Jennifer (Interviewer) (2:06)

Yes. We're in the same year.

Marty Cautious (2:08)

Yeah. I remember meeting you at an Uber and being like, oh, hey, nice to meet you.

Robert Ng (2:13)

This is what, like 2016 years? Nine years ago?

Marty Cautious (2:16)

Yeah, yeah, yeah.

Jennifer (Interviewer) (2:18)

Wow. Time flies.

Advith Chelikani (2:19)

So Robert did that program. He was at Doordash interning that summer. And then that's how I found out about that program. And I did it the next year I was at Slack and Marty did it the same year I did it. And Marty was at Airbnb. Marty and I met a bit that summer just because we were part of the same program. But really we ended up living together after we graduated. And that's how Marty and I became close. Then I switched to living with Robert. I live with Marty for a couple of years after I graduated. Then I lived with Robert for a couple of years and now all three of us live together.

Jennifer (Interviewer) (2:47)

How long have you been living together?

Robert Ng (2:49)

Well, now it's been since the start of the company.

Marty Cautious (2:51)

Three years.

Advith Chelikani (2:52)

Yeah.

Robert Ng (2:53)

Yeah.

Jennifer (Interviewer) (2:53)

Well.

Robert Ng (2:54)

And we still live together. That's the crazy thing. Like, a lot of people think that we like, you know, we used to live in the office and there's that whole story about that and that like iconic photo of Robert like on a mattress on the ground in the living room. But yeah, people think, oh, you're serious. B Now you must be. You're doing so well. You probably have like nice living situation and. No, we live in like a dinky apartment. That's like one apartment or doesn't get any light. See, we don't have windows to give people a sense. We are very, very scrappy. And I feel like this kind of part of the reason you like us, of course, is we are all in on the company, so it's really our only priority.

Jennifer (Interviewer) (3:28)

Definitely. That was one of the main topic I wanted to talk about today is recently there was a Wall Street Journal article, I think titled with something like no booze, no sleep, no booze, no fun about AI Era founding. I'm really curious. First, what do you agree disagree with the article and how do you think that the working culture and the grinding nature of the founders impact the company culture?

Robert Ng (3:58)

Yeah, I think one thing they got wrong, really wrong is. Or maybe they took a different spin on it, is that we are very motivated by fun and adventure. I feel like that actually when you talk about the founding of Pylon and why we did it, there are easier ways to make money that don't require grinding 12 hours a day for 10 years straight. Passion. It feels like even if you're really passionate about solving a problem, it's not worth spending that much time solving that problem. It's just too much hard work and sacrifice. So it really feels like adventure and fun is one of the best reasons to start a company. And so for us, that's definitely our core motivation. And so I think they got that wrong. And then also no booze. I think that's generally correct. We don't drink that often. Maybe just for big celebrations. No sleep is true for me at least. Robert. I think all of us, you maybe.

Advith Chelikani (4:47)

Get the best sleep out of the. Yeah. I feel like it's hard to have.

Robert Ng (4:50)

Longevity if you don't have enough sleep.

Advith Chelikani (4:52)

Yeah.

Marty Cautious (4:53)

We do invest in our sleep, though. Our mattresses are expensive.

Jennifer (Interviewer) (4:56)

I guess the most expensive furniture in that stinky office.

Marty Cautious (4:59)

I don't have a bed frame. Yeah.

Robert Ng (5:02)

This is like such classic, like, startup energy. It's like the. Yeah. Robert has a mat he used to have in the living room of our old office, a mattress that was on the floor with innate sleep on it. It's like the most start. So, like, no bed frame, no nothing. Like one pillow.

Marty Cautious (5:17)

I mean, if you look in the picture, too, in the background under the basketball hoop, you can see my closet as well and all my life's possessions right there.

Robert Ng (5:25)

Yeah.

Jennifer (Interviewer) (5:25)

Very minimalistic.

Robert Ng (5:27)

Yeah. And then the other thing that the article didn't fully capture was that I think, you know, first off, we work way more than nine. Nine, six, actually. So it's like we've never used that term. We just work all the time, in fact. I think so. Yeah. Minimum six days a week. That's like the norm. And then Advent used to work seven days a week. I don't know how like the machine. Robert. Robert and I feel like we need more time.

Advith Chelikani (5:51)

Right.

Robert Ng (5:52)

I feel like Saturdays at minimum.

Marty Cautious (5:53)

I need my Saturdays now.

Advith Chelikani (5:54)

I have my Saturday now.

Robert Ng (5:56)

I actually feel like you earned less than this year.

Jennifer (Interviewer) (5:59)

Is there a level of peer pressure they apply to each other? It's like, if you're working, I better be working too. And how does that also manifest within the company too? Like, if the three founders are always in the office, always working, the employees also feel the obligation that they should appear at 9 and leave early.

Robert Ng (6:14)

I don't think, like, man, it's. No, I don't think they feel that pressure. Maybe they feel it more now with the article that came out. Actually, I feel like people are questioning internally. We actually had to clarify, and I Like posted even candidates. Now there's some people that are totally scared off by it, but there's some people, like we had an AE who came in yesterday who was like, I'm.

Advith Chelikani (6:32)

All in on it.

Robert Ng (6:33)

Like, get me into the nine nine six. Like this is the moment in my life where I want to grind. And people in the team have been.

