Slava:   0:17
Hey. Hello, everyone, guys. So the thing that you just here in your years, it's kind of a podcast kind of a new, and I don't know how much you want to tell you about these, But 1st 1st let me trying to introduce a co host. Oh, wait, wait. No, no, no, No 11 important thing. So there are many people who tell me that my Russian accent sounds offensive. Eso pleased. I'm buying to these. Feel free to interrupt me, but you cannot. Uh uh. Okay, now the cohorts, they already kind of joining so one laughing that he will love that. Just hurt. Yes. Again, that was Zane's in Could. Introduce yourself, please.

Zain:   0:56
I'm Zane. I don't know how much. No, but Slava, but ah, I worked with this guy. He seems pretty nice.

Slava:   1:06
No one else told me that. So thank you. You can tell. You can tell if we just start working together recently because he tells them a nice guy. So, yes,

Sandeep:   1:15
Uh, time will tell. Yes, yes.

Slava:   1:20
Now we have another co host who physically cannot speak together with me because we're right now starting the same microphone.

Sandeep:   1:28
Thanks a lot for Slava. Hey, guys, this is Sunday, this is Sandeep. Zain working with Slava now and has a really good appreciation for him. But I can assure you that I worked with him in the past. And definitely. Yes. He is the awesome guy. And the most funny person you can hear, too. Let's get started. Okay.

Slava:   1:51
Oh, yes. Oh, yes. Um, can anyone told me precisely what the concept of the show is. So what we're going to speak about, like, the high level? Why? Why? Why anyone

Zain:   2:04
Gee, we were hoping you could tell us!

Slava:   2:06
Okay, so, yeah, way. We're going to speak about anything in IT. So this is a small island on a ward where we want to share our personal opinion. Personal. It's not tied to anyone. Our, not, definitely not our company, it's not the place we work. It's our purely personal judgment. So there should be in the future. That should be voice effect. Of all the effect that says air and some warning there is a bias. Tons of ice is because again, it's personal opinion on the average thing that happens in the industry on, like, I'm pretty sure that someone will not like many thing that I personally going to say at this, that is for sure that I can guarantee you personally. You probably whoever releasing right now you will not like me. So just don't listen. If you don't like, uh, yes, we're going to review some of the happenings in the IT world, news. Whatever we want. Maybe time to time. It will be non related to IT. Time to time. I would like to discuss phones, my friends might discuss laptops or, I don't know, even close. Whatever we want So you've been warned if for some reason you still want to stick to this podcast, come one in. Now I'm going to stop speaking and, uh, I will shut up. And I want someone to present at least one topic that we're going to start with a pilot pilot conversation.

Sandeep:   3:25
Yeah, thanks for that Slava. So one off the topic that was running in my mind and also personally I went through is effectively dealership on dhe. Effective leadership is a very broad topic, but what I wanted to talk about is, like, once we have a product that is really fast growing a lot off users lot off new features, lot off competitors. So you are in kind of a startup world or even established company, but you do have to run against time. So in this setting, how does a leadership react? How does a team needs to support that leadership and what all the various styles off working? How does it impact the fast running product on the team? So I felt this is a very interesting topic for many off us who is working in the field off the eye, where the field itself is moving so fast with so many cutthroat competition. So I thought, probably we can tough on this topic. What do you guys think?

Zain:   4:41
What's something particular that you were finding interesting about this?

Slava:   4:46
Yeah, that's that's exactly my My, my. My immediate question like doping is so broad like leadership. Like taking stick, find the person they can ask a person to do your work with the stick like you are the leader. So can you be more specific? What exactly mean?

