Meeting Title: AI Team Weekly Planning Date: 2025-03-17 Meeting participants: Janna Wong, Amber Lin, Miguel De Veyra, Casie Aviles


WEBVTT

1 00:02:14.740 00:02:17.269 Miguel de Veyra: Hey, Janet, excuse me.

2 00:03:47.300 00:03:49.000 Amber Lin: Hello guys.

3 00:03:53.360 00:03:54.460 Casie Aviles: Hey! Good morning!

4 00:03:55.380 00:03:58.269 Amber Lin: Good morning. Good morning for me. Good night for all of you.

5 00:03:59.210 00:04:03.289 Amber Lin: How we’ve been doing! How’s the weekend

6 00:04:08.440 00:04:11.099 Miguel de Veyra: It was a bit wild from my end, because it’s

7 00:04:12.210 00:04:17.269 Miguel de Veyra: yeah. Cause yeah, we had some. I would say, pre birthday celebrations.

8 00:04:17.570 00:04:20.630 Miguel de Veyra: And it’s been like the 1st time I’ve been, you know.

9 00:04:21.450 00:04:22.590 Miguel de Veyra: Let’s do this for a while.

10 00:04:23.300 00:04:24.550 Amber Lin: I see.

11 00:04:24.860 00:04:39.429 Amber Lin: I remember when I was transiting through the Philippines, when I was flying to the Us. The birthday parties go crazy like I was in a cab, and everyone was just singing and dancing it. It sounds like it was really fun.

12 00:04:39.760 00:04:58.600 Miguel de Veyra: Yeah, no, not nothing like that. Nothing like that. Definitely. It’s more of like a it’s more of like a bar that we went into. We were planning to drink lightly, but then the owner was there, and then one of like one of the baristas she was featured in like a couple of magazines already.

13 00:04:59.550 00:05:03.070 Miguel de Veyra: So it’s like, yeah, we got a lot of free drinks and stuff. And then, yeah.

14 00:05:03.070 00:05:03.910 Amber Lin: Crazy.

15 00:05:03.910 00:05:07.530 Miguel de Veyra: It was supposed to be towards Max. We went there until, like 3 4 Am.

16 00:05:08.770 00:05:10.700 Miguel de Veyra: Added to that floor

17 00:05:12.940 00:05:18.799 Amber Lin: So we okay, Sanjana, what about you? How’s your weekend

18 00:05:22.030 00:05:29.581 Casie Aviles: not much, really. But yeah, I was out last Friday, since it was my mom’s birthday. So just had a very simple celebration

19 00:05:31.310 00:05:35.250 Amber Lin: That’s so nice, Jenna, what about you

20 00:05:36.140 00:05:38.240 Janna Wong: So far for Neil. It’s just

21 00:05:38.460 00:05:41.239 Janna Wong: chilling with my dog. So yeah.

22 00:05:41.240 00:05:45.190 Amber Lin: I have a dog. What kind of dog is? He or she

23 00:05:46.149 00:05:48.659 Janna Wong: It’s a he, and then it’s still a puppy

24 00:05:49.287 00:05:52.772 Janna Wong: for the breeds doesn’t have a breed

25 00:05:54.240 00:05:57.329 Janna Wong: the rescue thing, or like being able

26 00:05:57.330 00:05:57.730 Amber Lin: Thanks.

27 00:05:58.040 00:05:59.910 Janna Wong: Parents, okay.

28 00:06:00.300 00:06:02.640 Amber Lin: Oh, I want to see the puppy.

29 00:06:03.560 00:06:04.110 Amber Lin: Thank you.

30 00:06:04.490 00:06:09.259 Amber Lin: You know we have like a fun channel in in in our slack

31 00:06:09.260 00:06:10.750 Miguel de Veyra: Oh, yeah, probably. Should.

32 00:06:10.750 00:06:13.059 Amber Lin: Would love to see your puppy

33 00:06:14.337 00:06:16.609 Janna Wong: A small little puppy

34 00:06:18.070 00:06:21.689 Amber Lin: I want to have a dog, but I live in an apartment, so I could not.

