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Why AI is bringing everyone back to the office · The Punch List

• [00:00:00] Kanav Hasija: There are very few engineers who know how to create an alpha in an AI model, how to create that differentiation, how to beat the competition. And those people are less in number, and their salaries have gone up from half a million or 1 million to 10, 15, $30 million, right? So if you're getting like paid 10 million cash and 20 million stock every year, you don't mind paying $10 million for a condo, or you don't mind paying $30 million for a big, single family home in Atherton or Palo Alto [00:00:35] Jon Wright: Welcome to the Punch List podcast. We have a great episode today. Kanav joining us from India, TK joining us from an undisclosed location in the San Francisco Bay Area, We have three very hot and interesting topics today. One, the tale of two cities, Seattle and San Francisco housing markets. Two, office getting some love again, maybe. And three, foreigners to the US buying less real estate. What's going on? What are the trends there? How's that gonna affect construction? And, also we'll just kinda share what's going on in our businesses, where our travel, has been, insights. So, Kanav, why don't you-- why are you in India right now? Just what's going on? [00:01:19] Kanav Hasija: Yeah, we're right now in Bangalore. Bangalore is like the tech capital of India. It's like the Silicon Valley of India. And we just opened our office here. I, I'm right now sitting in one of the cabins, in the conference rooms, and it's never been more productive since we opened office, man. It's, it's lovely. Let's bring people back to work, back to office. I love that. Even if there's AI, like you still need the human touch to work together. So I'm here for the launch, and we are loving it [00:01:47] Jon Wright: Well, that's great. I mean, I, I think we're seeing in the data office getting some love again. Just to jump to the second topic, maybe, I mean, office has been in the dregs. I would tell you, among the institutional investors, office still gets a little chuckle, and a laugh, and I'm not sure anyone's doing it, but, we're seeing some green shoots here. What does that mean? Maybe talk about it in terms of your perspective as a, running a business and leasing office. What, what was the motivation to do it, and what are we seeing in the data here? [00:02:21] Kanav Hasija: I see two points. I mean, post-COVID, we had a lot of office vacancies. People are coming back to work. That's one strong signal. And then the second big signal is AI is not taking jobs away. AI is bringing more jobs back. Every small and medium business realize they need more techies. They can do more with them now at less cost. So everyone needs software engineers in their companies, and they, and they want to build up, you know, lease up their office spaces. So, you know, people want more jobs and, people are coming back to office [00:02:56] Tanmaya Kala: To add to that, I always feel like, I think Apple is kind of a little bit ahead on these things than rest of the economy. I remember when Tim Cook was like, "Hey, you build things, ideas happen when people run into each other in corridors, when you whiteboard in a conference room." And at that time, there was some pushback because there was this whole motion towards work from anywhere, work from home, and how that's more effective and all that good stuff. And to be very honest, when we started the company, we had a work from anywhere model. And we thought, you know, that'll give more people more flexibility. We'll be able to get good hires, which did happen, but nothing beats the good old productivity of putting people in an office. I mean, I'm a construction guy. As a general contractor, you can't build buildings from home anyway, so we're used to being where the, where the job is at. But I think I'm seeing that in the tech environment as well, and it's, it's way more effective. I think second part of it also, the demand's been depressed for a while, like since COVID. I mean, Jon, you have, you and I have seen that for a long time, especially in Bay Area. So it had to snap back and kind of correct itself at some point, and I think we're seeing some correction here too. [00:04:09] Jon Wright: Yeah, that's right. And this has been going on for several years. My wife, for example, works for a large tech company. She's not remote. They're headquartered in the Bay Area, but, you know, they're operating all over the United States. And she's flying to the East Coast next week for a big whiteboard session because There's just so much inherent value to getting the team together for an in-person. And I'd say people were experimenting with trying to do that, like, you know, post-COVID. They'd come together and have a little social event. But I think what