And we win over 93% of the deals we seek at Ridge, which is a really high number. And we do it in a bunch of different ways. And so I think about all those ways and how they stack to build advantages. Another good example is we have something we call the Ridge Revenue Network, which is three thirty plus VPs and C level buyers at fortune 1,000 companies. And this is not completely anomalous in our industry. Like other firms have versions of this.
I can't think of another firm that does it quite as effectively and accountably at the earliest stages as we do. We track the crap out of our customer intros. We did somewhere between three and four hundred intros last year. We have quotas for different companies. We're Welcome to The Investor, a podcast where I, Joel Palafinkel, your host, dives deep into the minds of the world's most influential institutional investors.
In each episode, we sit down with an investor to hear about their journeys and how global markets are driving capital allocation. So join us on this journey as we explore these insights. All right, we are live on my weekly show. Excited to, have on this exciting guest here, Brendan Baker from Bridge Ventures. Got a chance to get to know each other pretty recently.
And, you know, he's also just a seasoned investor, you know, just kind of if you look at his background, you know, worked at Gray Lock and, you know, also worked at a lot of high growth companies as well. So I'm excited to kind of go a little deeper on your background, Brendan, and thank you for offering to, to share your story with us. I think it's just really exciting to hear everybody's origin story, and we're all going through different paths in life.
So, excited to kind of hear your unique path and fork of how you got to where you are. But maybe we could start with your career, your professional background, where you studied, where you grew up with your family and then just kind of navigate through that pathway to where you are now. Yeah, absolutely Joel. Thanks for having me on excited to be here. Love chatting about venture, works, what doesn't all those things, but let's do it. So I mean, going way back, I'm Canadian, I'm from Vancouver.
I grew up in the mountains and had a first brief career as a traditional engineer. So materials engineering, civil engineering. I kind of realized early on that I was gonna probably be a pretty average traditional engineer and I was better at other things. At the same time, was doing in parallel a lot of sort of aid and development work in Sub Saharan Africa. I lived in Ethiopia and Senegal a few times and was really passionate about that.
So I studied, I did that engineering degree at UBC and then ultimately did a master's at Cambridge and then an MBA at Oxford. I have three degrees. I probably should have gotten 1.5 of them. I don't know which zero five, I don't know one, but I have slightly too many.
But I went back to school to figure out sort of a way out of the engineering and hunting for how you build things, how you build, you know, take ideas into things, small things in the mass of things, whether it's a nonprofit for impact or whether it's a company for profit. I was always chasing that. And at Cambridge, I had some of my classes in the business school. Thought, shit, marketing, amazing how you actually get people to hear about you, you know, operations.
And so that led me to, I thought, okay, I should definitely do an MBA. At Oxford I did, I was really fortunate to come into contact with a small number of luminaries from Silicon Valley. Like think Reid Hoffman, Peter Thiel, folks like that, just for quick conversations. Honestly, Joel, like the language they were using and how they were thinking about the world was the light bulb went off. So immediately after that degree, I just made a beeline to the Bay Area. I was like, these are my people.
This is where, you know, these people are building huge things with, you know, not reckless ambition sometimes unfortunately, but generally huge amounts of that ambition. And this is where I wanna be. I wanna be building with these people. So yeah, so I hooked up, I connected with the AngelList folks. I had two introductions into Silicon Valley. Didn't have many. That was fortuitous. I jumped in. I was the second employee and joined the first day we had an office.
And I can go into that journey, but it was basically like, they said, we agreed on a Friday, on Sunday, They said, know, when are you thinking of coming here? And I said, I've already flown here. I'll see you on Monday in the office. I was just Oh, wow. Decisive about, you know, the ecosystem. Yeah. I mean, look, that's exciting. You know, I didn't know that you were like one of the early employees at List.
And and we we had a friendly kind of, like, just debate about the future of TxTx Adventure. Mhmm. But I didn't know you're the early employee. So tell me a little bit about, you know, as as I'm adjusting this light here, you know, to a little bit about tell me a little bit about how the the ecosystem was back then, how it was working for Angelis. I guess, did you spend time with Nabal a lot? You know, like, what are some of the early learnings that you learned working for such?
Because there was really not too many companies of its kind back then, and AngelList has pivoted a few times. Their AngelList used to kinda have, like, this they used to have kinda, like, this this deal flow feed. I remember I used to look at that because there would be, like, trending deals, know, that was one of the features that they initially had. And, and that kind of that kind of pivoted into like what it is now.
But just maybe unpack that for us in terms of like that experience as an operator working for AngelList, what we're like, you know, whatever you're allowed to share and you know, who the leadership was there and maybe some nuggets of wisdom that you you took with you to kind of go to the next step after that? Yeah, I mean, was it was totally fortuitous. I mean, the reason that I made the bet on them versus sort of the one other option, which would have turned out to be a good option actually.
The reason I really wanted to work with them is that I figured that they were at the center of one of the centers of the ecosystem and they were really thinking about how venture should become more modern and what can mess with the model. And that's something that I've been very passionate about over the past decade is how do you build modern venture and what does that look like? Or what are the forms that that can take? So yeah, it was early.
I'll digress very briefly and say, as I was finishing at Oxford, I did a little bit of research and my research was on the emergence of seed stage venture capital, which was really early. There were, if you look at PitchBook, there's a few 100 deals in 02/2009, twenty ten, twenty eleven, but it wasn't a standard stage like it is now. So that was ahead of its time. I was landing in a place where mass syndicated rounds, collecting a bunch of investors was kind of a new thing.
I mean, not really new, but in this form. And then the efficient connecting of investors and startups was, you know, there had been versions in the past. Some of them were work, some of them hadn't, but this was the first real out of the gate modern version of that. So if you back up and think about the AngelList team, before AngelList, they spent four years writing this blog on venture capital and fundraising called Venture Hacks. It was a good freaking blog.
