Meeting Title: Uttam <> Annie Date: 2025-05-05 Meeting participants: Annie Yu, Uttam Kumaran
WEBVTT
1 00:00:19.560 ⇒ 00:00:21.080 Annie Yu: Oh, hello! Tom!
2 00:00:21.080 ⇒ 00:00:23.559 Uttam Kumaran: Hey! How are you sorry for the delay?
3 00:00:24.230 ⇒ 00:00:26.419 Annie Yu: No worries. How’s it going.
4 00:00:26.420 ⇒ 00:00:29.800 Uttam Kumaran: Good good hold on. My dog is just trying to get in the get in the roof.
5 00:00:29.800 ⇒ 00:00:33.679 Annie Yu: Oh, right!
6 00:00:34.660 ⇒ 00:00:37.560 Uttam Kumaran: This is my. My boss is like making sure I’m working.
7 00:00:39.816 ⇒ 00:00:42.970 Annie Yu: Love, that.
8 00:00:42.970 ⇒ 00:00:44.180 Uttam Kumaran: How’s everything?
9 00:00:44.720 ⇒ 00:01:01.079 Annie Yu: Pretty good, pretty good. I think I’m I’m having a and this is rare like a light day today. So I’m going through me, and always document. And he asked me to to make some kind of organization or forwarding. So I’m gonna
10 00:01:01.080 ⇒ 00:01:01.590 Annie Yu: yes.
11 00:01:02.860 ⇒ 00:01:03.490 Uttam Kumaran: Nice.
12 00:01:04.090 ⇒ 00:01:09.100 Uttam Kumaran: Yeah, how do you? How is how is stuff going these last few weeks? Like, I feel like we talked maybe 2 weeks ago.
13 00:01:09.950 ⇒ 00:01:13.360 Annie Yu: I think so. Yeah, I feel like it’s been. It’s been a while since we like.
14 00:01:13.360 ⇒ 00:01:17.279 Uttam Kumaran: Yeah, yeah, every day for me. Seems like 2 weeks. So I just like.
15 00:01:18.270 ⇒ 00:01:22.680 Uttam Kumaran: I just wanna make sure I try to talk to everybody last the last 3 weeks I’ve actually been like
16 00:01:23.200 ⇒ 00:01:26.900 Uttam Kumaran: probably the most insane it’s ever been, and of course, like
17 00:01:27.150 ⇒ 00:01:30.195 Uttam Kumaran: last 3 months, have been also like very, very insane.
18 00:01:30.500 ⇒ 00:01:30.850 Annie Yu: Yeah.
19 00:01:31.790 ⇒ 00:01:37.690 Uttam Kumaran: But I it’s like, really, I think we’re in a great spot right now where
20 00:01:37.850 ⇒ 00:01:46.970 Uttam Kumaran: I look at the team we have. People are crushing it. We have a bit of extra capacity which is fine. I think I’m seeing that
21 00:01:47.130 ⇒ 00:01:51.670 Uttam Kumaran: across every single person in data everybody has like a
22 00:01:52.300 ⇒ 00:02:12.890 Uttam Kumaran: key like superpower as well as like a key interest in where they want to grow. The other thing is like, finally, I’m seeing that, like different people are meeting different people without me setting it up, which I’m very, very happy about, like I, I know amber does a really good job with meeting different people.
23 00:02:14.190 ⇒ 00:02:15.607 Uttam Kumaran: I know that.
24 00:02:16.650 ⇒ 00:02:29.480 Uttam Kumaran: like, the AI team is working with the data team. You and a wish are working together like it just makes me very, very happy, because that’s some sort that’s something that we always operated a company almost of like, just like freelancers.
25 00:02:30.020 ⇒ 00:02:34.919 Uttam Kumaran: And it’s tough like, I never wanted to run a company like that. I just couldn’t afford
26 00:02:35.330 ⇒ 00:02:38.380 Uttam Kumaran: time, wise or like money wise to
27 00:02:38.570 ⇒ 00:02:45.940 Uttam Kumaran: get people that were like working for Brainforge. People were like, I’m doing some 10 h here for Brainforge for 20 h. And so
28 00:02:46.210 ⇒ 00:02:51.800 Uttam Kumaran: it’s great. I think we’re spending a lot more time on sales tons, more time on marketing
29 00:02:52.292 ⇒ 00:02:59.170 Uttam Kumaran: and like, I’m pretty confident we’re gonna bump up our revenue like 20 or 30% in the next, like 2 months.
30 00:02:59.670 ⇒ 00:03:01.199 Uttam Kumaran: So like, it’s like.
31 00:03:01.200 ⇒ 00:03:01.810 Annie Yu: Wow!
32 00:03:01.810 ⇒ 00:03:03.476 Uttam Kumaran: Sort of like getting better.
33 00:03:03.810 ⇒ 00:03:04.195 Annie Yu: Yeah.
34 00:03:04.580 ⇒ 00:03:08.650 Uttam Kumaran: Very so. I’m like, very knock on wood, but it’s it’s it’s getting a lot better.
35 00:03:09.513 ⇒ 00:03:11.240 Annie Yu: yeah, I think I,
36 00:03:11.460 ⇒ 00:03:16.200 Annie Yu: I really like, don’t have visibility. Before I join so i
37 00:03:16.650 ⇒ 00:03:26.550 Annie Yu: like i’ve heard you and Robert, saying, that like, we are getting like, things are shaping up better. But I just, I don’t really know what it was like before. But
38 00:03:26.870 ⇒ 00:03:28.210 Annie Yu: yeah, I’m okay.
39 00:03:28.210 ⇒ 00:03:41.809 Uttam Kumaran: It’s also, you know, from a data perspective, we measured on 2 things I look at like how many sales meetings we’re having, how many proposals we’re sending out, and we were in a position where we’re maybe sending out one or 2 proposals
40 00:03:42.280 ⇒ 00:03:46.470 Uttam Kumaran: every other week. Now we’re sending about 5 a week.
41 00:03:47.490 ⇒ 00:03:48.630 Annie Yu: Oh, wow! Every.
42 00:03:48.630 ⇒ 00:03:59.810 Uttam Kumaran: And we’re sending almost one every day like I sent one we sent one today. I’ll send another tomorrow. I’ll just. I have to send another one today, another one tomorrow.
43 00:04:00.230 ⇒ 00:04:01.200 Uttam Kumaran: So like.
44 00:04:01.710 ⇒ 00:04:20.570 Uttam Kumaran: And it’s just a funnel. Right? So we have conversations with people. They establish the couple of things. How we qualify? I talk, I look at, is there actually a problem like, is it a data problem or an AI problem that we can solve? Is there urgency like, does it actually matter if we solve it? And then, 3rd is their budget
45 00:04:20.940 ⇒ 00:04:26.420 Uttam Kumaran: you get people with? Sometimes we’ll have one or 2 of those they’ll be like. This is totally a problem. And it is a data problem.
46 00:04:26.660 ⇒ 00:04:28.180 Uttam Kumaran: But we’re broke, and I’m like.