we're seeing is less about a social kind of like rah-rah and more about, "Hey, we need to get together and solve a, a thorny problem." And it's, like, a lot better to be breathing the same air and the same, you know, whiteboard marker scent, if you will, together, And two, Kanav, to your point about we need more engineers. So I run a s- a, a small, you know, real estate development investment company. I'm really AI native, and I can vibe code something to be pretty functional. But what I'm realizing is to deploy that larger, I need, I need some engineering help, right? To, to really solidify that, to make it safe, to make it accessible beyond a core group. So that's producing more demand, right? I'm producing more code that needs to be maintained and monitored and optimized by someone who knows what they're doing other than me with Claude code, right? So, I agree. I think, we're probably normalizing our demand for office again. You know, it's post-COVID. And we've said this many times on the podcast is that a commodity office with drop ceilings that smells bad and is a far commute, dead. Great office that's optimized and fit out for, the modern workforce and with less of a commute, alive, and maybe getting hot again. We'll see [00:06:10] Kanav Hasija: Jon, you're right. I mean, every retailer, distributor, manufacturer, broker, every common job in the US is realizing that they needed about five software engineers to make their tech work for them, so they never hired them, but now they can do with one. So they want to hire them. That's-- It's as simple as that. We were all settled in our ways of working. We knew how to build a company and run a company. But since AI has come upon, it's, it's new s- new ways of working. We are figuring our ways out. And if you are figuring your ways out of working in a new world, you need to meet together in person. You cannot do that in, in Zoom, you know, meetings. So it's that change of the world which, which makes people come back, to meet in person. [00:06:58] Tanmaya Kala: That's actually a great point. That's an interesting lens to it because, in the knowledge worker environment, right? Like, like forget like doing actually like mechanical or industry work, but in a knowledge worker environment, if you're doing the same steps again and again and, and it has been systematized, then yeah, you can work from anywhere because it's, you know, it's very easy to piecemeal work and divide it amongst like what a knowledge worker needs to do and, and, and measure what a person has done. But when you're creating something new that has not been created before, the only way to do it is you have to come together and collaborate and exchange ideas. [00:07:37] Jon Wright: Well said differently, if you're a knowledge worker doing the same thing over and over again, then you need to be careful that you don't become a markdown file and a skill and a cron job. [00:07:48] Tanmaya Kala: Where the value you're gonna bring is the differentiating and the creating, using an AI tool. [00:07:55] Kanav Hasija: So therefore, I think, yeah, that lends itself to more, creativity in-person working, right? Yeah, I'll, I'll give you a simple example, it happened just literally today, I could never have observed this or caught this if it were not in person in office. And what I realized today is AI has made software coding faster, so we can make products faster. AI is still not good in making videos. So to make a really amazing finesse product video, not a grade B, like grade A, A+ finesse explainer video about a product takes longer than it takes to make a product itself now, right? So it, it used to take six months to make a product and like, you know, one month to make a video. Now it makes two weeks to make a product. It takes three weeks to make a video. So making video of a product is a bottleneck, not the product itself. [00:08:53] Jon Wright: What AI does, I think, is it, it removes all these barriers of like the technical in some ways. And so you can think more and spend time on the content and the, the core idea and how you're communicating it versus like all of the technical around the platform and the way in which it's done, right? I can spend more time on a spreadsheet now thinking about scenarios and, you know, different hard, strategic questions and less about formula creation with like these Excel plugins from Claude, etc. And I think now because that's true and because the, your counterparty, if that's an investor or something else, they know that, or maybe your customer knows that. And so they're gonna expect higher and higher, level quality content and idea generation, Because they know baseline you can make a nice looking thing to convey it. You can make a nice PowerPoint deck or video. It's like, what's the quality of the idea here? [00:09:58] Kanav Hasija: So Jon, let me put