Meeting Title: Miguel x Uttam x Amber Date: 2025-03-25 Meeting participants: Miguel De Veyra, Amber Lin


WEBVTT

1 00:00:00.000 00:00:05.650 Amber Lin: High School in Canada, and then I went to University

2 00:00:05.650 00:00:07.530 Miguel de Veyra: Oh, boys! Yes.

3 00:00:07.730 00:00:08.410 Amber Lin: Yeah.

4 00:00:10.430 00:00:11.930 Miguel de Veyra: So a lot of countries.

5 00:00:14.440 00:00:18.250 Miguel de Veyra: Okay, wait. Let’s go. I think it’s assigned first, st

6 00:00:18.680 00:00:24.129 Miguel de Veyra: golden data sheet inaccurate, not ideal proof responses.

7 00:00:25.790 00:00:27.520 Miguel de Veyra: Parent issue.

8 00:00:29.240 00:00:35.400 Miguel de Veyra: Okay, so this is the parent. So this should just be assigned to me. Then improve, answer accuracy

9 00:00:35.400 00:00:39.479 Amber Lin: Remove the parent issue like we can remove that if you think that’s better

10 00:00:40.040 00:00:43.810 Miguel de Veyra: Yeah, honestly, this one is kind of the same, and

11 00:00:43.810 00:00:44.500 Amber Lin: Okay.

12 00:00:44.800 00:00:50.690 Miguel de Veyra: Wait. I think we should remove the ones that doesn’t have an acceptance criteria. How should we approach this

13 00:00:53.790 00:00:54.910 Amber Lin: Let’s see.

14 00:00:54.910 00:00:55.289 Miguel de Veyra: Is this?

15 00:00:55.665 00:00:59.419 Amber Lin: Created this mess because there are so many nested issues

16 00:00:59.420 00:01:02.900 Miguel de Veyra: So like cause like the ticket ticket stop.

17 00:01:04.269 00:01:09.070 Miguel de Veyra: So like, do we need need to sign these to everything.

18 00:01:11.050 00:01:14.940 Miguel de Veyra: do everything. And then what else

19 00:01:15.780 00:01:20.270 Miguel de Veyra: we need to clean duplicate tickets. We need to clean the duplicate tickets.

20 00:01:20.980 00:01:24.675 Miguel de Veyra: What else do we need to do limit subtasks

21 00:01:25.410 00:01:32.240 Amber Lin: Yeah, don’t have nested issues.

22 00:01:32.870 00:01:38.139 Miguel de Veyra: Yeah, let’s let’s let’s stick with this. Let’s assign 1st everything and then work from there.

23 00:01:38.570 00:01:39.310 Amber Lin: Okay.

24 00:01:39.530 00:01:44.600 Amber Lin: sounds good. I mean, we only have to work on the stuff in the cycle. So there’s not that much.

25 00:01:45.450 00:01:46.440 Miguel de Veyra: Include other stuff.

26 00:01:46.440 00:01:47.809 Miguel de Veyra: There’s 41,

27 00:01:48.922 00:01:50.330 Amber Lin: Oh! Never mind then.

28 00:01:51.410 00:01:53.930 Miguel de Veyra: Oh, I should we hide?

29 00:01:54.060 00:01:59.759 Miguel de Veyra: Oh, wait! Shows up. Okay. So without the sub tasks, it’s just this. So it’s not much

30 00:02:01.610 00:02:05.469 Miguel de Veyra: executive reporting. Dashboard has 12 subtas.

31 00:02:06.710 00:02:10.309 Miguel de Veyra: Oh, yeah, I think we should do this view and then just work on it from top down.

32 00:02:10.820 00:02:13.230 Miguel de Veyra: Improve answer accuracy.

33 00:02:13.830 00:02:21.760 Miguel de Veyra: What is this user story competition data.

34 00:02:22.459 00:02:26.349 Miguel de Veyra: We have to remove this one, I think, avoiding hallucination

35 00:02:26.350 00:02:28.990 Amber Lin: It’s a bit okay.

36 00:02:30.000 00:02:31.140 Amber Lin: We can delete

37 00:02:31.140 00:02:38.330 Miguel de Veyra: Yeah, we can. I mean, we can just add later on, update and add ABC documents

38 00:02:38.330 00:02:49.669 Amber Lin: Yeah, like the the turn. I know there’s an there’s more sub tasks in there that you can assign it to me. Can you click on the add documents. There’s more in there. Oh, there’s not okay. Great

39 00:02:49.670 00:02:56.230 Miguel de Veyra: Yeah, I think the thing is for this. How do we cause update and add all ABC documents is technically their job.

40 00:02:56.730 00:03:01.480 Miguel de Veyra: How do we tag that, then do I just send it to you. So just we know

41 00:03:01.480 00:03:04.739 Amber Lin: I think, just tag me, cause I’m gonna

42 00:03:05.140 00:03:08.589 Amber Lin: ask the clients to update. So it’s technically my job to

43 00:03:09.010 00:03:12.120 Miguel de Veyra: Okay, okay, I’m just gonna tag it here. Then

44 00:03:12.120 00:03:12.530 Amber Lin: Okay.

45 00:03:12.530 00:03:19.979 Miguel de Veyra: Comment, client client! Oh, oh, Amber, I think this is the thing

46 00:03:20.150 00:03:21.490 Amber Lin: Client.

47 00:03:21.600 00:03:24.860 Miguel de Veyra: Right now we know it’s clients.

48 00:03:27.502 00:03:30.110 Miguel de Veyra: Let’s add this thing called client right?

49 00:03:30.570 00:03:31.160 Amber Lin: Oh, sure!

50 00:03:31.160 00:03:32.110 Miguel de Veyra: Them, yeah.

51 00:03:32.440 00:03:33.499 Amber Lin: Okay, that’s good.

52 00:03:35.000 00:03:37.491 Miguel de Veyra: Okay, okay, so that’s done.

53 00:03:39.560 00:03:42.159 Miguel de Veyra: okay, so this is the executive dashboard.

54 00:03:44.830 00:03:45.530 Miguel de Veyra: Can.

55 00:03:46.090 00:03:48.099 Miguel de Veyra: There’s so much stuff here.

56 00:03:49.900 00:03:50.740 Miguel de Veyra: Okay,

57 00:03:52.700 00:04:01.239 Amber Lin: This is for the I added his template, and then they built out essentially. The last 6 or 7 tasks is from the template.

