Meeting Title: Friday Brainforge Demos & Retro Date: 2025-07-25 Meeting participants: Awaish Kumar, Mustafa Raja, luke, Uttam Kumaran, Rico Rejoso, Caio Velasco, Amber Lin, Casie Aviles, Hannah Wang, Annie Yu, Anne, Vashdev Heerani, Elissa Mae Cid, Robert Tseng
WEBVTT
1 00:01:18.590 ⇒ 00:01:19.690 Uttam Kumaran: Hey, everyone.
2 00:01:20.810 ⇒ 00:01:21.330 Caio Velasco: Hello!
3 00:01:21.330 ⇒ 00:01:21.900 Mustafa Raja: Okay.
4 00:01:23.050 ⇒ 00:01:23.840 Uttam Kumaran: Hey.
5 00:01:29.330 ⇒ 00:01:32.969 Uttam Kumaran: Kai, I just learned that you’re presenting. I’m happy. I’m excited.
6 00:01:33.289 ⇒ 00:01:34.249 Uttam Kumaran: Yes, I did.
7 00:01:34.250 ⇒ 00:01:38.640 Uttam Kumaran: I just I didn’t. I didn’t. I didn’t read the slides I like skipped through it. I didn’t want to spoil it.
8 00:01:40.440 ⇒ 00:01:46.750 Caio Velasco: Yeah, yeah, share the the screen? Or will someone else share?
9 00:01:47.857 ⇒ 00:01:51.530 Uttam Kumaran: I’m I’m happy to share. I keep things going. I’ll.
10 00:01:52.250 ⇒ 00:01:53.100 Caio Velasco: That’s good.
11 00:01:53.570 ⇒ 00:01:59.960 Uttam Kumaran: Yeah, just if I if I linger too long, let me know, but I generally can. I’ll follow.
12 00:02:06.110 ⇒ 00:02:07.719 Uttam Kumaran: Just wait for a couple people.
13 00:02:19.830 ⇒ 00:02:20.510 Awaish Kumar: Thank you.
14 00:02:28.190 ⇒ 00:02:30.030 Uttam Kumaran: Amber. How’s it been getting up
15 00:02:30.140 ⇒ 00:02:33.619 Uttam Kumaran: early? I guess I didn’t ask you what your schedule was like before.
16 00:02:33.620 ⇒ 00:02:34.050 Amber Lin: Huh!
17 00:02:34.050 ⇒ 00:02:34.559 Uttam Kumaran: Paying for it.
18 00:02:34.560 ⇒ 00:02:35.790 Amber Lin: Oh, no!
19 00:02:36.276 ⇒ 00:02:48.339 Amber Lin: I mean right now. My day starts at 7 30. My 1st meeting is always 7 30, you know, when I 1st started here. My 1st meetings was at 6 30, so.
20 00:02:48.820 ⇒ 00:02:49.709 Uttam Kumaran: That’s great!
21 00:02:49.710 ⇒ 00:02:51.799 Amber Lin: You’re better now.
22 00:02:55.660 ⇒ 00:03:00.140 Uttam Kumaran: Yeah, I feel like this is the kind of the price we pay for having
23 00:03:00.370 ⇒ 00:03:03.780 Uttam Kumaran: remote. I think we’ll we’ll get better over time.
24 00:03:04.950 ⇒ 00:03:11.500 Uttam Kumaran: But, like I don’t, I don’t know. I think I think some companies like to have meetings all in the morning. Some companies are later in the day.
25 00:03:12.010 ⇒ 00:03:16.930 Uttam Kumaran: I feel like we have to try to match it towards like energy, right? Like, I have a lot of energy in the morning.
26 00:03:17.620 ⇒ 00:03:20.390 Uttam Kumaran: and I’m usually like happy. And
27 00:03:21.240 ⇒ 00:03:33.500 Uttam Kumaran: there’s not like a world of stuff that I have to kind of fix. So I feel like it’s good for like sales where I have to come in and just be like super friendly client meetings
28 00:03:33.760 ⇒ 00:03:35.940 Uttam Kumaran: at the end of the day. It’s like
29 00:03:36.840 ⇒ 00:03:39.718 Uttam Kumaran: it’s a little bit tough for me.
30 00:03:44.740 ⇒ 00:03:48.079 Uttam Kumaran: Okay, let me share this. Get rid of.
31 00:04:20.950 ⇒ 00:04:25.180 Uttam Kumaran: Okay, I’m gonna share. And we can get started.
32 00:04:30.400 ⇒ 00:04:31.250 Uttam Kumaran: Okay.
33 00:04:33.420 ⇒ 00:04:45.599 Uttam Kumaran: great. So agenda for today. I think we’re gonna get. Oh, we have a little bit tighter on the like mid section of the agenda, like, I’m not gonna do sort of like our
34 00:04:45.760 ⇒ 00:04:49.670 Uttam Kumaran: like overview of the whole July. But I think next
35 00:04:49.920 ⇒ 00:04:59.247 Uttam Kumaran: in 2 weeks I’ll do like we’ll do a big July review. But we do have some updates on the team side. We do have some updates on the sales side.
36 00:05:00.030 ⇒ 00:05:01.710 Uttam Kumaran: and
37 00:05:01.970 ⇒ 00:05:14.400 Uttam Kumaran: yeah, I was just kind of wanted to share a little bit of like some changes we’re making on the AI platform. So yeah, this Kyle Kyle is hosting today. So I’ll let you sort of drive. And then, yeah, perfect.
38 00:05:14.570 ⇒ 00:05:28.039 Caio Velasco: Perfect perfect. So we will start with like a nice breaker, and I was trying to think about some things. But then I was on my pictures looking for things, for the next one is the lab share. And I was like, Oh, this remind me of something
39 00:05:28.340 ⇒ 00:05:32.499 Caio Velasco: this when I was very little, and I think I want to be a power ranger or something.
40 00:05:33.060 ⇒ 00:05:38.909 Caio Velasco: And and then I was thinking, having people could share a bit of what they
41 00:05:39.120 ⇒ 00:05:45.710 Caio Velasco: when you were a kid. What did you want to be when you grow up? What was your idea? If there’s something related more to a job.
42 00:05:45.860 ⇒ 00:06:03.119 Caio Velasco: or or something like a superhero, or I had like both things in my mind. I wanted to fly, or then power Rangers started to be big in Brazil like, no, I want to be that thing. And then at certain point, I started to play football. So as a lot of Brazilian kids.
43 00:06:03.270 ⇒ 00:06:09.320 Caio Velasco: you just want to become a football player. That’s it. A soccer player. And
44 00:06:10.020 ⇒ 00:06:14.329 Caio Velasco: but yeah, and then well, at certain point, I think, related to Job.
45 00:06:15.166 ⇒ 00:06:22.130 Caio Velasco: I was always with legal, always trying to build things with my hands. And then it’s like, okay, maybe at some point
46 00:06:23.390 ⇒ 00:06:35.669 Caio Velasco: and then engineering would make sense. But yeah, well, at the end, when you are doing engineering, you’re just writing stuff on the paper or a computer. So you’re not really building anything with your hands. But yeah.
47 00:06:35.880 ⇒ 00:06:41.110 Caio Velasco: so I don’t know if you can go like in a round or something, and people could share a little bit
48 00:06:41.240 ⇒ 00:06:42.539 Caio Velasco: about themselves.
49 00:06:43.460 ⇒ 00:06:51.399 Uttam Kumaran: Yeah, maybe I’ll go, and then I’ll popcorn it to the next person. But yeah, I I wanted to be an astronaut
50 00:06:51.680 ⇒ 00:06:52.670 Uttam Kumaran: growing up.
51 00:06:53.030 ⇒ 00:06:59.059 Uttam Kumaran: I don’t know. I was like obsessed with space and NASA, and like
52 00:06:59.620 ⇒ 00:07:24.829 Uttam Kumaran: I don’t know, I don’t know if I really understood. Like the engineering behind. I just knew it was very complicated. But we go to the planetarium like. I don’t know if anyone has been to that, but I don’t know if there’s 1, if it’s in San Jose or in California somewhere. But you go, and they have this like huge like theater where you kind of lay back, and they do the constellations. And they do like this like show. We go like again and again and again, but yeah, I feel like, now, it’s actually.
53 00:07:24.970 ⇒ 00:07:30.650 Uttam Kumaran: I know a lot more about what it’s like to. I I mean, from what I’ve read about it, it’s like.
54 00:07:30.840 ⇒ 00:07:44.840 Uttam Kumaran: imagine such a complicated problem to get to space and you know, when they were 1st thinking about going to the space in in 19 sixties, right? Everybody was like, is this is a waste of time, like.
