Meeting Title: Daily AI Team Sync Date: 2025-01-16 Meeting participants: Miguel De Veyra, Casie Aviles, Uttam Kumaran
WEBVTT
1 00:00:10.290 ⇒ 00:00:11.630 Miguel de Veyra: Hello! Hello!
2 00:00:11.630 ⇒ 00:00:13.510 Uttam Kumaran: To yo.
3 00:00:16.329 ⇒ 00:00:17.989 Miguel de Veyra: Oh, wait! There you go!
4 00:00:18.209 ⇒ 00:00:21.109 Miguel de Veyra: Alright. I think I should probably send this to Casey.
5 00:00:21.260 ⇒ 00:00:22.550 Uttam Kumaran: I just did.
6 00:00:22.550 ⇒ 00:00:23.560 Miguel de Veyra: Okay, okay.
7 00:00:28.510 ⇒ 00:00:30.739 Miguel de Veyra: how would how did the ABC thing go?
8 00:00:31.310 ⇒ 00:00:32.490 Uttam Kumaran: Hello! Thereo!
9 00:00:34.130 ⇒ 00:00:34.680 Uttam Kumaran: That’s good!
10 00:00:34.680 ⇒ 00:00:35.390 Uttam Kumaran: Celebrated.
11 00:00:35.390 ⇒ 00:00:36.160 Miguel de Veyra: I’ll do.
12 00:00:36.420 ⇒ 00:00:39.180 Uttam Kumaran: Everyone loves your Demos. Bro. I’ll
13 00:00:40.490 ⇒ 00:00:42.989 Uttam Kumaran: I’ll I’ll send you the Transcript.
14 00:00:43.770 ⇒ 00:00:44.350 Miguel de Veyra: Nice.
15 00:00:44.350 ⇒ 00:00:47.690 Uttam Kumaran: Or I’ll run, or this is why we should run the transcript of the summary. But
16 00:00:48.090 ⇒ 00:00:51.369 Uttam Kumaran: I don’t. We was on Google meet. So I have the transcript locally.
17 00:00:51.580 ⇒ 00:00:54.180 Uttam Kumaran: It was good. So we’re gonna put together
18 00:00:54.380 ⇒ 00:00:57.699 Uttam Kumaran: a proposal for them. They love that demo.
19 00:00:58.680 ⇒ 00:00:59.410 Miguel de Veyra: Nice.
20 00:01:00.660 ⇒ 00:01:07.330 Uttam Kumaran: I think they’re interested in that. But they’re also interested in some scheduling sort of optimization help.
21 00:01:08.290 ⇒ 00:01:08.700 Miguel de Veyra: Okay. Okay.
22 00:01:08.700 ⇒ 00:01:11.349 Uttam Kumaran: So that may be more like M. 8 N.
23 00:01:13.100 ⇒ 00:01:16.609 Uttam Kumaran: Zapier type, like automations.
24 00:01:17.370 ⇒ 00:01:18.869 Miguel de Veyra: Yeah, we’ll have to see their stock.
25 00:01:19.140 ⇒ 00:01:19.830 Uttam Kumaran: Yeah.
26 00:01:22.520 ⇒ 00:01:25.650 Miguel de Veyra: Probably using calendly or a Crm right?
27 00:01:25.650 ⇒ 00:01:34.479 Uttam Kumaran: They’re using like a. So basically, they’re a marketplace for telehealth. So they have patients. And they have the providers. They basically just do all the scheduling.
28 00:01:36.250 ⇒ 00:01:39.249 Miguel de Veyra: Oh, okay, I think I’ve worked with someone like this before.
29 00:01:39.250 ⇒ 00:01:40.280 Uttam Kumaran: Yeah.
30 00:01:41.250 ⇒ 00:01:43.180 Miguel de Veyra: Do they want voice or chat?
31 00:01:45.200 ⇒ 00:01:51.830 Uttam Kumaran: I I think they mainly just wanted like text, like help texting some of their people.
32 00:01:53.360 ⇒ 00:01:54.779 Uttam Kumaran: Text and email.
33 00:01:56.530 ⇒ 00:02:01.859 Miguel de Veyra: So based. Simple outreach. Yeah, I think me and Casey have experience there, both of us.
34 00:02:09.930 ⇒ 00:02:15.720 Uttam Kumaran: Okay, cool. So we we talk about stuff, how’s everything going.
35 00:02:19.497 ⇒ 00:02:28.009 Miguel de Veyra: From my side. Demos are going good. I’ve checked the notion. Ticket creation agent. Basically.
36 00:02:28.840 ⇒ 00:02:32.880 Uttam Kumaran: I was brainstorming it just before this call with Casey a bit.
37 00:02:33.640 ⇒ 00:02:40.869 Miguel de Veyra: And yeah, we’ll we’ll work on that, though we like. Do we prioritize that over the one for Craig.
38 00:02:44.130 ⇒ 00:02:48.029 Uttam Kumaran: I mean, they’re both probably like I think we could probably handle.
39 00:02:49.480 ⇒ 00:02:50.740 Miguel de Veyra: Yeah, we can handle both.
40 00:02:50.740 ⇒ 00:02:58.019 Uttam Kumaran: There’s yeah, there’s only 3. There’s only 3. Those are the only 3 priorities, right? So the the sales agent, the thing for Craig and the notion. So.
41 00:02:58.300 ⇒ 00:03:01.939 Uttam Kumaran: however, we want to split it up is fine.
42 00:03:07.890 ⇒ 00:03:10.080 Miguel de Veyra: Okay, yeah. And then
43 00:03:10.210 ⇒ 00:03:14.130 Miguel de Veyra: I think for the Demos, there’s really nothing much we want to do now, anyways.
44 00:03:14.660 ⇒ 00:03:19.009 Uttam Kumaran: Yeah, I think we’re just gonna wait. My only question was they, maybe this is a question
45 00:03:19.110 ⇒ 00:03:22.339 Uttam Kumaran: I don’t know. I was gonna ask you, I wanna see. Can we like?
46 00:03:22.560 ⇒ 00:03:26.720 Uttam Kumaran: Is there any way we can? Lego
47 00:03:27.040 ⇒ 00:03:30.899 Uttam Kumaran: do an iframe for each of the different Demos or no.
48 00:03:32.210 ⇒ 00:03:34.080 Miguel de Veyra: I frame it? Where? In here.
49 00:03:34.460 ⇒ 00:03:36.219 Uttam Kumaran: No, no! In the demo site.
50 00:03:39.570 ⇒ 00:03:42.250 Miguel de Veyra: What are we gonna iframe? Sorry. Yeah, we can. Iframe definitely.
