Meeting Title: Uttam_Demilade Date: 2025-02-18 Meeting participants: Demilade Agboola, Uttam Kumaran
WEBVTT
1 00:01:38.820 ⇒ 00:01:39.820 Uttam Kumaran: Hey!
2 00:01:42.600 ⇒ 00:01:43.460 Demilade Agboola: Hi! My.
3 00:01:43.460 ⇒ 00:01:45.498 Uttam Kumaran: Are you so sorry for the delay?
4 00:01:45.790 ⇒ 00:01:48.829 Demilade Agboola: It’s all good. It’s all fine. It happens. How are you.
5 00:01:48.830 ⇒ 00:01:53.889 Uttam Kumaran: Just good. I’m just just met. We just brought on another analytics engineer, and we have.
6 00:01:54.280 ⇒ 00:02:03.959 Uttam Kumaran: Well, I guess I don’t. Maybe I don’t count, but we have 3, and then me. So it’s finally have a crew of people. So we’re just kicking off where we have, like almost one person per
7 00:02:04.310 ⇒ 00:02:10.649 Uttam Kumaran: one or 2 clients. And it was nice today. So we just talked about like our whole stack and
8 00:02:11.130 ⇒ 00:02:16.699 Uttam Kumaran: building data marts building like very great data marts for every client. So yeah, it’s it’s been good. Yeah, how are you?
9 00:02:17.210 ⇒ 00:02:20.790 Uttam Kumaran: I’m pretty good. I definitely not just have a call meeting.
10 00:02:22.195 ⇒ 00:02:23.575 Demilade Agboola: So far I’m good
11 00:02:24.160 ⇒ 00:02:29.839 Demilade Agboola: nice to meet you. I’m excited about this and anyone that new recommends is definitely someone I would want.
12 00:02:29.840 ⇒ 00:02:31.939 Uttam Kumaran: Oh, man, Neil’s the best I
13 00:02:32.400 ⇒ 00:02:33.650 Demilade Agboola: Yes, hi!
14 00:02:33.650 ⇒ 00:02:55.779 Uttam Kumaran: I can’t tell you. So I I I actually previously. So I worked at we work when I was I 1st graduated. I lived in New York and actually worked directly with. I worked directly with Leah Gabby. And I was actually, I helped them sort of I worked on data culture in like 2020 for like maybe a 2 months. This, this was like in between
15 00:02:55.980 ⇒ 00:03:02.110 Uttam Kumaran: jobs. And they were just starting data culture. So it was like me, and like 2 of our other friends that we worked with them.
16 00:03:02.290 ⇒ 00:03:05.689 Uttam Kumaran: I help them. You know better. Pt, do you guys hear about that client.
17 00:03:05.690 ⇒ 00:03:09.039 Uttam Kumaran: Yeah. Yeah. So it’s 1 of the list of clients. I didn’t work on that project.
18 00:03:09.040 ⇒ 00:03:31.409 Uttam Kumaran: Okay, yeah, I was like one of their 1st clients. So I helped them with that. And then I actually. So then so then I I was at another company, and then I actually worked at Prequel with them. I led. I led product at Prequel, so I was like one of the 1st engineers there, and that’s how I met Neil, and then me and Neil became really good friends. And then, yeah, I left pretty cool, like, probably 2 years ago. Now.
19 00:03:32.720 ⇒ 00:03:38.388 Uttam Kumaran: and yeah. Me and Neil, like has helped me so much in my business like
20 00:03:39.050 ⇒ 00:03:46.090 Uttam Kumaran: I have. So I had so many questions about like how to run this. And man like, what an amazing friend like
21 00:03:46.420 ⇒ 00:03:49.599 Uttam Kumaran: when I started. You know, it’s like I’m just focused on like.
22 00:03:49.880 ⇒ 00:04:16.629 Uttam Kumaran: and I’ll tell you more about the business. But I’m just like, I guess, need one client, 2 clients. But then he’s like dude. You need to make 50% margin. Otherwise you’re screwed. He gave me this like how to think about it as a business, because, of course, he was running. You know, the data culture business but also, like, I think, he had a bunch of struggles there that we that I sort of helped him talk through. And it’s great, I mean. I wish he could come work with us. I know he has, like visa issues. We’re not big enough to sponsor right now. But
23 00:04:17.132 ⇒ 00:04:19.959 Uttam Kumaran: but yeah, I’m really glad he put us in touch.
24 00:04:20.450 ⇒ 00:04:23.320 Demilade Agboola: Oh, definitely, yeah, like Neil, Neil is the best like. Neil was
25 00:04:23.680 ⇒ 00:04:38.201 Demilade Agboola: on the very 1st projects I worked on. Neil was the pro the manager on that, the product manager on that, and he was just like great fire to help me settle in and just he’s always just been there, you know. Even after
26 00:04:38.610 ⇒ 00:04:51.449 Demilade Agboola: We finished like I finished working at this for culture. I still have his number. He’s on my Instagram like we were like, you know that because genuinely and truly, it grew beyond just the. But the friendship that you have at work is actually.
27 00:04:51.450 ⇒ 00:04:52.090 Uttam Kumaran: Yes.
28 00:04:52.090 ⇒ 00:04:53.027 Demilade Agboola: An actual friend.
29 00:04:53.340 ⇒ 00:04:54.120 Uttam Kumaran: Yes.
30 00:04:54.380 ⇒ 00:04:55.750 Demilade Agboola: You know. Yeah, it’s great.
31 00:04:55.750 ⇒ 00:05:12.000 Uttam Kumaran: It’s funny. I’m the opposite. He’s my friend, and I’m trying to find a way to work with him longer term. But but yeah. So yeah, I mean, maybe I’ll tell you a little bit about the business. I’m so brain forge, I I worked as a data engineer and analytics, engineer
32 00:05:12.120 ⇒ 00:05:41.129 Uttam Kumaran: since like 2018. So I’ve been using Dbt since, like 2,018 been using Snowflake since, like 2,018 I, I started as a data engineer. We work. And then I worked at a company called Flow Code. They do like circular QR codes. They are all over the Nba Nfl. They’re now like a bigger company. I was the 1st data engineering hire there built everything from Scratch like snowflake looker. Dbt. Fired another like 5 or 6 people ran that data team
33 00:05:41.220 ⇒ 00:05:46.920 Uttam Kumaran: and then moved over to sort of lead our data product, which was selling Apis and things like that.
34 00:05:47.220 ⇒ 00:06:03.760 Uttam Kumaran: So just started just like kind of like f my life up, over and over and over again, with more work. And then I went to Prequel after that. And Prequel was like we started from like 0. So built out the entire product, basically. So we hired our 1st engineers. I I led
35 00:06:03.890 ⇒ 00:06:06.700 Uttam Kumaran: everything from design, full stack.
36 00:06:06.980 ⇒ 00:06:12.510 Uttam Kumaran: back end like, built the entire 1st version of that product and then left Prequel.
37 00:06:12.690 ⇒ 00:06:17.989 Uttam Kumaran: And it was sort of like, Okay, what do I want to do, I think for me the options were like I go to a big company.
38 00:06:18.780 ⇒ 00:06:42.410 Uttam Kumaran: and that seemed pretty boring. I could go to another startup and like, I don’t know if I could like health wise, I could like handle that emotionally. So then I I was like, Okay, let me see if, like, maybe consulting could be a possibility. But I never really even thought of it. Like consulting. I think of brain forge and engineering company. I just think we happen to work on other people’s engineering problems. We also do a lot of for ourselves. But
39 00:06:42.590 ⇒ 00:06:51.480 Uttam Kumaran: I don’t think of us really as like consultants first.st But you know, we’re in that industry. And then, yeah, so I we started. I I sort of quit my job in April of 20
40 00:06:51.640 ⇒ 00:06:55.749 Uttam Kumaran: 23 got our 1st client in July of 2023.
41 00:06:56.493 ⇒ 00:07:00.689 Uttam Kumaran: Funny story like I I got
42 00:07:01.125 ⇒ 00:07:07.050 Uttam Kumaran: like, I just called everybody I knew and was like, does anyone want data work? A friend of mine was like, Yeah, my friend is working on a client, but they suck.
43 00:07:07.310 ⇒ 00:07:25.390 Uttam Kumaran: And they’re like, really like crazy people. And I was like, those are my people like, I’ve always worked with executives. So I’m like, Send them my way. They’re like, yeah dude. These guys like their problems all over the place they like don’t like what we’re doing. They’re rude. And I’m like, they’re like, we’re gonna drop them. Do you want. I was like perfect. And then they they’re still our client. They’re our longest client. There’s since
44 00:07:25.780 ⇒ 00:07:26.345 Uttam Kumaran: almost
45 00:07:27.100 ⇒ 00:07:32.659 Uttam Kumaran: a year and a half, and sort of got me out of out of from 0 to them. And then.
