Meeting Title: Intern-Assignments Date: 2024-06-25 Meeting participants: Nicolas Sucari, Uttam Kumaran, Priyadharshini Kalidoss, Atharv Gudi, Jared Patterson, Shankar Krishna Varma


WEBVTT

1 00:00:06.520 00:00:07.170 Priyadharshini Kalidoss: It.

2 00:00:08.090 00:00:09.389 Priyadharshini Kalidoss: I’m using a bugger.

3 00:01:41.580 00:01:43.629 Shankar Krishna Varma: Hey? Hi, ma’am! Happy anniversary!

4 00:01:48.190 00:01:49.769 Priyadharshini Kalidoss: Hi, Chelsea. Thank you.

5 00:01:51.330 00:01:53.989 Priyadharshini Kalidoss: We are just getting back home.

6 00:01:54.380 00:01:55.759 Shankar Krishna Varma: Oh, Cookie!

7 00:01:56.820 00:01:59.109 Priyadharshini Kalidoss: How was your? How did the function go.

8 00:01:59.500 00:02:01.479 Shankar Krishna Varma: All all good. All good. Thanks.

9 00:02:02.190 00:02:02.950 Shankar Krishna Varma: Okay.

10 00:02:14.950 00:02:15.770 Uttam Kumaran: Hey, everyone.

11 00:02:18.320 00:02:19.549 Shankar Krishna Varma: Hey! Hi! Tom!

12 00:02:20.290 00:02:21.481 Uttam Kumaran: Hey, Chimpan! How are you?

13 00:02:47.410 00:02:48.760 Uttam Kumaran: Hey, Priya! How are you?

14 00:02:50.860 00:02:52.670 Priyadharshini Kalidoss: Hey! Hi! Also! How are you.

15 00:02:53.330 00:02:56.994 Priyadharshini Kalidoss: hey? I’m good. Thanks.

16 00:03:14.850 00:03:15.510 Uttam Kumaran: Stop.

17 00:03:16.700 00:03:17.380 Uttam Kumaran: Ask.

18 00:03:19.050 00:03:21.819 Uttam Kumaran: Let me see if Akshay is gonna be free.

19 00:04:49.740 00:04:52.549 Uttam Kumaran: Give me one sec. I’m just getting my headphones.

20 00:04:55.320 00:04:56.290 Nicolas Sucari: Everyone, bye.

21 00:05:14.710 00:05:17.369 Uttam Kumaran: Great, I think. Everybody’s here, hey? Athar.

22 00:05:18.920 00:05:19.780 Atharv Gudi: Hello!

23 00:05:22.680 00:05:23.590 Uttam Kumaran: How’s it going.

24 00:05:27.330 00:05:30.500 Atharv Gudi: Good good. I managed to get out of my previous thing.

25 00:05:30.980 00:05:32.660 Uttam Kumaran: Nice. I’m doing great.

26 00:05:34.432 00:05:41.680 Uttam Kumaran: Cool. I guess we’ll jump right into things. So yeah, I’ve been watching the stand up. Report. Seems like everybody’s getting through Snowflake. So

27 00:05:41.970 00:05:46.170 Uttam Kumaran: I think today we finally are going to kind of look to assign

28 00:05:48.070 00:05:56.969 Uttam Kumaran: assign people with folks on the team as well as begin scheduling some work. So Nico and I spent the last

29 00:05:57.659 00:06:00.719 Uttam Kumaran: day working with the team directly.

30 00:06:00.800 00:06:04.009 Uttam Kumaran: basically planning out what a longer backlog

31 00:06:04.773 00:06:22.609 Uttam Kumaran: tasks. And so typically our process for executing work is we have Nico and I meet on Friday. We basically kind of think about what the plan is for the week. Then on Monday we meet with everybody on the team and basically agree on expectations for the week.

32 00:06:23.163 00:06:29.990 Uttam Kumaran: This is kind of a bit of a new process as is like a lot of processes here. So we’re just like testing out everything.

33 00:06:30.353 00:06:36.169 Uttam Kumaran: And then, ideally, what we’re now that we met with them yesterday. The plan is to kind of

34 00:06:36.310 00:06:43.770 Uttam Kumaran: give you guys a couple of options on things to work at on and overall.

