Jesse Zhang

That's why it's exciting.

That's why everyone's so focused on it.

One thing you can do then is you can just map out the spectrum of how much that human labor currently costs.

So with customer service, it's generally outsourced already, especially for the tier one, tier two type inquiries that AI is now handling.

It's generally not folks that are super highly paid.

And then on the other end, it's engineers, which is the most highly paid people.

The one way to think about it is that AI use case will start eating the spectrum of both ends.

And the reason why is that because engineers are the highest paid, they have the sophistication to like really leverage it well.

And like AI just gives them so much leverage.

I mean, there's other factors as well.

It just happens that coding is tokenizable and the models are really good at it.

That's one way to think about it.

I don't know any company that's like, hey, I would like to let go of a bunch of my engineers because now I have coding agents.

There's infinite engineering work to do.

So you're just augmenting them.

On the other end, it is more of the replacement sense.

You have a large BPO and that's costing you a ton of money.

And it's also like a really high operational thing to maintain because you have to hire people all the time.

There's a ton of churn, you need to train them, you need to QA them, you need to make sure that nothing goes wrong.

So AI is really valuable there as well because the work is easier for the AI to do.