Meeting Title: Weekly Managers Sync and Updates Date: 2025-08-06 Meeting participants: Amber Lin, Awaish Kumar, Robert Tseng, Uttam Kumaran
WEBVTT
1 00:00:29.730 ⇒ 00:00:30.870 Uttam Kumaran: Hi! Everyone.
2 00:00:33.350 ⇒ 00:00:34.030 Robert Tseng: Hey!
3 00:00:35.720 ⇒ 00:00:36.820 Uttam Kumaran: Lou.
4 00:00:43.620 ⇒ 00:00:44.320 Awaish Kumar: Hello!
5 00:00:48.930 ⇒ 00:00:51.319 Uttam Kumaran: Okay, give me one sec. Let me just
6 00:00:52.210 ⇒ 00:00:55.049 Uttam Kumaran: create the doc really quick. And then I don’t think
7 00:00:55.730 ⇒ 00:00:58.809 Uttam Kumaran: I think we have maybe a couple of things to cover. But hopefully.
8 00:00:59.510 ⇒ 00:01:01.750 Uttam Kumaran: tomorrow meeting can be a bit longer.
9 00:01:27.850 ⇒ 00:01:32.040 Uttam Kumaran: okay. I just created like a new template for Wednesday, and we could just take like
10 00:01:32.740 ⇒ 00:01:36.379 Uttam Kumaran: 5, 6 min. Just jot note down anything, and then we can run through stuff.
11 00:02:16.480 ⇒ 00:02:19.240 Amber Lin: Hello! Sorry I wasn’t connected to the audio, so say.
12 00:02:19.240 ⇒ 00:02:20.015 Uttam Kumaran: Oh!
13 00:02:21.166 ⇒ 00:02:23.803 Amber Lin: I was like, why is nobody talking?
14 00:02:25.950 ⇒ 00:02:32.044 Amber Lin: Okay? I just called Giselle. I was thinking with her on insomnia cookies
15 00:02:33.140 ⇒ 00:02:43.299 Amber Lin: ujam. Not for your review yet. I. We don’t have access to a lot of things. So for Spike, and then we’ll we’ll ask you to review.
16 00:02:43.620 ⇒ 00:02:45.550 Uttam Kumaran: Okay, cool. Yeah. See
17 00:02:45.660 ⇒ 00:02:52.050 Uttam Kumaran: whatever it is that seems pretty chill. So either Mustafa or Casey should be able to nail that you know.
18 00:02:56.210 ⇒ 00:03:12.409 Amber Lin: Well, I wanted to talk about recruiting, because I saw I saw those on the on in the thread, and I would love to talk about how we can standardize it, but we can save it for another call, or we can run through our normal. Do the Doc, and then talk about recruiting stuff. Later.
19 00:03:12.410 ⇒ 00:03:17.600 Uttam Kumaran: Yeah, maybe put it, just put it in the doc, either under your section or you can just put it in the
20 00:03:17.820 ⇒ 00:03:27.110 Uttam Kumaran: the next section, put in the Thursday topics, and then we’ll we have this time block. So we’ll just work through everything. And we’re not tomorrow. Yeah.
21 00:03:27.110 ⇒ 00:03:32.959 Amber Lin: Awesome we have it, for we have the managers meeting right now on Friday.
22 00:03:33.190 ⇒ 00:03:39.270 Amber Lin: just because we have our demo meeting on Friday. We can move it to Thursday.
23 00:03:39.450 ⇒ 00:03:41.709 Amber Lin: so we can have less meetings on Friday.
24 00:03:43.070 ⇒ 00:03:47.550 Uttam Kumaran: I am good with that. Yeah, fine. With that.
25 00:03:47.790 ⇒ 00:03:51.850 Amber Lin: Yeah, I I don’t see like, if it’s necessary to
26 00:03:52.000 ⇒ 00:03:55.510 Amber Lin: do, you have to do it like on Friday. I think it works.
27 00:03:55.510 ⇒ 00:04:01.630 Uttam Kumaran: Yeah, I think probably we’ll end up doing this meeting like more like 30 min on Wednesday.
28 00:04:01.630 ⇒ 00:04:02.030 Amber Lin: Okay.
29 00:04:02.030 ⇒ 00:04:08.930 Uttam Kumaran: And then we’re having. Yeah, maybe let’s do. Let’s do this on. Let’s do this tomorrow that way. Friday can be a little bit more clear.
30 00:04:09.230 ⇒ 00:04:10.150 Amber Lin: Yeah, okay.
31 00:04:10.310 ⇒ 00:04:10.860 Uttam Kumaran: Okay.
32 00:04:12.420 ⇒ 00:04:15.740 Amber Lin: I will edit that.
33 00:04:16.880 ⇒ 00:04:18.050 Amber Lin: Oh.
34 00:04:20.779 ⇒ 00:04:27.759 Amber Lin: have has everyone wrote in the Doc? If not, we’ll do 10 min, and we can all write in it.
35 00:04:27.960 ⇒ 00:04:32.260 Uttam Kumaran: Yeah, if we do like, kind of 5 or so minutes, I’m working stuff.
36 00:11:10.370 ⇒ 00:11:12.140 Uttam Kumaran: Okay, I’m I’m ready.
37 00:11:17.500 ⇒ 00:11:19.020 Amber Lin: Give me one sec.
38 00:11:43.650 ⇒ 00:11:44.780 Amber Lin: I’m ready to.
39 00:11:46.400 ⇒ 00:11:52.350 Uttam Kumaran: Okay, great. So let’s walk through. Things
40 00:11:56.050 ⇒ 00:11:57.859 Uttam Kumaran: should be.
41 00:12:05.442 ⇒ 00:12:06.529 Amber Lin: I can start.
42 00:12:07.030 ⇒ 00:12:08.830 Uttam Kumaran: Yeah. Please. Go ahead.
43 00:12:09.860 ⇒ 00:12:13.280 Amber Lin: My main priority is Eden, taking up a lot of time.
44 00:12:13.610 ⇒ 00:12:20.583 Amber Lin: took a lot of work. I feel a little bit better about it. I have a better grasp of the projects, and
45 00:12:21.480 ⇒ 00:12:27.650 Amber Lin: had some face time with Josh, and I’m asking Henry to add me to.
46 00:12:27.650 ⇒ 00:12:28.710 Uttam Kumaran: How’d it go?
47 00:12:30.700 ⇒ 00:12:34.960 Amber Lin: It’s better than I expected, because I have bad expectations.
48 00:12:36.540 ⇒ 00:12:48.279 Amber Lin: I was so scared, and afterwards I talked to them a lot. I was like, Oh, that’s better than I thought, and he’s like, Oh, yeah, Josh, Josh is more of the chill one. He has his time, but he’s mostly okay, I was like, okay, right?
49 00:12:49.406 ⇒ 00:12:55.219 Amber Lin: I think I would just morbidly scared of these people. But it’s okay.
50 00:12:56.375 ⇒ 00:12:56.930 Amber Lin: Great.
51 00:12:56.930 ⇒ 00:13:07.570 Uttam Kumaran: Great, great, great it’s it doesn’t get much more tense than this type of stuff, you know, because for the most part we don’t. We? I think we’re all pretty chill, but like they’re they have high expectations. So.
52 00:13:07.570 ⇒ 00:13:08.220 Amber Lin: Yeah.
53 00:13:08.775 ⇒ 00:13:14.770 Amber Lin: Then also had some face face time with the Emr project. So there’s a lot of stuff going on.
54 00:13:14.950 ⇒ 00:13:26.819 Amber Lin: What I want to do when I get free. Time is to update the project management, Doc, so that I can document all the different projects. And I’m gonna sync with Robert tomorrow on the future state, so I can
55 00:13:26.960 ⇒ 00:13:30.820 Amber Lin: feel a little better about planning and not have to scramble
56 00:13:31.340 ⇒ 00:13:56.210 Amber Lin: every single week so hopefully. That will help. I know. Just talk to Robert earlier this morning. Our concerns on Andrew and Henry I I know Robert’s talking to them, but I thought they were very senior, and they will take on the task. But it seems like because they’re still external folks that still need to keep a closer eye on them. So that’s a learning for me, too. Yeah.
57 00:13:56.380 ⇒ 00:14:00.699 Amber Lin: So that’s on Eden. The second is onboarding Giselle, getting her
58 00:14:00.900 ⇒ 00:14:06.166 Amber Lin: stuff to do, and then making sure she knows how to do them. So that’s taking a bit of time.
59 00:14:06.710 ⇒ 00:14:10.579 Amber Lin: for the other other client projects. ABC is
60 00:14:11.209 ⇒ 00:14:19.609 Amber Lin: yellow light inspect, mostly the inspector sheet issue, and also sites didn’t have any mind space to give to it. So
61 00:14:20.150 ⇒ 00:14:23.159 Amber Lin: I think that’s the only thing that’s going wrong. But.
62 00:14:23.160 ⇒ 00:14:34.926 Uttam Kumaran: I don’t see that as a yellow sorry to interrupt. I don’t see that as a yellow, like the inspector sheet issue and like issues. We’re gonna come up when we’re doing work for people. So I think the biggest thing is that
63 00:14:35.450 ⇒ 00:14:43.940 Uttam Kumaran: like one output of this work is that I want the AI team to flag these more proactively, like
64 00:14:44.120 ⇒ 00:15:03.449 Uttam Kumaran: Feedback, was already coming back from the team that things were wrong, right? And why did we wait for the client to email us to do that like you can already see those things. Right? So for me, this is something we could, was was extremely preventable, and we fix the issue in like 30 min. So.
