Avi Eyal on Why Great Founders Still Matter Most in the Age of AI

Speaker A: Very difficult to replace human ingenuity. It's very easy to have a system come up with all the permutations. It's much harder for a system to decide which permutation is appropriate. And it's almost impossible for your AI to uh, have the human ingenuity of the invention.

Speaker B: Welcome to Technoventure. I'm Peter High, president of metastrategy. My guest today is Avi Eyal. Avi is the co founder and managing partner of Entrez Capital, a global venture capital firm that manages approximately $1.5 billion in assets and has backed more than 100 companies across enterprise software, fintech, cybersecurity, artificial intelligence, digital health and consumer technology. Since his founding in 2009, Entre has built an impressive track record of identifying category, defining companies early, including investments in Monday.com, stripe, Coupang, riskified and Deliveroo. Avi leads the firm's investment strategy, works closely with founders in the earliest stages through global expansion, and serves on the boards of several portfolio companies. Before launching Entre Capital, he was a technology entrepreneur, having co founded Cura Software, Insight Technologies and Zen Prop, giving him first hand experience building companies before advising and investing in dozens of others. His work has earned repeated recognition on the Forbes Midas list, including his uh, ranking of 43 in the 2026 list. In our conversation today, we'll explore what distinguishes exceptional founders, how artificial intelligence is reshaping both startups and enterprise technology, why effective boards can become a competitive advantage, and how uh, AVI sees the next generation of innovation unfolding from AI infrastructure to quantum computing and beyond. Avi, welcome to Technoventure. It's great to speak with you today.

Speaker A: Hi Peter, thanks for having me on.

Speaker B: It's a great pleasure. I've been looking forward to this conversation. Um, Avi, maybe we begin with Entrez Capital, uh, for those who may be less familiar with it. Can you talk a bit about the firm you co founded and how you describe its points of differentiation relative to others in the venture capital yield?

Speaker A: Yes. So, um, we were very fortunate to start Entrez Capital, uh, quite a few years ago, um, with a, uh, partner of mine who we've uh, been uh, best friends since we were almost six years old. So the partnership extends many more years than the firm itself. And we were lucky enough to be partners in one or two companies m that we started prior to Entrez Capital. So when we started Entrez Capital we were really um, best mates and best partners and continue to be so to this day. Um, and I have A lot to thank for that. Um, Entrez Capital we have a tagline that we say that we um, back the exceptional to build the impossible. And uh, we truly believe that we trying to play a game where we are focusing on moonshots, on opportunities that ordinarily wouldn't um, be the businesses that are one of many, that many VCs back. And that I think has set us up uh, for success over the past years and has given us our own edge and our own moat in an extremely competitive world where uh, frankly speaking the big funds are far better capitalized and funded to invest in companies. Uh, and we've managed to hold our own and we've done that because we've been a bit more generic in what we invest in investing uh, in people. Uh, we have a formula where we say we uh, call it the four T's where uh, the first thing is team followed by timing, followed by technology and TAM and kind of we've tried to really look for the outsiders, look for the ones that, that find um, it hard to raise sometimes but are uh, great CEOs, great teams around them and make it a success.

Speaker B: Great description. Thank you so much for that. Avi, talk a little bit about what led you to found it in 09. I mentioned in the introduction you were a multi time entrepreneur. Uh2009, this is right after and still probably in somewhat the uh, aftermath of the financial crisis. So um, a dire time, certainly the worst uh, economics, economic, um, times of your life, of mine as well. Um, what was the inspiration to do so then?

Speaker A: So um, around 2009, um, I had sold um, my last business. Um, and we found ourselves in a place where um, and it was a bit of a false start because you know the first two years were writing a few checks and figuring out what we wanted to do before we actually launched Entree officially uh, in 2011. Um, but we really saw that the market was underserved. You know when I think when Buffett says uh, when the tribe goes out, you see he's wearing bathing shorts. Um, and we, we saw that there was a need to, to invest in early stage at a time where everyone was fearful. And we were very lucky because we had in the middle of the gfc, the global financial crisis, we had exited our last business and we found ourselves in a place where we were uh, sitting with a fairly sizable balance sheet. Um and we could take bets on our own. Um, and so our first fund was primarily our own capital and we were backing ourselves and we approached it from a Perspective of wanting uh, to be entrepreneurs and seeing that if we were going to start a fund business, um, in the venture space, we wanted to use our own capital, we wanted to risk our own capital and prove to ourselves that we could build a business. And if we could build a business and if it could work, then we would open and take outside capital. And so for us, um, it was very important to get the basics right. And we were lucky enough to be surrounded by uh, a bunch of folks, uh, in the ecosystem who were also starting out their first funds, um, and were very receptive to working together and sharing the risk, but also sharing each other's advantages and um, uh, kind of the ICP of each uh, fund of what they could bring to the table. And so we found 2009 to about 2014 or 15, um, that a lot of deals were shared and that allowed us to build a name for ourselves and deploy our capital, um, in, in a more measured way, uh, across a number of businesses and, and back people we believed in.

