Meeting Title: Eden Weekly Kick-Off Date: 2025-07-28 Meeting participants: Amber Lin, Annie Yu, Awaish Kumar
WEBVTT
1 00:00:44.500 ⇒ 00:00:45.700 Amber Lin: Hello!
2 00:00:46.210 ⇒ 00:00:48.630 Annie Yu: Hello, Amber! How was your weekend.
3 00:00:50.699 ⇒ 00:00:55.129 Amber Lin: We went. Weekend was very nice. But and then today we have
4 00:00:55.370 ⇒ 00:00:59.279 Amber Lin: a lot of meetings. So it’s not that nice anymore.
5 00:01:02.260 ⇒ 00:01:04.330 Amber Lin: Yup, that’s Monday.
6 00:01:06.930 ⇒ 00:01:08.409 Annie Yu: Have you decided where to.
7 00:01:08.410 ⇒ 00:01:13.010 Amber Lin: So I I think
8 00:01:14.440 ⇒ 00:01:23.579 Amber Lin: I think probably still somewhere in La. But right now we’re waiting for so, my girlfriend for the job. We’ll we’ll go.
9 00:01:23.760 ⇒ 00:01:24.479 Annie Yu: Yeah, yeah, yeah.
10 00:01:24.480 ⇒ 00:01:29.250 Amber Lin: Go there, so don’t know much yet. Wait. So today.
11 00:01:29.800 ⇒ 00:01:35.280 Amber Lin: here we have you here. I don’t know if a wish has the right link.
12 00:01:36.122 ⇒ 00:01:43.379 Amber Lin: I tagged him in the group. Chat. Is there anyone else? Demo is not here. Andrew’s on another call.
13 00:01:43.840 ⇒ 00:01:45.260 Amber Lin: Okay.
14 00:01:46.128 ⇒ 00:01:48.039 Annie Yu: Let me include Vashta.
15 00:01:48.040 ⇒ 00:01:50.510 Annie Yu: Is Robert joining? Probably not.
16 00:01:51.176 ⇒ 00:01:55.840 Amber Lin: Robert is in another call with Andrew.
17 00:01:56.040 ⇒ 00:01:59.400 Amber Lin: so you will not be here.
18 00:02:02.130 ⇒ 00:02:05.820 Amber Lin: Oh, didn’t add him to the meeting.
19 00:02:05.820 ⇒ 00:02:11.339 Annie Yu: And this Raj, he’s he’s the one that’s friends with Weish.
20 00:02:11.720 ⇒ 00:02:21.340 Amber Lin: Yeah, and he’s and he’s new. So I need to add him to this meeting. Link save.
21 00:02:22.020 ⇒ 00:02:23.410 Amber Lin: Okay.
22 00:02:41.320 ⇒ 00:02:43.490 Amber Lin: Oh, I wish it’s still not here.
23 00:02:44.050 ⇒ 00:02:44.780 Amber Lin: Hmm.
24 00:03:01.510 ⇒ 00:03:05.190 Amber Lin: interesting. Okay. Give me one sec.
25 00:03:05.310 ⇒ 00:03:05.850 Amber Lin: Oh.
26 00:03:05.850 ⇒ 00:03:06.350 Annie Yu: Okay.
27 00:03:07.070 ⇒ 00:03:07.849 Amber Lin: Let’s see.
28 00:03:09.270 ⇒ 00:03:19.440 Amber Lin: Do you know, can you let me know what the progress is on? The Ltv. Project is that we were talking so the people and Robyn
29 00:03:19.520 ⇒ 00:03:39.319 Amber Lin: away, saying, Andrew and I had a meeting earlier, and we’re looking at the projects for this week. And they said, If we can’t finish this project this week. We’ll have to think about if we want to keep project. I know you wanted to do it. So I wanted to check with you. What’s the progress on that.
30 00:03:40.274 ⇒ 00:03:43.149 Annie Yu: Yeah, I yeah. So for
31 00:03:43.560 ⇒ 00:03:49.250 Annie Yu: last week I didn’t get to the 2.2. And I think 2.2 is really the main
32 00:03:52.130 ⇒ 00:03:57.480 Annie Yu: The kind of the the meat of this project, because before that.
33 00:03:57.480 ⇒ 00:03:58.040 Amber Lin: Hi.
34 00:03:58.180 ⇒ 00:04:04.820 Annie Yu: Doing exploration, and then decided what to use, what not to use. And then this to my.
