Meeting Title: LMNT Standup Date: 2026-05-06 Meeting participants: Greg Stoutenburg, Advait Nandakumar Menon, Jasmin Multani, Awaish Kumar
WEBVTT
1 00:03:28.090 ⇒ 00:03:29.410 Jasmin Multani: Hey, team!
2 00:03:35.260 ⇒ 00:03:38.980 Jasmin Multani: Looks like Robert and Utam won’t be able to join us.
3 00:03:39.250 ⇒ 00:03:40.260 Jasmin Multani: Today.
4 00:03:43.040 ⇒ 00:03:43.730 Advait Nandakumar Menon: Okay.
5 00:03:51.490 ⇒ 00:03:57.480 Jasmin Multani: Maybe we should wait for Oish, because he knows all the… Data modeling stuff.
6 00:04:05.920 ⇒ 00:04:10.059 Jasmin Multani: And we’ll let… we can… we can start in, like, a couple minutes while we wait.
7 00:04:13.290 ⇒ 00:04:13.900 Advait Nandakumar Menon: Yep.
8 00:04:45.270 ⇒ 00:04:51.700 Greg Stoutenburg: Okay, for my part, I’ll, I pivoted my attention a bit ago, but,
9 00:04:52.560 ⇒ 00:05:11.579 Greg Stoutenburg: unless there’s a reason to keep the template that Garrett had been using, like, I mean, did Shivani say anything enthusiastic about any part of it, then I can keep that. Otherwise, it’s like, the more I look at it, the less I can tolerate it. And, I’ve just been deleting a lot of stuff, so…
10 00:05:12.170 ⇒ 00:05:13.160 Jasmin Multani: That’s fair.
11 00:05:13.600 ⇒ 00:05:15.330 Greg Stoutenburg: Okay.
12 00:05:16.840 ⇒ 00:05:18.479 Greg Stoutenburg: I’m just gonna keep deleting stuff, then.
13 00:05:18.900 ⇒ 00:05:21.660 Greg Stoutenburg: I mean, I think what I want to do is…
14 00:05:22.260 ⇒ 00:05:25.679 Greg Stoutenburg: I think we have a pretty consistent approach to…
15 00:05:26.140 ⇒ 00:05:37.439 Greg Stoutenburg: Let me start that sense over. The work streams are pretty steady in so far as the sorts of things that we’re delivering on a weekly and, sprint timeline basis tend to be stable.
16 00:05:37.570 ⇒ 00:05:50.539 Greg Stoutenburg: And so, I just don’t think that we need a… an update structure that, one, repeats the same kind of thing in a lot of places, and then, two, isn’t just kind of tailored to that, so…
17 00:05:51.130 ⇒ 00:05:53.829 Greg Stoutenburg: I think it makes sense to just go…
18 00:05:54.000 ⇒ 00:06:07.819 Greg Stoutenburg: alright, like, you know, what are we doing here? Primarily rolling out Omni. And so, right now, we’re touching revenue, wholesale, and supply chain. Give those updates, and then anything else. And then…
19 00:06:08.120 ⇒ 00:06:09.570 Greg Stoutenburg: I mean, I think that’s kind of…
20 00:06:10.190 ⇒ 00:06:12.880 Greg Stoutenburg: what we’re doing. Does that sound right?
21 00:06:13.590 ⇒ 00:06:16.660 Jasmin Multani: Yeah, in the… are you talking about the weekly deck?
22 00:06:16.920 ⇒ 00:06:17.660 Greg Stoutenburg: Yes.
23 00:06:17.960 ⇒ 00:06:23.370 Jasmin Multani: Okay, okay. Do you want us to review the weekly deck live right now, or should we do that end of day?
24 00:06:23.580 ⇒ 00:06:38.479 Greg Stoutenburg: let’s… let’s do… I’m not ready… I’m not gonna be ready for that until, you know, I… I sort of thought, like, alright, this is just gonna take me 10 minutes, I’m just gonna jump in, delete a couple things, and then run Claude like I usually do, and then, go from there, but I’m… I’m like…
25 00:06:38.980 ⇒ 00:06:57.020 Greg Stoutenburg: no, I need to be… I have to delete a lot more than I thought I was going to need to. And I’m also just trying to make sure that there isn’t, like, something that I’m missing that’s revealed here, so I’m studying it pretty closely. But I don’t… I don’t know that I need to do that. I… just before this call, I pivoted away and did some other stuff, so I’m kind of just continuing with it now.
