Meeting Title: ABC Standup Date: 2025-07-02 Meeting participants: Mustafa Raja, Amber Lin, Luke Daque, Brainforge


WEBVTT

1 00:01:18.510 00:01:19.890 Amber Lin: Hello!

2 00:01:20.680 00:01:21.849 Mustafa Raja: Hey! How are you?

3 00:01:22.060 00:01:22.980 Amber Lin: I’m good.

4 00:01:24.338 00:01:26.929 Amber Lin: Let me pull up linear.

5 00:01:27.390 00:01:30.459 Amber Lin: Think today will be a pretty quick stand up

6 00:01:37.240 00:01:44.149 Amber Lin: because for for your ticket is is everything up to date.

7 00:01:47.215 00:01:53.040 Mustafa Raja: Yeah, I would just want to know. How would you want to set this up?

8 00:01:54.731 00:02:10.750 Mustafa Raja: what I mean by that is how should this new integration be triggered? Should this something? Should this be something like the thing that we previously did

9 00:02:11.240 00:02:12.260 Mustafa Raja: for the other ticket?

10 00:02:12.732 00:02:25.320 Amber Lin: Yeah, I think so. So it’s say, similarly, when we press a, button run workflow

11 00:02:25.990 00:02:34.079 Amber Lin: show in column, so I think in that, in that workflow.

12 00:02:34.360 00:02:35.230 Mustafa Raja: Yeah.

13 00:02:35.850 00:02:38.279 Mustafa Raja: And did you get to take a look at the other one?

14 00:02:39.090 00:02:41.310 Amber Lin: Oh, no, I haven’t. My bad.

15 00:02:41.450 00:02:42.970 Mustafa Raja: Oh, yeah, I would say.

16 00:02:42.970 00:02:43.480 Amber Lin: Oh, okay.

17 00:02:43.480 00:02:45.880 Mustafa Raja: It’s a so it’s super easy.

18 00:02:46.450 00:02:48.885 Amber Lin: Okay, sounds good. I’ll go. Look at that.

19 00:02:49.190 00:02:53.699 Mustafa Raja: Okay, okay, and one more thing about this.

20 00:02:54.669 00:03:07.969 Mustafa Raja: I’ve spent almost 45 min so far on this ticket the one that I’m working on right now. Let me know how much this week I can spend on it if I need to.

21 00:03:08.800 00:03:16.369 Amber Lin: I see well, I think this 1 first, st we need to do rack right when we say when we say 3 points is probably

22 00:03:16.530 00:03:28.649 Amber Lin: close, like upper limit of of 6 HI don’t think I I remember you said you don’t think this will take 6 h, but, like that’s the amount we allocated so

23 00:03:29.760 00:03:36.730 Amber Lin: like it’ll be great if we can finish this sooner. But I think that’s that’s a pretty

24 00:03:39.670 00:03:43.859 Amber Lin: wide estimate of how much time we can spend on it.

25 00:03:44.830 00:03:45.630 Mustafa Raja: Yeah, yeah.

26 00:03:46.300 00:04:02.430 Mustafa Raja: yeah. So what? So what I meant is, for this week, how much I can spend on I’ve already worked for like one and a half hour for other ticket and 45 min on this. So in total, my, this week’s

27 00:04:03.572 00:04:10.039 Mustafa Raja: time spent on ABC. Would be 2 h and 15 min. So far.

28 00:04:11.440 00:04:16.279 Amber Lin: Okay, I see. I guess we can.

29 00:04:17.440 00:04:27.379 Amber Lin: I mean, this is for these 2 weeks. Right? So if we if we do this one, and thank you for reminding me of the times. I think once we do

30 00:04:27.770 00:04:32.530 Amber Lin: this one that’s pretty much for these 2 weeks.

31 00:04:32.740 00:04:35.370 Amber Lin: So I think

32 00:04:35.990 00:04:45.739 Amber Lin: I think that’s okay. If you you can do this this week we’ll just move your allocations from next week to this week. So you would have.

33 00:04:45.740 00:04:48.109 Mustafa Raja: Oh, no time to complete this one.

34 00:04:48.650 00:04:52.800 Mustafa Raja: Okay, okay, okay, okay, yeah. That makes sense.

35 00:04:53.270 00:04:53.950 Amber Lin: Here.

36 00:04:54.780 00:04:55.290 Mustafa Raja: Yeah.

37 00:04:55.290 00:04:55.970 Amber Lin: Okay.

38 00:04:56.350 00:04:56.680 Mustafa Raja: Okay.

39 00:04:56.680 00:04:57.390 Amber Lin: Awesome.

