Meeting Title: Weekly Managers Meeting Date: 2025-07-07 Meeting participants: Awaish Kumar, Amber Lin, Hannah Wang, Uttam Kumaran
WEBVTT
1 00:01:34.410 ⇒ 00:01:35.680 Amber Lin: Hi.
2 00:01:36.530 ⇒ 00:01:37.210 Uttam Kumaran: Hello!
3 00:01:39.790 ⇒ 00:01:40.920 Hannah Wang: Hello!
4 00:01:41.180 ⇒ 00:01:41.900 Awaish Kumar: Hello!
5 00:01:42.700 ⇒ 00:01:43.880 Uttam Kumaran: How’s everything?
6 00:01:45.400 ⇒ 00:01:46.330 Awaish Kumar: I’m good.
7 00:01:47.970 ⇒ 00:01:49.439 Awaish Kumar: How has been your weekend.
8 00:01:50.880 ⇒ 00:01:51.950 Uttam Kumaran: It was good.
9 00:01:52.070 ⇒ 00:01:54.660 Uttam Kumaran: Just traveled home like late last night.
10 00:01:58.230 ⇒ 00:01:59.230 Awaish Kumar: For work.
11 00:02:00.900 ⇒ 00:02:01.790 Uttam Kumaran: Huh!
12 00:02:03.390 ⇒ 00:02:08.070 Awaish Kumar: I, I said, you have been traveling for work on weekend, or just to have fun.
13 00:02:08.070 ⇒ 00:02:11.697 Uttam Kumaran: No, no, just visiting some friends for last week. I
14 00:02:12.440 ⇒ 00:02:16.609 Uttam Kumaran: I went and visited Robert about a week 2 weeks ago.
15 00:02:16.730 ⇒ 00:02:20.700 Uttam Kumaran: but I’ve been traveling since then, so I just got back home last night.
16 00:02:21.710 ⇒ 00:02:22.470 Awaish Kumar: Yeah.
17 00:02:24.590 ⇒ 00:02:28.320 Uttam Kumaran: That’s crazy. Traveling is very tiring.
18 00:02:29.010 ⇒ 00:02:29.779 Hannah Wang: Or it can.
19 00:02:29.780 ⇒ 00:02:31.480 Uttam Kumaran: Yeah. Long. Day.
20 00:02:31.970 ⇒ 00:02:32.820 Hannah Wang: Yeah.
21 00:02:37.690 ⇒ 00:02:42.129 Amber Lin: Long day for me, too. Well, we’ll make this quick.
22 00:02:44.290 ⇒ 00:02:45.540 Amber Lin: Let’s see.
23 00:02:46.800 ⇒ 00:02:53.930 Amber Lin: Well, do we have any items we wanted to discuss other than the quick round table.
24 00:02:56.207 ⇒ 00:03:00.449 Uttam Kumaran: Yeah, I guess I guess we can kind of chat through
25 00:03:00.720 ⇒ 00:03:06.049 Uttam Kumaran: like delivery okrs in the next meeting. That was really what I wanted to go through.
26 00:03:06.930 ⇒ 00:03:14.100 Uttam Kumaran: The other thing. I I thought I’d have a chance to do it before this meeting, but I didn’t get to. It is starting to put together like
27 00:03:14.480 ⇒ 00:03:19.210 Uttam Kumaran: the list of initiatives. And then basically like, who’s gonna be
28 00:03:19.420 ⇒ 00:03:21.910 Uttam Kumaran: who’s just gonna own that for the quarter?
29 00:03:22.481 ⇒ 00:03:26.400 Uttam Kumaran: I think we got a lot more clarity about partnerships
30 00:03:26.640 ⇒ 00:03:31.599 Uttam Kumaran: today, and we’re getting a little bit more clarity on marketing.
31 00:03:31.730 ⇒ 00:03:35.949 Uttam Kumaran: So I feel like we’re headed in a good direction there.
32 00:03:37.720 ⇒ 00:03:40.160 Uttam Kumaran: But I think probably we can.
33 00:03:40.637 ⇒ 00:03:46.890 Uttam Kumaran: We can decide on a format for stuff in the next meeting, and then I can fill it out this week.
34 00:03:49.120 ⇒ 00:04:07.630 Uttam Kumaran: otherwise. Yeah, I think maybe quick. Update for me. Default signed. So that’s great. I need to send a note on that. But yeah, that’s really good. And then, yeah, we have a. We just sent out an agreement to mega for a partnership as well.
35 00:04:07.820 ⇒ 00:04:09.940 Uttam Kumaran: So they should sign
36 00:04:12.790 ⇒ 00:04:18.583 Uttam Kumaran: And yeah, otherwise, like, just like a lot of partnership stuff from from my side
37 00:04:19.470 ⇒ 00:04:21.414 Uttam Kumaran: on the sales team.
38 00:04:23.190 ⇒ 00:04:35.159 Uttam Kumaran: yeah, I feel like that’s mainly it. Sid is off this week. Actually, I was just looking through my email. And then I realized that she’s on vacation. Actually, this week.
39 00:04:36.940 ⇒ 00:04:41.230 Uttam Kumaran: Yeah, so I’ll probably catch up with her again when she’s back
40 00:04:42.089 ⇒ 00:04:51.570 Uttam Kumaran: on Friday or on Monday. But I’ll probably catch up with her and understand sort of like what she thinks so far and progress.
41 00:04:51.820 ⇒ 00:04:57.550 Uttam Kumaran: and then sort of decide if we want to continue to extend a trial, or what decision we want to make
42 00:04:58.207 ⇒ 00:05:03.779 Uttam Kumaran: for her. So yeah, that’s probably it for me.
43 00:05:05.980 ⇒ 00:05:09.185 Amber Lin: Okay, yeah, for the initiative side.
44 00:05:10.170 ⇒ 00:05:31.760 Amber Lin: I don’t think it needs to be too polished. I just need overall. We just need to list out all the main initiatives, and then we can fill in the smaller ones under. I don’t think that will take too much times we can maybe do that together next meeting, or if I get time before next week, I’ll do a 1st draft, and we can look at it together on Wednesday.
45 00:05:32.230 ⇒ 00:05:32.950 Uttam Kumaran: Okay.
