Meeting Title: Demilade x Amber | CatchUP! Date: 2025-03-26 Meeting participants: Demilade Agboola, Amber Lin
WEBVTT
1 00:13:20.540 ⇒ 00:13:22.390 Amber Lin: Hello!
2 00:13:26.090 ⇒ 00:13:36.243 Amber Lin: No, I was I had a meeting with Utam because me and Miguel was meeting Miguel’s, the engineering lead on the AI team, and then
3 00:13:36.810 ⇒ 00:13:45.740 Amber Lin: oh! And then came on, and he was like, I don’t see no tickets. I don’t see no due dates. I don’t see no assignments. I don’t see no requirements. I’m like, I don’t know.
4 00:13:46.520 ⇒ 00:13:55.763 Amber Lin: He was like, What are you gonna have Friday? It’s already Wednesday. I don’t see anything for Friday. I was like, no, we have this. So we have this. But it was like, Oh, my goodness!
5 00:13:59.720 ⇒ 00:14:04.000 Amber Lin: So it it it took a it took a little while, because we’re
6 00:14:04.140 ⇒ 00:14:09.159 Amber Lin: on certain things we’re a little behind. So we’re catching up. He’s giving guidance
7 00:14:10.250 ⇒ 00:14:11.290 Demilade Agboola: Fair enough, fair enough.
8 00:14:11.770 ⇒ 00:14:15.400 Amber Lin: And this is the is there still a little bruise here
9 00:14:15.400 ⇒ 00:14:17.729 Demilade Agboola: Oh, okay, it’s calm down quite a bit.
10 00:14:17.730 ⇒ 00:14:22.744 Amber Lin: Yeah. And I’m I look a little swollen, but I look like a normal person. So it’s
11 00:14:23.040 ⇒ 00:14:23.869 Demilade Agboola: That’s okay.
12 00:14:23.870 ⇒ 00:14:25.310 Amber Lin: This side’s a little bigger.
13 00:14:25.470 ⇒ 00:14:30.220 Demilade Agboola: Yeah, I should get. I have like 5 teeth. I need to take out this year
14 00:14:30.760 ⇒ 00:14:34.039 Amber Lin: What! How do you have? 5 wisdom, teeth.
15 00:14:34.040 ⇒ 00:14:39.310 Demilade Agboola: So I have 4 wisdom teeth, and then I have one. So up, and I have 30. 33
16 00:14:40.500 ⇒ 00:14:41.880 Amber Lin: Oh!
17 00:14:42.040 ⇒ 00:14:49.680 Demilade Agboola: Yeah, so, but the extra one is in a weird location. So instead of it, like, it doesn’t have its own spots, it kind of
18 00:14:49.680 ⇒ 00:14:51.490 Amber Lin: So it’s like behind the teeth
19 00:14:52.170 ⇒ 00:15:01.430 Demilade Agboola: Yeah, exactly. It’s kind of like. So there’s a section where I have like 2 teeth. And then the the other one is just like kind of in between them. But it’s kind of like pushing.
20 00:15:02.320 ⇒ 00:15:03.380 Demilade Agboola: Yeah. So
21 00:15:03.930 ⇒ 00:15:06.130 Amber Lin: I didn’t know that was possible.
22 00:15:06.860 ⇒ 00:15:08.660 Demilade Agboola: Glad I could make your day, you know.
23 00:15:09.130 ⇒ 00:15:09.780 Amber Lin: Medical
24 00:15:09.780 ⇒ 00:15:11.025 Demilade Agboola: Discoveries.
25 00:15:13.390 ⇒ 00:15:19.139 Amber Lin: That’s so. That’s so cool, because I know a lot of creatures like some animals just have 2 lines of teeth.
26 00:15:19.300 ⇒ 00:15:22.130 Amber Lin: But we only one line. That’s interesting.
27 00:15:22.440 ⇒ 00:15:24.399 Demilade Agboola: Where are you based right now?
28 00:15:25.543 ⇒ 00:15:34.339 Demilade Agboola: So I’m currently in Malta. But I tend to go back and forth between Malta and the Us. Because my girlfriend lives there. She lives in Minnesota.
29 00:15:34.480 ⇒ 00:15:40.180 Demilade Agboola: so I should even be in the Us. In May, like
30 00:15:40.180 ⇒ 00:15:42.390 Amber Lin: Moving? Or are you visiting.
