Meeting Title: Brainforge x Element Dashboard QA Sync Date: 2026-04-16 Meeting participants: Jasmin Multani, Advait Nandakumar Menon
WEBVTT
1 00:00:56.880 ⇒ 00:00:57.740 Advait Nandakumar Menon: Hey!
2 00:01:00.010 ⇒ 00:01:01.120 Jasmin Multani: How are you feeling?
3 00:01:02.310 ⇒ 00:01:03.880 Advait Nandakumar Menon: Doing good, how about you?
4 00:01:05.219 ⇒ 00:01:08.399 Jasmin Multani: What are your reactions from the meeting?
5 00:01:10.110 ⇒ 00:01:12.010 Advait Nandakumar Menon: It’s…
6 00:01:12.140 ⇒ 00:01:20.200 Advait Nandakumar Menon: It’s like… it reminds me of that message I sent to you on Tuesday. I feel like she just wants to see the table on a spreadsheet just…
7 00:01:20.490 ⇒ 00:01:26.880 Advait Nandakumar Menon: ported over to Omni, and I don’t think she cares about the visualizations or whatever, like…
8 00:01:27.120 ⇒ 00:01:40.079 Advait Nandakumar Menon: in my opinion, dashboards aren’t for tables, like, I don’t know where you stand on that, but I don’t… it’s one thing you want to put a details tab or whatever, and want to zoom into the data from the visual, but…
9 00:01:40.470 ⇒ 00:01:54.420 Advait Nandakumar Menon: just having tables as visuals is another thing, but it’s her expectation, so we can only serve according to that, but yeah, she just wants that in the dashboard, and want to be able to talk to the data using Blobbies.
10 00:01:54.650 ⇒ 00:01:58.209 Advait Nandakumar Menon: how I understood her expectation for the dashboard.
11 00:02:00.170 ⇒ 00:02:11.339 Jasmin Multani: Yeah, I agree. It sounds like she wants to migrate out of the spreadsheets so that people are not overwriting the spreadsheets, not deleting the formulas.
12 00:02:13.980 ⇒ 00:02:28.689 Jasmin Multani: she does… she… in her… in our last Brain Forge and Element conversation with the broader team, she is, like, leaning on Blobby today. She’s, like, stress testing Blobby itself today.
13 00:02:28.930 ⇒ 00:02:36.210 Jasmin Multani: And she… is, like, notating, like, at what point can she trust Blobby?
14 00:02:36.320 ⇒ 00:02:40.010 Jasmin Multani: And she is, like, I think right now she…
15 00:02:40.730 ⇒ 00:02:53.710 Jasmin Multani: at this stage, she trusts the tables because, she has a counterpart in spreadsheets. So I think that’s why she wants her initial… initial stab to be…
16 00:02:54.890 ⇒ 00:03:03.830 Jasmin Multani: the table migration. And then she walked us through how she’s, trying to build graphs on Blobby.
17 00:03:03.890 ⇒ 00:03:16.689 Jasmin Multani: And it’s clear that she can’t rely on Blobby to make graphs, but, so maybe that’s, like, where we soup in. But she also talked about how she wants those stacked graphs to look like
18 00:03:16.970 ⇒ 00:03:17.690 Jasmin Multani: So…
19 00:03:17.810 ⇒ 00:03:18.470 Advait Nandakumar Menon: Yeah.
20 00:03:18.470 ⇒ 00:03:20.840 Jasmin Multani: I will say she has, like, a…
21 00:03:21.480 ⇒ 00:03:25.700 Jasmin Multani: opinions on graphs, but I don’t think she realizes…
22 00:03:27.400 ⇒ 00:03:45.349 Jasmin Multani: how to, how to portray it, or convey it out to people, because she had to do, like, several questions until she kind of got to the graph answer through Blobby, and I’m like, okay, we may literally just have to, like.
23 00:03:46.040 ⇒ 00:03:48.339 Jasmin Multani: Use a whiteboard.
24 00:03:48.890 ⇒ 00:03:51.100 Jasmin Multani: And draw it out for her.
25 00:03:51.260 ⇒ 00:03:57.600 Jasmin Multani: And even when I’m… because I had also asked her to, like, review the spec, And…
26 00:03:57.600 ⇒ 00:04:00.840 Advait Nandakumar Menon: Yeah, I think she agreed on the… no? Okay.
27 00:04:00.840 ⇒ 00:04:09.749 Jasmin Multani: she said… she said, like, oh yeah, it’s good, and I’m like, did you… I don’t think she read it. Like, I was like, did she read it? Like, I… I also, again…
28 00:04:10.380 ⇒ 00:04:19.009 Jasmin Multani: specific… because she waved it off, being like, oh, yeah, I don’t think we need to, like, drill down. I think, visual is, like, what I care about, and I’m like, okay, cool.
29 00:04:19.200 ⇒ 00:04:30.350 Jasmin Multani: And then, when I asked her in the Slack, like, give me feedback, and like, please refer to these P0 questions, this is where you can find them in the spec sheet. I don’t think she referred that, I think she literally just, like.
30 00:04:30.990 ⇒ 00:04:32.059 Jasmin Multani: Pulled up a dashboard.
31 00:04:32.060 ⇒ 00:04:32.590 Advait Nandakumar Menon: but definitely…
32 00:04:32.590 ⇒ 00:04:38.739 Jasmin Multani: 10 minutes, gave feedback. So that also is information for me.
33 00:04:38.990 ⇒ 00:04:42.769 Jasmin Multani: Because that means, during the spec development phase.
34 00:04:43.000 ⇒ 00:04:55.739 Jasmin Multani: That is when we, or I, sit down, and I’m like, this is what the rows are gonna look like, this is what the column is gonna look like, and literally whiteboard it with her. These are the graphs.
35 00:04:55.740 ⇒ 00:04:56.180 Advait Nandakumar Menon: Hmm.
36 00:04:56.180 ⇒ 00:05:02.999 Jasmin Multani: And this is how the information maps to the core question that you’re charging dollars for us.
37 00:05:03.120 ⇒ 00:05:10.550 Jasmin Multani: So that’s feedback for me. I think the reason why there’s so much back and forth in this QA session is because we never did that initial…
38 00:05:11.130 ⇒ 00:05:11.860 Advait Nandakumar Menon: Right.
39 00:05:11.860 ⇒ 00:05:31.360 Jasmin Multani: initial agreement, like… and I think that’s also what… it sounds like that’s what Awesh also wants when he asks for specs, because I was like, yeah, this is… these are the cuts. And he’s like, I think, we had a conversation, and I’m like, okay, I think I need to develop, like.