55 00:07:44.980 ⇒ 00:08:09.799 Uttam Kumaran: you know, and like, what are we gonna get out of this? But partly it was because we wanted to show like, hey, America can accomplish literally going to the moon, you know. And I thought when I was reading a lot about that as a kid, I was like, this is insane, like I, right? And you go outside and you look at the moon, and you’re like, how did we? Someone sat here and was like we should go there and go hang out up there and thought that was pretty cool. So yeah.
56 00:08:10.413 ⇒ 00:08:14.280 Uttam Kumaran: I’ll popcorn maybe to to a wish.
57 00:08:15.900 ⇒ 00:08:22.140 Awaish Kumar: Yeah, like I, who wanted to be a doctor initially like, Oh.
58 00:08:23.330 ⇒ 00:08:34.970 Awaish Kumar: but with the time like when I grew up like, I just figured out I couldn’t see people in pain. I can’t like. It’s very hard for me to go to in. Go in the
59 00:08:35.299 ⇒ 00:08:40.830 Awaish Kumar: so long see them, so I don’t know like I can’t be the person looking.
60 00:08:41.870 ⇒ 00:08:43.729 Awaish Kumar: making the curds or things like that.
61 00:08:44.360 ⇒ 00:08:46.070 Awaish Kumar: I just switched.
62 00:08:46.410 ⇒ 00:08:49.000 Anne: What did you want to do when you grew up?
63 00:08:49.260 ⇒ 00:08:54.600 Anne: Specific job superhero? I so great.
64 00:08:55.270 ⇒ 00:08:57.799 Awaish Kumar: Yeah, amber, you can go.
65 00:08:57.800 ⇒ 00:09:01.800 Anne: But not see how I sh Northberg.
66 00:09:02.650 ⇒ 00:09:04.989 Uttam Kumaran: Oh, and you’re and you’re unmuted.
67 00:09:09.240 ⇒ 00:09:10.300 Anne: One palao.
68 00:09:12.770 ⇒ 00:09:14.800 Uttam Kumaran: Go! Go ahead! Go ahead! Amber.
69 00:09:18.040 ⇒ 00:09:19.059 Caio Velasco: I think we can hear you.
70 00:09:19.060 ⇒ 00:09:21.160 Uttam Kumaran: Wait. We can’t hear you through your mic.
71 00:09:22.410 ⇒ 00:09:32.020 Amber Lin: You go. I want to be an industrial designer like interior designer product design and then, because I was going to different tours of
72 00:09:33.540 ⇒ 00:09:35.250 Amber Lin: It’s pretty.
73 00:09:35.670 ⇒ 00:09:36.900 Amber Lin: Oh.
74 00:09:39.640 ⇒ 00:09:41.370 Uttam Kumaran: You’re lacking a little bit.
75 00:09:41.370 ⇒ 00:09:44.530 Amber Lin: Time, and oh!
76 00:09:44.630 ⇒ 00:09:45.560 Amber Lin: Easier.
77 00:09:52.450 ⇒ 00:09:53.649 Uttam Kumaran: Maybe try video off.
78 00:09:53.650 ⇒ 00:09:57.569 Amber Lin: And yeah, let me try that.
79 00:09:58.540 ⇒ 00:10:01.560 Amber Lin: How? How is this? Is this better.
80 00:10:01.560 ⇒ 00:10:02.220 Uttam Kumaran: Back.
81 00:10:02.320 ⇒ 00:10:03.150 Uttam Kumaran: Yeah.
82 00:10:03.680 ⇒ 00:10:10.500 Amber Lin: Okay, yeah. I mean, I wanted to be an industrial designer. To design products.
83 00:10:10.620 ⇒ 00:10:14.780 Amber Lin: mostly less of a massive
84 00:10:16.870 ⇒ 00:10:27.889 Amber Lin: less of those like big machines, but more of daily stuff that helps people’s lives. I think when I was in when I was in primary school
85 00:10:28.130 ⇒ 00:10:30.570 Amber Lin: I had 2 patents.
86 00:10:31.250 ⇒ 00:10:40.819 Amber Lin: It were very silly little patterns, but we had a teacher in school that was helping us understand the process to do that. It was really cool.
87 00:10:40.970 ⇒ 00:10:42.080 Amber Lin: and I think
88 00:10:43.180 ⇒ 00:10:50.569 Amber Lin: like right now, I’m looking at so many home renovation videos. I was like, Oh, that that makes so much sense. That’s so good.
89 00:10:51.410 ⇒ 00:10:53.790 Amber Lin: That’s something that I do really like.
90 00:10:57.700 ⇒ 00:11:07.059 Uttam Kumaran: Yeah, I’ve also gotten more interested in like architecture. I think later in my life, now that I all I did was engineering, I’m getting more interested in like art, and
91 00:11:07.260 ⇒ 00:11:07.860 Uttam Kumaran: like.
92 00:11:07.860 ⇒ 00:11:08.650 Amber Lin: Hmm.
93 00:11:08.830 ⇒ 00:11:10.200 Uttam Kumaran: Lighting design.
94 00:11:10.730 ⇒ 00:11:15.670 Uttam Kumaran: Because I think there’s still a lot of science to it. There’s more science than you think
95 00:11:16.110 ⇒ 00:11:21.929 Uttam Kumaran: in how like a home is a flows, and like what you see, and like lighting
96 00:11:23.270 ⇒ 00:11:27.680 Uttam Kumaran: But that would be like, I feel like that’d be really fun to work on projects like that. So.
97 00:11:30.810 ⇒ 00:11:32.110 Caio Velasco: Okay? Who’s next?
98 00:11:35.380 ⇒ 00:11:36.430 Uttam Kumaran: Amber you wanna.
99 00:11:36.430 ⇒ 00:11:37.130 Amber Lin: Popcorn.
100 00:11:37.130 ⇒ 00:11:37.500 Uttam Kumaran: Somewhat.
101 00:11:37.500 ⇒ 00:11:38.460 Amber Lin: Person.
102 00:11:39.030 ⇒ 00:11:39.490 Uttam Kumaran: Yes.
103 00:11:39.490 ⇒ 00:11:41.973 Amber Lin: I will popcorn to someone.
104 00:11:42.730 ⇒ 00:11:45.079 Amber Lin: Let’s see, Sid, what about you?
105 00:11:48.300 ⇒ 00:11:52.470 Elissa Mae Cid: Hey? Hi! Everyone! Hello, Amber!
106 00:11:53.340 ⇒ 00:11:54.699 Elissa Mae Cid: I said.
107 00:11:55.650 ⇒ 00:11:59.880 Uttam Kumaran: Oh, yeah, I guess, Sid, we said, we intro to you last week. But maybe if you want to give a brief.
108 00:11:59.880 ⇒ 00:12:00.510 Elissa Mae Cid: Is that true.
109 00:12:01.194 ⇒ 00:12:27.527 Uttam Kumaran: You want to get brief intro. Talk about, I guess, like I’ll do the work. Intro Sid is on our sales team. She’s a sales coordinator. She’s helping with everything related to moving from notion to Hubspot for our Crm sort of follow up emails everything around our sales processes. But then I’ll I’ll leave you to go ahead and give a non work intro, and then, yeah, talk about the superhero or job.
110 00:12:28.850 ⇒ 00:12:36.259 Elissa Mae Cid: Yeah, sure. Well, I was surprised that they already focused in anyway. So a personal issue about the
111 00:12:38.380 ⇒ 00:12:39.430 Elissa Mae Cid: how do I?
112 00:12:40.820 ⇒ 00:12:41.670 Elissa Mae Cid: Well.
113 00:12:41.670 ⇒ 00:12:46.910 Uttam Kumaran: I guess I’ll get questions are, where where you live, what you like to do, what what you like
114 00:12:47.590 ⇒ 00:12:49.789 Uttam Kumaran: I don’t know. That’s what I would think about.
115 00:12:50.310 ⇒ 00:13:00.909 Elissa Mae Cid: Okay, alright. So I’m based in Philippines. So I’m in Rainforce, I think. 3 or a month already, almost a month. Things. I love to do.
116 00:13:01.375 ⇒ 00:13:07.960 Elissa Mae Cid: I’m a couch, but at the same time I also love to go out. So I think I’m
117 00:13:08.080 ⇒ 00:13:15.259 Elissa Mae Cid: I love to watch Netflix and watch crime, docus, anything that deals with serial killers
118 00:13:15.360 ⇒ 00:13:33.539 Elissa Mae Cid: and what else? But I’m saying, okay. So the question here, when you were a kid, what did you want to be when you grew up any specific job. Oh, so I remember when I was young I wanted to be a nun.