51 00:03:42.860 ⇒ 00:03:43.470 Uttam Kumaran: Okay.
52 00:03:49.150 ⇒ 00:03:51.020 Uttam Kumaran: So I’m gonna move this to done.
53 00:04:10.690 ⇒ 00:04:12.820 Uttam Kumaran: And then do we want to split this up.
54 00:04:16.680 ⇒ 00:04:18.190 Uttam Kumaran: Miguel, like.
55 00:04:18.190 ⇒ 00:04:24.970 Miguel de Veyra: No, no, yeah, this this, yeah. I was working on this basically different. Dbs.
56 00:04:25.727 ⇒ 00:04:29.589 Miguel de Veyra: I just benched it because I worked on Televira the past few days.
57 00:04:29.590 ⇒ 00:04:35.189 Uttam Kumaran: Well, then, okay, so let let’s let’s list them all out. And then I can just create those tickets
58 00:04:35.290 ⇒ 00:04:36.879 Uttam Kumaran: like a separate tickets.
59 00:04:36.880 ⇒ 00:04:39.170 Miguel de Veyra: Oh, yeah, okay, yeah, I’ll send it to you.
60 00:04:39.470 ⇒ 00:04:46.550 Miguel de Veyra: Oh, wait, wait. Case studies target industries. I think it’s this one.
61 00:04:47.780 ⇒ 00:04:54.849 Miguel de Veyra: At least, this is. This was what’s in my notes, target industries. And then, Demos, I think that’s it.
62 00:04:57.510 ⇒ 00:04:59.860 Miguel de Veyra: What’s that? AI data database.
63 00:05:00.290 ⇒ 00:05:01.879 Uttam Kumaran: No, this is all the tasks.
64 00:05:04.630 ⇒ 00:05:07.460 Uttam Kumaran: This is all the AI and data team tasks.
65 00:05:08.680 ⇒ 00:05:10.230 Miguel de Veyra: Do we want the bot to have that.
66 00:05:11.400 ⇒ 00:05:15.200 Uttam Kumaran: Yeah, cause that’s what you’re gonna need for the notion agent.
67 00:05:17.140 ⇒ 00:05:18.030 Miguel de Veyra: Eventually.
68 00:05:18.030 ⇒ 00:05:20.350 Uttam Kumaran: For example, if you wanna go update a task.
69 00:05:20.800 ⇒ 00:05:21.420 Miguel de Veyra: Yeah.
70 00:05:21.420 ⇒ 00:05:23.110 Uttam Kumaran: It’s gonna need that knowledge.
71 00:05:24.040 ⇒ 00:05:26.100 Miguel de Veyra: Do we do? We only want
72 00:05:26.524 ⇒ 00:05:33.439 Miguel de Veyra: the question I have you is, do we only want in progress? Not right? Once it’s done, we should remove it right.
73 00:05:34.650 ⇒ 00:05:36.030 Uttam Kumaran: No, I I mean.
74 00:05:36.330 ⇒ 00:05:40.669 Uttam Kumaran: I think we should just leave it as long as the metadata is there about the status? Then it’s fine.
75 00:05:41.710 ⇒ 00:05:42.540 Uttam Kumaran: right.
76 00:05:43.640 ⇒ 00:05:51.530 Miguel de Veyra: Okay. Yeah. Cause my my worry here is, you know, tasks. But they’re not really that big. There’s gonna be too much of them. That’s my worry.
77 00:05:52.090 ⇒ 00:05:56.030 Uttam Kumaran: But again, I guess. Get tell me what the tell me what the like.
78 00:05:56.440 ⇒ 00:05:58.999 Uttam Kumaran: just because there’s a lot doesn’t mean. What’s the problem.
79 00:06:00.337 ⇒ 00:06:02.960 Miguel de Veyra: Our knowledge, which is gonna balloon.
80 00:06:03.720 ⇒ 00:06:04.600 Uttam Kumaran: Or what.
81 00:06:05.520 ⇒ 00:06:10.770 Miguel de Veyra: Yeah, cause. Right now, we already have a hundred 13 records with sales and with leads and.
82 00:06:11.300 ⇒ 00:06:13.910 Uttam Kumaran: That’s not that. It’s not a lot dude.
83 00:06:15.200 ⇒ 00:06:19.930 Miguel de Veyra: Yeah, but I think there’s a ton of. But yeah, we’ll see again.
84 00:06:19.930 ⇒ 00:06:26.830 Uttam Kumaran: But I guess, like I guess here’s what I’m trying to get at. Tell me what the real problem is. You’re just telling me there’s a lot like what breaks down.
85 00:06:27.230 ⇒ 00:06:34.699 Miguel de Veyra: It could hallucinate eventually, because the data is too much. There’s too big of, you know, basically to run it on to run ragged.
86 00:06:36.500 ⇒ 00:06:40.809 Uttam Kumaran: Okay. But then let’s break that problem down. Are we not doing retrieval first? st
87 00:06:43.063 ⇒ 00:06:47.920 Miguel de Veyra: No, no, we are, we are, we are. It’s just also retrieval also has a limit.
88 00:06:49.270 ⇒ 00:06:53.790 Uttam Kumaran: But aren’t you retrieving the ticket and then doing the summary.
89 00:06:56.200 ⇒ 00:06:57.359 Miguel de Veyra: No, I mean.
90 00:06:57.580 ⇒ 00:07:02.810 Uttam Kumaran: You don’t par, you don’t parse through all the contents of every single.
91 00:07:03.580 ⇒ 00:07:07.040 Uttam Kumaran: Ask every time, do you? Right? You don’t need to do that.
92 00:07:07.350 ⇒ 00:07:08.390 Miguel de Veyra: For Ragda.
93 00:07:08.900 ⇒ 00:07:11.190 Uttam Kumaran: Yeah, you just need to get the metadata right.
94 00:07:13.045 ⇒ 00:07:18.069 Miguel de Veyra: Yes, but that it it still has to go through everything
95 00:07:19.920 ⇒ 00:07:22.730 Miguel de Veyra: unless we separate into different databases.
96 00:07:23.790 ⇒ 00:07:28.850 Uttam Kumaran: Okay. But I like, I just don’t think I didn’t know that. That’s how
97 00:07:29.340 ⇒ 00:07:35.749 Uttam Kumaran: that worked. I thought, you’re just looking at the metadata to find a match, and then you expand the contents
98 00:07:35.910 ⇒ 00:07:36.780 Uttam Kumaran: right.
99 00:07:37.450 ⇒ 00:07:41.859 Miguel de Veyra: Yes, but the there’s gonna be so much metadata to look into.
