1 00:00:00,080 --> 00:00:04,360 If there is not 10s of millions, hundreds of millions of dollars 2 00:00:04,360 --> 00:00:07,480 worth of seats for us to sell because everyone's been laid off 3 00:00:07,680 --> 00:00:09,520 the world. Like, like, like I need, I need 4 00:00:09,520 --> 00:00:13,120 to own a lot of guns. Like the least of my problems is 5 00:00:13,120 --> 00:00:15,840 my fucking SAS business. Like this is what it looks like 6 00:00:15,840 --> 00:00:17,640 to live in a Republic. It's messy. 7 00:00:18,040 --> 00:00:20,400 You, you, you. Like so it requires on the part 8 00:00:20,400 --> 00:00:24,360 of other actors to sort of interpret and what the will of 9 00:00:24,360 --> 00:00:26,080 democracy is beyond just like difference. 10 00:00:26,080 --> 00:00:29,560 Like every generation has felt broken in some way. 11 00:00:29,560 --> 00:00:31,520 I always think it's funny when people we've never been more 12 00:00:31,520 --> 00:00:33,560 divided. Bitch, we fought a civil war. 13 00:00:34,120 --> 00:00:36,800 Palantir is one of the most mysterious companies in tech. 14 00:00:37,000 --> 00:00:39,920 If you're an outsider, it's a company created by Peter Thiel 15 00:00:39,920 --> 00:00:42,040 that's gathering intelligence for the deep state. 16 00:00:42,040 --> 00:00:44,960 If you're an insider, it's an overvalued enterprise software 17 00:00:44,960 --> 00:00:47,440 company that's heavily reliant on human consultants. 18 00:00:47,480 --> 00:00:51,200 Today I talked to Barry McArdle, CEO of HECS, which he says 19 00:00:51,200 --> 00:00:53,320 aspires to be the cursor for data. 20 00:00:53,320 --> 00:00:56,520 He was a long time forward deployed engineer at Palantir 21 00:00:56,520 --> 00:00:58,000 and saw the company from the inside. 22 00:00:58,240 --> 00:01:01,280 We talk about Palantir subcontractor Anthropics, fight 23 00:01:01,280 --> 00:01:04,000 with the government, and argue about how much tech companies 24 00:01:04,000 --> 00:01:06,680 should defer to the President of the United States in a 25 00:01:06,680 --> 00:01:09,200 democracy. But first we also talk about 26 00:01:09,200 --> 00:01:11,920 what it was like working at Palantir, which he called 27 00:01:11,920 --> 00:01:16,120 mundane, while he simultaneously talked about projects in unnamed 28 00:01:16,120 --> 00:01:19,320 Middle Eastern countries. We dug into the forward engineer 29 00:01:19,320 --> 00:01:22,480 craze that Palantir pioneered, and these days every tech 30 00:01:22,480 --> 00:01:25,720 company wants to copy. Barry defends the model but 31 00:01:25,720 --> 00:01:27,600 doesn't actually use it at his own company. 32 00:01:28,080 --> 00:01:30,800 Welcome to the Newcomer Podcast hosted by me, Eric Newcomer. 33 00:01:30,800 --> 00:01:33,920 I am the author of the Newcomer Newsletter, which covers the 34 00:01:33,920 --> 00:01:36,760 business and people in the startups and venture capital 35 00:01:36,760 --> 00:01:39,480 industry. Check us out at newcomer.co. 36 00:01:39,640 --> 00:01:41,520 Thanks for listening. Here's my conversation with 37 00:01:41,520 --> 00:01:51,000 Barry McArdle. Well, literally I heard today 38 00:01:51,000 --> 00:01:56,840 that we didn't get invited to perplexity some perplexity event 39 00:01:57,040 --> 00:01:59,720 because they're mad that they were the most shorted company on 40 00:02:00,440 --> 00:02:02,400 your fault you're. Just asking the question. 41 00:02:02,440 --> 00:02:03,840 Yeah, you put me up to the stunt. 42 00:02:03,840 --> 00:02:06,240 Apparently, yeah. I thought, I think it's an 43 00:02:06,240 --> 00:02:07,960 interesting question. Who would you short? 44 00:02:09,080 --> 00:02:12,360 I think we're all, I think it's good that you're not able to 45 00:02:12,360 --> 00:02:14,840 short start-ups 'cause I think that would get into a very 46 00:02:15,400 --> 00:02:19,040 pernicious and shitty game. And imagine if venture funds 47 00:02:19,040 --> 00:02:21,680 were like hedge funds where they've got long positions and 48 00:02:21,680 --> 00:02:23,960 they've got short positions and they're like hedging, right? 49 00:02:23,960 --> 00:02:27,720 That'd be fascinating. The All right, I'm here with 50 00:02:27,720 --> 00:02:30,520 Barry McArdle. Welcome to the newcomer podcast, 51 00:02:30,560 --> 00:02:32,520 CEO of Hex. He's been a long time at 52 00:02:32,520 --> 00:02:35,560 Palantir. And as someone who's in my ear 53 00:02:35,560 --> 00:02:39,960 with fun ideas and on Twitter, Assassin and Spicy. 54 00:02:39,960 --> 00:02:43,840 So I expect you to live up to your Twitter persona on the 55 00:02:43,840 --> 00:02:44,840 podcast. Sparse. 56 00:02:44,840 --> 00:02:47,560 Sometimes I tweet a lot and then I'll go quiet for like months. 57 00:02:48,200 --> 00:02:52,080 You had a what your most viral one was on the subject we want 58 00:02:52,080 --> 00:02:53,840 to talk about. I don't want to butcher it. 59 00:02:53,840 --> 00:02:58,080 It's the IT was. It was, it's only, it's only for 60 00:02:58,080 --> 00:03:00,840 deployed if it's from the Palantir, a region of France. 61 00:03:00,840 --> 00:03:03,440 Otherwise it's just sparkling sales engineering I think was 62 00:03:03,480 --> 00:03:04,320 the. Exactly. 63 00:03:04,320 --> 00:03:07,880 So I, we want to start off with Palantir, I think from 2 levels, 64 00:03:07,880 --> 00:03:11,440 one sort of, I don't know the YouTube show level, which is 65 00:03:11,440 --> 00:03:14,880 like, I don't know, people hear Palantir and the headlines and 66 00:03:14,880 --> 00:03:17,680 like what to make of it. And then we'll do our nerdy tech 67 00:03:17,680 --> 00:03:21,080 show question, which is I feel like every startup in the world 68 00:03:21,080 --> 00:03:24,360 has learned that you can actually be a consulting company 69 00:03:24,400 --> 00:03:27,320 if you call it a forward deployed engineer. 70 00:03:27,440 --> 00:03:30,320 And I don't think will you. Be punished on multiples, you'll 71 00:03:30,320 --> 00:03:32,280 be rewarded. It's like, oh, all of a sudden 72 00:03:32,280 --> 00:03:33,800 it's good. Like, throw humans at it. 73 00:03:34,160 --> 00:03:35,440 Yeah. But let's start with like the 74 00:03:35,440 --> 00:03:38,160 spooky YouTube. And, you know, I mean, I, I just 75 00:03:38,160 --> 00:03:40,800 think a lot of people on the Internet hearing about Palantir 76 00:03:40,800 --> 00:03:43,880 just have a like, this is this is the deep state or like, 77 00:03:44,080 --> 00:03:47,240 having spent a lot of time, what, like 4 1/2 years, five 78 00:03:47,240 --> 00:03:48,120 years, five years. Yeah. 79 00:03:48,120 --> 00:03:49,880 Yeah. What Yeah. 80 00:03:49,880 --> 00:03:54,960 Is is Palantir the big bad? No, I, I and I'll just, I'll 81 00:03:54,960 --> 00:03:57,080 just claim by I haven't, I haven't been there in a few 82 00:03:57,080 --> 00:03:59,400 years now, but. You stay close to and you know, 83 00:03:59,400 --> 00:04:01,160 the whole network of people starting companies. 84 00:04:01,160 --> 00:04:03,680 Yeah, yeah. And I, I'm some, a lot of people 85 00:04:03,680 --> 00:04:06,000 there. I think the, the interesting way 86 00:04:06,000 --> 00:04:08,560 we understood ourselves then, and I suspect it's still very 87 00:04:08,560 --> 00:04:11,440 true now. And we, we said this in almost a 88 00:04:11,440 --> 00:04:13,360 slightly diminutive way. It was like we're a data 89 00:04:13,360 --> 00:04:16,360 integration company. Like it turns out that like all 90 00:04:16,360 --> 00:04:20,440 these companies in the world that these institutions or 91 00:04:20,480 --> 00:04:25,480 private companies and public institutions that you could, you 92 00:04:25,480 --> 00:04:27,120 know, wanted to be able to operate better. 93 00:04:28,040 --> 00:04:30,480 It really the the problems I'll come back to like some form of 94 00:04:30,480 --> 00:04:32,560 data integration. Like you actually have a lot of 95 00:04:32,560 --> 00:04:35,120 the data like available in some way. 96 00:04:35,360 --> 00:04:37,120 What you're saying is. We're, it's actually a really 97 00:04:37,120 --> 00:04:39,800 boring company with the CEO that says and sometimes we have to 98 00:04:39,800 --> 00:04:42,240 kill people. There is, I mean, I, I'll, I'll 99 00:04:42,240 --> 00:04:44,920 be honest, there is a kind of boring core to it. 100 00:04:44,920 --> 00:04:46,640 Like there were times where it was kind of like we're kind of 101 00:04:46,640 --> 00:04:49,800 just doing a lot of data plumbing and it, it obviously 102 00:04:49,800 --> 00:04:51,640 the brand is incredible. And I think the leadership there 103 00:04:51,640 --> 00:04:54,840 has done a great job developing and, and nurturing that brand. 104 00:04:55,320 --> 00:04:58,240 And look, look, I, I'm not saying that the results aren't 105 00:04:58,240 --> 00:04:59,480 there. It's a fabulous company. 106 00:04:59,480 --> 00:05:01,400 It's a company I'm very proud to have been at. 107 00:05:01,400 --> 00:05:04,080 I'm proud of almost feeling. Like like $300 billion. 108 00:05:04,320 --> 00:05:06,440 I can't look at the stock price now because I sold most of my 109 00:05:06,440 --> 00:05:09,320 shares at less this less than the stock price. 110 00:05:09,320 --> 00:05:11,360 I have a very discordant relationship with it. 111 00:05:12,480 --> 00:05:17,880 But yeah, like I I think at the core there's some really boring 112 00:05:17,880 --> 00:05:19,600 stuff that we just got really right. 113 00:05:19,600 --> 00:05:22,280 And the initial brilliance of Palantir in the early days was 114 00:05:22,280 --> 00:05:24,720 the ontology. It was this kind of insight of, 115 00:05:24,720 --> 00:05:28,880 you know, the, the, the slightly hagiographic version of it is 116 00:05:28,880 --> 00:05:32,680 like, you know, early team was going, the founders were going 117 00:05:32,680 --> 00:05:35,520 to these three letter agencies and sort of realizing that the 118 00:05:35,600 --> 00:05:38,320 problems they had. And you know, the mythos was a 119 00:05:38,320 --> 00:05:40,880 little bit like the, the reason we missed 911 or one of the 120 00:05:40,920 --> 00:05:43,560 reasons you kind of missed events like that is 'cause you 121 00:05:43,560 --> 00:05:46,000 actually had all the information somewhere, but you weren't able 122 00:05:46,000 --> 00:05:49,320 to get the complete picture. And so by being able to 123 00:05:49,320 --> 00:05:51,960 integrate it and build the ontology on top of it, OK, now 124 00:05:51,960 --> 00:05:53,880 you can see the whole picture and you can sort of make it 125 00:05:53,880 --> 00:05:57,240 something that humans can reason about and understand and engage 126 00:05:57,240 --> 00:06:01,200 with. And that shape of dynamic is 127 00:06:01,200 --> 00:06:04,080 true in the government, you know, intelligence community, 128 00:06:04,080 --> 00:06:06,280 military, also very true in a lot of private companies. 129 00:06:06,280 --> 00:06:08,920 And so a lot of what I did when I joined, I joined when we had 130 00:06:08,920 --> 00:06:11,600 like a very nascent commercial business. 131 00:06:11,600 --> 00:06:13,400 So I started my career in consulting. 132 00:06:13,440 --> 00:06:16,040 I'd been like on the really nerdy data tech side of my 133 00:06:16,040 --> 00:06:19,200 consulting projects. My friend who worked at Pouncer 134 00:06:19,200 --> 00:06:21,520 was like, you just come do this at like for real. 135 00:06:22,000 --> 00:06:24,320 And I started, we didn't really have a commercial product at 136 00:06:24,320 --> 00:06:26,040 all. And most of what we were doing 137 00:06:26,040 --> 00:06:28,040 was just sort of going around and doing effectively these 138 00:06:28,040 --> 00:06:31,080 consulting projects, integrating data, kind of stitching things 139 00:06:31,080 --> 00:06:34,040 together, giving people a finally, like a complete picture 140 00:06:34,040 --> 00:06:36,560 of their organization and the problems they had. 141 00:06:36,560 --> 00:06:38,120 And that by itself was really valuable. 142 00:06:38,120 --> 00:06:40,480 Because they would buy tech services but then not get the 143 00:06:40,480 --> 00:06:42,720 most out of them, stitching them up with everything. 144 00:06:42,760 --> 00:06:46,200 Yeah, you'd have, you'd have like the that, that era, you 145 00:06:46,200 --> 00:06:48,080 know, 10 years ago, you'd have a lot of people building these 146 00:06:48,080 --> 00:06:49,600 like data lakes. I was like, oh, we'll get all 147 00:06:49,600 --> 00:06:51,920 our data in the data lake. I was like, yeah, you land all 148 00:06:51,920 --> 00:06:55,400 the data in this S3 bucket basically or HDFS cluster. 149 00:06:55,400 --> 00:06:59,760 And it's like, now what we have the data, it's like, yeah, you 150 00:06:59,760 --> 00:07:00,560 have it. Are you use? 151 00:07:00,640 --> 00:07:02,160 Are you able to make better decisions because. 152 00:07:02,160 --> 00:07:04,920 Of it and and palander would help them like visualize it and. 153 00:07:04,960 --> 00:07:06,880 Yeah, it wasn't even viz. I, you know, it's funny 'cause 154 00:07:06,880 --> 00:07:09,160 people picture it like, oh, this analysis with the viz stuff, our 155 00:07:09,160 --> 00:07:13,400 viz was always like pretty mid. Is, is really the integration 156 00:07:13,400 --> 00:07:16,440 behind the scenes, which I know sounds kind of sexy and unsexy 157 00:07:16,440 --> 00:07:18,920 and vague, but like it's literally like, OK, you've got 158 00:07:18,920 --> 00:07:21,720 these five different data sets. They're all sort of talking 159 00:07:21,720 --> 00:07:23,320 about the same thing. You want to get a complete 160 00:07:23,320 --> 00:07:25,280 picture between them? How do you integrate them? 161 00:07:25,280 --> 00:07:27,120 What are the relationships between these? 162 00:07:27,400 --> 00:07:30,280 How do I see an event or an incident that's happening here 163 00:07:30,280 --> 00:07:32,280 and go understand what are the other times something like that 164 00:07:32,280 --> 00:07:34,280 has happened? What were the resolutions? 