소프트웨어 개발 및 비즈니스에 대한 AI의 영향에 대한 토론

### 비즈니스에서 소프트웨어 개발과 AI의 미래: 차마스, 데이비드, 데이비드와의 대화
* 🚀 차마스, 데이비드, 데이비드가 소프트웨어 개발, AI, 비즈니스의 미래에 대해 이야기하며 **소규모 기업이 업계를 혁신할 수 있는 잠재력**을 강조합니다.
* 🧠 Chamath는 고급 도구와 AI 기반 워크플로우를 사용하여 직원들의 생산성을 **100~200% 더 높여야 하는 소규모 팀**에 의해 소프트웨어 스택이 재구축될 것으로 예측합니다.
* 💻 데이비드 프리드버그는 AI에서 LLM(대규모 언어 모델)의 중요성을 강조하지만, **현재 대량의 엔터프라이즈 데이터를 처리하는 데는 한계**가 있다고 지적합니다.
* 🌐 차마스는 기술 솔루션 크라우드소싱을 위한 '웹 3 모델'을 언급하며, 이 새로운 접근 방식의 예로 **Benser라는 프로젝트**를 예로 들었습니다.
* 📈 데이비드 삭스는 **AI가 최소한의 비용으로 실시간 맞춤형 소프트웨어 개발**을 가능하게 함에 따라 기존의 SaaS 모델이 쓸모없어질 수 있다고 말합니다.
* 🃏 이 대화에서는 정신력과 장기적인 인지 건강을 위한 포커 플레이의 이점에 대해 이야기하며, **데이비드 삭스가 자신의 초기 포커 경험에 대한 개인적인 일화**를 공유합니다.
* 🎓 이 트리오는 **노력, 집중력, 친구와 가족을 지원하는 것의 중요성**에 초점을 맞춰 그들이 받은 가장 영향력 있는 조언을 되돌아봅니다.
* 🎂 이 행사는 **데이비드 프리드버그의 깜짝 생일 축하 행사**로 마무리되며, 두 사람의 끈끈한 우정과 전문적인 협업을 강조합니다.

주요 주제는 소프트웨어 회사, AI, 포커, 친구들 간의 진로 조언 등 다양한 주제에 대한 토론입니다.

e [Music], [Music]. Let's go [Music]. Boys, everybody give it up for the dictator himself, Jamal ptia, the Rainman. Yeah, definitely David Sachs and your sultan of science, David Friedberg. I love how it's freezing and there's one heat lamp, one heat. We're all [Laughter]. Just, I mean, these are literally like $80 for the night. Yeah, they cost about 50 bucks a night to rent, so I just thought 250 was enough. Yeah, be fun. No, no, I mean, this is a super expensive place, especially since this is what happens. This is my life. Oh, God. I come in and they're like, Uh, Jal. I'm like, Yeah. It's like, Chad's been here since 4:30. I'm like, Yeah, that's fine. That's great. It's, you know, he got here early. And they're like, He's been ordering on your tab. I'm like, Oh, no. So the event just flipped from being in the black to being in the red. A lot of people had questions for us.

so we thought we would do like a little Q&A, but I thought I would start with maybe asking the besties what has it been like. I think having this podcast get so big and the scrutiny it's under, but the excitement and just how it's affected your life, and maybe how you operate in the world. I think I may have told the story on the Pod, but um, I'll tell it again because I do like the story. So I think I was visiting Chamath in Milan. I think it was either last summer or two years ago. Two years ago, and we were literally just walking down the street in Milan, and somebody comes up to Chamath and stops him. It's like a tourist from Australia who's a fan of the Pod, yeah, and he wants to take selfies. I mean, he definitely, you know, Chamath was definitely his favorite bestie, and it was like this excited conversation, and that all happened, and then he moved on, and Chamath turned to me and said

oh, by the way, just some context here is that these two were in like a big fight, and there's some question about whether the Pod, yeah, whether the Pod would survive. And I think we were just talking about that as this guy came up to us. In any event, so he comes up, takes the selfie, and then leaves. And Cham turns to me and said, These two idiots better figure things out because I like being famous. I'd love to hear you guys talk more about the current state of gen and particular software companies. I know, chat, you got 8090 going. Love to hear about the lower cost of actually engineering software and building companies versus actually geni doing replacing human judgment, replacing judgment, self-driving the software itself, and those two Dimensions feel like they're not exclusive to each other, but they are two different axes. Love to hear kind of current thoughts on the return Potential from an investment standpoint. I think that the entire software stack is going to get rebuilt, and I think it's going to be a

