Meeting Title: Internal AI Team | Standup Date: 2025-04-11 Meeting participants: Miguel De Veyra, Casie Aviles, Amber Lin


WEBVTT

1 00:00:31.900 00:00:34.109 Miguel de Veyra: Yo yo yo! What’s up, mate?

2 00:00:35.450 00:00:36.930 Casie Aviles: Yeah. Below. Hello.

3 00:00:38.250 00:00:40.030 Miguel de Veyra: What was that in the land.

4 00:00:43.890 00:00:44.429 Casie Aviles: Few more.

5 00:00:44.430 00:00:45.240 Miguel de Veyra: Can we click?

6 00:00:45.240 00:00:49.430 Miguel de Veyra: Oh, of it now? Right cool.

7 00:00:59.220 00:01:01.849 Casie Aviles: Follow up. But you might know as a sales.

8 00:01:01.850 00:01:02.620 Miguel de Veyra: Oh!

9 00:01:03.360 00:01:04.150 Casie Aviles: Yeah.

10 00:01:06.340 00:01:08.090 Miguel de Veyra: I also don’t know about it.

11 00:01:09.430 00:01:13.899 Casie Aviles: As a Javi, I think Nagran nasay, ngayon.

12 00:01:14.800 00:01:16.509 Miguel de Veyra: You just locked up nice.

13 00:01:16.700 00:01:22.880 Casie Aviles: Young Javi coffee. So I think Javi Coffee Channel.

14 00:01:23.512 00:01:24.759 Miguel de Veyra: My clients. Hold on!

15 00:01:26.080 00:01:29.640 Casie Aviles: Meron Kasina, no Merong channel. Na.

16 00:01:29.640 00:01:30.190 Miguel de Veyra: We’re not.

17 00:01:30.190 00:01:32.950 Casie Aviles: Internal brain forge, lung team, lung.

18 00:01:33.610 00:01:37.830 Miguel de Veyra: At the Brand. New 9 Pm. Daily summary for Javi coffee or.

19 00:01:37.830 00:01:38.360 Casie Aviles: Yeah.

20 00:01:38.720 00:01:40.545 Miguel de Veyra: Oh, yeah.

21 00:01:41.880 00:01:42.950 Miguel de Veyra: Nice.

22 00:01:43.450 00:01:45.009 Casie Aviles: So, and a long time.

23 00:01:49.320 00:01:49.709 Casie Aviles: That’s true.

24 00:01:50.030 00:01:50.350 Casie Aviles: No.

25 00:01:55.716 00:01:59.019 Miguel de Veyra: For my own time.

26 00:02:06.413 00:02:07.859 Miguel de Veyra: I’m Berkeley.

27 00:02:13.600 00:02:15.790 Casie Aviles: Hmm! But then oh! Or live!

28 00:02:16.850 00:02:23.169 Miguel de Veyra: You know, it’s gonna send something like this.

29 00:02:23.670 00:02:26.570 Miguel de Veyra: And we’re working on having this on every

30 00:02:27.170 00:02:35.280 Miguel de Veyra: on every client, basically. And then sales number. It’s gonna run every week, and then it’s a Gpt. Agent in AI test agent.

31 00:02:37.000 00:02:38.319 Miguel de Veyra: So all right, Nick.

32 00:02:41.670 00:02:42.200 Miguel de Veyra: why.

33 00:02:46.470 00:02:48.730 Casie Aviles: Feedbackuma, Paso.

34 00:02:53.400 00:02:59.420 Miguel de Veyra: You also are not inside slack messages. Data source comes to target.

35 00:03:01.470 00:03:02.310 Casie Aviles: Amber.

36 00:03:02.620 00:03:03.399 Miguel de Veyra: Hey, Amber!

37 00:03:06.320 00:03:07.569 Miguel de Veyra: I’ve I’ve got.

38 00:03:08.919 00:03:14.670 Casie Aviles: For the data source. Slack data source. Yeah. I I mentioned

39 00:03:14.790 00:03:18.450 Casie Aviles: in the last message I had on AI team.

