Does God Play Dice with Your Business? Understanding AI, Risk, and Reality with Pavan Agarwal

 

[David] Listeners, we’re in for a different AI update podcast. We’re going to be talking with Pavan today and this is an interesting title. Does God play dice with my business? This was when Pavan sent me this slide deck, it got my attention. So I want you guys to sit back, listen to hear what Pavan has to say. Pavan, good to have you back with another AI update, brother.

[Pavan] Thank you, as you probably know, David, this is a famous quote from Albert Einstein. The actual quote is, God play dice with the universe? or rather, the actual quote is, God does not play dice with the universe. But as you know in business, and you you’ve gone through your ups and downs. It sure seems like that sometimes, right? Like you got everything planned and then something hits you out of left field and like poof, it’s gone. it’s God’s ineffable plan. no matter how much you plan, it seems like nothing is predictable.

[David] Right. And you gave this presentation. I want to give a shout out to Sandra. You talk about where you gave this presentation and just brief moments. So the listeners have an idea because we’re going to have her as a guest.

[Pavan] Yeah, yeah, so my friend and neighbor ⁓ Shanda, she’s a major business coach, huge following social media, hundreds of thousands of maybe millions of people follow her and she was having a high-end networking or a coaching event. I should say she was having a high-end coaching event. She invited me to give a little presentation on AI. So I whipped up this deck that morning and I gave it to her group and they loved it because it just sort of. It’s the question that’s on everyone’s mind is why does life feel so unpredictable and how do I deal with it as a business owner? and what mindset? So the question that we’re going to answer today is what mindset do I need to have to manage risk, to manage the unpredictability? And second is what mindset do I need to have in an AI world and things are changing so rapidly. Right. And finally, the answer is relax is just math. It’s not magic.

[David] Can’t wait to get into it. Let’s get going through this slide. That’s what I mean. I, I, I saw, went through this and I’m going, this is so good. Especially when you look at how your brain works as an engineer and a programmer.

[Pavan] Yeah, so let’s get moving. So anyone’s played 21. And by the way, we’re gonna be in Vegas in a week or so at the mindset conference and we’re gonna play a lot of 21. I’m just kidding, I don’t really do this stuff. But anyone’s played 21, this is the odds of guessing a stack, a single deck. If you play a single deck 21, this is the odds of when you shuffle that deck the odds of guessing the deck right and so when you shuffle a deck of cards and you’re betting against the house, these are your odds. But guess what? at the bottom of this slide here, you see this link. There was a movie called 21 where it’s about a couple of MIT kids who beat the casinos and broke the bank and then they got banned from gambling. There’s a paper here that’s actually written on how to break blackjack. I’m giving it away.

[David] But with these kind of, I can’t wait to have you explain how they did that.

[Pavan] Yeah, so that’s this paper and then by the way since then the casinos have modified the rules so a lot of what’s in this paper probably won’t work anymore and you know that’s their job. Their job is to win. So but in a fair blackjack game is actually you can beat it. You know, not every hand but consistently you can beat it over time, and anybody who wants to learn how to actually break Blackjack, there’s the link to the papers right here. Okay, and now why I bring this up is because this math, the math behind breaking the bank on Blackjack, okay, is exactly the same math underlying AI and that’s what’s so interesting and exciting. And I’m going to take you through a little bit of history lesson. And I’m going go back to how old, how ancient this mathematics is and this field of study is, so we’re going to go back to the time machine and let’s look at the history. So it actually started in 1906 in Russia. The Russians, they’re so smart. Okay, so there’s Russian mathematicians, two Russian mathematicians had a debate over God, Markov versus Nekrasov. Okay, and basically the idea is can math be used, can statistical modeling be used to explain free will and God. And as we know, God’s plans are ineffable and you can’t ever predict what’s going to happen next. You don’t know what God’s will and God’s plan is and that was the underlying debate here. One was saying that one said because probabilities are unpredictable. Like when you toss a coin, you don’t know what’s going to happen next. Okay. And that’s evidence of free will. And the other guy is saying, no, well, that may be true, but things that are dependent on each other, let’s say, you know, like when you, when you pull out a card from a deck of cards, right? If you just got dealt an ace, then you know, the probability of getting the next ace  is less likely, right? Cause there’s only four aces in the deck. And the other guy is saying, well, even when there’s a deck of cards and when there’s interdependencies like that, you could still guess what’s going to happen. OK, and if you could still guess what’s going to happen, then God’s plans are no longer ineffable and therefore the math proves that God doesn’t exist or at least in one dimension here. So that’s what the debate was. One was an atheist and one was a believer.

