Full Transcript for VC: How VCs Evaluate Technical Founders (TAM, Moats & Diligence), with Amanda Robson, Founder and GP of Modern Technical Fund

thread on this. 00:02:02.400 --> 00:02:18.319 They're one of the more active LPs in the venture ecosystem over the last 20 years, uh, released some data just this week that uh for the first time in their over 20-year cohort, there is fewer venture capital funds in the market as of 2025 than there was the year before. 00:02:18.400 --> 00:02:25.280 So there is more venture capital funds going out of business or no longer actively investing than there are coming to market. 00:02:25.439 --> 00:02:32.159 And looking at some pitchbook data to verify that, there's over 10,000 funds on paper at least investing in the US. 00:02:32.319 --> 00:02:37.199 And if you dig a little bit deeper, only half of those are actively investing. 00:02:37.360 --> 00:02:43.199 And it just goes to show, I think, the have and have nots of some of the ecosystem at large, but also how difficult it is. 00:02:43.360 --> 00:02:47.439 You know, they shared some data on graduation rates from fund one to fund two. 00:02:47.759 --> 00:02:51.599 And keep in mind, too, that these graduation dates, they're really good data points. 00:02:51.680 --> 00:02:54.400 Uh, but these are from 1990 to 2021. 00:02:54.560 --> 00:03:00.879 I'm fascinated to see what these look like five years later when you go through, you know, the market correction of 2022, 2023. 00:03:01.039 --> 00:03:09.039 We've seen some preliminary numbers at just how low the graduation rates have been for venture funds or new venture funds started over the last few years. 00:03:09.199 --> 00:03:13.599 So think since post the 2022 correction to today in early 2026. 00:03:13.759 --> 00:03:17.680 But these are the historical rates, which still um shows how challenging it can be. 00:03:17.840 --> 00:03:21.120 So fund one to fund two, just a 50% graduation rate. 00:03:21.439 --> 00:03:31.439 Fund one to fund four, which is the, you know, you probably crossed the chasm to being a you know real fund who's been operating in the marketplace for a decade or so, only 17%. 00:03:32.080 --> 00:03:37.599 And then the fund one to fund eight, where you have become a name brand in the industry, only four percent. 00:03:37.759 --> 00:03:40.639 Uh so it's it's not uh not an easy road. 00:03:40.800 --> 00:03:45.759 And um, I think we're seeing both ends of the venture ecosystem in a really acute manner today. 00:03:45.840 --> 00:03:46.240 Aaron Powell Yeah. 00:03:46.319 --> 00:03:49.599 I mean, we were very fortunate to oversubscribe our previous fund. 00:03:49.759 --> 00:03:58.879 You know, certainly seeing it when we talk to peers in the emerging manager space, that uh most of them were not able to do that. 00:03:59.039 --> 00:04:05.439 A lot of them had to kind of tweak their fund size downward to get to kind of a minimum viable fund over the past few years. 00:04:05.520 --> 00:04:18.560 And I think you're you're definitely seeing the haves and have nots when you get Andreessen with$15 billion, uh Lightspeed with$9 billion, and some of these other funds that are I saw Land from Basis set, somebody tweeted her fund was raised in a day. 00:04:18.800 --> 00:04:39.360 And you know, some of it could just goes to show if you're you're in a certain set of the right companies and you get DPI quickly and um you build a reputation for being the person in a space that is you know certainly the space to be in right now, and uh you know, props to LAN for being kind of early and and very deep in the in the AI space, that it gets a lot easier for you. 00:04:39.519 --> 00:04:42.560 So I think there's obviously this kind of haves and have nots. 00:04:42.639 --> 00:04:46.800 It's certainly happening in the fund and firm building space right now. 00:04:47.120 --> 00:04:56.399 As we go into a little bit more of like what's happening in the day-to-day, another thing that we're seeing right now is the whole SaaS is dead conversation. 00:04:56.800 --> 00:05:39.519 And you're seeing that in the public markets with uh you know, HubSpot's down to trading, uh, I think like a Forex, uh uh multiple, um, don't know what it is today, but you know, Datadog, they they have Zscaler, kind of the SaaS companies of the past few years that are kind of suppressed valuations, and it's kind of a reminder back to this time in 2016, although that rebounded, you know, now we have, I guess, another boulder in the way, which is AI, AI up-and-comers that are coming up and essentially um disrupting maybe not even the companies, but the notion that these companies are going to be worth what they're worth in a couple of years if um you know AI continues to trend in the the direction that it is. 00:05:39.759 --> 00:05:50.240 One of the interesting things that we saw recently online that I I tweeted about was Airtable completely reinvented the company and the product from scratch. 00:05:50.399 --> 00:05:51.920 I thought that was so gutsy. 00:05:52.079 --> 00:06:02.480 You're seeing a lot of companies, I think, in the incumbent SaaS arena say, okay, we'll inject AI into our product or we'll do a co-pilot or something like that. 00:06:02.639 --> 00:06:04.560 And Airtable is one of the first ones that I've seen. 00:06:04.639 --> 00:06:06.160 It's like, nope, that's not enough. 00:06:06.319 --> 00:06:10.879 We're gonna have to rebuild this platform from scratch, leveraging AI. 00:06:11.040 --> 00:06:15.680 And you even saw with Microsoft how Satya kind of was like, yeah, copilot's not enough. 00:06:15.759 --> 00:06:20.879 I'm gonna go be PM of of this product until it is what it should be. 00:06:21.120 --> 00:06:34.160 I think there's a lot of SaaS companies have been around since let's call it 2015, 2017, even 2021, that are gonna have to take a look in the mirror and say, hey, what would we build from scratch if we were rebuilding this product today? 00:06:34.319 --> 00:06:35.680 And maybe that's what we need to build. 00:06:35.759 --> 00:06:37.519 Maybe we need to cannibalize what we already built. 00:06:37.759 --> 00:06:38.399 What

are you seeing? 00:06:38.480 --> 00:06:39.680 What are your thoughts on that? 00:06:39.759 --> 00:06:41.519 Aaron Powell You can look at it two different ways. 00:06:41.680 --> 00:06:46.399 I mean, there's the one part of it is, and you mentioned it, and Airtable has done a fantastic job. 00:06:46.560 --> 00:07:02.959 There's going to be other companies and founders and executive teams that answer the bell, basically, which is a realization that just bolting on a few cool AI workflows on your traditional seat-based price, you know, enterprise software is likely not enough for a lot of these companies. 00:07:03.040 --> 00:07:08.639 And it's not just the private markets that you know sometimes can be ahead of the curve or should be ahead of the curve on a lot of these things. 00:07:08.800 --> 00:07:11.120 The public markets are reacting to it quickly as well. 00:07:11.360 --> 00:07:12.639 I mean, some data to back that up. 00:07:12.720 --> 00:07:15.439 The Meritech Public Software Index and data is fantastic. 00:07:15.519 --> 00:07:21.040 I know we had Alex Clayton on earlier in the series, but they did this really uh great split. 00:07:21.199 --> 00:07:24.959 So they took the public market software index and they put it into two buckets. 00:07:25.199 --> 00:07:29.040 So companies with AI tailwinds and companies without AI tailwinds. 00:07:29.199 --> 00:07:36.399 So since January of 2024, two years, the companies with AI tailwinds uh up 56% overall. 00:07:36.480 --> 00:07:39.759 Uh, those without down 22%, and that's accelerating. 00:07:40.000 --> 00:08:12.079 They've never seen a wider spread from the top of multiple companies which have AI tailwinds, your sort of Palantirs, your snowflakes, there's a number of others, and the ones that are facing serious questions about their business model, you know, their place within the priority stack of vendors of their particular particular corner of software and technology, given that there's up-and-AI native companies that are trying to take that budget, take that share of mind share within their particular corner of software. 00:08:12.319 --> 00:08:28.480 The optimistic way to look at it is if I was a founder today, if I was an investor today, if I was an operator joining a startup, there's some hope in that signal in the sense that that's the public markets validating that there is meaningful disruption happening in the private markets that's soon going to end up in the public markets. 00:08:28.639 --> 00:08:33.759 Not this death to B2B software, but maybe death to the old archetype of B2B software. 00:08:33.919 --> 00:08:54.080 And the current incumbents either answer the bell and you're an air table and you reorganize your product, your mission, your vision, uh, and re-accelerate as a result, or you're going to get caught by one of these new up-and-coming AI native companies that's got a better product, better workflows, building and moving faster, uh, different business model and structure. 00:08:54.320 --> 00:09:01.600 And, you know, those are the ones that if I'm an operator today, you know, choosing where I'm going to work next, or I'm an investor choosing the next great company. 00:09:01.679 --> 00:09:06.879 I think that's as difficult it is for our public market investors or friends that are public market investors. 00:09:06.960 --> 00:09:12.080 I think it's a really exciting uh opportunity for the AI native startup ecosystem. 00:09:12.320 --> 00:09:13.440 Yeah, absolutely. 00:09:13.679 --> 00:09:18.799 So Debbie Downer on the venture stuff, Debbie Downer on the SaaS stuff. 00:09:18.960 --> 00:09:23.440 Not even going to get into who's going to get jobs where once everything is AI-ified. 00:09:23.600 --> 00:09:40.399 So uh, but it is a good segue into the Robbie episode of the podcast because I think one of the things she talks about uh at length and is really disciplined on is avoiding what she calls AI theater. 00:09:40.639 --> 00:09:51.840 So when she's diligencing a company, how do you make sure that this is actually kind of AI at the core of the product, real infrastructure versus this hand-wavy kind of AI theater? 00:09:52.000 --> 00:10:03.919 Oh, this is uh AI, but it's really more of like if-then statements or not as much of actual e-use case or uh deep use cases of an LLM or kind of AI functionality. 00:10:04.240 --> 00:10:05.919 And we've seen this before as investors too. 00:10:06.080 --> 00:10:07.519 I mean, I think this is kind of everywhere. 00:10:07.679 --> 00:10:15.759 I think it's in vogue to slap AI on a product and say, hey, this is AI, but it's another thing to really get in the weeds. 00:10:16.000 --> 00:10:25.519 She's got a great network of technical founders and um technologists in different roles across businesses that she's able to diligence these companies with. 00:10:25.600 --> 00:10:27.519 So she's developed a great eye for it. 00:10:27.600 --> 00:10:34.480 Obviously, she's been in the BC game for a while, but thought it was a very thoughtful take on how she sizes up um AI deals. 00:10:34.559 --> 00:10:35.519 And uh I don't know. 00:10:35.679 --> 00:10:38.159 Any any key takeaways for you uh from the episode? 00:10:38.559 --> 00:10:41.519 Yeah, it was I just great first principles way to approach it. 00:10:41.600 --> 00:10:46.240 Like she approached it from okay, what is my definition for an AI native company? 00:10:46.480 --> 00:10:47.840 Because people have different definitions. 00:10:47.919 --> 00:10:54.720 It seems like it would be obvious, and and it's actually non-obvious when you talk to different investors or different founders, they'll give you a different answer. 00:10:54.879 --> 00:11:02.799 And I think what I liked about her definition was it's not just young companies started within the last couple of years and everyone there is AI native. 00:11:02.879 --> 00:11:03.840 That's not necessarily true. 00:11:04.080 --> 00:11:10.320 It's not people that are building their own models