46 00:05:33.515 ⇒ 00:05:39.410 Amber Lin: For my side, urban stems closing off current sprint
47 00:05:40.581 ⇒ 00:05:47.650 Amber Lin: today and then starting a new sprint. Tomorrow we’re a lot more engaged with stakeholders.
48 00:05:49.270 ⇒ 00:05:52.579 Amber Lin: Deprecation is pretty much out of the way.
49 00:05:53.160 ⇒ 00:05:55.930 Amber Lin: And then we had a pretty good retro today.
50 00:05:56.944 ⇒ 00:06:05.119 Amber Lin: For matter more just final documentations finally heard back from Matthew. So I’m gonna make meet with theirs
51 00:06:05.240 ⇒ 00:06:15.349 Amber Lin: data scientists, probably tomorrow to just hand off the last few items so that will be done soon. In in terms of ABC,
52 00:06:16.220 ⇒ 00:06:17.270 Amber Lin: I think.
53 00:06:18.760 ⇒ 00:06:31.619 Amber Lin: Come back. Come back to ABC. Let me let me think about. I was just thinking about. I was just in the work of ABC. So I need my mind to get out of it. So come circle back to me.
54 00:06:33.640 ⇒ 00:06:34.659 Uttam Kumaran: Okay, perfect.
55 00:06:35.630 ⇒ 00:06:43.659 Awaish Kumar: No, yeah, for me, like number one thing would. That typical is, you see.
56 00:06:44.280 ⇒ 00:06:47.240 Awaish Kumar: And so we are left with only one intent
57 00:06:47.724 ⇒ 00:06:53.240 Awaish Kumar: for this week, and she also told me that she has sent you a message, and I’ll
58 00:06:53.410 ⇒ 00:06:55.200 Awaish Kumar: I’m not sure if you’ve seen it. But
59 00:06:55.715 ⇒ 00:07:01.700 Awaish Kumar: she said, she will not be able to work this week, and she need to.
60 00:07:02.581 ⇒ 00:07:06.350 Awaish Kumar: Need answer from us that, okay, we are okay with that, or we want to.
61 00:07:06.350 ⇒ 00:07:08.519 Uttam Kumaran: Yeah. She sent me a note. I said, That’s fine.
62 00:07:08.750 ⇒ 00:07:12.669 Awaish Kumar: She can come after that and work on the project. Right? Okay?
63 00:07:13.200 ⇒ 00:07:15.230 Amber Lin: Where did one of them drop out.
64 00:07:16.610 ⇒ 00:07:17.240 Awaish Kumar: No.
65 00:07:17.240 ⇒ 00:07:19.989 Uttam Kumaran: For a week, she said. She has some health issues.
66 00:07:20.250 ⇒ 00:07:20.910 Awaish Kumar: Yep.
67 00:07:21.790 ⇒ 00:07:22.190 Amber Lin: Hmm.
68 00:07:24.870 ⇒ 00:07:25.900 Uttam Kumaran: That’s why you asked it.
69 00:07:27.490 ⇒ 00:07:31.980 Awaish Kumar: Okay, I will. I will let her know that we are okay and she can.
70 00:07:33.946 ⇒ 00:07:37.539 Awaish Kumar: Can I take care of her health and come back when she’s.
71 00:07:37.990 ⇒ 00:07:39.000 Amber Lin: She’s ready.
72 00:07:41.320 ⇒ 00:07:41.900 Uttam Kumaran: Okay.
73 00:07:42.620 ⇒ 00:07:49.918 Awaish Kumar: Oh, apart from that. So yeah, like I have.
74 00:07:51.450 ⇒ 00:07:57.370 Awaish Kumar: I set it up for Vishnu like he. He has started working. He has built a
75 00:07:57.580 ⇒ 00:08:03.240 Awaish Kumar: pipeline to move data from, octrify to snowflake in our dexter pipeline.
76 00:08:03.820 ⇒ 00:08:04.600 Uttam Kumaran: Thanks.
77 00:08:04.600 ⇒ 00:08:06.749 Awaish Kumar: I will review it and wish we should like
78 00:08:07.060 ⇒ 00:08:11.339 Awaish Kumar: it like like soon it should be in the production
79 00:08:13.940 ⇒ 00:08:22.059 Awaish Kumar: and then, like we we can like this week. The target is to get the snowflake data. We already have linear data in Snowflake.
80 00:08:24.010 ⇒ 00:08:30.410 Awaish Kumar: We already have a set up the real for them. So for real data like
81 00:08:30.570 ⇒ 00:08:35.950 Awaish Kumar: like, it’s, it’s our internal stance. So we we are okay with creating more projects. Right?
82 00:08:36.510 ⇒ 00:08:37.550 Uttam Kumaran: Yeah, that’s fine.
83 00:08:37.809 ⇒ 00:08:43.033 Awaish Kumar: Okay. So we’ll just create a new project and start working there as well.
84 00:08:44.539 ⇒ 00:08:47.459 Awaish Kumar: and you have seen the mother dog.
85 00:08:48.540 ⇒ 00:08:49.300 Uttam Kumaran: Yes.
86 00:08:49.630 ⇒ 00:08:58.890 Awaish Kumar: Select channel. I’ve set it up. I accepted the invite invite, and also have signed up, for mother, instance.
87 00:08:59.070 ⇒ 00:09:04.600 Awaish Kumar: So if you’re okay, like, like. I have signed it with my email. And I’ve invited you. I can.
88 00:09:04.600 ⇒ 00:09:05.360 Uttam Kumaran: Yeah, that’s fine.
89 00:09:05.360 ⇒ 00:09:07.819 Awaish Kumar: That’s our partner. That’s our account.
90 00:09:09.210 ⇒ 00:09:09.880 Uttam Kumaran: Perfect.
91 00:09:10.950 ⇒ 00:09:18.359 Awaish Kumar: And and also yeah. And for the client side, like for the Eden, like, we have some
92 00:09:19.068 ⇒ 00:09:23.830 Awaish Kumar: more work on one on the like. The X
93 00:09:24.510 ⇒ 00:09:28.530 Awaish Kumar: Cdp side, like robot, is already very involved in that. I’m
94 00:09:28.730 ⇒ 00:09:33.230 Awaish Kumar: and I will be involved in in that, too, in this week.
95 00:09:33.400 ⇒ 00:09:40.170 Awaish Kumar: and I’m also in panel, working on Emr side, so we might need more help on agent side.
