Meeting Title: CSO Client Presentation Dry Run Date: 2026-01-14 Meeting participants: Greg Stoutenburg, Luke Scorziell, Amber Lin, Uttam Kumaran, Clarence Stone
WEBVTT
1 00:00:19.060 ⇒ 00:00:20.000 Greg Stoutenburg: Yeah, exactly.
2 00:00:21.560 ⇒ 00:00:23.980 Greg Stoutenburg: Alright, can we try and help with it?
3 00:00:38.070 ⇒ 00:00:42.769 Greg Stoutenburg: Or… Yeah, because I can only be one owner.
4 00:00:42.770 ⇒ 00:00:44.020 Luke Scorziell: How’s it going, Greg?
5 00:00:44.020 ⇒ 00:00:45.480 Greg Stoutenburg: Hey, doing alright, how are you?
6 00:00:45.900 ⇒ 00:00:46.720 Luke Scorziell: Good.
7 00:00:46.890 ⇒ 00:00:48.769 Luke Scorziell: Like the, is that a Bulls jersey?
8 00:00:49.390 ⇒ 00:00:54.720 Greg Stoutenburg: I’m in my girlfriend’s loft. That’s… Thumbs. Let’s see.
9 00:00:55.500 ⇒ 00:00:56.559 Luke Scorziell: Looks like a…
10 00:00:56.560 ⇒ 00:00:58.910 Greg Stoutenburg: Iverson, whatever team he played for.
11 00:00:59.490 ⇒ 00:01:00.790 Luke Scorziell: Just as long ago.
12 00:01:00.790 ⇒ 00:01:07.910 Greg Stoutenburg: hockey jerseys, I’ll have something to say. Oh, are you a hockey fan? We got Messi and Pelley.
13 00:01:07.910 ⇒ 00:01:08.809 Luke Scorziell: Oh, that’s cool.
14 00:01:08.810 ⇒ 00:01:12.380 Greg Stoutenburg: Pele? I don’t know. Yeah, yeah.
15 00:01:12.590 ⇒ 00:01:14.139 Luke Scorziell: What hockey teams do you like?
16 00:01:14.310 ⇒ 00:01:17.010 Greg Stoutenburg: So, Detroit born and raised, so.
17 00:01:17.050 ⇒ 00:01:18.160 Luke Scorziell: Okay, I see.
18 00:01:18.390 ⇒ 00:01:20.419 Greg Stoutenburg: Red Wings, that’s the end of the sentence.
19 00:01:20.740 ⇒ 00:01:27.830 Luke Scorziell: Dang. Dang. Yeah. I’m a… I grew up a huge Ducks fan. I was watching that game last night against the Stars for a little bit.
20 00:01:28.200 ⇒ 00:01:41.140 Greg Stoutenburg: You know, so on Monday… on Monday night, the Red Wings retired Sergei Fedorov’s number, finally, and the thing that he says was the mistake of his career was in 2003, he left for the Ducks.
21 00:01:43.470 ⇒ 00:01:44.559 Luke Scorziell: Oh, that’s crazy.
22 00:01:44.560 ⇒ 00:01:50.539 Greg Stoutenburg: I think he eventually, like, tried to come back or something, but I don’t know, I mean, you know, professional athletes, their career’s only gonna be so long.
23 00:01:50.540 ⇒ 00:01:51.120 Luke Scorziell: Yeah, yeah.
24 00:01:51.120 ⇒ 00:02:01.160 Greg Stoutenburg: you know, he played 13 seasons for the Wings. I don’t know how old he might have been by the time he realized it was a mistake to go to Anaheim. Like, dude, you’re 40. It’s time to open a vineyard.
25 00:02:01.160 ⇒ 00:02:05.889 Luke Scorziell: Yeah, exactly. I know, well, it’s kind of, I was at a Blackhawks stand.
26 00:02:06.050 ⇒ 00:02:11.119 Luke Scorziell: So it was in Chicago, it was Blackhawks versus the Maple Leafs, and it was, like, one of their, like, original six.
27 00:02:11.120 ⇒ 00:02:11.510 Greg Stoutenburg: Yeah.
28 00:02:11.510 ⇒ 00:02:14.120 Luke Scorziell: Theories. It was really cool, and it’s…
29 00:02:14.670 ⇒ 00:02:28.089 Luke Scorziell: you know, obviously love Ducks hockey and everything, but it felt a little different… Yeah. …in the, like, Middle West, and especially those two original six teams. Red Wings are too, right? Yeah. So, yeah, it was just a little bit, like…
30 00:02:28.090 ⇒ 00:02:28.670 Greg Stoutenburg: Yeah.
31 00:02:28.670 ⇒ 00:02:30.249 Luke Scorziell: It’s like, whoa, this is different.
32 00:02:30.250 ⇒ 00:02:31.340 Greg Stoutenburg: religion.
33 00:02:31.340 ⇒ 00:02:36.689 Luke Scorziell: Yeah, because the… like, we were literally in standing room, and I had never seen that before.
34 00:02:36.840 ⇒ 00:02:37.500 Luke Scorziell: Like, I…
35 00:02:38.140 ⇒ 00:02:43.850 Luke Scorziell: I didn’t know that standing room was a thing, where you just stood in the back and there was, like, literally just not a seat for you.
36 00:02:43.850 ⇒ 00:02:46.329 Greg Stoutenburg: Yeah. I didn’t like that once.
37 00:02:46.760 ⇒ 00:02:47.519 Luke Scorziell: Alright, yeah.
38 00:02:47.520 ⇒ 00:03:02.899 Greg Stoutenburg: I lived in Chicago for a time, yeah, and I went to one, but I went to it with my friends who were Pittsburgh fans, and so they were like, oh, you know what would be fun? Let’s paint, like, pens on our chests in yellow paint. You know, this is the kind of idea you have when you’re 18.
39 00:03:02.900 ⇒ 00:03:03.610 Luke Scorziell: Yeah.
40 00:03:03.610 ⇒ 00:03:08.610 Greg Stoutenburg: And, and we did that, and, like, started getting threats from Chicago fans.
41 00:03:09.040 ⇒ 00:03:11.750 Greg Stoutenburg: I don’t know if we should have done this, guys.
42 00:03:11.920 ⇒ 00:03:15.959 Greg Stoutenburg: I’m gonna put my sweatshirt back on, because I just wanted to watch the game.
43 00:03:16.300 ⇒ 00:03:28.179 Luke Scorziell: Yeah, yeah, no, I had that same thought. We were… it was, like, me and my girlfriend and a couple friends in Chicago, and we just were like, oh, I wonder if the Blackhawks are playing tonight, so we, like, went to a game, or saw they were, and then went.
44 00:03:28.310 ⇒ 00:03:31.099 Luke Scorziell: I was like, I’m just gonna wear, like, very tame.
45 00:03:31.420 ⇒ 00:03:33.280 Luke Scorziell: Because I have no clue what the culture here is.
46 00:03:33.280 ⇒ 00:03:36.580 Greg Stoutenburg: Right, right. Don’t want to wear gang colors by accident, you know?
47 00:03:36.580 ⇒ 00:03:37.300 Luke Scorziell: Yeah.
48 00:03:37.300 ⇒ 00:03:41.119 Greg Stoutenburg: Well, it’s beige. Any team can wear beige, right? You know?
49 00:03:41.120 ⇒ 00:03:44.790 Luke Scorziell: Yeah, yeah, that’s true. So…
50 00:03:44.910 ⇒ 00:03:46.530 Luke Scorziell: Are you in Detroit right now?
51 00:03:46.750 ⇒ 00:03:52.290 Greg Stoutenburg: No, I am in York, Pennsylvania, which is where I live now. Okay. Yep. Yep.
52 00:03:52.290 ⇒ 00:03:53.000 Luke Scorziell: Nice.
53 00:03:53.710 ⇒ 00:03:54.660 Luke Scorziell: Nice.
54 00:03:54.660 ⇒ 00:03:55.890 Greg Stoutenburg: Yeah. How about you?
55 00:03:56.570 ⇒ 00:04:03.189 Luke Scorziell: I’m… literally right now in Santa Monica, but, I think I live, like, 3 blocks, actually, from Ember.
56 00:04:03.460 ⇒ 00:04:07.019 Luke Scorziell: So, in West LA, which is kind of crazy.
57 00:04:09.060 ⇒ 00:04:09.890 Luke Scorziell: Nice.
58 00:04:10.650 ⇒ 00:04:13.400 Greg Stoutenburg: Never been there, just know about the Everclear song.
59 00:04:14.050 ⇒ 00:04:15.740 Luke Scorziell: What song of it?
60 00:04:16.050 ⇒ 00:04:17.050 Greg Stoutenburg: Santa Monica.
61 00:04:17.550 ⇒ 00:04:19.919 Luke Scorziell: Oh, oh, oh. Yeah.
62 00:04:20.279 ⇒ 00:04:20.820 Greg Stoutenburg: No.
63 00:04:20.829 ⇒ 00:04:24.359 Luke Scorziell: That’s not anything, too.
64 00:04:25.349 ⇒ 00:04:26.629 Luke Scorziell: Well, I don’t know.
65 00:04:28.029 ⇒ 00:04:29.959 Luke Scorziell: It’s got its ups and its downs.
66 00:04:30.210 ⇒ 00:04:30.900 Greg Stoutenburg: Yeah.
67 00:04:31.730 ⇒ 00:04:35.569 Greg Stoutenburg: Well, yeah, I mean, just…
68 00:04:35.670 ⇒ 00:04:38.090 Greg Stoutenburg: You know how it is, never, never rip on…
69 00:04:38.250 ⇒ 00:04:41.250 Greg Stoutenburg: California weather, when talking to anyone else.
70 00:04:42.190 ⇒ 00:04:44.919 Greg Stoutenburg: We won’t be sympathetic.
71 00:04:46.690 ⇒ 00:04:47.789 Greg Stoutenburg: Let’s see what we have here.
72 00:04:47.790 ⇒ 00:04:50.459 Luke Scorziell: I have my, my sweatshirt on.
73 00:04:50.630 ⇒ 00:04:55.419 Greg Stoutenburg: What is it? What is it, like, 65?
74 00:04:55.420 ⇒ 00:04:59.069 Luke Scorziell: Let me see… Coming out of that.
75 00:05:03.960 ⇒ 00:05:07.129 Luke Scorziell: It’s, it’s a cool 74.
76 00:05:09.380 ⇒ 00:05:11.810 Greg Stoutenburg: That’s great.
77 00:05:12.500 ⇒ 00:05:29.269 Greg Stoutenburg: Yeah, being a… so I’m… yeah, being a born northerner, in the winter, I like to go down to Fort Lauderdale just to be warm for, like, a week. And, the coldest day… the coldest day when it was still hot enough that I wanted to get in the water and cool off was, 72.