165 00:07:34,280 --> 00:07:37,320 And is there a shared link? Like that is a lot of the kind 166 00:07:37,320 --> 00:07:38,720 of thing. And it's it's not like the 167 00:07:38,720 --> 00:07:43,040 actual like algebra behind the scenes is like, you know, it's 168 00:07:43,040 --> 00:07:45,000 just sequel queries. It's like fairly straightforward 169 00:07:45,000 --> 00:07:47,200 joins and stuff. And like every once in a while 170 00:07:47,200 --> 00:07:49,480 we'd get wild and do some regressions, but it's like. 171 00:07:50,200 --> 00:07:52,360 Really the reasons for deployed is you have to understand the 172 00:07:52,360 --> 00:07:53,960 customer enough to really understand the. 173 00:07:53,960 --> 00:07:58,320 Logic of this model around it then and, and I think the four 174 00:07:58,320 --> 00:08:02,360 deployed thing, this, this kind of gets into the, the, the role 175 00:08:02,360 --> 00:08:06,240 and what people misunderstand. Like when I joined, you know, we 176 00:08:06,240 --> 00:08:09,480 had these 4 deployed engineering teams and, and they still have 177 00:08:09,480 --> 00:08:11,720 them. At the time it was really like 178 00:08:12,360 --> 00:08:15,040 we didn't have a product. We were hacking a lot of stuff 179 00:08:15,040 --> 00:08:17,720 up there was that was the whole. Critique, apology over years it 180 00:08:17,720 --> 00:08:21,000 was it's just secretly A consulting like internally we'd 181 00:08:21,000 --> 00:08:22,640 we'd like. Take issue with that. 182 00:08:22,680 --> 00:08:24,880 Like I remember these emails someone of the guys in 183 00:08:24,880 --> 00:08:27,560 leadership would sign and being like, people don't understand 184 00:08:27,560 --> 00:08:29,000 us. They think we're just a services 185 00:08:29,000 --> 00:08:30,640 company. Like we'd kind of look around 186 00:08:30,640 --> 00:08:32,480 and be like, I don't know, it feels like we're doing services. 187 00:08:32,640 --> 00:08:35,200 I'd read this e-mail from a windowless conference room and 188 00:08:35,200 --> 00:08:38,280 so town where I'm like, basically I'm like hacking 189 00:08:38,280 --> 00:08:41,679 together an Excel spreadsheet to dump into a Jupiter notebook so 190 00:08:41,679 --> 00:08:44,280 I can export the results into our front end app builder to 191 00:08:44,280 --> 00:08:45,560 make it look like we did software. 192 00:08:45,560 --> 00:08:47,480 It was like, I don't know, it feels pretty servicey. 193 00:08:47,880 --> 00:08:51,720 But what wound up really working was you go and effectively do 194 00:08:51,720 --> 00:08:55,200 services. And at the time we didn't have a 195 00:08:55,200 --> 00:08:58,160 core platform really to speak of in the commercial side that we 196 00:08:58,160 --> 00:08:59,880 were doing these services on top of. 197 00:09:00,280 --> 00:09:02,080 But over time we built that platform leverage. 198 00:09:02,080 --> 00:09:04,160 But you go and you basically do these services. 199 00:09:04,160 --> 00:09:06,200 You go in and say, hey, we're going to solve your hardest 200 00:09:06,200 --> 00:09:09,040 problem. You know, Karp, Dr. Karp would 201 00:09:09,040 --> 00:09:12,760 meet Aceo or some leader and say, let me send you a team. 202 00:09:13,040 --> 00:09:15,160 They'll come in, just tell them your hardest problem. 203 00:09:15,160 --> 00:09:16,800 They'll come in and help try to solve it. 204 00:09:17,280 --> 00:09:20,200 And you'd kind of have like 3 months, the canonical pilot 205 00:09:20,200 --> 00:09:23,840 length to go and work super hard and fly around a lot and try to 206 00:09:23,840 --> 00:09:26,240 solve it. And what would wind up happening 207 00:09:26,240 --> 00:09:28,320 is you'd, you'd have to build new things in the field. 208 00:09:29,280 --> 00:09:31,520 And then like most of those things wouldn't work out, Like 209 00:09:31,520 --> 00:09:33,520 the pilot wouldn't convert, it wouldn't be valuable enough, 210 00:09:33,520 --> 00:09:35,920 whatever. But some of those things would 211 00:09:35,920 --> 00:09:39,200 go on to be multibillion dollar business, you know, like just 212 00:09:39,200 --> 00:09:43,160 products and and foundational parts of the platform and the 213 00:09:43,160 --> 00:09:45,880 whole model of forward deployed engineering that really, really 214 00:09:45,880 --> 00:09:47,120 worked. And the thing that people kind 215 00:09:47,120 --> 00:09:52,240 of miss is it's a radical deference to the field on what 216 00:09:52,240 --> 00:09:54,800 to build. Like most organizations, they're 217 00:09:54,800 --> 00:09:57,160 like, OK, we've got a road map and all these slides. 218 00:09:57,680 --> 00:09:59,360 We know the customers essentially. 219 00:09:59,360 --> 00:10:01,560 And I think especially a lot of founders like I, I'm like this 220 00:10:01,560 --> 00:10:03,480 sometimes, like I know what to build. 221 00:10:03,720 --> 00:10:05,560 We gotta go build this thing. We just gotta go find the 222 00:10:05,560 --> 00:10:06,200 customers. That's. 223 00:10:06,200 --> 00:10:08,240 Part of what you're selling the investors, it's like I have the 224 00:10:08,240 --> 00:10:10,920 vision. And the reality is like what 225 00:10:10,920 --> 00:10:13,320 really worked, at least in my time there, the way it worked 226 00:10:13,320 --> 00:10:16,200 was you just hired a lot of really smart people, kept the 227 00:10:16,200 --> 00:10:19,360 bar really high, gave them freakish, irresponsible amounts 228 00:10:19,360 --> 00:10:23,200 of ownership and autonomy. We were a bunch of like mid 20 229 00:10:23,200 --> 00:10:25,680 somethings being put in charge of these like really high stakes 230 00:10:25,720 --> 00:10:28,120 deployments and budgets. And it was just like. 231 00:10:28,120 --> 00:10:30,280 In some ways, you know Mckenzie's go to that too, where 232 00:10:30,280 --> 00:10:31,960 it's like, you speak for the firm, right? 233 00:10:31,960 --> 00:10:32,720 Or you. Kind of. 234 00:10:32,720 --> 00:10:36,040 I mean the McKenzie model's much more pyramidal and like command 235 00:10:36,040 --> 00:10:38,040 and control. You're improved at this top, but 236 00:10:38,040 --> 00:10:41,280 you get to speak you you set up a way that sort of your youngest 237 00:10:41,280 --> 00:10:43,680 people can sort of say the firm says blah blah. 238 00:10:43,680 --> 00:10:46,280 Blah, I guess, but those people are are parroting the firm's 239 00:10:46,280 --> 00:10:48,760 talking points, right? No one's hiring a 25 year old. 240 00:10:48,760 --> 00:10:51,160 No one's hiring McKenzie to get 25 year old coming in and 241 00:10:51,160 --> 00:10:53,080 telling you what you should do about your business strategy. 242 00:10:53,400 --> 00:10:55,800 You're hiring McKinsey because they ostensibly have this 243 00:10:56,120 --> 00:10:58,760 centralized expertise and they've got a practice around 244 00:10:58,760 --> 00:10:59,720 your thing. You're a telco. 245 00:10:59,720 --> 00:11:02,520 You're hiring someone from their telco practice to come in and 246 00:11:02,520 --> 00:11:05,000 they've got best practices and there's a lot of different ways 247 00:11:05,000 --> 00:11:06,560 to interpret. What you're hiring because the 248 00:11:06,560 --> 00:11:09,400 partner has inside information then everybody else is slowing 249 00:11:09,440 --> 00:11:13,160 down dresses it up in sort of process and it's like I know the 250 00:11:13,200 --> 00:11:15,440 answer we need to get to you like explain why we. 251 00:11:15,440 --> 00:11:18,680 There's a lot of different mental models of what consult, 252 00:11:18,680 --> 00:11:21,440 what job to be done consulting actually does. 253 00:11:21,640 --> 00:11:24,280 There's like the the like one that they'll advertise, which is 254 00:11:24,400 --> 00:11:26,920 we're the strategic advisors. We're here to provide our 255 00:11:27,040 --> 00:11:30,360 insider business insight and business expertise to help our 256 00:11:30,360 --> 00:11:32,840 partners make better decisions. Like, OK, yeah. 257 00:11:33,240 --> 00:11:35,160 But like there's different mental, there's different like 258 00:11:35,160 --> 00:11:36,720 sort of different versions of this. 259 00:11:36,720 --> 00:11:39,200 There's one that's like they work with kind of everyone and 260 00:11:39,200 --> 00:11:41,480 yeah, they teams don't talk to each other, but they're all kind 261 00:11:41,480 --> 00:11:43,360 of gets distilled into best practices. 262 00:11:43,360 --> 00:11:46,800 And, you know, it's kind of like how you can go get make sure if 263 00:11:46,800 --> 00:11:49,040 you're an executive, you're doing the right things. 264 00:11:49,360 --> 00:11:52,160 The other version of it and the version I saw in my brief stint 265 00:11:52,160 --> 00:11:55,600 in management consulting before Palantir was we were hired one 266 00:11:55,600 --> 00:12:00,280 time onto a project where we came to learn there was another 267 00:12:00,280 --> 00:12:03,520 consulting team from another firm working for another one of 268 00:12:03,520 --> 00:12:06,760 the VPS of the company on effectively the same problem. 269 00:12:07,320 --> 00:12:10,480 And these two VPS both had, they were like fighting about what to 270 00:12:10,480 --> 00:12:12,280 do. And they both hired consulting 271 00:12:12,280 --> 00:12:17,120 firms. And we were basically told, this 272 00:12:17,120 --> 00:12:20,640 is my theory from the VP, like I need you guys to build a deck, 273 00:12:20,640 --> 00:12:23,680 basically build a deck like a slide deck to back that up. 274 00:12:24,280 --> 00:12:26,760 And then we came to learn there was another VP who had told 275 00:12:26,760 --> 00:12:28,840 their firm that. And it was like we were both 276 00:12:28,840 --> 00:12:33,880 like the proxy army for these warring warlords, like these 277 00:12:33,880 --> 00:12:36,000 factions. And it was very weird and it was 278 00:12:36,000 --> 00:12:37,120 kind of like, what are we doing here? 279 00:12:37,120 --> 00:12:38,720 And like it. Says something about like 280 00:12:38,720 --> 00:12:41,880 intelligence. It's in the world of models, you 281 00:12:41,880 --> 00:12:43,280 know? Yeah, it's just like you're just 282 00:12:43,280 --> 00:12:46,320 accumulating your argument when really the the argument is not 283 00:12:46,320 --> 00:12:48,600 about the reason. So, so you can kind of, I 284 00:12:48,640 --> 00:12:51,400 actually thought about that more subsequently and I'm like, there 285 00:12:51,400 --> 00:12:53,640 is something kind of pure about it, which is like it's a war, 286 00:12:53,640 --> 00:12:57,680 it's a battle of ideas and you know, but I don't know. 287 00:12:57,680 --> 00:13:01,240 Anyway, the at the whole point is that pound here we were going 288 00:13:01,240 --> 00:13:05,320 in and you know, we would get attached to these problems and 289 00:13:05,320 --> 00:13:07,440 then try to work backwards to like, well, what's the product 290 00:13:07,440 --> 00:13:09,680 that could solve this? And sometimes it was kind of a 291 00:13:09,680 --> 00:13:11,720 hacky thing, like we just threw together this dashboard that 292 00:13:11,720 --> 00:13:13,480 lets you see this joint data set we have. 293 00:13:13,480 --> 00:13:15,200 So now you can correlate these two things. 294 00:13:16,880 --> 00:13:19,920 But but what actually wound up happening in mid twenty 10s is 295 00:13:19,920 --> 00:13:22,160 we had a lot of cases where we were coming into these 296 00:13:22,160 --> 00:13:25,480 commercial companies and they wanted some like higher order 297 00:13:25,480 --> 00:13:26,720 thing. They wanted like, well, we want 298 00:13:26,720 --> 00:13:28,280 to see an analysis about that, Sir. 299 00:13:28,280 --> 00:13:30,960 We want a machine learning model that shows us the correlation 300 00:13:30,960 --> 00:13:34,520 between that Sir, we want to see whatever and then we would have 301 00:13:34,520 --> 00:13:36,880 to go build and and the four deployed engineers would have to 302 00:13:36,880 --> 00:13:39,280 go build and kind of hack up a lot of infrastructure behind the 303 00:13:39,280 --> 00:13:41,320 scenes to be able to try to pull all that data together. 304 00:13:41,880 --> 00:13:43,120 And then you turn that into a product. 305 00:13:43,120 --> 00:13:44,080 Then we turn that into a product. 306 00:13:44,080 --> 00:13:47,240 So there's a team, the deployment in Europe that 307 00:13:47,240 --> 00:13:49,760 famously kind of like started productizing this like well 308 00:13:49,760 --> 00:13:53,240 we're writing these same shape of spark job orchestration 309 00:13:53,240 --> 00:13:56,680 things over and over again. We should build a thing to help 310 00:13:56,680 --> 00:13:59,920 do that. And then that sort of started 311 00:13:59,920 --> 00:14:02,600 snowballing and within that deployment and then spread. 312 00:14:02,600 --> 00:14:04,200 And one of the really cool things about the forward 313 00:14:04,200 --> 00:14:06,240 deployed model at Palantir that I saw was it was almost like a 314 00:14:06,240 --> 00:14:09,280 community driven adoption. Like you would see things go 315 00:14:09,280 --> 00:14:12,480 viral where you'd have one deployment go and invent 316 00:14:12,480 --> 00:14:14,840 something and then another deployment would pick it up 317 00:14:14,840 --> 00:14:18,240 because it's on GitHub and it to the once we sort of had a core 318 00:14:18,240 --> 00:14:20,880 platform and it got, we got better at that. 319 00:14:21,240 --> 00:14:23,720 Like, oh, like your deployment built that thing. 320 00:14:23,720 --> 00:14:24,920 Cool. Like can I, you could just 321 00:14:24,920 --> 00:14:27,880 install it and it would work on your platform too sick. 322 00:14:27,880 --> 00:14:30,360 And then you, you know, it's open for PRS so you can be 323 00:14:30,520 --> 00:14:32,320 contributing code back. And then these things would gain 324 00:14:32,320 --> 00:14:35,200 momentum. And someone who started a 325 00:14:35,200 --> 00:14:39,320 project working as an FDE on a thing and they built this thing 326 00:14:39,320 --> 00:14:42,280 just to solve this customer, maybe six months later, they're 327 00:14:42,280 --> 00:14:44,560 basically on. They're basically a dev team now 328 00:14:44,560 --> 00:14:47,280 that's kind of delaminated from the deployment. 329 00:14:47,920 --> 00:14:50,360 And now we're like the dev team. So you got too good at this all 330 00:14:50,360 --> 00:14:53,800 right now you're. Yeah, you'd see the cycle. 331 00:14:53,800 --> 00:14:56,160 So there's a product some very close friends of mine built, 332 00:14:56,640 --> 00:15:01,320 they were over in the Middle East working with a customer 333 00:15:01,320 --> 00:15:04,560 there. And they built a product to be 334 00:15:04,560 --> 00:15:08,200 able to do this sort of drill down data analysis to solve a 335 00:15:08,200 --> 00:15:11,080 problem there and a very esoteric problem, signals 336 00:15:11,080 --> 00:15:13,960 intelligence problem. And then that product was sweet. 337 00:15:13,960 --> 00:15:17,040 And a lot of people, including my deployment, were like, that 338 00:15:17,040 --> 00:15:19,840 would be really useful. And so we kind of lobbied and 339 00:15:19,840 --> 00:15:22,160 got them to deploy it for us and it was great. 340 00:15:22,160 --> 00:15:24,440 And then it spread and spread and now it's like a super core 341 00:15:24,440 --> 00:15:26,240 part of the Foundry platform does. 342 00:15:26,480 --> 00:15:28,520 It have a name. Or yeah, it's called Contour, 343 00:15:29,320 --> 00:15:30,320 like every, like everything there. 