35 00:04:04.820 ⇒ 00:04:09.310 Annie Yu: it would be the one that takes more time. But
36 00:04:11.040 ⇒ 00:04:21.020 Annie Yu: With this we should be able to have, like a predictive column as a deliverable but but usually after
37 00:04:21.399 ⇒ 00:04:28.480 Annie Yu: it still involves some some refinement or testing, but this is the the main part of that.
38 00:04:30.400 ⇒ 00:04:33.859 Amber Lin: Oh, okay, let me open up
39 00:04:34.640 ⇒ 00:04:37.630 Amber Lin: that one and let’s look at it.
40 00:04:38.655 ⇒ 00:04:40.290 Amber Lin: Cause if there
41 00:04:40.430 ⇒ 00:04:46.290 Amber Lin: cause I think this is the meeting where you can tell us where it might need some help on, and
42 00:04:47.059 ⇒ 00:05:03.410 Amber Lin: we can let away. Sure. Let them know on how they can assist you or help unblock you on these? Because I know we said you said this one was the main bulk of it. Then. Are any of these tickets invalid.
43 00:05:03.979 ⇒ 00:05:08.260 Amber Lin: I would, because I would love us to close this out this week.
44 00:05:08.770 ⇒ 00:05:12.990 Annie Yu: Yeah, so the
45 00:05:13.240 ⇒ 00:05:19.180 Annie Yu: like. I said, there, there, usually there should be. Follow up validation. So look at your like
46 00:05:19.470 ⇒ 00:05:28.500 Annie Yu: milestone. 3 are pretty much all validation and refinement. So that’s the usual process, and I mean.
47 00:05:30.250 ⇒ 00:05:30.690 Annie Yu: Oh, okay.
48 00:05:30.690 ⇒ 00:05:35.929 Awaish Kumar: I. I have a question like on on this project, like.
49 00:05:39.370 ⇒ 00:05:44.370 Awaish Kumar: Sorry I joined late. So yeah, sorry. If, like, what are the
50 00:05:46.020 ⇒ 00:05:56.979 Awaish Kumar: like? Did you have? Have you done anything which are like? Kind of something you you can show to the for example, Robert and and us that like
51 00:05:57.520 ⇒ 00:05:59.510 Awaish Kumar: whatever you have done on this project.
52 00:06:01.593 ⇒ 00:06:21.380 Annie Yu: So for the past tickets. All the deliverables are in a doc, because there’s no like a new column as a deliverable for the past few tickets. So I put everything in the in the doc, and then it’s the 2.2 where we should have a a like a predicted field.
53 00:06:25.160 ⇒ 00:06:32.760 Awaish Kumar: So like, for example, for the even for the baseline model. Right? Do you have any any line, charts, or anything
54 00:06:32.990 ⇒ 00:06:37.009 Awaish Kumar: which you can show like this is like our current baseline model.
55 00:06:37.470 ⇒ 00:06:40.740 Awaish Kumar: and then you compare it with visual predictions.
56 00:06:42.307 ⇒ 00:06:57.029 Annie Yu: I did not build any charts, because for the baseline, usually we, it’s not like a normal, like a regular analysis. It’s more so like directionally. We know I’m just making up because I can’t recall it off of
57 00:06:57.190 ⇒ 00:07:04.749 Annie Yu: my head now. But for the baseline it’s usually more so like what I wrote in the Doc. So people have a sense.
58 00:07:05.860 ⇒ 00:07:11.660 Awaish Kumar: For example, for baseline, like when I was working on one of the models. So
59 00:07:12.030 ⇒ 00:07:15.240 Awaish Kumar: I build a baseline based on all these.
60 00:07:15.380 ⇒ 00:07:23.000 Awaish Kumar: Well, we lost like real I was building an occupancy for forecasting.
61 00:07:23.340 ⇒ 00:07:34.530 Awaish Kumar: So I built what I took as a baseline like, for example, take last year’s data, and for each date, whatever the real occupancy is, is my baseline.
62 00:07:35.040 ⇒ 00:07:45.190 Awaish Kumar: So I’m saying that at least I should book this much right? So for that past occupancy which is my baseline model, I build a client chart, which shows.
63 00:07:45.330 ⇒ 00:07:50.920 Awaish Kumar: for example, the the occupancy from this day to this day is this, and when I build up
64 00:07:51.390 ⇒ 00:07:58.949 Awaish Kumar: when I was done with projection model the actual model and it has some forecasted values.