40 00:05:32.980 ⇒ 00:05:46.990 Jasmin Multani: a mock-up of a… I think it’d be clearest if I developed a mock-up of a table, and a mock-up of a chart, and just was like, hey, this is data I’ve made up, I just want you to align on the x-axis and the y-axis.
41 00:05:48.700 ⇒ 00:05:51.950 Jasmin Multani: So, I also don’t know, like.
42 00:05:52.650 ⇒ 00:05:56.900 Jasmin Multani: I think line charts are fine, but I think she has her own opinions.
43 00:05:59.070 ⇒ 00:06:03.700 Jasmin Multani: I can see why she was like, why would you do line charts?
44 00:06:04.670 ⇒ 00:06:09.970 Jasmin Multani: Fine. Fine, fine, fine. But… okay.
45 00:06:10.310 ⇒ 00:06:11.370 Jasmin Multani: Cool.
46 00:06:12.920 ⇒ 00:06:18.860 Jasmin Multani: Hopefully… oh, and the other thing, I talked to her about, like, when she brought up Blobby.
47 00:06:19.320 ⇒ 00:06:27.230 Jasmin Multani: I was like, yeah, I know Greg is cueing Blobby in his own versions of questioning, but I told…
48 00:06:27.490 ⇒ 00:06:39.880 Jasmin Multani: told her, like, oh, Advith and I, have a plan where once we’re done with, like, the visuals for dashboarding, we’re gonna move towards stress testing the blobby.
49 00:06:40.020 ⇒ 00:06:44.549 Jasmin Multani: where we’re literally documenting, hey, A-B testing.
50 00:06:44.790 ⇒ 00:06:49.759 Jasmin Multani: This is the question we asked. This is the expected answer we have.
51 00:06:50.270 ⇒ 00:06:53.270 Jasmin Multani: This is what Blobby gave us.
52 00:06:53.420 ⇒ 00:06:56.569 Jasmin Multani: And from there, if there’s misalignment.
53 00:06:56.760 ⇒ 00:07:00.480 Jasmin Multani: Then we’re gonna root cause, like, okay, was this…
54 00:07:01.730 ⇒ 00:07:13.159 Jasmin Multani: was this because we didn’t structure the question correctly? Was it because, our semantics labeling is not accurate? Or, maybe blobby is just not working well.
55 00:07:13.270 ⇒ 00:07:16.630 Jasmin Multani: So, I think she was very excited for that.
56 00:07:18.420 ⇒ 00:07:25.359 Jasmin Multani: So if we… but I had told her, I think in her mind, QAing a dashboard is, like, including
57 00:07:25.880 ⇒ 00:07:29.379 Jasmin Multani: The dashboard and the blobby.
58 00:07:29.910 ⇒ 00:07:30.560 Advait Nandakumar Menon: Okay.
59 00:07:30.560 ⇒ 00:07:34.460 Jasmin Multani: Whereas queuing, for me, I’ve been breaking it up as to, like.
60 00:07:34.700 ⇒ 00:07:48.890 Jasmin Multani: QA the dashboard itself, QA the blobby separately, QA, data integrity separately. Like, I want bite sizes of each ramping up, whereas she’s doing everything all at once, and…
61 00:07:49.410 ⇒ 00:07:56.510 Jasmin Multani: In my opinion, I think the framework is, like, data integrity, from, like.
62 00:07:56.670 ⇒ 00:07:59.310 Jasmin Multani: How integrat… what is the integrity?
63 00:08:00.230 ⇒ 00:08:04.149 Jasmin Multani: Versus the spreadsheets they’re using today.
64 00:08:04.490 ⇒ 00:08:10.359 Jasmin Multani: What is the visual cuts that help them make, data decision… data decisions?
65 00:08:10.550 ⇒ 00:08:17.930 Jasmin Multani: And then, like, lobby testing. I would want to have things accurate in that pyramid.
66 00:08:18.450 ⇒ 00:08:21.490 Jasmin Multani: Before signing off, and it sounds like she’s doing all three at once.
67 00:08:21.880 ⇒ 00:08:28.839 Jasmin Multani: Which, in my opinion, I would rather use the ramp-up rather than doing all things at once. How do you…
68 00:08:28.840 ⇒ 00:08:29.620 Advait Nandakumar Menon: Yeah, no.
69 00:08:29.750 ⇒ 00:08:37.280 Advait Nandakumar Menon: Of course, yeah, like… I don’t think putting it all together at once and trying to…
70 00:08:37.429 ⇒ 00:08:42.999 Advait Nandakumar Menon: look at the pieces together won’t work out, like… there is a high possibility of failure.
71 00:08:43.130 ⇒ 00:08:45.439 Advait Nandakumar Menon: If you go with that.
72 00:08:45.670 ⇒ 00:08:55.650 Advait Nandakumar Menon: So, I also tend to agree with you, like, splitting it into buckets and doing it one by one, and then consolidating it at the end would be a…
73 00:08:56.060 ⇒ 00:08:59.770 Advait Nandakumar Menon: Better approach, but… I’m not sure…
74 00:09:00.390 ⇒ 00:09:04.139 Advait Nandakumar Menon: How to make her that… understand that, or how…
75 00:09:05.140 ⇒ 00:09:24.090 Jasmin Multani: I think we just have to tell her. I think… I think… I don’t think we’ve been clear. Like, even with the pilot thing, she’s like, let’s… why are we using this conversation? We’re like, that’s literally the accelerator that we all signed off on. Like, it literally says, wholesale and retail, want to do dashboards each, what are you talking about? When did you make this decision?
76 00:09:24.190 ⇒ 00:09:25.530 Jasmin Multani: So…
77 00:09:25.530 ⇒ 00:09:26.730 Advait Nandakumar Menon: And even…
78 00:09:26.880 ⇒ 00:09:36.089 Advait Nandakumar Menon: Yeah, even in today’s call, like, she started, like, you were trying to go by the measurement logic first, and then the visual logic, but she was like, no, let’s look at it together.
79 00:09:36.300 ⇒ 00:09:43.300 Advait Nandakumar Menon: Yeah, so… I think that’s how she thinks about this whole thing, so… I don’t think…
80 00:09:43.900 ⇒ 00:09:48.190 Advait Nandakumar Menon: That’s sustainable, but… Yeah.
81 00:09:48.190 ⇒ 00:09:52.159 Jasmin Multani: I think she’s taking a top-down approach, whereas we’re, I feel like.
82 00:09:52.970 ⇒ 00:10:01.630 Jasmin Multani: when we’re setting up things, like going from the backend to UX design, I prefer things to be from the bottom up. Like, literally.
83 00:10:01.630 ⇒ 00:10:02.080 Advait Nandakumar Menon: Yeah.