Sandeep:   5:01
For example, let's start with the topic number one within this broad topic, like you guys mentioned hiding, so the product needs to be built faster. There is lot of requirements that needs to be implemented. There is customers already lining up for you on dhe, maybe what? We could talk us. What is the best hiding strategy? There are different ways of doing right because we need to grow fast really fast. One of the ways I will hide lot off general engineers may not be particular to the door mine or the product that I'm working on. For example, like we talked, we work in here, and we need to build a product for Emel researchers. Do you want to grow faster by hiring generics offerings in years? Who might be able to quickly ramp up onto this Emily or whatever the hell mine off the product you're building our? You want to make sure you hire software engineers who understands the domain at least a bit so they could work backwards and understand what and what is the use case off the users? This might be something that we could talk. What do you guys think?

Zain:   6:08
So your question is kind of like about whether you should hire a specialist or a generalist and get the generalised to ramp up.

Sandeep:   6:15
Yeah, and also the balance between hiding too fast on the generalised are managing that balance off like, say, one is two yen and then can be anything depends on the product, the current state off, the people who is working on things. So it might be a case. For example, I went through a team. I've been through a team where we have hundreds off requirements given by the users. But the biggest problem waas the time was critical. For example, a computer is building exactly similar product for you on dhe. You are trying to build the same product for that customer. Andi. If you hired a generalist, you're going to satisfy those requirements for now. But you cannot invent for the future. For example, if I do not understand the impact off a mission learning model with respect to computation, I can satisfy a server based user requirement today. But can I invent how the same thing can run best on a lawyer and device like mobile? Because I do not understand the concept fully. Maybe I will not even be aware that we need some kindof optimization to run it on mobile. Or maybe I'm too slow, and it might take too much time for me to realize and innovate products off the future, though I'm satisfying the requirements for now,

Zain:   7:52
it sounds like your kind. I guess the assumption that you're coming from is that the general list is pretty much going to be needed to be given a very specific set of instructions of what to do versus the Specialist can kind of figure stuff out on their own. It's kind of like the generalist is just taking an instruction manual for a Nike A furniture and just hammering away doing whatever stuff 12 and three are saying telling you to do. And I guess in your mind a specialist, someone who's more of a, uh, really just has been a built a lot of furniture. And he knows, Hey, I'm just not gonna even bother what the I came at. You get. Take this tabletop over here, attached it with these legs, uh, toss a mattress on top and suddenly and hanging from the ceiling. And I have my own loft bed instead of anything that was meant to be made

Sandeep:   8:42
exact, really satisfying the current requirement. Warsaw's like inventing for the future. That's exactly what

Zain:   8:49
I was stalking. It kind of sounded like the difference between a junior and a senior engineer were like the junior engineer. You kind of like Give them more prescribed work of what to do in a senior year is more expected to have the longer term vision

Sandeep:   9:06
that kind off simplify ce one off the way to see this, for example, like How many systems have you seen to be able to generalize a particular thing? Worse is like This is exactly how people are going to use my product and you go into the shoes off that customer and then went for the future. For example, me, as a general software engineer probably can write extensions for Jupiter Notebook to satisfy current systems requirement, however, can I come up with something like a new Jupiter notebook, which might not be bitter notebook itself? We thought, understanding exactly why Jupiter Notebook is being used by this research scientists. This

Slava:   9:58
conversation is like, you know, problem of the first world, like when you're thinking when you're speaking with someone who creating start up in Illinois. I think the problem's hire anyone like like the hiding person who learn javascript Yesterday who more or less capable of passing the interview, teaching them job just because they can inquire job people like this question about general is specialized. I think that we are. We're kind of blessed to be even in the position when you think about these and choosing between generalizes specialized because usually the world like you taking specialized even if you need a general's wife. Syverson. Whoever is able to passing through that is n general. Very huge problem on DA startup usually cannot compete money wise when the metropolitan areas, when they're outside of metropolitan areas, there is just no people there. It's just very, very, very hard to find anyone on. I do think that right now a lot of people just hiding whoever literally passing the bar and hoping to educate the portion to do whatever is needed. Ah, specifically for machine learning, deep learning things. There's not that many a specialized I don't know. How would you guys? But I haven't seen too many in the wild people who for machine learning, are capable off solving production. White task in the start of that

