Meeting Title: Data x AI team Meeting Date: 2025-04-30 Meeting participants: Luke Daque, Uttam Kumaran, Amber Lin, Demilade Agboola, Miguel De Veyra, Casie Aviles, Caio Velasco
WEBVTT
1 00:01:58.140 ⇒ 00:01:59.100 Demilade Agboola: Hello!
2 00:02:01.500 ⇒ 00:02:02.820 Amber Lin: Hi! There!
3 00:02:04.333 ⇒ 00:02:11.880 Amber Lin: We can wait a bit where we can just get started, and then they can get filled in. What do you think.
4 00:02:13.855 ⇒ 00:02:20.160 Demilade Agboola: Let me see, who are we waiting for? Botham Miguel and Kyle.
5 00:02:20.860 ⇒ 00:02:27.300 Amber Lin: Don’t know if it’s it’s gonna join, which I’m probably can join later in this meeting.
6 00:02:27.410 ⇒ 00:02:32.660 Amber Lin: Think right? Like the 1st 30 min he might be in a
7 00:02:33.030 ⇒ 00:02:39.250 Amber Lin: oh, no, he doesn’t have anything this 1st 30 min. Okay, let me ping him.
8 00:02:40.200 ⇒ 00:02:40.860 Amber Lin: Hey? Everyone!
9 00:02:43.100 ⇒ 00:02:47.510 Amber Lin: Hi! Devil, can you, Ping Kyle? I’ll go ping Tom.
10 00:02:48.190 ⇒ 00:02:50.640 Demilade Agboola: Okay. I’ll do that right now.
11 00:03:25.220 ⇒ 00:03:29.010 Amber Lin: Okay, both of them said. He will, so he will be coming.
12 00:03:30.870 ⇒ 00:03:32.510 Demilade Agboola: Did you say will, or wouldn’t.
13 00:03:33.547 ⇒ 00:03:36.569 Amber Lin: Will. I’m gonna give him the meeting link.
14 00:04:04.640 ⇒ 00:04:05.460 Caio Velasco: Through.
15 00:04:08.950 ⇒ 00:04:12.560 Amber Lin: Hi, just waiting on Utam, he said. He’ll be coming so.
16 00:04:13.220 ⇒ 00:04:16.409 Caio Velasco: Yeah, I was in a on a meeting with him, and I wish.
17 00:04:17.610 ⇒ 00:04:20.000 Amber Lin: Okay, we have everyone here.
18 00:04:20.300 ⇒ 00:04:24.749 Amber Lin: Hello, okay. Let’s kick it off. Who wants to start.
19 00:04:28.351 ⇒ 00:04:34.389 Demilade Agboola: So basically, what we’ve been working on like data platform issues, generally speaking.
20 00:04:34.520 ⇒ 00:04:38.150 Demilade Agboola: And Karen and I have been working on data documentation.
21 00:04:38.920 ⇒ 00:04:50.489 Demilade Agboola: And one of the things we’re thinking about from an a perspective is what what are things we struggle with. And we figured out like gaining context on a lot of what we do can be
22 00:04:51.240 ⇒ 00:04:57.100 Demilade Agboola: quite troublesome or quite hard, especially if you’re not new on if you’re new on the project, and the product has started before you.
23 00:04:57.807 ⇒ 00:05:03.369 Demilade Agboola: So to that we decided we came up with this documentation flow.
24 00:05:03.640 ⇒ 00:05:07.329 Demilade Agboola: I don’t know if you’ve seen it. I I tagged amber to it.
25 00:05:07.769 ⇒ 00:05:13.269 Demilade Agboola: But basically one. What we’re trying to now do is come up with like an Mvp. Concept of it.
26 00:05:13.960 ⇒ 00:05:17.730 Demilade Agboola: And we want to be able to at least use it
27 00:05:18.610 ⇒ 00:05:23.120 Demilade Agboola: a product that we currently have in the works. Maybe Javi, for instance.
28 00:05:23.719 ⇒ 00:05:25.969 Demilade Agboola: put together like the repo.
29 00:05:26.510 ⇒ 00:05:28.499 Demilade Agboola: the repo mix of the repo
30 00:05:29.055 ⇒ 00:05:32.409 Demilade Agboola: put together some of the documentation that exists in notion
31 00:05:32.630 ⇒ 00:05:35.399 Demilade Agboola: and just kind of see how
32 00:05:35.970 ⇒ 00:05:42.780 Demilade Agboola: we’re able to build a bot that answers like fundamental questions that an ae would ask or an analyst would ask about the project.
33 00:05:42.910 ⇒ 00:05:49.770 Demilade Agboola: So, for instance, if we’re looking at Javi, the question is, could be. How is cogs calculated, for instance, or
34 00:05:51.330 ⇒ 00:06:06.023 Demilade Agboola: What does it mean? Like like, just like just things about orders, for instance, how how is order, Cal, how is an order calculated here? Or how do we handle Amazon orders versus how we handle another source of orders, things like that, like something
35 00:06:06.760 ⇒ 00:06:14.449 Demilade Agboola: an analyst or an ae would need to know while building out the project, and would help speed up the process in which they would need to
36 00:06:16.110 ⇒ 00:06:19.560 Demilade Agboola: learn what’s going on in the project before they can start work.
37 00:06:20.380 ⇒ 00:06:28.970 Demilade Agboola: So I don’t know if anyone had like, if Kyle had anything to add. But that’s just basically the high level of like what? What exactly we were trying to bring today.
38 00:06:31.230 ⇒ 00:06:40.570 Uttam Kumaran: Yeah, I think the only thing I’ll I’ll mention is, I think, that the this data team in particular, is going to be the real
39 00:06:41.580 ⇒ 00:06:53.990 Uttam Kumaran: like, basically the the clients of the core agents. I mean, these will be the core users. But also I want them to be involved. You know, sort of in this next phase where we’re
40 00:06:54.130 ⇒ 00:06:58.740 Uttam Kumaran: we’re deciding on like, how the agent is gonna actually answer some of these questions.
41 00:06:59.326 ⇒ 00:07:24.519 Uttam Kumaran: And so I’m really, really excited. I think that this team is going to provide a really great structure for what kind of questions they expect the bot to answer and sort of push the AI team forward to make sure those are possible. I think also, the AI team will sort of be able to share how the the structure is getting built. And hopefully, you know the collaboration. You know, basically what my hope is that this takes really a lot of stress off of
42 00:07:24.630 ⇒ 00:07:28.775 Uttam Kumaran: tons and tons of like information gathering and information. Retrieval
43 00:07:29.360 ⇒ 00:07:37.480 Uttam Kumaran: forces us to structure our documents, you know, in a much better way, and then really just like helps every additional engineer that works on any project.
44 00:07:38.080 ⇒ 00:07:41.230 Uttam Kumaran: And and not only the engineers, but Pm’s sales.
45 00:07:41.710 ⇒ 00:07:47.799 Uttam Kumaran: So this is like a huge project for us, and I don’t. I don’t particularly. There’s only one other
46 00:07:48.480 ⇒ 00:07:52.339 Uttam Kumaran: sort of consultancy that I’ve seen that’s done this.
