Latent Space: The AI Engineer Podcast - AI to AE's: Grit, Glean, and Kleiner Perkins' next Enterprise AI hit — Joubin Mirzadegan, Roadrunner

Episode Date: December 12, 2025

Glean started as a Kleiner Perkins incubation and is now a $7B, $200m ARR Enterprise AI leader. Now KP has tapped its own podcaster to lead it’s next big swing.From building go-to-market the hard way in startups (and scaling Palo Alto Networks’ public cloud business) to joining Kleiner Perkins to help technical founders turn product edge into repeatable revenue, Joubin Mirzadegan has spent the last decade obsessing over one thing: distribution and how ideas actually spread, sell, and compound. That obsession took him from launching the CRO-only podcast Grit (https://www.youtube.com/playlist?list=PLRiWZFltuYPF8A6UGm74K2q29UwU-Kk9k) as a hiring wedge, to working alongside breakout companies like Glean and Windsurf, to now incubating Roadrunner which is an AI-native rethink of CPQ and quoting workflows as pricing models collapse from “seats” into consumption, bundles, renewals, and SKU sprawl.We sat down with Joubin to dig into the real mechanics of making conversations feel human (rolling early, never sending questions, temperature + lighting hacks), what Windsurf got right about “Google-class product and Salesforce-class distribution,” how to hire early sales leaders without getting fooled by shiny logos, why CPQ is quietly breaking the back of modern revenue teams, and his thesis for his new company and KP incubation Roadrunner (https://www.roadrunner.ai/): rebuild the data model from the ground up, co-develop with the hairiest design partners, and eventually use LLMs to recommend deal structures the way the best reps do without the Slack-channel chaos of deal desk.We discuss:* How to make guests instantly comfortable: rolling early, no “are you ready?”, temperature, lighting, and room dynamics* Why Joubin refuses to send questions in advance (and when you might have to anyway)* The origin of the CRO-only podcast: using media as a hiring wedge and relationship engine* The “commit to 100 episodes” mindset: why most shows die before they find their voice* Founder vs exec interviews: why CEOs can speak more freely (and what it unlocks in conversation)* What Glean taught him about enterprise AI: permissions, trust, and overcoming “category is dead” skepticism* Design partners as the real unlock: why early believers matter and how co-development actually works* Windsurf’s breakout: what it means to be serious about “Google-class product + Salesforce-class distribution”* Why technical founders struggle with GTM and how KP built a team around sales, customer access, and demand gen* Hiring early sales leaders: anti-patterns (logos), what to screen for (motivation), and why stage-fit is everything* The CPQ problem & Roadrunner’s thesis: rebuilding CPQ/quoting from the data model up for modern complexity* How “rules + SKUs + approvals” create a brittle graph and what it takes to model it without tipping over* The two-year window: incumbents rebuilding slowly vs startups out-sprinting with AI-native architecture* Where AI actually helps: quote generation, policy enforcement, approval routing, and deal recommendation loops—Joubin* X: https://x.com/Joubinmir* LinkedIn: https://www.linkedin.com/in/joubin-mirzadegan-66186854/Where to find Latent Space* X: https://x.com/latentspacepodFull Video EpisodeTimestamps00:00:00 Introduction and the Zuck Interview Experience00:03:26 The Genesis of the Grit Podcast: Hiring CROs Through Content00:13:20 Podcast Philosophy: Creating Authentic Conversations00:15:44 Working with Arvind at Glean: The Enterprise Search Breakthrough00:26:20 Windsurf's Sales Machine: Google-Class Product Meets Salesforce-Class Distribution00:30:28 Hiring Sales Leaders: Anti-Patterns and First Principles00:39:02 The CPQ Problem: Why Salesforce and Legacy Tools Are Breaking00:43:40 Introducing Roadrunner: Solving Enterprise Pricing with AI00:49:19 Building Roadrunner: Team, Design Partners, and Data Model Challenges00:59:35 High Performance Philosophy: Working Out Every Day and Reducing Friction01:06:28 Defining Grit: Passion Plus Perseverance This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

During my sales career, probably the number one thing that used to break my back was that the underlying software with like sales force 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 30 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. It's how it 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 know, an 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 like, 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. I got to ask you, how was the Zuck interview? Yeah, it's very interesting. I'll be recording. Yeah, I just wrote.