35 00:06:43.810 00:07:03.960 Uttam Kumaran: you know, I think, for the most part everybody is in the spot that they expect it to be so. Athar. You’ll be working directly with Patrick. Patrick is working on the data engineering side. I thought his area would be good for you to kind of get a good look at, because he kind of manages the platform of brain forge

36 00:07:04.000 00:07:16.750 Uttam Kumaran: the develop like how everybody develops. He manages also, like all of our code repositories, and it’ll give you a good overview of everything. How everything works. He has a couple of things that he wants to

37 00:07:17.171 00:07:19.178 Uttam Kumaran: work on that are related

38 00:07:20.110 00:07:23.409 Uttam Kumaran: to a few different like areas. So I’ll just start

39 00:07:24.060 00:07:25.510 Uttam Kumaran: here. And I’ll kind of

40 00:07:25.560 00:07:29.620 Uttam Kumaran: hopefully to show you in the projects of where things are.

41 00:07:29.680 00:07:37.955 Uttam Kumaran: The goal is that you guys will work directly with Nico and the actual mentor you guys have in the company to kind of

42 00:07:38.380 00:07:44.900 Uttam Kumaran: create. Some of these tickets agree on like, kind of what the acceptance is for the work, and then begin to work directly with them.

43 00:07:45.743 00:07:47.210 Uttam Kumaran: On execution.

44 00:07:47.605 00:07:49.530 Uttam Kumaran: And so one of the

45 00:07:50.890 00:07:54.715 Uttam Kumaran: an example of one that is on the

46 00:07:55.500 00:07:58.850 Uttam Kumaran: on the data engineering side is.

47 00:08:02.030 00:08:02.930 Uttam Kumaran: so

48 00:08:03.140 00:08:05.467 Uttam Kumaran: this is one where we’re gonna need

49 00:08:07.330 00:08:09.360 Uttam Kumaran: we’ll need more.

50 00:08:10.550 00:08:17.339 Uttam Kumaran: We’ll need. You’ll need to work with Patrick directly to kind of fill this out. But we have a task. We have a task with our related to testing.

51 00:08:17.520 00:08:33.820 Uttam Kumaran: And basically, what we do is we, we have a like hundreds of tests that run on our repository. Every time we like push code and right now, there, we want to begin. We want to work on a little bit of consolidation on where that all that code lives for those tests.

52 00:08:34.280 00:08:38.249 Uttam Kumaran: And this one hopefully will give you a good overview of the

53 00:08:39.820 00:08:48.999 Uttam Kumaran: Give you a good overview of the repository. Give me overview of like how testing works and like, you know, a good like way to get your feet wet until like your local setup.

54 00:08:50.350 00:08:54.760 Uttam Kumaran: and then we have some other stuff that’s like a little bit more in the weeds than this.

55 00:08:54.970 00:09:00.429 Uttam Kumaran: But this is what I’ll be connecting you and Patrick with, and kind of like. Begin

56 00:09:00.773 00:09:19.570 Uttam Kumaran: including you on meetings related to this. We have everything that kind of goes through. Stand up bot right now, so we don’t have meetings every day. But the one thing I’ll urge everybody, and we’ll kind of walk through everybody’s stuff today is to work directly with Nico and work directly with the folks on the team that you’re paired with

57 00:09:19.740 00:09:22.939 Uttam Kumaran: to get this stuff done to ask questions.

58 00:09:22.950 00:09:25.140 Uttam Kumaran: Use slack like really heavily.

59 00:09:25.180 00:09:45.790 Uttam Kumaran: We’re not like a super meeting heavy organization which is good because everybody has heads down work, but sometimes tough. If you’re shy, or if you’re nervous about like bothering everybody, I would totally get rid of that like assumption. The one thing that I want to urge everyone to do is ask a ton of questions.

60 00:09:46.720 00:09:48.660 Uttam Kumaran: So after this meeting I’ll

61 00:09:48.880 00:09:50.930 Uttam Kumaran: I’ll ping both of you guys.

62 00:09:50.960 00:09:53.310 Uttam Kumaran: Adarb and Patrick about

63 00:09:53.720 00:09:55.910 Uttam Kumaran: about about this work.

64 00:09:56.430 00:09:58.640 Uttam Kumaran: You guys can get started on this

65 00:09:59.242 00:10:06.169 Uttam Kumaran: Akshay. So Akshay, we talked a little bit about work yesterday on the analysis side.

