Software’s Epic Comeback, Meta’s AI Layoffs Blunder, South Korea Stock Market Chaos

18:48Big Technology Podcast:So, you know, one of the interesting and obviously not investment advice, but one of the interesting things that, you know, you'll be able to see in this moment is like, man, there's just going to be this like volatility and investors running one way and then, you know, because of some headlines and then running right back because of some earnings. And, you know, there's real opportunity there.

19:09Ranjan Roy:Has anyone who ever said not investment advice not followed up with investment advice in the history of podcasting

19:20i think like you have to you know you have to caveat it because if you're like you don't want

19:27Big Technology Podcast:you don't want people i i get it i get it but you just don't you don't want people trading off of the off of these you know observations um like trade based off of what your financial advisor tells you to do. I don't know. I think it's a worthwhile caveat. Any time. Not to be racist, but...

19:47Ranjan Roy:Not to give investment advice, but... I'm just giving you a...

19:51Big Technology Podcast:I'm moving on. I'm moving on. I'm moving on. Well, Ronjun, just because... Go ahead.

20:01Ranjan Roy:No, no, I... Bash me. No, no, I think... What are you supposed to say?

20:05Big Technology Podcast:You're supposed to say trade on it so the listeners come and they trade on it And then when it doesn't go right, they sue you. Like, no, you don't, you need to, you need to give like the appropriate context here.

20:14Ranjan Roy:Well, it's funny though, because I would say even that caveat, so much of like you watch the All In podcast or whatever else, like, I mean, there's just so much investment advice that is just given in any kind of conversation nowadays that I do. Okay, you know what? I appreciate the caveat. We don't want our listeners, as we'll get into the South Korea trading stories at the end of this podcast, ending up in any of these kind of situations.

20:46Big Technology Podcast:All right, pro caveat. So are you going to, after hearing me talk, are you going to go buy IGV? I was already, Robin Hood's already open.

20:58Ranjan Roy:It's already done. Just because you said it, Alex. I hold you responsible.

21:03Big Technology Podcast:Okay, because I was going to say, you're too late. The bounce already happened, but okay. That's more investment advice. The opportunity window has closed. That's more investment advice. You are done. You're going to get this show shut down because some lawyer is going to replay this and be like, well, my client is now in shambles after shorting and then longing IGV after hearing.

21:26Ranjan Roy:Well, actually, to bring it back to read it.

21:28Big Technology Podcast:August 28th episode.

21:29Ranjan Roy:to kind of, I think, wrap this. How much do you think Salesforce stock is up from the beginning of the year?

21:38Big Technology Podcast:Oh, okay. I thought you were going to ask me to predict something. I was like - No, no, no, no, no. Okay, what do you put it? Maybe 3%, maybe.

21:45Ranjan Roy:It's down 1.94%. It's almost flat. So it's fascinating. Again, in terms of thinking back through this year and this story, it is kind of a perfect round trip of software is dead, a clod code hype back in like February, March, April, vibe code your CRM and now back to, no one knows what's going to happen and we're back to flat for the year.

22:11Big Technology Podcast:No, I mean, I think that you could have your convictions in terms of where it's going to go. You just have to realize that it's not going to happen overnight. And that's like the case in point for our next story, which is that Meta had a very aggressive plan to trim its workforce. and transform its workforce based off of the capabilities of AI, only to learn a very difficult lesson, which is that it wasn't ready yet. Let's get into the story. This is from Reuters. Mark Zuckerberg had a bold plan to replace MetaStaff with AI. Here's how it imploded. In January, Meta CEO Mark Zuckerberg and his top lieutenants gathered for their annual leadership retreat at his Hawaii compound.

22:49Big Technology Podcast:There, they hatched a radical plan to reimagine work at the social media giant in the age of AI. Codename Project OT, short for Organizational Transformation. The planet envisioned an AI-native future for the future owner of Facebook and Instagram. Okay, that's such a weirdly phrased thing. For the owner, okay, of Facebook and Instagram. Gosh, anyway, dear Reuters. Okay, let me just go through this. AI would take over much of the daily work performed by thousands of human employees. Virtual workers would be overseen inside meta by smaller, talent-dense cadres of human staffers. And then in scenario planning exercise, two of these people said executive explored slashing the size of many teams across meta by as much as 60%.

