Meeting Title: Project Review - Andi Date: 2026-04-07 Meeting participants: Brylle Girang, Pranav, Uttam Kumaran
WEBVTT
1 00:07:42.730 ⇒ 00:07:43.720 Brylle Girang: Hey!
2 00:07:45.360 ⇒ 00:07:46.560 Pranav: How’s it going, B?
3 00:07:46.990 ⇒ 00:07:47.920 Brylle Girang: Good!
4 00:07:49.300 ⇒ 00:07:52.349 Brylle Girang: cursors down, so…
5 00:07:52.350 ⇒ 00:07:52.959 Pranav: Oh, shoot.
6 00:07:53.460 ⇒ 00:07:55.950 Pranav: Yeah, I was seeing that,
7 00:07:57.320 ⇒ 00:08:00.130 Pranav: I think, Utam just said it’s back up, right?
8 00:08:01.610 ⇒ 00:08:06.359 Brylle Girang: I’m actually trying it out now. Oh yeah, it’s working! Good.
9 00:08:07.950 ⇒ 00:08:09.240 Pranav: Nice, nice, nice.
10 00:08:17.040 ⇒ 00:08:18.350 Brylle Girang: So this is the first step.
11 00:08:18.660 ⇒ 00:08:19.900 Pranav: Book Defense?
12 00:08:20.420 ⇒ 00:08:21.140 Brylle Girang: Sorry?
13 00:08:21.540 ⇒ 00:08:23.380 Pranav: This is the first project defense.
14 00:08:23.380 ⇒ 00:08:30.839 Brylle Girang: Yes, this is the first project offense. We’re going to go back to our college days for this.
15 00:08:30.840 ⇒ 00:08:41.229 Pranav: Yeah, yeah, I never did it in college, but I have, like, friends that are doing, like, their PhDs and stuff, and so they’ll talk about how this is, like, the most stressful time, you know, for them.
16 00:08:41.510 ⇒ 00:08:46.200 Brylle Girang: Oh, gotcha! So, it’s not, like, a standard to have, like, physics?
17 00:08:48.410 ⇒ 00:08:53.049 Pranav: Not for undergrad. It’s, some master’s programs do, but it’s very… it’s like…
18 00:08:53.420 ⇒ 00:08:56.160 Pranav: for PhDs, you have to have a thesis. Yeah.
19 00:08:56.160 ⇒ 00:08:56.610 Brylle Girang: Nope.
20 00:08:57.250 ⇒ 00:09:11.410 Pranav: Yeah, so I think this kind of came from… I’m not sure exactly where Utam came up with this, or kind of got the idea for this. But yeah, the basis is kind of, like, PhD programs, like, they’ll have…
21 00:09:11.900 ⇒ 00:09:13.910 Pranav: You’ll have, like, your…
22 00:09:15.540 ⇒ 00:09:24.850 Pranav: it’s like your proposal, like, 2 years in, to kind of, like, say, hey, this is what I want to do. So this is more so… it’s less, like, so, like, a…
23 00:09:24.980 ⇒ 00:09:39.199 Pranav: yeah, thesis defense is one way to put it. I think it’s more so called, like, in, like, in academia, like, a proposal. And then, yeah, basically just kind of getting drilled to make sure, like, hey, we’re gonna invest the next 4 years into you, you know?
24 00:09:39.590 ⇒ 00:09:40.230 Pranav: Yeah.
25 00:09:40.230 ⇒ 00:09:46.970 Brylle Girang: Yeah, yeah, yeah. I think this is more of a Shark Tank pitch, as I’ve been mentioning Yeah.
26 00:09:46.970 ⇒ 00:09:50.470 Pranav: Yeah, I guess that’s another way to put it, too, yeah.
27 00:09:50.740 ⇒ 00:10:00.209 Brylle Girang: But that’s cool, because here in the Philippines, like, faces, defenses are, like, a standard, even when you are in the undergrad.
28 00:10:00.440 ⇒ 00:10:06.110 Brylle Girang: Well, yeah, it’s not… It’s cool seeing the differences.
29 00:10:06.870 ⇒ 00:10:09.150 Pranav: Yeah, yeah, totally.
30 00:10:10.600 ⇒ 00:10:13.639 Pranav: So did you, do your undergrad in the Philippines?
31 00:10:14.030 ⇒ 00:10:17.549 Brylle Girang: Yeah, yeah, I am a graduate of electronics engineering.
32 00:10:17.890 ⇒ 00:10:18.230 Pranav: Okay.
33 00:10:18.460 ⇒ 00:10:21.340 Brylle Girang: I just graduated, like, 2 years ago.
34 00:10:21.680 ⇒ 00:10:25.979 Brylle Girang: Nice. I was a working student, I was already working when I was studying.
35 00:10:26.100 ⇒ 00:10:37.110 Brylle Girang: But here in the pH, it’s really, really common, to, like, work when you’re studying, because the economy is just that bad, but…
36 00:10:37.110 ⇒ 00:10:37.570 Pranav: Hmm.
37 00:10:37.570 ⇒ 00:10:54.629 Brylle Girang: when we were studying, it’s also really common to not disclose, like, your educational progress with the company, so I worked with my previous company, they didn’t even know that I was studying, and then I just graduated.
38 00:10:55.100 ⇒ 00:10:57.079 Pranav: Oh, no way, that’s funny.
39 00:10:57.550 ⇒ 00:10:58.440 Brylle Girang: Yeah, it is.
40 00:10:58.440 ⇒ 00:11:01.089 Pranav: Yeah. Yeah, even here, like…
41 00:11:01.490 ⇒ 00:11:13.840 Pranav: I think a lot of people, like, and me included, like, I won’t put, like, my graduation date on LinkedIn. I’ll just put, like, you know… I think it’s just, like, you’re just at a disadvantage when you’re younger in your career, you know?
42 00:11:13.840 ⇒ 00:11:14.190 Brylle Girang: Yeah.
43 00:11:14.760 ⇒ 00:11:18.239 Pranav: You’ll just kind of be put into a box,
44 00:11:18.510 ⇒ 00:11:26.789 Pranav: So, yeah, I’ll just try to, you know… and I already look older for my age, so I think that works in my benefit here. But…
45 00:11:27.300 ⇒ 00:11:35.859 Pranav: Yeah, so, like, I just won’t… I used to have, like, you know, graduated in 2021 in my… in my bio, but then I removed it, because I was just like…
46 00:11:36.420 ⇒ 00:11:38.980 Pranav: You know, I just don’t want that. Yeah.
47 00:11:39.220 ⇒ 00:11:52.780 Brylle Girang: Yeah, yeah, it’s crazy, right? I’m pretty sure that we have had experiences where, you know, the applicants are being, in a way… how do you call this? Discriminated based on the experience of their age.
48 00:11:53.120 ⇒ 00:11:55.440 Pranav: 100%, that’s definitely happening, yeah.
49 00:11:56.050 ⇒ 00:11:57.689 Brylle Girang: Hey, what’s up? Hey, guys.
50 00:11:58.700 ⇒ 00:11:59.470 Uttam Kumaran: How are ya?
51 00:11:59.950 ⇒ 00:12:04.489 Brylle Girang: Yeah, we were just talking about the thesis defense experiences that we had.
52 00:12:04.750 ⇒ 00:12:06.290 Brylle Girang: At our college.
53 00:12:06.960 ⇒ 00:12:09.429 Uttam Kumaran: Oh, really? What was it like?
54 00:12:10.690 ⇒ 00:12:16.260 Pranav: I had no experience, but I think B had, like, some experience, because he did a thesis, in college.
55 00:12:16.710 ⇒ 00:12:19.319 Uttam Kumaran: Oh, okay. I’ve never done one.
56 00:12:19.470 ⇒ 00:12:37.969 Uttam Kumaran: I think I would like to do one now. I used to be a very non-confident, shy person my whole life, so, like, if I… back then, there was no fucking way you could have convinced me to do a thesis. I was like, I didn’t even want to do any book report. Now, I’m like… I’m like, alright, if it helps the company, whatever.
57 00:12:37.970 ⇒ 00:12:40.540 Uttam Kumaran: I’ll do a thesis defense.
58 00:12:42.590 ⇒ 00:12:43.420 Pranav: Yeah.
