Azeem Azhar

Whereas if you look at the interactions on claw.ai, the task mix is much more around augmentation, but it's also

likely to result in more success.

So these aren't just two channels.

They're two different stories about how AI integrates into the workplace and the future of work.

Which one is more indicative of what the future is?

We're going to investigate all those ideas like multi-step and over time.

I'm going to be a bit cheeky.

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.