Episode 48: Behind the scenes of a pitch riff session

Speaker A: Foreign.

Speaker B: Welcome to Decoding Sales, a podcast where an engineer, that's Alex, Elaine and a salesperson, that's me, Peter Ahn, talk about the art and science of sales. Today we're repurposing yet another piece of content. This is a riff session between Alex and myself where we actually dive deep into the Tiger Beetle pitch and the positioning around Tiger Beetle. Now as many of you know, I just recently joined the team at Tiger Beetle to lead their sales and customer experience side of the house and it's been an absolute joy as it goes with getting started. In any new role you have to really dive into framing, positioning, the technology that you're about to sell and introduce into the world. And so as part of doing that, I framed Alex in my words, what Tiger Beetle is and the power of Tiger Beetle. Now this is keep in mind, just to give myself a little bit of a break, this is within a couple weeks of me joining Tiger Beetle full time. So the pitch and the story arc will continue to evolve and iterate. But I wanted to share with you ah all a raw behind the scenes look as to what it feels like going back and forth in rapid fire succession on the pitch of Tiger Beetle as the only purpose built financial transactions database that can truly support for real time transactions over the next 30 years. So without further ado, we'll dive in, Alex will start talking and we'll get into the pitch. If you like this format and you have any thoughts about the pitch or the story arc, definitely do. Let us know@podcastersecodingsalespodcast uh.com and we'd of course always appreciate a review a rating on any of the podcast platforms that you're listening to this through. So thank you everyone, hope you enjoy this special shout out to our founder, Joran Grief, Louis, our head of solutions, Marina, our head of marketing and the rest of the Tiger Beetle team for letting me repurpose this and for being so, so helpful during my onboarding. They've been so gracious in my first couple months and I'm just thrilled to be part of the team. It's an absolute honor and I'm so, so excited to share Tiger Beetle with more and more customers as they realize the power of what's under the and the special unique capabilities of this talented team. I hope you all enjoy this recording.

Speaker A: Part of what we've talked about in the past for like early stage startups that is like the importance of like identifying some kind of like technology like trend, some like new thing that is changing the way the Businesses work and like an early stage sales leader, like you gotta actually understand it. So I, part of me is like, huh, maybe we should talk just a little bit about that. So people.

Speaker B: Yes.

Speaker A: Know enough, have enough. Like it's kind of meaningful right. In your decision matrix. Like if you couldn't answer this question, then probably, I'm assuming you would have not said yes to this, this offer. Um, so maybe you could just talk a little bit about how you thought about that particular aspect of this in relation to other aspects and maybe through that it'll come through like you can share a little bit about it. So people have the right.

Speaker B: Of course, yeah, I appreciate you asking that. So I think the trend is that um, you know, real time transactions are only increasing, right. If you think about. And it's not when, when you think about transactions you automatically think about financial transactions. And I mentioned Tiger Beetle is a financial transactions database. But a lot of workflows have this, the same shape, um, as, as a debit credit transfer. So let me give you an example. Solar now has allowed kind of energy billing to happen in like 15 to 30 minute increments, whereas we're used to actually paying a monthly bill. But that has changed drastically. You have surge pricing during certain hours. So that's on the energy side of things. If you think about Uber, when you're calling an Uber car, there is an amount of real time transactions that is happening between consumers and a finite set of cars that are on the docket.

Speaker A: Right.

Speaker B: Um, and then you think about financial transactions like the stock market is a uh, key example of this where there's hundreds of millions of trades happening across the world. But you know the interesting thing about that is Nvidia commands like 90% of the trades within the stock market. So when there's all these like people trying to trade stocks, the Nvidia row in a stock market environment is constantly locked because so many people are trying to hit it at the same time, right? So you have this like combination of high volume of real time transactions increasing, it's only going to continue. And then you have like a finite set of rows within a database that are constantly hit these like hot accounts. And so there's this perfect kind of storm of pain happening for the engineers, the folks who are maintaining the infrastructure of trying to actually shuttle these transactions around. Right? So that's the trend. The problem is that if you think about postgres, right. So you know, when postgres was invented first it's like the enterprise database, right? And most databases today, general purpose Databases are SQL based. And uh, yeah, you're right, it's pretty old. So Postgres is a 39 year old technology. It was invented the year I was born, 1986. And if you think about hardware back when postgres was invented, it's very different from hardware today. You're talking, you know, like chip sizes were a lot bigger, it was a lot slower. Um, folks didn't believe that things could get transacted as quickly as they could through like these tiny chips now.