this in a different context of what happened just in last four months, Product development has become faster than marketing. We are marketing slower than we are building, in the last four months, right? So marketing used to be always ahead of building in the software world for the last ten years. Now we are making stuff faster than we are able to market to the world. So we are scratching our heads in office and saying, "How can we speed that up?" It's a new world, which never happened like 10 years ago, [00:10:27] Jon Wright: Our human brains are the constraint now [00:10:29] Kanav Hasija: Yeah, I mean, you said this yourself. You didn't know half the things Claude built out three months ago, right? Because Claude never released it. Claude never marketed it to you because Claude is also way behind in marketing than, than development, right? So you never knew what Claude is up to until you learn from someone else [00:10:49] Jon Wright: For those things, you need to be in office. You cannot do these things in Zoom meetings perhaps we contrast the utopia that is San Francisco with its lowering vacancy rates, lowering office cap rates and high salaries, large secondaries, large bonuses. Let's compare that to what's going on in Seattle. Seattle has become a robust West Coast tech market, but what's going on right now? What's in the headlines here? [00:11:21] Kanav Hasija: So let's, let's set the context for the audience first, and then jump into it The biggest employers in Seattle is Amazon, Microsoft, The tech layoffs is hitting the housing market pretty bad, right? That's, that's Seattle for you. San Francisco, the home buyers have lost their minds. They've become so AI wealthy, and they're just giving any obscene amount of, you know, amounts of money to kind of buy properties because there's so much secondary out there happening in Anthropic and OpenAI and Space X AI and, and you know, whatnot. So it's on one side, they both are tech capital of the, of the US, but one doesn't have enough AI wealth, which is Seattle, and they have layoffs, and one has so much of AI wealth, San Francisco, and the market is just going bonkers there. [00:12:18] Tanmaya Kala: So almost SaaS versus AI going on here. I mean, CR companies are more SaaS-oriented [00:12:24] Kanav Hasija: I mean, Amazon and Microsoft are also invested in the AI game, but financially, not through their employees. They're not building stuff in AI, so they're having more layoffs for that purpose [00:12:38] Jon Wright: Yeah. And let's, explain to our audience who are maybe outside of the Bay Area, to explain the stunning reversal that's happened in San Francisco in the last, call it four years, where, by all accounts, in 2020 to 2021, '22, San Francisco was kind of like a zombie wasteland, COVID decimated, office market. You know, we had a crash in the condo values. We had a crash in, rents. Single-family homes were doing better because people were looking for more space. But people had pronounced it dead, which I think has happened many times in California and San Francisco's history, boom and bust. Now we have the beating heart, undisputed capital of AI is actually in San Francisco, which that's another, different trend. Usually, these large AI trends start in Silicon Valley physically and then move to San Francisco because these large companies want to recruit a younger workforce. But that's different this time. Actually, these companies started in the city. Here's why this is happening. Three things. One, massive salary competition. Engineers getting paid massive W2 salaries so they can afford to buy real estate. That's, that's one. Two, massive W2 bonuses, like huge signing bonuses, huge end-of-the-year bonuses. I mean, this venture capital money, this Claude and ChatGPT subscriptions flowing to the employees because there's a massive talent competition. And the third is companies also, another retention game is they're allowing their employees to sell their RSUs or grants or options onto a, this very opaque secondary market, And there's a variety of motivations for that, but a lot of it is for retention so that they can, you know, keep them. [00:14:32] Kanav Hasija: And these are, these are like 10, $15 million checks. And so that 27 or eight, 28-year-old engineer is writing a check for a condo in San Francisco, all cash, And this happened, Jon, because we talked, I think a few weeks a-ago that electricians went up from 60K, 70K to 150K in salaries because they were the bottlenecks in building data centers for AI. A similar thing is with engineers. There are very few engineers who know how to build, how to create an alpha in an AI model, how to create that differentiation, how to beat the competition. And those people are less in number, and their salaries have gone up from half a million or, or 1 million to 10, 15, $30 million, right? So if you're