31 00:15:42.390 ⇒ 00:15:46.490 Demilade Agboola: I’m done visiting. I like I visit, for
32 00:15:46.990 ⇒ 00:15:52.439 Demilade Agboola: I visit about like I spent about 5 months in the in the Us. I’m still trying to work on my like.
33 00:15:53.850 ⇒ 00:15:54.670 Amber Lin: Visa
34 00:15:54.670 ⇒ 00:16:01.259 Demilade Agboola: Yeah, the permanent like, visa sort of process. But for now it’s basically just like visiting.
35 00:16:01.855 ⇒ 00:16:09.280 Demilade Agboola: So I but this is gonna be a short trip. I have some stuff to do back here at the end of me, so I kind of.
36 00:16:09.430 ⇒ 00:16:13.650 Demilade Agboola: But my girlfriend’s graduation is on on the 16th of May. So I want to be around
37 00:16:13.670 ⇒ 00:16:23.059 Amber Lin: You’re welcome, I see, I see. Oh, she’s just gonna graduate. Is she doing like her bachelor’s or masters?
38 00:16:23.060 ⇒ 00:16:29.649 Demilade Agboola: A master’s, so she she’s doing a master’s in social work, so she’s a she’s a strong one. She’s a tough one.
39 00:16:29.980 ⇒ 00:16:42.479 Amber Lin: That’s so cool. I mean social work, especially in the Us. Like here, a lot of the social work deals with people with a lot of mental health problems and homelessness issues. So it’s really, it’s tough space to work in
40 00:16:42.640 ⇒ 00:16:47.520 Demilade Agboola: Yeah, it is actually. And like her long. Her long term plan is to be a therapist. So
41 00:16:49.060 ⇒ 00:16:51.780 Amber Lin: Is she from Malta as well
42 00:16:51.780 ⇒ 00:16:57.200 Demilade Agboola: No, no, she’s she’s she’s well. She’s originally from Nigeria, but she’s American.
43 00:16:57.580 ⇒ 00:16:59.280 Amber Lin: How did you guys meet
44 00:16:59.280 ⇒ 00:17:00.310 Demilade Agboola: Online
45 00:17:00.310 ⇒ 00:17:01.040 Amber Lin: Ultimate.
46 00:17:01.360 ⇒ 00:17:05.409 Demilade Agboola: Like. So, to be fair, I mean, I only moved to Malta in 2023
47 00:17:05.819 ⇒ 00:17:06.589 Amber Lin: Oh!
48 00:17:06.589 ⇒ 00:17:09.349 Demilade Agboola: To be Nigeria, you know, prior to that
49 00:17:10.082 ⇒ 00:17:11.409 Amber Lin: So we met
50 00:17:11.589 ⇒ 00:17:17.129 Demilade Agboola: We met online. We met also met Nigeria cause she came to Nigeria and we met, and
51 00:17:17.679 ⇒ 00:17:22.359 Demilade Agboola: I guess last time moved on like, you know, like, let’s make this work. And so
52 00:17:22.640 ⇒ 00:17:45.779 Amber Lin: Oh, that’s so cool that you guys do long distance because me and my girlfriend also we met on hinge. It was. It’s her 1st date. I had a lot of days already, like I had a plan I know how to like when I I had a filtering plan of like I text them. I was like, here’s my number, either text me or either call me, or we meet up in person. That’s whoever responds.
53 00:17:45.780 ⇒ 00:17:52.730 Amber Lin: It’s in my text. So it’s a funnel like, and then text, and we meet up, and I see how they are. But
54 00:17:52.730 ⇒ 00:17:58.420 Demilade Agboola: You know, it’d be really cool if you have like a flow charts where you have like your conversation
55 00:17:58.960 ⇒ 00:18:07.920 Amber Lin: Ugly removed from list, if okay, but a douche bag removed from list.
56 00:18:09.430 ⇒ 00:18:18.590 Amber Lin: But yeah, it was my girlfriend’s 1st date. So 1st date on hinge. So we met online. But long distance is so hard for me
57 00:18:19.450 ⇒ 00:18:26.240 Demilade Agboola: I mean to be fair. I don’t think it’s easy for anyone to be honest. I think most ideal situation is when you’re with your person.