58 00:04:02.580 00:04:04.210 Amber Lin: Gonna get accepted, etcetera.

59 00:04:04.560 00:04:08.439 Miguel de Veyra: Okay, okay, so should we clean clean this, then

60 00:04:08.600 00:04:10.499 Amber Lin: Cause. I think we can just add it right.

61 00:04:10.820 00:04:18.830 Amber Lin: Whatever you think is the process of how are we gonna get this past the client like, what kind of review steps do we need

62 00:04:19.220 00:04:20.859 Amber Lin: like on that side of the stuff

63 00:04:21.700 00:04:27.630 Miguel de Veyra: Cause. Yeah, cause I don’t think like looking at all of these 6 or 7, 6

64 00:04:28.200 00:04:28.520 Amber Lin: Hmm.

65 00:04:28.520 00:04:32.500 Miguel de Veyra: I I don’t see anyone who can who we can. Client review is gonna beat them. So

66 00:04:32.630 00:04:43.810 Miguel de Veyra: we do that every week. Product owner Pm. Review is not really a task. I think this is like a separate separate task that we do by the end of the week. This one we don’t really do

67 00:04:44.750 00:04:50.389 Miguel de Veyra: formatting and copy, build dashboard and dashboard tool. This is already done. We have it in real.

68 00:04:50.840 00:04:56.610 Miguel de Veyra: The data is available. Yes, define the use case, and I think this is all we can delete. This.

69 00:04:57.260 00:04:59.429 Miguel de Veyra: Is there a way to match, delete or no? No.

70 00:05:00.043 00:05:04.259 Amber Lin: I think you select all issues. So you shift. And then

71 00:05:04.522 00:05:05.309 Miguel de Veyra: There you go!

72 00:05:05.500 00:05:07.230 Amber Lin: And then you just

73 00:05:07.230 00:05:08.449 Miguel de Veyra: Enter. Okay, there you go.

74 00:05:08.450 00:05:09.250 Amber Lin: Thank you.

75 00:05:10.190 00:05:14.229 Miguel de Veyra: Okay, now we have. Why is it still 41.

76 00:05:15.380 00:05:17.230 Miguel de Veyra: Hello! Or let me. Hello!

77 00:05:17.750 00:05:23.660 Amber Lin: Can you click open patrick’s projects

78 00:05:24.140 00:05:26.729 Amber Lin: like I don’t know how much of it is.

79 00:05:29.550 00:05:31.950 Amber Lin: How do I add? Add him here?

80 00:05:33.020 00:05:33.635 Amber Lin: Oh,

81 00:05:34.360 00:05:40.539 Amber Lin: Then I guess his project is not. I think we have 41, because there’s so many nested subtests.

82 00:05:40.800 00:05:41.650 Amber Lin: so

83 00:05:41.960 00:05:45.309 Miguel de Veyra: Yeah. But oh, okay, here, this has 3. Also.

84 00:05:46.740 00:05:47.960 Miguel de Veyra: Okay, okay.

85 00:05:52.390 00:05:55.539 Miguel de Veyra: shit. So deep inside. No, we can’t really find it.

86 00:06:02.580 00:06:05.589 Miguel de Veyra: because there’s still 40 in one, and we deleted 6.

87 00:06:10.760 00:06:13.030 Miguel de Veyra: Oh, this is still in scope, though

88 00:06:14.710 00:06:19.280 Miguel de Veyra: so how do we see that 41? Is it here?

89 00:06:20.580 00:06:21.790 Amber Lin: What do you mean?

90 00:06:21.790 00:06:25.079 Miguel de Veyra: Like it says, Here, scope 41

91 00:06:25.430 00:06:28.209 Miguel de Veyra: started. This 20 completed is 10

92 00:06:29.880 00:06:37.970 Amber Lin: I think it’s 41 story points, not story cause I I kind of assigned a few with higher.

93 00:06:39.880 00:06:44.299 Amber Lin: like more story points. So I think that was a little bit confusing.

94 00:06:44.300 00:06:51.010 Miguel de Veyra: Oh, okay, I see. Because thought it was ticket numbers

95 00:06:51.880 00:06:58.439 Amber Lin: It’s it’s not. It’s not just ticket numbers, because I don’t think we have 41 tickets

96 00:06:58.440 00:07:01.399 Miguel de Veyra: Yeah, I was trying to find that I was like, where.

97 00:07:03.560 00:07:05.639 Miguel de Veyra: okay, okay, that should be fine. Then.

98 00:07:07.190 00:07:09.529 Miguel de Veyra: Okay, I think we can go back to board now.

99 00:07:10.140 00:07:11.010 Amber Lin: All right.

100 00:07:11.010 00:07:13.129 Miguel de Veyra: And then show sub issues.

101 00:07:13.260 00:07:14.332 Miguel de Veyra: Still, a lot

102 00:07:15.390 00:07:16.940 Amber Lin: So a lot. I know

103 00:07:18.020 00:07:20.999 Miguel de Veyra: Okay, dashboard. This should be in review.

104 00:07:21.650 00:07:26.120 Miguel de Veyra: Spreadsheet should be in review. Slack, alert, should be in review.

105 00:07:29.390 00:07:33.629 Miguel de Veyra: Okay, I guess we do. You wanna do the to do, or the in progress first, st

106 00:07:34.720 00:07:35.680 Amber Lin: Pardon me.

107 00:07:36.329 00:07:38.219 Miguel de Veyra: Do you want to do this or do this first? st

108 00:07:40.516 00:07:48.779 Amber Lin: Why don’t we just look at all this stuff in progress and then just get like, maybe

109 00:07:48.970 00:07:51.810 Amber Lin: figure out the issues, or maybe

110 00:07:53.230 00:07:53.799 Miguel de Veyra: That’s okay.

111 00:07:53.800 00:07:56.000 Amber Lin: Acceptance criteria like that

112 00:07:57.550 00:08:05.480 Miguel de Veyra: Okay, so let’s do identify some issue of improvement, some issue of what Etta here.

113 00:08:05.790 00:08:08.899 Miguel de Veyra: Oh, so it’s a sub issue and a sub issue. Okay, okay, that’s right.

