Meeting Title: Daily AI Team Sync Date: 2025-03-13 Meeting participants: Janna Wong, Amber Lin, Miguel De Veyra, Casie Aviles


WEBVTT

1 00:00:49.090 00:00:50.340 Miguel de Veyra: Hello! Hello!

2 00:00:55.780 00:00:56.629 Janna Wong: No, no.

3 00:00:58.800 00:01:00.119 Miguel de Veyra: And we will be.

4 00:01:00.490 00:01:06.940 Miguel de Veyra: Think you’re 5 min late, maybe. Let’s just wait.

5 00:04:11.670 00:04:16.879 Miguel de Veyra: Hey, guys? Hey, Casey, yeah, she’ll be late down around 5 min.

6 00:04:19.810 00:04:20.459 Casie Aviles: Okay.

7 00:04:21.260 00:04:25.890 Miguel de Veyra: Yeah, why is my sound still going to screen? Bro.

8 00:07:31.330 00:07:33.790 Casie Aviles: Surreal

9 00:07:47.410 00:07:54.899 Casie Aviles: message. Kung Anadoba Gavindan context. Masha de Sorile.

10 00:07:56.170 00:07:58.270 Miguel de Veyra: I have a message. Sorry. Ait.

11 00:07:59.390 00:08:00.719 Casie Aviles: Client ABC. Home.

12 00:08:04.820 00:08:09.260 Casie Aviles: I mean.

13 00:08:09.790 00:08:12.659 Miguel de Veyra: I thought, wait long. Check what I got up there

14 00:08:21.640 00:08:23.330 Miguel de Veyra: I don’t number 2.

15 00:08:24.420 00:08:24.960 Casie Aviles: Yep.

16 00:08:25.560 00:08:27.639 Miguel de Veyra: We need to discuss how we are going to display.

17 00:08:36.217 00:08:38.129 Miguel de Veyra: I’m not sure. Maybe.

18 00:08:39.850 00:08:43.810 Miguel de Veyra: Do we want to have an iframe for to bring for each site.

19 00:08:46.370 00:08:50.230 Miguel de Veyra: I think. Just iframe. So brain for zoom rail, paracontroll parameter.

20 00:08:52.110 00:08:52.760 Casie Aviles: Yeah.

21 00:08:53.936 00:08:57.680 Casie Aviles: Login, or something similar.

22 00:08:58.480 00:09:00.490 Miguel de Veyra: Technically copy paste Cologne in it.

23 00:09:03.140 00:09:05.820 Casie Aviles: Making sure my open item done.

24 00:09:07.143 00:09:13.329 Miguel de Veyra: No, I don’t think so. I think

25 00:09:16.890 00:09:17.440 Miguel de Veyra: yeah. But.

26 00:09:18.430 00:09:20.949 Casie Aviles: In my number, now.

27 00:09:22.150 00:09:24.949 Miguel de Veyra: Indeed this I don’t think it’s gonna be this weekend, though

28 00:09:26.527 00:09:31.590 Miguel de Veyra: I don’t think they can just putting it up to us. And then we need this tomorrow

29 00:09:32.460 00:09:34.110 Miguel de Veyra: can do that with them.

30 00:09:34.320 00:09:35.220 Miguel de Veyra: So Fridays.

31 00:09:35.711 00:09:38.170 Casie Aviles: Bonus, long naming bonus. Item.

32 00:09:38.170 00:09:49.470 Miguel de Veyra: Yeah, as priority number new, I would say, central Top and the others, everything’s working. Now listen.

33 00:09:50.130 00:09:57.039 Miguel de Veyra: can we get rid of all linear? This is more. Yes, I can.

34 00:09:57.460 00:10:05.189 Miguel de Veyra: Yeah, I just need to finish up. I guess the the ad that’s not even this week.

35 00:10:07.030 00:10:12.230 Casie Aviles: So update, no.

36 00:10:12.550 00:10:19.120 Miguel de Veyra: Oh, you update which is, you know, technically, there.

37 00:10:19.920 00:10:20.360 Casie Aviles: No.

38 00:10:21.135 00:10:23.459 Miguel de Veyra: Chat for that.

