Meeting Title: Brainforge x EY Project Strategy Sync Date: 2026-01-19 Meeting participants: Uttam Kumaran, Clarence Stone, Rico Rejoso
WEBVTT
1 00:00:10.890 ⇒ 00:00:11.969 Clarence Stone: We meet again.
2 00:00:12.840 ⇒ 00:00:14.625 Uttam Kumaran: Yeah, I guess.
3 00:00:17.130 ⇒ 00:00:19.169 Uttam Kumaran: Trying to work on the skin.
4 00:00:20.110 ⇒ 00:00:23.890 Uttam Kumaran: snowflake thing. I’ve got a free breath, but…
5 00:00:24.020 ⇒ 00:00:27.240 Uttam Kumaran: I’ve thought about it all day, so I kinda… Yeah.
6 00:00:30.930 ⇒ 00:00:31.780 Clarence Stone: Yeah.
7 00:00:32.880 ⇒ 00:00:34.579 Clarence Stone: It’s been a lot of meetings today.
8 00:00:34.990 ⇒ 00:00:36.300 Clarence Stone: Brainflip side.
9 00:00:36.410 ⇒ 00:00:37.320 Clarence Stone: Good.
10 00:00:38.820 ⇒ 00:00:44.259 Uttam Kumaran: It’s good, I mean, dude, this is, like, this is, like, the most normal day I’ve had as, like,
11 00:00:44.550 ⇒ 00:00:49.080 Uttam Kumaran: I prayed for it all on time, like, in terms of, like, calmness.
12 00:00:52.590 ⇒ 00:00:55.090 Clarence Stone: That’s good. This is how we need to keep it.
13 00:01:19.980 ⇒ 00:01:24.169 Clarence Stone: Yeah, so that video that I left you in that leadership chat.
14 00:01:24.170 ⇒ 00:01:24.770 Uttam Kumaran: Yeah.
15 00:01:26.100 ⇒ 00:01:31.020 Clarence Stone: You gotta watch it. I think I changed my mind. I think everybody should be an engineer.
16 00:01:32.140 ⇒ 00:01:35.270 Uttam Kumaran: Well, I always thought that. There’s no room for others.
17 00:01:35.760 ⇒ 00:01:43.030 Uttam Kumaran: You’re an engineer, dude, I always forget. You’re an engineer, so you’re part of it, you’re part of the squad, but yeah, dude, there’s no other… there’s no other roles.
18 00:01:43.600 ⇒ 00:01:47.390 Clarence Stone: I… I overthink it, but, like, as far as…
19 00:01:47.840 ⇒ 00:02:03.989 Clarence Stone: you know, the bar that he describes is, like, somebody in marketing comes up and says, like, hey, I want to chat with you, right? And he’s like, I don’t want to talk to you, you’re not part of the dev teams, right? And then he’s like, I find out that he’s making his own marketing agents. He’s a developer.
20 00:02:05.670 ⇒ 00:02:06.150 Uttam Kumaran: Yeah.
21 00:02:06.390 ⇒ 00:02:11.200 Clarence Stone: I think the bar is at least being able to produce things with AI.
22 00:02:11.650 ⇒ 00:02:23.390 Uttam Kumaran: See, our problem, dude, is, like, how do I, like… This is where, like, my…
23 00:02:24.710 ⇒ 00:02:28.449 Uttam Kumaran: how am I… how am I trying to say… what I’m trying to say is, like.
24 00:02:29.870 ⇒ 00:02:33.639 Uttam Kumaran: I think we should have that as a requirement for new people that join with that domain.
25 00:02:33.780 ⇒ 00:02:35.920 Uttam Kumaran: But I think we’re too early to do that.
26 00:02:36.460 ⇒ 00:02:37.620 Clarence Stone: Yeah. So…
27 00:02:38.550 ⇒ 00:02:49.479 Uttam Kumaran: Instead, what I’m looking for is that the people that bring come on are like Sheshu, where, like, yes, I can tell him, hey, the only thing I didn’t see here is, like, you’re not using AI to do any of this.
28 00:02:49.880 ⇒ 00:02:52.429 Uttam Kumaran: So go call a bunch of these people and figure out how to do that.
29 00:02:53.370 ⇒ 00:02:59.640 Uttam Kumaran: But, like, there’s a lot of people that are gonna be disqualified, because they’re not gonna ever… they’re gonna come in, they’re gonna try to do things the normal way.
30 00:03:01.120 ⇒ 00:03:02.150 Clarence Stone: Yeah. You know?
31 00:03:02.660 ⇒ 00:03:10.990 Clarence Stone: And I know you say that you’re too early, but I think by the end of this year, you’ll be able to have the footing to make that kind of switch.
32 00:03:11.820 ⇒ 00:03:13.240 Clarence Stone: I think it’s close.
33 00:03:13.470 ⇒ 00:03:15.900 Uttam Kumaran: Well, like, I honestly am, like, I…
34 00:03:16.650 ⇒ 00:03:23.850 Uttam Kumaran: like, Shreshu’s gonna be a real bridge between us figuring out who’s using… like, he’ll start to… we’ll start to look at Slack analytics, cursor Analytics.
35 00:03:24.160 ⇒ 00:03:26.080 Uttam Kumaran: And figuring out who’s not using it.
36 00:03:26.890 ⇒ 00:03:30.679 Uttam Kumaran: It’s more like, can we afford to add that as a criteria?
37 00:03:31.140 ⇒ 00:03:32.269 Uttam Kumaran: Like, I don’t know.
38 00:03:32.710 ⇒ 00:03:33.480 Uttam Kumaran: Yeah.
39 00:03:35.960 ⇒ 00:03:37.400 Clarence Stone: Yeah.
40 00:03:38.290 ⇒ 00:03:45.850 Uttam Kumaran: But dude, like, yeah, I mean, I’m kind of not interested in hiring anybody that isn’t gonna use this stuff, like, super, super heavy in every single role.
41 00:03:47.080 ⇒ 00:03:56.240 Clarence Stone: Here’s the thing, like, I feel like AI usage is a real low bar. You don’t have to be excellently technical to be good at using AI. Like…
42 00:03:56.240 ⇒ 00:03:59.510 Uttam Kumaran: Oh, but dude, there’s, like, a mental… some people just mentally, like…
43 00:04:00.650 ⇒ 00:04:05.930 Uttam Kumaran: they don’t… they’re not getting it. They’re not getting, like, every single thing you gotta try to use it with.
44 00:04:08.560 ⇒ 00:04:09.410 Clarence Stone: Yeah.
45 00:04:09.990 ⇒ 00:04:17.320 Clarence Stone: it’s… it’s… it’s… so… so, like, what you’re describing is, like, maybe a behavior that we’re trying to index on, right? Like.
46 00:04:17.660 ⇒ 00:04:26.159 Clarence Stone: The reason why I bring this up is it makes it easier for us to build that hiring agent if we can somehow describe that.
47 00:04:26.430 ⇒ 00:04:28.029 Clarence Stone: It’s this, like…
48 00:04:29.130 ⇒ 00:04:36.470 Clarence Stone: Willingness to try new things, right? And learn new things that matter more in this era than in the past.
49 00:04:40.220 ⇒ 00:04:41.020 Uttam Kumaran: Yeah.