getting like paid 10 million cash and 20 million stock every year, you, you don't mind paying $10 million for a condo, or you don't mind, mind paying $30 million for a, for a big, single family home in Atherton or Palo Alto [00:15:40] Jon Wright: TK, thoughts? You gonna move up to the city? [00:15:43] Tanmaya Kala: Nah, I love [00:15:44] Jon Wright: TK's never, never lived in the city. He's always lived in the South Bay or the East Bay, and he used to whine and moan when I would have in-person meetings in the city and he'd have to drive up. Now he's championing the in-person [00:15:57] Tanmaya Kala: Hey, I-- Oh, I championed in person back then as well, just in South Bay. Talking about San Jose a little bit, I know Google was gonna put $20 billion to build a big campus, in San Jose. That was all the news. And then during COVID, that was another casualty of COVID. In 2023, I mean, that was three years after COVID, they, they, shut that project down, because they didn't feel that they need such a big campus. [00:16:24] Jon Wright: Yeah, things are changing [00:16:25] Kanav Hasija: Jon, you were in New York this week, for the real estate, conference. You can talk about that. But before you do, how's New York, man? It was hot, but the city was bumping. It was good to see it, you know, packed. You know, typically New York kind of clears out in August. I think people go [00:16:42] Jon Wright: To The Hamptons, etc. But, I was really impressed to see how busy the city was and live and well, our financial capital is here in the United States. Yeah, no, so I was in a room, throughout the fall, I'm gonna be attending a lot of these. But, you know, 250 people, capital allocators in real estate, operators in real estate, deciding where the money goes. Lots of interesting thoughts. I mean, a similar theme I've been hearing for several years. One is that, private credit markets are very robust still. I'm financing construction deals and development deals and, you know, I have a lot of debt options, which is great. And that wasn't necessarily true for the asset class that I worked in before, you know, call it 12 years ago, in terms on the debt side. Unlocking private equity today is still very challenging. We are in a continued four, call it four-year, post-hangover from the '21, '22, end of the free money era, rate raise. So we talk a lot about data centers on this podcast. There's data center investment and construction, and then there's everything else, okay? And I'm talking about everything else, the real world here. Funding your projects is hard still. If you got a commodity asset in a, in a, you know, so-so market with a commodity thesis, good luck. People want large institutional private equity and, and, and also the GP and sponsor world are still locked up in illiquid large deals from '22 that are highly leveraged. They're probably making money, but not what they expected, and they're still locked up. The LPs are pissed about that. The GPs are pissed too. There's a standoff. And so that's not unlocked a bunch of other capital for new deals. It's also made a lot of capital-constrained GPs. And so one, effect of that is, one, equity's not available. Two, there's a, you know, it's in vogue right now for this co-GP model, where if you're a sponsor, you know, you basically take, equity as part of your sponsor contribution from another, investor And they share in your promote and your fees. I think that's a function of investors wanting higher yield, but also GPs being capital constrained and LPs dictating terms. So I think, you know, we're, we're looking at that. I think a lot of people are just embracing it to get their deals funded. But, you know, everything is deal by deal. Nobody's raising funds. This has been true for several years. You've got to be differentiated. And so, how that's affecting construction is, again, you have to have a unique thesis in a, in a strong market [00:19:24] Tanmaya Kala: For non-real estate savvy people, maybe you might wanna explain the difference between LP and co-GP and who those cast of characters are [00:19:32] Jon Wright: LP, limited partner, call it investor, an investor. Someone who's just investing your capital. A GP or general partner or sponsor, the actual real estate operator, the developer, who's building and bringing all the financing together and hiring the general contractor and acquiring the land and building it. They often will have to contribute equity too, albeit a lot smaller check, so they have some skin in the game. And what's happened is the investors wanna now be part of the operation. They wanna be part of the operator. And typically the, as the operator developer, you're getting an outsized return relative to your risk because you're taking a large risk. You're putting money in, you're maybe signing a guarantee on a loan, et cetera, and so you get