47 00:07:52.460 ⇒ 00:08:04.029 Uttam Kumaran: and their Demos looked really really bad and they said they spent a lot of time on it, so I don’t. I don’t know. Unfortunately, I don’t know whether there’s much.
48 00:08:04.300 ⇒ 00:08:17.340 Uttam Kumaran: There’s many great examples of this work being done not only in just other AI consultancies, but in just other businesses. So part of this stuff, it’s going to be new, so we may not have all the answers. In fact, like, I don’t know enough.
49 00:08:18.145 ⇒ 00:08:27.210 Uttam Kumaran: However, that’s also like extremely motivating where we’re gonna start to see what’s possible by bringing these sorts of teams together. So yeah, that’s sort of this
50 00:08:27.500 ⇒ 00:08:29.280 Uttam Kumaran: the stage from my end.
51 00:08:38.363 ⇒ 00:08:45.049 Uttam Kumaran: So yeah, I mean, I I think the biggest thing for me is just like how any questions that either team had
52 00:08:45.678 ⇒ 00:08:49.889 Uttam Kumaran: on on that core document, you know, and and
53 00:08:50.010 ⇒ 00:08:52.740 Uttam Kumaran: maybe demalade or Kyle. If you guys want to lead from
54 00:08:53.040 ⇒ 00:08:57.039 Uttam Kumaran: from the data side, we can sort of take this wherever we want to go.
55 00:08:58.590 ⇒ 00:09:02.820 Amber Lin: Yeah, do we wanna share screen? And also.
56 00:09:03.000 ⇒ 00:09:16.870 Amber Lin: do we have any more visual representations of like the workflows or key components? Because right now. It’s a big chunk of big document. Sometimes it’s a little bit hard to wrap my head around it.
57 00:09:19.520 ⇒ 00:09:23.220 Demilade Agboola: Unfortunately, right now we we just have text. But
58 00:09:23.590 ⇒ 00:09:24.190 Amber Lin: I see.
59 00:09:24.190 ⇒ 00:09:29.694 Demilade Agboola: Going forward, we can always try and add more like flow charts.
60 00:09:30.914 ⇒ 00:09:36.910 Amber Lin: Do you guys wanna share screen and like, guide us through where to look for what.
61 00:09:38.480 ⇒ 00:09:39.770 Demilade Agboola: Okay,
62 00:09:42.130 ⇒ 00:09:55.969 Demilade Agboola: so are we. Should we walk through the documentation? Or should we walk through what like use case would be like in terms of like, if I walk through Javi and like, oh, this will be like the notion, Doc, where we have some of this information.
63 00:09:56.160 ⇒ 00:10:02.740 Demilade Agboola: and then we want to like. Add this, and then we want to answer these sort of questions like, which would you? Which would you prefer.
64 00:10:02.840 ⇒ 00:10:07.869 Miguel de Veyra: I think quote should be fine, but preferably where we’ll get the data first.st
65 00:10:09.230 ⇒ 00:10:10.030 Demilade Agboola: Okay.
66 00:10:10.170 ⇒ 00:10:10.500 Miguel de Veyra: Total.
67 00:10:10.500 ⇒ 00:10:10.850 Demilade Agboola: So.
68 00:10:10.850 ⇒ 00:10:11.750 Miguel de Veyra: Annotation. First.st
69 00:10:12.620 ⇒ 00:10:19.130 Demilade Agboola: Okay, can you? Can you walk us through like Javi’s documentation? And just like, kind of how the kind of questions we’re looking to
70 00:10:19.290 ⇒ 00:10:22.399 Demilade Agboola: ask based off that documentation.
71 00:10:26.430 ⇒ 00:10:30.090 Caio Velasco: Did you? Did? Did you say my name? You didn’t get it.
72 00:10:30.610 ⇒ 00:10:31.320 Demilade Agboola: Yes. Okay.
73 00:10:31.320 ⇒ 00:10:34.219 Caio Velasco: Okay, because my my headphone is not very good tonight.
74 00:10:35.080 ⇒ 00:10:35.610 Demilade Agboola: So.
75 00:10:38.720 ⇒ 00:10:40.089 Caio Velasco: Let me see here.
76 00:11:03.940 ⇒ 00:11:06.449 Caio Velasco: Okay, get an icing machine.
77 00:11:08.550 ⇒ 00:11:09.190 Casie Aviles: Yes.
78 00:11:09.770 ⇒ 00:11:18.136 Caio Velasco: Yes, not sure. It’s like, should we give like an overview?
79 00:11:18.750 ⇒ 00:11:24.719 Caio Velasco: I mean, we already you can already have. But I’m not really, I think that at the end of the day we are just
80 00:11:24.930 ⇒ 00:11:31.290 Caio Velasco: trying to make I our lives like engineers life easier when
81 00:11:31.917 ⇒ 00:11:50.202 Caio Velasco: asking questions or looking for answers, or understanding what is new, or as Daniel? And he said, If you wanna ask a question about like how was ordered, modeled, or or anything really like that’s that’s the main idea. And as I understand, we have
82 00:11:53.270 ⇒ 00:11:57.049 Caio Velasco: well, like some I some ideas for sources.
83 00:11:57.512 ⇒ 00:12:26.510 Caio Velasco: For example, it could come from a loom video, or the latest Pr where the model was edited. Did the Dbt models themselves, which are in Github and maybe even one of the most important ones something that usually it’s defined with the client. Something like, you know, what are cogs? What would that mean, how is that calculated? etc? So this would be more or less the
84 00:12:26.680 ⇒ 00:12:29.719 Caio Velasco: I mean a, as we mentioned, like the data, the sources.
85 00:12:29.990 ⇒ 00:12:46.909 Caio Velasco: And and then we we sort of about like an example of a flow. As I mentioned, like someone would be asking this question, and the bot would come. And you know, do the job depending on? Where are the the post? The potential answers?
86 00:12:47.160 ⇒ 00:12:58.270 Caio Velasco: So I mean, in general, it’s that there’s not many more complexity in this. So that’s I think we can start with this, and if you have anything else to to add, feel free.
87 00:13:02.210 ⇒ 00:13:10.599 Demilade Agboola: I think the only thing to add is just like, can we sort of show like? So the data that we have available, you know, like for Joby, for instance, like
88 00:13:10.760 ⇒ 00:13:16.430 Demilade Agboola: I know, you have some documentation. I know Javi does have a little documentation, just generally speaking.
89 00:13:16.730 ⇒ 00:13:24.970 Demilade Agboola: So if we can show that and then, obviously, we can. Another source of data will be the report like the report mix.
90 00:13:25.230 ⇒ 00:13:37.700 Demilade Agboola: So if we put those 2 things together like documentation and the repo mix, how far can we go? And how much more do we need in terms of context? Because this is like an Mvp. That we’re trying to build out
91 00:13:38.020 ⇒ 00:13:43.720 Demilade Agboola: and just trying to see like how good it is right now, and what potentially.
92 00:13:43.830 ⇒ 00:13:46.620 Demilade Agboola: you know, a version 2 would look like would look like.
