Meeting Title: LMNT | Retail Topic Sync Date: 2026-03-24 Meeting participants: Advait Nandakumar Menon, Amber Lin


WEBVTT

1 00:02:18.370 00:02:19.480 Amber Lin: Hello.

2 00:02:20.250 00:02:21.630 Advait Nandakumar Menon: Hey, how’s it going?

3 00:02:22.060 00:02:30.719 Amber Lin: Pretty good. Alright, let’s… Dive in. How was the topic development yesterday?

4 00:02:32.460 00:02:34.789 Advait Nandakumar Menon: Yeah, it was,

5 00:02:34.920 00:02:45.960 Advait Nandakumar Menon: pretty insightful, like, working with Cursa, creating in the context, and just trying to understand what’s going on with the data itself, so… it was pretty nice.

6 00:02:47.710 00:02:56.510 Amber Lin: Cool. I think that’s… I mean, I haven’t done the daily summary model, but so far, I think this topic is good.

7 00:02:56.620 00:03:00.169 Amber Lin: I know Greg is still working on the dashboard plan, I think

8 00:03:00.490 00:03:05.139 Amber Lin: Today afternoon, we should be able to start that.

9 00:03:05.140 00:03:10.369 Advait Nandakumar Menon: So… He sent out a spec document for the dashboard?

10 00:03:10.660 00:03:13.949 Advait Nandakumar Menon: Just a little while ago, I think.

11 00:03:14.170 00:03:17.820 Amber Lin: Yeah, do you know that that’s finalized?

12 00:03:18.390 00:03:26.080 Advait Nandakumar Menon: I don’t think so, I think Utam or Jasmine might review it, so… Cool. Yeah, he’s…

13 00:03:26.080 00:03:26.780 Amber Lin: So…

14 00:03:26.780 00:03:27.920 Advait Nandakumar Menon: Central to the population.

15 00:03:29.120 00:03:35.700 Amber Lin: Cool, okay. So once they review, I think we’ll start building in this afternoon. We probably then don’t need the full

16 00:03:35.900 00:03:41.990 Amber Lin: 45 minutes right now, so I think I want to talk about some topics,

17 00:03:42.370 00:03:47.569 Amber Lin: Just some of the definitions, and then also show you the metric sheet we have.

18 00:03:48.610 00:03:53.290 Advait Nandakumar Menon: Sure, and I think that’s… I think you just replied, for the metrics.

19 00:03:53.930 00:03:57.780 Advait Nandakumar Menon: Greg has asked, if…

20 00:03:58.950 00:04:04.039 Advait Nandakumar Menon: We have finalized the metric sheet, because that’s the base for the topic, as well as the dashboard.

21 00:04:04.620 00:04:06.000 Amber Lin: Yeah,

22 00:04:06.270 00:04:14.120 Amber Lin: I replied saying that we’re adjusting some of these topics, like, if we base it on fact sales, the metric’s gonna be different than if we base it on…

23 00:04:14.730 00:04:15.580 Advait Nandakumar Menon: Okay, okay.

24 00:04:15.580 00:04:19.909 Amber Lin: Yeah, so I wanted to work on that with you right now as well.

25 00:04:20.310 00:04:20.959 Advait Nandakumar Menon: Yeah.

26 00:04:21.220 00:04:23.039 Amber Lin: But so, so far.

27 00:04:23.280 00:04:32.720 Amber Lin: we wanted… they wanted us to answer these questions for retail. We can’t do the PO order questions, but, for example, velocity.

28 00:04:33.040 00:04:40.880 Amber Lin: Like, we haven’t defined what velocity is. I think we should do a draft version, and then they can say they like it or not.

29 00:04:40.880 00:04:55.230 Amber Lin: And also, like, are retailers stocking out? It could be that they want to see explicitly out of stock, but I think they will want to see weeks of stock as well, to say, okay, these people are at risk, but we don’t know how to calculate

30 00:04:55.310 00:05:03.230 Amber Lin: weeks of stock. We… we haven’t defined that right now. So I think I want to discuss these two things with you.

31 00:05:03.350 00:05:05.429 Amber Lin: And how we can include that in the topic.

32 00:05:06.610 00:05:07.240 Advait Nandakumar Menon: Sure.

33 00:05:08.320 00:05:11.899 Amber Lin: Yeah, I think I have it…

34 00:05:13.560 00:05:19.520 Amber Lin: Velocity… velocity… yeah, I searched it on…

35 00:05:19.620 00:05:28.309 Amber Lin: I asked AI, and I think it means just the amount of… the amount sold

36 00:05:28.640 00:05:30.459 Amber Lin: In a given period.

37 00:05:31.750 00:05:32.120 Advait Nandakumar Menon: Okay.

38 00:05:32.120 00:05:33.110 Amber Lin: like…

39 00:05:34.200 00:05:41.480 Amber Lin: total sales divided by number of weeks, or, like, total sales divided by number of weeks divided by number of stores. I think that’s…

40 00:05:41.790 00:05:42.490 Amber Lin: That’s awesome.

41 00:05:42.490 00:05:43.520 Advait Nandakumar Menon: What else should be?

42 00:05:43.520 00:05:44.220 Amber Lin: Yeah.

43 00:05:44.220 00:05:44.540 Advait Nandakumar Menon: Okay.

44 00:05:44.540 00:05:48.490 Amber Lin: So… Like, if that’s what they mean, then…

45 00:05:48.940 00:05:54.229 Amber Lin: Sure, that’s… that’s not hard. I think Omni can calculate that.

46 00:05:54.410 00:05:55.090 Amber Lin: Mmm…

47 00:05:55.090 00:05:58.280 Advait Nandakumar Menon: Yeah, and the fax sales already have…

48 00:05:58.510 00:06:03.980 Advait Nandakumar Menon: The details or the definitions for some of the fields that can be used for this?

49 00:06:04.200 00:06:07.200 Advait Nandakumar Menon: Calculations, or… Yeah.

50 00:06:07.950 00:06:17.279 Amber Lin: Cool. Okay, so… let’s… let’s check, and then the second one of… How do we…

51 00:06:21.660 00:06:25.960 Amber Lin: How do we define that? Do we take, like, sales?

52 00:06:26.990 00:06:28.360 Amber Lin: So…

53 00:06:28.360 00:06:32.319 Advait Nandakumar Menon: Weeks of stock, what exactly,

54 00:06:32.980 00:06:35.130 Advait Nandakumar Menon: Do we mean by that metric?

55 00:06:35.130 00:06:41.380 Amber Lin: That is exactly what I don’t know. I think… This is, like… okay.

56 00:06:42.110 00:06:46.880 Amber Lin: Average weekly sales, incurring inventory divided by that.

57 00:06:47.480 00:06:51.820 Amber Lin: So how do we define average weekly sales?