46 00:07:33.210 ⇒ 00:08:00.269 Uttam Kumaran: yeah, we sort of got another client. Later that year I brought on our 1st data engineering hire in our analyst engineer in in December of 2023, and sort of been growing steadily. We kind of got one client every 3 months. Then one client every 2 months. In January of this year we signed like 3 clients in one month, and we’re sort of growing. We have about 15 people. Now, most of the crew is either data, engineering or data analysts.
47 00:08:01.740 ⇒ 00:08:03.195 Uttam Kumaran: And yeah, we’re just
48 00:08:03.770 ⇒ 00:08:10.370 Uttam Kumaran: we’re sort of in. We’re sort of now. The tides are turning where our problem isn’t money which it was for a long time like.
49 00:08:10.670 ⇒ 00:08:31.099 Uttam Kumaran: I haven’t looked open my bank account like transfer money in like a few months, which is really good. But our problem now is like, Okay, we need to like, execute the work. And so for me, I’m I’m interested in bringing on one the best analytics engineers on the planet. But also I want to bring on people that understand. The struggle of
50 00:08:31.420 ⇒ 00:08:35.640 Uttam Kumaran: this is like analytics, engineering on steroids like
51 00:08:36.230 ⇒ 00:08:40.809 Uttam Kumaran: having not only multiple clients, but multiple stakeholders within every client.
52 00:08:41.257 ⇒ 00:08:55.390 Uttam Kumaran: Is harder than if you’re just working in one company, right? But I wanna I wanna bring on analytics engineers that are open to that challenge. The second thing is, we have the opportunity to learn from every additional client. Right? So we primarily serve e-commerce and b 2 b saas
53 00:08:56.710 ⇒ 00:09:16.419 Uttam Kumaran: and we’ve worked with several companies in both of those industries that every additional company we bring on. They hire us not only because we know what we do, but we do it faster than anyone else, and we learn, and we like. We tell them here’s how you should structure your Utm campaigns. Here’s how you should merge Amazon and shopify like. Here’s how you should handle shipments, data and order lines. And like.
54 00:09:16.580 ⇒ 00:09:44.239 Uttam Kumaran: they’ve never met someone that’s like they, we get the problems that they’re facing at that level right? And so I do think that I also think about building our machine like, how do we build an amazing Ae crew? How do we build an amazing analyst crew? And then for every client we sort of have a client pod, you know, probably very similar to what you guys did where we have someone who’s like on the more like tech lead engagement manager side, we have a project manager. And then we have sort of engineers and analysts mixed in.
55 00:09:46.040 ⇒ 00:10:00.109 Uttam Kumaran: so yeah, that’s a little bit about us, sort of like all over the place. It’s morning. So I’m sort of just like hyped up on coffee. But yeah, I guess. Yeah, exactly so. But yeah, I would love to hear a little bit about you and sort of
56 00:10:00.240 ⇒ 00:10:03.210 Uttam Kumaran: what you’re doing now. And yeah, what you’re interested in.
57 00:10:03.991 ⇒ 00:10:18.740 Demilade Agboola: Yeah. So I my name is I’m Nigerian, and I grew up in Nigeria, and when I finished my university I was like, I studied electrical and electronics engineering. And I was like, it’s not what I want to do for the rest of my life.
58 00:10:18.740 ⇒ 00:10:22.323 Uttam Kumaran: I studied computer engineering. And yeah, it’s not what I want to do.
59 00:10:23.097 ⇒ 00:10:30.039 Demilade Agboola: So I just decided, okay, I I heard about data, and I was really curious about it. And I just went down the one hole.
60 00:10:30.120 ⇒ 00:10:56.629 Demilade Agboola: and 2 years later I found myself, as the 1st data hire of a company in Nigeria called direct. It’s a startup. And they were basically trying to. So Nigeria has a huge problem with like farmers, and like a number of them, are just like subsistence farmers like really small holder farmers. And so they were trying to bridge the gap and help them, you know, give them access to technology and the ability to know when to plant, when to harvest all that stuff.
61 00:10:56.800 ⇒ 00:11:05.150 Demilade Agboola: and they would be the middleman in between to buy off all their yield, and then sell it to other offtakers that they could, you know, so they could like aggregate it and sell it
62 00:11:05.690 ⇒ 00:11:06.560 Demilade Agboola: volume
63 00:11:07.145 ⇒ 00:11:21.849 Demilade Agboola: and so that’s what they did. So that was kind of the startup. So I worked in that. And then one of the problems they had was that they weren’t banked. So they created a Fintech kind of bank, this farmers, so they could have some credit history and some ability to be able to track how they spend money.
64 00:11:22.630 ⇒ 00:11:35.690 Demilade Agboola: And so I moved across, like laterally, to the Fintech of that company, and I was responsible for all things like data uptime, like devops to a certain extent, and like managing that. And so that’s what I was doing for 2 years of my life.
65 00:11:35.840 ⇒ 00:11:40.650 Demilade Agboola: Pretty fun! It was really challenging. But it was nice to be able to experience just having to
66 00:11:41.108 ⇒ 00:11:49.639 Demilade Agboola: think data for people set up the data infrastructures, and it’s answer the questions be proactive with that, but also just generally be responsible for like
67 00:11:50.130 ⇒ 00:11:55.039 Demilade Agboola: how things run learned about like Ec. 2 instances, which are things.
68 00:11:55.040 ⇒ 00:11:57.220 Uttam Kumaran: Did you do data before that at all? Or no, you just sort of.
69 00:11:58.090 ⇒ 00:12:00.419 Demilade Agboola: Yeah, like, I was learning on the job and trying to.
70 00:12:00.420 ⇒ 00:12:00.890 Uttam Kumaran: Nice.
71 00:12:00.890 ⇒ 00:12:03.859 Demilade Agboola: Like. I’m that sort of person. I love to be able to like
72 00:12:03.990 ⇒ 00:12:05.729 Demilade Agboola: figure things out on the job.
73 00:12:06.279 ⇒ 00:12:13.410 Demilade Agboola: And so that was what I did for 2 years, and then I then got a job with data culture
74 00:12:13.640 ⇒ 00:12:18.470 Demilade Agboola: until that was like my first, st like proper consulting experience. And
75 00:12:19.060 ⇒ 00:12:37.940 Demilade Agboola: that was lovely. To be honest, I was there for about 2 years as well worked on a bunch of projects, and I think it was one of those things where I really loved it, because it was I was learning a lot. Because I mentioned about missing consulting, because it’s 1 of those places where you need to be on top of what’s happening in.
76 00:12:37.940 ⇒ 00:12:38.750 Uttam Kumaran: Yeah.
77 00:12:38.750 ⇒ 00:12:57.640 Demilade Agboola: You need to know. You know everything that happened yesterday and all like. So I love that I love the ability to be able to be on the cutting edge of technology, on the ability to be able to like, recommend and see different solutions and production. And see, hey, there might actually be a better way. And that obviously figuring out better ways makes you better.
78 00:12:57.770 ⇒ 00:13:03.429 Demilade Agboola: And I think office and like my my mantra, and life is just like that, 1% keeps adding up right? So
79 00:13:03.640 ⇒ 00:13:15.079 Demilade Agboola: I loved it. I I worked for I worked there for 2 years. But unfortunately, data culture had, like a financial issues at some point. And so I was one of the people affected in their layoffs.
80 00:13:15.832 ⇒ 00:13:20.679 Demilade Agboola: To that point. I then moved to another company called to you
81 00:13:20.840 ⇒ 00:13:24.060 Demilade Agboola: the Logistics Company, based in Saudi Arabia
82 00:13:24.781 ⇒ 00:13:29.300 Demilade Agboola: and they basically were trying to migrate their stack from
83 00:13:30.001 ⇒ 00:13:35.640 Demilade Agboola: having all these reports like with all the logic in tableau and creating like a Dbt infrastructure.
84 00:13:36.350 ⇒ 00:13:41.040 Demilade Agboola: But they had the problem with the technical team. They really have, like the business like
85 00:13:41.190 ⇒ 00:13:45.319 Demilade Agboola: full access to the business. And then the business team didn’t really have technical infrastructure to.
86 00:13:45.320 ⇒ 00:13:45.830 Uttam Kumaran: Yeah.
87 00:13:46.090 ⇒ 00:13:46.920 Demilade Agboola: Dvt I don’t.
88 00:13:46.920 ⇒ 00:13:48.960 Uttam Kumaran: It’s our job. Yeah. Then it’s our job. Yeah.
