Latest / Icons of DC Area Real Estate / Bruce Kirsch- Leader in CRE Financial Modeling Education (#129)

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Bruce Kirsch- Leader in CRE Financial Modeling Education (#129) · Icons of DC Area Real Estate

0:00
Speaker A: Foreign hi, I'm John Koh and welcome to icons of D.C. area real estate.
0:14
Speaker B: A one on one interview show featuring the backgrounds, career trajectories and insights of the top luminaries in the Washington D.C. area Real estate market. The purpose of the show was to explore their journeys, how they got started, the pivotal moments that shaped their careers, and the lessons they've learned along the way. We also dive into their current work, industry trends, and some fascinating behind the scenes stories that bring unique perspective to our industry. Commercial Real Estate before we dive into today's conversation, I'd like to share some exciting news. The icons of D.C. area Real estate Podcast is now part of the Iconic Journey in cre, a nonprofit dedicated to supporting professionals at every stage of their real estate careers.
1:07
Speaker A: With our new website, www.ijcre.org, we're expanding.
1:16
Speaker B: Opportunities for everyone in the industry. If you're a student or new to the industry, I encourage you to join the Iconic Journey and CRE community, an exclusive space for learning, mentorship and networking. If you're an early to mid career professional navigating career transitions, our career coaching curriculum provides structured guidance to help you move forward with confidence. If you're an experienced professional looking to give back to the industry, I invite you to consider sponsoring or donating to the Iconic Journey and CRE nonprofit to help foster the next generation of commercial real estate leaders. And for everyone, the best way to stay connected is to subscribe to this podcast, whether directly or on Apple or Spotify so you don't miss an episode. The podcast has been delivering twice monthly episodes since August 2019 and I'm thrilled to continue these conversations under the nonprofit umbrella. Expanding our Reach and impact. To learn more about our community, career coaching or sponsorship opportunities, please visit our new website, www.ijcre.org. thank you for being part of this journey. And now let's get started with today's guest.
2:47
Speaker A: Thank you for joining me for another episode of icons of D.C. area real estate. My guest for today's show is Bruce Kirsch, who is the founder of REFM Real Estate Financial Modeling. For the past 17 years, Bruce has been a leading figure in helping professionals master the art of financial modeling in Microsoft's Excel. This isn't your typical interview. We've got a unique two part format today. In the first segment, we dive deep into Bruce's journey, from his upbringing on Long island and unexpected path through Hollywood and the mutual fund industry to the pivotal moment he found his calling in real estate and ultimately built refm. We'll explore the origins and growth of his company, the challenges he faced, and even his collaboration with the renowned Peter Linneman on the textbook Real Estate Finance and Investments. We also tackle some fundamental principles of financial modeling, including the role of projections amidst uncertainty and how to navigate unpredictable market events. Bruce shares his valuable insights gained from nearly two decades in the field. But that's not all. In the second part of the episode, Bruce presents a case study and delves into the exciting and often perplexing world of AI tools and real estate. He shares his experience experimenting with AI, the current limitations he's encountered, and his dream scenario for how AI could revolutionize tasks like auditing spreadsheets and analyzing deals. We even get into the fascinating discussion with one of our members, Chris, about the potential of AI and multifamily deal analysis and touch upon the groundbreaking work of Khan Academy's AI tool called KhanMigo. Get ready for a comprehensive conversation packed with practical knowledge, insightful perspectives, and a look into the future of real estate financial modeling with the one and only Bruce, Bruce Kirsch. So, Bruce Kirsch, well, welcome to icons of D.C. area real estate. Thank you for joining me today.
5:05
Speaker C: My pleasure. Thank you so much for having me, John.
5:08
Speaker A: For the audience we are this is a unique podcast, so I'm interviewing Bruce for the first hour in the traditional format of the podcast and then the second hour he is going to present a case study as we just spoke about. Before this conversation started, he was attempting to apply some AI tools, but he's going to talk about his challenges with that and what he thinks he could do with some tinkering with AI. We'll talk about that when the case study starts. Let me just start with the interview and thank you for joining me again. Bruce, please share your current role at refm, your company that you started, and your day to day activities, if you would.
5:58
Speaker C: Sure. So I'm Bruce Kirsch, founder of refm, which stands for Real Estate Financial Modeling. I didn't find the discipline of real estate financial modeling. I found the company that's named after that and people have been doing it long before me. And I have made a career over the last 17 years out of helping others to learn how to organize information in spreadsheets in Microsoft Excel exclusively and try to pull insights from the outputs that come from those analyses. And it's a tool, Microsoft Excel. It's not giving us any answers and it's not making any decisions for us. It's serving as a provider of a certain set of data points that come from a particular lens. And we as business people then need to make our own assessment as to, well, how much weight should I give to X, Y and Z? And what are the other factors that can't necessarily be represented in a financial analysis and thus in a spreadsheet? But my day to day is I am running the company and I spin a lot of plates. Everything revolves around this nucleus of financial modeling in Excel, though. So I have a consulting practice, I have a training practice, I have a coaching practice. I have created a suite of tools for sale for people to run their transactions through and raise capital from equity and debt sources. And I also serve as a mentor to those. I always have at least one intern working with me, and I try to give them some insights and skills and tools that can help them rise up a little bit faster. And that's kind of what I do.
8:03
Speaker A: That's great. It's very close to what I do, except mine's a little broader than just financial analysis. But we really appreciate it, Bruce. So let's now go back to your origins. Where did you grow up? And can you share some experiences from your childhood or early life that sparked your interest in real estate and finance?
8:25
Speaker C: Yeah, so I grew up on Long island, and I was fortunate to go to very good public schools. And I was, I think, sort of a typical suburban kid, you know, playing Little League baseball and going to, you know, day camp in the summer and mowing the lawn and those types of things. So I did, however, have some influences in my parents, which at the time I didn't realize, but they were predisposing me somewhat to the idea of working in real estate. My father was a civil engineer and my mother was trained as an interior designer. And so both of those are tangentially tied to commercial real estate and some of the applications and uses. So naturally, at the time, I was ignoring absolutely everything that they said to me about, you know, what was going on at their work or what, you know, types of challenges they were having. But once I started to get interested in real estate, as I was in my twenties, suddenly I was very interested in everything that they had to say. So I think that pretty much par for the course for human nature is there's some saying, I don't know who said it, but probably Mark Twain or Yogi Berra maybe, maybe somebody else. But I said the older I got, the more interesting my parents got. And so that holds true for me. That's great. Yeah. And as far as, you know, what are the things that impressed upon me some interest, helped Me develop some interest in commercial real estate. We were lucky to have living grandparents when we were growing up. And so we would spend a lot of money weekends going to visit the grandparents, driving into Queens and going back out. And so a lot of time sitting in the backseat. This was in the 1980s. There were no iPads, you know, and you just sort of, you could read a book in the backseat or you could just sort of gaze out the window. And a lot of times I would gaze out the window and you know, as you're going sort of into Queens, depending on how you're going, you can actually see the tips of the skyline Manhattan. And so that was always a highlight for me, just to be able to spy those amazing towers that create the skyline and just to gaze out the window and see all these industrial properties and suburban office properties and just to wonder about, well, how do these things work and how much would something like this be worth? I wasn't doing any deep thinking on it, but just being exposed to a lot of buildings through that was probably formative in some way.
11:23
Speaker A: Little side topic talking about that part of Long island in Queens. I finished a book last year that I've recommended to the community as well called the Power Broker by Robert Carroll. If you haven't read that book, Bruce, I highly recommend it. Have you read it?
11:39
Speaker C: I have not. I need to read it. However, I will say I did read the book that you recommended to me a couple weeks ago.
11:47
Speaker A: Oh, good.
11:48
Speaker C: And so I'll be touching upon that a little bit. And I, and I loved it. So I'm, you're, you're my go to guy now for book recommendations.
11:56
Speaker A: I've got a lot of them.
11:58
Speaker C: I, I want to, I want to read more. So I'm, I'm open ears.
12:02
Speaker A: Yeah, well, you know, the book he's referring to is Salman Khan's book, most recent book about his new software called Khanmigo, which ties into his Khan Academy coursework into an AI tool to help search and help with curricula. And I think for your practice, what you're doing, Bruce, I think that would be a real interesting tool to use potentially.
12:29
Speaker C: Absolutely. Yeah. And I will talk a little bit more depth about that later. I've certainly considered it and I keep sort of coming back to the idea of how I can use AI. And we'll talk more in detail about that in a few minutes. Yeah.
12:46
Speaker A: And I'm actually going to use it for this community as well. When I get it figured out. I'm going to play with it a Bit. So what led you to pursue a BA in communication from Stanford University? So it sounds like. Talk about that.
13:02
Speaker C: I was studious. I would say it's fair to characterize me as pretty studious when I was growing up and was very interested also in the visual arts. So I was like the yearbook photo editor. And my mother had a background as a hobbyist painter. So I had influences on the sort of artistic side of things as well. And I think that probably when I saw Raiders of the Ark for the first time, I probably was, I don't know, eight or nine years old. I don't know the year exactly it came out, but to see it.
13:40
Speaker A: Indiana Jones.
13:41
Speaker C: Yeah, to see that in the theaters, I basically wanted to be Indiana Jones, but knowing that was not gonna be possible, I actually wanted to be Steven Spielberg.
13:54
Speaker A: Oh, cool.
13:56
Speaker C: That ambition. And, you know, as a younger person, you don't really know what does it mean to be a director or producer. You just. You have a sense of it. But that was, I think, a very impactful experience for me is. Is, you know, seeing some of his films growing up. And so when I went to school, I pursued some coursework on the visual arts side, and I continued with photography, and I enjoyed it very much, and I had a terrific experience. And I was ready, though, to sort of get out into the world because I. You know what I think? I almost think that a gap year is probably a good thing for three out of four kids because it just gives you some room to breathe and not have to write papers and write papers and write papers and write papers. I know that's how you learn. But you can also learn and mature quite a bit, doing something different for nine months.