58 00:06:52.460 00:06:54.640 Amber Lin: like, 4-week trailing?

59 00:07:01.310 00:07:02.490 Amber Lin: Let’s see…

60 00:07:09.210 00:07:10.559 Amber Lin: I’m coming here.

61 00:07:11.110 00:07:12.010 Amber Lin: Alright.

62 00:07:12.110 00:07:19.690 Amber Lin: What is weaker stock?

63 00:07:40.390 00:07:46.820 Amber Lin: Yeah, because I know the retail guy also uses Weika stock for his… some of his.

64 00:07:46.820 00:07:47.210 Advait Nandakumar Menon: Okay.

65 00:07:47.210 00:07:48.230 Amber Lin: relations.

66 00:07:50.730 00:07:56.170 Amber Lin: Unisol… this is not helpful. I didn’t think we defined what…

67 00:07:56.480 00:07:59.740 Amber Lin: the range looks like. Let me pull up…

68 00:08:00.450 00:08:04.380 Amber Lin: What do you think? Have you calculated weeks of stock before?

69 00:08:04.670 00:08:06.229 Advait Nandakumar Menon: No, not really.

70 00:08:09.310 00:08:12.639 Amber Lin: Let’s… I think this one, he…

71 00:08:12.960 00:08:15.510 Amber Lin: He does talk about weeks of stock here.

72 00:08:16.040 00:08:22.020 Amber Lin: Like, he looks at… he def… he uses this view, so he has…

73 00:08:22.680 00:08:26.819 Amber Lin: Zero weeks on hand, da-da-da-da, and so he calculates.

74 00:08:27.810 00:08:30.090 Amber Lin: The weakest stock, kind of.

75 00:08:38.980 00:08:44.989 Amber Lin: And… On hand, in order unit.

76 00:08:49.050 00:08:50.649 Amber Lin: Where does he…

77 00:08:55.010 00:08:57.190 Amber Lin: How does he calculate that?

78 00:09:03.290 00:09:05.100 Amber Lin: I’m so confused.

79 00:09:05.890 00:09:13.759 Amber Lin: Anyways, we can assume, like, we can assume a number for weeks, maybe, like, a 4-week failing average.

80 00:09:17.810 00:09:18.760 Amber Lin: Cool.

81 00:09:23.220 00:09:25.470 Amber Lin: Let’s just use last 4 weeks.

82 00:09:27.900 00:09:31.360 Advait Nandakumar Menon: Assumption being, yeah, plus 4 weeks, right?

83 00:09:42.530 00:09:43.400 Amber Lin: Okay.

84 00:09:43.770 00:09:45.579 Amber Lin: What is a sell-through?

85 00:09:46.400 00:09:48.049 Amber Lin: I don’t know what that is.

86 00:09:57.360 00:10:06.660 Amber Lin: Okay… Okay, valid. Units… Okay…

87 00:10:10.690 00:10:14.120 Amber Lin: Unis sold divided by units received.

88 00:10:26.980 00:10:31.300 Amber Lin: So, sent… Salt is ready.

89 00:10:32.680 00:10:34.080 Amber Lin: Velocity.

90 00:10:34.260 00:10:36.290 Amber Lin: So, through…

91 00:10:39.290 00:10:40.660 Amber Lin: Okay, so what are we.

92 00:10:40.660 00:10:42.870 Advait Nandakumar Menon: To what percentage? Yeah.

93 00:10:42.870 00:10:48.919 Amber Lin: Yeah, so what are we going to use? Because they, they gave us 3 definitions.

94 00:10:50.260 00:10:55.909 Amber Lin: Are we doing receipts during that period, or just starting inventory?

95 00:10:58.390 00:11:08.420 Advait Nandakumar Menon: I… would… Stick with the starting inventory, because…

96 00:11:08.900 00:11:14.729 Advait Nandakumar Menon: That would be simple, in a sense, for now, but obviously we have to check with them, like.

97 00:11:14.960 00:11:18.460 Advait Nandakumar Menon: What their definition of, sell-through is.

98 00:11:20.880 00:11:21.650 Amber Lin: Cool. Okay.

99 00:11:21.650 00:11:22.310 Advait Nandakumar Menon: So…

100 00:11:22.310 00:11:26.160 Amber Lin: What about Reese? Like, they talk about Reese…

101 00:11:30.670 00:11:32.200 Advait Nandakumar Menon: Isn’t that the inventory?

102 00:11:33.800 00:11:39.990 Amber Lin: Yeah, but, like, some of their inventory is still, say, on order or in transit.

103 00:11:40.600 00:11:46.319 Amber Lin: Okay, we’ll just… yeah, you’re right, we’ll use the inventory.

104 00:11:48.500 00:11:49.180 Amber Lin: Or…

105 00:11:49.180 00:11:54.679 Advait Nandakumar Menon: Because out of that inventory, like, how much percentage sold is the sell-through, so…

106 00:11:55.680 00:12:01.889 Advait Nandakumar Menon: Unless you have different, breakdowns for the inventory, like.

107 00:12:02.070 00:12:06.660 Advait Nandakumar Menon: What’s actually in hand, what’s in transit, or whatever?

108 00:12:06.660 00:12:08.700 Amber Lin: Yeah, they do, they do.

109 00:12:09.440 00:12:11.650 Advait Nandakumar Menon: I would consider in hand…

110 00:12:14.230 00:12:15.349 Amber Lin: So, they have, like.

111 00:12:15.350 00:12:15.870 Advait Nandakumar Menon: Bye!

112 00:12:15.870 00:12:16.660 Amber Lin: On hand.

113 00:12:16.660 00:12:17.140 Advait Nandakumar Menon: Yeah.

114 00:12:17.140 00:12:20.299 Amber Lin: In transit, on order.

115 00:12:21.610 00:12:29.830 Amber Lin: So how will we… how will we determine… I think that will be more accurate, for example, like a monthly view.

116 00:12:29.940 00:12:32.110 Amber Lin: So how monthly view…

117 00:12:32.110 00:12:48.200 Advait Nandakumar Menon: Yeah, I would say that… so for… I would say we need on hand for sure, obviously, but in transit or on order, like, can there be situations where it can be canceled, for example, or it’s not received at all, or lost in transit?

118 00:12:48.200 00:12:48.940 Amber Lin: Mmm…

119 00:12:49.350 00:12:49.740 Advait Nandakumar Menon: And then…

120 00:12:49.740 00:12:50.260 Amber Lin: situation.

121 00:12:50.260 00:12:52.200 Advait Nandakumar Menon: Like that. I see.

122 00:12:52.400 00:12:58.150 Amber Lin: We would just count when the on-hand increases, maybe?

123 00:13:01.580 00:13:07.950 Amber Lin: Like, we wouldn’t… add the intransident one order in, we’ll just know that it exists, but it will get.

