1 00:00:02,740 --> 00:00:04,420 Speaker 1: Bloomberg Audio Studios. 2 00:00:04,880 --> 00:00:06,420 Speaker 2: Podcasts. Radio. 3 00:00:06,850 --> 00:00:07,290 Speaker 3: News. 4 00:00:10,950 --> 00:00:13,750 Speaker 2: Hello and welcome to the Money Stuff Podcast. This week 5 00:00:13,770 --> 00:00:15,650 Speaker 2: we have a rerun of an interview that we first 6 00:00:15,730 --> 00:00:19,490 Speaker 2: aired back in May 2025. It's a conversation that Katie 7 00:00:19,510 --> 00:00:22,300 Speaker 2: and I had with Ryan Patch and John Seale, the 8 00:00:22,320 --> 00:00:25,180 Speaker 2: guys who run Midnight Madness, the huge overnight puzzle hunt 9 00:00:25,220 --> 00:00:28,520 Speaker 2: across New York City. Midnight Madness is happening again in 10 00:00:28,540 --> 00:00:30,980 Speaker 2: just a couple of weeks on October 10th, So we 11 00:00:31,000 --> 00:00:34,099 Speaker 2: thought it was a perfect time to revisit this conversation. Enjoy. 12 00:00:34,120 --> 00:00:38,880 Speaker 2: I feel like it's going to be weird to do 13 00:00:38,900 --> 00:00:43,590 Speaker 2: an intro, but like, it's the Money Stuff Podcast. We're 14 00:00:43,600 --> 00:00:46,610 Speaker 2: here today with, I think, our second episode with a guest. 15 00:00:46,810 --> 00:00:47,030 Speaker 3: Yes. 16 00:00:47,050 --> 00:00:47,750 Speaker 2: With two guests. 17 00:00:47,870 --> 00:00:49,089 Speaker 4: Our second and third guests. 18 00:00:49,190 --> 00:00:52,270 Speaker 2: Second and third guests. They are Ryan Patch and John 19 00:00:52,310 --> 00:00:56,710 Speaker 2: Seale of the Great Gotham Challenge, two creators of puzzle hunts. 20 00:00:56,730 --> 00:00:57,610 Speaker 3: Welcome. 21 00:00:57,630 --> 00:00:57,990 Speaker 2: Welcome. 22 00:00:58,510 --> 00:01:00,850 Speaker 1: That's about all you need to say. We make puzzle hunts. 23 00:01:05,500 --> 00:01:09,220 Speaker 2: We got in touch because I am a degenerate puzzle 24 00:01:09,240 --> 00:01:14,319 Speaker 2: hunter in my way. And Ryan and John are taking 25 00:01:14,440 --> 00:01:17,959 Speaker 2: over or sort of have taken over the big financial 26 00:01:18,000 --> 00:01:20,620 Speaker 2: industry puzzle hunt that I have done occasionally, which is 27 00:01:20,920 --> 00:01:24,679 Speaker 2: sometimes called Compass, but is mostly called Midnight Madness and 28 00:01:24,740 --> 00:01:30,060 Speaker 2: runs overnight this year in October. So welcome, John and Ryan. 29 00:01:30,240 --> 00:01:31,240 Speaker 2: Thank you. Happy to be here. 30 00:01:31,620 --> 00:01:33,840 Speaker 1: Coming soon to New York City street near you. 31 00:01:34,900 --> 00:01:39,630 Speaker 2: This is a podcast probably about money, stuff related to money. 32 00:01:40,250 --> 00:01:41,270 Speaker 4: That's what we bill it as. 33 00:01:41,730 --> 00:01:43,330 Speaker 2: It's not always true, but that's kind of what we say. 34 00:01:43,810 --> 00:01:46,610 Speaker 2: And it has a listenership that includes a lot of 35 00:01:46,650 --> 00:01:51,200 Speaker 2: financial industry and tech industry people. And the overlap of 36 00:01:51,240 --> 00:01:54,500 Speaker 2: that audience with people who do puzzle hunts is meaningful, 37 00:01:54,860 --> 00:01:57,910 Speaker 2: but it's not perfect. by any stretch of the imagination. 38 00:01:58,490 --> 00:02:00,970 Speaker 2: And so I kind of want to explain what a 39 00:02:01,030 --> 00:02:04,360 Speaker 2: puzzle hunt is. And I feel like you guys might 40 00:02:04,440 --> 00:02:06,680 Speaker 2: say that you're something other than puzzle hunt guys exactly, 41 00:02:06,920 --> 00:02:09,020 Speaker 2: but I really want to explain what puzzles are. So 42 00:02:09,639 --> 00:02:11,280 Speaker 2: can I prompt you with that? 43 00:02:12,320 --> 00:02:17,220 Speaker 3: I think sometime in the 90s, maybe before the MIT 44 00:02:17,240 --> 00:02:20,520 Speaker 3: Mystery Hunt started, I got the sense that that is 45 00:02:20,580 --> 00:02:23,799 Speaker 3: the beginning of the industry that we are weirdly a 46 00:02:23,820 --> 00:02:27,050 Speaker 3: part of, largely by accident, I would say. because when 47 00:02:27,090 --> 00:02:30,390 Speaker 3: Ryan and I decided to start designing puzzle hunts, we 48 00:02:30,410 --> 00:02:32,910 Speaker 3: weren't aware of any of the existing ones. We thought 49 00:02:32,950 --> 00:02:35,410 Speaker 3: we were making something that no one had ever heard 50 00:02:35,450 --> 00:02:39,549 Speaker 3: of before. A puzzle hunt, in definition, doesn't have to 51 00:02:39,590 --> 00:02:41,960 Speaker 3: be location-based, but in our case and in many cases, 52 00:02:41,980 --> 00:02:46,160 Speaker 3: it's a location-based hunt in which people travel from place 53 00:02:46,200 --> 00:02:49,600 Speaker 3: to place, solve a complex puzzle, and by puzzle, I 54 00:02:49,639 --> 00:02:52,500 Speaker 3: don't mean jigsaw puzzle, but they receive a series of 55 00:02:52,600 --> 00:02:55,360 Speaker 3: clues and pieces of information that that have to be 56 00:02:55,419 --> 00:03:00,340 Speaker 3: combined in some way and thought of laterally in order 57 00:03:00,440 --> 00:03:04,739 Speaker 3: to yield a solution. And that solution will often take 58 00:03:04,780 --> 00:03:07,560 Speaker 3: them to a new place and they'll kind of repeat 59 00:03:07,580 --> 00:03:11,079 Speaker 3: that process. Maybe people are familiar with the amazing race. 60 00:03:11,100 --> 00:03:14,560 Speaker 3: It's combining elements of something like the amazing race with 61 00:03:15,150 --> 00:03:20,310 Speaker 3: elements of an escape room and all into a competition 62 00:03:20,350 --> 00:03:24,200 Speaker 3: in which people are competing against each other Most of 63 00:03:24,240 --> 00:03:27,520 Speaker 3: the time in small teams to prove their mettle and 64 00:03:27,740 --> 00:03:30,850 Speaker 3: arrive at the end first or with the highest standing 65 00:03:30,870 --> 00:03:31,389 Speaker 3: that they can. 66 00:03:31,970 --> 00:03:34,290 Speaker 2: I became aware of puzzle hunts before I became aware 67 00:03:34,310 --> 00:03:36,650 Speaker 2: of escape rooms. And I don't know if that's like 68 00:03:37,370 --> 00:03:40,110 Speaker 2: the actual chronology in the world where like people invent. 69 00:03:40,130 --> 00:03:41,190 Speaker 4: It's not my experience. 70 00:03:41,670 --> 00:03:43,820 Speaker 2: Yeah. Well, puzzle hunts are pretty niche. 71 00:03:44,150 --> 00:03:46,480 Speaker 1: Yeah, escape rooms came after puzzle hunts. 72 00:03:46,680 --> 00:03:48,360 Speaker 2: Yeah, that's what I thought. They sort of grew out 73 00:03:48,380 --> 00:03:50,200 Speaker 2: of the puzzle hunt idea and you could put an 74 00:03:50,240 --> 00:03:52,200 Speaker 2: escape room in a place and sell it to people 75 00:03:52,240 --> 00:03:54,000 Speaker 2: every day rather than do it once a year. 76 00:03:54,300 --> 00:03:57,920 Speaker 1: And escape rooms are definitely a little more consumer-oriented, whereas 77 00:03:58,000 --> 00:04:01,470 Speaker 1: a puzzle hunt, you have to be a certain glutton 78 00:04:01,490 --> 00:04:05,030 Speaker 1: for punishment or at least intellectual stimuli. Escape rooms are 79 00:04:05,050 --> 00:04:06,570 Speaker 1: great because you know at the end of 60 minutes 80 00:04:06,590 --> 00:04:09,410 Speaker 1: you're done, whereas a puzzle hunt, if you fail, you're 81 00:04:09,610 --> 00:04:13,040 Speaker 1: floundering in the middle of some urban landscape trying to 82 00:04:13,080 --> 00:04:14,020 Speaker 1: figure out where to go next. 83 00:04:14,740 --> 00:04:15,490 Speaker 2: At 3 a.m. 84 00:04:15,540 --> 00:04:15,810 Speaker 4: Often. 85 00:04:16,170 --> 00:04:18,070 Speaker 3: But you know what I would say is that I 86 00:04:18,110 --> 00:04:22,650 Speaker 3: think escape rooms and puzzle hunts share an origin story, 87 00:04:22,830 --> 00:04:25,869 Speaker 3: I would guess, which is that it's people saying, what 88 00:04:25,890 --> 00:04:27,650 Speaker 3: if we could be in a video game in real life? 89 00:04:28,000 --> 00:04:30,719 Speaker 3: So it's kind of taking this idea of a quest 90 00:04:31,120 --> 00:04:34,580 Speaker 3: and something to be solved and creating a real life 91 00:04:34,620 --> 00:04:35,560 Speaker 3: experience around that. 92 00:04:36,220 --> 00:04:36,460 Speaker 2: Right. 93 00:04:36,680 --> 00:04:36,860 Speaker 1: Yeah. 94 00:04:37,290 --> 00:04:40,670 Speaker 4: What differentiates a puzzle hunt from a scavenger hunt? Or 95 00:04:40,770 --> 00:04:42,490 Speaker 4: is that just a meaningless distinction? 96 00:04:42,510 --> 00:04:43,870 Speaker 2: Is it the puzzles? 97 00:04:44,690 --> 00:04:45,190 Speaker 1: Absolutely. 98 00:04:45,470 --> 00:04:47,530 Speaker 4: You get clues and you have to think critically in 99 00:04:47,589 --> 00:04:48,290 Speaker 4: scavenger hunts. 100 00:04:48,610 --> 00:04:51,080 Speaker 1: There's definitely a blurry line between the two. But I 101 00:04:51,120 --> 00:04:54,260 Speaker 1: think that the puzzle hunts are often once you arrive 102 00:04:54,300 --> 00:04:57,500 Speaker 1: at a location, you're not just there to find something. 103 00:04:57,900 --> 00:05:01,620 Speaker 1: You're there to solve a complex situation. And there's pen 104 00:05:01,660 --> 00:05:04,339 Speaker 1: and paper puzzle hunts. where you just like go to 105 00:05:04,380 --> 00:05:06,520 Speaker 1: a location and you're given a few pieces of paper 106 00:05:06,960 --> 00:05:11,640 Speaker 1: and they're all kind of these very crosswordy or language-based 107 00:05:11,740 --> 00:05:14,900 Speaker 1: or math-based puzzles that you wind up solving. And then 108 00:05:14,920 --> 00:05:18,810 Speaker 1: they result to a keyword or often the next location 109 00:05:18,820 --> 00:05:19,820 Speaker 1: that you're going to. And then you go to the 110 00:05:19,850 --> 00:05:21,730 Speaker 1: next location, you get handed another set of papers. So 111 00:05:21,750 --> 00:05:25,430 Speaker 1: there's always some very specific activity. Now, we came kind 112 00:05:25,450 --> 00:05:27,409 Speaker 1: of this from more of the immersion angle. We kind 113 00:05:27,450 --> 00:05:30,050 Speaker 1: of asked ourselves the question, what would it look like 114 00:05:30,130 --> 00:05:32,870 Speaker 1: if people felt like they were in a movie? And 115 00:05:32,910 --> 00:05:37,250 Speaker 1: then we started creating these quests and then we realized, well, 116 00:05:37,270 --> 00:05:40,110 Speaker 1: to kind of unlock the door that kind of lets 117 00:05:40,130 --> 00:05:41,609 Speaker 1: you into the next thing, there needs to be a puzzle. 