15:04
Speaker A: So between high school and college, you took a year off.
15:08
Speaker C: And I've met a lot of people who have done gap years, and I. I find that they're interesting people. And to go into college a little bit older, a little bit more mature as a freshman, I think is a good thing, but so everybody's different.
15:24
Speaker A: So why Stanford?
15:27
Speaker C: Well, because they took me, so. Oh, okay. It was kind of. It was kind of. Well, you can only go to one. So I had a handful of choices. I was lucky. And. Well, if you have been out there, anyone else has been out there, been on that campus, it makes a big impression. Yes, it does. So, you know, you imagine you're 18 years old and you get to go walk onto the Stanford campus. It's like, I can be here for.
15:59
Speaker A: It's magical.
16:01
Speaker C: It's an insanely beautiful place. Right. You Know, perfectly manicured and so on. And so that was a, a determinant is just to, to be in the California sunshine. Right. And, and there in particular. So I was, I was lucky, very lucky.
16:19
Speaker A: And what about your network from that? Was it good?
16:22
Speaker C: Yeah. So in network, no matter where you go to school, you know, network is, is what you put into it. And so I think that just like any other network, if you connect with someone down the road using that as your commonality, it gives you about 10 seconds of their attention. And what you say during that 10 seconds is going to determine whether or not it could turn into something. Right. So it gives you 10 seconds and use it wisely type of thing because you can't keep talking for 20 minutes about how you went to the same school and which dorm, you know, so it gives you an opening. And that's better than not having an opening. For sure, sure, sure.
17:14
Speaker A: So was there anything particularly you picked up there at all with regard to what, what you're doing now?
17:20
Speaker C: To some extent it's a great question and unexpectedly the answer is yes. I say unexpectedly because I was very much on the liberal arts side of the campus and I wasn't really pursuing anything quantitative and that was my choice. You feel very liberated when you're a student and suddenly you can choose your classes, right? That's one of the, the delights of going to college is that you don't get your classes on a, on a, on a page where it says this is what you're taking. It's, well, what should I take? So it's very exciting to be able to choose yourself and gravitate towards your interests. So communication and was one of my interests. You know, that was sort of the closest thing that Stanford had to a hands on filmmaking degree. It was very much not offering that. They had one course where you actually did hands on filmmaking and documentary film. So I eventually took that and enjoyed that very much. But what I did do a lot of was spend time in the photography darkroom, both for taking classes in photography, still photography, and on my own to try to improve my craft. And what I learned through that is stubbornness and persistence to try to create perfection and the importance of presentation and the importance of the ability to communicate and tell a story visually. And I didn't realize it at the time, but all of those things have now manifested in my products and my work and how I help others to do those types of things. Because when you're doing financial modeling, it's very much telling a story. It's A story about money. Sometimes it involves buildings and leases, sometimes it's something that's not in real estate. But you're presenting a narrative. And so that's very much what photography can be about, and certainly film as well, about telling stories and making a case really, for something I've always, at.
19:49
Speaker A: Least I've concluded in my 46 years of doing the business. There are three legs to the stool in our industry. The first is what your major was, communications and negotiations and interplay with people. Second is analytics, which is your other strength. And the third is design form function, the actual physical part of the real estate business. So those you have, you have two out of those three strengths. You can do quite well in our business if you have all three, the ability in all three, you will be a very special person in our industry.
20:28
Speaker C: And to that point, that's actually when I eventually got interested in real estate. That's what really interested me specifically in the idea of being a developer, is just how multidisciplinary it is and how intellectually challenging and stimulating it can be because you're trying to bring together all these pieces and get them to work in harmony with one another. So it's a fascinating career. It's a fascinating field generally.
20:58
Speaker A: No question.
21:00
Speaker C: That idea of being a developer was most compelling to me when I was younger.
21:06
Speaker A: So you, after Stanford, you worked in Hollywood for a while and then you got into the mutual fund business after that. So talk about that trajectory a little bit.
21:16
Speaker C: Yeah, I was a totally lost soul. I'm not going to sugarcoat it. I had no idea what I really wanted to do with my life. But you need a job, you need income. So again, I sort of still had this notion that I wanted to be a film director, producer or something of that type. And so where do you go if you want to do that? You go to Hollywood. Nowadays you can also come to Atlanta because Atlanta has probably, I don't know, the most active studios and know production scene other than Hollywood. But nonetheless, Atlanta is huge for production.
21:55
Speaker A: There's a big part of that. Right. Or at least that's how they got it started, right?
21:58
Speaker C: Yeah, yeah, yeah. CNN and Turner, Turner Broadcasting now the Tyler Perry Studios. And it's. It's an impressive set of operations that they have down in Atlanta. But I basically started out as everybody else does in Hollywood, which is answering phones, and it was not glamorous whatsoever. And I was trying to figure out while I was doing that, you know, is this really what I want to do? And so it's hard to know with little input. And so if you've only been out of school for a handful of months and then you've only been in a job for a handful of months, you don't have a lot of input and you're trying to make this very long term decision. And so, you know, I stuck around for a little while. It wasn't my, certainly wasn't my passion. And then we got to around 1999 and suddenly there was this thing called the Internet, which was something that I experienced while I was at Stanford. They were probably one of the earlier adopters of the Netscape browser. And I used it and it was really sort of neat and entertaining. It's amazing to think that that was only 25 years ago. Yeah, and it's interesting because I kind of feel like that's where we are with AI right now. But you know, the Netscape browser, you would go to pages and the pages would have a lot of text and the text were sometimes hyperlinks that led you to more pages with some text and maybe a picture here or there. It was very, very basic. But as Silicon Valley does, they painted a picture of tremendous, perhaps infinite growth of this medium. And San Francisco was the epicenter of that. And so I was mobile physically mobile physically, you know, young and single. And so I didn't have a lot of stuff. I was like, all right, I'm going to move to San Francisco and to try to see if there's something there, you know, related to the Internet. And so the first thing I did naturally was I needed to figure out how I could have an income. And so I had contact with a friend's older sister, was a recruiter and working for like a headhunter company. And so they said, you know, go talk to her and you know, you can get started. And so I went and did a little interview and then they sort of came back to me a day or so later and they said, yeah, we're going to send you in to interview for some vice president roles. And I thought they were joking. They weren't joking. And I was very young and very inexperienced. And really my skill set at that point was zero technical skills. You know, I could conference three or four people together on a phone call pretty well, but that was about it. And I just didn't get it, you know, why vice president of what? They said, well, you went to Stanford. And you know, I was like, yeah, but you know, it's just a school and you can't put me in front of people for something that I'M entirely unqualified for. So I turned it down because it just seemed so odd to me. Naturally they were headhunters, they were looking to make a fee. So they were trying to just throw people at the highest base computer positions possible and see what's would stick. And in the interim, I got placed at a mutual fund manager which one of the largest in the world, the capital group companies. And so I, you know, the diametric opposite of the Internet business. This is, you know, asset management. Old company started in the wake of the depression and very stable, very predictable type of thing. But I ended up working in equity research on the technology center there. So I was still tied into technology in a way, helping to analyze opportunities in hardware and in software and semiconductor.
26:28
Speaker A: Was this before the tech bust?
26:31
Speaker C: This was before the tech bust. And so then the bust happened and I was promoted and I actually relocated back to Los Angeles. So I was sort of up and down very rapidly, but still the same company. And I enjoyed it, I enjoyed research. But I also felt like this isn't what I want to do for 30, 40 years. Well, what are you going to do? You know, you can keep trying things out or you can maybe go and get a graduate degree and while you're a student, try to figure out your life and then you can point yourself in the right direction.
27:13
Speaker A: Sure.
27:15
Speaker C: And so I said, well, I know I want to be in business in some form, so I don't have a business degree. I had a communication degree, so I needed to get a business education. And so I said, all right, MBA makes the most sense for me. So I applied to business schools and was lucky enough to have some options. And I still didn't know what I wanted to do, that that was my task when I ended up at Wharton and I got to Philly a couple of weeks early and I was in this tiny little studio apartment that I was renting and I like took out a yellow legal pad and I just started making lists about what are the things that I could do two years from now, right. When I come out of this program and I have some business knowledge and so on, what not only would I be qualified to do, but what might I be interested in doing long term? And basically every, you know, consulting, investment banking and product management, everything just basically had a line cross through it until I got to real estate. And the more I started thinking about the idea of urban development and redevelopment, adaptive reuse, and all the while I was thinking about it, I was doing a lot of walks through Philadelphia, which is a fantastic City and seeing all the historic buildings and looking at all the developments that were happening, I felt like I had found my path and so I went in that direction. And I studied real estate at Wharton and was able to get an internship during my summer and eventually come out on the other side and went to work for a developer in Washington D.C.
29:07
Speaker A: So you went to. At Wharton, I assume you developed your relationship with Peter Linneman at that point. I'm guessing you took one or more of his courses.
29:16
Speaker C: Indeed, yeah. So I had Peter as a professor for his famous real estate finance and investments course. And we were using, I think at the time, the first edition of his textbook, which was self published. And it was like magic for me. He's. Peter is a. As in a sort of an electrifying presence generally. And he's in person, he's also sort of an imposing figure. He's quite tall and charismatic. And so it was like awesome. You know, it's just like I, I'm sitting there and I feel like I have the best teacher in the world. And it was exciting and. And it just helped to spur me on even, even more. And I. And yeah, so I met Peter and he was, you know, helping us in the real estate club with some competitions and things like that. And he's always been a tremendous supporter of students and learning and so. But business school is fast. Like you're in and you're out in 18 months. So I didn't, I didn't do any research for him or anything of that nature. It was really just. I was a student of his. He says I was an above average student. I don't know about that. Maybe a little below average. You know, everybody thinks they're average and that's obviously impossible. But he's kind enough to remember me as an above average student.
