

AI to AE's: Grit, Glean, and Kleiner Perkins' next Enterprise AI hit — Joubin Mirzadegan, Roadrunner
Latent Space
What You'll Learn
- ✓The guest's background in sales and startups, and how that led him to Kleiner Perkins
- ✓The challenges of enterprise software and the potential of using LLMs to abstract away complexity
- ✓The guest's experience interviewing high-profile figures like Mark Zuckerberg and Fei-Fei Li
- ✓The evolution of the guest's podcast from audio-only to video, and the importance of giving it time to grow
- ✓The vulnerability and challenges of being a podcast host, and the need to tune out the noise
Episode Chapters
Introduction
The guest discusses his background in sales and startups, and how that led him to Kleiner Perkins
Challenges in Enterprise Software
The guest talks about the challenges of enterprise software and the potential of using LLMs to abstract away complexity
High-Profile Interviews
The guest shares his experience interviewing figures like Mark Zuckerberg and Fei-Fei Li
Podcast Evolution
The guest discusses the evolution of his podcast from audio-only to video, and the importance of giving it time to grow
Challenges of Hosting
The guest reflects on the vulnerability and challenges of being a podcast host, and the need to tune out the noise
AI Summary
The episode discusses the guest's experience in the sales and startup world, and how that led him to join Kleiner Perkins and start a podcast focused on interviewing Chief Revenue Officers (CROs). He talks about the challenges of building enterprise software, the value of using large language models to abstract away complexity, and his experience interviewing high-profile figures like Mark Zuckerberg. The guest also reflects on the evolution of his podcast, the importance of giving it time to grow, and the benefits of the video format.
Key Points
- 1The guest's background in sales and startups, and how that led him to Kleiner Perkins
- 2The challenges of enterprise software and the potential of using LLMs to abstract away complexity
- 3The guest's experience interviewing high-profile figures like Mark Zuckerberg and Fei-Fei Li
- 4The evolution of the guest's podcast from audio-only to video, and the importance of giving it time to grow
- 5The vulnerability and challenges of being a podcast host, and the need to tune out the noise
Topics Discussed
Frequently Asked Questions
What is "AI to AE's: Grit, Glean, and Kleiner Perkins' next Enterprise AI hit — Joubin Mirzadegan, Roadrunner" about?
The episode discusses the guest's experience in the sales and startup world, and how that led him to join Kleiner Perkins and start a podcast focused on interviewing Chief Revenue Officers (CROs). He talks about the challenges of building enterprise software, the value of using large language models to abstract away complexity, and his experience interviewing high-profile figures like Mark Zuckerberg. The guest also reflects on the evolution of his podcast, the importance of giving it time to grow, and the benefits of the video format.
What topics are discussed in this episode?
This episode covers the following topics: Enterprise software, Large language models, Podcast hosting, Venture capital, Sales and startups.
What is key insight #1 from this episode?
The guest's background in sales and startups, and how that led him to Kleiner Perkins
What is key insight #2 from this episode?
The challenges of enterprise software and the potential of using LLMs to abstract away complexity
What is key insight #3 from this episode?
The guest's experience interviewing high-profile figures like Mark Zuckerberg and Fei-Fei Li
What is key insight #4 from this episode?
The evolution of the guest's podcast from audio-only to video, and the importance of giving it time to grow
Who should listen to this episode?
This episode is recommended for anyone interested in Enterprise software, Large language models, Podcast hosting, and those who want to stay updated on the latest developments in AI and technology.