23:36Big Technology Podcast:Sorry, a lot of reading here, but I feel like it's worth going through a little bit about what happened within there. So basically what they did was they set up this pilot, which had five, they had small tech pods, each consisting of two to three engineers and a designer, all equipped with AI tools. The groups would dispense with established processes for releasing new products, such as a fixed six-month planning cycle. Instead, they would aim to build prototypes in four-week sprints. The layers of middle management that would traditionally be there would be eliminated. Instead, the pods would report up to a single high-level unit head.

24:11Big Technology Podcast:Agent-assisted analysis would help set the day-to-day priorities. All right, Rajan, how do you think this went?

24:18Ranjan Roy:okay before i mean i think we were we can all guess how it went but okay the funny thing is like as you actually i'm glad you read that out in its entirety because it's like in theory or not even like that is a good idea to me that i mean if you separate it from the layoffs and all the other kind of organizational questions, like this is to me exactly what companies should be testing and doing and figuring out what the new operating model is and that teams should look different. So I honestly think any, as we get into, if it worked out, any indication of failure is solely attributed to the worst code name for a project ever, project OT, short for organization transformation like come on guys if you gave it some even spud would have been okay on this one but if uh if you gave it a good code name maybe this would have worked but project sounds like worse than mckinsey you know when the word from on high came on that project ot was happening do you know how it was announced to employees how one meta employee ran into the break room and said, by golly, pause everything.

25:40Big Technology Podcast:Project OT is here.

25:43Ranjan Roy:I don't know if that gets a by golly. I was thinking about it all week of when to save the by gollies for. I think we need another Leopold for another by golly. Salesforce up 22 % in a day might get one, but.

25:59Big Technology Podcast:No, no. Salesforce doesn't get a by golly. Let's be honest. In the rules of by golly, Salesforce doesn't get it.

26:05Ranjan Roy:Okay, but let's... The by golly bylaws. By golly bylaws. It's got to be a bigger...

26:10Big Technology Podcast:It has to be a trillion market cap or higher.

26:13Ranjan Roy:Yeah.

26:15Big Technology Podcast:We have rules here. We have standards. But let's talk about this, though, because it is interesting, right? Because, like, obviously they were influenced by the fact that smaller companies were able to operate faster with AI, right? They've probably been influenced by the narratives that, like, you could have a one person,$1 billion company. They've seen companies cut and be successful. I'm sure what Elon Musk did to X probably was in their minds, although who knows if that's a success or not. Probably not, actually, now that we think about it. And they also went to Asia, where things are much more advanced, places like Singapore.

26:47Big Technology Podcast:Okay, but what they found was that you can try to make your organization as AI forward as you want right now. The capabilities aren't there, right? So they're just starting to be there. Here's the part where the rubber met the road. Internal data indicated, this is so interesting, by the way, and I'm surprised that this story didn't get more play this week. Okay, here's what it says. Internal data indicated that the tech at the heart of the plan wasn't delivering. Employees' use of AI had resulted in a vast increase in the code they generated, but with questionable impact on productivity. For instance, code changes made to the internal software platforms and infrastructure employees use on the job were up 220 % year over year.

27:32Big Technology Podcast:But changes that led to new or upgraded features reaching meta users were only up 36%. Infrastructure teams were also warning of reliability warning signs caused by the AI coding search. In April, they said, unchecked agents were performing large-scale disruptive actions that humans are unlikely to execute. The result, major technical and security incidents, such as service disruptions and possible data leaks, spiked 40 % from the previous year. And the time staffers spent firefighting them went up 70%, according to internal posts. Okay, this is like the holy grail or the epitome of all the criticisms of AI.

