Meeting Title: AI Team Weekly Planning Date: 2025-03-24 Meeting participants: Amber Lin, Janiecegarcia, Miguel De Veyra, Casie Aviles


WEBVTT

1 00:02:23.980 00:02:25.359 Miguel de Veyra: Hey? Guys, good morning.

2 00:02:26.830 00:02:27.780 JanieceGarcia: Morning.

3 00:02:38.470 00:02:40.199 Amber Lin: Good morning, Janice.

4 00:02:41.120 00:02:41.900 JanieceGarcia: Ping.

5 00:02:43.380 00:02:44.480 Amber Lin: I have a lot less.

6 00:02:45.900 00:02:47.280 Amber Lin: I’m doing great

7 00:02:47.280 00:02:47.990 JanieceGarcia: Well, in.

8 00:02:48.480 00:02:51.400 Amber Lin: Yeah, a lot less fallen. So it’s nice.

9 00:02:51.650 00:02:52.540 Amber Lin: But it’s still there.

10 00:02:55.440 00:02:56.709 Amber Lin: Hi, team.

11 00:02:56.900 00:02:59.209 Amber Lin: Okay, we have everybody.

12 00:02:59.360 00:03:02.040 Amber Lin: So let me pull up.

13 00:03:03.090 00:03:17.909 Amber Lin: Let me just pull up what we talked about last Friday. So this meeting, we essentially just talk about what we want to do this week and what we want to prioritize. First, st because there’s a lot that

14 00:03:18.370 00:03:29.940 Amber Lin: we want to. So Janice will be really helpful in letting us know. Okay, this is the most important stuff right now, so let me pull up away what I sent.

15 00:03:39.667 00:03:42.049 Amber Lin: Here, let me share my screen.

16 00:03:43.600 00:03:45.450 Amber Lin: Here is

17 00:03:49.860 00:03:59.110 Amber Lin: so last Friday we talked about a few things so talked about the dashboard.

18 00:03:59.851 00:04:10.139 Amber Lin: Current progress, the phase 2 rollout, and then this is for utam, and then that’s not for us.

19 00:04:10.670 00:04:11.220 JanieceGarcia: Right.

20 00:04:11.760 00:04:18.010 Amber Lin: And so, okay, these. So we’re looking at these things.

21 00:04:18.810 00:04:24.049 Amber Lin: And so for the dashboard, we know that

22 00:04:24.540 00:04:35.719 Amber Lin: for the exacts they want a high level quality score, because right now we have the breakdown. But we don’t have the one single score score that’s easy to understand.

23 00:04:35.910 00:04:43.840 Amber Lin: and we also want to track the number of incorrect answers over time. So that’s 2 things for the dashboard

24 00:04:43.960 00:04:55.170 Amber Lin: and for the bot performances. I think this is just we continue to polish it as we work on the answers as we

25 00:04:57.030 00:05:04.989 Amber Lin: as we continue testing and knowledge knowledge management. This is pretty much done.

26 00:05:05.390 00:05:12.630 Amber Lin: This Janice, you have done a lot on it, I think on our team. We need to update the bot’s answers to check

27 00:05:12.830 00:05:19.659 Amber Lin: if they’re more accurate now because a lot of the bots. Answers are a little bit older. So we need to do that.

28 00:05:20.440 00:05:27.280 Amber Lin: And about the turn handling scenarios. This is the safe tactics, right

29 00:05:29.060 00:05:34.800 Amber Lin: Do you happen to have the documents, or is there someone we should go talk to for that document

30 00:05:35.680 00:05:43.780 JanieceGarcia: No, I know she’s working on those right now, so I’m not sure if she has the pest ones. But I can definitely ask

31 00:05:44.750 00:05:45.170 Amber Lin: Okay.

32 00:05:45.170 00:05:45.620 JanieceGarcia: I can.

33 00:05:45.620 00:05:45.960 Amber Lin: Sure.