93 00:13:48.280 ⇒ 00:13:55.849 Caio Velasco: Okay. So 1, st one would be what like like the notion document, for example, the one on stack bits.
94 00:13:56.260 ⇒ 00:13:58.069 Caio Velasco: the one we mentioned yesterday.
95 00:13:58.910 ⇒ 00:14:02.910 Demilade Agboola: Yeah. Oh, for any clients, really. Yeah, we just go through.
96 00:14:08.390 ⇒ 00:14:09.030 Miguel de Veyra: No
97 00:14:09.030 ⇒ 00:14:18.740 Miguel de Veyra: sorry. I have a question for the loom videos. Do we store it anywhere? Because I think the transcripts for that. We could also use this context, for
98 00:14:19.120 ⇒ 00:14:24.450 Miguel de Veyra: for the bot is there like a centralized place where we store that.
99 00:14:25.060 ⇒ 00:14:25.480 Demilade Agboola: Right now.
100 00:14:25.480 ⇒ 00:14:26.790 Caio Velasco: I agree.
101 00:14:27.390 ⇒ 00:14:31.060 Caio Velasco: Yeah, but but isn’t. I wish
102 00:14:31.470 ⇒ 00:14:37.299 Caio Velasco: bringing that into S. 3 like a database with all those things like loans and.
103 00:14:38.140 ⇒ 00:14:38.700 Miguel de Veyra: Okay.
104 00:14:39.610 ⇒ 00:14:41.030 Casie Aviles: We’re not sure. Right?
105 00:14:42.580 ⇒ 00:14:43.700 Casie Aviles: Yeah, sorry.
106 00:14:43.970 ⇒ 00:14:49.240 Casie Aviles: So, for I know that loom videos are stored in our shared library. So.
107 00:14:49.480 ⇒ 00:14:57.190 Casie Aviles: But the the thing with loom is that we don’t really have like Api for that like, that’s 1 of the things we
108 00:15:00.470 ⇒ 00:15:14.609 Casie Aviles: One of the things we asked the support team of loom because we wanted to. Yeah. So that’s 1 of the issues with loom. I mean, I know that we could go to a video and then just click the transcript. But that would be like manual.
109 00:15:15.020 ⇒ 00:15:22.409 Miguel de Veyra: Yeah. But how many? Like, I think it’s fine. So I don’t think we do with loom videos, do we do loom videos for
110 00:15:22.650 ⇒ 00:15:26.430 Miguel de Veyra: every week or every day for this. I think it’s very specific, right.
111 00:15:27.610 ⇒ 00:15:40.880 Demilade Agboola: Yeah, so that’s part of so part of this documentation. And the exact part of why we want to do an Mvp is, we want to 1st start with, like what we have readily available. And if we see like, Hey.
112 00:15:41.348 ⇒ 00:15:45.959 Demilade Agboola: this allows us to be able to do with like this much with what we have.
113 00:15:46.497 ⇒ 00:16:12.370 Demilade Agboola: We can always now start to drive the adoption of like loom videos for maybe Prs, or like, even for the Prs that we’re building, we we can integrate like a pr summarizer and then ingest as well, so that now the logic behind every Pr is clear. So if someone changed it on a particular date. And and there was a particular reason for that change, or what that change was. We start to have more context on that, I think the idea of the Mvp is just like
114 00:16:12.510 ⇒ 00:16:19.769 Demilade Agboola: how how intelligence, based off, like the data that we already have that is commonly available. Can we get answers on what we.
115 00:16:19.990 ⇒ 00:16:31.070 Demilade Agboola: you know, on the projects? Actually, I was just if we use the Java project or the start Blitz projects. If I was randomly assigned to that project, how much information can I get
116 00:16:31.260 ⇒ 00:16:52.130 Demilade Agboola: on that project in like the next over in the next 24 h, by just asking the bot versus having to read through all the documentation and read through everything, and then over time, we will start building processes in place for things like looms and things like Pr summarizers and zoom summarizers, such that
117 00:16:52.130 ⇒ 00:17:01.499 Demilade Agboola: okay, all the context is way, more context available, and that we can then use that to get, you know, way more information than we would right now.
118 00:17:03.330 ⇒ 00:17:11.310 Amber Lin: What would be the most important source like we have a few but what would be the priority.
119 00:17:13.349 ⇒ 00:17:36.764 Demilade Agboola: I think right now, as things stand as what we have, I think the most important source right now would be the code base, like the repo mix of all the of all the existing code right now. And obviously we would have some documentation on like, you know, we all kind of have, like a little documentation on things here and there. But going forward. Obviously, we want to be able to have way more context on things.
120 00:17:37.589 ⇒ 00:17:40.049 Demilade Agboola: and that is when we’re looking at adding, like.
121 00:17:40.149 ⇒ 00:17:57.219 Demilade Agboola: you know, zoom summary so like. Oh, based off what the client said on this there was a Pr. Shortly after to make that effect, and that is why you know this happened. So. Yes, I think right now our our strongest source of information will be.
122 00:17:57.360 ⇒ 00:17:59.420 Miguel de Veyra: Yeah. Repo, okay.
123 00:17:59.720 ⇒ 00:18:00.350 Amber Lin: Awesome.
124 00:18:00.728 ⇒ 00:18:12.080 Miguel de Veyra: For I have a question regarding the repo, which specific? How cause I I’m not sure if we can use the entire, or maybe we can probably look into how
125 00:18:12.450 ⇒ 00:18:13.890 Miguel de Veyra: cursor does it.
126 00:18:14.090 ⇒ 00:18:22.009 Miguel de Veyra: But I think the question I have in mind is, is there like a specific file where we can, you know, like it could be like the base from where we get.
127 00:18:22.430 ⇒ 00:18:26.990 Uttam Kumaran: So I. So one thing that i, 1 thing that I’ve been doing is I’ve been using repo mix
128 00:18:27.110 ⇒ 00:18:35.020 Uttam Kumaran: to create basically one file that has the entire repo in it. Can you check? Can you scroll down on this repo
129 00:18:35.927 ⇒ 00:18:39.860 Uttam Kumaran: Kyle, and just see like if there’s that files in there.
130 00:18:40.570 ⇒ 00:18:46.160 Uttam Kumaran: I mean, if you just no, no, in that, in that repo itself. Can you just scroll to the bottom on the left.
131 00:18:49.190 ⇒ 00:18:52.989 Uttam Kumaran: Okay, maybe it’s not here. Can you go to like?
132 00:18:53.510 ⇒ 00:18:56.329 Uttam Kumaran: if you go back to Brainforge Repos.
133 00:18:59.350 ⇒ 00:19:02.679 Uttam Kumaran: or just whatever to all the repos in the company, basically.
134 00:19:05.080 ⇒ 00:19:05.730 Caio Velasco: Okay.
135 00:19:06.977 ⇒ 00:19:09.620 Uttam Kumaran: And then you could just go to
136 00:19:13.190 ⇒ 00:19:15.490 Uttam Kumaran: Can you just type in like, ABC,
137 00:19:19.110 ⇒ 00:19:22.830 Uttam Kumaran: there, anything? Yeah. And just type in, just click on the top one.