40 00:03:19.791 00:03:22.769 Casie Aviles: I think. Yeah, we’ll proceed with Dlt for that.

41 00:03:22.770 00:03:23.970 Miguel de Veyra: Haven’t been a long time.

42 00:03:24.680 00:03:26.089 Miguel de Veyra: Okay, okay.

43 00:03:26.370 00:03:27.320 Amber Lin: Bye-bye.

44 00:03:28.640 00:03:29.710 Miguel de Veyra: Hey, everyone.

45 00:03:31.360 00:03:41.649 Amber Lin: We had a company. Happy hour yesterday I saw Robert and Hannah person, and it’s like Whoa!

46 00:03:42.120 00:03:46.930 Amber Lin: I only I only know them from their slack profile. Pic.

47 00:03:47.100 00:03:49.759 Amber Lin: I was like, wait, you’re this tall

48 00:03:49.870 00:03:53.460 Amber Lin: or like you were only this tall.

49 00:03:54.866 00:03:56.400 Miguel de Veyra: And there are only the.

50 00:03:56.730 00:03:57.760 Amber Lin: Huh!

51 00:03:57.760 00:03:58.970 Miguel de Veyra: Was Utam. There.

52 00:03:59.650 00:04:08.800 Amber Lin: Who comes coming this morning. He had a talk last night, so I think he’s flying in today, so I’ll see him, too. I I am.

53 00:04:08.920 00:04:10.760 Amber Lin: Oh, very, it’s see!

54 00:04:10.760 00:04:13.369 Miguel de Veyra: That’s why you were still replying like 3 h ago.

55 00:04:14.660 00:04:15.470 Amber Lin: Hmm.

56 00:04:15.470 00:04:18.180 Miguel de Veyra: He was still replying to me, like, 3 h ago.

57 00:04:18.690 00:04:21.470 Amber Lin: I know. I think he’s flying really early.

58 00:04:23.043 00:04:23.650 Miguel de Veyra: Let’s see.

59 00:04:23.960 00:04:24.930 Amber Lin: Yeah.

60 00:04:24.930 00:04:29.770 Miguel de Veyra: Okay, yeah, I think for today, we just wanna go through what we can demo later.

61 00:04:31.110 00:04:32.189 Amber Lin: Sure. Yeah.

62 00:04:32.600 00:04:38.939 Miguel de Veyra: I’m not sure I’m sorry. I’m not sure if I can go, because my, it’s my sister’s graduation. They haven’t sent an invite, so

63 00:04:39.170 00:04:41.409 Miguel de Veyra: I might go might not. If there’s a celebration.

64 00:04:42.230 00:04:44.250 Amber Lin: I mean the company Demo.

65 00:04:44.550 00:04:46.259 Miguel de Veyra: Yeah, yeah, yeah, for later.

66 00:04:46.260 00:04:51.920 Amber Lin: I mean, if you show me, or if Casey can be there, I can just show them. It’s fine.

67 00:04:52.390 00:04:54.149 Miguel de Veyra: Yeah, let me. Just

68 00:04:54.310 00:04:59.930 Miguel de Veyra: I mean the only thing, really, that we’re gonna demo is basically, you know, the Javi coffee, which is

69 00:05:00.270 00:05:02.310 Miguel de Veyra: you consider this done right, Casey.

70 00:05:03.890 00:05:09.340 Casie Aviles: Yeah, it’s I added it to the re in repair review face. But.

71 00:05:10.060 00:05:10.610 Amber Lin: I was like.

72 00:05:11.480 00:05:12.260 Miguel de Veyra: So this will.

73 00:05:13.080 00:05:19.809 Casie Aviles: I just have a question. So amber. Are you part of the client Javi? Copy channel.

74 00:05:21.200 00:05:22.400 Amber Lin: I have it. Yeah.

75 00:05:23.080 00:05:25.650 Casie Aviles: Okay, so what did the message

76 00:05:26.244 00:05:28.069 Casie Aviles: go through there from the bottom.