50 00:04:47.480 ⇒ 00:04:48.039 Clarence Stone: like, on.
51 00:04:48.040 ⇒ 00:04:51.920 Uttam Kumaran: Dude, because if I hire one… if I hire one AI assistant marketer.
52 00:04:52.440 ⇒ 00:04:54.240 Uttam Kumaran: That may save me 3 more.
53 00:04:54.830 ⇒ 00:04:56.580 Clarence Stone: Yeah, exactly.
54 00:04:56.720 ⇒ 00:04:57.980 Clarence Stone: Exactly.
55 00:04:58.100 ⇒ 00:05:05.120 Clarence Stone: And I think, like, the communication bridge between that person and the rest of the team is gonna be a lot more smooth, too.
56 00:05:05.370 ⇒ 00:05:07.129 Clarence Stone: Remember, like, if we’re gonna think about.
57 00:05:07.130 ⇒ 00:05:07.670 Uttam Kumaran: Yeah.
58 00:05:07.670 ⇒ 00:05:09.720 Clarence Stone: This is a better node.
59 00:05:11.650 ⇒ 00:05:12.370 Uttam Kumaran: Yes.
60 00:05:15.810 ⇒ 00:05:19.740 Uttam Kumaran: So… Correct.
61 00:05:21.470 ⇒ 00:05:22.130 Uttam Kumaran: Bye.
62 00:05:23.270 ⇒ 00:05:27.980 Clarence Stone: Yeah, so it’s not that, like, they have to be deeply technical, but rather, like.
63 00:05:29.060 ⇒ 00:05:36.330 Clarence Stone: willing to look at the problem and say, how do I use the new tools available for me
64 00:05:36.510 ⇒ 00:05:37.780 Clarence Stone: to do this.
65 00:05:40.020 ⇒ 00:05:43.800 Clarence Stone: It’s… it’s a weird way to describe a behavior.
66 00:05:44.150 ⇒ 00:05:44.800 Clarence Stone: I can’t call.
67 00:05:44.800 ⇒ 00:05:45.710 Uttam Kumaran: It is.
68 00:05:46.100 ⇒ 00:05:47.309 Uttam Kumaran: It is, yeah.
69 00:06:02.620 ⇒ 00:06:06.099 Uttam Kumaran: Okay, maybe we use this time, Clarence, to just talk through our stuff.
70 00:06:06.480 ⇒ 00:06:24.210 Clarence Stone: Yeah, actually, some quick housekeeping here. I missed your presentation to ABC last week, so, where did you guys all leave off? Like, can I still have the first 20-30 minutes to show, the analytics for the questions that they asked me specifically last time?
71 00:06:24.700 ⇒ 00:06:33.249 Uttam Kumaran: Yeah, totally. Yeah, so kind of, like, the way we were gonna do Wednesday is, we wanted to present something on,
72 00:06:34.680 ⇒ 00:06:38.099 Uttam Kumaran: We want to present something on, like, acquisition and awareness.
73 00:06:38.310 ⇒ 00:06:44.680 Uttam Kumaran: We wanted to present, like… like,
74 00:06:45.220 ⇒ 00:06:52.269 Uttam Kumaran: Amber was gonna go through sales again, and some cell phone retention, and then we were gonna present follow-ups from your side.
75 00:06:52.870 ⇒ 00:06:54.420 Uttam Kumaran: Okay. And then I need…
76 00:06:54.420 ⇒ 00:06:58.210 Clarence Stone: Sorry, shit, right?
77 00:06:58.540 ⇒ 00:07:01.000 Uttam Kumaran: Which one? No, we didn’t, we didn’t.
78 00:07:01.000 ⇒ 00:07:06.560 Clarence Stone: Okay, good, perfect. Alright, so everything fits… I get it now. Yeah, that makes sense.
79 00:07:06.970 ⇒ 00:07:07.620 Uttam Kumaran: Yeah.
80 00:07:09.380 ⇒ 00:07:17.279 Clarence Stone: Cool. Okay, so EY. Like, two top-of-mind things. One.
81 00:07:18.020 ⇒ 00:07:25.140 Clarence Stone: I want to pick, like, like, what is the best case study you guys have on… data work.
82 00:07:25.360 ⇒ 00:07:31.150 Clarence Stone: That… it doesn’t have to be Snowflake, but it’s…
83 00:07:31.870 ⇒ 00:07:40.900 Clarence Stone: it… like, this task is a lot about structuring data from different places, consolidating it, right, and prepping it to be AI-ready.
84 00:07:41.300 ⇒ 00:07:47.970 Clarence Stone: So, I’m wondering if you had any, like, case study materials already pre-made for that?
85 00:07:47.970 ⇒ 00:07:53.280 Uttam Kumaran: Yeah, so if you go to the platform, and you go to…
86 00:07:53.450 ⇒ 00:07:59.149 Uttam Kumaran: other actions, and go to Marketing Assets, you’re gonna see all of our marketing assets there, actually.
87 00:07:59.150 ⇒ 00:08:01.789 Clarence Stone: Which one’s fine.
88 00:08:01.790 ⇒ 00:08:02.740 Uttam Kumaran: And you can filter.
89 00:08:04.250 ⇒ 00:08:05.789 Uttam Kumaran: You could filter to data.
90 00:08:07.550 ⇒ 00:08:08.860 Uttam Kumaran: And then…
91 00:08:09.780 ⇒ 00:08:15.780 Uttam Kumaran: Yeah, it’s such a good use case, like, I’m interested to hear, to kind of see, but like, yeah, I mean, there’s a bunch of them for data.
92 00:08:16.730 ⇒ 00:08:22.510 Uttam Kumaran: Some of them involve snowflake, some don’t, but…
93 00:08:23.470 ⇒ 00:08:30.670 Uttam Kumaran: Yeah, like, that’s… that’s sort of like… that’s kind of like a… centralizing data, Modeling it.
94 00:08:31.790 ⇒ 00:08:35.160 Uttam Kumaran: is, like, all we do. So it’s, like, kind of, like, we probably have pieces of it.
95 00:08:35.419 ⇒ 00:08:37.019 Uttam Kumaran: And case study form.
96 00:08:39.529 ⇒ 00:08:47.019 Clarence Stone: Okay, so that’s… that’s one of the questions. The other thing I was gonna tell you is, I have a better understanding of what players are trying to do now. Like.
97 00:08:47.359 ⇒ 00:08:59.029 Clarence Stone: Every single tax department today, like, unless you’re, you know, in a massive company with its own data stacks, like, has their information all over the place.
98 00:08:59.029 ⇒ 00:09:09.629 Clarence Stone: And what they’re doing before they pass off information to EY is they’re pulling data from each of those source systems, checking it, correcting it, and then sending it to EY.
99 00:09:09.879 ⇒ 00:09:31.199 Clarence Stone: So, that’s what delayed the entire cycle of tax preparation on the tail end, right? And it also makes analysis and advisory really difficult, because you have to go back to the client, ask for a bunch of different things if you’re going to recommend to them how they structure, you know, changes, or make a deal, or, you know, decide to restructure things that are going on.
100 00:09:31.429 ⇒ 00:09:32.239 Clarence Stone: So…
101 00:09:32.240 ⇒ 00:09:32.830 Uttam Kumaran: Okay.