118 00:05:42,070 --> 00:05:44,060 Speaker 1: And so we kind of came at it from a 119 00:05:44,070 --> 00:05:47,040 Speaker 1: little more of a, an angle saying, well, we need 120 00:05:47,080 --> 00:05:48,940 Speaker 1: to have a key for that door. We need to 121 00:05:48,980 --> 00:05:52,560 Speaker 1: have a password for that door and started slowly integrating puzzles. 122 00:05:52,600 --> 00:05:54,640 Speaker 1: So we kind of backed into the puzzle hunt community 123 00:05:54,860 --> 00:05:58,210 Speaker 1: from more of like an immersive angle. Whereas the puzzle 124 00:05:58,230 --> 00:06:00,589 Speaker 1: hunt community has then kind of been pulled a little 125 00:06:00,870 --> 00:06:04,950 Speaker 1: more into the immersive community through escape rooms, through immersive theater. 126 00:06:05,650 --> 00:06:07,590 Speaker 1: And then you have, yeah, the scavenger hunt community, which 127 00:06:07,730 --> 00:06:12,480 Speaker 1: is kind of geocaching adjacent and just making hunts for 128 00:06:12,520 --> 00:06:16,980 Speaker 1: your 10-year-old kids adjacent. The worst version of a scavenger 129 00:06:17,020 --> 00:06:19,140 Speaker 1: hunt is like, take pictures of five out of state 130 00:06:19,160 --> 00:06:21,640 Speaker 1: license plates or like, you know, get a photo of 131 00:06:21,690 --> 00:06:23,810 Speaker 1: a person with a beard and is kind of our 132 00:06:23,870 --> 00:06:25,750 Speaker 1: guiding light that we move away from. 133 00:06:26,029 --> 00:06:30,130 Speaker 3: We draw a distinction in our world between puzzles and tasks. 134 00:06:30,850 --> 00:06:33,950 Speaker 3: And a puzzle is, it requires some sort of lateral 135 00:06:34,010 --> 00:06:37,330 Speaker 3: thinking and a task is just an action that you complete. 136 00:06:37,370 --> 00:06:39,570 Speaker 3: So I think a lot of scavenger hunts are task-based 137 00:06:39,730 --> 00:06:43,210 Speaker 3: versus a puzzle requires you to use your brain in 138 00:06:43,250 --> 00:06:43,810 Speaker 3: a different way. 139 00:06:44,670 --> 00:06:46,780 Speaker 2: Do you have like a classic puzzle or like a, 140 00:06:47,310 --> 00:06:50,630 Speaker 2: form of puzzle or a way to describe more concretely 141 00:06:50,650 --> 00:06:54,169 Speaker 2: what the puzzles and puzzle hunts are? Because like to me, 142 00:06:54,490 --> 00:06:56,450 Speaker 2: and I have not, I don't think done your challenges, 143 00:06:56,490 --> 00:06:58,950 Speaker 2: although I think I did at Midnight Matter, a compass 144 00:06:58,990 --> 00:07:02,770 Speaker 2: that might've been partly you're doing. And I have a sense, 145 00:07:03,730 --> 00:07:07,089 Speaker 2: like an inarticulate sense of what puzzle hunt puzzles feel like. 146 00:07:07,310 --> 00:07:08,890 Speaker 2: You know, I've done, I don't know, four or five 147 00:07:08,910 --> 00:07:10,810 Speaker 2: puzzle hunts in an escape room or two, but like, 148 00:07:11,210 --> 00:07:13,590 Speaker 2: how do you think about puzzles and like, what is 149 00:07:13,670 --> 00:07:16,420 Speaker 2: a puzzle and like, what kinds of things are puzzles? 150 00:07:16,980 --> 00:07:18,980 Speaker 2: Could you give a puzzle that we could talk about 151 00:07:19,000 --> 00:07:20,880 Speaker 2: on a podcast? Sure. 152 00:07:21,260 --> 00:07:23,840 Speaker 3: I think every puzzle hunt has its own tradition of 153 00:07:24,080 --> 00:07:27,620 Speaker 3: how it defines a puzzle. And Ryan and I are 154 00:07:27,660 --> 00:07:30,740 Speaker 3: the first people to be in charge of the Midnight 155 00:07:30,780 --> 00:07:34,000 Speaker 3: Madness tradition, kind of coming from the outside, not having 156 00:07:34,040 --> 00:07:37,760 Speaker 3: played and not being from the finance industry. So we 157 00:07:37,780 --> 00:07:39,640 Speaker 3: had to do our homework and spend a lot of 158 00:07:39,660 --> 00:07:43,760 Speaker 3: time learning what's a puzzle by the definition of Midnight Madness. 159 00:07:44,540 --> 00:07:48,690 Speaker 3: And one thing that we identified is Each one should 160 00:07:48,730 --> 00:07:53,070 Speaker 3: involve a logical leap. So there's typically a mental connection 161 00:07:53,690 --> 00:07:57,950 Speaker 3: that you make between two different types of information. So 162 00:07:58,210 --> 00:08:00,990 Speaker 3: an example of a puzzle that I think is a 163 00:08:01,010 --> 00:08:03,090 Speaker 3: good illustration of this from an event that we did 164 00:08:03,110 --> 00:08:06,300 Speaker 3: a few years ago was designed by our friend Josh Stabiner. 165 00:08:06,360 --> 00:08:08,860 Speaker 3: And it's a puzzle in which you receive a rap 166 00:08:08,900 --> 00:08:13,720 Speaker 3: sheet that looks like a police description of several perpetrators 167 00:08:13,780 --> 00:08:16,640 Speaker 3: of criminals. And each one has a description and then 168 00:08:16,660 --> 00:08:20,750 Speaker 3: a picture of what looks like a fingerprint for each one. 169 00:08:21,440 --> 00:08:24,930 Speaker 3: But you use clues in the descriptions and you use 170 00:08:25,510 --> 00:08:28,470 Speaker 3: clues of what the visual of the fingerprint looks like 171 00:08:29,010 --> 00:08:32,750 Speaker 3: to actually make a connection that you're not looking at fingerprints, 172 00:08:32,790 --> 00:08:37,270 Speaker 3: you're looking at topographical maps of mountains. And each one 173 00:08:37,330 --> 00:08:40,890 Speaker 3: you discover as you kind of read through the text 174 00:08:41,130 --> 00:08:43,850 Speaker 3: and look for words that might seem out of place 175 00:08:44,010 --> 00:08:47,199 Speaker 3: and kind of, evidence that the descriptions are not quite 176 00:08:47,300 --> 00:08:51,059 Speaker 3: fitting well to like how a policeman might describe a 177 00:08:51,360 --> 00:08:55,470 Speaker 3: criminal to recognize that each of the seven is representing 178 00:08:55,520 --> 00:08:59,370 Speaker 3: the seven highest peaks on each continent. And so then 179 00:08:59,410 --> 00:09:03,610 Speaker 3: you use that information to go back to the first descriptions. 180 00:09:03,929 --> 00:09:07,170 Speaker 3: And in there, you work with the information you have 181 00:09:07,210 --> 00:09:10,229 Speaker 3: to yield a final solution, which is a key word. 182 00:09:10,870 --> 00:09:12,490 Speaker 3: But in order to do that, you have to be 183 00:09:12,530 --> 00:09:16,890 Speaker 3: able to make this mental leap. and recognize that one 184 00:09:16,929 --> 00:09:18,449 Speaker 3: thing is actually representing another. 185 00:09:19,070 --> 00:09:21,680 Speaker 4: How do you make them difficult without being infuriating? Because 186 00:09:21,740 --> 00:09:25,260 Speaker 4: this is something different, but Bloomberg has a weekly quiz. 187 00:09:25,559 --> 00:09:26,000 Speaker 1: Quiz go. 188 00:09:26,059 --> 00:09:26,760 Speaker 4: Matt, you've played it. 189 00:09:26,760 --> 00:09:28,189 Speaker 2: I have. You've written it, right? 190 00:09:28,460 --> 00:09:30,970 Speaker 4: I used to be the curator of the quiz, and 191 00:09:31,510 --> 00:09:33,990 Speaker 4: one of the metrics on which I judged myself was 192 00:09:34,370 --> 00:09:37,089 Speaker 4: by how many people who started the quiz completed the quiz. 193 00:09:37,550 --> 00:09:39,590 Speaker 4: And there was like this fine balance I had to 194 00:09:39,630 --> 00:09:42,670 Speaker 4: find between making it challenging but not making it annoying. 195 00:09:43,150 --> 00:09:45,470 Speaker 4: So how do you find that balance when you're putting 196 00:09:45,490 --> 00:09:48,690 Speaker 4: together puzzles and make sure that people basically don't rage quit? 197 00:09:48,929 --> 00:09:50,880 Speaker 3: Yes, you're our sister in pain, I see. 198 00:09:52,440 --> 00:09:55,540 Speaker 1: I think that's the number one skill of a good 199 00:09:55,590 --> 00:09:58,730 Speaker 1: puzzle creator. I think that right there is the magic 200 00:09:58,809 --> 00:10:02,540 Speaker 1: sauce is figuring out something that's just hard enough that 201 00:10:02,679 --> 00:10:05,600 Speaker 1: makes people really feel like they've gone on a journey 202 00:10:05,800 --> 00:10:08,079 Speaker 1: and they were just about to quit, but then they 203 00:10:08,179 --> 00:10:11,980 Speaker 1: had that spark of inspiration that turned it all around 204 00:10:12,040 --> 00:10:14,020 Speaker 1: for them. And then everything fell into place. And then 205 00:10:14,070 --> 00:10:15,929 Speaker 1: looking back on it, it's like, oh, of course that 206 00:10:15,950 --> 00:10:18,650 Speaker 1: was the answer. It could never have not been the answer. 