Meeting Title: Brainforge Service Leads Weekly Sync Date: 2026-01-19 Meeting participants: Awaish Kumar, Samuel Roberts, Uttam Kumaran, Sheshu Chandrasekar, Clarence Stone
WEBVTT
1 00:02:09.970 ⇒ 00:02:10.949 Samuel Roberts: Anyways…
2 00:02:14.880 ⇒ 00:02:16.800 Awaish Kumar: Hi, how are you doing?
3 00:02:17.550 ⇒ 00:02:19.679 Samuel Roberts: Doing alright. How about you today?
4 00:02:21.250 ⇒ 00:02:23.010 Awaish Kumar: Yeah, I’m good as well.
5 00:02:23.580 ⇒ 00:02:24.620 Samuel Roberts: Good, good.
6 00:02:26.770 ⇒ 00:02:31.949 Samuel Roberts: Yeah, it’s very cold here today, it’s all snowy, and it’s very winter.
7 00:02:32.080 ⇒ 00:02:32.810 Samuel Roberts: Perk.
8 00:02:32.910 ⇒ 00:02:35.029 Awaish Kumar: I’m trying to stay warm in the attic here.
9 00:02:36.540 ⇒ 00:02:37.480 Samuel Roberts: Heyo, Tom.
10 00:02:37.900 ⇒ 00:02:40.390 Uttam Kumaran: Hey, you don’t… you don’t have a basement?
11 00:02:42.090 ⇒ 00:02:42.750 Samuel Roberts: Oh, we have a basement.
12 00:02:43.060 ⇒ 00:02:45.729 Uttam Kumaran: Okay, okay, I didn’t know if Ohio does basements.
13 00:02:45.730 ⇒ 00:02:53.010 Samuel Roberts: Oh, yeah, no, no, Ohio does basements, we actually… it’s like a… it’s like a half a story third floor, so it’s, like, kind of a finished attic.
14 00:02:54.220 ⇒ 00:02:57.379 Uttam Kumaran: You have, like, laundry down there, or, like, what do you have down there?
15 00:02:57.380 ⇒ 00:03:06.959 Samuel Roberts: The basement, yeah, the basement is like laundry, you know, all the mechanical stuff, the furnace and everything, the hot water heater, and then, it’s actually.
16 00:03:06.960 ⇒ 00:03:10.389 Uttam Kumaran: It’s, like, internally… is it internally… it’s internally accessible?
17 00:03:10.680 ⇒ 00:03:11.889 Samuel Roberts: Yeah, right from the kitchen.
18 00:03:12.230 ⇒ 00:03:13.470 Uttam Kumaran: Nice, okay, okay, cool.
19 00:03:13.470 ⇒ 00:03:19.819 Samuel Roberts: Yeah, so it’s good. It’s actually nice. I cut a little hole in the door when we first bought the house so that the cat litter boxes could be down there, which is…
20 00:03:19.820 ⇒ 00:03:20.719 Uttam Kumaran: Oh, great.
21 00:03:20.720 ⇒ 00:03:24.580 Samuel Roberts: Huge life improvement from, like, apartment living.
22 00:03:26.560 ⇒ 00:03:37.419 Uttam Kumaran: I need to think about, like, maybe a dog door, because I can’t do… I’m renting a house that I am at, but next house, I do want to do, like, a dog door that, like, I can,
23 00:03:37.850 ⇒ 00:03:44.109 Uttam Kumaran: sort of, like, put on an Alexa and have it open, because, like, I don’t… I don’t want it to be open all the time, but, like.
24 00:03:44.110 ⇒ 00:03:44.669 Samuel Roberts: Yeah. Awesome.
25 00:03:44.910 ⇒ 00:03:49.730 Uttam Kumaran: The dog wants to go out very often, and it’s so… it’s, like, kind of just annoying to, like, have to…
26 00:03:49.730 ⇒ 00:03:59.649 Samuel Roberts: No, I… yeah, I feel bad for my dog, because, like, it’s the same situation, where… but we don’t have, like, an enclosed yard. It’s not, like, I want… I don’t trust the dog to go out by herself right now, so…
27 00:04:00.080 ⇒ 00:04:01.370 Uttam Kumaran: Yeah, makes sense.
28 00:04:01.370 ⇒ 00:04:02.740 Samuel Roberts: But, yeah.
29 00:04:05.330 ⇒ 00:04:06.970 Uttam Kumaran: How’s, how’s the day going?
30 00:04:09.240 ⇒ 00:04:10.160 Samuel Roberts: You’re gonna write.
31 00:04:10.490 ⇒ 00:04:12.129 Samuel Roberts: Yes, hello, hi.
32 00:04:12.560 ⇒ 00:04:13.210 Sheshu Chandrasekar: Hi.
33 00:04:13.430 ⇒ 00:04:16.820 Sheshu Chandrasekar: No, Monday’s going well. How about you, how about everyone else?
34 00:04:18.089 ⇒ 00:04:18.809 Samuel Roberts: Yeah.
35 00:04:19.110 ⇒ 00:04:20.700 Uttam Kumaran: Good, dude, I feel like I’m having, like…
36 00:04:21.110 ⇒ 00:04:24.640 Uttam Kumaran: I’m having… oh, yes. Welcome, welcome, Shashu, to Service Lead.
37 00:04:24.640 ⇒ 00:04:25.200 Samuel Roberts: Yeah.
38 00:04:25.200 ⇒ 00:04:30.380 Uttam Kumaran: Does someone mind pinging Clarence, seeing if he’s gonna join? I don’t know if he’s gonna be here today.
39 00:04:33.430 ⇒ 00:04:38.940 Uttam Kumaran: Yeah, I feel like I’m having some of the most normal Like, I’m having, like…
40 00:04:39.180 ⇒ 00:04:44.849 Uttam Kumaran: a really normal workday, like, not as stressed. I mean, still, like, my days feel… my days…
41 00:04:45.000 ⇒ 00:04:50.210 Uttam Kumaran: someone always tries to ruin it, so that’s usually once a day. Not nobody internally, it’s all external, usually.
42 00:04:50.210 ⇒ 00:04:51.460 Samuel Roberts: You know?
43 00:04:52.490 ⇒ 00:04:56.639 Uttam Kumaran: But, like, you know, that’s okay, and yeah, today’s going really great. I,
44 00:04:57.150 ⇒ 00:05:00.750 Uttam Kumaran: I, yeah, I had some good meetings in the morning, and I’m spending…
45 00:05:00.960 ⇒ 00:05:04.639 Uttam Kumaran: The next few hours, just working on some sales stuff, and…
46 00:05:05.080 ⇒ 00:05:07.139 Uttam Kumaran: Yeah, I think things are overall pretty good.
47 00:05:07.670 ⇒ 00:05:08.880 Samuel Roberts: We’re.
48 00:05:08.980 ⇒ 00:05:22.269 Uttam Kumaran: I think in terms of, like, for service lead stuff, I think the biggest sort of set of improvements that I’m seeing is, like, we’re starting to be able to actually act on, like, new potential service lines, you know, like.
49 00:05:22.830 ⇒ 00:05:27.100 Uttam Kumaran: you know, one thing that came up today is, like, we just taught a client how to use Cloud Code.
50 00:05:27.320 ⇒ 00:05:35.069 Uttam Kumaran: Bernard did that, and, you know, we’re… there’s another client that we’re talk… there’s another potential prospect that we’re talking to that’s also interested in that.
51 00:05:35.240 ⇒ 00:05:39.700 Uttam Kumaran: And so, I’m sort of thinking about, okay, what does this mean from doing something to turning into
52 00:05:39.930 ⇒ 00:05:47.030 Uttam Kumaran: a reusable service, you know, that we can offer. Yeah. And that’s just something interesting for us to discuss.
53 00:05:48.230 ⇒ 00:05:52.349 Samuel Roberts: Definitely. Yeah, that was actually something, Leela brought up Friday. They were like, you know.
54 00:05:52.500 ⇒ 00:05:58.080 Samuel Roberts: Any tools or things, like, any ideas and stuff, they, you know, they wanted us to bring them.
55 00:05:58.280 ⇒ 00:06:09.810 Samuel Roberts: And, you know, on the spot on the call, they were asking about, like, what we’re doing for other clients, and I don’t know if, like, the Andy stuff really translates to them, but I was… it was encouraging that they were asking very specifically for, like.
56 00:06:10.030 ⇒ 00:06:12.709 Uttam Kumaran: Oh, that’s great. I didn’t even… I didn’t even know, I didn’t even…
57 00:06:12.710 ⇒ 00:06:17.419 Samuel Roberts: I forgot about that. I forgot about that too, you just mentioned that, because it was kind of, like, the last thing on the call, I think, but.
58 00:06:17.420 ⇒ 00:06:18.390 Uttam Kumaran: Oh, that’s awesome.
59 00:06:18.390 ⇒ 00:06:21.020 Samuel Roberts: I hadn’t… I hadn’t digested that until just now, so yeah.
60 00:06:21.500 ⇒ 00:06:22.200 Uttam Kumaran: Yeah.
61 00:06:23.620 ⇒ 00:06:24.649 Uttam Kumaran: A lot today.
62 00:06:29.550 ⇒ 00:06:32.849 Awaish Kumar: Yeah, I think Clarence, but he seems to be offline.
63 00:06:33.760 ⇒ 00:06:37.140 Samuel Roberts: Okay, yeah, it said, yeah, it said in a meeting and offline on the thing I saw, so…
64 00:06:41.410 ⇒ 00:06:44.499 Samuel Roberts: Yeah, for his calendar, he’s got something there. Could be this, though, who knows?
65 00:06:47.330 ⇒ 00:06:48.060 Samuel Roberts: Yes.
66 00:06:49.040 ⇒ 00:06:53.390 Samuel Roberts: Anyway, coop.
67 00:06:55.620 ⇒ 00:07:00.979 Samuel Roberts: Yeah, I don’t really have a ton that I was thinking about in terms of discussion today yet.
68 00:07:01.570 ⇒ 00:07:07.070 Samuel Roberts: Yeah, I’m just grabbing a coffee. Maybe, Shakley, do you want to give a brief introduction of yourself to… That’d be good.
69 00:07:07.070 ⇒ 00:07:07.680 Sheshu Chandrasekar: Yeah.
70 00:07:07.910 ⇒ 00:07:09.360 Uttam Kumaran: Yeah. Absolutely.
71 00:07:09.570 ⇒ 00:07:16.599 Sheshu Chandrasekar: Hey, Sam. Hey, Awash. I think, Oish, we met last week, but Sam, it’s good to meet you virtually. Yeah.