Advith Chelikani (6:39)

Saying like, oh, we know you guys. So we like know what it's actually like. But like people from the outside might like have a certain perception given what, what is in the article and what other people are saying. So I feel like there's the clarification that can be done. I at least had a bunch of interviews where people were not very pleased with that being in the article. I had to like clarify. Like no, that's not really what it's like. Like it's about getting stuff done and.

Robert Ng (7:01)

That does involve a lot of work.

Advith Chelikani (7:03)

But it's really just about output and like moving fast.

Marty Cautious (7:06)

Yeah, I think that's a careful distinction that we at least I've been telling people it's like as founders we're 996 and we're very happy to do 96 or more than that. But for the employees it's like hey, like we, we understand that like you have your own life and everything. I do think that some people do work really long hours and work really hard over the weekends just because they, they love their craft and they just when they're bored after dinner they just start working or like over the weekend. But like it's not like a requirement and everybody kind of knows that.

Robert Ng (7:32)

I will say though, like now especially as we're building our like a view on leadership team, we have like our head of sales is in on Sundays, like just the entire day and like grinding all the freaking time. And now that we're starting to recruit for a head of marketing, I almost feel like we, I don't know, I feel like now the bar has been set so high where I feel like we actually need, I feel like almost for the exec team maybe there's like different rule sets that we should apply at least on a go to market side. This is maybe different. Different because the thing is we've actually even split the company into like two now. So we have market on one side or specifically sales and marketing on one side of the office and then engineering, product design, CS on the other. And actually the two cultures are completely different totally.

Jennifer (Interviewer) (8:17)

Which always happens with B2B enterprise businesses. But I think in this case even more so there is the role and the responsibility split. But also I'm curious, given the nature of the working culture, does that impact sort of either the age group or type of people that you attract? Because I do remember that you mentioned the article where as founders you want to work very hard and you think employees should see that as positive because this is most meaningful work to you and you're building this to a success where they're not expected to do so, but they should be very motivated to see the founders are working super hard and treat this as their life's work. But I'm just curious about how you think about how it impacts sort of the dynamic you're bringing into. Into the.

Robert Ng (9:05)

I mean it should trickle down at least a little bit. I feel like we should have the expectation that people will work like some percentage of what we work. Right. So it's. And, and I think it is also motivating the people who just like know and they're experienced and like they're, they're not going to care. They're just going to work the hours that they want and go home when they need to, et cetera, because they just know they're going to do a good job and be efficient. I think we do enable then the younger set of team members to like stay in late and I think they get really excited about that. Like there are, there are a couple new.

Advith Chelikani (9:32)

Yeah, but I think it's about, yeah. Making it fun for the. Or I think they will stay late if they're having a good time and they're like seeing, you know, the company move forward. They're like, this was the same when we were new grads. I think like a lot of my social life was around the people at work and it was, I didn't think about that. I was working a lot. It was just a lot of fun and it was like blended work plus fun. And so at least that feels great if we can give that to people. Yeah.

Jennifer (Interviewer) (9:55)

What are some of the intentional decisions you have made that's impacting either the cultural aspect of how people are working together and bringing the fun. I remember when you're doing all hands, there's a lot of shout outs. There are also like the hand raisers. They're also like, you know, the different events you put on together. Like are those type of things you're trying to leverage to sort of bring the team closer with each other or like what are the other things you have done that find useful?

Robert Ng (10:30)

Yeah, probably one of the biggest is just the in person culture. I think it attracts a lot of people who explicitly are looking for that and they're like burnt out of being remote or they don't get to interact with their team members or get onboarded or learn from them. So I think in person is probably like one of the biggest things. I think I was gonna say we.

Advith Chelikani (10:48)

All eat lunch together for the most part. I think that actually has helped us get away with like way less process or like cross functional things for a longer amount of time because people just ended up talking to each other and people find out what other teams are working on, what the other people on their team are working on as the team grows. So that feels like it's gotten a lot of lift. Yeah. I don't know if we plan for all of this to happen, but that's been the side effect of that and.

Robert Ng (11:11)

Another one that I don't think we even realized how rare this was. But transparency on company metrics, which I then spreads to the rest of the team, like, everyone sees every deal that is won and the amount every person sees what deals are lost and the reason, like churn as well. And then there's also like a live company dashboard that everyone can see our revenue every single month, like in that moment in time. So. And then at the end of the month, we send you, of course, our investor update. They also receive that same update with cash and bank burn, all that fun stuff. And like, you know, what went well, what didn't go well. So the team is like very. Yeah, they're very aware of kind of what's going on in the company. Of course it's easier when things are going well. I think when one day things are going more poorly, maybe we'll have to lock down some of the information. But at least right now I think that's been really, really helpful. And then also this is probably reflected just in the way Robert Adveth and I engage is like we have this core value now, which is we are happy grinders. And you like to describe this as like the high competency, low ego, kind of like debate style culture. And it's, you know, if you, if you heard us, I mean, you've heard us, I guess in conversation in board meetings. Like, we just, we're very transparent and very direct and it's. We just debate ideas until we get tired and there's no like ego in it. It's actually we just are aligned on the core thing that we want to accomplish, which is build a really big generational business. And yeah, we're, we're not. Yeah, we're we're low ego about the.

Jennifer (Interviewer) (12:42)

Conversations we have on the point of transparency. Pylon that you guys are probably the best example of building in public. A lot of things are being shared very public on LinkedIn, on Twitter, of either business metrics or you did a fundraising of serious a. That was a very popular tweet.