119 00:13:34.450 ⇒ 00:13:55.849 Elissa Mae Cid: so I don’t know why, but I remember my Lola. My grandma was a devoted Catholic, and was kind of pushing me to become one, so I think, got brainwashed. But I guess I was young and neat, so that’s why she saw me as wanting to become one. But eventually, as I grew up, I wanted to do interior designing, or anything that deals with
120 00:13:56.280 ⇒ 00:14:02.799 Elissa Mae Cid: architect or anything but that didn’t push through as well, so eventually became a banker.
121 00:14:03.340 ⇒ 00:14:04.450 Elissa Mae Cid: There you go.
122 00:14:05.801 ⇒ 00:14:08.929 Uttam Kumaran: Do you wanna popcorn to the next person.
123 00:14:09.750 ⇒ 00:14:11.870 Elissa Mae Cid: Yeah, so that we can keep.
124 00:14:11.870 ⇒ 00:14:13.869 Caio Velasco: A little bit shorter, so that we can get on time.
125 00:14:14.080 ⇒ 00:14:17.450 Uttam Kumaran: Yeah, sorry I’m asking. I’m asking a lot of follow up questions.
126 00:14:18.991 ⇒ 00:14:27.310 Elissa Mae Cid: Yeah. So maybe I’m not done already. But if you are, just let me know. Maybe. Ann, yeah.
127 00:14:29.720 ⇒ 00:14:32.030 Anne: Hi, Hi, sorry about earlier.
128 00:14:32.640 ⇒ 00:14:34.449 Anne: I got too excited.
129 00:14:38.310 ⇒ 00:14:40.785 Anne: anyway. Mine.
130 00:14:43.180 ⇒ 00:14:49.670 Anne: Well, same as see they wanted to be a interior designer. Because, yeah, same
131 00:14:49.830 ⇒ 00:14:54.030 Anne: because my grandma used to like, you know, in an Asian household
132 00:14:54.250 ⇒ 00:14:59.100 Anne: you like, change your curtains to same color as your
133 00:14:59.350 ⇒ 00:15:02.820 Anne: placemats in the dining table, and those are
134 00:15:03.587 ⇒ 00:15:11.829 Anne: spoon and fork and your seat cover and stuff so, and then we used to
135 00:15:12.180 ⇒ 00:15:19.219 Anne: like every Friday we used to buy flowers in capital.
136 00:15:19.400 ⇒ 00:15:21.900 Anne: Yeah, that’s odd.
137 00:15:23.533 ⇒ 00:15:26.919 Anne: Yeah, thank you, Rico, for saying that.
138 00:15:27.547 ⇒ 00:15:30.922 Anne: That my case I don’t know. I’m really sorry about.
139 00:15:31.750 ⇒ 00:15:32.890 Uttam Kumaran: No, you’re good.
140 00:15:33.150 ⇒ 00:15:35.129 Uttam Kumaran: You want to popcorn to the next person.
141 00:15:35.620 ⇒ 00:15:39.949 Anne: Yeah. Yeah. I think next would be Rico.
142 00:15:45.720 ⇒ 00:15:47.819 Rico Rejoso: Yes, morning guys.
143 00:15:51.820 ⇒ 00:15:57.829 Rico Rejoso: when you were a kid. What do you want to be when you grow? I’m sorry for the voice. I’m sorry the weather got the best of me.
144 00:15:59.390 ⇒ 00:16:00.180 Uttam Kumaran: You’re good.
145 00:16:01.433 ⇒ 00:16:03.699 Rico Rejoso: I think. When I was a kid
146 00:16:04.020 ⇒ 00:16:11.763 Rico Rejoso: I was introduced to a lot of stuff by my parents, especially they were owning a lot of businesses back then and
147 00:16:12.250 ⇒ 00:16:34.430 Rico Rejoso: what was in my mind and my basically in the everyone or every all of us siblings was thinking we never wanted a job to start with, because when I was 4 I we were introduced to a lot of stuff which we never knew back then was like AR, or account AR and ap
148 00:16:34.820 ⇒ 00:16:37.219 Uttam Kumaran: 4 years old, you got introduced to Arap.
149 00:16:37.640 ⇒ 00:16:50.482 Rico Rejoso: Yeah, we never knew. Back then my father was like teaching me how to send invoices to to to their clients. They were like have 10 to 15 clients back. Then it’s a construction business.
150 00:16:50.930 ⇒ 00:16:52.640 Rico Rejoso: so it was like.
151 00:16:53.010 ⇒ 00:16:59.090 Rico Rejoso: and we never really appreciate the weekend, even though every Sunday we were bought through like
152 00:16:59.340 ⇒ 00:17:06.819 Rico Rejoso: to all places that we wanted to go. But it’s just that. After our after school hours we want, we need to
153 00:17:07.020 ⇒ 00:17:29.139 Rico Rejoso: help them with their businesses, since they didn’t really hire much employees. We have one accountant that they needed help with everything. So we were like shadowing everyone engineers, accountants, architects, and we never really knew what we wanted back then we just we just don’t want to work anymore at like, after 3 years of doing that one or after we’re going through grade school.
154 00:17:30.240 ⇒ 00:17:39.570 Rico Rejoso: So yeah, I never. I never knew what I wanted when I was a kid since we were introduced to a lot of stuff we just like want to get enough time for us to play with our childhood friends.
155 00:17:40.250 ⇒ 00:17:41.780 Rico Rejoso: Yeah, that’s it for me.
156 00:17:44.670 ⇒ 00:17:46.529 Uttam Kumaran: Nice. You want a popcorn next person.
157 00:17:46.940 ⇒ 00:17:54.249 Rico Rejoso: Yes, sure. Let’s go with, I think, a mustafa.
158 00:17:58.320 ⇒ 00:18:19.600 Mustafa Raja: Hey? So I wanted to be an electrical engineer. My uncle, used to be an electrical engineer, and he worked basically on most of the country’s grid things. And that inspired me because, that’s something that empowers a lot of people. So yeah, it felt cool.
159 00:18:21.980 ⇒ 00:18:22.760 Uttam Kumaran: Nice.
160 00:18:24.630 ⇒ 00:18:26.890 Mustafa Raja: Yeah, I popcorn to Casey.
161 00:18:30.400 ⇒ 00:18:33.380 Casie Aviles: I didn’t want to work. I wanted to be spider-man.
162 00:18:34.720 ⇒ 00:18:36.600 Uttam Kumaran: Yeah, finally.
163 00:18:37.540 ⇒ 00:18:38.380 Casie Aviles: Yeah, yes.
164 00:18:38.380 ⇒ 00:18:51.609 Casie Aviles: Seeing seeing this photo of Kyle reminds me of myself. When I was around. Yeah, 4 or same age, I would wear these my parents bought me like a spider-man costume. So I wore the full costume.
165 00:18:52.060 ⇒ 00:18:58.589 Casie Aviles: Yeah. And and yeah, with the mask and all I keep, I keep tripping and falling down. But I didn’t care.
166 00:18:59.060 ⇒ 00:19:06.209 Casie Aviles: And I just do. You know, acrobatics and shit, and I would crawl, try to crawl walls. Yeah.
167 00:19:08.420 ⇒ 00:19:12.689 Casie Aviles: that was me. Then? Yeah, I’ll call. Who else.
168 00:19:13.000 ⇒ 00:19:15.900 Caio Velasco: Let’s do 2 more people, and very good.
169 00:19:15.900 ⇒ 00:19:19.240 Casie Aviles: Okay, yeah, I’ll call, I guess. Hannah.
170 00:19:21.913 ⇒ 00:19:29.320 Hannah Wang: I also wanted to be an interior designer. So there’s that and then
171 00:19:29.500 ⇒ 00:19:39.609 Hannah Wang: I also wanted to be a nurse. So I actually applied to upenn, which is like which has a top like nursing program here in the Us. But then
172 00:19:39.740 ⇒ 00:19:41.900 Hannah Wang: I’m glad I didn’t get in, because
173 00:19:42.030 ⇒ 00:19:55.505 Hannah Wang: I can’t even look at blood, and I get really squeamish. So who? I don’t know what I was thinking and wanting to be a nurse. So back to my creative roots. It is so I’m here.
174 00:19:57.122 ⇒ 00:20:00.797 Hannah Wang: I will pick this last person
175 00:20:01.630 ⇒ 00:20:05.169 Hannah Wang: who didn’t go yet, can do Annie.