66 00:10:06.220 00:10:13.819 Uttam Kumaran: So we we were discussing with Jacob. Do you remember on the call yesterday about stuff like sales analysis.

67 00:10:15.900 00:10:17.159 Akshay kumar.G: Yeah, it was just 93.

68 00:10:17.820 00:10:35.329 Uttam Kumaran: Okay, great. So that sales analysis piece, I want to basically hand over to you to begin working on. And kind of own. So that’s a piece where I’m going to. Pair you with Jacob directly, and you guys can work together to plan that out.

69 00:10:35.625 00:10:41.750 Uttam Kumaran: There’s also a ticket in here that I’ll be adding, assigning to you, and then you can be able to see and begin to edit.

70 00:10:41.770 00:10:44.902 Uttam Kumaran: I’m again working directly with Nico and

71 00:10:46.720 00:10:51.840 Uttam Kumaran: and Jacob on scoping that ticket out. That’s purely on the analysis side.

72 00:10:54.260 00:10:54.879 Akshay kumar.G: You have a phone.

73 00:10:54.880 00:10:57.180 Uttam Kumaran: Does that make sense, or any questions? There.

74 00:10:58.340 00:11:00.140 Akshay kumar.G: Definitely like I will try to speak with

75 00:11:00.370 00:11:06.930 Akshay kumar.G: like I say, he was speaking about the evidence of that. Like to like learn basics about creating a page as well. I will try to catch up.

76 00:11:06.930 00:11:07.890 Uttam Kumaran: Exactly.

77 00:11:09.420 00:11:14.406 Uttam Kumaran: Yeah. I mean, everything will be like a learning curve. So don’t worry.

78 00:11:15.350 00:11:18.069 Uttam Kumaran: don’t worry too much, but

79 00:11:18.210 00:11:21.933 Uttam Kumaran: I think it’ll be. It’ll be really interesting for you to take that on

80 00:11:22.730 00:11:25.349 Uttam Kumaran: and you know, give give it a good shot, so

81 00:11:26.230 00:11:27.010 Uttam Kumaran: great.

82 00:11:28.430 00:11:35.229 Uttam Kumaran: Priya, so, Priya, you’ll also be working. I’m gonna pair you with the analytics engineering team.

83 00:11:35.774 00:11:40.400 Uttam Kumaran: They have several, you know, tickets outstanding related to

84 00:11:40.894 00:11:46.959 Uttam Kumaran: testing over some data model updates. And so that’ll give you a good overview of

85 00:11:46.980 00:11:52.610 Uttam Kumaran: Dbt as well as how to go in and push code and and push updates to models.

86 00:11:53.126 00:11:56.590 Uttam Kumaran: So I’m gonna go ahead and pair you with Brian

87 00:11:57.116 00:11:58.900 Uttam Kumaran: from that side and

88 00:11:58.950 00:12:02.230 Uttam Kumaran: kind of provide you with a ticket that you can go through the same process with

89 00:12:02.430 00:12:05.899 Uttam Kumaran: again the goal here. And this particular open ended one.

90 00:12:06.110 00:12:14.009 Uttam Kumaran: Because we’re we’re just like we’re running as quick as we can. So the goal here is for you to work directly with your mentor and scope out the tickets.

91 00:12:14.539 00:12:19.849 Uttam Kumaran: And basically understand from them what they expect and have check-ins with them directly.

92 00:12:20.275 00:12:25.009 Uttam Kumaran: We’ll continue to use. Stand up, bot! But the goal is to communicate directly with them.

93 00:12:25.553 00:12:29.910 Uttam Kumaran: So I’ll connect you guys, Bria, you and Brian directly after this.

94 00:12:31.290 00:12:32.460 Priyadharshini Kalidoss: Yeah, still.

95 00:12:33.580 00:12:34.580 Priyadharshini Kalidoss: events.

96 00:12:35.796 00:12:43.699 Uttam Kumaran: And then, Jared. So, Jared, you’re working directly with me on sales stuff. I still want to give you some stuff on the data side.

97 00:12:44.074 00:12:56.090 Uttam Kumaran: That’s working with Jacob. That’s similar to kind of Akshay’s work on the evidence side. If not, it’s using some of the data, the models that we already have built to answer some open questions.

