Meeting Title: Brainforge Recruiting Strategy Sync Date: 2026-01-09 Meeting participants: Robert Tseng, Uttam Kumaran, Clarence Stone, Rico Rejoso
WEBVTT
1 00:03:44.750 ⇒ 00:03:45.500 Uttam Kumaran: 8th.
2 00:03:47.130 ⇒ 00:03:48.370 Uttam Kumaran: Okay.
3 00:03:48.910 ⇒ 00:03:50.040 Robert Tseng: Yeah.
4 00:03:51.730 ⇒ 00:03:58.869 Robert Tseng: Well, I guess, like, quick thing on the delivery thing. So yeah, I mean, basically, with the… with the edge layer thing.
5 00:03:59.520 ⇒ 00:04:05.830 Robert Tseng: Turns out that, like, it’s… it’s too good. Like, they think, like, the cons…
6 00:04:05.990 ⇒ 00:04:15.069 Robert Tseng: they’re getting… they’re getting questions from legal on, like, whether or not it’s… it’s… it’s okay to, like, navigate around consent, which is interesting. I’ve never run into this before, so…
7 00:04:17.269 ⇒ 00:04:21.229 Uttam Kumaran: Yeah, I mean, I, I was like.
8 00:04:21.549 ⇒ 00:04:27.659 Uttam Kumaran: I mean, I get it, like, I… but I thought… I thought we are doing the consent flags, like…
9 00:04:27.660 ⇒ 00:04:36.630 Robert Tseng: Yeah, we are doing consent flags, everything we’re doing is legal, like, technically, but, like, I guess, or at least my… what… whatever my understanding was, but…
10 00:04:36.730 ⇒ 00:04:48.829 Robert Tseng: I guess we’ll see. I think, Eden’s basically consulting their lawyers, and I’m asking a couple people as well, that are in the digital marketing world. I’m curious.
11 00:04:49.210 ⇒ 00:04:51.940 Robert Tseng: But we’ll see how that… how that turns out. Yeah.
12 00:04:52.910 ⇒ 00:04:53.510 Uttam Kumaran: Cool.
13 00:04:53.620 ⇒ 00:04:55.220 Uttam Kumaran: Nice. Yeah.
14 00:04:56.110 ⇒ 00:04:56.940 Uttam Kumaran: Interesting.
15 00:04:58.040 ⇒ 00:04:59.730 Robert Tseng: Yeah.
16 00:05:00.540 ⇒ 00:05:03.170 Uttam Kumaran: Okay, let’s go through our list.
17 00:05:07.610 ⇒ 00:05:12.659 Robert Tseng: Yeah, I mean, I guess, I sent you some messages about LA, and then…
18 00:05:12.950 ⇒ 00:05:20.430 Uttam Kumaran: deck kind of person, deck designer, then that reduces some weight, but yeah, she’s doing… she’s handling a lot of the coordination right now.
19 00:05:20.850 ⇒ 00:05:21.600 Robert Tseng: Yeah.
20 00:05:21.630 ⇒ 00:05:31.429 Robert Tseng: So, now that she’s out of sales coordination stuff, because Rico is able to stand in and, you know, and, like, those pieces are moved off, even partnership stuff, I want off her plate eventually.
21 00:05:31.460 ⇒ 00:05:42.099 Robert Tseng: You know, if she’s doing… yeah, the design is obviously, of itself, she’ll just have more things that she has to produce, slash manage Joe to kind of do on deck… on the deck side.
22 00:05:42.100 ⇒ 00:05:52.280 Robert Tseng: But I told her, like, the main thing she needs to add to her scope is, like, engagement with the… with the… with the assets. Like, now that we’re tracking high-intense engagements.
23 00:05:52.280 ⇒ 00:06:07.070 Robert Tseng: newsletter sign-ups, downloadable things, like, event… events that we’re hosting, event sign-ups as well, like, yeah, making sure that every, every asset that we produce is, like, tied to a CTA, like,
24 00:06:07.090 ⇒ 00:06:25.129 Robert Tseng: Yeah, like, in terms of, like, the mark… the sales structure that I set up, her… the thing that she’s optimizing for is turning marketing qualified leads into sales-qualified leads. So, Vixoul gave us a benchmark this week of, like, hey, you should expect maybe 30% of your marketing qualified leads to turn into SQLs.
25 00:06:25.130 ⇒ 00:06:34.800 Robert Tseng: And I was like, well, I think that’s… that’s a… that’s a… that, to me, is a clear metric that she needs to… she needs to be responsible for. So, if she wants to, like.
26 00:06:35.260 ⇒ 00:06:41.540 Robert Tseng: kind of… be, like, yeah, as far as how her… how her role needs to evolve.
27 00:06:42.010 ⇒ 00:06:43.430 Robert Tseng: Yeah, but I mean…
28 00:06:43.920 ⇒ 00:06:59.710 Robert Tseng: But I asked her to put together the proposal, I gave her some template based off of, like, a couple of the other JDs that we made. I just basically copied Luke’s JD, and I was like, here, just take this and rework it based off of what we discussed. But yeah, I think that’s…
29 00:06:59.770 ⇒ 00:07:07.059 Robert Tseng: hopefully by the time we… we get to LA, like, I… that’s… that’s what… that’s what I want her to agree to, for what her role should become. Sure.
30 00:07:09.180 ⇒ 00:07:16.750 Robert Tseng: But then, obviously, since she’s pregnant, like, her first trimester will end in two weeks, so I think she’ll be out of her,
31 00:07:17.020 ⇒ 00:07:22.799 Robert Tseng: her current state by then. But yeah, I think… I think things will… I think things will get better.
32 00:07:23.310 ⇒ 00:07:42.449 Uttam Kumaran: Yeah, Hannah has a ton of tribal knowledge, dude, so, like, even just to have her at all, like, is great. But I agree with you, like, I would rather move her into higher leverage stuff. Like, I found this guy, Joe, like, if… as soon as I keep getting things off my plate, if we’re, like, we need some type of other resource, I can go find that.