65 00:15:04.094 ⇒ 00:15:11.189 Uttam Kumaran: that’s fine. We will have to learn from these. But as part of all of these investigations, and like
66 00:15:11.340 ⇒ 00:15:16.935 Uttam Kumaran: sort of figuring out what the problems are, there has to be okay, how do we mitigate this in the future? So
67 00:15:17.300 ⇒ 00:15:19.699 Uttam Kumaran: we’ll have, we’ll it’ll get better. But I actually
68 00:15:19.890 ⇒ 00:15:22.010 Uttam Kumaran: my! I don’t care that you’re spending.
69 00:15:22.120 ⇒ 00:15:26.850 Uttam Kumaran: I don’t actually don’t want you to spend more time there. So we’re fine.
70 00:15:26.850 ⇒ 00:15:32.989 Amber Lin: I think more as in I just wanna make sure I have things ticketed out and
71 00:15:33.467 ⇒ 00:15:51.362 Amber Lin: go in a pro in in that progress, and then I’ll assign the tickets to Giselle if I need help. But I don’t think I’ve thought about how things are going. I’m mostly just oh, I met with them. Here are the things, but I’m not pushing on any of the initiatives necessarily.
72 00:15:52.050 ⇒ 00:15:56.081 Amber Lin: That’s what I meant. Insomnia is getting set up.
73 00:15:56.850 ⇒ 00:16:13.480 Amber Lin: getting Giselle to do the manual fill. I just met with her and then scoping automations. Data platform is stagnant, for now, because Annie has some other tasks, though we do have the design document I’ve asked both of them to review.
74 00:16:13.980 ⇒ 00:16:22.729 Amber Lin: I will need some help from a wish for the architecture. Advice, if but if a wish, you’re okay okay with it. I’m going to push Vash up to
75 00:16:23.600 ⇒ 00:16:35.879 Amber Lin: build those models if we need any models. And if Annie gets too busy. Is there someone else we can ask to do real because real is less of a
76 00:16:36.190 ⇒ 00:16:38.030 Amber Lin: dashboard. Then.
77 00:16:38.030 ⇒ 00:16:38.870 Uttam Kumaran: Oh! What is this for.
78 00:16:38.870 ⇒ 00:16:42.980 Amber Lin: Data platform for the productivity dashboard.
79 00:16:42.980 ⇒ 00:16:45.230 Uttam Kumaran: Oh, yeah, like, I mean.
80 00:16:46.490 ⇒ 00:16:52.900 Uttam Kumaran: yeah, like that. I can do real. Casey can do it. Mustafa can do it. Rosha can do it like.
81 00:16:54.390 ⇒ 00:17:01.270 Uttam Kumaran: Demo. A can do it like anyone else can do it. So if she, if she’s like
82 00:17:01.830 ⇒ 00:17:04.783 Uttam Kumaran: not able to do this, just move it off of her plate.
83 00:17:05.030 ⇒ 00:17:06.769 Amber Lin: I think I’m gonna do that.
84 00:17:07.380 ⇒ 00:17:11.199 Uttam Kumaran: Yeah, it just seems like she’s doing a bunch of other stuff. So let’s just like
85 00:17:11.700 ⇒ 00:17:15.339 Uttam Kumaran: not do it. Or, yeah, I’ll also like.
86 00:17:15.510 ⇒ 00:17:23.859 Uttam Kumaran: I don’t know. I I don’t. How much time are we spending talking about the data platform stuff? Because this is something that Giselle can push forward and like
87 00:17:24.900 ⇒ 00:17:26.890 Uttam Kumaran: right. We’ll just hand it to her to do.
88 00:17:26.890 ⇒ 00:17:28.630 Amber Lin: Yeah, okay, yeah, I can do that.
89 00:17:28.940 ⇒ 00:17:31.100 Uttam Kumaran: Cause. It’s an internal thing, and like
90 00:17:32.570 ⇒ 00:17:34.280 Uttam Kumaran: she should be able to do that.
91 00:17:34.280 ⇒ 00:17:36.660 Amber Lin: Yeah, I think, especially now that we have the
92 00:17:36.980 ⇒ 00:17:42.799 Amber Lin: the, the architecture design. It’ll be a lot easier, very easy, to hand to her.
93 00:17:43.520 ⇒ 00:17:49.290 Amber Lin: Okay, are we noting down decisions anywhere?
94 00:17:50.008 ⇒ 00:17:50.920 Uttam Kumaran: Yeah, at the bottom.
95 00:17:50.920 ⇒ 00:17:56.010 Amber Lin: Oh, okay, I will note that down.
96 00:17:57.360 ⇒ 00:17:58.450 Amber Lin: Okay.
97 00:17:59.604 ⇒ 00:18:13.979 Amber Lin: for a bit stems just our new sprint. Seems like it’s going well, talking to analysts every 2 weeks. So talking tomorrow and then making sure that we cover for Kyle when he’s out of office next week, which I think we’re fine.
98 00:18:14.350 ⇒ 00:18:16.519 Amber Lin: He doesn’t have too heavy of tests.
99 00:18:16.900 ⇒ 00:18:25.459 Amber Lin: And then last thing is recruiting. I already talked about it earlier, made some improvements on time allocations.
100 00:18:25.980 ⇒ 00:18:30.390 Amber Lin: and then for my personal stuff. I should plan for Pto or I’m gonna
101 00:18:30.810 ⇒ 00:18:33.929 Amber Lin: burnout. So I’m planning for that.
102 00:18:36.350 ⇒ 00:18:38.139 Amber Lin: That’s all from my side.
103 00:18:38.880 ⇒ 00:18:39.480 Uttam Kumaran: Okay.
104 00:18:39.870 ⇒ 00:18:40.200 Amber Lin: Yeah.
105 00:18:40.710 ⇒ 00:18:46.569 Robert Tseng: Yeah, we should. We should definitely, if anybody I mean, I also mean, we can talk Pto. But we should
106 00:18:46.980 ⇒ 00:18:51.819 Robert Tseng: make sure we don’t. If this we all go off at the same time we’re we’re screwed, so we should.
107 00:18:51.820 ⇒ 00:18:52.290 Uttam Kumaran: Yeah, let’s.
108 00:18:52.290 ⇒ 00:18:52.830 Robert Tseng: Yeah.
109 00:18:52.830 ⇒ 00:18:55.439 Uttam Kumaran: Let’s discuss tomorrow. Yeah, I just put that down.
110 00:18:55.440 ⇒ 00:18:56.120 Robert Tseng: Yeah.
111 00:18:56.790 ⇒ 00:18:57.330 Uttam Kumaran: Yeah.
112 00:18:59.623 ⇒ 00:19:02.169 Uttam Kumaran: Okay. Cool. Yeah. Robert, you wanna go.
113 00:19:03.001 ⇒ 00:19:08.078 Robert Tseng: Yeah, I guess I’ll just I just threw a few things on there that were top of mind for me.
114 00:19:08.660 ⇒ 00:19:16.010 Robert Tseng: yeah. So I guess priority one on the even side. Fortunately I kind of took a step back this week, which is.
115 00:19:16.010 ⇒ 00:19:16.960 Uttam Kumaran: Yes.
116 00:19:16.960 ⇒ 00:19:17.610 Robert Tseng: Good.
117 00:19:17.610 ⇒ 00:19:18.050 Amber Lin: Day.
118 00:19:18.297 ⇒ 00:19:20.280 Robert Tseng: I think my time has been going on.
119 00:19:20.280 ⇒ 00:19:22.780 Uttam Kumaran: Someone else is talking to. Josh. That’s good. That’s.
120 00:19:22.780 ⇒ 00:19:24.579 Robert Tseng: Yeah. The fact that you know amber.
121 00:19:24.580 ⇒ 00:19:25.360 Uttam Kumaran: How you man gosh!
122 00:19:25.360 ⇒ 00:19:26.830 Uttam Kumaran: Copy me!
123 00:19:26.830 ⇒ 00:19:49.069 Robert Tseng: Yeah. I think oasis on the Remo. Okay. So we keep calling Emr. So it acquired remote and like, there’s a doc here that we need to walk through like, I think, Derek’s, we’re, gonna I think we should not view them as the same client. These are 2 clients. It basically gave us a referral to another client, and we’re gonna pitch them at 10 KA month. That’s what we’re gonna do.
124 00:19:49.140 ⇒ 00:20:08.350 Robert Tseng: And yeah, I mean? It’s a. It’s a different client. It’s a Saas client. They’re building a they, you know, they basically are, you know, Eden acquired them. But they’re building the Emr software for Eden. They’re not as good as I mean, they’re. I don’t think they’re that great. And so they need like a dB architect
125 00:20:08.779 ⇒ 00:20:22.100 Robert Tseng: so that they can get their whole production data in a place. You know, we just work with analytics replicas at this point. So like we’re not, we don’t really have anyone staff that’s like neat that can really drive that strategy.
126 00:20:23.310 ⇒ 00:20:41.050 Robert Tseng: I think that you know you didn’t split on this. Adam knows that like he needs another person. Josh thinks we can just repurpose our team to go and do that work for them. And so I I think I just by the end of the week I want to level set with them like, no, this is a different different skill set. We’re not going to.
127 00:20:41.250 ⇒ 00:20:52.260 Robert Tseng: I don’t want to wind down our our analytics work to go and like, make our team go and support remote like I don’t. I don’t think that we would be successful in that. So.
