Certainty vs. Conviction: Unlocking Innovation in Corporates and Startups

On this episode of Digital Squared, Tom is talking to Trent Johnson, Chief Strategy Officer at Cie, a venture studio that serves as an innovation lab and accelerator. Trent is a seasoned entrepreneur and venture studio expert and he shares so many valuable insights on the ever-evolving landscape of digital transformation and AI. Together we discuss the journey of building startups, the pivotal role of venture studios, and the critical concept of de-risking new ventures.

Transcript

 0:00  
Welcome to Digital squared, a podcast that explores the implications of living in an increasingly digital world. We're on a mission to inspire our listeners to use technology and data for good. Your host, Tom Andriola is the Vice Chancellor for Information Technology and data and Chief Digital Officer at the University of California at Irvine, join us as Tom and fellow leaders discuss the technological, cultural and societal trends that are shaping our world.

Tom  0:31  
On this episode, I'm talking with Trent Johnson, Chief Strategy Officer at Cie, a venture studio that serves as an innovation lab and accelerator. Trent is a seasoned entrepreneur and venture studio expert, and he shares so many valuable insights on the ever evolving landscape of digital transformation and AI together, we discuss the journey of building startups, the pivotal role of venture studios and the critical concept of de-risking new ventures. Trent, welcome to the podcast.

Trent  1:01  
Hey, Tom Good to be here. Good to see you again.

Tom  1:04  
Absolutely. Okay. Hey, so I could try to explain Cie, but I rather you do it, because I've come to know it as a little bit of a different, differentiated firm. So please tell our audience a little bit about Cie. 

Trent  1:19  
Yeah, Cie is a venture studio, and that's probably a fancy way of saying our core business is building startups and digital products. We do that for two primary groups. So one would be like partners, like corporates and other enterprise, and the other would be our own portfolio, or founders of notes. Cie basically grew out of our serial entrepreneur founders. And what those folks were really good at was standing up startups. They'd done a few dozen of them, and what they started to notice was that there was this pattern in kind of year zero to two of things that they would typically do in order to de risk a transaction. They pulled all those items together and created about a 12 to 13 week process that allows us to move through a digital venture or a digital product really quickly and get, more often than not, very great results on the back end.

Tom  2:13  
Yeah, that's again, getting to know it a little bit. I found it incredibly unique, and again, having both early, small company experience and large company experience, and knowing how hard is for big corporations to generate that type of velocity with their innovations, I found it really interesting. So how did you find your way to Cie tell us a little bit about the journey that got you there?

Trent  2:34  
Yeah, yeah. Like Steve Jobs would say the that's only makes sense when you're looking backwards. I think when I got out of business school in like the .com era, my first landing spot was basically KPMG consulting in the Netherlands. And I worked for the Big Three Dutch banks back then, pretty much all our large corporate clients fancied themselves creating startups within their four walls. So that was like the first foreshadowing back then, we called things e-business solutions, but instead of digital, I suspect it's the same thing, but 

Tom 2  3:07  
I've got a business card Trent that says I'm an E business consultant that I've kept right people do the grad students today, they don't even believe that was actually a term.  It's amazing.

Trent 3:15  
 It should be in parchment or something, Tom, but I probably have one as well. But back then, much of the solutions that we were implementing were CRM, ERP solutions, e-commerce solutions and the like. And then my career chapter one, large scale digital transformation, basically, then went on to creating my own startup. So got a taste for early stage doing that and the insanity that's associated with it. But then I had a couple kids and had to get a real job. So basically went back to boutique consulting and my boutique consulting roots, and there I spent a fair amount of time working with private equity portfolio companies, particularly around ops and performance enhancement. So a lot more of the stuff that I did there, in addition to the digital transformation, were all about margin enhancement, anything from basically a consolidation to basically an outsourcing transaction. So got that experience. And then my last chapter, if you will, started maybe about 10 years ago, moved basically to start working with early stage startups, matriculated through a VC called Wavemaker partners, and then ultimately to Cie, which is where I am now. And again, much of the stuff we do is build startups and digital products for large corporates, as well as our own portfolio.

