Meeting Title: US | Internal TDD Review Date: 2025-08-01 Meeting participants: Demilade Agboola, Uttam Kumaran
WEBVTT
1 00:02:27.240 ⇒ 00:02:28.330 Uttam Kumaran: My friend.
2 00:02:33.080 ⇒ 00:02:33.650 Demilade Agboola: Hi, Tom.
3 00:02:34.160 ⇒ 00:02:35.479 Uttam Kumaran: Hey! How are you?
4 00:02:35.840 ⇒ 00:02:37.090 Demilade Agboola: Pretty good. How are you.
5 00:02:37.720 ⇒ 00:02:38.860 Uttam Kumaran: I’m good.
6 00:02:38.980 ⇒ 00:02:41.440 Uttam Kumaran: How’s everything? How’s vacation?
7 00:02:42.565 ⇒ 00:02:46.714 Demilade Agboola: Vacation was nice. I got to spend time with my family.
8 00:02:47.060 ⇒ 00:02:49.070 Uttam Kumaran: Oh, wow. Okay. Nice.
9 00:02:49.070 ⇒ 00:02:52.689 Demilade Agboola: We haven’t all been together since like 2020, so it was nice to be.
10 00:02:52.690 ⇒ 00:02:55.030 Uttam Kumaran: No way. Wow!
11 00:02:55.530 ⇒ 00:02:57.779 Demilade Agboola: Yeah. And then my girlfriend.
12 00:02:57.780 ⇒ 00:02:59.580 Uttam Kumaran: Why is that anything in particular.
13 00:03:00.240 ⇒ 00:03:10.790 Demilade Agboola: I mean. So 2020 was when my father passed. So we were around for his funeral, and that was in Nigeria. Then my brother moved to the Uk. My sister moved to Luxembourg.
14 00:03:11.530 ⇒ 00:03:14.590 Demilade Agboola: and I was in Nigeria up until like 2023,
15 00:03:14.780 ⇒ 00:03:20.590 Demilade Agboola: and we just never. Then I moved to Malta in 2023, and we just never like planned anything.
16 00:03:21.270 ⇒ 00:03:35.859 Demilade Agboola: And I guess we just felt like, okay, it’s been too long. We all need to like. I have seen my brother. My sister has seen my my brother, you know. We’ve seen each other individually. We’ve just not had like a family thing, or we’ve not all been together at 1 point in time. So
17 00:03:36.485 ⇒ 00:03:41.989 Demilade Agboola: so we said, no, we had to fix that this summer. So yeah, we all went to Luxembourg.
18 00:03:42.960 ⇒ 00:03:43.830 Uttam Kumaran: Oh, nice!
19 00:03:43.830 ⇒ 00:03:53.109 Demilade Agboola: It was nice. We it was nice. The the my nephews and nieces played with themselves, they were so happy to finally see each other after a long time.
20 00:03:55.450 ⇒ 00:04:00.530 Demilade Agboola: Yeah, it was. It was. It was pretty cool, it was pretty cool. My girlfriend also came as well. She came from the Us.
21 00:04:00.530 ⇒ 00:04:01.710 Uttam Kumaran: No way.
22 00:04:01.710 ⇒ 00:04:02.910 Demilade Agboola: Yeah. So it was like a full.
23 00:04:02.910 ⇒ 00:04:04.900 Uttam Kumaran: How long have you guys been dating.
24 00:04:05.150 ⇒ 00:04:08.230 Demilade Agboola: 5 years, little over 5 years.
25 00:04:09.110 ⇒ 00:04:10.480 Uttam Kumaran: Amazing dude.
26 00:04:10.480 ⇒ 00:04:16.252 Demilade Agboola: Yeah, so yeah, it’s been. It was quite nice. We all went to the park.
27 00:04:16.660 ⇒ 00:04:21.579 Demilade Agboola: that was like a while. So so it was like Disneyland, because Disneyland has, like
28 00:04:22.380 ⇒ 00:04:33.620 Demilade Agboola: Disneyland, Paris, even though it works. It’s like very busy and stuff. And this is summer, too. So we went to a smaller park, but it was nice. There were a lot of rides. There were a lot of queues.
