Meeting Title: AI Team Standup Date: 2025-04-29 Meeting participants: Uttam Kumaran, Amber Lin, Miguel De Veyra, Casie Aviles, Awaish Kumar
WEBVTT
1 00:00:10.660 ⇒ 00:00:12.690 Amber Lin: Hello! Again.
2 00:00:13.740 ⇒ 00:00:14.690 Casie Aviles: Inc.
3 00:00:15.180 ⇒ 00:00:16.570 Amber Lin: Alright hello!
4 00:00:16.950 ⇒ 00:00:18.670 Amber Lin: Oh, hello!
5 00:00:19.100 ⇒ 00:00:20.190 Uttam Kumaran: Hello!
6 00:00:21.020 ⇒ 00:00:21.790 Miguel de Veyra: Everyone.
7 00:00:22.438 ⇒ 00:00:24.109 Amber Lin: Waiting for a wish.
8 00:00:24.260 ⇒ 00:00:25.110 Uttam Kumaran: Okay.
9 00:00:26.320 ⇒ 00:00:28.610 Amber Lin: But I’m just gonna get started.
10 00:00:31.400 ⇒ 00:00:38.529 Amber Lin: Oh, yesterday I saw that we have some really really good process with the matter. More agent.
11 00:00:39.642 ⇒ 00:00:41.809 Amber Lin: We also had.
12 00:00:41.980 ⇒ 00:00:48.240 Amber Lin: I know we improved on the formatting for the slack agent. I just don’t know where that ticket is.
13 00:00:50.620 ⇒ 00:00:51.220 Amber Lin: Oh.
14 00:00:51.810 ⇒ 00:00:56.659 Miguel de Veyra: Yeah, I mean, it’s a bigger ticket. Yeah, it should be in progress.
15 00:00:58.250 ⇒ 00:00:58.930 Miguel de Veyra: Yeah.
16 00:01:01.362 ⇒ 00:01:02.930 Amber Lin: Okay, let’s just start.
17 00:01:02.930 ⇒ 00:01:06.820 Uttam Kumaran: For the for the sales. One. Yeah, I I think it’s like pretty.
18 00:01:06.940 ⇒ 00:01:14.329 Uttam Kumaran: Can you paste the link in here, Miguel, because maybe I, me and Robert can go play around with the prompt, too.
19 00:01:15.830 ⇒ 00:01:16.750 Miguel de Veyra: Okay. Sure.
20 00:01:17.330 ⇒ 00:01:19.710 Uttam Kumaran: You know, so that we don’t have to bother you guys.
21 00:01:20.150 ⇒ 00:01:24.240 Miguel de Veyra: Yeah, cause the prompt, for that is pretty. It’s pretty bare bones.
22 00:01:24.490 ⇒ 00:01:28.100 Uttam Kumaran: Yeah, if you can, just and then also like, how can I test it?
23 00:01:28.250 ⇒ 00:01:32.210 Uttam Kumaran: Or maybe like, maybe let’s spend 10 min at the end of this meeting we can walk through it.
24 00:01:32.810 ⇒ 00:01:33.690 Miguel de Veyra: Okay. Okay. Sure.
25 00:01:33.690 ⇒ 00:01:34.570 Uttam Kumaran: Okay. Okay.
26 00:01:36.120 ⇒ 00:01:40.500 Amber Lin: Walk here.
27 00:01:40.910 ⇒ 00:01:48.310 Amber Lin: Excuse me. Updates, here I saw I saw the Madam Robot. It’s awesome. What do you think is a
28 00:01:48.500 ⇒ 00:01:53.019 Amber Lin: what do you need cause? I know you kind of wanted feedback from the different people.
29 00:01:54.410 ⇒ 00:01:56.569 Casie Aviles: Yeah, I did that.
30 00:01:57.301 ⇒ 00:02:01.020 Amber Lin: The team working on matter more on the agent. So.
31 00:02:01.330 ⇒ 00:02:03.830 Casie Aviles: Yeah, it would be great if we could have some
32 00:02:04.320 ⇒ 00:02:10.350 Casie Aviles: feedback and some testing for that. So we make sure that it’s breaking
33 00:02:11.100 ⇒ 00:02:16.690 Casie Aviles: that as intended and based on what they need, if they need any more
34 00:02:18.045 ⇒ 00:02:24.200 Casie Aviles: features, or like any inaccurate responses from the bot.
35 00:02:24.690 ⇒ 00:02:30.329 Uttam Kumaran: Yeah. So one thing on this is probably any like the Mattimore team is
36 00:02:31.068 ⇒ 00:02:35.370 Uttam Kumaran: like, it’s Annie and Luke who are not the most senior folks.
37 00:02:35.610 ⇒ 00:02:39.180 Uttam Kumaran: So to give you guys context, I’m working with Kyle.
38 00:02:39.740 ⇒ 00:02:41.390 Uttam Kumaran: Just close my door one second.
39 00:02:48.010 ⇒ 00:02:58.890 Uttam Kumaran: I’m working with Kyle and demalade on a like pretty expansive, like data platform documentation project
40 00:02:59.598 ⇒ 00:03:03.580 Uttam Kumaran: which has like a ton of ties into this work.
41 00:03:05.290 ⇒ 00:03:07.570 Uttam Kumaran: I’m just gonna share it with you.
42 00:03:11.230 ⇒ 00:03:16.820 Uttam Kumaran: Yeah, I’ll just I’m just gonna share it here in zoom
43 00:03:29.850 ⇒ 00:03:30.919 Amber Lin: Oh, my God!
44 00:03:32.040 ⇒ 00:03:38.250 Uttam Kumaran: So part of this, and it’s not done yet. But part of this is basically enabling.
45 00:03:38.720 ⇒ 00:03:42.979 Uttam Kumaran: like AI to pull from this documentation.
46 00:03:43.090 ⇒ 00:03:45.470 Uttam Kumaran: And they’re basically building. Like.
47 00:03:45.920 ⇒ 00:03:51.549 Uttam Kumaran: you guys are doing this the like for v, 1 of it, they’re basically planning for like the V, 2, v, 3,
48 00:03:52.830 ⇒ 00:04:02.270 Uttam Kumaran: so I honestly think Demolata and Kyle are probably the best 2 to give feedback. I would book time directly with them.
49 00:04:03.356 ⇒ 00:04:04.489 Uttam Kumaran: And just
50 00:04:05.510 ⇒ 00:04:11.110 Uttam Kumaran: give them whatever they need to poke around. They’re gonna they’re this is super top of mind for them right now.
51 00:04:12.806 ⇒ 00:04:13.980 Amber Lin: And Kyle.
52 00:04:13.980 ⇒ 00:04:14.670 Uttam Kumaran: Yes.
53 00:04:14.670 ⇒ 00:04:16.440 Amber Lin: What do we want from them?
54 00:04:19.209 ⇒ 00:04:22.009 Uttam Kumaran: Yeah, I guess. Good quick question for Casey.
55 00:04:23.680 ⇒ 00:04:30.639 Casie Aviles: Yeah, I guess just feedback on the bot, and you know how it could help them more pretty much
56 00:04:32.120 ⇒ 00:04:36.809 Casie Aviles: right now. The bot is more like it has contacts on slack and zoom.
57 00:04:37.260 ⇒ 00:04:38.440 Amber Lin: So.
58 00:04:38.990 ⇒ 00:04:40.140 Casie Aviles: Yeah, what are the like? The.
59 00:04:40.140 ⇒ 00:04:44.100 Amber Lin: Types of questions. Common problems.
60 00:04:45.650 ⇒ 00:04:51.180 Amber Lin: Gather common from common needs.
61 00:04:52.950 ⇒ 00:04:55.740 Amber Lin: Questions. Do what?
62 00:04:56.400 ⇒ 00:04:57.440 Amber Lin: Mask?
63 00:04:59.790 ⇒ 00:05:01.250 Amber Lin: Good morning.
64 00:05:04.190 ⇒ 00:05:06.179 Amber Lin: That’s not how I spelled that.
65 00:05:06.680 ⇒ 00:05:10.500 Amber Lin: What else? So that was, that would be the main thing.
66 00:05:16.100 ⇒ 00:05:16.939 Amber Lin: Yeah, I think.
67 00:05:17.110 ⇒ 00:05:18.519 Casie Aviles: You can start with that.
68 00:05:19.310 ⇒ 00:05:25.989 Amber Lin: Okay, so that would help us. Is this all we need to iterate? The bot.
69 00:05:31.210 ⇒ 00:05:37.959 Casie Aviles: Some other minor things, I guess, for, like the formatting like, how readable is it for them.
70 00:05:37.960 ⇒ 00:05:40.449 Uttam Kumaran: Amber. Your screen is still sharing, or it’s actually.
71 00:05:40.450 ⇒ 00:05:42.320 Amber Lin: Oh, sorry. Yeah.
72 00:05:42.550 ⇒ 00:05:44.590 Amber Lin: Let me share my linear
73 00:05:49.520 ⇒ 00:05:50.370 Amber Lin: this one.
74 00:05:52.040 ⇒ 00:05:55.710 Amber Lin: 10.
75 00:06:01.050 ⇒ 00:06:04.520 Amber Lin: So yeah, I’ll get that.
76 00:06:06.980 ⇒ 00:06:08.990 Amber Lin: Should I do? Or should you do it?
77 00:06:10.490 ⇒ 00:06:12.079 Casie Aviles: I can. I can write it. Okay.
78 00:06:14.210 ⇒ 00:06:16.800 Amber Lin: Oh, I mean to meet with. And Kyle.
79 00:06:17.860 ⇒ 00:06:20.039 Casie Aviles: Oh, yeah, I can. I can message them.
80 00:06:20.380 ⇒ 00:06:21.070 Amber Lin: Okay.
81 00:06:27.639 ⇒ 00:06:31.140 Amber Lin: I’ll probably also join in that call, if possible.
82 00:06:31.400 ⇒ 00:06:36.069 Amber Lin: So I’ll try and book it. But I’ll let you own this ticket, because you know what you need from them.
83 00:06:36.840 ⇒ 00:06:40.029 Amber Lin: Awesome. So we’ll do. That
84 00:06:45.960 ⇒ 00:06:50.389 Amber Lin: is, oh, wait. She’s not here yet.
85 00:06:50.730 ⇒ 00:06:57.829 Amber Lin: Okay, right? So we have that that’s awesome. Today we’ll get the feedback.
86 00:06:58.700 ⇒ 00:07:02.819 Amber Lin: And how does the
87 00:07:06.550 ⇒ 00:07:15.029 Amber Lin: are we good to? Oh, yes, from yesterday. How is the process? From slack s 3 to super base.
88 00:07:25.875 ⇒ 00:07:30.284 Uttam Kumaran: Miguel Casey, it’s you guys, it’s not. Neither of us are working on that.
89 00:07:30.600 ⇒ 00:07:31.280 Casie Aviles: Sorry.
90 00:07:32.490 ⇒ 00:07:34.460 Casie Aviles: My my guts are just noisy here.
91 00:07:34.460 ⇒ 00:07:34.900 Uttam Kumaran: Oh!
