$1.5B AI Founder: This Is Your Golden Age to Build With AI

1. 0:00 – 0:57

   Intro

   1. MMMarina Mogilko0:00

      What do you think are the jobs that have the highest risk of extinction?

   2. JZJesse Zhang0:03

      Jobs where [beep]

   3. MMMarina Mogilko0:05

      Meet Jesse Zhang, twenty-seven years old and already co-founder of a $1.5 billion AI company. His startup, Decagon, powers conversations for brands like Hertz, Duolingo, and Notion. In just two years, his team has grown to nearly two hundred, so he is hiring. But the question is, how and who? You're seeing some of the companies actually laying off agencies that they're using, right? What do you feel like the percentage of these companies is?

   4. JZJesse Zhang0:29

      Within those categories that I listed, maybe one-third, one-third, one-third.

   5. MMMarina Mogilko0:32

      So it is happening, and you see it. In this episode, we explore the future of work, from the jobs most at risk in the AI era, and we're gonna talk about new career paths that are opening up and the skills that will define the next generation of leaders.

   6. JZJesse Zhang0:46

      For people with non-technical backgrounds that want to get into it, I think right now is a golden time.

   7. MMMarina Mogilko0:50

      And when you interview people for a company, can you name some skills that you're looking for? Welcome to Silicon Valley Girl, everyone. Jesse,

2. 0:57 – 5:11

   Is AI taking our jobs?

   1. MMMarina Mogilko0:57

      you founded a company that helps corporations build AI agents to automate processes inside those corporations, and one of your customers said working with you is like having sixty-five people working on a particular pro- problem. Do you see it as creating more opportunities or, like, taking jobs from people who were doing these tasks?

   2. JZJesse Zhang1:18

      Yeah, no, hap- happy to give some context. So you mentioned kinda using AI agents to automate things. We, we focus specifically on conversations with end users, right? So as an example, let's say, uh, you know, we work with a hotel chain, and as you can imagine, a lot of the customers that go and stay in the hotels and, and so on, they'll have a lot of inquiries, like, "I wanna book a room," or, "I want to upgrade my room," or, "I have questions about my loyalty points." Um, these are classic... You know, you can think of these as customer service or customer support inquiries that come in, and the AI agent's job is to have a conversation with them. This can be over the phone. It can be over live chat, and the AI agent can have the full conversation. It might need to go look up information about you, right? It might need to figure out, like, what are your past stays, or it might need to figure out, like, what loyalty tier you are. So it might- it can go in and look up information. It can take actions as well, so it can go and, and book a room for you, and, and so on. So in a nutshell, that's what we do, and so those are the... You know, you mentioned automating processes.

   3. MMMarina Mogilko2:16

      Mm-hmm.

   4. JZJesse Zhang2:16

      That's, that's kinda what we do. Uh, it's, it's more about automating these conversations. Um, so back to your question about how we view the innovation, the, the, and sort of impact on these organizations. It really depends on what the organization is looking to get out of, get out of AI agents, and different organizations are in different stages. Uh, some people are in heavy growth mode, right? So the AI agent is more of an amplification of what they currently do. There's, there's no one that's replacing per se, but it's, it's making, it's making their operation just much faster and, and making it so that it's a lot less operationally intensive for them to grow, right? If they grew five X in the last year, maybe they don't need to, you know, five X their support team. So that, that's one, uh, thing that we see. Other organizations that we talk to are more focused on, um, the quality of the experience. Maybe they just don't care about cost, so they don't really care how many... Uh, they're not, you know, replacing anyone. They're, they're more just kind of like, "Okay, we think that having the AI agent here will make the customers a lot happier with us because, you know, they can get answers instantly. They can get what they wanted, you know, within a few seconds, rather than waiting on hold." And so that's what we're seeing, and th- those are kind of different profiles. And, of course, there is also a third, uh, category of company, where maybe they're just in cost-saving mode, and so what they're using AI for is kind of, you know, making their operations more efficient and, uh, either reassigning those folks to other, uh, jobs or, more realistically, sometimes they're using, like, outsourced, um, you know, agencies, and they can downsize those, right?

   5. MMMarina Mogilko3:47

      Mm-hmm.

   6. JZJesse Zhang3:47

      So those are, those are the three categories of companies, and, uh, we're, we're, we're seeing kind of a, a pretty good diversity between those.