89 00:13:48.960 ⇒ 00:14:00.850 Demilade Agboola: Exactly. So I I basically came in and I was trying to like help migrate that. So I had to come up with like the roadmap like prioritize? What are the most important tables? How do we migrate them? How do we set them in such a way that we can actually
90 00:14:01.030 ⇒ 00:14:05.560 Demilade Agboola: build a large majority of our tables and our logic in Dbt
91 00:14:05.940 ⇒ 00:14:21.910 Demilade Agboola: as well as education. So again, because I was in the business team, I was trying to drive Dbt adoption and education. I wanted people to be able to think of, hey? I need to be able to report instead of if it’s not high priority. How do I build a Dbt model instead of going directly into tableau?
92 00:14:22.070 ⇒ 00:14:26.110 Demilade Agboola: So for context, we had, like 700
93 00:14:26.957 ⇒ 00:14:29.819 Demilade Agboola: different tables. By the time I was done
94 00:14:30.210 ⇒ 00:14:32.529 Demilade Agboola: come a long way on the roadmap.
95 00:14:32.992 ⇒ 00:14:37.230 Demilade Agboola: We had, like so many reports. I believe we had 500 plus reports.
96 00:14:37.970 ⇒ 00:14:59.740 Demilade Agboola: Some of them were obsolete, but, like the idea was, you know, they had so many like tables. Everyone wanted something C-suite finance marketing. Everyone was operations. Everyone just had tables and models for different things. So obviously that wasn’t the most efficient way to build it. But they were at the point where they couldn’t stop, and you know the people needed someone to come, and you know, push them in that direction.
97 00:14:59.930 ⇒ 00:15:01.506 Demilade Agboola: So which I did.
98 00:15:02.060 ⇒ 00:15:07.600 Demilade Agboola: And it was was. It was a good experience. I’ll be a bit slow. I did miss the thrill of.
99 00:15:07.929 ⇒ 00:15:17.160 Uttam Kumaran: Dude. Be careful what you wish for. I feel like no, no, I know what you mean. I mean, Dude. I’m the same way like I need
100 00:15:17.540 ⇒ 00:15:23.039 Uttam Kumaran: I. This is like a blessing and a curse like I need to be fully occupied, right like
101 00:15:23.640 ⇒ 00:15:45.099 Uttam Kumaran: I need to lock in, and I like to lock the F in. And I’m like, Okay, cool, we need to. There’s something on any data is always something on fire. Right? I don’t. I think if there’s not. And this I just talked to the team about this, because I think a lot of engineers, they always aspire that like, okay, one day things are going to be calm, and it’s gonna be quiet never. Otherwise we don’t have a business right.
102 00:15:45.699 ⇒ 00:15:56.059 Demilade Agboola: That’s why, when you said the the when data is trustworthy and clean, I’m like the elusive, trustworthy and clean, because, like it’s never really unclean. There’s always that like. At least there’s some question marks here and there.
103 00:15:56.060 ⇒ 00:15:56.570 Uttam Kumaran: Totally.
104 00:15:56.570 ⇒ 00:16:00.709 Demilade Agboola: Amount of question marks. But like, you’re never at the point where, like, I’m 100%.
105 00:16:00.710 ⇒ 00:16:19.020 Uttam Kumaran: 100. I’ve never worked at a company. Yeah, you’re you’re totally correct. And also it’s our job. But our job is going to be always perfection. It’s like, you know, when you when they if you watch any sports documentaries, they win 10 games in a row. They’re still like we still have something we can improve. Right? So one, I think about that like, how can we
106 00:16:19.100 ⇒ 00:16:42.350 Uttam Kumaran: keep getting better? But also, I want to maintain that our ae, team operates different from the analyst team. Right? Like our Ae team, things can be on fire. But we need to think about how do we catch the right bullet and like process it? Right? Like, okay, we’re taking on dashboard. We we need to support 10 dashboards. Okay, what can we? How do we take all those requests and build a sophisticated data mark for all of those.
107 00:16:42.420 ⇒ 00:16:54.659 Uttam Kumaran: And then how do we work with the analyst to be like, you guys need to get us way more requirements before we can go. Do this right. And so you have that exchange. And also I told them I said, I just told. Say, I said, that’s never going to stop. But in fact, our demeanor
108 00:16:54.780 ⇒ 00:16:59.689 Uttam Kumaran: in the fire is what we can control, right like, how we operate, how we act and how we.
109 00:16:59.950 ⇒ 00:17:17.620 Uttam Kumaran: how we calm everyone down. And we sort of find the path forward is our job, the analyst team. I’m going to tell the analyst team a different story. I’m gonna say your job is to solve the problem as fast as possible. There’s always going to be a healthy back and forth. The Ae team is going to be like, slow down. We should build a model. The analyst team is going to be like
110 00:17:17.829 ⇒ 00:17:22.070 Uttam Kumaran: I. They’re they’re having a meeting in 10 min. I gotta rip this in excel, like.
111 00:17:22.230 ⇒ 00:17:39.149 Uttam Kumaran: you know. And actually, I’m okay. I’m actually want that conflict because we we there are trade offs right? And so I’m not. I’m not. There’s no problem with that conflict. In fact, it’s a discussion every day. But you need to have a principled way. You arbitrate right? Those those types of things. So yeah, I totally agree.
112 00:17:39.610 ⇒ 00:17:40.190 Demilade Agboola: You know.
113 00:17:40.420 ⇒ 00:17:49.000 Demilade Agboola: So yeah, it was. It’s it was a great experience. But it’s just slow, you know. Sometimes everything requires like the Jira ticket, and you know there’s that process.
114 00:17:49.510 ⇒ 00:17:57.110 Demilade Agboola: you know. Everything needs to be done, which I mean is great like it was good to have that structure, but the times when I just wanted to, you know.
115 00:17:57.360 ⇒ 00:18:15.339 Demilade Agboola: dive back in. So that allowed me to even like consult on the site, you know. Just get a couple of projects in and just work on that by myself. But that and that was great, because, like that also put me in space where I was prototyping like entire projects from start to finish, and.
116 00:18:15.340 ⇒ 00:18:15.830 Uttam Kumaran: Yeah.
117 00:18:15.830 ⇒ 00:18:24.080 Demilade Agboola: Yeah, I had what like the problems were. And that’s kind of, I think, what I I do enjoy and what I thrive in, because, like, it also forces me to do research. Figure out like.
118 00:18:24.150 ⇒ 00:18:33.520 Demilade Agboola: is this the best possible thing I could recommend in terms of technicality and financial? The balance of technology and financials as well.
119 00:18:33.540 ⇒ 00:18:54.959 Demilade Agboola: So yeah, that’s basically, you know my story. There’s also stuff in there about like the things I’ve had to work on projects and all that, but you know those are the the number of them like I really enjoyed. When I had to like Geo code. We had the clients who they were like they. They were doing homicide data in the Us.
120 00:18:55.270 ⇒ 00:19:03.910 Demilade Agboola: And effectively, I had to create this model that converted the addresses in which it happened to like last long points.
121 00:19:04.350 ⇒ 00:19:08.400 Demilade Agboola: and because we needed to create a heat map based off that
122 00:19:09.021 ⇒ 00:19:19.959 Demilade Agboola: but like they were using. They were using bigquery. Bigquery doesn’t have that in built. So I had to set up a custom function that would call the Google Maps. Api.
123 00:19:19.960 ⇒ 00:19:20.653 Demilade Agboola: Oh, nice!
124 00:19:21.000 ⇒ 00:19:28.152 Demilade Agboola: Retrieve it. So I had to set up a custom function in bigquery where the cloud function in
125 00:19:28.770 ⇒ 00:19:30.100 Demilade Agboola: that created call function.
126 00:19:30.100 ⇒ 00:19:31.009 Uttam Kumaran: Yeah, yeah.
127 00:19:31.010 ⇒ 00:19:34.899 Demilade Agboola: And then send it. Get the res, get the result, putting the table
128 00:19:35.610 ⇒ 00:19:52.569 Demilade Agboola: and then make incremental, because obviously, Google maps Apis have a charge after a certain point. So you you want to reduce the the need to keep calling everything. And so that was that was a fun project. It was technical. But it was fun, because I had to work with like different bits and pieces of like, the Google cloud.
129 00:19:52.630 ⇒ 00:20:14.019 Demilade Agboola: But yeah, there’s just other things I’ve had to work on over. But, like generally, I just love it. The idea of like having to figure out like, how do we go from here to this point. How do we ensure the table works? How do we ensure like? We answer those questions quickly? And how do we ensure. We do that like the minimal cost possible, because we don’t want to like rack up a bill at the end of the month for the time. Yeah, so
130 00:20:14.170 ⇒ 00:20:18.009 Demilade Agboola: yeah, that’s basically like the summary of like stuff I’ve done.
