Meeting Title: Brainforge Weekly Sync Date: 2026-05-12 Meeting participants: Advait Nandakumar Menon, Jasmin Multani
WEBVTT
1 00:00:30.280 ⇒ 00:00:31.489 Jasmin Multani: Hey, Abdiv.
2 00:00:33.960 ⇒ 00:00:35.039 Advait Nandakumar Menon: Hey, that’s my name.
3 00:00:35.340 ⇒ 00:00:36.549 Advait Nandakumar Menon: How’s it going?
4 00:00:36.960 ⇒ 00:00:38.490 Jasmin Multani: It’s going!
5 00:00:39.420 ⇒ 00:00:41.259 Advait Nandakumar Menon: Yep, same here.
6 00:00:43.800 ⇒ 00:00:44.520 Jasmin Multani: Great.
7 00:00:44.670 ⇒ 00:00:49.660 Jasmin Multani: You’re updating your Clockify, like… Super succinctly, right?
8 00:00:50.190 ⇒ 00:00:50.950 Advait Nandakumar Menon: Yeah, yeah.
9 00:00:51.720 ⇒ 00:00:54.740 Jasmin Multani: Okay, okay, just wanna make sure. I saw you were up at, like…
10 00:00:55.320 ⇒ 00:00:59.260 Jasmin Multani: You were up pretty early this morning, so I just want to make sure that’s also being recorded.
11 00:00:59.690 ⇒ 00:01:04.470 Advait Nandakumar Menon: Yeah, sometimes I… I work late night, sometimes I work early morning.
12 00:01:04.470 ⇒ 00:01:05.000 Jasmin Multani: Yeah.
13 00:01:05.000 ⇒ 00:01:07.240 Advait Nandakumar Menon: so… Yeah.
14 00:01:07.540 ⇒ 00:01:17.240 Jasmin Multani: as long as, like, the total hours are accurate, that’s what we’ll need, because Brill is asking us to also monitor when people go
15 00:01:17.480 ⇒ 00:01:24.279 Jasmin Multani: Overtime, so that he can… the team can also be like, oh, we need to advocate for more, we’re…
16 00:01:24.950 ⇒ 00:01:27.329 Jasmin Multani: Hourly charges, from the client.
17 00:01:27.920 ⇒ 00:01:30.080 Jasmin Multani: So it’s not a penalty.
18 00:01:30.080 ⇒ 00:01:32.970 Advait Nandakumar Menon: Okay. I do try to…
19 00:01:33.310 ⇒ 00:01:41.449 Advait Nandakumar Menon: stick to the 8 hours limit that’s assigned to me, so maybe that’s… are you seeing any discrepancy? Is that why you’re asking?
20 00:01:41.450 ⇒ 00:01:45.370 Jasmin Multani: No, no, I haven’t done… I haven’t checked yet, so I’m just like, as long as it’s 8…
21 00:01:45.730 ⇒ 00:01:48.939 Jasmin Multani: That’s what Bill told me, and I was like, okay, I’m gonna have to check into this.
22 00:01:49.490 ⇒ 00:01:52.970 Jasmin Multani: I know Amber’s are succinct, but yeah.
23 00:01:53.480 ⇒ 00:02:06.459 Advait Nandakumar Menon: So, water is going above 8, I usually don’t clock it in, because it doesn’t happen all the time, but there are days, especially this week, since default is there, and next week, we are meeting the milestone as well, so…
24 00:02:06.630 ⇒ 00:02:13.830 Advait Nandakumar Menon: Yeah, sometimes I try not… I try to not let it go above 8 hours, so…
25 00:02:13.830 ⇒ 00:02:17.200 Jasmin Multani: Okay, cool, cool, cool. No worries. And it’s not a penalty, I’m just like…
26 00:02:17.630 ⇒ 00:02:17.990 Advait Nandakumar Menon: Okay.
27 00:02:17.990 ⇒ 00:02:21.740 Jasmin Multani: check everything, and I work odd hours, too.
28 00:02:22.160 ⇒ 00:02:28.369 Jasmin Multani: And, like, it’s like, when do I have… when does my brain function to do I see work, and, like.
29 00:02:28.480 ⇒ 00:02:36.419 Jasmin Multani: when does my brain function when I can do review work? So I think I’m gonna change up my hours as well, but I’ll be available.
30 00:02:37.040 ⇒ 00:02:38.160 Advait Nandakumar Menon: Yeah, yeah.
31 00:02:38.610 ⇒ 00:02:39.659 Advait Nandakumar Menon: Sounds good.
32 00:02:40.400 ⇒ 00:02:44.209 Advait Nandakumar Menon: And I noticed you were pretty early as well, you were available today.
33 00:02:44.540 ⇒ 00:02:49.310 Jasmin Multani: Yeah, I was like… I’m behind. I’ve been…
34 00:02:49.310 ⇒ 00:02:49.810 Advait Nandakumar Menon: I feel like it.
35 00:02:49.810 ⇒ 00:02:50.760 Jasmin Multani: behind.
36 00:02:50.900 ⇒ 00:02:57.969 Jasmin Multani: So, I don’t know how long, like, I prefer having slow mornings, and just, like.
37 00:02:58.270 ⇒ 00:03:00.949 Jasmin Multani: Reading, waking up really slow, eating.