92 00:07:34.900 ⇒ 00:07:35.280 Casie Aviles: Just kidding.
93 00:07:35.787 ⇒ 00:07:38.830 Uttam Kumaran: I was like I was like.
94 00:07:38.830 ⇒ 00:07:39.579 Casie Aviles: Can you guys hear me?
95 00:07:39.580 ⇒ 00:07:42.820 Uttam Kumaran: Make something up. But yeah, I can hear you. I can hear you.
96 00:07:43.540 ⇒ 00:07:44.400 Casie Aviles: Yeah, okay,
97 00:07:44.930 ⇒ 00:07:49.890 Casie Aviles: yeah, for slack to. I I mean, S, 3 to super base. So that right now,
98 00:07:50.900 ⇒ 00:07:53.249 Casie Aviles: I guess what we’re figuring out is like.
99 00:07:53.450 ⇒ 00:08:00.899 Casie Aviles: because right now, how we did the matter more agent is we just dumped it into context. For now.
100 00:08:02.720 ⇒ 00:08:06.750 Casie Aviles: Yeah. So we didn’t really do any rag there yet.
101 00:08:07.530 ⇒ 00:08:10.409 Casie Aviles: Except for, like the zoom part, since the zoom
102 00:08:10.820 ⇒ 00:08:16.270 Casie Aviles: transcripts are on super base. So the slack messages are not on super base.
103 00:08:16.680 ⇒ 00:08:21.730 Casie Aviles: So so yeah, I guess. Still, the
104 00:08:22.030 ⇒ 00:08:28.290 Casie Aviles: the thing that we need to figure out there is like how we want to get the
105 00:08:28.460 ⇒ 00:08:31.650 Casie Aviles: data there, like how we want it to
106 00:08:32.220 ⇒ 00:08:39.870 Casie Aviles: be in super base. And how should it? You know, how? How can the AI reliably access the required information from super base.
107 00:08:40.179 ⇒ 00:08:41.039 Amber Lin: I see
108 00:08:41.587 ⇒ 00:08:53.289 Amber Lin: yesterday we talked about there was a 1st step that we wanted to do of giving away a sample spreadsheet, of how we wanted to see the slack data. Is that still something that we want to do.
109 00:08:54.510 ⇒ 00:08:56.499 Casie Aviles: Yeah, yeah, that’s still.
110 00:08:56.500 ⇒ 00:09:02.930 Amber Lin: Okay, I guess we didn’t have time to do that yesterday, because we were doing this.
111 00:09:05.990 ⇒ 00:09:09.629 Amber Lin: So I will put that as
112 00:09:09.790 ⇒ 00:09:11.920 Amber Lin: there’s something we can do today.
113 00:09:13.700 ⇒ 00:09:16.380 Casie Aviles: Yeah, I can. I can start to finalize this today.
114 00:09:16.380 ⇒ 00:09:22.279 Amber Lin: Okay, once we have that, it will be helpful to.
115 00:09:23.200 ⇒ 00:09:23.890 Amber Lin: Oh.
116 00:09:27.590 ⇒ 00:09:28.830 Amber Lin: ticket. Go.
117 00:09:29.980 ⇒ 00:09:44.140 Amber Lin: Yeah, to just experiment with the metamor agent data to see how we can to just quickly experiment with different ways. We can use it for super base, because once we have this, we’ll be able to have the
118 00:09:47.360 ⇒ 00:09:50.519 Amber Lin: we’ll be able to do it for other teams as well.
119 00:09:57.122 ⇒ 00:10:01.109 Amber Lin: Question, what is this? Which one is? This ticket?
120 00:10:01.110 ⇒ 00:10:04.399 Casie Aviles: Oh, I was. Yeah, I was. This was for document
121 00:10:05.660 ⇒ 00:10:09.880 Casie Aviles: create a slack agent. So I moved it to to do because I wanted to.
122 00:10:09.990 ⇒ 00:10:11.380 Amber Lin: Finish it today.
123 00:10:11.630 ⇒ 00:10:14.460 Amber Lin: Awesome. Okay. I’ll add it. I’ll add a due date.
124 00:10:15.776 ⇒ 00:10:17.010 Amber Lin: Let’s see.
125 00:10:26.790 ⇒ 00:10:33.269 Amber Lin: I kind of want to get this one started, too. I know we’re just not on the call yet.
126 00:10:33.530 ⇒ 00:10:39.450 Amber Lin: Would we be able to just be on a call with a ways and figure it out
127 00:10:39.590 ⇒ 00:10:46.009 Amber Lin: because he knows he knows the transformation part. And you know the end product.
128 00:10:46.250 ⇒ 00:10:49.429 Amber Lin: Think we’ll be a lot faster if we work together.
129 00:10:49.430 ⇒ 00:10:50.990 Uttam Kumaran: Yeah, I would do that.
130 00:10:50.990 ⇒ 00:10:52.080 Amber Lin: Brainstorm.
131 00:10:52.430 ⇒ 00:10:54.670 Uttam Kumaran: Yeah, that’s what I would suggest, too.
132 00:10:54.670 ⇒ 00:10:55.420 Amber Lin: Okay.
133 00:10:57.330 ⇒ 00:11:02.249 Uttam Kumaran: He’s yeah, he’s like, knee deep in the slack data. So I think you guys can probably
134 00:11:02.390 ⇒ 00:11:07.839 Uttam Kumaran: just do a bunch of testing of like how to move this to super base, and he’s getting more knowledgeable about any then. So.
135 00:11:09.060 ⇒ 00:11:10.010 Amber Lin: Next
136 00:11:22.970 ⇒ 00:11:25.859 Amber Lin: a bit of a long ticket. But here you go.
137 00:11:26.130 ⇒ 00:11:30.689 Amber Lin: I’ll put it in the matter more client agents. So we just experiment based on that.
138 00:11:30.900 ⇒ 00:11:38.089 Amber Lin: I would love for these 2 to get done to to be done today because we’re not
139 00:11:38.756 ⇒ 00:11:41.849 Amber Lin: we’re not shipping a new Asian today. So
140 00:11:42.130 ⇒ 00:11:45.109 Amber Lin: I think we do have some time to
141 00:11:45.460 ⇒ 00:11:56.910 Amber Lin: do this. Oh, Casey, question, how much time do you have left in the day? I know, Miguel said his day was gonna done. How does your how does your day look like.
142 00:11:58.450 ⇒ 00:12:01.249 Casie Aviles: I think I have 5 more hours.
143 00:12:02.150 ⇒ 00:12:03.260 Amber Lin: Okay. Sounds good.
144 00:12:03.260 ⇒ 00:12:04.540 Casie Aviles: 6, yeah.
145 00:12:04.740 ⇒ 00:12:10.420 Amber Lin: I see so I will go
146 00:12:10.700 ⇒ 00:12:16.349 Amber Lin: if you message them. Can you just like add me to the meeting as well.
147 00:12:16.810 ⇒ 00:12:21.629 Amber Lin: so I can take care of a little bit more of that. And you can.
148 00:12:21.750 ⇒ 00:12:27.070 Amber Lin: I really want this to this to get better, because then we can
149 00:12:27.270 ⇒ 00:12:29.320 Amber Lin: do the other tickets as well.
150 00:12:34.675 ⇒ 00:12:40.150 Amber Lin: okay, yeah. I need to update that ticket.
151 00:12:41.320 ⇒ 00:12:47.640 Amber Lin: Great. So that’s for slack we have 4 sources
152 00:12:47.860 ⇒ 00:12:51.200 Amber Lin: that we want to include for agents.
153 00:12:52.450 ⇒ 00:12:56.990 Amber Lin: We have also. We have also Github.
154 00:12:56.990 ⇒ 00:12:57.660 Miguel de Veyra: And good talk.
155 00:12:58.330 ⇒ 00:12:59.090 Amber Lin: Yeah.
156 00:13:01.760 ⇒ 00:13:03.979 Amber Lin: Do you know the progress on that?
157 00:13:04.400 ⇒ 00:13:07.910 Amber Lin: Let me actually let me ping a wish if he can join.
158 00:13:14.590 ⇒ 00:13:19.399 Uttam Kumaran: Did our site did so. This cycle started on this week.
159 00:13:20.110 ⇒ 00:13:23.269 Miguel de Veyra: Yeah, I think, so, yeah, I think, so.
160 00:13:23.270 ⇒ 00:13:25.340 Uttam Kumaran: Okay, cool. I was gonna have a panic attack.
161 00:13:28.680 ⇒ 00:13:29.340 Amber Lin: 5, 5.
162 00:13:29.340 ⇒ 00:13:30.990 Miguel de Veyra: Second day.
163 00:13:30.990 ⇒ 00:13:35.347 Uttam Kumaran: Sorry I was like what the heck there’s so much.
164 00:13:35.710 ⇒ 00:13:36.530 Amber Lin: Thank you.
165 00:13:37.200 ⇒ 00:13:38.950 Uttam Kumaran: Okay. Never mind. Sorry guys.
166 00:13:43.125 ⇒ 00:13:50.570 Amber Lin: Let’s see about this zoom data. Is there anything that we’re stuck here on?
167 00:13:52.560 ⇒ 00:13:53.080 Amber Lin: Oh.
168 00:13:53.080 ⇒ 00:13:54.950 Uttam Kumaran: That’s all on the waste right?
169 00:13:54.950 ⇒ 00:13:56.710 Amber Lin: Okay, yes, this is.
170 00:13:57.040 ⇒ 00:14:03.970 Uttam Kumaran: Yeah, but anything on a wish. Let’s just move past because he just ceased here, just has to come. Give us updates.
171 00:14:04.360 ⇒ 00:14:09.659 Amber Lin: Okay, are we doing this
172 00:14:09.820 ⇒ 00:14:12.290 Amber Lin: right now? Should we move it back?
173 00:14:15.730 ⇒ 00:14:16.950 Amber Lin: So we’re doing the.
174 00:14:17.730 ⇒ 00:14:18.239 Miguel de Veyra: I mean we.
175 00:14:18.240 ⇒ 00:14:18.589 Casie Aviles: Oh, yeah.
176 00:14:21.050 ⇒ 00:14:22.829 Amber Lin: Should we move it back to.
177 00:14:22.830 ⇒ 00:14:24.680 Uttam Kumaran: I think. Move it back.
178 00:14:25.050 ⇒ 00:14:31.459 Uttam Kumaran: Yeah, to give you contact. So it looks like we’re able, like, last 2 cycles. We got about 20
179 00:14:32.070 ⇒ 00:14:34.839 Uttam Kumaran: 5 tickets, 2125 tickets.
180 00:14:34.840 ⇒ 00:14:35.310 Amber Lin: Okay.
181 00:14:35.310 ⇒ 00:14:39.380 Uttam Kumaran: Right now we’re at 44 tickets, which includes a wish.
182 00:14:42.170 ⇒ 00:14:45.060 Uttam Kumaran: So I just want to make sure that
183 00:14:46.444 ⇒ 00:14:48.690 Uttam Kumaran: like Oasia, 7 of those tickets.
184 00:14:51.170 ⇒ 00:14:53.130 Uttam Kumaran: Actually no Oish has.