29 00:04:33.770 ⇒ 00:04:37.840 Demilade Agboola: and it wasn’t too far from my sister’s place. It was. It was. It was a pretty good trip.
30 00:04:38.160 ⇒ 00:04:39.590 Uttam Kumaran: Oh, your sister lives there.
31 00:04:40.170 ⇒ 00:04:42.200 Demilade Agboola: In Luxembourg. Yeah.
32 00:04:42.770 ⇒ 00:04:44.389 Uttam Kumaran: Oh, nice! What does she do?
33 00:04:44.670 ⇒ 00:04:47.059 Demilade Agboola: She works as she’s a manager in Amazon.
34 00:04:47.670 ⇒ 00:04:49.170 Uttam Kumaran: Oh, lovely, awesome.
35 00:04:49.865 ⇒ 00:04:50.560 Demilade Agboola: Yeah.
36 00:04:52.030 ⇒ 00:04:53.660 Uttam Kumaran: That’s like the central location.
37 00:04:54.891 ⇒ 00:04:57.630 Demilade Agboola: Yeah, it was. It was pretty and
38 00:04:58.201 ⇒ 00:05:05.679 Demilade Agboola: it was kind of just nice to, and my sister’s place works as well cause like there’s there’s a hotel right on the street.
39 00:05:06.570 ⇒ 00:05:09.590 Demilade Agboola: So, for instance, my girlfriend and I stayed in hotel
40 00:05:10.606 ⇒ 00:05:20.929 Demilade Agboola: so it was easy for us to come and go into the house at whatever times it just kind of worked to be honest. So we just didn’t. We just made it. We just did.
41 00:05:21.260 ⇒ 00:05:24.690 Uttam Kumaran: Call it nice. Oh, that’s lovely!
42 00:05:24.850 ⇒ 00:05:25.460 Demilade Agboola: There!
43 00:05:26.610 ⇒ 00:05:34.609 Uttam Kumaran: This week’s been good dude we got. I think the Tdd. Is in a great place. I think the only thing I’m gonna probably try to work on today is just
44 00:05:34.810 ⇒ 00:05:38.200 Uttam Kumaran: like what the final models are gonna look like, yeah.
45 00:05:38.890 ⇒ 00:05:41.979 Uttam Kumaran: But yeah, I feel like we got
46 00:05:42.330 ⇒ 00:05:45.639 Uttam Kumaran: sort of approval from everyone on on what was in there. And
47 00:05:46.163 ⇒ 00:05:51.329 Uttam Kumaran: you know, I’m glad we’re kind of doing this new process, so I feel good about it.
48 00:05:51.330 ⇒ 00:05:54.070 Demilade Agboola: Yeah, I saw some of the. I saw some of the questions
49 00:05:54.440 ⇒ 00:06:03.740 Demilade Agboola: that they want an asset. And I’m like, okay, like it definitely doable. We just need to be able to. Once we finalize like the metrics that they want
50 00:06:03.940 ⇒ 00:06:07.150 Demilade Agboola: in terms of like, how things are defined in the data.
51 00:06:08.740 ⇒ 00:06:11.120 Demilade Agboola: Yeah, shouldn’t be so hard to like. Roll them up
52 00:06:11.827 ⇒ 00:06:13.840 Demilade Agboola: and get those numbers available to them.
53 00:06:14.270 ⇒ 00:06:15.060 Uttam Kumaran: Yeah.
54 00:06:15.600 ⇒ 00:06:16.300 Demilade Agboola: No.
55 00:06:16.790 ⇒ 00:06:25.219 Demilade Agboola: But and I noticed that so also saw a comment that you made where like, they would also need like numbers that they can aggregate
56 00:06:27.730 ⇒ 00:06:33.780 Demilade Agboola: and look at. And I also feel like, Yeah, that will be like, not aggregate, or it’s not numbers they can look at to audit
57 00:06:34.855 ⇒ 00:06:41.060 Demilade Agboola: like an order list of some sort. And yeah, I actually think that would be very helpful to create like a
58 00:06:42.940 ⇒ 00:06:49.400 Demilade Agboola: a table that has all the values they need in one space like
59 00:06:50.442 ⇒ 00:07:00.709 Demilade Agboola: so for each order, for instance, you have the amount, or you have the maybe prorated subscription. You have the discounts. You have the, you know, refunds whatever that is
60 00:07:00.920 ⇒ 00:07:06.239 Demilade Agboola: all in one place, in in a way that’s kind of easy for them to be able to troubleshoot.