Speaker B: Fascinating. Thank you so much for sharing that as well. And you're based in Tel Aviv and I wonder talk uh, about the advantages of being based there. Of course one of the advantages is that you have access to uh, nominal entrepreneurs that are emerging out of Israel. Uh, but that's not the, your, your scope is not limited just to um, the country of Israel. Talk about the advantages of having a perch there, but tentacles into the, the rest of the, the entrepreneurial world, so to say. I'd um, love to understand that.

Speaker A: So when we started Entre Capital, um, I wasn't in Israel and we based Entre Capital out of London and we found that given that we knew the US very well because we had started a number of businesses in the US Our uh, way to sell to founders, ah, in Europe and the UK and starting more so in Israel was to tell them we grew businesses in the US market, which is number one market. We understand the market, we have connections in the market and we can get you to that market. And you know, being founders and having access, we can bring something that you don't have. And that was a really good selling point for those companies. Um, but being entrepreneurial, we went to the States and in the States we went to companies and we said, look, we grew up outside the US we have offices in London, um, we all on, we understand how Europe works and you know, you're taking all this money from Sequoia and these other funds, um, but they don't really know how to do business in Europe. And Elsewhere and we do. So why don't you bring us in for a small portion of the round in your funding rounds and we'll help you bring uh, the rest of the world. And that sold well. So we had a really good go to market, so to speak. And that's how the fund got started. And after two years or so we realized that the real opportunities that were emerging, the real, real opportunities were primarily out of Israel, more so than they were out of Europe. And after having done a couple of deals in Israel, my, um, partner stayed in London. I went and came to Israel and started, started the business in Israel as well and still, um, ran the global business from. I'm from Israel and um, the message to the Israelis was my accent is not exactly Israeli, so I can help you get to other places. And we did, um, and I think that that method worked for us in the early days and managed to get us into incredible companies such as Rapid Monday.com, uh, Hibob, Riskified and many others. M. And I think we caught the wave at the right time. And so we were very lucky to end up with our first fund being uh, an incredibly successful fund returning over 33 times the money. Um, so we were off to a really good start that way. And as we grew, uh, the business, um, we ended up having our back office in Israel, a lot of the marketing based in Israel. Um, and so today about 80% of the firm sits in Israel, 20% is overseas. Um, but we cover and still do a lot of business in Europe, uh, the U.K. but in Australia, but of Africa, and a fair amount, almost a third in the U.S. ah.

Speaker B: As someone who has clearly been a global citizen, you, uh, spent a lot of your formative years in South Africa. Uh, you started companies in the US you're based in Israel where you were born. I, um, wonder, forgive me for asking you to paint with a broad brushstroke, but I wonder if you can offer some, some thoughts about the commonalities and differences across the various areas in which you, you invest, especially Israel and the US but also the extent to which you might, might typify, uh, some of the British, uh, or continental Europe, European companies. Uh, are there any meaningful differences that you would call out or are there more similarities than differences as you think about the kinds of teams that you invest in and the, the, the ideas they develop, the ambitions they have and so on?

