Meeting Title: AI Team Standup Date: 2025-05-06 Meeting participants: Amber Lin, Miguel De Veyra, Casie Aviles, Awaish Kumar


WEBVTT

1 00:00:19.250 00:00:20.629 Miguel de Veyra: Hello! Hello!

2 00:00:22.610 00:00:23.150 Casie Aviles: Hey!

3 00:00:37.910 00:00:39.110 Amber Lin: Hi.

4 00:00:42.790 00:00:47.029 Amber Lin: thank you guys. That meeting it was a. It was a tough meeting.

5 00:00:49.523 00:00:53.930 Miguel de Veyra: No, it’s okay. I think I found the solution, Casey, though this is a bit.

6 00:00:57.940 00:01:01.740 Miguel de Veyra: It’s a bit unorthodox. But yeah, we’ll discuss this later

7 00:01:02.560 00:01:04.370 Miguel de Veyra: or tomorrow, because I’m done for the day.

8 00:01:06.030 00:01:11.630 Amber Lin: Okay, let’s just let. Then let’s just go through the AI stuff.

9 00:01:11.630 00:01:13.019 Miguel de Veyra: They’ll learn here they can see you.

10 00:01:13.300 00:01:15.849 Amber Lin: Yeah, let’s go. Do that. Let me share my screen.

11 00:01:31.920 00:01:41.980 Amber Lin: Go on the current cycle. I added a few tickets as we were talking through the other meeting. We’ll go through them once we like go through this cycle

12 00:01:43.590 00:01:49.370 Amber Lin: cycle tickets. So let’s start here and go. How was how was yesterday?

13 00:01:53.860 00:02:01.990 Miguel de Veyra: yeah. The urban stems. I’m not sure with this urban stems the one that has client. Wait, let me just check.

14 00:02:03.670 00:02:19.669 Miguel de Veyra: I don’t know urban stem should be good. I’m just working with Casey to basically create the bot for this because I followed the instructions he gave, and it didn’t work for me, and then we checked it out earlier. And then there seems to be some sort of bug that we need to work on

15 00:02:20.260 00:02:23.860 Miguel de Veyra: on my end. So yeah, I that’s why I put this on escalated.

16 00:02:25.400 00:02:33.580 Miguel de Veyra: And then the pool parts. Which channel do we want there? Because, I added an AI team. There’s no client dash

17 00:02:34.410 00:02:38.620 Miguel de Veyra: pool parts, so I’m not sure which. What’s the name of the Channel? I’m not there.

18 00:02:40.690 00:02:49.409 Amber Lin: It’s client dashboards to go. Let me just add the brain forge bot to this as well.

19 00:02:49.748 00:02:51.099 Miguel de Veyra: Okay, that makes sense.

20 00:02:51.100 00:02:54.160 Amber Lin: Let me just go add that oh.

21 00:02:56.090 00:03:00.509 Miguel de Veyra: Yeah, but yeah, since I wasn’t able to really process this today.

22 00:03:01.730 00:03:05.450 Miguel de Veyra: But zoom is there so slack it doesn’t, doesn’t really work.

23 00:03:06.060 00:03:06.880 Amber Lin: Okay.

24 00:03:12.100 00:03:21.160 Amber Lin: is it already added on? I’m trying to figure, I remember how to add it last time. Hmm, integrations.

25 00:03:28.960 00:03:29.910 Amber Lin: Oh.

26 00:03:33.980 00:03:38.640 Amber Lin: nothing is already there in pool parts

27 00:03:39.060 00:03:41.409 Amber Lin: in the client channel. Hopefully, it’s.

28 00:03:41.410 00:03:43.100 Miguel de Veyra: Okay. Let me check.

29 00:03:43.770 00:03:44.620 Amber Lin: Yeah.

30 00:03:51.130 00:03:52.390 Miguel de Veyra: So give me a minute.

31 00:04:03.080 00:04:09.369 Miguel de Veyra: They only have access to in external pool parts, external marketing sales and shipping.

32 00:04:10.193 00:04:14.750 Amber Lin: It’s in client. It’s in client pool parts to go as well. I just checked.

33 00:04:19.339 00:04:20.849 Miguel de Veyra: Lion, lion.

34 00:04:22.070 00:04:24.520 Amber Lin: Line, dash, dash, pool, parts.

35 00:04:24.520 00:04:27.230 Miguel de Veyra: Yeah, we don’t have access to it.

36 00:04:28.370 00:04:30.520 Amber Lin: Let me share my screen.

37 00:04:31.620 00:04:33.100 Amber Lin: So

38 00:04:37.250 00:04:38.560 Amber Lin: this is here.

39 00:04:39.250 00:04:40.720 Amber Lin: We’re in 4 parts.

40 00:04:40.950 00:04:43.439 Amber Lin: Says it’s here in the in the Channel.

41 00:04:44.190 00:04:49.990 Amber Lin: Ask if I need to look it up, Link. It’s right here.

42 00:04:50.540 00:04:59.309 Miguel de Veyra: Okay, it’s added, yeah, wait. Let me check another token.