34 00:05:45.960 00:05:47.599 JanieceGarcia: I can get with Yvette and ask her

35 00:05:47.980 00:05:53.980 Amber Lin: Okay, sounds good. And then this is the training bot is in development.

36 00:05:54.180 00:06:00.770 Amber Lin: And the last item that we talked about is the Csr bot rollout. So I think.

37 00:06:01.080 00:06:23.980 Amber Lin: in my opinion, this is pretty important, because we need to get head start because it relies on other people as well. It. Realize also on the Cs office we need to pick who’s going? It’s who’s it gonna be? And then we need to tell them what this is and get them to use it. And then we need to know what we’re collecting from them. So

38 00:06:24.060 00:06:33.499 Amber Lin: just out of all of these, Janice, what is your feeling of what we should do, one to immediately, and to put our priorities on

39 00:06:34.460 00:06:38.669 JanieceGarcia: Definitely updating the bot. Answers double, checking those

40 00:06:39.670 00:06:46.109 JanieceGarcia: Because we’re going to actually use. There’s a couple new hires for pests

41 00:06:46.110 00:06:46.450 Amber Lin: Don’t!

42 00:06:46.902 00:06:54.590 JanieceGarcia: And so that’s who they’re going to use on the testing. Besides, just myself. Shannon and Grace

43 00:06:57.670 00:07:01.490 Amber Lin: I see. So let me pull up our

44 00:07:02.212 00:07:18.310 Amber Lin: task tracker. And then i’ll mark it as most important here, share thing here, so let’s see.

45 00:07:26.620 00:07:28.080 Amber Lin: Where is it?

46 00:07:30.340 00:07:34.199 Amber Lin: And this one will to be.

47 00:07:34.950 00:07:36.010 Amber Lin: And

48 00:07:38.350 00:07:59.209 Amber Lin: so this is. This is important, so that we I mean you already put in all the ideal answers. So right now, what we’re gonna do when we fill in the new bot answers essentially, just to check. Okay, how similar it is right now. So we can say, Okay, we’re pretty confident that the bot is going to do that right.

49 00:07:59.890 00:08:00.510 JanieceGarcia: Right.

50 00:08:00.880 00:08:07.880 Amber Lin: Okay, sounds good. Let’s make that a priority day.

51 00:08:10.230 00:08:11.080 Amber Lin: Okay?

52 00:08:15.030 00:08:27.490 Amber Lin: Okay, let’s, we can assign this a little bit later, so that I think smoothly. Here.

53 00:08:28.723 00:08:34.090 Amber Lin: What’s next? What do you think is next on?

54 00:08:34.480 00:08:41.229 Amber Lin: Oh, what do you think is next? On what’s most important

55 00:08:42.640 00:08:44.059 JanieceGarcia: Oh!

56 00:08:48.040 00:08:53.460 Amber Lin: And maybe we should. Do we know who we’re handing it out to like? Do we need a group of 5

57 00:08:54.750 00:08:56.420 JanieceGarcia: I do not know

58 00:08:56.420 00:08:59.639 Amber Lin: Oh, well, who do you think will be best?

59 00:08:59.970 00:09:05.480 Amber Lin: Yeah. Event, probably, if that will let you maybe pick because

60 00:09:06.680 00:09:10.089 Amber Lin: Maybe I know you said there’s some I know

61 00:09:10.880 00:09:12.819 JanieceGarcia: There’s there are!

62 00:09:12.820 00:09:13.460 Amber Lin: Oh,

63 00:09:15.060 00:09:23.329 JanieceGarcia: Well, they are they’re already training right now on the pest side. And then I I know I have a couple that are starting, but

64 00:09:23.540 00:09:27.779 JanieceGarcia: today they’re literally starting today. So

65 00:09:28.490 00:09:33.139 JanieceGarcia: they won’t be ready for the button till like the end of next week or the following week.

