399. Why You Should Always Bet on The Founder, The Future of Cybersecurity, and Will AI Live up to the Hype? (John Cowgill)

399. Why You Should Always Bet on The Founder, The Future of Cybersecurity, and Will AI Live up to the Hype? (John Cowgill)

John Cowgill of Costanoa Ventures joins Nate to discuss Why You Should Always Bet on The Founder, The Future of Cybersecurity, and Will AI Live up to the Hype?. In this episode we cover:

  • How Do Costanoa Ventures Run References
  • Do Investors Need to Have a Thesis
  • What Is Applied Big Data and How Will It Change the Enterprise
  • Bets on AI in the Enterprise
  • How Generative AI Can Be a Catalyst for Esoteric Industries

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Transcribed with AI:
Todayโ€™s guest is John Cowgill, General Partner of Costanoa Ventures. Costanoa is an early stage, Valley-based venture firm focused on investing in finTech, data, applied AI and security. John has been at the firm for 8 years, joining as an associate and recently becoming a GP. Prior to Costanoa, John was a consultant at McKinsey, where he advised consumer and technology companies on strategy and operations projects. John, welcome to the show!
Can you share a bit about yourself and how you ultimately made your way from management consulting to joining co cinoa?
Yeah, so I actually started my career in startups, I went to school at Northwestern, and was given a strong incentive by my mom to graduate early to reduce the cost of that school. So I spent my senior year working for startups and caught the startup bug, doing sales and business development for two companies in Chicago, fell in love with the pace of startups, the ability to own things and move quickly and learn a lot. As you mentioned, I’d done a summer internship and management consulting, had a return offer, thought I should do that and get that experience. And I’m glad I did, and that a lot of amazing people. And I learned a lot but I was I was itching to get back into startups. But I was a non technical guy I was living in Chicago at the time, I wanted to come out to the Bay Area. And coming from a management consulting background, you get funneled into go do Biz Ops at LinkedIn, or Google or Uber and those are great companies. But I knew I wanted to do something earlier. And I realized they just didn’t know what to look for didn’t have a network out here. And I total serendipity. I got introduced to my partner Greg, who at the time had, you know, gotten to fun to at Kosta Noah, he’d founded the firm about a decade ago. And they were looking to bring on their first associate, and say this with no mock humility. I don’t know why they hired me, but they gave me a shot. And I’m, you know, always be grateful to them for that. And the pitch he gave me was, hey, come, come learn what makes a great startup, you know, support us as an associate, bring the analytical skills you developed in management, consulting, and a little bit of your sales skills and come do this for two years, figure out what looks good. And then you can go join a startup. And you know, Famous last words, because I’m still here eight years later, but it’s been an amazing journey, amazing place to learn. Very great.
He clearly made the right decision, because you went from associated GP and eight years, and we’ll talk about the firm in a bit. But I’m, I’m curious to learn more about your experience over those eight years. I mean, what have been some of your biggest lessons since joining as an associate nearly eight years ago?
Yeah. The biggest lesson is that there’s no straight line to success in startups. And I think a lot of times coming in as a bit of an outsider, you hear about these incredible stories in Silicon Valley where everything is up into the right, and it’s just this clean exponential growth curve, my biggest takeaway from eight years and ventures that that’s BS, and that every startup has periods where you just don’t know if you’re going to make it where things look really tough. And you have moments of near death, even in breakout startups, one of the things that I’ve learned in this job is you really need to have steady hands and have belief in your own decision making ability and conviction and the companies that you invest in. Because almost every company, your conviction is going to be tested. And it’s the founders who believe in what they’re doing. And the investors who believe in the companies that make it through the other sides, especially in an environment like this. So I could give example, after example, in our portfolio, but that’s been my single biggest lesson from watching companies. As an investor. You know, I think the biggest thing that I’ve probably taken away from from working in Costa now is just how lucky I am, frankly, to be in a firm that operates the way we do where we work together as a team. You sort of mentioned as we were chatting before this started that, you know, in this environment, you learn a lot about how different venture capital firms operate. And I’d say there’s so many ways to be a venture capitalist, there’s so many different types of firms that have very different strategies, very different ways of working with the portfolio. I don’t think I appreciated that when
I joined coasted, I don’t certainly didn’t appreciate how unique of a place I was joining. So extremely grateful for that as well. Yeah, but as you look back over the past eight years, you said there are a number of stories or examples you could give. Are there any salient points or inflection points in your career over those eight years that you felt like were big on lots or epiphanies or anything that really catalyzed your success as an investor?