72 00:07:16.600 ⇒ 00:07:17.010 Samuel Roberts: Of course.
73 00:07:17.010 ⇒ 00:07:28.750 Sheshu Chandrasekar: Yeah, I’m currently the head of ops right now, just helping out Utam and Robert and everyone to see how we can streamline the process here.
74 00:07:29.110 ⇒ 00:07:34.320 Sheshu Chandrasekar: Brainforge. Yeah, so super excited to work closely with you to
75 00:07:34.590 ⇒ 00:07:51.379 Sheshu Chandrasekar: figure out, like, hey, what’s the pain points that you’re facing on your day-to-day, and how I can help you, you know, make your work manageable, and if not even elevate your work as much as I can. So, that’s why I’m brought in, and yeah, I’m super excited to collaborate and work closely over the next couple weeks.
76 00:07:51.780 ⇒ 00:07:53.290 Samuel Roberts: Yeah, no, that sounds great.
77 00:07:53.730 ⇒ 00:07:55.030 Samuel Roberts: Welcome, welcome.
78 00:07:56.460 ⇒ 00:08:03.910 Uttam Kumaran: Yeah, so really, like, part of the… kind of the thing I’m sort of interested in is, like, how ops is gonna support delivery, like, more deliberately.
79 00:08:04.660 ⇒ 00:08:08.379 Uttam Kumaran: You know, and I see ops as sort of, like.
80 00:08:08.680 ⇒ 00:08:24.150 Uttam Kumaran: just kind of the head of processes, but may not own the process, but is sort of tasked with establishing it. And so I think, like, what I’m hopeful that Cheshu gets some awareness of is, like, all of our current delivery rituals, right?
81 00:08:24.150 ⇒ 00:08:24.550 Samuel Roberts: convey.
82 00:08:24.550 ⇒ 00:08:30.300 Uttam Kumaran: stand-ups, these meetings that are across, sort of, the functional roles,
83 00:08:30.730 ⇒ 00:08:46.749 Uttam Kumaran: But then even everything around, like, for example, you know, if we need help basically saying, like, hey, there’s often times that, for example, like, a client, an active client asks, hey, what else do you guys do? How else can you help? How is someone in the delivery team supposed to answer that?
84 00:08:46.950 ⇒ 00:08:52.279 Uttam Kumaran: You know, we should probably just create a process doc around that, and like, you know, and similarly, like, hey.
85 00:08:52.380 ⇒ 00:08:54.259 Uttam Kumaran: We noticed that we did, like.
86 00:08:54.790 ⇒ 00:09:04.570 Uttam Kumaran: we just trained two clients on cloud code. Okay, that’s, like, probably more than enough conference that we should probably, like, take something to market. What are the next steps, right?
87 00:09:04.920 ⇒ 00:09:07.130 Uttam Kumaran: Those are all…
88 00:09:07.270 ⇒ 00:09:11.420 Uttam Kumaran: That’s the, like, examples of things that, like, I think are still totally open to figure out.
89 00:09:13.550 ⇒ 00:09:14.130 Samuel Roberts: Yeah.
90 00:09:16.390 ⇒ 00:09:17.540 Samuel Roberts: Excuse me.
91 00:09:18.890 ⇒ 00:09:27.360 Uttam Kumaran: So yeah, I mean, maybe today we can talk, maybe we do talk a little bit about that. I think, two new services that kind of came up in my mind.
92 00:09:27.710 ⇒ 00:09:37.720 Uttam Kumaran: Are really, like, one is sort of, like, dbt, like, dbt audit, like, Snowflake audit.
93 00:09:38.430 ⇒ 00:09:48.470 Uttam Kumaran: And then also, like, sort of, like, AI training, which is, like, cursor… Cloud code… Like… Maybe,
94 00:09:48.670 ⇒ 00:09:59.130 Uttam Kumaran: I don’t know, so, like, those are kind of two ideas. Are there any other, like, services or potential services that you guys can think of that we’ve done for clients that we want to…
95 00:09:59.270 ⇒ 00:10:00.360 Uttam Kumaran: Discuss.
96 00:10:00.830 ⇒ 00:10:06.310 Uttam Kumaran: That way, I can take this meeting and even, you know, hand it to Luke, basically, and be like, here’s… you can think about it.
97 00:10:06.690 ⇒ 00:10:11.359 Awaish Kumar: Yeah, last time we met with Lu Kang, like, last week.
98 00:10:11.540 ⇒ 00:10:15.170 Awaish Kumar: I will discuss standardizing the services.
99 00:10:15.340 ⇒ 00:10:22.150 Awaish Kumar: I shared, like, we came up with two services on a call with Robert while we were doing this,
100 00:10:22.960 ⇒ 00:10:26.460 Awaish Kumar: like, the mind storming in the Figma.
101 00:10:26.730 ⇒ 00:10:29.570 Awaish Kumar: So, one was really related to, like.
102 00:10:30.080 ⇒ 00:10:33.320 Awaish Kumar: marketing, like, which kind of Zoran’s work?
103 00:10:33.500 ⇒ 00:10:36.420 Awaish Kumar: So we try to standardize what he’s doing.
104 00:10:36.580 ⇒ 00:10:40.720 Awaish Kumar: And then define it as a package service.
105 00:10:40.920 ⇒ 00:10:45.579 Awaish Kumar: And then there was one related to Product analytics, so…
106 00:10:46.210 ⇒ 00:10:49.880 Awaish Kumar: Those were kind of, like, we basically agreed in a call.
107 00:10:50.680 ⇒ 00:10:56.280 Awaish Kumar: And, I shared with that with Luke, like, you can basically convert them into offers.
108 00:11:12.210 ⇒ 00:11:17.310 Uttam Kumaran: Okay. Is there anything else on the data side? Or anything, Sam, on the AI side?
109 00:11:18.080 ⇒ 00:11:27.060 Samuel Roberts: Yeah, I was… I mean, the cloud code’s not a bad idea. I was kind of struggling to come up with this, because, like, we’ve done a few things that… and they’re all kind of, like, bespoke per client. It’s very…
110 00:11:27.220 ⇒ 00:11:29.380 Samuel Roberts: Deb ShopPilie, and I don’t know…
111 00:11:30.260 ⇒ 00:11:36.780 Uttam Kumaran: Well, like, I guess, think even broadly about, like, now the stuff that we’ve done for Andy and for Lilo.
112 00:11:37.020 ⇒ 00:11:46.880 Uttam Kumaran: like… Yeah, I’m just trying to think through, like, are there things that, like, seem more…
113 00:11:47.160 ⇒ 00:11:48.969 Uttam Kumaran: Seemed, like, less bespoke.
114 00:11:49.460 ⇒ 00:11:50.370 Samuel Roberts: Yeah.
115 00:11:52.000 ⇒ 00:12:00.259 Samuel Roberts: I mean, there was, I mean, you know, Interlude, you know, was an interesting one, because it was definitely, like, taking things people were doing in Cloud already.
116 00:12:00.880 ⇒ 00:12:03.090 Samuel Roberts: Kind of mapping that into a process.
117 00:12:03.910 ⇒ 00:12:08.450 Samuel Roberts: you know, these other ones are kind of, like, the…
118 00:12:09.280 ⇒ 00:12:14.740 Samuel Roberts: they’re a little more specific. I mean, Andy obviously could apply, I suppose, to other, you know, customer service
119 00:12:15.100 ⇒ 00:12:16.780 Samuel Roberts: type roles.
120 00:12:16.980 ⇒ 00:12:20.730 Samuel Roberts: I don’t know if that’s really, like, a service. I think the… yeah, go ahead.
121 00:12:20.730 ⇒ 00:12:30.949 Uttam Kumaran: Yeah, I guess even to think about it in a different way, like, we could even start by saying, like, what are the services we develop as part of, like, the A&D project, right? Like, if I was to go…
122 00:12:30.950 ⇒ 00:12:31.540 Samuel Roberts: Yeah.
123 00:12:31.540 ⇒ 00:12:37.000 Uttam Kumaran: Example would be, like, like, the Google Chat chatbot integration.
124 00:12:37.970 ⇒ 00:12:43.929 Uttam Kumaran: Right? It’s… you can sort of… you can consider, like, okay, there may be many people that are interested in, like.
125 00:12:44.250 ⇒ 00:12:47.390 Uttam Kumaran: bringing chat experiences into their Google Workshop.
126 00:12:47.390 ⇒ 00:12:47.780 Samuel Roberts: space.
127 00:12:47.780 ⇒ 00:12:48.710 Uttam Kumaran: Right.
128 00:12:48.980 ⇒ 00:12:53.229 Uttam Kumaran: So, I would encourage you to think… Kinda, like, think that way.
129 00:12:53.850 ⇒ 00:12:54.950 Samuel Roberts: That’s better, yeah.
130 00:12:55.460 ⇒ 00:12:59.929 Awaish Kumar: Yeah, like, okay, in that case, like, one of the…
131 00:13:00.260 ⇒ 00:13:06.750 Awaish Kumar: So, on the data side, one of the services I can think of is migrating… migration of BI.
132 00:13:07.370 ⇒ 00:13:13.590 Awaish Kumar: tools. Now that AI is, like, being hot in the market.
133 00:13:14.160 ⇒ 00:13:20.639 Awaish Kumar: if, like, people may be interested in moving from Tableau to Omni, or something like that.
134 00:13:22.720 ⇒ 00:13:23.680 Uttam Kumaran: That’s a great one.
135 00:13:27.650 ⇒ 00:13:28.640 Uttam Kumaran: What else?
136 00:13:41.250 ⇒ 00:13:42.499 Awaish Kumar: God, I think…
137 00:13:43.680 ⇒ 00:13:49.819 Awaish Kumar: like, I can think of quite a few things which we are doing right now, like migration of
138 00:13:49.980 ⇒ 00:13:55.580 Awaish Kumar: data platforms, like, we are moving… we are helping Eden move from Basque to Remo.
139 00:13:55.820 ⇒ 00:14:04.619 Awaish Kumar: So, migration of… like, there are… there could be two services out of that. Migration of data pipelines, and we have migration…
140 00:14:04.830 ⇒ 00:14:12.389 Awaish Kumar: Of platform itself, so… On a… like, we are helping them move personal data.
141 00:14:13.580 ⇒ 00:14:18.420 Awaish Kumar: Right? As well as the reporting data, so… like, there could be.