[David] Okay. And that was in 1906. Okay.

[Pavan] That was 1906. So this was really an academic debate. No one’s trying to build AI. This was a purely academic debate, mathematics debate. Two mathematicians, one an atheist, one a believer, debating over this. So this, I kind of already explained this. So there’s something called independent events, which is a coin toss. And there’s a lot of large numbers that if you toss a coin a lot of times, then it’s going to pretty much, it’s predictable that it’s going to be pretty much. 50-50, right? 50 % heads and 50 % tails, right? You toss it 100 times, you’re going to see about 51 is heads and 49 is tails and so on. It’s just the way it works. Okay, but if you deal a deck of cards, and those are dependent probabilities, right? Based on what you get dealt next depends on what you were dealt previously, right? and dependent probabilities do not follow the law of large numbers. OK. And so Markov said, no, can prove I can prove that dependent probabilities, dependent events do follow the law of large numbers. They are predictable as well. That was Markov’s hypothesis. That means that means you can predict what the next card is going to be. That’s the hence the reference to the 21, you know, playing 21. OK, so that’s this is really cool. So like this guy more than 100 years ago, 120, literally 120 years ago, figured out that that you can you can beat Blackjack in essence. He wasn’t trying to beat Blackjack, but that’s what he figured out. OK, so, Markov disproved it and he wrote, he published a paper back in 1906 and the proof, you know, obviously, you know, stood the test of time has been.  has been, you know, the mathematics hose and has been tested experimentally over and over again. And basically what you’re seeing here on this slide is called a Markov chain.

[David] So you’re saying Markov did not disprove free will, God’s will, he disproved that its existence could be proven through statistical modeling. Interesting.

[Pavan] Right. So he basically he disproved Neskrov’s claim that because of law of laws numbers, God’s will exists, you know and so he disproved that just one specific argument that was used to prove God, he disproved that one argument, which was it was it was a dumb argument on the basis of which to prove God anyways. But anyway, that was their their silly side debate that they were having. Not so silly. I mean, it changed the world. It literally this thing that you’re seeing right here in front of you, this this Markov chain diagram, this literally changed the world in dramatic ways. you can’t.

[David] And you’re going to explain how that happened, and how that is.

[Pavan] Yes, I’m going to explain how that is.

[David] But before we go on the statement you have all Wall Street traders know that every new trade must be memoryless. What do you mean by that?

[Pavan] Right. Anyone who’s trading, anyone who trades shares or bonds,  you know that that it doesn’t matter if you bought a stock at 50. Right. And today and now the value fell to forty six. Right. You don’t worry about the four dollars that that you lost, if you keep living in the past thinking about, I bought it at 50 and also at 46. I can’t take this trade. I’m going to lose money. Right. And then next thing you know, it falls to 40 or 30 and you lose even more money. Right. You’re supposed to trade on that moment. Forget about what what you bought something at and look based on the information you have, you make the trade. Right. A very Wall Street traders are very, very disciplined and they stuck.

[David] And that’s what you mean by memoryless. In other words, they’re not remembering what they bought it at. They’re looking at the current condition at the moment.