61 00:07:06.350 ⇒ 00:07:09.910 Demilade Agboola: or figure out what’s going wrong in certain numbers.
62 00:07:12.000 ⇒ 00:07:13.320 Uttam Kumaran: Yeah, I agree.
63 00:07:14.520 ⇒ 00:07:24.910 Uttam Kumaran: Yeah, I mean, overall, I feel like there’s not. I feel like, I don’t think there’s gonna be like a too many tables. I think we’re just gonna have, like, really trying to just destroy like tableau items.
64 00:07:25.270 ⇒ 00:07:30.151 Demilade Agboola: Oh, definitely, definitely, that that table has run its course.
65 00:07:30.640 ⇒ 00:07:31.189 Uttam Kumaran: Got it.
66 00:07:31.360 ⇒ 00:07:37.449 Demilade Agboola: And also that other thing. Yes, if we can, if we can get done with tables, items except and
67 00:07:38.590 ⇒ 00:07:48.789 Demilade Agboola: and their inventory Xf tables. I think we’ve done a good job with them, because honestly, it’s just an honest man. It’s just like a it’s a mess to be honest.
68 00:07:52.020 ⇒ 00:07:57.600 Demilade Agboola: Yeah, so just providing clean staging and facts. Tables for them will be very important.
69 00:07:58.184 ⇒ 00:08:07.900 Demilade Agboola: I noticed for some of the models Kyle referenced, using some of the old models to rebuild these neofact tables, which I said.
70 00:08:08.520 ⇒ 00:08:10.920 Demilade Agboola: Yeah, we should not use the old logic. We should.
71 00:08:10.920 ⇒ 00:08:11.360 Uttam Kumaran: Yeah.
72 00:08:11.360 ⇒ 00:08:12.980 Demilade Agboola: Rebuild. Yeah, we need to rebuild up.
73 00:08:14.130 ⇒ 00:08:23.499 Uttam Kumaran: So that’s what I think for Kyle. We’re gonna have to just like I think me and you are gonna have to just be a little bit more prescriptive, because I think this is the 1st time sort of doing something of this scale.
74 00:08:24.501 ⇒ 00:08:30.540 Uttam Kumaran: So we can be a little bit more prescriptive when in grooming on like, okay, what are? What are the models we want to make?
75 00:08:31.870 ⇒ 00:08:38.150 Uttam Kumaran: But kind of my goal. And this is something that, you know, I’ve never seen done really well is
76 00:08:41.289 ⇒ 00:08:53.840 Uttam Kumaran: mapping out models to like the questions right? Which was actually gonna help the analysts a lot. Because when we go to the analysts we’ll say, cool these questions that you ask are not all possible.
77 00:08:54.010 ⇒ 00:08:58.240 Uttam Kumaran: And here’s like sample queries to do those you know.
78 00:08:58.610 ⇒ 00:09:04.159 Demilade Agboola: Yeah, I I think one of the things we can do is try to map the questions into dashboards
79 00:09:04.500 ⇒ 00:09:06.280 Demilade Agboola: like so
80 00:09:06.740 ⇒ 00:09:13.800 Demilade Agboola: or like, I don’t know how to. Not necessarily dashboards, but like group the common questions together like these are the dashboards.
81 00:09:14.490 ⇒ 00:09:19.609 Demilade Agboola: Not necessarily that like these are the people that will use these these questions. So, for instance, the finance team
82 00:09:19.750 ⇒ 00:09:33.650 Demilade Agboola: has their questions, which is currently, what’s being done? Is it a thing of like everyone in finance team would use one dashboard if they need one dashboard. Okay, cool. How do we create the models that answer these dashboard questions?
83 00:09:34.360 ⇒ 00:09:35.010 Uttam Kumaran: Yeah.
