$1.5B AI Founder: This Is Your Golden Age to Build With AI | Jesse Zhang, CEO Decagon

What will happen to jobs in the age of AI? Jesse Zhang, co-founder of $1.5B startup Decagon, joins me to talk about how AI agents are changing the future of work. We dive into which roles are disappearing, which new ones are being created, and the skills you need to stay competitive. Jesse also shares his journey of building one of the fastest-growing AI companies in Silicon Valley, advice for new founders, and what the next generation of entrepreneurs should know about starting in AI.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

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• 0:30Speaker 01

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• 1:00Marina Mogilko?

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

• 1:03Speaker 03

  Jobs where...

• 1:05Marina Mogilko?

  Meet Jesse Zhang, 27 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 200. 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?

• 1:29Speaker 03

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

• 1:32Marina Mogilko?

  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 going to talk about new career paths that are opening up and the skills that will define the next generation of leaders.

• 1:46Speaker 03

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

• 1:50Marina Mogilko?

  And when you interview people for a company, can you name some skills that you're looking for? Welcome to Silicon Valley Girl, everyone. Jessie, 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 65 people working on a particular problem. Do you see it as creating more opportunities or like taking jobs from people who were doing these tasks?

• 2:18Speaker 03

  Yeah, no, happy to give some context. So you mentioned kind of using AI agents to automate things. We focus specifically on conversations with end users, right? So as an example, let's say, 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 so on, they'll have a lot of inquiries like, I want to book a room, or I want to upgrade my room, or I have questions about my loyalty points. 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 and might need to go look up information about you, right? It might need to figure out like, what are your past stays?

• 3:03Speaker 03

  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 book a room for you and so on. So in a nutshell, that's what we do. And so those are the, you know, you mentioned automating processes, that's, that's kind of what we do. It's more about automating these conversations. So back to your question about how we view the innovation and sort of impact on these organizations. It really depends on what the organization is looking to get out of AI agents. And different organizations are in different stages. 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

• 3:45Speaker 03

  their operation just much faster and make it so that it's a lot less operationally intensive for them to grow, right? If they grew 5X in the last year, maybe they don't need to, you know, 5X their support team. So that's one thing that we see. Other organizations that we talk to are more focused on the quality of experience. Maybe they just don't care about cost, so they don't really care how many, they're not, you know, replacing anyone, they're, they're more just kind of like, okay, we think that having an 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 those are kind of different profiles.

• 4:27Speaker 03

  And of course, there is also a third 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 either reassigning those folks to other jobs. Or more realistically, sometimes they're using like outsourced, you know, agencies and they can downsize those. Right. So those are, those are the three categories of companies and we're, we're, we're seeing kind of a pretty good diversity between those.

• 4:53Marina Mogilko?

  Yeah, because I feel like when we're talking about jobs that might get eliminated by AI, we talk about those like customer support roles first. And it's interesting to hear that it's like with, 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, but like agencies that they're using, right? What, what do you feel like the percentage of those companies is?

• 5:21Speaker 03

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

• 5:26Marina Mogilko?

  Okay. So, so it is happening and you see it.

• 5:28Speaker 03

  Yeah. And I think the agencies themselves, I think they're also just shifting to new things. Right. So let's say you operate a big call center with a lot of folks. I, I, 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. So instead of handling the, you know, tier one types of conversations of, you know, like book a room for me. You're, you're more involved in kind of building a relationship with the client, handling, handling more like the tier two, tier three, like complex interactions. You could, and then there's kind of other things that emerge, right? So for example, a big thing nowadays is collecting data for the AI or having people review the AI. And so I think it's just kind of the nature of the job changes. And that's pretty much what happens every single time there's a big technology shift.

• 6:12Marina Mogilko?

  And what do you think is going to happen to entry level jobs? I just saw these stats where there were 30% more applications for entry level jobs this year and 15% less spots in the companies. What do you think is going to happen?

• 6:25Speaker 03

  Yeah, I think the types of things that people end up doing now are going to be different just enabled by AI. Right. So if you even think about. Software engineering is one of the most popular jobs 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 because the amount of software that you need to build is kind of uncapped. It's more like the more people you have.

• 6:55Marina Mogilko?

  It's essentially growing, I feel like.

• 6:56Speaker 03

  Exactly, right? Like the more people you have, the faster you can get there almost. So it's not necessarily like, hey, there's fewer jobs, but 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 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 it's hard to measure the impact.

• 7:29Marina Mogilko?

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

• 7:35Speaker 03

  I don't really have strong thoughts on those. I mean, I can tell you what we use as a company. So on the coding side, we have, you know, classic Cursor, Claude Code, companies like that. Lovable is quite impressive in terms of prototyping and building things out. On the non-engineering side, folks use things like Notetakers and, 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. So those are the tools. In terms of building AI agents, I don't think like the typical person

• 8:13Speaker 03

  will build their own agent per se. I mean, you can build a simple one with ChatGPT, for example, but most of our.