114 00:08:08.900 00:08:10.052 Amber Lin: Yeah, I’m so sorry

115 00:08:11.470 00:08:16.619 Amber Lin: that that how I didn’t know how linear works. So that’s what it ended up being

116 00:08:17.630 00:08:22.730 Miguel de Veyra: Okay. So this one is golden. Looking at inaccurate, not ideal answers.

117 00:08:22.850 00:08:31.070 Miguel de Veyra: okay, so I get this one. Just to show you. I believe it’s it should be this one, right? So when something is like shit, answer, it goes here

118 00:08:31.390 00:08:32.010 Amber Lin: Hmm.

119 00:08:32.010 00:08:34.529 Miguel de Veyra: So technically that satisfies it. Right?

120 00:08:35.419 00:08:45.269 Amber Lin: Yes, I think my only is that we can also look at the ones already in the data sheet, and then improve on those as well. But yes, I do think

121 00:08:45.809 00:08:48.999 Amber Lin: they are like they are overlapping

122 00:08:49.440 00:08:50.349 Miguel de Veyra: Okay. Okay.

123 00:08:51.390 00:08:54.469 Amber Lin: But there’s a separate task for that. That’s the spreadsheet. One

124 00:08:54.470 00:08:55.390 Miguel de Veyra: Yeah. Yeah.

125 00:08:57.260 00:09:06.749 Miguel de Veyra: Looking at the golden day, looking at the inaccurate, not ideal answers to improve our ad. I mean, we kind of filled it up already. I do. Isn’t this the thing I did

126 00:09:06.950 00:09:07.970 Miguel de Veyra: like here?

127 00:09:14.900 00:09:18.260 Miguel de Veyra: Yeah, I think it’s this one. So I guess we can close this. What do you think.

128 00:09:18.540 00:09:20.569 Miguel de Veyra: or should we assign this to client

129 00:09:25.650 00:09:27.340 Miguel de Veyra: Think we should assign this to client

130 00:09:28.210 00:09:29.340 Amber Lin: Sure.

131 00:09:29.340 00:09:33.899 Miguel de Veyra: Alright looking because I don’t. I don’t understand the golden date

132 00:09:33.900 00:09:38.189 Amber Lin: Yeah, sorry. This this was not very clear. I think I just meant to.

133 00:09:38.610 00:09:50.889 Amber Lin: This is part of improving the our answer. So we? We look at the ones that we’re not doing well in the golden data sheet already. And then

134 00:09:51.520 00:09:53.760 Miguel de Veyra: Okay, do you just wanna delete this

135 00:09:54.050 00:09:54.810 Amber Lin: Sure. Yeah.

136 00:09:54.810 00:09:55.850 Miguel de Veyra: It’s too broad.

137 00:09:56.270 00:09:57.179 Amber Lin: Yeah, sure.

138 00:09:57.400 00:09:58.849 Miguel de Veyra: Okay, okay, let’s delete that.

139 00:09:59.030 00:10:00.599 Miguel de Veyra: Okay. So technically.

140 00:10:00.600 00:10:06.720 Amber Lin: Specificity do you want with the tickets like what is what is a good ticket?

141 00:10:08.500 00:10:11.390 Miguel de Veyra: Yeah, yeah, that’s like, that’s a good question. Actually.

142 00:10:12.290 00:10:18.750 Miguel de Veyra: what is a group ticket? So ideally, it has what to do with them. Say again, user story

143 00:10:20.490 00:10:24.990 Amber Lin: You goal user story acceptance criteria.

144 00:10:33.120 00:10:34.799 Miguel de Veyra: Max. 2 subtasks.

145 00:10:42.260 00:10:44.829 Miguel de Veyra: Okay, why is this not going here?

146 00:10:47.910 00:10:51.699 Miguel de Veyra: Turn into I see.

147 00:10:54.960 00:10:55.790 Miguel de Veyra: Okay.

148 00:11:01.000 00:11:04.440 Miguel de Veyra: okay, so ideally, we have one of these.

149 00:11:16.630 00:11:20.690 Miguel de Veyra: But if the subtasks for this are done, does this mean this ticket is done

150 00:11:25.000 00:11:31.380 Amber Lin: And so to me, this kind of ongoing. But then maybe it shouldn’t be a ticket

151 00:11:31.710 00:11:41.839 Miguel de Veyra: Yes, no, I think I think that’s correct. It should be a ticket, because here it says, identify not really do anything with that. So it’s just to identify right? See a list

152 00:11:41.840 00:11:44.050 Amber Lin: Lead the part of improve on them, so

153 00:11:44.505 00:11:44.960 Miguel de Veyra: Yeah.

154 00:11:44.960 00:11:46.659 Amber Lin: Identify the under deal

155 00:11:47.280 00:11:52.809 Miguel de Veyra: See, see a list of answers that are not good user story.

156 00:11:53.270 00:11:54.849 Miguel de Veyra: I don’t know what user story means.

157 00:11:55.500 00:12:20.440 Amber Lin: User story. Essentially, just a sentence like the client said it. It’s like, Oh, as a say, as a Csr. I want the response to be quick, so I can get back to my customer or as a manager like, oh, when people update the documents, I want to be able to prove that. So I want to, so I can make sure everything’s aligned. So it’s like that

158 00:12:20.840 00:12:21.750 Miguel de Veyra: Okay. Okay.

159 00:12:21.890 00:12:22.450 Amber Lin: Hmm.

160 00:12:23.150 00:12:27.199 Miguel de Veyra: How do I turn this into a checkbox? Is it this one

161 00:12:28.454 00:12:35.900 Amber Lin: You type in 2 square brack delete the bullet point like the bullet point icon and type in 2 square brackets

162 00:12:35.900 00:12:40.609 Miguel de Veyra: Oh, okay, okay, okay, yeah. Then that should be good.

163 00:12:42.280 00:12:44.930 Miguel de Veyra: User story should not. Okay. There you go. Yeah.

164 00:12:45.560 00:12:50.470 Miguel de Veyra: So slack, alert. I’ll show you. It’s ABC logs. It’s this one.

165 00:12:51.040 00:12:52.250 Miguel de Veyra: Add or

166 00:12:53.150 00:12:59.919 Miguel de Veyra: shows you this, and then the quality score we also we also want to share who type who was the one who requested it.

167 00:13:05.070 00:13:08.760 Amber Lin: Oh hmm!