131 00:20:20.440 ⇒ 00:20:27.820 Uttam Kumaran: So what do you? What do you see for your career like? Do you want to keep? I guess you have 2 paths, typically right as ae one. You.
132 00:20:28.530 ⇒ 00:20:34.080 Uttam Kumaran: I mean, you get more technical. You start. You’re you’re able to do almost like full stack. Right? You’re able to do de work.
133 00:20:34.200 ⇒ 00:21:01.469 Uttam Kumaran: You’re kind of able to do analysts work. You’re maybe go even deeper. But you know, in our world probably know in consulting like we never get to work on like the like. The when I worked at a company for like 2 years. Then, finally, you get to like, really tough, like incremental strategy problems like, okay, now, we have 50 people that are accessing. We need to build scale a lot of our clients. They’re just like we’re still in like, the just get the basic data, mark phase. And many of them don’t
134 00:21:01.670 ⇒ 00:21:02.779 Uttam Kumaran: frankly like.
135 00:21:03.110 ⇒ 00:21:07.579 Uttam Kumaran: if I bring up Dvt, they’re like, what is that like? Why are we paying for that, you know. And so.
136 00:21:07.710 ⇒ 00:21:19.180 Uttam Kumaran: unfortunately, I don’t think we work on like the edge problems there. The problems that we work on is like is like, how do we manage a team of great aes, and how do we work? How do we do everything faster?
137 00:21:19.280 ⇒ 00:21:40.399 Uttam Kumaran: Right? So if we go from requirements to model. How do I do that faster, either with better process? How do we use AI and or just how do we like learn from our past customers. So those are the problems that we’re focused on. Second, I think we’re gonna get more technical in our type of analysis that we do right like, we have some very talented analysts that are gonna start to do things beyond, just like
138 00:21:40.430 ⇒ 00:22:10.099 Uttam Kumaran: basic dashboarding that we want them to do work on churn probabilities. We want them to work on really tough Ltv modeling. We want them to do correlation analysis like AV testing like tough, tough analyst challenges. That’s where I really see our opportunity. I think with the a team, we’re gonna continue to be like, okay, we need a new data source, or this logic needs to change or segmentation needs to change. But our job is really their. Our client is ultimately going to be the analyst team. And how did how fast can they move?
139 00:22:10.140 ⇒ 00:22:35.129 Uttam Kumaran: So it’s all sort of domino effect of like. However fast we move, how confident we are! They can move faster, and then I want them to work on like, do the toughest analysis, right? Like we have, like a hundred 1 million dollar Ecom companies that aren’t doing any sort of incrementality testing bundle testing. I’m like, guys, you’re you could be like the best, you know. And so I think of ourselves as an extension of their company. And I’m like, how do we supercharge them? Right?
140 00:22:35.637 ⇒ 00:22:54.960 Uttam Kumaran: And you know, like their operations team, they probably dream one day of doing these things. They have no idea how to technically get it done. And so that’s sort of the support I want to play, I guess, going back to my question, like, of course, there’s 1 thing in going more technical. There’s also one thing in sort of leading more aes like sort of what do you see like next for you.
141 00:22:55.888 ⇒ 00:23:08.420 Demilade Agboola: To be fair for me. It’s a combination of both at this point, like, I don’t think it’s an either, or right now. I think maybe 5, 10 years in the future, I would definitely have to like, okay, settle down.
142 00:23:08.900 ⇒ 00:23:12.989 Demilade Agboola: I’m about what? 6 years into my career. And I still feel
143 00:23:13.320 ⇒ 00:23:20.050 Demilade Agboola: the desire to be able to learn more and be more technical and like, push the boundaries of how I can
144 00:23:20.190 ⇒ 00:23:21.070 Demilade Agboola: on
145 00:23:21.510 ⇒ 00:23:33.330 Demilade Agboola: do things, because, like I said, I really do enjoy that. But I’m also aware that obviously being like 5, 6 years in comes with that, because you to know and translate what you’ve learned to other people.
146 00:23:33.530 ⇒ 00:23:42.890 Demilade Agboola: And I have been in situations where I’ve had to do that. And I’ve also seen that, like, you know, my period, like my previous role in data culture.
147 00:23:43.262 ⇒ 00:24:12.680 Demilade Agboola: We had, like someone who was just coming in into the Ae fold. And so it was also like one project you would have to be aware and just be able to translate and break down requirements, and you know, position her in the best way to succeed in my role into you. I had to be there to be able to, because again, they knew sequel. But just like the transition to Dbt, so trying to help them guide them on that path, help them figure out the best ways to build incremental models, figure out the giving them a checklist
148 00:24:12.820 ⇒ 00:24:21.449 Demilade Agboola: so they could figure out how to go from. You know, 0 to 100 real quick. Just trying to figure out like that balance of like managing and helping people.
149 00:24:21.720 ⇒ 00:24:28.250 Demilade Agboola: and also just myself also growing. So at this point I I’m I would see a merger of both.
150 00:24:28.250 ⇒ 00:24:28.690 Uttam Kumaran: Cool.
151 00:24:28.690 ⇒ 00:24:31.850 Demilade Agboola: I’m open to like. I definitely want to experience both.
152 00:24:32.356 ⇒ 00:24:38.980 Demilade Agboola: But like, I’m 5 years, 10 years on the line, I think that’s where you have to kind of make that like definite, like.
153 00:24:38.980 ⇒ 00:24:46.990 Uttam Kumaran: You don’t. You don’t necessarily need to, but it’s a good thought exercise like I I went more technical. But then I also went into business like I was like.
154 00:24:47.320 ⇒ 00:24:49.889 Uttam Kumaran: Okay, let me go learn what it takes to build the products.
155 00:24:50.180 ⇒ 00:24:54.150 Uttam Kumaran: Now, my role is like, I don’t know all over the place kind of like.
156 00:24:54.350 ⇒ 00:24:59.950 Uttam Kumaran: I still love doing data work every day. I think now, I’m sort of back to doing at least 2 to 3 h of data work every day.
157 00:25:00.310 ⇒ 00:25:09.060 Uttam Kumaran: But I guess. Tell me about like, what was the pods? What was the structure on clients like? Were you on multiple clients? There was it like daily meetings on clients like what was the structure.
158 00:25:09.957 ⇒ 00:25:21.079 Demilade Agboola: So structuring, digital culture was basically depending on your workload. And like feedback, you gave because feedback was an important thing. But generally I was on 2 to 3 projects.
159 00:25:21.659 ⇒ 00:25:22.649 Demilade Agboola: At the time.
160 00:25:23.287 ⇒ 00:25:35.439 Demilade Agboola: And we usually would have one internal meeting every week. We could increase it, depending on like if we’re we’re missing deadlines. And we needed to like get things across the line really quick.
161 00:25:36.049 ⇒ 00:25:45.490 Demilade Agboola: But usually we had one meeting every week internally. So the internal team. And then one meeting with the clients, we would give them feedback and let them know what was going on with that
162 00:25:45.894 ⇒ 00:25:52.070 Demilade Agboola: and basically the combination of those meetings allowed us to prioritize what the data work had to be for that week.
163 00:25:52.280 ⇒ 00:25:58.010 Demilade Agboola: And so usually internally, we would catch up to then figure out like, Hey, how’s that coming along?
164 00:25:58.492 ⇒ 00:26:09.530 Demilade Agboola: And we also give feedback to the clients as to what we were doing, and if they had any questions, or if they had any like quick suggestions, and allow them to do, maybe test one or 2 things even before.
165 00:26:09.700 ⇒ 00:26:12.900 Demilade Agboola: So we came up with things like, for instance, we had like wireframes
166 00:26:13.610 ⇒ 00:26:20.809 Demilade Agboola: for dashboards, so we could create, like big man dashboards in figma like very low very high fidelity dashboards
167 00:26:20.950 ⇒ 00:26:28.899 Demilade Agboola: where we could show them like this is how the dashboard is going to be. So the filters we’re looking at. And they were like, actually, no, we don’t need that filter. We we want this filter instead.
168 00:26:28.900 ⇒ 00:26:29.500 Uttam Kumaran: Yeah.
169 00:26:29.500 ⇒ 00:26:38.629 Demilade Agboola: So we don’t waste all this time defining a model to answer a dashboard that they don’t need so things things like that we’re trying to also figure out how
170 00:26:38.870 ⇒ 00:26:41.179 Demilade Agboola: to the answer as quickly as possible.
