AI to AE’s: Grit, Glean, and Kleiner Perkins’ next Enterprise AI hit — Joubin Mirzadegan, Roadrunner

During my sales career, probably the number one thing that used to break my back was that the underlying software with, like, Salesforce CPQ and others, just to, like, create a quote, get it approved, is horrific. Like, you think if you think you've seen bad software, you haven't until you've seen a thirty second loading screen to get from one page to another when you're trying to close a deal with, like, two days left in a quarter. This is just, like, standard across the industry.

So I worked at every job that I was ever at. I used to get yelled at because I would, like, be asking people to, like, turn something within a day or two because I needed to get a quote out the door. I was like, oh my god.

I actually think you can abstract away a bunch of the complexity with these LLMs, and it's, you you know, know, unstructured and structured text that you can reason with and do stuff with. Right? Like, that's why coding is such a great use case.

That's why Harvey is such a great use case because you have, like, all this case law, and you can point the LLM at it, and you can reason with it, then you build a bunch of enterprise features and functionality and workflows on top of that. This is a very similar problem in nature. And so that was, like, the light bulb moment of, okay.

I think we can actually build something better. I feel good. I feel comfortable in this seat.

How's my levels? What's that? How's my levels?

Yeah. You're good. Alright.

I gotta ask you, how was the how was the Zuck interview?

Were you nervous?

It's pretty exciting.

I think the transition from the CRO to the founder, whatever happened, like what episode 70 or 80 when I was like, because it was only CROs for a while. The thing that I found refreshing, I'm curious if you've seen this, is that founders and CEOs have an authority to speak in a different way than somebody on the executive team where they can just talk. And so much of what I wanna do is have like an earnest and honest conversation.

And it's harder to do that when you're thinking, is my boss gonna think? Yeah. Whereas if you're the founder, You can just just speak, you know?

you know? Yeah. The first one.

Yeah. Yeah. Yeah.

Yeah. Yeah. I I did.

I I I appreciate it, man. It's a as you know, it's a labor of love. Mhmm.

Doing anything every week for six years. Yeah. I mean, I guess it started every other week, and then it became every week after this transition from chief revenue officers to to CEOs.

Yeah. Exactly. Doing anything for that long every week, you better enjoy it.

Yeah. You know, like, I've always told myself the minute I stop looking forward to sitting down with someone and talking to them is probably the minute the show should be over.

joined Kleiner Perkins, I was quite young and I was definitely figuring out like what is going on in venture. Can say a little bit what you did before. Yeah, I grew up in startups and then in sales and then had a great run.

Those startups ultimately ended up getting acquired, the last one by Palo Alto Networks, which is like a big cybersecurity company. They asked me to move to the Central US and build out their public cloud business in the Central US. Took that business from zero to quite a bit in a short period of time.

Kleiner heard about the work that I was doing and then got in touch to see if there is an opportunity for me to kind of work with founders on once you've built the product, like what do you do? Yeah. Right.

And I remember thinking at the time like, no way, like venture sounds amazing, but like, isn't that the job that I'm supposed to do, like at the end Like, of my this sounds incredible, but like maybe later on. So anyway, we got to talking and it was became very obvious, like there was a unique opportunity here. Fast forward.

One of the things that ended up happening was I was working really closely with Arvind Deglean. It's actually the last incubation that we've done here. And Arvind is maybe the most genius product and technical mind that I've ever worked with.

He definitely I would say go to market is not native to him. And so he and I were doing a lot of work together to figure out like, alright, we've built this incredible glean product. At the time it was called SCIO or SCIO.

I still don't know how to I still don't know how to pronounce it. And we were running all these routes together of like, I think you should do this. I think you should do this.

And then eventually it became very clear to me that we actually need somebody to run the routes. Okay. Because like I couldn't do it and he couldn't do it.

And so long story short, I started figuring out, well, like, what leaders do I know? What sales leaders do I know? And for me, I didn't know that many relative to a bunch of other people that were doing the job that I was doing.

We've been in the industry for thirty years who are at the tail end of their career, who do have this like coaching tree of leaders. And so I couldn't really help him hire somebody. And I realized then that I needed an excuse to get to know people that I do not know today.

And so that was the genesis was like, how do I figure out a creative way to get to know these chief revenue officers and help them tell their story? You know, like KP was like, you know, maybe prove it. They came to you.

You came to them. They came to you. Who?

KP. Oh, no. I went to KP and I was like, I think we should start a podcast that interviews CROs.

And they were like, mean, it was skepticism would be generous. It was it was you know, we don't do a lot of talking as a firm. We generally let our portfolio and our founders speak on our behalf.

And so, you know, there's definitely, like, other venture podcasts. Most of them are, like, pretty cringe, if I'm being honest. KP was skeptical, and I kinda realized I also didn't do a very good job articulating what I thought it could be.

So I recorded an episode anyway with my old boss at the time, and I sent it to some of my partners here. And I just said, hey. This is what it would sound like.

