OpenAI prioritizes adoption and compute over near-term cash flow

Transcript

From the transcript TBPN publishes with the episode.

1. 1:44:52

   I'm kind of smiling to myself because when anyone normally says talk to me about non GAAP metrics, I can see like most of people's eyes roll back in their heads. I live for non GAAP metrics. I would love to do that. Please. Look, I think in a CFO seat, first of all, it's really important to think about input metrics and output metrics. Mhmm. And things like revenue, which is a GAAP metric, as well as a non GAAP metric, they're very laggy.

2. 1:45:14

   Yeah. Like, if you're spending your whole time focusing on the revenue number Mhmm. In an operator seat, like, you are completely missing what's going on with the business. So I push my team a lot to get out of kind of ultimately what the P and L looks like, and I'll come back to it though, and go way upstream and say, what are the true input metrics that tell us about the health of our business? And so I think it does start with that funnel of monthly actives to weekly actives to daily actives.

3. 1:45:40

   Because we do I mean, our mission is literally AGI for the benefit of humanity. So we know how many billions of people live on the planet. The fact that we're starting to be able to talk in billions and percentage of the world's population blows my mind. Today, 85% of our users are outside The United States. And I love that stat. And in fact, if you go look at where where are the big populations of users, it just tracks global population. Right? It's countries like India, Indonesia, Brazil, Vietnam, like The Philippines. Like, go to anywhere that has big population. The US too, of course, but that will be your tracker.

4. 1:46:20

   So that's kinda number one when I think of an input mac metric. From there, on the consumer side, you're right. Things like time and app, I've actually always had somewhat of a love hate affair with. But I think in this case, because we're giving people intelligence, teaching them how to use that, I actually think, is where time and app does become important. And one of the things we've really seen with ChatGPT are people are spending more time with it.

5. 1:46:46

   Now, we balance that with things like mental health and so on, making sure that we're not creating bad things like we might have seen in prior eras of computing. But I think we're just getting started on that front. Beyond that, like, when we go into areas like the API, I don't look only at usage. Right? I can look at tokens per minute as a usage metric. But I look at things like latency. I actually try to look at the elasticity of demand. We know that developers want performance. They want intelligence. But they also want to make sure the API is always up, and they want price.

6. 1:47:18

   And they're often willing to trade across those three things. It's a linear program, depending on what your use case is. And so I think it's important that we are offering things to developers that allow them to optimize across those three metrics, for example. So that's kind of your input metrics. And again, I could wax lyrical, but I won't. But then you go to what you really asked. So investors on the other side, right, they want to see a P and L. They're like, I want to be able to compare you to other companies. Want to be able to create maybe a DCF. Like, I want to think about fundamental valuation for a company if I'm going to invest in it.

7. 1:47:54

   And so today, what I really try to push investors on is we are not a company that should be optimizing for free cash flow today because there's just too much opportunity. Yeah. Like that point about compute, we have to make a decision on compute today with an eye to what we're gonna need in two to three years. Because data centers don't just spring up overnight. Like, they're not mushrooms. They literally take time and the effort.

8. 1:48:19

   Getting there. Failed at, frankly, I would say is three years ago, we didn't have enough foresight to say how big could chat cheap petite because it didn't exist. Yeah. It's just a shame on us if we keep doing that over and over. So there can be a bit of a mismatch between our belief on revenue because we don't yet know the product versus the input, which is the cost today on compute. And so getting investors comfortable with the fact that there's probably losses for a period of time.

9. 1:48:47

   I say probably because ChatGPT, just generally, the revenue models continue to surprise to the upside. But at least for now, we should be in big investment mode. And then you kind of said it well, like, as companies mature, you move to more gap metrics. Right? If you look at, you know, the large, the Mag seven, many cases, they're looking at, like, real gap net income. So the whole way down to the bottom of the p and l. We're just not there yet. And we should take advantage of that advantage because we can invest as a private company.

10. 1:49:17

    How do you think about timing fundraises? From my understanding or or or rumors, the last, you know, the most recent financing was very oversubscribed and at the same time, you're still committing to CapEx in the future that is a multiple of current, you know, the current run rate. And so you in the CFO seat, I'm sure there's you're you're trying to find this balance of like what does the business need today while, you know, not diluting the company, you know, too much knowing the the sort of growth rate of the business.