124 00:13:07.950 00:13:11.009 Advait Nandakumar Menon: You mean, like, a cumulative value for on-hand?

125 00:13:12.430 00:13:19.370 Amber Lin: Yeah, I think so, like, the incremental increases throughout time, but, like, that’s so much work.

126 00:13:21.570 00:13:25.979 Advait Nandakumar Menon: Do we have that already, that level of… Detailed in the data.

127 00:13:26.500 00:13:27.579 Amber Lin: What do you mean?

128 00:13:27.950 00:13:32.210 Advait Nandakumar Menon: like… Do we have on-hand quantity for each?

129 00:13:32.550 00:13:33.600 Advait Nandakumar Menon: B…

130 00:13:33.600 00:13:36.530 Amber Lin: I think they have, like, begin… yeah, yeah, they do.

131 00:13:37.760 00:13:44.890 Advait Nandakumar Menon: Okay, then it makes sense, like, if they’re asking for a monthly view, like, hey, what’s the,

132 00:13:45.340 00:13:47.939 Advait Nandakumar Menon: Celtro for this month.

133 00:13:48.110 00:13:52.970 Advait Nandakumar Menon: Then… From the daily level of grain, we can just…

134 00:13:53.280 00:13:57.759 Advait Nandakumar Menon: Make it incremental or cumulative, and take the value that’s

135 00:13:58.180 00:14:00.969 Advait Nandakumar Menon: On the last day of the month,

136 00:14:01.230 00:14:04.400 Advait Nandakumar Menon: Divided by the number of units sold.

137 00:14:05.480 00:14:07.219 Amber Lin: Okay, so we have…

138 00:14:07.220 00:14:10.690 Advait Nandakumar Menon: I mean, the other way around, the units sold by the… yeah.

139 00:14:11.430 00:14:21.690 Amber Lin: Okay, cool. Alright, so how would we include that in… I think these are going to be omni questions, right?

140 00:14:22.680 00:14:26.430 Amber Lin: We used to stop, we might need to include in our model.

141 00:14:27.040 00:14:29.850 Amber Lin: What do you think? For these three things?

142 00:14:31.120 00:14:40.930 Advait Nandakumar Menon: For specifically with respect to stock and on-hand… I think Cursor already suggested…

143 00:14:42.970 00:14:48.440 Advait Nandakumar Menon: A sample query, maybe… it’s all there in Omni if you want to check it out.

144 00:14:50.610 00:14:51.510 Amber Lin: Cool.

145 00:14:51.680 00:14:56.770 Amber Lin: Alright, let’s… let’s try out… do you want to share screen, and we should test these questions now?

146 00:14:57.510 00:14:58.150 Advait Nandakumar Menon: Sure.

147 00:15:02.190 00:15:04.280 Advait Nandakumar Menon: Let me just set my screen up.

148 00:15:25.260 00:15:26.560 Advait Nandakumar Menon: Can you see my screen?

149 00:15:27.250 00:15:27.770 Amber Lin: Yeah.

150 00:15:31.030 00:15:34.209 Advait Nandakumar Menon: Yeah, so, this is a topic, and…

151 00:15:35.070 00:15:37.850 Advait Nandakumar Menon: I did include some sample queries, so…

152 00:15:38.320 00:15:42.450 Advait Nandakumar Menon: That would include this on-hand and out-of-stock.

153 00:15:43.170 00:15:44.710 Advait Nandakumar Menon: Related stuff.

154 00:15:45.870 00:15:47.840 Advait Nandakumar Menon: We can try to test it out.

155 00:16:03.820 00:16:07.420 Amber Lin: We can click Retail, and then go to your…

156 00:16:10.860 00:16:11.550 Amber Lin: Cool.

157 00:16:12.970 00:16:22.249 Amber Lin: So, the question was… What is the POS velocity by SKU and retailer?

158 00:16:30.920 00:16:44.500 Amber Lin: I think what we’ll have to do is define sample questions in the topic. I just read some of what they did for Eden. They have pretty detailed, topic design, so let me…

159 00:16:44.740 00:16:47.699 Amber Lin: While it’s generating, I’ll try and go grab that.

160 00:16:48.330 00:16:49.080 Amber Lin: bronze.

161 00:16:49.080 00:16:57.549 Advait Nandakumar Menon: Yeah, so that’s where this sample queries, or the questions, cursor has defined comes into play, so maybe we have to define, like, this.

162 00:16:58.360 00:16:59.720 Amber Lin: Yeah, I agree.

163 00:16:59.720 00:17:04.480 Advait Nandakumar Menon: That shows up on the homepage if you… Saw before.

164 00:17:07.470 00:17:08.440 Amber Lin: Wait, sorry?

165 00:17:09.310 00:17:15.869 Advait Nandakumar Menon: Just before I ran this query, it showed the sample questions, so…

166 00:17:17.470 00:17:17.890 Advait Nandakumar Menon: Yeah.

167 00:17:17.890 00:17:23.220 Amber Lin: Cool. Okay, so it’s giving us for the 90… Face…

168 00:17:23.900 00:17:32.090 Amber Lin: Total units sold and sales amount… wait, that’s not… What’s that?

169 00:17:32.840 00:17:34.050 Amber Lin: Boom.

170 00:17:37.570 00:17:40.459 Amber Lin: Yeah, I think we need to define velocity.

171 00:17:41.200 00:17:45.420 Amber Lin: His dad’s just… Amount sold.

172 00:17:46.080 00:17:48.539 Amber Lin: This is not, like, velocity.

173 00:17:50.490 00:17:51.200 Advait Nandakumar Menon: Huh.

174 00:17:52.060 00:17:55.859 Amber Lin: Yeah, we can say… can you ask it to do, like, a…

175 00:17:56.290 00:18:00.250 Amber Lin: Velocity means, like, amount per week.

176 00:18:53.210 00:18:54.070 Advait Nandakumar Menon: Hmm…

177 00:18:58.860 00:19:00.110 Advait Nandakumar Menon: What about this?

178 00:19:03.040 00:19:08.639 Amber Lin: I think that looks pretty decent. Can you scroll to the start of the column? Can I see what it’s like?

179 00:19:08.950 00:19:15.230 Amber Lin: Okay, so it has retailer, product name… okay, okay, that’s good. So, I think we just need to…

180 00:19:15.540 00:19:17.189 Amber Lin: Have a definition.

181 00:19:18.220 00:19:26.750 Amber Lin: But do we include definitions in… And.

182 00:19:29.450 00:19:30.250 Advait Nandakumar Menon: topic?

183 00:19:30.250 00:19:32.380 Amber Lin: In the topic, is my question.