142 00:14:18.420 ⇒ 00:14:23.840 Uttam Kumaran: Yeah, I… I would say, like, that… that one… Kind of feels like…
143 00:14:26.120 ⇒ 00:14:30.230 Uttam Kumaran: Yeah, it’s almost like source data migration, right? Or, like…
144 00:14:30.860 ⇒ 00:14:33.679 Uttam Kumaran: It’s sort of like reporting. Yeah, yeah.
145 00:14:35.400 ⇒ 00:14:40.119 Awaish Kumar: Yeah, so one is pipeline migration, and that happens quite often.
146 00:14:40.230 ⇒ 00:14:41.890 Awaish Kumar: I have done in my…
147 00:14:42.290 ⇒ 00:14:49.029 Awaish Kumar: carrier, like, quite a few times, like, people move from… start with Postgres, as it is an easy
148 00:14:49.310 ⇒ 00:14:54.939 Awaish Kumar: Thing to start with, then move on to cool cloud, like, on-prem to cloud migration.
149 00:14:56.490 ⇒ 00:15:03.680 Awaish Kumar: maybe now that people… Snowflake is hot in the market, people might be moving from, like, pick carry to Snowflake migration.
150 00:15:04.820 ⇒ 00:15:06.080 Awaish Kumar: We’ll shift to some of the.
151 00:15:11.570 ⇒ 00:15:12.440 Uttam Kumaran: Yes.
152 00:15:18.660 ⇒ 00:15:19.430 Uttam Kumaran: Okay.
153 00:15:19.590 ⇒ 00:15:22.899 Uttam Kumaran: Sam, what do you think? Now, kind of, like, hearing some of those examples?
154 00:15:23.450 ⇒ 00:15:30.040 Samuel Roberts: Yeah, I mean, I mean, there’s definitely, like, the, you know, even, you know, the Google Chat over thing got me thinking of just, like, rag chat in general.
155 00:15:30.230 ⇒ 00:15:34.740 Samuel Roberts: Over doc… like, documentation.
156 00:15:36.930 ⇒ 00:15:41.289 Uttam Kumaran: Okay, great. So I… so, probably, yeah, go ahead.
157 00:15:41.570 ⇒ 00:15:49.730 Samuel Roberts: Yeah, I was just gonna say, like, I mean, that could apply to a few different forms of documentation. Obviously, like, if it’s, you know, PDFs or things, if there’s people searching for, you know.
158 00:15:50.220 ⇒ 00:15:54.949 Samuel Roberts: all kinds of stuff in a chat, environment. Probably not.
159 00:15:55.230 ⇒ 00:15:57.079 Samuel Roberts: Crazy.
160 00:15:57.780 ⇒ 00:16:09.580 Samuel Roberts: you know, we’ve made it a little more complicated, I think, with Andy, because it’s all the Google Docs, and they’re changing, and everything needs to stay up to date and stuff, but if there’s just, like, a ton of, you know, documentation that someone has in a, you know, depending on what
161 00:16:09.760 ⇒ 00:16:12.760 Samuel Roberts: Field it is, or something.
162 00:16:13.510 ⇒ 00:16:15.480 Uttam Kumaran: Yeah, so one way I would describe this…
163 00:16:15.610 ⇒ 00:16:22.850 Uttam Kumaran: is to, like… so I think this is super helpful, and what I’m trying to do on, like, a meta level, what I’m trying to do here is give you guys…
164 00:16:23.130 ⇒ 00:16:27.250 Uttam Kumaran: the, like… Help you start to underst…
165 00:16:27.250 ⇒ 00:16:36.119 Samuel Roberts: see, like, what is, like, commercially, like, wrappable as a service, and so I’ll… like, in this conversation, I’ll play more of a salesperson. Like, what I… when I hear that.
166 00:16:36.120 ⇒ 00:16:42.949 Uttam Kumaran: I think about, like, okay, there’s probably a surface around, like, knowledge engineering and context preparation.
167 00:16:43.470 ⇒ 00:16:43.950 Samuel Roberts: Yeah.
168 00:16:43.950 ⇒ 00:16:47.039 Uttam Kumaran: For example, at ABC, we got in, and there’s, like.
169 00:16:47.220 ⇒ 00:16:53.949 Uttam Kumaran: there’s, like, PDFs, there’s, like, random Google Docs, there’s spreadsheets, but, like, none of them are, like.
170 00:16:54.250 ⇒ 00:16:58.560 Uttam Kumaran: They’re all kind of messy, so… It is sort of like…
171 00:16:59.270 ⇒ 00:17:09.060 Uttam Kumaran: context prep, right? Okay, we need to get this into a database, deprecate spreadsheets, move this into a single file, right? And so, that’s sort of, like, what I hear.
172 00:17:09.339 ⇒ 00:17:12.549 Samuel Roberts: Totally, totally, yeah, that’s definitely… serviceable.
173 00:17:12.550 ⇒ 00:17:17.339 Uttam Kumaran: That’s great, I think certainly we have, like, the slack
174 00:17:17.819 ⇒ 00:17:20.839 Uttam Kumaran: We sort of almost have, like, on the integration side.
175 00:17:20.849 ⇒ 00:17:21.619 Samuel Roberts: Yeah.
176 00:17:21.619 ⇒ 00:17:26.109 Uttam Kumaran: Right? We have, like, Google Chat integration. We certainly have Slack.
177 00:17:26.299 ⇒ 00:17:30.739 Uttam Kumaran: I don’t really want to advertise N8N stuff anymore.
178 00:17:30.740 ⇒ 00:17:31.430 Samuel Roberts: No.
179 00:17:31.430 ⇒ 00:17:35.040 Uttam Kumaran: as… so, like, I would like to move away from that, but, like.
180 00:17:36.130 ⇒ 00:17:37.799 Uttam Kumaran: You know, we do have, like.
181 00:17:38.720 ⇒ 00:17:42.230 Uttam Kumaran: So we have, like, cursor training, FOD code training.
182 00:17:43.280 ⇒ 00:17:45.900 Uttam Kumaran: Like, what are other, kind of, like, general…
183 00:17:46.470 ⇒ 00:17:49.679 Uttam Kumaran: Sort of, like, things that we’ve done for folks.
184 00:17:49.980 ⇒ 00:17:55.779 Samuel Roberts: Yeah, I mean, like, a general end-to-end training, if people want to use it, like, it’s not a bad tool for the right…
185 00:17:56.400 ⇒ 00:18:02.819 Samuel Roberts: company, you know what I mean? Like, if it’s… I think, like, we definitely have a lot of knowledge there still that it would be a shame to, like, waste.
186 00:18:04.070 ⇒ 00:18:11.940 Samuel Roberts: And, you know, for simple things, like, if people are on, like, a Zapier and need something a little more powerful, like, it’s not the wrong tool, so I wouldn’t say that’s a…
187 00:18:12.050 ⇒ 00:18:19.900 Samuel Roberts: a bad idea. I wouldn’t, you know, lead into it as, like, a tool we’re using, but as a training, like, not a bad idea.
188 00:18:20.250 ⇒ 00:18:27.640 Samuel Roberts: Yeah, let’s see… I mean, some of this MCP stuff is interesting,
189 00:18:27.870 ⇒ 00:18:33.990 Samuel Roberts: you know, we were obviously specifically looking at a few for Lilo, we’ve done a bunch that way, but, like.
190 00:18:33.990 ⇒ 00:18:38.700 Uttam Kumaran: even our own, like, internal Google Cloud… Yeah, talk to me about that. Yeah, yeah.
191 00:18:38.820 ⇒ 00:18:50.750 Samuel Roberts: Yeah, I mean, when I went to the Google Workspace repo, like, it looks like they’re even trying to host it, like, as a cloud service per user. So, like, if it’s something that even is, like, setting something like that up for
192 00:18:50.900 ⇒ 00:18:53.110 Samuel Roberts: For the right company that needs
193 00:18:53.410 ⇒ 00:19:02.030 Samuel Roberts: you know, an MCP, like, kind of like we do, where, like, we could run it locally, but it would be much better and more user-friendly for the whole team if it was a thing you could just OAuth into.
194 00:19:03.440 ⇒ 00:19:10.410 Samuel Roberts: Which is kind of how we set up with the Meta stuff and the Google stuff specifically for Lilo anyway. So I suppose, you know, if there’s…
195 00:19:10.620 ⇒ 00:19:20.609 Samuel Roberts: there’s two sides to that. There’s, like, actually building, like, MCP tools for a company, but then there’s also just, like, deploying the tool itself,
196 00:19:21.220 ⇒ 00:19:29.139 Samuel Roberts: into whatever environment they need. Like, obviously for Lilo, it’s very specific to their chat, but for something like, you know, Andy and Google Chat, like, it could be…
197 00:19:29.490 ⇒ 00:19:32.770 Samuel Roberts: Hitting some other data… some other tool.
198 00:19:34.910 ⇒ 00:19:40.530 Uttam Kumaran: Yeah, so I think, Sheshu, you’re, you’re, like, you’re kind of familiar with
199 00:19:40.710 ⇒ 00:19:44.859 Uttam Kumaran: MCP and, like, Cursor, and, like, you’ve kind of used some of these tools before?
200 00:19:45.900 ⇒ 00:19:50.189 Sheshu Chandrasekar: Yeah, I’ve… I’ve played around with some NSTP tools, like, especially with Cloud.
201 00:19:50.190 ⇒ 00:19:51.389 Samuel Roberts: Because I was, like.
202 00:19:51.560 ⇒ 00:19:56.840 Sheshu Chandrasekar: It was so popular when it first came out, so… played around with it.
203 00:19:57.130 ⇒ 00:19:58.639 Sheshu Chandrasekar: But in all honesty, like.
204 00:19:59.800 ⇒ 00:20:07.650 Sheshu Chandrasekar: I think it’s only useful… it was only useful for me because I wanted to, kind of get my calendar organized a little bit.
205 00:20:07.920 ⇒ 00:20:25.160 Sheshu Chandrasekar: And also, I had some documents, like, for example, if I had a calendar that said, like, okay, I need to fill out, renew my passport or something, right? It would fetch, like, documents in my drive, and pull up the relevant personal documents I had. And it helped me with those types of stuff, but
206 00:20:25.220 ⇒ 00:20:31.029 Sheshu Chandrasekar: Nothing too crazy. Oh, I’m sorry, Robert just pinged me right now.
207 00:20:33.210 ⇒ 00:20:34.790 Uttam Kumaran: You’re saying join the sales thing?
208 00:20:35.310 ⇒ 00:20:36.560 Sheshu Chandrasekar: I think so.