128 00:20:52.420 ⇒ 00:20:57.289 Uttam Kumaran: I also agree, like, I agree, for 2 reasons. One, this work is a lot slower.
129 00:20:58.035 ⇒ 00:20:59.760 Uttam Kumaran: And like, really.
130 00:21:00.140 ⇒ 00:21:08.309 Uttam Kumaran: yes, like, I think the analytics team is A is a consumer of the output. But apart from that, like, no need to throw another work stream in there.
131 00:21:10.337 ⇒ 00:21:13.609 Uttam Kumaran: You know, to do more like data engineering, consulting stuff.
132 00:21:14.010 ⇒ 00:21:20.390 Robert Tseng: Yeah, I mean, maybe, like one or 2 people on our team could like double dip into that and help there.
133 00:21:20.875 ⇒ 00:21:42.340 Robert Tseng: But you know. I think we you know Adam thinks that we can. We can just direct the remote team on what to do. So like we can leverage their engineering team. So I feel like this is just like a super senior person. I guess it’s like more of a strategy engagement to start, and I don’t expect it to be heavy on engineering for us. So
134 00:21:42.837 ⇒ 00:21:47.489 Robert Tseng: anyway, like, I think that’s that’s a pitch that we should try to
135 00:21:47.770 ⇒ 00:21:49.619 Robert Tseng: kind of send them by the end of the week.
136 00:21:51.660 ⇒ 00:21:57.842 Robert Tseng: yeah. And then on the go to market OP. Side. I think it’s been great. I’ve been able to spend a lot of time here.
137 00:21:58.420 ⇒ 00:22:03.079 Robert Tseng: I I mean, I don’t think I’ve talked much about with the other.
138 00:22:03.330 ⇒ 00:22:08.330 Robert Tseng: with, you know. Wish and amber, but I can. Just I I send a request to share my screen.
139 00:22:09.510 ⇒ 00:22:10.559 Uttam Kumaran: Oh, yeah. Yeah.
140 00:22:11.010 ⇒ 00:22:14.000 Robert Tseng: Yeah, I mean, I just wanna show you a bit of what I’m what I’m doing. So
141 00:22:14.418 ⇒ 00:22:30.789 Robert Tseng: yeah, I think from here, like, these are the weekly metrics that we’ve set up for like to go to market team and like kind of what we’re trying to hit now. So I mean it’ll take some. It’s not like we weren’t doing these things before, but maybe we weren’t really setting like targets to it. So yeah, like
142 00:22:31.020 ⇒ 00:22:54.819 Robert Tseng: making sure that our, you know, we’re not just posting consistently, but we’re amplifying it with comments on posts building out different playbooks to help with the messaging, as Sid and Hannah are drafting responses to partners and stuff. And so like, yeah, there’s all these sections here. You can go and look at everything here. But as far I’ve been able to. I put that together last week, and teams have been executing on it.
143 00:22:54.850 ⇒ 00:23:03.949 Robert Tseng: And yeah, I mean, I think I’m seeing improvements daily there. So I’m happy with that. We’re gonna keep. Keep pushing there.
144 00:23:04.527 ⇒ 00:23:11.629 Robert Tseng: There’s 2 playbooks specifically that I want to build out. One is like asking our existing network
145 00:23:12.071 ⇒ 00:23:32.980 Robert Tseng: to make intros, I think rather than just doing cold dms, only like I think we should try to. We are between Utam and I. We’re already connected to, like, you know, 8,000 people, whatever. So like we should just, you know, there must be some distance from there? We can ask. That’s just a second second degree connection away. So
146 00:23:33.464 ⇒ 00:23:51.550 Robert Tseng: that. And then also the age old. How do we convert like a full time, you know, position into a consulting role. And there’s a couple of conversations that I’m in where I’m kind of. I’m testing different messaging there to try to see if we can have something that’s more repeatable.
147 00:23:52.690 ⇒ 00:23:53.070 Uttam Kumaran: Okay.
148 00:23:53.230 ⇒ 00:23:56.172 Robert Tseng: And then, yeah, I’m running our playbook by
149 00:23:57.030 ⇒ 00:24:09.239 Robert Tseng: our advisors, and so they want it to be. They want to consume it in a deck. And so I just need to grab some screenshots of some of the stats that we are measuring, and hopefully they’ll give some feedback on on that
150 00:24:09.775 ⇒ 00:24:20.899 Robert Tseng: but that was a relationship. I was like trying to kind of drum up again, because we haven’t been leveraging Pixel for for go to market stuff at least lately. So I wanted to get back on there.
151 00:24:21.050 ⇒ 00:24:22.749 Robert Tseng: I wanted to re-engage with them.
152 00:24:23.379 ⇒ 00:24:43.489 Robert Tseng: Another new client side not going. Well, I think. Yeah, it was gonna be a challenge to stretch across other clients. Yeah, I think Annie just completely didn’t do anything on spark plug. So I don’t know. I thought I gave her the opportunity to go and and and put something together could have been anything, and I would have.
153 00:24:43.640 ⇒ 00:24:44.499 Robert Tseng: I would have like.
154 00:24:44.500 ⇒ 00:24:45.440 Uttam Kumaran: That document.
155 00:24:46.400 ⇒ 00:24:52.799 Robert Tseng: Yeah, I mean, it’s just a it’s just a doc. And I mean, I don’t know. Like to me the outline was like.
156 00:24:52.960 ⇒ 00:25:13.680 Robert Tseng: I don’t know. She probably gpt most of it. It’s like, Oh, track Xyz events and build Xyz reports. And so I was like, Okay, build it. And then she didn’t build anything, which is, which is fine. She’s never used the tool before, but I would have rather her spent her time like trying to actually dig in and build some stuff. But if she’s just gonna give up before putting out anything, then
157 00:25:13.820 ⇒ 00:25:16.879 Robert Tseng: I mean, yeah, I’m gonna end up just finishing it today.
158 00:25:18.340 ⇒ 00:25:23.400 Robert Tseng: Yeah. So I don’t know. Like, I think, yeah, she’s she’s just
159 00:25:23.910 ⇒ 00:25:29.309 Robert Tseng: she. I’m sure she could learn. But she just needs more hand holding there, which is fine. I think
160 00:25:29.470 ⇒ 00:25:29.990 Robert Tseng: I don’t know.
161 00:25:29.990 ⇒ 00:25:32.700 Robert Tseng: We’re gonna just doing sorry.
162 00:25:35.630 ⇒ 00:25:38.689 Amber Lin: Oh, no! Your term sounds like a robot.
163 00:25:39.514 ⇒ 00:25:39.980 Robert Tseng: Yeah.
164 00:25:40.000 ⇒ 00:25:40.830 Amber Lin: We? We don’t.
165 00:25:41.550 ⇒ 00:25:43.780 Amber Lin: Can you dial in, or is it better now?
166 00:25:43.920 ⇒ 00:25:45.100 Robert Tseng: Is it any better.
167 00:25:45.100 ⇒ 00:25:45.630 Amber Lin: It’s better now.
168 00:25:45.630 ⇒ 00:25:46.560 Uttam Kumaran: Yeah, better.
169 00:25:46.560 ⇒ 00:25:55.339 Uttam Kumaran: I just like, I just like stood up to walk around. Okay, I’ll sit down. No, I was saying, the coaching stuff should help there. But
170 00:25:55.460 ⇒ 00:26:01.410 Uttam Kumaran: yeah, it is what it is. Like, we’re we’re gonna find another analyst. And yeah.
171 00:26:02.670 ⇒ 00:26:11.718 Robert Tseng: Yeah, on the insomnia stuff. I think Amber’s been doing a good job staying on top of it there. Yeah, it’s an early stage client. We’re just there’s like,
172 00:26:13.070 ⇒ 00:26:24.200 Robert Tseng: just opening cans of worms trying to find the right people, at least on my side. Like my main stakeholder is going maternity. Cmo has her own agenda, and
173 00:26:24.320 ⇒ 00:26:48.330 Robert Tseng: out of tech, like I’m slowly peeling back the layers trying to figure things out. So the actual amount of execution. Work is very little and it seems like, you know, the team is being resource to go and do that. It’s just kind of just filling in some spreadsheets for now and then. Yeah, we want to automate some of this reporting. So yeah, I think this will keep picking up, but I think it’s good. As long as I can spend a couple of hours
174 00:26:48.740 ⇒ 00:26:56.259 Robert Tseng: a week talking to people there. I think you know we I’m still trying to build up a case for
175 00:26:56.560 ⇒ 00:26:59.330 Robert Tseng: the extension past past the 1st month. So.
176 00:26:59.570 ⇒ 00:27:03.539 Uttam Kumaran: Yeah, I will say on on this piece. This is the 1st client that
177 00:27:04.980 ⇒ 00:27:07.709 Uttam Kumaran: so many people I’ve heard of
178 00:27:08.423 ⇒ 00:27:14.269 Uttam Kumaran: like beyond any client that I think we’ve had so far like, I think, this athletic greens
179 00:27:14.480 ⇒ 00:27:21.660 Uttam Kumaran: from my past experience, probably the only one I’ve seen that’s like at this reach, and I don’t know. Maybe that’s just more on like the consumer side. But
180 00:27:22.030 ⇒ 00:27:26.879 Uttam Kumaran: like, I think, a very strong brand for us to nail like, there’s a lot of brand equity there.
181 00:27:27.710 ⇒ 00:27:28.590 Amber Lin: Totally.