77 00:05:28.421 00:05:29.829 Amber Lin: Oh! Let me check!

78 00:05:30.320 00:05:32.760 Casie Aviles: I muted it, cause it terrific.

79 00:05:33.210 00:05:35.329 Amber Lin: Pinging me. But let me go. Check.

80 00:05:36.695 00:05:42.040 Amber Lin: Joggy yeah.

81 00:05:42.650 00:05:43.330 Casie Aviles: It’s there.

82 00:05:43.330 00:05:44.000 Casie Aviles: Nice?

83 00:05:44.350 00:05:46.731 Casie Aviles: Yeah, because I’m not there. But the bot is there.

84 00:05:48.070 00:05:55.450 Amber Lin: It’s so funny I can add you if you want, but it’s kind of noisy if we don’t work.

85 00:05:55.940 00:05:57.479 Amber Lin: Yeah, let me.

86 00:05:57.960 00:06:00.250 Miguel de Veyra: I think Utham doesn’t want other people.

87 00:06:00.250 00:06:02.120 Casie Aviles: Utah removed me there. It’s fine.

88 00:06:02.120 00:06:04.239 Amber Lin: Oh, I see! I see!

89 00:06:04.400 00:06:05.510 Miguel de Veyra: Okay. And then.

90 00:06:05.510 00:06:05.880 Amber Lin: It was.

91 00:06:05.880 00:06:11.060 Miguel de Veyra: So this one’s pretty much done. I think we just should for the demo. I think we just send them screenshots

92 00:06:12.060 00:06:18.400 Miguel de Veyra: that works, and then the other one is for sales. We’re pretty much done on this one, too. It’s it basically just

93 00:06:18.590 00:06:23.490 Miguel de Veyra: gives them a list of all you know this. What of all the.

94 00:06:24.096 00:06:39.340 Amber Lin: I was thinking I might ask Robert a little bit more in person, because I don’t want I don’t know how he wants to use it specifically, but I think all the technical parts are done. We might want to give him message suggestions.

95 00:06:40.370 00:06:41.570 Miguel de Veyra: Yeah, I.

96 00:06:41.570 00:06:43.700 Amber Lin: But I’ll need to get that from him.

97 00:06:44.210 00:06:48.189 Miguel de Veyra: Yeah, it’s this one, the message context. But again, there’s no information.

98 00:06:48.190 00:07:05.090 Amber Lin: I know, I know. So I’m gonna get the context from him and then get some sample messages from him. And then with that I think we can do a little bit more, but I’ll wait for him to get back. So I put that as my test in linear. So don’t worry.

99 00:07:05.370 00:07:10.579 Miguel de Veyra: Yeah, okay, so yeah, I mean this one. So we have 2. And then where’s the last one? The one

100 00:07:10.790 00:07:12.909 Miguel de Veyra: the brain forge. Gpt.

101 00:07:12.910 00:07:15.090 Amber Lin: Oh, we have the bravery strategy. Bt.

102 00:07:15.090 00:07:16.059 Miguel de Veyra: Is it here?

103 00:07:17.790 00:07:18.170 Miguel de Veyra: This year.

104 00:07:19.340 00:07:22.800 Casie Aviles: Yeah. But it’s also yeah. An AI show and tell.

105 00:07:23.955 00:07:24.410 Miguel de Veyra: Okay.

106 00:07:25.957 00:07:30.660 Amber Lin: Does this Gpt agent have any contacts, or it’s just gpt.

107 00:07:30.660 00:07:31.810 Miguel de Veyra: It’s just gpt.

108 00:07:32.020 00:07:33.270 Amber Lin: Okay. I see.

109 00:07:34.290 00:07:35.010 Miguel de Veyra: Let’s see.

110 00:07:41.770 00:07:44.849 Miguel de Veyra: Oh, it’s not working, mate, it’s not looking good, Brad.

111 00:07:46.930 00:07:52.089 Casie Aviles: Deployment. Yeah, with azure. There’s a problem with azure.