100 00:07:44.580 ⇒ 00:07:48.259 Uttam Kumaran: I just don’t, I guess, like my push back would be
101 00:07:48.600 ⇒ 00:07:55.110 Uttam Kumaran: a hundred rows. Even a thousand rows is like no amount of data like this is the smallest.
102 00:07:55.730 ⇒ 00:08:01.549 Uttam Kumaran: We’re gonna be working with clients who have like millions and millions of records. So I don’t really.
103 00:08:01.920 ⇒ 00:08:08.740 Uttam Kumaran: Maybe if we do a maybe we should do a spike on rag over hundreds of dos, because
104 00:08:09.010 ⇒ 00:08:30.060 Uttam Kumaran: again, I haven’t done it, and maybe if you haven’t done it, then both of us, we should go do some research on changing our rag method, basically because I do think that there are rag methods just that can go through that many documents like, without having to bring everything into context. I think it may require a couple of changes. One. It may require better better metadata about each row
105 00:08:30.180 ⇒ 00:08:33.770 Uttam Kumaran: like a summary of like what’s in the thing, for example?
106 00:08:34.717 ⇒ 00:08:38.579 Uttam Kumaran: But I do think that maybe we should do so. Maybe we should do a spike on.
107 00:08:39.970 ⇒ 00:08:41.460 Miguel de Veyra: Right, basically yeah.
108 00:08:41.460 ⇒ 00:08:58.859 Uttam Kumaran: Basically on rag. And I would like that, too, because I wanna I wanna look at what we’re doing for embedding. I wanna look at what we’re doing for the vector dB, I wanna look what we’re doing for retrieval. So maybe let’s just do a thing on rag. And maybe we could just outline everything, and then we can even do a presentation internally.
109 00:08:59.500 ⇒ 00:09:04.370 Miguel de Veyra: Okay, yeah, sure. Sure. I’ll look into that cause. I remember Utah. Remember the Hpi stuff.
110 00:09:04.780 ⇒ 00:09:05.500 Uttam Kumaran: Yeah.
111 00:09:05.500 ⇒ 00:09:08.129 Miguel de Veyra: That was 70 pages of like.
112 00:09:08.310 ⇒ 00:09:11.899 Miguel de Veyra: you know, very a lot of text.
113 00:09:12.110 ⇒ 00:09:14.260 Miguel de Veyra: It was already hallucinating.
114 00:09:14.850 ⇒ 00:09:20.519 Uttam Kumaran: But this is but this is where it’s like, I I don’t think we like. I think that’s a solvable problem.
115 00:09:21.060 ⇒ 00:09:22.219 Miguel de Veyra: Yeah, yeah, yeah.
116 00:09:22.220 ⇒ 00:09:25.470 Uttam Kumaran: Meaning like, there’s several strategies to fix that
117 00:09:25.600 ⇒ 00:09:29.079 Uttam Kumaran: like you do chunking. We have several agents.
118 00:09:29.400 ⇒ 00:09:45.980 Uttam Kumaran: but also dude like Gemini. Context window is huge like, Quad context window is getting bigger. So I feel like they can take on a lot of work. But yeah, I think we probably just need to break the steps down. So let’s do let’s do a spike on rack between us, and we can figure it out.
119 00:09:46.330 ⇒ 00:09:47.690 Miguel de Veyra: Okay. Yeah. Sure. Sounds good.
120 00:10:13.920 ⇒ 00:10:17.330 Uttam Kumaran: Okay, so I’m going to create a
121 00:10:18.150 ⇒ 00:10:22.010 Uttam Kumaran: take it here, which is, gonna be
122 00:10:22.380 ⇒ 00:10:27.520 Uttam Kumaran: break up tickets or minimum motion
123 00:10:37.610 ⇒ 00:10:38.450 Uttam Kumaran: this year.
124 00:10:48.330 ⇒ 00:10:49.050 Uttam Kumaran: 5.
125 00:10:54.310 ⇒ 00:11:00.409 Miguel de Veyra: Oh, yeah, because I remember, Casey, didn’t we do something like this where they had like 20,000 records.
126 00:11:01.720 ⇒ 00:11:06.680 Casie Aviles: Yeah. But for that, we, the rag was like, yeah, it’s right
127 00:11:06.680 ⇒ 00:11:11.100 Casie Aviles: from us, because we use open AI right? Openai assistance.
128 00:11:13.000 ⇒ 00:11:17.100 Miguel de Veyra: Yeah, it was. Was it performing good, Casey? I think it was okay. Right?
129 00:11:18.746 ⇒ 00:11:21.180 Casie Aviles: Yeah. It was mostly fine.
130 00:11:21.650 ⇒ 00:11:23.810 Miguel de Veyra: Like 80% of the time, right?
131 00:11:24.660 ⇒ 00:11:32.189 Casie Aviles: Yeah, or the good thing with any 10 and and super base, I guess, is we could. You know, there are a lot of factors that we could
132 00:11:33.175 ⇒ 00:11:36.550 Casie Aviles: tweak like, yeah, for example, like the chunking. And
133 00:11:37.140 ⇒ 00:11:41.509 Casie Aviles: yeah with metadata. So that’s actually something I am trying with
134 00:11:41.670 ⇒ 00:11:44.410 Casie Aviles: the zoom thing with this transcript. So
135 00:11:44.690 ⇒ 00:11:51.489 Casie Aviles: I am custom further customizing the metadata filters. So yeah, maybe that’s something we can explore.
136 00:11:51.490 ⇒ 00:11:52.070 Miguel de Veyra: Yeah.
137 00:11:57.750 ⇒ 00:12:00.050 Uttam Kumaran: Okay, cool.
138 00:12:08.520 ⇒ 00:12:15.569 Uttam Kumaran: Yeah, I feel like for all this, we’re actually pretty good on right now. So I’m just gonna move this to backlog because
139 00:12:15.750 ⇒ 00:12:17.579 Uttam Kumaran: we have a lot of work we’re doing.
140 00:12:21.350 ⇒ 00:12:22.480 Uttam Kumaran: I’ll leave that.
141 00:12:23.050 ⇒ 00:12:33.180 Uttam Kumaran: Okay. So for the zoom agent, basically, I think, the sales one is done.
142 00:12:33.680 ⇒ 00:12:39.850 Uttam Kumaran: I think we what we have 2, we’ve we have 2 additional sort of features we want to do. One is we want to start expanding
143 00:12:40.180 ⇒ 00:12:47.199 Uttam Kumaran: 1st to the AI team for engineering, related tickets for engineering, related summaries.
144 00:12:48.130 ⇒ 00:12:48.560 Casie Aviles: No, no.