185 00:14:54.160 ⇒ 00:14:58.880 Uttam Kumaran: Yeah, I wish has 7 of those tickets, and then there’s
186 00:15:00.870 ⇒ 00:15:06.670 Uttam Kumaran: wait. What am I looking at? Cycle for? Issue assignee. Oh, but there’s some with no assignee.
187 00:15:09.910 ⇒ 00:15:14.929 Uttam Kumaran: Oh, this is points. Oh, I see. I see. Okay, okay, never mind. So we’re at.
188 00:15:15.100 ⇒ 00:15:17.350 Uttam Kumaran: We scoped 44 points.
189 00:15:18.300 ⇒ 00:15:21.060 Uttam Kumaran: And then, yeah, it looks like
190 00:15:24.830 ⇒ 00:15:27.140 Amber Lin: Think we can move some of these.
191 00:15:29.000 ⇒ 00:15:35.019 Amber Lin: Let’s see, I do agree that a wage has quite a few tickets.
192 00:15:36.900 ⇒ 00:15:41.979 Uttam Kumaran: Well await in case you have 19 and 13, and then Miguel is at 9.
193 00:15:44.620 ⇒ 00:15:46.660 Uttam Kumaran: I think it’s fine
194 00:15:47.140 ⇒ 00:15:54.050 Uttam Kumaran: now, like if we if I’m just, if I’m looking like the matter, more is under review Zoom Meetings to super base
195 00:15:54.190 ⇒ 00:15:58.579 Uttam Kumaran: Oasius data source slack messages.
196 00:15:58.980 ⇒ 00:16:04.929 Uttam Kumaran: So that’s definitely, I def definitely think we probably underestimated on that, because that’s currently at a 3.
197 00:16:05.390 ⇒ 00:16:11.390 Uttam Kumaran: That’s fine. I don’t think we need to change it necessarily. I don’t really know what’s what like the process should be, but, like.
198 00:16:11.390 ⇒ 00:16:18.880 Amber Lin: Yeah, this one should the ones oh.
199 00:16:20.890 ⇒ 00:16:23.240 Amber Lin: I don’t know how that! How long.
200 00:16:23.240 ⇒ 00:16:26.049 Uttam Kumaran: Fine. So then, if we’re looking at, yeah, go ahead.
201 00:16:26.790 ⇒ 00:16:34.100 Miguel de Veyra: Because I think the for the data sources, everything, I believe, should also already be in S. 2
202 00:16:34.270 ⇒ 00:16:42.050 Miguel de Veyra: s. 3. So it’s technically done like the Github linear slap. And then that’s why this are in test.
203 00:16:42.050 ⇒ 00:16:48.999 Uttam Kumaran: But I but I I guess, like we need to verify like this. All should move to review then, right? Because
204 00:16:49.180 ⇒ 00:16:54.670 Uttam Kumaran: I still want to take a look like what away sent today, which was just like, take a look at what the data looks like.
205 00:16:55.270 ⇒ 00:17:01.210 Uttam Kumaran: I still want to have a little bit of that. So I would move each of these to review if they’re basically in that state.
206 00:17:02.350 ⇒ 00:17:04.849 Miguel de Veyra: The 2 you moved Amber. He’s still testing that.
207 00:17:06.720 ⇒ 00:17:10.709 Amber Lin: A test. What’s the difference between the testing and the review?
208 00:17:13.000 ⇒ 00:17:18.660 Uttam Kumaran: So I think testing, I mean, this is a good question. I think we should determine.
209 00:17:18.770 ⇒ 00:17:28.379 Uttam Kumaran: Testing is sort of like the work is done. And there should. Basically, there’s a step. There should be a step in every ticket. That’s like, what are the what’s the process to test this?
210 00:17:28.823 ⇒ 00:17:31.959 Uttam Kumaran: But you’re right. I guess I don’t really know what the difference is, either.
211 00:17:39.383 ⇒ 00:17:43.190 Amber Lin: I’ll wait for a ways to do that. But.
212 00:17:43.190 ⇒ 00:17:43.800 Uttam Kumaran: Okay.
213 00:17:43.800 ⇒ 00:17:52.029 Amber Lin: I will just. I’ll just assume that we just need to look at everything in the Progress and ready for Development section. I’ll leave this to him.
214 00:17:52.450 ⇒ 00:17:55.689 Uttam Kumaran: Because would mostly just be looking at here.
215 00:17:57.504 ⇒ 00:17:59.469 Amber Lin: Did he respond?
216 00:18:00.000 ⇒ 00:18:02.250 Amber Lin: Oh, okay, he’s on a client.
217 00:18:03.460 ⇒ 00:18:03.990 Uttam Kumaran: Okay.
218 00:18:04.490 ⇒ 00:18:05.380 Amber Lin: Sounds good.
219 00:18:11.940 ⇒ 00:18:14.879 Amber Lin: What do we need to do? Another client agent.
220 00:18:17.620 ⇒ 00:18:22.519 Uttam Kumaran: Well, yeah, I guess this is where. Now, now that we have these updated
221 00:18:25.100 ⇒ 00:18:27.690 Uttam Kumaran: I mean, it looks like
222 00:18:30.770 ⇒ 00:18:39.110 Amber Lin: I think we can have a few of these looking at backlog and requirements started.
223 00:18:39.570 ⇒ 00:18:42.230 Uttam Kumaran: I mean it. It looks like we just have like.
224 00:18:42.760 ⇒ 00:18:45.079 Uttam Kumaran: I mean, I don’t know. It just looks like we
225 00:18:48.510 ⇒ 00:18:51.260 Uttam Kumaran: I I honestly think we should just keep
226 00:18:51.470 ⇒ 00:19:00.300 Uttam Kumaran: finishing up all these. I think the only I think, Miguel, you’re the only one, I think, that you only have the 2. But the Schwartzberg work was that covered under here.
227 00:19:01.410 ⇒ 00:19:02.600 Uttam Kumaran: but that was last. Is that last.
228 00:19:02.600 ⇒ 00:19:05.090 Miguel de Veyra: I think. Yeah, that was last week.
229 00:19:05.370 ⇒ 00:19:09.110 Uttam Kumaran: Okay? So then, yeah, I would. I think probably
230 00:19:09.780 ⇒ 00:19:17.849 Uttam Kumaran: you may need 2 more items or a couple more items, because I think a waste. And Casey, just closing out the data sources is great, and then
231 00:19:18.500 ⇒ 00:19:19.389 Uttam Kumaran: we can plan.
232 00:19:19.390 ⇒ 00:19:20.280 Amber Lin: New York.
233 00:19:20.830 ⇒ 00:19:25.309 Miguel de Veyra: What about the ones you sent in sales? Should we work on that? Or should we prioritize the ones here.
234 00:19:26.082 ⇒ 00:19:30.407 Uttam Kumaran: Well, I think in terms of bringing in new stuff. Let’s look at
235 00:19:31.410 ⇒ 00:19:34.180 Uttam Kumaran: Let’s basically look at what’s in ready for development.
236 00:19:34.450 ⇒ 00:19:39.059 Uttam Kumaran: And like what’s in requirements started. So if there’s anything else we want to bring in from there.
237 00:19:39.900 ⇒ 00:19:49.530 Amber Lin: Yeah, this is all kind of in in progress, because we’re always was just looking at Dexter.
238 00:19:49.660 ⇒ 00:19:52.850 Amber Lin: So everything related to Daxter is kinda in.
239 00:19:52.850 ⇒ 00:19:54.857 Uttam Kumaran: But, for example, like
240 00:19:55.840 ⇒ 00:19:56.410 Amber Lin: Thanks.
241 00:19:56.410 ⇒ 00:19:59.709 Uttam Kumaran: So super base integration of linear tickets.
242 00:20:06.980 ⇒ 00:20:13.450 Amber Lin: It’s that kind of could be in parallel with the slack messages.
243 00:20:15.300 ⇒ 00:20:23.800 Uttam Kumaran: Well, I guess like, what are this? Because I I just have sent like a hundred things. So none of that I mean to like, we don’t need to work on any of that. I just need to write. Write it down. Basically.
244 00:20:23.800 ⇒ 00:20:24.270 Amber Lin: Me somewhere.
245 00:20:24.270 ⇒ 00:20:31.550 Uttam Kumaran: But like couple of things that I asked that we could prioritize is like.
246 00:20:31.830 ⇒ 00:20:39.929 Uttam Kumaran: I want, like, I just kinda wanna I’m using github I’m using, like, chat gpt projects right now.
247 00:20:40.540 ⇒ 00:20:43.610 Uttam Kumaran: And I can start just
248 00:20:43.810 ⇒ 00:20:49.430 Uttam Kumaran: using the bots in slack instead, I have like 5 different 5 or 6 different projects I’m using.
249 00:20:49.840 ⇒ 00:20:56.399 Uttam Kumaran: So I was like, Okay, can I get some documentation on how to build a simple slack agent like the 4? 0, Bot!
250 00:20:57.200 ⇒ 00:20:57.870 Amber Lin: Hmm.
251 00:20:59.050 ⇒ 00:21:01.269 Uttam Kumaran: So I can make a ticket for that.
252 00:21:01.550 ⇒ 00:21:04.750 Casie Aviles: I think we already have one. That’s what I put in to do.
253 00:21:05.260 ⇒ 00:21:07.989 Uttam Kumaran: Okay, so that one is.
254 00:21:08.310 ⇒ 00:21:12.640 Casie Aviles: Yeah, that one stock agent documentation that’s in progress. Now.
255 00:21:15.980 ⇒ 00:21:17.219 Uttam Kumaran: Wait. Where’s that one?
256 00:21:20.360 ⇒ 00:21:22.650 Uttam Kumaran: Oh, how to make a slack agent? Okay?
257 00:21:22.850 ⇒ 00:21:28.600 Uttam Kumaran: Then maybe I would just hand Casey. I would just hand, I guess. Okay, let’s just look at what else? Okay? So that’s
258 00:21:28.750 ⇒ 00:21:30.180 Uttam Kumaran: that’s tracked here.
259 00:21:30.550 ⇒ 00:21:40.330 Uttam Kumaran: So I’m just gonna I’ll just link this here cool.
260 00:21:42.440 ⇒ 00:21:45.260 Uttam Kumaran: I think the other piece is
261 00:21:51.400 ⇒ 00:21:58.120 Amber Lin: We can also spit out basic versions for all of the other client hubs.
262 00:21:58.620 ⇒ 00:22:02.420 Uttam Kumaran: I mean, I would just do that like why not?
263 00:22:02.800 ⇒ 00:22:08.410 Amber Lin: Right cause. We’re we know that we’re doing the basic
264 00:22:09.940 ⇒ 00:22:13.310 Amber Lin: like the basic contents we could.
265 00:22:13.520 ⇒ 00:22:20.490 Amber Lin: I don’t know how difficult it would be. What do you think would need to get done? Like to use to replicate.
266 00:22:21.530 ⇒ 00:22:24.770 Casie Aviles: I mean, I could just replicate the same workflows for.
267 00:22:24.770 ⇒ 00:22:25.490 Amber Lin: Okay.
