Meeting Title: Uttam <> Abigail-Weekly Date: 2024-09-17 Meeting participants: Abigail Zhao, Uttam Kumaran
WEBVTT
1 00:00:57.320 ⇒ 00:00:58.250 Uttam Kumaran: Hey!
2 00:01:00.760 ⇒ 00:01:01.375 Abigail Zhao: Hi.
3 00:01:01.990 ⇒ 00:01:03.860 Uttam Kumaran: Hey? What’s up? How’s the week?
4 00:01:04.560 ⇒ 00:01:08.649 Abigail Zhao: Good. So far. Low key, like already. Kind of tired. But it’s okay.
5 00:01:09.630 ⇒ 00:01:14.250 Uttam Kumaran: Yeah. Same. Last 2 days I’ve been like.
6 00:01:15.140 ⇒ 00:01:18.779 Uttam Kumaran: but basically it was in meetings from like 9 to 3.
7 00:01:19.840 ⇒ 00:01:23.720 Uttam Kumaran: And like it’s just tough cause, like, I just sit here and I’m like
8 00:01:23.930 ⇒ 00:01:26.550 Uttam Kumaran: talk. I just talked like 8 h, and I’m like.
9 00:01:26.750 ⇒ 00:01:29.580 Uttam Kumaran: where am I like? What am I doing?
10 00:01:29.850 ⇒ 00:01:31.060 Uttam Kumaran: Oh.
11 00:01:32.270 ⇒ 00:01:33.470 Abigail Zhao: Yup!
12 00:01:34.000 ⇒ 00:01:35.829 Uttam Kumaran: We actually just kicked off a pro
13 00:01:35.880 ⇒ 00:01:48.719 Uttam Kumaran: project with Brian. Actually, he’s working on Javi coffee. So he started that today. And then we kicked off our project with Bitecoco. The Coconut Water Company.
14 00:01:49.020 ⇒ 00:01:49.320 Abigail Zhao: Yeah.
15 00:01:49.320 ⇒ 00:01:53.918 Uttam Kumaran: So we’re doing some like AI stuff for them.
16 00:01:55.430 ⇒ 00:02:00.069 Uttam Kumaran: so yeah, what’s been up? I know we didn’t get a chance to talk last week.
17 00:02:01.490 ⇒ 00:02:08.373 Uttam Kumaran: but I think the biggest thing. I I haven’t seen any stuff in the Channel, but I know last time we talked about
18 00:02:08.850 ⇒ 00:02:16.872 Uttam Kumaran: some of the medical stuff with Chang. I guess he hasn’t sent anything yet but I think mainly that. And I know we talked about the
19 00:02:17.340 ⇒ 00:02:21.058 Uttam Kumaran: updating that like, lead street. I mean, the
20 00:02:22.198 ⇒ 00:02:25.339 Uttam Kumaran: what’s it called like the competitor sheet. Right? Yeah.
21 00:02:27.820 ⇒ 00:02:31.470 Uttam Kumaran: yeah. Those. I think those are still, probably like the the biggest things.
22 00:02:32.157 ⇒ 00:02:38.250 Uttam Kumaran: But yeah, let me know. If you’ve if you’ve been able to take a crack at any of that, or if you need any feedback from me.
23 00:02:38.490 ⇒ 00:02:42.810 Abigail Zhao: Okay, yeah. I mean, I’m still just kind of working through it right now, like.
24 00:02:43.521 ⇒ 00:02:46.170 Abigail Zhao: fiddling around in Apollo and stuff like that.
25 00:02:46.170 ⇒ 00:02:46.860 Uttam Kumaran: Okay.
26 00:02:46.860 ⇒ 00:02:49.799 Abigail Zhao: Nothing is like totally done yet. But yeah, I’ll let you know when
27 00:02:50.270 ⇒ 00:02:51.540 Abigail Zhao: it’s already.
28 00:02:51.950 ⇒ 00:02:56.909 Uttam Kumaran: Okay, cool. Yeah. And I know I messaged you. I think the kind of the biggest thing I’m thinking about is like.
29 00:02:57.316 ⇒ 00:03:00.780 Uttam Kumaran: a lot of folks, especially some of the interns we have this summer.
30 00:03:00.820 ⇒ 00:03:07.700 Uttam Kumaran: We put together a little bit of like a data curriculum, and I’m starting to think through like what that could look like. And basically, how do we?
31 00:03:08.160 ⇒ 00:03:11.110 Uttam Kumaran: How do we internally, basically like
32 00:03:11.390 ⇒ 00:03:14.940 Uttam Kumaran: level people up and train people to go from like 0 to one
33 00:03:15.030 ⇒ 00:03:17.830 Uttam Kumaran: in like data, engineering and data modeling.