112 00:07:52.820 00:07:54.689 Casie Aviles: I think that’s also linked to why the.

113 00:07:54.690 00:07:56.480 Miguel de Veyra: That’s why. Yeah, let’s start demoing.

114 00:07:56.480 00:07:57.360 Casie Aviles: There!

115 00:07:57.360 00:07:58.449 Miguel de Veyra: Oh, yeah.

116 00:07:59.130 00:08:01.290 Miguel de Veyra: Devil anything. Just send them screenshots.

117 00:08:01.290 00:08:02.980 Amber Lin: Okay. Good. Good.

118 00:08:02.980 00:08:04.410 Miguel de Veyra: Doesn’t work. Then, you know.

119 00:08:04.410 00:08:05.840 Amber Lin: Oh, yeah.

120 00:08:05.840 00:08:07.829 Miguel de Veyra: We’re we kind of like fools.

121 00:08:08.720 00:08:13.419 Amber Lin: Let me go. Send. I’ll just go send Nico screenshots right now.

122 00:08:15.420 00:08:20.350 Amber Lin: or if you wanna send a screenshot that would be great, too. Let me just go find

123 00:08:21.210 00:08:22.800 Amber Lin: let me go!

124 00:08:25.780 00:08:26.880 Miguel de Veyra: But my password.

125 00:08:27.820 00:08:28.670 Amber Lin: -Oh.

126 00:08:28.670 00:08:30.480 Miguel de Veyra: Oh, there you go! What the hell.

127 00:08:31.730 00:08:34.949 Miguel de Veyra: what? What’s the name of that again? General Gl.

128 00:08:35.850 00:08:39.850 Miguel de Veyra: Yeah, I think it’s like AI show and tell right now.

129 00:08:40.429 00:08:42.659 Miguel de Veyra: Yeah, let’s check the executions.

130 00:08:45.149 00:08:46.279 Miguel de Veyra: It did run.

131 00:08:49.720 00:08:50.800 Casie Aviles: It? Did it run.

132 00:08:51.300 00:08:53.600 Miguel de Veyra: Yeah, it did. It just didn’t send the message.

133 00:08:59.340 00:09:00.559 Miguel de Veyra: What was the question.

134 00:09:00.560 00:09:04.610 Amber Lin: One for Javi. It’s just slack messages right.

135 00:09:05.920 00:09:07.770 Miguel de Veyra: Bro. I don’t think it got called.

136 00:09:09.240 00:09:11.120 Casie Aviles: Yeah, I didn’t get called. I think.

137 00:09:11.400 00:09:12.470 Miguel de Veyra: Yeah, yeah.

138 00:09:12.700 00:09:17.170 Miguel de Veyra: I guess what we can do is just maybe we didn’t add it. We have to add, Here.

139 00:09:17.990 00:09:18.839 Miguel de Veyra: let’s see.

140 00:09:19.510 00:09:21.619 Casie Aviles: Yeah, can you try there in that channel?

141 00:09:21.620 00:09:23.030 Miguel de Veyra: Yeah. See?

142 00:09:39.470 00:09:42.239 Casie Aviles: This is weird.

143 00:09:43.890 00:09:45.940 Casie Aviles: Yeah. Well, I’ll check.

144 00:09:50.180 00:09:53.140 Miguel de Veyra: Yeah, it’s not well. Oh, no.

145 00:09:54.170 00:09:55.739 Miguel de Veyra: this is a slack issue. No.

146 00:09:56.480 00:09:57.920 Casie Aviles: I’m not sure, because this.

147 00:09:58.370 00:10:05.610 Miguel de Veyra: It was working before. Yeah, I mean, we can just show this. Technically speaking.

148 00:10:08.680 00:10:10.089 Casie Aviles: Triggered. For some reason.

149 00:10:16.010 00:10:21.360 Miguel de Veyra: Yeah, I mean, we can just show. I guess this conversation in the screenshot do it like that?

150 00:10:21.650 00:10:25.570 Amber Lin: Yeah, I’m sending Nico the screenshots. I’ll go find I’ll go find.