If you're interested and I still have a job here, like, me know. This is what it would sound like. And they were like, oh, this is actually better than we thought.

Like they had to feel it. You know, it's like a product that they had to actually feel. To Ali's point, we were like, all right, let's just do 10 and see how it goes.

And then after ten, we were like, oh, this is actually, like, kind of working. I'm getting to know these CROs. It's getting easier to get to know them.

And then I made a commitment to myself that I was gonna get to a 100. Like, just told myself, like, I will not make a judgment on what this is or isn't until we get to a 100. Yeah.

My observation is that I dunno if you feel this way, but, like, it's a very vulnerable feeling. Like, even if you're the one asking the questions, not answering the questions, you're really, like, out there. You feel very exposed.

Yeah. And the comments are a vicious place. And so I don't know.

For me, I was like, all right. Until you get to a 100, you don't really know what the quality of the work is, and you kind of are making a pre commitment that you're gonna tune out the noise. Because otherwise, you start overreacting to what any single person thinks about any given episode.

And then usually, I think that's why most podcasts, you know, don't make it past five episodes Mhmm. Is because people start to be like, oh, maybe it's not good. Like, they start reacting.

Right? Each of these slides feels more real. And so that's why I made that.

Yeah. That's why I decided to do it. Yeah.

in the comments because there are no comments. I guess with audio. ITune reviews or with audio.

Right, right, right. Yeah. Yeah.

It was audio only. It was actually easier with them as audio only. Yeah.

In many ways. And not everyone has to be video. Actually, I think the core reason why we wanted to do video was it became very obvious.

Like for me, I listen to more podcasts than most. Like, I'm quite voracious about listening And to I realized my behavior changed once I got YouTube premium, where if you turn your phone off, you know, off or whatever, it's just it's just noise. And then when you turn it back on, you you flip the home screen up, it's video.

Yeah. And so I kinda wanted the multimodality where, for example, if I'm cooking, it's the video's open or if I take a shower, the video's open. And then if I'm on a run or something, I just click it off and then it's just the audio.

It was, I think, more and more obvious to us then. I think quite clear now, I suspect you'd agree that that you you need both.

And I feel like somehow when you start video first, it translates better to audio than the other way around. My only knock on video is that it's default more produced. Yeah.

And so much of what I wanna do is just have a conversation. And the minute that you have cameras everywhere with lights all over the place illuminating something, it feels more noticeable to the guest. You know what I mean?

Like, it just feels more produced. Therefore, they start to imagine themselves as they're like They're on TV. Here's what I want to sound like when I'm on a podcast.

As opposed to here's what I just sound like. Yeah. You know?

And I think as soon as you see cameras and you just start acting differently, it's like, well, this is not how you are in real life. Like what? You know, it's just a different thing.

And so that's my one knock on the on the video format. Yeah. I noticed, you know, you you also did the thing to me where you just start the conversation, right?

You don't have a, well, here's the intro. Here's the birth story. Here's the origin story, which I try to do sequentially a little bit.

But that's one of your tricks. Right? Well, I would say I go through an extreme level of detail to make sure that the guest feels very comfortable when they sit down.

So one example of that is, you know, how you're greeted at the door, water, all those things. The second is recording just starts. There is no, like, okay.

Are you ready? Because the minute that somebody says, like, okay. Are you ready?

Go. You claim up. You're like, okay.

I'm gonna be the guest that I wanna be. It's like, you know, when you're sleeping at night before you go onto a podcast, you're like, okay. How am I gonna sound?

What am I gonna say that's gonna make me feel smart? You know what I mean? Make me sound smart.

And so you start to build this, like, idealized version of yourself that you wanna project to the world, which is, like, not real. And so start talking as soon as you sit down. The temperature of the room.

Like, like the temperature to be cold. I don't want people to feel like they're sweating or hot. Feels like kind of cool in here.

Right? The way that the lights are, you'll notice the lights are all up, not down. Like I I think it bounces off.

Yeah. Think it's important to not make it feel spotlighty. Yeah.

If that makes sense. Yeah. The way that I do prep and then and then for the guest prep, like, for example, I will have read everything about them.

Right? And so I'll build basically my own mental model of who I think they are, and then I'll spend the conversation kind of poking at that mental model. And then I never give the guest the questions.

Because if you give the guest the questions, well, all of a sudden, it's like a rehearsed set of conversations, which is not how real life goes. Mhmm. And so, like, I go through, I guess, kind of a lot to make sure that it feels real.

And I guess If I had Zuck okay.

at the time, in the early days of Glean, it's when Arvin came to Mamoon, this pitch of doing enterprise search was like the eye roll of the industry. Meaning like if you ask any chief information officer, if you ask any venture capitalist, they've been hearing that same pitch for a couple of decades now Yeah. Where everybody has promised, Google included, like the best companies in the world, that they're gonna solve enterprise search once and for all.

And so, you know, I give Mamoun a bunch of credit because he realized that if this problem is gonna be solved once and for all, it's probably gonna be somebody like Arvin that can do it. On the technology side, like AI, this was whatever, 2019, 2038, 2019. This was not like LLMs had not been birthed yet.