[Pavan] The current situation. You gotta look at the current situation and trade on that. That’s your best outcome will always be when you trade on the current situation and forget about what happened before. And so everyone at Wall Street knows, every trader knows, every experienced trader knows this, but no one really knows, well, no one. But the most creators don’t know why that works and the reason why that works again is the Markov chain. OK, so basically what Markov proved was that what happens next only depends on the state of affairs right now at this moment. The present is the only thing that determines that can help you predict the future, not the past. So really what Markov saying, forget about the past. Forget that you bought the shares at 50. That is irrelevant to the fact that it’s at 46 right now and it just issued their earnings forecast and you got to make a trade going forward. So you should you can only make bottom line is you can only make decisions based on the present and on the data on the president and forget about everything in the past.

[David] There’s, there’s the life principle here as well, Pavan, because how many people live in the past and they never are able to be successful in the present or the future. That’s

[Pavan] We all live in the past. It’s very hard to remember, the every time you made a mistake, every time we’ve deceived or been hurt or conversely, every time we did something right, had a good time, good things have happened and we get bound to those emotions and we repeat those things. And that doesn’t necessarily mean because something good happened last time and because you turned right, something good happened. Doesn’t mean you’re to turn right the rest of your life.

David Lykken Right. Okay.

[Pavan] So, it’s just because what happened yesterday is not going to, not be driving you what’s going to happen to what you’re going to do tomorrow, right? It’s just only only that matters is what you’re seeing at the moment. Which is really a surprising a moment of clarity, if you really understand this, like only what’s in front of you right now. This second is how you’re supposed to make your decision.

[David] Makes sense.

[Pavan] Yeah, it is sort of sort of. I mean, it’s a little bit of counterintuitive, right? I people like. Yeah, because it’s like, well, what about experience?

[David] It is, it is definitely counterintuitive. Yeah. I’m a trader. So I love trading and I’ve always known you cannot, the past does not give you any help. And when you’re moving forward and you’ve lost some money, you just take it right where it’s at.

[Pavan] Yeah. All that does is create emotional, emotional loops and makes your life very painful. So again, the whole point is the universe is predictable. There’s a probability not predictable, but there’s you can assign probabilities of what could happen next based on exactly what things are right now and the history of how you got there has absolutely no bearing. All right, so let’s talk about what, so 1906, and let’s move forward, how ominous image you have there, vanity knowledge is going to knowledge minus wisdom. Right. And and, know, all that knowledge from Markov minus the wisdom created this terrible instrument of demonic instrument of weapons. So fast forward from 1906 to to 1940. Right. So 34 years later, okay, so this little debate between these two mathematicians in Russia, that math, without that math that Markov pioneered, we couldn’t have made a nuclear bomb. Let’s stop and think about that for a minute. Without the math that these two mathematicians,

 

[Pavan] Without that math that these two Russian mathematicians having this philosophical debate, if they didn’t have that debate, the Manhattan Project would not have succeeded.

 

[David] That, mean, the implications of attaining those two, I’m still struggling a little bit on that, but keep going.

 

[Pavan] Yeah, yeah. And the fundamental, the problem in building a nuclear bomb is that you have to figure out what the critical, the right amount to create the chain reaction. Right. And the chain reaction is one, you know, one neutron hitting another atom and then that spins off more neutrons to hit and hit another atom. Right. So, and then you have to know exactly how much to pack together and the configuration and all this kind of stuff so that to trigger the chain reaction. OK. And what they were trying to do to solve that. And remember, this is before supercomputers. Right. So they couldn’t even actually just run it. They can run simulations. And even then, I don’t think a supercomputer today could ever run the simulation because of the billions of atoms. Because one neutron hits another one that throws off ten other neutrons that may or may not hit more atoms and so on and so on. Right. And the question is, how much uranium do you need to create this chain reaction and how does it need to be packed? OK. And if you put too much, it doesn’t work. you too little, it doesn’t work. All right. So. So but when you look at the whole chain reaction problem, One of the mathematicians, one of the physicists on the Manhattan Project said, hey, wait a minute. This is a Markov chain. I don’t care how we got to the point of this neutron getting released. All I care about is once the neutron is released, what’s the probability of it releasing the next one? So again, the same idea is applied that it doesn’t matter, the past of the chain reaction, all that matters is at this point in the reaction, what’s the probability of the next of the reaction continuing. So once again, the past doesn’t matter. Down to the subatomic level, the past doesn’t matter. where’s the state of the nuclear fuel at any moment? And then what’s the probability of going out and creating another reaction?