Like I still point people to their content a decade later because a lot of it's timeless. It's still relevant, yeah. It's amazing. And they had, I think 40,000 or tens of thousands of subs. They did a really good job and they were really thinking about it from a game theoretic point of view. Like how does a founder build this system to successfully fundraise and what are the incentives on that system and what are investors doing, etcetera, etcetera. So they came from that basis.
They had a lot of knowledge. And the other thing that I think that Nivia and Naval, the two co founders of AngelList had that is rare and is required to tackle this market in the way that they have is I just see them as fundamentally a combination of insiders and outsiders in the industry. So they had successfully built companies, they had successfully invested, for example, like Angel Investor and Twitter, etcetera.
So they were insiders, they understood it, but they also didn't think that this was the end state. Like they weren't brought up in this apprenticeship associate model of venture capital who thought and thought that this was the only way it could be done. They had both of those and that allowed them to build this platform. To get to your question, I mean, first day we had an office, we had a one room office with four of us.
Yeah, spent a lot of time with Nivia and Naval and Brandon who's gone out to found Instacart. So it was a good little room to be in. But essentially, you know, when I arrived, we had, I think a few 100 investors, maybe actually it was less than that. It was probably sub 100 investors on the platform and we were getting a dozen pitches a day, something like that. Our tech stack was literally a woohoo form on a WordPress blog, and we were making introductions out of Gmail. That was our tech stack.
So what was the innovation? So back then, right? Like we, when you think about like venture back then you think of like, you know, Don Valentine, and you know, the OGs from from the Valley. So what was the what was the, you know, so you talked about some of the feature set, but what was considered innovation? Because that's changed now, right?
I mean, I don't know if they had all the syndication and the fund admin back then, but what was kind of like considered innovation back then when you joined? So it's a good question, Joel. I think the best answer I can give is it was the efficient connecting of investors, the initial innovation. And there have been a bunch actually, I wouldn't characterize AngelList as having pivoted. Would say they've built layers of value on top of this core basic thing that we were doing back then.
But I would say the innovation was the efficient connecting of investors and startups where startups didn't have to walk through investor networks and take coffee meetings and figure out who was a match and vice versa in a very industry aware way. So I'll say it briefly and we can go down this path if we want, but a lot of people have built websites with a button where you can sort of like push button to meet startups, push button to meet investors and they by and large fail.
And they fail because they don't understand the dynamics behind that interaction. They don't understand like what does an investor need in this relationship? What the founder need in this relationship in preparation? So a good example is we obsessed about subject lines in emails and I spent hours and hours and hours refining pitches to make sure that they were showcasing the right type of information. We knew that we had twenty seconds with an investor to get them to read a pitch and review it.
That the currency with them was like really trust of the quality in their time. And we had a founder would probably take eight hours to dial in their pitch. So if you didn't understand, and we understood that social proof and social capital is one of the currencies of our ecosystem. It's not just an economic economy and a technology economy. Like you have to think about the influence of these people.
And so if you understood all those layers and incentives below that button on the internet, then you had a shot. And if understood how to attract both sides of this marketplace, I mean, it's kind of a marketplace place problem at the beginning, then you can get to a critical mass to have this system that starts to spin up in itself.
Yeah, no, I think that's that that is a huge shift because back if you think back then, the Don Valentine days, I mean, you, you had to, you know, sneak by the secretary and drop off a physical pitch deck like a piece of paper or you have to kind of smooth investors even though you're a founder and you don't have any money. I mean, the dynamic is really, really strange, right?
It's like you have to wine and dine investors when, you know, the investors should be kind of taking you out and supporting you. But that's just how it was back then. You kind of had to woo those people.
And I think if you can democratize that and have kind of a manual matching system, because to your point, it's just people invest based on I feel like how they feel like based on what they trust and and how they feel versus, hey, here's a basket of securities essentially that I can pick from and let me pick the best one and then and then expect the founders to automatically just see money coming into their bank account. It's much more, you know, organic than that.
And it's the same, you know, we're going to talk about this definitely, probably soon. But like, that's I see that similar dynamic with GPs and LPs, right? Like people invest in who they trust and people invest in people who they feel something with very similar to like, if you choose a spouse or like a person that you want to date, you know, it feels right. And feel like it's not too different from picking companies or picking picking funds to invest in.
But but that so there was kind of more of like a like a manual tech stack, you kind of have like a G drive and like a pretty much a person reaching out kind of connecting people. Right? Yeah, absolutely. And if you think about, I mean, you're talking about, Joel, is a semi efficient market, which is what startup fundraising is and what GPLP fundraising is. They're semi efficient markets. They're not completely efficient. They're not complete inefficient either.
And through my career, I'm guessing yours as well, we've seen sort of where the needle has moved on this efficiency spectrum. And so if you think about how, like back to the Don Valentine example, how inefficient that was, like all this artifice that you had to create as a founder when the supply and demand of capital was that imbalanced that you had to go through and how strong those signals were. I'll give you an example of an important single signal in a semi efficient market.
Like the quality of your referrer, like who introduced me to this founder as an investor is a really important signal in a semi efficient market because you don't have all the information and you don't have all the awareness and judgment about this particular area. So you gotta rely on somebody who knows that founder or knows what she's building that area or something like that. As it becomes a more efficient market that lessens importance.
And so this is really what we're talking about and what I care about, which is like the journey that ventures on gradually towards a slightly more efficient market. AngelList is one good example, there have been a bunch of tools like YC as a model that has made it dramatically efficient. You introduce what a demo day is, a demo day is a local marketplace for startup shares.