59 00:12:45.180 ⇒ 00:12:54.809 Brylle Girang: So we were also talking about how this would go. I said that I’m imagining that this will be more of a shark tongue pitch, and the thesis defense…
60 00:12:55.170 ⇒ 00:12:57.340 Brylle Girang: So… Let’s get it!
61 00:12:58.160 ⇒ 00:13:16.029 Uttam Kumaran: No, I’m also interested in how this is gonna go, like, I think, you know, I’m really in my role now on head of delivery, like, setting the stage for, like, where whoever’s gonna fit into this role, like, sits and supports. So it’s even interesting for me to start thinking about, like, okay, where…
62 00:13:16.290 ⇒ 00:13:26.139 Uttam Kumaran: like, what questions to ask. But yeah, I mean, I think we… I think this… today is just gonna be, like, a little bit of, like, a test case of, like, how this process is gonna work.
63 00:13:26.310 ⇒ 00:13:43.610 Uttam Kumaran: Yeah, but I think having me and Bea here is gonna be helpful. So yeah, I mean, I think let’s just, like, let’s get started, and I’ll sort of just, like, riff on questions, and you let me know. I mean, I think a good place to start is, like, I think sort of the question that I probably will ask everybody is, like.
64 00:13:43.670 ⇒ 00:13:50.479 Uttam Kumaran: yeah, like, tell me how ABC makes money, and then also give me a sense of, like.
65 00:13:50.760 ⇒ 00:13:56.070 Uttam Kumaran: What some of the challenges that… that we’re trying to solve for them are.
66 00:13:56.920 ⇒ 00:13:58.720 Pranav: Yeah, sure, so, like…
67 00:13:58.840 ⇒ 00:14:16.840 Pranav: what does ABC do, right? And then how do they make money? So what do they do first is, like, they provide these home and commercial, like, services, like, property care, as well as just, like, maintenance services. And their whole thing is, like, being a one-stop shop for all this stuff.
68 00:14:16.970 ⇒ 00:14:34.879 Pranav: Specifically, like, what we’re doing for them, too, is we’re helping with the customer service side, which is their whole… that’s where all the deals are coming through. For them to make revenue, like, this needs to be… it’s really dependent on this customer service side of things being… working very well.
69 00:14:35.330 ⇒ 00:14:40.660 Pranav: Now… Yeah, so, I mean, I can go into further depth there, which is why I feel.
70 00:14:40.660 ⇒ 00:14:45.360 Uttam Kumaran: Yeah, like, what, what, yeah, like, what is the struggle right now, and, like, why…
71 00:14:45.550 ⇒ 00:14:50.639 Uttam Kumaran: why do you think they’re paying us to help solve that? Like, what, what, like, yeah, if you could describe that.
72 00:14:51.400 ⇒ 00:14:58.200 Pranav: Yeah, so I think they’re seeing this as, like, a major kind of bottleneck for their business right now.
73 00:14:58.200 ⇒ 00:15:13.689 Pranav: Because based on the high-level analytics that they’re… that they’re capturing right now, is that they’re noticing cancellations, they’re noticing large hold times, and then, you know, they work in person too, right? So they’re seeing, and they’re also getting feedback from,
74 00:15:13.690 ⇒ 00:15:24.079 Pranav: The people managing, like, each of these individual department cohorts of, hey, these, like, we see people just, like, messaging in, like, kind of…
75 00:15:24.160 ⇒ 00:15:29.570 Pranav: in panic about, like, getting certain information. So there’s that…
76 00:15:29.770 ⇒ 00:15:47.180 Pranav: real-time, like, experience that they’ve seen of, like, hey, people are, like, seem like they’re kind of a mess, jumping from document to document, just searching for the latest information. And then also the analytics support that as well, right? With, like, the large hold times that they’re noticing, cancellations as well. So…
77 00:15:47.250 ⇒ 00:15:57.960 Pranav: they’ve definitely captured, and I think captured correctly, that there is a lot of room for improvement here. And it’s just money kind of just sitting there waiting for them.
78 00:15:59.990 ⇒ 00:16:03.690 Uttam Kumaran: Cool. Like, okay, I think it’s clear, so tell me, like, what…
79 00:16:04.080 ⇒ 00:16:11.950 Uttam Kumaran: you know, let’s say I’m the CEO of ABC, who we happened to meet recently. Like, if he was, like.
80 00:16:12.670 ⇒ 00:16:21.579 Uttam Kumaran: okay, I’m about to hand you guys $50,000, like, what am I getting… what am I getting in return? Not only what am I getting in terms of
81 00:16:21.870 ⇒ 00:16:29.369 Uttam Kumaran: Like, code or whatever, but, like, what… in addition to that, what outcomes can I expect?
82 00:16:30.100 ⇒ 00:16:31.560 Pranav: Yeah, I think…
83 00:16:31.780 ⇒ 00:16:50.540 Pranav: with, like, 50K, or just kind of, like, enough money for us to, like, completely fix this problem, right? We can definitely make these CSRs much more tech-enabled, and also providing to, like, the managers, like Janice, like Yvette, certain analysis that can then
84 00:16:50.610 ⇒ 00:16:52.930 Pranav: Be driving their…
85 00:16:52.970 ⇒ 00:17:08.239 Pranav: like, specific progress on a per-CSR basis. All of that data exists, and they’re actually also… they’re actually all already capturing it, so that’s, like, one less step for us. That analysis portion of thing… things is just not happening.
86 00:17:08.240 ⇒ 00:17:18.439 Pranav: And so, what does that mean, actually, right? Like, so, there are these transcripts that are just sitting there, that are just waiting to be investigated.
87 00:17:19.270 ⇒ 00:17:35.189 Pranav: basically what we can do, and what we’re doing as part of, like, our first project for Q2, is that we’re going to be extracting the intent from all of the customers that are calling the CSRs. And so what that’s going to help us with is assessing, like, okay.
88 00:17:35.490 ⇒ 00:17:48.739 Pranav: we don’t need to depend on just conversations with just Yvette, Janice, to understand, okay, what are our customers asking the CSRs? We have the data in front of us, we can hear it directly from the customers themselves.
89 00:17:49.030 ⇒ 00:18:05.819 Pranav: What that’ll help us do is then we can… there’s nothing lost in translation, there’s nothing… we can go into, like, the very nitty-gritty about, like, these are the exact questions that are being asked, and then it’ll make us… it’ll allow us to understand what are the gaps in the knowledge base that we’ve created for them.
90 00:18:06.730 ⇒ 00:18:14.039 Pranav: Secondly, like, it also kind of gives us an understanding of, like, the amount of…
91 00:18:14.600 ⇒ 00:18:32.920 Pranav: like, usage that Andy should be able to support, right? Right now, we know that it’s being underutilized, and we’ve been… we know that for a fact, because it’s just not getting that much utilization based on how much business that they’re driving. However, we haven’t defined, like, what that peak is, right? How do we know, like, it’s getting
92 00:18:33.270 ⇒ 00:18:37.309 Pranav: perfectly utilized, or it’s, like, properly utilized at this point.
93 00:18:37.310 ⇒ 00:18:40.729 Uttam Kumaran: So can we drill into that? Like, you know, we’ve been working with…
94 00:18:41.290 ⇒ 00:18:43.830 Uttam Kumaran: we’ve been working with ABC for a while.
95 00:18:43.970 ⇒ 00:18:46.799 Uttam Kumaran: I think hearing that, like, we haven’t…
96 00:18:47.140 ⇒ 00:18:56.439 Uttam Kumaran: folks are still not leveraging the product is, like, okay, what… I’m sort of interested in, like, what have we tried, and, like, how are we fixing that?
97 00:18:57.880 ⇒ 00:18:58.320 Pranav: Yeah.
98 00:18:58.320 ⇒ 00:19:05.340 Uttam Kumaran: you know, I think we have confidence that it’s working. I think everybody on their side says it’s working. So what’s the gap right now?
99 00:19:05.480 ⇒ 00:19:10.110 Uttam Kumaran: From… from people, from… from actually getting, like, total adoption.
100 00:19:11.070 ⇒ 00:19:16.879 Pranav: Yeah, so, I think a lot of these people, they’re not super,
101 00:19:18.000 ⇒ 00:19:30.320 Pranav: it’s… and I think it’s like anybody, if they’re using a product that failed them in the past, and they know how to get the solution, they’re gonna go in that direction, right? Like, hey, I know this is working for me, and it’s like.