43 00:05:10.970 00:05:13.610 Miguel de Veyra: I thought, here, okay, okay, I got it.

44 00:05:15.040 00:05:16.540 Miguel de Veyra: That’s a different token.

45 00:05:19.380 00:05:22.820 Miguel de Veyra: Okay, yeah. Well, I’ll work on that tomorrow.

46 00:05:27.440 00:05:29.410 Amber Lin: Okay, let me go back to the linear.

47 00:05:37.730 00:05:39.030 Amber Lin: So

48 00:05:42.490 00:05:46.379 Amber Lin: right? And how is this one?

49 00:05:47.000 00:05:49.840 Amber Lin: So this will go back in progress.

50 00:05:50.150 00:05:52.389 Amber Lin: What about this? This ticket.

51 00:05:55.170 00:05:56.860 Miguel de Veyra: Yeah, that’s still in progress.

52 00:05:57.410 00:06:04.389 Amber Lin: Okay, what is the what does the progress look like? What do we have and what we? What do? We don’t have.

53 00:06:06.438 00:06:08.950 Miguel de Veyra: I think, for here we just need to list down, which

54 00:06:09.430 00:06:13.010 Miguel de Veyra: cause I’m not sure which repos we have access to.

55 00:06:13.430 00:06:15.500 Miguel de Veyra: or which are our own, and which are.

56 00:06:15.500 00:06:23.120 Amber Lin: I do believe. Have you talked to a wish about it? Because wish was working with to

57 00:06:23.550 00:06:25.359 Amber Lin: where is his tickets?

58 00:06:26.061 00:06:28.168 Amber Lin: To figure out how to

59 00:06:29.000 00:06:32.550 Amber Lin: add the different repos. Where is that ticket?

60 00:06:35.590 00:06:39.839 Amber Lin: Like the personal access tokens for the different repos.

61 00:06:40.390 00:06:43.379 Miguel de Veyra: I’m not sure he hasn’t communicated with us.

62 00:06:44.350 00:06:45.696 Amber Lin: Oh, okay.

63 00:06:48.480 00:06:52.620 Miguel de Veyra: Cause. I think the idea here is he’ll just get everything so we can just process it.

64 00:06:53.670 00:06:58.840 Amber Lin: Okay, so that should be in his 2 S.

65 00:06:59.110 00:07:00.659 Amber Lin: Very, github.

66 00:07:01.840 00:07:02.999 Amber Lin: Think it’s time.

67 00:07:03.600 00:07:04.730 Amber Lin: What’s a place?

68 00:07:11.710 00:07:16.534 Amber Lin: Can you guys ask him how this is going?

69 00:07:20.200 00:07:22.319 Miguel de Veyra: Okay, yeah, sure. I’ll I’ll send him a message.

70 00:07:22.730 00:07:23.430 Amber Lin: Yeah.

71 00:07:29.640 00:07:30.750 Amber Lin: Oh, this one.

72 00:07:36.300 00:07:37.680 Miguel de Veyra: Okay, understandable.

73 00:07:38.300 00:07:38.910 Amber Lin: Oh!

74 00:07:44.380 00:07:48.259 Miguel de Veyra: But yeah, let’s go back to this current cycle.

75 00:07:57.270 00:08:04.299 Miguel de Veyra: yeah, I think that’s pretty much it for this one. I think we need to focus on like the the newer tickets.

76 00:08:04.300 00:08:11.290 Amber Lin: Platform. Yeah, cool and then do you think we have capacity? Because we don’t like

77 00:08:11.400 00:08:15.140 Amber Lin: this is just kind of gonna happen on the background.

78 00:08:16.040 00:08:24.589 Amber Lin: Full parts will get initiated, I think. Just to clarify this one. We’re only missing like what what’s left to be done here.

79 00:08:27.050 00:08:29.509 Miguel de Veyra: Reports. We need to process luck

80 00:08:29.740 00:08:32.020 Miguel de Veyra: because we weren’t able to process that.

81 00:08:34.141 00:08:42.239 Amber Lin: How does that look like? Because we we have the Brainforge bot in there now, like, does it take 5 min? Does it take an hour.

82 00:08:42.240 00:08:43.370 Miguel de Veyra: No, that takes.

83 00:08:43.470 00:08:45.530 Miguel de Veyra: It’s probably 3 points worth of work.

84 00:08:46.290 00:08:47.620 Amber Lin: Oh, really. Okay.

85 00:08:48.110 00:08:51.960 Miguel de Veyra: Yeah, because basically, we’re gonna get all slack messages and then

86 00:08:52.140 00:08:55.020 Miguel de Veyra: process it. Put put it into the super base.

87 00:08:55.540 00:08:56.200 Amber Lin: Hmm.

88 00:09:04.160 00:09:08.639 Amber Lin: okay, sounds good. So that’s what needs to be done.

89 00:09:15.890 00:09:18.360 Amber Lin: I thought that was gonna be done yesterday.

90 00:09:19.311 00:09:21.519 Miguel de Veyra: No cause we had.