rewarded for that. But now the investors not only want their return as investors, but they want a piece of your return too. And so rather than fighting that, I think a lot of people are just trying to see, if they can make that work, and still get deals done [00:20:32] Kanav Hasija: I mean, I think that's the reason why this, the survey that just got released this week said commercial real estate is the top ranked investors asset class, even surpassing equities and bonds and cash. I mean, that was a big move, I would say, because cash was the biggest one, then equities and, and then real estate. I think real estate jumped to, to number one on sentiment, which is great [00:21:01] Tanmaya Kala: When you say that, is it like higher than like putting money in AI companies? [00:21:05] Kanav Hasija: That's more targeted and more risky, TK. But if you look at a diversified view, right? You could say "Hey, I want to put in money in all the tech stocks as one equity fund," rather than putting money in SpaceX or NVIDIA or, you know, one of them, I want to put in money in all the tech companies. I think investors are saying they will do that too, but at less, at less exposure. They will put more exposure into real estate, then cash and then equities. [00:21:32] Jon Wright: I think hard assets and hard tech are having a little, a little mini moment right now because AI has made SaaS, everyone calling to question SaaS and software. And so everyone's like, "Okay, let's talk about the real world and people building things in the real world," which I think is interesting for all of us, whether you're building robots or you're building housing or you're building a tech company that's helping build hard assets like you guys are. I think-- from my personal investment point of view too, with the turbulence we see around us due to many things, which I don't wanna get into right now, but we, we see the turbulence in the market and the [00:22:11] Tanmaya Kala: World economy. I think going towards hard asset feels like you're on solid ground too. I mean, at least I feel that. So that's why I think maybe many other people are feeling that. [00:22:23] Kanav Hasija: It's a double, benefit now, right? You want more cash in turbulent times. So REITs are good. I mean, you, you invest in REITs, you get not just the compounding, you also get the cash back. [00:22:33] Jon Wright: Real estate investment trust, publicly traded [00:22:36] Kanav Hasija: Right. A good chunk of my portfolio has shifted to all the, all those REITs and they're doing really well right now. [00:22:41] Jon Wright: Okay, last topic. Non-US citizens, foreigners buying less real estate in the US. We've typically been a large magnet for real estate capital like London, like other world capitals. What's going on? How do you explain this? [00:22:57] Kanav Hasija: Yeah. So it's very interesting. I've never seen this bigger drop. 19% less real estate being bought by foreigners as compared to one year ago, which is a huge drop. It's almost like one fifth reduction, in real estate. And I think the biggest reason for this, what I find is the unpredictability in immigration. We have no idea, like, can we come here, get educated, live here for long enough or not? And if you can't, like why even buy real estate? Should just rent it out, So it's the H-1B unpredictability, it's the green card unpredictability, which is causing this big issue. All those Chinese immigrants giving all cash deals to get their kids, you know, study for four years in, in Stanford or whichever university, and then, sell that house later after four years. It's all going away [00:23:55] Tanmaya Kala: As an immigrant, I'll keep my mouth shut on this one. [00:24:00] Jon Wright: This is episodic. This is not a... You know, if, if things calm down, this is, this is a blip. And I mean, I'm trying to speak optimistically 'cause this has, always been an important part of the luxury market for sure in coastal markets. So it's really important, for everyone's home values and for investor operators. But if things do change, calm down, the other demand drivers for this are still in place. It just seems to be the immigration issue right now. [00:24:29] Kanav Hasija: Yeah, it's not bad for the US economy. I mean, if you look at it, immigrants were coming in. I'm an immigrant myself, but immigrants were coming in and, and paying more prices than they should on buying real estate. So them coming less in the market are, are, I would say is making the markets more affordable. [00:24:46] Jon Wright: Interesting [00:24:47] Kanav Hasija: In the, in the non-AI areas. Of course, in the AI bubble, it's not the immigrants, it's the employees who get the stock options which are bumping it up [00:24:55] Tanmaya Kala: Yeah, I mean, I think the housing inventory is still pretty tight anyways. So, so it's not like, with this reduction