66 00:09:33.690 00:09:36.920 JanieceGarcia: with the ones that I have today. But I think there’s

67 00:09:37.130 00:09:44.530 JanieceGarcia: there’s 2 on the pest side that start today. But right now there’s actually 3 already that they’re working with.

68 00:09:45.280 00:09:46.260 Amber Lin: Okay?

69 00:09:47.690 00:09:55.859 Amber Lin: So we should. Maybe we should pick someone that already has some experience. So we can get started this week

70 00:09:56.210 00:09:59.421 Amber Lin: instead of waiting until next week. Okay.

71 00:09:59.880 00:10:02.119 JanieceGarcia: Okay, where did I?

72 00:10:05.850 00:10:06.970 JanieceGarcia: Maybe.

73 00:10:07.140 00:10:07.990 JanieceGarcia: Okay.

74 00:10:09.600 00:10:12.580 Amber Lin: I’m gonna take notes somewhere else

75 00:10:13.700 00:10:16.829 JanieceGarcia: Oh, there’s 2. No, they are.

76 00:10:17.030 00:10:17.710 JanieceGarcia: Yeah.

77 00:10:46.160 00:10:48.350 Miguel de Veyra: Amber. Sorry. Just a quick question.

78 00:10:49.050 00:10:49.410 Amber Lin: Nope.

79 00:10:49.410 00:10:54.220 Miguel de Veyra: Update, bot answers is the golden data sheet or something else

80 00:10:54.430 00:11:04.549 Amber Lin: Yeah golden data sheet. Let me show you what it looks like right now. So this where is it

81 00:11:04.940 00:11:05.740 Amber Lin: here?

82 00:11:07.930 00:11:16.180 Amber Lin: So as you can see, there’s a lot of the answers that we don’t have.

83 00:11:16.410 00:11:20.279 Amber Lin: Janice put in the ideal answers, we don’t.

84 00:11:21.760 00:11:28.709 Amber Lin: Yeah. So once we do that, we can say, Okay, is this, is this accurate or not?

85 00:11:29.080 00:11:30.170 Amber Lin: And so

86 00:11:30.170 00:11:32.430 Miguel de Veyra: Can you be the one filling up the answer quality?

87 00:11:32.960 00:11:34.670 Miguel de Veyra: Is it gonna be us or Denise

88 00:11:36.761 00:11:38.719 Amber Lin: Janice, what do you think

89 00:11:40.690 00:11:44.509 JanieceGarcia: For the ideal answers. I mean, I definitely

90 00:11:44.670 00:11:47.889 JanieceGarcia: we’ll put those in. But I need to make sure to

91 00:11:48.180 00:11:56.501 JanieceGarcia: that. We’re updating the master sheet, but I know Yvette had gone through, and she made all those edits on that

92 00:11:57.380 00:11:59.140 JanieceGarcia: master Sheet as well

93 00:11:59.300 00:12:00.950 Amber Lin: Like the central dock,

94 00:12:02.481 00:12:05.050 JanieceGarcia: So they all should pretty much match. Now.

95 00:12:05.730 00:12:06.610 Amber Lin: Oh, great!

96 00:12:07.622 00:12:11.820 Miguel de Veyra: What I meant was for this answer quality, for example, inaccurate no info.

97 00:12:12.560 00:12:15.750 Miguel de Veyra: Are we the ones who’s gonna do this? Or is it gonna be their number

98 00:12:16.760 00:12:34.729 Amber Lin: Yeah, Janice, what do you think? So once we fill in the new bot answers, do you want us to go in and say, this is matched, and this is ideal. To be able to say, would you be able to take a look and say, Okay, this is this is good match. This is not good

99 00:12:35.290 00:12:38.439 JanieceGarcia: I can. I can definitely take a look and and see at that

100 00:12:39.040 00:12:45.850 Amber Lin: Okay, sounds good. So we will update, and then we will. Ping you once we’re once we’re done updating

101 00:12:46.020 00:12:46.610 JanieceGarcia: Okay.

102 00:12:51.620 00:12:52.260 Amber Lin: Okay.