344 00:15:30,320 --> 00:15:33,120 It went through multiple names. It's been named like 4, it was 345 00:15:33,120 --> 00:15:35,480 named 4 things. And there's, there's so many 346 00:15:35,480 --> 00:15:37,880 examples like that. And, and there's so many 347 00:15:37,880 --> 00:15:40,160 wonderful things about this, like contour is sick. 348 00:15:40,440 --> 00:15:42,080 And it was never on anyone's road map. 349 00:15:42,080 --> 00:15:45,320 It's just like 3 guys went and invented it because they needed 350 00:15:45,320 --> 00:15:48,880 it and it caught on and spread and you know, it was never on 351 00:15:48,880 --> 00:15:50,200 anyone. It was never on some central 352 00:15:50,200 --> 00:15:53,480 road map like in Q32016. We're going to go build this 353 00:15:53,480 --> 00:15:56,320 thing Now. The downside, the sort of 354 00:15:56,320 --> 00:15:59,880 invisible downside that's easy to ignore is there was also a 355 00:15:59,880 --> 00:16:02,440 ton of shit we built that went nowhere that was a complete 356 00:16:02,440 --> 00:16:04,560 waste of time. We had deployments where we were 357 00:16:04,560 --> 00:16:08,920 flying super expensive people, first class every week 358 00:16:08,920 --> 00:16:12,200 somewhere, you know, just just tons of time and opportunity 359 00:16:12,200 --> 00:16:15,320 cost and just pyres of money. Basically like customers were 360 00:16:15,320 --> 00:16:17,400 paying for it, right? Customers were paying for it, 361 00:16:17,400 --> 00:16:18,560 yeah. And they were kind of paying for 362 00:16:18,560 --> 00:16:20,680 the sort of service version of it in the short term. 363 00:16:20,680 --> 00:16:23,200 And there were customers. I actually met someone recently 364 00:16:23,200 --> 00:16:24,840 who was a customer of ours in that era. 365 00:16:25,560 --> 00:16:27,480 And she was, she kind of was like, yeah, we're. 366 00:16:27,640 --> 00:16:31,840 We felt pretty burned by you guys and I, I just think it's 367 00:16:31,840 --> 00:16:33,760 almost like this kind of necessary downside. 368 00:16:33,760 --> 00:16:37,520 I hate to be so glib about it, but like of having this high 369 00:16:37,520 --> 00:16:41,840 rate of innovation in the field, like, you know, people say fail 370 00:16:41,840 --> 00:16:44,680 fast, fail fast, move fast and break things like these, these 371 00:16:44,680 --> 00:16:48,080 ethos things in the valley. It's it's really representative 372 00:16:48,080 --> 00:16:50,560 of what we what anyone who's really done this well really 373 00:16:50,560 --> 00:16:54,440 knows, which is the reiteration and learning is everything. 374 00:16:54,960 --> 00:16:57,080 And one of the big problems in enterprise software is a lot of 375 00:16:57,080 --> 00:16:59,880 enterprise software is built by big lumbering teams who are 376 00:16:59,880 --> 00:17:05,160 working from 10:00 to 3:45 in air conditioned offices in the 377 00:17:05,160 --> 00:17:09,200 valley with ample ping pong breaks and what you know, blah, 378 00:17:09,200 --> 00:17:12,079 blah, blah, blah, blah, blah. Working off of these long multi 379 00:17:12,079 --> 00:17:14,760 quarter Rd. Maps and they're very sparsely 380 00:17:14,760 --> 00:17:17,760 talking to customers and you know you're what you're going to 381 00:17:17,760 --> 00:17:20,200 get from that is you're going to get consistency, you know you're 382 00:17:20,200 --> 00:17:22,520 going to get predictability, you're going to get all these 383 00:17:22,520 --> 00:17:25,359 things that that companies value as they get bigger. 384 00:17:25,760 --> 00:17:27,640 You're not going to get emerged. But you're not going to get 385 00:17:27,640 --> 00:17:28,160 that. Innovation. 386 00:17:28,160 --> 00:17:30,720 Sometimes here it like we didn't really figure it out. 387 00:17:30,720 --> 00:17:33,520 Other times it's like it's so valuable, we're just spread it 388 00:17:33,520 --> 00:17:35,600 to the rest of government. Yeah, these structures wind up 389 00:17:35,600 --> 00:17:40,200 being almost designed to squash like high variance innovation, 390 00:17:40,200 --> 00:17:43,800 like what all process does. The whole point of a process is 391 00:17:43,800 --> 00:17:47,120 to reduce variance. So you're you're an evangelist 392 00:17:47,120 --> 00:17:51,080 and defender for the forward deployed engineer, but your own 393 00:17:51,080 --> 00:17:53,280 company doesn't do that. Like what? 394 00:17:53,680 --> 00:17:57,640 What is your heuristic for what company should use a forward 395 00:17:57,640 --> 00:18:00,000 deployed engineer? And then why did you decide yes, 396 00:18:00,000 --> 00:18:01,440 we have a lot of FD not to former? 397 00:18:01,440 --> 00:18:03,840 FD ES at hex. So what you see is a lot of 398 00:18:03,840 --> 00:18:07,440 start-ups now adopting the FD model where they're like we're, 399 00:18:07,440 --> 00:18:09,280 we're, we have 4 deployed engineers. 400 00:18:09,920 --> 00:18:13,640 Well, I and I, when I, when I critique this, it's not like to 401 00:18:13,640 --> 00:18:17,800 gatekeep the title, whatever. Like it's really like, do you 402 00:18:17,800 --> 00:18:20,920 understand what worked? What, why this works for 403 00:18:20,920 --> 00:18:23,720 Palantir? Because I think a lot of people 404 00:18:23,720 --> 00:18:26,520 are cargo colting. They're saying, oh, Palantir did 405 00:18:26,520 --> 00:18:28,640 this and look at their revenue multiple and look at their 406 00:18:28,640 --> 00:18:30,160 success. If we do forward deployed 407 00:18:30,160 --> 00:18:33,800 engineering, we'll be as successful and they kind of go 408 00:18:33,800 --> 00:18:36,160 through the motions and then they're not getting the same 409 00:18:36,160 --> 00:18:37,520 results. And they're like, why? 410 00:18:38,200 --> 00:18:40,800 Well, you don't under really understand the physics of it. 411 00:18:41,240 --> 00:18:44,160 And from us when we were starting the company, you know, 412 00:18:44,160 --> 00:18:46,640 we'd obviously lived that, but we were like, we want actually 413 00:18:46,640 --> 00:18:47,640 want to kind of go the opposite way. 414 00:18:47,640 --> 00:18:50,440 We want to build 1 consistent piece of software that we can 415 00:18:50,440 --> 00:18:54,480 deliver in scale and. Super out of fashion right now. 416 00:18:54,520 --> 00:18:55,880 Super out of. Fashion right now, I know. 417 00:18:56,160 --> 00:18:59,080 But the raising rounds as an investor, but somehow, but not 418 00:18:59,080 --> 00:19:01,400 on some of the narratives. But but, but no. 419 00:19:01,400 --> 00:19:03,760 But it's, it's, there's a synthesis here, right? 420 00:19:04,040 --> 00:19:08,120 Like what we do is we just talk to customers. 421 00:19:08,120 --> 00:19:10,120 I'm in New York right now. I'm visiting customers. 422 00:19:10,400 --> 00:19:12,880 I'm bouncing all over town the next few days just visiting 423 00:19:12,880 --> 00:19:15,600 customers, getting up close. And I'm doing my best not to 424 00:19:15,600 --> 00:19:18,080 just meet with them in a conference room, but like, I 425 00:19:18,080 --> 00:19:20,360 want to go by someone's desk. I want to be like, great, what 426 00:19:20,360 --> 00:19:21,320 are you up to? What are you working on? 427 00:19:21,320 --> 00:19:23,040 Can you show me hex? Can you show me what you're 428 00:19:23,040 --> 00:19:25,560 working on? Like go get up close. 429 00:19:25,560 --> 00:19:27,920 I'm I'm bringing individual, I'm not bringing our sales, my sales 430 00:19:27,920 --> 00:19:29,520 people on those visits. I'm bringing the engineers and 431 00:19:29,520 --> 00:19:31,040 designers. I'm like, I want to go see this 432 00:19:31,040 --> 00:19:35,400 stuff And I try to get our whole team doing that and go get in 433 00:19:35,400 --> 00:19:37,320 front of customers, really understand what they're doing, 434 00:19:37,320 --> 00:19:39,480 really understand what they're asking for, really understand 435 00:19:39,480 --> 00:19:41,800 what they want and what they're using as an alternative. 436 00:19:41,800 --> 00:19:45,040 Like go do a great job at that and and talk to customers. 437 00:19:45,040 --> 00:19:47,320 And if we actually have a problem at Hex, it's like, I 438 00:19:47,320 --> 00:19:49,920 think some days it's like, I worry our EPD team is our 439 00:19:49,920 --> 00:19:52,280 engineer product and design teams are talking to customers 440 00:19:52,280 --> 00:19:54,040 too much. Like it's like, guys, at some 441 00:19:54,040 --> 00:19:54,920 point we got to go write the code. 442 00:19:54,920 --> 00:19:57,760 You know, it's like we talk, we talk to customers a lot. 443 00:19:58,040 --> 00:20:00,400 And some of it's just you're a smaller company and so you can't 444 00:20:00,400 --> 00:20:02,640 just have everybody. Yeah, it's a. 445 00:20:02,640 --> 00:20:04,360 Cultural, but it's a cultural thing. 446 00:20:04,360 --> 00:20:08,400 It's like, I, I think it's really important to have people 447 00:20:08,760 --> 00:20:10,400 really build empathy for customers. 448 00:20:10,400 --> 00:20:13,240 I mean I I don't I think the worst engineering in the world 449 00:20:13,240 --> 00:20:15,960 is done via ticket. Like if you wanted to have some 450 00:20:15,960 --> 00:20:17,240 tickets to like manage your work. 451 00:20:17,240 --> 00:20:19,440 Yeah, I mean it's a core Y combinator. 452 00:20:19,480 --> 00:20:21,680 You know, principle of building companies is like what? 453 00:20:21,840 --> 00:20:23,840 Build something people want know your customer. 454 00:20:23,840 --> 00:20:26,440 You know that sort of sent. But a lot of most people don't 455 00:20:26,440 --> 00:20:27,200 do that. They don't do that. 456 00:20:27,200 --> 00:20:28,240 They said they have the road map but. 457 00:20:28,240 --> 00:20:31,000 What what start-ups do you think or smaller companies, non 458 00:20:31,000 --> 00:20:34,440 palantir companies are doing for deployed engineers in a smart 459 00:20:34,440 --> 00:20:35,880 way? The only, I mean, the only one I 460 00:20:35,880 --> 00:20:39,000 know who's doing at the Palantir version, which is basically, we 461 00:20:39,000 --> 00:20:42,280 don't really know what to build. We're just going to go in bed 462 00:20:42,280 --> 00:20:45,400 with customers, get them to pay us some services thing to cover 463 00:20:45,400 --> 00:20:48,240 the time maybe and and have some exchange of value. 464 00:20:48,520 --> 00:20:50,760 And we'll just build the platform depending on what we 465 00:20:50,760 --> 00:20:53,640 learn. Is my friend Arjun at Distill 466 00:20:53,880 --> 00:20:59,040 Distill with AY he he's. I think there may be other 467 00:20:59,040 --> 00:21:01,480 companies now doing some version of this but he's the one who I 468 00:21:01,480 --> 00:21:04,000 know is doing it the most pure. Is he super charismatic? 469 00:21:05,040 --> 00:21:07,880 I think he's very charismatic. And not like what's just funny, 470 00:21:07,880 --> 00:21:10,240 you refer to Alex Carp earlier as Doctor Carp. 471 00:21:10,280 --> 00:21:12,520 He's he's like a philosophy PhD. Yeah, right. 472 00:21:12,760 --> 00:21:16,920 Like, like not there uniquely has to sort of like, you know, 473 00:21:16,920 --> 00:21:19,720 we we're like Wizard of Oz, like we're gonna do a magic thing. 474 00:21:19,720 --> 00:21:24,080 I'm like, can anyone else really sell that besides that company, 475 00:21:24,080 --> 00:21:25,440 you know, in the sort of he's just. 476 00:21:25,440 --> 00:21:27,240 Called him Doctor Carp. He's just he's doctor. 477 00:21:27,240 --> 00:21:28,840 It's like when you it's like when you grow up in your 478 00:21:28,840 --> 00:21:33,040 neighbors like Mr. Mr. Smith, you know to you and like later 479 00:21:33,040 --> 00:21:35,400 in life you run into them again. You still call him Mr. Smith, 480 00:21:35,400 --> 00:21:37,160 this is. Funny you guys how you're like 481 00:21:37,160 --> 00:21:38,480 I'm. Jim, I'm Jim now, son. 482 00:21:38,480 --> 00:21:40,120 It's all right. He talks about it like, you 483 00:21:40,120 --> 00:21:42,280 know, it's a culture of, you know, people will tell him like 484 00:21:42,280 --> 00:21:44,320 he's totally wrong or whatever, but that's just a very 485 00:21:44,320 --> 00:21:46,360 deferential way to refer to him. I don't know. 486 00:21:46,400 --> 00:21:49,760 Yeah, but it was, it is a very decent, you know, they're very 487 00:21:49,760 --> 00:21:53,280 open, very transparent, very best idea wins. 488 00:21:53,680 --> 00:21:56,640 Not a lot of job titleature. I mean, I had the same job title 489 00:21:56,640 --> 00:21:59,240 all five years I was there. I went, I had people reporting 490 00:21:59,240 --> 00:22:00,800 to me. I was doing IC stuff, I was 491 00:22:00,800 --> 00:22:03,360 doing big lead stuff. It didn't matter. 492 00:22:03,360 --> 00:22:06,120 Like in when you're in that environment, you kind of forget 493 00:22:06,120 --> 00:22:08,480 about job titles for a while. You forget about there's 494 00:22:08,480 --> 00:22:10,280 different, you squeeze the balloon, the problems emerge 495 00:22:10,280 --> 00:22:11,800 elsewhere. Like there's going to be shadow 496 00:22:11,800 --> 00:22:14,400 hierarchies and stuff. Every cultural thing has 497 00:22:14,400 --> 00:22:17,680 trade-offs, but I I thought the culture there really was 498 00:22:17,680 --> 00:22:19,200 designed. It's, it's almost like it, it, 499 00:22:19,280 --> 00:22:24,480 it, it was very sharply designed around getting a very specific 500 00:22:24,480 --> 00:22:28,400 thing, which is maximum pace of iteration and learning. 501 00:22:30,720 --> 00:22:34,240 And that meant there's all these negative trade-offs. 502 00:22:34,480 --> 00:22:36,840 But culturally I think we always like acknowledge them and 503 00:22:36,840 --> 00:22:39,120 accepted them. And there was a time, I remember 504 00:22:39,120 --> 00:22:41,680 we had a period when I was there where a lot of people have left 505 00:22:41,680 --> 00:22:44,000 because they felt like there wasn't a growth path for them 506 00:22:44,000 --> 00:22:47,680 and because we didn't have like a job title ladder to climb like 507 00:22:47,680 --> 00:22:49,840 a lot of people are used. To Was it hard to raise money 508 00:22:49,840 --> 00:22:52,560 without a clear title where people knew where it's? 509 00:22:52,560 --> 00:22:55,000 Hard for me to raise money. Or just I would imagine going 510 00:22:55,000 --> 00:22:57,320 off and starting a company you want to be able to say I was 511 00:22:57,320 --> 00:22:59,960 important here or somewhere, which is sort of a vague. 