internally, even though those are quite clearly AI native companies. 00:11:10.480 --> 00:11:14.399 But it also can be a company, I think she used Superbase as an example, which is a great one. 00:11:14.639 --> 00:11:28.000 The product itself is not necessarily AI native, but it is obviously powering so many AI native workflows from a data perspective that you would treat it as an AI company in the sense that it's riding the exact same tailwinds. 00:11:28.159 --> 00:11:44.639 So their product itself isn't necessarily, you know, AI-ified with all these different workflows and doesn't have to be per se, as long as it's sitting in the right part of the infrastructure stack for companies that are using it and becomes of you know a vital part of the AI story for a lot of other, you know, of their customers and a lot of the rest of the ecosystem. 00:11:44.879 --> 00:12:11.360 What was cool about the way she diligences it too is she doesn't do customer references traditionally, because she's got this network of buyers, she can go in and make an introduction to somebody who would be a customer, watch the founder pitch live, get the response of somebody who is a almost fresh perspective, fresh mind, and not the customer who gives you a rosy reference because they don't want to lose access to the tool, even though that's not necessarily a bad thing. 00:12:11.519 --> 00:12:12.720 Um, and we see that all the time. 00:12:12.879 --> 00:12:30.720 I mean, it's the power of having these 300 operators across AI and software and the technology landscape on GTM fund side of things, where, you know, it's great to do the customer reference side of things, but what can be even deeper and more meaningful sometimes is, hey, let's introduce you to somebody who's sold in this category before. 00:12:30.960 --> 00:12:34.799 Let's introduce you to somebody who would be a buyer and be a net new customer. 00:12:34.960 --> 00:12:42.159 You know, usually the founder loves it because you're giving them either a net new lead potentially or somebody who can give them advice on their space. 00:12:42.240 --> 00:12:52.080 But from our side of things, when we're making investment decisions, it gives you somebody with you know expertise within a market and a fresh perspective on hey, is this novel? 00:12:52.240 --> 00:12:52.879 Is this interesting? 00:12:53.039 --> 00:12:54.399 Would you create budget for it? 00:12:54.559 --> 00:12:56.639 You know, how how does the founder position and pitch it? 00:12:56.799 --> 00:12:57.679 Good takeaways. 00:12:57.840 --> 00:13:02.960 All right, let's get into the episode with Amanda Robbie Robson from Modern Technical Fund. 00:13:03.200 --> 00:13:03.919 Thanks for being here. 00:13:04.159 --> 00:13:04.559 Of course. 00:13:04.720 --> 00:13:05.440 Happy to be here. 00:13:05.600 --> 00:13:05.919 Yeah. 00:13:06.159 --> 00:13:07.600 So new fund. 00:13:07.759 --> 00:13:08.399 Very exciting. 00:13:08.639 --> 00:13:09.200 New fund. 00:13:09.360 --> 00:13:17.519 Though it feels like it's new-ish because technically it like closed earlier this year, but I'm just, you know, riding up the 2025 launch after launch. 00:13:17.840 --> 00:13:19.360 What eight deals so far? 00:13:19.600 --> 00:13:20.480 Actually, nine. 00:13:20.720 --> 00:13:20.960 Nine. 00:13:21.039 --> 00:13:21.200 Yeah. 00:13:21.679 --> 00:13:23.600 Sneaky, sneaky last deal since the year. 00:13:23.759 --> 00:13:25.120 Sneaky last deal just got out. 00:13:25.279 --> 00:13:25.919 It came in. 00:13:26.159 --> 00:13:26.399 Yeah. 00:13:26.639 --> 00:13:27.039 Oh yeah. 00:13:27.120 --> 00:13:29.120 So how many do you think you'll actually do from this fund? 00:13:29.360 --> 00:13:30.879 So the fund will be about 25. 00:13:31.039 --> 00:13:35.679 So I am actually I I just passed the one year mark since first close. 00:13:35.919 --> 00:13:39.759 So I'm pretty much on pace, and then from a dollars deployed on pace too for three years. 00:13:40.000 --> 00:13:40.320 Awesome. 00:13:40.399 --> 00:13:41.440 Tell us about the fund. 00:13:41.919 --> 00:13:52.960 So um I started the fund technically like a year and a half ago, it started getting conceptualized, but really started fundraising for it and everything in kind of like mid to late 2024. 00:13:53.120 --> 00:13:56.080 My background, I've been in venture for a long time, for 10 years. 00:13:56.240 --> 00:13:58.080 It's funny because it's basically been my only job. 00:13:58.240 --> 00:14:01.440 So I have no other skill other than BC and like, what is that? 00:14:01.600 --> 00:14:04.240 It's like all these different random skills together. 00:14:04.399 --> 00:14:11.360 But I started the fun because I saw this gap for technical founders in building something that was hyper-tailored to helping them move faster at the earliest stages. 00:14:11.440 --> 00:14:12.639 And a lot of that's through network. 00:14:12.720 --> 00:14:19.440 So I built out a network of technical buyers and technical sellers who work really closely with my founders on getting their first products to market. 00:14:19.519 --> 00:14:20.960 And it's been super effective so far. 00:14:21.039 --> 00:14:44.320 So of the nine companies, for every one of them, we've either helped with a really key hire, either sourcing it, closing it, or key design partners for some multiple, um, or helped get them really good advice, whether it comes to like pricing, go to market, how to actually do sales, because we brought in, I brought in a bunch of folks onto my team as advisors who were the first like sales or marketing hires at awesome like technical companies like Upland or Drata. 00:14:44.960 --> 00:14:46.480 Uh so yeah, that's what the fund is. 00:14:47.039 --> 00:14:48.000 Love the network model. 00:14:48.240 --> 00:14:54.000 So it's technical founders uh and technical buyers was the marketplace or the the network. 00:14:54.240 --> 00:14:55.039 Yeah, the network. 00:14:55.120 --> 00:15:03.840 Um, and it's uh all cyber data or dev

tool-oriented founders, and I'm writing anywhere from 500k to million dollar checks and all super early, so pre-seed or seed. 00:15:04.000 --> 00:15:09.919 And then focus areas are the US and Israel, but all these really companies are focused on the US market from a go-to-market standpoint. 00:15:10.240 --> 00:15:11.679 And it's technical founders only. 00:15:11.919 --> 00:15:12.639 Technical founders only. 00:15:14.399 --> 00:15:14.559 Yeah. 00:15:14.879 --> 00:15:15.279 Yeah, yeah, yeah. 00:15:15.279 --> 00:15:18.720 And that's really been the focus of um basically my entire investing career. 00:15:18.960 --> 00:15:23.440 So when I was at Norwest, which is the first VC fund I was at, it's a highly technical team. 00:15:23.600 --> 00:15:27.200 Like the partners I worked with were all like ex Cisco and like networking. 00:15:27.279 --> 00:15:30.159 So like you couldn't get by if you didn't understand technical founders. 00:15:30.320 --> 00:15:36.159 And I kind of found my footing being kind of like the business counterpart to technical founders at the earliest stages. 00:15:36.320 --> 00:15:38.639 And so it just kind of happened that way. 00:15:38.720 --> 00:15:49.440 And I kind of built up my first three and a half years at Norwest working with technical founders, was the security and dev tool lead at Cowboy Ventures for five years and then created this fund. 00:15:49.840 --> 00:15:57.200 I definitely want to go to your background at these other firms, but um my first question, I guess, is what is a technical founder? 00:15:57.360 --> 00:16:00.159 Like how do you how do you even size up somebody's technical jobs? 00:16:00.320 --> 00:16:03.360 Like it's one thing to see on their LinkedIn that they had a technical role. 00:16:03.519 --> 00:16:10.639 It's another thing to be able to, I mean, you're pre-seed seed stage, so they may not even have any product yet that they built from scratch. 00:16:10.799 --> 00:16:12.240 So how do you size that up? 00:16:12.639 --> 00:16:12.960 Yeah. 00:16:13.120 --> 00:16:15.120 Uh so really it's like two things. 00:16:15.200 --> 00:16:18.879 And I I would think that most people would agree and have the same sense of the first one. 00:16:18.960 --> 00:16:24.320 It's an elite engineer, um like an elite builder, and also an engineer that has really good product sense. 00:16:24.559 --> 00:16:28.159 So they can see what a product should look like from end to end. 00:16:28.320 --> 00:16:34.480 And then the other piece that I really focus on are engineers that can be highly commercial and are really focused on solving customer problems. 00:16:34.720 --> 00:16:41.039 Probably the best example of a company that I've worked with or a founder that I've worked with that's like that is the CEO Drata Adam. 00:16:41.200 --> 00:16:45.360 He's like insanely smart when it comes to products and engineering. 00:16:45.440 --> 00:16:51.039 But actually, I think like his superpowers is his ability to look at what a customer needs and translate that into product specs. 00:16:51.279 --> 00:16:56.480 So that's kind of what I look for as someone who's a builder, but they're incredibly like customer user oriented. 00:16:56.799 --> 00:17:04.079 And are the teams almost always only technical, or do you often find some one is technical, one is go to market? 00:17:05.200 --> 00:17:16.000 Almost always at the stage I'm investing in, um, they'll split up who's leading engineering and kind of the main build and who's doing go-to-market, but they're they're both technical. 00:17:16.400 --> 00:17:21.599 So usually the CEO, and it's not always like this, but like typically the CEO be the one leading go-to-market. 00:17:21.920 --> 00:17:23.920 So it means that they have to learn go-to-market. 00:17:24.240 --> 00:17:33.359 And I know this is a huge thing that you guys work on too with your founders, but that's a huge part of the role that I can kind of play and help them with is figuring out what amazing go-to market is like. 00:17:33.440 --> 00:17:37.440 And they have those instincts and they can really build towards solving customer problems. 00:17:37.599 --> 00:17:44.720 But a lot of the baseline things around how do you actually manage POCs or sales cycles or like how do you think about going after leads or messaging? 00:17:44.799 --> 00:17:46.960 I I work really closely with my founders on that. 00:17:47.119 --> 00:17:53.680 But yeah, it's almost always like multiple engineer, like technical founders, and then one of them will take on this go-to-market role. 00:17:54.000 --> 00:17:57.440 How do you then I guess work with them on? 00:17:57.599 --> 00:18:07.279 So, for example, you've got technical founders you you trust implicitly because you fund them, you did your diligence, they start to build, they go to market. 00:18:07.680 --> 00:18:14.799 Do you kind of say, hey, you go do what your instincts tell you to do, and I will support with my advice, my network, all that? 00:18:14.960 --> 00:18:27.759 Or do you say, hey, I've got nine portfolio companies and I've been an investor and I've seen kind of this playbook before, and like here's what the best companies are doing, and try and push that, you know, or the companies in the direction. 00:18:27.920 --> 00:18:31.440 Hey, PLG is really important for a product like this because of X, Y, and Z anecdotes. 00:18:31.519 --> 00:18:34.880 Like you should do PLG even if they weren't considering that before. 00:18:35.200 --> 00:18:36.799 Oh, yeah, that's a really good question. 00:18:37.119 --> 00:18:49.200 I I will never I well, first, I think that you kind of earn the right to like through trust and through giving good advice and through your own expertise to give that kind of directive advice for founders. 00:18:49.359 --> 00:18:57.519 Um, usually what ends up happening is they will have a sense of what they need and they'll have a sense of what they're good at and what they're not good at. 00:18:57.759 --> 00:19:03.359 And so I'll come in and