34 00:03:18.370 ⇒ 00:03:20.029 Uttam Kumaran: And then, like data analysis.
35 00:03:20.060 ⇒ 00:03:22.540 Uttam Kumaran: I’m kind of starting to work on like
36 00:03:23.200 ⇒ 00:03:26.050 Uttam Kumaran: what that curriculum kind of looks like.
37 00:03:26.260 ⇒ 00:03:27.789 Uttam Kumaran: And basically, how
38 00:03:28.150 ⇒ 00:03:40.900 Uttam Kumaran: how internally, we can best like. Let people kind of self pace and study. And I guess for you the biggest thing would be like learning like how to do kind of some of the actual like data work that we do. But then, at the same time.
39 00:03:41.251 ⇒ 00:03:49.120 Uttam Kumaran: how do we build a system where, like me or Patrick, or the other folks on the team that are that do the work can like kind of
40 00:03:49.330 ⇒ 00:03:55.110 Uttam Kumaran: have like office hours, or something like that. I think the biggest thing I’m thinking about is like, how do we?
41 00:03:55.310 ⇒ 00:04:08.620 Uttam Kumaran: How do we provide? How do I provide like enough like interactive stuff as well as stuff to read, and then like real examples for people to work on. Of course, it’s going to be tough, because anything that’s client work is like
42 00:04:08.880 ⇒ 00:04:21.939 Uttam Kumaran: is is going to be like under the gun type work. So I’m trying to not throw people at that. I think. Instead, it’s like, is there work that we can do internally? Or is there stuff we can hold presentations on
43 00:04:22.000 ⇒ 00:04:24.220 Uttam Kumaran: and things like that. But interested in like.
44 00:04:24.370 ⇒ 00:04:30.889 Uttam Kumaran: do you have any ideas about like what would be the best way cause I learned just by like taking online courses and like.
45 00:04:30.890 ⇒ 00:04:31.470 Abigail Zhao: No.
46 00:04:31.470 ⇒ 00:04:33.904 Uttam Kumaran: But also like doing the job.
47 00:04:34.530 ⇒ 00:04:37.249 Uttam Kumaran: so yeah, I don’t know if you have any thoughts.
48 00:04:37.980 ⇒ 00:04:46.830 Abigail Zhao: I would say, like me. Personally, I work. I learn best just by like doing like I feel like if you gave me a reading, or something like
49 00:04:46.900 ⇒ 00:04:51.210 Abigail Zhao: I I’ll read it, but, like I I can’t promise I’ll retain, like all of it.
50 00:04:51.210 ⇒ 00:04:51.980 Uttam Kumaran: Yeah.
51 00:04:52.680 ⇒ 00:05:00.539 Abigail Zhao: But yeah, I understand what you mean about like, client work like client work like that, honestly, might be like, too high stakes. Yeah.
52 00:05:00.690 ⇒ 00:05:01.900 Abigail Zhao: but
53 00:05:01.920 ⇒ 00:05:14.670 Abigail Zhao: yeah, like, I think any like online course could probably be helpful like any online course where, like, basically, I would also be doing like some level of like coding alongside with it, or whatever like type of data work stuff.
54 00:05:15.660 ⇒ 00:05:16.480 Uttam Kumaran: Okay.
55 00:05:16.480 ⇒ 00:05:17.349 Abigail Zhao: That I need to.
56 00:05:17.350 ⇒ 00:05:29.479 Uttam Kumaran: Yeah, let me think, because the biggest things is like, I want people to be familiar with like Snowflake, dbt, and like some analysis, but I’m kind of want to think about like how we can get people towards
57 00:05:29.720 ⇒ 00:05:46.220 Uttam Kumaran: like, for example, it’s like, How do I? How do we provide some people that are consistent, but like include, like different mediums of learning, like things. You can read things you can watch and things you can do, because for me. It’s like you kind of pick which one you start with, and you may go back to the reading, and you may want to watch something, and it’s like.
58 00:05:46.280 ⇒ 00:05:51.839 Uttam Kumaran: how do we set up like, okay, what is like, what are each of the key areas to kind of do that?
59 00:05:51.860 ⇒ 00:06:05.060 Uttam Kumaran: I would say we had a lot of people that have come in from 0. And then I think the biggest challenge is like, like, Okay, how do I start? And there’s just like so much. So I’m trying to think of like what the best things, what the best like, I mean ideally
60 00:06:05.160 ⇒ 00:06:17.489 Uttam Kumaran: as free as possible until we get to a point where it’s like cool. There’s like, actually like a really great course that maybe you should take that like walks you through this or this certification that you can get? So I’m kind of thinking about that.