65 00:07:59.050 ⇒ 00:08:17.970 Awaish Kumar: Then, like you can add a new line in the same chart, which shows this is the baseline model. This is what I built, and then you. You can compare it with the the actual value which are coming in. So like you can say like, 2 weeks ago, I I projected like, after 2 weeks
66 00:08:18.340 ⇒ 00:08:26.920 Awaish Kumar: we we are going to have. for example, Ltv. Xyz. And the real value is this, baseline? Is this things like that?
67 00:08:27.250 ⇒ 00:08:29.269 Awaish Kumar: So if you could just build this
68 00:08:29.450 ⇒ 00:08:37.739 Awaish Kumar: like some some charts or something which you can like actually show to the, for example, every team member that, like what you are doing.
69 00:08:38.159 ⇒ 00:08:40.669 Awaish Kumar: No, no, that would be nice.
70 00:08:41.460 ⇒ 00:08:50.490 Annie Yu: Got it. Yeah. Cause I wrote all the findings and insights in in text instead of a a chart.
71 00:08:55.360 ⇒ 00:08:58.929 Awaish Kumar: Yeah, like having a a few charts with, you know.
72 00:08:59.170 ⇒ 00:09:04.990 Awaish Kumar: like like it can’t. It doesn’t need to be very complicated thing or out of the box right? Maybe just
73 00:09:05.640 ⇒ 00:09:11.320 Awaish Kumar: like simple line charts will be enough just to show that. Okay, that’s what I did.
74 00:09:11.600 ⇒ 00:09:13.969 Awaish Kumar: And this is the
75 00:09:14.580 ⇒ 00:09:22.390 Awaish Kumar: baseline model. This is the real Ltv, and I’m working on working like the forecasting part. And
76 00:09:22.610 ⇒ 00:09:28.390 Awaish Kumar: I build these features with that. That can be something right up, whatever
77 00:09:28.902 ⇒ 00:09:35.850 Awaish Kumar: new like features you are using for your new model. And if you have already built those, or you need someone’s help
78 00:09:36.430 ⇒ 00:09:42.320 Awaish Kumar: to to build those features for you. So things things like that right? So
79 00:09:42.730 ⇒ 00:09:48.660 Awaish Kumar: like, instead of having a detailed document, we need like these bullet points like
80 00:09:49.010 ⇒ 00:09:53.409 Awaish Kumar: this is done. This is done. This is done. I’m blocked here. I need help here and
81 00:09:53.730 ⇒ 00:09:58.640 Awaish Kumar: and like, it’s 80% done or 50% done, whatever it is.
82 00:10:01.387 ⇒ 00:10:09.429 Annie Yu: So does that mean? Yeah. So I don’t know if I should move to 2.2 now, or should I spend more time on 2.1.
83 00:10:11.300 ⇒ 00:10:12.339 Awaish Kumar: Yeah, like.
84 00:10:13.080 ⇒ 00:10:19.580 Awaish Kumar: it’s more like like this. What I’m asking is not more than like 2 h of work. Right?
85 00:10:22.180 ⇒ 00:10:27.690 Awaish Kumar: So you already have a detailed Doc, which really show every aspect of your work right?
86 00:10:27.810 ⇒ 00:10:30.610 Awaish Kumar: What I’m asking is a summarized version of that.
87 00:10:30.940 ⇒ 00:10:35.389 Awaish Kumar: You you just let let the team know, like
88 00:10:35.510 ⇒ 00:10:38.070 Awaish Kumar: the big milestones we have done.
89 00:10:38.480 ⇒ 00:10:47.849 Awaish Kumar: and which are in progress, and what? What? And if you need on something, help on something? And then what is the current task? And and on the side, if you build like
90 00:10:48.020 ⇒ 00:10:52.969 Awaish Kumar: 2, 3 line charts, I I think that should be done in a in a few hours.
91 00:10:53.840 ⇒ 00:11:02.532 Annie Yu: Yeah, yeah, no, that that works. But then to the question,
92 00:11:03.310 ⇒ 00:11:18.500 Annie Yu: to your your question, amber. If we wanna do all things this week. I think it’s usually like even the last week, the 2.2 I didn’t get to it was because I did not have enough time. It’s not because I was blocked.
93 00:11:18.500 ⇒ 00:11:25.620 Amber Lin: Hmm, so, okay, so what what amount of time would she need?
94 00:11:29.180 ⇒ 00:11:30.030 Amber Lin: Sorry.
