[00:00:28] Jay: Hi, everyone. Welcome to the First Customer podcast. My name's Jay Aigner. Today, I'm lucky enough to be joined by Dan Goldsmith, Matt Wallach, and Jonathan Brassington, general partner and founders at Proofpoint. Hi, guys. How are you?

[00:00:42] Dan: Jay

[00:00:43] Jay: so I'm gonna go round robin real quick. I know you guys, Dan, I've had you on the podcast.

I know you're all local Philly guys, but, can I please get a quick round robin on, let's start with Matt. Matt, where did you grow up, and did that have any impact on you being an entrepreneur?

[00:00:58] Matt: Yeah, I think it did. I grew up in Delaware County, Wallingford, Pennsylvania. I think that it probably impacted my being an entrepreneur because I was not surrounded by rich people growing up, and I was surrounded by kind of hardworking people. there were no rich kids at the school. and I think that it probably gave me motivation to try to do stuff on my own. and the most important thing I learned growing up there was on the soccer field. I was a really competitive soccer player, and what I learned was the harder you work, the more you win, and I really love winning. And if you're playing a game where you're the main player, like if you're an entrepreneur, the harder you work, the more you win if you're good at it. And so it was sort of one way of taking the other people out of the equation, and so I was always starting little businesses on my own where I didn't have to rely on anyone but myself, and if I worked hard, then it worked. So I do think that my upbringing there in Wallingford played a role

[00:02:00] Jay: Love that. 

Dan, where are you from, buddy, and did that have an impact?

[00:02:06] Dan: It's good to see you, Jay. So I grew up in Chester County, in Chester Springs, Pennsylvania, which, you know, 50-plus years ago there was really nothing out here, so I felt a little bit out on an island. But my upbringing was all about family. I had parents that were incredible and brilliant, and I had an older sister who effortlessly got straight As, and she's absolutely brilliant.

I've had the privilege of working with her for the better part of the last 25 years. So what imprinted on me more than anything else was I was never gonna be the smart one. I wasn't, I didn't really have anything athletic like Matt did with soccer. So my shtick was being willing to do stuff that other people weren't willing to do.

Taking risks, taking on challenges. generally when people said something cannot be done, I would run after that thing, headfirst. So that's a little bit of me and how I grew up.

[00:02:51] Jay: Jonathan. What about you, buddy?

[00:02:54] Jonathan: So I grew up in, British Guyana in South America. and it was, I was certainly influenced, from an entrepreneurial point of view by my extended family. Many of my aunts and uncles were traders. Guyana imported most of its consumable products and, and then exported, rice, sugar, and bauxite. And y- you were-- as a trader, it was very entrepreneurial because everything was hustle, right? And I lived that as a young, child and then a teenager working in their businesses, and that bug kind of stuck with me as I moved to the US.

[00:03:33] Jay: So I've heard three very kind of strong entrepreneurial stories. Matt, how do you guys work together then if you're all really, really strong independent entrepreneurs?

[00:03:46] Matt: yeah, I think on paper we look very similar, but if you know the three of us, we're a little less similar. Dan is the hardest working individual I've ever met, except for his sister. His sister actually laps him, which is weird. but Dan is just a machine, and he gets a million things done a day. And John is just loved by everyone who's ever met him. they want to spend more time with him. They want him on the floor. They want him in the room. They want him as their friend. They want him at the dinner. If you've met John, you love John, and I'm somewhere in the middle. I can be lovable, I can work hard, but I would say I'm less consistent about both of them

[00:04:22] Dan: Matt's not being,as generous to himself as he is with us. Matt has this uncanny ability like no other human being to cut to the chase and drive to the very specific point that, you know, it would probably take me or John hours to get to. He can walk in a room, ask one question, and it changes everyone's point of view, and that impacts our strategy, it impacts execution.

So as Matt mentioned, the three of us are very different,in some ways, but, you know, very complementary

[00:04:51] Jay: I wanna see how good your guys' memory is. John, do you remember who your first customer was at your business?

[00:05:00] Jonathan: In the business that I founded, LiquidHub, absolutely. It was the Vanguard Group

[00:05:06] Jay: How did you get those guys?

