Meeting Title: US x BF | Planning & Retro Date: 2025-10-27 Meeting participants: Uttam Kumaran, Emily Giant, Amber Lin, Awaish Kumar, Demilade Agboola
WEBVTT
1 00:00:15.270 ⇒ 00:00:17.240 Uttam Kumaran: Hello, nice background.
2 00:00:18.700 ⇒ 00:00:24.860 Emily Giant: Yeah. Also nice background to you, Utam. Your dog is, like, fully paying attention today.
3 00:00:25.020 ⇒ 00:00:27.000 Uttam Kumaran: He’s just grilling me in the back of my head.
4 00:00:27.000 ⇒ 00:00:28.210 Emily Giant: He is!
5 00:00:28.210 ⇒ 00:00:31.210 Uttam Kumaran: If this guy doesn’t keep typing, I’m gonna.
6 00:00:31.210 ⇒ 00:00:32.470 Emily Giant: Spaz out.
7 00:00:33.340 ⇒ 00:00:37.850 Emily Giant: He’s like, he needs to give me a W-A-L-K. Now.
8 00:00:37.850 ⇒ 00:00:38.880 Uttam Kumaran: Yeah.
9 00:00:39.300 ⇒ 00:00:40.499 Uttam Kumaran: What do you think?
10 00:00:43.560 ⇒ 00:00:46.800 Emily Giant: Oh my gosh, his ears are too much.
11 00:00:48.250 ⇒ 00:00:50.239 Uttam Kumaran: Yeah, they’re bigger than his head.
12 00:00:50.240 ⇒ 00:00:51.590 Emily Giant: He’s so cute.
13 00:00:53.620 ⇒ 00:00:59.229 Uttam Kumaran: Okay, cool. Let’s, we can check out the board.
14 00:01:15.290 ⇒ 00:01:18.349 Uttam Kumaran: Is PK joining, or no?
15 00:01:18.350 ⇒ 00:01:20.280 Emily Giant: I don’t think so, he usually can’t.
16 00:01:20.280 ⇒ 00:01:20.910 Uttam Kumaran: Okay.
17 00:01:22.040 ⇒ 00:01:23.290 Uttam Kumaran: That’s fine.
18 00:01:23.640 ⇒ 00:01:31.489 Uttam Kumaran: So, I guess maybe first thing to start off with is, are there revenue issues from the weekend?
19 00:01:31.700 ⇒ 00:01:35.730 Uttam Kumaran: Cleared, and then I have a couple of follow-ups on that to ask.
20 00:01:35.730 ⇒ 00:01:42.109 Emily Giant: So, I was never totally clear on what the issues were, because once the refresh went through, the dashboard looked normal.
21 00:01:42.110 ⇒ 00:01:42.490 Uttam Kumaran: Okay.
22 00:01:42.490 ⇒ 00:01:56.419 Emily Giant: But my concern is that, Demolade and I had a meeting with Perry the day before she left, and she changed a column in her, forecast that,
23 00:01:56.670 ⇒ 00:02:03.339 Emily Giant: overinflated AOV, and that was the only thing that looked a little high to me. It wasn’t, like.
24 00:02:03.400 ⇒ 00:02:16.889 Emily Giant: super, super high, but it was 130, and that just felt like… Menakshi was, like, somewhat unclear on what the problem was, she just said it didn’t look right, so it’s hard for me, without looking through every order.
25 00:02:17.320 ⇒ 00:02:25.450 Emily Giant: to know exactly what she meant. But once that refresh went through, there were no, like, glaring…
26 00:02:25.690 ⇒ 00:02:28.220 Emily Giant: issues with the dashboard that I saw.
27 00:02:29.220 ⇒ 00:02:31.539 Demilade Agboola: Do the numbers match the numbers in Shopify?
28 00:02:33.110 ⇒ 00:02:33.790 Emily Giant: Pardon?
29 00:02:34.190 ⇒ 00:02:39.130 Demilade Agboola: the daily numbers match the daily Shopify numbers, or are they, like, in the same ballpark?
30 00:02:39.490 ⇒ 00:02:44.549 Emily Giant: Yeah, then I think it must have been resolved as soon as the refresh was successful.
31 00:02:49.020 ⇒ 00:02:49.590 Uttam Kumaran: Okay.