40 00:04:57.840 00:04:58.510 Mustafa Raja: Yeah.

41 00:04:59.070 00:05:08.260 Amber Lin: Do you know? Oh, Hi, Luke, Mustafa feel free to hop off? I think I’ll just. I’ll talk with Casey and Luke, and that should be everything.

42 00:05:08.770 00:05:10.349 Mustafa Raja: Okay. Okay. Bye, bye.

43 00:05:10.350 00:05:12.149 Amber Lin: Alright thanks. Bye!

44 00:05:13.380 00:05:14.750 Amber Lin: Hello, Luke!

45 00:05:17.437 00:05:23.700 Luke Daque: I think I might need help from. I wish on this the the yeah, the.

46 00:05:23.700 00:05:24.360 Amber Lin: Stay tuned.

47 00:05:24.360 00:05:24.990 Luke Daque: Data.

48 00:05:25.630 00:05:25.990 Amber Lin: Okay.

49 00:05:25.990 00:05:31.349 Luke Daque: S. 3. I haven’t started the S. 3 to really yet, because I was like focusing on that.

50 00:05:31.730 00:05:32.949 Luke Daque: as I think.

51 00:05:33.448 00:05:39.480 Luke Daque: But yeah, I think I might need help from a wish, because, like, it’s probably I’m

52 00:05:39.770 00:05:44.110 Luke Daque: not doing the correct doing it correctly or something, because I can’t.

53 00:05:45.560 00:05:49.400 Luke Daque: I I can’t like figure out which tables are needed.

54 00:05:50.670 00:05:56.020 Luke Daque: But yeah, maybe I’ll try to set up time with Aish today.

55 00:05:56.740 00:05:57.140 Amber Lin: Sure.

56 00:05:57.140 00:05:59.719 Luke Daque: For that. So we can like push through with that.

57 00:06:00.350 00:06:03.939 Amber Lin: Okay, can this be done today?

58 00:06:05.470 00:06:08.729 Luke Daque: Yeah, I can. Yeah, I can try to work on that one.

59 00:06:09.290 00:06:11.590 Amber Lin: Yeah, that would be. That would be great.

60 00:06:11.890 00:06:15.889 Luke Daque: Don’t we have a real dashboard already for ABC. Though.

61 00:06:16.060 00:06:17.020 Amber Lin: Yes, we do.

62 00:06:17.430 00:06:19.840 Luke Daque: And it’s already connected to S. 3.

63 00:06:21.190 00:06:24.169 Luke Daque: It’s connected to a different data source.

64 00:06:24.170 00:06:27.709 Amber Lin: I’m not sure it’s probably connected to Snowflake, but we want.

65 00:06:27.710 00:06:28.280 Luke Daque: To be.

66 00:06:28.280 00:06:30.100 Amber Lin: Able to use the new data.

67 00:06:30.870 00:06:33.969 Luke Daque: I see, so would it be.

68 00:06:34.360 00:06:39.160 Amber Lin: It might be better to use. I I don’t know.

69 00:06:39.807 00:06:47.669 Amber Lin: We already had some things set up in real that Annie did so let me quickly show you what it looks like.

70 00:06:49.300 00:06:49.950 Luke Daque: Okay?

71 00:06:52.260 00:06:58.970 Luke Daque: Like, I was wondering, would this connection be for the same real project that we have, which

72 00:06:59.390 00:07:05.860 Luke Daque: which basically means we will have 2 sources for that real project, one coming from sounds like it.

73 00:07:05.860 00:07:07.050 Luke Daque: one from s. 3.

74 00:07:07.050 00:07:13.139 Amber Lin: I see. So I think what we will do is we can make one

75 00:07:13.310 00:07:19.830 Amber Lin: to develop for now, and once the current one we’re setting up. It’s done. We’ll remove the previous one.

76 00:07:20.130 00:07:22.690 Luke Daque: So we have.

77 00:07:23.706 00:07:31.159 Amber Lin: We have 2 reports. The the last one is just evaluations. So this one is

78 00:07:31.560 00:07:41.429 Amber Lin: for our internal bot performance. So this wouldn’t be as affected. So this is not related to the 8 by 8 data that we’re getting.

79 00:07:42.830 00:07:52.439 Amber Lin: This one, this one is what gets affected by the different.

80 00:07:52.950 00:07:54.390 Luke Daque: By the different

81 00:07:56.220 00:07:57.840 Amber Lin: Data that we’re getting in.