182 00:27:30.790 ⇒ 00:27:36.249 Robert Tseng: Yeah, I think there’s a lot of opportunity. I think I just have to find the right advocates.
183 00:27:37.150 ⇒ 00:27:44.630 Robert Tseng: yeah, I’m like talking to their head of tech next week. I already got access to Meta Base dug in. They have like 200 models. They don’t do anything like
184 00:27:45.168 ⇒ 00:28:00.391 Robert Tseng: with dbt, so it’s all just like straight production replica that goes into Meta base. And nobody can read it. So like, there’s there’s like, there’s like a lot of good data work opportunity that I would like to just kind of expose. And
185 00:28:00.840 ⇒ 00:28:26.999 Robert Tseng: yeah. And the fact that it, this automation that we’re doing for this report was kind of the catalyst was that the marketing team was frustrated, that it’s been 6 months, and the data team hasn’t put put it together for them yet. So if we can come in and automate this reporting within one month, which is already very slow, in my opinion, because it’s not that hard. I think that’s we’re just that’s gonna it’s gonna win us a lot of Brownie points to keep keep working with this team.
186 00:28:28.640 ⇒ 00:28:29.220 Uttam Kumaran: Great.
187 00:28:29.590 ⇒ 00:28:30.170 Robert Tseng: Yeah,
188 00:28:32.300 ⇒ 00:28:41.729 Robert Tseng: yeah. So. And then I think I didn’t mention Ellie. We’re still like, I don’t know. Still passing like documents back and forth like I. They sent me something.
189 00:28:41.910 ⇒ 00:28:47.840 Robert Tseng: I haven’t finished reading and signing their document, but I guess I’m I’m fine with them, not starting until next week.
190 00:28:49.290 ⇒ 00:28:49.870 Uttam Kumaran: Okay.
191 00:28:54.580 ⇒ 00:28:56.670 Uttam Kumaran: okay, great, yeah. I think.
192 00:28:57.764 ⇒ 00:29:01.130 Uttam Kumaran: I just pinged again to try to continue our
193 00:29:01.580 ⇒ 00:29:05.616 Uttam Kumaran: product analyst campaign. And yeah, we just need someone there.
194 00:29:06.420 ⇒ 00:29:11.570 Uttam Kumaran: I’ll send some more notes over. And actually I did get some
195 00:29:11.720 ⇒ 00:29:19.729 Uttam Kumaran: should have hit these people up. I did get 2 recommendations from a friend of mine that’s at shopify for some data analyst folks. But I did not hit them up.
196 00:29:20.530 ⇒ 00:29:28.560 Uttam Kumaran: Let me call them today. But okay, heard great wait. You wanna go.
197 00:29:29.930 ⇒ 00:29:30.520 Awaish Kumar: Yep.
198 00:29:32.410 ⇒ 00:29:33.490 Awaish Kumar: So
199 00:29:36.740 ⇒ 00:29:44.600 Awaish Kumar: for me, like like the point number one, which is already discussed like regarding the real demo, and
200 00:29:45.240 ⇒ 00:29:46.400 Awaish Kumar: oh!
201 00:29:47.070 ⇒ 00:29:50.940 Awaish Kumar: From our side. And I agree with the Rob Roberts conclusion. And that’s what I
202 00:29:51.100 ⇒ 00:29:53.509 Awaish Kumar: also wrote in the document that we
203 00:29:53.770 ⇒ 00:29:58.090 Awaish Kumar: are like kind of as a you design the
204 00:29:58.800 ⇒ 00:30:02.070 Awaish Kumar: help them maybe design and drive the project and not
205 00:30:02.680 ⇒ 00:30:06.129 Awaish Kumar: get our hands on the implementation of the back end work.
206 00:30:06.440 ⇒ 00:30:11.180 Awaish Kumar: And because we don’t have any DVD.
207 00:30:11.980 ⇒ 00:30:14.429 Awaish Kumar: Architecture. But this is more like
208 00:30:14.610 ⇒ 00:30:17.950 Awaish Kumar: setting up a back end system for a.
209 00:30:17.950 ⇒ 00:30:18.390 Uttam Kumaran: Is this?
210 00:30:18.390 ⇒ 00:30:18.750 Awaish Kumar: See that!
211 00:30:18.750 ⇒ 00:30:20.389 Uttam Kumaran: Back in for the product.
212 00:30:20.860 ⇒ 00:30:22.080 Awaish Kumar: Yeah, yeah.
213 00:30:22.080 ⇒ 00:30:23.940 Uttam Kumaran: Like back end postgres.
214 00:30:24.270 ⇒ 00:30:25.310 Awaish Kumar: Yes, yes.
215 00:30:25.770 ⇒ 00:30:26.882 Uttam Kumaran: Okay, so let me
216 00:30:27.623 ⇒ 00:30:31.419 Uttam Kumaran: I haven’t read the doc. But let me read that today, and then I will
217 00:30:31.640 ⇒ 00:30:34.609 Uttam Kumaran: put some feelers out, I’ll I’ll call sightsight, too.
218 00:30:35.240 ⇒ 00:30:38.590 Awaish Kumar: So Remo is a pro. For example, a a platform
219 00:30:38.720 ⇒ 00:30:41.150 Awaish Kumar: kind of alternative to bask, for example.
220 00:30:41.260 ⇒ 00:30:49.940 Awaish Kumar: where multiple clients can set up sell their product, like Eden and anyone else can also be a client, and they can also, like run their.
221 00:30:50.560 ⇒ 00:30:54.360 Awaish Kumar: It seems like a sailing system
222 00:30:54.710 ⇒ 00:31:10.240 Awaish Kumar: on there as well, so it’s kind of they need help with the back end of the product itself, along with setting up the all the like web books as as must do so like implementing all of that, and then bringing
223 00:31:10.410 ⇒ 00:31:19.320 Awaish Kumar: by providing a way to basically send the events from the system to something is, oh.
224 00:31:20.020 ⇒ 00:31:22.499 Awaish Kumar: so that’s it. And
225 00:31:25.043 ⇒ 00:31:34.570 Awaish Kumar: yeah, no point number 2 regarding polytomic connectors. Like they they already said they are working on Etl side, and.
226 00:31:34.570 ⇒ 00:31:37.090 Uttam Kumaran: Yeah, what was the what was the urgency thing that came up.
227 00:31:38.570 ⇒ 00:31:47.930 Awaish Kumar: Like like, Robert mentioned that like crossing data, we really need that connector, like, maybe at the end of the week. So we can start working on it.
228 00:31:47.930 ⇒ 00:31:48.310 Amber Lin: Yeah.
229 00:31:48.310 ⇒ 00:31:49.299 Awaish Kumar: In the next week.
230 00:31:50.871 ⇒ 00:31:52.029 Robert Tseng: Okay, yeah. I don’t think
231 00:31:52.030 ⇒ 00:32:01.140 Robert Tseng: they told us they could build anything within a week. And we made this request was last week, 2 weeks ago, so to hear that it was 2 weeks away was just kind of like. Well.
232 00:32:01.720 ⇒ 00:32:02.110 Uttam Kumaran: I mean.
233 00:32:02.110 ⇒ 00:32:02.710 Robert Tseng: But I’ve seen.
234 00:32:03.080 ⇒ 00:32:05.340 Uttam Kumaran: When did we? When did we tell them?
235 00:32:08.260 ⇒ 00:32:10.419 Uttam Kumaran: I feel like we thought we told him this week.
236 00:32:12.445 ⇒ 00:32:13.619 Robert Tseng: I don’t know. I don’t.
237 00:32:13.620 ⇒ 00:32:18.240 Uttam Kumaran: Oh, Wednesday, yeah, I guess. Oh, loop, loop!
238 00:32:18.490 ⇒ 00:32:19.180 Amber Lin: No.
239 00:32:19.180 ⇒ 00:32:19.640 Uttam Kumaran: Or.
240 00:32:19.640 ⇒ 00:32:25.490 Amber Lin: I think we told them for urban stems this week. We told them, probably for Eden before.
241 00:32:26.020 ⇒ 00:32:29.930 Uttam Kumaran: I told them, yeah, I guess I confirmed on Thursday.
242 00:32:30.680 ⇒ 00:32:42.550 Uttam Kumaran: Yeah, okay, I mean, we’ll put pressure on. It’s that’s fat. Even a week is like, kind of pretty fast like, but you’re right. Okay, we’ll keep. Just keep pressure on whatever
243 00:32:42.840 ⇒ 00:32:45.760 Uttam Kumaran: they’ll get us something like, yeah.
244 00:32:46.730 ⇒ 00:32:50.415 Awaish Kumar: Seat inside. I think that’s much more for
245 00:32:51.690 ⇒ 00:32:54.509 Awaish Kumar: of a priority right now, as I see it.
246 00:32:54.720 ⇒ 00:33:02.220 Awaish Kumar: like putting data to not stream platform, and I’m spiking it right now. We we don’t have any answer yet, like.
247 00:33:03.290 ⇒ 00:33:06.430 Awaish Kumar: so maybe I will finish it today, and then
248 00:33:08.120 ⇒ 00:33:14.069 Awaish Kumar: by tomorrow we can see like, we can ask, ask if they can build it, or
249 00:33:14.260 ⇒ 00:33:16.310 Awaish Kumar: we ourselves can find a solution.
250 00:33:17.053 ⇒ 00:33:21.229 Awaish Kumar: Number 3 is just an update on like Emr.