Speaker A: Yes. So I think that this is something that is, uh, needs to be plotted in on a time series because a lot has changed over the last decade and A half. Um, when we started Investing in Israel 15 years ago, the teams were primarily technologists. Uh, some folks had sold their business uh, to US companies generally US companies had worked in US companies and had come back to Israel with managerial skills, better managerial skills. And slowly over the last 15 years Israel became from what everyone thinks of as a startup nation to a scale up nation, um, where there are dozens of unicorn companies that have come out of Israel today. And there's no issue with building big outcomes in Israel. Whether you take wiz has an exit at 32 billion amis at 6 billion um, Monday, which you know uh, has had a bit of a tough time with, with the markets now but, but you know once we IPO'd we got to evaluation of 16 billion and so the real outcomes that, that have come out of Israel and continue to come out of Israel and Israelis are real go getters and extremely uh, bright. Um, they are technologists with a business mind more so and a managerial mind. Um, funnily enough in Europe what we saw is that only in the last five years or so have the Europeans started becoming more aggressive in terms of building big outcomes. But Revolut and a couple of companies like that, aside from um, but they've been the exception rather than um, not the norm but m more regularly occurring. But what's happened in Europe is that folks weren't as deeply embedded in technology. They were less technologists. And so I think that the view in Europe between 2010 and 2020 was very much to copy other models that existed elsewhere, um, and use their knowledge of their markets even though their markets were so fragmented to be able to try and build something there. What we've seen in the last couple of years is that European teams are increasingly more technology savvy. Um today you see far more uh, deep tech teams coming out of Europe. Um, and we think that they kind of, that the European teams are progressing up the chain. And having said that you can still build incredible businesses out of Europe. Um, historically there haven't been the deep uh technology businesses. Um, and in the US we kind of find that it's ah, a, uh pretty much a constant stream of a mature environment which hasn't specifically changed a lot in terms of the type of entrepreneur over the last 15 years. Um, speed goes through phases of uh, momentum um but we find that each one has its different culture and approach to doing things. And yet we find a convergence uh, that I think that in the next five or ten years probably you will not worry uh, about the cultural difference or the history of the ecosystem, whether it's Europe, Israel, uh, or North America, I think they'll be pretty much, uh, aligned or. I certainly hope so.

Speaker B: Thank you for those insights. Super interesting. I want to return to something you mentioned earlier about being a generic investor. As you, as you pointed out, not having a specific lane that you cover, for example, but rather focusing on the four T's you noted. You noted team, timing, technology and total addressable market. Um, let's talk about team. I assume that that order is also meaningful. And you mentioned it's the people that you are investing in, thus the team, the first app. Talk a bit about the sorts of things that you're looking for in a team, in a founding team. And I'd also be interested the extent to which that's changed between 09 and now. You talked a little bit about some of the changes, just even in the environments that you are investing in, a bit more of a convergence associated with that. So I'd be curious what changes you're seeing or what you're finding more attractive as you think about a team to invest in, uh, now versus your earlier days as an investor.

Speaker A: Yeah. So, um, I think my thinking of the characteristics of a person or a set of people, um, that make a good team, uh, have probably matured over the years. Um, but having said so, it hasn't changed. The fundamentals haven't changed at all. You're uh, still looking for a team that has a good balance between business and technology. Um, typically teams of two or three are ideal. Um, and founding teams, that is, and the characteristics of the founding team rather than the person, uh, is really someone who comes. Folks who come from a background where they deeply understand the market that they're tackling. Uh, if we look at someone like TJ Parker at PIC, for example, uh, from the age of 12 or 14, he was riding a bicycle, deliver, delivering prescription prescriptions, uh, from his father's, uh, uh, drugstore, um, in Rhode Island. And that deep knowledge and understanding that he got over so many years, um, in that field allowed them to build, to see the opportunity and build a business like Pullpack. Um, so I think that kind of understanding, deep understanding of what you're trying to build, the market that you're going after, those are so critical. Um, a couple other things. We look for folks who are bright, um, you think out the box, um, but are grounded in terms of, um, being able to translate their vision and their roadmap into what is actually achievable and when, uh, so folks who are pedantic um, and when I say folks, again it's the team. So you can have the evangelist, the visionary, but they have to be matched with someone who's got the eye on the numbers and is pedantic. You, um, and then kind of for us the nature of a person. Are there a good person, uh, fundamentally, do they have like a good heart? Um, are ah, they going to stick with you like you stick with them? Uh, I think oftentimes people take uh, an investor's money at that point in time because they need it, but they lack a certain loyalty that comes three or four or five years down the line when um, the new money comes in. Um, and so someone who's honest and trustworthy. These are just kind of fundamental things that are extremely important for us.

Speaker B: Evaluating if somebody is a good person, I, uh, mean makes a lot of sense. Um, but it also suggests a necessity to really get to know them. Right. A, an introductory meeting, uh, is like a first date. We show our best selves. Um, and so that point in particular, I'd be interested in the tactics you use to try to establish that.