103 00:12:53.320 00:12:54.840 Amber Lin: Sounds good

104 00:13:00.470 00:13:05.590 Amber Lin: thing. In my opinion. We select a group of 5.

105 00:13:05.790 00:13:09.300 Amber Lin: maybe we confirm the list by tomorrow.

106 00:13:09.900 00:13:10.520 JanieceGarcia: Okay.

107 00:13:10.990 00:13:12.089 Amber Lin: It’s fine

108 00:13:12.090 00:13:16.839 JanieceGarcia: Well, I’m gonna send you that an email, letting her know like just a follow up, letting her know how

109 00:13:16.980 00:13:19.249 JanieceGarcia: everything went, and then what we talked about, too. So

110 00:13:19.250 00:13:20.810 Amber Lin: Okay. Yeah. Totally.

111 00:13:20.810 00:13:22.650 JanieceGarcia: Let me do that. I’ll put that on. There

112 00:13:23.190 00:13:23.475 Amber Lin: Okay?

113 00:13:23.880 00:13:33.019 Amber Lin: And for the team, I think to be prepared prepared for the group of 5 testing.

114 00:13:35.680 00:13:46.889 Amber Lin: I think we need to make sure that we’re able to measure these metrics cause right now, like maybe the length of the call or

115 00:13:47.040 00:13:55.730 Amber Lin: like thing, we, we have quality measures. But I don’t think we have business outcome measures.

116 00:13:56.200 00:14:05.589 Amber Lin: so say the length of the call that call takes, and maybe the so I think my

117 00:14:05.590 00:14:07.150 JanieceGarcia: Like the average handle time

118 00:14:07.830 00:14:09.329 Amber Lin: Yeah, yeah, like, if that

119 00:14:09.330 00:14:12.529 JanieceGarcia: Average handle time actually shrinks down a little bit

120 00:14:13.330 00:14:23.790 Amber Lin: Yeah, totally. So I think we need some data from without the bot and with the bot. By bet, you already have the average handle time, right? So

121 00:14:24.648 00:14:33.020 Amber Lin: team, what is your opinion on how we’re gonna measure? This is, are we going to have the call data? Where are we gonna get the call data

122 00:14:37.330 00:14:38.519 Miguel de Veyra: Where is that you think

123 00:14:43.040 00:14:43.710 JanieceGarcia: I’m

124 00:14:44.010 00:14:51.499 JanieceGarcia: thinking, too like with the because once Utam is able to get into the 8 by 8 system

125 00:14:52.390 00:14:54.780 JanieceGarcia: to be able to get more of our

126 00:14:56.490 00:14:58.469 JanieceGarcia: our data. You know our data from

127 00:14:58.470 00:14:59.830 Amber Lin: Nice from our Steve

128 00:15:00.080 00:15:04.849 JanieceGarcia: So I know that that’s something that he’s working with or working with Tim on

129 00:15:04.850 00:15:05.320 Amber Lin: Good.

130 00:15:05.320 00:15:05.730 JanieceGarcia: I believe

131 00:15:06.126 00:15:14.850 Amber Lin: Who’s who’s in your team takes looks over the 8 by 8 system, so I can nudge Utam on that

132 00:15:15.790 00:15:22.540 JanieceGarcia: That’s Tim. It! And I don’t know where we’re at with getting that info

133 00:15:23.150 00:15:32.549 Amber Lin: I I see. I think that’s pretty important, because we’ll test, and then we’ll we’ll not know if it’s working or not. So I think we need the call data

134 00:15:32.940 00:15:38.290 Amber Lin: in order to measure measure the effectiveness of our call at all.

135 00:15:38.580 00:15:54.569 JanieceGarcia: And I know I know Yvette, too, has already given, like some of what our average is, and being able to listen to some calls. So I know we’ve we’ve sent him stuff, but it’s already things that have been recorded, or that has happened.

136 00:15:55.411 00:16:01.148 Amber Lin: Yeah, I have that. So I know we have average handling time before.