Yeah. I think they kind of obviously had an agenda coming in, which was basically to raise the profile of CZI and Priscilla Chan, with Zuck being supporting character, right? And I think they accomplished their mission because my quick hot take in a single sentence is if Priscilla Chan gets half of what she wants to do done, she will have more impact on humanity than Mark Zuckerberg. right the facebook will just be a funding mechanism for the greatest bio research work done in human history wow were you nervous you must be nervous uh i wasn't nervous because of the sheer amount of prep that the czzii people put into us which is like honestly like low key to understand what it's like with the executive staff of a hundred billionaire i've never dealt with someone like that yeah they are so good they like they like they

prepped us so well so that like I felt like I knew exactly. You mean Zuck's team isn't randomly letting people walk in off the street and just ask whatever without any pre-based pre-vasing knowledge. I feel I had to like interview three times to get even in that room. So yeah, it was very, it's very fascinating. We were very honored to be picked by them because we're not a biofocus podcast. No. But the whole point was to reach out to engineers. And while there, we're on a stronger fron. Yeah. That's awesome, man. I mean, it feels like a breakthrough, doesn't it? You've had some studs on. Yeah. We just had Fafelita. Today?

Today? Yeah, just released. You came from that? Well, Labs. No, and we just released it. Oh, you did. Oh, nice. It was a couple weeks ago.

Who else have you done? There's a bunch. Greg Bachman. You've done some amazing people. Is it surreal? Yeah, it's surreal for me who started out as just like an independent creator. Let's see where this goes to now we're legitimately in that tier of podcast. They get invited to everything.

So that is very surreal. Yeah. It's pretty exciting. Who would have thought, you know? I mean, I think. like for you, I've been following your progress for a while. I don't think when you are still like a CRO podcast, I don't think I was caught on yet. But I think like anyone following top founders who really wants to get real stories, they eventually find their way to you. And you get really good stuff. So congrats. I appreciate that. I, I think the transition from the CRO to the founder, whatever, it happened like what, episode 70 or 80 when I was like, because there 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 want to do is have like an earnest and honest conversation. And it's harder to do that when you're thinking, what is my boss going to think? Whereas if you're the founder, you can just speak. You can just speak, you know? I think yes and it's also nice for distribution because obviously that's the more famous or public-facing person. So people do want to tune in. So you probably caught my attention for one of those episodes. I don't even remember which.

But you know, you've had so many. And even the non-CEOs, I think I would highlight for listeners, your Emily Choi episode from Coinbase. Yeah. Yeah, it's like so raw. And so like you went there with all the politics questions, you know? Yeah, the first one. Yeah, yeah, yeah, yeah, I did. I appreciate it, man. It's a, as you know, it's a labor of love. Doing anything every week for six years. Yeah. I mean, I guess it started every other week and then it became every week after the transition from chief revenue officers

to CEOs. Yeah, exactly. Doing anything for that long every week, you'd 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. Well, it hasn't happened yet. Hasn't happened yet. I was talking with Ali, one of your partners, and they said you even had to justify your purchase of a roadcaster just to support your work. Doesn't Kleiner see the value in this?

So in the early days, when I joined Kleiner Perkins, I was quite young. And I was definitely figuring out like what is going. on in venture. I can you 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 U.S. and build out their public cloud business in the central U.S. 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, like, venture sounds amazing, but like, isn't that the job that I'm supposed to do like at the end of my career? Like, this sounds incredible, but like maybe later on. So anyway, we got to talking and it was, it became very obvious, like there was a unique opportunity here. Fast forward. one of the things that that ended up happening was I was working really closely with Arvin

at Glean, exactly the last incubation that we've done here. And Arvin 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, all right, we've built this incredible Glean product at the time I was called CIO or SIO. 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 30 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, it was like, you know, that? Maybe. I just prove it. They came to you? You came to them? They came to you? Who? K.P. Oh, no. I went to KP and I was like, I think we should start a podcast that interviews CROs. And they were like, I mean, it was, skepticism would be generous. 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 from being honest. KP was skeptical. I kind of 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, let 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 10, we were like, oh, it's actually like kind of working. I'm getting to know this CRO, it's getting easier to get to know them. And then I made a commitment to myself that I was going to get to 100. Like I just told myself, like, I will not make a judgment on what this is or isn't until we get to 100. Yeah, it's the same. It's really weird that this number also appears when Marcus Brownlee talks about how to start being a YouTuber. Because you just don't know what you are until you just give yourself the room to experiment.