Zain:   11:21
was like just been hiring, trying to hire someone

Slava:   11:24
a a Yeah, just just talking. Yeah, I don't know the reason noticeably bullet, but if let's say we were speaking about some major call situation in society where you can equally choose general specialist or or professional in particular fields, we need to work, work backwards from the problem. I mean, I'm going to tell this a lot, like I just like the sounds were, I think, the more the only answer. That could be better that, like what work's work backwards from? The problem is, it depends. So that would be the best answer. The 2nd 1 leg. Let's work backwards, and this is just too generous. If you can describe the problem like I don't know what what you're trying to solve, figure out the average size of the cow in the field. Like then I can tell you

Sandeep:   12:17
that's a really good point on. When I mentioned about this topic, it's not only for big companies are started. So what we're saying is that as a leader, you understand the pace at which we need to go, for example, thinking about inventing for future. I cannot deprive my existing customers, so it definitely yes, I need to increase my head calm high as much as possible. Keep building it, but I need to have a longer vision to make sure I inject Would not do. Specialist. That's exactly what I was saying. Way Need tohave an issue in the team like one historian for one specialist Toe end Really good generalists from that air depends on the product company Current State off your team. Bilious reasons. If we continue on the hiring spree off having a lot of generalised in the team, it's going to be really hard for you to make a term a role in the team toe in mind for the future and with I need to intercept this hiring spree, introduced this specialist and kind off start innovating for the future. When I get a confidence that my current customers need our Matt, he's going to be, like, really helpful and necessary. If you want to stay longer with your products in the market,

Slava:   14:02
you speak. You're speaking allies, project marketing guy like I understand the words. I have no idea what just like What does it mean in the wait for the future or stuff like that? I have no idea what does it mean? I, um I do afraid off doing any predictions because I know how sue, how often they are going. They turned out to the falls. When you're building for long term, I would personally prefer to make as generating this possible who would be reeling to dive to any particular problem. They happen hand and convert themselves to specialists in the field in the particular particular problem, because I really don't know what it's mean. For example, to long term in the wait. I know the words, yes, but if we're trying to work backwards from this definition, they usually doesn't mean much. If you have long term idea, it's almost like playing in casino. If it works or not. If you being pragmatic, this mean that by default you don't have long term idea, even pragmatically working with the customer's needs. And yes, there are there would be some customers needs that requires a long term solution just because you cannot solve it with stools attend, that is for sure. Ah, but yet again this problem will lead you to completely different fields today it might be requires you have especially is who knows typescript. Tomorrow it might be much Matich in pure mathematician in some cases, make sense to outsource this task with people who can help you much faster than your generally specialties can learn this but my personal 10 cents I would prefer to work with entrepreneur mind set people who has some skills and engineering some skills like that is not a critical point. The critical point. They open mindedness in the entrepreneur skills so they can dive and effectively become specialists in the field were needed. Or they can come back to me and say, Look, here is a field and we actually can solve the problems We'll hire, sort of not the higher but, um, if we involve some external party to help with this, like hire temporary worker who knows way better than we are physics for problem A just for the duration of the months and that's about it. Or maybe it makes sense to invested, but again that this all depends on the particular situation. It's kind of indirectly indirectly touches another topic about about the successful product, but they're not going to jump there because they have no idea if we exhausted this one or not yet um,

Zain:   16:45
let's get closer to what you were discussing about. When What is the point of the specialist engineer? And this is like kind of what some deep was referring to was like his. Your mind, The specialist engineer is the that one of their values is that they will help come up with the long term product ideas and visions. And I guess Theus assumption that you're making is that you need to have that really deep technical knowledge to be able to see the opportunities that the technology makes available for a customer product. And I think worst love us coming from is that if you kind of have more of an overview off the different areas and you had no of other areas and you're kind of like more a little bit more broadly, uh, exposed, then you can see the opportunities that are available by connecting these different areas, like Lego pieces instead of necessarily you having really deep insight into one particular area. And if you need that expertise for some reason, either you can, uh, gain that expertise yourself or consult with someone or hire someone at that time who has that particular expertise that you need. But the longer term vision are getting the idea generation and then proving that that idea is really something that the market wants is something that wouldn't necessarily need the technology expertise that just it would need more of a entrepreneurial mindset works where you kind of, like have the broader focus on the different areas and then you can dig deep for and then you can, uh, iterated quickly on it And, like, actually validate those ideas and assumptions.