Episode Description
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/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction and the Zuck Interview Experience 00:03:26 The Genesis of the Grit Podcast: Hiring CROs Through Content 00:13:20 Podcast Philosophy: Creating Authentic Conversations 00:15:44 Working with Arvind at Glean: The Enterprise Search Breakthrough 00:26:20 Windsurf's Sales Machine: Google-Class Product Meets Salesforce-Class Distribution 00:30:28 Hiring Sales Leaders: Anti-Patterns and First Principles 00:39:02 The CPQ Problem: Why Salesforce and Legacy Tools Are Breaking 00:43:40 Introducing Roadrunner: Solving Enterprise Pricing with AI 00:49:19 Building Roadrunner: Team, Design Partners, and Data Model Challenges 00:59:35 High Performance Philosophy: Working Out Every Day and Reducing Friction 01:06:28 Defining Grit: Passion Plus Perseverance
Full Transcript
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. 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 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. All right. I got to ask you, how was the Zuck interview? Yeah, it's very interesting. Are we 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 a 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 impacts on humanity than Mark Zuckerberg. Right. Facebook will just be a funding mechanism for the greatest bio research work done in human history. Wow. Were you nervous? You must have been nervous. I wasn't nervous because of the sheer amount of prep that the CZI 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 prepped us so well. So, 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-brazing knowledge? I feel like I had to like interview three times to get even in that room. So yeah, it was, it was very, it was very fascinating. we're very honored to be picked by them because we're not a bio-focused podcast. No. But the whole point was to reach out to engineers. And while they're there, we're on a stronger footing. 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 Fei Fei Li today. Today? Yeah, just released. You came from that? Well, labs. No, and then we just released it. Oh, you did? Oh, nice. That was a couple of weeks ago. Who else have you done? There's a bunch. Greg Brockman. 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 that gets 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 were 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 think the transition from the CRO to the founder, whatever, it 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. Yeah. 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? Yeah. Whereas if you're the founder, 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, yeah, I did. I appreciate it, man. It's, 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 this transition from chief revenue officers 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. 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. 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 was 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 time, like this sounds incredible, but like maybe later on. So anyway, we got to talking and it was, it was, it 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 Arvin to 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. It was called CO 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, 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, 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, if I'm being honest. KP was skeptical. And 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 these CROs. 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 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 of podcast is nobody can talk back in the comments because there are no comments. I guess. With audio. iTunes reviews. With audio. Right, right, right. Yeah. Yeah, it was audio only. It was actually easier with it 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 listen 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, it's just noise. And then when you turn it back on, you, you flip the home screen up, it's video. And so I kind of wanted the multimodality where, for example, if I'm cooking, you know, it's the videos open or take a shower, the videos 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 you need both. You do need both. I think the question is, 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 of things, right? One, well, we are a technical podcast, so we can show code, we can show diagrams, to show demos of the products. And so do we spend the editor effort and money to put that into the video on the off chance that the 5% of our audience watching on YouTube actually sees it? I don't know. It's not super clear. The other more relevant thing is when you look at people like All In or Dorkesh, they start video and then they win audio. Or 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'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 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 a 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 guest that I want to be. It's like, you know, when you're sleeping at night before you go on to 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 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's it bounces off. Yeah. I 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 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, very well prepped and screened. Sometimes you just don't get to 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, Jubin, 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. So it's really not that bad. That's true. It's really not that bad. That was Create a Corner. I do want to obviously get you on the sort of professional side, but obviously I love to indulge in Create a 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 arvind that made you understand well here's what works in applying ai to the enterprise or whatever like selling it to enterprise yeah i think um at the time in the early days of glean it when arvind 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 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 Mamoun 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, 2019. This was not like LLMs had not been birthed yet, right? And so I think in the beginning, 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 auth like this multi cake of protections to make sure that I never see what I never supposed to see right Like I never see SWIX 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. 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, extremely unobvious. 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, um, sort of default rejection. Yeah. So what do you do there? What do you, what do you learn? Yeah. 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 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, it's a 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 passing a bill through Congress, right? 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 what's in the bill, the product. Make sure everybody else, you're helping them manage their own process and organization. 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 what's weird is you have a special expertise. I think 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 there 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 were 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 Nipure 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 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 in 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 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. And then maybe market, product, money. Yeah, market's really good. Well, I guess, you know, maybe bundle market with products or just assume that market is given, given I only work in DevTools. But yeah, that's an 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 Varun 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 code base. and a very tough go-to-market. I've heard from multiple Windsor folks that you went there and did like sales training, cheerleader sessions. What is it that you do? At Windsor or in general at KP? You use Windsor for an example, but use that to tell the story of- Of KP? Yeah. 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. It 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 Varun get access to world-class customers so we doubled down on that and hired 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, but like he's never had to actually build the machine that is sales and marketing. I think this is something that people don't appreciate about Winsurf is that they look at the product, they understand it's a, you know, it's agentic IDE, 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, um, and maybe we can quantify as well, right? I think like something like zero to a hundred million AOR in seven months or 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 uh coding is an incredible use case for ai right now right but i don't expect like government fortune 500 to adopt at this at this kind of rate then that's why i was seriously miscalibrated on like i was with them i did a podcast with them on the day of Windsurf's launch. And even then I was like, eh, I don't know. This seems like a cursor clone. I think what Windsurf 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. 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'll pay the $20 a month. Exactly. And then they'll just love us so much, we'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 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 for engineers so like 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. So you've seen it firsthand. It's no joke. This is why, I mean, I put it as part of my why Cognition thesis. Core Cognition, Devin Cognition is very good at product in 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 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't be serious about everything and everything's the number one priority. That's right. That's right. What the hell? But they did, they, they, they pulled it off, which is impressive. The one anecdote I guess I'll 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's like a whole studio set that you can do anything out of and make it interesting on video. And that'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 Glean 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? 