138 00:19:25.760 ⇒ 00:19:28.249 Uttam Kumaran: but scroll down, and there’s a repo mix output.
139 00:19:29.630 ⇒ 00:19:31.170 Miguel de Veyra: But I can talk some about.
140 00:19:31.170 ⇒ 00:19:32.390 Uttam Kumaran: The Xml, yeah.
141 00:19:34.300 ⇒ 00:19:39.310 Uttam Kumaran: so this is the entire repo in one file. So you should just be able to take this.
142 00:19:39.500 ⇒ 00:19:43.750 Miguel de Veyra: Yeah, yeah, okay, this is good. Can we have this for everyone.
143 00:19:44.240 ⇒ 00:19:45.350 Uttam Kumaran: Yeah, yeah.
144 00:19:45.670 ⇒ 00:19:46.296 Miguel de Veyra: Yeah, cause.
145 00:19:46.610 ⇒ 00:19:51.920 Uttam Kumaran: That’s a tick. That’s a ticket on my side. But yeah, so basically for everybody’s context, repo, mix
146 00:19:54.040 ⇒ 00:20:07.149 Uttam Kumaran: repo, mix basically is like a sort of an AI. It’s more of a workflow. It’s not not nothing really to do with AI, but basically it takes all the files and neatly formats it into like an AI native single file
147 00:20:08.389 ⇒ 00:20:13.360 Uttam Kumaran: which allows it to be easily consumable by AI, basically
148 00:20:13.560 ⇒ 00:20:15.350 Uttam Kumaran: so which it has, like the file pad.
149 00:20:15.350 ⇒ 00:20:16.140 Miguel de Veyra: This.
150 00:20:17.180 ⇒ 00:20:17.760 Uttam Kumaran: Yeah.
151 00:20:18.000 ⇒ 00:20:18.580 Miguel de Veyra: Okay, you just.
152 00:20:18.580 ⇒ 00:20:19.280 Uttam Kumaran: This.
153 00:20:20.120 ⇒ 00:20:20.449 Miguel de Veyra: Just for.
154 00:20:20.450 ⇒ 00:20:26.630 Uttam Kumaran: So, yeah, I mean, that’s what I was trying to make clear is that you guys, you don’t need to bring in the entire repo. You just need to bring in this file.
155 00:20:26.940 ⇒ 00:20:29.849 Miguel de Veyra: Okay, yeah. Cause I, that’s what I was worried about.
156 00:20:31.290 ⇒ 00:20:36.109 Uttam Kumaran: Yeah, you should just bring in this file. And like, you could probably just throw this into context, or you can
157 00:20:36.950 ⇒ 00:20:38.920 Uttam Kumaran: you just chunk this or whatever.
158 00:20:38.920 ⇒ 00:20:40.279 Miguel de Veyra: Yeah, yeah.
159 00:20:40.880 ⇒ 00:20:43.680 Caio Velasco: Does this file get updated when there’s a Pr.
160 00:20:44.160 ⇒ 00:20:45.000 Uttam Kumaran: Yes.
161 00:20:45.770 ⇒ 00:20:46.300 Caio Velasco: Okay.
162 00:20:46.890 ⇒ 00:20:47.530 Uttam Kumaran: Correct.
163 00:20:51.210 ⇒ 00:20:55.439 Caio Velasco: Okay, yes, okay. Maybe this would be the then the repo or this.
164 00:20:56.282 ⇒ 00:20:58.810 Miguel de Veyra: Sorry the main.
165 00:20:58.810 ⇒ 00:20:59.420 Caio Velasco: No, no.
166 00:20:59.420 ⇒ 00:21:06.930 Miguel de Veyra: The data that you guys need are the ones from loom, and this one right? And then that the agent should be pretty much done.
167 00:21:07.340 ⇒ 00:21:12.400 Miguel de Veyra: I mean, yeah, we have to like int integrate, slack and zoom. But I think this, too, should be the core.
168 00:21:13.300 ⇒ 00:21:15.310 Amber Lin: Is it notion or loom.
169 00:21:17.490 ⇒ 00:21:25.339 Miguel de Veyra: I think the loom, because they eventually I think they’ve already mentioned that they’re planning to do some looms every Pr. Or every now and then.
170 00:21:25.490 ⇒ 00:21:28.569 Miguel de Veyra: so maybe explaining what happened. So I think that should be.
171 00:21:28.570 ⇒ 00:21:28.970 Amber Lin: This.
172 00:21:28.970 ⇒ 00:21:30.400 Miguel de Veyra: Pretty, important, too.
173 00:21:31.639 ⇒ 00:21:39.109 Amber Lin: Where is the existing documentation? Is that in notion that would kind of just be our base of like general information, then.
174 00:21:40.460 ⇒ 00:21:46.300 Demilade Agboola: I mean. So, to be fair, we we’ve not necessarily have the best documentation, like
175 00:21:46.460 ⇒ 00:21:51.050 Demilade Agboola: habit, but I know on certain projects like Javi. Some documentation does exist.
176 00:21:51.520 ⇒ 00:21:56.279 Demilade Agboola: And I know that exists. I know Kyle has like a document in notion.
177 00:21:56.560 ⇒ 00:22:04.210 Demilade Agboola: and I think there’s a bit more information there in notion on the Javi projects. For instance.
178 00:22:06.220 ⇒ 00:22:27.530 Caio Velasco: Yeah, for the Japanese since I started, like in the not in the even in middle, in the in the, at the end of the project. I started documenting things like on the business side that I thought was important to guide my work. But then that was that’s something I just tip of the iceberg. So. But the idea would be, for example, here this was done by Ryan.
179 00:22:28.277 ⇒ 00:22:33.040 Caio Velasco: And there’s like a whole document about a lot of things regarding that this client.
180 00:22:33.270 ⇒ 00:22:37.629 Caio Velasco: but also, as you can mention at the end of the day, I think we would be looking
181 00:22:38.130 ⇒ 00:22:41.020 Caio Velasco: to have something just like an SA queue.
182 00:22:41.510 ⇒ 00:22:45.179 Caio Velasco: just, you know, question and answers about the most important things.
183 00:22:45.997 ⇒ 00:22:52.790 Caio Velasco: And then just to reduce scope. Let’s say that the most important thing would be things related to
184 00:22:53.698 ⇒ 00:22:57.950 Caio Velasco: to march to the March layer.
185 00:22:58.813 ⇒ 00:23:02.570 Caio Velasco: For example, this is Jeremy.
186 00:23:02.980 ⇒ 00:23:09.609 Caio Velasco: We have, like the the pipeline, either raw int march layers.
187 00:23:09.740 ⇒ 00:23:16.879 Caio Velasco: and then we would be looking at everything done in March, which is like the the last thing we do ready for to be consumed by
188 00:23:17.010 ⇒ 00:23:20.950 Caio Velasco: by like, downstream, by the client and by the analysts.
189 00:23:21.210 ⇒ 00:23:26.339 Caio Velasco: So maybe we would, we could start like trying to figure out our documents
190 00:23:26.690 ⇒ 00:23:30.250 Caio Velasco: for this part, having the most important things here.