91 00:09:21.670 00:09:23.749 Miguel de Veyra: We weren’t able to put the bot

92 00:09:24.720 00:09:26.549 Miguel de Veyra: right. We I got a detector.

93 00:09:31.930 00:09:32.680 Amber Lin: Okay?

94 00:09:34.118 00:09:38.429 Amber Lin: Github, and linear to all agents.

95 00:09:39.370 00:09:41.599 Amber Lin: what do we have? And what do we don’t have.

96 00:09:42.829 00:09:46.869 Miguel de Veyra: The one with the wish we’ll we have to speak, speak to a wish, basically.

97 00:09:52.370 00:09:53.980 Amber Lin: Remaining.

98 00:09:54.160 00:09:56.360 Miguel de Veyra: On which tokens Yada Yada.

99 00:09:58.870 00:10:01.830 Amber Lin: Okay? And for linear, we need to

100 00:10:02.060 00:10:05.369 Amber Lin: do, we figure out linear at all. This one.

101 00:10:06.400 00:10:08.960 Amber Lin: Let me just remove linear from this. Then.

102 00:10:12.641 00:10:18.979 Amber Lin: when we say add to all agents, he’s gonna put it in S. 3, right? And what are we gonna do.

103 00:10:19.332 00:10:30.270 Miguel de Veyra: Basically, just get the Xml file. It should be pretty easy to add it in to each agent, because basically, that’s just Xml file download it, and then put it into.

104 00:10:30.270 00:10:30.780 Amber Lin: Hmm.

105 00:10:30.780 00:10:36.990 Miguel de Veyra: Or I think it’s I think it’s text file, he said. But yeah, that should be pretty simple. Once it’s there.

106 00:10:37.490 00:10:38.120 Amber Lin: Okay?

107 00:10:39.300 00:10:43.090 Amber Lin: Sounds good. So let’s check with him on that.

108 00:10:45.450 00:10:49.180 Amber Lin: This one, I mean.

109 00:10:49.540 00:10:57.770 Amber Lin: we have few left in cycle. Are we gonna do the linear to super base? Or are we trying to figure out notion, to

110 00:10:58.020 00:11:00.370 Amber Lin: like how to access notion.

111 00:11:00.370 00:11:04.929 Miguel de Veyra: I think linear super base, because we have capacity cases a bit free.

112 00:11:05.190 00:11:07.769 Miguel de Veyra: But I think, yeah, this laptop.

113 00:11:08.070 00:11:10.830 Miguel de Veyra: Well, I think that takes priority.

114 00:11:11.750 00:11:16.999 Miguel de Veyra: But yeah, we should be able to process that. We’re gonna sign that I think to Casey, the linear.

115 00:11:18.228 00:11:22.889 Amber Lin: Sorry I I was just in the progress of this ticket. So for

116 00:11:23.200 00:11:29.909 Amber Lin: notion, do we also add it to like S. 3, or to super base like, how does that? How is that gonna work.

117 00:11:30.624 00:11:33.289 Miguel de Veyra: We’ll just get it, basically from

118 00:11:34.281 00:11:38.499 Miguel de Veyra: the there’s, there’s a way to get it directly from.

119 00:11:39.310 00:11:44.099 Miguel de Veyra: From notion itself, but via any 10, so there’s no need to purchase files on single base.

120 00:11:45.140 00:11:50.789 Amber Lin: Okay. So who are is gonna take this ticket. And how long is that? Gonna take.

121 00:11:51.240 00:11:54.359 Miguel de Veyra: That’s probably gonna take 5 points. And then

122 00:11:55.210 00:11:57.420 Miguel de Veyra: I don’t think this should be on this cycle.

123 00:12:01.180 00:12:03.870 Miguel de Veyra: There’s no, there’s no notion documentation yet.

124 00:12:05.213 00:12:24.839 Amber Lin: can we at least, and figure out how the workflow is gonna be? Because once they have the documentation ideally, we’ll just be able to process that right? But we but then, if we do it next week, then we still have to figure out, okay, hey, how how is this gonna work? And then it’s gonna take another week.

125 00:12:25.920 00:12:32.040 Miguel de Veyra: I think the one we here. The task that that’s better to make is the guidelines for that.

126 00:12:32.920 00:12:35.069 Amber Lin: Is the guidelines. Gonna take that long.

127 00:12:36.068 00:12:45.279 Miguel de Veyra: Cause we have to test. Basically, that’s part of what we what we need to do. We need to test on what’s gonna work and what’s not, so we can give them an accurate set of guidelines.

128 00:12:48.540 00:12:49.610 Amber Lin: Or notion.

129 00:12:49.870 00:13:02.489 Miguel de Veyra: Yeah yeah, for notion. So we’re gonna test. You know what? What does? Bullet points work because we know tables work. It doesn’t work for Github, but we’re not sure if it works for notion.

130 00:13:03.990 00:13:06.189 Amber Lin: Is that gonna take the whole day.

131 00:13:08.582 00:13:12.690 Miguel de Veyra: Probably that’s what 3 point job, I believe.

