Meeting Title: Kaela - Pranav Sync on first interview Date: 2026-03-03 Meeting participants: Pranav Narahari, Kaela Gallagher
WEBVTT
1 00:02:47.340 ⇒ 00:02:50.929 Kaela Gallagher: Hey, sorry, I was totally in the wrong link.
2 00:02:51.760 ⇒ 00:02:53.680 Pranav Narahari: All good, all good.
3 00:02:53.860 ⇒ 00:02:58.469 Kaela Gallagher: Okay, first one, first one done! How are you feeling?
4 00:02:58.470 ⇒ 00:03:09.270 Pranav Narahari: It was… it was good. I, for some reason, thought it would be really strapped for time. But then I realized, like, after I got through half of it, I was like.
5 00:03:09.960 ⇒ 00:03:18.659 Pranav Narahari: I was like, how long has it been? It’s only been 9 minutes. So, I was like, okay, let me… I was just allowing her to be more, like, verbose with her answers.
6 00:03:19.010 ⇒ 00:03:26.719 Pranav Narahari: Yeah, but… I think what I kinda wanna do, too, is… with, with,
7 00:03:27.650 ⇒ 00:03:35.289 Pranav Narahari: And I… you mentioned, like, you kind of, like, sent me, like, some more questions that might be more tailored to, like, her type of,
8 00:03:35.500 ⇒ 00:03:36.660 Pranav Narahari: background?
9 00:03:36.850 ⇒ 00:03:38.820 Pranav Narahari: I’m wondering, though…
10 00:03:39.100 ⇒ 00:03:58.979 Pranav Narahari: how should I go about these interviews? Should I kind of go about them with, like, just using that, like, question guide that we have for, like, the interview itself, like, AI engineer? Or should I be more dynamic with it, with just, like, kind of understanding, like, what their background is, and just kind of, like, making a…
11 00:03:59.590 ⇒ 00:04:09.069 Pranav Narahari: more, like, opinionated judgment of, like, okay, is that going to be what we need at Brainforge right now? And I guess I don’t even need to do that part, I can just do the…
12 00:04:09.600 ⇒ 00:04:15.029 Pranav Narahari: Like, the summarization of just, like, understanding where are they, what is their kind of, like…
13 00:04:15.380 ⇒ 00:04:21.029 Pranav Narahari: like, career background? Like, where… where would they be a good, like…
14 00:04:21.200 ⇒ 00:04:24.640 Pranav Narahari: fit as? Like, what type of role?
15 00:04:25.190 ⇒ 00:04:28.330 Pranav Narahari: Yeah, I wonder what you kind of think about that.
16 00:04:29.420 ⇒ 00:04:32.179 Kaela Gallagher: Yeah, I… I would say, like.
17 00:04:33.090 ⇒ 00:04:45.869 Kaela Gallagher: the questions are there if you feel like you… you need them. The questions are there because we have, like, the rubric for each kind of round of the process, and there’s, like, different
18 00:04:45.870 ⇒ 00:04:56.389 Kaela Gallagher: Sections that you’re supposed to be, like, evaluating, so the questions are sorted into those sections to help you come up with your score, like, 1 to 5 for those.
19 00:04:56.910 ⇒ 00:04:57.510 Pranav Narahari: Gotcha.
20 00:04:57.830 ⇒ 00:05:16.920 Kaela Gallagher: I mean, you’re gonna… you’re gonna, like, find your own kind of interviewing, style, but given that you’re, like, the second round, which is supposed to be, you know, more technical if they’re an engineer, or, like, really kind of rule-focused, if they’re maybe more on, like, the functional side.
21 00:05:16.920 ⇒ 00:05:17.900 Kaela Gallagher: Yeah.
22 00:05:18.300 ⇒ 00:05:20.289 Kaela Gallagher: Like, you can totally, kind of.
23 00:05:20.460 ⇒ 00:05:29.999 Kaela Gallagher: dig in deeper. The way that I would recommend conducting interviews is when you open it up, kind of, like, setting an agenda of, like.
