Meeting Title: [Eden] Daily Standup Date: 2025-07-29 Meeting participants: Fireflies.ai Notetaker Tigran, Robert Tseng, Mitesh Patel, Annie Yu, Awaish Kumar, Amber Lin


WEBVTT

1 00:00:46.950 00:00:48.000 Mitesh Patel: Hey, Robert.

2 00:00:49.210 00:00:50.130 Robert Tseng: Hey, Mattesh.

3 00:01:03.650 00:01:07.619 Robert Tseng: you have anything you want to talk about before the others join.

4 00:01:08.390 00:01:10.949 Mitesh Patel: No I just wanted to

5 00:01:11.587 00:01:19.140 Mitesh Patel: have a discussion, and maybe we do it during this call or after with Andrew, you, Kevin, and me.

6 00:01:20.140 00:01:23.300 Robert Tseng: Oh, yeah. Well, he booked time at 4 pm. Eastern.

7 00:01:23.300 00:01:23.870 Mitesh Patel: Good.

8 00:01:23.870 00:01:24.600 Robert Tseng: Yeah.

9 00:01:25.080 00:01:29.269 Mitesh Patel: Oh, never mind. Okay, there it is. It’s on my calendar. I missed it.

10 00:01:29.640 00:01:33.730 Robert Tseng: Okay, yeah. So I guess I was planning to talk. Then.

11 00:01:34.100 00:01:35.929 Mitesh Patel: Okay, that’s cool.

12 00:01:36.730 00:01:43.889 Mitesh Patel: yeah. The old. So couple of questions I saw, you know Annie’s messages. Hi, Annie, how are you?

13 00:01:46.000 00:02:02.310 Mitesh Patel: about the the row as snapshot. I don’t, you know. First, st yeah, I went through it ran through it a couple of different times, and I understand that it’s supposed to give sort of. Here’s what the Ncac. Look like on that date.

14 00:02:04.009 00:02:12.069 Mitesh Patel: And it. I think it does that effectively. But I’m not sure if that serves

15 00:02:12.440 00:02:22.850 Mitesh Patel: the need that we have, which is yes. We started collecting these snapshots on whatever it was the 21.st So that’s the furthest I can go back.

16 00:02:24.470 00:02:37.299 Mitesh Patel: I think you know, when I look in bask right like the orders database, and and I don’t know if you can. If you have access to if we have access to the orders table in bask. But if we did, we can go back to the beginning of the year

17 00:02:37.370 00:02:56.731 Mitesh Patel: right and and and and that’s why I think that might be a better solution. I I don’t know the snapshot thing I think, works, but I can’t go like, for example, what was it in June right now? Right? I don’t think I need to go much further back than that.

18 00:02:57.760 00:03:04.150 Mitesh Patel: so it’ll work going forward, but I think we need a better, better, better solution.

19 00:03:05.010 00:03:22.679 Robert Tseng: Yeah. So I mean, like, the whole point of that was so that we wouldn’t have this like changing metric. Right? The the changing metric. There’s Josh’s needs. But then we wanted something where we actually knew what the rosque or the the Cac. Was for that you know, point point in time.

20 00:03:23.738 00:03:29.429 Robert Tseng: We can’t. Well, we didn’t. Well, we can’t retroactively do that, because.

21 00:03:29.960 00:03:39.529 Robert Tseng: yeah, I mean, I guess things that had already moved by then. We weren’t really storing the changes before then. So I mean we could. I mean, I hear that you

22 00:03:39.710 00:03:50.509 Robert Tseng: want to. I mean, we have all the order history. I mean, we could try to retroactively calculate it. I’m just trying to like visualize in my head like, how would we even

23 00:03:50.740 00:03:51.980 Robert Tseng: do that?

24 00:03:53.620 00:04:12.150 Robert Tseng: well, we know the daily spends. We have a record of that. And we know all the orders. I mean it would. It would be a guess, I guess. Okay, I wouldn’t say it’s a guess. But I mean we we, if if you’re trying to just try to retroactively fill back to the beginning like the start of the year like. Is that? Is that what you’re asking for?

25 00:04:12.870 00:04:16.320 Mitesh Patel: Yeah? And and and look, if we have the orders table, right?

26 00:04:16.630 00:04:19.740 Mitesh Patel: Yeah, we can always look at the order date.

27 00:04:19.740 00:04:20.290 Robert Tseng: Yeah.

28 00:04:20.870 00:04:23.610 Mitesh Patel: Right. That’s never gonna change in the orders table.

29 00:04:25.170 00:04:39.909 Mitesh Patel: Now, if you know the the status changes to refunded whatever then we have, you know that’s the source of the truth that we can maintain. But in in the Orders table this date is always there. The date prescribed is always there.

30 00:04:40.100 00:04:47.580 Mitesh Patel: Right, so we can always do analysis, going back and saying, how much time did it take to prescribe or confirm the order.

31 00:04:47.710 00:04:48.220 Robert Tseng: Yep.

32 00:04:48.220 00:05:10.259 Mitesh Patel: And then how much you know when once it was shipped right there’s you can see them. We have so many delays and shipment right. But when something happened, you you know you were in that chat with Adam and me about having a sort of company events, calendar or marketing calendar. Right? We can say, hey, when we switched pharmacies, and there were fulfillment delays. How much, how much you know.

33 00:05:10.310 00:05:27.819 Mitesh Patel: Sort of what happened to shipping times or fulfillment times. And then what happened to number, you know a number of waters refunded during that time. So that’s if we maintain this, we can always run not only the Ncac. Report like.