209 00:20:37.180 ⇒ 00:20:48.680 Uttam Kumaran: Okay. Well, I guess, like, yeah, maybe… basically what I want… what I was gonna ask you, too, is, like, hearing kind of all this, are there any services that you think, like, even in the AI or the data world, you think we.
210 00:20:48.680 ⇒ 00:20:58.979 Sheshu Chandrasekar: Yeah, I did want to talk about… I did want to, like… I don’t know how much involvement, Brainforge has… Brainforge has in this, but maybe, like, voice agents, right? I mean…
211 00:20:58.980 ⇒ 00:20:59.360 Samuel Roberts: Hmm.
212 00:20:59.360 ⇒ 00:21:08.589 Sheshu Chandrasekar: I’ve been noticing so much, like, activity in that, and there’s so many partnership opportunities, and everyone’s talking about how’s the next trillion dollar opportunity. I mean.
213 00:21:09.280 ⇒ 00:21:11.510 Sheshu Chandrasekar: like, I have a thesis that…
214 00:21:11.800 ⇒ 00:21:26.189 Sheshu Chandrasekar: a lot of services-based companies, like, we’re thinking of ABC Construction, healthcare, they’re all gonna move to voice agents at some point, and not everyone is able to onboard onto voice agents, like, rapidly, and maybe we could
215 00:21:26.470 ⇒ 00:21:37.949 Sheshu Chandrasekar: we could be, a forefront of, like, champion in that sense, that we can be like, hey, like, we develop voice agents, and we think we can, like, help you out, reduce X amount of…
216 00:21:38.120 ⇒ 00:21:40.439 Sheshu Chandrasekar: calls per day, right?
217 00:21:40.440 ⇒ 00:21:41.950 Uttam Kumaran: So, Sam, I guess…
218 00:21:42.170 ⇒ 00:21:43.970 Samuel Roberts: Yeah. Hearing that, like…
219 00:21:44.830 ⇒ 00:21:47.110 Uttam Kumaran: How would you frame it as a service?
220 00:21:51.330 ⇒ 00:22:01.970 Samuel Roberts: Yeah, I mean, we… you and I chatted a little bit about this for ABC, like, throwing together something, with VAPI, I think it was, just to see what it could do.
221 00:22:02.260 ⇒ 00:22:07.300 Samuel Roberts: As a service, it feels like we want to, like…
222 00:22:07.430 ⇒ 00:22:11.499 Samuel Roberts: Sell that as, like, an entry point into these other things, maybe?
223 00:22:12.930 ⇒ 00:22:13.929 Samuel Roberts: I don’t know…
224 00:22:13.930 ⇒ 00:22:17.619 Uttam Kumaran: I almost see it as, like, another… it’s like another integration, right?
225 00:22:17.850 ⇒ 00:22:21.759 Samuel Roberts: Yeah, that’s what I mean, like, I don’t think it’s its own, you know, I wouldn’t just be, like, you know, voice…
226 00:22:22.100 ⇒ 00:22:31.440 Samuel Roberts: like, yeah, I think integration is the right way to think about it. That’s kind of what I was… like, if we had that into Andy, it would be another… another piece of it, rather than, like, a whole thing.
227 00:22:33.600 ⇒ 00:22:43.850 Uttam Kumaran: Yeah, so we… we would have this, like, voice, and yeah, Shishi, we’ve done voice, and in particular, you’ll… you should go check out, like, our case study bot that we built.
228 00:22:45.880 ⇒ 00:22:51.790 Uttam Kumaran: We basically built a bot that interviews you for case studies internally, and it uses voice. Oh, okay.
229 00:22:52.590 ⇒ 00:23:00.699 Samuel Roberts: I actually forgot how good that was, because when I… when I threw the Slack notifications in there the other day, I tested it, just ran, like, a very quick, like, case study on the thing itself, and it was…
230 00:23:01.010 ⇒ 00:23:04.939 Samuel Roberts: I forgot how, like, uncanny it is, actually. It’s really interesting.
231 00:23:06.310 ⇒ 00:23:06.890 Uttam Kumaran: Yeah.
232 00:23:08.670 ⇒ 00:23:12.259 Uttam Kumaran: So we have Google Chat, Slack, Voice. I think,
233 00:23:12.490 ⇒ 00:23:16.589 Uttam Kumaran: I mean, we are starting to do image… And video generation.
234 00:23:16.590 ⇒ 00:23:20.999 Samuel Roberts: Yeah, yeah, we do have a little bit of that now, so that could be something we…
235 00:23:22.220 ⇒ 00:23:22.790 Samuel Roberts: We’re in.
236 00:23:22.790 ⇒ 00:23:30.270 Uttam Kumaran: Is that, like, you consider that additionally, like, an integration, or that, like… Is that more like contents?
237 00:23:33.920 ⇒ 00:23:35.650 Samuel Roberts: What do you mean?
238 00:23:35.760 ⇒ 00:23:37.609 Samuel Roberts: context for the… like, for…
239 00:23:37.610 ⇒ 00:23:42.169 Uttam Kumaran: Well, I guess, like, I’m trying to think about, like, A content, meaning…
240 00:23:42.270 ⇒ 00:23:46.280 Samuel Roberts: Oh, content, yeah, yeah, okay, so I… yeah, context threw me off. Content, definitely.
241 00:23:46.280 ⇒ 00:23:51.120 Uttam Kumaran: I think we could… Slides versus images versus videos versus, like.
242 00:23:53.560 ⇒ 00:23:54.810 Samuel Roberts: Yeah, I think…
243 00:23:59.350 ⇒ 00:24:08.159 Samuel Roberts: I mean, yeah, there’s a lot of different use cases here, but I don’t know where we want to, like, settle into. I mean, the, like, we already kind of have, like.
244 00:24:08.500 ⇒ 00:24:10.959 Samuel Roberts: CPG, kind of…
245 00:24:11.800 ⇒ 00:24:16.960 Samuel Roberts: like, I don’t want to be like what Lilo’s doing, but broader, but that’s kind of what I’m, you know…
246 00:24:18.680 ⇒ 00:24:20.790 Samuel Roberts: Could be… could be something like that.
247 00:24:23.550 ⇒ 00:24:24.340 Uttam Kumaran: And so what?
248 00:24:24.340 ⇒ 00:24:25.280 Samuel Roberts: Stuff I don’t know much about.
249 00:24:25.280 ⇒ 00:24:28.379 Uttam Kumaran: What are… what is… what is the thing we’re doing for Lilo in particular?
250 00:24:28.380 ⇒ 00:24:32.069 Samuel Roberts: So that, I mean, that tool is just, like, add, add, you know…
251 00:24:32.390 ⇒ 00:24:38.029 Samuel Roberts: image generator. So they have all the products in Shopify, and it can fetch all of the, like.
252 00:24:38.150 ⇒ 00:24:45.600 Samuel Roberts: like, the stock photos from their Shopify store, and you can make add content right there.
253 00:24:45.900 ⇒ 00:24:49.299 Samuel Roberts: I think they had some video stuff too, but,
254 00:24:49.970 ⇒ 00:24:56.740 Samuel Roberts: I’d be curious to even dig into some of the prompts that Replit generated for them that were pretty powerful, it seems, so…
255 00:24:59.170 ⇒ 00:25:05.180 Samuel Roberts: you know, I don’t know if just, like, ad… ad content generation is really the sell here, but I’m sure there’s other places where
256 00:25:05.600 ⇒ 00:25:12.660 Samuel Roberts: You know, very specific image generation stuff could be… Could be helpful.
257 00:25:17.190 ⇒ 00:25:23.620 Samuel Roberts: Yeah, video I know less about at this point. I feel a little bit, like, less confident there, until we play around more with…
258 00:25:24.030 ⇒ 00:25:26.240 Samuel Roberts: with Lilo, at least.
259 00:25:26.240 ⇒ 00:25:26.900 Uttam Kumaran: Okay.
260 00:25:27.480 ⇒ 00:25:29.900 Samuel Roberts: Slides and stuff is still interesting, that seems like an area.
261 00:25:29.900 ⇒ 00:25:30.389 Awaish Kumar: And we…
262 00:25:30.390 ⇒ 00:25:32.459 Samuel Roberts: We’ve even bounced around a bit, but yeah.
263 00:25:34.150 ⇒ 00:25:40.750 Awaish Kumar: Can you use, like, lLMs to get the… Price? Like, the pricing?
264 00:25:44.720 ⇒ 00:25:45.570 Uttam Kumaran: What do you mean?
265 00:25:45.570 ⇒ 00:25:49.240 Awaish Kumar: competitors, like, for example, like, companies like Element.
266 00:25:49.870 ⇒ 00:25:53.579 Awaish Kumar: like, using AI to help them with, like, price their product.
267 00:25:53.910 ⇒ 00:25:56.639 Awaish Kumar: Any specific stores, like.
268 00:25:56.640 ⇒ 00:25:57.530 Samuel Roberts: Hmm.
269 00:25:57.790 ⇒ 00:25:59.349 Awaish Kumar: To, to boost the revenue.
270 00:26:05.600 ⇒ 00:26:06.429 Samuel Roberts: Yeah, I don’t know, what are they…
271 00:26:07.830 ⇒ 00:26:11.900 Uttam Kumaran: Well, I would almost… well, I guess, what is the generalizable, sort of, like.
272 00:26:12.270 ⇒ 00:26:13.020 Samuel Roberts: Yeah.
273 00:26:13.650 ⇒ 00:26:21.679 Awaish Kumar: Yeah, but this… like, you… we can talk… like, if we have this kind of service which can be applied to any CPG company.
274 00:26:24.710 ⇒ 00:26:26.589 Samuel Roberts: So, like, some kind of, like, price analysis?
275 00:26:27.260 ⇒ 00:26:28.270 Awaish Kumar: Yeah, price.
276 00:26:28.270 ⇒ 00:26:31.440 Uttam Kumaran: But I guess, go, go, like, one step higher.
277 00:26:32.150 ⇒ 00:26:38.560 Uttam Kumaran: Like… I would almost put that as in, like, Sort of, like, AI-assisted.
278 00:26:40.700 ⇒ 00:26:43.499 Uttam Kumaran: Like, yeah, competitive analysis, right?
279 00:26:43.500 ⇒ 00:26:44.340 Samuel Roberts: Yeah, yeah.
280 00:26:48.990 ⇒ 00:26:52.869 Uttam Kumaran: So then what I would put is, I would put, like, AI-assisted analysis.
281 00:26:53.710 ⇒ 00:26:57.510 Uttam Kumaran: And this one option there is, like, competitive analysis.