Yeah, well, I think my first year at COSTA No, I was just trying to figure out which way was up. Like I said, I’m not quite sure why they gave me the opportunity, but I’m grateful for it. And I think it was probably about a year in where things started to click and I started to understand a little bit more how we made decisions, what we look for in founders and that probably flicked in an investment. It was actually the first investment that I made co lead with my partner Greg sands and a company called roadster. And it was the first time I really felt like I got to conviction on an investment. I did a bunch of diligence work, I spent a bunch of time with the founders. And it was a pretty contrarian bet at the time. It was a company that built software that sold in two car dealerships. And at the time, 2017, everyone was convinced that all cars were going to be completely autonomous in five years, and that car dealerships were going to be a thing of the past. It’s funny to put yourself back in that headspace, but in 2017, that really was where the investment community was. And I’d say it was really leading that investment, getting to my own conviction. And then watching that company over the course of four and a half years, ultimately, to acquisition. I just learned so much watching that team operate, seeing the highs and the lows, there were plenty of highs and there were some really scary lows, some true near death moments. I just give a ton of credit to that team, and that just grateful to have had the opportunity to watch them through it. I learned a lot from that company. Yeah. What about
in hindsight, like, as you look back at some of your biggest mistakes over the past eight years, whether they’re big misses that you’ve had, and say no to a company that ended up breaking out? I mean, there could be a variety of things that come to mind, but specifically from your mistakes. What have you learned?
Yeah, I mean, how much time do we have to talk about? We do a whole episode on that there have been a lot of investment mistakes I’ve made over the last eight years, I think about them a lot. And I think about what did I get wrong? And I think there are a couple of patterns. So I’ll start there with just you know, investment misses, and what I think I’ve gotten wrong in the past, I think the single most important thing we do, you know, we are seed stage investors, we invest at formation in probably two thirds of the companies we invest in, is pick founders. And there’s the Warren Buffett quote of you know, when a management team with a reputation for brilliance hits a market with a reputation for bad economics, it’s the reputation of the market that wins. I think that’s actually wrong in our business. Because there are multiple companies I passed on, I knew the team was exceptional. And I just thought the market was going to be too hard. And those are some of my biggest misses. You know, a company that comes to mind, there’s a company called a fresh, it’s in the grocery data, retail space, you know, grocers, it’s, it’s like local governments and hospital systems. And grocers are the three worst customers in the world. But I knew those founders were special, I just had such a strong opinion of them. That one hurts doubly bad because I passed on the seat. And then they were grateful enough to give me an opportunity a and I passed again and both times it ultimately bubbled down to just thinking that the market was too hard. So that would be be one category of misses. I can keep going up pause, if you want to
know I wanted to double click on the founder part because I know you guys are laser focused on the founder, what are you specifically looking for?
So we talked about it a little bit before but the first thing is grit it is the single most important thing in any startup founder is the ability to just push through all of the crap that gets thrown at you as a startup founder. And that might be my other biggest lesson of eight years in venture is just how much water founders have to carry and how difficult the job of being a founder is. That said, you know, grit, you have to marry grit with sort of a humility, and an ability to acknowledge when things aren’t working. So part of your job is running through brick walls, but part of your job is also saying, hey, this brick wall maybe isn’t worth running through anymore, and we need to pivot or we need to adapt or change our strategy. That’s a tough combination to find in someone. But it’s something we really look for grid grid plus humility. You know, I think we always like to find founders who we think are domain experts and who really understand their category. But I also love it when we find founders who didn’t come from the category and became a native and went down the rabbit hole and got deep. I almost like that more, because it shows that intellectual humility and curiosity that I referenced prior, it’s related to grit. Go ahead.