24 00:05:30.180 ⇒ 00:05:46.659 Kaela Gallagher: hey, it’s great to meet you, like, would love to just start off with you telling me a little bit about yourself and your background, and what brought you to Brainforge, and then we’ll dive into some more, technical questions that I have for you, specific to the role, and then we’ll save
25 00:05:46.660 ⇒ 00:05:59.330 Kaela Gallagher: A few minutes at the end for your questions. And when you kind of, like, set it up like that for the candidate, I think it makes them feel, like, instantly a little bit more relaxed of, like, oh, I know what to expect, and you’re getting, like, more of, like.
26 00:05:59.810 ⇒ 00:06:01.840 Kaela Gallagher: True responses from them.
27 00:06:02.180 ⇒ 00:06:03.270 Kaela Gallagher: Yeah.
28 00:06:03.270 ⇒ 00:06:09.640 Pranav Narahari: I kind of just dove right into it in, like, the first, like, 30 seconds. I think I was definitely afraid of just, like.
29 00:06:09.840 ⇒ 00:06:29.449 Pranav Narahari: not getting through, yeah, the time, which now I feel like is not an issue, because I was just doing the calculation in my head, I was like, okay, 15 questions here, 2 minutes each, but so you’re also saying, like, I don’t need to ask all those questions, I just need to ask questions within those specific, like, categories, so I can give an accurate… okay. Exactly, exactly.
30 00:06:29.450 ⇒ 00:06:34.659 Kaela Gallagher: Exactly. And I think, like, what’s best for, like, the candidate experience, too, is, like.
31 00:06:34.840 ⇒ 00:06:49.160 Kaela Gallagher: say they mention something like, oh, I would set up a database in this way, and you’re like, oh, we just did that with one of our clients. You can be like, oh, we actually just had a client who needed a solution like that, but the problem we ran into was this. How would you.
32 00:06:49.160 ⇒ 00:06:49.540 Pranav Narahari: addressed.
33 00:06:49.540 ⇒ 00:06:52.050 Kaela Gallagher: That problem, and, like, really kind of make it…
34 00:06:52.520 ⇒ 00:06:56.729 Kaela Gallagher: tailored to what their Brainforge experience would look like. I think.
35 00:06:56.730 ⇒ 00:06:57.100 Pranav Narahari: That’s.
36 00:06:57.130 ⇒ 00:07:03.410 Kaela Gallagher: Candidates, like, really kind of put themselves in the… in the role and get more excited about joining us, too.
37 00:07:04.000 ⇒ 00:07:10.079 Pranav Narahari: Yeah, so there was actually a moment where I did that with, like, the hallucinations question, because that’s something that we just went through, like, last week.
38 00:07:10.080 ⇒ 00:07:10.660 Kaela Gallagher: Yes.
39 00:07:10.660 ⇒ 00:07:18.289 Pranav Narahari: And so, I think that was really easy for me to, like, assess, like, okay, is this…
40 00:07:18.810 ⇒ 00:07:33.429 Pranav Narahari: is this a good solution that she’s coming up with, or maybe not the best solution? And, you know, even if it’s not the best solution, is it, like, on the right track, right? Yeah. Yeah, so I was keeping that in mind.
41 00:07:33.760 ⇒ 00:07:37.619 Kaela Gallagher: Yeah, and then I would say, too, like, so you’re part of…
42 00:07:37.680 ⇒ 00:07:53.449 Kaela Gallagher: the AI process. You’re the second… second round for the AI process. And under our AI bucket, like, there’s obviously going to be the AI engineers, which is probably most of what you’re going to see, and we have some people in first rounds right now, already moving… moving forward to you.
43 00:07:53.450 ⇒ 00:08:05.430 Kaela Gallagher: But then in this case, like, Miranda was kind of like an AI product person, so if you wanted to pull, sample questions from, like, the product
44 00:08:05.640 ⇒ 00:08:08.560 Kaela Gallagher: Category that we have.
45 00:08:08.800 ⇒ 00:08:09.650 Pranav Narahari: Yeah.
46 00:08:09.780 ⇒ 00:08:15.490 Kaela Gallagher: You can do that, if you feel like you want more of, like, the functional side, if you want to test more of that… those skills.