145 00:12:48.971 ⇒ 00:12:54.360 Uttam Kumaran: And then we want to start expanding to client meetings.
146 00:12:57.390 ⇒ 00:13:01.939 Uttam Kumaran: So how should I should I like you want me to just create those tickets.
147 00:13:02.200 ⇒ 00:13:05.900 Uttam Kumaran: And then also, I want to do the manual process where we can upload a transcript.
148 00:13:07.850 ⇒ 00:13:08.750 Casie Aviles: Yes, yes.
149 00:13:12.930 ⇒ 00:13:16.890 Miguel de Veyra: Could I put that manual upload into the internal tools? Then.
150 00:13:22.880 ⇒ 00:13:29.230 Uttam Kumaran: What do you mean? Oh, yeah, yeah. I mean, basically, you could paste in a transcript or send in a transcript
151 00:13:29.430 ⇒ 00:13:33.430 Uttam Kumaran: via DM, and then it’ll do it potentially.
152 00:13:33.760 ⇒ 00:13:34.830 Miguel de Veyra: Okay. Okay.
153 00:13:34.830 ⇒ 00:13:39.050 Uttam Kumaran: Or, yeah, we yeah, I think I think again, having everything go through slack.
154 00:13:39.660 ⇒ 00:13:43.029 Uttam Kumaran: Having slack be the Ui is gonna be the best for us internally.
155 00:13:43.480 ⇒ 00:13:44.320 Miguel de Veyra: Okay. Okay.
156 00:13:47.400 ⇒ 00:13:51.867 Casie Aviles: I think I was. I was playing around with that yesterday.
157 00:13:52.430 ⇒ 00:13:56.669 Casie Aviles: I think I guess you could test it out, Witham, if you you could send like
158 00:13:56.790 ⇒ 00:14:00.810 Casie Aviles: you could tag the Zoom agent and then attach a transcript.
159 00:14:02.080 ⇒ 00:14:04.800 Uttam Kumaran: Hmm, okay, it works.
160 00:14:07.363 ⇒ 00:14:08.030 Casie Aviles: Yeah, yeah.
161 00:14:08.520 ⇒ 00:14:09.390 Casie Aviles: Should.
162 00:14:12.210 ⇒ 00:14:13.639 Casie Aviles: I can test right now.
163 00:14:20.240 ⇒ 00:14:22.500 Miguel de Veyra: Maybe we can test you. The Televiro Transcript.
164 00:14:24.730 ⇒ 00:14:27.390 Uttam Kumaran: Yeah, no, I literally have it. You want to try it right now.
165 00:14:29.000 ⇒ 00:14:30.380 Miguel de Veyra: Yeah, let’s try it.
166 00:14:30.380 ⇒ 00:14:31.630 Uttam Kumaran: Okay, there.
167 00:14:33.050 ⇒ 00:14:37.779 Casie Aviles: But is it the same format as the transcripts from zoom.
168 00:14:37.780 ⇒ 00:14:38.630 Uttam Kumaran: No.
169 00:14:39.380 ⇒ 00:14:41.749 Casie Aviles: Oh, okay, so there might be some
170 00:14:41.850 ⇒ 00:14:45.939 Casie Aviles: issues with that. But yeah, let’s see if it will.
171 00:14:45.940 ⇒ 00:14:48.785 Uttam Kumaran: Can I just slack? Can I just slack it directly.
172 00:14:53.210 ⇒ 00:14:54.899 Uttam Kumaran: or I have to tag it.
173 00:14:56.451 ⇒ 00:14:57.809 Casie Aviles: Yeah, you have to target
174 00:14:59.540 ⇒ 00:15:02.069 Casie Aviles: because it triggers on bot mention.
175 00:15:06.160 ⇒ 00:15:08.919 Casie Aviles: Oh, it should be in the 8th test channel.
176 00:15:09.470 ⇒ 00:15:11.189 Uttam Kumaran: Yeah, where is the test? Channel? Okay?
177 00:15:14.450 ⇒ 00:15:15.879 Casie Aviles: Oh, it didn’t work.
178 00:15:17.820 ⇒ 00:15:19.930 Miguel de Veyra: Does it accept text, or only files.
179 00:15:22.800 ⇒ 00:15:24.640 Casie Aviles: It could get files.
180 00:15:25.090 ⇒ 00:15:27.690 Casie Aviles: I was playing around with it yesterday, but
181 00:15:27.990 ⇒ 00:15:30.370 Casie Aviles: hang on! Yes, it’s not working right now.
182 00:15:33.069 ⇒ 00:15:33.849 Uttam Kumaran: So what the.
183 00:15:37.790 ⇒ 00:15:41.430 Miguel de Veyra: I think you need to type. Oh, no, no, it’s there.
184 00:15:46.740 ⇒ 00:15:48.599 Miguel de Veyra: Maybe you have to click, share this file.
185 00:15:48.830 ⇒ 00:15:49.540 Miguel de Veyra: No.
186 00:15:52.590 ⇒ 00:15:54.419 Uttam Kumaran: Yeah. What if I Oh, God!
187 00:15:55.550 ⇒ 00:15:56.940 Uttam Kumaran: But I shouldn’t do this.
188 00:15:57.947 ⇒ 00:16:00.030 Miguel de Veyra: I should. Yeah, probably a file.
189 00:16:02.330 ⇒ 00:16:04.130 Casie Aviles: Yeah, this the same way I did
190 00:16:16.240 ⇒ 00:16:19.280 Casie Aviles: like these were working yesterday, but
191 00:16:20.100 ⇒ 00:16:21.839 Casie Aviles: I’ll just have to go and check.
192 00:16:22.750 ⇒ 00:16:24.620 Casie Aviles: Why, it’s not working right now.
193 00:16:25.830 ⇒ 00:16:29.849 Uttam Kumaran: And then I’m gonna send, listen, and
194 00:16:35.610 ⇒ 00:16:37.269 Uttam Kumaran: you can give it a go.
195 00:16:37.920 ⇒ 00:16:39.810 Casie Aviles: Oh, wait! That’s the lead researcher.
196 00:16:40.250 ⇒ 00:16:44.780 Uttam Kumaran: Oh, shit my bad.
197 00:16:52.950 ⇒ 00:16:53.890 Uttam Kumaran: Okay, good.
198 00:16:56.430 ⇒ 00:16:59.040 Uttam Kumaran: Okay. But here you go. At least you have it. So
199 00:17:05.349 ⇒ 00:17:07.699 Uttam Kumaran: okay, great. So I think between
200 00:17:08.819 ⇒ 00:17:12.690 Uttam Kumaran: slack to notion the Zoom Meeting summarizer.