34 00:05:27.950 00:05:36.870 Mitesh Patel: because the number of waters received on that day is what drives the the impact calculation right? That would never change, no matter how far back I went.

35 00:05:40.510 00:05:50.639 Robert Tseng: I see what’s changing it right now? The Ncac. Doesn’t isn’t the one that’s changing.

36 00:05:50.640 00:06:12.670 Mitesh Patel: Yeah, ncac, is changing. Because, right, you know, we’re looking at, and as we should, the the truth, the source of the truth that we want for confirmed orders, changes when there’s refunds right? Even though auto was paid, confirmed, paid for. It changes because the next, you know, and especially we had a because we got these delays right now fulfillment delays. We have a a spike in refunds.

37 00:06:12.930 00:06:22.820 Mitesh Patel: so every day there’s more refunds that cut in the new. The number of new customer orders or number of new customers changes.

38 00:06:23.510 00:06:27.929 Mitesh Patel: the spend remains the same. So now my Ncat keeps going up every time I look at it.

39 00:06:30.010 00:06:36.460 Robert Tseng: Yeah, well, yeah, that’s that’s why the okay. And then, as far as like, so the snapshot.

40 00:06:36.750 00:06:45.479 Robert Tseng: I mean, it’s no different than like, just if basically the for Josh report. But it’s because it’s already fixed. It’s not gonna change anymore. Looking back.

41 00:06:45.480 00:06:46.819 Mitesh Patel: Right, right.

42 00:06:47.330 00:06:53.689 Robert Tseng: So yeah, we’ll capture stuff moving forward. But even that will be different from what

43 00:06:54.100 00:06:57.780 Robert Tseng: I mean. It’s it’s it’s gonna be different from what you see in the fort. Josh.

44 00:06:58.640 00:07:04.999 Mitesh Patel: It will be different. It will be. That’s fine. It can be different than what’s in the 4 Josh report, because the 4 Josh report will change.

45 00:07:05.000 00:07:05.630 Robert Tseng: Yeah.

46 00:07:05.750 00:07:22.719 Robert Tseng: but it changes to a point, and then it stops changing. And that’s what happens for all the historical stuff. Right? And so if we end up giving you a view that has snapshots from the 21st going onwards, and then everything retroactively is just like it stopped changing because it’s like fixed after a certain point.

47 00:07:22.880 00:07:28.625 Robert Tseng: I’m just like seeing I’m just trying to see is that is that consistent like, it’s it’s

48 00:07:29.640 00:07:38.419 Robert Tseng: like it. Only I feel like it’s more apples to apples to compare like snapshots rather than comparing, I mean, because if we just waited.

49 00:07:38.420 00:07:41.969 Mitesh Patel: Snapshot is based on this right number of orders that day.

50 00:07:42.270 00:07:42.850 Robert Tseng: Yep.

51 00:07:43.290 00:07:45.649 Mitesh Patel: Right. So if we always go back to this table

52 00:07:46.380 00:07:50.069 Mitesh Patel: and you have this data going back to the beginning of the year, I can go back

53 00:07:50.290 00:07:53.590 Mitesh Patel: the previous to the snapshots of July 21.st

54 00:07:53.840 00:07:57.270 Robert Tseng: Yeah, thank, you.

55 00:07:58.580 00:08:03.340 Mitesh Patel: And it gives us all these other insights through which is, you know, kind of roadmap items right.

56 00:08:03.770 00:08:04.340 Robert Tseng: Yeah.

57 00:08:04.540 00:08:09.440 Mitesh Patel: Yeah, alright, anyway, that’s that’s the

58 00:08:10.000 00:08:12.809 Mitesh Patel: sort of just just my, that’s that’s the ask.

59 00:08:13.130 00:08:20.829 Robert Tseng: Okay, yeah, I let me. I’m gonna set aside time, Annie, and a wish we’ll meet again later today. And I just wanna

60 00:08:21.750 00:08:26.109 Robert Tseng: kind of try to. Yeah, we’re just try to see what adjustments we need to make here.

61 00:08:26.970 00:08:27.530 Mitesh Patel: Okay.

62 00:08:27.750 00:08:28.260 Robert Tseng: Yeah.

63 00:08:31.750 00:08:33.520 Mitesh Patel: Okay. Cool. Thanks.

64 00:08:33.520 00:08:34.090 Mitesh Patel: Yep.

65 00:08:36.411 00:08:41.509 Robert Tseng: I’m just gonna let Amber kind of run through the rest of the stand up. If if you don’t have anything else.

66 00:08:45.130 00:08:50.600 Amber Lin: Okay, sounds good. I’ll share screen fine.

67 00:08:50.820 00:08:52.380 Amber Lin: So

68 00:08:52.860 00:09:10.630 Amber Lin: I ordered this so that we start from the most important projects. There’s a few items that came up in a few channels that I do want to address today, and then we’ll get to them in a bit. Can I get an update for the marketing, tagging, and tracking project.

69 00:09:10.630 00:09:21.160 Robert Tseng: Yeah, so yeah, the Gtm container. Andrew already looked at stuff. I we kind of went over it yesterday. can we just put that as like a client review right now.

70 00:09:22.970 00:09:24.310 Robert Tseng: I

71 00:09:25.270 00:09:32.579 Robert Tseng: I I think to me then, this is something I’m going to discuss with Mattesh again later today. So just as a heads up, it’s like, Okay, well.

72 00:09:32.830 00:09:38.460 Robert Tseng: I think Andrew’s given me a clear point of view on what it’s what we would need to do to.