28:15Big Technology Podcast:You write more code. You're not necessarily more productive. You ship more. And when you ship more, you have bigger security flaws. And when those security flaws hit, you have to spend more time cleaning up after them than you would previously. And then the whole thing basically didn't work. Even Zuckerberg basically admitted that AI agent technology isn't at the point that he expected it. So what do you think about this, Ranjan?

28:39Ranjan Roy:I think employee incentive is kind of like what's probably at fault here. Because I'm guessing given the timeline, this would be exactly when just use more and more AI as opposed to what is your actual end goal and then let them use AI in a much more lean team without middle layers of management. Again, the way you've read out that first part around what an AI native team could look like still makes a ton of sense to me. But if you tell people you're going to be judged on how fast you move, how many tokens you consume, how much AI you do and use, of course you're going to end up in those kinds of situations versus what is the actual task you're trying to do or project you're trying to execute on and you do whatever you have to do to get there and we're going to eliminate all the middle layers of management.

29:39Right.

29:39Big Technology Podcast:And this kind of goes to the theme that we've been talking about really throughout this episode, which is that like the capabilities can be there, but to think that it's just like a straight shot to like exponential growth or to this being implemented perfectly is somewhat foolish. Like these type of bumps in the road are going to happen for everybody. So there's going to be moments where like, they'll be like, all right, well, AI, you know, isn't working. It's not there. And in some cases, it really won't be there. But in some cases, it will be there. It's just that the human side of things takes a long time to get right.

30:13Ranjan Roy:No, completely agreed. I also, I mean, speaking of the human side of things, it is fascinating to me. How do you think that level of CEO, whether it's Zuckerberg or others, like think about their employees and their teams like they're i see like numbers well no but but even if it was numbers like i don't know like so much of the communication or even the way this reporting shows these kind of decisions being made like ce these are the ceos who chose the like hiring and growth trajectories of these companies since covid i mean these companies have always has been pretty heavy in terms of overall employment relative to the actual cash generating parts of the business, whether it's Google or Meta.

31:05Ranjan Roy:But I don't know, I still wish one of these CEOs would stand up and be like, I hired too many people, we are too bureaucratic, I am a founder, I am Mark Zuckerberg, and I know how to run lean and fast businesses, and we are not that today, And we will be. And actually, sorry, he did that. That was a whole year of efficiency.

31:28Big Technology Podcast:I feel like they've all done it. Elon Musk has done it, too.

31:31Ranjan Roy:I know. I know. But his always feels a bit more performative. When Zuck says it, I believe it. I believe it. And he did his year of efficiency. But where? Shouldn't it have already happened by now?

31:45Big Technology Podcast:That was before AI. And they did lay off a lot of people there, right, at the expense of morale in some cases. But yeah, I mean, they're trying again, but it just isn't working. And in fact, this is the end of the story, right? So basically, they had a 10 % cut. They went ahead with it, but they had a bigger cut that they were planned that was supposed to go on in November, and Zuckerberg called it off. He said that employees should not expect other company-wide layoffs this year, and he expressed desire to give them stability. He did also say in a recording that Reuters was able to get from his remarks to the company that like you have two main expenses.

32:24Big Technology Podcast:One is compute. And the other is, I think he called it people related stuff, which is kind of like your salaries. And he said, when our compute expense goes up, the other part has to go down. So I think that's like kind of what he's thinking about. But I think it's fair to say that the tech environment in 2026, you know, even if you made your cuts in 2022 is a completely different world than it was in 2022. to.

32:50Ranjan Roy:Okay, fair point on that, agreed on that. Do you think meta needs to lay off, like that argument that as compute expenses go up, we're going to have to find savings somewhere else that's going to be people, do you think that's the right approach and the right belief?

33:09Big Technology Podcast:I mean, if your people are good, then no, I think it's the wrong approach. I mean, also, like, I don't know, I might get sort of some criticism for saying this, but I always find it a little bit uh rich when a ultra profitable publicly traded 1.5 trillion dollar company with massive margins is like we need to find cost savings i mean i guess like if you if you you know obviously it's important to perform for wall street but um but i i don't know i i it's it's sort of rich to me that like a company that's like yeah spending billions of dollars for AI talent and billions more on compute won't spend some portion of that type of expense on people, especially if it thinks the people are good.