35 00:06:22.870 00:06:25.669 Amber Lin: Actually, I want a cat. But I think I’m allergic

36 00:06:26.250 00:06:27.289 Janna Wong: Oh, yeah.

37 00:06:30.772 00:06:40.560 Amber Lin: Guys, I put a figma board. I’m gonna try this so that we can all look at it. I’m on the March 17th to 21 board

38 00:06:40.910 00:06:44.859 Miguel de Veyra: And I am on the action items from last week

39 00:06:45.090 00:06:54.689 Amber Lin: So I just copy and paste this stuff from last time. Just want to check. If you guys think there’s anything else we need to do so. I think this will make things a lot faster

40 00:06:58.920 00:07:02.350 Miguel de Veyra: Do we need to fill up the agile photo here

41 00:07:03.030 00:07:03.980 Amber Lin: Huh!

42 00:07:04.110 00:07:04.710 Amber Lin: Alright!

43 00:07:05.800 00:07:07.890 Miguel de Veyra: What’s this? Oh, okay, never mind.

44 00:07:07.890 00:07:17.120 Amber Lin: Yeah, yeah, sorry. This was just a template that I got from fixing. There’s a lot of stuff there already. But I’m just here in the action items from last week.

45 00:07:17.720 00:07:19.410 Amber Lin: Is there anything else?

46 00:07:34.260 00:07:36.559 Miguel de Veyra: Yeah, Google Chat, we need that

47 00:07:37.530 00:07:42.239 Miguel de Veyra: start, roll it out. Go ahead. Sorry.

48 00:07:42.240 00:07:45.340 Miguel de Veyra: I think we can get rid of this. The start. Looking into that

49 00:07:45.460 00:07:50.920 Amber Lin: I don’t think it was. It wasn’t mentioned in the call. So, okay, okay.

50 00:07:51.426 00:07:56.860 Amber Lin: when can we implement a Google chat? And when can we start the rollout? What do you guys think

51 00:07:58.780 00:08:01.069 Miguel de Veyra: I think Casey would be the best suited to answer

52 00:08:01.070 00:08:01.770 Amber Lin: Okay.

53 00:08:02.780 00:08:04.969 Casie Aviles: Sorry I don’t have much context from

54 00:08:06.316 00:08:08.800 Casie Aviles: the action items last Friday

55 00:08:08.800 00:08:17.960 Miguel de Veyra: Oh, yeah, yeah, let me just give you technically. Brev, this is just the remember we have, like the Csr Bot, we just want the trainer.

56 00:08:18.420 00:08:24.750 Miguel de Veyra: We just wanted to basically the same. The update bot, we just want it on Google chat, also a different bot

57 00:08:27.910 00:08:28.470 Amber Lin: Yeah.

58 00:08:29.050 00:08:29.670 Casie Aviles: Perfect.

59 00:08:33.885 00:08:36.629 Miguel de Veyra: You think we can do that today or tomorrow?

60 00:08:37.590 00:08:41.740 Miguel de Veyra: I know the problem we had was we? We weren’t sure right. If it’s allowed to have 2 bots

61 00:08:43.070 00:08:47.039 Casie Aviles: Yeah, I got L, yeah, yeah, okay, yeah. I’ll work on that

62 00:08:48.890 00:08:49.780 Amber Lin: The.

63 00:09:03.250 00:09:06.259 Miguel de Veyra: Yeah. And then let me just share something to you guys

64 00:09:07.530 00:09:12.290 Miguel de Veyra: Cause. I think this was the priority from last week’s call with the with the team.

65 00:09:12.960 00:09:16.880 Miguel de Veyra: the ABC team. It’s basically this one. Because, you know.

66 00:09:17.130 00:09:18.249 Miguel de Veyra: we want to show them how many

67 00:09:20.270 00:09:23.209 Amber Lin: Thank you for mentioning dashboard. This is so important I’m calling.

68 00:09:24.780 00:09:28.029 Amber Lin: Do I have access to this? I want to show her and

69 00:09:28.300 00:09:28.790 Miguel de Veyra: This one.

70 00:09:28.790 00:09:30.689 Amber Lin: Or later. Okay?