39 00:10:25.630 00:10:26.270 Casie Aviles: Okay.

40 00:10:26.270 00:10:27.870 Miguel de Veyra: Yeah, I, think you need.

41 00:10:27.870 00:10:29.299 Casie Aviles: Also it’s a pound, but.

42 00:10:29.620 00:10:30.819 Miguel de Veyra: Yeah, yeah, yeah.

43 00:10:31.370 00:10:32.320 Casie Aviles: Okay. Okay.

44 00:10:34.320 00:10:35.660 Miguel de Veyra: That was.

45 00:10:35.940 00:10:41.769 Miguel de Veyra: Sometimes it takes like 30 40 seconds, like about 1 min.

46 00:10:42.710 00:10:51.200 Miguel de Veyra: so I think, respond within 30 seconds.

47 00:10:58.970 00:11:00.130 Casie Aviles: And.

48 00:11:07.280 00:11:08.440 Amber Lin: Hi guys.

49 00:11:10.030 00:11:10.600 Miguel de Veyra: Hey! Amber.

50 00:11:10.600 00:11:15.419 Amber Lin: Hi! Sorry I’m late. That’s why I’m back in the team.

51 00:11:18.140 00:11:18.570 Miguel de Veyra: Oh, great!

52 00:11:24.040 00:11:25.720 Amber Lin: It’s interesting.

53 00:11:26.180 00:11:28.300 Amber Lin: Oh, thank you.

54 00:11:33.100 00:11:34.060 Amber Lin: Posted.

55 00:11:34.200 00:11:39.760 Amber Lin: Let’s start a little bit of updates on my end. Yesterday I.

56 00:11:39.760 00:11:41.950 Miguel de Veyra: Your your mic is kind of muffled.

57 00:11:42.340 00:11:45.020 Amber Lin: Oh, I’m sorry. Let me try again.

58 00:11:48.893 00:11:56.530 Amber Lin: Would you mind starting there, Miguel? Can you tell us about what you did yesterday? I’ll get my mic set up.

59 00:11:56.700 00:11:59.970 Miguel de Veyra: Okay? Sure? Yeah. So yesterday, I just continued on

60 00:12:00.940 00:12:13.490 Miguel de Veyra: the update agent stuff and the add knowledge, which is, both are technically working. But you know, I’m trying to find ways, basically on how to make it faster.

61 00:12:13.760 00:12:17.500 Miguel de Veyra: And then I also started on the voice agent stuff. But

62 00:12:18.560 00:12:24.410 Miguel de Veyra: I don’t think that’s gonna be a priority this week, anyways. So I’m not really spending much time into it.

63 00:12:24.520 00:12:29.200 Miguel de Veyra: And then the other thing I did yesterday was, I was what do you call it?

64 00:12:30.230 00:12:36.040 Miguel de Veyra: I contacted this other potential team Member Joy. And yeah.

65 00:12:37.210 00:12:39.950 Miguel de Veyra: I’m probably gonna be talking to her next week. Tuesday.

66 00:12:40.730 00:12:47.279 Amber Lin: Okay, yeah, let me write that down.

67 00:12:47.630 00:12:49.720 Amber Lin: Update and add.

68 00:12:50.140 00:12:57.120 Amber Lin: what’s the voice one about? I saw that uten posted in the chat. But I’m not exactly sure what it is.

69 00:12:57.487 00:13:04.840 Miguel de Veyra: It’s basically instead of people, you know, instead of cause. Right now, ABC has like people taking the calls right.

70 00:13:04.840 00:13:05.570 Amber Lin: Hmm.

71 00:13:05.570 00:13:07.930 Miguel de Veyra: Answering general questions and stuff.

72 00:13:08.190 00:13:12.840 Miguel de Veyra: So instead of that, it’s gonna be a bot talking to them. So.

73 00:13:13.100 00:13:18.450 Amber Lin: Oh, oh, I see! So it’s a AI call agent.

74 00:13:18.720 00:13:21.039 Miguel de Veyra: Yeah, yeah, something like that voice agent.