Speaker A: So I think a fair amount of it comes from uh, doing detailed references on the person. So we spend a lot of time doing detailed references. Um, part of it is just kind of, you know, you have a smell, uh, folks get a, you know, you smell when something is right or wrong. So I think that seeing a person, mannerism, reactions, um, you know, um, ah, simple things, you know, simple things that make a big difference. Um, you know, I'll give you an example. It may sound ridiculous but know, um, and this depends on which place you, you, you're investing it in, you know, which country. But in Israel when founders come to see us, you know, we offer them drinks, water, uh, coffee, etc, you come sit down, you get your coffee, you have the meeting. And like one of the things that you notice is the ones who at the end of the meeting pick up their cup and either throw it in the bin or take it back to the kitchen versus the ones who just leave it on the table and walk out. You know, it's like small nuances like that, one could argue. Um, we also have a unique, we think a unique approach. Certainly, certainly. Um, outside the US where we have a lady on the team, she's a partner who handles uh, organizational development and uh, she's a Partner, got a PhD in psychology. She led Org Dev and HR for a 5000 person tech company. Um, and she's helped dozens of other companies and she's part of the team and she will meet the founders separately and together. Um, and what we'll do is we'll put together, um, a makeup of the founders individually and of the team. And that will give us a really good insight whether we want to do the deal. Because from the meetings with her, we can pretty much tell if this team is going to survive or not. I mean, with fairly good certainty. And so that's important. But more than that, we figure out who the people are that are needed around them. So who are the VPs, the EVPs, the COOs, you know, the next level down in management that they'll need in order to succeed. And then we'll help them recruit that first set of management, um, and the first employees. Because that's so critical, especially when you raising a limited amount of money and you're driving as fast as possible. Can you imagine in a seed round that you raise the seed funding and you bring in a salesperson ahead of sales is the wrong person. So you lose three to six months in finding them, you lose three to six months in getting them up to speed and then you find out they can't sell and then you've got six to 12 months of money left that you gotta ask them to leave, find another person and get your sales back up. So they're critical hires. And so we find that having Maya on our team, uh, has been a fundamental differentiate and help for us to help identify and determine that makeup of the founders.

Speaker B: Yeah, very interesting. I appreciate you sharing that. Um, I want to get into uh, your thoughts on artificial intelligence. You've noted that it isn't simply another investment category. Um, I'm paraphrasing you here, but you said it's changing how companies are built, how quickly they scale, and even how venture firms evaluate opportunities. Talk a little bit about this age we're in now and um, how it differs, perhaps, uh, um, underscoring some of what I've just mentioned or other, other sort of top line insights before we get into more specifics.

Speaker A: Yeah, so I think it's not unique to say that it's a fundamental generational change in how everything works today, uh, and how things will work in the future. And I think that we are really taking the first baby steps, uh, in this, you know, with you can point to the hundreds of billions that have been invested and really we're still at the start, um, most systems and Companies are not AI enabled today. Most workforces are not AI enabled today. When I say most, like over 90%, uh, the biggest impact that AI has had today is maybe on software development and coding where it's had a meaningful change. But in every other category, every other job function, it's really only touching the surface, scratching the surface. Sorry. And there's so much more to come. Um, and it won't look anything like what it looks today.

Speaker B: You talked about some of the areas that it's impacting. Software development, coding. M I wonder, as you think about the industries that are being most impacted, um, how do you think about that, as you think about investing in startups that will take on incumbents. Are there certain industries for example, that are particularly focal from your perspective? Or again, are you more generic as you think about that?

Speaker A: Yeah. So I think that um, clearly the software industry itself and the technology industry itself is the first to fall, um, is the first to get the benefits of AI and AI deployment because it's the early adopters. Um, the real interesting area will be where it goes beyond that. Um, and so one can look at it from a perspective of the legal profession or the accounting profession, um, you know, uh, dentistry, things like that. But one can also look at it, you know, more horizontally. Healthcare, um, you know, manufacturing, etc. I think there's no doubt that every industry is going to be transformed by it. Some will happen quicker than others. Um, and I think that lighter industries will be easier to transform. I think heavier industries, things like manufacturing, et cetera, will take a bit longer because the cost of a mistake is so much greater. Um, and so we finding that we're making interesting investments in the vertical AI space in places like uh, legal, um, finance, You know, um, uh, a whole bunch of, you know, healthcare, um, but in healthcare support, not in actually, you know, first line. M so we're not at the point yet where we feel the market is ready to do automated monitoring of your ICU using AI. You know, I think that kind of, you probably want to be a bit careful there. Right. Um, but things like drug discovery and things like that, there's a path that increases the permutations of what can be tested and found and you can get to the point of getting into medical trials much quicker. But we don't think that you should, um, now, you know, rely completely on AI for medical trials. Um, we think that's kind of a step where, you know, one still has to be responsible. Um, so there are the areas that will be transformed first in AI will be the low hanging fruits where the cost of an error is not so big. Um, and the rest will slowly and surely, uh, start happening. I mean we have a company now which is a native ERP system, native AI ERP system called Light, um, and they replacing uh, companies like Oracle, netsuite, things like that, uh, for the first time where it's phenomenal, you can build a much lighter system which achieves uh, pretty much the same. And by automating some of the functions using agents and uh, and automations behind those agents, but in a very specific way where you are on top of the workflow, where your range of outcomes cannot be uh, infinite, um, it can work and that's where it's making a big change.