207 00:10:18,950 --> 00:10:22,020 Speaker 1: And bringing people on that journey and allowing them to 208 00:10:22,059 --> 00:10:24,260 Speaker 1: go on that journey themselves. And then by the end 209 00:10:24,300 --> 00:10:26,730 Speaker 1: of it, having that, I heard it recently described as 210 00:10:26,950 --> 00:10:29,670 Speaker 1: I think secondhand fun or second degree fun, where it's like, 211 00:10:29,770 --> 00:10:32,010 Speaker 1: it's sucked in the moment, but when you look back 212 00:10:32,130 --> 00:10:35,250 Speaker 1: on it, it's a pleasureful thing. And so creating that moment, 213 00:10:35,370 --> 00:10:38,110 Speaker 1: it's very difficult and we've struggled with it. And, you know, 214 00:10:38,150 --> 00:10:40,550 Speaker 1: we created the great Gotham challenge. I created the first 215 00:10:40,630 --> 00:10:42,860 Speaker 1: one by myself. John was a participant. This is how 216 00:10:42,880 --> 00:10:45,840 Speaker 1: we started working together. And no one finished it. Everyone 217 00:10:45,860 --> 00:10:49,870 Speaker 1: rage quit. It was in 2009. The stock market had crashed. 218 00:10:49,950 --> 00:10:52,370 Speaker 1: I just graduated college and couldn't get a job. And 219 00:10:52,429 --> 00:10:55,710 Speaker 1: so me and another friend created this and it was 220 00:10:55,750 --> 00:10:57,929 Speaker 1: supposed to be like a four hour thing. Everyone just 221 00:10:57,990 --> 00:11:00,060 Speaker 1: texted us after hour four and was like, I am 222 00:11:00,340 --> 00:11:02,400 Speaker 1: a quarter of the way through. Please put a bullet 223 00:11:02,440 --> 00:11:03,880 Speaker 1: in my head. And so it's just like, okay, come 224 00:11:03,920 --> 00:11:06,200 Speaker 1: to the finish line. But anyways, we've gotten better. We've 225 00:11:06,220 --> 00:11:08,340 Speaker 1: been doing this for about 11 years and a lot 226 00:11:08,360 --> 00:11:10,900 Speaker 1: of it is playtesting. Like we have a community of 227 00:11:10,950 --> 00:11:14,290 Speaker 1: people that just playtest our puzzles and They time themselves 228 00:11:14,330 --> 00:11:17,250 Speaker 1: and we make sure we know how long a puzzle 229 00:11:17,270 --> 00:11:20,230 Speaker 1: should take and what the right deviation is. And it's 230 00:11:20,290 --> 00:11:22,610 Speaker 1: also a lot of argument. Like we've just got people 231 00:11:22,650 --> 00:11:24,650 Speaker 1: that we really trust and who have done a lot 232 00:11:24,670 --> 00:11:27,160 Speaker 1: of these things. And someone says, this is way too hard. 233 00:11:27,179 --> 00:11:28,900 Speaker 1: This is way too easy. And we just go 12 234 00:11:28,900 --> 00:11:31,620 Speaker 1: rounds until we find something that we all agree on. 235 00:11:31,679 --> 00:11:34,760 Speaker 1: And we trust each other. So part of it's not 236 00:11:34,780 --> 00:11:36,199 Speaker 1: working in a vacuum and part of it's just a 237 00:11:36,240 --> 00:11:39,199 Speaker 1: lot of experience and a part of it's playtesting. John 238 00:11:39,220 --> 00:11:41,220 Speaker 1: and I are creative by nature, and we brought in 239 00:11:41,280 --> 00:11:43,979 Speaker 1: an operations person to help run our company named Teresa, 240 00:11:44,059 --> 00:11:47,740 Speaker 1: who's brilliant and has saved our company many times. But 241 00:11:47,900 --> 00:11:52,179 Speaker 1: one of the things she instigated is, no, we playtest things. 242 00:11:52,200 --> 00:11:53,720 Speaker 1: We playtest things thoroughly. 243 00:11:54,179 --> 00:11:55,880 Speaker 2: I think another part of the answer to Katie's question 244 00:11:55,960 --> 00:11:58,500 Speaker 2: is when I've done puzzle hunts, there's some sort of 245 00:11:59,360 --> 00:12:03,450 Speaker 2: hint mechanism where you can, without fully giving up, you 246 00:12:03,470 --> 00:12:05,270 Speaker 2: can give up a little and get some sort of help. 247 00:12:05,309 --> 00:12:07,510 Speaker 2: Can you talk about how you think about that? 248 00:12:08,570 --> 00:12:11,830 Speaker 1: Yeah. And it's interesting because we've seen this done different ways. 249 00:12:11,970 --> 00:12:15,250 Speaker 1: And in the Midnight Madness puzzle hunt that we stage 250 00:12:15,490 --> 00:12:18,770 Speaker 1: every other year for the finance industry, there's kind of 251 00:12:18,870 --> 00:12:24,709 Speaker 1: a bespoke, personalized, what's called game controller who meters out hints. 252 00:12:25,110 --> 00:12:28,530 Speaker 2: It's like your personal tormentor. Right. Right. Exactly. 253 00:12:28,610 --> 00:12:31,120 Speaker 1: And this is actually something very unique about the Wall 254 00:12:31,150 --> 00:12:35,179 Speaker 1: Street vibe is that the game controllers are known to 255 00:12:35,300 --> 00:12:38,500 Speaker 1: be a little malicious and a little kind of Because 256 00:12:38,520 --> 00:12:40,920 Speaker 1: we've been kind of apprenticing with the current creators for 257 00:12:40,940 --> 00:12:43,939 Speaker 1: the last four years and we've taken it over this year. 258 00:12:44,020 --> 00:12:46,480 Speaker 1: And so we've watched them and tried to learn and 259 00:12:46,559 --> 00:12:49,760 Speaker 1: we've been like, this seems weird. This seems mean. And 260 00:12:49,780 --> 00:12:52,110 Speaker 1: they're like, oh no, it's what people want. Like it's 261 00:12:52,140 --> 00:12:54,990 Speaker 1: what the, it's what the players want. That's done in 262 00:12:55,030 --> 00:12:59,170 Speaker 1: a very like bespoke, handcrafted concierge way, both the hinting 263 00:12:59,250 --> 00:13:02,850 Speaker 1: and the tormenting. Whereas like on our Great Gotham Challenge 264 00:13:02,910 --> 00:13:05,469 Speaker 1: branded puzzle hunts that we do, there's kind of a 265 00:13:05,830 --> 00:13:09,020 Speaker 1: unified pre-canned hint system that That, you know, when you 266 00:13:09,100 --> 00:13:11,260 Speaker 1: feel like you're at a dead end, you can take 267 00:13:11,300 --> 00:13:14,110 Speaker 1: a hint and there's a certain time penalty. And we've 268 00:13:14,140 --> 00:13:18,110 Speaker 1: introduced a fun gamified mechanic where the longer you're on 269 00:13:18,130 --> 00:13:21,630 Speaker 1: a puzzle, the less penalty time you get. And so, yeah, 270 00:13:21,650 --> 00:13:23,410 Speaker 1: there absolutely needs to be a hint system. And that's 271 00:13:23,530 --> 00:13:26,610 Speaker 1: absolutely a way that you keep people within the same universe. 272 00:13:26,650 --> 00:13:29,850 Speaker 1: If there was no hint system, then you'd see deviations 273 00:13:29,890 --> 00:13:31,750 Speaker 1: of 200% on times. 274 00:13:32,190 --> 00:13:34,710 Speaker 2: My experience of like Compass or Midnight Madness is like, 275 00:13:34,910 --> 00:13:37,860 Speaker 2: if you're like getting on the subway to go to 276 00:13:37,900 --> 00:13:41,930 Speaker 2: the wrong burrow, your game control will be like, hold on. Right, yeah, yeah, yeah. 277 00:13:41,950 --> 00:13:44,570 Speaker 2: There's some amount of like, don't do something really stupid. 278 00:13:45,450 --> 00:13:47,990 Speaker 1: And that's the, yeah, that's the designer's job is to, yeah, 279 00:13:48,030 --> 00:13:52,270 Speaker 1: figuring out how to let people fail enough that they 280 00:13:52,309 --> 00:13:54,819 Speaker 1: go through those peaks and valleys of emotions, but not 281 00:13:54,860 --> 00:13:57,420 Speaker 1: letting them fail so much that they're just destroyed. 282 00:13:58,500 --> 00:14:00,560 Speaker 2: Yeah, you want to feel like you can fail so 283 00:14:00,600 --> 00:14:02,359 Speaker 2: that when you succeed, you feel good about it. 284 00:14:02,700 --> 00:14:02,860 Speaker 1: Right. 285 00:14:18,480 --> 00:14:22,250 Speaker 2: Can we talk about Midnight Madness? I've written about having 286 00:14:22,300 --> 00:14:26,830 Speaker 2: done one or two compass hunts, which my understanding is that, like, 287 00:14:27,470 --> 00:14:32,989 Speaker 2: at some point, a kind of Goldman Sachs-affiliated group of 288 00:14:33,030 --> 00:14:37,220 Speaker 2: Wall Street people started a Midnight Madness puzzle hunt, possibly 289 00:14:37,280 --> 00:14:40,960 Speaker 2: named after a movie of the same name. And... It 290 00:14:41,020 --> 00:14:43,880 Speaker 2: was called Midnight Madness because it started at, I don't know, 291 00:14:43,880 --> 00:14:46,820 Speaker 2: 4 p.m. and went until 2 p.m. the next day. 292 00:14:47,100 --> 00:14:48,620 Speaker 1: Everything you've heard is correct, yes. 293 00:14:48,780 --> 00:14:52,650 Speaker 2: Yeah. And it was run by, I think, Alicia Wiesel 294 00:14:52,790 --> 00:14:57,230 Speaker 2: at Goldman. And then it became so overwhelming that my 295 00:14:57,390 --> 00:14:59,770 Speaker 2: understanding was, like, the winners got to run it the 296 00:14:59,830 --> 00:15:02,740 Speaker 2: next time. And I know, like, Colin Tykel ran it 297 00:15:02,760 --> 00:15:05,900 Speaker 2: for a while. And that is, like, in my understanding, 298 00:15:05,940 --> 00:15:08,200 Speaker 2: the premier, like, Wall Street puzzle hunt. And all of 299 00:15:08,240 --> 00:15:10,950 Speaker 2: the teams are, like... Eight Goldman teams and six Chain 300 00:15:10,970 --> 00:15:13,190 Speaker 2: Street teams. Is that basically correct? 301 00:15:13,710 --> 00:15:17,230 Speaker 3: Most of that's correct. Alicia designed it for, I think, 302 00:15:17,570 --> 00:15:21,290 Speaker 3: maybe a decade or a little less. And at some point, 303 00:15:21,770 --> 00:15:23,580 Speaker 3: I think he decided it was too much for him 304 00:15:23,650 --> 00:15:26,660 Speaker 3: to continue and just decided, I can't keep doing this. 305 00:15:26,700 --> 00:15:27,240 Speaker 2: I need to quit. 306 00:15:27,360 --> 00:15:30,300 Speaker 3: And the team that won the year that he called 307 00:15:30,320 --> 00:15:33,800 Speaker 3: his final year decided that they loved the game too 308 00:15:33,860 --> 00:15:37,160 Speaker 3: much to let it die. So they said, we'll take over. 309 00:15:37,760 --> 00:15:40,650 Speaker 3: We'll Put it under a different name so that people 310 00:15:40,710 --> 00:15:43,630 Speaker 3: recognize that it's under new management. They ran it for 311 00:15:44,090 --> 00:15:47,390 Speaker 3: several years and then they decided we can't keep doing this. 312 00:15:47,470 --> 00:15:50,810 Speaker 3: It's destroying our lives and our relationships. 