Right? And so I think in the beginning, like, it was a pretty serious slog with Glean because you're asking these systems to basically crawl through an organization's entire corpus of data, do it with all of the permissioning, do it with all of the off, like this multilayered cake of protections to make sure that I never see what I'm never supposed to see. Right?

Like, never see Swix's, you know, like comp data, for example. And so getting that right is, like, insanely hard. Then let's just assume, which in Glean's case they did, that you get the technology right.

Then you have to figure out how do you get past the, like, eye roll of all the people that are, like, just default skeptical. Yeah. Like, the category is just dead to them.

The category is completely dead to them. Yeah. Then you've got to figure out, like, how do you deploy that, right?

Do you deploy it on their premise? Do you deploy it in the cloud? All the security.

Then you've got to go through an insane amount of hoops because this is, like, pretty sensitive information that you're indexing. So you've got to go through all of that. I would say the thing about Glean is now it's become one of the like obviously great AI companies that's, like, in the heart of the hurricane.

Back then, it was, like, extremely unobvious.

the cofounder of Rubrik. Yeah. So he noticed this problem at Rubrik, left Rubrik to start Glean, and he basically built Glean for Rubrik.

Right? And the bet that he was gonna make was like rough and tumble, what Rubrik wanted is probably what the rest of the world was gonna want. So it was like their core design partner.

So I think, like, he had access to all the right people. He knew all of the systems. That was, like, really important.

Like, having these early, early believers that are willing to basically codevelop the solution with you, that you have, like, unfettered access to get things done. It was still an insane effort to do it, but I think it made it a lot easier. And that way, at least you can show, hey, this is like working in production for somebody.

Yeah. Right? I'll pause there.

Does that make sense? Yeah. I said design partner process.

Yeah. So I think it's a pretty common go to market for early stage enterprise, I guess. Right.

Like, that's your ability to communicate what have you built and then how do you get that through an organization. It's like it's like passing a bill through congress. Right?

Like, you you have this thing going and you gotta get all of these stakeholders inside a customer aligned, get them all up to speed on like what's in the bill, like the product, make sure everybody else like you're helping them manage their own process and organization. Right? It's no joke.

go to market, I guess, in a in a very, very targeted way. I think if you're an engineer, it's even harder now than it used to be. And the reason for that is this technology is so new for organizations that they both have to figure out how do I use LLMs and AI within my own org and how do I use your product within that ecosystem?

Right? So like they're first trying to figure out how do I use the underlying sand that's changing underneath it. And then how do I use your product on top of, like, quicksand?

Right? That's, like, a really hard problem, which is why you see so many companies doing, like, this forward deployed engineer motion where what they're going in and doing is saying, okay. Number one, like, here's how we think about LLMs and where you can get best use of it.

Number two, here is this engineer that we're gonna forward deploy into your environment that we're gonna, like, basically, like, co develop this solution, custom fit for this org. So you have to do, like, a lot of handholding. And the reason is because, like, we're just so early to AI right now that, like, of course, you have to do a lot of handholding.

product, money. K?

Yeah. Okay. Right.

I can buy that stack rank. Yeah. I would maybe reswizzle it a little bit, but I could buy that.

Yeah. Like maybe I would say like people and then I would double people. Like I would probably add it again.

Sure.

I joined six years ago, my charter was kind of twofold at KP. Number one was, hey, we have this group of CIOs and customer networks. Can you help us manage it?

Right? Number two was, hey, our founders need a lot of help on sales and distribution. Where you can, can you help them there?

That was like the core charter, right? Then I realized that in order to help founders with go to market, like we needed to help them hire. That was the excuse for the podcast.

Right? It was like, all right, need an excuse to get to know these people so I can help these founders hire great CROs. Then that all started to work.

And we were like, great, let's double down on helping founders with sales. So we hired somebody on my team, Liam. Then we were like, great, let's double down on helping folks like Varun get access to world class customers.

So we doubled down on that and hired somebody else. And we're like, great, let's help founders with building their demand gen funnels and a bunch of stuff on the marketing side. Okay, hire Suzanne.

So that was kind of the first three years was like, how do we like KP generally invests in technical founders. That's like, I'd say a majority, not all, but a lot. And those technical founders are generally exceptional at product and edge and usually have never closed the deal before or usually have never created like a pop of funnel, like demand flow.

Right. And so we wanted to, as a firm, really help that muscle for KP founders. Okay.

Like Varun is a great example. He's an amazing engineer.

It was the most torrential growth I think I've ever seen in a KP company. It was insane.

You have some pretty good companies. It was insane. Yeah.

Tell me more. We're seeing companies like Harvey and others doing following a similar path. But, like, I mean, you know better than anybody.

don't know. This seems like a cursor code. I think what Windsurf got right was probably a couple of things.

The first was a commitment from the founders that they wanna both build Google class product and Salesforce class distribution. Yes. Like, was a true commitment from the beginning.