95 00:11:31.120 ⇒ 00:11:40.629 Awaish Kumar: And you. We can talk. Since the wishes here we can talk about the time estimates for these tickets, and then we can see if it’s enough
96 00:11:40.630 ⇒ 00:11:41.680 Awaish Kumar: key points, right?
97 00:11:44.770 ⇒ 00:11:45.470 Annie Yu: Yeah.
98 00:11:46.030 ⇒ 00:11:48.070 Amber Lin: Yeah, is that an accurate estimate.
99 00:11:48.320 ⇒ 00:11:58.960 Annie Yu: Yes, I I yeah, I think the estimate itself is accurate. But I had other tickets to do. That’s why I didn’t get to the 2.2.
100 00:11:59.660 ⇒ 00:12:06.740 Awaish Kumar: So can I. Can we see amber like the full all the tickets and assigned to any, instead of just one project.
101 00:12:08.060 ⇒ 00:12:12.350 Amber Lin: Yeah, let me see. Let me go here.
102 00:12:15.910 ⇒ 00:12:16.880 Amber Lin: See?
103 00:12:22.712 ⇒ 00:12:24.879 Amber Lin: Well, right now.
104 00:12:25.520 ⇒ 00:12:29.180 Amber Lin: Okay, no. I’m sorry. It’s from over here.
105 00:12:31.070 ⇒ 00:12:35.630 Amber Lin: Active tickets by assignee.
106 00:12:37.700 ⇒ 00:12:38.520 Amber Lin: Okay.
107 00:12:41.070 ⇒ 00:12:43.895 Awaish Kumar: The only the Annie’s ticket.
108 00:12:45.290 ⇒ 00:12:47.919 Amber Lin: Yeah. Let me pull up.
109 00:12:49.850 ⇒ 00:12:50.580 Amber Lin: Huh!
110 00:12:52.400 ⇒ 00:12:55.999 Amber Lin: These are the currently active ones assigned to Annie.
111 00:12:56.100 ⇒ 00:13:04.240 Amber Lin: And so this this sprint you should be able to have less. Let me filter here as well.
112 00:13:18.420 ⇒ 00:13:22.279 Amber Lin: so this is a mess.
113 00:13:25.590 ⇒ 00:13:28.019 Amber Lin: Grouping by status.
114 00:13:28.590 ⇒ 00:13:35.040 Amber Lin: Okay, I think these were completed last week.
115 00:13:38.710 ⇒ 00:13:46.930 Amber Lin: And so I think this week, right now I there’s less stuff, and if on your plate
116 00:13:47.729 ⇒ 00:14:07.299 Amber Lin: I’ll try to limit the ones of ad hoc requests that come in, but I do think some of them would need your help to answer, especially when it’s free. With Rebecca’s request we might need you to help answer them. But I think in this meeting we want to have a
117 00:14:07.470 ⇒ 00:14:14.070 Amber Lin: accurate idea of how many hours you have and how many, how many tickets you can realistically complete.
118 00:14:18.320 ⇒ 00:14:22.560 Annie Yu: Yeah, and.
119 00:14:22.560 ⇒ 00:14:27.619 Awaish Kumar: So what is the like? Amber like? Can we
120 00:14:27.930 ⇒ 00:14:33.720 Awaish Kumar: list them based on priority? And then we can assign the store story points.
121 00:14:36.670 ⇒ 00:14:39.590 Amber Lin: You mean for this Ltv project, or just in general.
122 00:14:39.790 ⇒ 00:14:46.470 Awaish Kumar: For for like for any, all the tickets on any for Eden, we we should like right
123 00:14:47.200 ⇒ 00:14:50.599 Awaish Kumar: prioritize like, or like order them in in
124 00:14:51.030 ⇒ 00:14:53.310 Awaish Kumar: in order of priority, and then.
125 00:14:55.630 ⇒ 00:14:56.310 Amber Lin: Okay.
126 00:14:57.587 ⇒ 00:15:01.210 Amber Lin: Let’s do that priority.
127 00:15:02.570 ⇒ 00:15:08.070 Amber Lin: I think we should also note that there will be. There will be items that
128 00:15:10.150 ⇒ 00:15:13.039 Amber Lin: our ad hoc that will come in, and then I might need.
129 00:15:13.040 ⇒ 00:15:13.960 Awaish Kumar: Yeah, yeah. But that’s.
130 00:15:13.960 ⇒ 00:15:15.679 Amber Lin: To prioritize those as well.
131 00:15:16.740 ⇒ 00:15:17.900 Awaish Kumar: Yeah. But when?