Marty Cautious (12:58)

How.

Jennifer (Interviewer) (12:59)

How has that impacted sort of how you're seeing this, this benefit of building in public and how did it get comfortable also doing. So you're a LinkedIn influencer.

Robert Ng (13:11)

Let's ask you the question. Did you. Were you influenced by us before you invested in us? Do you remember? Were you seeing our content?

Jennifer (Interviewer) (13:19)

I definitely remember every time I open LinkedIn there was a pylon post. So the keeping top of mind part definitely worked very well. And yeah, it's great to. To. To hear from a first party perspective of what went well. What not like the thinking behind each decision just reads very thoughtful and I certainly liked a lot about that.

Robert Ng (13:43)

Yeah, I think for us. So originally it was just for pipeline generation and so posting like really shitty content. Originally it was so bad. It was. Do you remember that one with the magnifying glass?

Marty Cautious (13:55)

Oh, I'm thinking of the cheetah one. Oh, that was really funny.

Robert Ng (13:58)

Basically there was. It was so bad in the beginning. There were like months. And what's funny is like the history of that. It was so not planned in the way that some people might think of. Like, oh, we were like, very strategic about it.

Advith Chelikani (14:11)

Actually.

Robert Ng (14:12)

There was a YC founder from our batch who said, like, oh, I have like a few thousand followers on LinkedIn, which we thought was huge at the time. Like, oh my God, this guy's massive. And he was like. And he.

Jennifer (Interviewer) (14:23)

How many followers do you have now?

Robert Ng (14:24)

Like 45,000. So definitely growing.

Jennifer (Interviewer) (14:28)

Wow.

Robert Ng (14:28)

Yeah, we're getting there. We're getting there.

Jennifer (Interviewer) (14:31)

What's your goal?

Robert Ng (14:32)

I mean, just revenue, that's all. Somehow I need leads. We need to translate.

Jennifer (Interviewer) (14:39)

Is there a goalpost of like person or company X that have way more followers than.

Robert Ng (14:45)

I think there's like one person in the customer success space who actually just retired Nick Mehta, who started Gainsight and he has like a hundred K followers. And so you're halfway there. That's pretty crazy actually. So, like, in terms of influence, that is like an insane, like, we're quite far given how long we've been doing this. So that is exciting. But I feel like there has been a little bit of a plateau in like, maybe we've saturated a lot of the people that you know really like the type of content we produce. So yeah, we need to keep expanding. But when we started it was just, hey, we want to produce pipeline. This other YC founder told us that it's working for them. And so we just started posting like anything about at the time, like how to do customer support on Slack and it didn't work for months. And then there was one post that we made about how, you know, it took us 17 days to go from idea to paid MVP. And it was a photo of the three of us in our apartment at the time. And that post just like absolutely took off. I didn't even realize it had taken off actually. I remember adv you like three days later, it's like a weekend or maybe Monday and you're like, oh, I think the post is doing really well. And it like suddenly check, it's like, okay, hundreds of likes. It's like, wow, that's like more than the five that we usually get. And then it like it went up to like a thousand plus and 300k impressions. And I don't remember if we like immediately saw the demo spike or something. Like I don't remember having that thought. But we definitely started hearing from prospects coming in that like, oh, we see you guys on LinkedIn or even just like anecdotally at events that we would go to, it's like, oh, we like, you guys seem to be doing well. So this perception started building that first off people know who we are and then also they think we're doing really well and they're excited about the content. So we tried to replicate that post many times. And that post, what it really told us was people like stories and they like the build in public type content that I think really beforehand was not present on LinkedIn, I think it was present on X, but never to this. More like professional network.

Jennifer (Interviewer) (16:39)

Definitely you have definitely figured out at this point the algorithm to hack LinkedIn. Switching gear to Pylon. Tell us how Pylon is not just another support ticketing system or a chatbot.

Robert Ng (16:53)

Yeah, so we're the first customer support platform that's built for B2B companies. And so one way to think about this is if you just look at consumer companies, they just have one customer facing team which is just the support team and they deal with very simple transactional tickets. In B2B you have many customer facing teams that all should be working together, sharing customer data, sharing customer workflows. And so you end up buying this combination of tools, not just like a customer support platform, but things for Customer success, account management, professional services, solutions. And we've built one product that's encompassing all the needs of all those teams. And so that's what that B2B focus looks like. And of course, if we have all these workflows and data altogether and these different teams working within it, there's a lot of opportunity for AI to make things a lot faster, for sure.

Jennifer (Interviewer) (17:38)

And tying back to the earlier question, if you want to build something really fun, B2B support is probably not the first thing people reach out to of, like, this is so fun that I'm building a B2B support system. How did you get to this idea and what was the navigation and the pivots throughout the way?

Robert Ng (17:53)

Yeah, I mean, there were many pivots. Do you guys want to name a few? Like the.

Advith Chelikani (17:57)

We started.

Marty Cautious (17:57)

Yeah, tech, I think, and then we.