33:55Big Technology Podcast:The only reason you don't do that is if you don't think the people are good.

33:58Ranjan Roy:Yes, but I think that's implicit in that because when you're willing to spend, what did they pay for Alexander Wang again?

34:06Big Technology Podcast:I think 14 bill.

34:07Ranjan Roy:Yeah.

34:08Big Technology Podcast:14, 15 bill.

34:08Ranjan Roy:Clearly, he believes that if people are good, he will open his wallet. So I agree. I think that's implicit in any of these kind of decisions and Project OT.

34:23Big Technology Podcast:Okay, let's quickly talk about this meta settlement because you brought it up in our document and I think it's worth talking about. In its most recent earnings call, Meta said that one of the big liabilities for this company is going to be that it is now exposed to all forms of lawsuits about its addictive, the addictive nature of its products and what it's been doing to kids. Well, Meta was in court with a bunch of U.S. states about this issue. Exactly. So there's the private citizen examples, and then there's also the states. And it just agreed to settle a suit that was asking for hundreds of billions of dollars for$18 billion.

35:01Big Technology Podcast:Let me read it quickly from Reuters. Meta agrees to pay$18 billion to settle U.S. lawsuits over children's social media addiction. And it's going to pay it over the next decade and strictly limit how teenagers use Facebook and Instagram under an agreement with nearly all U.S. states to resolve claims it designed those social media platforms to addict children. The settlements announced on Wednesday and a federal trial over allegations Metis Products harmed children and the company misled the public about their safety. They were seeking$200 billion in civil penalties. They got 18. Is it over? I'm curious to hear your perspective.

35:39Big Technology Podcast:Is it over or are we going to continue to see these type of judgments against meta over time? All right.

35:45Ranjan Roy:I'll get into is it over in just a moment, but I am very excited by this news. The reason being that how to fix social media is something I've written about and thought about for a long time. I'm excited because in August 2nd, 2019, I'd written a piece for the margins five point plan to fix social media. And two of the things that I've been shouting about for years now are one to demetricate, to remove like counts and actually the numbers that kind of drive people towards obsessing over their performance, especially for just everyday people, if you're not a brand. And one of the settlement part of requirements, the settlement was to turn off like counts by default for miners.

36:32Ranjan Roy:The other, this is my favorite, like, I honestly think all feeds should just be reverse chronological order. No algorithm. And I think like the way TikTok just destroyed this. I wrote this in 2019. Like TikTok came along and just said, not only are we not going to just add some algorithmic logic to how posts get shown, we're going to do away with the feed. It's just going to be one big algorithmic injection of content into your veins. So another part of the settlement is that this will at least give teens the ability to use a non-algorithmic or chronological feed. I still think that should be the default for everyone.

37:14Ranjan Roy:I still use Twitter slash X with the following feed more than the For You feed. But I was excited here to see that at least some of these ideas are getting put into practice. I think there's a lot of others. There's a default two hour per day usage limit on users under a teen. They can't use it from midnight to 6 a.m. No notifications during school hours. So I think like specifically for teens, I think there's a lot of good things here, but I honestly think this should apply to everyone, not just teens.

37:51Big Technology Podcast:Oh, that's a very interesting. I mean, that will never go forward. But as a parent. But I should. Do you feel better having a kid in the world with this type of these type of restrictions? It seems like it seems great news. Now, part of it is on the parents, but part of it's on the technology companies. And I think this is helpful for parents. What do you think?

38:09Ranjan Roy:No, no. I as a parent of a seven year old child, I'm hoping we kind of solve some of this by the time he's like 13 and 14 getting a phone. I am hoping this stuff gets solved a bit more. um and i don't think like putting the responsibility on the parents i think it certainly matters but especially for teenagers like of high school age the idea if everyone is obsessed with this the idea of going into school and like restricting it while everyone is just kind of like looking at each other's like counts and seeing what the most popular kid i mean how do you fight? That's the technology. That's the tool that was designed to do that.