71 00:09:30.690 00:09:32.469 Miguel de Veyra: Let me send it to ait

72 00:09:32.470 00:09:32.800 Amber Lin: Yeah.

73 00:09:32.800 00:09:38.059 Miguel de Veyra: I said I I had to fix it. I had to work early today because I didn’t know you had a call, but

74 00:09:38.060 00:09:38.580 Amber Lin: Think.

75 00:09:38.580 00:09:45.250 Miguel de Veyra: The the problem was, there was technically just to give you guys a this is generated from real

76 00:09:45.480 00:09:57.580 Miguel de Veyra: real data. But I it was working Friday. I sent it, but then I didn’t realize that there was a timeout of maximum one day, and then you have to refresh the token. So I actually have. And then I tried. You know.

77 00:09:57.950 00:10:02.800 Miguel de Veyra: I tried doing it via front end, only because that’s what we have doesn’t work.

78 00:10:03.050 00:10:12.839 Miguel de Veyra: So I had to create like an entire back end just to do that. But now it’s fully working, and the token will refresh every 23 h, because 24 h is the limit

79 00:10:13.230 00:10:14.869 Amber Lin: Okay, that’s great.

80 00:10:15.458 00:10:27.960 Amber Lin: I’m looking at this. This is awesome, because then we get to know which which questions they ask and how frequent. But do you think there’s a place we can see on the accuracy of our answers?

81 00:10:28.180 00:10:30.349 Amber Lin: Because I think they want to see that too.

82 00:10:30.820 00:10:31.530 Miguel de Veyra: I know.

83 00:10:31.530 00:10:35.499 Miguel de Veyra: No, it’s it should be here, but

84 00:10:36.390 00:10:47.190 Miguel de Veyra: it should be here displayed here somewhere. But it’s not yet, because we’re not grading this course, I guess what we can do is after we can probably update the record. No, Casey.

85 00:10:50.280 00:10:56.019 Miguel de Veyra: We can probably do something like that. But, as as mentioned last Friday

86 00:10:56.935 00:11:06.650 Miguel de Veyra: The the only thing they really care about is if people are talking to it, you know, and then average execution time because I brought up the Brain Trust

87 00:11:07.490 00:11:09.539 Casie Aviles: Yeah, I was going to ask about that like.

88 00:11:09.790 00:11:12.650 Casie Aviles: why don’t we pull in the data from the Evals

89 00:11:13.100 00:11:21.170 Miguel de Veyra: No, I thought I cause we told them that. Hey, isn’t this what we want? We just have to give them access, but they don’t even care about this stuff

90 00:11:22.781 00:11:30.990 Miguel de Veyra: they want. Yeah, because what I’m told us, we’re, you know, we’re talking to a bunch of executives technically. So they don’t. They don’t understand this like I had to, you know even me

91 00:11:30.990 00:11:39.610 Amber Lin: Yeah, I think trust is way too complicated, I think what we have on real, probably with the accuracy score is good enough

92 00:11:39.610 00:11:40.370 Miguel de Veyra: The call.

93 00:11:40.370 00:11:49.030 Amber Lin: Quality score. I’ll check with your fed. I’m meeting with her in around 3 h or so. I’ll check with her, based on the real

94 00:11:49.030 00:11:49.930 Miguel de Veyra: I think.

95 00:11:50.190 00:11:53.460 Miguel de Veyra: Yeah, I think what we need to add here is the thumbs up or thumbs down

96 00:11:55.110 00:12:02.180 Miguel de Veyra: out of the 1, 65, the 45 conversations. How many were thumbs up? How many were thumbs down? How many

97 00:12:02.180 00:12:03.210 Amber Lin: 1, 0, okay.

98 00:12:03.210 00:12:06.290 Miguel de Veyra: Reactions. That would be a good addition to add here.

99 00:12:09.390 00:12:13.989 Miguel de Veyra: because last 4 weeks, let’s say, there you go

100 00:12:15.050 00:12:21.349 Amber Lin: Okay. Casey, how is the thumbs up and thumbs down? Feature going? I think.