30:46
Speaker A: So then you went to work for a developer here in Washington. And who was that? What was the situation?
30:51
Speaker C: Yeah, so this was 2003, which, for those of you who did not live through that as adults, was go, go, go, Red hot, almost white hot. Condominium market. Residential condominium market.
31:06
Speaker A: Yes.
31:07
Speaker C: And that's actually exactly what I want to do. I want to do adaptive reuse condos in the city center. And I was able to land this director of acquisitions role at this company, boutique firm, Metropolis Development company. And so that was very late, though. Real estate generally recruits late in the cycle. Like you have people in the second year of business school, they've had. They'll have everything locked up either by the end of the summer in between or by January, like they're done. They're just mentally they're checked out and they're just cruising. And I held out because I really wanted this job type in particular. And I knew I would have to sort of hustle for it. And I didn't get that job, I don't think until like mid April. And we graduated early May. So luckily that that worked out. And it was fascinating. The, the principal of the firm was a former broker, very successful broker, and he had transitioned into development. And I was. Because it was a small firm, you know, privy to pretty much all of the aspects of the business. And it is fascinating, right, to go to meetings with architects and discuss massing for a site and then to talk about interior finishes and put together.
32:32
Speaker A: It's Cliff Bettleson that you're talking about, right?
32:38
Speaker C: Scott Panic.
32:39
Speaker A: Oh, Scott. Okay.
32:40
Speaker C: From previously Studly.
32:42
Speaker A: Okay.
32:43
Speaker C: And. And I, I was loving it. And the market was just getting every day better and better and better. Well, as we all know, the problem with getting white hot is you can't get any hotter than white hot. So one day, from my conversations with the real estate agents that we were working with and others that I knew, they described it as suddenly the phone stopped ringing. So just sort of like this vacuum. All of a sudden they were as busy as they had ever been and prices were going up and up and up and up and up. And suddenly it was just silence. And that was sort of.
33:28
Speaker A: That was late 2007, early 2008.
33:30
Speaker C: Yeah. And that was. And that's. That was the beginning of the descent and a lot of unfortunate chaos in the market. And so I experienced that, which I think it's good, it's very good to experience a downturn early in your career. Not that you can time it or plan it, but if you experience a downturn early in your career, I think it gives some humility as to the fact that everyone, everyone is just a tiny boat on the ocean. And when the water level rises, everyone rises. And when the water level drops, you don't get to just levitate, you're going to go down with it. And you need to have a plan and you need to have resources because the water level can be low for quite some time. And I experienced that with another firm. I was actually working for another firm in Washington D.C. which was establishing a foothold as a New York based firm called the Cleric Group. And they were establishing a foothold in Washington DC. I was one of two executives in their DC office working on entitling an office Building in Bethesda and looking at other opportunities. And unfortunately I was laid off in second round of layoffs. And so there I was in 2009. 2000, yeah, early 2009 and now what? And so I had some severance. Didn't last. I had some unemployment, it didn't last. Obviously you need to have an income. So I was trying to figure out for someone with my skill set which was working in Excel at that point, I had some decent skills to try to value development sites and so on, what could I do that? Because those jobs are gone. All the acquisition jobs are the first ones to get job because you're retreating. The companies are all retreating and trying to preserve value in the assets that they have. And they're not looking to put out money and no one's looking to put out money until finally they are again. And so I thought about this idea of, well, I do enjoy learning and I've enjoyed just casually on the side helping others from time to time with their spreadsheets. And I enjoyed that teaching to help them be empowered. And so I said, maybe I can do some financial modeling, teaching of some sort. And that was the first thought. And then from there I went over to Georgetown and to the real estate club and I said, hey, I have this material that I'd love to present to you guys for an hour, no charge, can I come and do it? And they were foolish enough to say yes. And so I gave them a little, you know, little lesson that I had put together and they said it was really good. And so I did it maybe a couple more times. You sort of teach for free a few times to get feedback and then you can't teach for free forever, obviously. So eventually I worked up the courage to put on a class for which I was selling seats. And I did that at GW in one of their auditoriums and I got a nice turnout and it was well received. And off, off we went. And then from there I went to, to Boston and to LA and to New York and you know, did similar types of college oriented training weekends. And that then turned into an initial corporate training opportunity. And that blossomed over time. And I also had some consulting clients who needed help with a model because they, they had to fire their analysts, but they still needed to fix their spreadsheet, you know, so there was some consulting work available as well.
37:49
Speaker A: And was there an inspiration at all or was just, you know, one day you just said, I think I can do this, or was there somebody that said, you know, Bruce, you have this Skill, you should use this or did anybody ever tell you that, you know, it's something you should do or think about?
38:06
Speaker C: No, not really. Maybe it was just me thinking very highly of myself. Maybe it was. And it was also a little bit desperation. You know, it turns out that, it turns out that starvation and homelessness are fantastic motivators. Okay? So you got to figure something out. That's what I landed on. Luckily it was worth the time and the effort, clearly.
38:34
Speaker A: So let me step back for just a moment. I want to get into a little bit of the roots of financial analysis here before we get into building your business here. So in financial modeling, projections are often a form of educated conjecture, especially in real estate, where market conditions can shift unpredictably. Given that financial analyses rarely align perfectly with actual outcomes. And since you do it for a living, I would like to see if you've ever done a pro forma that actually came true.
39:11
Speaker C: A ten year projection, if I have it. Sheer probability and luck.
39:18
Speaker A: Yeah, right.
39:20
Speaker C: You're 100% correct.
39:22
Speaker A: So how do you view the role of projections in guiding investment decisions despite their inherent uncertainty?
39:32
Speaker C: Well, I like to think about it as a flight plan.
39:37
Speaker A: Okay.
39:37
Speaker C: A pilot's not going to get onto the Runway to lift off without a flight plan. And I also like to think of it as a pre flight checklist. What are all the things that I need to double check before I buckle into the pilot's seat? So I need a plan and I need a very thorough list of critical items and also non critical, yet important items that I need to have buckled up and buttoned up for this to hopefully go well.
40:14
Speaker A: And so how. Yeah, okay, keep going.
40:18
Speaker C: So it's just basically, you know, you need to have a plan. Nobody can knowingly tell a true story about the future, but you need to tell yourself and others some story that gives some analytical overlay of what could potentially happen. And if this happens, then that happens, and if not, then we do this. So no one knows. But otherwise, if you don't put something together, some narrative, some framework, we're all just going to sit on the porch in a rocking chair, Right? I understand that's the alternative is zero forward motion.
41:03
Speaker A: I'm getting to first principles here. So I'm really trying to figure out what's the basis for doing it in the first place. And so how do you view the role of projections in guiding investment decisions despite their inherent uncertainty? And then decision making, I assume is the primary reason, as one has to decide what and where to invest. But looking over my career externalities like one, inflation controls in the 1970s and 1980s, raising interest rates to over 20%. Back then, the SNL crisis in the late 1980s and early 1990s, that actually shut the capital markets down altogether. And then in 9 11, we had no idea whether we're going to be attacked and what that did to impact values of real estate in major cities like Washington and New York. The global financial crisis, which you just talked about, and shut down two large investment banks and basically the capital markets didn't know what they were going to do. At one point there was a lot of uncertainty like I've never seen in the capital markets. And then of course COVID 19 most recently, which was the opposite of all the other crises in that it took demand completely away from real estate. So those are pretty dramatic issues. How do you project for that? I don't think you can. So how do you compensate for those kind of events? I guess is what I'm trying to get to.
42:39
Speaker C: Yeah, it's a great question. And something I said to a colleague as we were in the throes of the COVID 19 before the, before the vaccine had been announced, it was kind of scary. And I said to my colleague, I said, the bullet point that says pandemic is now present on the PowerPoint slide of thousands and thousands of real estate players. Nobody had pandemic on their risks slide prior to March of 2020, I would imagine. Right. Nobody had a bullet point for where we might be wrong, how we might get hurt pandemic. Well, suddenly everyone has a bullet point for pandemic. And over time, as these big shocks happen to the business, I think that slide, which is entitled risks gets more and more bullet points. It does revolve around a couple of different things though. One is the capital markets. And as my mentor Peter Linneman says, real estate is a capital intensive business and there's no denying that. And so anything that is going to impede the flow of capital is going to impact the markets or anything that's going to impact release tidal wave of capital is going to influence the real estate markets. So with that, and now our eyes are open to the physical aspect of real estate. Right? People were not going to the office. Las Vegas was literally shut down. Right between the capital element and the physical element. I think everyone has a better sense of just how fragile real estate can be. Nonetheless, we need to have some plan and try our best to not convince ourselves out of making that investment. Okay. You can always put so much contingency and such negative growth expectations that you say, well, I'm not doing this deal. Right. You could talk yourself into any deal in your analysis. You could also talk yourself out of any deal. Every deal is good at some price and every deal is good at some exit cap rate and growth expectations. You have to do it. You have to do it. But as I said, as those who experience a downturn, whether in the beginning of their career or at any point in their career, it gives some humility. And so if you're doing a 10 year projection and you're saying, well, I'll just grow rents at 3%, say, well, in your experience, have rents really grown consecutively at 3% over a decade or not so much. Okay. And so that realization and the ability to model in stresses on the transaction can allow you to see things with a little more open eyes and understand that if it can be acceptable and sufficient reward in that quote, realistic case where you have ups and downs, then if everything goes that much better, you can handle it. Right. You can handle being wildly successful. But if you're only thinking about the outcome is wildly successful, anything that's below that you may not be prepared for. Right. Such as, you know, taking 90% LTV on a construction loan, those types of things. Right. Just because construction loans are offered at times at, you know, 80, 90% loan to cost doesn't mean you have to take it. The attraction is there. Sure, the temptation is there, but you don't have to take 90% loan to cost. You're salivating at the idea of how your equity returns are going to be boosted and magnified, but nobody's forcing you to take 90% loan to cost. You can say, I'm going to go 70, I want some cushion. And yes, it requires I bring more equity and yes, that's going to require an effort and so on. But that type of consideration and that decision is informed by how things have played out in your experience. And then also just studying the past, studying the shocks in the market that have happened.