171 00:26:42.140 ⇒ 00:26:46.389 Uttam Kumaran: But dude, that seems like not many meetings like for us. I’m sort of like
172 00:26:47.600 ⇒ 00:26:50.620 Uttam Kumaran: I’m trying to move like fast. So I’m like
173 00:26:50.780 ⇒ 00:26:54.710 Uttam Kumaran: yo, let’s even for the Ae crew, because I also think there’s part of
174 00:26:55.160 ⇒ 00:26:58.829 Uttam Kumaran: I want to spend time talking about clients. But then you never talk about the machine.
175 00:26:59.060 ⇒ 00:27:18.219 Uttam Kumaran: And for me, I’m I’m kind of both where I like. Look at all the thing. But then I’m like, okay as a crew. How do we improve? Cicd, how do we improve linting? Can we improve like? Can we take from other clients? That’s the stuff that I feel like gets us from just like fighting the fires every day to being okay. How do we build the better.
176 00:27:18.580 ⇒ 00:27:23.489 Demilade Agboola: Yeah, I also think even things like thinking of like Dvt markers you could build on.
177 00:27:23.490 ⇒ 00:27:41.249 Uttam Kumaran: Yeah, yeah, like, how do we share macros? The other thing, we we have templated repos. So when we start a new client, we already have a repo set up with everything. You just swap the profiles, and then, if it’s Gcp. If it’s bigquery or snowflake, you swap the profiles. So we saw that we also have scripts for Snowflake. So
178 00:27:42.060 ⇒ 00:27:54.089 Uttam Kumaran: I go and set up all the R back so raw, intermediate, so raw, intermediate mart broad staging. Dev. We set up all the warehouses. We set up all the roles we set up the users like
179 00:27:54.480 ⇒ 00:28:09.340 Uttam Kumaran: we just build all that, because then that takes like a week like, and I’m like dude. I’m gonna do this in like 1 h now and sometimes clients may not know. But then again, we get like for me. The how do we get to the 1st quality dashboard faster?
180 00:28:09.440 ⇒ 00:28:11.179 Uttam Kumaran: I don’t want that to take a month.
181 00:28:11.400 ⇒ 00:28:17.800 Uttam Kumaran: Maybe we could get away with it being a month like, maybe I could just be like, it’s gonna take a month and they would be okay with it. But
182 00:28:18.000 ⇒ 00:28:39.849 Uttam Kumaran: I’m not okay with it. I’m like, I want us to be the best right. And I want us to know. We know as engineers. We’re like, if everything just went a little bit better. We could have got it in a week, right? And so that’s the sort of thing is like, can we set up snowflake and everything in a day. Can I get everything set up in the Etl in the net the next day, can we? And also we do Amazon for 5 different clients. Why can’t we just have.
183 00:28:40.280 ⇒ 00:28:43.050 Uttam Kumaran: like boilerplate intermediate
184 00:28:43.712 ⇒ 00:29:06.430 Uttam Kumaran: packages, basically, right? Like we were using some of 5 train packages. But we could start developing our own. Internally, we’ve done shopify for 10 people, right? And then, okay, that solves the modeling problem. Then it’s just the dashboard. And I mean, that’s the that’s the thing that’s most subjective, right? So that should get probably the most amount of time. But that’s the things that like. If you just if you’re just talking about clients every day. You have never have the opportunity to sort of be like
185 00:29:07.090 ⇒ 00:29:09.499 Uttam Kumaran: yo, can we? Let’s take a step back and like.
186 00:29:09.620 ⇒ 00:29:13.829 Uttam Kumaran: how could we have done this better retros, and you kind of get out of the fire a little bit right.
187 00:29:13.830 ⇒ 00:29:18.090 Demilade Agboola: Yeah, fair. Fair. Yeah. I agree with that. Like, they’re basically to be able to
188 00:29:18.746 ⇒ 00:29:30.680 Demilade Agboola: replicate as quickly as possible is is huge. Because I didn’t they? And also I like the fact that you said, your your clients are generally like e-commerce clients so like it’s the same sort of problem. So.
189 00:29:30.680 ⇒ 00:29:31.360 Uttam Kumaran: Totally.
190 00:29:31.360 ⇒ 00:29:33.080 Demilade Agboola: The solutions
191 00:29:33.410 ⇒ 00:29:42.610 Demilade Agboola: across them. Because if it was a Fintech, if you got like a Fintech company, you would have different questions. You can’t necessarily. I mean, some things will be replicable. But, you know, get different questions. You have to ask.
192 00:29:42.610 ⇒ 00:29:43.230 Uttam Kumaran: Yeah.
193 00:29:43.230 ⇒ 00:29:48.600 Demilade Agboola: Like getting clients in similar mode allows you to be able to replicate. And I think at the end of the day those like
194 00:29:49.277 ⇒ 00:29:53.210 Demilade Agboola: those things at scale allow you to be able to move quickly.
195 00:29:53.450 ⇒ 00:29:54.040 Uttam Kumaran: Yeah.
196 00:29:54.040 ⇒ 00:29:59.800 Demilade Agboola: But the 1st clients are taking you a month. Second client takes you 3 weeks, 2 weeks, one week.
197 00:30:00.090 ⇒ 00:30:00.650 Uttam Kumaran: Yeah.
198 00:30:00.650 ⇒ 00:30:05.950 Demilade Agboola: We get to a point where it’s like, Oh, a new client comes in and we just know what we’re gonna do.
199 00:30:06.440 ⇒ 00:30:17.710 Demilade Agboola: And we know how to be able to handle like any that might occur as well. Because we’ve had so many of these sort of clients that we can understand how to be able to like what the ideal state looks like, and how to get.
200 00:30:17.710 ⇒ 00:30:18.270 Uttam Kumaran: Totally.
201 00:30:18.270 ⇒ 00:30:20.360 Demilade Agboola: That point to that point, we can.
202 00:30:20.360 ⇒ 00:30:28.580 Uttam Kumaran: And a lot of our clients. They we don’t do like staff augmentation stuff where we’re like. Here’s 5 engineers. We do like holistic like we come in as their data team.
203 00:30:28.700 ⇒ 00:30:31.680 Uttam Kumaran: They’re like you, you make the decisions for us.
204 00:30:31.890 ⇒ 00:30:36.510 Uttam Kumaran: We’re we’re not often working with people where they’re like, we need exactly these things. They’re kind of like.
205 00:30:37.000 ⇒ 00:31:02.130 Uttam Kumaran: I think we need these things, but like you could tell that they’re not sure. And then when we come and we’re like yo, I’m telling you, we worked with 500 million dollar companies just like you. You should do this. They’re like perfect. Finally, someone comes in and owns it right? And so we’ve done that now in e-commerce, and b 2 b sas quite a bit. And we’ve worked for some some really big brands that again, I think we’re we’re still in the mode of building out great data mart and dashboards. But that’s sort of what we’re working on.
206 00:31:02.250 ⇒ 00:31:22.509 Uttam Kumaran: And then the last thing is, I think, beyond that we’ll start to use AI pretty heavily later this year. We also want a big part of our businesses selling AI services. When I started the business, one of my goals was to try and like automate as much of the business as possible with AI, because I started it right when Gpt. 3.5 came out
207 00:31:22.780 ⇒ 00:31:33.500 Uttam Kumaran: and we we hire. We have. We have a team of 3 AI engineers internally that help to sort of automate everything around our business. And then now, we’re also starting to do AI for clients like building agents and things like that.
208 00:31:33.940 ⇒ 00:31:51.839 Uttam Kumaran: So we’re starting to automate the Pm process. And then we’ll also start. Our crew of Aes will help the AI team basically come in and say, what do we need to automate like? Can I just give you the Ddl. And you can sort of spit out Dbt, right? And that allows us to sort of go from a week to like
209 00:31:52.010 ⇒ 00:31:57.639 Uttam Kumaran: few days right? And like, that’s for us. We’re like nobody, right. But I I want us to compete with Deloitte.
210 00:31:57.920 ⇒ 00:32:01.489 Uttam Kumaran: Right? I fortunately. Unfortunately, I don’t look at like
211 00:32:02.500 ⇒ 00:32:15.739 Uttam Kumaran: data culture and the other people at our level. I don’t look at that. I look at like, I want to compete with accenture. I want to compete with Deloitte, Bcg, Bain. Those guys are doing 0 work, and they’re making a hundred.
212 00:32:15.740 ⇒ 00:32:17.510 Demilade Agboola: 100% of the money. Yeah.
