Meeting Title: Friday Meeting Prep Date: 2025-06-05 Meeting participants: Hannah Wang, Amber Lin, Uttam Kumaran
WEBVTT
1 00:00:36.150 ⇒ 00:00:39.569 Amber Lin: But Hi! Hannah!
2 00:00:41.210 ⇒ 00:00:42.460 Hannah Wang: Hello!
3 00:00:42.790 ⇒ 00:00:44.998 Amber Lin: Hi! I’m very dead.
4 00:00:45.550 ⇒ 00:00:46.869 Hannah Wang: Oh, are you?
5 00:00:47.940 ⇒ 00:00:48.700 Hannah Wang: I’ll go!
6 00:00:49.518 ⇒ 00:00:51.509 Amber Lin: I am in Chicago.
7 00:00:51.790 ⇒ 00:00:55.369 Hannah Wang: You’re doing like an East Coast World tour.
8 00:00:55.680 ⇒ 00:01:05.369 Amber Lin: Somewhat. Yeah, I was. I flew to DC. Cause Nico’s based in DC. And then I was in New York and I came here. I think
9 00:01:05.540 ⇒ 00:01:07.080 Amber Lin: a day ago.
10 00:01:08.050 ⇒ 00:01:11.039 Hannah Wang: And then are you going to one more place? No right.
11 00:01:11.040 ⇒ 00:01:14.079 Amber Lin: No, I am. I am trained.
12 00:01:16.020 ⇒ 00:01:18.490 Amber Lin: That’s enough traveling for me.
13 00:01:18.490 ⇒ 00:01:19.050 Hannah Wang: Yeah.
14 00:01:19.050 ⇒ 00:01:29.579 Amber Lin: I know I need my bed, and I cause I’m staying at hostels. So it’s tolerating the snores of my dear roommates at night.
15 00:01:29.800 ⇒ 00:01:30.840 Hannah Wang: Oh, shoot!
16 00:01:31.420 ⇒ 00:01:38.979 Hannah Wang: And yeah, hostels are cheaper, but it’s like a gamble.
17 00:01:39.700 ⇒ 00:01:40.810 Hannah Wang: Your roommate might.
18 00:01:40.810 ⇒ 00:01:46.859 Amber Lin: I know I I mostly gamble for snores and interesting smells.
19 00:01:46.860 ⇒ 00:01:47.586 Hannah Wang: Oh, ew.
20 00:01:49.610 ⇒ 00:01:57.780 Amber Lin: Usually those are fine if you live in a female dorm, but if it’s a mixed dorm that you get interesting things.
21 00:01:58.330 ⇒ 00:02:02.459 Hannah Wang: No dude snoring is a problem like a lot of.
22 00:02:02.460 ⇒ 00:02:08.860 Amber Lin: No, that’s why I think if you date someone, you should sleep with them, sleep in the same bed.
23 00:02:09.570 ⇒ 00:02:10.280 Hannah Wang: Yeah.
24 00:02:10.990 ⇒ 00:02:20.700 Amber Lin: Before you decide. I know. Cause. What if you’re deep in a relationship and you discover they snore badly. So bad.
25 00:02:20.700 ⇒ 00:02:23.410 Hannah Wang: Not a deal breaker. If you love them enough, you know.
26 00:02:23.410 ⇒ 00:02:25.800 Amber Lin: I can’t sleep.
27 00:02:25.940 ⇒ 00:02:33.120 Hannah Wang: You he has. Your partner will have to get like sleep. Apnea tests or something.
28 00:02:34.165 ⇒ 00:02:39.270 Hannah Wang: Yeah, I know, like, apparently there’s like tongue exercises. You can do to.
29 00:02:39.270 ⇒ 00:02:39.930 Amber Lin: Hmm.
30 00:02:39.930 ⇒ 00:02:41.317 Hannah Wang: Like reduce snoring.
31 00:02:41.780 ⇒ 00:02:42.890 Amber Lin: Interesting.
32 00:02:43.440 ⇒ 00:02:48.139 Hannah Wang: Yeah. Eric used to snore a lot, but then, which is pillow.
33 00:02:48.140 ⇒ 00:02:51.349 Amber Lin: Oh, gosh, yeah, it’s mostly the pillow.
34 00:02:51.350 ⇒ 00:02:51.690 Hannah Wang: Position.
35 00:02:51.690 ⇒ 00:02:54.580 Amber Lin: Of your head, and how it blocks your tongue.
36 00:02:54.840 ⇒ 00:03:01.980 Hannah Wang: Yeah, like was too high. So I think his tongue, just like got jammed into his throat or
37 00:03:02.990 ⇒ 00:03:05.420 Hannah Wang: pathway of breathing, and that he’s.
38 00:03:05.420 ⇒ 00:03:07.290 Amber Lin: I see, I see.
39 00:03:07.290 ⇒ 00:03:10.790 Hannah Wang: That, or I became a deep, deeper sleeper. But I don’t think so.
40 00:03:11.440 ⇒ 00:03:13.620 Hannah Wang: So that’s good.
41 00:03:13.620 ⇒ 00:03:15.210 Hannah Wang: Okay.