47:43
Speaker A: So do you have any kind of tool to input a black swan type event in your projections depending on the length of the projection going forward? Or I mean, do you have a way to kind of do that or is that just an arbitrary, okay, let's kind of look at the history of the pattern of history over the last 20 years and then say in the next five years, I fully expect three years from now we're going to have a recession and we're going to have a liquidity event of some sort.
48:17
Speaker C: Yeah.
48:18
Speaker A: So how should we, Mark, how should we model for that?
48:22
Speaker C: Well, the modeling for that is generally something with a negative number as far as, you know, rent growth. And you're probably also going to get a double whammy with increased inflation at the same time on the expense side. But really the mitigator there is in the ability to ride it out. Okay, so am I levered up so much that I, if I lose a tenant during that time, I'm going to be breaking my DSCR covenants and now I'm in trouble, or do I have enough cushion on my DSCR that even if I lose a big tenant, I'm not going to be in violation and I can ride it out? It's not going to be pleasant. But if you can ride out two years to three years of really terrible conditions, well, you're back into the up part of the cycle by that point. And we know that it's going to improve again. It is proven and so that I don't have any magic tricks for modeling it. But you know, the ability to ride it out sometimes rests upon the term of the loan. Right? So if it's attractive to take a five year loan because it's less expensive, but you really need the flexibility to own that property for 10 years, you could be in big trouble, right? If, if your loan's maturing at year five and there's no debt out there to replace it, big, big problem.
50:01
Speaker A: So, so let's flip back again to the origin and the vision for REFM and how it's evolved since you first started it. You started going to college campuses and teaching courses. So how did you institutionalize the business per se? How did that grow to the point where you now are recognized nationally and, you know, people know who you are.
50:28
Speaker C: Somebody once asked me on the phone, he said, do you do this full time? And I said, no, just seven days a week. Some of it does come down to just a lot of work. It's for anyone who has started a business. It's just there's an endless list and you're wearing a number of hats and you're trying to put out fires and you're trying to grow at the same time. And so the hard work is necessary but not sufficient. You do need some luck. You do need some timing. You need some breaks. You know, one of the breaks that I got was through Georgetown University. Chuck Schill hired me as an adjunct teacher. He saw some promise in my teaching and I, I had never had that on my life path. I also didn't have the being laid off on my know, projected life path. So life's going to definitely throw you some curveballs, and it'll also open up some doors at the same time. And so I, after every training, would try to improve my materials, and I still do it. I've taught some of these lessons hundreds of times, and literally, I always go back to the hotel or back to my office with at least a couple or three bullet points saying, how can I make. How. If I had done these three things, it would have been a better lesson. Let me fix that. My files, all my teaching files are on version 65, version whatever, because I'm always looking to make them stronger and a better tool for the learner. Really, it's not about me giving the perfect presentation. It's about how can you be the most impactful to the learner in a very limited period of time, and how can you leave them with the most valuable set of future references so that when they return to those materials, they still find value in them and they can lean on them with confidence?
52:33
Speaker A: So how did your collaboration with Peter Linneman on the textbook Real Estate Finance and Investments come about?
52:40
Speaker C: So that was a direct result of my being on the adjunct faculty at Georgetown and their master's in real estate program. I was teaching real estate Finance Investments, and naturally, I thought of the book that I learned from. And so I reached out to Peter and I said, I'm going to be teaching and I need a book. And he said, you're in luck. We're still publishing the book. And so I said, all right, going to need, you know, 40 copies or whatever the size of the class was. And that reconnected me with him. And I had great students. Many, many of those students are at tremendous platforms or doing their own things, and they were very bright and they asked some terrific questions. And so I, in trying to teach them to the best of my ability, you know, the first year is tough because you haven't been through your lessons yet, so you have lesson plans, but until they're delivered and you have a feedback loop, you don't know if they're going to be impactful or not. So that first year was probably the most valuable year because people asked a ton of questions, and I had no bank of questions. So, you know, how. How do you rebuild this figure in the textbook? For example, why is this line different? Well, I went to Peter with a collated list of questions, and I told him, you know, some of these are mine, some of these are from my students, and you help clarify and he was impressed at the level of precision and detail that those questions were addressing. And he said, well, you know what, we're actually working on the next edition of the book. Would you be interested in editing it? We're impressed with how closely of a read you and your students did and so on. So obviously I said, of course, that would be an amazing opportunity and an honor. And so, so that's how I got formally connected with the textbook and I edited at least two editions of it and eventually was honored with the opportunity to be co author, and I'm co author now of the current edition with Peter. And it's again, not something that I had ever had on my life plan. You know, it's one of the things you do in business school and the very beginning, you know, you'll be in some sort of leadership class or something and they'll say, you know, your first homework assignment is to, you know, chart out your career for the next 20 years. And so you tell the story about, well, I'm going to go work for a medium sized developer and then I'll go to a larger developer and then I'll go, you know, break off on my own. It's a fiction, just like everything else forward looking is, is a fiction. So serendipity has played a big role in where I am now and I'm grateful for all these opportunities that I've had.
55:36
Speaker A: So how has technology influenced REFM's offerings, particularly with the creation of Valuate software?
55:44
Speaker C: Yeah, so I've always been sort of a tech gadget person. I love the latest stuff that's coming out. I always like to read about it, the new phones, the new this, the new that. It just fascinates me how things are just constantly improving on the technology side. And so in 2011, 2012, I had this idea and this ambition to basically put financial models that we had been working on just as regular Excel files, put those online into the browser and serve as a alternative that was modern and sleek and mobile friendly for making financial projections. And so I raised some capital to do this and I engaged a software development firm and we built a platform that is tremendous in terms of its capabilities and scalability. And we did not have the traction that was on the pro forma, let's put it that way, in terms of subscription, it's not hard to get people to take something for free. It's very hard to get people to take out their credit cards. And so I learned some good business lessons through that. I did, however, have success with an enterprise Customer. I'm now on my 9th or 10th year of the license with this enterprise customer. So that has been a success and widely deployed to the national association of Realtors. So our software actually lives within their Realtors property resource database, which holds. Holds 130 million listings. So on every one of those 130 million pages, you can click a button which says, run an investment analysis with valuate. And that's pretty neat. And they've had, you know, hundreds of thousands of Realtors have put hands on the program over time. So that's. That's something that I'm grateful for. And, you know, even if. Even if you don't. If things don't work out as you would like financially, just knowing that you're helping people solve problems is also gratifying. It is.
58:10
Speaker A: So that's probably the largest impact you've had in the real estate industry. Is that software then? To some extent. Right.
58:16
Speaker C: You know, I think just, you know, sort of sheer volume of individuals. Yes, for sure. No doubt. And I've also trained personally, you know, thousands and thousands of people. People over the years on the commercial side and.
58:33
Speaker A: Right.
58:34
Speaker C: National Association Realtors has some, maybe 10% of those practitioners really work often in commercial transactions. Most of them are residential. So, yeah, I think just having been around for 17 years and, you know, I have actually one student, former. Former student, who, I don't know, maybe even like four years ago or so, ended up being the chief investment officer at Kedler. And I remember when I taught them in 2009, and I was like, wow, isn't that wild?
59:15
Speaker A: That's great.
59:16
Speaker C: At this point, it's fun to see.
59:18
Speaker A: Your alums do really well.
59:20
Speaker C: It's trippy. It's wild.
59:22
Speaker A: Yep.
59:23
Speaker C: So.
59:24
Speaker A: So what significant challenges is Rafm faced and how have you navigated them to achieve growth?
59:32
Speaker C: Growth is tough. And anybody who tells you otherwise either hasn't tried to do it or is just talking about things that they don't know about. Growth is very painful because it's change, and change is very painful. Why do you try to grow? Well, you grow in part to survive and in other parts to offer more and do better and serve clients better. And so I've had different corporate structures over the years, and what I found is that managing people is very difficult and certainly not my skill set. And I'm okay to admit that. And it's also a challenge to keep revenues coming in regularly such that you can operate a business without getting an ulcer while you're in your 20s or 30s, because payroll comes every two weeks. And these are real people depending upon you and they're expecting that paycheck to come. So it can be very stressful when you have people relying on you for their food and shelter.
1:00:56
Speaker A: How large is your team now?
1:00:59
Speaker C: So right now we're at our most lean. So I've always had this big outsourced sort of technology component, but I've also had, and that's there, I mean, I've been with them 15 years. So they're effectively, we're effectively married, but they're not salaried. It's, it's a contract relationship. Right now it's just me on the staff. You're looking at the whole corporate structure and I do actually have my colleague who's an intern here sitting over there. So that's not true. It's not just me. I, as I said, I love to work with interns who are looking to rise up and work hard. So yeah, it's possible to have a company that has market wide recognition and not be a 20, 50 or 100 person company.
1:01:56
Speaker A: That's great.