78 00:05:31.260 ⇒ 00:05:32.060 Greg Stoutenburg: Yeah.
79 00:05:32.280 ⇒ 00:05:33.410 Luke Scorziell: Thanks. Yeah.
80 00:05:33.410 ⇒ 00:05:37.360 Greg Stoutenburg: Again, that’s… that’s also, like, you know, that’s… that’s Atlantic water, I think.
81 00:05:37.360 ⇒ 00:05:38.340 Luke Scorziell: Yeah, yeah.
82 00:05:38.340 ⇒ 00:05:39.369 Greg Stoutenburg: the water for you.
83 00:05:39.660 ⇒ 00:05:41.999 Luke Scorziell: Yeah, no, the Pacific is, like.
84 00:05:42.130 ⇒ 00:05:45.939 Luke Scorziell: I guess it’s freezing cold. I’ve only ever really been out here,
85 00:05:46.100 ⇒ 00:05:47.300 Luke Scorziell: So I haven’t been in the airline.
86 00:05:47.470 ⇒ 00:05:49.450 Luke Scorziell: Atlantic, or in the…
87 00:05:50.020 ⇒ 00:05:50.550 Greg Stoutenburg: Yeah.
88 00:05:50.550 ⇒ 00:05:53.729 Luke Scorziell: I want to do, like, a Caribbean trip, but I don’t know. We’ll see.
89 00:05:53.850 ⇒ 00:05:54.580 Luke Scorziell: Wow.
90 00:05:54.780 ⇒ 00:06:07.279 Greg Stoutenburg: Yeah, I went on a Caribbean trip one time, and it was during the time I lived in Chicago, and that was the one week where, against all odds, it was warmer in Chicago than it was in Nassau, and I was like.
91 00:06:07.280 ⇒ 00:06:07.860 Luke Scorziell: No, I…
92 00:06:08.160 ⇒ 00:06:10.330 Greg Stoutenburg: This was supposed to be a getaway.
93 00:06:10.530 ⇒ 00:06:11.830 Greg Stoutenburg: We’re here.
94 00:06:12.630 ⇒ 00:06:18.710 Luke Scorziell: That’s funny. Yeah, I know, the weather can be like that. I was… when I… when we were in Chicago, it was like…
95 00:06:20.220 ⇒ 00:06:24.820 Luke Scorziell: It was, like, November, mid-November, right before Thanksgiving, and the weather was, like…
96 00:06:25.350 ⇒ 00:06:38.459 Luke Scorziell: I think it was in the 70s, and everyone was like, this is such a nice weekend, like, ugh, like, you’re so lucky, and I was like, oh, Chicago’s not that bad. And then as we were leaving, it, like, turned into… there was, like, this bitter wind, and I was just…
97 00:06:38.460 ⇒ 00:06:39.190 Greg Stoutenburg: Yeah.
98 00:06:39.190 ⇒ 00:06:43.360 Luke Scorziell: that’s different. I don’t feel that in SoCal.
99 00:06:43.570 ⇒ 00:06:44.480 Greg Stoutenburg: Yeah.
100 00:06:44.950 ⇒ 00:06:47.400 Greg Stoutenburg: And is that… are you… are you from California?
101 00:06:47.830 ⇒ 00:06:50.799 Luke Scorziell: Yeah, yeah, I grew up, like, 2 hours outside of LA.
102 00:06:50.800 ⇒ 00:06:51.620 Greg Stoutenburg: Okay.
103 00:06:52.310 ⇒ 00:06:53.970 Luke Scorziell: Born and raised here.
104 00:06:54.360 ⇒ 00:06:54.900 Greg Stoutenburg: Cool.
105 00:06:55.920 ⇒ 00:06:56.530 Greg Stoutenburg: Nice.
106 00:06:56.530 ⇒ 00:06:57.280 Luke Scorziell: So…
107 00:06:58.290 ⇒ 00:06:59.060 Greg Stoutenburg: I’m gonna load.
108 00:06:59.060 ⇒ 00:07:00.769 Luke Scorziell: What brought you down to Pennsylvania?
109 00:07:01.570 ⇒ 00:07:11.879 Greg Stoutenburg: Well, so that was, career number one brought me down to Pennsylvania. So I got my philosophy PhD in 2016, and I was.
110 00:07:11.880 ⇒ 00:07:12.230 Luke Scorziell: stuff.
111 00:07:12.230 ⇒ 00:07:16.190 Greg Stoutenburg: Old-time professor at York College of Pennsylvania.
112 00:07:16.190 ⇒ 00:07:17.790 Amber Lin: Wow!
113 00:07:17.790 ⇒ 00:07:19.530 Greg Stoutenburg: Yeah, yeah, yeah, yeah, yeah.
114 00:07:19.530 ⇒ 00:07:22.229 Amber Lin: It’s different from what you do right now.
115 00:07:22.230 ⇒ 00:07:32.089 Greg Stoutenburg: It is. So, yeah, yep, philosophy PhD 2016, professor, classes, you know, paper.
116 00:07:32.420 ⇒ 00:07:40.559 Greg Stoutenburg: thing. And yeah, so that’s why I moved here. And then within, you know, within a few years of doing that work, I was like.
117 00:07:40.610 ⇒ 00:07:54.049 Greg Stoutenburg: this act, like, actually, this isn’t for me. The PhD was great, and, you know, working with students who were interested was great, but, like, it’s like, you go through all this work to do this thing because you’re really interested in it, but then that’s just not the full-time job.
118 00:07:54.620 ⇒ 00:08:11.569 Greg Stoutenburg: It’s just not the job. The job is actually getting uninterested freshmen through their critical thinking course that they only took because it sounded easier than math. Like, it’s like, alright, well, I enjoyed writing a dissertation, like, I enjoyed that whole culture and things like that, but it’s like, I don’t want to do this, so…
119 00:08:11.570 ⇒ 00:08:16.530 Amber Lin: What did you do your dissertation on? I’m so curious. Like, what area of philosophy?
120 00:08:16.530 ⇒ 00:08:24.710 Greg Stoutenburg: Yeah, epistemology. So my dissertation was on skepticism about knowledge, and what reasons for believing are, and what it would take to ever have them.
121 00:08:24.850 ⇒ 00:08:28.830 Amber Lin: Yeah. Can you give me an example of what that means?
122 00:08:29.070 ⇒ 00:08:39.019 Greg Stoutenburg: Yeah, sure. So here’s something you probably think is true, right? Like, if I know… if I know that I have glasses in my hand.
123 00:08:39.640 ⇒ 00:08:48.339 Greg Stoutenburg: Then I also know there is something in my hand, right? Or if I know that I have glasses in my hand, then I know that there are physical objects in the world.
124 00:08:49.040 ⇒ 00:08:51.310 Amber Lin: Seems pretty obvious, right? Yes. Seems pretty obvious.
125 00:08:51.710 ⇒ 00:09:04.480 Greg Stoutenburg: Or, if I know, but, well, basically, you can very quickly go from that principle that it seems like you accept, that everybody would accept, to just, like, you don’t know anything. Here’s an example, right?
126 00:09:04.570 ⇒ 00:09:20.010 Greg Stoutenburg: I… I might think something like this. I know that when this meeting is over, I’m going to, put in a little more work for some clients, and then I will have dinner in a couple hours, right? It seems like I know something like that, right?
127 00:09:20.120 ⇒ 00:09:27.149 Greg Stoutenburg: But if I know that, think about things that would be implied by knowing that. If I know that that will happen, I know I won’t have a heart attack in the next 20 minutes.
128 00:09:29.140 ⇒ 00:09:32.259 Amber Lin: Oh, so it’s the negative that…
129 00:09:32.260 ⇒ 00:09:42.199 Greg Stoutenburg: That’s implied. Well, yeah. Well, so this is the idea, right? It seems like we all accept this. If I know some claim, then I also know anything that would be implied by it.
130 00:09:42.410 ⇒ 00:09:52.490 Greg Stoutenburg: Right? I would have to, right? But then you start to think about things like this. Wait, what are some things that I already know that I… that I can’t possibly know that are implied by something I think I know?
131 00:09:53.340 ⇒ 00:09:54.710 Amber Lin: I just picked one of these.
132 00:09:54.710 ⇒ 00:09:58.009 Greg Stoutenburg: So here’s another example, right? If I know that I will…
133 00:09:58.370 ⇒ 00:10:00.900 Greg Stoutenburg: be going to a Detroit Red Wings game on the first Friday of March.
134 00:10:01.680 ⇒ 00:10:03.879 Greg Stoutenburg: I won’t die between now and then.
135 00:10:04.460 ⇒ 00:10:10.799 Greg Stoutenburg: If… and let’s just keep going, if I know I won’t die between now and then, I don’t need to worry about paying for health insurance.
136 00:10:10.800 ⇒ 00:10:14.219 Amber Lin: I know I can drive as fast as I want.
137 00:10:14.330 ⇒ 00:10:20.740 Greg Stoutenburg: I know I can, have some beers and get on my motorcycle, and I won’t… I won’t be killed, right?
138 00:10:21.580 ⇒ 00:10:28.500 Greg Stoutenburg: You start to realize, wait, there are all these things that we ordinarily say we know that imply all sorts of things we’re sure we don’t know.
139 00:10:29.970 ⇒ 00:10:31.370 Amber Lin: Right? Who cares?
140 00:10:31.370 ⇒ 00:10:35.619 Greg Stoutenburg: But then it looks like this is just an argument that all those things that we ordinarily say we know, we just don’t know them.
141 00:10:37.300 ⇒ 00:10:42.060 Uttam Kumaran: Greg, do you ever know about, like, map crews? Like, this is very similar to what we would do in, like, discrete…
142 00:10:42.130 ⇒ 00:10:44.200 Greg Stoutenburg: Yeah. Like, where we’re putting together proofs.
143 00:10:44.200 ⇒ 00:10:54.420 Uttam Kumaran: Yeah. They’re just more, like, logic proofs, I guess, but, like, in math, it’s sort of similar. It’s like, oh, if you know X is this, and you know this combination is this, then you can also rule out a bunch of these combinations.
144 00:10:54.420 ⇒ 00:10:55.190 Greg Stoutenburg: Right.
145 00:10:55.190 ⇒ 00:10:55.570 Uttam Kumaran: You know?
146 00:10:55.570 ⇒ 00:10:56.520 Greg Stoutenburg: Yeah.
147 00:10:56.520 ⇒ 00:10:57.740 Uttam Kumaran: That’s interesting.
148 00:10:57.740 ⇒ 00:11:14.899 Greg Stoutenburg: Yeah. Yeah, totally. And, I mean, and this kind of argument gets, when someone wants to formalize it, like, you can formalize this sort of argument, and, you know, it’s… I mean, it’s valid, which is why… which is why someone would be concerned about it. You can recognize that the structure of the argument is good, so then it’s just a question of, like, alright, well.