75 00:13:21.580 00:13:28.890 Amber Lin: Cool. Do you think we should talk about that in this Friday’s meeting, or is it too early to even tell them.

76 00:13:29.550 00:13:36.430 Miguel de Veyra: I think Yvette already knows. That’s probably gonna be. I’m not sure. Have you discussed it with them about the phase? 2 of the proposal.

77 00:13:36.730 00:13:45.099 Amber Lin: Yeah, they’re in progress of talking. Apparently events gonna get back to us today. So we’ll see how that goes.

78 00:13:45.850 00:13:47.139 Miguel de Veyra: Okay. Okay. Yeah.

79 00:13:47.140 00:13:47.780 Amber Lin: Yeah.

80 00:13:48.050 00:13:52.180 Miguel de Veyra: We should, we could mention it, but I’d ask Utham 1st if he wants to mention it.

81 00:13:52.180 00:13:54.799 Amber Lin: Okay, I will check. I will check again.

82 00:13:56.560 00:14:00.429 Amber Lin: Perfect! Thank you, Casey. What about you?

83 00:14:01.910 00:14:10.669 Casie Aviles: Hey? Yeah. So I just continued working on the feedback part. And I started to log the feedback

84 00:14:11.000 00:14:18.579 Casie Aviles: in a database. So yeah, let me show how it works quickly. But basically, if you

85 00:14:20.140 00:14:25.330 Casie Aviles: yeah, click here and then it should show in a snowflake database.

86 00:14:26.310 00:14:30.230 Casie Aviles: Okay, right?

87 00:14:32.190 00:14:33.430 Casie Aviles: Let me reload.

88 00:14:39.030 00:14:42.269 Casie Aviles: Yeah, over here. So I just click the

89 00:14:42.710 00:14:45.980 Casie Aviles: thumb up button and it should show up here.

90 00:14:46.640 00:14:47.910 Casie Aviles: And Yahoo.

91 00:14:49.080 00:14:53.609 Amber Lin: Yeah. Can you let me screenshot the thought? The last part?

92 00:14:53.830 00:14:57.970 Amber Lin: I’ll just tell them that just to the bottom of the.

93 00:15:02.818 00:15:04.289 Casie Aviles: Yeah, which part is.

94 00:15:04.579 00:15:08.059 Amber Lin: The last part. So the where it shows thumbs up thumbs down.

95 00:15:10.200 00:15:11.630 Amber Lin: Yeah, right there.

96 00:15:12.610 00:15:13.310 Amber Lin: So

97 00:15:16.360 00:15:17.480 Amber Lin: that’s good.

98 00:15:17.960 00:15:18.980 Amber Lin: Awesome.

99 00:15:19.620 00:15:29.640 Amber Lin: That’s really good. And what do you see? Is the next step for this? Would we sort of modify our responses based on that? Or how do you see it going.

100 00:15:31.880 00:15:33.289 Miguel de Veyra: You want me to answer this, Casey?

101 00:15:33.710 00:15:35.550 Casie Aviles: I mean, yeah, you you could go ahead.

102 00:15:36.440 00:15:42.860 Miguel de Veyra: Yeah, ideally, what we’re gonna do is probably because the thumbs up are really useless for us. It’s the thumbs down that we’ll focus into.

103 00:15:43.050 00:15:48.270 Miguel de Veyra: We’ll probably do like a I don’t know. Weekly review session with them have to pay.

104 00:15:48.270 00:15:56.230 Miguel de Veyra: you know. The answer was bad here. How is there a certain way, you know, we could improve this, or why was it dumped down in the 1st place.

105 00:15:56.870 00:15:57.620 Miguel de Veyra: right.

106 00:15:57.880 00:15:59.709 Amber Lin: See, that’s a great idea.

107 00:16:00.480 00:16:01.350 Amber Lin: Okay?

108 00:16:02.283 00:16:04.600 Amber Lin: Anything more from you, Casey?

109 00:16:06.179 00:16:20.230 Casie Aviles: No, not really I I guess just the minor one that I did was to clean up a bit of the documentation and make sure it’s I just made this here. So I’m not sure if this is up completely accurate. But

110 00:16:20.330 00:16:28.079 Casie Aviles: yeah, you could also check with Miguel if if I got it right. This is just to make it easier to understand, like the whole

111 00:16:28.861 00:16:35.459 Casie Aviles: how we yeah, how we set up everything. So I just added for the feedback evals.