251 00:33:21.340 ⇒ 00:33:28.809 Awaish Kumar: Apart from Emr index, is also a project, a separate project in the on the eating side.
252 00:33:30.160 ⇒ 00:33:31.860 Awaish Kumar: and we’ll do
253 00:33:32.716 ⇒ 00:33:43.349 Awaish Kumar: and they have just kind of completed this project, and the data is already coming in. So we might start like, maybe you can start working on modeling stuff.
254 00:33:44.960 ⇒ 00:33:50.599 Awaish Kumar: I don’t know if you want to like. Put put that on a on a list of priorities for Eden.
255 00:33:51.100 ⇒ 00:33:52.030 Awaish Kumar: Goodbye.
256 00:33:54.060 ⇒ 00:33:54.790 Uttam Kumaran: Okay.
257 00:33:55.950 ⇒ 00:33:56.350 Awaish Kumar: And.
258 00:33:56.350 ⇒ 00:33:59.840 Uttam Kumaran: Is there a is there? Is that a set? Is there a doc for that? Or is that something else?
259 00:34:02.820 ⇒ 00:34:03.370 Awaish Kumar: Surely.
260 00:34:03.370 ⇒ 00:34:05.329 Amber Lin: Anything you guys are talking about.
261 00:34:06.250 ⇒ 00:34:07.820 Awaish Kumar: It’s kind of a race.
262 00:34:07.980 ⇒ 00:34:20.750 Awaish Kumar: I have simple data, kind of all the like. It’s kind of questionnaire which we fill and the all the data and answers and questions like all that is all coming in into a table from via segment.
263 00:34:20.909 ⇒ 00:34:25.140 Awaish Kumar: So it’s already there. We can like, see the data and everything
264 00:34:25.946 ⇒ 00:34:33.850 Awaish Kumar: it like it was kind of asked few months back from their marketing team. They wanted to understand how
265 00:34:35.429 ⇒ 00:34:36.520 Awaish Kumar: okay.
266 00:34:37.010 ⇒ 00:34:54.859 Awaish Kumar: like in want to understand how people answer the questions and things like that. So we didn’t have the ability to do that before. But now in the new setup we might have. So it’s it’s just in the testing. This is just the test data right now. So we don’t have any urgency. But we can start
267 00:34:55.350 ⇒ 00:35:01.550 Awaish Kumar: focusing on that, like once it goes, live. You should have the models and the dashboards ready.
268 00:35:03.720 ⇒ 00:35:04.310 Uttam Kumaran: Okay
269 00:35:06.085 ⇒ 00:35:13.749 Uttam Kumaran: on your next point for ABC, yeah, honestly, like, I’m there, we have a lot of great data for them. And
270 00:35:13.930 ⇒ 00:35:19.200 Uttam Kumaran: like, I’m still not seeing I’m seeing what’s in the dashboard. But
271 00:35:19.330 ⇒ 00:35:23.339 Uttam Kumaran: I’m still not seeing like any sort of like analysis on that work.
272 00:35:24.174 ⇒ 00:35:28.650 Uttam Kumaran: I don’t know amber, if, like, this is again like an any problem.
273 00:35:28.850 ⇒ 00:35:31.759 Uttam Kumaran: But like, I’ve asked so many times for like.
274 00:35:32.110 ⇒ 00:35:36.620 Uttam Kumaran: can someone analyze like that data and like, ask some questions about
275 00:35:36.730 ⇒ 00:35:41.429 Uttam Kumaran: the types of calls they’re getting what our AI is doing, what it’s not. And it seems like
276 00:35:42.340 ⇒ 00:35:50.380 Uttam Kumaran: she doesn’t give a shit about that. So I’m kind of in. I’m I’m at the point where I’m gonna hand all the data work on ABC, that Mustafa Casey.
277 00:35:50.610 ⇒ 00:35:55.350 Uttam Kumaran: and they’ll they’ll they’ll bust through that wide open like they’ll.
278 00:35:55.350 ⇒ 00:35:58.920 Amber Lin: Okay, I can. I? I’m tab here. Should.
279 00:35:58.920 ⇒ 00:36:09.040 Uttam Kumaran: Because they care. They actually give a shit about this. So I’m sort of like, kind of done asking, because it’s like it’s running basic SQL queries to just find trends in the data.
280 00:36:10.050 ⇒ 00:36:11.700 Uttam Kumaran: Like, so.
281 00:36:12.410 ⇒ 00:36:16.349 Amber Lin: Yeah, let me do that. Tomorrow, I think.
282 00:36:16.500 ⇒ 00:36:21.729 Amber Lin: would love you to come to the meeting with Yvet to talk about the 8 by 8 AI
283 00:36:22.644 ⇒ 00:36:28.269 Amber Lin: but noted on the dashboard insights. I’ll make sure to
284 00:36:28.760 ⇒ 00:36:34.339 Amber Lin: do that, especially now that we have the transcript Api, which I’m still waiting on, boss. Step on.
285 00:36:34.910 ⇒ 00:36:35.760 Uttam Kumaran: Yeah, like.
286 00:36:36.130 ⇒ 00:36:46.429 Uttam Kumaran: one thing that could be helpful is like, if we can start a document around like questions that we want answered on the ABC data.
287 00:36:46.660 ⇒ 00:36:47.200 Amber Lin: Thank you.
288 00:36:47.400 ⇒ 00:36:48.300 Uttam Kumaran: And then
289 00:36:48.620 ⇒ 00:36:53.670 Uttam Kumaran: the team can go answer those like I don’t. I’m not really concerned. I think the dashboard we have is fine, but
290 00:36:53.860 ⇒ 00:37:06.460 Uttam Kumaran: the client is not asking good questions because they’re themselves not very data driven. But I have about a hundred questions that would blow their minds if we could get answered. So you can give me if we can just write a doc about like
291 00:37:06.740 ⇒ 00:37:10.400 Uttam Kumaran: ABC, like you could just do. Q. 3. Like.
292 00:37:11.560 ⇒ 00:37:16.800 Uttam Kumaran: Data questions. I will just write there and then those can all get ticketed and and answered.
293 00:37:16.960 ⇒ 00:37:23.270 Uttam Kumaran: and you’ll that’ll give you like so much fodder for your decks for the meeting, so you’ll be
294 00:37:23.570 ⇒ 00:37:25.360 Uttam Kumaran: set up. Well, versus like.
295 00:37:26.320 ⇒ 00:37:33.880 Uttam Kumaran: yeah, like, whatever it is. Now, I just don’t know how you can look at the data like that and not be curious about all these things like that.
296 00:37:33.880 ⇒ 00:37:34.390 Awaish Kumar: Like.
297 00:37:34.390 ⇒ 00:37:35.040 Uttam Kumaran: That’s right.
298 00:37:35.790 ⇒ 00:37:39.089 Awaish Kumar: Yeah, also, like, we didn’t have any such kind of
299 00:37:39.310 ⇒ 00:37:43.489 Awaish Kumar: make it like, for example, for data platform, we when we ask for
300 00:37:43.850 ⇒ 00:37:46.290 Awaish Kumar: like, we have this data. Let’s
301 00:37:47.310 ⇒ 00:37:49.864 Awaish Kumar: like, let’s find out what kind of
302 00:37:50.832 ⇒ 00:38:02.899 Awaish Kumar: metrics there are for, like, normally people want to measure as a as part of the productivity dashboard, and like we do have some that was now like from
303 00:38:03.010 ⇒ 00:38:10.989 Awaish Kumar: Flash Day, for example, and which basically cover like almost like everything we
304 00:38:11.360 ⇒ 00:38:15.999 Awaish Kumar: if we have something like that and ask us someone.
305 00:38:16.000 ⇒ 00:38:19.840 Uttam Kumaran: Dude it requires like it requires some interest. Like.
306 00:38:19.980 ⇒ 00:38:43.449 Uttam Kumaran: if, for example, you’re gonna ask me, how do you measure the productivity of business? We all we all know what like. We all have some sense of what that means like, or ask AI like, how would I measure the productivity of business these 4 sources. It’ll give you all the you don’t need me to tell me. I would like to see how many linear tickets we close today, like, I’m not like someone special. And that’s like a unique idea. But this is just where I’m like.
307 00:38:44.862 ⇒ 00:38:46.570 Uttam Kumaran: feel like that is the right
308 00:38:46.570 ⇒ 00:38:53.950 Uttam Kumaran: of having to write some basic stuff down where I I haven’t read the Vosh dev art thing, but I will, but I just know it’s like
309 00:38:54.330 ⇒ 00:38:57.260 Uttam Kumaran: it’s just so painful for me sometimes where I’m like
310 00:38:57.930 ⇒ 00:39:10.089 Uttam Kumaran: can especially. This is way more on the on the analysis side, which I think we’re gonna start to correct one way or another. But it’s just so painful that people just aren’t interested in like the business problems they’re trying to. We’re trying to solve. Like.
311 00:39:10.400 ⇒ 00:39:11.969 Uttam Kumaran: I don’t know.
312 00:39:17.350 ⇒ 00:39:24.350 Uttam Kumaran: Yeah. And then, okay, so for for priority. 5.
313 00:39:24.766 ⇒ 00:39:31.420 Uttam Kumaran: Yeah, I guess. Like, I was, my, one of my questions was, gonna be on like, tell me about the candidates that you interviewed. Was anyone good.
314 00:39:34.920 ⇒ 00:39:36.592 Amber Lin: On my side.