149 00:11:15.280 ⇒ 00:11:28.519 Greg Stoutenburg: what do we do? What can we say we know? So yeah, and sometimes that principle that if you know one thing and you know that something… then you should know anything that’s implied by it. It’s sometimes called the closure principle for knowledge.
150 00:11:28.620 ⇒ 00:11:31.250 Greg Stoutenburg: Yeah.
151 00:11:32.750 ⇒ 00:11:33.150 Uttam Kumaran: Nice.
152 00:11:33.150 ⇒ 00:11:34.940 Amber Lin: That’s so cool.
153 00:11:37.970 ⇒ 00:11:47.379 Amber Lin: I think you must be very good at educating your, the clients that don’t know what they’re talking about, just like your freshman students.
154 00:11:48.530 ⇒ 00:11:54.219 Greg Stoutenburg: Yeah, I hope so. I mean, I will say one thing that does… one thing that I think did come…
155 00:11:54.450 ⇒ 00:12:12.810 Greg Stoutenburg: you know, like, anytime someone goes out of their way to learn something, like, through some course of education, they already have a little bit of it. Something that I think really helped in getting the philosophy PhD, you know, being a professor, things like that, is learning how to figure out what someone doesn’t understand.
156 00:12:12.810 ⇒ 00:12:13.880 Amber Lin: and explain.
157 00:12:13.880 ⇒ 00:12:17.830 Greg Stoutenburg: In a way that actually addresses what’s going to help them understand it.
158 00:12:17.830 ⇒ 00:12:18.849 Amber Lin: So I do think that…
159 00:12:18.850 ⇒ 00:12:19.320 Greg Stoutenburg: That is…
160 00:12:19.320 ⇒ 00:12:19.940 Amber Lin: Aww.
161 00:12:19.940 ⇒ 00:12:23.169 Greg Stoutenburg: I do think that that’s, an asset, and that’s helpful.
162 00:12:23.430 ⇒ 00:12:30.080 Amber Lin: Alright, cool, okay. I have satisfied my curiosity. I will leave it to you guys.
163 00:12:30.260 ⇒ 00:12:39.189 Uttam Kumaran: These are… I feel like these are, like, both of you guys are way smarter than I’ll ever be, so I’m very, very happy to even just listen in. I just… that’s dope.
164 00:12:41.620 ⇒ 00:12:49.249 Uttam Kumaran: Let’s, let’s talk through… Yep. I guess, both Idra and Default, right?
165 00:12:49.250 ⇒ 00:12:49.580 Greg Stoutenburg: Yep.
166 00:12:49.580 ⇒ 00:12:51.390 Uttam Kumaran: If we want to go through that, yep.
167 00:12:51.590 ⇒ 00:12:53.030 Uttam Kumaran: So, yeah, I’m…
168 00:12:53.460 ⇒ 00:13:08.019 Uttam Kumaran: Sorry, this has been just an insane day. I, like, was… yeah, there’s just a lot, I’ll send some updates in Slack, but, yeah, I just want to kind of talk through how we’re gonna tackle both when maybe we spend more time on Hydra,
169 00:13:08.230 ⇒ 00:13:11.349 Uttam Kumaran: you know, I think Awash just got the meeting kind of booked.
170 00:13:11.590 ⇒ 00:13:16.450 Uttam Kumaran: And yeah, I kind of would… would love to…
171 00:13:16.990 ⇒ 00:13:18.649 Uttam Kumaran: I would love to sort of just, like.
172 00:13:18.790 ⇒ 00:13:25.940 Uttam Kumaran: Roleplay, like, how we’re gonna, go through that call, you know, if you wanna do that.
173 00:13:26.830 ⇒ 00:13:32.099 Greg Stoutenburg: Yeah, he booked Hedra for tomorrow, right? Hydra’s the one that’s actually on the.
174 00:13:32.100 ⇒ 00:13:33.370 Uttam Kumaran: Yes, yes.
175 00:13:33.370 ⇒ 00:13:36.339 Greg Stoutenburg: Okay, let’s go to Hedra first.
176 00:13:36.830 ⇒ 00:13:41.730 Greg Stoutenburg: Yeah, and I was able to connect with him, and… clarify something, I…
177 00:13:41.890 ⇒ 00:13:43.619 Greg Stoutenburg: I got confused about how many…
178 00:13:43.840 ⇒ 00:13:53.260 Greg Stoutenburg: how many new work streams we were actually pitching. I mean, I thought it was one, and then he said some things that made me think, oh, is this two? And no, we actually meant a continuation of one that’s already ongoing, so that’.
179 00:13:53.260 ⇒ 00:13:53.900 Uttam Kumaran: Yes.
180 00:13:55.930 ⇒ 00:14:08.200 Greg Stoutenburg: Okay, so for Hydra, from everything I’ve put together and talking to lots of people, I think the deal with Hydra is that we want to recognize that this is a time when
181 00:14:08.460 ⇒ 00:14:10.210 Greg Stoutenburg: Urgency and clarity.
182 00:14:10.360 ⇒ 00:14:17.589 Greg Stoutenburg: Are paramount for making sound business decisions that are going to help them Thrive in the market.
183 00:14:17.590 ⇒ 00:14:23.899 Uttam Kumaran: I would even go one step before. I would just start by, like, introducing yourself and your background.
184 00:14:23.950 ⇒ 00:14:26.670 Greg Stoutenburg: Yeah, sorry, I’m talking to you. Should I pretend that I’m talking to Hedra now?
185 00:14:26.670 ⇒ 00:14:27.939 Uttam Kumaran: That would be great.
186 00:14:28.280 ⇒ 00:14:29.420 Greg Stoutenburg: Okay, thanks, alright.
187 00:14:29.420 ⇒ 00:14:33.260 Uttam Kumaran: Yeah, and I’ll try to play a character, but I’ll also break out. I think, first.
188 00:14:33.580 ⇒ 00:14:39.300 Uttam Kumaran: The client has no clue who you are, they know brain pores, all they know is they know brain pores, they know we do data work.
189 00:14:39.750 ⇒ 00:14:50.110 Uttam Kumaran: I think one is, like, sort of like, yeah, why, like, who’s Greg, and, like, why are you, like, the absolute fucking best at product analytics?
190 00:14:50.110 ⇒ 00:14:53.289 Greg Stoutenburg: It’s because I’ll talk to other people here, and they’ll help.
191 00:14:53.640 ⇒ 00:15:08.989 Greg Stoutenburg: Okay, great. Hey all, hi. Hi, chat, chat, chat. Hi, I’m Greg Stautenberg. I just started Brainforge in late last year, and I’m excited to be taking on the, taking on this project and working with you all.
192 00:15:08.990 ⇒ 00:15:32.789 Greg Stoutenburg: Just a little bit of background on me. I’ve been working in SaaS for the last 4 years, and, specifically focused on product-led growth, motivated by product analytics. Before that, I was a, fun fact, I was a philosophy professor, and, you know, taught classes, and still teach logic sometimes, and things like that. So, I like digging in on ideas, I like clarity, I like explaining things, and I like
193 00:15:32.790 ⇒ 00:15:36.659 Greg Stoutenburg: Putting together the kinds of resources that will allow a person to
194 00:15:36.700 ⇒ 00:16:01.319 Greg Stoutenburg: to make sound decisions, see the direction that they want to go in. Since this is directly related to the project that we’re talking about now, I’ve had a close relationship with Amplitude. I became a power user in about 2021, back when I worked for Stack Overflow, and have used Amplitude for everything from ad hoc reports, like how many people downloaded this thing, to what do we need to do to improve our onboarding.
195 00:16:01.320 ⇒ 00:16:10.469 Greg Stoutenburg: activation, our retention, and upgrade funnels. And that’s been sort of my bread and butter for the last several years.
196 00:16:10.960 ⇒ 00:16:14.359 Greg Stoutenburg: Maybe here there’s a question, something like that, you know.
197 00:16:14.360 ⇒ 00:16:32.989 Uttam Kumaran: Yeah, most of the time, they’ll be like, it’s super great to meet you, Greg, thanks. Yeah, they’ll say, like, I assume you know a little bit about our product. I think at that point, it would also be great for you to basically say what their product is back to them. Be like, yup, I’ve explored your product, love this space, I think you guys are crushing it, the numbers speak for themselves, like…
198 00:16:32.990 ⇒ 00:16:33.360 Greg Stoutenburg: Yep.
199 00:16:33.360 ⇒ 00:16:43.920 Uttam Kumaran: like, this is what I understand about the product, and then you can just kind of, like, lead into… basically, one thing you want to do is understand where people are in understanding what product analytics is.
200 00:16:44.250 ⇒ 00:17:01.329 Uttam Kumaran: you can say, hey, have you worked with Amplitude or done any product analytics in the past? It allows you to understand, like, how dumb you kind of need to go. Yeah. The worst thing you could do is, like, don’t ask that, and then you stay at, like, a certain level, and then you realize, like, people are either, like, way past that level, and you kind of missed it, or they’re way below it, and you’re, like.
201 00:17:01.430 ⇒ 00:17:04.430 Uttam Kumaran: they sort of, like, I don’t even know what’s going on. Yeah.
202 00:17:04.430 ⇒ 00:17:05.730 Greg Stoutenburg: That’s a good call out.
203 00:17:05.730 ⇒ 00:17:06.609 Uttam Kumaran: Yeah.
204 00:17:06.609 ⇒ 00:17:07.359 Greg Stoutenburg: And that’s…
205 00:17:07.369 ⇒ 00:17:21.599 Uttam Kumaran: Sorry, and I don’t have the… I don’t have these, like, written down, but I… No, it’s good. I realize that I do these as you’re talking, and I’m like, what would I do in this situation? Yeah, so I would… one is, like, you kind of want to gas yourself up, so, like, yeah, Stack Overflow is, like, probably the best.
206 00:17:21.619 ⇒ 00:17:29.310 Uttam Kumaran: thing to say in this moment. Talk about your background and amplitude, and then ask them a question, and then basically gas their product up.
207 00:17:29.410 ⇒ 00:17:41.259 Uttam Kumaran: That makes everyone feel nice, and then basically, talk about, like, do you guys, like, what’s your experience with product analytics at the past places you worked at? For context, like, I think Sandra…
208 00:17:41.500 ⇒ 00:17:45.900 Uttam Kumaran: I think she may have worked at Clay before?
209 00:17:46.050 ⇒ 00:17:48.020 Uttam Kumaran: Oh, she worked at,
210 00:17:48.670 ⇒ 00:17:54.239 Uttam Kumaran: What’s the, heyGen? Shooten. HeyGen is, like, this generative video platform where you can, like.
211 00:17:54.240 ⇒ 00:17:54.840 Greg Stoutenburg: Yeah.
