Entrepreneurial Thought Leaders (ETL)
00:30:55 · Michael Bernstein, Ravi Belani
[00:30:55] S2: I think if I were to advocate for, or anyone were to advocate for, like, completely cutting out talking to actual humans, like, I would lose my HCI card. Right? Like, this is a tool, and any tool has strengths and weaknesses. I think the strengths of this is that it gives you sort of instantaneous access to perspectives that might be hard to reach, the ability to iterate, but ultimately, you are trying to build a deep understanding of what the problem really is. And I think at some point, that has to involve talking to to real people. [00:31:23] S1: I just wanna reinforce that because I think there's a huge temptation just to not do the discovery work and just rely upon the LLMs to give you the insights. But I... But your philosophy is is that that is still sacred. [00:31:35] S2: I... What I see people using Simile to do is that they take what used to be like, oh, we have, like, two ideas, and we have to be conservative about those two ideas, and we have to be certain that they're gonna work so that we can go take them to users and, you know, gather feedback and do and do this. Now I can actually have a 100 ideas and really trial them and iterate on them, and then whittle that down to a much better two that I actually go into the field and see. [00:31:59] S1: Okay. So you can do more of an expansion or a pre pre pre discovery expansion and then...
00:31:59 · Ravi Belani, Michael Bernstein
[00:31:59] S1: Okay. So you can do more of an expansion or a pre pre pre discovery expansion and then... [00:32:05] S2: And as a as a result, it means that people take bigger risks. I think the the the most frustrating thing is if you know you only have like one or two options you can actually field test, you're going to take the sure bet because you don't want to walk back empty handed. But suddenly, now I can take all sorts of risks and see what's going to happen. [00:32:21] S1: Okay, so we're going to lean into taking more risks. And I loved what you said that we're now entering into the era... We're passing model development as the era of focus, and we're moving into applications. And I loved the eye of Mordor comment because I do think there's a real fear that if somebody builds an application, because of the concentration of capital and talent in the big three, in Open AI, Anthropic, and Google, that once the eye of mortar comes to you, your time is limited. And because of how quickly people can build products, how small the competitive differentiation is. So I'm curious if you do think that we're going into the era of applications, and I know you touched upon this a little bit, but can you double click a little bit more on how do you think about a durable moat? How should you in or triage out potential applications to build that will have a moat given the resources of the big three?
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?