176 00:20:07.150 ⇒ 00:20:28.469 Annie Yu: Yeah, fun. Fact. I also wanted to be an astronaut. And there’s like also like a science museum near where I grew up. So we always go, and there’s like a tunnel with like face stars. And there’s also like a short video starting with like a human. And it zooms out all the way through the space. I think that’s how
177 00:20:28.560 ⇒ 00:20:39.799 Annie Yu: I got inspired. But also, like, after a while, I wanted to be Ferris Spooler. When I saw that movie for the 1st time, like he’s so cool I want to be him
178 00:20:41.230 ⇒ 00:20:42.250 Annie Yu: about me.
179 00:20:45.950 ⇒ 00:20:51.389 Caio Velasco: Cool. Thank you guys, so let’s go to the next one, because we already took a bit more time.
180 00:20:52.534 ⇒ 00:21:00.390 Caio Velasco: Lab share. So I decided to share a bit of some steps I took, let’s say, in the last 5,
181 00:21:01.080 ⇒ 00:21:02.340 Caio Velasco: 7 years.
182 00:21:03.600 ⇒ 00:21:12.140 Caio Velasco: And how did I get here to Spain. And I think that’s also very, very connected, actually to at least at the end, to remote working
183 00:21:12.400 ⇒ 00:21:16.629 Caio Velasco: and like open doors for you to do like lots of different things.
184 00:21:17.258 ⇒ 00:21:24.250 Caio Velasco: So I was born in in and raised in Rio Janeiro. So 1st picture on on the left.
185 00:21:25.111 ⇒ 00:21:31.430 Caio Velasco: That’s like the main beach area in Rio Janito always packed, so I was used to like
186 00:21:31.800 ⇒ 00:21:35.799 Caio Velasco: good weather sometimes is too much too too hot. Lots of people.
187 00:21:36.160 ⇒ 00:21:40.789 Caio Velasco: But I was always, somehow also connected to the Us.
188 00:21:41.205 ⇒ 00:21:48.349 Caio Velasco: I spent like maybe one year and a half when I was 3 in Utah, in South Lake City with my mom and dad
189 00:21:48.881 ⇒ 00:21:55.740 Caio Velasco: and and I think somehow that was inside me. And then, when I was, I don’t know, like
190 00:21:55.980 ⇒ 00:22:02.119 Caio Velasco: 17 or something, I was already thinking, Yeah, maybe one day I want to study abroad, or
191 00:22:02.260 ⇒ 00:22:16.070 Caio Velasco: or even I don’t know, play soccer abroad or something. And then I well, I did a part of my bachelor in in the Us. But it was North Carolina.
192 00:22:16.493 ⇒ 00:22:31.729 Caio Velasco: for a semester, and then I visit New York. That features from from Central Park, I was like, Oh, my God! This is so cool! I mean, we don’t have that much in of parks, and at least in Rio Jane. We have the beach and other things, but not that part.
193 00:22:32.970 ⇒ 00:22:55.220 Caio Velasco: So I was always going to the West for different reasons, even to like work. I worked as a how do you say? Like a food runner, I think, in a restaurant in Fort Lauderdale, near Miami for like 3 months when it was like summer for us in Brazil. Lots of people, lots of friends were. They were doing that for like an experience abroad.
194 00:22:55.731 ⇒ 00:23:04.160 Caio Velasco: Then it was like multiple times, and then I also did my master. But it was later on in life. Then it was la
195 00:23:04.627 ⇒ 00:23:12.669 Caio Velasco: which for me was really nice, because it’s a bit similar, let’s say, weather wise and like beaches, and you know things to do like in Rio.
196 00:23:12.970 ⇒ 00:23:31.600 Caio Velasco: And and then, later on, I went to. I was trying to like, pursue one of my studies, and like maybe a Phd. Or something. Then I ended up moving to the Netherlands, which for me was like super random, because I was just applying to some nice programs. And well, I got accepted in one. I was like, Okay, that’s where I’m going.
197 00:23:32.300 ⇒ 00:23:38.395 Caio Velasco: And but unfortunately it was like Covid. And and at that time
198 00:23:39.100 ⇒ 00:23:41.370 Caio Velasco: why was everything was super difficult.
199 00:23:41.570 ⇒ 00:23:46.450 Caio Velasco: And then I was like, Okay, maybe I should realign some things.
200 00:23:46.620 ⇒ 00:23:55.609 Caio Velasco: Then I ended up leaving the Netherlands. But then it was really really a nice experience, although the weather is very complicated, especially if you come from South America.
201 00:23:55.710 ⇒ 00:23:57.429 Caio Velasco: but it’s a very cool place.
202 00:23:57.580 ⇒ 00:24:08.610 Caio Velasco: And and then well, at that time my mom got retired, and then she wanted really also to have more experiences abroad.
203 00:24:08.750 ⇒ 00:24:11.150 Caio Velasco: So she moved to Portugal.
204 00:24:11.581 ⇒ 00:24:20.049 Caio Velasco: And then that’s the picture in the left as well in the bottom like. That’s a picture from from Lisbon area. Then I had my mom closer to me.
205 00:24:21.540 ⇒ 00:24:35.829 Caio Velasco: And and at that time I was already working remotely, and, you know, trying to see if I could do different things as well. And then, at certain point, I was always with, like some people going to
206 00:24:36.385 ⇒ 00:24:54.169 Caio Velasco: to Spain, and I was hearing a lot of things, while also, like citizenship process is easier for South Americans. The country is a bit more, in my opinion. A bit more. Let’s say things work faster in Spain than in Portugal, maybe not than other places, but at least
207 00:24:54.270 ⇒ 00:25:06.799 Caio Velasco: in Portugal. It’s all funny, because if you come from other places to Spain. You also hear that you know things? Never. This is always gonna be for tomorrow. That’s very Spanish. Nothing is working today.
208 00:25:06.800 ⇒ 00:25:11.319 Uttam Kumaran: Yeah, I’m trying to live. The Spanish lifestyle here.
209 00:25:12.090 ⇒ 00:25:12.750 Caio Velasco: Like.
210 00:25:12.750 ⇒ 00:25:34.809 Caio Velasco: And then I was like, Okay, I’ll move. And I have a friend close by. The weather is also super nice, and Spain is growing a lot. There’s like some tech in Barcelona, Valencia. This picture is from Taragona, which is a historic town very nearby Barcelona, maybe
211 00:25:35.468 ⇒ 00:25:38.419 Caio Velasco: half an hour, or for by car or something.
212 00:25:39.218 ⇒ 00:25:45.489 Caio Velasco: Then. And yeah, that those experiences I was like, I wasn’t expecting to have them.
213 00:25:45.690 ⇒ 00:25:50.709 Caio Velasco: When I went. I started college, for example, I had an idea to study abroad, and that was it.
214 00:25:50.830 ⇒ 00:25:56.220 Caio Velasco: But then, I think life was was bringing me like other opportunities.
215 00:25:56.818 ⇒ 00:26:00.309 Caio Velasco: So now, for example, working for Brainforge living here.
216 00:26:01.420 ⇒ 00:26:07.190 Caio Velasco: you know that like changing. Of of course, my life and my previous job also helped me a lot in that part.
217 00:26:07.410 ⇒ 00:26:12.889 Caio Velasco: So yeah, this there’s always pros and cons normal nor normal, like there’s always trade offs involved.
218 00:26:13.298 ⇒ 00:26:19.770 Caio Velasco: But so far has been really, really nice experience, and I’m looking forward to the next one. I’m not sure when it’s gonna be but
219 00:26:20.330 ⇒ 00:26:27.735 Caio Velasco: so yeah, that’s a little bit about what I’ve been doing so far, let’s say and.
220 00:26:28.180 ⇒ 00:26:36.389 Uttam Kumaran: Yeah, I guess that’s my question is like, What what have you seen? The recurring theme, I mean, all of these places seem like pretty metropolitan cities, like nothing
221 00:26:36.660 ⇒ 00:26:39.890 Uttam Kumaran: too remote or like, you know.
222 00:26:41.130 ⇒ 00:26:41.740 Caio Velasco: But.
223 00:26:41.740 ⇒ 00:26:46.460 Uttam Kumaran: Clear from your photos that you’re like. It’s mostly nature related photos, you know.
224 00:26:46.720 ⇒ 00:26:58.409 Caio Velasco: That is true, that is true. I do like it very connected to it, I think, even though Rio Janit is like a super large town, like 6 7 million people in the city, plus the rest of the State.