Or if you think of what NFX has done with Signal and a way that startups can get a better idea of who the best investor actually is for what I'm building as a founder. It's helpful. You go from 80% mismatches until you get to the first meeting on where you invest and where you're building to maybe 50% and saves everybody time. Yeah, no, I agree. And I think recently, I was pretty blown away. I used I don't know if you've ever used Zillow. People use it just to kind of look at real estate.
And there was kind of a property that I was just randomly interested in. Was in the Midwest. And I was like, Oh, I'm interested. And like, immediately, there was somebody that called me. And they're like, Hey, do you want to talk to the broker in like five minutes? And I was in the mall, like with my family. And literally in two minutes, I was on the call with the actual broker, like the person that had the property. And that person I had a cell phone.
Now I like knew somebody that's like in Kentucky that had access to that, that deal flow that market. So I think that in my mind, was almost like a magical experience. Damn, this is so it was like literally in real time. They did a three way intro and we were like on the call. And I was like, wow, imagine if somebody did that. I'm sort of thinking about like, my wheels are spinning. Was like, wow. So that's really still what it takes.
I think still for founders and also for, GPs and LPs, there needs to be some type of curated intro still. I don't know, it's just not as compelling because there's just so much, there's so many deals, right? I mean, you go on AngelList, you can look at like an index of PropTech, climate change, Fintech, they're all great. And they all have a similar benchmark, right? There's a there's a typical benchmark for expectations on IRR.
So then how do you pick, you know, you only have so much capital to deploy. And, you know, you wish that you can invest in everybody. So how do you know, you know, what is the signal to actually pick the right one when there's so much selection? And it's the same thing with dating, right? Like, think about like dating, like, you're on Tinder, there's so many dates, there's so much selection, and you're never happy. Right? Yeah. Yeah. I agree with all that.
So there's, like, so many frameworks, but so that so that was the first step with AngelList. So it sounds like you were what was your role there? You're doing, like, product or, like, business development? I landed and we didn't know what I was gonna do. I said, I'm gonna show up in your office because I love what you're doing and we're gonna, you know, I'm gonna figure out what to do. I think we called me the deal flow manager or something like that.
But essentially I worked with Nivi and Naval, mostly Naval to screen eight of the first 9,000 pitches that went through that platform. And then ultimately it was just me screening dozens, two hundreds of pitches a day and then working with hundreds of, I think three to 500 founders dialing in their pitches and then making connections. Was like the market maker essentially early on as the team. They had an engineering team.
We had an engineering team that essentially built up AngelList around Nawal and I into what it is today. And I mean, you spoke about judgment and deal filtering, you know, we were that, we were the sort of the point of judgment in the flow, but what they ultimately built and have become, which was the plan was a distributed network where the judgment is happening sort of within that network among investors.
Joel, I haven't seen a model yet that we're starting to see some, but generally almost all venture models have relied on some human judgment somewhere in the system. Even if you build predictive models and you structure that data, you're usually sort of capturing some human judgment in your structured data, like First Round Capital led this deal. So it's a good one, etcetera. So that was me and that was Naval and then it became, you know, everybody on the platform as that platform matured.
Yeah, it was a sourcing and screening skill set, but then there's an investor that still has to choose, right? So there's that choosing fact. That's why I say like, it's, it's pretty interesting. Yep. To think about that when you finally pull the trigger. I always point back to dating, because there's just so many perils, like, you finally choose that person, whether to date them or to marry them even though you did so much synthesis. Right?
You did like qualitative analysis, quantitative analysis, you did pros and cons. Right? And and then in venture you got right, you got the team, the TAM, the traction, all those filters, but at the end of the day, there's still a an action and event to decide to choose, right? And that that right now is not automated. There's not you can't just put, you know, 100,000,000 into chat GTP and then, like, hope for the best and then think that they'll replace a human. So we're not there yet.
I I I think it could be at some point, you know, if there's, like, enough data, and, like, you know, downside risk mitigation somehow. Have no idea, But I think it'll happen at some point where like the venture model will change. And we are seeing that with stuff like AngelList, you know, there's a marketplace, you know, AngelList had a talent fund, where they were using a lot of data science based on the traction of startups hiring.
So there was like a whole fund built out of like all the all the data that they had in terms of talent data. So I think that's an interesting signal, right? I mean, startups are trying to hire that's probably that probably means that they're gaining momentum, gaining more revenue to, to hopefully get to the next fundraise.
So and then and the one thing I want to talk about is like, you know, I see Naval is like this mythical creature, you know, like when you watch some of his YouTube videos, he talks about happiness. He talks about like time boxing your life where like, you know, hey, if you don't make 10 if this not if this does not lead you to something that allows you to earn $10,000 per an hour, like, don't do it. You know, he has, like, all these crazy decision models.
So I just wanna hear, like, any nuggets or pieces of wisdom that you took away from him because, again, I just see him as, like, just a like, this just magical person that has so much wisdom. Like, it is not even about venture or tech, but it's also just about life. You know? I know he's read a lot of philosophical stuff, so there's gotta be some stuff that fed into you that that inspired you from that. I think, you know, he's leaned more into that in the past few years.
It was always there a little bit. Naval is as advertised and Nivy and Naval are both, I think brilliant people. They are absolutely as advertised. I've been fortunate to work with a lot of really smart people and some people who the industry thought that they were brilliant. And then when pee peeked behind the covers, it's a little bit less so, but those two are as advertised and Naval is in my opinion, one of the brilliant folks in our industry.
The philosophical piece was already there a little bit. I think it's really become more developed in the years since, but him just having, you know, he has a different structured, very reasoned view of the world. That's what allowed them to create this amazing blog, which was Venture Hacks, is they just saw it differently than everybody else and they spotted things.
So very, you know, he was good to work with, incisive to the point, there's not a lot of wasted space or oxygen and taught me a lot about NIVY too. They taught me a lot about how to think of a good startup early on. I mean, pretty quickly, I think I showed a fair amount of judgment there and my ability to sort of weed good from bad, but really helpful in that respect and just like quick processing, you know, what is good in this area, what's not good in that area.