101 00:12:22.080 00:12:30.599 Amber Lin: Yeah, it’s only for us, like, I mean, it’s only internal. So I guess the next thing we could do is to send them the updated code today

102 00:12:31.260 00:12:36.120 Casie Aviles: So I’m going to email them with the yeah, with the thumbs up, thumbs down. Feature

103 00:12:36.390 00:12:37.000 Amber Lin: Which.

104 00:12:38.070 00:12:40.389 Miguel de Veyra: I have a question. By the way, Casey.

105 00:12:44.010 00:12:46.160 Miguel de Veyra: This data is from snowflake. Right?

106 00:12:46.520 00:12:47.050 Casie Aviles: Yep.

107 00:12:47.980 00:12:55.470 Miguel de Veyra: So technically, the what do you call this? The thumbs up, thumbs down, should be here

108 00:12:56.390 00:12:58.090 Casie Aviles: It’s in a separate table

109 00:12:58.540 00:13:00.340 Miguel de Veyra: Oh, shit, that’s the thing.

110 00:13:03.430 00:13:09.529 Miguel de Veyra: Okay? Okay, yeah, that makes sense. As I cause Uttan was the one who made this amber. So we have

111 00:13:09.530 00:13:09.960 Miguel de Veyra: you, too.

112 00:13:10.010 00:13:11.580 Miguel de Veyra: Yeah, we have to talk to him

113 00:13:12.120 00:13:22.890 Casie Aviles: Yeah, would would need to have, like, you know, access to real and maybe ideally, we should be able to do it ourselves and have it over to us

114 00:13:23.910 00:13:24.980 Miguel de Veyra: The real, actually

115 00:13:25.470 00:13:26.410 Amber Lin: Yeah.

116 00:13:27.070 00:13:34.130 Amber Lin: we can just text in the, can you just text in the ABC channel of Udo community give us access to the real

117 00:13:35.070 00:13:37.370 Miguel de Veyra: Yeah, I think I have access to real estate

118 00:13:37.720 00:13:41.729 Amber Lin: I just of course, I don’t know how to use this. But oh, okay, okay.

119 00:13:42.030 00:13:44.179 Miguel de Veyra: We’re not data engineer. Yeah, we’re not data.

120 00:13:44.180 00:13:45.739 Miguel de Veyra: Can- can you add me? There

121 00:13:46.205 00:13:48.030 Casie Aviles: Miguel, if you have access

122 00:13:48.350 00:13:50.420 Miguel de Veyra: I’m not sure if I have the

123 00:13:50.420 00:13:51.880 Amber Lin: Let me check

124 00:13:52.560 00:13:58.780 Miguel de Veyra: Oh, wait, let me check. I’m not sure I have the user suite, Amber House

125 00:13:59.870 00:14:00.610 Amber Lin: Maybe yeah.

126 00:14:00.610 00:14:04.050 Miguel de Veyra: Org admin. Wait, Miguel, where does? Where is Miguel?

127 00:14:04.830 00:14:06.290 Amber Lin: Yeah, I don’t know.

128 00:14:06.290 00:14:07.500 Miguel de Veyra: Yeah, I’m org admin

129 00:14:08.450 00:14:09.070 Amber Lin: Oh!

130 00:14:09.430 00:14:10.090 Casie Aviles: So you

131 00:14:10.300 00:14:14.759 Miguel de Veyra: I see a add users there, yeah, yeah, yeah, I just

132 00:14:14.760 00:14:17.620 Amber Lin: I do not have that. I can just view

133 00:14:21.240 00:14:22.130 Amber Lin: good

134 00:14:22.130 00:14:22.790 Miguel de Veyra: Okay.

135 00:14:24.360 00:14:24.730 Amber Lin: Right.

136 00:14:24.730 00:14:25.500 Casie Aviles: Nice

137 00:14:25.500 00:14:26.470 Miguel de Veyra: Okay. Nice.

138 00:14:26.770 00:14:32.589 Amber Lin: So yeah, I guess what we’ll do here is it’s on. It’s on here. By the way, you go to projects

139 00:14:32.700 00:14:34.910 Miguel de Veyra: Here here.