47 00:08:15.490 ⇒ 00:08:20.440 Pranav Narahari: Gotcha. So, in the future, should I kind of, like… do…
48 00:08:20.990 ⇒ 00:08:34.400 Pranav Narahari: more research on, like, their background to assess, okay, are they a product fit? Are they an engineering fit? And then base the questions going in to that, or should I, like, on the fly, kind of, like, in the interview, figure that out?
49 00:08:34.650 ⇒ 00:08:48.080 Kaela Gallagher: Yeah, so we have, like, a role kind of tagged for them on the Notion profile. So you’ll want to look at that before going into the interview. So hers is tagged as, like, an AI product manager, and the way that we’ve…
50 00:08:48.350 ⇒ 00:08:53.980 Kaela Gallagher: tagged that so far is based on the Loom screening, and then the initial interview with Sam.
51 00:08:54.160 ⇒ 00:08:55.410 Kaela Gallagher: Yep.
52 00:08:55.790 ⇒ 00:09:08.869 Kaela Gallagher: I would always have the candidates linked in up in front of you, just so when they’re like, oh, at my previous job, you know what it is. And then… which you can also just easily access that from their Notion, page.
53 00:09:09.120 ⇒ 00:09:27.740 Kaela Gallagher: And then the other thing that I would be sure to look at, like, ahead of the call, is, like, Sam’s overall score, so he gave her, like, mostly 4s and a 3, and then his note was, could be a good fit for product manager, I think we need to align the second interview, it won’t… because it won’t be technical, I assume.
54 00:09:28.050 ⇒ 00:09:29.569 Kaela Gallagher: So, that would probably.
55 00:09:29.570 ⇒ 00:09:29.920 Pranav Narahari: annoying.
56 00:09:29.920 ⇒ 00:09:31.999 Kaela Gallagher: be helpful to, like, look at ahead of time, too.
57 00:09:32.360 ⇒ 00:09:36.959 Pranav Narahari: Right, yeah, I read that, like, right before, and I was like, oh, this is supposed to be a technical interview.
58 00:09:37.190 ⇒ 00:09:39.289 Kaela Gallagher: Oh, oh, oh.
59 00:09:39.290 ⇒ 00:09:45.400 Pranav Narahari: So I was like, this… that’s… I was gonna actually talk to Sam about that, like, right after.
60 00:09:46.660 ⇒ 00:09:55.590 Pranav Narahari: But, yeah, okay. Yeah, I definitely would have operated a little bit differently thinking about that. I think I still have, like, enough context to go off of, though.
61 00:09:55.980 ⇒ 00:10:01.910 Kaela Gallagher: I think she handled the technical questions, like, fairly well, considering she’s not hands-on engineering.
62 00:10:02.360 ⇒ 00:10:08.579 Pranav Narahari: Yeah, yeah. I think there was, like, a few things there where I was just a little bit like…
63 00:10:10.090 ⇒ 00:10:20.580 Pranav Narahari: I think in front of a client, she, like, seemed very comfortable, and to your point, like, you know, this is, like, not a super low-stress environment, right? Like, being in an interview, like, I’ve been there, like, it’s not going to…
64 00:10:20.580 ⇒ 00:10:31.560 Pranav Narahari: it’s not super easy to just, like, kind of communicate, get your thoughts across, but I thought she did a good job, like, not stuttering or, like, kind of being, like, completely, like, lost in her thoughts. Yeah.
65 00:10:32.000 ⇒ 00:10:33.500 Pranav Narahari: Yeah, so the…
66 00:10:33.620 ⇒ 00:10:45.770 Pranav Narahari: if I was to go off of her being an AI engineer, I would say, like, I think the gap is, like, not… is, like, too large in terms of, like, being able to, like, you know, hop in, like.
67 00:10:45.830 ⇒ 00:11:02.830 Pranav Narahari: kind of code a little bit. For product manager, now I’m just gonna rewatch the interview, and then just kind of assess, like, what my questions were, how well she answered it, and then look through the lens of being, like, a product, like, for an AI product manager.