42 00:03:15.770 ⇒ 00:03:17.450 Amber Lin: Ohtam’s here! Hi.
43 00:03:17.450 ⇒ 00:03:18.020 Uttam Kumaran: Hello!
44 00:03:19.750 ⇒ 00:03:22.740 Uttam Kumaran: Last meeting of the day. I’m so happy.
45 00:03:22.740 ⇒ 00:03:25.999 Amber Lin: So how did the what was the matter? More meeting seem fine? I I feel
46 00:03:26.000 ⇒ 00:03:38.119 Amber Lin: it seemed fine. If it’s also because they finally figure things out. I think this is the client I’ve detested the most so far, because I’ve had a bad experience.
47 00:03:38.960 ⇒ 00:03:39.320 Uttam Kumaran: But they.
48 00:03:39.320 ⇒ 00:03:40.499 Amber Lin: But I think now is fine.
49 00:03:40.500 ⇒ 00:03:42.419 Uttam Kumaran: Like there’s like nothing wrong.
50 00:03:42.600 ⇒ 00:03:45.040 Amber Lin: I know, but like every time
51 00:03:45.340 ⇒ 00:04:00.889 Amber Lin: he makes it seem like it’s such a big deal, and and that, and that everything’s wrong, and I think I don’t like to speak in absolutes. And I was thinking today I was like, Why does Utam give Matthew so much more confidence?
52 00:04:01.640 ⇒ 00:04:03.140 Amber Lin: Cause you used to say, Oh.
53 00:04:03.140 ⇒ 00:04:06.080 Uttam Kumaran: I kind of just like well, one I
54 00:04:06.280 ⇒ 00:04:09.840 Uttam Kumaran: I tend to say you are right, but you know a lot.
55 00:04:10.110 ⇒ 00:04:10.530 Amber Lin: Hmm.
56 00:04:10.940 ⇒ 00:04:13.029 Uttam Kumaran: And then the second piece is.
57 00:04:13.560 ⇒ 00:04:20.609 Uttam Kumaran: you just have to know who your audience is like. Some people are really good with admitting what they don’t know some people. They aren’t good with that
58 00:04:24.940 ⇒ 00:04:25.800 Amber Lin: Hmm.
59 00:04:25.800 ⇒ 00:04:28.549 Uttam Kumaran: Like the second piece is a lot on like
60 00:04:29.700 ⇒ 00:04:42.129 Uttam Kumaran: I just like sort of it’s like, I know he’s kind of like. They’re just a little all over the place. So one is like, I’m just there. The Matthew does not have the confidence to validate whether whether we’re right.
61 00:04:42.564 ⇒ 00:04:46.649 Amber Lin: In order to do that, we have to sort of like over execute.
62 00:04:46.900 ⇒ 00:04:49.660 Uttam Kumaran: And then get Trevor to be like they’re right.
63 00:04:50.060 ⇒ 00:04:51.110 Amber Lin: Hmm.
64 00:04:51.110 ⇒ 00:04:54.710 Uttam Kumaran: I guess Trevor is the true, like authority on the technical side.
65 00:04:56.168 ⇒ 00:05:01.800 Uttam Kumaran: The second piece is like a way, should have been able to answer all those questions like.
66 00:05:01.800 ⇒ 00:05:02.410 Amber Lin: Yeah.
67 00:05:02.410 ⇒ 00:05:07.539 Uttam Kumaran: Dbt, why is this not happening like I didn’t say anything new.
68 00:05:07.780 ⇒ 00:05:08.350 Uttam Kumaran: That means
69 00:05:08.350 ⇒ 00:05:13.329 Uttam Kumaran: done all the work. I the only thing I’m I was like, why didn’t Luke put all this into Dbt yet
70 00:05:14.170 ⇒ 00:05:18.170 Uttam Kumaran: like, why did he create the views? But like someone should, someone should have asked him that. But
71 00:05:19.650 ⇒ 00:05:20.850 Uttam Kumaran: yeah, that’s it.
72 00:05:20.970 ⇒ 00:05:41.289 Amber Lin: Oh, well, and I I feel better after this meeting. I think it was a combination of I don’t have things planned, and then they don’t know what they want, and then I just feel extra bad on my behalf on their behalf, and it just it should show. But I think I’m good now, like, after we did that planning, I and did this meeting. I think I’m feeling better.
73 00:05:41.290 ⇒ 00:05:44.590 Uttam Kumaran: Yeah, just don’t also don’t overthink it. This is actually like.
74 00:05:44.870 ⇒ 00:05:47.080 Uttam Kumaran: this is a very, very simple.
75 00:05:47.290 ⇒ 00:05:49.580 Amber Lin: Yeah, I know.
76 00:05:49.580 ⇒ 00:05:51.020 Uttam Kumaran: And then it’s also clear where he was like.
77 00:05:51.020 ⇒ 00:05:51.620 Amber Lin: Yeah.
78 00:05:51.620 ⇒ 00:05:58.380 Uttam Kumaran: Like, I don’t want like. Let’s not even care about the decks. I’m like, okay, so like, what should we do like you sort of let. I want them to sort of
79 00:05:58.640 ⇒ 00:05:59.300 Uttam Kumaran: dictate.