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, going to 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 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 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, you get told no way more than you get told yes. After you get told no enough times, internal, something 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 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, 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? Does that make sense? Yeah, it totally makes sense. It's very first principles thinking is the way that Scott Wu would 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 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. 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 an interview sometimes you just don get that because that what sales training is for It like people prep battle cards They get time with the product. They get time with the founders. Then they get it, right? It's hard to get that in the interview. Yeah, but 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? What's really funny is, well, one of my core memories as an engineer learning the ropes in startups was our new head of sales coming in at Netlify, which is a KP company, coming in saying, you know, I was very stressed. I was like, well, you know, our competitors have these, 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. You know? 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 get in the weeds with people. I think that's the 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. 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 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? Right. 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 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 um it is a machine so much there's boot camps there's battle cards but in the early days like it is um 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 uh it really is but this is why you know people with more experience can come in and 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 you're not deep enough in the product execute 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, you know? Um, 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. Uh, I don't know what you did. You just like, you just did like motivational sessions or something. I honestly, they did, they did most of the heavy lifting. I probably like went in there and did some like random rah, rah stuff. Uh, 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. 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, super stuff and secret, but it's going to be the hottest new KP incubation 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. During my sales career, probably the number one thing that used to break my back was that the underlying software with Salesforce CPQ and others, just to 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. OK, and this is just this is just like standard across the industry. This is 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. OK. 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. OK. And then it's like 1099 a month. Very simple. Right. Then you're like, OK, 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 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 uh 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 just starts to like increase exponentially then you're like actually um i want to just i want the customer to pay as they go. That might 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 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? 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-anything, 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 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 fixing this? No, no, no. So in those dinners. Yeah, yeah. Why is nobody fixing this? All right, yeah. 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 like a Harvey is doing, you 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. 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 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 like the same thing that's happening in in 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 okay so that that happened then i come to find out okay uh 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, we love that. And the reason we love that is like, boy, would I rather compete with like whatever, a hundred thousand 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 questions, 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 um 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 glean had with rubric 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 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 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'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 um point being um after talking with uh 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 Ilya to be like, hey, if we do this, like, 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 and world-class. So anyway, that was the thing, or I should say the million series of things that tipped us over the edge. Well, where are you today? What are you ready to share in terms of what the product is, the people you're working with, the problems you solved? 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, that's it. Team first. Oh, 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. 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 N market of EDU is not that compelling. Depends. They were not that inspired by it. They wanted to go build. If you're a capitalist and like you can do this. That's the whole business. Yeah. They wanted to go build a giant company. They independently found this problem, independently got excited about it. Salesforce CPQ? How do you deliver a better software 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 Mamoun interviews me on grit, where we'll talk, 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 rubric 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 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 sass consumption like you want the mess okay to throw that at your data model to make sure that nothing tips it over and so those are the types of of of design partners that 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 done since you started 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 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 through 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 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. That's, I like the way that you phrased that. I love earning right to do bigger things. But you don't, you don't, what, something that makes me uncomfortable with founders saying, oh, we'll build a compound startup as early as you are, is, well, 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 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. 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 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. 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 pump 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 sales for cpq which most people are you 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. And so like that is where the magic of Roadrunner will come. So you're, maybe if I can abstract a little 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? 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. 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. you know like there's way more strategic things that they could be doing yeah i mean in in cognition it's just like a really active slack channel where everyone's just throwing stuff at each other all day long it's it's a mess yeah it's mayhem yeah it's complete mayhem um interesting okay so any 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 uh 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, um, yeah, we're, um, you need product an 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, we'll, uh, get you that. Your client is very good at getting that. and I don't think I don't think there's any doubt there okay so just zooming out a little bit I was prompted a bit earlier you're 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 first think 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 go. Basketball has been the sport of choice recently. Although every time I pick up a ball, I'm like pretty convinced I'm going to like, you know, like tear my ACL or something. Anyway. 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. 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 cognitive load of like, what days am I going to work out this year? 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% of the time than it is to do it 90% of 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, 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 slight 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 in 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 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 pie eating 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 going to 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 pod? Shoot us on Rex. Yeah, I do. I'm very critical. 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 right 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 stopped it's also 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 rex i think some of uh 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 uh 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 it's not the easiest speaker to follow no it is a bit jumbled yeah uh 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, 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. Yeah. And like, you know, maybe if I were to do more on this side of the table versus yours, I think speaker training might make sense. Well, you know, speaking comes in all shapes and forms, including running a company. So, 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, Grit, who I had the honor of flying out to Pennsylvania and interviewing, which was amazing. The same school. So the background also is that Penn invented positive psychology or pioneered 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 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 kind of flow state grit or passion grit and whatever adjective you want to add to it. Totally. It'd be nice. But thanks for being on Lanespace. I feel like I've been a little bit experiencing the grit experience myself. And thanks for joining us. It was hard for me not to ask you too many questions. I know. I tried. You get one. You get one. What was on 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- Karpathi? 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 autodidactic as well, which is something I strongly identify with. You don't really know something unless you've really taught it to yourself and built 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. Thank you.
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