132 00:13:13.470 00:13:14.380 Amber Lin: Okay.

133 00:13:14.710 00:13:16.359 Miguel de Veyra: So like 3 to 4 h.

134 00:13:18.930 00:13:30.720 Amber Lin: Okay, we have 3 more days in this cycle of 2 people.

135 00:13:31.980 00:13:36.039 Amber Lin: Yeah, I can. I can let me just put this somewhere, and then.

136 00:13:36.040 00:13:38.150 Miguel de Veyra: This one, I think. And we need to finish that today.

137 00:13:38.960 00:13:39.730 Amber Lin: Yeah.

138 00:13:39.880 00:13:42.860 Amber Lin: Finish out. Sorry. Finish out which one.

139 00:13:43.270 00:13:46.190 Miguel de Veyra: The github the the notion thing.

140 00:13:46.390 00:13:50.080 Miguel de Veyra: because Utam is expecting us to send it to owash by end of day.

141 00:13:50.530 00:13:51.130 Miguel de Veyra: It’s all for.

142 00:13:51.130 00:13:51.560 Amber Lin: Yeah.

143 00:13:51.560 00:13:56.250 Miguel de Veyra: Take some time today to finish it, and then just minus it to my time tomorrow.

144 00:13:59.370 00:14:02.930 Amber Lin: Let me add all these to cycle, and then we can look at it.

145 00:14:03.230 00:14:08.329 Amber Lin: So we have Java documentation. This is not ours, but

146 00:14:11.520 00:14:29.970 Amber Lin: So just say like, Send send Javi documentation by. This is probably Kyle by like Thursday, and then

147 00:14:31.720 00:14:34.000 Amber Lin: guidelines for documentation

148 00:14:34.890 00:14:42.239 Amber Lin: like, honestly, isn’t this the same as what we have for ABC, just a tiny bit of tweaks like, how detailed does that need to be.

149 00:14:46.720 00:14:54.330 Miguel de Veyra: We’re not sure what the notion limitations are, because ABC is on Github. Right? I mean, Github, sorry Google Docs.

150 00:14:54.740 00:15:00.047 Amber Lin: I see. Okay, sounds good. And I’ll say, that’s for today.

151 00:15:01.790 00:15:06.150 Amber Lin: verify, yeah, this is a spike.

152 00:15:07.980 00:15:08.750 Amber Lin: Oh.

153 00:15:09.120 00:15:13.769 Miguel de Veyra: Yeah. And then Kca, for this one, we need to get back to Utam tomorrow.

154 00:15:17.530 00:15:24.929 Amber Lin: Tomorrow. What needs to like? Are we presenting him? Impossible solution? Many solutions, the cost.

155 00:15:24.930 00:15:26.540 Casie Aviles: Do we just need like a plan.

156 00:15:27.060 00:15:34.920 Miguel de Veyra: Yeah, basically, what’s you know, we need to spike and then come up with something on

157 00:15:36.210 00:15:40.740 Miguel de Veyra: what’s the best way to not spend 252,000 tokens.

158 00:15:41.110 00:15:47.330 Casie Aviles: I can. I guess I can give some initial ideas right now, but we could do some further deep dives, so.

159 00:15:47.330 00:15:56.629 Miguel de Veyra: Yeah, I think we can. I think honestly, what I’ll do is I’ll just continue my shift to tomorrow. So tomorrow, you know, I just won’t go to work, so we have some shit to present.

160 00:15:58.556 00:16:09.520 Casie Aviles: Okay? So basically, there’s like 2 approaches that we’ve been floating around already. Right with how the AI accesses the knowledge that it needs.

161 00:16:09.700 00:16:13.609 Casie Aviles: So we have the the 1st one is the context.

162 00:16:14.473 00:16:20.289 Casie Aviles: approach, which is what we’re doing right now and then. The second one is the rag approach.

163 00:16:20.500 00:16:23.490 Casie Aviles: which is something I’ve also been

164 00:16:24.449 00:16:30.350 Casie Aviles: experimenting with. But so I would get. I would give some pros and cons for each.

165 00:16:30.770 00:16:35.390 Casie Aviles: So yeah, I guess you for that bullet you could just put, I guess. Rag RAG, yeah.

166 00:16:35.910 00:16:37.670 Miguel de Veyra: Or the and then the other thing.

167 00:16:37.670 00:16:38.410 Casie Aviles: Yeah, so.

168 00:16:38.410 00:16:42.085 Miguel de Veyra: The other thing we can add here is what the hell do you call it?

169 00:16:45.010 00:16:48.609 Miguel de Veyra: Casey? Because, honestly, I think one thing we could do is just

170 00:16:48.720 00:16:56.359 Miguel de Veyra: whatever the message it get the keyword, search slack, using it like, use the filter like search super base

171 00:16:57.600 00:16:58.130 Miguel de Veyra: right.

172 00:16:58.130 00:17:04.199 Casie Aviles: Yeah, we could we? That’s we could. That’s when a potential idea, we could definitely add that there. So.