Speaker B: You reference agents, Avi, um, how do you see workforces themselves even among the companies that you are investing in, changing as a result of uh, agentic workforces that are taking the place at least of some of the people that in years past would have been new hires. So thus the makeup of the human element of the team versus the AI version of the portion of the team. Talk a bit about that evolution if you would.

Speaker A: So again I think that we haven't seen much in the change of non tech workforces in the tech world. What we're seeing is that some of the entry level functions um, have changed. So software development, entry level software developers um, I suppose are being more repurposed to become forward deployed engineers um, because of the coding changes and that a senior developer can run any number of agents and any number of processes uh, in parallel and get answers in seconds versus uh, days and weeks from software developers and testing and things like that. So I think there's a fundamental change in the makeup of the workforce in high tech. Um, for example when you look at the sales organization in high tech that's also changing. So um, there's far more automation of SDR functions for example. Um, so and those folks who used to be SDRs either uh, need to find something else to do or get repurposed into the next level of salesperson or customer success or things like that. Same uh, thing's happening with um, the service and support desk where more and more questions get answered automatically uh, using AI, um, because the answers are there. It's just someone has to know to search for something and now it's available quite easily. So we see a fundamental change in the workforce. We also see that AI is enabling smaller workforces. So um, the rate at which the teams grow. In a small startup, um, you would have started a small startup with 7, 10 people and today you can start it with 3 people um, and get to much better outcomes. So fundamentally I think that's changing. But on the other hand it's not necessarily that workforce is going away. I think that workforce is getting repurposed. So either more people are starting companies or more people are shifting into other functions in other industries. So um, I don't believe in this theory that uh, some try to hype up that there will be huge reduction in workforces um, and it'll be huge job losses and you know, et cetera. Um, I think folks will get re educated and it'll figure out itself uh, as we go along.

Speaker B: Avi, how do you see uh, compute evolving over the coming years and where do you topics like quantum computing or new hardware architectures fit into that picture?

Speaker A: So um, a lot of the compute today is focused around AI GPUs, data centers and a lot of that is premised on the, the so called inevitable growth of infrastructure for the frontier models. Uh, the big. And I'm quite a, I'm an engineer by training so maybe I'm trying to apply uh, some engineering principles to it. I uh, studied computer engineering and electronic engineering. But I'm also trying to look at it from a perspective of the previous hype cycles that we were in and when everyone was uh, thought it was uh, you know, doomsday, uh, and you know, um, there'll be no electricity and you know we're drinking all the water, we're going to use all the water, um, et cetera. And I'm very much uh, opposed to that. I think that what will inevitably happen is that most of the AI compute will move to the edge, it'll move closer to the user and most certainly a big portion of it will end up on their phone, uh, or their device. Um, and as that rises over the next few years. It's already starting. But as it rises over the next few years, um, folks will run their own set of racks with very specific models that are far more efficient and optimized. The edge will run a bunch of models, the phones will run a bunch of models which will make them far more optimized and the frontier models will probably end up in a place where they are the uh, Encyclopedia Britannica if you will, the old world book that you ran to find information that wasn't easily accessible around you. Um, and I think that that's what will eventually happen. And if that happens, then suddenly the amount of compute that you need at data centers won't rise in an exponential format. Um, um, the amount of electricity that you'll need won't rise in the same format because as chips come out and as technologies, new technologies come out, they optimize the use of electricity and band. So what happens is that today you have GPU racks that switch um, on copper, uh, you know, and um, they'll use um, they'll use um, something like 30 to 50 uh, megajoules um of energy per per K or something or you know, to switch. And what will happen is that that will come down as you move to optical switches end to end optical. So from the chip you'll have optical out of the chip to the rack to the switch to the, to the, to the next uh, rack, et cetera, et cetera. That will all move into optical uh, and fiber. And as that moves to that you'll get a 10 times gain in uh, efficiency in terms of electricity. And if you get that 10 times gain in efficiency then well we actually have a fair amount of electricity sitting around today. So uh, you know, my sense is that these things um, right. Size themselves as you go along because human ingenuity and research match. The other thing I would say is that uh, we've been big proponents of quantum computing for the past eight years and we feel that quantum computing um, becomes readily available uh in the next three years. And so by 2028, 2029, there's going to be billions being spent on quantum uh, computing racks and quantum computing uh systems. We also think that, and we firm believe that the challenges with error correction and quantum compute, the um, uh challenges um, with getting um to operate at room temperature and things like that will get solved and are being solved and as far as we can see. And so your quantum computer will change from being something which is the size of a large room with big air conditioning and you know, cooling systems, it'll end up being a chip. And that chip could even end up on your phone. So uh, and in fact we have a company called Quantum uh Transistors which is actually has already um, baked their um, first uh quantum cpu. And so um, we believe the market's moving there. And what will happen is that quantum computers will capture 20 to 30% over the next decade of AI compute where AI compute that's far more uh efficient and serves the purpose of uh, uh quantum computers can solve the problem much quicker and effectively for that subset of total compute that'll move to quantum. And so we firm believers in companies doing that. Um, and we've invested in eight or nine quantum computing companies uh to achieve that. So we think that the world is changing and as always, and we right at the beginning of this, of this change