80 00:05:59.760 ⇒ 00:06:04.629 Uttam Kumaran: But also, like, I’m also gonna push back when I hear that, like we didn’t do something right. Or
81 00:06:05.010 ⇒ 00:06:06.500 Uttam Kumaran: I’m gonna say, like, Look you
82 00:06:06.850 ⇒ 00:06:08.999 Uttam Kumaran: like. We’re trying our best, but like you can’t.
83 00:06:09.000 ⇒ 00:06:12.899 Amber Lin: I know they gave. They told us to do the visualizations. We did the visualization.
84 00:06:13.220 ⇒ 00:06:14.580 Amber Lin: Now they want something else.
85 00:06:14.580 ⇒ 00:06:17.930 Uttam Kumaran: I guess this is where I’m saying is that if you say Go, do the viz.
86 00:06:18.830 ⇒ 00:06:25.919 Uttam Kumaran: Like I should have been there to be like. Oh, we need we should not. We should not have done 3 weeks of python biz.
87 00:06:25.920 ⇒ 00:06:26.930 Amber Lin: Yeah, yeah.
88 00:06:27.210 ⇒ 00:06:32.030 Uttam Kumaran: Like I didn’t know we were still doing python. This cause like that was supposed to be a week.
89 00:06:32.490 ⇒ 00:06:38.119 Uttam Kumaran: So we need technically to call the to call alerts.
90 00:06:39.450 ⇒ 00:06:40.989 Amber Lin: Is what I hear.
91 00:06:41.240 ⇒ 00:06:41.910 Uttam Kumaran: Yes.
92 00:06:42.130 ⇒ 00:06:43.630 Amber Lin: Awesome, noted.
93 00:06:46.250 ⇒ 00:06:47.110 Uttam Kumaran: Yeah.
94 00:06:49.380 ⇒ 00:07:01.739 Amber Lin: anyways, I’m good. I’m good about that. Now, I just before that meeting, I felt like a little stressed, but it has it has improved. So about our Friday meeting.
95 00:07:02.130 ⇒ 00:07:05.089 Uttam Kumaran: Also I can get you. We work passes by the way.
96 00:07:05.570 ⇒ 00:07:08.805 Amber Lin: I know I’m in, but I’m in Chicago.
97 00:07:09.210 ⇒ 00:07:13.230 Uttam Kumaran: I know, but like it’s also loud in the these coffee shops, and you’re on a wire.
98 00:07:13.230 ⇒ 00:07:17.200 Amber Lin: That is, that is true. That is true. I admit that is true.
99 00:07:17.200 ⇒ 00:07:19.029 Uttam Kumaran: Yeah. So I just like.
100 00:07:19.460 ⇒ 00:07:24.689 Uttam Kumaran: what? What’s if we’re some of these contracts are like 30, 40 grand. I can get you a $30 we work like. I don’t mind.
101 00:07:25.680 ⇒ 00:07:27.229 Uttam Kumaran: Gonna keep our clients.
102 00:07:27.760 ⇒ 00:07:28.330 Amber Lin: Okay.
103 00:07:28.330 ⇒ 00:07:29.612 Uttam Kumaran: That’s my math.
104 00:07:30.040 ⇒ 00:07:30.470 Amber Lin: Oh, good!
105 00:07:30.470 ⇒ 00:07:32.520 Uttam Kumaran: Or if you’re like able to actually like.
106 00:07:33.010 ⇒ 00:07:36.259 Uttam Kumaran: get stuff done and not like, yeah, that’s more.
107 00:07:36.260 ⇒ 00:07:37.249 Amber Lin: I don’t get.
108 00:07:37.250 ⇒ 00:07:38.320 Uttam Kumaran: It’s not about you getting it.
109 00:07:38.320 ⇒ 00:07:38.730 Amber Lin: Done.
110 00:07:38.730 ⇒ 00:07:39.670 Uttam Kumaran: More of like.
111 00:07:39.970 ⇒ 00:07:41.729 Amber Lin: Does it look professional to the client.
112 00:07:41.730 ⇒ 00:07:49.077 Uttam Kumaran: Like professional. So like, yeah, I don’t want you to be like scrambling 1st finding. I mean, I was doing that for a long time. So
113 00:07:50.310 ⇒ 00:07:53.969 Amber Lin: Yeah. Well, I find that it’s a nice way to travel.
114 00:07:54.280 ⇒ 00:07:55.310 Amber Lin: So.
115 00:07:55.310 ⇒ 00:07:55.970 Uttam Kumaran: Yeah.
116 00:07:57.240 ⇒ 00:08:00.620 Uttam Kumaran: You know, it’s it’s also we work. It’s really cheap. It’s like 30 bucks.
117 00:08:00.620 ⇒ 00:08:01.890 Amber Lin: Okay, I’ll consider.
118 00:08:01.890 ⇒ 00:08:05.610 Uttam Kumaran: You’ll end. You’ll end up spending 7 bucks and uber to get to wherever you’re going.
119 00:08:05.610 ⇒ 00:08:07.580 Amber Lin: Oh, that’s yeah. That’s true.
120 00:08:08.410 ⇒ 00:08:09.550 Amber Lin: Okay.