in buying, you have houses going unused or like, you know, there's like, oh, there, there are vacant homes. It's not like that. It's just, I think it's more like you're getting less bang for your buck if you're a property owner. [00:25:16] Jon Wright: Well, TK, I'll speak for you. I love you dearly, and I want your immigrant money to come buy in my neighborhood and pay a hefty price and get my comps up and then play with my kids on the street here. [00:25:32] Tanmaya Kala: Yeah. [00:25:32] Jon Wright: You're welcome to buy on my street. Please do so. [00:25:36] Tanmaya Kala: Your street is too expensive. We looked at it. [00:25:40] Kanav Hasija: Come to my town, man. Let's tumble the hills [00:25:42] Tanmaya Kala: Given California is earthquake country, I stay away from the hills too. I'm kidding. Sorry, not to scare anyone. [00:25:50] Jon Wright : All right, great episode today. Lots of interesting topics and thoughts. Any parting thoughts, Kanav? [00:25:56] Kanav Hasija:We are just gonna do the new Building Corner. We're gonna touch upon Empire State Building as the last segment, and then that will hopefully be a new corner for our audience. So if you like our Building Corner, please put in your comments, and like, subscribe and share The Punch List podcast [00:26:15] Jon Wright: Absolutely. TK, final thoughts [00:26:18] Tanmaya Kala: Please give comments on Building Corner. I personally love it. Also, let us know if you prefer AI Corner. We can, we can do that too. So [00:26:27] Jon Wright: Or if there's just a certain host that you like more or less, go ahead and we can take it. Even if it's me that you dislike, just go ahead and comment, like, subscribe. We can take it. We like the feedback [00:27:10] Kanav Hasija: The building I wanna pick up this week is Empire State Building. When you go to the tour for Empire State on the second floor, they show all the history of how it was built. It surprised me that it took seven months to design and 14 months to construct that building. Soup to nuts, less than two years. We still can't build a building of that size in five years, let alone two, after 85 long years. What's wrong? Why can't we build a building that fast? [00:27:36] Jon Wright: You bring up a good point. [00:27:37] Tanmaya Kala: Because it kind of goes back to this AI conversation we keep having. Building industry is a great example of no matter how much better your tools are, it's about people and how, competent they are, right? So Empire State Building did not definitely had better cranes and welding machines than we do today. But what they did have was very thoughtful planning, And I think that's the future of AI as well. It's a tool. It's a better tool, but if people are not competently using it, I can see that becoming a problem too. So... [00:28:12] Kanav Hasija: Let's put all the naysayers behind first, right? Because it, it was built 85 years ago. There were less regulations, there was less safety requirements than today, there was less permitting requirements than today. So yes, they didn't have to go through a long cycle of one year or six months. They didn't have to go through a lot of fire, life safety issues that they have to go today. Keeping all that aside, it still took Salesforce [00:28:34] Tanmaya Kala: Mm-hmm. [00:28:36] Kanav Hasija: Years to build in San Francisco, right? Which, which is less number of stories than a hyperscale building, or less height and square feet as-- in feet as well. But it's still not like two years versus seven years is still a huge gap. So it's not just about fire, life safety. It's not just about regulations. There's something more to that, right? [00:28:52] Tanmaya Kala: There is, in fact, I look at World Trade Center as a good example too. It took eight and a half years from soup to nuts, and it's in New York. I give San Francisco a bit of a pass because San Francisco is bay mud, which is the worst soil condition to build on. [00:29:06] Jon Wright: Yeah, the foundation design's very different between those two, but seven years still is the point is it's like a huge gap [00:29:13] Tanmaya Kala: It's, it's a huge gap. And, and World Trade Center is in New York. It took eight and a half years still. I mean, it's a taller building, but it's on the same bedrock that, uh, Empire State Building is on. I mean, New York is great to build, uh, skyscrapers because it's on a bedrock and they don't have the seismic requirements we do in, in California for right reasons, of course. To be very honest, I'll be very upfront, I don't exactly know what is the reason other than I feel like the competence of those guys was way higher and there was lot more alignment, on how it was built. When it comes to stakeholders and decision-making, there were fewer more competent people than we have this, like we get to building a building, we have this large bloated