213 00:32:17.510 ⇒ 00:32:39.289 Uttam Kumaran: And so I’ve it makes me angry when I wake up when I think about that. And so for me, that’s who I think about competing with. We’re but we’re nobody we don’t have, you know. So we have to win through raw execution. And ultimately, there’s gonna be no other data consultancy that can go to a client and say, Give us a week. We’ll show you what we can do. Everybody’s gonna say, okay, we need 2 weeks to scope.
214 00:32:39.530 ⇒ 00:32:57.130 Uttam Kumaran: Within one month we have the dashboard. In 2 months we’ll do a check in blah blah! Blah! I don’t. I don’t care about that at all. That’s the natural way. Consultants think I’m not a consultant, you know. So I I change our business in that. We are an engineering company. Our job is not to sandbag
215 00:32:57.250 ⇒ 00:33:01.550 Uttam Kumaran: right? And there’s a balance. Sales and other teams may be like we should slow things down.
216 00:33:01.690 ⇒ 00:33:05.349 Uttam Kumaran: but I always think about speeding things up and making things.
217 00:33:05.600 ⇒ 00:33:09.659 Uttam Kumaran: You know, we should be undeniable in our in our data efforts. You know.
218 00:33:10.110 ⇒ 00:33:16.920 Demilade Agboola: That’s definitely definitely. And I I see why you need people who don’t just see it as like we’re solving
219 00:33:17.500 ⇒ 00:33:22.660 Demilade Agboola: the problem or like building dashboards. We’ll get into this like kpis with clients.
220 00:33:22.800 ⇒ 00:33:34.789 Demilade Agboola: But who are seeing it as like an overall thing a bigger than just like you know. Oh, let’s get dbt in or no, but like, how can we use Dbt in this project in a scalable, maintainable way?
221 00:33:34.790 ⇒ 00:33:35.470 Uttam Kumaran: Yeah.
222 00:33:35.470 ⇒ 00:33:50.159 Demilade Agboola: Continuously do this in such a way that like, it’s replicable. And it’s easy to use across things. So yeah, that’s that’s definitely a different way to like doing it than just like, oh, what is the what’s what Kps are we trying to address and all that?
223 00:33:50.160 ⇒ 00:33:50.780 Uttam Kumaran: Yeah.
224 00:33:50.780 ⇒ 00:34:00.389 Demilade Agboola: Basically trying to understand and trying to ensure that, like what you’re modeling and how you’re modeling and how you move with the clients is as quick and as snappy as possible.
225 00:34:00.390 ⇒ 00:34:01.020 Uttam Kumaran: Yeah.
226 00:34:01.720 ⇒ 00:34:06.970 Uttam Kumaran: I mean, dude. I feel like I don’t usually do this, but I would love for you to come work with us like, what?
227 00:34:07.240 ⇒ 00:34:10.090 Uttam Kumaran: What do you think like? How can I try and make
228 00:34:10.280 ⇒ 00:34:18.179 Uttam Kumaran: that happened? I mean, let me tell you a little bit about what we need right now one, as I mentioned, we’re a team of, I mean, we have a bunch of people across data.
229 00:34:18.731 ⇒ 00:34:29.889 Uttam Kumaran: But we have 3 other analytics engineers. 2 of which are part time. They just joined recently, but they’re probably more junior than you are. So sort of
230 00:34:30.330 ⇒ 00:34:39.109 Uttam Kumaran: sort of figuring out, okay, like, who’s going to be the best team. But I really want to bring on someone who’s a partner on the Ae. Side, who is like, Okay, I’ve seen
231 00:34:39.300 ⇒ 00:34:43.099 Uttam Kumaran: ae like cross clients before.
232 00:34:43.300 ⇒ 00:35:07.490 Uttam Kumaran: So you have that mindset of like, okay, we’re never gonna be just working with one person. We have a process. But for me that allows me to sort of step above that and sort of see. Okay, what can we learn from every e-commerce customer? So I think that you’ve kind of fit that perfect perspective of like. Still being able to do the work like dude. I still write Dbt. Models every day, but then, being able to even like, run like an A sync where it’s like.
233 00:35:07.770 ⇒ 00:35:08.900 Uttam Kumaran: who’s blocked
234 00:35:09.030 ⇒ 00:35:18.949 Uttam Kumaran: like, okay, who needs like teaching everybody. Okay, we should do incremental here. Okay, there’s a solution here. Building process like that’s sort of what we really need on the Ae. Side.
235 00:35:19.070 ⇒ 00:35:20.140 Uttam Kumaran: And then.
236 00:35:20.540 ⇒ 00:35:25.589 Uttam Kumaran: like, I don’t know, I would love to see if there’s an opportunity for you to come like work with us, you know, in any way.
237 00:35:26.268 ⇒ 00:35:46.910 Demilade Agboola: Yeah. As like, I will def so part of the reason why Neil recommended me as well, because, like, I was on the lookout for a new role in the sense of like I mentioned, my previous role was a bit too slow, and I kind of wanted something a bit more fast paced. And 2 is the my role like I said, was in Saudi Arabia. So I visit the us like
238 00:35:47.230 ⇒ 00:35:52.539 Demilade Agboola: 5 months a year. My girlfriend is here. So I keep coming in and out of the Us. So that allows me to.
239 00:35:52.970 ⇒ 00:35:57.399 Demilade Agboola: That means when I’m here. I kind of have to work weird hours. I’m up at one o’clock.
240 00:35:57.400 ⇒ 00:35:57.870 Uttam Kumaran: Yeah, yeah.
241 00:35:57.870 ⇒ 00:36:08.469 Demilade Agboola: Something a bit more us based, or at least flexibility of that. So that when I’m here I can work you know us hours when I’m back in like Malta, because that’s where I live.
242 00:36:08.965 ⇒ 00:36:29.800 Demilade Agboola: In Malta, when I’m in Malta I can work like my afternoon to like evening hours. So like, I have that balance of being able to do that. So yeah, this, this will be something I’m definitely very open to and I also like the actual scope of being able to come back in, and not just even just do consulting like I have known it, but like at the
243 00:36:29.960 ⇒ 00:36:30.660 Demilade Agboola: like
244 00:36:31.110 ⇒ 00:36:55.640 Demilade Agboola: from an engineering perspective, like to view it as totally higher perspective, and just trying to understand what exactly we can keep doing to optimize and replicate and ensure that like, Hey, we’re not spending too much time on this being able to come in on people’s projects and just be like, hey? Is there anything you could you need some help with? You seem to have been blocked on this for a couple of days. Like a week. Is there anything that we can either do
245 00:36:56.087 ⇒ 00:37:09.449 Demilade Agboola: to help you out now and then also convert the learnings from that project into things that we can create templates for. And, you know, optimize and all that. So that ability to be able to do that, something that excites me and something I’ll be looking forward to.
246 00:37:09.870 ⇒ 00:37:31.470 Uttam Kumaran: Perfect. Well, let me know, like what you think I mean. I would love to connect you with my business partner. He’s also he’s more coming from the analytics side, like he’s done a lot of stuff in event data modeling, amplitude, mixed panel post hog stuff like that. And my background is more ae side, and probably in the last 3 months we actually merged sort of our companies, because now we offer like full stack
247 00:37:31.630 ⇒ 00:37:56.453 Uttam Kumaran: sort of data for folks I would love for you to talk to him, but also like he I mean, if I I’m gonna tell him that like that we would love to have you so. I think maybe the next step is for you to think about like what would it take in terms of, you know, money in order to have you make a switch. I mean, I want to give you enough time to like Suss this out. I’m happy to introduce you to everybody, or whoever you want to talk to, or you can come sit on meetings, or whatever. But
248 00:37:56.820 ⇒ 00:38:03.669 Uttam Kumaran: I know that it’s rare to meet people like us who get the who kind of get it. And so I definitely want to
249 00:38:03.780 ⇒ 00:38:07.810 Uttam Kumaran: like find a way for this to work out especially, I mean, of course.
250 00:38:07.970 ⇒ 00:38:24.920 Uttam Kumaran: like, you know, Neil and everything. So I know that you get the problems we’re dealing with and for me, I think selfishly about having trying to have a partner on the Ae. Team who kind of gets it right and can be like, almost grow into whatever you want to call them. The manager or whatever, but just sort of like.
251 00:38:25.020 ⇒ 00:38:41.210 Uttam Kumaran: is interested in sort of running this like ae pod of people that, like any client that comes in, we sort of know what the game plan is and what the playbook is, and of course, again, consulting my job is to bring the engineers tougher problems and more money.
252 00:38:41.360 ⇒ 00:38:48.459 Uttam Kumaran: So that’s what I want to go focus on. Right? I want to get the toughest problems. And I want to pay people as much as I can pay them. And
253 00:38:48.900 ⇒ 00:38:54.849 Uttam Kumaran: having someone like you on the team just allows me more time to go focus on those things from the business level.