121 00:08:09.550 ⇒ 00:08:11.229 Uttam Kumaran: Okay, let’s talk about this stuff.
122 00:08:12.418 ⇒ 00:08:19.220 Amber Lin: Tomorrow. We don’t have someone presenting. So Hannah’s presenting, I believe.
123 00:08:19.370 ⇒ 00:08:20.050 Hannah Wang: Yeah.
124 00:08:20.300 ⇒ 00:08:21.120 Amber Lin: Okay?
125 00:08:21.420 ⇒ 00:08:24.829 Amber Lin: And do we have the slides ready for that?
126 00:08:25.060 ⇒ 00:08:26.709 Hannah Wang: Yup. I put it in the chat.
127 00:08:26.710 ⇒ 00:08:28.210 Amber Lin: Yay, okay.
128 00:08:29.750 ⇒ 00:08:34.580 Amber Lin: So we have that in terms of.
129 00:08:35.030 ⇒ 00:08:38.140 Hannah Wang: In terms of Demos. Yes, I can’t.
130 00:08:38.140 ⇒ 00:08:40.909 Amber Lin: Talk about the Pm tech, lead stuff.
131 00:08:41.440 ⇒ 00:08:43.609 Hannah Wang: Oh, that’s what that stands for. Okay.
132 00:08:43.610 ⇒ 00:08:44.130 Amber Lin: Yeah.
133 00:08:44.130 ⇒ 00:08:45.250 Hannah Wang: It’s a cycle.
134 00:08:45.250 ⇒ 00:08:46.740 Amber Lin: Yeah, I know it’s confusing.
135 00:08:48.171 ⇒ 00:08:52.877 Hannah Wang: Okay, yeah. I mean, I got the icebreaker. I got the lab share.
136 00:08:53.680 ⇒ 00:09:19.570 Hannah Wang: I just need one of you, Tom or Robert, one of you to update this or these 3 slides, and then I have 3 demos lined up. 1st one is the AI stuff you talked about. Second is the tech lead stuff. And then, 3, rd I asked Annie if she’s okay presenting her Eden stuff, and if she is, and I’ll keep this, if not, we can delete it and then I just left
137 00:09:19.760 ⇒ 00:09:22.922 Hannah Wang: these last slides as they are.
138 00:09:24.160 ⇒ 00:09:27.500 Hannah Wang: Anything else I should add or figure out.
139 00:09:29.300 ⇒ 00:09:30.669 Uttam Kumaran: I think that’s okay.
140 00:09:31.370 ⇒ 00:09:38.280 Amber Lin: Yeah, do we have a slide that we kind of go through every single client, and how they’re doing.
141 00:09:38.280 ⇒ 00:09:39.879 Hannah Wang: Yeah, slide, 10.
142 00:09:40.220 ⇒ 00:09:48.070 Amber Lin: Okay, are we, Todd? Are we gonna talk about our current hiring plans?
143 00:09:49.210 ⇒ 00:09:51.850 Uttam Kumaran: Well, okay, well, let me. I think on this slide.
144 00:09:52.210 ⇒ 00:09:55.650 Uttam Kumaran: Do we want to talk about like the Pm tech lead
145 00:09:56.730 ⇒ 00:09:58.790 Uttam Kumaran: and add those as columns here.
146 00:10:00.690 ⇒ 00:10:02.720 Amber Lin: Oh, sure! Why don’t we, that we’ve
147 00:10:02.720 ⇒ 00:10:07.969 Amber Lin: be over the notion table? We don’t need to make a new one. Just make a screenshot.
148 00:10:09.140 ⇒ 00:10:11.789 Uttam Kumaran: Well, I want to do the progress thing here, and the notion.
149 00:10:11.790 ⇒ 00:10:12.230 Amber Lin: Oh!
150 00:10:12.530 ⇒ 00:10:14.029 Uttam Kumaran: The screenshots can look ugly.
151 00:10:14.030 ⇒ 00:10:14.575 Amber Lin: Okay.
152 00:10:15.120 ⇒ 00:10:15.470 Amber Lin: Ha-ha!
153 00:10:15.470 ⇒ 00:10:18.730 Amber Lin: Okay, not that. I thought our slide looked pretty.
154 00:10:19.410 ⇒ 00:10:21.779 Uttam Kumaran: Like it’s just like I feel like I’m
155 00:10:22.480 ⇒ 00:10:27.990 Uttam Kumaran: yo jay today on the call with him. Hannah was like, I’ve never seen a software company like.
156 00:10:28.670 ⇒ 00:10:31.149 Uttam Kumaran: have a good fucking website.
157 00:10:31.150 ⇒ 00:10:31.590 Amber Lin: Yeah, yeah.
158 00:10:32.010 ⇒ 00:10:35.659 Uttam Kumaran: Yeah, he was like, it’s he’s like, yo really kudos. I was like, Yeah, I know.
159 00:10:35.660 ⇒ 00:10:36.690 Hannah Wang: He! He! He!
160 00:10:36.690 ⇒ 00:10:37.400 Uttam Kumaran: 9.
161 00:10:37.700 ⇒ 00:10:38.210 Amber Lin: Yay!
162 00:10:38.210 ⇒ 00:10:38.849 Hannah Wang: And then.