137 00:16:02.120 00:16:03.520 Amber Lin: It just like, not after.

138 00:16:03.520 00:16:16.459 Amber Lin: Yeah, if we test with the Csrs. If we don’t know the calling time it it we can’t say it’s improved. I think we can accurate, but we can’t say that we have helped anything

139 00:16:16.460 00:16:18.330 JanieceGarcia: Right? Exactly. Yeah.

140 00:16:18.730 00:16:22.260 Amber Lin: Yeah, so I think this is really important.

141 00:16:23.240 00:16:27.959 Amber Lin: I can. I think I can just email Tim, and

142 00:16:28.230 00:16:36.950 Amber Lin: and see if I can get it from my end. Because Unam gets really, really busy. So I’ll just, I’ll just tag everybody in the email.

143 00:16:37.710 00:16:42.020 Amber Lin: Okay, yeah, he was like, perfect.

144 00:16:42.500 00:16:43.260 Amber Lin: Okay.

145 00:16:43.420 00:16:54.750 Amber Lin: I mean, we still have some time, because we’re still picking the Csrs, and maybe we’re picking it by Tuesday. Hopefully he gets we can get this by sometime end of week. Hopefully.

146 00:16:54.860 00:17:00.550 Amber Lin: I don’t know how complex it is, so we’ll see 8.

147 00:17:06.160 00:17:12.680 Amber Lin: And but yeah.

148 00:17:15.270 00:17:28.840 Amber Lin: oh, team on the we go, Casey and Jenna for the feedback loop. Last time we talked about alerting our team when the bot can’t answer. So how is that

149 00:17:29.050 00:17:32.010 Amber Lin: going to work?

150 00:17:32.330 00:17:33.729 Amber Lin: What do you guys think

151 00:17:36.110 00:17:42.330 Miguel de Veyra: Ideally, because the bot will not make up answers. So it’s gonna say, Hi, hey? I have no information about that.

152 00:17:42.980 00:17:52.139 Miguel de Veyra: What we can do. Basically, I think Casey is just create another tool or workflow. Where, if that’s the case, it’s just another tool where it sends to a slack

153 00:17:52.270 00:17:53.110 Miguel de Veyra: right

154 00:17:53.880 00:17:59.059 Casie Aviles: Yeah, yeah, definitely. It’s going to be another workflow. And we could like

155 00:18:00.580 00:18:04.210 Casie Aviles: Since we’re tracking the output of the bot, we could

156 00:18:04.470 00:18:08.330 Casie Aviles: just have an alert and read that. Yeah, output

157 00:18:12.600 00:18:16.980 Amber Lin: Okay, we can work on creating

158 00:18:17.460 00:18:20.970 Miguel de Veyra: That’s yeah. Let’s pretty fast

159 00:18:22.800 00:18:25.459 Amber Lin: Okay, okay, this is not gonna take too much time. Is that what you said

160 00:18:25.780 00:18:26.859 Miguel de Veyra: Yeah, yeah, yeah.

161 00:18:26.860 00:18:32.030 Amber Lin: Okay. Great. That sounds good. Thanks.

162 00:18:32.400 00:18:36.660 Amber Lin: Right? And structures

163 00:18:36.660 00:18:45.339 Miguel de Veyra: And then sorry for the for the feedback loop. It’s only on slack, not on Google sheets or anything like that, so they can see

164 00:18:46.270 00:18:48.320 Amber Lin: Oh, Janice, what do you think?

165 00:18:49.330 00:18:50.430 JanieceGarcia: Do? What? Say that again

166 00:18:51.230 00:19:21.110 Amber Lin: So last Friday we talked about. We want to know when the bot can answer, and so we want to. One alert us. Our team in the slack so that we can look at them. And we also want to let you guys be able to see what are the answers. And the bot got wrong. So Miguel brought up a great point of okay, we’re gonna alert us in slack. But we might also want to have a Google Sheet. So what do you think

167 00:19:22.220 00:19:27.220 JanieceGarcia: I think that would be good. So that way, we can know, okay, where do we need to update where do what

168 00:19:27.630 00:19:32.760 JanieceGarcia: where do we need to? Come in and figure out if those questions are

169 00:19:33.700 00:19:35.740 Amber Lin: Okay, so, essentially.