[David] Okay, I’m hearing and can’t wait for you to walk us through the rest of this.

[Pavan] Okay, I don’t know if I’ve lost.  know if I’ve lost the audience by now, but the bottom line is math that started in 1906 by two Russian mathematicians was fundamental to the Manhattan Project and ending World War II.

[David] which would set up the Monte Carlo simulations or the tree, which we do use in trading and all the time now.

[Pavan] Right, right, because the Monte Carlo tree search is what was created as a derivative math from Markov chains. It’s just another way to represent the Markov chains. And this is what the Manhattan Project guys called it. It’s a way to do the calculation. It’s a methodology. So yeah, I apologize for introducing a new term here in the middle. But it’s still a Markov chain represented in a slightly different way, calculated a different way and then they named it the Monte Carlo tree, and then it’s named after why they call it Monte Carlo. Again, back to the whole casino thing that we began with is based on the casinos in Monte Carlo. It’s a gambling question. So, probability gambling, nuclear weapons, all the same thing at the end of the day. You know, this tells you when you have knowledge and not have wisdom, then you take something beautiful like this math and you can reverse it is something obscene.

[David] Yeah, and that’s a good word for what we’re looking at in that mushroom cloud. It’s obscene.

[Pavan] Yeah, no wisdom equals to perversion. Ok, so this is kind in a nutshell, like after the AI geniuses watching this will be like, you missed a whole lot. There’s more to it than just these three events. But I’m pulling out the most important ones in my mind, in my opinion, than the most important ones. So we have already talked about 1906, which is without that math, nothing would exist. The 1970. The back propagation paper was published, which is the fundamental of modern neural networks and then 2015 which makes everything all this AI explosion today possible was published by Google in 2015. Google DeepMind used the Monte Carlo Tree search or the Markov chains basically. Okay, and they created AlphaGo. So they beat the world champion Grandmaster Go player. So Google’s AI beat Grandmaster Go player. Okay, remember the Go board is a game board that has infinite possibilities. Every move can create an infinite number of possible moves. Right? very much like a nuclear reaction or a deck of cards, right? And so again, they use the same principle of saying look at the board now and calculate and create this Monte Carlo tree and calculate the most likely next best move and make the move. Okay, so that’s a fundamental of every AI system today is when Google had that breakthrough with AlphaGo, it’s like these Monte Carlo trees are everywhere. Okay, so all this protein folding AI and all the science AI and everything is based on this breakthrough right here. All the physics AI and everything is based on this. Okay, and then finally in 2017, and that’s what makes LLMs and everything else that we’re seeing in AI possible is the attention is all you need, which that paper simplified the whole way we look at language. Okay. Are you with me so far? So 1906, 1970, 2015, 2017, and modern AI is born. So the message take away from this is what really moves the needle on AI. What really creates the breakthroughs is not the latest version of ChatGPT or cloud or something like that. What really moves the needle is fundamental math. When fundamental math breakthroughs occur, then you’ll see big strides in AI.

[David] And I can’t wait to find, and you have created some of those, have you not?

[Pavan] We have, yeah. So we don’t publish our breakthroughs. We’re a commercial operation. We’re not an academic operation. Those are trade secrets. So the question is, can ChatGPT beat the house of Blackjack? Well, ChatGPT or every other modern LLM and every AI, modern AI is nothing more than a very sophisticated Markov chain or Monte Carlo tree, very large and very sophisticated Monte Carlo tree, which is a Markov chain. So yes, wouldn’t it be hard at all for it to give it a hand and it’ll tell you the most probability whether you should hit or not hit. It’s a very simple thing for modern AI to do.

