"The CEO Must Be the Chief AI Officer"

**Pedro Franceschi** (0:00)
You wake up, whatever problem you have in your life, why can't you solve it with AI? And just start there. I think the CEO needs to be the chief AI officer.
It's not an engineering team thing, it's not a product team thing, it's like, you have to understand the bounds of the technology better than anyone. I think a good proxy for how to spend your time is, what are things that only you can do and the models cannot do? You have to sort of refound the very concept of what the company's self-identity is.

**SPEAKER_2** (0:32)
Welcome back to another episode of The Lightcone. Today, we're joined by Pedro Franceschi, co-founder and CEO of Brex.
Pedro started Brex in the YC winter 17 batch and built it into one of the most important fintech companies of the last decade. He's here today because Brex has gone deeper on AI than almost any enterprise company we know. And Pedro's own AI setup is so compelling that when he came to YC for lunch, it sent our entire team down a rabbit hole of building on their own. So Pedro, welcome to the Lightcone.

**Pedro Franceschi** (1:06)
Thanks for having me. Excited to be here.

**SPEAKER_3** (1:08)
Thanks for changing our lives. Yeah. Oh, God.

**Pedro Franceschi** (1:11)
That lunch.
I'm like, I think the model company should be sponsoring me for it. The token consumption increase we supposedly generated on that lunch. That was the precursor of G-Brain, I guess.

**SPEAKER_2** (1:23)
I was still working on G-Stack. I was still a 2013 Web 2 engineer who time traveled instantly to the AI tools of January 2026
I was probably half a million lines of Rails code in, and I could create a G-Stack because of that to help me make a software factory. Yeah. Then after I met you, I realized everything is about freeing the claw.

**SPEAKER_3** (1:47)
Free the claw. I knew you were going to say that.

**SPEAKER_2** (1:49)
And then-

**Pedro Franceschi** (1:50)
And give it tokens. Yeah.

**SPEAKER_2** (1:51)
Well, no, I mean-

**Pedro Franceschi** (1:52)
Let it rip.

**SPEAKER_2** (1:53)
The craziest thing was realizing what I had gotten wrong that I think, actually, most people in software are still getting it wrong, is they've been treating the LLM like this very precious thing that's very expensive.

**Pedro Franceschi** (2:07)
Yeah.

**SPEAKER_2** (2:08)
So as a result, you have to literally put the agent inside a Foxconn factory.
It's like, can you imagine? I mean, that's what the half a million lines of Rails code was for me. It's like, no, no, no, I need to control what the LLM sees because it's about really, really like, I only want the context from here. And let me write all the if statements to make sure like a Foxconn engineer, you're waking up at 6 a.m. and if you don't, you're going to get electroshocked. I mean, this terrible thing that you do to agents. Yeah. And they want to be like at the Esalen Institute and that's what OpenClaw is.

**Pedro Franceschi** (2:45)
Exactly.
And it's funny because I feel like every single good AI product you've used is an agent loop with tools. That's it. There's no... you try to over engineer the harness and do certain things, but at the end of the day, it's skills tools and a model. Like there's not really much else.

**SPEAKER_2** (3:03)
Maybe we start earlier because one of the things we'd love to kind of get down as a part of lore is like, how did you get so AI-pilled and like all the way to the edge?

**Pedro Franceschi** (3:14)
Well, I'll tell you my encounter with LLMs, which was... So I remember in the pandemic, there was someone gave me an API access to GPT-3 and I was playing with it and I was like, okay, this is really cool.
There's something here that could be special. But it was the kind of thing that was like, yeah, it feels like a research project, the kind of thing that Google used to release and you play with it for 10 minutes and you stop. ChatGPT came out and I think everybody was sort of interested in it. Where I think it got interesting was when you started to see reasoning models and of course, tools, but I think everything else was sort of a blip until December. And the way I describe it to my team is like, you know, electricity was invented in December.
And I think electricity was Opus 4.5 and sure, Opus models and OpenAI models got better and better since then. But to me, that was the tip of the spear where you could say, yes, coding harnesses actually work. And you know, cloud code existed for probably a year before, but it wasn't that valuable yet. And I remember during the holiday break, I was playing with it and it was pretty shocking, probably some reaction that everybody here had. And I think the question becomes, if you think about, you're standing, looking at 200 years of history, and then you imagine you are, we're now in May, you're five or six months after electricity was invented. And we'll see if we're still playing with candles and questioning, what can you do with candles and fire? And you know, like-