61 00:06:17.895 ⇒ 00:06:24.840 Uttam Kumaran: So maybe I’ll work on something, and I can share that I have, like most of the day, blocked off tomorrow for
62 00:06:25.040 ⇒ 00:06:41.139 Uttam Kumaran: for writing. So I’ll be kind of like working on that alongside some other stuff. And then, yeah, I also message just about like, if sometime in the future, I think like, try to convert this into something paid. I just feel like I I wanna make sure that people that work for us
63 00:06:41.180 ⇒ 00:07:03.140 Uttam Kumaran: are getting one experience, of course, but also like, if I can, if I can send any cash your way that we can afford. I’m happy to so also, like it, make sure that people are bought in. But also, like we appreciate, like basically all the work, cause it’s been really, really helpful. So that’s what I’m kind of thinking about. I’ll have to think a little bit
64 00:07:03.970 ⇒ 00:07:23.020 Uttam Kumaran: like what what that means, and then also kind of get will include probably some commitment in terms of like cool. We’re gonna try to aim for like this amount of time. And this amount of time per week. But that way, hopefully, it allows you to get a little bit more bought in. And then, of course, like we appreciate, like all the effort. And I think things are just going to get
65 00:07:23.310 ⇒ 00:07:30.910 Uttam Kumaran: more busy. And there’s gonna be more people involved in the sales side in the next week or 2. That I’m like interviewing. And so
66 00:07:30.920 ⇒ 00:07:35.780 Uttam Kumaran: I just wanna make sure it doesn’t feel it. I wanna make sure there’s 2 feelings, is one there’s still like
67 00:07:35.890 ⇒ 00:07:37.950 Uttam Kumaran: you’re learning a lot, but also
68 00:07:38.680 ⇒ 00:07:46.770 Uttam Kumaran: doing free work, for someone is like one thing. But this isn’t volunteer. This is like a money making operation, and I am very aware of that. So I want to make sure that it’s like
69 00:07:46.780 ⇒ 00:07:53.560 Uttam Kumaran: we just don’t have a bunch of unpaid interns, and we’re making a lot of money off them. That’s like, not the goal. Actually, it’s actually just like.
70 00:07:53.650 ⇒ 00:08:02.269 Uttam Kumaran: I think this is a really great experience, something hopefully that you could put on your resume. But also I want to find ways to make sure everyone is compensated in some manner.
71 00:08:03.530 ⇒ 00:08:13.296 Uttam Kumaran: so I’m kind of figuring it out with with like our lawyers and like how to we’re we’re doing a big revamp of a bunch of contracts, too. So but just so, you know, hopefully that
72 00:08:13.900 ⇒ 00:08:15.849 Uttam Kumaran: sweetens the deal a little bit.
73 00:08:16.671 ⇒ 00:08:22.149 Abigail Zhao: Yeah, okay, yeah. I mean, take your time. I’m not like in any like.
74 00:08:23.200 ⇒ 00:08:25.799 Abigail Zhao: I don’t. I don’t know how how to phrase it. I’m not like.
75 00:08:25.800 ⇒ 00:08:27.269 Uttam Kumaran: And I know what you’re gonna see. Yeah.
76 00:08:28.240 ⇒ 00:08:35.699 Uttam Kumaran: no. But it’s actually I I know. And it’s but it’s more for, like I I want to make I for me. I also have peace of mind that, like.
77 00:08:36.309 ⇒ 00:08:40.759 Uttam Kumaran: You’re committed to to doing work for us consistently. And then also
78 00:08:41.038 ⇒ 00:08:56.539 Uttam Kumaran: you know, we’ve had interns kind of flow in and out, and people come in and floating around. The one thing about. If you get people who work for free, you can’t guarantee anything. And so for me it’d be like cool like, if this would basically love be like cool. You have 10 h of work, and then we continue to roll that over. And then again, the company’s growing
79 00:08:56.969 ⇒ 00:08:58.519 Uttam Kumaran: like as
80 00:08:58.699 ⇒ 00:09:04.439 Uttam Kumaran: the the less I sleep the more the company grows. So like, that’s that’s basically what happens. And so
81 00:09:04.469 ⇒ 00:09:07.549 Uttam Kumaran: over, especially over the next month we’re going to see a lot more activity.
82 00:09:07.859 ⇒ 00:09:10.259 Uttam Kumaran: I could. I could just feel it. So.
83 00:09:10.670 ⇒ 00:09:14.479 Uttam Kumaran: That’s it. That’s that’s my main kind of idea. So
84 00:09:16.159 ⇒ 00:09:16.899 Uttam Kumaran: yeah.
85 00:09:16.900 ⇒ 00:09:18.459 Abigail Zhao: Okay. Yeah. Sounds good.
86 00:09:18.920 ⇒ 00:09:21.380 Uttam Kumaran: Cool. Anything else?