say, okay, like for instance, I was actually just helping um one of my companies with a head of sales search. 00:19:03.680 --> 00:19:07.599 And they were, and I it's really like probing and asking a lot of questions. 00:19:07.680 --> 00:19:10.160 So they were like, okay, here's some of the candidates we're looking at. 00:19:10.319 --> 00:19:13.359 And I'm looking at them, I'm like, so none of them have been at exceptional companies. 00:19:13.440 --> 00:19:18.319 And if you look at your engineering team, they're all from exceptional companies, they're all like top one to five percent engineers. 00:19:18.640 --> 00:19:23.839 If you look at these people's profiles, they don't really scream like top one to five percent sales leaders. 00:19:24.079 --> 00:19:31.039 And so then I introduce them to a few like top, top sales leaders who are part of my like advisor network, and then that helps reorient them. 00:19:31.200 --> 00:19:33.279 And then I'll also help with like their process. 00:19:33.359 --> 00:19:39.519 So, with in that case, then helped interview a bunch of folks, gave my direct feedback, helped them kind of understand what greatness looked like. 00:19:39.680 --> 00:19:43.359 And then they're but it's not me kind of telling them like, hey, you need to figure this out. 00:19:43.440 --> 00:19:52.319 Like they know what they know and what they don't know, and it's really helping guide them based on the things that I might know better by working with really world-class technical sales teams before. 00:19:52.559 --> 00:19:57.119 Um, but yeah, it's it's usually not so directive of like, hey, you need to go like do PLG. 00:19:57.200 --> 00:20:02.079 It's usually like they know what they need, they know that they need to like find someone who's amazing, but they don't know how. 00:20:02.240 --> 00:20:03.279 So I really help with the how. 00:20:03.680 --> 00:20:05.519 Yeah, advice is a is a funny thing like that. 00:20:05.680 --> 00:20:21.200 I mean, we definitely want to set our founders up to you know, meet these CROs and CMOs that we have in our our network, and we also all often vet exactly like who to connect to who that's gonna be relevant like that and what kind of advice they're they're gonna provide. 00:20:21.599 --> 00:20:29.839 What we like to do is more like anecdotes, you know, like stories, like, oh, in in the past, like this was important, or here's what we're seeing from the marketplace, things like that. 00:20:30.000 --> 00:20:34.079 Without saying like you need to do this, this is the you have to go and you should go. 00:20:34.160 --> 00:20:42.799 And like we kind of are more like, hey, this is what's happening in the marketplace, or this is you know what we're seeing as a best practice, but we trust you, we invested in you. 00:20:43.119 --> 00:20:46.240 You make the decision, you know your space better, you know your product better. 00:20:46.480 --> 00:20:46.799 Yeah. 00:20:47.119 --> 00:20:49.839 Um I want to get into your background. 00:20:50.000 --> 00:20:53.119 So started out Norwest, started the career at Norwest. 00:20:53.440 --> 00:20:56.000 I had done uh two years in banking before that. 00:20:56.160 --> 00:20:56.319 Okay. 00:20:56.960 --> 00:20:59.039 But other than that, yeah, it's all been venture. 00:20:59.279 --> 00:21:05.359 And actually, how I got into uh banking on the West Coast was like really funny, and actually a skill that helped me a lot. 00:21:05.440 --> 00:21:06.480 I was in I'm from Canada. 00:21:06.720 --> 00:21:10.640 So I grew up in Canada, went to school in Canada, didn't even really think about coming to the States. 00:21:10.880 --> 00:21:18.559 And I did a summer in banking in Toronto and realized that if you did um banking in Canada, you'd be working with metals and mining or oil and gas companies. 00:21:18.640 --> 00:21:19.599 Like that's all we had at the time. 00:21:19.680 --> 00:21:22.079 There's more tech now, but like this is like 12 years ago. 00:21:22.319 --> 00:21:33.680 Um, so I just started cold calling tech like banks and on the West Coast, and like shockingly, people were just very open to it and were like, who's this random Canadian girl who wants to work here? 00:21:33.839 --> 00:21:36.319 So that's how I got my job in banking on the West Coast. 00:21:36.480 --> 00:21:40.240 Um, so I did that for two years, and then I loved working with founders, and that's how I ended up in the U.S. 00:21:40.400 --> 00:21:44.720 Once you're in San Francisco, it's you know a small amount of time before you go from banking to VC, right? 00:21:44.960 --> 00:21:45.200 Oh, yeah. 00:21:47.119 --> 00:21:51.039 And then Norwest, then cowboy, working with uh Aileen. 00:21:51.279 --> 00:21:56.559 So what do you what are you bringing from that experience to now your own fund? 00:21:56.960 --> 00:21:57.759 Oh, so much. 00:21:57.920 --> 00:21:59.839 Um, so much from both Norwest and Cowboys. 00:22:00.160 --> 00:22:02.799 Cowboy, but I was at Cowboy for five years. 00:22:03.119 --> 00:22:17.119 And I learned so much there that I think really helped me not just with like fine-tune my investing because I was all focused on seed and uh pre-seed there versus at Norwest, we were doing kind of everything early stage, which ranged from seed to series A, series B. 00:22:17.359 --> 00:22:22.480 But at Cowboy, um, we were just doing seed, and I also had to, I was a first sector specialist investor. 00:22:22.559 --> 00:22:25.200 So I came in to cover um DevTools and Cyber. 00:22:25.359 --> 00:22:28.240 And so learned a lot about how many sector specialists were there? 00:22:28.480 --> 00:22:29.359 So I was the first. 00:22:29.519 --> 00:22:32.720 When I joined, they were two GPs, they were both generalists. 00:22:32.799 --> 00:22:39.119 Um, and then I came in as a first sector specialist, and then we brought in another sector specialist, Jill Williams, who covered FinTech after. 00:22:39.200 --> 00:22:43.920 So that kind of became the model for like

up-and-coming investors for them to be sector specialists. 00:22:44.079 --> 00:22:53.279 Um, so but I learned so much about brand building, and that's where I started the open source startup podcast, started building networks of CISOs, CTOs, my technical go-to-market network. 00:22:53.359 --> 00:23:00.880 Um, and that whole brand building kind of exercise really helped a lot when it came to, you know, building not just my brand, but an independent fund brand. 00:23:00.960 --> 00:23:04.799 Um, and then also uh everything around like the fund model. 00:23:04.880 --> 00:23:12.720 So if you're at a big fund, like I was at Norwest, but kind of pick any of your big funds, you have no real idea about the overarching fund model. 00:23:12.799 --> 00:23:14.160 Like you just think about your own PL. 00:23:14.240 --> 00:23:15.519 Like, how are my companies doing? 00:23:15.839 --> 00:23:20.720 But like Cowboy and funny enough, like my model is very similar to Cowboys, like 25-ish companies. 00:23:20.880 --> 00:23:25.440 Um, we like lived in the fund model, and you wanted every company to be able to return your fund when you first invest. 00:23:25.759 --> 00:23:31.279 And you're looking at dilution along the way, you're looking at follow-ons, you're trying to like make sure you have enough to cover your fall-ons. 00:23:31.440 --> 00:23:44.640 And so that experience has like was so vital to how I did my fund construction, but also how I think about the fun math and the kinds of exits that this fund needs in order to like return the fund, hopefully have like a really good return profile. 00:23:44.799 --> 00:23:51.039 So, yeah, that was like insanely valuable, even though at the time it was like painful because I'm like, oh, at Norwich didn't have to do any of this. 00:23:51.279 --> 00:23:55.200 Like, well, what so like what exactly did you bring from like a brand standpoint? 00:23:55.440 --> 00:24:00.640 Because I think the branding is is great for modern technical fund uh MTF. 00:24:00.880 --> 00:24:02.400 I don't know why I always think it's make the future. 00:24:02.640 --> 00:24:03.440 Did you do an MTF? 00:24:03.759 --> 00:24:04.880 No, oh I like that though. 00:24:05.039 --> 00:24:05.680 Make the future. 00:24:06.160 --> 00:24:07.359 So do like events on that. 00:24:07.519 --> 00:24:07.680 Yeah. 00:24:08.160 --> 00:24:08.880 You know what's funny? 00:24:09.039 --> 00:24:22.400 I think um one of the things that I uh I've like learned about brand from friends who are much better at brand than me is like you can make a lot of brand things work, but you want it to be super authentic to you. 00:24:22.640 --> 00:24:26.480 And so when I started the open source startup podcast, it's so direct. 00:24:26.559 --> 00:24:27.680 Like I'm a very direct person. 00:24:27.759 --> 00:24:30.240 And actually, the founders I worked with are also very direct. 00:24:30.400 --> 00:24:35.680 Engineers like to know like the name to tie to the thing, and it's like they understand it