98 00:12:56.348 00:13:03.571 Uttam Kumaran: I don’t. Wanna. I know you’re helping me a bunch on the sales side, so I don’t wanna like inundate you with like too much stuff. So ideally. What we’re gonna do is

99 00:13:04.412 00:13:08.537 Uttam Kumaran: work directly with Jacob and figure out something that’s manageable.

100 00:13:09.320 00:13:14.709 Uttam Kumaran: And then again, we some of the stuff that we’re we’re we’re providing to y’all

101 00:13:15.091 00:13:18.890 Uttam Kumaran: fortunately, it’s not on like too much of a time constraint, which is great.

102 00:13:19.204 00:13:24.749 Uttam Kumaran: However, I do want you guys that the goal of this process is not just for you to get work done.

103 00:13:25.153 00:13:30.259 Uttam Kumaran: It’s actually to learn like how these different software would work and then have a stakeholder that actually

104 00:13:30.697 00:13:33.640 Uttam Kumaran: judges what you produce. And there’s a feedback loop

105 00:13:34.250 00:13:45.899 Uttam Kumaran: like if I were just to be like, Hey, go get this stuff done. That’d be kind of bad. I feel like. So in this process like, I want you guys to learn how to use evidence. Dbt, snowflake rail

106 00:13:46.010 00:13:51.909 Uttam Kumaran: and learn how to use Github and hot. Learn how to like actually present work.

107 00:13:52.100 00:14:04.160 Uttam Kumaran: Right? So you’re learning how to work in an engineering organization, and so taking on these small tasks, running through the entire process of scoping them out, executing, asking questions, iterating.

108 00:14:04.190 00:14:07.279 Uttam Kumaran: It’s basically what I want everybody to to take a stab at.

109 00:14:09.520 00:14:14.780 Uttam Kumaran: So I’ll be pairing you directly with a ticket from Jacob as well. And then

110 00:14:14.930 00:14:15.840 Uttam Kumaran: again.

111 00:14:16.010 00:14:19.940 Uttam Kumaran: I would, I think, Nico, should we just like

112 00:14:20.070 00:14:23.760 Uttam Kumaran: you think we should create a channel for this? Or I think maybe people can just ping

113 00:14:24.300 00:14:25.390 Uttam Kumaran: and

114 00:14:26.190 00:14:28.389 Uttam Kumaran: like the pool parts channel. I don’t know.

115 00:14:36.579 00:14:37.929 Uttam Kumaran: Nico. Can you hear me?

116 00:14:39.990 00:14:43.749 Nicolas Sucari: Sorry I can’t hear. I’m sorry. Can you repeat again.

117 00:14:43.750 00:14:47.800 Uttam Kumaran: Yeah, no, I was saying, should we just have everybody like communicate?

118 00:14:47.890 00:14:50.020 Uttam Kumaran: And the pool parts channel.

119 00:14:51.178 00:15:10.279 Nicolas Sucari: I I was thinking just about that like it would be good to have like if for example, Priya is gonna be or actually, it’s gonna be like linked to Jacob. Probably like, have a channel with Jacob, actually, you and me, so that we can channel like all communications on how this stuff and the same on.

120 00:15:10.280 00:15:30.710 Nicolas Sucari: and all these engineering and that engineering stuff to have like a dedicated channel for each of them so that they can send questions to them there. Obviously they can go private, like in a private conversation, but it will be easier to have like a a channel so that we can also answer questions. And if there is anything like more, general, you can go. You can still go to

121 00:15:30.820 00:15:33.770 Nicolas Sucari: to the brain for the intern channel.

122 00:15:33.770 00:15:34.100 Uttam Kumaran: Okay.

123 00:15:34.407 00:15:38.709 Nicolas Sucari: So that everyone can see, and if not, we have internal engineering. I mean.

124 00:15:38.740 00:15:53.849 Nicolas Sucari: I think that it would be best but then, if if you want to include everyone on the full cart channel, that’s okay, too. The only thing is that there. Yeah, there, everyone’s there. So probably everyone can help, too.

125 00:15:53.980 00:15:54.879 Nicolas Sucari: I don’t know.

126 00:15:54.880 00:15:56.289 Uttam Kumaran: Okay, yeah, I think.

127 00:15:56.290 00:15:59.859 Nicolas Sucari: Depends on how you want like going going forward.

