Meeting Title: AI Team | Planning - Retro Date: 2025-05-02 Meeting participants: Amber Lin, Miguel De Veyra, Casie Aviles, Awaish Kumar


WEBVTT

1 00:03:20.670 00:03:22.220 Amber Lin: 19.

2 00:03:26.330 00:03:26.990 Casie Aviles: Hello!

3 00:03:27.830 00:03:37.580 Amber Lin: Hi. So today, kinda wanna do a quick retro of the past 2 weeks and

4 00:03:38.642 00:03:48.600 Amber Lin: next Monday, we’ll go figure out, okay, what next steps. We need to do so. Let me make a fake jam for us.

5 00:03:48.970 00:03:49.670 Miguel de Veyra: Hey, everyone.

6 00:03:50.370 00:04:14.630 Amber Lin: Hello! I was saying that we could do a bit of a retro for the past 2 weeks, because I think we made a lot of significant progress. And I want us to also reflect on what went well and what could be done better. And then next Monday we’ll kind of go over. Okay, what is, what is our next steps? And what do we want to do for the next sprint?

7 00:04:14.920 00:04:22.879 Amber Lin: And I’m going to create a fake jam for us and and go from there.

8 00:04:25.695 00:04:26.710 Amber Lin: Any.

9 00:04:27.010 00:04:32.480 Amber Lin: So while I’m doing that, any updates from.

10 00:04:33.335 00:04:35.109 Miguel de Veyra: Yeah, I could share my screen.

11 00:04:36.560 00:04:37.479 Awaish Kumar: Let me!

12 00:04:37.480 00:04:38.350 Miguel de Veyra: And.

13 00:04:41.680 00:04:42.180 Awaish Kumar: Okay.

14 00:04:42.180 00:04:46.549 Miguel de Veyra: Can can everyone. This is so bright. Okay, can everyone see the screen.

15 00:04:48.060 00:04:50.790 Casie Aviles: Yeah, I can’t see it.

16 00:04:51.260 00:04:57.389 Miguel de Veyra: Okay, yeah. Okay. So basically, I’ve been able to, you know, do

17 00:04:57.880 00:05:02.760 Miguel de Veyra: Eden and Yavi only. But, as you can see, like, this is all the records.

18 00:05:10.040 00:05:16.000 Miguel de Veyra: Okay? And then it’s, I also added, like, this date, the metadata is also here. The

19 00:05:17.020 00:05:19.590 Miguel de Veyra: it’s basically just this one. If I’m being honest.

20 00:05:22.710 00:05:30.429 Miguel de Veyra: Yeah. So Eden and Yavi, I’ve able. I’ve been able to basically put every message into

21 00:05:30.540 00:05:34.739 Miguel de Veyra: super base. And then I can all already use that as

22 00:05:37.350 00:05:40.509 Miguel de Veyra: right here, I can already use this as

23 00:05:42.120 00:05:47.679 Miguel de Veyra: context in super base. But the way I do this is just the past 30 days. That’s what the

24 00:05:48.380 00:05:50.680 Miguel de Veyra: what do you call this? That’s what the

25 00:05:52.270 00:05:56.930 Miguel de Veyra: date field is for, I guess for this one it’s Ds that we’re using

26 00:05:57.530 00:06:00.020 Miguel de Veyra: cause I doubt past 30 days.

27 00:06:00.170 00:06:07.970 Miguel de Veyra: It’s really that important. But I guess we could just have this as an AI step eventually, if you want to. You know the entire school.

28 00:06:08.871 00:06:19.140 Miguel de Veyra: But yeah, I I just need. I guess some help here, because for whatever reason, when I was testing it out in slack, it’s not calling the tool, whatever I do.

29 00:06:19.280 00:06:23.270 Miguel de Veyra: I was working on it yesterday. But yeah, that’s pretty much

30 00:06:23.550 00:06:30.570 Miguel de Veyra: the update here. And then I wanna basically integrate this sort of schedule trigger

31 00:06:30.770 00:06:35.140 Miguel de Veyra: which I’m gonna speak with Casey or know how to do.

32 00:06:35.540 00:06:37.640 Miguel de Veyra: But yeah.

33 00:06:38.050 00:06:51.629 Miguel de Veyra: basically, that’s it. The only different thing that Casey, I think we did here is that I I had to run this. Where is it? Basically, I had this code that just uploads to

34 00:06:53.090 00:06:54.780 Miguel de Veyra: that uploads it. To

35 00:06:56.270 00:07:08.399 Miguel de Veyra: what do you call this 2 super base? Yeah, but I don’t think this is. It’s because the the file. This, too, is like 4 MB. And 5 MB. Which is pretty big, but I don’t think we need that. If we’re gonna do this daily

36 00:07:08.510 00:07:09.330 Miguel de Veyra: right.

37 00:07:11.730 00:07:17.950 Awaish Kumar: Can I? Yeah. So if if you can share, make the super base.

38 00:07:18.090 00:07:21.699 Awaish Kumar: So the service data, if you open that page.

39 00:07:21.900 00:07:22.980 Miguel de Veyra: This one.

40 00:07:24.850 00:07:25.640 Awaish Kumar: Yeah.

41 00:07:25.800 00:07:28.179 Awaish Kumar: Can can you open that tab?

42 00:07:29.310 00:07:30.129 Miguel de Veyra: Which tab sorry.

43 00:07:30.130 00:07:30.890 Casie Aviles: Super, base.

44 00:07:30.890 00:07:34.450 Awaish Kumar: So the Supervis not entertain the supervis.

45 00:07:34.800 00:07:36.449 Miguel de Veyra: But am I not in super base.

46 00:07:36.820 00:07:37.439 Amber Lin: And this is.

47 00:07:37.440 00:07:39.259 Awaish Kumar: We are seeing the annot and flow.

48 00:07:40.020 00:07:40.940 Amber Lin: No, it’s continue.

49 00:07:40.940 00:07:42.460 Amber Lin: I can see the super base.

50 00:07:42.460 00:07:48.140 Awaish Kumar: Okay, now I can. So if we go to the project slack messages.

51 00:07:48.140 00:07:48.740 Miguel de Veyra: Yeah.

52 00:07:52.860 00:07:55.860 Awaish Kumar: And this way, yeah, I was confused on which to you. So I just.

53 00:07:56.180 00:07:57.020 Miguel de Veyra: I shouldn’t.

54 00:07:57.020 00:07:59.859 Awaish Kumar: No, no, I’m just saying, can you switch the project?

55 00:08:00.100 00:08:03.250 Awaish Kumar: I have created a new project. Slack messages.

56 00:08:04.210 00:08:06.989 Miguel de Veyra: You want me to move this into this, or do I? Is it.

57 00:08:07.910 00:08:10.560 Awaish Kumar: I’m just saying you to open the.

58 00:08:10.690 00:08:11.400 Miguel de Veyra: No.