But think Naval's a brilliant guy who charts his own path and is a good human too. Mean, this is gonna be a little stereotypical tech talk, but I think the last time I saw him in person, we randomly found each other at Burning Man way out on the playa. Oh, wow. Gave other a big hug and hung up for a little while, and that wasn't totally surprising. Yeah. I just think he's he's got his own path going and it's working for him and and and it's true to who he is.
Mhmm. This might be helpful for the audience too in terms of, like, there's just gotta be some insights that you gather that are probably still relevant today when you when you went through all that volume. Right? You went through thousands and thousands of deals. You sourced and screened. Right? So what were the common threads? And I feel like this carries a lot of merits because you work with so many smart people. What was a common thread that helped you bubble up the best deals to the top?
You know, you've looked at thousands of deals. What was it? Was it the team, the TAM, the market size, the traction? What what kind of really stood out as like a common thread to say, hey, you know what? This kind of fits the mold for a top Angel list deal. Yeah, mean, there's a couple of answers, a couple of layers to that answer. So I'll hit a couple of different things, Joel. So first, realizing the importance of social capital, unfortunately, right?
Because this is hindering a lot of access for founders, like so and so is invested in a deal so other people get attention, right? So what gets funded is slightly different than what deserves to be funded, but what gets funded is one where there's oftentimes a critical mass of support or endorsement around the company. So thinking really carefully about that. And that's why people care about who's on the early cap table, who their advisors are, how strong the referrers are.
Unfortunately, still continues today. And it was something that the Angela's crew realized, but or knew, but the rest of the industry didn't. There are some signals when you see many, when you see literally thousands of pitches and up to a couple 100 a day, you absolutely see signals of quality. So I don't know if this would work now, but what we had was structured pitches and they were call it a couple dozen different fields.
And one of those fields that was an incredible predictor for me of quality was how will your product reach the market? Or how will your product reach users? I can't remember the exact phrasing. Would say essentially. A 100%. Now we know it as distribution. Like we have more knowledge as an industry, but back then there was a little bit less. So I promise you 90 plus percent of pitches said something like our product is so good, people will come to it.
And that answer was a predictor, was an indicator sophistication for me. Like, do these people know what they're doing? Do they know that 95% of companies or more need to work hard to get to their customers or their users? And so the 5% or 10% who had a good answer to that were ones that I wanted to look at more deeply and then think about more deeply. So how did like back then, right? I mean, was this the 90s? So we didn't have we didn't have social, we didn't have mobile.
So was it mostly like, yeah, what were like people's growth hacks or like growth strategies back then? Was it like newsletters, like like physical, like ads in the newspaper? Was 2010. Okay, it's not that bad. So it's not that bad. Mobile, yeah, we had an iPhone. There's no newspapers. Yeah, had we had we had iPhones. Blogs were. Yeah, I was picturing you working there like in the eighties or something. So so so yeah, that's why I brought up like Don Valentine.
I mean, was probably in the seventies. I mean, don't check me on history, but yeah, so 2010. So we had the iPhone, right? So there's some data and some stats. But yeah, what were the common growth strategies back then? Because it is quite different now. Yeah. So blogs were a big deal, right? So like automatic and that whole sort of open source ecosystem was really important.
RSS was still working still effective and still used and social was coming up, right? If If you think about Facebook was reasonably popular, Tumblr was a really big deal. And so you not only had these channels that were social, but you had a lot of new mechanics that were inherent in those. This is how Zynga got really big, on the back of Facebook and a lot of sort of viral mechanics. So you had this whole set of approaches that were much more viral in nature.
And people were talking lot about K factor and how you get users through other users. And that was pretty nascent still. And afterwards I went to Greylock and they had invested in a lot of Facebook and LinkedIn and Pandora and stuff. So they understood these mechanics really well. But that was a phase in time where people were understanding how to game one platform to build an audience and then translate into their own audience or their audience on multiple platforms.
I mean, Twitter is a good example. They were also ascendant at that time. Yeah. And then, you know, not to get you completely sidetracked, but we, you know, going back to signals of quality, you know, how will your product use you reach users, your distribution what were some other signals of quality looking at thousands of decks? I think it really depends on the sector. So this is gonna be an unsatisfying answer, which I shouldn't say before I answer and say something, but I will.
And it leads to one of the biggest recommendations I have for new VCs coming into the industry is just to say that when you see hundreds or thousands of pitches, you just develop a really nice instinctive calibration of what quality looks like and what quality doesn't look like in different areas.
And it's tough because it could be like, okay, you to you need to have a certain critical mass of data points in information security to know what a good information security seed stage or series A stage company or founder looks like. E commerce for pets, then you need to have a whole new set of reference points around that. And so I advocate for both, for new folks coming into the industry, understand where you're hunting and make it more defined than just generalists.
I think we're kind of moving out of an era of generalist venture capitalists and also just see as much as you can really early on to develop that calibration for quality. That's the best I can do. Yeah, no, that's really helpful. So you learned a lot, you know, really built up their their infrastructure. And then, you know, we all know where AngelList is today, you know, one of the market leaders with community and and and just connecting people.
And then it sounds like the next step because that was a that was a role where you're doing a lot of sourcing and screening and then, you know, your next step at Greylock. I think that's where Reid Hoffman was. Right? Still is. Yeah. Yeah. So he's still there. So that was Reid Hoffman's one too. And I think we talked about us both knowing Chrissier. You know, Chrissier, you know, wrote the book Blitzscaling.
So, Chrissier has grown to be a good buddy of mine, but, but, know, with Greylock, you know, what are what was the transition in your role? So you were you still doing a lot of sourcing and screening? You know, how did your role kind of evolve into into that capacity? Because that's also a tier one fund. Yeah, it was, you know, it is a great firm when I joined in 2011 and I'll sort of get to how I joined and what the remit was.