bunch of 10, 20, and 30 person companies that do it. And I think the core artifact of a new company today are two decisions. The first decision is that you must demand that the people that join you use every available tool at their disposal, and you measure them against a counterfactual where that counterfactual is what your productivity was at a traditional company. And you need to be 100 to 200% more productive. So if an engineer is writing, you know, x amount of features or x amount of code, they need to be at 2 or 3x. And if you do that in an existing company, all I've seen is organ rejection. So that's the first decision is so the people that join you, you must expect that they do that, which means that you also have to deprive them of any help along the way, no administrative help, no HR help, no Finance help, all of that stuff needs to be a workflow or a bot or some form of AI logic. So that's one critical.

decision. And I think the second is that the document that matters more than ever is that PRD that defines the v0 MVP of the product, because I don't think you should be writing much code. I think what you really need to be doing is defining, in excruciating detail, what the feature set is, what the parameters are, what the guardrails of how features should behave in certain boundary conditions, fed into an LLM that then spits out the code, that then compiles, and then you have a working product. And that is a 10, 20, 30% effort that can probably topple giants. It'll take a couple of years for us to get to that place, but in that world, there is no room for a $500 million into a SAS company. It doesn't make any sense. And the reason is the 10 and 20 person company can price that thing at just a fraction of what the incumbent charges because the incumbent has an Opex load that's not correlated to features, it's correlated

to the fact that you have 50,000 people across 50 offices all over the world. With all this ridiculous infrastructure that all of a sudden becomes obsoleted. So I think there's two models. One is more of the lightweight approach. So like saaks and jcal both seed a lot of stuff, get it off the ground, spin it up, and then raise money like he just did with glue, which is like I'm going to build something, get it to a place where the rest of us can kind of pile on. But the other version is much more distributed. And I'll say a dirty word here, but I think it matters. Like it's like this web 3 model does actually apply here where there are some really interesting early adventures in crowdsourcing technical completion. I would encourage you to look at a project that I'm starting to focus a little bit on called benser. And I was like, what is this thing? And it's basically a thing where you go and solve technical problems and produce.

features that people require that need and you get paid in this underlying currency that is actually a distributed form of venture that actually makes sense like a bounty essentially. Yeah, we're like you know 15 companies that need a replacement to Salesforce just say here's the Bounty and here's the feature set and it's a crowdsourced or a community sourced PRD and then some LLM spits out the code like that is this crazy new world that we're going to so it's all about speed of execution. I think s you have any thoughts on it and what you're seeing you know in the field right now. Yeah, I mean I I I think in having conversations with Enterprises and businesses what they basically want is to be able to throw all of their data somehow into a LLM and be able to ask you questions so they've seen chat GPT and they basically want to be able to do that but with their own Enterprise data and it sounds easy but it's actually like pretty hard to make that happen one.

problem is that the llms don't have that big. What's called a context window, which is kind of like you could. It's almost like active memory or something like that. And we're in the early days of it's like in the early days of computers where the. You know you had to worry about your Ram was like 8 megab 16 then 32 then 64. Remember that get some we had and 3 and2 in disc or whatever. And eventually just people stopped talking about Ram because it went away as a constraint. Yeah, but we're still in the days of you have to be selective about what you feed into the model because it just can only absorb so much information. So if you give it all of your Enterprise data. How's it even know where to look. And so you've got to figure out how to optimize it so that you can give the. The model the right chunks of data to give you the right answers. And that's actually it's a complicated problem right now. And and uh.

we're dealing with it at glue. We're in. We just invested in a company, a startup called Raggi, which is basically RAG as a service, do retrieval augment and generation as a as a service. It's basically helps solve this problem. So, I think that that's kind of the stage that we're at is everyone kind of knows where they want to get to and we're just dealing with some of the limitations so that the model can work, you know, effectively. And you know what you see right now are like glimpses of, you know, genius or greatness. Like if you feed the exact right chunks into the model, you'll get like answers that can blow you away. But then sometimes you'll just get an answer that just kind of isn't that good. And again, the reason is because the model didn't really know where to look for the answer. So, you know, right now it's like again glimpses of something amazing and we just have to kind of get to more predictability around that. And there's a lot effort.