26 00:06:58.660 ⇒ 00:06:59.759 Jasmin Multani: All good, all good.
27 00:07:00.880 ⇒ 00:07:10.399 Greg Stoutenburg: Did she say anything, about… I mean, I know we would flash this, but I don’t think we ever really, like, went into it. I don’t think she ever really engaged with it.
28 00:07:11.000 ⇒ 00:07:13.259 Jasmin Multani: No, and I think this is gonna…
29 00:07:14.300 ⇒ 00:07:18.730 Jasmin Multani: We have to, like, recheck if this is mirroring the current milestones.
30 00:07:19.050 ⇒ 00:07:20.530 Greg Stoutenburg: I’m just gonna delete it.
31 00:07:21.700 ⇒ 00:07:22.540 Greg Stoutenburg: Gone.
32 00:07:23.890 ⇒ 00:07:24.520 Greg Stoutenburg: Go.
33 00:07:24.740 ⇒ 00:07:27.830 Greg Stoutenburg: Where’s the button? Gone. Okay.
34 00:07:28.040 ⇒ 00:07:33.060 Jasmin Multani: I think number 2, like, she liked the North Star metrics. I think she wanted that.
35 00:07:33.370 ⇒ 00:07:34.020 Greg Stoutenburg: Okay.
36 00:07:34.680 ⇒ 00:07:42.350 Jasmin Multani: And personally, I do like that we have a separation between data modeling and data strategy, so it’s clear who,
37 00:07:42.980 ⇒ 00:07:45.349 Jasmin Multani: She needs to ask and follow up with.
38 00:07:45.350 ⇒ 00:07:47.450 Greg Stoutenburg: Yeah, okay.
39 00:07:47.610 ⇒ 00:07:53.239 Greg Stoutenburg: Cool. As I look at the weekly deck, I don’t see anything that articulates that, really.
40 00:07:58.200 ⇒ 00:07:59.969 Greg Stoutenburg: Oh, I see. Okay.
41 00:08:02.530 ⇒ 00:08:05.080 Greg Stoutenburg: So there’s a section that begins with modeling.
42 00:08:05.510 ⇒ 00:08:07.430 Greg Stoutenburg: On what’s currently slide 7.
43 00:08:13.200 ⇒ 00:08:14.940 Greg Stoutenburg: So, maybe, I mean…
44 00:08:16.420 ⇒ 00:08:22.730 Greg Stoutenburg: Could we just say Omni rollout status? That’s sort of, like, one big chunk, and then modeling is the other big chunk?
45 00:08:24.990 ⇒ 00:08:29.190 Jasmin Multani: Hmm, yeah, but what are we… What are we modeling out?
46 00:08:30.060 ⇒ 00:08:39.789 Greg Stoutenburg: I was just trying to echo what you just said. So, you’re… you’re saying she likes when we approach it as two topics, one being data strategy, another being data modeling? Did I hear that right?
47 00:08:39.799 ⇒ 00:08:45.249 Jasmin Multani: That’s what I’m saying. That’s what I’m saying that I like. And I feel like…
48 00:08:45.839 ⇒ 00:08:51.219 Jasmin Multani: If it’s helping us be more crisp, it’ll probably be helping her be more crisp.
49 00:08:52.450 ⇒ 00:08:56.150 Greg Stoutenburg: Okay, can you help me understand the distinction between
50 00:08:56.490 ⇒ 00:08:59.189 Greg Stoutenburg: I guess… I guess… alright, let me put it differently.
51 00:08:59.560 ⇒ 00:09:05.239 Greg Stoutenburg: I guess I think of the work that we’re doing on modeling as a deliverable on the data strategy work.
52 00:09:05.720 ⇒ 00:09:07.430 Greg Stoutenburg: So,
53 00:09:10.590 ⇒ 00:09:11.829 Greg Stoutenburg: Yeah, is that right?
54 00:09:13.560 ⇒ 00:09:21.299 Jasmin Multani: We work in parallel, but it’s not like I can go back into, like, I can’t make edits in dbt.