38 00:03:01.360 ⇒ 00:03:04.420 Jasmin Multani: But then I realized, like, that’s…
39 00:03:05.120 ⇒ 00:03:10.279 Jasmin Multani: I also need to coordinate when Robert does his sale pitches, and I feel like…
40 00:03:10.450 ⇒ 00:03:11.200 Advait Nandakumar Menon: I don’t know.
41 00:03:11.530 ⇒ 00:03:16.859 Jasmin Multani: So then I’m like, oh, shoot, like, I have to give these… this information to him ASAP.
42 00:03:17.280 ⇒ 00:03:20.380 Jasmin Multani: So that he can, like, improve his sales pitch, because he’s.
43 00:03:20.380 ⇒ 00:03:20.790 Advait Nandakumar Menon: Yeah.
44 00:03:20.790 ⇒ 00:03:23.100 Jasmin Multani: Literally flies out and meets these clients.
45 00:03:24.080 ⇒ 00:03:29.859 Jasmin Multani: So I’m like, okay… Certain things should be urgently done every morning.
46 00:03:29.860 ⇒ 00:03:30.190 Advait Nandakumar Menon: Right.
47 00:03:30.470 ⇒ 00:03:32.380 Jasmin Multani: And there’s just, like, a lot of, like.
48 00:03:34.210 ⇒ 00:03:40.779 Jasmin Multani: admin stuff, and I’m like, oh my god. Right. So, I think I have to, like, change the way I work a little.
49 00:03:41.430 ⇒ 00:03:45.369 Jasmin Multani: But I really want to keep the first 2 hours.
50 00:03:45.480 ⇒ 00:03:48.150 Jasmin Multani: Of waking up to be just, like, slow.
51 00:03:48.610 ⇒ 00:03:49.130 Advait Nandakumar Menon: Hmm.
52 00:03:49.130 ⇒ 00:03:51.560 Jasmin Multani: But we’ll see how that works.
53 00:03:51.930 ⇒ 00:03:54.079 Advait Nandakumar Menon: Yeah, yeah, I understand.
54 00:03:54.700 ⇒ 00:04:05.109 Jasmin Multani: Cool, cool, cool, cool. And then I think how I’ll do is, like, in the even… in the afternoons, I’ll still be on Slack, but, like, focus will be on, like.
55 00:04:05.390 ⇒ 00:04:09.459 Jasmin Multani: immediately reviewing your work. So I think I’m gonna front-load my personal work.
56 00:04:09.590 ⇒ 00:04:16.160 Jasmin Multani: And, like, doing things that are across clients. And then,
57 00:04:16.310 ⇒ 00:04:21.119 Jasmin Multani: end my day by, like, checking, because I feel like my brain is better… my brain can review throughout.
58 00:04:21.959 ⇒ 00:04:22.969 Advait Nandakumar Menon: No.
59 00:04:22.970 ⇒ 00:04:24.500 Jasmin Multani: words, but…
60 00:04:24.760 ⇒ 00:04:31.190 Jasmin Multani: Yeah. If there’s anything you urgently need, let me know, be like, hey, I need this answer now, versus…
61 00:04:31.710 ⇒ 00:04:32.500 Jasmin Multani: disconnected.
62 00:04:33.260 ⇒ 00:04:34.250 Jasmin Multani: Yep, yep.
63 00:04:34.630 ⇒ 00:04:43.910 Jasmin Multani: Awesome. So, let’s talk tickets and work streams. Is there anything you wanna… Talk about, first off.
64 00:04:44.850 ⇒ 00:04:52.260 Advait Nandakumar Menon: Apart from this, I don’t think so, except, I scheduled a monthly check-in, I think that…
65 00:04:52.480 ⇒ 00:04:56.429 Advait Nandakumar Menon: Something that slipped away, so I think you asked for Thursday, right?
66 00:04:56.610 ⇒ 00:05:00.029 Jasmin Multani: Yeah, just cause I’m gonna be out of office on Friday, so…
67 00:05:01.210 ⇒ 00:05:06.679 Jasmin Multani: there is one meeting I’ll try to make on Friday, but I think I’m just gonna… I might just be on my phone, or I might just watch
68 00:05:07.020 ⇒ 00:05:07.790 Jasmin Multani: coding.
69 00:05:08.190 ⇒ 00:05:08.540 Advait Nandakumar Menon: It’s.
70 00:05:08.540 ⇒ 00:05:12.220 Jasmin Multani: that evaluation… tuning…
71 00:05:12.580 ⇒ 00:05:13.970 Advait Nandakumar Menon: Yeah, yeah, yeah.
72 00:05:16.450 ⇒ 00:05:26.180 Jasmin Multani: Yeah, I might tune in for that. I might just, like, watch the… I’ll probably watch the recording for that, but I feel like your monthly check-ins, we should do that live.
73 00:05:26.180 ⇒ 00:05:27.010 Advait Nandakumar Menon: Okay.
74 00:05:27.010 ⇒ 00:05:30.089 Jasmin Multani: do it on Thursday, or we can do it on Monday, whichever one you like.
75 00:05:30.880 ⇒ 00:05:32.709 Advait Nandakumar Menon: Would Monday work?