Advith Chelikani (18:00)

Started by building this idea. Most easily accessible people to do user discovery on was. Well, first. We basically started the whole journey by first deciding we want to start a company and then figuring out what to work on. So it was driven by. To your point, the fun is more like the journey rather than the specific thing we're building. I think it's pretty easy to get excited and like, intellectually curious about most types of things. And so, yeah, we're, I think, more excited about the process of company building. The first thing we worked on was we went back to college and, like, those were the easiest set of people to do user discovery on. And so we talked to a bunch of the administrators and asked them what problems they had. The career center lady had said terrible ideas about college, like alumni being connected with college students. So we built some kind of portal for alumni to get connected to students.

Marty Cautious (18:43)

We built every mistake possible. Like, we were just like, building before, like, selling. We were working in these tar pit spaces that don't make any sense to build a company in. Yeah, it was pretty brutal, but yeah.

Robert Ng (18:56)

And then also important context. Like, we at different points were working separately as well. And so you guys. Did you guys also work on things separately beforehand or just together just to get. Okay, so. Yeah, so you guys start together and this is like a year and a half before pylon, right?

Advith Chelikani (19:10)

More. Yeah, it was like shortly after the pandemic. Yeah, I think I messaged Robert and I was like, I was having a existential crisis of, like, I was. I think we started on my 23rd birthday when I was like, I feel like I'm wasting my life. Do you want to work on something?

Robert Ng (19:24)

Yeah. And then separately, I had left Airbnb maybe like half a year before they started and was like pivoting through many ideas with two different sets of co founders actually. And at some point. So I then, you know, these two sets of two co founders didn't work out for many reasons. Also like the same classic mistakes of one was like, oh, like work with the business co founder. And then another was hey, like I couldn't convince the person to leave their company and they were kind of later stage in life and had a family and didn't want to take the risk. And then I like, you know, courted them strongly and. And they rejected me multiple times. Like I actually. So I like we had like the reason. Well, we can ask them right now. But there was a good reason.

Marty Cautious (20:07)

Yeah, I think it makes sense.

Robert Ng (20:09)

But basically, okay, like you know, I'm messaging them. I'm like, hey, you guys are doing sort of stuff. We're doing startup stuff. We like talk. Robert and I didn't know each other that well at the time, so it was primarily like at this being the glue. And so I had messaged you, you were like, I'm working with Robert on these things. And then like we kind of like, I remember like have some like messenger video chat or something. And then I thought they were down to work with me. And then a week later I'm like, so when are we getting started? And then they're like oh, like I don't know about that. And so that was rejection, like number one. And then we came up for a KP fellow alumni or I came up. You guys were in. I was in LA during the pandemic and then you guys were in SF working on your ideas. I came up, tried to convince you guys again and literally like I remember, I think it was like a Friday. You guys had said like no again. And you're like, we're actually going to go work with these other guys who like understand the logistics space because that's what they were working on. And then. Yeah, you guys. Yeah. You were like, oh yeah, we're going to do that does make sense to work with you. So I gave up this.

Jennifer (Interviewer) (21:11)

And then serious co founder chasing.

Robert Ng (21:12)

Yeah, yeah, yeah.

Jennifer (Interviewer) (21:15)

Just co founder dating.

Robert Ng (21:16)

Yeah, no, I mean I got, yeah. Rejected twice by these magnificent people. Very, very hard to chase. I purs. I pursued but then I gave up. And yeah, you guys had decided to work with these other people and then what say what happened over that weekend when you basically.

Advith Chelikani (21:35)

Yeah, we, we were pretty excited about this logistics idea. It was kind of related to what I was working on at Samsara, spun out and like explored more into an idea. It actually felt like the first idea that like passed the mom test for us and was something that couldn't turn into a big company. But we determined that we didn't have enough founder market fit there because it would be a very sales heavy idea in like the freight brokerage space. So then we were paired trying to pair up with these two guys who had like, I think started unicorns in the logistics space and had a sales background. But then we realized that we thought they weren't going to do that much work, but they wanted 50% of the, of the company and so we just couldn't reach a conclusion on the equity there. And then we also learned that you shouldn't choose your co founder based on like the idea you're working on because you'll probably pivot. And yeah, it actually would have just been poor all around. But we came to that conclusion and then we're like, okay, we shouldn't pair up with random people. Yeah.

Robert Ng (22:24)

So then on Monday or like maybe like the night before, they messaged me, they're like, hey, do you want to cowork from our apartment?

Jennifer (Interviewer) (22:31)

And I, the co founder work trial.

Robert Ng (22:33)

Yeah. And I actually, I'd given up. I was like, yeah. I mean, they literally rejected me three days ago. They're just trying to hang out. That's it. And so, yeah, like show up in the morning, like, sit down. There's like this like mini like desk clump in their apartment. And yeah. And then like Adiff turns to me and he's like, so we talked about it and I think we should work.

Advith Chelikani (22:52)

And I'm like, what are you talking about?

Robert Ng (22:55)

I was like stunned. I literally had been like three months of me like trying to get you guys to say it.

Jennifer (Interviewer) (23:01)

That was no idea or no, no.

Advith Chelikani (23:03)

So the context that he left out is that the reason we just, we thought it wouldn't be a good idea to work together is it felt like in the period where you like don't actually have an idea that's validated, more and more people piling on becomes a crude term of like intellectual masturbation. We're just like telling each other the.

Robert Ng (23:19)

Idea is good and like, it's like kind of going in a circle and.

