Meeting Title: Javy-Project-Internal-Review Date: 2024-11-11 Meeting participants: Robert Tseng, Luke Daque, Payas Parab
WEBVTT
1 00:05:54.750 ⇒ 00:05:55.589 Robert Tseng: Hey! Luke!
2 00:05:57.430 ⇒ 00:05:58.920 Luke Daque: Hey, Robert, how’s it going.
3 00:05:59.660 ⇒ 00:06:01.670 Robert Tseng: Good! How are you? How was your weekend.
4 00:06:02.410 ⇒ 00:06:07.989 Luke Daque: Yeah, doing. Great. The weekend was fine. We watched a circus. So yeah, it was cool.
5 00:06:08.290 ⇒ 00:06:09.150 Robert Tseng: Oh, nice!
6 00:06:09.980 ⇒ 00:06:12.650 Luke Daque: Yeah, it’s been a while since we watched one. So
7 00:06:13.710 ⇒ 00:06:14.169 Luke Daque: yeah.
8 00:06:15.080 ⇒ 00:06:15.970 Luke Daque: pretty fun.
9 00:06:16.440 ⇒ 00:06:24.139 Robert Tseng: Yeah, I can’t remember. I think the last one I went to is probably last year. Watch some performance in in Vegas. I think.
10 00:06:24.600 ⇒ 00:06:26.159 Luke Daque: Wow! Nice.
11 00:06:27.450 ⇒ 00:06:30.529 Luke Daque: I think, prior to last week. The last one I
12 00:06:30.700 ⇒ 00:06:33.700 Luke Daque: saw was when I was still a little kid. So
13 00:06:33.810 ⇒ 00:06:36.390 Luke Daque: it’s pretty. It’s been a long time.
14 00:06:36.670 ⇒ 00:06:37.515 Robert Tseng: Yeah.
15 00:06:39.120 ⇒ 00:06:46.690 Robert Tseng: Do you? Do you go up like, do you go around like the islands often, or like the North Island? Or do you usually just stay in mid to now.
16 00:06:47.604 ⇒ 00:06:49.279 Luke Daque: Yeah, I pretty much should.
17 00:06:49.410 ⇒ 00:06:58.479 Luke Daque: Yeah. I’ve been trying to like explore the Philippines Islands. I’ve been doing like island hopping and stuff like that going to the Beaches. Pretty fun.
18 00:06:59.090 ⇒ 00:06:59.830 Robert Tseng: Nice.
19 00:07:00.030 ⇒ 00:07:00.910 Luke Daque: Yeah, I.
20 00:07:00.910 ⇒ 00:07:03.319 Robert Tseng: I’m assuming it’s a good time to be there right now.
21 00:07:04.240 ⇒ 00:07:04.890 Luke Daque: Oh!
22 00:07:04.890 ⇒ 00:07:09.760 Robert Tseng: No, not super rainy and the weather is probably better in the fall.
23 00:07:10.410 ⇒ 00:07:13.190 Luke Daque: Yeah. Well, I guess it depends. Like.
24 00:07:13.290 ⇒ 00:07:19.469 Luke Daque: usually it’s summer times the the best time. But it’s pretty hot, though, like during the summer.
25 00:07:19.650 ⇒ 00:07:20.174 Luke Daque: It’s
26 00:07:20.830 ⇒ 00:07:23.209 Luke Daque: There’s like the least amount of rain.
27 00:07:23.430 ⇒ 00:07:24.899 Luke Daque: Is the rain really like.
28 00:07:25.060 ⇒ 00:07:28.029 Luke Daque: yeah. Destroys the the fun or something. But
29 00:07:29.110 ⇒ 00:07:29.790 Luke Daque: yeah.
30 00:07:30.420 ⇒ 00:07:31.240 Robert Tseng: Okay.
31 00:07:31.630 ⇒ 00:07:32.540 Robert Tseng: hey? Bias.
32 00:07:32.540 ⇒ 00:07:33.910 Payas Parab: Hey? How are you guys.
33 00:07:34.350 ⇒ 00:07:35.659 Robert Tseng: Good! How are you?
34 00:07:35.660 ⇒ 00:07:37.080 Payas Parab: I’m doing all right.
35 00:07:39.160 ⇒ 00:07:41.920 Robert Tseng: Alright. I don’t think Nico’s here today, so I think it’ll.
