2026-01-20_demilade_-_luke_-_dbt_audit_service_4685c42c

Meeting Title: Demilade - Luke - dbt audit service Date: 2026-01-20 Meeting participants: Demilade Agboola, Luke Scorziell, Luke’s Notetaker, Uttam Kumaran

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WEBVTT

1 00:07:38.040 ⇒ 00:07:39.749 Luke Scorziell: Hey, Dean Milate, how’s it going?

2 00:07:40.170 ⇒ 00:07:41.420 Luke Scorziell: the ghost, Rudy.

3 00:07:42.910 ⇒ 00:07:44.810 Luke Scorziell: you too much.

4 00:07:49.180 ⇒ 00:07:50.769 Luke Scorziell: Demulade, are you there?

5 00:07:52.890 ⇒ 00:07:54.429 Demilade Agboola: I… sorry, I…

6 00:07:54.430 ⇒ 00:07:55.100 Luke Scorziell: Yay.

7 00:07:55.960 ⇒ 00:07:56.469 Demilade Agboola: I was just trying.

8 00:07:56.470 ⇒ 00:07:57.090 Luke Scorziell: No.

9 00:07:57.090 ⇒ 00:07:58.070 Demilade Agboola: Enough, Robert.

10 00:07:58.500 ⇒ 00:07:59.329 Demilade Agboola: How are you?

11 00:08:00.190 ⇒ 00:08:02.020 Luke Scorziell: Good. How are you doing?

12 00:08:02.530 ⇒ 00:08:10.930 Demilade Agboola: Pretty good. A bit hungry, though, but I can’t eat, because apparently I have to fast. Oh, really?

13 00:08:11.350 ⇒ 00:08:14.739 Demilade Agboola: 12… at least 12-hour fast before my…

14 00:08:14.950 ⇒ 00:08:17.359 Demilade Agboola: Appointment, because it’s, like, blood tests and stuff.

15 00:08:18.290 ⇒ 00:08:18.810 Luke Scorziell: Oh, yeah.

16 00:08:18.810 ⇒ 00:08:20.159 Demilade Agboola: I don’t know, yeah.

17 00:08:20.660 ⇒ 00:08:22.625 Demilade Agboola: I’m… And…

18 00:08:23.990 ⇒ 00:08:27.139 Luke Scorziell: We’ll stay off the food topics then.

19 00:08:27.140 ⇒ 00:08:28.469 Demilade Agboola: Okay, sounds good.

20 00:08:28.820 ⇒ 00:08:33.200 Luke Scorziell: But, yeah, what time is it over there?

21 00:08:33.870 ⇒ 00:08:37.120 Demilade Agboola: It’s… 1223.

22 00:08:37.450 ⇒ 00:08:41.279 Luke Scorziell: Okay. Well, I can, I mean, we can try to, like, rapid fire.

23 00:08:41.460 ⇒ 00:08:47.160 Luke Scorziell: This, I don’t wanna… I was on a call with a partner, and then…

24 00:08:47.350 ⇒ 00:08:49.379 Luke Scorziell: Yeah, I was just going all the long. But.

25 00:08:49.380 ⇒ 00:08:50.610 Demilade Agboola: It’s all good.

26 00:08:52.020 ⇒ 00:08:56.089 Luke Scorziell: Yeah, I guess, like, the…

27 00:08:57.020 ⇒ 00:09:01.290 Luke Scorziell: One of the motions that we’re trying to do right now is, like, develop,

28 00:09:01.910 ⇒ 00:09:14.430 Luke Scorziell: I’m, like, learning all of the startup buzzword speak, so, like, motion previously meant nothing to me, but now, you know, it means, like, I guess, what we’re doing. So, the plan is, to…

29 00:09:14.630 ⇒ 00:09:23.159 Luke Scorziell: kind of launch a couple different services. So we started with the edge-to-activation one that Zoran, is good with, and so that’s, like.

30 00:09:23.590 ⇒ 00:09:31.510 Luke Scorziell: Getting more accurate attribution, and whatnot. And then with, the DBT audit.

31 00:09:31.610 ⇒ 00:09:42.050 Luke Scorziell: Like, kind of hoping to then, like, probably not next week, but maybe the week after, get a campaign up and going around, like, what is this? What can we do for you?

32 00:09:42.210 ⇒ 00:09:48.660 Luke Scorziell: Like, what are some of the pain points and whatnot that you might be experiencing? So, I guess, like, that’s where I’m coming in of, like.

33 00:09:49.060 ⇒ 00:09:54.519 Luke Scorziell: Yeah, wanting to, like, chat with you and kind of understand more of

34 00:09:55.140 ⇒ 00:09:59.600 Luke Scorziell: Like, to be honest, I have… I don’t barely even really know it.

35 00:10:00.200 ⇒ 00:10:09.199 Luke Scorziell: dbt is, other than that I’ve heard it a lot, and I think it’s a provider. So, like, you know, some of it might be…

36 00:10:09.390 ⇒ 00:10:12.639 Luke Scorziell: educating me from there, but

37 00:10:12.920 ⇒ 00:10:19.879 Luke Scorziell: Yeah, I think we’re just looking to kind of get, like, an overview, and then I can ask you some, like, specific questions and whatnot.

38 00:10:20.520 ⇒ 00:10:22.549 Luke Scorziell: But, yeah, does that, like…

39 00:10:22.810 ⇒ 00:10:24.220 Demilade Agboola: Yeah, something.

40 00:10:24.610 ⇒ 00:10:26.199 Luke Scorziell: Makes sense, on your end?

41 00:10:26.390 ⇒ 00:10:27.410 Demilade Agboola: Yeah, it does.

42 00:10:28.580 ⇒ 00:10:29.200 Luke Scorziell: Oh.

43 00:10:29.640 ⇒ 00:10:30.560 Luke Scorziell: Okay.

44 00:10:31.510 ⇒ 00:10:34.349 Luke Scorziell: Let me pull up… I thought I had a…

45 00:10:35.310 ⇒ 00:10:40.940 Luke Scorziell: Yeah, maybe you could just give me, like, a quick overview of, like, what is…

46 00:10:41.590 ⇒ 00:10:44.570 Luke Scorziell: Yeah, what is a dbt audit, and why would you need it?

47 00:10:46.290 ⇒ 00:10:49.480 Demilade Agboola: So DBT is a…

48 00:10:51.170 ⇒ 00:11:01.859 Demilade Agboola: It’s a SQL compiler, so basically think of SQL, but on steroids. It basically gives you the ability to do way much more than just regular SQL.

49 00:11:02.150 ⇒ 00:11:08.439 Demilade Agboola: So you can start to apply things like version control and other, like, software engineering practices to it.

50 00:11:08.870 ⇒ 00:11:15.469 Demilade Agboola: So that is the first step of, like, having dbt in your infrastructure.

51 00:11:15.780 ⇒ 00:11:23.250 Demilade Agboola: As to why you would want to audit it is… It gets really messy.

52 00:11:23.250 ⇒ 00:11:25.480 Luke Scorziell: Basically, so things like code.

53 00:11:25.880 ⇒ 00:11:34.910 Demilade Agboola: And over time, like, a lot of people build out their infrastructure with just the, we need things to happen, we need to see the numbers mentality.

54 00:11:35.160 ⇒ 00:11:45.609 Demilade Agboola: But over time, it starts to clog up in terms of it’s hard to find out, like, what is what and why things were done.

55 00:11:45.850 ⇒ 00:11:51.390 Demilade Agboola: Two, sometimes things are not done well in such a way that it takes a long time for things to run.

56 00:11:51.690 ⇒ 00:12:03.399 Demilade Agboola: And usually, let’s take the average, or the usual cadence for a lot of people’s infrastructure. A lot of people want their data infrastructure to run overnight.

57 00:12:03.550 ⇒ 00:12:05.319 Demilade Agboola: Such that by morning.

58 00:12:05.560 ⇒ 00:12:11.670 Demilade Agboola: people can log into their, you know, BI tool and see the numbers for the previous day.

59 00:12:11.990 ⇒ 00:12:18.289 Demilade Agboola: So what that means is, people… you start your ingestion processes by, say, 12am your time.

60 00:12:19.250 ⇒ 00:12:31.879 Demilade Agboola: you’re trying to ingest the new data from the previous day. That might take, like, an hour, two hours. Sometimes, actually, people start at 1AM. So, just so that they have all the data from the previous day, so there’s no, like, missing 12 o’clock overlap weirdness.

61 00:12:32.060 ⇒ 00:12:32.730 Demilade Agboola: So we’ll sell.

62 00:12:34.050 ⇒ 00:12:39.780 Demilade Agboola: It takes maybe an hour, an hour and a half to ingest your data, depending on the volume of data you’re working with.

63 00:12:40.150 ⇒ 00:12:44.149 Demilade Agboola: And depending on, like, the different source number of sources you’re working with.

64 00:12:44.340 ⇒ 00:12:46.540 Luke Scorziell: So, you might get to 2.30.

65 00:12:46.940 ⇒ 00:12:54.470 Demilade Agboola: At that point, if your dbt takes like, 4 hours.

66 00:12:54.650 ⇒ 00:12:55.480 Demilade Agboola: Hypothetically.

67 00:12:56.050 ⇒ 00:12:56.850 Demilade Agboola: the run.

68 00:12:57.480 ⇒ 00:13:07.749 Demilade Agboola: you are getting really close to the time that people will start, like, logging in, especially if you have, like, a marketing team. So, like, I know with Eden, for instance, their team

69 00:13:08.000 ⇒ 00:13:11.679 Demilade Agboola: By 5 AM, 6am, they’re already looking at dashboards, right?

70 00:13:11.890 ⇒ 00:13:15.580 Demilade Agboola: So, depending on when people start their days, and depending on

71 00:13:15.810 ⇒ 00:13:22.729 Demilade Agboola: What happens? Because, for instance, if things break and you need to restart the entire process, it can take forever as well.

72 00:13:24.080 ⇒ 00:13:39.119 Demilade Agboola: being able to know where your bottlenecks are, being able to know how you can gain time on your, dbt runs, potentially you can save… you can half the time, maybe even more, on your dbt runs.

73 00:13:39.330 ⇒ 00:13:57.650 Demilade Agboola: So think about that for a minute. What that does is, number one, it gives you a bit more leeway in terms of having your reports ready for business hours, so that’s one. Number two, it also means that you have more room to grow. So you can add more data sources, you can do more things, because

74 00:13:58.240 ⇒ 00:14:13.209 Demilade Agboola: you’re not bound by, oh, shoot, it’s so close to business hours that, like, what… how do we realize what we need to see every day? You can feel more comfortable being, like, okay, let’s see… get a more frequent refresh on this data.

75 00:14:14.260 ⇒ 00:14:27.090 Demilade Agboola: So yeah, that’s… those are, like, the major things, like, a dbt audit will do for you. It allows you to be able to rework things, because sometimes people… their basic… there are principles to building out models as well.

76 00:14:27.230 ⇒ 00:14:32.000 Demilade Agboola: Things that are… Don’t repeat yourself, which is called the dry principle.

77 00:14:32.140 ⇒ 00:14:37.860 Demilade Agboola: You have things like being able to have a… So…

78 00:14:38.810 ⇒ 00:14:47.109 Demilade Agboola: the entire infrastructure, when you build out your models, is called a DAG, which is a direct acyclic graph, that’s what that stands for.

79 00:14:47.860 ⇒ 00:14:48.240 Luke Scorziell: Okay.

80 00:14:48.450 ⇒ 00:14:56.510 Demilade Agboola: the basic concept of a DAG is the acyclic is a very important word in there. It means that, like, there’s no cycles within your…

81 00:14:56.630 ⇒ 00:14:57.310 Demilade Agboola: rough.

82 00:14:57.430 ⇒ 00:15:09.839 Demilade Agboola: So, what that means is your graph needs to flow in a direction. So, if you have a staging model, it flows into your intermediate models, which will flow into your math models that are used to build your dashboards, right?

83 00:15:10.800 ⇒ 00:15:13.239 Demilade Agboola: It’s acyclic, it goes in that direction.

84 00:15:13.380 ⇒ 00:15:31.269 Demilade Agboola: What some people do, though, is they create cycles. So, you can have a… I have seen this before, a staging model that feeds an intermediate model that feeds a math model that comes back to an intermediate model. That breaks the concept of an acyclic graph.

85 00:15:31.970 ⇒ 00:15:36.020 Demilade Agboola: There are principles around building that, and…

86 00:15:36.160 ⇒ 00:15:48.029 Demilade Agboola: The idea of being able to do those audits is we want to ensure that, as best as possible, we’re following the right principles, as best as possible, we’re not repeating ourselves, as best as possible, we’re ensuring that, like.

87 00:15:48.170 ⇒ 00:16:00.809 Demilade Agboola: one needs to be found is easily found. As best as possible, we’re pointing out things about documentation that can be done better. As best as possible, we’re trying to set up dbt tests to maintain high data quality.

88 00:16:01.250 ⇒ 00:16:06.209 Demilade Agboola: Yeah, so there’s a bunch of reasons why you would want to do an audit.

89 00:16:07.520 ⇒ 00:16:08.840 Luke Scorziell: Yeah, okay.

90 00:16:08.960 ⇒ 00:16:16.310 Luke Scorziell: So there was… there’s… you said the dry principle? Or drag?

91 00:16:16.680 ⇒ 00:16:18.810 Demilade Agboola: dry, yeah, so DRY.

92 00:16:19.220 ⇒ 00:16:21.560 Luke Scorziell: CRY, okay, so don’t repeat yourself.

93 00:16:22.690 ⇒ 00:16:25.030 Luke Scorziell: And then…

94 00:16:25.500 ⇒ 00:16:38.010 Luke Scorziell: DAG, so the direct acyclic graph, and then, are there other, like… I’m just thinking in terms of, like, if we put out, like, a LinkedIn post of, like, here are some of the best practices, like, are there other principles that you’re thinking about?

95 00:16:38.950 ⇒ 00:16:44.149 Demilade Agboola: When I’m going through, yeah, naming conventions, another one. So.

96 00:16:44.750 ⇒ 00:16:51.709 Demilade Agboola: brain naming interventions that, reflect the data sources, as well as reflect what is going on in the models.

97 00:16:52.230 ⇒ 00:16:55.639 Demilade Agboola: So it’s very clear to people that are using it.

98 00:16:56.200 ⇒ 00:17:06.679 Demilade Agboola: Do you have good, like, just documentation? Like, do you document the logic of what you’re doing?

99 00:17:08.900 ⇒ 00:17:14.700 Demilade Agboola: Also, things around, like, testing. Do you have good tests to ensure that the data quality is high?

100 00:17:15.650 ⇒ 00:17:16.329 Demilade Agboola: -Oh.

101 00:17:20.890 ⇒ 00:17:27.900 Demilade Agboola: Are your assumptions clearly stated somewhere, which is also part of the documentation, but do you clearly state what assumptions you’re making on your data?

102 00:17:28.220 ⇒ 00:17:28.990 Demilade Agboola: So that…

103 00:17:28.990 ⇒ 00:17:29.410 Luke Scorziell: Yeah.

104 00:17:29.410 ⇒ 00:17:32.869 Demilade Agboola: People who are looking into it can have an idea of what’s going on there.

105 00:17:33.450 ⇒ 00:17:37.239 Demilade Agboola: Yeah. Just a bunch of things that, like…

106 00:17:37.890 ⇒ 00:17:40.560 Demilade Agboola: Once you’re… once you’re going into it, you start to…

107 00:17:41.700 ⇒ 00:17:42.370 Luke Scorziell: Yeah.

108 00:17:48.610 ⇒ 00:17:49.410 Luke Scorziell: Okay.

109 00:17:49.610 ⇒ 00:17:52.450 Luke Scorziell: So… And then…

110 00:17:55.650 ⇒ 00:17:59.549 Luke Scorziell: Have we… we’ve done this for certain, like, clients already?

111 00:17:59.960 ⇒ 00:18:03.389 Demilade Agboola: Yeah, we’ve done it for, like, Urban Stems, and we’ve done it for…

112 00:18:03.700 ⇒ 00:18:09.479 Demilade Agboola: Magic Spoon. Magic Spoon was the latest client that, I had to do an audit for.

113 00:18:10.470 ⇒ 00:18:16.880 Luke Scorziell: And what, what did… maybe we could start with urban, stems, like, what was the problem that they were facing?

114 00:18:17.300 ⇒ 00:18:20.022 Demilade Agboola: Everything. So…

115 00:18:21.090 ⇒ 00:18:22.640 Luke Scorziell: Fair, fair.

116 00:18:23.150 ⇒ 00:18:27.610 Demilade Agboola: So I think, for them, it was just… they had…

117 00:18:28.660 ⇒ 00:18:32.329 Demilade Agboola: One person has built out the infrastructure over, like, many years.