132 00:15:17.900 ⇒ 00:15:20.180 Amber Lin: So this is Annie’s current
133 00:15:22.930 ⇒ 00:15:27.700 Awaish Kumar: As they come in. We are going to have it. Like as as Utham said, we are going to have a tickets, and
134 00:15:28.110 ⇒ 00:15:32.560 Awaish Kumar: and they are going to end up like we are, we at the end of the we are going to see right?
135 00:15:33.840 ⇒ 00:15:36.350 Awaish Kumar: But for now, like we can just sounds good.
136 00:15:36.350 ⇒ 00:15:39.290 Awaish Kumar: We can all put in order.
137 00:15:41.280 ⇒ 00:15:45.824 Awaish Kumar: Okay, are you okay with the current order, a like, remove some things.
138 00:15:47.810 ⇒ 00:15:48.480 Amber Lin: Me!
139 00:15:49.680 ⇒ 00:15:50.420 Awaish Kumar: Yeah.
140 00:15:51.514 ⇒ 00:15:54.130 Amber Lin: I want to add.
141 00:15:54.280 ⇒ 00:15:59.259 Amber Lin: I want to add the tickets from this Ltv project. I don’t know how much we can.
142 00:15:59.260 ⇒ 00:16:02.429 Awaish Kumar: Not. Already they are already there.
143 00:16:03.628 ⇒ 00:16:18.179 Amber Lin: We only have 2.1 and 2.2 winter mentioned. We do want to see if we can finish off this project this week. So we would need to add milestones 3 and 4, unless we’re gonna forego those tickets.
144 00:16:19.420 ⇒ 00:16:22.950 Awaish Kumar: Well, yeah, like 2, 1, 1, 2, 1, 2, and 2.3.
145 00:16:23.460 ⇒ 00:16:27.510 Awaish Kumar: They should be added into this cycle.
146 00:16:29.200 ⇒ 00:16:31.000 Awaish Kumar: For others like we can.
147 00:16:32.640 ⇒ 00:16:36.749 Awaish Kumar: Yeah, but I but that’s what I said when we put an order.
148 00:16:36.860 ⇒ 00:16:43.470 Awaish Kumar: and then we assign the story point. So we can actually see, like, what is the what is realistically possible.
149 00:16:44.070 ⇒ 00:16:46.330 Amber Lin: Okay, okay, valid.
150 00:16:47.870 ⇒ 00:16:49.469 Amber Lin: Alright, let’s go here.
151 00:16:50.100 ⇒ 00:16:54.090 Amber Lin: So let’s look at Annie’s current tickets.
152 00:16:54.520 ⇒ 00:17:01.150 Amber Lin: These 2 are in review. So those are fine. That’s urgent.
153 00:17:01.340 ⇒ 00:17:12.200 Amber Lin: That’s also in review product level monthly trend. That’s a ad hoc request from Ronald.
154 00:17:13.385 ⇒ 00:17:19.609 Amber Lin: Josh chimed in. So I do believe this is high priority, and that will take some. Annie’s time.
155 00:17:20.420 ⇒ 00:17:21.150 Awaish Kumar: Yeah.
156 00:17:28.830 ⇒ 00:17:31.049 Amber Lin: I think that all these are
157 00:17:31.280 ⇒ 00:17:34.460 Amber Lin: all the ones left are Ltv projects.
158 00:17:35.470 ⇒ 00:17:37.159 Awaish Kumar: What about? 5? 3, 1.
159 00:17:39.010 ⇒ 00:17:42.029 Amber Lin: 5, 3, 1. 0, that was the one we were just in.
160 00:17:42.170 ⇒ 00:17:48.510 Amber Lin: This is Forano. Josh did say this, we should get this to Arano, so that you believe that’s important.
161 00:17:49.710 ⇒ 00:17:51.600 Awaish Kumar: And there’s an another one also
162 00:17:52.130 ⇒ 00:17:56.319 Awaish Kumar: above it. That one is also like 5 story points.
163 00:17:58.699 ⇒ 00:18:03.730 Amber Lin: That’s 1.1. So that’s also that’s that’s completed. Actually.
164 00:18:03.730 ⇒ 00:18:07.126 Awaish Kumar: Okay, it should be in review.
165 00:18:19.590 ⇒ 00:18:21.919 Awaish Kumar: 1.1 is in review.
166 00:18:25.350 ⇒ 00:18:34.570 Awaish Kumar: Okay? So we have. So we have this 5, 3, 1, and then all the Ltv tickets, right?