168 00:13:10.430 00:13:13.049 Miguel de Veyra: So yeah, technically, that that thing is done.

169 00:13:13.170 00:13:14.560 Miguel de Veyra: So this ticket is done

170 00:13:15.210 00:13:15.850 Amber Lin: Okay.

171 00:13:16.520 00:13:18.790 Miguel de Veyra: Improve answer accuracy.

172 00:13:19.100 00:13:24.560 Miguel de Veyra: So I guess this one we can move to Pr review this one is one client.

173 00:13:26.230 00:13:29.089 Miguel de Veyra: So how do you? How do? Should we do this? Then

174 00:13:32.130 00:13:34.639 Amber Lin: Yeah, and can we go back to the parent issue?

175 00:13:34.900 00:13:35.670 Miguel de Veyra: Yeah, yeah.

176 00:13:37.230 00:13:38.420 Amber Lin: Oh, if hmm!

177 00:13:39.250 00:13:43.740 Amber Lin: I feel like this, don’t have. This doesn’t need to be nested so

178 00:13:43.740 00:13:45.089 Miguel de Veyra: Yeah, they should be

179 00:13:45.280 00:13:48.679 Amber Lin: Yeah, so can you select both of them? Select both of them

180 00:13:48.850 00:13:49.470 Miguel de Veyra: Yeah.

181 00:13:49.910 00:13:53.809 Amber Lin: And then right click to remove parent issue.

182 00:13:55.310 00:13:57.590 Miguel de Veyra: Yeah, there we go, and then we can delete this one.

183 00:13:58.260 00:13:59.310 Miguel de Veyra: Oh, shit.

184 00:14:00.620 00:14:02.379 Miguel de Veyra: Okay, this one. We delete right?

185 00:14:02.770 00:14:03.310 Amber Lin: Hmm.

186 00:14:03.650 00:14:06.210 Miguel de Veyra: Improve. I still need to find it improve.

187 00:14:07.610 00:14:12.290 Miguel de Veyra: Yeah, okay.

188 00:14:13.230 00:14:14.650 Amber Lin: That’s a bit less fast.

189 00:14:14.880 00:14:15.540 Amber Lin: Alright.

190 00:14:15.540 00:14:20.230 Miguel de Veyra: Okay, executive reporting dashboard. This is the next one that’s pretty big.

191 00:14:20.490 00:14:23.080 Miguel de Veyra: Oh, wait, let’s go. Actually, let’s close the other 2.

192 00:14:23.240 00:14:32.509 Miguel de Veyra: Client. Should we just put client here, or should this be on somewhere else?

193 00:14:32.910 00:14:39.850 Amber Lin: Yeah, I was wondering. I maybe just in the blocked, because kind of like they need. That’s what they need to do, or just put it in

194 00:14:40.090 00:14:46.129 Miguel de Veyra: Yeah, okay, hmm, in in my previous job we had this client who

195 00:14:47.580 00:14:48.110 Amber Lin: Hmm.

196 00:14:48.640 00:14:52.249 Miguel de Veyra: So if you know, because technically, there’s nothing you can do about it.

197 00:14:52.390 00:14:52.710 Amber Lin: Yeah.

198 00:14:52.710 00:14:55.010 Miguel de Veyra: And the cloth is your shit. So client, move

199 00:14:56.240 00:15:04.130 Miguel de Veyra: and feedback to data. Yeah, this one. I think there’s only this one I’m I’m just gonna clarify first, st before we notice to peer review

200 00:15:04.410 00:15:07.200 Miguel de Veyra: executive reporting dashboard.

201 00:15:10.180 00:15:10.960 Miguel de Veyra: It’s such

202 00:15:10.960 00:15:14.809 Amber Lin: Just the just the thumbs up, and I think we should be done with

203 00:15:14.810 00:15:19.889 Miguel de Veyra: Okay, okay, so this one is technically the same thing run clear sprints with.

204 00:15:20.040 00:15:22.440 Miguel de Veyra: I’m not sure this is a task

205 00:15:22.970 00:15:28.869 Amber Lin: This is like I don’t know where this came from. I think Wutum changed this

206 00:15:29.599 00:15:31.750 Miguel de Veyra: I’ll just assign this to you, because this is

207 00:15:31.750 00:15:33.560 Amber Lin: No, this is this is me. This is me sorry!

208 00:15:33.560 00:15:36.549 Miguel de Veyra: Yeah, it seems like.

209 00:15:36.680 00:15:44.509 Miguel de Veyra: keep the client up to date. I think this is also yours. Oh, we should probably add something like this also, if it’s like a a bit, general. Yeah.

210 00:15:45.040 00:15:45.760 Amber Lin: Hmm.

211 00:15:46.050 00:15:46.720 Miguel de Veyra: Right.

212 00:15:46.950 00:15:48.330 Amber Lin: Sure that’s great.

213 00:15:48.330 00:15:55.560 Miguel de Veyra: And then, for example, if you want to create a ticket, and you’re not sure if what is this just type engineering, I guess something like this engineer.

214 00:15:56.970 00:15:58.059 Miguel de Veyra: Then I can look into it

215 00:15:59.300 00:16:06.749 Amber Lin: Use the comment feature. I’ll probably just tag like comment of tag you, and then you can look at it

216 00:16:07.070 00:16:13.290 Miguel de Veyra: Okay, clean up. Document. Okay, what does this central Doc should be well formatted

217 00:16:14.180 00:16:22.260 Amber Lin: Yeah, I think last, this is not a priority at all. Like last meeting, they were like, Oh, is the availability

218 00:16:22.520 00:16:30.549 Amber Lin: spreadsheet? Does it look pretty, or whatever it it is not. But I don’t think it’s very important that it does.

219 00:16:30.860 00:16:33.299 Amber Lin: So it’s just there, but we don’t

220 00:16:33.300 00:16:35.950 Miguel de Veyra: Yeah, who’s gonna who’s assigned here?

221 00:16:36.920 00:16:43.350 Miguel de Veyra: Cleaned up? Yeah. Cleaned up spreadsheet with zip codes. And I think this is theirs. Cause I we can’t touch it.

222 00:16:43.910 00:16:46.350 Miguel de Veyra: We don’t even have edit access to this

223 00:16:46.580 00:16:48.180 Amber Lin: Oh, that’s so funny!