170 00:19:35.740 00:19:36.360 JanieceGarcia: For that.

171 00:19:36.750 00:19:46.799 Amber Lin: I see. So creating a kind of like a version of this we’ll just have an answer and say, Oh, it got it wrong, and then we’ll see how what we’re gonna do to update it

172 00:19:47.170 00:19:52.319 JanieceGarcia: Yeah, okay, so that way, we know, too. Okay, hey, Janice, you need to go in and

173 00:19:52.990 00:19:56.620 JanieceGarcia: fix this or add this training document.

174 00:19:56.620 00:19:57.160 Amber Lin: No.

175 00:19:59.750 00:20:06.120 Amber Lin: I see. Great team. Do you think this will? How long would this take to add it also to Google Sheet

176 00:20:06.631 00:20:11.619 Miguel de Veyra: Won’t be that long we can probably finish that by end of day. No case

177 00:20:11.620 00:20:12.450 Amber Lin: Okay.

178 00:20:12.450 00:20:16.377 Miguel de Veyra: Cause. I don’t think there’s really, because looking at the priorities for today,

179 00:20:16.800 00:20:22.090 Miguel de Veyra: it’s it’s really not up to the port. There’s really not much dev stuff

180 00:20:23.000 00:20:23.830 Amber Lin: Okay.

181 00:20:24.500 00:20:41.040 Amber Lin: sounds good. And I think I want to talk about the dashboard. Do you guys think because this week I know I talked to Utam, and he said, We’re gonna pause with Gene internally. So we can all do the ABC.

182 00:20:41.950 00:20:44.089 Amber Lin: For for this week.

183 00:20:44.310 00:20:53.159 Amber Lin: So I’m thinking we should also update the dashboard cause. I think that’s really important.

184 00:20:53.160 00:20:53.910 Miguel de Veyra: Yes.

185 00:20:54.966 00:20:58.499 Amber Lin: Was there like a decision made last week about the

186 00:20:59.440 00:21:07.780 Miguel de Veyra: Sorry I was on beef Tuesday, Friday, on what the single high level quality score would be like. Is this a 1 out of 5. Is this, a thumbs up

187 00:21:07.780 00:21:22.499 Amber Lin: Yeah, I think it’s like a 1 of 10, maybe one out of 5 score. Essentially, all the 3. The 3 different metrics are a little bit confusing for the exacts, and we want to just have one score that’s super simple to understand

188 00:21:22.710 00:21:31.079 Miguel de Veyra: Okay, okay? And then track the number of incorrect, incomplete answers over time. Yeah, that’s technically brain trust

189 00:21:31.960 00:21:39.620 Amber Lin: Yeah, great. So we will essentially just adding those 2 metrics into real, so super fast

190 00:21:39.790 00:21:40.780 Miguel de Veyra: Yes.

191 00:21:41.110 00:21:46.439 Amber Lin: Okay, add metrics to Bill.

192 00:21:47.000 00:21:54.820 Amber Lin: Okay, I think we have a decent amount for today.

193 00:21:57.330 00:22:12.759 Amber Lin: I think before we distribute the task, I think by the end of week our goal would be to be already testing on the Csrs like, do you think Janice and the team? Do you think this is a good goal of end of week

194 00:22:13.030 00:22:17.099 Amber Lin: goal to be testing with the already testing with the 5 Csrs

195 00:22:17.630 00:22:18.440 JanieceGarcia: I think so.

196 00:22:19.390 00:22:41.530 Amber Lin: 5 CS. Rs, we will have essentially able to measure and look at perform things.

197 00:22:43.570 00:22:44.400 Amber Lin: Oh.