So you almost need to be a bit naive, in a way to be a founder to take on some of the challenges, right? And
without a doubt, it’s actually the counter to the Warren Buffett argument about management teams is I think, the famous Paul Graham essay on schlepped blindness, you know, where he essentially says, there’s so many hard problems around us every day that founders are blind to and you almost need a certain degree of naivete to sort of acknowledge this, this massive problem right in front of us, and often, you know, great businesses get built there. So I couldn’t agree more with that. Going back to what we look for in founders. I mean, I think it’s related to grit, but velocity, you know, just people who get things done and get them done quickly. You know, it is the single weapon of formation stage startup passes speed, there’s no mode in a formation stage startup, but the ability to move faster than an incumbent. That’s really the weapon that they have. So we care a lot about velocity. Maybe the last one, we could go on a long list but I think super important and complete non negotiable for us is just integrity and values. And so when we reference founders and we do a lot of back channeling, we always probe to make sure that there’s never been a question In that regard, because there are going to be times in a startup where it can be tempting to take a shortcut, and it always comes back to bite you. But you need someone who has a strong moral backbone in front of a company.
You know, maybe your answer to this question is going to be No, but I’m curious if you guys have any tactics or hacks any way that you approach, evaluating founders that that’s different than that of our peers.
Yeah, I don’t know if we do. But I’ll tell you a little bit about what we do. So we have a very thorough it’s a nine page reference guide that we use to run references. And I think, you know, I will say a lot of people and I’ve been on referenced calls, I think run them in a pretty slapdash manner. It’s, oh, is this person good? They’re a good person. Great. You know, where would you stack rank and other high? Okay, great. You know, even with people we already have a really high opinion of, we tend to schedule 45 minute reference calls. And we really go deep on the stories and anecdotes that illuminate these traits that we’re looking for. I do think back channel referencing is a huge part of venture capitalists job. And by the way, I encourage founders to backchannel reference us in VC firms. You know, if you’re talking to someone who’s been coached on what to say, it’s a little harder to get to the truth than if you can find someone who’s worked with someone in the past, and will give you the unvarnished off the record truth. So we do a lot of it. And again, I encourage founders to do it to us as well. I think we’ve explored having a kind of founder roleplay assessment where we sort of throw questions at founders and see how they respond to them. You know, if this happened, how would you respond? I think I’ve found that again, to sort of fall a little too much into the It’s easy in that environment to sort of say the right things, I want to know what you’ve done in the past, because the data is going to ultimately be more telling. But I think it’s an area we’re trying to get better. I think the it gets back to velocity, right? I mean, that is grit, its velocity, its integrity, those are the three legs of the stool for us. There’s lots of lots of other things that can be great. It’s great. When you’ve got, you know, a great customer network, it’s great when you’ve got, you know, maybe some special piece of technology you’re pulling out of a past roll, but those three things are non negotiables. Yeah, philosophy is so important.
what point do you guys do references during your process? Because some do it right. At the end? They’re like academisation. And it’s like validating the Yes. Which feels like the wrong time to do it. Yeah,
I’d say it starts the second I need a founder, there’s different forms of referencing, right, I always go through the front door and ask for references. But if I’m connected to a founder, the first thing I do is figure out if there’s a quick and easy shared connection that I can do some back channeling with. And so that’s the fastest path to get really excited. And frankly, the fastest path to know is if I hear from someone I trust, like, I wouldn’t work with this person again. It’s it’s a no, you know, I only make two to three investments per year. You know, certainly there are cases where people, you know, have a bad experience with someone and there might be, you know, two sides to every story. But I just be honest, that I’m not going to get past someone I trust saying, oh, this person isn’t, you know, exceptional. They have to be exceptional. It’s at the center of everything we do. So it starts the second I get connected to a founder,
how many times would you say that you found yourself at total conviction, the business, you love, the approach, the market, the opportunity, etc? You even like the founder and what you hear in your interactions with them. But the references just don’t check out the way that you’d hoped that they would, how many times and what percentage of the time you’re saying no, to those, those situations?