58 00:18:26.697 ⇒ 00:18:32.100 Demilade Agboola: I think it’s at least our phase now is much better in the sense that, like
59 00:18:32.240 ⇒ 00:18:38.070 Demilade Agboola: we do see, like I was literally around from December till about February.
60 00:18:38.479 ⇒ 00:18:45.959 Demilade Agboola: I’ll be back in May, and then I know we’re good. I would also be back in July, but then we want to go to.
61 00:18:46.120 ⇒ 00:18:49.609 Demilade Agboola: I got the Uk or Luxembourg to meet my family like my siblings.
62 00:18:49.610 ⇒ 00:18:50.140 Amber Lin: Oh!
63 00:18:50.868 ⇒ 00:18:54.700 Demilade Agboola: So like we do see often, you know, it’s not every
64 00:18:54.700 ⇒ 00:18:55.720 Amber Lin: I see.
65 00:18:55.720 ⇒ 00:19:00.150 Demilade Agboola: And even like last year out, like last year, I was basically in the Us. From
66 00:19:01.510 ⇒ 00:19:03.919 Demilade Agboola: about what the paradigms are on, for
67 00:19:04.140 ⇒ 00:19:08.480 Demilade Agboola: I believe I was around February, March, I came in June.
68 00:19:08.950 ⇒ 00:19:10.780 Demilade Agboola: I left in September.
69 00:19:11.620 ⇒ 00:19:14.370 Demilade Agboola: I came back in like December, so like it’s
70 00:19:15.480 ⇒ 00:19:21.679 Demilade Agboola: I’m around, just, you know. It’s not as it’s not like every day, but like I mean, you take what you get.
71 00:19:23.380 ⇒ 00:19:28.727 Demilade Agboola: It’s way different from like when next time I gonna see and no one has an answer to that. That is the worst
72 00:19:28.960 ⇒ 00:19:51.060 Amber Lin: No, I when we’re long distance, even just daily I asked my girlfriend, where are we gonna call? When are we gonna call? And she. It doesn’t have a good sense of time, so she can’t tell me when we’re gonna call, and I get so frustrated so I can’t believe it like long distance. And like, When are we gonna see each other? When are we gonna see each other? And the answer is just, I don’t know. That is
73 00:19:51.400 ⇒ 00:19:53.430 Amber Lin: horrible for me.
74 00:19:54.680 ⇒ 00:19:57.480 Demilade Agboola: Yeah, that is terrible. That’s a horrible place to be in
75 00:19:57.750 ⇒ 00:20:00.689 Amber Lin: I know. Wait! When did you join Brain Forge?
76 00:20:01.490 ⇒ 00:20:02.450 Amber Lin: Oh, good luck!
77 00:20:03.290 ⇒ 00:20:06.790 Demilade Agboola: Oh, no, no, no! This is literally my 1st month, so
78 00:20:08.080 ⇒ 00:20:08.600 Amber Lin: What?
79 00:20:08.600 ⇒ 00:20:11.370 Demilade Agboola: My yeah, my start date was on the
80 00:20:11.750 ⇒ 00:20:15.429 Demilade Agboola: 10, th I believe, or something like this is like the second
81 00:20:15.430 ⇒ 00:20:21.820 Amber Lin: March March 10.th I think we really started like in about the same time I started March 6th
82 00:20:22.790 ⇒ 00:20:23.514 Demilade Agboola: Yeah.
83 00:20:24.680 ⇒ 00:20:30.800 Demilade Agboola: I mean, I was hopping into meetings prior just to like, get the feel of the company. My official starting
84 00:20:32.310 ⇒ 00:20:34.300 Amber Lin: I see? Wait.
85 00:20:34.540 ⇒ 00:20:44.280 Amber Lin: So what do you do for them? Do? Do you do like data modeling, or more on the analysis side?
86 00:20:46.070 ⇒ 00:20:50.959 Demilade Agboola: So I mean, ideally, it’s more like data modeling.
87 00:20:51.260 ⇒ 00:20:54.810 Demilade Agboola: Oh, but cause I have like
88 00:20:55.940 ⇒ 00:20:59.589 Demilade Agboola: experience across the data spectrum. In that sense.