73 00:09:38.580 00:09:51.820 Robert Tseng: I mean he he can. He can own Google tag manager moving forward, we we could take it off of Sebastian’s plate, but it just feels like our efforts are duplicative, because still doing his thing. And then it’s like, well.

74 00:09:52.260 00:10:01.189 Robert Tseng: we were asked to go in and do stuff as well, and I I don’t, I think, before we move forward and step on his toes like, I just want to have a clear

75 00:10:01.360 00:10:04.630 Robert Tseng: like delineation of what like what our calls are here.

76 00:10:04.630 00:10:14.479 Amber Lin: Got it. Yeah, I saw your message yesterday, so I know what’s going on. Does that mean that the tickets will be paused for a bit until we confirm, perhaps today.

77 00:10:14.910 00:10:15.340 Robert Tseng: Yeah.

78 00:10:15.340 00:10:20.299 Amber Lin: Okay. Sounds good. Did Andrew get access to segment?

79 00:10:20.300 00:10:24.420 Robert Tseng: Yeah, he has access, and he also has access to Meta. So I told him to go.

80 00:10:24.420 00:10:34.780 Amber Lin: Yeah, I closed that one. Thanks. That’s good. Ohish! Robert had a request to turn the current segment models into Dvt models. Now it’s not blocked. Right?

81 00:10:35.120 00:10:36.859 Amber Lin: That’s not blocked. Okay.

82 00:10:36.860 00:10:37.400 Awaish Kumar: But.

83 00:10:39.210 00:10:41.119 Robert Tseng: So we’re very excited.

84 00:10:41.480 00:10:43.629 Amber Lin: Ask Robert if you need more details.

85 00:10:43.630 00:10:56.839 Robert Tseng: That’s not the most urgent thing, because the the query does work. But we should try to get it done this week. Yeah, in terms of priority wanted, you know, just calling that out like the the pipeline does work. It’s just would prefer it to be in dpt.

86 00:10:57.540 00:10:58.370 Amber Lin: Okay.

87 00:10:58.710 00:11:00.250 Amber Lin: Sounds good.

88 00:11:03.360 00:11:03.800 Amber Lin: And.

89 00:11:03.800 00:11:09.000 Awaish Kumar: Okay, yeah, like, I don’t see like what Steve here.

90 00:11:09.330 00:11:10.120 Amber Lin: Hmm.

91 00:11:10.250 00:11:15.150 Awaish Kumar: Can we add him in? Stand ups, watch them.

92 00:11:15.460 00:11:16.100 Robert Tseng: Vashtev.

93 00:11:16.100 00:11:21.290 Amber Lin: Oh, gosh, no, I I think. Actually, let’s see.

94 00:11:21.590 00:11:25.309 Amber Lin: you all can add people to stand ups, I believe.

95 00:11:26.950 00:11:29.050 Amber Lin: Wait, let me let me check.

96 00:11:34.180 00:11:36.510 Amber Lin: Okay, sorry about that.

97 00:11:39.380 00:11:41.019 Amber Lin: Okay, I added him.

98 00:11:45.270 00:11:47.629 Amber Lin: We want Andrew as stand up as well.

99 00:11:47.630 00:11:48.250 Robert Tseng: No.

100 00:11:48.430 00:11:56.820 Amber Lin: Okay, yeah. So okay. And then on the farm Ops side, so

101 00:11:57.290 00:12:04.960 Amber Lin: that one download is not here. So these are mostly Rebecca’s requests. So yesterday. Let’s see.

102 00:12:05.640 00:12:10.440 Amber Lin: so Rebecca has this one she sent in the Channel.

103 00:12:14.080 00:12:18.490 Amber Lin: That this table doesn’t seem that accurate.

104 00:12:23.402 00:12:24.760 Amber Lin: Who would be

105 00:12:25.000 00:12:31.240 Amber Lin: Annie? Could you take a quick look into this, and let me know if this is a quick task for

106 00:12:31.780 00:12:38.590 Amber Lin: if it can be, if it needs to be a longer ticket, let me know, and then we’ll create that.

107 00:12:39.320 00:12:47.810 Annie Yu: Yeah, I’m suspecting that will still need engineering help, because we never changed the calculation. But I’ll take a look at that and let you know.

108 00:12:48.500 00:12:48.990 Amber Lin: Okay.

109 00:12:50.426 00:12:54.100 Robert Tseng: But I understand the ask like the Rebecca’s point, I mean, like.

110 00:12:54.330 00:13:02.019 Robert Tseng: however, this is set up. Yeah, like every every dose should be a personalized dose. So if it’s showing like.

111 00:13:02.920 00:13:07.997 Robert Tseng: maybe it’s just the way that we’re naming it like I maybe it’s just unclear to her. But

112 00:13:08.740 00:13:21.900 Robert Tseng: there, yeah, there’s no like standard and personalized plan option anymore. Everything is personalized. So I think she’s expecting everything to since July to look like 100.

113 00:13:21.900 00:13:22.580 Amber Lin: Yeah.

114 00:13:22.860 00:13:23.210 Robert Tseng: Yeah.

115 00:13:23.514 00:13:28.389 Amber Lin: So I think it sounds like we need to clarify how we define the 2 colors.

116 00:13:30.460 00:13:34.520 Amber Lin: Alright, okay.

117 00:13:35.950 00:13:37.240 Amber Lin: Sounds good.

118 00:13:42.510 00:13:44.989 Amber Lin: that one, Robert. You’re doing.