173 00:17:05.000 00:17:09.079 Miguel de Veyra: You know, basically a super base search or something something like that.

174 00:17:10.530 00:17:12.820 Casie Aviles: So keyword search, you mean.

175 00:17:12.829 00:17:14.469 Miguel de Veyra: Yeah. Yeah. Keyword, search.

176 00:17:16.230 00:17:20.609 Casie Aviles: Okay? So that okay, so it’s not like, it doesn’t use embeddings. Right?

177 00:17:21.359 00:17:24.819 Miguel de Veyra: Yeah, yeah, because, are we gonna really embed?

178 00:17:25.619 00:17:27.509 Miguel de Veyra: 5 5 words.

179 00:17:30.410 00:17:35.378 Casie Aviles: Yeah, okay, I get it. So I can give some pros and cons for context.

180 00:17:35.960 00:17:40.529 Casie Aviles: yeah. So the pros for context, this is much faster to implement.

181 00:17:43.560 00:17:46.289 Miguel de Veyra: I think, Casey, let’s discuss this later. Not now.

182 00:17:46.760 00:17:47.550 Casie Aviles: Oh, sorry. Okay.

183 00:17:47.550 00:17:48.710 Miguel de Veyra: Yeah, yeah, let’s do this later.

184 00:17:48.710 00:17:49.410 Casie Aviles: Sorry.

185 00:17:49.410 00:17:51.140 Miguel de Veyra: Yeah, no, no worries, no worries.

186 00:17:54.060 00:17:57.460 Miguel de Veyra: Yeah. I think for this one. It’ll take, probably in the entire day.

187 00:18:00.350 00:18:04.599 Miguel de Veyra: Yeah, well, yeah, I’ll work with Casey on this one, but I think we should assign it to him.

188 00:18:05.180 00:18:05.840 Amber Lin: Okay.

189 00:18:06.500 00:18:06.980 Miguel de Veyra: Let’s see.

190 00:18:06.980 00:18:10.240 Amber Lin: And we’ll say due date.

191 00:18:10.240 00:18:11.140 Miguel de Veyra: Tomorrow.

192 00:18:11.140 00:18:12.670 Amber Lin: One, Great.

193 00:18:13.590 00:18:16.410 Casie Aviles: At least just a plan, because of, yeah.

194 00:18:16.410 00:18:25.710 Miguel de Veyra: Yeah, we’re not gonna implement that. Oh, and then the other thing I I’m looking at right now. Can we just add it there? Sorry amber summary trees. So basically.

195 00:18:26.040 00:18:28.569 Miguel de Veyra: yeah, I’ll explain it later on. The on our call.

196 00:18:29.462 00:18:33.030 Amber Lin: Is it for the for the swag?

197 00:18:33.030 00:18:33.850 Miguel de Veyra: Yep. Yep.

198 00:18:34.510 00:18:35.460 Amber Lin: Oh, okay.

199 00:18:35.670 00:18:37.050 Miguel de Veyra: Summary trees.

200 00:18:38.570 00:18:42.290 Amber Lin: Summer very intriguing, because it.

201 00:18:42.430 00:18:42.920 Miguel de Veyra: Yeah, yeah.

202 00:18:42.920 00:18:44.749 Amber Lin: That website. Okay?

203 00:18:45.490 00:18:54.319 Amber Lin: And probably we should also Google, other less related solutions or less possible solutions. So just.

204 00:18:54.320 00:18:55.210 Miguel de Veyra: That’s part of it.

205 00:18:55.620 00:18:57.530 Miguel de Veyra: Summary trick and keyword search.

206 00:18:58.130 00:18:59.140 Amber Lin: Awesome.

207 00:18:59.400 00:19:02.809 Amber Lin: Great! I’ll I trust you guys with that. That.

208 00:19:02.810 00:19:04.030 Miguel de Veyra: And then.

209 00:19:04.030 00:19:04.870 Amber Lin: Tickets.

210 00:19:05.060 00:19:09.029 Miguel de Veyra: I think we need to move some stuff around then, because they, you know.

211 00:19:09.415 00:19:17.120 Amber Lin: Well, let’s let’s look at what we have. Right? So that’s it’s already in feeling good progress

212 00:19:17.240 00:19:19.180 Amber Lin: like that’s not

213 00:19:19.340 00:19:25.619 Amber Lin: our stuff. Oh, he’s figuring. Oh, he’s figured out the linear tickets to S. 3. Okay, great

214 00:19:26.204 00:19:31.780 Amber Lin: that’s not our stuff. The only thing here is that’s Kyle stuff.

215 00:19:32.330 00:19:40.469 Amber Lin: So the main thing is this, I think this is important. I’m gonna I’m gonna say, this is for later.

216 00:19:43.930 00:19:44.760 Amber Lin: Alright.

217 00:19:45.130 00:19:48.960 Amber Lin: So this is high priority. It’s urgent.

218 00:19:50.074 00:19:54.320 Amber Lin: Is this good like? Can I say this is done?

219 00:19:56.490 00:19:59.360 Amber Lin: Slash 3 s. 3 just super. Basic.