[00:05:09] Jonathan: As a, local Philly business, we,built a lot of relationships with people in the community, and we went to a vendor pitch, where we asked them to give us their hardest problem that nobody else wanted, and we took that project on and earned their trust

[00:05:30] Jay: You made it sound so easy

[00:05:32] Jonathan: It took a long time

[00:05:35] Jay: Dan, who was... Well, you've owned several business. I know everybody's owned several businesses on this call for the most part. But, Dan,first customer, I know we've talked about this and you had a couple memorable ones. Pick your favorite, first customer at your businesses. Which one was it?

[00:05:49] Dan: So I'm gonna pick, Veeva. Matt and I were together at Veeva for a long time, but when I joined Veeva, I was the flag carrier, flag bearer for our international expansion starting in Europe. And our first customer was LEO Pharmaceuticals out, specifically out of Eastern Europe. So it was Slovenia, the Czech Republic, Slovakia.

And, I'll forever remember them as a customer. I'll forever feel indebted because when you start a business and you have no customers, it's really hard to get them to sign a contract and agree. In fact, I remember through procurement telling me that we should be paying them to use our product, instead of the opposite.

that didn't happen, but LEO is still a customer,of Veeva 

[00:06:32] Matt: That's actually a good intro into my answer. 

[00:06:35] Jay: I was gonna say, is it the same one? It can't be,

or is it? 

[00:06:38] Matt: because I was there from the beginning. Dan was there from the beginning of Veeva International. So to put it in context for people who don't know Veeva, it's a pretty big company now, $3 billion in revenue, publicly traded. But, you know, you gotta go all the way back to the beginning to remember the first customer. I was selling, so I was the sales rep, 'cause there were, you know, five of us, and the other guys were building the product. The customer was called Publicis Selling Solutions. They were a contract sales organization. They signed a contract because I begged them because I really wanted a customer before we had a press release that launched the product. the contract was for $3,360, and in return, they were allowed to charge us $3,360 in consulting fees for helping us build the product. Now, they never sent us a bill. They did pay their bill, but every big business starts small. Like we can't all start with Vanguard like Dr. Brassington

[00:07:43] Dan: Yep.

[00:07:44] Matt: earlier. Veeva started with a $3,000 deal, and I signed it myself, and then Peter, my co-founder, said, "Dude, you're running sales.

You can't sign the order form yourself." And so that was the last order form I, I signed at Veeva

[00:07:58] Jay: I love that. Well, I mean, all right, so you've all... I, you, I get it. You've all done lots of really successful things. You've sold businesses, you've done other things. Like why... Can somebody tell me why there's the natural progression to start investing and building other people's businesses? And like, what, why are you guys all doing that?

Why does everybody kind of do that after they've hit a certain point? Like what are you guys getting out? What did you get out of that? I know, Dan, we've talked, so again, we know a little bit, I know a bit more about your story and the angel investing and kind of, I would say like, I, don't know all the details, but baby you're stepping your way into it as to where you are now, but much different. why is that the case? I mean, anybody,John, like,why is investing now something that you're excited about and something that like actually makes you passionate that you wanna continue doing? I'll put that down as John

[00:08:46] Jonathan: Oh, so look, from our lens, when we started working with founders and operators at that early stage, one of the things we recognized, very quickly is that we had the opportunity to benefit from mentors along the way that helped us when they probably had a lot of things to do, but they took the time to help us at pivotal stages of the growth of our businesses. On that premise, we built lots of pattern recognition of how entrepreneurial businesses go from startup to scale. So we're at this stage of our life where it's super exciting to work with high-energy entrepreneurs, help them realize what are the steps and the methods to build and scale their businesses, roll up our sleeves and channel their passions, help them to avoid making all the many mistakes the three of us have made number of times on the journey of-- that we've had building our businesses

[00:09:43] Jay: Matt, Dan, anything to add? Like, why do you guys do it? why are you, like, investors now?

[00:09:49] Matt: so I was pretty happily retired from Veeva,

[00:09:52] Jay: did hear this, by the way. I heard they dragged you off the golf course. I did hear that. That

is true 

[00:09:57] Matt: they dragged me off the golf course. I'm not on the golf course as much. I'm still doing a lot of the philanthropy stuff that I was doing. I'm not giving that up. I have less kids around, and so I'm not really taking time away from them. They don't need as much. But I wouldn't have done it if it wasn't all this AI stuff that's going on. that is the thing that makes it interesting enough for me to do it. Spending time with these guys, great, but it wouldn't have been enough if there wasn't some seminal change going on. And I think that the, what's going on with AI today feels a lot like what happened with software as a service 20 years ago. And Dan and I and John, from different perspectives, were at the beginning of that. And I think that having managed through that and seen what it requires for customers to buy stuff and actually use it versus just buying it and screwing up a different technology, I think gave us a lot of experience on how to adopt something brand new. and it's not as easy as just building a great new product. And so I think that not only is it interesting to see these companies that are kind of at the forefront of using AI to do interesting things, but I think we can be at the forefront of helping people figure out how to adapt, how to adopt it broader than just a bunch of pilots, and to actually use it and actually get value from it

[00:11:17] Jay: Dan, anything?

