Meeting Title: Mattermore Project Retro Date: 2025-07-11 Meeting participants: Amber Lin, Annie Yu, Luke Daque


WEBVTT

1 00:04:59.540 00:05:00.920 Luke Daque: Hello! Hello!

2 00:05:02.900 00:05:03.710 Amber Lin: Hi.

3 00:05:03.710 00:05:04.760 Annie Yu: Hello!

4 00:05:05.640 00:05:09.689 Amber Lin: Hello! This is a. This is a easy meeting.

5 00:05:09.880 00:05:13.430 Luke Daque: It’s just for us to talk about how things went.

6 00:05:14.620 00:05:15.229 Luke Daque: Yeah, I see.

7 00:05:15.230 00:05:18.299 Amber Lin: So, yeah, I can hear you.

8 00:05:18.700 00:05:22.730 Luke Daque: Can’t you let me check.

9 00:05:27.540 00:05:32.460 Amber Lin: So there’s this is just so we do. A oh.

10 00:05:32.460 00:05:33.140 Luke Daque: Hear you now.

11 00:05:33.140 00:05:34.410 Amber Lin: Project.

12 00:05:34.640 00:05:38.200 Amber Lin: Yeah, I can hear you. We can. And can you hear, Luke?

13 00:05:39.190 00:05:39.930 Annie Yu: Yes.

14 00:05:41.190 00:05:41.980 Amber Lin: Okay.

15 00:05:42.370 00:05:47.270 Amber Lin: Oh, wait. Where is this?

16 00:05:50.790 00:05:53.170 Amber Lin: Oh, interesting.

17 00:05:53.880 00:05:54.800 Amber Lin: Okay.

18 00:06:00.160 00:06:04.769 Amber Lin: Okay. I wanted us to do a project project.

19 00:06:05.060 00:06:10.040 Amber Lin: Retro. I think we could do wanna try this?

20 00:06:13.320 00:06:14.610 Amber Lin: So

21 00:06:19.850 00:06:30.489 Amber Lin: this is just so that we think about how we did as a as a team for this project, and how we can take our learnings and use it for the future.

22 00:06:31.460 00:06:43.009 Amber Lin: So if you guys can, I would love for us to take some time. I hope you all can see the whiteboard, and you can add a sticky note, I think, by by pressing N

23 00:06:43.310 00:06:51.150 Amber Lin: also. So add some. Add some stickies to

24 00:06:51.540 00:06:58.159 Amber Lin: these bubbles, and then we’ll talk about it after, say.

25 00:06:58.620 00:07:04.170 Amber Lin: 5 to 8 min, 5 min. All said. Is Heimer.

26 00:07:04.690 00:07:07.479 Amber Lin: Can everybody access the whiteboard.

27 00:07:10.700 00:07:13.100 Annie Yu: I think so. Yes.

28 00:07:14.140 00:07:15.020 Amber Lin: Great.

29 00:07:15.310 00:07:18.280 Luke Daque: Where? Where can I find this.

30 00:07:18.950 00:07:21.400 Luke Daque: It’s just in this, in the zoom.

31 00:07:21.400 00:07:23.139 Amber Lin: Yeah, it’s just in the zoom. I thought it was.

32 00:07:23.140 00:07:27.619 Luke Daque: Cool. Yeah, I thought there was like, I needed to go somewhere. But yeah.

33 00:07:27.620 00:07:32.950 Amber Lin: Yeah, usually there is. But I think this is okay.

34 00:07:33.320 00:07:37.060 Amber Lin: I started the timer 5 min. I’ll I’ll write some things down.

35 00:07:46.403 00:07:48.526 Luke Daque: Trying to remember what we did.

36 00:07:59.780 00:08:03.539 Amber Lin: I guess I we can also have a section for

37 00:08:04.300 00:08:08.099 Amber Lin: like didn’t like. If you want to put anything there.

38 00:08:09.570 00:08:13.149 Annie Yu: Oh, wait! Are we focusing on one section at a time? Is that.

39 00:08:13.150 00:08:20.940 Amber Lin: No, just just put in whatever I added like didn’t like section at the top, because there’s some things I did not like.

40 00:08:22.620 00:08:23.170 Amber Lin: Hi.

41 00:08:23.170 00:08:27.119 Luke Daque: Yes, we that can be in the law for right, but like it’s just.