47 00:04:29.250 ⇒ 00:04:50.050 Uttam Kumaran: alright. But like before, we would chase those because I would never, I never had the courage to ask, is there actually money? Here’s our budget. Now we’re like confident. So I can rule people out really quickly, and those people don’t get rolled out, they forever. They just were to say, Hey, you may not be able to afford us. Here’s a partner of ours. Or maybe we can work together in the future. So
48 00:04:50.560 ⇒ 00:05:00.749 Uttam Kumaran: once we get to that funnel, we then have to then scope out the project, get them to basically verbally say, this is the scope I want. I’m okay with the price. And then we sent the we send.
49 00:05:00.920 ⇒ 00:05:07.089 Uttam Kumaran: We basically send them the contract to sign. So we’re getting people. We’re getting a lot more people to the next phase.
50 00:05:07.885 ⇒ 00:05:10.010 Annie Yu: A lot faster, which is.
51 00:05:10.480 ⇒ 00:05:12.039 Uttam Kumaran: Just great, you know.
52 00:05:12.410 ⇒ 00:05:18.009 Annie Yu: So it’s from proposal, and then kind of a verbal agreement, and then contract.
53 00:05:18.010 ⇒ 00:05:21.872 Uttam Kumaran: Yeah, let me show you like a visual of what this looks like.
54 00:05:23.400 ⇒ 00:05:25.550 Uttam Kumaran: that will help a little bit. So
55 00:05:29.870 ⇒ 00:05:33.089 Uttam Kumaran: this is something. I made this visual like.
56 00:05:33.830 ⇒ 00:05:38.980 Uttam Kumaran: almost like 2 years ago. And then Amber found it recently. And I was like, Oh, yeah, I was kind of like spot on.
57 00:05:39.250 ⇒ 00:05:40.085 Annie Yu: Nice.
58 00:05:40.920 ⇒ 00:05:46.830 Uttam Kumaran: But yeah, basically, we have like awareness, outreach qualification
59 00:05:47.140 ⇒ 00:05:53.369 Uttam Kumaran: closing. And then we go from setup onboarding, servicing, renewal and expansion.
60 00:05:54.050 ⇒ 00:05:55.360 Uttam Kumaran: Right? So
61 00:05:55.970 ⇒ 00:06:04.220 Uttam Kumaran: we may start off like this is like anyone who, who like likes us on Linkedin, sees our Linkedin stuff, meets with me randomly says, Hi, at an event.
62 00:06:04.380 ⇒ 00:06:08.330 Uttam Kumaran: Then we basically try to get them into a meeting where we say.
63 00:06:08.480 ⇒ 00:06:15.210 Uttam Kumaran: Hey, can we meet to talk about your data problems. Can I just share what we’re up to? Then? Finally, there’s like qualification.
64 00:06:15.340 ⇒ 00:06:16.410 Uttam Kumaran: which is like
65 00:06:17.080 ⇒ 00:06:24.400 Uttam Kumaran: I wrote, I know I must have wrote these at some point which is like budget timeline is the person that we’re meeting with the actual person that can sign.
66 00:06:24.540 ⇒ 00:06:26.810 Uttam Kumaran: Have they worked with contractors before.
67 00:06:26.930 ⇒ 00:06:34.279 Uttam Kumaran: like sort of evaluating whether it’s real. And then we put together an sow statement of work and then
68 00:06:34.740 ⇒ 00:06:36.560 Uttam Kumaran: try to get them to sign the paper
69 00:06:36.660 ⇒ 00:06:40.500 Uttam Kumaran: right. But like that’s that’s like before the work even begins.
70 00:06:40.730 ⇒ 00:06:49.629 Uttam Kumaran: Right? But the problem is our like, our conversion rates on this are are getting better and and meaning.
71 00:06:49.930 ⇒ 00:06:57.740 Uttam Kumaran: We have more volume. We’re able to move more of this to meetings and more of our meetings are now turning into
72 00:06:58.230 ⇒ 00:06:59.609 Uttam Kumaran: statement of work.
73 00:07:00.020 ⇒ 00:07:04.060 Uttam Kumaran: Right now our biggest crunch is on conversion, meaning
74 00:07:04.470 ⇒ 00:07:12.249 Uttam Kumaran: one way or another, like I would say, we’re probably like anywhere from 5 to 10% conversion, meaning, if we talk to.
75 00:07:13.810 ⇒ 00:07:16.579 Uttam Kumaran: Like if we talk to 10 people, if we, if it
76 00:07:16.580 ⇒ 00:07:20.639 Uttam Kumaran: 10 people to the qual that are qualified, one of them closes.
77 00:07:21.090 ⇒ 00:07:21.590 Annie Yu: Yeah.
78 00:07:21.590 ⇒ 00:07:24.840 Uttam Kumaran: So it’s it’s like, could be 5 to 10%. So
79 00:07:25.130 ⇒ 00:07:27.759 Uttam Kumaran: this is where our goal is like, how do we increase that?
80 00:07:28.130 ⇒ 00:07:34.400 Uttam Kumaran: Or we just have to talk to more people. And unfortunately, because we don’t, we’re we don’t have. It’s just me and Robert doing sales.
81 00:07:34.850 ⇒ 00:07:37.849 Uttam Kumaran: We we’re now get the point where we’re talking to a lot of people. But
82 00:07:38.190 ⇒ 00:07:49.230 Uttam Kumaran: we’re thinking a lot about, how do we increase this? This like conversion rate of of people that we meet have the problem, have the budget of the need express that they’re interested in working with us. And how do we close them and start start a project.
83 00:07:49.890 ⇒ 00:07:51.880 Uttam Kumaran: You know. Part of that is momentum.
84 00:07:52.110 ⇒ 00:07:57.899 Uttam Kumaran: Part of that is like having materials. Like all of our case studies and stuff of that. It’s like people know, we’re like, legit.
85 00:07:58.170 ⇒ 00:08:01.370 Annie Yu: Like there’s a lot of freelancers, and that compete.
86 00:08:01.480 ⇒ 00:08:17.530 Uttam Kumaran: In this world. None of them will have anything that looks nearly as good as the stuff we’re producing that will come across as polished as we have, just because I’ve bombed sales so many times. So we learned like how to do it. And then you sort of just like.
87 00:08:17.870 ⇒ 00:08:22.400 Uttam Kumaran: wake up and just keep trying, you know. So so we’re seeing that it’s getting a lot better.
88 00:08:23.300 ⇒ 00:08:31.680 Annie Yu: and when you say, compared to other contractors, are they more like in the visual contractor or like also like a crew, like a team.
89 00:08:32.020 ⇒ 00:08:34.051 Uttam Kumaran: Yeah, it’s a good question. So
90 00:08:36.710 ⇒ 00:08:43.990 Uttam Kumaran: there’s. So there’s so there’s a couple of like different types of people in this world. And if you’re interested, we have actually like a
91 00:08:46.410 ⇒ 00:08:48.559 Uttam Kumaran: I have a Google sheet with like.
92 00:08:49.000 ⇒ 00:08:54.180 Uttam Kumaran: like 200 competitors, you can go click and learn about any of them in case you’re interested in seeing like
93 00:08:54.350 ⇒ 00:08:59.630 Uttam Kumaran: who’s in our world. But what you’ll find, and I’ll I’ll share this with you.
