TITV One Year Anniversary Show

**Akash Pasricha** (0:01)
Welcome, everyone, to The Information's TITV. The information was first to report just moments ago. The information reported exclusively...
Welcome, everyone, to this special edition of The Informations TITV. My name is Akash Pasricha. It is Tuesday, July 14th, and we are coming to you from our San Francisco office, where we are celebrating the one year anniversary of our show, and what a crazy year it has been. When we first started this show, there was no such thing as fable. There was barely any conversation about TPUs or Tranium. SpaceX and X and XAI were all still separate private companies. There was no open claw. No one cared about AI margins, and orbital data centers were very much still a distant dream. Some things never change.
This is our 250th episode. And today, rather than looking back on it all, we're going to look ahead to what we think will be the big teams that are going to dominate our next 250 shows. We're going to start with a conversation about what the AI company of 2030 is going to look like. We're then going to take a deep dive into the tech itself with a discussion on open source and also all the challenges that AI researchers still haven't solved. We're also going to talk about the big questions facing physical AI and the space industry. And we're going to end with some healthy debate with two of our top editors. We've got some great guests coming on. The CEO of Decagon is joining us. We've got a top robotics founder coming on. The co-founder of Robinhood, who is now building Cowboy Space Corporation, is joining us in a bit.
But I want to start with two of my favorite guests from the past year. Jeanne Grosser is COO at Vercel. She is on the front lines of the AI coding craziness. Tomasz Tunguz is a general partner at Theory Ventures. He is one of the most frequent guests on our show. Welcome to the both of you. It is so great to have you here.

**Jeanne DeWitt Grosser** (2:02)
Thanks for having us.

**Tomasz Tunguz** (2:04)
It's good to be here.

**Akash Pasricha** (2:05)
So I want to start, Jeanne, with a question about what the AI company of 2030 looks like. You have such an interesting perspective on this because you were at Stripe for nearly a decade. You built an entire go-to-market team over there, and now you're building an AI native go-to-market team. So what does the team look like nowadays? How is it different from Stripe?

**Jeanne DeWitt Grosser** (2:28)
There's a lot of places where we're getting a lot of leverage out of AI. So I would say the mix of roles within a company is shifting. As an example, we obviously are growing headcount still, a high-growth company, but within go-to-market, the percent year-on-year growth and headcount by sub-functions was meaningfully different at the start of this year. So an example, sales development, that we grew but less than our account executives. Typically, those might grow more in tandem. We've actually been able to take our support headcount down year-on-year, despite more than doubling the total number of customers that we have.
And actually, our H1 first half of the year ends at the end of this month. And so we're sort of doing an H2 replanning because it's only been five months, but our plan already is kind of just feels like ancient history. And one of the provocations G always has is like, we can't get this company to have more than 1,024.

**Akash Pasricha** (3:27)
G is the, this is Guillaume the-

**Jeanne DeWitt Grosser** (3:29)
Yeah, Guillermo.

**Akash Pasricha** (3:30)
Guillermo.

**Jeanne DeWitt Grosser** (3:30)
Founder CEO. But his provocation is, Vercel can never employ more than 1,024 people, which is 2 to the 10th.

**Akash Pasricha** (3:38)
And how many people does it employ right now?

**Jeanne DeWitt Grosser** (3:40)
Eight something. So-

**Akash Pasricha** (3:42)
We're getting there.

**Jeanne DeWitt Grosser** (3:42)
We're getting there. So we have to figure it out.

**Akash Pasricha** (3:44)
So are we replacing all SDR salespeople with AI? What does this look like?

**Jeanne DeWitt Grosser** (3:49)
No.
I mean, we're getting meaningfully more scale.
And so both more productivity because the humans themselves can do things much more efficiently, and then actually more productivity due to better outcomes, because there are many ways in which we're now getting AI to sort of be a 99th percentile performer 99% of the time, whereas if you have a 30% sales development function, you're going to have a bell curve, if you will, on how they perform.

**Tomasz Tunguz** (4:15)
It is really interesting. Those were the first two use cases in AI, right? Like automated sales and automated customer support. So you're really starting to see a lot of success from it.