220 00:19:59.736 00:20:00.310 Casie Aviles: Can you.

221 00:20:00.310 00:20:01.710 Miguel de Veyra: I mean, that’s affected by this.

222 00:20:01.710 00:20:02.570 Casie Aviles: Right there. Yeah.

223 00:20:02.940 00:20:03.670 Miguel de Veyra: Yeah.

224 00:20:04.580 00:20:05.240 Amber Lin: Hmm.

225 00:20:08.980 00:20:15.900 Casie Aviles: Oh, I think I added some screenshots below of the tests that they did.

226 00:20:17.610 00:20:25.429 Amber Lin: Oh, I think, wouldn’t this also be helpful to tell Utam? Hey, how does Rag perform like? How how good can rag be?

227 00:20:25.740 00:20:30.330 Amber Lin: So this could be part of your argument when you do the spike and present to him tomorrow.

228 00:20:32.130 00:20:35.409 Casie Aviles: Yeah, okay, so I guess this one’s done.

229 00:20:36.080 00:20:39.820 Amber Lin: I’ll see that it’s done great. So we have

230 00:20:50.700 00:20:56.830 Amber Lin: these 2. Both are initialized right like Slack and zoom.

231 00:20:57.860 00:20:59.030 Amber Lin: Both of these.

232 00:21:01.320 00:21:02.279 Casie Aviles: Oh, wait! Sorry!

233 00:21:02.780 00:21:04.467 Miguel de Veyra: Sorry initialized lap

234 00:21:05.270 00:21:06.890 Amber Lin: Say, these 2 are done.

235 00:21:08.200 00:21:10.589 Miguel de Veyra: Initialization. I think, yeah.

236 00:21:10.970 00:21:16.859 Amber Lin: Okay, yeah, we can do. If we need improvements, we’ll make another ticket.

237 00:21:18.240 00:21:19.130 Amber Lin: All right.

238 00:21:22.180 00:21:29.540 Amber Lin: let’s all. Let’s just add these there. For the golden data sheet I can make

239 00:21:30.140 00:21:36.040 Amber Lin: if I guess for this one. The only thing is, do you think Javi is good enough, Javi Bot.

240 00:21:36.140 00:21:48.309 Amber Lin: for them to ask the questions like, Are we very far away from what we expect the bot to be? Should we ask Kyle to test and verify the questions now like, would that be helpful?

241 00:21:48.310 00:21:50.320 Miguel de Veyra: I’ve already asked them to test it.

242 00:21:50.840 00:21:55.910 Amber Lin: Oh, fantastic! So I will put that there.

243 00:21:56.770 00:21:58.210 Amber Lin: That’s not your task.

244 00:22:00.140 00:22:04.460 Amber Lin: I just wanna assign this somewhere so we can look at. Look at the stuff we need.

245 00:22:08.061 00:22:11.768 Miguel de Veyra: That one. I’ll probably have to work on that, because I need to send it to.

246 00:22:12.520 00:22:20.969 Amber Lin: Yeah, let me check if there’s anything anything else. Nope, Nope, all right.

247 00:22:22.750 00:22:27.849 Amber Lin: Funny, we’re back to the spike of rag. Okay, so I go for all right.

248 00:22:27.850 00:22:29.150 Miguel de Veyra: Went full circle.

249 00:22:29.630 00:22:32.849 Amber Lin: I know. I guess we can never have avoided it.

250 00:22:34.925 00:22:43.784 Amber Lin: Alright! So we have these. Let’s look. Let’s figure out the due dates of like when we want to do what cause I agree. It’s quite a bit of stuff.

251 00:22:45.150 00:22:47.170 Amber Lin: let’s say we move that.

252 00:22:47.980 00:22:51.400 Miguel de Veyra: Yeah, we can move this to Thursday. I think.

253 00:22:52.630 00:23:02.080 Amber Lin: Thursday. Okay, let’s push. Push it back a bit if we need like. Eventually, wanna get all of these done by Friday. But we can like shift things around.

254 00:23:05.390 00:23:07.380 Amber Lin: Yes, this.

255 00:23:07.580 00:23:10.770 Miguel de Veyra: That’s the day there’s also today.

256 00:23:12.410 00:23:15.660 Amber Lin: This source via Nan.

257 00:23:15.890 00:23:16.780 Miguel de Veyra: Yeah, yeah.

258 00:23:16.780 00:23:18.139 Amber Lin: A lot of work today.

259 00:23:18.860 00:23:28.830 Miguel de Veyra: Now we have to do with them is gonna get past. So but yeah, I mean, I’ll just extend again. I’ll just extend my shift today, and then I’ll just, you know I just won’t go to work tomorrow.

260 00:23:29.170 00:23:31.810 Amber Lin: I’ll say I’ll say, like tomorrow, like.

261 00:23:32.660 00:23:38.820 Amber Lin: ultimately, this is not this one’s not like as pressing right. Cause this. They’re waiting on us for.

262 00:23:38.820 00:23:39.500 Miguel de Veyra: Yeah, yeah.