102 00:19:30.560 ⇒ 00:19:45.289 Pranav: it’s something that is critical, because they’re on the phone, and they don’t want to be just testing something that might take 30 seconds of their time, and it might not end up going nowhere. Especially if it’s failed them in the past, right? So I think it’s a little bit of…
103 00:19:45.340 ⇒ 00:20:02.920 Pranav: breaking that muscle as well. People are kind of just… in that moment, they’re gonna do what’s most convenient to them. And so, at this point, for a lot of the CSRs, it’s been convenient for them to just go into the central dock, and then just look for info… and then they know where the information is in the central dock.
104 00:20:02.970 ⇒ 00:20:10.100 Pranav: And so they don’t even go through ANDI, because maybe in the past they went through ANDI early days, and it was failing for them.
105 00:20:10.240 ⇒ 00:20:15.139 Pranav: now they just bypass it entirely, so I don’t even know if Andy can give them the right answer.
106 00:20:15.280 ⇒ 00:20:27.360 Pranav: that’s what I… that’s a big reason for why, usage is low. It’s also the people that are driving usage, or trying to get people at ABC to use Andy,
107 00:20:27.690 ⇒ 00:20:34.620 Pranav: are the trainers. And so that means we need to get the… the buy-in from the trainers as well. So…
108 00:20:34.910 ⇒ 00:20:49.189 Pranav: the trainers are the ones that are gonna do a little bit more of, like, the edge case checking, and they’re the kind of the spokesperson for Andy, so getting them on board, too, is really gonna drive usage up, which…
109 00:20:49.460 ⇒ 00:21:03.739 Pranav: we’re doing, but I think, based on, like, what I’ve researched, what I’ve heard from Amber, what I’ve also heard from Janiece and Yvette, is that there’s been a period where, like, basic things were not working, there was down times on Andy, and that really, like.
110 00:21:03.890 ⇒ 00:21:10.090 Pranav: that really hurt, kind of, the case for using Andy. Yeah.
111 00:21:10.370 ⇒ 00:21:21.209 Uttam Kumaran: Okay. And you feel like we’ve… we have a path towards moving, like, past… I think even just harping on, like, those issues that you called out, you feel like we have enough…
112 00:21:21.540 ⇒ 00:21:37.070 Uttam Kumaran: to move past that, like, you know, if you were to say the opposite, okay, the system was unstable, is the system stable? Like, are people confident? People weren’t confident, the data was inaccurate, everything is accurate. Like, do you feel like you’re able to check off all those boxes?
113 00:21:38.410 ⇒ 00:21:40.299 Pranav: Yeah, yeah, so I think…
114 00:21:41.000 ⇒ 00:21:49.780 Pranav: I feel much more confident in the system now, but then also the main purpose of these next… this next quarter is to make it as…
115 00:21:50.120 ⇒ 00:21:56.999 Pranav: accurate as possible, and yeah, how we’re doing that is with transcripts. So,
116 00:21:57.120 ⇒ 00:22:08.859 Pranav: at the end of the day, these documents… I don’t feel confident that the central doc is fully encompassing everything that is needed, for the CSRs, and in that… and then…
117 00:22:08.860 ⇒ 00:22:19.999 Pranav: by… as a product of that, Andy’s not going to be able to answer every single question that the CSRs need. And that’s just because we haven’t leveraged transcripts. We’ve just kind of been going based on what…
118 00:22:20.210 ⇒ 00:22:30.230 Pranav: Just based on thumbs up and thumbs-down feedback. And then from the initial creation of the central doc, which is just, like, yeah, people throwing documents together.
119 00:22:31.170 ⇒ 00:22:33.649 Pranav: And so, yeah, I think in this next…
120 00:22:33.950 ⇒ 00:22:46.960 Pranav: like, 2 months, we’re going to be able to really find the gaps of, like, where the central docs are not fully answering the questions that they should be answering, and then we can add that information in there.
121 00:22:47.920 ⇒ 00:23:04.519 Uttam Kumaran: And are you, like, how are we doing on the data side? Like, I feel like a lot of these issues, right, we should be catching them before they hit our desk, like, anecdotally, right? Inaccurate data, downtime, like, what is the plan for us to actually get ahead of that?
122 00:23:04.760 ⇒ 00:23:19.230 Uttam Kumaran: And, you know, seeing that, really, the reason why we haven’t gotten adoption is, like, people are nervous about the system health, like, how are we the first… gonna be the first people to, like, be like, hey, system is struggling right now, versus them alerting us?
123 00:23:19.980 ⇒ 00:23:21.759 Pranav: Yeah,
124 00:23:22.730 ⇒ 00:23:39.459 Pranav: what we’re… I think moving to GCP was a big thing, because it’s a much more stable environment. With N8N, we were just seeing outages, we were seeing updates to our flow that weren’t even being made by us, just based on module changes that were happening on N8N’s side.
125 00:23:39.460 ⇒ 00:23:43.079 Pranav: And so now we’re definitely much more in control of our own application.
126 00:23:44.790 ⇒ 00:23:51.940 Pranav: Also, a big issue before wasn’t necessarily just downtime, but it was also just execution time. We were noticing just, like.
127 00:23:52.780 ⇒ 00:23:56.400 Pranav: like, P95 times would be, like, above 20 seconds.
128 00:23:56.830 ⇒ 00:24:02.960 Pranav: now we’re seeing, like, P80, P90, P95 times are all under 5 seconds.
129 00:24:03.270 ⇒ 00:24:03.680 Uttam Kumaran: Okay.
130 00:24:03.680 ⇒ 00:24:20.480 Pranav: And that’s a huge win. Yeah, so I did mention, like, downtimes being one thing before, and I talked to Sam about that as well, to talk about, like, hey, how are we notified? Maybe we do certain polling to, like, assess the health of our backend systems.
131 00:24:20.570 ⇒ 00:24:25.330 Pranav: that’s something that… that’s something that we’ll implement as well.
132 00:24:25.660 ⇒ 00:24:41.340 Pranav: But this execution time thing, which was, I think, the major driver for, like, decreased usage, and, like, not getting adoption from ABC, has now been completely fixed. Like, like, right now, when I look at,
133 00:24:41.390 ⇒ 00:24:51.260 Pranav: like, last week when I was, like, comparing, you know, it was our first rollout of the new application compared to, like, the N8N application, yeah, we’re down over 50% in execution time.
134 00:24:52.070 ⇒ 00:24:53.040 Uttam Kumaran: Okay, cool.
135 00:24:53.230 ⇒ 00:25:07.999 Uttam Kumaran: Alright, that makes sense. So walk me through this, walk me through the project plan. So I looked at it briefly. Tell me about, like, how… or give me a sense of, like, why we came up with these…
136 00:25:08.120 ⇒ 00:25:11.309 Uttam Kumaran: Like, revenue tiers, or how you’re thinking about that?
137 00:25:13.010 ⇒ 00:25:18.169 Pranav: Yeah, so… The revenue tiers,
138 00:25:18.640 ⇒ 00:25:22.679 Pranav: is kind of something I walked into, right? Okay.
139 00:25:23.530 ⇒ 00:25:24.690 Pranav: So…
140 00:25:25.270 ⇒ 00:25:35.349 Pranav: not that… I mean, I do kind of like it, you know, we’ve had the same North Star, as, like, the client, so it’s fun in that way.
141 00:25:35.600 ⇒ 00:25:40.249 Pranav: And… It really allows us to, like, always have…
142 00:25:40.560 ⇒ 00:25:49.130 Pranav: in the… whenever we’re making a decision, like, we have to think about it from the lens of, is this going to increase usage? Which is…
143 00:25:49.420 ⇒ 00:26:03.660 Pranav: Which is, I do like thinking in that way, because that’s exactly how Yvette and Janiece are thinking as well. And so, for both of these projects, I feel very confident that they’re going to increase usage.
144 00:26:04.680 ⇒ 00:26:17.730 Pranav: Transcripts being one, is that, currently the type of feedback that Janiece can give to trainers is very high level, because there’s no data that’s really driving,
145 00:26:17.980 ⇒ 00:26:28.609 Pranav: her conversation with the trainers, other than the fact of the breakdown of usage per department. So she sees it, like, lowering in the last week, she’s just like, hey, why did it go down?