212 00:17:54.840 ⇒ 00:18:13.170 Uttam Kumaran: you kind of put in your avatar, and you can generate, like, cold video outbound and stuff like that. So she may or may not have familiarity. This is where you can mention, like, yeah, we did some re… I know you guys have Hostog already in there, but it’s my understanding that maybe nothing has been configured. And then you can start to get into, like.
213 00:18:13.670 ⇒ 00:18:21.099 Uttam Kumaran: just set the stage, and then be like, here’s why this is, like, super dire, you know? So yeah, if you want to go through that, that’s perfect.
214 00:18:21.840 ⇒ 00:18:26.690 Greg Stoutenburg: Yeah, that’s great. So, and I’ll… I’ll… okay.
215 00:18:26.690 ⇒ 00:18:27.829 Greg Stoutenburg: Mike, back on.
216 00:18:27.830 ⇒ 00:18:51.289 Greg Stoutenburg: Yeah, yeah, yeah, it’s great, yeah. I’ve got two, I got a lot of contacts from my colleagues internally, and I spent some time in your app. I think it’s awesome what you’re doing with Hedra. I can see why someone would be really excited about it. I can see why, I can see why, you know, you’d be ready to take this to the next level. It’s very, very cool that someone can just come to your site and sign up and start making these amazing visuals.
217 00:18:51.290 ⇒ 00:18:55.440 Greg Stoutenburg: you know, just using AI. Like, that’s awesome. I think that’s really cool.
218 00:18:55.440 ⇒ 00:19:20.409 Greg Stoutenburg: Now, as far as… as far as taking that sort of thing and turning it into the kind of business and sort of product that’s going to allow a user to come in and be successful with it and makes lots of money, that’s sort of what I’m here to help with. So, if I can just ask, like, I know, again, I know from internal context, you’ve used PostHog a little bit, but, have you… how familiar are you with product analytics?
219 00:19:20.410 ⇒ 00:19:25.269 Greg Stoutenburg: And with tools that are used for the kind of work that we’re going to propose to do.
220 00:19:26.240 ⇒ 00:19:40.710 Uttam Kumaran: Yeah, so we… we installed PostSoft, like, at some point. We have one person from the team, Joe, I think, that installed it, but I don’t necessarily know if we’re looking at anything but, sort of, our Stripe dashboard and, like, our core, like, how many users are signing up.
221 00:19:40.740 ⇒ 00:19:41.810 Greg Stoutenburg: Yeah.
222 00:19:41.950 ⇒ 00:19:51.520 Uttam Kumaran: So I would say I have familiarity with it, but where I’m sure it’s, like, kind of underutilized, which is why I sort of asked Awash, like, hey, maybe you can tell us a little bit more about, like.
223 00:19:51.690 ⇒ 00:19:55.629 Uttam Kumaran: how… what product analytics would… would help us with, you know? I don’t know.
224 00:19:56.200 ⇒ 00:20:11.170 Greg Stoutenburg: Yeah, yeah, okay, yeah, that’s good. And, you know, really, we see that a lot. I’ve… I was at a place where I used Posog for about a year and a half, so I’m familiar with the tool, and it is a very common thing for a company to get a tool set up.
225 00:20:11.170 ⇒ 00:20:21.629 Greg Stoutenburg: Kind of track some fundamental things that are important, things like how many users have signed up, how much money are we making, and things like that. So that’s very common.
226 00:20:21.640 ⇒ 00:20:37.170 Greg Stoutenburg: what we’re gonna propose to do is… is approach this in a much more structured way. So, what we’ll want to do is make sure that we’re tracking all the right events that are gonna line up to core stages of the user journey. Now…
227 00:20:37.170 ⇒ 00:20:41.730 Greg Stoutenburg: Regardless of what tool we use, and we can talk about tools in a little bit,
228 00:20:41.730 ⇒ 00:21:01.339 Greg Stoutenburg: we’re going to want to look at things like, when someone comes to your website, what actions do they take from there? And how many actions are going to result in them doing things like clicking to sign up, successfully sign up, and then doing something important inside of your app. And we’ll call that… that whole sequence activation, right?
229 00:21:01.340 ⇒ 00:21:04.339 Uttam Kumaran: I would even go… I would even go one step further.
230 00:21:04.750 ⇒ 00:21:11.310 Uttam Kumaran: Before the meeting, just think about what events matter. Like, instead of saying, like.
231 00:21:11.450 ⇒ 00:21:31.129 Uttam Kumaran: doing the thing that matters. What matters to them is that people upgrade, people sign up, people sign up for a paid plan up front, people upgrade from upgrade to Enterprise, and people create their first image, video, right? So, like, I would just literally just say that, because the platform is basically, like, an image video generation tool, so I would say.
232 00:21:31.390 ⇒ 00:21:34.410 Uttam Kumaran: The core events, in your example, are…
233 00:21:34.420 ⇒ 00:21:47.629 Uttam Kumaran: the time to… from sign-up, to first video creation, to first image creation, to maybe the… because if you use a tool, and I can give you… I can give you… I have an account on there with a bunch of tokens, I can give you access if you want to look at it.
234 00:21:47.630 ⇒ 00:21:59.820 Uttam Kumaran: But you just go in, you can just say, like, I want this, I want this. So it’s like, how fast can you get that? And then also, I think a big event is, like, upgrades. Like, how are we getting people to upgrade, purchase new tokens? I would just say the events itself.
235 00:21:59.820 ⇒ 00:22:05.329 Greg Stoutenburg: Yeah, yeah. Okay, so basically, instead of giving, like, a general overview, say, you know, in 30 seconds.
236 00:22:05.330 ⇒ 00:22:07.029 Uttam Kumaran: Because it’s only about them.
237 00:22:07.310 ⇒ 00:22:19.330 Uttam Kumaran: Right, right. Meaning, like, meeting… yes, I think the event matters, but what’s also… what hits with them is, like, time to first video generation. They’re like, I got it, I got it, you know?
238 00:22:19.750 ⇒ 00:22:20.470 Greg Stoutenburg: Right.
239 00:22:20.610 ⇒ 00:22:21.360 Greg Stoutenburg: Yeah.
240 00:22:21.380 ⇒ 00:22:45.479 Greg Stoutenburg: Yeah, that’s good. And I’ll come up with a short list, but great. Then, off the top of my head, it’s things like… Yeah, so we’re gonna look at core events that matter for your application, right? Like, how long it takes a user from the time they land to the time they sign up. From the time they sign up until the time that they create their first video. The users who are creating a video to paying for something, hitting some first paywall from usage, and joining the insert name here.
241 00:22:45.480 ⇒ 00:22:46.929 Greg Stoutenburg: plan.
242 00:22:46.930 ⇒ 00:22:57.930 Greg Stoutenburg: the users… what the users who are doing, then, who… who join that plan and then eventually upgrade to a further paid plan. So we’re going to look at some of these things that are really core events in your…
243 00:22:58.040 ⇒ 00:23:11.600 Greg Stoutenburg: applications, and make sure that you understand them really well, and make sure that you know what you need to know in order to make sound decisions. And we’ll help with some of the decision, with some suggestions about how you might go about making those decisions as well, what you can be experimenting on.
244 00:23:13.080 ⇒ 00:23:14.980 Uttam Kumaran: At this point, I would pause and be like.
245 00:23:15.160 ⇒ 00:23:16.860 Uttam Kumaran: What do you think so far, the ring with me?
246 00:23:17.300 ⇒ 00:23:17.870 Greg Stoutenburg: Yeah.
247 00:23:18.160 ⇒ 00:23:31.469 Uttam Kumaran: So I would be like, what do you think so far? Is everyone with me? Do you kind of get the value of PA? You don’t want to move to, like, talking about the how we’re gonna do it if they don’t understand the what at this point, right? So again, just, like, I would just stop at this point and be like, what do you think?
248 00:23:31.640 ⇒ 00:23:41.949 Uttam Kumaran: Yeah. The best thing that can happen is they’re like, dude, you’re spot on, like, we have no idea how long this takes, or, like, we know it takes a long time, we don’t know how to optimize. Like, you want to get them to almost be, like, I have the issue, right?
249 00:23:42.230 ⇒ 00:23:43.270 Greg Stoutenburg: And so…
250 00:23:43.270 ⇒ 00:23:48.800 Uttam Kumaran: Ideally, I wouldn’t move past this point until they are clear on, like.
251 00:23:49.230 ⇒ 00:23:57.310 Uttam Kumaran: that’s the fact that they have this problem. If at this point, they tell you, like, actually, we understand all of our metrics super well, we know, like.
252 00:23:57.400 ⇒ 00:24:13.959 Uttam Kumaran: we’re able to understand, like, the time to each of these four events super, super well, we’re able to run A-B tests, we’re doing that, then you’re like, okay, we have no job, right? I’m telling you so they don’t do that, so you should assume at this point that they will say, yes, yes, yes, we have those problems, right? Yeah, right, yeah.
253 00:24:14.860 ⇒ 00:24:17.870 Greg Stoutenburg: Yeah, no, that’s good, and I’ll give some thought about how to frame
254 00:24:18.020 ⇒ 00:24:30.550 Greg Stoutenburg: how to frame the question at this stage, because that does feel like… it feels to me as well like this is a natural sort of pause. It’s the end of, you know, sort of stage one of a pitch, about how to… how to make sure they’re really seeing the pain point.
255 00:24:30.780 ⇒ 00:24:31.780 Greg Stoutenburg: Yes.
256 00:24:32.290 ⇒ 00:24:36.240 Greg Stoutenburg: Maybe I even just… maybe I even just give it to them, .
257 00:24:36.240 ⇒ 00:24:43.570 Uttam Kumaran: Yeah, like, the biggest, the biggest thing in these calls is, like, really almost just, like, let there be space.
258 00:24:43.750 ⇒ 00:24:46.050 Uttam Kumaran: Like, even if…
259 00:24:46.100 ⇒ 00:25:00.229 Uttam Kumaran: even if at this point, we just, like, the rest of the call is just, like, discussing how bad they are at doing that, that’s a great call, right? Yeah. Because this call is really about, like, getting them to say this is a problem, and we want it solved.
260 00:25:00.250 ⇒ 00:25:04.339 Uttam Kumaran: Rest of it is, like, sort of, like, logistics around MasterW.
261 00:25:04.360 ⇒ 00:25:16.310 Uttam Kumaran: Without this, though, there’s no logistics in the SOW. So really getting them to articulate, like, we have this problem. Ideally, if you can articulate… if they can articulate and get to the point where they’re like.
262 00:25:16.310 ⇒ 00:25:30.029 Uttam Kumaran: yes, you’re right, like, this is a super crowded space, and our build, like, it’s sort of like what Robert mentioned, which is, like, our ability to win is to really be the best at optimizing these flows and getting customers to that point of, like.