that's going into solving some of these sorts of issues. It's not just llms. It's also, yeah, although it is at the llm level. It's also the infrastructure around it, you know, and to put the two thoughts together, I think the people who embrace this are becoming bionic at work. I mean, we had many challenges in podcast production around things like transcripts or doing show notes and learning um, hey, about this person who's a guest. Um, they were on these three podcasts. Now we have producers at our company who will take those three podcast interviews, download the MP3, put them into, you know, a chat GPT, and say, what are the key points in here? What are the key timestamps, and even what questions would you ask or what are relevant topics this person's talking about, and these data sets are disparate and they're not connected so you can't say, well, what's David saaks talking about if you're going to have them on your podcast on Twitter because there's no way to get that information um.

could tell you what the topics are. It's pretty anyway um and and those individuals are becoming so valuable in organizations. And it's allowing people to do so much work so fast and then unlocking things that were just not possible. And that to me is very obvious inside the startups we invest in because when they're resource constrained, they look for the fastest, cheapest way to do things. And if you watch those startups, they're the same ones who when other people were racking servers, they were using AWS, they were using cloud computing, and they figured it out first. And then they built businesses that you may have heard of like Dropbox, YouTube. That whole wave was a group of people who just fundamentally said that the paradigm of cloud computing is going to work even though it's not perfect right now, even though it's slow or expensive or breaks, whatever. I'm just going to go all in on that. And Dropbox made this critical error. I don't know if you remember that Sachs where they stood up their own data centers instead of you.

know, they were just scared to have their data at, I guess, AWS or whatever was, and so it's going to be unbelievable how many businesses become viable with just three, four, five employees, and that's the, that's what I'm seeing on the field, Freeberg, any that's on AI right now. Uh, I just, I think that there's a chance that SAS gets kind of obviated. I've shared this in the past. I think that there's a chance that SAS looks like this kind of temporary phenomenon that occurred between the ubiquity of the internet and the prevalence of AI for writing software. If, if you've worked with any Enterprise non-traditional Enterprise from a traditional industry, meaning they didn't grow up in software and they're not software native, they have IT departments, and those IT departments are really good at procurement of software, and that's really been their primary function, but they all try to hire software engineers, and they generally suck, and but they understand the needs of the business, and I think that if they can have software written for them at a

basically a cost of zero to improve their workplace productivity. Which was the original thing that was enabled software in the first place. It starts to really change how folks are sourcing and using software. That it can actually be written for them in real time by software. And so, I think that the tooling and the capabilities to enable the Enterprise to write their own custom workplace productivity tools. And their own custom workplace software. Whether that's customer facing or internal facing really becomes kind of the standard maybe going forward. And you know you see this what I think Doug Leone called the greatest business model in human history. Which is SAS getting kind of blown up in that new landscape. So, I think there's a chance that that happens non-zero chance. And I've just seen this in in a bunch of settings where folks are having software written for them by the software. And they kind of just really state clearly here's the layout here's what I wanted to do. And with a couple of rounds of iteration they can get it working pretty well.

they don't need to go pay some third party of per seat license fee per year to use it. I have heard about your poker love through the podcast I've been listening for a few years, and it was really fun to experience it with you last night. Could you comment a little bit on like how you think about your utility function personally? Is it networking, strategy, training, is it fun? Like, could you comment a little bit on how you all think why we play poker? There is networking that has occurred at it, but I think also, you know, you made a good comment about it, or maybe Bobby Baldwin said it. He never saw or was, you know, a poker player like get old and lose their mental facilities, right? Like they, Bobby Baldwin ran the city center in Aria for a long time. He plays in our game, and he made this comment. He's like, have you ever seen a poker player get Alzheimer's or dementia, right? He was saying that about Doyle Brunson 'cause Doyle, when he died, was super sharp, sharp as a tack.

body failed before his mind filled. Yeah, and it's true. It's like it's one of these unique games where you can really stay mentally sharp as you get old. Yeah, absolutely. Saaks, you still love it? Yeah, definitely. Yeah, look, I like it for the same reason that you guys like it. There was a phase early on where like I would play in the World Series of Poker. I would like go to that, and then I was just like, you know, I actually don't like sitting there for three days playing with strangers. It's actually not that fun to do that, and the thing that's fun is just playing with your friends. So now I just play in friend games. I first started playing poker when I did. I ever tell you this? I worked at a pool hall in Upstate New York. I was 16 years old. I got paid 425 an hour to work at this pool hall. I like clean toilets and scrub down the tables, and the guy sat at the pay phone all day was the bookie for