151 00:10:25.570 00:10:31.488 Miguel de Veyra: And then for your for this one, the channel, I think. I guess we just have to ask

152 00:10:32.190 00:10:38.519 Miguel de Veyra: Robert, if we should create like a separate channel like circle back reminders. Cause I doubt we want to add this on, you know.

153 00:10:38.800 00:10:40.840 Miguel de Veyra: on sales, because then sales is gonna be like

154 00:10:42.090 00:10:45.629 Miguel de Veyra: stuff, and then I’m running this weekly right now. Is that fine.

155 00:10:46.010 00:10:46.530 Amber Lin: Who.

156 00:10:46.700 00:10:48.479 Miguel de Veyra: I’m running this weekly right now.

157 00:10:50.045 00:10:56.429 Amber Lin: I think so like I don’t think there’s any point of running it that frequently.

158 00:10:56.620 00:10:57.560 Miguel de Veyra: Okay. Okay.

159 00:10:58.480 00:11:04.680 Amber Lin: Yeah, cause these leads. I don’t think if we if we message them every day, they’re gonna block us.

160 00:11:05.010 00:11:06.330 Miguel de Veyra: Yeah, you have to.

161 00:11:07.713 00:11:11.070 Miguel de Veyra: Yeah, I think that’s pretty much it for Demos.

162 00:11:11.640 00:11:12.570 Amber Lin: Okay.

163 00:11:12.852 00:11:16.239 Miguel de Veyra: Know there’s a problem in ABC. That case is trying to solve.

164 00:11:16.510 00:11:22.500 Casie Aviles: Yeah, the one with the feedback. For some reason it’s not showing up on for this week. So.

165 00:11:22.500 00:11:26.969 Amber Lin: Yeah, yeah, I was checking that. I was a little bit confused.

166 00:11:27.180 00:11:28.510 Amber Lin: Do we know.

167 00:11:31.557 00:11:34.059 Miguel de Veyra: Do we know why? Why, it’s happening.

168 00:11:35.025 00:11:43.069 Casie Aviles: Yeah, the feedback isn’t. Basically, it’s not getting logged on Snowflake. So I’ll just have to add it. For now, as a quick fix.

169 00:11:44.800 00:11:46.419 Miguel de Veyra: Is that eliminate that issue.

170 00:11:48.240 00:11:52.929 Casie Aviles: Yeah, I think so. It’s or, yeah, it’s my SQL, query. I guess.

171 00:11:53.560 00:11:54.480 Miguel de Veyra: Think, yeah.

172 00:11:55.290 00:11:55.850 Casie Aviles: So.

173 00:11:56.410 00:11:58.869 Miguel de Veyra: Okay, yeah, I think. And then

174 00:11:59.300 00:12:02.400 Miguel de Veyra: for ABC, is there anything else? I don’t think so. Right? That’s it.

175 00:12:02.731 00:12:11.019 Amber Lin: Other are just errors that I meant to solve with Janice, but she declined the meeting today, so I couldn’t do anything about it today.

176 00:12:11.990 00:12:19.399 Amber Lin: but just errors here and there, and we’re gonna have a bigger rollout next week. So.

177 00:12:19.400 00:12:19.910 Miguel de Veyra: I think.

178 00:12:19.910 00:12:23.480 Amber Lin: It will mostly be maintenance

179 00:12:23.690 00:12:30.260 Amber Lin: with the issues. And then some oh, by the ways, here and there, and he’s doing really great. By the way

180 00:12:30.410 00:12:36.699 Amber Lin: like she’s the dashboard is looking really good like. Finally, I feel like we have data people on the team.

181 00:12:37.705 00:12:44.540 Amber Lin: So she she matched the oh, she matched the bot data to the call data.

182 00:12:45.350 00:12:46.310 Miguel de Veyra: Oh, okay.

183 00:12:46.310 00:12:49.210 Amber Lin: Yeah. So I’m happy about that.

184 00:12:51.210 00:12:52.710 Miguel de Veyra: And then I think.