But, know, I think we had Facebook, LinkedIn, Palo Alto Networks, Pandora and Workday all go public in the same year or within sort of a eighteen month span. I mean, you have a better year in venture capital than that. Was phenomenal. But backing up, I mean, yeah, at AngelList, I was doing a lot of screening and connecting, right? I didn't have to source because our reputation, I mean, we had hit product market fit and you had a lot of inbound with the brand Greylock.
Thousands of people on both sides, investors and startups wanted to work with us. So it was a small burden off of your back of not having to because you had to do a lot that nothing we didn't touch on is just the outbound that you have to go through, right? You have to go out there and actually find those deals. Because AngelList wasn't really I guess it sounds like it was still the early days.
So that's a completely different dynamic, where you're managing a fire hose versus creating the fire hose, right? Exactly. That's exactly right. So screening, picking and connecting versus sourcing and sort of filling the top of the funnel.
So what I mean, what I had developed with my research coming out of Oxford and at AngelList was a really strong set of opinions that venture capital is changing and is becoming more modern, is using product code, data system process research to basically build these embedded advantages within venture capital firms. And that's what I care about. I enjoy investing. I love it. It's a super fun part of my job.
I love working with counters, but I really also care about how our industry becomes a more modern version of itself over the next decade. So that was the mindset that I had. And I think the conversation I was recruited into Greylock by John Lilly and James Slavitt. And I think the conversation was something like, I think the industry is changing and you all might be in trouble. And I think their answer was essentially, we don't totally believe you, but you don't seem like total crank.
So you can come in and have an office and you can start thinking about this. And I did, and I started experimenting and poking around and ultimately hired, you know, analysts and engineers and built more of a program to see how we could use data code process and research to get some scale and some visibility into mostly top of funnel sourcing that we didn't have before. And twenty eleven, twelve, thirteen, fourteen, it was pretty early in that.
Now you see more models of interesting firms doing that. It's a little more common and a lot of the stuff that we did within Greylock, like company tracking, talent tracking at scale, etcetera, have been done more publicly or by other firms. And so that was that was the remit was to work on top of funnel. And, you know, again, you know, another legend at the firm. Reid Hoffman, he talks a lot about distribution, I forgot the name of his conference, but, you know, he wrote the book blitzscaling.
So what are some big learnings or wisdom that you you glean from Reed? I mean, I'm gonna I'll lump all the a bunch of the partners in instead of talking about Reed. Oh, That's great. That was a place. I mean, Reed, I have huge amount of respect for. He's a fundamentally good human. He Mhmm. He's also brilliant. I'm not just saying this about people to suck up to them. I mean, he is Like a huge love fest live on LinkedIn. I mean, I don't I don't mean that.
I've I've had the privilege of working with some really smart people and being in the same room with them and learning from them. Reid follows his passions. He follows his curiosity and instinct. He's good to people like fame, power, whatever hasn't changed that at all. And he's always thinking about what the next wave is going to be and he's always thinking about impact.
He cares about improving the world in a way that is non existent in venture capital, but you know, a smaller set of folks do that. I loved working with a bunch of people there. I'll drop a couple names, but I mean, many of them were fantastic, but I learned a lot from John Lilly. We thought He thought a lot, and we also spent a lot of time thinking about what modern networks would look like and how you would tackle, you know, the large incumbents.
Like what would it take to tackle Microsoft Microsoft Word with cloud native, social native, or sort of collaborative first approach that became Quip, which was sold into Salesforce? How would you tackle Photoshop from a collaborative first principles approach that became Figma? Was his investment. I'm super happy that that's worked out for everybody.
So I learned a lot from John, learned a lot from David Z. I mean, of the things that David is really good at is really understanding what two or three things matter for a given investment decision and not trying to fill up an investment memo with, equally spaced sections on team market traction, risk, etcetera. Like what are the two to three questions that actually matter here? And David was exceptional at that. But I learned from a ton of people there.
It was an incredible place to be Do those two to three questions get it's those two to three questions that get extracted, do those vary based on the company or are there a couple main heavy hitters that, you know, are always relevant with any kind of deal? I guess if there's two to three questions that you're asking yourself or even asking the founder.
I think you can do the basics pretty well in venture and say, okay, the buckets are team product market traction and maybe a fifth bucket and really inspect those and you can get to like a six out of 10 pretty easily that way. But I think really asking the questions, okay, well, what does product mean if you're tackling this type of market with this type of customer, they're gonna buy in this way and the competitive dynamics are, ABC, you have these different players.
How do you have to build a product differently or be on a different product path versus something that is, the easiest example is like PLG product led growth attempts versus something that's top down enterprise sales. They're just gonna be a very different initial product. And if you have a mismatch in your teams, like one of them, a team thinks about the world from a PLG point of view, but it's in a category where an enterprise sale really makes more sense.
You need to know that you need to have that opinion about how to think about the product in that context. And so it's a little more than just having these buckets. Think it's understanding or having a strong opinion of what the success path of a company would look And then what are the risks and what is unproven for this early stage company? And how do you start to tackle and assess those questions?
Sure. Okay, so you built a huge track record, I'm assuming from Greylock built some really good industry experience. And then and then just kind of tell me what happened after that. Yeah, kept working with next career steps. Yeah, I mean, I kept working with other firms, for a while as sort of an advisor working with firms like Wing and five hundred Startups and Hone. Earlier you mentioned models that tell you to invest or not and that being the future.
I mean, I can tell you that's actually worked already because I've built some of that stuff in the industry. And so in corners of our industry, can build machine learning driven models that probably can auto deploy. And I've done a bit of but ultimately started working with Alex, my partner at Ridge, four plus years ago, tackling sourcing.