   7. MMMarina Mogilko3:53

      Yeah, 'cause I feel like when we're talking about jobs that might get eliminated by AI, we talk about those, like, customer support roles first. Uh, and uh, it's interesting to hear that. It's like with, um... You know, when we talk about mental health, like, if there is a therapist on your phone, it doesn't mean it's replacing therapists. It's just making therapy more accessible for everyone. But in your industry, you said you're seeing some of the companies actually laying off the, like, agencies that they're using, right? What, what do you feel like the percentage of those companies is?

   8. JZJesse Zhang4:21

      I think, yeah... I mean, within those categories that I listed, maybe one-third, one-third, and one-third.

   9. MMMarina Mogilko4:25

      Okay, so, so it is happening, and you see it?

   10. JZJesse Zhang4:28

       Yeah, and I think the agencies themselves, I, I think they're also just shifting to new things, right? So let's say you operate a, a big call center with a lot of folks. Um, a- a- I don't think it's a matter of like, "Oh, crap, there's not stuff for us to do anymore." There's just other things.

   11. MMMarina Mogilko4:42

       Mm-hmm.

   12. JZJesse Zhang4:42

       So instead of handling the, you know, tier-one types of conversations of, you know, like, "Book a room for me,"-

   13. MMMarina Mogilko4:48

       Mm-hmm

   14. JZJesse Zhang4:48

       ... you're, you're more involved in kind of building a relationship with the client, handering- handling more, like, the tier two, tier three, like, complex interactions. Um, you could... And then there's kind of other things that emerge, right? So for example, a big thing nowadays is, uh, collecting data for the AI or having people review the AI. So I think it's just kind of the nature of the job changes, and that's pretty much what ev- happens every single time there's

3. 5:11 – 6:49

   One tool that can transform your business

   1. JZJesse Zhang5:11

      a big technology shift.

   2. MMMarina Mogilko5:12

      I think a lot of you guys are listening to this and thinking, "Yeah, clearly he has computer science background. He's built this company, and AI is definitely helping him improve his life 'cause he is building something that's changing the world. But how do I actually use AI in my own business since I can't code?" And here's the problem I see all the time. People try to run everything on several different tools: one for email, another for CRM, then payments, then scheduling. Add phone calls to that, and suddenly, you're juggling subscriptions just to stay organized. That's where HighLevel makes a huge difference. It's an all-in-one platform that lets you run and automate your business from day one. You can build websites and funnels with drag and drop. You can automate emails and SMS and IG DMs. You can manage clients with a built-in CRM. You can schedule calls, take payments, even host courses, and keep all your messages in one shared inbox. And the best part? You get your own AI employee, actually, several of them. Voice AI that picks up calls and books appointments, conversation AI that replies across platforms, reviews AI follows up for five-star reviews, content AI writes posts and emails, and a workflow assistant that keeps everything running, all starting at just $97 a month. No contracts, no complicated setup. If you're just starting out or ready to simplify what you already have, HighLevel helps you run like a real business right from the beginning. Check it out. The link's in the description, and if you use my link, you'll actually get a thirty-day trial instead of the usual fourteen days. So try it out and see how much easier your business can run with HighLevel....

4. 6:49 – 8:05

   The future of entry-level work

   1. MMMarina Mogilko6:49

      And what do you think is gonna happen to entry-level jobs? I just saw these stats where there were thirty percent more applications for entry-level jobs this year, and fifteen percent less spots in the companies. What do you think is gonna happen?

   2. JZJesse Zhang7:02

      Yeah, I think the types of things that people end up doing now are gonna be different, just enabled by AI, right? So if you even think about software engineering is one of the most popular jobs-

   3. MMMarina Mogilko7:14

      Yeah

   4. JZJesse Zhang7:14

      ... um, in the last decade or so. We have a lot of software engineers, and there's no way we will slow down on hiring a software engineer anytime soon, 'cause the amount of software that you need to build is, is kind of, like, uncapped. It's, it's, it's more like the more people you have-

   5. MMMarina Mogilko7:32

      And it's exponentially growing, I feel like. [chuckles]

   6. JZJesse Zhang7:33

      Exactly, right. Like, the more people you have, the faster you can get there, almost.

   7. MMMarina Mogilko7:37

      Yeah.