55 00:09:21.300 ⇒ 00:09:21.770 Greg Stoutenburg: So that’s…
56 00:09:21.770 ⇒ 00:09:33.529 Jasmin Multani: I primarily rely on OASH, and, like, we’re partners on that. So… and then on the flip side, like, when OASH is done with the modeling, then I take on the baton.
57 00:09:33.530 ⇒ 00:09:41.849 Jasmin Multani: And start QAing the data tables themselves. So I think it helps by, like, having those two work streams show, like.
58 00:09:42.510 ⇒ 00:09:50.460 Jasmin Multani: who’s carrying the baton while the other person is, like, working on other things. I think that… that helps.
59 00:09:50.740 ⇒ 00:09:51.530 Greg Stoutenburg: Okay.
60 00:11:01.400 ⇒ 00:11:02.100 Greg Stoutenburg: Okay.
61 00:11:03.400 ⇒ 00:11:09.169 Greg Stoutenburg: Yeah, okay, so I think that can be treated as its own section, like, modeling treated as, like, sort of a distinct section.
62 00:11:09.300 ⇒ 00:11:13.150 Greg Stoutenburg: Yeah.
63 00:12:15.910 ⇒ 00:12:17.469 Greg Stoutenburg: We’re waiting for a wish.
64 00:12:18.660 ⇒ 00:12:22.979 Jasmin Multani: I don’t know if he’s actually gonna come. Sorry, I thought you were reviewing something.
65 00:12:22.980 ⇒ 00:12:28.520 Greg Stoutenburg: Oh, I’m sorry, no, I… sorry, I thought you said something about waiting, so I was just… just deleting stuff in this deck.
66 00:12:28.520 ⇒ 00:12:31.469 Jasmin Multani: You’re good. Let me message him right now.
67 00:12:31.470 ⇒ 00:12:36.939 Greg Stoutenburg: Yeah, let’s just jump in. I’m not gonna have this to share today. I,
68 00:12:37.300 ⇒ 00:12:43.390 Greg Stoutenburg: I will… I’ll make some changes, I’ll, I’ll have a draft together.
69 00:12:43.580 ⇒ 00:12:51.019 Greg Stoutenburg: early tomorrow morning, I’m okay with treating the call tomorrow as, like… it’s just like, hey, pivot!
70 00:12:51.020 ⇒ 00:13:04.559 Greg Stoutenburg: Greg’s back, took over the deck, and we know, like, we know what the top of mind things are, so let’s just think on them, ask her how Rest and SS week was, give our updates, forecast what’s coming next, and move on. I…
71 00:13:04.560 ⇒ 00:13:14.300 Greg Stoutenburg: I don’t think that weekly huddles are an ideal time to really get into the nitty-gritty of anything. I mean, as far as, like, updates go, I think that’s a time to talk through, like.
72 00:13:14.320 ⇒ 00:13:22.660 Greg Stoutenburg: you know, here are the specifics, here’s the stashboard spec we made for you, or, here are the needs that we have, so…
73 00:13:23.710 ⇒ 00:13:27.360 Greg Stoutenburg: Yeah, so that will be the plan for tomorrow’s, tomorrow’s call.
74 00:13:29.170 ⇒ 00:13:33.100 Jasmin Multani: Okay, do you think anything’s changed?
75 00:13:33.420 ⇒ 00:13:49.700 Jasmin Multani: on my end, like, between today and tomorrow, we’re gonna have her review Advait’s, wholesale dashboards, and, so that’ll be her homework for tonight. Sweet. I’m also gonna, she told me that she…
76 00:13:50.060 ⇒ 00:13:55.680 Jasmin Multani: likes the SKU to UPC master list idea, because Atomic asked her.
77 00:13:55.850 ⇒ 00:14:03.250 Jasmin Multani: Nice. It’s like, Atomic asks her for the same exact thing, and then she’s like, oh, okay, this is a real thing.
78 00:14:03.250 ⇒ 00:14:06.180 Greg Stoutenburg: Was she then able to go, like, oh, I’m ready, I have it?
79 00:14:06.400 ⇒ 00:14:21.060 Jasmin Multani: No, she was like, Jasmine, you give me your spec requirements, and then I’m gonna compare it to what Atomic spec requirements will be for, this master list, and then we build. And then have one person adjust everything. I was like, cool.