118 00:18:32.880 ⇒ 00:18:36.540 Demilade Agboola: And… It was just not done with good principles.

119 00:18:40.600 ⇒ 00:18:48.730 Demilade Agboola: So you had, you had Emily, a new person, take over, and she was just lost. It was… it was a cluster…

120 00:18:49.540 ⇒ 00:18:55.179 Demilade Agboola: It was just a cluster of, like, rubbish, basically, and it was really hard for her to, like, make sense of stuff.

121 00:18:56.230 ⇒ 00:18:59.160 Demilade Agboola: But in her way of trying to patch things.

122 00:18:59.570 ⇒ 00:19:10.329 Demilade Agboola: She was consistently adding to the confusion and the mess of it, because again, she’s trying to service, like, business stakeholders, so she doesn’t have time to stop

123 00:19:10.810 ⇒ 00:19:30.790 Demilade Agboola: And do something like that. Also, she didn’t necessarily have the expertise to, but, like, beyond that, even if she did, it’s hard for one data person who is building things that people need on a daily to stop and go back and audit and just break everything and take everything apart, or build a new infrastructure. So that’s the advantage of having us, because we can come in

124 00:19:30.990 ⇒ 00:19:33.450 Demilade Agboola: You can still keep doing your daily…

125 00:19:33.700 ⇒ 00:19:46.839 Demilade Agboola: like, work, and getting the report out on a day, and we can audit and implement a parallel infrastructure and eventually move you to that parallel infrastructure, which is what kind of what we do with Urban STEM.

126 00:19:47.070 ⇒ 00:20:04.120 Demilade Agboola: So the idea is, for the parallel infrastructure, we’re able to say, hey, we’ve looked at how things were done before, this was really badly done, you’re having, again… so another concept, by the way, you can add that, is modularity. Modularity is a software engineering concept, where

127 00:20:05.440 ⇒ 00:20:09.259 Demilade Agboola: You don’t have… Really long lines of code.

128 00:20:09.490 ⇒ 00:20:10.090 Demilade Agboola: Any fun?

129 00:20:10.630 ⇒ 00:20:16.469 Demilade Agboola: It’s really bad practice. It’s hard to decode, it’s hard to figure out where things go wrong.

130 00:20:16.640 ⇒ 00:20:25.630 Demilade Agboola: And over time, because people keep changing line 583, or line 600 and something, it’s really hard to keep track of the changes people are making.

131 00:20:25.760 ⇒ 00:20:40.260 Demilade Agboola: So, the idea is you want to have more modular code, you want to have smaller bits of code, ideally about, like, 100 lines thereabouts, so it’s easier to read, easier to figure out what’s going on. I mean, obviously, you can still go a little bit over, but, like, the idea is you want to kind of have that guideline around that.

132 00:20:40.770 ⇒ 00:20:48.920 Demilade Agboola: But then they didn’t have modular code, so they had, like, these long bits of code that were, like, maybe 600 lines, and…

133 00:20:49.130 ⇒ 00:21:07.660 Demilade Agboola: something is wrong, it’s in line 6, 585 or 423, which, to figure out ways to debug that is very hard, but if you have modular code, you can keep tracing each bit of code and say, okay, it’s in this portion, things went bad.

134 00:21:07.750 ⇒ 00:21:12.420 Demilade Agboola: And so now you can easily debug 100 lines versus debugging some reading.

135 00:21:12.420 ⇒ 00:21:13.090 Luke Scorziell: Hmm.

136 00:21:13.090 ⇒ 00:21:16.950 Demilade Agboola: Yeah, so… Modularity is a concept that we also will apply.

137 00:21:17.080 ⇒ 00:21:19.130 Demilade Agboola: But yeah, they didn’t have modular code.

138 00:21:20.680 ⇒ 00:21:21.600 Demilade Agboola: And…

139 00:21:22.050 ⇒ 00:21:33.379 Demilade Agboola: They didn’t always have the most precise tests, so things will break, and tests will flag that something was wrong, but they’ll be like, this test has been failing for… for years, it’s fine, we need to overlook it.

140 00:21:33.950 ⇒ 00:21:34.590 Luke Scorziell: Come on.

141 00:21:34.590 ⇒ 00:21:40.119 Demilade Agboola: So yeah, it’s this… that’s why I said, like, everything, like, it was just a huge mess.

142 00:21:40.410 ⇒ 00:21:47.300 Demilade Agboola: Yeah. And I remember Emily, like, she was always wanting to bang her head against the wall, because she’s just like, I’m so frustrated.

143 00:21:47.750 ⇒ 00:21:51.470 Demilade Agboola: But we were able to build infrastructure that

144 00:21:51.820 ⇒ 00:22:02.490 Demilade Agboola: It was easier. She found it easier to debug, she found it easier to find things, she knew where things were. The logic, things were named much better, so she was able to know, okay, so this is the logic.

145 00:22:02.580 ⇒ 00:22:22.039 Demilade Agboola: for how we calculate loted goods versus unlotted goods, it was split, so she could always go, oh, there’s a problem with how the lotter goods are being calculated. She goes to that file, she goes in there, and she’s able to figure out how to handle that process of debugging, like, lotter goods versus unlotted goods.

146 00:22:22.050 ⇒ 00:22:22.970 Demilade Agboola: Or…

147 00:22:23.250 ⇒ 00:22:29.969 Demilade Agboola: goods that were… so they have a hub-and-spoke model, versus, like, what that means is, for some… for some certain areas.

148 00:22:30.210 ⇒ 00:22:33.190 Demilade Agboola: All the goats will go to a particular point.

149 00:22:33.780 ⇒ 00:22:37.949 Demilade Agboola: And then it goes to the SPOC, which is, like, the fulfillment centers.

150 00:22:37.990 ⇒ 00:22:56.400 Demilade Agboola: Versus some other goods which would go directly to the fulfillment centers, right? So having to split that logic into two places, it was very easy for her to go, there’s a problem with hub-and-spoke, like, logic. She goes to the hub-and-spoke model, looks through, like, a hundred lines of code, figures out, okay, this is what we need to change, changes it.

151 00:22:56.470 ⇒ 00:23:07.149 Demilade Agboola: Before, it was all one big jumbo file, which sometimes is really hard to see how things are interacting, figure out where the exact lines were, so that’s kind of what we did in that situation.

152 00:23:07.260 ⇒ 00:23:08.769 Luke Scorziell: To make things easier for them.

153 00:23:09.470 ⇒ 00:23:17.629 Luke Scorziell: Yeah, okay, sweet. No, that’s super helpful. And what… what was her position? Like, who… what role did she hold in the organization?

154 00:23:17.750 ⇒ 00:23:18.520 Luke Scorziell: Emily?

155 00:23:19.020 ⇒ 00:23:31.410 Demilade Agboola: Alpha and Omega, that’s a joke, but she was… she was a one… she was a one-man team, so she was the… I’ll say analytics engineer, but she was basically a data analyst, analytics engineer, doing just a lot of stuff.

156 00:23:32.720 ⇒ 00:23:33.550 Luke Scorziell: Oh, okay.

157 00:23:33.870 ⇒ 00:23:35.980 Luke Scorziell: Oh, wait, is this Tom on here?

158 00:23:37.120 ⇒ 00:23:39.729 Luke Scorziell: Oh, that’s so funny, I didn’t even notice you joined.

159 00:23:41.980 ⇒ 00:23:48.309 Luke Scorziell: Let me… I’ll get my, like, non-video participants off, because I have my note-taker.

160 00:23:48.310 ⇒ 00:23:51.700 Uttam Kumaran: I’m just listening in, so I just joined, I was, like, finishing some stuff.

161 00:23:52.240 ⇒ 00:23:56.730 Luke Scorziell: No, no, you’re good. I always… I have my, like, show non-video participants off.

162 00:23:56.730 ⇒ 00:23:57.370 Uttam Kumaran: Hello.

163 00:23:57.370 ⇒ 00:24:04.019 Luke Scorziell: So I never… I just don’t see when people, don’t have their cameras on. But, that’s funny.

164 00:24:04.170 ⇒ 00:24:12.130 Luke Scorziell: And then, okay, so that’s for Urban Stems, then what about for Magic Spoon? What,

165 00:24:12.830 ⇒ 00:24:18.609 Luke Scorziell: Yeah, tell me about them, like, their kind of problem, what were they struggling with, how did we come in and help?

166 00:24:19.290 ⇒ 00:24:26.659 Demilade Agboola: So, they didn’t have a struggle, per se, like, for them, everything was fine, so it wasn’t necessarily a thing of, like, they had,

167 00:24:27.450 ⇒ 00:24:36.360 Demilade Agboola: they were not… they weren’t crippled by things, they were able to still function, so I think for them, it was just like, hey, we’d like to see if there’s anything we could gain.

168 00:24:36.620 ⇒ 00:24:41.719 Demilade Agboola: So we’re able to notice a couple of things, though. They have, like, long-running models.

169 00:24:41.960 ⇒ 00:24:50.790 Demilade Agboola: And so, what that means is there were certain models that would run for over, like, 40 minutes, some would run for over, like, 25 minutes.

170 00:24:50.950 ⇒ 00:24:55.189 Demilade Agboola: And the entire infrastructure ran for, like, 2 and a half hours.

171 00:24:55.570 ⇒ 00:25:01.039 Demilade Agboola: So, obviously, if we’re able to get those, like, models down, as well as make

172 00:25:01.260 ⇒ 00:25:08.070 Demilade Agboola: gains across multiple models in the infrastructure. We potentially could get those… those runs down to, like.

173 00:25:08.880 ⇒ 00:25:16.010 Demilade Agboola: an hour 40 minutes, maybe even an hour 30 minutes. Like, we can knock off an hour in the entire process of what’s going on.

174 00:25:16.400 ⇒ 00:25:23.769 Demilade Agboola: So the idea is we’re trying to see how we can drive efficiency. We’re also able to see things like…

175 00:25:23.780 ⇒ 00:25:25.599 Luke Scorziell: They didn’t have.

176 00:25:26.770 ⇒ 00:25:27.840 Demilade Agboola: Sources?

177 00:25:28.800 ⇒ 00:25:39.679 Demilade Agboola: Linked into their, so there’s something called sources.yaml, where you’re able to link sources From your warehouse into

178 00:25:40.140 ⇒ 00:25:45.499 Demilade Agboola: Like, dbt, and it creates, like, references to those sources.

179 00:25:45.970 ⇒ 00:25:52.620 Demilade Agboola: They don’t… they don’t set that up, so what they effectively do is they are just pointing directly… they hard-code the name of the…

180 00:25:53.060 ⇒ 00:25:58.360 Demilade Agboola: of the… table into the… into dbt.

181 00:25:58.540 ⇒ 00:26:07.549 Demilade Agboola: Which, I mean, it works, but the advantages are you can’t do, like, sauce freshness tests, you can’t do anything to, like, figure out if things are wrong with your sauce.

182 00:26:09.340 ⇒ 00:26:18.149 Demilade Agboola: And so that… they’re losing out on an advantage there. They also don’t have any tests or any documentation anywhere set up for anything, so…

183 00:26:18.420 ⇒ 00:26:23.150 Demilade Agboola: Any logic, you have to kind of figure out by, like, reading.

184 00:26:23.500 ⇒ 00:26:29.410 Demilade Agboola: The code, and obviously, if you don’t have any business context,

185 00:26:29.610 ⇒ 00:26:36.310 Demilade Agboola: you can’t figure out every single thing via code. You can get some context, but you can’t figure out every single thing via code.

186 00:26:37.000 ⇒ 00:26:46.759 Demilade Agboola: So that would make it hard if they were to hire a new person and that person was ramping up. It’s kind of hard to figure out what’s going on, what decisions were made, why it was made, all that stuff.

187 00:26:47.430 ⇒ 00:26:52.540 Demilade Agboola: So those were, like, the three main, pain points for Arject Explorer.

188 00:26:52.660 ⇒ 00:26:58.650 Demilade Agboola: Efficiency… Documentation and sources implementation.

189 00:27:00.090 ⇒ 00:27:00.890 Luke Scorziell: Okay.

190 00:27:08.510 ⇒ 00:27:11.469 Luke Scorziell: It seems like a common struggle is that…

191 00:27:11.870 ⇒ 00:27:14.049 Luke Scorziell: When someone new is coming in.

192 00:27:14.340 ⇒ 00:27:27.319 Luke Scorziell: to the organization, that’s when, like, all the stuff that you’ve kind of been like, oh, we’ll just ignore this test that’s been broken for years, and then you bring someone new in who’s different, and it’s like.

193 00:27:27.770 ⇒ 00:27:31.619 Luke Scorziell: You know, oh my gosh, this is terrible, and they’re gonna fail at this role unless…

194 00:27:31.910 ⇒ 00:27:34.990 Luke Scorziell: We actually fixed the problem that’s going on.

195 00:27:35.420 ⇒ 00:27:44.160 Demilade Agboola: I mean, maybe not fail, but they’ll eventually just kind of become part of the system, and it’s hard, because, like, people will learn bad habits, quote-unquote, over time.

196 00:27:44.310 ⇒ 00:27:49.030 Demilade Agboola: And so, if people come into your system that is already broken,

197 00:27:49.350 ⇒ 00:27:53.840 Demilade Agboola: They would most likely learn to, like… again, let’s take an example of a test.

198 00:27:53.950 ⇒ 00:27:59.089 Demilade Agboola: that keeps Plug in an error that isn’t an error.

199 00:28:00.300 ⇒ 00:28:04.180 Demilade Agboola: I come in, they’re initially worried, I’m like, oh, this test keeps failing.

200 00:28:04.530 ⇒ 00:28:06.989 Demilade Agboola: But, after, like, 2 weeks.

201 00:28:07.170 ⇒ 00:28:11.830 Demilade Agboola: It’s just noise. It becomes background noise, and to just know that that test always fails.

202 00:28:12.120 ⇒ 00:28:13.070 Demilade Agboola: So…

203 00:28:13.540 ⇒ 00:28:22.680 Demilade Agboola: The people come in, get the bad habit, but in some certain cases, it just also provides friction for, like, knowledge transfer.

204 00:28:22.990 ⇒ 00:28:23.570 Demilade Agboola: So…

205 00:28:23.570 ⇒ 00:28:23.890 Luke Scorziell: leaves.

206 00:28:23.890 ⇒ 00:28:28.649 Demilade Agboola: You are coming into a company that has very little to any documentation on their code.

207 00:28:28.840 ⇒ 00:28:37.919 Demilade Agboola: You’re gonna come in, and you’re probably going to struggle, unless you’ve literally worked with that com… like, a very, very similar company before.

208 00:28:38.250 ⇒ 00:28:49.969 Demilade Agboola: Because every company has, like, a little bit of context that you need to know into how they calculate revenue, into how they handle inventory, and, like, how things are going. And if there’s no…

209 00:28:50.390 ⇒ 00:29:05.120 Demilade Agboola: well-defined bits of code that’s modular and is documented. It’s really hard to, like… you’re gonna have to be reading 600 lines of code to figure out what’s going on here, or, you know, 800 lines of code to figure out what’s going on there.

210 00:29:05.330 ⇒ 00:29:10.059 Demilade Agboola: So, yeah, it becomes really hard to ramp up in such an organization versus if

211 00:29:10.220 ⇒ 00:29:15.319 Demilade Agboola: Things were clearly broken down into very digestible bits, and were also…

212 00:29:15.770 ⇒ 00:29:19.549 Demilade Agboola: There was also documentation to accompany those digestible bits.

213 00:29:20.550 ⇒ 00:29:21.140 Luke Scorziell: Yeah.

214 00:29:23.150 ⇒ 00:29:27.500 Luke Scorziell: Sweet. And then what was, like, the solution that you guys had for Magic Spoon? How did that go?

215 00:29:28.390 ⇒ 00:29:31.029 Demilade Agboola: So that’s still a work in progress,

216 00:29:31.920 ⇒ 00:29:36.159 Demilade Agboola: That’s still a work in progress, but the general concept was just, like.

217 00:29:36.370 ⇒ 00:29:44.890 Demilade Agboola: For certain models, to drive efficiency, we will change something called the matarization of the models. What that means is…

218 00:29:45.890 ⇒ 00:29:49.660 Demilade Agboola: dbt… within dbt, you can choose how tables are.

219 00:29:49.920 ⇒ 00:29:54.160 Demilade Agboola: So, for ease of understanding, every… let’s call everything a table.

220 00:29:54.710 ⇒ 00:29:58.199 Demilade Agboola: But, like, you can choose how these tables are created.