42 00:08:27.120 00:08:31.962 Amber Lin: True, but it’s so positive. I have negative emotions.

43 00:08:38.250 00:08:38.890 Luke Daque: Huh!

44 00:09:04.530 00:09:08.980 Luke Daque: Wow! So many didn’t like no umbrella.

45 00:09:09.426 00:09:11.210 Amber Lin: It’s just for me.

46 00:09:12.990 00:09:14.999 Annie Yu: No, same. Here.

47 00:09:32.490 00:09:35.729 Annie Yu: wait! What’s which ones didn’t like is that.

48 00:09:35.730 00:09:38.160 Amber Lin: Guys at the top. It’s above liked.

49 00:09:38.160 00:09:39.230 Annie Yu: Oh, okay.

50 00:09:39.230 00:09:44.449 Amber Lin: Yeah, I just made another one. So my 1st time using this template. So I don’t know either.

51 00:09:44.450 00:09:45.220 Annie Yu: Okay.

52 00:10:09.840 00:10:10.530 Luke Daque: Oh!

53 00:12:33.650 00:12:36.220 Amber Lin: Okay, do we need 2 more minutes.

54 00:12:39.494 00:12:40.179 Annie Yu: Sure!

55 00:12:40.490 00:12:41.240 Amber Lin: Okay.

56 00:14:28.520 00:14:31.889 Annie Yu: By the way, can you guys hear me type or.

57 00:14:31.890 00:14:32.265 Amber Lin: Oh!

58 00:14:32.640 00:14:33.500 Annie Yu: No yes.

59 00:14:33.500 00:14:36.729 Luke Daque: No, no, we can’t hear you.

60 00:14:37.190 00:14:43.869 Annie Yu: I feel like I always type very loudly, and I always wonder if others can hear. Wait, so you hear nothing.

61 00:14:43.870 00:14:45.840 Amber Lin: Nope, no anything.

62 00:14:45.840 00:14:51.440 Annie Yu: Yeah, I guess zoom is doing a good job in like suppressing typing noises or something.

63 00:14:51.440 00:14:52.070 Annie Yu: Okay.

64 00:14:52.350 00:14:58.980 Amber Lin: Okay, can we take 2 min to read what everybody

65 00:14:59.535 00:15:12.654 Amber Lin: wrote, and also add stamps, or just add, say, I think if you click, click on it. If you click on the note, you can add an emoji. So if you agree with it,

66 00:15:13.270 00:15:18.839 Amber Lin: add a action to it, so I’ll set 2 min. We’ll read everything, and we’ll discuss.

67 00:16:24.760 00:16:28.720 Luke Daque: We all have 10 min, it looks like, and then there’s another retro.

68 00:16:32.405 00:16:44.060 Amber Lin: but it it will be alright. ABC won’t take too long. It just we should talk about like there’s 1 or 2 things we should talk about, that’s all. If we go over this. It’s okay.

69 00:16:44.560 00:16:54.559 Amber Lin: actually, that’s what I that’s what I’ll do. Keep doing this. I’ll move the ABC back 10 min. It can. It can just be like.

70 00:16:56.410 00:16:58.120 Amber Lin: 20 min retro.

71 00:17:18.569 00:17:25.230 Amber Lin: Okay, let’s let’s regroup.

72 00:17:29.420 00:17:30.330 Amber Lin: Okay.

73 00:17:33.760 00:17:40.379 Amber Lin: okay, I’m gonna put on the right? I’m gonna say, these are are.

74 00:17:41.170 00:17:42.860 Luke Daque: Takeaways.

75 00:17:43.260 00:17:46.970 Amber Lin: And we can put it there.

76 00:17:55.580 00:18:09.010 Amber Lin: I think this does any. Okay, we only have 2 people. I’ll let everyone talk about what they think, and then I’ll write things down as you talk. So Annie, or Luke, one of you, go ahead.

77 00:18:12.190 00:18:21.652 Annie Yu: Yeah, I think after reading through everyone’s notes, I feel like we have pretty like there’s consensus.

78 00:18:22.470 00:18:22.800 Luke Daque: Okay.