313 00:15:51,370 --> 00:15:54,670 Speaker 2: Because all these people have like real jobs in the 314 00:15:54,710 --> 00:15:59,580 Speaker 2: financial industry and also extracurricularly design these insane things. All 315 00:15:59,600 --> 00:16:00,380 Speaker 2: night puzzle hunts. 316 00:16:00,700 --> 00:16:02,239 Speaker 1: As opposed to us who have fake jobs in the 317 00:16:02,260 --> 00:16:04,840 Speaker 1: financial industry. Yes, that's correct. No, we have real jobs 318 00:16:04,900 --> 00:16:05,440 Speaker 1: in puzzle hunts. 319 00:16:05,480 --> 00:16:08,100 Speaker 2: Yeah, exactly. So this is your job. It's not their job. 320 00:16:08,160 --> 00:16:10,810 Speaker 1: It's a little more sustainable for us. But yes, exactly. Like, 321 00:16:10,850 --> 00:16:13,530 Speaker 1: I don't know how they could possibly do it because 322 00:16:13,970 --> 00:16:17,050 Speaker 1: this is my full time job. It already is so 323 00:16:17,110 --> 00:16:19,670 Speaker 1: hard for me. I can't imagine working at a hedge 324 00:16:19,730 --> 00:16:22,010 Speaker 1: fund while simultaneously doing this. 325 00:16:23,170 --> 00:16:26,560 Speaker 2: So you guys are professional puzzle hunt makers and they 326 00:16:26,620 --> 00:16:28,910 Speaker 2: are professional hedge fund managers. As you look at their work, 327 00:16:28,930 --> 00:16:30,970 Speaker 2: what do you think? Were they good at it? If 328 00:16:30,990 --> 00:16:32,730 Speaker 2: you have like the regular puzzle hunt community and then 329 00:16:32,750 --> 00:16:34,250 Speaker 2: you have like the hedge fund guys, is there a 330 00:16:34,290 --> 00:16:35,810 Speaker 2: different style or mindset? 331 00:16:36,310 --> 00:16:39,320 Speaker 3: Yeah, that's something Ryan and I were just discussing, actually. 332 00:16:39,530 --> 00:16:41,500 Speaker 3: There are things that are unique to it. There are 333 00:16:41,600 --> 00:16:44,600 Speaker 3: ways that maybe we look at things a bit differently. 334 00:16:44,780 --> 00:16:49,440 Speaker 3: For instance, talking about hints, Ryan and I, as puzzle designers, 335 00:16:49,540 --> 00:16:53,200 Speaker 3: we kind of believe that a really well-designed puzzle should 336 00:16:53,220 --> 00:16:57,110 Speaker 3: be able to be completed by a good puzzler without 337 00:16:57,660 --> 00:17:00,620 Speaker 3: needing to be hinted in any way. Whereas I think 338 00:17:01,220 --> 00:17:03,760 Speaker 3: they're coming from a world in which they feel like 339 00:17:03,820 --> 00:17:06,280 Speaker 3: if it's not hard enough to require someone to take hints, 340 00:17:06,320 --> 00:17:09,170 Speaker 3: then it's not hard enough. So that's been an adjustment, 341 00:17:09,510 --> 00:17:11,389 Speaker 3: I think, for us to kind of recognize. 342 00:17:12,010 --> 00:17:15,510 Speaker 1: We're a little more breadcrumb that leap of logic in 343 00:17:15,550 --> 00:17:17,010 Speaker 1: a way that like at the end of a good 344 00:17:17,070 --> 00:17:19,720 Speaker 1: murder mystery, you look back and you're like, oh, the 345 00:17:19,760 --> 00:17:22,109 Speaker 1: hints were always there that it was the butler. And 346 00:17:22,150 --> 00:17:24,650 Speaker 1: so we're a little more on that end versus, yeah, 347 00:17:24,710 --> 00:17:26,930 Speaker 1: they're more like, you have to make this leap of 348 00:17:26,990 --> 00:17:29,659 Speaker 1: logic with no prior breadcrumbs. 349 00:17:29,980 --> 00:17:33,140 Speaker 2: I'm with you. I've had some Midnight Madness experiences where 350 00:17:33,160 --> 00:17:35,840 Speaker 2: you're like, you get the hint and you're like, no 351 00:17:35,880 --> 00:17:38,760 Speaker 2: one would have gotten that. That makes no sense. Yeah. 352 00:17:38,800 --> 00:17:42,440 Speaker 3: Another big distinction, though, that we've come to terms with, though, 353 00:17:42,940 --> 00:17:44,820 Speaker 3: that I think is really interesting and says a lot, 354 00:17:45,500 --> 00:17:47,500 Speaker 3: and we didn't believe this to be true when we started, 355 00:17:47,560 --> 00:17:49,939 Speaker 3: but I think we've come around to the idea that 356 00:17:50,410 --> 00:17:53,200 Speaker 3: the people who are attracted to this Midnight Madness game 357 00:17:53,240 --> 00:17:56,939 Speaker 3: who come from Wall Street, they do crave, I hesitate 358 00:17:56,980 --> 00:18:00,080 Speaker 3: to use the word glutton for punishment, but they do 359 00:18:00,180 --> 00:18:05,180 Speaker 3: crave a certain amount of intensity and some would even 360 00:18:05,260 --> 00:18:09,080 Speaker 3: say torture that I think was surprising to us. 361 00:18:09,100 --> 00:18:11,200 Speaker 2: Yeah, I mean, just the fact that it is sort 362 00:18:11,240 --> 00:18:14,610 Speaker 2: of runs overnight is cruel. 363 00:18:15,430 --> 00:18:18,910 Speaker 4: In a way, it's like endurance athletics, but with your 364 00:18:18,930 --> 00:18:20,150 Speaker 4: mind and your body. 365 00:18:20,640 --> 00:18:24,660 Speaker 2: Totally. Yeah. You have a day job running puzzle hunts 366 00:18:24,740 --> 00:18:28,410 Speaker 2: under your own brand and like puzzle hunt activities for 367 00:18:28,530 --> 00:18:29,350 Speaker 2: corporate clients. 368 00:18:29,630 --> 00:18:29,770 Speaker 1: Right. 369 00:18:29,930 --> 00:18:31,630 Speaker 2: My sense is that a lot of your clients are 370 00:18:31,750 --> 00:18:34,209 Speaker 2: also in the financial industry and like puzzle hunting and 371 00:18:34,290 --> 00:18:36,350 Speaker 2: finance overlap a lot. Is that right? 372 00:18:37,530 --> 00:18:40,810 Speaker 1: Yes. You're onto us. We didn't mean to do it 373 00:18:40,830 --> 00:18:45,670 Speaker 1: that way, but the market found us. Yeah. 374 00:18:46,630 --> 00:18:48,510 Speaker 2: What do you think it is about like financial people 375 00:18:48,590 --> 00:18:50,129 Speaker 2: and puzzle hunts? Like where do they go together? 376 00:18:50,890 --> 00:18:53,609 Speaker 3: Several things. One is I think the finance industry and 377 00:18:53,630 --> 00:18:57,310 Speaker 3: the tech industry have become really closely intertwined. And as 378 00:18:57,369 --> 00:19:01,040 Speaker 3: I said, the tradition of the MIT mystery hunt, a 379 00:19:01,100 --> 00:19:03,899 Speaker 3: lot of these people that come from Cambridge end up 380 00:19:04,460 --> 00:19:07,860 Speaker 3: in New York, end up doing finance related jobs. And 381 00:19:08,000 --> 00:19:11,910 Speaker 3: so they've crafted a taste for this type of thing 382 00:19:12,130 --> 00:19:13,330 Speaker 3: already earlier in life. 383 00:19:14,010 --> 00:19:15,910 Speaker 2: Does everyone at MIT do the mystery hunt? 384 00:19:16,150 --> 00:19:17,629 Speaker 3: I don't think everyone does it. And a lot of 385 00:19:17,650 --> 00:19:20,510 Speaker 3: people who do it are also not currently at MIT. 386 00:19:20,710 --> 00:19:23,229 Speaker 2: I've been invited on teams that it seemed like more 387 00:19:23,260 --> 00:19:25,320 Speaker 2: trouble than I was worth. Yeah. 388 00:19:25,380 --> 00:19:27,859 Speaker 3: I mean, that's a, that's like a three day event 389 00:19:27,900 --> 00:19:28,879 Speaker 3: or a four day event. 390 00:19:29,060 --> 00:19:31,399 Speaker 2: And it seems like a hundred people and you can 391 00:19:31,440 --> 00:19:33,060 Speaker 2: do it remotely. It just seems like a lot. 392 00:19:33,619 --> 00:19:34,180 Speaker 1: It is a lot. 393 00:19:34,300 --> 00:19:35,419 Speaker 3: You're not wrong about that. 394 00:19:35,540 --> 00:19:39,139 Speaker 1: Our COO, Teresa participated this last year and had a 395 00:19:39,280 --> 00:19:42,720 Speaker 1: fantastic time and We're going to try to go next year. 396 00:19:42,790 --> 00:19:44,189 Speaker 1: And she went there on a team and it's like, 397 00:19:44,210 --> 00:19:46,190 Speaker 1: how fun can like being holed up in a, in 398 00:19:46,210 --> 00:19:49,250 Speaker 1: a hotel room solving puzzles, you know, but it really 399 00:19:49,310 --> 00:19:52,900 Speaker 1: seems like the winning teams are, it's not just about 400 00:19:52,960 --> 00:19:56,119 Speaker 1: puzzle solving acumen, but about organization of brainpower. You know, 401 00:19:56,160 --> 00:19:59,479 Speaker 1: how do you effectively deploy a hundred people to effectively 402 00:20:00,140 --> 00:20:03,949 Speaker 1: manage problems and contribute and make these lateral leaps and, 403 00:20:04,310 --> 00:20:06,470 Speaker 1: It seems like that's the key to the MIT mystery hunt, 404 00:20:06,490 --> 00:20:10,010 Speaker 1: which is, I think, such an interesting social management problem. 405 00:20:10,230 --> 00:20:13,550 Speaker 4: Yeah, I was reading a Quartz article from 2013, I 406 00:20:13,570 --> 00:20:15,929 Speaker 4: think it was, because Midnight Madness went on a bit 407 00:20:15,970 --> 00:20:17,780 Speaker 4: of a hiatus and then it came back. 408 00:20:17,859 --> 00:20:18,060 Speaker 2: Right. 409 00:20:18,170 --> 00:20:21,840 Speaker 4: And the article is talking about how originally the thinking, 410 00:20:21,980 --> 00:20:24,480 Speaker 4: you know, among the Goldman Sachs teams who participated was 411 00:20:24,520 --> 00:20:26,639 Speaker 4: that they wanted to stack their teams with quants. They 412 00:20:26,680 --> 00:20:29,020 Speaker 4: just wanted a lot of big brains. But the team 413 00:20:29,040 --> 00:20:31,980 Speaker 4: that ended up winning... was a group that worked together. 414 00:20:32,000 --> 00:20:34,500 Speaker 4: And I think they were client facing and they chalked 415 00:20:34,540 --> 00:20:37,050 Speaker 4: their winning up to just, we know how to work together. 416 00:20:37,109 --> 00:20:39,950 Speaker 4: We don't necessarily have the smartest guy in the room, 417 00:20:39,990 --> 00:20:41,909 Speaker 4: but we all know how to manage together. 