102 00:09:33.160 ⇒ 00:09:34.570 Clarence Stone: like, when…
103 00:09:34.940 ⇒ 00:09:43.300 Clarence Stone: So, like, the relationship that I think she would want if there was an external vendor is to be able to
104 00:09:43.470 ⇒ 00:09:50.149 Clarence Stone: One, make whatever process of data standardization pipeline into Snowflake a standardization.
105 00:09:50.760 ⇒ 00:09:53.049 Clarence Stone: Right? Where instead of, like.
106 00:09:53.390 ⇒ 00:10:10.050 Clarence Stone: having a vendor do it every single time, it’s come up with maybe an agent that walks you through it. Maybe a, you know, set of pipelines that’ll, you know, take any sort of data structure and say, this is how it fits in, these are the data points that we’re missing, right? So…
107 00:10:10.370 ⇒ 00:10:13.439 Clarence Stone: There’s that aspect of it, and then, like.
108 00:10:13.760 ⇒ 00:10:26.279 Clarence Stone: the reason why I was so interested in the Lilo thing, Utam, is, like, I think that’s what she wants to buy. I think, like, if I pitched to her that, you know, we would stand up the first
109 00:10:27.200 ⇒ 00:10:30.579 Clarence Stone: Set of pipelines, and then turn around and teach
110 00:10:30.860 ⇒ 00:10:37.370 Clarence Stone: you know, EY’s oversees dev teams how to use it and apply it, right, by using, you know, coding tools.
111 00:10:37.520 ⇒ 00:10:54.500 Clarence Stone: Like, that would be an instant buy. So I’m trying to put together, like, how organizations should think about development in the future, and how, like, this project should go. Because apparently there’s 6 clients that she wants to turn around and sell it to, as well, on top of this one.
112 00:10:56.330 ⇒ 00:11:01.149 Uttam Kumaran: Yeah, I mean, so that’s the best way to… that would be the best way to utilize us.
113 00:11:10.680 ⇒ 00:11:13.770 Clarence Stone: See, Rico, the question was so difficult, he left.
114 00:11:19.280 ⇒ 00:11:21.750 Rico Rejoso: I think you pressed the wrong button, yeah.
115 00:13:27.300 ⇒ 00:13:30.689 Uttam Kumaran: Yeah, no, so I’m with you, like,
116 00:13:31.240 ⇒ 00:13:36.110 Uttam Kumaran: She basically wants us to build, like, Yeah, it’s just…
117 00:13:36.530 ⇒ 00:13:38.979 Uttam Kumaran: There’s just gonna be a heavy discovery, like…
118 00:13:39.100 ⇒ 00:13:42.950 Uttam Kumaran: Yes, we could do… I’m fairly confident we can do all the pieces.
119 00:13:43.240 ⇒ 00:13:46.910 Uttam Kumaran: But, like, ultimately, I hear you, like, we’re not gonna be the users of this.
120 00:13:47.890 ⇒ 00:13:48.660 Clarence Stone: Yeah.
121 00:13:48.780 ⇒ 00:13:50.140 Clarence Stone: Yeah,
122 00:13:54.070 ⇒ 00:14:12.679 Clarence Stone: Like, I… the other reason why I’m really interested in this model is it might be exactly how you would pitch work to a bunch of enterprises as well. It’s like, hey, we’ll help you catch up, and then we’re going to train your team to maintain it.
123 00:14:13.870 ⇒ 00:14:14.870 Clarence Stone: Right?
124 00:14:16.990 ⇒ 00:14:19.840 Uttam Kumaran: Yeah. It’s sort of a really interesting, like.
125 00:14:19.900 ⇒ 00:14:23.099 Clarence Stone: You know, all-in-one package.
126 00:14:24.940 ⇒ 00:14:25.630 Uttam Kumaran: Yes.
127 00:14:28.270 ⇒ 00:14:37.260 Clarence Stone: In terms of the data, I’m pretty comfortable with explaining tax data and structure, so, I wouldn’t be too worried. I think you guys got it.
128 00:14:38.030 ⇒ 00:14:38.930 Clarence Stone: It’s…
129 00:14:40.120 ⇒ 00:14:48.819 Clarence Stone: there’s, like, a whole wish list of AI capabilities on top of the Snowflake that, you know, Claire also wants. Like.
130 00:14:48.820 ⇒ 00:14:51.389 Uttam Kumaran: Yes, yeah. So that we’re doing, we’re gonna…
131 00:14:51.560 ⇒ 00:14:58.189 Uttam Kumaran: Even CES today asked me, they’re like, we actually want to see how far we can get without a BI tool, just using natural language notion.
132 00:14:58.770 ⇒ 00:15:01.379 Clarence Stone: Nice. We’ll be working on that for them next.
133 00:15:01.550 ⇒ 00:15:02.500 Uttam Kumaran: Next month.
134 00:15:05.230 ⇒ 00:15:06.050 Uttam Kumaran: Yeah.
135 00:15:09.640 ⇒ 00:15:21.180 Clarence Stone: Dude, in the ops, in the platform, what does the hits actually mean? Because I picked a… a document all the way at the bottom that was actually, like, what I needed. That’s why I was like, which one?
136 00:15:21.430 ⇒ 00:15:26.570 Uttam Kumaran: Oh, hits is just, like… so, we built, like, a custom pixel, so… Right now…
137 00:15:26.570 ⇒ 00:15:26.875 Clarence Stone: Oh.
138 00:15:27.180 ⇒ 00:15:37.320 Uttam Kumaran: all of these are hosted on Brainforge.ai, so they’re not like, they’re like links. And so I had Mustafa build a custom pixel, like, it’s like a small JS that…
139 00:15:37.760 ⇒ 00:15:38.949 Clarence Stone: Oh, yeah. Excellent.
140 00:15:38.950 ⇒ 00:15:45.549 Uttam Kumaran: that just sends an event anytime someone opens it. So the… some of these we haven’t… we basically developed for, like, one…
141 00:15:45.730 ⇒ 00:15:47.409 Uttam Kumaran: one deal, so…
142 00:15:56.620 ⇒ 00:15:59.419 Clarence Stone: Yeah, the data capability stack, that’s the…
143 00:15:59.420 ⇒ 00:16:04.670 Uttam Kumaran: Yeah, the data capabilities one has a lot, and then we also have one for Snowflake that we’re working on.
144 00:16:05.030 ⇒ 00:16:06.040 Clarence Stone: Oh, okay.
145 00:16:06.040 ⇒ 00:16:07.830 Uttam Kumaran: Just Snowflake-related stuff.
146 00:16:11.140 ⇒ 00:16:16.529 Clarence Stone: Yeah, the ask was that… We do as much native Snowflake as possible.
147 00:16:16.940 ⇒ 00:16:18.249 Uttam Kumaran: Yeah, that’s fine.
148 00:16:19.720 ⇒ 00:16:20.930 Uttam Kumaran: That’s pretty common.
149 00:16:55.230 ⇒ 00:16:57.139 Clarence Stone: Dodie wants to talk to us today.
150 00:16:58.120 ⇒ 00:17:01.009 Uttam Kumaran: Yeah, I think some people are off, like, I think Greg’s off.