[David] Simple, okay.

[Pavan] Yeah. And again, as I said earlier, there’s a paper already out published on this exactly the math on how this is done.

[David] And that was the paper you mentioned in the previous slide.

[Pavan] That in the beginning, yes. That was the paper I mentioned in the beginning slide. Correct.

[David] Fascinating. Now this imagery got my attention.

[Pavan] All right, so will AI nuke my business? So we create these great tools or weapons, whether it’s AI or Nuke, and in the wrong hands, it can destroy the world, like any other tool. Will it nuke your business? If you don’t apply it and learn it and use it, yes, your competitors will nuke you. That’s kind of the simple the simple lesson from that. And then the second is. And probably the more most important lesson that to take away from from this presentation, from this discussion is it’s just math, it’s not magic. Right. If you if you scroll through social media and you listen to like all the hype that’s out there and people talking about it, I was going to this, I was going to do that. And yeah, it’s going to do a lot of those things. But so much of social media and pop culture is presented like this is some kind of magic, right? There’s no magic. There’s no magic. It’s no more magical than the calculator on your phone or on your desk or no more magical than, you know, watching, you know, having a video call with your mom, right? That’s a video call with your mom’s on your wireless device would have seemed like magic in the 80s.

[David] Right. It would have been, yes.

[Pavan] Yeah, right. That’s like something out of Dick Tracy movie or something like that. But, you know, these days everyone’s doing it. It’s just tech. It’s just math. Right. So just so don’t get like overwhelmed by it. There’s no magic. It’s just it’s just a process. It’s math and anyone can learn it. It’s straightforward. Right. And and don’t be scared of this. And like you have to be mathematician to make use of it. The reason I went into all this math is so that you can just relax. There’s no magic here. Someone else has already done the heavy lifting, already done the math, unless you’re a mathematician and you want to, and your intent on making the next breakthrough on AI, okay, don’t worry about the math. Just understand the tools and use it for what it can do.

[David] Yeah, and that’s the lesson out of this.

[Pavan] Yeah, exactly. Well, that’s one of the lessons out of this. And we’re going to cover a couple more lessons. Right. So, going back to the math with 120 years of this math. Well tested and so much technology, almost like in many ways, all the technology you use today goes back to what Markov. The math that Markov founded pioneered in 1906. OK. And it’s fundamentally what you know what happens next depends only on the state of affairs and more important more to the point. The state of your mind now. So live in the moment. OK, meaning, you know, so if you’re trying to make a decision, right, be be drop the drop all the the the emotions of the past. Have a clear understanding of the present of this moment. Right, don’t don’t worry about what happened yesterday. Things happened yesterday.

[David] As a consultant in my own life, I’m sitting and thinking the profoundness of this statement live in the moment, but I’ve always heard that. But when you think about what you’re talking about here, as it relates to that, gives new light of the importance of this principle.

[Pavan] Yes, yes. And here’s the thing to take away from is this live in the moment, right? Make decisions based on the facts, real hard facts that you have in front of you. What do you know right now and make the decisions based on that? OK, this isn’t a philosophy. This is science now. There is 120 years of math supporting this. This is real science. This is why every Wall Street trader is adamant about following this science. Now you can make a bad decision because you didn’t have enough information or you didn’t consider all the facts. Right. But. Right. Either you didn’t consider what happens usually is you don’t consider all the facts in the present and then you end up including facts from the past that are not relevant in the present. That’s why most bad decisions are made. Feelings from that you take feelings from the past and you bundle it in as facts of the present. Again, the best example of when you take feelings of the past and make it a present day fact is you bought the shares at 50 and that is a dimension to your current decision process. Well, no, it doesn’t matter what you bought the shares at. You take that out of the input. You play the board as it is today. don’t like when you play chess, the fact that he just lost your queen doesn’t matter. Now you have to play the board with what you’ve got.

