What the Sigma: Disrupting Data Analytics with Mike Palmer | Okay, Computer.
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Guy Dami, welcome to a special edition of the OK Computer podcast. Why is it special? Because you're here with me. Well, every edition of the OK Computer is special. I know you enjoy it more with Deirdre Bosa and some of your other co-hosts, but you're stuck with me now for the next few minutes. No, I'm not stuck with you. You and I are going to do a quick intro because I had a great conversation with Mike Bosa.

He is the CEO of Sigma Computing. Sigma Computing is a cloud-based business analytics platform. And they use that term BI, business intelligence. So it was a really interesting conversation. I met Mike a couple weeks ago at the RBC Capital TMT conference. And we were at a closed-door dinner.

dinner and some of the things that he had to say about the Gen AI ecosystem, how it affects data analytics companies and SAS models and the like. It was pretty fascinating. Stick around for that. And by the way, guys, so he and I are sitting here, you know, we do a little research, you know, before a podcast. I saw that he went to the University of Rochester. I said, you know, I grew up in Syracuse, not far from

University of Rochester. And he said, oh yeah, where? And I said, Fayetteville, Manlius. And he said, no way, because I grew up in Liverpool, which is across the town. And I said, oh really, what year did you graduate? He said, 91. I said, I graduated in 91. We both played lacrosse. We both played against each other probably for six years, from seventh grade to our senior year in college. Is that weird? That's a little weird. It is fascinating to me that you both grew up in the same era,

same area and played lax against each other, yet just connecting these dots. Now, maybe if you had AI back in the day, you could have seen into the future and identified this. Well, again, Mike's a brilliant guy, and I really enjoyed learning about Sigma Computing and kind of see where they sit in the ecosystem and how companies like him are navigating this big pivot

by many, many companies, whether they're suppliers or whether they're customers. And he had a lot to say about that. All right. You and I, we're just going to spend a few minutes of what's going on in the public markets here, because I think there's some interesting price action. This is $130 on Tuesday afternoon. We're looking at an oracle that is down, what, 7.5% or so after they reported their earnings. We're looking at semiconductor stocks that are really taking it on the chin today. We got a few more

earnings this week, one in Adobe that you and I are going to closely watch and another in Broadcom. You know, Broadcom, a day before their earnings is trading down four and a quarter percent. Adobe is also down a little bit here. Oracle, like I said, down 8%. What were your big takeaways from Oracle? Because we were looking at the sort of AI ecosystem. They've been telling this story. They're talking about growth off a low base. They think they printed about 24% in their cloud division.

But the server providers, Dell is down nearly 5%. Micron, which makes the storage, is down 4.5% on the day. Lots...

Micron that makes the memories that goes into the servers, right? And then you have some gains out of Google has nothing to do with their cloud business today. But thoughts on everything that's going on here because, again, to me, going into the year end, it's about as clear as mud what this AI trade is. Well, in terms of just Oracle, what we saw, revenue miss, EPS miss.

And then cloud services was up year over year, I think 12.1%, but that was light of what the street was expecting as well. So when you've had the moves of this magnitude and gotten yourself to the valuation, a name like Oracle got, they really needed to knock the cover off the ball in order for this move to continue. And we were talking about it on market call the other day, we were hard pressed to believe in this environment, they'd be able to do that. So

There you go. Again, it doesn't mean it's a broken stock or broken company by any stretch, but it's had a big run. And it's interesting, you know, Citi just raised their target to 194 from 157 for Oracle. And I think a couple other people raised as well. But with that said, they've all suggested that, you know, this was a quarter that was probably a bit of a

disappointment and you might see it back and fill. So about a disaster of a quarter by any stretch, but these companies have gotten themselves in positions where they really have to perform and in a way that the market is not expecting on the upside. Because if you're in line or slightly lower,

This is what's been happening. Yeah, so we've been talking about some of the weaker players, in our opinion, as it relates to the AI ecosystem. But two of the monsters have been NVIDIA, which has like basically 85% of the high-end GPU market. And then Taiwan Semiconductor, which has the similar sort of market share, a big customer of NVIDIA here. Both stocks seem to be

paused a little bit now we've talked about the smh etf that tracks the semiconductor space it's down a little more than 10 on the year this is when the nasdaq was making seemingly new highs every day for the last month or so same as the s p 500 we've addressed the fact that nvidia's 175 gains on the year nearly 25 of the gains of the s p 500 you know if these names which had

huge outperformance guy. We're not going to participate in the same way as we head into the new year. The semi-space looks like it's in a tough spot. And that's why you and I are so focused on what Broadcom has to say, because Broadcom is not a small company in the space. No, it's not. And you probably have it in front of you, but I think Broadcom is approaching an $800 billion market cap and

And it's a name that's performed, and it's a name that we've talked about that you can actually wrap your head around in terms of valuation. So we'll see if that could stem the tide. But it's interesting you mentioned the SMH. A lot of these names within that space basically topped out back in July of this year. NVIDIA, obviously, the day after their earnings release a month or so ago. But you have to look.

and look at the names like Qualcomm and Micron. You mentioned Taiwan Semi, but Texas Instruments, all these stocks have been really underperforming now for quite some time. I'll throw AMD in the mix as well, which recently got a downgrade. And you say there's something going on in the semiconductor space that nobody's really talking about because I think they're blinded by

until recently the outperformance of NVIDIA. So it definitely bears watching over the next couple weeks. Yeah, and I'll just say this about the Broadcom into the print, you know, expected 28% EPS growth next year. Okay, so that's 2025. It's trading about 27 and a half times that. High teens expected...

sales growth, and then you have margins about 76 and a half percent. And you and I have been talking a lot about Nvidia's margin expansion that they've seen over the last couple years. They've had tremendous demand, so they've had lots of pricing power. So let's see what Avago, that would be the Broadcom, that's ABGO is the ticker. Let's see what their guidance is because that stock guy back in late June,

put in an all-time high. And here it is. It's been going sideways, basically, for the better part of the summer into this current period. And just, it seems to me, it's kind of stuck in the mud, as our friend Carter Braxton Wirth would say. It's a pair of twos here. So if that guidance doesn't impress and it doesn't leave analysts and investors to, let's say, have greater confidence in 2025, I think this stock is coming in a bit.

