But the model names are linear by price.

I think the names are more of a reference to price. Luna is always cheaper than terra which is cheaper than Sol which is cheaper than Astra (for the same model number).

But you never heard someone say "you should still code in assembly so you can understand what your compiler is doing".

Is this more like case one or case two? Will it matter if you understand in a few years?

Or more people are using harnesses that do what openrouter does so they don't need it anymore?

Or they are using other GPU providers directly to run their open source models?

I don't think this data is conclusive. It's a very unique subset who are using openrouter.

We also didn't have the advantage of good whisper models so voice input wasn't a thing. I feel like that hurt adoption as well.

With AI, everyone now gets to act like a PE. Your job is to design, the AI builds like the junior engineers. Then you review their work. You may never understand the details, and that's ok, as long as you know the main ideas and where to ask for the details (in this case the LLM instead of a human).

So we built an app that did it for you, just like yours, using machine learning and AI (and some simple rules based on due date and expected time to do the task).

Turns out people don't want to pay for that, even at $2/mo. We even had group features, so that a parent could put tasks on their kid's list, or a group of students could use it for a group project, or a team at work could use it to coordinate team tasks.

We also had templates -- tell us you're a single person who lives alone, and we would auto-add tasks like washing the sheets and cleaning the toilets. Or we could add a daily exercise routine or even a daily bible study if you told us you were a religious Christian.

Feel free to take these features. I hope you have better luck than I did.

2. I have an M1 chip and I'm not sure it's supported.

3. ChatGPT can open both browers, not sure if Safari plugin builder can

But if it does all those things, great. My point was more that plugins won't be a problem anymore because AI can build them.

Safari is always the best on my Mac, but my complaint has always been the lack of plugins.

But just now I ported one of my favorite plugins from Chrome to Safari using ChatGPT. I told it I already have it installed in Chrome so it can get the source code there, and then told it to port it and install it.

After 20 minutes and few bucks in tokens (estimated, I actually used my 6% of my $20/mo plan), I have Session Buddy in Safari.

So maybe the plugins aren't a problem anymore...

If they're not, they should be.

> Will you still say it's great when it is the society as a whole?

Yes. A world in which menial tasks are taken care of by computers is a wonderful idea.

The important part is that our society needs to transform around that. If all capital accrues to the owners of the AI, then we'll have a problem. If we remake society so that everyone shares in the success, that's a very different idea.

But have you considered how that is Donald Trump/Joe Biden's fault?

/s in case it isn't obvious.

That's what school is for. For the last 150 years we've automated a bunch of things, and then we send people to school to learn how those automations work, so they can make better automations.

Maybe law school will have to be a year longer. Or maybe some forward thinking firms will have new associates check the work of the LLM to gain that experience.

Each time we move up an abstraction layer, people object, saying that nothing will work right if we move up that high in the stack. Give it time. I'll bet in 5-10 years, almost no one will look at code anymore, except in special cases.

We still have people who write in assembly, we still have people who write in C, mostly for performance reasons. Because you still need to be close to the CPU to get that last bit of performance. But in most cases, it doesn't matter. It doesn't matter if the LLM makes bad code if it works and passes all the tests.

Granted, this is the first time we're going from deterministic to non-deterministic, but is it really? Large scale distributed systems are already non-deterministic. They create inputs and situations that programs aren't designed to handle all the time. What's a little more chaos? :)

For example, redlining an OEM agreement with my vendor. They pretty much all use the same template, and the objections are always the same. I tried using Claude first, and even my lawyer was impressed that it found things they missed. Then I used Claude to redline that type of contract and the other side said "your lawyer was surprisingly thorough". I had my lawyer do the final check, but saved a bunch of money doing the first three rounds with Claude instead. And my lawyer basically just said "looks good to me" by the time they reviewed it.

Or even writing a simple will or estate document.

It seems like LLMs are great for the kind of generic work you'd usually pawn off to a new associate or paralegal, but not for the important things that partners usually do.