140 00:14:39.140 00:14:41.360 Miguel de Veyra: honestly, though, I don’t know how you can edit.

141 00:14:45.240 00:14:46.140 Miguel de Veyra: But yeah.

142 00:14:48.320 00:14:49.040 Casie Aviles: Okay.

143 00:14:49.040 00:14:53.240 Miguel de Veyra: And then another thing I did, by the way, is, yeah.

144 00:14:53.240 00:14:57.410 Miguel de Veyra: cause I had to create like a back end, entire code.

145 00:14:58.540 00:15:04.970 Miguel de Veyra: But then we have we have to save. This is the one we have to refresh every 23 h. Technically, this code.

146 00:15:06.530 00:15:11.359 Miguel de Veyra: this is the frame of the ice. The. This is the basically the source of the iframe

147 00:15:11.740 00:15:12.730 Amber Lin: Oh!

148 00:15:13.350 00:15:17.310 Miguel de Veyra: So everything comes from here that gets displayed here. So if we sorry

149 00:15:17.310 00:15:17.970 Amber Lin: Okay.

150 00:15:17.970 00:15:20.399 Miguel de Veyra: If we copy paste that here that should appear

151 00:15:21.530 00:15:24.310 Miguel de Veyra: There you go. We’re just iframing it technically over here.

152 00:15:24.330 00:15:25.219 Amber Lin: Nice to meet you

153 00:15:26.547 00:15:30.369 Miguel de Veyra: Yeah, but this, we’re running it on Hero on this one

154 00:15:31.760 00:15:34.260 Amber Lin: Okay, yeah, I see.

155 00:15:34.930 00:15:37.440 Miguel de Veyra: So, yeah, I think that’s pretty much it for this one

156 00:15:39.362 00:15:44.409 Miguel de Veyra: Can you make sure, Amber, that you can access it? Sorry, just to make sure, because I had a hard

157 00:15:44.410 00:15:49.429 Amber Lin: I can. I can view it. I can view it. I don’t think I can make any edits, but I can see the dashboard

158 00:15:49.430 00:15:59.490 Miguel de Veyra: Yeah, yeah, that’s good enough. And then if they if some people want to try it, and then they can’t, they can just click on the knowledge assistant over here, and then they should be able to chat to the bot

159 00:16:00.716 00:16:03.653 Amber Lin: The where all the

160 00:16:04.050 00:16:06.180 Miguel de Veyra: The knowledge assistant. Yeah, the bot is here

161 00:16:06.180 00:16:10.569 Amber Lin: Yeah, let me check that. Give me a second. I wanna make sure I have it.

162 00:16:11.960 00:16:19.929 Amber Lin: Oh, oh, okay, enter password. What was the password? Again?

163 00:16:19.930 00:16:21.940 Miguel de Veyra: A, BC, home, small letters.

164 00:16:24.300 00:16:25.010 Amber Lin: Okay.

165 00:16:25.880 00:16:27.039 Miguel de Veyra: Were you able to get

166 00:16:27.430 00:16:28.130 Amber Lin: Yes.

167 00:16:29.050 00:16:29.580 Amber Lin: Okay.

168 00:16:30.320 00:16:36.260 Miguel de Veyra: So, yeah, ideally. If you want, I could create like another one of these

169 00:16:37.340 00:16:40.499 Amber Lin: And then just put the trainer assistant.

170 00:16:42.350 00:16:43.100 Amber Lin: Hmm.

171 00:16:43.100 00:16:49.090 Miguel de Veyra: Just in case. Just so, they have access to it before we, you know, while we’re trying to figure out how to do the

172 00:16:49.900 00:16:52.289 Amber Lin: The Google Chat integration

173 00:16:53.150 00:17:01.959 Amber Lin: we could. How long would that take, though? I mean, if it takes any longer than say, half an hour to an hour. I just say we can just figure out how to implement it to Google, chat

174 00:17:03.344 00:17:05.529 Miguel de Veyra: Yeah, probably take more than that.