1:01:57
Speaker C: But everything takes time and everything is a constant maintenance. Anybody who tells you that you can put a business on autopilot and it's just going to keep growing and growing, try it. Okay, now tell me how that turns out. So one of the things that has challenged me over the years is I've been doing this 17 years, I've inspired many others and I have far more competitors now than I ever have on all of the fronts, the consulting front, the modeling tools front, the training front. And that's a validation that you know it is a niche that's worth being in. But when you have competition, naturally you have to focus on specialization, differentiation, improvement. And that's, I think the best thing that you can do is not be in a vacuum to have competitors and to figure out, well, who do you really want to be, who do you really want to serve and how can you be the best at that? And that's the goal, is to improve so you can thrive.
1:03:17
Speaker A: So I'm going to ask one more question and then we'll do the model, if that's okay with you, Bruce. So what advice would you give to individuals aspiring to enter the field of real estate financial modeling today?
1:03:33
Speaker C: My advice is we're human and we make mistakes. And you too will make mistakes and you just need to learn from them. Right? To not learn from a mistake is a big mistake. So even if it's embarrassing, you have to obviously be honest about it. And then you need to surface it so that people know, especially if it impacts others. But maintain some sense of humbleness as you work in these models. And even if you think that you know, well, I don't make mistakes and so on, you do, it's probability, everybody does. And so you do need to put in the hours. There's no substitute for repetitions. If there were, I would be marketing that. You have to just like it's a skill. Right. It's like playing an instrument or playing a sport. You need to observe how it's done. You need to study the ways that people approach it. And then if you want to own that skill and be a success at it, you need to build the skill. And then once you built the skill, you need to keep it sharp. It's a never ending process. I model quite a bit, but even if I'm out of Excel for a week or so and I get back in a little rusty not firing on all cylinders, so, you know, just like playing the violin, if you take a month off when you go back, you're not going to be at the top. You have to always sort of, you always have a little bit of a backslide. So it's a very humbling profession or humbling function because there's thousands of numbers. As we established, probability is you're going to make mistakes. On top of that, all your numbers are wrong. Right. Because it's all a fiction. So it's a challenge though. And if you like the challenge and you like the prospect of solving puzzles, then it could be a good fit.
1:05:44
Speaker A: So I, I lied. I'm going to ask another question, actually. Two more. So what makes you excited as a financial now what is it about? What turns you on about seeing numbers, doing the numbers and then, you know, seeing them work or understanding, oh, look at this trend. Now I understand why I did this or how this works. And then the other one is what emerging trends in the, in real estate, finance and modeling are you excited about? And we then we could get into the model itself, if that makes sense.
1:06:20
Speaker C: Sure. So the thing about a spreadsheet is it starts out blank and it's up to us to populate it. If you don't know what you should be doing, it's hard to know if what you end up doing is good, bad or mediocre. The spreadsheet is the nexus of where your knowledge of the real estate business and transactions comes together with some level of spreadsheet skills and some level of programming skills. If you want to have models that are fully dynamic in nature, we can't forget that all of this used to be done on paper, with pencil, right? All of this used to be done on calculator. And it's just a tool. It's a way of representing inputs and outputs and potential scenarios. And so I think the important thing is to always be increasing your knowledge of the real estate business and the mechanics of transactions and leases and waterfall structures. Ask yourself or someone else why, why is this the convention? Okay, Conventions become baked and become the typical way of doing things. For a good reason, right? And so think about, well, before there were these things, maybe it was done slightly differently and then sort of all converged to this is how it's typically done. Why, nine out of ten times the answer is risk management. But think about, well, what risk to whom, and is the way that it ended up crystallizing in this particular way rational? And it is, in almost all cases, it's rational. It's a way to mitigate risk for multiple parties and keep folks properly aligned. And those are the things that I think keep it interesting and then get reflected in, in the numbers.
1:08:42
Speaker A: Okay, so I'm now going to turn it over to you, Bruce, to demonstrate to us your analytical model and then talk about, and as, as I led into this some AI tools that you experimented with and told me before we started today that you're struggling with. I want to understand why you're struggling with them and then also paint a scenario as to how they could help you in your dream world, how you think, okay, this needs to do the following things to make this really special. Yeah, to help building the pro forma.
1:09:27
Speaker C: So, as we discussed before the call, and let me see if I can share my screen properly here. As we discussed prior to the call, it's promising, this area of AI. It's promising, it's interesting, it's exciting, it's got all the buzz of the Silicon Valley PR apparatus. And. And yet I've been looking into it for the past, you know, three years or so, trying to keep pace with, trying to keep pace with the advances. And I have not come away with a, aha. Compelling use case for it, partly because it's not totally trustworthy. Imagine this. Imagine you are working at a firm and you're introduced to a new colleague. New colleague comes in. You've never worked with them before, but you guys are going to be working together and you get to know each other. Just before the person who introduces you to your new colleague leaves, he says to you, oh, by the way, Bruce, from time to Time. Your new colleague is going to hallucinate, okay? He's going to hallucinate and he's going to be very firm about the veracity of those hallucinations. In what world would I not run, not walk, run in the opposite direction of that job, Right? It's going to come randomly and he's going to pound the table as to this is correct. Okay? So that for me is a big concern, I think, for many others as well. And that's kind of where we are, right? As I said, it's hard to remember, hard to read, hard to believe that the Internet, you know, to the consumer is just 25 years old. Crazy to believe that. I think we're on sort of like this is the year 2000 for AI, right? We're. We're like this is year one, basically. And does the, does the AI industry want you to think that we're so far advanced and everything can be trusted and so on? Yes, yes, they want you to think that. And there's nothing wrong with that. That's marketing, okay? You know, sophisticated business people understand marketing. They understand that the sizzle is being sold. And there may not be a big stake, but there's a lot of sizzle. That's okay, that's fair. But just as an example, you know, all this fanfare and PR announcements and so on when Copilot, Microsoft's ingenious AI is put into Excel. Now you have Copilot in Excel as part of your Microsoft 365 subscription. Oh, okay, great. Let me try it. Okay. I pull up a very simple spreadsheet. This is just one of our figures from the textbook. And I said, well, see what you can do. You know, I'm all for working more efficiently. I'm all for doing less manual keystrokes and less mousing around the page and so on. So help me out, buddy. I just type in to Copilot here, you know, highlight all cells with constants that are numbers, right? So that, that's one of the auditing techniques that I use when I audit someone else's work or my own work is. I'll say, I want to know. Even though there's. There is a color coding convention in place here which shows the inputs are in this bold blue font and outputs are in a regular thickness black font. Perhaps somebody at some point hard coded one of these numbers. Let's say I hard code this number. I want to know before I pass off this spreadsheet as, hey, everything's good. We can trust it. I want to Know if there has been any of that that's happened in the past. And so copilot, please tell me. And it does its thinking and spins its wheel and all that. And after about 90 seconds, it gives me this. It looks like the data may have subsections. I only work with ranges that have a single row at the bottom. Remove the group rows and subtotals and try again. Okay, so I tried to get some help and I didn't get any help. And really, I could have done it in eight seconds. Okay? And aha. Somebody at some point hard keyed a number into the spreadsheet. It doesn't apply to this loan, it doesn't apply to this deal. And this is important. So we need to keep in mind, as skeptical and potentially negative as it sounds, we need to keep in mind that the technology business has a habit of using their customers as guinea pigs. Sometimes it's very impactful, sometimes it's downright deadly. Right. People were actually paying extra for the Tesla autopilot feature so it could drive them into a wall. They were literally paying extra for that. That's insane. But these are the types of things that we need to be cautious about. Okay? We are in charge of our work. We are the ones employed. We are the ones who want to keep our jobs. We cannot blindly trust any of these things. That said, is it all negative? No, it's not all negative. Does everyone like increasing their productivity, increasing their output in their efficiency? Absolutely. Where can AI help us? And by the way, there's other examples of where it's let me down. I've asked it to write formulas for me. I've asked it to explain financial concepts to me. And it's. I've asked it to build macros for me to do some simple tasks and some a little more involved tasks. And I'm like, I'm truly trying, giving it a chance. I'm really trying to see it shine. And it's just fallen short on all of those fronts to date. Not just say that. It'll always be like that. But I'm busy. You're all busy. We only have so much time to fool around with something that isn't helping us. So if you try five times to get a tool to do a job and the tool doesn't do the job after five times, maybe it's not the right tool. Right? Maybe you should abandon the tool. So this tricky thing though is we don't know what we don't know. So if you perhaps are relatively new to financial modeling or to Modeling a certain type of thing, such as a waterfall structure, you can ask for help. It will confidently provide you with some answers. And you can implement that. It'll literally give you formulas in a generic form. You can create named cells and use those as variables and you can carry it out. So it will give you something that sort of ends up living and breathing. But if you don't know that it misguided you on, how do you calculate the preface or how does the promote work? You're just carrying out the instructions. It doesn't know and you don't know. Well, why doesn't it know? Well, hasn't it been trained? Sure, but how has it been trained? Who's trained it? Right. OpenAI and copilot and Claude and whatever else is vying for the spotlight on that particular day were not created for real estate financial modeling applications. They were created for everything. You know, make me a reservation for 6:00 at Murphy's, you know, that type of thing. That, and write me a formula for a waterfall structure. I mean, you, you can expect it to have been equally trained on all of those fronts. So those are some initial, initial thoughts. It's frustrating when you want to leverage a tool and you can't. One of the examples of that is it can do a lot of good grunt work. So it can take, for instance, a list and it can clean up that list. Something as simple as somebody sends you a list of names and emails, right? And they bullet the list. And because they bullet the list, you can't copy the whole thing and just paste it into the field for the recipients. So you drop it into OpenAI ChatGPT instead and you say, remove the bullets. Beautiful, right? It would have taken you 90 seconds to do it. It takes it two seconds. So that's great. That's a win in my book. It could do similar things like pulling comps or leases. Pulling comps for investment sales, taking a rent roll for a multifamily and cleaning it up where it comes out of the property management system. And it's kind of a horror show in terms of how it's formatted cells that are merged and not merged and irregular reporting of some numbers breaking out of the title of a line item onto two lines instead of it all being in a single line. It can do things like that. So that's promising. The data collection is going to give the most benefits to people who have access to those databases, to COSTAR and CREXI and Axiometrics and whatever other comps databases they have. If you don't have access to get past the paywall there, it's not so helpful. I saw recently another application where it could draw a neighborhood map for you. You give it the address of a building and it'll cut a neighborhood map out of Google Maps. And if you're trying to show neighborhood amenities, it'll place the McDonald's logo where the McDonald's is and the Starbucks logo and those types of things. So it can also work with graphics and save time in that regard. And those things are obviously easy to audit. Well, that's not where McDonald's is. And so if you have to fix something, you drag the McDonald's icon over to the correct side of the street and so on.