268 00:22:26.070 ⇒ 00:22:31.619 Casie Aviles: The agents so like how matter more is working right now. I could replicate that and create
269 00:22:31.770 ⇒ 00:22:33.290 Casie Aviles: an agent for each.
270 00:22:33.430 ⇒ 00:22:34.020 Amber Lin: Hmm.
271 00:22:38.330 ⇒ 00:22:42.730 Uttam Kumaran: But like, I guess I wanna I wanna have a Casey. I think your plate is pretty full because
272 00:22:43.450 ⇒ 00:22:46.569 Uttam Kumaran: it’s like making sure all the slack integration works.
273 00:22:47.050 ⇒ 00:22:53.369 Uttam Kumaran: And then, just like continuing, basically, I wanna, I want to close out the slack and zoom and
274 00:22:53.550 ⇒ 00:22:55.800 Uttam Kumaran: github and linear as soon as we can.
275 00:22:56.400 ⇒ 00:22:59.670 Amber Lin: So that all I would love to happen. This cycle.
276 00:22:59.930 ⇒ 00:23:02.910 Uttam Kumaran: So if you have more time, I would do that. I think.
277 00:23:03.280 ⇒ 00:23:07.590 Uttam Kumaran: Miguel, I think it’s question for you on like, where do you want to stretch.
278 00:23:09.680 ⇒ 00:23:14.639 Miguel de Veyra: I can do the the basically, it’s just duplicating and just changing the contents.
279 00:23:15.950 ⇒ 00:23:18.969 Miguel de Veyra: Just so we have a bot for each and every client.
280 00:23:19.820 ⇒ 00:23:24.640 Uttam Kumaran: That would be great. So like, can we like, how is there a
281 00:23:25.090 ⇒ 00:23:27.569 Uttam Kumaran: are we doing projects for every bot, or like.
282 00:23:27.570 ⇒ 00:23:33.329 Amber Lin: Yeah, I’m we’ll. I’ll make projects for that. I’m just gonna.
283 00:23:33.330 ⇒ 00:23:37.929 Uttam Kumaran: I would just do like, whatever is the initialization step, and like the few.
284 00:23:38.450 ⇒ 00:23:42.399 Uttam Kumaran: the few tickets like, let’s scope out all the tickets
285 00:23:42.600 ⇒ 00:23:48.439 Uttam Kumaran: for each agent, and then just move in the couple that you’re gonna do, which is like, initialize the
286 00:23:48.850 ⇒ 00:23:52.686 Uttam Kumaran: initialize, the new slack app right?
287 00:23:53.460 ⇒ 00:23:55.459 Uttam Kumaran: whatever like the couple of steps are.
288 00:23:55.460 ⇒ 00:23:55.870 Amber Lin: Hmm.
289 00:23:55.870 ⇒ 00:23:58.169 Uttam Kumaran: And then, yeah, just rip them for all clients.
290 00:23:58.686 ⇒ 00:24:06.719 Uttam Kumaran: And then ideal like, I guess the only risk is that if there’s like a giant infrastructure change, and you have to make it across bunch of them.
291 00:24:06.870 ⇒ 00:24:08.730 Miguel de Veyra: Yeah, however, at this point.
292 00:24:08.980 ⇒ 00:24:13.520 Uttam Kumaran: I think, like we’re sitting on that information. Let’s just go for it.
293 00:24:13.520 ⇒ 00:24:13.870 Amber Lin: Yeah.
294 00:24:13.870 ⇒ 00:24:14.600 Miguel de Veyra: Okay. Yeah. Sure.
295 00:24:14.600 ⇒ 00:24:17.139 Amber Lin: I’ll make. I’ll make projects for them.
296 00:24:18.300 ⇒ 00:24:26.589 Uttam Kumaran: And then, Casey, is there any chance that that like how to make a slack agent? Docs you can work on? Because I’m gonna I’m gonna take on.
297 00:24:26.840 ⇒ 00:24:30.249 Uttam Kumaran: Cause. I also want to do some Nan work today. So I’m gonna take on
298 00:24:30.500 ⇒ 00:24:32.083 Uttam Kumaran: creating some of these.
299 00:24:32.480 ⇒ 00:24:33.060 Casie Aviles: Sure I can.
300 00:24:33.060 ⇒ 00:24:33.549 Uttam Kumaran: Slack age.
301 00:24:33.550 ⇒ 00:24:34.749 Casie Aviles: I can finish this.
302 00:24:37.920 ⇒ 00:24:42.819 Uttam Kumaran: Okay, because I am deep in
303 00:24:43.530 ⇒ 00:24:45.899 Uttam Kumaran: prompt world this week. And last week.
304 00:24:46.670 ⇒ 00:24:52.160 Amber Lin: Awesome Miguel for all the different agents. How long
305 00:24:52.520 ⇒ 00:24:58.460 Amber Lin: does it take? Yeah, I know you say you’re done for it to take? Can we have it by tomorrow.
306 00:24:59.280 ⇒ 00:25:02.509 Amber Lin: or at a Wednesday.
307 00:25:02.510 ⇒ 00:25:09.120 Miguel de Veyra: Yeah, yeah, I think how many, how many ages it’s. I think each should be around like
308 00:25:09.550 ⇒ 00:25:14.670 Miguel de Veyra: 2 to 3 at 2 points. I think so. Yeah, it should be. It should be okay tomorrow.
309 00:25:14.670 ⇒ 00:25:22.109 Amber Lin: Okay, so like each would be, I’ll make a I’ll make new tickets for this so I’ll just say like
310 00:25:22.730 ⇒ 00:25:23.889 Amber Lin: option. 2.
311 00:25:23.890 ⇒ 00:25:31.020 Miguel de Veyra: But to clarify this is just the the general details. Right? Not really, of course not. The zoom slack.
312 00:25:31.580 ⇒ 00:25:33.650 Miguel de Veyra: Well, like, what are we doing for matter more.
313 00:25:34.450 ⇒ 00:25:39.900 Casie Aviles: But for matter more, we have the Zoom transcript and slack channels.
314 00:25:41.080 ⇒ 00:25:42.899 Uttam Kumaran: I mean. That’s so, then that’s what I would.
315 00:25:43.080 ⇒ 00:25:47.690 Uttam Kumaran: I mean, I would ideally, this is my question is like.
316 00:25:47.820 ⇒ 00:25:54.620 Uttam Kumaran: how on on every agent. How far are we on all the 4 core ones, Github, zoom, slack, linear.
317 00:25:59.560 ⇒ 00:26:03.580 Uttam Kumaran: and like which one is most important cause like, I wanna get the I mean, I guess.
318 00:26:03.710 ⇒ 00:26:07.570 Uttam Kumaran: Yup, we had. We need the slack bots anyways, for each of those.
319 00:26:07.570 ⇒ 00:26:08.130 Miguel de Veyra: Yeah.
320 00:26:08.460 ⇒ 00:26:10.000 Uttam Kumaran: So part of this is like.
321 00:26:10.890 ⇒ 00:26:20.059 Uttam Kumaran: how fast can we develop those for every client? The second piece is like I would love for it to not just have like, a basic prompt like, it can actually reference the Github or something.
322 00:26:22.010 ⇒ 00:26:24.850 Uttam Kumaran: So this is where it’s like, our trade off is like, either.
323 00:26:25.140 ⇒ 00:26:28.140 Uttam Kumaran: Yeah, you continue working directly with
324 00:26:28.470 ⇒ 00:26:34.569 Uttam Kumaran: Casey and a wish on, just like finishing up this core source to super base work.
325 00:26:34.730 ⇒ 00:26:38.450 Uttam Kumaran: Or you go work on the the new agents
326 00:26:39.140 ⇒ 00:26:43.259 Uttam Kumaran: which will take from that work. I that’s the trade off, I think, like I don’t know I need.
327 00:26:43.670 ⇒ 00:26:47.399 Uttam Kumaran: I sort of need your advice to on like what what we should do here.
328 00:26:51.760 ⇒ 00:26:52.499 Miguel de Veyra: Wait! Let me think!
329 00:26:52.500 ⇒ 00:26:53.270 Casie Aviles: I think.
330 00:26:53.860 ⇒ 00:26:55.700 Uttam Kumaran: Yeah, take a sec. I mean, yeah.
331 00:26:56.230 ⇒ 00:26:57.680 Uttam Kumaran: yeah, what do you think? Casey?
332 00:26:58.140 ⇒ 00:27:04.110 Casie Aviles: I mean, think we could, you know, go with the initial solution which is to just.
333 00:27:04.110 ⇒ 00:27:05.689 Miguel de Veyra: Finish up for.
334 00:27:05.690 ⇒ 00:27:15.089 Casie Aviles: In context right now, because I right now honestly, with the transfer to super base, there’s a lot of gray area for me. There.
335 00:27:15.280 ⇒ 00:27:16.540 Uttam Kumaran: Okay, so.
336 00:27:16.730 ⇒ 00:27:21.770 Casie Aviles: I don’t know if I could, like, you know, reliably create good output with that. But
337 00:27:21.880 ⇒ 00:27:25.679 Casie Aviles: right now, with how we do, ABC, we’re not actually doing
338 00:27:25.940 ⇒ 00:27:32.780 Casie Aviles: rug there. We’re like putting it the necessary stuff into context. So we’re leveraging
339 00:27:33.040 ⇒ 00:27:35.990 Casie Aviles: Google Gemini’s context window for that.
340 00:27:35.990 ⇒ 00:27:36.480 Uttam Kumaran: Okay.
341 00:27:36.480 ⇒ 00:27:41.390 Casie Aviles: And we just we just have, like some workarounds like.
342 00:27:41.670 ⇒ 00:27:47.429 Casie Aviles: how do we split up the documents? How do we make the bot reference? The correct document? So.
343 00:27:47.430 ⇒ 00:27:48.130 Uttam Kumaran: Okay.
344 00:27:49.180 ⇒ 00:27:49.600 Casie Aviles: Yeah.
345 00:27:49.600 ⇒ 00:27:50.030 Uttam Kumaran: So I guess.
346 00:27:50.030 ⇒ 00:27:51.210 Casie Aviles: The fastest.
347 00:27:53.000 ⇒ 00:27:54.210 Uttam Kumaran: Okay. So then
348 00:27:56.430 ⇒ 00:28:04.510 Uttam Kumaran: I just think, like the matter, more work is going to be helpful. But the feedback you’re going to get is going to be better on Javi, because we have more history with Javi.
349 00:28:05.190 ⇒ 00:28:08.570 Uttam Kumaran: So so I guess this is my. This is my feedback is that
350 00:28:08.780 ⇒ 00:28:19.140 Uttam Kumaran: if it’s helpful to test and get the matter more stuff done faster, because it’s not that much data go for it. But if there’s really like one client to like test and nail with.
351 00:28:19.310 ⇒ 00:28:26.689 Uttam Kumaran: I would try it with Javi. So I think both of those are still in the sprint. The things I don’t notice is like
352 00:28:29.330 ⇒ 00:28:33.399 Uttam Kumaran: is. So I see here Zoom Meetings, the super base.
353 00:28:34.410 ⇒ 00:28:41.640 Uttam Kumaran: This is just slack messages into S 3, right? So that’s that one.