112 00:16:36.236 00:16:43.830 Amber Lin: I think that will be really helpful, especially we if we have new members coming on, and then they’ll really understand what this is.

113 00:16:45.340 00:16:50.750 Casie Aviles: Yeah. And ideally, we also have, like for the update agent, like how it works.

114 00:16:52.310 00:16:53.849 Amber Lin: Okay, cool.

115 00:16:54.788 00:17:05.750 Amber Lin: Miguel Casey, how is the Brain trust thing going? Because I know mentioned that we maybe want to show the client the events. Maybe they’ll have access to dashboard.

116 00:17:05.990 00:17:07.499 Amber Lin: What’s your opinion on that?

117 00:17:10.500 00:17:11.210 Casie Aviles: Okay.

118 00:17:11.210 00:17:12.060 Casie Aviles: Brain, trust.

119 00:17:12.460 00:17:12.900 Casie Aviles: Thank you.

120 00:17:13.319 00:17:15.829 Miguel de Veyra: Yeah, is there a way we can iframe that Casey.

121 00:17:16.920 00:17:19.299 Casie Aviles: Oh, I’m not sure, actually, but

122 00:17:19.770 00:17:24.949 Casie Aviles: I think there, there might be a way, but I’m just reading it earlier.

123 00:17:26.140 00:17:31.150 Miguel de Veyra: Yeah, I can check. There’s probably a way to Api call it, and then just display it. All

124 00:17:31.790 00:17:35.699 Miguel de Veyra: right. Trust Api. But yeah, we’ll run a spike on that

125 00:17:37.670 00:17:39.729 Miguel de Veyra: Api docs. Wait, let me check.

126 00:17:41.370 00:17:46.459 Casie Aviles: Because I thought, like what Uta mentioned was for real.

127 00:17:46.700 00:17:54.900 Casie Aviles: So yeah. But it makes sense also to have the like. The Eval scores

128 00:17:55.530 00:17:59.349 Casie Aviles: displayed, so that the client has access to it.

129 00:18:01.970 00:18:05.339 Miguel de Veyra: Amber. Do you know if we are on

130 00:18:05.550 00:18:08.350 Miguel de Veyra: what do you call this? If we are on enterprise plan?

131 00:18:11.740 00:18:12.400 Miguel de Veyra: Yeah.

132 00:18:12.791 00:18:15.919 Amber Lin: I think we got updated to enterprise right?

133 00:18:16.500 00:18:20.479 Miguel de Veyra: Because ideally, we could probably ask them. If you know, there’s a way to iframe it.

134 00:18:21.832 00:18:24.570 Amber Lin: To what frame it? What does it mean?

135 00:18:25.326 00:18:31.140 Miguel de Veyra: If we have like a slack channel with them, we can, you know, ask them directly, so it’s easier, can you.

136 00:18:31.460 00:18:33.909 Miguel de Veyra: Casey? Let’s see if we’re on enterprise.

137 00:18:38.690 00:18:41.120 Miguel de Veyra: It’s not shown. Wait, maybe you’re not admin.

138 00:18:42.840 00:18:46.519 Amber Lin: We’re on the pro plan. It says.

139 00:18:46.950 00:18:48.140 Miguel de Veyra: Hour on the program.

140 00:19:22.840 00:19:28.470 Casie Aviles: But yeah, okay, I’ll also look into you know how we could give access. Yeah.

141 00:19:30.130 00:19:32.369 Amber Lin: Okay, I’ll write that down.

142 00:19:34.110 00:19:35.380 Amber Lin: That’s great.

143 00:19:36.493 00:19:41.230 Amber Lin: Jenna. What about Robert’s agent? How is that going.

144 00:19:41.490 00:19:46.229 Janna Wong: Yeah. For the mistrel. Mixture.