184 00:19:37.290 00:19:40.120 Advait Nandakumar Menon: Are you asking if we should do it in Omni, or…

185 00:19:40.120 00:19:50.069 Amber Lin: Yeah, like, it’s apparently possible in Omni, I just don’t want the client to come say, hey, why didn’t it answer in the first go? This client is kind of picky.

186 00:19:51.220 00:19:51.660 Advait Nandakumar Menon: Huh.

187 00:19:55.620 00:20:01.940 Advait Nandakumar Menon: You mentioned about the example for Eden, where the topic Was pretty detailed out.

188 00:20:01.940 00:20:07.330 Amber Lin: I’m reading it right now, so it has…

189 00:20:08.720 00:20:15.470 Amber Lin: I’ll also share screen. So it has, like, in the AI context, what this covers.

190 00:20:15.730 00:20:20.760 Amber Lin: What it combines. I think we have that.

191 00:20:20.990 00:20:27.049 Amber Lin: What’s included? We did that. When to use this topic? Maybe we need to add this.

192 00:20:27.370 00:20:30.560 Amber Lin: And then we have example questions.

193 00:20:30.710 00:20:32.809 Amber Lin: Which we will be including that.

194 00:20:35.600 00:20:37.389 Amber Lin: I think we can try.

195 00:20:37.540 00:20:43.850 Amber Lin: To have the… And then there’s, like, related topics to this.

196 00:20:44.470 00:20:50.430 Amber Lin: I think we can try defining things there, but… .

197 00:21:21.200 00:21:24.130 Advait Nandakumar Menon: So, for Eden, how… have they defined it?

198 00:21:24.400 00:21:29.650 Advait Nandakumar Menon: an Omni on… in Snowflake, LBT.

199 00:21:29.890 00:21:34.499 Amber Lin: I don’t see any definitions in… in there.

200 00:21:35.520 00:21:40.100 Amber Lin: But here, I’m just reading the OmniGuides.

201 00:21:40.720 00:21:43.680 Amber Lin: Anyways, do you want to try the other questions?

202 00:21:44.140 00:21:48.980 Amber Lin: We can try the… Like, what’s the waste of…

203 00:21:49.960 00:21:52.449 Amber Lin: I guess our retailers shocking out?

204 00:21:55.430 00:21:56.070 Advait Nandakumar Menon: Yeah.

205 00:22:00.870 00:22:02.250 Advait Nandakumar Menon: Can you repeat that?

206 00:22:02.770 00:22:05.189 Amber Lin: Are retailers stocking out?

207 00:22:07.480 00:22:10.040 Amber Lin: And I guess, who is close to stalking out?

208 00:24:06.090 00:24:10.000 Amber Lin: Okay, so, yeah, out of stock…

209 00:24:10.130 00:24:12.649 Amber Lin: Okay, they used the low order point.

210 00:24:13.400 00:24:19.259 Amber Lin: Cool. Can you ask it to use weaker stock?

211 00:24:19.900 00:24:21.890 Amber Lin: What?

212 00:24:21.890 00:24:22.670 Advait Nandakumar Menon: Sorry, what’s that?

213 00:24:22.670 00:24:29.500 Amber Lin: Can you ask it to calculate weeks of stock using, say, Past 4 weeks average sales.

214 00:24:39.400 00:24:45.230 Amber Lin: And then, say, show me… Stores that have…

215 00:24:45.670 00:24:50.489 Amber Lin: Right. Zero weeks of stock, 1 to 2, 2 to 3, 4.

216 00:26:18.570 00:26:22.359 Amber Lin: I mean, this doesn’t look… that doesn’t look bad.

217 00:26:24.070 00:26:24.949 Advait Nandakumar Menon: Sorry, what’s that?

218 00:26:24.950 00:26:31.240 Amber Lin: I think this looks pretty good. And then they can drill down, if they want, to individual stores.

219 00:26:32.100 00:26:35.869 Amber Lin: I mean, it just shows us it can… it’s able to calculate that.

220 00:26:36.150 00:26:43.050 Amber Lin: So, we’ll just need to define… Like, define what… how these.

221 00:26:43.050 00:26:45.930 Advait Nandakumar Menon: Each of this is… Yeah, okay.

222 00:26:46.690 00:26:52.610 Amber Lin: Cool, okay. Sent you some stuff for…

223 00:26:53.530 00:26:59.859 Amber Lin: like, the Omni con… how the AI context works in Omni is sent in our Zoom chat.

224 00:27:00.450 00:27:03.850 Amber Lin: So, we can look at that, and…

225 00:27:05.560 00:27:09.420 Amber Lin: And see how we can, improve.

226 00:27:10.200 00:27:15.720 Amber Lin: There’s also, like, parameters…

227 00:27:20.090 00:27:27.940 Amber Lin: Default filters… Anyways, okay.

228 00:27:30.170 00:27:35.570 Amber Lin: Well, I think this… this topic is… Good so far.

229 00:27:36.350 00:27:41.850 Amber Lin: Do you want to put the topic in, like, PR review?

230 00:27:44.390 00:27:51.949 Advait Nandakumar Menon: So… do I have the permission to do that? Because I don’t have access to the GitHub, so…

231 00:27:52.440 00:27:56.470 Amber Lin: I don’t think… oh, I see, hmm.

232 00:27:57.300 00:27:59.060 Amber Lin: Can you show me what it looks like?

233 00:28:00.740 00:28:05.729 Amber Lin: It should just be on our, like, on our GitHub, I think?

234 00:28:07.250 00:28:07.970 Amber Lin: Let’s see…

235 00:28:07.970 00:28:20.400 Advait Nandakumar Menon: I don’t think it’s our GitHub, it’s because… so this is the repository that you see over here. When I click on it, it’s on Team Elements GitHub, and under that, there’s a.

236 00:28:20.400 00:28:22.030 Amber Lin: I see, I see.

237 00:28:22.030 00:28:23.669 Advait Nandakumar Menon: Yeah, so I don’t have access.

238 00:28:23.670 00:28:24.930 Amber Lin: Oh, okay.

239 00:28:25.100 00:28:29.839 Amber Lin: Is there a way I can log into your branch?

240 00:28:33.140 00:28:34.540 Amber Lin: Or log into your grant.

241 00:28:34.540 00:28:37.930 Advait Nandakumar Menon: The other funny thing is,

242 00:28:39.190 00:28:45.030 Advait Nandakumar Menon: I’m using the API key that’s, wait a second…

243 00:28:46.800 00:28:50.510 Advait Nandakumar Menon: Yeah, I’m using the API key that’s in 1Pass, and I think…

244 00:28:50.680 00:28:54.569 Advait Nandakumar Menon: It is yours, so it’s showing, like, you are the one who’s doing the…

245 00:28:55.450 00:28:57.530 Amber Lin: Oh, that’s so funny.

246 00:28:57.850 00:29:01.469 Amber Lin: Well, then I have… then I should have your branch. Like, I think I have the.