68 00:11:03.070 ⇒ 00:11:09.289 Pranav Narahari: But yeah, I think… I haven’t fully figured out, like, what I’ll score yet, but…
69 00:11:09.470 ⇒ 00:11:11.419 Pranav Narahari: I think rewatching will help me a lot.
70 00:11:11.640 ⇒ 00:11:19.650 Kaela Gallagher: Okay, okay, yeah, perfect. That sounds like a good plan. One more thing to call out here, so I would say.
71 00:11:19.670 ⇒ 00:11:34.679 Kaela Gallagher: Prior to the interview, most important things to have is title, LinkedIn pulled up, and then the comments here. So, this was somebody that was referred to us by Robert, so she did the same college program that Robert, Amber, and I did.
72 00:11:34.850 ⇒ 00:11:35.880 Kaela Gallagher: Okay.
73 00:11:35.950 ⇒ 00:11:44.219 Pranav Narahari: And when I talked to Robert about her, he said what he had in mind for her was a half GTM and half AI product role.
74 00:11:44.280 ⇒ 00:11:50.499 Kaela Gallagher: So I left that comment here just for some context as well. Obviously, if we go through the interviews and we’re like.
75 00:11:50.900 ⇒ 00:11:59.050 Kaela Gallagher: oh, no, that’s totally wrong. We want her for this other role as well. You can leave that feedback, but I just left that comment there.
76 00:11:59.580 ⇒ 00:12:01.470 Kaela Gallagher: After my conversation with Robert.
77 00:12:01.800 ⇒ 00:12:02.560 Pranav Narahari: Okay.
78 00:12:02.560 ⇒ 00:12:03.400 Kaela Gallagher: Perfect.
79 00:12:03.400 ⇒ 00:12:12.779 Pranav Narahari: And so how does it work, like, for me? So I know, like, it’s, like, 19 out of 25 is, like, a pass, but it’s also, like, I thought we talked about before, like.
80 00:12:13.060 ⇒ 00:12:25.220 Pranav Narahari: we have multiple interviews, and then, like, after the final interview, like, there’s a discussion to see, like, do we want to accept them or not? Does that only happen if they pass, like, the threshold of 19?
81 00:12:26.340 ⇒ 00:12:28.030 Kaela Gallagher: Yes, so…
82 00:12:28.920 ⇒ 00:12:36.710 Kaela Gallagher: In order for us to hire somebody at the end of the final round, they need to have passed all three rounds.
83 00:12:37.570 ⇒ 00:12:39.309 Pranav Narahari: Mmm, I see.
84 00:12:39.310 ⇒ 00:12:54.340 Kaela Gallagher: So if… if you decide, like, Miranda didn’t pass this round, then we would just stop the interview process right there. We don’t want to, like, we want to be dequeuing people as early in the process as possible, just to save all of our time.
85 00:12:55.600 ⇒ 00:12:57.250 Pranav Narahari: Yeah, that makes sense.
86 00:12:57.520 ⇒ 00:12:58.560 Pranav Narahari: Okay, got it.
87 00:12:58.560 ⇒ 00:13:11.499 Kaela Gallagher: So, I know previously, like, the scorecards were weighted, and then there was this, like, total score thing, but we’re just doing… there’s a few categories, rank them 1 through 5, pass or fail.
88 00:13:11.720 ⇒ 00:13:12.930 Kaela Gallagher: And that’s that.
89 00:13:13.520 ⇒ 00:13:14.960 Pranav Narahari: Yep. Okay.
90 00:13:15.210 ⇒ 00:13:20.080 Pranav Narahari: Sounds good. And then for, the final round.
91 00:13:21.080 ⇒ 00:13:24.109 Pranav Narahari: See, I think if Utam did the final round, it would…
92 00:13:24.210 ⇒ 00:13:29.550 Pranav Narahari: be… and I mean, he could obviously, like, wear the hat of Rob or wear the hat of whoever,
93 00:13:29.800 ⇒ 00:13:36.700 Pranav Narahari: But I think it would be more technical. Is Robert gonna give the final round for this person? For Miranda?