128 00:16:00.365 00:16:00.730 Nicolas Sucari: Yeah.

129 00:16:00.730 00:16:01.483 Uttam Kumaran: I think,

130 00:16:03.590 00:16:04.480 Uttam Kumaran: yeah, I.

131 00:16:04.480 00:16:06.589 Nicolas Sucari: I mean, we can create 3 channels, right

132 00:16:07.052 00:16:26.547 Nicolas Sucari: analytics, engineering analysis, and that engineering and assign each of them to each of that different channels and start like channeling specific questions regarding each of the roles there. And if there is something more general that everyone needs to know, we can go to the internal engineering or clients reports that kind of stuff.

133 00:16:27.070 00:16:28.830 Nicolas Sucari: Okay, okay, yeah.

134 00:16:29.570 00:16:30.390 Uttam Kumaran: Okay. Great

135 00:16:31.150 00:16:38.349 Uttam Kumaran: the other thing I wanted to just walk through. Briefly, everybody is actually going to be working on a specific client that we have

136 00:16:38.410 00:16:40.430 Uttam Kumaran: all pull parts to go

137 00:16:41.410 00:16:45.189 Uttam Kumaran: and I’m just gonna do a little bit of

138 00:16:45.350 00:16:50.910 Uttam Kumaran: kind of presentation on, like what they do and kind of like a little bit of overview of the business.

139 00:16:52.600 00:16:57.269 Uttam Kumaran: so cool parts to go they sell cool parts direct to consumer.

140 00:16:57.320 00:16:58.650 Uttam Kumaran: So for

141 00:16:58.660 00:17:02.469 Uttam Kumaran: I mean for folks in in the States. Like

142 00:17:02.580 00:17:09.969 Uttam Kumaran: pools, like everybody here, like a lot of people at their home have a pool, I mean, like pools are everywhere. Basically, pools have pumps in them.

143 00:17:10.488 00:17:14.910 Uttam Kumaran: I’m sure. Aka, you’re familiar with pumps from your like Nike stuff.

144 00:17:15.283 00:17:21.639 Uttam Kumaran: But basically, the pumps are used to flow water through filters, and there’s different types of pumps.

145 00:17:21.859 00:17:28.359 Uttam Kumaran: pumps to do, heating different formats in ground or above ground pool pumps.

146 00:17:28.676 00:17:39.070 Uttam Kumaran: And they sell these direct to consumer. Right now in in the Us. The pool pump industry is really owned by these pool service professionals, meaning they come to your house. They install whatever

147 00:17:39.110 00:17:43.179 Uttam Kumaran: they want. These guys sell directly to consumers. Typically.

148 00:17:43.260 00:17:46.270 Uttam Kumaran: and you can install these directly into your pool.

149 00:17:46.300 00:17:58.279 Uttam Kumaran: And so they do roughly like 20 to 30 million dollars in revenue per year. And we’re managing all of their data. Data from what people are buying to where it’s getting shipped

150 00:17:58.665 00:18:05.969 Uttam Kumaran: all the way to people asking for refunds to where they’re marketing. So the entire pie we’re working on

151 00:18:06.150 00:18:12.199 Uttam Kumaran: in particular, a lot of the focus right now is on sales growth as well as shipping cost mitigation.

152 00:18:12.567 00:18:18.000 Uttam Kumaran: I’m sure. Gary, we kind of saw a little bit of stuff we worked on. But we’re shipping cost work. We did directly for them.

153 00:18:18.409 00:18:28.740 Uttam Kumaran: And so the work that you’ll be doing that you folks will be working on with Jared and with the Ae. Team, and Patrick is all related to making their life easier and bringing them more money.

154 00:18:29.254 00:18:47.740 Uttam Kumaran: So we’ll be working on things like measuring their sales on understanding, that the distance that things need to ship to get the customers and a whole sort of analysis. And we have actual actions that we’ll be taking, that is, either gonna make the money or saving costs, which are our 2 main directives.

155 00:18:48.274 00:18:57.340 Uttam Kumaran: Cool parts has, like a bunch of key Apis Kpis called the performance indicator. Basically, the main ways that they measure their business

156 00:18:58.760 00:19:03.230 Uttam Kumaran: for us. Right now, we’re really focused on sales, profit and chipping costs.