201 00:17:12.980 ⇒ 00:17:18.849 Uttam Kumaran: And then I’m gonna go ahead and mark this specific pages into notion as done.
202 00:17:25.060 ⇒ 00:17:27.230 Uttam Kumaran: So the stuff that we want to move
203 00:17:27.930 ⇒ 00:17:32.640 Uttam Kumaran: next is the stuff for Craig and slack to notion.
204 00:17:34.010 ⇒ 00:17:39.200 Uttam Kumaran: For the Zoom Meeting summarizer. I’m gonna go ahead and create the 2 new tickets.
205 00:17:40.110 ⇒ 00:17:50.280 Uttam Kumaran: Create 2 new tickets, one for manual upload of transcripts.
206 00:17:50.440 ⇒ 00:18:01.429 Uttam Kumaran: The second is, gonna be for AI theme zoom summarizer great. And then
207 00:18:03.270 ⇒ 00:18:05.329 Uttam Kumaran: I think there was one more.
208 00:18:09.800 ⇒ 00:18:16.160 Uttam Kumaran: Yeah, the stuff for Craig I’m gonna just move into.
209 00:18:16.430 ⇒ 00:18:18.200 Uttam Kumaran: Did you take a look at that, Casey?
210 00:18:19.248 ⇒ 00:18:21.900 Casie Aviles: Yeah, yeah, I was checking it earlier.
211 00:18:22.120 ⇒ 00:18:23.260 Uttam Kumaran: What do you think?
212 00:18:24.160 ⇒ 00:18:29.309 Casie Aviles: I I it’s fairly straightforward. I guess it’s just going to read from
213 00:18:29.420 ⇒ 00:18:33.140 Casie Aviles: excel. I I mean spreadsheet, a spreadsheet, and then
214 00:18:33.660 ⇒ 00:18:36.830 Casie Aviles: process that the only thing I’m wondering is if
215 00:18:37.720 ⇒ 00:18:45.490 Casie Aviles: if a few shot prompting would be enough to like copy Craig’s style of writing. But
216 00:18:46.110 ⇒ 00:18:47.809 Casie Aviles: yeah, that’s something I love.
217 00:18:48.650 ⇒ 00:18:49.820 Casie Aviles: Explore.
218 00:18:49.820 ⇒ 00:18:55.760 Uttam Kumaran: I think. Do do that, for now I have some other solutions we could use, like we’ve been using twain
219 00:18:56.826 ⇒ 00:19:00.523 Uttam Kumaran: for our copy on the marketing side, and it’s been good.
220 00:19:00.990 ⇒ 00:19:05.740 Uttam Kumaran: But let’s just do for now, and see how he likes it. You know.
221 00:19:06.660 ⇒ 00:19:07.370 Casie Aviles: Okay.
222 00:19:14.850 ⇒ 00:19:21.650 Uttam Kumaran: Okay. So for the slack to notion, what do you think? Miguel and Mike date? We had
223 00:19:22.690 ⇒ 00:19:29.669 Uttam Kumaran: the day for the spike, but should I put a different date. To like get it done.
224 00:19:30.620 ⇒ 00:19:34.729 Miguel de Veyra: Oh, can we decide on date after the spec.
225 00:19:35.570 ⇒ 00:19:39.009 Uttam Kumaran: Yeah, I didn’t know whether you’re like, oh, you’re just looking at it today.
226 00:19:39.420 ⇒ 00:19:40.459 Miguel de Veyra: Yeah, yeah, yeah.
227 00:19:40.460 ⇒ 00:19:44.809 Uttam Kumaran: Okay, okay, then let’s let’s decide. Then I also slacked you. I sent some examples.
228 00:19:45.570 ⇒ 00:19:46.000 Miguel de Veyra: Okay.
229 00:19:46.000 ⇒ 00:19:47.329 Uttam Kumaran: That we would use it for
230 00:19:55.050 ⇒ 00:19:56.320 Uttam Kumaran: how are you feeling.
231 00:19:58.159 ⇒ 00:20:01.600 Miguel de Veyra: Better better drunk, medical.
232 00:20:07.150 ⇒ 00:20:12.869 Casie Aviles: So this has to be like a a separate agent, right separate, slack, but.
233 00:20:13.890 ⇒ 00:20:15.349 Uttam Kumaran: Yeah, I guess I’ll let
234 00:20:15.580 ⇒ 00:20:21.310 Uttam Kumaran: Miguel think about what the sort of yeah. But ideally, it’s an agent, or it’s like a workflow.
235 00:20:23.480 ⇒ 00:20:24.470 Miguel de Veyra: Picketeer.
236 00:20:26.380 ⇒ 00:20:28.880 Uttam Kumaran: Yeah, agent, yeah. Tickets here, or like.
237 00:20:30.490 ⇒ 00:20:33.220 Uttam Kumaran: you could put it all under one notion. Sort of bot.
238 00:20:34.340 ⇒ 00:20:35.500 Uttam Kumaran: But yeah, yeah.
239 00:20:35.500 ⇒ 00:20:39.960 Uttam Kumaran: Sub agent. And the whole notion. Bob is probably a sub agent for. But okay.
240 00:20:42.100 ⇒ 00:20:44.390 Miguel de Veyra: Okay, yeah, yeah. We’ll. I’ll figure it out.
241 00:20:47.880 ⇒ 00:20:52.059 Uttam Kumaran: Cool, and then we can work on the spike next week.
242 00:20:56.210 ⇒ 00:20:58.669 Uttam Kumaran: I wanna spend like a day doing this.
243 00:21:01.110 ⇒ 00:21:07.580 Uttam Kumaran: Okay, cool. I’m hoping next week we can get the demo page onto the site as well. So.
244 00:21:10.100 ⇒ 00:21:12.299 Miguel de Veyra: Oh, that’s what you mean is, do
245 00:21:12.670 ⇒ 00:21:15.849 Miguel de Veyra: basically to put the demo page into the website.
246 00:21:16.290 ⇒ 00:21:17.289 Uttam Kumaran: Yeah, yeah, yeah.
247 00:21:17.290 ⇒ 00:21:17.715 Miguel de Veyra: Oh!
248 00:21:18.140 ⇒ 00:21:18.520 Uttam Kumaran: I know.
249 00:21:18.520 ⇒ 00:21:23.860 Miguel de Veyra: I was wondering what you meant. Ifa, what will we iframe into the demo website.
250 00:21:24.450 ⇒ 00:21:31.169 Uttam Kumaran: Oh, yeah, well, I think we’re gonna know, because sometimes some people like we wanna embed that in different parts of the site.
251 00:21:31.530 ⇒ 00:21:32.160 Miguel de Veyra: Yeah.