That's going to be the tell. And I think the level you have to sort of flag if you're playing our home game in terms of stocks is the recent low we made at the end of November, about 158 and change. So there's going to be your support. We've had this big bounce up to about the 180 or so level, giving some of that back. But to your point,

Since that parabolic move we saw in June of this year, the stock has been sideways to slightly lower. So it's clearly worth watching as well. We can't get out of here before we talk about Tesla guy. The stock is making a new all-time high. It's up 5% today. That November 2021 high has been eclipsed. If we close up here on 409, that would be the highest closing high ever. The stock has gone up

about 60% from the day after the election to where it is right now. When you think about those sorts of gains as a $1.4 trillion market cap company now is three quarters of a trillion, what I want to say six weeks ago. I've never seen this sort of value creation in such a short period of time and market cap terms based on nothing fundamental. Can we agree on that? Now,

The idea is, is that if Musk is just sniffing Trump's jock at Mar-a-Lago and in the White House into the new year, and that for some reason is going to miraculously get them closer to full self-driving and then closer to robo-taxi, that's why this stock is going up. That's why the stock has this valuation. I think it's just pulled forward a lot, a lot of performance because back when the stock was 250 about two months ago, pretty bearish on full self-driving and robo-taxi and the stock was 250. So here at 400,

If you don't have a change in fundamental view, I just don't know how you buy the stock up here. Well, I mean, it was $200 stock. I mean, I'm rounding down a little bit, but on Halloween. So this stock has now doubled since Halloween. And that sort of lines up to your point with the...

Obviously, the election, but the run-up to the election as well, as the polls suggested that candidate Trump was in a position to win. So through that lens, it makes a lot of sense. Through the fundamental lens, maybe not so much. And through the technical lens, as you pointed out, we're right up against those prior highs we saw.

in November of 2021. So it's going to be interesting to see if we build on this or if it stalls out and creates this major double top. One last thing, because I think it's kind of a related trade. So Bitcoin is trading about 95.5 right now. It traded a little bit above 100. That seemed to be a magical level that a lot of folks were looking towards. And when you think about why the enthusiasm that we've seen over the last month or so, obviously has a lot to do with the hope for deregulation as it

regards this space and not only deregulation, but maybe some smarter regulation that gives some guardrails around how companies can kind of think about this as a risk asset class, whether they're investors or whether they're thinking about using the blockchain technology, right, to do other things, whatever their industry is. It could be financial services. It could be health care. You know, talk to me a little bit what you think.

this move over the last call it month or six weeks or so because we were trading 60,000 in mid-October and here we are at 95.5. And it seems like the folks that are along this thing think it's going straight to 200 from here, Guy. People like Tom Lee have talked about it. Tom thinks I think 125 or 130,000 by the end of the year. I'm not going to fight against him. I mean, so many of his prognostications have been spot on. But I look at this and it's not as you've

point out, not dissimilar to what we're seeing in Tesla. Very friendly administration towards crypto. I think the hope that somehow this incoming administration will create some sort of Bitcoin reserve, we'll see. You know, we've seen pullbacks before. And my concern here is, you know, is crypto going to be the thing that takes down potentially

the broader market. So as we're sitting here, 95,000 and change, we've traded above 100 a couple times. Some of the ancillary plays have had actually more of a move to the downside. For example, I think if you look at this move in Ethereum, which again, I want to say made the same high that we made back in March of this year, that's starting to roll over as well. It's just something to watch without question.

as we get into year end. Right. And the last thing I'll just say is that Ethereum, you know, again, smart contracts, there were supposed to be all these DeFi applications built on top of that. We haven't seen too many yet. I guess you have to be in the weeds to kind of point them out as it relates to Bitcoin. A lot of folks will highlight the fact two trillion dollar market cap, not too different than Google. Google's rallying a bunch today. But, you know, Google's a company that's going to do three hundred billion dollars in revenue and do over one hundred billion dollars

in net income, right? So it obviously kicks off something where a Bitcoin doesn't. I don't think that's a great analogy, but it's something that you'll hear, Guy Adami. Well, I appreciate it. A lot of animal spirits. I know that's a term that you can't stand. That's why I wanted to get it in here. But I think what you just said, is it Bitcoin? Some sort of correction there, taking out some of that enthusiasm relates to risk taking in the markets.

Maybe that's the case. And maybe as we get into year end and they mark up a bunch of this generative AI stuff that has worked, not the crap that we just described, maybe January is a tougher month for stocks and for the crypto guy. We shall see, Dan Nathan. It's been a joy joining you on the OK Computer, my favorite album, by the way. Yeah, it is mine, too, for the Radiohead. All right. Stick around for my conversation with Mike Palmer, CEO of Sigma Computing. You're not going to want to miss it.

All right, welcome to OK Computer. I'm Dan Nathan. I am joined by Mike Palmer. He is the CEO of Sigma Computing. We're going to get all up into what Sigma does, but I want to go through a whole host of things. We're going to talk a little bit about the macro as it relates to tech, how we met. We kind of met, but didn't meet a couple weeks ago at RBC's TMT conference at a dinner with a bunch of other private people.

tech CEOs, a bunch of bankers, the CEO of RBC Capital, which was really interesting to hear his take on a whole host of things, how actually they use technology and how they're thinking about banking and how they think about the landscape going forward. So we're going to hit a bunch of that. I want to start with thank you for being here. It is an absolute pleasure. You and I met, but we didn't meet, as I just said. We were at this dinner. It was a long table. There was probably about 10 or so tech CEOs.

There was probably a half a dozen bankers from RBC, and it was the CEO, like I said, and you were all the way at the other end. I couldn't really see you, but it was a discussion for about two hours, and it was, to me, very fascinating. You kind of stole the show. I got out of there, and I said to Jesse Chassie, who runs Tech ECM at RBC, I said...

I'd like to talk to Mike with the mics on. So that's what we're doing here. So thanks again for being here. Before we get into Sigma, before we get into the macro, before we kind of hear a little bit about how you're working with partners, your growth trajectory, valuations and the like, I want to take a step back as you and I just talked about

for two minutes. We happened to hail from the same town, which is pretty fascinating. So we just went through a whole bunch of stuff. We both, and I hope I'm not just kind of doing something you want to do. We graduated high school in 1991 across town in Syracuse. We both played lacrosse. We just realized that we probably played each other for six years starting in seventh grade, right? Yeah.

We had to have. Right? So Liverpool, Fayetteville, Manlius, super cool stuff. You went on to University of Rochester. I want to hear this. When you got out of there, you went to work for Teach for America. I did. And so I heard... My sisters were at Syracuse. They graduated in 1992. The keynote speaker was Wendy Kopp. And I remember it, okay, who was the founder of Teach for America. And I was fascinated a little bit about the organization. I'd heard of...

the Peace Corps and stuff like that. It was kind of like the Peace Corps for education. Talk a little bit about how you went from U of R, your major there, you weren't not like computer science or anything like that, and how you got to Teach for America. Great question. I wish there was a fancier story than I have no idea what the hell to do with my life. And I was, in fact...