59 00:08:11.400 00:08:12.980 Miguel de Veyra: Messages. Okay. Okay.

60 00:08:14.080 00:08:14.950 Miguel de Veyra: Okay. Okay.

61 00:08:16.350 00:08:17.150 Awaish Kumar: No.

62 00:08:22.980 00:08:25.460 Awaish Kumar: yeah. So I have created these 2 tables.

63 00:08:28.140 00:08:31.349 Awaish Kumar: Basically, they don’t show you the data.

64 00:08:37.419 00:08:39.470 Amber Lin: I wish. Do you want to share screen.

65 00:08:41.740 00:08:55.890 Awaish Kumar: So right? Okay, let me see that. But yeah, what I was saying, trying to say that I’ve created a pipeline in texture which runs daily, and it is going to get all the messages from slack and put it in this table.

66 00:08:56.250 00:09:00.020 Awaish Kumar: If you’re okay with the schema, I will look and see why they are empty.

67 00:09:01.270 00:09:02.725 Miguel de Veyra: Okay. Yeah. Sure.

68 00:09:05.000 00:09:07.459 Amber Lin: Oh, so we don’t run it through S. 3.

69 00:09:08.000 00:09:12.969 Awaish Kumar: So now it it does run so slack messages go to S. 3

70 00:09:13.970 00:09:25.760 Awaish Kumar: from s. 3 they go to the super base, but, as I mentioned previously, we have been doing using any 10. It was taking a lot of time. So I created a python script, basically.

71 00:09:26.230 00:09:31.579 Awaish Kumar: which which transforms these files into client client based folders

72 00:09:32.311 00:09:37.429 Awaish Kumar: and then finally stores them here in the suburban streets, man.

73 00:09:39.110 00:09:45.439 Awaish Kumar: So directly from python script, we we don’t have a Internet flow in between as well.

74 00:09:46.440 00:09:49.399 Casie Aviles: Okay, so that’s on Dogster. Right?

75 00:09:50.140 00:09:56.540 Awaish Kumar: Yeah, flow is running on Dexter. But you will see the data here, and you will also

76 00:09:57.291 00:10:04.229 Awaish Kumar: in. Aw, if I’m also storing the transform data in S. 3. If you in internally, I bucket. If we go to the

77 00:10:04.530 00:10:07.109 Awaish Kumar: slack slack messages it will.

78 00:10:07.388 00:10:08.500 Casie Aviles: It’s in S 3.

79 00:10:08.710 00:10:11.330 Casie Aviles: Yeah, I did see it always. Yeah, I did see it today.

80 00:10:11.330 00:10:13.739 Awaish Kumar: This is like messages transformed. Then yes.

81 00:10:13.740 00:10:14.420 Casie Aviles: Transform.

82 00:10:14.420 00:10:16.069 Awaish Kumar: That’s 1 of the files as well.

83 00:10:16.380 00:10:18.060 Amber Lin: Hmm awesome.

84 00:10:18.400 00:10:23.890 Awaish Kumar: So there are transform files, and the data is going to be loaded here directly without editing

85 00:10:26.170 00:10:40.540 Awaish Kumar: and it is running. The flow is running. But I I don’t see the data here. I have to debug that part. But yeah, but it will bring in all the data. All the slack messages and the usernames

86 00:10:41.300 00:10:44.149 Awaish Kumar: channel ids everywhere. Everything for that client.

87 00:10:44.470 00:11:06.240 Amber Lin: That’s great. How is my question is, how have we? I guess today, once we figure out this data, we also wanna see if it works with our agents right? Cause we wanna just call the slack part done if we can make sure that it works with the agent workflows.

88 00:11:07.520 00:11:15.410 Amber Lin: and I know, Miguel, you already have the workflow. I guess we just plug what awaii did into the super base source.

89 00:11:16.010 00:11:16.700 Amber Lin: It’s.

90 00:11:16.700 00:11:21.959 Miguel de Veyra: Oh, honestly, I’m not sure if we still need

91 00:11:22.090 00:11:26.210 Miguel de Veyra: to get from S. 3, because basically, it’s just the same source.

92 00:11:26.600 00:11:27.300 Amber Lin: Oh!

93 00:11:27.520 00:11:28.454 Miguel de Veyra: Right.

94 00:11:29.840 00:11:37.159 Miguel de Veyra: the dates here, everything. And then we’re technically just getting from one or 2 channels, anyways, so we can just add it here.

95 00:11:37.560 00:11:39.209 Awaish Kumar: I’m not sure. What do you guys think.

96 00:11:40.268 00:11:44.670 Amber Lin: I know the reason why we want S. 3 is to have a single source of truth.

97 00:11:44.670 00:11:47.439 Miguel de Veyra: No, we can still get. Send it to S. 3, but.

98 00:11:47.440 00:11:48.079 Amber Lin: Oh, okay.

99 00:11:48.080 00:11:50.940 Miguel de Veyra: We don’t necessarily have to get it from there. Because.

100 00:11:51.150 00:11:55.210 Miguel de Veyra: yeah, if I depended on the S. 3, integration would help nothing today.

101 00:11:55.880 00:11:56.560 Amber Lin: Okay.

102 00:11:57.310 00:11:58.520 Miguel de Veyra: So I was thinking.

103 00:11:58.520 00:12:03.899 Awaish Kumar: So you are using Elliton connectors directly slack connectors correctly.

104 00:12:05.058 00:12:06.649 Miguel de Veyra: You wanna see the way I did it.

105 00:12:07.470 00:12:17.700 Awaish Kumar: I’m I’m just asking like, are you using anten slack connectors to get the slack messages right? You’re not meeting. Okay.

106 00:12:20.860 00:12:28.420 Awaish Kumar: Yeah, why we wanted the other. Why we chose. The other process was to streamline all the ways like, if you can

107 00:12:28.630 00:12:37.160 Awaish Kumar: can like, and I’m not sure if N. At N. Can be used for all everything like

108 00:12:37.260 00:12:40.209 Awaish Kumar: can. Can it work for Github and everything.

109 00:12:41.340 00:12:49.749 Miguel de Veyra: For Github, it’s a lot more simpler because we have that. What do you call it? Github? What do you call it? Casey the github something, the one

110 00:12:51.590 00:12:55.490 Miguel de Veyra: repo mix. Yeah. So we we need basically, we just need to get the.

111 00:12:55.620 00:13:06.340 Miguel de Veyra: we just need to get the repo mix file and then just throw that to the agent and then throw it to get to S. 3. So I would assume that’s a lot simpler, right? So I don’t. I don’t really want to worry about the

112 00:13:06.550 00:13:07.940 Miguel de Veyra: Github anymore.

113 00:13:09.220 00:13:11.790 Miguel de Veyra: We I do have in S. 3. I have.

114 00:13:11.970 00:13:15.199 Awaish Kumar: Already have this like, git full git, update as well.