38:53Ranjan Roy:To me, the crazy part of all this is like, this is by definition what Instagram is designed to do. Like that's, I mean, that's from a business perspective, from a product perspective, which to argue against that is crazy. So I don't know. I think overall, this is the right direction. I mean, why Meta is doing this? I think I have a bit of a theory around, but I at least am glad it's the right direction.

39:19Big Technology Podcast:Hit me with the theory.

39:21Ranjan Roy:Yeah. I mean, so one of the other things that came out was apparently there was conversation that they would be willing to move down to a one hour per day limit if TikTok and YouTube were to follow. My read on this is Meta knows as a business, like it's already in the whole AI game, there's a lot of different opportunities there. They know that they like in terms of diversifying, they have a lot and maybe teens, especially from an advertising perspective, there's already a lot of protections around that, even if teens are just addicted to using it. So from a business perspective, maybe you can limit the damage.

40:01Ranjan Roy:But YouTube and TikTok is much younger skewing. YouTube, my God is like everyone pretends it's not an algorithmic social network, but in reality, it's the same dynamics that addict YouTube from, I mean, I'll say that like I have to, I actually like my son, I will put on a YouTube video and like the one rule is you cannot hit any of the recommended right rail videos and whether he always follows that or not is up for debate. But like, to me, that's like step one of rabbit hole. Suddenly he's like alt right or a flatter thing or whatever it is, just 12 videos later. But I think this was just a straight shot at TikTok and YouTube.

40:49Big Technology Podcast:He's telling people that they shouldn't follow his investment advice right before recommending a stock.

40:55Ranjan Roy:No, no, no. He actually, when he's talking trading tips and his Robinhood account on YouTube. He means it. He's saying, follow me, put your money where my mouth is. He's not etching at all. He's not etching. The seven-year-olds don't do that. They know what they're doing.

41:13Big Technology Podcast:They're a little more honest about it. He's triple effort on SK Hynek's and he's going all the way. Oh, we laugh. We laugh. I respect that.

41:24Ranjan Roy:Yeah, but do you think they're going after TikTok and YouTube here, especially YouTube to me?

41:30Big Technology Podcast:Yeah, I mean, they know. everybody it's amazing how how YouTube has become this this force that's eating into everything eating into cable TV eating into Netflix of course eating into the social networks and I would even go further and say there's no such thing as social networks anymore in this world that you're hoping for where there's no reverse chronological order or there's no there's no algorithmic feed it's long past the point in time where that was even a possibility and I think that you know Social media was a moment, but it's now just all entertainment. Meta knows that. TikTok knows it.

42:04Big Technology Podcast:YouTube knows it. And they're all competing on the same product, which is effectively shorts.

42:08Ranjan Roy:Actually, I'm curious. I was talking about this with my wife this week, actually, because in terms of using Instagram, none of my friends post. Like middle-aged males. No one's really posting anything. So the entire feed is like entertainment. There's a lot of good stuff in there. I forget that like out of my wife's friend group, a lot of people are still posting their families, trips, kids, everyday life. And so like actually her feed is still, there is a social network element where my feed it's zero.

42:50Big Technology Podcast:What about for you? Well, I think the stories are certainly posts from people, But I would also argue that, you know, even if she's posting and even if some of her friends are posting, the amount of time that you spend on your friends and family content, you know, to use some meta terms, I would be stunned if it was if it was more than 10 percent of your total Instagram.

43:12Ranjan Roy:Yeah. And I could see it because actually you would just run out like even with people posting. Yeah.

43:17Big Technology Podcast:Right. Exactly. Some of those are brands, but more so like the whole experience, I think, is just to get you in that Reels feed.

43:24Ranjan Roy:Yeah. Social network is dead. shorts are shorts are where it's at even on youtube do you watch when you open youtube are you yes are you short sing or are you uh uh horizontal videoing i'm watching horizontal

43:39Big Technology Podcast:video but my shorts feed is kind of kind of broken on youtube it's like they must know that like i'm like uh you know i i have an account an active account on youtube and i'm posting there because like it's like every short that i get is like use this sound to get a million views oh yeah yeah

43:55Ranjan Roy:Yeah, yeah, yeah. You're in Hustle Bro, like, content creator land.