I was five years at U of R. That's how little I knew what to do. I had a four-year. I could have graduated. They had a really neat program called Take Five, where they give you a free fifth year. I took advantage of that, still trying to figure it out. So you did a master's? I did not. I did a second degree, an undergraduate. Oh, cool. You get to put together your own kind of program. Yeah. So I guess I got to learn more. Mm-hmm.

Having said that, none of it was very practical, to be honest with you. And Teach for America both seemed like a good cause, but I think probably more importantly than anything else was we're both, as you said, from Syracuse. For those of you out there that have never been to Syracuse, my guess is you will never go there either.

There's not a lot going on in Syracuse. I had very little perspective on the world. Is your family still there? No, everyone has moved. Well, yeah, everyone has moved. And Syracuse, actually, I'll tell you a little stat about Syracuse, Buffalo, and Rochester. It's the one place in the US that have had a consistently declining population over a long period of time. And it's really hard to grow GDP under those circumstances. So it's not economically the place where you can, I guess, realize your ambitions.

And so I joined Teach for America and got moved to California. And that was really how everything began for me. I always tell everybody about Teach for America, the thing that you learn teaching is how to entertain an audience. You can imagine, I taught ESL physics. So you can imagine- - Did you know anything about ESL physics by then or no? - I knew physics. - Oh, physics, okay. - And I thought, wrongfully,

I thought, this is great. My grandmother is Cuban and I was like, this is great. Mexican kids will speak Spanish, no problem. 80% of the kids in my class were Vietnamese. - Oh wow. - So I was like, this is what I was not prepared for. So you could imagine it's like, I don't know, the seventh or eighth class of the day, you're learning physics and you speak very little English. How little attention that you wanna pay in that class at that time. So as a teacher, you were figuring out how am I going to get this point across to these kids? And they're kids from very diverse backgrounds.

And I did that for two years. And I will tell you that its relevance in terms of business is extraordinary. Being able to be in front of an audience, being able to make your point clear and understood is a really hard skill to learn. And you definitely learn it in the battlefield. At a very early age. A lot of folks, when you think about, you're nearly three decades out from college. And you think about that experience early on. And then you think about how you have to go in front of lots of different stakeholders, right? Whether it be

You know, the folks that you're trying to win business from, obviously investors and the like. You do speaking at like conferences like we just talked about. A lot of folks really get nervous about that stuff. They're really good at certain things. And that's the one thing that like really terrorizes them. Right. And so you learn that at a very early age how to do that.

You definitely get over it quickly. And funny thing is actually just even bridging a little further, when I left Teach for America at a brief stint at Anderson Consulting, but that was the time when, you know, remember the dot-com era started to really take off and talk about learning things before you were, you know, sort of ready from an experience point of view. At that time in San Francisco, there just weren't enough people to kind of fuel the jobs that were being created. So if you had any experience doing anything at all, you were immediately a leader. Mm-hmm.

But you really had no skills. Have you been at San Francisco since then? The whole time? I moved there in 1996 and I've lived within the city ever since. You know, San Francisco is a topic unto itself. Yeah. Probably an entire 10 podcasts on that one. We'll do that next time. Yeah, exactly. Let's avoid that one for now. Actually, I...

I'm a big advocate for San Francisco. It has its ups and downs. But yes, I've been there 30 years now. Wow, that's amazing. And then so just talk about like your career, how you got into technology and kind of this trajectory of that. So one benefit of Teach for America was that they kind of facilitate your transition into something else. And that brought me, as I mentioned, to Anderson Consulting, which is, of course, now Accenture. And then left there because I don't like the idea of the union system, you know, where you start as an analyst, you do your years, you go to a consultant, you do your years. Like I'm a

the most capitalist person you're ever going to meet. And for me, I like, or I often refer to this as a jungle animals versus zoo animals. I'd rather die in the jungle hunting my own than be fed. - I like that. - And so I left and went to a startup that didn't make it. But as I said before, kind of rose to a leadership position there probably before my time, took half of that company to another one, merged it in, and we eventually sold that company

That was my first two experiences in what it was like to run a startup, which I will tell you is a jungle affair. But those lessons have been with me ever since. Yeah. Well, I want to learn about lessons that you've learned because you took over at Sigma as a CEO in the throes of the pandemic in May of 2020, which is pretty interesting. Let's drill down on Sigma a little bit because I think I saw this on maybe your website or maybe on some social. You said Sigma Computing is not

another BI tool, which I thought was really interesting. So BI, business intelligence. And so why did you lead with that? I think it's in your bio of the company on Twitter or something like that. Yeah, and mostly because I don't think the world needed another BI tool. So I mean, you certainly don't want to solve yesterday's problem.

I often tell folks when they look at joining companies or the way that I think about companies that I believe will be successful is I actually don't look at the company. I look at whatever's below that company. And in Sigma's case, the thing that was changing was first, you had these many years of declining storage prices in platforms like AWS. And the law of economics will tell you that the cheaper the price, the more the volume. That's exactly what was happening. You had huge amounts of data piling up in these cloud platforms.

And it kind of went from being a liability. And if you were in the infrastructure space, the way that showed up is you would kind of move data from one layer to another layer until it eventually wound up in like tape that no one could even restore from to an asset where everyone's like, well, wait a minute, there's something in this data. We could do something better, right? We can make better decisions. We can make faster decisions. But the challenge is it's so big now. Like how are we going to leverage it? And then we had old terms like big data, which have

since gone away, Snowflake, Databricks, Redshift came along and organized that data for us. So you had these two amazing technology developments, but it didn't change for the average person. If I was working in marketing or the inventory team, or I was at RBC as a wealth manager,

Snowflake and Databricks, frankly, just didn't make a whole lot of difference for me. It was a database shift from premises to cloud. Great for an IT person. We wanted to make that layer that had changed dramatically, make a dramatic impact for that wealth manager. We wanted them to have access to tens, if not hundreds of billions of records on demand.

We didn't want to have to have them go to an expert to do their jobs. So we set out to, and frankly, Rob Woolen and Jason Franz, who founded Sigma, set out to build a product for the average person.