418 00:20:41,930 --> 00:20:42,750 Speaker 3: Yeah. 419 00:20:42,790 --> 00:20:45,470 Speaker 2: And also like if it's all quants, like you want 420 00:20:45,530 --> 00:20:48,470 Speaker 2: different kinds of intelligence too, like in solving the puzzles 421 00:20:48,530 --> 00:20:49,990 Speaker 2: as well as in creating the puzzles. Like, you know, 422 00:20:50,010 --> 00:20:51,889 Speaker 2: as I was thinking about like why the financial industry 423 00:20:51,910 --> 00:20:54,710 Speaker 2: likes puzzle hunts, I mean, I was thinking like teamwork 424 00:20:54,800 --> 00:20:57,899 Speaker 2: is always pretty heavily emphasized when you like interview at 425 00:20:57,920 --> 00:21:00,290 Speaker 2: a financial firm and like the idea of like, Getting 426 00:21:00,310 --> 00:21:04,129 Speaker 2: different types of intelligence together and trying to delegate responsibility 427 00:21:04,170 --> 00:21:07,290 Speaker 2: and brainstorm together does seem useful in the job. And 428 00:21:07,310 --> 00:21:11,020 Speaker 2: then it hadn't even occurred to me that the 100% 429 00:21:11,020 --> 00:21:15,460 Speaker 2: MIT mystery hunt teams are an enormous management problem. But yes, 430 00:21:15,680 --> 00:21:18,700 Speaker 2: if you can manage a puzzle hunt team of 100 people, 431 00:21:18,740 --> 00:21:20,980 Speaker 2: that does seem useful for managing a hedge fund. 432 00:21:21,500 --> 00:21:24,859 Speaker 1: They create custom software platforms just to manage the puzzles. 433 00:21:25,780 --> 00:21:28,040 Speaker 1: It's incredible. I did want to go back to, you 434 00:21:28,080 --> 00:21:30,260 Speaker 1: were correct in that Midnight Madness grew out of Goldman. 435 00:21:31,000 --> 00:21:35,369 Speaker 1: And I'd say maybe still less than, I mean, maybe 40% 436 00:21:35,369 --> 00:21:38,149 Speaker 1: of our teams are Goldman, 30 to 40% of our teams. 437 00:21:38,530 --> 00:21:40,350 Speaker 1: So they're a huge supporter. And just to give the 438 00:21:40,390 --> 00:21:43,510 Speaker 1: context for your listeners, this Midnight Madness is a charity 439 00:21:43,550 --> 00:21:46,629 Speaker 1: event for Good Shepherd Services. And so the great part 440 00:21:46,650 --> 00:21:49,109 Speaker 1: is instead of going to a fundraiser where you have 441 00:21:49,150 --> 00:21:51,550 Speaker 1: to buy a table and sit through speeches and watch 442 00:21:52,010 --> 00:21:54,869 Speaker 1: pretty picture videos, you stake a team to compete. And 443 00:21:54,910 --> 00:21:57,820 Speaker 1: so I'd say, yeah, still definitely a huge, the biggest 444 00:21:57,859 --> 00:22:01,080 Speaker 1: showing is from Goldman, but there's probably 15 to 20 445 00:22:01,080 --> 00:22:05,880 Speaker 1: different firms represented, everything from bigger investment banks to quant 446 00:22:05,920 --> 00:22:09,199 Speaker 1: firms to really small shops. And I don't even know 447 00:22:09,240 --> 00:22:11,490 Speaker 1: all the different types of shops that are represented there. 448 00:22:11,910 --> 00:22:15,649 Speaker 1: And it goes from places where the CEO is leading 449 00:22:15,690 --> 00:22:19,510 Speaker 1: the team and to places where the CEO is stakes 450 00:22:19,590 --> 00:22:21,950 Speaker 1: the team and then like puts his best people on 451 00:22:21,990 --> 00:22:23,969 Speaker 1: the team and shows up at the finish line or 452 00:22:24,030 --> 00:22:26,290 Speaker 1: also places where just like they just look at it 453 00:22:26,330 --> 00:22:28,580 Speaker 1: as a donation and let the people who want to 454 00:22:28,600 --> 00:22:28,919 Speaker 1: show up. 455 00:22:29,600 --> 00:22:31,879 Speaker 2: But the idea is like basically Midnight Madness is a 456 00:22:31,900 --> 00:22:35,440 Speaker 2: fundraiser for Good Shepherd. The team is up to six people. 457 00:22:35,480 --> 00:22:35,800 Speaker 4: Correct. 458 00:22:36,000 --> 00:22:38,720 Speaker 2: And it costs something like $ 40, 000 to sponsor a team. 459 00:22:38,790 --> 00:22:41,990 Speaker 2: So it's exactly it's a meaningful donation. Yeah. 460 00:22:43,010 --> 00:22:45,760 Speaker 1: And so we'll have 25 teams duking it out on 461 00:22:45,840 --> 00:22:48,500 Speaker 1: October 4th, the early hours of October 5th, duking it 462 00:22:48,540 --> 00:22:50,400 Speaker 1: out for the title of the most, you know, most 463 00:22:50,440 --> 00:22:52,000 Speaker 1: intelligent and really best. 464 00:22:52,800 --> 00:22:55,720 Speaker 2: So in my experience, the production values for Midnight Madness 465 00:22:55,820 --> 00:22:58,370 Speaker 2: are really high. Like the year I did it most recently, 466 00:22:58,390 --> 00:23:02,889 Speaker 2: it ended on the Intrepid, like the aircraft carrier, solving 467 00:23:02,970 --> 00:23:05,669 Speaker 2: a puzzle on a real Enigma machine. I don't know 468 00:23:05,690 --> 00:23:07,550 Speaker 2: if you know this, but it's very finance industry coded. 469 00:23:07,590 --> 00:23:09,310 Speaker 2: Like you're not a hedge fund unless you have a 470 00:23:09,350 --> 00:23:11,800 Speaker 2: real Enigma machine somewhere. And it was like, you know, 471 00:23:11,820 --> 00:23:13,950 Speaker 2: you had to like, get clues by going to like 472 00:23:13,990 --> 00:23:16,270 Speaker 2: a screening of a movie on a rooftop in Brooklyn 473 00:23:16,570 --> 00:23:18,590 Speaker 2: and like there was a like chessboard in the Brooklyn 474 00:23:18,630 --> 00:23:21,890 Speaker 2: Museum it was like a real pretty high-end experience I'm 475 00:23:21,930 --> 00:23:23,929 Speaker 2: very interested in like talking about the puzzle aspect but 476 00:23:23,970 --> 00:23:27,570 Speaker 2: like as designers I feel like you're more interested in 477 00:23:27,590 --> 00:23:30,570 Speaker 2: like the cool experiences side of it you talk about that. 478 00:23:31,450 --> 00:23:34,330 Speaker 3: Yeah that I mean that was really intimidating and it's 479 00:23:34,369 --> 00:23:37,370 Speaker 3: interesting when Ryan and I started designing games like this 480 00:23:37,410 --> 00:23:39,770 Speaker 3: when we were in college just for our friends and 481 00:23:39,850 --> 00:23:42,369 Speaker 3: scraping together a couple of bucks from our own pocket 482 00:23:42,430 --> 00:23:44,470 Speaker 3: and trying to dream as big as we could. And 483 00:23:45,100 --> 00:23:48,060 Speaker 3: only many years later, we came across an article about 484 00:23:48,080 --> 00:23:50,919 Speaker 3: the tradition of Midnight Madness and learned that there was 485 00:23:50,960 --> 00:23:55,120 Speaker 3: a puzzle that year where teams had controls that were 486 00:23:55,359 --> 00:23:58,179 Speaker 3: actively controlling the lights on the Empire State Building and 487 00:23:58,220 --> 00:24:02,340 Speaker 3: changing the colors to solve a puzzle. And we were 488 00:24:02,560 --> 00:24:06,260 Speaker 3: absolutely floored by the kind of production value available to 489 00:24:06,280 --> 00:24:09,770 Speaker 3: these game designers and thought like, wow, if we could 490 00:24:09,810 --> 00:24:11,879 Speaker 3: just do something like that one day, that would be 491 00:24:11,940 --> 00:24:15,510 Speaker 3: the biggest dream that we could dream for ourselves. And yeah, 492 00:24:15,550 --> 00:24:18,750 Speaker 3: so a lot of the fee that people contribute to 493 00:24:18,950 --> 00:24:21,810 Speaker 3: stake a team does go towards the production of a 494 00:24:21,950 --> 00:24:26,630 Speaker 3: very fantastic and epic game. And that's part of the appeal. 495 00:24:27,070 --> 00:24:29,449 Speaker 3: It is interesting for us to try to design for 496 00:24:29,490 --> 00:24:32,090 Speaker 3: the man or woman who has everything, quote unquote. And 497 00:24:32,490 --> 00:24:34,650 Speaker 3: if you're super wealthy and you have all these kind 498 00:24:34,690 --> 00:24:39,180 Speaker 3: of opportunities and experiences available to you on a regular basis. 499 00:24:39,280 --> 00:24:41,979 Speaker 3: What is impressive? What can make an impression on that 500 00:24:42,020 --> 00:24:44,560 Speaker 3: type of person? I think that's part of where this 501 00:24:44,600 --> 00:24:46,820 Speaker 3: tradition has come from of like, wow, it has to 502 00:24:46,840 --> 00:24:50,619 Speaker 3: be bombastic and having access to landmark locations in New 503 00:24:50,640 --> 00:24:52,800 Speaker 3: York City that you wouldn't normally have is a big 504 00:24:52,840 --> 00:24:55,310 Speaker 3: part of it. The scale has changed a bit. I 505 00:24:55,350 --> 00:24:58,310 Speaker 3: think when Alicia was designing it, maybe a much bigger 506 00:24:58,390 --> 00:25:02,750 Speaker 3: portion of the fee went towards the production value of 507 00:25:02,790 --> 00:25:05,870 Speaker 3: the game and We're allocating a different kind of percentage 508 00:25:06,410 --> 00:25:07,469 Speaker 3: to the charity versus the. 509 00:25:07,510 --> 00:25:08,650 Speaker 1: More to the charity, to be clear. 510 00:25:09,609 --> 00:25:11,880 Speaker 2: No, we don't know. Do you have a list of like, 511 00:25:12,180 --> 00:25:14,159 Speaker 2: here are some cool locations, let's see if we can 512 00:25:14,200 --> 00:25:17,440 Speaker 2: get them and then like often get told no? Absolutely. 513 00:25:17,619 --> 00:25:19,290 Speaker 2: If you want to like get the intrepid, like how 514 00:25:19,369 --> 00:25:21,210 Speaker 2: easy is that? And when you call and you say, hi, 515 00:25:21,230 --> 00:25:23,790 Speaker 2: we run a puzzle hunt with a lot of golden people. Like, 516 00:25:23,810 --> 00:25:25,270 Speaker 2: does that work? Or people are like, what are you 517 00:25:25,310 --> 00:25:25,890 Speaker 2: talking about? 