254 00:38:55.770 ⇒ 00:39:17.439 Demilade Agboola: That’s fair. That’s fair. Yeah, like, I said, that would be something I would definitely really enjoy to do and like cause you when you asked about the managerial technical thing, it’s just like, Yeah, generally, I I at this point, I want to be able to work on both be someone who, like, you know, you can slot things on my calendar. We can figure things out. We can hack the headest problems
255 00:39:17.750 ⇒ 00:39:26.749 Demilade Agboola: like right there right then, but at the same time like I can also, you know, bring the knowledge of like this is how best to solve things.
256 00:39:27.070 ⇒ 00:39:36.090 Demilade Agboola: and actually do the things themselves as well, so that that basically to be able to wear different hats will be will be something that’ll be very useful.
257 00:39:36.441 ⇒ 00:39:40.598 Demilade Agboola: So yeah, I’m excited about this. I really would like to see how far we can take this
258 00:39:40.830 ⇒ 00:39:41.380 Uttam Kumaran: Cool.
259 00:39:41.560 ⇒ 00:39:46.870 Demilade Agboola: This is this, this feels like the next step in my career. So I’m.
260 00:39:46.870 ⇒ 00:39:53.669 Uttam Kumaran: Awesome. I appreciate that. I know it’s a lot. But dude also. What I learned about business is, there’s no rules. So I feel like.
261 00:39:53.810 ⇒ 00:39:57.139 Uttam Kumaran: I meet people, and I know that people get it. And I’m like
262 00:39:57.640 ⇒ 00:40:24.820 Uttam Kumaran: the lovely thing about having no bosses. I sort of can do what I want to do, and so I don’t know. You tell me how you want to move forward like I would love to introduce you to my business partner. Love for you to have a chance to say Hi to him. But even if you, if you know that you have time, part time, would love to even see if you want to just hop in and sort of even just like suss us out a little bit more and join meetings. But of course, like, I wanna be able to make a full time offer and have someone like you come work with us
263 00:40:24.910 ⇒ 00:40:34.949 Uttam Kumaran: for 8 HA day. We do have someone that’s in Spain right now. And we do have people that are in Asia. So time zone is less of a problem, although I would really love someone who can be at least
264 00:40:35.260 ⇒ 00:40:52.849 Uttam Kumaran: at least as much as possible on before, like one pm, because that’s where in all of our like meetings are. But I don’t really care. I again. We only work up. We only think about time zone, because the work’s not getting done. If the work gets done, I don’t. I don’t even care when it gets done. And I I just want to hire the best people wherever they are. So
265 00:40:53.261 ⇒ 00:41:00.580 Uttam Kumaran: that’s sort of our story on like the time zone stuff. You know, and we do a good job of protecting the engineers from like
266 00:41:01.310 ⇒ 00:41:03.800 Uttam Kumaran: meeting directly with clients and having to like
267 00:41:04.060 ⇒ 00:41:22.619 Uttam Kumaran: do show and tell like we try to keep it like I want our engineers to be spending 6 HA day coding right? I leave 2 h for meetings and slack and stuff, but I know how hard it is to like lock in takes an hour to lock in, and then, if you start, get a slack, if you have a call. So that’s why I try to like
268 00:41:22.760 ⇒ 00:41:25.570 Uttam Kumaran: leave the middle of the day free for engineers.
269 00:41:26.930 ⇒ 00:41:47.969 Uttam Kumaran: which is tough because I have to play. I have to sort of like guard off the business side of stuff, but I know dude. It takes 4 h for me to just like even get like one thing done and sit in Vs code and like kind of like, do stuff. So I want to keep. We only have daily stand ups again because we want to get the work done. But also we’re running a remote company. So I think it’s good to to like, meet with people every day.
270 00:41:48.250 ⇒ 00:42:00.400 Demilade Agboola: Yeah, to be fair like that. That’s part of these are kind of things that like like I hear and make. That makes me happy, because, like sometimes, it’s hard to explain to people why I’m not a fan of just like randomly tossing these things in there.
271 00:42:00.400 ⇒ 00:42:04.530 Uttam Kumaran: Same dude. Oh, my God! It’s so worse.
272 00:42:05.230 ⇒ 00:42:06.190 Demilade Agboola: We’ve got to think.
273 00:42:06.190 ⇒ 00:42:11.120 Uttam Kumaran: About my life like I. I had to go on the business side, and it’s so boring like
274 00:42:11.280 ⇒ 00:42:16.870 Uttam Kumaran: it’s like meeting, meeting meeting and no. And then nobody thinks about any other problem like engineering where I’m like
275 00:42:17.010 ⇒ 00:42:21.089 Uttam Kumaran: as we’ve seen this before, like I said, can we just like create a process and like.
276 00:42:21.300 ⇒ 00:42:28.630 Uttam Kumaran: and I think about it the same way. But again, I want this to be the best place to work for data people. And I do think it helps
277 00:42:28.770 ⇒ 00:42:37.059 Uttam Kumaran: that. I’m very opinionated about getting data work done. I feel like I struggle because I’m jumping from 10 things. I still find a way to get it done. But
278 00:42:37.210 ⇒ 00:43:04.809 Uttam Kumaran: the way, just because I can get it done doesn’t mean everybody’s schedule needs to be like that. In fact, I’m very. I look at people’s calendars, and I get people out of slack channels. I’m like always thinking about how to reduce the cognitive load so that you have 6 h of core core engineering time. You can spend that talking to people doing whatever. But without that nothing gets done. Right. We will be if it’ll be Friday, and you’ll be like I never even found an hour to push like one line. Pr.
279 00:43:04.980 ⇒ 00:43:07.019 Uttam Kumaran: And I hate those weeks.
280 00:43:07.278 ⇒ 00:43:17.349 Demilade Agboola: Honestly, yeah, I I totally. And and sometimes it’s just like you have a 30 min meeting, a 30 min break, and then a 30 min meeting, and you know that that 30 min break doesn’t really count, because.
281 00:43:17.350 ⇒ 00:43:19.170 Uttam Kumaran: I’m gonna watch Youtube the whole time.
282 00:43:20.340 ⇒ 00:43:21.329 Demilade Agboola: Until I get into that.
283 00:43:21.330 ⇒ 00:43:22.969 Uttam Kumaran: Because what are you gonna do? Yeah, or.
284 00:43:22.970 ⇒ 00:43:23.470 Demilade Agboola: Okay, so.
285 00:43:23.470 ⇒ 00:43:27.444 Uttam Kumaran: Onto slack messages all day. And like, yeah, dude, it’s hard. And I
286 00:43:28.710 ⇒ 00:43:36.489 Uttam Kumaran: and I don’t know it’s I think it’s gonna be endless battle, but I don’t know. I feel like I feel lucky that I was an engineer, and so I
287 00:43:36.760 ⇒ 00:43:38.660 Uttam Kumaran: I look at our company like
288 00:43:39.560 ⇒ 00:44:01.740 Uttam Kumaran: not as like, you know. They say something like, Do as I don’t do as I do as I say, but not as I do like. I think about that a lot. And I’m like, if I if I’m not able to do it like, how do we require this? And how do we build a team of great engineers, like some people, will come to us from all sorts of backgrounds. Our goal in the 1st 3 months is they become brain forge engineers, right, like wherever background they came from.
289 00:44:02.200 ⇒ 00:44:13.400 Uttam Kumaran: We want to set them up for success, because people will realize, wow! If I get 6 h of free time, I trust that people aren’t gonna just like waste, that they’re gonna be like, actually be able to lock in and do
290 00:44:13.450 ⇒ 00:44:36.109 Uttam Kumaran: like really large scale data model changes, testing all those things like the things that you’re. It’s almost like I describe it like picking the trash up off the floor type stuff where it’s like you’re running around. You’re never gonna do that. But if you have time you’re like, Hey, let me go. Do some documentation. Let me let me let me go redo some big refactor where I put everything in folders renames dude. That stuff takes like hours and hours to do. You know.
291 00:44:36.270 ⇒ 00:44:42.319 Demilade Agboola: Yeah. And I think when you’re in that zone or when you’re in that space, you, it’s only productive
292 00:44:42.450 ⇒ 00:44:49.189 Demilade Agboola: messaging when they are the ones that have to reach out. So like you run into an issue. And now you need someone to help you.
293 00:44:49.410 ⇒ 00:44:49.930 Uttam Kumaran: Yes.
294 00:44:49.930 ⇒ 00:44:53.350 Demilade Agboola: You have a question about like how those you know.