Advith Chelikani (23:23)

You'Re not, because you're not in execution mode. So you can't like unload your resources on like trying to execute. You're just like kind of thinking and doing user discovery. So it felt counterproductive to do that with Too many people. So we're like, okay, once we come up with an idea and we're committed, maybe then it makes sense to like pair, like pair up. And at this point, that's why it felt like this logistics idea was pretty validated and so we could like start to move into execution mode.

Marty Cautious (23:43)

Yeah, that's the pretty good terminal idea. Honestly, like when we were validating the idea at yc, like we listed all the ideas we had, we had worked on and it was. The logistics idea was like clearly the best one.

Advith Chelikani (23:55)

And like they recommended we work on.

Marty Cautious (23:56)

This idea and they told us the pylon one is like, okay.

Jennifer (Interviewer) (23:59)

But like, obviously you went in with that idea, you came out with a pylon idea. So what happened there?

Robert Ng (24:05)

So this was actually very, very helpful that it worked out this way because we, we. So I had an idea that was some like fintech thing and they had this idea that was logistics. And so, okay, we both have an idea. How do we decide which one to work on? So it actually forced us to be more critical about idea evaluation and comparing. So we literally wrote down, we're like, okay, well let's like explore both. And so I think we spent like a day or two looking at both ideas, like trying to map out the markets for each one. So we literally have a Google sheet that we could find where it's like, okay, this fintech idea, if it goes perfectly well, here's how much revenue we could generate if we capture the whole market, right? And so that one was I think like high tens of millions. I think it was like 40 million in revenue. It was like max. It was small, right? That's like, max, we win the market. Then the logistics idea was like hundreds of low hundreds of millions, I think in revenue that for that initial product idea. And then we had this idea that working on B2B SaaS at the time was kind of like selling out. And it was like, you choose all the cool things were like dev tools or some vertical SaaS thing. And then B2B SaaS was where people iterate to and they're like, once they get burnt out on trying other cooler ideas. And I don't know, we put. So we had, because we were in idea evaluation phase, we had idea one, idea two, and then we put rippling in like a third tab and we're like, okay, how big is rippling? And we just realized that the market for rippling was so big because you just take everyone who needs to be paid money for payroll, just multiply that times a number and you're like, oh my God, the order of magnitude here is probably. It must have been like hundreds of billions or something. Something crazy.

Advith Chelikani (25:37)

I think it was like tens of billions.

Robert Ng (25:38)

Tens of billions. So like two orders of magnitude higher. And so that exercise was actually incredibly helpful because then it was like, okay, we have to critically think about ideas and battle test them against each other. And so it was actually one of our first big decisions or learnings that, okay, this is how to think about the difference in these ideas. And then also throughout the process of idea evaluation, we had decided that the goals of the so understanding the motivation for us, we were very aligned. That the why was kind of fun. And like, hey, we had all romanticized this idea of building a company and that was what kind of pushed us. The what we decided we just wanted to build a really big company, honestly, like just a good business, which is like very counter to, I think a lot of founders who are very obsessed with just like, hey, I want to build like a really nice product or something. For us, it's like the business is really important. So yeah, we looked, we looked at, you know, this is over the course of like many months and throughout the history of the company. But like we would look at, for example, how many SaaS companies got to certain sizes and went public. And so for example, we looked at, hey, 76. There are 76 public SaaS companies who are worth over a billion dollars at the time. And this is measured by like cloud spend or their cloud software is more than 40% of their revenue. So we found some list that did this. So only 76, which is really small for 1 billion. Exactly. 10 billion is 26. That's like crazy. And then 100 billion was like 4. And so it's like, okay, wow, that's not a lot of companies. And so if you observe, if you just try to like understand why did some companies get to $10 billion market cap that we're able to then see, really market was a really, really big differentiator where you just, no matter what, it's going to be a competitive landscape. And so you may as well choose the mega markets to go after. And that's going to give you the biggest success of building something big long term. Because the worst thing that could happen is we execute perfectly and spend 10 years doing something. And we were capped from the start. And so we were only evaluating basically horizontal categories at that point. And so things like sales, marketing support, payroll, et cetera.

Jennifer (Interviewer) (27:50)

Great. It clearly went from the top down math to find the biggest Market and then find the horizontal nature of the categories to go after that. That said, Support itself has already quite a lot of players. There's Zendesk, their Intercom. There are a lot of AI native conversational support bots and systems where Pylon is really focused on building this multi product, cross functional, more platform style with very AI native functionalities and features. Do you think you had a clear vision on this is where you want to go in the beginning or what were the moments where you find clarity? There is a big opportunity here. Like this is how we should, you know, cut into sort of the space and have a very, I guess both retentive but also growable base.

Robert Ng (28:53)

Right. It was not clear from the beginning. Well, what we knew is we wanted to be in a really big market so that we could eventually pivot and grow into something. So we understood that like often people wedge in with something and then kind of like expand later. And so customer support like go to market systems was generally what we were wedging into. And so our first actual insight was, hey, within go to market a lot of people are starting to talk to their customers over shared slack channels. Microsoft Teams, Discord, WhatsApp, kind of like new conversational tools. And those were for the first time becoming popular not just internally within a company, but between them as well. So for example, one of our first customers, Hitouch, they had like 300 shared Slack channels with their customers. And that was, you know, that was totally different than supporting them over email or like a chat widget interface or ticket forms. And suddenly they have all these customers speaking there, they're sending marketing updates there, they're getting product feedback, they're getting support tickets, but none of it's being tracked. And yet none of you basically can't scale that way. Even though the customers really want it, the vendor really likes it as well. So the insight was, hey, this is happening and there's no solution to help people actually work in this way.