263 00:25:30.160 ⇒ 00:25:35.959 Uttam Kumaran: where they’re seeing value for the product, and they want to use it more, and they want to upgrade more. If we don’t…
264 00:25:36.100 ⇒ 00:25:45.130 Uttam Kumaran: if we don’t do that, and we’re not the best in pack at that, like, someone else is gonna come steal our lunch. Again, like, that’s a… they may not say this about themselves, but…
265 00:25:45.130 ⇒ 00:25:50.460 Greg Stoutenburg: Right. Getting them to be, like, articulate the pain in exactly the way you want them.
266 00:25:50.500 ⇒ 00:25:52.129 Uttam Kumaran: Then you kind of have them on the hook.
267 00:25:52.190 ⇒ 00:26:11.700 Uttam Kumaran: The rest, really, after that point, it’s basically showing the depth of our SOW, and like, okay, we’re… we’re very detailed, we’re super experts here, and then it’s sort of logistics on price. But again, nothing happens if they can’t admit the problem. You’re sort of, like, DOA after that.
268 00:26:12.200 ⇒ 00:26:17.419 Greg Stoutenburg: Yeah, yeah, yeah. No, that’s good. Okay, cool.
269 00:26:17.590 ⇒ 00:26:19.760 Greg Stoutenburg: Yeah, I can take that. Okay.
270 00:26:20.100 ⇒ 00:26:21.500 Greg Stoutenburg: Now…
271 00:26:21.800 ⇒ 00:26:28.359 Greg Stoutenburg: from here, I think, yeah, we have that conversation, they say some things, you know, so-and-so set this up, probably someone
272 00:26:28.480 ⇒ 00:26:32.309 Greg Stoutenburg: This is the team where…
273 00:26:32.780 ⇒ 00:26:36.669 Greg Stoutenburg: we get some resistance from the… from leadership, I believe.
274 00:26:38.060 ⇒ 00:26:42.499 Greg Stoutenburg: So here, I have a feeling probably someone will speak up and say, actually, this and this is in good shape.
275 00:26:42.720 ⇒ 00:26:45.600 Greg Stoutenburg: Or, actually, what we really need is…
276 00:26:46.170 ⇒ 00:26:50.430 Greg Stoutenburg: Another sort of insert here. So I probably need to roll with that some.
277 00:26:50.650 ⇒ 00:26:51.550 Greg Stoutenburg: And…
278 00:26:51.550 ⇒ 00:26:57.190 Uttam Kumaran: Really, it’s like, as long as the people who are on the caller makes it, they are like, this is important.
279 00:27:00.730 ⇒ 00:27:13.680 Uttam Kumaran: the logistics of, okay, like, what are the next steps? Like, who needs to sign this? It’s gonna be this guy, Michael, who’s the CEO. What does Michael need to see for us to get this over the line? But again, you’re phrasing it like, we’re on the same team.
280 00:27:13.680 ⇒ 00:27:28.400 Uttam Kumaran: we’re getting over this… the line. This is not our money, this is the company’s budget, right, that we’re both working together to accomplish, versus, like, okay, who do I need to talk to to get the signature on this thing so we can start… it’s like… it’s like, it’s so little about Brainforge.
281 00:27:28.540 ⇒ 00:27:46.609 Uttam Kumaran: It’s only about, like, these people that are gonna be the ones we’re working with. We want to deliver Sandra and Justin, who they always want to call, I think. We want to deliver you guys the best wins, so you, like, Michael is like, our… my growth team is the best fucking grow team in AI right now. This is something that the best growth teams do.
282 00:27:46.640 ⇒ 00:27:57.559 Uttam Kumaran: Like, you will not find a growth team that’s sophisticated in AI that is not leaning on product analytics in a heavy way. I bet you. And if you do, then, like.
283 00:27:57.640 ⇒ 00:28:05.490 Uttam Kumaran: then, like, yeah, then we can cancel this whole thing, right? So, like, but those are things where it’s, like, it makes people really, like, almost in, like, a FOMO. They’re like, you’re totally right, like.
284 00:28:05.490 ⇒ 00:28:09.410 Greg Stoutenburg: The fact that we can’t run A-B tests, the fact that we don’t know what our time to…
285 00:28:09.410 ⇒ 00:28:14.239 Uttam Kumaran: first golden event is the fact that we don’t know what combination of events leads to an upgrade, like.
286 00:28:14.510 ⇒ 00:28:21.960 Uttam Kumaran: the fact that we can’t tell you that within a reasonable amount of time is, like, really, like, what’s gonna lead us down, like, a bad path. And, like.
287 00:28:21.960 ⇒ 00:28:22.610 Greg Stoutenburg: Right.
288 00:28:22.610 ⇒ 00:28:34.809 Uttam Kumaran: these are the… these are the ways you kind of get them to feel this, like, super pain, and it’s… it’s accurate. Like, I don’t know, do you think OpenAI’s not, like, doing heavy product analytics? Like, so, like, what are we… it’s not a debate, you know?
289 00:28:35.360 ⇒ 00:28:56.020 Greg Stoutenburg: Now, it’s not a debate, and I think on something like this, it’s important to recognize as well that, like, there are other AI video generation tools out there. So, it’s not a matter of just having the kit. There are lots of competitors that can do the same thing. The ones that are gonna win are gonna be the ones that win in the market by having the product that’s the most usable, that’s the most sticky.
290 00:28:56.020 ⇒ 00:28:59.149 Greg Stoutenburg: That gets people in the right positions.
291 00:28:59.150 ⇒ 00:29:04.580 Greg Stoutenburg: gets them to pay in some way. And product analytics is how you find out how to do that.
292 00:29:04.850 ⇒ 00:29:05.410 Uttam Kumaran: Yeah.
293 00:29:06.220 ⇒ 00:29:07.440 Uttam Kumaran: Yeah. Exactly.
294 00:29:07.440 ⇒ 00:29:15.910 Greg Stoutenburg: That sounded good. I’ll say that tomorrow, too. Okay. So then, yeah, I mean, I think from here, I don’t know how much more we do in this roleplay from here.
295 00:29:16.400 ⇒ 00:29:17.379 Greg Stoutenburg: So, for me, I think…
296 00:29:17.380 ⇒ 00:29:23.080 Uttam Kumaran: I think, basically, you can just walk through the scope, make sure they understand what the four components are, and the timelines.
297 00:29:23.240 ⇒ 00:29:23.970 Greg Stoutenburg: Yeah.
298 00:29:23.970 ⇒ 00:29:28.249 Uttam Kumaran: Again, you’re mainly… they’re not going to know how this is done, typically, before.
299 00:29:28.630 ⇒ 00:29:29.250 Greg Stoutenburg: Yeah, yeah.
300 00:29:29.250 ⇒ 00:29:33.639 Uttam Kumaran: So, part of this is, like, showing them why we came up with these.
301 00:29:33.640 ⇒ 00:29:37.380 Greg Stoutenburg: how long it typically takes, and then you arrive at the price.
302 00:29:37.640 ⇒ 00:29:47.659 Uttam Kumaran: And I would say, like, just don’t be shy. Either you’ll get, like, a, oh, shit, there’s, like, no way, which is fine, or you’ll get, like, a, okay, cool.
303 00:29:48.060 ⇒ 00:29:49.730 Uttam Kumaran: If we say or if they go.
304 00:29:49.970 ⇒ 00:29:55.600 Uttam Kumaran: then we underpriced. If you get an oh shit, like, we’ll have to get that approved, and we’re like, okay, we’re, like, in the ballpark.
305 00:29:55.700 ⇒ 00:29:56.460 Uttam Kumaran: Yeah. You know?
306 00:29:56.460 ⇒ 00:29:56.920 Greg Stoutenburg: Yeah, yeah.
307 00:29:56.920 ⇒ 00:30:07.850 Uttam Kumaran: And that… so… so that’s what I would just, like, drive to. You’ll send the stock, and people will be looking through it, they’re meeting. And again, these are, like, SF, like, quick-moving people, like, similar to… similar to Beatfall, so, like.
308 00:30:08.230 ⇒ 00:30:11.719 Uttam Kumaran: They’re just kind of like, okay, cool, we want it, like, let’s go.
309 00:30:12.010 ⇒ 00:30:12.670 Greg Stoutenburg: Yeah.
310 00:30:12.670 ⇒ 00:30:13.699 Uttam Kumaran: Is what we want to hear.
311 00:30:14.140 ⇒ 00:30:23.880 Greg Stoutenburg: Yeah, very good. So then I think from here, I’ll… yeah, I’ll find the right way to talk through this without just reading the document to them, because no one wants that. But…
312 00:30:24.260 ⇒ 00:30:43.920 Greg Stoutenburg: Microphone. So the goal is gonna be to give you guys four things. It’s gonna be to make it so that you can make pricing decisions without guesswork. So you won’t feel like you’re taking shots in the dark, you won’t feel like you’re just comparing against competitors. We want to make it so that you are in a position where you feel like you have a good, strong basis for making pricing decisions that you’re going to make.
313 00:30:44.980 ⇒ 00:30:59.130 Greg Stoutenburg: We want to make it so that you can use activation as a growth lever. Something that gets repeated in a lot of SaaS circles and a product-led growth circles, is that your single biggest opportunity to monetize someone is in the very first moments after the time they come to your website.
314 00:30:59.130 ⇒ 00:30:59.580 Uttam Kumaran: Hell yeah.
315 00:30:59.580 ⇒ 00:31:01.040 Greg Stoutenburg: they sign up. Activate.
316 00:31:01.040 ⇒ 00:31:02.000 Uttam Kumaran: Oh yeah, that’s great.
317 00:31:02.000 ⇒ 00:31:06.680 Greg Stoutenburg: My… I’ve made… my work in the last 4 years has been focused largely on activation.
318 00:31:07.080 ⇒ 00:31:15.979 Greg Stoutenburg: This is where a ton of money is won, or a ton of money is lost, so we want to make sure that you’re able to use Activation as a very strong growth lever for your company.
319 00:31:16.020 ⇒ 00:31:36.179 Greg Stoutenburg: Third outcome is having a repeatable system for learning what matters about users. It’s helpful, but just not enough to be able to go in and make an ad hoc chart at any time to answer some particular question. We want to make sure that you’re able to, at any time, look at the right pieces of information so that you’re informed about the overall health about, health of your product.
320 00:31:37.280 ⇒ 00:32:02.229 Greg Stoutenburg: Finally, providing an executive-grade decision infrastructure. So in addition to just having the information in front of you, we want to make sure that you’ve got a finger on the pulse of things like activation health, your retention across your user segments, broken out by whatever your important segments are, and you’ve got signals for expansion and churn risk. So, again, the idea being, along with activation, to make sure that you’re able to monetize in all of
321 00:32:02.230 ⇒ 00:32:04.269 Greg Stoutenburg: the right places, your user base.
322 00:32:05.690 ⇒ 00:32:10.199 Greg Stoutenburg: Okay. And then maybe we discuss that or something, I don’t know, chat, chat, chat.