119 00:13:44.990 00:13:50.320 Robert Tseng: Yeah, I’m I’m gonna do it. Today. I’m gonna have to do some of this stuff.

120 00:13:50.860 00:13:54.780 Amber Lin: Okay, it’s not blocked anymore. Right?

121 00:13:54.780 00:13:55.830 Robert Tseng: It’s not blocked.

122 00:13:55.830 00:13:56.180 Amber Lin: Okay.

123 00:13:56.180 00:13:58.850 Robert Tseng: Or even if it is, I’m gonna put something out.

124 00:13:59.200 00:14:08.609 Amber Lin: Okay, is that the same as Rebecca’s request to have projections so that she can deliver? Okay, so mark this as a duplicate.

125 00:14:10.370 00:14:12.770 Robert Tseng: Or they’re related. I want. I wouldn’t say they’re duplicate, but.

126 00:14:12.770 00:14:13.829 Amber Lin: Oh, okay.

127 00:14:14.400 00:14:14.850 Robert Tseng: Yeah.

128 00:14:15.094 00:14:17.049 Amber Lin: I’ll just leave it there for you. Then.

129 00:14:17.050 00:14:18.240 Robert Tseng: Okay. Thanks.

130 00:14:21.120 00:14:24.609 Amber Lin: Okay, Annie, on the Ltv forecasting.

131 00:14:25.370 00:14:32.720 Amber Lin: I know you were able to make some graphs, which is which is really great.

132 00:14:33.620 00:14:38.299 Amber Lin: Jonah asked, when I sent a Monday overview of

133 00:14:38.830 00:14:45.799 Amber Lin: what we’re doing for the Ltv project, and why we’re doing it? Since you already have

134 00:14:46.210 00:15:01.079 Amber Lin: the graphs. Can you give him a quick overview of this project? And then, if he supports this, then we can keep doing it. If not, I think this is a good point to decide if we want to continue or not.

135 00:15:01.080 00:15:06.227 Robert Tseng: I I grabbed time with Annie today already we’ll we’re gonna cover this

136 00:15:07.650 00:15:08.055 Amber Lin: Awesome.

137 00:15:08.570 00:15:10.710 Amber Lin: So that’s good. So I’ll.

138 00:15:10.710 00:15:16.969 Annie Yu: I do, I reply to him, or I should wait until we meet Robert.

139 00:15:17.400 00:15:18.080 Amber Lin: You should.

140 00:15:18.080 00:15:19.240 Amber Lin: Yeah, you yes.

141 00:15:19.240 00:15:21.279 Robert Tseng: Yeah, you can. You can. You can wait. It’s fine.

142 00:15:21.280 00:15:21.560 Amber Lin: Yeah.

143 00:15:23.407 00:15:24.780 Amber Lin: Let me say.

144 00:15:28.150 00:15:29.717 Amber Lin: there you go.

145 00:15:36.230 00:15:38.680 Amber Lin: Gonna move in there first, st

146 00:15:39.010 00:15:49.739 Amber Lin: and then for the Emr side. I wish this might not be a valid ticket. I just remembered you said we stole. Someone said, we still need to get data from Google sheets. Is that still valid?

147 00:15:50.350 00:15:52.000 Amber Lin: Do we get the data.

148 00:15:52.810 00:15:56.910 Awaish Kumar: No, no, it’s not like we we want to like, just

149 00:15:57.570 00:16:03.170 Awaish Kumar: consolidate all the sheets from where we are getting the data, not actually getting.

150 00:16:03.170 00:16:04.080 Amber Lin: Hmm.

151 00:16:07.890 00:16:17.140 Awaish Kumar: So like I I just wanted to meet with terminal day to week, see like what like. I know some of the sheets, so I just wanted him to review it. So

152 00:16:17.570 00:16:26.939 Awaish Kumar: so that like, if he’s making any extra requests which I’m not aware of, we can have it from one place and see what can be automated in the Emr.

153 00:16:27.240 00:16:34.000 Awaish Kumar: Instead of getting data from sheet, we might just get, for example, product information directly from Emr. Api.

154 00:16:34.000 00:16:34.410 Awaish Kumar: Have a friend.

155 00:16:35.240 00:16:35.960 Amber Lin: Okay.

156 00:16:37.710 00:16:43.249 Amber Lin: Okay. So this we cannot do yet. But we need to want it to be back to be back.

157 00:16:45.180 00:16:51.679 Amber Lin: Okay, I don’t. Well, Cameron hasn’t sent the.

158 00:16:51.800 00:16:54.189 Amber Lin: They haven’t sent the documents yet.

159 00:16:54.968 00:16:57.460 Amber Lin: I’ll go ping again today.

160 00:16:57.780 00:17:03.899 Amber Lin: Can you confirm if these are the right, I’ll tag you

161 00:17:05.020 00:17:08.859 Amber Lin: if these are the right document.

162 00:17:10.250 00:17:15.069 Amber Lin: It’s gonna ask for magic business.

163 00:17:15.920 00:17:16.609 Amber Lin: Yeah.

164 00:17:16.750 00:17:23.670 Amber Lin: if you help me confirm these, I’ll go chase after, and I’ll ask Tech to Grant to help me if needed.

165 00:17:27.140 00:17:37.620 Awaish Kumar: We need current data models to be roadmap. Yeah, that’s like, Emr, for like er diagrams.

166 00:17:39.380 00:17:41.439 Awaish Kumar: Is is that on edgy? Yeah.

167 00:17:41.920 00:17:43.199 Amber Lin: Do we need this?