94 00:09:01.740 ⇒ 00:09:28.630 Uttam Kumaran: What you’ll find is that there’s a lot of people in this like one to 10 employees range. Because if me and you tomorrow, we’re like, Hey, we like, let’s say, we’re both working at Nike. We’re like, hey? So my, so my friends, hiring for like data people, he said, like he has, like some at work for me. Do you want to go? Do that work? Sure. And then me and you can just start a company and be like we’re a consultancy now like, that’s it. So a lot of the people on this list are that where they’re just like
95 00:09:29.120 ⇒ 00:09:36.070 Uttam Kumaran: one of their homies is like giving them some money to do some data work. And they’re like, let’s go do some data work. So some of these are one people.
96 00:09:36.250 ⇒ 00:09:44.509 Uttam Kumaran: The like. Really, the tough part is what’s described in in business as crossing the chasm.
97 00:09:45.120 ⇒ 00:09:49.109 Uttam Kumaran: which is a great book, by the way. But basically you have this like.
98 00:09:50.060 ⇒ 00:09:56.850 Uttam Kumaran: you just have this like chasm that you need to cross cross, which is like, how do you go from like.
99 00:09:57.160 ⇒ 00:10:02.719 Uttam Kumaran: just like a 1 or 2 people to like a legitimate enterprise because legitimate enterprise.
100 00:10:02.920 ⇒ 00:10:10.320 Uttam Kumaran: It’s just like a different animal, right like, when I started the business it was just me. And so I had 2 clients. I was
101 00:10:10.450 ⇒ 00:10:17.649 Uttam Kumaran: making all the money, and then but I but I had also done that in the past, and my goal was never to like
102 00:10:17.810 ⇒ 00:10:23.859 Uttam Kumaran: just like, do that, because you almost have like 2 or 3 bosses. And you’re working like insane. So it like never gets better.
103 00:10:24.359 ⇒ 00:10:35.649 Uttam Kumaran: So I always. So I was like cool. We’re gonna hire, and we have to reinvest. But you have to reinvest first, st like quite a long amount of time before you start to get the benefits of scale, meaning
104 00:10:35.950 ⇒ 00:10:42.369 Uttam Kumaran: like, for us to go out and hire for us to go out. Have a marketing team for us to pay for software
105 00:10:43.047 ⇒ 00:10:49.089 Uttam Kumaran: we need to pull out of the profit that you’re making to go do that, to have lawyers to have contracts
106 00:10:49.760 ⇒ 00:10:55.429 Uttam Kumaran: and then also like to even have time to sell right? Like, I’m spending 50% of my time on sales.
107 00:10:55.610 ⇒ 00:10:59.720 Uttam Kumaran: If I was a solo person like one of those other people on the list.
108 00:11:00.910 ⇒ 00:11:06.860 Uttam Kumaran: Where does the 50% of time cover? I’m working for clients right? Like you’re not typically
109 00:11:07.430 ⇒ 00:11:09.350 Uttam Kumaran: working for one client. And then, like
110 00:11:09.870 ⇒ 00:11:12.580 Uttam Kumaran: the moment you sell a second client, you have no more time for sales.
111 00:11:12.580 ⇒ 00:11:13.350 Annie Yu: Yeah, yeah.
112 00:11:13.350 ⇒ 00:11:18.540 Uttam Kumaran: Like it’s like, it’s a huge bottleneck. And so that’s that’s where people get jamm
113 00:11:19.058 ⇒ 00:11:24.439 Uttam Kumaran: so commonly I have a lot of friends in this one to 10 employee world.
114 00:11:24.590 ⇒ 00:11:27.186 Uttam Kumaran: and that’s some of the people that come and work for us here and there.
115 00:11:28.140 ⇒ 00:11:39.329 Uttam Kumaran: but, like they, it’s so hard to get to the next level. I mean, I I don’t even think we’re there yet, but it’s taken 2 years of like and like working like every single day, so
116 00:11:39.740 ⇒ 00:11:55.439 Uttam Kumaran: some people never make it past that. But then slowly, you kind of climb where you you get like one more employee, another person to help you with operations. You find ways to save money. You then maybe get a bigger contract. That’s like more reliable. So you don’t have to work as much
117 00:11:55.955 ⇒ 00:12:00.550 Uttam Kumaran: and then that’s the sort of things that we’ve been sort of. Step by step by step, going
118 00:12:01.980 ⇒ 00:12:05.459 Uttam Kumaran: The other one other way is to raise money right? So like you could.
119 00:12:06.000 ⇒ 00:12:13.550 Uttam Kumaran: you could be one of these small people, raise money. That then gives you the ability to then hire people and buy your time back.
120 00:12:13.780 ⇒ 00:12:27.199 Uttam Kumaran: We’d never raise money, so we sort of have to make more money. I then can like maybe hire people, and then that buys my time back, and then I then do the dance again, and then, like we sort of like incrementally like, climb the ladder.
121 00:12:29.140 ⇒ 00:12:32.319 Uttam Kumaran: But that’s been. That’s sort of been our our process so far.
122 00:12:34.540 ⇒ 00:12:39.669 Uttam Kumaran: So there, there’s not a lot of companies that make it past like 2550 employees.
123 00:12:41.590 ⇒ 00:12:46.149 Uttam Kumaran: It’s just like a if you just have to become like a different person.
124 00:12:46.300 ⇒ 00:12:49.510 Uttam Kumaran: like the problems we’re dealing with are way different than
125 00:12:50.220 ⇒ 00:12:52.530 Uttam Kumaran: what we were dealing with even 6 months ago.
126 00:12:53.370 ⇒ 00:12:58.419 Annie Yu: Yeah. Yeah. Then, among those that say like one to 10, did they also
127 00:12:58.570 ⇒ 00:13:07.159 Annie Yu: like not consider contractors they hire like, do they? Is that like for, like full time, employees only.
128 00:13:07.740 ⇒ 00:13:12.020 Uttam Kumaran: Yeah, like, like, let’s, let’s look at this guy, for example, right? My
129 00:13:12.660 ⇒ 00:13:15.420 Uttam Kumaran: data is okay. My data is.
130 00:13:15.970 ⇒ 00:13:21.919 Uttam Kumaran: it’s just one. It’s just like one date, probably like just one dude.
131 00:13:22.230 ⇒ 00:13:24.170 Uttam Kumaran: 17 years in experience.
132 00:13:24.560 ⇒ 00:13:26.610 Uttam Kumaran: Mitchell. Yeah. So it’s just Mitchell.
133 00:13:27.000 ⇒ 00:13:27.970 Uttam Kumaran: And
134 00:13:28.690 ⇒ 00:13:34.710 Uttam Kumaran: if you’re to. So some. But like these, it’s hard to hire employees because it’s like full time work.