pretty often. I mean, we keep a really high bar and references and we go deep in them. And they are the single most important data point as we are doing diligence. Yeah, I’d say, usually, it is something I unearth by the call it 50 yard line of diligence. That doesn’t happen when I’m all the way to the end of the process. But but it happens. And I’ll say, if I’m at that stage, and we’ve spent a lot of time together, and I’ve really, in my own judgment, built conviction and a founder, and then I’ve gotten a really bad reference. I’ll absolutely tell the founder, I’ll acknowledge confidentiality and protect who I talked to, if you know, that was part of the conversation, but I’ll say, hey, we spoke to some people that had x&y experience with you, and I want to hear what your experience was. And you know, talk to me about it. And I’d say, I can’t immediately come call to mind a case where that happened. And I ended up investing, it may have happened. But I wouldn’t be opposed. If I got over a negative reference after talking to a founder founders deserve the opportunity to you know, have their day in court if we’re at that point in the process. But it does happen where I love the idea. I do some actual and I come back and think yeah, this probably isn’t gonna meet our conviction bar. So it’s best to let the founder know and respect their time.
Yeah. Well, I want to turn our attention to Kosovo in a moment. But I have one last question for you. And that’s when you think about your last eight years of investing. Are you more or less bullish on the next state than the last eight years?
A man, it’s a great question. I’ll say short answer more bullish. But I will acknowledge a couple of things. It’s been a great eight years to be a venture investor, or at least a great seven years to be a venture investor, things were pretty much up into the right. And I made 13 investments over eight years, nine of them received for him or series, I haven’t actually had one go out of business yet. And without a doubt, that is, in large part due to Well, first, the management teams of those companies and the great work they do. But a big part of is it’s been a great financing environment. And there’s been a lot of opportunity for companies that are doing important work to get financing. The next eight years loss rates are gonna go up, things are going to be harder, there will be fewer unicorns over the next eight years than I think there have been over the past eight years, certainly if one adjust for inflation. That said, I think that the durable companies that get built over the next eight years are going to be massive companies, opportunities to build great companies. Right now, I’m going to talk about some of the technology tailwinds that we’re investing behind. But you can look back over 30 plus years of venture capital. And you can see that it’s actually these vintages that happen right after a massive bull market turns to bear market. That’s what great companies get built in great companies got built 2001 to 2003, tons of great companies got built 2009 to 2011. I think a lot of great companies are going to be built 2023 to 2026. So I’m really excited about the opportunity to go and do that. But I also will say it’s going to be harder, outcomes will be better, but things will be harder. Yeah.
Well, to reference Warren Buffett again, I guess be greedy when others are fearful. Right. So tell us a bit more about personal. I am curious to hear a bit more about the investment philosophy. And you’ve you shared some of your principles already. But what areas are you guys interested in the broad strokes, I’m a firm? Yeah,
we’re seeing series A enterprise technology focused venture firm, we do about two thirds of our work and seed a third series A and broadly everything we’re investing in is an application of data in the enterprise or enabling infrastructure for applications of data and yet enterprise. So T categories applied AI, data infrastructure, cybersecurity, FinTech, primarily b2b FinTech applications that have some data component, everything we do fits into those buckets. And I’d say what I love about the way we work is our approach, I think how we invest is more important than what we invest in. And the way we invest is high conviction, high concentration. So we’re five Investment Partners, every investment partner does on average two to three investments per year, we make about 12 investments per year as a fund and do about 36 investments over the course of each fund. So that’s a really high degree of concentration for a partnership, and every bet we make matters. But the way that we structure the fund, you know, we reserve more than most funds do alongside our early stage funds, we have opportunity funds, which just double down in our companies at later stage. What it allows us to do is with our companies that you know, grow to be breakouts, we can bring to those companies, the capital of a multistage firm, we’ll put 30 to $40 million to work. But that first two to $3 million seed check, it really matters to us, it’s not buying an option. It’s a company, we’re all in on making succeed. So I think it’s the most aligned approach with founders to investing. And it’s frankly, the form of investing I like the most because you get to actually build deep relationships with founders and work with them. The downside of it is I have seen it a lot. And I that’s still the part of the job that I dislike, we just don’t make a lot of investments. But when we invest, we’re all in. And I think that’s what’s special about Costa nella, it shows up in the way we work as a partnership, we all support each other on each other’s deals. Behind our investment partnership, we have a full time team of operating partners who are senior executives and their respective functions, so sales, product marketing and talent, they spend all their time with the portfolio supporting them in operations. And I think if you talk to founders in our portfolio, what we hope you’ll hear and what I think you will hear is Costa knows the most engaged in value add investor on the cap table. That’s what we’re striving for at least and working to earn every day. So that’s a little bit about us.