[David] Part that is if this is more than a philosophy, what you’re doing is you’re getting this to the point where it is. my gosh.

[Pavan] Right? So it doesn’t matter what’s going on around you, right? What happened? You just you got to have a calm state of mind. It could be a nuclear bomb going off. It doesn’t matter, got it when you’re taking the decision right now. Calm, clear state of mind and move on.

[David] That’s a tremendous graphic. Wow.

[Pavan] Right and you know a business feels like that so much right yeah it’s there are really hard days when it feels like bombs are going off everywhere right doesn’t matter right but you still got to move forward you still got to make decisions and those decisions can only be made on what real data you have right now

[David] Yeah. Amazing, I really find this so fascinating.

[Pavan] Alright, so the last bit of philosophy, you know, we’ll drop is why do we insist on living in the past? What keeps as human beings we keep getting dragged into all the good and bad things that happened in past and we let it we keep letting those things influence us in the moment, and my theory on that is that is vanity. It’s our vanity. Our ego gets hurt, right? Our ego gets lifted or it gets hurt based on things that happened in the past. And we confuse our ego with who we are. And now the two different things. Right. So vanity is definitely the devil’s favorite sin.

[David] It’s so true.

[Pavan] And those of you who know the Buddha’s story, that was his last test before he became the Buddha. Before Siddhartha became the Buddha, his last test that got through at him was see if he could defeat his own vanity.

[David] And the outcome was…

[Pavan] The outcome was that he did. And very, very, very few people have ever, if you defeat, yeah, yeah. mean, you basically become a Buddha if you control and defeat your vanity. So anyone out there thinking they defeat the vanity, yeah, that’s vanity in itself.

[David] So, Pavan, take this all now back to what we’re talking about in AI. There’s a lot of people that are working on the past, where they’re stuck in the past and their minds there. Things are changing. We have a new reality out there. AI things that are going on. People like you that have brilliant minds that in this presentation just tells me again reminds me how brilliant your brain is. But carrying that now to the applied, what should people be thinking as they look at, you’ve started think about what you said today. Think about their business and how should they be moving forward?

[Pavan] Yeah, so first is. You know, don’t get over hyped by social media, by what’s being thrown out there, right? I read all of the, not all, as much as I can. I think I read all the important papers that come out of Google and Apple and MIT and other major institutions, major academics on AI and on the math. And there’s a lot of interesting stuff that comes out. I have not seen another paper yet that is as significant as the ones that I mentioned. I’ve not seen anything that’s as significant as Google Go or as the attention is all you need or as Markov chains things like that, right? So that means we’re at a plateau, right? AI is at a plateau and when you’re in a technology plateau things will get marginally better. know, they’re usually there’s more applications of the science but there isn’t necessarily, we don’t have another breakthrough yet and a breakthrough will happen when new math is invented. Okay, so

[David] Now that math, let’s talk about that. You’re the mathematician. Does new math get invented or does it exist? It’s just us discovering it. Because all it mean the question I would have is all math has already been created. We just don’t have the knowledge of it, right?

[Pavan] I think I forget which think which physicist said this but the the best mathematician is God and you know we’re just we’re just trying to figure out his formulas.

[David] Yeah, scratching the surface of it to be honest. I agree. I agree. Absolutely. I agree. Alright, so going back to the lessons that we need to learn from your presentation today, what are the things that you would encourage business owners?

[Pavan] Right, so the bottom line is that the good news is that I believe there’s a plateau. There’s a plateau in not an application, but in fundamental capability.

[David] So a plateau compared to where we have been, where there has been the contrast in is there’s been steep learning, a lot of learning, but now we’re hitting a plateau and leveling off and able to capitalize on it.