282 00:26:58.450 ⇒ 00:27:01.760 Uttam Kumaran: Right, so this is sort of a lot of the things that, like, Amber was doing.
283 00:27:03.290 ⇒ 00:27:07.950 Awaish Kumar: Yeah, like, but, like, my…
284 00:27:08.270 ⇒ 00:27:13.989 Awaish Kumar: The analysis is just like you are sharing some insights on a deck, right?
285 00:27:14.310 ⇒ 00:27:18.999 Awaish Kumar: I’m more talking about maybe… A service which basically can…
286 00:27:19.380 ⇒ 00:27:23.729 Awaish Kumar: Get you the actual prices, and can help you update in the system.
287 00:27:23.940 ⇒ 00:27:28.640 Awaish Kumar: So that is reflected directly in the system, not just stay on the deck.
288 00:27:33.050 ⇒ 00:27:34.789 Awaish Kumar: Like, end-to-end service.
289 00:27:35.710 ⇒ 00:27:36.300 Uttam Kumaran: analytics.
290 00:27:36.300 ⇒ 00:27:39.980 Awaish Kumar: So… Actually putting in operational data.
291 00:27:45.890 ⇒ 00:27:49.880 Uttam Kumaran: Okay, yeah, I’ll probably… I guess I got short of them with you, but I kind of need to…
292 00:27:51.130 ⇒ 00:27:56.690 Uttam Kumaran: For that, like, we’ve… yeah, I’m sort of, like, kind of… maybe we have to talk to Amber and kind of see, like, what it is and everything.
293 00:27:57.370 ⇒ 00:27:58.150 Samuel Roberts: Yeah.
294 00:28:03.850 ⇒ 00:28:20.820 Samuel Roberts: I mean, there’s also, like, you know, board stuff in terms of, like, ingesting meetings and having a searchable, like, I don’t know… I know, I mean, some of these tools have that, so if you’re using, you know, Zoom, maybe you’re getting the AI assistant there, but maybe at places like us where there’s some meetings happening in different places or something, like.
295 00:28:21.020 ⇒ 00:28:22.410 Samuel Roberts: There’s still a…
296 00:28:23.480 ⇒ 00:28:27.030 Samuel Roberts: This might just go to some of the con- the contact stuff you said before, but…
297 00:28:27.970 ⇒ 00:28:29.820 Uttam Kumaran: Yeah, so this is where, like…
298 00:28:30.890 ⇒ 00:28:34.199 Uttam Kumaran: You know, I’ve seen this being described as, like, work OS.
299 00:28:34.650 ⇒ 00:28:35.160 Samuel Roberts: Yeah.
300 00:28:35.600 ⇒ 00:28:38.459 Uttam Kumaran: Someone described to me as, like, business…
301 00:28:38.820 ⇒ 00:28:43.639 Uttam Kumaran: Like, sort of their, business consciousness, is what someone explained this to me as.
302 00:28:43.850 ⇒ 00:28:45.839 Uttam Kumaran: I understand that. Yeah.
303 00:28:45.840 ⇒ 00:28:47.160 Samuel Roberts: Yeah, yeah.
304 00:28:47.220 ⇒ 00:28:50.699 Uttam Kumaran: But yeah, I mean, I feel like there’s probably something…
305 00:28:50.740 ⇒ 00:28:56.379 Samuel Roberts: to dive into there? Like, obviously, that’s very broad, and there’s probably a lot of things happening there.
306 00:28:56.650 ⇒ 00:29:01.249 Samuel Roberts: Just in the space, but I’m trying to think if there’s, like, very targeted ones, like…
307 00:29:02.250 ⇒ 00:29:06.109 Uttam Kumaran: Yeah, like, what is something that, like, Every… every company would…
308 00:29:06.260 ⇒ 00:29:08.760 Uttam Kumaran: need, which is, like, potentially, like.
309 00:29:09.610 ⇒ 00:29:16.139 Uttam Kumaran: I mean, one, it would potentially be, like, a… recording… pool setup.
310 00:29:16.690 ⇒ 00:29:17.090 Samuel Roberts: Damn.
311 00:29:17.090 ⇒ 00:29:20.420 Uttam Kumaran: And then transcript, ingestion and processing.
312 00:29:21.010 ⇒ 00:29:21.560 Samuel Roberts: Right.
313 00:29:25.880 ⇒ 00:29:26.780 Samuel Roberts: Yeah.
314 00:29:29.140 ⇒ 00:29:32.000 Samuel Roberts: Yeah, I’d be curious to see, because I’m sure there’s, you know, like I said, there’s probably
315 00:29:32.200 ⇒ 00:29:37.999 Samuel Roberts: people out there, startups out there, big companies out there, all trying to do that. I’m wondering if there’s, like, even a targeted, like.
316 00:29:38.360 ⇒ 00:29:39.260 Uttam Kumaran: Industry-specific.
317 00:29:39.540 ⇒ 00:29:42.760 Samuel Roberts: like, you know, like, what we’re doing for Lilo is very specific to their…
318 00:29:42.760 ⇒ 00:29:43.689 Uttam Kumaran: I mean, the other thing we get.
319 00:29:43.690 ⇒ 00:29:45.589 Samuel Roberts: Our version of their platform, kind of thing.
320 00:29:46.930 ⇒ 00:29:51.989 Uttam Kumaran: Yeah, one way to narrow it is we could just say we’re doing it for service business.
321 00:29:52.460 ⇒ 00:29:53.040 Samuel Roberts: Yeah.
322 00:29:55.610 ⇒ 00:29:56.620 Samuel Roberts: Doesn’t work.
323 00:29:56.920 ⇒ 00:30:03.120 Awaish Kumar: Like, if we want to just keep it, like, kind of small services, it could be one of them.
324 00:30:03.250 ⇒ 00:30:05.869 Awaish Kumar: One of it could be, like, what we started with.
325 00:30:07.470 ⇒ 00:30:09.750 Awaish Kumar: Using an attend?
326 00:30:10.050 ⇒ 00:30:13.900 Awaish Kumar: create, like, Slack board, which can… and chat with you at all.
327 00:30:14.020 ⇒ 00:30:15.360 Awaish Kumar: Select messages.
328 00:30:15.540 ⇒ 00:30:16.350 Awaish Kumar: Basically.
329 00:30:20.660 ⇒ 00:30:21.320 Samuel Roberts: Hmm.
330 00:30:22.100 ⇒ 00:30:25.970 Awaish Kumar: like, connect with Slack directly in NNDIT, it will read the data there.
331 00:30:26.550 ⇒ 00:30:27.210 Awaish Kumar: Ow.
332 00:30:28.020 ⇒ 00:30:32.310 Awaish Kumar: Basically, generate a… Slack up.
333 00:30:32.310 ⇒ 00:30:37.659 Uttam Kumaran: But I’m almost trying… I’m trying to… I’m just almost, like, trying to think about, like, the generalizable service, though.
334 00:30:37.660 ⇒ 00:30:38.600 Samuel Roberts: Right.
335 00:30:39.430 ⇒ 00:30:43.129 Uttam Kumaran: Because that seems that that falls under, like, Slack integration.
336 00:30:44.560 ⇒ 00:30:44.950 Awaish Kumar: Bye.
337 00:30:44.950 ⇒ 00:30:49.760 Uttam Kumaran: I do think that this workOS thing is more of, like, agency WorkOS, maybe.
338 00:30:50.250 ⇒ 00:30:50.940 Samuel Roberts: Yeah.
339 00:30:50.940 ⇒ 00:30:52.500 Uttam Kumaran: Agency or service?
340 00:30:53.510 ⇒ 00:30:55.290 Uttam Kumaran: Business WorkOS.
341 00:30:55.730 ⇒ 00:31:00.060 Samuel Roberts: Right, like, you know, like a client management, almost, like, helping you
342 00:31:00.580 ⇒ 00:31:06.380 Samuel Roberts: You know, kind of what we… the issues we’ve been having, like, the stand-up info, the… the,
343 00:31:07.030 ⇒ 00:31:12.160 Samuel Roberts: You know, being able to chat over all the transcripts for a given client, and know the current status of a project, like…
344 00:31:15.760 ⇒ 00:31:24.539 Samuel Roberts: I mean, there could even be, like, if we lean into that a little more, there could be some ways that we could… you know, I’m just thinking, like, internal platform now, like, you know, we’ve talked about
345 00:31:24.670 ⇒ 00:31:37.530 Samuel Roberts: the idea of a client having, like, a current status, and, like, keeping all that, and tracking that over time, and, you know, right now it kind of just leans into the transcripts and parsing that for the stand-up, but if it was, like.
346 00:31:37.780 ⇒ 00:31:40.559 Samuel Roberts: You know, what are the goals, what are the tickets, what are the…
347 00:31:41.560 ⇒ 00:31:47.149 Samuel Roberts: I think I’m getting a little too into it now, but, I could see there being something…
348 00:31:47.260 ⇒ 00:31:48.890 Samuel Roberts: marketable there.
349 00:31:54.130 ⇒ 00:31:57.559 Samuel Roberts: You know, kind of what we’re, like, building towards with the platform anyway.
350 00:32:01.370 ⇒ 00:32:06.380 Uttam Kumaran: Yeah, I mean, look, to be honest, like, a lot of people are gonna… Like…
351 00:32:06.650 ⇒ 00:32:11.609 Uttam Kumaran: Like, people are already asking me about, like, if we can build our platform for that.
352 00:32:12.210 ⇒ 00:32:19.189 Samuel Roberts: Yeah, I had that thought as I was working on it, I’m like, this isn’t very, like, generalizable as the code is right now, but it could be.
353 00:32:19.320 ⇒ 00:32:28.320 Uttam Kumaran: Well, we learned, like, all the things we were doing for LEED, a lot of them we… I forced us to do it for us, because I knew people were gonna ask us for this. We were just conversing.
354 00:32:28.940 ⇒ 00:32:29.800 Samuel Roberts: Yeah.
355 00:32:30.110 ⇒ 00:32:38.079 Uttam Kumaran: So, in that sense… Yeah, I mean, like, for example, like, the case study…
356 00:32:38.790 ⇒ 00:32:40.460 Uttam Kumaran: Saying is something that everyone.
357 00:32:40.460 ⇒ 00:32:40.820 Samuel Roberts: Yeah.
358 00:32:40.820 ⇒ 00:32:42.219 Uttam Kumaran: This company needs, right?
359 00:32:42.660 ⇒ 00:32:43.310 Samuel Roberts: True.