Okay. And most founders, okay, a lot of founders will say the product will sell itself. As long as we build a good enough product, people will come.

They'll come, they pay the $20 a month. Exactly. And then they'll just love us so much, we'll do it magically upgraded.

Exactly. Which usually doesn't work that way. So that was like, I think number one was like a real commitment to doing it upfront and knowing that if you can marry those two things, like it's magic.

Okay. I think the second was that they were in a great market that was getting pulled. Generally speaking, the coding market still today is just getting dragged by the industry because it's such a good use case.

Engineers are expensive. Having a copilot for them is like makes a lot of sense. The technology is there to be able to take the structured nature of code and reason with it to then produce outputs that are great for engineers.

So that was kind of number two. And then I think the third was probably just like they moved fast. They hired great and they hired fast.

Yeah. Were you involved like Graham, Jeff? I would give more credit to Liam on my team who is like intricately involved in building out that entire go to market.

That team, I guess, is now at Cognition. At Cognition. So you've seen it firsthand.

Yeah.

how serious Windsurf was about distribution, not just product. Okay. The lesson that I take away from them is like they were as serious about building an incredible product as they were about building incredible sales and go to market.

Yeah.

do not just go on their LinkedIn and look at all the fancy logos that they have gone and worked at and immediately assume that because they were at Snowflake or because they were at Databricks, they must be good for your AI company. It just doesn't work that way. In fact, in many cases, it's the inverse is true, where if you had to sell the number three product in a market and you had to fight tooth and nail and you were still successful there, you're probably like, if you go to a great company, gonna have a much higher proclivity to do well, right?

Whereas if you were I don't know. If you joined Snowflake at a 100,000,000 of ARR and you join, like, their enterprise team in the Bay Area, it's like, yeah, I get it. But, like, that's not that impressive.

No offense to anybody that joined Snowflake at that time. There were some diamonds in the rough. So I think that's that's one.

Well, it's like more like they're a fit for exactly that scenario if you're in that scenario. That's right. But you're not.

That's right. That's right. Especially for startups.

Right? The problem with that is that you have to actually interview them. Like, like, you can't just see what they did on their LinkedIn profile and know if they're good or not.

Like, you have to, like, actually dig in. And even more, it's not necessarily all of the things that they have actually done that make them good because It's like all sorts of intangible things that you have to, like, feel. Right?

Like, all the same things that we would, you know, wanna feel with a founder. Right? Like, do they have a chip on their shoulder?

What are they motivated by? Is it money? Is it, living in the shadow of their brother or sister?

Is it that they grew up in a first generation immigrant household? Whatever it is. Right?

So but you are really deep on the background. Really deep on understanding, hey, there's gonna be a million things that go wrong here. When they do, what is the driving force that's actually gonna push you over the hump?

And especially in sales, like you get told no way more than you get told yes. After you get told no enough times, internal, some, like, flame within needs to continue to burn, to continue to push you. Right?

And hiring for that, like, this is why, like, every exec recruiter and everything is, they've got it so wrong in most cases because they just go to the fanciest LinkedIn profile Right. And are like, oh, yeah. Yeah.

This person has, like, all of these great logos. This is the person you should hire. I'll give you an anecdote.

Inside the KP portfolio, okay, our top eight companies let's take five exec roles across the top eight companies. Companies like Rippling and Glean. Okay?

38 out of 40 of those roles. Okay. Those executives report to the CEO for the first time in their career.

Okay. So what does that tell you? Like, well, generally, it's like their experience is not the thing.

Like, it's the context that they've built. It's the trust that they have. It's their ability to like learn fast and grow with the company.

It is not like, what have you done at your last five companies?

big failure mode. I think the other, especially in AI today, is that the bar for how technical you are is going up. It's just going up.

So salespeople gotta be technical? Much more technical. That's a tough one.

Like, more technical than they used to be. Yeah. And what do I mean by technical?

Like, you don't have to, in my opinion, understand like every intricacy of the transformer. Exactly, the transformer. But you should be able to go over to an engineer's desk and ask the right questions to get a depth of understanding that you can actually communicate and articulate effectively to a customer.

Right? And I think like that matters a lot. That matters a lot.

Yeah.

a shift that I'm seeing. I'll add one more thing that really, really matters. Have they worked at a company that is similar in size?

Yes. So for example, if you're a seed or series a founder and you're evaluating sales leaders and AEs that have only been at companies that have done like 50,000,000 or more of ARR when they joined, it's probably gonna be really difficult for them. And the reason for that is because they've had a brand their entire life.

They've had inbound leads that just come to them. Right? They they generally can, like, lean on the credibility of the company to be able they've had a playbook that they just have to execute and run.

Right? So it's like all these things that make the feeling of being, call it, like, first sales leader, first AE, where you're way more of an artist than you are like a scientist. Like it's not this medic type playbook in the very beginning.

And then when you get to like where Windsurf was or is now, it's like very systematized. Right? It is a machine.

