The Exchanges

Q OpenAI part of the history. Exactly. So then you leave OpenAI in September, 20, 22. And I would say in Silicon Valley, the two hottest companies at the time were you and Langchain. What was that start like? And what did you decide to start with a more developer focus, kind of like a, AI engineer tool rather than going back and to do some more research on something else.

A Yeah. First, I'm not a trained researcher, so going through OpenAI was really kind of a, the PhD I always wanted to do. But research is hard. You're digging into a field all day long for weeks and weeks and weeks, and you find something, you get super excited for 12 seconds, and at the 13 seconds you're like, oh yeah, that was obvious. And you go back to digging. I'm not a trained Like formally trained researcher, and it wasn't kind of a necessarily an ambition of me of creating, of having a research career. And I felt the hardness of it. I enjoyed a lot of like that a ton, but at the time I decided that I wanted to go back to something more productive. And the other fun motivation was like, uh, I mean, if we believe in AGI and if we believe the timelines might not be too long, It's actually the last train leaving the station to start a company. After that, it's going to be computers all the way down. And so that was kind of the true motivation for like, uh, trying to go, uh, to go there. So that's kind of the core motivation at the beginning of personally. And the, uh, the motivation for starting a company was pretty simple. I had seen GPT-IV internally at the time. It was September, 20, 22. So it was pre-chat GPT, but GPT-IV was ready since, I mean, I'd been ready for a few months internally. I was like, okay, that's, that's obvious. The capabilities are there to create an in…

AI assessment note: “thesis was there's probably a lot to be done at the product level to unlock the usage.”

Q That kind of personal automation, would you say it's kind of like, um, LLM Zapier type of thing? Like if this, then that, and then, you know, do this, then this, this is so very, you're programming with English.

A So you're programming with English. So you're just saying, oh, you do this. And then that you can even create some, some, some form of API. As you say, when I give you the command X do this, when I give you the command Y do this and you describe the workflow, but you don't have to create boxes and create the workflow explicitly. It's just need to describe what's Are the tasks supposed to be and make the tool available to the agent? Tool can be a semantic search. The tool can be querying into a structured database. The tool can be searching on the web. Um, and obviously the interesting tools that we only starting to scratch are actually creating external actions like reimbursing something on Stripe, sending an email, clicking on a button in the admin or something like that.

AI assessment note: “you describe the workflow, but you don't have to create boxes”

Q And I noticed that in your language, you're very much focused on non-technical users. You don't really mention API here. You mention instruction instead of system prompt, right? That's very conscious.

A Yeah, it's very conscious. It's a mark of our designer, Ed, who kind of pushed us to create a friendly product. I was knee deep into AI when I started, obviously, and my co-founder Gabriel was, uh, was at Stripe as well. Uh, we started a company Glazer that got acquired by Stripe 15 years ago, was at Alain, a healthcare company in, in Paris after that. It was a little bit, uh, less so knee deep in AI, uh, but, uh, really focused on product. And I didn't realize how important it is to make that technology not scary to end users. It didn't feel scary to me. But it was really seen by head, our designer, that it was feeling scary to the users, and so we were very proactive and very deliberate about creating a brand that feels not too scary, and creating a wording and a language, as you say, that, that really tried to communicate the fact that it's gonna be fine, it's gonna be easy, you're gonna make it.

AI assessment note: “Yeah, it's very conscious. It's a mark of our designer, Ed”

Q Yeah. Do you see in the future products offering kind of like a simulation environment the same way all SaaS now kind of offers APIs to build programmatically? Like in cybersecurity, there are A lot of companies working on building simulative environments so that then you can use agents like Red Team, but I haven't really seen that.

A Yeah, no, me neither. Uh, that's a super interesting question. I think it really going to depend on how much, uh, because you need to simulate to generate data, you need to train data to train models. And the questions at the end is, are we going to be training models or are we just going to be using frontier models as they are? On that question, I don't have a strong opinion. It might be the case that we'll be training models because in all of those AI-first products, the model is so close to the product surface that as you get big and you want to really own your product, you're going to have to own the model as well. Owning the model doesn't mean doing the pre-training. That would be crazy. But at least having an internal post-training realignment loop makes a lot of sense. And so if we see many companies going towards that over time, Then there might be incentives for the SASSs of the world to provide assistance in getting there. But at the same time, there's a tension because those SASSs, they don't want to be interacted by assistance. They want it there by agents. They want, they want the human to click on the button. So that's an interesting thing.

AI assessment note: “Yeah, no, me neither. Uh, that's a super interesting question.”

Q No, no, no, I know. Of course they say it's true, but like also how well is it going to go?

A So I'm not, I'm not talking about deflecting the customer traffic. I'm talking about building AI on top of Salesforce and Zendesk, basically, if I understand correctly. And all of a sudden, your product surface becomes much smaller because you're interacting with an AI system that will take some actions. And so all of a sudden, you don't need the product layer anymore. And you realize that, oh, those things are just Database that I pay a hundred times the price, right? Because you're a post S-curve company, and you have tech capabilities, you are incentivized to reduce your costs, and you have the capability to do so, and then it makes sense to just scratch the SaaS away. So it's interesting that we might see kind of a bad time for SaaS in post-hyper-growth tech companies. So it's still a big market, but it's not that big, because if you're not a tech company, You don't have the capabilities to reduce desk cost. If you're a high gross company, always going to be buying because you go faster with that. But there's an interesting new space, a new category of companies that might remove some SaaS. Yeah.

AI assessment note: “we might see kind of a bad time for SaaS in post-hyper-growth tech companies.”

Q What do you need to show as incremental results to get funded for further results?

A It's an imperfect process. If you're working on math and AI, obviously there's kind of a prior that it's going to be aligned with the company. So it's much easier than to go into something much riskier, I guess. You have to show incremental progress, I guess. It's like you ask for a certain amount of a compute and you deliver a few weeks after and you, so you demonstrate that you have a progress. Progress might be a positive result. Progress might be a strong negative result. And a strong negative result is actually often much harder to get or much, much more interesting than a positive result. And then it's, uh, it's, it generally goes into, as any organization, you would have kind of a people finding your project or any other project kind of a cool and fancy. And so you would have that kind of phase of growing up computer allocation for it all the way to a point. And, and then maybe you reach an apex and then maybe you go back to, uh, Mostly to zero and restart the process because you're going in a different direction or something like that. That's how I felt.

AI assessment note: “Progress might be a positive result. Progress might be a strong negative result.”