84 00:09:35.010 ⇒ 00:09:39.440 Demilade Agboola: Yeah, that way. It’s kind of easy to number one. Figure out what’s going on.
85 00:09:40.400 ⇒ 00:09:42.499 Demilade Agboola: Put the common questions together.
86 00:09:43.650 ⇒ 00:10:02.449 Demilade Agboola: and that allows us to be able to also just debug. We can create tags easily in looker. I’m sorry not looking in. Dbt, so we can say, Hey, these are the finance models and say, something’s going on. We can easily do a finance like tag finance refresh. And then also it just runs everything that we need to do for.
87 00:10:02.905 ⇒ 00:10:03.359 Uttam Kumaran: Yeah.
88 00:10:03.360 ⇒ 00:10:03.820 Demilade Agboola: What’s next?
89 00:10:03.820 ⇒ 00:10:08.400 Uttam Kumaran: Something I don’t think we put here is sort of like the execution.
90 00:10:09.910 ⇒ 00:10:11.180 Demilade Agboola: Yeah. So
91 00:10:13.190 ⇒ 00:10:22.010 Demilade Agboola: same thing. Like if it’s maybe sn snop, we can do a dashboard for like, just kind of like, have an idea of what dashboards the
92 00:10:22.260 ⇒ 00:10:25.510 Demilade Agboola: who will be using what kind of right.
93 00:10:25.900 ⇒ 00:10:29.810 Demilade Agboola: and that we once we build out the dashboards.
94 00:10:30.520 ⇒ 00:10:47.159 Demilade Agboola: it’s much easier to maintain from a Dbt perspective, because it’s easy to trace that everything. If a dashboard goes bad, we know these are the. This is the lineage of all models that feed that dashboard. And this is the marked model that feeds that dashboard. So it’s much easier to like debug
95 00:10:47.633 ⇒ 00:10:59.390 Demilade Agboola: figure out where the numbers start to go bad. It’s not ideally, should not be too wide of a table to the point that it’s hard to like. Figure out what columns we’re looking at, which is the problem with tableaus items, except
96 00:10:59.590 ⇒ 00:11:10.989 Demilade Agboola: I don’t know. It probably has, like what maybe 100 200 columns. It’s really hard to like. Figure out that not one or 2 columns that you’re using to like, figure some to like debug?
97 00:11:12.130 ⇒ 00:11:17.450 Demilade Agboola: But yeah, I think, yeah, just being able to model. That would be very helpful to be
98 00:11:17.740 ⇒ 00:11:18.419 Demilade Agboola: to be.
99 00:11:19.000 ⇒ 00:11:19.929 Demilade Agboola: That makes sense.
100 00:11:26.000 ⇒ 00:11:28.790 Demilade Agboola: When do we want to understand? Soon.
101 00:11:29.620 ⇒ 00:11:30.330 Uttam Kumaran: Sorry.
102 00:11:30.330 ⇒ 00:11:33.320 Demilade Agboola: When do we want to present this to the urban stems team?
103 00:11:34.210 ⇒ 00:11:50.419 Uttam Kumaran: Well, we we kind of presented a version of this this week, I mean, but my goal is to try to get this all done by today. But it’s probably not going to get there. I think I want to try to spend some time today on the actual data model.
104 00:11:53.080 ⇒ 00:11:57.330 Uttam Kumaran: But I mean, like, I wanna kind of start working on stuff next week.
105 00:11:57.640 ⇒ 00:12:01.790 Demilade Agboola: Yeah, that would be great. Just us to be able to turn things out.
106 00:12:04.590 ⇒ 00:12:12.499 Demilade Agboola: yeah, I think next week what we need to do is start off with the staging, and basically just ensure that we have the
107 00:12:13.400 ⇒ 00:12:18.699 Demilade Agboola: the numbers that we like, the sources that we need properly. Ingested
108 00:12:20.421 ⇒ 00:12:24.340 Demilade Agboola: figure out. Loop loop is also a very important part of this equation.
109 00:12:25.190 ⇒ 00:12:27.990 Demilade Agboola: ingest that create the staging model for that.
110 00:12:28.270 ⇒ 00:12:33.439 Demilade Agboola: And then once we have that, we can start thinking intermediate intermediate intermediate tables.