And keeping in mind, when you do that in Silicon Valley, we've got decades in Silicon Valley of building technical tools for technical people. Very little has been built in the B2B space for average people. And Sigma wants to really change that dynamic. So we're pretty well on our way. Yeah. So you just mentioned the three founders. What were the conditions- Two founders, just to be clear. Yeah. What were the conditions in which you came in at a very difficult time? I mean, when you think, I'm sure you started talking to them prior to the pandemic and the like, but-

I'm just curious because obviously, you know, businesses, they evolve over a period of time. Sometimes to scale that business, you need some fresh blood, that sort of thing. So explain a little bit about that transition. This was a, I will say, a crazy story, but I've come to believe and understand that most startups have crazy stories.

we tend to only hear about the ones that start at point A and go up into the right forever. But the reality is that it's a pretty winding path. Rob and Jason founded Sigma coming out of Sutter Hill Ventures as EIRs in 2014 with the idea that I've already mentioned. And I think the necessary underlying conditions weren't there. Nothing had changed to really demand a different product in the way that we've gone after that market. Of course, over those years,

Snowflake in particular really rose to prominence, obviously was the largest software IPO in history. And I think at that time, the convergence of Snowflake in the market and then later Databricks with the idea that we could take this billion person strong skillset called a spreadsheet and put it on top of this really new and powerful thing called a cloud data warehouse just kind of found its time. So on the downside, the company was six years in, it had

$800,000 in ARR and 50 employees at a time when every other tech company was booming. So it was a tough spot to be in. The flip side was it had absolutely the best idea. So to Rob and Jason's credit, first decision that we made in 2020, and in fact, when I interviewed with Rob was the day San Francisco shut down in COVID. We were the last three people in the Sigma office before it closed by mandate.

The first decision we made was to rewrite the whole product. You imagine like the gut punch of working at a startup for six years and starting over. And that's exactly what we did. Now, having said that. Was that your vision? Like, obviously there was some realization that those two founders came to, right? To go hire somebody to help them transform the business. And I'm just curious, like how involved were you in that process? Because I think at some point, I'm sure you wanted to put your own imprint on this company for the path forward.

You know, the funny thing is there's very little I's and me's in building a company. I'll tell you a little story about Sigma to give you understanding how much resilience companies need to build up. The reason that they looked for a CEO was that Rob had been the CEO and they had come up with what I would consider to be a version 1.0 product in 2019. And they hired a sales leader, a sales and marketing leader to start to take that to market. And one of the things that we say when you're building a company is that every salesperson you hire is actually a product manager.

They're not a salesperson. The last thing you want from them is actual sales. What you want is to learn as fast as you can about the interaction between you and the customer, right? The three whys. Why do they need something? Why would they choose your product? And why do they need it now? And you want to learn as fast as you can to get to product market fit. The person they hired to do that tragically died six months later on the job and

had a terminal illness, didn't disclose it. And you can imagine you're already struggling as a company and now you're struggling through this. And I think Rob at the time had decided what he really loved doing even to this day is building great product. Wasn't necessarily doing the CEO job. And

had the humility, I think, to say like, look, I'm just going to get someone else to do this because I know where I'm going to add the most value. I came in some number of months after that. So that was in November. I started in April or early May. That was the decision, actual decision-making process. And all remote. So like, how long did it take to get to know your employees other than on Zoom? Great question. Yeah.

I have two answers to that question. One is I started a practice that I continue to this day. In fact, the last things I did before coming here, I meet every single person that joins the company in a one-on-one. It used to be 30 minutes, but now it's a 50. How many employees do you have? We have 500 today. And just burst across where? Just primarily in the US? We have a couple hundred in San Francisco. We have a couple hundred in New York. And then we, of course, we're

enterprise sales model. So we have folks regionally spread out as well. And then we have maybe 20 in London now. Okay, cool. But back to the story was, well, I got to know those people through those one-on-ones, but we were, I would consider us to be the first company that mandated its employees come back to the office.

which was for quite a while, as you imagine, kind of a struggle for hiring. But at the same time, it was absolutely the right thing for speed. Which, by the way, I mean, there was such, you know, between New York and San Francisco primarily, there was a totally different view on that, you know? And I think a lot of businesses, and I've said this again and again, mentorship is really important. And I just feel like

I'm sure like we've heard it about education. We've heard it about the kids, you know, what that meant for them in school. But professionally, man, like there had to be so many of these folks who like wanted to stay home, who are set back now in their careers, probably years, if not, you know, like they're going to end up going to find something else to do. So was that kind of part of the realization for you? Yeah. And chemistry and all those sorts of things, you know, like how do you create a culture on Zoom? Yeah.

You can't. I know people try to defend this, but to use your words, I use these words all the time. You're either a mentor or a mentee. There is no one in between. So if you allow a really professional, standalone, independent person, meaning that is fully capable of doing a job to work remotely, you gave up on the mentorship part. If you allow a person that hasn't figured out how to do the job, you've given up on the mentorship part. Maybe more importantly than that,

is that every day I walk into Sigma, it's a very different company. And the time to learn is the thing that we most value. So trying to disseminate those lessons across, I don't know, 500 homes, as opposed to like the two, I honestly believe it has put us in the leadership position we're in today because we learn faster than everybody else. And if that comes at the expense of commute, so be it.

Having said that- People should listen to podcasts on their commute. You know what I mean? Like, come on. Exactly. There's plenty of ways to make it productive. Like this podcast, by the way. Exactly. Yeah. And it wasn't the most popular decision, honestly. At the same time, philosophically, it's very simple. People who invest in small companies, whether it's with their time or with their money, take huge amounts of risk. My job and our job as leaders is to reduce that risk as much as we possibly can and isolate it to the thing we have to take a risk on. And in the history of the world, I had not seen a good model of

let's work all from our houses. So we were going to take that risk off the table. I think it's paid off. - Yeah, and just as an aside, because as two former LAX pros, do you remember that movie "Scrooge" from the late 80s? There's a scene where, and this is going to the I's and me's, there was a scene where

this guy said, as my lacrosse coach said, there's no I in the word team. Like I thought that was really funny. And aside, that's one of my favorite movies from the eighties. Um, let's talk a little bit about that. Uh, I was getting to like, at what point did you realize once you kind of reoriented the business, obviously it was still a very tough time and into 21 where you were like, I'm going to put my imprint on this business going forward because I have to assume like, you know, founder led companies, um,

you know, they don't get too much pushback, right? And you come in, you take over and you're given a mandate for all intents and purposes. So at what point did you say, okay, I'm gonna do things a little differently that had been done, you know, over the last, let's say five, 10 years?