32 00:02:49.810 ⇒ 00:02:53.860 Uttam Kumaran: So, I think one of the pieces I just wanted to add is just, like, having
33 00:02:53.970 ⇒ 00:02:58.880 Uttam Kumaran: Like, ideally, in that situation, we want to be able to catch
34 00:02:59.870 ⇒ 00:03:02.759 Uttam Kumaran: those issues, like, via Metaplane, faster.
35 00:03:03.220 ⇒ 00:03:09.729 Uttam Kumaran: So, like, I think one thing Awash, wondering if you can work on… Creating…
36 00:03:10.140 ⇒ 00:03:15.489 Uttam Kumaran: like, Metaplane, set of monitors just for revenue?
37 00:03:17.230 ⇒ 00:03:24.359 Awaish Kumar: Last time I did, but I’ve… what I went through is, like, orders, fake orders, fake transactions.
38 00:03:24.500 ⇒ 00:03:35.509 Awaish Kumar: And all these tables, where I thought, like, the… are most important for getting the revenue, but I see this… this model which fail, it is, like, components XF model.
39 00:03:35.510 ⇒ 00:03:35.870 Emily Giant: Yeah.
40 00:03:36.360 ⇒ 00:03:40.590 Awaish Kumar: This is being used, so it’s hard to, like, actually find out which one is…
41 00:03:41.610 ⇒ 00:03:46.980 Demilade Agboola: Yeah, so right now, for things like revenue, it’s Tableau Items XF and,
42 00:03:47.330 ⇒ 00:03:55.019 Demilade Agboola: Components XF. Those are the old models that we’re trying to deprecate and get rid of, but they’re still currently used to…
43 00:03:56.600 ⇒ 00:03:58.610 Demilade Agboola: How are the existing dashboards.
44 00:04:02.890 ⇒ 00:04:04.979 Demilade Agboola: Those are the troublesome models right now.
45 00:04:05.370 ⇒ 00:04:05.970 Emily Giant: Yeah.
46 00:04:07.780 ⇒ 00:04:20.550 Uttam Kumaran: So maybe a wish, I can have you take a look, and I just want to make sure that now that we have a kind of a good grasp on issues, I want us… the next kind of goal for us is, like, we should be flagged
47 00:04:20.709 ⇒ 00:04:24.670 Uttam Kumaran: You know, we should be flagged.
48 00:04:25.120 ⇒ 00:04:27.489 Uttam Kumaran: First, when there’s an issue, you know?
49 00:04:28.030 ⇒ 00:04:35.960 Uttam Kumaran: So I just want to make sure that you can work with the team on figuring out, like, what exact columns need, and also I want to think about not only just, like.
50 00:04:36.150 ⇒ 00:04:37.280 Uttam Kumaran: Faleness.
51 00:04:38.810 ⇒ 00:04:43.890 Uttam Kumaran: But also, like, like, ranges for metrics.
52 00:04:46.800 ⇒ 00:04:47.930 Uttam Kumaran: So this one’s, like.
53 00:04:48.310 ⇒ 00:04:55.510 Uttam Kumaran: pretty high, because I just want to make sure… every week where we get flagged that there’s an issue and we haven’t figured out first is a problem, you know?
54 00:04:55.780 ⇒ 00:04:56.420 Emily Giant: Yeah.
55 00:04:57.000 ⇒ 00:04:57.549 Awaish Kumar: Oh, God.
56 00:04:57.550 ⇒ 00:04:58.160 Uttam Kumaran: Bore.
57 00:04:59.400 ⇒ 00:05:01.610 Uttam Kumaran: Okay, great.
58 00:05:02.440 ⇒ 00:05:10.120 Uttam Kumaran: What else are, like, the, like, high-level priorities for this week? So we have a GA meeting later today. I know we’re.
59 00:05:10.530 ⇒ 00:05:28.370 Amber Lin: We have the project review meeting on Thursday, and then the local migration on Thursday. Last week, we said the issues were, one, close out North Beat integration issues, two, daily revenue summary tables, three, continuous scenario analysis, and four.
60 00:05:28.370 ⇒ 00:05:36.789 Amber Lin: I think we said implement prepaid versus revenue logic and finalized suborders. I don’t think we can do all of them, but that’s what we…
61 00:05:36.920 ⇒ 00:05:38.239 Amber Lin: Had on our plate.
62 00:05:39.930 ⇒ 00:05:43.339 Awaish Kumar: We also have a North Beam issue, right?
63 00:05:43.550 ⇒ 00:05:46.299 Uttam Kumaran: Yeah, so what was the f- what was the.