Sandeep:   18:41
Yeah, you're spot on. Actually, if you go back towards Lava was saying, for example, I need a physics expert, and I'm goingto consult with the temporary person O. R. It can be even another consulting company. That's exactly what I was trying to save. They're generally software engineers are the pillars. However, we do need such concern stations at the right time. If not, we're going to get into that cycle off the same circular, which it's kind of like fitting the existing model. How can you build something like tensorflow if you're not having a specialist building the algorithms on applications off the planning for the future? When I say let's go back to 2012. Deep learning was not generally applicable across industry. And if Google did not hard computervision, natural language processing and other domain specific experts, they could not have even thought off a need for a library like Tensorflow. However, once the idea, the need and the requirements, that doesn't come as like one bullet point, it evolves in the team as you get more exposed with people off diverse experience. But to get tenser floor, tow the state where it is today in last four years, the generalised software with entrepreneurial mindset who could pick up things are the one who built it. I totally agree that, but to come up with something like Okay, we need to build something like this. This is the foundation. That's where a specialist would have played a significant role. That's what I was trying to come up.

Zain:   20:40
E. I would wonder if, like taking the tensorflow example cause tens of flu like I don't know the history behind how tense flow was built, but I would assume that it wasn't just someone who thought, Hey, we should have, like this public library to do machine learning don't like 15. Hey, listen, Jeff dean that it's a completely different thing. But But, uh, I would imagine the start off as just like an internal collection that its very first like fetal stage was. It was just an internal collection of libraries that people found useful for doing machine learning. Then it became a bit more mature and still internally, more mature, like iterations of the coming war. Mature until finally one day Jeff Dean came along and said, Hey, you know what? We've got something very close now to being something that could be a really good public library. Let's actually Paul delicious stuff. Maybe rewrite this thing and make it much better, or somehow re factor this effectively into something that we can publish publicly on dhe. So that what you don't necessarily like if this assuming this was a the case, which maybe it wasn't assuming if it was the kid case was something like that, you wouldn't add like the division ery level, you wouldn't necessarily need tohave that deep technical knowledge of everything that's been built into tents flow over the years. But you would need to have that mindset of Hey, we've got Resource X here, and we could do action. Why on it to make it more publicly useful to like the public and to our company.

Slava:   22:29
I was listening to you guys and what to provide. Provide my immune this because I have the point that's quite unpopular in the industry right now. Actually, don't think that the vision and the Mayan expertise are super available for the success of his wife. So 11 specific ideological item that's requires for for logical chain. The huge success of any product is random due to, due to some random events that this that this key point and there was me because there is a logic behind it. If you're speaking about any successful project in the world, tens or floor, it doesn't any. You always need. Thio provide the numbers of how many other project had half exactly the same environment and exactly same criterias for the success who actually haven't succeeded because we, as a human, would have this natural tendency to post facto explain everything that happened. Why the people who deliver it has amazing insight is amazing, especially so whatever. But I do believe that hockey stick success it's usually purely random factor this is hard to to accept because this mean that's Moonshots by default cannot succeed in this environment. But the's actually opens the door off questions, then how we can build at least more than