146 00:26:29.240 ⇒ 00:26:32.410 Pranav: But that’s not… that’s not really actionable, right? Like…
147 00:26:33.030 ⇒ 00:26:49.990 Pranav: like, the trainers aren’t getting feedback of, like, okay, why aren’t they using it? And so with our transcripts Initiative, department-based insights, the whole idea is that we can give actionable advice on a week-to-week basis on, hey, where were the CSRs using Andy?
148 00:26:49.990 ⇒ 00:26:57.020 Pranav: where were they not using ANDI, and ANDI could have been used. That’s what’s going to be most useful for the CSRs.
149 00:26:57.100 ⇒ 00:27:08.970 Pranav: For us, internally, I think it’s really gonna open the floodgates for so many different, like, expansion opportunities. One being is, okay, what is our ceiling with transcripts? Because…
150 00:27:09.340 ⇒ 00:27:25.700 Pranav: we can’t be asking for usage to be, like, 100K if, like, the type of questions are only going to be, like, there’s only going to be, like, 50K questions per month, right? Yeah. So then, we shouldn’t have a goal of 100K, like, a request per month. So that’s one thing. We can kind of, like.
151 00:27:25.800 ⇒ 00:27:32.640 Pranav: start having, like, a clearer picture of, like, hey, we should be able to get to this point, given, like.
152 00:27:32.980 ⇒ 00:27:36.989 Pranav: like, doing X, Y, and Z, like, initiative.
153 00:27:37.500 ⇒ 00:27:48.379 Pranav: Another thing, too, is, like, we’re gonna be able to analyze gaps. Like, there’s probably areas where, like, even if they asked Andy these questions, they’re not doing it currently, but they could have.
154 00:27:48.380 ⇒ 00:28:08.740 Pranav: Andy is not going to give them the right answer. And so, what we’re doing as part of the transcripts, or the department-based insights, is that we’re going to give a report to each one of the trainers of 100 questions, 100 categories, I would say, and maybe we’ll have, like, a specific question tied to each one of those categories.
155 00:28:08.740 ⇒ 00:28:10.520 Pranav: of… hey, like.
156 00:28:10.690 ⇒ 00:28:20.079 Pranav: how does this… this is what Andy answered. It has not been verified by human feedback, so, like, a lot of the stuff we can verify based on thumbs up or thumbs down feedback.
157 00:28:20.420 ⇒ 00:28:32.939 Pranav: And so, the trainer’s just having, like, 100 questions in front of them, and we can do this on a weekly basis, that’s really going to make the central doc and Andy much more accurate.
158 00:28:34.710 ⇒ 00:28:38.720 Uttam Kumaran: I think one question I had here was, like,
159 00:28:39.200 ⇒ 00:28:42.060 Uttam Kumaran: I feel good about the milestones.
160 00:28:42.250 ⇒ 00:28:46.690 Uttam Kumaran: I also feel good about, like, you’re limiting this to 20 hours a week.
161 00:28:46.890 ⇒ 00:28:52.270 Uttam Kumaran: I’m just, like, I think the 20 hours… I think this is where, like, one…
162 00:28:52.680 ⇒ 00:29:07.990 Uttam Kumaran: And we’ll do some feedback at the end, but I totally want you to have a stronger perspective on the revenue side. Like, yes, you walked into this, and yes, like, I kind of set this up, but, like, you need to be able to defend why this is the way it is.
163 00:29:08.200 ⇒ 00:29:20.669 Uttam Kumaran: So that could be partly, like, okay, looking… looking… working with me on, like, why did we set this up? Like, how did we even arrive? Because I have all the calculations on why we arrived at, like, 4 bucks, 2 bucks.
164 00:29:20.680 ⇒ 00:29:30.989 Uttam Kumaran: So, I want you to be able to do that, so that’s one piece there. Second piece on 20 hours, I think what’s… what would be helpful to also see here is, like, I feel like we…
165 00:29:31.170 ⇒ 00:29:33.209 Uttam Kumaran: Are kind of averaging, like.
166 00:29:33.910 ⇒ 00:29:45.000 Uttam Kumaran: maybe, like, 50 hours right now, right? And so, my concern is… this is a huge decrease, and…
167 00:29:45.280 ⇒ 00:29:46.100 Uttam Kumaran: like.
168 00:29:46.270 ⇒ 00:29:53.809 Uttam Kumaran: I’m, like, I love seeing less time going to this project, but I want to know, like, how you’re, like.
169 00:29:54.620 ⇒ 00:30:03.630 Uttam Kumaran: it doesn’t seem like you’re actually doing less work, right? So, I want to understand how you’re getting from, like, 40, 50 hours a week.
170 00:30:03.730 ⇒ 00:30:19.370 Uttam Kumaran: right, to this 20 hours, and, like, what mechanisms you’re using to do that. You know, some common mechanisms could be, okay, we’re using AI a lot more, okay, like, generally, tickets are laid out so people aren’t just, like.
171 00:30:19.790 ⇒ 00:30:26.090 Uttam Kumaran: waiting on things. I have a deep partnership with Sam, but I want to see, like, kind of something around…
172 00:30:26.820 ⇒ 00:30:32.250 Uttam Kumaran: How we got… how we’re gonna get from 50 to 20 hours maintaining the same pace.
173 00:30:32.600 ⇒ 00:30:35.980 Pranav: Yeah, I think, I mean, sorry, go ahead.
174 00:30:36.540 ⇒ 00:30:42.170 Uttam Kumaran: Yeah, I’m just gonna give a couple things, then we can go into there. So, on the milestone side.
175 00:30:42.400 ⇒ 00:30:46.280 Uttam Kumaran: I feel pretty… Good.
176 00:30:46.430 ⇒ 00:30:51.449 Uttam Kumaran: I think the only pieces I saw in here that there is,
177 00:30:51.830 ⇒ 00:30:54.619 Uttam Kumaran: Something around, like, daily memos.
178 00:30:54.930 ⇒ 00:31:01.229 Uttam Kumaran: And I just, like, you know, on step 8 in the central doc, you said build daily batch and memo.
179 00:31:01.470 ⇒ 00:31:07.460 Uttam Kumaran: I know there’s, like, some daily and weekly processes, some manual, some not manual. I just wanted to be really clear, like.
180 00:31:08.030 ⇒ 00:31:12.459 Uttam Kumaran: What we’re… what they’re gonna… like, what the touchpoints are with the client.
181 00:31:12.460 ⇒ 00:31:13.050 Pranav: Yeah.
182 00:31:13.250 ⇒ 00:31:21.369 Uttam Kumaran: Right? Like, you have the Friday meeting, you have this Monday meeting, and then if… is there gonna… if there’s gonna be this daily process, I think it’s gonna be helpful for you to just call that out.
183 00:31:21.580 ⇒ 00:31:26.429 Uttam Kumaran: I’m a big fan of as much artifacts as we can get their feedback on.
184 00:31:26.590 ⇒ 00:31:40.790 Uttam Kumaran: I would love to see stuff like this daily. Like, I would love us to keep, like, at least one meeting a week, but then have these, like, automated or semi-automated touchpoints daily, but I just think it’s not super clear to me, because there’s this daily memo.
185 00:31:40.870 ⇒ 00:31:46.980 Uttam Kumaran: But then you also have two other meetings, and then I haven’t seen the memo yet, right? So, I think that’s what I’m…
186 00:31:47.170 ⇒ 00:31:52.550 Uttam Kumaran: I just want, sort of, some more clarity on. Apart from that,
187 00:31:53.080 ⇒ 00:31:59.099 Uttam Kumaran: I feel okay about the timeline. I mean, ultimately, I would like…
188 00:31:59.610 ⇒ 00:32:02.760 Uttam Kumaran: My ask for you is, how do you get this done faster?
189 00:32:03.920 ⇒ 00:32:04.460 Pranav: Yeah.
190 00:32:04.910 ⇒ 00:32:08.190 Uttam Kumaran: You know, and this is where, like, I want you to partner with
191 00:32:08.370 ⇒ 00:32:11.500 Uttam Kumaran: me, B, Sam, on, like.
192 00:32:12.490 ⇒ 00:32:17.019 Uttam Kumaran: how can… like, there’s… there’s two ways in which I push you. I would say…
193 00:32:17.290 ⇒ 00:32:20.769 Uttam Kumaran: I think the 20 hours a week is a good goal.