151 00:18:09.780 ⇒ 00:18:21.129 Clarence Stone: Alright, so… so just so you know, maybe you can give me some feedback on… on my game plan here. Like, I think what I’m gonna do is send over one of your…
152 00:18:21.700 ⇒ 00:18:34.100 Clarence Stone: case study decks. I’m liking the data one so far. And, I’m gonna create a couple slides for Claire to explain to her that, like, I…
153 00:18:34.300 ⇒ 00:18:38.800 Clarence Stone: Like, using pods is gonna be super slow, and it’s not gonna be scalable.
154 00:18:39.210 ⇒ 00:18:40.430 Clarence Stone: And then.
155 00:18:40.770 ⇒ 00:18:51.480 Clarence Stone: I’ll outline a pattern where, you know, you have AI-enhanced teams that are doing the first cut, creating agents and automations and pipelines, and then, you know.
156 00:18:51.730 ⇒ 00:18:57.600 Clarence Stone: Documenting it so that it can scale out to your average depth, pods.
157 00:18:57.850 ⇒ 00:19:00.520 Clarence Stone: And say, like, this is how we should do it.
158 00:19:02.810 ⇒ 00:19:04.130 Uttam Kumaran: Yeah, I agree.
159 00:19:05.690 ⇒ 00:19:07.230 Clarence Stone: Yeah, I mean, like…
160 00:19:07.230 ⇒ 00:19:07.900 Uttam Kumaran: Yeah.
161 00:19:08.960 ⇒ 00:19:10.000 Clarence Stone: You go for it.
162 00:19:10.220 ⇒ 00:19:11.280 Uttam Kumaran: No, go for it, go for.
163 00:19:12.200 ⇒ 00:19:17.160 Clarence Stone: I was gonna say, by the way, Claire was the one that introduced me to Casper, and Casper is doing.
164 00:19:17.160 ⇒ 00:19:17.700 Uttam Kumaran: Oh, it’s.
165 00:19:17.700 ⇒ 00:19:21.930 Clarence Stone: And actually, like, she’s on the board of Casper.
166 00:19:22.570 ⇒ 00:19:23.970 Uttam Kumaran: Oh, damn. Yes.
167 00:19:23.970 ⇒ 00:19:30.349 Clarence Stone: I was like, Claire, why would you go for this, like, kind of ridiculous dev layout? Like, why…
168 00:19:30.350 ⇒ 00:19:32.099 Uttam Kumaran: And you know it’s working for the other company around.
169 00:19:32.230 ⇒ 00:19:47.130 Clarence Stone: I’m literally doing something completely different, the opposite of what you’re proposing here at Casper. And I’m like, I know a, you know, small shop, AI shop in Shiner that’s doing this, and, you know, getting way better results. Like, they have 4 people.
170 00:19:47.880 ⇒ 00:19:50.030 Clarence Stone: Why are you accepting this right now?
171 00:19:50.450 ⇒ 00:19:51.330 Clarence Stone: You know?
172 00:19:52.770 ⇒ 00:19:55.679 Clarence Stone: So that’s been the narrative I’ve been playing against.
173 00:19:56.300 ⇒ 00:19:57.120 Uttam Kumaran: Yeah.
174 00:20:04.150 ⇒ 00:20:08.589 Uttam Kumaran: I mean, I agree, I think you’d rather us build, like, the platform and then train people, you know?
175 00:20:11.870 ⇒ 00:20:20.400 Clarence Stone: Yeah, and then, like, it’ll raise the level of all the dev teams, too. Like, it’s kind of absurd to be paying for this many pods.
176 00:20:21.150 ⇒ 00:20:21.970 Uttam Kumaran: Yes.
177 00:20:23.480 ⇒ 00:20:30.850 Clarence Stone: Yeah, there was a shit ton of data-busy work that you run into, like, you know, it makes sense to pull in the pods to say, like, hey, this is…
178 00:20:31.390 ⇒ 00:20:37.169 Clarence Stone: you know, what we need your help doing, but I doubt that, because you probably automate all that shit with AI. It’s gonna be rare.
179 00:21:30.300 ⇒ 00:21:33.350 Clarence Stone: By the way, I paid the 100 bucks for co-work, and it’s really good.
180 00:21:34.590 ⇒ 00:21:36.649 Uttam Kumaran: Oh, really? I just… well, I just bought a…
181 00:21:36.930 ⇒ 00:21:41.009 Uttam Kumaran: I just re-bought… bought for us, I have 4 more seats, so I was gonna…
182 00:21:41.340 ⇒ 00:21:43.960 Uttam Kumaran: see who else wants one, because I… I’m…
183 00:21:43.960 ⇒ 00:21:44.859 Clarence Stone: So good.
184 00:21:45.040 ⇒ 00:21:47.350 Uttam Kumaran: Having it work on some Excel modeling for me.
185 00:21:52.020 ⇒ 00:21:53.510 Uttam Kumaran: The work is actually good.
186 00:21:54.360 ⇒ 00:21:56.559 Clarence Stone: Yeah, it’s really good.
187 00:21:56.560 ⇒ 00:21:57.740 Uttam Kumaran: I’ll be having it, too.
188 00:21:58.360 ⇒ 00:22:15.700 Clarence Stone: I treat it like an assistant. I go, hey, grab all the files that refer to this, and give me a summary of what’s in each of them, and then, you know, score them based on how relevant it is to X, Y, and Z thing I’m working on right now. Or,
189 00:22:16.360 ⇒ 00:22:20.540 Clarence Stone: Yeah, just like… just like a helper assistant, really, right? Like…
190 00:22:20.540 ⇒ 00:22:25.300 Uttam Kumaran: Let’s see, but I’m already doing that, dude, we’re already doing that kind of in cursor, so I guess, like.
191 00:22:25.590 ⇒ 00:22:26.450 Uttam Kumaran: It’s possible.
192 00:22:26.450 ⇒ 00:22:33.749 Clarence Stone: Cowork is, like, in natural language, though. Like, I don’t know how to explain it, like, it’s not in your IDE.
193 00:22:33.750 ⇒ 00:22:34.739 Uttam Kumaran: Yeah, yeah, yeah.
194 00:22:34.740 ⇒ 00:22:38.599 Clarence Stone: Like, it doesn’t do anything different than what you can do in Cursor, like…
195 00:22:38.770 ⇒ 00:22:44.059 Uttam Kumaran: It’s just, like, more, like… Yeah, it’s just, like, not built on VS Code.
196 00:22:44.200 ⇒ 00:22:50.039 Clarence Stone: Exactly, like, that’s why I’m like, I agree with you, everything is cursor now. Everything needs to be computer.
197 00:22:50.460 ⇒ 00:22:57.130 Clarence Stone: That used to be the joke, by the way. Me and my buddies used to say everything is computer, because, like, whatever you buy, there’s a frickin’ computer in it.
198 00:22:57.600 ⇒ 00:23:03.209 Clarence Stone: you know, like, you get a fridge, it’s a smart fridge, you know?
199 00:23:04.890 ⇒ 00:23:05.620 Uttam Kumaran: Yes.
200 00:25:08.480 ⇒ 00:25:15.579 Uttam Kumaran: It’s so funny, because I just… I think about sending stuff in Slack, and then I’m like, actually, I’m just gonna link to the GitHub phone and find out who doesn’t have access to GitHub.
201 00:25:20.480 ⇒ 00:25:22.709 Uttam Kumaran: Otherwise, you’re not gonna be able to read everything nowhere.