76 00:05:32.710 ⇒ 00:05:37.809 Jasmin Multani: Yeah, yeah, I know default is wrapping up, so…
77 00:05:37.810 ⇒ 00:05:48.039 Advait Nandakumar Menon: Yeah, yeah, I appreciate that. And so, with that in mind, I think you mentioned you’ll share some spreadsheet or some file with me so that I can…
78 00:05:48.240 ⇒ 00:05:48.960 Jasmin Multani: Yeah.
79 00:05:48.960 ⇒ 00:05:49.290 Advait Nandakumar Menon: Welcome!
80 00:05:49.290 ⇒ 00:05:53.339 Jasmin Multani: Reminder, did I not share it with you?
81 00:05:53.870 ⇒ 00:05:55.670 Advait Nandakumar Menon: Nope, I didn’t get it.
82 00:05:55.670 ⇒ 00:05:57.360 Jasmin Multani: Oh, sorry, okay.
83 00:05:57.360 ⇒ 00:05:58.780 Advait Nandakumar Menon: No, that’s fine, that’s fine.
84 00:05:58.780 ⇒ 00:06:03.140 Jasmin Multani: I shared it with Amber, but, here.
85 00:06:04.660 ⇒ 00:06:06.940 Jasmin Multani: So, here it is.
86 00:06:07.530 ⇒ 00:06:12.100 Jasmin Multani: Let me know if you have editing access. But basically,
87 00:06:12.270 ⇒ 00:06:15.880 Jasmin Multani: Create a copy of this. We can walk through it right now.
88 00:06:16.530 ⇒ 00:06:27.180 Jasmin Multani: Yeah, that would help. Yeah. So, catch me up on your background, like, your technical background and your education background.
89 00:06:28.720 ⇒ 00:06:40.670 Advait Nandakumar Menon: So I did my… bachelor’s in Computer Science from India. I worked at TCS for almost
90 00:06:40.770 ⇒ 00:06:51.050 Advait Nandakumar Menon: 3 years, so over there, I was, like, BI analyst, and towards the last couple of months, I did some data engineering work as well, so…
91 00:06:51.100 ⇒ 00:07:05.780 Advait Nandakumar Menon: This was for, like, an airline client and a loyalty, so… it’s British Airways, basically, I can tell you that. And they had this, loyalty reward platform as well, so… was working on both those things.
92 00:07:06.220 ⇒ 00:07:11.249 Advait Nandakumar Menon: For data engineering, I primarily worked in Snowflake, migrating.
93 00:07:11.670 ⇒ 00:07:15.660 Advait Nandakumar Menon: data from Redshift to Snowflake.
94 00:07:15.800 ⇒ 00:07:29.279 Advait Nandakumar Menon: And with respect to BA Analyst, I’m not sure if you’ve heard of Teradata, it’s an older legacy warehouse, so I was doing some integration, like, different source system integration, doing some quick analysis.
95 00:07:29.590 ⇒ 00:07:38.919 Advait Nandakumar Menon: Data validation, query cleansing and optimization, all those stuff. So, that was…
96 00:07:39.100 ⇒ 00:07:44.149 Advait Nandakumar Menon: me, after my bachelor’s, then I came here to do my master’s in IT.
97 00:07:44.800 ⇒ 00:07:55.180 Advait Nandakumar Menon: After which, towards the end of the course, like, in my last semester, I started interning in a small startup, same consulting setup as a data analyst.
98 00:07:55.340 ⇒ 00:07:58.090 Advait Nandakumar Menon: I was primarily building dashboards there.
99 00:07:58.360 ⇒ 00:08:02.249 Advait Nandakumar Menon: With Tableau and Snowflake, and…
100 00:08:02.920 ⇒ 00:08:17.419 Advait Nandakumar Menon: basically ingesting data from Salesforce. So we were handling a couple of different clients. I was working on 3 different clients, mainly, so one was for an insurance tech company, so that’s the Salesforce and Tableau and Snowflake stuff.
101 00:08:17.680 ⇒ 00:08:33.170 Advait Nandakumar Menon: The other was manufacturing company, it’s based in Ohio as well. So over here, I was using Power BI and basically getting the data from their ERP, which they are using to manage their workloads, and then QuickBooks for finance as well.
102 00:08:34.030 ⇒ 00:08:48.540 Advait Nandakumar Menon: And then the other… I think I mentioned this to you before, when you mentioned about, the nonprofit that Robert is working with. Yeah, so I work with a non-profit as well. It’s a film commission based out of Cleveland.
103 00:08:48.800 ⇒ 00:08:53.230 Advait Nandakumar Menon: So, for them, basically, they wanted to automate
104 00:08:53.720 ⇒ 00:08:57.980 Advait Nandakumar Menon: How their data gets populated within their donor database.
105 00:08:58.360 ⇒ 00:09:17.969 Advait Nandakumar Menon: So, they weren’t ready to pay for the API keys or any of the API setup, since they are a non-profit, they wanted to save money, so all I really did was set up an automated Excel template, which they can just grab and just click on upload within their donor database. So, this is my background on a high level.
106 00:09:18.280 ⇒ 00:09:23.370 Jasmin Multani: Yeah, so it’s interesting that, like, you graduated with a computer science degree.
107 00:09:23.490 ⇒ 00:09:27.810 Jasmin Multani: Did you… and you fell into data, is that more of, like.
108 00:09:28.050 ⇒ 00:09:36.869 Jasmin Multani: Are you… would you say that you really preferred data over, development work, or was it just, like, what you… what was available?