163 00:10:38.850 ⇒ 00:10:39.630 Uttam Kumaran: Trying.
164 00:10:39.630 ⇒ 00:10:40.450 Hannah Wang: Yeah.
165 00:10:43.633 ⇒ 00:10:49.889 Hannah Wang: Insert column like that. Pm, and tech lead.
166 00:10:52.275 ⇒ 00:10:53.320 Uttam Kumaran: Yes.
167 00:10:55.170 ⇒ 00:11:03.310 Uttam Kumaran: And should we do like a account? Executive 4.
168 00:11:04.930 ⇒ 00:11:07.530 Uttam Kumaran: I just wanna make it really clear what the.
169 00:11:07.830 ⇒ 00:11:08.850 Amber Lin: It’s okay.
170 00:11:08.850 ⇒ 00:11:12.500 Uttam Kumaran: Yeah, or you just do a, you could just do ae and tl.
171 00:11:12.760 ⇒ 00:11:16.559 Amber Lin: Hey? He sounds like analytics, analytics, engineer.
172 00:11:16.560 ⇒ 00:11:17.240 Hannah Wang: Yeah, it does.
173 00:11:17.240 ⇒ 00:11:19.140 Uttam Kumaran: Just okay, can do account.
174 00:11:19.140 ⇒ 00:11:20.490 Amber Lin: Owner. Yeah.
175 00:11:20.730 ⇒ 00:11:23.440 Uttam Kumaran: You do acc dot EX.
176 00:11:23.440 ⇒ 00:11:24.190 Amber Lin: Oh! Hi!
177 00:11:24.480 ⇒ 00:11:25.140 Uttam Kumaran: Yeah.
178 00:11:25.470 ⇒ 00:11:26.385 Amber Lin: Yeah, how about?
179 00:11:26.880 ⇒ 00:11:27.520 Uttam Kumaran: Great.
180 00:11:27.720 ⇒ 00:11:30.831 Uttam Kumaran: I’ll I’ll I can fill
181 00:11:32.150 ⇒ 00:11:35.349 Uttam Kumaran: these out, and then long term we can get little profile circles.
182 00:11:36.280 ⇒ 00:11:36.690 Hannah Wang: Okay.
183 00:11:36.690 ⇒ 00:11:38.270 Amber Lin: Go ahead!
184 00:11:40.136 ⇒ 00:11:47.460 Hannah Wang: Anything else. I’m just gonna fiddle with this as we talk. But huh!
185 00:11:47.928 ⇒ 00:11:50.500 Uttam Kumaran: So Zoom Platform, I’m gonna demo.
186 00:11:51.580 ⇒ 00:11:57.530 Uttam Kumaran: Can. I? I’m just gonna put like, can I just list a couple of like things I wanna
187 00:11:58.230 ⇒ 00:12:01.930 Uttam Kumaran: talk about on this. So I want to talk through
188 00:12:02.530 ⇒ 00:12:10.450 Uttam Kumaran: a couple of like use cases like how to create tickets from a meeting.
189 00:12:10.920 ⇒ 00:12:17.360 Uttam Kumaran: I’m also gonna look at how to great tickets.
190 00:12:19.000 ⇒ 00:12:21.359 Uttam Kumaran: What are the other Gpts that I use?
191 00:12:25.710 ⇒ 00:12:32.670 Uttam Kumaran: Oh, yeah, how to create black updates from tickets?
192 00:12:36.180 ⇒ 00:12:37.329 Uttam Kumaran: I’m gonna do.
193 00:12:37.330 ⇒ 00:12:40.149 Amber Lin: And also the scoping. We have a.
194 00:12:40.150 ⇒ 00:12:45.069 Uttam Kumaran: Yeah, how? To determine how to create project scope.
195 00:12:47.270 ⇒ 00:12:48.556 Amber Lin: Project, scope.
196 00:12:50.521 ⇒ 00:12:52.888 Uttam Kumaran: I’m gonna talk about
197 00:12:59.580 ⇒ 00:13:03.019 Amber Lin: Honestly, if we wanna talk about it, we can also talk about
198 00:13:03.190 ⇒ 00:13:05.629 Amber Lin: how to best create a prompt
199 00:13:06.300 ⇒ 00:13:08.530 Amber Lin: let people use your prompt.
200 00:13:08.530 ⇒ 00:13:08.940 Amber Lin: Yeah.
201 00:13:08.940 ⇒ 00:13:10.340 Amber Lin: Oftentimes, sir.
202 00:13:12.090 ⇒ 00:13:13.990 Uttam Kumaran: Yeah, I think I’ll go through these.
203 00:13:17.300 ⇒ 00:13:19.419 Hannah Wang: Nice. That’d be helpful.
204 00:13:26.470 ⇒ 00:13:27.240 Uttam Kumaran: Okay.
205 00:13:31.190 ⇒ 00:13:37.290 Amber Lin: Oh, it’s another update. I interviewed Anna. I put the notes in the project management channel.
206 00:13:37.610 ⇒ 00:13:40.199 Amber Lin: Yeah, I read them. What? What was the what do you think?
207 00:13:40.725 ⇒ 00:13:41.250 Amber Lin: Oh.