168 00:17:43.640 00:17:44.869 Amber Lin: We need it right?

169 00:17:48.400 00:17:52.850 Awaish Kumar: Yeah, like this. This is more like how they are going to send it to us through.

170 00:17:53.660 00:18:00.170 Awaish Kumar: It might not be a document. It’s can be a some discussion about.

171 00:18:00.580 00:18:01.200 Amber Lin: Okay?

172 00:18:03.010 00:18:08.359 Amber Lin: And then the following 4 and 5 does that does 3 and 4. Does that make sense.

173 00:18:09.850 00:18:13.029 Awaish Kumar: Yeah, they. That’s what they did

174 00:18:13.630 00:18:22.390 Awaish Kumar: using the current data model. That’s what we are going to get right. The difference between, like the so

175 00:18:22.390 00:18:25.130 Awaish Kumar: as they mentioned like, there is now new language

176 00:18:25.610 00:18:34.819 Awaish Kumar: in the past. We had orders, we had subscriptions. Now all that is not this, that concept is different in Emr.

177 00:18:35.070 00:18:36.549 Awaish Kumar: They are using kind of different language.

178 00:18:37.520 00:18:38.389 Awaish Kumar: For all these things.

179 00:18:38.390 00:18:42.664 Amber Lin: I see. Okay, I see. Okay, I got that.

180 00:18:43.380 00:18:53.939 Amber Lin: Well, also, Robert, we’ll we’re to book the Mr. Meeting with the broader group. I think I need to ask Tigran for help for scheduling.

181 00:18:55.084 00:18:58.000 Amber Lin: I don’t know their calendars very well to coordinate.

182 00:18:58.000 00:18:58.360 Awaish Kumar: Hey?

183 00:18:58.360 00:18:59.660 Awaish Kumar: Yeah, I mean.

184 00:18:59.660 00:19:00.090 Amber Lin: Yeah.

185 00:19:00.090 00:19:01.639 Awaish Kumar: Well, I’m enjoying our meeting.

186 00:19:01.640 00:19:10.289 Robert Tseng: I I don’t. I guess. When are we gonna have, like a clear point of view on like what they’re doing like? I don’t feel like we need to meet with them that much.

187 00:19:10.290 00:19:10.850 Awaish Kumar: Thanks.

188 00:19:13.751 00:19:21.859 Awaish Kumar: So like we like like from their point of view, like we met with the

189 00:19:22.210 00:19:28.112 Awaish Kumar: Cameron, he shared that like they are in a testing phase and want to roll out in this

190 00:19:29.083 00:19:38.049 Awaish Kumar: in this month like in the next month, like in the next 4 weeks that they want 10% of the traffic

191 00:19:38.479 00:19:43.749 Awaish Kumar: to come to new Emr from their website. And still 90% goes to the past

192 00:19:45.314 00:19:51.940 Awaish Kumar: and they are looking to, like, you know, move over everything in in next 2 months.

193 00:19:52.260 00:19:56.620 Awaish Kumar: and all the existing system. They decide they want to move it in 6 months.

194 00:19:56.870 00:19:58.230 Awaish Kumar: So the

195 00:19:58.410 00:20:12.849 Awaish Kumar: for the current system, and how they are working like we have requested some documents because the the he mentioned that there’s a lot of changes, and the kind of models they have built and kind of concepts they are utilizing in Emr.

196 00:20:13.080 00:20:19.219 Awaish Kumar: very different from the Wasc system.

197 00:20:19.644 00:20:25.339 Awaish Kumar: But it was not like very clear to us as well in the meeting, that what exactly is the difference?

198 00:20:25.993 00:20:36.280 Awaish Kumar: That’s why I have requested some of the documents, and he mentioned he will compile in this week and send it over to us. Like. By the end of week or by next Tuesday.

199 00:20:40.910 00:20:48.701 Awaish Kumar: Okay, things like the orders and subscriptions that he mentioned. We have now fulfillments and concepts of

200 00:20:50.093 00:20:59.529 Awaish Kumar: engagement, and and like the things like that. So he, some. Some of the vocabulary is different. And get to understand all of that.

201 00:20:59.750 00:21:04.513 Awaish Kumar: I I asked for some like er er diagrams. And

202 00:21:05.460 00:21:08.449 Awaish Kumar: these data models they have right now.

203 00:21:10.150 00:21:16.705 Awaish Kumar: So we can understand bit more of like how the system is working. And if we can like,

204 00:21:17.810 00:21:23.019 Awaish Kumar: I mentioned like, we can share what the current bus system is, and he was not really

205 00:21:23.250 00:21:27.789 Awaish Kumar: wanted to do that. Like to to support our analytics.

206 00:21:27.900 00:21:33.575 Awaish Kumar: he mentioned. Like we we should start afresh with the new models, instead of going from

207 00:21:34.120 00:21:38.629 Awaish Kumar: existing vast system and trying to remap all the things to the vast system.

208 00:21:41.160 00:21:42.130 Robert Tseng: Yeah.

209 00:21:44.710 00:21:49.737 Robert Tseng: Okay. So like, I think, my biggest concern is that

210 00:21:51.720 00:22:01.660 Robert Tseng: Well, yeah, I mean, obviously, them being just their product engineers. They don’t care about any of the legacy stuff. They’d rather just build it from scratch. That’s always easier for them.

211 00:22:03.580 00:22:09.300 Robert Tseng: But then we understand the legacy system. I even think that, like

212 00:22:10.430 00:22:17.579 Robert Tseng: well, as they’re building all of these different objects and kind of built in in their new system.

