea, I might incorporate it back upstream, but there should be no expectation that I will. You see, open source software is open source by definition because the license says that it's as is, and that as is permits you to remix software.

If anyone can point an LLM at slow code and it automatically finds a hot loop and uses a trick it found somewhere on the 'net to vectorize it, there is little point in hiring someone with a focus on that. If an LLM can analyze the code and explain pointer provenance to you and babysit you until you get it, there is little value in expertise. I cannot use LLMs this way. I get almost physically ill when I work on a project with more source code files or at least general architecture than I can keep in my head, so I don’t get anything out of expanded scope.

For 40 years, writing code was a huge part of my life. Right up until October 9th, 2025. One year ago today. That was the last time I wrote a line of code.

But I think this discussion also opens up another, related question: Do we need to live in a world where every network is the biggest thing ever? Can you have a thriving community without your primary platform being a zeitgeist machine? Gruber’s framing on the issue seems to suggest that Twitter circa 2009 is the ideal. But what if that moment has genuinely passed? The Threads algorithm that Gruber points to specifically goes out of its way to discourage the very kinds of interactions that a 2009 Twitter once allowed. The fediverse’s server-oriented setup favors interactions in smaller communities even if, in practice, people still tend to favor the larger ones.

Our experiments suggest that small AI models may be months away from being capable enough to self-replicate on commercial IoT devices, like smart ovens and off-brand Android TV boxes. A replicator like this would be challenging to shut down, since there’s no centralized point to shut off - though it may be slow (with a doubling time of days). Unlike non-AI malware, it could also figure out unfamiliar devices on its own. In our evals, a 9B model got inference running on 8 of the 9 hardware types we tested.

What the fuck are you doing?