252 00:21:32.912 ⇒ 00:21:37.359 Uttam Kumaran: But we’re gonna put it behind demo.brainforge.ai regardless. So.
253 00:21:37.360 ⇒ 00:21:39.290 Miguel de Veyra: Have you talked to your friend? By the way.
254 00:21:39.936 ⇒ 00:21:45.279 Uttam Kumaran: Yeah, I mean, I could. But I’m basically waiting for designs to talk to, to talk to them.
255 00:21:45.880 ⇒ 00:21:56.229 Uttam Kumaran: So as soon as I don’t want them to to think about like functionality. So basically, as soon as whatever we have on Heroku needs to get deployed, I can get a I can call a favor in.
256 00:21:56.790 ⇒ 00:22:00.580 Miguel de Veyra: Okay, yeah, it’s just basically routing anyways.
257 00:22:01.470 ⇒ 00:22:01.930 Uttam Kumaran: Yeah.
258 00:22:02.263 ⇒ 00:22:06.599 Miguel de Veyra: Regarding Craig, are we gonna send him like an sow or not? Yet?
259 00:22:06.750 ⇒ 00:22:13.539 Uttam Kumaran: Yeah. So Craig is, basically he, the way we’re kind of interacting with him is he’s actually sending us a lot of leads.
260 00:22:15.230 ⇒ 00:22:22.400 Uttam Kumaran: So we’re not. He’s not paying right now. We have plans to get towards a contract.
261 00:22:22.670 ⇒ 00:22:23.260 Uttam Kumaran: Oh.
262 00:22:23.260 ⇒ 00:22:23.650 Miguel de Veyra: Okay. Okay.
263 00:22:23.650 ⇒ 00:22:32.280 Uttam Kumaran: This quarter, Craig. It literally sends us so much business, though, like he’s connecting me with every like a tons and tons of companies.
264 00:22:33.160 ⇒ 00:22:35.059 Uttam Kumaran: was like, Okay, this is a good like.
265 00:22:36.070 ⇒ 00:22:36.830 Miguel de Veyra: Partnership with.
266 00:22:36.830 ⇒ 00:22:40.810 Uttam Kumaran: Yeah. And and I don’t know, Casey, you can attest the stuff he wants is like very easy.
267 00:22:41.490 ⇒ 00:22:42.123 Casie Aviles: Yeah, yeah.
268 00:22:42.750 ⇒ 00:22:56.599 Uttam Kumaran: So I just was like, you know, he he wants like simple things like, Help me write this copy and stuff in Google sheets. Craig is like dude, I would say. Craig may be the most connected person and technology that I know. Like in my life.
269 00:22:57.040 ⇒ 00:23:02.390 Uttam Kumaran: Oh, wow! Yeah, he’s friends with like, like.
270 00:23:03.030 ⇒ 00:23:11.379 Uttam Kumaran: like the a lot of very rich, successful tech people. So, and he’s making introductions for business for a lot of us. So.
271 00:23:12.010 ⇒ 00:23:14.630 Miguel de Veyra: Also on our last meeting. He basically was like.
272 00:23:15.110 ⇒ 00:23:21.710 Uttam Kumaran: I’m working on figuring out how I can fund you guys like how I can get a contract in place to have you guys more on Retainer.
273 00:23:22.220 ⇒ 00:23:24.720 Miguel de Veyra: Oh, yeah, that was also what I have in mind.
274 00:23:25.320 ⇒ 00:23:30.079 Uttam Kumaran: Like, hey? You could have like 10 h of our time per month, or something, or.
275 00:23:30.460 ⇒ 00:23:32.960 Miguel de Veyra: Yeah, yeah. At the moment I’m like, less.
276 00:23:35.280 ⇒ 00:23:35.960 Miguel de Veyra: Okay?
277 00:23:39.710 ⇒ 00:23:43.240 Miguel de Veyra: And then, what else do we need to talk about?
278 00:23:43.940 ⇒ 00:23:49.210 Miguel de Veyra: I just, oh, yeah, about the recruiting part. I I spoke with Jana.
279 00:23:49.730 ⇒ 00:23:50.310 Uttam Kumaran: Okay.
280 00:23:50.620 ⇒ 00:23:59.199 Miguel de Veyra: Regarding the clay stuff. He doesn’t. She doesn’t have experience on it specifically, but I think we could take her on as part time. Maybe, like.
281 00:23:59.410 ⇒ 00:24:09.259 Miguel de Veyra: I don’t know, like a very cheap rate, 3 4 bucks, basically, you know, learn it, for now and then, once you learn it, we’ll gauge you, and then, if you can do it full time alone.
282 00:24:09.410 ⇒ 00:24:11.340 Miguel de Veyra: then we’ll increase your rate.
283 00:24:12.630 ⇒ 00:24:17.459 Uttam Kumaran: Okay, yeah, I mean, we don’t. We still haven’t closed anything yet, but I think it’s good to keep her sort of
284 00:24:18.050 ⇒ 00:24:18.890 Uttam Kumaran: oh, great.
285 00:24:19.890 ⇒ 00:24:23.139 Miguel de Veyra: Yep, I’ve spoken to her. Yeah, okay? And then.
286 00:24:25.280 ⇒ 00:24:27.030 Miguel de Veyra: yeah, I think that’s pretty much it.
287 00:24:29.620 ⇒ 00:24:32.570 Uttam Kumaran: Okay, guys slack me if anything else.
288 00:24:34.140 ⇒ 00:24:34.720 Miguel de Veyra: Okay. Thank.
289 00:24:35.192 ⇒ 00:24:43.229 Uttam Kumaran: I want to hear about all the slack sort of Api and and all those things, because
290 00:24:43.940 ⇒ 00:24:46.589 Uttam Kumaran: we’re gonna start using slack much more
291 00:24:47.420 ⇒ 00:24:54.120 Uttam Kumaran: for our own. So any docs or blogs that you read just send them to the
292 00:24:54.727 ⇒ 00:25:01.909 Uttam Kumaran: cause I’m gonna be. I want to read all of them. I’m I it just. I may read it like later tonight, or whenever, but.
293 00:25:02.659 ⇒ 00:25:08.050 Miguel de Veyra: I want to sort of absorb like cause. I want to see what everybody’s doing to get a sense of what’s possible, and then.
294 00:25:08.350 ⇒ 00:25:12.879 Uttam Kumaran: For me. It’ll help me think creatively how we get it, how we push things to like the next level.
295 00:25:13.360 ⇒ 00:25:14.060 Miguel de Veyra: Okay.
296 00:25:15.820 ⇒ 00:25:16.540 Uttam Kumaran: Awesome.