33 00:07:42.780 ⇒ 00:07:43.740 Uttam Kumaran: Yeah.
34 00:07:44.000 ⇒ 00:07:50.140 Uttam Kumaran: So, like, that’s something also, like, look, Shashu, part of Sheshu’s job is gonna be, like, I need this role.
35 00:07:50.710 ⇒ 00:07:56.749 Uttam Kumaran: buy me, like, 100 people to go talk to, and well, let’s… let’s, like… it’s sort of what I do, which is, like, I call Rico, and I’m like.
36 00:07:56.880 ⇒ 00:08:00.940 Uttam Kumaran: I call Rico and Ryan. I’m like, I have… I need this type of person.
37 00:08:01.520 ⇒ 00:08:09.220 Uttam Kumaran: I need, like, 30 Upwork, and I need, like, 30 LinkedIns, and then I’ll tell you the right ones.
38 00:08:09.490 ⇒ 00:08:10.370 Uttam Kumaran: And then…
39 00:08:10.760 ⇒ 00:08:23.229 Uttam Kumaran: like, hit as many of them, and I want to close this role by 2 weeks. And, like, that’s what we do. And so, Sheshu’s job is to take the fact that we’re doing that, and, like, somehow productionalize that. Like, I have a role, I have the scope.
40 00:08:23.620 ⇒ 00:08:34.409 Uttam Kumaran: find me anyone on Upwork or any of the freelance platforms that I can just get in contact with. Like, we found Joe on Upwork through the same method. 25 bucks an hour, he does decks for, like, some big law firm in New York.
41 00:08:34.750 ⇒ 00:08:35.390 Uttam Kumaran: like.
42 00:08:35.390 ⇒ 00:08:36.400 Robert Tseng: Oh, really? Huh.
43 00:08:36.409 ⇒ 00:08:37.039 Uttam Kumaran: Yeah.
44 00:08:37.209 ⇒ 00:08:52.199 Uttam Kumaran: Yeah, he’s, like, so he works for some big-ass law firm, he works from home in Brooklyn, all he does is, like, decks. Like, like, very, like, fast, like, for deals and stuff, and then also, like, longer-term stuff. All he does is presentations. I was like, sick.
45 00:08:52.309 ⇒ 00:08:57.609 Uttam Kumaran: Word, let’s go. You know? But, like, that’s the stuff that Sheshu has to come in and be like, cool.
46 00:08:58.209 ⇒ 00:09:08.829 Uttam Kumaran: I… we… because now I have, like, I have, like, 5 other roles that I need to basically go do that for. Like, connect me with everybody who knows anything about dbt in Austin, or Dallas, or Houston, like.
47 00:09:09.279 ⇒ 00:09:11.129 Uttam Kumaran: go. You know?
48 00:09:11.309 ⇒ 00:09:13.899 Robert Tseng: That’s the sort of stuff that I… that we need to happen.
49 00:09:15.439 ⇒ 00:09:22.419 Uttam Kumaran: Otherwise, again, we’re gonna have to either… there’s two things that have to happen. One is then, if we can’t do that, then we’ll have to go through headhunting.
50 00:09:22.549 ⇒ 00:09:24.559 Uttam Kumaran: And the fees are really horrible.
51 00:09:24.849 ⇒ 00:09:30.149 Uttam Kumaran: But our, kind of, network is, like, kind of getting exhausted. So, like, that’s… Yeah.
52 00:09:30.699 ⇒ 00:09:40.949 Uttam Kumaran: But see, that’s, like, part of the… I don’t want to react, but that’s, like, what I need from recruiting, really. It’s, like, a recruiting ops, like, get me in front of, like, get me in front of a bunch of people. Like, I don’t want to hand off the qualification.
53 00:09:41.139 ⇒ 00:09:42.999 Uttam Kumaran: It’s not that hard to qualify people.
54 00:09:43.439 ⇒ 00:09:47.249 Uttam Kumaran: Whether they’re good or not, right now, you know?
55 00:09:47.649 ⇒ 00:09:50.769 Uttam Kumaran: because we’re just handling… we’re just hiring technical talent, so I’m, like, within…
56 00:09:50.879 ⇒ 00:09:56.129 Uttam Kumaran: From their resume itself, I’m like, good or bad, and then I call them, I’m like, cool, move or don’t move.
57 00:09:56.279 ⇒ 00:09:57.089 Uttam Kumaran: It’s like…
58 00:09:57.090 ⇒ 00:09:57.820 Robert Tseng: Yeah.
59 00:09:57.820 ⇒ 00:10:00.180 Uttam Kumaran: not that hard. We’re not… we’re not looking for, like.
60 00:10:00.910 ⇒ 00:10:05.619 Uttam Kumaran: We’re not hiring, like, multi-hundred-thousand dollar, like, super long-term folks, so…
61 00:10:06.780 ⇒ 00:10:10.080 Uttam Kumaran: Like, as we… dude, half our crew I hired, like, off one call.
62 00:10:11.680 ⇒ 00:10:13.739 Robert Tseng: So… Oh, oh, oh, oh yeah, okay.
63 00:10:13.740 ⇒ 00:10:16.800 Uttam Kumaran: Half our existing crew, I hired off, like, one call.
64 00:10:17.190 ⇒ 00:10:18.760 Uttam Kumaran: No technical interview.
65 00:10:19.890 ⇒ 00:10:26.820 Uttam Kumaran: You know, as it’s sort of, like… so that’s why it’s just, like, most of our stuff is increasing our top of funnel.
66 00:10:27.400 ⇒ 00:10:27.930 Robert Tseng: Yeah.
67 00:10:30.450 ⇒ 00:10:34.250 Uttam Kumaran: Okay, cool, so I’m okay with that for Hannah. Why don’t we… we can…
68 00:10:34.410 ⇒ 00:10:37.139 Uttam Kumaran: Why don’t you want us to just draft?