Oh, I remember distinctly when I started, I asked Rob, how do you want to do this transition? And Rob said to me, he's like, you're the CEO, just go do it. So first credit has to go to Rob and Jason because the humility there was, we hired you to do the job, go do the job. I'm not going to stand in your way. I'm not going to make it harder. In fact, I'm going to dump it on you and tell you like, go make it happen. So I had a ton of support from Rob and Jason. I had a ton of support from our board.

and still do, those things are fundamental if you're gonna be successful. The second thing was really culture. One of the things that I've realized about early stage companies are largely led by their product and engineering teams because your first job is build a great product. And engineers are not competitive. Salespeople are competitive because they win or lose. There is no middle ground. So the first thing I wanted to imprint on the company was let's take all of the things that are great about this culture, which were a high velocity mentality around doing things,

helpfulness and add winning. And so we spent time actually writing down what we call operating principles, which are not values because none of us really believe that anyone that have values on the wall do anything about those values. Operating principles are very measurable. We know what behaviors we're looking for. And one of them was like winning matters.

And we measure winning. We measure winning on a sales basis, on a performance for product basis. I really wanted to imprint the idea that winning matters on the company early on so that we could demonstrate progress. And I think, again, everyone contributes something. That's probably the one that I would say I was most passionate about. So just do me a favor and explain in your own words what the primary purpose

So I come back to, again, the idea that when things change below you, you have an opportunity to have a customer think differently. And when customers adopted platforms like Snowflake and Databricks, they suddenly had via the Internet a mechanism that could change the way that you think about your product.

to give a lot of people access to data that they could not do before. Keep in mind, like they were coming from environments where you had storage silo A, storage silo B, application A, application B. You had to have some sort of proxy for the people consuming the data to get access to it. That changed. And so what we do is take advantage of

What cloud platforms delivered and then cloud data warehouse has delivered so that we've built an interface and affect a UI for various types of skill sets to directly access that data. What that means is if you know how to run a spreadsheet, you can take those spreadsheet skills and for the first time, apply them on 50 billion records. We show our product to people and they look like that pivot table, you know, has 50 billion rows in it.

That's amazing. No one's ever done that. If you try to do that in a Google sheet or in Microsoft Excel, you have a million row limitation. But for most people today, there's no magic in a million rows. You have to aggregate data to the point it has no meaning. So if you're working in that wealth management team, or if you're working as a trader, you want like the most granular data, that's the most accurate, the most live, so that it's almost like an arbitrage play, so that you uniquely found something that's going to give you that

little advantage and that you can do that on demand. So you don't wait, right? So I have the best data in the fastest possible time with my skillset, no intermediary, I'm going to win. So what Sigma does is give that spreadsheet interface. You can write Python, you can write SQL, you can do collaboration with your

peers, you can not only do all the legacy BI stuff that I hate talking about. I love talking about the spreadsheet stuff, which is like forecasting and reconciliation of data. You can also build applications. So I often say we do all the things BI does. Everyone knows that definition. Yeah.

But no one should be paid for looking at a dashboard. People get paid for automation. You can look at historical data, you can forecast it, you can reconcile it, and then you can build on those conditions automations that make your business move faster and more accurately. That is Sigma. Yeah. And you mentioned financial services. Is that a primary end market right now? 100%.

Well, first of all, all financial services businesses are data arbitrage businesses. So if you can walk in and say, I can give you a far more secure and governed way of giving more people access to better data faster, this is basically the definition of what you want in financial services, which is why you see companies like JP Morgan using Sigma, DTCC, Blackstone, Northern Trust, I can keep going. They understand that

The more they're able to extend that access, the better they will be as companies. We have a unique side value, which is the fact that in this architecture, we never move data out of that warehouse. So uniquely, we not only were this where case where we are providing better access with less risk. So we don't cash anything. We don't extract it. So if you have like these cybersecurity products, you have lineage, you have governance, all of that that you've built in your warehouse is 100% consistent with Sigma on the top of it.

So faster and more secure is a rare message in IT, and that's something we are able to deliver. - Yeah, and so give me a sense of, let's say, partners versus competitors. - So if a partner, clearly for us, coming back to this idea of the layered stack, is going to be the database provider. They are enabling huge amounts of data to be accessed on demand.

But they, as we all know, famously get paid on a utility basis. So if you're an investor in Snowflake or Databricks, what you care about is consumption. We enable that consumption because we are bringing more people to the platform. We're allowing them to do more things on that platform. Often metaphorically talk about communication. If you think way back into the 20s and you wanted to communicate between businesses and type a letter, you had to go to somebody with a skill set called typing and you would dictate something and they would maybe pump out X number of letters a day and

And over time, as we've lowered the bar for communication, we learned to type ourselves and then we eventually had a phone and then we had text messages and Slack. Nothing got replaced.

We added. So the lower the barrier, the more you get. And the same phenomenon happens in Sigma. We have extended the ability for more people to do things far more easily, therefore they do more of it. The consequence for a Databricks and a Snowflake means that's more consumption. So we are a partner because we are synergistic in taking this data asset, making it more and more relevant to businesses. They obviously monetize that, as do we. Businesses get better value, they're faster.

they're better. Customers are obviously the ones that are sitting on the other end of that. If I'm a wealth manager, I'm working compliance at a large bank, but I could be in the supply chain or inventory team for a retailer. Those are all people. Every job is a data-driven job. The problem has always been the distance between that user and the data itself.

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In today's hyper-fast markets, it's never been more important to consider every option to raise capital, drive growth, and create value. Stay one step ahead with Strategic Alternatives, a podcast from RBC Capital Markets. In this season, RBC's experts will examine how corporates and investors are evaluating their strategic plans, reassessing their portfolios, and reallocating capital to help them lead today and define tomorrow. Tune in to Strategic Alternatives, the RBC Capital Markets podcast,

podcast today. Based on our conversation from a few weeks back, it sounds like you have a really great knowledge and understanding of what works in the public markets. And you just raised capital in May at a $1.5 billion valuation. You raised a couple hundred million dollars. And I think in the press release, it says up 60% from the prior raise, which is kind of interesting. And we talked about this at that dinner. There's a lot of folks who

who don't want to raise capital right now. They don't want to consider an IPO because they don't want to do a down round for all intents and purposes, right? And so when I think about this, like what's worked in the public markets right now, it was very narrow, right? It was the hyperscalers. It was NVIDIA, you know, who are providing the chips that go into the servers, that go into the data centers. And then there was memory. And now it seems to be

broadening out a little bit. And you had a lot of interesting comments about enterprise software in general. So I want to just take one step back here because this platform, your company prior to you getting there was built on machine learning capabilities, right? And so then we get to the end of 2022 and ChatGBT, what, three and a half comes out and it seems like, you know, less as it relates to consumers, despite the fact the first use case really was a consumer, you know, kind of interface.