208 00:13:41.250 ⇒ 00:13:41.600 Uttam Kumaran: No.
209 00:13:42.300 ⇒ 00:13:52.629 Amber Lin: What do you mean? I can’t say no like what defines yes or no. I think she’s like decent, for maybe.
210 00:13:52.630 ⇒ 00:13:57.530 Uttam Kumaran: It a hell! Yes, like what defines a hell? Yes, we don’t even have it.
211 00:13:57.530 ⇒ 00:14:02.280 Uttam Kumaran: Not that sounds like not a hell anytime. Someone’s like yo. Did you love doing that thing? You’re like hell? Yes.
212 00:14:03.550 ⇒ 00:14:05.860 Amber Lin: Huh, like, very.
213 00:14:05.860 ⇒ 00:14:07.459 Uttam Kumaran: Sounds like a not a hell. Yes.
214 00:14:07.630 ⇒ 00:14:11.020 Amber Lin: Well, it’s not a hell, yes, but do you need a hell? Yes.
215 00:14:11.170 ⇒ 00:14:11.930 Uttam Kumaran: Yes.
216 00:14:12.340 ⇒ 00:14:12.810 Hannah Wang: No.
217 00:14:12.810 ⇒ 00:14:13.339 Amber Lin: Pissed.
218 00:14:14.600 ⇒ 00:14:18.530 Uttam Kumaran: I mean, we don’t need one. And like it’s also like. But also, for example, Con seen.
219 00:14:18.530 ⇒ 00:14:18.890 Amber Lin: And.
220 00:14:18.890 ⇒ 00:14:19.560 Uttam Kumaran: Better.
221 00:14:21.450 ⇒ 00:14:24.190 Amber Lin: True, he might have different rates, though.
222 00:14:25.420 ⇒ 00:14:25.940 Uttam Kumaran: True.
223 00:14:25.940 ⇒ 00:14:26.440 Amber Lin: Oxfor.
224 00:14:26.440 ⇒ 00:14:28.499 Uttam Kumaran: I I hate. Yeah. His rates weren’t that bad?
225 00:14:28.500 ⇒ 00:14:36.570 Amber Lin: Okay cause. Ultimately, we need a Pm. To cover additional projects, and we need them to help shape the
226 00:14:36.730 ⇒ 00:14:38.159 Amber Lin: Pmo puncture.
227 00:14:38.160 ⇒ 00:14:41.399 Uttam Kumaran: It’s just that. I think he’s good because he has a Pmp.
228 00:14:42.490 ⇒ 00:14:47.769 Uttam Kumaran: So if we go, if we buy us towards like, hey, every single person we hire is like better than all of us.
229 00:14:48.220 ⇒ 00:14:48.670 Amber Lin: True.
230 00:14:48.670 ⇒ 00:14:51.649 Uttam Kumaran: That’s my like. That was my cause. That was my criteria. When I look for people.
231 00:14:51.650 ⇒ 00:14:52.030 Amber Lin: True.
232 00:14:52.030 ⇒ 00:14:53.759 Uttam Kumaran: I want to just find people with that.
233 00:14:53.760 ⇒ 00:15:00.296 Amber Lin: Yeah, I mean, if you make me compare without the consideration of money, I would say con over Anna
234 00:15:02.160 ⇒ 00:15:06.450 Amber Lin: but like they both have quite long of experience.
235 00:15:08.610 ⇒ 00:15:12.450 Amber Lin: Iona was working in operations management for a while. So
236 00:15:12.660 ⇒ 00:15:17.220 Amber Lin: that’s also interesting. But I I guess that’s all. That’s not what we need.
237 00:15:17.420 ⇒ 00:15:18.300 Uttam Kumaran: Yeah.
238 00:15:18.470 ⇒ 00:15:27.619 Amber Lin: Yeah, okay, yeah. I mean, probably you have to interview her again, or Alex has to interview her again.
239 00:15:29.900 ⇒ 00:15:30.360 Amber Lin: That’s what.
240 00:15:30.360 ⇒ 00:15:34.340 Uttam Kumaran: Let’s see what I’m gonna see. I’m gonna ask Alex to interview Con first, st
241 00:15:36.080 ⇒ 00:15:42.439 Uttam Kumaran: but I I will. I’ll let’s let’s do something on hiring. I can share just what what roles we’re hiring for, and why.
242 00:15:45.352 ⇒ 00:15:48.889 Hannah Wang: Okay, is that you want that exact update.
243 00:15:50.329 ⇒ 00:15:50.909 Uttam Kumaran: Yeah.
244 00:15:50.960 ⇒ 00:15:51.710 Amber Lin: Sure.
245 00:15:51.710 ⇒ 00:15:52.320 Hannah Wang: Yeah, that’s.
246 00:15:52.320 ⇒ 00:15:57.499 Amber Lin: Or maybe just a slow slide, because we need a web dev, we need Apf.
247 00:15:58.430 ⇒ 00:16:01.780 Amber Lin: and maybe a wish is looking for a intern.
248 00:16:02.470 ⇒ 00:16:04.250 Uttam Kumaran: Yeah, I can put that.