323 00:32:11.000 ⇒ 00:32:25.740 Greg Stoutenburg: For the scope of work, what we’re looking at is we’ll spend some time just working on strategy and alignment, make sure that we’ve got a plan that everyone agrees on, we’ll collaborate, we can make revisions to the stock, and just iron out anything that we need to iron out. We’ll…
324 00:32:25.740 ⇒ 00:32:35.599 Greg Stoutenburg: We’ll… we’ll find out what you already know, and what you’ve already decided upon. That’ll be things like looking at, setting up a tracking strategy for,
325 00:32:35.600 ⇒ 00:32:42.710 Greg Stoutenburg: For your events that will be used in the product analytics tool, and some of those, sort of, basic strategic and alignment
326 00:32:42.730 ⇒ 00:32:51.969 Greg Stoutenburg: Type questions. We’ll move from there. How many sections did I put here? We’ll move from there to creating the actual product analytics implementation itself.
327 00:32:51.970 ⇒ 00:33:16.970 Greg Stoutenburg: We can have a conversation about what the right tool is for you. I understand you’ve been using PostHog, but if you’re open to it, I’d like to have a conversation about moving to Amplitude, which is a tool that we’re excited about. I’ve used it a lot in the past before, sort of top-quality product analytics tool, and Brainforge has an important relationship to Amplitude in that we’re partners with Amplitude, so we have access to
328 00:33:16.970 ⇒ 00:33:36.410 Greg Stoutenburg: excellent resources and things like that. We’ll create that tracking plan, and that’ll make it so that product… so that events that need to be tracked in your product are being tracked in amplitude, so we have visibility into what’s going on. Make sure the data pipelines are working the way that they’re supposed to, and that the data that you have is quality.
329 00:33:36.900 ⇒ 00:34:00.559 Greg Stoutenburg: And then some things that we’ll be building will be your revenue-focused dashboards. And we were talking earlier about those questions that you need to be able to answer in, you know, with certainty, with high degrees of confidence. That’s going to be these dashboards here. These are going to be the insights that, when we, when we do this engagement, you’ll have. So that’s going to be an executive dashboard with things like your high-level KPIs, information about, retention, activation, and churn.
330 00:34:00.980 ⇒ 00:34:02.739 Greg Stoutenburg: Your revenue dashboards.
331 00:34:02.830 ⇒ 00:34:18.730 Greg Stoutenburg: anything containing… pertaining to revenue, we want to make sure that you’ve got that in… in good shape. Time to value metrics, those key events that we were talking about before that are early in the user journey, we’ll put together a dashboard that’s just for that, that satisfies that growth lever.
332 00:34:18.810 ⇒ 00:34:27.480 Greg Stoutenburg: Same for retention, your customer lifecycle overall, and then product engagement. Who’s using what, and what does it signify?
333 00:34:28.040 ⇒ 00:34:37.279 Greg Stoutenburg: So those are the things that you’ll… you’ll have throughout this project, and then finally, we’ll make sure at the conclusion of this scope of work that,
334 00:34:37.290 ⇒ 00:34:52.220 Greg Stoutenburg: Your people internally are able to use these things, you know how the tools work, you know how to find additional information if we didn’t already provide it, and make sure that you’re in good shape as we figure out what the future of the relationship would look like from there.
335 00:34:54.429 ⇒ 00:34:54.979 Uttam Kumaran: Great.
336 00:34:55.710 ⇒ 00:35:04.089 Greg Stoutenburg: I think I probably don’t… I mean, this is… this is pretty straightforward. This is just, like, giving a little bit more detail about what we’re gonna do, so I’ll probably kind of skim over that.
337 00:35:04.400 ⇒ 00:35:09.880 Uttam Kumaran: Yeah, I would say, like, like, kind of do the dance. So, depending on how, where their interest is.
338 00:35:10.020 ⇒ 00:35:10.510 Greg Stoutenburg: Yeah.
339 00:35:10.510 ⇒ 00:35:19.849 Uttam Kumaran: you’re gonna find that some people are very interested in the technical implementation. You’re gonna find some people are very interested in the output. You’re gonna find that some people got sold within the first 5 minutes, and…
340 00:35:19.850 ⇒ 00:35:20.230 Greg Stoutenburg: Yeah.
341 00:35:20.230 ⇒ 00:35:28.030 Uttam Kumaran: you should just kind of, like, just talk about next steps, and then risk, you know, and then have fun. So, like, the worst thing you could do is script too much.
342 00:35:28.320 ⇒ 00:35:28.690 Greg Stoutenburg: I’m like.
343 00:35:28.690 ⇒ 00:35:32.459 Uttam Kumaran: You do almost want to have, like, the decision tree in front of you.
344 00:35:32.580 ⇒ 00:35:48.390 Uttam Kumaran: Like, the problem with me is, like, I’m not a natural salesperson, so I think about all the options, and then it seems like I’m doing a dance, but it’s pretty prescribed for that, like, they usually go a certain way. But again, there’s, like, these checkpoints, so you don’t want to move…
345 00:35:48.660 ⇒ 00:35:58.910 Uttam Kumaran: forward with, you know, a call if they don’t really grasp what it is you’re selling and how important it is. And you may be surprised, like, yes, these guys are running, like, an AI company.
346 00:35:59.040 ⇒ 00:36:02.560 Uttam Kumaran: They may not even know what product analytics is, and so…
347 00:36:02.560 ⇒ 00:36:03.180 Greg Stoutenburg: Yeah, yeah.
348 00:36:03.180 ⇒ 00:36:06.019 Uttam Kumaran: It’s really important just to, like, bait…
349 00:36:06.280 ⇒ 00:36:21.829 Uttam Kumaran: And then after it, like, I think going through your pace, make sure to stop to ask questions, to just say, like, do you have any questions? It needs to be a group effort. Like, you actually hope that there’s feedback. If there is no feedback, like, you almost are like, okay, something’s wrong here.
350 00:36:21.830 ⇒ 00:36:30.229 Uttam Kumaran: Because there’s gonna be something in here that we didn’t reflect, and you want to make sure that we can… one action item is gonna be, yeah, we’ll come back and make those edits.
351 00:36:30.230 ⇒ 00:36:50.199 Uttam Kumaran: like, is… and so that you can have that when you present to your CEO, right? So, really stop and make sure that there is feedback. Like, I wouldn’t continue… I would be very, very surprised if there’s no feedback if we didn’t get something right. And it’s not our job to get it right, it’s our job to implement the feedback and get this over the line with them, right?
352 00:36:50.830 ⇒ 00:37:01.599 Uttam Kumaran: co-author with us, there’s no opportunity for that. So that’s… that’s probably what I would say, and otherwise, I think you’re… you’re kind of golden. Like, I think you can kind of go through and continue to show our depth, but…
353 00:37:01.870 ⇒ 00:37:06.549 Uttam Kumaran: At some point, they’ll be like, okay, we’re with you, like, I think we’re good on the scope, like.
354 00:37:06.850 ⇒ 00:37:13.169 Uttam Kumaran: then maybe it’s a debate on pricing. Like, I can be there, and I can help talk through pricing, but…
355 00:37:13.200 ⇒ 00:37:27.549 Uttam Kumaran: for the most part, again, they… we already have an existing scope with them, so, like, I don’t think they’re… we’re basically… we’re like, look, we’re using our hourly, and we’re kind of biasing towards what you wanted, which was, like, a fixed monthly scope. This is the cost to, like, handle both these items.
356 00:37:27.550 ⇒ 00:37:29.750 Greg Stoutenburg: Yeah. Like, there’s plenty of, like…
357 00:37:29.750 ⇒ 00:37:35.489 Uttam Kumaran: It’s actually, like, much easier for me to tell you how to defend our pricing than it is, like, this initial part, so…
358 00:37:35.490 ⇒ 00:37:51.420 Greg Stoutenburg: Yeah, okay. Yeah, for pricing, by the way, after that exchange in Slack, I just… I just combined the two items as though it’s a single line item, and just said $40K for 3 months, and if they… if they then want to hash out, you know, or get more details, or cut something out, then I think…
359 00:37:51.800 ⇒ 00:37:57.789 Greg Stoutenburg: I mean, my mind just goes straight to defer to you and Robert. I mean, this is… Yeah, that’s fine. Okay, yeah.
360 00:37:57.790 ⇒ 00:37:59.309 Uttam Kumaran: I have no problem. I mean, I’ll…
361 00:37:59.550 ⇒ 00:38:01.500 Uttam Kumaran: I’ll be there, I have no problem.
362 00:38:01.760 ⇒ 00:38:02.490 Greg Stoutenburg: Yeah.
363 00:38:03.140 ⇒ 00:38:14.820 Greg Stoutenburg: My mind also goes to, depending on what they want to cut out, the price of the other thing may immediately increase, you know? Like, when Robert was saying, like, you know, I was thinking…
364 00:38:14.820 ⇒ 00:38:18.959 Uttam Kumaran: If they’re talking about pricing, we’ve sold… we got… we got. Yeah.
365 00:38:18.960 ⇒ 00:38:42.019 Greg Stoutenburg: Right. No, that’s a good point. Yeah. Okay, yeah, and then I think from there, we just have an open-ended conversation about, you know, their thoughts, we talk about their feedback, ask for next steps, I’ll emphasize, and I’ll… I’ll make sure to have said this earlier in the conversation, this is a proposal, and this is something that we want to collaborate on. We want to make sure that we’re delivering the work that’s going to be valuable to them, so…
366 00:38:42.020 ⇒ 00:38:45.399 Greg Stoutenburg: Just because this is my take on…
367 00:38:45.400 ⇒ 00:38:51.560 Greg Stoutenburg: what they need, you know, I want their input as well to, you know, I’ll say things like that. Okay.
368 00:38:51.560 ⇒ 00:38:55.820 Uttam Kumaran: Yeah, yeah, yeah. One thing, I mean, one way that I say it is, I’m like, I want every dollar
369 00:38:55.890 ⇒ 00:39:02.029 Uttam Kumaran: spent with Brainforge should be 5 out, and I’m not afraid of saying that, like, that’s what we want, right? So, like…
370 00:39:02.030 ⇒ 00:39:19.370 Uttam Kumaran: There’s… you will be hard-pressed to find another consultant that says that, because they are lying, typically. I think that… I really believe that in my heart, you know, and I really want that. I want it to be 10 bucks if I could. I feel like that’d be kind of crazy. Maybe… I do think for some clients, we are delivering $10 worth of,
371 00:39:19.370 ⇒ 00:39:34.180 Uttam Kumaran: with the value, but I was… so, again, like, that’s… that’s the kind of stuff where you just want… if we get to the point where we’re debating pricing, like, okay, they like the scope, they want something from us, and then we kind of go from there. I’m not expecting them to just say, yes.