very quickly. 00:24:35.920 --> 00:24:38.720 So, Modern Technical Fund was actually a placeholder name. 00:24:38.880 --> 00:24:40.880 I was like, I want to build a modern technical fund. 00:24:41.119 --> 00:24:43.839 And then I was like, why don't I like that's literally what I'm trying to do? 00:24:44.000 --> 00:24:44.160 Yeah. 00:24:44.400 --> 00:24:46.319 And then I even like coded up my website. 00:24:46.400 --> 00:24:47.759 It's like the most direct thing ever. 00:24:47.920 --> 00:24:52.799 It's like we invest in these regions, this check size, here are the companies, here are the quotes, here's it, like, here's the network. 00:24:52.880 --> 00:24:56.079 Literally, here are all the LinkedIns of everybody who's like a formal advisor. 00:24:56.240 --> 00:24:57.680 And it's like, there's no fluff. 00:24:58.079 --> 00:24:58.720 It's very direct. 00:24:58.799 --> 00:25:00.079 The website is very direct. 00:25:00.319 --> 00:25:07.599 I like that it was like, um, if we're not the most impactful check on your cap table, then we fucked up. 00:25:07.920 --> 00:25:09.119 Because Lou says it right there on the website. 00:25:09.359 --> 00:25:11.759 It's funny too, because I co-invest with so many amazing people. 00:25:11.839 --> 00:25:14.480 And I'm just like, it's not a sudden you, but I'm just like, I really want to be able to do that. 00:25:14.640 --> 00:25:15.200 I'm competitive. 00:25:15.440 --> 00:25:15.680 Yes. 00:25:15.839 --> 00:25:16.000 Yeah. 00:25:16.079 --> 00:25:25.119 And you want like, especially at the earliest stages, those key hires when it's like a team of like 10 or like key design partners, like that's everything for a company. 00:25:25.279 --> 00:25:33.119 Like I closed um one of our like best logo design partners for actually the company that I just invested in, and it's like so meaningful to them. 00:25:33.200 --> 00:25:35.119 Cause that's like life or death at that stage. 00:25:35.359 --> 00:25:36.000 Absolutely. 00:25:36.240 --> 00:25:37.920 What about um people? 00:25:38.319 --> 00:25:39.680 So is it just you? 00:25:39.839 --> 00:25:41.680 Do you have is it is it you and about it? 00:25:41.759 --> 00:25:42.640 I say it's the royal we. 00:25:42.799 --> 00:25:43.519 I'm like, it's just me. 00:25:44.000 --> 00:25:46.640 That's how it was for when I started the media company back in the day. 00:25:46.720 --> 00:25:50.799 And it was nice because I'd always play off to like, ah, yeah, you know, legal won't let us do that. 00:25:50.960 --> 00:25:53.920 It's like somebody's gotta be, it can't just be me, right? 00:25:54.079 --> 00:25:58.559 But um so do you plan on growing a team, building a team? 00:25:58.640 --> 00:26:00.160 What's the what does that look like? 00:26:00.240 --> 00:26:03.440 And is there you know, you have fun ones 22? 00:26:03.599 --> 00:26:03.759 Yeah. 00:26:03.920 --> 00:26:04.799 Where does that go? 00:26:05.119 --> 00:26:06.240 It's a really good question. 00:26:06.400 --> 00:26:09.680 I'm just gonna be so real

with you because this is like something in fundraising. 00:26:09.839 --> 00:26:13.680 Like every LP like asks you, and they're just like, oh, like what does this become? 00:26:13.839 --> 00:26:20.000 And to be totally honest, when I started out, my initial thinking was, you know, I could one of two paths. 00:26:20.160 --> 00:26:29.039 I could either keep this being like a solo thing, or I could go and try and build the next great, like technical oriented fund, like the next like bold start, cyber starts, amplify, whatever. 00:26:29.359 --> 00:26:42.799 The the last year I probably had the most fun and the most effective investing ever because for my check size with like pre-seed and seed rounds the way they are, I don't have to lead and I can still have this like the same return profile as like a fund that's much bigger. 00:26:43.039 --> 00:26:49.839 So I'm open to bringing other people on, but it would have to be someone I think who has to who can own everything end to end. 00:26:50.000 --> 00:26:58.160 Like I think it's really hard at the earliest stages to break up the investing role and be like, oh, I'm gonna have junior people who are gonna source and or like I'm just gonna do the board work, whatever it is. 00:26:58.240 --> 00:26:59.839 Like, I kind of want to do everything end-to-end. 00:26:59.920 --> 00:27:06.000 So if there's a person who emerges that's really special that I think would make a ton of sense to partner with, then I'm open to doing that. 00:27:06.240 --> 00:27:08.720 But I kind of like love what I'm doing now. 00:27:08.880 --> 00:27:12.880 And I think that this is going to be like some of my best investing. 00:27:12.960 --> 00:27:15.680 So I'm kind of like, Do you want to keep the fund size the same then, roughly? 00:27:15.920 --> 00:27:16.240 I think so. 00:27:17.279 --> 00:27:20.240 Someone's gonna come back to this and be like, hey, you said you weren't gonna grow your fund size. 00:27:20.640 --> 00:27:28.000 Yeah, I mean, I don't think they will uh you know take it a task on that, but like you think you'll do every two-year deployment, 22. 00:27:28.559 --> 00:27:29.519 Every three-year deployment. 00:27:29.839 --> 00:27:35.519 And I honestly, my current thinking is it'll be every three-year deployment, it'll be around the same size. 00:27:35.680 --> 00:27:42.160 Like, I think um 50 million is the dividing point where like once you're over a 50 million fund, then you kind of have to lead. 00:27:42.319 --> 00:27:50.880 And right now I I I've co-led a number of deals, like a pre seed, but you really don't have that much flexibility because right now my ownership target is like anywhere from three to six percent. 00:27:51.039 --> 00:27:55.680 And that works with kind of a lot of things, but over 50 million, it it gets tough to like return the fund. 00:27:55.920 --> 00:28:00.160 So then, so then you know, people management thing doesn't matter as much. 00:28:00.319 --> 00:28:05.359 You know, you kind of probably outsource your contract fund admin and all that type of stuff, like a lot of the small funds do. 00:28:05.599 --> 00:28:06.960 So it makes it very straightforward. 00:28:07.200 --> 00:28:12.559 You're just focused on all right, I'm finding the best companies, investing in the best companies, my investors are happy. 00:28:12.640 --> 00:28:15.920 You know, you know, you've you've kind of got your re-up kind of built in there. 00:28:16.000 --> 00:28:23.839 Eventually you'll have a line out the door of people who are on the wait list, yeah, you know, ideally to come in, and that might push you to to do a bigger fund or something like that. 00:28:24.000 --> 00:28:25.599 So that's exciting. 00:28:25.839 --> 00:28:39.920 Um from a I guess a company investment standpoint, um you're getting in it like pre-seed seed, you've seen what great looks like. 00:28:40.240 --> 00:28:44.640 How do you keep the bar high and deploy on schedule? 00:28:44.960 --> 00:28:54.880 Yeah, so I would say um in today's investing environment, keeping the bar high, I think really comes down to valuation and fun math. 00:28:54.960 --> 00:28:58.400 And can each investment, especially if you want it to return your fund, does it all make sense? 00:28:58.640 --> 00:29:10.240 Because there are some really high potential founders that I see raising at like 30 to 70 million posts with barely anything built out, with kind of even a vague idea of what exactly they want to build. 00:29:10.319 --> 00:29:12.480 And they're talented, but they're first-time founders. 00:29:12.559 --> 00:29:19.279 And to me, those can be really, really hard because like the risk versus potential return, it's just like really, really tough. 00:29:19.440 --> 00:29:34.240 Um, so for me, I think about maintaining a bar in today's world as um, I won't do anything that's really over like 20 million-ish post for first-time founders that don't have traction, where there isn't any product, like that just like won't fly for me. 00:29:34.319 --> 00:29:36.960 So it honestly ends up eliminating a lot of YCS stuff. 00:29:37.200 --> 00:29:48.240 Um, I will and I have done a number of seeds where there was like a product built that already had a ton of validation, traction, or like second-time founders that like had a really, really good exit before. 00:29:48.400 --> 00:29:50.640 But I think for me, like that is really kind of the bar. 00:29:50.720 --> 00:29:55.279 It really comes down to valuation because there's some really talented founders out there that just don't make sense for my model. 00:29:55.359 --> 00:29:55.680 Yep. 00:29:55.839 --> 00:29:58.319 Um you do do second time founders though. 00:29:58.480 --> 00:29:58.799 I do, yeah. 00:29:58.960 --> 00:30:01.519 Second time founders at we'll do first time, second time founders. 00:30:01.599 --> 00:30:05.759 We'll do both, but I'll do second time founders at higher valuations because that they know what they're doing. 00:30:05.839 --> 00:30:10.160 And like there's so many parts of