109 00:09:37.680 ⇒ 00:09:41.839 Advait Nandakumar Menon: I would say it’s something I prefer, because
110 00:09:41.990 ⇒ 00:09:47.249 Advait Nandakumar Menon: I did do a lot of coding in bachelor’s, but… It never really…
111 00:09:48.110 ⇒ 00:09:50.870 Advait Nandakumar Menon: stood out to me, I think data…
112 00:09:51.510 ⇒ 00:09:54.140 Advait Nandakumar Menon: was something I wanted to get into, and…
113 00:09:54.370 ⇒ 00:10:06.390 Advait Nandakumar Menon: like, doing BI work, analyst work, and I think it looked very intriguing to me. And then later on, when I worked as an engineer for some point, that part as well.
114 00:10:07.290 ⇒ 00:10:15.530 Advait Nandakumar Menon: stood out to me, like, setting up the data foundation infrastructure, which, I can slowly develop over time, as well as something I thought
115 00:10:16.060 ⇒ 00:10:23.059 Advait Nandakumar Menon: It will be good to have, because then you will be, like, a full stack, like, you know the engineering part, and then analytics and everything, so…
116 00:10:23.330 ⇒ 00:10:32.120 Advait Nandakumar Menon: Yeah, and also consulting, like, helping different clients and helping them win is something I’m passionate about, so…
117 00:10:32.290 ⇒ 00:10:36.929 Advait Nandakumar Menon: That played a role as well in the couple of companies I worked with.
118 00:10:37.150 ⇒ 00:10:38.309 Jasmin Multani: Okay, cool, cool, cool.
119 00:10:38.640 ⇒ 00:10:42.969 Jasmin Multani: And you say you want to be an engineer. Is that specifically data engineer?
120 00:10:44.060 ⇒ 00:10:54.399 Advait Nandakumar Menon: Yeah, data engineer or analytics engineer, like, I want… like, even day before when… no, day before yesterday, Avesh was explaining about dbt and everything, so…
121 00:10:54.570 ⇒ 00:11:11.500 Advait Nandakumar Menon: I do want to get into those tools a little more, like DBT, Snowflake development, and basically, I think what Aviation Uttam is doing now, and even Demi, but I also want the flexibility to do what we are doing now as well, like…
122 00:11:11.500 ⇒ 00:11:12.210 Jasmin Multani: Hmm…
123 00:11:12.210 ⇒ 00:11:14.230 Advait Nandakumar Menon: The analytics part, so…
124 00:11:14.230 ⇒ 00:11:15.190 Jasmin Multani: Yeah.
125 00:11:15.850 ⇒ 00:11:20.030 Jasmin Multani: So at my last team, it was pretty flexible.
126 00:11:20.210 ⇒ 00:11:28.460 Jasmin Multani: Before, before Brainforge. I was an analyst, but I got put onto the detection engineering team.
127 00:11:28.960 ⇒ 00:11:36.629 Jasmin Multani: And so I would be able to work alongside with the engineers and the data scientists. So I would be, like, programming the scripts.
128 00:11:36.730 ⇒ 00:11:47.100 Jasmin Multani: But then, they would be… like, I was basically, like, Detecting bad accounts that were… Suspected of selling drugs.
129 00:11:47.250 ⇒ 00:11:52.180 Jasmin Multani: So a lot of my work was like, yeah, the programming part was pretty easy.
130 00:11:52.430 ⇒ 00:11:57.570 Jasmin Multani: compared to what I did at DoorDash. The programming part was pretty easy, the robust part was, like.
131 00:11:58.130 ⇒ 00:12:01.569 Jasmin Multani: Narrowing down the behavioral aspects.
132 00:12:01.750 ⇒ 00:12:05.570 Jasmin Multani: I’m being like, hey, given the signals.
133 00:12:05.740 ⇒ 00:12:10.060 Jasmin Multani: Or these emoji signals, yes, this leads to a high true positive, so…
134 00:12:10.190 ⇒ 00:12:13.469 Jasmin Multani: My role, it was, like, that was, like, the robust part.
135 00:12:14.460 ⇒ 00:12:19.079 Jasmin Multani: But where I work… leaned on with data… data engineers.
136 00:12:19.860 ⇒ 00:12:22.930 Jasmin Multani: Or the engineers in general,
137 00:12:23.390 ⇒ 00:12:31.430 Jasmin Multani: What they would do is, like, they would take our flagged accounts, and they would route it to the, effective moderators.
138 00:12:31.590 ⇒ 00:12:39.179 Jasmin Multani: So, like… from what I understand, from what I saw, it seemed like they wore multiple hats?
139 00:12:39.340 ⇒ 00:12:44.280 Jasmin Multani: like, they were able to do the data engineering part, they were able to do the UX part.
140 00:12:44.730 ⇒ 00:12:45.409 Advait Nandakumar Menon: screens on the URL.
141 00:12:45.410 ⇒ 00:12:49.140 Jasmin Multani: So we can be like, hey, can the moderators literally
142 00:12:49.340 ⇒ 00:12:55.680 Jasmin Multani: touch and, like, click on these, like, if we send them 100 comments, suspected of… Right.
143 00:12:56.080 ⇒ 00:13:05.639 Jasmin Multani: Criminal behavior, hey, here’s my menu of drugs. Of those 100, can the moderator click and say, hey, only 5 of these were true.