135 00:13:34.870 ⇒ 00:13:36.050 Uttam Kumaran: and
136 00:13:36.200 ⇒ 00:13:42.089 Uttam Kumaran: you need to have enough work coming in to be able to like, sustain that. So sometimes, and then also
137 00:13:42.570 ⇒ 00:13:50.459 Uttam Kumaran: one of the things that sometimes, if you’re if you don’t have a long term mindset is you’ll brand your entire company based on your persona.
138 00:13:50.650 ⇒ 00:13:55.730 Uttam Kumaran: For example, there’s a company that I follow which is called Velotti analytics.
139 00:13:56.260 ⇒ 00:14:01.020 Uttam Kumaran: This guy, Nick Vallotti is like the CEO
140 00:14:02.510 ⇒ 00:14:05.679 Uttam Kumaran: and until recently everything was branded
141 00:14:05.980 ⇒ 00:14:09.370 Uttam Kumaran: towards him. I mean, it kinda is still really branded towards him.
142 00:14:09.570 ⇒ 00:14:12.639 Uttam Kumaran: But now the business cannot exist without him.
143 00:14:13.770 ⇒ 00:14:18.669 Uttam Kumaran: Like he is the business right? The name of the company is his name right? Like
144 00:14:19.230 ⇒ 00:14:24.860 Uttam Kumaran: so, for I was never interested in like I. This needs to run without me, because otherwise I’m the brisk
145 00:14:25.130 ⇒ 00:14:26.040 Uttam Kumaran: right, like
146 00:14:26.420 ⇒ 00:14:36.019 Uttam Kumaran: in business, is just managing risk. And if if I’m the reason where we exist in my name and like my background, and we never build the company’s reputation.
147 00:14:36.130 ⇒ 00:14:42.760 Uttam Kumaran: Then there’s no separating me and the company. So if something happens to me. Then something happens to the company
148 00:14:43.400 ⇒ 00:14:46.719 Uttam Kumaran: like, I think, a lot about building the resilience that way.
149 00:14:47.353 ⇒ 00:14:58.000 Uttam Kumaran: And that’s why I’m I’m open to promoting people. I want people to feel like this is their company. I want people to stay with us as long as they feel comfortable, because this
150 00:14:58.120 ⇒ 00:15:01.430 Uttam Kumaran: starts to scale beyond, just like one or 2 people.
151 00:15:01.940 ⇒ 00:15:12.469 Uttam Kumaran: Maybe we could continue to grow. And we sort of do all the sales we like manage everything. And we just sort of keep. Everyone’s aside. So it’s not very healthy. It’s very, very difficult.
152 00:15:13.022 ⇒ 00:15:17.229 Uttam Kumaran: And I don’t think we reached like the scale we want to get to, you know.
153 00:15:18.820 ⇒ 00:15:19.460 Uttam Kumaran: Yeah.
154 00:15:26.140 ⇒ 00:15:37.930 Uttam Kumaran: but I’m happy. I mean again, I think we moved. We moved away from a lot of like having part time contractors having this like great squad. And so for me, I’m thinking I’m just like, how do I reinvest in everybody here.
155 00:15:38.210 ⇒ 00:15:43.210 Uttam Kumaran: not only in more money, but more opportunity.
156 00:15:43.846 ⇒ 00:15:49.650 Uttam Kumaran: More like leadership, the ability for the company to serve you and like your career.
157 00:15:49.790 ⇒ 00:15:52.540 Uttam Kumaran: because for me, a lot of the times
158 00:15:53.010 ⇒ 00:15:55.360 Uttam Kumaran: they talk about employees, they talk about like
159 00:15:57.010 ⇒ 00:16:00.760 Uttam Kumaran: You know, one of the common metrics in consulting is what’s called attrition, meaning like.
160 00:16:00.860 ⇒ 00:16:03.450 Uttam Kumaran: What’s your employee? Turnover year over year.
161 00:16:03.610 ⇒ 00:16:07.530 Uttam Kumaran: And so it’s always harder to hire someone than it is to keep
162 00:16:07.920 ⇒ 00:16:11.970 Uttam Kumaran: commonly. That’s like a miss that’s like not understood, though, like
163 00:16:12.430 ⇒ 00:16:21.919 Uttam Kumaran: a lot of companies will be like we’re hiring. We’re hiring 20 people, 30 people, but like, instead of hiring, you could have just like kept your people happy. You probably wouldn’t have needed to hire
164 00:16:22.190 ⇒ 00:16:24.570 Uttam Kumaran: like how many people? Right?
165 00:16:24.940 ⇒ 00:16:27.869 Uttam Kumaran: So I think about that a lot as well, you know.
166 00:16:28.160 ⇒ 00:16:31.239 Annie Yu: So that number is the lower the better right.
167 00:16:31.240 ⇒ 00:16:37.550 Uttam Kumaran: Slower the better. Yeah. So we so this is where it’s like the problem. The problem is, these businesses
168 00:16:37.820 ⇒ 00:16:42.130 Uttam Kumaran: just become like math problems at at the end of it. They just become like optimization problems.
169 00:16:42.460 ⇒ 00:16:46.540 Uttam Kumaran: You have revenue, you have costs, you have people, you have margin.
170 00:16:46.960 ⇒ 00:16:52.389 Uttam Kumaran: And so. But there are benchmarks, of course, like we may not hit all of them. Of course. Also.
171 00:16:52.580 ⇒ 00:16:54.479 Uttam Kumaran: we’re not running like a sweatshop.
172 00:16:54.590 ⇒ 00:16:59.590 Uttam Kumaran: So there’s certain things that I won’t compromise on like which
173 00:16:59.930 ⇒ 00:17:05.160 Uttam Kumaran: you may, you may go to a company like your numbers are great, but then you go in, and everybody hates their life, and like.
174 00:17:05.369 ⇒ 00:17:11.859 Uttam Kumaran: it’s like really horrible like, that’s certain things that we have principles that that’s where principles
175 00:17:12.010 ⇒ 00:17:18.110 Uttam Kumaran: like allow us to make decisions that not completely driven by money or outcome.
176 00:17:18.630 ⇒ 00:17:27.569 Uttam Kumaran: And so, but like, of course, like we, I have like probably 7 or 8 of these benchmarks in our mind that that’s what our our goals are going for whether it’s revenue margin
177 00:17:29.060 ⇒ 00:17:53.019 Uttam Kumaran: like revenue per employee, whether we’re looking at our average rate, things like that. But employee attrition is like for me something that I really am like focused on because I don’t. I want people to come like it would, I think, even for the company. It’s so healthy. People come in at whatever level they gain. All this sort of like tribal knowledge about the company, and then they move up
178 00:17:53.400 ⇒ 00:17:58.459 Uttam Kumaran: cause instead of for us. We’ve made a lot like I’ve tried to hire. People like that are senior level.
179 00:17:59.120 ⇒ 00:18:02.839 Uttam Kumaran: They’re like, never good enough like they bring a lot of baggage.
180 00:18:03.170 ⇒ 00:18:05.270 Annie Yu: They commonly.
181 00:18:05.500 ⇒ 00:18:10.720 Uttam Kumaran: Like don’t want to do the work, cause they’re like senior.
182 00:18:11.179 ⇒ 00:18:17.540 Uttam Kumaran: I don’t know like I’m staring at Looker right now. I’m like still doing stuff like. So how senior does it get?