79 00:18:22.800 00:18:33.179 Annie Yu: I think from the beginning what we like really lacked was a clear requirement from from the client, and I feel like they were just

80 00:18:33.360 00:18:39.740 Annie Yu: I think, initially, we thought, okay, we were just gonna deliver some visuals. And then

81 00:18:40.010 00:18:45.640 Annie Yu: slowly, we realized, okay, they didn’t really know what they wanted. So there was no like

82 00:18:46.190 00:19:01.711 Annie Yu: clear steps and requirements, and I feel like the client just threw lots, lots of different ideas at different times, so it was hard to like, be grounded to like a certain thing at a time, but also feel like

83 00:19:02.340 00:19:13.990 Annie Yu: During the middle of the project we did that kind of regroup session. It was really helpful. I don’t think we have any more like hiccups. After that I think things went very smoothly.

84 00:19:15.890 00:19:21.330 Amber Lin: Yeah, I I totally agree. And I mean.

85 00:19:21.540 00:19:34.827 Amber Lin: what the regroup tells us is probably that we should raise these problems more often like if and

86 00:19:35.550 00:19:43.540 Amber Lin: point out when we need a regroup, and probably even as a

87 00:19:43.640 00:19:56.760 Amber Lin: as a step, we could have, like a mid project check in or like every sprint check in

88 00:19:57.840 00:20:00.059 Amber Lin: is what I what I just thought of.

89 00:20:01.760 00:20:03.329 Amber Lin: What do you think.

90 00:20:05.900 00:20:12.630 Luke Daque: Yeah, I definitely agree. Yeah, it looks like we do have the same sentiment, like everybody

91 00:20:12.810 00:20:21.930 Luke Daque: is not very happy with, like how the client was giving us the requirements, and, like even the access levels, like it

92 00:20:22.220 00:20:25.379 Luke Daque: was one of the biggest blockers, or, like.

93 00:20:26.220 00:20:28.629 Luke Daque: Yeah, like that we had for like.

94 00:20:28.750 00:20:31.510 Luke Daque: it even spanned for a couple of weeks. I guess.

95 00:20:32.020 00:20:38.500 Luke Daque: So, yeah, and yeah, what personally, like, I was just like.

96 00:20:39.163 00:20:41.216 Luke Daque: I think you already know. But like

97 00:20:41.640 00:20:54.650 Luke Daque: I wasn’t really happy with like doing the data models with the synthetic data that we had, and because I was very sure that what we were gonna do it again differently when the real data comes, because it’s never

98 00:20:54.840 00:21:02.339 Luke Daque: we won’t really know what it looks like, and like any errors or issues that we encounter, and stuff like that. But.

99 00:21:02.520 00:21:03.020 Amber Lin: Yeah.

100 00:21:03.020 00:21:06.929 Luke Daque: Yeah, what I also do really like, though, was like

101 00:21:07.500 00:21:16.030 Luke Daque: especially when Annie was on leave, and we were able to still work on like updating the power bi stuff. So basically, like everybody was

102 00:21:16.220 00:21:21.039 Luke Daque: able to help each other out and not just like it’s not just like one person.

103 00:21:22.084 00:21:25.029 Luke Daque: I don’t know how to explain. It’s like we’re not

104 00:21:26.151 00:21:29.940 Luke Daque: counting on just one person to do a certain

105 00:21:30.190 00:21:32.919 Luke Daque: task and stuff like that. So that’s a good.

106 00:21:33.360 00:21:33.760 Amber Lin: Yeah.

107 00:21:33.760 00:21:38.379 Luke Daque: And improvement for like the team dynamics and stuff like that. So yeah.

108 00:21:38.380 00:21:43.997 Amber Lin: Oh, that’s so. That’s so. Right. I wanna write that down. So

109 00:21:45.710 00:22:00.320 Amber Lin: so that means that we have like still overlap redundancy to cover somewhere. That’s on leave.

110 00:22:02.490 00:22:11.209 Amber Lin: So I wrote down for the your last point. I wrote down. So when we are in the future, when we’re staffing the teams to have that

111 00:22:11.370 00:22:19.449 Amber Lin: skill set, or even as a good team, professional development.

112 00:22:19.570 00:22:22.480 Amber Lin: That’s something we could do. And

113 00:22:22.840 00:22:33.740 Amber Lin: the other one i i’ve really, I’m glad that you pointed out that the synthetic data is probably not really aligned.

114 00:22:36.290 00:22:43.170 Amber Lin: with the what real data will come in. Oh.