512 00:22:59,960 --> 00:23:02,080 It was actually interesting because I did another thing in 513 00:23:02,080 --> 00:23:05,320 between Palantir and Hex, I went to a relational biotech company 514 00:23:05,320 --> 00:23:06,320 here. Yeah, I was just called Trial 515 00:23:06,320 --> 00:23:07,520 Spark at the time, not confirmation. 516 00:23:07,520 --> 00:23:10,960 I remember interviewing and I was like, what do I, what do I 517 00:23:10,960 --> 00:23:12,600 say? I do like I'm a deployment 518 00:23:12,600 --> 00:23:13,880 strategist. What's that mean? 519 00:23:13,920 --> 00:23:17,040 Like, and I think people who are hiring from Palantir kind of 520 00:23:17,040 --> 00:23:20,920 knew they were like, OK, we kind of knew that that was a thing 521 00:23:22,720 --> 00:23:24,480 when I was raising money. It wasn't a big I don't that 522 00:23:24,520 --> 00:23:25,680 didn't really come up. It was just the. 523 00:23:25,680 --> 00:23:28,400 Product just sort of the. It was just that we clearly had 524 00:23:28,400 --> 00:23:29,840 a sense of what we were doing and what we wanted. 525 00:23:29,840 --> 00:23:32,600 To do but say what Hex does just we don't even think about the 526 00:23:32,600 --> 00:23:33,840 company, but just so people know where. 527 00:23:33,880 --> 00:23:35,760 You're coming. So we're building AI data 528 00:23:35,760 --> 00:23:39,240 analytic software like sometimes people call us cursor for data 529 00:23:39,240 --> 00:23:43,440 or things like that. It's basically you can use 530 00:23:43,440 --> 00:23:46,000 natural language to go ask any. Other questions just list a 531 00:23:46,000 --> 00:23:48,880 bunch of highly valued companies like Cursor for data, Anthropic 532 00:23:48,880 --> 00:23:50,360 for. We were opening up for one data. 533 00:23:50,480 --> 00:23:52,640 We were called. Bigma, Bigma for data, it's 534 00:23:52,680 --> 00:23:55,000 like, yeah, because the first, the first arc of the company 535 00:23:55,000 --> 00:23:57,880 really was like, there's all these local fragmented data 536 00:23:57,880 --> 00:23:59,720 analysis things. We've spent all this time 537 00:23:59,720 --> 00:24:01,480 bringing your data together and you're just putting dashboards 538 00:24:01,480 --> 00:24:03,160 on top. You know, we wanted to build 539 00:24:03,160 --> 00:24:07,600 this cloud based front end for all of your data work and it was 540 00:24:07,600 --> 00:24:09,360 very similar to what Figma had done when we started the 541 00:24:09,360 --> 00:24:11,240 company. Figma was, you know, on its way 542 00:24:12,200 --> 00:24:15,080 north and was really taking off and sort of an inspiration of 543 00:24:15,080 --> 00:24:17,680 like, oh, you can take these local fragmented workflows, 544 00:24:17,680 --> 00:24:21,280 bring them to the cloud, bring make them collaborative and in 545 00:24:21,280 --> 00:24:24,240 the process of doing that, bring more people in as participants. 546 00:24:24,600 --> 00:24:28,200 Those are really the initial thesis of hex and then a couple 547 00:24:28,200 --> 00:24:31,720 years end of the journey, like GPT 3 came out and then ChatGPT 548 00:24:31,720 --> 00:24:34,360 came out and this was a thing we really got entranced by. 549 00:24:34,800 --> 00:24:38,800 So the the second-half of the company or more than half now 550 00:24:38,800 --> 00:24:42,040 the company has been figuring out how to really apply AI and 551 00:24:42,040 --> 00:24:45,120 now agents to work for a data analysis, which is the Holy 552 00:24:45,120 --> 00:24:46,640 Grail. Like the Holy Grail. 553 00:24:46,640 --> 00:24:48,960 The reason people buy data tools, ostensibly invest 554 00:24:48,960 --> 00:24:51,240 billions and billions of dollars over your data infrastructure is 555 00:24:51,520 --> 00:24:53,360 because you want to know things and you want to make better 556 00:24:53,360 --> 00:24:55,640 decisions. And we make that really easy and 557 00:24:55,640 --> 00:24:57,280 we do a very different set of things. 558 00:24:57,280 --> 00:25:00,320 Well, then what Palantir did, we don't do like data integration 559 00:25:00,320 --> 00:25:02,520 and infrastructure stuff. We're very much like the app and 560 00:25:02,520 --> 00:25:04,560 collaboration layer where. Where do you say relative to 561 00:25:04,760 --> 00:25:06,800 business intelligence? Yeah, we are. 562 00:25:06,800 --> 00:25:09,360 We think of ourselves as reinventing that like we are. 563 00:25:09,360 --> 00:25:10,880 What? People don't like that space or 564 00:25:10,880 --> 00:25:12,840 what's the like? You don't use that term. 565 00:25:12,840 --> 00:25:14,480 I didn't, yeah. I didn't want to use that term 566 00:25:14,480 --> 00:25:17,760 because it had so much baggage. Like when people think for a 567 00:25:17,760 --> 00:25:20,840 long time, when people think BI, they're like, OK, well, I think 568 00:25:20,840 --> 00:25:24,000 of all the features that Tableau has built for 20 years and I 569 00:25:24,000 --> 00:25:25,840 think about dashboards and I want you to do that. 570 00:25:26,600 --> 00:25:30,040 And we are actually originally were very insistent on like we 571 00:25:30,040 --> 00:25:32,520 actually think that the old way of thinking about BI is like 572 00:25:32,520 --> 00:25:35,560 super low value. We think dashboards is going to 573 00:25:35,560 --> 00:25:38,040 raise more questions than answers is something I've said a 574 00:25:38,040 --> 00:25:40,040 lot. And like the most of the 575 00:25:40,040 --> 00:25:42,480 valuable data work is not happening happening in these 576 00:25:42,480 --> 00:25:44,960 dashboards. And instead it's people are 577 00:25:44,960 --> 00:25:47,640 trying to do it in this melange of other tools. 578 00:25:47,640 --> 00:25:50,760 Jupiter notebooks and SQL queries and spreadsheets and 579 00:25:50,760 --> 00:25:56,000 screenshots of a chart pasted into APDF of a deck attached to 580 00:25:56,000 --> 00:25:57,840 an e-mail you're. More rooted in like the role 581 00:25:57,840 --> 00:26:00,680 like you're hiring these smart data analysts and we want to. 582 00:26:01,160 --> 00:26:05,280 Originally start, our initial sort of beachhead landing thing 583 00:26:05,280 --> 00:26:07,200 was like we're going to come in and we're going to revolutionize 584 00:26:07,640 --> 00:26:09,440 your way. Your data team works right and 585 00:26:09,440 --> 00:26:11,600 very similar to Figma coming in and we want to revolutionize. 586 00:26:11,600 --> 00:26:14,560 Now you're like you don't need to hire them or how do you? 587 00:26:14,560 --> 00:26:19,080 Every AI embracing company has its trade off between supporting 588 00:26:19,080 --> 00:26:20,960 the role versus saying, oh, we're helping. 589 00:26:21,040 --> 00:26:22,720 I think we're. Helping to reinvent and evolve 590 00:26:22,720 --> 00:26:24,560 it. And we have a great data team. 591 00:26:24,560 --> 00:26:25,560 Hex. It's almost like over 592 00:26:25,560 --> 00:26:30,280 provisioned in the sense of we just have really wonderfully and 593 00:26:30,280 --> 00:26:33,520 talented people on it, but also hired people that have been 594 00:26:33,520 --> 00:26:36,800 thought leaders and writers in our space for a while who are 595 00:26:37,320 --> 00:26:39,800 amazing collaborators for us to build the product. 596 00:26:39,800 --> 00:26:42,960 But also collaborators just thinking about like what is what 597 00:26:42,960 --> 00:26:45,000 are these roles becoming? And it's interesting to see our 598 00:26:45,000 --> 00:26:47,680 own employees kind of disrupting their own job a little bit. 599 00:26:47,680 --> 00:26:50,080 And it's probably similar to what it feels like to be an 600 00:26:50,080 --> 00:26:52,360 engineer or cursor or something like you're trying to reinvent 601 00:26:52,360 --> 00:26:55,400 the way your job works. And so you know, where we see 602 00:26:55,400 --> 00:26:58,400 ourselves as fellow travellers with that data audience of like 603 00:26:58,600 --> 00:27:01,600 how we're helping reinvent the way their job works and what 604 00:27:01,600 --> 00:27:03,240 that looks like and what it looks like to fulfill the 605 00:27:03,240 --> 00:27:05,520 mission they've always wanted for their organizations, which 606 00:27:05,520 --> 00:27:08,080 is you want data to be useful and help solve problems. 607 00:27:08,320 --> 00:27:11,600 And now with with AI, you know, the the fastest growing part of 608 00:27:11,600 --> 00:27:14,640 our user base, of course, is all these other people in these 609 00:27:14,640 --> 00:27:18,800 companies that are now able to use data in a way they weren't 610 00:27:18,800 --> 00:27:20,200 able to before. And in that way, we are 611 00:27:20,200 --> 00:27:24,040 fulfilling what BI want, always wanted and purported to be and 612 00:27:24,040 --> 00:27:26,120 what people thought they were buying with their billions of 613 00:27:26,120 --> 00:27:29,040 dollars of BI spend, which was we want to make everyone 614 00:27:29,040 --> 00:27:31,240 data-driven. Well, you got a lot of 615 00:27:31,240 --> 00:27:32,960 dashboards. Are you feeling data-driven? 616 00:27:32,960 --> 00:27:35,040 Are you able, you know, is everyone able to ask their 617 00:27:35,040 --> 00:27:36,240 questions? Because if you can't interrogate 618 00:27:36,240 --> 00:27:37,880 the dashboard, you don't know it's limited. 619 00:27:37,880 --> 00:27:39,680 They're really good. Like dashboards are fine people. 620 00:27:39,680 --> 00:27:42,080 There's this big discourse now. Dash dashboards are dead. 621 00:27:42,280 --> 00:27:44,560 Everything has to be dead or broken or, you know, whatever. 622 00:27:46,200 --> 00:27:49,200 Dashboards are dead. I'm like, dashboards are fine. 623 00:27:49,720 --> 00:27:52,600 They're fine, but they've always been fine. 624 00:27:52,600 --> 00:27:53,680 Like the? Extent they're dead, I see 625 00:27:53,920 --> 00:27:57,080 people want to ask a question directly of data in dashboards, 626 00:27:57,080 --> 00:27:58,560 which is. The same as when we started the 627 00:27:58,560 --> 00:28:00,840 company. It's like dashboards are great 628 00:28:00,840 --> 00:28:03,560 for seeing what happened, this KPI, blah, blah, blah, whatever. 629 00:28:03,560 --> 00:28:05,200 It's a collection of these charts. 630 00:28:05,600 --> 00:28:09,320 Great, fine. But often what you look at is 631 00:28:09,320 --> 00:28:11,640 you look at that chart and you go, OK, well I want to ask a 632 00:28:11,640 --> 00:28:13,120 next question. Why, why did that happen? 633 00:28:13,120 --> 00:28:15,440 I want to drill down on this and there are other times something 634 00:28:15,440 --> 00:28:18,000 like that has happened. That's what we built Hex to 635 00:28:18,000 --> 00:28:22,120 really excel at. And now it like the architecture 636 00:28:22,120 --> 00:28:23,920 and a lot of the things we built, we kind of feel like we 637 00:28:23,960 --> 00:28:27,960 had right place, right time because the way we even 638 00:28:27,960 --> 00:28:31,560 structured the product is really conducive to these agent work 639 00:28:31,560 --> 00:28:34,040 flows, which is which are about depth. 640 00:28:34,040 --> 00:28:36,320 A lot of times, like the magic of these things is you can ask a 641 00:28:36,320 --> 00:28:38,640 first question, get an answer, and then you can ask follow-ups 642 00:28:38,640 --> 00:28:41,280 and it can go now and drill in and have multiple different tool 643 00:28:41,280 --> 00:28:44,520 calls and paths is exploring. And all these things we built, 644 00:28:44,640 --> 00:28:47,120 even going back to the very beginning that we didn't know 645 00:28:47,120 --> 00:28:50,000 were going to be useful because we have magic robots that can 646 00:28:50,000 --> 00:28:53,360 talk to us now. It's all very useful now. 647 00:28:53,360 --> 00:28:55,760 Now useful for way more people, which is really really cool. 648 00:28:57,480 --> 00:29:00,200 Are you using cloud or what is the intelligence sort of? 649 00:29:00,360 --> 00:29:03,640 Behind this, we use cloud and the GPT models and it's very 650 00:29:03,640 --> 00:29:05,080 interesting. We have good relationships with 651 00:29:05,080 --> 00:29:08,800 both companies. We spend time with their 652 00:29:08,800 --> 00:29:11,520 research teams and who's. Doing better right now. 653 00:29:12,600 --> 00:29:15,600 They're both doing great. I think the GPT 5.4 models which 654 00:29:15,600 --> 00:29:17,600 are the latest ones to come out are really fantastic. 655 00:29:17,600 --> 00:29:20,040 And we have a quote, my Co founder Caitlin, who I think 656 00:29:20,040 --> 00:29:23,440 you've met has a quote in their launch blog posts summering up 657 00:29:23,440 --> 00:29:26,160 our findings. But they really, really good and 658 00:29:26,560 --> 00:29:28,760 getting better. I think what we're seeing is 659 00:29:28,760 --> 00:29:32,280 these models, the main focus of the labs right now appear to be 660 00:29:32,960 --> 00:29:37,520 kind of hill climbing the models on coding tasks, which is you 661 00:29:37,520 --> 00:29:39,560 can kind of squint your eyes and look at hacks and be like, it's 662 00:29:39,560 --> 00:29:41,160 like coding. It's like you guys write SQL and 663 00:29:41,160 --> 00:29:45,000 Python And Dataviz. And the improvements on those 664 00:29:45,000 --> 00:29:48,680 models of coding tasks does make our performance for our domain 665 00:29:49,200 --> 00:29:52,480 better incrementally. But but surprisingly, actually 666 00:29:52,480 --> 00:29:55,640 we even saw with, I won't say which one, but one of the latest 667 00:29:55,640 --> 00:29:57,480 new model releases from one of the labs, it was actually a 668 00:29:57,480 --> 00:30:00,040 regression for the evals we have. 669 00:30:00,040 --> 00:30:03,320 We have a really extensive set of really rigorous data 670 00:30:03,320 --> 00:30:06,120 analytics evals that are not like the naive ones, like how 671 00:30:06,120 --> 00:30:09,000 many widgets did we saw last quarter, but like really brutal, 672 00:30:09,320 --> 00:30:13,000 like the real world shit that people ask of data. 673 00:30:13,600 --> 00:30:16,920 And it's interesting to see the models sometimes even regress 674 00:30:17,240 --> 00:30:18,920 cuz clearly they've been trying to be like hill climbed on 675 00:30:18,920 --> 00:30:20,600 something else. And one of the big problems is 676 00:30:20,600 --> 00:30:23,400 in data analysis, it's non verifiable and there's actually 677 00:30:23,400 --> 00:30:25,800 different ways to answer a question and it's it's. 678 00:30:26,400 --> 00:30:29,760 Right coding, has this sort of code worked it built this thing 679 00:30:29,760 --> 00:30:33,680 you can sort of right whereas the sort of analysis. 