64 00:05:46.750 ⇒ 00:05:48.579 Amber Lin: Oh, I sent it in the chat.
65 00:05:48.580 ⇒ 00:05:52.130 Uttam Kumaran: Yeah, yeah, so for North Beam, yeah, we’re gonna talk on Thursday about…
66 00:05:53.500 ⇒ 00:06:01.590 Awaish Kumar: Northwind, they share the… they share a service from which, using that, we can… Get the order attribution.
67 00:06:01.800 ⇒ 00:06:02.640 Uttam Kumaran: Yes.
68 00:06:03.620 ⇒ 00:06:09.419 Awaish Kumar: And it’s $5 per month extra, and the way I was doing kind of a…
69 00:06:09.850 ⇒ 00:06:19.320 Awaish Kumar: that’s why I said, like, using that, I could find only 50% of the orders, and they said exactly that, like, their dashboard is just for seeing high-level
70 00:06:19.620 ⇒ 00:06:34.880 Awaish Kumar: like, the channels, which are, like, Facebook, like, popular channels, like Facebook, TikTok, and Google, and things like that. And they are not showing all of them there, so we can’t use the normal export feature in the orders, tab.
71 00:06:39.750 ⇒ 00:06:41.150 Uttam Kumaran: Okay. Okay.
72 00:06:54.720 ⇒ 00:06:56.520 Awaish Kumar: Okay, what else for this week?
73 00:06:59.870 ⇒ 00:07:01.720 Amber Lin: Scenario analysis?
74 00:07:02.240 ⇒ 00:07:06.370 Uttam Kumaran: Yeah, so we just need to… yeah, so we just need to put together…
75 00:07:07.100 ⇒ 00:07:09.440 Awaish Kumar: Yeah, that makes sense. So I can…
76 00:07:10.720 ⇒ 00:07:13.519 Uttam Kumaran: There’s just some follow-ups on scenario analysis.
77 00:07:15.410 ⇒ 00:07:16.599 Uttam Kumaran: I’ll take that.
78 00:07:17.000 ⇒ 00:07:25.079 Emily Giant: I think historical revenue and making sure that that is streamlined in Looker and in dbt is the number one priority.
79 00:07:27.690 ⇒ 00:07:28.390 Uttam Kumaran: Okay.
80 00:07:29.810 ⇒ 00:07:37.660 Demilade Agboola: When you say streamlined, are you referring to the issues that Menaki had, or are you talking about just having that into
81 00:07:38.060 ⇒ 00:07:39.649 Demilade Agboola: The new models were built in.
82 00:07:40.360 ⇒ 00:07:44.349 Emily Giant: new models we’re building. Just that, like, they’re one…
83 00:07:45.150 ⇒ 00:07:52.219 Emily Giant: single, like, look or view, or all available in the same model so that the data all flows together over time.
84 00:07:53.270 ⇒ 00:07:58.070 Demilade Agboola: Yeah, so that’s the US 415 that I’m working on.
85 00:07:58.560 ⇒ 00:08:07.719 Demilade Agboola: Basically, I’m almost there, it just keeps breaking at some certain points, but I’m, like, really close to having everything in one place.
86 00:08:07.720 ⇒ 00:08:09.110 Emily Giant: Okay, perfect.
87 00:08:12.770 ⇒ 00:08:13.350 Uttam Kumaran: Okay.
88 00:08:13.890 ⇒ 00:08:20.950 Uttam Kumaran: So, I was hoping to kind of get to that during our Thursday meeting, which is sort of, like, the plan for a lot of Looker migration.
89 00:08:21.660 ⇒ 00:08:24.130 Uttam Kumaran: But is there anything, like, short-term
90 00:08:25.520 ⇒ 00:08:27.099 Uttam Kumaran: We want to create a ticket for.
91 00:08:31.310 ⇒ 00:08:36.700 Emily Giant: Create a ticket for?
92 00:08:37.750 ⇒ 00:08:40.300 Uttam Kumaran: Like, for the… for this Looker streamlining.
93 00:08:42.450 ⇒ 00:08:48.900 Demilade Agboola: Also, how I’m doing it, first to interrupt, but how I’m just doing it is, basically, I’m trying to create a dbt model
94 00:08:49.190 ⇒ 00:08:51.869 Demilade Agboola: That has everything in one place, so…
95 00:08:52.760 ⇒ 00:08:59.909 Demilade Agboola: Before the date… before the migration date, we have all the data, and after migration date, we have all the data unioned into one.
