 Hi everybody, welcome to this cube conversation. My friend Chris Lynch is here, he's Executive Chairman and CEO at AtScale Investor. Good to see you man, thanks for coming in. It's my pleasure. Good to see you Dave. You're welcome all the way out to Marlboro. The Mean Streets of Marlboro, I love it. How's your summer been? Haven't had a lot of some between the lousy weather and the Cape and just a lot of work travel. I've got down there a few weekends just coming back there actually this past weekend but Labor Day's over so it's back to school, back to work. We, I can't remember if some of this busy. I haven't taken any time off. We had three Super Studio events out in our Palo Alto office but then I tapped out a Google Next to go to Saratoga but we did Snowflake, we had Databricks. Obviously you were at Google Next. How were those shows for you guys? All three shows were great for us. I was shocked at the Google show, how well attended it was. It was obviously Labor Day, rolling into Labor Day weekend which I wasn't thrilled about but the show was excellent for us. A lot of qualified interest in applied AI in the universal semantic layer that obviously we sell at at scale and unlike a lot of shows there weren't a lot of people just collecting charge keys. There were a lot of people that were coming in that projects, they were thinking about how they could deploy a next generation stack to replace their SAS stuff and so it was a great show for us. So you were Databricks growth partner of the year, is that right? They're emerging partner of the year, yes. Okay, meeting what? Smaller companies that are- I think out of the start of community we were their best partner. And then BigQuery partner or what do you guys do? We're a Google partner but we also won an award for, I think it was even further segmented because they've got a lot of partners but we did get an acknowledgement out there and more importantly, we got a lot of qualified leads and prospects. That's good. And so let's see, last year, so Alex you got to bring up the picture. Last year with Tech Tackles Cancer in Boston, we have you on the right here, beautiful. Your shirt was still on at that point in time. Of course on the left we see that you can actually get cleaned up beautifully so Tech Tackles Cancer this year was May in London. And you're doing it again in November in Boston? Yes, November. What's that all about? What's the change in- So November 7th in Boston, same location that we had this summer before at the Sinclair and Harvard Square and I think tickets are already on sale. We're still adding sponsors so if you're interested in being a sponsor or a singer, you know how to get a hold of me, chris.lynch at atscale.com or get a hold of me through LinkedIn but the last year was in London because the charity is a global charity. So the research we support is for cancer research, we fund researches around the world through our organizations and we dispense the care obviously around the world. So it's a global organization and I felt like to make that point because I don't want to being associated exclusively with me or Boston because it's way bigger than that. It's about the tech community, which is global and opportunities for us to build the muscle memory of giving back. This is one cause of many that we could get behind but that it's global. So we did it in support of Cancer UK which is Princess Diana's started that foundation and we had a show at the Omera in London and I think we raised 120 or 130,000 pounds and our first night there and it wasn't bad for a first night and it was a great show. Well, it was a great show in Boston. First time I went was last summer and we were doing a lot of the previews here out of the studio. We did a lot of remotes just to pump it up but it was billed as live karaoke, live band karaoke, but it's not karaoke. You guys are actually singing, correct? And the talent is good and it's not like karaoke. You go to karaoke bar, you're like enough but you had a lot of bands, you had folks from HPE, Pure, obviously you, Steve Du Plessis and dozens of people. It was actually quite amazing. So congratulations on getting that off the ground. Thank you, thank you. Well, we have, excuse me, we have big aspirations. We're planning on doing another show in London. We've been invited by our partner at Google in Madrid to do a show, so I'm looking forward to that and we expect to move to every theater around the world eventually. Great, great cause. So theCUBE Global will follow you around. So let's talk a little tech. So this AI craze is obviously going down. You've seen a lot of hype cycles before. Your kind of AI meets the semantic layer. What do you, first of all, what do you make of people like AI was invented in November, 2022? We know it's been around for a long time. You've been talking about AI since the big data days. But what do you make of this? My instantaneous that Al Gore invented it, just ask him. Yeah, add that to us. Another notch on his belt, the internet and AI. What we do now, we got the internet from him, we got global