115 00:13:15.630 00:13:22.369 Awaish Kumar: So if you go into the internal AI bucket, you go to the Github and the Eden Javi both have

116 00:13:22.600 00:13:25.110 Awaish Kumar: the and fine.

117 00:13:25.350 00:13:32.490 Awaish Kumar: So Github data is also there from there. So I just wanted to understand. Like right now we are maintaining 2 different flows.

118 00:13:32.690 00:13:36.440 Awaish Kumar: I’m maintaining one. And you guys are also maintaining one.

119 00:13:36.810 00:13:45.050 Awaish Kumar: We would just want to make a decision to use the one flow, if possible.

120 00:13:45.560 00:13:48.910 Miguel de Veyra: Oh, yeah, I mean we should. We should probably use whatever whatever’s working.

121 00:13:49.830 00:13:57.170 Amber Lin: Can you guys meet after this meeting to like figure out which one we’re gonna use.

122 00:13:57.410 00:13:58.800 Miguel de Veyra: Okay, yeah, yeah, sure, sure.

123 00:13:58.800 00:14:08.380 Amber Lin: Yeah, yeah, cool. So essentially, I just want to know how how far or how close we are to

124 00:14:08.550 00:14:12.320 Amber Lin: making sure that slack the slack part works.

125 00:14:12.940 00:14:28.680 Amber Lin: So that’s essentially that’s the update. I think me and Uton wants to hear of just everything’s going great. We’re just lacking the last mile or just pushing that through for today, and we can call the slack part done. And that’s great.

126 00:14:28.680 00:14:29.870 Miguel de Veyra: Yeah, that makes sense.

127 00:14:30.300 00:14:35.050 Miguel de Veyra: Honestly, the slack part. I just need to convene with Casey, because.

128 00:14:35.180 00:14:38.579 Miguel de Veyra: no matter what I did, mate, I couldn’t get it to call the agent.

129 00:14:40.240 00:14:40.990 Miguel de Veyra: I don’t know.

130 00:14:40.990 00:14:41.370 Miguel de Veyra: Fine.

131 00:14:41.370 00:14:46.319 Casie Aviles: Yeah, there’s like a problem with tool calling. I’ve noticed that as well. So

132 00:14:46.490 00:14:49.469 Casie Aviles: yeah, I mean, we could investigate further. Why.

133 00:14:49.470 00:15:02.820 Miguel de Veyra: Yeah, yeah, let’s prioritize this over, whatever whatever else? Because, as because I talked to them, I think 2 days ago before the holiday, we need to get things. As you know, we we can’t be bombarded by another

134 00:15:03.200 00:15:05.790 Miguel de Veyra: infrastructure problem. We need to get something out.

135 00:15:06.030 00:15:14.669 Miguel de Veyra: So as long as we get this. This is already connected to Eden and Yavi and slack. I just need this to to work, basically

136 00:15:14.910 00:15:19.780 Miguel de Veyra: because this is already working. It’s up to date, and then I’m assuming for this one

137 00:15:20.050 00:15:23.400 Miguel de Veyra: I can just schedule, and then just add it to super base.

138 00:15:23.710 00:15:27.070 Miguel de Veyra: so we can just track it all here so that should be pretty fast.

139 00:15:27.070 00:15:31.240 Miguel de Veyra: Okay, I’ll let you guys need to figure that out.

140 00:15:31.240 00:15:33.089 Miguel de Veyra: Probably do the retro.

141 00:15:33.590 00:15:36.479 Amber Lin: Yeah, I’ll do the retro. So

142 00:15:36.790 00:15:40.110 Amber Lin: I’ll send the link to you guys.

143 00:15:46.200 00:15:53.929 Amber Lin: We sent it in our Zoom chat and also in our slack channel if we need

144 00:16:03.880 00:16:20.377 Amber Lin: yay, okay, so let’s start on the furthest left of step one add tickets and categories. So essentially, what went well and what problems do we face for the past 2 weeks, you know, last week was helping us

145 00:16:21.220 00:16:25.069 Amber Lin: for like Monday to Wednesday, and then

146 00:16:25.740 00:16:33.330 Amber Lin: What do we? What do we do like? What? What went really well, and even like what was.

147 00:16:34.000 00:16:35.750 Amber Lin: what do we?

148 00:16:36.561 00:16:47.160 Amber Lin: Didn’t do well before, but then we did. Well, this sprint. So I’m gonna start like a quick 4 min timer, and we’ll just put down our ideas in the sticky notes.

149 00:16:47.500 00:16:49.489 Amber Lin: Can everybody access this.

150 00:16:51.150 00:16:52.640 Casie Aviles: Yes, I’m there.

151 00:16:53.280 00:16:54.830 Amber Lin: Okay, awesome.

152 00:16:58.340 00:17:01.010 Amber Lin: I wish, are you able to access it?

153 00:17:02.090 00:17:03.700 Miguel de Veyra: Oh, it’s all internal.

154 00:17:14.060 00:17:15.350 Casie Aviles: I think, Oasius on me.

155 00:17:15.359 00:17:17.229 Awaish Kumar: I have requested access.

156 00:17:17.640 00:17:21.980 Amber Lin: Hi, yeah, let me let me edit.

157 00:17:23.010 00:17:23.829 Amber Lin: Hmm!

158 00:17:38.560 00:17:41.490 Amber Lin: I’m gonna start the 4 min timer and then we’ll

159 00:17:41.680 00:17:49.140 Amber Lin: we’ll add things to the very left of step, one so green and purple box.

160 00:18:06.480 00:18:08.109 Miguel de Veyra: Sorry the timer has started right.

161 00:18:08.540 00:18:09.210 Amber Lin: Yeah.

162 00:18:09.850 00:18:14.010 Miguel de Veyra: Okay, 4, 2012.

163 00:21:26.410 00:21:27.130 Miguel de Veyra: Hmm.

164 00:21:44.390 00:21:47.389 Amber Lin: Do we need more time on the problems we faced.

165 00:21:56.690 00:21:58.470 Miguel de Veyra: Oh, yeah, probably like a minute or 2.

166 00:21:59.010 00:22:01.459 Amber Lin: Okay. I’ll do another.

167 00:22:01.660 00:22:03.270 Casie Aviles: Yeah, one more minute, I guess.

168 00:22:03.820 00:22:08.410 Amber Lin: Okay.

169 00:23:25.130 00:23:25.970 Miguel de Veyra: Thinker.

170 00:23:51.020 00:23:56.949 Miguel de Veyra: What sorry guys? Just a quick question. What’s the name of the repo for Eden? It’s not just Eden right.

171 00:24:03.000 00:24:04.250 Awaish Kumar: In the Github.

172 00:24:04.250 00:24:05.239 Miguel de Veyra: Yeah, yeah, yeah.

173 00:24:05.690 00:24:08.520 Awaish Kumar: It’s in the Analytics project. It’s not in the.

174 00:24:09.030 00:24:12.229 Miguel de Veyra: Oh, no, it’s not in Rainforge. Okay, I need access to that.