So one of the commonly held beliefs you said that you disagreed with prior to the show was that investors need to have a thesis. I’m curious why you feel that way and how that manifests in Coachella?
Yeah. There are a lot of ways to be successful as a venture capitalist. And there are some great VCs who are very thesis led, but it’s just not the way that we’ve wired our firm. We have focus areas, and we have areas of expertise. But we think that founders are the experts. And we let our curiosity guide us to founders who show us where the light is. And so we always have some themes. We always have some areas that we think might be interested. But the problem with being too thematic is you go looking for a company that fits your thesis. And in so doing, I think you might end up optimizing for things that are less important. Namely, you may end up not picking the right founder. I would contend that at the stage where investing the founder is more important than the thesis because Companies pivot all the time, themes change markets change, you want to be in business with people who can react to that, and who can grind through those changes. So we all have our areas of focus at Costa nila, I’m probably the most generalist of the five partners. If you look at my portfolio, it looks like it’s all over the place. I’m invested in for security companies. I’ve got four applied AI companies, I work with two space companies, there actually are some unifying themes across those companies that I can talk about. But what really unifies them is all of them have founders that I just believe in as people, I can’t wait to work with people who I’m excited to get phone calls from people who share the attributes we talked about earlier?
Yeah. Well, it’s like you said earlier, success is not a straight line in this business. Right? So whatever you’re investing in, it’s likely to be a totally different company. Totally different state, three years down the road. Yeah, I mean, we think about things very similarly, as well, where if you have someone who’s very deep in their space, they’re the experts. They know what the future looks like, more so than we ever could. So we should always default to what the founders vision is, rather than our own, because that’s how you miss great opportunities.
Totally. I mean, I think our job is certainly to diligence and confirm what a founder is telling us. And one of the things I think we pride ourselves on is our ability to do really thorough Diller diligence really quickly and get up to speed on opportunities that maybe we weren’t clued into. And I do think having expertise matters, we have it in spades in our categories. But what we don’t have is at any given point, oh, we’re trying to go find a company that does X. I’ve seen some investors have a ton of success with that approach. But it isn’t our approach. Yeah. Well, you you piqued
my curiosity, when you said there are some Unifying Threads across your investment. So I would be curious to double click on that. And here. What are the you know, homogenous threads across? Yeah, your partnerships?
Yeah, I mean, I referenced it earlier. But it always comes back to novel applications of data in the enterprise. You know, when Greg founded the firm, 10 years ago, 2012, the opening blog post was, what is applied big data? And how is it going to change the enterprise? Applied Big Data? Obviously, it turned into applied machine learning deep learning, we’re now entering a new era of AI with foundational models, but it’s always been weird. Is there an opportunity to take a dataset, apply it to a problem that could be automated or augmented with that data, and investing in the infrastructure that enables those applications and data? So I can pick any company in my portfolio and explain to you how it is either a novel application of data or enabling infrastructure for those novel applications of data. But that shows up in many ways. It shows up in commerce enablement, it shows up in dental revenue cycle management, it shows up in auto car dealerships, there’s there’s so many opportunities to bring data to bear on problems in the enterprise. And again, it’s why we try not to be too thematic, because we want to let entrepreneurs show us where the light is where those incredible applications of data are.