36 00:07:41.920 ⇒ 00:07:42.380 Luke Daque: Yeah.
37 00:07:42.380 ⇒ 00:07:43.820 Robert Tseng: Probably be this group.
38 00:07:44.480 ⇒ 00:07:46.991 Payas Parab: The brain forge holiday for you guys. Veterans day.
39 00:07:47.270 ⇒ 00:07:47.655 Luke Daque: No.
40 00:07:48.040 ⇒ 00:07:48.640 Payas Parab: About.
41 00:07:50.810 ⇒ 00:07:53.780 Luke Daque: Has been like asking for this holiday for a while.
42 00:07:55.030 ⇒ 00:07:57.039 Payas Parab: I think he’s in the Us. Actually.
43 00:07:57.180 ⇒ 00:07:57.860 Luke Daque: Yeah.
44 00:07:58.840 ⇒ 00:07:59.600 Payas Parab: Oh.
45 00:08:00.350 ⇒ 00:08:10.419 Payas Parab: awesome! There are only 2 things I kind of wanted to check in with you on I have the. I made a pull request about updating the key Kpis, dashboard so that we don’t have
46 00:08:11.220 ⇒ 00:08:12.955 Payas Parab: put the sequel in
47 00:08:14.130 ⇒ 00:08:25.329 Payas Parab: inside Meta base. I don’t know. I don’t remember what full request number is, but I was hoping if you could review that that’d be great, so I can just recreate all those charts. Oh, you merged it.
48 00:08:25.730 ⇒ 00:08:26.460 Luke Daque: No, and.
49 00:08:26.460 ⇒ 00:08:28.059 Payas Parab: But yeah, oh, okay.
50 00:08:28.060 ⇒ 00:08:29.150 Luke Daque: Just checked it.
51 00:08:30.570 ⇒ 00:08:33.759 Luke Daque: Yeah, yeah, I can. I can merge this.
52 00:08:33.760 ⇒ 00:08:44.790 Payas Parab: Yeah, 37. I would just double check it because I’ve never done the that context before that, like the that style of sequel code. So I just wanna make sure it all looks right. But it’s just recreating
53 00:08:45.160 ⇒ 00:08:46.607 Payas Parab: those key metrics.
54 00:08:47.090 ⇒ 00:08:47.730 Luke Daque: Yeah.
55 00:08:47.730 ⇒ 00:08:54.970 Payas Parab: So that would be, that would be awesome. The other thing is the refunds. I think, Tom, and you guys kind of close that I saw that Pr got merged.
56 00:08:55.020 ⇒ 00:09:03.659 Payas Parab: and you kind of like feel good about being able to explain the logic on it and like where it’s at and why it is different than what they may see.
57 00:09:04.560 ⇒ 00:09:05.380 Luke Daque: Right.
58 00:09:05.380 ⇒ 00:09:13.770 Payas Parab: So good to go on that one thing I I realized I didn’t send was the the the spreadsheet. The the last item would be the
59 00:09:13.820 ⇒ 00:09:20.910 Payas Parab: the spreadsheet for the assumptions and creating that in 5 tran or pulling it in through 5 tran. I can coordinate with you
60 00:09:20.950 ⇒ 00:09:25.470 Payas Parab: offline here. Just trying to get the
61 00:09:25.680 ⇒ 00:09:29.640 Payas Parab: the spreadsheets into snowflake. So we can just build a basic version.
62 00:09:29.870 ⇒ 00:09:36.840 Luke Daque: Right? Yeah, if you can get me like, if you can send me the spreadsheet. Yeah, I can. I can create it. I can link it in Snowflake.
63 00:09:37.210 ⇒ 00:09:37.599 Payas Parab: Got it.
64 00:09:37.600 ⇒ 00:09:38.400 Luke Daque: 5. Grand.
65 00:09:38.720 ⇒ 00:09:41.620 Payas Parab: And I just named the range right, and then it should be.
66 00:09:41.620 ⇒ 00:09:42.300 Luke Daque: Yeah.
67 00:09:43.360 ⇒ 00:09:43.880 Payas Parab: Perfect. I’ll.
68 00:09:43.880 ⇒ 00:09:45.979 Robert Tseng: We’ll just ask for access.