early stage of like getting to product market fit. 00:30:10.240 --> 00:30:11.279 Cause that's really like the stages. 00:30:11.599 --> 00:30:12.640 They're de-risked slightly. 00:30:12.880 --> 00:30:13.440 They're de-risked. 00:30:13.519 --> 00:30:17.519 Like they have a team of people that they've worked with with before that they can pull from. 00:30:17.839 --> 00:30:19.680 They know how to get a product to market. 00:30:19.839 --> 00:30:22.799 They like they're both technical and understand some of the go-to-market side. 00:30:22.880 --> 00:30:24.880 So there's a lot that they've already like figured out. 00:30:24.960 --> 00:30:31.599 Um, with first-time founders, you kind of want to see that they figured some stuff out if they're going to be raising a higher valuation. 00:30:31.759 --> 00:30:35.519 I think right now, like, it's just kind of crazy some of the stuff that I'm seeing. 00:30:35.759 --> 00:30:36.000 Yeah. 00:30:36.079 --> 00:30:36.240 Yeah. 00:30:36.400 --> 00:30:37.279 It's a crazy time. 00:30:38.960 --> 00:30:40.160 It's a crazy time for sure. 00:30:40.720 --> 00:30:48.960 From starting as a small operator-led role in fund to evolving to an institutional platform, Angelist has been a core partner in every phase of GTM funds growth. 00:30:49.200 --> 00:31:01.279 Their software-first fund admin infrastructure allowed us to scale without sacrificing agility, from onboarding hundreds of LPs seamlessly to handling compliance, capital calls, and reporting as our fund size evolved. 00:31:01.359 --> 00:31:08.799 As we expanded from fund one to fund two, Angelist took care of the back office operations, allowing us to stay focused on what matters most. 00:31:08.960 --> 00:31:13.119 Investing in world-class founders and building the strongest go-to-market network and venture. 00:31:13.279 --> 00:31:16.079 They scaled with us across multiple funds and into the future. 00:31:16.240 --> 00:31:21.440 If your fund is growing in size or complexity, check them out at angelist.com slash GTM fund. 00:31:21.680 --> 00:31:24.160 That's Angelist.com slash GTM fund. 00:31:24.720 --> 00:31:28.640 What are you looking at in terms of, you know, when you're sizing up a company in terms of moats? 00:31:28.799 --> 00:31:34.880 Like how do you make sure that this company is not going to be cannibalized and this company will actually be able to defend itself? 00:31:35.200 --> 00:31:48.319 Yeah, um, it's really hard at like pre-seeds seed stage because like of all the things you can invest behind, like market tailwind, team, product, traction, like you don't usually have a GA product or traction. 00:31:48.400 --> 00:31:50.079 It's just like the team and the market tailwind. 00:31:50.400 --> 00:31:55.279 Um, so it usually comes down to why is this the best possible team to go after that opportunity? 00:31:55.440 --> 00:31:58.559 Like what edge do they have as far as knowledge, network? 00:31:58.720 --> 00:32:03.039 Like there has to be something that they're the

best at for that particular opportunity. 00:32:03.359 --> 00:32:08.240 Um, but it's usually not so tangible because there's nothing really there at that point. 00:32:08.400 --> 00:32:18.240 Um, so for instance, actually, there's um there's a company that I announced um not too long ago, but they've been ramping really, really quickly called Run Reveal that I did with Costanoa and Runtime Ventures. 00:32:18.400 --> 00:32:21.920 And what was so unique about that team, they're building a security data platform. 00:32:22.079 --> 00:32:30.400 And I looked at that space forever because there's really old school legacy companies like Sumo and Splunk that are huge, um, and like everybody hates them. 00:32:30.720 --> 00:32:40.799 And the thing that was so unique about this team is they brought like a level of data expertise and data understanding, and just the way that they thought about managing data was so different from every other approach that I'd seen. 00:32:40.960 --> 00:32:50.079 So they understood, they understood security, but they actually are data experts, almost more so, um, versus so many other teams that I see going after that space, they're much more like security focused. 00:32:50.240 --> 00:32:56.160 So I think it's like, why does that team have something special that allows them to take a different approach than what others have taken? 00:32:56.799 --> 00:32:57.039 Yeah. 00:32:57.200 --> 00:33:00.960 And then what about when it is a little bit further along? 00:33:01.119 --> 00:33:05.599 Like, have you invested in anything that has had tech that you can put your hands on? 00:33:06.079 --> 00:33:13.680 Oh, yes, but I would say usually if there's tech that I can look at, um, it's been open source founders usually. 00:33:13.759 --> 00:33:15.119 Um, so there's something that you can look at. 00:33:15.200 --> 00:33:19.200 There's a community you can look at, you can see how it deploys. 00:33:19.359 --> 00:33:30.960 Um, and one of the most interesting things about investing in open source companies, like true open source companies where they've open sourced like a majority of what the value is gonna be, um, or at least like a good portion of what it's gonna be. 00:33:31.119 --> 00:33:35.680 You can just see the quality of build and you can see how customers react to it and how they're using it. 00:33:35.920 --> 00:33:41.599 If it's core infrastructure, like if it's actually like replacing or being used in kind of really important processes. 00:33:41.839 --> 00:33:44.240 So there's just a lot there that you can actually work with. 00:33:44.640 --> 00:33:47.680 What do you do then from a diligence standpoint for these founders? 00:33:47.759 --> 00:33:54.960 And what's the um what do you what would you say like the average relationship duration is before you make an investment in somebody? 00:33:55.200 --> 00:34:01.680 Are these people you've known for a year and you've been tracking them and um you know, and and what does that look like? 00:34:01.839 --> 00:34:07.119 Is that like a couple of check-ins, invite them to an event, or is that somebody you worked with in the past? 00:34:07.279 --> 00:34:08.480 Like what does all that look like? 00:34:08.800 --> 00:34:09.599 It depends. 00:34:09.840 --> 00:34:13.440 Um I would say, yeah, like it really depends every time. 00:34:13.599 --> 00:34:23.199 Like I did a seed investment in a company that I'd actually looked at the pre-seed for, and it's an open source company, it's an Israeli company, and they actually actually we had announced it too, so I can talk about it. 00:34:23.280 --> 00:34:24.079 It's called Metal Bear. 00:34:24.320 --> 00:34:31.920 Um, so I'd already met the founders, um, and I'd kind of been tracking what they were doing and saw the project, saw who was using the project, saw kind of momentum on it. 00:34:32.079 --> 00:34:34.239 It was just a really interesting take on a hard problem. 00:34:34.320 --> 00:34:37.199 They basically eliminate the need for staging environments and engineering. 00:34:37.360 --> 00:34:42.400 You can code locally directly in your full production environment, which is just like a really interesting concept. 00:34:42.800 --> 00:34:44.880 So I'd kind of been tracking it for a while. 00:34:44.960 --> 00:34:50.000 So there, like that happens sometimes when you kind of meet founders, you think they're really interesting, and you track it. 00:34:50.159 --> 00:34:57.760 Um, I actually just invested in my eighth investment was in a founder that I looked at his first company when I was at Norwest. 00:34:58.159 --> 00:34:59.519 And it was in a really tough space. 00:34:59.599 --> 00:35:02.320 It was in cyber training, which is just like such a hard space. 00:35:02.480 --> 00:35:05.920 And he still got it to like an amazing exit, like got good traction. 00:35:06.159 --> 00:35:10.079 And I just like he was like someone I would reach out to for security diligence on things. 00:35:10.159 --> 00:35:17.039 Cause when I referenced him way back when, he he came out as like an A plus kind of like founder and guy, but I didn't like what he was building. 00:35:17.119 --> 00:35:20.960 So it was kind of like A plus founder, like C or D opportunity, in my opinion. 00:35:21.039 --> 00:35:21.199 Yeah. 00:35:21.280 --> 00:35:24.800 So then I known him and then, you know, for this new company, I love what he's going after and building. 00:35:24.880 --> 00:35:28.079 So there was already kind of a standing relationship there and references done. 00:35:28.159 --> 00:35:30.639 I tracked him, so there was a lot kind of background. 00:35:30.800 --> 00:35:36.559 I would say that almost all founders that I work with, there is some connections that we have. 00:35:36.719 --> 00:35:42.000 So it's easy for me to get very trusted references on like the quality of work that they've done or just kind of like who they are. 00:35:42.239 --> 00:35:48.239 It's very rare that someone is completely cold where we have no kind of like