144 00:13:05.950 ⇒ 00:13:08.960 Jasmin Multani: Bad violations.
145 00:13:09.250 ⇒ 00:13:19.830 Jasmin Multani: That would help create, like, a feedback loop to be like, oh, this is, of the recall, here’s how you stamp down precision, and improve the upstream detection model.
146 00:13:20.270 ⇒ 00:13:22.460 Advait Nandakumar Menon: Yeah, a little bit of software engineering as well, right?
147 00:13:22.460 ⇒ 00:13:23.220 Jasmin Multani: Yeah.
148 00:13:23.220 ⇒ 00:13:24.710 Advait Nandakumar Menon: Yeah, yeah, yeah.
149 00:13:24.710 ⇒ 00:13:38.060 Jasmin Multani: And the freedom there was that, like, they got to pick their own projects, there was no real, like, roadmap, we all got to do whatever we wanted, which could be a good thing or a bad thing. But what I’ve noticed about engineer… but, like, even with those engineers.
150 00:13:38.280 ⇒ 00:13:45.270 Jasmin Multani: Eventually, we got reorged, and they were told, like, you guys now have to be site… Site Reliability Engineers.
151 00:13:46.830 ⇒ 00:13:53.599 Jasmin Multani: And they were able to adapt to it. They weren’t happy about it, but they were able to, like, cross over their skill sets.
152 00:13:56.180 ⇒ 00:14:00.319 Jasmin Multani: just from the outside looking in, I’m like, oh, engineering’s pretty broad, but it looks
153 00:14:00.690 ⇒ 00:14:03.400 Jasmin Multani: You pick up skills as you go along.
154 00:14:04.210 ⇒ 00:14:08.249 Jasmin Multani: So, what I would suggest is…
155 00:14:10.040 ⇒ 00:14:14.970 Jasmin Multani: For your next… whatever your next ideal role is.
156 00:14:15.990 ⇒ 00:14:31.890 Jasmin Multani: figure out, like, okay, what’s… what’s… what does a… what’s the difference between analytics engineer? What’s the difference between data engineer? How much… you could probably scope out your next upcoming projects to be like, hey, on this project, I’m gonna be, like.
157 00:14:32.330 ⇒ 00:14:38.600 Jasmin Multani: I’m gonna put on my data science hat for 30%, but I want to put on my engineering hat for 70%.
158 00:14:38.940 ⇒ 00:14:49.940 Jasmin Multani: So… I would… A… Decide, how are you getting that source of truth?
159 00:14:50.170 ⇒ 00:14:59.020 Jasmin Multani: Is that through ADs? Is that through talking to OH? Do you need to set up one-on-ones with OH? On my side, like, I can also…
160 00:14:59.120 ⇒ 00:15:10.839 Jasmin Multani: tell the rest of the team that, hey, what does development… how… can you set up a peer-to-peer mentorship? Because I can… I can give you, like, the structure, but that source of truth experience of
161 00:15:11.050 ⇒ 00:15:15.370 Jasmin Multani: engineering, like, I think you’re gonna have to go towards a real engineer.
162 00:15:15.490 ⇒ 00:15:16.620 Advait Nandakumar Menon: Right.
163 00:15:17.100 ⇒ 00:15:29.739 Jasmin Multani: And what could that look like? Does that look like you leaning on internal AI engineers, dbt engineers? Does that look like you reaching out to LinkedIn, on LinkedIn, and asking people for, like, coffee chats?
164 00:15:29.880 ⇒ 00:15:34.809 Jasmin Multani: So I’d say, like, The more you do that, the better.
165 00:15:35.260 ⇒ 00:15:38.360 Jasmin Multani: I can tell, like, you’re very, like, detail-oriented.
166 00:15:38.900 ⇒ 00:15:43.229 Jasmin Multani: But eventually, you’re gonna have to become a software engineer that proposes
167 00:15:43.340 ⇒ 00:15:45.749 Jasmin Multani: That says, like, hey, given this research.
168 00:15:46.210 ⇒ 00:15:50.019 Jasmin Multani: I looked everything, I made the relationships myself.
169 00:15:50.150 ⇒ 00:15:54.950 Jasmin Multani: I reached out to this product owner myself,
170 00:15:56.300 ⇒ 00:16:04.070 Jasmin Multani: And given our conversation and what information they gave me, given my questioning, Here’s my recommendation.
171 00:16:04.300 ⇒ 00:16:04.910 Jasmin Multani: And then you.
172 00:16:04.910 ⇒ 00:16:05.440 Advait Nandakumar Menon: Feel good.
173 00:16:05.440 ⇒ 00:16:08.589 Jasmin Multani: So, there really is, like, a communication piece.
174 00:16:09.030 ⇒ 00:16:10.540 Jasmin Multani: And a trade-off piece?
175 00:16:10.760 ⇒ 00:16:17.870 Jasmin Multani: And I think that’s… Can be scripted easily, but it’s gonna be a matter of, like.
176 00:16:18.830 ⇒ 00:16:22.290 Jasmin Multani: Pressing on that muscle each time, you get an opportunity.
177 00:16:22.570 ⇒ 00:16:24.240 Jasmin Multani: Every week, I’d say.
178 00:16:24.350 ⇒ 00:16:31.259 Jasmin Multani: And just being able to brainstorm off of ideas.