183 00:18:18.370 ⇒ 00:18:23.030 Uttam Kumaran: So then I’m like, and then I sort of question like, what can’t be taught
184 00:18:23.230 ⇒ 00:18:31.689 Uttam Kumaran: right like, I would rather you learn how to do something and then bring your relationships in the company with you versus bringing someone in who like.
185 00:18:31.930 ⇒ 00:18:34.670 Uttam Kumaran: Oh, you’re head of someone’s. I brought in someone as head of data.
186 00:18:34.910 ⇒ 00:18:36.260 Uttam Kumaran: They run data like.
187 00:18:36.940 ⇒ 00:18:50.290 Uttam Kumaran: what’s the title like, what’s the title? The the importance is like your impact, you know. And a lot of senior people I worked with suck like they don’t have. They? Just like got a high title from someplace, and they got lucky.
188 00:18:50.786 ⇒ 00:18:51.499 Uttam Kumaran: The gosh!
189 00:18:51.500 ⇒ 00:18:55.890 Uttam Kumaran: Super! Lucky that they someone, their buddy, who was manager, named them manager.
190 00:18:56.090 ⇒ 00:19:00.476 Uttam Kumaran: And then they’re like trying to come here and be manager like dude. You’re not like not good.
191 00:19:01.650 ⇒ 00:19:04.080 Annie Yu: Yeah, that’s definitely a thing. I think
192 00:19:04.800 ⇒ 00:19:08.810 Annie Yu: I I saw that a lot like back in Ike. I feel like.
193 00:19:08.810 ⇒ 00:19:09.370 Uttam Kumaran: Okay.
194 00:19:10.131 ⇒ 00:19:15.188 Annie Yu: Like. The only way to go up is like stepping on someone’s.
195 00:19:15.610 ⇒ 00:19:16.070 Uttam Kumaran: Yeah.
196 00:19:16.070 ⇒ 00:19:24.109 Annie Yu: And then like it doesn’t really matter how good, how skillful you are at, but more so like how
197 00:19:24.750 ⇒ 00:19:33.359 Annie Yu: how show off you can be, or like taking others credits. But it’s like I definitely see those, and I hate it.
198 00:19:33.800 ⇒ 00:19:37.220 Uttam Kumaran: Yeah, it’s rough, I mean, on some level, like there.
199 00:19:38.030 ⇒ 00:19:47.049 Uttam Kumaran: like people like always say, like, I don’t want to play company politics. And I got really good at playing company politics, just because in order for my work to shine.
200 00:19:47.480 ⇒ 00:19:50.060 Uttam Kumaran: Team to succeed. I needed to. So like.
201 00:19:50.260 ⇒ 00:19:54.020 Uttam Kumaran: because otherwise the work we were doing was never gonna get out to customers.
202 00:19:54.020 ⇒ 00:19:54.510 Annie Yu: Yeah.
203 00:19:54.510 ⇒ 00:20:03.139 Uttam Kumaran: And so, but also at the same time, like you want to play a healthy level which mainly should just be like, I want to express what I want. And I wanna
204 00:20:03.680 ⇒ 00:20:05.379 Uttam Kumaran: share what I’m working on.
205 00:20:05.840 ⇒ 00:20:10.739 Uttam Kumaran: But like anything beyond that, I’m really thankful we don’t have anyone in the company that’s like
206 00:20:11.230 ⇒ 00:20:15.819 Uttam Kumaran: like that at all. In fact, I think it’s most people are pretty shy, which is great.
207 00:20:16.640 ⇒ 00:20:24.079 Uttam Kumaran: because that’s something where you can build people’s confidence versus. If some people come in here overconfident, it’s hard to change that a lot
208 00:20:24.280 ⇒ 00:20:25.050 Uttam Kumaran: right?
209 00:20:26.220 ⇒ 00:20:29.900 Uttam Kumaran: And so I’m like very happy, like. Our meetings are very, very chill.
210 00:20:30.130 ⇒ 00:20:34.599 Uttam Kumaran: I think, for the most part, like only stuff with clients, is like kind of the unchild part.
211 00:20:37.440 ⇒ 00:20:47.579 Uttam Kumaran: like. We’ll see how long I could keep it going like that. But that’s what my hope is like. If I’m the most energetic person here, then, that’s
212 00:20:48.100 ⇒ 00:20:49.649 Uttam Kumaran: that’s just fine, you know.
213 00:20:50.020 ⇒ 00:20:54.439 Annie Yu: No, I think you are setting a good example. Really. I mean that.
214 00:20:55.240 ⇒ 00:21:05.869 Uttam Kumaran: It’s hard. It’s, you know, it’s it’s tough. Also, you know, I think we got we got very, very lucky, like founding finding folks like you, and and a wish and demalade and Kyle, and like.
215 00:21:06.230 ⇒ 00:21:07.339 Uttam Kumaran: I just think
216 00:21:08.730 ⇒ 00:21:21.839 Uttam Kumaran: but also we we got unlucky in other ways. So like you’re not see the people who didn’t work out. They’re not here because they didn’t work out, but it’s also like none of those things we like fired people as it was like, it was all pretty amicable.
217 00:21:23.066 ⇒ 00:21:28.600 Uttam Kumaran: Yeah. And and I cause I can’t really like, do the emotional? It’s really tough.
218 00:21:28.600 ⇒ 00:21:29.010 Annie Yu: Hmm.
219 00:21:29.900 ⇒ 00:21:38.180 Uttam Kumaran: But yeah, I guess, like, well, I I wanted to ask you about like I asked you about thinking about goals and stuff. So I wanted to see if you, if you had any thoughts on that.
220 00:21:38.400 ⇒ 00:21:41.200 Annie Yu: Yeah, I wanna say, I actually haven’t filled out the form.
221 00:21:41.200 ⇒ 00:21:42.849 Uttam Kumaran: That’s fine, that’s fine.
222 00:21:43.265 ⇒ 00:21:48.670 Uttam Kumaran: Provided another version which we went through last week, some of them overlapped.
223 00:21:48.670 ⇒ 00:21:52.549 Uttam Kumaran: That’s fine. I just wanted to ask in general. If you had been thinking about it at all.
224 00:21:53.230 ⇒ 00:21:58.540 Annie Yu: Yeah, I think I’m gonna pull up. I guess a wishes document.
225 00:21:58.540 ⇒ 00:21:59.439 Uttam Kumaran: Yeah, yeah, yeah.
226 00:22:02.390 ⇒ 00:22:03.770 Uttam Kumaran: I’m just curious.
227 00:22:06.090 ⇒ 00:22:12.809 Annie Yu: Yeah, I’m I’m gonna I’m still gonna find it. So I can anchor my thoughts.
228 00:22:25.440 ⇒ 00:22:30.170 Annie Yu: yeah. So I think what I shared also with him was that
229 00:22:32.890 ⇒ 00:22:35.529 Annie Yu: And never mind, I can find that. But
230 00:22:37.720 ⇒ 00:23:03.199 Annie Yu: I’m I’m now like taking part-time masters in data science. So obviously, I do want to get more hands-on experience alone. Like machine learning. We also talk about because machine learning is kind of like part of AI, right? So he also asked further, are you more interested in like, I guess, developing automation models, or more so like using those models. So for me, I think it’s like using those models. So I.
