The linked article is dated March 31, 2026.

Meh.

It would undoubtedly be very expensive at first, and therefore only available to the very wealth (probably not ultra-wealthy -- even without automation, caring for such a clone wouldn't be a full-time job, so call it maybe $30k/year -- within the reach of the upper middle class). But competition would drive automation, and we already have most of the techniques required, having developed them to deal with coma patients and the like, but at lower cost because this case would be dealing with a fundamentally healthy body. My guess based on some napkin math is that cost could be driven down as low as $10k per year. Maybe lower.

$10k per year is expensive, sure, but having an immunologically-perfect organ donor could absolutely be worth it for someone making as little as $200k per year.

If the cost could be driven down to $5k per year... then it's in the range where most middle-class Americans could afford it, even if it meant that they'd have to cut back a little somewhere else; maybe drive an older car rather than leasing a new one, or similar.

I'm just talking about statistical patterns. I know little about Microsoft patches. I abandoned Windows in 2001, right around the time XP was released, and have never looked back.

Not remotely similar to my experience. Granted I'm writing Rust, and the Rust compiler is *really* picky, so by the time the agent gets something that compiles it's a lot closer to correct than in other languages. Particularly if you know how to use the type system to enforce correctness.

Yes, you have to know how to write tests. A few decades of experience helps a lot. I find I actually spend a lot more time focused on the details of APIs and data structures than the details of tests, though. Getting APIs or data structures wrong will cost you down the road.

Also, I suppose it helps a bit that my work is in cryptography (protocols, not algorithms). The great thing about crypto code is that if you get a single bit wrong, it doesn't work at all. If you screw up the business logic just a little bit, you get completely wrong answers. The terrible thing is that if you get a single bit wrong, it doesn't work at all and gives you no clue where your problem might be.

Of course that's just functional correctness. With cryptography, the really hard part is making sure that the implementation is actually secure. The AI can't help much with that. That requires lots of knowledge and lots of experience.

Deep experience is absolutely required. My antennas are quite good after 40 years.

You really have to know what questions to ask, and what answers not to accept. It also helps to know what kinds of errors the LLM makes. It never outright lies, but it will guess rather than look, so you have to know when and how to push it, and how to manage its context window. When stuff starts falling out of the context window the machine starts guessing, approximating, justifying. Sometimes this means you need to make it spawn a bunch of focused subagents each responsible for a small piece of the problem. There are a lot of techniques to learn to maximize the benefit and minimize the errors.

Yeah, I am definitely not doing UI work.

Speak for yourself. I wrote Android's Keymaster implementation in less than a month, and it was about that size, and then re-wrote most of it in a week when it turned out I'd made some core assumptions that Qualcomm couldn't match in their implementation. It was relatively bug-free for a decade -- even when a third-party security research lab spent a month scrutinizing it. They found a handful of things, but nothing serious. I was amazed, especially since I'd seen the reports they turned in on some other code.

That's just one example. In my nearly 40-year career I've had a half dozen crazy-productive weeks like that, and usually when working on particularly-complex bits. If you haven't had that experience, that's unfortunate. It's not something I could do frequently (or would want to), but it's a glorious feeling when you're that deep in the zone.

Mostly agree. I abandoned the Mac around Systen 7.5 era for the 486DX 66Mhz. The multitasking and protected memory spaces put it in advance of the Mac, and the CPUs started to lag the competition as well.

I came back in the OS X era (can't remember if I ever had Cheetah, but I definitely had Jaguar) where although the chips were a bit slower overall it didn't matter much because the OS was just better. Now the chips are better, the OS is better (for versions of 'better' that don't include gaming)...but the OS as compared to its own standards is worse than it used to be. Better than Win 11 - hmm. Not the highest bar anymore.

Which, to be honest, fundamentally misunderstands used RAM readings. Vast majority of that 'used' RAM is in easily discardable caches - Apple had the same PR problem with misleading reports when they released whatever the version was about 4-5 years ago and their tools reported full memory.