213 00:22:18.420 00:22:23.038 Robert Tseng: I mean, we’re assuming that they’re building it correctly for

214 00:22:25.330 00:22:28.350 Robert Tseng: like for for Eden like this time around.

215 00:22:28.520 00:22:33.608 Robert Tseng: But if we don’t like, we understand, like, I think there just needs to be like

216 00:22:35.020 00:22:46.639 Robert Tseng: like, I don’t think bass data model like is terrible like, I think a part of it is like we didn’t understand it like even in the last call we had when I went on site it seemed like

217 00:22:46.780 00:22:53.970 Robert Tseng: the the team was like sharing some stuff with Damelade that, like he, they he didn’t realize before.

218 00:22:56.020 00:23:07.509 Robert Tseng: like one example would be. We’ve been trying to connect orders and transactions for the longest time, and continually like hounding like bask to do

219 00:23:07.860 00:23:09.300 Robert Tseng: till I change

220 00:23:09.820 00:23:37.400 Robert Tseng: to change their web hook so that they can connect orders and transactions. But to them those 2 entities are not linked, and that transactions were always linked to treatments, and they wanted like treatment to be like the main ledger for all the different transactions that were happening, and then, within the treatments. It’s like A, you know, one to many or many, to many relationship with with orders from there. And so it’s just like I point that out. It’s like one example of.

221 00:23:38.020 00:23:46.239 Robert Tseng: okay. Well, like, let’s say, we let this Emr team like build their product. I feel like we’re gonna run into the same thing where, like.

222 00:23:46.960 00:23:58.570 Robert Tseng: maybe like, it makes sense to them and like how they build their product. But then, when we’re trying to do all of these joins like downstream in the data layer like.

223 00:23:59.108 00:24:19.310 Robert Tseng: it’s it’s not gonna be very clean. And we’re gonna ask for something that’s like order and transactions. And they’re not gonna be able to do it. And it’s it’s like, just, it’s the same problem just in a different system. Do you understand? Like, I feel like that’s my, that’s my concern, like why we needed to

224 00:24:19.450 00:24:30.039 Robert Tseng: be involved in their engineering decisions early on anytime they’re building an object. They should send a sample like ton of tests, and so that we can. So we can help them

225 00:24:30.150 00:24:33.429 Robert Tseng: like we can be that perspective because they’re not.

226 00:24:33.730 00:24:46.749 Robert Tseng: They don’t care about like they’re they’re. I’m sure they’re not building for what the data should look like at the end, like we kind of have to be the ones that can define that for. So, anyway, I think that was a bit long, but.

227 00:24:46.750 00:25:04.449 Awaish Kumar: Yeah, like, that’s that what I understand from like, they have built the product for for their operations. So it it can run smoother. But like, that’s that’s the knowledge I I wanted to get from them like, what different data model they have and what are what are the flows on their

228 00:25:05.799 00:25:16.649 Awaish Kumar: on their platform like, if a quarter comes or treatment started, and how then it works. He was trying to explain a lot of things. But yeah, it was a lot

229 00:25:16.940 00:25:19.630 Awaish Kumar: for to to be covered in 30 min meeting.

230 00:25:19.980 00:25:20.310 Robert Tseng: No.

231 00:25:20.310 00:25:29.329 Awaish Kumar: Why we. We have requested a lot of different documentation. I hope he provides everything we need. So like, we understand the all the flows in the system.

232 00:25:29.970 00:25:38.090 Awaish Kumar: the treatment flow, or the order. How the order happened, and how the recurring, like subscription thing is working in their in their system.

233 00:25:38.330 00:25:44.770 Awaish Kumar: And if we understand that, like, we can easily join these 2 tables with with like accurately.

234 00:25:45.570 00:25:48.379 Robert Tseng: Okay, who’s the lead? Is Cameron the lead.

235 00:25:49.840 00:25:50.470 Awaish Kumar: Camera.

236 00:25:50.470 00:25:59.819 Amber Lin: Development lead on the Emr and then I believe I noted all the stakeholders somewhere. Let me grab that here.

237 00:26:00.520 00:26:01.380 Amber Lin: Sure.

238 00:26:03.690 00:26:08.300 Amber Lin: So Adam is a Pm. Lead of the Mr. Project Cameron is a Dev. Lead.

239 00:26:08.520 00:26:11.260 Robert Tseng: Oh, they haven’t. They have an atom on their side, too.

240 00:26:12.610 00:26:14.299 Amber Lin: Think it’s the same Adam.

241 00:26:14.300 00:26:16.299 Robert Tseng: Because Adam is the CEO of Eden.

242 00:26:16.520 00:26:20.600 Amber Lin: I have a feeling it’s the same people.

243 00:26:21.030 00:26:24.720 Amber Lin: Wait, Adam Mcbride.

244 00:26:24.720 00:26:25.350 Robert Tseng: Yeah.

245 00:26:25.740 00:26:28.389 Amber Lin: Yeah. So it should be the same person.

246 00:26:28.390 00:26:30.310 Robert Tseng: He’s pme the Emr.

247 00:26:31.120 00:26:34.620 Amber Lin: Think that’s what they mean about the project. Lead.

248 00:26:35.450 00:26:43.959 Robert Tseng: Okay. Well, in that case, Dude, there’s just, I’m sure Adam is not vming this thing. They’re just. He’s just letting them do whatever.

249 00:26:44.090 00:26:47.939 Robert Tseng: Oh, my goodness, this is not going gonna go. Well, okay.