179 00:16:32.340 ⇒ 00:16:36.080 Jasmin Multani: And also being able to decide for yourself, it’s like.
180 00:16:36.530 ⇒ 00:16:43.579 Jasmin Multani: what does full-stack mean? And what do you actually like doing? And what do you definitely don’t like doing?
181 00:16:44.480 ⇒ 00:16:45.500 Jasmin Multani: Yeah.
182 00:16:45.500 ⇒ 00:16:46.020 Advait Nandakumar Menon: Yep.
183 00:16:46.940 ⇒ 00:16:51.409 Jasmin Multani: Yeah. And then, on my side, I’ll also talk to, like, the other engineers.
184 00:16:52.190 ⇒ 00:16:53.630 Jasmin Multani: at the company.
185 00:16:53.950 ⇒ 00:16:58.449 Jasmin Multani: To figure out, like, what your next step would be to level up.
186 00:16:58.450 ⇒ 00:16:59.819 Advait Nandakumar Menon: Sure, sure.
187 00:16:59.820 ⇒ 00:17:05.609 Jasmin Multani: But your homework, for now, is gonna be Fill this out.
188 00:17:05.770 ⇒ 00:17:11.500 Jasmin Multani: Like, We’re checking in on May… in May, but reflect for the past 4 weeks.
189 00:17:12.020 ⇒ 00:17:12.800 Advait Nandakumar Menon: Yeah.
190 00:17:12.800 ⇒ 00:17:23.669 Jasmin Multani: So, be like, how would you rate your communication skills, analysis, stakeholder, da-da-da-da-da? What would you want to stop doing, start doing, continue doing, da-da-da-da-da?
191 00:17:23.900 ⇒ 00:17:24.219 Advait Nandakumar Menon: Thank you.
192 00:17:24.220 ⇒ 00:17:25.329 Jasmin Multani: the feedback.
193 00:17:26.770 ⇒ 00:17:28.119 Jasmin Multani: And so…
194 00:17:28.940 ⇒ 00:17:46.120 Jasmin Multani: keep it… you just keep it loose. Like, I know I didn’t give you that much structure, like, what does communication mean? What does analysis mean? Like, it’s pretty open-ended now. But, I think part of your homework is also going to be, like, give me the JDs of the companies and…
195 00:17:47.750 ⇒ 00:17:51.340 Jasmin Multani: the projects that you’re excited to work on, that you’d be like.
196 00:17:51.340 ⇒ 00:17:51.730 Advait Nandakumar Menon: Fantastic.
197 00:17:51.730 ⇒ 00:17:55.220 Jasmin Multani: Interesting. And it doesn’t have to be, like, a life mission or anything, it could just be
198 00:17:56.570 ⇒ 00:17:58.209 Jasmin Multani: Seems like they’re doing something cool.
199 00:17:58.410 ⇒ 00:18:04.140 Jasmin Multani: That way I can backtrack and be, like, and talk to, like, relevant people and be like, okay, how did…
200 00:18:04.690 ⇒ 00:18:12.360 Jasmin Multani: Given this person’s resume, like, how does he… what type of projects does he need to take on? Certifications does he need to take on in order to level up?
201 00:18:15.100 ⇒ 00:18:22.349 Jasmin Multani: Yeah, and then eventually, like, Eventually, I’m gonna encourage you to reach out to people on LinkedIn as well.
202 00:18:23.010 ⇒ 00:18:26.510 Jasmin Multani: To do coffee chats and be like, present yourself.
203 00:18:26.720 ⇒ 00:18:28.749 Jasmin Multani: Get comfortable with, like.
204 00:18:29.830 ⇒ 00:18:38.209 Jasmin Multani: being able to explain your ideas at a broad end, and don’t limit that to engineers. I’d say pitch yourself to data scientists.
205 00:18:38.560 ⇒ 00:18:47.400 Jasmin Multani: get used to, like, brainstorming big ideas, in… live, in person. I think that’s a really good skill to have.
206 00:18:47.860 ⇒ 00:18:55.580 Jasmin Multani: But being able to do it in a way that you’re not, like, grilling, where people are not grilling each other, to be like, oh, I know, I know this, do you know this?
207 00:18:55.850 ⇒ 00:18:56.620 Jasmin Multani: Rather than.
208 00:18:56.620 ⇒ 00:18:57.170 Advait Nandakumar Menon: Yeah.
209 00:18:57.470 ⇒ 00:18:59.459 Jasmin Multani: Do it in, like, a calm, curious way.
210 00:19:00.090 ⇒ 00:19:04.410 Jasmin Multani: I feel like that makes it easier for someone to want to hire you.
211 00:19:04.580 ⇒ 00:19:07.270 Jasmin Multani: It’s, like, there’s a soft skill aspect to it.
212 00:19:07.270 ⇒ 00:19:08.089 Advait Nandakumar Menon: Yeah, yeah.
213 00:19:08.550 ⇒ 00:19:14.559 Jasmin Multani: Yeah, and then, in the meantime, I’ll just, like, ask around what people do.
214 00:19:14.560 ⇒ 00:19:15.280 Advait Nandakumar Menon: True.
215 00:19:16.770 ⇒ 00:19:17.870 Advait Nandakumar Menon: That weren’t…
216 00:19:17.870 ⇒ 00:19:22.980 Jasmin Multani: That should be good. Okay, so that’s that. Let me know if you have… Access to this?