680 00:30:34,000 --> 00:30:36,280 Yeah, it's a little squishier. And so this is something we 681 00:30:36,280 --> 00:30:39,320 work, we try to This is why we spend time at the labs is like 682 00:30:39,320 --> 00:30:42,400 trying to like help figure out like how, how can we make the 683 00:30:42,400 --> 00:30:44,280 bottles better for this? Should we be RL in our own 684 00:30:44,280 --> 00:30:45,720 models? I know there's a lot of like 685 00:30:45,920 --> 00:30:47,480 even conflicting opinions internally. 686 00:30:47,480 --> 00:30:49,360 Are you spending money on your own models? 687 00:30:49,360 --> 00:30:52,200 We do we run some of our own inference for some specialized 688 00:30:52,200 --> 00:30:54,640 tasks. The main we are using the like 689 00:30:54,640 --> 00:30:57,880 GPT and clawed sort of state-of-the-art models for like 690 00:30:57,880 --> 00:31:00,640 our main agent backbone. But we, we see some interesting 691 00:31:00,640 --> 00:31:03,240 opportunities and it's not impossible that the lab, those 692 00:31:03,840 --> 00:31:08,560 anthropic and open AI even allow they, they used to sort of in 693 00:31:08,560 --> 00:31:10,880 the older era had a lot more fine tuning tools. 694 00:31:10,880 --> 00:31:13,280 And I think they may come back in some places too, where they 695 00:31:13,600 --> 00:31:16,480 sort of allow you to do these RL regimes on top of their base. 696 00:31:16,720 --> 00:31:19,960 And where are you on sort of agent mania, you know, are you 697 00:31:19,960 --> 00:31:21,520 building? Are are you going to be like 698 00:31:21,520 --> 00:31:24,920 sell, you know, are agents as representative as humans in your 699 00:31:24,920 --> 00:31:26,440 product? You're going to be selling seats 700 00:31:26,440 --> 00:31:28,920 to agents or you think that's sort of out of control? 701 00:31:28,920 --> 00:31:31,360 Or I, I think that's, I think it's probably overshot a little 702 00:31:31,360 --> 00:31:34,720 bit. I mean, we've talked I, you 703 00:31:34,720 --> 00:31:36,720 know, with the pricing thing is interesting. 704 00:31:37,920 --> 00:31:39,480 You're selling seats. We sell seats. 705 00:31:40,360 --> 00:31:43,920 Another not cruel thing. We sell seats usage. 706 00:31:43,920 --> 00:31:45,400 Pricing right now, what's going on? 707 00:31:45,400 --> 00:31:47,960 We are, we're adding, you know, usage on top because one thing 708 00:31:47,960 --> 00:31:50,640 that's crazy is our weekly actives chart and our messages 709 00:31:50,640 --> 00:31:53,520 per week chart is like straight vertical now. 710 00:31:53,520 --> 00:31:55,760 It's like gone fully parabolic. Like the product is really 711 00:31:55,760 --> 00:31:57,200 working. The agents are really good. 712 00:31:57,520 --> 00:31:59,080 People are loving them and using them. 713 00:31:59,080 --> 00:32:00,400 Yeah. They're costing you more. 714 00:32:00,440 --> 00:32:04,160 Fortunate part is our cost chart looks the same and if you're if 715 00:32:04,160 --> 00:32:06,680 you're a if you're a company today that has working agents, 716 00:32:06,720 --> 00:32:08,800 these things are expensive to run and you need to charge for 717 00:32:08,800 --> 00:32:09,840 them. So we're we're going to do it 718 00:32:09,840 --> 00:32:13,600 with our seats have like a base amount of tokens and then or 719 00:32:13,600 --> 00:32:15,480 credits and then you can get above. 720 00:32:15,640 --> 00:32:17,240 It's pretty standard now for a lot of tools. 721 00:32:17,240 --> 00:32:19,000 It's like lovable replay, etcetera, but. 722 00:32:19,040 --> 00:32:21,840 Why seats at all? It's a good question. 723 00:32:22,600 --> 00:32:25,240 I think in some ways it allows a base of predictability for 724 00:32:25,240 --> 00:32:26,680 customers. We were, we're a product that 725 00:32:26,680 --> 00:32:29,560 wants to get really wide in your organization and if we can say, 726 00:32:29,560 --> 00:32:32,400 Yep, it's, you know, however many $50 or whatever for a seat 727 00:32:32,840 --> 00:32:34,680 for a month, you, you know, and that comes with this number of 728 00:32:34,680 --> 00:32:37,840 credits and the average user is going to their usage is going to 729 00:32:37,840 --> 00:32:39,200 be covered by that. That's really nice for 730 00:32:39,200 --> 00:32:40,680 predictability. I mean, that is a big thing. 731 00:32:40,680 --> 00:32:44,320 People who have never sold or bought at scale enterprise 732 00:32:44,320 --> 00:32:48,080 software know like having it be fully variable is like that is 733 00:32:48,080 --> 00:32:52,800 tough As for a lot of companies. And, and generally, like I, I do 734 00:32:52,800 --> 00:32:55,360 have these funny conversations sometimes about seats where even 735 00:32:55,360 --> 00:32:58,480 with smart V ZS, which was funny, that are like, well, you 736 00:32:58,480 --> 00:33:01,600 know, there's going to be pressure on the number of seats 737 00:33:01,600 --> 00:33:03,440 you're going to be able to sell because customers are hiring 738 00:33:03,440 --> 00:33:08,400 less people or whatever. And I'm like, we've grown a lot 739 00:33:08,400 --> 00:33:10,800 and we're doing really well, but we're still, the amount of 740 00:33:10,800 --> 00:33:13,880 revenue we make today is still very, very small to the 741 00:33:13,880 --> 00:33:16,680 incumbents and where we want to go and all the time we think we 742 00:33:16,680 --> 00:33:19,120 can capture. And I'm like, if there is not 743 00:33:20,240 --> 00:33:22,800 10s of millions, hundreds of millions of dollars worth of 744 00:33:22,800 --> 00:33:25,560 seats for us to sell because everyone's been laid off. 745 00:33:25,760 --> 00:33:27,440 The. World's like, like I need, I 746 00:33:27,440 --> 00:33:31,320 need to own a lot of guns. The least of my problems is my 747 00:33:31,320 --> 00:33:34,280 fucking SAS business. Like I'm there's gonna be riots 748 00:33:34,280 --> 00:33:37,160 in the street. And so I think it's kind of 749 00:33:37,160 --> 00:33:40,040 funny this conversation about this like, yes, on the margin, 750 00:33:40,280 --> 00:33:42,720 is it possible that some of our customers will just be like 751 00:33:42,840 --> 00:33:45,360 small or in absolute terms, the number of people? 752 00:33:45,600 --> 00:33:47,200 Yes. Are there still a lot of seats 753 00:33:47,200 --> 00:33:49,400 to sell for our products like ours? 754 00:33:49,960 --> 00:33:51,920 Yes. Do a lot of customers still want 755 00:33:51,920 --> 00:33:53,840 to buy seats cuz it makes sense for what they're doing? 756 00:33:54,200 --> 00:33:56,560 Yes. Can I layer a consumption model 757 00:33:56,560 --> 00:33:59,800 on top that helps me both cover costs and also capture upside 758 00:33:59,800 --> 00:34:01,720 from real power users who are getting excess value? 759 00:34:02,160 --> 00:34:04,600 Yes. And over time we may tweak those 760 00:34:04,600 --> 00:34:05,680 dials. I don't know, a year from now, 761 00:34:05,680 --> 00:34:07,120 maybe we turn the seats down to 0. 762 00:34:07,120 --> 00:34:10,719 Maybe we maybe it goes back. Elena Verna at Lovable has this 763 00:34:10,719 --> 00:34:13,560 blog post that we talked about internally where she's like, I 764 00:34:13,560 --> 00:34:16,639 think the token cost is gonna come down significantly and 765 00:34:16,639 --> 00:34:19,360 we're all gonna be back to selling seats, Who knows? 766 00:34:19,600 --> 00:34:23,480 So we like having the options and we wanna, ultimately our job 767 00:34:23,480 --> 00:34:25,760 is to actually meet our customers where they're at. 768 00:34:25,760 --> 00:34:27,560 And people always joke. Customers don't wanna pay 769 00:34:27,560 --> 00:34:29,199 anything. Well, I actually disagree. 770 00:34:29,199 --> 00:34:32,080 I think customers understand the value and want to pay for 771 00:34:32,080 --> 00:34:34,840 something that's going to provide good value for them. 772 00:34:35,000 --> 00:34:37,239 They want to support you. They want to be supported. 773 00:34:37,639 --> 00:34:40,199 I'm a buyer of a lot of software at Hex now and I'm, I'm very 774 00:34:40,199 --> 00:34:41,719 happy to pay for stuff that works well. 775 00:34:41,920 --> 00:34:43,880 And if I feel like there's price to value and if I see the bill 776 00:34:43,880 --> 00:34:45,840 for what we're paying for something and I'm like, yeah, 777 00:34:45,840 --> 00:34:47,679 but we love it. I'm like great, cool. 778 00:34:47,840 --> 00:34:50,600 Where are you on this? Yeah, White collar works about 779 00:34:50,600 --> 00:34:52,920 to get decimated and our country's going to be, I don't 780 00:34:52,920 --> 00:34:55,040 know, going for the guns. Like, I, I literally was talking 781 00:34:55,080 --> 00:35:01,000 to a, you know, a very respected person, you know, who was like, 782 00:35:01,000 --> 00:35:03,600 oh man, we're going to enter like an insane political moment. 783 00:35:03,600 --> 00:35:06,280 Like every, you know, democratic cities. 784 00:35:06,280 --> 00:35:08,840 You know, if you know, all the Goldman analysts or something 785 00:35:08,840 --> 00:35:11,920 are about to get fired, you know, then you're going to have 786 00:35:11,920 --> 00:35:14,520 this sort of weird class, you know, just like you're going to 787 00:35:14,520 --> 00:35:16,880 have pockets of people who are very resentful about the new 788 00:35:16,880 --> 00:35:18,080 economy. Like I don't know how I. 789 00:35:18,080 --> 00:35:20,600 Already see it? I mean downward mobility, 790 00:35:20,600 --> 00:35:23,720 downwardly mobile elites. That is right. 791 00:35:23,720 --> 00:35:25,720 The most dangerous force in America is the leading. 792 00:35:25,720 --> 00:35:27,880 Indicator well, I mean, forget about America, just study 793 00:35:27,880 --> 00:35:31,560 history, right? Like that is a bad thing like 794 00:35:31,560 --> 00:35:35,520 that, that is that will lead to problems and I, I don't know for 795 00:35:35,520 --> 00:35:39,680 sure what the future looks like. I would say I applaud Dr. Karp. 796 00:35:39,680 --> 00:35:41,800 I'll still say Doctor Karp, who I think has been a very bold 797 00:35:41,800 --> 00:35:44,560 voice in saying like we should all be thinking about how we're 798 00:35:44,560 --> 00:35:47,120 using AI to like increase employment and productivity. 799 00:35:47,720 --> 00:35:52,440 And I, I agree with that. Now I'm building a tool that you 800 00:35:52,440 --> 00:35:55,520 can kind of look at like, do I need as many data scientists or 801 00:35:55,520 --> 00:35:57,960 data analysis I have? Sure. 802 00:35:58,160 --> 00:36:00,320 I also see a lot of the data scientists and data analysis we 803 00:36:00,320 --> 00:36:03,040 have using the shit out of it, doing a ton, being way more 804 00:36:03,040 --> 00:36:06,680 productive, being more valuable for their companies and often 805 00:36:06,680 --> 00:36:08,720 now starting to work at these higher levels of strategic 806 00:36:08,720 --> 00:36:10,680 insight and maybe their roles are starting to evolve. 807 00:36:10,960 --> 00:36:14,000 So it's not at all clear to me. We build an AI product. 808 00:36:14,000 --> 00:36:15,200 We use a lot of AI tools internally. 809 00:36:15,400 --> 00:36:16,880 I'm trying to hire as fast as I can. 810 00:36:17,320 --> 00:36:20,240 So we'll see. The other thing I think about is 811 00:36:20,240 --> 00:36:22,520 like where is the productivity? I mean, I, I can look within our 812 00:36:22,520 --> 00:36:24,480 own customers and see them doing more and all of this. 813 00:36:24,840 --> 00:36:28,200 I think a really interesting question is we're a year and a 814 00:36:28,200 --> 00:36:33,560 half now into coding agents being mainstream and we're 815 00:36:33,560 --> 00:36:38,400 billions of dollars of revenue into tokens paid to Claude and 816 00:36:38,400 --> 00:36:42,280 Codex and Cursor and other things that start with C and 817 00:36:44,280 --> 00:36:47,080 where where's the where's the explosion in software? 818 00:36:47,240 --> 00:36:49,000 We're getting a lot of vibe coded stuff. 819 00:36:49,000 --> 00:36:50,600 We're getting a lot of sort of slop wear. 820 00:36:50,880 --> 00:36:53,840 But if you look at the the the software companies you buy from, 821 00:36:54,200 --> 00:36:56,840 it's like, where's the where's the like cornucopia? 822 00:36:56,840 --> 00:36:58,840 Like why am I not getting new features every day? 823 00:36:58,840 --> 00:37:00,000 Right. It's so we. 824 00:37:00,080 --> 00:37:02,040 We've built a maybe. The bottleneck looks elsewhere. 825 00:37:02,040 --> 00:37:04,560 I don't know. My my my business lead has built 826 00:37:04,560 --> 00:37:07,760 us, you know, internal like ticketing tool that he vibe 827 00:37:07,760 --> 00:37:09,320 coded. We're we're about to see, you 828 00:37:09,320 --> 00:37:13,840 know, when the metal meets the pavement or whatever the whether 829 00:37:13,840 --> 00:37:16,120 you know, we can accept payments and everything safely through 830 00:37:16,120 --> 00:37:18,920 it, but. Like why like you that? 831 00:37:19,000 --> 00:37:20,520 But I get. That's right, you can. 832 00:37:20,520 --> 00:37:23,360 Doesn't need to be perfect, is. That Riley, yeah, yeah, that 833 00:37:23,360 --> 00:37:25,360 Riley can do that is cool. It's huge. 834 00:37:25,360 --> 00:37:27,120 I mean, it's pretty. It's pretty, but. 835 00:37:27,120 --> 00:37:28,440 But like, should he be doing that? 836 00:37:29,440 --> 00:37:32,800 Yeah, there's a lot of things to do, but the I think it'll be 837 00:37:32,800 --> 00:37:34,400 good, you know, we'll keep track of everyone. 838 00:37:35,560 --> 00:37:38,800 But to your point, I mean, do you feel pressure as the at at a 839 00:37:38,800 --> 00:37:41,480 start up, your investor was want to hear this story of like, 840 00:37:41,480 --> 00:37:44,720 yeah, we're moving so much faster because of, you know, 841 00:37:45,560 --> 00:37:48,320 cursor or whatever. And and you're saying no, but 842 00:37:48,320 --> 00:37:49,880 it's not like I do. Feel like we are. 843 00:37:49,880 --> 00:37:52,880 It is also interesting. We are living, you know, I've 844 00:37:52,880 --> 00:37:54,160 got, I've just came from our office. 