96 00:09:40.530 ⇒ 00:09:41.310 Uttam Kumaran: Okay.
97 00:09:41.670 ⇒ 00:09:46.039 Awaish Kumar: Like. I’m not sure right now how much with their
98 00:09:46.360 ⇒ 00:09:49.379 Awaish Kumar: that can be that will be clear in insurance.
99 00:09:49.850 ⇒ 00:09:56.099 Uttam Kumaran: Okay, okay, I know also, Aish. You send me to those 2 profiles.
100 00:09:57.240 ⇒ 00:10:00.870 Uttam Kumaran: For potential data engineers. I wonder if we should maybe reach out
101 00:10:01.240 ⇒ 00:10:04.780 Uttam Kumaran: to them, or if you recommend both of them, then
102 00:10:04.970 ⇒ 00:10:13.650 Uttam Kumaran: you can go then, if they’re if they’re if they know that that you sent them my way, we can go ahead and just reach out and set up meetings with them.
103 00:10:14.650 ⇒ 00:10:22.480 Awaish Kumar: Like, like what we are looking for, a data engineer or data analytics engineer, and on what level and.
104 00:10:22.940 ⇒ 00:10:31.330 Awaish Kumar: The 2 I sent like they are more like junior to mid level and more of data analytics, engineers.
105 00:10:32.960 ⇒ 00:10:34.919 Awaish Kumar: and one profile I sent
106 00:10:35.612 ⇒ 00:10:43.029 Awaish Kumar: he’s more like senior. And he’s a data engineer like this is like, kind of kind of full stack, like end to end
107 00:10:43.250 ⇒ 00:10:45.600 Awaish Kumar: analytics and engineer as well.
108 00:10:46.540 ⇒ 00:10:58.640 Uttam Kumaran: Yeah, I’m more interested, probably in the in the last guy. But honestly like, if you recommend all of them, then it’s worth us talking to them, and then just getting a vibe for what they’re interested in.
109 00:11:00.520 ⇒ 00:11:01.110 Awaish Kumar: Okay.
110 00:11:03.640 ⇒ 00:11:04.160 Uttam Kumaran: Okay
111 00:11:04.160 ⇒ 00:11:17.846 Uttam Kumaran: that way. We yeah, that way, we they yeah, we just we can just chat with them. I think it’s it’s clear that I think we probably need one more person on the data engineering side, like, I can tell that.
112 00:11:19.090 ⇒ 00:11:23.329 Uttam Kumaran: like, you’re helping support all the internal dagster work.
113 00:11:23.640 ⇒ 00:11:26.120 Uttam Kumaran: But it’s something that we can probably hand off
114 00:11:26.430 ⇒ 00:11:29.170 Uttam Kumaran: and someone to kind of handle
115 00:11:29.280 ⇒ 00:11:38.569 Uttam Kumaran: Meta plane and some more observability stuff. So that’d be really nice to have, and then someone to come on and and take on new clients on the De side.
116 00:11:40.550 ⇒ 00:11:43.469 Awaish Kumar: So just be good to to talk to people like even.
117 00:11:43.570 ⇒ 00:11:52.509 Uttam Kumaran: There’s no, there’s no risk in talking to people, and then just sort of keeping them in our rolodex, you know, as if you have recommendations.
118 00:11:54.260 ⇒ 00:12:00.739 Awaish Kumar: Yeah, like, I like, these are people I have worked with. I have one more. He was kind of
119 00:12:01.010 ⇒ 00:12:04.700 Awaish Kumar: interstate offer, seeing my living in post.
120 00:12:05.560 ⇒ 00:12:11.089 Awaish Kumar: Oh, he, he’s also like my colleague has has been a data engineer.
121 00:12:11.090 ⇒ 00:12:11.590 Uttam Kumaran: Nice.
122 00:12:11.900 ⇒ 00:12:17.769 Awaish Kumar: 8 years and kind of a lead kind of managing a team somewhere right now.
123 00:12:18.600 ⇒ 00:12:24.179 Uttam Kumaran: Okay, yeah. For anyone you recommend. That’s interested, like we should totally just chat with them.
124 00:12:25.120 ⇒ 00:12:25.520 Amber Lin: So.
125 00:12:25.520 ⇒ 00:12:26.310 Awaish Kumar: So, yeah.
126 00:12:26.310 ⇒ 00:12:30.979 Amber Lin: Put them in the channel, and we can add Rico, and we can.
127 00:12:31.880 ⇒ 00:12:33.290 Awaish Kumar: Yeah, I I.
128 00:12:34.580 ⇒ 00:12:41.790 Awaish Kumar: So we have resumes like 2 of them already shared. For one i i can share, and then we can like set up.
129 00:12:41.790 ⇒ 00:12:43.230 Awaish Kumar: Yes, it is interesting.
130 00:12:43.230 ⇒ 00:12:48.659 Uttam Kumaran: Yeah, yeah, if you if you if you don’t mind just introducing us via email.
131 00:12:51.260 ⇒ 00:12:54.389 Uttam Kumaran: yeah, you can just introduce me. And then I can sort of take it from there.
132 00:12:55.950 ⇒ 00:12:57.499 Awaish Kumar: Okay, I will do that.
133 00:12:57.970 ⇒ 00:13:02.280 Uttam Kumaran: That’s pretty easy. Yeah. And then cause I’ll get Rico involved to help schedule.
134 00:13:03.091 ⇒ 00:13:07.109 Awaish Kumar: Yeah. And one more thing that, Olga, like I
135 00:13:07.320 ⇒ 00:13:10.439 Awaish Kumar: have like a meeting set up tomorrow with.
136 00:13:10.440 ⇒ 00:13:10.920 Uttam Kumaran: Okay.
137 00:13:11.360 ⇒ 00:13:16.510 Awaish Kumar: So I like, do you have a specific expectations, or it will be more like
138 00:13:16.770 ⇒ 00:13:21.120 Awaish Kumar: understanding the the past experiences, projects, technical side.
139 00:13:21.630 ⇒ 00:13:26.959 Uttam Kumaran: Yeah, I think the latter just understanding her past experiences. What she’s interested in.
140 00:13:27.536 ⇒ 00:13:32.050 Uttam Kumaran: I know amber has a set of questions that she typically asks.