145 00:19:46.340 00:19:51.220 Janna Wong: Sorry I forgot the name for these great beans, and then

146 00:19:51.350 00:20:07.120 Janna Wong: for the export one I mean the Expo West one, the one that I have issues yesterday. I’m still not able to like. Scrape it even with the Regex. It’s still outputting like an empty area on my end.

147 00:20:07.340 00:20:14.870 Janna Wong: But the mix panel one is, I think, already good to go just waiting on, like what to do

148 00:20:15.070 00:20:22.129 Janna Wong: in terms of like, how how many to scrape, and such in to add to clay? Something like that.

149 00:20:22.680 00:20:23.870 Janna Wong: So yeah.

150 00:20:23.870 00:20:29.950 Amber Lin: I can check here. What’s some things that you want me to ask, Robert.

151 00:20:30.120 00:20:37.960 Amber Lin: of how many to scrape, or who what direction to scrape, or where does he want it to go?

152 00:20:38.240 00:20:39.809 Amber Lin: I can ask him.

153 00:20:43.790 00:20:52.120 Janna Wong: Like? How does does he want to like scrape all from the mix panel site and then

154 00:20:52.270 00:21:01.980 Janna Wong: for the exhibitor site one, the expo West. I’m still having troubles with it. I’m not able to scrape anything from that site as well.

155 00:21:02.430 00:21:06.900 Amber Lin: Sounds good. I’ll ask him about the mix panel. One.

156 00:21:07.360 00:21:09.659 Janna Wong: Okay, sounds good. Thank you so much.

157 00:21:09.830 00:21:18.630 Amber Lin: Perfect a little bit on my end. I met with Shannon and Grace yesterday, and their complaint is not on

158 00:21:18.810 00:21:20.519 Amber Lin: is mostly that

159 00:21:20.960 00:21:28.430 Amber Lin: this stuff is not update up to date, which they acknowledge is their fault. So they would. They’re starting to update

160 00:21:28.790 00:21:30.330 Amber Lin: the document.

161 00:21:31.098 00:21:38.581 Amber Lin: From my understanding. Our Csr Bot responds from the spreadsheet and the central Doc. Right?

162 00:21:39.620 00:22:07.000 Amber Lin: Yeah. And so, after confirming with event, I think Shannon and Grace right now they have commenting access, and then Janice will go in and then make sure that the comments are adequate, and then they will update it so hopefully. They are driving the updates on there, and there’s nothing really we can do about that. So it’s just, I’ll just push them on updating it because it’s for their own good, and

163 00:22:07.350 00:22:17.049 Amber Lin: was not able to meet with Janice this morning because she was. She said she can’t make it, which is unfortunate, because we still kind of need the golden data sheet.

164 00:22:17.150 00:22:21.299 Amber Lin: And so the last thing is about the website scraping.

165 00:22:21.590 00:22:26.910 Amber Lin: I think Scott has different ideas about what the scraping is, for

166 00:22:27.220 00:22:38.859 Amber Lin: in my understanding, we already have all the pest services. But when I looked at the website, it’s more of what generic service is available in each

167 00:22:39.710 00:22:40.670 Amber Lin: big

168 00:22:40.940 00:23:03.989 Amber Lin: area. Say, like, Austin has these services, and it’s not zip code. And it’s all the services from ABC. So just confused as to are we gonna scrape it or not, because if we if we have to, I’ll just put it all in a Google Doc today, and I’ll ask for the pro version and just ask Chat Gbt to process all of them all at once.

169 00:23:04.140 00:23:06.620 Amber Lin: But I just don’t know. What do you guys think.

170 00:23:16.730 00:23:27.859 Casie Aviles: Sorry. Yeah, it’s not clear to me, either, like what they? Because, yeah, we’ve

171 00:23:28.000 00:23:30.509 Casie Aviles: scrape the pest services in the past

172 00:23:31.770 00:23:35.550 Casie Aviles: like the old website they had. So we we already have that.

173 00:23:37.020 00:23:38.750 Miguel de Veyra: The AV cps right.

174 00:23:40.420 00:23:41.670 Amber Lin: Sorry go ahead.

175 00:23:41.890 00:23:46.300 Miguel de Veyra: They have the cause. This was the wait. Let me see if I can find it.