224 00:16:48.590 00:16:50.890 Miguel de Veyra: Sure I am okay.

225 00:16:50.890 00:16:55.219 Amber Lin: So they wanted us to clean it up. But they don’t even gave. Okay.

226 00:16:55.590 00:16:56.420 Amber Lin: I see

227 00:16:59.070 00:17:04.039 Miguel de Veyra: Golden data sheet. Yeah, this is, I think this is, we should probably move this to blocked.

228 00:17:11.540 00:17:15.089 Miguel de Veyra: Let’s just move that be able to deploy the newest code.

229 00:17:17.400 00:17:22.149 Miguel de Veyra: What the hell I remote deploy. Yeah, this one we moved to blocked.

230 00:17:25.329 00:17:29.430 Miguel de Veyra: Cause yeah, we’re just gonna send the code to Tim for now

231 00:17:30.390 00:17:38.639 Amber Lin: Okay, maybe that could just be in the backlog, or it doesn’t seem like something very urgent

232 00:17:38.950 00:17:40.840 Miguel de Veyra: How do I see the box again?

233 00:17:45.730 00:17:50.470 Miguel de Veyra: Shit issues? So I guess I go here

234 00:17:59.700 00:18:01.730 Miguel de Veyra: so empty columns. There you go!

235 00:18:02.130 00:18:06.540 Miguel de Veyra: How come Ambra, how come? We can’t see the empty rooms.

236 00:18:07.070 00:18:09.699 Miguel de Veyra: How do I see the backlogs

237 00:18:10.652 00:18:14.680 Amber Lin: It’s on the left. So just scroll scroll on the

238 00:18:14.890 00:18:16.340 Miguel de Veyra: No, that’s my left

239 00:18:16.340 00:18:22.089 Amber Lin: Oh, what? Oh, you’re inactive! So click on all issues on the top, right next to ABC

240 00:18:22.503 00:18:23.330 Miguel de Veyra: Okay. Okay.

241 00:18:23.330 00:18:23.940 Amber Lin: Yeah, we’re in

242 00:18:23.940 00:18:25.639 Miguel de Veyra: Oh, sure. Okay. Okay.

243 00:18:25.910 00:18:26.540 Amber Lin: There we go!

244 00:18:27.330 00:18:29.690 Miguel de Veyra: Okay, yeah, okay, that that makes sense.

245 00:18:30.110 00:18:36.639 Miguel de Veyra: So, okay, this one. I guess we could move this to requirements. Start? No.

246 00:18:40.590 00:18:42.189 Miguel de Veyra: actually, it’s not this one?

247 00:18:43.430 00:18:44.640 Miguel de Veyra: No, not that one!

248 00:18:44.640 00:18:52.880 Amber Lin: Yeah, that’s that’s kinda my thing. It can be deleted like it’s pm, like, it’s

249 00:18:53.630 00:18:56.460 Miguel de Veyra: No, that wasn’t the one we were looking at.

250 00:18:57.030 00:19:00.210 Miguel de Veyra: Wait, wait! Did I hide anything? Show solutions?

251 00:19:00.450 00:19:05.159 Miguel de Veyra: It the one we were looking at? What was the one for Patrick? What the hell

252 00:19:05.160 00:19:06.420 Amber Lin: Oh, yeah.

253 00:19:06.635 00:19:07.279 Miguel de Veyra: Where is it?

254 00:19:07.280 00:19:13.340 Amber Lin: Go to the projects on the left the left bar go projects

255 00:19:14.320 00:19:15.410 Miguel de Veyra: Improving? What before

256 00:19:15.410 00:19:19.270 Amber Lin: Yeah. And then the agent AI architecture is Patrick’s.

257 00:19:19.470 00:19:26.890 Amber Lin: So the top there’s overview and issues. So if you click on issues there, that’s his test.

258 00:19:28.360 00:19:30.160 Miguel de Veyra: Okay, that’s so genital.

259 00:19:31.000 00:19:33.703 Miguel de Veyra: Anyways, let’s get back here. I guess.

260 00:19:34.870 00:19:37.520 Miguel de Veyra: So I guess in progress is kind of clear.

261 00:19:39.420 00:19:42.129 Miguel de Veyra: This one we don’t wanna touch. It’s blocked.

262 00:19:42.531 00:19:43.990 Miguel de Veyra: So it was this one

263 00:19:44.180 00:19:46.760 Miguel de Veyra: the be able to remotely deploy

264 00:19:47.030 00:19:47.990 Amber Lin: Yeah.

265 00:19:47.990 00:19:51.290 Miguel de Veyra: Yeah, we can do this to block, because this is already in

266 00:19:51.290 00:19:55.239 Amber Lin: Okay, let’s move it to blocked and delete this parent issue.

267 00:19:56.780 00:19:59.239 Amber Lin: I can actually, I can. I can do that

268 00:19:59.590 00:20:02.579 Miguel de Veyra: But it has this sent them to Newcom

269 00:20:03.740 00:20:06.149 Amber Lin: It’s kinda it’s kind of time

270 00:20:06.150 00:20:07.629 Miguel de Veyra: Yeah. Yeah. True. True.

271 00:20:08.400 00:20:08.890 Miguel de Veyra: Okay.

272 00:20:08.890 00:20:12.399 Amber Lin: We’ll go into linear and do that

273 00:20:12.660 00:20:15.070 Miguel de Veyra: Make checklist for rollout

274 00:20:15.240 00:20:20.820 Amber Lin: Yeah, that’s me, because I I want this rollout to happen. And it’s

275 00:20:21.560 00:20:27.580 Amber Lin: they don’t know. They don’t know what how to do the rollout like they haven’t gave me the

276 00:20:29.460 00:20:31.800 Miguel de Veyra: Yeah, that’s okay. That’s fine.

277 00:20:31.800 00:20:36.620 Amber Lin: What is project scaffolding? Okay, this stuff is in a backlog

278 00:20:37.723 00:20:39.930 Miguel de Veyra: 1 40.

279 00:20:44.230 00:20:48.780 Miguel de Veyra: I’m also gonna delete a few here. So so

280 00:20:49.550 00:20:54.770 Miguel de Veyra: this is probably gonna be here set up tool to run offer on

281 00:20:54.890 00:20:57.730 Miguel de Veyra: import. No, there should be here.