So much. There's boot camps, there's battle cards. But in the early days, like it is it's creative ways of getting something done.

It's creative ways of getting something done, and it just looks more like art than it does in science. And so if you've never had to do that before, it's gonna feel quite foreign to you. Yeah.

It's it it really is. But this is why, you know, people with more experience can can come in and show the show us the ropes. Like, by the way, I would not probably be a good salesperson at Windsurf today.

this, like, perfect playbook that was handed to me where I'm, like, qualifying criteria per letter of the playbook. You know, this is not my thing.

Honestly, they did they did most of the heavy lifting. I probably, like, went in there and did some, like, random rah rah stuff. Yeah.

And then Which they need. And then introduced Varun to a bunch of a bunch of customers. But the KP team, my team did a majority of the heavy lifting.

And so I give Liam, Lauren, Suzanne a bunch of credit for the work that they did there. Yeah. Okay.

So now we come around to your current thing.

thesis? I would say you're right. Like, during my sales career, probably the number one thing that used to break my back was that the underlying software with, like, Salesforce CPQ and others, just to, like, create a quote, get it approved is horrific.

Like you think if you think you've seen bad software, you haven't until you've seen a thirty second loading screen to get from one page to another when you're trying to close a deal with like two days left in a quarter. Okay? And this is just this is just, like, standard across the industry.

This is how it works. This is how it works. At every job that I was ever at, I used to get yelled at because I would, like, be asking people to, like, turn something within a day or two because I needed to get a quote out the door.

It happened when I was leading teams. They would always be getting yelled at because they were trying to move too fast for these systems to work. Okay.

And the reason the underlying systems do not work is basically pricing models went from a world where it's like, all right, Swix, like you want to get a Netflix account. You have like one seat you that maps to one person. Okay.

And then it's like $10.99 a month. Very simple.

Right. Then you're like, okay, actually, want a family plan. Okay.

Well, now you can add five people, no more than that. And it's like $8.99 a month.

That's like how pricing models have generally worked in the B2B context. It's like, I want to sell a thousand licenses of, you know, pick your product, LinkedIn. Right?

That maps to a thousand people at an organization. Okay? What has happened is that we have now done you know, like, companies have, like, 30 products, more, 50 and a 100 in some cases.

Those products scale by volume and then there's discounts associated with them. Then you have to do renewals. Then you wanna do early renewals.

Then you wanna do expansions. Then you wanna do them across like 15 different product lines, right? So the complexity just starts to like increase exponentially.

Then you're like, actually, I want the customer to pay as they go. That might be how you guys are selling today. It's like, well, I actually just like make sure they pay a minimum amount and then anything above that, we'll just bill them.

Right? It's like how Databricks is. Very custom function.

Exactly. Like, that's how a lot like, that's how Cursor and others are too. It's like amount of tokens that I consume, just pay, just bill me for that.

So like these pricing models have gone bananas. Okay. And by the way, this has barely even started.

And the reason it's barely even started is like with AI, all of these pricing models are minimally going to start to look like consumption based pricing, Right? That's like how you consume Exactly. That's how you consume Anthropic, and that's how you consume OpenAI.

Yep. And so the problem is about to get way worse. Okay?

And so it was a problem that I kind of, like, was feeling because I was like, oh, the underlying data model is just breaking because twenty years ago, Salesforce CPQ was not designed for like all of these permutations. Right? It was like a static world where one person is a Netflix license.

The most you could do is a family account. Right? Yeah.

Okay. So that happened. Then I joined KP.

And Lauren on my team and I started a group of tech CIOs, 35 tech CIOs. Okay. Companies like Uber and Box and others.

Okay. That meet twice a year. And this was like four years ago.

So pre LLMs, pre anything, I asked them, what is the number one problem that you have in your company right now? So I at a dinner with like five CIOs and they were like, CPQ. And I'm like, no way.

And they were like, no, I'm not kidding you. They said, we are getting yelled at by our chief revenue officers and salespeople all the time because the underlying software that we're delivering to them doesn't work. Fast forward, six months later, we have a second dinner.

Okay. Different group of CIOs in network. Okay.

So now I'm with five other CIOs. I ask them, what's the number one problem you have in your company? All of them said the exact same answer.

And I was like, woah, like, that's pretty rare. Like, you just don't pain does not grow on trees like that. And so we, as a firm, got very excited because we were like, it's pretty rare and unique to have this many customers that have this bad of a kind of uniform pain.

So we did a full market map. We were trying to invest in a company, didn't find anything compelling. Okay.

Just like could not find any great companies. Okay. Then GPT 3.

5 comes out and I was like, oh my God, I actually think you can abstract away a bunch of the complexity with these LLMs. And it's unstructured and structured text that you can reason with and do stuff with, right? Like, that's why coding is such a great use case.

That's why Harvey is such a great use case, because you have like all this case law, and then you can point the LLM at it and you can reason with it. Then you build a bunch of enterprise features and functionality and workflows on top of that. This is a very similar problem in nature.