It just took the whole tech world by storm. And not just in the public markets, you just mentioned Databricks. It has a $55 billion valuation, right? Snowflake, which you mentioned in the public markets, has a $60 billion valuation. But, and you just mentioned it was the largest software IPO ever, and I think it came in late 2020 or early 2021. At one point, this stock was up like 200% because it was like...

you know, it was the flavor of the month sort of thing. Well, it's down 55%. It's still down on the year and Databricks is now, you know, raising at much higher valuations. So let's talk about how the narrative around generative AI with enterprise, you know, software companies, because there's a lot of stuff going on.

Like the other day, I don't know if you saw Mark Benioff. He was on CNBC. They had just reported earnings. The stock was at a new all-time high. It was up 10%. He's on with Jim Cramer. And one of the first comments that comes out of his commentary was taking a shot at Microsoft. It was taking a shot at...

co-pilot and he's like go talk to people within microsoft you know who work there they're not even using co-pilots all right so let's talk about what this generative ai narrative has meant for you because it's changed an awful lot but i keep saying this is already part of the fabric of a lot of companies like yours it's just moving forward now at a different sort of narrative does that make sense oh i agree that it is another layer yeah

Right. We talked about cloud data warehouse layer. It's another layer. I tell everybody that one of the there are two benefits from getting older. One of them is your network is bigger. And the second is that you have more pattern matching skills. And one of the frameworks that I think of from that pattern is tech changes first, product

products change second, and people change third. And I think that we are still early in the product part of that for AI. Obviously, the technology changed. You mean like use cases, basically. Yeah. You can change the fundamental capability of a technology, as we saw where we married old ideas of AI with new things in GPUs. But products that take advantage of that are really just starting to be built now. Kind of the race is on. There's a lot of money flowing into AI. Mm-hmm.

To be frank, a lot of that is going to get wasted. That's just the way it works. That was the commentary. A lot of folks don't want to admit that right now. If you think of the hundreds of billions of dollars that are being invested to build out data centers, but a whole host of other products and services, they're going to benefit from the speed of the compute. And so they don't want to hear it. And they keep hearing this, that they'd really rather ask for forgiveness than permission. But the rate of

CapEx quarter over quarter or even year over year is declining, right? And at some point, if there's less demand for this compute, to your point, because a lot of these private companies just fall by the wayside. And we're already starting to see that. You're starting to see cuts. You're starting to see valuation come down a little bit. Then you're going to have a build out of overcapacity. And we've seen this in almost every tech cycle. So speak to that a little bit, because you had a lot of commentary at that dinner again about enterprise software and

how there's risk to some of these models in the SaaS space that were thought to be the next stage of this, but yet they were massively underperforming for the better part of this year in public markets until you saw a dash for trash in some sort of way, until you said, okay, we can only bid up 50%.

Facebook so much based on their, you know, the investments they made in meta AI. And it goes across all the hyperscalers. Microsoft was massively underperforming until very recently. So talk about that a little bit. There are two things going on here. Obviously, you rightfully speak about like the amount of capital flowing into AI and the industry is built in a way as to throw a bunch of dollars out there and

almost I refer to it as Highlander, right? We start to see like who kills who to the point where there's like a few big companies that remain. And obviously the goal for a lot of these investors is, you know, win that Highlander race and hope that the gains at the top of the pyramid outweigh the losses at the bottom of the pyramid. And I think we're very early in that cycle.

One of the things that I look at with a little bit of skepticism is what companies are building true products, which ones are building really just easy to replicate extensions off of publicly available LLMs.

If your use case is a prompt engineered LLM for a department, you're not going to make it. It's going to be too easy to rebuild that. And even if you get to a certain scale, someone is going to do even an 80% good job as you do, and then it's going to be price pressure. So I have some skepticism about some of the products, if you will, being built there.

I have a lot of skepticism about the rate at which companies are going to be able to adopt these things. If you work, as we said earlier, in the financial services space,

You've got a regulator. AI makes a bunch of assumptions that regulators have no idea how to think about. By the way, I've been saying this on Fast Money and I get so much pushback and regulatory. Like you're not like think about hallucinations. Like think about like, you know, if you're not like clicking through to the citations, like I sit on the desk at Fast Money and I'll hear some guests say something. I'll go to perplexity and I'll figure it out.

But before I say it on national TV and try to take some, I'm not trying to take anybody down, but to have like an opposing viewpoint, I better look at that citation. You know what I mean? So then you say to yourself, how much time is it actually like saving me right now? Is that, is that a decent thought process? I think it's a reasonable one. You mentioned Copilot earlier and we have a lot of developers. I kind of look at Copilot as a single digit hours per week savings for our developers.

That's just not that great. And Copilot's not new, right? It's been around for some time. And it's not to say that if we look far enough into the future, there won't be breakthroughs along the way that materially change that dynamic. But to think that we're going to wake up six months from now and we're going to reduce our development team by 50% is a pipe dream in my mind. And I think anyone that comes out to say these things is trying to position themselves in a space as opposed to talk to reality. You're one of very few people

that I've heard put your neck out there and say these sorts of things. I mean, like, it's just like, there's a lot of folks drinking the Kool-Aid. And so I also think about these LLMs, I mean, like the big ones, right? They're getting commoditized here, you know? And you have an open AI, which is desperately trying to create...

web search and browser and all these sorts of things, because how do you justify 150 billion valuation? How does Anthropic, which has one product right now, justify a 20, 30 billion, whatever it was at last thing? Because there's no difference in my mind between Claude and ChatGPT. And I use perplexity because I can choose any of them. And to me, they're no different, really. Mistral, Gemini. Yeah.

Lama. Yeah. Like there are, and you're right, they tend to converge over time and then someone breaks through and they converge over time, which is great for the rest of us that use them as a utility. And are you using them as just like an individual a lot? Like rather than going to Google and just as a person, as an individual person, uh,

Not really, to be honest with you. So you're still Googling things. But Gemini is giving you that contextual answer now, right? And so that's my point. And we can move on from this in a second. But if you pay perplexity $20 a month because you want pro and you have access to those four different models and the one that they're developing, why would anybody pay $20 a month to just chat GPT or cloud? Like, isn't that like logical? I don't get that.