297 00:25:17.440 ⇒ 00:25:23.740 Uttam Kumaran: Okay? And then Casey, for the stuff for Craig. Do you want me to throw us on an email? Or do you want to just start
298 00:25:23.920 ⇒ 00:25:27.900 Uttam Kumaran: doing stuff, and then let me know when you have questions.
299 00:25:29.290 ⇒ 00:25:31.730 Casie Aviles: Yeah, I’ll just let you know if I have any questions.
300 00:25:31.730 ⇒ 00:25:32.589 Uttam Kumaran: Okay, okay.
301 00:25:34.670 ⇒ 00:25:38.965 Uttam Kumaran: Oh, and then last thing, yeah.
302 00:25:39.740 ⇒ 00:25:40.560 Miguel de Veyra: Oh, yeah.
303 00:25:40.560 ⇒ 00:25:41.904 Uttam Kumaran: You thought I forgot.
304 00:25:42.240 ⇒ 00:25:45.950 Miguel de Veyra: Yeah, I was like, okay, so we’re not gonna speak about it. Next time.
305 00:25:45.950 ⇒ 00:25:50.770 Uttam Kumaran: Okay, wait. I wanna I wanna go to our messages.
306 00:25:51.380 ⇒ 00:25:57.019 Uttam Kumaran: Okay, I did almost forget with us because we were talking about a lot of stuff. But I was like, Yeah, there’s 1 more thing.
307 00:26:01.390 ⇒ 00:26:08.550 Uttam Kumaran: Okay. So Miguel messaged me, I mean. And and one thing is like, this is totally like.
308 00:26:08.980 ⇒ 00:26:32.919 Uttam Kumaran: I don’t know. Low stress conversation. Actually. What I hope to get out of this conversation is that any sort of concerns around this? You guys voice don’t hold it in cause. I’ve been a lot of companies where I’ve held a lot of this in, and it turns into resentment. It’s like, when you have a relationship or like with your parents like you want to say something, you never say it, and then you hold a resentment. And then, when finally, when you say it, you’re like, oh, that was not bad.
309 00:26:33.510 ⇒ 00:26:34.410 Miguel de Veyra: Yeah, yeah.
310 00:26:34.815 ⇒ 00:26:36.090 Uttam Kumaran: You know Miguel told me.
311 00:26:36.090 ⇒ 00:26:36.820 Miguel de Veyra: Diving.
312 00:26:36.820 ⇒ 00:26:39.239 Uttam Kumaran: Yeah, Miguel told me that you guys were like.
313 00:26:39.430 ⇒ 00:26:46.009 Uttam Kumaran: Hey, we’re not. We’re not. We’re not getting any clients. So there’s gonna be budget cuts and stuff. And again, like I
314 00:26:46.130 ⇒ 00:26:55.950 Uttam Kumaran: I don’t. It doesn’t matter to me how serious or how lighthearted that was one. You guys, you should just one if you have that concern, tell me, please, because
315 00:26:56.360 ⇒ 00:27:01.389 Uttam Kumaran: and then, second, there’s absolutely no cuts on the on the AI side.
316 00:27:01.710 ⇒ 00:27:02.240 Uttam Kumaran: Exactly.
317 00:27:02.240 ⇒ 00:27:06.589 Uttam Kumaran: I wish I could pay you guys more. And we could hire more people.
318 00:27:07.010 ⇒ 00:27:18.679 Uttam Kumaran: we are. We have some really, really amazing opportunities that are at the finish line. And the work we’re doing internally, I know you may think that like, Hey, it’s like.
319 00:27:18.920 ⇒ 00:27:46.839 Uttam Kumaran: we’re just like working on little fun things internally. I I think you you know hopefully, as you’ve seen after working with me for some time, there’s always like a bigger plan to everything. And so a lot of the work that we’re doing internally. Yes, it does help us internally. But second, we’re learning what it takes to completely revolutionize a company with AI by doing it on ourselves. Right. It’s you guys, are you guys familiar with Brian Johnson, the guy who’s doing all the health stuff.
320 00:27:48.240 ⇒ 00:27:50.990 Miguel de Veyra: Oh, the the guy who’s like doesn’t wanna die.
321 00:27:50.990 ⇒ 00:27:54.440 Uttam Kumaran: Yes. So his whole thing is basically like.
322 00:27:54.890 ⇒ 00:28:05.880 Uttam Kumaran: nobody knows how this research all works. So I’m going to use my body as a research vessel and figure it out how to live forever. That’s basically, that’s not what we’re doing, exactly, but kind of
323 00:28:06.090 ⇒ 00:28:13.909 Uttam Kumaran: where we have the whole data part of the business. But the lovely thing is, we’re a great guinea pig to automate our entire business.
324 00:28:14.060 ⇒ 00:28:14.900 Uttam Kumaran: and
325 00:28:15.020 ⇒ 00:28:30.670 Uttam Kumaran: at at minimum we’re the client for all our work, and we make more money. And it’s because we we do things faster and we can deliver faster. However, all of the demos, all of these tools that we’re working on. We’re turning around and marketing and gonna start to sell so definitely
326 00:28:31.508 ⇒ 00:28:34.650 Uttam Kumaran: please don’t be nervous about
327 00:28:35.280 ⇒ 00:28:37.490 Uttam Kumaran: budget cuts or anything like one
328 00:28:37.700 ⇒ 00:28:48.110 Uttam Kumaran: like, there’s no plan to do that. Second. If that was even a a possibility. I would let you know, like very much ahead of time. And
329 00:28:48.250 ⇒ 00:28:49.000 Uttam Kumaran: yeah.
330 00:28:49.000 ⇒ 00:28:50.854 Miguel de Veyra: It’d be like a month or 2.
331 00:28:51.120 ⇒ 00:29:08.820 Uttam Kumaran: It would be way longer than I we could keep. We keep going for a while like it’s just that I want to win with you guys like you know, for me, I don’t want to just sort of struggle and sort of make ends meet. So we’re this is why we’re working super super hard. And you guys know me, I’m working every day like all the time
332 00:29:08.980 ⇒ 00:29:16.669 Uttam Kumaran: we’re we have some big wins this month, and you’re gonna see things are gonna grow really, really fast to where you’ll look back at this conversation and be like
333 00:29:17.000 ⇒ 00:29:24.730 Uttam Kumaran: that was the dumbest thing ever, because we’re in a way. Different place. You know. So and also again, like
334 00:29:24.890 ⇒ 00:29:28.950 Uttam Kumaran: all the credit on the AI side to you guys like you guys developed everything. And
335 00:29:29.310 ⇒ 00:29:33.840 Uttam Kumaran: I’m just here to package it up and and make it look nice, so
336 00:29:36.900 ⇒ 00:29:38.330 Uttam Kumaran: I don’t know, Casey, what do you think.