Upstate New York, and he would take all his the bets on the pay phone and write him down. And one day, like after he got to know me for a couple months, he's like, Come and play poker with us at our home game. And they played limit hold him like one two 50 Cent $1 one two, and these took all my money. And I was 16 going to college like cold. I had to walk through the snow. I couldn't afford boots or a jacket. It was like really shitty, and they took all my money. Yeah, and I had to call my mom, and I lied to her, and I'm like, Mom, I lost my jacket. Can you like loan me 150 bucks Western Union it so I can buy a jacket? So that summer, I bought all the books in the from the back of the poker magazines to learn how to play poker strategy. And it was all limit hold him at that time. And then my freshman year of college at Cal, I made 10 grand that summer playing limit Holden at the Oaks Card Club.

playing tournaments in 612, and after that, I was and I learned so much about investing and life and like perseverance through ups and downs because you sit there, you grind it out as long as you have a positive EV decision, you know you made the right decision over time. The money will come to you. You don't need to like win every hand, and to learn that at that age, I think was really influential to me in entrepreneurship and investing and in decision-making later on in life. It was very important to me. So when I sold my company in 2013, I was introduced to Cham and invited to come to the pl in the home game. For me, it was like a very kind of nostalgic because I hadn't played really much since 2001, 2002. What's the most impactful advice you've been given and how's it shaped your careers early on? I got two good pieces of advice. One was from Mike Savino, who's here somewhere speaking tomorrow. There it is um, and he said uh, the piece of

advice his dad gave him was look to the left and come in an hour before that guy, and then look to the right and come in an hour later than that guy, just basically the hard work stuff. And I had gotten that from my mom as well, who worked three or four jobs to put us through school, and my dad who worked really hard. And so the hard work ethic I think was the key to a lot of My Success because I just decided I'm just going to outwork everybody because I was coming not from Harvard or Stamford but from Bay Ridge Brooklyn, and you know going to night school at forom so I I had to use hustle and there was no connections there was no network. I just had to literally kill what I ate. And then after I sold my first company, I was at Ted at the Billionaire's dinner with my book agent John Brockman and uh I had still had a chip on my shoulder but I had sold my company and he uh said hey schmock you you made it stop fighting.

with everybody. And I was like, okay, I'll stop fighting with everybody. Uh, I still, you took that advice. I took it. Sometimes I flip a coin. When did you do that? Um, not get that memo. When did you get that advice last night or, yeah, I just got it. You're just texting me right now. Um, but it was actually because I had to fight for everything. I think I just kept fighting to try to get to the next, you know, level. And you know, at a certain point, I decided I'd be like super magnanimous and just be helpful and Elder Statesman like, um, and it's, I'm not perfect, but you know what? Well, I mean, when you don't see me working, you don't see me working with startups, you're, you know, like I am tireless in my ability with patience for them and supportive. And I just, and I try to do that with my friends as well. Is just, you know, what's the point of being successful if you can't support the people around you who you love and try.

to pay for it. So those are just, you are like the most reliable wingman of all of us. Oh, thank you. You know, it value your friends and your family is like just such critically important advice because at the end of the day, all you have is your memories and you make them with your friends and your family. And so I am on a mission to make great memories with my friends and family, as many as possible. And actually, this is part of it. Like you all being here and just that's why I always tell you like make a couple of friends. It's like it's hard to make friends, especially as you get older, and people kind of tighten up their circles. Like make a couple of new friends, you know, and go do things together. Anyway, some philosophy. I don't know advice that you got the best advice. Career advice I got was from Peter Thiel who advised me not to go to law school, and unfortunately, I didn't listen to him. I went anyway, but it ended up not mattering.