• 8:25Speaker 03

  Employee base, I would say, are kind of using tools to amplify themselves instead of like creating their own agents.

• 8:30Marina Mogilko?

  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 heavier lift for small businesses.

• 8:44Speaker 03

  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 requests or customer service agents that they have, it's, it's just way larger than anything else. And so it makes sense for us to work with these companies if we can.

• 9:07Speaker 03

  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 corporations, because 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 smaller clients. But 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 to craft the agent.

• 9:52Speaker 03

  And then you, you can kind of prioritize it more for the smaller folks.

• 9:55Marina Mogilko?

  So you're automating customer support for others. But inside of your company, what are the processes that used to exist that do not exist now because they're fully automated?

• 10:03Speaker 03

  The thing that comes mostly to mind is 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 other notes or watching videos and stuff like that. But yeah, if you use, you know, 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.

• 10:47Speaker 03

  It's it makes things much easier.

• 10:49Marina Mogilko?

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

• 10:52Speaker 03

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

• 10:56Marina Mogilko?

  Less than two hundred. Have you ever gone from more people to less people in the past few years?

• 11:01Speaker 03

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

• 11:03Marina Mogilko?

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

• 11:08Speaker 03

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

• 11:14Marina Mogilko?

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

• 11:41Speaker 03

  I don't think you have to be technical, but I think being technical helps a lot. 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 you didn't, you don't have to be technical. It it's just, it's just very helpful. If you have the time and the interest, like, why not learn it?

• 12:05Marina Mogilko?

  Yeah, it's just 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.

• 12:16Speaker 03

  Yeah, I mean, for for people with non-technical backgrounds, I want to get into it. Just, yeah, I think right now is a golden time. 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 tools are getting so much. Exposure is that you you there's just like a much larger audience now, right? Instead of being someone super technical, you can even be semi-technical or not technical at all. And now you have a great opportunity to build your own things.

• 12:42Marina Mogilko?

  I love that. Can you give advice to people who are watching, who are graduating from college? Because you went straight to starting a company. It was another company, was a company connected with video games. 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?

• 13:01Speaker 03

  Yeah, I mean, I've thought about this a lot because we've also recruited a lot of people out of college that we're 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 because 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 all 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.

• 13:42Speaker 03

  So if you you work at a startup, um, in my my my thesis is like, if you do choose to work at a startup, you ideally choose one that's posts product market fit because 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 and like how to like what good looks like, right? 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 because you you gain a lot of intuition around how to work with people, what types of profiles you need, you know, intuition around, um, you know, how to approach customers, how to work with customers, what's the right dynamic to have with your customers?

• 14:25Speaker 03

  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. But yeah, if if you have energy, then um, there's definitely nothing wrong with just learning as you go.

• 14:38Marina Mogilko?

  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?

• 14:46Speaker 03

  I mean, it's hard to say at a very high level, but I would say jobs where there is is it's just kind of like straight up outputs where like, let's say right now, you know, what AI is 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 people often talk about. You know, like what jobs AI is eliminating? Because it's kind of easy to see like, oh, well, AI can do this. That means we don't need humans anymore. But that's true of any technology, any technology that's like good at something.

• 15:30Speaker 03

  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 of writing marketing materials or just like writing stuff in general.

• 15:42Marina Mogilko?

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

• 15:46Speaker 03

  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.

• 15:54Marina Mogilko?

  Yeah.

• 15:54Speaker 03

  You 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 of questions? 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 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 use Decagon to design the way that their AI should behave.

• 16:38Speaker 03

  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 because that's how you communicate to the AI of how to, you know, answer something.

• 16:52Marina Mogilko?

  And they were customer support before, those people?

• 16:54Speaker 03

  Yeah, so before they were kind of, you know, managers, CX managers, or, 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 roles have kind of evolved as well, right? So 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 can get these folks that were very interested in this, but we've kind of given them 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 now in charge of AI

• 17:36Speaker 03

  and designing it and leveraging it and reviewing the answers and figuring out how to make it better.

• 17:41Marina Mogilko?

  So Jesse's an employer, right? He's hiring people in today's AI world. And again, we've seen this stats, AI is replacing people, no more jobs, blah, blah, blah. But he's still hiring, his company is growing, he needs more high skilled workers. The question I want to 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 manager of AI?

• 18:22Speaker 03

  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 the folks that are using Decagon is, oh, I saw this conversation that could have 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, here's the knowledge that it used. And so someone who can actually clearly think through that is going to be very effective at this. And the other trait I would say is around communication. So in the same way that we communicate with coworkers now,

• 19:07Speaker 03

  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 at Decagon is through natural language, so like plain English. So someone who is really good at communicating can write down instructions essentially for the AI to follow in a very, very nice way. Whereas someone who potentially less good at communicating, 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 would kind of put that into the communication skills. So it's kind of like analytical and communication skills.