And then that quickly became a conversation about, would you like to join first time and sorry, full time as a partner and really contribute to building, you know, the next generation of Ridge? Yeah, yeah. So I mean, that's a that's a pattern I've been seeing too. So there's there's two big forks that I've been seeing with VCs, especially technical people. So I don't know if I share with you earlier. I'm also an electrical engineer, I worked in product for some time.
So those kinds of people, it's really interesting. And I was kind of mentoring somebody a little earlier, because there was a whole concept of like the jack of all trades. Mhmm. And I think that's still great because you can kind of jump in. You could be like an Elon Musk, right? You can like one day launch a rocket company and then later launch a brain control company.
But I think what's also really interesting is if you're like a double or a triple threat, so if you're good at product, but you're also good at explaining the product in ten seconds, those two combinations are not always easy to find. And then, you know, maybe another one for engineering is like if you're good with engineers, but you're also great with right? Like those two, two or three like power skills that normally it's like three or four people you'd have to hire.
But that person, because they have those two skills together, it's really interesting. So like VCs that kind of come from like a tech or product background or builders, I'm seeing a lot of them use AI to build their own CRMs. You know, they're they're building their own databases. They're integrating in with Zapier to, you know, automate things. So I've been seeing a lot of that too. So maybe you can share some thoughts on that or kind of what you've been seeing in terms of the building process.
Yeah, absolutely. I mean, so much of what you say I agree with, I sort of feeling like I'm nodding my head over here and, you know, double or triple threats. I agree with that. And, you know, we could talk about specialization versus generalism in venture as well, if we want. But on the building side, I mean, I just don't think our industry has historically been very well run. We assemble this capital and maybe a brand, build a brand and assemble these people.
And there's just not much infrastructure or system to it. And what I really care about, and I'm kind of agnostic about the way you tackle it honestly. I think there's a couple of dozen models that can work very effectively in venture if you execute the crap out of them. But what I care about is building an internal embedded advantage and making parts of your venture work systematic, right?
And so, we deal with a lot of code, we deal with a lot of data, we use a lot of data at Ridge and we're not the only firm that does that now. It's still not the majority of firms, but there's a growing set of us and we do all that and it's effective, but I care just as much about how we make great diligence systems with processes that are highly systematic. And I care about how we win at an extraordinarily high rate, the deals that we seek.
And neither of these things are particularly code based. Like we've written a little bit of code to automate parts of that, but it's much more like how do you build a process code and human system to tackle this again and again and again. And we win over 93% of the deals we seek at Ridge, which is a really high number and we do it in a bunch of different ways. And so I think about all those ways and how they stack to build advantages.
You know, another good example is we have something we call the Ridge Revenue Network, which is three thirty plus VPs and C level buyers at fortune 1,000 companies. And this is not completely anomalous in our industry. Like other firms have versions of this. I can't think of another firm that does it quite as effectively and accountably at the earliest stages as we do. We track the crap out of our customer intros. We did somewhere between three and four hundred intros last year.
We have quotas for different companies. We're gonna send you 25 or 50 customers this year. We have a dashboard we look at every week, we capture every single introduction.
So when you can build that value and build that embedded advantage and then communicate that to a founder with a lot of confidence, with a lot of accountability and with a lot of evidence to back it up, like we're not just saying we're gonna send you customers, here are examples of where we've done it and here's what our quota is for You can win more deals and you can become involved with more great companies.
And so what I care about, I love the code and data stuff, but I care about how you build these unfair, like these systems of unfair advantage within your firm that a team works really closely with. Yeah, yeah. So I think that's it. I totally agree with that. And I think when you're building alongside the founders and you're telling them, hey, you know what, like you guys, know, we want to back you guys. But hey, we're also builders, so we're building software, we're processing petabytes of data.
And that's kind of a different type of venture firm, right? It's almost kind of like building a data company, or b2b SaaS network within a firm would mean most venture funds, these people are busy, you know, going to every single founder event. But if you can kind of like, sound a little different and actually do something different and function like a data company. That's essentially how you're going to get edge.
Then the other piece that I've been really, really passionate about, you know, seeing so many emerging managers through my platform is the community aspect of it. So, people you know, so this is a big takeaway for me. And this is actually driving me to think about a rebrand. You know, people don't really look people love Ridge Ventures, but who they really love is actually Brendan. Right?
Like, there's a the best brands now, and I think that's gonna continue to happen in the future is a human, is a person. So when you think about, like, mister beast, people I actually met somebody that ate the mister beast burger. I didn't go to eat his burger, because it was, a two hour wait. And and I know somebody that ate the burger, and it was, like, it was worse than, Shake Shack. So Shake Shack in my mind too, maybe I'm a snob, but I don't think their burger is, like that tasty.
It's it's okay. But like, if it's just as good as Shake Shack, like, don't think it's that amazing of a burger, but it's magical because it's like Mr. Beast Burger. Right? And he's built this huge community of people that believe in what he's doing. They believe in his mission. And you see that now in venture with a lot of the funds, building huge communities and networks on like on Twitter, and now on TikTok as well.
So I think when you have that, you can build franchises, you can sell different products. I mean, we see Kim Kardashian launching her PE fund. We see we see Gwyneth Paltrow really, you know, scale out that goop brand. So I think that's really powerful, where like the brand of the fund is actually the person.
And then if that person moves on, that brand still follows that person versus, you know what, I was at, I was at Sutton Capital for some time, and then I launched, you know, Beach Capital, you know, that that, you know, you don't kind of have to lose that portability of like you being tied to that. And same thing like, I mean, you know, SpaceX, Tesla, it's all Elon, right? So like, it's the same, it's kind kind of the same thing. So I don't know what your thoughts are on that.