175 00:24:12.910 00:24:13.570 Awaish Kumar: But.

176 00:24:16.680 00:24:31.690 Amber Lin: Okay, so I’m gonna do another 2 min timer. And do you see? At the bottom there’s a white bar right? And there’s 1 that says stamps, or if you click E on your keyboard, you can have stamps so.

177 00:24:31.690 00:24:32.450 Miguel de Veyra: Oh, okay. Yeah.

178 00:24:32.660 00:24:39.920 Amber Lin: You can add a plus one stamp to the things that you agree on, and then, after 2 min, we’ll discuss.

179 00:25:33.700 00:25:34.900 Miguel de Veyra: Okay. I think I’m done.

180 00:25:38.730 00:25:43.180 Amber Lin: Go look at the problems we faced. Give me a sec.

181 00:26:45.780 00:26:49.269 Amber Lin: So it seems like.

182 00:26:49.440 00:26:50.980 Miguel de Veyra: I’ll clean this up a bit.

183 00:26:55.240 00:27:00.640 Amber Lin: Okay, so what went? Well, it seems like we all agree that.

184 00:27:02.330 00:27:06.840 Amber Lin: This this sprint we had really good communication.

185 00:27:07.540 00:27:15.769 Amber Lin: And so let me let me copy that here

186 00:27:20.120 00:27:26.099 Amber Lin: good communication seems like we also agree that we shipped.

187 00:27:26.930 00:27:32.590 Amber Lin: shipped it oh, shipped a lot of things, and

188 00:27:33.170 00:27:43.189 Amber Lin: we essentially have really good progress on different things, and we also agree that.

189 00:27:45.222 00:27:47.340 Amber Lin: I wish it was very helpful.

190 00:27:52.860 00:27:54.300 Amber Lin: And

191 00:27:58.220 00:27:59.650 Amber Lin: let’s see.

192 00:28:07.260 00:28:13.419 Amber Lin: great fantastic. And then what problems do we face?

193 00:28:13.840 00:28:17.520 Amber Lin: And I think we agree that

194 00:28:18.080 00:28:20.790 Amber Lin: it was a bit hard to keep

195 00:28:21.900 00:28:24.840 Amber Lin: hard to keep the momentum. Sometimes.

196 00:28:27.930 00:28:38.640 Amber Lin: We spend a lot of time choosing platforms and very

197 00:28:38.820 00:28:48.310 Amber Lin: deep in technicalities, was kind of like similar with not shipping first, st and

198 00:28:50.660 00:28:56.029 Amber Lin: and then I guess we also always pointed out that we ended up kind of working on the same thing.

199 00:28:56.750 00:29:05.890 Amber Lin: So those are the main things that we agreed on and like.

200 00:29:06.300 00:29:12.549 Amber Lin: why don’t we? Why don’t discuss for the ones we’re doing. Well, how can we keep that up?

201 00:29:13.338 00:29:16.510 Amber Lin: And for the ones that we

202 00:29:16.840 00:29:22.379 Amber Lin: did didn’t do as well like, how do we improve on that.

203 00:29:23.630 00:29:31.870 Amber Lin: So let’s start by like what was helpful in communication.

204 00:29:35.930 00:29:39.909 Casie Aviles: Yeah. So since I put it there, oh, wait. Sorry.

205 00:29:40.750 00:29:50.590 Amber Lin: Yeah, I’m gonna just type things here. I here’s some available stickies and okay?

206 00:29:50.870 00:29:52.720 Amber Lin: And and

207 00:29:57.880 00:30:07.130 Amber Lin: so what made that go? Well, like, what what do we mean, or how did we?

208 00:30:07.970 00:30:09.450 Amber Lin: How do we?

209 00:30:55.680 00:31:00.530 Amber Lin: I’ll take, and we can.

210 00:31:02.450 00:31:06.260 Amber Lin: Great! I’ll set 2 min, and then we can talk about it.

211 00:32:19.550 00:32:20.650 Miguel de Veyra: 50 log, but.

212 00:33:10.210 00:33:11.230 Amber Lin: Great

213 00:33:13.050 00:33:18.270 Amber Lin: I’ll each. I’ll let Christian talk about their their little stickies.

214 00:33:18.710 00:33:22.210 Amber Lin: So Casey, we’ll start with you.

215 00:33:23.975 00:33:26.110 Casie Aviles: Yeah, sure. So I wrote here that

216 00:33:27.490 00:33:31.699 Casie Aviles: so basically, when Otam also provided his feedback for me.

217 00:33:32.810 00:33:37.169 Casie Aviles: we agreed that we should I should be, you know, signaling blockers early.

218 00:33:38.370 00:33:42.409 Casie Aviles: That’s 1 of the problems that we encountered last

219 00:33:42.810 00:33:54.769 Casie Aviles: for the past few weeks, where I was just, I guess, deep in the work, but it was really, you know, it wasn’t clear whether there wasn’t any progress, and, like the work, seemed to go on forever. So

220 00:33:55.020 00:34:01.470 Casie Aviles: I guess, being able to signal that I can’t do something like if it’s taking more time than I,

221 00:34:01.700 00:34:07.329 Casie Aviles: then it should be. Then I guess it’s you know it’s good to signal the blockers early and just ask for help.

222 00:34:07.620 00:34:08.219 Amber Lin: Thank you.

223 00:34:08.900 00:34:13.880 Casie Aviles: So. Yeah, I guess that’s 1 thing that I think has improved with

224 00:34:14.270 00:34:18.209 Casie Aviles: how I communicate. Additionally, I think the

225 00:34:18.877 00:34:22.272 Casie Aviles: eod threads that you send amber are also helpful.

226 00:34:22.820 00:34:25.349 Casie Aviles: it lets it lets me, you know, just drop

227 00:34:25.540 00:34:32.059 Casie Aviles: what I’ve worked on so far, and it’s good that also showing transparency on where we are at.

228 00:34:32.429 00:34:39.099 Casie Aviles: So I think, yeah, that’s that’s really good. I mean, I don’t mind if it’s frequent, it’s fine, because you know, just

229 00:34:39.320 00:34:41.770 Casie Aviles: so people could know like where we are at.

230 00:34:42.350 00:34:45.360 Amber Lin: Yeah, awesome. I’ll keep doing that.

231 00:34:46.760 00:34:49.880 Amber Lin: Miguel was from you.

232 00:34:50.989 00:34:57.529 Miguel de Veyra: Yeah, I mean, I basically had like 3 or 4 1 once we do them this week. Some of it are with Casey.

233 00:34:57.719 00:35:01.199 Miguel de Veyra: But yeah, basically, the gist of it is that you know.

234 00:35:02.249 00:35:06.659 Miguel de Veyra: Cause remember the dlt stuff we got stuck there for a very, very long time.

235 00:35:06.660 00:35:07.740 Amber Lin: Yeah.