295 00:44:53.350 ⇒ 00:44:54.450 Uttam Kumaran: It’s on your terms.
296 00:44:54.450 ⇒ 00:44:55.750 Demilade Agboola: On your term. So like, yeah.
297 00:44:55.750 ⇒ 00:44:56.190 Uttam Kumaran: Yes.
298 00:44:56.190 ⇒ 00:45:06.039 Demilade Agboola: It doesn’t take you out of the zone, you know. You need it to progress in your zone. That is useful. But if you’re just like slacking them, or they have to like respond to this or this.
299 00:45:06.040 ⇒ 00:45:06.800 Uttam Kumaran: Hard.
300 00:45:07.470 ⇒ 00:45:08.190 Demilade Agboola: It’s a quick
301 00:45:08.190 ⇒ 00:45:20.099 Demilade Agboola: you need to hop into like, yeah, it kind of just throws you off every time you come back in. You’re like, where do I stop? It’s hard to now focus. So I usually find out that a lot of times, especially if I have like meeting heavy days.
302 00:45:20.290 ⇒ 00:45:23.539 Demilade Agboola: I end up having to work at night like best audio.
303 00:45:23.540 ⇒ 00:45:26.020 Uttam Kumaran: No suit me, too. Oh, my God, yeah, it’s like.
304 00:45:26.020 ⇒ 00:45:31.830 Demilade Agboola: So I end up having, like 10 h, days, or something cause like. I know that when I can get the time to work.
305 00:45:31.830 ⇒ 00:45:32.410 Uttam Kumaran: Yeah.
306 00:45:32.410 ⇒ 00:45:37.239 Demilade Agboola: By the end of the day, where everyone’s gone offline, I can just be in my zone.
307 00:45:37.370 ⇒ 00:45:41.749 Demilade Agboola: put on my computer like with the monitor and just work until.
308 00:45:41.750 ⇒ 00:45:42.430 Uttam Kumaran: Yes.
309 00:45:42.430 ⇒ 00:45:44.569 Demilade Agboola: Like I. I get what I need to get to it for.
310 00:45:44.570 ⇒ 00:45:48.320 Uttam Kumaran: But imagine you have it in the middle of the day. It’s like, Oh, my God!
311 00:45:48.320 ⇒ 00:45:50.226 Uttam Kumaran: I’ll cry.
312 00:45:51.300 ⇒ 00:46:03.240 Demilade Agboola: Like, I said, it’s things like that that just like when I hear things like this, it does make me feel like, yeah, this this is something like this is a space that understands like problems I’ve had, and also like sees things in the same way, I kind of see them.
313 00:46:03.737 ⇒ 00:46:12.820 Demilade Agboola: Yeah, I’m open to like a full time offer in the sense of at this point, like, like I said, I was actually just like looking for the next thing for my career.
314 00:46:13.731 ⇒ 00:46:18.090 Demilade Agboola: I’m definitely open to seeing like how we can make things work full time.
315 00:46:18.711 ⇒ 00:46:26.198 Demilade Agboola: and just seeing like how I can come in, optimize the processes and just trying to see. Hey, how about we try this instead?
316 00:46:26.720 ⇒ 00:46:35.420 Demilade Agboola: be ready for some push back. I I do tend to have like opinions, but like it’s all to optimize us. Download my own thing. I will be
317 00:46:35.690 ⇒ 00:46:37.300 Demilade Agboola: said in, you know.
318 00:46:38.010 ⇒ 00:46:42.731 Demilade Agboola: like, Hey, how about we optimize it this way. How can how can we look at it this way?
319 00:46:44.420 ⇒ 00:47:00.509 Demilade Agboola: I always feel like all these things as like I see my perspective. You see your perspective. We can have this conversations. And just figure out the idea is, how do we push these things as quickly as possible? And how do we get to the point where people are optimized to set up for success? The team generally, as well as the business, so.
320 00:47:01.320 ⇒ 00:47:14.370 Uttam Kumaran: I think 2 things that I’ll leave you with and and also over email, I’ll connect you with my business partner. I think 2 things. One think about sort of what you would need in terms of money to move over and like what? What like, what a package could look like.
321 00:47:14.490 ⇒ 00:47:36.770 Uttam Kumaran: I think, the only caveat I’ll give. There is 2 things, one, we’re we’re working on a process to try to incentivize everybody to grow. And and one of our company principles is, everybody eats which a lot of people didn’t know what that meant. And I’m like, Okay, I’m the only one like Rep, listening to rap music. And like, I’m like, no, nobody knows. What was that? What do you mean? Nobody knows what that means. But basically, I’m like.
322 00:47:36.900 ⇒ 00:47:55.670 Uttam Kumaran: I want to create a layered approach that if the company wins people everybody wins. If the client you’re working on wins the people working on the client wins. I think I don’t know how it was a data culture, but I think it’s really rare in engineering for people to think about incentive based compensation. However, I
323 00:47:55.990 ⇒ 00:48:02.699 Uttam Kumaran: I don’t know why, because that’s because you don’t have good attribution to how work is attributed to a success right?
324 00:48:03.039 ⇒ 00:48:08.750 Uttam Kumaran: And so for me, I’m I’m worth think spending more time thinking about. If a client renews with us, if a client
325 00:48:08.780 ⇒ 00:48:33.549 Uttam Kumaran: expands with us, and if the company overall makes a profit, how do we share that with the team? And so we’re trying to think about how that becomes a component of pay as well. We’re just working on it. It’s like on the laundry list of things we’re doing. But that’s something that I want to also commit to is that I think we’re gonna make that a component that if things go well, you actually will make way more than
326 00:48:33.870 ⇒ 00:49:02.220 Uttam Kumaran: like anywhere else, you would be doing this job and that way. It gives people like the incentive to say, Okay, if this client renews, there’s this amount. But if they love us so much that they they like, give us more work. Then there’s this much. And then also, if, like overall as a company, we then hit something, there’s there’s some sort of percentage. So we’re working on that. I think I’ll let. I’ll let robert, my business partner, talk a little bit more about that but sort of if you have some time over the next day or 2 to think about that. We move
327 00:49:02.500 ⇒ 00:49:06.889 Uttam Kumaran: very quickly, so I would love to try to see how we can.
328 00:49:07.110 ⇒ 00:49:11.730 Uttam Kumaran: you know, come to an agreement even this week or earlier, and sort of see how we can
329 00:49:12.230 ⇒ 00:49:16.404 Uttam Kumaran: get you to hop on stuff. I I would I would love nothing more than that. So
330 00:49:16.760 ⇒ 00:49:18.020 Uttam Kumaran: yeah, let me know.
331 00:49:18.500 ⇒ 00:49:20.339 Demilade Agboola: Sounds good. I am.
332 00:49:20.630 ⇒ 00:49:22.939 Demilade Agboola: We’ll let you like, probably looking out for the email.
333 00:49:22.940 ⇒ 00:49:24.190 Uttam Kumaran: I’ll send an email. Yeah.
334 00:49:24.190 ⇒ 00:49:28.680 Demilade Agboola: Alright sounds good. And yeah, I’m open to a switch.
335 00:49:29.873 ⇒ 00:49:31.760 Demilade Agboola: Currently on
336 00:49:33.770 ⇒ 00:49:44.807 Demilade Agboola: I’m currently available for like any offers. And just being able to like. Figure that out. I will. Maybe when I have conversation with Robert, I will try and think of what incentives look like, but I will just also get like
337 00:49:45.440 ⇒ 00:49:50.210 Demilade Agboola: also, like a scope of how these things work with your company.
338 00:49:50.210 ⇒ 00:49:50.890 Uttam Kumaran: Definitely.
339 00:49:51.300 ⇒ 00:49:52.500 Uttam Kumaran: Yeah.
340 00:49:53.740 ⇒ 00:50:01.909 Uttam Kumaran: perfect. Yeah. All good questions. Any question is on the table. So feel free to ask about anything. And again, I’m happy to introduce you to engineers on the team, or whoever I mean.
341 00:50:02.060 ⇒ 00:50:10.350 Uttam Kumaran: You know. Also, I’m happy to add you to meetings, or whatever you you wanna take a look at. But I’ll I’ll send an email and have an introduce to Robert, and then we can go from there.
342 00:50:10.620 ⇒ 00:50:11.560 Demilade Agboola: Alright, sounds good.
343 00:50:11.560 ⇒ 00:50:14.460 Uttam Kumaran: Okay, yeah, really. Great to meet you, man, hopefully. Talk soon.
344 00:50:14.610 ⇒ 00:50:15.290 Demilade Agboola: Talk, soon.
345 00:50:15.290 ⇒ 00:50:16.070 Uttam Kumaran: Okay? Bye.