360 00:32:47.350 ⇒ 00:32:54.329 Uttam Kumaran: Yeah, there’s something around that, which is, like, like, Brainforge platform.
361 00:32:55.090 ⇒ 00:32:55.720 Samuel Roberts: Yeah.
362 00:32:57.310 ⇒ 00:33:01.440 Samuel Roberts: Yeah, or even, like, yeah, pieces of it, like you’re saying, like, the case study thing itself could just be a…
363 00:33:01.950 ⇒ 00:33:02.910 Samuel Roberts: You know, a tool…
364 00:33:02.910 ⇒ 00:33:03.930 Uttam Kumaran: case studies and stuff like that.
365 00:33:03.930 ⇒ 00:33:04.359 Samuel Roberts: I was getting…
366 00:33:04.360 ⇒ 00:33:05.500 Uttam Kumaran: files.
367 00:33:05.500 ⇒ 00:33:06.310 Samuel Roberts: Yeah.
368 00:33:15.270 ⇒ 00:33:16.020 Uttam Kumaran: Okay.
369 00:33:16.680 ⇒ 00:33:18.519 Uttam Kumaran: Cool. What else have we done?
370 00:33:20.220 ⇒ 00:33:26.150 Uttam Kumaran: Asian… yeah, we have, like, for example, I think cursor training, cloud coach training, NADM training.
371 00:33:26.520 ⇒ 00:33:29.080 Uttam Kumaran: I also think about, like, Mastra.
372 00:33:30.150 ⇒ 00:33:30.740 Samuel Roberts: Yep.
373 00:33:30.740 ⇒ 00:33:36.139 Uttam Kumaran: Right, eval… Training… What else comes to mind?
374 00:33:36.790 ⇒ 00:33:37.870 Samuel Roberts: Hmm…
375 00:33:42.780 ⇒ 00:33:47.429 Samuel Roberts: I mean, from, like, a… I mean, I kind of touched on this before, but, like, thinking back to Interlude, like.
376 00:33:47.650 ⇒ 00:33:49.789 Samuel Roberts: Something about, like, just, like, automating
377 00:33:49.940 ⇒ 00:33:53.480 Samuel Roberts: A process that someone might already be doing pretty, like.
378 00:33:53.700 ⇒ 00:33:59.800 Samuel Roberts: like, people using Claw in very particular ways, I don’t know how that is marketable.
379 00:33:59.800 ⇒ 00:34:00.370 Uttam Kumaran: Yeah, like…
380 00:34:00.370 ⇒ 00:34:06.459 Samuel Roberts: like, the language, but, like, something that’s just, like, you know, more automation AI-focused, rather than, like.
381 00:34:07.360 ⇒ 00:34:10.569 Samuel Roberts: you know, solve that process that we’re doing.
382 00:34:10.870 ⇒ 00:34:17.940 Uttam Kumaran: It’s sort of like, you have this, like, bulky, custom GPT, custom cloud project.
383 00:34:19.219 ⇒ 00:34:20.810 Uttam Kumaran: to something else.
384 00:34:21.070 ⇒ 00:34:28.150 Samuel Roberts: Because I bet there’s a number of people doing that stuff exactly like… like he was, where he’s got a system defined, but…
385 00:34:28.320 ⇒ 00:34:34.120 Samuel Roberts: like, why is… why is he pasting everything everywhere? You know, like, it’s not a huge lift to make that an agent.
386 00:34:34.540 ⇒ 00:34:37.139 Samuel Roberts: Or a series of agents, like we did.
387 00:34:37.889 ⇒ 00:34:42.509 Uttam Kumaran: Yeah… Like, what’s… let me ask Chatri, what’s, like, a business…
388 00:34:43.519 ⇒ 00:34:50.049 Uttam Kumaran: Sales-facing name for a service, where we take, bucks.
389 00:34:50.779 ⇒ 00:34:53.759 Uttam Kumaran: SMGPT, thing.
390 00:34:53.979 ⇒ 00:34:55.059 Uttam Kumaran: broadcasts.
391 00:34:55.620 ⇒ 00:34:58.060 Samuel Roberts: Process automation feels too generic, but…
392 00:34:58.060 ⇒ 00:35:03.000 Uttam Kumaran: Yeah, and turn them into… like, what are we turning them into?
393 00:35:04.380 ⇒ 00:35:11.390 Uttam Kumaran: like, more… Predictable… Bye.
394 00:35:12.130 ⇒ 00:35:14.470 Uttam Kumaran: left, funky.
395 00:35:14.800 ⇒ 00:35:15.529 Samuel Roberts: Yeah, scale.
396 00:35:15.530 ⇒ 00:35:20.260 Uttam Kumaran: Maybe… scalable… And shareable.
397 00:35:20.610 ⇒ 00:35:21.680 Samuel Roberts: Terrible, yeah.
398 00:35:22.870 ⇒ 00:35:26.620 Uttam Kumaran: more… like, observability…
399 00:35:26.620 ⇒ 00:35:28.739 Samuel Roberts: An ability to diagnose.
400 00:35:30.550 ⇒ 00:35:32.179 Uttam Kumaran: Okay, let’s see what it says.
401 00:35:33.740 ⇒ 00:35:41.830 Uttam Kumaran: operationalizes bespoke AI work. The buyer pain is not we need a cool GPT, this thing’s fragile, opaque, and impossible to scale or trust.
402 00:35:42.840 ⇒ 00:35:50.740 Uttam Kumaran: AI systemization… I don’t know, Clarence, maybe what Clarence will have a good idea here. AI systemization, AI operationalization, ugh.
403 00:35:50.840 ⇒ 00:35:51.890 Uttam Kumaran: So I’m done.
404 00:35:53.110 ⇒ 00:35:54.280 Uttam Kumaran: AI…
405 00:35:54.560 ⇒ 00:35:56.540 Clarence Stone: Hey, I just got here.
406 00:35:57.010 ⇒ 00:36:03.609 Uttam Kumaran: We’re just, we’re discussing, like, I’ll send this note in. We’re discussing, sort of, like, potential services that
407 00:36:03.870 ⇒ 00:36:08.929 Uttam Kumaran: We’ve identified from all the things that we do, Enterprise AI hardening.
408 00:36:13.500 ⇒ 00:36:16.520 Uttam Kumaran: AI system standardization.
409 00:36:19.630 ⇒ 00:36:23.050 Uttam Kumaran: From custom GPTs to enterprise AI systems.
410 00:36:24.330 ⇒ 00:36:26.520 Uttam Kumaran: Enterprise AI hardening.
411 00:36:29.990 ⇒ 00:36:30.690 Uttam Kumaran: Awesome.
412 00:36:30.690 ⇒ 00:36:31.220 Samuel Roberts: environment.
413 00:36:31.390 ⇒ 00:36:33.120 Uttam Kumaran: Some of these are so stupid.
414 00:36:36.100 ⇒ 00:36:39.109 Uttam Kumaran: I guess I’m just trying to think of, like, what the name is, basically, but…
415 00:36:39.110 ⇒ 00:36:40.930 Samuel Roberts: Yeah, no, I hear you.
416 00:36:42.330 ⇒ 00:36:44.409 Uttam Kumaran: Do people know what hardening is? Like…
417 00:36:44.910 ⇒ 00:36:50.550 Samuel Roberts: Yeah, I mean… I mean, the right people might know what that means, but yeah, maybe there’s another word that’s just, like…
418 00:36:52.230 ⇒ 00:36:56.570 Samuel Roberts: Yeah.
419 00:37:06.520 ⇒ 00:37:10.250 Clarence Stone: So, my advice here is to think about
420 00:37:10.520 ⇒ 00:37:14.730 Clarence Stone: The feature, and then describe what the product would be for that.
421 00:37:16.730 ⇒ 00:37:17.660 Clarence Stone: So.
422 00:37:17.660 ⇒ 00:37:33.800 Uttam Kumaran: Well, like, the feature here is, like, you know, we’ve had clients come to us because they have, like, a bunch of, like, Claude code. They have a bunch of, like, custom GPTs that, like, talk to each other, and they have, like, a bunch of Claude projects that, like, get to copy-paste from one project to the other, you know, it’s, like, kind of clunky.
423 00:37:34.050 ⇒ 00:37:35.310 Uttam Kumaran: Something, like, nasty.
424 00:37:36.470 ⇒ 00:37:40.419 Uttam Kumaran: And you’re like, could you turn this into something, like, real that I can, like, have other people
425 00:37:40.950 ⇒ 00:37:44.219 Uttam Kumaran: You don’t need to know, like, rocket science to use this.
426 00:37:45.140 ⇒ 00:37:49.929 Clarence Stone: Yeah, so, like, streamlining, multi-agent workflows.
427 00:37:50.090 ⇒ 00:37:56.630 Clarence Stone: Improving the reliability, predictability, or outputs of
428 00:37:57.110 ⇒ 00:38:00.100 Clarence Stone: You know, adjacent workflows, something like that.
429 00:38:00.720 ⇒ 00:38:01.440 Uttam Kumaran: Okay.
430 00:38:03.020 ⇒ 00:38:10.649 Clarence Stone: Right, that’s really the feature, and then, like, the product you’re actually selling, you know, you… say, AI implementation.
431 00:38:13.460 ⇒ 00:38:14.450 Uttam Kumaran: I agree.
432 00:38:15.670 ⇒ 00:38:18.420 Uttam Kumaran: most, like, AI… Yeah…
433 00:38:24.060 ⇒ 00:38:26.319 Uttam Kumaran: Hmm… I see what you mean.
434 00:38:26.940 ⇒ 00:38:27.700 Clarence Stone: Yeah.
435 00:38:37.670 ⇒ 00:38:42.500 Uttam Kumaran: Okay, I’m good. That’s actually really helpful, I’m just, like, having blanking on this file.
436 00:38:42.900 ⇒ 00:38:44.450 Uttam Kumaran: For this one, I’m gonna put, like…
437 00:38:44.450 ⇒ 00:38:47.570 Clarence Stone: Into the patch, because, you can just, like.
438 00:38:47.720 ⇒ 00:38:54.509 Clarence Stone: you probably have GPT suggest that to you, right? Like, these are all the things that we do, like, how do we wrap this into an easy.
439 00:38:54.510 ⇒ 00:38:54.860 Samuel Roberts: Yeah.
440 00:38:54.860 ⇒ 00:38:58.500 Clarence Stone: Describable two, three-word product name.
441 00:38:59.630 ⇒ 00:39:00.970 Uttam Kumaran: Yeah, okay, okay.
442 00:39:01.260 ⇒ 00:39:06.890 Uttam Kumaran: So, if you look, guys in the Service Leads channel, I just sent all of them.