Advith Chelikani (30:05)

So one of the criteria for an idea for us was like why now? Why is it compelling to start this company right now? If you started two years in the past, something would not. If you think about problem companies on like problem solution, willingness to pay, either problem is not there in the world or so technology for solutions not available two years ago or something. And if you started two years in the future, somebody would have beaten beating you to it. So this like trend, when we surveyed a bunch of people felt like a clear like change in the way that people approach talking to their customers. Plus you know, Shortly after the AI stuff you feel like you can build a way better solution when you have access to conversational data. So it felt like a very opportune. Why now?

Jennifer (Interviewer) (30:41)

Yeah, now it feels like a default of like when the two parties start to establish a commercial engagement. The Slack channels are set up first and then you figure out sort of where it goes from there. And also my takeaway is the forward deploy engineering phenomenon is actually a very huge tailwind for tools like pylon because the FTEs needs to converse with the customers very closely and sort of back and forth. It's very different from in the past. You email a ticket, you get back. It's very much co working culture in Slack and you still need a system to manage that. And Pylon many times more often than not it's the default tool for this. I have a question related to this which is a lot of times the support and very close engagement with customers also hides a lot of the technical operational debt for the customers as well. Because if it's a broken onboarding, if it's unclear documentation, usually you can solve it by having more conversations, but long term it probably becomes more of a burden. How do you help customers navigate that? And is that something, you know, you're very consciously building products to resolve or kind of.

Advith Chelikani (31:54)

I mean a lot of it is like using AI to structure the conversational data going on. So a lot of our feature set is like drawing insights from that. So whether it's like identifying product feedback or common. One of the features in the product is this idea of identifying gaps in your documentation where we'll cluster all the conversations that we're watching, whether they come from like Slack or email or you know, synchronous stuff from calls and cluster them into like topics into topics and then you can identify the fact that you're missing documentation based on those topics or like something's a feature request and it's a gap in your product. So we try to give you tools to like reframing that. Yeah, tools to like operationalize the way you're doing support to start, but now customer success, more forward deployed. All these like customer facing roles, how do you like operationalize them? Because also a lot of our customers are trying to run lean but do stuff at a bigger and bigger scale. So I think it fits into that story as well.

Robert Ng (32:43)

Yeah, and one of the really important pieces of context for our customer base is because we focus on B2B. There's so much context and data about customers everywhere. And so especially when you think about all the AI solutions people are building. If you want to have even like a shot of having an agent do some piece of work, they need a lot of context across a lot of different systems. So our customers will have support teams, success teams, solutions teams, and all of them kind of have notes or call recordings or projects that are kind of stored in these different systems. And because we are building the one platform that can own all that data and all those workflows and frankly also the place where all those actual human agents live, that's setting us up really well to build a combination of assistants to make them faster and then agents to kind of span all the different functions of work that they do.

Jennifer (Interviewer) (33:34)

How do you see AI as technology impact your roadmap? I believe when you started Pylon, chatgpt moment hasn't happened yet.

Robert Ng (33:43)

Yeah, it was. Well, so right as it happened, I.

Advith Chelikani (33:47)

Think the company incorporated on the day ChatGPT launched, so.

Robert Ng (33:50)

No, no, no, it was seven. Seven. Oh yes, yes, you're right.

Marty Cautious (33:52)

We had the Same birthday at ChatGPT.

Robert Ng (33:53)

Yes, we had the initial idea for Pylon which is. Well the idea was, hey, there's a problem with Slack support. So you know, that's November 21st. I want to say one day later Zendesk gets acquired, which is also important context by private equity. So one day after we had the initial idea and then like six or seven days later ChatGPT comes out. And so the timing like was incredible. Like we could not have nailed the timing better.

Advith Chelikani (34:20)

So we have built everything like knowing or we have built everything in an AI native way because we knew it existed from basically the beginning. So I think a lot of the. Oh like unlock of having conversational data is only powerful because of a lot of the. Yeah, chatgpt.

Marty Cautious (34:34)

I think we also took a very product first approach there too because I think a lot of the other people in our batch were just like throwing AI at the wall and seeing what would stick. But we went to the customers first, figured out what the problems were and just made sure that AI actually was the answer. We were very skeptical of AI to begin with, but it ended up being the right answer for a lot of the use cases. And now it's kind of like a core part of the product or everywhere in the product.

Jennifer (Interviewer) (34:54)

And these are not functionalities like auto resolving like a ticket because the B2B nature and the very unique context rich nature of these tickets, it's very much around auto tagging, around like context summary, like a ticket summary, like going, going back to to history finding the relevant information.