82 00:07:59.960 00:08:07.830 Amber Lin: So a few things that was done here. So 1st of all, stuff up here, so stuff

83 00:08:08.170 00:08:17.060 Amber Lin: from call kpis all the way down to call count by rep. These are all directly from 8 by 8,

84 00:08:17.380 00:08:18.179 Amber Lin: and then.

85 00:08:18.180 00:08:19.250 Luke Daque: Nice.

86 00:08:19.540 00:08:30.650 Amber Lin: What Annie did is they did it. I think she did a join based on either user, I think username. So then we were able to get the calls here that

87 00:08:30.990 00:08:42.250 Amber Lin: this user used Andy on. So we, I think you will be able to see her logic in real. She also documented it somewhere. So she joined

88 00:08:42.951 00:08:47.169 Amber Lin: essentially, the 8 by 8 data with our internal data.

89 00:08:47.480 00:08:49.849 Amber Lin: And then we were able to get these.

90 00:08:50.610 00:08:51.530 Luke Daque: Gotcha.

91 00:08:51.740 00:08:53.020 Amber Lin: But that’s.

92 00:08:53.480 00:08:57.860 Luke Daque: That 8 by 8 data is in Snowflake at the moment. The one that Annie.

93 00:08:58.248 00:09:07.560 Amber Lin: Yes, yes, I think it’ll be helpful if you look at look at the data in Snowflake and see what it says, because

94 00:09:07.950 00:09:15.680 Amber Lin: that was manually downloaded from 8 by 8 by the we see people, Gotcha.

95 00:09:15.680 00:09:17.500 Amber Lin: See if I can.

96 00:09:19.010 00:09:19.710 Luke Daque: Yeah.

97 00:09:19.710 00:09:23.030 Amber Lin: How would I send? Give you access to this?

98 00:09:23.760 00:09:27.949 Amber Lin: Do I send you a 1 pass, or I send you the link to this.

99 00:09:27.950 00:09:30.920 Luke Daque: Do you have? Do you have an admin access to.

100 00:09:31.410 00:09:35.330 Amber Lin: Let me make. Does that mean I’m admin.

101 00:09:37.930 00:09:39.979 Amber Lin: No, I don’t think so.

102 00:09:40.540 00:09:46.119 Luke Daque: So if you go to yeah, if you go to user roles and accounts and then see if you can

103 00:09:48.070 00:09:52.239 Luke Daque: ground overall. I don’t think I don’t think you have.

104 00:09:53.160 00:09:56.770 Luke Daque: You can just view who awesome granting

105 00:09:56.980 00:10:02.380 Luke Daque: rules, but you can’t create one. Maybe we can ask a wish to give me access.

106 00:10:02.800 00:10:05.259 Amber Lin: Does the wish have admin on this.

107 00:10:05.260 00:10:06.400 Luke Daque: I don’t know, or maybe it’s.

108 00:10:06.400 00:10:07.040 Amber Lin: I think.

109 00:10:07.040 00:10:09.449 Luke Daque: Maybe old Time, or Who’s who’s.

110 00:10:10.100 00:10:15.680 Amber Lin: Casey Casey should be able to give you access.

111 00:10:16.400 00:10:17.030 Brainforge: Hey, guys.

112 00:10:17.030 00:10:18.780 Amber Lin: So hi.

113 00:10:18.780 00:10:19.120 Brainforge: Nice.

114 00:10:19.120 00:10:22.620 Amber Lin: Do you have? Do you have admin access on Snowflake.

115 00:10:23.331 00:10:31.470 Brainforge: I yeah, I just, I wish was asking me earlier, and I couldn’t grant roles either. I think it’s it might only be Utah. I’m not sure.

116 00:10:31.470 00:10:34.770 Amber Lin: Oh, okay.

117 00:10:36.250 00:10:37.130 Amber Lin: Oh.

118 00:10:40.260 00:10:49.329 Amber Lin: the system system. Admin. Okay, let’s so a wish. And Luke needs access to Snowflake. Right?

119 00:10:49.680 00:10:50.130 Luke Daque: Yes.

120 00:10:50.380 00:10:54.360 Amber Lin: Oh, go! Ask that.

121 00:10:55.000 00:11:01.329 Brainforge: Yeah, I don’t understand the roles, either, it says his admin. But I I can’t create anything. Yeah.

122 00:11:02.490 00:11:03.520 Amber Lin: No worries.

123 00:11:04.250 00:11:07.050 Amber Lin: Oh, huh!

124 00:11:07.800 00:11:15.550 Amber Lin: Wait! Does this does this mean? I just need to add you to Snowflake.

125 00:11:16.620 00:11:22.030 Luke Daque: Yeah, let’s probably just ask ultam. Maybe he has the Admin actual admin access.