176 00:23:46.870 00:23:50.699 Miguel de Veyra: Th, this was the one we scraped before. Correct me if I’m wrong, Casey.

177 00:23:51.550 00:23:53.209 Miguel de Veyra: but I believe it was this one right.

178 00:23:53.210 00:23:54.739 Casie Aviles: Yeah. The old website.

179 00:23:55.156 00:23:55.570 Amber Lin: Yes, no.

180 00:23:55.570 00:23:56.040 Casie Aviles: One.

181 00:23:56.040 00:24:04.230 Amber Lin: Yeah, that is so old. Okay, I think they want it from the new one. Does this go into postal calls, or just general service?

182 00:24:04.230 00:24:06.499 Miguel de Veyra: No, no, these are just general services.

183 00:24:06.500 00:24:10.659 Amber Lin: Okay. I think they just want us to do it for the new website as well.

184 00:24:11.600 00:24:13.199 Miguel de Veyra: So foregone, Peter.

185 00:24:13.630 00:24:31.380 Amber Lin: Yeah for the ABC home Commercial. Yeah, just for, say, the areas that their office is in just to maybe scrape this website and then click into. So there’s probably 2 hierarchies, this one. And then if you click into one

186 00:24:32.570 00:24:39.840 Amber Lin: and essentially just that page, it doesn’t really go any more granular than that, I think. Can you click on one of them?

187 00:24:43.070 00:24:47.699 Amber Lin: Yeah, yeah, they don’t go any more granular than that.

188 00:24:52.310 00:24:54.960 Miguel de Veyra: But don’t they have this data in the database?

189 00:24:57.383 00:24:59.250 Amber Lin: Apparently not.

190 00:25:00.000 00:25:00.620 Miguel de Veyra: Okay.

191 00:25:04.110 00:25:07.120 Amber Lin: I mean, if you let’s let’s see.

192 00:25:07.610 00:25:16.100 Amber Lin: how much capacity would you guys have today? If not, I can copy and paste everything, and then

193 00:25:17.280 00:25:19.580 Amber Lin: we’ll see

194 00:25:23.020 00:25:24.039 Amber Lin: what’s gonna happen.

195 00:25:24.040 00:25:24.730 Casie Aviles: I can’t help it.

196 00:25:25.370 00:25:32.949 Amber Lin: Okay, okay, I will write out what we need to scrape, and I’ll share Google Doc with you. And then we will.

197 00:25:33.120 00:25:35.140 Amber Lin: The chat Gpt process.

198 00:25:37.770 00:25:38.650 Casie Aviles: Okay.

199 00:25:39.867 00:25:51.979 Amber Lin: One last question. Do you think we should stop at this level of granularity? Or do you think we should go into, say, mosquito control, and then script that page as well. Do you think it’s necessary.

200 00:25:56.440 00:26:03.010 Miguel de Veyra: I cause. I think there’s a structure here. We can’t just copy paste, anyways, because I’m because this is in Austin, right?

201 00:26:03.180 00:26:03.570 Amber Lin: And.

202 00:26:03.570 00:26:06.340 Miguel de Veyra: So let’s say we go to Bell County.

203 00:26:06.830 00:26:11.160 Amber Lin: And then best and rodent, they probably have almost the same.

204 00:26:11.710 00:26:18.760 Amber Lin: Yeah. But they think their point is that it’s not always all the same. So that’s why they just want us to scrape things.

205 00:26:20.710 00:26:25.889 Miguel de Veyra: Only, okay. But that’s so inefficient because the idea they just give us which ones are not.

206 00:26:27.071 00:26:32.139 Amber Lin: They gave us a list of what we want to scrib. I’ll send that to the chat later.

207 00:26:33.190 00:26:34.820 Miguel de Veyra: 1st and road enter.

208 00:26:34.980 00:26:40.510 Miguel de Veyra: Yeah, cause ideally, what we’re gonna do is we’re only focusing on past right? Still.

209 00:26:40.510 00:26:47.022 Amber Lin: Yeah, I know. That’s why I was confused. Because if we’re gonna expand to other divisions.

