I know the Leopard era design is having a bit of a retro cool moment right now (frutiger aero) but for me its all about that pre-Leopard Aqua. Something very bright and friendly about that design language where the Leopard era feels a bit dark, moody, and dusky. Bordering on chiaroscuro. Especially when you compare classic Aqua to like the classic Windows look which while coming off as corporate felt like it had a precision to it (at least to my kid brain).

I have to say my hot take is that I actually kinda like Liquid Glass. It feels like a bit of a throwback to that era and dragging objects behind transparency to see the refraction was the first time in a long time I've ever just been transfixed with just playing with a UI detail. Especially since I use the Dock as bootleg taskbar (undock everything so the only things in it are the open applications and autohide), when it does pop up its fun to see everything bend around.

People have to come to grips with the possibility that a technology can be extremely impressive but be a bust in utility. I'm not saying that's what AI is, I'm saying that nobody actually knows.

So porting should be perfect conditions for an AI agent. It has the testing suite. It has the original implementation. Hell, it can A/B the original with its working copy and attach the original to a debugger.

So yeah I dunno. I guess despite some people's rhetoric on this site we shouldn't underestimate how difficult these tasks are "in the real world" (as opposed to like a game port which doesn't have real money on the line so far). And it is kind of a miracle these tools can even get in the ballpark and fool a lot of people.

My experience is agents really need cheap easily runnable third party ways to validate their work and stay on track. This usually means compilers and test suites but it can also mean visual checks (like all those vibecoded game ports flooding feeds right now). Of course, these things are useful for humans too. Tightening the feedback loop is always good. But for agents, the lack of feedback can be catastrophic. Better models can ward off catastrophe for longer but eventually without enough feedback, the errors not only accumulate but increase the chance of future errors.

To the points in the conclusion, humans still have the edge on dealing with vagueness and lack of clarity in goals. And we fill in the details of our goals in real time. In other words, the act of writing code feeds back into the other parts of building a program. Agents aren't like this, if they can see where they're going they can get there with remarkable tenacity but without it they'll get somewhere goal shaped fast. You can use agents to take big steps for you, but you're going to lose some fine touch.

Also most of the software that's really successful has some sort of lock in or network effect. The code is not the only valuable service being provided. To wit, there exist open source off the shelf solutions for hosting your own ridesharing, chat services, social networks, internet search, etc. Why isn't anyone pointing agents at those projects to spruce them up and run them? The network is what's valuable.

I mean we already live in a world where extremely valuable software exists right in the open for free. The actual artifact of code is in abundant supply and does not have a very high price. AI can't bring the price down lower than free.

But yeah the majority of startups don't have well thought out reasoning either. In the end, there's no substitute for hard work. AI can reduce the iteration time maybe.

The net effect is that the most likely scenario is if one big lab fails, they will likely all fail. Their revenues are all correlated.

To go to your dotcom comparison, the winner will be the ones picking through the assets that were written down by orders of magnitude and trying new products with the technology until one sticks to the wall. But I don't know if a dramatic crash is guaranteed either.