   8. JZJesse Zhang7:37

      So it's not necessarily like a, "Hey, there's, there's fewer jobs," but, um, the nature changes, right? So now, pretty much every single one of our engineers is heavily using AI in their job, and it's kind of one of those things where it's, it's hard to quantify exactly what the impact is. One, because we started the company after that technology was there, so, like, we've always had that technology. But even if you kind of compared someone just coding by themselves versus with an AI agent, like, obviously, you can feel that the AI makes them faster and, like, more productive, but

5. 8:05 – 10:35

   Top 3 apps for building AI agents

   1. JZJesse Zhang8:05

      it's hard to measure the impact.

   2. MMMarina Mogilko8:06

      What are your top three, ah, tools to build an AI agent, for someone who's non-technical, ideally?

   3. JZJesse Zhang8:12

      I don't really have strong thoughts on those. I mean, I can sh- tell you what we use as a company. So on the coding side, we have, you know, the classic Cursor, Cloud Code, um, companies like that. Lovable is quite impressive in terms of prototyping and, and building things out. On the non-engineering side, folks use things like note-takers and, um, you know, ChatGPT in and of itself is quite useful just for researching and making, you know, people more well-equipped on the go-to-market side, for example.

   4. MMMarina Mogilko8:46

      Mm-hmm.

   5. JZJesse Zhang8:46

      So those are the tools. Um, in terms of building AI agents, I, I don't think, like, the typical person will build their own agent, per se. I mean, um, you can, you can, you can build a simple one with ChatGPT, for example, but most of our employee base, I would say, are, are kind of using tools to amplify themselves instead of, like, creating their own agents.

   6. MMMarina Mogilko9:07

      Mm-hmm. So do you feel like smaller businesses, like, in two or three years, if they want an AI agent, they would go to a company like yours? Or you still will be working with larger corporations because this is something that's-

   7. JZJesse Zhang9:19

      Oh

   8. MMMarina Mogilko9:19

      ... a heavier lift for small businesses?

   9. JZJesse Zhang9:21

      Yeah, interesting. I would say that currently, our focus is on the large organizations. There's a bunch of reasons for that. I mean, one is that they have the scale, and so they-- if you think about the number of customer inquiries that they get or the number of customer service r- requests or cover ser- customer service agents that they have, it's, it's just way larger than a- anything else, and so it makes sense for us to work with these companies if we can.

   10. MMMarina Mogilko9:42

       Mm-hmm.

   11. JZJesse Zhang9:44

       Um, another reason is that AI agents are still generally in their infancy, so there's still a lot of figuring out to be done, and because of that, the product's going through a ton of iteration, and it makes a lot of sense to iterate, you know, side by side with these larger corporization- corporations, 'cause y- you can build around them. And then, you know, the ideal path is, like, okay, once the product is mature enough, maybe then you can start productizing it for, um, smaller clients. But I, I think the issue is that because the clients are smaller, you don't actually have the time or the capacity to really spend time building around them, so you have to have something that's more productized. So I think that's the ideal progression for AI agents is, if you can work with the largest corporations, you can work with them closely and kind of refine the product and really figure out, like, what needs to be in there and to craft the agent, and then you, you can kind of productize it more for the smaller folks.

   12. MMMarina Mogilko10:33

       So you're automating customer support for others,

6. 10:35 – 11:51

   How companies automate with AI

   1. MMMarina Mogilko10:35

      but inside of your company, what are the processes that used to exist that do not exist now because they're fully automated?

   2. JZJesse Zhang10:40

      The thing that comes mostly to mind is, uh, doing the research. So let's say you are looking into a new space and trying to figure out, you know, what are the, you know, best fits for Decagon. Or you're trying to understand for a specific company, like, you know, what, what is the history so you can be... you know, you can have a good understanding with them, so when you talk to them, you can have empathy, you can have, you know, the right context for them. And so normally, people would have to spend a good amount of time, you know, Googling stuff and putting it all in notes or watching videos and stuff like that. But yeah, if you use new deep research or one of the AI agents to do the research for you, you can get it done within, you know, a few minutes, and then there's sources as well, so you can validate stuff. It's-- it makes things much easier.

   3. MMMarina Mogilko11:26

      Yeah, absolutely. How many people do you have now on the team?

   4. JZJesse Zhang11:29

      We are a little less than... we're still less than two hundred.

   5. MMMarina Mogilko11:33

      Less than two hundred.

   6. JZJesse Zhang11:34

      Yeah.

   7. MMMarina Mogilko11:34

      Have you ever gone from more people to less people in the past few years?

   8. JZJesse Zhang11:38

      No, but we've only been around for two years, so...