Speaker B: avi what analogies of the past few years with the um, AI revolution, latest iteration of the AI revolution This era that we're in are instructive for technology executives as they contemplate what's to come for Quantum. I mean on the one hand I'm speaking very broadly here, but uh, in many ways it's the progress associated with AI that now have people thinking about Quantum, which was viewed by many to be decades out, as being pulled, pulled forward. As you're pontificating two, three years away from, from, from real value, uh, in the mainstream. Um, it presents unbelievable opportunity which you've just underscored some of the aspects of that. It also has associated risks that are considerable, just as AI does in both of those categories as well. So I wonder, are there lessons we ought to be drawing from? Um, the experiences of the fast pace of change in artificial intelligence, progress made, um, uh, issues averted or issues encountered to what's to come with regard to Quantum.

Speaker A: So I think it's very important to think of Quantum as to kind of abstract your business needs and what you're trying to achieve from the actual idea of I need to have a quantum computer or an AI cloud system or something like that. I think you as a business one has needs and one needs solutions for those needs. And you know today when you consume your resources for compute, you don't say to yourself, well this is coming from my on premise server or my uh, you know, um, down the road internal server farm or if it's coming from aws, it's kind of in the background. What's important to you is, is the business need. So when one relates to, when one relates to quantum computing, um, as a, as a, as a business executive making a decision, you'll say I have to do um, recalculation of all my um, uh, financial positions. Um, I have to do it three times a day instead of once a week and it cost me a million dollars to do it once a week before. If you're a big uh, finance organization and I want to do it three times a day and my budget is a million, how am I going to do it? And you find the right tools to hopefully get that done for you, that's where Quantum will become a huge need. Um, now specifically with Quantum, there's a push and a pull. So the thing that will pull Quantum, more recognition and understanding of quantum systems and things like that in an organization is something called um, uh, pqc, which is post Quantum, uh, cryptography and that's with us today. Today, uh, the European Union are, uh, putting together an act which, uh, requires every company to adopt pqc post Quantum, uh, cryptographic, uh, solutions. Uh, nist. The US has done that already. And, um, we saw in the last, uh, week that there was actually an executive order which uh, also accelerates that even further. Um, so on the one hand, the one thing that you, that every organization has always been the most concerned about is encryption, is making sure that they have RSA encryption, that the passwords are encrypted, that the access to information is encrypted is kind of the most important thing. Um, and yet very small budget goes to it. All right, Relative to the whole IT budget. That is the pull by organizations that will bring quantum and quantum awareness more and more into, uh, into this world. And companies like Kryptonite and other companies doing PQC will be beneficiaries of that. And that's on the one hand, that's the kind of, the immediate thing that's really starting to happen today and that you don't necessarily need a quantum computer in the background to be able to start adopting these technologies. But again, you don't care if it's a d, uh wave computer or an IMQ computer or a quantum art computer or uh, quantum transistor computer or continuum computer. Those are. Besides the fact you don't ask what is Amazon running AWS on it just, you know it exists and you know you have access to it. Same here. So the preparation and the adoption of these technologies and simulating how these technologies work is already happening, um, and is already happening with the largest Fortune 500 companies around the world. The next step is as the computers, as the quantum computers come on stream with the first generation and the second generation and so on and so forth over the next couple of years, uh, the adoption and putting it into production will become significant.