89 00:21:00.461 ⇒ 00:21:04.890 Demilade Agboola: It allows me to be able to like, hop into like dashboards and also figure out what’s kind of wrong with them.
90 00:21:04.890 ⇒ 00:21:05.360 Amber Lin: As well
91 00:21:05.360 ⇒ 00:21:13.129 Demilade Agboola: Couple of projects like like on the 18 project. There’s times when I would have to just figure out like what’s wrong and why our numbers are normal.
92 00:21:13.130 ⇒ 00:21:13.530 Amber Lin: Cheers.
93 00:21:13.530 ⇒ 00:21:15.849 Demilade Agboola: That allows me to troubleshoot that as well
94 00:21:15.850 ⇒ 00:21:16.300 Amber Lin: No.
95 00:21:16.960 ⇒ 00:21:21.290 Demilade Agboola: My main strength. And what I like to focus on is like more of the data modeling
96 00:21:22.120 ⇒ 00:21:50.520 Amber Lin: Oh, I see. Yeah, it was like, after I started working in this company, it really showed me, okay, this whole spectrum of the data stuff, because to me, mostly, I was mostly in the analysis and visualization. So for me, the pipeline was really short because you get the data. And then you visualize it like. And then, now I’m like, Oh, there’s models, and there’s like different applications and so many files. So I was like, Oh, wow!
97 00:21:50.700 ⇒ 00:21:54.261 Amber Lin: That’s why that’s why people get paid
98 00:21:55.160 ⇒ 00:21:59.130 Demilade Agboola: Yeah, there is a lot you can. It can sometimes be like overwhelming in terms of like.
99 00:21:59.750 ⇒ 00:22:02.680 Demilade Agboola: there’s so many sources. There’s so much logic
100 00:22:03.980 ⇒ 00:22:08.390 Demilade Agboola: And sometimes our logic is not properly defined or clearly defined. So it’s just like.
101 00:22:09.440 ⇒ 00:22:14.735 Demilade Agboola: okay, so what do you define as a session? Or what is your revenue? How do you define?
102 00:22:16.740 ⇒ 00:22:21.249 Demilade Agboola: just like different things like a customer, a user? What’s when you say daily active user?
103 00:22:21.380 ⇒ 00:22:41.609 Demilade Agboola: What does Active mean? What does what does daily mean like? Are you seeing over the last 24 h from the start point of the dashboard? Are you seeing last 24 h like just generally. What time zone are you using, like all the kind of things you have to start like factoring that in before you like, you know, can start to define metrics for the users or for the end users
104 00:22:42.360 ⇒ 00:22:45.550 Amber Lin: I see that’s really that’s really interesting.
105 00:22:46.000 ⇒ 00:22:47.359 Demilade Agboola: Yeah, yeah.
106 00:22:47.770 ⇒ 00:22:54.489 Amber Lin: How long have you been working? Cause I think you’re very experienced, but I I don’t know how long you’ve been working
107 00:22:55.455 ⇒ 00:23:00.650 Demilade Agboola: So I have been working for 6 years.
108 00:23:01.350 ⇒ 00:23:02.690 Demilade Agboola: They’re about
109 00:23:03.920 ⇒ 00:23:07.199 Demilade Agboola: But like in a lot of it, it was. It was like
110 00:23:08.110 ⇒ 00:23:15.620 Demilade Agboola: very high intensity work. So my 1st job, I worked 2 years in a startup where you basically, it’s like all hands. And I can also see a freshly
111 00:23:15.620 ⇒ 00:23:21.510 Amber Lin: Yeah, you. That’s why you do every you know how to do everything, because they don’t have anyone for anything else.
112 00:23:21.640 ⇒ 00:23:33.839 Amber Lin: Yes, that was my 1st hired. My second was also a data consulting company where it’s supposed to log again. They’re working on 2, 3 projects, quick turnarounds, fast delivery. What is like needed.
113 00:23:34.620 ⇒ 00:23:46.410 Amber Lin: Okay, what’s the difference between what do you think is the difference between data consultancy and like the startup? Because I I know we are kind of a data consultancy, but I get confused
114 00:23:46.650 ⇒ 00:24:02.740 Demilade Agboola: So a startup. Ideally, you’re like usually in the in the broad sense, is just like a business that is in its early missionaries that is tackling whatever problem you’re trying to solve. So it doesn’t be it based startup.