141 00:13:32.150 ⇒ 00:13:45.660 Uttam Kumaran: but yeah, just kind of doing an initial screen understanding. Like, if, like, her communication skills, past projects like what she’s looking for, and then we can sort of decide if we have an open slot or not.
142 00:13:47.290 ⇒ 00:13:49.879 Amber Lin: What is this person for? Tomorrow?
143 00:13:51.719 ⇒ 00:13:56.879 Uttam Kumaran: She got recommended by Jodi for for a data analyst position
144 00:13:57.080 ⇒ 00:14:02.039 Uttam Kumaran: like she has experience in power Bi and a few other things, the data analyst side.
145 00:14:02.500 ⇒ 00:14:05.490 Amber Lin: Hmm, yeah, I can.
146 00:14:05.820 ⇒ 00:14:16.309 Amber Lin: I can. Honestly, if it’s just a quick 1st round screening, I think the set of 4 questions I can send it in the product managers. Channel.
147 00:14:18.450 ⇒ 00:14:26.480 Amber Lin: I think these 4 questions are a pretty good screen on just overall. How this what this person?
148 00:14:27.291 ⇒ 00:14:32.119 Amber Lin: It’s like I’ll send it in the Channel. This is what I asked for. Initial screenings.
149 00:14:35.390 ⇒ 00:14:37.999 Awaish Kumar: Okay, yeah, please do send them. I’ll
150 00:14:39.970 ⇒ 00:14:45.329 Awaish Kumar: I will, definitely. I’ll like, keep that in my list of questions tomorrow.
151 00:14:48.220 ⇒ 00:14:50.419 Awaish Kumar: Yeah. So that’s it from my side.
152 00:14:51.380 ⇒ 00:14:52.010 Uttam Kumaran: Okay.
153 00:14:54.810 ⇒ 00:15:12.440 Hannah Wang: Okay for my side. Lots of partnership stuff, lots of back and forth going on but yeah, I think we had a meeting earlier today to kinda hone down on the couple that we wanna focus on for this quarter, and then we’ll start to reevaluate
154 00:15:13.270 ⇒ 00:15:32.390 Hannah Wang: as the weeks go by for promotion stuff. I try to schedule something like a brain forge session. For Robert with a couple of people that he wanted to talk to, but no one got back. So he’s gonna talk to pies tomorrow. So that should be interesting. And then
155 00:15:33.663 ⇒ 00:15:50.096 Hannah Wang: I followed up with blue people for tech and tequila so I just got that. We just got that email like a couple of minutes ago. So that’s gonna move forward for August, I believe. And then I’ll look for other
156 00:15:51.070 ⇒ 00:16:04.639 Hannah Wang: events that you guys can either attend or maybe speak at and then I know that for speaking engagements we need to fill out like a form. If I could get assistance on that, if I find one form example.
157 00:16:04.640 ⇒ 00:16:05.110 Uttam Kumaran: Totally.
158 00:16:05.110 ⇒ 00:16:15.592 Hannah Wang: And I could just use your, I could just use your responses for later ones. But yeah, I’ll look for a couple of events that you guys can attend or speak at
159 00:16:15.910 ⇒ 00:16:23.949 Uttam Kumaran: So on the events thing. We’re gonna expand. Casey has a ticket on his plate to expand, to, to get Luma events
160 00:16:24.060 ⇒ 00:16:30.630 Uttam Kumaran: as well this week. And then that automation is gonna start getting scheduled to run every few days.
161 00:16:30.750 ⇒ 00:16:35.550 Uttam Kumaran: So ideally, we’re gonna just basically start to get a running list of events.
162 00:16:35.820 ⇒ 00:16:48.189 Uttam Kumaran: and we can start to add locations to it. And then I think the spreadsheet is a good way, like once a week, or whatever. Whenever I get I can just go through and say, These are these are events that I can sign up, for I can go to.
163 00:16:49.000 ⇒ 00:16:49.690 Hannah Wang: Okay.
164 00:16:50.330 ⇒ 00:16:55.060 Uttam Kumaran: So. Yeah, I think. I think the process should be pretty smooth now.
165 00:16:55.690 ⇒ 00:16:56.460 Hannah Wang: Sweet.
166 00:16:56.660 ⇒ 00:16:59.639 Hannah Wang: Okay, I’ll have Robert take a look at that
167 00:17:00.260 ⇒ 00:17:06.179 Hannah Wang: the the spreadsheet again after you made the New York and Texas ones. I think.
168 00:17:06.180 ⇒ 00:17:17.300 Uttam Kumaran: Yeah, and I, I’m I put some columns. I put 2 columns there, just marking some Texas ones that I can definitely go to. And then some of the ones I marked. I just had. I had one or 2 questions about like
169 00:17:19.109 ⇒ 00:17:21.810 Uttam Kumaran: if we needed to pay, and like a couple of things.
170 00:17:21.810 ⇒ 00:17:22.200 Hannah Wang: Okay.
171 00:17:22.200 ⇒ 00:17:32.110 Uttam Kumaran: But but but yeah, for for the most part, I just mark the ones that I’m interested in, or if I wasn’t interested, I I left the reason why, so that we have a log of that as well.
172 00:17:32.110 ⇒ 00:17:38.429 Hannah Wang: Hmm! And then for the ones that you were interested in, were you able to sign up? Or do you need like
173 00:17:38.940 ⇒ 00:17:42.060 Hannah Wang: me to sign up for you, or how can I make that easier.
174 00:17:42.060 ⇒ 00:17:49.420 Uttam Kumaran: Yeah, I guess I I left some comments there for for some of them that were free. I did sign up for some of them that.
175 00:17:49.420 ⇒ 00:17:50.110 Hannah Wang: Okay.
176 00:17:50.110 ⇒ 00:17:53.040 Uttam Kumaran: We maybe have to pay. I just left some comments.
177 00:17:53.320 ⇒ 00:17:53.640 Uttam Kumaran: Yeah.
178 00:17:53.640 ⇒ 00:17:56.299 Uttam Kumaran: So maybe it’s just a little bit of a back and forth.
179 00:17:56.640 ⇒ 00:17:57.140 Uttam Kumaran: Goodbye.
180 00:17:57.480 ⇒ 00:18:05.240 Uttam Kumaran: Any clarifying questions. And then, otherwise, yeah, like I, I’ll I’ll just I usually can. Just, I can just book it. It’s fine.