96 00:09:00.110 ⇒ 00:09:04.140 Demilade Agboola: And that will now be the new data source that Emily can tap into in Looker.
97 00:09:04.390 ⇒ 00:09:08.540 Demilade Agboola: So she already has tapped into it, but we just need to add the…
98 00:09:09.660 ⇒ 00:09:15.630 Demilade Agboola: older data, the legacy data as well, that data source. So that’s kind of what’s happening right now.
99 00:09:16.930 ⇒ 00:09:22.819 Demilade Agboola: And that has also been used… I mean, that’s what Perry had, like, tested and used for her local instance.
100 00:09:23.850 ⇒ 00:09:27.640 Demilade Agboola: But once we have the legacy, then we can put everything
101 00:09:28.420 ⇒ 00:09:33.820 Demilade Agboola: Of the, like, live dashboards onto what we would have created, or what we have created already.
102 00:09:37.340 ⇒ 00:09:38.020 Emily Giant: Yeah.
103 00:09:42.040 ⇒ 00:09:42.650 Uttam Kumaran: Okay.
104 00:09:43.770 ⇒ 00:09:48.889 Uttam Kumaran: I mean, do you think there’s, like, a concise, like, ticket to make?
105 00:09:49.220 ⇒ 00:09:53.959 Uttam Kumaran: Or… I mean, I can… I can just highlight just that, and…
106 00:09:54.420 ⇒ 00:10:03.459 Demilade Agboola: So, we could have… so we have 415 already, and then what we could just add is, like, the… and replace existing looker,
107 00:10:04.440 ⇒ 00:10:08.260 Demilade Agboola: Existing local dashboards with new data.
108 00:10:12.970 ⇒ 00:10:20.340 Uttam Kumaran: So yeah, a lot of this we’re gonna go through on Thursday, but, I feel like if this is, like, a super priority, then we should just do this now.
109 00:10:20.870 ⇒ 00:10:24.359 Uttam Kumaran: Emily, is this a you thing?
110 00:10:25.980 ⇒ 00:10:27.460 Emily Giant: Yeah, yep.
111 00:10:27.780 ⇒ 00:10:29.439 Uttam Kumaran: It’s like a coordination, but, like…
112 00:10:29.440 ⇒ 00:10:34.680 Emily Giant: Yeah, I can’t… do it until I know what the fields are.
113 00:10:35.600 ⇒ 00:10:36.989 Emily Giant: In the new bottle.
114 00:10:37.890 ⇒ 00:10:42.999 Emily Giant: Because I’ve already added it for… The fact line items.
115 00:10:45.200 ⇒ 00:10:48.690 Uttam Kumaran: So, you’re saying we can’t do it until we know what the fields are?
116 00:10:48.940 ⇒ 00:10:49.850 Demilade Agboola: Yeah, so it will be…
117 00:10:49.850 ⇒ 00:10:50.779 Emily Giant: in the model.
118 00:10:51.110 ⇒ 00:10:56.770 Demilade Agboola: Yeah, it’ll be the same… it’ll be the same fields, basically, but the same format and structure.
119 00:10:57.430 ⇒ 00:10:59.310 Uttam Kumaran: We do the content validation and stuff.
120 00:11:00.580 ⇒ 00:11:05.059 Emily Giant: Yeah, or even… even to, like, replace… The reports, like…
121 00:11:05.630 ⇒ 00:11:13.999 Emily Giant: I don’t… I don’t want to… yeah, I guess it’s the same thing. I don’t want to replace them until we’ve done, like, QA on historicals and…
122 00:11:14.450 ⇒ 00:11:21.680 Uttam Kumaran: Okay, so the… so what we… what we probably need here is, in our, like, like,
123 00:11:23.660 ⇒ 00:11:27.310 Uttam Kumaran: In our spreadsheet, we should just create, like, a,
124 00:11:28.010 ⇒ 00:11:29.960 Uttam Kumaran: A new sheet that is just…
125 00:11:30.200 ⇒ 00:11:40.550 Uttam Kumaran: regarding, like, revenue migration, and what we should do, Demolade, is just have the old model columns, and then where to source that from in the new model.
126 00:11:44.160 ⇒ 00:11:51.190 Uttam Kumaran: So that’s, like, that’s… that, I think, is the clearest thing. Like, that’s… that’s probably what we’re gonna discuss on Thursday, anyways.