337 00:29:40.250 ⇒ 00:29:43.190 Casie Aviles: Yeah, I don’t have much to say, but.
338 00:29:44.840 ⇒ 00:29:49.060 Uttam Kumaran: I’m sure you’ve never had this conversation. I’ve never had this conversation in a company before. But.
339 00:29:49.210 ⇒ 00:29:56.650 Uttam Kumaran: dude, I’m just saying that like, yeah for me. If you guys are nervous, please tell me also, like I don’t know. I feel like
340 00:29:57.080 ⇒ 00:30:00.999 Uttam Kumaran: we they were so early.
341 00:30:01.590 ⇒ 00:30:07.319 Uttam Kumaran: Like, you’re gonna be pleasantly surprised at how our work over time compounds
342 00:30:07.630 ⇒ 00:30:13.809 Uttam Kumaran: and how quickly things are gonna change like we’ve only been doing AI for like 3 months.
343 00:30:14.180 ⇒ 00:30:17.349 Uttam Kumaran: 4 months right, Miguel, like, how long?
344 00:30:18.180 ⇒ 00:30:22.220 Miguel de Veyra: Probably even less, right? 3 4 months, probably.
345 00:30:23.580 ⇒ 00:30:28.839 Uttam Kumaran: Like. You say that with me like 3 months. That’s no amount of time. But one of those months is holidays.
346 00:30:29.430 ⇒ 00:30:30.040 Miguel de Veyra: Oh, yeah. Yeah.
347 00:30:30.040 ⇒ 00:30:31.270 Uttam Kumaran: Progress we made
348 00:30:32.100 ⇒ 00:30:44.940 Uttam Kumaran: right. So things take a little bit of time. Unfortunately, like the data part of our business, it took me 2 months to sign our 1st client 3 months to sign our second client, and then 7 months to sign. Our 3rd client
349 00:30:45.680 ⇒ 00:30:52.139 Uttam Kumaran: took takes a long time, so we’re moving very, very fast. And yeah, I mean.
350 00:30:53.020 ⇒ 00:30:59.950 Uttam Kumaran: we just want we’re doing things the right way. And we’re going for big things. That’s why I don’t want us to take projects where they lowball us. They don’t pay us enough.
351 00:31:00.448 ⇒ 00:31:06.569 Uttam Kumaran: Don’t think our worth is our our work is valuable, like, I wanna go after the big, big challenging stuff, you know.
352 00:31:14.370 ⇒ 00:31:15.900 Miguel de Veyra: I guess for me it’s just
353 00:31:16.940 ⇒ 00:31:20.470 Miguel de Veyra: yeah, I guess for me, I mean, I think it’s not really that serious
354 00:31:20.700 ⇒ 00:31:23.919 Miguel de Veyra: when you know me and Casey talked about it. It’s just
355 00:31:24.280 ⇒ 00:31:27.679 Miguel de Veyra: like for looking at it from a business perspective, right?
356 00:31:30.332 ⇒ 00:31:34.560 Miguel de Veyra: But yeah, I guess we. I guess we missed the part where we’re doing a lot of stuff internally.
357 00:31:34.887 ⇒ 00:31:46.672 Uttam Kumaran: No. But also, you know, you guys are right to be like, Hey, we don’t have any AI clients like, doesn’t the revenue from AI directly fund our salary. No, that’s not how it works.
358 00:31:47.260 ⇒ 00:31:58.150 Uttam Kumaran: the way I think about bringing you guys on, especially how early you guys are, is you guys work for Brainforge. You may work for clients, but you guys are part of like the core company.
359 00:31:58.700 ⇒ 00:32:11.929 Uttam Kumaran: There is definitely will be some client revenue that are tied to some people’s salaries and things like that. But we’re building an entire division like entire service line here. So it’s it’s gonna be a little bit weird to start.
360 00:32:12.230 ⇒ 00:32:16.440 Uttam Kumaran: But this is where again, like all the work on the data side we’re doing.
361 00:32:16.830 ⇒ 00:32:22.300 Uttam Kumaran: we’re using a lot of those proceeds to fund this and that way. We now have 2 really, really amazing
362 00:32:24.330 ⇒ 00:32:25.310 Uttam Kumaran: sort of.
363 00:32:26.060 ⇒ 00:32:26.750 Miguel de Veyra: Gorgeous.
364 00:32:26.750 ⇒ 00:32:27.430 Uttam Kumaran: Yeah.
365 00:32:28.260 ⇒ 00:32:29.360 Miguel de Veyra: Okay. Yeah.
366 00:32:31.170 ⇒ 00:32:32.978 Miguel de Veyra: See? Now, it’s not as heavy.
367 00:32:33.280 ⇒ 00:32:40.329 Uttam Kumaran: No, I mean, look, it could be heavy like it’s fine. But I just want to say that, like I think about these things a lot. So
368 00:32:43.230 ⇒ 00:32:45.149 Miguel de Veyra: Yeah. Thanks for the clarification. Ethan.
369 00:32:45.150 ⇒ 00:32:46.459 Uttam Kumaran: Of course, of course.
370 00:32:46.840 ⇒ 00:32:47.749 Casie Aviles: And thank you.
371 00:32:52.900 ⇒ 00:32:54.310 Miguel de Veyra: But yeah, I think.
372 00:32:54.430 ⇒ 00:32:58.930 Miguel de Veyra: yeah, that’s I guess we forgot about. You know, we’ve been doing a lot of
373 00:32:59.390 ⇒ 00:33:01.589 Miguel de Veyra: stuff for AI for the internal.
374 00:33:01.780 ⇒ 00:33:06.669 Miguel de Veyra: Yeah. Cause you, yeah, I forgot you mentioned, we have to treat brain for just client. Also.
375 00:33:07.650 ⇒ 00:33:12.649 Uttam Kumaran: Yeah, and and dude. I mean, we are a big client like that. We have a lot of money that we can save using AI, and
376 00:33:17.260 ⇒ 00:33:18.909 Uttam Kumaran: yeah, so excited.
377 00:33:19.940 ⇒ 00:33:20.570 Miguel de Veyra: Okay.
378 00:33:24.590 ⇒ 00:33:26.500 Uttam Kumaran: Alright, thanks, guys. We’ll talk soon.
379 00:33:26.500 ⇒ 00:33:28.120 Miguel de Veyra: Thanks, guys. Talk soon. Bye, bye.
380 00:33:28.120 ⇒ 00:33:28.740 Uttam Kumaran: Bye.