87 00:09:21.470 ⇒ 00:09:26.209 Uttam Kumaran: I can answer any any other questions, or anything to chat about.
88 00:09:27.330 ⇒ 00:09:28.450 Abigail Zhao: Hmm!
89 00:09:28.860 ⇒ 00:09:32.420 Abigail Zhao: Nothing. I can think off the top of my head right now. But
90 00:09:32.530 ⇒ 00:09:33.610 Abigail Zhao: yeah.
91 00:09:33.920 ⇒ 00:09:36.753 Uttam Kumaran: Yeah, I know we we were. Gonna we were planning to have
92 00:09:37.240 ⇒ 00:09:43.160 Uttam Kumaran: like sales meetings and stuff. But it’s just been like, if you look at my calendar I’m having like a nightmare 2 days.
93 00:09:43.501 ⇒ 00:09:55.000 Uttam Kumaran: But I’m also trying to be organized. And I want I’m gonna I’m gonna follow up with Chang after this, and just ping him, and just say, Hey, Abigail’s ready to kind of take on any notes that you have on the medical side.
94 00:09:55.040 ⇒ 00:09:59.739 Uttam Kumaran: And then, yeah, maybe whenever you’re ready on the competitive side.
95 00:10:00.100 ⇒ 00:10:02.020 Uttam Kumaran: let me know and and grab
96 00:10:02.240 ⇒ 00:10:23.019 Uttam Kumaran: 2030 min to chat through that. I found that document from another like kind of like data guy in the space who like compile that list. It’d be really nice to like, compile that and publish it back out, but also like, just keep for our records like who all the people are, because I reference that list a lot to look at like who’s still active?
97 00:10:24.760 ⇒ 00:10:26.919 Uttam Kumaran: so I’m really looking forward to that. So.
98 00:10:28.016 ⇒ 00:10:33.460 Abigail Zhao: Do you just want me to like? Add it to the like spreadsheet, like whatever I find or like.
99 00:10:33.460 ⇒ 00:10:43.370 Uttam Kumaran: Yeah, like, I, yeah, I would just add them to there and then you can see how they have like different columns. But you could use whatever you find in Apollo, you may maybe add all the data.
100 00:10:43.470 ⇒ 00:10:57.119 Uttam Kumaran: and then you can make you can add in all the data in one sheet and then bring it over to the master sheet, or you can create like a new one. But some of the some of those companies that are on there now don’t exist anymore. I also don’t know how to like
101 00:10:57.260 ⇒ 00:10:58.340 Uttam Kumaran: how to like.
102 00:10:58.470 ⇒ 00:11:01.620 Uttam Kumaran: remove them or like, how do I find out that they don’t exist.
103 00:11:01.650 ⇒ 00:11:04.779 Uttam Kumaran: But, like 1st things first, st see if you can just go through and add.
104 00:11:05.530 ⇒ 00:11:11.399 Uttam Kumaran: like all of them, and and see like. And I would click around click around and make sure that they are like in our industry, or
105 00:11:11.500 ⇒ 00:11:17.059 Uttam Kumaran: like data consultancies, basically the big things you’re looking at data, analytics or data modeling.
106 00:11:18.490 ⇒ 00:11:40.109 Uttam Kumaran: But then, yeah, I think that’ll be really cool. And I wanna, I’m providing that to all of our designers and content people to basically look at for inspiration. So that’s really where it’s going is like, when people say, like, Okay, what are like people in our industry doing? I kind of want to send them that list of like. Here’s everyone in our industry. So poke around and see kind of how people are doing things. So. And then, you know. Eventually we’ll
107 00:11:40.210 ⇒ 00:11:50.790 Uttam Kumaran: I ideally, what I want to do is basically use AI to scrape each of them like once a month, and so we can keep tabs on like what new things people are doing or changes.
108 00:11:52.330 ⇒ 00:11:57.670 Uttam Kumaran: so that’ll be like probably something I I’ll ask you to work with Miguel on. Once we have the list going.
109 00:11:59.130 ⇒ 00:12:00.540 Abigail Zhao: Okay. Sound. Good.
110 00:12:01.110 ⇒ 00:12:01.720 Uttam Kumaran: Cool.
111 00:12:01.970 ⇒ 00:12:08.230 Uttam Kumaran: Okay? Well, if nothing else, let me know if I can help with anything but probably talk tomorrow or Thursday.
112 00:12:09.046 ⇒ 00:12:10.179 Abigail Zhao: Okay, cool.
113 00:12:10.180 ⇒ 00:12:12.010 Uttam Kumaran: Okay. Thanks. Abigail.
114 00:12:12.010 ⇒ 00:12:14.200 Abigail Zhao: Yeah. Have a good day bye.