Or illogical, I guess. And we have two dynamics here. We have a consumer dynamic and an enterprise dynamic. And I think in the enterprise space, and I'm not a consumer guy and I don't comment on it because I don't know anything about it. But on the enterprise side-

purchasing behavior is not going to change with enterprise. And I agree with your point. You have to have differentiation. If you don't, you don't have pricing power. I do think they're anthropic as differentiating itself from open AI in terms of deployment model. They're really trying to focus on working more individually with an enterprise. Open AI views itself more as like the way that AWS did many years ago. Here's my platform, take it or leave it. So we see some refinement, if you will, in the market. But in that conversation, the other topic that I think is maybe a little bit

more controversial, or maybe one that is starting to pick up a little bit, comes back again to the layers. So you have AI as a value-add proposition, but a lot of these companies that are trying to tack on AI to what they do are fundamentally at risk already. And in particular, my target here is what I'll just refer to as departmental SaaS applications. When we think about the fungibility that we created when we went to AWS, I tell people if

If you grew up in the time that we did and you went to a large enterprise data center, you could name. They had brand names like the hardware products in the data center. You knew who they were. That's a NetApp thing. That's an EMC thing. That's a Dell thing. No one asks AWS, what server am I going to be on? They just get a price performance guarantee. They move on. Databases have consolidated data now into these massive warehouses. Right.

So we've created a huge amount of fungibility for data. But we took the same siloed applications and stuck them on top, and we called them SaaS. And now you have companies saddled with 50 to 100 not integrated, hard to manage, not customizable, expensive applications. They're next. I really believe that we're going to start to see an environment where you have more of that platform play, where you start to see these departmental applications consolidated onto common platforms and

eroding, if you will, that sort of portfolio until we get down to some of what are now called the system of record applications, the ones that are operating at real scale. But I think they become at risk because the way that they maintain their position is because of integrations. And the more that the companies that integrate with them go away, the more they become isolated. That I think is the change that is in the offing for large enterprises now.

And I really strongly believe five years from now, you're going to look at an environment far more simplified, consolidated application stack than we see today. Mm-hmm.

which is probably going to be one of the biggest disruptions in tech and B2B and SaaS since what we just learned over the last two and a half years about how disruptive generative AI is likely to be. But I think what I'm taking away from you is that we're likely to see that in a longer time period than a lot of folks who are valuing these things in the public and private markets right now. Let's finish off with this because, again, you had a lot to say earlier.

about this as far as exits and the anticipation of exits. So obviously, and this was after the election that we met, people are pretty excited about deregulation. We haven't seen a lot of M&A or strategic M&A in tech. There was a bit of private equity led M&A, I wanna say going back two, two and a half years or so, especially in the software space. But when you think about a NASDAQ that is up almost 28% on the year after having similar sort of gains last year, I've been surprised that folks

weren't dusting off those S1s. And you could have actually made a bid for another company this past summer or something like that and just waited to see what the new administration, if there was going to be a new administration, whether they were going to be more open to this sort of stuff. And I get a sense right now, at least a lot of folks who are like all gung ho about what Microsoft and Apple and Google and Amazon and Meta might be able to do in the M&A,

It seems like whoever's in charge of the FTC might not be that much more open to what we've had. Some of these cases that are brought against all those names that I just mentioned by the FTC and the DOJ, they don't seem like they're going away anytime soon. VP-elect J.D. Vance was actually kind of on Lena Kahn's side on some of this stuff. So to me, if you can't bring an IPO in this market, forget M&A.

When the hell else are you going to be able to do it? So let's talk about that a little bit because Jesse had a lot to say, and he's done some great writing on this about what the common thought process is about a company, what they need to do, whether it be on a recurring revenue standpoint or profitability to IPO or size of the kind of market cap. You had some great things to say about it. Let's repeat it for the audience here. I mean –

In the context of what we were talking about, we're up 80% on a top line basis year over year. We'll do that again next year. So it started with people saying it's a tough environment. It's not a tough environment. It's just not. We just saw a jobs report yesterday, up again. We have a very strong economy. It is not a tough environment. The question is whether you have a great product or you're in the right market. So number one was, this is actually a great market to grow a company. It's a great market, number one.

Two, really comes down to the idea of, on the one hand, this forward-looking technology on the AI side. And yes, there are tons of dollars flowing into that space. There's a lot of opportunity. The challenge with investment is always timing, right? In some case, is AI going to be a big part of the future? Yes. When?

Don't know. How? Don't know. So there's a lot of money flowing into those bets for sure. Do you think that's like a bubble right now? Or like some of the valuations in the private market seem bubblish. We've seen massive multiple expansion. The last time Microsoft traded at 35 times, you know what I mean? That was like the top, you know, or at least for some period. And so what makes me a little nervous, not what's going on in the private markets, not a lot of transparency. You know, we know how those valuations scale.

skip up. But it feels like a lot of those things that you just mentioned are being pulled forward, at least in the valuations in the public markets. The funny thing is I have the opposite view. Oh, really? I am far more worried about the private market valuations. I feel like in watching some of the deals that I've seen go down, and one of the things about building a company is that you really need to manage it up into the right steadily over time. And I think people fool themselves that if they get an outsized valuation that it has proven anything.

But when you get an outsized valuation on a B or a C or a D round, who wins?

The employees don't win because they didn't monetize that. Your investors don't win. Actually, they've taken a ton of risk. You don't win as a CEO. I can tell you that because that monkey is now on your back. You're going to have to grow into that number. And as you think toward a successful exit of some sort, how are you going to get all those people paid? Keep in mind, right? You take that high valuation. Your next employee is now on a fair market value that is going to be really hard to justify. I am more concerned about the disconnect

that's already happening on the private side. You have a NTM basis, six to 10 multiples out there for SaaS companies. There are some that are clearly on the high side, large caps maybe. But I feel like I look at those and think, okay, that at least we understand. But when we start to see 40 or 50 times next 12 months,

How are you going to grow into that? Sales. But sales. I just want to be really clear. Yeah, yeah, yeah. Not even revenue. I know, yeah. So that's like, that's going to be tough. But both things can be true, by the way. And if we learned anything from 21 into 22 was that the public markets led the private markets, right? As far as, you know, and Snowflake is,

you know, the best example of that. That was north of a hundred and a billion dollar market cap in the months after its IPO. And it was trading at like 80 times sales. Well, if you look at OpenAI, it's doing about the same thing. How do you grow into that, you know, that multiple and how do you get to the public markets? And you know what I mean? So that's what's crazy. What's different now is that you just mentioned, you know, a D round. Okay. We're very few are able to monetize that.