My observation is that, I don't know 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 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 going to tune out the noise.

Because otherwise, you start overreacting to what any single person thinks about any game. given episode. And then usually, I think that's why most podcasts, you know, don't make it past five episodes is because people start to be like, oh, maybe it's not good. Like, they start reacting, right? Each of these slights feels more real. And so that's why I made that. Yeah, that's why I decided to do it. Yeah. You started audio only, right? So you didn't, well, the beauty podcast is nobody can talk back in the comments because there's no comments. I guess with audio. iTunes reviews. With audio. Right, right. Yeah. Yeah, it was audio only. It was actually, easier within was audio only. Yeah. In many ways. And now 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 listened to more podcasts than most. Like, I'm quite voracious about listening to podcasts. And 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 noise. And then when you turn it back on, you flip the home screen up, it's video. And so I kind of wanted the multi-modality where, for example, if I'm cooking, you know, it's the video's open or take a shower, the video's open. And then, you know, 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 need both. You do need both. I think the question is, can you do, can you just transition the video without any change in the format whatsoever. And I think that has difficulties for me. I noticed anecdotally that, so for example, there's a couple things, right? One, well, we are a technical podcast, so we can show code, we can show diagrams, we show demos of the products. And so, like, do we spend the editor effort and money to put that into the video on the off chance that, like, the 5% of our audience watching on YouTube actually sees it?

I don't know. It's not, like, super clear. The other more relevant thing is when you look at people like All In or Dorcash, they start video and then they went audio or, you know, like it's kind of like a video first mentality. 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. And so much of what I want to 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.

Do 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. Yeah. Here is 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, just a different thing. And so that's my one knock on the video format. Yeah. I noticed, you know, 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 your 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 going to be the jest that I want to be. It's like, you know, when you're sleeping at night before you go on a podcast, you're like, okay,

how am I going to sound? What am I going to say that's going to make me feel smart? You know what I mean? Make me sound smart. And so you start to build this like, I don't. idealized version of yourself that you want to 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 I like the temperature to be cold. I don't want people to feel like they're sweating or hot. It 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 think it bounces off. Yeah, I think it's important to not make it feel spotlighty. Yeah. If that makes sense. The way that I do prep and then and then for the guest prep. Like for example, I will have. 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 guests the questions. Because if you give the guests the questions, well, all of a sudden, it's like a rehearsed set of conversations, which is not how real life goes. And so like I go through, I guess, kind of a lot to make sure that it feels real. Yeah. It's funny because we get asked a lot for questions up front. For example, the Zuck pod was very, very well prepped and screened. Sometimes you just don't get the interview if you don't do that. I won't do it. Yeah.

I just won't do the interview. Yeah, we're more flexible there. Okay, if I had Zuck, okay, if I was like, if you told me, you can have Zuck, but he has to see the questions before, I'd probably. Because, like, look, the secret is the PR team is going to screen the questions, but you can go off script. Yeah. You can ask follow-up questions. Yeah.

So it's really not that bad. That's true. It's really not that bad. That was Creative Corner. I do want to obviously get you on the sort of professional side, but obviously I love to indulge in Creator Corner. Come back to Glean. Glean is obviously KP's most recent incubation and success.

It's done super well. What's something that you realized working Marvin that made you understand, well, here's what works in applying AI to the enterprise or whatever, like selling AI to enterprise. Yeah, I think at the time in the early days of Glein, It's when Orvin came to Mahmoon, this pitch of doing enterprise search was like the eye role 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 going to solve enterprise search once and for all.