And so that was, like, the light bulb moment of, okay, and then we can actually build something better. Then I started asking myself, well, like, why is nobody why is nobody fixing this? Yeah, Why is nobody fixing this?

Right. Like, that's the question. Like, why has the incumbent Salesforce, anybody else not fixed this?

Why is this still an issue? Okay, The reason is because all of these tools were basically built in a pre LLM era. Their data models are broken because they did not see consumption and a million SKUs and the sprawl that comes with that coming.

In order for them to basically build a product that handles all of the complexity and permutations, they have to rebuild their entire data model and architecture from the ground up, which is the same thing that basically most incumbents have to do today. Right? Which is why there's, like, so much frenzy around early stage startups in VC.

Because in order for an incumbent to go do what an like a Harvey is doing, have to literally rebuild that company from the ground up. Like, you have to build the entire architecture differently. Like, it reminds me when I was in the public cloud.

Like, my career was in the public cloud before this. In the very early days, everybody was moving from on prem to AWS. Okay?

And initially everybody was like, great, we'll just lift and shift our application and just throw it into the public cloud. And all of a sudden you realize like, oh no, like S3 buckets can just like disappear. Right?

So like, no, well, you actually have to rebuild this stack cloud native from the ground up. That's the same thing that's happening in AI today.

Okay, so that happened. Then I come to find out, okay, in this case, Salesforce, which is like the gorilla in the room, they have like 95% market share. They have end of lifed their CPQ solution and they are making everybody move to a new product.

Okay. So they are trying to do this. That product does not exist yet.

If it does, it's incredibly flimsy. We've talked to some of the people that are trying it right now. And so we basically have a two year window where we have to beat them to the punch.

And we love we love that. And the reason we love that is like, boy, would I rather compete with, like, whatever 100,000 person Salesforce that I don't even know what kind of engineers may or may not still be there versus, like, OpenAI. You know?

Like, that's just like that's who we wanna out sprint. Then I started asking myself, well, like, why hasn't anybody done this yet? And the short answer is one, I don't think the technology was there.

And the second, going back to your earlier question, Swix, is this is a very complicated go to market and distribution question. It is upmarket. The problem is more upmarket because that's where the complexity is.

And and in order to, like, do something elegantly upmarket, you need to, like, know what you're doing in the enterprise. Right? And it just so happens that you need early believers like Glean had with Rubrik that are willing to take a bet with you in a, like, design partnership to codevelop it with you.

And it just so happens, going back to our earlier conversations, that episodes one through 80 were interviewing CROs Exactly. Who are the people that have the pain. You've been preparing this The the whole other thing that I was, like, responsible for the KP was, like, these CIO networks are the ones responsible for delivering software to these people to alleviate their pain.

And so it's like, I just so happen to know basically all of the key stakeholders in this problem. So actually, at that point, I was like, oh, man. Like, do I really wanna like, life's pretty like, KP, life's you know, like, I've I know I've seen what a company what it looks like, the bite out of your life that it takes to, like, build a company.

So anyway, point being, after talking with my partner at home and, like, understanding, like, is this a commitment that we're willing to make And talking to my partners at Kleiner Perkins, like folks like Mamoun and Ilia, to be like, hey, if we do this, like, I think I think I have to do it. Like, I don't think I don't think it's gonna really make sense for us to hire somebody off the street right now. And then I'll build a cofounding team that is, like, technically excellent and world class.

So anyway, that was the thing, or I should say the million series of things that that tipped us over the edge.

I will work backwards from the list

We're at nine people today, two co founders, AJ and Eugene. AJ went to Caltech at 15 and finished second in his class. Like, the guy was in diapers when he was in school.

Was absurd. Met Eugene his first day of school. They've been working together basically ever since.

AJ went to Robinhood, Eugene went to Meta. They went to NASA together, built a bunch of the software for the rover, the Mars rover. Then they started a company together called Athena, which was an LLM for college students to send their applications.

It would grade it, tell them how is it, all that.

wanted to go build a giant company. They independently found this problem, independently got excited about it. Salesforce CPQ?

How do you deliver better software for AEs? Yeah, CPQ. Okay.

They were asking their founder friends, like, what's the number one problem at your company? And they kept answering this question. So anyway, then we met.

It became very obvious that what I had was like unfair distribution, an understanding of the problem coming from sales. And what they had was extraordinary technical chops. So anyway That's team.

That's team. Plus, some killers, across the board. By the time this comes out, we'll have soft launched.

The only other interview that I'm doing besides you is when Mahmoon interviews me on Grit, where we'll talk about it. We're co developing the solution with design partners. I was very inspired by what Glean did.

So Glean built for Rubrik. We're building for four design partners, shared Slack channel, weekly stand ups. Like we are taking the same bet that basically Glean made, which is that what these four design partners want is probably going to be what the rest of the world wants.

Do you want diversity in those four? Like, you know what mean? What you really want is we had to make sure that our data model is infinitely flexible, that we don't run into the next permutation that we haven't seen.