Yeah, well, I mean, it’s, I think data has definitely been in the spotlight over the past six months, one year with, obviously generative AI and everything that’s happening in this space. So I’m curious to get your opinion on specific areas that you find are interesting at the moment. But more generally, I feel very grandiose claims have been made, where the AI opportunity is even surpass that of the internet, which is a fairly hefty claim. I’m curious how you and Costa Nova view the opportunity of AI for investors overall, like, well, how big will this be? How do you guys think about the future of AI and its role in the enterprise?
Yeah, we’re really excited. And we’re really skeptical. I think we’ve been investing in AI since the beginning. And I was chatting with a friend of mine the other day, and we were lamenting, everyone’s trying to do AI in the enterprise now. And he made the comment, we feel like aI hipsters like we were in this before, it was cool, which is a little bit our sentiment, there are a lot of exciting applications of AI. And it’s happening at an incredibly fast clip. And it’s impossible not to be excited about it. That said, another lesson from eight years and venture is you need to be incredibly skeptical and careful about whatever the really hot thing is, especially as an early stage investor, because by the time something’s gotten really hot, the innovators have been working on it for three or four years. So if you go back in time, you know, when I joined Costa Nova, everyone was excited about chatbots. You know, in 2017, everyone’s excited about Ty’s vehicles go back a year, everyone just thought, oh my gosh, crypto inflection, it’s about to be crypto everywhere. You know, if you made a seed investment and autonomous vehicles and 2017 seed investment chatbots in 2016, to seed investment in crypto last year, maybe you make it but that’s going to broadly not be where you want to place bets. So making bets on AI and the enterprise right now feels a little bit like that. That said, there are there are so many opportunities that you You’d be crazy to just draw a line and say, Oh, we’re out on all things AI in the enterprise. I think what we’re looking for are the orthogonal bets. In the bets that we think are maybe a little bit 123 years ahead to the prior point. So the things that are really, really hot right now, we’re pretty skeptical of but the things that people are maybe not talking about as much were a little more excited about. Yeah, I’ll pick one in particular, which is, I think it’s been relatively under discussed how much all of these new tools, specifically large language models, and diffusion models for generating images, just create new weapons for bad guys to go after people. This is a whole new threat landscape. But what I think is interesting is, you know, the same tools that give bad guys ability to hack and attack enterprises in new ways are probably the same tools that need to be used by enterprises to respond to those threats, interested in the security cybersecurity opportunities in both leveraging large language models to respond to threats to train employees, but also to detect threats and manage threats, we’re going to start seeing some really crazy hyper sophisticated spear phishing attacks with these tools. And my belief is that the best line of defense for those tools is probably having good guys leverage them as well. So we’ve been looking at a lot of opportunities around AI and cybersecurity, certainly a hot area, but I’d say relatively less disgust and less than some of the other things you see. And yeah, there’s actually
going to be one of the areas I was going to ask you about. Maybe before getting there, though, you mentioned some areas are overhyped, or to the areas that you guys look at. And you’re, you’re you’re not excited about they feel saturated. They don’t feel differentiated.
Yeah. Well, there’s a broad class of what I’d call just horizontal applications of AI that I just think are not the domain of startups, unfortunately, they’re going to be won by large enterprise. And so I think all of the writing applications of large language models with regards to copywriting marketing sales, I just think that’s incredibly saturated. It’s incredibly cool. It demos incredibly well, but they’re both so many players there. And I think there’s not, to me, at least, my belief, not enough obvious need for article isation, that, broadly, users won’t just go directly to chat GPT or some other large language model and get the output that they need. I’ve in the last month had pitches around using large language models in AI for weather for text to speech, for, I’d say, a set of use cases around marketing that I just I think that those applications, they’re they’re too obvious, they’re too horizontal. And frankly, a lot of them feel like fairly thin wrappers on top of someone else’s model. So I think we’re not generally excited about things like that. We’re looking for things that are a little less obvious, a little more orthogonal, maybe one to two years away from being at the center of the hype cycle. That’s where I think you can invest in AI in the enterprise and you know, this environment and still make money.