warming from him, and we got AI from him. So what do you make of this latest hype? Is Gen AI, I mean, it's obviously amazing. You use chat GPT, it's mind blowing what it can do. But as an entrepreneur and as an executive, how do you think it's changed the way in which people are gonna be thinking about technology and investing in technology? So I'd answer a couple ways. First of all, the way I think of at scale, we're the bridge between BI, traditional BI and AI. And under that semantic layer, at the end of the day, Dick Egan used to have a saying. They just say to all the sales people at EMC. And I know your connection's there. He used to say, it's about the software stupid, when they thought like, hey, this is all us. Really about the software they built and their product. Well, I stole that, the Egan's are investors in at scale. So I got licensed to steal it, but I say it's about the data stupid. So AI, generative AI, machine learning, at the end of the day, it's all about the data. The software is only gonna be as valuable as its ability to leverage and understand the data. So what do I think's happening? I think in the marketplace, straight up AI plateaued about two years ago because we ran out of smart people to sell it to. It was smart people selling to smart people. That's a small market. The big markets are dumb people like me selling to dumb buyers like me. What I mean by that is that you don't have to be a data scientist, you don't have to be a rocket scientist. When mere mortals can leverage the technology, can absorb the technology, that's when it becomes a big market. So I think to answer your question, I think we're not even out of the first inning of the power of these technologies. And we'll accelerate that power as we gain understanding of business context, of decision context and data provides that. The data that for instance, an at scale universal semantic layer would deliver. So we definitely have a dog in the fight and we want to see applied AI growing because that's where applied AI delivers value. We've got two phenomenons, we've hit one early days of a technology limited ability for consumers to absorb it and use it and gain value. So we plateaued because we got it in the hands of all the smart people, but not all the people that do the work, not all the people that are making all the decisions, sort of the people in the corner, the one percenter brains. Obviously that has some value, but when it's ubiquitous is when it changes the world. So how is that going to happen? It's going to happen in a market where no one's got an appetite to experiment. Everyone's hiding under the table, right? Everybody wants ROI. Everybody wants lower churn. Everybody wants customer growth, right? Everybody wants cost savings. Applying these technologies to that is how we're going to gain traction and ubiquity. Gen AI, it's not going to solve all the problems. And today it's in that hype cycle of it can do everything in anything, which means it won't do anything unless we focus it on the basic use cases of today where they can be leveraged very simply, very directly and it can control and can find manner while the rest of us catch up with the power of the technology, while the regulators catch up with the power of the technology, right? So we set up the guard rooms, we set up, right? Imagine the Wild West if instead of horses and buggies, everybody had a 911 and a Ferrari. No roads, no lights, right? We would have already wiped ourselves out as a human race. Well, we could do the same thing with this stuff if we don't figure it out. So it's kind of like a kid playing with nuclear weapon, right? You might hit Moscow. Can I say that? Oops. Or he might blow his foot off, right? Technology is super powerful, right? Have we matured and developed to be able to take advantage and apply it to do good? Well, your point about, you said, dumb people like us, right? What do you mean by that? As people that don't necessarily, you may be able to code. I can't code anymore, but the point I want to make is, and I'm packing a lot of what you said is, in tech, at least in the most recent cycles, it's been the consumer piece that drove the uptake and then eventually seeped into the enterprise and changed the economics. And it looks like the same thing's happening here. Like you say, AI was like smart people selling to smart people. And we even saw this in the data, the spending data. It started to wane coming out of the pandemic. And then of course, after chat, GPT, it's gone back up. But the consumer applications are what's got it all started, what made it ubiquitous. And then the other thing is, when you think about the internet, the power law of the internet, which a lot of people have written about, it was like five or six companies dominate and then they get most of the volume and then there's a huge long tail. And it seems like something similar has happened here, but different, I want to get your opinion on this. So you're going to have the big AI models, LLMs from Meta and OpenAI and Microsoft and Google and Amazon. But then you have, and