247 00:29:01.470 00:29:01.830 Advait Nandakumar Menon: Yeah.

248 00:29:01.830 00:29:02.500 Amber Lin: here.

249 00:29:02.680 00:29:03.170 Advait Nandakumar Menon: I…

250 00:29:03.170 00:29:03.700 Amber Lin: Cool.

251 00:29:03.700 00:29:09.229 Advait Nandakumar Menon: I think you should… you can just go under model, and… Let me show…

252 00:29:09.690 00:29:11.849 Amber Lin: Yeah, I found it, no worries.

253 00:29:12.220 00:29:20.140 Advait Nandakumar Menon: Okay, yeah, so it lets me pick a branch, like, some… I don’t know if this is your branch, but Element Topics V1.

254 00:29:20.330 00:29:20.950 Amber Lin: Yeah.

255 00:29:21.300 00:29:22.460 Amber Lin: mine before.

256 00:29:22.630 00:29:23.430 Amber Lin: Yeah, I saw…

257 00:29:23.430 00:29:26.169 Advait Nandakumar Menon: I think you should be able to see mine as well, yeah.

258 00:29:26.170 00:29:33.780 Amber Lin: Cool. Okay, that sounds good. I want to take the rest of the time to look at the metrics sheet.

259 00:29:34.710 00:29:35.390 Advait Nandakumar Menon: Ultra?

260 00:29:36.000 00:29:42.189 Amber Lin: And then, like, I might make some edits on the AI context and see what we can improve.

261 00:29:42.340 00:29:48.770 Amber Lin: So let me… I’ll share screen, and then we’ll look at the sheet together. I might need some of your help there.

262 00:29:49.100 00:29:50.290 Amber Lin: Yeah.

263 00:29:50.480 00:29:54.820 Amber Lin: So, it’s right here. I’m gonna share this…

264 00:29:55.490 00:29:58.570 Amber Lin: Shared this with you, mostly working on this page.

265 00:29:58.570 00:30:00.300 Advait Nandakumar Menon: Should I just stop sharing?

266 00:30:00.300 00:30:00.890 Amber Lin: Yeah.

267 00:30:01.160 00:30:02.869 Amber Lin: Feel free to stop share.

268 00:30:03.960 00:30:05.510 Amber Lin: Okay.

269 00:30:09.200 00:30:11.330 Amber Lin: Sent you the link in chat.

270 00:30:12.020 00:30:13.190 Amber Lin: So…

271 00:30:14.770 00:30:22.200 Amber Lin: This, I think, still needs some updating. This is already, like, updated compared to this one.

272 00:30:22.380 00:30:27.150 Amber Lin: But this is the fields I included.

273 00:30:27.570 00:30:32.720 Amber Lin: Like, I don’t know how many of these are still true anymore.

274 00:30:33.060 00:30:38.499 Amber Lin: Like, some of these are just not going to be true, because they’re not in scope yet.

275 00:30:38.970 00:30:42.939 Advait Nandakumar Menon: Can we start… can we start over? I’m sorry, I just opened the…

276 00:30:42.940 00:30:45.150 Amber Lin: Yes, yes, yes. So…

277 00:30:45.150 00:30:45.890 Advait Nandakumar Menon: Oh, yeah, mother.

278 00:30:46.010 00:30:52.749 Amber Lin: These are metrics that’s being used, in the dashboards or in our models.

279 00:30:52.870 00:30:53.550 Amber Lin: air.

280 00:30:55.460 00:30:57.140 Amber Lin: Some of these are just…

281 00:30:57.530 00:31:10.439 Amber Lin: not live yet, they’re just been being discussed, like, these… they just discussed it. It’s not really a metric that we modeled, but I… it’s just here.

282 00:31:11.540 00:31:16.260 Amber Lin: But… like, I think our job is to…

283 00:31:16.730 00:31:26.320 Amber Lin: Make sure that this is up-to-date, and that it comes from… Comes from the… right model.

284 00:31:26.420 00:31:31.960 Amber Lin: But I… I feel like if we were to change the…

285 00:31:32.090 00:31:37.189 Amber Lin: how we use our models in Omni. I feel like a lot of these are no longer…

286 00:31:37.890 00:31:41.779 Amber Lin: I think no longer valid, especially if we…

287 00:31:43.970 00:31:48.489 Amber Lin: Like, these summed up metrics, I don’t know if they’re valid anymore.

288 00:31:52.260 00:31:52.930 Amber Lin: Yeah.

289 00:31:53.650 00:32:00.809 Amber Lin: Anyways, I think the main thing is making sure that the logic is correct here, and making sure…

290 00:32:01.090 00:32:05.899 Amber Lin: like, the model… Mart’s model is correct here.

291 00:32:07.070 00:32:19.709 Amber Lin: they didn’t have any Mars models here before, so I was wondering, do you think we should include, like, the base model this was calculated from, or the model that this metric

292 00:32:19.870 00:32:21.689 Amber Lin: Like, it’s used in.

293 00:32:24.190 00:32:26.489 Advait Nandakumar Menon: I think we should include both.

294 00:32:28.440 00:32:29.870 Advait Nandakumar Menon: So we should pause…

295 00:32:29.870 00:32:34.480 Amber Lin: columns? One to say, like, where it’s… Words created.

296 00:32:35.520 00:32:40.549 Advait Nandakumar Menon: Yeah, because that would be the, source of truth, right? Like…

297 00:32:40.760 00:32:41.700 Amber Lin: That’s true.

298 00:32:42.310 00:32:44.330 Advait Nandakumar Menon: Yeah. Okay. So I…

299 00:32:46.350 00:32:55.909 Advait Nandakumar Menon: would say we need to include where it’s coming from and where it’s being used as well. But, what about column O? Like, isn’t that the source system, or am I…

300 00:32:56.180 00:33:02.030 Amber Lin: This is, like, where the data is connected, like, the API is coming from.

301 00:33:02.400 00:33:03.920 Advait Nandakumar Menon: Oh, okay. Okay.

302 00:33:03.920 00:33:06.950 Amber Lin: So, we can say source models.

303 00:33:08.750 00:33:09.930 Amber Lin: And…

304 00:33:37.400 00:33:48.680 Amber Lin: from Fact Sales, I think? No, this is, like… Order… Line items.

305 00:33:50.520 00:33:52.870 Amber Lin: I mean, these are wholesale ones.

306 00:33:53.730 00:33:56.819 Amber Lin: I think these are… Yeah, I think you should just…

307 00:33:57.960 00:34:01.490 Advait Nandakumar Menon: You should just filter to the business domain to retail, I guess.

308 00:34:01.580 00:34:03.730 Amber Lin: Yeah, okay, let’s do that.

309 00:34:04.250 00:34:06.760 Amber Lin: Clear… Me too.