282 00:20:58.270 00:21:05.330 Miguel de Veyra: Roll out! Roll out port to 25, we added to do escalation, but if fuck

283 00:21:06.600 00:21:13.600 Miguel de Veyra: as a Csr I should be able to escalate to my manager if the bot doesn’t know the answer, so I can feel.

284 00:21:15.240 00:21:17.260 Miguel de Veyra: Are we supposed to do something here?

285 00:21:18.420 00:21:19.110 Amber Lin: Hmm.

286 00:21:19.110 00:21:20.759 Miguel de Veyra: Add escalation, path.

287 00:21:21.860 00:21:28.110 Amber Lin: Oh, I think it’s more of like options

288 00:21:28.470 00:21:32.089 Amber Lin: on how to do it. I don’t think it’s a priority.

289 00:21:32.590 00:21:36.939 Amber Lin: but it’s probably something that will come up as they as they test

290 00:21:37.610 00:21:38.320 Miguel de Veyra: Yeah.

291 00:21:38.540 00:21:38.900 Amber Lin: Yeah.

292 00:21:38.900 00:21:44.930 Miguel de Veyra: Okay? I mean, if the answer isn’t here, it’s kind of escalated already, because it goes here right

293 00:21:45.150 00:21:54.900 Amber Lin: Oh, that’s true. I think I more meant of during the call. So say a Csr is on the call, and then the bot can’t answer. What are they gonna do

294 00:21:57.540 00:22:02.799 Miguel de Veyra: But is that our task, or is that more on their side

295 00:22:03.611 00:22:17.679 Amber Lin: Yeah, maybe, like, I guess the most we can do is to have the bot respond. Oh, you can reach out to this person. But I I suppose in that context they just go search like, go search their database

296 00:22:18.010 00:22:21.930 Amber Lin: or go ask someone like, do what they usually do

297 00:22:22.430 00:22:29.099 Miguel de Veyra: Yeah, let’s move this to wait. What was the name of it again? Let’s hope that to

298 00:22:29.250 00:22:30.989 Miguel de Veyra: ready for development, I guess

299 00:22:30.990 00:22:31.410 Amber Lin: Sure.

300 00:22:31.410 00:22:32.650 Miguel de Veyra: Until they bring it up.

301 00:22:33.020 00:22:37.490 Miguel de Veyra: Benchmark quality score, Patrick, Dublin.

302 00:22:41.030 00:22:48.020 Miguel de Veyra: What so output benchmarks are test quality of that that does, I mean.

303 00:22:48.610 00:22:55.700 Miguel de Veyra: But this one should be sorry. Can you

304 00:22:57.956 00:22:59.419 Miguel de Veyra: Wait. Where is it?

305 00:23:00.090 00:23:06.210 Miguel de Veyra: The waiter? Benchmarks quality score isn’t just, isn’t it? This one locality score

306 00:23:06.680 00:23:17.470 Amber Lin: Wait. What is that? I think? Let me look at the can. You click into the task? Because I think that’s okay. That is not our task. That is Patrick.

307 00:23:18.020 00:23:23.480 Amber Lin: the not the escalation, but the benchmark. That is Patrick. So I think

308 00:23:23.680 00:23:30.380 Amber Lin: let’s go into issues and click on filter. Let’s filter out his product. So we don’t get confused

309 00:23:31.090 00:23:34.470 Amber Lin: right under. ABC, click, filter, click, project

310 00:23:35.409 00:23:38.709 Amber Lin: project under cycle. So go down a little bit more

311 00:23:39.442 00:23:46.680 Amber Lin: project and then we’ll select everything other than his agentic AI architecture. We’ll select everything else

312 00:23:48.830 00:23:50.479 Amber Lin: and no project. Yeah.

313 00:23:53.020 00:23:53.920 Miguel de Veyra: Okay.

314 00:23:54.390 00:23:58.980 Amber Lin: And show sub issues, display

315 00:24:00.300 00:24:02.050 Miguel de Veyra: I am not sure

316 00:24:02.050 00:24:04.429 Amber Lin: Can you click on display and then

317 00:24:04.810 00:24:06.200 Miguel de Veyra: I mean it showed.

318 00:24:08.043 00:24:11.680 Miguel de Veyra: I guess we have to show empty columns, too. There you go

319 00:24:12.060 00:24:12.770 Amber Lin: Oh!

320 00:24:16.680 00:24:19.350 Miguel de Veyra: Okay. So I guess this is a bit more like it

321 00:24:21.410 00:24:26.859 Amber Lin: I’m looking at the improve answer. You readability and usability. Do you think that’s done?

322 00:24:27.300 00:24:28.540 Miguel de Veyra: Sorry which one is it

323 00:24:28.770 00:24:36.219 Amber Lin: I’m I’m on 82. I’m in the backlog right now. So issue 82

324 00:24:38.530 00:24:39.750 Miguel de Veyra: Like, I think that’s

325 00:24:39.750 00:24:40.330 Amber Lin: Button.

326 00:24:41.640 00:24:49.280 Miguel de Veyra: What’s the acceptance? Kitty? Answer should not be too long. Yes, yes should be well structured. Yes.

327 00:24:49.850 00:24:50.639 Amber Lin: Do we then

328 00:24:50.640 00:24:52.500 Miguel de Veyra: I should be able. Yeah.

329 00:24:52.810 00:24:53.370 Amber Lin: Okay.

330 00:24:53.704 00:24:55.040 Miguel de Veyra: It should be done

331 00:24:55.040 00:24:57.350 Amber Lin: Okay, I’ll put it in P.

332 00:24:57.603 00:24:58.619 Miguel de Veyra: Worked on this. Yeah.

333 00:24:58.620 00:25:01.289 Amber Lin: Product, owner, client, review, client, review.

334 00:25:01.430 00:25:04.229 Miguel de Veyra: If okay, I’ll move it there. Great.

335 00:25:04.460 00:25:10.880 Miguel de Veyra: Because if we’re planning to to get it down to like 50 to a hundred dollars for sprint

336 00:25:11.500 00:25:12.940 Amber Lin: Upper cycle.

337 00:25:13.730 00:25:14.750 Amber Lin: Yes.

338 00:25:15.380 00:25:17.529 Miguel de Veyra: That means I can’t work on this at all.