127 00:11:52.930 ⇒ 00:11:55.769 Demilade Agboola: Yeah, we could definitely look into that. I mean…
128 00:11:56.940 ⇒ 00:12:05.989 Uttam Kumaran: It’s… I mean, this is where I just want to make sure that we have, like, a… because what’s gonna happen in Looker is there’s gonna be random fields that we, like, didn’t support, or, like.
129 00:12:06.130 ⇒ 00:12:09.830 Uttam Kumaran: To deprecate, and then we’ll have to think through, like, what the plan is there.
130 00:12:10.070 ⇒ 00:12:13.920 Uttam Kumaran: Because if we just… if we do the swap, it’ll cause a ton of issues.
131 00:12:14.120 ⇒ 00:12:17.960 Uttam Kumaran: There’ll be some that are just the same exact name, so then it won’t be a problem.
132 00:12:21.240 ⇒ 00:12:22.459 Demilade Agboola: That sounds good.
133 00:12:22.460 ⇒ 00:12:23.180 Uttam Kumaran: Okay.
134 00:12:26.890 ⇒ 00:12:33.539 Uttam Kumaran: So I think the goal here… Create one column…
135 00:12:33.640 ⇒ 00:12:37.120 Uttam Kumaran: For old table, and one column.
136 00:12:37.910 ⇒ 00:12:39.660 Uttam Kumaran: Or a new table.
137 00:12:40.600 ⇒ 00:12:45.730 Uttam Kumaran: And matching the… Table, columns…
138 00:12:49.270 ⇒ 00:12:53.439 Uttam Kumaran: Or where to source… The new models from.
139 00:12:53.610 ⇒ 00:12:54.340 Uttam Kumaran: Okay.
140 00:12:54.820 ⇒ 00:13:02.960 Uttam Kumaran: Okay, great. So all these make sense.
141 00:13:03.210 ⇒ 00:13:07.240 Uttam Kumaran: What is this item? Emily, this is yours.
142 00:13:10.210 ⇒ 00:13:12.440 Emily Giant: Oh, yeah, okay, so that’s…
143 00:13:12.640 ⇒ 00:13:22.389 Emily Giant: is probably gonna be a dev fix at the end of the day. I have a Jira ticket, but, like, there’s 49,000 orders marked as unfulfilled, and…
144 00:13:22.520 ⇒ 00:13:29.160 Emily Giant: the way that we have… I… like, the way that we have created the revenue mart, like, there’s…
145 00:13:29.280 ⇒ 00:13:43.150 Emily Giant: the absolute column is, like, what’s fulfilled, and if these aren’t getting successfully fulfilled in Shopify, then our revenue numbers are really off. So I created that to track the progress in that JIRA ticket, so that we know when
146 00:13:43.810 ⇒ 00:13:48.759 Emily Giant: We can actually, like, successfully validate, revenue.
147 00:13:51.190 ⇒ 00:13:57.970 Emily Giant: But we don’t do anything here, we just need to know when it’s fixed, or we’re gonna be spinning our wheels, trying to figure out why revenue is off.
148 00:13:58.290 ⇒ 00:13:59.030 Uttam Kumaran: Okay
149 00:14:07.880 ⇒ 00:14:09.620 Uttam Kumaran: Okay,
150 00:14:16.660 ⇒ 00:14:18.930 Uttam Kumaran: Okay, so I’m just gonna move that to blocked.
151 00:14:19.200 ⇒ 00:14:23.420 Uttam Kumaran: Anything else we want to move into this sprint that is, like, super high?
152 00:14:24.740 ⇒ 00:14:25.860 Uttam Kumaran: Priority?
153 00:14:30.340 ⇒ 00:14:33.079 Uttam Kumaran: So, we’ll get… we’ll get plans on GA.
154 00:14:33.720 ⇒ 00:14:34.450 Emily Giant: Hmm.
155 00:14:37.580 ⇒ 00:14:41.710 Emily Giant: No, I think we just really need to… get revenue.
156 00:14:41.990 ⇒ 00:14:47.760 Emily Giant: correct and reliable, and that’s, like, my main, main… concern.
157 00:14:54.810 ⇒ 00:14:55.400 Uttam Kumaran: Okay.
158 00:15:06.630 ⇒ 00:15:12.089 Uttam Kumaran: But I still… I still see these two, like, here that are, like, logic for revenue prepaid versus.
159 00:15:12.340 ⇒ 00:15:16.870 Emily Giant: Yeah, that one we can add to the Sprint. I thought it was already in the sprint, sorry.