Robert Ng (35:13)

Yeah and what's so cool is like I mean man this was like amazing that we just landed here with the original problem. Like Adventh already mentioned this but there's so much conversational data that previously was totally unstructurable, meaning you could not really build automated workflows off of this unstructured data. And so now it's like imagine there's the obvious use case of hey, a support question comes in. First off, many questions come in through support channels or other channels and they might not even be support questions. So step one would be identifying who should this actually get routed to? Is this a piece of product feedback that we should auto log to linear? Is it something that should be routed to the solutions team because they're mid migration? Is it something that should be routed to the security team because it's a question about their SoC2 and so that's an easy example. Hey you would come in, the previous workflow would be hey we have a bunch of keywords to mark priority. If they say urgent or priority or whatever then mark it as high priority. Now we can use AI to understand and prompt on top of the question that comes in and then route it to the right place. Or for example a lot of our customers are using a product we have called account intelligence to build signals on top of the customer data. So across the call recordings you have across the support tickets that come into pile and across stuff in your CRM you can build these signals that tell you hey, this customer might be interested in purchasing this additional SKU that you guys have. Or hey, they're at risk of churn because they're starting to indicate these things that usually tell us that are usually early signals of a churn risk or hey, they need onboarding help. And so you can take this unstructured data, structure it into these signals or different fields and then build automated workflows off of it which is like and then that doesn't even have to be customer facing. It could happen internally and just alert the team to help them prioritize accounts better and take actions faster.

Jennifer (Interviewer) (37:02)

Definitely these are the reasons why many AI native companies or the modern I guess SaaS companies are using pylon as the default solution from high touch, any scale to apply intuition. Many, many great logos. Now that you are at the spot of I'd call early product market fit, how do you think about the next three to five years? Like what's the ultimate vision of pylon outside of like being a ten hundred billion company what are some of the big bets that you need to make today that will influence the outcome?

Robert Ng (37:30)

I'm curious, what do you guys. So first off, by the way, like for context on who like makes product decisions, it's these two.

Jennifer (Interviewer) (37:36)

You guys are selling it, dude.

Robert Ng (37:39)

I just post on LinkedIn at this point, but Robert and Ave. Yeah, what do you guys, product wise, what you doing are.

Marty Cautious (37:44)

I guess the way I think of it is like we're taking a very rippling like strategy. We're trying to be a compound startup and spin up like several different verticals. You already see with the support vertical and the account intelligence vertical, trying to go after like the customer success, account management Persona. It's kind of like spinning up what those next verticals are going to be. I think it's a very risky but like high risk, high reward kind of strategy here. And I think like we're, we have things in the works I guess and.

Robert Ng (38:09)

Also one, one thing about like market. So I think a lot of people, especially in the AI support space are going straight enterprise, which makes sense if you're just doing like for example transactional ticketing on top of an existing support.

Jennifer (Interviewer) (38:21)

Platform because that's where the highest volume of conversations.

Robert Ng (38:24)

Exactly. But actually we're like capturing the next generation of people that are starting now or growing quickly. So the up to 500 employees generally customer Persona. And so we're capturing those people and then teaching them the pylon way of operating and so they might onboard with, hey, first they use our ticketing and then it's like hey, now we need to understand the health of our customers and who to prioritize. Okay, we have a solution for that. Okay, we now have multiple team members who need context on accounts. Okay, we have a solution for that. And so we capture them early, they start to grow, they start to have these additional problems and then we start to give them the solutions that they need that are the new AI native way of operating. That's all in one platform versus having to go and buy five separate tools. So I think right now a lot of people call us like or we, we call ourselves. We made this up. It's not other people, but like that. We called ourselves for a long time like the Zendesk killer and it was very focused on just the ticketing aspect. But now we're like increasingly have all these additional products where there'll be very much a like hey, like pylon is this like all in one tool. It's going to have all of our customer operations needs versus like Separately I'd have to like buy Zendesk and like vitally and like you know, all these other like CS or account management related gainsight. Right. A separate AI products. Like people buy like five or six tools. Like it's crazy. And we, this is, this is one of the things that AI actually enables is like we as a team just move way, way faster than everyone else at this point. Or not faster than everyone else, but now you can build a company like this that has this product surface area. And so yeah, it's possible for the first time. We're like executing super heavily on it with a cracked engineering team. And yeah, I think, yeah, you're really.

Jennifer (Interviewer) (40:02)

Building the operating system for companies that are touching customer or all the customer facing teams that are having conversations and touch points.

Robert Ng (40:10)

Yeah, and they're.

Marty Cautious (40:11)

Because we control all of the customer data or we're attached into where you talk to your customers both on the call recording side and the Async support like support ticketing side. So like because we have access to all the data, we can do everything that flows down from there and like set up those verticals. I think like in the long, long term it's kind of going to be around like the future is not just like individual people kind of like doing the work that they're doing today. It's probably going to be people orchestrating AI agents or something like that. And like how can we be best positioned to kind of like build that next layer and like the future of all of these different roles.

Advith Chelikani (40:43)

The way I explain to people too is that we are trying to smooth curve businesses like legacy system of record to like some fully agentic thing where that's not the state of both people's perception of the technology and the technology today. So we're trying to be like the new age system of record, system of engagement, system of intelligence and then you know, agents doing all your workflow. So for now it's like people and agents coexisting within the product. And because we got to build it that way from the start, we can like help people transition to this fully agentic world. As everything is ready for that, all.

Marty Cautious (41:13)

The other incumbents are probably going to run into the innovator's dilemma where they're going to be afraid of throwing away their product to shift to this new way of doing things. But just because we've built it from the beginning, that way it'll be much easier for us to get over the dilemma.

Robert Ng (41:27)

It's also crazy, I mean surface area wise, I mean you tell Us. How impressed were you when you saw what we.

Jennifer (Interviewer) (41:32)

It is an incredible large surface of product.