[00:11:19] Dan: Yeah, I mean, John and Matt covered a lot of it. For me, on the personal front, you know, I've been the beneficiary of mentorship and opportunities over the last 30 years through my career. and I think now more than ever, founders need investors who have operating experience and can help them see around corners and navigate very unknown and complex waters at this stage.

let's be clear, the three of us spend a lot of time thinking about Proofpoint and starting Proofpoint, and if we did not think there was the need for an investment firm like ours that took an operator-led approach and building that pattern recognition the way that we work with these companies, then we wouldn't have started, Proofpoint.

But for me personally, the opportunity to work with these amazing founders, these brilliant founders, hardworking founders, and sort of give back that gift of mentorship and guidance that the three of us all benefited from, I think that's a lot of fun, too. that's a big reason why I'm in it

[00:12:15] Jay: How

are you guys not wasting... So go ahead, Jonathan. Go

[00:12:18] Jonathan: Yeah, the one thing I wanna add is, you know, as we became investors and then, you know, we reflected back on fact that many of us raised capital, whether it's from private investors or public companies or we-- and we've helped entrepreneurs raise capital. One of the things we always recognized was that there was a special type of investor that every entrepreneur liked. So when we designed Proofpoint Capital, we set out to build that kind of investor that entrepreneurs would value, right? And there are a lot of investors that don't add as much value. We set the context of who would we have liked to invest in us along the journey that would have helped us in demonstrably critical ways

[00:13:01] Jay: Well, how are we not wasting time with all this garbage coming at you? I would have to assume right now with vibe coded every... Like, how is any of this stuff real? Like, how are you guys getting through some list of anything to go like, "Yeah, this actually is a real technology that's actually does stuff, that has a real backend," and it's al- and it's not just, you know, they didn't write this in Claude before they got on this call.

Like, how are you guys dealing with that world in general? Because I have to assume it's just a fire hose of hot garbage, coming at you guys. And anybody can jump in on that one

[00:13:35] Matt: So the strategy of what we're going to invest in helps. we're not investing in pre-revenue companies, and I think that eliminates, I don't know, 60, 70% of kind of the hot garbage

[00:13:49] Jay: Mm-hmm. 

[00:13:50] Matt: because we're not investing in a kid with an idea and a vibe-coded demo. We're investing in a company that has been at it long enough that they've built a product that is fully deployed at least one customer and the customer loves it. That gets rid of a lot of people. And it can't just be a pilot. It has to be past the pilot. it's not that hard to do a pilot. Like when Dan started his company, got three pilots really quick. It's easy. Anybody could do it. That was a

[00:14:17] Jay: Yeah.

[00:14:17] Matt: dig, Dan. You're supposed to like fight back

[00:14:21] Dan: No, I, if I can do it's easy. There you

[00:14:23] Jay: but 

[00:14:24] Dan: go.

[00:14:24] Jay: but how... That's the question though, how even... So what is the process? What is your intake process? Like, how are you actually validating that these companies have revenue? And like, is there like a, is there a website and you're just getting a million things a day? Like how does this work?

How are you guys getting new customers in or new companies you wanna invest in and like actually take the time to look at them?

[00:14:44] Matt: Dan's been in charge of

that. I'll let him go for it 

[00:14:46] Dan: so our situation is a little bit unique, Jay. what... Let me start. Traditionally, what VCs do is they're surfing, PitchBook and Frequint and Crunchbase and a lot of these public databases or subscription-based databases, and they search with different filter criteria, and then they have droves, you know, historically they've had droves of analysts sending emails out to try and generate interest and that's how they can connect with companies.