And so, you know, I give Mamun a bunch of credit because he realized that if this problem is going to be solved once and for all, it's probably going to be somebody like Arvin that can do it. On the technology side, like AI, this was whatever, 2019, 2018, 2018, 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 Glein 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 multi-layered cake of protections to make sure that I never see what I'm never supposed to see. right like i never see swix's you know like comp data for example and so getting that right it's 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 iroll 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 then you 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 got to go through an insane amount of hoops because this is like pretty sensitive information that you're indexing. So you got to go through all of that. I would say the thing about clean 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. So, so let's, I want to double click on that and then, uh, because I feel like we just did the breath of the problem, but let's talk about getting past the category is dead, uh, sort of default rejection. Yeah. So what do you do there? What do you, what do you learn? Yeah. I mean, what did you try and didn't work? The advantage that

Arvin had was that he was previously the co-founder of Rubrik. 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 going to make was like rough and tumble what Rubrik wanted is probably what the rest of the world was going to 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 co-develop the solution with you, that you have 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, it's a design partner process. Yeah. 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 passing a bill through Congress, right? Like you have this thing, Glean, and you got to 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. It is no joke. I don't think people realize how hard it was back then. I think it still is very hard.

You know, and it's what's weird is you have a special expertise. I think the engineers that are listening maybe don't have the appreciation of the work that this involves. It is a little bit of almost like a military mapping of the organization that you have to sort of understand who your champions are and who the, where the resistance is and how you want to sort of prosecute a campaign to go to market, I guess, 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 like 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's this engineer that we're going to forward deploy into your environment that we're going to 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 like of course you have to like surround these customers with a bunch of technical resources to like make it successful yeah are the regrets like buckets of regrets that you have there's also like the did you spend your life working on things that you think are you care about that you're like yeah I mean you know even if the finances

didn't super work out I'm still happy I worked on it if I did not like the mission or the job or like the people I worked with, that would be a bigger regret than the nuclear finance side. Obviously, finance does matter. I always think about it as like, well, in terms of ranking, you should probably put people products and money in sort of roughly that order. If you're evaluating a company? Yeah, as an employee. Obviously, if you start something. People, product, money.

Okay. Because products is either the shift than people. And then the money, if the first two don't really work, then basically, no amount of money will really make up for it. Yeah, okay. Right. I can buy that stack rank. Yeah.

I would maybe re-sizzled 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. And then maybe market product money. Yeah. Markets really good.

Well, I guess, you know, I maybe bundle market with products or just assume that market is given, given I only work in DevTools. But yeah, that's, that's important. distinction. Coming back to you or just general learnings from KP before we go into Roadrunner. I just wanted to also touch on the other conversation that you had with Varroon from windsurf, which I really enjoyed. Shout out to him. He's going to listen, obviously. Love that guy. Another interesting company that I was finding parallels to glean in a sense that kind of you have to just get people to hand over their entire codebase.

And a very tough go to market. I've heard from multiple windsurf folks that you went there and did like sales training cheerleader sessions. What is it do you do? At Windsor for in general at KP. You used Windsor for an example, but use that to tell the story of. Of KP? When 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.

So that was the excuse for the podcast, right? I was like, all right, I 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 Varroon get access to world-class customers. So we double 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. Like, Faroon is a great example. He's an amazing engineer.

But, like, he's never had to actually build the machine that is sales and marketing and go to market. I think this is something that people don't appreciate how it surf is that they look at the products. And they understand it's, you know, it's agentic ID. But actually, there's a sales machine that is one of the best I've ever seen. Yeah. And you have to build it. So I'm like, well, tell me more about it. I think.

And maybe we can quantify as well, right? I think like something like zero to 100 million error in seven months, something like that, eight months. It was the most torrential growth I think I've ever seen in a KP company. It was insane. That's a high bar because 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. Like, coding is an incredible use case for AI right now. Right. But I don't expect like government Fortune 500 to adopt at this kind of rate. And that's why I was seriously miscalibrated on. Like, I was with them.

I did a podcast with them on the day of WinSurf's launch. And even then I was like, eh, I don't know. It seems like a cursor code. I think what WinSurf got right was probably a couple of things. The first was a commitment. from the founders that they want to both build Google class product and Salesforce class distribution. Yes. Like it was a true commitment from the beginning.