69 00:09:46.400 ⇒ 00:09:48.259 Payas Parab: No worries sharing it right now
70 00:09:49.590 ⇒ 00:09:51.730 Payas Parab: and then. Let me also share with you
71 00:09:53.350 ⇒ 00:10:00.299 Payas Parab: also. Wait. Your name’s Ryan. Right? You go by, Ryan, or do you go by? I get so confused like all the time.
72 00:10:00.460 ⇒ 00:10:08.990 Luke Daque: Yeah, I initially went with Ryan. But there’s another employee that’s also named Ryan. So I that’s why I named myself Luke in in the Zoom calls.
73 00:10:08.990 ⇒ 00:10:09.530 Payas Parab: Okay.
74 00:10:09.530 ⇒ 00:10:11.190 Robert Tseng: Oh, really. Okay.
75 00:10:11.190 ⇒ 00:10:12.230 Payas Parab: Sometimes that’s.
76 00:10:12.230 ⇒ 00:10:15.650 Luke Daque: That’s my second. Luke’s my second name. So yeah.
77 00:10:15.880 ⇒ 00:10:19.189 Robert Tseng: Oh, my bad! I’ve been calling you Luke this entire time.
78 00:10:19.470 ⇒ 00:10:20.440 Luke Daque: Yeah, that’s fine.
79 00:10:21.790 ⇒ 00:10:22.200 Payas Parab: Awesome.
80 00:10:23.940 ⇒ 00:10:30.159 Payas Parab: Alright. So I shared that. And I’ll name the ranges. I basically just pulled from the last 3 months. The top skews
81 00:10:30.270 ⇒ 00:10:40.419 Payas Parab: the top, whatever the top skews that are in the order line database. And then I pulled in the intermediate table you had for now. But what we’re gonna do is like I have it.
82 00:10:40.683 ⇒ 00:10:44.879 Payas Parab: And I can share my screen. Here is just like the key fields that we had in here.
83 00:10:44.970 ⇒ 00:10:55.272 Payas Parab: It’s just going to be like this is like the finance. Bro likes it as like a yellow with blue. So they can like update any of these. I’m just gonna like. Clean the sheet up a little bit, just to like make it more aesthetic.
84 00:10:55.720 ⇒ 00:10:56.290 Luke Daque: Yeah.
85 00:10:56.290 ⇒ 00:11:03.520 Payas Parab: And then what I’m also gonna do is set up at the very top. I’m gonna like, put in, which I need to do like default assumption.
86 00:11:03.580 ⇒ 00:11:09.202 Payas Parab: So that like, if there isn’t a skew that’s identified, then, like we, we have a way to handle it. Because
87 00:11:09.900 ⇒ 00:11:12.920 Payas Parab: He mentioned that that was it. But these are yeah. These are the
88 00:11:13.190 ⇒ 00:11:22.249 Payas Parab: top skews from the last 3 months. I don’t know if we maybe need to expand this right now. It’s just pulling in the averages of those key fields that came from the artifact.
89 00:11:22.430 ⇒ 00:11:23.050 Payas Parab: And then.
90 00:11:23.050 ⇒ 00:11:23.510 Luke Daque: Esha.
91 00:11:23.510 ⇒ 00:11:27.659 Payas Parab: We will just give this to them so that they can update that as needed.
92 00:11:28.300 ⇒ 00:11:29.070 Luke Daque: Okay.
93 00:11:29.570 ⇒ 00:11:30.680 Luke Daque: sounds good.
94 00:11:30.710 ⇒ 00:11:32.890 Luke Daque: Yeah. I’ll link this in.
95 00:11:32.890 ⇒ 00:11:34.500 Payas Parab: Yep. Awesome.
96 00:11:34.500 ⇒ 00:11:37.130 Luke Daque: Let you know once it’s it’s in Snowflake.
97 00:11:37.610 ⇒ 00:11:39.420 Payas Parab: Awesome. Great.
98 00:11:40.357 ⇒ 00:11:43.052 Payas Parab: Were there any items pending on my side
99 00:11:44.858 ⇒ 00:11:47.651 Luke Daque: You did send the number for
100 00:11:48.050 ⇒ 00:11:48.560 Payas Parab: The retry.
101 00:11:48.560 ⇒ 00:11:52.050 Luke Daque: Yeah. But yeah, I still haven’t looked into that in snow.
102 00:11:52.050 ⇒ 00:11:52.380 Payas Parab: Okay.