126 00:11:22.330 00:11:23.220 Amber Lin: Yeah.

127 00:11:23.220 00:11:24.000 Luke Daque: What else?

128 00:11:26.270 00:11:34.070 Amber Lin: How do I share this specific link?

129 00:11:34.660 00:11:35.990 Amber Lin: Let me try.

130 00:11:38.160 00:11:44.360 Amber Lin: Can you see if you can open that? If you already have admin, if not like, I’ll I’ll ping you, Tom.

131 00:11:45.380 00:11:53.560 Luke Daque: No, I don’t think I will have just like you need need to add that access.

132 00:11:54.870 00:11:56.749 Luke Daque: But yeah, let me open it

133 00:12:06.580 00:12:07.640 Luke Daque: golden.

134 00:12:09.840 00:12:13.280 Luke Daque: Yeah, it’s asking for a username and password. So.

135 00:12:16.490 00:12:20.240 Amber Lin: I see no worries. Let me go.

136 00:12:23.910 00:12:24.830 Amber Lin: Yeah.

137 00:12:46.930 00:12:47.730 Amber Lin: okay.

138 00:12:48.190 00:12:49.619 Amber Lin: Sounds good.

139 00:12:50.370 00:12:52.440 Amber Lin: I think that would. That would help

140 00:12:52.790 00:12:59.339 Amber Lin: if we get to look at these, and I think Annie’s where is that?

141 00:13:00.171 00:13:04.479 Amber Lin: Annie also wrote down some of the logic that she did when she.

142 00:13:04.480 00:13:04.870 Luke Daque: Increase.

143 00:13:04.870 00:13:08.559 Amber Lin: That dashboard. So that would also be helpful.

144 00:13:08.980 00:13:11.989 Amber Lin: I think, for now we can just

145 00:13:12.890 00:13:15.459 Amber Lin: we can create a new one.

146 00:13:15.670 00:13:22.610 Amber Lin: Or let’s see, we hmm.

147 00:13:23.460 00:13:32.649 Amber Lin: Let’s just connect it to see if it works. We can create a test dashboard to see if it actually connects. I just wanted to be able to present

148 00:13:32.860 00:13:39.749 Amber Lin: presents, or we’re not meeting with them. So as long as this gets done, I think it’ll be a lot easier

149 00:13:40.240 00:13:49.899 Amber Lin: to like. Compare what data I mean. You can also just put all of it in in real. I don’t know which one’s easier as long as we get it connected that should be good.

150 00:13:52.350 00:13:53.110 Luke Daque: Okay.

151 00:13:53.840 00:13:55.960 Amber Lin: Yeah, let me check.

152 00:13:56.250 00:13:59.629 Amber Lin: Oh, great! This has all data. I’m I’m going to go cancel that

153 00:14:03.360 00:14:06.760 Amber Lin: status canceled.

154 00:14:07.390 00:14:08.290 Amber Lin: Great.

155 00:14:11.780 00:14:14.849 Amber Lin: I think. Look! That’s all everything for this.

156 00:14:15.180 00:14:23.209 Amber Lin: I I’ll just ping here to grab time with a waste.

157 00:14:24.390 00:14:28.830 Amber Lin: I’ll just ping you here.

158 00:14:29.590 00:14:32.308 Luke Daque: Sounds good. Yeah, I also already. Message, I wish

159 00:14:32.610 00:14:33.570 Amber Lin: Oh, okay.

160 00:14:33.570 00:14:35.810 Luke Daque: So yeah, hopefully, he replies.

161 00:14:37.020 00:14:50.410 Amber Lin: Okay, I’ll just say, let us know how it goes with this. Okay, great.

162 00:14:50.760 00:14:55.390 Amber Lin: Okay. Thanks. Luke. Feel free to hop off. I’ll talk with Casey.

163 00:14:55.840 00:14:57.509 Luke Daque: Sounds, good thanks. Thanks. Guys.

164 00:14:57.510 00:14:58.330 Amber Lin: And thanks.

165 00:15:02.860 00:15:03.690 Amber Lin: Okay.

166 00:15:07.000 00:15:07.880 Amber Lin: Oh.

167 00:15:07.960 00:15:09.760 Brainforge: I just finished this one.

168 00:15:09.950 00:15:10.930 Amber Lin: Awesome.

169 00:15:12.150 00:15:13.780 Amber Lin: So let me check.

170 00:15:14.100 00:15:23.000 Amber Lin: We have 1, 2, 3, that one I haven’t talked to you about, so ignore the last one.