231 00:23:03.200 ⇒ 00:23:03.600 Uttam Kumaran: Yeah.
232 00:23:03.600 ⇒ 00:23:16.149 Annie Yu: Gonna do more like predict. Not just predictive modeling. I see that a lot. But that’s just part of that. And also like clustering. So yeah, that’s that’s where I’m trying to get more
233 00:23:16.980 ⇒ 00:23:23.230 Annie Yu: hands-on experience. I feel like the projects I’ve done with. Schools are very
234 00:23:23.960 ⇒ 00:23:31.430 Annie Yu: like things are very structured. And then it’s, I think many people who are data scientists have done that at school.
235 00:23:31.430 ⇒ 00:23:31.930 Uttam Kumaran: Yeah.
236 00:23:31.930 ⇒ 00:23:34.300 Annie Yu: So we we like. We’re designing.
237 00:23:34.300 ⇒ 00:23:38.660 Uttam Kumaran: No, but you’re you’re just you’re not. You’re never gonna have real world use cases at school. It’s gonna be like
238 00:23:39.030 ⇒ 00:23:40.610 Uttam Kumaran: fake stuff. Basically.
239 00:23:40.610 ⇒ 00:23:42.820 Annie Yu: Yeah, yeah, but also.
240 00:23:42.820 ⇒ 00:23:43.350 Uttam Kumaran: Stuff.
241 00:23:43.732 ⇒ 00:23:48.327 Annie Yu: But also, I’m not super comfortable, like owning a project like that.
242 00:23:48.710 ⇒ 00:23:49.300 Uttam Kumaran: Totally.
243 00:23:49.300 ⇒ 00:24:00.929 Annie Yu: Also, I think it’ll be great to have experience, but also, like maybe have someone on the side as a coach where I can ask questions when when needed. But that’s.
244 00:24:00.930 ⇒ 00:24:01.710 Uttam Kumaran: Great.
245 00:24:01.710 ⇒ 00:24:09.449 Annie Yu: That’s like my main thing. And then another thing is I definitely do want to get certified, but also
246 00:24:09.740 ⇒ 00:24:11.140 Annie Yu: that would be.
247 00:24:12.920 ⇒ 00:24:23.610 Annie Yu: I think I’m pretty pretty comfortable with tableau, but I’ve never got certified. So that’s something that I would love to look into, but or but that maybe not.
248 00:24:24.970 ⇒ 00:24:33.180 Annie Yu: Maybe that’s not a priority. I think I think I just thinking out loud. And then I also shared this with the wish is about
249 00:24:33.360 ⇒ 00:24:38.180 Annie Yu: Dvt, so it’s still a fuzzword to me, and I think.
250 00:24:38.540 ⇒ 00:24:41.659 Uttam Kumaran: But you’re do. You’re doing a lot of modeling in real.
251 00:24:42.430 ⇒ 00:24:45.970 Uttam Kumaran: basically taking that. And you’re just like it’s the same thing just like that.
252 00:24:46.670 ⇒ 00:24:48.310 Annie Yu: Okay, okay, and.
253 00:24:48.310 ⇒ 00:24:56.769 Uttam Kumaran: Meaning it. There’s no visualization. But but I think so. I think you definitely I’m talking to him about trying to get everyone to go through the Dvt certification.
254 00:24:56.770 ⇒ 00:24:57.460 Annie Yu: Hmm.
255 00:24:57.460 ⇒ 00:25:05.519 Uttam Kumaran: Like, I think that is gonna be very, very high leverage. I will love to ask him if he thinks there’s another certification that’s relevant for
256 00:25:06.100 ⇒ 00:25:14.359 Uttam Kumaran: data science. But you’re already doing masters. So I think what’s more important is for us to basically one.
257 00:25:14.700 ⇒ 00:25:20.470 Uttam Kumaran: If there’s an opportunity for us to use data science on our own data in the company.
258 00:25:20.590 ⇒ 00:25:25.889 Uttam Kumaran: like a company like again, we’re now bringing in all of our slack Github
259 00:25:26.260 ⇒ 00:25:32.719 Uttam Kumaran: bunch of stuff into S. 3 and into Snowflake. So in case there’s anything you could do to build
260 00:25:33.220 ⇒ 00:25:43.390 Uttam Kumaran: like part of one of the things that’s gonna be a project for me later. This quarter is starting to build our company Kpis and our company dashboards. I think we’re gonna have some fun because
261 00:25:43.770 ⇒ 00:25:50.390 Uttam Kumaran: it’s like basic stuff’s gonna be easy. I think it’s gonna be interesting to start to look at predictive trends and like start to set goals and forecasts.
262 00:25:50.510 ⇒ 00:26:01.040 Uttam Kumaran: But again, we’re not a very high volume in the some senses, but in some other parts, like we have more volume, so that could be interesting. There. There could be some interesting analytics.
263 00:26:01.590 ⇒ 00:26:04.530 Uttam Kumaran: I think also, as we go after
264 00:26:07.290 ⇒ 00:26:12.620 Uttam Kumaran: after we as we go after larger clients, I think there’s going to be more opportunity for really great
265 00:26:12.880 ⇒ 00:26:21.729 Uttam Kumaran: heavy data science work. For example, this is where I think for me, it’s I’ve never worked with a data science team
266 00:26:22.050 ⇒ 00:26:38.290 Uttam Kumaran: that’s actually produced like anything worthwhile. So I don’t. I don’t like it’s not what I don’t. When I think about like moving the needle for these businesses, I think a lot about like just basic data modeling and like basic Kpi setting, because a lot of them struggle with just that.
267 00:26:38.460 ⇒ 00:26:42.339 Uttam Kumaran: But that’s sort of my like. That’s my blind spot is like.
268 00:26:42.450 ⇒ 00:26:49.030 Uttam Kumaran: Hey, how do I? How do I start to understand whether a client is a good candidate for like
269 00:26:49.400 ⇒ 00:26:50.780 Uttam Kumaran: adding more
270 00:26:50.970 ⇒ 00:27:01.359 Uttam Kumaran: layering on more analytics in whatever direction. I think Robert Robert knows that pretty well. But this is where, again, we have a couple of clients that are pretty are processing a lot of volume.
271 00:27:01.480 ⇒ 00:27:10.160 Uttam Kumaran: for example, working with urban stems. They’re a flower company. They do tons and tons of volume. Certainly, like, I think there’s applications for
272 00:27:11.680 ⇒ 00:27:19.890 Uttam Kumaran: something in that world where, if we were to come up with the thesis and maybe like and I built like, what is the experiment we could run to test
273 00:27:20.100 ⇒ 00:27:22.380 Uttam Kumaran: like whether this project or this client
274 00:27:22.900 ⇒ 00:27:28.090 Uttam Kumaran: has some juice there, we could certainly put in front of them like 100.