339 00:25:18.730 00:25:28.189 Amber Lin: What is? Can you let me know a little bit more like, what does it look like to have 50 h on a broad like per cycle.

340 00:25:28.530 00:25:35.540 Amber Lin: That means like 5 h per day. What? How much can we get done in 5 h? What does it look like

341 00:25:38.090 00:25:42.909 Miguel de Veyra: 5 h of total time of the team. My, my time included right

342 00:25:43.430 00:25:47.810 Amber Lin: Yeah, everybody. So also my time, I guess, like I spend.

343 00:25:48.150 00:25:53.830 Amber Lin: I guess, in in now less than like 30 min for me.

344 00:25:53.830 00:25:54.680 Miguel de Veyra: Yeah.

345 00:25:55.000 00:25:58.930 Amber Lin: And I think both you and Casey spent like 2 h kinda

346 00:25:58.930 00:26:00.910 Miguel de Veyra: No, no case. You spent a lot of time

347 00:26:00.910 00:26:02.270 Amber Lin: Oh dear!

348 00:26:02.270 00:26:04.000 Miguel de Veyra: Probably 8 HA day.

349 00:26:04.280 00:26:05.630 Amber Lin: Oh no!

350 00:26:05.630 00:26:07.929 Miguel de Veyra: And I probably spend the same amount of ours

351 00:26:07.930 00:26:10.680 Amber Lin: No, no, I mean like what we want to get to. I know

352 00:26:10.680 00:26:11.190 Miguel de Veyra: Yeah, yeah.

353 00:26:11.190 00:26:15.190 Amber Lin: We’re like 8 h per day on this. But what we want to get to is

354 00:26:15.190 00:26:20.549 Miguel de Veyra: Probably have Casey work on this 4 HA day, and then me and you 30 min

355 00:26:20.900 00:26:24.836 Amber Lin: Okay, yeah. So that would be,

356 00:26:25.860 00:26:35.369 Amber Lin: how much like, for example, tasks that we are just doing right now? Can you give me a sense of how much each of them kind of takes like. If we look at the in progress

357 00:26:36.060 00:26:40.589 Amber Lin: and the in progress parts like, how much does do they take? How long do they take

358 00:26:41.630 00:26:47.760 Miguel de Veyra: So this one pro should probably take an hour or 2. It really depends because we’re we’re not really the best data engineers

359 00:26:47.990 00:26:48.540 Amber Lin: Hmm.

360 00:26:48.540 00:26:52.549 Miguel de Veyra: So I think Casey can do it. It’s probably gonna take an hour or 2

361 00:26:53.680 00:26:57.549 Miguel de Veyra: and then executive reporting dashboard. What’s what’s in here again.

362 00:26:57.650 00:27:00.579 Miguel de Veyra: So yeah, that’s basically the same right? Because that’s it.

363 00:27:01.860 00:27:04.810 Miguel de Veyra: So yeah, so this 2 should probably take

364 00:27:05.000 00:27:10.439 Miguel de Veyra: 2, 1 to 2 h, 3 to 4. If we can’t figure out the real stuff

365 00:27:11.080 00:27:11.859 Amber Lin: I’m sorry.

366 00:27:12.270 00:27:23.930 Miguel de Veyra: Yeah. And then, yeah, I think that’s pretty much it. This one’s the update cause. This one was the one we did today. This probably took me and Casey a combined of 8 h to 9 h each.

367 00:27:24.500 00:27:25.900 Amber Lin: To do the

368 00:27:27.330 00:27:31.540 Miguel de Veyra: This 3, the slack alerts. It’s because basically what we did

369 00:27:32.580 00:27:40.539 Miguel de Veyra: Was we. We edited this, tested it a bit, and then we created like a new agent out here

370 00:27:41.830 00:27:46.080 Miguel de Veyra: to basically analyze it and send it to slack or g sheets

371 00:27:46.840 00:27:50.590 Amber Lin: I see. So it’s a essentially a new workflow.

372 00:27:50.590 00:27:53.200 Miguel de Veyra: Yeah, and additional node

373 00:27:53.610 00:27:54.510 Amber Lin: I see.

374 00:27:54.510 00:27:58.640 Miguel de Veyra: Okay, so this one, yeah, this took this 3 took 9 h

375 00:27:59.740 00:28:03.939 Miguel de Veyra: in total. And then this one. So it’s like 1112 h in total.

376 00:28:04.300 00:28:05.780 Amber Lin: We’re like, yeah.

377 00:28:06.030 00:28:10.729 Amber Lin: So we can’t be doing that much or that that kind of would have been

378 00:28:11.020 00:28:14.040 Amber Lin: almost the total of this week. Because

379 00:28:15.230 00:28:18.569 Amber Lin: if we technically have 25 h per week

380 00:28:18.570 00:28:19.260 Miguel de Veyra: Yeah.

381 00:28:19.480 00:28:24.650 Amber Lin: And that took already like 3.rd How many hours total have we spent already?

382 00:28:24.650 00:28:27.730 Miguel de Veyra: Probably I I’d say 12 to 13

383 00:28:28.230 00:28:31.490 Amber Lin: 12 to 13. So we we have half

384 00:28:31.490 00:28:32.880 Miguel de Veyra: And that’s not counting. Yesterday

385 00:28:33.940 00:28:35.060 Amber Lin: I’m sorry.

386 00:28:35.060 00:28:38.920 Miguel de Veyra: And it wasn’t counting yesterday, cause this, this one was only today.

387 00:28:40.100 00:28:43.270 Miguel de Veyra: So counting yesterday, we’re probably already at 20

388 00:28:44.000 00:28:49.639 Amber Lin: Okay. So honestly, I feel like this week. This is all we’re gonna give to know

389 00:28:49.910 00:28:51.240 Miguel de Veyra: Yeah, I think.

390 00:28:51.240 00:28:52.190 Amber Lin: He said

391 00:28:52.360 00:28:52.890 Miguel de Veyra: Yeah.

392 00:28:52.890 00:28:57.239 Amber Lin: So kind of said today when I asked her, What do you want from us?

393 00:28:57.970 00:29:03.280 Miguel de Veyra: That’s why I think the way we should do it is probably because it’s every 2 weeks right?

394 00:29:03.540 00:29:08.580 Miguel de Veyra: So like around Thursday before the call even.