   9. MMMarina Mogilko11:40

      So you're, you're only growing, right. Do, do you see hiring more people in the future?

   10. JZJesse Zhang11:45

       Oh, of course. Yeah, we're hiring super fast right now, and it's one of the bottlenecks, I would say, for the business is we need more people.

7. 11:51 – 13:19

   Can non-tech founders build billion-dollar startups?

   1. MMMarina Mogilko11:51

      Do you think it's possible to build a company these days without being technical, if you want to build in AI space? Because, you know, we're talking about Lovable, that lets you deploy faster and come up with MVPs. We're talking about Natan, that lets you build AI agents with just a block scheme.

   2. JZJesse Zhang12:06

      Mm-hmm.

   3. MMMarina Mogilko12:07

      Um, do you think you still have to be technical to build a billion-dollar company, or you can be a one person, you know, with a good idea and a bunch of tools, uh, building something that's gonna help the market?

   4. JZJesse Zhang12:18

      I, I don't think you have to be technical, but I, I think being technical helps a lot.

   5. MMMarina Mogilko12:22

      Mm-hmm.

   6. JZJesse Zhang12:23

      'Cause you just have better intuition, and you understand the inner workings a little bit more, and so you can make better decisions faster, I would say. But yeah, even now, even without AI, you didn't- you don't have to be technical. Um, it, it's just, it's just very helpful. If you have the time and the interest, like, why not learn it?

   7. MMMarina Mogilko12:42

      Yeah, it's just m- maybe for people who are like, they don't see themselves as coders necessarily, but they feel like they're missing out on this huge era of change because they don't understand what's going on.

   8. JZJesse Zhang12:53

      Yeah, I mean, for, for people with non-technical backgrounds that wanna get into it, just, yeah, I think right now is a golden time.

   9. MMMarina Mogilko12:59

      Mm-hmm.

   10. JZJesse Zhang12:59

       You can, you can do a lot more than you did before. I mean, that's part, part of the reason why a lot of these coding, um-... tools are getting so much, um, exposure is that you, you- th- there's just, like, a much larger audience now, right? Instead of being someone super technical, you can, you can be semi-technical or not technical at all, and, and now you have a great opportunity to build your own

8. 13:19 – 15:15

   College grads: work or launch your own thing?

   1. JZJesse Zhang13:19

      things.

   2. MMMarina Mogilko13:19

      I love that. Can you give advice to people who are watching who are graduating from college? Because you went straight to, uh, starting a company. It was another company, it was, uh, a company, uh, connected with video games. But have you ever had this thought of, like, "No, I should go work for a company first, get some experience"? Why did you decide to go straight into business?

   3. JZJesse Zhang13:38

      Yeah, I mean, I've thought about this a lot 'cause we've also recruited a lot of people out of college that... And were also considering building their own thing. And I think my general sense is, if you feel ready, and you feel a lot of energy and conviction in doing your own thing, then go for it, you know? Like, it's gonna be quite tough. I would say, for me, it was very tough right out of college, just 'cause you don't have enough intuition around things. But if you feel ready for that, and you're okay with it being tough and kind of just trudging through it, then, yeah, just do it. I think we, we... I, I love seeing people that are just, like, having the confidence and can just go for it. On the flip side, yeah, the reason to kind of work somewhere would be to gain experience and gain that intuition. So if you, you know, work at a startup, um, and my, my, my thesis is, like, if you do choose to work at a startup, you sh- ideally choose one that's post, uh, product-market fit. 'Cause otherwise, you don't learn that much. Like, if you're pre-product-market fit, you're, you're kind of building stuff, but maybe you'll learn some technical skills. You don't really learn that much around, like, what, what you should look for in a company-

   4. MMMarina Mogilko14:39

      I love that.

   5. JZJesse Zhang14:39

      -and, like, how to-

   6. MMMarina Mogilko14:40

      Yeah.

   7. JZJesse Zhang14:40

      like, what good looks like, right?

   8. MMMarina Mogilko14:41

      Mm-hmm.

   9. JZJesse Zhang14:42

      So okay, you join a post-PMF company, maybe it just hit PMF, and things are inflecting, and things are really working. Yeah, you... That could be really helpful. 'Cause you, you gain a lot of intuition around how to work with people, what types of profiles you need. You gain a lot of intuition around, um, you know, how to approach customers, how to work with customers, what's the right dynamic to have with your customers. Um, you know, how to build products and how to build product at scale that doesn't break all the time. So that's the benefit of actually doing the second route. Um, but yeah, if, if you have energy, then, um, there's definitely nothing wrong with just learning

9. 15:15 – 18:18

   Jobs most at risk of extinction

   1. JZJesse Zhang15:15

      as you go.