160 00:15:16.870 ⇒ 00:15:17.470 Uttam Kumaran: Okay.
161 00:15:21.740 ⇒ 00:15:23.100 Uttam Kumaran: And then this one, too.
162 00:15:26.090 ⇒ 00:15:32.160 Emily Giant: Update, explore… I think… Yeah, have y’all been able to validate that table?
163 00:15:32.800 ⇒ 00:15:36.350 Uttam Kumaran: Yeah, Oasis actually found a couple of issues.
164 00:15:36.550 ⇒ 00:15:37.300 Emily Giant: Okay.
165 00:15:37.530 ⇒ 00:15:38.300 Awaish Kumar: Excuse me.
166 00:15:38.940 ⇒ 00:15:39.490 Uttam Kumaran: Yeah.
167 00:15:39.780 ⇒ 00:15:51.830 Awaish Kumar: transactions, and I only found duplicates, and and I think, like, we had… We have duplicate,
168 00:15:52.120 ⇒ 00:15:57.889 Awaish Kumar: based on order ID. But when I see the amount, and, like.
169 00:15:58.080 ⇒ 00:16:05.130 Awaish Kumar: If we consider it as a payment transaction, then it might be a… like, we will have multiple rows per order.
170 00:16:06.160 ⇒ 00:16:08.350 Awaish Kumar: For transaction, we have just one row.
171 00:16:09.410 ⇒ 00:16:11.139 Awaish Kumar: Like, if you look at the…
172 00:16:11.460 ⇒ 00:16:18.079 Awaish Kumar: Transaction type, amount, like, then it makes it clear that, like, this is something different.
173 00:16:18.520 ⇒ 00:16:20.110 Awaish Kumar: Different transaction.
174 00:16:21.150 ⇒ 00:16:21.850 Emily Giant: Okay.
175 00:16:25.260 ⇒ 00:16:33.150 Awaish Kumar: But I don’t know why, like… so we have… I had one order where one transaction type is authorization.
176 00:16:33.440 ⇒ 00:16:36.619 Awaish Kumar: Red amount shows $30.
177 00:16:36.870 ⇒ 00:16:41.899 Awaish Kumar: Then the… Same order ID, but another transaction.
178 00:16:42.010 ⇒ 00:16:48.660 Awaish Kumar: With a transition type is payment, and it’s $100, so things like that.
179 00:16:49.350 ⇒ 00:16:51.860 Awaish Kumar: The state was successful for all of them.
180 00:16:52.130 ⇒ 00:16:59.269 Emily Giant: Okay. If you want to send me any examples or, like, huddle or something, just so we can, like, knock out those things, let me know, because…
181 00:16:59.640 ⇒ 00:17:07.000 Emily Giant: They might be things that are like, oh, that’s a gift card, or oh, that’s, you know, something that’s obvious to me just from working here.
182 00:17:07.200 ⇒ 00:17:08.569 Emily Giant: Yeah, just let me know.
183 00:17:10.099 ⇒ 00:17:19.129 Awaish Kumar: Yeah, I can send you the examples, but I just want to make, like, I want to make a note that, like, we are not considering them as a…
184 00:17:19.349 ⇒ 00:17:23.049 Awaish Kumar: Single row per order, it’s single row per transaction, and.
185 00:17:24.119 ⇒ 00:17:26.090 Awaish Kumar: The router might have multiple transactions.
186 00:17:26.230 ⇒ 00:17:26.859 Emily Giant: Okay.
187 00:17:27.220 ⇒ 00:17:29.079 Emily Giant: That’s fine. As long as there’s, like.
188 00:17:29.420 ⇒ 00:17:35.050 Emily Giant: an identifying factor that says it’s a unique line, then that makes sense to me.
189 00:17:35.050 ⇒ 00:17:35.530 Awaish Kumar: the.
190 00:17:35.530 ⇒ 00:17:36.180 Emily Giant: Yeah.
191 00:17:36.480 ⇒ 00:17:43.270 Amber Lin: Hi guys, I need to use this meeting room for another call. Is it okay if you guys huddle, and if there’s anything else? Yeah, that’s fine.
192 00:17:43.270 ⇒ 00:17:44.000 Uttam Kumaran: Yeah, that’s how.
193 00:17:44.000 ⇒ 00:17:44.640 Amber Lin: Sounds good.
194 00:17:44.950 ⇒ 00:17:45.950 Uttam Kumaran: Okay, I’ll send one.