845 00:37:54,160 --> 00:37:57,680 I've walked by any engineer's desk and they've got cursor or 846 00:37:57,680 --> 00:38:00,480 cloud code or codecs. Now they've gotten very popular 847 00:38:01,280 --> 00:38:02,600 up on their screen. They're using it. 848 00:38:02,880 --> 00:38:05,320 I think we're still figuring out how to use these things, like 849 00:38:05,320 --> 00:38:07,240 we're setting up cloud dev environments to make it easier 850 00:38:07,240 --> 00:38:09,040 to have multiple different agents that can work in their 851 00:38:09,040 --> 00:38:11,760 own dev boxes. And it's like, OK, so now our 852 00:38:11,760 --> 00:38:13,960 engineers are just bouncing between 5 different agents 853 00:38:13,960 --> 00:38:15,520 working on different tasks at a time. 854 00:38:15,760 --> 00:38:19,200 Who's reviewing all this code? Who's initiating the thought on 855 00:38:19,200 --> 00:38:21,880 what we should build? I mean, I'm almost like really 856 00:38:21,880 --> 00:38:24,560 excited about the idea of just getting this torrent of PRS from 857 00:38:24,560 --> 00:38:26,080 all of our engineers. I'm also slightly worried 858 00:38:26,080 --> 00:38:29,400 because we're a product that's prided itself on sign and 859 00:38:29,400 --> 00:38:31,280 consistency and fit and finish and feel. 860 00:38:31,760 --> 00:38:35,640 And our designers are busy now like trying to do Polish commits 861 00:38:35,640 --> 00:38:40,840 on to all these PRS. And it's how do we even get all 862 00:38:40,840 --> 00:38:42,920 this out into the product in a way that our customers 863 00:38:42,920 --> 00:38:44,800 understand? It's gonna be changing fast and 864 00:38:45,000 --> 00:38:46,360 that's exciting, but also stressful. 865 00:38:46,360 --> 00:38:48,200 It's like, I think we're all still figuring out how to 866 00:38:48,200 --> 00:38:49,960 metabolize all of this something. 867 00:38:49,960 --> 00:38:53,840 Tells me there's just like a pace of that humans can absorb 868 00:38:53,880 --> 00:38:56,200 the products. Change like I, I think it's 869 00:38:56,200 --> 00:38:58,200 literally like if you eat too much food, like your body can 870 00:38:58,200 --> 00:39:05,280 only metabolize so much of it. And like, I think we're still 871 00:39:05,280 --> 00:39:08,920 just figuring this out. And so I, I don't know that 872 00:39:08,920 --> 00:39:10,200 these things are going to happen overnight. 873 00:39:10,200 --> 00:39:12,880 And like, if your model of a Goldman analyst is that they're 874 00:39:12,880 --> 00:39:16,080 just doing this really rote, repeatable work that an agent 875 00:39:16,080 --> 00:39:18,240 can replace. Sure. 876 00:39:18,560 --> 00:39:20,880 Is that all that a Goldman analyst does? 877 00:39:20,880 --> 00:39:22,920 It's the same, I think about for data people, if you're like, 878 00:39:24,040 --> 00:39:26,000 what, how do we understand those jobs? 879 00:39:26,000 --> 00:39:28,400 What are actually the bottlenecks and companies doing 880 00:39:28,400 --> 00:39:31,800 certain things we're supposed to early in figuring this out? 881 00:39:33,000 --> 00:39:35,520 Particularly, it's interesting to me, I've observed almost like 882 00:39:36,040 --> 00:39:38,960 coding agents have disrupted product management faster than 883 00:39:38,960 --> 00:39:41,720 engineering because the engineers are almost becoming 884 00:39:41,720 --> 00:39:44,960 PMS in a funny way where it's like, it's kind of unintuitive, 885 00:39:44,960 --> 00:39:48,200 but like the, the a lot of our engineers, you know, are now 886 00:39:49,120 --> 00:39:53,880 their, their, their job is less like, OK, I take the, the, the 887 00:39:54,080 --> 00:39:57,360 product spec that was written in English and I translate it to 888 00:39:57,360 --> 00:39:59,400 code syntax. Like that used to be the thing 889 00:39:59,400 --> 00:40:01,440 it's like. Your engineering candidate. 890 00:40:01,600 --> 00:40:04,040 Oh, you know how to take English and turn it into TypeScript. 891 00:40:04,040 --> 00:40:05,120 Great. Welcome. 892 00:40:05,560 --> 00:40:06,840 Right. That was kind of like at least 893 00:40:06,840 --> 00:40:08,960 the first order heuristic of what we're like interviewing you 894 00:40:08,960 --> 00:40:11,440 for with like coding interviews. Well, now there's magic robots 895 00:40:11,440 --> 00:40:14,560 that can do that. And so and so instead, so we're 896 00:40:14,560 --> 00:40:18,280 gonna keep our smartest people, the engineers, and shift them to 897 00:40:18,280 --> 00:40:20,320 sort of the strategy rather than. 898 00:40:20,480 --> 00:40:22,080 Yes, it's not like, it's not like. 899 00:40:22,120 --> 00:40:25,440 A product manager, I would never be an engineer, but I mean, that 900 00:40:25,440 --> 00:40:27,960 is sort of, it's like, OK, if they're not writing the code, 901 00:40:27,960 --> 00:40:30,800 they're still very smart, understand sort of the core 902 00:40:30,800 --> 00:40:32,480 product, and so they're gonna become the product. 903 00:40:32,480 --> 00:40:35,160 Going back, by the way, the type of engineers we try to hire are 904 00:40:35,160 --> 00:40:37,520 those that like talking to customers and like thinking 905 00:40:37,520 --> 00:40:40,080 about what to build and enjoy our product space. 906 00:40:40,080 --> 00:40:43,240 It's a cool product space. So yeah, those people have 907 00:40:43,240 --> 00:40:45,160 always liked that, and now they just have kind of more time and 908 00:40:45,160 --> 00:40:47,120 brain space for that, and they can be thinking about what to 909 00:40:47,120 --> 00:40:49,600 build and how should this work and the architectures and all 910 00:40:49,600 --> 00:40:50,680 this, and it's really cool to see. 911 00:40:51,000 --> 00:40:56,040 So we'll see how these roles change what designers do. 912 00:40:56,120 --> 00:40:58,640 Our designers have coded for a long time, but now they're 913 00:40:58,640 --> 00:41:00,520 coding a ton. They're mostly coding. 914 00:41:01,000 --> 00:41:04,040 It's like, well, are you, what, what do you do? 915 00:41:04,520 --> 00:41:07,000 Are you just an engineer that has like really good taste and 916 00:41:07,000 --> 00:41:08,960 more tattoos? Like what's that? 917 00:41:09,440 --> 00:41:11,440 It's very interesting to see happen. 918 00:41:11,520 --> 00:41:15,480 And internally I'm just trying to lead everyone through it 919 00:41:15,680 --> 00:41:19,560 saying we're all learning this together and if you don't 920 00:41:19,560 --> 00:41:22,160 disrupt your job, someone else. Well, and don't worry. 921 00:41:22,640 --> 00:41:25,320 How many people do we need to get to a huge exit hex? 922 00:41:25,960 --> 00:41:28,760 I don't know. More than we have today, so, and 923 00:41:28,760 --> 00:41:30,480 more than our. Competitors so we wanna get good 924 00:41:30,480 --> 00:41:32,200 ones you guys are all safe let's all. 925 00:41:32,200 --> 00:41:34,520 Figure out how we can all use our time really well, and then 926 00:41:34,520 --> 00:41:36,640 we'll go build this thing and have it be really valuable. 927 00:41:36,640 --> 00:41:40,480 So I wanted to go back to Palantir and some of the, I 928 00:41:40,760 --> 00:41:44,160 mean, obviously we just had this Anthropic took the headline 929 00:41:44,160 --> 00:41:46,400 because they were the ones sort of fighting with the government 930 00:41:46,400 --> 00:41:49,160 over, yes, fighting with the Department of War or Defence, 931 00:41:49,160 --> 00:41:52,200 depending where you sit on. Yeah, sit on things. 932 00:41:52,200 --> 00:41:55,080 Not going to take a position. I think we I've gone back to 933 00:41:55,080 --> 00:41:57,360 defence. I mean defence was established 934 00:41:57,360 --> 00:41:59,560 by Congress. So it is sort of a branding 935 00:41:59,560 --> 00:42:00,840 exercise. You don't need to weigh in on 936 00:42:00,840 --> 00:42:05,800 this, but I think core to the conflict the, you know, 937 00:42:06,200 --> 00:42:08,120 Anthropic had two concerns, right? 938 00:42:08,240 --> 00:42:11,560 One was this autonomous targeting and the other was this 939 00:42:11,560 --> 00:42:14,320 piece that we are gonna do domestic surveillance. 940 00:42:14,600 --> 00:42:16,760 And I think embedded in the domestic surveillance is that 941 00:42:17,000 --> 00:42:21,600 fundamentally because of how much better their technology and 942 00:42:21,600 --> 00:42:24,120 technology generally has gotten, the government can just acquire 943 00:42:24,120 --> 00:42:28,000 publicly available data and then come up with this NSA dragnet. 944 00:42:28,000 --> 00:42:30,720 That wouldn't have been possible, you know, when 945 00:42:30,720 --> 00:42:34,040 Congress was writing laws about domestic surveillance. 946 00:42:34,200 --> 00:42:36,840 And obviously pound tier like fits fits into this. 947 00:42:36,840 --> 00:42:39,800 So what is your view of? Like what's possible in terms 948 00:42:39,800 --> 00:42:42,000 of? Exhibit A in a tech company that 949 00:42:42,640 --> 00:42:47,680 lives in that Gray area. I was there 10 years ago after 950 00:42:47,680 --> 00:42:51,840 the 2016 election, and it had been not so long before that 951 00:42:51,840 --> 00:42:54,800 that we had like an, it was like an all hands or a, some sync 952 00:42:54,800 --> 00:42:58,120 version we had of this. That was like doing a like a 953 00:42:58,120 --> 00:43:00,200 win. Like the deployment team lead 954 00:43:00,200 --> 00:43:04,320 came up on stage to like talk about our work with ICE, which 955 00:43:04,320 --> 00:43:06,080 we're really proud of because we were working with this team 956 00:43:06,080 --> 00:43:08,280 called HSI. It's like the really good guy, 957 00:43:08,320 --> 00:43:10,520 you know, the, the, whatever else you feel about other parts 958 00:43:10,520 --> 00:43:13,200 of the government, he's stopping human trafficking and like drug 959 00:43:13,360 --> 00:43:16,560 smuggling, Like go, go HSI. Yeah. 960 00:43:18,440 --> 00:43:21,040 And then like, you know, that election, the vibe shifted on 961 00:43:21,040 --> 00:43:23,400 all of tech shifted 10 years ago is kind of a long time. 962 00:43:23,400 --> 00:43:25,480 Remember back. But like and all of a sudden 963 00:43:25,480 --> 00:43:28,760 this became really tough. And we had internal concerns. 964 00:43:28,760 --> 00:43:30,600 We had protests outside the office. 965 00:43:31,160 --> 00:43:34,080 We had applicants not wanting to come people not people not 966 00:43:34,080 --> 00:43:36,040 applying or pulling out of interview processes because we 967 00:43:36,040 --> 00:43:38,160 were evil. And there was a big clamor 968 00:43:38,160 --> 00:43:42,120 internally to get Doctor Carr, Alex Carp to, to say something 969 00:43:42,120 --> 00:43:44,080 publicly say something engage on this. 970 00:43:45,280 --> 00:43:48,960 And I, I was, I was among the frustrated on that. 971 00:43:48,960 --> 00:43:51,840 I'll, I'll confess, like, you know, I'm interviewing 972 00:43:51,840 --> 00:43:53,480 candidates who are like half the interview. 973 00:43:53,480 --> 00:43:55,880 They're just asking me questions about how I like, I can sleep at 974 00:43:55,880 --> 00:43:56,680 night or something. I'm like. 975 00:43:57,800 --> 00:44:00,520 It's also so secretive that it's hard to even necessarily not 976 00:44:00,520 --> 00:44:03,560 even inside the company. And inside we knew and and I 977 00:44:03,560 --> 00:44:06,640 think we had an appreciation and I still have a deep appreciation 978 00:44:06,640 --> 00:44:10,160 for like this was a company that recognized that to serve the 979 00:44:10,160 --> 00:44:15,960 government, to serve the government in these spaces, you 980 00:44:15,960 --> 00:44:17,400 have to be comfortable in the Gray areas. 981 00:44:17,400 --> 00:44:18,920 And that doesn't mean moral compromise. 982 00:44:18,920 --> 00:44:22,240 It actually means moral clarity and having principles, even when 983 00:44:22,240 --> 00:44:25,800 they're hard. And, you know, in retrospect, he 984 00:44:26,200 --> 00:44:27,520 was totally right. And they're, they're much more 985 00:44:27,520 --> 00:44:29,240 public engaging in the forum now. 986 00:44:29,240 --> 00:44:31,240 But I think at the time, the right thing for us was to just 987 00:44:31,240 --> 00:44:35,320 stay quiet, not engage, not not inflamed us and say let's focus 988 00:44:35,320 --> 00:44:41,640 on our work and let's focus on doing the best we can and also 989 00:44:41,760 --> 00:44:43,800 embrace the fact that we live in a democracy. 990 00:44:44,320 --> 00:44:47,520 But you have a view on this anthropic blow up specifically? 991 00:44:47,720 --> 00:44:50,080 Well, yeah, that's my yeah. The kind of segue it's. 992 00:44:50,600 --> 00:44:52,600 I love Anthropic. We're partners with them. 993 00:44:52,600 --> 00:44:56,120 They're customers of ours. I don't, I say this with love, 994 00:44:56,120 --> 00:44:59,400 but I do think it's like the heart and the head. 995 00:44:59,400 --> 00:45:02,080 Like from a heart. You understand some of these 996 00:45:02,080 --> 00:45:05,680 concerns. Like, would I, like, would most 997 00:45:05,680 --> 00:45:08,720 Americans vote for doing mass surveillance? 998 00:45:09,040 --> 00:45:11,120 You know, you can go gather up all this information and figure 999 00:45:11,120 --> 00:45:13,200 out where everyone's loyalties lie or something like, no, I 1000 00:45:13,200 --> 00:45:16,040 think most Americans would not want that. 1001 00:45:17,640 --> 00:45:20,200 But that's why we have a democracy and you can vote. 1002 00:45:20,200 --> 00:45:22,920 People can vote for that. And I think what we came to 1003 00:45:22,920 --> 00:45:25,640 appreciate a Palantir, what sort of respect is like, well, what, 1004 00:45:25,640 --> 00:45:27,440 OK, we're gonna have red lines and what we're willing to do, 1005 00:45:27,440 --> 00:45:29,560 does the government have to call us every time they want to use 1006 00:45:29,760 --> 00:45:32,760 Gotham was our product every time there was any palantir to 1007 00:45:32,800 --> 00:45:35,280 use this thing like. Isn't this an extreme deference 1008 00:45:35,600 --> 00:45:37,880 to the executive branch specifically? 1009 00:45:37,880 --> 00:45:40,640 I mean, it's not like Congress has passed the law, said, oh, we 1010 00:45:40,640 --> 00:45:42,480 love Palantir. Like you. 1011 00:45:42,520 --> 00:45:45,320 You could have a belief that like our product is so 1012 00:45:45,480 --> 00:45:47,680 significant. They have, I mean they they sort 1013 00:45:47,800 --> 00:45:50,080 of every year. Did power, but they haven't. 1014 00:45:50,080 --> 00:45:52,840 Like expressly said, this is great I. 1015 00:45:52,880 --> 00:45:55,240 Mean I'm, I'm not like a constitutional scholar. 1016 00:45:55,240 --> 00:45:57,960 I'm just saying. But I do think, and I don't want 1017 00:45:57,960 --> 00:45:59,880 to, you know, you don't, you're not, you're just the one here 1018 00:45:59,880 --> 00:46:02,440 talking about it now. But like they're, they're, I do 1019 00:46:02,440 --> 00:46:05,040 think there's this argument that it's like, oh, we're deferring 1020 00:46:05,040 --> 00:46:06,280 to democracy. It's like you're deferring to 1021 00:46:06,280 --> 00:46:11,160 like 1 branch that's taking on a lot of power and saying we 1022 00:46:11,160 --> 00:46:13,400 represent democracy. This is what it looks like to 1023 00:46:13,400 --> 00:46:15,080 live in a Republic. It's messy. 