181 00:18:05.240 ⇒ 00:18:13.829 Hannah Wang: Okay, yeah, I’ll take a look at your questions and do some research or like, follow up with the organizer or something. If I can’t find the answer.
182 00:18:15.810 ⇒ 00:18:21.164 Hannah Wang: And then for design, yeah, we have that meeting tomorrow.
183 00:18:22.510 ⇒ 00:18:31.537 Hannah Wang: I mean my one like, I don’t know if we’re doing risks right now, but like one risk is the marketing tickets like you mentioned are kind of all over the place.
184 00:18:31.820 ⇒ 00:18:32.360 Uttam Kumaran: Yeah.
185 00:18:32.360 ⇒ 00:18:48.479 Hannah Wang: I know Rico is gonna come in and kinda help. But I think right now there’s just like a lot of initiatives that we’ve started. So I think it’s not reflected in linear that. Well, so I think it’s just the growing pain of expanding.
186 00:18:49.360 ⇒ 00:19:16.440 Hannah Wang: yeah. So I guess, amber when you and I groom with Rico Tuesday and Thursday. We can just kinda hammer down on what we’re focusing on. Because I think a lot of the tickets on that board are from before, even like Q, 2 and q, 1 when we didn’t really have like a sharp focus on what we wanted to do in terms of like assisting sales and partnerships and all that stuff. So yeah, we can go through that this week.
187 00:19:18.380 ⇒ 00:19:20.220 Amber Lin: And.
188 00:19:21.760 ⇒ 00:19:27.590 Uttam Kumaran: Whatever we can do to enable Rico to effectively run those will be really really helpful.
189 00:19:28.345 ⇒ 00:19:28.890 Amber Lin: Yeah.
190 00:19:29.060 ⇒ 00:19:31.709 Uttam Kumaran: Like if it’s if it’s just like.
191 00:19:33.335 ⇒ 00:19:38.560 Amber Lin: I’ve run him through how to how I create tickets with AI.
192 00:19:38.670 ⇒ 00:19:45.609 Amber Lin: I think that’s the most fundamental thing that will be helpful. Also, last time that we met we went through how to
193 00:19:45.720 ⇒ 00:19:50.500 Amber Lin: essentially navigate linear. And I think, with the 2 grooming sessions
194 00:19:51.130 ⇒ 00:19:54.579 Amber Lin: with Hannah, we’ll equip Rico to understand
195 00:19:54.740 ⇒ 00:20:01.570 Amber Lin: what needs to, what tickets mean and how it means to get things done, and then I think
196 00:20:02.190 ⇒ 00:20:08.419 Amber Lin: I’ll I’ll try to be with him, for I’ll probably book a session with him to run him through the basics.
197 00:20:09.150 ⇒ 00:20:13.150 Amber Lin: And now I’ll work closely with him for the first, st
198 00:20:13.690 ⇒ 00:20:19.729 Amber Lin: say sprint or 2 sprints or so for the marketing team to make sure that he’s ready.
199 00:20:21.710 ⇒ 00:20:26.200 Uttam Kumaran: Yeah, okay, perfect. Yeah, I kind of. I kind of want him to to have his
200 00:20:26.690 ⇒ 00:20:40.990 Uttam Kumaran: have a have a good go at it. So I’m not gonna intrude too much. There just is a kind of a lot to coordinate between, like Ryan’s pace and needing stuff from design. And between everybody, but I do think that
201 00:20:41.190 ⇒ 00:20:43.960 Uttam Kumaran: it will alleviate a lot of pressure for me.
202 00:20:44.576 ⇒ 00:20:54.370 Uttam Kumaran: And from Hannah, if he’s able to just come on and and make sure things get moved forward, and he can sort of bug me, or whoever for reviews on the design side.
203 00:20:55.005 ⇒ 00:20:58.159 Uttam Kumaran: That will take take kind of one big piece off.
204 00:20:59.186 ⇒ 00:21:00.740 Uttam Kumaran: So yeah.
205 00:21:01.770 ⇒ 00:21:02.350 Amber Lin: Hmm.
206 00:21:03.430 ⇒ 00:21:25.449 Hannah Wang: Yeah, I already kind of inadvertently looped him in into the campaign work that we’re gonna do. So I’ve I scheduled a kick off meeting for that on Thursday. And I I think, yeah, he, I think he expressed interest in wanting to help with that. So we’ll just see. Yeah, there’s just like a lot of moving parts. But
207 00:21:25.810 ⇒ 00:21:33.759 Amber Lin: Campaign parts, he said, yes, I don’t think we explicitly asked him for the sales part, but I would assume he’s done, but we will confirm with him.
208 00:21:35.370 ⇒ 00:21:38.459 Hannah Wang: Okay, I mean, like the campaign stuff. Yeah, go ahead.
209 00:21:38.800 ⇒ 00:21:41.649 Uttam Kumaran: Yeah, I think the campaign stuff is really like.
210 00:21:42.060 ⇒ 00:22:09.179 Uttam Kumaran: I don’t. I? I just think anything we’re doing where there is like a marketing or a sales campaign. I want to start to track. This is something that I think it’ll it could be handed off to Sid longer term. But yeah, I just I just think that that team there’s just there’s a bunch of stuff between Ryan and Ray and then there’s the website. And there’s sort of partnerships we’re now doing some more like sort of co-marketing, like there’s just a lot to organize.
211 00:22:09.671 ⇒ 00:22:17.199 Uttam Kumaran: So I do think that he would be helpful to to just make sure all those tickets are are clean, and then assist everyone there.
212 00:22:17.910 ⇒ 00:22:18.810 Amber Lin: I agree.
213 00:22:19.340 ⇒ 00:22:26.400 Amber Lin: Yeah, I need to carve out time to help them. My Monday has been crazy. I think tomorrow we’ll be having time to do that.
214 00:22:26.760 ⇒ 00:22:27.095 Uttam Kumaran: Okay.
215 00:22:27.800 ⇒ 00:22:28.450 Hannah Wang: Right?
216 00:22:29.330 ⇒ 00:22:39.879 Hannah Wang: Yeah. I mean, you saw how I was track manually tracking all the partnership stuff, I think. Yeah, having, we created the projects last week. So I think, having that will be helpful.