175 00:17:05.990 00:17:11.790 Amber Lin: Yeah, we can just put it into Google. I think they can wait. I I think they they trust us to.

176 00:17:13.240 00:17:15.209 Amber Lin: Yeah, I don’t wanna waste your time on that?

177 00:17:16.808 00:17:20.509 Amber Lin: Okay, we have the document update. Bot.

178 00:17:21.099 00:17:25.379 Amber Lin: we’re going to implement it to Google Chat, who’s going to be responsible for this

179 00:17:26.849 00:17:28.389 Casie Aviles: Think it’s me right

180 00:17:28.580 00:17:29.140 Miguel de Veyra: Yeah.

181 00:17:29.140 00:17:30.030 Casie Aviles: Or, yeah.

182 00:17:32.005 00:17:37.819 Amber Lin: Okay, A, C, and that will be later. Thumbs up, thumbs down.

183 00:17:38.500 00:17:46.410 Amber Lin: And then, Miguel, what would you be working on this this week. I know you’re out of office Thursday and Friday, so I just wanted to make sure

184 00:17:47.906 00:17:51.240 Miguel de Veyra: The dashboard stuff. Technically, I’ve already done so

185 00:17:51.930 00:17:55.599 Miguel de Veyra: basically, just updated on what event wants to see

186 00:17:56.480 00:17:57.250 Amber Lin: Hmm.

187 00:18:00.400 00:18:01.290 Amber Lin: okay.

188 00:18:01.840 00:18:12.019 Amber Lin: Sounds good. Is there? Was there anything else? Oh, yeah. I kind of scraped the website I copy and pasted as much as I could.

189 00:18:12.340 00:18:22.600 Amber Lin: Can one of you, maybe, Miguel, since Casey’s working on the Google Chat implementation, can you look at how to just link it into our system?

190 00:18:22.880 00:18:25.750 Miguel de Veyra: Oh, yeah, sure. Yeah, sure, that’s

191 00:18:25.970 00:18:31.979 Miguel de Veyra: do, I add technically, you can just add it to Central Doc, and that should be fine. I know you put it on Google Docs, right?

192 00:18:32.290 00:18:45.075 Amber Lin: Yes, it’s on Google docs. But I maybe I want you to look over a little bit. It’s not that clean. It’s just copy and paste. So there’s a lot of information on there. It is extremely, extremely long. I did not clean it with

193 00:18:45.810 00:18:47.439 Amber Lin: would touch Vt.

194 00:18:47.440 00:18:48.630 Miguel de Veyra: Okay, yeah. I’ll find it.

195 00:18:48.630 00:18:55.372 Amber Lin: And there’s different tabs. So I just want you to look over a little bit and just add it to

196 00:18:55.710 00:18:57.829 Miguel de Veyra: Pass, though, or is it like everything else

197 00:18:58.327 00:19:04.299 Amber Lin: It is everything they have for the locations, they told me, and

198 00:19:04.470 00:19:09.039 Amber Lin: because each service and they have a page. So there’s 5 tabs. It’s

199 00:19:09.210 00:19:17.329 Amber Lin: I think I sent it. I sent it in our slack and essentially where is

200 00:19:20.420 00:19:22.720 Amber Lin: sorry. Where is it?

201 00:19:23.870 00:19:27.180 Amber Lin: Essentially the 5? th The last tab is

202 00:19:27.340 00:19:30.349 Amber Lin: granularly each service that you have.

203 00:19:30.700 00:19:34.219 Amber Lin: and then the 1st say the second tab is

204 00:19:34.460 00:19:40.730 Amber Lin: all of the different service they have, but not which. What each service is, does that make sense

205 00:19:40.910 00:19:41.550 Miguel de Veyra: Yeah.

206 00:19:42.180 00:19:48.849 Amber Lin: Okay, okay. So I think we probably need access to need to use all of that data. And

207 00:19:49.490 00:20:02.319 Amber Lin: I think it will answer in the oh, by the ways, because then we already know the other services, and also, maybe when they asked about passive Oh, what is this service? And then we can describe it a little bit more.