315 00:39:37.270 ⇒ 00:39:44.090 Amber Lin: I I had it into. I was scheduled with Lester on Monday. Didn’t show up, so
316 00:39:44.720 ⇒ 00:39:52.459 Amber Lin: moving moved him to Thursday, today I’m meeting with Karen later, and then
317 00:39:53.688 ⇒ 00:39:58.160 Amber Lin: thursday. I’m meeting Lester and Blas, Reyna
318 00:39:58.980 ⇒ 00:40:06.390 Amber Lin: and Friday. I’m talking to Usama, and then I’m also talking to Emily Ward.
319 00:40:07.570 ⇒ 00:40:10.560 Uttam Kumaran: But you already met with Usama. Right? Is this like what? What is this interview.
320 00:40:11.000 ⇒ 00:40:15.020 Amber Lin: This is the second second interview. The 1st one was like a screening.
321 00:40:15.020 ⇒ 00:40:15.460 Uttam Kumaran: Okay.
322 00:40:15.460 ⇒ 00:40:18.909 Amber Lin: Not totally sure if I want to talk to him.
323 00:40:19.160 ⇒ 00:40:19.910 Uttam Kumaran: Okay.
324 00:40:20.423 ⇒ 00:40:28.130 Amber Lin: But like, but but we’re already we haven’t signed with Vinay yet, like that’s what
325 00:40:28.630 ⇒ 00:40:34.219 Amber Lin: that’s what my concern is like until we sign with Vinay. I don’t want to stop talking.
326 00:40:34.220 ⇒ 00:40:36.159 Uttam Kumaran: Then why don’t you just punt it to next week?
327 00:40:36.160 ⇒ 00:40:36.530 Amber Lin: Okay.
328 00:40:36.530 ⇒ 00:40:38.780 Uttam Kumaran: Focus on Emily, hunt it to next week.
329 00:40:38.780 ⇒ 00:40:39.649 Amber Lin: Okay. I’ll do that.
330 00:40:39.650 ⇒ 00:40:42.410 Uttam Kumaran: Like, just say, like, I’d like to re, I just want to reschedule. We’re busy.
331 00:40:42.410 ⇒ 00:40:47.489 Robert Tseng: Oh, I can’t believe Renee is gonna drive into the city to meet me tomorrow. I feel bad, but like.
332 00:40:48.020 ⇒ 00:40:51.269 Uttam Kumaran: Don’t feel bad. Dude. What? This is. A great opportunity.
333 00:40:53.780 ⇒ 00:40:54.560 Uttam Kumaran: Yeah, I’m like.
334 00:40:54.560 ⇒ 00:40:58.210 Robert Tseng: Trying to pick a pick a cafe for to to meet him at right now.
335 00:40:58.570 ⇒ 00:41:01.320 Uttam Kumaran: You can park right outside your place. You have ample parking.
336 00:41:05.440 ⇒ 00:41:13.620 Uttam Kumaran: No, I’m excited, dude. I’m I’m glad I’m I’m I’m well. I’m excited one way or another, we’ll find out the answer. But yeah.
337 00:41:14.300 ⇒ 00:41:15.029 Uttam Kumaran: let’s see.
338 00:41:15.030 ⇒ 00:41:20.100 Awaish Kumar: Yeah, from my side for the interviews I had met with
339 00:41:20.470 ⇒ 00:41:24.109 Awaish Kumar: to like almost everyone I met with, like.
340 00:41:24.290 ⇒ 00:41:27.671 Awaish Kumar: like I would say, like half of them were like,
341 00:41:28.510 ⇒ 00:41:31.899 Awaish Kumar: I didn’t have any relevant experiences on it.
342 00:41:32.020 ⇒ 00:41:33.720 Awaish Kumar: Haven’t been working on
343 00:41:33.990 ⇒ 00:41:40.639 Awaish Kumar: create relevant technologies. So they were interested in like they they are interested in. For example, working in AI or.
344 00:41:40.800 ⇒ 00:41:45.500 Uttam Kumaran: You know, they’re all everybody’s interested in working with us. That’s not the problem. Yeah.
345 00:41:45.500 ⇒ 00:41:55.699 Awaish Kumar: But I will find like, if they are doing any relevant work. We, the phone like for for these guys to do. And then
346 00:41:55.880 ⇒ 00:42:03.009 Awaish Kumar: 50% of them were like more like junior roles or mid level. But I’m just.
347 00:42:03.550 ⇒ 00:42:03.870 Amber Lin: Hmm.
348 00:42:03.870 ⇒ 00:42:05.590 Awaish Kumar: Like if when I.
349 00:42:05.590 ⇒ 00:42:06.319 Uttam Kumaran: So, yeah.
350 00:42:06.811 ⇒ 00:42:08.778 Awaish Kumar: Hear a lot of
351 00:42:09.650 ⇒ 00:42:14.689 Awaish Kumar: The the introduction is great and and all the great words, but they’re not very
352 00:42:14.800 ⇒ 00:42:18.490 Awaish Kumar: deep dive, and I’m gonna see like, it’s more like.
353 00:42:18.490 ⇒ 00:42:19.200 Amber Lin: Huh!
354 00:42:19.450 ⇒ 00:42:22.269 Awaish Kumar: Not so technical, or something like that.
355 00:42:22.270 ⇒ 00:42:29.230 Uttam Kumaran: So can you think about like, if we were to put some of those questions further, like upstream, what would they be?
356 00:42:29.790 ⇒ 00:42:31.500 Uttam Kumaran: Because for the technical folks.
357 00:42:32.482 ⇒ 00:42:35.709 Uttam Kumaran: It’s right now. It’s sort of all based on resume.
358 00:42:36.080 ⇒ 00:42:45.439 Uttam Kumaran: But of course, like, I think we know, some of that is just like fudge so like, what questions should we ask upfront, or have them record a loom for like? What questions do you ask in that part of that deep dive?
359 00:42:47.750 ⇒ 00:42:49.790 Awaish Kumar: Like I want to ask for.
360 00:42:50.020 ⇒ 00:42:57.700 Awaish Kumar: for example, like the mention of statistic, what? What have been working, what kind of projects they have recently worked.
361 00:43:00.390 ⇒ 00:43:09.030 Awaish Kumar: how how long they have been working with these tech stack, for example, someone says, I’ve I’ve been working with python for so how long
362 00:43:10.250 ⇒ 00:43:18.650 Awaish Kumar: and where? What is your like a professional experience doing, for example, data, engineering, or they work
363 00:43:20.120 ⇒ 00:43:36.910 Awaish Kumar: and and like, I would ask for what like the kind of complex. Give an example of a complex data pipeline you have wrote, or give me an example of a project which is like which you are most proud of, and then I start from there and then deep dive into more
364 00:43:37.080 ⇒ 00:43:40.790 Awaish Kumar: technical stuff. From what whatever they say.
365 00:43:40.790 ⇒ 00:43:56.150 Amber Lin: Okay, I mean, that sounds like we can at least in our screening. Ask them to tell us the years experience they have with specific things that we’re interested in, and that will help us screen out some of them. They can still exaggerate. But
366 00:43:56.290 ⇒ 00:43:59.850 Amber Lin: I just want to save and waste some time, because it takes a lot.
367 00:43:59.850 ⇒ 00:44:07.209 Uttam Kumaran: No, I agree. But like, this is where I actually needed, because I’ve been interviewing everybody. And this is helpful to hear you guys go through, because
368 00:44:07.320 ⇒ 00:44:16.200 Uttam Kumaran: I don’t think I was really good at like breaking this down. But this is helpful, and, in fact, what we’ll do is we’ll go one step further. I’ll just put these questions. So you have to record a loom
369 00:44:17.690 ⇒ 00:44:19.420 Uttam Kumaran: and answer all these questions.
370 00:44:19.560 ⇒ 00:44:21.919 Uttam Kumaran: And then that’s the filter, right? So
371 00:44:22.430 ⇒ 00:44:29.049 Uttam Kumaran: we’ll we’ll be able to watch that, and I’m sure like that’ll be a good filter for folks like it. It was helpful for the Pm. Stuff, so.
372 00:44:29.050 ⇒ 00:44:31.640 Amber Lin: Yeah. And if for us.
373 00:44:31.640 ⇒ 00:44:37.910 Uttam Kumaran: Yeah. So I’ll have Rico do. That. Was Zoran any good like for me. I thought he was doing some stuff with like
374 00:44:38.910 ⇒ 00:44:43.410 Uttam Kumaran: Google tag manager, and I don’t know. Maybe he could be better than Andrew like. What do you think.
375 00:44:43.600 ⇒ 00:44:46.070 Awaish Kumar: Yeah, he, yeah.
376 00:44:46.590 ⇒ 00:44:48.610 Awaish Kumar: So I don’t really have not data.
377 00:44:49.772 ⇒ 00:45:03.807 Awaish Kumar: So I had. I didn’t have very much experience with Gtm, so I couldn’t evaluate that part. But like he, he said, like he has extent extensive experience with Gtm stuff, and
378 00:45:04.390 ⇒ 00:45:10.020 Awaish Kumar: then like the other stuff which I have asked. Like with Python SQL. Modeling
379 00:45:10.480 ⇒ 00:45:13.801 Awaish Kumar: like he’s he has not been doing that like.
380 00:45:14.170 ⇒ 00:45:14.680 Uttam Kumaran: Yeah, yeah.
381 00:45:15.211 ⇒ 00:45:18.399 Awaish Kumar: Side. I like we can have
382 00:45:18.750 ⇒ 00:45:21.390 Awaish Kumar: one more interview with, for example.