80 00:14:21.340 ⇒ 00:14:32.469 Greg Stoutenburg: Got it. I was hoping it was gonna be, like, she doubted it, and then, you know, but, like, went with it anyway, and then, you know, and then it came up, and she’s like, oh, I have it, yeah, yeah, of course, I knew that.
81 00:14:32.470 ⇒ 00:14:38.430 Jasmin Multani: Yeah, and the thing is, like, apparently Element’s internal UPC is not reliable.
82 00:14:38.610 ⇒ 00:14:49.400 Jasmin Multani: SKUs more reliable. Okay. So that tells me, is it reliable because these bigger companies like Target and Walmart, is it because they’re really good and robust about
83 00:14:49.600 ⇒ 00:14:53.669 Jasmin Multani: their data hygiene, and then we’re over-relying on them? Is that why?
84 00:14:54.140 ⇒ 00:14:57.250 Jasmin Multani: Yeah. We need to have a better hygiene, we need to have…
85 00:14:57.610 ⇒ 00:15:01.410 Jasmin Multani: element to pick up the hygiene for UPCs. Yeah.
86 00:15:02.900 ⇒ 00:15:20.649 Greg Stoutenburg: I can see how that drift would happen, right? Like, if it’s the case that… and I’m just gonna make this up, right? If 80% of your sales are going through these two retailers, you’re gonna understand their operations really well, and you might start just defaulting to their language, and sort of ignoring the other pieces, so that might not even be so much on their minds, like.
87 00:15:21.030 ⇒ 00:15:24.690 Greg Stoutenburg: the SKUs we care about are the ones that make nearly all the money.
88 00:15:25.260 ⇒ 00:15:27.050 Greg Stoutenburg: So, I can see why that would happen.
89 00:15:27.270 ⇒ 00:15:31.200 Jasmin Multani: Yeah, but I’m also, like, I don’t know, I don’t know if that’s a good, like, company…
90 00:15:31.200 ⇒ 00:15:34.630 Greg Stoutenburg: No, it’s not a good practice. No. No, that was not a defense. No, that was not a defense.
91 00:15:34.630 ⇒ 00:15:52.739 Jasmin Multani: not be relying on them. So at least, like, by… and it looks like Atomic is gonna give them an answer by Friday. I have the wish list of how I want them to be. I’m just gonna scrape it through our existing data tables to be like, hey, here are examples of, like, data inaccuracies.
92 00:15:52.790 ⇒ 00:16:01.039 Jasmin Multani: I started doing that a bit, but she gave me a link, then she… I think she deleted that link.
93 00:16:01.290 ⇒ 00:16:09.540 Jasmin Multani: So, I’m just gonna show what I have based off of her sources, or our sources internally, and then be like.
94 00:16:10.620 ⇒ 00:16:14.350 Jasmin Multani: There has to be someone who’s auditing this on the ground.
95 00:16:14.720 ⇒ 00:16:23.280 Greg Stoutenburg: Yeah. Yeah, and if there’s not, then, like, we need to find that person and tell them how to own it, or we own it.
96 00:16:23.840 ⇒ 00:16:24.890 Greg Stoutenburg: Yeah.
97 00:16:25.020 ⇒ 00:16:39.589 Jasmin Multani: it’s just gonna be a one-time ingestion. It’ll be, like, a one-time big overhaul, and then after that, it’ll just be, like, incremental, so, like, whenever there’s a change, that’s when we adjust that SKU list, but I imagine this is just gonna be a static table.
98 00:16:40.360 ⇒ 00:16:40.910 Jasmin Multani: delete.
99 00:16:40.910 ⇒ 00:16:43.910 Awaish Kumar: Gastro mentioned, the school list is…
100 00:16:44.090 ⇒ 00:16:51.630 Awaish Kumar: is very dynamic. You have seen, like, there is a… notification from Slack,
101 00:16:51.910 ⇒ 00:17:02.409 Awaish Kumar: in Slack channel that comes in, like, we are missing few schools. If you see that Google Sheet, like, there’s a lot of them there, and the school… if we go from a school
102 00:17:02.750 ⇒ 00:17:16.970 Awaish Kumar: to, UPC, then it’s, like, based on sizes, based on flavors, there are different schools. So it’s going to be quite frequent changes we have to do if we just go from school.