310 00:34:08.010 00:34:08.820 Amber Lin: Alright.

311 00:34:08.929 00:34:16.580 Amber Lin: Let’s… I think we can take… we have, like, 15 minutes. Let’s… let’s read through this to see if this makes sense.

312 00:34:17.679 00:34:22.489 Amber Lin: Thanks.

313 00:34:22.649 00:34:30.149 Amber Lin: I’ll just mark these as true. If they tell us this is in scope, we can do that. Cool. There’s sales velocity…

314 00:34:30.489 00:34:32.429 Amber Lin: I think this is in scope.

315 00:34:32.739 00:34:36.939 Amber Lin: Let’s add in the… the few things we were…

316 00:34:37.279 00:34:44.289 Amber Lin: I think we were just talking about right now, there’s sales… Good morning.

317 00:34:45.190 00:34:48.449 Advait Nandakumar Menon: on the… Yeah, okay.

318 00:34:54.290 00:34:59.260 Amber Lin: Sales velocity, what was the other thing? We exist.

319 00:34:59.260 00:35:01.160 Advait Nandakumar Menon: Weeks of stroke? Yeah.

320 00:35:04.430 00:35:09.790 Amber Lin: Wait, what? There’s something called Waste Available Inventory.

321 00:35:10.800 00:35:11.590 Amber Lin: Okay.

322 00:35:13.880 00:35:15.810 Amber Lin: Okay, there’s Lisa’s stock.

323 00:35:19.130 00:35:25.349 Amber Lin: Which… How do we define that?

324 00:35:28.400 00:35:30.019 Advait Nandakumar Menon: Yeah, let me just…

325 00:35:40.970 00:35:45.350 Amber Lin: It was, like we said, it was… .

326 00:35:49.530 00:35:55.689 Advait Nandakumar Menon: Yeah, it’s the… Current inventory by the average weekly sales.

327 00:35:56.070 00:35:56.870 Amber Lin: Cool.

328 00:36:16.280 00:36:19.179 Amber Lin: Smallest time grain is a B.

329 00:36:20.340 00:36:27.250 Advait Nandakumar Menon: Current inventory by last 4 weeks of… yeah, you got that, okay. Yep. Sorry about that.

330 00:36:27.640 00:36:35.030 Amber Lin: Oh, good. Okay, so this is… This isn’t what I… Boom.

331 00:36:35.850 00:36:41.620 Amber Lin: Is this a sum, or is it, like, a ratio?

332 00:36:44.000 00:36:47.970 Amber Lin: Anyways, we can do it here, so it will be, like, some…

333 00:36:49.630 00:36:52.000 Advait Nandakumar Menon: I would say that’s a ratio.

334 00:36:52.720 00:36:53.330 Amber Lin: Okay.

335 00:36:58.150 00:37:00.190 Advait Nandakumar Menon: I mean, that’s what Omni did, right?

336 00:37:01.490 00:37:10.270 Amber Lin: Okay, so we sum… On here, starting… Bigot, bigoting.

337 00:37:12.350 00:37:13.930 Amber Lin: on hand.

338 00:37:18.130 00:37:19.810 Amber Lin: divided by…

339 00:37:23.190 00:37:25.290 Amber Lin: average…

340 00:37:28.530 00:37:31.199 Amber Lin: How do I define this formula?

341 00:37:32.310 00:37:35.969 Advait Nandakumar Menon: Are you sharing your screen? Because I’m trying to follow you on the…

342 00:37:37.510 00:37:37.930 Amber Lin: That’s true.

343 00:37:37.930 00:37:40.430 Advait Nandakumar Menon: And I’m not able to see what you’re typing out.

344 00:37:40.430 00:37:41.669 Amber Lin: Oh, it’s down here.

345 00:37:41.780 00:37:43.409 Amber Lin: It’s in the corner.

346 00:37:44.650 00:37:48.470 Advait Nandakumar Menon: Okay. Okay, I see it now. Sum of beginning on hand…

347 00:38:00.000 00:38:12.529 Amber Lin: Like, beginning on hand… How do I… how would the formula… Express… Like… That is 4 weeks average.

348 00:38:41.630 00:38:44.359 Amber Lin: Anyways, I’m just gonna put that in for now.

349 00:38:45.760 00:38:48.790 Amber Lin: Okay.

350 00:38:50.900 00:38:53.519 Advait Nandakumar Menon: It should be the units sold, right?

351 00:38:53.990 00:38:56.639 Advait Nandakumar Menon: Oh, you already put, put that? Okay.

352 00:38:57.230 00:39:01.520 Amber Lin: Units sold, and then we have sales through…

353 00:39:18.280 00:39:20.840 Amber Lin: Oh, what is sell-through again.

354 00:39:31.880 00:39:35.950 Amber Lin: Wait, current inventory is not just on hand, right?

355 00:39:36.740 00:39:37.889 Amber Lin: Is it?

356 00:39:39.330 00:39:44.639 Advait Nandakumar Menon: No, we, I think we discussed it to be the in-transit,

357 00:39:45.860 00:39:49.189 Advait Nandakumar Menon: All those stuff, but I think we settled on…

358 00:39:49.870 00:39:53.799 Amber Lin: I think for sell-through, we said, like, beginning on…

359 00:39:53.920 00:39:58.280 Amber Lin: One stop. A beginning, like, start a period on hand.

360 00:39:58.810 00:40:00.100 Advait Nandakumar Menon: Yeah, yeah.

361 00:40:00.770 00:40:06.840 Amber Lin: Okay, this is, like, beginning on… And…

362 00:40:07.150 00:40:11.480 Amber Lin: But, like, this one is just total pipeline?

363 00:40:13.450 00:40:16.019 Advait Nandakumar Menon: Yeah, it should be the current value, like…

364 00:40:16.430 00:40:20.419 Amber Lin: So this would include anything that’s in transit for lease of stock.

365 00:40:22.010 00:40:24.380 Amber Lin: On transit and on order, right?

366 00:40:25.340 00:40:33.989 Advait Nandakumar Menon: Does that, like… when you think about current inventory, does it sum up all that stuff, like, on hand, in transit, and…

367 00:40:34.430 00:40:39.590 Advait Nandakumar Menon: out of place. Does it sum those values? Is that what the total pipeline inventory means?

368 00:40:39.590 00:40:44.980 Amber Lin: Yeah, I’ll be more explicit. I’ll say in transit, on order.

369 00:40:45.760 00:40:54.280 Amber Lin: And let me include, actually… This, so you can see… What it looks like.

370 00:40:55.780 00:41:00.500 Amber Lin: Cool, so there’s some supply chain, like, there’s on-hand, there’s these.

371 00:41:01.790 00:41:02.439 Advait Nandakumar Menon: Huh.