maybe Coher and some of those other guys, but then you're going to have a long tail of applied AI that's very domain specific. So maybe it's the size of model by domain specificity. And you're going to have a lot of those that are very unique, very highly tuned. What do you think about that? So I see AI platforms, AI infrastructure, and then I see applied AI, which to me are apps. So it's a stack. And it's a stack ultimately, right? As the markets grow, but this is a game of girth. You're building chips, right? You're talking about hundreds of millions of dollars of investment in time. You're talking about building one of these massive platforms, hundreds of millions of dollars in time, building domain, use case specific, applied AI apps. Anybody can do it, thanks to the cloud vendors, the hyperscalers ironically, right? So they are giving birth to thousands of companies that will be in this AI ecosystem that are building applications that frankly, at some level, disintermediate the hyperscalers. So in my opinion, what will happen is once there's enough traction here, because this train has left the station. The platforms are here. As the applications catch up and the users catch up, you're going to see a consolidation of what we've seen in every interesting vertical integration. So those applied AI companies are going to get swallowed up by the platform players who are going to be fueled and funded by the infrastructure players. So I'll bring this back to Askel. So we have been working to develop, George Gilbert, myself, the rest of the team, Rob Streche, kind of build a model of the future of data apps. And the premise is basically we used Uber as an example, where you have people, places, and things, riders, drivers, ETAs, destinations, fairs. Those are all data elements. And they're incoherent. But Google basically wrote their own semantic layer to make them coherent. Well, it's great if you've got 3,000 engineers and they're all geniuses, but the average company can't do that. So they need an off-the-shelf horizontal technology that they can apply to their business so they can inform their business in real time. And they need a semantic layer to do that. So first of all, does that premise make sense that that Uber for the enterprise is where the future of data apps is going? And how does the semantic layer fit in as a horizontal platform? So it's in my interest to say this. I'll qualify, but I do agree with your thesis as it relates to the Uber analog. And I believe that it means that a universal semantic layer is a requirement because it's that grid, it's that highway. So I think by definition, it happens. It has to be universal. We're multi-cloud, we're hybrid cloud. That's an important part of this because different workloads are optimized for different platforms and different technologies, and you have to recognize the speed at which we can absorb AI technology. One is understanding the domain of use case, but the other is there's a legacy of any organization that's existed for the last five years is built on data, last 10 years even more. So think about the Fortune 5000. How many of them are riddled with silos of data that they can't connect, that they can't look at in a complete way in their own organization? And none of them can share it and look at inside their supply chains or their ecosystems. We make data a product. We allow you to make it a service. Your data, you don't have to be in the data business. Guess what? Everyone is in the data business. And we allow that data to be monetized, external and internal to organizations. But that requires a universal semantic layer. It's not enough to say, OK, we can stitch our stack together. Nobody wants one stack from one vendor. That's so 1980s. Well, but this is the thing too, is those different data products or data elements that I was describing, a semantic layer essentially makes them coherent elements that can be coordinated in real time. Correct. And so data is coming in that informs the state of your business and actually with AI can take action on that business without necessarily human involvement. I mean, obviously there's going to be humans involved in many decisions, but humans don't have to be involved in every decision. Humans not involved in every little decision that's going on behind the Uber app. You can cancel, you can change, you can whatever. But a human is not updating the ETA in real time. The system is doing that. And that's enabled by that coherence. So that's a very powerful concept. But you said something interesting. Nobody wants just a single stack. You see an interesting battle going on now between Snowflake, Databricks. I would say Google absolutely is in that mix. Microsoft. Microsoft and AWS, obviously, because they're big, not because of their tech stack necessarily. I think Microsoft's data stack is open AI and Databricks and some of their own stuff. AWS is this collection of stuff that they've developed over the years, but still very powerful tool. Microsoft announced recently that they're going to compete against their great