1024 00:46:15,480 --> 00:46:16,680 You, you, you. Elect right. 1025 00:46:16,680 --> 00:46:19,840 So it requires on the part of other actors to sort of 1026 00:46:19,840 --> 00:46:23,080 interpret and what the will of democracy is beyond just like 1027 00:46:23,080 --> 00:46:25,480 difference to the executive. You described a Republican, but. 1028 00:46:26,000 --> 00:46:29,720 The argument that Palantir is making and trying to suggest 1029 00:46:29,800 --> 00:46:32,640 anthropic embrace is sort of like yield to just the 1030 00:46:32,640 --> 00:46:35,080 executive's interpretation of what the will of. 1031 00:46:35,080 --> 00:46:42,200 Democracy is yes, yes. And that will of that executive 1032 00:46:42,360 --> 00:46:45,880 is bound that that's Article 2 is bound by Article 1, the 1033 00:46:45,880 --> 00:46:47,760 legislative branch and the laws they pass. 1034 00:46:47,760 --> 00:46:50,520 And look, I, I, I'm not going to get into like debates on like 1035 00:46:50,520 --> 00:46:54,200 current Supreme Court issues or all that, but like, at least if 1036 00:46:54,200 --> 00:46:57,960 you read the Constitution, it's pretty damn clear, like the, the 1037 00:46:57,960 --> 00:47:01,160 legislator pass, the legislature passes laws, including the power 1038 00:47:01,160 --> 00:47:04,600 of the purse. They control what money is spent 1039 00:47:05,160 --> 00:47:06,440 and the executive executes on that. 1040 00:47:06,440 --> 00:47:08,400 And there's all these, you know, unitary executive and all these 1041 00:47:08,400 --> 00:47:09,480 things. I'm not going to get into all 1042 00:47:09,480 --> 00:47:11,920 that, but I will just tell you, even you see this play out now, 1043 00:47:12,440 --> 00:47:17,720 there is a funding bill issue in Congress right now for 1044 00:47:18,120 --> 00:47:22,680 Department of Homeland Security where there appears to be a 1045 00:47:22,880 --> 00:47:25,840 legislative majority or controlling legislative majority 1046 00:47:25,840 --> 00:47:29,080 that is not comfortable with funding Homeland Security at the 1047 00:47:29,080 --> 00:47:32,160 way that they have been. And that is the democratic 1048 00:47:32,160 --> 00:47:34,080 process working out. And you can look at the last 1049 00:47:34,080 --> 00:47:35,840 this current Congress and say, well, they've been overly 1050 00:47:35,840 --> 00:47:39,040 deferential to the executive and whatever and that may well be. 1051 00:47:39,280 --> 00:47:41,040 But you see this happening. And now people, we're looking 1052 00:47:41,040 --> 00:47:42,840 forward to the midterms and people are worried about that 1053 00:47:42,840 --> 00:47:44,840 and they're going to react to the public sentiment. 1054 00:47:45,440 --> 00:47:48,000 And if public doesn't want something great, what a 1055 00:47:48,000 --> 00:47:51,000 wonderful opportunity for a political entrepreneur in 1056 00:47:51,000 --> 00:47:54,000 Congress to get up and propose a bill banning this type of mass 1057 00:47:54,000 --> 00:47:56,200 surveillance. They're just outlawed. 1058 00:47:56,200 --> 00:47:58,840 You can pass a law to do that. That is a thing. 1059 00:47:59,200 --> 00:48:01,200 That's your job. Actually, that's literally their 1060 00:48:01,200 --> 00:48:02,920 job. If this is a thing we don't want 1061 00:48:02,920 --> 00:48:05,040 to have, we both want. Congress to take a more active 1062 00:48:05,040 --> 00:48:07,840 role in saying what they support and what they don't. 1063 00:48:07,840 --> 00:48:11,640 And I agree that I mean, ISIS and Homeland Security is a good 1064 00:48:11,640 --> 00:48:14,120 example where Congress is stalling on it. 1065 00:48:14,440 --> 00:48:18,360 I mean, we also live in this liberal democracy where unless 1066 00:48:18,360 --> 00:48:21,840 it is a I understand in a war, people get drafted and summoned 1067 00:48:21,840 --> 00:48:25,080 into government service. But the, the in normal times, I 1068 00:48:25,080 --> 00:48:29,360 think the belief in America is that you don't have to do 1069 00:48:29,360 --> 00:48:31,160 something for the government if you don't want, you know, you're 1070 00:48:31,160 --> 00:48:32,520 not like. Off the pay taxes, right? 1071 00:48:33,640 --> 00:48:35,200 Right. Besides sort of making the whole 1072 00:48:35,200 --> 00:48:37,640 thing work with taxes, you don't have to like go work for the 1073 00:48:37,640 --> 00:48:40,080 government. You don't have to, and Anthropic 1074 00:48:40,080 --> 00:48:42,000 doesn't have to. No, no one does but the. 1075 00:48:42,000 --> 00:48:44,920 Criticism of anthropic is they sort of need to be summoned into 1076 00:48:44,920 --> 00:48:50,280 it. Maybe they could just an option 1077 00:48:50,280 --> 00:48:52,440 they have is say we actually don't want to work with you 1078 00:48:52,440 --> 00:48:54,320 guys, we're going to withdraw from the contract. 1079 00:48:54,640 --> 00:48:57,040 Best of luck using other AI providers like that that's 1080 00:48:57,040 --> 00:48:58,840 allowed. They're not. 1081 00:48:59,040 --> 00:49:00,600 There's not the. Trump There's a war. 1082 00:49:00,760 --> 00:49:03,680 Powers Act, There's a War Powers Act where the government can 1083 00:49:03,680 --> 00:49:06,480 mandate like I think it's called war powers that I think it's 1084 00:49:06,480 --> 00:49:07,800 just like we saw some of this during COVID. 1085 00:49:07,800 --> 00:49:10,600 Like that's one of the ones they floated they but they ended up 1086 00:49:10,600 --> 00:49:13,120 saying, oh man, it's a supply chain risk. 1087 00:49:13,120 --> 00:49:16,240 It's more dangerous, apparently. But they're but that's them 1088 00:49:16,240 --> 00:49:17,120 that's almost doing the opposite. 1089 00:49:17,120 --> 00:49:19,040 They're almost cutting them out. I mean, I'm just saying, I'm 1090 00:49:19,040 --> 00:49:21,520 just saying that like an option they have is just to not do it. 1091 00:49:21,880 --> 00:49:25,040 Now going back at Palantir, one of the things we talked about 1092 00:49:25,040 --> 00:49:27,840 that I do believe to be true is if we're not engaging on this 1093 00:49:27,840 --> 00:49:34,640 issue, other companies with less scruples, with less principle 1094 00:49:34,640 --> 00:49:37,200 point of view and by the way less effective software are 1095 00:49:37,200 --> 00:49:40,440 going to. And we have a privacy and civil 1096 00:49:40,440 --> 00:49:42,400 liberties team account here that I loved. 1097 00:49:42,400 --> 00:49:44,360 If there's a lot of them are still there, they're incredible 1098 00:49:44,360 --> 00:49:47,000 people, very thoughtful that we worked with very closely on a 1099 00:49:47,000 --> 00:49:50,880 lot of these things that and, you know, you kind of look down 1100 00:49:50,880 --> 00:49:53,480 the street at the other defense contractors and you go, they 1101 00:49:53,480 --> 00:49:55,720 don't have that shit or they do. There are a lot of lawyers who 1102 00:49:56,320 --> 00:50:00,560 but it's, it's, it's like, would we rather be the ones engaging 1103 00:50:00,560 --> 00:50:02,680 on this and thinking critically about it and trying to find the 1104 00:50:02,680 --> 00:50:06,840 synthesis of how you have robust defense with civil liberties, or 1105 00:50:06,840 --> 00:50:10,760 would you rather see the field? And for us, the calculus was we 1106 00:50:10,760 --> 00:50:13,160 would rather be here, even if it's a little uncomfortable, 1107 00:50:13,200 --> 00:50:17,440 because that's our role in this pluralistic, messy democracy we 1108 00:50:17,440 --> 00:50:18,440 have. I mean, I agree. 1109 00:50:18,440 --> 00:50:20,280 That there was sort of a misguided time where the tech 1110 00:50:20,280 --> 00:50:23,160 industry said we shouldn't do, you know, Google didn't want to 1111 00:50:23,160 --> 00:50:25,000 work with the government or, you know, there was like, we're not 1112 00:50:25,000 --> 00:50:26,200 work with the Department of Defense. 1113 00:50:26,600 --> 00:50:30,680 We've moved to a point where it's patriotic to support the 1114 00:50:30,680 --> 00:50:32,720 government. Yeah, but I but I think there's. 1115 00:50:32,720 --> 00:50:35,480 Nothing like nothing like multiple wars breaking out to 1116 00:50:35,480 --> 00:50:37,680 kind of get Americans to like wake up and be like, oh, maybe 1117 00:50:37,680 --> 00:50:40,760 we need maybe we need good capabilities and weapons. 1118 00:50:40,760 --> 00:50:45,840 Like Anderol was like super unsexy off SPAC, not a sexy VC 1119 00:50:45,840 --> 00:50:46,840 thing. And then all of a sudden a war 1120 00:50:46,840 --> 00:50:48,640 breaks out in Ukraine that's becoming like a drone war. 1121 00:50:48,640 --> 00:50:50,640 And everyone's like Anderol's amazing. 1122 00:50:50,680 --> 00:50:52,080 But I've always thought Anderol's amazing. 1123 00:50:52,080 --> 00:50:55,000 And I know all the founders and, you know, but it was funny to 1124 00:50:55,000 --> 00:50:57,400 kind of see them going from these like black sheep to now 1125 00:50:57,400 --> 00:51:00,880 these darlings on the other side of a war that kind of reminds 1126 00:51:00,880 --> 00:51:03,920 you it's not the end of history. Like the Ukraine war is a 1127 00:51:03,920 --> 00:51:06,840 reminder that like, no, this is that we live in a dangerous 1128 00:51:06,840 --> 00:51:08,560 world. But the argument that you're 1129 00:51:08,560 --> 00:51:11,920 making that Palantir, you know, we're so it's so thoughtful 1130 00:51:11,920 --> 00:51:16,040 about, you know, sort of civil rights or whatever, or like 1131 00:51:16,240 --> 00:51:18,480 understanding the effect of its technology. 1132 00:51:18,640 --> 00:51:21,640 The argument right now is that tech companies shouldn't be the 1133 00:51:21,640 --> 00:51:24,080 ones deciding, and the government should have total, 1134 00:51:24,240 --> 00:51:29,280 total control. Like that's the line from what 1135 00:51:29,280 --> 00:51:31,760 heck, said. The Palantir seems to to sort of 1136 00:51:31,760 --> 00:51:33,840 say, whoa, we're not creating contracts that limit you. 1137 00:51:35,440 --> 00:51:37,640 But they can just choose not to engage in a contract. 1138 00:51:38,000 --> 00:51:39,960 There were, there were, there was work. 1139 00:51:40,160 --> 00:51:41,800 I can't talk about it. There were things at Palantir 1140 00:51:41,800 --> 00:51:44,680 that we just decided not to do, countries we decided not to work 1141 00:51:44,680 --> 00:51:48,880 with lucrative, lucrative deals where we sent teams out to go 1142 00:51:50,000 --> 00:51:54,520 diligent something and came back and said this is not an area we 1143 00:51:54,520 --> 00:51:57,040 are not comfortable here. We don't think we can actually 1144 00:51:57,120 --> 00:51:59,920 have our software to be deployed in a way that we think is gonna 1145 00:51:59,920 --> 00:52:03,000 preserve the things we want. We're just not gonna engage. 1146 00:52:03,080 --> 00:52:05,560 I mean, that's an option. But Andrew Abbott had a contract 1147 00:52:05,560 --> 00:52:07,720 they liked and then the Defense Department. 1148 00:52:08,160 --> 00:52:09,560 Yeah, I mean, I've read their stuff. 1149 00:52:09,760 --> 00:52:12,920 I've read Emil Michael's interview with Empire Wires, 1150 00:52:12,920 --> 00:52:18,000 Empire Wires, and I don't wanna. The last thing I want to do is 1151 00:52:18,040 --> 00:52:20,200 get in any of that. I'll just say this. 1152 00:52:20,200 --> 00:52:23,320 Do you want to be spicy? It's just of the moment. 1153 00:52:23,520 --> 00:52:26,760 I'm not trying to get. Are you neutral on it or are you 1154 00:52:26,800 --> 00:52:28,040 you? What is your you know you're 1155 00:52:28,040 --> 00:52:29,840 supportive of? The department I, I, I was 1156 00:52:29,840 --> 00:52:32,120 raised at pound tier and I, I part of the reason I was there 1157 00:52:32,120 --> 00:52:34,400 and part of the reason I still am supportive of is I think our, 1158 00:52:34,680 --> 00:52:39,080 we, we, the West needs the best capabilities. 1159 00:52:39,200 --> 00:52:41,960 And one of the things that defines the Western Western 1160 00:52:41,960 --> 00:52:45,520 society and the Western alliance is democracies and these 1161 00:52:45,520 --> 00:52:48,440 republics we have and in the United States, this wonderful 1162 00:52:48,440 --> 00:52:52,560 Republic we have that in every generation has felt broken in 1163 00:52:52,560 --> 00:52:54,120 some way. I always think it's funny when 1164 00:52:54,120 --> 00:52:55,440 people we've never been more divided. 1165 00:52:55,720 --> 00:52:59,560 Bitch, we fought a civil war like, like, like we this, this 1166 00:52:59,600 --> 00:53:02,840 just what this looks like and, and, and no one's ever going to 1167 00:53:02,840 --> 00:53:04,840 be totally happy with the current state of it. 1168 00:53:04,840 --> 00:53:06,840 And that is kind of just how these things work. 1169 00:53:06,840 --> 00:53:11,080 And I, I don't say that to be like fatalistic or even like, Oh 1170 00:53:11,080 --> 00:53:13,160 well, just whatever the government use the software 1171 00:53:13,160 --> 00:53:16,080 however you want. I just think it's like the, the, 1172 00:53:16,240 --> 00:53:22,480 the voters take the there's a saying I liked, which is people 1173 00:53:22,480 --> 00:53:24,840 deserve to get what they voted for good and hard. 1174 00:53:25,520 --> 00:53:27,960 And you know what? They're getting a good and hard 1175 00:53:27,960 --> 00:53:28,400 right now. I. 1176 00:53:28,400 --> 00:53:31,960 Just I just think it we're still a liberal society where people 1177 00:53:31,960 --> 00:53:35,160 participate or don't and like we are anthropic is being bullied 1178 00:53:35,160 --> 00:53:37,600 into participating. Like the government is using the 1179 00:53:37,600 --> 00:53:40,840 tools and you control whether you're supportive of them or 1180 00:53:40,840 --> 00:53:43,560 not. You know, it's it my my issue is 1181 00:53:43,560 --> 00:53:47,800 not yes, the Department of War is in charge of making war and 1182 00:53:47,800 --> 00:53:50,480 anthropics in charge of using their technology how they want, 1183 00:53:50,480 --> 00:53:53,880 and my issue is them using every lever they can to coerce 1184 00:53:53,880 --> 00:53:56,320 anthropic to acting against this their moral. 1185 00:53:56,320 --> 00:54:00,520 Beliefs, I mean, this administration has has been not 1186 00:54:00,520 --> 00:54:03,080 been shy about employing coercive techniques. 1187 00:54:03,440 --> 00:54:05,080 Look at law firms. I mean, there's a lot of. 1188 00:54:05,160 --> 00:54:06,920 And a lot of people want to extract away the current 1189 00:54:06,920 --> 00:54:08,800 administration, like whenever we're having this argument, 1190 00:54:08,800 --> 00:54:12,160 they're like, oh, the the executive, whoever they may be. 1191 00:54:12,160 --> 00:54:13,920 And it's like it's executive with the black record. 