383 00:45:22.500 ⇒ 00:45:26.710 Awaish Kumar: someone can Robert or Andrew, or something.
384 00:45:27.290 ⇒ 00:45:29.270 Uttam Kumaran: Is Andrew working out Robert.
385 00:45:33.430 ⇒ 00:45:34.470 Robert Tseng: I don’t know.
386 00:45:35.630 ⇒ 00:45:36.349 Robert Tseng: I think.
387 00:45:36.350 ⇒ 00:45:36.920 Uttam Kumaran: Okay.
388 00:45:41.180 ⇒ 00:45:50.580 Robert Tseng: Yeah, like, no, nobody’s really owning the work stream there, I mean. Henry came back, and I caught up with him earlier. He said that he tried to.
389 00:45:50.710 ⇒ 00:45:51.490 Robert Tseng: You know.
390 00:45:52.760 ⇒ 00:45:58.540 Robert Tseng: I I just feel like everything still, kind of comes back to me ultimately, like I have to say everything that’s going on. So like, I,
391 00:45:58.540 ⇒ 00:46:02.089 Robert Tseng: yeah, it’s like, Excuse city, like, what are these people doing?
392 00:46:02.530 ⇒ 00:46:04.290 Robert Tseng: Yeah. So
393 00:46:05.070 ⇒ 00:46:23.580 Robert Tseng: I mean, I told Henry, like, I need to make a call on him by by next week. But then also, I’m also like Dude Henry. If you don’t, I mean, he says he’s still traveling, he’ll he was like apologetic about things. But I was like, I don’t know dude. If you say you’re gonna be back this week, I’m expecting you to be online. If you just gotta be off for longer. Just tell me. But.
394 00:46:23.580 ⇒ 00:46:46.540 Uttam Kumaran: Dude. The one thing we learned from the from the last go around is like, I, just we need to be tighter on. If people are starting to drop the ball, especially new folks like he’s dropping the ball in deep, like one of the things I I wrote here is like he’s he’s dropping the ball in default. And I’m if if I don’t see something by the end of the week I’m gonna move him off that client, and I’ll take that work myself.
395 00:46:47.192 ⇒ 00:46:56.489 Uttam Kumaran: Because I would rather do it. I can honestly probably teach Mustafa how to do amplitude by the time he gets back from whatever country he’s in. So
396 00:46:57.210 ⇒ 00:47:00.590 Uttam Kumaran: I’m my tolerance is a lot. It’s just a lot lower because
397 00:47:01.110 ⇒ 00:47:04.900 Uttam Kumaran: I can’t deal. I think we’re just moving. We just have to have a higher standard. So.
398 00:47:05.910 ⇒ 00:47:11.790 Uttam Kumaran: If folks are gonna disappoint us like I’m no longer gonna like, say, let’s ask again, or let’s try something like.
399 00:47:12.030 ⇒ 00:47:17.259 Uttam Kumaran: move them out. Someone will figure. We’ll figure it out. We’ll get the next person, you know.
400 00:47:17.700 ⇒ 00:47:18.050 Robert Tseng: Yeah.
401 00:47:21.560 ⇒ 00:47:27.200 Amber Lin: He declined. Most of meetings this week. I really I so I couldn’t get a hold of him. I don’t see him.
402 00:47:27.200 ⇒ 00:47:31.649 Robert Tseng: Talked to him. His his flight back from Russia got like effed up, and he’s like.
403 00:47:31.650 ⇒ 00:47:32.190 Amber Lin: I see.
404 00:47:32.190 ⇒ 00:47:34.239 Robert Tseng: Like 5 layovers or whatever. So he’s not.
405 00:47:34.240 ⇒ 00:47:37.729 Uttam Kumaran: But why didn’t you say anything? Why didn’t you say something to anybody?
406 00:47:38.430 ⇒ 00:47:39.050 Robert Tseng: I don’t know.
407 00:47:42.650 ⇒ 00:48:02.620 Uttam Kumaran: Right like I I mean I get it. But like I also don’t care like work from the lounge, I don’t whatever, but like also just say something like you’re getting paid by a company to work on stuff like, just be like, I’m not around or like, sorry I’m not gonna take care of it instead. He didn’t respond. And then I pinged again. And then he said, I’ll get to it
408 00:48:03.120 ⇒ 00:48:09.820 Uttam Kumaran: asap, which is today at 6 am. And it’s it’s today at 4 pm. And there’s not. There’s nothing there.
409 00:48:10.440 ⇒ 00:48:22.006 Uttam Kumaran: I just like, I’m I just have seen this movie too many times, like, I’m like, 5th time, I’ve seen this fucking movie. I don’t want to watch this movie anymore.
410 00:48:22.580 ⇒ 00:48:25.030 Uttam Kumaran: So okay, I mean, we can. We can.
411 00:48:25.540 ⇒ 00:48:30.459 Uttam Kumaran: My thing is like, we gotta make a call on on Andrew and him next week.
412 00:48:30.690 ⇒ 00:48:36.079 Uttam Kumaran: I like, do you? Are you? You have like a decent sense of like what the Gtm. Work is.
413 00:48:36.370 ⇒ 00:48:45.609 Uttam Kumaran: or do we have a doc like? Can I send it to this guy, Zoran, and be like? Is this up your alley? I think he’d be cheaper, and this guy, like his energy, was good. I don’t know. I thought his energy was good.
414 00:48:47.180 ⇒ 00:48:50.470 Awaish Kumar: Yeah, he’s a good communicator, I would say, like we.
415 00:48:52.180 ⇒ 00:48:58.589 Awaish Kumar: He’s like, positive good communicator wanted like, but I get a feeling that is more like
416 00:48:59.100 ⇒ 00:49:04.030 Awaish Kumar: want to be solution architect driving the project, and beautiful.
417 00:49:05.990 ⇒ 00:49:12.079 Robert Tseng: Yeah, I think I think Andrew’s good, like he’s definitely able to communicate things, and, like the
418 00:49:12.190 ⇒ 00:49:25.510 Robert Tseng: whatever he says is enough to like, keep the team at day. But he’s not a lead on this project. He’s just like a he just want. He’s just the consultant. So like somebody still needs to drive the project forward.
419 00:49:25.900 ⇒ 00:49:27.860 Uttam Kumaran: But what does that mean? Like?
420 00:49:28.310 ⇒ 00:49:35.040 Uttam Kumaran: Speak to me in English? What is? What does that mean? I’m the consultant. I’m not the lead. Who’s like, what does that mean? Like, he’s not
421 00:49:35.040 ⇒ 00:49:36.290 Uttam Kumaran: yeah, he saying.
422 00:49:36.520 ⇒ 00:49:44.699 Robert Tseng: He’s just answering questions about how the tagging and tracking tech and process works. But he doesn’t make any decisions on like
423 00:49:45.420 ⇒ 00:49:51.780 Robert Tseng: what they should invest in. He does. He won’t comment on roadmap. He’s just kind of like, well, whatever you guys want like.
424 00:49:51.780 ⇒ 00:49:56.029 Uttam Kumaran: Is there? Is there a doc on the tag manager work we’re doing for them
425 00:49:56.480 ⇒ 00:50:01.590 Uttam Kumaran: or like? Is there any way we can shove free meetings into AI and get me like A.
426 00:50:01.830 ⇒ 00:50:05.189 Uttam Kumaran: Here’s the scope of the work, and I want to send it to the sky and be like, what do you think.
427 00:50:05.450 ⇒ 00:50:07.330 Robert Tseng: Okay, yeah, we could do that.
428 00:50:08.100 ⇒ 00:50:11.950 Uttam Kumaran: Just like, I mean, like what this like. We don’t need to make a call, but.
429 00:50:11.950 ⇒ 00:50:19.869 Robert Tseng: I was there. And I was like, Okay, we’re gonna do, Meta. And then we’re gonna do north beam, pinterest reddit like I made the decision.
430 00:50:20.010 ⇒ 00:50:30.949 Robert Tseng: And then we went, and we did. Meta, like Henry didn’t do it like I ended up just doing it with some of oasis help and then our north beam, which has been sitting there so like, I don’t know like it just
431 00:50:31.100 ⇒ 00:50:38.620 Robert Tseng: feels like no one. Yeah, no, no one like nothing. I I don’t see anybody owning that project so
432 00:50:41.300 ⇒ 00:50:46.960 Robert Tseng: I mean, I could just go back to it next week, and I’ll move it forward again. But I I’m not touching it this week.
433 00:50:46.960 ⇒ 00:50:49.419 Uttam Kumaran: No, no, no! If you do it, then someone’s gotta go.
434 00:50:49.770 ⇒ 00:50:50.330 Robert Tseng: Yeah.
435 00:50:50.820 ⇒ 00:50:52.160 Uttam Kumaran: Yeah. So
436 00:50:52.850 ⇒ 00:50:59.831 Uttam Kumaran: if I don’t know amber, if if you have a couple of transcripts that are good to like, do an overview of the go to market stuff.
437 00:51:00.490 ⇒ 00:51:01.890 Uttam Kumaran: tag, manager stuff.
438 00:51:02.498 ⇒ 00:51:03.850 Awaish Kumar: And you can decide.
439 00:51:04.650 ⇒ 00:51:06.950 Amber Lin: Probably Robert has that recording.
440 00:51:07.420 ⇒ 00:51:07.950 Amber Lin: I think.
