Azeem Azhar

So when I looked at this data after your previous economic report, the way I took this away was human employees like you and I

We think of ourselves and what our job entails in the round.

And so when we get a superpower tool like Claw.ai, we think about how we do that job better, make it more interesting, make it more challenging, get through not just our must-do list, but our coulds and woulds where the real value and enjoyment may lie.

Whereas it turns out that companies actually see their employees as bundles of tasks where you can discretize them and you don't ask the question, what does Peter really need to kind of manifest himself fully as the head of economics at Anthropic, which is what you think of about your job in your head?

They think,

What are the 17 tasks Peter does and which are the ones can we automate discreetly?

And I felt it actually said something a little bit more about that different perspective, the relationality that an individual has with their own work and the honesty with which their boss actually thinks about that individual.

Well, I mean, what we're doing there is we're going back and we're playing through what happened with previous waves of general purpose technologies and automation.

And I think the observation you made that maybe what people do on the chat interfaces is a little bit of an early warning about, or early signal rather than warning, about what you can do when you start to automate it.

Because I think

One of the observations would be that if all you do is automate a task-like data entry that had fundamentally been gated by the marginal value of the nth item that was entered into data by a human who you're paying per hour, you had already taken a scarcity mindset to that, and you were only going to look at the minimal amount of data that you needed to achieve the outcome.

Now, if that cost drops by a factor of, say, 1,000,

you're not just talking about looking at five more customer records.

You're talking about looking at a thousand times more, which is a regime shift, right?

Even if the fundamental kind of economic organizational model remains the same, a thousand X is a regime shift, which means new behaviors emerge.

And some of the things that I see when I talk to businesses is, you know, a large part of them are doing the sorts of things we've discussed by automating data entry.

But what they've done is they've automated the horse.

They've automated the fact that they used to look at 10,000 pieces of data a day by humans and now they look at 10,000 by machines rather than saying, well, what if we looked at 10 billion and how would that change our business downstream from that?

I mean, you know, I feel that there's something there.

Oh, wow.