115 00:22:46.100 00:22:49.339 Amber Lin: wait! I feel like I didn’t summarize your point.

116 00:22:50.050 00:22:56.779 Annie Yu: On this one. I think one thing that I actually just learned toward the end of the project was

117 00:22:57.060 00:23:01.700 Annie Yu: cause. I like totally agree with Luke. I think when.

118 00:23:02.740 00:23:08.730 Annie Yu: like, initially, I thought, okay, we were just doing the synthetic data. But eventually we’ll get the actual data, and then

119 00:23:08.930 00:23:32.830 Annie Yu: everything will require like a redo like looks at. And it’s not just like a plug and play. When actually that comes in, we’ll definitely have to spend more time there. So I feel like a like a waste of time working on synthetic data that like for every step. But then I think I did not know until the end of the project that.

120 00:23:33.280 00:23:37.869 Annie Yu: You were never gonna get access to actual data? Or was that.

121 00:23:37.870 00:23:38.610 Luke Daque: Yeah.

122 00:23:38.610 00:23:40.679 Annie Yu: Yeah, I think I just learned that

123 00:23:41.165 00:23:44.519 Annie Yu: after I came back, or like before I left.

124 00:23:44.690 00:23:45.650 Annie Yu: So was.

125 00:23:45.650 00:23:45.980 Amber Lin: Oh!

126 00:23:45.980 00:23:56.689 Annie Yu: Something that changed during the project or the initial expectation was always that we we were gonna only work on synthetic synthetic data.

127 00:23:58.020 00:24:10.370 Amber Lin: Yeah, I I really agree with that. I think they also one. The client also didn’t know. So then they weren’t able. They wanted us to assume that we’ll get the real data. But I think

128 00:24:10.780 00:24:28.180 Amber Lin: we should point out the difference in in our project approach if we knew we won’t be getting

129 00:24:29.830 00:24:34.929 Amber Lin: real data. Cause then, Luke, I don’t think you would feel that you’re working.

130 00:24:35.545 00:24:36.160 Annie Yu: Times.

131 00:24:36.160 00:24:44.589 Amber Lin: Time. Because that’s we’re we’re getting paid for just making synthetic data work. And I also think there was another thing of like

132 00:24:44.880 00:24:46.330 Amber Lin: the project

133 00:24:46.600 00:24:54.710 Amber Lin: purpose. Because I think for a long time all 3 of us were just really really confused on, like.

134 00:24:54.870 00:25:03.840 Amber Lin: why, we’re even doing this project, especially when we thought they were getting the real client data. I was like, why are you bringing us on now

135 00:25:04.270 00:25:14.569 Amber Lin: for just to just to fiddle around and make you feel safer like. I didn’t really understand why they were throwing money away. But I was like, if they’re paying us like, okay.

136 00:25:14.570 00:25:19.699 Annie Yu: To be fair. I think, Utop initiated that I think, proposed that, like.

137 00:25:19.700 00:25:24.529 Amber Lin: I know. Okay. So so he if he knew, then he didn’t tell us like.

138 00:25:24.929 00:25:25.330 Annie Yu: Okay.

139 00:25:25.760 00:25:34.060 Amber Lin: Like, why are we doing this project like? Why our clients

140 00:25:34.540 00:25:47.830 Amber Lin: spending money? I don’t think either of us had, like consensus of the project purpose. I don’t think we had consensus of like how this project would be built out.

141 00:25:49.540 00:25:59.050 Amber Lin: like I. I feel like we kind of knew that we needed the data, and then we needed the modeling, but that it was so high level that we didn’t have a clear plan.

142 00:26:00.560 00:26:01.370 Annie Yu: Yeah.

143 00:26:02.370 00:26:07.639 Amber Lin: So that’s the that’s the thing.

144 00:26:08.580 00:26:17.470 Amber Lin: Yeah. And oh, going back to Annie to your 1st one, I think that’s what we all agree with is, we really should get the requirements

145 00:26:17.600 00:26:27.270 Amber Lin: in place as before we start, and

146 00:26:28.610 00:26:41.209 Amber Lin: and if they require anything else, they need to officially request scope, change.

147 00:26:41.370 00:26:51.250 Amber Lin: cause. I I still remember that meeting where he was just talking to you directly. And then he was like this, that that and I was like, what the what the hell is going on.