43:58Big Technology Podcast:I wish I was in Hustle Bro content creator. I'm in this, like, terrible rabbit hole of, like, the worst bottom-of-the-barrel content with the same song and the same title on each one of them. Okay. I would happily sign up for a full day long of Gary Vee shorts compared to this. Oh, my God. I would.

44:16Ranjan Roy:Never. I would. The words have been uttered before, but you just said it.

44:20Big Technology Podcast:I like them.

44:21Ranjan Roy:I actually feel like watching a horizontal video on YouTube kind of feels like listening to music on vinyl. There's just something classic about it. 20 minutes. It feels good. It's nourishing. It's nourishing. It's just that's old school. Yeah. I'm getting caught in the shorts feed a little bit, I'll say. My Shorts Feed is a good mix of cooking content, music, some video editing stuff. But overall, it's reasonable.

44:54Big Technology Podcast:I got to find some way to get you on my Shorts Feed for like an hour to reset my algorithm to Ron John content. So I'm out of this terrible, terrible rabbit hole I'm in. Okay, we need to take a break. We have to take a break and we have to come back and talk about a topic that we've addressed on the show. but we haven't gone into the depth that it deserves, which is the volatility, the collapse, and the rebound of South Korea's stock market. So we'll do that right after this. Today's executives are more threatened, more exposed, and more vulnerable than ever before. Corporations spend billions on workplace security.

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47:16Big Technology Podcast:That's q-u-i-n-c-e dot com slash bigtech. One thing I've noticed about companies adopting AI is that they're often making decisions based on how they think work gets done, not how it actually happens. Without real visibility, it's easy to automate the wrong processes. That's exactly the problem Scribe was built to solve. Scribe is a workflow AI platform trusted by 94 % of the Fortune 500. Scribe Optimize gives leaders a view of how work actually happens across their organization, showing which workflows take the most time and where there are opportunities to improve. Optimize automatically discovers workflows across approved business applications, even when a process starts in Salesforce and ends somewhere else.

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48:40Big Technology Podcast:Well, they've certainly lived a few lives since then because the South Korean stock market has crashed and rebounded somewhat. And I think this story that I'm going to read a little bit of it from the Wall Street Journal is another indicative story. Because people who listen to and watch the show say, why do you talk about the AI bubble? There's no bubble. Even if there's no bubble, let's say, let's take that as granted. If there's no bubble as a given, there could be and there are already little bubbles and investing behavior that is putting people at risk. So I don't think it's completely worth dismissing.

49:16Big Technology Podcast:And that's why I think it's worth bringing our listeners and viewers and all of you at home up to speed on this story in South Korea. This is from the Wall Street Journal. The world's craziest stock market has turned into a fright ride. South Korea now hosts the world's craziest stock market, showcasing a stomach-churning volatility not seen in major markets in years. The benchmark Kospi index has more than tripled in value. Driven by faith in the AI boom, two South Korean companies, memory chip makers Samsung Electronics and SK Hynix, soared to trillion-dollar valuation and became twin forces, pushing record market gains.

49:52Big Technology Podcast:Then the index plummeted around 40 % over six weeks in June and July, burning hundreds of thousands of investors. A sober warning to those betting big on the AI industry, the rollercoaster ride has continued. the Kaspi has since rebounded about 20 % from its lows. Now, just going down 40 % and up 20%, it doesn't sound too devastating if you're not levered, but that is the problem. A lot of people have been levered. So this is just very quickly the pain fell hardest on South Korea's individual investors who account for 60 % to 70 % of the index's daily trading volume. They are known as ants, weak individually, but capable of collective power and fed the market with the deep faith in Samsung and SK Hynix and buying those largely, well, not largely, but with a healthy appetite for levered ETFs.