partner, Databricks. Well, Microsoft competes against all of its partners. But what I'm suggesting is they think they're going to deliver every element of the stack because they want to connect it to their antiquated stack, but they've got, obviously, 450,000 SAS customers. So they got a lot to protect, but the world's changed. Yeah. And so, well, it's pretty interesting point about Databricks is that basically Databricks was the Microsoft strategy for years. I mean, a lot of the VMs are running Databricks inside of Azure and then the open AI comes in and it was kind of a shot across that bow. So that's an interesting sort of dynamic there. So I mean, I would think the semantic layer unifies all that those different data elements. So it's a key strategic linchpin for the future of data apps. How would you play this as an investor right now? You're seeing a lot of the later stages call it, let's say what, series C, guys looking for C rounds, maybe even B rounds that weren't native AI or obviously having some trouble. Maybe the early stage valuations are down, so VCs are falling all over themselves to get into the AI game. I'm not sure a lot of them know what they're doing. You know, you would have a better take on that than I, but how would you play this as an investor right now? Would you wait, would you pray and spray? So, I think it's a great time to start a company because they think as an investor, I won't call them, I don't think valuations are low. I think they are more realistic from an investor perspective. From an entrepreneur perspective, the way I always look at these things, it's about the numerator and the denominator and it's only about that when you can pay me in hard currency. So, I don't worry about value as the entrepreneur. What I worry about is capitalizing the company to the next phase of its maturity so that the company's making progress in its value. Hitting your milestones, delivering incremental value, whatever the market's gonna give you, the market's gonna give you is your point. So, I think it's a great time to start a company and by the way, you're not selling into this headwinds because you're building a product, right? And in any sort of disruption, economic disruption, socioeconomic disruption, right? Global disruption creates opportunity, industry disruption. So, I think it's the greatest time there ever was until the next time to start a company because you're surrounded with disruption, you're surrounded with hyperscalers that let you build the infrastructure required in a matter of minutes, hours, to start developing your product. And you're not gonna have to sell to anybody for 12, 14, 18 months and probably not for 36 months before you gotta start making quarters and stuff. So, it's a great time to build a company because also customers are paying attention, they're interested, right? If you get an idea that can make her save her money to the front of the line, they'll vet, they'll give you access to the use cases, their domain because they're desperate, right? To find how do they do more with less? Like everybody in difficult economic times. And you can compress the time, it's way cheaper now. So, great time to start a company. If you're a company like AtSQL, you're in that middle ground, it's harder, right? It's definitely harder. The deals take longer, the bar, ROI bar is higher, et cetera, et cetera, et cetera, right? And financing those companies is also harder because the valuations have come down so much, right? In the last period of time. Now, companies that are in growth mode and need cash and the last time they raised was in that 24 month bubble. They've got to be prepared for a recap or a down round and everyone just has to, again, remember what I said at the beginning. In my mind's eye, it's about the numerator and the denominator, right? So, spend it like you, it's yours because it is yours. So, raise less, do more with less, be disciplined about it because there's no free lunch. And accept that at the end of the day, your number one job is to capitalize the company to execute on the opportunity. And that might mean you're gonna raise $100 million if you're one of these unicorns without the horn these days. And you're gonna raise it a lot less than you raised around two years ago, even though maybe your metrics are better, but you got a 30X multiple before and you're gonna get a five now. Yeah, the two-edged sword of metrics, right? Because you're saying before, when you're a startup, you don't have to worry about the metrics, you know, other than hitting your milestones and getting the product on, et cetera, but once you actually have revenue, it's like, what's your cocktail TV? And what's your retention rate? If you see the company, you're investing in the people, you're investing in the market opportunity, and to a lesser degree, the product concept, right? But it's a concept, it's a slide deck if you're the first check in, right? So, I bet on the people and I bet on the market. And great people and great markets through trial and error, through execution, figure the rest out. How do