202 00:25:24.690 ⇒ 00:25:27.710 Clarence Stone: I… when,
203 00:25:28.550 ⇒ 00:25:36.569 Clarence Stone: when Pranav was talking about using CLI in the stand-up this morning, I almost said, like, make them do command line Git.
204 00:25:36.570 ⇒ 00:25:38.259 Uttam Kumaran: Yeah, yeah, yeah.
205 00:25:39.820 ⇒ 00:25:42.090 Clarence Stone: I still remember it. Get rebates.
206 00:25:42.550 ⇒ 00:25:44.980 Uttam Kumaran: No, I remember it too, but it’s like…
207 00:25:44.980 ⇒ 00:25:46.200 Clarence Stone: So…
208 00:25:46.200 ⇒ 00:25:47.170 Uttam Kumaran: Crazy.
209 00:25:48.430 ⇒ 00:25:51.279 Uttam Kumaran: What a time. It’s, like, just insane that, like.
210 00:25:51.630 ⇒ 00:25:54.440 Uttam Kumaran: Nobody’s ever gonna have to know that stuff again.
211 00:25:56.280 ⇒ 00:26:00.499 Clarence Stone: When the Git UI first came out, like.
212 00:26:00.720 ⇒ 00:26:08.350 Clarence Stone: It used to break your branches if you clicked the wrong things, so, like, the entire… like…
213 00:26:08.480 ⇒ 00:26:13.800 Clarence Stone: Design and dev team was forced to use it in command line.
214 00:26:14.340 ⇒ 00:26:18.900 Clarence Stone: So I was forced to learn how to do it, and now I just… I just use command line.
215 00:26:19.660 ⇒ 00:26:20.340 Uttam Kumaran: Yeah.
216 00:26:21.320 ⇒ 00:26:26.100 Uttam Kumaran: Dude, one thing I want to do, and I haven’t been able to figure it out, is, like.
217 00:26:27.810 ⇒ 00:26:31.549 Uttam Kumaran: I wanna think about how we,
218 00:26:35.490 ⇒ 00:26:41.730 Uttam Kumaran: Potentially through, like, audio… Like, summaries of, like, meetings and,
219 00:26:42.330 ⇒ 00:26:49.860 Uttam Kumaran: like, potentially longer write-ups. Like, I want to make it easy, because sometimes I’m in the car, and I want to… or I’m walking, and I want to just listen to a document.
220 00:26:50.530 ⇒ 00:26:54.080 Uttam Kumaran: And I have to, like, take it, put it into 11 Labs.
221 00:26:54.430 ⇒ 00:26:55.589 Uttam Kumaran: And then, like.
222 00:26:56.180 ⇒ 00:27:04.120 Uttam Kumaran: it’s sort of like… yeah, I don’t know, trying to think of some ways for us for more people to use audio as a medium to, like, listen to long documents or things.
223 00:27:05.910 ⇒ 00:27:07.359 Uttam Kumaran: You kind of see what I mean?
224 00:27:07.830 ⇒ 00:27:11.660 Clarence Stone: Yeah, I know what you mean. So, wait, go back to the use case, though. Like…
225 00:27:11.660 ⇒ 00:27:19.230 Uttam Kumaran: Like… like, an example is, like, Robert wrote up a big thing on, like, our go-to-market plan, And…
226 00:27:19.410 ⇒ 00:27:24.870 Uttam Kumaran: Or actually, here’s a… here’s a better… here’s a better example. There was an article that he sent…
227 00:27:25.090 ⇒ 00:27:29.129 Uttam Kumaran: That we sent last week.
228 00:27:31.050 ⇒ 00:27:35.659 Uttam Kumaran: That was on, like, assertions. Do you remember me sending that in the Great Britain channel?
229 00:27:36.120 ⇒ 00:27:39.390 Clarence Stone: Yep, I just actually read that last week.
230 00:27:39.390 ⇒ 00:27:44.329 Uttam Kumaran: So that was one where I’m like, look, not everybody reads Substacks.
231 00:27:44.980 ⇒ 00:27:52.369 Uttam Kumaran: So I… but I… I want to absorb what the fuck that article is saying, and I’m like, okay, I wish I could just send, like.
232 00:27:52.640 ⇒ 00:27:54.779 Uttam Kumaran: It’s like, it’s a 5-minute…
233 00:27:55.450 ⇒ 00:28:05.649 Uttam Kumaran: I wish I could just send, like, an MP3 transcription of it to the channel. But they didn’t give me one in the sub-cycle article, and then I was also like.
234 00:28:05.860 ⇒ 00:28:09.880 Uttam Kumaran: fuck, it’s, like, not that easy for me to actually do that. Like, I have to go, like.
235 00:28:10.220 ⇒ 00:28:12.150 Uttam Kumaran: Buy Eleven Labs Pro.
236 00:28:12.420 ⇒ 00:28:14.289 Uttam Kumaran: So what I was thinking is, like.
237 00:28:14.420 ⇒ 00:28:20.400 Uttam Kumaran: basically creating a simple part of the platform where I can upload any internet article
238 00:28:20.580 ⇒ 00:28:24.079 Uttam Kumaran: And then it just, like, creates an MP3 audio transcription.
239 00:28:25.900 ⇒ 00:28:34.289 Uttam Kumaran: That way, for people that don’t have to… like, for example, that would have been a good thing someone just pressed play and continued doing what they’re doing, right? Like, I don’t… probably 3 people read that.
240 00:28:36.760 ⇒ 00:28:42.299 Clarence Stone: Yeah, I thought there was an open source version of.
241 00:28:42.390 ⇒ 00:28:45.440 Uttam Kumaran: There is no, there isn’t… there is an open source.
242 00:28:45.640 ⇒ 00:28:46.790 Uttam Kumaran: ETS.
243 00:28:48.670 ⇒ 00:28:53.960 Uttam Kumaran: But I was just thinking, I’m like, dude, there’s so many long-form things that people just aren’t gonna listen to.
244 00:28:54.130 ⇒ 00:28:56.660 Uttam Kumaran: like, I wish Notion just released, like, a…
245 00:28:57.420 ⇒ 00:29:00.160 Uttam Kumaran: Like, you could listen to this page, you know?
246 00:29:00.740 ⇒ 00:29:02.769 Uttam Kumaran: And they… they don’t, so…
247 00:29:05.030 ⇒ 00:29:13.059 Uttam Kumaran: Notebook LM also isn’t great, because it sort of summarizes into, like, a podcast, which I’m like, this is… yes, it’s fun sometimes, but it’s, like, kind of gimmicky.
248 00:29:15.810 ⇒ 00:29:17.370 Clarence Stone: Yeah.
249 00:29:17.760 ⇒ 00:29:28.480 Uttam Kumaran: So I was gonna just probably build something quick and try to ship it. But actually, you know what I should do? I should just send this transcript to Codex.
250 00:29:29.980 ⇒ 00:29:32.330 Uttam Kumaran: I didn’t fucking figure it out.
251 00:29:37.340 ⇒ 00:29:44.219 Clarence Stone: I mean, it’s probably a really quick app to build. Like, you just drop in the link, and then it creates an audio snippet.
252 00:29:46.640 ⇒ 00:29:47.420 Uttam Kumaran: Yeah.