111 00:12:33.730 ⇒ 00:12:35.709 Demilade Agboola: and then the mark tables.
112 00:12:36.140 ⇒ 00:12:36.800 Uttam Kumaran: Yeah.
113 00:12:38.830 ⇒ 00:12:42.980 Demilade Agboola: Well we do have. I have done some staging for like orders, and order.
114 00:12:42.980 ⇒ 00:12:43.889 Uttam Kumaran: Oh, nice. Okay.
115 00:12:43.890 ⇒ 00:12:46.610 Demilade Agboola: Yeah, so it’s not. We’re not starting from ground 0 in that.
116 00:12:47.090 ⇒ 00:12:47.570 Uttam Kumaran: Okay.
117 00:12:47.810 ⇒ 00:12:50.760 Demilade Agboola: Yeah, but we might want to.
118 00:12:50.760 ⇒ 00:12:55.289 Uttam Kumaran: Can you Link? Can you? Can you link those you can just put them at literally anywhere in this? Doc.
119 00:12:56.020 ⇒ 00:12:57.350 Demilade Agboola: What’s up? Diet.
120 00:12:58.010 ⇒ 00:13:00.470 Uttam Kumaran: I haven’t seen some of the new stuff
121 00:13:00.620 ⇒ 00:13:05.629 Uttam Kumaran: that you worked on. I’m just looking in the old. No existing repo.
122 00:13:06.020 ⇒ 00:13:13.940 Demilade Agboola: Yeah, I did that like Post mother’s Day, just to build some foundation for some of the the things
123 00:13:15.390 ⇒ 00:13:20.830 Demilade Agboola: that is part of the new model structure part give me one second.
124 00:13:24.460 ⇒ 00:13:26.550 Demilade Agboola: So orders
125 00:13:30.890 ⇒ 00:13:32.579 Demilade Agboola: I should put in the doc.
126 00:13:49.600 ⇒ 00:13:50.310 Demilade Agboola: Yeah.
127 00:14:40.480 ⇒ 00:14:44.169 Demilade Agboola: okay, so I just tagged you in it.
128 00:14:45.520 ⇒ 00:14:45.865 Uttam Kumaran: Okay.
129 00:14:46.500 ⇒ 00:14:50.989 Demilade Agboola: Oh, okay, so so those are just like
130 00:14:51.290 ⇒ 00:14:58.010 Demilade Agboola: the staging. We might need to like rework certain things because, this is from Hevo and Oms data.
131 00:14:58.865 ⇒ 00:15:03.820 Demilade Agboola: We might decide to switch it to shopify directly, because.
132 00:15:03.820 ⇒ 00:15:07.400 Uttam Kumaran: Okay, yeah, no. That’s what they wanted.
133 00:15:07.400 ⇒ 00:15:11.119 Demilade Agboola: Yes. In that case we’ll need to rework these to skip the
134 00:15:11.450 ⇒ 00:15:15.280 Demilade Agboola: skip the Oms data and just go directly to the shopify data.
135 00:15:16.900 ⇒ 00:15:17.720 Uttam Kumaran: Hmm.
136 00:15:20.170 ⇒ 00:15:29.529 Demilade Agboola: So I kind of just did it like legacy deliveries, legacy orders like, I kind of just all like orders and sub orders all that stuff, but we might split it.
137 00:15:29.760 ⇒ 00:15:33.079 Demilade Agboola: or we might rework it, based on what we deem necessary.
138 00:15:36.030 ⇒ 00:15:36.880 Uttam Kumaran: Okay.
139 00:15:42.800 ⇒ 00:15:47.449 Uttam Kumaran: so what’s next after inventory revenue? And then, what’s what are what are we going to next.
140 00:15:48.280 ⇒ 00:15:55.770 Demilade Agboola: I think at that point we can start to ask them what matters to their business, because I think usually we can start looking at things like marketing.
141 00:15:55.990 ⇒ 00:15:56.360 Uttam Kumaran: Okay.
142 00:15:57.263 ⇒ 00:15:58.329 Demilade Agboola: You know.