Speaker B: Very interesting. Avi, um, as somebody who also has consequential investments in cybersecurity and in fact, um, operates in a country where there are legendary companies in this space. You already mentioned a couple of them in Wiz and Armis and others that have emerged out of Israel. Um, I wonder, how do you think about the challenges associated with AI or Quantum, among others, um, the ability for entrepreneurs to tackle the issues to come. It's the unfortunate consequence that the bad actors have access to the same tools, many of them well funded, many of them very, very bright. Um, how do you think about the tension, the push, pull, uh, pull of progress made by, by the bad actors and the progress made by entrepreneurs to counter them.

Speaker A: So you know, if you look back 10 or 15 years ago, there were fewer bad actors and so there were also fewer technologists with the skills to be able to combat the bad actors. Um, and I would say that just like the bad actors have multiplied, so have the technologists. Um, you know, in Israel there's ah, a specific unit in the military called 8200 which produces, I won't say the number, but a significant number of uh, cyber technologists every year. And every year there's conscription and every year that number increases and as those folks leave, the market has more of them. So certainly, uh, in the cyber world, um, Israel is producing them uh, at the same or greater quantities every year. Um, and those folks become more tech savvy quicker, uh, because there's far more of a base that's been established from which to work from now. You have mythos, you have these other tools that are coming out and if we have it, they have it know pretty much. Um, and it's challenging but you know, if, if someone wrote a mythos, someone wrote an anti mythos. Um, and so one would hope that um, as these things happen there'll be more zero day attacks, there'll be more, uh, the frequency of attempts will, you know, to attack infrastructure and things like that will grow substantially. And so the challenge of um, countries around the world is to really build up this sovereign skill in being able to defend against that and defend their critical infrastructure against it. And so um, I think it comes back to the same thing of deploying the right people in the right places to ensure that everything gets covered.

Speaker B: I wonder, um, Avi, how has your work changed given uh, some of the innovations that you've described? How are you leveraging some of the very tools you're investing in or others beyond the, your, your portfolio, uh, to, to, to get more out of your day. I'd be, be curious about how your, your, your workflow, your, your daily habits have changed as a result of incorporating some of the innovations we've talked about and perhaps others we've not yet.

Speaker A: Yeah, so um, I have a, a personal assistant tool that I use called Catch. Uh, so it's a, ah, Israel. Um, and it kind of like handles meetings for me, setting up meetings, arranging uh, parking for people coming to see me or you know, just the noise, um, and the little things that happen which just kind of irritate and do the usual thing, order my lunch, you know, book, uh, my usual hotel when I'm going overseas, you know, the things I care sometimes just even if it's uh, uh, interacting with my travel agent. Um, so, so that's a kind of on one level and, and I think that everyone has to um, find what they comfortable with, um, in, in being able to share and, and, and the uh, the error rate one is willing to um, bear and tolerate uh, when you do this. Right. So that's on the one hand, um, from a work perspective. We've been using AI for a number of years now in order to make it much simpler to automatically connect me with certain people on LinkedIn, uh, because it makes sense, because something happens in the ecosystem, um, reach out to founders when they leaving, just before they expected to leave a company that they've sold to, you know, once the vesting happens and things like that, just like the ordinary little things that are, one would have done manually. Um, there are a lot of these agents and tools and things like that that we've built internally, um, using CLAUDE or other systems, um, to solve for us. So you know, so those kind of things we've, we're comfortable with, with releasing, um, we use uh, AI a lot more for market research. Very um, good in consolidating information across uh, terabytes of data that we have on the history of companies over the last 15 years who've come to us, to the CRM system that we use, uh, to look at interactions with people, to understanding competitive landscapes and you know, things like that. So from that perspective it, it kind of does a lot of preparation work which I would have spent hours doing before. Um, so those areas are very useful for us, um, creating market maps, things like that for us. Um, uh, it doesn't mean that you take it entirely off the table and you don't have to do it anymore, but it just means that you've reduced uh, your work by anywhere from 60 to 80%, uh, that you did because the information is ready for you. Um, so I think it's an enabler, uh, for us, um, we're very far away from saying, uh, an AI that can make the decision for us, uh, in what we do. Um, and AI is very far away from dealing with the most important question, which is our four T's, which is the team. Um, you know, as I said to you earlier, you've got to smell, you've got to be able to feel it and smell it to, to know that uh, you're hopefully onto the right thing. Yeah.