157 00:19:03.360 00:19:09.569 Uttam Kumaran: So the goal is to reduce shipping costs. The goal is to increase profit, and the goal is to increase sales.

158 00:19:10.118 00:19:18.180 Uttam Kumaran: We use this tool called real which I mentioned to some folks that in during these path that you guys will be working on, you’ll be

159 00:19:18.220 00:19:20.579 Uttam Kumaran: getting familiar with will.

160 00:19:25.080 00:19:26.482 Uttam Kumaran: So this is

161 00:19:27.240 00:19:30.821 Uttam Kumaran: This is real. Real is just an operational analytics tool.

162 00:19:31.450 00:19:35.599 Uttam Kumaran: I recently just posted about this and

163 00:19:36.098 00:19:42.270 Uttam Kumaran: on Linkedin. But real is a great tool that we use to basically help them measure everything. So on this chart on this

164 00:19:42.420 00:19:45.909 Uttam Kumaran: dashboard, you’re basically seeing all the key metrics.

165 00:19:45.920 00:19:51.659 Uttam Kumaran: You’re seeing a ton of dimensions about orders, about customers, about refunds discounts.

166 00:19:51.820 00:19:56.079 Uttam Kumaran: We also have several other models here, for example, shipments

167 00:19:56.150 00:20:01.919 Uttam Kumaran: where we have all their data around shipping. How much is getting shipped where it’s getting shipped from?

168 00:20:02.050 00:20:06.220 Uttam Kumaran: So this is our main analysis tool that we use to help them answer questions.

169 00:20:06.240 00:20:12.059 Uttam Kumaran: So our goal, the analytics engineering team’s goal, is to make sure that this has models ready.

170 00:20:12.150 00:20:16.049 Uttam Kumaran: And then the analysis team’s goal is to use this to answer questions.

171 00:20:16.410 00:20:26.090 Uttam Kumaran: and that’s really the supply chain. So kind of the thing. You know, I was talking to Nico a bit about this yesterday is like data is just you can think of it just similar to your production line.

172 00:20:26.200 00:20:49.810 Uttam Kumaran: When we produce a data model, it needs to go from raw data, it needs to get pipelined into snowflake. That’s all. On the data engineering side, there needs to be code written to actually combine and convert that raw data into tables that are usable by the analysis team. That’s all the analytics engineering work and the analysis team works directly with the customer to ask those why questions

173 00:20:49.930 00:20:54.570 Uttam Kumaran: and then seek out answers and help that the business would make take action.

174 00:20:54.880 00:21:03.060 Uttam Kumaran: And so that’s the production line of of data. And so it’s interesting for this client, which is in common is we’re actually in every we’re involved in every step of the way.

175 00:21:03.619 00:21:23.719 Uttam Kumaran: And that’s hopefully what you guys get to see context of is how something goes from the raw data to the data models all the way to an analysis question. Of course, like, as you go further. Technical require some technical knowledge. So Athar has a really good understanding of sequel. So that’s why I wanted to pair him with

176 00:21:23.780 00:21:39.649 Uttam Kumaran: with Patrick first, st so him can get so he can get like this kind of fundamental understanding of how data gets pushed in and gets the Dbt but for the folks that are just kind of getting their feet way to SQL. I want you to kind of get more familiar with the models and more familiar with the analysis side of things.

177 00:21:42.670 00:21:58.148 Uttam Kumaran: so any questions there? What I’ll be doing right after this is just setting up the slack channels, assigning guys tickets and then sending a little blurb to all the folks, the guys in the team to basically that they know that.

178 00:22:08.090 00:22:27.390 Shankar Krishna Varma: Alright a thumb. So I was. I was just curious when you say this, okay, so these dashboards are the data that is there. After the shipments and everything. Right? So are we also having any mechanism of collecting analytics? In terms of events of the website. Are we doing that? Similar to Google analytics.

179 00:22:28.110 00:22:33.779 Uttam Kumaran: Yeah, so we we aren’t. We don’t have any tasks right now that are related to

180 00:22:34.282 00:22:38.107 Uttam Kumaran: the web events we are collecting, all of them, though.

181 00:22:38.540 00:22:43.300 Uttam Kumaran: mainly we are looking at the actual conversion data out of shopify.