143 00:15:58.440 ⇒ 00:16:05.019 Demilade Agboola: But like, if we don’t have a clear line of inventory and revenue marketing doesn’t really matter as heavily because
144 00:16:06.670 ⇒ 00:16:14.260 Demilade Agboola: you need to be able to tie back to like your revenue. So if if your revenue is not in a great spot like it, it’s there’s no point like
145 00:16:15.050 ⇒ 00:16:23.350 Demilade Agboola: with marketing and stuff. So we can definitely do like marketing. We can definitely do like, I know.
146 00:16:24.250 ⇒ 00:16:39.939 Demilade Agboola: Sorry on stage. Yeah, I we can definitely do like marketing definitely do some more stuff around operations. Like what other things you want to do. But even then we can take even deeper cuts into like revenue and inventory. To be honest.
147 00:16:40.070 ⇒ 00:16:42.719 Demilade Agboola: because what we’ve done so far, like
148 00:16:43.560 ⇒ 00:16:55.059 Demilade Agboola: high level giving you the numbers sort of thing, but like things like creating alerts for certain things like when a certain inventory might be out of stock. For instance.
149 00:16:55.510 ⇒ 00:16:56.160 Uttam Kumaran: Yeah.
150 00:16:56.160 ⇒ 00:17:12.870 Demilade Agboola: Being able to forecast revenue or forecast inventory, or like things like that, just helping them be a bit more proactive. With these things is is definitely the next like step beyond just the hey, these are your numbers for last week, or as things are right now.
151 00:17:14.980 ⇒ 00:17:16.220 Uttam Kumaran: Yeah, I agree.
152 00:17:16.460 ⇒ 00:17:17.099 Demilade Agboola: Yeah.
153 00:17:21.160 ⇒ 00:17:24.880 Demilade Agboola: So, for instance, an example would be available for sale.
154 00:17:25.288 ⇒ 00:17:30.760 Demilade Agboola: So for inventory, there’s this concept of available for sale which should never be negative, because that means that
155 00:17:30.980 ⇒ 00:17:36.499 Demilade Agboola: they have overbooked flowers that they don’t have. If I.
156 00:17:36.500 ⇒ 00:17:37.100 Uttam Kumaran: Yeah.
157 00:17:37.100 ⇒ 00:17:51.280 Demilade Agboola: Yeah. So just being able to let them know. Hey, you know now that your numbers are in a good spot, everyone is confident in it. You have negative values here like you should probably look into that stock and figure out why you overbooked that
158 00:17:51.610 ⇒ 00:17:59.929 Demilade Agboola: things like that just being able to allow them be more proactive, and not necessarily run into issues, as often will be the next step.
159 00:18:05.440 ⇒ 00:18:10.839 Uttam Kumaran: Another question that came up a bunch is just people need like dates for all types of different statuses like
160 00:18:11.020 ⇒ 00:18:15.509 Uttam Kumaran: they want the create a day delivery date.
161 00:18:16.530 ⇒ 00:18:18.193 Uttam Kumaran: Personally, they also want
162 00:18:19.040 ⇒ 00:18:23.639 Uttam Kumaran: the original order, and if it was replaced, what was the order it was replaced with.
163 00:18:24.020 ⇒ 00:18:26.800 Uttam Kumaran: which is just like crazy. They don’t have that already.
164 00:18:27.800 ⇒ 00:18:48.910 Demilade Agboola: Yeah. Yeah, that’s that’s part of why I said, the deeper cuts with inventory or revenue whatever we’re looking at. To be honest. So we are giving them right now. I think this phase one is number one, putting the things like the staging models, intermediate models and models in good order. But we will definitely need, like deeper cuts to these things.
165 00:18:49.430 ⇒ 00:18:52.079 Demilade Agboola: let them know what’s happening. Let them know
166 00:18:52.420 ⇒ 00:18:55.079 Demilade Agboola: on what has happened in such a way that
167 00:18:55.713 ⇒ 00:19:00.659 Demilade Agboola: they can make better decisions and see, have better visibility all from one place.
168 00:19:00.940 ⇒ 00:19:16.259 Demilade Agboola: because right now they can’t actually figure it out. It’s not like they can’t. It’s just hard. They would need to like, hop into multiple spaces, go into dash, going to Netsuite, get the information about this from this, and then merge it together and say, this is what happened.