221 00:29:59.880 ⇒ 00:30:10.099 Demilade Agboola: So you can create it as a view, which, as a view, it is not materialized, it’s not… it’s not created, quote-unquote. It’s a query.

222 00:30:10.430 ⇒ 00:30:17.070 Demilade Agboola: So every time you try to hit your DB for that table, quote-unquote, what it’s doing is it’s…

223 00:30:17.290 ⇒ 00:30:22.629 Demilade Agboola: Saying, hey, run the query that creates this table, and get me the latest information.

224 00:30:23.230 ⇒ 00:30:26.149 Demilade Agboola: That I need from that query, right?

225 00:30:26.150 ⇒ 00:30:26.730 Luke Scorziell: Damn.

226 00:30:27.020 ⇒ 00:30:39.500 Demilade Agboola: So that’s what AV will do. You can materialize it as a table, so what that does is, at the specified time in which it needs to run, it would recreate all artifacts over time.

227 00:30:39.930 ⇒ 00:30:46.279 Demilade Agboola: So, if I say every morning I want this to be created as a table, it would delete the old table

228 00:30:46.450 ⇒ 00:30:48.840 Demilade Agboola: I replace it with a new table.

229 00:30:49.390 ⇒ 00:30:53.309 Demilade Agboola: From everything all… from the beginning of time up till that date.

230 00:30:53.410 ⇒ 00:31:04.609 Demilade Agboola: Now, where that can be very problematic is if I have a ton of data. So if I was a big company that produced a ton of data, and every day I was producing, say.

231 00:31:05.060 ⇒ 00:31:07.589 Demilade Agboola: A million rows of data, right?

232 00:31:07.920 ⇒ 00:31:10.299 Demilade Agboola: And I have data since 2020.

233 00:31:10.570 ⇒ 00:31:16.160 Demilade Agboola: What that means is every morning when the table runs, it will delete the old table.

234 00:31:16.330 ⇒ 00:31:24.860 Demilade Agboola: And create every single day from 2020 till 2026, including the 1 million rows that were created yesterday.

235 00:31:25.020 ⇒ 00:31:32.269 Demilade Agboola: Which, obviously, especially if the data doesn’t change over time, it’s a waste of resources to keep building that over time.

236 00:31:32.510 ⇒ 00:31:37.139 Demilade Agboola: So what we then do is a materialization called the incremental strategy.

237 00:31:37.380 ⇒ 00:31:39.379 Demilade Agboola: So what that means is, hey.

238 00:31:39.900 ⇒ 00:31:47.779 Demilade Agboola: Keep everything static up until, say, a specified period, and for only new rows that have changed, or the newly created rows.

239 00:31:48.000 ⇒ 00:31:51.529 Demilade Agboola: I pin them to the bottom of the table, or I pin them to the table.

240 00:31:51.770 ⇒ 00:31:54.399 Demilade Agboola: Right, so that’s kind of how that table would work.

241 00:31:54.590 ⇒ 00:32:04.270 Demilade Agboola: And so that saves you a bunch of time, because instead of having to recreate every single day, or every single 12 hours, or whatever cadence you want.

242 00:32:04.910 ⇒ 00:32:11.389 Demilade Agboola: You now have… Only the new data that will be added to the table.

243 00:32:11.560 ⇒ 00:32:19.750 Demilade Agboola: So that saves you a bunch of runtime, so that’s compute resources being saved, so you don’t have to compute everything from scratch every single day.

244 00:32:20.180 ⇒ 00:32:25.590 Demilade Agboola: As well as, you know, just general runtime, so your data is ready much faster.

245 00:32:26.540 ⇒ 00:32:27.110 Luke Scorziell: Yeah.

246 00:32:27.110 ⇒ 00:32:31.930 Demilade Agboola: And that… Faster bit can potentially make you even starter.

247 00:32:33.020 ⇒ 00:32:39.380 Demilade Agboola: increase the cadence of your dbt runs if you need to see your data much closer to Real time.

248 00:32:40.560 ⇒ 00:32:42.149 Luke Scorziell: Yeah, okay, sweet.

249 00:32:42.830 ⇒ 00:32:49.290 Luke Scorziell: Okay. No, maybe, like, just… it might be more just, like, technical…

250 00:32:49.390 ⇒ 00:32:52.969 Luke Scorziell: Or, I don’t know if technical’s the right word, but, like, fill-in-the-blank type questions.

251 00:32:53.260 ⇒ 00:32:56.670 Luke Scorziell: But typically, it sounds like

252 00:32:56.880 ⇒ 00:33:01.849 Luke Scorziell: Like, a… this would be a data engineer that buys this, or what is the…

253 00:33:02.020 ⇒ 00:33:07.560 Luke Scorziell: Like, who is the point of, contact that you might have doing a dbt audit?

254 00:33:10.470 ⇒ 00:33:13.049 Luke Scorziell: Our analytics engineer is what Emily was.

255 00:33:13.320 ⇒ 00:33:22.790 Demilade Agboola: So, when you mean point of contact, do you mean the person who will be biting it and trying to push it to the stakeholders, or do you mean the person I will be interacting with on a daily?

256 00:33:23.860 ⇒ 00:33:28.019 Luke Scorziell: Maybe both. Maybe you can explain both to me.

257 00:33:28.900 ⇒ 00:33:35.269 Demilade Agboola: So… the person who will bite on it would most likely be a…

258 00:33:35.510 ⇒ 00:33:39.760 Demilade Agboola: Technical person, so like a data engineer, analytics engineer sort of person.

259 00:33:40.030 ⇒ 00:33:42.950 Demilade Agboola: Who will…

260 00:33:44.560 ⇒ 00:33:50.779 Demilade Agboola: who is, like, probably maybe wearing a hat that can make the decision? So, like, a CTO,

261 00:33:51.030 ⇒ 00:33:54.290 Demilade Agboola: Probably the data engineering background, that sort of thing.

262 00:33:54.860 ⇒ 00:34:05.689 Demilade Agboola: Or, basically, a very frustrated business stakeholder who can see That some of this…

263 00:34:05.830 ⇒ 00:34:20.349 Demilade Agboola: things that you will see in the article are things that they’ve heard, like, in meetings. They might not necessarily always remember the details, but they know that, you know, maybe they’ve asked for data before, and it’s like, well, dbt is still running.

264 00:34:20.469 ⇒ 00:34:29.010 Demilade Agboola: Or the dbt runtimes have increased or something. They don’t really understand what’s going on, but it’s just, like, that would be the non-technical stakeholder.

265 00:34:30.600 ⇒ 00:34:44.040 Demilade Agboola: have that. They don’t necessarily know what the issues are, but they’ve probably heard in passing, or in a meeting here, about how, like, oh, our runtime is just taking forever, or,

266 00:34:44.460 ⇒ 00:34:49.769 Demilade Agboola: They asked questions about their data, and it took forever for them to get an answer about it, that kind of thing.

267 00:34:50.360 ⇒ 00:34:58.109 Demilade Agboola: So that would be the non-technical person who would be pitching, or who would want to, like, jump on this.

268 00:34:58.220 ⇒ 00:35:04.879 Demilade Agboola: In terms of who I’m interacting with on a daily, it will purely be technical. It’ll probably be, like, an analytics engineer.

269 00:35:05.990 ⇒ 00:35:06.730 Luke Scorziell: Okay.

270 00:35:08.670 ⇒ 00:35:14.029 Luke Scorziell: That’s basically, like, I’m not getting my decisions fast enough. I don’t really know what DBT is, but I know it takes forever.

271 00:35:14.260 ⇒ 00:35:17.089 Luke Scorziell: Can you speed this up for me? Would be, like.

272 00:35:17.430 ⇒ 00:35:20.180 Luke Scorziell: the long and short of it .

273 00:35:20.360 ⇒ 00:35:22.040 Demilade Agboola: Effectively.

274 00:35:22.040 ⇒ 00:35:28.080 Luke Scorziell: And then are there… Are there, like, preconditions that they maybe, like, need to have?

275 00:35:28.280 ⇒ 00:35:35.249 Luke Scorziell: Or… Like, obviously, I probably need to be using dbt.

276 00:35:35.410 ⇒ 00:35:39.689 Luke Scorziell: Are there other, like, Tech stack items that they need.

277 00:35:40.400 ⇒ 00:35:46.209 Demilade Agboola: I mean, obviously, we can start with the dbt audit and scale to, like, just a general audit of the infrastructure.

278 00:35:46.460 ⇒ 00:35:51.150 Demilade Agboola: But yeah, for a dbt or DT, they need to have dbt, and they also need to…

279 00:35:52.610 ⇒ 00:35:59.049 Demilade Agboola: I mean, to be honest, they have dbt, we will hop in and just kind of figure out what else they missed, or what else is missing.

280 00:35:59.270 ⇒ 00:36:08.650 Demilade Agboola: Whether it’s their… infrastructure around dbt, whether it’s their documentation around dbt, whether it’s…

281 00:36:09.030 ⇒ 00:36:13.869 Demilade Agboola: Just not fully utilizing the resources dbt gives them.

282 00:36:14.450 ⇒ 00:36:29.000 Demilade Agboola: But yeah, it would… like, once we… once you have dbt, and things are just not… things feel clunky, because a lot of people get dbt with the promise of things to… like, things are going to change once we get this tool, it’s this magic tool, because dbt…

283 00:36:29.190 ⇒ 00:36:31.039 Demilade Agboola: Especially, like, 3 years ago.

284 00:36:31.200 ⇒ 00:36:36.650 Demilade Agboola: Now it’s cooled off, but, like, especially, like, between 5 to 3 years ago, it was the…

285 00:36:36.990 ⇒ 00:36:37.940 Demilade Agboola: Hardest them on the…

286 00:36:37.940 ⇒ 00:36:38.480 Luke Scorziell: Yeah.

287 00:36:38.480 ⇒ 00:36:43.899 Demilade Agboola: So, a lot of people got it, and they don’t necessarily feel like those promises may have conveyed.

288 00:36:44.480 ⇒ 00:36:46.310 Demilade Agboola: So it’s like…

289 00:36:46.310 ⇒ 00:36:46.980 Luke Scorziell: Yeah.

290 00:36:47.270 ⇒ 00:36:52.209 Demilade Agboola: How do we help you get closer to those promises? How do we help you figure out what you’re missing?

291 00:36:52.330 ⇒ 00:36:53.990 Demilade Agboola: to fully utilize dbt.

292 00:36:54.840 ⇒ 00:36:56.909 Luke Scorziell: Yeah, I gotta say.

293 00:36:56.960 ⇒ 00:36:58.040 Demilade Agboola: And then…

294 00:36:58.040 ⇒ 00:37:03.190 Luke Scorziell: As far as, like, the literal, just, logistics of doing this. Is it, like.

295 00:37:03.320 ⇒ 00:37:07.650 Luke Scorziell: Of a 4-week sprint, or are you…

296 00:37:07.770 ⇒ 00:37:09.749 Luke Scorziell: Like, are you coming in and…

297 00:37:10.180 ⇒ 00:37:13.520 Luke Scorziell: Like, I don’t know, just what is the, like, process of…

298 00:37:14.800 ⇒ 00:37:15.220 Demilade Agboola: It depends.

299 00:37:15.220 ⇒ 00:37:21.099 Luke Scorziell: What do they get when they get a… yeah. Like, maybe it would be, like, a standard bundle that we could offer on it.

300 00:37:21.870 ⇒ 00:37:25.990 Demilade Agboola: It depends on… so, it depends on what you need,

301 00:37:26.820 ⇒ 00:37:30.909 Demilade Agboola: Because if what you need is… I just need a roadmap.

302 00:37:31.480 ⇒ 00:37:44.899 Demilade Agboola: like, a North Star presented for, like, presented to us. That could be done in, like, 3 to 4 weeks, to be honest, and that’s, like, that gives us conservative… that’s very conservative, that gives us enough time to do everything we need, but…

303 00:37:45.120 ⇒ 00:37:46.660 Demilade Agboola: Because…

304 00:37:48.240 ⇒ 00:37:56.420 Demilade Agboola: It also varies on people’s stock. Some people have a lot of models, some have fewer models, so again, I think a 3-4 week bundle will be…

305 00:37:59.270 ⇒ 00:38:07.269 Demilade Agboola: it will be fine for, like, whoever. Like, if you have a lot of models, we should still be able to get it done in that time. If you have a few models, it will definitely get it done in that time.

306 00:38:07.560 ⇒ 00:38:14.440 Demilade Agboola: So the first stage could obviously be the auditing. The next stage could also be, like, implementation on top of that.

307 00:38:14.600 ⇒ 00:38:18.329 Demilade Agboola: Which, again, it’s kind of hard to place.

308 00:38:18.470 ⇒ 00:38:23.110 Demilade Agboola: For some people, you could implement changes in One month.

309 00:38:23.520 ⇒ 00:38:30.130 Demilade Agboola: For another set of people, you could be 3 months in and still be working on stuff, because they have so much

310 00:38:30.680 ⇒ 00:38:37.860 Demilade Agboola: stuff that’s going on within the infrastructures, right? You can have multiple data sources, you can have

311 00:38:39.320 ⇒ 00:38:41.320 Demilade Agboola: Very complex business logic.

312 00:38:42.310 ⇒ 00:38:42.980 Luke Scorziell: Yeah.

313 00:38:42.980 ⇒ 00:38:45.819 Demilade Agboola: So that might be harder to place or cap.

314 00:38:46.650 ⇒ 00:38:55.889 Demilade Agboola: Potentially, what you could do is… have it by… Maybe Mart?

315 00:38:56.110 ⇒ 00:39:00.479 Demilade Agboola: So by March would probably be something like… Hey, we can…

316 00:39:00.890 ⇒ 00:39:10.480 Demilade Agboola: do an audit, plus maybe your sales, like, your revenue and sales data in another additional month or two, for instance. Or…

317 00:39:10.660 ⇒ 00:39:13.509 Demilade Agboola: We can do your audit in one month, and then…

318 00:39:13.700 ⇒ 00:39:17.840 Demilade Agboola: The subsequent month, or month and a half, say six weeks?

319 00:39:17.960 ⇒ 00:39:18.739 Demilade Agboola: We will do…

320 00:39:19.370 ⇒ 00:39:26.050 Demilade Agboola: inventory data, like, whatever. So, like, we can have a… an Odysplus-1 sort of concept.

321 00:39:28.920 ⇒ 00:39:30.620 Luke Scorziell: Yeah, yeah. Okay.

322 00:39:30.620 ⇒ 00:39:33.959 Demilade Agboola: But I mean, the entire stack, the entire stack could take a really long time.

323 00:39:34.780 ⇒ 00:39:36.769 Luke Scorziell: Well, it sounds like get an audit.

324 00:39:37.020 ⇒ 00:39:38.229 Luke Scorziell: But they can, like…

325 00:39:38.860 ⇒ 00:39:51.970 Luke Scorziell: Or give… do an audit for a month, give them a roadmap, say, here are all the problems we found, here’s what we would do, and then, you know, if you’d like to move forward, this is what it would cost for the implementation, and then we can give them kind of a specific timeline based on

326 00:39:52.420 ⇒ 00:39:54.419 Luke Scorziell: Like, what we found in the roadmap.

327 00:39:55.020 ⇒ 00:39:58.310 Demilade Agboola: Yeah, we could even timeline based on what we found in the roadmap. We can also…

328 00:39:59.660 ⇒ 00:40:01.860 Demilade Agboola: We can also do setting, like.

329 00:40:02.250 ⇒ 00:40:08.810 Demilade Agboola: priority, data mats. So what data mats is, is… .

330 00:40:08.810 ⇒ 00:40:09.380 Luke Scorziell: Scott?

331 00:40:09.700 ⇒ 00:40:13.849 Demilade Agboola: Where the data… where data is fetched from is considered a data mat.

332 00:40:14.060 ⇒ 00:40:20.700 Demilade Agboola: And so, we categorize that usually by… Business concepts, so, like…

333 00:40:21.060 ⇒ 00:40:27.009 Demilade Agboola: You can have a revenue data match, you can have a sales data match, you can have a,

334 00:40:28.620 ⇒ 00:40:31.139 Demilade Agboola: I’m blanking for some reason. You can have a marketing.

335 00:40:31.140 ⇒ 00:40:31.850 Luke Scorziell: product.

336 00:40:31.850 ⇒ 00:40:35.340 Demilade Agboola: Yeah, product, you can have a marketing data mat.

337 00:40:35.560 ⇒ 00:40:39.599 Demilade Agboola: Basically, you can have just a bunch of data mints, and…

338 00:40:39.790 ⇒ 00:40:55.379 Demilade Agboola: the concept is, we might not be able to touch every single data mat, but you can prioritize. Maybe the important thing is, hey, our revenue has been in shambles for the past 2 years. How do we get this to scratch? So we can say, hey.