372 00:41:04.090 00:41:08.270 Amber Lin: Which I don’t think… I don’t know if these are still valid.

373 00:41:18.270 00:41:21.700 Amber Lin: I think this is just… Wait, what?

374 00:41:22.550 00:41:26.239 Amber Lin: Available inventory slash sales robots.

375 00:41:28.700 00:41:29.940 Amber Lin: Oh.

376 00:41:30.960 00:41:35.760 Amber Lin: I mean, that… do you think that works, too, as weeks of stock?

377 00:41:38.370 00:41:43.240 Advait Nandakumar Menon: I would say, so… wait, so does this mean, like, sales velocity is…

378 00:41:46.350 00:41:50.730 Amber Lin: Sales velocity, technically… how do we define sales velocity?

379 00:41:51.250 00:42:05.039 Amber Lin: Right, we did say it was, like… Sales… Given a certain period.

380 00:42:06.970 00:42:09.159 Advait Nandakumar Menon: No, what I’m asking is,

381 00:42:09.950 00:42:15.150 Advait Nandakumar Menon: Sales velocity and weeks of stock, you have just added those two rows to the spreadsheet, right?

382 00:42:15.150 00:42:16.260 Amber Lin: Yeah.

383 00:42:16.830 00:42:21.050 Advait Nandakumar Menon: But this week’s available inventory is…

384 00:42:21.050 00:42:26.530 Amber Lin: This was here before, but that’s essentially just Lisa Stock. I think we can rename it.

385 00:42:28.330 00:42:36.999 Advait Nandakumar Menon: Yeah, no, what I mean is, it is already referencing to the sales velocity, so is sales velocity all… also something that has been defined before?

386 00:42:37.730 00:42:40.790 Amber Lin: I don’t see a formula.

387 00:42:42.120 00:42:43.959 Amber Lin: So, I don’t think so.

388 00:42:44.640 00:42:50.329 Amber Lin: Sales… Yeah, let’s check. Sales velocity…

389 00:42:52.760 00:42:57.079 Amber Lin: It just says some units sold by store, I don’t think that’s valid.

390 00:42:58.480 00:43:01.720 Amber Lin: There’s no sales velocity.

391 00:43:01.850 00:43:02.690 Amber Lin: Right?

392 00:43:02.940 00:43:06.149 Advait Nandakumar Menon: Okay, where is it? I’m not even seen.

393 00:43:07.430 00:43:08.259 Amber Lin: Let’s see here.

394 00:43:08.840 00:43:11.010 Advait Nandakumar Menon: Okay, yeah, Annual, yeah.

395 00:43:11.170 00:43:12.919 Amber Lin: That doesn’t make sense to me.

396 00:43:14.570 00:43:16.199 Advait Nandakumar Menon: Stop on the internet.

397 00:43:17.660 00:43:19.599 Advait Nandakumar Menon: Sold by store.

398 00:43:22.970 00:43:26.799 Advait Nandakumar Menon: Is… maybe… is that the definition that they are going for?

399 00:43:27.230 00:43:29.249 Advait Nandakumar Menon: Do you have any idea about that?

400 00:43:29.440 00:43:35.800 Amber Lin: I’m not sure, this wasn’t the most updated, this was, like, created a long time ago.

401 00:43:36.600 00:43:38.070 Advait Nandakumar Menon: Okay.

402 00:43:38.070 00:43:38.980 Amber Lin: Yeah.

403 00:43:46.430 00:43:53.050 Amber Lin: I’d say it’s… some units… Sold.

404 00:43:53.450 00:43:58.110 Amber Lin: divided by… Period.

405 00:44:05.440 00:44:11.520 Advait Nandakumar Menon: Yeah, it can be the units sold by the period, by the number of stores, if required.

406 00:44:17.800 00:44:19.409 Amber Lin: Oh, this is…

407 00:44:20.220 00:44:24.569 Advait Nandakumar Menon: Like, units per week, or units per store per week?

408 00:44:25.600 00:44:26.570 Amber Lin: Yeah.

409 00:44:28.730 00:44:31.599 Amber Lin: Avivable inventory, fuck myself.

410 00:44:46.950 00:44:52.949 Amber Lin: I mean, I, it’s… I think, personally, I think we should go with 4 weeks.

411 00:44:53.370 00:45:02.519 Amber Lin: Because then, we… it seems like we need to define a period, like, for example, the 90 days, and ask it, what’s the sales velocity?

412 00:45:02.730 00:45:06.330 Amber Lin: Or else it’s gonna give us, like, all-time sales velocity.

413 00:45:08.340 00:45:12.490 Advait Nandakumar Menon: Okay, so, regarding that…

414 00:45:14.690 00:45:23.259 Advait Nandakumar Menon: in the topic design, like, should we create a default filter for 90 days? Because, that’s something…

415 00:45:23.380 00:45:25.380 Advait Nandakumar Menon: Caressa gave me yesterday?

416 00:45:25.850 00:45:26.300 Amber Lin: Hmm.

417 00:45:26.300 00:45:30.219 Advait Nandakumar Menon: But I removed it because I wasn’t sure that something

418 00:45:30.540 00:45:33.120 Advait Nandakumar Menon: That should be included in the design, so…

419 00:45:35.080 00:45:39.819 Amber Lin: We haven’t heard confirmation from them yet, so I honestly don’t know.

420 00:45:41.610 00:45:42.260 Advait Nandakumar Menon: Okay.

421 00:45:43.800 00:45:51.760 Advait Nandakumar Menon: I mean, what I’m trying to say is that something like that is included, then you were just asking me, like, otherwise it’ll look over all the time, right?

422 00:45:53.010 00:45:54.870 Amber Lin: Yeah. I think that’s…

423 00:45:54.870 00:45:55.650 Advait Nandakumar Menon: Could be about…

424 00:45:55.650 00:45:58.359 Amber Lin: Follow their definition right here.

425 00:45:58.810 00:46:03.780 Amber Lin: Or do we use our… definition.

426 00:46:07.860 00:46:11.309 Advait Nandakumar Menon: I mean, it depends, I’m not sure of,

427 00:46:12.460 00:46:15.719 Advait Nandakumar Menon: Their definitions are serving them well, like…

428 00:46:16.610 00:46:19.010 Advait Nandakumar Menon: Is it? Do you have any idea about that?

429 00:46:19.880 00:46:24.640 Amber Lin: Nope, I haven’t talked to them about… What their definitions are.

430 00:46:25.890 00:46:30.019 Advait Nandakumar Menon: So, are all the definitions on the sheet from our side?

431 00:46:30.460 00:46:31.150 Amber Lin: Huh.

432 00:46:31.540 00:46:44.129 Amber Lin: Most of it is, like, if you want to see what it looked like before, you can go to this sheet, the original core metrics, but I created most of, like, anything that’s in gray on the…

433 00:46:44.270 00:46:48.580 Amber Lin: the work in progress sheet, I just… I added, like, a week ago.