354 00:28:41.970 ⇒ 00:28:45.100 Uttam Kumaran: We have extract zoom data.
355 00:28:46.860 ⇒ 00:28:52.770 Uttam Kumaran: Okay? So that’s that one we have. Write script to move data to Github.
356 00:28:53.780 ⇒ 00:28:58.539 Uttam Kumaran: Oh, okay, this is just Github to S. 3. Okay, this is Github.
357 00:28:58.720 ⇒ 00:29:02.220 Uttam Kumaran: I’m just gonna edit. Some things live. So this is Github to S. 3.
358 00:29:02.880 ⇒ 00:29:07.719 Uttam Kumaran: And then we have linear tickets, 2 s. 3
359 00:29:08.820 ⇒ 00:29:16.049 Uttam Kumaran: great. So get up to S. 3 linear tickets. S. 3. This is zoom to s. 3 right
360 00:29:18.020 ⇒ 00:29:20.790 Uttam Kumaran: zoom to s. 3.
361 00:29:21.070 ⇒ 00:29:23.049 Amber Lin: Do you wanna share your screen with Tom.
362 00:29:23.050 ⇒ 00:29:23.950 Uttam Kumaran: Yeah.
363 00:29:25.610 ⇒ 00:29:31.179 Uttam Kumaran: So if zoomed s. 3 github to s, 3 linear to s. 3, this is zoom.
364 00:29:33.030 ⇒ 00:29:34.710 Amber Lin: S. 3 to super. Please.
365 00:29:34.710 ⇒ 00:29:35.370 Uttam Kumaran: Yep.
366 00:29:40.850 ⇒ 00:29:42.870 Uttam Kumaran: And then this is slack.
367 00:29:43.970 ⇒ 00:29:48.719 Uttam Kumaran: S 3, right? Okay, so we’re we’re basically gonna complete. All the S 3 work
368 00:29:48.870 ⇒ 00:29:51.240 Uttam Kumaran: seems like by the end of this week.
369 00:29:51.730 ⇒ 00:29:57.279 Uttam Kumaran: I. Then we then need S. 3 to super base for every source.
370 00:29:57.510 ⇒ 00:30:10.350 Uttam Kumaran: Right? Which is, yeah. So this is black s. 3, 2 stupa base.
371 00:30:11.730 ⇒ 00:30:12.570 Uttam Kumaran: Right?
372 00:30:13.240 ⇒ 00:30:17.740 Uttam Kumaran: Great. So that’s let’s consider that one.
373 00:30:18.400 ⇒ 00:30:20.400 Uttam Kumaran: Do we have a
374 00:30:24.000 ⇒ 00:30:31.549 Uttam Kumaran: okay. This is like Github S. 3 to super base.
375 00:30:32.550 ⇒ 00:30:33.609 Amber Lin: Hi! I wish.
376 00:30:35.060 ⇒ 00:30:35.650 Awaish Kumar: Cool.
377 00:30:36.390 ⇒ 00:30:37.270 Uttam Kumaran: Hello,
378 00:30:46.210 ⇒ 00:30:51.829 Uttam Kumaran: okay. So this is, there’s gotta be some zoom to super base right?
379 00:30:51.830 ⇒ 00:30:59.560 Amber Lin: There’s 1 in for backfill. So for the past one. So that’s ticket 1 48. It’s in back.
380 00:30:59.560 ⇒ 00:31:01.590 Uttam Kumaran: Yeah, I’m just gonna combine these.
381 00:31:03.090 ⇒ 00:31:08.150 Uttam Kumaran: So I’m gonna say, zoom s 3 to super base.
382 00:31:09.200 ⇒ 00:31:11.749 Uttam Kumaran: Let’s just move it into the cycle.
383 00:31:13.310 ⇒ 00:31:22.270 Uttam Kumaran: So then, what are we missing? We’re we have github, linear zoom, slack, so slack github.
384 00:31:22.460 ⇒ 00:31:29.350 Uttam Kumaran: zoom, and then we’re missing the linear right? So linear.
385 00:31:29.490 ⇒ 00:31:30.170 Uttam Kumaran: Oh.
386 00:31:32.253 ⇒ 00:31:35.219 Amber Lin: One for 6, and before we started.
387 00:31:35.550 ⇒ 00:31:40.700 Uttam Kumaran: Okay, so we’re gonna do linear s, 3 to super base.
388 00:31:40.880 ⇒ 00:31:45.380 Uttam Kumaran: Okay? Like this is, I would say, this is
389 00:31:47.090 ⇒ 00:31:52.560 Uttam Kumaran: good enough scope for this cycle. I think the only thing is
390 00:31:52.660 ⇒ 00:32:00.279 Uttam Kumaran: I want to just take a look at who’s working on what? So
391 00:32:01.135 ⇒ 00:32:03.870 Uttam Kumaran: I’m gonna move the spike out
392 00:32:04.220 ⇒ 00:32:08.989 Uttam Kumaran: for now, well, actually, okay, I’m gonna just move this spike out of this cycle.
393 00:32:10.020 ⇒ 00:32:17.759 Uttam Kumaran: So basically, okay, each of this one is all this cycle. It’s assigned to me.
394 00:32:20.100 ⇒ 00:32:30.230 Uttam Kumaran: The Javi agent. So these, okay, how do I just select ease?
395 00:32:34.300 ⇒ 00:32:36.299 Uttam Kumaran: Where do you want the cycle?
396 00:32:37.860 ⇒ 00:32:39.920 Uttam Kumaran: Thank you. Say, call.
397 00:32:41.120 ⇒ 00:32:47.089 Uttam Kumaran: Okay. So I guess let’s talk about these tickets.
398 00:32:49.540 ⇒ 00:32:55.890 Uttam Kumaran: And let’s sort by signee.
399 00:32:56.310 ⇒ 00:33:06.470 Uttam Kumaran: So, Miguel, I think, like which ones of these would you want to take on from this cycle.
400 00:33:07.630 ⇒ 00:33:10.030 Uttam Kumaran: and I’ll go to here. This is a better view.
401 00:33:19.062 ⇒ 00:33:20.949 Uttam Kumaran: Why is this not?
402 00:33:25.170 ⇒ 00:33:28.419 Uttam Kumaran: Where were all those things I just worked on.
403 00:33:30.420 ⇒ 00:33:31.330 Uttam Kumaran: Oh.
404 00:33:37.710 ⇒ 00:33:44.740 Uttam Kumaran: Michael, for these are all cycle 4. Cycle 4. Cycle 4. Cycle 4
405 00:33:45.250 ⇒ 00:33:51.630 Uttam Kumaran: is all okay. Great. So now, if I go back to cycle, this guy
406 00:33:52.240 ⇒ 00:33:59.200 Uttam Kumaran: cool. So I think, Miguel like, let me know which ones of these we can peel off.
407 00:34:00.380 ⇒ 00:34:13.780 Uttam Kumaran: I mean, it’s gonna be between, I think the 3 of y’all. But I don’t know. I would love to cause it’s gonna be tough enough to just become an expert in one or 2 of these versus like all 4. So I want to sort of spread the wealth a little bit.
408 00:34:15.570 ⇒ 00:34:19.269 Miguel de Veyra: I think I can work on the S. 3 to super base tickets.
409 00:34:20.580 ⇒ 00:34:21.239 Uttam Kumaran: Okay.
410 00:34:28.230 ⇒ 00:34:42.010 Miguel de Veyra: Because there’s technically right now, there’s 2 ways we load. I I mean, at least, for now there’s 2 ways we we do loading into super base. One is from direct to the meeting. Like after the Zoom transcript.
411 00:34:42.300 ⇒ 00:34:46.849 Miguel de Veyra: the analyz, the analyzation part. We just throw it straight into super base
412 00:34:47.110 ⇒ 00:34:51.060 Miguel de Veyra: and then the other part is the one where we are working with the weish.
413 00:34:52.120 ⇒ 00:34:59.710 Miguel de Veyra: where, you know, we have to get basically the past stuff from s. 3, because we send it all to S. 3, and then
414 00:34:59.980 ⇒ 00:35:02.110 Miguel de Veyra: get them somehow to super base.
415 00:35:02.330 ⇒ 00:35:03.080 Uttam Kumaran: Okay.
416 00:35:03.700 ⇒ 00:35:07.329 Miguel de Veyra: So that’s like, that’s basically the the a bit more complex.
417 00:35:09.360 ⇒ 00:35:09.890 Miguel de Veyra: Yeah.
418 00:35:11.030 ⇒ 00:35:25.989 Awaish Kumar: Yeah. Like, for, for example, I’ve been working on slack data. And the slack data, which is an S. 3, is like, I think it’s quite easy to rearrange it for the clients, and I can like I’ve been building in it in flow.
419 00:35:26.120 ⇒ 00:35:40.869 Awaish Kumar: and I think we can do it, using that. And we can easily migrate data like from polytomic s. 3, and then s. 3 to super base. And and during that flow also rearrange based on the Plan.
420 00:35:42.530 ⇒ 00:35:43.370 Uttam Kumaran: Okay, cool.
421 00:35:43.990 ⇒ 00:35:46.209 Uttam Kumaran: So I just think that. So
422 00:35:46.760 ⇒ 00:35:51.600 Uttam Kumaran: I mean, right now, we have these 4 sources. I think, Miguel, like the only one that’s not covered right now is linear.
423 00:35:53.720 ⇒ 00:35:56.949 Uttam Kumaran: So I would say, do you want to take linear instead?
424 00:35:57.590 ⇒ 00:35:59.630 Uttam Kumaran: Cause that’s just a whole nother like.
425 00:35:59.970 ⇒ 00:36:00.990 Miguel de Veyra: Yeah, yeah, sure.
426 00:36:01.770 ⇒ 00:36:06.509 Uttam Kumaran: That way. Casey can work on the slack stuff. I mean, it’s
427 00:36:06.720 ⇒ 00:36:09.430 Uttam Kumaran: you can work on stuff talking to a waste today on that.
428 00:36:09.840 ⇒ 00:36:11.829 Uttam Kumaran: We’re all working on it together. I just
429 00:36:11.970 ⇒ 00:36:17.130 Uttam Kumaran: github is moving like considering moving their repo mix stuff.
430 00:36:17.130 ⇒ 00:36:19.260 Miguel de Veyra: Oh, okay, okay, so it’s bossed right now.
431 00:36:20.200 ⇒ 00:36:23.530 Uttam Kumaran: Well, not pause. I mean we. Why don’t we do it?
432 00:36:25.652 ⇒ 00:36:32.719 Awaish Kumar: Basically, I have created a script which is loading data to S. 3. We just have to now
433 00:36:33.270 ⇒ 00:36:35.399 Awaish Kumar: further, like, just move it.
434 00:36:35.910 ⇒ 00:36:41.259 Awaish Kumar: Oh, no regular basis, and then move it to super base.
435 00:36:42.490 ⇒ 00:36:49.050 Uttam Kumaran: Okay, yeah. So can you link that that script here a wish.
436 00:36:49.820 ⇒ 00:36:54.380 Awaish Kumar: Okay, it is I. I can link it here. Yeah, I created a new repo.