236 00:35:07.740 00:35:11.979 Miguel de Veyra: And then, basically, my conversation with him was like, you know.

237 00:35:12.390 00:35:15.470 Miguel de Veyra: he suggested it. We don’t actually have to do it.

238 00:35:16.700 00:35:21.360 Miguel de Veyra: And it was very different from what me and Casey initially thought that, hey, this is what.

239 00:35:21.360 00:35:22.010 Amber Lin: We do?

240 00:35:22.530 00:35:25.619 Miguel de Veyra: And then, basically, we discussed that, hey.

241 00:35:25.890 00:35:34.509 Miguel de Veyra: you know, it’s still up to me on what we need or what we get, what we have to use basically to achieve whatever we need.

242 00:35:35.210 00:35:35.680 Amber Lin: Hey!

243 00:35:35.680 00:35:37.709 Miguel de Veyra: Because we can’t be stuck on, you know.

244 00:35:38.040 00:35:47.000 Miguel de Veyra: like, for example, we needed to initialize the I mean, just the real world example, I guess is we needed to initialize 2 clients right?

245 00:35:48.050 00:35:52.830 Miguel de Veyra: And then, yeah, basically, we’ve just thought, find a way to do

246 00:35:53.190 00:36:04.579 Miguel de Veyra: to get slack data into to the bottom. We did it. So if I waited, we probably still won’t have stuff to do. But yeah, basically, action first, st you know, we can always replan later.

247 00:36:06.090 00:36:13.119 Miguel de Veyra: But yeah, that’s basically what we’re doing. And also I have to speak with with them almost every day now, because we haven’t been really speaking

248 00:36:14.080 00:36:16.000 Miguel de Veyra: great, very, very helpful.

249 00:36:17.330 00:36:22.460 Amber Lin: So let’s see, that would be like, Oh.

250 00:36:26.660 00:36:28.170 Amber Lin: speaking

251 00:36:33.020 00:36:34.080 Amber Lin: okay.

252 00:36:35.210 00:36:42.810 Amber Lin: And what about the letting go of what can’t be.

253 00:36:42.990 00:36:45.770 Miguel de Veyra: Yeah, this is basically just you know

254 00:36:46.680 00:36:49.569 Miguel de Veyra: them like, Hey, it’s probably not the best

255 00:36:49.820 00:36:58.220 Miguel de Veyra: way for me and Casey to work on Dlt on stuff like that, basically anything from source to S. 3.

256 00:36:58.420 00:37:03.560 Miguel de Veyra: Or, you know, if you want to use that to do that, I told you that we’ll leave that to.

257 00:37:04.190 00:37:10.380 Miguel de Veyra: Basically, it’s non agent work. Right? We can. We can still use S. 3. But we don’t necessarily have to depend on that.

258 00:37:10.930 00:37:11.670 Amber Lin: So.

259 00:37:11.930 00:37:13.759 Casie Aviles: Basically moving data around.

260 00:37:14.040 00:37:14.849 Miguel de Veyra: Yeah, yeah.

261 00:37:17.780 00:37:23.229 Casie Aviles: And that’s also, I guess, partly related to, you know. Push back. So

262 00:37:23.460 00:37:26.150 Casie Aviles: I guess Utam expects us to also push back

263 00:37:27.690 00:37:30.579 Casie Aviles: when something is not working, or, you know.

264 00:37:31.130 00:37:33.859 Casie Aviles: be able to justify it. So.

265 00:37:35.000 00:37:38.859 Amber Lin: I mean, he even told you don’t even need to justify it. If it’s not working, it’s not working.

266 00:37:39.010 00:37:40.730 Miguel de Veyra: You need something that works.

267 00:37:42.970 00:37:54.700 Amber Lin: So that would be, let’s say, if something, if something doesn’t work

268 00:37:55.840 00:38:00.119 Amber Lin: it’s okay to just say, so.

269 00:38:00.260 00:38:01.520 Miguel de Veyra: Yeah, just move on.

270 00:38:01.780 00:38:04.860 Amber Lin: And just move on right.

271 00:38:05.940 00:38:16.419 Amber Lin: And now we’ll say like, and that kind of relates to getting help as well.

272 00:38:19.960 00:38:28.679 Miguel de Veyra: Yeah. And then I would say, I think another one sorry guys. But I think another thing is, yeah, I mean, I could. You know I needed help because the agent was not really.

273 00:38:29.520 00:38:34.110 Miguel de Veyra: But I think if you need help, don’t stop there. Just look at what else you can do.

274 00:38:36.260 00:38:40.369 Amber Lin: That’s true, and if you need help.

275 00:38:40.550 00:38:42.209 Miguel de Veyra: Don’t let blockers stop you.

276 00:38:44.650 00:38:45.340 Amber Lin: Well, that’s.

277 00:38:45.340 00:38:46.210 Miguel de Veyra: Operational.

278 00:38:55.000 00:38:59.860 Amber Lin: Fantastic, great! And a wish. What about

279 00:39:02.560 00:39:06.050 Amber Lin: What about your ticket? Sorry not ticket. You’re sticky.

280 00:39:07.170 00:39:08.410 Awaish Kumar: How are you

281 00:39:12.300 00:39:13.520 Awaish Kumar: at the end?

282 00:39:26.270 00:39:27.090 Awaish Kumar: Alright.

283 00:39:30.400 00:39:36.689 Awaish Kumar: where is that moved? Yeah. Okay. Yeah. It. It was really easy

284 00:39:36.880 00:39:46.985 Awaish Kumar: to access Greg and Cassie to get some information on how they are doing, what they are doing, what platforms are being used, and

285 00:39:47.720 00:39:53.580 Awaish Kumar: how to access them like things like that all the like. The 1st steps to get

286 00:39:53.820 00:39:56.749 Awaish Kumar: hands on all all these tools and

287 00:39:57.656 00:40:01.919 Awaish Kumar: and get get get information, and the and the knowledge

288 00:40:02.080 00:40:04.189 Awaish Kumar: from them. It was really helpful.

289 00:40:04.560 00:40:07.459 Awaish Kumar: So yeah, and that really helped me

290 00:40:07.630 00:40:13.249 Awaish Kumar: to build quickly on top of what was available.

291 00:40:14.140 00:40:24.399 Amber Lin: Fantastic. I think we have a really good team organ. Our team is all always really happy to help each other. I think that’s 1 of the reasons why we also should fast.

292 00:40:26.245 00:40:27.529 Amber Lin: Great.

293 00:40:27.640 00:40:35.609 Amber Lin: And let’s look at the next thing, because we did ship a lot of things this

294 00:40:36.285 00:40:41.759 Amber Lin: this past sprint. I’m gonna set 2 min, and we can just write down like

295 00:40:42.460 00:40:50.659 Amber Lin: what went well, I think it all kind of overlaps with with the last part. But there’s definitely some things we can learn from there.