115 00:24:03.030 ⇒ 00:24:04.970 Demilade Agboola: But not all startups are different. Consulting
116 00:24:05.270 ⇒ 00:24:11.710 Amber Lin: Oh, so the startups, like you mean, mostly, for, like like our clients. So you were working on their side
117 00:24:11.710 ⇒ 00:24:23.589 Demilade Agboola: No? No? Well, yes, but I was working for an agri tech company but I wasn’t working with, so they didn’t have like my very 1st job they didn’t have like
118 00:24:24.080 ⇒ 00:24:26.680 Demilade Agboola: it was in Nigeria. They were trying to figure things out
119 00:24:26.980 ⇒ 00:24:33.480 Amber Lin: And they don’t need to make sense of their data. So I just wanted someone who could come in and make things run
120 00:24:34.904 ⇒ 00:24:38.299 Demilade Agboola: So I was literally their in-house data person.
121 00:24:38.990 ⇒ 00:24:39.350 Amber Lin: Hmm.
122 00:24:39.350 ⇒ 00:24:39.910 Demilade Agboola: Yeah.
123 00:24:40.590 ⇒ 00:24:58.480 Demilade Agboola: I, because of how startups work, you can. You kind of do a lot of things as well. So I also from the fact that they were an agri-tech company because they were trying to like get yield off the smallholder farmers in Nigeria, sell them to like and be like a bridge to prevent like wastage
124 00:24:59.250 ⇒ 00:25:00.359 Amber Lin: Oh no!
125 00:25:00.360 ⇒ 00:25:11.869 Demilade Agboola: And then because the farmers also didn’t have like banking applications. So they didn’t have credit history. So they set up a Fintech to handle that. So I moved laterally to the Fintech, and I started running the
126 00:25:11.870 ⇒ 00:25:35.030 Amber Lin: Cool, you know, that is actually because before I worked at Brainforge oh, you also have 5 min, so I’ll make it quick before I worked at Brainforge. I was volunteering at this organization student Pm, for them. And they’re also doing argy tech before Latin America. So exactly like, how are the farmers like. They’re connecting the farmers to the investors or buyers in North America.
127 00:25:35.030 ⇒ 00:25:45.819 Amber Lin: I was like, oh, what crops are doing good and handling all that data, and then they also want financial education. So, hearing what you said, I feel like they stole that idea
128 00:25:46.000 ⇒ 00:25:49.380 Demilade Agboola: Put it on lots of American farmers.
129 00:25:49.380 ⇒ 00:25:51.463 Demilade Agboola: I mean, like they see.
130 00:25:52.090 ⇒ 00:26:03.830 Demilade Agboola: the intention is flattery. So like I feel like I. To be honest, I think with businesses it’s really not about the ideas per se like, I mean, obviously have a good idea. But you can have a good idea. And it’s half term, yeah.
131 00:26:03.830 ⇒ 00:26:04.440 Amber Lin: Yeah.
132 00:26:04.440 ⇒ 00:26:06.850 Demilade Agboola: And no one ever gets to use that product. So
133 00:26:06.850 ⇒ 00:26:13.386 Amber Lin: That’s true. Wait! What is the startup called? I’m gonna show them that someone has already done it.
134 00:26:13.980 ⇒ 00:26:15.350 Demilade Agboola: It’s called forever grief.
135 00:26:15.660 ⇒ 00:26:16.380 Amber Lin: Huh!
136 00:26:16.380 ⇒ 00:26:17.970 Demilade Agboola: It’s called Thrive a Greek
137 00:26:18.930 ⇒ 00:26:20.970 Amber Lin: Thrive, I agree.
138 00:26:22.720 ⇒ 00:26:24.510 Amber Lin: Let’s see.
139 00:26:24.970 ⇒ 00:26:32.729 Amber Lin: Oh, the yeah, the one in Nigeria. Okay, let me go. I’ll go. Look into that, and I will.
140 00:26:32.850 ⇒ 00:26:38.559 Amber Lin: I will send something. This is essentially what they want to do. This is so funny
141 00:26:38.560 ⇒ 00:26:38.970 Demilade Agboola: So.