253 00:29:53.590 ⇒ 00:29:56.860 Uttam Kumaran: Yeah, I’ll try to… Staff is helping me.
254 00:30:11.280 ⇒ 00:30:19.499 Uttam Kumaran: Yeah, so what else? So I’m gonna… so I’m… I’m getting… I’m working on, like, sort of getting in front of those… those snowflake wraps,
255 00:30:19.820 ⇒ 00:30:26.909 Uttam Kumaran: But, like, how else can I… how else can I help? Like, if I get a little bit more context, we can work on a deck just for this opportunity.
256 00:30:27.550 ⇒ 00:30:34.029 Clarence Stone: Yeah, I can… I can give you, I guess, like, the full story. I could,
257 00:30:34.410 ⇒ 00:30:43.800 Clarence Stone: like, I think from the Snowflake end, if you just get recommended as the vendor of choice, it’s gonna be pretty straightforward and easy. Like.
258 00:30:43.800 ⇒ 00:30:44.420 Uttam Kumaran: Okay.
259 00:30:45.230 ⇒ 00:30:52.350 Clarence Stone: It’s just that, like, I want to make sure that whoever’s working with UI knows to recommend you guys, because.
260 00:30:52.350 ⇒ 00:30:52.990 Uttam Kumaran: Yes.
261 00:30:53.360 ⇒ 00:31:00.430 Clarence Stone: what Claire’s gonna ask from them is to… to build it, like, entirely for EY.
262 00:31:00.490 ⇒ 00:31:15.969 Clarence Stone: Obviously, they’re gonna say no, right? But what happens after is, like, super critical. Like, if they want to send a forward deployed engineer and assign one, fine, but they’re not gonna do the full build, so they should, you know, refer out
263 00:31:16.350 ⇒ 00:31:18.120 Clarence Stone: Vendors that they work with.
264 00:31:18.820 ⇒ 00:31:19.740 Clarence Stone: Right.
265 00:31:21.020 ⇒ 00:31:26.910 Clarence Stone: So… Yeah, like, I don’t know how to connect the dots on that side.
266 00:31:26.910 ⇒ 00:31:28.960 Uttam Kumaran: Yeah, so, like, one is, like.
267 00:31:29.210 ⇒ 00:31:34.150 Uttam Kumaran: I’m gonna see if I can get above those sales reps, and just explain this.
268 00:31:34.560 ⇒ 00:31:38.550 Uttam Kumaran: And try to get the intro to those reps from someone above them.
269 00:31:39.050 ⇒ 00:31:41.220 Clarence Stone: Because me going direct to them.
270 00:31:41.900 ⇒ 00:31:43.610 Uttam Kumaran: Is… is an option.
271 00:31:43.860 ⇒ 00:31:49.089 Uttam Kumaran: But, I would rather go above them first. So that’s what I’m gonna try tonight.
272 00:31:49.470 ⇒ 00:31:53.299 Uttam Kumaran: In the partnerships channel, I just sent a little bit of a thing about, like.
273 00:31:53.410 ⇒ 00:32:02.039 Uttam Kumaran: I’m sort of gonna start circling around Snowflake and building our… an internal hub just around Snowflake. We probably have, like, 15 to 20 contacts there.
274 00:32:02.470 ⇒ 00:32:07.820 Uttam Kumaran: And we’re not, like… We’re not organized enough to work with,
275 00:32:08.150 ⇒ 00:32:10.780 Uttam Kumaran: like, there… Snowflake, there’s not, like, a…
276 00:32:11.210 ⇒ 00:32:13.910 Uttam Kumaran: there’s not, like, a single person, right? So…
277 00:32:14.110 ⇒ 00:32:22.900 Uttam Kumaran: We have to treat every relationship almost, like, individually, and understand why that person is talking to us, and how we help them.
278 00:32:23.220 ⇒ 00:32:29.699 Uttam Kumaran: Right? Like, so, for me, when I go to them, I’m not… nobody there cares about Snowflake, they care about themselves first.
279 00:32:29.900 ⇒ 00:32:32.109 Uttam Kumaran: So, I have to go think about, like.
280 00:32:32.330 ⇒ 00:32:39.670 Uttam Kumaran: Okay, this person… why… and what… why would they have to… why would they make this sort of referral thing to us, right?
281 00:32:39.890 ⇒ 00:32:45.849 Uttam Kumaran: So that’s what I’m sort of, like, trying to figure out.
282 00:32:48.860 ⇒ 00:32:56.680 Uttam Kumaran: So let me do… let me send that note today. Worst case, I will go to… I will go to those reps and say, hey, I have, like.
283 00:32:57.020 ⇒ 00:33:00.359 Uttam Kumaran: I have a business relationship into this EUI deal.
284 00:33:00.720 ⇒ 00:33:04.440 Uttam Kumaran: Do you know… do you know if they’ve already signed, like, paper with Eli? Like…
285 00:33:05.220 ⇒ 00:33:08.849 Clarence Stone: So, like, Snowflake?
286 00:33:09.400 ⇒ 00:33:10.070 Uttam Kumaran: Yeah.
287 00:33:10.520 ⇒ 00:33:13.819 Clarence Stone: Oh, Snowflake has a MSA with EY, so…
288 00:33:13.820 ⇒ 00:33:19.070 Uttam Kumaran: So then what I’m gonna say is there’s, like, probably, like, there’s, like, there’s an additional SOW on the table.
289 00:33:19.280 ⇒ 00:33:23.799 Uttam Kumaran: that… like… They’re debating how to execute on it.
290 00:33:24.920 ⇒ 00:33:31.390 Uttam Kumaran: like, I would… We have a way to promote us, and we’re gonna push to develop the entire
291 00:33:31.560 ⇒ 00:33:33.359 Uttam Kumaran: application on Snowflake.
292 00:33:33.770 ⇒ 00:33:37.939 Uttam Kumaran: It’s gonna be a scope that’s, like, gonna be too larger for Snowflake PS.
293 00:33:39.030 ⇒ 00:33:43.400 Uttam Kumaran: and they’re gonna wanna go with us, I would love to help you bring this deal over the line.
294 00:33:44.090 ⇒ 00:33:45.630 Uttam Kumaran: That’s how I’ll frame it to them.
295 00:33:45.640 ⇒ 00:33:55.599 Clarence Stone: You can even, like, sell the fact that I’m here now, too. You say, like, somebody who worked at that business unit is telling you about it because they’re now at Brainforge.
296 00:33:55.910 ⇒ 00:33:57.220 Uttam Kumaran: Yeah, okay, okay.
297 00:33:57.460 ⇒ 00:34:10.900 Clarence Stone: Right? Like, I know enough about that, like, data landscape that we can, you know, tackle it, and it’s niche information. Like, not everybody who works in Snowflake can just come in and understand financial data.
298 00:34:13.150 ⇒ 00:34:13.969 Uttam Kumaran: Makes sense.
299 00:34:17.889 ⇒ 00:34:18.620 Uttam Kumaran: Okay.
300 00:34:19.199 ⇒ 00:34:22.139 Uttam Kumaran: So that’s what I’m gonna do, and I’m… we have, like, about
301 00:34:22.429 ⇒ 00:34:25.059 Uttam Kumaran: 10 to 15 people that I’m gonna reach out to.