437 00:36:54.730 ⇒ 00:36:55.280 Uttam Kumaran: Oh, nice!
438 00:36:55.280 ⇒ 00:36:56.330 Awaish Kumar: Lived in India.
439 00:36:57.020 ⇒ 00:36:59.700 Awaish Kumar: So I will just link that repository here.
440 00:37:03.280 ⇒ 00:37:04.500 Uttam Kumaran: Yeah, what is it called?
441 00:37:05.640 ⇒ 00:37:07.480 Awaish Kumar: It’s called dexter pipelines.
442 00:37:09.572 ⇒ 00:37:11.410 Uttam Kumaran: Okay, hold on.
443 00:37:13.300 ⇒ 00:37:16.590 Uttam Kumaran: Oh, they changed the way Github looks. Heck!
444 00:37:22.640 ⇒ 00:37:27.090 Uttam Kumaran: I don’t see it there, so maybe you might have to share it.
445 00:37:31.410 ⇒ 00:37:32.900 Awaish Kumar: You cannot see it in the.
446 00:37:33.850 ⇒ 00:37:39.530 Uttam Kumaran: Never mind. Never mind. I got it. I got it. Sorry. Their Ui, the other search function didn’t work.
447 00:37:41.400 ⇒ 00:37:44.420 Uttam Kumaran: Okay, cool. So let me put this
448 00:37:44.560 ⇒ 00:37:52.049 Uttam Kumaran: here, and the the pipeline that you mentioned is Github to S. 3 pipeline perfect. We’ll probably need to do
449 00:37:52.390 ⇒ 00:37:54.749 Uttam Kumaran: me, and you can do a larger like airflow
450 00:37:54.890 ⇒ 00:37:58.519 Uttam Kumaran: our Daxter Walkthrough with everybody. But okay, this is great.
451 00:37:59.140 ⇒ 00:37:59.960 Uttam Kumaran: So.
452 00:37:59.960 ⇒ 00:38:02.769 Awaish Kumar: Yeah, like, Dexter is like, kind of
453 00:38:03.330 ⇒ 00:38:09.679 Awaish Kumar: is, is it evolving tool? They have added lots of features recently. So I’m getting like some.
454 00:38:10.010 ⇒ 00:38:14.609 Awaish Kumar: I learned something and and then find out. Okay. It was outdated and.
455 00:38:15.110 ⇒ 00:38:18.180 Uttam Kumaran: I feel like it’s better than airflow, like the airflow. 3.
456 00:38:20.610 ⇒ 00:38:22.400 Awaish Kumar: Like. I have worked quite
457 00:38:22.930 ⇒ 00:38:28.689 Awaish Kumar: well with airflow. I think that’s and
458 00:38:29.690 ⇒ 00:38:38.069 Awaish Kumar: The only good thing about like between Dexter and flow is about the Dexter sales. They provide data lineage
459 00:38:38.240 ⇒ 00:38:47.050 Awaish Kumar: like we can. If we would just want to work on like kind of DVD thing on Dexter. That’s then it’s good because
460 00:38:47.280 ⇒ 00:38:51.770 Awaish Kumar: they provide like we can write assets for each
461 00:38:51.980 ⇒ 00:38:54.350 Awaish Kumar: function, and then they like kind of
462 00:38:54.680 ⇒ 00:39:03.570 Awaish Kumar: tech, keep track of lineage or something like that. Otherwise airflow is much more powerful in pipeline stuff and orchestration.
463 00:39:04.030 ⇒ 00:39:04.680 Uttam Kumaran: Okay?
464 00:39:07.280 ⇒ 00:39:11.290 Uttam Kumaran: And then the last piece here, maybe Amber, do you want to take on this feedback?
465 00:39:11.770 ⇒ 00:39:13.490 Uttam Kumaran: Yeah, your, I think.
466 00:39:13.692 ⇒ 00:39:14.500 Amber Lin: Think about that one.
467 00:39:14.500 ⇒ 00:39:19.420 Uttam Kumaran: I think you’ll just. You’ll just rock this, and you’re meeting with everybody and building those relationships. Anyways.
468 00:39:20.290 ⇒ 00:39:20.940 Uttam Kumaran: Okay.
469 00:39:21.550 ⇒ 00:39:26.579 Uttam Kumaran: I mean, I feel pretty good about this again. I think, like Casey Miguel like, how do you feel about this
470 00:39:28.180 ⇒ 00:39:29.920 Uttam Kumaran: bread? Now.
471 00:39:34.012 ⇒ 00:39:37.889 Casie Aviles: And then, of course, this leaves this leaves room for like random stuff here and there.
472 00:39:42.030 ⇒ 00:39:43.319 Casie Aviles: Yeah, I’m good with this.
473 00:39:43.610 ⇒ 00:39:48.540 Uttam Kumaran: Okay, and then awash on.
474 00:39:49.840 ⇒ 00:39:51.610 Amber Lin: Your side, any.
475 00:39:51.610 ⇒ 00:39:54.499 Uttam Kumaran: Yeah, let me know what we can update
476 00:39:57.390 ⇒ 00:40:02.240 Uttam Kumaran: or anything I can. We basically need to up, review or approve.
477 00:40:04.470 ⇒ 00:40:09.599 Awaish Kumar: Like, I, I updated on slack data discovery which I’ve been working on.
478 00:40:10.384 ⇒ 00:40:14.429 Awaish Kumar: I can provide access to Dexter for everyone. I actually
479 00:40:15.115 ⇒ 00:40:17.879 Awaish Kumar: edit your credentials with them, but I.
480 00:40:17.880 ⇒ 00:40:24.820 Uttam Kumaran: Yes, so tell me, what’s the like? What’s the like? What’s the pricing like? What’s the plan?
481 00:40:25.840 ⇒ 00:40:35.000 Awaish Kumar: So right now, I’m on a like this is a trial version. After that we can move to starter plan and starter plan is a kind of $10
482 00:40:35.860 ⇒ 00:40:36.850 Awaish Kumar: per month.
483 00:40:39.310 ⇒ 00:40:44.980 Awaish Kumar: And it basically has some limited kind of you want to say.
484 00:40:46.672 ⇒ 00:40:50.940 Awaish Kumar: You like around 10,000, you credits.
485 00:40:50.940 ⇒ 00:40:51.730 Uttam Kumaran: Yeah, whatever.
486 00:40:51.730 ⇒ 00:40:54.969 Awaish Kumar: That is, yeah, how much is a credit?
487 00:40:55.380 ⇒ 00:40:57.150 Awaish Kumar: It’s like one.
488 00:40:57.260 ⇒ 00:41:03.754 Awaish Kumar: Basically, one task in a pipeline is equal to one credit. So if we create a
489 00:41:04.370 ⇒ 00:41:08.439 Awaish Kumar: pipeline which creates like 2 operations and 2 assets.
490 00:41:08.440 ⇒ 00:41:08.890 Uttam Kumaran: I see.
491 00:41:08.890 ⇒ 00:41:15.810 Awaish Kumar: And then one is scheduling. So this is kind of 5 credit pipeline. So every time it runs it’s like 5 credits.
492 00:41:16.260 ⇒ 00:41:16.830 Uttam Kumaran: Okay.
493 00:41:20.130 ⇒ 00:41:25.520 Uttam Kumaran: is this like, the this is like as cheap as this gets. I mean, dude cause airflow is like, basically free.
494 00:41:25.770 ⇒ 00:41:28.280 Uttam Kumaran: Whatever like.
495 00:41:28.650 ⇒ 00:41:29.020 Awaish Kumar: It’s.
496 00:41:29.020 ⇒ 00:41:33.029 Uttam Kumaran: We can easily migrate to airflow right later. So if we need to.
497 00:41:33.800 ⇒ 00:41:42.309 Awaish Kumar: You know. I I kind of it’s it’s kind of a bit different, like we have, if we use proper, like Dexter.
498 00:41:42.540 ⇒ 00:41:45.979 Awaish Kumar: the the features and libraries from Dexter
499 00:41:46.290 ⇒ 00:41:51.660 Awaish Kumar: and like. Then we have to come rewrite some of the scripts.
500 00:41:52.040 ⇒ 00:41:52.450 Uttam Kumaran: Okay.
501 00:41:52.450 ⇒ 00:42:03.870 Awaish Kumar: If we are not writing python native code, right? I import for something from Dexter libraries. Then it needs to rework. If we want to migrate to airflow.
502 00:42:14.105 ⇒ 00:42:14.400 Uttam Kumaran: Oh.
503 00:42:15.320 ⇒ 00:42:18.590 Awaish Kumar: We can try it out. We can try out with
504 00:42:18.840 ⇒ 00:42:26.380 Awaish Kumar: airflow as well like I have. I know I can like deploy and monitor open source version.
505 00:42:26.900 ⇒ 00:42:31.469 Uttam Kumaran: Yeah, let’s do it later. Whatever I don’t know, it’s not worth it right now.
506 00:42:32.090 ⇒ 00:42:32.785 Awaish Kumar: Okay.
507 00:42:33.750 ⇒ 00:42:36.121 Uttam Kumaran: In terms of yeah, in terms of
508 00:42:38.620 ⇒ 00:42:44.999 Uttam Kumaran: yeah, I guess let’s talk about how we want to do this. If we want to split an email. I can give you a split email.
509 00:42:46.150 ⇒ 00:42:49.560 Uttam Kumaran: I mean, the the $100 a month gives us 3 users
510 00:42:54.770 ⇒ 00:42:57.960 Uttam Kumaran: the stolo gives us one user.
511 00:42:57.960 ⇒ 00:42:59.189 Awaish Kumar: One Reservio.
512 00:43:02.130 ⇒ 00:43:05.479 Uttam Kumaran: But we still have 30 days right? How long do? How much longer do we have
513 00:43:06.640 ⇒ 00:43:08.070 Uttam Kumaran: so probably 20 days.
514 00:43:08.301 ⇒ 00:43:10.150 Awaish Kumar: The better of like 2020 days. Yeah.
515 00:43:10.990 ⇒ 00:43:15.350 Uttam Kumaran: Okay, then let’s kick this to later.
516 00:43:18.080 ⇒ 00:43:22.329 Uttam Kumaran: Let’s do. Let’s do. Let’s do this next cycle. We’ll we’ll figure that out later.
517 00:43:26.490 ⇒ 00:43:30.770 Uttam Kumaran: Okay, cool. And then how do you think about how should we move some of these like
518 00:43:31.290 ⇒ 00:43:43.179 Uttam Kumaran: we want to do a meeting to review these? Do you want to like record something or like I I was just gonna go look in S. 3. But like I want to know, similar to the message you sent about the slack messages like if there’s anything in particular to look at.