overlap in any ways. 00:35:48.400 --> 00:35:55.199 Um, but then it's up to me to make sure that I have the right networking connections at companies that are going to create kind of the next set of amazing technical founders. 00:35:55.519 --> 00:35:55.599 Yeah. 00:35:55.760 --> 00:35:59.840 And because your check size, it's very strategic to most other leads, right? 00:35:59.920 --> 00:36:06.000 So you can co-lead or lead a pre-seed, but not really a seed with uh, you know, a million is your highlight. 00:36:06.159 --> 00:36:06.960 Millions a high point. 00:36:07.039 --> 00:36:07.199 Yeah. 00:36:07.280 --> 00:36:13.280 So for seeds today, it doesn't, but it is really fun because I've never been able to be so collaborative with people. 00:36:13.440 --> 00:36:15.840 Like I don't feel like I'm competitive with anyone. 00:36:16.000 --> 00:36:20.559 Like I'm competitive for allocation, but like, you know, if a founder wants me in, usually it can make sense. 00:36:20.800 --> 00:36:21.199 Absolutely. 00:36:21.440 --> 00:36:25.119 Um so that's the part that's been really fun, because it just feels like you get more opportunity. 00:36:25.440 --> 00:36:25.679 Yeah. 00:36:26.000 --> 00:36:28.559 So you have two other things that you work on. 00:36:28.719 --> 00:36:31.119 So open source um podcasts. 00:36:31.280 --> 00:36:31.599 Yeah. 00:36:31.840 --> 00:36:34.400 And then your what is it, the angel network that you have? 00:36:34.639 --> 00:36:35.039 Yeah, yeah, yeah. 00:36:35.119 --> 00:36:35.599 Modern angels. 00:36:35.840 --> 00:36:36.400 Modern Angels. 00:36:36.719 --> 00:36:43.360 So how do those I guess provide sourcing support or diligence support? 00:36:43.519 --> 00:36:46.400 Or are those, you know, do you do you leverage those for the fund? 00:36:46.800 --> 00:36:47.760 I definitely do. 00:36:48.000 --> 00:36:52.559 Um, but a lot of times it comes in ways that aren't so direct, if that makes sense. 00:36:52.719 --> 00:36:54.880 Like they're just very complimentary to the work that I do. 00:36:55.119 --> 00:37:03.280 And I would say like there's so many connections that I've made through both of folks who become regular angels, frequent angels into my companies. 00:37:03.360 --> 00:37:11.840 Um, a number of people that I had on the open source podcast, I became good friends with, and they've either invested in my fund or suddenly like they just become like, you know, part of a network. 00:37:12.079 --> 00:37:13.760 The open source podcast really started. 00:37:13.920 --> 00:37:17.119 I uh built it with Tim Chen, who's like an awesome solo GP. 00:37:17.280 --> 00:37:20.559 Honestly, one of the biggest encouragers of like me to go do this too. 00:37:20.800 --> 00:37:23.760 And we started it because both of us were looking at a lot of DevTool companies. 00:37:23.840 --> 00:37:26.639 Naturally, a lot were open source, like four and a half years ago. 00:37:26.880 --> 00:37:34.159 And we just didn't find very good content out there on how to actually build an open source business because there were so many open source projects that people were trying to turn into businesses. 00:37:34.320 --> 00:37:40.880 It was kind of unclear like the right model or license to use or when you monetize, like how much you open source. 00:37:41.119 --> 00:37:44.960 So we started interviewing founders originally for a blog post. 00:37:45.119 --> 00:37:48.239 Um, and we interviewed like Armand at HashiCorp. 00:37:48.559 --> 00:37:53.760 Um, we interviewed Ben Siegelman at LightSup for this blog post, and we were like, wait, the conversations were way more interesting than the blog posts. 00:37:53.920 --> 00:37:57.519 Like, maybe we record those, and then we like start a podcast out of it. 00:37:57.599 --> 00:38:03.679 And then we just both enjoyed it so much that we've done 160 or 70 episodes now over the like five years. 00:38:03.760 --> 00:38:04.480 It just keeps going. 00:38:04.559 --> 00:38:13.679 And it's honestly just because we like it, but it it's it helps with diligence because I get to see and like hear from all these founders on their stories, the opportunities that they found. 00:38:13.840 --> 00:38:17.519 And they're all very relevant because I'm looking in a lot of their spaces to make investments. 00:38:17.679 --> 00:38:20.800 But then I also just make connections through them pretty organically. 00:38:21.039 --> 00:38:25.199 So there's just like so many benefits that weren't like, you know, intentional. 00:38:25.360 --> 00:38:27.679 They just kind of happen because you're just like in the mix. 00:38:27.840 --> 00:38:30.639 And by the way, I feel like that is like the one thing. 00:38:30.800 --> 00:38:42.000 Like so many VC firms, myself included, and like firms I've worked at, try to like productize things so much and be like, oh, we're gonna have this like sourcing strategy or system or like database, whatever, and that's gonna be how we do it. 00:38:42.079 --> 00:38:46.880 But like the reality is you have to keep doing different things and keep meeting different people and like iterating. 00:38:47.039 --> 00:38:52.239 And like both of those efforts have helped with that like iteration of just meeting new people and like thinking about things differently. 00:38:52.480 --> 00:38:59.920 And then Angel Network that's 400-something angels that just wanted to potentially invest in what you're investing in. 00:39:00.159 --> 00:39:00.639 Oh, yeah. 00:39:00.719 --> 00:39:04.800 So that started um now probably three years ago. 00:39:05.039 --> 00:39:15.760 And it started because I had so many dude friends that were angel investing together, and they would have all these WhatsApp groups and trade deal flow, and I had all these awesome like female operator friends, um, and actually it was specifically two. 00:39:16.000 --> 00:39:23.199 I was having dinner with the um head of strategy at Figma and CMO at this like public fintech company, Upstart, who were two of my best friends, and they wanted to angel

invest. 00:39:23.440 --> 00:39:30.320 And so I brought them into deals that we did at Cowboy, but I didn't know I assumed they were getting pulled into other deals because they're both just like sick operators. 00:39:30.559 --> 00:39:32.000 And turns out they weren't. 00:39:32.079 --> 00:39:33.360 And I was like, this makes no sense. 00:39:33.519 --> 00:39:33.679 Yeah. 00:39:33.920 --> 00:39:42.159 So I like basically got their info about check size everything, put it in a Google sheet, shared it with other VC friends, and then like kept talking about this effort. 00:39:42.239 --> 00:39:46.000 And so many like people basically wanted to join it, and it quickly turned into a hundred women. 00:39:46.159 --> 00:39:47.360 I brought them all in a Slack group. 00:39:47.440 --> 00:40:00.239 I'm like, hey, this is not a this is not like us all needing to, you know, like do SPBs and invest together, but a network of people who can trade deal flow, who can bring people into deals, and it just kind of grew organically. 00:40:00.320 --> 00:40:04.320 And it's been pretty awesome because then I've also made some really good friends out of it. 00:40:04.480 --> 00:40:12.559 Um, like the head of security engineering, Angie at Anthropic, like she was one of the original ones that got into it, and we've just become like such good friends out of it. 00:40:12.639 --> 00:40:15.840 And it's like a relevant connection, but also she's just like an awesome person. 00:40:16.000 --> 00:40:23.840 So I think things like this just help very organically like grow the network, and they're in service of the community as opposed to just like nice little flywheel that yeah. 00:40:23.920 --> 00:40:40.719 I mean, you have the media extension on the podcast, you have the community extension with both the folks that are LPs in the fund, but then also the Angel Network, and those folks can all act as deal flow sources, diligence, and you know, portfolio company support, similar to kind of the model that we have. 00:40:40.880 --> 00:40:59.679 So uh the technical side of things, of of course, was whereas the GTM side of things, when you look at companies and you're sizing them up, um you know, you're talking about technical founders, but um how how do you look at commercialization? 00:40:59.840 --> 00:41:00.880 How do you look at TAM? 00:41:01.119 --> 00:41:04.079 How do you look at their the ability to sell, how this is gonna be big? 00:41:04.159 --> 00:41:13.679 I mean, we had a company we passed on recently where you know, I hate doing like, oh, the TAM is not big enough, but there's there are still some times where it is not big enough. 00:41:13.760 --> 00:41:16.559 There were like a hundred potential customers for this. 00:41:16.639 --> 00:41:26.719 They were selling to airlines, and it's like I don't know how to reconcile that because each individual airline is could be a big c customer, but that eventually caps out. 00:41:27.360 --> 00:41:30.000 I don't know what the exit potential

is gonna be. 00:41:30.239 --> 00:41:50.480 Um and you kind of end up in this like this mess where I feel like the best opportunities are grand slam potential, but like single double de-risk, you know, like at the worst case scenario, and then there's the opportunities where it's like grand slam potential and strikeout risk, and like those are fine-ish too. 00:41:50.960 --> 00:42:02.800 But if you have like eh, home run potential, but strikeout risk, then it's kind of like well, this isn't gonna be that big of a company, but it's also still super risky. 00:42:03.199 --> 00:42:12.320 So, shouldn't I be looking for stuff that's like high reward medium, lower risk instead of you know, low reward high risk? 00:42:12.639 --> 00:42:18.159 So, how are you sizing these things up in terms of TAM commercialization and distribution? 00:42:18.480 --> 00:42:23.840 Yeah, so um I would separate, yeah, the TAM question and then how commercial the founders are. 00:42:24.000 --> 00:42:28.880 So on the TAM question, there has to be it's less like the overall size of TAM now. 00:42:28.960 --> 00:42:37.360 Like in the case of Drata, the compliance software market, I think Gardner said it was like 200 million or something, which is hilarious because now there's like multiple billion dollar companies there. 00:42:37.519 --> 00:42:40.639 But the tailwind was there to increase the number of potential customers. 00:42:41.039 --> 00:42:42.880 So that's the thing that I look for the most. 00:42:43.440 --> 00:42:44.639 Momentum of TAM growth. 00:42:45.119 --> 00:42:45.519 Exactly. 00:42:45.679 --> 00:42:47.360 Yeah, I think that's a really good way to frame it. 00:42:47.440 --> 00:42:51.360 Cause like for a while, you only needed something like SOC 2 if you're selling to big enterprise. 00:42:51.440 --> 00:42:59.360 And then slowly but surely everyone was like, Well, there's so much risk with our vendors and the data that they're handling, like, why don't we make every vendor have to have SOC 2? 00:42:59.599 --> 00:43:04.639 So literally every startup that wanted to sell to anyone, it was like a complete blocker for them. 00:43:04.960 --> 00:43:07.280 And there were like kind of inklings of that happening. 00:43:07.440 --> 00:43:16.400 And so if you kind of could see that and you're like, okay, what if, like, are we on a path to the world uh in the world for there to be the need for every single company to have SOC2 compliance? 00:43:16.480 --> 00:43:16.639 Yes. 00:43:16.719 --> 00:43:18.320 Okay, then like that's rapidly growing. 00:43:18.559 --> 00:43:20.559 And I think that's happening in AI a lot too. 00:43:20.719 --> 00:43:33.920 Like, I remember one of my biggest um misses was I, when I was at Norwest, um, I was following the scale AI story and um had done a bunch of research in the background, um, because I think it was after the series A. 00:43:34.079 --> 00:43:37.360 So it was between series A and series B, and like heard really good things about the team. 00:43:37.519 --> 00:43:44.400 And so had done a bunch of background research just to like get a meeting with the team to basically say, like, hey, here's like basically what all the kind of like the market's saying about you. 00:43:44.559 --> 00:43:48.320 And they were so concentrated because at the time it was all autonomous car companies. 00:43:48.400 --> 00:43:52.480 Cause that was kind of like the first big like AI way was very like autonomous focused. 00:43:52.639 --> 00:43:54.559 And it was heavy customer concentration. 00:43:54.719 --> 00:43:58.400 And at the time, I couldn't really see like, oh, but this is gonna rapidly change. 00:43:58.480 --> 00:43:59.599 So this concentration is gonna change. 00:43:59.679 --> 00:44:04.400 It's Everybody needs AI and suddenly your potential customer set are like all these other companies. 00:44:04.559 --> 00:44:13.519 So I think it's like having an instinct or insight on that from an investor perspective, that's a thing that can kind of it's like there's something that's changing to make a market really, really big. 00:44:13.760 --> 00:44:14.000 Yeah. 00:44:14.559 --> 00:44:19.920 And then from my distribution standpoint, how does that channel through? 00:44:20.159 --> 00:44:20.480 Yeah. 00:44:20.639 --> 00:44:24.719 So um it depends what their distribution they plan on their distribution being. 00:44:24.880 --> 00:44:32.320 So if they, if it's going to be a direct sale, which honestly, like most companies will have some direct sale component to it, um, why are they the best at it? 00:44:32.400 --> 00:44:33.679 Or why can they be the best at it? 00:44:33.760 --> 00:44:41.840 So one of the things I do, I actually almost never ask, if they do have like one or two design partners or customers or whatever, I I never ask to talk to them. 00:44:41.920 --> 00:44:44.800 Cause I'm like, one, that's like kind of annoying for founders. 00:44:44.880 --> 00:44:46.239 But then two, I don't know them. 00:44:46.320 --> 00:44:50.960 And I have my own network of potential customers and users who will give me the full download of it. 00:44:51.039 --> 00:44:54.079 And they're not warm, like they're not, you know, one of their friends. 00:44:54.320 --> 00:45:00.719 So I have them pitch, and oftentimes I sit in and watch them pitch and I watch how good they are at engaging them, at like pulling product specs. 00:45:00.800 --> 00:45:07.360 So actually, my most recent investment is in a very early TAM, but I think is gonna rapidly grow space. 00:45:07.599 --> 00:45:13.599 And the founder, it's funny because so many of the CISOs of my network were like, this isn't a problem for us yet. 00:45:13.679 --> 00:45:14.719 We're not looking for tools there. 00:45:14.880 --> 00:45:17.840 And then they met with her and they're like, God, she's so compelling. 00:45:18.079 --> 00:45:25.599 Like, maybe, maybe like, you know, for this kind of market, she has to be educating the market and like she kind of has that. 00:45:25.679 -->