372 00:39:34.180 ⇒ 00:39:41.980 Uttam Kumaran: without putting up a fight. So, you should expect something, and then we sort of… we can kind of talk… we can kind of talk through it, but…
373 00:39:41.980 ⇒ 00:39:44.000 Greg Stoutenburg: Yes, ultimately, like, I’m…
374 00:39:44.000 ⇒ 00:39:50.440 Uttam Kumaran: I don’t have any fear in saying, we need this to be something that actually delivers value for you. Otherwise, there’s no reason for us to do this work.
375 00:39:50.710 ⇒ 00:39:51.270 Greg Stoutenburg: Yeah.
376 00:39:52.130 ⇒ 00:39:53.370 Greg Stoutenburg: Yeah, very good.
377 00:39:53.890 ⇒ 00:39:56.090 Greg Stoutenburg: Okay.
378 00:39:56.940 ⇒ 00:40:01.520 Greg Stoutenburg: Cool. Others who were watching, any of the thoughts?
379 00:40:06.390 ⇒ 00:40:07.740 Greg Stoutenburg: Feel pretty good about this.
380 00:40:08.440 ⇒ 00:40:10.350 Uttam Kumaran: Yeah. I am going…
381 00:40:10.350 ⇒ 00:40:13.569 Luke Scorziell: Yeah, a lot of great stuff, honestly, with,
382 00:40:13.940 ⇒ 00:40:18.970 Luke Scorziell: Yeah, again, just from a content perspective, this is interesting for me to, like, I’m writing down content ideas.
383 00:40:19.240 ⇒ 00:40:26.780 Luke Scorziell: From what you’re pitching, and yeah, well, yeah. So, good stuff.
384 00:40:27.050 ⇒ 00:40:30.249 Luke Scorziell: Sure, I could give more critical feedback if I wasn’t listening from that perspective.
385 00:40:33.760 ⇒ 00:40:53.749 Uttam Kumaran: I am running to an in-person partner meeting, so I may jump, but, like, I’m gonna, caitlin just called me, like, during this call, so I need to call her back, but, I feel like it’s honestly gonna be a bit easier, Greg, on that side, with Caitlin. I actually think probably the way you did it is just the perfect way.
386 00:40:54.730 ⇒ 00:41:08.560 Uttam Kumaran: I feel like you’re gonna… most likely, you’re gonna get questions just about, like, how it is we’re doing it, and how we are… what are the core components, because I know… I know that she doesn’t have a ton of experience in product analytics, but again, like, I feel…
387 00:41:08.770 ⇒ 00:41:13.270 Uttam Kumaran: Hydra is really the one where I think we’re most nervous about, because I already sort of got, like.
388 00:41:13.690 ⇒ 00:41:17.199 Uttam Kumaran: Kind of, like, verbal approval from default, but again, like, it’s
389 00:41:17.750 ⇒ 00:41:22.839 Uttam Kumaran: I think the way you pitched it today is perfect, so as long as you do that, like, we’ll be there, and we’ll get it over the line.
390 00:41:23.210 ⇒ 00:41:37.190 Greg Stoutenburg: Sounds good. Before you hop, for pricing, you’d made a comment, we have an hourly rate with them. I think we’re maybe waiting for Robert to throw something on here, I don’t recall exactly. Should I just put… pick a number?
391 00:41:38.460 ⇒ 00:41:42.509 Uttam Kumaran: Well, we already have, we already have a,
392 00:41:43.490 ⇒ 00:41:46.900 Uttam Kumaran: what do you call it? Like, we already have paper with them, like, we’re already billing them.
393 00:41:46.910 ⇒ 00:41:48.050 Greg Stoutenburg: So… Okay.
394 00:41:48.130 ⇒ 00:41:53.220 Uttam Kumaran: If you want to tag… yeah, you can tag Robert, or tag me, and I’ll make sure it just gets in there.
395 00:41:53.510 ⇒ 00:41:54.810 Greg Stoutenburg: Alright, I’ll just put it here.
396 00:41:55.510 ⇒ 00:42:04.849 Uttam Kumaran: So we can talk about, like, what our current scope is, but basically, they wanted 20 hours from us. It was already… we’re already gonna be halfway here, so really, we’re talking about, like, adding on.
397 00:42:17.990 ⇒ 00:42:18.660 Greg Stoutenburg: Okay.
398 00:42:19.820 ⇒ 00:42:23.980 Uttam Kumaran: Cool, maybe I’ll let Clarence give some thoughts, but I’m just gonna… I’m just gonna run into this coffee shop, so…
399 00:42:23.980 ⇒ 00:42:24.400 Greg Stoutenburg: Cool.
400 00:42:24.400 ⇒ 00:42:25.420 Uttam Kumaran: I’ll leave you guys.
401 00:42:25.620 ⇒ 00:42:26.650 Greg Stoutenburg: See you, Tom. Thanks.
402 00:42:26.650 ⇒ 00:42:27.859 Uttam Kumaran: Okay, thank you.
403 00:42:28.790 ⇒ 00:42:36.840 Clarence Stone: Hey, Greg, I just hopped in halfway through, so I need to capture everything, so… I think Utam’s feedback was pretty good.
404 00:42:36.840 ⇒ 00:42:37.830 Greg Stoutenburg: Great, yeah.
405 00:42:38.380 ⇒ 00:42:49.530 Greg Stoutenburg: Awesome, yeah, thanks. Yeah, I mean, we just did, just some basics, like, intro of myself, asking some questions on some discovery stuff, like, you know, how,
406 00:42:49.820 ⇒ 00:42:53.420 Greg Stoutenburg: How much do they know about what product analytics tools are used for?
407 00:42:53.430 ⇒ 00:43:12.100 Greg Stoutenburg: I give sort of a basic overview as I’ve tried to figure out what they know and maybe what they don’t, so that I’m pitching at the right level, and then kind of point to the promise of what you can do with these tools, and say some things about, you know, winning in the marketplace and stuff like that. And then that’s probably around when you got on.
408 00:43:12.720 ⇒ 00:43:13.340 Clarence Stone: Yeah.
409 00:43:13.340 ⇒ 00:43:14.260 Greg Stoutenburg: Yeah, okay.
410 00:43:14.260 ⇒ 00:43:20.069 Clarence Stone: Yeah. I’ve had a chance to read this, and I left you notes already, it looks… Yeah, thank you.
411 00:43:20.070 ⇒ 00:43:44.300 Clarence Stone: I actually, as a follow-up to this, wrote an entire guide on SOWs. It’s still something that Robert and Mutam are reviewing, so, like, I’ll put that as a conditional that it’s not quite done yet, but if you wanted some inspiration on how to, like, on questions that might be helpful to ask, you know, my document’s a pretty good reference of that.
412 00:43:46.020 ⇒ 00:43:48.999 Clarence Stone: So let me try and pull it up and drop the link for you.
413 00:43:49.000 ⇒ 00:43:50.010 Greg Stoutenburg: Yeah, that sounds good.
414 00:43:51.720 ⇒ 00:44:10.330 Greg Stoutenburg: Yeah, that sounds good. I think… so for my part, the experience of putting these SOWs together was, like, I… I had one model of an SOW in the form of what Robert showed me, probably in December, and then I made a new SOW for a renewal, put that in front of README,
415 00:44:11.230 ⇒ 00:44:13.229 Greg Stoutenburg: A week ago.
416 00:44:13.600 ⇒ 00:44:30.500 Greg Stoutenburg: And they liked it, so great. And then, in working on… I think that’s right. I feel like the… I already don’t know what year it is. And then, in putting together these SOWs, I started by relying on some of the stuff that’s in GitHub, and, you know, I… I felt like I ended up with…
417 00:44:30.770 ⇒ 00:44:44.280 Greg Stoutenburg: one version of an SOW that I really liked, and then one that I really didn’t. And I think some of it is… I think what was better, when I think about it, or, like, Robert made, like, some really heavy edits on the Hydra one, whereas the default, this is…
418 00:44:46.050 ⇒ 00:45:05.640 Greg Stoutenburg: not heavy edit, was the, like, the emphasis on why we’re doing this. And that was helpful to me, even as a person putting it together, because, it helps center what the whole point of putting together an SOW is, which is not, like, a comprehensive schedule. Like, I appreciated your comments, like, don’t give, like, estimates of what’s gonna happen in week 7.
419 00:45:05.640 ⇒ 00:45:08.640 Greg Stoutenburg: You’re right. I don’t know, and I know that I don’t know.
420 00:45:09.220 ⇒ 00:45:21.869 Greg Stoutenburg: But I was following a template. The point is to, like, see what we’re trying to do for the client, and then get them on board and collaborate with us on it. So that was…
421 00:45:22.190 ⇒ 00:45:33.019 Clarence Stone: Yeah, so the wisdom I want to impart to you is, I think, just based on how well each of these reviews are going each time, so it’s on the left side, Guide to Creating SOWs,
422 00:45:33.170 ⇒ 00:45:55.720 Clarence Stone: you seem to have stumbled or concluded on a really great core starting point on SOWs, and that’s amazing, because now you have a great place to, you know, start filling in information, but the one piece of wisdom that I try to impart in this write-up is that an SOW is actually a conversation you’re having with the client.
423 00:45:55.740 ⇒ 00:46:15.740 Clarence Stone: Right? It is a back-and-forth conversation of, like, what are you gonna offer me? What can I offer you? What do you need from me in order to give me that? When are you gonna get it? How do you like to work? How should I work so that I fit into your schedule? Right? So it’s more of, like, a conversation on, how do we work together?
424 00:46:15.740 ⇒ 00:46:17.510 Clarence Stone: Right? To meet that goal.
425 00:46:17.800 ⇒ 00:46:39.829 Clarence Stone: So, great starting points are always a good thing, but from there, like, you know, just be flexible. Be willing to change or adjust to based on, like, whatever your client ends up needing, right? Because it might deviate significantly from, you know, where you started, but that’s okay, because, you know, you guys are building this together, and as long as…
426 00:46:39.830 ⇒ 00:46:42.680 Clarence Stone: Things that you’re expressing are contractually sound.
427 00:46:42.980 ⇒ 00:46:44.020 Clarence Stone: You’re good.
428 00:46:44.270 ⇒ 00:46:44.870 Greg Stoutenburg: Yeah.
429 00:46:45.210 ⇒ 00:46:46.979 Greg Stoutenburg: I like it. Yeah, cool.
430 00:46:48.870 ⇒ 00:46:54.450 Greg Stoutenburg: Great, yeah, I’ll read this later. Yeah, awesome.
431 00:46:54.930 ⇒ 00:46:56.550 Greg Stoutenburg: That’s very helpful, thank you.
432 00:46:56.550 ⇒ 00:47:09.059 Clarence Stone: Yeah. Cool. And hopefully along the way, like, you’ll make best friends with whoever you’re building this SOW with, and become, you know, what was it, like, people who struggle together end up bonding together, and.
433 00:47:09.060 ⇒ 00:47:09.560 Greg Stoutenburg: Yeah.
