The Exchanges

Q So, uh, what attracted you to join these companies?

A Absolutely. Um, I think, um, different stages of my life, I think different things were more attractive. Um, starting off with Nvidia, I think what I was really attracted to was just the vision of the founder, vision of Jensen, and the reputation around Nvidia. Keep in mind that this happened Back in 2015. So this was well before Nvidia became what it is today. Um, back then, um, Nvidia was extremely prestigious in the semiconductor world, and it was starting to show a lot of, um, possibilities, both for AI workloads and for Bitcoin mining. But I think what attracted me was how futuristic the company was, the kind of stuff they were doing. And the vision of the founder. The second thing which attracted me was I, I knew a bunch of folk who were already working at NVIDIA. So the culture was something which was extremely attractive to me. NVIDIA is one of the few companies in the Bay, um, where the average employee tenure is probably closer to double digits than single digits, at least when I was working. Uh, primarily because of the loyalty which the leadership team And Jensen engenders, uh, in the entire workforce. So that's kind of what attracted me to NVIDIA. When I think about Meta, that was a bit later, and I, these, this opportunity came across where I would get to work on integrity, which was something which was fascinating for me, uh, because of everything which happened …

AI assessment note: “starting off with Nvidia, I think what I was really attracted to was”

Q Now you're running your own startup. Do you think the intensity that you are running your own startup was the same intensity across these three organizations?

A Yes, I think so. Maybe not in the same dimensions. Um, I think intensity, multiple different dimensions, but I would argue that The common thread among all these companies are incredibly ambitious, incredibly smart people, all trying to solve very challenging problems, um, and be the first at doing it. And so just that intrinsic competition would make sure that We were really, really driving ourselves, uh, to do the right thing and succeed. In some ways that's common to, you know, what's happening now at Feature League, where I would say that, um, it's a similar thing where you're kind of driven to succeed. Um, but I think there's more dimensions beyond just that when you're trying to run your own startup.

AI assessment note: “Yes, I think so. Maybe not in the same dimensions.”

Q And coming back to synthetic users, you know, uh, how big do you think the market for synthetic users is?

A So Vishal, let's think about it from the perspective of synthetic humans, as opposed to just users, because I want to cover Not just people who are currently using your product and mimicking their behavior, but also potentially future, right? And, uh, I, I think I was recently seeing this podcast by, or this video by a A-sixteen Z partner, where he referred to this as social simulation. And he talked about this being as the next frontier in AI and machine learning. We're being able to predict images. We've been able to predict text. Now can we predict human behavior or the way humans think? The applications are enormous, like we obviously started with market research, but even the word market research or user research is so loaded, you can think about something as narrow as usability, but you can also think about which ad copy Will work well with this kind of human. Um, you can think about what kind of user interface flows work well with this particular human at this point of time. And when you think about it in that way, the applications can range from product building all the way to government policy making and politics. As an example, how do I, if, uh, you know, I'm in an election, how do I ensure that I am giving the right message to the plurality of my constituents so that they are more impelled to vote for me? Or if I'm in policymaking, how do I ensure that the policies w…

AI assessment note: “I think the market is tremendously large.”

Q And apart from the above companies that we discussed, right? Name three companies that you respect the most in the AI world. And what, what, how do you think that they win in distribution? And they can be Cursor, Windsurf or anybody else?

A When I think about AI companies I admire, I, I still think of Nvidia as one of the biggest AI companies, primarily because without a lot of what they do on the bare metal, a lot cannot be achieved on the top layers. Uh, second big company, which I admire, and I think the reason why they win is because they're literally building for the future. Um, they are defining the future market as opposed to reacting to the market. A second big company which I think is amazing in the AI world is, um, um, all the, like DALI, the specific product from OpenAI. Why do I talk about DALI is the wow factor of creating images. Made AI so easy to access for the average person that I think, uh, it's brought on a lot of more people into using these kind of tools. So I think the way they went about doing that was just amazing. The, if I think about a third company which is really, really good at this, I don't think this company exists, but I think there is going to be a company in the future which generates, you know, media content, hyper-personalized to the person, hyper-dynamic, based upon the context of the viewer. I don't think that company is there today, but maybe somebody is already building up on it. I think that would be a company which would be very interesting for me. In terms of its potential impact. Um, yeah, those would be the three things I would think of.

AI assessment note: “When I think about AI companies I admire, I, I still think of Nvidia”

Q And this is for other founders, right? What helped you in your capital raise journey? Your pre-seed was oversubscribed. You, you get regular VC inbounds, which you're not able to cope with.

A I think, um, Uh, I was just, uh, uh, you know, uh, writing a letter to my team the other day. Um, the focus should be on building a business, building a product, and solving a value. It should not be on purely What your valuation is, um, you know, and, and raising money. When, I think VCs are a really smart group of people in pattern recognition, and when they see something working, they will come to you. But on the flip side, if suppose you're focused on just attracting the money, I think you're kind of getting distracted from the actual art of building a business. Of solving a real customer problem, which is monetizable. And that means that, you know, you are less attractive, uh, you know, to a lot of investors. That's my thesis. Again, I'm so early in this game. Maybe my thesis is completely wrong. Uh, it's helped me the first time. Let's see whether it helps me, you know, in the future rounds. Uh, but like, I have a lot of conviction that If I can build something which is very valuable to customers, if I can build a solid business, then the money will come. You know, there will be VC interest because there are a lot of proof points. I've de-risked a lot of things for VCs. Um, whereas if I'm just focused on a narrator and it's a hollow shell, VCs are smart enough to look through the hollow shell. And so I think that's where you'll churn out. Uh, like a lot of stuff. So I wou…

AI assessment note: “the focus should be on building a business, building a product, and solving a value.”

Q So how do you build a world where, let's say maybe 10 years from now, both synthetic agents and AI agents, synthetic humans and AI agents coexist?

A I would imagine there could be a world in the future where, um, even when I think about Feachali right now, there are aspects which I want it to happen from a workflow automation perspective constantly. And AI agents fit in well, very well there. And then there are aspects where I want to mimic human behavior, where synthetic humans fit in. I could also see a world where synthetic humans kind of use AI agents to automate some of their work, uh, you know, going forward. So I would always see the, the, the two things are kind of intersecting with each other, parallel with each other. Um, from a technological perspective, there's a lot of overlap, uh, but applications is of course this.

AI assessment note: “synthetic humans kind of use AI agents to automate some of their work”