84 00:10:02.080 ⇒ 00:10:11.390 Jasmin Multani: Comparing it with the SQL queries, being like, did our drag-and-drop, BI tool accurately do what I told it… wanted it to do?
85 00:10:13.030 ⇒ 00:10:17.489 Jasmin Multani: I’m also trying to figure out the data sources as well, and I’m like, I…
86 00:10:17.490 ⇒ 00:10:18.130 Advait Nandakumar Menon: Yep.
87 00:10:18.130 ⇒ 00:10:19.949 Jasmin Multani: So, thank you for being patient there.
88 00:10:20.200 ⇒ 00:10:21.660 Advait Nandakumar Menon: Nope, nope, for sure.
89 00:10:22.690 ⇒ 00:10:35.410 Jasmin Multani: Okay, so next 15-ish minutes, I wanted to go over… Prioritizing.
90 00:10:36.940 ⇒ 00:10:37.860 Jasmin Multani: So…
91 00:10:37.860 ⇒ 00:10:38.460 Advait Nandakumar Menon: Yeah.
92 00:10:39.950 ⇒ 00:10:44.300 Jasmin Multani: Let’s go over… So…
93 00:10:48.280 ⇒ 00:10:49.210 Jasmin Multani: 4 o’clock.
94 00:10:51.050 ⇒ 00:10:56.280 Jasmin Multani: So… let’s base it off of, like, how annoyed she was.
95 00:10:57.930 ⇒ 00:11:03.910 Jasmin Multani: So… measurement logic, she’s like, I’ve been asking you about this multiple times.
96 00:11:04.150 ⇒ 00:11:06.410 Jasmin Multani: We’ll keep this deleted from now.
97 00:11:06.670 ⇒ 00:11:16.729 Jasmin Multani: In the fall… in the last meeting that we had, she then added, like, oh, you know, but having revenue as part of
98 00:11:17.010 ⇒ 00:11:36.049 Jasmin Multani: a budget, that would be helpful, and I’m like, well, we… I was like, okay, yeah, that’s great context. But, like, we already decided to delete it, what the hell? So… feedback on how she thinks is, like, she doesn’t like standalone numbers, like, total, total numbers. She likes it
99 00:11:37.310 ⇒ 00:11:41.289 Jasmin Multani: Against a… against some sort of context, like…
100 00:11:41.850 ⇒ 00:11:42.320 Advait Nandakumar Menon: Okay.
101 00:11:42.320 ⇒ 00:11:50.010 Jasmin Multani: She’s like, if it were the last month, that’d be great, but, like, running total doesn’t make sense, unless it’s, like, running total against budget, and I’m like.
102 00:11:50.680 ⇒ 00:11:54.220 Jasmin Multani: it’s your dashboard. It’s… it’s a dashboard. You can make it…
103 00:11:54.960 ⇒ 00:11:59.590 Jasmin Multani: However, like, I’ve been in rooms where VPs were like, I want the running total.
104 00:12:00.220 ⇒ 00:12:00.580 Advait Nandakumar Menon: Who knew?
105 00:12:00.580 ⇒ 00:12:06.160 Jasmin Multani: for the year, and I’m like, cool. It’s literally your decision. Yeah, yeah.
106 00:12:06.740 ⇒ 00:12:13.000 Jasmin Multani: So, there’s that. So, this has been deleted, so I’m gonna say, call this as done.
107 00:12:17.670 ⇒ 00:12:19.480 Jasmin Multani: Done!
108 00:12:20.940 ⇒ 00:12:25.249 Jasmin Multani: Just make it visual, just make the top show, but…
109 00:12:25.660 ⇒ 00:12:29.140 Jasmin Multani: I’ll let you decide that. Yep.
110 00:12:30.180 ⇒ 00:12:33.130 Jasmin Multani: I don’t know if I published it. I don’t remember if I published it.
111 00:12:33.130 ⇒ 00:12:35.430 Advait Nandakumar Menon: I don’t… yeah, I think it’ll be in draft.
112 00:12:36.010 ⇒ 00:12:36.840 Jasmin Multani: Yeah.
113 00:12:37.680 ⇒ 00:12:47.970 Jasmin Multani: Just delete… delete the metric summary tiles, and make the, green… Refresh us.
114 00:12:48.990 ⇒ 00:12:49.760 Jasmin Multani: Cool.
115 00:12:53.540 ⇒ 00:12:55.720 Jasmin Multani: Yeah.
116 00:12:55.920 ⇒ 00:12:59.880 Jasmin Multani: So the wholesale revenue trend… we said that was… you called that one.
117 00:13:32.220 ⇒ 00:13:37.110 Jasmin Multani: Okay, so these two get deleted. This is smaller, probably up here.
118 00:13:37.570 ⇒ 00:13:39.959 Jasmin Multani: At the same level of the filters.
119 00:13:40.290 ⇒ 00:13:42.420 Jasmin Multani: You extend this out?
120 00:13:43.300 ⇒ 00:13:47.020 Jasmin Multani: And then, she definitely wants rubbing, like.
121 00:13:47.670 ⇒ 00:13:51.670 Jasmin Multani: So, trying to, like, figure out what you had said. You had said that
122 00:13:53.390 ⇒ 00:13:57.729 Jasmin Multani: The source, the data source, is not really revenue, it’s sales.
123 00:13:58.390 ⇒ 00:14:04.780 Advait Nandakumar Menon: Yeah, it says sales, but yeah, I termed it as revenue in the topics and the views.
124 00:14:04.880 ⇒ 00:14:10.599 Advait Nandakumar Menon: According to the spec, so do we change that back?
125 00:14:10.970 ⇒ 00:14:23.139 Jasmin Multani: Let’s change, change, revenue… If it… okay, if the topic… if the raw data says sales, Right, sales.
126 00:14:23.140 ⇒ 00:14:24.820 Advait Nandakumar Menon: Avda sales, yeah, okay.
127 00:14:25.110 ⇒ 00:14:26.720 Jasmin Multani: Okay, so this is important.
128 00:14:26.920 ⇒ 00:14:31.999 Jasmin Multani: We also need to measure out… we also have to, context.
129 00:14:32.220 ⇒ 00:14:34.140 Jasmin Multani: Add the sales context.
130 00:14:35.900 ⇒ 00:14:44.390 Jasmin Multani: I’m just like, sales is sales. What do you mean? But, if we can ask Awayish.
131 00:14:44.760 ⇒ 00:14:53.280 Jasmin Multani: Like, do you know how the… is the sales reflective of raw sales, like, net?
132 00:14:53.550 ⇒ 00:14:58.199 Jasmin Multani: gross… Is it inclusive of discounts? Do we know that?
133 00:15:00.830 ⇒ 00:15:10.459 Advait Nandakumar Menon: I think it’s total sales, but I’m not sure with respect to wholesale, but for retail, I have split out the definition.