296 00:40:51.064 00:40:54.410 Amber Lin: I’ll just also move the wood block that’s next to it.

297 00:40:54.580 00:40:58.030 Amber Lin: What slowed us down so we can.

298 00:40:58.710 00:41:00.070 Amber Lin: Oh, dang!

299 00:41:01.190 00:41:08.680 Amber Lin: Here, we can just figure those out. I’ll set like a 4 min timer. We’ll talk about

300 00:41:09.260 00:41:10.879 Amber Lin: the blue and purple.

301 00:41:20.100 00:41:22.909 Miguel de Veyra: Wait. Sorry. Which one are we working on the green one right shipped along.

302 00:41:23.214 00:41:29.000 Amber Lin: The green and the purple, if some of them just overlap so just put whatever is where.

303 00:43:42.480 00:43:43.350 Miguel de Veyra: One.

304 00:43:44.270 00:43:49.580 Miguel de Veyra: Why, okay, okay, come on.

305 00:44:51.670 00:44:55.339 Miguel de Veyra: Sorry while everyone’s working on it. And and then which Github

306 00:44:55.450 00:45:00.569 Miguel de Veyra: connection is valid, which credential? I I couldn’t seem to get any to work.

307 00:45:04.620 00:45:06.869 Casie Aviles: Have you tried the one I created.

308 00:45:07.200 00:45:09.410 Miguel de Veyra: The get. Kc. Github, General.

309 00:45:10.780 00:45:11.330 Casie Aviles: Yeah.

310 00:45:11.570 00:45:19.620 Miguel de Veyra: Okay, wait. Let me repository, or the owner doesn’t work right? You have to put in Brain Forge.

311 00:45:22.700 00:45:25.260 Casie Aviles: Oh, not oh, yeah.

312 00:45:27.320 00:45:28.779 Miguel de Veyra: Let’s try this out.

313 00:45:29.380 00:45:30.310 Miguel de Veyra: Expression.

314 00:45:31.570 00:45:32.600 Miguel de Veyra: My name!

315 00:45:44.420 00:45:46.010 Miguel de Veyra: Oh, there you go! You have the coffee.

316 00:47:01.230 00:47:03.040 Miguel de Veyra: What is this big ass thing?

317 00:47:03.900 00:47:06.549 Miguel de Veyra: Asking the uncomfortable questions.

318 00:47:13.060 00:47:13.830 Miguel de Veyra: Don’t.

319 00:47:34.861 00:47:37.590 Amber Lin: I’m also gonna paste in some of the

320 00:47:38.050 00:47:45.150 Amber Lin: when I was working on how to structure are link updates.

321 00:47:45.740 00:47:47.920 Amber Lin: I’m just gonna drop it in there.

322 00:47:53.490 00:47:55.480 Amber Lin: So you guys can look at it.

323 00:48:11.160 00:48:22.334 Amber Lin: Great. Let’s talk about. Let’s talk about these 2 parts. So why did why were we able to shift fast. I think.

324 00:48:23.260 00:48:25.960 Amber Lin: I’ll still let everybody share

325 00:48:26.170 00:48:30.649 Amber Lin: their tickets will start from you again, Casey, and then we’ll go the same order.

326 00:48:33.550 00:48:36.130 Casie Aviles: Okay, yeah. So for me, I just added.

327 00:48:36.660 00:48:42.049 Casie Aviles: Yeah, 2 sticky. So the 1st one is choosing to do something that we already know works.

328 00:48:42.290 00:48:42.700 Amber Lin: Hmm.

329 00:48:42.700 00:48:45.519 Casie Aviles: So I guess that’s 1 way to

330 00:48:46.574 00:48:52.859 Casie Aviles: move things faster, because then we would have clear estimations like, how far, how fast can we do this like.

331 00:48:53.210 00:48:59.710 Casie Aviles: how far is it until it’s completely done? So if we know something, if we

332 00:48:59.870 00:49:05.289 Casie Aviles: set the goal as something like the work is already clear to us how we want to do it.

333 00:49:06.073 00:49:08.496 Casie Aviles: Yeah, it’s going to be faster, of course.

334 00:49:09.310 00:49:10.939 Casie Aviles: but yeah, I guess the the

335 00:49:11.110 00:49:15.020 Casie Aviles: the opposite of that is the ambiguity. So if we don’t know something.

336 00:49:15.180 00:49:18.300 Casie Aviles: and that’s where things can start to, you know.

337 00:49:20.008 00:49:22.119 Amber Lin: Take a slower pace.

338 00:49:22.500 00:49:26.329 Casie Aviles: So the second part is just, you know, setting clear goals.

339 00:49:28.020 00:49:32.369 Casie Aviles: Yeah, for me. I think that that one day that we spent with Utam just

340 00:49:32.680 00:49:38.920 Casie Aviles: checking our fig. It was in Miro first, st and then we transferred to figma, and just

341 00:49:39.350 00:49:42.190 Casie Aviles: able to see that that was

342 00:49:42.740 00:49:52.970 Casie Aviles: good, because, you know, it allows I’m I’m more of a visual person. So that really helps me. Just see like, where are we? Where we? So instead of just looking at tickets and lists.

343 00:49:53.180 00:50:00.480 Casie Aviles: being able to see like that specific part in the architecture diagram is helps.

344 00:50:00.480 00:50:01.940 Amber Lin: Yeah, clarity.

345 00:50:01.940 00:50:08.309 Amber Lin: I totally agree. I work that way, too. And I I put inspired by that, I would say, Okay, I think

346 00:50:08.560 00:50:09.909 Amber Lin: it helps us

347 00:50:10.110 00:50:23.819 Amber Lin: feel like it’s not such a big task. And we’re that we’re doing things forever. I think it helps us also feel accomplished that we finish one of the tasks if we can break it down very clearly.

348 00:50:25.720 00:50:26.350 Casie Aviles: Yeah.

349 00:50:33.340 00:50:35.719 Amber Lin: Yeah. Okay. Miguel.

350 00:50:37.398 00:50:40.051 Miguel de Veyra: Sorry we’re at the Green one right?

351 00:50:40.430 00:50:41.090 Amber Lin: Yeah.

352 00:50:42.950 00:50:44.229 Miguel de Veyra: What did I write? Sorry?

353 00:50:46.430 00:50:48.940 Miguel de Veyra: Oh, yeah, yeah. Basically. Yep.

354 00:50:49.800 00:50:59.959 Miguel de Veyra: yeah. I mean, just do what works. I agree with Casey. And then just, you know, act first.st I mean, that’s what I did like right now. We have access to Github already, like the agent is 3 out of 4.

355 00:51:00.720 00:51:01.709 Amber Lin: So you know.

356 00:51:01.710 00:51:04.530 Miguel de Veyra: Just keep doing whatever works best.

357 00:51:04.690 00:51:15.430 Miguel de Veyra: Right? I mean, not best, but the fastest, because, like what we did in ABC, you know, just we have to get give the clients something 1st

358 00:51:16.190 00:51:19.840 Miguel de Veyra: before we try to optimize our solutions. Basically.