191 00:23:30.715 ⇒ 00:23:34.975 Caio Velasco: I I don’t know if we would. If we do have something
192 00:23:35.520 ⇒ 00:23:40.669 Caio Velasco: for Job, to be honest, as you said, there’s not like much documentation
193 00:23:40.910 ⇒ 00:23:45.909 Caio Velasco: on this side. So maybe yeah, the repo, the looms, the existing looms.
194 00:23:47.440 ⇒ 00:23:51.000 Caio Velasco: But that’s that’s how fine I know about Javi.
195 00:23:51.950 ⇒ 00:23:55.690 Amber Lin: Awesome. Is there a client you guys would like to get started on
196 00:23:55.830 ⇒ 00:23:58.339 Amber Lin: what would be the best client to do this for.
197 00:24:01.240 ⇒ 00:24:02.390 Caio Velasco: Well, I think maybe Javier.
198 00:24:02.390 ⇒ 00:24:04.370 Miguel de Veyra: Yeah, yeah, let’s do. Yeah.
199 00:24:05.250 ⇒ 00:24:05.860 Amber Lin: Okay.
200 00:24:06.100 ⇒ 00:24:31.740 Amber Lin: awesome cause on our side. Also, we’re developing an agent. That has context to slack through all these different sources. And I can answer some basic questions. And then I think for Github, it will be awesome addition to just answering more code specific questions. So we’ll get started on, do you guys have a project in linear for this Mvp, or should we create one.
201 00:24:33.600 ⇒ 00:24:33.900 Demilade Agboola: Okay.
202 00:24:34.640 ⇒ 00:24:36.860 Demilade Agboola: Not sure. If.
203 00:24:37.730 ⇒ 00:24:41.309 Uttam Kumaran: There is a pro. There is a project in linear already.
204 00:24:41.700 ⇒ 00:24:45.050 Amber Lin: Yeah, what is it called? I’m looking at data platform.
205 00:24:47.940 ⇒ 00:24:54.109 Uttam Kumaran: Well, this, this, all this work is around data. on the documentation v, 1.
206 00:24:57.460 ⇒ 00:25:03.919 Uttam Kumaran: So basically, th, this team is is working on like creating the the 1st format. So if you go to issues.
207 00:25:04.130 ⇒ 00:25:04.730 Amber Lin: Hmm.
208 00:25:05.014 ⇒ 00:25:07.570 Uttam Kumaran: If you go to issues for just that project.
209 00:25:07.570 ⇒ 00:25:11.680 Amber Lin: Yeah, I’m looking at it now. There’s 4 items.
210 00:25:11.860 ⇒ 00:25:16.890 Uttam Kumaran: Yeah, yeah, yeah, so this team is basically deciding on
211 00:25:17.240 ⇒ 00:25:20.530 Uttam Kumaran: like confirming basically the core document. And then.
212 00:25:21.310 ⇒ 00:25:22.060 Amber Lin: I see. Okay.
213 00:25:22.060 ⇒ 00:25:32.130 Uttam Kumaran: I kind of want this all. If if we if we can all kind of be coordinated a little bit, it’s helpful, because you guys ultimately be consuming that document. In addition, as one of the sources among many.
214 00:25:32.130 ⇒ 00:25:32.670 Miguel de Veyra: Yeah.
215 00:25:33.710 ⇒ 00:25:34.460 Uttam Kumaran: You know.
216 00:25:34.460 ⇒ 00:25:35.090 Amber Lin: It.
217 00:25:36.960 ⇒ 00:25:50.469 Amber Lin: for do you want me to create a different project for? Mv, this Mvp, specifically, I feel like this is less on documentation, but actually a development on the AI.
218 00:25:50.470 ⇒ 00:25:53.869 Miguel de Veyra: Part of the the one we have already.
219 00:25:54.820 ⇒ 00:26:02.039 Amber Lin: Yeah, kind of it’s it’s kind of like overlapping. So I’m just thinking of where we can keep track of these things.
220 00:26:04.620 ⇒ 00:26:06.959 Miguel de Veyra: I think we just added on the Yavi project under the 8.
221 00:26:06.960 ⇒ 00:26:07.840 Uttam Kumaran: Well, like.
222 00:26:08.200 ⇒ 00:26:12.240 Uttam Kumaran: So I mean, the notion piece is really like.
223 00:26:12.390 ⇒ 00:26:19.670 Uttam Kumaran: there’s 2 things right. This is, gonna be con. This is the notion document is part of the notion, pipeline, that you guys are going to consume.
224 00:26:20.320 ⇒ 00:26:30.579 Uttam Kumaran: But then there’s also like answering, just like getting in a golden data sheet for the evals like having this team test. So there is 2 teams here.
225 00:26:33.310 ⇒ 00:26:38.960 Uttam Kumaran: you know. One thing you can do is like you in linear. You can create an initiative that combines projects. But yeah, I guess I’m like.
226 00:26:40.600 ⇒ 00:26:43.289 Uttam Kumaran: but I guess, like, I don’t know what the bent like. What
227 00:26:43.460 ⇒ 00:26:45.179 Uttam Kumaran: what do you think is like
228 00:26:46.160 ⇒ 00:26:48.709 Uttam Kumaran: tough with managing it right now, as is.
229 00:26:50.278 ⇒ 00:26:57.740 Amber Lin: Just so that if we do a if I want to look at how far we progressing in this project, I need to jump around.
230 00:26:57.940 ⇒ 00:27:02.570 Amber Lin: because not all of the tasks are are in one place. That that will be all.
231 00:27:04.890 ⇒ 00:27:05.420 Uttam Kumaran: See
232 00:27:05.950 ⇒ 00:27:14.749 Amber Lin: Yeah, I think I can. Just if you don’t mind, I can just add you to the AI team, because when it comes to, we want to gather.
233 00:27:15.476 ⇒ 00:27:43.360 Amber Lin: This comes to the part I wanted to talking about a golden data sheet. So essentially for that, we want to know what type of answers you want to get answered, and also what is the ideal? Answer, so that will help us evaluate our performances and sort of guide the bot to the, to the ideal state, and that is something that we want. We will need your guys help on. So
234 00:27:43.460 ⇒ 00:27:54.380 Amber Lin: my thought is that I’ll create a project or ticket for that in the AI team, or I could just put it here, and we’ll work towards that.
235 00:27:57.790 ⇒ 00:27:58.290 Caio Velasco: For me.
236 00:27:58.290 ⇒ 00:27:58.949 Uttam Kumaran: Maybe create.
237 00:27:58.950 ⇒ 00:27:59.540 Caio Velasco: Either.
238 00:27:59.540 ⇒ 00:28:00.020 Uttam Kumaran: Yeah. Go ahead.
239 00:28:00.020 ⇒ 00:28:02.679 Caio Velasco: Whatever, and whatever is good for you. Right?
240 00:28:02.990 ⇒ 00:28:03.939 Caio Velasco: I don’t mind.
241 00:28:04.990 ⇒ 00:28:10.220 Uttam Kumaran: Yeah, I think maybe creating it in the AI team, because I sort of consider Kyle and demalade as like
242 00:28:10.500 ⇒ 00:28:11.930 Uttam Kumaran: the clients.