225 00:26:58.700 ⇒ 00:27:25.620 Caio Velasco: And but still you have the natures present, you know. You look up, and you see, like the mountain here, the Christ here, or whatever here, and the other beaches, and this and that and that. Of course, there are bad areas as well, where some areas are very complicated. But you have those things there, maybe for someone from Sao Paulo. The other city is different, because it’s a more like a concrete jungle. So it’s a different experience would be probably saying different things.
226 00:27:25.890 ⇒ 00:27:31.530 Caio Velasco: But yeah, I really like, when, for example, when I was in the Netherlands. The the nicest thing for me was the
227 00:27:31.740 ⇒ 00:27:44.829 Caio Velasco: the canals that they built, which, if I’m not wrong to avoid this, since the city is like lower than the sea level that helps like they engineered the city to to help for the future right.
228 00:27:44.830 ⇒ 00:27:45.830 Uttam Kumaran: Like Venice.
229 00:27:45.830 ⇒ 00:27:55.469 Caio Velasco: Right right? And and that’s the water around you. For me. It was amazing. Like, you can bike around and you always see water around you. That was for me, for mind blowing
230 00:27:56.044 ⇒ 00:28:03.840 Caio Velasco: portugal also has its beauties. Spain, of course, has its beauties a bit more dry in Spain, at least middle and south.
231 00:28:04.688 ⇒ 00:28:07.480 Caio Velasco: But yeah, nature is involved, for sure.
232 00:28:08.180 ⇒ 00:28:08.860 Caio Velasco: Yep.
233 00:28:09.010 ⇒ 00:28:09.770 Uttam Kumaran: Nice.
234 00:28:12.090 ⇒ 00:28:14.338 Caio Velasco: Yeah, so that’s it.
235 00:28:15.560 ⇒ 00:28:16.970 Caio Velasco: The awesome.
236 00:28:16.970 ⇒ 00:28:18.260 Caio Velasco: What is next?
237 00:28:20.040 ⇒ 00:28:41.946 Uttam Kumaran: We’ll just kind of drive into. Yeah. So I think, for I’ll just kind of quickly run through some of these. So couple of things that we did make progress on. We we are sort of migrated from notion to Hubspot. Sid has been leading that initiative. We established our marketing campaign framework. And so that’s sort of running now.
238 00:28:42.360 ⇒ 00:28:56.750 Uttam Kumaran: you know, I’ll kind of talk a little bit about new team members, but we are bringing a few more folks on to get related to some of the areas that we’re starting to get more work in and we need sort of specialists. So Cdp was was one of them, including product analytics.
239 00:28:57.026 ⇒ 00:29:14.200 Uttam Kumaran: I think there’s still a couple of things that are open finishing the website redesign. I know this is something that Hannah has been leading, although there’s been a lot of competing priorities. But we are making good, I think, in the last 2 weeks in particular, and last week and a half we’ve made a lot of strides like
240 00:29:14.380 ⇒ 00:29:17.289 Uttam Kumaran: I. This stuff looks so good.
241 00:29:17.360 ⇒ 00:29:42.230 Uttam Kumaran: It’s like it’s incredible. Maybe, Hannah, you can share a little bit of it later, or you could wait until it’s whole thing is done, but looks really really good. I I we get a lot of praise for our existing website. And I think if you asked Hannah, and and if you ask me, we we look at it a lot. And there’s so much that could be way better. And people like already are like, your website looks amazing.
242 00:29:42.270 ⇒ 00:29:55.959 Uttam Kumaran: This next version it will be like, oh, you guys are like a very big company. It it looks very, very polished. We’ve come a long way. So super excited referral partners. So we’ve actually signed 2
243 00:29:56.050 ⇒ 00:30:16.970 Uttam Kumaran: referral partners for us are folks that are basically like kind of like friends of Brainforge. They’re in the field. They meet a lot of other businesses. And they. We want to leverage their network to bring us clients. And ideally, we want to compensate them in terms of a referral program. But additionally, not just saying like, Hey, whenever you feel like it send us, we have like a recurring
244 00:30:17.040 ⇒ 00:30:32.929 Uttam Kumaran: meeting with them. So every few weeks or so we meet with each of them, make sure they have our latest services. They know our clients, and we benefit from their network. And when they’re in the field and talking to people. If they can’t, for whatever they they’re selling, if they can’t service them, they can
245 00:30:32.960 ⇒ 00:30:51.360 Uttam Kumaran: pass them to us. And so we’re nicely building. Like several sales channels. We have stuff on upwork. We have Linkedin, we have our cold linkedin. We have referral partners, agency partners. So we have the events. So it’s all of these are sort of running and we’re starting to see. I think a lot of
246 00:30:51.780 ⇒ 00:31:10.850 Uttam Kumaran: you know, leads come in through many of those channels which is great. Finalizing the Q. 3 okrs. The one thing that I’m working on with rico is sort of a like what I’ll call a like stoplight framework for okrs, where you’re gonna be able to see all of them and basically see like
247 00:31:11.070 ⇒ 00:31:16.329 Uttam Kumaran: whether they’re blocked in progress or done. This is something that I’ll present in the next
248 00:31:16.676 ⇒ 00:31:32.470 Uttam Kumaran: meeting. Should be done by then. But ideally, we can review in this meeting all of our existing okrs, and at least see the status. So I’m really excited for that. And then we’re still looking for mid level project managers and project manager coordinator.
249 00:31:32.470 ⇒ 00:31:49.322 Uttam Kumaran: I think this has been a not a more difficult role to hire from, although it’s a much more crucial role, and we’re looking for folks with Pmp certification, which is like the, you know, really official certification in that world. And ideally, people that come from agency background.
250 00:31:50.210 ⇒ 00:32:12.780 Uttam Kumaran: I would say, we’re we’re. I’m meeting a lot of folks like even today. I have 2 more interviews later this evening. But I’m trying to find the right person. And so this has been kind of ongoing. And same with the Pm. Coordinator. This is someone to support the Pm team. Ideally, someone that wants to grow into a you know, certified project manager later in their career.
251 00:32:13.300 ⇒ 00:32:15.180 Uttam Kumaran: And so both of these are still open.
252 00:32:17.940 ⇒ 00:32:40.219 Uttam Kumaran: great, and so on the team side, I just wanted to kind of make a couple of announcements and introductions. So Henry, who is not here, he’s out this week. He’s actually traveling to Russia, I think today or tomorrow, he is coming in to lead everything around product analytics. And like Cdp, so basically, segment amplitude.
253 00:32:40.500 ⇒ 00:32:53.390 Uttam Kumaran: Configuring events so very excited. I think a lot of folks on this call have worked with him or are working with him currently. But I’ll probably have him introduce himself in the next time. Vashtev is here. Vashtev, do you wanna say? Hello.
254 00:32:53.390 ⇒ 00:33:16.793 Uttam Kumaran: He’s joining us as a data engineer. He! He’s he is a friend of a wish, actually, and is going to be taking on like data engineering tasks like data pipelining Dagster. You know a lot of stuff on the Snowflake side. Right now, I think if we talk about data, engineering,
255 00:33:17.460 ⇒ 00:33:21.109 Uttam Kumaran: me and Oish are really the only core data engineers, and
256 00:33:21.290 ⇒ 00:33:37.070 Uttam Kumaran: anything that gets assigned to me is is usually late. So we need lots of other folks that can come on and take data engineering related tasks. So I’m I’m very excited to to have him here. Vasha, do you want to give a brief introduction?
257 00:33:37.735 ⇒ 00:33:40.180 Uttam Kumaran: Yeah, I don’t know if he’s still on.
258 00:33:40.460 ⇒ 00:33:41.769 Uttam Kumaran: Oh, yeah, go. I got it.
259 00:33:42.230 ⇒ 00:33:52.090 Vashdev Heerani: Thank you. Good morning, everyone. So I I have around 6 year working experience in data engineering field.
260 00:33:52.380 ⇒ 00:34:01.100 Vashdev Heerani: I initially started my career as a hadoop developer, then moved to the spark and then by spark.
261 00:34:01.200 ⇒ 00:34:08.849 Vashdev Heerani: And then data breaks. And finally I ended up with the with informatica recently
262 00:34:09.150 ⇒ 00:34:14.250 Vashdev Heerani: and now, hopefully, Dbt is the next goal for me.
263 00:34:14.360 ⇒ 00:34:23.200 Vashdev Heerani: So I I am very like I’m very excited to to work on this this dimensional work.
264 00:34:24.480 ⇒ 00:34:29.879 Uttam Kumaran: Do you wanna share where, where you are in the world, and any hobbies, or anything we should know.