210 00:26:47.610 00:26:52.429 Amber Lin: why would we do anything other than Pest when they haven’t paid us for more than pest.

211 00:26:52.710 00:26:58.790 Miguel de Veyra: Yeah, I think we just stick with best. Right now, I think the most efficient way to do this would be

212 00:26:59.390 00:27:02.879 Miguel de Veyra: just base it on Austin. And then we try to find.

213 00:27:03.010 00:27:05.800 Miguel de Veyra: you know which one doesn’t have cause. I think it’s

214 00:27:06.830 00:27:09.560 Miguel de Veyra: basically trying to find which one doesn’t have one of these.

215 00:27:09.750 00:27:13.990 Amber Lin: Okay, yeah, yeah, that will be. You’re right. That will be a lot faster. I think.

216 00:27:14.524 00:27:25.139 Amber Lin: I think I can look into that because I know both you guys are probably pretty busy, and if you want to help, we can just split a few locations because they’re not at every office.

217 00:27:28.170 00:27:30.549 Miguel de Veyra: I think. Wait, Amber. I think it’s

218 00:27:30.820 00:27:33.600 Miguel de Veyra: it’s different. For example, if you go to Austin.

219 00:27:33.880 00:27:39.509 Miguel de Veyra: they offer all this, you know, different services. If you go to Waco.

220 00:27:39.800 00:27:40.230 Amber Lin: Yeah.

221 00:27:40.230 00:27:44.679 Miguel de Veyra: They don’t, but we don’t really care about the others. We only care about pest.

222 00:27:45.110 00:27:53.469 Amber Lin: No, I think they want us to shrink everything because this is not granular. They just want to know what’s available in what area.

223 00:27:54.560 00:28:05.039 Amber Lin: I can do it. We don’t have to hand it to them, but I think they will want it eventually in phase 2 as well. This wouldn’t take too much time I can get. I can get started on it.

224 00:28:05.160 00:28:07.710 Amber Lin: and then I mean.

225 00:28:08.914 00:28:13.650 Miguel de Veyra: Once Utong confirms phase 2, then we can maybe roll it out.

226 00:28:14.350 00:28:19.430 Miguel de Veyra: Yeah, okay, yeah. Cause, honestly, what I would do is just copy paste everything. And then.

227 00:28:19.850 00:28:22.710 Amber Lin: Yeah, I’ll do that, too.

228 00:28:23.240 00:28:23.970 Miguel de Veyra: Okay.

229 00:28:24.260 00:28:43.740 Amber Lin: Okay? That’s great. We’re we’re presenting. Tomorrow we have 2 things. We have one meeting with the client, which I will make a slide deck of, and I’ll put our accomplishments in there, and we have a demo for our Friday team company meeting.

230 00:28:43.940 00:28:46.660 Amber Lin: What do you guys want to present on the company meeting.

231 00:28:48.320 00:28:50.629 Miguel de Veyra: I mean best would be the one channel name.

232 00:28:51.050 00:28:54.599 Miguel de Veyra: cause, you know, that’s directly impacting the company.

233 00:28:55.110 00:28:55.890 Miguel de Veyra: Okay.

234 00:28:55.890 00:29:03.880 Amber Lin: I think we’ll demonstrate that. And I’ll I’ll same. I’ll just copy and paste what we give to the clients there, because I think you, what you guys did is also really impressive.

235 00:29:04.010 00:29:05.780 Amber Lin: So we’ll just have 3 things.

236 00:29:05.930 00:29:08.589 Miguel de Veyra: Yeah, and just record the loom video.

237 00:29:08.820 00:29:20.949 Amber Lin: Yeah, yeah, totally, I will. I will ask you guys for that. Once we organize things, I know we have another meeting in 5 min. So if you guys want to take a little break, I’ll see you guys. Then.

238 00:29:20.950 00:29:21.800 Miguel de Veyra: Okay. Okay.

239 00:29:21.820 00:29:24.030 Janna Wong: Okay, thanks guys.

240 00:29:24.390 00:29:25.140 Casie Aviles: Thank you.

241 00:29:25.580 00:29:26.500 Amber Lin: I.