134 00:15:10.870 ⇒ 00:15:25.210 Advait Nandakumar Menon: Like, even if you ask Blobby today, like, retail, it’ll say, like, it’s just POS, and it doesn’t have any refund or revenue or whatever. So, that clarity is there for retail. For wholesale, I am…
135 00:15:25.510 ⇒ 00:15:28.209 Advait Nandakumar Menon: I’m not 100% sure.
136 00:15:28.610 ⇒ 00:15:32.490 Jasmin Multani: Okay, so… Let’s chat with,
137 00:15:32.850 ⇒ 00:15:35.720 Jasmin Multani: It’s defined in the raw table.
138 00:15:36.090 ⇒ 00:15:44.110 Jasmin Multani: So let’s ask… by Jasmine, to Alice, Greg, and Bill Gates, because they’ve been here within us.
139 00:15:44.590 ⇒ 00:15:47.409 Jasmin Multani: I’m also gonna make these into chat, come on.
140 00:15:50.520 ⇒ 00:15:54.160 Jasmin Multani: And then I’m gonna put these in, linear.
141 00:15:54.670 ⇒ 00:15:56.320 Advait Nandakumar Menon: Yeah, yeah, yeah.
142 00:15:57.220 ⇒ 00:16:01.589 Jasmin Multani: So measurement logic, wholesale revenue, wholesale… okay, so…
143 00:16:02.270 ⇒ 00:16:10.280 Jasmin Multani: This is something that I had asked, like, We should… ask Awayish, right?
144 00:16:19.120 ⇒ 00:16:30.190 Jasmin Multani: Consistent capitalization of values… Wholesale revenue product. What does other represent decide to drop off the leash?
145 00:16:37.370 ⇒ 00:16:39.420 Jasmin Multani: Then, like, she just doesn’t want the total.
146 00:16:39.880 ⇒ 00:16:40.770 Jasmin Multani: Which…
147 00:16:41.930 ⇒ 00:16:49.319 Advait Nandakumar Menon: Yeah, so… That table, it’s currently showing the total revenue, like, not just the top 20, like.
148 00:16:49.820 ⇒ 00:16:57.049 Advait Nandakumar Menon: the overall revenue and the overall percentage. So, if she wants it to be just the total of the top 20,
149 00:16:57.150 ⇒ 00:17:04.030 Advait Nandakumar Menon: And the percentage of the top 20, we can do that. We can remove the total altogether as well.
150 00:17:06.079 ⇒ 00:17:25.729 Advait Nandakumar Menon: But in order to calculate the percentage of revenue, it needs the total value to be in the table, so that’s a limitation I came across in Omni, like, the total should be present at the bottom so that it can calculate the percentage of the total, so…
151 00:17:26.410 ⇒ 00:17:30.289 Advait Nandakumar Menon: That’s one reason I was forced to put the total there, but…
152 00:17:31.220 ⇒ 00:17:38.910 Advait Nandakumar Menon: If she says only the top 20s total, or percentage of the top 20’s total is enough, then we can… I can try to do that as well.
153 00:17:39.340 ⇒ 00:17:41.350 Jasmin Multani: Yeah, we can either…
154 00:17:41.760 ⇒ 00:17:49.580 Jasmin Multani: Try to hide that, but if we can’t, then let’s just relabel what total means, and just literally say total of…
155 00:17:50.290 ⇒ 00:17:54.860 Jasmin Multani: This is, like, 100% means the top 20.
156 00:17:55.930 ⇒ 00:17:59.000 Jasmin Multani: Err… no, 100% was, like, all.
157 00:17:59.000 ⇒ 00:18:01.670 Advait Nandakumar Menon: 100% is all, yeah, yeah.
158 00:18:01.670 ⇒ 00:18:09.299 Jasmin Multani: Yeah, and she, she was like, yeah, if you add these all up together, it’s 28%, and I’m like, yeah, fuck, okay.
159 00:18:12.920 ⇒ 00:18:25.790 Jasmin Multani: Yeah, if… let’s try to hide it. If you can’t, we’ll call it out. Maybe we ask, the Omni partners directly, and be like, can we do… how do we do this?
160 00:18:26.020 ⇒ 00:18:27.050 Jasmin Multani: Okay.
161 00:18:30.510 ⇒ 00:18:32.560 Jasmin Multani: Also, want to point out…
162 00:18:32.560 ⇒ 00:18:35.429 Advait Nandakumar Menon: So, do you still want it to be the total of…
163 00:18:35.760 ⇒ 00:18:38.890 Advait Nandakumar Menon: All together, and not just the top 20, is that what you’re saying?
164 00:18:40.170 ⇒ 00:18:43.349 Jasmin Multani: She wants to… she wants to get rid of it completely.
165 00:18:44.470 ⇒ 00:18:45.430 Jasmin Multani: Right?
166 00:18:45.430 ⇒ 00:18:49.579 Advait Nandakumar Menon: Like… like, the percentage, as well as the total at the bottom?
167 00:18:55.190 ⇒ 00:19:03.280 Advait Nandakumar Menon: Because we have the percentage column, and that’s what I was saying. In order to calculate the percentage, we need the total at the bottom to do it, so…
168 00:19:04.910 ⇒ 00:19:12.700 Advait Nandakumar Menon: Right now, it’s calculating the percentage based on the total total, not just the top 20, like you said.
169 00:19:14.150 ⇒ 00:19:20.750 Advait Nandakumar Menon: So, that forces… I mean, necessitates the total to be at the bottom of the table.
170 00:19:21.800 ⇒ 00:19:24.929 Jasmin Multani: Yeah, I mean, I think it’s a good call, but, like.
171 00:19:25.260 ⇒ 00:19:40.210 Advait Nandakumar Menon: So, the 15 million you see here is not just the top 20, it’s the overall. And the percentage here, example, for the first row is, it’s 9.4% of the 15 million, so it’s not the 9.4% of the total of the top 20, so…
172 00:19:40.210 ⇒ 00:19:41.380 Jasmin Multani: There I go.
173 00:19:41.700 ⇒ 00:19:50.090 Advait Nandakumar Menon: And in order to calculate the 9.4%, the 15 million should be present in the visual right here, as you see.
174 00:19:50.460 ⇒ 00:19:51.540 Jasmin Multani: Oh, okay.
175 00:19:51.880 ⇒ 00:19:54.440 Advait Nandakumar Menon: Yeah, so that’s what I was trying to say.
176 00:19:54.600 ⇒ 00:20:02.759 Jasmin Multani: Yeah… I’m just trying to… yeah, if she says she doesn’t really care about the percentage, then fine. Like…
177 00:20:03.440 ⇒ 00:20:17.919 Advait Nandakumar Menon: Or I can try to do it, like, instead of 15 million of all together, I can do the sum of the top 20, and the percentage will be, of the top 20 sum. So, maybe I can try to do that.