Well, what I worry about when things get to the public markets is that you have these growth funds that are already participating. So then you ask yourself, who is the incremental buyer in the public market? Yeah, Fidelity and Capri and all those guys. Wellington, they're going to put orders in, but they've been participating, that sort of thing. So that's what's different, I think, if you go back, let's say, 10 years or 20 years. Does that make some sense? There's no doubt that...

what were not even crossover funds years ago, have participated for years now on the earlier and earlier side, in some cases even C-Rod. Well, that's really important. All right. So these multi-strat funds that were never participating in privates, they're looking to add alpha because a lot of them have actually been underperforming the market and you're paying two in 20 for that sort of underperformance. So how do they get alpha? You get involved in something that

is generally illiquid that you don't have to take marks the way you do on a quarterly basis, right? And report to your investors. They're kind of like side pockets, if you will. They definitely had, seemed to think they had to diversify back in the day. I do feel like now-

You know, we have a lot of debates about, and I hear a lot of debates about, can you go public or what does it take to go public? And a lot of folks will pine on this. We have an amazing board member in Brad, Brad Gerstner from Altimeter talks a lot about this. I'm not sure that, you know, I think he would make the case and I hate speaking on his behalf. I don't think that the core fundamentals have changed. If you have a strong, if you're selling into a big time, if you have a strong top line growth and you do that on a relatively efficient basis, you can go public. Uh,

You can, an institutional investor will recognize that, which is why back in the conversation we were having along at the table, when people are sort of blaming the environment, I think the first thing they need to look at is their own business. And if they're not able to deliver one of those things, the problem is not in the external environment.

So I don't know. I'm not the most- So what do you expect for 2025? Let's assume that the economy keeps humming along here. Let's say we get deregulation. Let's say interest rates go down for the right reasons. Are you expecting just an absolute stampede towards new issues? And one of the things that's

interesting comparing it to 2021 is you're not going to have these shitty SPAC models, right? Like, so these are going to be companies that are meant to go public and there's going to be demand for them, hopefully. And they're fitting this new narrative.

I don't know that there's a demand in 2025. I think there are a lot of companies. You and I, we were talking about the dot-com era back earlier in the conversation and $100 million companies that was considered a public company candidate. I don't think we're at that place anymore. So I think you're looking at $300 to $600 million.

million-dollar companies. ServiceTitan is a good example right now. But the problem with that is now you're looking at companies that are potentially growing a lot more slowly. So it's a really interesting dynamic. As they become more mature. And Mark Cuban has said this again and again, and he knows that from experience in the late 90s, is if you don't get to market where you still have that kind of really good growth that makes it attractive for investors to pay a slightly higher multiple than they would normally do for something that's a bit...

more mature of a business, like you kind of have to hit that stride to some degree. - Yeah, I think timing, I'm sure matters at some point. You know, I think 2025, I think the bigger story in 2025 and 2026 is gonna be the number of zombie companies that have to come out into the daylight.

I think there are a lot of them that are going to run out of capital. They don't really have an incentive to wind things down in the way that they probably should at this point. And they're all sitting on valuations that, you know, in some cases are probably 10x what they're worth. When I go to the conferences that I go to, the real lunch table conversation is, how do we wind these things down? And to your point earlier, and it's not to say that they're going to rise to the FTC level, but the M&A environment has been basically dead. So the one question will be, does anyone kind of wade in to consolidate these companies? Yeah.

Yeah.

Well, listen, you and I have a lot to catch up on in 2025 because it'll be interesting to see how these valuations work out, what gets wrapped up, what gets stuffed together. Listen, my sense is there's a lot of VCs out there who would love to kind of jam a bunch of their portfolio companies together and cut some costs and do that sort of thing. So it'll be really interesting to watch. It'll also be interesting to see as we get into the new year what sort of M&A, what gets filed to the IPO market. I'm probably pretty optimistic about that.

because a lot of these VCs, they need exits, right? They need to recycle a lot of this capital. So, okay, Mike Palmer, we covered a lot of ground. I'm really glad we got to do this because I feel like we met at that table. I got to hear a lot of great stuff out of you. And so hopefully you'll come back and we'll do this again. I would love to. I enjoyed every minute of it, especially to meet an old lax competitor. Oh my God. We got to go back and look at the 1991 Central New York, you know,

record there. I think we closed in the ranks higher than you guys. You know what? I think we got to the sectional finals and we got destroyed by West Tennessee, which you probably remember. They always were. They were the number one. Yeah. So, you know, one thing before we get out of here is like, you know, Central New York used to be a powerhouse in lacrosse and they're kind of done right now. They don't send a lot of kids to Division I anymore. It's really weird. I moved out to California, as we said earlier, 30 years ago, not quite 30 years ago. The number of lacrosse teams and programs, I mean...

My lacrosse stick looked like something an alien would have brought to California. And now it's not just even just men's lacrosse, like women's lacrosse is like...

It's just crazy. I love the women's game, by the way. I think it's great. I will. I'll admit to being confused quite a bit. Well, there's just a few weird rules like shooting space and you know, that sort of thing. Yeah. But, but it's a great game and it's obviously a bit less violent and the like here. So if you watch the PLL, the premier lacrosse league, which I love and I'm friends with the founder and the like, I think there's almost like gratuitous violence in that. You know what I mean? There's a little bit of a UFC and lacrosse and it's all related to its origins. Uh,

I will say, I think there's a difference between West Coast and East Coast, where East Coast is a little bit more physical, especially in the women's. I have two daughters, by the way, that play. Are they playing or no? My older one played in high school. My other one, I think, is starting in the spring. And I

And I just feel like in the West Coast, watching women's lacrosse feels a little bit like a game played by referees. That's a great way to put it. My dad, who loves lacrosse, he played in college in the early 60s, and he's the one who got my brother and me into it. He loves the women's game. Syracuse, he still lives up there. They've been fantastic for years. Yeah.

But he gets frustrated by the same things that you get frustrated by. So that's a great way to put it. And we'll leave it there. You and I are going to go get those records from 1991, and we'll see. And when we come back, we'll revisit it. So Mike Palmer, I really appreciate you being here. Thanks, Dan. It was a pleasure being here. If you like what you heard, make sure to hit follow and leave us a review. It helps other people find the show. We also want to hear from you. Email us at contact at riskreversal.com.