250 00:26:48.450 00:26:49.659 Amber Lin: You should bring it up.

251 00:26:49.660 00:26:50.420 Robert Tseng: Yeah.

252 00:26:51.260 00:27:05.380 Robert Tseng: okay, so I’m basically going to raise this concern. So I guess, wish what I’m gonna do. I’m gonna tell Adam like they need to give us these requirements. And I’m gonna tell them the risks kind of that I just described. I’ll probably summarize it a bit clearer.

253 00:27:05.836 00:27:12.770 Robert Tseng: Yeah, I’m I’m just gonna and then if it comes from Adam, they’ll give us whatever they they need, because he’s the one paying the bills. So.

254 00:27:12.770 00:27:13.730 Amber Lin: Yeah, okay.

255 00:27:14.750 00:27:15.960 Robert Tseng: Okay, so.

256 00:27:15.960 00:27:16.370 Amber Lin: Okay.

257 00:27:16.370 00:27:19.330 Robert Tseng: That’s that’s good. I’m I’ll I’ll follow up on this.

258 00:27:19.660 00:27:20.710 Amber Lin: Okay, great.

259 00:27:21.490 00:27:23.280 Amber Lin: So skip.

260 00:27:28.980 00:27:31.680 Robert Tseng: Oh, man, it’s gonna take a while.

261 00:27:34.240 00:27:34.980 Amber Lin: Okay.

262 00:27:41.830 00:27:43.070 Amber Lin: hmm.

263 00:27:44.760 00:27:53.090 Amber Lin: yeah. I’ll try to add linear the Eden team to linear as guests. I’ll start with the most important ones and then work my way there.

264 00:27:53.090 00:27:57.730 Robert Tseng: Oh, yeah, I’m like worried about that, because I don’t want us to add, like 20 people into our linear like.

265 00:27:57.730 00:28:02.150 Amber Lin: Oh, I know. I think we can add them as guests I need to clarify.

266 00:28:02.590 00:28:05.259 Amber Lin: It should be. That’s what I was searching yesterday.

267 00:28:05.260 00:28:05.830 Robert Tseng: Okay.

268 00:28:06.320 00:28:06.910 Amber Lin: Yeah.

269 00:28:07.200 00:28:08.949 Robert Tseng: Okay. In that case I don’t care. You can add as well.

270 00:28:08.950 00:28:22.969 Amber Lin: Yeah, I think I’ll book this meeting when Harry is back, because he should. So I’m just putting it there. Mainly the I want to talk about the ad hoc tickets, and we, since we have 2 min.

271 00:28:23.293 00:28:23.939 Robert Tseng: Talking yet.

272 00:28:24.210 00:28:33.620 Amber Lin: Yeah. So I made the 2 tickets from Nick G. This one wish is for you. I included.

273 00:28:34.912 00:28:38.570 Amber Lin: The thread here. I’ll go copy over

274 00:28:40.640 00:28:46.769 Amber Lin: I’ll copy the thread so that you can read it as well. But that’s something we should do.

275 00:28:47.770 00:28:53.870 Awaish Kumar: Okay. Yeah. The SMS concern thing. I can just add.

276 00:28:59.920 00:29:01.449 Amber Lin: There’s a slack thread.

277 00:29:02.770 00:29:05.130 Amber Lin: That’s something we need to do.

278 00:29:05.990 00:29:11.540 Awaish Kumar: So customer interest model is one Swan calendar.

279 00:29:14.670 00:29:16.340 Amber Lin: rob, surance.

280 00:29:16.340 00:29:18.289 Awaish Kumar: Customer English Profiles Right.

281 00:29:24.400 00:29:25.140 Robert Tseng: Yes.

282 00:29:26.900 00:29:31.079 Awaish Kumar: It. It has already has the SMS consent. Field.

283 00:29:31.560 00:29:35.380 Robert Tseng: Oh, did it? Okay. I assume that we didn’t, because.

284 00:29:35.380 00:29:37.790 Amber Lin: Oh, okay, so this is, this is cancelled.

285 00:29:37.790 00:29:46.189 Robert Tseng: Well, it’s not even working, anyway. I I checked. Everything is marked as true. So it’s not even coming in correctly. So that’s more of a Nick G problem at this point.

286 00:29:46.190 00:29:49.079 Robert Tseng: Oh, yeah. So this is canceled.

287 00:29:53.855 00:30:08.599 Robert Tseng: but yes, I think this would be a good use case, because we haven’t pushed this model into customer. I/O, yet. So if this is the urgent thing well, I mean we can’t do it right now, cause it’s not working. We can put blocked. But yeah, I was thinking that, for when Henry comes back he can

288 00:30:08.720 00:30:13.409 Robert Tseng: make that one of the success criteria when he pushes that into customer.

289 00:30:13.580 00:30:18.870 Amber Lin: Okay, yeah. Sounds good. Is, can I close the last meeting? Follow ups.

290 00:30:20.013 00:30:23.540 Robert Tseng: Yeah. I already sent the follow ups.

291 00:30:23.540 00:30:24.110 Amber Lin: Great.

292 00:30:24.110 00:30:27.630 Robert Tseng: It was a notion, Doc, that everyone stuffed in. So it was good.

293 00:30:27.630 00:30:32.133 Amber Lin: I see. I imagine you and Annie is talking about Josh Jonah’s request.

294 00:30:32.620 00:30:33.480 Amber Lin: Okay.

295 00:30:34.150 00:30:53.719 Amber Lin: I’m gonna put in here. Annie Ronald’s request. I know he needs it mid week. Josh also chimed in to say, this is important, so I do think we should complete this. Are you still on track. Have you started yet.