94 00:13:36.700 ⇒ 00:13:37.910 Kaela Gallagher: So…
95 00:13:38.700 ⇒ 00:13:58.560 Kaela Gallagher: this one we’ll have to game plan with Utam and Robert if we move her forward, because of this, like, AI product kind of position. I would assume that she would do kind of, like, our strategy challenge for the final round, not, like, a AI engineered coding exam. Okay.
96 00:13:58.830 ⇒ 00:14:05.080 Kaela Gallagher: So, in that case, maybe it would be Robert in the strategy panel that’s doing her final.
97 00:14:06.170 ⇒ 00:14:14.769 Kaela Gallagher: Especially if she’s also going to, like, potentially do some go-to-market stuff, then we would need Robert in the final.
98 00:14:15.470 ⇒ 00:14:19.350 Pranav Narahari: Gotcha. Is there a notion where I can see just, like.
99 00:14:19.490 ⇒ 00:14:23.210 Pranav Narahari: all these different… and I did see somewhere where there’s, like.
100 00:14:24.440 ⇒ 00:14:35.000 Pranav Narahari: there’s, like, 6 or 7 different, like, funnels for, like, different types of roles. Is there a way where I can see, like, okay, who’s the person interviewing for, like.
101 00:14:35.400 ⇒ 00:14:41.919 Pranav Narahari: for the different type of roles, just so I can see, like… because I’m wondering, too, like, was I the right person to interview
102 00:14:44.230 ⇒ 00:14:48.480 Kaela Gallagher: Yeah, so that… this was all set up before I… I got here, so…
103 00:14:48.600 ⇒ 00:14:49.839 Pranav Narahari: Yeah, no, all good.
104 00:14:49.840 ⇒ 00:14:51.360 Kaela Gallagher: But.
105 00:14:51.360 ⇒ 00:15:00.029 Pranav Narahari: I’m also just, like, super interested in this, like, I feel like this is, like, super, like, critical part of, like, the company, and it’s, like, also a fun part. I was, like, really excited for this interview.
106 00:15:00.030 ⇒ 00:15:00.430 Kaela Gallagher: Yeah.
107 00:15:00.430 ⇒ 00:15:03.609 Pranav Narahari: Like, I love to just, like, be more helpful in any way, so…
108 00:15:04.060 ⇒ 00:15:23.469 Kaela Gallagher: Yay, thank you. Okay, yeah, so where you can find that, we used to have it, like, deep within some document, but I took it and I put it at the bottom of our hiring and recruitment page. So you can see here, first, second, and finals for each category.
109 00:15:23.660 ⇒ 00:15:26.130 Pranav Narahari: Okay, yes, I remember seeing this, but…
110 00:15:26.670 ⇒ 00:15:30.279 Pranav Narahari: Aren’t there more roles now, too? Like, that we were…
111 00:15:30.430 ⇒ 00:15:36.170 Pranav Narahari: Let me see… and I’m honestly just so bad with Notion, like, just getting around places, so…
112 00:15:36.690 ⇒ 00:15:44.230 Pranav Narahari: I think you saw me in the beginning of that meeting, too, just, like, pulling up the questions, like, it took me a sec, but…
113 00:15:44.660 ⇒ 00:15:54.060 Kaela Gallagher: No worries. So, these are the rules that we have posted right now. So, we have mostly engineering positions… oh, wait, actually…
114 00:15:54.320 ⇒ 00:16:09.690 Kaela Gallagher: let me refresh this, I think we’ve adjusted it. We have the AI engineer, the data engineer, and the analytics engineer, and then we just have, like, a senior kind of strategy associate data role open as well.
115 00:16:09.990 ⇒ 00:16:11.700 Kaela Gallagher: So each…
116 00:16:11.700 ⇒ 00:16:13.160 Pranav Narahari: She was applying for that.
117 00:16:14.740 ⇒ 00:16:22.370 Kaela Gallagher: I think the AI product role was kind of created for her, because she came through Robber, and it was, like.
118 00:16:22.370 ⇒ 00:16:22.800 Pranav Narahari: Hmm.
119 00:16:22.800 ⇒ 00:16:26.750 Kaela Gallagher: Oh, let’s just chat with you and, like, see where you could fit, kind of situation.