243 00:28:12.230 ⇒ 00:28:17.259 Uttam Kumaran: And so basically, you consider them like the product owners. So I think
244 00:28:17.610 ⇒ 00:28:22.080 Uttam Kumaran: I think they’re gonna continue to work on things here that are outside of the AI team scope.
245 00:28:22.230 ⇒ 00:28:26.936 Uttam Kumaran: Right? Like we’re working on documentation and things that are purely on the data side.
246 00:28:27.380 ⇒ 00:28:36.079 Uttam Kumaran: There is going to be some pieces where they want to enable the best consumption of this through the AI agent, and then, of course, being able to edit it
247 00:28:36.240 ⇒ 00:28:47.449 Uttam Kumaran: through another AI agent. So any tickets? Similarly, how you would assign a ticket to like Janice or something on the ABC. Consider assigning it to them as well. I think that’s fair.
248 00:28:47.991 ⇒ 00:28:53.020 Uttam Kumaran: Because there’s gonna be work on the data platform side. That is like quite a bit beyond
249 00:28:53.460 ⇒ 00:28:55.430 Uttam Kumaran: just building the agents.
250 00:28:55.810 ⇒ 00:29:02.060 Uttam Kumaran: But if there is a specific task as part of building the Java agent that like they need to take on. I think that’s fine.
251 00:29:03.210 ⇒ 00:29:04.000 Uttam Kumaran: Yeah.
252 00:29:04.000 ⇒ 00:29:11.139 Amber Lin: Yeah, awesome. Sounds good. I’ll just make a project in our AI team. Don’t know if you have to jump. I saw that you have.
253 00:29:11.140 ⇒ 00:29:11.860 Uttam Kumaran: Do.
254 00:29:12.150 ⇒ 00:29:13.120 Uttam Kumaran: Yes.
255 00:29:13.460 ⇒ 00:29:14.779 Amber Lin: Yeah, okay.
256 00:29:14.780 ⇒ 00:29:15.580 Uttam Kumaran: Thanks guys.
257 00:29:16.070 ⇒ 00:29:16.740 Amber Lin: Bye.
258 00:29:17.060 ⇒ 00:29:17.620 Uttam Kumaran: Bye.
259 00:29:19.100 ⇒ 00:29:20.240 Amber Lin: And
260 00:29:22.150 ⇒ 00:29:37.959 Amber Lin: So I guess we want to figure out. What features or what do you want this spot to be able to do? I know Uta mentioned updating it as well. Can you give us a list of specific requirements? You want this to look like.
261 00:29:42.660 ⇒ 00:29:46.039 Demilade Agboola: Like right now? Or should we just create a list and send to you.
262 00:29:47.882 ⇒ 00:30:01.230 Amber Lin: On the top of your head, or a list would be helpful, because if you tell us what features you want, Miguel and Casey would be kind of. We’ll kind of be able to tell you how things might work, or how long or how difficult things might be.
263 00:30:02.842 ⇒ 00:30:08.397 Demilade Agboola: I think it would just be basically asking questions about the latest
264 00:30:09.760 ⇒ 00:30:15.420 Demilade Agboola: changes or basic not necessarily test changes, but like changes or like what
265 00:30:15.810 ⇒ 00:30:22.819 Demilade Agboola: business logic is available in the data or what the business logic is in the data. So things around
266 00:30:23.740 ⇒ 00:30:47.459 Demilade Agboola: like I said, an example will be cogs, because I know I know just from like watching the Javi slack. I know that there were times when Cog was an issue, just being able to be like. Oh, what is the current definition of cogs, for instance, would be a great question. All the all the fact things that factor into calculating cogs, for instance, or
267 00:30:53.100 ⇒ 00:30:56.589 Caio Velasco: Cost, just just in case someone doesn’t know like when you come.
268 00:30:56.590 ⇒ 00:30:57.250 Demilade Agboola: Oh, yeah.
269 00:30:57.250 ⇒ 00:31:02.909 Caio Velasco: Yeah, pro profits like revenue mind costs within costs. There are like a lot of things.
270 00:31:03.090 ⇒ 00:31:10.193 Caio Velasco: Those things can be called many things. And for for Amazon it’s called Cost of goods. Sold something.
271 00:31:12.510 ⇒ 00:31:16.391 Demilade Agboola: You know. So just just that sort of thing.
272 00:31:17.790 ⇒ 00:31:27.869 Demilade Agboola: we could come up with a list of like questions, especially like in the Javi context. I think Kyle will probably be better the better person to that, because he worked more closely with Javi than I did.
273 00:31:28.430 ⇒ 00:31:29.929 Demilade Agboola: But the basic idea is.
274 00:31:29.930 ⇒ 00:31:30.580 Amber Lin: Let’s see.
275 00:31:32.060 ⇒ 00:31:33.299 Demilade Agboola: I didn’t hear what you said. Sorry.
276 00:31:34.195 ⇒ 00:31:40.529 Amber Lin: I’ll make a spreadsheet so we can put in the questions, and then we can put in the ideal answers in another column.
277 00:31:41.330 ⇒ 00:31:47.440 Demilade Agboola: Gotcha. Yeah. So we could just do that. And then we can send that over. Have like a list of questions. That will be.
278 00:31:47.580 ⇒ 00:31:50.440 Demilade Agboola: But why did you would like the bot to be able to answer.
279 00:31:51.980 ⇒ 00:32:07.319 Caio Velasco: Yeah. And one thing also, at least on my side. I’m not sure about them, maybe has much more experience than I have in this, but I’m not very familiar with like AI agents, bots, etc. Just like logic in my mind that I believe it does.
280 00:32:08.033 ⇒ 00:32:30.490 Caio Velasco: But so then, I think, would be also important to have a meeting with either Miguel or or Katie, or both, just to understand, like, what is the work you guys do when you start creating this so that they can understand like, Oh, okay, when they ask for like question, that’s what that’s exactly what they mean? Or is it something else? So that I can also like participate in the pain?
281 00:32:31.176 ⇒ 00:32:34.010 Caio Velasco: So, yeah, this could be something that we could do as well.
282 00:32:34.510 ⇒ 00:32:52.459 Miguel de Veyra: Okay, yeah, I think that should also be very help, because from cause. Right now, to be honest, we’re prioritizing slack and zoom. But from the looks of it. What should have been our priority was, you know, I think we should have asked you guys 1st to be honest, because from the looks of it. The priority is
283 00:32:53.228 ⇒ 00:33:02.430 Miguel de Veyra: github, 1st of all, and then the documentation, because honestly, the only documentation we have access to for Yavi is the one in notion, and it’s very lackluster.
284 00:33:03.070 ⇒ 00:33:06.359 Casie Aviles: I think it’s the client page that that’s just it.
285 00:33:06.710 ⇒ 00:33:13.350 Miguel de Veyra: Yeah, the the client page, I mean, there’s some documentation there. I checked it. But I don’t even have access to like the Google docs and stuff.
286 00:33:14.890 ⇒ 00:33:16.490 Miguel de Veyra: So you know.