Tom  4:36  
You and I, when we first talked, we had these kind of different connection points. I have history in the Netherlands. That's where you started your career. You've been an intra-preneur, right, doing the innovation from inside the enterprise. I had an opportunity to do that. So it was interesting. Some of the kind of, the lineups, the paths, very different. So this podcast is called Digital Squared: Life in an ncreasingly digital world. You mentioned the Internet period. This period, to me, feels similar in that we are going through a high level of disruption, not just that we're going to change the way we do things, but many organizations and leaders are having to change the way they think about things for the future. I'd be really curious to get your perspective on what is this period of time that we're in right now look like to you and contrast it from past periods?

Trent  5:23  
Yeah, looking back. And what I would say is, as I look at my career, getting out of business school and basically starting around, like the internet and the .com era, if I fast forward, then there was like a milestone that was like social media, a milestone that was cloud, and now we're in like that AI, the next one might be web three. AR, VR, IoT, all those kinds of things, right? The way I tend to look at it, it's maybe a bit different, like one one way, or one thing I think that I remember a long time ago, back in B School, was this concept that I heard, and it's probably like one of the few things I remember from this one professor, but it was the theory of constraints. And it was really interesting because it was like an ops management topic. And what it was is like, if you ever look at a system, follow the bottleneck, and if you can fix the bottleneck, that's how you basically unlock value. So if I think about each of those digital milestones along the way, the internet, .com, social media, cloud, so forth. Each one of them unlocked a certain amount of value, right? So if you think about like the internet as an example, I as a business now can expand my reach, because I now have an online presence, I could do increased marketing. The value unlocked was obviously like increased revenues. If I think about the.com era, there's a ton of investment, so very similar to this last bit that we've been going through ton of investment, ton of innovation. We repackaged the way we thought about value in business models. And if you think about the value unlock again, more increased revenues, just the different ways that we repackage value. But then fast forward to like social media and cloud, which those unlocks were more, from my perspective, engagement, stickiness, you were able to unlock long term value, one to one, marketing and personalization of those experiences in social media. And then Cloud, I think, started to be more of a cost saving, SG and a rationalization unlock, right? Because I'm now putting things that I used to have in my four walls in a shared tenant model, where someone else is actually executing the things, but I'm getting the value from it along the way. Every one of those things unlock value, I think, in the time that we're in now, when I look at and some of these other technologies, very interesting things are happening. Right? If you look at AI, it promises automation, efficiencies, improve customer engagement, that type of stuff. So what's really interesting is the value unlocked that it promises is both growth in terms of if I can apply AI to sales lead nurturing as an example, in top of funnel, and if I apply it basically to efficiency game, hey, consolidate these reports for me, so I don't have to hire a person to do the busy work, right? I think the thing that we have to be very mindful of in this day and age is digital had a propensity to remove the constraint, right? And I think the thing that we have to be careful of is that in this day and age, we humans aren't the constraint, right? And you and I talked about this before that, it feels very similar to an outsourcing model, and we can dig into that one in terms of the way, like that trajectory started with a hype cycle, and then basically how it got to some notion of equilibrium. I think those bits are largely similar, but that's the way I tend to think of kind of this day and age. 

Tom  8:43  
Yeah, I'd like to pull on that string about the outsourcing paradigm that you just mentioned, right? Because most people wouldn't put that together with what's going on. I think people would agree about the growth opportunity, about the operational efficiency and opportunity improved margins, and how you could turn that into scale. But tied to the outsourcing, let me pull that string and have you go one level deeper on the onion.