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'll pay the $20 a month. Exactly. And then they'll just love us so much. They'll magically upgrade. Exactly.

Which usually doesn't work that way. So that was like, I think number one was like a real commitment to doing it up front 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 co-pilot for them makes a lot of sense. The technology is there to be able to take the structured nature of code.

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 was 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. No, like, it's no joke. This is why, like, I mean, I put it as part of my, like, why cognition thesis, core cognition, Devin cognition is very good at product and inch, but they didn't really have that much of a sales team.

And here's the most crack sales team I've seen in coding, at least, in DevTools. And you just bring them together. Like, how hard can this be? Like, it's just like a really good formula for success. Yeah. I don't want to understate 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. And it's easier said than done. Yeah, you can be serious about everything and everything's the number one priority. That's right. That's right. What the hell?

But they pulled it off, which is impressive. The one anecdote I guess I will share on the distribution side, is they're the first company I've seen with like a real one floor of it is just dedicated to their video production. One floor of the sort of office down in Redwood City. And I've never seen that. I'm like, you know, you're a pretty young company. You're mostly developer tools. But like here is like a whole studio set that you can do anything out of and make it interesting on video. And it's because you really care about getting this across, you know, even though you're just selling software. Totally. Like, I'm sure Glean doesn't have it. I don't think I've seen a video from Glea

and that's not just a screen share. Totally. Okay, give me one more thing on just like your, like, how do you hire a sales team like this? Like, we have founders listening. They're building interesting ad products. They don't really know how to go to market. Do you have to offer an arm and a leg to hire your first sales leader?

Do you have to only work with Kleiner to do that? Like, what is the actual principle that you advise founders to follow? I'll give you some anti-patterns. The first is 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,

can I have a much higher proclivity to do well, right? Whereas if you were, I don't know, if you joined Snowflake at $100 million 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 are some diamonds in the rough.

So I think that's one. Well, it's more like they're 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.

The problem with that is that you have to actually interview them. 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 you're hiring for potential. 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, want to feel with a founder. Right? Like, do they have a chip on their shoulder? What are they motivated by? Is it money? Is it, you know, living in the shadow of their brother or sister? Is it that they grew up in, you know, a first generation immigrant household? Whatever it is, right? But you go really deep on the background. Really deep on understanding, hey, there's going to be a million things that go wrong here. When they do, what is the driving force that's actually going to push you over the hump? And especially in sales, like you get told no, wait a lot.

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 exact recruiter and everything is like 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 exact 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. It's the context that they've built. It's the trust that they have. It's their ability to learn fast and grow with the company. It is not like what have you done at your last five companies.

Does that make sense? Yeah, it totally makes sense. It's very first principle of thinking is the way that Scott Wu put it. Yeah. So I'd say that's like probably one 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 got to 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. Like 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. And so like that bar has started to raise more and more for me on like can you actually describe the product and what you do and how it fits into a broader ecosystem without relying on like some sales engineer to do it for you. Yeah, but like in a in an interview, sometimes you just don't get that because you that's what sales training is for. It's like people prep battle cards. They get time with the product. They take time with the founders. they get it, right? It's hard to get that in the interview. Yeah, but it's it's not hard to look at somebody's background and understand were they willing to do that. Yeah, yeah. Did they actually want to do that? It's what's really funny is well, one of my core memories as an engineer learning the the ropes and startups was our new head of sales coming in at NL5, which is a KP company, it's coming in saying, you know, I was very stressed. I was like, well, you know, competitors have these, these, these things. We need to match them and exceed them. And he's like,