Yeah. How do you think about generative AI being a catalyst for some of these esoteric spaces like construction or manufacturing AG, those that have lagged behind technology adoption, where I feel one of the main objections is always what is the catalyst and that space, because everyone points to well, millennials are overtaking leadership positions to procure software, and it feels very fluffy. But this is a real technology catalyst in which could unlock certain use cases that weren’t possible before without the technology. So I’m curious if that’s an area that you guys have been looking in as well, some of these sleepier industries in which technology could unlock more adoption, and faster growth of the solution in the market beyond the
early adopters. Yet, we’ve invested in the last six months in one company, that part of the pitch is leveraging large language models in janitorial services. And another one that’s an IT service automation. So we believe there are a lot of opportunities in the sleeper industries. I mean, I think the first thing that comes to mind for me is this is a really rich, natural expressive interface that one can bring to a less technical user and essentially expose the power of AI to that user in a way that just wasn’t possible before the advent of large language models. You know, I think the challenge has been with regards to deploying AI in Sleepy industries, hard to train the end user hard to get the data that you need. And I use the analogy of, you know, if you’re trying to deploy AI and construction, six years ago, it was like climbing a 100 storey building and get a bunch of data, you had to go and label the data, you had to go and train your own model from scratch, and then you had to get, you know, the end user accustomed to using it, it might require them to start adopting some new process. You know, in this era, you can start on the 90th floor of that 100 floor building, right? You come in with a powerful model that already has a very natural language interface. And I’m referring to basically chat GPT interface that lets a user start to interact with a with a very powerful model out of the gate. Certainly one needs to define the guardrails, figure out what the actual use case is. There is process change, there is training required, but I just think we’ve both dramatically lowered Are the barrier to building AI models and also dramatically lowered the user experience barrier to getting you know, in customers who may not be as sophisticated to start actually leveraging this technology in their day to day lives?
Yeah. John, if we could feature anyone on the show, who should we interview on? What topic would you like to speak about?
Yeah, a lot of great co investors have had a chance to work with I would probably pick Brad Gillespie at IA ventures. I’ve been working with him for almost six years now, at Kepler communications. He’s got just incredibly high EQ, very clear thinker in the boardroom, you know, probably the highest value per word spoken of any board member I’ve ever worked with. And I think interviewing him on the topic of what does it take to be a great board member? I would love to listen to that podcast.
What book article or video would you recommend to listeners something, ideally in recent memory that you found particularly informative or inspiring?
Yeah. You know, the book I’ve been recommending to a lot of founders recently has never split the difference, which is the book on negotiation from from Chris Voss, he’s also got a great master class. The reason is, I think we’re in an era right now where there’s a lot of hard conversations that need to be had. And I think Chris does an extraordinary job of outlining, you know, what he calls tactical empathy, but how to understand someone who has a very different point of view from you, and ultimately win them over to your side so that the topic is negotiation, but I really think that applies to any hard conversation a founder or an investor needs to have. So I’d recommend that book to anyone.
Awesome. And last, what’s the best ways for listeners to connect with you and Coach cinoa?
Yeah, we recently migrated domains. We are now at to Costa nola.vc. So you can shoot me an email at John at Kosta noah.vc. Awesome.
Well, thanks again for doing this. This was a lot of fun, and I’m looking forward to having you on again in the future.
Yeah, thanks so much. This is a blast. Appreciate your time.
All right, that’ll wrap up today’s interview. If you enjoyed the episode or a previous one, let the guests know about it. Share your thoughts on social or shoot them an email, let them know what particularly resonated with you. I can’t tell you how much I appreciate that. Some of the smartest folks in venture are willing to take the time and share their insights with us. If you feel the same accomplishment goes a long way. Okay, that’s a wrap for today. Until next time, remember to over prepare, choose carefully and invest confidently thanks so much for listening
Transcribed by https://otter.ai