339 00:40:55.470 ⇒ 00:41:02.220 Demilade Agboola: This is the audit, and then if you want us to tackle your most pressing data amount, give us 6 weeks, and we’ll do that for you as well.

340 00:41:02.930 ⇒ 00:41:04.100 Luke Scorziell: Yeah, okay.

341 00:41:04.310 ⇒ 00:41:10.249 Luke Scorziell: Sweet, and then, do we need ax… I don’t know if we need to, like…

342 00:41:11.280 ⇒ 00:41:15.550 Luke Scorziell: Okay, commercials, risks, and additions, proofs, ordinance,

343 00:41:17.790 ⇒ 00:41:21.150 Luke Scorziell: I guess, how do we… hmm…

344 00:41:22.550 ⇒ 00:41:25.370 Luke Scorziell: How do we know when it’s successful?

345 00:41:26.010 ⇒ 00:41:33.549 Luke Scorziell: So, like, what are a couple outcomes that we would measure, maybe, or that we could, like, show, like, here’s a KPI that we’re looking at?

346 00:41:38.340 ⇒ 00:41:42.579 Luke Scorziell: And I guess there’s, like, run… runtime is what you mentioned, like, how could we improve the runtime?

347 00:41:43.540 ⇒ 00:41:48.610 Demilade Agboola: So runtime is a good… is a good indicator, we’re on time.

348 00:41:48.610 ⇒ 00:41:55.050 Luke Scorziell: I mean, we probably wouldn’t really see too much with, like, the roadmap, right? I mean, obviously we’re not gonna be making changes, but maybe we would say, like.

349 00:41:55.530 ⇒ 00:42:02.120 Luke Scorziell: And we could measure, like, the number of insights, I don’t know.

350 00:42:02.120 ⇒ 00:42:08.660 Demilade Agboola: No, no, so, like, usually it will probably be runtime, which is very, like, key.

351 00:42:09.090 ⇒ 00:42:12.340 Demilade Agboola: That’s probably one of the most measurable ones.

352 00:42:12.450 ⇒ 00:42:26.729 Demilade Agboola: other stuff are harder to measure, because documentation… I mean, you can show that as well, like, it’s the same way part of what, like, Utam pushes towards, like, clients, is that we’ll get you documentation on your data sources and all of that.

353 00:42:27.040 ⇒ 00:42:31.180 Demilade Agboola: is you can also have documentation for your dbt

354 00:42:31.620 ⇒ 00:42:34.269 Demilade Agboola: sources, as well as your dbt models.

355 00:42:34.410 ⇒ 00:42:38.029 Demilade Agboola: Done. So that will be an outcome.

356 00:42:40.320 ⇒ 00:42:44.609 Luke Scorziell: Well, there’s, like, also adoption KPIs, so, like, who’s using it.

357 00:42:45.030 ⇒ 00:42:46.670 Luke Scorziell: I guess, or, like, our…

358 00:42:47.580 ⇒ 00:42:57.849 Demilade Agboola: That might be harder to, again, determine, especially if it’s, like, a one-man team. So, like, if you take Urban Stems, like, Emily was using it, it was a hassle, it was a pain in the butt.

359 00:42:58.370 ⇒ 00:42:59.860 Demilade Agboola: And she did enjoy it.

360 00:43:00.480 ⇒ 00:43:02.190 Demilade Agboola: But she was using it.

361 00:43:03.050 ⇒ 00:43:04.270 Luke Scorziell: 100%.

362 00:43:04.270 ⇒ 00:43:10.719 Demilade Agboola: Yeah, so she had no choice but to use it. But she much preferred to use

363 00:43:11.100 ⇒ 00:43:15.500 Demilade Agboola: the new thing we built for her. Even after we left.

364 00:43:15.740 ⇒ 00:43:24.040 Demilade Agboola: She… anytime any new thing comes in, she’s putting in the new infrastructure and using it, because it’s just much easier for her to understand what’s going on there.

365 00:43:24.230 ⇒ 00:43:31.459 Demilade Agboola: So, it’s… adoption is there, but it’s kind of hard to quantify, if you get what I mean.

366 00:43:32.130 ⇒ 00:43:34.999 Luke Scorziell: Yeah, yeah, that makes sense. I mean, it’s almost like…

367 00:43:35.120 ⇒ 00:43:41.310 Luke Scorziell: I could see the cycle being, we bought DBT 5 years ago, we’re pretty much ready to give it up and do a new RFP for a new…

368 00:43:41.450 ⇒ 00:43:47.929 Luke Scorziell: solution, maybe a latch ditch effort, is, like, we do an audit to see if we can clean it up.

369 00:43:48.270 ⇒ 00:43:56.270 Luke Scorziell: And then it’s like, oh, we didn’t have to go through an RFE, that saves us a ton of time, effort, energy, all that kind of stuff.

370 00:43:57.210 ⇒ 00:44:01.439 Luke Scorziell: And then, like, are there risks? Sorry, now you have to…

371 00:44:01.610 ⇒ 00:44:06.399 Luke Scorziell: In 60 seconds, what, are there, like, risks that, that you,

372 00:44:07.270 ⇒ 00:44:12.610 Luke Scorziell: Like, could see with this audit, like, to their data, or their company and business?

373 00:44:13.140 ⇒ 00:44:21.819 Demilade Agboola: Number one would be access, so if you don’t get access quickly, it’s hard to do anything. So access to GitHub, access to dbt…

374 00:44:22.320 ⇒ 00:44:27.009 Demilade Agboola: Oh, not GitHub, they’re a Git provider, so it’s not always necessarily GitHub.

375 00:44:27.500 ⇒ 00:44:37.049 Demilade Agboola: So access to their Git provider, access to dbt, that would be one.

376 00:44:37.500 ⇒ 00:44:45.709 Demilade Agboola: 2 would be… concurrent data requests, so if they…

377 00:44:45.990 ⇒ 00:44:49.169 Demilade Agboola: Have other things they want us to do in terms of data.

378 00:44:49.740 ⇒ 00:44:57.710 Demilade Agboola: Beyond just auditing, and we don’t necessarily staff for that, it can be hard to, like, multitask across two things.

379 00:44:58.060 ⇒ 00:45:10.400 Demilade Agboola: Also, in terms of… Again, potential risk is the volume of people’s infrastructure.

380 00:45:10.610 ⇒ 00:45:17.700 Demilade Agboola: So some people, again, like I said earlier, some people’s infrastructure isn’t that, like, voluminous, but some have, like, really large data.

381 00:45:17.820 ⇒ 00:45:21.579 Demilade Agboola: And a lot of models going on there, so that would be harder, too.

382 00:45:21.810 ⇒ 00:45:24.000 Demilade Agboola: untangle.

383 00:45:24.680 ⇒ 00:45:29.550 Demilade Agboola: Off the top of my head, those are, like, the three main things I would say.

384 00:45:29.770 ⇒ 00:45:31.790 Demilade Agboola: Well, potential, like, risks and…

385 00:45:36.390 ⇒ 00:45:37.810 Luke Scorziell: However, we, like, mitig.

386 00:45:37.810 ⇒ 00:45:39.630 Demilade Agboola: that risk. Sorry, you said.

387 00:45:39.630 ⇒ 00:45:40.200 Luke Scorziell: Sorry.

388 00:45:40.730 ⇒ 00:45:44.760 Luke Scorziell: with the… with the… oh, can you hear me now? With the volume,

389 00:45:44.930 ⇒ 00:45:47.920 Luke Scorziell: how are we kind of mitigating that risk? Like…

390 00:45:48.520 ⇒ 00:45:51.619 Luke Scorziell: Was there a point at which we’re just like, hey, this is too much, or…

391 00:45:51.920 ⇒ 00:45:55.569 Luke Scorziell: Like, how can we, like… Bring that risk down.

392 00:45:56.030 ⇒ 00:46:00.559 Demilade Agboola: I think with… with volume, it’s probably a thing of, like, one A’s.

393 00:46:00.680 ⇒ 00:46:06.229 Demilade Agboola: Early recognization, like, you need to be able to quickly recognize that, hey, this is the, like…

394 00:46:06.430 ⇒ 00:46:12.770 Demilade Agboola: your data stack has 4,000 models. We’re not going to be able to audit 4,000 models in 4 weeks, right?

395 00:46:12.890 ⇒ 00:46:13.510 Demilade Agboola: For instance.

396 00:46:14.460 ⇒ 00:46:28.149 Demilade Agboola: I say that because, like, my previous company, we had, like, 4,000 models, so… now we’re not really going to audit all of that in 4 weeks, realistically speaking. So things like that would be helpful. I think…

397 00:46:28.610 ⇒ 00:46:33.880 Demilade Agboola: Being able to recognize early, communicate early.

398 00:46:34.090 ⇒ 00:46:36.970 Demilade Agboola: As well as being able to…

399 00:46:38.470 ⇒ 00:46:42.660 Demilade Agboola: Get, like, a range of how many… models.

400 00:46:42.970 ⇒ 00:46:51.970 Demilade Agboola: And models are a bit vague, because you can say 200 models, but each of those 200 models, for instance, can have 8,000 lines, right? Like, that becomes really hard.

401 00:46:52.070 ⇒ 00:47:01.020 Demilade Agboola: But you can have 600 models that only have, like, 100 lines in each of them, which is just, like, easier, right? So,

402 00:47:01.760 ⇒ 00:47:08.079 Demilade Agboola: Yeah, I think number of models would be a good start to have an idea of, like, what kind of…

403 00:47:08.360 ⇒ 00:47:13.439 Demilade Agboola: Range we’re talking about, but obviously it gets a bit deeper than that, but you don’t want to make it too complex.

404 00:47:14.210 ⇒ 00:47:20.249 Luke Scorziell: Yeah. Okay. Sweet. I think that’s most of what I…

405 00:47:20.480 ⇒ 00:47:25.739 Luke Scorziell: need for now? I don’t know, are there, like… is there anything I’m missing? Anything, like… I mean, we can follow up, too.

406 00:47:26.030 ⇒ 00:47:34.100 Luke Scorziell: So… I guess my goal at this is gonna be to take the notes from this conversation.

407 00:47:34.490 ⇒ 00:47:40.250 Luke Scorziell: Kind of plug it into a, like, take my notes, the meeting notes.

408 00:47:40.450 ⇒ 00:47:42.600 Luke Scorziell: Come up with content, come up with, like.

409 00:47:43.000 ⇒ 00:47:48.529 Luke Scorziell: Maybe, like, an SOW of sorts? I don’t know that I fully have enough for that yet. And then,

410 00:47:49.390 ⇒ 00:47:53.570 Luke Scorziell: And then we can start pushing it out, but… and you would be, like, the main stakeholder?

411 00:47:53.790 ⇒ 00:47:56.100 Luke Scorziell: Doing this? Like, you’re the guy, it sounds like.

412 00:47:56.760 ⇒ 00:47:58.440 Demilade Agboola: The, yeah.

413 00:47:59.360 ⇒ 00:47:59.980 Luke Scorziell: Okay.

414 00:48:00.810 ⇒ 00:48:02.320 Luke Scorziell: Cool.

415 00:48:02.320 ⇒ 00:48:06.950 Uttam Kumaran: There’d end up being probably a few people that can actually execute the audit.

416 00:48:07.090 ⇒ 00:48:10.310 Uttam Kumaran: Like, I think it would be Demi, or Awash.

417 00:48:10.610 ⇒ 00:48:22.979 Uttam Kumaran: maybe Ashwini, but certainly I think Demi probably is the closest and has conducted both of… what’s sort of a through line between the one we did for Urban Stems and the one we did for Magic Spoon.

418 00:48:24.190 ⇒ 00:48:28.090 Uttam Kumaran: The nice thing is… We…

419 00:48:28.380 ⇒ 00:48:33.600 Uttam Kumaran: a lot of our system… a lot of our clients, we’ve come in fresh, where we’re the first people to write dbt.

420 00:48:33.610 ⇒ 00:48:34.950 Luke Scorziell: Which means, like.

421 00:48:35.190 ⇒ 00:48:37.789 Uttam Kumaran: There’s a lower chance of it going awry.

422 00:48:37.900 ⇒ 00:48:42.060 Uttam Kumaran: As we get into these larger enterprise clients with established situations.

423 00:48:42.230 ⇒ 00:48:47.259 Uttam Kumaran: They’re more than likely already have a setup, and it’s more than likely that nobody really

424 00:48:47.370 ⇒ 00:48:49.249 Uttam Kumaran: Cared, or, like, took care of it.

425 00:48:49.630 ⇒ 00:48:50.250 Uttam Kumaran: Because good.

426 00:48:50.250 ⇒ 00:48:50.770 Luke Scorziell: engineer.

427 00:48:51.260 ⇒ 00:48:54.219 Uttam Kumaran: It takes, like, a lot of mindfulness about, like.

428 00:48:54.690 ⇒ 00:48:59.350 Uttam Kumaran: The way you set things up and clean up. And so…

429 00:48:59.570 ⇒ 00:49:09.929 Uttam Kumaran: one of the things that we could do is, like, if we’re able to go into a sector, you know, there’s sort of two ways I think about on the sales side. One is…

430 00:49:10.440 ⇒ 00:49:15.650 Uttam Kumaran: We are dbt partners, so always there’s an opportunity for you to go

431 00:49:15.770 ⇒ 00:49:22.500 Uttam Kumaran: call DBT and say, like, hey, we’re thinking about going to the sector, do you guys already have existing clients here?

432 00:49:22.930 ⇒ 00:49:25.339 Uttam Kumaran: we’re running this dbt audit service.

433 00:49:25.530 ⇒ 00:49:27.059 Uttam Kumaran: Anyone come to mind?

434 00:49:27.260 ⇒ 00:49:29.060 Uttam Kumaran: Second is…

435 00:49:29.230 ⇒ 00:49:46.090 Uttam Kumaran: Oftentimes, people in big companies, when they’re hiring, will put dbt in the job descriptions of the talent they’re hiring. That’s another good way to find out if they have dbt in their system, is the data engineering and analytics engineering JDs have dbt as a requirement.

436 00:49:46.520 ⇒ 00:49:49.189 Uttam Kumaran: And the third is, like, many people, like.

437 00:49:49.420 ⇒ 00:49:57.410 Uttam Kumaran: like, they may not have it at all, you know? And so, it’s a way for us to also get in to say, like, you need this tool.

438 00:49:57.410 ⇒ 00:49:58.000 Luke Scorziell: Yeah.

439 00:49:58.000 ⇒ 00:50:06.969 Uttam Kumaran: You know, and so this audit service is something that, like, most likely, will be doing several types of,

440 00:50:08.060 ⇒ 00:50:11.370 Uttam Kumaran: Like, and I’ll even add you,

441 00:50:11.510 ⇒ 00:50:16.180 Uttam Kumaran: I’ll even forward you this, this, this message that I wrote,

442 00:50:16.530 ⇒ 00:50:22.449 Uttam Kumaran: But we were basically discussing this with the service leads. I sent in the go-to-market channel as, like.

443 00:50:22.980 ⇒ 00:50:35.859 Uttam Kumaran: these are, like, all of the services. We spent, like, an hour sort of thinking about what are all the services that we do that we haven’t really mapped out. So there’s a lot of other audits that we can do, you know, there’s a dbt audit, Snowflake audit, we could totally do something around.

444 00:50:36.410 ⇒ 00:50:39.530 Uttam Kumaran: BI slowness…

445 00:50:39.990 ⇒ 00:50:52.259 Uttam Kumaran: You know, so there’s a couple of other audits that we can do, in addition, you know, so yeah, I feel like I’m sort of interested in, like, hearing also from Yuka, how long does it take us to go from

446 00:50:52.500 ⇒ 00:51:02.290 Uttam Kumaran: a conversation like this into, like, okay, we have all the materials we need, or are we just gonna basically, like, pair it with campaigns in order to knock some of these out? Yeah, so…

447 00:51:02.940 ⇒ 00:51:06.790 Luke Scorziell: Yeah, I mean, also, Dave Mulatta, if you have to…

448 00:51:07.620 ⇒ 00:51:10.640 Luke Scorziell: An appointment in the morning, so… so…

449 00:51:10.780 ⇒ 00:51:14.290 Luke Scorziell: Feel free to hop if you need to. But.

450 00:51:14.290 ⇒ 00:51:18.820 Demilade Agboola: What’s on… sorry, just… just a heads up, I have a medical checkup tomorrow.