And a lot of VCs will talk about the volume of the deals they, they look at. And there is a certain amount of volume you need to look at to be out in the market. because of who we are, because of the last 30 years of operating, we've developed a trusted network of people. So a lot of the, what we would call a deal flow, if you will, in, venture vernacular, comes through our network.

Probably the highest quality comes through our network. And what that looks like is we have trusted advisor, you know, people of ours in our network who are bringing opportunities to us. You know, so they have a, they know someone who's a high-performing founder who has a great idea, or they think it's a great idea that they're bringing to us, because they know there'd be a potential good match.

or companies are reaching out to us because they know our story from places like LiquidHub and Veeva and Structure and others. So, they see, our value proposition of operators as investors and operators who have worked at the top of their profession as operators resonates very quickly with founders.

One of,our, and this is an important point, when we started, part of our thesis was that given our backgrounds and given the way that we engage and work with founders would want us to be their investors. They'd want us on their boards. They'd want us to be involved if nothing else has proven true over the past six to nine months, it's that fact.

It's the fact that when we talk to founders, we ask different questions, we think about the businesses differently, and it's not because, Jake, we get more data or there's some secret sauce in the data. It's because we look at the companies through both an investor lens and an operator lens, and we're able to see patterns that don't show up in a spreadsheet.

And so because of that and the way we engage and the potential value we can add, when we talk to a founder, they want us to be part of their team. They want us to be on their board. They want us to be their investor. So, and then there's the formal process of diligence and doing all the details. the hard part is we'll look at 1,000 companies, and there might be one or two that are the right fit for us, and the right fit, as Matt mentioned, has to fit a certain category and stage.

 but more than anything else, it has to be a company where we can help create and drive unique value and outcomes with that company. we've looked at a lot of great companies that, are not the best fit for us because it's out of a domain or area where we have expertise and network, so we'll avoid those.

[00:17:34] Jay: What happens if you guys make the wrong bet? Do you just lose a lot of money? Or just, is it just but a headache? You're just like, "This sucked. This wasn't a good one, and we have enough to balance out the rest of the portfolio." Have you guys had that yet? I mean, I know you've lived in this world for a long time and seen those. Have you guys experienced that yet? And what happens? Do you guys plan for that? Like a certain percentage is not working out and you cut your losses, and that's a write-off? Or how do you guys deal with the downside of a company that just doesn't pan out?

[00:18:02] Jonathan: we've done a lot of deals together and some are amazing outcomes with, you know, massive return on capital and some are losses, right? That's an expectation in the venture investing world. There is an expectation that you would have some percentage of your deals that, would be your loss ratio, right? So the bet for us, Jay, is with our first fund, we would invest in 20 companies, and we expect several of them to be significant winners, with a few of them likely returning multiples of the fund, right? But we also are practical about it, and there'd be a few that may not work out, and they may be sold.

We may get back our money or get back half our money, and that's an expectation in the overall formula of the risk-reward ratio of a venture fund

[00:18:58] Jay: it. Dan, you were talking a little bit beforehand about, kinda how fund is comprised and how you guys kinda came up with the idea, like, and how you're... I would-- I feel like everything's a two-sided marketplace for the most part. Like, every business is just, like, connecting one thing with another.

Like, and this feels like kinda what you guy- There's the venture side, and then there's the investment side. you guys are getting money and giving money. How does that work? And, like, how do you gu- how do you pick a number? Like, how do you... I know you guys are very analytical, and you have all sorts of data, but just from a general, how would you guys pick the stuff you wanna do?

Like, how do you how are you working with the companies that are at the right stage, at the right phase? I know you've experienced this for a long time, but tell me, what does that look like when you're sitting down to kinda figure out what the portfolio needs to look like?

[00:19:37] Dan: Yep. So the first filter is pretty straightforward. like Matt mentioned, we own companies that are post-revenue, but just post-revenue. We own companies that, we're interested in companies that are not too large. So what that usually means is companies from a revenue perspective are about 500,000 a year in revenue to maybe seven or eight million in revenue.

we want companies that are focused on technology and specifically AI, obviously, with so many companies focused on AI and AI software. we also focus on companies that are vertical, because of our background. We've been vertical professionals for our entire career, vertical meaning industry-specific.

So that means if you're a consumer-focused company or you're a horizontal company or security software company, those are not the right fit for us. So we have a certain criteria. some of our core industries obviously would be financial services like sciences and healthcare, where the three of us have spent the majority of our careers.