organization of people who have a lot of opinions and say into things. [00:29:59] Kanav Hasija: Do we need even need to say competent? Just having less decision makers is, is good enough to increase productivity, right? [00:30:06] Tanmaya Kala: The reason I say competent is, and I think we in this day and age are very competent as well, but I think back in building construction was what you would call AI of this time, right? If you say went to sleep in 1899 in New York and woke up in 1915, 16 years later, you'll see a completely different skyline. If you went to sleep in 2010 and woke up in 2026, 16 years later, the skyline would probably look exactly-- You won't even be able to tell it apart in New York. So, so [00:30:40] Jon Wright: Are you kind of saying advances in material science and materials used in steel and concrete just there was a big jump. [00:30:48] Tanmaya Kala: It was a big jump. Built environment was where the edge was. Right now the edge is in the software space. So it's a more philosophical thing, But coming to Empire State Building, let's talk numbers first. So 21 months from start to finish. These guys, the architect, was hired August of 1929. May 1st of 1931, project opens under budget and early. Only 2% of projects in this day and age can say that. Uh, there is a great book called "How Big Things Get Built." It tracks that data, and this day and age, only 2% of those, uh, projects can boast, uh, what this boasts right now. Under budget and early. It took 410 calendar days, to build the building. They were doing four and a half floors per week. That's almost, a floor a day. And, um, at their peak, they were able to put 14 floors in a 10-day stretch. Lot of people involved. Peak manpower was 3,500 people, which is way larger than anything we see these days. The amount of coordination it would have taken to bring all these pieces in. There's a great book on Empire State Building, where they talk about the steel guys would love to warm their hands on the steel because it was built in Bethlehem Steel, which was in Philadelphia. It will roll right out of the line, put on a truck, would reach Empire State Building, and steel would still be warm. That's how fresh. [00:32:14] Jon Wright: That's just two things right there in terms of supply chain speed plus 500 truck deliveries a day. No way that would be allowed in a major metro now. You'd have all the coordination, and the neighbors, and your permitting, and the greenhouse gas emissions, and the noise, and we just don't let people operate that fast anymore [00:32:34] Tanmaya Kala: Fast [00:32:34] Kanav Hasija: More thing to be said there, right? So this is what I-- I took a photo of that second floor where they were talking about stuff. This is the plan of, week-by-week plan of how the steel will be manufactured If you look at the bottom, it was designed, it was authored by the architects. Which architects today maps out the supply chain of steel, let alone the cost of construction? I'm not blaming the architects here. I'm just saying there are so many different stakeholders today. An architect, an engineer, a contractor, a subcontractor, they all are taking their own decisions. There are thirty-five organizations taking decisions [00:33:12] Jon Wright: In a modern building today of that size, you would probably have a design team of 75 plus firms [00:33:22] Kanav Hasija: And there were only three firms in Empire State that took all the decisions. There were just three firms. Same number of scales, but only three firms, That's something to be said about that [00:33:32] Tanmaya Kala: I mean, even how they thought through schedule, we have went a little backward on. Um, so, so that schedule you pulled up, I, I love that. I actually wrote a white paper on it at a different point of time. It's, it's line of balance, location-based scheduling. We don't do that. We do Gantt chart scheduling, which hides a lot of bullshit. From a risk management perspective, it's a great idea, and I'll, I'll probably get the Primavera people might take out a hit on me for saying that. But, that's a fact. I have this, uh, this is one of my favorite book. It's called Location-Based Management System on Construction, and they studied Empire State Building like to a-- like this is the picture you took, um, there. They studied the Empire State Building and went backwards on how we should be building schedules for buildings. And well, you know, we don't, we don't use that. [00:34:21] Jon Wright: Do they work on the weekends? Generally they did, but the numbers I'm telling you where it's like four and a half floors per week and like, I mean, those are still real numbers. [00:34:30] Tanmaya Kala: Even like in 410 days they put the building together. It's still hard to beat that number. Like if I were to share this... And, and they didn't always work on the weekends, I'll