434 00:47:09.560 ⇒ 00:47:12.720 Clarence Stone: And then, they’ll come back for you for more work. Yeah.
435 00:47:12.720 ⇒ 00:47:15.239 Greg Stoutenburg: Yeah, and this is, you know, this is, I mean…
436 00:47:15.580 ⇒ 00:47:20.969 Greg Stoutenburg: besides these, 3 for Brain Forge, I’ve put together, like.
437 00:47:21.920 ⇒ 00:47:38.879 Greg Stoutenburg: two other SOWs ever. And so, like, one thing that has become very clear is it’s a lot easier to write an SOW if you have all… just depending on how much context you have, like, how much relationship there is already. Like, the one for README, I got that done easily…
438 00:47:39.550 ⇒ 00:47:56.859 Greg Stoutenburg: quickly, like, I knew what I wanted to say, you know, like, right away. Whereas these other ones, you know, putting together notes and just hearing internally, you know, I heard they want this, or I think they want this, say it this way, is a much bigger challenge to put together something that you think is going to be useful to the client.
439 00:47:57.030 ⇒ 00:48:12.510 Clarence Stone: Yeah, so Greg, I hope then you see that, like, the CSO role is so critical for the success of, like, followed on business, right? Because that CSO should be the person that can actually answer a lot of these relationship questions.
440 00:48:12.510 ⇒ 00:48:12.990 Greg Stoutenburg: Yeah.
441 00:48:12.990 ⇒ 00:48:29.910 Clarence Stone: How does this client make work? How do they like seeing their SOWs? How do they present work to their, like, what are their major concerns and behaviors, right? If you have that information, your SOW is so much better, because it’s not just a contract, it’s like an agreement on how you want to work together with somebody.
442 00:48:29.910 ⇒ 00:48:41.290 Greg Stoutenburg: Yeah, yeah, no, for sure. And I for sure do see that. Yeah, I’m in the position of being on the receiving end of a couple of handoffs, which just makes it more challenging, but yeah, no, for sure.
443 00:48:41.530 ⇒ 00:48:48.580 Clarence Stone: Yeah, so once we reach, like, some maturity and stabilization in this role, I really hope that this starts to get easier.
444 00:48:48.580 ⇒ 00:49:12.680 Clarence Stone: And Greg, I also like to leave, like, light at the end of the tunnel for everyone, so the next thing that I want to work on is actually coming up with a standardized MSA, so like a Master Services Agreement, so that all the SOWs that you guys tack on will be a lot shorter. You don’t have to talk about billing, you don’t have to talk about how you’re going to charge for hours and things like that. It’ll just be all standardized as a starting point.
445 00:49:12.680 ⇒ 00:49:27.020 Clarence Stone: We’ll let Utama and Robert kind of, you know, manage and negotiate those bigger pieces. Like, I think the SOW should just be focusing on the project and deliverables that you’re gonna have for that project itself, and make building these a lot easier.
446 00:49:27.020 ⇒ 00:49:30.370 Greg Stoutenburg: Yeah, yeah. Yeah, I like that. That sounds great.
447 00:49:30.490 ⇒ 00:49:42.170 Greg Stoutenburg: Yeah, and I think similarly, both of these SOWs are, they both involve a product analytics implementation component, and so it seems like going down the line, there will be something repeatable
448 00:49:42.330 ⇒ 00:49:43.889 Greg Stoutenburg: Through a couple of these.
449 00:49:44.070 ⇒ 00:49:59.450 Clarence Stone: Yeah, and, you know, and Luke, I would love your thoughts on this, but, like, my perspective on locking in an MSA for a lot of larger clients, it just makes getting follow-on work so much easier, because you sit, like, in their system as a permanent MSA.
450 00:49:59.640 ⇒ 00:50:12.870 Clarence Stone: Right. Which means, like, Greg, if you notice additional reporting, benefits that they can get, or follow-on, capabilities that they might want, you just have to do the SOW that goes on top of that. Right, right.
451 00:50:12.870 ⇒ 00:50:22.499 Clarence Stone: Yeah. So, like, that’s sort of where I want to, you know, push organizations towards, and, you know, getting that set up and formulated and standardized is… it’s coming.
452 00:50:22.500 ⇒ 00:50:29.309 Clarence Stone: But, like, you know, I at least want to tell you that, like, hey, we want to work towards making this easier as things go.
453 00:50:30.270 ⇒ 00:50:32.209 Greg Stoutenburg: Yeah, I like it. Cool.
454 00:50:33.070 ⇒ 00:50:33.750 Clarence Stone: Cool.
455 00:50:33.750 ⇒ 00:50:37.919 Luke Scorziell: I’m just kind of flying the wall, learning what all the engineers are talking about.
456 00:50:39.270 ⇒ 00:50:56.389 Clarence Stone: But on the MSA front, Luke, if you have any certain, like, thoughts, like, please feel free to ping me, on how that should work. Because my vision really is, like, can we just have, like, a base agreement of all the fundamentals that are just, like, sent out as a standard package, and then just layer in the SOWs on top?
457 00:50:56.390 ⇒ 00:51:15.589 Clarence Stone: Right? And I’m a little aggressive on my GTM behaviors, so, like, a new standard that I would do once this is implemented is to say, no SOW can be signed off unless the last step is doing an assessment, and then providing the client recommendations on further things that they can benefit from.
458 00:51:15.900 ⇒ 00:51:16.280 Greg Stoutenburg: Hmm.
459 00:51:16.280 ⇒ 00:51:20.320 Clarence Stone: So at the end of every project, issue B, hey, we built this for you, here’s the outcome.
460 00:51:20.320 ⇒ 00:51:20.690 Greg Stoutenburg: Oh, yeah.
461 00:51:20.690 ⇒ 00:51:37.950 Clarence Stone: a bunch of other things you can do, and here’s the other possible outcomes. Yeah. And we should never leave a project without that, because if we have a standing MSA, all we’re going to do is give them a menu of other things to pick from, and you should be feeding you and your team, you know, consistently through a single relationship like that.
462 00:51:39.590 ⇒ 00:51:45.840 Luke Scorziell: And do we… is that something we currently have? Because I’ve kind of been trying to work with the engineering team to see what the services
463 00:51:46.150 ⇒ 00:51:49.499 Luke Scorziell: Like, do we have a standardized set of services that we…
464 00:51:49.500 ⇒ 00:51:50.200 Clarence Stone: No, we don’t even…
465 00:51:50.200 ⇒ 00:51:50.730 Luke Scorziell: for money.
466 00:51:50.730 ⇒ 00:52:03.459 Clarence Stone: service menu or anything like that. And, Luke, like, this is something that’s been on my to-do list, and I keep deferring it as we, you know, go on. Like, so we just launched this new, you know, team structure, so my.
467 00:52:03.460 ⇒ 00:52:03.890 Luke Scorziell: Yeah.
468 00:52:03.890 ⇒ 00:52:28.719 Clarence Stone: making sure everyone’s, like, being supported, and you guys probably get a bajillion pings from me saying, like, do you need help? Do you need help now? How about now, right? So, like, after, you know, those things get stabilized, I hope to kind of shift gears into creating, you know, like, broader architecture that’ll make these processes easier. And on top of that, we… I think we should be bringing on a head of ops soon in obsolete, so now I can offer…
469 00:52:28.720 ⇒ 00:52:34.400 Luke Scorziell: Some of those things that have been on the, you know, back of my pipeline to help you guys out with as well.
470 00:52:35.110 ⇒ 00:52:38.660 Luke Scorziell: Okay. Yeah, I’ve still been meaning to get a meeting with you, but that might…
471 00:52:38.990 ⇒ 00:52:43.100 Luke Scorziell: solve some of the redundant work that potentially I’m trying to do with the engineers of, like.
472 00:52:43.630 ⇒ 00:52:46.899 Luke Scorziell: What are you doing, and what is the most high leverage, and how can we…
473 00:52:47.480 ⇒ 00:52:49.799 Luke Scorziell: positioning this, and I wrote a market motion.
474 00:52:50.050 ⇒ 00:53:04.039 Clarence Stone: It would be, like, great if you… like, I’ll make sure that you… you have a connect with the new ops lead when we bring him on. Yeah. He’s… I think he’s gonna start with 20 hours, like we do for, you know, all our new team members, so,
475 00:53:04.160 ⇒ 00:53:19.360 Clarence Stone: like, there’s, like, 2 or 3 simple tasks that we want him to get done just as a provisional employee, and then, like, I don’t think to start talking to him about what’s, you know, actually in your broader pipeline. Okay. We’ll make sure to connect you two when he starts.
476 00:53:19.830 ⇒ 00:53:30.910 Luke Scorziell: Yeah, well, I’ll just go… if it’s still good with you, I’ll just try to grab 30 minutes on your calendar, and maybe I can just kind of see what’s going on in your brain, and I can tell you what’s going on in mine. So I’ve just been jumping in headfirst, so…
477 00:53:30.910 ⇒ 00:53:36.740 Clarence Stone: Yeah, absolutely. My calendar’s up to date, so feel free to… to tack on whatever
478 00:53:36.870 ⇒ 00:53:38.780 Clarence Stone: Okay. Anytime works for you.
479 00:53:39.360 ⇒ 00:53:39.950 Luke Scorziell: Perfect.
480 00:53:41.460 ⇒ 00:53:42.020 Greg Stoutenburg: Cool.
481 00:53:42.700 ⇒ 00:54:07.610 Clarence Stone: So, Greg, long story short, help is on the way, and I hope, you know, the questions that I put in with SOW, it helps a little bit more. But, you know, I am so appreciative that, you know, you and other CSOs and everyone who took on this new leadership role, that you guys are taking it on fully. Like, I did not expect in week one that you and OH would start putting together SOWs. Like, putting together this guide was pretty low on my list, because I didn’t
482 00:54:07.610 ⇒ 00:54:13.860 Clarence Stone: anticipate that. But I love that you guys are taking initiative, so I have to, you know, move at your pace and speed up as well.
483 00:54:13.860 ⇒ 00:54:16.960 Greg Stoutenburg: Alrighty. Good to hear.
484 00:54:17.160 ⇒ 00:54:18.569 Greg Stoutenburg: Cool.
485 00:54:20.070 ⇒ 00:54:22.550 Greg Stoutenburg: Alright, is that a wrap? I think that’s a wrap.
486 00:54:22.620 ⇒ 00:54:23.280 Clarence Stone: Cool.
487 00:54:23.710 ⇒ 00:54:24.630 Luke Scorziell: Dude.
488 00:54:26.920 ⇒ 00:54:27.569 Luke Scorziell: the name of it.
489 00:54:27.720 ⇒ 00:54:28.430 Clarence Stone: Thanks, guys.
490 00:54:29.380 ⇒ 00:54:30.200 Greg Stoutenburg: Zip.