217 00:22:40.190 ⇒ 00:22:41.879 Amber Lin: But I would say, move to both.
218 00:22:42.160 ⇒ 00:22:47.079 Amber Lin: Yeah, I think that’s another area as not as now that I know a little bit about
219 00:22:47.890 ⇒ 00:22:54.830 Amber Lin: more about project management that I can help make sure that that runs for all the teams in the company.
220 00:22:55.960 ⇒ 00:22:56.740 Hannah Wang: Awesome.
221 00:22:56.740 ⇒ 00:23:25.119 Uttam Kumaran: Yeah. And the operations work. I think it’s it’s still like only a couple of hours a day. If that. So I think he does have. He does have a good amount of time. Even the operations work like, I think eventually he can. He can basically pm that as well, and it’ll just be me as the only other person on that team. So I think you can basically indicate to him that both of those he could start to run like Pm. Points on and see if he can handle it.
222 00:23:25.630 ⇒ 00:23:28.690 Amber Lin: Okay, let me let me write that down.
223 00:23:29.480 ⇒ 00:23:30.220 Amber Lin: Oh.
224 00:23:30.220 ⇒ 00:23:38.680 Uttam Kumaran: Does the operations work is like contracts. Like helping me set up like tools or access
225 00:23:39.448 ⇒ 00:23:42.260 Uttam Kumaran: and then we we’re writing sops.
226 00:23:42.490 ⇒ 00:23:46.189 Uttam Kumaran: All of that are easy to just take it out and.
227 00:23:47.590 ⇒ 00:23:48.240 Uttam Kumaran: Yeah.
228 00:23:49.150 ⇒ 00:23:54.690 Amber Lin: Yeah, let me quickly just put a placeholder to talk to him on that
229 00:23:56.520 ⇒ 00:24:05.940 Uttam Kumaran: Yeah, I just think, having a probably a good explanation. Him was like, Hey, just try to track all your work in linear. Here’s quick ways to go from slack to linear or like make tickets.
230 00:24:06.590 ⇒ 00:24:16.130 Uttam Kumaran: And then I think, you can also ask him to probably just schedule like a operations.
231 00:24:16.410 ⇒ 00:24:21.269 Uttam Kumaran: I mean, I don’t know we. But the AI folks I’m doing like every I’m doing a
232 00:24:21.960 ⇒ 00:24:24.000 Uttam Kumaran: weekly sprint. Basically.
233 00:24:24.864 ⇒ 00:24:30.950 Uttam Kumaran: so operations can be pretty similar like. I have a good understanding of all the operations. Work at least a few days out.
234 00:24:31.777 ⇒ 00:24:35.129 Uttam Kumaran: And we used to do that used to do that with Marianne. So.
235 00:24:35.560 ⇒ 00:24:36.230 Amber Lin: Okay.
236 00:24:37.360 ⇒ 00:24:45.970 Amber Lin: yeah, I’m gonna send. I sent him a placeholder. So I remember, I think for my side. Tomorrow we want to look at
237 00:24:48.280 ⇒ 00:25:00.849 Amber Lin: time allocations. I was wondering if you had to have time. Could you record a quick video on just how your current sheet is set up? Because I just want to know where to find different things.
238 00:25:03.079 ⇒ 00:25:07.360 Uttam Kumaran: The spreadsheet. Yes, so I did. I did a bunch of work actually.
239 00:25:09.430 ⇒ 00:25:14.610 Uttam Kumaran: I did a bunch of work with a spreadsheet yesterday.
240 00:25:14.780 ⇒ 00:25:24.689 Uttam Kumaran: So we have all the allocations I have. And so basically, I have everything. Now, in one place we have all the revenue we have all of our people costs.
241 00:25:26.370 ⇒ 00:25:34.003 Uttam Kumaran: and we have. We’re we’re starting to also get contracted, forecasted revenue. So we have, like a pretty good amount of stuff.
242 00:25:35.640 ⇒ 00:25:40.410 Uttam Kumaran: in in one place. But yeah.
243 00:25:40.930 ⇒ 00:25:48.799 Amber Lin: If you, if you have time, just record a video because we are meeting again tomorrow on allocations, because now we should have July’s.
244 00:25:48.970 ⇒ 00:25:52.699 Amber Lin: Oh, we have 1st of the 1st week of July’s numbers.
245 00:25:52.990 ⇒ 00:25:59.349 Amber Lin: or at least to read. Go back to look at, look at it again, to see where we can standardize for the
246 00:25:59.960 ⇒ 00:26:03.539 Amber Lin: for the future of time allocation. So we’re meeting again tomorrow.
247 00:26:09.800 ⇒ 00:26:13.890 Amber Lin: I think, for me on the ABC. Side.
248 00:26:16.120 ⇒ 00:26:29.342 Amber Lin: last week was pretty short so there wasn’t think we were still able to get the main workflows set up, which was really helpful to look at the feedback. I think in terms of risk.
249 00:26:30.190 ⇒ 00:26:33.620 Amber Lin: it is one.
250 00:26:33.750 ⇒ 00:26:38.609 Amber Lin: I always fear that this document is taking longer than it should
251 00:26:39.414 ⇒ 00:26:49.759 Amber Lin: and today I also think the risk is that I’m working on it too much, and I should. But sometimes it’s like if I if I allocate to the trainers
252 00:26:50.290 ⇒ 00:26:53.559 Amber Lin: like Janice and Shannon, they don’t really do much.
253 00:26:54.060 ⇒ 00:26:54.780 Amber Lin: I’ve tried.
254 00:26:54.780 ⇒ 00:26:55.100 Uttam Kumaran: Yeah.
255 00:26:55.100 ⇒ 00:27:03.939 Amber Lin: It still doesn’t get done. I’ve asked if that and it still doesn’t really get done. And so what I could do is ask you about more often.
256 00:27:04.470 ⇒ 00:27:05.760 Amber Lin: That would work.
257 00:27:06.240 ⇒ 00:27:18.069 Amber Lin: Probably what I also could do is firmly state that I would not do this. I will ticket it out very, very clearly, and then put it in front of your vet and put it in front of
258 00:27:18.541 ⇒ 00:27:21.069 Amber Lin: Steven. And, as you say, like, Hey.
259 00:27:21.320 ⇒ 00:27:28.799 Amber Lin: because it is their their job. So I think if I do that that could be better. I just never thought that was an option.