451 00:51:19.190 ⇒ 00:51:24.489 Demilade Agboola: So it’s basically 8am, 10 AM,

452 00:51:24.660 ⇒ 00:51:29.690 Demilade Agboola: like, I have a bunch of, like, tests, and then I have my consultancy at, like, 3PM, which would…

453 00:51:30.300 ⇒ 00:51:36.979 Demilade Agboola: overlap with, early… like, the early morning data service stand-up meeting, but I’ll drop my.

454 00:51:36.980 ⇒ 00:51:37.630 Uttam Kumaran: Okay.

455 00:51:37.630 ⇒ 00:51:45.810 Demilade Agboola: on the… like, the individual, like, see, I’ll drop my default and Magic Spoon updates prior to the meeting.

456 00:51:46.320 ⇒ 00:51:51.659 Uttam Kumaran: Okay, cool. Yeah, I’ll be on, later tonight, so I know if you need help on,

457 00:51:52.190 ⇒ 00:52:07.310 Uttam Kumaran: Magic Spoon audit stuff, let me know. I also sent Mary a message, just to catch up with her on, like, renewal stuff. So, as I, when she gets back to me, I’ll, and as we hop on the phone, I’ll loop you in, so…

458 00:52:08.130 ⇒ 00:52:09.580 Luke Scorziell: Okay, alright, sounds good.

459 00:52:09.910 ⇒ 00:52:11.220 Uttam Kumaran: Okay, alright, thank you, Luke.

460 00:52:12.210 ⇒ 00:52:18.479 Luke Scorziell: Yeah, so, I guess, Utam, going back to… For that, then, is…

461 00:52:18.740 ⇒ 00:52:20.599 Luke Scorziell: I mean, you can tell me what you think.

462 00:52:21.890 ⇒ 00:52:25.550 Luke Scorziell: Kind of my theory right now… Is that…

463 00:52:26.010 ⇒ 00:52:28.379 Luke Scorziell: It’s just kind of, like, map a service.

464 00:52:28.820 ⇒ 00:52:33.289 Luke Scorziell: out. I can show you, I mean, it’s pretty rudimentary.

465 00:52:33.450 ⇒ 00:52:37.540 Luke Scorziell: But, like, I’m trying to build my own little, like, hub in Notion.

466 00:52:39.990 ⇒ 00:52:44.269 Luke Scorziell: Maybe this will kind of explain it, but, like, kind of that, like, chart, I think, that I sent you.

467 00:52:44.760 ⇒ 00:52:50.670 Luke Scorziell: Last week of… Gtm…

468 00:52:51.710 ⇒ 00:52:56.379 Luke Scorziell: I mean, this is, like, this is super… They’re gonna exchange. But,

469 00:52:57.780 ⇒ 00:53:00.109 Luke Scorziell: Basically, like, it’s gonna launch a service.

470 00:53:00.300 ⇒ 00:53:04.269 Luke Scorziell: Can we attach, like, a couple ICP profiles to that service?

471 00:53:04.430 ⇒ 00:53:06.909 Luke Scorziell: So, like, the dbt audit maybe is, like.

472 00:53:07.070 ⇒ 00:53:09.439 Luke Scorziell: We have a new… it’s like a,

473 00:53:10.030 ⇒ 00:53:14.779 Luke Scorziell: data analytics, or CTO with data background, I don’t know.

474 00:53:15.250 ⇒ 00:53:17.180 Luke Scorziell: Whatever. And then we,

475 00:53:17.390 ⇒ 00:53:21.610 Luke Scorziell: That creates the name in this database, and then we kind of do, like, a content campaign.

476 00:53:21.950 ⇒ 00:53:26.379 Luke Scorziell: or content and sales campaign around that.

477 00:53:26.590 ⇒ 00:53:31.750 Luke Scorziell: So I guess, like, on your end, it’s… Like, if they’re…

478 00:53:32.010 ⇒ 00:53:36.160 Luke Scorziell: And I, I think that we could… Probably…

479 00:53:36.340 ⇒ 00:53:37.980 Luke Scorziell: Once we get good at it.

480 00:53:40.760 ⇒ 00:53:46.790 Luke Scorziell: do, like, two a… I don’t know if it makes sense to do two a week. I kind of imagine it, like, one…

481 00:53:47.090 ⇒ 00:53:50.790 Luke Scorziell: Launching every two weeks, and then each one has, like, a…

482 00:53:51.150 ⇒ 00:53:54.919 Luke Scorziell: Yeah, like, and then each service has, like, a 3-week runtime.

483 00:53:55.350 ⇒ 00:53:55.880 Luke Scorziell: And then.

484 00:53:55.880 ⇒ 00:54:00.490 Uttam Kumaran: I mean, there’s kind of a couple things. One is, like…

485 00:54:01.070 ⇒ 00:54:05.000 Uttam Kumaran: for… it’s sort of, like, interesting. I want to know, like, what does it take

486 00:54:05.390 ⇒ 00:54:15.740 Uttam Kumaran: what does every service need in terms of, like, a marketing or internal artifact, right? Like, I’m sure we need, like, who the internal, like, subject matter expert is.

487 00:54:15.810 ⇒ 00:54:18.080 Luke Scorziell: Examples, case studies…

488 00:54:18.080 ⇒ 00:54:21.489 Uttam Kumaran: probably, like, the copy, right? And then…

489 00:54:21.490 ⇒ 00:54:22.140 Luke Scorziell: Bitch.

490 00:54:22.140 ⇒ 00:54:29.839 Uttam Kumaran: it doesn’t necessarily… yeah, okay, perfect. Yeah, it doesn’t, like, it doesn’t necessarily need to,

491 00:54:32.440 ⇒ 00:54:35.160 Uttam Kumaran: what do you mean? Like, it doesn’t necessarily…

492 00:54:35.560 ⇒ 00:54:39.340 Uttam Kumaran: Need to be associated with a campaign for us to launch a service.

493 00:54:39.530 ⇒ 00:54:44.690 Uttam Kumaran: The reason I’m saying that is that many of our services, like, if we…

494 00:54:45.160 ⇒ 00:54:49.990 Uttam Kumaran: for example, I… what I listed on our page was, like, probably, like, 30 services.

495 00:54:50.900 ⇒ 00:54:51.710 Luke Scorziell: Yeah.

496 00:54:51.870 ⇒ 00:54:52.460 Luke Scorziell: Huh.

497 00:54:52.460 ⇒ 00:54:56.500 Uttam Kumaran: By the time we get 30, it’s gonna, I don’t know, 2 years from now, right?

498 00:54:56.500 ⇒ 00:54:57.510 Luke Scorziell: Yeah, that’s like, yeah.

499 00:54:57.510 ⇒ 00:55:06.830 Uttam Kumaran: More of what I’m saying is, like, we may also, in parallel, just need to continue to streamline, like, getting some of these services, like, documented.

500 00:55:07.160 ⇒ 00:55:09.289 Uttam Kumaran: And out onto the website.

501 00:55:09.550 ⇒ 00:55:12.590 Uttam Kumaran: And the website is really, I think, the last…

502 00:55:13.130 ⇒ 00:55:15.370 Luke Scorziell: Like, where they need to end up.

503 00:55:15.820 ⇒ 00:55:21.050 Uttam Kumaran: And then, for some of them, yes, you may associate them with a campaign, but…

504 00:55:21.410 ⇒ 00:55:22.520 Uttam Kumaran: If that may not always.

505 00:55:22.520 ⇒ 00:55:23.410 Luke Scorziell: Not all.

506 00:55:24.650 ⇒ 00:55:26.840 Luke Scorziell: Yeah, yeah, okay.

507 00:55:26.980 ⇒ 00:55:30.600 Luke Scorziell: Yeah, no, no, no, I mean, that makes sense. I think, like, a landing page…

508 00:55:30.740 ⇒ 00:55:33.520 Luke Scorziell: Because if it’s, like, we literally just want to sprint.

509 00:55:33.770 ⇒ 00:55:36.859 Luke Scorziell: Over the next, like, 3 months, or this quarter, to, like.

510 00:55:37.040 ⇒ 00:55:41.200 Luke Scorziell: Basically see, like, can we get all of these services on the website?

511 00:55:41.460 ⇒ 00:55:43.490 Luke Scorziell: That’s like a, you know, I think…

512 00:55:44.010 ⇒ 00:55:48.050 Luke Scorziell: Well, I don’t want to speak too soon, but I feel like some amount of that is achievable.

513 00:55:48.180 ⇒ 00:55:54.830 Luke Scorziell: depending on, like, you know, I think if I can formulate, like… like, I don’t know where I even found this, but it was just a template.

514 00:55:54.960 ⇒ 00:55:55.920 Luke Scorziell: I’ve, like.

515 00:55:56.270 ⇒ 00:56:00.319 Luke Scorziell: the different things that you might need for a service, so I was just, like, going through this.

516 00:56:00.490 ⇒ 00:56:07.220 Luke Scorziell: Figuring it would be, like, Good enough. And so…

517 00:56:07.720 ⇒ 00:56:12.179 Luke Scorziell: So if it’s just that, and it’s like, we have a case study on the website.

518 00:56:12.620 ⇒ 00:56:16.660 Luke Scorziell: a… like, internal… internally, I guess we would need…

519 00:56:16.800 ⇒ 00:56:27.589 Luke Scorziell: With SOWs, are we… do we need… is that, like, custom for every client, or do we kind of have, like, a standard S… or would we want to have, like, a standard SOW per service that then we can kind of customize?

520 00:56:28.140 ⇒ 00:56:38.100 Uttam Kumaran: It’s cus- it’s, well, we have a standard SOW template, and then we sort of list the services that we’re gonna do as part of that scope, and, like, what the deliverables are.

521 00:56:39.320 ⇒ 00:56:46.570 Luke Scorziell: Okay. But that… and that’s something that the delivery team more so does, or is that… I’m still getting familiar with that.

522 00:56:46.730 ⇒ 00:56:50.669 Uttam Kumaran: Yeah, whoever’s… whoever’s writing the SOW, so…

523 00:56:50.880 ⇒ 00:56:54.839 Uttam Kumaran: At this moment, anyone on the delivery team can write an SOW.

524 00:56:56.180 ⇒ 00:56:56.820 Luke Scorziell: Got it.

525 00:56:57.210 ⇒ 00:57:07.550 Uttam Kumaran: Because we’re… we… instead of having it… all of it go through sales, and again, sales right now is just me and Robert, we made it open so anybody can go sell work.

526 00:57:08.010 ⇒ 00:57:08.800 Uttam Kumaran: Right.

527 00:57:09.090 ⇒ 00:57:18.269 Uttam Kumaran: And so what me and Clarence are doing is training everybody how to write SOWs, but again, it’s less important for, like.

528 00:57:18.420 ⇒ 00:57:21.769 Uttam Kumaran: It’s less important for selling additional clients.

529 00:57:21.970 ⇒ 00:57:28.469 Uttam Kumaran: it’s more important for net new clients. Like, a lot of people go to our site, and they still don’t know the breadth of things that we can accomplish.

530 00:57:29.920 ⇒ 00:57:33.370 Luke Scorziell: Yeah, okay, so this is… I mean… Yeah.

531 00:57:33.370 ⇒ 00:57:37.309 Uttam Kumaran: So, I would… in my mind, that is a number one problem, because

532 00:57:37.730 ⇒ 00:57:43.050 Uttam Kumaran: Going into an existing client and writing the SOW is not that hard.

533 00:57:43.990 ⇒ 00:57:44.540 Luke Scorziell: Damn.

534 00:57:44.540 ⇒ 00:57:50.609 Uttam Kumaran: It’s actually, like, the fact that many people are probably coming to our site and don’t know what we do.

535 00:57:50.720 ⇒ 00:57:54.339 Uttam Kumaran: I don’t know the breadth of things that we do, like, we don’t have a landing page.

536 00:57:54.570 ⇒ 00:58:01.009 Uttam Kumaran: for every service, you know? We don’t have, like, the website is not set up in a way

537 00:58:01.340 ⇒ 00:58:06.009 Uttam Kumaran: to do that, and, like, it’s something that Ann and Hannah and I started on, but…

538 00:58:06.340 ⇒ 00:58:09.750 Uttam Kumaran: We just got… I just got busy, I couldn’t carry it through.

539 00:58:11.240 ⇒ 00:58:21.020 Luke Scorziell: Yeah, well, I think, I mean, I’ve kind of been assuming that this… or just, yeah, assuming this responsibility of doing it, which, like, I think is great.

540 00:58:21.480 ⇒ 00:58:26.469 Luke Scorziell: to… to get them out. So then… well then, I mean, I can then shift my focus

541 00:58:27.380 ⇒ 00:58:37.410 Luke Scorziell: Yeah, I think I’m trying to balance, like… Real… or just… I don’t know.

542 00:58:37.410 ⇒ 00:58:44.939 Uttam Kumaran: So this is where, like, you’re gonna have… this is where… and I’m telling this to a lot of people at Brainforge, is sort of what I told you. There’s a lot of work to get done.

543 00:58:45.120 ⇒ 00:58:58.680 Uttam Kumaran: So, your job is to say no to things. But if you’re having trouble with that, then Robert and I will help you prioritize. But you’re… what you’re gonna find is that you’re not going to be able to say yes to everything.

544 00:58:58.910 ⇒ 00:59:09.729 Uttam Kumaran: And so what I’m not looking for is a yes, it’s like, okay, cool, I’ve heard that that’s a problem, we’re not going to be able to get it until Q2. Okay, that’s fine.

545 00:59:10.190 ⇒ 00:59:10.680 Uttam Kumaran: It’s like.

546 00:59:10.680 ⇒ 00:59:11.510 Luke Scorziell: Yeah, okay.

547 00:59:11.510 ⇒ 00:59:21.610 Uttam Kumaran: I can only ask you to do it, because I’m not… I can’t do it, right? And so, for me, I’m… what I can tell you is, like, what all the problems are, how we’ve solved it, how we tried to solve it before.

548 00:59:22.050 ⇒ 00:59:27.049 Uttam Kumaran: And then to continue to tell you, like, look, the fact that people go to the website, don’t know what we do.

549 00:59:27.200 ⇒ 00:59:29.270 Uttam Kumaran: That’s kind of an issue.

550 00:59:29.390 ⇒ 00:59:30.100 Uttam Kumaran: But…

551 00:59:30.100 ⇒ 00:59:30.750 Luke Scorziell: Yeah.

552 00:59:30.750 ⇒ 00:59:40.260 Uttam Kumaran: That being said, what do we have the capability of doing? It’s like, maybe we don’t have the capability of doing non-campaign associated services. Okay.

553 00:59:40.700 ⇒ 00:59:41.370 Uttam Kumaran: like…

554 00:59:41.370 ⇒ 00:59:41.730 Luke Scorziell: Yeah.

555 00:59:41.730 ⇒ 00:59:46.420 Uttam Kumaran: But you have to deliver that, like, I don’t know. I don’t know what we have.

556 00:59:46.660 ⇒ 00:59:49.110 Uttam Kumaran: The capacity for, and so…

557 00:59:50.040 ⇒ 00:59:51.319 Luke Scorziell: Yeah, I mean, I can’t stop.

558 00:59:51.320 ⇒ 01:00:10.860 Uttam Kumaran: stop asking, I’m gonna keep asking, but I… that’s what I’m sort of expecting from… and this is something I think that me, you, Robert, Sheshu, and Clarence will meet, you know, more often, and… and this is what ultimately, like, for us, we’re gonna keep putting pressure, but we’re not looking for a…

559 01:00:11.320 ⇒ 01:00:16.339 Uttam Kumaran: take everything on, and then, therefore, everything kind of gets done half-baked. It’s like.

560 01:00:16.610 ⇒ 01:00:18.270 Uttam Kumaran: For you guys to be like.

561 01:00:18.390 ⇒ 01:00:24.120 Uttam Kumaran: Okay, no, we already have agreed upon priorities, like, this can’t get added to a priority, or something has to get knocked off.

562 01:00:24.320 ⇒ 01:00:34.099 Uttam Kumaran: Because that’s where I don’t know exactly what you and Robert have as priorities, so I’m just gonna… I’m just sort of, like, continuing to roll with the punches and looping you in where it’s, like.

563 01:00:34.320 ⇒ 01:00:38.959 Uttam Kumaran: Seems like it’s interesting, and, like, you can see it, a new part of the business.

564 01:00:39.080 ⇒ 01:00:40.010 Uttam Kumaran: But totally…

565 01:00:40.010 ⇒ 01:00:40.800 Luke Scorziell: Yeah, bro.

566 01:00:40.940 ⇒ 01:00:42.480 Uttam Kumaran: Like, what you’re… yeah.

567 01:00:42.480 ⇒ 01:00:54.019 Luke Scorziell: No, that makes sense. I think that’s helpful to know. I think probably just being able to say no to things is a good skill for me to learn more of. Because I think, like, in part, it’s like, the more I learn about the business, the more ideas I’m getting.