Speaker B: The fact that you've invested, uh, and have a partner who's a PhD in psychology and have thought so much through the four T's, I could see that you're foreseeing some of the limitations that are likely to be there for some time to come. What other limitations have you found, Avi? Uh, do you think it will be difficult for AI to compete with a human on, as you think about at least the medium term?

Speaker A: Sure. Um, I think more and more it'll capture more of the functions and points of interaction that you have, um, with other folks. But by the same token you're going to be outsourcing your points of interaction to an agent as well. And so we really feel that the idea of agents conversing with each other in a trusted mechanism is something which has yet to be solved, uh, and will take a long time to solve. But inevitably a lot of the noise, a lot of the stuff you hate dealing with, um, will be automatic. And if you can solve those, um, the, the real touch points that you'll have will be touch points, um, that you have to prove who you are in certain circumstances. You know, um, you'll have to be able to, um, have personal interactions because you're not going to have an AI agent who's a partner who makes an investment and then deals with the founder, because the founder will have an agent that deals with the partner. And so the next thing you'll know, you'll have agents running, uh, companies, um, which will happen, but kind of it defeats, uh, the purpose, um, defeats the object. And I think you'll get it more wrong than right. Um, so I don't know what the balance will be, um, but very difficult to replace human ingenuity. Um, it's very easy to have a system come up with all the permutations. It's much harder for a system to decide which permutation is appropriate and at a point in time or given other circumstances, um, and it's almost impossible for your AI to uh, have the human ingenuity of the invention, uh, itself, um, and I think that that still remains in the human realm.

Speaker B: In closing, Avi, I wanted to see if there's anything you would recommend to others to stay current on some of the topics we've talked about. You have the great advantage, of course, to speaking on a regular basis with people who are shaping the technology landscape just as you are playing your part in shaping that landscape as well as. So I know the uh, the touch points you have with many smart people is uh, irreplaceable. But as you think about the voices that, the books you read, the podcasts you listen to the blogs that you, you cover, what comes to mind that you would recommend to others, uh, to at least have an approximation of your, your level of ability to see around corners.

Speaker A: So um, history repeats itself always and human nature repeats itself always, uh, which is maybe the cause of a lot of history. But and so what I do is I spend time reading history books um, to try and form an understanding of people's motivations and how things have happened in the past and therefore understanding the signals of these things reoccurring in the future. And that's on the one hand. And then on the other hand, um, I have a ah, fairly um, organized uh, x, uh feed of things and lists and things that I follow, um, where I've identified the people who uh, I respect and I may disagree with but uh, I uh, completely respect but kind of their points of view and seeing what they publish and what they put up. And some of it could be uh, certain articles from nature which you know, you can identify. But other things can be uh, Alex Karp from Palantir talking on cnbc, um, or things like that. And those kind of keep you up to date and give you a lot of other viewpoints in a very easily uh, consumable mechanism. Um, so that complements the other side which is the history. And then kind of in the middle is uh, journals, uh, patents, things when I'm looking at something in more depth and trying to research and better understand it. So I may refer to um, uh, you know, books, uh, uh, or research papers or things like that where there's something very deep and within that I'll use AI to help me find information or to ask questions instead of reading 100 pages. Um, so it gives me a ah, great way to interact. So between the three things. Uh, I think you can't follow everything and you can't be doing everything. But if you can find two or three things that you can stick to and it works for you, um, hopefully you don't have information overload and you can, you can uh, tell the woods from the trees. Right?

Speaker B: Well, I greatly appreciate the time you've taken with me uh, today. Thank you so much for sharing a bit about the things that excite you areas you're investing in some of your own theses as you think, uh, about the near and medium term at a minimum. Uh, it's been fantastic to get to know you better and uh, to gain from your wisdom. So thank you for your time today

Speaker A: and thank you for yours. I really appreciate uh, you inviting me to the show.

Speaker B: Thanks for listening to Technoventure. If you enjoyed this conversation, subscribe wherever you get your podcasts and leave a rating. Thank you and I look forward to seeing you next time.