Nope, that's engineering thinking, like, give me anything. I'll sell it. And I was like, wow, that's a good sales guy. But I think to some extent, sales guys, salespeople who can sell regardless of the product, that's the old school way kind of, where they just know how to do the steak dinners and golf things and whatever else they do to make their number versus now, I think the rise of the more technical sales hire who really has to care actually about the products and explain and, and, get in the weeds with people. I think that's that's 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 million or more of AARR when they joined, it's probably going to 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 generally can like lean on the credibility of the company to be able to. They've had a playbook that they just have to execute and run, right? So there'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 bootcams. 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 going to feel quite foreign to you. Yeah. It's, yeah, it really is. But that's why, you know, people are more experienced can come in and show the, show us the ropes. Like, by the way, I would not probably be a good, uh, salesperson at windsurf today. I just probably, like, I am not the person that's going to, like, execute this, like, perfect playbook that was

handed to me, where I'm, like, qualifying criteria per letter of the playbook. You know, like, this is not my thing, you know. But I think you were, you, you kind of made a good fractional sales leader, I would say. Yeah. Because people still talk about you internally. I don't know what you did. You just like, you just did like motivational sessions or something. 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 KPT, 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. A few months ago, I think, two months ago, you sat down, you told me, I'm working on a new thing. And it's like super stealth and secret. But it's going to be the, you know, hottest new KP incubations since Glean. And I'm super interested in it. All I know is it leans on basically everything you've done.

everything we talked about. But can you introduce Roadrunner and the 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 30 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 just how it works. It's how it 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. 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 1099 a month.

Very simple, right? Then you're like, okay, actually, I 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 business. 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 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 want to do early renewals. Then you want to do expansions. Then you want to do them across. like 15 different product lines, right?

So the complexity is just starts to like increase exponentially. Then you're like, actually, I want to just, I want the customer to pay as they go. That may be how you guys are using, how you guys are selling today. It's like, well, I actually just like, like make sure they pay a minimum amount. And then anything above that, we'll just bill them, right? It's like how data breaks. Very custom function. Exactly.

Like that's how a lot, like that's how cursor and others are too. It's like a 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.

Because of tokens. Exactly. That's how you consume Anthropic and that's how you can consume OpenAI. Yeah. 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.

20 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 like pre-LLMs, pre-L-L-L-L-N. I asked them, what is the number one problem that you have in your company right now? So I was 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 this in this 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 whoa 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, you know, an 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 like, okay, I think we can actually build something better. Then I started asking myself, well, like, why is nobody, like, why is nobody fixing this? No, no, no, so in those dinners. Yeah, yeah, why is nobody fixing this? All 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 skews 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 like a Harvey is doing, you have to do. 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. And 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 S3Buck is can just like disappear. Right? So like, no, well, you actually have to rebuild this stack cloud native from the ground up. That's like the same thing that's happening in AI today. And so that's like the classic innovators dilemma, right? Which is like, what do you do? Yeah, do you re-architecture or do you wait?

Do you argue? 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 life their CPQ solution. And they're 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 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 open AI. You know?

Like that's just like, that's who we want to 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 up-market. The problem is more up-market, because that's where the complexity is. And in order to, like, do something elegantly up-market, you need to, like, know what you're

doing in the enterprise, right? And it just so happens that you need early believers like Gleene had with Rubrik that are willing to take a bet with you in a like design partnership to co-develop it with you. And it just so happens going back to our earlier conversations that episodes 1 through 80 were interviewing CROs, who are the people that have the pain. You've been preparing this the whole time. The other thing that I was like responsible for the KP was like these CIO networks who are the ones responsible for delivering software. to these people to alleviate their pain. And so it's like, I just so happened to know basically all of the key stakeholders in this problem.

So you're the guy? So actually, at that point, I was like, oh man, like, do I really want to, like, life's pretty, like, KP, life's, you know, like, I have, I know, I have seen what a company, what it looks like, the bite out of your life that it takes to, like, build a company. Anyway, point being, after talking with my partner at home and understanding, like, is this a commitment that we're willing to make? And talking to my partners at Kleiner Perkins, like folks like Mamun and Ilya, to be like, hey, if we do this, like, I think I think I have to do it. Like, I don't think it's going to really make sense for us to hire somebody off the street right now. and then I'll build a co-founding team that is like technically excellent in world class.

So anyway, that was the thing, or I should say the million series of things that that tipped us over the edge. Well, where are you today? What are you ready to share in terms of what the product is, what the people you're working with, the problems you solve? Yeah. So I will work backwards from the list that you used of how you would evaluate companies. Because it's the same thing as me. Wait, money first? All right.