So what you want are the hairiest design partners that have every SKU, hardware, software, SaaS, consumption. You want the mess to throw that at your data model to make sure that nothing tips it over. And so those are the types of design partners that we wanted.

And it's helpful. Like, I know the CIO. I know the CRO.

In most cases, I know the CEO. And so like, you don't have to deal with the, like, normal big company BS of, like, legal and procurement and all these things. They can, like, you know, help shepherd you through the org.

Yeah. Let's talk about data model.

you The team probably spent only doing data model. That is it. Like late nights.

And what does do data model mean? Like, for example, there are rules that every customer has where it's like, if you're an AE in The UK, you can only quote certain SKUs that have certain discounts on them. Like you can only have so many there's only a max discount that you can present a customer, right?

If you're doing a deal through a channel partner and you're doing it out of Canada, there's all these rules that are connected to it. So imagine like all of these SKUs, all of these rules, all of this thing is like this extraordinarily interconnected system that has to be accounted for. And so making sure that we threw as much of the real life information rules and permutations as possible to, like, not tip over the data model was incredibly, incredibly important.

So like, that's where we spent a large, large portion of the time getting right. Does that make sense? Yep.

And I also know that, you know, best lead plans run into reality and then they get screwed up with the first contact. Right? For sure.

Like, you know, even if you get consumption right, for example, where you're like, alright, they can do it. How do you represent that on the UX, right, or Cognition or Windsurf, like magic. And if you get that right, which is I think what we're about to get right, then you earn the right to go build a big company.

in the valley, founders will pretend like the mission that they have is like bigger than it is. For example, if you're doing what we're doing, I think we're solving a really important problem for a certain set of people. Okay.

High value people? Yes. Yes.

But like, we're not helping a mental health crisis. We're not like feeding people in other countries, you know? Like, we're not doing what what the Chan Zuckerberg Initiative is doing.

And I think it's really annoying when people pretend like what they are doing is like this revolutionary thing. It's like, no, what you're doing is solving a really hard problem for a specific set of people. If you're able to solve that problem and those people are delighted, then you earn the right to go solve the next problem.

If you solve enough problems in perpetuity, then you earn the right to go build a big company. And when you go build a big company, then you get all of the cool things that come with that. People taking on bigger roles and responsibilities than they ever had, engineers owning new product initiatives, soup to nuts, ICs that then become managers that have no business becoming managers.

Of course, all the financial stuff that comes with that. In my mind, I'm like, that's a mission that I can get behind. I still think the problem that we're solving is interesting and cool, but I think it's really annoying when you're like, oh my god, this is the thing that I've been thinking about since I was one years old, and everybody else also has to feel like this.

I don't I I find that annoying.

I think if you dream the dream, where LLMs will be a superstar in this company is like, if you're one of our customers and all quotes go through Roadrunner, okay, basically, you can imagine a world where it just recommends, like, just do this deal. Like, oh, you're doing a deal at Costco. Great.

We just did a deal with Nordstrom that looks a lot like this deal. Okay? You should adjust these things and then deliver it this way.

And so the system Like proactively suggesting things. The system will basically have all of the historical information about what have you done. And once it has all of that, it will then tell you this is how you should bundle it up.

And by the way, today, that's all human in the loop. Today, if you're a new rep at Glean or a new rep at Cognition and you wanna, like, put one of these deals together, you're, like, calling DealsDesk and finance. You're, like, calling the top AEs at the company and be like, how do you even, like, put this together?

Right? And then if you're using Salesforce CPQ, which most people are, you're like, then go into, like, loading screen hell, then you built a bunch of custom software on top of that because the data model doesn't work. So you have to, like, fits around with it to, like, actually make it work.

Like, it's a complete nightmare. Yeah. And so, like, that is where the magic of of Roadrunner will will come.

very specifically AEs are quite expensive and they spend a ridiculous amount of time doing administrative work trying to get these hacky systems to go. Perfect. And right now, the amount of bouncing around and ping ponging that they have to do inside of an organization just to get a quote created and approved is a nightmare.

We should solve that. And by the way, guess what? DealsDesk and all these people should not be doing that either.

You know? Like, there's way more strategic things that they could be doing. Yeah.

Yeah. It's complete mayhem. Interesting.

we are not demand constrained. Like, I know every customer and they're all, like, banging down my door right now. The only fight that I've ever had or have with my co founders is that I'm like, hey, these 10 customers want to come and join us and work with us.

And they're like, we do not have engineering bandwidth. Like, our roadmap is being dragged out of us. Yeah.

It's very clear what we have to go do. There's no surprises from here on the things that we need to go actually build. Obviously, the strategy is the same.

The tactics will bob and weave. And so, yeah, we're You need product at inch. We are meaningfully bandwidth constrained on amazing talent that wants to go through the grind of building an early stage company.

So physically, to your prompt on running, I work out every day no matter what. First thing? Sweat every day as soon as I wake up.