443 00:39:08.020 ⇒ 00:39:20.220 Uttam Kumaran: This is lovely, and I also think this isn’t everything, you know? But roughly, right now, someone who comes to us can get all… these are, like, menus. This is our menus. This does not include everything we already do.
444 00:39:20.620 ⇒ 00:39:27.559 Uttam Kumaran: Right? And so, I would like us to continue to think about these as, like, things we can do and things we currently do.
445 00:39:27.730 ⇒ 00:39:30.529 Uttam Kumaran: Ideally, things we currently do…
446 00:39:31.290 ⇒ 00:39:46.539 Uttam Kumaran: or have done in the past are, like, the first things that we need to clarify. But strategically, for example, there’s no… there’s nothing, like, preventing us from getting into, like, data science workloads, right? No. And we just haven’t had it to someone ask us. But there will be also things that we want to proactively get into.
447 00:39:46.670 ⇒ 00:39:54.520 Uttam Kumaran: And once we kind of codify this, we can go to external. Because, for example, I have… there’s 3 companies that are asking me to train them in person.
448 00:39:55.610 ⇒ 00:39:56.300 Samuel Roberts: Mmm.
449 00:39:56.300 ⇒ 00:39:57.780 Uttam Kumaran: And train their team in cruising.
450 00:39:58.690 ⇒ 00:40:00.890 Samuel Roberts: Through existing clients.
451 00:40:01.480 ⇒ 00:40:05.709 Uttam Kumaran: And so, for me, I want to be like, okay, the demand is there.
452 00:40:05.990 ⇒ 00:40:10.809 Uttam Kumaran: But, like, how much is the price? What does it include? How long does it take?
453 00:40:12.150 ⇒ 00:40:16.490 Uttam Kumaran: like, we need to figure those things out, you know? Because then I can go to them and say, hey, oh yeah.
454 00:40:16.640 ⇒ 00:40:22.579 Uttam Kumaran: just awesome timing. We have our… we have a Purse for training module that we love to do here. Here’s everything it comes with.
455 00:40:23.000 ⇒ 00:40:27.140 Uttam Kumaran: It’s, like, 3 meetings, it’s, like, 3 workshops and this for 5 drinks.
456 00:40:28.490 ⇒ 00:40:29.250 Samuel Roberts: Yeah.
457 00:40:29.860 ⇒ 00:40:34.800 Uttam Kumaran: Like, Claris, how do they do this at other clubs? Is this kind of, like, how it works? It’s new service development?
458 00:40:35.060 ⇒ 00:40:45.130 Clarence Stone: So that’s… that’s how EY did it. Pricing is even almost spot on. We charge, like, anywhere from 5 to 12.
459 00:40:45.260 ⇒ 00:41:01.250 Clarence Stone: Depending on whether it’s, like, a single day or a multi-session, but Utham, I think the challenge here is that we don’t have a thick bench. EY was using this… I was selling this at EY because, like, we had people sitting around, right?
460 00:41:01.250 ⇒ 00:41:02.020 Samuel Roberts: Right.
461 00:41:02.200 ⇒ 00:41:08.040 Clarence Stone: And it would just be like, alright, now you have to go plan and teach, right? Because you have extra hours. But…
462 00:41:08.240 ⇒ 00:41:17.670 Clarence Stone: our team’s so efficient, like, I think we have to look at this pricing and say, is this a ROI benefit compared to the other pricing stack?
463 00:41:18.590 ⇒ 00:41:19.620 Clarence Stone: Or, like…
464 00:41:19.620 ⇒ 00:41:20.980 Uttam Kumaran: What do you mean?
465 00:41:21.690 ⇒ 00:41:22.500 Clarence Stone: Like, like.
466 00:41:22.500 ⇒ 00:41:23.510 Uttam Kumaran: By the last part.
467 00:41:23.810 ⇒ 00:41:26.240 Clarence Stone: Like, our team doesn’t have anybody other than Ben.
468 00:41:26.910 ⇒ 00:41:27.500 Samuel Roberts: Yeah.
469 00:41:27.500 ⇒ 00:41:30.319 Clarence Stone: Right, like… So bandwidth in general, right?
470 00:41:30.320 ⇒ 00:41:39.459 Uttam Kumaran: No, no, we… it would be… it would be, like, we would be doing the training until I can basically either go talk to Colin, like, one of our friends who does training, or, like.
471 00:41:39.570 ⇒ 00:41:43.720 Uttam Kumaran: Basically, we’d have to build out training as, like, a service line.
472 00:41:43.980 ⇒ 00:41:47.359 Uttam Kumaran: But we already do a lot of it. We just don’t do it formally.
473 00:41:48.550 ⇒ 00:41:49.100 Clarence Stone: Yeah.
474 00:41:49.100 ⇒ 00:41:50.230 Uttam Kumaran: A lot of our people are.
475 00:41:50.230 ⇒ 00:41:59.670 Clarence Stone: Like, is the ROI going to be enough? Like, how much do we need to charge for it to make sense that we would take a day out of our people’s time?
476 00:42:01.950 ⇒ 00:42:02.990 Uttam Kumaran: I see.
477 00:42:03.540 ⇒ 00:42:04.130 Samuel Roberts: Yeah.
478 00:42:11.160 ⇒ 00:42:17.990 Uttam Kumaran: Yeah… I mean… look, like, how long does it take? Like, it took… it took Pranav…
479 00:42:18.620 ⇒ 00:42:21.559 Uttam Kumaran: An hour to train them on clog code.
480 00:42:21.720 ⇒ 00:42:24.410 Uttam Kumaran: Maybe, like, another 2 hours.
481 00:42:25.200 ⇒ 00:42:31.410 Uttam Kumaran: Before and after. Maybe another… 2 to 5 hours, like, there’s probably, like, 5 hours total.
482 00:42:31.600 ⇒ 00:42:35.670 Uttam Kumaran: to train both of them on cloud code, including, like, all their past descriptions.
483 00:42:36.050 ⇒ 00:42:38.590 Uttam Kumaran: And probably preparing, and then some post-work.
484 00:42:40.980 ⇒ 00:42:45.999 Uttam Kumaran: like… I mean, I think we could have easily sold that for 5 grand.
485 00:42:48.100 ⇒ 00:43:00.669 Clarence Stone: Yeah, I… yeah, Pranav’s situation, I think it makes sense, because it sounds like the team knew, like, how to pick up on the tools. So, I think a lot of it also depends on, like, what is the proficiency of the team we’re about to teach.
486 00:43:01.140 ⇒ 00:43:02.249 Samuel Roberts: Yeah, of course.
487 00:43:02.600 ⇒ 00:43:13.000 Clarence Stone: Like, dude, if they are, like, in an enterprise environment, like, and they don’t use any of these tools, and, like, all of a sudden the company’s like, we have to turn it on for everybody, like, you’re gonna start.
488 00:43:13.000 ⇒ 00:43:13.860 Uttam Kumaran: Yeah, yeah, yeah.
489 00:43:15.050 ⇒ 00:43:18.120 Samuel Roberts: Yeah, these guys were pretty warm to it already with Replit and everything, so…
490 00:43:19.400 ⇒ 00:43:23.430 Uttam Kumaran: So then it’s almost like we have, like, training… tears.
491 00:43:24.500 ⇒ 00:43:27.969 Uttam Kumaran: Like, basically what we did, we ran, like, a single-day workshop.
492 00:43:29.420 ⇒ 00:43:34.079 Uttam Kumaran: just now. But, like, for an enterprise thing, it may be, like, tons and tons. Okay, I see what you mean.
493 00:43:34.590 ⇒ 00:43:35.430 Clarence Stone: Yeah.
494 00:43:35.800 ⇒ 00:43:40.719 Uttam Kumaran: For the thing that EY did, which was, like, 10Gs, like, well, what does that include?
495 00:43:41.260 ⇒ 00:43:44.740 Clarence Stone: So, it started with a half a day
496 00:43:45.030 ⇒ 00:44:03.800 Clarence Stone: like, design thinking session, where it would be, like, an hour and a half of a manager or a senior describing where AI is at, what it’s capable of, and then showing off some of the work that we’ve created, and then spending another hour asking the client, what would you do with AI?
497 00:44:03.920 ⇒ 00:44:09.599 Clarence Stone: Right, and then those use cases then go into the following day, where it’s, like, a full-day session.
498 00:44:09.860 ⇒ 00:44:14.040 Clarence Stone: Explaining how to create agents, and actually building out one of the use cases.
499 00:44:14.620 ⇒ 00:44:23.309 Clarence Stone: Now, these sessions are for business people, right? You don’t know a shit about AI, so it is incredibly time-consuming, because, like.
500 00:44:23.510 ⇒ 00:44:31.600 Clarence Stone: they have no idea what any of this is. They’re, like, normal dudes from the data team, or normal dudes from the tax team, and stuff like that.
501 00:44:33.070 ⇒ 00:44:34.120 Uttam Kumaran: I see.
502 00:44:41.920 ⇒ 00:44:49.200 Clarence Stone: I think, like, I think you still offer it, right? Like, let’s look at the demand and then see, like, who’s interested, right?
503 00:44:49.200 ⇒ 00:44:54.610 Uttam Kumaran: Well, we can start with the first thing, which is, like, have all your team come into, like, a 2-hour block meeting.
504 00:44:55.720 ⇒ 00:44:56.909 Uttam Kumaran: And we’ll train you well.
505 00:44:58.400 ⇒ 00:45:03.799 Uttam Kumaran: Because we’re gonna do this for people, by the way. Like, there’s a bunch of clients that want to learn for sure alongside those.
506 00:45:04.040 ⇒ 00:45:08.829 Uttam Kumaran: So, this is the third time we’ve done it. We did it for Urban Sems, after we train them on cursor.
507 00:45:09.270 ⇒ 00:45:11.860 Uttam Kumaran: I’ve trained internally, so that counts.
508 00:45:12.300 ⇒ 00:45:19.580 Uttam Kumaran: Then we have, like, like, folks at Element want to learn, and… Yeah, a couple others, so…
509 00:45:19.840 ⇒ 00:45:22.909 Uttam Kumaran: Maybe we start with the smallest thing, which is, like, a hot day.
510 00:45:24.910 ⇒ 00:45:25.930 Uttam Kumaran: virtual.
511 00:45:26.500 ⇒ 00:45:27.160 Uttam Kumaran: workshop.