1:21:45
Speaker A: What about prompting, Bruce? So let me. As you build a spreadsheet, you're prompting it with assumptions, okay? So the inputs are your assumptions from one. So each assumption has a basis to it of some sort.
1:22:01
Speaker C: Right.
1:22:02
Speaker A: So let's assume that you're asking, you know, what is the, what's the rationale behind 3% annual increase in base rent? What's the rationale for the vacancy factor that you have? Where's the data come from that gives you that assumption? And why shouldn't I do some sensitivity analysis to that based on the demographics of the market I'm in? The particular market conditions that the project property has of the type of property is what gives you the assurance that this is the right assumption at this moment on this project? And how does AI maybe help you with that a little bit at least to do a bracketing of assumptions potentially?
1:22:51
Speaker C: Yeah, so it's a great question. And running sensitivity analysis is key to any type of projection because you are, first of all admitting that there are a range of potential outcomes. And you're trying to observe how bad is it if this set of things were to happen, this combination of things were to happen? Again, you can always handle, well, if all these things happen, this is how good it is. You're really, when you're doing sensitivity analysis, you're really trying to inspect the potential downside. How bad does the world need to get for us to really feel pain? And how much pain are we going to feel if we lose, right. Our anchor tenant? And how long is that space going to be vacant? So the more you can give it the model in terms of inputs, the more you can then simulate the potential outcomes. And so you asked about rent growth. You know, the idea of modeling something at 3% rent growth, you know, for 10 years straight is cute, right? It's a cute idea. Unfortunately, that's also how it's taught know even, you know, at the best materials, except for our textbook where we say, you know, bad things do happen. And the case that we use for our property level pro forma modeling is actually a decline. A year after acquisition, there's a decline. And then you restabilize it. Most, most lessons will just show, okay, you buy it at this and up we go. A perfect slope, right? Knowing the historical performance is key. And so if you can have the AI do a historical analysis of, well, what has rent growth actually been. And averaging, it is not really all that useful, frankly, because averaging takes out the volatility, it takes out the peaks and the valleys. Maybe there is an AI application where you can say, you know, plot the equation for the last five years of rent growth and rent contraction and then let's apply that going forward. But let's, you know, increase the ups by 10% and let's make the downs a little more severe by 20%. And it'll sort of clone that line. Not straight line, but it'll clone that curve and then you could apply it going forward. That could be really useful for sure. And again, it's not going to be right, unfortunately. But we're trying to do the best we can to use our experience and history of data to inform what we think is going to happen going forward. As far as prompting goes, this, you said to me the other day that there's actually courses in prompting now, and I was kind of surprised, but also not. It makes perfect sense. There is a most productive way to communicate with these AI interfaces and it's not going to prompt you to prompt it better, unfortunately. So you could ask it a question slightly differently than the first way that you pose the question and you could get back much better data and much better outputs. But you don't know that. You don't know that. You have to fiddle with it. You have to try. You have to cut it a little bit differently. You have to word it a little bit differently. You know, that said, you can also put in to it and you say, I'm going to be writing a prompt for checking out this data series or for analyzing this local market and what's the best way to word the prompt so that I get the best coverage of the geography and so on and so forth, and it can actually help you fine tune your prompt, which is helpful. And again, though some taking everything that comes out the other end with a grain of salt for the newness of it or the Fact that, you know, probably more effort was put into how do we get it to make a reservation for us at Murphy's at 6. Then is this the right way to model the promote in a commercial real estate transaction? Right. Keeping all of that in mind and not expecting too much right now.
1:28:13
Speaker A: So let's put on your dream cap. Looking at this pro forma here, what would you like it to be able to do for you that you can't do by yourself or what would help with making it more effective or efficient for you to do it?
1:28:38
Speaker C: Yeah, I would like to have an AI that I train so that I can give it parameters and share my techniques of, for example, auditing a spreadsheet. It's a very labor intensive task and so I go through a series of steps which I published on my blog before, you know, this is what I do when I order a spreadsheet. I would love for it to be able to go through those seven or eight steps and do all those things and give me a one page report first pass of, you know, these are the things that were identified based on the parameters that you've given us. That would be super helpful. But again, every now and then I'm going to hallucinate. We're still there, we're still in that state of the art. So take it as informative but verify again your job, your responsibility, you want the paycheck for sure. You have to certify, right? You have to certify. By the way, I mean I remember all the tech mania, you know, when I was building value aid in 2010, 2011, 2013, there were so many people putting real estate application, 95% of those companies went away. Okay, same thing with crowdfunding. There was, there were hundreds of crowdfunding platforms. Hundreds. During the frothiness of that, how many left are there? Five maybe. Okay, most of these things are going to go away, especially the ones that aren't well capitalized. So I would say choose carefully about which ones you trust. You know, the, the most ones that we're privy to as the general public right now are all very well capitalized. So you know, bankruptcy of Google I think is a very remote possibility. So you rely a lot on, on their AI. Probably not a big risk that it's going to vanish one day. I would love for it to be able to do that for one and.
1:31:13
Speaker A: Well, what ChatGPT is done, just to interrupt for a second that I've seen is they've actually developed now flavors of AI and I don't know if you've actually looked at it and gone out on their web. But you can come up with almost any discipline and there's now been an AI created for it. So there could be a Bruce Kirsch AI built just as you talked about, and you just need an engineer to help you do it, but you can actually use their software and build it.
1:31:48
Speaker C: That's a very flattering notion. And yes, no, but you're right, you're right. You know, I've, I've learned a few things over 20 plus years in real estate and in teaching that I could communicate as a body of knowledge and it could then carry out in that same style. So it's something that is intriguing, without a doubt. The other thing that I'll tell you is in my sincere search for the killer application of AI in commercial real estate, I have a group of former interns who are all younger folks in their 20s, still working across the business, even at some of the most sophisticated firms. And I texted them last week and I'm like, tell me, what's the most painful thing that you do in your day to day that you would love to offload to an AI, assuming you could trust it, and so on. And the most common response that I got was pulling comps, pulling market data from the various paid comps and data services. But I did also get one from one of the gentlemen and he said, I'd love for it to automate small talk with colleagues. Which is a fair response because it does suck up a lot of time. I mean, if you're just going out to the break room to get a coffee, you just like to go and get a coffee sometimes and not get embroiled in something like that.
1:33:42
Speaker A: How that would apply here? And I'm going to throw a curve at you here, but why wouldn't listening to other people and collaborating on ideas for an analysis. Oh, I hadn't thought about that way of looking at it. And so can you collect those through AI? Different ways of approaching something. So for instance, if you're doing a restructuring of a deal and most of your analysis, I assume, is on stabilized assets and occasionally development deals. But a restructure is a deal that can go 100 different directions. And so it depends on the business plan that you have for the asset. And that can vary all over the place. So you can look at a vacant office building in downtown Washington and say, okay, it doesn't lay out real well for residential, but we can do it. But we have to do the following things to make it make it work, which costs a lot of money and time. Or we can do an adaptive reuse of a different, more functional, let's say all conference space or something like that. Do something different. Maybe lease it to a universe, sell it to a university and they do classrooms in the building or just all kinds. So you have like 10 different scenarios for the same asset that can have a completely different financial outcome. So to me, there's where AI could come in and say, wait a minute, let's look at the probabilities of all these things occurring and what's the best solution among the business plans that we have for this financial analysis? Does that make sense?
1:35:22
Speaker C: Yeah, 100%. And it's a very important point that you make. As you were speaking, I was also thinking about, well, what about if you and I had a meeting at 10, what about if we could put our eyes together prior to the 10:00am and say, discussion, four possible adaptive reuse programs for the building and quantify the irr. And then we walk into the meeting, it's already collaborated. They're collaborated outputs. Now that I think is super interesting. Right. And There are multiple AIs out there that will do floor plans. So you could even say, you know, for the office, you know, make sure you include one for office and for the office one, you know, keeping the office building and office building for the office 1. Give me a typical floor plan layout for, you know, open plan. So you and I could walk into this meeting with maybe four or different programs for the building, some floor plans that can be in a very productive meeting for us.
1:36:52
Speaker A: Plus you'd have cost analysis of all the retrofit in there.
1:36:56
Speaker C: Yeah.
1:36:57
Speaker A: And you have access to the data for costs of each of these things.
1:37:02
Speaker C: Yeah. And so that's very exciting to me. Right. To be able to basically, if we can have our second meeting in the first meeting. Right?
1:37:14
Speaker A: Yeah. Right.
1:37:15
Speaker C: That's awesome. That's awesome. For our productivity, we can have our third meeting in our meeting. Right.
1:37:24
Speaker A: Reverse engineering that. You have to set up assumptions for each one of those four scenarios that you just talked about. Where do those assumptions come from?