275 00:27:28.300 ⇒ 00:27:31.319 Uttam Kumaran: And then, yeah, you would just do it like we do anything else.
276 00:27:31.774 ⇒ 00:27:34.050 Uttam Kumaran: I think what I would be interested in.
277 00:27:34.490 ⇒ 00:27:37.725 Uttam Kumaran: you know, to hear is what constitutes a
278 00:27:38.340 ⇒ 00:27:46.649 Uttam Kumaran: like, what what constitutes a qualified problem set that that you can apply data science to in order to solve. And what doesn’t
279 00:27:46.790 ⇒ 00:27:51.999 Uttam Kumaran: like. What does a good problem look like in that space. That’ll help me sort of think through the clients we have.
280 00:27:52.841 ⇒ 00:28:00.949 Uttam Kumaran: The other thing I’m I’ll send. I’m sending you this book, and I’m reading in engineering. It’s called Competing on Analytics. I just started reading it.
281 00:28:01.070 ⇒ 00:28:02.120 Uttam Kumaran: Very good.
282 00:28:03.550 ⇒ 00:28:08.200 Uttam Kumaran: It’s kind of short, but like very practical use cases for
283 00:28:10.480 ⇒ 00:28:14.160 Uttam Kumaran: for data, science, and like heavy analytics in business.
284 00:28:16.640 ⇒ 00:28:19.360 Uttam Kumaran: If you want to let me know? I can probably buy for you.
285 00:28:21.510 ⇒ 00:28:22.350 Uttam Kumaran: But
286 00:28:22.800 ⇒ 00:28:32.039 Uttam Kumaran: I don’t know. I’ve been reading more about like, How do we actually do more practical analysis, like beyond just dashboards, something that’s that we’re all talking about right now. So
287 00:28:33.160 ⇒ 00:28:36.160 Uttam Kumaran: yeah, I’m super super interested in in trying to make that happen.
288 00:28:37.070 ⇒ 00:28:37.840 Annie Yu: Yeah.
289 00:28:41.410 ⇒ 00:28:45.630 Annie Yu: interesting is the 1st edition. Is that a new book.
290 00:28:46.070 ⇒ 00:28:48.939 Uttam Kumaran: Yeah, I got it at half price. Books got my copy.
291 00:28:48.940 ⇒ 00:28:49.960 Annie Yu: Nice.
292 00:28:50.980 ⇒ 00:28:52.970 Uttam Kumaran: It’s cheap. It’s like 4 bucks.
293 00:28:53.570 ⇒ 00:28:55.979 Annie Yu: Yeah, that’s amazing.
294 00:28:57.632 ⇒ 00:29:03.410 Uttam Kumaran: Okay, that’s great. I mean, I like that that to hear that you want to get more like technical on that side.
295 00:29:03.670 ⇒ 00:29:05.770 Annie Yu: One thing about
296 00:29:06.560 ⇒ 00:29:30.260 Annie Yu: I don’t know the right word, like data engineering data modeling. I think I really love that being in this role, I get to have more exposure to that world. But I also shared this with a wish. I think this is not where my interest lies. I do want to learn more about it. I want to get more knowledgeable around Dbt, but I don’t want it to be my day to day in the future.
297 00:29:30.260 ⇒ 00:29:31.010 Uttam Kumaran: Yeah, yeah.
298 00:29:31.010 ⇒ 00:29:32.099 Annie Yu: To have that.
299 00:29:32.100 ⇒ 00:29:32.500 Uttam Kumaran: I know.
300 00:29:32.500 ⇒ 00:29:34.868 Annie Yu: Visibility of the workflow.
301 00:29:35.870 ⇒ 00:29:39.250 Uttam Kumaran: Good. I mean, that’s fine, like I think it’s helpful for you
302 00:29:39.370 ⇒ 00:29:44.919 Uttam Kumaran: to be vocal about what part you want to get more technical in, and I certainly think you should like
303 00:29:46.240 ⇒ 00:29:52.989 Uttam Kumaran: to be candid, our company lacks in the direction that you’re trying to go, meaning we don’t have people who are thinking about
304 00:29:53.240 ⇒ 00:30:00.970 Uttam Kumaran: practical analytics and actually like, how do we start to move from
305 00:30:01.310 ⇒ 00:30:06.889 Uttam Kumaran: just goal setting, forecasting to predictive, to like running heavier like
306 00:30:07.310 ⇒ 00:30:15.209 Uttam Kumaran: models, and to achieve a certain outcome or insight like that’s where where we want to go. And that’s also where I think
307 00:30:16.510 ⇒ 00:30:27.049 Uttam Kumaran: a lot of companies in our world stop because it’s hard to do those things like to do what we do. It’s hard but to do that is like really need to have everything set up.
308 00:30:27.050 ⇒ 00:30:27.450 Annie Yu: And if we.
309 00:30:27.450 ⇒ 00:30:31.920 Uttam Kumaran: We can start to bring that to companies that don’t have access to great talent.
310 00:30:32.050 ⇒ 00:30:35.720 Uttam Kumaran: like, I mean, it’ll be really, really successful, you know. So I
311 00:30:35.950 ⇒ 00:30:40.559 Uttam Kumaran: yeah, I think it’s certainly we need to start to establish a practice of like, how do we
312 00:30:40.750 ⇒ 00:30:47.339 Uttam Kumaran: actually like? How do we actually think beyond the da, the dashboard and beyond, like.
313 00:30:47.950 ⇒ 00:30:52.579 Uttam Kumaran: just a basic sequel based time series analysis, you know.
314 00:30:54.820 ⇒ 00:31:00.069 Uttam Kumaran: Yeah, I mean, I’d be curious if maybe you and a ways work on like I just don’t know like how to even think about what problems
315 00:31:00.720 ⇒ 00:31:03.309 Uttam Kumaran: fit for that solution, you know.
316 00:31:03.630 ⇒ 00:31:06.859 Uttam Kumaran: But I’m I know we have clients right now that could use that.
317 00:31:11.490 ⇒ 00:31:14.689 Annie Yu: Yeah, I’ll let you know.
318 00:31:17.290 ⇒ 00:31:18.720 Annie Yu: As I go.
319 00:31:19.320 ⇒ 00:31:30.959 Annie Yu: I feel like right now. I’m learning a lot of things that I don’t even know where would be applicable. Like, I’m learning like different kind of data structure, like different kind of trees
320 00:31:31.550 ⇒ 00:31:42.640 Annie Yu: and all that. So I’ll let you know what I think. But but even back in my other program, I I remember we also did like
321 00:31:42.960 ⇒ 00:31:48.230 Annie Yu: just forecasting, even using like excel, even though I I did not enjoy
322 00:31:48.750 ⇒ 00:31:54.900 Annie Yu: so or that. But I think there are it. It doesn’t require a lot of
323 00:31:55.180 ⇒ 00:31:58.670 Annie Yu: different data to to get it to get it. Yeah.
324 00:31:58.670 ⇒ 00:32:05.420 Uttam Kumaran: Yeah, I wonder? Like once, maybe I’ll even show you like, probably next month we’ll have all of our company data organized in Snowflake.