because I ended up joining PayPal, uh, after I graduated from law school. So I wish I had a better story. The best career advice I've actually heard for Silicon Valley was the advice that Eric Schmidt gave Cheryl Sandberg when she joined Google, which is, When you get invited to take a seat on a rocket ship, don't ask for a seat, just get on board. I actually think that is perennially great advice for anyone in Silicon Valley. You know, there aren't that many of these rocket ships, so when you get a chance to be on one, you should just take it and worry about the titles and all that kind of stuff later, yeah, the details later. I think like the biggest piece of advice that I still struggle to take every day, every time I have, though it's had a profound impact on my life, is to focus. Um, I think the bigger a portfolio you develop, the less Alpha there is. You try and minimize beta, but you take all the alpha away if you do that. In 2009, I

focused my company on the agriculture market, which was crazy. We were in like seven verticals and doing all sorts of stuff. When I focused on EG, and I went deep, and I like went on a long hike in Iceland, and I like came up with this crazy idea for the product for the ACT market. And I came back, we launched it, and we did like 30 million in sales that year, and that made a huge impact in my life, and the trajectory of the business changed. And every time I focused and avoided distractions, it's made a huge impact. I think my decision to become a CEO again back in November was a really important one for me, and I realized I was on lots of boards and doing lot L of investing and thinking about LS of things. But now I can really dig deep, and I think that everyone assumes that there's this power law in the world, that you are a passive participant in. You're either going to catch one of the power law winners, or you're going to lose it. Therefore, you've got a portfolio your

way to a power law to catch a power law. I don't give a about that because I think my job in life is to make the power law and to make that outcome. And I feel like that has made a huge impact on how I think about life. And it's really um every time I've tried to act on it, it's it's actually paid back significantly. So focus is the biggest piece of advice I've gotten that I think matters. So the version of that that I tell Founders all the time is always be all in on your best idea because Founders have a whole bunch of different ideas. Sometimes they're doing multiple startups, sometimes they're thinking about pivoting, but they're still hanging on to the old idea. And I always give them permission to Pivot. I'm like, don't worry about what you said you're going to do whatever two quarters ago and you raised this money justes whatever you think the best idea is right now like let's go all in on that. Do not hedge your bets. I think

that's just really important for Founders, and it goes back to what you're saying. It's just so hard to execute any idea that you can't be hedged as a Founder. Seven Samurai, yeah Akira Kurasawa did such an amazing job representing this ethos. I think like you strike, and you strike perfectly, and you strike with full force and with all your energy and everything you have, your whole character, everything, and you can accomplish incredible things. You have to put one foot in front of the other every day, and you have to focus on tangible progress. And where that fails is when most people, and I do it a lot, and I've tried to get better as I've gotten older, is when I get comparative and I compare myself to the other person, the other company, the other funding round. There's so many reasons for you to feel like you're less than something else, and the reality is that has nothing to do with you. You're not in control of that, but it's so hard. And then if I

don't take that medicine. I become insecure, and then I make mistakes that are entirely avoidable. So it's just tangible progress, the things that I can control. That's probably the most useful piece of advice that I try to remind myself of every day. And then I kind of have these two jobs. One is I'll incubate companies from time to time if I get intellectually curious enough, but the other part is just as an investor. And the best piece of advice I got as an investor is you are a big Wave Rider, and the swells that become ginormous are not visible when you paddle into them. And so you got to commit, and you got to go, and you are going to have less than 100% hit rate, and you will get massively washed out, and you just got to get to the surface and swim back up. And as an investor, that's been helpful because I've had some huge wins, but I've also had some huge losses and some total embarrassments and flameouts, and it's

the totality of that that allows me to swim back out. So those are two different things, but the entrepreneurial one and the life one is more valuable because so easy to get distracted and feel insecure because of what somebody else is doing, and it always ends up screwing me up. I think that's a good note to end on. Give it up for my besties and we're going to take a little walk over here for a little surprise. If I could have my four besties follow me over. [Music] Here, I'm going to walk over here because it's a very special day or a special time of the year. It's the Sultan of Science's birthday again, so come on around, and we got him a beautiful cake and then a tiny little vegan cake, and we're all going to sing the Sultan happy birthday. 3, 2, 1. Happy Birthday to you, happy Birthday to happy birthday dear D, happy birthday to you. We love you Freir. [Music] N [Music]

The Besties Take Napa | All-In Special

Chamath Palihapitiya, Jason Calacanis, David Sacks & David Friedberg cover all things economic, tech, political, social & poker.

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All-In Podcast

자말 프티아와 그의 친구들은 매우 비싼 레스토랑에 갔는데, 한 사람이 자말의 계산대로 주문해 이벤트가 적자가 났습니다.