So the first filter is really those clear, quantifiable criteria that will filter out a lot of the companies. After that filter, we're looking for a number of things. We're looking for companies that are in markets. So a lot of venture firms will talk about investing first and foremost in the founder and the team.

We actually look at market first. it's something we learned from the businesses that we ran. You can't fix a bad market. it may be hard, but you can fix a team, you can fix a product, but you can't fix a bad market. So one of the first things we look at is this a good market that can sustain and you can build a very successful scaled company into?

Then we'll look at the team, we'll look at the people, look at the founders. and a big topic for a lot of investors right now is the moat or the defensibility. So we spend a lot of time working with these key companies to understand not only are they in a great market with potential, but are they building products and a team, are they structurally doing things in a way that is both defensible and enduring.

so there's some proof points, pun intended, that allows us to evaluate, these companies and then make a smart decision. John, Matt, what else would you add?

[00:21:48] Jonathan: Okay. when we started to think about our investment strategy, we used a framework that exists in the investing world of thinking about companies by stage, right? So one dimension with stage. So for stage, you know, in-- generically, that's pre-seed, seed, early growth expansion,and then buyout. And then there are funds that focus on specific stages. Our stages that we choose are seed and early stage. As Matt pointed out earlier, we don't do pre-seed, which would be pre-revenue companies, and we're not doing private equity buyout. So we have a very specific stage definition. Then we built on what are the type of company. We don't do B2C, right? Almost all of our businesses are B2B or B2B2C, right? So many of them have that enterprise go-to-market motion where we have deep expertise within our team as well as our broader in-operator network, right? We then look at, as Dan pointed out, the difference between horizontal companies that are industry agnostic versus industry specific or vertical companies. We made that choice. So we went through several criteria where we applied filters to say, how do we focus on adding the maximum value of our expertise in picking, winning, and then value creation for the companies to invest in? Because we're in the business of making bets that will return meaningful outcomes for our investors

[00:23:21] Jay: Yep. Matt, what do you think the best mode is for a company these days for, to protect against AI? What's the number one kind of thing?

[00:23:32] Matt: you mean for existing companies to protect 

[00:23:35] Jay: For an existing company, I should have phrased it better. Yes, an existing company to protect itself, and its IP or its product

[00:23:42] Matt: can imagine I've thought about this one a lot 

[00:23:44] Jay: Maybe 

[00:23:45] Matt: you know, Veeva's market cap went from fifty billion to twenty-five billion, and Veeva was a little better every day during that time. So, you know, and it just moved along with all these other software companies. So, you know, as a board member there, we're thinking like, you know, how do we message that everybody's wrong? and so what is the best moat? So I think the best, like the number one top of the pyramid is unique data. Data that is valuable to run the company, to make decisions that nobody else can get because it gets created by the usage of your system. I think that's the most.

The second and similar is relations-- is trusted relationships. So if you have broad distribution and people don't like you, that's not a moat. But if you have broad distribution and salespeople all over in relationships with lots and lots of customers across your market, and they trust you,

[00:24:41] Jay: that is really hard to compete against because people have generally not thrown out enterprise software that has high switching costs if they like the company. We usually say you have to hate your enterprise software vendor for at least two years before you replace them. those are the two most important things. And if I were to list five things, I'm not saying code. It's, it was never about the software code. So the thing that you can do fastest and easiest now, write lots of code, that is not impinging on someone's competitive advantage. What it is doing is it's potentially putting pressure on their ability to keep prices where they are potentially. but it's-- you're not gonna replace someone with a cheap solution if it's an important enterprise system, if it's a system of record, and especially not if you trust the company and you rely on the data that only that system can provide

Yep. that answer. Anybody else have anything on that? John? Dan?

[00:25:43] Dan: You know, Jay I'll add something maybe a little bit adjacent, not exactly. But I was reading an article yesterday about investing in companies and founders and startups, and it was talking about the new flex in tech is how little money you've raised, not how much money you've raised. And I, this is, the first time I've done this one.

I read the article twice, and because it was really interesting, it made me think deeply. But we've been through this era over the last decade or so of companies touting, "Hey, we raised $100 million. We raised $500 million," and going after that. In addition to what Matt highlighted around, it's never been the code or how many lines of code that have been written creating that moat.