103 00:17:17.650 ⇒ 00:17:21.660 Awaish Kumar: Maybe… yeah, maybe… We should divide
104 00:17:22.280 ⇒ 00:17:27.420 Awaish Kumar: And… by something, right? So that we can actually
105 00:17:28.190 ⇒ 00:17:31.119 Awaish Kumar: Identify what is the product, and…
106 00:17:31.120 ⇒ 00:17:31.460 Jasmin Multani: Yeah.
107 00:17:31.650 ⇒ 00:17:37.860 Awaish Kumar: everything related to that. And then flavors and sizes become, like, your secondary thing.
108 00:17:38.630 ⇒ 00:17:39.260 Jasmin Multani: Yep.
109 00:17:39.260 ⇒ 00:17:40.270 Awaish Kumar: I don’t know, yeah.
110 00:17:40.520 ⇒ 00:17:46.920 Awaish Kumar: Otherwise, it’s going to be quite frequent, because sizes can change, they can… Put up a new…
111 00:17:47.040 ⇒ 00:17:51.850 Awaish Kumar: Size plus flavor combination quite often, and then it can grow.
112 00:17:52.380 ⇒ 00:17:57.350 Jasmin Multani: Yeah, so let me summarize. Awish, are you saying it’s better
113 00:17:57.600 ⇒ 00:18:02.560 Jasmin Multani: to have you PC, or is it better to stick to SKU?
114 00:18:04.110 ⇒ 00:18:07.759 Awaish Kumar: You know, my point is that, like, if we are taking
115 00:18:07.900 ⇒ 00:18:13.409 Awaish Kumar: If we are taking the ownership of this, we have to be mindful that it’s going to be
116 00:18:13.450 ⇒ 00:18:25.680 Awaish Kumar: quite frequent changes when we, go… when we pass this, like, phase. The problem comes afterwards. Like, we are now… after that, we might not be managing this sheet.
117 00:18:25.680 ⇒ 00:18:41.949 Awaish Kumar: we move… move forward, work on other things, and the problem is that, okay, we might not capture UPC2 school mapping, they’re not missing things, and the issues… so we just have to, like… this will be a kind of a regular exercise. We… every week, we have to
118 00:18:41.990 ⇒ 00:18:48.830 Awaish Kumar: reflect on… On this sheet, and identify if there are missing schools, and fill that in.
119 00:18:50.750 ⇒ 00:18:51.690 Jasmin Multani: Okay.
120 00:18:54.480 ⇒ 00:19:05.700 Jasmin Multani: Okay, we’ll consider that. I think it’s still up in the air if, like, if both Atomic and Brainforge are pushing for this, I think it’s still up in the air, like, who’s gonna manage it?
121 00:19:07.060 ⇒ 00:19:08.200 Awaish Kumar: Yeah, I…
122 00:19:09.130 ⇒ 00:19:16.250 Awaish Kumar: So, either it will be someone from Element Team, or it’s Brain Forge, as far as I understand, because atomic…
123 00:19:16.510 ⇒ 00:19:19.040 Awaish Kumar: Would be a downstream of our work.
124 00:19:20.630 ⇒ 00:19:34.789 Awaish Kumar: Yeah, we will be filling in the data to Atomic. Like, that was the initially… initial goal that we discussed, that we will be standardizing the data, and then we will be sending it to Atomic. I don’t know if something changed in between.
125 00:19:35.830 ⇒ 00:19:37.270 Jasmin Multani: Okay, okay, okay.
126 00:19:37.690 ⇒ 00:19:38.759 Jasmin Multani: Sounds good.
127 00:19:43.130 ⇒ 00:19:44.939 Jasmin Multani: Other than that…
128 00:19:45.200 ⇒ 00:19:52.319 Jasmin Multani: yeah, dashboards in the SKU list, like, revamp of the SKU list, and just sizing out how big that lift will be, if we were to, like.
129 00:19:53.170 ⇒ 00:19:59.340 Jasmin Multani: make this an operation of updating the UPC and SKU list. I think that’s the hardest part right now.
130 00:20:05.260 ⇒ 00:20:06.000 Jasmin Multani: Cool.
131 00:20:07.190 ⇒ 00:20:14.959 Jasmin Multani: So, should we… Greg, should we wait for your deck to come through? Awish, do you have anything else to add for modeling of what we should expect?