148 00:26:52.130 00:26:59.900 Amber Lin: It was like he just had this random request, and it it was

149 00:27:00.090 00:27:17.390 Amber Lin: out of scope from what they originally requested, because they never requested that. But now he’s saying that, and because we never confirmed that that was our original scope. We kind of just had to do what he what he said. So we need something to defend like our work.

150 00:27:19.660 00:27:20.420 Amber Lin: Yeah.

151 00:27:22.130 00:27:24.823 Annie Yu: I think we definitely did some detour there.

152 00:27:25.160 00:27:25.940 Amber Lin: Yeah.

153 00:27:32.660 00:27:39.070 Amber Lin: And then think in terms of like just project management.

154 00:27:39.970 00:27:44.270 Amber Lin: More communications are helpful.

155 00:27:47.110 00:27:56.420 Amber Lin: even if they don’t respond. I can say that I did communicate, and they will read it, but they most of the time don’t respond. And also to

156 00:27:57.950 00:27:59.600 Amber Lin: require.

157 00:28:09.630 00:28:16.699 Amber Lin: okay, I think that’s our. That’s our takeaways. Is there anything else that

158 00:28:16.900 00:28:20.349 Amber Lin: you would say if someone were to do a future project?

159 00:28:22.250 00:28:25.869 Amber Lin: What would you say? We we would take away from this

160 00:28:26.250 00:28:34.659 Amber Lin: a future project or a client similar to this, where maybe just about the type of client we take and stuff just any any comments.

161 00:28:36.611 00:28:43.110 Annie Yu: For me one other learning, and I actually, I don’t think it’s a black and white thing, but.

162 00:28:43.110 00:28:43.510 Amber Lin: Hello!

163 00:28:43.510 00:28:52.239 Annie Yu: Like after like that midpoint. I’m like I refuse to talk to Matthew from now.

164 00:28:52.240 00:28:55.820 Amber Lin: Saw you hop off, girl. I saw you on the last meeting.

165 00:28:55.820 00:28:56.550 Annie Yu: And I.

166 00:28:56.550 00:28:59.101 Amber Lin: John, you saw his face, and you left.

167 00:28:59.420 00:29:03.789 Annie Yu: No, yeah. And I stand by that. I’m like, I feel like, because

168 00:29:04.050 00:29:31.110 Annie Yu: how I had to talk to him. It led to so much miscommunication. So I also remember telling you, Amber, I’m I’m just gonna talk to you from now on. You’re you’re my Pm, you. You communicate with them. But I feel like in different projects. There are always times that like in Eden. Sometimes I still have to talk to a stakeholder, which is fine, I think, because they have a very clear question, that we can just directly communicate.

169 00:29:31.110 00:29:31.500 Amber Lin: Oh!

170 00:29:31.500 00:29:42.659 Annie Yu: On. So I feel like it’s not black and white. But when I think for me it’s like when the client is not clear himself. I’m not gonna talk to him.

171 00:29:43.020 00:29:48.560 Amber Lin: And okay, yeah, let me create one. So.

172 00:29:48.941 00:29:51.989 Annie Yu: Yeah, you saw me. I also like.

173 00:29:51.990 00:29:52.590 Amber Lin: It’s so.

174 00:29:52.590 00:30:01.415 Annie Yu: I am. I was seeing the names I’m like, Okay, I don’t recognize this person and embers here. Looks not here. I wish it’s not here. Okay. I’m out.

175 00:30:04.243 00:30:12.990 Amber Lin: So only only let engineers clients

176 00:30:13.220 00:30:16.829 Amber Lin: talk to Engineer Luke. What about you?

177 00:30:20.050 00:30:26.630 Luke Daque: I don’t know like I I wasn’t there in that meeting or something, but I can understand Annie’s point.

178 00:30:28.600 00:30:30.000 Luke Daque: But it also

179 00:30:30.460 00:30:34.610 Luke Daque: that could. Also, I don’t know like it. It can mean 2 things right. It can be

180 00:30:34.750 00:30:43.010 Luke Daque: a good learning experience for growth, for the engineers as well, and data analysts, and they and stuff like that

181 00:30:43.610 00:30:50.260 Luke Daque: in terms of communication. But yeah, it’s all it’s. It’s difficult, like, it has its

182 00:30:51.830 00:30:54.359 Luke Daque: like pros and cons, I guess

183 00:30:54.820 00:30:59.140 Luke Daque: it’s not. All. People are very good at like communicating. And

184 00:30:59.830 00:31:03.889 Luke Daque: yeah, it could just lead to misunderstanding like Annie mentioned.