Team first. Team first. Okay. Team was your first, wasn't it? Yeah, but you said backwards. No, no, no. I'll work top down. Okay.

Team first. Yeah. 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. It was absurd. Met Eugene his first day of school.

They've been working together basically ever. Since AJ went to Robin Hood, 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. Then they realized like the Tam or end market of EDU is not that compelling. Depends.

They were not that inspired by it. They wanted to go build. If you're capital and like you can do this. That's what business. Yeah. They wanted to go build a giant company. They independently found this problem, independently got excited about it. Sales more CPQ.

How do you deliver a better software for, for AEs? Yeah, CPQ. Okay. Because 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 Mamun 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 Glein did. So Glean built for rubric, we're building for four design partners, shared Slack channel, weekly standups. 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 I mean? What you really want is we had to make sure that our data model is infinitely flexible. Yeah. That we don't run into the next permutation that we haven't seen.

And so what you want are the hairiest design partners that have every skew, hardware, software, SaaS, consumption. Like, 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. Did you get it right from the start or what was the biggest changes that you've done since you started? Yeah. 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 a A.E. in the UK, you can only quote certain skews 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 skews, 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, all right, they can do it. How do you represent that on the U.S., 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. I like the way that you phrase that. I love earning right to do bigger things. You don't, what, something that makes me uncomfortable with founders saying, oh, we'll build a compound startup. in as early as you are is while the ambition's very big but have you earned it 100%. Can I actually tell you one other thing that kind of annoys me? I think a lot of times 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 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 the 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.

you know, 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 like the thing that I've been thinking about since I was one years old. And everybody else also has to feel like this. All right, I find that annoying. Well, sometimes you have to just puff yourself up for the fundraise. But there's always like sort of two versions of the story. AI findings. You know, we are an AI engineering podcast.

We do care about how AI is being utilized to, transform and revolutionize things. I think you're going to find it in small little ways, but any surprises. 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. Exactly. 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 want to like put one of these deals together, you're like calling deals desk 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 help. 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. And so like that is

where the magic of Roadrunner will come. So you're maybe if I can abstract a little bit, bit, you're kind of automating the deal desk and not the AE. You're extending, you're augmenting the AE, you're improving ramp up time for the AE or productivity of the AE. How would I describe it? I would say, we are... Like, whose job are you taking away? Like, I would say, 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? Deals desk and all these people should not be doing that either. Like there's way more strategic things that they could be doing. Yeah. I mean, in Connation, it's just like a really active Slack channel where everyone's just throwing stuff at each other all day long. It's a mess. Yeah, it's ma'am. Yeah, it's complete mayhem. Interesting. Okay. So anything else you want to cover on just Roadrunner in general? Like, your vision. I think we covered a lot of it. Just any part of the story that, you know, you want to get on the record.

No, I would just say, like, we are not demand constraint. 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 like 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 are, um, any product at inch. We are meaningfully bandwidth constrained on amazing talent that wants to go through the grind of building an early stage company. Yeah, well, we'll get you that. Kleiner is very good at getting that.

I don't think there's any doubt there. Okay, so just zooming out a little bit, I was prom said a bit earlier. You like running a lot. Uh-huh. Just tell me more about like just the general overall philosophy of high performance, right? I guess it kind of, what does that mean to you?

I think we had this conversation about this. What does that mean to you from like your personal life into work? I'll be like, I'll try and be tactical. Yeah, rather than abstract. So physically, to your prompt on running, I work out every day, no matter what. I sweat every day as soon as I wake up. Home Jim? It's either, so it's pretty consistent.

Mondays I bike up Hawkehill, 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. Oh, that's sport. Basketball has been the sport of choice recently, although every time I pick up a ball. all, I'm, like, pretty convinced I'm going to, like, you know, like, tear my ACL or something,

you know? Anyway, it depends how hard you push yourself. Yeah. I guess you push pretty hard. Yeah. Physically, I will work out every day, salad for lunch every day. I've been doing, 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 going to work out every day rather than have the cost. cognitive load of like, what days am I going to work out this week? Or when am I going to do it? Or like for lunch. I'm just going to have a salad. I have salads for lunch. Yes. There's no choice. I don't want to make the choice. The way I phrase it, I think Tim Urban says this. It's much easier to do something 100% on the time than it is to do it 90% on the time. 100%. Right. Like, think about