• 19:39Marina Mogilko?

  Yeah, love it. You've been doing this for two years. How did you initially find the problem and what made you stick to it? Because there are so many problems that could be solved with AI.

• 19:50Speaker 03

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

• 20:01Marina Mogilko?

  So you had your co-founders, you were like, let's start something. And the first thing you were gonna do, just talk to customers, right?

• 20:07Speaker 03

  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 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, conversational AI, customer service. And people have tons of people on their team or kind of outsourced agency that's doing this. And they see a lot of opportunity.

• 20:52Speaker 03

  And 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 was the impact on my business.

• 21:00Marina Mogilko?

  You tried to specifically B two B, right? Straight away. Because like, it's not like you were talking to a lot of different people.

• 21:05Speaker 03

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

• 21:08Marina Mogilko?

  Because you wanted to go to B two, into B two B, right?

• 21:10Speaker 03

  Yeah, I mean, that, yeah, that was a conscious decision, I suppose. My first company was a BDC company and wanted to try something different. And also I think it is much easier to reason through B two B. B two C, there's a lot more intuition based, you know, run experiments.

• 21:24Marina Mogilko?

  And I feel like fundraising and everything is just, the predictability of a business with B two B is way better.

• 21:31Speaker 03

  Yeah, for sure.

• 21:32Marina Mogilko?

  Way easier.

• 21:32Speaker 03

  Yeah.

• 21:33Marina Mogilko?

  Thank you. Can you give one piece of advice to everyone who's watching and wants to start a company in AI?

• 21:40Speaker 03

  Well, one is that you kind of have to find your own way because. One of the things that I believe in is that it's actually super easy to overindex on what other people have done. And that might not work for you because other people have different strengths and different circumstances as well. And you might, those might not be obvious, by the way, when you first hear about it. So I think when you're young, you have a tendency to like read these articles or like podcasts or whatever about other founders. You're like, okay, I'm just gonna do that because that's what worked. But different people have different strengths, right? Like Ashwin and I have different strengths compared to other founders, but also with each other. So you have to figure out what works for you. That's probably the big thing is like, don't overindex on what you hear and just try to introspect and figure out what you're good at.

• 22:24Speaker 03

  And then, I mean, you can learn from other people's stories as well. I mean, 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. In B2B stuff, like the purest signal is like, are you getting revenue? Like, are people paying you? Because if they're not, then is what you're doing actually useful? Or like, I mean, that's not necessarily the case, but like you just want to get as much signal as possible. And I think that's, that was our learning, basically. So for other people that are building a B2B, 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.

• 23:09Speaker 03

  You should just spend time talking to customers 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 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.

• 23:28Speaker 00

  LinkedIn is pretty amazing at helping you grow your small business. We cannot make your email response time faster. We can help you sell, market, and hire in one place. We cannot help you find space for your three desk drinks. Why do you have three? And while we can't help you find the perfect volume for your presentation video, LinkedIn can help you find the perfect audience for your business. Grow your small business on LinkedIn. Learn more at LinkedIn.com/smallbusiness.

• 24:24Speaker 01

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• 24:28Marina Mogilko?

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

• 24:31Speaker 03

  Yeah, of course.

• 24:32Marina Mogilko?

  With customers?

• 24:32Speaker 03

  Yeah.

• 24:33Marina Mogilko?

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

• 24:38Speaker 03

  Oh, no. I don't think people would pay.

• 24:42Marina Mogilko?

  Well, sometimes they would, like you put you on the waitlist.

• 24:45Speaker 03

  Yeah, maybe. I mean, yeah, so that is like one type of signal. But you want to, yeah, if, yeah, 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. That'd be nice. I think there's no way that'll happen for a sizable deal. That's just not how companies make decisions. But yeah, if you at least can commit, get them to commit to like, hey, if you deliver this, this would be worth this much to us. And actually assign a number to it. That is, that's the kind of step one, right? The 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's so many parallels. Like, sales is mostly just about, like, can you relate to the customer?

• 25:30Speaker 03

  Like, can you truly put yourself in their shoes? And understand how to make decisions, what's important, what are the trade-offs? How am I viewing these vendors I'm talking to?

• 25:43Speaker 03

  And if you can do that well, then, I mean, yeah, in my opinion, that's what generally makes a good salesperson. Man, that's what makes a good founder as well.

• 25:51Marina Mogilko?

  All right. So my key takeaways, learn how to sell, learn how to code,

• 25:57Marina Mogilko?

  learn how to communicate with people and with AI. Love that. Thank you so much, Jesse.

• 26:03Speaker 03

  Yeah, thanks for having me.

• 26:03Marina Mogilko?

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

• 26:08Speaker 00

  LinkedIn is pretty amazing at helping you grow your small business. We cannot stop your new clients from emailing you at 3 a.m.

• 26:17Speaker 00

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• 26:38Speaker 04

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