   2. MMMarina Mogilko15:15

      Okay, if you were brutally honest, uh, what do you think are the jobs that have the highest risk of extinction in the next five years?

   3. JZJesse Zhang15:24

      I mean, it's hard to say at a very high level, but I would say jobs where there is... it's, it's just kind of like straight-up output, where, like, let's say right now, you know, what AI's really good at, right, it's, like, it's writing, you know, marketing materials. And if the job is just writing marketing materials, then I think those jobs are kind of hard to justify. And so what will happen, I think, is that those jobs will kind of evolve. Um, like, pe- people often talk about, you know, like, what jobs AI is eliminating because it's kind of easy to see, like, "Oh, well, the AI can do this. That means we don't need humans anymore." Uh, but that's true about any technology. Any technology that's, like, good at something, you don't really need humans to do that thing. So what the job becomes is, like, humans kind of, like, guiding that technology. So yeah, I mean, a classic example, writing marketing materials or just, like, writing stuff in general.

   4. MMMarina Mogilko16:19

      Do you have that person in your, on your team, or is it, like, a marketer?

   5. JZJesse Zhang16:23

      Yeah, we have a marketing team, and they use AI, right? But there's, there's no sort of, like, need anymore for someone that just writes the copy.

   6. MMMarina Mogilko16:30

      Like a copywriter, yeah.

   7. JZJesse Zhang16:31

      You know, have someone who controls the AI that writes the copy, right? So, and the same with what we're doing. Like, when we, when we think about, you know, customer service or customer experience, you don't necessarily need people to, you know, handle the, like, how do I reset my password type questions. Um, you can have people that either can work on the higher-level, harder questions or kind of manage the AI that, you know, solves those questions. And so, uh, for us, what we're seeing actually with a lot of our customers, a lot of our customers, is that people kind of grow into new roles that are much more exciting. So it could be like, there's now this concept of, like, a conversation architect or AI architect, and their whole job is to, you know, use Decagon to design the way that their AI should behave. And, you know, that, that requires a little bit of a different skill set. You have to be fairly good at reasoning, you have to be fairly good at communicating, 'cause that's how you communicate to the AI of how to, you know, um, answer something.

   8. MMMarina Mogilko17:29

      And they were customer support before, those people?

   9. JZJesse Zhang17:31

      Yeah, uh, so before they were kind of, you know, your managers, uh, c- CX managers or, um, you know, they were in charge of kind of their original knowledge base, or they were in charge of kind of the old-school chatbots. And so their, their roles have kind of evolved as well, right? So a, a big part of Decagon is enabling those people, and so we have a big focus on customer enablement. We have a program that we call Decagon University that up-levels them into the new AI age. And the benefit is that now you kind of get these folks that were very interested in this, but we've kind of given them a, a much smoother path to figure out, like, "Okay, here's how you build intuition around AI. Here's how I use them." And now they're much more effective at their jobs because they're, you know, now in charge of the AI and designing it and leveraging it and reviewing the answers and figuring out how to, you know, make it better.

10. 18:18 – 20:20

    Skills you need to land a great job

    1. MMMarina Mogilko18:18

       So Jesse's an employer, right? He's hiring people in today's AI world, and again, we've seen the stats. AI is replacing people, no more jobs, blah, blah, blah. [chuckles] But he's still hiring. His company's growing. He needs more high-skilled workers. The question I wanna ask him is: What do employers like him look for in candidates in today's market? What skills are critical? How do you stand out? Let's dive into what it really takes to be a part of a high-growth startup. And when you interview people for a company, can you name some skills that you're looking for? Not necessarily technical, but maybe, like, their personal traits that will help them transition from just being customer support to, you know, manager of AI.