208 00:20:02.590 00:20:04.389 Amber Lin: That’s what that’s what I thought

209 00:20:05.030 00:20:10.960 Miguel de Veyra: Wait. Didn’t Scott say last week? It’s not well now I’m confused a bit sorry

210 00:20:12.834 00:20:15.959 Amber Lin: A little confusing, I agree. Let me share my screen and

211 00:20:16.382 00:20:18.070 Miguel de Veyra: Sorry I got lost.

212 00:20:18.640 00:20:21.359 Amber Lin: I know I would be also really lost.

213 00:20:22.820 00:20:25.080 Amber Lin: So this is their.

214 00:20:25.210 00:20:27.880 Amber Lin: This is the pages we script I copy and pasted

215 00:20:27.880 00:20:28.340 Miguel de Veyra: Yeah.

216 00:20:28.340 00:20:43.860 Amber Lin: This, the ABC website say, we’re in Austin. Let me show you the titles. See, here we have the clients, electrician, exterior cleaner. We have all that in each and in each of this it only essentially goes

217 00:20:44.470 00:20:55.570 Amber Lin: granular in Oh, my God, this is crazy! So there’s like washer, repair, refrigerator, repair blah blah, and then

218 00:20:56.640 00:21:02.219 Amber Lin: here, these, these are different locations, and here in the last one.

219 00:21:03.460 00:21:06.529 Amber Lin: So if we go to best efficient

220 00:21:06.770 00:21:10.130 Amber Lin: appliance, repair, repair. These are the specific

221 00:21:10.490 00:21:16.409 Amber Lin: pages of Oh, this is that. How do they do it? Blah! Blah! So this is much more granular.

222 00:21:16.750 00:21:30.629 Amber Lin: I didn’t want to repeat it for repeat these pages for each of the services in each location, because then there will be a lot of duplicates, and this document will be too long. So this is the specific services. If that makes sense

223 00:21:31.060 00:21:31.670 Miguel de Veyra: Yep.

224 00:21:32.540 00:21:33.340 Amber Lin: Okay.

225 00:21:35.800 00:21:37.680 Miguel de Veyra: 422 pages long, now

226 00:21:38.120 00:21:40.743 Amber Lin: I know I’m sorry.

227 00:21:42.040 00:21:46.030 Amber Lin: That’s right. Yeah, because thought were like this.

228 00:21:46.030 00:21:52.230 Miguel de Veyra: Yeah, it’s gonna add, no, I don’t think I’ll add it all to the knowledge, to the context, because

229 00:21:52.780 00:21:54.340 Miguel de Veyra: all the work we did for

230 00:21:54.740 00:21:56.949 Miguel de Veyra: bring it down. Yeah, it’s gonna be too slow

231 00:21:57.090 00:21:58.899 Amber Lin: Yeah. That’s why I want to give it

232 00:21:58.900 00:22:05.920 Miguel de Veyra: Yeah. Didn’t mention. Didn’t Scott mentioned last week that what was the purpose again? Why, we were scraping everything. Sorry

233 00:22:06.593 00:22:17.229 Amber Lin: Because, you know, we have their spreadsheet. The spreadsheet is just zip code and technician. It doesn’t explain what the service is.

234 00:22:17.640 00:22:25.159 Amber Lin: and they wanted it to one, explain what the service is where it pass, and 2 also have

235 00:22:25.270 00:22:27.880 Amber Lin: explanations for other divisions.

236 00:22:29.100 00:22:32.110 Amber Lin: So service is also from other divisions

237 00:22:33.290 00:22:37.779 Miguel de Veyra: Oh, did we get that clear to to them that we’re also gonna do the other divisions

238 00:22:40.760 00:22:47.190 Amber Lin: Never objected. I can, I can make sure. But we could add the pest stuff

239 00:22:47.190 00:22:51.659 Miguel de Veyra: Yeah, I think we can add the because I think, Scott, I don’t know. Scott said a lot last time, but

240 00:22:52.799 00:22:55.849 Miguel de Veyra: he mentioned that we’re only gonna be doing pests

241 00:22:56.870 00:23:00.959 Miguel de Veyra: now, because that’s the only thing that they, you know, they paid for

242 00:23:01.640 00:23:02.410 Amber Lin: Okay.