265 00:34:30.610 ⇒ 00:34:32.989 Vashdev Heerani: Yeah, right now I’m in Pakistan.
266 00:34:33.389 ⇒ 00:34:39.229 Vashdev Heerani: So in from Kachi like like I
267 00:34:39.480 ⇒ 00:34:57.879 Vashdev Heerani: like, I am 5 to 6 kilometer away from Avesh right now I don’t know. Avesh is in Karachi or not, but very close to to Avesh, living very close to Avesh, and my hobby is generally. Not. Not kind of I’m not
268 00:34:58.413 ⇒ 00:35:09.549 Vashdev Heerani: indoor guy kind of so and and the part time I I do watch Netflix series and movies kind of stuff.
269 00:35:10.880 ⇒ 00:35:13.250 Uttam Kumaran: How did you? How did you meet? How did you meet? Owish.
270 00:35:14.910 ⇒ 00:35:20.680 Vashdev Heerani: So we we met back in 2,007
271 00:35:20.980 ⇒ 00:35:31.859 Vashdev Heerani: 2,013. Sorry. So we were, class fellow from 2,013 to 2,017 during our bachelor.
272 00:35:34.110 ⇒ 00:35:36.409 Uttam Kumaran: Nice. Well, how was Oasha in college?
273 00:35:37.210 ⇒ 00:35:38.440 Vashdev Heerani: Yeah.
274 00:35:39.150 ⇒ 00:35:41.370 Uttam Kumaran: No! No! How. How was oas in college?
275 00:35:41.890 ⇒ 00:35:45.944 Vashdev Heerani: So. Oh, sorry, so I wish it’s kind of
276 00:35:47.530 ⇒ 00:35:55.939 Vashdev Heerani: kind of he he he was my roommate, and he kind kind of he is kind of
277 00:35:56.320 ⇒ 00:35:59.006 Vashdev Heerani: some artwork like, basically
278 00:36:00.750 ⇒ 00:36:04.190 Vashdev Heerani: add to 10 h, or even 12 HA day. And
279 00:36:04.726 ⇒ 00:36:12.070 Vashdev Heerani: after that he he topped the class, and he usually do that. He kind of do a smart work.
280 00:36:13.890 ⇒ 00:36:21.429 Uttam Kumaran: Yeah, it’s genius. Yeah, I slept. I didn’t sleep at all. And I and I got like B minuses. So I’m like, completely opposite, basically.
281 00:36:21.430 ⇒ 00:36:21.840 Vashdev Heerani: And he.
282 00:36:22.213 ⇒ 00:36:22.960 Uttam Kumaran: Thank you.
283 00:36:22.960 ⇒ 00:36:25.440 Vashdev Heerani: He he get a plus mostly.
284 00:36:26.180 ⇒ 00:36:47.585 Uttam Kumaran: Yeah, I have a friend. I we all have friends like that, who who like just show up and ace the test like very jealous. I did not do that. So I’m very, very excited to have you. I think everybody on the company you’ll you’ll get a chance to work with from the AI team to the data team. I think everybody could use some of your help. And so I’m super super excited. I think
285 00:36:47.910 ⇒ 00:37:13.825 Uttam Kumaran: we have a lot to gain from you, being here, so appreciate it. And then Sam, who I don’t believe is here. He’d be joining us on Monday is joining us as an AI lead. I’ll probably let Sam give a little bit more of a background when when he’s, you know, kind of can present himself, but really interesting background previously ran a Hair Salon Company and then left that, and was CTO of a couple of startups.
286 00:37:14.180 ⇒ 00:37:40.674 Uttam Kumaran: I believe he was also in Europe. I don’t know whether he’s in Spain or or exactly where or in Uk, and then yeah. Just has a really interesting background in mechanical engineering. CTO, like, what sort of full stack web development. So he’ll be helping me on running the AI team. And and also just starting to think about deeper architecture and developing our AI platform so really, really excited to have him
287 00:37:41.260 ⇒ 00:37:46.779 Uttam Kumaran: great. And then on recruiting, as I mentioned, we’re still kind of in the in the
288 00:37:47.030 ⇒ 00:37:50.061 Uttam Kumaran: look out for all 3 of these roles,
289 00:37:50.840 ⇒ 00:37:59.479 Uttam Kumaran: especially on the project management side. So if anyone has worked with a great project manager in their career, or or has a friend that’s they think is a good project manager.
290 00:37:59.980 ⇒ 00:38:02.320 Uttam Kumaran: you know we’re happy to talk to anybody. So
291 00:38:03.627 ⇒ 00:38:06.680 Uttam Kumaran: yeah, sales, maybe, Robert, I’ll let you give like a brief.
292 00:38:09.360 ⇒ 00:38:18.239 Uttam Kumaran: I don’t know. Minute or so on on sales stuff. I just. I just put on the new clients. But we have a lot of stuff happening. So maybe I’ll let you give a little bit of a sense of how it’s going.
293 00:38:18.410 ⇒ 00:38:29.599 Robert Tseng: Okay, yeah. Yeah. So I guess most of you probably knew that I was out last week. Kind of travel of conferencing in La, and then
294 00:38:29.660 ⇒ 00:38:52.729 Robert Tseng: visiting clients. I’m even wearing an Eden hat. I went on site last week, and yeah, I was spending some time in Denver as well. Yeah, I mean, we, this this list of new clients. These are all you know, folks that we’ve been talking about. Probably. I mean some as recent as last week. Some kind of have been in the pipeline going through different
295 00:38:52.740 ⇒ 00:39:15.169 Robert Tseng: stages in the past past month. And so yeah, I think it’s just like a culmination of a lot of the conversations we were having. And you know the start of Q. 3. That are all kind of coming through at the same time. There’s even more stuff going on that’s not really listed here. But yeah, it’s honestly been like a whirlwind of like just new deals coming in left and right. And like.
296 00:39:15.450 ⇒ 00:39:30.090 Robert Tseng: yeah, we’re having. We’re having a different problem now, trying to figure out how we’re how we’re going to be able to serve all these clients. But yeah, it’s been. It’s been really exciting. I guess Uta and I are. Gonna look at the numbers later today, I honestly don’t have any sense of like
297 00:39:30.330 ⇒ 00:39:40.450 Robert Tseng: how much new business we actually brought in. It just feels like it’s a bunch of Logos. And yeah, I’m I’m excited to to see these these take off.
298 00:39:43.440 ⇒ 00:39:47.870 Uttam Kumaran: Great. Yeah, I’m I think I’ll give. Maybe my perspective as well is like
299 00:39:48.764 ⇒ 00:39:54.350 Uttam Kumaran: we. You know, I I maybe I’ve said this before, but last year, this time, like
300 00:39:54.460 ⇒ 00:39:57.489 Uttam Kumaran: we were struggling to get like one client a month.
301 00:39:58.108 ⇒ 00:40:07.299 Uttam Kumaran: You know. So it’s maybe like one or 2 clients every quarter these days. It seems like we’re sending out a proposal every day, or basically like
302 00:40:07.710 ⇒ 00:40:33.749 Uttam Kumaran: I, we probably could. I think some of them are just getting like late on. But it’s really really amazing. And now we’re starting to see that pace catching up where people are starting to buy the product. So it kind of works in 2 ways where we’re able to not only disqualify people faster. As I mentioned before, like, we want to work with people that have budget for this that have that real interest in in doing this in a in a major way. But we’re also able to
303 00:40:33.790 ⇒ 00:40:50.620 Uttam Kumaran: take on this new capacity, now that we have support from a lot of other teams. The other only the other thing I want to shout out, is Kyle? Actually gave us a great referral to do be cars, and I Kyle we had. I had a great conversation with, I think in my presence, Felipe.
304 00:40:50.620 ⇒ 00:40:51.920 Caio Velasco: Yes, yes, perfect.
305 00:40:51.920 ⇒ 00:41:07.299 Uttam Kumaran: Yes, I had a great conversation with him. He’s interested. I think he needs us. I I actually told him to go. He’s talking to some other people. And I said, Take what I said. You go compare it to what the other folks are saying. He needs us like.
306 00:41:07.570 ⇒ 00:41:20.249 Uttam Kumaran: I think they they need us across the entire data stack. So I just want to shout out to you that that’s a great introduction. But a lot of people were involved in making that happen. We have marketing, helping with our assets.