Speaker A: Right.

Speaker B: And so the design principles of the database were created based off of concepts that Postgres and SQL codified. Right. And so what does that mean? It means now going back to the real time transaction story and sorry, this is becoming long, I might cut out and edit some of this, but hopefully you're still following me. Like to do a single credit debit transaction in something like the stock market or like solar energy billing or even like a gaming platform where you have like transactions going on through like the gaming economy. Um, it takes like 2 to 10 SQL queries to complete a single transaction. Right. Because the um, app has to call to the database and say, okay, does Alex have enough funds? Yada yada. And then it has to call back and say, okay, this is Peter ready to receive the funds. There's all these SQL queries that happen now. What Yorin and the team has um created is a way to actually batch 8,000 transfers into a single CPU loop versus having to go back and forth 2 to 10 times or even 20 times.

Speaker A: Giving a single SQL query or a single transaction CPU loop. Doesn't make sense. That's not a thing.

Speaker B: Yeah, so a single query. Yeah, exactly.

Speaker A: Mhm.

Speaker B: Like where you're able to batch 8,000 of these into a single CPU loop. Like a single trip around from like the app to the database.

Speaker A: Single round trip to the database. Yeah, exactly.

Speaker B: Right. And so because they're, because chips now are highly performant where you can actually do this, you can actually go from a world where maybe at most you could, you know, you could have like thousands of transactions per second with your application. Now you can design for a world where you can um, confidently, safely do a million transactions per second. Right. And so that's what really drew me in. And I think that kind of trend means that a lot of these fintech companies, banks and any company that has this shape of real time transaction is rooted right now in legacy technology in terms of the database layer. And so I'm excited to introduce the tiger beetle kind of technical concepts as well as also kind of how we actually go to market obviously, which is why I'm joining. But anyways, I'll stop there.

Speaker A: Yeah. Do you think you could do that again and do it in like three sentences?

Speaker B: The trend that I'm excited about with Tiger Beetle is that real time transactions across the world and across different types of businesses is increasing. Not only like financial transactions, if you think about like consumer wallets, we now like expect funds to show up in our account instantly, but also with other use cases. For example, with solar energy now you expect to be charged on like 15 to 30 minute increments versus monthly. So if you think about the sheer volume of transactions happening across businesses, it's only increasing. The problem is that a lot of those transactions are powered by and are facilitated by databases that are very, very old. A lot of these are general purpose SQL based databases that just are not efficient. Um, considering the, the hardware improvements that have happened right from the 80s up until now. And so Tiger Beetle is allowing companies to take advantage of those hardware improvements and has designed uh, OLTP financial transactions database that is more purpose built to actually safely and quickly allow for these financial transactions to happen to the tune of like a million transactions per second versus like thousands if you were to leverage old school databases. So, so that's really kind of what, what the trend is that I'm excited about.

Speaker A: Can I try doing it in three sentences?

Speaker B: Sure, yeah.

Speaker A: Yeah. I just want to see if I can do this.

Speaker B: Yeah. So, so how many sentences was that?

Speaker A: Was that I stopped counting after like.

Speaker B: Yeah, okay.

Speaker A: So we live in a world where real time transactions are increasing massively because it makes the economy like far more efficient and allows you to save money for example on uh, electric costs if you're billed hourly. The problem is all the databases that we used to do this weren't designed for this kind of like real time processing. And in particular many of these transactions require making edits to a central resource. For example, in the stock market a lot of trades are on the on Nvidia like 90% which means that that particular individual row needs an enormous number of edits every second. Databases can do thousands, Tiger Beetle can do millions. Which means that you can scale these real time transactions by an enormous factor which allows many more people to take advantage of them and save enormous cost at the same time.