Robert Ng (41:34)

Yeah. So like, I mean that is a fact.

Jennifer (Interviewer) (41:37)

Thanks to Robert and Ben.

Marty Cautious (41:38)

Adam.

Robert Ng (41:38)

Yeah, well, yeah, and it's funny like, yeah. I remember when we demoed to you the first time when we were raising our Series A. Yeah. You and the other partner, the partner who was on the call, you guys were like this is. We ran out of time to show everything and that was like at series A. Right. With we had probably what like 10 people at the time and like already the pro. We could not demo everything to you in like a 45 minute call. And now it's like, I mean we're about to. So I think we might actually be one of the fastest moving product teams of all time. Like I'm not kidding, like it's certainly.

Jennifer (Interviewer) (42:13)

Among the top that I've, I've seen.

Robert Ng (42:16)

Like, I think when we.

Jennifer (Interviewer) (42:17)

It's a lot of new feature launches which is why you know, every, every day I open LinkedIn, it's a, it's a new feature launch.

Robert Ng (42:22)

Yeah, it's actually crazy like when we think about other companies who have tried to execute like multi product strategies, we. So we love studying the history of all these companies that have come before us and like our favorite is Ripple Rippling is like such a great company and even them, it took them multiple years to launch product number two or three. We started building out the ticketing support platform at this point I think a year and 10 months ago. And we have now built the equivalent of Zendesk. We're close to building the equivalent of Gainsight. We built these AI agent products that are people's whole companies and it's been a very short period of time and so yeah, we are moving. I think we might be the fastest company to ever execute this type of strategy and yeah, it's crazy to see so far it's successful.

Jennifer (Interviewer) (43:15)

Last question. You're certainly at a point of pushing the boundaries of what's possible of also building a new generation of AI native system of record for companies to operate on top of. When you, when there's no data, no consensus and no time given, you're moving very fast to make these decisions. Whose voice do you trust the most?

Robert Ng (43:40)

Whose voice do we trust?

Marty Cautious (43:41)

I guess we just argue each other.

Robert Ng (43:42)

Yeah.

Jennifer (Interviewer) (43:43)

Is it your instincts?

Advith Chelikani (43:45)

I think it's a lot of gut as well, but it's informed by like a lot of like being in the weeds still on like all the customer calls, like both from the sales side and the post Sales side. So feel like, I mean, the root of it is like customer what people are saying in the market. But I think we apply our own layer of like, interpretation.

Marty Cautious (44:03)

Yeah.

Robert Ng (44:04)

I will say like Robert and Advent have incredible product intuition. Like incredible product. And like, I mean, part of it is like the, you know, what if they're a tie? What if they're.

Advith Chelikani (44:15)

Well, no, no.

Robert Ng (44:15)

So I'll tell you exactly what happens. So like we. And by the way, I used to be in these debates too, and I just kept losing, so I like gave up. But this is how we solve all problems in the company by debating super heavily. And it's like the steel sharpen steel mentality where it's like, okay, we know the end goal is build this generational company that goes public in this period of time that gets a billion in revenue. Right. So that's what we want to accomplish. And so always when we're debating ideas, it's with that insight in mind. And so, yeah, both, whether it's like a business or strategy discussion, we will just debate ideas heavily. So we'll bring up a thing, all three of us will be in a room, and then we'll just like argue about it for like hours. And it's like, in fact, we use, and we used to do it very publicly within the company. So probably up until like 10 people we would just like yell at each other. And it's not, it's not like in an angry way. It's like in a, like, we just were so, like having so much fun. Honestly, it's like debating for sport. And so you're, you're basically just like getting excited about. No, like, that doesn't make sense. Because of this thing. Or like, oh, like we, yeah, this. I, yeah, we should take this other strategy instead of. And it's almost like fun. It's just incredibly fun. Our team thought we were like in crisis every day because they would hear like us saying, in fact, I remember at some point we were like, yeah.

Advith Chelikani (45:29)

We should probably stop arguing in front.

Robert Ng (45:30)

Of the rest of the company.

Jennifer (Interviewer) (45:32)

So do you still do that or.

Robert Ng (45:33)

No, now we do it in private. People would freak out, especially the new people who are not used to it or hadn't seen it. But we would get so passionate about the different ideas that we wanted to debate. And so what happens is, okay, we have a problem. We are going to debate the idea very heavily. And it might be something so small. There are some really tiny things that we debate on, but we'll debate it super heavily until we get too tired to make a decision. And if we can't make a decision, it means we don't have enough information. And if it's not critical or priority enough, we have to push it. Otherwise we debate until we kind of all arrive at the same conclusion. And if we don't arrive at this, it's rare, I think, that we don't arrive at the same end conclusion because at that point we've explored every outcome of where each decision could take us and it's a very fun and exhausting process.

Jennifer (Interviewer) (46:29)

Sounds very intense.

Robert Ng (46:30)

Yeah. And so it's super high intensity, I think. I don't know if other teams do it to the same level that we do, but it's very fun. I think you have to love it. This is very much like a like sport almost in itself. So awesome.

Jennifer (Interviewer) (46:44)

Cool. We're at time. It's so wonderful having the three of you. I feel like we need a part two for this conversation. Thank you so much for taking the time.

Robert Ng (46:51)

Thanks, Jennifer.

Marty Cautious (46:52)

Thank you.

Podcast Host/Announcer (46:56)

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