69 00:10:37.260 ⇒ 00:10:40.069 Uttam Kumaran: I guess maybe we can work on the scope.
70 00:10:41.190 ⇒ 00:10:43.410 Uttam Kumaran: And then draft an amendment contract.
71 00:10:43.890 ⇒ 00:10:44.490 Robert Tseng: Yeah.
72 00:10:49.440 ⇒ 00:10:57.539 Robert Tseng: Yeah, I mean, told her to give me a draft of her scope, I can help edit it, but yeah, but on our side, we’ll just do a contract amendment there.
73 00:10:57.540 ⇒ 00:10:58.240 Uttam Kumaran: Okay, good.
74 00:11:01.260 ⇒ 00:11:02.970 Robert Tseng: Yeah. And then…
75 00:11:02.970 ⇒ 00:11:04.690 Uttam Kumaran: Amber, same thing, like…
76 00:11:04.990 ⇒ 00:11:10.560 Uttam Kumaran: like, it’s funny, because Clarence was kind of like, is Amber happy or sad? I’m like, dude, Amber’s like…
77 00:11:10.720 ⇒ 00:11:16.689 Uttam Kumaran: It’s hard to read, Amber. I think she’s happy, I think she loves this type of data work, dude.
78 00:11:16.890 ⇒ 00:11:24.769 Uttam Kumaran: So, I also… but I sort of want to make sure that, like, I think she wants to kind of go more CSO. I don’t think she has, like, the…
79 00:11:25.600 ⇒ 00:11:30.389 Uttam Kumaran: I don’t know, it’s sort of tough. Sometimes, like, ABC is a really easy client, because they’re so kind.
80 00:11:30.670 ⇒ 00:11:35.769 Uttam Kumaran: But I don’t know if she has, like, the EQ to sort of really do the relationship building.
81 00:11:35.910 ⇒ 00:11:43.990 Uttam Kumaran: Yeah. Like, I think… but also, she’s… she’s probably the most AI-enabled data person That we have, like.
82 00:11:43.990 ⇒ 00:11:44.829 Robert Tseng: Yeah, yeah, yeah.
83 00:11:44.830 ⇒ 00:11:50.719 Uttam Kumaran: You know, so she’s ripping… she’s basically doing, like, extremely fast analysis, all through cursors, so…
84 00:11:50.910 ⇒ 00:11:53.659 Uttam Kumaran: I would like her to just kind of, like, go deeper there.
85 00:11:53.800 ⇒ 00:11:57.229 Uttam Kumaran: I’m not sure how much, like… I think maybe her…
86 00:11:57.500 ⇒ 00:12:01.590 Uttam Kumaran: her, like, mindset is, like, I need to get kind of towards the revenue side of the business.
87 00:12:01.820 ⇒ 00:12:04.279 Uttam Kumaran: I don’t necessarily think that’s where her skill set is.
88 00:12:04.940 ⇒ 00:12:11.879 Uttam Kumaran: like, relationship building, and I think she’s just, like, actual, just, like, a machine, and more of where she should go is, like.
89 00:12:12.050 ⇒ 00:12:18.010 Uttam Kumaran: Amber, as Clarence, that role, which is, like, EP into, like, how do you automate more shit.
90 00:12:18.670 ⇒ 00:12:19.770 Clarence Stone: Yup, and .
91 00:12:19.770 ⇒ 00:12:32.330 Uttam Kumaran: What I like about her is she’s super direct, and because she doesn’t have, like, as much EQ, she’s, like, so direct, and she’s just like, why isn’t this happening? And I love that, like, we should use her as bad cop to go get everybody to use more AI.
92 00:12:33.290 ⇒ 00:12:35.010 Uttam Kumaran: Because she’ll just be like, why didn’t you?
93 00:12:35.010 ⇒ 00:12:35.360 Clarence Stone: That’s…
94 00:12:35.360 ⇒ 00:12:36.890 Uttam Kumaran: It’s, like, very basic, you know?
95 00:12:37.080 ⇒ 00:12:40.000 Clarence Stone: That’s what I wanna… okay, if there is…
96 00:12:40.000 ⇒ 00:13:01.020 Clarence Stone: you know, a more prevalent notion within the company’s culture that, like, the only way to progress and be successful is to have client-facing roles. We want to be able to quickly buck that trend and really show that, you know, you can add value immensely to an organization in so many different ways, right? Especially when it comes to finding internal alignment.
97 00:13:01.020 ⇒ 00:13:01.950 Clarence Stone: I mean…
98 00:13:02.230 ⇒ 00:13:12.310 Clarence Stone: that’s so much more powerful and useful to the organization than, you know, having somebody on the, you know, frontline having client conversations when they’re not quite comfortable yet. So,
99 00:13:12.740 ⇒ 00:13:30.430 Clarence Stone: exactly what you said, Nutan, but I also want her to then look into the data and say, hey, these are marketing opportunities, or sector opportunities, or, you know, service opportunities that we’re not capturing, because she’s doing data analytics. Why not take a look at our own data and find those optimizations, too?
100 00:13:30.430 ⇒ 00:13:33.190 Uttam Kumaran: No, she could totally do that, yeah, and so that’ll be, like.
101 00:13:33.190 ⇒ 00:13:34.519 Clarence Stone: As soon as…
102 00:13:35.130 ⇒ 00:13:41.559 Uttam Kumaran: Yeah, as soon as… she already did the first couple versions of our internal stuff, there’s just no owner, like, I can’t have her own it.
103 00:13:41.740 ⇒ 00:13:49.349 Uttam Kumaran: So, like, Sheshu or whoever will own the creation of them, and then… the problem is… the good thing is, dude, we’re all, like, data people, so, like.
104 00:13:49.670 ⇒ 00:13:54.660 Uttam Kumaran: I don’t need her to go look at our margin and tell me, like, where we’re making money, like, I think we’ll be fine there.