568 01:00:54.580 ⇒ 01:00:56.629 Uttam Kumaran: Yeah, there’s a lot to do here.

569 01:00:56.630 ⇒ 01:00:57.340 Luke Scorziell: helpful.

570 01:00:57.680 ⇒ 01:01:05.700 Uttam Kumaran: There’s a lot to do here, and then it’s up to you to be like, okay, there’s two options. Either we need more capacity, which is, like.

571 01:01:05.980 ⇒ 01:01:08.680 Uttam Kumaran: the budget’s kind of already set. So then.

572 01:01:08.680 ⇒ 01:01:09.040 Luke Scorziell: Yeah.

573 01:01:09.040 ⇒ 01:01:19.750 Uttam Kumaran: It’s like, how can I either leverage existing resources, right? Like, for example, you go into Demolade is using, like, an existing resource. Additionally, though, if you’re, like, need…

574 01:01:19.750 ⇒ 01:01:30.309 Uttam Kumaran: For us to get… for us to get these service landing pages out, I need an AI way to… for me to rip landing pages. I can’t wait for Hannah and design. Okay, like, I can go think about that for you, you know?

575 01:01:31.040 ⇒ 01:01:37.259 Luke Scorziell: Yeah, well, it’s interesting, because I think right now, and this is just me processing the things that are going on,

576 01:01:37.580 ⇒ 01:01:40.780 Luke Scorziell: Current is, like, content kind of feels…

577 01:01:40.910 ⇒ 01:01:43.070 Luke Scorziell: It feels like it’s sort of…

578 01:01:43.480 ⇒ 01:01:48.979 Luke Scorziell: like, that’s the area that I’m like, I think we really just need… like, if I could just have a plan for the next…

579 01:01:49.150 ⇒ 01:01:49.890 Luke Scorziell: 3 months.

580 01:01:49.890 ⇒ 01:01:53.579 Uttam Kumaran: I agree, like, if you were an out…

581 01:01:53.580 ⇒ 01:02:04.880 Luke Scorziell: I don’t have to think about it again for, like, until a month, when then we make the next plan. And then it’s like… and then basically I just get outlines to Ryan, Ryan runs.

582 01:02:04.880 ⇒ 01:02:05.359 Uttam Kumaran: I’m not sure.

583 01:02:05.360 ⇒ 01:02:12.249 Luke Scorziell: GPT thing, and then I can… so that’s, to me, I think, like, still been priority number one. I’m just trying to figure out

584 01:02:12.870 ⇒ 01:02:23.840 Luke Scorziell: what it is that we want to be saying with our content, and that’s where I’m, like, we have the partners, we have the services, we have the thought leadership, we have, like, events.

585 01:02:23.930 ⇒ 01:02:27.530 Uttam Kumaran: Okay, so it’s all in service of that content goal.

586 01:02:28.950 ⇒ 01:02:32.510 Luke Scorziell: Yes, yeah, where it’s like, Do we…

587 01:02:32.670 ⇒ 01:02:34.539 Uttam Kumaran: Wanna just talk about, like.

588 01:02:34.550 ⇒ 01:02:46.280 Luke Scorziell: one service a week, or, like, one service for 3 weeks, then switch to another service for another 3 weeks. Then, as we’re kind of doing campaigns around that, and then simultaneously, or next quarter, we can build them into the website.

589 01:02:46.400 ⇒ 01:02:49.249 Luke Scorziell: Or do we, you know, and then it’s like.

590 01:02:49.720 ⇒ 01:02:55.220 Luke Scorziell: So I think that’s kind of the primary place that I… Want more of a system.

591 01:02:55.520 ⇒ 01:02:58.989 Luke Scorziell: 4, and that… I don’t know, I’m thinking, like.

592 01:02:59.670 ⇒ 01:03:03.729 Luke Scorziell: Because I could ask Maya if she’s interested in doing a, like, quick project.

593 01:03:03.810 ⇒ 01:03:15.370 Luke Scorziell: Because that’s, like, her specialty, is making the content calendars and pillars, which I know that… I think, yeah, so either I need to say no to more things, and clear stuff off my plate, and just focus on that, or…

594 01:03:15.430 ⇒ 01:03:24.879 Luke Scorziell: potentially bring in… see if, like, I could get a one-off project of just, like… Well, there’s, like, two ways, right? So, like, put yourself… put yourself in our spot, like…

595 01:03:25.010 ⇒ 01:03:29.610 Uttam Kumaran: For me, the one thing the company can’t have me stop doing is, like, pushing.

596 01:03:29.840 ⇒ 01:03:37.829 Uttam Kumaran: But, I’m not pushing, like, sort of, like, the way typical people push. I’m pushing strategically, like.

597 01:03:38.170 ⇒ 01:03:43.779 Uttam Kumaran: I’m like, okay, we’re doing these services, is there a way to get a two-for-one special here? Like…

598 01:03:43.920 ⇒ 01:03:45.569 Uttam Kumaran: Can we think about…

599 01:03:46.010 ⇒ 01:04:03.960 Uttam Kumaran: I went through yesterday, and I was like, hey guys, let’s, like, think about other services, because I know Luke’s thinking about services, and maybe I’ll give him a list and, like, see if that’s helpful. For you, the way to be, like, is, like, okay, I heard that we need… right now, we have a problem where, like, people come to the… come to our website, they don’t know the breadth of what we do.

600 01:04:04.160 ⇒ 01:04:11.289 Uttam Kumaran: Kind of being like, what is that worth to us to solve? And how does that fit among all the other things that

601 01:04:11.650 ⇒ 01:04:20.239 Uttam Kumaran: you and your team have been asked to solve, then it’s easy to go back to, like, me or Robert, be like, yo, is this top of the list, or is this middle, or bottom?

602 01:04:20.340 ⇒ 01:04:34.130 Uttam Kumaran: And then we make a decision, and you can expect us to help make that… 100%, both of us can make those decisions. What’s hard for me is that, like, in that moment when I see you going around the company doing services.

603 01:04:34.280 ⇒ 01:04:41.370 Uttam Kumaran: I’m like, okay, let me… I’m gonna be in front of a couple, like, important people, let me extract every service that we do.

604 01:04:41.700 ⇒ 01:04:47.030 Uttam Kumaran: And, like, I’m like, okay, and then I’m like, next time I talk to Luke, I’ll just mention that, like.

605 01:04:47.620 ⇒ 01:04:48.000 Luke Scorziell: So…

606 01:04:48.000 ⇒ 01:04:49.749 Uttam Kumaran: We have all these other services.

607 01:04:49.870 ⇒ 01:04:53.800 Uttam Kumaran: I’ll see, like, how you’re doing and doing what you’re doing, and then be like.

608 01:04:53.980 ⇒ 01:05:06.619 Uttam Kumaran: consider it if it’s on your list, then consider it put on your list, or if it’s not, that’s also fine. But alternatively, you could be like, look, what’s it worth? And then, it’s sort of like, okay, we can either solve it by A, like, adding bandwidth.

609 01:05:06.770 ⇒ 01:05:15.799 Uttam Kumaran: or B, finding internal bandwidth, or C, like, leveraging AI, right? And so… Those are, like, cheaper.

610 01:05:15.940 ⇒ 01:05:19.120 Uttam Kumaran: The first one is, like, the most expensive.

611 01:05:19.120 ⇒ 01:05:19.680 Luke Scorziell: Yeah.

612 01:05:19.810 ⇒ 01:05:28.919 Uttam Kumaran: going to the market, getting fucked people. However, the other thing is, dude, is, like, the more priorities you take on at a single moment, the higher risk that you mess one up.

613 01:05:29.050 ⇒ 01:05:31.709 Uttam Kumaran: And so, we do have a lot… we have…

614 01:05:31.890 ⇒ 01:05:41.230 Uttam Kumaran: if you think of, like, the sales team and the capacity as, like, a pipe, right? There’s only certain… a certain amount of water you can handle at a certain amount of speed.

615 01:05:41.380 ⇒ 01:05:49.960 Uttam Kumaran: Right? Meaning, like, we’re already kind of moving pretty fast, and if I’m like, cool, like, add another workstream, add another workstream, and also push that fast.

616 01:05:50.160 ⇒ 01:05:57.250 Uttam Kumaran: you may not… it may just blow everything up. So you kind of got to be aware of, like, okay, can we… maybe we can only handle, like.

617 01:05:57.420 ⇒ 01:05:59.869 Uttam Kumaran: Three core objectives per week.

618 01:06:00.150 ⇒ 01:06:13.490 Uttam Kumaran: And our job is to nail those, and then in order to do 4 or 5, I need another person, or we need someone to own partnerships. That’s a great way to sort of, like, position the opportunity.

619 01:06:13.640 ⇒ 01:06:14.240 Uttam Kumaran: See what I mean?

620 01:06:14.240 ⇒ 01:06:14.900 Luke Scorziell: Yeah.

621 01:06:15.230 ⇒ 01:06:17.970 Luke Scorziell: Yeah. Okay, no, this is super helpful.

622 01:06:17.970 ⇒ 01:06:30.989 Uttam Kumaran: That’s how we think about it on the engineering side. Like, I think about it, like, my team has a basket of hours, but we can’t split those hours, like, a hundred ways, because then I’m spending 15 minutes on 30 things.

623 01:06:31.140 ⇒ 01:06:35.180 Uttam Kumaran: So, we can only naturally do, like, 3 or 4 things at a time. I tell this to clients.

624 01:06:35.410 ⇒ 01:06:46.510 Uttam Kumaran: even if you increase our budget, it’s not like we’re gonna start doing 9 things in parallel. I’m just gonna do 4 things faster. But, like, we do have a natural limit on the context switching.

625 01:06:46.510 ⇒ 01:06:47.860 Luke Scorziell: You know, and… Yeah.

626 01:06:47.860 ⇒ 01:07:02.350 Uttam Kumaran: I really want to make sure that, like, you don’t get into the trap that I’m in, where I have to contact switch, like, an extreme amount. It’s very, very taxing, and it’s… and it’s not a good way to work. And so most of our teams, I feel like.

627 01:07:02.670 ⇒ 01:07:11.190 Uttam Kumaran: 3 to 5 priorities at a time is, like, healthy. You know, some are gonna be high prio, urgent, some are gonna be low, and then there’s gonna be ad hoc.

628 01:07:11.640 ⇒ 01:07:15.780 Uttam Kumaran: And just kind of thinking about things that way, of, like, your team’s bandwidth.

629 01:07:16.100 ⇒ 01:07:16.799 Luke Scorziell: Should I take it back?

630 01:07:17.200 ⇒ 01:07:17.830 Uttam Kumaran: We’ll help you, like.

631 01:07:17.830 ⇒ 01:07:18.200 Luke Scorziell: Yeah.

632 01:07:18.200 ⇒ 01:07:19.680 Uttam Kumaran: shiny object syndromes.

633 01:07:20.430 ⇒ 01:07:24.789 Luke Scorziell: Yeah, yeah, I mean, I know the part, it’s like, literally, it’s…

634 01:07:24.920 ⇒ 01:07:31.719 Luke Scorziell: the content, getting content to Ryan, and then starting campaigns around the ICPs that we have. Like, those are pretty much…

635 01:07:32.100 ⇒ 01:07:37.420 Luke Scorziell: Like, really the priorities, honestly, and then a lot of the other stuff is more just, like.

636 01:07:38.230 ⇒ 01:07:39.400 Uttam Kumaran: Nobody’s down right now.

637 01:07:39.600 ⇒ 01:07:40.330 Luke Scorziell: I’m learning.

638 01:07:40.330 ⇒ 01:07:54.329 Uttam Kumaran: note it down, because that… because again, you’re going to hear these over and over. Another way that typical product teams do prioritization is they literally do by frequency. Like, how many times has a customer complained about this issue?

639 01:07:54.450 ⇒ 01:08:01.910 Uttam Kumaran: And how big are those? How important are those customers? And then they basically arrive at their backlog prioritization. See what I mean?

640 01:08:02.140 ⇒ 01:08:08.170 Uttam Kumaran: And so what’s, what’s one way? Well, again, all my lens on prioritization is going to be from engineering, because…

641 01:08:08.400 ⇒ 01:08:16.769 Uttam Kumaran: I feel like we do a good job at, like, dealing with these kind of things, but you always want to note it down, right? The worst thing you could do to a client is be, like.

642 01:08:17.670 ⇒ 01:08:22.640 Uttam Kumaran: Oh, yeah, like, I heard you say it 3 months ago, can we go back through this? Instead, you’re like, look, I heard you.

643 01:08:23.229 ⇒ 01:08:25.439 Uttam Kumaran: Let me, let me look back at the roadmap.

644 01:08:25.629 ⇒ 01:08:32.429 Uttam Kumaran: If we can do it, we’ll do it. If not, we can’t. And then it’s like, hey, look, here’s the 5 more important items in front of this.

645 01:08:33.039 ⇒ 01:08:46.619 Uttam Kumaran: And I’m gonna be like, oh yeah, that would be sick if we get those done, actually, like, just keep going on those, right? Like, for example, you told me, like, our number one objective is just to make sure we get content out reliably. That is more important than getting the services on a page.

646 01:08:47.290 ⇒ 01:08:47.899 Luke Scorziell: Yeah.

647 01:08:48.229 ⇒ 01:08:57.919 Uttam Kumaran: Like, I can very squarely say that. There are some things that may be, like, a little bit tighter, like, closer, but for me, that’s more important, because people are buying from me and Robert, and they’re looking us up.

648 01:08:58.319 ⇒ 01:09:00.819 Uttam Kumaran: And then they’re looking at the website to kind of check a box.

649 01:09:01.179 ⇒ 01:09:10.379 Uttam Kumaran: As AEO, SEO, backlinks get more important, some people are going to go to the website first, right? And then we’re going to want to make sure that’s, like, in a good spot, so…

650 01:09:11.380 ⇒ 01:09:15.149 Luke Scorziell: Yeah, okay, so, I mean, I think, like, I mean, I could just…

651 01:09:16.170 ⇒ 01:09:19.460 Luke Scorziell: It’s… yeah, I’m literally even just writing it down right now, it’s like…

652 01:09:19.859 ⇒ 01:09:22.940 Luke Scorziell: Content strategy and getting content out every week.

653 01:09:23.279 ⇒ 01:09:25.979 Luke Scorziell: Like, campaigns going out every week.

654 01:09:26.149 ⇒ 01:09:35.480 Luke Scorziell: hopefully 2 to 3, and then me getting on 2 or 3 sales calls a week. I think, like, for me, it’s like, if I think of, like, what are the highest leverage things.

655 01:09:35.630 ⇒ 01:09:36.880 Luke Scorziell: That’s probably it.

656 01:09:37.029 ⇒ 01:09:39.269 Luke Scorziell: in my mind, and then I feel like…

657 01:09:40.130 ⇒ 01:09:51.489 Uttam Kumaran: And every week, every week, you… if you have new priorities, you should get… you should pressure Robert into telling you that those are the priorities, and then when new priorities come up.

658 01:09:51.700 ⇒ 01:10:01.729 Uttam Kumaran: you will often find that it’s from me or Robert, it’s from people, like, who you’re directly supporting. You gotta tell them to qualify it across your other priorities.

659 01:10:01.730 ⇒ 01:10:02.190 Luke Scorziell: Yeah.

660 01:10:02.190 ⇒ 01:10:13.069 Uttam Kumaran: Even for our… for our clients, I do this, where I’m like, hey, you just told me something the other day, now you’re telling me this. What do you want me to do? The worst thing I can do is say yes to both, and F up both.

661 01:10:13.430 ⇒ 01:10:22.480 Uttam Kumaran: Right? So I hold them to task, and so this is where, on the weekly calls, you can say, hey, we had XYZ new requests come up. It doesn’t seem like I can do that.

662 01:10:22.730 ⇒ 01:10:28.529 Uttam Kumaran: Do you think, like, we should adjust priorities, or should I just say, like, that’s next quarter?

663 01:10:29.400 ⇒ 01:10:29.940 Uttam Kumaran: I met.

664 01:10:29.940 ⇒ 01:10:30.660 Luke Scorziell: act.

665 01:10:30.660 ⇒ 01:10:40.200 Uttam Kumaran: you’ll… either way, you’ll get a… you’re gonna get… you’re gonna get an answer, you know? That’s a good way of, like, doing that, and then also, naturally, over the quarter, you build up your roadmap for next quarter.

666 01:10:41.260 ⇒ 01:10:41.940 Luke Scorziell: Yeah.

667 01:10:42.230 ⇒ 01:10:53.810 Uttam Kumaran: You know, so it’s this sort of constant, like, throwing things in the backlog, prioritizing. There will be some things that are urgent, like, that we can’t avoid, that we will have to just, like, figure out how to… how to manage it.