287 00:33:17.100 ⇒ 00:33:17.889 Amber Lin: Of course.
288 00:33:17.890 ⇒ 00:33:46.689 Amber Lin: since last week we’re gonna be doing github and linear. So that’s perfect. We’re just wrapping up slack and zoom this week, and I think earlier next week we should have a meeting where we kind of walk you through, how things are created and why we do certain things, and on the side we’ll also be progressing on the Github. So this is really helpful for and we’ll just prioritize Github next week.
289 00:33:47.416 ⇒ 00:33:54.549 Amber Lin: Should we make this a regular meeting, or just have, like a small stand up here and there?
290 00:33:54.880 ⇒ 00:33:57.350 Amber Lin: Or how do you guys want to do this?
291 00:33:57.660 ⇒ 00:34:00.370 Miguel de Veyra: I think a small stand up here and there should be okay.
292 00:34:00.370 ⇒ 00:34:02.439 Caio Velasco: Yeah, yeah, I agree.
293 00:34:02.950 ⇒ 00:34:11.660 Amber Lin: Yeah. Okay. So earlier next week, I’ll schedule a meeting for us to just understand AI, and then we’ll maybe do like
294 00:34:12.290 ⇒ 00:34:14.960 Amber Lin: meetings and.
295 00:34:14.969 ⇒ 00:34:21.219 Miguel de Veyra: This cause. I think Amber does. The Github integration should be a lot easier now.
296 00:34:21.600 ⇒ 00:34:21.960 Amber Lin: Oh!
297 00:34:21.960 ⇒ 00:34:25.420 Miguel de Veyra: Honestly, I don’t think that should be a problem given that, you know.
298 00:34:27.920 ⇒ 00:34:31.599 Miguel de Veyra: What do you call this? We hope we have that. What? What was that thing that you
299 00:34:31.600 ⇒ 00:34:32.440 Miguel de Veyra: to mix.
300 00:34:32.440 ⇒ 00:34:33.130 Demilade Agboola: Reporting.
301 00:34:33.139 ⇒ 00:34:36.599 Miguel de Veyra: Mix. Yeah, cause I think that solves all the problems to be honest.
302 00:34:37.210 ⇒ 00:34:38.130 Amber Lin: Oh, awesome!
303 00:34:38.130 ⇒ 00:34:46.279 Miguel de Veyra: Yeah, we can. Probably if if we have that, for every client, once with them is done, we could probably yeah, Github is probably gonna be the easiest part of all.
304 00:34:46.540 ⇒ 00:34:52.910 Amber Lin: Okay, I, what we can do is I can just invite you guys to our
305 00:34:53.179 ⇒ 00:35:04.300 Amber Lin: AI stand up or we can just talk about some updates beforehand related to this project. And then you guys can just hop off and we’ll continue talking about our other AI stuff
306 00:35:04.510 ⇒ 00:35:05.750 Amber Lin: like that could work.
307 00:35:06.180 ⇒ 00:35:10.849 Miguel de Veyra: And then could you add me and Casey to that document? Kyle.
308 00:35:12.140 ⇒ 00:35:12.930 Caio Velasco: Yes.
309 00:35:17.780 ⇒ 00:35:20.770 Caio Velasco: Is it this data platform documentation.
310 00:35:25.450 ⇒ 00:35:26.559 Caio Velasco: this one right?
311 00:35:26.900 ⇒ 00:35:30.760 Amber Lin: Yeah, I think everyone in Brainforce should have access.
312 00:35:32.990 ⇒ 00:35:36.810 Amber Lin: Do we have a slack chat that talks about this.
313 00:35:39.201 ⇒ 00:35:41.729 Caio Velasco: We do have data platform, slack channels.
314 00:35:42.106 ⇒ 00:35:43.610 Demilade Agboola: Just give them access.
315 00:35:44.110 ⇒ 00:35:45.090 Miguel de Veyra: Oh, okay. Okay.
316 00:35:45.890 ⇒ 00:35:48.710 Demilade Agboola: I mean you. You’re already everyone with brain for.
317 00:35:48.710 ⇒ 00:35:50.970 Caio Velasco: Yeah, the link is in the chat.
318 00:35:52.000 ⇒ 00:35:53.209 Miguel de Veyra: Send you the link.
319 00:35:58.250 ⇒ 00:36:07.990 Amber Lin: You guys want a separate channel to just send updates specific to this Mvp, or, do you guys just want to like hover around in our AI team.
320 00:36:09.210 ⇒ 00:36:09.950 Amber Lin: Maybe it’s.
321 00:36:09.950 ⇒ 00:36:12.810 Miguel de Veyra: I think we should create like a separate channel called the
322 00:36:13.250 ⇒ 00:36:15.310 Miguel de Veyra: Data AI coordination, or something like that.
323 00:36:15.310 ⇒ 00:36:21.729 Amber Lin: Yeah, we have one. I’ll just rename it. We have one from a long time ago. Okay, I’ll do that
324 00:36:22.180 ⇒ 00:36:24.470 Amber Lin: data.
325 00:36:25.500 ⇒ 00:36:27.970 Amber Lin: A I channel.
326 00:36:28.883 ⇒ 00:36:36.679 Amber Lin: I guess the last thing we wanted is we have a slack agent that has access to
327 00:36:37.270 ⇒ 00:36:48.030 Amber Lin: slack and zoom, and we wanted to get some. It’s kind of related to the golden data set. But questions beyond just
328 00:36:49.166 ⇒ 00:36:50.499 Amber Lin: the code.
329 00:36:51.320 ⇒ 00:37:07.660 Amber Lin: It’s kind of like the task summarizer Demo, that we talked about a while back. Of what capabilities do you want that agent to have? And what type of questions you want it to answer? Not just about like data questions.
330 00:37:11.974 ⇒ 00:37:15.520 Demilade Agboola: That sounds pretty cool. How far along is that?
331 00:37:17.540 ⇒ 00:37:18.100 Amber Lin: Hmm.
332 00:37:18.960 ⇒ 00:37:23.930 Demilade Agboola: I said, that sounds like, how far along is that? Have you been able to work on that.
333 00:37:26.025 ⇒ 00:37:28.280 Amber Lin: Yeah. The task summarizer, you mean.
334 00:37:28.530 ⇒ 00:37:30.109 Demilade Agboola: Yes, let’s ask me, Riza.
335 00:37:30.520 ⇒ 00:37:33.150 Amber Lin: Yeah, Miguel Casey, I’ll leave that to you.
336 00:37:33.650 ⇒ 00:37:40.579 Casie Aviles: Oh, yeah, for the task summarizer, we did manage to create like an initial version, although right now it’s not
337 00:37:41.030 ⇒ 00:37:43.980 Casie Aviles: activated for Javi, because of.
338 00:37:45.710 ⇒ 00:37:49.130 Casie Aviles: Yeah, there are some improvements that we had to make.
339 00:37:52.000 ⇒ 00:37:56.259 Demilade Agboola: Okay, that sounds cool. Yeah, I I think like
340 00:37:56.770 ⇒ 00:38:03.749 Demilade Agboola: that would also be really helpful. But I’d like, I think, in the context of what in the everyday life.