105 00:13:54.860 ⇒ 00:14:00.630 Uttam Kumaran: I just need her to accelerate other people, and I like her because she doesn’t… She’s sort of, like.
106 00:14:00.740 ⇒ 00:14:02.630 Uttam Kumaran: because I think she, like.
107 00:14:02.890 ⇒ 00:14:08.849 Uttam Kumaran: doesn’t… she, like… I don’t know if it’s, like, lacks empathy, but she’s just so blunt that it’s actually very helpful.
108 00:14:08.960 ⇒ 00:14:14.709 Uttam Kumaran: Like, I do want to leverage her to basically go to people and be like, why aren’t you using AI, or why aren’t you moving fast enough?
109 00:14:15.680 ⇒ 00:14:18.150 Uttam Kumaran: I think that’s a great way to leverage her.
110 00:14:20.160 ⇒ 00:14:20.730 Robert Tseng: Okay.
111 00:14:21.460 ⇒ 00:14:22.730 Robert Tseng: Yeah, well, I mean…
112 00:14:22.730 ⇒ 00:14:29.160 Clarence Stone: I don’t want her to feel like doing that is a step backwards in comparison to someone doing market-facing activity.
113 00:14:29.160 ⇒ 00:14:38.749 Uttam Kumaran: No, I just think she… yeah, I don’t think… I think if we ex… but if we explain that there is both money and, like, responsibility in this other thing, then she’ll be fine.
114 00:14:38.750 ⇒ 00:14:39.380 Clarence Stone: Okay.
115 00:14:42.120 ⇒ 00:14:45.470 Robert Tseng: Okay. Well, yeah, I mean, I think, I think we can, we can,
116 00:14:45.580 ⇒ 00:14:54.159 Robert Tseng: discuss, like, kind of more… I mean, we should just… we should document some of this stuff, too, and I mean, we haven’t revisited her scope of work in a while, so I think she’s
117 00:14:54.500 ⇒ 00:15:01.870 Robert Tseng: she wants to discuss it, and she asked for it, so… I’m expecting, if I go to LA, she’ll want to talk about it then.
118 00:15:02.660 ⇒ 00:15:05.300 Uttam Kumaran: Okay, yeah, I think she’s great. I would like her to…
119 00:15:05.510 ⇒ 00:15:11.270 Uttam Kumaran: just kind of push people back. Because, yeah, a lot of this… a lot of this data analysis, dude, you could rip really fast, and…
120 00:15:11.410 ⇒ 00:15:13.279 Uttam Kumaran: I feel like a lot of our analysts
121 00:15:13.410 ⇒ 00:15:18.229 Uttam Kumaran: especially because they’re not… they’re not as technical, will be slow to adopt AI.
122 00:15:18.470 ⇒ 00:15:21.809 Uttam Kumaran: And it’s, in fact, like, running queries and running a bunch of them.
123 00:15:22.090 ⇒ 00:15:28.159 Uttam Kumaran: And having AI sort of give you a little bit of the story first is, like, speeds up the process a lot.
124 00:15:28.900 ⇒ 00:15:29.530 Robert Tseng: Yeah.
125 00:15:29.750 ⇒ 00:15:44.939 Robert Tseng: On the analyst side, I think for juniors, we should just get more background like her, where they’re, like, not… they’re not true… they’re not… haven’t been corrupted by industry yet. They really learn how to do it from the ground up, the Brainforged way, like, yeah, and then…
126 00:15:44.940 ⇒ 00:15:50.629 Uttam Kumaran: That’s what I don’t know, like, maybe I should just, like, try… we should, like, yeah, I need to figure out, like, what this person is.
127 00:15:50.630 ⇒ 00:15:51.770 Robert Tseng: Congrats, yeah.
128 00:15:54.480 ⇒ 00:15:59.610 Uttam Kumaran: Yeah, the problem with analysis, I don’t know if you feel like this, it’s like, everybody kind of figures out the way that works for them.
129 00:15:59.870 ⇒ 00:16:04.260 Uttam Kumaran: They kind of, like, never shed that, whether it’s their, like, shitty spreadsheet or whatever.
130 00:16:04.260 ⇒ 00:16:05.600 Robert Tseng: Yeah, yeah.
131 00:16:05.600 ⇒ 00:16:09.109 Uttam Kumaran: I mean, yeah, I’m not gonna at anybody, but…
132 00:16:09.330 ⇒ 00:16:15.849 Uttam Kumaran: more saying it’s, like, everybody figures out what’s good for them, versus, like, this is something brand new, like, Amber’s probably just, like.
133 00:16:16.360 ⇒ 00:16:22.560 Uttam Kumaran: Like, I wanted… I wish I could watch her, how she does cursor stuff, because… until she’s moving really, really fast.
134 00:16:24.190 ⇒ 00:16:24.760 Robert Tseng: Yeah.
135 00:16:25.440 ⇒ 00:16:32.530 Uttam Kumaran: And it’d be a shame if we, like, have people, like, doing VLOOKUPs.
136 00:16:32.980 ⇒ 00:16:33.950 Robert Tseng: Yeah.
137 00:16:34.730 ⇒ 00:16:53.090 Robert Tseng: I mean, even for the short time that Sezen was here, Amber pairing with Sezen for a couple times, like, completely… I mean, it… I think it helped her a lot, so… and Sezen was, like, not that skilled, so she was impressionable. I think she was probably lacking in some of the raw talent in terms of how fast she would pick things up compared to
138 00:16:53.090 ⇒ 00:17:01.909 Robert Tseng: to Amber, but Amber can impact other people that are, like, just coming out of… and transitioning over, and she helps… she helps them pick it up quickly, too. So I think it’s just, like.
139 00:17:02.030 ⇒ 00:17:12.560 Robert Tseng: if we can get more raw talent that’s, like, able to be maybe molded more into, like, an amber type, like, I think we could… we should… we should leverage her to do that. Yeah.