이 팟캐스트는 큰 싸움이 벌어지는 와중에도 팬들이 차마스에게 다가오는 등 큰 인기를 얻으며 쇼의 영향력을 보여줬습니다.

토론은 소프트웨어 회사의 현재 상태로 옮겨가며, 수익 잠재력과 업계에 새로 진입한 회사의 주요 결정에 중점을 둡니다.

PRD는 제품의 MVP를 정의하고 세부 기능 세트 및 매개 변수를 통해 개발 프로세스를 안내하는 데 매우 중요합니다.

제품 개발에 대한 보다 가벼운 접근 방식과 크라우드소싱 기술 솔루션이 포함된 웹 3.

0 모델의 잠재력에 대한 필요성이 점점 더 커지고 있습니다.

기업들은 컨텍스트 윈도우의 제한으로 인해 데이터 분석에 LLM을 활용하는 데 어려움을 겪고 있으며, 정확한 결과를 위해 데이터 입력의 최적화가 필요합니다.

서비스형 걸레를 제공하는 스타트업, Raggi의 영향력

검색 증강 및 서비스형 생성을 제공하는 스타트업인 Raggi는 현재 모델 효과의 한계에 직면해 있습니다.

모델의 예측 가능성과 신뢰성을 개선하기 위한 노력을 기울이고 있으며, 주변 인프라에 중점을 두고 있습니다.

이러한 기술의 도입은 개인을 조직의 소중한 자산으로 변화시켜 신속한 업무 처리를 가능하게 하고 새로운 가능성을 열어주고 있습니다.

소프트웨어 개발에 대한 AI의 잠재적 영향

연사는 AI가 널리 보급됨에 따라 기존의 서비스형 소프트웨어(SaaS)가 쓸모없어질 가능성이 있다고 생각합니다.

이제 전통적인 기업이 아닌 기업도 거의 또는 전혀 비용 부담 없이 실시간으로 맞춤형 소프트웨어를 개발할 수 있게 되어 향후 소프트웨어의 소싱 및 사용 방식이 바뀔 가능성이 있습니다.

연사는 또한 AI 기반 소프트웨어 개발이 표준이 되어 현재의 SaaS 비즈니스 모델을 혼란에 빠뜨릴 수 있다고 언급합니다.

포커는 정신을 가다듬는 데 도움이 되었고 인내와 의사결정에 대한 귀중한 교훈을 주었습니다.

어린 나이부터 시작한 포커는 투자와 인생에 대해 가르쳐주었고, 궁극적으로 그의 커리어에 영향을 미쳤습니다.

게임을 잠시 중단했지만 포커에서 배운 교훈은 계속해서 큰 영향을 미쳤고, 기업가 정신과 투자에 대한 그의 접근 방식을 형성했습니다.

연사의 부모님으로부터 받은 노력과 근면함의 중요성에 대한 조언은 비주류 출신인 그의 성공에 결정적인 영향을 미쳤습니다.

처음에는 어깨에 힘이 들었지만, 첫 회사를 매각하면서 그는 싸움을 멈추고 다른 사람들을 더 많이 지원해야 할 필요성을 깨달았습니다.

연사는 친구와 가족을 지원하는 것의 가치와 그들과 함께 추억을 만드는 것의 중요성을 강조하며 자신이 받은 조언의 영향력을 강조합니다.

실리콘밸리에서 성공하는 기업에 주저 없이 입사하는 것이 중요한 커리어 조언이라고 PayPal 졸업생이 말합니다.

하나의 아이디어나 틈새 시장에 집중하는 것의 효과는 연사에게 큰 영향을 미쳤으며, 이는 매출의 상당한 증가로 이어졌습니다.

수동적으로 따라가는 것이 아니라 자신만의 '힘의 법칙'을 만들어야 한다는 연사의 신념은 삶과 비즈니스에 대한 접근 방식을 형성했습니다.

창업자로서 집중력 유지의 중요성

집중력을 유지하고 다른 사람과의 비교를 피하는 것은 창업자의 성공을 위해 매우 중요합니다.

가시적인 성과와 통제할 수 있는 것에 집중하는 것이 창업가에게 가장 유용한 조언입니다.

투자자로서 파도를 타고 손실을 극복할 수 있는 능력은 장기적인 성공의 열쇠입니다.