668 01:10:54.650 ⇒ 01:10:55.220 Luke Scorziell: Yeah.

669 01:10:55.220 ⇒ 01:11:03.179 Uttam Kumaran: And we will, right? If we need to bring in someone, if we need to pull in other resources, or just ball up, we will, but we can’t do that for everything.

670 01:11:04.380 ⇒ 01:11:06.410 Luke Scorziell: Yeah, yeah, no, for sure.

671 01:11:07.190 ⇒ 01:11:14.310 Luke Scorziell: Which reminds me of the Atlassian, Atlassian guy? Sorry. Yeah, yeah, yeah.

672 01:11:14.810 ⇒ 01:11:17.540 Luke Scorziell: He…

673 01:11:17.540 ⇒ 01:11:19.329 Uttam Kumaran: Send him what we were, like…

674 01:11:20.300 ⇒ 01:11:22.699 Luke Scorziell: Thinking for Vixel? Is that fine?

675 01:11:23.310 ⇒ 01:11:25.410 Luke Scorziell: Or are you think… were you thanking someone else?

676 01:11:25.410 ⇒ 01:11:26.769 Uttam Kumaran: Well, like, what did he.

677 01:11:26.770 ⇒ 01:11:30.789 Luke Scorziell: Or I guess we were talking about more, like, our… or he wanted client-facing…

678 01:11:31.150 ⇒ 01:11:36.629 Luke Scorziell: more, like, client-facing tools that we’ve done with AI agents, so I thought.

679 01:11:36.630 ⇒ 01:11:39.290 Uttam Kumaran: Oh yeah, he’s gonna want the ABC thing.

680 01:11:40.660 ⇒ 01:11:42.010 Luke Scorziell: Yeah, I mean, I think…

681 01:11:46.040 ⇒ 01:11:50.869 Uttam Kumaran: I think we should just, yeah, we should just demonstrate… the ABC thing.

682 01:11:51.710 ⇒ 01:11:55.830 Luke Scorziell: Okay. Do we need to put… and that’s… that’s, like, Thursday, right, you said?

683 01:11:56.860 ⇒ 01:11:57.330 Uttam Kumaran: What’s on?

684 01:11:57.330 ⇒ 01:11:58.030 Luke Scorziell: Thursday night.

685 01:11:58.030 ⇒ 01:12:02.669 Uttam Kumaran: This Thursday! Oh, is it this Thursday? Oh, Jesus Christ, really?

686 01:12:03.160 ⇒ 01:12:04.800 Luke Scorziell: Yeah.

687 01:12:12.600 ⇒ 01:12:14.039 Uttam Kumaran: I mean, what do you think?

688 01:12:16.570 ⇒ 01:12:18.369 Uttam Kumaran: Up to you, like, we also don’t.

689 01:12:18.370 ⇒ 01:12:18.830 Luke Scorziell: I got you.

690 01:12:19.230 ⇒ 01:12:19.989 Uttam Kumaran: If it’s, like.

691 01:12:19.990 ⇒ 01:12:20.510 Luke Scorziell: Yay.

692 01:12:20.510 ⇒ 01:12:28.360 Uttam Kumaran: This is where, like… You may… you just got… you could be like, actually, It’s tight, like…

693 01:12:30.460 ⇒ 01:12:35.570 Luke Scorziell: Well, what… I mean, can you… what do they even… like, they’re… they’re having a bunch of enterprise customers get together, and like…

694 01:12:35.570 ⇒ 01:12:39.980 Uttam Kumaran: No, I think they’re presenting to… like, engineering folks.

695 01:12:41.810 ⇒ 01:12:43.819 Luke Scorziell: Oh. I just thought…

696 01:12:43.820 ⇒ 01:12:51.519 Uttam Kumaran: He connected with a friend of mine that’s like, hey, do you have anyone that could present something in Austin? Probably an AI friend of mine mentioned us.

697 01:12:56.790 ⇒ 01:13:00.120 Luke Scorziell: I mean, do you feel like it’s within your capacity to, like, go and…

698 01:13:00.770 ⇒ 01:13:07.020 Uttam Kumaran: Definitely, I mean, that’s just, like, I could do it, but if it’s not valuable to you, then I don’t want to do it.

699 01:13:08.140 ⇒ 01:13:17.859 Luke Scorziell: Yeah, I don’t feel… I mean, I guess if we put something together on ABC, like… but we already have the case studies, and, like, I don’t think it’s, like… I’m not, like, dying for content from that.

700 01:13:20.440 ⇒ 01:13:23.670 Uttam Kumaran: Okay, let’s just say it’s, like, too tight, sorry, like, that’s fine.

701 01:13:23.670 ⇒ 01:13:24.540 Luke Scorziell: Yeah.

702 01:13:24.690 ⇒ 01:13:25.330 Luke Scorziell: Okay.

703 01:13:25.330 ⇒ 01:13:29.169 Uttam Kumaran: That’s okay, like, I’m totally fine. If you want me to say that, I can say that.

704 01:13:29.240 ⇒ 01:13:31.079 Luke Scorziell: But, like… I can also message Joe.

705 01:13:31.120 ⇒ 01:13:37.650 Uttam Kumaran: I think we’re just gonna have to be, like, really ruthlessly, prioritization… prioritizing.

706 01:13:39.050 ⇒ 01:13:42.039 Luke Scorziell: Yeah, no, I agree. So…

707 01:13:42.770 ⇒ 01:13:45.730 Luke Scorziell: Okay, this is… yeah, this is super helpful.

708 01:13:46.700 ⇒ 01:13:49.529 Uttam Kumaran: If this is just gonna be the story of our life.

709 01:13:49.530 ⇒ 01:13:50.670 Luke Scorziell: Yeah, haha.

710 01:13:50.840 ⇒ 01:13:55.879 Uttam Kumaran: You know, I’m telling you, there’s a lot… like, being at those companies, like, there’s a lot of trash on the ground.

711 01:13:56.030 ⇒ 01:14:01.420 Uttam Kumaran: And, like, it’s really hard to pick everything up, so you have to be very, very cautious.

712 01:14:01.790 ⇒ 01:14:08.130 Uttam Kumaran: It’s so weird, because, like, you know, I’m both saying that, and I’m actively, like, throwing trash at your feet. But…

713 01:14:08.130 ⇒ 01:14:09.630 Luke Scorziell: I mean, that’s fine.

714 01:14:09.880 ⇒ 01:14:16.420 Uttam Kumaran: That’s what I want. I want you to, I just want you to be aware, like, of that, like…

715 01:14:16.670 ⇒ 01:14:20.120 Uttam Kumaran: Worst thing you can do is, like, expect that we… that…

716 01:14:20.270 ⇒ 01:14:23.680 Uttam Kumaran: I think that we expect you to just say yes to everything, that’s totally not the case.

717 01:14:24.430 ⇒ 01:14:27.850 Luke Scorziell: Yeah, okay, no, that’s good to be empowered with that.

718 01:14:28.040 ⇒ 01:14:30.800 Luke Scorziell: I think my default is, like, I’ll just figure it out how to do it.

719 01:14:30.960 ⇒ 01:14:36.190 Uttam Kumaran: Yeah, yeah. I would rather you crush it, and then we win, and we take fewer bets.

720 01:14:36.750 ⇒ 01:14:44.620 Luke Scorziell: Yeah, okay, yeah, I mean, I think… I think content, for sure. I mean, even just seeing the numbers from last week is, like, a huge bet. And, I mean, that’s kind of what we’re…

721 01:14:44.730 ⇒ 01:14:46.670 Luke Scorziell: Hoping to do, straight away, so…

722 01:14:46.850 ⇒ 01:14:50.330 Luke Scorziell: I’ll just… yeah, honestly, I should just use AI to come up with a…

723 01:14:50.850 ⇒ 01:14:54.360 Luke Scorziell: A plan, and just have, like, 30 days of play for the next few months.

724 01:14:55.520 ⇒ 01:14:56.230 Uttam Kumaran: Okay.

725 01:14:56.230 ⇒ 01:14:58.670 Luke Scorziell: So, that’s… yeah, I don’t think it’s that deep.

726 01:15:00.920 ⇒ 01:15:09.199 Luke Scorziell: And… yeah, okay. Well, I’ll text Andrew, I mean, yeah, I think probably better to tell him now than just.

727 01:15:09.200 ⇒ 01:15:10.210 Uttam Kumaran: Yeah, yeah, yeah, yeah.

728 01:15:10.210 ⇒ 01:15:13.600 Luke Scorziell: like… get to Thursday and dip. But…

729 01:15:13.960 ⇒ 01:15:20.960 Luke Scorziell: I think the Vixel presentation is interesting, and especially if that can get us clients, and then it kind of forces us to, like, think about or go to market.

730 01:15:21.100 ⇒ 01:15:24.829 Luke Scorziell: function more. If there’s… yeah, if there was something that you were like.

731 01:15:24.830 ⇒ 01:15:31.019 Uttam Kumaran: Well, also, dude, you can take my Vixel presentation and chop it up, like, I’ll try to record it locally, too.

732 01:15:31.260 ⇒ 01:15:32.859 Uttam Kumaran: You can chop that up.

733 01:15:33.320 ⇒ 01:15:38.270 Uttam Kumaran: for content, and like, you know, there’s a lot from that. I think that’ll be more applicable.

734 01:15:39.010 ⇒ 01:15:41.409 Luke Scorziell: Okay. Yeah, and I think,

735 01:15:42.100 ⇒ 01:15:49.019 Luke Scorziell: Like, as soon as the… in my mind, again, it’s like, when the content engine is running, then it’s kind of, okay, how do we start thinking about

736 01:15:49.490 ⇒ 01:15:53.689 Luke Scorziell: Like, improving the content and doing better, like, more…

737 01:15:54.100 ⇒ 01:15:58.289 Luke Scorziell: like, partnership content or video content, but for now, I’d just like to get, like.

738 01:15:58.960 ⇒ 01:16:01.929 Luke Scorziell: Like, just written and design posts done.

739 01:16:02.180 ⇒ 01:16:06.229 Luke Scorziell: So… But yeah, okay.

740 01:16:06.780 ⇒ 01:16:10.729 Luke Scorziell: Well, good to catch up. Thanks for joining on the call, too.

741 01:16:10.730 ⇒ 01:16:13.220 Uttam Kumaran: Again, like, I’m free to talk, like.

742 01:16:13.460 ⇒ 01:16:27.139 Uttam Kumaran: especially, again, for you, Shashu, Clarence, like, I’m just trying to be available. I’m mostly available in the evening, so even if, like, end of day, you’re… you could just literally Slack me, like, hey, can… because usually what I do is I look to see if you’re online, and then I’ll just, like.

743 01:16:27.550 ⇒ 01:16:28.930 Luke Scorziell: Give you a ring.

744 01:16:28.960 ⇒ 01:16:35.950 Uttam Kumaran: So, I’m happy to chat, like, every single day if you want, but it just may end up being, like, after

745 01:16:36.410 ⇒ 01:16:38.689 Uttam Kumaran: like, around this time, usually when I’m, like.

746 01:16:38.690 ⇒ 01:16:39.340 Luke Scorziell: Yeah.

747 01:16:39.810 ⇒ 01:16:49.150 Luke Scorziell: No, that’s fine for me, because, like, this is the time when everyone else is logged off, and the noise has kind of quieted down, and I’m on the Pacific coast, just,

748 01:16:49.920 ⇒ 01:16:51.789 Luke Scorziell: Vibing, doing my own thing, so…

749 01:16:52.630 ⇒ 01:16:55.599 Luke Scorziell: This is, like, my thinking time every day.

750 01:16:56.020 ⇒ 01:17:00.129 Luke Scorziell: Versus the mornings are a little bit more of my, like.

751 01:17:01.070 ⇒ 01:17:05.540 Luke Scorziell: I mean, it’s only been two and a half weeks, I guess, but, like, trying to put out fires and whatnot.

752 01:17:05.740 ⇒ 01:17:09.650 Luke Scorziell: So… But… Yeah.

753 01:17:10.260 ⇒ 01:17:15.129 Luke Scorziell: Sweet. No, I’ll take you up on that, and if I don’t, then you can bug me about it.

754 01:17:15.280 ⇒ 01:17:19.310 Uttam Kumaran: I’ll still… I mean, you’ll still get a random call from me, I got… I usually, like…

755 01:17:19.780 ⇒ 01:17:32.820 Uttam Kumaran: Like, I’m ending it with some more free time these days, so usually I just… I’m either, like, doing as much AI stuff as possible, which I think you saw some of today, or I just call people randomly. I’m like, where can I help? So, yeah.

756 01:17:33.140 ⇒ 01:17:39.510 Luke Scorziell: That was a question, too, and I did pop in a second, but with, the…

757 01:17:42.860 ⇒ 01:17:51.270 Luke Scorziell: Yeah, like, I’ve been getting… I’m in a lot of the partnership stuff, I think it’s valuable, just for me having more context. I think, like, from your perspective, is that…

758 01:17:51.940 ⇒ 01:18:01.510 Luke Scorziell: like, what is… where does… where would that fall on, like, the priorities of things that… that maybe I should be involved with? Because I know, like, it seems like Holly could use help, and…

759 01:18:01.830 ⇒ 01:18:03.710 Luke Scorziell: I think, like, my gut is, like.

760 01:18:04.410 ⇒ 01:18:09.060 Luke Scorziell: I just need to know enough about the partners to be able… like, I don’t even remember the Omnipost, honestly.

761 01:18:09.170 ⇒ 01:18:10.219 Luke Scorziell: Like, I… when they.

762 01:18:10.220 ⇒ 01:18:17.360 Uttam Kumaran: Yeah, well, the Omni folks, really, remember I told you, I’m like, hey, I’m talking to some people about Omni, let’s just rip something about Omni.

763 01:18:17.690 ⇒ 01:18:18.640 Uttam Kumaran: Yeah.

764 01:18:19.420 ⇒ 01:18:20.430 Uttam Kumaran: And you can see, like.

765 01:18:20.430 ⇒ 01:18:20.990 Luke Scorziell: it.

766 01:18:21.520 ⇒ 01:18:25.790 Uttam Kumaran: But see, this is the thing where, like, the fact that we just do them, like…

767 01:18:26.110 ⇒ 01:18:29.789 Uttam Kumaran: There’s, like, serendipity, you know, when we just make that happen.

768 01:18:31.260 ⇒ 01:18:35.310 Luke Scorziell: Yeah, and they seemed really excited about it. So… .

769 01:18:37.010 ⇒ 01:18:40.259 Uttam Kumaran: My larger point there is that,

770 01:18:40.620 ⇒ 01:18:54.889 Uttam Kumaran: I… I think there’s gonna be a lot of… you can use the partner stuff to fill your content pipeline, but I don’t need you to manage the partners at all. But I do wanna… I do want to help you achieve your goals by giving you a layup

771 01:18:54.970 ⇒ 01:19:01.490 Uttam Kumaran: on the posting and reach side. Like, dude, they literally said they’ll put $1,000 of budget towards, like, our posts.

772 01:19:01.600 ⇒ 01:19:02.470 Uttam Kumaran: like…

773 01:19:02.470 ⇒ 01:19:03.869 Luke Scorziell: Yeah, that’s crazy.

774 01:19:03.870 ⇒ 01:19:08.240 Uttam Kumaran: More of what I’m trying to help you with is to hit your goals.

775 01:19:08.240 ⇒ 01:19:08.859 Luke Scorziell: Yeah, yeah.

776 01:19:08.860 ⇒ 01:19:10.950 Uttam Kumaran: We’ve got some content and marketing goals.

777 01:19:11.090 ⇒ 01:19:13.910 Uttam Kumaran: as currently, I’m, like, partnerships lead.

778 01:19:14.030 ⇒ 01:19:19.269 Uttam Kumaran: okay, I just was able to… we basically got on a call where I’m like, a partner’s gonna pay to boost our shit.

779 01:19:19.380 ⇒ 01:19:26.120 Uttam Kumaran: You have some goals of, like, hitting some sort of partner source or marketing source, metrics.

780 01:19:26.380 ⇒ 01:19:27.510 Uttam Kumaran: Okay, like…

781 01:19:27.830 ⇒ 01:19:42.740 Uttam Kumaran: like, here’s a layup, like, I want you… I want to help you hit that. That’s all… that’s all this is. I don’t… I don’t really want you to get dragged into anything else, but one of the key ways that I’m talking about working with our partners is,

782 01:19:43.260 ⇒ 01:19:50.019 Uttam Kumaran: is through marketing with them, and I think it’s something unique, so I’m always gonna be telling our partners.