103 00:11:52.380 ⇒ 00:11:55.459 Luke Daque: Because, yeah, it doesn’t look like the numbers are matching.
104 00:11:55.510 ⇒ 00:11:58.849 Luke Daque: But but yeah, I have to look into that.
105 00:11:58.920 ⇒ 00:12:00.089 Luke Daque: And I think,
106 00:12:01.490 ⇒ 00:12:02.950 Luke Daque: I think
107 00:12:04.320 ⇒ 00:12:08.410 Luke Daque: Aman sent an update, I mean, asked for a couple of
108 00:12:08.490 ⇒ 00:12:15.747 Luke Daque: measures for the real George’s dashboard. I’ll be that’s what I’ve been working on as well, like I’m adding a a couple of
109 00:12:16.050 ⇒ 00:12:17.140 Payas Parab: Gorgeous.
110 00:12:17.140 ⇒ 00:12:17.760 Luke Daque: Yeah.
111 00:12:18.360 ⇒ 00:12:19.620 Payas Parab: I just wanna make sure that.
112 00:12:19.620 ⇒ 00:12:20.170 Luke Daque: There!
113 00:12:23.970 ⇒ 00:12:24.899 Payas Parab: wait. I wasn’t exactly.
114 00:12:24.900 ⇒ 00:12:28.770 Robert Tseng: Exactly sure which ones he was asking for. But anyway, sorry bias go ahead.
115 00:12:28.770 ⇒ 00:12:34.559 Payas Parab: No, no, I was gonna ask, are we? Are we like kind of like deprecating real completely from their side? So I just wanted to make sure.
116 00:12:34.560 ⇒ 00:12:37.240 Luke Daque: Oh, right? Yeah, I think we we talked about that right?
117 00:12:38.000 ⇒ 00:12:44.069 Payas Parab: I I just wanna make sure. Yeah, we we don’t cause I think Utah mentioned it felt to him like it was just confusing them.
118 00:12:44.550 ⇒ 00:12:45.270 Luke Daque: Yeah.
119 00:12:45.270 ⇒ 00:12:48.189 Payas Parab: To have multiple tools. I I don’t know if there’s like.
120 00:12:49.840 ⇒ 00:12:59.590 Payas Parab: is there a way we can potentially see what users have used the real dashboard and like, see if they’re actually using it. Cause I think Tom was feeling that it just creates confusion.
121 00:13:00.450 ⇒ 00:13:01.720 Payas Parab: Just wanna make sure.
122 00:13:02.160 ⇒ 00:13:06.600 Luke Daque: Yeah, I I’m not sure if there’s a way, but I can check but but based on
123 00:13:06.690 ⇒ 00:13:11.399 Luke Daque: a month’s message, it looks like it did look into the real dashboard and.
124 00:13:11.400 ⇒ 00:13:12.160 Payas Parab: Yeah.
125 00:13:12.370 ⇒ 00:13:13.130 Luke Daque: Yeah.
126 00:13:13.690 ⇒ 00:13:16.620 Payas Parab: Do they provide analytics? Does real provide analytics
127 00:13:16.710 ⇒ 00:13:18.480 Payas Parab: on dashboard? No?
128 00:13:24.970 ⇒ 00:13:25.840 Payas Parab: okay.
129 00:13:26.180 ⇒ 00:13:27.100 Payas Parab: Got it
130 00:13:27.640 ⇒ 00:13:31.609 Payas Parab: alright sweet. So I I think if they’re still like, kind of using that. But then.
131 00:13:31.980 ⇒ 00:13:42.049 Payas Parab: yeah, I need to the cog stuff. Whatever pulls in from the data we upload now right now, I’ll use that to build the cogs kind of like dash and view
132 00:13:43.066 ⇒ 00:13:48.879 Payas Parab: and then we’ll obviously, when they update the spreadsheet at 5 channel update it. So we’ll be good to go there.
133 00:13:49.110 ⇒ 00:13:49.740 Luke Daque: Cool.
134 00:13:49.740 ⇒ 00:13:56.800 Robert Tseng: Yeah, I think getting the cog stash like a v 1 to to them this week would be good just to give them something on the analytics side.
135 00:13:56.800 ⇒ 00:13:57.130 Payas Parab: Yep.