307 00:41:20.250 ⇒ 00:41:45.400 Uttam Kumaran: We have I’m able to now cop on a meeting and just know what exactly what to say, what, how we price it, what they’re gonna get. And so we’re now can go from referral to having that conversation to hopefully closing. It’s starting to compress a lot. So I’m super super excited. We’re starting to see the compounding benefits of this the next challenge here is executing which is like
308 00:41:45.600 ⇒ 00:42:06.150 Uttam Kumaran: I I have like. I’m so excited that we’re seeing this. But the you know, the flip side to this is like we’re gonna start to get pinched as we’re starting to see a little bit on the project management side on the delivery side, which is okay, it’s a it’s a better problem to have than having no business but it. It’s gonna be the next challenge for us to figure out so
309 00:42:08.850 ⇒ 00:42:11.860 Uttam Kumaran: great operations. Rika.
310 00:42:13.070 ⇒ 00:42:27.522 Rico Rejoso: Yes, thank you. Just a few points on the operation side. Shout out to the eit for making or for integrating clock if I and operating app it’s now working, although I think there will be more changes into it in the future.
311 00:42:28.530 ⇒ 00:42:41.419 Rico Rejoso: I I think this will help us in the Pm. Side as well. When it comes to allocating hours, and also a reminder for the clock clock. If I hours we’ve been monitoring it. And I’ve also discussed this with some of the department head
312 00:42:42.027 ⇒ 00:42:56.629 Rico Rejoso: regarding to individuals not properly logging other clockify hours. So just a few just reminded to get it done. We’re almost at the end of the month. So let’s make sure that everything is listed there. Thank you. Next up.
313 00:42:58.050 ⇒ 00:42:59.840 Uttam Kumaran: Thanks. Hannah.
314 00:43:00.946 ⇒ 00:43:25.450 Hannah Wang: Yeah, I’ll keep this short, which I’m already kind of talked about how we brought on 2 referral partners. And I feel like we’re always in the works with finding other partners to work with. So there’s like a vendor and agency partners that we’re talking to for design. Yeah, we’re trying to crank out a lot of case studies that the AI team is doing. So if you have a AI team, if you have cool things, please
315 00:43:25.560 ⇒ 00:43:26.765 Hannah Wang: tell me
316 00:43:28.120 ⇒ 00:43:53.639 Hannah Wang: And then the homepage I guess there’s like a v 0 point 1 or like before v, 2. That’s currently live right now. So if you want to check out our website, there’s like a new hero section so that’s like a sneak peek. And then campaigns, I mean, which I’m already mentioned. But yeah, we have a new kind of marketing campaign. Brief template that we’re gonna start using for all of our campaigns. So
317 00:43:54.200 ⇒ 00:43:55.560 Hannah Wang: yeah, exciting.
318 00:43:58.160 ⇒ 00:43:59.370 Uttam Kumaran: Great amber.
319 00:44:05.030 ⇒ 00:44:16.309 Amber Lin: For my side. Not too much updates on the Pmo, we’re continuing to refine the processes. And as we identified this, this
320 00:44:16.690 ⇒ 00:44:18.940 Amber Lin: sprint. The past 2 weeks I’ve been a bit.
321 00:44:19.440 ⇒ 00:44:40.760 Amber Lin: And so we’re finding ways to right size it to our organization rice. So you might see a bit of a change in rituals. But if any of you feel like we have too many meetings. Meetings are not helpful, or we have 2 little meetings that you have no idea what’s going on. Please feel free.
322 00:44:40.880 ⇒ 00:44:52.969 Amber Lin: And then, we’ll definitely change up our processes according to your feedback, because every team just has 3 or 4 people. So your experience really matters. And just tell
323 00:44:53.320 ⇒ 00:44:55.789 Amber Lin: me if you want to change anything.
324 00:44:58.890 ⇒ 00:44:59.490 Uttam Kumaran: Great
325 00:45:01.839 ⇒ 00:45:10.530 Uttam Kumaran: cool. I wanted to, maybe just give a little bit of an update on like how stuff is going on the platform side. So let me just share
326 00:45:11.470 ⇒ 00:45:12.609 Uttam Kumaran: this.
327 00:45:13.880 ⇒ 00:45:32.340 Uttam Kumaran: so everyone here, some of you may or may not be familiar like, this is sort of the platform that we’re developing basically to serve us internally. I’m constantly trying to use it and break it and find new things that we can implement to help our team deliver faster but also take off
328 00:45:32.340 ⇒ 00:45:45.990 Uttam Kumaran: boring, busy work. One of the things that we did is you’re gonna be able to see, we’re starting to add clients here on the left side. The operations team will start to own this, but you can actually go here and add clients
329 00:45:46.268 ⇒ 00:46:15.839 Uttam Kumaran: directly now, and you can just go add them so Rico will be sort of handling this as part of our new client onboarding process. Another thing is, we have several agents here. These are sort of equivalent to just like having a set prompt. So things like our design assistant executive coach. These are things that I’m using in chat. Gpt, basically as projects that I’m starting to use here in the platform. One of the things that we’re going to be working on as part of this is actually, you’re going to be able to see conversations that people are having
330 00:46:16.137 ⇒ 00:46:38.159 Uttam Kumaran: with the agent sort of in a sidebar. So we’ll be adding that over time. Also, in the AI tool section we have a linear tickets agent. So I would highly encourage anyone who’s tasked to create tickets or is on the Pm team to be using this you can paste in transcripts notes. You can just write into this, and it will actually help you generate the tickets.
331 00:46:38.478 ⇒ 00:46:53.429 Uttam Kumaran: And give an easy interface to go, actually create them in linear, which is, you know, a huge win. One of the other things that’s now available is marketing assets. So particularly probably for everybody in the sales team. Robert Sid.
332 00:46:53.746 ⇒ 00:47:07.300 Uttam Kumaran: Hannah, this is now a list of all of our map marketing assets that you can get very quickly. So if you’re in a if you’re in a conversation, or if you have to draft an email, you’re like, Hey, I need. I want to get a case study really quickly. You just log in.
333 00:47:07.690 ⇒ 00:47:15.449 Uttam Kumaran: grab exactly the one you need. We’re gonna work on changing the names and making this. But it’s like I use this every day.
334 00:47:16.250 ⇒ 00:47:22.319 Uttam Kumaran: to see to get case studies sent to people. And we’re also starting to add the hits here. So
335 00:47:22.720 ⇒ 00:47:30.025 Uttam Kumaran: as people start to access these, we’re gonna start to be able to see how many people are which documents are the most popular.
336 00:47:30.480 ⇒ 00:47:37.929 Uttam Kumaran: this is basically like what comes out of the box for many paid document hosting things. So we saved ourselves on other like
337 00:47:38.270 ⇒ 00:47:54.759 Uttam Kumaran: 30 bucks, a user for docusign, for docusign or doc box, or whatever. So I’m so I’m really excited. There. Again. I’ll just highlight that you can go into any of the clients here and see all of the meetings associated with it. Additionally, once you click into a meeting.
338 00:47:54.760 ⇒ 00:48:09.890 Uttam Kumaran: you can get things like the transcript which you can copy and paste into Chat Gpt, or wherever you can create linear tickets directly you can create email summaries. So this is again for a Pm or sales team, you can come in. Select the type of email
339 00:48:10.318 ⇒ 00:48:30.030 Uttam Kumaran: and generate this. So email sending is a really common thing that that has to happen as part of things like this and also creating slack summaries. So you can generate those as well. We’re also going to be updating the video player. So it’ll almost be like a Youtube kind of interface where you can do speed, fast, forward hopefully, see chapters or something.
340 00:48:31.380 ⇒ 00:48:35.519 Uttam Kumaran: And the last thing I wanted to share is
341 00:48:36.085 ⇒ 00:48:42.010 Uttam Kumaran: sort of our work. On the lead side. So this is.
342 00:48:42.818 ⇒ 00:48:45.329 Uttam Kumaran: Let me try to share this.
343 00:48:47.760 ⇒ 00:48:53.560 Uttam Kumaran: This is sort of what leads are gonna look like in the platform soon.
344 00:48:53.580 ⇒ 00:48:59.270 Uttam Kumaran: So for anyone on the sales team you’ll be able to see open Hubspot deals directly in the platform.
345 00:48:59.571 ⇒ 00:49:22.328 Uttam Kumaran: Not that we’re gonna be using this to input any information. This is just display of that but what the power of this is we’re gonna start to be able to link all the Zoom Meetings, so you’ll be able to see all the meetings associated with a deal and be able to play them rewatch them. Use AI summaries and again nicely. These are all in the same place as as our other things.
346 00:49:22.620 ⇒ 00:49:39.459 Uttam Kumaran: And so we’ll add, we’ll be able to quickly add things like generate. Follow up emails. Stuff like that. Again, we we ideally won’t be. This is not going to be a source of truth for any information. Anything will either come from Hubspot or get synced back to Hubspot. But I think one helpful view.