Trent  9:05  
Yeah, so if you think about a typical outsourcing transaction, right? So business process outsourcing was a thing a decade ago, right? As an example and how you would go about managing one of those transactions, you would find a department like whether it was HR or finance or some department, and the very first thing that you would do is you would inventory the business processes, right? You would look at the business processes from top to bottom. So if you were to take like finance as an example, you would have AP, AR, pretty much all the functions they're in, and then how you're analyzing these functions or on really interesting dimensions, right, like degree of subjective decision making. And what you're basically trying to answer is this question of, given the same quality of resources, the same systems, what prevents you from doing this process? Some. Or else in India or in Eastern Europe or something like that. The calculus, I believe, for AI, is very similar, right? It starts with this view of AI as this. You think about it, AI is really good at a number of things and getting better at others, right? It's really good at aggregating data, finding initial correlations within the data, summarizing the data, and then you start to get into this realm of interrogating the data and creating inferences from the data, which I think currently is still the realm of humans. And AI is steadily gaining but if I look at that continuum for AI, very much the same way I would look at an outsourcing transaction, there's an inflection point, just like an outsourcing of things. As a company, I am comfortable taking somewhere else and having somewhere someone else do it, because one, it's not strategic, or two, high volume, high cost, high repeatability, I think all those things still apply in an AI context, and then there's this inflection point right? Of, Oh, the other stuff is going to be retained, and I'm going to hire people to manage the outsourcers. I'm going to manage people to manage the AI and the prompt engineers, right? There's a lot of parallels there. And I think the last bit is, if you play that model out from when it became really popular, everybody wanted to do it because, hey, I could put money to the bottom line. These savings went straight to the bottom line. So there was an economic catalyst that kind of drove everybody doing this thing. You got past the hype cycle, you got past the capacity in the model, and then basically came down to equilibrium, right. Fast forward a decade or so later. Yeah, there's outsourcing everywhere, right? We have guys that we work with overseas and folks that we work with here, but it's found equilibrium. It's not as scary, but there was an amazing amount of displacement. When it was going on. We were all freaked out. And I think those are like, the similarities that I see between those. 

Tom  12:00  
Yeah, that's really interesting, right? The way you just walk through it, it's like you could almost fill in the blank, pull that word out of the blank, and plug this new thing in. It's taking work to India now it's giving work to AI, oversight from the home office. Right? At what point do you start to let the decision not need the home office's approval before we let it go through? So I'm thinking back to my own experience of through the period that you're talking about, how we took those outsourcing organizations or capabilities that we built, right? Because sometimes it was third party, sometimes, if you were large enough, you built your own center in a place like Bangalore, India, and you started doing things, and of course, you started with the more mundane things, and just taking the savings through labor. But then I know, when I was with Phillips at the time, I was one of the first, like, I gave them the first real innovation project, right? So it's, I want you to build a handheld solution for our service engineers that were in the field. We were in diagnostic imaging at the time, and everyone said, there's not enough creativity in that workforce over there to be able to quote, unquote, innovate. That's something we need to do in the West, in Western Europe, in the United States. And I would say, in working with them, we've been so impressed we think they can do it, and we want to give them a shot. And I think what I learned through that was we underestimated what they were capable of on two levels. Is the creativity was there was a lot closer to the creativity that we were used to in our traditional ways, but because they came from a different market, they thought differently about the problem the Value Engineering mentality of India, of how to make things low cost from the start and make Value Engineering trade offs was something that we never did in the Western markets. And so we would bring things to market at completely different cost points. That would in many ways be a better solution, right? It was a third solution that we could get a different part of the market to adopt. Do you think AI is going to give us some of those kind of aha moments? I didn't think it could do it, but man, it actually is giving us something we've never really had to consider before

Trent  14:02  
I think eventually we will get there. I think if I think about the difference between the incremental innovations versus the breakthrough innovations, the closest proxy that I can see is when you look at these AI generated photographs where they take two completely alien concepts and munge them together and it it is, in effect, to some degree, creativity, because I'm taking beyond decomposing something into its component parts and trying to make them go faster or more efficient, or something like that, what this is doing is what creative people do? They decompose stuff, they break apart business models. They reassemble business models into kind of new components, and then test those things very quickly to see if there's any there. So I think eventually it gets there. I think that there is a bit of a leap on inference beyond correlation and beyond just rote putting pieces together, that would drive that creativity. I don't think we're there yet. I don't think we are far. I would be surprised to know what that breakthrough looks like, because now that violates a correlation we were talking about of comparing an outsourcing transaction to a AI transaction in that now basically AI, as would like your offshore providers encroaching more and more into the sacred territory of what you thought was the retained organization, or the realm of the human in the case of AI.

Tom  15:32  
Yeah, no, I think it's fascinating. And I think going to, to your point, like past periods, there's going to be this high, disruptive period. And you know, we've been talking at our organization a lot about the highest levels of anxiety and fear that people have around AI, partially because they don't understand it, partially because they hear some of these stories about what it might do to their futures. But at the end of the day, everyone's going to need to learn how to use it, just like another tool. And so how do you get people onto the playing field, deal with some of the fear and anxiety that they have, and then get them into that mode of just start playing with it? I know that where I'm at with it, and I don't consider myself anywhere near expert, but I talk to people who are pushing it harder, and I'm increasingly amazed with every every thing I listen to, every conversation about you can really get it to bring a high quality result back to you if you do that or you use it that way. And so it's just like the boundary keeps moving. And I worry about the people who are behind right because the distribution between those who are really not learning or not in learning mode right now and those who are pushing the envelope on the front edge is getting farther and farther, and this is where we have real economic disruptions in our societies.