194 00:32:21.010 ⇒ 00:32:25.000 Uttam Kumaran: I think you’re gonna have a tough time hitting it without severe automation.
195 00:32:25.160 ⇒ 00:32:35.329 Uttam Kumaran: like, significant automation in terms of AI taking on tasks, AI drafting these memos and alerting you to issues, and, like, really rich data.
196 00:32:35.720 ⇒ 00:32:41.980 Uttam Kumaran: So, yeah, that’s kind of, like, what I wanted to share, because I… the Data Foundation
197 00:32:42.800 ⇒ 00:32:47.190 Uttam Kumaran: It’s good, you have it on the first milestone, But…
198 00:32:47.350 ⇒ 00:32:53.600 Uttam Kumaran: I’m just concerned that there’s still, like, a lot of work that has to happen, and 20 hours is not a lot of time.
199 00:32:54.080 ⇒ 00:32:56.830 Uttam Kumaran: So, for example, what if you hit 20 hours by Wednesday?
200 00:32:57.420 ⇒ 00:32:59.259 Uttam Kumaran: Like, because there’s an error.
201 00:32:59.650 ⇒ 00:33:04.140 Uttam Kumaran: So I want you to think about, like, look at the history of this client, because there has been issues.
202 00:33:04.530 ⇒ 00:33:16.320 Uttam Kumaran: I want you to have a backup plan on, like, okay, I’ve actually… I actually think I can do this in 10 hours, and so 20 hours is buffer, like, think like that, you know? And be really aggressive on the automation.
203 00:33:17.210 ⇒ 00:33:23.710 Pranav: I, I think… that is a little bit baked into this, okay. Because, yeah, for, like…
204 00:33:24.230 ⇒ 00:33:30.459 Pranav: let’s… let’s go, like, for project to project. Like, for the Central.co-pilot,
205 00:33:30.880 ⇒ 00:33:48.779 Pranav: the code that really needs to be created there is, yeah, the deduplicate… the checking for duplicate and checking for conflicting information. I think AI is going to do a great job of writing out that script. Also, for assessing what is the right place within.
206 00:33:48.780 ⇒ 00:33:57.500 Pranav: the document to, insert new information, I think AI is gonna do a great job of, like, that script as well.
207 00:33:58.170 ⇒ 00:34:05.530 Pranav: the… where I think there’s gonna be a lot of, kind of, work to be done for the Central.co pilot is just really on, like.
208 00:34:05.590 ⇒ 00:34:19.649 Pranav: Maybe provisioning a little bit more infrastructure. So we kind of need to… when we’re doing, like, checking for conflicting, checking for duplicate information, we’re kind of setting up, like, more embeddings.
209 00:34:19.650 ⇒ 00:34:27.109 Pranav: Yeah. And so that’s where the complexity, like, comes up, and that’s where I think there’s gonna be more, like, human-driven development.
210 00:34:27.120 ⇒ 00:34:33.000 Pranav: But in terms of, like, actually, like, writing code, like…
211 00:34:33.760 ⇒ 00:34:45.599 Pranav: it’s really… I feel like it’s all AI, and I kind of just experienced, too, like, I think Sam did, like, an amazing job, like, creating these linear tickets, and this past week, I was… I banged out, like.
212 00:34:45.719 ⇒ 00:34:50.509 Pranav: 12 tickets in, like, one and a half days for Eden. And then.
213 00:34:50.510 ⇒ 00:34:55.050 Uttam Kumaran: Yeah, dude, I’m shipping 30 PRs a day, like, on the platform, like…
214 00:34:55.050 ⇒ 00:34:55.530 Pranav: Yeah.
215 00:34:55.530 ⇒ 00:34:59.610 Uttam Kumaran: I’m… I’m, like, in a different world, so that’s why I’m pushing you to be, like.
216 00:35:00.070 ⇒ 00:35:05.080 Uttam Kumaran: yo, like, we’re here right now. I think exactly what you did.
217 00:35:05.910 ⇒ 00:35:24.590 Uttam Kumaran: keep, like, do it on everything you touch. Like, but don’t sacrifice quality. See, this is the thing, some people I can… I know are gonna make the mistake of, like, oh, AI can do my job now, let’s just trigger shit without giving it a lot of context. This is why we’re gonna have a lot of these backstops for quality.
218 00:35:24.730 ⇒ 00:35:30.800 Uttam Kumaran: And for, like, timeliness, but I also agree, dude, what you’re seeing on Eden, like.
219 00:35:30.950 ⇒ 00:35:39.649 Uttam Kumaran: keep doing it. Additionally, anyone that works on your project, force them to do that too. Like, you shouldn’t have people who are
220 00:35:39.790 ⇒ 00:35:58.449 Uttam Kumaran: who are less efficient than you are. You’re much busier, right? And you’re gonna be much busier. And so, like, you… for you to be on the front leg of these clients is to basically think about, like, okay, how do I actually stay ahead and proactive, and how do I accomplish this earlier than we promised?
221 00:35:58.630 ⇒ 00:36:05.840 Uttam Kumaran: Because if you were to say, we can do it in 2 hours, and I would say don’t promise that, like, say 10, 20 hours, say 2 months, but I’m gonna be like.
222 00:36:06.570 ⇒ 00:36:11.019 Uttam Kumaran: Yo, bang this out in a… bang this out in a month? Month and a week?
223 00:36:11.170 ⇒ 00:36:16.849 Uttam Kumaran: or bang as much of this out by the time you get to Austin, so that we can be like, yeah, we crushed through this.
224 00:36:17.110 ⇒ 00:36:25.820 Uttam Kumaran: And, like, we’re crushing, and then… then what you could do is, like, your time can get more spent thinking about the people. As you mentioned, and this is, I think, like.
225 00:36:26.420 ⇒ 00:36:32.170 Uttam Kumaran: I feel like we’re nearing a good end, because I have… that’s sort of the net of my feedback here, and so there’s some changes.
226 00:36:32.380 ⇒ 00:36:38.759 Uttam Kumaran: I think you and you need to think and work with people like Bea and Janiece on the people at ABC.
227 00:36:39.050 ⇒ 00:36:50.579 Uttam Kumaran: Right? The people are the blocker. It’s very similar in our company. Like, until people learn why this tool is better, and better for them to do their job and get promoted.
228 00:36:50.910 ⇒ 00:36:52.600 Uttam Kumaran: They’re not going to use it.
229 00:36:52.830 ⇒ 00:37:00.039 Uttam Kumaran: And so what you’re dealing with is, yes, it may seem, okay, the system’s not working, system’s not working, but I’m telling you, like.
230 00:37:00.530 ⇒ 00:37:09.379 Uttam Kumaran: that is small… that is a smaller problem… like, that is an easier problem to solve than the human adoption problem. The human adoption problem will take you to 2 months.
231 00:37:09.650 ⇒ 00:37:19.460 Uttam Kumaran: Like, in your time in that, whatever, 5 or 10 hours, you should try to call, like, you should try to spend an hour with the worst user of Andy.
232 00:37:19.890 ⇒ 00:37:36.419 Uttam Kumaran: Right? You should spend an hour with the best user of Andy. You should arrive… when you come here, you should… we should set up some meetings with them, so that you can get them to evangelize. You should talk to B and be like, how do… how do, like, playbooks and systems in a call center get permeated, and like, how do I push that?
233 00:37:36.530 ⇒ 00:37:41.719 Uttam Kumaran: Because that, you’re not going to be able to solve through AI. You’re gonna run out of time if you wait till the end.
234 00:37:41.940 ⇒ 00:37:50.479 Uttam Kumaran: And I think it’s… it’s… as engineers, sometimes we’re like, if I build it, they’ll come. Like, I think I wanna… I wanna, like, shift us, where…
235 00:37:50.780 ⇒ 00:37:57.120 Uttam Kumaran: you’re gonna build all this, I’m actually very comfortable with that, but I want you to shift your time towards, like, the adoption problem.
236 00:37:57.550 ⇒ 00:38:10.069 Uttam Kumaran: And that’s, like, all people-driven. That’s, like, your relationship with the trainers. And that’s where, like, look, you can say, like, hey, I have a clear path, but I need, like, some of these time, or you need my time, or whatever, to go meet with those people.