136 00:13:58.069 ⇒ 00:13:58.899 Robert Tseng: Otherwise.
137 00:13:59.040 ⇒ 00:14:09.519 Robert Tseng: Yeah, I think, wait, recharge. I didn’t really understand Nico’s update. What is it like? What are we? What are we waiting for there, like the sync, was already there, like it seems like again, really understand that.
138 00:14:09.730 ⇒ 00:14:20.840 Luke Daque: Yeah, the sinks already there. And it’s happening. It’s already in Snowflake. But when we looked into the data into the from the raw tables. It looks like there were only 13 orders or something. 16 orders, and.
139 00:14:20.840 ⇒ 00:14:24.409 Robert Tseng: Okay. So that’s is that still the case? Now I guess I haven’t looked. But.
140 00:14:24.410 ⇒ 00:14:28.240 Luke Daque: Yeah, it’s still the case now, unfortunately. So we’ll have to look into
141 00:14:28.950 ⇒ 00:14:34.350 Luke Daque: like, maybe we’re looking at the wrong folders, or I mean wrong tables, or maybe
142 00:14:34.670 ⇒ 00:14:37.260 Luke Daque: we’ll have to look into a different approach
143 00:14:37.670 ⇒ 00:14:38.650 Luke Daque: to
144 00:14:39.370 ⇒ 00:14:44.020 Luke Daque: integrate the data into Snowflake, because maybe it’s 5 grand that’s
145 00:14:44.310 ⇒ 00:14:47.469 Luke Daque: messing up or something. But yeah, we’ll. We’ll look into that.
146 00:14:48.250 ⇒ 00:14:48.830 Robert Tseng: Yeah.
147 00:14:50.400 ⇒ 00:14:51.100 Robert Tseng: okay.
148 00:14:52.120 ⇒ 00:14:55.210 Robert Tseng: I mean, I know that we were like trying to.
149 00:14:55.950 ⇒ 00:15:04.069 Robert Tseng: just like set expectations to them on around the ingestion. I guess he was thinking that 5 Chan was was like, gonna be very cheap. And it’s not
150 00:15:04.360 ⇒ 00:15:04.910 Luke Daque: Yeah.
151 00:15:04.910 ⇒ 00:15:05.450 Robert Tseng: Just
152 00:15:05.660 ⇒ 00:15:13.539 Robert Tseng: I wonder how much he’s paying for this cloud fair workers that are putting data into amplitude right now, like I I don’t know. Maybe I can ask that for him.
153 00:15:13.730 ⇒ 00:15:17.360 Payas Parab: 5 trend that does seem expensive, though right like I was looking at that. My cell phone.
154 00:15:17.360 ⇒ 00:15:17.750 Luke Daque: Yeah.
155 00:15:17.750 ⇒ 00:15:18.800 Payas Parab: Is that like.
156 00:15:18.930 ⇒ 00:15:24.819 Payas Parab: do you guys like negotiate have like a partner rate or something, too? Because I know you guys were looking at 5 Tran partnership.
157 00:15:24.820 ⇒ 00:15:30.090 Luke Daque: Yeah, I don’t think we are partners yet with 5 grand. But yeah, I think that’s what Wu-tam is working on.
158 00:15:30.090 ⇒ 00:15:31.969 Robert Tseng: 5. Fan is just expensive.
159 00:15:32.500 ⇒ 00:15:33.030 Luke Daque: Yeah.
160 00:15:33.030 ⇒ 00:15:33.670 Robert Tseng: Yeah.
161 00:15:33.940 ⇒ 00:15:34.560 Payas Parab: Okay.
162 00:15:34.810 ⇒ 00:15:46.090 Luke Daque: I did like disable a couple of tables that we were not using like from shopify and Amazon. So maybe we’ll have to disable a couple of other tables from the rest of the sources as well.
163 00:15:46.240 ⇒ 00:15:49.849 Luke Daque: the ones that we aren’t reuse reusing cause. Yeah, that’s
164 00:15:50.470 ⇒ 00:15:52.149 Luke Daque: it’s expensive.
165 00:15:52.150 ⇒ 00:15:57.799 Robert Tseng: Yeah, I mean, for their volumes, like, it makes sense to me that it was like 1,500.