you size that up? And a lot of venture capitalists and investors would say, I wanna bet on guys that have done it before, is that a criterion for you as an investor or is it more you get to know the person, you look him or her in the eye and you say, okay, this person has what it takes, the market's there, they're smart, they're trustworthy, they're fun to work with. Do you require sort of prior proof? Because a lot of young entrepreneurs are like, I can't get the traction with the VCs because I haven't done it before. It's like, I will then maybe find a mentor that has done it before. How do you feel about that? So, I'm gonna start with, it's about 10 years ago, maybe more. I did the commencement speech at Bentley. How do you like that? And I start, yeah, yeah, I like it now. But one of the things that I said was, and I forgot where I found it, but I couldn't attribute it to anybody, but it's not mine. Professionals built the Titanic. Amateurs built the Ark. So, I look for character, tenacity, will, intellectual honesty. And you can find out those things from people, even if they haven't started a company before. It takes those things, in my opinion, to start a company. But the way I find it is, I meet people everywhere. And I look for people that aren't perfect. I look for people that have had setbacks in life because all the startups I've been involved in have failed multiple times, even though they've all ultimately succeeded. So, I understand that it's how you respond to failure, to setbacks. That's probably the single most important factor whether you're gonna be successful as an entrepreneur or not. So, I look for people that have had stuff happen in life that they could have externalized it and said, I'm here because this happened to me. My parents got divorced. My dad died, the dog died. I didn't, they love my older brother more, right? Unsuccessful people externalize. Successful people internalize. I wanna ask you about that. Because you are a hard-o. You can be tough, I'm sure, to work for. But on the other hand, people have always said to me, I know where I stand with Chris. He lays it down. This is what he expects of me. If I deliver, we're gonna be good. If I don't, he's gonna tell me. I told you, if you don't deliver, you're gonna be gone. So, I wanna come back to something you said about externalizing and internalizing. You have said before you'd rather be lucky than good. You know, you happen to be both. But okay, that's cool. But I wanna ask you about attitude. Because something you said before, a lot of times unsuccessful people will blame others for their failures and it causes them to give up to lose that persistence. How were you overtaken? Because everybody gets negative thoughts put into their heads. And somehow you've gotta succeed in pushing them out. How did you do that? How did you create that sort of positive flywheel in your life and did that lead to your success? I think early in my life, I had some personal tragedies that I didn't have the luxury of, I lost my mother in a tragic way and I was the oldest. I had a lot of responsibilities related to that. And I didn't have a chance to think about it or feel sorry for myself. I just had to do it for my other siblings, my dad, my family. So I think circumstance gives you that opportunity. Sounds weird to call it an opportunity. But I think that everything in life happens to you can be a gift. You just gotta figure it out, right? And if your first reaction is that you're gonna use it for an excuse for everything you do in your life, then one, you don't think that much of your life. And two, you don't get what life's about. Cause like nobody exists that doesn't go through some heartache. Like we all say we have our, I grew up Irish Catholic. They used to have that saying, everyone has their crosses to bear, right? I do think everyone has their crosses to bear. It's called being human, right? And just the circle of life stuff tells you, right? We watch Disney cartoons, every single one of them, the old people die. Well, guess what? Cause old people are gonna die whether it's in a kid's cartoon, right? It's just, it is the circle of life. So you're gonna experience tragedy. You're gonna experience setbacks. People who are happy take those on. They put them on their shoulders. So I just learned at a young age that like if something is in front of me, it's a challenge for me. And I like people and I look for people and I listen to people and I look for people that have had stuff happen in their life, but they're positive and they never use it as an excuse. Like in my company, if we have a bad quarter, you're never gonna hear me or anybody who continues to work for me say, well, it's the economy, the market crashed, right? It's global warming. It's Russian Ukraine. Unless you have a hundred percent market share, right? It's us, right? Cause we all play in the same world with the same frailties as human beings. And some of us figure it out. They learn how to walk and chew bubblegum at the same time. And some don't. And you gotta own it. And people who own