441 00:51:07.950 ⇒ 00:51:13.289 Awaish Kumar: What kind of work we are doing, at least that really Google tag manager. But it’s more like
442 00:51:13.550 ⇒ 00:51:19.489 Awaish Kumar: your Ctl for marketing marketing tools like putting data to CIO to
443 00:51:19.930 ⇒ 00:51:23.860 Awaish Kumar: North Beam and do like maybe Meta.
444 00:51:24.100 ⇒ 00:51:24.610 Awaish Kumar: But.
445 00:51:24.610 ⇒ 00:51:25.360 Robert Tseng: Yeah, it’s not.
446 00:51:25.360 ⇒ 00:51:26.410 Robert Tseng: It’s not pure.
447 00:51:26.410 ⇒ 00:51:40.039 Robert Tseng: It’s not pure Google tag, manager work. I mean, I don’t want to. I mean, Andrew was like, yeah, I’ll do the audit. I’ll delete this and that, clean it up like, we don’t really need that like, I don’t think that’s I don’t. Yeah. So we I
448 00:51:40.610 ⇒ 00:51:41.830 Robert Tseng: I’m just having him. QA.
449 00:51:41.830 ⇒ 00:51:50.240 Robert Tseng: I don’t worry about like I don’t care whether it’s reverse detail or tag manager like. Whatever it is. I’m gonna send this guy and be like.
450 00:51:50.380 ⇒ 00:51:52.620 Uttam Kumaran: What parts of this can you do?
451 00:51:52.770 ⇒ 00:51:54.339 Uttam Kumaran: And like, that’s it.
452 00:51:54.767 ⇒ 00:51:59.380 Uttam Kumaran: Cause, if we start being? Yeah, I don’t know. Just like, yeah.
453 00:52:01.600 ⇒ 00:52:02.270 Robert Tseng: Yeah.
454 00:52:04.730 ⇒ 00:52:24.440 Robert Tseng: I think Henry’s relying too much on a wish to make the decisions. A wish can do the the engineering work. But then he needs to be the architect, and I think well, whatever it’s right. I mean, now that he’s back, I’m assuming he’s officially back tomorrow. I I need to. I need to see a turnaround from him over the next week. Otherwise it’s not gonna work.
455 00:52:24.940 ⇒ 00:52:25.810 Uttam Kumaran: Okay. Okay.
456 00:52:25.810 ⇒ 00:52:26.360 Robert Tseng: Yeah.
457 00:52:28.810 ⇒ 00:52:32.399 Uttam Kumaran: Okay, but otherwise a waste. None of the other folks are like worth it.
458 00:52:35.887 ⇒ 00:52:36.840 Uttam Kumaran: That you interviewed.
459 00:52:38.060 ⇒ 00:52:42.580 Awaish Kumar: Yeah, but like, we are looking for senior guys, then no.
460 00:52:42.960 ⇒ 00:52:44.540 Uttam Kumaran: Okay. Okay, okay, great.
461 00:52:47.270 ⇒ 00:52:55.962 Uttam Kumaran: cool. Let’s maybe one I’ll make. I just can go through my stuff. So yeah, I’m just onboarding Sam.
462 00:52:57.200 ⇒ 00:53:03.310 Uttam Kumaran: just pushing him to more and more stuff. We have a leads meeting tomorrow. He’s he’s been pretty good, and like
463 00:53:03.915 ⇒ 00:53:23.050 Uttam Kumaran: our work is kind of all over the place in the AI side, but he seems really interested in everything. He’s been great help with meeting Mustafa, meeting Casey working with them and stuff also very nice guy to work with. And so I I feel good. It has been taking stuff on. Yeah, I’m just trying to onboard, Giselle, and whatever she needs from me.
464 00:53:23.210 ⇒ 00:53:32.499 Uttam Kumaran: you know. Basically, I’m throwing her into the deep end on stuff. And I told her, Look, you don’t need to understand the technicals, I said. Don’t worry about that, but once the ticket is made.
465 00:53:32.680 ⇒ 00:53:39.859 Uttam Kumaran: you need to be driving that forward, so you need to make sure that everything is a due date. As an estimate, the other thing amber is, I’m telling you, basically like
466 00:53:40.230 ⇒ 00:53:52.629 Uttam Kumaran: whatever you and the Pm team decide, it’s kind of like what I’m saying. So she looked like she’s like, she asked me, like, what times are the meetings? Something like look, everything that’s exists on default and interlude. I made up.
467 00:53:53.050 ⇒ 00:54:03.830 Uttam Kumaran: There was no structure. So I said, you and the Pm office can decide on what structure you guys want. But that’s why I’m kind of. I’m kind of kicking it back to you guys as a crew to think through like.
468 00:54:03.830 ⇒ 00:54:04.710 Amber Lin: Want to.
469 00:54:04.890 ⇒ 00:54:06.770 Uttam Kumaran: Yeah, like, what is pm, light.
470 00:54:07.000 ⇒ 00:54:15.329 Uttam Kumaran: Okay, what’s like, what are the meeting cadences for these? And then also, like as a Pm. Crew like, I know you guys will be meeting to talk about like, what do we want to check in? But
471 00:54:15.500 ⇒ 00:54:23.939 Uttam Kumaran: I’m that’s kind of how I’m I’m speaking to her where I’m like you can do whatever you want. But I said, the clear thing for me is like everything needs to be in tickets.
472 00:54:24.190 ⇒ 00:54:31.769 Uttam Kumaran: Tickets need due dates, estimations, and priorities, and someone needs to be checking that. Those things get done, I said. If you can do those.
473 00:54:32.060 ⇒ 00:54:32.930 Uttam Kumaran: then
474 00:54:33.340 ⇒ 00:54:50.570 Uttam Kumaran: I’m I’m in the clear like. So I said, if I could hand that to you, I’m in the super clear. So that’s basically what I would like to see. I. But I also said, Look, it’s gonna take a week or 2. And I said, look broadly to get a sense of what we’re doing on the data. AI side, it’ll take a while. But if you can just handle the the
475 00:54:51.170 ⇒ 00:54:55.019 Uttam Kumaran: Pm related, basic stuff would be really great.
476 00:54:56.090 ⇒ 00:54:56.410 Amber Lin: Yeah.
477 00:54:57.440 ⇒ 00:54:58.270 Amber Lin: I’m gonna.
478 00:54:58.520 ⇒ 00:54:59.260 Uttam Kumaran: Yeah.
479 00:54:59.260 ⇒ 00:55:01.400 Amber Lin: With her, probably tomorrow.
480 00:55:01.590 ⇒ 00:55:02.480 Uttam Kumaran: Okay.
481 00:55:03.510 ⇒ 00:55:15.898 Uttam Kumaran: cool. Yeah, I I don’t. I think out of everyone. You’ll probably have to spend the most time with her. To just show her workflows and also have her use the platform and AI stuff for everything. It’ll accelerate her a lot.
482 00:55:18.170 ⇒ 00:55:23.029 Uttam Kumaran: and then, yeah. So interlude is actually crushing like.
483 00:55:23.600 ⇒ 00:55:31.650 Uttam Kumaran: And that’s gonna be a very high margin project. We just we’re nailing it for them. I think we’re gonna also, probably we may continue to do more stuff with them after
484 00:55:32.116 ⇒ 00:55:36.753 Uttam Kumaran: yeah, Henry’s dropping the ball and figure out, what about that for default?
485 00:55:37.980 ⇒ 00:55:43.039 Uttam Kumaran: officially today? Miguel’s off boarding, I think, probably by end of by end of week.
486 00:55:43.485 ⇒ 00:55:55.470 Uttam Kumaran: Sort of every everything I’ve on that I said last week. So that’s sort of it. Yeah, I wanted to consider sort of some sort of spot bonus for some of the folks that are really crushing it, like I think
487 00:55:56.060 ⇒ 00:55:57.910 Uttam Kumaran: Casey, Mustafa.
488 00:55:58.390 ⇒ 00:56:06.380 Uttam Kumaran: Rico, and Ryan are all doing well. You know, we’ve spent a lot of time talking about the people that aren’t doing so well, and I think
489 00:56:06.660 ⇒ 00:56:09.890 Uttam Kumaran: especially given like Miguel’s leaving.
490 00:56:10.458 ⇒ 00:56:20.000 Uttam Kumaran: I think it could be nice to show them some recognitions. I don’t have a
491 00:56:20.280 ⇒ 00:56:23.769 Uttam Kumaran: number in mind, but I will do some research on like.
492 00:56:24.730 ⇒ 00:56:29.470 Uttam Kumaran: it’s probably some percent of salary or something. But I’ll I’ll I could propose it to this group
493 00:56:29.780 ⇒ 00:56:35.590 Uttam Kumaran: and then also get validation from finance, and then we could do something. I think it would go a long way for them.
494 00:56:36.110 ⇒ 00:56:40.060 Amber Lin: Okay. I need to hop to talk to Karen. I need to use.
495 00:56:40.060 ⇒ 00:56:40.830 Uttam Kumaran: Okay. Okay.
496 00:56:40.830 ⇒ 00:56:42.520 Amber Lin: We’ll talk tomorrow.
497 00:56:42.850 ⇒ 00:56:44.940 Robert Tseng: Okay. Okay. Alright. Alright. Okay.
498 00:56:44.940 ⇒ 00:56:45.260 Robert Tseng: Everyone.
499 00:56:45.260 ⇒ 00:56:45.940 Uttam Kumaran: Thanks guys.