178 00:20:19.780 ⇒ 00:20:23.799 Jasmin Multani: This is verbatim what she wrote, and when I read this, she literally.
179 00:20:25.690 ⇒ 00:20:30.490 Advait Nandakumar Menon: Yeah, she asked to remove it, and she also said the other way, but…
180 00:20:30.820 ⇒ 00:20:34.219 Advait Nandakumar Menon: I can do it all. What do you recommend?
181 00:20:36.910 ⇒ 00:20:39.359 Advait Nandakumar Menon: Cutting it off is probably easier than what you’re gonna.
182 00:20:39.360 ⇒ 00:20:40.189 Jasmin Multani: Yeah, I mean, like.
183 00:20:40.190 ⇒ 00:20:40.880 Advait Nandakumar Menon: Should we…
184 00:20:41.030 ⇒ 00:20:43.190 Jasmin Multani: Cut this out and this?
185 00:20:45.750 ⇒ 00:20:46.580 Advait Nandakumar Menon: like…
186 00:20:46.580 ⇒ 00:20:46.920 Jasmin Multani: I mean.
187 00:20:46.920 ⇒ 00:20:51.490 Advait Nandakumar Menon: the, yeah, that column and the total.
188 00:20:52.440 ⇒ 00:20:53.250 Jasmin Multani: Yeah.
189 00:20:53.970 ⇒ 00:20:55.410 Advait Nandakumar Menon: Yeah, I can do that.
190 00:21:01.440 ⇒ 00:21:04.959 Jasmin Multani: Should we just, like… maybe I should just send a screenshot.
191 00:21:05.460 ⇒ 00:21:08.200 Jasmin Multani: And literally scribble this out.
192 00:21:09.010 ⇒ 00:21:12.729 Jasmin Multani: fucking now, but she’s not gonna be happy about that.
193 00:21:13.560 ⇒ 00:21:15.989 Jasmin Multani: Let me just follow up on Luther on this.
194 00:21:16.820 ⇒ 00:21:17.450 Advait Nandakumar Menon: Okay.
195 00:21:18.900 ⇒ 00:21:19.920 Jasmin Multani: Follow up…
196 00:21:24.870 ⇒ 00:21:32.180 Jasmin Multani: She was also like, what value does it offer? And I’m like, it does offer a value. You want to know who you’re…
197 00:21:32.750 ⇒ 00:21:34.930 Jasmin Multani: Top contenders are and how much they’re burning.
198 00:21:35.420 ⇒ 00:21:41.220 Jasmin Multani: Offer mock-ups.
199 00:21:43.120 ⇒ 00:21:44.340 Jasmin Multani: For…
200 00:21:44.340 ⇒ 00:21:50.439 Advait Nandakumar Menon: Yeah, now that I think about it, percentage of the top 20-some doesn’t make sense, like…
201 00:21:50.920 ⇒ 00:21:56.420 Advait Nandakumar Menon: You want to know how much of a total revenue they are… Contributing, right?
202 00:21:56.800 ⇒ 00:21:57.740 Advait Nandakumar Menon: Aye.
203 00:21:58.820 ⇒ 00:21:59.900 Advait Nandakumar Menon: Yes.
204 00:22:01.150 ⇒ 00:22:02.400 Jasmin Multani: It’s her world.
205 00:22:03.370 ⇒ 00:22:04.450 Jasmin Multani: It’s her world.
206 00:22:04.730 ⇒ 00:22:13.080 Jasmin Multani: But I’ll give her some mock-ups and be like, you don’t want the total, right? Like, this is total equals, like.
207 00:22:13.900 ⇒ 00:22:18.410 Jasmin Multani: Everything, and wholesale… is this, like, running total?
208 00:22:18.810 ⇒ 00:22:20.140 Jasmin Multani: of all time.
209 00:22:21.290 ⇒ 00:22:24.040 Advait Nandakumar Menon: Yeah, it’s a thumb, it’s just a thumb, yeah.
210 00:22:24.320 ⇒ 00:22:25.580 Jasmin Multani: Of all time, yeah.
211 00:22:26.380 ⇒ 00:22:30.720 Jasmin Multani: Okay, I’ll send her a mock-up and then tag you in it.
212 00:22:30.900 ⇒ 00:22:31.589 Jasmin Multani: I’ll still…
213 00:22:31.590 ⇒ 00:22:35.860 Advait Nandakumar Menon: I wouldn’t say it’s all-time, I think it depends on the…
214 00:22:36.110 ⇒ 00:22:40.250 Advait Nandakumar Menon: date filter I’ve applied over the… I think it’s the last 6 months.
215 00:22:41.230 ⇒ 00:22:45.160 Advait Nandakumar Menon: Like, that 15 million there and this one over here should match up, yeah.
216 00:22:45.450 ⇒ 00:22:47.289 Jasmin Multani: Oh, yeah, yeah, okay, good call.
217 00:22:47.780 ⇒ 00:22:48.590 Advait Nandakumar Menon: Yeah.
218 00:22:50.680 ⇒ 00:22:53.420 Jasmin Multani: Okay, cool, that’s the last one.
219 00:22:53.600 ⇒ 00:23:04.409 Jasmin Multani: So how would we rank… so between… okay, and then we have to add these net new, and she said if, it’s already in one, don’t bother putting in others, right?
220 00:23:05.260 ⇒ 00:23:07.979 Advait Nandakumar Menon: Yeah, she didn’t really care about this dashboard.
221 00:23:26.140 ⇒ 00:23:31.889 Jasmin Multani: She talked about it being about, like, oh, this is similar to customer behavior.
222 00:23:33.520 ⇒ 00:23:34.210 Advait Nandakumar Menon: Yeah.
223 00:23:34.540 ⇒ 00:23:36.200 Jasmin Multani: She for sure wants something.
224 00:23:37.270 ⇒ 00:23:38.960 Jasmin Multani: I’m sorry, not too late. Okay.
225 00:23:39.090 ⇒ 00:23:45.120 Jasmin Multani: Also, as I’m cutting this, because she said, oh, I only expect this to be done by May.
226 00:23:45.300 ⇒ 00:23:48.589 Jasmin Multani: end of May, maybe, what we do is, like, we…
227 00:23:48.910 ⇒ 00:23:52.810 Jasmin Multani: Really work on one dashboard per day.
228 00:23:53.340 ⇒ 00:23:54.110 Advait Nandakumar Menon: Huh.
229 00:23:54.110 ⇒ 00:23:56.919 Jasmin Multani: Make sure it’s good, and then send it out to her.