    2. JZJesse Zhang18:59

       Yeah, so I mean, one, you have to be fairly analytical because you have to be able to break something down into steps, right? So a big part of w- the, the folks that are using Decagon is, "Oh, I saw this conversation that could've been better."... How do I figure out how to update the AI so that it can answer these conversations better in the future? And that involves, okay, well, I need to kind of dig into the conversation, and we have a lot of tooling here that helps them. Like, okay, this message, here's how the AI got this message. Here's, like, the reasoning. Here's, like, the step that it took. Uh, here's the knowledge that it used. And so someone who can actually clearly think through that is gonna be very effective at this. And the, the other s- trait I would say is, is around, uh, communication. So, um, in the same way that we communicate with coworkers now, in the future, you have these AI agents, and one of the areas that we've pioneered so far is, like, how do you communicate with the AI agent to teach it new things? And the way we do it w- at Decagon is through, uh, natural language, so like plain English. So someone who is really good at communicating can, you know, write down instructions, essentially, for the AI to follow in a very, very nice way. Whereas someone who's potentially less good at communicating, th- they might write it down, but then the AI could get confused because, like, two of the steps contradict with each other or something. So I, I would kind of put that into the communication skills, so it's kind of like analytical and communication skills.

    3. MMMarina Mogilko20:16

       Yeah. Love it. You've been doing this for two years.

11. 20:20 – 21:36

    How to spot the right startup idea

    1. MMMarina Mogilko20:20

       Um, how did you initially find the problem, and what made you stick to it? 'Cause there are so many problems that could be solved with AI.

    2. JZJesse Zhang20:27

       We found the problem mostly through talking to customers. So our whole approach to building product and figuring out what to do is to be super tight with our customers.

    3. MMMarina Mogilko20:39

       So you had your co-founders-

    4. JZJesse Zhang20:40

       Yeah

    5. MMMarina Mogilko20:40

       ... You were like, "Let's start something," and the first thing you were gonna do, just, just talk to customers, right? Figure out what they need.

    6. JZJesse Zhang20:45

       Yeah. So Ashwin, my co-founder, and I, we had both started companies before, and we had reasonable outcomes, but they were all kind of, like, up and down rides. And a lot of the reasons to have downs in, in a startup's journey, especially in the early days, is that you are building something and working really hard, but then you realize that there's no market for it, or customers don't really care that much about it, or they won't pay for it. So I think we just became a lot better at that process and talking to customers and really figuring out, like, what is the ground truth behind what they actually care about. And in this case, it was, you know, uh, conversational AI, customer service, and people have tons of people on their team or kind of outsourced agency that's doing this, and they f- they see a lot of opportunity. And the, the, the nice part about what we're building is that it's very quantifiable, right? You can, you can measure how well you're doing. You can see, like, what, what is the

12. 21:36 – 22:12

    Should you start in B2B or B2C?

    1. JZJesse Zhang21:36

       impact on my business.

    2. MMMarina Mogilko21:37

       You targeted specifically B2B, right, straight away?

    3. JZJesse Zhang21:39

       Uh-

    4. MMMarina Mogilko21:39

       'Cause, like, it's not like you were talking to-

    5. JZJesse Zhang21:41

       Oh

    6. MMMarina Mogilko21:41

       ... different people to figure out the-

    7. JZJesse Zhang21:43

       Yeah, we were mostly talking to large businesses, yeah.

    8. MMMarina Mogilko21:45

       'Cause you wanted to go to B2- into B2B, right?

    9. JZJesse Zhang21:47

       Yeah, I mean-

    10. MMMarina Mogilko21:48

        Mm-hmm

    11. JZJesse Zhang21:48

        ... That, that, yeah, that was a conscious decision, I suppose. My first company was a B2C company and wanted to try something different, and also, I think it is much easier to reason through B2B.

    12. MMMarina Mogilko21:58

        Yeah.

    13. JZJesse Zhang21:58

        Uh, B2C, there's a lot more intuition-based, you know, run experiments and stuff like that.

    14. MMMarina Mogilko22:01

        And I feel like fundraising and everything is just... The predictability of a business with B2B is way better.

    15. JZJesse Zhang22:08

        Yeah, for sure.

    16. MMMarina Mogilko22:09

        Way easier.

    17. JZJesse Zhang22:09

        Yeah.

    18. MMMarina Mogilko22:10

        Thank you. Can you give

13. 22:12 – 25:28

    Advice for future AI founders

    1. MMMarina Mogilko22:12

       one piece of advice to everyone who's watching and wants to start a company in AI?