167 00:18:35.010 ⇒ 00:18:35.580 Awaish Kumar: Or less.
168 00:18:35.580 ⇒ 00:18:36.120 Amber Lin: Yeah.
169 00:18:38.300 ⇒ 00:18:43.650 Awaish Kumar: So it’s like 2, 5, 3.
170 00:18:45.510 ⇒ 00:18:48.829 Awaish Kumar: It’s kind of 2 days of we can add more right then.
171 00:18:53.990 ⇒ 00:18:57.460 Amber Lin: Yeah, Annie, how many I think you have around
172 00:18:58.030 ⇒ 00:19:02.399 Amber Lin: 20 h on this project each week?
173 00:19:03.750 ⇒ 00:19:04.730 Amber Lin: Right?
174 00:19:05.980 ⇒ 00:19:11.690 Amber Lin: And for 20 h each week, I think this week.
175 00:19:14.320 ⇒ 00:19:18.879 Amber Lin: That one I wish you said probably takes about.
176 00:19:20.060 ⇒ 00:19:24.069 Awaish Kumar: Yeah, then, yeah, with the 20 h. Like, I think that’s like, that’s enough. Right
177 00:19:25.090 ⇒ 00:19:28.839 Awaish Kumar: with the store ones assigned. I’m not sure like how they were assigned.
178 00:19:29.000 ⇒ 00:19:34.919 Awaish Kumar: But with whatever is assigned based on that like, it’s enough workload for this one.
179 00:19:40.700 ⇒ 00:19:44.630 Amber Lin: yeah, and do you agree with the story points? We have here.
180 00:19:54.520 ⇒ 00:19:55.600 Annie Yu: Let’s see.
181 00:19:59.790 ⇒ 00:20:02.229 Annie Yu: Yeah, I think I I do. Wanna
182 00:20:02.550 ⇒ 00:20:07.610 Annie Yu: I do want to fit in more, but I don’t know if I can. But these ones are fair.
183 00:20:07.610 ⇒ 00:20:09.410 Amber Lin: Okay, okay?
184 00:20:10.280 ⇒ 00:20:12.430 Amber Lin: So we’ll say, that’s for this week.
185 00:20:12.780 ⇒ 00:20:13.829 Annie Yu: Then it’s that.
186 00:20:14.190 ⇒ 00:20:18.719 Annie Yu: Is that like too slow in terms.
187 00:20:18.720 ⇒ 00:20:19.860 Amber Lin: Of them.
188 00:20:19.860 ⇒ 00:20:21.370 Annie Yu: The whole project process.
189 00:20:21.370 ⇒ 00:20:29.750 Amber Lin: I do. I do think so. So in terms of the whole project. We did start 2 weeks ago, and
190 00:20:31.640 ⇒ 00:20:37.810 Amber Lin: wrap it up as soon as possible. How long would this project take?
191 00:20:46.410 ⇒ 00:20:50.849 Amber Lin: It’s another option is that if it does, if it does take.
192 00:20:50.960 ⇒ 00:21:01.039 Amber Lin: say, 3 weeks I think I’ll have to ask Utam and Robert, and they might want to have your time on other projects, too.
193 00:21:01.870 ⇒ 00:21:05.470 Annie Yu: Yeah. So I think I wanna live. Leave that
194 00:21:05.640 ⇒ 00:21:09.369 Annie Yu: to you. I mean, I mean, I can work
195 00:21:10.020 ⇒ 00:21:17.049 Annie Yu: on those tickets. But I also don’t want to work through them and then realize we
196 00:21:18.230 ⇒ 00:21:21.170 Annie Yu: are not gonna continue? Does that make sense.
197 00:21:22.050 ⇒ 00:21:30.569 Amber Lin: Okay, yeah, that makes sense. So I guess my only thing is I want to confirm, how long will this take? So I can help them, make that decision.
198 00:21:36.960 ⇒ 00:21:41.049 Awaish Kumar: From from the given story points. I I can see that.
199 00:21:41.871 ⇒ 00:21:44.480 Awaish Kumar: It it can take like
200 00:21:44.970 ⇒ 00:21:48.590 Awaish Kumar: this week, and one more week at least.
201 00:21:50.730 ⇒ 00:21:52.540 Annie Yu: Yeah, that I will agree.
202 00:21:54.860 ⇒ 00:22:03.909 Amber Lin: Okay, can we realistically complete all of these next week?
203 00:22:07.340 ⇒ 00:22:12.920 Amber Lin: If it’s 2 weeks, I think I can argue for the case to complete this project.