237 00:38:10.120 ⇒ 00:38:21.740 Uttam Kumaran: Perfect. But, like, I would rather you go spend that, and that is… that is what’s gonna, like, get us the next contract. Because then you’re gonna make 10 more friends, the whole CSR department’s gonna be, like, their team’s rocks.
238 00:38:21.930 ⇒ 00:38:23.800 Uttam Kumaran: We can’t lose them, right?
239 00:38:24.370 ⇒ 00:38:26.720 Pranav: Yeah. Yeah. Yeah. So…
240 00:38:26.720 ⇒ 00:38:30.419 Uttam Kumaran: So I want you to… I want you to think about a… I think a couple pieces of feedback.
241 00:38:30.720 ⇒ 00:38:47.599 Uttam Kumaran: And then I think you could… we could wrap this up today. I think overall, I didn’t… some of the positives… I think, like, this doc is great. I think you did a great job, like, I like the CSO sign-off, the SL sign-off, I like seeing the open questions. I love seeing, like.
242 00:38:47.730 ⇒ 00:38:58.420 Uttam Kumaran: actually a technical approach organized in this format, clearly with milestones. The engagement overview, again, I think I want to see a little bit more, like.
243 00:38:58.500 ⇒ 00:39:12.589 Uttam Kumaran: the business case for the SOW terms, that’s fine, like, I think that’s good feedback even for me. I don’t think I made that really clear. I also want to see a section on cost, and I think we can probably change this B from total S to hours to just, like.
244 00:39:12.950 ⇒ 00:39:13.810 Uttam Kumaran: Cost.
245 00:39:14.070 ⇒ 00:39:29.370 Uttam Kumaran: Right? So I want to know what the cost is in terms of time, I want to know the cost, like, what kind of, like, what skill sets are needed. And this is a mix… again, Sam should be sharing this. He’s like, he… basically, if we… if we’re not able to get this in 20 hours, he’s gonna be the first person that I’m like.
246 00:39:29.430 ⇒ 00:39:42.250 Uttam Kumaran: okay, you agree… you agree that we could do this? But something a little bit… we’re not measuring margin, really, but if you hit 20 hours, we’ll be in great shape here. But I think just you having context about those two pieces.
247 00:39:42.410 ⇒ 00:39:46.869 Uttam Kumaran: And we can meet as CSO group and discuss that too, so…
248 00:39:47.340 ⇒ 00:39:55.450 Uttam Kumaran: So if you wanna, like, just make a couple of those changes, or maybe if you wanna… I’m gonna hop to another thing, if you wanna stay on with B and just, like, wrap it up.
249 00:39:55.840 ⇒ 00:40:01.989 Uttam Kumaran: and, like, just make some of those changes, that’s perfect. I feel comfortable, like, signing off on this today.
250 00:40:03.680 ⇒ 00:40:05.429 Pranav: Okay, yeah, we could do that.
251 00:40:06.340 ⇒ 00:40:06.920 Uttam Kumaran: Okay.
252 00:40:06.950 ⇒ 00:40:07.850 Pranav: Cool. You want me to get.
253 00:40:07.850 ⇒ 00:40:08.620 Uttam Kumaran: Great, this one’s great.
254 00:40:09.010 ⇒ 00:40:11.260 Pranav: The… the revenue, though? Because I…
255 00:40:11.260 ⇒ 00:40:19.439 Uttam Kumaran: Leave some comments in there, or Slack me, and let’s Slack about it, and I can give you some context, because I have that.
256 00:40:19.980 ⇒ 00:40:39.260 Pranav: Okay, cool. Yeah, I think I can probably… there was, like, aside from just, like, what I’ve put into, like, the project plan, there’s, like, a section in the SOW that I can probably reread again to kind of go into… go into that. Maybe it’s in there, maybe it’s not, like, the context that I’m looking for.
257 00:40:39.410 ⇒ 00:40:42.250 Pranav: But, yeah, we can also talk about it as well. That would be helpful.
258 00:40:42.250 ⇒ 00:40:44.690 Uttam Kumaran: Yeah, and see if you can search through cursor…
259 00:40:44.990 ⇒ 00:40:47.199 Uttam Kumaran: And see if there’s anything from the past.
260 00:40:47.300 ⇒ 00:40:51.759 Uttam Kumaran: I’ll… there’s some logic to how we did it. We basically thought about, like, the average…
261 00:40:52.000 ⇒ 00:40:54.330 Uttam Kumaran: CSRs, like, hourly rate.
262 00:40:54.760 ⇒ 00:41:01.659 Uttam Kumaran: looked at, like, how many questions, how many calls they’re getting, sort of backed into a number. I would like us to get tighter, like.
263 00:41:02.140 ⇒ 00:41:12.130 Uttam Kumaran: some of that may be wrong, I sort of… it was, like, back of the envelope math two years ago, like, I was just sort of trying to figure out the deal here. So I… I would like you to have a clear perspective.
264 00:41:12.220 ⇒ 00:41:27.150 Uttam Kumaran: And the other thing is, like, again, put yourself in the shoes of the CEO. Let’s say we walk into ABC when you’re here, and the CEO’s there. And I’m literally throwing you to the wolves. I’m like, Vernab would love just to take 5 minutes of your time to just, like.
265 00:41:27.250 ⇒ 00:41:29.030 Uttam Kumaran: Tell you about the project.
266 00:41:29.290 ⇒ 00:41:43.409 Uttam Kumaran: Like, I think you did… you’re… I know you, you’re gonna do really well on the small details, so I’m not worried about that. It’s, like, I think you need to get to the business case faster. Like, even when I asked you, like, what is the outcomes.
267 00:41:43.590 ⇒ 00:41:50.070 Uttam Kumaran: I was hesitant to say, like, explain me the what, and then explain me the outcomes. Start with the outcomes.
268 00:41:50.370 ⇒ 00:42:05.150 Uttam Kumaran: be like, you’re giving me $50,000, I’m gonna… not only am I gonna save you this much in churn, but, like, your employee retention is gonna go up by this much, and so you’re basically getting, like, a quarter million dollars in return for this money.
269 00:42:05.540 ⇒ 00:42:07.909 Uttam Kumaran: And here’s how we’re gonna do that, right?
270 00:42:08.050 ⇒ 00:42:17.549 Uttam Kumaran: the CEO is… doesn’t think in, like, there’s a Google Doc here and that. That’s, like… that’s just, like, ammo. But, like…
271 00:42:17.550 ⇒ 00:42:18.110 Pranav: Yep.
272 00:42:18.320 ⇒ 00:42:22.889 Uttam Kumaran: frame… really, and I’m gonna pull everybody this way, is framing in terms of outcomes.
273 00:42:23.210 ⇒ 00:42:32.740 Uttam Kumaran: Because when you frame in outcomes, you can then do price the outcomes, and we’re, as you can tell, we’re… we’re putting a lot of downward pressure on cost.
274 00:42:33.190 ⇒ 00:42:37.499 Uttam Kumaran: So, we, we can’t, we can’t price on what we’re doing.
275 00:42:38.000 ⇒ 00:42:40.889 Uttam Kumaran: Yeah. We have to price on what… on the value we’re delivering.
276 00:42:41.530 ⇒ 00:42:42.550 Pranav: Yep, yep.
277 00:42:43.740 ⇒ 00:42:53.109 Uttam Kumaran: So if you’re like, hey, you’re spending 50K? And you’re gonna deliver that for 10K.
278 00:42:53.240 ⇒ 00:42:59.780 Uttam Kumaran: 20K, whatever it is, right? And so, that’s how our business is going. And…
279 00:42:59.950 ⇒ 00:43:10.339 Uttam Kumaran: this is where I don’t want to set margin targets, but I feel like we’re going to have healthy margins. I want to set customer success and outcome goals. That’s what matters. At any margin, that’s what matters.
280 00:43:10.340 ⇒ 00:43:20.530 Uttam Kumaran: The most. And I’m already putting a lot of downward pressure on margin, so I want you to think about the cost, but think of it in a way of, like, what’s the thing I need to accomplish the outcome?
281 00:43:20.840 ⇒ 00:43:35.000 Uttam Kumaran: I don’t want us thinking too much in terms of, like, I can make 90% margin on this. Instead, I’d be like, dude, if you’re making 90% margin, go to the CEO and be like, yo, you’re getting fat ROI on us. Like, you should totally give us other projects, right?
282 00:43:35.120 ⇒ 00:43:35.630 Pranav: Yeah.