Windows does use more RAM than most, but it showing almost all the RAM full is the same kind of caching strategy that macOS uses. Apple eventually started calling this "Memory Pressure" and gave it a simple traffic light system. RAM is doing you no good if it's free, might as well use it to cache if there's not a hard requirement for it right that moment.

I strongly believe Word peaked with Word 4.2 on the Mac - System 6, 1Mb RAM. There are those who would argue 5.1a on the Mac because it included envelope printing, but it was much, much slower and needed more like 2 or 4Mb.

Then they unified the version numbers across the platforms and moved to this pcode stuff in v6. This was so bad and so slow on the Mac that they actually issued an apology for it. Things have gone downhill since then, and v6 was released 1994.

This is so true, so true.

And it's not even US specific. In the wake of the Ukraine war, German parliament voted to give itself 100 billion of additional taxpayer money (i.e. debt) to spend on defense. Recently a report came out of all the money spent so far, 90% did not go towards the intended purpose.

Why any of the jokers in charge of our governments are still not in jail baffles me more and more every year. Oh yes, it's because they make the rules, sorry, my bad.

That's what campaign donations get you, if they are large enough.

This is why congress occasionally bullies the big tech companies. We all think they might want to have some regulation or to punish them. Oh sweetie... they're saying "nice company you have there... would be a shame if something happened to it..."

The best time to leave github was when the evil empire bought it. The second best time is now.

Seriously. Anyone who thought MS wouldn't fuck it up in the same way they fuck up everything they touch can't be helped. It's Microsoft for crying out loud.

A year? I've regularly written that much in a month, and sometimes in a week. And, counter-intuitively, its during those sprints when I'm pumping out thousands of lines per day that I write the code that turns out to be the highest quality, requiring the fewest number of bugfixes later. I think it's because that very high productivity level can only happen when you're really in the zone, with the whole system held in your head. And when you have that full context, you make fewer mistakes, because mistakes mostly derive from not understanding the other pieces your code is interacting with.

Of course, that kind of focus is exhausting, and you can't do it long term.

By focusing on the structure, not the details. The LLM and the compiler and the formatter will get the low-level details right. Your job is to make sure the structure is correct and maintainable, and that the test suites cover all the bases, and then to scan the code for anomalies that make your antennas twitch, then dig into those and start asking questions -- not of product managers and developers, usually, but of the LLM!

But, yeah, it is challenging -- and also strangely addictive. I haven't worked more than 8 hours per day for years, but I find myself working 10+ hours per day on a regular basis, and then pulling out the laptop in bed at 11 PM to check on the last thing I told the AI to do, mostly because it's exhilarating to be able to get so much done, at such high quality, so quickly.

That's a valid point, though right now while they're facing competition from startups the dealerships do provide them with a moat that they want to preserve. If/when the startup threat is gone, the automakers will go back to hating the dealerships.

I think people forget how everyone laughed at Tesla because everyone knew that starting a new car company in the United States was impossible. Now we also have Lucid and Rivian. Maybe someday Aptera will manage to get off the ground. This is a novel situation for American carmakers.

They had to say it that way, because the more accurate statement is that the dealership law unfairly advantages existing automakers. It's not about the dealerships being good or bad, it's about the fact that setting up a dealership network takes a lot of time and money and requiring it is a good way to keep new competition out.

The correct term is "regulatory capture". Private businesses use the power of the state to protect, subsidize or otherwise benefit them and harm competitors and potential competitors. It's extremely common and the more pervasive the regulation is, the more common it is. Red tape and government procedures benefit entrenched players who have built the institutional structures and knowledge to deal with them.

This isn't to say that all regulation is bad... but a lot of it is. There was never any consumer benefit to banning direct sales. All regulations should be thoroughly scrutinized for their effects on the market, direct and indirect.