Trent 16:46  
I completely agree with with that. Tom I think that the thing that I think about is just even over the course of my career, I just remember those days when you'd get recruited by a firm, they take you through their boot camp, they teach you a bunch of stuff, and you had this foundation upon which to build right enter AI into that model that can do all those things that we would hire, at least in consulting analysts for and senior consultants for, and a lot of that craft that you did basically that would help you learn not what to think, but how to think, how to decompose problems, and all that kind of stuff that that potentially goes away, because, for all intents, I just need a really smart person to know what question to ask that AI and I can get, like a It's a scary reasonable approximation of what I would get from like a zero to three year analyst or young consultant. So I think, like in that model, I tend to because we see it now, there's a vast gap in kind of middle management that that tier of of middle management skill set, versus the seniors, and I think it's because, as a result of just the evolution we've seen, companies maybe have invested less in that foundational education. You're hoping to get a few middle managers that you can train up. But ultimately, when you start to think about the bottom of the pyramid, like people that are just coming into the workforce, it'll be really interesting to see, like, how you cover that divide, that gap between what they know foundationally and what I can give them in order to be productive, right? I think that's going to be that's going to be a real challenge.

Tom  18:26  
It's going to be a real challenge. And I what I see from my vantage point is universities are starting to talk more seriously about the preparation to get them to that chasm, and the work and the companies who are worried about their future and having the workforce that they need are starting to reach back and saying, that's the workforce that we need, but there's this chasm in between. We need solutions to bridge that chasm. What do they look like? And these are things like the National talent collaborative that's come together. Jamie Dimon from JP Morgan is a leading voice on that, and some of it is provocative and critical, but what he's trying to say is, our needs are changing dramatically with the introduction, and there needs to be new models. And so again, this is why, I think, sort of make it a very high, disruptive period as we go forward in the next few years. Let's talk about some of the entrepreneurs and startups that you work with, right? You've been with, worked with, some that have been wildly successful, others that fail. What are some of the lessons learned? You talked a little bit about that. The model at Cie is built around lessons learned about those first two years of what leads to a higher probability of success. What are some of those lessons?

Trent  19:32  
Yeah, a lot of the things that we tend to focus on is like, how do you de risk a transaction? And they're typically maybe, like three choke points where you see, like, early stage companies not do as well as they could. The first is just what's the problem you're solving and why solve it? Now we see a lot of people not necessarily sharpen their pencil as much as they need to, and as a result, their initial hypothesis is flawed. Thing number one. Thing number two is most often what we call getting to signal. And like our entrepreneurs, spend a lot of time over the years in terms of the tips and tricks of understanding how to detect customer signal that yes, not only are you solving a valuable problem, but the problem that you are solving has the potential to be commercialized, right? Because a lot of times, people are happy to keep using the freemium of the thing with no thought of ever converting right over to some kind of a paid user or providing kind of remuneration for that value created. I think number three that I think is really interesting. When you look at early stage startups, they're fighting this battle between trying to mature quickly assuming they have signal. They're fighting this battle between trying to mature quickly and punch above their weight class, but now going to market and getting the sales flywheel going. That's usually the thing, and you usually have to do that before you run out of money. So like the back of the envelope, those would be like the biggest three choke points that we see.

Tom  21:11  
You shared a term with me in our first meeting. You talked about, and I think you were talking about entrepreneurs and early stage companies. You talked about certainty versus conviction. Please tell us more about that.