120 00:16:28.220 ⇒ 00:16:37.639 Kaela Gallagher: So these are, like, the roles we’re actively hiring for right now, and each of these roles is gonna fall into one of these categories. Data, AI, or strategy.
121 00:16:39.210 ⇒ 00:16:49.350 Kaela Gallagher: like, the senior associate would interview with the strategy team, AI, obviously with the AI team, and then data and analytics engineers would be under the data team.
122 00:16:50.550 ⇒ 00:16:52.100 Pranav Narahari: Gotcha. Okay.
123 00:16:52.290 ⇒ 00:16:53.390 Pranav Narahari: That makes sense.
124 00:16:53.690 ⇒ 00:16:59.380 Kaela Gallagher: Yeah. So, if you ever need to reference this, yeah, it’s on the hiring and recruitment page.
125 00:17:00.060 ⇒ 00:17:02.389 Pranav Narahari: Hiring and recruitment page, okay, perfect.
126 00:17:07.910 ⇒ 00:17:10.140 Kaela Gallagher: And you can also get, like, a snapshot of…
127 00:17:10.560 ⇒ 00:17:18.789 Kaela Gallagher: Where everybody is at, and you can see yourself tagged, like, on a couple upcoming interviews, one on the 3rd and one on the 5th.
128 00:17:19.020 ⇒ 00:17:22.280 Pranav Narahari: Oh, well, this is the one that you just had, but yeah, the one on the 5th.
129 00:17:23.060 ⇒ 00:17:25.059 Pranav Narahari: One on the 5th, okay, cool. Thursday.
130 00:17:25.389 ⇒ 00:17:26.189 Kaela Gallagher: Yeah.
131 00:17:26.889 ⇒ 00:17:32.059 Kaela Gallagher: Sam just… just interviewed that person, like, an hour ago, and we already got her scheduled.
132 00:17:32.660 ⇒ 00:17:34.189 Pranav Narahari: Oh, nice, that’s awesome.
133 00:17:34.460 ⇒ 00:17:35.040 Kaela Gallagher: Yeah.
134 00:17:35.140 ⇒ 00:17:36.290 Pranav Narahari: Okay, cool.
135 00:17:36.340 ⇒ 00:17:49.489 Kaela Gallagher: Yeah, let me know if you, like, have any other questions, and I’ll try to check in, like, ahead of your next couple interviews as you’re getting the hang of things, just make sure you have, like, all the information that you need ahead of time.
136 00:17:49.840 ⇒ 00:17:55.060 Pranav Narahari: Yeah, no, this is super helpful. I feel like I should be all set for the next one.
137 00:17:55.060 ⇒ 00:17:55.620 Kaela Gallagher: Okay.
138 00:17:55.620 ⇒ 00:18:06.179 Pranav Narahari: Yeah, but yeah, I’m definitely happy to, like, sync whenever, and, like, yeah, we can, like, maybe hop in, like, a quick, like, 10-minute call right before my next one, just to make sure, like, okay, I got everything I need, but
139 00:18:07.020 ⇒ 00:18:08.730 Pranav Narahari: Yeah, this is super helpful, thank you.
140 00:18:08.730 ⇒ 00:18:27.340 Kaela Gallagher: Yeah, of course. And your next one on Thursday should be a little bit more straightforward, because it’s an AI and automation engineer, and so it’ll just be pretty technical. Sam’s notes were pretty positive, and he just said, like, would be very curious to see if her technical skills match, but it seems like she has good experience, so… yeah.
141 00:18:27.340 ⇒ 00:18:28.940 Pranav Narahari: Cool. Awesome.
142 00:18:28.940 ⇒ 00:18:31.219 Kaela Gallagher: Awesome! Thanks for your help with this!
143 00:18:31.480 ⇒ 00:18:33.060 Kaela Gallagher: Yeah, thank you. Alrighty.
144 00:18:33.260 ⇒ 00:18:34.760 Kaela Gallagher: Talk to you later.
145 00:18:35.020 ⇒ 00:18:35.690 Pranav Narahari: See ya.
146 00:18:35.690 ⇒ 00:18:36.469 Kaela Gallagher: Alrighty, bye.