169 00:19:16.900 ⇒ 00:19:38.360 Demilade Agboola: So if they’re in a pickle they can figure it out. It’s like not. It’s not a thing of like. They can never figure it out. It’s just not easy. It’s just not convenient, and we need to be able to give them everything in one spot so that they can always like just use it at once about the dates. Yeah, that they love dates. There’s date of fulfillment, date of purchase. This dates for everything to be honest.
170 00:19:40.590 ⇒ 00:19:42.300 Uttam Kumaran: Yeah, I agree, okay.
171 00:19:55.890 ⇒ 00:19:56.950 Uttam Kumaran: okay.
172 00:19:56.950 ⇒ 00:19:57.650 Demilade Agboola: Alright!
173 00:19:58.090 ⇒ 00:19:58.780 Uttam Kumaran: Cool
174 00:20:00.180 ⇒ 00:20:03.209 Uttam Kumaran: So I’m gonna try to wrap this up today.
175 00:20:03.450 ⇒ 00:20:08.170 Uttam Kumaran: I blocked out a lot of my day today to kind of like, do some writing like this, and finishing this up.
176 00:20:08.630 ⇒ 00:20:09.880 Demilade Agboola: Okay. Sounds good.
177 00:20:10.720 ⇒ 00:20:15.060 Uttam Kumaran: So I’ll tag you if I need anything. And then yeah, on Monday we’ll plan on
178 00:20:15.770 ⇒ 00:20:19.250 Uttam Kumaran: doing our best to ticket this stuff out.
179 00:20:19.670 ⇒ 00:20:21.190 Demilade Agboola: Okay. Sounds good.
180 00:20:22.110 ⇒ 00:20:22.830 Uttam Kumaran: Okay.
181 00:20:23.090 ⇒ 00:20:23.890 Demilade Agboola: Alright, man.
182 00:20:24.300 ⇒ 00:20:24.640 Uttam Kumaran: You do.
183 00:20:24.640 ⇒ 00:20:29.369 Demilade Agboola: Thanks a lot, for, like, you know, covering all like my, my work all week. Appreciate it.
184 00:20:29.370 ⇒ 00:20:35.208 Uttam Kumaran: Oh, of course, of course. Yeah. And and it I was kind of poking into stuff on Eden as well.
185 00:20:35.830 ⇒ 00:20:43.909 Uttam Kumaran: you know that that project is consistently just like all over the place. But let let me give you some good news. We have
186 00:20:44.070 ⇒ 00:20:47.449 Uttam Kumaran: 2 great candidates for project management.
187 00:20:48.273 ⇒ 00:20:52.080 Uttam Kumaran: That we’re hoping to close next week.
188 00:20:52.410 ⇒ 00:21:13.420 Uttam Kumaran: So stuff is going to get a lot more organized around here which I cannot wait for shit. So I’m very, very happy. Yeah, we have. We have 2 people that are sort of in the final rounds. And I can also give amber a break because she’s basically project managing as everything. So.
189 00:21:13.420 ⇒ 00:21:23.250 Demilade Agboola: Yeah. And there’s a lot of stuff happens with Eden like they always have. Someone always has an idea it’s either Jonah or Carthels or mitesh. There’s just stuff going on there.
190 00:21:23.960 ⇒ 00:21:36.820 Uttam Kumaran: Yeah, and I. And so I just want to get everyone more support, you know. So no, of course, of course. And I want to make it easy also for people to take time off. I mean one thing I’ll talk about next week. I mean, I I feel like some folks are better than others. But
191 00:21:37.564 ⇒ 00:21:45.449 Uttam Kumaran: yeah, like, the more we can start to build redundancies like the better it’ll get, you know. So yeah.
192 00:21:48.060 ⇒ 00:21:49.930 Demilade Agboola: Okay. Sounds good. Thanks. A lot.
193 00:21:49.930 ⇒ 00:21:50.660 Uttam Kumaran: Okay.
194 00:21:50.930 ⇒ 00:21:53.570 Uttam Kumaran: Thank you. Dude talk soon. Okay, bye.