283 00:43:35.630 ⇒ 00:43:40.759 Uttam Kumaran: So, this meeting, I want you to just align on the outcome so that on the renewal call.
284 00:43:40.930 ⇒ 00:43:58.839 Uttam Kumaran: you can have a crisp, like, here’s what you’ve paid us so far, here’s what we believe we delivered, here’s the reasoning why, and, like, I think if you give us another $30K to go deeper on transcripts, to expand Andy across the company, you’re gonna get this. Like, what do you think?
285 00:43:59.670 ⇒ 00:44:01.170 Uttam Kumaran: Bingo, you know?
286 00:44:02.140 ⇒ 00:44:08.619 Uttam Kumaran: And that’s where I think also you have room to improve. Like, you’re good technically, you know that, and you’re good at the details, so…
287 00:44:08.730 ⇒ 00:44:16.150 Uttam Kumaran: start to think about, like, the pitching side of things. But again, it’s… it’s… it’s just storytelling, but it’s…
288 00:44:16.290 ⇒ 00:44:34.460 Uttam Kumaran: lead the… like, lead with the, spoiler alert, right? Okay. What you’ll find in sales is the more people talk about how we’re gonna get there, how we’re gonna get there, how we’re gonna get there, and I’m seeing this a lot as CEO, because I get pitched a lot for people to do stuff for us.
289 00:44:34.770 ⇒ 00:44:44.840 Uttam Kumaran: Dude, I’m like, yo, I don’t have time. I’m gonna… if I give you 10K, what can I expect out of this? I’m also really in the weeds, so I’m like, we need a plan, but like…
290 00:44:45.150 ⇒ 00:45:00.359 Uttam Kumaran: if we’re not… if you’re not gonna put a plan together in front of me, and be like, here’s clearly how… if you spend 10K with me, we get 50, then I’m not gonna do it, because I can do that internally. I can go to Ricoh, I can go to B, I’ll say, you have 10 grand, let’s accomplish these outcomes, go for it, right?
291 00:45:00.620 ⇒ 00:45:08.710 Uttam Kumaran: So, that’s… that’s where I think, like, there… you… you have some good opportunity for, you know, for improvement. I think Greg has the opposite problem.
292 00:45:09.020 ⇒ 00:45:12.609 Uttam Kumaran: Greg is… Really good at the storytelling.
293 00:45:12.820 ⇒ 00:45:19.129 Uttam Kumaran: But then I think in the details, he doesn’t… he doesn’t have the depth. Just a different… just a different problem, you know?
294 00:45:19.130 ⇒ 00:45:20.640 Pranav: Yep, yep, yep, yep.
295 00:45:20.810 ⇒ 00:45:21.680 Pranav: Yeah.
296 00:45:22.420 ⇒ 00:45:23.330 Pranav: Okay.
297 00:45:23.610 ⇒ 00:45:27.980 Uttam Kumaran: Cool. Okay, give this a shot today, and then just slap me as you need… as you have questions.
298 00:45:28.350 ⇒ 00:45:30.710 Pranav: Yeah, totally. Perfect. Okay.
299 00:45:31.050 ⇒ 00:45:32.540 Uttam Kumaran: Alright, thank you guys.
300 00:45:32.540 ⇒ 00:45:33.320 Brylle Girang: to them.
301 00:45:34.210 ⇒ 00:45:36.040 Brylle Girang: Good, that’s been great!
302 00:45:36.620 ⇒ 00:45:38.849 Pranav: Yeah, went pretty good.
303 00:45:39.620 ⇒ 00:45:52.490 Pranav: Yeah, I kind of want to go over this transcript as well, to kind of just, like, get full feedback before I just completely finish this up, but yeah, I mean, I’m happy to go through some of the stuff right now.
304 00:45:55.630 ⇒ 00:46:05.470 Brylle Girang: Yeah, I left some comments in the project plan, just so that we’re guided on what we need to do, but going back to our discussion earlier, I think it,
305 00:46:05.860 ⇒ 00:46:22.880 Brylle Girang: talking… actually talking with Andy, and with ABC, rather, is going to be a good plan, because the transcripts will give us, like, the who, who uses Andy, who doesn’t use Andy, and the how, like, how often are they using Andy, but it’s not going to give us, like, the why.
306 00:46:23.220 ⇒ 00:46:36.539 Brylle Girang: around the adoption, right? Why are they not using Andy? And I think the best way that we can understand the why there is actually just talking with them. Like, talk with the best, talk with the worst.
307 00:46:36.650 ⇒ 00:46:43.389 Brylle Girang: just… then just try to understand, like, what the gap is. And our goal is going to just close that gap.
308 00:46:43.720 ⇒ 00:46:44.640 Brylle Girang: Between… between.
309 00:46:44.640 ⇒ 00:46:45.020 Pranav: No.
310 00:46:45.130 ⇒ 00:46:47.850 Brylle Girang: The best adopters and the worst adopters.
311 00:46:49.220 ⇒ 00:46:50.220 Pranav: Yeah, yeah.
312 00:46:50.580 ⇒ 00:46:51.050 Pranav: I see.
313 00:46:51.050 ⇒ 00:47:04.669 Brylle Girang: I think, I think what’s going to help me, also help you out here, is if I could, like, try to learn more about ABC and how to run things, I might go through the recordings that we had.
314 00:47:04.760 ⇒ 00:47:12.159 Brylle Girang: With them, and if that’s not enough, I might ask to jump in on one call with them specifically regarding adoption, but…
315 00:47:12.870 ⇒ 00:47:15.879 Brylle Girang: Okay, yeah, that helps,
316 00:47:16.870 ⇒ 00:47:22.970 Brylle Girang: So let’s go through this one by one. For these calculations, I think Uta mentioned that
317 00:47:23.420 ⇒ 00:47:31.149 Brylle Girang: this was done by him, but I think what we want to happen here is to see if you can interact to the same conclusion.
318 00:47:31.280 ⇒ 00:47:33.499 Brylle Girang: Based on what we’re going to do with them.
319 00:47:33.720 ⇒ 00:47:35.190 Brylle Girang: On the next month.
320 00:47:36.100 ⇒ 00:47:36.800 Pranav: Yeah.
321 00:47:36.800 ⇒ 00:47:46.490 Brylle Girang: put them check the… maybe the average cost for call center agents around their areas, but I think it’s going to be good if you could also check, like, the average street.
322 00:47:46.620 ⇒ 00:47:50.789 Brylle Girang: for ABCCSRs, and I think a good pitch here
323 00:47:51.280 ⇒ 00:48:03.340 Brylle Girang: is just… just tell Andy, here’s what you’re paying one person if you use Andy, and if you adopt… if you adopt Andy to the maximum, here’s what’s going to save you, etc.
324 00:48:05.550 ⇒ 00:48:11.099 Pranav: Yeah, yeah, I think that makes sense. Yeah, because at the end of the day, like.
325 00:48:11.440 ⇒ 00:48:17.690 Pranav: This should be used for… creating that new contract, right? And so, yeah, understanding, like.
326 00:48:17.990 ⇒ 00:48:30.450 Pranav: how we arrived at this, will be useful, because then I can say, hey, like, I don’t think this is accurate, I don’t think that’s accurate. Yeah, okay, that sounds good to me. I’ll get more insight into that.
327 00:48:30.740 ⇒ 00:48:37.100 Brylle Girang: Yeah, ultimately, the goal here is to, you know, push more sessions so that we can get to a higher cost selling.
328 00:48:37.610 ⇒ 00:48:38.590 Brylle Girang: Yeah.
329 00:48:39.580 ⇒ 00:48:49.880 Brylle Girang: Yeah, for the estimated hours, I think this is where we might need Otam’s help, because one thing that he mentioned is that, if you could get, like, the calls instead.
330 00:48:50.330 ⇒ 00:49:04.799 Brylle Girang: of the total hours, that would be more helpful for him, but right now, I don’t have a clear understanding on how we can get the cost without trying to know what the salaries are for our team members, right? So…
331 00:49:04.870 ⇒ 00:49:10.800 Brylle Girang: We might need some there, but I think the main thing that we need to focus on is
332 00:49:10.930 ⇒ 00:49:17.369 Brylle Girang: How are we able to cut down the hours to 20? And how do you feel about that?