518 00:25:26,340 --> 00:25:28,399 Speaker 1: It's everything. We didn't get the Intrepid. I think that 519 00:25:28,420 --> 00:25:31,080 Speaker 1: was the year before we started working with them. So 520 00:25:31,119 --> 00:25:36,020 Speaker 1: I can't speak to specifically renting the Intrepid, but it's always... Yeah, 521 00:25:36,040 --> 00:25:39,360 Speaker 1: at midnight. Yeah, or into 2 a.m. Some things are, wow, 522 00:25:39,380 --> 00:25:41,020 Speaker 1: we're never going to get that. And then people come 523 00:25:41,060 --> 00:25:43,270 Speaker 1: back to us and like, yeah, how about $ 2, 500? And 524 00:25:43,290 --> 00:25:44,730 Speaker 1: you're like, great, let's do it. 525 00:25:45,030 --> 00:25:49,469 Speaker 2: What's the most surprising location or thing you've gotten access to? 526 00:25:50,210 --> 00:25:53,380 Speaker 3: Last game, we did a puzzle in FAO Schwartz where 527 00:25:53,430 --> 00:25:55,720 Speaker 3: teams had to play the big piano with their feet 528 00:25:56,000 --> 00:25:59,340 Speaker 3: to solve a puzzle. That was a really fun one 529 00:25:59,400 --> 00:26:01,800 Speaker 3: for someone who grew up watching the movie Big with 530 00:26:01,840 --> 00:26:02,459 Speaker 3: Tom Hanks. 531 00:26:03,200 --> 00:26:05,600 Speaker 4: We could also ask the inverse of that question. I mean, 532 00:26:05,619 --> 00:26:07,760 Speaker 4: where have you been turned down from that you really 533 00:26:07,800 --> 00:26:08,660 Speaker 4: wanted to happen? 534 00:26:09,480 --> 00:26:11,869 Speaker 1: Every year there's a theme. In 2023, it was the 535 00:26:11,910 --> 00:26:14,810 Speaker 1: Lost Cosmonauts, which is a riff on a conspiracy theory 536 00:26:14,850 --> 00:26:17,850 Speaker 1: that there's cosmonauts that were launched into space. that we'd 537 00:26:17,970 --> 00:26:19,990 Speaker 1: never heard about. And kind of the seed of the 538 00:26:20,050 --> 00:26:21,830 Speaker 1: idea is that somehow they're still alive and we have 539 00:26:21,850 --> 00:26:23,570 Speaker 1: to bring them home. And so we were going to 540 00:26:23,590 --> 00:26:26,950 Speaker 1: do a cosmonaut training course, like in a swimming pool 541 00:26:27,020 --> 00:26:29,000 Speaker 1: in New York city. And so I was trying to get, 542 00:26:29,480 --> 00:26:33,740 Speaker 1: you know, one of those huge inflatable, like water obstacle courses, 543 00:26:34,100 --> 00:26:37,080 Speaker 1: you know, we were going to like order this $ 10, 000 544 00:26:36,400 --> 00:26:39,659 Speaker 1: inflatable obstacle course from China and then like set it 545 00:26:39,760 --> 00:26:42,040 Speaker 1: up in an Olympic size pool in New York city. 546 00:26:42,300 --> 00:26:45,040 Speaker 1: And it just did not fly. And, you know, we 547 00:26:45,100 --> 00:26:48,480 Speaker 1: had a, a poor Good Shepherd staffer who was in 548 00:26:48,520 --> 00:26:50,980 Speaker 1: charge of trying to find me my swimming pool. And 549 00:26:51,000 --> 00:26:52,919 Speaker 1: she was just like, Ryan, I don't think anyone's going 550 00:26:52,940 --> 00:26:56,350 Speaker 1: to let us inflate this giant obstacle course in the pool. 551 00:26:56,630 --> 00:26:58,609 Speaker 3: I've always wanted to do a puzzle in the Natural 552 00:26:58,650 --> 00:27:00,850 Speaker 3: History Museum, like with the big whale. 553 00:27:01,109 --> 00:27:02,350 Speaker 4: Night at the museum style. 554 00:27:02,810 --> 00:27:07,270 Speaker 3: Yeah, exactly. You have to become like an official partner 555 00:27:07,290 --> 00:27:10,010 Speaker 3: of the museum. And it's like a an annual membership 556 00:27:10,190 --> 00:27:12,870 Speaker 3: that costs $ 30, 000. And then there's all these other hoops 557 00:27:12,890 --> 00:27:13,810 Speaker 3: you have to jump through. 558 00:27:13,910 --> 00:27:16,840 Speaker 4: You can get a Bloomberg terminal with that. Jeez. 559 00:27:17,119 --> 00:27:20,179 Speaker 1: Some of the best locations we've had are like the 560 00:27:20,300 --> 00:27:24,180 Speaker 1: rooftop of the Port Authority bus terminal. On the north 561 00:27:24,240 --> 00:27:27,040 Speaker 1: end of the Port Authority bus terminal, there's an uncovered 562 00:27:27,080 --> 00:27:30,560 Speaker 1: parking deck that anyone can access. And you can look 563 00:27:30,660 --> 00:27:33,770 Speaker 1: down 41st Street all the way to the library, through 564 00:27:33,790 --> 00:27:37,510 Speaker 1: Times Square, through Bryant Park. And at night, it's one 565 00:27:37,530 --> 00:27:40,689 Speaker 1: of the most... incredible places in New York City. And 566 00:27:40,730 --> 00:27:42,780 Speaker 1: it's just sitting there for anyone to come and see, 567 00:27:43,080 --> 00:27:45,679 Speaker 1: or we'll like park a box truck on the side 568 00:27:45,700 --> 00:27:47,740 Speaker 1: of the street and have people go in. And there's 569 00:27:47,780 --> 00:27:50,939 Speaker 1: like a speakeasy type establishment with like a live band 570 00:27:51,080 --> 00:27:53,340 Speaker 1: inside a box truck delivery truck just parked on the 571 00:27:53,380 --> 00:27:55,880 Speaker 1: side of the road. And so the venues that we 572 00:27:55,940 --> 00:27:58,220 Speaker 1: love are those types of unexpected delight that kind of 573 00:27:58,260 --> 00:28:01,100 Speaker 1: like are hidden in that New York City is so 574 00:28:01,700 --> 00:28:02,960 Speaker 1: good at kind of concealing. 575 00:28:04,160 --> 00:28:07,280 Speaker 2: What about like best puzzles, right? So you've talked about 576 00:28:07,320 --> 00:28:09,119 Speaker 2: like The simplest level is like you get handed a 577 00:28:09,140 --> 00:28:10,580 Speaker 2: piece of paper and you do some piece of paper. 578 00:28:10,600 --> 00:28:14,149 Speaker 2: Like certainly like at Midnight Madness with production values, what 579 00:28:14,170 --> 00:28:16,750 Speaker 2: they are like, there are some amount of like doing 580 00:28:16,790 --> 00:28:19,750 Speaker 2: puzzles on cool physical objects. Like what are some like 581 00:28:19,850 --> 00:28:22,770 Speaker 2: cool physical objects that have been purposed as puzzles? 582 00:28:23,050 --> 00:28:25,909 Speaker 1: I have one sitting right here. It's like a Palantir 583 00:28:26,170 --> 00:28:28,210 Speaker 1: orb crystal ball that we distributed. 584 00:28:28,230 --> 00:28:29,170 Speaker 2: You're holding up a crystal ball. 585 00:28:29,770 --> 00:28:32,510 Speaker 1: Yeah, holding up a crystal ball. And it reacts with 586 00:28:32,630 --> 00:28:37,060 Speaker 1: different colors and flashing patterns based on where you are geographically. 587 00:28:37,619 --> 00:28:41,040 Speaker 1: And so there was a whole puzzle in 2021 scattered 588 00:28:41,160 --> 00:28:44,520 Speaker 1: all over Central Park. And as you approach different locations, 589 00:28:44,660 --> 00:28:47,940 Speaker 1: the globe did different things and flash different color sequences. 590 00:28:47,980 --> 00:28:51,710 Speaker 1: And then those were decoded. One of my favorite puzzles from, 591 00:28:52,010 --> 00:28:55,290 Speaker 1: I think this is an Alicia, I don't know, but 592 00:28:55,450 --> 00:28:57,290 Speaker 1: I've read about it in one of the many articles 593 00:28:57,310 --> 00:28:59,790 Speaker 1: that I'm sure you guys said was the circuit board 594 00:28:59,830 --> 00:29:01,890 Speaker 1: where you had to assemble a circuit board and then 595 00:29:01,950 --> 00:29:05,840 Speaker 1: one of the transistors overheated and you discovered that the 596 00:29:05,940 --> 00:29:08,410 Speaker 1: circuit board was actually a, a map of New York 597 00:29:08,450 --> 00:29:10,710 Speaker 1: City subway stations. And when you looked at it through 598 00:29:10,750 --> 00:29:15,020 Speaker 1: a infrared camera, you know, it was identifying which station 599 00:29:15,040 --> 00:29:18,000 Speaker 1: to go to. So that's another example of something that 600 00:29:18,220 --> 00:29:20,340 Speaker 1: lives in my head as a great use of a 601 00:29:20,400 --> 00:29:21,120 Speaker 1: physical object. 602 00:29:37,580 --> 00:29:39,450 Speaker 4: Just to go back to Midnight Madness really quickly. 603 00:29:39,500 --> 00:29:41,260 Speaker 1: I mean, so you have. 604 00:29:41,100 --> 00:29:44,000 Speaker 4: These three to four to five hour puzzles, I believe 605 00:29:44,020 --> 00:29:47,700 Speaker 4: you said. Midnight Madness seems like a different beast entirely 606 00:29:47,740 --> 00:29:49,200 Speaker 4: in that, you know, it runs overnight. 607 00:29:49,580 --> 00:29:51,670 Speaker 2: Yeah, like what is your time expectation for this year's 608 00:29:51,710 --> 00:29:53,570 Speaker 2: Midnight Madness? Like when does it start and when do 609 00:29:53,590 --> 00:29:55,270 Speaker 2: you expect the last team to finish? 610 00:29:55,870 --> 00:29:59,090 Speaker 3: Yeah, about 12 to 14 hours, depending on how fast 611 00:29:59,130 --> 00:30:02,520 Speaker 3: teams are. The idea is to start it early afternoon, 612 00:30:02,600 --> 00:30:06,560 Speaker 3: one or two, and then it ends sometime shortly after midnight. 613 00:30:06,800 --> 00:30:08,440 Speaker 3: Hopefully not too much longer than that. 614 00:30:08,960 --> 00:30:12,580 Speaker 4: So it's in early October. When do you start planning 615 00:30:12,620 --> 00:30:12,940 Speaker 4: for it? 616 00:30:13,400 --> 00:30:16,070 Speaker 3: Typically about a year in advance. So it's about a 617 00:30:16,110 --> 00:30:17,209 Speaker 3: year in the making. 618 00:30:17,910 --> 00:30:20,430 Speaker 2: Do you design games for a lot of big Wall Street? 619 00:30:20,530 --> 00:30:22,910 Speaker 2: Can you say your repeat clients or something? 