It's also not the amount of dollars that have been raised either that necessarily determines the winner. And I think Veeva is the prime example, you know, one of the most efficient companies. I think, Matt, what is it, six or seven million raised in the history of the company. it might be one of the most capital, if not the most capital-efficient, companies in the history of technology.

And so I think we're gonna see in conjunction with how easy it is now to build, how easy it is to maintain, how easy it is to upgrade technology, we're gonna see that capital efficiency play much more into the equation of valuations and success of companies moving forward

[00:27:06] Jay: And how much of that, how much of a company's reliance on AI do you guys take into account, right? Like, how much of the technology itself is proprietary anymore versus like... And do you guys-- do you do deep... I mean, you obviously do due diligence, but like deep code dives to understand which is which, and Matt or John, anybody who would like jump in on that, like where's the line drawn between like what somebody owns and what's their outsourced AI?

[00:27:33] Matt: The the first line is the intelligence of the system using the underlying models that are available to it, to everyone, right? 

So if it's, you know, it's using OpenAI and the others, Anthropic, the others, like anybody could do that. And so it's-- we haven't seen a model where you create a really deep competitive moat where the intelligence of your system is these base foundation models. So that's the first level. then we have to try to figure out, you know, where is there some IP? have they invented something or is it just publicly available stuff and they're writing some code and they just think that they're gonna be smarter or faster or better in some way? it's-- I don't know that we're doing code reviews at any point,

 because we're not investing in the infrastructure, right?

If we were investing in a company that wanted to build a model that's gonna compete with OpenAI, the software code itself, the technology, like they gotta invent something. You might do a deep software, deep dive there, but we're not investing at that layer. We're investing much higher in the stack at the application layer, and it's not about the specific code, it's about what it does and what it does for the company, what it does for the country

[00:28:50] Jay: Yep. And does the cost and the token usage come into anything you guys do right now? if it requires... Yeah, but I always love this, my favorite question lately is like, you know, what would you guys do, especially engineering teams because they freak out. what would you do if, you know, Claude was a thousand times more expensive today, right?

They go, "Oh, shit." Like I, I actually don't know what... You can't pass that on to your customer. Like that's not gonna work. So, but do you guys take that into account when you're looking at things these days? Like how, again, it's similar to this last question, but how reliant they are and how much money they're spending and how much of that is compared to the rest of the spend spent on AI?

'Cause I mean, eventually I think, Anthropic and everybody would just like us to all have a token budget and, you know, we punch our card and we go about our day. But like realistically, is that something you guys look at today is how much you're actually spending on AI?

[00:29:44] Jonathan: So look, this is all like a relatively new phenomenon, right? Which is exciting for us because we're a vintage twenty twenty-six fund, right? Which means the companies we're investing and betting on are new, in, the grand scheme of things. So of course, as AI adoption is increasing at a rapid pace, we have to be thinking about AI economics, and we have to think about it, in two, specific lens. One is how are-- how is each of our portfolio companies using AI to build and operate their existing businesses? So to generate code and to run their own operations, right? So that token consumption is a big deal, Jay, that we have to monitor, and we have to make sure that those operators that are running these businesses are thinking about that in a thoughtful way. The second thing, though, is how do you build AI native products and agents and embed them into your offering to your end customers, right? And then you're passing along, along token economics into your pricing strategies. So this whole concept of token economics is a brand-new thing, right? People are trying to get their heads around it.

You know, we're seeing examples of, hey, a single developer created a thousand agents and generated two million dollars of Anthropic cost in a single month, and suddenly the head of development or product team said, "What the heck happened?" Right? So these are things you have to plan-- you have to be thoughtful of.

nobody had frameworks or policies in place for this twelve months ago. Wasn't a problem.

[00:31:14] Jay: Yeah. No, I saw something the other day. It was the new EBITDA. They added an extra T in the middle for tokens. I thought that was pretty good. all right. I have one final question for each of you. Dan's already answered this one, so you better be creative, with this answer. But if you could do anything on earth and you knew you wouldn't fail, I love asking a group like this. Matt, if you could do anything on earth and you knew you wouldn't fail, what would it be?