1192 00:54:13,920 --> 00:54:16,240 People had critiques of the last administration in the way that 1193 00:54:16,240 --> 00:54:19,840 they were acted coercively toward private enterprises and 1194 00:54:19,840 --> 00:54:20,760 some sectors as well. This. 1195 00:54:20,760 --> 00:54:23,120 Is by not inviting Tesla to Electro. 1196 00:54:23,120 --> 00:54:25,040 These other examples people have stuff on crypto. 1197 00:54:25,040 --> 00:54:26,320 I mean, I, I'm just sure I'm I'm. 1198 00:54:26,480 --> 00:54:28,280 I'm, I'm just saying I'm just, yeah, I'm just. 1199 00:54:28,280 --> 00:54:32,200 Saying like you can point these, this is not, this is not a novel 1200 00:54:32,200 --> 00:54:34,480 new like criticism of government. 1201 00:54:35,920 --> 00:54:39,920 I, you were right, we live in a liberal democracy and I and I 1202 00:54:41,800 --> 00:54:44,040 one way you could look at this as anthropic is getting bullied. 1203 00:54:44,040 --> 00:54:47,400 Another and something I will say I admire is anthropic is saying 1204 00:54:47,400 --> 00:54:50,200 we're patriotic Americans. We want our government to have a 1205 00:54:50,200 --> 00:54:52,160 great capability. We are proud of the product we 1206 00:54:52,160 --> 00:54:54,200 make. We want it to be employed and we 1207 00:54:54,200 --> 00:54:56,200 just have some concerns and limitations on where it can be 1208 00:54:56,200 --> 00:54:59,240 employed. That is a perfectly valid place 1209 00:54:59,240 --> 00:55:01,080 to be. And the government, if you take 1210 00:55:01,080 --> 00:55:04,400 them at face value, is saying we're we want to work with 1211 00:55:04,400 --> 00:55:08,760 private enterprise, but we need to have the flexibility to go 1212 00:55:08,760 --> 00:55:10,800 engage in the things we have to engage in to do the things we 1213 00:55:10,800 --> 00:55:12,840 want to do. Emil Michael on that post was 1214 00:55:12,840 --> 00:55:16,360 like, you know, we do a lot of stuff with guns, but if you're 1215 00:55:16,360 --> 00:55:18,160 not comfortable with, I'm paraphrasing, but if you're not 1216 00:55:18,200 --> 00:55:20,480 comfortable with that, maybe you can't work with us. 1217 00:55:20,480 --> 00:55:22,640 And like, I do think that's one of the things you kind of have 1218 00:55:22,640 --> 00:55:26,480 to stare into like, again, going back to the time of Palantir, 1219 00:55:26,480 --> 00:55:28,680 like there's things we did and worked on that you kind of look 1220 00:55:28,680 --> 00:55:32,480 at and you're like, not because it's like morally repugnant, but 1221 00:55:32,480 --> 00:55:36,560 it's like, does any you know, no, I would certainly never 1222 00:55:36,560 --> 00:55:39,440 stand up and like celebrate like people dying. 1223 00:55:39,680 --> 00:55:41,640 Like even if there are adversaries, there's something 1224 00:55:41,640 --> 00:55:43,320 there's just, you know, people kind of look at that and it's 1225 00:55:43,320 --> 00:55:45,640 like you can the the reluctant warrior, right? 1226 00:55:45,640 --> 00:55:51,520 It's like the and to engage in these areas is to have to engage 1227 00:55:51,520 --> 00:55:56,800 on the the reality of this, the Gray areas, the the grizzly on 1228 00:55:56,800 --> 00:55:59,520 the ground way that the sausage is kind of made. 1229 00:56:00,080 --> 00:56:03,000 And I think you can try to abstract that away, but it's 1230 00:56:03,000 --> 00:56:04,600 it's. I just think Ethereopia picked 1231 00:56:04,600 --> 00:56:08,600 this fight at a very savvy time. I mean, we just went to war with 1232 00:56:08,600 --> 00:56:11,440 Iran. We bombed a school, you know 1233 00:56:11,520 --> 00:56:13,880 like no all in they have no plan like. 1234 00:56:13,960 --> 00:56:16,360 It was all in Claude's plan. They were about to be wrapped 1235 00:56:16,360 --> 00:56:19,320 into this whole thing like, I don't know, I I just think that 1236 00:56:19,320 --> 00:56:21,200 some of us as if Claude. Planned it because. 1237 00:56:21,200 --> 00:56:23,760 People were deferring to our anyway. 1238 00:56:24,560 --> 00:56:27,920 I don't know. I, I, I'm not trying to get 1239 00:56:28,000 --> 00:56:31,200 overly involved. All I'll say is I have a lot of 1240 00:56:31,200 --> 00:56:33,040 optimism and hope this gets worked out. 1241 00:56:33,320 --> 00:56:36,360 And I have a lot of optimism and hope for how AI can just improve 1242 00:56:36,360 --> 00:56:38,280 the way our government works and improve the way our military 1243 00:56:38,280 --> 00:56:40,640 works when we need to unsheath it. 1244 00:56:41,240 --> 00:56:48,320 And I think that it is our job as citizens to be engaged, to 1245 00:56:48,320 --> 00:56:52,320 vote, to lobby our representatives, to make sure 1246 00:56:52,320 --> 00:56:55,360 that if there are limitations, we want to add around that, that 1247 00:56:55,360 --> 00:56:57,120 those are done. And I think we're going to see 1248 00:56:57,120 --> 00:57:00,080 that play out in the Democratic cycles ahead, as we always have. 1249 00:57:00,440 --> 00:57:03,400 That's how this process works, and we will watch it work. 1250 00:57:03,400 --> 00:57:06,240 Yeah, that's my take. The we could. 1251 00:57:06,640 --> 00:57:08,120 I want to move on to another topic. 1252 00:57:08,200 --> 00:57:11,760 I mean, our last topic before I let you go, just raising money 1253 00:57:11,760 --> 00:57:13,840 from venture capitalists. I feel like I have a lot of VCs 1254 00:57:13,840 --> 00:57:16,760 on on the show and, you know, they tell their story about how 1255 00:57:16,760 --> 00:57:19,640 things work. As a founder, I'm curious like 1256 00:57:19,640 --> 00:57:23,600 what you really look for in VCs or who you think's doing it well 1257 00:57:24,000 --> 00:57:28,360 right now. One thing I try to do is I when 1258 00:57:28,360 --> 00:57:29,920 I talked. When I do like rounds of VC 1259 00:57:29,920 --> 00:57:33,000 catch UPS, either current investors or perspective ones, I 1260 00:57:33,120 --> 00:57:35,800 try to have the same conversation each time, like 1261 00:57:35,800 --> 00:57:38,240 pick a topic. It's very interesting kind of 1262 00:57:38,240 --> 00:57:40,920 doing this side by side and not like it's not one-dimensional 1263 00:57:40,920 --> 00:57:43,280 like 1 is better or worse, just like a lot of different 1264 00:57:43,280 --> 00:57:45,240 dimensions. And one of the things I feel 1265 00:57:45,240 --> 00:57:47,280 like I've I've come to really look for is like first 1266 00:57:47,280 --> 00:57:48,640 principles understanding of things. 1267 00:57:48,640 --> 00:57:51,920 So like we were talking about pricing and so about pricing 1268 00:57:51,920 --> 00:57:56,480 like the, the kind of like thin VC version is like kind of 1269 00:57:56,480 --> 00:57:59,560 regurgitating A blog post and sort of while these other people 1270 00:57:59,560 --> 00:58:02,080 are doing this and these guys are doing this and here's what 1271 00:58:02,080 --> 00:58:04,480 margin they have in all this. I'm always trying to figure out 1272 00:58:04,480 --> 00:58:07,600 like the first principles version of it of like, if we 1273 00:58:07,600 --> 00:58:10,800 really strip it back and understand the technology and 1274 00:58:10,800 --> 00:58:13,600 understand our customers, what do they want? 1275 00:58:13,600 --> 00:58:17,160 And you can kind of tell when AVC has been like really 1276 00:58:17,160 --> 00:58:19,360 involved and very thoughtful with one of their portfolio 1277 00:58:19,360 --> 00:58:22,040 companies where they can say it. They're like, oh, well, at this 1278 00:58:22,040 --> 00:58:24,240 company, the way we looked at it is this. 1279 00:58:24,440 --> 00:58:26,920 And what we found is this, and we had this one customer told us 1280 00:58:26,920 --> 00:58:28,240 this and that made us think about this. 1281 00:58:28,240 --> 00:58:32,400 And you know, like, like they can really like unpack it and 1282 00:58:32,400 --> 00:58:35,400 it's very different from like sort of the blog post version 1283 00:58:35,400 --> 00:58:37,160 synthesis. So that's something I feel like 1284 00:58:37,160 --> 00:58:40,880 I, I really, really look for and someone who's like thinking 1285 00:58:40,880 --> 00:58:44,360 about things clearly and with fresh eyes and people, you know, 1286 00:58:44,360 --> 00:58:49,240 there's like a sort of criticism of VCs like the herd animals or 1287 00:58:49,240 --> 00:58:50,840 whatever. And there is a lot of that look. 1288 00:58:51,440 --> 00:58:54,640 But I'm always interested when I when I talked to someone who's 1289 00:58:54,640 --> 00:58:58,760 got like a really novel insider opinion or a contrarian take cuz 1290 00:58:58,760 --> 00:59:01,680 I at least I know I'm getting like fresh thinking it is. 1291 00:59:02,000 --> 00:59:05,200 I feel like I used to roll my eyes at first principles 1292 00:59:05,200 --> 00:59:07,920 thinking, I think now that I have a business, I mean, you 1293 00:59:07,920 --> 00:59:10,320 know, media is its own sort of animal. 1294 00:59:10,600 --> 00:59:13,200 But there are things where it's like if you apply generic 1295 00:59:13,200 --> 00:59:17,360 principles of like well run media companies, some I are 1296 00:59:17,360 --> 00:59:20,000 lessons I should definitely learn and some you'd say, oh, 1297 00:59:20,000 --> 00:59:24,200 you really don't understand some of the core things that make my 1298 00:59:24,200 --> 00:59:26,520 business work. And you really do need somebody 1299 00:59:26,520 --> 00:59:30,000 who has like empathy for like what is working about your 1300 00:59:30,000 --> 00:59:32,720 business and what is sort of like the core sort of non 1301 00:59:32,720 --> 00:59:34,400 negotiable. And if you have someone just 1302 00:59:34,400 --> 00:59:39,080 sort of sloppily applying like just like heuristics without 1303 00:59:39,080 --> 00:59:42,160 understanding like what's really working it can, it could send 1304 00:59:42,200 --> 00:59:44,000 you on a total. Totally. 1305 00:59:44,080 --> 00:59:46,440 I do a lot of Angel investing. I love it. 1306 00:59:46,440 --> 00:59:49,120 It's like a great, I'm busy with my day job, but it's actually 1307 00:59:49,120 --> 00:59:51,600 like a great kind of like mental stimulus that makes me think 1308 00:59:51,600 --> 00:59:53,840 more about hex and I'm I try to be really careful. 1309 00:59:53,840 --> 00:59:56,240 Like if you're a founder coming to me asking for advice, you 1310 00:59:56,240 --> 00:59:58,240 have to sit through my 5 minute like disclaimer this. 1311 00:59:58,240 --> 01:00:00,120 Is why you shouldn't trust anyone else you are in. 1312 01:00:00,400 --> 01:00:03,440 It in a one. This is like, I'm probably wrong 1313 01:00:03,440 --> 01:00:06,600 taking the greatest stop because I, I just, I like I and what I 1314 01:00:06,600 --> 01:00:10,680 try to do as best I can is tell people, I will tell you what we 1315 01:00:10,680 --> 01:00:12,880 did and why I think it worked or didn't work. 1316 01:00:13,080 --> 01:00:15,520 I will try to unpack from first principles the facts in the 1317 01:00:15,520 --> 01:00:18,080 ground, what we've seen, the data to back it up. 1318 01:00:18,360 --> 01:00:20,720 And then you can draw a conclusion on whether those like 1319 01:00:21,160 --> 01:00:25,680 ground facts, how well those map to you 'cause that I think is 1320 01:00:25,680 --> 01:00:27,520 the thing you're trying to do. And I find this experience 1321 01:00:27,520 --> 01:00:28,960 myself. I'll go talk to founders and get 1322 01:00:28,960 --> 01:00:31,840 advice, talk to three really smart founders and get 5 1323 01:00:31,840 --> 01:00:34,400 different opinions. And it's, it's like what? 1324 01:00:34,400 --> 01:00:37,680 They're all really smart. Like Dylan at Figma said this 1325 01:00:38,240 --> 01:00:41,960 and Kazar, an applied intuition said this and you know, I'm 1326 01:00:41,960 --> 01:00:43,920 like, Oh God, that there are opposite things. 1327 01:00:43,920 --> 01:00:45,600 What do you do? And it's like, well, you did you 1328 01:00:45,600 --> 01:00:50,080 really understand the like grounding thing and, and the 1329 01:00:50,080 --> 01:00:53,320 path dependency. And it's the other part of this 1330 01:00:53,320 --> 01:00:56,480 job is like, it's a lot of luck and it's a lot of circumstance. 1331 01:00:56,480 --> 01:00:59,280 And you know, you ask, how did you find that great executive? 1332 01:00:59,280 --> 01:01:01,960 Oh, well, I did the search like this, but like, also like 1333 01:01:01,960 --> 01:01:06,200 someone happened to be available on the market and you know, 1334 01:01:06,200 --> 01:01:09,600 it's, it's, it's, it's always like the survivorship bias thing 1335 01:01:09,600 --> 01:01:13,040 too of like, well, this worked for this person, therefore it'll 1336 01:01:13,040 --> 01:01:14,640 work for me. Or the failureship bias thing 1337 01:01:14,640 --> 01:01:17,480 that you also hear from a lot of VCs, which is, well, this other 1338 01:01:17,480 --> 01:01:20,040 company tried to do that and it didn't work, Therefore it won't 1339 01:01:20,040 --> 01:01:21,600 work for you. And So what was the first 1340 01:01:21,600 --> 01:01:23,480 principle of why it did or didn't work? 1341 01:01:24,280 --> 01:01:25,880 And can you really understand that? 1342 01:01:26,000 --> 01:01:30,240 That's like a a thing I'm always trying to grasp for as best I 1343 01:01:30,240 --> 01:01:32,400 can and usually failing, but sometimes get it ready. 1344 01:01:33,000 --> 01:01:34,440 Gary, thank you for coming on the show. 1345 01:01:34,480 --> 01:01:35,880 Thank you, this is fun. Great. 1346 01:01:36,080 --> 01:01:38,800 That's our episode and thanks for sticking around to the end. 1347 01:01:38,800 --> 01:01:41,680 Please, if you've made it this far, you've got a like comment, 1348 01:01:41,680 --> 01:01:44,160 subscribe. Excited to grow the channel? 1349 01:01:44,160 --> 01:01:47,680 And of course, you can find our writing and reporting on sharps 1350 01:01:47,680 --> 01:01:51,200 and venture capital at newcomer.co. 1351 01:01:51,680 --> 01:01:53,600 We also host events. You can check out what we're 1352 01:01:53,600 --> 01:01:57,040 doing at Newcomer dot events, share their podcasts, help us 1353 01:01:57,320 --> 01:02:00,800 get distribution, support the channel, comment support, like 1354 01:02:00,800 --> 01:02:02,320 comment, subscribe. You know, you know the deal. 1355 01:02:03,320 --> 01:02:04,840 Thanks. Thanks for being on the journey 1356 01:02:04,840 --> 01:02:06,120 with us. All right, see you next week.