347 00:49:40.840 ⇒ 00:50:06.370 Uttam Kumaran: The only other thing is, we’re starting in the in slack. You’ll start to see AI channels with the Pm. Team, the Ops team, the design team. I know there’s already one with the engineering team. So as people have ideas for AI please use the AI show and tell channel or send notes. I know a lot of people are trying to use it, and we have opportunity to make it better. It’s getting there again. This is like a thing that the team and I are working.
348 00:50:06.460 ⇒ 00:50:34.970 Uttam Kumaran: Of course, on the side like we we are. Most of our time is going to client work, but it’s something that’s been really really helpful, so highly. Encourage everybody to to use this but at minimum try to use chat. Gpt. Try to use perplexity. To ask questions. And see if you can use AI to answer things. It’s good. And then, of course, send those results, even if you’re not able to solve your problem, because I think there’s a lot of different ways to use AI that people can help with. So
349 00:50:36.167 ⇒ 00:50:50.112 Uttam Kumaran: the last thing is, we’re also going to be adding, departments. This should come out probably early next week. You’ll be able to see sales Ops finance, legal recruiting all within the platform.
350 00:50:51.130 ⇒ 00:51:02.619 Uttam Kumaran: so it’ll be in a very similar format to just our clients. And that’ll kind of round out basically the classification for all of our meetings. The last piece I don’t. I think it may be out
351 00:51:02.770 ⇒ 00:51:04.560 Uttam Kumaran: is.
352 00:51:04.870 ⇒ 00:51:14.220 Uttam Kumaran: if you you can actually change the team. So if this is misclassified. You can go in here and actually just assign it to a new team. So that’s something that’s new.
353 00:51:17.480 ⇒ 00:51:20.805 Uttam Kumaran: Yeah, I think that’s it.
354 00:51:22.090 ⇒ 00:51:31.590 Uttam Kumaran: I guess maybe we can move to shout outs. If anyone has any shout outs, they want to do, or any questions for me that can answer in the last, you know. Few minutes.
355 00:51:46.308 ⇒ 00:51:50.800 Uttam Kumaran: I guess I wanted to give a shout out to Alright, go ahead! Go ahead!
356 00:51:51.830 ⇒ 00:51:54.899 Amber Lin: No, you go. I’m gathering my thoughts.
357 00:51:55.850 ⇒ 00:52:16.589 Uttam Kumaran: Okay, yeah. I wanted to give a shout out to Rico, rico has been incredibly helpful. Is working through flooding in. That’s affecting him and and his family, and and just continuing to help us out. And I think it’s it’s really admirable. But also, Rico, make sure like stuff is
358 00:52:16.630 ⇒ 00:52:39.619 Uttam Kumaran: fine, and and you and your your folks are safe. It’s been incredibly helpful Rico has helped not only to set up new sops for clients and team members. He’s helping with finance. He’s helping with Pm team. It’s been such a step change in our operations. To have him on the team, and so just want to thank him. I work with him very closely.
359 00:52:39.978 ⇒ 00:52:49.661 Uttam Kumaran: He knows that I I ping him almost every 45 min or so. And it’s it’s been tremendous having him for for at least my
360 00:52:50.040 ⇒ 00:52:53.440 Uttam Kumaran: my workflows and and needs. So thanks, Rico.
361 00:52:58.920 ⇒ 00:53:00.000 Rico Rejoso: Yeah. Happy. To help.
362 00:53:01.880 ⇒ 00:53:10.080 Hannah Wang: Well, I also wanted to shout out Rico, too. I feel like he’s taking on the initiative of pming the marketing team.
363 00:53:11.930 ⇒ 00:53:27.999 Hannah Wang: And that’s been really helpful. Just because, yeah, our board is actually manageable. Now, I think it’s not just like a bunch of tickets that are not groomed, which makes me feel better. And I like having that organized and we like have more structure. So thank you, Rico.
364 00:53:41.190 ⇒ 00:53:44.569 Uttam Kumaran: Any other shout outs for this week.
365 00:53:46.833 ⇒ 00:53:50.079 Amber Lin: Let’s see, I think on my team
366 00:53:51.880 ⇒ 00:53:56.269 Amber Lin: the ABC side, I want to thank you guys for developing
367 00:53:58.580 ⇒ 00:54:13.239 Amber Lin: fast and very reliable. My AI engineers on the Apc team. It’s been. It’s just been great working together. Like most of the stuff we figure out a way to do it, and then
368 00:54:14.420 ⇒ 00:54:20.130 Amber Lin: I think for what was it?
369 00:54:22.280 ⇒ 00:54:23.190 Amber Lin: Oh.
370 00:54:24.320 ⇒ 00:54:33.680 Amber Lin: yes, and then for my other teams. Oh, there we go! Thank you for your time for providing feedback on how to reduce hours
371 00:54:33.830 ⇒ 00:54:44.840 Amber Lin: spent. Because I was very, very, very stressed this week. So it’s really nice to hear. Okay, here’s at least step one into to approaching that problem.
372 00:54:46.500 ⇒ 00:54:51.719 Amber Lin: Since also, since we were, we didn’t meet last week.
373 00:54:52.396 ⇒ 00:55:08.280 Amber Lin: Thank you for Robert to coming in person. Thanks for the meal and thanks for career advice that was really nice. And also. Thank you, Hannah, for emotional support this week.
374 00:55:10.040 ⇒ 00:55:11.609 Amber Lin: That’s all for me.
375 00:55:15.180 ⇒ 00:55:19.185 Rico Rejoso: Yeah, on my, yeah. I also wanted to shout out
376 00:55:20.322 ⇒ 00:55:24.999 Rico Rejoso: shout out to the AI team for again for the operating clock. If I think
377 00:55:25.500 ⇒ 00:55:52.609 Rico Rejoso: it’s a big help for us, since we’ve been blocked on that end for like 3 weeks, I guess. Yeah. And finally, it’s working, although there will be I mean I will be asking for some assistance and other ends as well. So I’ll talk to them about it, and also we found. Thank you so much for the guidance as well. All throughout. So I mean, I’m new. So everything and every support from each department head was very helpful to me. Thank you, guys.
378 00:55:56.480 ⇒ 00:55:57.130 Uttam Kumaran: Great.
379 00:55:57.820 ⇒ 00:56:06.740 Uttam Kumaran: Okay? If nothing else, then we can sign off 5 min early today. I. My favorite segment was the superhero job segment. So that was really great.
380 00:56:07.620 ⇒ 00:56:12.669 Uttam Kumaran: A lot of interior design interests. So yeah, I don’t know. Maybe we should
381 00:56:13.360 ⇒ 00:56:23.822 Uttam Kumaran: take advantage of that somehow, or I should. I should find us an interior design client something like that, I mean, we were trying to work with this company.
382 00:56:26.650 ⇒ 00:56:29.330 Uttam Kumaran: And look if if anyone wants to
383 00:56:29.450 ⇒ 00:56:36.070 Uttam Kumaran: help sell into them. We have an in Kathy Kuo home. I don’t know. I guess they’re like very, very famous.
384 00:56:37.930 ⇒ 00:56:49.560 Uttam Kumaran: but yeah, we got an intro to them. They kind of ghosted us. I don’t know if if people are interested and we should go after it again. I could think about some, some angle. But yeah.
385 00:56:56.610 ⇒ 00:57:00.482 Uttam Kumaran: yeah, we could do a campaign around interior design clients.
386 00:57:00.870 ⇒ 00:57:01.410 Amber Lin: Hmm.
387 00:57:03.370 ⇒ 00:57:04.160 Uttam Kumaran: Okay.
388 00:57:04.590 ⇒ 00:57:13.630 Uttam Kumaran: great. Well, thank you, everybody. I’ll be in slack. Please message me if you need anything. Thank you, Kyle, for hosting, and you know, for making this meeting fun.
389 00:57:14.832 ⇒ 00:57:17.910 Uttam Kumaran: And yeah, enjoy the weekend. Everybody.
390 00:57:18.280 ⇒ 00:57:18.870 Caio Velasco: Thank you.
391 00:57:18.870 ⇒ 00:57:20.729 Rico Rejoso: You, too. Bye, thanks, guys.
392 00:57:20.730 ⇒ 00:57:21.670 Hannah Wang: Thank you.
393 00:57:21.670 ⇒ 00:57:22.110 Amber Lin: Hey!
394 00:57:22.110 ⇒ 00:57:22.800 Uttam Kumaran: Bye.