217 00:19:23.470 ⇒ 00:19:28.030 Jasmin Multani: But, feel free to dump the JDEs in here, in one of these sheets.
218 00:19:28.630 ⇒ 00:19:29.809 Jasmin Multani: I can review.
219 00:19:30.510 ⇒ 00:19:35.659 Jasmin Multani: also… I’m not doing this to encourage you to leave BringForge, I’m doing this
220 00:19:36.260 ⇒ 00:19:41.209 Jasmin Multani: We can make you a sharpened tool, and for Brainforge.
221 00:19:42.000 ⇒ 00:19:43.529 Advait Nandakumar Menon: Yep, that’s the plan.
222 00:19:44.470 ⇒ 00:19:45.399 Jasmin Multani: Cool, cool, cool.
223 00:19:46.080 ⇒ 00:19:53.099 Jasmin Multani: And then… yeah, feel free to push that meeting to Monday, and then you can have the weekend just, like.
224 00:19:53.310 ⇒ 00:19:55.660 Jasmin Multani: Go over it, go to a coffee shop, and like…
225 00:19:55.930 ⇒ 00:19:57.840 Jasmin Multani: Draft up that… that month’s month.
226 00:19:57.840 ⇒ 00:19:58.950 Advait Nandakumar Menon: Yep.
227 00:19:59.430 ⇒ 00:20:03.810 Jasmin Multani: In the meantime, I’ll, like, drop a request in our…
228 00:20:04.440 ⇒ 00:20:09.979 Jasmin Multani: with, like, with them and Robin, be like, what does development look like? Like, mentorship, peering, whatever.
229 00:20:11.440 ⇒ 00:20:13.660 Jasmin Multani: Okay, cool.
230 00:20:14.340 ⇒ 00:20:18.489 Jasmin Multani: And then… later today, I need to look into this.
231 00:20:20.080 ⇒ 00:20:20.700 Advait Nandakumar Menon: Yep.
232 00:20:21.190 ⇒ 00:20:26.539 Jasmin Multani: And I need to review the answers, and maybe, like, add any other cuts that I think she would look into.
233 00:20:26.770 ⇒ 00:20:29.640 Jasmin Multani: She’s probably gonna want to review this today, live.
234 00:20:30.470 ⇒ 00:20:35.540 Jasmin Multani: But my gut tells me we’re gonna go over the dashboards, the three dashboards in the meeting today.
235 00:20:35.540 ⇒ 00:20:38.310 Advait Nandakumar Menon: Yeah. She had a couple of questions.
236 00:20:38.310 ⇒ 00:20:39.170 Jasmin Multani: Yeah, yeah.
237 00:20:39.170 ⇒ 00:20:40.030 Advait Nandakumar Menon: Yeah…
238 00:20:40.340 ⇒ 00:20:45.180 Jasmin Multani: So we’re gonna go over those, we’re gonna go over urinalysis.
239 00:20:45.530 ⇒ 00:20:49.179 Jasmin Multani: And what decisions we’re gonna make off of that analysis.
240 00:20:49.540 ⇒ 00:20:55.299 Jasmin Multani: And then I’m gonna intro her to the Omni e-commerce stuff.
241 00:20:56.680 ⇒ 00:20:58.929 Jasmin Multani: I’m gonna clean this up a little bit more.
242 00:20:59.610 ⇒ 00:21:03.950 Jasmin Multani: But I think we can ask her to review this async.
243 00:21:05.090 ⇒ 00:21:08.720 Jasmin Multani: After… I’ll float it to her, but like…
244 00:21:08.970 ⇒ 00:21:12.799 Jasmin Multani: I’ll ask her, like, you have 48 hours, or 24 hours.
245 00:21:17.030 ⇒ 00:21:24.180 Advait Nandakumar Menon: I should have left this as a comment, or I don’t know. Now that I’m thinking about it, do you remember the time that she said she doesn’t want to look at the spec, but…
246 00:21:24.500 ⇒ 00:21:27.670 Advait Nandakumar Menon: She wants to sit together and whiteboard it out, and…
247 00:21:27.670 ⇒ 00:21:28.900 Jasmin Multani: Hmm, yeah.
248 00:21:28.900 ⇒ 00:21:35.590 Advait Nandakumar Menon: Yeah, so I’m wondering if sending this to her is the… I’ll be like…
249 00:21:35.590 ⇒ 00:21:42.800 Jasmin Multani: Yeah, I’ll be like, just read it through, and then we’ll also have… we can also do a whiteboarding session if she has any…
250 00:21:43.590 ⇒ 00:21:47.250 Jasmin Multani: Because I feel like she’s not going to be able to synthesize all of this if we just.
251 00:21:47.250 ⇒ 00:21:47.699 Advait Nandakumar Menon: Or something.
252 00:21:47.700 ⇒ 00:21:57.759 Jasmin Multani: So I want to give her to her so she can read it, marinate on it, and then be like, hey, if you want to do, like, a live whiteboarding session, let’s do it.
253 00:21:57.910 ⇒ 00:22:01.189 Jasmin Multani: But these are, like, the proposed things I shared.
254 00:22:01.710 ⇒ 00:22:04.420 Jasmin Multani: She can go from there.