302 00:34:25.280 ⇒ 00:34:28.730 Uttam Kumaran: like, we have about 10 to 15 contacts, I’m gonna reach out to a couple.
303 00:34:28.960 ⇒ 00:34:39.370 Uttam Kumaran: Like, because we have some people that cover Texas, but they cover, like, Texas small business, right? So I’m just gonna try to find out who those two are.
304 00:34:39.699 ⇒ 00:34:44.990 Uttam Kumaran: and either they’re the right person, or, like, I’ll find out who the right person is.
305 00:34:45.090 ⇒ 00:34:48.010 Uttam Kumaran: And then… get this escalated, basically.
306 00:34:48.920 ⇒ 00:34:59.980 Clarence Stone: Perfect, yeah, and you know, the first client that we’re building this for is a Texas company, too, and Clary’s out of Texas, so, like, out of all things, like, I really think Brainforce should win this one.
307 00:34:59.980 ⇒ 00:35:12.429 Uttam Kumaran: So that’s, I guess, my point is, like, it’s for EY, but, like, it’s the EY Texas Business Unit, because that’s what they’re gonna be, like, ask… because their thing is so territory-based. So, I’m gonna…
308 00:35:13.070 ⇒ 00:35:16.319 Uttam Kumaran: Like, is that a fair, like, way of putting it?
309 00:35:16.860 ⇒ 00:35:19.280 Clarence Stone: So, EY…
310 00:35:19.630 ⇒ 00:35:35.489 Clarence Stone: EY’s does have regions, but the financial services region is the whole entire state, country. So, like, the FSO is its own business unit, but also covers the entire country, so it’s a little tough. Like, I don’t understand
311 00:35:35.700 ⇒ 00:35:40.759 Clarence Stone: like, the matchup between Snowflake’s territories and how they would handle that for EY.
312 00:35:41.530 ⇒ 00:35:46.099 Uttam Kumaran: Okay, okay, fair. So what I’m gonna do is basically say that. I’m gonna go… that’s gonna be my way in.
313 00:35:46.240 ⇒ 00:35:49.040 Uttam Kumaran: like, I’m gonna email our partner manager.
314 00:35:49.120 ⇒ 00:35:50.789 Clarence Stone: Say, hey, I have a deal.
315 00:35:51.060 ⇒ 00:35:56.210 Uttam Kumaran: on the line with Eli, FSO, right? Is that a fair way of saying it? I’ll just say it’s…
316 00:35:56.210 ⇒ 00:36:04.589 Clarence Stone: The partner that’s working on this project is from Texas. The company that this would be for is in Texas.
317 00:36:04.590 ⇒ 00:36:10.810 Uttam Kumaran: Yeah, their resulting client is in Texas. These are the two reps that I’ve heard are on it.
318 00:36:10.940 ⇒ 00:36:18.080 Uttam Kumaran: like… I’m gonna go ahead and register it in the Snowflake Partner Network. Like, how would you, like…
319 00:36:18.560 ⇒ 00:36:23.690 Uttam Kumaran: I have, like, we… we are being… we’re gonna be considered to do the implementation.
320 00:36:23.830 ⇒ 00:36:31.380 Uttam Kumaran: I would like help, like, figuring this one out. Can we hop on a call? And if I hop on a call, I’ll… I’ll…
321 00:36:31.630 ⇒ 00:36:36.190 Uttam Kumaran: if you’re interested in hopping on, I’ll bring you. Otherwise, like, I have enough to kind of…
322 00:36:36.540 ⇒ 00:36:42.959 Uttam Kumaran: to just at least get in front of those two reps and get all the information we need. So, I’m gonna send that today.
323 00:36:43.250 ⇒ 00:36:45.489 Clarence Stone: Yeah, I’m down to hop on with you two.
324 00:36:45.490 ⇒ 00:36:45.840 Uttam Kumaran: Okay.
325 00:36:46.130 ⇒ 00:36:47.190 Clarence Stone: That, yeah, that’d be awesome.
326 00:36:47.190 ⇒ 00:36:54.959 Uttam Kumaran: I mean, none of this stuff, like, people are smart, like, it’s not, like… I don’t… mainly, they’re all extremely self-serving.
327 00:36:55.090 ⇒ 00:37:00.500 Uttam Kumaran: So we just need to, like, help them hit whatever metrics they have. Like, they’re gonna be useless.
328 00:37:00.940 ⇒ 00:37:01.700 Clarence Stone: Like.
329 00:37:01.700 ⇒ 00:37:03.549 Uttam Kumaran: Most… 98% of the ch…
330 00:37:03.920 ⇒ 00:37:09.110 Uttam Kumaran: 98% of the time, they’re useless. So, most of it is just, like, exactly what you meant, is, like.
331 00:37:09.590 ⇒ 00:37:13.520 Uttam Kumaran: I almost want Claire to get an email mentioning us.
332 00:37:13.690 ⇒ 00:37:23.829 Clarence Stone: That would be huge, too. Because, like, from, like, the EY side, like, I made all my senior manager friends push Brainforge.
333 00:37:23.960 ⇒ 00:37:25.749 Clarence Stone: Who were also on that account.
334 00:37:25.910 ⇒ 00:37:40.350 Clarence Stone: So, like, all my SM friends are like, I don’t know if this is gonna work, but I’m gonna recommend it, right? And… and then now Claire’s like, I think I want to pick them, but, you know, are… are they, you know, the best months?
335 00:37:40.350 ⇒ 00:37:41.190 Uttam Kumaran: Zach, yeah.
336 00:37:41.190 ⇒ 00:37:41.980 Clarence Stone: Yeah. Okay.
337 00:37:42.320 ⇒ 00:37:45.200 Clarence Stone: Yeah, now if she hears it from… like…
338 00:37:45.750 ⇒ 00:37:50.289 Clarence Stone: like, Snowflake themselves, there’s, like, really no argument here.
339 00:37:50.820 ⇒ 00:37:51.820 Uttam Kumaran: Okay, okay.
340 00:37:52.670 ⇒ 00:37:53.400 Uttam Kumaran: Yeah.
341 00:37:54.250 ⇒ 00:37:56.170 Uttam Kumaran: Okay, cool, let me, let me,
342 00:37:56.500 ⇒ 00:37:58.330 Uttam Kumaran: Let me do that as soon as I’m back home.
343 00:37:58.720 ⇒ 00:38:15.110 Clarence Stone: Yeah, and I’m waiting, like, as soon as that gets lined up, I know what she’s gonna message me is, like, how does Brainforge want to, you know, insert them, like, self into this project? Like, what would they deliver? What would we still deliver? And I would have to model that out on the UI side for you guys.
344 00:38:15.110 ⇒ 00:38:20.639 Clarence Stone: So this is perfect, because I can actually run that by you guys and say, does this look good with you, and things like that.
345 00:38:21.160 ⇒ 00:38:22.139 Uttam Kumaran: Okay, okay.
346 00:38:23.020 ⇒ 00:38:25.280 Clarence Stone: Yeah, I, I am technically…
347 00:38:25.410 ⇒ 00:38:33.010 Clarence Stone: serving as the MD on this account, and she’s… Claris is treating me like it, even though, like, I’m a contractor.
348 00:38:33.830 ⇒ 00:38:38.229 Uttam Kumaran: No, I can tell, I can tell.