204 00:22:13.450 ⇒ 00:22:24.240 Awaish Kumar: But yeah, but like for amber, like, if if they have something to see like the even the Eden team, they might get interested and put can like give. Give us more time on this project.
205 00:22:24.950 ⇒ 00:22:25.440 Awaish Kumar: Like.
206 00:22:25.440 ⇒ 00:22:27.430 Amber Lin: Okay, that’s a. That’s a good point.
207 00:22:28.080 ⇒ 00:22:37.349 Awaish Kumar: If any can show like the the things I said, like the baseline model. And then in 2.2, she creates, actually a a model
208 00:22:37.700 ⇒ 00:22:40.590 Awaish Kumar: which predict levels.
209 00:22:40.900 ⇒ 00:22:45.589 Awaish Kumar: It can be like simple regulation, as as she said. But what they want is like.
210 00:22:46.225 ⇒ 00:22:57.940 Awaish Kumar: just not work in just the background, like whatever you do should be somewhere for them like for Robert to see, and for Robert to like share with client like. Okay, that’s what we are doing
211 00:22:58.240 ⇒ 00:23:03.289 Awaish Kumar: so, if you, whatever you are doing, if you build the charts alongside of that.
212 00:23:03.490 ⇒ 00:23:09.470 Awaish Kumar: then, like he can get more time on this one like they can see. Okay, they have built something.
213 00:23:09.470 ⇒ 00:23:10.279 Amber Lin: That’s a great point.
214 00:23:10.280 ⇒ 00:23:16.359 Awaish Kumar: And if something, yeah, so like 2.3 is comparing baseline with the
215 00:23:17.489 ⇒ 00:23:24.889 Awaish Kumar: with, for example, from any any simple model you build, and comparing the
216 00:23:25.050 ⇒ 00:23:34.900 Awaish Kumar: both the models side by side. Get them interested into this project, and then we might get one more week on this or 2 more weeks on this
217 00:23:35.270 ⇒ 00:23:43.279 Awaish Kumar: you can continue on this. But if you, if we are going, we are going to work in background without showing something that it might get cancelled.
218 00:23:45.520 ⇒ 00:23:47.089 Annie Yu: Yeah, yeah, that’s fair.
219 00:23:49.520 ⇒ 00:24:01.951 Amber Lin: Okay, so I’ll take that feedback. I’ll go communicate it to the team. I’ll also say also say that it needs 2 weeks, and then you will start to give more output so that we can get more time.
220 00:24:02.580 ⇒ 00:24:10.590 Amber Lin: I think one thing that you can do now, because it’s still kind of pending is to give some
221 00:24:10.920 ⇒ 00:24:14.429 Amber Lin: export 2.1, so we can show it as well.
222 00:24:15.110 ⇒ 00:24:25.269 Awaish Kumar: Amber. I just have one more comment here. So if, like, instead of saying 2 weeks, should we communicate in hours or story points? Because if any gets.
223 00:24:25.270 ⇒ 00:24:27.400 Amber Lin: Good point. Yeah, I’ll do that.
224 00:24:27.400 ⇒ 00:24:32.189 Awaish Kumar: Ad hoc request like. Then the time goes there right, and we are not going to complete this.
225 00:24:32.190 ⇒ 00:24:32.520 Amber Lin: The way.
226 00:24:32.960 ⇒ 00:24:37.110 Awaish Kumar: So we should be like, Okay, yeah, I’ll I’ll do that storyboards.
227 00:24:38.870 ⇒ 00:24:41.920 Amber Lin: Okay, yeah, I can do that.
228 00:24:44.950 ⇒ 00:24:45.870 Amber Lin: So.
229 00:24:45.870 ⇒ 00:24:52.339 Annie Yu: In the meantime, I should still, I guess, build some charts from 2.1 instead of just the write-ups.
230 00:24:53.480 ⇒ 00:24:57.119 Annie Yu: cause I I do have the write ups. I don’t have to charge, so I guess
231 00:24:58.390 ⇒ 00:25:01.629 Awaish Kumar: Yeah, like, it would be nice if we if you explain like.
232 00:25:01.780 ⇒ 00:25:07.500 Awaish Kumar: I don’t think these charts are going to be very complicated for you. You know the dashboard and stuff.
233 00:25:08.320 ⇒ 00:25:12.780 Awaish Kumar: Okay, should just take an hour and we build something.