185 00:31:04.910 00:31:16.330 Annie Yu: Like if it’s about still about figuring out requirements. That’s something that’s where I like. I don’t want to be. But if it’s something we already we have already.

186 00:31:16.330 00:31:17.060 Amber Lin: Oh!

187 00:31:17.060 00:31:19.730 Annie Yu: Delivering. I feel like that’s.

188 00:31:19.730 00:31:20.470 Luke Daque: Yeah.

189 00:31:20.470 00:31:21.170 Annie Yu: Place where we.

190 00:31:21.170 00:31:22.890 Luke Daque: That’s a good point. Yeah.

191 00:31:24.530 00:31:35.460 Amber Lin: Get caught with figuring out requirements with the client. It should be

192 00:31:39.340 00:31:43.780 Amber Lin: so. The sales tech lead and Pm. Should figure out the requirements. I agree?

193 00:31:44.642 00:32:08.549 Amber Lin: I think. Oh, another thing that I remembered we should escalate internally first, st before we escalate to the client. I think we did a really good job later on, of escalating to me, and then to away internally before the client cause some of the things we just need another pair of eyes to look at it, and we’re like, Oh, never mind.

194 00:32:08.550 00:32:24.780 Amber Lin: and then the client will get will get really annoyed if we keep asking them those questions when we can solve it internally. So I think that’s just like a team charter, like team agreement thing that we will. We will implement for new projects that’s work at what I can think of

195 00:32:24.820 00:32:29.820 Amber Lin: and like, I guess, similarly, like to like SAI,

196 00:32:30.090 00:32:33.650 Amber Lin: if needed, like same thing for that.

197 00:32:34.710 00:32:36.600 Amber Lin: That’s what I can think of.

198 00:32:37.880 00:32:38.969 Luke Daque: That makes sense.

199 00:32:40.150 00:32:41.660 Amber Lin: Yeah, okay.

200 00:32:41.930 00:32:57.089 Amber Lin: I mean, that’s the close of the project. Thank you. Everybody. I think we had a lot of learnings from this client because it was a it was a. It was a bumpy ride, and I I really enjoy working with both of you.

201 00:32:57.750 00:32:58.900 Annie Yu: Same here, and.

202 00:32:58.900 00:32:59.360 Amber Lin: Thanks.

203 00:32:59.580 00:33:03.409 Annie Yu: What was the final accession about.

204 00:33:03.870 00:33:06.120 Amber Lin: Oh, they had an in-house.

205 00:33:06.680 00:33:15.229 Amber Lin: this data, scientists come on. So it was just for me to show him. Hey, this is where things are. This is what it looks like.

206 00:33:15.340 00:33:18.180 Amber Lin: It’s just like a final handoff.

207 00:33:18.480 00:33:19.509 Annie Yu: Hmm, hmm.

208 00:33:19.690 00:33:20.550 Amber Lin: Yeah.

209 00:33:24.880 00:33:26.430 Amber Lin: don’t you? All?

210 00:33:26.570 00:33:30.699 Amber Lin: Well, we’re all in the next retro.

211 00:33:32.160 00:33:41.419 Amber Lin: yeah, Annie, I feel like you don’t have to be on necessarily, because there’s not really much that you were asked to do this this time.

212 00:33:43.040 00:33:45.614 Annie Yu: Yeah, I can drink the next one. Yeah.

213 00:33:45.900 00:34:00.300 Amber Lin: Okay, you can skip it, I think. Mostly Uta wanted us like as a team to talk about like. Why, why, the dashboard was left out so long. But I think that’s it.

214 00:34:00.860 00:34:01.360 Amber Lin: So.

215 00:34:01.360 00:34:01.820 Luke Daque: Okay.

216 00:34:01.820 00:34:03.809 Amber Lin: We’ll hop to that one.

217 00:34:04.310 00:34:07.239 Luke Daque: Sounds good. See you there? Bye-bye.

218 00:34:07.240 00:34:08.567 Amber Lin: You too, bye.