1:37:34
Speaker C: This is. This is the problem. Not the problem, but the challenge. This is the challenge. Right. It's just like, it's just like anything else. Garbage in, garbage out, you know, no matter how, no matter how sophisticated the calculator. So I think that the most valuable implementation of these AIs is where your firm has a trove of data for past projects and tremendous insight into construction costing and maybe even in house design and if you can train a private AI with your data, knowing that your data is not going out to the world, not being resold to the highest bidder, but staying internal, staying private. Well, now we have something really interesting because I've got good inputs and I've got someone doing at least the initial heavy lifts to give us a lay of the land. That's really exciting.
1:38:50
Speaker A: You know, it's. The analogy to me is the Bloomberg terminal. When Bloomberg came out, it was the only data source that you had for certain capital market real time learning. To me, if you could build an AI tool like Bloomberg, the Bloomberg thing, it's like, wow, this is, here it is, this is, this is kind of the main thing to have to do this.
1:39:22
Speaker C: And, and I think it's, it's going to come, it's going to come how quickly we don't know. But again, this deal, since I lived through the birth of the pub, the Internet as it was available to the public, that's what today sort of feels like to me on the AI.
1:39:43
Speaker A: Okay.
1:39:43
Speaker C: And that's exciting. That's great.
1:39:45
Speaker A: So we talked about a little earlier before we started an analysis discussion and that is the book that you, that I recommended you last week about Khan Academy's creation of this, its own AI tool called Khanmigo. So what you're talking about, I think is what Sal Khan has already done for Khan Academy to some extent.
1:40:11
Speaker C: Correct. And thank you for that book recommendation. It was very enjoyable and certainly interesting. And yes, just to recap for those who haven't read it yet or don't.
1:40:25
Speaker A: Know the backstory, Brave New Words it's called.
1:40:28
Speaker C: Correct, yeah, Brave New Words. He has created an AI specific to his domain. His domain is primarily elementary education up through college, actually through college now. Okay, so it started out more so elementary, but they've been working their butts off and they've grown and grown and grown and served millions of students. Amazing accomplishment, very inspirational. And yeah, so they, they have essentially these domain specific trained agents or they call them conmigos. And for students, they can query it and discuss with it and it'll even take on the Persona of a historical figure.
1:41:27
Speaker A: And for teachers, for teachers, it builds curricula for them.
1:41:32
Speaker C: Yeah, it's, it's an absolute game changer for teachers. And his grand vision is eventually every student would, could effectively have their own tutor. That is basically the best education that anybody at any socioeconomic bracket could have. It's an entity, happens to be an algorithm, but it's this entity that sort of floats beside you and makes you learn in the most productive possible way. And alerts your physical human instructors to your progress and your gaps so that they can understand where they might need to, you know, add value or clarify. And it's a wild, exciting vision.
1:42:31
Speaker A: It actually coaches you on, it prompts you, it coaches you, it reminds you. It's, it's pretty incredible what it does.
1:42:41
Speaker C: Yeah. And so, yeah, so we could, we could be, you know, going towards something like that for. Or commercial real estate, some variation of that.
1:42:54
Speaker A: So I'm going to open up for questions. I already got one here from Chris and Chris, why don't you come on live, turn on your, turn on your areas. Chris, go ahead and ask Bruce, sorry.
1:43:05
Speaker D: I just had a question about the Khanmigo. Sorry I joined a little late, I was in some meetings. But is that an active product that's fully functioning right now?
1:43:12
Speaker A: It is, yes.
1:43:13
Speaker D: So that's incredible.
1:43:14
Speaker A: Go out on Khan Academy's website and just look up Khanmigo and you can actually play with it and you could teach it what you want to do, to do. And it would take this application. You have to teach it though and have to know what to. As Bruce said, you couldn't ask Khan Nigo to find a, promote by downloading a spreadsheet, I don't think.
1:43:41
Speaker C: No, I actually just went in right before the call to see if they had anything real estate related. They have some financial literacy subject matter but they don't have currently, you know.
1:43:54
Speaker A: You could do net present value, you could do simple finance.
1:43:57
Speaker C: Yes, simple. Yeah. Time value of money. It certainly, it certainly has those types of things for sure. Yeah. Amortization, it'll, it'll teach you how amortization works.
1:44:08
Speaker D: But I mean how high of a grade level does it go?
1:44:12
Speaker C: I think through college. Yeah.
1:44:15
Speaker A: Oh yeah, it's incredible.
1:44:17
Speaker C: It's wild.
1:44:19
Speaker A: Just about every discipline you can think of too. Philosophy, economics, history, math, geometry, you know, calculus, advanced mathematics to advanced calculus, even to you know, number theory and you know, some more advanced mathematical tech. I mean that's his background is engineering so I don't know if he gets into structural engineering and all those kinds of things. But it's, it's pretty amazing. And Khan Academy is built, you know, it's all a non profit so everything's free, everything's incredible.
1:44:52
Speaker D: Yeah, I mean deep learning, no answers. I think that's probably the most like integral part of it that makes it unique. I mean with chat GPT, I use it all the time for, I mean I definitely resonate with what you said about like automating, like small talk with colleagues, but I think it plays one. I mean, I work at a smaller firm where it's up five of us and we're handling all these assets. And one of the more pivotal, pivotal things that we, that ChatGPT provides in my everyday is being able to automate, like, hey, write this email, you know, where I don't have to spend. It can be professional and I don't have to put too much brain power into it or doing my analyses and then being able to have it write a draft to. Then I formalize to final submission. And it definitely makes things far more efficient.
1:45:46
Speaker A: Well, I'm recording this podcast and in the background, Zoom has an AI tool. I will get a full summary of this entire episode in writing right after this episode is over. And that's a great AI tool for me for note taking. I never have to take notes again.
1:46:06
Speaker C: Exactly. It's. It's that. That's a huge value added. In fact, I, I do, for my refi certification course, I do office hours and some learners, if they can't make it, they will literally send their AI in their place. And it then shared the transcript back to the group. And I was, the first time I saw it, I was blown away.
1:46:34
Speaker A: Yeah.
1:46:37
Speaker C: And you could, you could base like a video, you could scrub to certain places in, you know, in the conversation. You could search the conversation for keywords. Wow, that is amazing.
1:46:52
Speaker D: And the one thing otter, I utilize OTTER as well. I think mine joins your open hours.
1:46:58
Speaker C: John, all the time.
1:46:59
Speaker D: Basically what it'll pop out is also the action items. So I'll have it join a lot of my checkup meetings, my weekly checkup meetings. And it'll send, I, Lindsay needs to do this, this and this. And then I'll input it into our like project tracking system and then allows to just have everything fed to me. And I think it takes away kind of the needing to remember component of it out.
1:47:25
Speaker A: So, Chris, let's, let's do. I'm. Let's do have some fun here. Do a little case study as to what we think AI could do for the future. So you're in the multifamily space, right? So you're buying. So let's say you get a deal in. You're looking at it. So you get a basic set of facts. It's an existing property. You've got a historical operating statement, you got financing, you've got the current operating. And then you have to decide, okay, this market is good. And I'm optimistic about it. So I'm going to put this one set of scenario in that I think is realistic, but I'm also worried that there's going to be some major issue coming up in the market. So I'm going to throw another set of scenarios. And so let's say you come up with three or four different scenarios and as Bruce said, you ask before you have your first sit down with everybody else, you ask it to ask to prepare four different, you know, pro formas for you and then sit down and, and then have a comparative analysis among the four as to what the pluses and minuses of each each of them are. And it tells you that narratively also compares them in a narrative analysis before your first meeting on the deal. So that.
1:48:46
Speaker D: Yeah, yeah, I, my, I mean my concern with that is, I mean with us being kind of the smaller guy in a lot of these ponds that we're in, I think the concern is that it takes away a lot of the margin in which we, we plan. So I think what it. Since it's an algorithm, I imagine they'd have to be proprietary and calculated to whatever you would want it to be. But my, if everyone's asking the same type of device. So like let's say John, you were to come out with some sort of algorithm and it underwrites deals. My concern is that every single person that utilizes your service that puts those documents into the system will theoretically come up with a similar answer. So it takes out.
1:49:29
Speaker A: Depends on the assumptions though. So if you have different assumptions.
1:49:33
Speaker D: Yeah, but that would just be my general like concern with that. I think in the short term I like, I think it will get developed one day inevitably. However, I think in the short term I think a utilization of it is, is universalizing the data because when we get a lot of data it'll come in like 20 different formats. Especially if it's some of these secondary not seconds like these third party sites like Real Page where they spit it out in like a disgusting format and you have to send it off to send it off overseas and they, they scrub it within the day and they send it back. I think a lot of those things it'll, it'll serve a lot of utilization. I also think what it can do is formalize a lot of the information in which you're gathering or creating in a more digestible format for people. Because although I feel like I'm very strong in like my personality or my weight ability to portray information, I've dealt with other people in the industry that aren't necessarily as strong in that. And being able to formalize a lot of these reports or these pro formas or create a very digestible document for someone might be also very like good use.
1:50:48
Speaker A: What's your reaction to that, Bruce?
1:50:52
Speaker C: Sorry, say it again.
1:50:53
Speaker A: What's your reaction to what he just said?
1:50:56
Speaker C: I'm on board. I'm on board. Yeah. I mean I've heard some applications of people who aren't native English speakers. Right. Or maybe you want to invest in a Spanish speaking country and you're trying to attract investors who are in that country. Well, you better have a nice investment memo in Spanish. That's just mind blowing. And I think that's here at our disposal now, which is just tremendous. I think at the end of the day what this is going to do is in some small way help people get better clarity on opportunities and risks more quickly and that turns into a more liquid market. So anything that we do and apply to real estate practices and analysis practices that ends up making the market more liquid benefits everyone.
1:52:07
Speaker A: Okay, so we're coming close to the end. Any other questions you have, Chris, for.
1:52:14
Speaker C: For Bruce right now?