185 00:12:53.878 00:12:59.240 Miguel de Veyra: yeah, another thing I wanted to bring up was, basically, we’re trying to go below 12.5 h right?

186 00:13:00.820 00:13:02.749 Amber Lin: 12.5 h.

187 00:13:02.750 00:13:04.930 Miguel de Veyra: For 25 h. Basically for this client.

188 00:13:04.930 00:13:16.440 Amber Lin: 25. I think 12.5 will be a bit hard, because you guys don’t need to do much engineering. But Annie needs to do work, and I need to do. I need to figure out the rollout stuff.

189 00:13:16.760 00:13:22.429 Miguel de Veyra: So basically shouldn’t should instead of ours, shouldn’t we like use points

190 00:13:23.290 00:13:30.940 Miguel de Veyra: for them like, Hey, you know, like, if it’s 24 h, that’s basically what 16 points maximum for this client a week.

191 00:13:32.290 00:13:34.620 Amber Lin: Oh, you’re talking about estimates.

192 00:13:34.620 00:13:41.810 Miguel de Veyra: Yeah, yeah, me, and Casey was basically on overdrive. Because, you know.

193 00:13:42.170 00:13:46.120 Miguel de Veyra: there was a lot that needed to be done thankfully, we were able to finish somewhere here.

194 00:13:46.670 00:13:49.079 Miguel de Veyra: but I think moving forward, that could be an issue.

195 00:13:51.340 00:13:53.930 Amber Lin: Where you said you had a lot of different tasks.

196 00:13:54.680 00:14:00.489 Miguel de Veyra: I mean, like, there was like a lot of stuff that was, you know, basically just came in all at the same time.

197 00:14:01.520 00:14:07.629 Miguel de Veyra: So I think we need to measure by, you know, each person basically have how many points a week.

198 00:14:07.870 00:14:18.940 Amber Lin: Yeah, yeah, let’s how was, since this is Friday, and we still have 3 min. How was it this week like, did you guys, how many hours did you feel like you worked.

199 00:14:19.893 00:14:24.229 Miguel de Veyra: I mean, it’s here. It’s 34, and I haven’t really worked today.

200 00:14:24.530 00:14:31.310 Miguel de Veyra: But it’s just one day, Tuesday, Thursday, and then last week

201 00:14:34.330 00:14:34.880 Miguel de Veyra: with you.

202 00:14:34.880 00:14:35.450 Amber Lin: Cool.

203 00:14:36.060 00:14:37.610 Miguel de Veyra: Actually I should be done for the week.

204 00:14:39.060 00:14:47.129 Amber Lin: Yeah, can you check on the time sheet up there? Time sheet click up? Yeah, I just wanna check ABC, how long it did.

205 00:14:47.508 00:14:51.540 Miguel de Veyra: Didn’t add any ABC. Work beyond.

206 00:14:57.030 00:15:04.810 Amber Lin: Would you add it? Actually? So we can, we can check how many hours we spent on ABC today? This week.

207 00:15:05.460 00:15:07.530 Miguel de Veyra: Oh, okay, sure. I think I spent.

208 00:15:08.700 00:15:13.499 Miguel de Veyra: Yeah, probably. How long did we spend yesterday, Casey, on this 2 h.

209 00:15:15.000 00:15:16.960 Casie Aviles: Let me check my time.

210 00:15:17.590 00:15:19.070 Miguel de Veyra: Probably towards right.

211 00:15:19.070 00:15:21.280 Casie Aviles: Yeah, 2 of us. That’s what I logged.

212 00:15:21.280 00:15:24.870 Miguel de Veyra: And then I think we spent like 30 min on here.

213 00:15:25.980 00:15:26.980 Amber Lin: Yeah, okay.

214 00:15:28.040 00:15:30.679 Miguel de Veyra: Okay, I’ll just do this to be honest, this is a lot easier.