325 00:32:05.900 ⇒ 00:32:07.240 Uttam Kumaran: And maybe we can.
326 00:32:07.780 ⇒ 00:32:10.920 Uttam Kumaran: We can try to see if there’s anything we could do with that like.
327 00:32:11.450 ⇒ 00:32:24.990 Uttam Kumaran: And I don’t know. I don’t know what we could predict predict something. But like, we have all of our slack data, we have all of our linear data. We’re gonna get everything in there. So could be interesting to show graphs about like
328 00:32:25.130 ⇒ 00:32:27.840 Uttam Kumaran: when people are talking on slack. And how do we predict
329 00:32:27.990 ⇒ 00:32:30.080 Uttam Kumaran: there are better policies or something.
330 00:32:30.480 ⇒ 00:32:33.500 Uttam Kumaran: and we turn a case, turn that into a case, study and publish it. You know.
331 00:32:34.390 ⇒ 00:32:37.190 Annie Yu: Yeah. Sounds like a fun fun. One.
332 00:32:37.190 ⇒ 00:32:43.040 Uttam Kumaran: Yeah, okay, cool. Anything else for me?
333 00:32:43.430 ⇒ 00:32:48.430 Uttam Kumaran: I just mainly wanted to say, Hi, I’m glad that you and a ways talked and everything’s going well.
334 00:32:48.620 ⇒ 00:32:50.728 Annie Yu: Yeah, I think not. They
335 00:32:51.270 ⇒ 00:33:00.798 Annie Yu: outstanding. Now I think that’s pretty much it. And I guess when is the best time to visit Austin?
336 00:33:01.300 ⇒ 00:33:03.679 Uttam Kumaran: Oh, no way you thinking about visiting.
337 00:33:05.280 ⇒ 00:33:23.569 Annie Yu: My my my partner Raymond’s previous boss, left the company to join Spacex there, and there are like very good buddies. So he’s probably gonna visit him at 1 point. So yeah, we’re.
338 00:33:23.570 ⇒ 00:33:25.500 Uttam Kumaran: You should tell me when? Yeah.
339 00:33:25.500 ⇒ 00:33:26.030 Annie Yu: Yeah.
340 00:33:26.030 ⇒ 00:33:27.399 Uttam Kumaran: And we’re gonna be.
341 00:33:27.630 ⇒ 00:33:31.319 Uttam Kumaran: I think this this, if you’re thinking about this month, I’m gonna be out of town.
342 00:33:31.320 ⇒ 00:33:34.295 Annie Yu: This month, probably too soon.
343 00:33:34.890 ⇒ 00:33:45.149 Uttam Kumaran: Okay. So then I mean, next month I’ll be next month, and I won’t be here. July 4.th But we’re usually here. So you let me know. And like, Yeah, I mean whatever you need. If you’re here.
344 00:33:46.100 ⇒ 00:33:48.709 Annie Yu: Summer, usually like very muggy, though.
345 00:33:48.910 ⇒ 00:33:52.869 Uttam Kumaran: It’s not really that muggy. It’s just hot. It’s like 110.
346 00:33:52.870 ⇒ 00:33:58.450 Annie Yu: Okay, yeah, I get irritated whenever it’s just too hot and humid. So.
347 00:33:59.400 ⇒ 00:34:03.380 Uttam Kumaran: No, it’s but there’s ace they run A/C everywhere here, so
348 00:34:04.070 ⇒ 00:34:08.819 Uttam Kumaran: you’ll be you’ll be fine, but it’s it’s so nice here you should totally visit, if you have a chance.
349 00:34:09.210 ⇒ 00:34:16.369 Annie Yu: Yeah, probably. Yeah. I’ll let you know. I I don’t think it’ll happen in these 2 months. But
350 00:34:16.580 ⇒ 00:34:19.600 Annie Yu: Whoa! We have. We’ve never been so definitely.
351 00:34:19.600 ⇒ 00:34:23.810 Uttam Kumaran: Well, you should let me know when, and maybe I’ll try to see if other people want to come. We do offsite or something here.
352 00:34:24.530 ⇒ 00:34:25.219 Uttam Kumaran: Yeah.
353 00:34:25.409 ⇒ 00:34:26.249 Annie Yu: Yeah.
354 00:34:26.250 ⇒ 00:34:31.120 Uttam Kumaran: Yeah, that’d be nice, I know. I know. Robert would totally come. Maybe Amber.
355 00:34:31.120 ⇒ 00:34:32.149 Annie Yu: Come down to.
356 00:34:32.159 ⇒ 00:34:33.849 Uttam Kumaran: No, he’s been there. He’s been there.
357 00:34:33.969 ⇒ 00:34:43.579 Uttam Kumaran: but also, like people can say, in this house there’s 2 free bedrooms, and someone can sleep in this room. There’s like a ton of space. We want to do like a off site house.
358 00:34:43.689 ⇒ 00:34:46.599 Uttam Kumaran: But all or people can get Airbnb or Hotel, or whatever.
359 00:34:47.639 ⇒ 00:34:49.349 Annie Yu: That’s a good idea. Well.
360 00:34:51.219 ⇒ 00:34:54.769 Uttam Kumaran: Yeah, maybe we can plan it for next the next quarter.
361 00:34:55.049 ⇒ 00:34:57.399 Uttam Kumaran: I guess. Yeah, it’d be July, right? So.
362 00:34:57.400 ⇒ 00:34:58.380 Annie Yu: Is it July?
363 00:34:58.380 ⇒ 00:35:01.619 Uttam Kumaran: June, June, July, yeah.
364 00:35:01.780 ⇒ 00:35:02.380 Annie Yu: Yeah.
365 00:35:04.240 ⇒ 00:35:04.920 Uttam Kumaran: Okay.
366 00:35:05.190 ⇒ 00:35:11.070 Uttam Kumaran: cool, alright. Well, let me know how I can help. And yeah, if you read anything interesting during your master’s like.
367 00:35:11.670 ⇒ 00:35:13.480 Uttam Kumaran: send it to the team, because.
368 00:35:14.258 ⇒ 00:35:18.400 Uttam Kumaran: I don’t think I have time to do that do a master’s. But
369 00:35:18.610 ⇒ 00:35:27.220 Uttam Kumaran: I would like to do the 80 20. So if there’s anything you’re reading that you’re like, Damn! This is really cool, like I would love to to read it, because I’m
370 00:35:27.700 ⇒ 00:35:33.199 Uttam Kumaran: I don’t know. I’m like I’m I’m on to do every certification I want to do alongside everybody as well. So.
371 00:35:33.350 ⇒ 00:35:35.980 Annie Yu: I’m glad that we’re gonna start pushing that forward.
372 00:35:36.250 ⇒ 00:35:41.590 Annie Yu: Yeah, that sounds great. Thank you so much. Nice catching up.
373 00:35:41.590 ⇒ 00:35:43.720 Uttam Kumaran: Yeah, nice catching up. We’ll talk to you soon.
374 00:35:43.950 ⇒ 00:35:44.790 Annie Yu: Back to you.
375 00:35:44.790 ⇒ 00:35:45.370 Uttam Kumaran: Bye.