But I think, for me, that's my thesis with the next step adventure. Like, if you already have the community, it's much easier to build a technology, especially if the community really resonates with your mission. If you can build, you obviously have to build a good product, but it's much easier to have the community that really is following your mission.
And then you know, they're using your product because it's much easier and that community lives there versus like building the product and then say, hey, you know what, like, we're gonna build this product, it's gonna cost us like, you know, half a million to build the MVP. And then we're gonna do a bunch of Facebook marketing to hope that we'll get some users, especially with the rising ad cost. But like, that's my thesis.
I don't know if you like what your reaction is to that on community and like, and I think that's, and then let's also talk about like the fund and LP ecosystem kind of where you see that too. Yeah, let's hit the community one first. I mean, there's a lot that I agree with what saying. I would say the caveat is, again, I think that there's a couple dozen different models of venture that can work effectively and win.
And the community oriented ones are probably like a quarter of that bucket where people are really leaning into it. I mean, it's always been the case from Valentine on that reputation precedes investors and brand, what we all call brand is a big thing for investors. That's not a new thing. I think the social media piece has helped a lot a new generation, a certain portion of the new generation really build their brands and followings.
But I think a lot of the, like we don't have the loudest voice at Ridge and we don't have the most well known brand, if you pull our near network community, I think the NPS is really, really high, which is one of the reasons we win a lot of deals when we sort of connect folks with other folks to reference us. And I think you have, especially in the more, call it boring areas of software enterprise or company building, you don't have these loud public social media brands.
You have a lot of people who are incredibly well respected by the people who know. So I think there's different layers of that and what that following influenced brand can look very different. I think I've been super curious to do a quick analysis of like the most public people on Twitter and their, you know, their returns. I can't I don't have that data, but I would love to see that analysis and I'm not sure what would what would show up. Yeah, no, it's a good point.
I think the performance is really the meat and potatoes of like, you know, obviously, you're delivering value to your your LPs. And then I think another data point or another column to add to that too is maybe like capital raised, right? So the the reputation like when we got like 20 VC, right? We've got, you know, we've got that person, raising, you know, a couple couple $100,000,000 in capital.
But then Greylock is, you know, especially when that got started, I'm sure they were not, like, the loudest social media influencer. I mean, I I I don't see Reed as type of personality. More quiet and conservative, and it's actually really hard to get access to be able to invest in Greylock, I'd assume, because it's a oversubscribed fund. So to your point, yeah, I mean, community can also be driven by the the well known reputation of that person, which causes oversubscription, essentially.
Yeah. And I mean, what I care about Joel a lot is not how we build individual, like, I would like Brendan Baker's reputation to be great and for, you know, millions of adoring fans, but actually what I care about is how Ridge is seen. And so I actually care about how you build that institutional reputation as a firm, not as individuals, because I think that's right. If you move from place to place, your reputation follow you.
I actually believe that the future of venture is much more sort of strong firms versus hopefully strong free agents. And you see, it's interesting, you see a lot of firms like Ridge, we tend to do really well if people sort of inspect our reputation at close range. Other firms I think are really interesting. One that is relatively new and has done a great job is Better Tomorrow Ventures. I think they just have an inherent ability to build a great community.
They're kind of near the early stages of that journey, but the way that I think those two interact with their ecosystem you know, engenders a lot of goodwill, a lot of respect, And like that community aspect has become one of the reasons that folks wanna work with them.
And you have everything from that to what First and Brett has built at First Round, which is just sort of like institutionally building that community in structured ways, generation of GP after generation of GP or generation of startup investment, the waves of different funds and who they've invested in and just building all the tools for first round to create and own that community. And I think that's what like, that's what more firms should aspire to be over time. I think that's a good point.
I think that, you know, what you described is essentially what everyone should be graduating into, you know, the community focused, it is hard. Yeah. And you need the infrastructure, you need to also have mature people that can help you envision that infrastructure and communicate that clearly to LPs because a lot of these LPs have mandates that they got to follow. So if you don't, if you're not in alignment with their mandate, you just can't fit their criteria.
So having someone that's kind of been around the block and done that before, you know, for these fund managers, you know, they would be beneficial for them to partner with somebody. We see the we see the athlete community doing that a lot, too, because they they haven't been in that sector before. So you know good CEOs they find the right people that have experience to kind of come in and lead the way to kind of get them to institutional stages.
So I think that's a really good point and definitely an important graduation point for everybody to grow into as they as they evolve and investor as investors. Tell us or to start interrupting Joel, but something that you do well, right? Like this is exactly what you're doing is building structured approaches to building a community of trust and respect and attracting more people that want to work with you and work with people around you. Think that's exactly what you're Yeah.
And I'll be honest, I mean, best way for me to learn, I'm not anybody that's a guru or an expert, but I just try to find smart people and like, have them share like their knowledge. And I just try to aggregate it in the best way. Then in doing that, I just kind of build my own education that way from from just smarter people. So I think it's a network effects of just doing that in itself.
For me, too, like when I, know, the the fund accelerator community that I built, it's really been fun because I've seen like the that we have smaller funds, these funds have large communities and networks. But then I have, you know, there are funds in our community that are on fund five that actually don't have a network, but by default, they do because, you know, they're just so they're just so inundated with inbound requests.
And, you know, they're on they're on their fund five, their fifth fund, they're raising like two funds at the same time. Right. So just from all of that traction and momentum, it's really to your point, that reputation that kind of makes them institutional grade. And, and then, you know, I want to spend I know we got like seven minutes left, but I want to go deeper because this is something we're both passionate on. Was like, where do you think venture needs to evolve in the future?
You know, so we we have all these all these frameworks and technologies and communities. We're all building, you know, APIs and and, you know, smart screening technologies. But what are we still missing? And I and I wonder if like my experience with that Zillow magical experience is something there. Like, you know, you found a fund or no, you you found, an LP that you were interested in, and then maybe a platform's like, hey, do you want to meet him?