260 00:27:29.340 ⇒ 00:27:32.880 Uttam Kumaran: Yeah. An option also could be to see if there’s anyone else on their side.
261 00:27:33.380 ⇒ 00:27:33.810 Amber Lin: Yeah.
262 00:27:34.151 ⇒ 00:27:36.539 Uttam Kumaran: More junior, or someone who’s actually like.
263 00:27:37.180 ⇒ 00:27:39.860 Uttam Kumaran: who actually wants to work with us like
264 00:27:40.523 ⇒ 00:27:51.169 Uttam Kumaran: I forgot the woman’s name, but Joy, like anyone who is like really fired up about the project that maybe wants to help execute this. It’s just not. Yeah. I don’t. I don’t know.
265 00:27:52.040 ⇒ 00:28:02.940 Amber Lin: Yeah, I think they want to work it. And the problem with them is that their information is so bottlenecked. The junior people don’t really know much about the processes or is not allowed to make
266 00:28:03.340 ⇒ 00:28:04.660 Amber Lin: adjustment
267 00:28:05.382 ⇒ 00:28:18.620 Amber Lin: and so then it gets stuck between our meetings. But I think what I’m gonna do is because I don’t want to bind up our time keeping. Keep doing this. But then, without the documentation, it’s hard to have good answers.
268 00:28:19.000 ⇒ 00:28:23.827 Amber Lin: I think we’re close to a point where we will have
269 00:28:24.740 ⇒ 00:28:27.979 Amber Lin: better, better results. But I’ve like
270 00:28:28.770 ⇒ 00:28:33.269 Amber Lin: I will like for this project. It’s always like, I don’t want to spend too much time.
271 00:28:35.490 ⇒ 00:28:41.479 Amber Lin: Since we looked at the time. Allocations. I don’t want us to spend too much time, but then we need to get things done
272 00:28:42.067 ⇒ 00:28:56.782 Amber Lin: but I but overall, I believe in the development side. Our time is pretty good. It’s mostly in terms of my time. I I think there’s other stuff also in the company that I can help with
273 00:28:57.430 ⇒ 00:29:02.940 Amber Lin: And so I’m trying to regulate the time I spent on this specific project.
274 00:29:04.800 ⇒ 00:29:07.529 Uttam Kumaran: Yeah, I think it’s for me like my
275 00:29:07.690 ⇒ 00:29:16.760 Uttam Kumaran: question is just gonna be like, is the adoption piece still bottlenecked by the, you know? Answers,
276 00:29:20.340 ⇒ 00:29:24.860 Uttam Kumaran: right? Because I think we’ve been improving the doc over the last 3, 4 weeks.
277 00:29:24.990 ⇒ 00:29:26.973 Uttam Kumaran: Like, are we seeing like,
278 00:29:27.830 ⇒ 00:29:30.740 Uttam Kumaran: that impact anything on the adoption side
279 00:29:31.160 ⇒ 00:29:35.870 Uttam Kumaran: or like, I guess, like. What is that to be? Probably my question.
280 00:29:36.320 ⇒ 00:29:41.270 Amber Lin: Yeah, the adoption is going up slowly.
281 00:29:43.390 ⇒ 00:29:47.040 Amber Lin: I think we’re pretty much closer to a point
282 00:29:47.760 ⇒ 00:30:00.620 Amber Lin: to where we can. We can put in other practices to make sure that adoption goes up, because before, if we force them, it wasn’t really able to go up, even if we did, because it was just not accurate.
283 00:30:01.720 ⇒ 00:30:06.669 Amber Lin: But you’re right in that like after the sprint. I do want to
284 00:30:06.910 ⇒ 00:30:16.189 Amber Lin: move from documentation to more of those tactics and systems to make sure that they do use it.
285 00:30:17.840 ⇒ 00:30:26.559 Amber Lin: I think I just. I also need some time to think about this project, because this last week’s been short. And today has just been a lot of execution.
286 00:30:27.684 ⇒ 00:30:34.049 Amber Lin: I think one other thing on the on the data side Luke is a bit slow.
287 00:30:34.990 ⇒ 00:30:36.080 Uttam Kumaran: Yeah.
288 00:30:36.750 ⇒ 00:30:40.009 Amber Lin: Tasks are not really getting done.
289 00:30:41.570 ⇒ 00:30:42.900 Uttam Kumaran: For what project?
290 00:30:43.240 ⇒ 00:30:45.809 Amber Lin: For every singer, Madame, is done.
291 00:30:48.040 ⇒ 00:30:51.230 Uttam Kumaran: Yeah, I mean, I I feel the same way, like I don’t know.
292 00:30:51.610 ⇒ 00:30:57.419 Uttam Kumaran: I’m not sure what’s taking so long sometimes, but his work is quite slow.
293 00:31:00.820 ⇒ 00:31:15.490 Uttam Kumaran: this is sort of I’m I’m kind of at an impasse to where I don’t know if I can assign him like some of the work on that one that a wish like I tried to assign on the data platform side, just taking, like 4 or 5 days when it should take, like probably an hour or 2 to do
294 00:31:15.810 ⇒ 00:31:19.010 Uttam Kumaran: so. I’m not just. I just don’t know where the time is going.
295 00:31:20.048 ⇒ 00:31:22.690 Uttam Kumaran: And he’s not really like
296 00:31:23.190 ⇒ 00:31:28.120 Uttam Kumaran: doesn’t really send a message when things are finished, like I having to reach out often
297 00:31:28.300 ⇒ 00:31:30.689 Uttam Kumaran: to ask like when things are getting done.
298 00:31:31.010 ⇒ 00:31:34.319 Uttam Kumaran: So I’m not sure like, what? What’s the best move here.
299 00:31:40.160 ⇒ 00:31:44.039 Awaish Kumar: I did already communicated that he needs to be more proactive.
300 00:31:44.470 ⇒ 00:31:45.200 Awaish Kumar: God.
301 00:31:48.210 ⇒ 00:31:52.699 Awaish Kumar: and that’s like, so is it really
302 00:31:53.180 ⇒ 00:32:01.529 Awaish Kumar: only the is it problem that he’s logging more hours, or is, he’s not just like not working, not logging anything.