263 00:23:39.500 00:23:48.998 Amber Lin: It’s kind of as they figure out their documentation. We still have some time. So I like, I I want you to actually go to bed.

264 00:23:49.350 00:23:54.489 Miguel de Veyra: Notion. We can put this as low, and then put this on, I think, end of week.

265 00:23:55.400 00:23:59.480 Amber Lin: This. This is high priority for the documentation.

266 00:24:01.000 00:24:03.019 Amber Lin: Let’s say, yeah, let’s say, and.

267 00:24:03.020 00:24:04.770 Miguel de Veyra: Let’s just do end of week. Yeah.

268 00:24:05.150 00:24:08.690 Amber Lin: Okay end of this week.

269 00:24:09.060 00:24:11.410 Amber Lin: So we want to figure that one out early.

270 00:24:11.410 00:24:13.670 Miguel de Veyra: Linear super base. I think we can.

271 00:24:15.119 00:24:20.040 Miguel de Veyra: Casey, do you have capacity to work on this like Friday, or something.

272 00:24:20.300 00:24:27.139 Amber Lin: Yeah, I feel like this is more of a 3rd after our data meeting task. So like, either later Thursday or Friday.

273 00:24:27.600 00:24:30.300 Miguel de Veyra: Yeah, yeah, let’s just move that to Friday. And if we.

274 00:24:30.300 00:24:31.390 Amber Lin: And I’ll move this.

275 00:24:31.390 00:24:31.760 Casie Aviles: Okay.

276 00:24:31.760 00:24:32.410 Amber Lin: I see.

277 00:24:32.760 00:24:39.729 Miguel de Veyra: But I think the priority right now is this lab, because the thing is, we’ll probably have to do that for everything, including

278 00:24:40.370 00:24:43.270 Miguel de Veyra: the track thing. We have to do that for everything. I believe.

279 00:24:44.200 00:24:49.830 Amber Lin: Okay, so this is today the backfills.

280 00:24:50.580 00:24:55.840 Amber Lin: What is the priority to backfilling other client agents?

281 00:24:58.780 00:25:03.849 Amber Lin: Think we have Javi and Eden.

282 00:25:04.980 00:25:05.800 Amber Lin: Right?

283 00:25:06.700 00:25:08.629 Amber Lin: What else do we need.

284 00:25:12.480 00:25:16.139 Miguel de Veyra: Have we started on client off the record.

285 00:25:18.588 00:25:22.139 Amber Lin: Starting. Wednesday, starting. Wednesday.

286 00:25:22.550 00:25:29.459 Miguel de Veyra: Okay, okay? Cause, I don’t think we have capacity for this week anymore, at least.

287 00:25:31.850 00:25:33.690 Amber Lin: Oh!

288 00:25:34.360 00:25:37.410 Miguel de Veyra: What about ABC, you guys had a meeting yesterday right.

289 00:25:37.760 00:25:42.219 Amber Lin: Yeah. Oh, I totally forgot about that. Yeah. So there’s

290 00:25:42.660 00:25:47.990 Amber Lin: like, it’s mostly just a trainer. Bot, that’s on the ABC side.

291 00:25:48.777 00:25:54.760 Amber Lin: This is more urgent and pressing. I can think.

292 00:25:55.740 00:25:57.700 Miguel de Veyra: Have they signed the new deal or not yet.

293 00:25:58.455 00:26:00.830 Amber Lin: They’re pretty close. I would say.

294 00:26:01.930 00:26:11.889 Amber Lin: Yeah, so this week there will be like a few points of tasks that we want to do there. But since we are wanting to keep the hours low, probably around like

295 00:26:12.560 00:26:17.109 Amber Lin: around, like 5 to 10 points like maximum a day of work, I would say.

296 00:26:18.931 00:26:26.340 Amber Lin: so I could save like a day of Casey’s time on on there, like, we can shift this.

297 00:26:27.950 00:26:33.240 Amber Lin: Okay, shift that one go to super base.

298 00:26:34.200 00:26:37.970 Amber Lin: Yeah, okay, I I’ll say, like linear something later

299 00:26:38.750 00:26:43.129 Amber Lin: end of this week. And this week we’ll figure out if we want to keep these 2

300 00:26:43.270 00:26:47.080 Amber Lin: that we want to do and then

301 00:26:50.300 00:26:52.010 Amber Lin: initialize.

302 00:26:56.710 00:27:01.120 Amber Lin: Yeah, what? What do we need to do like overall good

303 00:27:01.670 00:27:06.190 Amber Lin: for the data team? Is it is it true that all we need is this.

304 00:27:06.310 00:27:09.880 Amber Lin: is this documentation like, what else do we need.

305 00:27:10.560 00:27:19.019 Miguel de Veyra: Yeah, yeah, from them. That’s the the guidelines we need to provide them. And then they have to give us basically the documentation that they’ve made based on those guidelines.

306 00:27:19.020 00:27:24.179 Amber Lin: Okay? And then after that, we kind of figure out we’re back to all our agent work right?