230 00:23:57.060 ⇒ 00:24:08.800 Jasmin Multani: So, instead of saying queuing is done by end of week, because, hey, we’ve also now increased, she’s asking for another dashboard, I’m also gonna vocalize this over…
231 00:24:09.850 ⇒ 00:24:12.639 Jasmin Multani: So, Utam, and Robert.
232 00:24:13.490 ⇒ 00:24:21.380 Jasmin Multani: And be like, she wants a third dashboard now, and she wants it to look like this tech table. Yeah.
233 00:24:22.010 ⇒ 00:24:34.219 Jasmin Multani: So, I’m gonna say… I’m gonna extend our deadline, sure. …to get the dashboard QA, and I’m gonna tell her, hey, our QA isn’t… we’re doing QAing by, like.
234 00:24:34.540 ⇒ 00:24:42.660 Jasmin Multani: dashboard logic, dashboard visuals, and queuing blobby. So, I’m just letting her know that, like.
235 00:24:42.900 ⇒ 00:24:48.450 Jasmin Multani: We… we’re on the same page of what needs to be QA’d, but we’re dividing it up into chunks.
236 00:24:49.230 ⇒ 00:24:49.860 Advait Nandakumar Menon: Okay.
237 00:24:49.860 ⇒ 00:24:56.330 Jasmin Multani: And, like, I wanted to understand this, because supply chain… the supply chain dashboard is going to be crazy.
238 00:24:56.610 ⇒ 00:25:02.130 Jasmin Multani: And I want her to, like, get used to our method of validating.
239 00:25:03.260 ⇒ 00:25:05.340 Jasmin Multani: Because it’s literally…
240 00:25:05.480 ⇒ 00:25:09.599 Jasmin Multani: even she is like, I don’t know if we’re gonna get… be able to finish by June, and I’m like.
241 00:25:10.860 ⇒ 00:25:16.450 Jasmin Multani: Okay, yeah, I agree. But just a heads up, like, Yeah.
242 00:25:16.640 ⇒ 00:25:17.250 Jasmin Multani: I’ll cut the.
243 00:25:17.250 ⇒ 00:25:17.850 Advait Nandakumar Menon: Yep, nothing.
244 00:25:17.920 ⇒ 00:25:18.890 Jasmin Multani: Yeah, okay.
245 00:25:18.890 ⇒ 00:25:19.480 Advait Nandakumar Menon: Yep.
246 00:25:19.670 ⇒ 00:25:23.169 Jasmin Multani: So, since this is gonna be, like, a net new build.
247 00:25:24.460 ⇒ 00:25:32.340 Jasmin Multani: This is gonna take longer. So, let’s keep this… let’s do the pulse check as P0.
248 00:25:34.060 ⇒ 00:25:38.000 Jasmin Multani: This one as… P1.
249 00:25:38.730 ⇒ 00:25:39.310 Advait Nandakumar Menon: Okay.
250 00:25:39.310 ⇒ 00:25:40.070 Jasmin Multani: Right?
251 00:25:40.380 ⇒ 00:25:43.300 Jasmin Multani: And this one has P2. Reason.
252 00:25:43.300 ⇒ 00:25:44.030 Advait Nandakumar Menon: Okay.
253 00:25:45.360 ⇒ 00:25:50.560 Jasmin Multani: Our agreement for this contract was just… One to two dashboards.
254 00:25:51.130 ⇒ 00:25:51.810 Advait Nandakumar Menon: Huh.
255 00:25:51.810 ⇒ 00:25:55.830 Jasmin Multani: So if we’re gonna cut a dashboard, I guess we’re gonna cut this one.
256 00:25:56.330 ⇒ 00:25:59.580 Advait Nandakumar Menon: Yeah, because… Just the way she reacted, yeah.
257 00:25:59.580 ⇒ 00:26:07.250 Jasmin Multani: Yeah, yeah. And, I want Robert to know that she’s asking for a net new dashboard that we have now built from scratch.
258 00:26:07.560 ⇒ 00:26:12.520 Jasmin Multani: Yeah. Because she did not review the spec. She,
259 00:26:12.670 ⇒ 00:26:16.490 Jasmin Multani: Gave us a sign-off, but really didn’t read it.
260 00:26:16.640 ⇒ 00:26:22.959 Jasmin Multani: So, just know that I’ll be cutting 3 different tickets.
261 00:26:23.370 ⇒ 00:26:28.989 Jasmin Multani: for wholesale. But, be on the lookout of this possibly getting cut.
262 00:26:29.770 ⇒ 00:26:30.620 Advait Nandakumar Menon: Yep, yep.
263 00:26:31.030 ⇒ 00:26:44.879 Jasmin Multani: And now, also, based off of, like, what Robert and Utam say, if they’re like, our contract only says 2, then I’m gonna let Shivani know, like, hey, we’re gonna cut this one, but we’re gonna go forward with this.
264 00:26:45.360 ⇒ 00:26:46.990 Advait Nandakumar Menon: Yeah, yeah, fair enough.
265 00:26:47.460 ⇒ 00:26:56.199 Jasmin Multani: And also, in the meeting, in that follow-up, in the larger meeting that we had, She does expect…
266 00:26:56.620 ⇒ 00:27:06.569 Jasmin Multani: just to be iterative, and she wants to review one dashboard per day. She wants to go through a dashboard a day. I’m like, okay.
267 00:27:06.570 ⇒ 00:27:07.290 Advait Nandakumar Menon: Okay.
268 00:27:08.260 ⇒ 00:27:14.059 Jasmin Multani: So, tomorrow, just do an easy couple dashboards,
269 00:27:15.210 ⇒ 00:27:19.820 Jasmin Multani: Probably one of the retail dashboards, so that… because they’re… they look like an easier lift.
270 00:27:20.560 ⇒ 00:27:21.150 Advait Nandakumar Menon: Yep.
271 00:27:21.150 ⇒ 00:27:24.399 Jasmin Multani: And because, because we didn’t go through the retail ones today.
272 00:27:25.290 ⇒ 00:27:29.939 Advait Nandakumar Menon: Yeah, I would say the retail, Executive one.
273 00:27:30.170 ⇒ 00:27:37.430 Advait Nandakumar Menon: Like I said, it seems to align with the spreadsheet that she’s using. I hope she is happy by that, but…
274 00:27:39.070 ⇒ 00:27:41.940 Advait Nandakumar Menon: Yeah, she can also surpass, but let’s see.
275 00:27:44.220 ⇒ 00:27:46.909 Jasmin Multani: Which column? Which Titan is?
276 00:27:53.730 ⇒ 00:27:57.769 Jasmin Multani: Yeah, we didn’t get to ask her which… Table she wants.