783 01:19:50.320 ⇒ 01:19:52.739 Uttam Kumaran: About our capacity to market with them.

784 01:19:53.410 ⇒ 01:19:58.580 Luke Scorziell: Yeah, which I love, too. I mean, it was really helpful, like, to be on that call, and I think I’d like to follow up with Tam.

785 01:19:58.700 ⇒ 01:20:02.500 Luke Scorziell: Just to kind of pick her brain, too. And then that’ll develop, hopefully, a relationship there.

786 01:20:02.770 ⇒ 01:20:06.549 Uttam Kumaran: Yeah, so, but again, I don’t need you involved in the partner stuff.

787 01:20:06.630 ⇒ 01:20:25.469 Uttam Kumaran: In any other way. I just think, one, at minimum, you’re gonna fill up your content pipeline with partner content. Second is, all of these partners are gonna love this, and they’re gonna wanna do events and stuff with us. So, be selfish and just think about, like, how some of these things can help you hit your goals.

788 01:20:26.960 ⇒ 01:20:31.489 Uttam Kumaran: And then just say no to things, like, if it’s like, hey, I don’t know how this is directly relevant.

789 01:20:31.880 ⇒ 01:20:43.419 Uttam Kumaran: Cool. Because all I’m doing is finding… trying to find 100,000 ways for us to grow, and then be like, what do you think? Like, you help me decide whether this is valuable or not for whatever our goals are.

790 01:20:43.420 ⇒ 01:20:43.960 Luke Scorziell: Yeah.

791 01:20:43.960 ⇒ 01:20:54.749 Uttam Kumaran: Now, whether the goals are right or wrong, that’s up to you and Robert, but for me, I saw that, like, we have a goal on, like, trying to hit a certain amount of marketing, sourced deals.

792 01:20:55.170 ⇒ 01:21:11.909 Uttam Kumaran: And I’m like, okay, so we need to find a way to do marketing. I was like, okay, I’m gonna get this Mixpanel thing going, I’m gonna, you know, I think we’ll end up with something with Omni, I’m gonna try to get in front of Snowflake, but I can’t… you own the marketing and campaign

793 01:21:12.190 ⇒ 01:21:19.770 Uttam Kumaran: like… like, basically bored, right? Like, or the roadmap. So all I can do is be like, cool.

794 01:21:20.200 ⇒ 01:21:28.319 Uttam Kumaran: Luke on my team owns that board, but we have space to co-partner… to co-market with partners. Let me try to get you on that board.

795 01:21:28.640 ⇒ 01:21:43.230 Uttam Kumaran: The worst thing I can do is sort of interrupt and, like, take the ownership… so I don’t… I have to loop you in, because you’re the owner of that. Like, I’m no longer the owner of that. And so, that’s how I’m making you aware, and I’m gonna do my best to…

796 01:21:43.330 ⇒ 01:21:50.610 Uttam Kumaran: Try to get… to try to, like, help you fill up your content pipeline with that sort of partner source content, you know?

797 01:21:52.570 ⇒ 01:22:00.839 Uttam Kumaran: And I really, really believe that Omni’s gonna be the first, but not the last person to put their own budget behind our stuff, because it’s really, really good.

798 01:22:02.450 ⇒ 01:22:10.079 Luke Scorziell: And is the roadmap there, do you think, like, work with a smaller partner, like Omni, and then work our way up to, like, working with a snowflake or something?

799 01:22:10.080 ⇒ 01:22:14.919 Uttam Kumaran: Yeah, so we… so we have, like, yeah, this is probably something we can discuss in…

800 01:22:15.080 ⇒ 01:22:24.919 Uttam Kumaran: like, kind of a little bit at length about how we’re gonna do partners. We had a really good conversation today with an advisor about this. Right now, like, we have too many.

801 01:22:24.920 ⇒ 01:22:27.610 Luke Scorziell: Partners, like, and they’re all the same importance.

802 01:22:27.930 ⇒ 01:22:34.019 Uttam Kumaran: So, more than likely, we will slim down both our total amount of, like.

803 01:22:34.260 ⇒ 01:22:37.460 Uttam Kumaran: Partners, and have just a few that are important.

804 01:22:37.640 ⇒ 01:22:40.960 Uttam Kumaran: We will probably have two categories. We’ll probably have, like.

805 01:22:41.350 ⇒ 01:22:45.180 Uttam Kumaran: friends of Brainforge partners, who were just, like.

806 01:22:45.360 ⇒ 01:22:55.700 Uttam Kumaran: we love your tool, maybe occasionally we post together, maybe occasionally they send us a deal, and then we’ll have people that we love, like, we’re best, like, BFFs. Like…

807 01:22:55.820 ⇒ 01:23:02.690 Uttam Kumaran: Snowflake, like, Omni, and probably, like, maybe one more. Snowflake is, like.

808 01:23:02.980 ⇒ 01:23:16.509 Uttam Kumaran: we’re, like, begging for them to, like, help us out. Omni, they are, like, new, but they… they may get really, really effing big, and I want to kind of, like, ride their coattails while they get really, really big.

809 01:23:16.510 ⇒ 01:23:17.130 Luke Scorziell: See, that’s wrong.

810 01:23:17.130 ⇒ 01:23:25.399 Uttam Kumaran: And naturally, they also need us. You know, they need us in market doing unique things to help them stand out. And so it’s really, really symbiotic.

811 01:23:26.730 ⇒ 01:23:27.550 Luke Scorziell: Yeah.

812 01:23:28.200 ⇒ 01:23:28.970 Luke Scorziell: Okay.

813 01:23:29.120 ⇒ 01:23:33.919 Luke Scorziell: Yeah, okay, that’s… yeah, and I think that’s kind of what I’ve been looking for, is, like.

814 01:23:34.390 ⇒ 01:23:43.830 Luke Scorziell: who are the three that I should be thinking about in terms of content? Because it’s like, in my mind, if we’re posting about everyone every single day, it’s like.

815 01:23:43.990 ⇒ 01:23:45.690 Luke Scorziell: Not really that interesting.

816 01:23:45.690 ⇒ 01:23:48.820 Uttam Kumaran: We’re not gonna post about everyone, yeah, I think…

817 01:23:48.940 ⇒ 01:23:52.970 Uttam Kumaran: I think we’re… I think after today, we’re a lot more conscious that, like.

818 01:23:53.090 ⇒ 01:23:59.710 Uttam Kumaran: Some partners are just gonna remain, like, friends, and we’re not gonna take up our… real estate,

819 01:24:00.170 ⇒ 01:24:01.250 Uttam Kumaran: for them?

820 01:24:01.370 ⇒ 01:24:10.919 Uttam Kumaran: And then, some people, we’re gonna just think about them every single day. Because there’s more than likely that 50-60% of our deal volume will come from partners.

821 01:24:12.420 ⇒ 01:24:12.880 Luke Scorziell: Yeah.

822 01:24:12.880 ⇒ 01:24:17.319 Uttam Kumaran: Like, if we really nail it, and that’s, like, absolutely massive, you know?

823 01:24:18.480 ⇒ 01:24:19.349 Luke Scorziell: Okay, good luck.

824 01:24:19.350 ⇒ 01:24:23.029 Uttam Kumaran: sort of, like, what we’re gonna be thinking about, and, like, Snowflake is one of them.

825 01:24:23.240 ⇒ 01:24:30.250 Uttam Kumaran: But for a snowflake, again, we’re gonna have to really, really push from, like, every single angle we have, we’ll have to push on a Snowflake.

826 01:24:30.830 ⇒ 01:24:36.910 Uttam Kumaran: From content to certifications to, like, actual deals sourced.

827 01:24:37.190 ⇒ 01:24:39.800 Uttam Kumaran: It’s a really, really different type of partner.

828 01:24:41.190 ⇒ 01:24:46.160 Luke Scorziell: Yeah, cause they’re a lot… They’re the hyperscaler.

829 01:24:46.470 ⇒ 01:24:51.430 Uttam Kumaran: Yeah, and they have hundreds and hundreds of people that are vying for their attention.

830 01:24:52.020 ⇒ 01:24:59.269 Uttam Kumaran: And so we’ll have to fight for that. I’m confident we’ll get there, but… Again, I think…

831 01:24:59.400 ⇒ 01:25:02.659 Uttam Kumaran: For me, a lot of, I think, this quarter is gonna be, like.

832 01:25:02.920 ⇒ 01:25:04.910 Uttam Kumaran: How do I focus my time?

833 01:25:05.240 ⇒ 01:25:08.749 Uttam Kumaran: On just the things that are, like, highest leverage.

834 01:25:08.990 ⇒ 01:25:13.340 Uttam Kumaran: And… don’t do anything else.

835 01:25:13.650 ⇒ 01:25:16.300 Uttam Kumaran: And that’s really gonna be, like, my challenge, I think.

836 01:25:17.520 ⇒ 01:25:17.880 Luke Scorziell: Yeah.

837 01:25:17.880 ⇒ 01:25:18.769 Uttam Kumaran: For the most part.

838 01:25:20.710 ⇒ 01:25:25.550 Luke Scorziell: And… Yeah, I mean, I like Resonate, I feel like a lot of those different,

839 01:25:26.280 ⇒ 01:25:28.519 Luke Scorziell: issues, or, like, I think I’m…

840 01:25:28.520 ⇒ 01:25:34.579 Uttam Kumaran: It’s really tough, because, like, I only have 8 to 10 hours a day, and…

841 01:25:34.970 ⇒ 01:25:41.800 Uttam Kumaran: We have to every day take steps, like, in the right direction, and it’s not always easy to know

842 01:25:42.300 ⇒ 01:25:54.090 Uttam Kumaran: like, we really can, like, we have to ruthlessly prioritize. Like, I think the last two quarters, there were some definite distractions, like, there were some partners that it ended up being, like, kind of like a waste of time.

843 01:25:54.250 ⇒ 01:25:58.220 Uttam Kumaran: There were some marketing things that ended up being kind of a waste of time, so…

844 01:25:58.770 ⇒ 01:26:03.360 Uttam Kumaran: We’re gonna… we’re just really gonna slim down the priorities, and then nail them.

845 01:26:03.500 ⇒ 01:26:06.649 Uttam Kumaran: And then just trust the process.

846 01:26:07.350 ⇒ 01:26:13.409 Uttam Kumaran: You know? And, like, keep an eye, really, on the metrics that we want to hit, which is, like, getting the pipeline filled.

847 01:26:13.600 ⇒ 01:26:16.289 Uttam Kumaran: And just, like, not fall for distractions, and then…

848 01:26:16.640 ⇒ 01:26:24.960 Uttam Kumaran: like, ultimately, I think our superpower is really just gonna be using as much AI and favors, like, as much as humanly possible.

849 01:26:26.980 ⇒ 01:26:33.489 Uttam Kumaran: And the AI piece, I think, like, you’re gonna see after today and this week, like, how much I was able to get done.

850 01:26:33.820 ⇒ 01:26:38.859 Uttam Kumaran: like, I basically built the slide deck thing, like, in, like, an hour and a half, like…

851 01:26:39.180 ⇒ 01:26:40.600 Uttam Kumaran: Alright. With, like…

852 01:26:40.600 ⇒ 01:26:43.990 Luke Scorziell: Robert is doing the same thing, but on the sales side, kind of.

853 01:26:44.750 ⇒ 01:26:48.869 Uttam Kumaran: Yeah, no, yeah, he’s with a lot of content automation, and so…

854 01:26:49.060 ⇒ 01:26:55.109 Uttam Kumaran: like, what I think I just need from the rest of the company is for everyone to sort of, like.

855 01:26:55.520 ⇒ 01:26:56.460 Uttam Kumaran: not…

856 01:26:56.720 ⇒ 01:27:03.180 Uttam Kumaran: for everyone to take some of the challenges and think, like, how much of these challenges can be done via AI,

857 01:27:03.410 ⇒ 01:27:07.460 Uttam Kumaran: And, like, can I just go ahead and, like… Ask.

858 01:27:07.760 ⇒ 01:27:08.670 Luke Scorziell: like…

859 01:27:10.570 ⇒ 01:27:18.660 Uttam Kumaran: maybe I just gotta figure out how to do it with AI, like, you know, it’s all possible. But if people are, like, kind of, like, are like, oh, let’s just do this old-fashioned way.

860 01:27:18.920 ⇒ 01:27:27.919 Uttam Kumaran: It’s gonna be tough. Like, for me, when we talk about, okay, how fast it’s gonna take us to get design and the landing pages for every service, I’m like.

861 01:27:28.340 ⇒ 01:27:32.239 Uttam Kumaran: shit, like, there’s gotta be a faster way to do this with AI, like…

862 01:27:32.860 ⇒ 01:27:40.739 Uttam Kumaran: if we… don’t we already have a landing page design? So what do you kind of need? You… we just need to do all the copy, and then maybe I should just rip… have AI rip…

863 01:27:41.170 ⇒ 01:27:44.670 Uttam Kumaran: Through creating them, And just… just post them.

864 01:27:44.790 ⇒ 01:27:45.680 Uttam Kumaran: And then…

865 01:27:45.680 ⇒ 01:27:48.560 Luke Scorziell: I mean, I think it’s better than nothing. Like, you were saying with all the…

866 01:27:48.560 ⇒ 01:27:50.440 Uttam Kumaran: I think it’s better than nothing, right?

867 01:27:50.440 ⇒ 01:27:53.189 Luke Scorziell: content, like, it’s, like, it doesn’t need to be great.

868 01:27:53.340 ⇒ 01:27:55.900 Luke Scorziell: content. I think there are places where…

869 01:27:56.160 ⇒ 01:28:02.950 Luke Scorziell: like, probably, obviously, you do want to have, like, good quality content from, especially, like, you and Robert, but I think

870 01:28:03.240 ⇒ 01:28:05.459 Luke Scorziell: As far as the website, it’s, like, mainly just…

871 01:28:05.460 ⇒ 01:28:10.450 Uttam Kumaran: That’s what I prefer you guys to focus on, versus focusing on…

872 01:28:12.170 ⇒ 01:28:17.090 Uttam Kumaran: Like, getting content up on the website that people may not spend a lot of time reading, you know?

873 01:28:18.000 ⇒ 01:28:18.650 Luke Scorziell: Yeah.

874 01:28:18.770 ⇒ 01:28:19.540 Luke Scorziell: Yeah.

875 01:28:19.990 ⇒ 01:28:23.250 Luke Scorziell: Okay, sweet. Well, I gotta… I’m gonna…

876 01:28:23.660 ⇒ 01:28:25.739 Luke Scorziell: Hop off, but thanks for calling.

877 01:28:26.690 ⇒ 01:28:28.590 Uttam Kumaran: Yeah, dude. Yeah, let me know how I can help.

878 01:28:29.070 ⇒ 01:28:31.519 Luke Scorziell: Yeah, I will. So, this is a super honest.

879 01:28:31.520 ⇒ 01:28:33.879 Uttam Kumaran: Eating of, what, tomorrow, or on Thursday?

880 01:28:34.100 ⇒ 01:28:36.040 Luke Scorziell: Yeah, Thursday,

881 01:28:39.490 ⇒ 01:28:44.260 Luke Scorziell: Yeah, we’re having… which is a great reminder, because we need to make a reservation today.

882 01:28:46.540 ⇒ 01:28:49.700 Luke Scorziell: They’re only open between, like, 5 and 10.

883 01:28:49.820 ⇒ 01:28:54.230 Luke Scorziell: During the week, and so yesterday I missed my window to call them.

884 01:28:54.590 ⇒ 01:28:55.860 Luke Scorziell: But…

885 01:28:56.460 ⇒ 01:29:07.319 Luke Scorziell: Yeah, yeah, I’m hype. It’s gonna be exciting. So, that’s fun to, like… obviously we’re fully remote, but having, like, some in-person stuff. And then I’m hopeful, I mean, I think it’d be really fun to…

886 01:29:09.470 ⇒ 01:29:11.510 Luke Scorziell: I initially talked about that, but…

887 01:29:11.850 ⇒ 01:29:13.990 Luke Scorziell: If that works out, that’d be really,

888 01:29:14.780 ⇒ 01:29:19.550 Luke Scorziell: Like, cool to go to and meet, like, the actual customers that we’re working with.

889 01:29:20.160 ⇒ 01:29:22.470 Uttam Kumaran: No, totally, I agree, I agree.

890 01:29:22.910 ⇒ 01:29:25.439 Uttam Kumaran: Okay, alright, perfect, I’ll let you go. I appreciate the call.

891 01:29:25.440 ⇒ 01:29:28.759 Luke Scorziell: Yeah, likewise. Alright, talk to you later.

892 01:29:29.060 ⇒ 01:29:30.310 Uttam Kumaran: Thank you, bye.