333 00:49:19.780 ⇒ 00:49:24.399 Pranav: Oh, cutting it down 220? Yeah, I feel pretty good about that.
334 00:49:24.790 ⇒ 00:49:31.829 Pranav: Yeah, for the 50 hours before… is interesting to me.
335 00:49:33.480 ⇒ 00:49:45.829 Pranav: I mean, yeah, I did feel pretty good about 20 hours per week, just given this, right? Like, at the end of the day, this is something that I could probably do myself, if it made the most sense for me to do it.
336 00:49:45.970 ⇒ 00:49:47.700 Pranav: Within 20 hours per week.
337 00:49:47.860 ⇒ 00:49:50.939 Pranav: Which is kind of…
338 00:49:51.220 ⇒ 00:49:58.639 Pranav: now I’m just thinking about, okay, like, having Casey or Mustafa fill in for that, rather than me.
339 00:50:00.610 ⇒ 00:50:10.059 Pranav: But what I should do also is to assess why was it 50 hours a week before, like, so I need to go into Clockify to, like, look at what all of the…
340 00:50:10.250 ⇒ 00:50:14.440 Pranav: you know, for the month of January, for the month of February,
341 00:50:14.680 ⇒ 00:50:18.019 Pranav: What was the reason that we were spending 20 hours per week?
342 00:50:19.300 ⇒ 00:50:24.390 Pranav: And then, yeah, I will… I mean, sorry, 50 hours per week, and then I can…
343 00:50:24.590 ⇒ 00:50:31.249 Pranav: See, I… one, my… My inkling is that, one.
344 00:50:31.530 ⇒ 00:50:39.599 Pranav: a lot of the stuff that they were building before, I don’t think, had a lot to do with infrastructure, and I think…
345 00:50:39.900 ⇒ 00:50:50.419 Pranav: we weren’t… we could actually use Cursor to build infrastructure, right? Like, there’s the whole GCP CLI, that we could be taking advantage of.
346 00:50:50.620 ⇒ 00:50:54.549 Pranav: So, that could also be cloud, like, AI-driven.
347 00:50:54.850 ⇒ 00:51:07.979 Pranav: Another thing, though, is I don’t think that there was clear, direction in, like, timelines that were put in place. So when things were, like, lagging over time,
348 00:51:08.960 ⇒ 00:51:09.770 Pranav: they’re…
349 00:51:09.930 ⇒ 00:51:21.710 Pranav: it wasn’t getting caught, it was just kind of like, okay, yeah, we’ll get it done at some point. So I think just having these hard deadlines, like, is gonna help, but I don’t think that’s enough in terms of
350 00:51:22.640 ⇒ 00:51:32.480 Pranav: I feel still confident by the 20 hours per week, but I want to have a more clear and confident case to say, hey, it’s not just going to be based on clearer deadlines, it’s also going to be because of, like.
351 00:51:32.970 ⇒ 00:51:42.560 Pranav: XYZ taking the load off because AI’s gonna do every… do all of that stuff. So, I’ll have a better pitch for that as well.
352 00:51:42.880 ⇒ 00:51:43.930 Pranav: Yeah.
353 00:51:44.370 ⇒ 00:51:45.180 Pranav: Yeah.
354 00:51:45.310 ⇒ 00:51:59.410 Pranav: Okay, today, I didn’t feel like it’s gonna take longer than 20 hours. I think the things that Utsom was saying, like, hey, like, we should bake in, like, you know, errors and stuff like that, I think that is baked in.
355 00:51:59.570 ⇒ 00:52:04.560 Pranav: I really think, like, if things were to go super well, like, we could get things done even quicker.
356 00:52:06.270 ⇒ 00:52:10.260 Brylle Girang: Gotcha, okay. I think those are good insights. It would be good if we could
357 00:52:10.490 ⇒ 00:52:16.940 Brylle Girang: maybe add that as a note here, but I think, you know, with the 50 hours, I actually think that that’s…
358 00:52:17.030 ⇒ 00:52:31.700 Brylle Girang: that has been more than that in the past, especially since, you know, we have Casey working on this full-time, we have Sam working on this, like, half of his priorities, and we also have… we also had Amber, so that’s, like, a total of, you know, 60 hours.
359 00:52:31.700 ⇒ 00:52:33.249 Pranav: Working full-time on this?
360 00:52:33.700 ⇒ 00:52:34.440 Brylle Girang: Sorry.
361 00:52:34.830 ⇒ 00:52:37.560 Pranav: Is Casey working 40 hours a week on this? I don’t think so.
362 00:52:37.560 ⇒ 00:52:44.370 Brylle Girang: PC is in a fixed contract for us, and I am guessing that it’s going to be, like, 40 hours per week?
363 00:52:44.430 ⇒ 00:52:58.239 Brylle Girang: a standard, and this is the only client that Casey is working on. That’s why Otem has been pushing us to, like, trim down, or try to get a better understanding of what Casey’s work is actually doing.
364 00:52:59.730 ⇒ 00:53:05.739 Brylle Girang: But yeah, I… I’m saying that Casey might be working full-time on Andy, on ABC.
365 00:53:06.850 ⇒ 00:53:14.540 Pranav: Okay. Yeah. I think also now, though, since we have Eden, he’ll be splitting his time a little bit more. Yeah.
366 00:53:15.390 ⇒ 00:53:16.920 Pranav: But, okay, yeah.
367 00:53:17.730 ⇒ 00:53:30.579 Brylle Girang: Yeah, at the end of the day, let’s just go back to, you know, under-promising and then over-delivering. If you could add a buffer on, like, the cost or the total hours, and then try to, you know, do less than that, that would be amazing.
368 00:53:31.270 ⇒ 00:53:35.280 Pranav: Okay, so, for the hours, right,
369 00:53:36.710 ⇒ 00:53:43.359 Pranav: where should I fit in versus Sam fit in? Because, in terms of, like.
370 00:53:44.340 ⇒ 00:53:58.490 Pranav: estimates, I thought that was something that the… this SL should be the one kind of defining, and then I’m like, hey, we need to get things done quicker, or we have less resources, and then that’s where it goes. He’s kind of signed on these 20 hours,
371 00:54:00.530 ⇒ 00:54:02.009 Pranav: Should I just kind of…
372 00:54:02.660 ⇒ 00:54:08.150 Pranav: Do we want to have, like, a call, maybe me, you, and him, to kind of, like, discuss a little bit more about…
373 00:54:09.020 ⇒ 00:54:18.340 Pranav: I mean, I do think it’s baked in, the 20 hours a week. I don’t want to just increase it just because, you know, we’re saying we should increase it.
374 00:54:19.230 ⇒ 00:54:25.670 Pranav: Yeah, that’s kind of, like, where I’m thinking about it, because, like, for me, in my head, I think this can get done in 20 hours per week.
375 00:54:26.540 ⇒ 00:54:44.270 Brylle Girang: Yeah, totally. I think this… this needs to be a conversation between you and Sam. Ultimately, Sam should know, who we need to allocate, how many hours they should dedicate, but you should know if that’s, like, enough for the client, or if that’s enough for our business and our revenue.
376 00:54:44.590 ⇒ 00:54:48.509 Brylle Girang: So I think that’s going to be, like, the main conflict that we need to solve.
377 00:54:50.130 ⇒ 00:54:50.840 Pranav: Okay.
378 00:54:55.160 ⇒ 00:55:04.519 Brylle Girang: Okay, yeah, this is… this is good. Let me know if you need any help, but will you go through this doc and then try to update this?
379 00:55:04.760 ⇒ 00:55:13.380 Pranav: Yeah, by end of day, I’ll have it, fully updated. I’m just gonna hop into, like, some Eden stuff right now, but then, yeah, by that time…
380 00:55:13.580 ⇒ 00:55:20.830 Pranav: I just want to make sure, because Utam did give, like, a bunch of comments, so I just want to make sure, like, I address all of it. Yeah. Yeah.
381 00:55:21.530 ⇒ 00:55:22.140 Brylle Girang: Perfect.
382 00:55:22.320 ⇒ 00:55:22.850 Brylle Girang: Thanks.
383 00:55:22.850 ⇒ 00:55:23.310 Pranav: Cool, cool.
384 00:55:23.310 ⇒ 00:55:23.710 Brylle Girang: W.
385 00:55:23.710 ⇒ 00:55:25.930 Pranav: Yeah. Thanks, V. Talk soon.