Home gym? It's either so it's it's pretty consistent. Mondays, I bike up Hawk Hill, which is like over the Golden Gate and up into the Headlands.

It's like a nice way to start the week. I'll run twice a week. I'll usually lift weights twice a week.

I usually play a sport or something. So let's play it. Basketball has been the sport of choice recently.

Although every time I pick up a ball, I'm, like, pretty convinced I'm gonna, like, you know, like, tear my ACL or something. You know?

I I will work out every day. Salad for lunch every day. I've been it's just easier.

I've just found that if I can just do the same things over and over again, my life is just easier. I don't have to think about it. Like, for example, on the working out thing, it is way easier to know that I am gonna work out every day rather than have the cognitive load of, like, what days am I gonna work out this week?

Or when am I gonna do it? Or, like, for lunch.

Does that mean I can skip today? Or yeah. Exactly.

And even to your question on, like, the style of workout, like, I'm just doing whatever I feel like besides Mondays, Like, I feel like doing that day. And even if I go and, like, lift at the gym, it's just full body. Whatever I feel like is next, I'll compound every exercise, and I'll just run through it.

Like, I don't have, like, a set because I just wanna reduce friction as much as I can just, like, get those things done.

meaning, like, it kinda has to be a habit that you've had that you can then carry on to founding a company because like the amount of demand on your time, it's like a piety contest and the prize is just more pie. And so like there is no limits to how much has to be done. And so I think I just got lucky where I had some of these habits before.

Yeah. And then I was able to just like carry them on. Otherwise, like even now I'm like, I feel very constrained being able to do some of these things.

No, totally. Of the real reason I was gonna ask was you listen to a lot of podcasts while you're doing all this. What are your favorite other podcasts?

Oh, man. Do you listen to your own podcast? She does on Recs.

Yeah. I do. I'm very critical.

I I send notes to my editor, my co host. Yeah. I used to listen to everyone and then my editor was like because it was like before we would release, I would have like a litany of notes.

And eventually they're like, dude, we've been doing this for whatever, 200 plus episodes. You don't have to listen to everyone and send notes. It just bogs down everything.

Just trust us.

I think some of O'Shaughnessy's invest like the best are pretty good. This whole thing with Colossus. It's yeah.

It's interesting. Yeah. I think some of Joe Rogan and some of Tim Ferriss is good.

Some. Yeah. Some of Shane Parrish is good.

Yeah. Like, I have guests that I like when they interview them, but I don't follow I personally don't follow any host religiously. Like, I get interested in guests, and then I'll go down the rabbit hole for, like, what shows have they been on, and I'll just listen to those.

And then if I like the interviewer, then I'm like, oh, this is a new show. Maybe I'll go check out one or two more. But I'll go like like, for example, like, I've gone as deep as deep can go on Elon.

Like, there's probably I have probably listened to and he does a bunch of them. You know? I've probably listened to a bunch of them.

And if he's been on He's not the easiest speaker to follow. No. It is a bit jumbled.

Yeah. So I'll go deep on a guest. I'll go deep on a guest.

Have you done speaker training?

is that asking the questions is way easier than answering them. And so How's it feel? I would say I would say on the you have way more control over a conversation when you're asking the questions.

Yeah. Sure. I'm just I'm just loving stuff.

Yeah. Exactly. And you're usually speaking whatever, like 20% of the time, and the guest speaks, like, 80% of the time.

And you, like, have a general sense of where you wanna go. And so I got the plan here. Yeah.

is an ability to transfer enthusiasm from one person to another. And I think that when you're recruiting, when you are on stage at your conference speaking, when you're an interviewer or interviewee, when you go home for the holidays and hang out with your family, like, I think all of that, I really like this definition of how do you transfer enthusiasm. And I think it has to be raw and I think it has to be organic.

I think that's if I were to train or be trained, I would really try to get to the essence of like, how do I help transfer my enthusiasm about whatever it is that I'm talking about into those that are listening. Yeah. The challenge for you is you're pretty naturally good at it.

And her definition is, I'm sure a book about it, it's hard to define it quite narrowly, but passion plus perseverance over a sustained period of time. And I think the natural tendency when you think about grit is like literally gritting your teeth. Like, how do you just endure?

And I think the operative word in her definition is passion. The way that I think about it is like, how can I put myself in positions where the thing that I'm doing, the thing that I'm working on, the job that I'm doing, the company that I'm building, the relationship that I'm in, how can I be in more of those situations where I really care? Because if I really care, then I can transfer my enthusiasm to others.

If I really care, then it'll feel like play to me when it feels like work to everybody else. If I really care, like in the podcast example, I'll just do it for longer than anybody else and just, like, out sustain you. But I think it's all because I really care.

And so I think this idea of passion is probably the thing that I love most about her definition, which is like, alright. Just try and do things that I really care about. And therefore, it's just like it feels light for me.

And then I don't have to feel like I'm always gritting my teeth to do things that matter.

the tables have been turned on me. Crazy experience. Fresno Mini.

Thanks, man.