Zain:   24:12
actually push back a little bit on your assumptions. Are your statement there that it's a random thing? Because I think your your actual claim, which is a valid claim, is that we don't have enough evidence to be certain of the narratives that people build up around, why a certain company became more popular or not. But I think I would suggest that the right conclusion to take from that would be that way don't have any evidence to enough evidence to be confident about the popular story. But the lack of having that evidence is not evidence to say that. Hey, the thing is random, like the success comes randomly because that needs its own evidence to say, Hey, this is coming from like this is randomly distributed success,

Slava:   25:06
sure, but there is way more evidence that this is random. Like, for example, there are tons of the product that, far from being optimal, that shows that what get a huge popularity gin and just by chance, like quite a keyboard that we're using our novel laptops. This is far as far away from the bean option was possible. QWERTY keyboard was designed Ali out of the keyboard to reduce the speed in which people in the early machine was typing. Because when we're typing with the full spiel that the the human capable, the harder would fail very quickly. So they designed a layouts precisely to decrease the speed. But just because of the random sequence of who went, this became the most popular product far away from the optimum. There's many experts that try to change it, but as method because expertise doesn't matter in this huge success, the same almost everywhere. If you take any particular product us like take Windows. Are you actually saying to me that we can see why it's successful? But no one was able to replicate? Very likely. If you look in the market in the same time frame, you'll find tons of Lasses that has exactly the same criterias that Microsoft implemented. By the way, Emma's Doors was bought by Bill Gates, so it's not even implemented by him. But he made it successful, which also means that implementations and expertise behind the condition was not the key, completely something different. But even if you try post factum to explain something difference, the's something else doesn't mean that no one else seen absorbed this. Only we right now, so smart that we have discovered that create tedious. Or maybe it's more more probabilistic that other people tried to re create the same thing. But likelihood was not in favor of their creation. And it's made. It's very simple to count failed the Thames eso. We have more evidence than that. It's random than we have evidence that it's not random because no one was able to figure out criterias that you can apply to have none round of effect, though even like good example tender for amazing popular framework. How many other are not? Are these the good evidence that it's random or maybe other deep learning frame? We're just ignoring some creative areas that tens of four used to became popular. What is more, more life like

Zain:   27:46
what? One possibility is like a If you've read, I think Malcolm Gladwell's book Blink talks about how certain ideas spread, like how fashion spreads was one of the example that gave he had there were like a few different types of people. There were people who were innovators who came up with a different ideas. There were people who were connectors on. Then some other third category. I forget what it was, but the core idea was that, like you would have somebody he would come up with, like a basic idea innovation, maybe someone else who might like to see that and improve upon it make it a bit better. But with them, those two people generally their sphere of influence would tend to be pretty small. And then somehow like the idea. The thing that would really make the ideas popular was if that the three idea was then seen by someone who's known as a connector, and that person started adopting that idea and then from that connector person, the idea spread out to all the people that they're connected with, which is effectively like in our product analogy. This wouldn't be the equivalent of ah, finding a winning marketing strategy or PR strategy outreach strategy on which is a really hard thing to do because people have limited time and attention and you need some lever to be able to actually gain that attention, gain that time from people, uh, actually pretended to your product to generate that buzzer on your product. Got cold departments of large companies that are dedicated just to like getting this part Working s O. That piece alone could make a big difference like that. You'd put partnerships with other companies, for example, under that bucket, because those are things that are extremely difficult to get right, because it's and it's a relative, fairly ambiguous thing. It's not like an engineering work where if you do exactly put a, you'll get the exact up would be. It's very dependent on the environment of the time of what strategy will work to actually get that attention of your desired market. So,