249 00:16:05.270 ⇒ 00:16:07.369 Uttam Kumaran: Where did my slides go?
250 00:16:48.370 ⇒ 00:16:51.680 Amber Lin: Oh, let me go check the polls of who’s gonna be there?
251 00:17:07.520 ⇒ 00:17:09.140 Hannah Wang: I mean, not everyone answered.
252 00:17:10.214 ⇒ 00:17:12.040 Hannah Wang: It’s just 6 6 people.
253 00:17:12.040 ⇒ 00:17:19.760 Amber Lin: Yeah, we only have 8 answers. Casey is now Miguel’s, maybe, and
254 00:17:20.910 ⇒ 00:17:26.539 Amber Lin: 6 attendees haven’t heard from Demote Kyle. Annie.
255 00:17:27.380 ⇒ 00:17:30.520 Uttam Kumaran: Let’s do it cause? Then I’ll just send. We just record it. And I’ll send it there.
256 00:17:31.350 ⇒ 00:17:34.100 Uttam Kumaran: A little mini. Everybody can listen to as a mini podcast.
257 00:17:34.720 ⇒ 00:17:37.320 Amber Lin: I don’t know if they’re gonna do it. But okay.
258 00:17:37.580 ⇒ 00:17:42.439 Uttam Kumaran: That’s fine cause. I also want to have it, because I will start to use this to write my like
259 00:17:43.340 ⇒ 00:17:44.870 Uttam Kumaran: monthly updates.
260 00:17:46.330 ⇒ 00:17:51.469 Amber Lin: Great. And then who for? Whoever’s there we can just play the icebreaker. It’ll be pretty fun.
261 00:18:12.340 ⇒ 00:18:13.950 Hannah Wang: Whoa! You’re on the bus!
262 00:18:14.180 ⇒ 00:18:21.640 Amber Lin: I know I specifically took this bus because it’s next to is driving next to the water.
263 00:18:21.640 ⇒ 00:18:22.760 Hannah Wang: Oh, wow!
264 00:18:22.760 ⇒ 00:18:25.079 Amber Lin: So I’m in Chicago, and I’m heading up.
265 00:18:25.080 ⇒ 00:18:26.909 Uttam Kumaran: I was just in Chicago 4 days ago.
266 00:18:27.070 ⇒ 00:18:32.900 Amber Lin: Oh, I remember, you told me, and then we completely missed each other. Yeah.
267 00:18:35.340 ⇒ 00:18:39.649 Hannah Wang: What part of oh, I guess Chicago is not that big, but.
268 00:18:39.650 ⇒ 00:18:42.234 Amber Lin: It’s not that big.
269 00:18:43.720 ⇒ 00:18:51.999 Amber Lin: I was surprised. I was able to walk most of the time, but it’s it feels really nice. I like it.
270 00:18:52.320 ⇒ 00:18:55.270 Hannah Wang: Yeah, it’s it’s cute. There.
271 00:18:55.270 ⇒ 00:19:00.270 Amber Lin: Because yes, I don’t know. I like it a little bit more than New York.
272 00:19:00.760 ⇒ 00:19:01.240 Hannah Wang: Oh, no!
273 00:19:01.240 ⇒ 00:19:03.100 Hannah Wang: New York’s like so chaotic.
274 00:19:07.240 ⇒ 00:19:07.700 Uttam Kumaran: Funny.
275 00:19:09.800 ⇒ 00:19:11.780 Uttam Kumaran: I’m gonna go see, Robert, I think end of the month.
276 00:19:11.780 ⇒ 00:19:21.380 Amber Lin: Oh, okay, exciting I was. I tried to meet him, but Robert is not in New York until Friday, so miss him as well.
277 00:19:21.500 ⇒ 00:19:22.240 Amber Lin: Good.
278 00:19:22.710 ⇒ 00:19:23.797 Amber Lin: It’s a good day.
279 00:19:28.453 ⇒ 00:19:34.499 Amber Lin: Okay. Seems like everything we have is in place. We’re ready.
280 00:19:34.500 ⇒ 00:19:36.989 Uttam Kumaran: Demo so tech lead pm, work.
281 00:19:37.830 ⇒ 00:19:42.389 Uttam Kumaran: He didn’t report certification updates.
282 00:19:46.350 ⇒ 00:19:51.679 Hannah Wang: Oh, wait! Sorry! Where do you want me to add the hiring update.
283 00:19:54.480 ⇒ 00:19:57.930 Uttam Kumaran: Let’s let’s just do it instead of stretch this week.
284 00:19:57.930 ⇒ 00:20:03.370 Hannah Wang: Okay, I’m gonna hide this slide.
285 00:20:10.520 ⇒ 00:20:11.470 Hannah Wang: Okay.
286 00:20:17.910 ⇒ 00:20:21.950 Uttam Kumaran: Yeah. And I’m not gonna go through all, not gonna go through the sales thing. I guess
287 00:20:22.200 ⇒ 00:20:24.060 Uttam Kumaran: I’ll try to do this once a month.
288 00:20:24.820 ⇒ 00:20:25.790 Hannah Wang: Okay.
289 00:20:26.340 ⇒ 00:20:28.980 Uttam Kumaran: I can. I’ll just talk about it in the exact updates.