182 00:22:43.530 00:22:56.830 Uttam Kumaran: So we’re not. We don’t do a lot on the marketing side in terms of looking like what people do in the pages themselves. That’s an open area. But mainly we look at where we’re spending money, where the customers are getting acquired from, and then what they’re buying.

183 00:22:56.990 00:22:59.139 Uttam Kumaran: So we’re not doing a lot on the.

184 00:22:59.240 00:23:06.430 Uttam Kumaran: You know what people are clicking on, what people are doing what people are are doing. But it’s a it’s a it’s a great question. It’s open area.

185 00:23:08.140 00:23:08.970 Shankar Krishna Varma: Worth it.

186 00:23:22.360 00:23:35.900 Uttam Kumaran: Great if no other questions, then I will slack everybody right after this, with like some instructions and everybody, you’ll start to see that you’re in the Github Repository, and that you have your

187 00:23:37.020 00:23:46.169 Uttam Kumaran: tasks assign against this will be a learning process. There’ll be things that in this in the learning that kind of weren’t covered. There’ll be software, I’m sure, that we need to

188 00:23:46.340 00:23:49.939 Uttam Kumaran: improve on and install and stuff like that, so don’t get dissuaded.

189 00:23:50.294 00:24:01.245 Uttam Kumaran: Just the one thing I would say is, I’m very busy. So, Nico, and whoever on your mentor side are your best friends. I’ll do my best to kind of answer questions as possible. But

190 00:24:02.225 00:24:06.075 Uttam Kumaran: I actually want you guys to work directly with the folks on the ground.

191 00:24:06.480 00:24:11.040 Uttam Kumaran: because it’ll give you a sense of like what their engineering cycles are, and how to ask great questions. So.

192 00:24:13.670 00:24:14.967 Nicolas Sucari: Yeah. And guys,

193 00:24:15.560 00:24:33.040 Nicolas Sucari: just want to let you know that you can ping me through slack anytime. Worry about it. I will try to help with everything and also great job on answering that standably both it’s really helpful for us to tell and me to know what you’ve been doing what you’ve been learning.

194 00:24:33.040 00:24:46.029 Nicolas Sucari: And please continue to do that, because let us know, like the progress that you’re making on each of the different things. And if you have any blocker also, it raises an alarm to us and make us have some action about it.

195 00:24:46.335 00:25:04.040 Nicolas Sucari: So don’t hesitate if you want to. Yeah, just ping me through slack. You need anything about any tool about any task that you’re working on, and I will try to help or try to contact you with the different team members so that they can help you figure out how we can solve the different issues.

196 00:25:04.322 00:25:25.489 Nicolas Sucari: And yeah, and we are still working on creating some like guide documents, how to implement different tools on how to do different processes. So if you have any idea on a process or any tool that you would like to have like a guide, step step by step, guide on how to implement or how to yeah, create something. Let me know, and I will work with you to to create that, too. Okay.

197 00:25:30.710 00:25:31.470 Nicolas Sucari: Pope.

198 00:25:31.920 00:25:38.169 Uttam Kumaran: Okay. If no other questions, then I’ll talk to everybody on slack, and then we still have our Friday meeting. But I think.

199 00:25:38.240 00:25:40.369 Uttam Kumaran: Nico, I wonder if we shouldn’t move that

200 00:25:40.430 00:25:42.079 Uttam Kumaran: do earlier in the day

201 00:25:42.560 00:25:43.240 Uttam Kumaran: doesn’t have that.

202 00:25:43.240 00:25:44.090 Nicolas Sucari: Yeah, I.

203 00:25:44.090 00:25:45.210 Uttam Kumaran: And many meetings.

204 00:25:45.730 00:26:14.719 Nicolas Sucari: It. It would be great to know the time zones of each of you guys so that I can try to figure out like, what is the best time to have that meeting? So yeah, so that we can arrange the best time that we can be all that meeting on Friday. It’s really nice meeting, because we join as a team. Altogether, we share what we’ve been doing on the week. We share some progress on different stuff. And yeah, it’s really interesting. So if everyone can attend there, it would be great.

205 00:26:16.060 00:26:20.699 Uttam Kumaran: Yeah. So maybe Nika, like a quick poll in engineering, might be easiest.

206 00:26:20.930 00:26:30.239 Uttam Kumaran: We can get the other guys ideally, we do it at like 10 Am. Central that way. It’s been a little bit more time, and then I want that to be more of a like a feedback.