277 00:27:58.790 ⇒ 00:28:03.970 Jasmin Multani: But does the funneling make sense of how she was describing this?
278 00:28:06.710 ⇒ 00:28:09.840 Jasmin Multani: Like, was it… was it clear what she really wanted?
279 00:28:10.810 ⇒ 00:28:16.580 Advait Nandakumar Menon: Yeah, it looks like she wanted to start at the higher level, and then load.
280 00:28:17.520 ⇒ 00:28:20.440 Advait Nandakumar Menon: Drill it down into category-wise, or…
281 00:28:21.210 ⇒ 00:28:26.540 Advait Nandakumar Menon: store-wise, or whatever, so that’s how I understood it as…
282 00:28:26.820 ⇒ 00:28:33.799 Advait Nandakumar Menon: Whether that’s possible in a tabular view with an Omni seems to be seen. That’s another thing we need to…
283 00:28:35.290 ⇒ 00:28:36.550 Advait Nandakumar Menon: Check…
284 00:28:37.100 ⇒ 00:28:37.860 Jasmin Multani: Yeah.
285 00:28:38.450 ⇒ 00:28:47.000 Jasmin Multani: From… if we can’t do that, what I think we should as…
286 00:28:49.320 ⇒ 00:28:51.430 Jasmin Multani: Is this the retail? Okay, wholesale.
287 00:28:54.790 ⇒ 00:28:55.540 Jasmin Multani: Is this still working?
288 00:28:55.540 ⇒ 00:29:01.089 Advait Nandakumar Menon: Because I was able to do what’s there on the second tab and the third tab.
289 00:29:01.250 ⇒ 00:29:06.710 Advait Nandakumar Menon: In a way, if you look at the executor, dashboard.
290 00:29:07.820 ⇒ 00:29:09.080 Advait Nandakumar Menon: of retail.
291 00:29:09.080 ⇒ 00:29:11.509 Jasmin Multani: Of retail.
292 00:29:17.700 ⇒ 00:29:18.809 Jasmin Multani: I mean, just…
293 00:29:36.820 ⇒ 00:29:39.880 Advait Nandakumar Menon: You can go to Shared.
294 00:29:40.650 ⇒ 00:29:43.040 Jasmin Multani: Sorry, I haven’t eaten, so I’m just…
295 00:29:43.040 ⇒ 00:29:43.400 Advait Nandakumar Menon: Fair enough.
296 00:29:48.190 ⇒ 00:29:48.900 Advait Nandakumar Menon: Yep.
297 00:29:48.900 ⇒ 00:29:50.339 Jasmin Multani: That’s something…
298 00:30:08.080 ⇒ 00:30:09.489 Advait Nandakumar Menon: Because this is how…
299 00:30:09.700 ⇒ 00:30:10.090 Jasmin Multani: What’s up?
300 00:30:10.090 ⇒ 00:30:13.989 Advait Nandakumar Menon: Yeah. No, this is how the spreadsheet also breaks it down.
301 00:30:15.920 ⇒ 00:30:19.889 Jasmin Multani: Yeah. But I, I, I think, over here…
302 00:30:20.490 ⇒ 00:30:24.200 Jasmin Multani: I don’t know where she was looking at the… this is retail.
303 00:30:28.390 ⇒ 00:30:29.360 Advait Nandakumar Menon: The wholesale?
304 00:30:29.730 ⇒ 00:30:33.890 Jasmin Multani: Yeah, this is… I want to talk about wholesale. So when she means funneling.
305 00:30:34.620 ⇒ 00:30:34.940 Advait Nandakumar Menon: Yes.
306 00:30:35.160 ⇒ 00:30:37.560 Jasmin Multani: I think she wants to have, like…
307 00:30:38.660 ⇒ 00:30:43.839 Jasmin Multani: She was saying that, like, hey, new applicants should be coming first, and then.
308 00:30:44.210 ⇒ 00:30:45.010 Jasmin Multani: mounts.
309 00:30:45.300 ⇒ 00:30:46.490 Jasmin Multani: created.
310 00:30:46.860 ⇒ 00:30:51.250 Jasmin Multani: I’ll just… I’ll just… I’m just gonna swap in.
311 00:30:52.060 ⇒ 00:30:54.190 Jasmin Multani: Swap in the screenshot.
312 00:30:54.710 ⇒ 00:30:57.660 Jasmin Multani: And just give you a mock-up, with really
313 00:30:58.080 ⇒ 00:31:07.489 Jasmin Multani: numbers, but I think I have… I think I understand what she meant about, like, the funnel, and it being, like, a life journey. Like, it should have.
314 00:31:07.490 ⇒ 00:31:08.190 Advait Nandakumar Menon: Okay.
315 00:31:08.190 ⇒ 00:31:13.379 Jasmin Multani: when she reads it down, she’s gonna look at it sequentially, so she’s gonna look at…
316 00:31:13.380 ⇒ 00:31:14.400 Advait Nandakumar Menon: Okay, okay.
317 00:31:15.290 ⇒ 00:31:16.780 Advait Nandakumar Menon: Yeah, yeah, that makes sense.
318 00:31:17.060 ⇒ 00:31:22.379 Jasmin Multani: Like, when she looks at onboarding, she’s gonna be like, okay, What is the…
319 00:31:22.380 ⇒ 00:31:23.489 Advait Nandakumar Menon: Cloud first year.
320 00:31:23.490 ⇒ 00:31:29.709 Jasmin Multani: total… what is the total number? And then she wants to break it down into, like, of the total number.
321 00:31:30.370 ⇒ 00:31:37.039 Jasmin Multani: 307 were applicants, and then all 307 were accounts created.
322 00:31:37.730 ⇒ 00:31:38.440 Advait Nandakumar Menon: Okay.
323 00:31:39.220 ⇒ 00:31:45.629 Jasmin Multani: Then, see, because see, these whole applicants are subsets of accounts created.
324 00:31:46.120 ⇒ 00:31:46.840 Advait Nandakumar Menon: Neo.
325 00:31:46.980 ⇒ 00:31:54.230 Jasmin Multani: Sorry, I’m also just trying to learn… I’m learning about this as I go along, but, like, this is weird, like…
326 00:31:54.690 ⇒ 00:31:58.780 Jasmin Multani: Why is this 184 and one this 180? So this…
327 00:31:59.850 ⇒ 00:32:04.050 Jasmin Multani: Yeah, I just don’t understand how these numbers are talking to each other.
328 00:32:05.210 ⇒ 00:32:09.350 Jasmin Multani: So we’re gonna have to, like, do a data integrity, check.
329 00:32:09.480 ⇒ 00:32:14.989 Jasmin Multani: But, at least she shared She has shared,
330 00:32:15.410 ⇒ 00:32:19.369 Jasmin Multani: what she expects. So let’s… let’s do that.