140 00:17:13.359 ⇒ 00:17:17.899 Uttam Kumaran: Yeah, I met a bunch of kids at this UT thing I did who, like, wanted to get into data.
141 00:17:18.569 ⇒ 00:17:24.189 Uttam Kumaran: Maybe I’ll… I need to… They all emailed me, I didn’t get back to anybody.
142 00:17:25.479 ⇒ 00:17:27.859 Uttam Kumaran: Yeah. Okay.
143 00:17:29.849 ⇒ 00:17:31.029 Uttam Kumaran: Yeah.
144 00:17:31.309 ⇒ 00:17:35.449 Uttam Kumaran: And then, do you want to… should we… can we make a decision on Jasmine, or how do we feel?
145 00:17:37.560 ⇒ 00:17:39.750 Robert Tseng: Yeah.
146 00:17:40.260 ⇒ 00:17:41.400 Uttam Kumaran: Or do you guys chat?
147 00:17:42.540 ⇒ 00:17:45.749 Robert Tseng: Yeah, yeah, Clarence and I briefly chatted on this, yeah.
148 00:17:47.650 ⇒ 00:17:50.440 Uttam Kumaran: I just want to reference your message with him. So…
149 00:17:51.060 ⇒ 00:17:56.689 Robert Tseng: But yeah, so if she’s not… I guess Clarence’s point was that she…
150 00:17:59.630 ⇒ 00:18:02.700 Robert Tseng: wants to just be an IC, right? And, like…
151 00:18:04.460 ⇒ 00:18:18.269 Robert Tseng: is interested in the EP role, doesn’t… does not want to be a CSO, and, like, do we… do we want to have someone like that? That… I don’t think that’s a really… that’s not really a head of delivery, that’s just, like, a senior analyst to me.
152 00:18:18.780 ⇒ 00:18:20.849 Robert Tseng: I still think that she’s good, so, but I mean.
153 00:18:20.850 ⇒ 00:18:24.019 Uttam Kumaran: Yeah, I think for that role, that’s… yeah, I feel fine.
154 00:18:24.420 ⇒ 00:18:24.830 Robert Tseng: Yeah.
155 00:18:24.830 ⇒ 00:18:27.659 Uttam Kumaran: If that’s a criteria, then I feel totally fine. Yeah.
156 00:18:28.490 ⇒ 00:18:29.070 Robert Tseng: Okay.
157 00:18:31.350 ⇒ 00:18:42.870 Robert Tseng: Yeah, but I guess we were trying to see, like, how do we… is there, like, something that we can start her part-time on without her having to, like, kind of be a part of the rituals? Like, because, like…
158 00:18:43.760 ⇒ 00:18:56.860 Robert Tseng: I mean, on the strategy analytics side, unless I sell more, which is just gonna take me… take me a few weeks to kind of… to… to bring… bring more, back… back into this… this side of the… the business, like.
159 00:18:56.860 ⇒ 00:19:04.130 Robert Tseng: she’s not gonna have a full-time… she doesn’t have full-time… a full-time amount of work, just being an EP and IC right now.
160 00:19:05.470 ⇒ 00:19:13.910 Robert Tseng: Like, she doesn’t seem like she’ll go in to start a new engagement, like, she’s not gonna want to co-sell, she’s not gonna be, like, an early-stage kind of, like…
161 00:19:14.210 ⇒ 00:19:17.210 Robert Tseng: Client person, like…
162 00:19:20.210 ⇒ 00:19:23.820 Uttam Kumaran: Yeah, I think, I mean, I just… I would just say she’s, like, a senior analyst on your team.
163 00:19:23.820 ⇒ 00:19:24.360 Robert Tseng: Yeah.
164 00:19:24.710 ⇒ 00:19:31.259 Uttam Kumaran: But if she can’t start part-time, then I’m… Like, basically out.
165 00:19:31.260 ⇒ 00:19:31.780 Robert Tseng: Yeah.
166 00:19:32.350 ⇒ 00:19:37.349 Uttam Kumaran: I’m basically out, because I can’t… we can’t… we… it’s, like, too much of a risk. I’ll find you more people.
167 00:19:37.870 ⇒ 00:19:38.430 Robert Tseng: Yeah.
168 00:19:40.540 ⇒ 00:19:47.739 Uttam Kumaran: It’s just how we do things right now, you know? So, like, she can help… she can help coach or, like, review stuff.
169 00:19:48.240 ⇒ 00:19:48.940 Uttam Kumaran: But…
170 00:19:48.940 ⇒ 00:19:49.550 Robert Tseng: Yeah.
171 00:19:50.820 ⇒ 00:20:02.819 Robert Tseng: Yeah, maybe that’s a way to kind of get her part-time for now, just so she can learn enough about us, like, what we do, and yeah, maybe that’s… maybe that would be the only option for her to move forward.
172 00:20:04.460 ⇒ 00:20:12.110 Uttam Kumaran: Yeah, because I think I’m gonna find you more senior people who are, like, work from home, who can start part-time for us to test.
173 00:20:12.270 ⇒ 00:20:13.380 Uttam Kumaran: And then ramp.
174 00:20:13.630 ⇒ 00:20:15.249 Uttam Kumaran: Like, I think I’m gonna get that.
175 00:20:18.620 ⇒ 00:20:24.929 Uttam Kumaran: I also think maybe we gotta hire… we gotta hire, like, industry people, like, people who are in these… in the business… in, like.
176 00:20:25.450 ⇒ 00:20:30.520 Uttam Kumaran: The go-to, like, the top 20. Like, maybe I go to, like.
177 00:20:31.450 ⇒ 00:20:35.730 Uttam Kumaran: I find someone who’s working as, like, some deep, analysts at, like, Kroger.
178 00:20:35.980 ⇒ 00:20:38.250 Uttam Kumaran: Or, like, an analyst that, like.