519 00:43:45.340 ⇒ 00:43:50.849 Awaish Kumar: No, I I’ve been just looking at ways to move it to super base, basically. So they can
520 00:43:51.170 ⇒ 00:44:07.440 Awaish Kumar: work on age building the agents. So that was one way to move the slack. And I think, I can build that flow today for slack and maybe for linear as well, so like it can be moved to supervised. And then
521 00:44:08.096 ⇒ 00:44:15.580 Awaish Kumar: finally, it can be used, because in linear also, we have different projects for different clients. So it’s easy to then
522 00:44:16.440 ⇒ 00:44:19.149 Awaish Kumar: using the project. Id, we can easily and
523 00:44:19.450 ⇒ 00:44:22.250 Awaish Kumar: filter the tickets, basically for the client
524 00:44:22.520 ⇒ 00:44:26.440 Awaish Kumar: and loaded in a table which can be fed into a agent.
525 00:44:29.360 ⇒ 00:44:29.960 Uttam Kumaran: Okay.
526 00:44:30.790 ⇒ 00:44:38.019 Awaish Kumar: So I can. We can work. I can work with Meg and Casey to move it to super base.
527 00:44:38.370 ⇒ 00:44:41.999 Awaish Kumar: and from there they can like take it to build agents.
528 00:44:42.450 ⇒ 00:44:43.010 Uttam Kumaran: Okay.
529 00:44:43.770 ⇒ 00:44:46.629 Uttam Kumaran: So as long as you guys coordinate on this, I’m I’m okay with that.
530 00:44:47.550 ⇒ 00:44:53.649 Awaish Kumar: So right now I’m not stuck on anything, so if if there is anything I can, I will let you know.
531 00:44:53.890 ⇒ 00:44:54.930 Uttam Kumaran: Okay, perfect.
532 00:45:01.980 ⇒ 00:45:03.489 Uttam Kumaran: great. Yeah. Let’s just clean up a call.
533 00:45:03.927 ⇒ 00:45:07.429 Awaish Kumar: Just wanted to know about like like we
534 00:45:07.760 ⇒ 00:45:10.359 Awaish Kumar: kind of use Dexter. But I want to
535 00:45:10.994 ⇒ 00:45:20.719 Awaish Kumar: make this like I I think it would be good if we make this decision with between Dexter and flow now, because after we spent a lot of time in learning Dexter.
536 00:45:20.720 ⇒ 00:45:21.160 Uttam Kumaran: Okay.
537 00:45:21.160 ⇒ 00:45:28.579 Awaish Kumar: And then we know if we have to migrate, then, like we have been spent, we will be spending lots of hours to learn something which, if we are not using.
538 00:45:28.580 ⇒ 00:45:35.420 Uttam Kumaran: I mean. So let’s let’s have a brief conversation now and then. We can bring it up with the data platform crew is.
539 00:45:35.420 ⇒ 00:45:35.899 Awaish Kumar: And then.
540 00:45:35.900 ⇒ 00:45:38.989 Uttam Kumaran: Airflow, you would run it like
541 00:45:39.900 ⇒ 00:45:43.100 Uttam Kumaran: like, where would you? Where would you run an airflow box.
542 00:45:44.366 ⇒ 00:45:53.260 Awaish Kumar: So previously I have run in a in a Ec. 2 machine, and also some machines which are kind of cheaper than
543 00:45:53.910 ⇒ 00:45:54.719 Awaish Kumar: WS.
544 00:45:54.970 ⇒ 00:46:01.819 Awaish Kumar: Oh, but kind of like. So if I have kind of Hun $100 machine
545 00:46:02.433 ⇒ 00:46:05.190 Awaish Kumar: per month, which can be basically used
546 00:46:05.899 ⇒ 00:46:16.420 Awaish Kumar: like for us. It’s like we. We don’t have enough task right now. We maybe use a smaller machine kind of between 50 to $100 per month. We can utilize a machine, to.
547 00:46:16.530 ⇒ 00:46:20.380 Awaish Kumar: to deploy, use airflow, open source, airflow.
548 00:46:25.910 ⇒ 00:46:31.710 Uttam Kumaran: And like, what are the odds like? What’s the what is your expectation in terms of like
549 00:46:31.860 ⇒ 00:46:33.749 Uttam Kumaran: maintenance? And like devops?
550 00:46:35.640 ⇒ 00:46:37.130 Uttam Kumaran: I mean, we’re not doing anything.
551 00:46:37.130 ⇒ 00:46:42.310 Awaish Kumar: So, as I have worked with, we have worked with open source airflow with kind of
552 00:46:42.570 ⇒ 00:46:45.430 Awaish Kumar: around on a single machine.
553 00:46:45.910 ⇒ 00:46:46.540 Uttam Kumaran: Yes, it’s good.
554 00:46:46.540 ⇒ 00:46:52.140 Awaish Kumar: On a single machine. But we have been running task on a using bash.
555 00:46:52.570 ⇒ 00:47:03.240 Awaish Kumar: s ssh, on multiple machines. But yeah, for this setup I have worked for like around 300 to 500 tasks which it can handle.
556 00:47:03.490 ⇒ 00:47:14.279 Awaish Kumar: But then, if we have like more than 1,000 2,000 tasks, then we need to bring in, because then a single scheduler won’t be enough. Then we may have to move up to more
557 00:47:14.530 ⇒ 00:47:18.550 Awaish Kumar: architecture level like a dip. Managed version kind of has to know more or whatever.
558 00:47:20.290 ⇒ 00:47:25.040 Uttam Kumaran: I mean, should we consider like using astronomer.
559 00:47:26.870 ⇒ 00:47:34.040 Awaish Kumar: So for the pricing for the stone over, I’m really not sure, because previously they were kind of fixed.
560 00:47:34.540 ⇒ 00:47:37.719 Awaish Kumar: they were on a fixed pricing like 200 or something of
561 00:47:38.120 ⇒ 00:47:42.689 Awaish Kumar: 200 $300 per month. Now they are like also using credits.
562 00:47:43.210 ⇒ 00:47:48.630 Awaish Kumar: So I’m not sure I have not read into detail how they calculate these credits.
563 00:47:50.990 ⇒ 00:47:57.239 Uttam Kumaran: I actually. So here’s a couple of things. One, we have a ton of Microsoft and aws credits.
564 00:47:57.920 ⇒ 00:47:59.030 Uttam Kumaran: Okay.
565 00:47:59.850 ⇒ 00:48:05.099 Awaish Kumar: Aw, Microsoft, okay, on aws, we have, I think, managed airflow.
566 00:48:05.750 ⇒ 00:48:06.349 Uttam Kumaran: Yeah, let me
567 00:48:06.550 ⇒ 00:48:07.120 Awaish Kumar: They do too much.
568 00:48:07.120 ⇒ 00:48:14.170 Uttam Kumaran: Let me just let me just check like if I even have the credits or like, let me just give me one second. Let me just check how much we have cause.
569 00:48:14.720 ⇒ 00:48:23.180 Uttam Kumaran: Now that we talked a little bit about it, I’m sort of more on team airflow, because
570 00:48:23.970 ⇒ 00:48:28.379 Uttam Kumaran: I’ve I I used to run airflow on Gcp. And it was fine.
571 00:48:29.190 ⇒ 00:48:30.410 Awaish Kumar: From composer.
572 00:48:30.560 ⇒ 00:48:31.730 Uttam Kumaran: Yeah, composer.
573 00:48:33.730 ⇒ 00:48:35.610 Uttam Kumaran: And it was fine.
574 00:48:37.220 ⇒ 00:48:44.879 Uttam Kumaran: and as long as everything goes through version control, there’s not going to be a ton of people like scheduling jobs. And we’re not. We’re we’re not really like.
575 00:48:45.100 ⇒ 00:48:47.239 Uttam Kumaran: we’re not like a product company. So
576 00:48:47.340 ⇒ 00:48:56.010 Uttam Kumaran: ultimately, we just want to make sure that we can get the Dbt failures, and that people can go debug the Dbt jobs for the most part. That’s probably going to be the number one use case.
577 00:48:58.080 ⇒ 00:48:59.510 Uttam Kumaran: Right? So
578 00:49:00.120 ⇒ 00:49:07.789 Uttam Kumaran: it’s gonna be like, is the ui like cause this is for me. This is like, 4 years ago the ui sucked so it was like horrible to like.
579 00:49:07.940 ⇒ 00:49:09.570 Uttam Kumaran: Get people to use it.
580 00:49:13.350 ⇒ 00:49:14.649 Awaish Kumar: Cash flow, do I.
581 00:49:17.160 ⇒ 00:49:17.850 Uttam Kumaran: Yeah.
582 00:49:21.000 ⇒ 00:49:25.090 Awaish Kumar: Yeah, like, it’s kind of better than previous. But it’s still like, if
583 00:49:25.340 ⇒ 00:49:33.709 Awaish Kumar: if we are like, we’ll be putting like hundreds of tasks in a single dag is going to get a mess of like
584 00:49:34.460 ⇒ 00:49:37.020 Awaish Kumar: it. It won’t the you.
585 00:49:37.140 ⇒ 00:49:42.930 Awaish Kumar: The visualization of those workflows will be which will not be that Killino.
586 00:49:46.340 ⇒ 00:49:47.629 Uttam Kumaran: As as Daxter.
587 00:49:50.160 ⇒ 00:49:56.230 Awaish Kumar: On Dexter, like, it’s kind of yeah, this is, I think it’s the same for Dexter as well. Right? We have.
588 00:49:56.230 ⇒ 00:50:02.280 Uttam Kumaran: So. So here’s another thing is like we have a couple of other tools that we we want to consider running open source.
589 00:50:02.750 ⇒ 00:50:05.510 Uttam Kumaran: For example, we could run windmill, open source.
590 00:50:07.010 ⇒ 00:50:07.770 Awaish Kumar: Okay.
591 00:50:08.160 ⇒ 00:50:11.069 Uttam Kumaran: So my broader question for you is like.
592 00:50:11.810 ⇒ 00:50:16.969 Uttam Kumaran: for example, a lot of the tools I use, I decided to use like document so as open source.
593 00:50:17.350 ⇒ 00:50:22.479 Uttam Kumaran: A windmill is open source N. 8 N. Is open source.
594 00:50:24.700 ⇒ 00:50:27.540 Uttam Kumaran: I’m missing a couple, but
595 00:50:29.286 ⇒ 00:50:34.990 Uttam Kumaran: like we could run our own and like, save probably another 502,000 bucks a month.
596 00:50:37.570 ⇒ 00:50:39.410 Uttam Kumaran: I wonder if, like, we should just
597 00:50:39.680 ⇒ 00:50:46.789 Uttam Kumaran: come to a larger decision on open source versus cloud managed pipelines.
598 00:50:49.830 ⇒ 00:50:51.070 Uttam Kumaran: You know, for some of this.
599 00:50:53.060 ⇒ 00:50:53.760 Awaish Kumar: Yeah.
600 00:50:56.690 ⇒ 00:50:57.899 Awaish Kumar: But with the
601 00:50:58.600 ⇒ 00:51:05.180 Awaish Kumar: like. What? I would say that for a smaller scale we are okay with running open source.
602 00:51:05.310 ⇒ 00:51:11.679 Awaish Kumar: But if when we grow, we are growing like we need a team to maintain that otherwise we have to migrate to cloud.
603 00:51:12.050 ⇒ 00:51:12.650 Awaish Kumar: So.
604 00:51:12.650 ⇒ 00:51:13.190 Uttam Kumaran: See.