296 00:30:54.020 00:30:59.069 Annie Yu: No, I’ll start and prioritize this today. But I do need enough focus time.

297 00:30:59.230 00:31:00.740 Amber Lin: Okay, yeah, no worries.

298 00:31:03.290 00:31:05.470 Amber Lin: And then this one.

299 00:31:08.980 00:31:09.975 Amber Lin: okay.

300 00:31:12.270 00:31:14.540 Amber Lin: This was Cutter’s request.

301 00:31:15.296 00:31:19.960 Amber Lin: Annie checked on this. We will need some de help

302 00:31:20.210 00:31:22.910 Amber Lin: I wish. Can Vashav help with this.

303 00:31:25.370 00:31:28.450 Awaish Kumar: But what is required, like what is the required.

304 00:31:28.450 00:31:31.950 Amber Lin: And it was required from these.

305 00:31:32.290 00:31:36.720 Annie Yu: I can share that thread and demand and also share some context. There.

306 00:31:36.720 00:31:37.220 Amber Lin: Okay.

307 00:31:37.220 00:32:03.549 Annie Yu: So I think they used to do separate. As for different methods, and now they are consolidating, they are just doing one method for all the method. 1, 2, 3, 4, 5. So I think we are trying to get all the ask spent, and then distribute it evenly to those methods. I think that’s what he did in that Pr. But I I guess the numbers are not reflected correctly as expected.

308 00:32:07.390 00:32:09.070 Awaish Kumar: Okay, what is the model?

309 00:32:10.750 00:32:12.359 Awaish Kumar: Which model is that like.

310 00:32:14.400 00:32:15.839 Annie Yu: That one.

311 00:32:16.160 00:32:23.290 Annie Yu: It’s the product sales summary by transaction. I know that he changed

312 00:32:24.060 00:32:29.089 Annie Yu: a a more upstream file. That’s that this one’s using.

313 00:32:33.130 00:32:34.750 Awaish Kumar: Is that a urgent.

314 00:32:38.628 00:32:46.419 Amber Lin: Cutter would ideally want to have it by end of week, so I wouldn’t say it’s urgent. It’s more like medium. I just wanna make sure that everybody knows.

315 00:32:46.770 00:32:53.360 Awaish Kumar: No, I I just want to understand the requirement, because this is one of the table which is more post critical table

316 00:32:53.670 00:32:56.129 Awaish Kumar: we have, and I don’t want Vashnav to

317 00:32:56.690 00:32:58.359 Awaish Kumar: who work on this right now.

318 00:32:58.590 00:32:59.885 Amber Lin: Okay, valid.

319 00:33:02.650 00:33:08.399 Amber Lin: Could you take a quick look into it, not to fix it, but just to look at what it needs.

320 00:33:10.220 00:33:12.439 Awaish Kumar: Yeah, I. And he can meet, and fair.

321 00:33:12.440 00:33:12.790 Amber Lin: Thanks.

322 00:33:13.320 00:33:14.120 Awaish Kumar: Understandable.

323 00:33:14.120 00:33:14.550 Amber Lin: Sounds good.

324 00:33:14.859 00:33:21.360 Annie Yu: Wish. Can you try to read the thread? I don’t think I have much time to meet, at least not today.

325 00:33:23.470 00:33:30.099 Awaish Kumar: Okay, maybe meet him. I wish we’ll read, maybe read the straight thread today. If you need, you guys need to meet, we can

326 00:33:30.100 00:33:31.130 Awaish Kumar: this this?

327 00:33:32.600 00:33:36.899 Awaish Kumar: Yeah, that’s what I’m looking for like, where is that in like? Is that in a

328 00:33:37.380 00:33:41.970 Awaish Kumar: like select thread which has more information than in this ticket.

329 00:33:43.825 00:33:46.100 Annie Yu: Yeah, let me find that and add.

330 00:33:48.920 00:33:50.350 Amber Lin: Okay, sounds good.

331 00:33:50.860 00:33:57.530 Amber Lin: And oh, Robert, if you need feel free to jump, I’m just gonna finish up some ad hoc stuff.

332 00:33:57.640 00:33:58.340 Awaish Kumar: No!

333 00:33:58.340 00:33:59.240 Awaish Kumar: Already! No!

334 00:33:59.240 00:34:01.309 Amber Lin: Okay, I’ve already left.

335 00:34:04.840 00:34:08.069 Amber Lin: Okay, that’s gonna be a 1 time when it comes back.

336 00:34:15.199 00:34:16.710 Amber Lin: finish request.

337 00:34:27.190 00:34:28.000 Amber Lin: Okay.

338 00:34:33.310 00:34:35.369 Amber Lin: this is something.

339 00:34:38.070 00:34:39.170 Amber Lin: Okay.

340 00:34:55.969 00:35:00.259 Amber Lin: Now, I think we’re pretty much through all the cog stuff.

341 00:35:01.960 00:35:05.460 Amber Lin: I think. Only, oh, wow!

342 00:35:06.130 00:35:07.679 Amber Lin: Enable for

343 00:35:21.650 00:35:28.000 Amber Lin: okay, I’ll do these ad grooming. Thank you guys for this meeting. I think we covered a lot

344 00:35:30.290 00:35:31.279 Amber Lin: all right.

345 00:35:31.280 00:35:32.030 Annie Yu: Thanks.

346 00:35:32.340 00:35:33.530 Amber Lin: Thanks. Everyone.