303 00:32:03.600 ⇒ 00:32:09.830 Uttam Kumaran: Yeah, I mean, it’s probably worth checking. But I don’t know, like I assigned just a couple of simple tickets last week
304 00:32:10.200 ⇒ 00:32:14.569 Uttam Kumaran: like to do some analytics on slack.
305 00:32:14.840 ⇒ 00:32:20.439 Uttam Kumaran: and to get a couple things done on the metaplane side. And
306 00:32:20.680 ⇒ 00:32:23.740 Uttam Kumaran: I don’t know. Things are moving and.
307 00:32:23.740 ⇒ 00:32:24.860 Awaish Kumar: Yeah, I
308 00:32:25.040 ⇒ 00:32:33.660 Awaish Kumar: I feel the same previously, but when I try to ask him like things to estimate the hours.
309 00:32:33.800 ⇒ 00:32:41.030 Awaish Kumar: he, if he was not very far from what I would have said. I would have said, like 3 h, 4, or 5 h to do that, but
310 00:32:41.220 ⇒ 00:32:44.869 Awaish Kumar: then it was not done in that time period when he
311 00:32:45.080 ⇒ 00:32:47.399 Awaish Kumar: I didn’t have anything else to do like.
312 00:32:47.980 ⇒ 00:32:48.430 Awaish Kumar: Yeah.
313 00:32:48.430 ⇒ 00:32:57.540 Awaish Kumar: the deadline is end of week. And why like? And we are on Monday, and you don’t have anything else to do. So it should be like tomorrow, not on Friday. So.
314 00:32:57.540 ⇒ 00:32:58.310 Uttam Kumaran: Yeah.
315 00:32:58.580 ⇒ 00:33:01.650 Awaish Kumar: Things like that. Yeah, I feel that.
316 00:33:02.180 ⇒ 00:33:06.670 Awaish Kumar: But I think we should like make that clear, as a
317 00:33:08.050 ⇒ 00:33:16.800 Awaish Kumar: like, you know, in my next one on one. I can make 2 things clear on, on, like. If
318 00:33:16.950 ⇒ 00:33:23.325 Awaish Kumar: he commits some availability, then, like we, we need to have that incrementally, like
319 00:33:24.420 ⇒ 00:33:27.589 Awaish Kumar: giving some hours regularly every day.
320 00:33:30.030 ⇒ 00:33:33.979 Awaish Kumar: We can try that like giving some feedback.
321 00:33:35.070 ⇒ 00:33:39.660 Uttam Kumaran: Yeah, I think some feedback would be helpful. I mean, I think it would be really helpful for even for you to like.
322 00:33:39.780 ⇒ 00:33:43.189 Uttam Kumaran: Just sit with and spend 30 min, look through his tickets
323 00:33:43.450 ⇒ 00:33:46.280 Uttam Kumaran: and just say, like, Hey, can you explain how
324 00:33:47.010 ⇒ 00:33:52.550 Uttam Kumaran: these tickets were assigned like last week? And they’re they’re not like.
325 00:33:52.550 ⇒ 00:33:52.870 Awaish Kumar: Like.
326 00:33:52.870 ⇒ 00:33:56.249 Uttam Kumaran: Near being done and like how long things are taking.
327 00:33:56.550 ⇒ 00:34:01.549 Uttam Kumaran: and like sort of how you can better communicate with the Pm’s, because for me
328 00:34:01.930 ⇒ 00:34:05.920 Uttam Kumaran: like my. My only option is to go sit with them and and
329 00:34:06.500 ⇒ 00:34:10.600 Uttam Kumaran: and be like what’s going on. Can we meet right and like?
330 00:34:10.739 ⇒ 00:34:15.620 Uttam Kumaran: I don’t see any proactivity like I don’t see him setting. I had to set up that meeting today
331 00:34:16.000 ⇒ 00:34:22.150 Uttam Kumaran: like like he could have set that meeting up that today that we had last week, right
332 00:34:22.827 ⇒ 00:34:25.389 Uttam Kumaran: like on Thursday or Friday like.
333 00:34:25.670 ⇒ 00:34:30.770 Uttam Kumaran: and I’m having to reach out for like every single ticket to see like when things are getting done.
334 00:34:35.500 ⇒ 00:34:36.399 Awaish Kumar: Okay. Yeah.
335 00:34:36.400 ⇒ 00:34:40.020 Amber Lin: You know how this discussion goes. I need to hop actually.
336 00:34:40.305 ⇒ 00:34:40.590 Uttam Kumaran: Okay.
337 00:34:40.590 ⇒ 00:34:47.360 Amber Lin: Actually we need. I need this meeting room. But I would love a decision. Where? How? That would go as well.
338 00:34:48.550 ⇒ 00:34:51.826 Uttam Kumaran: Okay, okay, yeah, let’s let’s talk about it.
339 00:34:52.500 ⇒ 00:35:08.120 Uttam Kumaran: let’s talk about a little bit more on Wednesday, and then we can prep something or a wish. If you wanna message me in the managers meeting, we can work Async and prepare something to share with him. I do feel very similarly in that, like any work that gets assigned to him, it’s
340 00:35:08.260 ⇒ 00:35:10.350 Uttam Kumaran: seems like it’s a little bit of a risk.
341 00:35:12.260 ⇒ 00:35:15.709 Uttam Kumaran: So I kind of do want to make it really clear that, like.
342 00:35:15.880 ⇒ 00:35:20.120 Uttam Kumaran: we’re noticing that not only on the internal work, but
343 00:35:20.240 ⇒ 00:35:25.120 Uttam Kumaran: like on the client work as well, and that we kind of need to see a change.
344 00:35:26.470 ⇒ 00:35:30.990 Uttam Kumaran: So let’s work Async on on that. And and we can communicate something.
345 00:35:31.690 ⇒ 00:35:32.440 Amber Lin: Okay.
346 00:35:32.770 ⇒ 00:35:33.790 Uttam Kumaran: Okay. Okay.
347 00:35:34.470 ⇒ 00:35:36.199 Hannah Wang: Thanks all. Thank you.
348 00:35:36.200 ⇒ 00:35:37.170 Uttam Kumaran: Thanks. Everyone.
349 00:35:37.510 ⇒ 00:35:37.950 Hannah Wang: Bye.
350 00:35:37.950 ⇒ 00:35:38.870 Amber Lin: Bye, bye.