359 00:51:20.520 00:51:22.670 Miguel de Veyra: And sometimes the simplest, is the answer.

360 00:51:23.970 00:51:27.360 Amber Lin: Yeah, and.

361 00:51:27.760 00:51:29.579 Miguel de Veyra: Which I think those are the 2 things I wrote.

362 00:51:29.890 00:51:35.499 Amber Lin: Totally, and I my mine was just echoing your thoughts.

363 00:51:36.560 00:51:46.660 Amber Lin: It’s you know, first, st yeah, and a wish you said knowledge sharing.

364 00:51:46.920 00:51:49.079 Amber Lin: Can you talk a little bit more about that.

365 00:51:49.870 00:51:56.139 Awaish Kumar: Yeah, like in the team, like we are flexible

366 00:51:56.320 00:52:01.880 Awaish Kumar: to share the knowledge we are open to share the knowledge and flexible enough to

367 00:52:02.180 00:52:04.749 Awaish Kumar: to adopt to the new tools

368 00:52:04.920 00:52:08.110 Awaish Kumar: and ways of implementation, if if

369 00:52:08.370 00:52:12.220 Awaish Kumar: if needed, and it can make things better and faster.

370 00:52:19.650 00:52:20.640 Amber Lin: Awesome.

371 00:52:21.870 00:52:26.159 Amber Lin: Here, is it? Why don’t we start in the

372 00:52:28.051 00:52:31.060 Amber Lin: what made us a bit slower.

373 00:52:32.740 00:52:44.079 Casie Aviles: Yeah, okay, so I, I think, yeah, I only placed one sticky here, which is the difficulty and balancing trade off. So I guess, for this is just this might be mine personally. But

374 00:52:45.065 00:52:48.890 Casie Aviles: yeah, there’s I have this mental thinking where

375 00:52:49.260 00:52:56.949 Casie Aviles: you know. Sometimes we have to. There’s a lot of like ambiguity in terms of how we ought to do something.

376 00:52:57.420 00:53:03.960 Casie Aviles: and that can sometimes. You know, we might get get drowned in technicalities. So

377 00:53:04.540 00:53:06.430 Casie Aviles: what I’m trying to say is like.

378 00:53:06.690 00:53:07.100 Amber Lin: Oh!

379 00:53:07.100 00:53:11.339 Casie Aviles: I try to perfect something first, st and then that can

380 00:53:11.530 00:53:20.819 Casie Aviles: you know? Lead me into a rabbit hole instead of getting something that works first.st So that is, you know. That’s 1 of the main reasons why I think

381 00:53:21.050 00:53:23.440 Casie Aviles: my work would would slow down.

382 00:53:28.120 00:53:29.250 Amber Lin: Sounds great

383 00:53:32.960 00:53:33.640 Amber Lin: cool.

384 00:53:34.925 00:53:35.640 Amber Lin: Miguel.

385 00:53:37.832 00:53:39.400 Miguel de Veyra: Honestly, I think.

386 00:53:42.090 00:53:47.390 Miguel de Veyra: yeah, I mean, I agree with Casey. I think that part we see eye to eye. And then

387 00:53:47.990 00:53:54.860 Miguel de Veyra: and then, yeah, the technicalities. That’s why I don’t delve into that too much, because we are all technical people, anyways.

388 00:53:56.120 00:53:59.929 Miguel de Veyra: and then choosing the platforms. I agree with that also.

389 00:54:02.840 00:54:07.819 Miguel de Veyra: What slowed us down. I think this week, honestly, we were pretty fast last week.

390 00:54:08.710 00:54:10.660 Miguel de Veyra: Yeah, we were still up in the air.

391 00:54:10.760 00:54:15.819 Miguel de Veyra: So yeah, stopper. 1, 2. I agree with that. Yeah.

392 00:54:15.970 00:54:22.500 Miguel de Veyra: And then the other. The other things like, you know, I don’t know

393 00:54:22.710 00:54:26.060 Miguel de Veyra: I have. I’m out of ideas here. Sorry I’ve been working since 10 Am.

394 00:54:26.060 00:54:27.920 Amber Lin: That’s okay. That’s okay.

395 00:54:28.050 00:54:35.880 Amber Lin: That’s okay. what’s it? Stop going on?

396 00:55:00.330 00:55:09.920 Amber Lin: yeah. And I also just added, what exactly we need to do to get to the next one phase, which is kind of related to

397 00:55:10.190 00:55:12.180 Amber Lin: some visualizations.

398 00:55:14.153 00:55:18.790 Amber Lin: Anyways, I wish you also had something there as well.

399 00:55:19.160 00:55:20.780 Awaish Kumar: Oh, yeah. So it’s like.

400 00:55:20.950 00:55:32.060 Awaish Kumar: I wanted to have like more investigation tickets, like, for example, you want to have a new flow. Let’s investigate what is the best way to put it, and.

401 00:55:32.060 00:55:32.490 Amber Lin: No.

402 00:55:32.490 00:55:38.869 Awaish Kumar: What is the right way to do it? And what are the tools can we use, and which are available for us, or things like that.

403 00:55:39.010 00:55:41.149 Awaish Kumar: so that

404 00:55:41.780 00:55:49.580 Awaish Kumar: after the investigation is done we are clear on what needs to be done, how it can be achieved and how long it’s going to take.

405 00:55:51.820 00:55:53.609 Miguel de Veyra: So some sort of a spike.

406 00:55:54.630 00:55:56.249 Casie Aviles: Yes, exactly. That’s fine.

407 00:55:58.590 00:56:01.449 Miguel de Veyra: Then I think one thing we need to do with spikes is that

408 00:56:01.820 00:56:04.049 Miguel de Veyra: you know we have to be honest. If it didn’t

409 00:56:04.280 00:56:09.069 Miguel de Veyra: like, if it didn’t result into anything like we can’t have a 2 day, spike. I think.

410 00:56:11.900 00:56:12.450 Casie Aviles: Yeah.

411 00:56:13.590 00:56:18.150 Miguel de Veyra: Like, I would say Spike should probably half a day.

412 00:56:19.450 00:56:23.569 Miguel de Veyra: especially if it’s like a new tool we’re checking out. That’s probably

413 00:56:24.520 00:56:30.479 Miguel de Veyra: like cause. That’s the problem. Me and Casey have perpetual spike.

414 00:56:33.707 00:56:38.930 Amber Lin: No, for pets, fuel, spikes, and.

415 00:56:38.930 00:56:44.410 Casie Aviles: Yeah, I I agree that that can happen. And I guess we just need like, clear

416 00:56:44.890 00:56:52.299 Casie Aviles: outcomes for those kinds of tickets like like a tool recommendation, or, you know, something like that

417 00:56:53.640 00:56:55.029 Casie Aviles: have to clarify that.