if you were deciding, I want to work out four days a week. Then you have to figure out like, what are you going to do? Yeah. You know, did I skip yesterday? Does that mean I can skip today? Exactly. And even to your question on like the style of workout. out. 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 want to reduce friction as much as I can, just like get those things done. On a personal reflection, like, there's a real reason I'm asking this question, but just a

side comment and you can comment if you want. I feel like this is so important, like your personal health and your fitness and your sort of peak productivity practice, that I find it interesting that VCs don't do that to their founders. Like, hey, I'm going to lock you in a room. Basically, only HF0 does this. Hey, I'm going to lock you in a room, you know, like make you, make you eat healthy, make you like, you know, take care of everything so you can go work on a company. Cognition has an engineering sort of basement. And I've advocated pumping oxygen into there because that is like a very valuable thing to have. And like, the problem is that. The problem is that it kind of has to come from within, meaning like it kind of 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 pieating 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. Kind of the real reason I was you listen to a lot of podcasts where you're doing all this. What are your favorite other podcasts?

Oh, man. Do you listen to your own pod? Shoot us on Rex. Yeah, I do. I'm very critical. I send notes 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. Like, you don't have to listen to everyone and send notes. Like, it just bogs down everything. Just, like, trust us. So I've started. I've created some space.

Yeah, right. Anyway, so I wasn't asking about our pod, but just like, just other pods that you enjoy and recommend to others. I'm just giving people recs. I think some of Oshonnesses invests like the best are pretty good. This whole thing with Colossus. 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, and he does a bunch of, of them, you know, I'd probably listen to a bunch of them. And if he's been on, it'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? No. Coaching, you know, we're considering that just because, you know, you basically do public speaking as part of your job, right? And well, you should probably get coaching for it, just like anything else. You know, my reflection doing this with you now 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 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 want to go. And so, I got the plan here. And like, you know, maybe if I were to do more on this side of the take.

versus yours, I think speaker training might make sense. Well, you know, speaking comes in all shapes and forms, including running a company. So I do view it as a very general use case. For me, I run a conference. And so I do the keynote every time every conference. So it really actually does matter because I set the example for my speakers. My favorite definition of sales 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 like, 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 like 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? The challenge for you is you're pretty naturally good at it. So it's going to be hard to find someone who is better than you to train you. So, you know, a bit of a compliment. Speaking of definitions, my favorite closing question, what is the definition of grit to you?

The namesake of the show came from Angela Duckworth's book, Great. Who I had the honor of flying out to Pennsylvania an interview, which was amazing. The same is cool. So the background also is that Penn invented positive psychology or pioneers. positive psychology. And she came from that line of thinking. Yeah. And her definition is, I'm sure to book about it, so it's hard to define it quite narrowly, but passion plus perseverance over a sustained period of time. And I think the like natural tendency when you think about grit is like literally gritting your teeth. Like how do you just endure? And I think the like

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, I don't know, I 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. It's probably a superlative form of grids that really captures that it's going to flow state grit or passion grid and whatever adjective you want to add to it. Totally. It would be nice. But thanks for being on, Lane Space. I feel like I've been a little bit experiencing the grid experience myself.

And thanks for joining us. It was hard for me not to ask you too many questions. I know. I tried. You got one. What was your mind? Do you have a dream guest? Dream guest, I would say.

is a supporter of ours that has promised to be on at some point, Andre. He's a... Carpathie? Yeah, yeah. He's been a mentor for a long time. He's a teacher. He's very authentic and very super knowledgeable. And I think an inspiration for a lot of us who are trying to figure out, you know,

like from trusted sources, like the truth of what's possible with LLMs. And he's very autodynactic as well, which is something I strongly identify with. You don't really know something unless you've really taught it to yourself and build everything, a version of it for yourself. And he does represent the simplicity and clarity that I want to see in the world that I try to represent within space. Really cool, man. I appreciate you doing this. It's the first time I've been, the tables have been turned on me. Crazy experience.

First of many. Thanks, man.