[Pavan] Yes, so the bottom line is, is there’s been the science has put us to a point where there’s enough there in AI. It’s enough of it has come together where it’s really usable and we can do and it has real business applications that we can make money with it. OK, and this before, you know. Before Google’s attention paper, that didn’t exist. Okay, there was application that was more niche specific application of AI. Now after Google’s attention paper, there’s broad based application that everyone can use and the plateau means is that we have the sciences at a plateau, the technology is getting better so that more and more of us can use it and it’s cheaper and easier to use the AI. every day we’re inventing and discovering new ways to apply it. Okay, so don’t bother yourself with the science and the math of how this actually works. It doesn’t really matter. Okay, just get in there and pick your favorite tool and hopefully your favorite tool is Angel AI and start learning it, using it. And like what I’ve seen from my own experience is customers are using Angel AI in ways that I never even thought about. Like, wow, that’s really cool. I didn’t think you could do it for that, right? Because it’s…

[David] Can you give us a good example for that? Can you give an example? Cause I mean, I love these. Thank you for sending over all the testimonials that you do and they can all be found on your website: angelai.com. You can go down testimonials of yours and read them and you should, because there’s people that are discovering the, some new uses and tool error use cases for angel AI all the time. Give us a couple of examples of the ones that have really impressed you recently.

[Pavan] I think I was talking to a Realtor recently and he’s connected it to his inbound lead process and as the lead comes in, it automatically qualifies the AI for the Realtor. The AI is automatically approving the customer, right? And he’s getting and then immediately going back and giving answers back to the customer. So he’s now for his customers like a super-agent. And so he’s connected in a certain way with his emails that I never thought about and he made it work. They’re like, OK, that’s cool.

[David] So when you say he has inbound leads, are they leads that are coming via email?

[Pavan] From his website, email, know, whatever.

[David] So it’s not limited to one source. And he has those leads coming into his email or into, into Angel AI is he’s, he’s built the…

[Pavan] He’s getting the documents and he’s set up bots to load it in Angel and let it run and give his answer. So, he’s literally changed his whole…

[David] Bots are inside of Angel..

[Pavan] Outside of Angel. Yeah. And to that matter, we’re going to make that process really, really easy now. And last week, we released a press release about this, about Angel AI Open Cloud integration. And I’m sure everyone listening to this has heard of Open Claude.

[David] Absolutely

[Pavan] And so Angel AI will now be tightly integrated with OpenClaw. So if you have your Open, so that you can go to Angel AI, it’ll set up your OpenClaw environment and Angel will be an agent inside OpenClaw. And you can just make this whole process of connecting to your leads, connecting to your workflow becomes even more transparent and easy.

[Pavan] Fascinating. Pavan, every time we get together with you, you challenge my brain, you grow, we grow and learn more what’s behind the curtain and as well as what we can do moving forward. Thank you so much.

[Pavan] Yeah, and one more thing I wanna add to that is, and you asked for examples, is the sort of native CRM capabilities that are in Angel. And people are using that a lot to generate leads. And…

[David] Yeah, now you’re hitting a really interesting topic. Explain how are people doing that?

[Pavan] Yeah, so here’s the thing, when you use Angel, you earn points for using it, and you earn a lot of points when you refer Angel to somebody else, you earn a bunch of points, like tons of points. And so we have people out there with million plus points. And then you can use those points. One of the things you can use the points for is you can use it to buy leads, like data, like high quality, expensive data. You can buy…

[David] And where are they buying the leads from then?