395 00:29:08.820 00:29:13.370 Miguel de Veyra: or on the call we decide, hey, what’s the priorities for the next cycle?

396 00:29:13.940 00:29:17.509 Miguel de Veyra: We’re just gonna talk to them a little bit about

397 00:29:17.730 00:29:21.240 Amber Lin: That I know he’s gonna talk with the execs. But

398 00:29:21.360 00:29:26.409 Amber Lin: I think we are gonna set the priorities, and he’s gonna tell them about our hours

399 00:29:26.410 00:29:28.899 Miguel de Veyra: Yeah, yeah, because yeah.

400 00:29:29.120 00:29:34.460 Miguel de Veyra: because I think that should be the way to do it. Because right now, the reason we got into this pass

401 00:29:35.450 00:29:39.749 Miguel de Veyra: It’s because of scope, creep like it just grew and grew. We already have a voice agent for them

402 00:29:40.830 00:29:52.239 Amber Lin: Yeah, yeah, my bad, because I think I for me, it was like, Oh, I only have this client. Okay, what do they want? Okay, we can do that. And then we can do that too. And we can do that too. So it really got really messy

403 00:29:52.540 00:29:58.580 Miguel de Veyra: Yeah, because ideally, I think with them, long term wants me also gone on development side, like fully

404 00:29:59.050 00:30:06.160 Miguel de Veyra: focus on recruitment. And I think coaching, which I’m trying to do with Casey and practicing with him because we’re close friends

405 00:30:07.000 00:30:08.869 Miguel de Veyra: So it’s a bit open. But yeah.

406 00:30:10.430 00:30:13.470 Amber Lin: We? We’re you’re practicing with Casey on

407 00:30:13.470 00:30:18.379 Miguel de Veyra: Coaching him on how to do so. That’s why we hop on a call like 3 to 4 HA day.

408 00:30:19.666 00:30:25.700 Amber Lin: That’s great cause. He will be taking over a lot of development stuff that you do. So

409 00:30:25.700 00:30:26.480 Miguel de Veyra: Yeah, yeah.

410 00:30:26.480 00:30:29.460 Amber Lin: It’s nice to have recalling him

411 00:30:30.670 00:30:33.739 Miguel de Veyra: I’m probably gonna spend like 2 HA day or 3 HA day.

412 00:30:33.980 00:30:41.390 Miguel de Veyra: maybe 2, 2 h, like just hopping on calls with developers, and then I think we should probably hop on a call. Are you already on full time?

413 00:30:41.980 00:30:49.999 Amber Lin: Yeah, I’m on full time. I’m waiting for them to send me the contract. But honestly, I’ve since I started I’ve been working 8 HA day

414 00:30:50.000 00:30:50.340 Miguel de Veyra: Exactly.

415 00:30:50.340 00:30:51.748 Amber Lin: There’s not really a difference

416 00:30:52.528 00:30:54.520 Miguel de Veyra: Yeah, I think, yeah.

417 00:30:55.650 00:31:01.330 Miguel de Veyra: yeah, I think we should probably spend like at least 15 to 20 min before we end the day.

418 00:31:01.690 00:31:02.410 Amber Lin: Hmm.

419 00:31:02.866 00:31:06.520 Miguel de Veyra: I think the idea I have there is

420 00:31:07.370 00:31:16.139 Miguel de Veyra: For people who don’t work during the hours we have, for example, Jana and some other people who might want to work earlier. We still have, like the tasks for them, right

421 00:31:16.300 00:31:16.660 Amber Lin: Hmm.

422 00:31:16.660 00:31:17.790 Miguel de Veyra: For the next day.

423 00:31:18.633 00:31:28.129 Miguel de Veyra: Yeah, I think that’s something we should definitely do, probably around 2 to 3 am. Like, it doesn’t have to be a call, maybe. Just you know a chat. Hey? Here’s what the team did today.

424 00:31:28.430 00:31:29.170 Amber Lin: Sure

425 00:31:29.500 00:31:34.499 Amber Lin: I mean, as long as I’m not in other meetings I’m happy to jump on a call, because this has been real helpful

426 00:31:34.890 00:31:42.200 Miguel de Veyra: Because I think that that way. I can also help Jana out, because right now we can’t really give her a task, because at the end of the day.

427 00:31:42.620 00:31:46.480 Miguel de Veyra: At the at the end of her day we just start working.

428 00:31:46.740 00:31:54.210 Miguel de Veyra: and then we give out tasks, and then every task that’s there is, we try to finish it right? So tomorrow she doesn’t really have a job to do

429 00:31:55.940 00:31:59.950 Amber Lin: Tomorrow. Yeah, she’s joining tomorrow. And we’re

430 00:32:00.140 00:32:02.439 Amber Lin: like, what? What do you think?

431 00:32:02.790 00:32:05.850 Amber Lin: Yeah, what do you think she can do when she joins tomorrow?

432 00:32:08.150 00:32:13.059 Miguel de Veyra: I am not sure to be honest, because we don’t cause. I want her to work on the internal stuff, but

433 00:32:13.660 00:32:15.940 Miguel de Veyra: I think we’re still cleaning that stuff. Yeah.

434 00:32:16.200 00:32:18.150 Amber Lin: So it’s kind of on us, too.

435 00:32:22.280 00:32:23.520 Miguel de Veyra: Yeah.

436 00:32:24.970 00:32:29.040 Miguel de Veyra: And then, yeah, but yeah, I think that’s pretty much it. It’s already 3 Am. My time.

437 00:32:29.180 00:32:32.070 Miguel de Veyra: I don’t think Utop’s gonna come anytime soon. Anyways.

438 00:32:32.070 00:32:48.709 Amber Lin: Yeah, okay, just let’s just say we’ll meet tomorrow. I have time to meet tomorrow earlier, like my 8 Am. Which is kind of a few like an hour or 2 after our AI meeting, so it’s more likely hour for you, and I’ll jump to. I need to jump to the Pm. Meeting, I totally forgot

439 00:32:48.710 00:32:49.790 Miguel de Veyra: Okay. Okay.

440 00:32:49.790 00:32:53.639 Amber Lin: Okay, thank you, Miguel. I’ll work on it more alrighty. Bye-bye.

441 00:32:53.640 00:32:54.050 Miguel de Veyra: Bye, bye.

442 00:32:54.050 00:32:54.770 Amber Lin: Good night.