290 00:20:30.340 ⇒ 00:20:31.133 Hannah Wang: Yeah. Okay.
291 00:20:35.300 ⇒ 00:20:38.710 Hannah Wang: Okay. Cool. Anything else.
292 00:20:39.840 ⇒ 00:20:42.349 Uttam Kumaran: Are we gonna do a icebreaker? Okay.
293 00:20:42.530 ⇒ 00:20:43.370 Hannah Wang: Yeah.
294 00:20:44.210 ⇒ 00:20:45.290 Amber Lin: Please like.
295 00:20:45.290 ⇒ 00:20:48.360 Hannah Wang: And are like fun, or I don’t know. It’s not like a question.
296 00:20:50.060 ⇒ 00:20:50.560 Uttam Kumaran: Yes.
297 00:20:50.960 ⇒ 00:20:51.340 Hannah Wang: So.
298 00:20:51.340 ⇒ 00:20:57.490 Amber Lin: Awesome, you know. We should probably try to have the camera on policy as well.
299 00:20:58.140 ⇒ 00:20:58.790 Uttam Kumaran: Yes.
300 00:20:58.790 ⇒ 00:20:59.675 Amber Lin: Yeah.
301 00:21:00.560 ⇒ 00:21:06.570 Uttam Kumaran: I’ll send a note. I’ll send a note today, just saying I’ll send it out
302 00:21:06.570 ⇒ 00:21:08.040 Uttam Kumaran: right now. Just say like, Hey, we’re.
303 00:21:08.040 ⇒ 00:21:10.450 Amber Lin: Like Gloria, awesome.
304 00:21:23.600 ⇒ 00:21:24.260 Uttam Kumaran: Okay.
305 00:21:24.600 ⇒ 00:21:25.150 Hannah Wang: Okay.
306 00:21:25.530 ⇒ 00:21:27.060 Amber Lin: All right.
307 00:21:27.610 ⇒ 00:21:29.810 Uttam Kumaran: Anything, Hannah, you need from me
308 00:21:30.630 ⇒ 00:21:32.580 Uttam Kumaran: a bunch of stuff to review.
309 00:21:33.630 ⇒ 00:21:39.090 Hannah Wang: I know you, asked Robert to review the partner. Kit stuff. But then.
310 00:21:39.270 ⇒ 00:21:44.060 Hannah Wang: yeah, there’s like a couple of comments here and there. You can just like
311 00:21:44.480 ⇒ 00:21:50.381 Hannah Wang: check out the sales thread. I think I like tagged you in it.
312 00:21:51.810 ⇒ 00:22:02.620 Hannah Wang: But other than that oh, I made a 1 pager for the what is it called lead.
313 00:22:03.030 ⇒ 00:22:08.829 Hannah Wang: or the thing that Mustafa did? The AI case study that you sent me.
314 00:22:08.830 ⇒ 00:22:09.739 Amber Lin: Oh, wow!
315 00:22:09.740 ⇒ 00:22:12.239 Hannah Wang: I just made a 1 pager for that one cause I know.
316 00:22:12.240 ⇒ 00:22:12.990 Uttam Kumaran: Okay.
317 00:22:12.990 ⇒ 00:22:17.559 Hannah Wang: For tomorrow, but I didn’t wanna like keep bothering you about which one is.
318 00:22:17.560 ⇒ 00:22:19.770 Uttam Kumaran: Oh, I, yeah, okay, that’s helpful.
319 00:22:20.150 ⇒ 00:22:25.710 Hannah Wang: I made one I don’t know where. If I tagged you in it or not, I think I.
320 00:22:26.350 ⇒ 00:22:27.219 Uttam Kumaran: You did.
321 00:22:27.220 ⇒ 00:22:34.390 Hannah Wang: Message. Yeah. So I made it. There’s some copy that I need help for. But it’s like, basically done
322 00:22:34.560 ⇒ 00:22:40.430 Hannah Wang: in in case you like need it tomorrow. But yeah, let me know like which one you want me to
323 00:22:40.750 ⇒ 00:22:42.069 Hannah Wang: tackle next.
324 00:22:42.450 ⇒ 00:22:43.000 Uttam Kumaran: Okay.
325 00:22:44.180 ⇒ 00:22:46.438 Hannah Wang: But yeah, hopefully, that’s helpful.
326 00:22:47.970 ⇒ 00:22:52.609 Hannah Wang: And other than that, I think we’re good. Yeah.
327 00:22:52.610 ⇒ 00:22:53.300 Uttam Kumaran: Okay.
328 00:22:57.260 ⇒ 00:22:57.770 Hannah Wang: Okay.
329 00:22:57.770 ⇒ 00:23:00.359 Amber Lin: Yay, thanks, everybody.
330 00:23:01.120 ⇒ 00:23:01.940 Uttam Kumaran: Thank you.
331 00:23:02.450 ⇒ 00:23:03.720 Uttam Kumaran: Talk to you soon.
332 00:23:03.720 ⇒ 00:23:05.619 Amber Lin: Okay. Talk tomorrow. Bye, bye.
333 00:23:05.620 ⇒ 00:23:06.370 Uttam Kumaran: By.