620 00:30:23,090 --> 00:30:25,330 Speaker 3: Yes, we have a lot of Wall Street clients. That's 621 00:30:25,350 --> 00:30:27,370 Speaker 3: our biggest audience and our biggest client base. 622 00:30:27,880 --> 00:30:29,750 Speaker 1: We have like NDAs. 623 00:30:29,790 --> 00:30:33,770 Speaker 2: In your business, you do like relatively short, like one 624 00:30:33,810 --> 00:30:36,450 Speaker 2: day events for like team building events for companies who 625 00:30:36,490 --> 00:30:38,370 Speaker 2: hire you to design games, right? Yeah. 626 00:30:38,590 --> 00:30:41,450 Speaker 1: Three to four hours long based on how much we 627 00:30:41,650 --> 00:30:43,270 Speaker 1: think that they can take or how much we know 628 00:30:43,310 --> 00:30:46,000 Speaker 1: that they can take. As we have repeat clients, we 629 00:30:46,420 --> 00:30:48,500 Speaker 1: start to understand the culture of the company and what 630 00:30:48,520 --> 00:30:50,760 Speaker 1: they're looking for and what they can handle. And yeah, 631 00:30:50,880 --> 00:30:51,620 Speaker 1: there's been some. 632 00:30:51,640 --> 00:30:52,440 Speaker 2: Who can handle the most? 633 00:30:52,960 --> 00:30:55,230 Speaker 1: Well, you know, there's a difference between who can handle 634 00:30:55,250 --> 00:30:58,090 Speaker 1: the most and who wants to give off the vibe 635 00:30:58,110 --> 00:31:00,790 Speaker 1: like they can handle the most. We can answer both. 636 00:31:02,530 --> 00:31:06,110 Speaker 1: We have NDA. All of these companies are so secretive. 637 00:31:06,890 --> 00:31:07,680 Speaker 2: We'll bleep them out. 638 00:31:08,060 --> 00:31:11,380 Speaker 1: It's really hard. Fortunately, Bridgewater has been very generous that 639 00:31:11,400 --> 00:31:13,680 Speaker 1: they allow us to talk to say that we have 640 00:31:13,740 --> 00:31:16,560 Speaker 1: done many hunts for them. And they actually came to 641 00:31:16,640 --> 00:31:20,610 Speaker 1: us only recently in 2021 after they did Midnight Madness, 642 00:31:20,730 --> 00:31:23,340 Speaker 1: formerly known as Compass, with us. And we've worked with 643 00:31:23,390 --> 00:31:27,160 Speaker 1: them multiple times a year for different teams. And they're 644 00:31:27,200 --> 00:31:27,900 Speaker 1: awesome to work with. 645 00:31:28,400 --> 00:31:30,820 Speaker 2: I do want to know where Bridgewater falls on the 646 00:31:31,120 --> 00:31:33,560 Speaker 2: can't handle things and want to give the impression, but 647 00:31:33,640 --> 00:31:35,300 Speaker 2: it seems rude to make you answer. 648 00:31:35,880 --> 00:31:39,340 Speaker 1: They're great. I mean, don't make us pick between our children. 649 00:31:39,400 --> 00:31:41,420 Speaker 1: We love all of our puzzle children equally. And the 650 00:31:41,460 --> 00:31:44,180 Speaker 1: only thing I'll say is specifically the team we work 651 00:31:44,220 --> 00:31:47,870 Speaker 1: for does love the puzzly puzzles. You know, there's definitely 652 00:31:47,880 --> 00:31:51,530 Speaker 1: a gradient of people that love the experience, they love 653 00:31:51,550 --> 00:31:55,520 Speaker 1: the locations and the feedback we get from Bridgewater, at 654 00:31:55,540 --> 00:31:59,420 Speaker 1: least the point of contact who helps us plan their 655 00:31:59,460 --> 00:32:01,660 Speaker 1: events is that they want the puzzles, they want the goods. 656 00:32:02,280 --> 00:32:05,480 Speaker 3: Yeah, they want the brutality. They like it to be difficult. 657 00:32:05,860 --> 00:32:08,330 Speaker 1: And it's been really interesting for us as, again, outsiders, 658 00:32:08,350 --> 00:32:11,010 Speaker 1: like we both went to art school, figuring out what's 659 00:32:11,030 --> 00:32:13,890 Speaker 1: the difference between like a Quant hedge fund and a 660 00:32:13,910 --> 00:32:17,290 Speaker 1: Bridgewater and a Goldman and where they all function in 661 00:32:17,350 --> 00:32:18,930 Speaker 1: this world. It's been quite the education. 662 00:32:19,710 --> 00:32:22,810 Speaker 3: They each have a different culture that manifests differently in 663 00:32:22,850 --> 00:32:25,510 Speaker 3: our games. And often the culture is kind of inspired 664 00:32:25,550 --> 00:32:26,370 Speaker 3: by the founder. 665 00:32:26,450 --> 00:32:27,550 Speaker 2: Like some of. 666 00:32:27,520 --> 00:32:30,320 Speaker 3: Them are work hard, play hard, and they like to 667 00:32:30,380 --> 00:32:33,420 Speaker 3: party hard. And that's a culture that emanates from the founder. 668 00:32:33,460 --> 00:32:36,340 Speaker 3: And some of them are more like about work-life balance 669 00:32:36,400 --> 00:32:40,430 Speaker 3: and generosity. And they each kind of have a very 670 00:32:40,470 --> 00:32:44,050 Speaker 3: distinct culture that we can recognize just in our limited 671 00:32:44,090 --> 00:32:47,350 Speaker 3: touch points through our games. And also when a lot 672 00:32:47,370 --> 00:32:49,430 Speaker 3: of our client base was more tech, like Google and 673 00:32:49,450 --> 00:32:53,590 Speaker 3: Meta and tech firms, we joke about like making our 674 00:32:53,650 --> 00:32:56,270 Speaker 3: own private investments based on how well we see people 675 00:32:56,330 --> 00:32:59,910 Speaker 3: doing in our games. Because we definitely recognize that companies 676 00:32:59,950 --> 00:33:02,790 Speaker 3: that are doing well for us were also doing well 677 00:33:02,810 --> 00:33:03,550 Speaker 3: in the market. 678 00:33:04,650 --> 00:33:07,070 Speaker 1: And then when those same companies three years later stopped 679 00:33:07,110 --> 00:33:09,650 Speaker 1: doing well, it meant something. 680 00:33:10,970 --> 00:33:11,130 Speaker 3: Hmm. 681 00:33:11,700 --> 00:33:13,740 Speaker 2: Stop doing around the puzzles. The puzzles were like a 682 00:33:13,980 --> 00:33:18,260 Speaker 2: leading indicator of the stock or. Exactly. Yeah. Has a 683 00:33:18,280 --> 00:33:20,340 Speaker 2: hedge fund ever been like, you're good at puzzles. Come 684 00:33:20,380 --> 00:33:20,860 Speaker 2: work for us. 685 00:33:21,660 --> 00:33:25,180 Speaker 1: Not in-house, but we know some hedge funds that do 686 00:33:25,220 --> 00:33:28,480 Speaker 1: have in-house puzzle creators and have hired our friends as 687 00:33:28,520 --> 00:33:31,220 Speaker 1: in-house puzzle creators. So it exists. It's a thing. 688 00:33:31,260 --> 00:33:32,160 Speaker 2: I've seen some of that. 689 00:33:32,220 --> 00:33:32,460 Speaker 4: Right. 690 00:33:32,780 --> 00:33:37,380 Speaker 2: Because like, clearly, like there is a big, like recruiting 691 00:33:37,420 --> 00:33:39,880 Speaker 2: dynamic of a lot of these firms like to hire 692 00:33:39,920 --> 00:33:42,170 Speaker 2: people who are good at puzzles. They like to pose 693 00:33:42,210 --> 00:33:44,890 Speaker 2: puzzles to them as part of the recruiting process. They 694 00:33:44,910 --> 00:33:47,970 Speaker 2: like to attract people who like puzzles. So that seemed 695 00:33:47,990 --> 00:33:50,989 Speaker 2: like an overlap. In the puzzle creator community, is there 696 00:33:51,030 --> 00:33:53,250 Speaker 2: like a trend where a lot of people have a 697 00:33:53,290 --> 00:33:54,910 Speaker 2: certain degree or a certain background? 698 00:33:55,550 --> 00:34:00,620 Speaker 1: Certainly, yeah. Stats, math, business, definitely. But then there's also 699 00:34:00,630 --> 00:34:03,280 Speaker 1: people who do a lot of more linguistic puzzles. There's 700 00:34:03,300 --> 00:34:05,680 Speaker 1: like a whole kind of like the crossword, you know, 701 00:34:05,700 --> 00:34:09,000 Speaker 1: that whole world is a little more linguistic and they 702 00:34:09,020 --> 00:34:10,260 Speaker 1: have a different background. 703 00:34:10,850 --> 00:34:14,160 Speaker 2: When I've done puzzle hunts, there's always a cryptic crossword 704 00:34:14,260 --> 00:34:17,200 Speaker 2: cluing type puzzle, and I'm always the guy who solves those. 705 00:34:17,219 --> 00:34:18,739 Speaker 2: That's my one contribution to the team. 706 00:34:19,160 --> 00:34:19,859 Speaker 4: Right, right. 707 00:34:20,380 --> 00:34:23,960 Speaker 1: A good puzzle creation team has... A good puzzle is 708 00:34:24,000 --> 00:34:25,900 Speaker 1: created by people with a lot of different backgrounds. 709 00:34:25,920 --> 00:34:28,120 Speaker 2: I assume that when you do team building events, it's 710 00:34:28,200 --> 00:34:31,320 Speaker 2: a company for 200 people, but do you ever have 711 00:34:32,030 --> 00:34:33,610 Speaker 2: these five people who are going to do a puzzle 712 00:34:33,620 --> 00:34:34,110 Speaker 2: hunt together? 713 00:34:34,469 --> 00:34:34,689 Speaker 4: Yeah. 714 00:34:35,330 --> 00:34:37,890 Speaker 1: I mean, yeah. If you can afford us, we'll do it. 715 00:34:37,950 --> 00:34:40,739 Speaker 1: And we've done... groups as small as four and groups 716 00:34:40,860 --> 00:34:43,799 Speaker 1: as large as, what, 300, 400, John? 717 00:34:44,320 --> 00:34:46,379 Speaker 2: Wait, can you tell me about the groups of four? Like, 718 00:34:46,420 --> 00:34:47,239 Speaker 2: how does that come in? 719 00:34:47,780 --> 00:34:50,910 Speaker 1: Either someone's birthday. It's a birthday party, usually. 720 00:34:50,930 --> 00:34:52,489 Speaker 2: It's like someone who really likes puzzles. 721 00:34:52,710 --> 00:34:56,030 Speaker 1: Someone who really likes puzzles. And either they can afford 722 00:34:57,010 --> 00:35:00,609 Speaker 1: our services because we just run a past event for them, 723 00:35:00,790 --> 00:35:03,489 Speaker 1: or they have a ton of money and we do 724 00:35:03,530 --> 00:35:06,980 Speaker 1: something completely tailored to them that's like, all about their 725 00:35:07,060 --> 00:35:09,370 Speaker 1: life and all about their 50 years and all about 726 00:35:09,450 --> 00:35:12,370 Speaker 1: their kids. And those are really fun too. 727 00:35:12,790 --> 00:35:17,270 Speaker 3: We've done many birthdays for CEOs of like hedge funds. 728 00:35:17,930 --> 00:35:19,609 Speaker 2: Yeah, I was going to say like, this feels like 729 00:35:19,670 --> 00:35:22,270 Speaker 2: a classic hedge fund manager 50th birthday party. 730 00:35:22,650 --> 00:35:25,330 Speaker 1: We did one hedge fund who said that they wanted, 731 00:35:26,190 --> 00:35:27,690 Speaker 1: maybe if you want to talk about our white whale 732 00:35:27,730 --> 00:35:30,980 Speaker 1: was the one of the co-CEOs of this is a 733 00:35:31,120 --> 00:35:34,140 Speaker 1: small fund. And they said, okay, I'm going to, I 734 00:35:34,200 --> 00:35:38,180 Speaker 1: want to do this across Europe for my 50th birthday. 