605 00:51:14.240 ⇒ 00:51:17.080 Awaish Kumar: But on like as like as I said.
606 00:51:17.330 ⇒ 00:51:20.859 Uttam Kumaran: But, like, let’s say we double. It’s still not like crazy.
607 00:51:24.100 ⇒ 00:51:30.660 Uttam Kumaran: like if we if we grow like 5 top 10 times as big, sure.
608 00:51:32.100 ⇒ 00:51:36.450 Awaish Kumar: Yeah, that’s that’s okay. Like, if we, for now we if we have, like
609 00:51:38.470 ⇒ 00:51:43.219 Awaish Kumar: 1020 pipelines, if we migrate to 50, 60 pipelines.
610 00:51:43.450 ⇒ 00:51:46.830 Awaish Kumar: it will be okay, like for for some.
611 00:51:46.830 ⇒ 00:51:53.210 Uttam Kumaran: I mean, like, for the most part we’re not. We don’t do any modification of the Dbt pipelines like
612 00:51:53.510 ⇒ 00:51:58.719 Uttam Kumaran: from the day the kind start with us right like we don’t really make adjustments.
613 00:51:59.890 ⇒ 00:52:03.039 Uttam Kumaran: The only thing that I want to figure out is like.
614 00:52:03.160 ⇒ 00:52:07.320 Uttam Kumaran: how can we have it as a blocking step for Cicd in airflow.
615 00:52:09.920 ⇒ 00:52:17.490 Uttam Kumaran: See what I mean like if we want to run tests and stuff like can airflow block the Pr.
616 00:52:18.460 ⇒ 00:52:19.660 Uttam Kumaran: probably right.
617 00:52:25.680 ⇒ 00:52:27.760 Awaish Kumar: I I don’t think so.
618 00:52:28.970 ⇒ 00:52:34.139 Amber Lin: Hi, guys, quick. Note, I need to use this room for the pool for its meeting.
619 00:52:34.140 ⇒ 00:52:35.739 Uttam Kumaran: Oh, yeah. Yeah. Yeah. No. Problem.
620 00:52:36.132 ⇒ 00:52:48.700 Amber Lin: Can you guys use another meeting room and also for our AI team? What are we gonna work on? What are we gonna ship tomorrow. What are we working on today?
621 00:52:50.510 ⇒ 00:52:56.799 Amber Lin: We have the figuring out the s slack s 3 to super base for Matamor.
622 00:52:59.900 ⇒ 00:53:00.600 Amber Lin: Miguel.
623 00:53:00.760 ⇒ 00:53:06.719 Miguel de Veyra: Yeah, I can work on, I think by end of day tomorrow, probably a couple of initialization on the Asians.
624 00:53:07.453 ⇒ 00:53:09.580 Amber Lin: I have to speak with Casey first.st
625 00:53:09.580 ⇒ 00:53:12.069 Amber Lin: Okay, sounds good. So.
626 00:53:12.070 ⇒ 00:53:19.840 Miguel de Veyra: Then the sales agent, the links are there. But yeah, I I need more context from from Robert.
627 00:53:19.840 ⇒ 00:53:26.750 Amber Lin: Yeah, would you be able to just quickly chat with Utam about that.
628 00:53:27.390 ⇒ 00:53:30.220 Miguel de Veyra: I mean we are chatting on it on the Sales Channel.
629 00:53:30.420 ⇒ 00:53:35.180 Uttam Kumaran: Yeah, if you just if you just send where I can, where we can edit that, then.
630 00:53:35.660 ⇒ 00:53:42.860 Amber Lin: Awesome. So can I put for initialization the deadlines? Can I put it for tomorrow?
631 00:53:46.330 ⇒ 00:53:48.370 Miguel de Veyra: Probably 2 of it tomorrow. Yes.
632 00:53:48.370 ⇒ 00:53:49.315 Amber Lin: Okay.
633 00:53:50.830 ⇒ 00:53:56.250 Amber Lin: Oh, how come? It’s just 2 of it. I thought you said we’re replicating the workflows.
634 00:53:56.840 ⇒ 00:53:58.660 Miguel de Veyra: Yeah. But I checked the workflows
635 00:53:58.900 ⇒ 00:54:01.710 Miguel de Veyra: cause we need to basically migrate. I checked the.
636 00:54:01.820 ⇒ 00:54:03.410 Amber Lin: The ones Casey did.
637 00:54:03.770 ⇒ 00:54:04.110 Amber Lin: Okay.
638 00:54:04.110 ⇒ 00:54:06.040 Miguel de Veyra: Need to get the slack data. But yeah.
639 00:54:06.040 ⇒ 00:54:07.936 Amber Lin: I see. Sounds good.
640 00:54:08.640 ⇒ 00:54:18.479 Amber Lin: We have urban stems, pool ports. Eden, Javi, since you’re still here, which 2 should we initialize? Javi? We have some stuff. I don’t know if it’s good, though.
641 00:54:23.310 ⇒ 00:54:26.980 Uttam Kumaran: I would just pick. I would probably just do the Javi one if you have a chance.
642 00:54:27.430 ⇒ 00:54:29.209 Miguel de Veyra: Okay, Javier, and.
643 00:54:29.210 ⇒ 00:54:30.960 Amber Lin: And what what else.
644 00:54:31.320 ⇒ 00:54:34.490 Uttam Kumaran: I would do, Javi, and I would do. I would do. Eden. Yeah.
645 00:54:34.490 ⇒ 00:54:35.960 Amber Lin: Okay, sounds good.
646 00:54:36.310 ⇒ 00:54:36.840 Amber Lin: So.
647 00:54:36.840 ⇒ 00:54:38.149 Uttam Kumaran: Get the most feedback.
648 00:54:39.510 ⇒ 00:54:40.370 Amber Lin: I see.
649 00:54:41.370 ⇒ 00:54:42.549 Miguel de Veyra: Okay, yeah. Noted on that.
650 00:54:45.730 ⇒ 00:54:55.739 Amber Lin: and then for the other ones. I know you’re you guys are having a holiday Thursday, so I’ll mark the other ones as either. Later this week we can move it to next week.
651 00:54:56.090 ⇒ 00:54:57.369 Miguel de Veyra: I think Friday should be okay.
652 00:54:57.370 ⇒ 00:54:58.615 Amber Lin: Okay, sounds good.
653 00:54:59.410 ⇒ 00:55:05.049 Amber Lin: And then maybe we can get started on at least like
654 00:55:05.240 ⇒ 00:55:27.880 Amber Lin: under, because for S. 3 to super basic blocker for us is, we need to understand what the end goal should look like. So some someone like the ticket where we want to see. Okay, what the spreadsheet of what’s the format of slack data? We want to see of what was brought up. Okay, what are what are the data you need? Like, what will benefit?
655 00:55:28.240 ⇒ 00:55:29.050 Amber Lin: Yeah.
656 00:55:29.300 ⇒ 00:55:34.760 Miguel de Veyra: We’ll speak to, I think, for that part, unless at least on my end. I’ll speak to ovation next week.
657 00:55:34.980 ⇒ 00:55:43.229 Amber Lin: Yeah, okay, sounds good. We probably need another like, I’ll probably split out some tickets to get that done for.
658 00:55:43.230 ⇒ 00:55:43.690 Miguel de Veyra: Okay.
659 00:55:43.690 ⇒ 00:55:48.309 Amber Lin: Github and linear, just so that we fulfill the requirements before we actually start.
660 00:55:48.830 ⇒ 00:55:53.799 Awaish Kumar: Yeah, like, I have shared the sample. If you if you see the message I’ve shared the
661 00:55:53.910 ⇒ 00:55:57.599 Awaish Kumar: I’ve already created simple with existing data and
662 00:55:59.690 ⇒ 00:56:07.199 Awaish Kumar: in the my recent message in in group and and and also.
663 00:56:07.200 ⇒ 00:56:07.913 Miguel de Veyra: Sorry guys.
664 00:56:08.270 ⇒ 00:56:12.110 Awaish Kumar: We have started working, creating a flow, as I mentioned.
665 00:56:12.480 ⇒ 00:56:15.279 Awaish Kumar: to move migrate data from S. 3 to
666 00:56:15.856 ⇒ 00:56:21.290 Awaish Kumar: to super base. And I think I have found a way to do that as well. Using any 10.
667 00:56:21.790 ⇒ 00:56:22.860 Amber Lin: Okay.
668 00:56:22.860 ⇒ 00:56:23.440 Awaish Kumar: So.
669 00:56:23.440 ⇒ 00:56:27.876 Amber Lin: Oh, okay, I’ll let you guys talk about it then.
670 00:56:28.320 ⇒ 00:56:30.100 Awaish Kumar: I think I would just need like
671 00:56:30.400 ⇒ 00:56:39.660 Awaish Kumar: 2 min with with any of you guys. So probably you can help me with some edit and questions, but otherwise I can build that flow.
672 00:56:40.280 ⇒ 00:56:40.830 Amber Lin: Awesome.
673 00:56:40.830 ⇒ 00:56:41.490 Miguel de Veyra: Okay. Sure.
674 00:56:41.490 ⇒ 00:56:42.870 Amber Lin: But will you guys.
675 00:56:42.870 ⇒ 00:56:46.909 Miguel de Veyra: We can. We can probably hop on a 30 min. Call tomorrow. No, Casey.
676 00:56:47.250 ⇒ 00:56:48.050 Casie Aviles: Sure, sure.
677 00:56:48.670 ⇒ 00:56:49.970 Miguel de Veyra: Yeah, I think that would be helpful.
678 00:56:50.590 ⇒ 00:56:57.030 Amber Lin: I mean, I guess I wish only needed like 2 quick answers. I’ll leave it to you guys. But maybe.
679 00:56:57.030 ⇒ 00:56:58.910 Miguel de Veyra: Yeah, I mean, we have some questions, too.
680 00:56:59.080 ⇒ 00:57:05.429 Amber Lin: Great a quick meeting today, because we also, I know for Casey there’s a ticket of like.
681 00:57:06.040 ⇒ 00:57:10.929 Awaish Kumar: Yeah, I’m available today. If, like, you guys wanna meet like, just let me.
682 00:57:11.900 ⇒ 00:57:12.440 Miguel de Veyra: Okay.
683 00:57:13.680 ⇒ 00:57:14.330 Amber Lin: Yeah.
684 00:57:15.060 ⇒ 00:57:15.490 Miguel de Veyra: How’s everyone?
685 00:57:15.490 ⇒ 00:57:18.639 Amber Lin: Able to do that today. I need to jump. But can we do that?
686 00:57:18.640 ⇒ 00:57:19.270 Miguel de Veyra: Okay.
687 00:57:19.490 ⇒ 00:57:20.260 Amber Lin: Awesome.
688 00:57:20.740 ⇒ 00:57:21.690 Amber Lin: Okay.
689 00:57:22.380 ⇒ 00:57:22.960 Casie Aviles: Thanks guys.
690 00:57:22.960 ⇒ 00:57:23.810 Awaish Kumar: See you bye.
691 00:57:23.810 ⇒ 00:57:24.400 Miguel de Veyra: I’ll do it.