Sandeep:   30:13
for example, you talked about Tensorflow. I would say that there are multiple deep learning frameworks went inside, flow came out. But what stood out is that Google's experience in reaching to the people in the right channel, for example, writing lot of tutorials. Having Google Developer group having like Google developer experts, there is a program in Google, for example, they're not employed by Google, but they write a lot off blocks, tutorials, organized local meet ups. So there are few defined way off reaching people in the right, more on which is scalable. That is what the Google has expert ized or a period of time across multiple open source project. So it was not a random even where tens of floor reached its users in a better way than other deep learning frameworks did. So it might be a few percentage off Randomness are just because of the time being, like you mentioned. But there is a pattern on the expert eyes off doing that. That's exactly what I was saying. People who has done that before you'll be able to sell your board faster to the same destination. I was not arguing that other expert generalists cannot do that, but how quickly on in what way we will reach their destination. But how fast I can reach can accelerate a bit. And how can I do that? And it's not random. Always there is a pattern. There are some secrets, us why a company can make my people open source projects successful and why a company can take my tipple open source project and make it a very successful business. Products, for example, Aid oblivious. No one other than a jobless is able to monetize open source software that well in enterprise world. Why is other companies not able to do that? There is a secret sauce off doing certain things in a certain way. So even though there might be some randomness, it's not like there were other things very similar. But because off some random events this product was successful. That might be not like black. Get statement. What do you think?

Slava:   32:48
I disagree with those of us with other U. S. Zane is actually directly mentioned almost almost with the book, and that that book is actually by itself is direct mentioning of this fact. We don't have a partner that we can use, but we can describe post factum post factum. This is our human nature to do exactly what they need us, they would send him just describe. We want to logically explain this, but they said pure mathematical evidence, if you would remove your subjective desire to have this formula, tells you that if you will formulate, like spend some time to formulate this pattern and then ask questions. How many other companies applied exactly the same partner together with example and have failed without this number? It's hard to say that it's not not random, and the thing is because it's so in our it's so embedded in our nature to believe in these existing such formula for the huge success, with only one trying to calculate. But it's not hard, like, if you're speaking about any success framework the same company, ask other, many framework are successful the same level or service's and sorry. I think they want to say something.

Zain:   34:07
Well, I just wanted to provide a counter example, which is, I mean to a certain extent, you're right, that the pattern is not like it's not deterministic, right? It's because you your success is not simply on how well you connects. Based on how well you could execute yesterday's pattern, it's how long how well you can, Executing yesterday's principle and adapted to today's reality and the today's reality always keeps changing and to kind of like, uh, a za counter example to your idea of like how many companies fail because there are. All these companies are competing with each other on similar areas. And if you take the example of, say, the sports team, like an NFL team or a soccer team, they're all competing with each other. And they're all crying relatively the same, like working on the same pattern. And they're all trying to do the same thing to win the championship. But the end of the day, only one of those teams will win the championship. Is it because, like it was random or because, like there was no pattern than what they could do? No, they're all following, like roughly the same set of principles. Their ability to execute on those principles will vary and their ability to adapt those principles to the latest reality of how, if other teams have adapted to the techniques of the championship team last year, um, those tactics used by the championship team last year will no longer be as effective. And they have to be able to adapt to that. You're a reality to still be successful and come out on top so that adaptability is a big con, a big part of this and to a certain extent there is like amount of randomness effectively that gets injected into this because not everyone will be able to adapt to every situation as well. Or you may not notice the opportunities that this new situation presents to you. But just because being being able to take advantage of the new situation eyes not a deterministic thing, I I would say that taking that base and extrapolating from that that success itself is inherently random. That that seems like a bigger leap to me.