166 00:15:58.120 ⇒ 00:16:12.150 Robert Tseng: yeah, with another client with 5 Tran. They had like a data source that was probably bringing in like 1.5 million events a month. And that was like 900 bucks. So you know, they’re they’re yeah. I’m not surprised that it came out so high.
167 00:16:13.745 ⇒ 00:16:17.980 Payas Parab: One other question I had to was sorry. This is like random, but the the like on the
168 00:16:18.070 ⇒ 00:16:45.180 Payas Parab: the cost assumption table. Right? We’re gonna pull that in, and it’s going to be its own kind of raw field right? And then will it flow into the intermediate order line and then ultimately into prod order line. Will everything be inside order line, or will it be done somewhere else? Is there like or cause we we don’t want to do any joins or anything, any sequel in Meta base? Right? So that which prod table will these assumptions ultimately flow through? I just wanna make sure I know.
169 00:16:45.440 ⇒ 00:16:48.690 Luke Daque: These are for cogs. Right? So they, these should
170 00:16:48.990 ⇒ 00:16:50.379 Luke Daque: flow into
171 00:16:50.540 ⇒ 00:16:53.100 Luke Daque: the the fact order line, and
172 00:16:53.290 ⇒ 00:16:54.130 Luke Daque: we’ll both
173 00:16:54.500 ⇒ 00:16:57.659 Luke Daque: borderline and orders eventually, just like
174 00:16:57.970 ⇒ 00:17:05.739 Luke Daque: order lines will have the products in them, and we can join them to the skews and get these averages in.
175 00:17:06.270 ⇒ 00:17:07.420 Payas Parab: Got it. Okay.
176 00:17:12.060 ⇒ 00:17:12.920 Payas Parab: awesome.
177 00:17:13.520 ⇒ 00:17:15.619 Payas Parab: Any other items here, or just
178 00:17:16.280 ⇒ 00:17:17.369 Payas Parab: we’re good.
179 00:17:18.952 ⇒ 00:17:22.279 Luke Daque: Let me see, I don’t think we have anything else.
180 00:17:23.869 ⇒ 00:17:33.989 Robert Tseng: Okay, well, I guess well, we’re gonna meet with them tomorrow. So I guess if we like, yeah, what do we do? We think we’ll get like some of this done by tomorrow to update Aman.
181 00:17:35.160 ⇒ 00:17:42.270 Luke Daque: Yeah, I should be able to get the cogs assumptions in. And yeah, I’ll I’ll update that. I just merged by us. Pr, as well.
182 00:17:42.270 ⇒ 00:17:43.030 Payas Parab: Okay, excellent.
183 00:17:43.030 ⇒ 00:17:44.200 Luke Daque: For the Kpis.
184 00:17:44.310 ⇒ 00:17:44.980 Luke Daque: Yep.
185 00:17:45.410 ⇒ 00:17:55.129 Payas Parab: And then for the cogs, the cogs. So if we set up that 5 Tran connector, do you think it’s feasible to get that broad order line data ready today or or no.
186 00:17:55.810 ⇒ 00:17:57.645 Luke Daque: Yeah, I can. I can work on that today.
187 00:17:57.850 ⇒ 00:18:01.731 Payas Parab: That’d be awesome cause. Then I can just quickly whip up the like, you know.
188 00:18:02.180 ⇒ 00:18:06.740 Payas Parab: like all the items right? It’s like like some dashboarding views, so that we have, like a 1
189 00:18:06.820 ⇒ 00:18:11.779 Payas Parab: on the cogs data inside, with the orders data to present them on tomorrow.
190 00:18:12.060 ⇒ 00:18:13.469 Luke Daque: Makes sense. Yeah, cool.
191 00:18:13.760 ⇒ 00:18:15.909 Luke Daque: Yeah, I can work on this after the call.
192 00:18:15.910 ⇒ 00:18:20.820 Payas Parab: Awesome. Let me know if you need any help. I’m happy to kind of dive in or make any changes directly as well.
193 00:18:21.130 ⇒ 00:18:21.790 Luke Daque: Sure.
194 00:18:22.160 ⇒ 00:18:23.700 Payas Parab: Alright, awesome.
195 00:18:24.170 ⇒ 00:18:25.300 Payas Parab: Cool guys.
196 00:18:25.840 ⇒ 00:18:27.420 Robert Tseng: Alright, bye.
197 00:18:27.420 ⇒ 00:18:28.020 Luke Daque: Buh-bye.