512 00:45:27.160 ⇒ 00:45:42.949 Clarence Stone: I think it works best for existing clients, by the way, because the way it happened at Lilo was perfect, right? Like, in the process of handing off existing work, like, you’re also introducing to them how they can work better with the things that we’ve helped them build.
513 00:45:42.950 ⇒ 00:45:43.550 Samuel Roberts: Yeah.
514 00:45:43.710 ⇒ 00:45:46.209 Clarence Stone: Right, so that’s a really good add-on.
515 00:45:46.800 ⇒ 00:45:49.200 Clarence Stone: That they just, like, make sense.
516 00:45:49.620 ⇒ 00:45:59.670 Clarence Stone: But, like, when, you know, you don’t know an organization, it’s like, we’ll teach you everything about AI. Oh, man, what if we walk in a room with donuts, right? We’re gonna spend all day frustrated.
517 00:46:01.720 ⇒ 00:46:03.220 Uttam Kumaran: I see, okay, okay.
518 00:46:04.750 ⇒ 00:46:07.260 Uttam Kumaran: But dude, I have a good feeling also, like…
519 00:46:07.660 ⇒ 00:46:10.729 Uttam Kumaran: As part of new client engagement, I can tack it on.
520 00:46:11.690 ⇒ 00:46:14.779 Clarence Stone: Yeah, right now, we didn’t price for that separately.
521 00:46:15.250 ⇒ 00:46:15.940 Samuel Roberts: Right.
522 00:46:17.660 ⇒ 00:46:21.090 Uttam Kumaran: Like, I didn’t charge them extra for it, it’s just part of what we promised.
523 00:46:32.770 ⇒ 00:46:41.200 Clarence Stone: Maybe… maybe that’s how the price modeling should be, by the way, dude. Like this one.
524 00:46:41.200 ⇒ 00:46:42.220 Uttam Kumaran: Comes with this.
525 00:46:43.060 ⇒ 00:46:44.950 Clarence Stone: Yeah, I was looking through, like.
526 00:46:46.070 ⇒ 00:47:01.480 Clarence Stone: how construction prices work with my buddy this weekend, and one of the most interesting things is, like, as a policies, like, if they ever ask you, do you also want us to do X, Y, or Z, you just always say no, because they’re gonna overcharge you, like, 4X for that additional fee.
527 00:47:01.480 ⇒ 00:47:02.230 Samuel Roberts: True.
528 00:47:03.920 ⇒ 00:47:15.589 Clarence Stone: It’s like, oh, you want gutters put in. Okay, do you want gutter guards on top of that? That’ll be, you know, a couple hundred bucks more. Well, you just go online and you look at how much gutter guards cost, they’re, like, a buck or two each.
529 00:47:17.080 ⇒ 00:47:32.370 Clarence Stone: So, look, those add-ons end up being the highest margin things that you can tack on. So maybe the process is, like, through the cycle of winning work, right, before you finalize that SOW, let go, like, is there any add-ons that we can just tack on towards the end of this?
530 00:47:34.980 ⇒ 00:47:35.720 Uttam Kumaran: Yeah.
531 00:47:37.950 ⇒ 00:47:40.019 Uttam Kumaran: Okay, yeah, something we’ll have to think about.
532 00:47:40.320 ⇒ 00:47:40.890 Clarence Stone: Yeah.
533 00:47:41.160 ⇒ 00:47:43.570 Uttam Kumaran: Part of it’s… part of it’s,
534 00:47:44.330 ⇒ 00:47:47.739 Uttam Kumaran: Like, my gut instinct is because of where we are.
535 00:47:47.860 ⇒ 00:47:51.129 Uttam Kumaran: Most of these services are just going to be…
536 00:47:51.400 ⇒ 00:47:55.730 Uttam Kumaran: Sort of allow us to win work, because it’s like, we do all these things, so you don’t…
537 00:47:55.910 ⇒ 00:48:00.690 Uttam Kumaran: Like, don’t worry, like, when we get to the point at which you need this, you’ll… you can come to us.
538 00:48:01.330 ⇒ 00:48:04.739 Uttam Kumaran: Less relevant about, like.
539 00:48:04.960 ⇒ 00:48:11.269 Uttam Kumaran: becoming a training company. Like, I don’t want to go do training for people that aren’t gonna also buy our development services.
540 00:48:11.950 ⇒ 00:48:17.820 Uttam Kumaran: It’s more like the folks that buy our development services, they should be like, oh yeah, Rateforge offers, like, hella other things, so…
541 00:48:18.450 ⇒ 00:48:24.339 Clarence Stone: Yeah, like, seamless developer handoff, with training included for 5 grand.
542 00:48:28.290 ⇒ 00:48:30.130 Uttam Kumaran: That seems pretty cheap, but yeah.
543 00:48:30.150 ⇒ 00:48:32.580 Clarence Stone: Yeah, I mean, mainly price, but like…
544 00:48:32.920 ⇒ 00:48:34.549 Clarence Stone: You have to add that, you know.
545 00:48:34.550 ⇒ 00:48:35.480 Uttam Kumaran: I know, I know.
546 00:48:35.480 ⇒ 00:48:41.000 Clarence Stone: So who’s teaching you everything, or do you want us to train your people to also do it, right?
547 00:48:43.830 ⇒ 00:48:45.810 Uttam Kumaran: Yeah, or what we do is, like.
548 00:48:46.140 ⇒ 00:48:55.410 Uttam Kumaran: we have sort of a hooked training workshop, and then it’s like, if you want us to do this with, like… but this only covers, like, 3 people. Like, if we need to do 10 people.
549 00:48:55.890 ⇒ 00:48:59.719 Uttam Kumaran: And, like, make sure that it gets adopted, it’s, like, a whole training SOW.
550 00:49:03.690 ⇒ 00:49:04.540 Clarence Stone: Yep.
551 00:49:10.430 ⇒ 00:49:20.289 Clarence Stone: Which opens up the broader conversations of, like, you know, something for us to start to think about is, do we shift to a MSA-type structure?
552 00:49:21.390 ⇒ 00:49:22.439 Uttam Kumaran: We are. We are.
553 00:49:22.460 ⇒ 00:49:26.019 Clarence Stone: Yeah, pack on these SOWs pretty easy after that point.
554 00:49:26.020 ⇒ 00:49:27.640 Uttam Kumaran: No, we are moving towards that.
555 00:49:28.490 ⇒ 00:49:30.300 Uttam Kumaran: Like, probably within the next month.
556 00:49:31.270 ⇒ 00:49:33.160 Samuel Roberts: What is an MSA chart structure? What is that?
557 00:49:35.380 ⇒ 00:49:35.890 Clarence Stone: So.
558 00:49:35.890 ⇒ 00:49:37.949 Uttam Kumaran: Master… yeah, go ahead, go on.
559 00:49:38.630 ⇒ 00:49:54.249 Clarence Stone: So Sam, like, we’ve been doing just SOWs, right, which just cover the same work and everything that we’re gonna agree to building. But larger organizations, it just takes a long time to onboard vendors, so you’ll…
560 00:49:54.250 ⇒ 00:50:01.130 Clarence Stone: start with a Master Services Agreement first, which outlines, like, how you’re going to work with Brainforge.
561 00:50:01.170 ⇒ 00:50:05.220 Clarence Stone: Right? Minus the terms of, like, the work we’re about to do, which would be in that.
562 00:50:05.220 ⇒ 00:50:06.100 Samuel Roberts: Right.
563 00:50:06.460 ⇒ 00:50:07.079 Clarence Stone: That makes sense.
564 00:50:07.080 ⇒ 00:50:07.510 Samuel Roberts: Yes, yeah.
565 00:50:07.630 ⇒ 00:50:10.249 Clarence Stone: piling on SOWs non-stop.
566 00:50:10.420 ⇒ 00:50:11.649 Samuel Roberts: Right, right.
567 00:50:12.180 ⇒ 00:50:15.130 Samuel Roberts: Okay, cool, yeah. Makes sense.
568 00:50:19.510 ⇒ 00:50:29.050 Uttam Kumaran: Okay. Cool, guys. I think this is good progress today. I’m gonna… I’m just gonna go try to jump-catch the end of the sales meeting, and, like, I’ll let them know what we’ve talked about.
569 00:50:29.170 ⇒ 00:50:34.810 Uttam Kumaran: But I think this is a good way for us to use this sort of, like, SL regroup.
570 00:50:35.190 ⇒ 00:50:37.409 Uttam Kumaran: You know, I think, like.
571 00:50:37.570 ⇒ 00:50:49.839 Uttam Kumaran: Sam, in particular, I think Awash has sort of, like, a full plate of, like, you know, 6 or 7 clients he’s sort of, like, looking over. I think as your time starts to go that way, too, I think we can… we’ll be able to discuss more, because
572 00:50:50.250 ⇒ 00:51:00.499 Uttam Kumaran: you know, I think… I think we’ll end up with, like, probably, like, another one or two AI clients, but you’ll be kind of overseeing all of those, and I think we’ll discuss sort of, like, what the challenges are.
573 00:51:00.780 ⇒ 00:51:07.729 Uttam Kumaran: And then Shashu is like, yeah, he’s here for you guys, so… I think I really want you all to lean on him for anything operationally.
574 00:51:07.920 ⇒ 00:51:10.570 Uttam Kumaran: That you guys are having issues with.
575 00:51:10.940 ⇒ 00:51:13.549 Uttam Kumaran: I want him to play, like, sort of ultimate backup.
576 00:51:14.240 ⇒ 00:51:18.830 Uttam Kumaran: And then I’m, like, ultimate, ultimate backup on everything, you know? Sounds good.
577 00:51:19.010 ⇒ 00:51:26.629 Uttam Kumaran: So I’m sort of hoping that she’s able to see every role and sort of start their own process development across most things, so…
578 00:51:28.640 ⇒ 00:51:29.260 Awaish Kumar: Okay.
579 00:51:31.680 ⇒ 00:51:33.919 Uttam Kumaran: Okay, I’m gonna go try to catch down with a sales manager.
580 00:51:34.610 ⇒ 00:51:35.200 Samuel Roberts: Right.
581 00:51:35.430 ⇒ 00:51:36.840 Samuel Roberts: Bye-bye. Talk to you later.
582 00:51:36.840 ⇒ 00:51:37.730 Uttam Kumaran: Thank you, guys.
583 00:51:37.880 ⇒ 00:51:38.600 Uttam Kumaran: Alright.
584 00:51:39.430 ⇒ 00:51:40.590 Clarence Stone: Awesome, thanks guys.
585 00:51:41.440 ⇒ 00:51:42.080 Uttam Kumaran: Thank you.