418 00:56:56.230 00:56:59.849 Awaish Kumar: Like it’s in all kind of

419 00:57:00.080 00:57:04.218 Awaish Kumar: not just regarding tools like investigation, like.

420 00:57:05.020 00:57:09.040 Awaish Kumar: whenever we have a project, we go with planning.

421 00:57:09.980 00:57:15.950 Awaish Kumar: Sometimes you are not sure like this event can be solved.

422 00:57:16.130 00:57:16.910 Awaish Kumar: Yeah, correct.

423 00:57:16.910 00:57:26.050 Awaish Kumar: or or can be done so like investigation, that part as well. And while doing that we become more clear about

424 00:57:26.831 00:57:32.310 Awaish Kumar: the execution, time and everything. And then we can more accurately predict, like.

425 00:57:32.430 00:57:34.139 Awaish Kumar: how long it’s going to take.

426 00:57:45.970 00:57:46.850 Amber Lin: Right.

427 00:57:47.180 00:57:55.909 Amber Lin: I think we have a lot of realizations, and we’re pretty much at the hour mark. So I think

428 00:57:58.350 00:58:12.550 Amber Lin: I’ll just run through each person real, quick of what is something that we can do next sprint based on all of these fantastic learnings, like, what is something that you want to focus on and do better for the next sprint.

429 00:58:16.950 00:58:20.879 Amber Lin: Oh, whoever wants to go first, st if I don’t have to nominate.

430 00:58:21.230 00:58:22.120 Casie Aviles: Oh, sorry!

431 00:58:22.840 00:58:24.809 Miguel de Veyra: You have ABC. In 5 min. Now.

432 00:58:25.250 00:58:25.680 Amber Lin: Yes,

433 00:58:26.110 00:58:33.139 Miguel de Veyra: Okay, yeah, yeah, that makes sense. So I think I’ll I think I’ll speak for the team. Just let’s just focus on delivering

434 00:58:33.260 00:58:40.139 Miguel de Veyra: cause. You know, I basically started the initialization work, for I mean, I had cases blueprint for Yavi

435 00:58:40.290 00:58:56.809 Miguel de Veyra: and I just improved on that. And you know, basically, it took me 2 days to yeah, maybe one and a half day to get things working. That’s from that’s and that’s including the data transformation from source to context. Right? Just keep on

436 00:58:57.890 00:59:05.410 Miguel de Veyra: pumping out, you know, agents, and then just make sure, you know, to avoid perpetual spikes.

437 00:59:05.730 00:59:09.629 Miguel de Veyra: Don’t get stuck on something that you’re trying to make

438 00:59:09.770 00:59:15.630 Miguel de Veyra: work. Just keep working on it and make sure. And then and then remember utens words that you know

439 00:59:15.780 00:59:19.240 Miguel de Veyra: we need something out there so they can test.

440 00:59:19.340 00:59:20.770 Miguel de Veyra: Treat them like ABC.

441 00:59:21.590 00:59:25.830 Amber Lin: Hmm Casey.

442 00:59:26.780 00:59:32.929 Casie Aviles: Yeah, I mean, yeah, pretty much every I guess just it would help if also we have like, we could

443 00:59:33.875 00:59:42.129 Casie Aviles: design like an architecture. Or you know, from the 1st day like, this is what we know we can do. And this is what we know.

444 00:59:42.930 00:59:44.779 Casie Aviles: Yeah, I, yeah, basically, that.

445 00:59:44.980 00:59:49.170 Casie Aviles: And if we there are some gaps, we fill it out as we go.

446 00:59:49.380 00:59:50.590 Casie Aviles: So yeah.

447 00:59:51.640 00:59:52.400 Amber Lin: Okay.

448 00:59:53.250 00:59:54.529 Amber Lin: A wish.

449 00:59:56.520 00:59:57.340 Awaish Kumar: Like.

450 00:59:58.790 01:00:04.989 Awaish Kumar: So I have deployed this Dexter. And the

451 01:00:05.580 01:00:08.919 Awaish Kumar: so 2 sources we are bring bringing in through that.

452 01:00:09.120 01:00:21.229 Awaish Kumar: Next time we can work on bringing linear in, and also maybe work work on adding more.

453 01:00:22.401 01:00:24.870 Awaish Kumar: The clients like. Now that we

454 01:00:25.160 01:00:34.089 Awaish Kumar: I have it in Javi, we can just it’s really easy, like we can just now write the configuration, and it can bring all the clients in

455 01:00:34.863 01:00:39.280 Awaish Kumar: so we can work on that part.

456 01:00:42.150 01:00:45.839 Awaish Kumar: and maybe, like clearing up tools and and things like that.

457 01:00:47.196 01:00:48.430 Amber Lin: Sounds good.

458 01:00:54.160 01:01:03.369 Amber Lin: fantastic! I’ll send this to Tom. I think we had a really great retro I will jump to my ABC.

459 01:01:03.510 01:01:10.750 Amber Lin: Meeting and Gail. Thank you for delivering that. I try to test it. I don’t think it knows we’re doing like

460 01:01:11.620 01:01:17.170 Amber Lin: Central Dog like Pest related updates. But I’m not gonna show them that. So it’s okay.

461 01:01:18.548 01:01:23.600 Miguel de Veyra: Which one? No, they they you have to provide it. The text it does it have window.

462 01:01:24.080 01:01:30.030 Amber Lin: Yeah, I know it’s okay. I didn’t have time to like figure it out. I’ll just show them that we have something.

463 01:01:30.580 01:01:31.370 Miguel de Veyra: Okay. Okay.

464 01:01:31.630 01:01:34.390 Amber Lin: Yes, thank you all.

465 01:01:34.390 01:01:35.160 Miguel de Veyra: During the call.

466 01:01:35.850 01:01:40.169 Awaish Kumar: Just to mention Casey and me. The data

467 01:01:40.905 01:01:46.109 Awaish Kumar: the slack data which I showed like the tables have the data right now you can.

468 01:01:47.360 01:01:49.690 Awaish Kumar: and you can take a look at that as well.

469 01:01:50.000 01:01:50.600 Miguel de Veyra: Okay.

470 01:01:51.670 01:01:52.290 Amber Lin: You guys.

471 01:01:52.290 01:01:52.650 Casie Aviles: Yes.

472 01:01:52.650 01:02:02.420 Amber Lin: You guys can meet a bit like, I guess we kind of wanted to figure out what architectural workflow we’re using feel free to meet afterwards. I just have to hop.

473 01:02:03.190 01:02:03.840 Casie Aviles: Sure.

474 01:02:04.450 01:02:04.900 Amber Lin: Okay.

475 01:02:04.900 01:02:05.560 Miguel de Veyra: Everyone. Bye-bye.

476 01:02:05.560 01:02:06.710 Amber Lin: Bye, bye.

477 01:02:06.950 01:02:07.700 Casie Aviles: Thank you.