215 00:15:30.930 00:15:42.880 Amber Lin: Yeah, sure. And I mean Casey. If you can add it, I’ll be great. So I can know. Oh, how are we doing this week should we take on less from the client, so it will give me an idea to say no better.

216 00:15:43.130 00:15:45.310 Miguel de Veyra: Yeah, especially for.

217 00:15:45.310 00:15:49.450 Casie Aviles: I added my logs yesterday for.

218 00:15:50.590 00:15:52.570 Amber Lin: Okay, yeah.

219 00:15:53.870 00:16:08.739 Amber Lin: And Miguel, I think it’s a great idea. We’ll start to like starting next next Monday. When we plan we’ll try to have all the tickets, and then we’ll give estimates, and we’ll say, Okay, 16 points, Max, as you, as you said.

220 00:16:09.030 00:16:15.100 Miguel de Veyra: Yeah, I think. Wait. Sorry. No. Next week would be, I think, 15 point cause it 5 is 8 h right?

221 00:16:15.720 00:16:19.590 Amber Lin: Oh, wait! Cause you guys are out Thursday, Friday. We need to make it less.

222 00:16:19.810 00:16:23.470 Miguel de Veyra: Yeah, so it’s 15. Normally, a week would be 25 points.

223 00:16:23.470 00:16:29.610 Amber Lin: Oh, oh! Oh! Oh! That’s why I was like wait an hour is more than 1 point. I was confused.

224 00:16:30.500 00:16:33.850 Miguel de Veyra: Yeah. So I I don’t know. I guess it’s just a better way to track it.

225 00:16:34.350 00:16:35.860 Amber Lin: Yeah, I agree, okay.

226 00:16:36.560 00:16:49.019 Amber Lin: sounds good. Thank you. Guys. I sent Nico all the screenshots. You guys, you guys probably don’t have to be there. I feel like he’s gonna he’s gonna ask you about the diagrams.

227 00:16:49.240 00:16:53.339 Amber Lin: But other than that, Miguel, I don’t think you have to be there.

228 00:16:53.490 00:16:54.080 Miguel de Veyra: What do you know?

229 00:16:54.080 00:16:56.069 Miguel de Veyra: Yeah, yeah, I’m not gonna be definitely busy.

230 00:16:56.210 00:17:01.489 Amber Lin: Oh, ABC, both of you, I didn’t. I didn’t even send you the invite I was like, I don’t think you need to waste your time. There.

231 00:17:01.490 00:17:05.979 Miguel de Veyra: Oh, yeah, I mean for the company, demo. Yeah, I’ll try to be there. But we’ll see.

232 00:17:05.980 00:17:06.740 Amber Lin: Okay.

233 00:17:07.140 00:17:08.139 Amber Lin: Okay. Sounds good.

234 00:17:08.140 00:17:08.710 Casie Aviles: Me there.

235 00:17:08.710 00:17:12.420 Miguel de Veyra: And then for this one number, if you could like, quickly take a look so I could send this to Josh.

236 00:17:15.390 00:17:16.160 Miguel de Veyra: Basically it’s.

237 00:17:16.160 00:17:16.970 Amber Lin: Just, you know.

238 00:17:16.970 00:17:19.060 Miguel de Veyra: We’ll just. I don’t want to do that

239 00:17:19.550 00:17:24.300 Miguel de Veyra: anymore. Just give us how you’ll approach it right.

240 00:17:24.300 00:17:28.510 Amber Lin: Okay. Yes, I’ll go. Look if this is in recruiting. Okay, I’ll go. Take a look.

241 00:17:29.240 00:17:30.020 Miguel de Veyra: Okay.

242 00:17:30.480 00:17:31.660 Amber Lin: All right.

243 00:17:31.770 00:17:36.220 Amber Lin: Thank you, guys. We’re so good on time. Perfectly. 15 min.

244 00:17:36.380 00:17:37.060 Miguel de Veyra: Bye, bye, guys.

245 00:17:37.060 00:17:37.810 Casie Aviles: Thanks guys.

246 00:17:37.810 00:17:39.030 Amber Lin: Okay. Bye-bye.