142 00:26:38.970 ⇒ 00:26:46.344 Amber Lin: This is exactly what they want to do. And I and I told them, Okay, when I have time I’ll make an Mvp. For them. I’ll just send them this.
143 00:26:47.920 ⇒ 00:27:00.260 Amber Lin: And the point is that they’re all volunteers. So I don’t even know how they’re ever gonna get to that. They only have data people, and they don’t have any developers. So they don’t even have a website. So it’s a mess
144 00:27:00.560 ⇒ 00:27:15.780 Demilade Agboola: Yeah, I think, yeah, I think the hard part would be co, I think in a way, I don’t know. It depends. It depends on the level of the farmers like I know in Nigeria they didn’t really need an app. They need an app for different things, but they need an app for the farmers per se, because
145 00:27:16.120 ⇒ 00:27:17.359 Amber Lin: People don’t have phones.
146 00:27:17.360 ⇒ 00:27:19.048 Amber Lin: Yeah, they didn’t really have phones.
147 00:27:20.190 ⇒ 00:27:26.679 Demilade Agboola: And it was largely just a function of them being able to get connections with these
148 00:27:27.620 ⇒ 00:27:37.360 Demilade Agboola: big big offtakers, that’s what they call them. Once you have those connections with offtakers you’re planning. How do we bundle all the
149 00:27:38.350 ⇒ 00:27:38.800 Amber Lin: Oh!
150 00:27:38.800 ⇒ 00:27:48.679 Demilade Agboola: Like. So it’s a lot of logistics, a lot of like, okay, when exactly, are the harvest going to come? How do we bundle everything. So it’s a lot. It’s logistics heavy.
151 00:27:50.010 ⇒ 00:27:50.960 Amber Lin: Oh, wow!
152 00:27:50.960 ⇒ 00:27:57.139 Demilade Agboola: Comes in. If you’re trying to do things like you’re trying to raise capital. So maybe you might want to make it open to
153 00:27:57.501 ⇒ 00:28:04.040 Demilade Agboola: the public, which is what they did for a period of time, but they may open to the public where you can invest in the farms.
154 00:28:04.140 ⇒ 00:28:07.129 Demilade Agboola: and then when they sell the yield.
155 00:28:07.570 ⇒ 00:28:13.749 Demilade Agboola: you’ll get a certain percentage or a certain like dividend, and then they’ll take the rest, you know. So that was their profit.
156 00:28:14.130 ⇒ 00:28:15.329 Amber Lin: That’s so interesting.
157 00:28:15.330 ⇒ 00:28:20.249 Demilade Agboola: So that allows them to scale cause that you know by people investing, they can, you know, raise a lot of money. We also
158 00:28:20.250 ⇒ 00:28:36.660 Amber Lin: Yeah. Oh, my God, that is so helpful! I’m gonna steal that idea and tell them, though I don’t even see them implementing it like I have. I have not very much faith in the volunteers that don’t even respond to the messages, so
159 00:28:36.660 ⇒ 00:28:41.038 Demilade Agboola: That’s fair. I thought very good was like, it’s a white. It’s a y combinator
160 00:28:41.670 ⇒ 00:28:45.916 Demilade Agboola: startup, you know, but they they’re they’re pretty solid and pretty solid
161 00:28:46.270 ⇒ 00:28:57.809 Amber Lin: Yeah, it looks pretty good. Yeah, anyways, I I know you need to run, but I wish this conversation was longer, but I was. I was so caught up in the
162 00:28:58.170 ⇒ 00:29:05.509 Demilade Agboola: It’s fine. I think, to. I don’t know. I should have some other time. Maybe not today. Because today is
163 00:29:05.960 ⇒ 00:29:07.970 Demilade Agboola: crazy. It’s a lot happening.
164 00:29:09.020 ⇒ 00:29:15.810 Amber Lin: Talk next week, because there’s no like we’re not working on a specific project. This is just like, Catch up
165 00:29:16.420 ⇒ 00:29:20.089 Amber Lin: chat. I’ll see. I’ll I’ll check in next week.
166 00:29:20.090 ⇒ 00:29:25.780 Amber Lin: Sounds good at the company meeting. Okay? And you have to run. Bye-bye. Thanks for calling
167 00:29:25.780 ⇒ 00:29:26.490 Demilade Agboola: Yeah.