243 00:23:02.410 00:23:06.170 Miguel de Veyra: Yeah, but I don’t know. Well, I think it’s best to clarify with them

244 00:23:06.730 00:23:07.460 Amber Lin: Okay.

245 00:23:07.720 00:23:15.950 Miguel de Veyra: Because if we do the if we do the other services now, they’re gonna start thinking, hey? Maybe we should. Just, you know, why can’t we just add the rest into this one?

246 00:23:16.120 00:23:20.080 Miguel de Veyra: And then we’re not gonna be able to sell any more agents to them.

247 00:23:20.290 00:23:21.000 Amber Lin: Okay.

248 00:23:21.590 00:23:34.340 Amber Lin: then the past stuff is also in there. Could you just look at that part specifically, and I will clarify with Uta my meeting with him a little bit later. I will check with him if he wants the other stuff in as well

249 00:23:34.340 00:23:39.589 Miguel de Veyra: Yeah, I’ll probably just get the details of like the type of services in Pastor

250 00:23:40.260 00:23:41.550 Amber Lin: Yes, and then the

251 00:23:41.550 00:23:43.279 Miguel de Veyra: Locations where they are

252 00:23:44.230 00:23:55.880 Amber Lin: Yes. So under each tab and under the second tab, the pass under each location, and then under the last tab of the service descriptions.

253 00:23:56.020 00:23:59.700 Amber Lin: Essentially the pest division. So, yeah.

254 00:24:01.362 00:24:04.390 Miguel de Veyra: Did you share that in? Sorry? Or did you share that again?

255 00:24:04.390 00:24:08.040 Amber Lin: Let me just copy that. I’ll share it again.

256 00:24:08.040 00:24:09.000 Miguel de Veyra: Okay. Sure.

257 00:24:09.190 00:24:10.560 Amber Lin: Yeah, copy the link.

258 00:24:11.380 00:24:25.470 Amber Lin: I’ll share in our slack test services back to location.

259 00:24:25.590 00:24:27.180 Amber Lin: I’m fine.

260 00:24:29.810 00:24:31.780 Amber Lin: Pretty cool from

261 00:24:37.540 00:24:42.320 Amber Lin: I I commented the 3 things that we will need.

262 00:24:44.630 00:24:47.769 Amber Lin: and let me just act full time.

263 00:24:49.240 00:24:51.910 Amber Lin: Sure, really.

264 00:24:54.290 00:25:03.749 Amber Lin: I think that’s all right. Is there anything else you guys can think of from our from our Jira board that we should also do anything else that we didn’t put on there

265 00:25:04.667 00:25:08.120 Miguel de Veyra: Do you wanna introduce linear to us, or how we’ll do it?

266 00:25:10.345 00:25:16.869 Amber Lin: Yes, sorry I will. I will allocate that to let me do that.

267 00:25:18.850 00:25:19.650 Amber Lin: Oh.

268 00:25:23.350 00:25:24.620 Amber Lin: sorry!

269 00:25:26.090 00:25:26.990 Amber Lin: Great!

270 00:25:27.520 00:25:28.570 Amber Lin: That’s me.

271 00:25:29.780 00:25:30.720 Amber Lin: Yeah.

272 00:25:31.850 00:25:35.530 Amber Lin: It doesn’t seem like we had too much

273 00:25:35.670 00:25:40.850 Amber Lin: right now I will see what comes in from Utam.

274 00:25:41.040 00:25:41.710 Miguel de Veyra: Okay.

275 00:25:42.190 00:25:44.600 Amber Lin: Yeah, I’ll check in with you guys tomorrow.

276 00:25:47.420 00:25:48.170 Miguel de Veyra: Okay.

277 00:25:48.500 00:25:50.440 Amber Lin: Okay. Thank you guys.

278 00:25:50.650 00:25:52.380 Miguel de Veyra: Thanks. Everyone have a good day.

279 00:25:52.380 00:25:53.440 Amber Lin: Bye.

280 00:25:53.440 00:25:54.130 Janna Wong: Yeah.