234 00:25:12.780 ⇒ 00:25:18.209 Annie Yu: They? They might not also be like super insightful, though, but but I can build some charts.
235 00:25:19.050 ⇒ 00:25:26.080 Awaish Kumar: Yeah, like, once you build them, you might get feedback from Robert or something, and then they might get more insight from there.
236 00:25:26.730 ⇒ 00:25:27.280 Annie Yu: Yeah.
237 00:25:28.030 ⇒ 00:25:30.450 Amber Lin: Okay.
238 00:25:34.772 ⇒ 00:25:45.070 Amber Lin: I guess one last question, why did never mind? It took long. Because you I was trying to think why it took so long. Was it because you had a lot of ad hoc
239 00:25:45.310 ⇒ 00:25:46.370 Amber Lin: requests.
240 00:25:47.219 ⇒ 00:25:55.660 Annie Yu: That was part of it, and I think I spent more time on the snapshot snapshot
241 00:25:55.820 ⇒ 00:26:01.620 Annie Yu: because we we tested the model for for a few days, and couldn’t figure out.
242 00:26:02.390 ⇒ 00:26:06.839 Annie Yu: Eventually I wrote a query, and I think that’s working
243 00:26:07.690 ⇒ 00:26:13.040 Annie Yu: good now. But that took me a few hours, because I expect to.
244 00:26:13.040 ⇒ 00:26:14.510 Amber Lin: I see. I see.
245 00:26:17.920 ⇒ 00:26:18.730 Amber Lin: I see.
246 00:26:26.130 ⇒ 00:26:38.580 Amber Lin: okay, thanks everyone. I think I I need more time to room this cycle. And yeah, I have.
247 00:26:38.580 ⇒ 00:26:38.980 Awaish Kumar: She!
248 00:26:38.980 ⇒ 00:26:57.410 Amber Lin: Hop to another meeting soon, which I don’t think I can join the Emr meeting with you, because there’s a lot of ad hoc tickets that I want to create that. But if you want my help creating the roadmap, so I’ll transcript from that meeting. And see what we can. Is that okay with you? Or do you want me at the meeting?
249 00:26:59.621 ⇒ 00:27:01.779 Awaish Kumar: Yeah, that’s okay. I can
250 00:27:02.320 ⇒ 00:27:06.859 Awaish Kumar: talk to him. I I will take the notes so I can. And I can share with you.
251 00:27:07.670 ⇒ 00:27:13.467 Amber Lin: Okay, yeah, sounds good. And then we have. It’s using my meeting room. So it would record everything.
252 00:27:14.870 ⇒ 00:27:20.600 Amber Lin: yeah, I sent it for to Cameron. I don’t know if he has accepted.
253 00:27:21.400 ⇒ 00:27:28.580 Amber Lin: Yeah, so that would be in half an hour, and I’ll hop to the ABC. Planning meeting.
254 00:27:29.420 ⇒ 00:27:31.530 Amber Lin: So is that let’s see.
255 00:27:32.250 ⇒ 00:27:33.819 Awaish Kumar: So do you need me on this one.
256 00:27:33.820 ⇒ 00:27:42.860 Amber Lin: I think that’s is the data is the data issue resolved for ABC guide.
257 00:27:43.290 ⇒ 00:27:45.260 Awaish Kumar: Yeah, no like I don’t.
258 00:27:45.260 ⇒ 00:27:48.089 Amber Lin: Be there for the first, st like 5 to 10 min.
259 00:27:49.514 ⇒ 00:27:54.320 Amber Lin: Don’t need you for the whole 30, but it’s just on the data side might need some help.
260 00:27:54.760 ⇒ 00:27:59.597 Amber Lin: Okay, I’m I’m on this. Actually, that’s why I was saying I’m working on that.
261 00:28:00.860 ⇒ 00:28:02.759 Awaish Kumar: Right now, I want to just.
262 00:28:02.760 ⇒ 00:28:03.130 Amber Lin: Yeah.
263 00:28:03.130 ⇒ 00:28:04.719 Awaish Kumar: In the next 30 min, sir.
264 00:28:06.990 ⇒ 00:28:11.299 Amber Lin: Okay, I’ll hop to the ABC. Yeah, probably.
265 00:28:11.300 ⇒ 00:28:13.660 Amber Lin: Only need you guys there for like, 5 or 10.
266 00:28:13.930 ⇒ 00:28:14.780 Annie Yu: Yeah, yeah.
267 00:28:16.650 ⇒ 00:28:17.590 Amber Lin: Alrighty!