[00:31:36] Matt: Wow. That is a good question. my-- So there's a quote by a guy named Bill Heineman, who was a great, amateur golfer years ago. he said that it was to sum up his approach to philanthropy. and he said that in golf we have a handicap system so that someone who is lousy at golf can play with someone who's good, and it evens it out. It evens the playing field so that they can play a competitive match together. In real life, there is no handicap system, so if you are born disadvantaged, it's very hard to catch up. And that was my philosophy for the philanthropy that I've been doing before I saw that quote, but he summarized it better than I have, so I've used that quote. So I think if I could do something, anything, and not fail, it would be to provide... It would be to level the playing field for kids. 'cause that's what breaks my heart, is to see kids in an environment where it's not the American dream. That kid could work as hard as he or she wants, and they're not getting out.

And so I would create some kind of charity, nationwide charity, to provide opportunities for kids that would really level the playing field. And I would do it through some kind of sports, but have it be kind of that's the Trojan horse to do the mentorship and leadership training and job training, that underprivileged kids need.

[00:33:06] Jay: Love it. And you can't fail in this scenario, so congratulations. just, you just leveled the playing field for everybody. Jonathan, if you do anything on Earth and you wouldn't fail, what would it be?

[00:33:18] Jonathan: And it wouldn't fail, that being the operative thing.

So my, big, hairy, audacious goal is very personal because, I lost my wife two and a half years ago to breast cancer,

[00:33:32] Jay: I'm sorry 

[00:33:33] Jonathan: right? So I've been really looking increasingly optimistic about the advances in healthcare and healthcare treatment protocols for cancer, and now the use of AI for drug discovery, right?

So if I would do anything and not fail, I'd be thinking about how to eradicate cancer utilizing, you know, these advances in AI technology, especially for childhood cancer. Breaks my heart to see how underserved that whole space is today.

[00:34:10] Jay: Well, Dan, you better come with the best thing ever, buddy, because, Matt has leveled the playing field, Jonathan's cured childhood cancer, and you better bring the heat with this one, buddy. What do you... what would you do if you couldn't fail?

Oh, you're muted. 

Oh, it's great, you're 

[00:34:26] Matt: button on, but people would still be able to hear him

[00:34:30] Jay: Oh, that's the best.

[00:34:31] Dan: they both went really big on, on this one, and I think I can at least, match on this one. So I would go out and tackle the mental and behavioral health epidemic that we are just seeing the early stages of, that I think is gonna-- You know, we're seeing major issues and problems with this.

And what's been... As I've gone on, you know, with my broader family, a journey of understanding mental and behavioral health and how it really impacts people's lives and the ones you love, and feeling helpless in that journey, it's become more important to me. And specifically, Jay, I talk to a lot of dads, and there's a little bit of coding that goes on when you start talking about your experience and you start pulling back those layers of, you know, maybe there's something, that there's a common experience here with a family member or loved one, or especially a child that has struggled with mental health, and that's a very important initiative to me.

I had a conversation with a good friend of mine out of Chicago and the head of NAMI at the time, the CEO of NAMI, the National Association of Mental Illness. And I asked him the question, I said, "If we took all the healthcare professional resources focused on mental health, the healthcare professionals, and we understood the enormity in the Chicagoland of needs in mental and behavioral health, what kind of coverage could we,achieve?"

And they said 2%. So when you have a problem that is so imbalanced, where capacity and demand,are so different, it's not the small changes that are gonna help solve that problem, it's the big ones. So that's something I would tackle. And the first thing I would tackle is opening up the dialogue for people of our generation who have kids in their late teens or twenties to remove the stigma and create a dialogue where we can create a much better infrastructure for support for these individuals who are in need.

[00:36:15] Jay: those are all beautiful. Mine was to go to space. So,

 not quite as altruistic as all of you guys, but, no, those are all... I love all those, and I appreciate that they're all personal to all you guys. so much success on this call, and it's just funny 'cause you're just like a bunch of normal dudes.

That's my favorite part of all of just, like, networking with people, and over the years, you're just like, "Oh, that guy's just a normal guy. He was super successful, but he's still just like a normal dude. He's a dad. He's a whatever." So, and Dan, our time a little bit together has kind of exemplified that, you know, just, an every man, and both you guys seem the same way.

So thank you guys for being on today. If, people wanna find out more about Proofpoint, how do they do that, Dan?

[00:36:53] Dan: You go to www.proofpointcapital.com

[00:36:57] Jay: There it is. All right, gentlemen, have a great rest of your week. I'll be following along and, we'll talk again soon, all right? 

Thanks, 

[00:37:03] Jonathan: Thank you.

[00:37:04] Matt: Bye

[00:37:05] Jay: See you guys 

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