50:51Big Technology Podcast:And the ETFs are single stock. So some of them are double or triple levered. So if you bet on Samsung in a double levered, when Samsung goes up 5%, you're up 10%. Or triple levered, when it goes up 5%, you're up 15%. But when it goes down 5%, you're down 10 % or 15%. And so when it goes down 40%, you're wiped. And that's sort of the problem that we're seeing in South Korea right now. Ranjan, you talked about how things were roaring within South Korea. Now, not so much. What does this tell us?

51:23Ranjan Roy:I think this, to me, the most fascinating part of the story is actually first this term ants. I kind of when I was reading this, I was looking more into it. Apparently, it started in 2020 in the covid stock trading boom, but definitely kind of took on its own form during this latest hype cycle. But I mean, to me, the most fascinating part of this is the connection with Leopold and situational awareness, Because like you are massively levered in a concentrated form on one side over here in the U.S. with Leopold, even though like plenty of U.S. investors were definitely involved in the trade. But also but and then you have this army of ants and the South Korean traders all pushing this up.

52:11Ranjan Roy:And timeline wise, it is fascinating because knowing that it was the like double and triple levered ETFs came out end of May, like you just start to see how this all maps perfectly. And as you said, up 40 percent, then down 20 percent net might not seem that bad. But I mean, you're getting cleared out if you're levered on this kind of stuff. So I think like, I don't know, it's there's the trade itself in the medium and long term. And we've talked a lot about timelines today, but also wondering, like, I don't know how these trades come into existence. How's information being shared? What people are going back to not investment advice?

52:55Ranjan Roy:Who is convincing everyone that they're missing out on SK Hynix and the other levered GTFs also, I think, is pretty interesting here.

53:04Big Technology Podcast:Well, I think this is important to discuss because remember we talked a little bit ago about how fantasy football and online sports gambling have been presented to people as the, you know, sort of the only place where you could have agency, where everything else feels rigged, where you don't have an opportunity to buy housing, where you don't have an opportunity to really save for retirement. You can't see an economic future. So people go that way. A lot of those same dynamics are out play at play here. And I would say that even though mostly the story we're talking about is in South Korea, it's something to be aware of everywhere else.

53:36Big Technology Podcast:Let me just read a couple stories of individual investors within South Korea who ended up getting cleaned out by this situation. Yoon Kyung Min, a 44-year-old sound engineer, said he still can't believe the financial disaster of the past two months. After quitting his job, he had invested half of his severance pay into semiconductor stocks and saw$7 ,200 evaporate in a week. If my wife finds out, I will be in serious trouble, said Yoon, who said he confessed only to a bit of bad luck without giving details. Yoon thought the market would rise forever. Then there's Lee Kiyong. Lee Kiyong, a 25-year-old software developer, said she lost all the money she made when stocks soared this year.

54:14Big Technology Podcast:She started investing in December, when her first paycheck from her new job left her convinced she would never earn enough money to buy a home. She ceded a trading account with around$14 ,000 from her savings and crypto gains. She invested all of it into SK Hynix and later into single stock levered ETFs. She started her own Instagram to document her ride to riches. See, Ranshan, people are still poking. People are still posting. By May, her account was up more than 58%. And her posts were drawing an average of 4 million views. But however, her holdings are now worth less, 5 % less than when she started in December.

54:55Big Technology Podcast:her investments multiplied so fast and vanished so quickly it felt like it was all a dream i got greedy she said i kept thinking what if i climbed higher uh even higher after i cashed out

55:08Ranjan Roy:concerning i think this is kind of a interesting tie-in of all of our stories into one place again because like again uh both do you think she gave the not investment advice disclaimer

55:22Big Technology Podcast:or she on her instagrams certainly not she was like this is pure she said follow me the riches

55:28Ranjan Roy:but but but again the same addictive mechanisms and the same move away from friends and family content to entertainment content and that entertainment content being investment content and algorithmically being shoved in front of people and then them feeding into the actually buying the stocks. It is kind of an amazing, terrifying way of seeing it all come together in one place.