331 00:32:19.620 ⇒ 00:32:20.930 Jasmin Multani: Oh, God.
332 00:32:21.330 ⇒ 00:32:39.210 Jasmin Multani: I think for tonight, you’re off the hook, I guess. Later tonight, I will cut you tickets, and I’ll give you a priority between retail and wholesale, and I’m also gonna remap the milestones, because… just because, like, we…
333 00:32:39.450 ⇒ 00:32:42.579 Jasmin Multani: In our call today aligned that, like.
334 00:32:43.220 ⇒ 00:32:47.339 Jasmin Multani: We’re not releasing this to the VPs until October.
335 00:32:47.510 ⇒ 00:32:49.560 Jasmin Multani: So, Shibugani…
336 00:32:49.660 ⇒ 00:32:58.270 Jasmin Multani: Which is new. Her boss was like, contain this dashboarding stuff as much as possible. So what she’s told us is
337 00:32:58.820 ⇒ 00:33:05.189 Jasmin Multani: Even though these dashboards are being used by other parts of the company, by other VPs.
338 00:33:06.700 ⇒ 00:33:09.490 Jasmin Multani: People that she hasn’t even met properly yet.
339 00:33:09.600 ⇒ 00:33:17.330 Jasmin Multani: Shivani, between now and August, is going to get us to 90% completion on the dashboards.
340 00:33:17.330 ⇒ 00:33:18.000 Advait Nandakumar Menon: Okay.
341 00:33:18.000 ⇒ 00:33:26.079 Jasmin Multani: And it’s all gonna be coming down to her opinion. Whether or not she has experience in,
342 00:33:26.250 ⇒ 00:33:32.079 Jasmin Multani: Certain aspects, like… who knows? But she’s gonna be making…
343 00:33:32.220 ⇒ 00:33:36.850 Jasmin Multani: those decisions for those VPs in those separate departments.
344 00:33:37.760 ⇒ 00:33:40.909 Advait Nandakumar Menon: Okay, what’s gonna… how the dashboard is gonna look like, basically?
345 00:33:40.910 ⇒ 00:33:44.880 Jasmin Multani: She’s… she’s… it’s only gonna be her, and we’re not gonna do…
346 00:33:45.190 ⇒ 00:33:57.459 Jasmin Multani: I was like, okay, so there’s no one… like, I get that the VPs are not being exposed, but, like, what about other people in supply chain who are senior managers, who are… we’re interviewing them and giving them.
347 00:33:57.460 ⇒ 00:33:57.930 Advait Nandakumar Menon: feedback.
348 00:33:57.930 ⇒ 00:34:03.440 Jasmin Multani: on this stuff, and she’s like, not even them. I’m the final call, and I’m like, Okay.
349 00:34:03.850 ⇒ 00:34:10.079 Jasmin Multani: Even though, like, I’m just like, you are also learning these work streams for the first time.
350 00:34:10.280 ⇒ 00:34:10.840 Advait Nandakumar Menon: Yeah.
351 00:34:10.840 ⇒ 00:34:12.330 Jasmin Multani: I’m hers.
352 00:34:12.630 ⇒ 00:34:21.159 Jasmin Multani: teammates. Like, she’s actively… like, yesterday she was like, what does this metric mean? What is… what does this metric stand for to her teammate?
353 00:34:21.800 ⇒ 00:34:24.419 Jasmin Multani: In a company size of 50.
354 00:34:25.679 ⇒ 00:34:30.759 Jasmin Multani: So, she’s kind of also learning some of these metrics for the first time.
355 00:34:31.320 ⇒ 00:34:31.670 Advait Nandakumar Menon: Yeah.
356 00:34:31.679 ⇒ 00:34:40.799 Jasmin Multani: gonna have to come in to be like, okay, Shivani, what is your source of truth? Like, do you have something in mind that you want us to recreate?
357 00:34:41.429 ⇒ 00:34:50.139 Jasmin Multani: What is it? If you don’t have something for us to recreate, we will give you mock-ups, but you have to put your eyes to the mock-ups and say yes or no.
358 00:34:50.860 ⇒ 00:34:52.000 Advait Nandakumar Menon: Yeah, okay.
359 00:34:52.650 ⇒ 00:35:03.749 Jasmin Multani: So just as a heads up, like, we’re not gonna have, like, a training. The only person we’re training on this is Shivani, and maybe the VP of Supply.
360 00:35:04.110 ⇒ 00:35:06.960 Jasmin Multani: Maybe. That’s gonna be her judgment call.
361 00:35:07.320 ⇒ 00:35:13.279 Jasmin Multani: So that also helps us reallocate time.
362 00:35:13.900 ⇒ 00:35:19.249 Jasmin Multani: back from the roadmap, so that we can use it to do more QAing and, like.
363 00:35:19.840 ⇒ 00:35:23.429 Jasmin Multani: More day-over-day stress testing the way she wants it to be.
364 00:35:24.110 ⇒ 00:35:25.110 Advait Nandakumar Menon: Yeah, yep.
365 00:35:25.620 ⇒ 00:35:26.429 Advait Nandakumar Menon: Sounds good.
366 00:35:28.690 ⇒ 00:35:33.490 Jasmin Multani: Feel free to log off tonight, I think it’s 5 already, where you’re at.
367 00:35:33.490 ⇒ 00:35:33.980 Advait Nandakumar Menon: Yeah.
368 00:35:33.980 ⇒ 00:35:48.519 Jasmin Multani: Rest up. Tomorrow, I will have things ready for you to jam on, and, even before our meeting with Shivani, like, let’s figure out what… let’s, like, literally label out what is ready.
369 00:35:49.500 ⇒ 00:35:50.910 Jasmin Multani: And what isn’t?
370 00:35:51.680 ⇒ 00:35:59.509 Advait Nandakumar Menon: Yeah, no, that’s perfect. So, I’ll be on the lookout for your tickets, and I’ll have a look at the spec document as well, and…
371 00:35:59.820 ⇒ 00:36:01.799 Advait Nandakumar Menon: Yeah, we can take it from there.
372 00:36:02.400 ⇒ 00:36:09.259 Jasmin Multani: Okay, alright, thank you so much for being on top of everything. Also, make sure you log the extra 30 minutes that you stayed for.
373 00:36:09.380 ⇒ 00:36:10.720 Advait Nandakumar Menon: Sure, sounds good.
374 00:36:10.870 ⇒ 00:36:12.329 Jasmin Multani: Alright, take care! Bye!
375 00:36:12.330 ⇒ 00:36:13.800 Advait Nandakumar Menon: Talk soon. Bye-bye.