Speaker B: That's pretty good. Yeah, yeah. Ah, still like seven or eight sentences.

Speaker A: I had a lot of commas and semicolons. Peter, I promise you if I wrote that out it would be three sentences.

Speaker B: That was Good. That was really good though. Actually. I think the combination of the two would be good. Do you want me to try it again?

Speaker A: Okay, well, yeah, why don't you do like your version, like another version. How, how would you talk about it? Based on how I talk about, I'm

Speaker B: going to try and brutally prioritize it this time. So I might like leave out a lot of things.

Speaker A: I think that's actually the right.

Speaker B: I might not like it, but let me, let me give it a shot. Right. So the trend is that real time transactions are increasing, um, enormously across the world.

Speaker A: Right.

Speaker B: People expect funds to show up immediately when call for an Uber ride. We expect the, to be there with the minutes and know who the driver is within seconds. The problem is the databases powering these real time transactions can't keep up. And so what Tiger Beetle is doing is it's using hardware concepts of today to help you transact at a scale of millions of transactions per second. Whereas old school databases can help you do thousands a second.

Speaker A: That's pretty good. That's pretty good. The only thing I would like add to that, actually I would probably talk about the thousands when I talk about

Speaker B: the problem and I say, yeah, that's a good Paul. Instead of it being like a footnote afterwards.

Speaker A: Yeah, I think that, that like thousands to millions is like where you're getting like a lot of the, like, oh, there's something there. If you're like right now the uh, average database can only do thousands of these transactions a second, which means it, it's really hard and bespoke and challenging to build these systems and expense, you know, something like that. That was way too many words. But like, I think there's something there. And um, this is maybe more of an investor pitch than a customer pitch at this point, but you know what I'm saying, Like I feel like.

Speaker B: Sure, sure, sure, yeah, yeah. But it's still, I think, yeah, I think investor pitch is more. Or closer to like broadly applicable.

Speaker A: Yeah, exactly. Our, our listeners are not going to be like, yeah, they're not all going

Speaker B: to be customers or understand like the true shape of the problem.

Speaker A: Exactly, exactly. Yeah.

Speaker B: Uh, yeah. Okay. Okay, cool, cool. Do you want me to try it one more time?

Speaker A: Yeah, sure, why not?

Speaker B: The shape of the problem is real time transactions are increasing enormously across multiple types of businesses. If you think about um, the stock market, there's more trades happening than ever and accounts like Nvidia account for 90% of the trade. So there's a lot of contention and issues with trying to like, actually scalably, um, offer a, uh, seamless experience there and then. When you think about solar energy, we're now used to being charged on 15 to 30 minute increments versus monthly. The problem is that the databases underlying these real time transactions can only keep up to the tune of thousands of transactions per second, even if you were to horizontally scale your databases. And what Tiger Beetle has found is that that's just unacceptable, especially considering how much the hardware has improved today. And so they've actually developed a, uh, purpose built financial transactions database that can process millions of transactions per second to help businesses run a thousand times faster.

Speaker A: I think you're saying your previous version was better. That one got a little bit like, flabby, a little wordy. Right.

Speaker B: I think the beginning was like, not.

Speaker A: Yeah, you got, you tripped over it. Like when you got into the like, Nvidia thing, it was like it was all downhill from here.

Speaker B: Can I try it one more time actually?

Speaker A: Yeah, yeah, yeah.

Speaker B: Pretty fun. Okay. I might even just use it as a YouTube video. Yeah, yeah.

Speaker A: This might turn into more of a YouTube thing than a podcast. But you know what? I think this is, I do think this is fun.