198 00:22:48.390 00:22:49.330 Amber Lin: and

199 00:22:52.920 00:22:55.900 Amber Lin: Whoa, okay.

200 00:22:58.960 00:23:00.340 Amber Lin: sounds good.

201 00:23:00.450 00:23:03.830 Amber Lin: And so for the

202 00:23:17.220 00:23:22.890 Amber Lin: right. So, Miguel and

203 00:23:23.140 00:23:31.920 Amber Lin: Case, you and Janice and what are we? What are each of you going to work on today?

204 00:23:33.340 00:23:37.480 Miguel de Veyra: Oh, it’s sorry.

205 00:23:38.400 00:23:42.500 Miguel de Veyra: I think there’s only 3 3 tasks for the Devs right? The feedback loop

206 00:23:43.600 00:23:45.110 Amber Lin: There’s this.

207 00:23:46.620 00:23:48.030 Miguel de Veyra: Oh, yeah, that one I’ll do.

208 00:23:50.290 00:23:53.340 Casie Aviles: Bye, I can do the dashboard stuff

209 00:23:53.540 00:23:58.379 Miguel de Veyra: Oh, you, okay, yeah. And then, Jen, I’m not sure if you’re still gonna work today, if

210 00:24:03.840 00:24:05.809 Miguel de Veyra: but yeah, I can also work on the

211 00:24:07.030 00:24:08.059 Amber Lin: The feedback loop

212 00:24:08.430 00:24:09.870 Miguel de Veyra: Yeah. Yeah. The feedback loop

213 00:24:10.310 00:24:11.135 Amber Lin: Okay.

214 00:24:12.100 00:24:27.140 Amber Lin: I mean, when I have some time, I can also help with this. But, Jonathan, if you have time, you can also help with this one, and I will go. Ask Tim. I will ask him if if he can give us the 8 by 8.

215 00:24:28.140 00:24:34.459 Amber Lin: Okay, so I think, for, for Janice is just

216 00:24:35.590 00:24:42.740 Amber Lin: confirming the save taxes and confirming the Csr list by tomorrow

217 00:24:43.270 00:24:52.750 Miguel de Veyra: And then I think another task could be amber to to update the what do you call it? The expected answers in brain trust

218 00:24:53.850 00:24:55.389 Amber Lin: Oh, in brain. Trust. Okay.

219 00:24:55.390 00:25:00.719 Miguel de Veyra: Because, yeah, Janice already filled up the golden data sheet. Right? So we have to. It’s still using the old one

220 00:25:01.280 00:25:05.617 Amber Lin: Oh, that’s very, very important. Yes, I agree.

221 00:25:06.800 00:25:10.020 Amber Lin: who’s gonna do that? So I can

222 00:25:10.020 00:25:11.460 Miguel de Veyra: Gonna work with Casey on that

223 00:25:11.800 00:25:12.420 Amber Lin: Okay.

224 00:25:16.000 00:25:17.839 Amber Lin: okay, sounds good.

225 00:25:19.150 00:25:19.920 Amber Lin: No.

226 00:25:21.040 00:25:27.799 Amber Lin: Yeah. I think we have a decent amount to work on today. And then we’ll check back in about the progress tomorrow.

227 00:25:29.850 00:25:30.690 Miguel de Veyra: Thanks. Everyone.

228 00:25:31.060 00:25:31.730 Amber Lin: Awesome.

229 00:25:31.730 00:25:32.960 Miguel de Veyra: Thank you.

230 00:25:32.960 00:25:41.019 Amber Lin: Thank you, Janice, for coming. This is really helpful of letting us know. Okay, this is most important. It made it made the meeting a lot faster

231 00:25:41.373 00:25:47.379 JanieceGarcia: Nice, awesome. Okay? Well, great. Well, thank you guys for inviting me. I’ll see you all tomorrow.

232 00:25:48.070 00:25:49.170 Amber Lin: Yes, bye-bye.