179 00:20:39.080 ⇒ 00:20:43.089 Uttam Kumaran: I don’t know, some other, like, big companies, we just try to poach them, versus, like.
180 00:20:43.490 ⇒ 00:20:46.199 Uttam Kumaran: Finding true consultants for this stuff.
181 00:20:49.250 ⇒ 00:20:55.840 Robert Tseng: So… we were… like, the head of delivery, I agree, should probably be an ex-consultant.
182 00:20:55.840 ⇒ 00:20:57.240 Uttam Kumaran: At a delivery, yeah. Somebody who, yeah.
183 00:20:57.240 ⇒ 00:21:04.149 Robert Tseng: Yeah, so that… that role, I think I’m aligned that we’re just gonna have to keep finding people from that… from that world.
184 00:21:04.360 ⇒ 00:21:06.050 Robert Tseng: The senior analyst role.
185 00:21:06.100 ⇒ 00:21:22.839 Robert Tseng: I mean, the analyst role has always been kind of tough for us to hire, because it’s just… the range is so wide. And, like, yeah, I believe you’ll be able to get in front of a lot of people, but I do think this is, like, where on the recruiting side, we just need to have somebody who’s help… who’s gonna help us hire better analysts. Like, I feel like we’ve been very hit or miss with this.
186 00:21:22.840 ⇒ 00:21:35.910 Robert Tseng: like, yeah, I mean, even you saying, oh, you want to go hire a Kroger analyst? I’m like, Jacob was a good analyst, probably, for Home Depot, but, like, not for us, right? And that’s why he ended up just moving on and going to Facebook.
187 00:21:36.530 ⇒ 00:21:39.030 Robert Tseng: And… yeah, I mean, like.
188 00:21:39.720 ⇒ 00:21:54.840 Robert Tseng: even… and even Henry started out in a situation where he was doing well, and then, like, after it was, like, no longer disaster on… on Eden, like, he just didn’t know how to continue from there. It’s like, they’re… they… even… even him, who’s…
189 00:21:54.940 ⇒ 00:22:09.930 Robert Tseng: supposed to be a little bit wider than what we were finding, like, was not… not able to… like, there are no real analysts that can truly be effective at every stage of the company’s growth. It’s like, I just don’t feel like we’ve come across anybody like that yet.
190 00:22:10.080 ⇒ 00:22:29.119 Robert Tseng: And so we’re kind of helping that situation by, like, being more specific about who we’re saying no to. We’re not, like, working with everyone under the sun anymore, like, the organization, from an ICP perspective, will be… will continue to get more narrow. And hopefully the needs are more defined, even if they’re cross-context, like, it’s just, like, easier to…
191 00:22:29.120 ⇒ 00:22:44.059 Robert Tseng: like, define what that skill set is, but I think that’s, like, a… that’s a partnership that needs to happen between, like, recruiting and on the sales side, because, like, that’s gonna influence what deals I say yes to for, like, what analysts we’re able to staff there, rather than, like.
192 00:22:44.990 ⇒ 00:22:58.420 Robert Tseng: Yeah, we’re able, like, we’re able to do the low-level analyst stuff pretty well now, and very quickly with the AI work, but somebody to actually, like, do change management with the analytics, we don’t have anybody on staff that’s able to do that.
193 00:23:01.710 ⇒ 00:23:03.000 Uttam Kumaran: Yeah, I agree.
194 00:23:03.840 ⇒ 00:23:05.059 Uttam Kumaran: So we sort of, like.
195 00:23:05.060 ⇒ 00:23:12.389 Robert Tseng: And that’s the high leverage stuff that we’re gonna be billing the $2.50 an hour plus for, for on the analytics stuff… on the analytics side.
196 00:23:12.580 ⇒ 00:23:15.680 Robert Tseng: Yeah.
197 00:23:16.150 ⇒ 00:23:23.730 Robert Tseng: So, in order to really build, like, a… like, a long-standing strategy and analytics organization, like,
198 00:23:24.010 ⇒ 00:23:36.330 Robert Tseng: Yeah, we’re gonna have to have this, like… yeah, like, the junior analyst role, I agree, we’re very good at hiring this now, we can… I have no problem. As those needs come up, we’ll be able to go and find people and train them up quickly to do it, the Brainforge way.
199 00:23:36.500 ⇒ 00:23:40.229 Robert Tseng: But yeah, we just… we’re not good at hiring senior analysts when we don’t know
200 00:23:40.710 ⇒ 00:23:41.500 Robert Tseng: It’ll be a risk either way.
201 00:23:41.500 ⇒ 00:23:42.340 Uttam Kumaran: banker?
202 00:23:43.000 ⇒ 00:23:43.800 Uttam Kumaran: Yeah, we didn’t.
203 00:23:43.800 ⇒ 00:23:44.280 Robert Tseng: Well, we thought.
204 00:23:44.280 ⇒ 00:23:44.790 Uttam Kumaran: The highest…
205 00:23:44.790 ⇒ 00:23:48.760 Robert Tseng: be a good one, like, yeah, bias coming in, somebody who’s, like.
206 00:23:49.000 ⇒ 00:24:04.419 Robert Tseng: he thinks in systems, can just, like, build up a spreadsheet model really quickly, but he’s also just, like, a Python savant or whatever. I mean, he just, personality-wise, he wasn’t a good fit for us. But, like, yeah, somebody of that… of that… of that background. Getting the pure tech analysts, like.
207 00:24:04.420 ⇒ 00:24:12.450 Robert Tseng: trained in Meta, or Google, or Amazon. We… I mean, I’ve hired a couple of those, like, they… they’re not good, they’re very, like, narrow in their scope.
208 00:24:12.490 ⇒ 00:24:29.599 Robert Tseng: I think Jasmine is a… was a bit of a mix, because she was in a strategy and operations role at DoorDash, and kind of pivoted a couple different departments, so she got a wide range of skills, but just within one organization. So, I just, you know, she just may be a little bit,
209 00:24:30.010 ⇒ 00:24:33.090 Robert Tseng: Yeah, well, anyway, it’s a pseudo-consulting background.