Speaker B: I mean, like, yeah, it's fun. And it also shows, like, sales leaders don't have the silver bullet right away, you know, um, or maybe it shows that I don't have skill, I don't know. But anyways, okay. The trend that's happening right now is that real time transactions are increasing enormously across all types of businesses and industries. Um, if you think about the, um, age of like fintech companies, now we expect funds to show up immediately within our e wallets. When we call an Uber, we expect the car to show up quickly and to know who our driver is within seconds. But the problem is that the underlying databases trying to keep up with these real time transactions are based off of legacy concepts that were invented in the 80s and 90s. And so if you extrapolate that to performance, a lot of these databases can only do thousands of transactions per second, even if you were to optimize, um, and horizontally scale these databases. And so what Tiger Beetle has done, what Yorin has done, the founder is figured out a way to design the database purpose built for today's hardware principles where you can actually now design for a world where you can safely transact a million transactions per second versus thousands to help your business run a thousand times faster.

Speaker A: Pretty good. Can I try one more actually? Yeah, yeah, go for it. Yeah. Okay. I think I have a way to say this that's pretty good. So what's happening in the world today is we have all of these new products and services that are basically real time. And to make real time services work, you need real time transactions and take an Uber or real time solar price and things like that. Now, the way that those systems work, they need to do enormously high volumes of transactions. But the databases that people use to do that only can support on the order of a few thousand transactions a second. And so every company that's building these systems needs an entire engineering team designed to scale up those transactions. It's expensive, it's error prone, and it's very challenging. What Tiger Beetle has done is they have recognized that due to advances in hardware, since these legacy databases were built that are being used by these companies, there are new ways to architect that transaction processing system that gets you native support for millions instead of thousands of transactions per second. Which means new businesses can start from scratch without having to build an enormous hardware, Hardware and infrastructure footprint in order to achieve this. The same scale.

Speaker B: Oh, I love that. Uh, I love the last part of which means, like the impact statement. Yeah, that's really, really good.

Speaker A: Okay.

Speaker B: Yeah. I think part doing this exercise, I think like the three sentences thing doesn't do it justice is not what I'm realizing, you know, but you kind of need the push. Yes. There's a way the story arc happens that can be a lot more concise.

Speaker A: Yeah. I think it's really three bullet points.

Speaker B: It is, it is. There's like a here's what's happening, here's the problem, and here's a solution.

Speaker A: And here's why this. Yeah.

Speaker B: And here's the impact of getting to that solution.

Speaker A: Yeah, right. Exactly.

Speaker B: Okay, I want to try it one more time because you gave me, like, a lot of inspiration.

Speaker A: Great. Go for it.

Speaker B: Okay, so here's what's happening today. Here's a trend. There's a lot more products that are being released where real time transactions is a foundational component of that product. Right. So you think about Ubers, you expect to know your driver pretty much instantly when you're calling your car. Uh, when you're doing stock market trades. This batch transaction world where you wait a day to see what's cleared is increasingly becoming unacceptable, especially with E Wallet companies that allow you to transact immediately. And then with things like solar billing. Um, now we're used to seeing things on a 15 to 30 minute increment, whereas in the past we maybe were getting a monthly bill. The problem with that trend is that the underlying databases can't keep up to the tune of being able to maybe do thousands of transactions per second, whereas the need is for millions of transactions per second. And it's because a lot of these databases were invented when hardware principles were very, very different. If you think about the chip in the 80s and 90s, it's very different from the power of the chip today. Right. Things are getting smaller and more performant. And so what Tiger Beetle has done is they've reinvented and re architected the database from the ground up to actually support a world where you could safely transact a million transactions per second versus thousands. And the implication of that is that you don't need this heavyweight upfront investment in infrastructure and a huge footprint to be able to keep up with that speed. You can actually start to, um, create a solution that's purpose built for real time transactions and launch products faster while still ensuring that your costs don't skyrocket.

Speaker A: Yeah, it's pretty good.

Speaker B: I think there's still more tightening, but I think that that shape with like 30% less words.