341 00:38:04.838 ⇒ 00:38:10.419 Demilade Agboola: being able to ask questions, especially from like the analyst or the A’s directly to the
342 00:38:11.340 ⇒ 00:38:13.380 Demilade Agboola: but about the
343 00:38:14.200 ⇒ 00:38:22.050 Demilade Agboola: current state of the code base will be always will always be very helpful just to know what the business logic is and
344 00:38:22.430 ⇒ 00:38:26.890 Demilade Agboola: potentially what the what’s going on, I I think.
345 00:38:27.020 ⇒ 00:38:29.519 Demilade Agboola: would add more context, like, why.
346 00:38:29.650 ⇒ 00:38:32.970 Demilade Agboola: but at least just knowing what is existing sometimes can be very helpful.
347 00:38:34.430 ⇒ 00:38:40.110 Miguel de Veyra: And also I think it would be very helpful if you can. If you guys can come up with like, I don’t know.
348 00:38:40.450 ⇒ 00:38:50.219 Miguel de Veyra: 10 would be a good number, but ideally more questions that would be asked for the bot daily. So we can, you know, tailor, those questions a bit to those questions a bit more.
349 00:38:52.930 ⇒ 00:38:57.319 Caio Velasco: Yeah, we can definitely provide. Like, I can go through slack and see
350 00:38:57.830 ⇒ 00:39:05.799 Caio Velasco: like what Robert was asking, what the client was asking or what we were asking, yeah, and just make like a compiled list.
351 00:39:06.780 ⇒ 00:39:09.210 Miguel de Veyra: We have that. Then? Yeah, we can.
352 00:39:09.390 ⇒ 00:39:18.160 Miguel de Veyra: because we cause, of course, we wanna you know, of course, we want the bot to know a lot of things. But we wanna be like better on the specific things that
353 00:39:18.370 ⇒ 00:39:22.059 Miguel de Veyra: the what actually has to be asked on a daily basis. Right?
354 00:39:22.900 ⇒ 00:39:23.430 Caio Velasco: Yep.
355 00:39:26.710 ⇒ 00:39:32.600 Caio Velasco: And for things like this number is it? Is it gonna be like a ticket in linear so that we don’t forget.
356 00:39:33.036 ⇒ 00:39:52.249 Amber Lin: Totally I would. I’ll I think that’s very helpful. I’m gonna create a project and the main thing that I would. We would need your help on is to create that sheet with questions and ideal answers. So I’ll ticket that out and
357 00:39:52.912 ⇒ 00:39:59.480 Amber Lin: I’ll give you guys all the resources we need, and I’ll like I’ll check in with you. So we don’t forget.
358 00:40:00.460 ⇒ 00:40:03.330 Caio Velasco: Perfect that one in the meeting next week, right.
359 00:40:04.337 ⇒ 00:40:11.640 Amber Lin: Yes, I’ll make. I’ll create. I’ll create a meeting next week. I’ll look at your calendars to see when’s available.
360 00:40:12.360 ⇒ 00:40:13.020 Caio Velasco: Perfect.
361 00:40:14.060 ⇒ 00:40:19.510 Amber Lin: Okay, any other questions or anything. We remembered.
362 00:40:20.560 ⇒ 00:40:22.299 Miguel de Veyra: Anything you want to ask. Ryan.
363 00:40:24.370 ⇒ 00:40:27.339 Caio Velasco: No, on my end. I think I think it’s all good.
364 00:40:28.020 ⇒ 00:40:30.499 Miguel de Veyra: No, I mean like Ryan Luke, you’re here.
365 00:40:31.310 ⇒ 00:40:32.120 Caio Velasco: Hello!
366 00:40:32.473 ⇒ 00:40:33.180 Miguel de Veyra: Go ahead.
367 00:40:33.180 ⇒ 00:40:33.560 Miguel de Veyra: Here.
368 00:40:33.560 ⇒ 00:40:35.080 Miguel de Veyra: I think, yeah, yeah.
369 00:40:35.080 ⇒ 00:40:39.039 Caio Velasco: Oh, we’re just starting, man. I’m just kidding.
370 00:40:39.425 ⇒ 00:40:45.200 Luke Daque: Sorry about that. But yeah, I was just listening through. It was like I I.
371 00:40:45.640 ⇒ 00:40:48.339 Amber Lin: Joined like midway, I guess.
372 00:40:48.630 ⇒ 00:40:57.910 Luke Daque: But yeah, I think this is, this is good, like, at least we are. We finally get to start. We’ve been talking about this for
373 00:40:58.620 ⇒ 00:41:05.269 Luke Daque: like several months already, like having a data and AI sync session. So, but yeah, it’s fine.
374 00:41:05.270 ⇒ 00:41:11.149 Miguel de Veyra: This. Yeah, this session is pretty like eye opening. Because, looking back now, we’ve been
375 00:41:11.520 ⇒ 00:41:20.399 Miguel de Veyra: honestly, I think we’ve been focusing on the wrong stuff. And if we just talk to you guys first, st then, you know, I think we could have gotten like a
376 00:41:20.730 ⇒ 00:41:22.959 Miguel de Veyra: initial version pretty quickly.
377 00:41:24.270 ⇒ 00:41:26.389 Miguel de Veyra: And that’s really tailored to what you guys need.
378 00:41:26.590 ⇒ 00:41:31.020 Amber Lin: I mean, that means next week we can do it really quickly. So it’s good news.
379 00:41:31.530 ⇒ 00:41:31.943 Caio Velasco: What’s the.
380 00:41:32.150 ⇒ 00:41:32.680 Luke Daque: Nice.
381 00:41:32.680 ⇒ 00:41:39.005 Caio Velasco: Yeah, but don’t worry. We we also didn’t know where to look at. So now now we also do so we are all in the same page.
382 00:41:39.240 ⇒ 00:41:40.229 Amber Lin: Yes, yes.
383 00:41:40.230 ⇒ 00:41:40.760 Luke Daque: Yeah.
384 00:41:40.950 ⇒ 00:41:41.690 Amber Lin: Excited.
385 00:41:41.950 ⇒ 00:41:43.499 Amber Lin: This is really great.
386 00:41:44.950 ⇒ 00:41:45.990 Amber Lin: Okay.
387 00:41:46.130 ⇒ 00:41:47.400 Amber Lin: Next week.
388 00:41:48.270 ⇒ 00:41:53.129 Amber Lin: Does everyone in this meeting want to be on the meeting next week?
389 00:41:56.220 ⇒ 00:41:59.069 Amber Lin: Okay, I see sound good.
390 00:41:59.690 ⇒ 00:42:04.630 Amber Lin: I will book that I’ll talk. We’ll talk in the Channel. I’ll add. You guys.
391 00:42:07.240 ⇒ 00:42:07.790 Miguel de Veyra: Everyone.
392 00:42:08.230 ⇒ 00:42:09.699 Amber Lin: Sounds good, thank you.
393 00:42:10.750 ⇒ 00:42:11.670 Amber Lin: Bye.
394 00:42:12.430 ⇒ 00:42:13.520 Luke Daque: Thanks. Bye-bye.