132 00:20:17.050 ⇒ 00:20:25.580 Awaish Kumar: on the modeling, like, I don’t know, the one thing she asked regarding Pele Builder Access thing, flag for wholesale.
133 00:20:25.800 ⇒ 00:20:31.530 Awaish Kumar: I can’t fu- I can’t find any… I couldn’t find any…
134 00:20:31.800 ⇒ 00:20:36.090 Awaish Kumar: data for that. In the…
135 00:20:36.230 ⇒ 00:20:41.949 Awaish Kumar: in the… in whatever data we are getting from Shopify, so I have erased that with the…
136 00:20:42.120 ⇒ 00:21:01.810 Awaish Kumar: wholesale team, so I haven’t got a reply, so that’s one thing that is blocked. If she comes up with a question for that, we know that it’s… it’s blocked on the wholesale team, so that they let us know, like, how they figure that out, so we can actually do that, and there’s no way to identify without that knowledge.
137 00:21:01.900 ⇒ 00:21:04.100 Awaish Kumar: Second, we pushed some…
138 00:21:04.490 ⇒ 00:21:15.009 Awaish Kumar: columns for wholesale. I don’t know if that could be useful somewhere. I sent the update in the Slack. Apart from that,
139 00:21:15.120 ⇒ 00:21:21.000 Awaish Kumar: per element, I am… I’m working on Amazon congestion right now.
140 00:21:22.960 ⇒ 00:21:37.649 Awaish Kumar: So that, like, today I will be done with ingestion, and tomorrow I will pick up the modeling piece. So, eCom modeling, at least for the order table and the DM customer, you will have all these basic tables ready to go.
141 00:21:40.740 ⇒ 00:21:48.030 Awaish Kumar: And for the supply chain, I don’t know, I… I haven’t received any update from Ashwani, I’m not sure if you both are collaborating on that.
142 00:21:48.600 ⇒ 00:21:55.229 Jasmin Multani: Yeah, I have to take… I have to switch gears and take a look at that after. But I have a question.
143 00:21:55.560 ⇒ 00:21:58.420 Jasmin Multani: Yeah, I have to look at that after this call.
144 00:22:06.110 ⇒ 00:22:06.740 Jasmin Multani: Okay.
145 00:22:06.740 ⇒ 00:22:19.269 Greg Stoutenburg: From my side, yeah, I’m just… I’m… I’m gonna do an update of the deck. I’ll need to lean on the team pretty heavily for this one, just make sure that the updates are in order, as I’m picking this back up.
146 00:22:19.450 ⇒ 00:22:21.640 Greg Stoutenburg: But this’ll be the only time for that.
147 00:22:22.030 ⇒ 00:22:23.769 Greg Stoutenburg: And, yeah, I…
148 00:22:25.740 ⇒ 00:22:34.730 Greg Stoutenburg: I don’t want to obsess too much about the structure, I just want to make sure that it puts the information in front of Shivani that is going to be relevant to her, and shows our progress, and that we’re helping the client.
149 00:22:34.860 ⇒ 00:22:47.040 Greg Stoutenburg: And, yeah, and then really get into something. I really want to emphasize the value of client service, and so, I think really having things to talk with her about is something I want to be
150 00:22:47.040 ⇒ 00:22:58.769 Greg Stoutenburg: steering us toward. So, let’s… let’s get the updates in, make sure that they’re understood, identify any blockers, call out risks, and then get into the discussion phase. So, in a call scheduled.
151 00:22:58.930 ⇒ 00:23:03.999 Greg Stoutenburg: for, a whole hour. I’d love to get through just our update stuff.
152 00:23:04.830 ⇒ 00:23:07.640 Greg Stoutenburg: Within the first 15 minutes, preferably less.
153 00:23:07.640 ⇒ 00:23:09.050 Jasmin Multani: Okay. Okay, good.
154 00:23:10.500 ⇒ 00:23:11.080 Greg Stoutenburg: Yep.
155 00:23:11.580 ⇒ 00:23:15.179 Greg Stoutenburg: And, thanks for your patience as I get this… as I get the deck out.
156 00:23:15.600 ⇒ 00:23:16.639 Jasmin Multani: Of course, of course.
157 00:23:19.690 ⇒ 00:23:20.820 Greg Stoutenburg: That’s it from me.