Speaker A: I want to. Yeah, I have two thoughts. One is. I don't know if you need all three examples in the first section. And two, can I just. I think that it actually would make sense to pull into the problem. The existing solutions are bespoke and expensive because clearly like Uber exists. The problem is. You're right.

Speaker B: Yeah.

Speaker A: Right.

Speaker B: Coinbase and Robinhood.

Speaker A: Yeah, yeah, yeah, yeah, yeah. Uh, yeah. So let me try something.

Speaker B: Okay, Cool, cool.

Speaker A: So we live in a world where transactions and interactions are increasingly becoming like real time things like calling an Uber and getting a driver instantaneously. Now those, there's still. There are tons of those transactions. There are like millions of those happening in real time around in some cases. And the problem is the databases of the present, by default kind of naturally only support thousands of these transactions. So all of these companies that handle real time transaction processing have to overcome this enormous hurdle of building their own bespoke solutions to this problem. This transaction problem. It's expensive, it costs a lot of money, a lot of hardware, a lot of engineers. What Tiger Beetle has realized is rather than building unique bespoke solutions, they can go deeper down the stack and re architect the database to take advantage of modern chip technology that has improved since the original core databases that people are building on were built to shift from a world where the default is thousands to where the default is the ability to process millions of transactions per second. What this means is that all of those existing companies Become legacy infrastructure. They either need to upgrade and save a ton of money on their existing infrastructure, or new competitors can use tools like Tiger Beetle to undercut their costs and massively outperform them because they can use many fewer engineers and many fewer hardware resources to get the same or better results.

Speaker B: Dude, that is killer. I love this. Can we do like a couple more runs? Like for a couple more minutes?

Speaker A: We got like five minutes. Why not just like.

Speaker B: Okay, okay, cool. Let's just keep. This is hard stuff. Okay, so I'm going to try and condense your feedback and use what you just said. Okay, so here we go. So the need for real time transactions to really make sure your businesses run fast and you're able to ship products that have revenue implications. Okay, let me start over. Um, because what I was trying to do there is see if I could talk about the impact in the beginning too.

Speaker A: Yeah. Oh, I have an idea for you. Customers and society as a whole is increasingly expecting real time information.

Speaker B: This is good. Yeah.

Speaker A: And that means real time transactions. You want to get an Uber? You can't. You're not waiting a day, you are waiting seconds for that driver.

Speaker B: Yes, I like that. Okay, okay, let me try and go down. Oh, sorry, did you want to continue?

Speaker A: Okay, okay, Take it.

Speaker B: So customers across multiple industries are now expecting real time answers and transactions. So you think about an Uber. You're not waiting minutes even to see who your driver is. You expect that within seconds. If you think about the leading fintech e wallet companies, you're able to actually now transfer funds pretty immediately. The problem is the underlying databases that are trying to keep up with these real time transactions. The core databases were invented in an era where the hardware chip was vastly different. And so a lot of these companies have invested a ton of bespoke resources to try and make databases of the 80s and 90s keep up with this pace of real time transactions. Well, Tiger Beetle, and that costs a lot of money, a lot of time, and a lot of engineers. Now what Tiger Beetle has done is they've realized this is a huge problem and so re architected the database from the bottom up. Um, from the ground up, I should

Speaker A: say from the chip up.

Speaker B: Ah, from the chip up. And have created a solution where you can now actually safely, um, transact millions of transactions per second. They created a database that is designed for that world, whereas the databases of the past maybe can at most to thousands of transactions per second. And so the implications of companies leveraging Tiger Beetle is that they don't have to have a Massive infrastructural footprint to, to keep up with real time transactions. And in fact, even compared to incumbent fintech or finance or real time companies, they can actually move even faster and produce, uh, even more performant experience for their customers who, like I said at the beginning, are increasingly demanding. Real time. Yeah, something like that maybe.