307 00:27:24.560 00:27:25.180 Miguel de Veyra: Yeah.

308 00:27:25.710 00:27:31.360 Amber Lin: Okay, sounds good. So I could say that we figure out pool parts in urban stems

309 00:27:31.720 00:27:34.010 Amber Lin: as as well. This week.

310 00:27:34.540 00:27:40.770 Miguel de Veyra: Yeah, yeah, definitely, those 2, though it’s gonna of course, use the the least. The lazy method of slack.

311 00:27:41.090 00:27:41.630 Amber Lin: Stop.

312 00:27:44.790 00:27:47.249 Amber Lin: So I could say, this is more like

313 00:27:48.150 00:27:54.439 Amber Lin: Thurs, Thursday, or something cause I can get luke to give us a list of questions for pool parts, too.

314 00:27:57.240 00:27:58.220 Amber Lin: Thursday.

315 00:28:01.390 00:28:04.410 Amber Lin: and get up to all agents

316 00:28:09.060 00:28:14.700 Amber Lin: notion. So I could scoot this a little bit you know what

317 00:28:15.050 00:28:20.759 Amber Lin: maybe like. Have a plan, or at least know how it gets done by Thursday, I would say.

318 00:28:27.000 00:28:29.519 Amber Lin: Okay, sounds good.

319 00:28:30.840 00:28:32.659 Amber Lin: I’ll check in tomorrow.

320 00:28:33.010 00:28:37.989 Amber Lin: I know you either, if you, if you do work today, I’ll just check in like

321 00:28:38.220 00:28:43.589 Amber Lin: early tomorrow to mark your end of day, or just, we’ll talk and we’ll talk in slack.

322 00:28:43.850 00:28:48.870 Amber Lin: And then for ABC,

323 00:28:49.360 00:29:06.830 Amber Lin: I’ll record like a video or something of what what we talked about for Scott. I think it applies to also our work for the data team as well as more of a knowledge base management, like having different schemas for

324 00:29:07.150 00:29:12.549 Amber Lin: the documents. So I’ll like, I’ll digest it, and I’ll send it to you guys.

325 00:29:21.130 00:29:21.980 Amber Lin: Okay?

326 00:29:22.510 00:29:29.730 Amber Lin: Oh, Hi, wish since you’re here, question question on the Github sources.

327 00:29:30.500 00:29:31.689 Amber Lin: do we have to figure out.

328 00:29:31.690 00:29:40.180 Awaish Kumar: To make. We? We have all the sources in the get up like which were requested yesterday.

329 00:29:40.310 00:29:45.530 Awaish Kumar: Javi. It didn’t metamor, and the I’m gonna stand.

330 00:29:46.610 00:29:49.440 Amber Lin: Oh, awesome! So I can say that this is.

331 00:29:50.050 00:29:52.329 Awaish Kumar: This is, this is done right?

332 00:29:56.120 00:30:06.260 Amber Lin: Awesome. Miguel. Do you know where to go? Access these like, where is all of those data stored like, how can Miguel go access that.

333 00:30:08.170 00:30:10.120 Awaish Kumar: I have shared the link with Miguel.

334 00:30:10.120 00:30:11.970 Miguel de Veyra: Yeah. Yeah. He sent it to me already.

335 00:30:12.210 00:30:14.470 Amber Lin: Awesome. So

336 00:30:16.040 00:30:22.549 Amber Lin: I can scoot that a bit earlier, because I feel like we need the github to answer the people’s questions.

337 00:30:30.970 00:30:34.190 Amber Lin: What you think, Miguel, what do you think.

338 00:30:34.190 00:30:36.399 Miguel de Veyra: Oh, so sorry! What again! My bad.

339 00:30:36.922 00:30:44.110 Amber Lin: Can we move? Do you think we need the Github added to all Asians a bit earlier, or at least like added to.

340 00:30:44.500 00:30:47.599 Miguel de Veyra: No, we have to watch stuff for today and tomorrow.

341 00:30:49.850 00:30:52.300 Amber Lin: Okay, is.

342 00:30:52.300 00:30:53.779 Miguel de Veyra: Well, yeah, I think Thursday, is there?

343 00:30:54.330 00:30:54.880 Amber Lin: Right.

344 00:30:55.080 00:30:55.909 Miguel de Veyra: Sorry, what.

345 00:30:56.170 00:30:58.399 Amber Lin: Like Javi has Github right.

346 00:30:58.400 00:30:59.370 Miguel de Veyra: Yeah. Yeah. Yeah. Via script.

347 00:30:59.370 00:31:04.736 Amber Lin: Okay. Okay, then it’s fine. Then we have something to test. Alrighty sounds good.

348 00:31:06.240 00:31:09.890 Amber Lin: okay, thank you all for the meeting. I’ll let you know about the ABC stuff.

349 00:31:10.660 00:31:11.910 Miguel de Veyra: Okay. Thanks. Everyone.

350 00:31:11.910 00:31:13.350 Amber Lin: Okay. Bye-bye.

351 00:31:14.110 00:31:14.860 Casie Aviles: Thank you.