say that, but yeah, there were some weekends they worked on. But if I were to like Kanav was saying, if I were to compare it to, to other buildings, like typical New York City building of this size takes about four years. Empire State took 1.1. Which was again, to be honest, Chrysler, which was six months before, like took six months longer, roughly the same size, a little shorter. [00:35:05] Kanav Hasija: Yeah, less coordination at that time, no? [00:35:06] Tanmaya Kala: It's not just coordination. The, the key thing I feel is, so William F. Lamb was the lead architect and lot, lot of credit goes to him. But I would say like if you read this, so no caryatids straining for effect, no buttresses, no cornices to cast shadows. Whatever style it may be is the result of a logical and a simple answer to the economic and technical demands of this unprecedented program. It's a very heavy statement, but if you look at most buildings in New York, of the time, of the age, they would have gargoyles and, and ca-- like they'll have all these things sticking out of the building, which was aesthetically looked upon as a big value add. He cut all that out. There are many little things they did based on this logic where they went backwards from how do I maximize rentable square footage? What do my tenants really want? They want more light. Okay, I'm gonna move the cores to the middle. Right now it's a very common practice to have elevator and restroom cores in the middle. Empire State Building was the first one to do that. And it came from a business need, not, you know, they just went backwards from, what do my tenants need? I'm gonna go backwards from that. Do tenants really care about gargoyles sticking off the side of the building or not, right? [00:36:22] Jon Wright: Well, I'd be okay if the tenants did like that and they chose to put them on there for a business reason versus... And a lot of these elements today are driven by city planners the complex exterior facade is because of planning requirements [00:36:38] Tanmaya Kala: And that really basically having one focus, right? Having speed as the focus because they had to open by May... So May 1st is a very critical time. May 1st was, is the most active leasing sea-- May is the most active leasing season, uh, in New York, at least back in the day. So they had to open by May 1st because that's when most people do, uh, move in. So that's, that date was critical and they worked backwards from it and they said, "We gotta make this happen." And, and so architects prioritize speed over all these other things like, you know, like, like it says here, windows sat, sat flush. They didn't stick out. Well, that was uncommon for that time actually. You know, they standardized steel frames. I mean, again and again and again they chose things that were more efficient. At that time many people criticize it to look like, "Oh, this is a building that looks like a pencil." But architect put their ego aside and focused on, know, speed and efficiency, which really made the difference . [00:37:40] Jon Wright: And no one would today would say that that building is not beautiful. That building is beautiful and iconic and a gem to the New York City skyline [00:37:48] Tanmaya Kala: Yeah. And it had 67 elevators, like just, just to make, make it all work because at that time, because you couldn't like, you know, elevators couldn't go like all the way. I mean, it's 102 stories. That's hard to build. And [00:38:02] Kanav Hasija: Wasn't that in the 1950s? I'm, I'm digressing a bit, but to your point about what consumers want, I think it came in after the Empire State in 1950s, which says elevators could not speed up so much. So the hack they did for people to not feel that they are wasting time in elevators is they put in a mirror in elevator so that they can watch themselves comb their hair, do whatever to kind of lose track of time [00:38:22] Jon Wright: Well, that's the most interesting thing for human beings, [00:38:25] Tanmaya Kala: Mm-hmm. Yeah mirrors and, uh, and then, I mean, they, they also put like glass in the elevator so that it just, um, [00:38:34] Jon Wright: Look what I think about is, you know, modern times is Elon Musk, and look how fast they put together their Memphis data center and other facilities. And so I think it's possible. I think if you have the economic motivation, and you have a cooperative jurisdiction and a hard-driving, entrepreneur and development and construction team, I think we could get there again. I think we probably do have some constraints on the supply chain that we'd have to deal with, uh, through some pre-planning, but, uh, which can't just be solved by a great team like doing the building, but has to be... It's kind of a larger systemic thing. But I, I think it's possible again under the right conditions. And we should set a goal to do that.