Speaker A: I think that's getting in the direction. I have a few quick thoughts. One is, uh, the safer thing. Always use say that and I know that's really important and a lot of Tiger Beetle stuff is on that and I would either cut it or introduce that early on and say like, you know, and by the way, this bespoke infrastructure, it's still. One of the reasons it's so hard is people need to make sure these transactions are correct.

Speaker B: Yes, yes. I like what you said about error prone. I think that's a good way to actually introduce that.

Speaker A: Yeah.

Speaker B: Because that's the other side of safer.

Speaker A: Yeah.

Speaker B: Because like, yeah, with SQL you can. It's not, it's a mutable database, it's not an immutable database. This is awesome, man. This is so fun. Uh, I appreciate it, dude.

Speaker A: I really like the, like just calling all the existing players who aren't using Tiger Beetle, like legacy giants who are like going to be hunted down.

Speaker B: Yeah, yeah, yeah, yeah. That was really good actually.

Speaker A: Uh, I, I thought that was like really good. I think you should figure out how to work that. Yeah.

Speaker B: Oh yeah, I do like that. Like they're going to have to. This is an inevitable shift that they're going to have to address.

Speaker A: Yeah. Like their cost structure will just be like worse.

Speaker B: Yes, yes, yes.

Speaker A: And more error prone, which means they can't innovate as fast, which means that they have to deal with problems rather than like investing in the next wave of technology. I mean it basically, it means they can't innovate as fast fundamentally and they can't ship products. And they can ship.

Speaker B: All these companies have like different products that they want to launch.

Speaker A: Yeah.

Speaker B: And most of them have like this core ledger that needs to be accurate.

Speaker A: Right. Yeah. I do think it's also like, I would maybe just hammer home a little bit more. Like everyone expects this.

Speaker B: Yeah. Uh, yeah, you're right.

Speaker A: I think you kind of did actually. But yeah, but there's like, I would just, I would just hang on to that point, I think.

Speaker B: Sure, sure. Yeah. Like real time is all around us.

Speaker A: Real time is all around us and it's only going to get more real time.

Speaker B: It's just that we haven't Thought about the under the hood architecture that powers that.

Speaker A: Uh, yeah. And it's really hard to do that. Tiger Beetle makes it really easy. So we have a bunch of legacy players plus a greenfield for people to develop on. It's like, new.

Speaker B: Amazing. Well, I know you have a hard stop. This was fun, man. This took an unexpected turn.

Speaker A: This was a real. A real unexpected turn. I like this Stu, though. I mean, it was kind of like, how do Alex and Peter grapple with, like, you know, describing something? I don't know how interesting it'll be to other people, but it was fun.

Speaker B: I thought it was fun. Yeah.

Speaker A: I got something out of it.

Speaker B: Yeah.

Speaker A: I got more excited about Tiger Beetle. Good. Oh, good. Okay.

Speaker B: So I kind of partially did my job, even though it came out as a jumble in the beginning.

Speaker A: Yeah. I also think that, like, giving a little time to breathe and, like, writing some bullet points, I'm almost like, yeah, I bet you could really write, like, some killer bullet points.

Speaker B: I think so. Yeah. And Joran says this where, like, he, like, loves this concept of simmering.

Speaker A: Yeah.

Speaker B: Simmering on a topic.

Speaker A: Yeah.

Speaker B: Right. And like, I like that because it. It, like, kind of takes the pressure away from, like, having the golden nuggets, like, up front.

Speaker A: Exactly.

Speaker B: As you could see, like, I'm kind of, like, evolving my.

Speaker A: Yeah.

Speaker B: Perspectives on the product, which. That's my excuse for my first pitch being jumbled.

Speaker A: That's. Yeah. I mean, I threw it at you off the. Off the cuff, too, so.

Speaker B: No, I love it. I love it.

Speaker A: Although I guess you should be able to do that at some point.

Speaker B: No, I should. I really should. But it's like, there's so many, like, Easter eggs and nuggets in the technology that sometimes it's like, there's a lot.

Speaker A: How do you distill it down? Is like.

Speaker B: Yeah.

Speaker A: Always really interesting.