00:45:29.599 And I and I just fundamentally believe that this is gonna become a really big problem in a pretty quick amount of time. 00:45:29.679 --> 00:45:29.920 Yeah. 00:45:30.079 --> 00:45:33.360 So I just try to like test them out, and it's like mutually beneficial. 00:45:33.519 --> 00:45:36.159 Cause even if I pass, they've met a bunch of like customer prospects from me. 00:45:36.239 --> 00:45:37.440 So it's like, yeah, great. 00:45:37.599 --> 00:45:39.679 So I try to do that as much as possible. 00:45:39.840 --> 00:45:43.360 Um, and yeah, I want to see what their distribution advantage is. 00:45:43.440 --> 00:45:49.119 And it doesn't necessarily come down to like, oh, they already have a pre-existing network of CISOs themselves, because like I can help bring that. 00:45:49.280 --> 00:45:55.920 It's how good are they at engaging and like really impressing their like potential user buyer group. 00:45:56.079 --> 00:45:58.159 So that's where like having the network can really help. 00:45:58.559 --> 00:46:05.440 We had very similar one just now uh we invested in where we were like, I don't know if it's a need to have or nice to have. 00:46:05.599 --> 00:46:06.960 We were kind of on that line. 00:46:07.280 --> 00:46:17.360 And the uh principal at GTM Fund, Viba V, her um what would it be, brother-in-law works for a potential customer company. 00:46:17.440 --> 00:46:19.440 And so we're like, Can you take a look at this? 00:46:19.760 --> 00:46:23.440 And uh his response was like, I want to buy this now. 00:46:23.599 --> 00:46:26.239 Can I also can I can I write an angel check? 00:46:26.400 --> 00:46:28.960 Like I was like, ah, those are the responses you want to hear. 00:46:29.039 --> 00:46:36.559 So uh we ended up making the investment, obviously a couple other data points, but those are yeah, that that's what you want to hear. 00:46:36.800 --> 00:46:37.679 Yeah, totally. 00:46:37.840 --> 00:46:41.440 And it's funny too, because it's always so nuanced at the early stages. 00:46:41.599 --> 00:46:46.320 Cause like, you know, like for instance, run reveal, it's like a sim. 00:46:46.960 --> 00:46:53.519 So a lot of security teams, like, they're very skeptical of other sim companies because they're like, yeah, we hate Splunk Sumo, we haven't seen anything good. 00:46:53.760 --> 00:46:58.880 And so there was like nuance of like finding the right potential people for them to talk to that would give me the right advice. 00:46:58.960 --> 00:47:00.320 I wouldn't just be like, ah, I don't want to do this. 00:47:00.480 --> 00:47:03.920 And the funny thing is, a lot of the naysayers now are like, oh wait, now I won't look at this. 00:47:04.079 --> 00:47:09.440 So you kind of have to like find the right people to do that kind of diligence or like hear the pitch. 00:47:09.599 --> 00:47:09.840 Yeah. 00:47:10.000 --> 00:47:16.800 And yeah, sometimes it's hard because like I'll get not like bad, but I'll get like less interested by your perspectives on something. 00:47:16.880 --> 00:47:21.119 You really have to dissect that and like be like, okay, wait, did I introduce the wrong profile of person? 00:47:21.360 --> 00:47:24.480 Or like you kind of have to like almost study your own diligence. 00:47:24.719 --> 00:47:24.880 Yeah. 00:47:25.199 --> 00:47:26.559 Well, you're verticalized. 00:47:26.719 --> 00:47:39.119 So are you, do you feel like when you speak to the founder, you're actually learning a ton from them and then you have to go back and verify that, or do you come with a prepared mind in a way where you are almost fact-checking what they're saying in real time? 00:47:39.440 --> 00:47:44.880 It's you, I there have I can't remember the last time that I met a founder and I was like, oh, is this a pain point? 00:47:45.039 --> 00:47:48.239 Is this like usually what happens is like, oh, huh, interesting. 00:47:48.400 --> 00:47:51.519 I know this is a problem, but I haven't heard someone taking this approach before. 00:47:51.679 --> 00:47:53.280 And then usually I'm like, can it work? 00:47:53.440 --> 00:47:56.320 And like that, and then like I try to work through that with them in real time. 00:47:56.639 --> 00:48:02.159 And that's usually the thing that I'm thinking through is like, is their approach going to actually work or be that different? 00:48:02.320 --> 00:48:08.239 But there are a lot of meetings where someone will pitch them to me and I'm like, I've heard this almost exact pitch so many different times. 00:48:08.480 --> 00:48:11.679 And like this just doesn't feel like something that new or different to me. 00:48:11.840 --> 00:48:16.880 So uh, so then that helps me kind of get through the ones that are less interesting a lot faster. 00:48:17.119 --> 00:48:21.360 Um, the thing that's tricky about being so verticalized, like I do a lot of cyber investing. 00:48:21.760 --> 00:48:30.639 There aren't that many, like if a company becomes big, there are maybe like, I don't know, six or seven major categories are gonna go after, whether it's like identity, GRC, and like, or detection engineering. 00:48:30.719 --> 00:48:38.639 And then some of them you you can't like I'm very mindful of conflicts, but then you get into this issue where like if they're gonna get big, they're gonna end up overlap. 00:48:39.360 --> 00:48:39.679 Yeah. 00:48:39.920 --> 00:48:41.119 What do you think you'll do? 00:48:41.440 --> 00:48:43.199 Honestly, very nice problem to have. 00:48:43.440 --> 00:48:46.639 It's a nice problem to have if they get really big, but it's like we have too many unicorns. 00:48:46.960 --> 00:48:51.280 No, but like at the beginning, you kind of it's even hard because you know, like founders will have really big ambition. 00:48:51.440 --> 00:48:53.679 So like a lot of founders will be like, well, I'm gonna get there eventually. 00:48:53.840 --> 00:48:55.519 And they'll almost self-select you out of others. 00:48:55.760 --> 00:48:56.960 You're like, you have like five of these. 00:48:59.119 -->