[Pavan] They’re buying it from, know, Angel goes out to data brokers and buys the data. Right. So you use the points to buy the data and Angel takes care. You don’t have to worry about that because Angel goes and gets it from data brokers and loads it up. And then you then you turn around and use the angel prospecting app and it’ll start calling and nurturing those leads for you. So it’s like you let these agents run on their, these angel agents run on their own and you’re generating business. But not only are you generating business, but it’s taking the business all the way across the finish line in your closing business. And now imagine that integrated into OpenClaw where OpenClaw is now connected to, the beauty of OpenClaw is that it’s connected to everything else in the universe, right, or in the cyberverse, right? Your emails, your WhatsApp, your social media, your accounting system, this, that, OpenClaw can connect to anything you teleconnect to and imagine like those leads coming in and customers being contacted all different ways and OpenClaw is sending out all the messages the way you want it to to everything else. mean, it’s just, there’s no limit to this. You can literally have a one man machine basically. If you’re a realtor, could set this up and buy yourself, be nurturing tens of thousands of customers that would normally take a large team to do. But now you have hundreds of agents doing it for you. You just set up the open file agents to it.

[David] We truly entered a new world, Pavan.

[Pavan] Yeah, and again, it’s just, there’s so much creativity out there that to be captured, right? And anyone listening, you just gotta get in there, just use it, right? and apply your creative energy and you’re to be able to create amazing things just like you know get a hammer, nails and a saw and you can build a house right. Those are fundamental tools. AI is a fundamental tool to building a business empire. What you can do now on your own that’s what’s changed right is what you as one person can do. Right? It would normally have required a large team, large expensive team and training and investment. You could just do if you just take that time and money and invest in yourself and just learning, learning some of these tools and using it. It’s equivalent of having a team of hundreds.

[David] That’s true. I mean, we’re seeing evidence of that all the time is we’re looking more and more the productivity. Productivity should be able to go up dramatically, as far as it relates to the number of loans, someone can originate self-serve and not and still not give up their life to accommodate or to serve that many people. It’s really about providing service.

[Pavan] It’s not just about providing service, we’re better service.

[David] Better service, yes, that’s a good way to put it, yes, absolutely.

[Pavan] Customers will feel the difference. That’s what’s really going to end up at the end of the day, customers who’s working with your competitor who’s not on AI and who’s a very good guy, working his or her, know, tush off, right? And sincere and cares. then you with AI, also really good guy working your tush off. Okay, but that same 8 hour day you’re going to deliver a level of service that’s 100 times better than the other guy simply because that customer is going to feel like that customer feel like you are dedicated to that customer, to that person. Like for example, I’ll give an example of that just happened two days ago. One of my top producers in Texas, she posted her Angel Twin link, her Angel AI link with her twin. So was like it’s AngelAI/Christina or something like that. She posted it on her realtors listing post and says, you want to take, if you’re interested in this house, click here and talk to me and take, take your loan application. All right. She got six loan applications from one post.

[David] Wow. and didn’t have to talk to a person because it was…

[Pavan] Her twin talk to the person.

[David] And how convincing is that today? I’ve seen it. So I’m asking the question, knowing the answer, but explain just how convincing and interactive ability it is.

[Pavan] Well, know, look, it’s not designed to convince you to say that this is the real Christina, not the twin Christina, right? We’re not trying to fool anyone. And the minute you try to do that, never use AI to try to fool someone that it’s you, okay? Because then you lose the trust. Trust is the most important in the business. it’s very clear that you’re talking to Yes, so the customer is very clear that he’s talking to the AI of Christina. But the customer also creates a bond and a connection with that AI, similar to the way that he would with Christina. He feels more comfortable. like, I can get along with Christina. I think I do want to work with her.

[David] So when someone like Christina uses this tool, does it shorten its time it takes and the volume she can do that the time that I loan from map to closing.

[Pavan]Yeah, absolutely. She took seven loan applications and never talked to the borrower. Her twin talked to the borrower.

[David] That’s extraordinary.

[Pavan] I mean, she did call him afterwards and just check up on him. How you doing? Right. But that’s not the same. Can you imagine? You how much you should take? You should take dozens of applications and you know how much time it takes.

[David] Oh, yes. This is amazing. Thank you so much, Pavan.

[Pavan] Thank you, David Cheers

[David] You bet