210 00:24:33.090 ⇒ 00:24:37.259 Uttam Kumaran: Is this the role we’re having the most difficulty with?
211 00:24:37.530 ⇒ 00:24:38.570 Robert Tseng: Yeah, I think so.
212 00:24:38.830 ⇒ 00:24:40.700 Uttam Kumaran: But then this is what I’m gonna ask Shashu.
213 00:24:40.700 ⇒ 00:24:43.019 Robert Tseng: This and the go-to-market.
214 00:24:43.620 ⇒ 00:24:44.199 Robert Tseng: I always…
215 00:24:44.200 ⇒ 00:24:44.650 Uttam Kumaran: Yeah. So sports.
216 00:24:44.650 ⇒ 00:24:46.419 Robert Tseng: Sales coordinator, yeah.
217 00:24:47.020 ⇒ 00:24:52.990 Uttam Kumaran: So then… then I think for the… for the first 30, 60, 90 days, we tell Sheshu, like, you have to build
218 00:24:53.140 ⇒ 00:25:00.540 Uttam Kumaran: A process, like, a repeatable process, and the first sort of target is, like, hiring this this person.
219 00:25:00.730 ⇒ 00:25:06.319 Uttam Kumaran: And… Yeah, because I also agree, you need… we should look… we need to look for, like.
220 00:25:08.410 ⇒ 00:25:13.230 Uttam Kumaran: like, yeah, M&A, banker types, maybe with a background in data.
221 00:25:13.900 ⇒ 00:25:16.390 Uttam Kumaran: Or, like, some of those people that want to leave.
222 00:25:17.550 ⇒ 00:25:24.290 Uttam Kumaran: Because you do… I do… you kind of, like, that kind of work, did you need some, like, real FP&A, like, kind of, like, strict people?
223 00:25:24.940 ⇒ 00:25:30.189 Uttam Kumaran: Yeah. But then, but then, yeah, for, like, marketing analysis and stuff like that.
224 00:25:32.920 ⇒ 00:25:42.359 Uttam Kumaran: you kind of need, like, someone to run decks in the meeting, and then that person has, like, a couple analysts, like, that could just do spreadsheets, or do their domain stuff, and, like, surface it.
225 00:25:43.700 ⇒ 00:25:45.850 Uttam Kumaran: Like, that’s why, like, PE people…
226 00:25:47.100 ⇒ 00:25:52.859 Uttam Kumaran: like, yeah, like, M&A people, bankers, like, that’s all they… this is, like, kind of what they do.
227 00:25:53.930 ⇒ 00:25:54.490 Robert Tseng: Yeah.
228 00:25:55.050 ⇒ 00:25:59.409 Robert Tseng: I’m gonna spend some more time over the weekend kind of thinking about, like, how to, like.
229 00:26:00.570 ⇒ 00:26:02.699 Robert Tseng: How to describe this.
230 00:26:03.420 ⇒ 00:26:12.949 Uttam Kumaran: I wonder if also you can… I wonder if you can… what you can do is you can write it down, and then ask ChatGPT to give you firms where this is the type of work they do.
231 00:26:13.250 ⇒ 00:26:16.040 Uttam Kumaran: Like, are there strategy firms?
232 00:26:16.770 ⇒ 00:26:19.559 Uttam Kumaran: That we should try to go poach from, maybe.
233 00:26:20.070 ⇒ 00:26:25.060 Clarence Stone: I know someone who can do both of those things for you guys, but he’s gonna be expensive.
234 00:26:25.440 ⇒ 00:26:26.450 Uttam Kumaran: How expensive?
235 00:26:27.210 ⇒ 00:26:28.280 Clarence Stone: 240.
236 00:26:28.990 ⇒ 00:26:30.009 Uttam Kumaran: 240 an hour?
237 00:26:30.420 ⇒ 00:26:32.910 Clarence Stone: No, 240 as a salary.
238 00:26:33.950 ⇒ 00:26:34.969 Uttam Kumaran: Oh, that’s fine.
239 00:26:35.270 ⇒ 00:26:36.520 Uttam Kumaran: If he’s that good.
240 00:26:37.030 ⇒ 00:26:41.090 Clarence Stone: Yeah, y’all should talk to him. I mean, so, background on…
241 00:26:41.390 ⇒ 00:26:50.530 Clarence Stone: Mike E, by the way, he’s also out of LA. He’s a CPA that worked directly with the hedge fund, and then joined EY Consulting.
242 00:26:51.650 ⇒ 00:27:00.760 Clarence Stone: So, he’s got a lot of data analytics skill sets, and then a lot of change management implementation type skill sets, and a lot of client presentation skill sets.
243 00:27:05.550 ⇒ 00:27:08.550 Uttam Kumaran: Yeah, I mean, I think he could probably end up making that or more here.
244 00:27:08.550 ⇒ 00:27:12.610 Clarence Stone: Like, because it’s a… that’s… we only have one robber, basically, that could do that, so…
245 00:27:12.930 ⇒ 00:27:17.720 Clarence Stone: I had a car conversation with him in the Tesla a few days ago, and I was just like.
246 00:27:18.180 ⇒ 00:27:26.760 Clarence Stone: you know, that number’s not impossible. If you, like, actually were doing exactly what you’re doing at EY here, like, I think you would be able to hit that. And he’s like.
247 00:27:26.760 ⇒ 00:27:33.440 Uttam Kumaran: No, I… I also… Robert and I have talked about this. We’re not paying people very high for, like, what is…
248 00:27:33.930 ⇒ 00:27:38.169 Uttam Kumaran: What you can really make as a good data person here, like… I have friends that…
249 00:27:39.030 ⇒ 00:27:43.050 Uttam Kumaran: like, our, like, mid at data, making more than that.
