Azeem Azhar

We've taken a big step back.

You've got to run around and get all your tacit knowledge written down and stuck in markdown files.

I mean, it's a really fantastic point and it shows how quickly the field is moving because no one was saying this a couple of years ago, right?

And your report came out before Claude Opus 4.5.

And Opus 4.5 has really changed the world, at least for certain early adopters.

It's particularly good at coding, for example, and it has absolutely cut into my sleep.

You can see my URA scores just collapse over the last month.

And I'm getting up at 4 a.m., I'm firing off a bunch of parallel agents, then I'm going for my walk, and then I'm coming back to see what they've done.

This year, we're recording this on January the 15th, I have written, or rather I've commanded Opus 4.5 to write about 10,000 lines of code per day.

So I'm up at about 150,000 lines of code according to some measure that I did.

I'm just curious about how that kind of capability jump changes the way you think people might behave based on what you had seen in this very, very extensive empirical study you conducted.

This is such an important point.

So let me go back to before Opus 4.5.

So what you looked at in the report, one observation was that when people used the API, the system could do a 3.5 hour task, long task.

In other words, a task a human might take 3.5 hours to do with a 50% success rate.

But if they were using Claw.ai, that 50% success threshold was a 17-hour task, which is two workdays in Europe and, of course, one workday in the Bay Area.

I'm just quite curious about a few details there, right?

So what is a 17-hour human task and how much time were the humans having to do it?

Because it's really different if I just, you know, bark a command at Claude, who will rid me of this turbulent priest?

and it goes off and does it for 17 hours versus I have to sit over the machine and every 30 minutes give it feedback.