it, right? They do the best in life, right? Are you a planner? Like, do you like plan, like meticulously write your plans down and just kind of manifest them? Or do you just sort of visualize what you want to have happen and go get it? The latter, but I'm not recommending my style or anything, but I'm not super detail oriented and I'm precise and I watch details, but I surround myself with people that capture them, right? So for me, I more, I visualize things and then I sort of direct and lead in that way. And then I do the pattern matching of where I want to go. And do I think this thing or this thing is gonna help me get there? Or do I think like they may end up on my flank and they're, you know, negative, right? Then I'm directing based on that saying, okay, what is that, starboard? Whatever that is. I told you I don't know how to swim. Or, you know, we head to the port, maybe we gotta, you know, shoot one of our nuclear submarine bombs after him. I don't know, but the idea is I always keep optionality and I'm staying at a level where I'm watching everything, but at a high enough level that I can adjust because small adjustments I make end up for everyone that I work with, bigger adjustments depending on what's happening. What about the people that you surround yourself with? I forget who it was the other day. It was this somebody who was described, maybe some podcast described as like a self-made, I think this person was a billionaire, I can't remember, like a self-made. And this individual said, I wasn't self-made. I relied on so many other people, mentors, people that could fill gaps and skills that I didn't have, you know, other capabilities. I mean, somebody could look at you and say, you're self-made, extremely successful. But what would you say to that? Did you build like an inner circle or what some call a mastermind alliance? And did you rely on that? How did that affect your growth in your career? Well, I don't think anybody by that definition is self-made, right? Because I don't think anybody accomplishes anything of substance on their own, right? And it takes a lot of people to execute. The bigger the idea, the more people it takes to execute. So I don't think anybody does anything alone. I think for me, I surround myself because I do think I'm self-aware. I surround myself with people that compliment me, right? And I'm secure enough as a 60-year-old dude that I'm not worried about anybody being better than me. I've always surrounded myself with people that are better than me. And as long as they spell my name right on the check, I'm okay with it, right? So from my perspective, it's about knowing who you are, right? And how to get the best out of yourself and surrounding yourself with opportunities that do that for you and people that do that for you. If I thought about, if I was winning a Grammy, 100%, the first place I'd start are my folks and my family. What did they teach me that made me a success in business? I grew up poor and a house full of love, so I never equated money with happiness. I equated love and people with happiness. So I don't chase money, money chases me. I chase interesting people, solving interesting problems, right? So if I didn't have that, I wouldn't be here, right? I've been working since I was seven. I didn't know until I was almost an adult that that was the source of supplemental income for the family. I had 300 customers. I learned more about business on that paper out. I had to go pick up the papers. I had to deliver the papers. I had to collect the money for the papers. It was a story of the guy who stiffed you when you were a little kid, right? I don't think you ever- Not for long. I don't know where I heard that story. You didn't tell it to me, but I heard it, somebody told me that story. So I mean, I learned real lessons to chase adults for my money and my tip. Stiffed you, but you got it back. Yeah, of course. How old were you? I was probably, I don't know, 10 or 11. But all those experiences and then all the people that I've worked with, all the mentors going back to like, I learned how to build a culture from Ken Olson, Paul Severino, right? I was part of commercializing, not just the internet, but the web with Cheng Wu, right? Cheng Wu. So like, at the end of the day, and then you know, like the guy that I walked in the door here with, right? There are so many people that I've worked with. I mean, many of the people I work with, either in my direct company or my investments, have worked with me for 20, 30 years. A lot of loyalty. Mental loyalty is obviously very important to you. That's clear. And you've been able to attract people, to stay with you, kind of no matter what. And so Chris Lynch, amazing. Thank you. I mean, it's kept you for so long, but I appreciate you coming out here. I know you're super busy and it's always great to sit down with you. Well, thank you. I feel the same. Thank you. Appreciate that. All right, thank you for watching this CEO conversation with amazing friend, investor, brother, Chris Lynch. We'll see you next time. This is Dave Vellante for theCUBE.