349 00:38:38.230 ⇒ 00:38:45.800 Clarence Stone: It’s like, she’s just like, oh, we found a different way to pay you? Okay, then our original working relationship goes back.
350 00:38:47.540 ⇒ 00:38:48.760 Uttam Kumaran: I was like.
351 00:38:48.760 ⇒ 00:38:50.790 Clarence Stone: It’s so funny, you just took a…
352 00:38:52.290 ⇒ 00:38:55.849 Uttam Kumaran: I know, it must be really tough times for that company, but .
353 00:38:55.940 ⇒ 00:39:00.770 Clarence Stone: Hey, dude, you have leverage over, like, a really big organization, so that’s fine. Yeah.
354 00:39:00.770 ⇒ 00:39:08.730 Uttam Kumaran: Well, I mean, they got really used to working with me and my velocity, and they can’t find anyone to replace me, so, like, I’m gonna use it to our benefit.
355 00:39:09.070 ⇒ 00:39:09.680 Uttam Kumaran: Yeah.
356 00:39:11.190 ⇒ 00:39:14.499 Uttam Kumaran: Okay, sick, let me, let me make this happen. This month.
357 00:39:14.750 ⇒ 00:39:17.680 Uttam Kumaran: for me, on the partner side, is Cracking Snowflake.
358 00:39:17.970 ⇒ 00:39:26.189 Uttam Kumaran: And, like, I’m gonna show us, like, how it’s done there, like, and then what we’re gonna do is take a lot of the same learnings and apply it to the other vendors that we work with.
359 00:39:26.350 ⇒ 00:39:28.959 Uttam Kumaran: Like, basically, we’re gonna… I’m gonna just map out…
360 00:39:29.240 ⇒ 00:39:34.530 Uttam Kumaran: We’re gonna… we’re gonna just go after account execs, like, we go after, like, deals, basically.
361 00:39:34.780 ⇒ 00:39:38.899 Uttam Kumaran: And yeah, we should have a bunch more stuff come our way.
362 00:39:38.910 ⇒ 00:39:45.559 Clarence Stone: I know you guys are planning a bunch of events, so if any of them are in Austin, like, let me know, I can drive up.
363 00:39:47.680 ⇒ 00:39:53.550 Uttam Kumaran: There are, yeah, so… We’re partnering, we’re trying to do an event with Mixpanel,
364 00:39:53.860 ⇒ 00:39:56.280 Uttam Kumaran: We’re trying to do an event with Mixpanel in March.
365 00:39:56.510 ⇒ 00:39:58.340 Uttam Kumaran: So we’re,
366 00:39:58.560 ⇒ 00:40:07.980 Uttam Kumaran: in… end of Feb, actually. So we just… we just, like, are aligning on budget, and then… I’m also gonna try to do something with Snowflake.
367 00:40:08.280 ⇒ 00:40:13.839 Uttam Kumaran: In the next, like, 2-3 months. But yeah, we’ll… our KPIs try to do one event a month.
368 00:40:14.230 ⇒ 00:40:18.370 Uttam Kumaran: So, we’ll hit that soon.
369 00:40:18.940 ⇒ 00:40:24.790 Uttam Kumaran: And yeah, I mean, basically, I mean, the whole wor… our whole network is invited.
370 00:40:24.940 ⇒ 00:40:27.389 Uttam Kumaran: But yeah, that should be good.
371 00:40:28.490 ⇒ 00:40:29.270 Clarence Stone: Nice.
372 00:40:29.270 ⇒ 00:40:33.220 Uttam Kumaran: That way, also, again, we can invite prospects and anyone to come to any of those, you know?
373 00:40:33.610 ⇒ 00:40:48.700 Clarence Stone: Yeah, exactly. I think those events are going to be pretty powerful. Like, the more these, you know, account leads realize that they can win more sales by having an implementation partner, the better it is for us, right?
374 00:40:48.700 ⇒ 00:40:49.649 Uttam Kumaran: No, I agree.
375 00:40:49.920 ⇒ 00:40:55.020 Clarence Stone: you can sell so much more when you can just say, hey, I know some guys that’ll make this work perfectly for you.
376 00:40:56.380 ⇒ 00:40:57.990 Uttam Kumaran: Oh, I, I totally agree.
377 00:41:07.400 ⇒ 00:41:08.070 Clarence Stone: Cool.
378 00:41:08.530 ⇒ 00:41:09.130 Uttam Kumaran: Okay.
379 00:41:09.250 ⇒ 00:41:10.680 Uttam Kumaran: Cool, dude.
380 00:41:10.680 ⇒ 00:41:14.250 Clarence Stone: I got two things. We went to all our meetings, and we still got to catch up. That was all possible.
381 00:41:14.250 ⇒ 00:41:23.650 Uttam Kumaran: No, that’s good, and then, well, we’ll be hanging out a bunch this week, and I’m excited to do… to get everybody in one room on Friday would be good, and then, yeah, Wednesday should be good, too, so…
382 00:41:23.650 ⇒ 00:41:28.550 Clarence Stone: on Friday, like, is there, like, wherever we’re gonna meet, like, is there, like, a…
383 00:41:28.880 ⇒ 00:41:34.900 Clarence Stone: like, private call room, because I have an hour long with Casper that I need.
384 00:41:34.900 ⇒ 00:41:37.739 Uttam Kumaran: Yeah, I was gonna just get us into a WeWork, dude.
385 00:41:37.910 ⇒ 00:41:43.420 Uttam Kumaran: And then… Like, yeah, there’s plenty of, there’s plenty of, like, boots.
386 00:41:43.730 ⇒ 00:41:52.619 Uttam Kumaran: And I was gonna get us a conference room, maybe for, like, 2 hours, so we can… we have an all-hands, and then you’re free to use that, or yeah, there’s… there’s all these phone booths there.
387 00:41:53.210 ⇒ 00:42:00.469 Clarence Stone: Yeah. Yeah, I’m probably gonna be stuck in a phone booth for one of those hours, but the rest of Friday, I’m all brainforge.
388 00:42:00.910 ⇒ 00:42:02.179 Uttam Kumaran: Okay, okay, second.
389 00:42:05.080 ⇒ 00:42:10.899 Uttam Kumaran: Okay, alright, let me, let me, let me tell you as soon as, like, I get my… some emails out for Snowflake.
390 00:42:11.380 ⇒ 00:42:13.600 Uttam Kumaran: Later today.
391 00:42:14.600 ⇒ 00:42:15.860 Clarence Stone: Yeah, that makes sense.
392 00:42:16.230 ⇒ 00:42:16.880 Uttam Kumaran: Okay.
393 00:42:17.380 ⇒ 00:42:18.300 Uttam Kumaran: Alright.
394 00:42:18.440 ⇒ 00:42:20.050 Uttam Kumaran: Thanks, dude. I’ll talk to you soon, man.
395 00:42:20.260 ⇒ 00:42:20.800 Clarence Stone: Yep.
396 00:42:21.240 ⇒ 00:42:22.400 Uttam Kumaran: Okay. Sounds good.
397 00:42:23.900 ⇒ 00:42:25.060 Clarence Stone: Adios.
398 00:42:25.290 ⇒ 00:42:25.740 Uttam Kumaran: Bye.