434 00:46:50.020 00:46:51.020 Advait Nandakumar Menon: Oh, okay.

435 00:46:51.020 00:46:51.630 Amber Lin: Yeah.

436 00:46:53.420 00:46:56.960 Advait Nandakumar Menon: And has this been reviewed by them, or anyone up top?

437 00:46:56.960 00:47:01.329 Amber Lin: No, we, we’re, like, we’re, we’re getting it ready for review.

438 00:47:01.450 00:47:03.890 Amber Lin: Is the main… is our main goal.

439 00:47:05.240 00:47:06.100 Advait Nandakumar Menon: Okay.

440 00:47:06.450 00:47:07.100 Amber Lin: Yeah.

441 00:47:07.800 00:47:13.400 Advait Nandakumar Menon: If that’s the case, if they’re anyway gonna review it, then I would… Say, stick with…

442 00:47:13.780 00:47:19.420 Advait Nandakumar Menon: Our definition, because if you’re saying most of these other definitions on the sheet are…

443 00:47:19.720 00:47:23.250 Advait Nandakumar Menon: Something we came up with, I would say, yeah.

444 00:47:23.720 00:47:28.730 Amber Lin: And also, like, this is… this is not a proper formula, anyways.

445 00:47:28.910 00:47:35.040 Amber Lin: So, I’m gonna say… Yes, derived metric.

446 00:47:35.360 00:47:37.650 Amber Lin: Yes, derived metric.

447 00:47:37.950 00:47:46.090 Amber Lin: I am going to… Electric time.

448 00:47:52.200 00:47:53.920 Amber Lin: ratio…

449 00:47:58.880 00:48:02.979 Amber Lin: ratio… I am going to delete that row.

450 00:48:09.070 00:48:09.740 Amber Lin: Cool.

451 00:48:10.390 00:48:11.370 Amber Lin: Okay.

452 00:48:11.750 00:48:18.649 Amber Lin: I don’t think we’re using any of these.

453 00:48:19.120 00:48:20.670 Amber Lin: 2, right?

454 00:48:22.470 00:48:22.860 Advait Nandakumar Menon: Okay.

455 00:48:27.730 00:48:31.519 Amber Lin: Oh, okay, okay, I understand. I think these should still…

456 00:48:34.100 00:48:39.879 Amber Lin: Like, that’s inventory available for retailers, this is available, I think.

457 00:48:40.710 00:48:45.959 Amber Lin: Okay, we don’t have those yet.

458 00:48:49.030 00:48:49.770 Amber Lin: Cool.

459 00:48:50.090 00:48:55.109 Amber Lin: I’ll say false. Retail available inventory, probably also false.

460 00:49:10.320 00:49:18.420 Amber Lin: Less aim to go through this sheet and update it, but, like, most of the stuff in the… in the bag is, like, whatever.

461 00:49:19.790 00:49:20.640 Advait Nandakumar Menon: Huh.

462 00:49:20.720 00:49:28.020 Amber Lin: But… 1, 2… Like, edit these and make sure they’re up to date.

463 00:49:29.780 00:49:33.369 Amber Lin: We’re at time. Do you think we can look at

464 00:49:34.510 00:49:43.570 Amber Lin: this together. Okay, we… I can either… we can split the work, I can look at this, or… and you can update

465 00:49:43.890 00:49:46.730 Amber Lin: the topics with the AI suggestions?

466 00:49:47.410 00:49:48.740 Amber Lin: Or…

467 00:49:48.740 00:49:49.069 Advait Nandakumar Menon: Yeah, honey.

468 00:49:49.070 00:49:53.080 Amber Lin: you can look at this, and I can do the topic and submit a PR, whatever.

469 00:49:54.940 00:49:56.149 Amber Lin: What do you think?

470 00:49:58.950 00:50:00.889 Amber Lin: Or do you just want to split it half and half?

471 00:50:03.560 00:50:10.169 Advait Nandakumar Menon: We can… I can take over this, but I might need a little more context as to, like…

472 00:50:10.510 00:50:13.300 Advait Nandakumar Menon: What do you really require from me on this sheet?

473 00:50:14.290 00:50:32.130 Amber Lin: Makes sense. I think… I think I should take the first pass. I just realized that half of these, like, is the spreadsheet metrics, so let… let me actually do that, and let me know once you’ve added more AI contacts in a topic, and when it’s ready to be in the PR.

474 00:50:32.130 00:50:32.850 Advait Nandakumar Menon: Okay.

475 00:50:33.140 00:50:39.869 Amber Lin: Yeah, and… Like, we… Can you look through Omni’s definition to see

476 00:50:40.020 00:50:49.200 Amber Lin: where we should include these, like, should we include it in the topic description, or should we just create a model for it? So let me know.

477 00:50:49.520 00:50:55.209 Amber Lin: What your decision there is, and if we need a model, we’ll need to send it in our internal channel.

478 00:50:56.720 00:51:05.140 Advait Nandakumar Menon: Okay, so by… You mean the metrics on the sheet needs to be added to.

479 00:51:05.290 00:51:09.100 Amber Lin: No, just, just the 3 that we were working on for…

480 00:51:09.100 00:51:09.620 Advait Nandakumar Menon: Okay.

481 00:51:09.620 00:51:21.639 Amber Lin: these… like, either it needs to go in a topic, or it needs to go into, like, a dbt model. Like, either way, I’ll let you decide. And if we need a model, we need to tell our team.

482 00:51:23.480 00:51:24.020 Advait Nandakumar Menon: Okay.

483 00:51:24.260 00:51:24.660 Amber Lin: Yeah.

484 00:51:24.660 00:51:28.640 Advait Nandakumar Menon: So, I will look into that, like, where the three metrics should go into.

485 00:51:28.940 00:51:35.049 Amber Lin: Yeah, and then update the AI context of the topic, and let me know when it’s ready to…

486 00:51:35.350 00:51:36.649 Amber Lin: be in a PR.

487 00:51:37.730 00:51:43.289 Advait Nandakumar Menon: Sure. The AI context should follow the best practice… the link you just sent, right?

488 00:51:43.990 00:51:45.300 Amber Lin: Yeah, yeah.

489 00:51:46.140 00:51:46.620 Advait Nandakumar Menon: Okay.

490 00:51:46.620 00:51:48.960 Amber Lin: I think just dump it in cursory will help.

491 00:51:49.240 00:51:51.040 Advait Nandakumar Menon: Yeah, yeah, yeah, that sounds good.

492 00:51:51.530 00:51:53.239 Amber Lin: Sounds good, alright.

493 00:51:53.240 00:51:55.219 Advait Nandakumar Menon: Sounds good. Thanks. Bye-bye.