Trent  21:21  
I think our conversation when something like I can sum up everything that I've learned about innovation between corporates and early stage in two words, certainty and conviction. And I tend to have a belief that those words define the motivation of the innovators that exist within those, each of those environments. And so when I've worked like earlier in my career, when I worked with large enterprise, a lot of the underlying motivation was all about certainty, right? It's all about like, how do I analyze the space and make sure that I'm like solving the right problem. And then there's a lot of ceremony that they have to go through internally to get access to that person's customer or access to this data and that type of thing. But it's all around this idea of not disrupting the business model, not messing with the golden goose, so to speak. And I think what that does is it has the tendency certainty does to create some innovation theater, because you're going through the rote activities of things that should create innovation, but you are constrained by the very nature of that ecosystem that that literally prevents you from taking too much of a risk, or, my favorite, is basically the things that you do in corporate finance, like creating a business case when you don't even know if you have signal or convict. You don't even know if there's engagement or a willingness to pay for that thing. But yet, I would like you to forecast the next five years of revenues and expenses. That's nuts, right? It doesn't exist. It's witchcraft and just world according to try. I'll speak for myself, not my firm, but like when I've seen that in the past, I've seen corporates go through very unnatural things to appease the model, so to speak, in in in the hopes of creating kind of innovation. And I think that's, that's where certainty, I think, defines one side of the box. Conviction, on the other hand, is the word I would use to define when I've met entrepreneurs on the early stage side. And so conviction is is both something that you see with the entrepreneur and the investor. And it is this idea that if you've been an investor, I'll start there. If you've been an investor, you put your cash in and you've seen it go to zero, you get religion very quickly that you never want to feel like that again, right? You never want to experience what that is and explaining that to your partner and all that kind of stuff. So as a result, you, as an investor, VCs, all of them get really comfortable with calling people's baby ugly, right? There's no that thing's going to fail because of that. And so what that creates is an environment where entrepreneurs, I suspect, much like actors and actresses, are basically told, No, not you. You're doing an audition. No, not you, for these reasons. And what it does, at least for the great entrepreneurs, is they basically learn how to de risk a transaction over time. But that what that requires is conviction, because you're entering a a market space that is chocked full of ambiguity. There's more that you don't know than what you do know, and as a result, how you navigate that is by having incremental conviction along the way. Oh, I got to prove the right hypothesis. Oh, I have to test it with customers. Oh, I have to prove engagement. Oh, I have to prove willingly. To pay. Oh, I have the framework of a baby bird startup, and I'm gonna give it some worms and help it to grow that type of stuff. And so what I think is, when you look at the DNA that exists on both sides, conviction versus certainty versus conviction, what you find is there's actually a lot of stuff that each of these sides can learn from each other, but it's that in their environments, I don't have the luxury of certainty if I'm an early stage guy, because I'll run out of money, and I don't have the luxury of just going with my gut on the corporate side because it might cost me my job and my reputation. So I think those are just the two things, and it's very easy to just sum them up in those two words, because you can tether a lot of behaviors to those two motivations.

Tom  25:49  
Yeah, I love the description, right? I love the succinctness of the words, and which is why I wanted you elaborate, and your way of describing it, I think is so clear for those of us who have lived in one or both of those worlds. I think the other thing in hearing you talk about it is in the answer to be successful is not to try to split the middle, because there's no success in that middle. Unless you tell me otherwise, you can't be half of both and make parties happy. That's the definition of appeasement, right? If you try to appease both sides and you have double, double the failure, you got to pick your lane then in terms of what what you're doing? 

Trent 26:24
Yeah, I think that is the case. I think the the biggest unlock, really Tom, is like the humility of folks knowing what's not their lane, right? And I think the most successful outcomes that I've seen on both sides of the pond are people acknowledging what they don't know, right? I don't know because I grew up in a pure risk off environment, right? I don't know how to take those risks and those things and what's a calculated risk, and how to de-risk ambiguity help me understand that. On the other side, I could say, Okay, I don't know everything that I need to know about making sure that I'm focused on the right hypothesis. I don't know how to fully understand voice of the customer. I don't fully understand go to market strategy and how to expand into new markets and stuff like that. So there are things, again, there are things that both sides do extremely well, but that Venn Diagram of splitting it down the middle, I think that's a very rare place to be if you have the visibility on both sides. I do think however it you don't need to, you don't need to have it. You just need to understand that, that there's a blank space there, and what you fill it with. 

Tom 27:35
If you're listening to this podcast and you have that itch to go do your own startup today. Let's just say a person younger than you and me who's ready to take that leap, what would you advise them to think about? How would I be thinking about building the next successful company? What was your advice to that kind of person? 