735 00:35:38,300 --> 00:35:40,819 Speaker 1: And I was like, yes, let's do it. Call us. 736 00:35:41,340 --> 00:35:42,380 Speaker 1: And then they never showed. 737 00:35:42,500 --> 00:35:45,720 Speaker 2: But did you have a preliminary budget? 738 00:35:47,219 --> 00:35:49,879 Speaker 1: No, no, we didn't. We didn't even get that far. 739 00:35:49,940 --> 00:35:51,719 Speaker 1: But it was it was a really it was for 740 00:35:51,739 --> 00:35:55,060 Speaker 1: a fund that was celebrating their 25th anniversary, I think, 741 00:35:55,239 --> 00:35:57,680 Speaker 1: in London. And so we got to build a six 742 00:35:57,700 --> 00:36:00,219 Speaker 1: hour hunt in London. And that was one of our favorites, 743 00:36:00,239 --> 00:36:03,310 Speaker 1: still our favorite jobs to date. But It could have 744 00:36:03,330 --> 00:36:06,350 Speaker 1: been the lead-in to a cross-Europe scavenger hunt, but it 745 00:36:06,530 --> 00:36:07,009 Speaker 1: wasn't to be. 746 00:36:07,210 --> 00:36:09,890 Speaker 2: Yeah. Wait, you said something about you had a lot 747 00:36:09,950 --> 00:36:11,950 Speaker 2: of tech clients and now you have fewer tech clients 748 00:36:12,050 --> 00:36:15,450 Speaker 2: and it's more finance-gearing? What do you think is causing that? 749 00:36:15,590 --> 00:36:21,110 Speaker 1: Yeah, we've definitely seen the shift from when tech was 750 00:36:22,210 --> 00:36:25,069 Speaker 1: the coolest place to be and now these companies have 751 00:36:25,160 --> 00:36:28,970 Speaker 1: matured and they're still great places to work, but there's 752 00:36:28,989 --> 00:36:30,680 Speaker 1: a little less of an edge to them. I think 753 00:36:30,739 --> 00:36:34,910 Speaker 1: we've seen... they're also working a little less hard at 754 00:36:35,090 --> 00:36:38,069 Speaker 1: employer retention and they're pulling back the perks. And so 755 00:36:38,110 --> 00:36:42,680 Speaker 1: we've seen pre-pandemic specifically, we do a lot of like 756 00:36:42,680 --> 00:36:47,040 Speaker 1: 50 to 80% events for big tech companies, growing tech companies, 757 00:36:47,400 --> 00:36:50,180 Speaker 1: that sort of thing. And then post-pandemic, we've seen a 758 00:36:50,780 --> 00:36:53,200 Speaker 1: lot fewer tech companies. And when the tech companies do come, 759 00:36:53,260 --> 00:36:55,450 Speaker 1: this is more of a return to office thing, but 760 00:36:55,530 --> 00:36:57,650 Speaker 1: it's a much smaller group. So people are getting together 761 00:36:58,180 --> 00:37:01,100 Speaker 1: in much smaller groups, they're going out with their, their 762 00:37:01,120 --> 00:37:04,120 Speaker 1: immediate five to 12 team members and not their full 763 00:37:04,140 --> 00:37:06,759 Speaker 1: division or whatever. And so we, at the same time, 764 00:37:06,800 --> 00:37:09,620 Speaker 1: we've seen a lot more hedge funds and AI companies 765 00:37:09,680 --> 00:37:12,940 Speaker 1: coming in. And so, yeah, as the type of company 766 00:37:12,980 --> 00:37:19,110 Speaker 1: where young, ambitious, really smart people work at kind of shifts, 767 00:37:19,530 --> 00:37:21,410 Speaker 1: we do see that in our, in our clients as well. 768 00:37:22,050 --> 00:37:23,830 Speaker 2: So it's like, if you work at Facebook, like 10 769 00:37:23,830 --> 00:37:25,310 Speaker 2: years ago, you were like, Oh, I really want to 770 00:37:25,350 --> 00:37:29,700 Speaker 2: solve puzzles. Like I'm motivated to like, use my brain. 771 00:37:29,760 --> 00:37:31,140 Speaker 2: And now it's like, yeah, I'm going to rest and 772 00:37:31,219 --> 00:37:32,600 Speaker 2: rest and not go on a puzzle hunt. 773 00:37:33,140 --> 00:37:35,839 Speaker 1: I don't want to say exactly, but yeah, that's a 774 00:37:36,040 --> 00:37:37,989 Speaker 1: little bit of the vibe I get. One of the 775 00:37:38,010 --> 00:37:40,270 Speaker 1: reasons that I started reading money stuff was after you 776 00:37:40,310 --> 00:37:43,990 Speaker 1: wrote that huge crypto article, Matt. And at the same time, 777 00:37:44,050 --> 00:37:46,830 Speaker 1: we were building a completely bespoke kind of alternate reality 778 00:37:46,870 --> 00:37:52,210 Speaker 1: game puzzle community for a NFT firm. And we had 779 00:37:52,310 --> 00:37:53,720 Speaker 1: no idea what we were doing in crypto, no idea 780 00:37:53,760 --> 00:37:56,520 Speaker 1: what we were doing with NFTs. And so Reading your 781 00:37:56,560 --> 00:37:58,580 Speaker 1: article helped me like get my head around this whole 782 00:37:58,620 --> 00:38:02,200 Speaker 1: concept as we were building out this game, community, world, 783 00:38:02,219 --> 00:38:05,580 Speaker 1: IP universe that we were hired to do kind of 784 00:38:05,620 --> 00:38:09,020 Speaker 1: like as an extension of the Bored Ape Yacht Club universe. 785 00:38:09,340 --> 00:38:13,240 Speaker 1: And it was- Did you get paid? We did get paid. 786 00:38:13,260 --> 00:38:13,340 Speaker 3: Yeah. 787 00:38:13,450 --> 00:38:17,570 Speaker 1: Yeah, we got paid. It was an incredible, incredible experience. 788 00:38:17,590 --> 00:38:22,290 Speaker 1: And we got to create characters and create stories. And 789 00:38:22,410 --> 00:38:25,660 Speaker 1: sometimes our events are a little more puzzle-y oriented. And 790 00:38:25,680 --> 00:38:28,520 Speaker 1: this was the most built out we've ever created a 791 00:38:28,560 --> 00:38:32,439 Speaker 1: whole world. We created locations and characters and plot points 792 00:38:32,500 --> 00:38:38,850 Speaker 1: and betrayals and stashed puzzles in lockers at the LAX 793 00:38:38,910 --> 00:38:42,190 Speaker 1: airport and in bars in London and slipped burner phones. 794 00:38:42,270 --> 00:38:44,890 Speaker 1: And it was a really fun event. Now, the project 795 00:38:44,910 --> 00:38:47,540 Speaker 1: as a whole didn't survive more than a few years, 796 00:38:47,640 --> 00:38:49,839 Speaker 1: but we kind of were in this at one of the, 797 00:38:50,020 --> 00:38:53,420 Speaker 1: the crypto bull markets. And, uh, that's a real moment 798 00:38:53,460 --> 00:38:53,860 Speaker 1: in time. 799 00:38:53,960 --> 00:38:56,040 Speaker 2: I know we've talked about hedge funds and tech firms. 800 00:38:56,239 --> 00:39:00,000 Speaker 2: Like we didn't even talk about like, what does the 801 00:39:00,040 --> 00:39:02,299 Speaker 2: chart of like your crypto exposure look like? 802 00:39:02,600 --> 00:39:04,900 Speaker 1: Yeah. 803 00:39:04,980 --> 00:39:06,960 Speaker 2: It was all crypto firms and then you never heard 804 00:39:06,980 --> 00:39:07,440 Speaker 2: from them again. 805 00:39:07,680 --> 00:39:08,779 Speaker 1: It's that's pretty much it. 806 00:39:08,840 --> 00:39:09,160 Speaker 2: Yeah. 807 00:39:09,739 --> 00:39:11,839 Speaker 1: We haven't done any of our private kind of team 808 00:39:11,860 --> 00:39:14,630 Speaker 1: building events for crypto firms. This was a, kind of 809 00:39:14,650 --> 00:39:18,860 Speaker 1: like a public-facing event for the crypto community. And it 810 00:39:18,890 --> 00:39:21,200 Speaker 1: was led by a guy who wanted to create this 811 00:39:21,300 --> 00:39:24,480 Speaker 1: series of IP around some of the Bored Apes, or 812 00:39:24,719 --> 00:39:26,870 Speaker 1: to be more specific, the Mutant Apes, which is a 813 00:39:26,910 --> 00:39:28,690 Speaker 1: whole sub-genre of apes. 814 00:39:29,469 --> 00:39:30,290 Speaker 2: And I think we'll end it there. 815 00:39:30,730 --> 00:39:33,210 Speaker 1: Yeah, yeah, yeah, exactly. 816 00:39:34,830 --> 00:39:36,520 Speaker 2: John and Ryan, thank you so much for coming on. 817 00:39:36,530 --> 00:39:37,049 Speaker 2: This was fun. 818 00:39:37,469 --> 00:39:38,070 Speaker 3: Thank you for having us. 819 00:39:38,070 --> 00:39:40,319 Speaker 1: It's great to be here. Hope to see you on 820 00:39:40,340 --> 00:39:40,700 Speaker 1: the streets. 821 00:39:41,030 --> 00:39:41,930 Speaker 4: Thank you, guys. 822 00:39:42,300 --> 00:39:43,680 Speaker 1: Honored to be your sanctuary guests. 823 00:39:44,140 --> 00:39:51,250 Speaker 2: Yeah, wow, what a distinction. And that was the Money 824 00:39:51,270 --> 00:39:52,830 Speaker 2: Stuff podcast. I'm Matt Levine. 825 00:39:53,050 --> 00:39:54,090 Speaker 4: And I'm Katie Greifeld. 826 00:39:54,550 --> 00:39:56,609 Speaker 2: You can find my work by subscribing to the Money 827 00:39:56,630 --> 00:39:58,470 Speaker 2: Stuff newsletter on Bloomberg.com. 828 00:39:59,290 --> 00:40:01,689 Speaker 4: And you can find me on Bloomberg TV every day 829 00:40:01,870 --> 00:40:04,759 Speaker 4: on open interest between 9 to 11 a.m. Eastern. 830 00:40:04,780 --> 00:40:06,320 Speaker 2: We'd love to hear from you. You can send an 831 00:40:06,360 --> 00:40:10,000 Speaker 2: email to moneypod at Bloomberg.net. Ask us a question and 832 00:40:10,020 --> 00:40:10,960 Speaker 2: we might answer it on air. 833 00:40:11,540 --> 00:40:13,660 Speaker 4: You can also subscribe to our show wherever you're listening 834 00:40:13,700 --> 00:40:15,739 Speaker 4: right now and leave us a review. It helps more 835 00:40:15,780 --> 00:40:16,520 Speaker 4: people find the show. 836 00:40:17,480 --> 00:40:20,200 Speaker 2: The Money Stuff Podcast is produced by Anna Mazarakis and 837 00:40:20,239 --> 00:40:20,940 Speaker 2: Moses Andam. 838 00:40:21,280 --> 00:40:23,200 Speaker 4: Our theme music was composed by Blake Maples. 839 00:40:23,700 --> 00:40:25,820 Speaker 2: Brendan Francis Noonan is our executive producer. 840 00:40:26,120 --> 00:40:28,150 Speaker 4: And Sage Bauman is Bloomberg's head of podcasts. 841 00:40:28,590 --> 00:40:30,890 Speaker 2: Thanks for listening to The Money Stuff Podcast. We'll be 842 00:40:30,910 --> 00:40:32,270 Speaker 2: back next week with more stuff.