1:52:16
Speaker D: No, I'll definitely be looking into taking the course and then. Yeah, I mean that's, I don't really have any more questions. I will digress though. You stated that it's good for individuals that don't necessarily speak the same language. Otter has like a real time dictation and my, my grandfather can't hear because he's deaf now and we literally just put it on the table in front of him and then he listens to us talk or reads everything that we have with like real time subtitles.
1:52:48
Speaker A: That's great. Yeah, weird digression, but that's cool. So Bruce, can you conclude now and let's talk a little bit about your company's services and do a little advertisement here a little bit for your service. You know, what you're offering with regard to a discount on taking the courses. And also, you know, let's assume that some people have taken or planning to take the free analytical thing. What's the next step once they get the results from that? They have to, they get to choose. Go ahead and talk through that if you would.
1:53:27
Speaker C: Yeah. So we provide training and tools essentially and also consulting services. So on the training front it's self study in nature, self paced and we have basically everything that you need to go from I need to understand the foundations of the commercial real estate business to I need to build my Excel skill set to I want to have A good mind for framing and investment opportunity and being able to look at investments and analyze them. And so that's, that's really what we are, you know, offering. And sort of the apex of that is our refi certification program. So this is what I'm showing here. We are offering a special discount. Did you share the code with them or not yet?
1:54:23
Speaker A: I thought I did, but go ahead and put it up.
1:54:25
Speaker C: I, I'm pretty sure it's the word iconic, but.
1:54:28
Speaker A: Iconic, yes. Yeah, yeah, that's the code. So they just put that in as they register for the course.
1:54:33
Speaker C: Yeah, as you enroll. And there's just a tremendous amount to learn. I think this session, we should do it again next year this time. And there could be a very different conversation that we're having, you know. Yeah, you don't need to hear about my background a second time.
1:54:50
Speaker A: Right.
1:54:50
Speaker C: No, we could, we could dive right into the state of AI.
1:54:54
Speaker A: I wanted to ask one because I haven't dived into your software too deeply. But let me ask you at a high level, the depth of what you have in place. So, you know, I look at, because I was a real estate analyst for 25, 30 years, so I, I've not seen every structure, but I've seen a lot of them and I'm going to guess there's some you haven't tackled. Like for instance, tax exempt bond analysis on multifamily, for instance, which is a unique process and unique underwriting net present. You know, I was in the CTL business, so I don't know if you're familiar with the credit tenant lease analysis business where bonds are used for real estate acquisition. And it's a, it's a very unique spreadsheet that the firm I work for, we developed, but it's based on credit, et cetera. So it's an interesting analysis. And the other one is how detailed you are on mixed use development projects where you have four different uses in one asset that you're looking at. You have that tool.
1:56:07
Speaker C: So I had the pleasure and honor of building the financial model for the Wharf.
1:56:17
Speaker A: Oh, okay. There you go.
1:56:20
Speaker C: That was actually sort of our big, our first big engagement and boy was it big. And so through that process learned that one size definitely doesn't fit all for these major mixed use projects. And so the way we built, we built our tools, our Excel templates is they're all purpose built for that property slash transaction type. And then if we have something where it's going to be multiple property types, we merge them together in a custom Way everything has to be custom to try to build the sort of off the shelf mix major mixed use template. I. It can be done. Anything can be done. But they're always just so specific and.
1:57:14
Speaker A: And you're just layering worksheets on top of each other. In essence.
1:57:18
Speaker D: Yeah.
1:57:18
Speaker C: And very, I mean this model was some, it was 110 tabs by the time we were done, but. Oh my God, that, that unlocked an 850 million dollar construction loan for them. So, yes, it was worth it.
1:57:33
Speaker A: Well, I, look, I was up in New York City last weekend and I walked through Hudson Yards. I don't know if you've seen that project.
1:57:41
Speaker C: Oh, yeah, I've been there many times.
1:57:42
Speaker A: I mean, that model had to have been equally, if not more sophisticated than the warps model.
1:57:52
Speaker C: Sure. Yeah. It's a lot of moving parts, as I like to say. Just like a tuxedo.
1:57:58
Speaker A: Yeah, yeah. So in essence, it's an assembly of just a lot of spreadsheets. In essence.
1:58:05
Speaker C: Yeah. There's. I mean, we have it at this point. We have our own questionnaire. If someone's doing major mix use, we'll send you a questionnaire with. We did everything the long way and the hard way on the wharf because it was the first time.
1:58:17
Speaker A: Right, right.
1:58:18
Speaker C: Coming out of that, we're like, we should have asked these 15 questions on the front end.
1:58:22
Speaker A: Sure.
1:58:23
Speaker C: So we actually have that and we give it to people before we even start to discuss with them.
1:58:30
Speaker A: So do you get into, let's just say that you're in, you're a CW Capital or a firm like that that's in the CMBS B piece buying business and they're looking at financial analysis of properties that are underwater and trying to figure out what valuations you're going to look at to come out the other side of a deal. And how do you create, you know, a value proposition to a prospective buyer of bond issues? Are you into that at all or not? Or is that a.
1:59:03
Speaker C: That's not, that is not my domain. No.
1:59:05
Speaker A: Yeah. And that's not more of a securities analysis potentially than it is a real estate analysis. Okay, got that.
1:59:12
Speaker C: This is one of the things that I tell people is that know, God willing, health permitting, if you want to work in real estate for 50, 60 years, have at it. And during that time it'll probably take you that entire time to, quote, have seen it all and then some. And then some. Right. Don't, don't think that there's nothing, nothing more to learn after you've been in the business 10 years. You just don't know about all of these specialty areas and all of these other niches and.
1:59:45
Speaker A: Right.
1:59:45
Speaker C: Financing permutations and combinations that could exist or do exist. It's a fascinating business and it's a challenging business. And you can always find something new to learn, without a doubt.
2:00:02
Speaker A: Okay, Bruce, I'm going to wrap it up now, but I would like to give you the opportunity to share, you know, your observations over the past 17 years doing what you've been doing, and then your overall perspective of the real estate industry itself, if you can.
2:00:22
Speaker C: Yeah, so when I first, when I was working for the developer in between the two developers that I worked for, I tried to go off on my own with a partner and do some smaller entrepreneurial housing ventures. And I was the more analytical of the two involved. And so I really, really, really leaned on Excel and I wanted clarity. And I think that's what everyone is trying to get, is future clarity. Right. But you can't have perfect clarity. You never have perfect information at the time. And so it gives us great comfort to be very precise as humans. But never forget that, as Peter Linneman says, being right to the penny and off by millions is not really helpful. So there is a point of diminishing returns as we try to say, well, let's make the model more detailed and more detailed and more line items and more inputs. And first of all, just for usability purposes, it becomes cumbersome, Right. If, if I make 20 inputs or I make 60 inputs, how much more accurate is it having made 40 more inputs? Probably not a lot if you, if you really, you know, play it out. But there's always a, a place in there where people are most comfortable, and that's their prerogative, and they should do what's comfortable for them and builds confidence for them. As far as, you know, the real estate business, again, it's a tremendous opportunity. It's very multidisciplinary. There's a million ways to make a million dollars in real estate. Most important thing, as in any business, is your reputation. And so, as we know, there's going to be ups and there's going to be downs. If you lose all your money but you keep your reputation, you can come back. If you lose your reputation, a heck of a lot harder to come back. And you have to think decade in decades. Right. You have to think in decades. Because unless you want to stop, keep going, make more money, do more interesting things, make a bigger impact and so on. The thing that follows you throughout everything is well, what do people think about you? That conversation happens a lot, then we don't even know about. Happens behind everyone's back before opportunities either present themselves or don't. You know, people want to know, is this person trustworthy? Are they moral, are they ethical, how aggressive are they? Those types of things. And that's sort of what I'll end with is at the end of the day, all of these calculations and the attempts to tell a story about properties and money and leases, it's about trust. And so do your best with the tools that you have or find the best tools for you. But you're trying to create trust for your investors, you're trying to create trust for those who are lending to you. And trust comes from doing things in a predictable manner, again, again, again and again, even if it's not pleasant. And trust is worth more than anything.
2:04:17
Speaker A: So I usually ask one more question to all my guests and you may have just answered it in your own way, but I'm going to ask it anyway. And then you can put whatever you want on it. But if you could put a sign on the Capitol Beltway for millions to see, what would it say? Bruce?
2:04:40
Speaker C: Wow. And what's the goal of the sign?
2:04:45
Speaker A: Well, it's your message to the world, basically. So what, you know, or to the people what, listening. Some people say thank you for, you know, all your. My experience in the industry or other people, you know, more of a personal message. Other people might say, like Bob Murphy of MRP said believe. He said believe. So, you know. Yeah, famous television character came up with that one.
2:05:16
Speaker C: So, yeah, I think I, I think I would say if you lived here, you'd be home by now. Just kidding. I think I'd say don't take yourself too seriously.
2:05:25
Speaker A: There you go.
2:05:26
Speaker C: Because for anyone who's run a business or worked for a while, there's going to be good times, there's going to be less good times. You got to be able to laugh at yourself. You have to be able to laugh at your situation and persevere and hopefully it's more goods than bads in terms of experiences. But nobody's immune to the height of the water. And you'll survive if you have a plan and the willingness. So some things you just have, you have to laugh off and keep moving.
2:06:09
Speaker A: Great. Well, thank you, Bruce. On that note, and for those listeners, take a look at the show notes, I will once again put all the data in about Bruce's courses and the links, etc. For you to hopefully join up to take his course and learn. So thank you, Bruce.
2:06:29
Speaker C: Appreciate you so much.
2:06:31
Speaker A: Really me today. Yeah. This has been fun. Thanks a lot. Have a great day. Take care. Bye.