250 00:27:45.420 ⇒ 00:27:53.810 Uttam Kumaran: And so, it’s not that bad. Like, I don’t think that’s, like… yes, from, like, a Brain Forge perspective, it’s a… it is… it is a lot, but in the industry, it’s, like.
251 00:27:54.410 ⇒ 00:27:56.330 Uttam Kumaran: Not that… not that pricey.
252 00:27:56.710 ⇒ 00:27:57.949 Uttam Kumaran: producing LA.
253 00:27:58.710 ⇒ 00:28:01.950 Uttam Kumaran: Yeah, dude, should… can I… can we… can we talk to him? And then Robert’s gone.
254 00:28:01.950 ⇒ 00:28:12.570 Clarence Stone: Absolutely. I’ll do a warm intro to you guys, and you guys speak to Mike. Really good kid, man. He’s got Passover promotion three times in a row now, so…
255 00:28:13.080 ⇒ 00:28:17.690 Clarence Stone: He’s got no excuses. As soon as there’s a good offer, he should be taking it.
256 00:28:18.760 ⇒ 00:28:19.500 Uttam Kumaran: Nice.
257 00:28:19.970 ⇒ 00:28:22.850 Clarence Stone: Yeah, and so I just want to throw in there, like.
258 00:28:24.060 ⇒ 00:28:42.280 Clarence Stone: out of all of these things, we’re talking about pretty high-level senior roles. I just want to make sure that you guys also put into somewhere in the factors of evaluating how well you work with, you know, some of the people that are… or you think you will work with, some of the people that you’re hiring, because
259 00:28:42.620 ⇒ 00:28:46.790 Clarence Stone: I… sometimes, my personal experience, that beats everything. Like.
260 00:28:46.790 ⇒ 00:28:47.799 Uttam Kumaran: What do you mean? Say it again?
261 00:28:47.800 ⇒ 00:28:48.310 Clarence Stone: not have.
262 00:28:48.310 ⇒ 00:28:48.799 Uttam Kumaran: Say it one more time?
263 00:28:48.800 ⇒ 00:28:57.329 Clarence Stone: They’re raw talent, but if they’re, like, somebody that takes feedback well and just, like, really kind and easy to hang out with, like, they’ll pick it up, you know?
264 00:28:57.750 ⇒ 00:28:58.150 Robert Tseng: Yeah.
265 00:28:58.150 ⇒ 00:28:59.779 Clarence Stone: Just want to throw that in there.
266 00:28:59.780 ⇒ 00:29:04.949 Uttam Kumaran: No, we definitely are, but I think, like, when it gets to more technical stuff.
267 00:29:05.540 ⇒ 00:29:11.470 Uttam Kumaran: for me, you kind of have to, like… I kind of… can’t wait for you to learn SQL, like, at some minimums.
268 00:29:11.470 ⇒ 00:29:14.489 Clarence Stone: analytics, you need the… you need to bring the goods, but…
269 00:29:14.490 ⇒ 00:29:16.959 Uttam Kumaran: Yeah, but once you get into this world.
270 00:29:17.170 ⇒ 00:29:21.910 Uttam Kumaran: Yeah, like, I would rather them be good at putting deck together and having strategy.
271 00:29:22.040 ⇒ 00:29:27.699 Uttam Kumaran: But, like, be like, I’ve never done any SQL, because I only do Excel, like, I don’t care about that.
272 00:29:28.440 ⇒ 00:29:32.780 Uttam Kumaran: Because we’re gonna staff junior people under these… the more senior folks.
273 00:29:33.290 ⇒ 00:29:37.330 Uttam Kumaran: Their job is more on the client presentation and, like, rolling with the punches.
274 00:29:37.560 ⇒ 00:29:41.910 Uttam Kumaran: You know, like, being able to walk into ABC and do that presentation, you know, type of stuff.
275 00:29:45.020 ⇒ 00:29:51.249 Uttam Kumaran: All those types of people I just know are, like, ex-bankers. Like, I… when I’ve worked with those people in companies.
276 00:29:51.660 ⇒ 00:29:58.810 Uttam Kumaran: most of those people are all, like, yeah, ex-bankers or PE that kind of wanted to go in-house.
277 00:29:59.150 ⇒ 00:30:01.870 Clarence Stone: There should be a shit ton of them available, we just gotta find those.
278 00:30:01.870 ⇒ 00:30:04.999 Uttam Kumaran: Oh, yeah, so if we talk to him, we’ll start to put the profile together, and then I think.
279 00:30:05.000 ⇒ 00:30:13.459 Clarence Stone: There’s gotta be a bunch of them. Like, they just shed a ton of people. Deloitte just, fired a bunch of senior manager CPAs, yesterday.
280 00:30:18.240 ⇒ 00:30:27.869 Uttam Kumaran: Yeah, this is the thing, like, so if we just get all these… but this is, again, this is the thing I want Shashi to work on, is, like, build a repeatable process for us to go from JD to, like, 100 people to target.
281 00:30:27.970 ⇒ 00:30:31.740 Uttam Kumaran: You’re basically doing, like, Sorcerer’s job.
282 00:30:34.100 ⇒ 00:30:38.919 Uttam Kumaran: we already do this, like, really what Ryan does, basically what Ryan does.
283 00:30:41.100 ⇒ 00:30:43.520 Uttam Kumaran: Oh. Okay, I’m gonna go,
284 00:30:44.090 ⇒ 00:30:46.200 Uttam Kumaran: I’m gonna go talk to a growth assistant.
285 00:30:46.770 ⇒ 00:30:47.340 Robert Tseng: Okay.
286 00:30:47.600 ⇒ 00:30:49.050 Robert Tseng: Alright, thanks guys.
287 00:30:49.360 ⇒ 00:30:49.680 Clarence Stone: Awesome.
288 00:30:49.680 ⇒ 00:30:52.050 Uttam Kumaran: Okay, perfect. Thank you all. Talk to you soon.