55:55Big Technology Podcast:So when people say, you know, this is AI is not a bubble. Stop talking about this type of idea. Do you think it's fair to kind of point to these examples and be like, you know, even if we don't see systemic risk, like we do talk about systemic risk more often than we do, like, you know, risk to individual investors if they have conviction. I think, do you think it's still worth worth kind of covering and talking about just so people are aware of like what could happen if it goes south because you know it's happened here but maybe it happens elsewhere

56:25Ranjan Roy:no but this is the main thing about any kind of and and even the word bubble is all relative like when is something a washout or a downturn versus a bubble is always kind of difficult to like i think that's more just like how cleanly packaged it is in the narrative eventually but But to me, like Leopold and situational awareness, these stories, this is the early part of any kind of bubbles ending cycle. And again, having lived through the 2008 on a trading floor like 2007, there was these there was Countrywide and Bear Stearns and before long before Lehman, like there was those hedge funds name again that collapsed back in like March.

57:11There was, you know, there are these like bits and pieces coming out.

57:16Ranjan Roy:And I do think it's very important because both at a human and individual level. And like, I think the big difference from 2008 was like, for the average person and individuals, the price of your home and your home equity was the kind of like exposure. whereas whatever is happening in this cycle way more people thanks to robin hood and democratize investing are exposed so whatever we see happen i mean there's a lot more people with skin in the

57:47Big Technology Podcast:game right now yeah can i can i try to really wrap it up here for us wrap it up the we've today we've talked about basically three stories of a belief that the line that you're seeing in AI will happen rapidly and will happen immediately and exponentially, right? So we talked a little bit about Sespocalypse, right? The belief that software was about to be annihilated by AI. Then we talked about Meta's attempt to use AI to replace work. And now we're talking about, basically this is a story of people believing that the memory crunch was was never going to let up to the point that like samsung and sk hynix are worth betting on you know triple or double levered to the point like one of the traders said i thought the market would never stop going up even when it can feel like you're in the middle of an exponential and things are just going to keep going and you know the demand will keep going and there's never going to be any let up there are going to be air pockets here and it is going to be turbulent right and i think that's kind of the lesson of this show right it's basically just like you know no matter how much conviction you have and what's going on with ai no matter how much it's progressed and accelerated since 2022 it's not worth it there's a there's a goldilocks zone between going all in too late and all in too early and uh and there's there's real risk in going in all in too early because of the human side of things and the bumps and the fact that there is some turbulence along the way inevitably.

59:25Ranjan Roy:I think you may have just achieved the most difficult thing to do in any kind of podcast. Tie up everything neatly at the end. We never do that and are never good at that and usually just trail off and whatever tangent we went into and i i think you nailed it i think you got it there

59:48Big Technology Podcast:stuck the landing thank you state of ai in 2026 i'm not gonna buy galley but but i i want to so anyway no save save your buying i'll save it i keep the by golly in the holster wishing you great weekend wow it's almost september i'll see you in september ranch on see you summer's over

1:00:09Ranjan Roy:lock in for what's going to be an interesting September.

1:00:13Big Technology Podcast:The rest of this year is going to be absolute chaos and I can't wait for it.

1:00:17Ranjan Roy:Yeah. All right. See you.

1:00:19Big Technology Podcast:All right. See you next time. Thanks everybody for listening and watching and we'll see you next time on Big Technology Podcast.

1:00:25Ranjan Roy:This episode is brought to you by ChatGPT. Hey, it's Bill Simmons from the Bill Simmons Podcast. Have you guys heard about ChatGPT work? It's the new way to use ChatGPT for bigger multi-step projects. And when you need more than just answers, give ChatGPT work access to your apps and files, and it can create real work documents like spreadsheets, slides, and structured reports. Get started at ChatGPT.com by selecting work mode available on Plus and Pro plans. I'm not giving up. I am selling the building. The final season of FX is the bear.

1:01:05Big Technology Podcast:The restaurant is flooded. Everything's either gonna be okay... No! Stop!

1:01:11Ranjan Roy:Or not.

1:01:13Big Technology Podcast:We are outgunned and we are outmanned. We have each other.