Entrepreneurial Thought Leaders (ETL)
00:33:12 · Michael Bernstein, Ravi Belani
[00:33:12] S2: Yes. I think there are a few things to consider. One is I think of the large language models that you would use day to day, whether that's Gemini or Claude or whatever, as having sort of like a gravity well. Right? People go to them automatically, they turn to them by default for everything. Right? So when people try to make, you know, here's my app, here's my design, here's my tool, We have to assume that people have a, like, a default toward the existing thing. They're gonna try to ask Claude or ChatGPT at first. So you have to be so much better that you can sort of hit escape velocity and not get pulled into the gravity well of the language model. [00:33:54] S1: Can you quantify that, or is there a litmus test to know if you're so much better? [00:33:57] S2: Yeah. Do people say wow? Honestly, they're not saying wow, it's not gonna last. [00:34:03] S1: Okay. [00:34:03] S2: I've seen so many things where it's like, it's better, but like we're creatures of habit. And so unless it's like truly deeply like fits into a different category in my head, meh. [00:34:20] S1: And the old heuristic was always if people actually tell other people unprompted about the product, then that's also the heuristic. It's something qualitative, it's not a quantitative I would [00:34:29] S2: say that there's one other bit here which is interesting, which is that I think we're entering an era where because people will turn to their agents by default, suddenly value means not only did you open my app, my web thing, but does agent use my MCP or other?
00:34:29 · Michael Bernstein, Ravi Belani
[00:34:29] S2: say that there's one other bit here which is interesting, which is that I think we're entering an era where because people will turn to their agents by default, suddenly value means not only did you open my app, my web thing, but does agent use my MCP or other? [00:34:48] S1: That's a good heuristic. Yes. [00:34:50] S2: Like is it providing something that is useful? Because that winds up for some folks being like an interesting metric of like usage. Yeah. Right? Are the questions that they're asking their agent, is the agent seeing fit to actually go query us because we are the ones who have the correct answers about that. [00:35:06] S1: That's great. That's a great way to think about it. I want ask one more question, I'm going do the signature questions for the class, which is you faced this classic dilemma when you were starting out about whether or not to build a horizontal platform that can simulate almost anything or focus narrowly on a single use case. Yep. And like you... Like test marketing. I was wondering if you could walk us through that decision because I think that's something that abstracts to a lot of founders on where to start.
00:35:31 · Michael Bernstein
[00:35:31] S2: Yeah. I don't think there's any magic here. Like, I think what I'll probably say is gonna echo what a lot of people would say. Something that's good for everything may simultaneously be good for nothing. Right? You have to find use cases that really stick, and then you can expand out from there. Now at the beginning when we were talking to people, everyone was like, oh, this is gonna be used just for message testing of market research, and I was privately hoping, like, I really hope this is wrong because while that's important, it's not the thing that gets me up. We're much more interested in societal simulations, simulation of really tough counterfactuals you know, around health and and public policy and things like this. But people don't know how to start there. Right? Like, we're, like, ask it anything, people are like, oh, right? They get completely stuck. But if someone knows, like they... They're already asking questions. They know how to uninstall, so to speak, the thing they're doing, or like install this next to it and say, oh, I get it. And then they can sort of explore the the new uses. So we started by, you know, as you even saw in the demo there, we try to guide people toward kind of use cases that we know work well, that are common use cases that people want to ask about. We try to help them not only land there, but also have conviction that this is the right place to ask that question. Mhmm. And then over time, people start... Like, once they do that, they're like, oh, well, I can also do this, and
00:36:53 · Ravi Belani, Michael Bernstein
[00:36:53] S1: they start expanding. Fantastic. I'm gonna start to ask the signature questions, but if you have a question, start thinking about queuing up if you want to. So Michael, if you're 20 years old today and starting and starting this company... [00:37:05] S2: I am 20. What are you talking about? [00:37:06] S1: Well, you're 20 for the twenty third time, it sounds like. Oh. Oh, 20... Well, 20... The first. That's okay. Keep going. I think it's twenty third. Yeah. Like when you're 20 the first time, that's 20 for the first time. It's not 21. [00:37:17] S2: But we can Okay. Okay. Fine. Fine. Okay. [00:37:19] S1: If you're 20 years old, what would you spend the next five years learning or building?
00:37:19 · Ravi Belani, Michael Bernstein
[00:37:19] S1: If you're 20 years old, what would you spend the next five years learning or building? [00:37:24] S2: Well, I'm teaching here, so I feel like I gotta say HCI. Look, I think if you buy the Myspace hypothesis, the big gap is what problems do we need to solve? And I think that something around human centered design is what teaches us to look for these opportunities. It's this thing called Pasteur's quadrant. It's like solve real world problems that have like very deep and horizontal application. Like Pasteur, like famously... Okay. What did he invent? Vaccine. Right? Because there was a thing in front of him. He did fundamental research that was targeting a very... A problem that was right in front of him. I think this is where HCI likes to live. It's like, what are real human needs where there's real technological opportunity? That's where I like to live, and I think that Simile just grew out of that. We saw the problems in social media trying to predict what's going to go wrong or trying to understand the effects of policies, And I think that training yourself to understand how do I connect needs with technological opportunity, that is what HCI does. And so I would be taking exactly the thing that I'm teaching. Easy answer, I guess. [00:38:38] S1: What's the best mistake you've ever made?
00:38:38 · Ravi Belani, Michael Bernstein
[00:38:38] S1: What's the best mistake you've ever made? [00:38:42] S2: Applying by accident to a PhD. So I was here as an undergrad. My undergrad advisor suggested that I I wanted to apply to a PhD, but I wasn't sure if I had enough experience. He said, Okay, you should apply for master's programs first. So I did. Turns out... MIT has this dropdown. Are you applying for the SM? Because they do the Latin thing where they reflect MS to SM. SM or PhD? Turns out they ignore that drop down, and so I applied to the PhD without realizing it. And then I got in. I said, oh, well, guess guess I'm gonna do that then. So, that was my best mistake. Set me off on my path. [00:39:23] S1: And I know there's a long pipeline, so I'm gonna discuss one more signature question. We'll move to the students, which is what have you refused to compromise on and what has that cost you?