Slava:   36:29
You know that this incorrect, I'm set huge success more than its success. You can always attribute the hard work and and strategy, that's for sure more than its success. And that is why I do think that moderate success is what anyone need to aim and how the cheap mother excesses completely different story I was thinking about particularly high level. Haughey sticks success of the product because yes, you can name one or two very, very popular things that any companies doing everything else is moderate, moderate Exactly, because, yeah, that that two spikes would be random on the example with school with ah, championship is very good. You Actually, yes, it's it's ah, exactly results that can be achieved you to these moderate success and result. They they're as moderate. It's not like that. There is a team that can suddenly get all the mining for the championship to come. That doesn't get there. It's just impossible on. If there would be some way to get it, I actually would claim that someone will will get it eventually. Now here's an interesting experiment that in the past was done. Very, very interesting. Mental experiment. So let's say that you I forgot who I think I'll have described this experiment, but he get it from summer. So what? So you're sending to us population, uh, of prediction about the future markets you're sending through whole U. S population. 50% you're sending them that markets will go up 50%. Markets will go down next month. You taking the half of the population that got the right prediction from you, you dividing into and sending and get again, right? Prediction. Approximately in like 10 months, you will still have some for a sub part of the population that constantly getting right prediction from you doesn't mean that you have discovered the Potter pattern that works 100% and post factum that people that blindness to get prediction from you forced Factum, They will find the reason why the prediction work, that is for sure. They will find the formula why it worked. But it's not that they actually have find the formal. The reason being that our work is so complex that there is infinite amount of formulas they can apply for situation that by default by itself means that you can find explanation off any partners you confined patterns, anything you want. Thanks, partner. Might be really strange. Like the popularity of particular hardware device was correlating with temperature in Zimbabwe. Like, why not? And you will find it Does it means, like with example off sending a prediction that this is actually cause ality off this events. I don't know s Oh, yeah, I was speaking about only these crazy popularity went that by design doesn't exist in the football field. And by the way, interesting Internet.

Zain:   39:35
That one is. Ah, look at that. That that I can I have a much, much less of an objection to that idea that it's the crazy level of popularity. That is the one that's not predictable.

Slava:   39:49
Yeah, and I want to close. This was one particular mental example for you guys. Uh, so the we have human incorrectly calculating probability example is a falling quant. If we think that your fast, random person how how, what are the likelihood that would be one person on course that two times in their own have win? Ah, jackpot on lottery, that multi 1,000,000 jackpot. The thing is that it's likely who looks very, very small. However, if you ask the question slightly differently, A doesn't matter which person, Because for me, Slava, the likelihood of winning double jackpot is infinitely small. But if you calculate how many people helped played, how many lottery exists, the chances that on this purse there is exist some person who done it twice, approximately 30% already, and I will answer this. Yes, such person already exist. So in order to claim that that the event is not random, you always need to know how many monkeys are playing in the game. If you don't know that, you never can claim that this run random and this is part of the problem. If you're saying that we have a successful framework that doing blah without knowing how many people have tried to create successful problem was doing block you might be actually within us. Just just normal distribution. And you have a spike of success. You always need to count this number. So beware. Beware. I want you guys to have 11 non mentality thought when you're reading a book about successful people, always ask yourself how many people don't exactly the same and never got successful. If you don't have that in the book, stop reading it. They just started to spread by storm you and like, uh, all successful people eating pickles. So go in pickle.

Zain:   41:45
Yeah, even though there is this one. A hedge fund, not henchman. Sorry. Venture Capitalist Fund. They were doing the analysis of all the companies that were under them. And, uh, what what attributes successful companies have in common and had to commit one of their out liar cos because otherwise you would have a really successful company. The company started with the letter you had over.

Sandeep:   42:17
That's interesting. Dark. Nobody here. I think none ofus. Three people here is objecting that there is a random now, but I think all of us kind off agree that there is a pattern to take you from 0 to 1. But there is that randomness and various other factors that will take you from 1 200 So still, there is a importance for the pattern to start off. It cannot be like from zero. You start off with the randomness. What is? I think

Slava:   42:54
I actually I actually want to make it the homework for our listeners on and write comments about what you get thinking. Let's let's powers and finish. And these because it's Ah, yeah, I actually have a meeting to go. Okay, so thank you, everyone. And I just want to quickly remind we have two amazing cohorts with me today. It's Zane. Say something by

Zain:   43:21
All right. Hey, guys. Thanks. Goodbye.

Sandeep:   43:24
And Sandy. Thank you, guys. It was fun. Chat with you by design.

Slava:   43:30
Oh, yeah. This annoying voices speaking right now.