158 00:23:21.030 ⇒ 00:23:22.680 Jasmin Multani: Okay, should we call it, then?
159 00:23:24.150 ⇒ 00:23:27.060 Jasmin Multani: Okay, we can keep Tay short, but.
160 00:23:27.060 ⇒ 00:23:27.580 Greg Stoutenburg: Cool.
161 00:23:27.820 ⇒ 00:23:33.419 Jasmin Multani: Let us know what else you… what the discussion piece should be in the last 45 minutes.
162 00:23:33.420 ⇒ 00:23:34.060 Greg Stoutenburg: Yeah.
163 00:23:34.060 ⇒ 00:23:41.799 Jasmin Multani: Like, one or two, if it’s radio silent, like, what are one or two things we can throw at her, and that we can all add on to?
164 00:23:42.010 ⇒ 00:23:47.239 Greg Stoutenburg: Yep. Yeah, one thing I’m just gonna ask for rest and assess takeaways, she’ll have them.
165 00:23:47.870 ⇒ 00:24:05.190 Greg Stoutenburg: Another is, I think we can go over… if it doesn’t get covered earlier in the day, so, you know, I’ll look at your proposal for a topic QA process, and we’ll, you know, we’ll take a shot at that, and if we feel like it’s ready to show, we’re like, we’ll just say, hey, this is a discussion item, this is something that the team is working on.
166 00:24:05.190 ⇒ 00:24:15.149 Greg Stoutenburg: really set that expectation for, like, the level of polish that’s on it, and I think that that could be an opportunity to talk through that there, since she was interested in that.
167 00:24:17.650 ⇒ 00:24:23.459 Greg Stoutenburg: And then, Advait, so you’re gonna be demoing wholesale with her tomorrow? Did I hear that correctly?
168 00:24:24.320 ⇒ 00:24:33.869 Advait Nandakumar Menon: Yeah, so tomorrow is the wholesale dashboard, and also I’m working on bringing up the list of topics in which some of the fields are restricted to Blobby right now, and…
169 00:24:34.130 ⇒ 00:24:38.289 Advait Nandakumar Menon: Maybe it will be useful to get information from her, like, which fields
170 00:24:38.420 ⇒ 00:24:43.839 Advait Nandakumar Menon: Should be relevant and exposed to Blobby, and which should be just hidden, so…
171 00:24:44.000 ⇒ 00:24:46.549 Advait Nandakumar Menon: That’s something we discussed yesterday, so yeah.
172 00:24:46.900 ⇒ 00:24:52.190 Greg Stoutenburg: Yeah, just from my understanding, so, were you saying that you have a call with her tomorrow to go through that?
173 00:24:52.820 ⇒ 00:24:58.259 Advait Nandakumar Menon: We have the QA call, like, me and Jasmine, with her every Tuesday and Thursdays.
174 00:24:58.260 ⇒ 00:25:00.079 Greg Stoutenburg: Okay, okay, oh, so you meant during that time.
175 00:25:00.390 ⇒ 00:25:01.810 Advait Nandakumar Menon: Okay, great. Yeah.
176 00:25:01.810 ⇒ 00:25:03.830 Greg Stoutenburg: Okay, cool.
177 00:25:04.150 ⇒ 00:25:05.010 Greg Stoutenburg: Okay.
178 00:25:05.380 ⇒ 00:25:05.900 Greg Stoutenburg: Sounds good.
179 00:25:05.900 ⇒ 00:25:06.920 Jasmin Multani: I’m arguing that, too.
180 00:25:06.920 ⇒ 00:25:18.759 Greg Stoutenburg: Yeah, yeah, yeah, no, I just… for some reason, it did not occur to me that that was the time you meant you’d do that. That makes perfect sense, since it does kind of have that name on it. Okay, cool.
181 00:25:18.870 ⇒ 00:25:20.750 Greg Stoutenburg: Alright.
182 00:25:21.340 ⇒ 00:25:24.729 Greg Stoutenburg: Yeah, I think that’ll… I think that’ll cover us.
183 00:25:25.350 ⇒ 00:25:27.150 Jasmin Multani: I’m good. Alright, thank you.
184 00:25:27.150 ⇒ 00:25:29.830 Greg Stoutenburg: Cool. Alright, see y’all. Thanks. Bye.