207 00:26:30.640 00:26:37.450 Uttam Kumaran: you know, and then, like we can get feedback on like docs. We want to write stuff that went wrong things like that and have a more open, ended conversation.

208 00:26:39.020 00:26:40.049 Uttam Kumaran: so perfect.

209 00:26:40.730 00:26:41.449 Nicolas Sucari: Perfect. Yep.

210 00:26:41.900 00:26:43.030 Nicolas Sucari: excellent.

211 00:26:43.670 00:26:44.899 Nicolas Sucari: I’ll do that. Okay.

212 00:26:46.480 00:26:48.790 Uttam Kumaran: Alright, thanks, as I’ll talk to you on slack.

213 00:26:49.920 00:26:50.720 Nicolas Sucari: Thank you. Thanks.

214 00:26:51.055 00:26:51.390 Shankar Krishna Varma: Gonzales.

215 00:26:51.390 00:26:51.930 Atharv Gudi: Bye.

216 00:26:53.070 00:26:54.099 Nicolas Sucari: Jared, can you

217 00:26:54.540 00:26:55.609 Nicolas Sucari: stay for a minute.

218 00:26:56.840 00:26:57.530 JARED PATTERSON: Yeah.

219 00:26:58.670 00:27:02.969 Nicolas Sucari: Just wanted to ask you, have you been working with webflow or something like that?

220 00:27:04.970 00:27:06.000 JARED PATTERSON: I’ll leave.

221 00:27:06.680 00:27:08.495 JARED PATTERSON: have not I.

222 00:27:09.100 00:27:10.720 Nicolas Sucari: Don’t worry about it. Yes.

223 00:27:10.770 00:27:17.839 Nicolas Sucari: I I just started to look into web flow like I know you were working with them on some kind of stuff of the website, basically.

224 00:27:17.840 00:27:18.460 JARED PATTERSON: And he’s.

225 00:27:18.460 00:27:20.279 Nicolas Sucari: Stuff. I’m trying. Yeah.

226 00:27:20.860 00:27:23.676 JARED PATTERSON: Yeah, just like we would we were using

227 00:27:25.290 00:27:26.722 JARED PATTERSON: what is it?

228 00:27:28.100 00:27:38.999 JARED PATTERSON: figma? Or something like that? Fig, Jen, just to like map out everything, but he had said that he was. Gonna I think he does want me to work on it eventually. I’ve never done before, though.

229 00:27:39.840 00:28:05.310 Nicolas Sucari: No, no, no, me me neither. But I was just accessing workflow workflow is the Cms that we’re using for like creating the web page. As we are not developing this. Obviously there, there is code, but it’s kind of a no code way of creating the web page and I was trying to access. And it says to someone, has been doing some changes, whether it was online. So I don’t know if it was you or anyone else. I’m gonna ask them. Don’t worry about it.

230 00:28:05.310 00:28:06.679 JARED PATTERSON: I don’t think I’ve

231 00:28:06.790 00:28:07.710 JARED PATTERSON: like.

232 00:28:09.020 00:28:09.889 JARED PATTERSON: I’ve never even.

233 00:28:09.890 00:28:15.130 Nicolas Sucari: Oh, yeah, okay, don’t worry. I think mine’s great. If you have any

234 00:28:15.140 00:28:29.299 Nicolas Sucari: any any doubts on how to use Figma, let me know I’ve been using it a lot for the past yeah, 3, 4 years. I’m not a designer. I probably don’t know how to assign stuff, but I know how like the Ui looks big enough how to do some stuff if you want.

235 00:28:29.590 00:28:30.320 Nicolas Sucari: It’s good.

236 00:28:30.320 00:28:35.290 JARED PATTERSON: Yeah, thank you. No, I I honestly. The only reason I use it is just to kind of like

237 00:28:35.370 00:28:40.610 JARED PATTERSON: I’ve used it with Utam just to kind of plan stuff. I haven’t used it directly myself, though.

238 00:28:41.710 00:28:42.370 JARED PATTERSON: Urban.

239 00:28:42.370 00:28:42.780 Nicolas Sucari: Perfect.

240 00:28:43.680 00:28:45.010 Nicolas Sucari: Thank you, Jared Bye.

241 00:28:45.010 00:28:45.710 JARED PATTERSON: You.