Trent 27:58
The advice changes by the year, and the reason why that is, is, Tom, when you and I were younger, and we both decided, hey, we're going to go out and create a startup, right? There were a lot of things that we would have to do, like organically, right? We would have to find the right product, we would have to build a website, we would have to go find a sales team, we would have to do all of these enabling capabilities that kind of live within the operating and business model of our startup right? Now, there's so many of those things that are turnkey, right? Like I can literally stand up a website in five or 10 minutes. I can literally go to Amazon and get access to a giant market, or Shopify get access to a giant market. Not only will they give me a giant market, they'll also give me the products to sell, right? And all it requires is insert operator here, right? So I think the difference now versus, say, when we would have been startup, aspiring startup folk, is because it is so easy to stand up a startup, right? The onus is on. What's like, where are you going to be focused? And I think that the test now, the test historically, has always been, hey, find a big problem to solve that a lot of people needs solved, and build a solution that's better than anybody else's and market the hell out of it and go build a startup. I think there's so much money and so much capability out there now that are chasing problem statements with solutions, it's crowded. It really is crowded. And don't get me wrong, we'll go through the boom bust cycles of Yeah, everybody's got a PowerPoint deck. Guess what? They get washed out and whoever is left wins to fight another day. But the advice that I would almost tell anyone that's looking now is, it's a crowded space, start with commercial commercialization and work backwards, right? So what's literally a thing? Think about whatever the idea is that. You have, who's going to pay for it? Why are they going to pay for it? What's the quickest way to stand it up and test it and do that quickly? Is thing number two. Thing number one is always a good old Google search, because a lot of people have a ton of ideas. It's best thing they're wrapped around thinking about this, how it'll be awesome. And the most surprising thing that you will find is somewhere, someone has thought about the thing, and they've probably embarked on the thing. And there's a lot that you can learn by just testing the idea, testing the hypothesis, right? It's like one of those three choke points we talked about, but that that would be, like, my advice, a bit more cynical than, like, 20 something year old me, but, but definitely, you get the battle scars and you know, we're gonna go poking around for opportunity, I suspect.

Tom  30:53  
But it's a different world. Right to to your point. When you and I were we're at that phase. We didn't have the internet, we didn't have Google, where would we have found that? There's already three other startups that have basically the same idea. Today, we have a myriad of sources that are in the palm of our hand where we could source that, whether it's going into a funding database, or whether it's just a straight Google search or now whether it's asking a large language model, and where you could also say, and with my concept, are there anything that really would differentiate me from this and get a first level answer? So whether you got something that actually would is that hypotheses would stand out in any way. It is fascinating. I think it's I think it's fascinating also to have been through the period and then listening to this, this generation's kind of young people who have that ambition and how they think differently. They think differently because they've grown up in a different world. And it's actually a lot of fun to sit down and listen to them talk about how that different world shapes the way they think. But I love drawing on your experience to where would you start? Because I think that's what they lack, right? They are more digitally native, and know these things, and are picking up things that you and I had to learn along the way, that they're just very native, native and natural to them, but they don't have the experience of some of the basics that someone there's got to be a customer, they have to be willing to pay, and they have to be willing to stay with you, and because they have myriad of opportunities to switch away from you. 

Trent  32:30  
So all of those things, yeah, the rare commodity that we see in our work is not ideas. It literally is not there. There's no lack of ideas. The hardest thing to come by is operators that know how to execute. Because if you're an operator that knows how to execute, you have a real appreciation for how hard it is. And before you even open your mouth to say the word startup, man, that thing had better be spectacular, because in exchange for that thing that you're going to pursue, it's a lot of sleepless nights, it's potentially arguments with your partner. It's, hey, do I get that really cool car this year or 10 years from now? So there's a lot of that stuff that I would almost say is a proper soul searching. Because one thing I would say is, like, when I was a younger person and I built a startup, and I didn't know what I didn't know, man, if somebody told me, like, oh yeah, dude, you realize you're responsible for other people's mortgages and other people's like, their happiness and their kids are going to eat because of what you're doing. Oh, I'm not sure I'm signing up. I think it's you know, again, all the points make sense in reverse, but who knows. 

Speaker 2  33:53  
But yeah, all right, so we're gonna leave it there. Trent I want to thank you so much for joining us in the podcast. I love what you're doing, but I also just love talking to you. You bring such a wealth of experience and bring it across in a very fun and understandable way. So thanks so much for joining us on the podcast. 

Speaker 3  34:08  
Really have appreciated your time, your intelligence and just having me on your show. Always here if you want to exchange some notes, and great to see you. Thank you.