00:48:59.920 Well, what one day? 00:49:00.079 --> 00:49:00.960 Like five years from now? 00:49:01.039 --> 00:49:03.119 Like, oh, that'll be a great problem for everybody to have, right? 00:49:03.360 --> 00:49:03.679 Totally. 00:49:03.760 --> 00:49:05.119 I've like it's that we get to that point. 00:49:05.199 --> 00:49:08.480 Like, and then the thing is companies will pivot sometimes, so you have to like manage it. 00:49:08.639 --> 00:49:18.000 But yeah, I try not to have direct conflict risk, but there are some times where like I have two companies right now where they're both like actually one more than the other, is like we might get into that space at some point. 00:49:18.159 --> 00:49:20.079 And I was kind of like Some point. 00:49:20.239 --> 00:49:21.920 Get some like, but anyway, they let me do it. 00:49:22.239 --> 00:49:23.119 Somewhere over the rainbow. 00:49:23.440 --> 00:49:23.760 Exactly. 00:49:23.840 --> 00:49:24.800 Yeah, some point. 00:49:25.039 --> 00:49:30.159 Um, where are you getting your like news or learning from these days? 00:49:30.400 --> 00:49:35.519 Is it talking to people, listening to podcasts, any specific specific podcasts, communities? 00:49:36.000 --> 00:49:39.760 Oh, that's a good so honestly, real-time news. 00:49:40.000 --> 00:49:41.519 I get so much of it from X. 00:49:41.760 --> 00:49:49.440 Like, I feel like that's like the most real time, because you don't even get like just the event, you get all these different perspectives on it, and you can kind of sort through whose opinions you want. 00:49:49.519 --> 00:49:55.760 And I actually like to see both sides because it's just like helpful in like you know, forming kind of holistic um view of the situation. 00:49:56.000 --> 00:50:00.960 But yeah, as far as like podcasts, there's so many different like good cyber ones that I listen to. 00:50:01.199 --> 00:50:04.239 There's a lot of good content out there from like different founders now. 00:50:04.320 --> 00:50:09.039 I feel like there's almost too much content that I have to like speed through a lot of it. 00:50:09.280 --> 00:50:12.639 Um, but yeah, I don't know if there's like very specific ones. 00:50:12.719 --> 00:50:15.280 It kind of is just like an amalgamation of like different things. 00:50:15.599 --> 00:50:20.239 Um, like I really like a lot of the new media outlets, like Upstarts, Alex Conrad's. 00:50:20.400 --> 00:50:21.760 Like, I love his deep dives. 00:50:21.920 --> 00:50:23.440 He's really, really great. 00:50:23.599 --> 00:50:30.800 Um, I love uh Eric Newcomers who's like for general tech stuff, but with like a good like a perspective on it and really like well thought through writing. 00:50:30.960 --> 00:50:32.239 Um so I like all the things. 00:50:32.400 --> 00:50:38.800 Are there any cyber-specific podcasts or um any Israeli, you know, newsletters or podcasts or anything like that? 00:50:39.119 --> 00:50:40.000 Oh, that's a good question. 00:50:40.159 --> 00:50:45.760 There aren't that many, I would say necessarily like Israeli newsletters that I follow. 00:50:46.000 --> 00:50:52.719 Um, there's been a few, I mean, as like the war's been going on, there have been a few like individual podcasts that have like really summarized stuff really well. 00:50:52.960 --> 00:50:56.880 But I would say that like following all the firms, they all will kind of like summarize what's going on there. 00:50:56.960 --> 00:51:00.719 Like I do a lot of work with TLV partners, for instance, like the teammate team's awesome. 00:51:00.800 --> 00:51:05.679 And just like following them, seeing what their commentary is, seeing what things they link to has been really helpful. 00:51:05.840 --> 00:51:13.519 But then I would also say I'm on the ground perspectives from people, especially for that situation, because like you can't really trust a lot of the news out there, or at least I've had a hard time. 00:51:13.679 --> 00:51:19.360 Um, my founder's perspectives has been like, because they're just in it and like can tell you what's going on. 00:51:19.440 --> 00:51:21.280 So that's been probably the biggest thing. 00:51:21.679 --> 00:51:26.079 So what makes an actual AI company versus just AI theater? 00:51:26.320 --> 00:51:26.480 Yeah. 00:51:26.639 --> 00:51:31.119 So I think it's funny because so many investors now will say we only invest in AI. 00:51:31.280 --> 00:51:33.840 And then their definition of it is very different. 00:51:34.079 --> 00:51:37.119 And so I I've been trying to come up with my own definition. 00:51:37.280 --> 00:51:41.119 I think like the worst definition are AI native, like what is AI native? 00:51:41.199 --> 00:51:45.840 AI native is companies built by founders that are like under the age of like 23. 00:51:45.920 --> 00:51:49.119 Like they grew up with these AI tools, which I think is a terrible definition. 00:51:49.519 --> 00:51:54.639 Um, there's also um a definition that it's a company that has their own model. 00:51:54.800 --> 00:51:57.199 And I think that is true for sure. 00:51:57.360 --> 00:51:58.960 Those are all AI native companies. 00:51:59.119 --> 00:52:05.679 But I actually think that an AI native company is a company whose core product offering is an AI product. 00:52:05.840 --> 00:52:09.280 Um, and it's not kind of like an ancillary thing. 00:52:09.440 --> 00:52:13.119 That doesn't mean that there aren't non-AI companies that are going to be really valuable. 00:52:13.199 --> 00:52:21.199 And I have invested and looked at companies that are applying AI to automate like different parts of their process, but their core offering is not AI. 00:52:21.360 --> 00:52:35.679 And I think what's interesting in the infrastructure space, um, I would say more infrastructure and data versus security, but in infrastructure and data, you have a number of companies that are enabling AI in different ways, but they're not like uh if you looked at like, is there core product offering AI? 00:52:35.840 --> 00:52:36.960 Like, is it an AI product?

00:52:37.039 --> 00:52:42.159 No, it's a database product or it's an observability product, but it's for AI workloads. 00:52:42.320 --> 00:52:52.639 So I think that's kind of the way that I think about it when it comes to investing in AI companies, is it are these companies supporting the generation of AI native application companies that are coming out? 00:52:52.800 --> 00:52:58.320 Um, and usually that comes down to them helping with something around data storage, observability. 00:52:58.480 --> 00:53:01.119 Like they're really enabling these applications in different ways. 00:53:01.280 --> 00:53:06.559 Um, and a lot of times they'll apply AI themselves, but they themselves are more of like an infrastructure player. 00:53:06.719 --> 00:53:08.079 Like Superbase is a good example. 00:53:08.159 --> 00:53:12.159 It's like enabling so many AI applications, but they themselves aren't really like an AI application. 00:53:12.239 --> 00:53:13.039 They're just an enabler. 00:53:13.280 --> 00:53:13.519 Yeah. 00:53:13.760 --> 00:53:14.639 Interesting. 00:53:15.039 --> 00:53:17.360 What are you uh using internally? 00:53:18.239 --> 00:53:22.880 Um like are you have you AI-ified to fund? 00:53:23.519 --> 00:53:28.159 It's funny because I think like there's so many different perspectives on this. 00:53:28.239 --> 00:53:29.599 I just kind of use it as I need it. 00:53:29.760 --> 00:53:33.440 Like I tried a number of the AI products for the podcast, and they were just like kind of okay. 00:53:33.519 --> 00:53:37.199 And I like the outsourced guy that I was using, so I've like been using him instead. 00:53:37.360 --> 00:53:39.039 Um I use an AI scheduling bot. 00:53:39.119 --> 00:53:41.760 That's probably the one thing that's saved me the most amount of time. 00:53:42.000 --> 00:53:46.480 I basically just like pull in this AIEA and they'll do a bunch of scheduling stuff for me. 00:53:46.639 --> 00:53:48.239 So that's been like the best use of time. 00:53:48.880 --> 00:53:57.199 Diligence memos, like But the for memos for me, it's like I'm basically putting down my like raw thoughts, like why I think something is like gonna be huge. 00:53:57.280 --> 00:53:58.880 And it's like a one-page memo. 00:53:59.039 --> 00:53:59.199 Yeah. 00:53:59.360 --> 00:54:03.599 Cause it's funny, I used to do these like really beefy memos um when I was at bigger funds. 00:54:03.840 --> 00:54:09.760 And usually the reason you did that was so that your partners could like really understand and validate the things you were saying. 00:54:09.920 --> 00:54:20.800 But if it's just you, it's like I want to record my thinking so that in the future I can know if I made a good or bad decision on the basis of like, was I lucky or was I actually right? 00:54:21.199 --> 00:54:24.880 But I don't actually think that, you know, I have all my notes in different places. 00:54:24.960 --> 00:54:25.599 Like, I don't need all that. 00:54:25.679 --> 00:54:26.960 Like, I'm not trying to prove it to someone else. 00:54:27.039 --> 00:54:28.719 I'm just recording my point of view. 00:54:29.039 --> 00:54:33.679 Yeah, I know we we definitely use a lot of it for competitive analysis. 00:54:34.079 --> 00:54:53.920 Um, you know, it just just the sleuthing and like copy and pasting you'd have to do pre, you know, GPT to go find competitive analysis, TAM sizing, all that kind of stuff is now just like a well-written prompt or two in a GPT, and then you have like this the whole thing is like written for you. 00:54:54.079 --> 00:55:04.239 So certainly use it that way, but it's it's almost always like verifying what we already believe, not like helping us get to a belief, you know. 00:55:04.719 --> 00:55:07.360 I think it is really like ChatGPT is so helpful with writing. 00:55:07.519 --> 00:55:10.960 Like when I especially because I'm now trained in on my style of writing. 00:55:11.199 --> 00:55:17.280 And so I would never, and I think you can tell when someone something is like entirely like Chat GPT built. 00:55:17.519 --> 00:55:17.760 Absolutely. 00:55:18.000 --> 00:55:20.000 But it's more like, oh, I'm trying to say this thing. 00:55:20.079 --> 00:55:21.199 Can you make this sound a little bit better? 00:55:21.280 --> 00:55:22.239 And it just saves you time. 00:55:22.400 --> 00:55:24.880 So it's kind of like this co-pilot helping with writing. 00:55:25.039 --> 00:55:33.199 Or you know what I do a lot is if I have like a summary for one of the podcast episodes, I'm like, hey, can you put this into a LinkedIn post using my like style of language? 00:55:33.280 --> 00:55:34.400 It just saves so much time. 00:55:34.559 --> 00:55:36.159 Then you can like iterate on it too. 00:55:36.400 --> 00:55:38.480 But yeah, the writing piece is really good. 00:55:38.639 --> 00:55:44.719 But yeah, it's almost like it's not that great at it's well, actually, it's not great at all at original thought. 00:55:44.800 --> 00:55:56.400 Uh so there's like absolutely it's never gonna kind of replace, and it's funny because even on like, oh, you can be like this non-technical person and build a company, do whatever, it's like, no, there needs to be like an original thought, original product, original thing built. 00:55:56.639 --> 00:55:57.920 And it's not gonna do that. 00:55:58.000 --> 00:56:01.599 So it can do a lot of like personal things, like personal tasks. 00:56:01.760 --> 00:56:05.440 But yeah, if you want to build or say or do something differentiated, it's not gonna give you that. 00:56:05.599 --> 00:56:05.920 Yeah. 00:56:06.159 --> 00:56:10.400 That was another fantastic episode of the VC series on the GTM Now podcast. 00:56:10.559 --> 00:56:15.679 Head over to Apple, Spotify, or YouTube and give us a like and subscribe, and we'll see you on the next one.