And, like, imagine if you could actually connect with that LP because that LP definitely needs to find a fund manager. Like, I feel like that would be really cool. And it was just something that I wanted to bring up with you on this talk. But, know, we got five minutes. Tell me like what else you think could really change venture? Yeah, I mean, I think I've been thinking more. I think that's absolutely right.
I think there's probably space for a widely adopted AngelList at the GPLP fundraising level. I think you'd have to not be able to just provide that button to immediately connect with the person, but there's just so much, there's so much like trust and filtering and other things behind, like before you get to that point that would influence whether that would succeed. Like how do LPs believe that, I mean, do this, right?
So how do LPs feel comfortable that these are vetted, credible GPs that are worth their time, that are doing something slightly different. I mean, maybe the angle is like, what is that? I'm riffing it completely at this stage, like, what is that institutional advantage that this person or this firm is building and how is that verifiable versus, oh, do you have proprietary or non proprietary deal flow? Do you have good deal judgment as individuals, etcetera?
Maybe it's structuring that or building a set of LPs who actually care. Well, I mean, lot of them actually care, but like bet the next wave of their investing and they're supporting GPs on that. I think about it more though, Joel, from a firm point of view and how we build individual modern venture capital firms. I don't have one cohesive answer, but I do have some pretty strong themes that I care about.
I mean, first, we're building teams that are much more representative and diverse than ever before. And that's actually happening quicker than it seems because these seats don't come up that often, but we're moving in that direction thankfully pretty quickly, I think. Not as fast as we probably want, but we're moving I think about a lot of like, how do you get scale? And scale means a lot of things.
It can mean saving one partner hour with two hours of analyst time, or it can mean 2,000,000 data points collected by a machine. So there's a spectrum of scale, but how do you build scale and system into your firm so that you can be more efficient and give your team sort of superpowers on the way to finding and supporting great companies. But above it all, what I think about is alignment. Like why do you exist in the industry? What value are you bringing to startups?
Do they understand what that value is? Do they care about it? Do they choose you over other firms because you show evidence of that value? And then how do you back that up when you're working with them to increase their odds of success? And then that value has got to come from somewhere. Is it a network? Is it a set of customers? Is it a data advantage? Is it insights that are unique in some way, but like what is the machine that creates that?
And so the more you align and focus your firm around like the layers of this, the stronger it is in my opinion. And the more that it's a dispersed, diffused generalist firm with a shared pool of capital, the harder I think it's gonna be in the future. And this isn't to say that the firms that are generalists with great brands won't succeed. I mean, lot of them will.
But if I'm making emerging manager bets these days, I'm probably making it on really aligned, really focused and really specialized investors in my opinion. Yeah, no, that's that's a good point. I mean, that's why people I mean, for me, that's the entire reason why I built this platform, because I have a cool index of people that are focusing on different sector areas. And then underlying that is really hard to access deal flow.
Plus, you know, so this is a this is the break in the model right now on the incentive side. So there's a fund manager that's trying to raise their fund. There's an LP this that obviously has a mandate that has to deploy capital. And then, know, there's a broker dealer, right? So the broker dealer, their incentive is just to close capital. It may not even be a great fund or it may not even be a great deal, but they're just trying to close capital.
Right. So I think that issue in itself creates a quality issue. And and that's kind of resonating with what you were saying earlier. So, you know, if you think about it, when you invest in direct deals, a lot of times you get some insights from other funds who are friends. So I think LPs who are friends with other LPs that are they both have to do the same thing for their job.
They have to find interesting buckets of of opportunities to deploy their capital to compound and preserve capital and then also protect it. So I think, you know, one hypothesis I have is, you know, allowing LPs to kind of share essentially deals like with each other or funds.
And that's organically how I've found some really interesting fund managers, you know, there'll be an LP and say, hey, there'll be two or three LPs and they'll be like, Joel, this is a really cool fund manager, he's focusing on climate change, or hey, here's a really hot FinTech fund. Do you know him and him or her? And, you know, it's kind of come organically through, you know, almost like grassroots recommendations.
So, you know, with that in mind, you know, how do you programmatically build something that augments that? I don't think we're at the point where to your point, it's it's not like an index where you can, you know, purchase the S and P 500 or or just, you know, buy Facebook or Tesla through through a platform. I think with this type of investment product, it still needs to be through like a warm recommendation. I don't know. I think that's probably right.
And look, there's other stuff that comes out of those recommendations. Like how does this manage manager treat your capital? Do they treat it with respect? Do they report well? Are they fair and reasonable in their valuations? Like, are they treating your capital the way that you would like it to be treated? And these things don't come through in Cambridge Associates, you know, benchmarks whatnot. And so there's still a lot of information that you get from other LPs.
I do believe there's a future out there where it's a little more efficient. And I admit, I don't really know what it looks like yet. Yeah, there are some there are some platforms that are now building some qualitative reviews. But then I think the challenge also is like, how are they getting incentivized? Like, do they get incentivized if like a fund signs up? And then, you know, they write a nice review about the fund to pay them.
So I think the incentives, you know, those are kind of things that we'd have to, you know, we we'd have to have a whole workshop on this. You know, if you've if you actually do wanna, you know, do something like this, that could be kind of cool. But, but anyways, I know we're out of time. And, Brendan, you know, this hour flew by. So definitely a lot of crazy stories, that I did not expect. So, you know, super grateful for you taking your time out. I know you're busy.
And, you know, hopefully, we get to catch up soon. Really appreciate it. Yeah. It's been a super fun conversation as expected, Joel, so thanks for having me on. Yeah. Likewise. Well, take care. Have a good weekend. And everybody else, enjoy the rest of your week. Take care. Alright. Take care. Bye.