171 00:15:23.260 00:15:28.639 Amber Lin: So this one. Let me go check real quick.

172 00:15:31.590 00:15:32.580 Amber Lin: Awesome.

173 00:15:32.970 00:15:38.579 Amber Lin: Thank you. Thank you. I’ll do the internal review for that.

174 00:15:41.510 00:15:43.849 Amber Lin: Any help you need for this one.

175 00:15:44.890 00:15:46.899 Brainforge: And I just haven’t started this yet.

176 00:15:47.160 00:15:48.320 Amber Lin: Hmm, okay.

177 00:15:49.380 00:15:52.380 Brainforge: Yeah, I can dedicate some time later for this.

178 00:15:53.660 00:16:06.999 Amber Lin: That sounds good. I’ve already. There’s already some stuff here, so probably we can just copy and paste the central doc over, let it run it, and then copy and paste all the comments

179 00:16:07.350 00:16:10.740 Amber Lin: in that spreadsheet, and run, run the AI again.

180 00:16:11.030 00:16:12.940 Amber Lin: so that should be pretty fast.

181 00:16:13.310 00:16:13.980 Brainforge: Okay.

182 00:16:14.430 00:16:15.155 Amber Lin: Yeah.

183 00:16:16.090 00:16:24.689 Amber Lin: I think this was a. This was a similar thing that we have to the service coverage service coverage one.

184 00:16:24.860 00:16:31.090 Amber Lin: So back to the Central Doc messages.

185 00:16:35.440 00:16:38.079 Amber Lin: So I’m trying to.

186 00:16:38.440 00:16:45.720 Amber Lin: I was trying to create a list of all the different codes.

187 00:16:48.460 00:16:55.670 Amber Lin: I don’t think you need to get started on this one. I’ll flesh out the tickets a little bit more, but it’s pretty similar to

188 00:16:56.245 00:17:02.300 Amber Lin: the master coverage list is when, whenever a service code was mentioned somewhere.

189 00:17:03.610 00:17:09.549 Amber Lin: in the central talk. We can put it. We can put it here, but I’ll flush out the requirements.

190 00:17:10.200 00:17:16.029 Amber Lin: and we can probably talk about it tomorrow, when the other ticket is done.

191 00:17:16.339 00:17:17.289 Brainforge: Alright, then.

192 00:17:17.750 00:17:19.710 Amber Lin: Okay, yeah.

193 00:17:20.413 00:17:22.880 Amber Lin: Oh, the spreadsheet one.

194 00:17:23.720 00:17:27.019 Amber Lin: Were we able to do a test on that.

195 00:17:27.569 00:17:29.149 Brainforge: Oh, no, no, not yet.

196 00:17:29.490 00:17:36.710 Amber Lin: Okay, no worries. So let’s say, step one. What do we say was, gonna be our 1st

197 00:17:36.970 00:17:40.299 Amber Lin: 1st test is just to connect it with Nan.

198 00:17:40.500 00:17:47.179 Brainforge: Yeah, we’ll just, you know, do the same approach. For now where we add it to the context.

199 00:17:48.520 00:17:51.890 Brainforge: And then, if that’s not gonna work, then

200 00:17:52.090 00:17:54.049 Brainforge: I’ll migrate it to super base.

201 00:17:55.970 00:18:08.250 Amber Lin: Okay, that’s NAN, and if it doesn’t work migrate to super base.

202 00:18:09.430 00:18:13.000 Amber Lin: I think we need to transpose

203 00:18:15.020 00:18:20.279 Amber Lin: and migrate to super base. How long would this initial test take?

204 00:18:23.170 00:18:29.819 Brainforge: I think 2 2 points should be a good estimate.

205 00:18:31.680 00:18:33.379 Amber Lin: Okay. So I’ll say.

206 00:18:36.400 00:18:39.579 Amber Lin: if it doesn’t work we’ll make another ticket. So

207 00:18:41.450 00:18:41.990 Brainforge: Bye.

208 00:18:42.140 00:18:51.879 Amber Lin: So alright. We can say that this is, we’ll test this before Friday.

209 00:18:53.166 00:18:57.359 Amber Lin: Let me know if we wanna test it together.

210 00:18:58.360 00:18:58.770 Brainforge: Okay.

211 00:18:59.320 00:19:00.720 Amber Lin: Yeah, sounds good.

212 00:19:01.870 00:19:03.460 Amber Lin: I’ll talk to you tomorrow. Then.

213 00:19:03.960 00:19:05.150 Brainforge: Okay. Yeah. Thanks. Amber.

214 00:19:05.150 00:19:06.550 Amber Lin: Alright. Thank you.