    2. JZJesse Zhang22:17

       Well, one is that you kind of have to find your own way, 'cause one of the things that I believe in is that it's actually super easy to over-index on what other people have done, and that might not work for you. 'Cause other people have different strengths and different, uh, circumstances as well, and you might... And those might not be obvious, by the way, when you first hear it about it. So I think when you're young, uh, you have a tendency to, like, read these articles or, like, podcasts or whatever about other founders, and you're like, "Okay, I'm just gonna do that 'cause that's what worked." But different people have different strengths, right? Like, Ashwin and I have different strengths, uh, you know, compared to other founders, but also with each other. So you have to figure out, you know, what, what works for you. That's probably the big thing, is, like, don't over-index on what you hear, and just f- try to introspect and figure out what you're good at. Uh, and then, I mean, you can learn from other people's stories as well. I mean, I... Our story, I think the probably the biggest takeaway is that you have to spend the first stage of your company-building journey gathering as much signal as possible, and everything is about really getting signal on what to build and what's useful. Uh, in B2B stuff, like, the, the purest signal is, like, uh, is, uh, are you getting revenue? [chuckles] Like, are people paying you? 'Cause if they're not, then is what you're doing, like, actually useful or, like... I mean, that's not necessarily the case, but, like, you just wanna get as much signal as, as possible, and I think that's, that was our learning, basically. So for other people that are building B2B, I would, I would probably suggest, again, you know, figure out your own path, but I would suggest that you should not really try to build stuff first at all. You should just spend time talking to customers and, um, and not just talking to them. Like, you should really figure out, like, a game plan for how you take a conversation with a customer and, like, really go deep into, you know, what they're willing to pay for, how they think about ROI, how they make decisions. And once you have enough data points there, then you can actually figure out what is the right thing to build.

    3. MMMarina Mogilko24:05

       Did you actually ask them to pay when you were having those conversations-

    4. JZJesse Zhang24:08

       Yeah, of course

    5. MMMarina Mogilko24:08

       ... with customers?

    6. JZJesse Zhang24:09

       Yeah.

    7. MMMarina Mogilko24:09

       So you're like, "If we're gonna build this..." Or did you ask them to submit the card without having a product?

    8. JZJesse Zhang24:15

       Oh, no. Uh, I don't think people would pay [chuckles] people to-

    9. MMMarina Mogilko24:19

       Well, sometimes they would. Like, you put, put you on the wait list-

    10. JZJesse Zhang24:22

        Yeah, maybe

    11. MMMarina Mogilko24:23

        ... give them the 90% discount

    12. JZJesse Zhang24:23

        I mean, yeah, so that is, like, one-

    13. MMMarina Mogilko24:24

        Mm-hmm

    14. JZJesse Zhang24:24

        ... type of signal, but you want to... Yeah, if... Yeah, [chuckles] I mean, maybe, yeah, maybe you just have a conversation with someone, they're like, "Holy crap, like, I need this so badly, I'll just pay you right now."

    15. MMMarina Mogilko24:34

        Yeah.

    16. JZJesse Zhang24:35

        That'd be nice. I think, I- uh, there, there's no way that'll happen for a sizable deal. [chuckles] That's just not how companies make decisions. But, uh, yeah, if, if you at least can commit, get them to commit to, like, "Hey, if, if you deliver this-

    17. MMMarina Mogilko24:46

        Mm

    18. JZJesse Zhang24:46

        ... this would be worth this much to us," uh, and actually assign a number to it, that is, that's, like, kind of step one, right?

    19. MMMarina Mogilko24:51

        Mm-hmm.

    20. JZJesse Zhang24:51

        And step two, you kind of get into, "All right, well, how are you justifying that? Like, who needs to make the call? Like, whose budget is it coming out of?" It's kind of classic discovery. So I think that's why early-stage founding is, like, so much like sales. There are so many parallels. Like, sales is mostly just about, like, can you relate to the customer? Like, can you truly put yourself in their shoes and understand how do they make decisions, what's important, what are the trade-offs? How am I viewing these, like, vendors I'm talking to? And if you can do that well, then, I mean, yeah, in my, in my opinion, that's what generally makes a good salesperson. Um, and that's what makes a good founder as well.

    21. MMMarina Mogilko25:27

        Love

14. 25:28 – 25:44

    Final takeaways

    1. MMMarina Mogilko25:28

       it. So key ta- my key takeaways, learn how to sell, learn how to code- [chuckles] ... underst- learn how to communicate with people and with AI. Love that. Thank you so much, Jesse.

    2. JZJesse Zhang25:40

       Yeah, thanks for having me.

    3. MMMarina Mogilko25:40

       I think it was very informational for everyone who's starting a business.

Episode duration: 25:44