255 00:22:05.460 ⇒ 00:22:15.060 Advait Nandakumar Menon: Yeah, and I think I also wanted to ask this, but your first comment, you have already asked it, like, what’s the source of truth document that’s…
256 00:22:16.310 ⇒ 00:22:18.179 Advait Nandakumar Menon: Being followed right now.
257 00:22:18.180 ⇒ 00:22:20.280 Jasmin Multani: Yeah, it’d be nice if she already had that.
258 00:22:20.810 ⇒ 00:22:26.040 Jasmin Multani: But we’ll see. I’m only seeing copies rather than actual setups.
259 00:22:30.330 ⇒ 00:22:32.060 Jasmin Multani: And so…
260 00:22:33.260 ⇒ 00:22:40.970 Jasmin Multani: As we… even though we’re waiting for this to be whiteboarded and, like, cleared off, do you feel comfortable writing the topics?
261 00:22:41.710 ⇒ 00:22:48.109 Advait Nandakumar Menon: Yeah, this is useful information, like I said. So what I’ll do is I’ll take this…
262 00:22:48.390 ⇒ 00:22:50.410 Advait Nandakumar Menon: Put it in cursor.
263 00:22:50.770 ⇒ 00:23:01.470 Advait Nandakumar Menon: I’ll take our existing snowflake model, and the dbt models, and put it in cursor, and basically, from there, I will try to ideate
264 00:23:01.990 ⇒ 00:23:05.090 Advait Nandakumar Menon: A foundation for the topic.
265 00:23:05.260 ⇒ 00:23:10.240 Advait Nandakumar Menon: And… Ideally, with the different data cuts.
266 00:23:10.490 ⇒ 00:23:22.079 Advait Nandakumar Menon: this is looking at… I think it will be more than a single topic, but it can be one single dashboard, but just the different tiles will be powered by different topics, so…
267 00:23:22.260 ⇒ 00:23:24.669 Advait Nandakumar Menon: That should not be an issue.
268 00:23:25.440 ⇒ 00:23:29.770 Advait Nandakumar Menon: Yeah, I think the only places,
269 00:23:30.740 ⇒ 00:23:39.890 Advait Nandakumar Menon: Not an issue, but the filters are up top, like, it should respond to all the different tiles and the topics, so that’s the only thing.
270 00:23:40.000 ⇒ 00:23:43.459 Advait Nandakumar Menon: I might have to look into, like, maybe having a…
271 00:23:44.130 ⇒ 00:23:49.230 Advait Nandakumar Menon: Parent filter that operates all the other ones, or…
272 00:23:49.620 ⇒ 00:23:53.930 Advait Nandakumar Menon: Using the advanced layout, I can have a filter per
273 00:23:54.140 ⇒ 00:23:58.060 Advait Nandakumar Menon: Tile, or, like, visual, or whatever, so…
274 00:23:58.380 ⇒ 00:23:59.469 Jasmin Multani: Okay, yeah. Yeah.
275 00:23:59.640 ⇒ 00:24:02.980 Jasmin Multani: We can play around with that and can ask for that in person, too.
276 00:24:03.650 ⇒ 00:24:04.340 Advait Nandakumar Menon: Yeah.
277 00:24:06.380 ⇒ 00:24:12.699 Jasmin Multani: So, there’s this, I’ll have her review it.
278 00:24:13.410 ⇒ 00:24:15.460 Jasmin Multani: And then we’ll go over, I think…
279 00:24:15.730 ⇒ 00:24:21.099 Jasmin Multani: This will be part of a live discussion, and the dashboarding stuff will be the live discussion.
280 00:24:21.870 ⇒ 00:24:22.470 Advait Nandakumar Menon: Yeah.
281 00:24:23.310 ⇒ 00:24:27.560 Jasmin Multani: And then in the… before our meeting, I wanna read through this.
282 00:24:28.450 ⇒ 00:24:33.799 Jasmin Multani: Yeah. And tell her, like, yeah, we’re gonna send this to a Wish update, da-da-da-da-da.
283 00:24:34.520 ⇒ 00:24:40.889 Advait Nandakumar Menon: Yeah, if you need anything more, or if you have any queries, let me know, I can.
284 00:24:41.460 ⇒ 00:24:44.859 Advait Nandakumar Menon: Give you… or point you to the right thing.
285 00:24:45.300 ⇒ 00:24:49.129 Jasmin Multani: Okay, sounds good. Is there anything else you want to chat about?
286 00:24:50.210 ⇒ 00:24:54.159 Advait Nandakumar Menon: No, do you need anything else from me before the meeting with her?
287 00:24:54.700 ⇒ 00:24:58.150 Jasmin Multani: Nothing before the meeting. I am gonna cut you a ticket on the topics.
288 00:24:58.390 ⇒ 00:25:04.190 Jasmin Multani: Oh, so you can get started on that, but you don’t have to do that before the meeting.
289 00:25:04.520 ⇒ 00:25:06.060 Advait Nandakumar Menon: Okay. Okay.
290 00:25:06.580 ⇒ 00:25:07.810 Jasmin Multani: Cool. Great.
291 00:25:07.810 ⇒ 00:25:08.719 Advait Nandakumar Menon: Sounds good.
292 00:25:09.290 ⇒ 00:25:10.239 Jasmin Multani: Take care, bye.
293 00:25:10.240 ⇒ 00:25:11.480 Advait Nandakumar Menon: Alright, bye-bye.