Meeting Title: Recruiting Team Retro Date: 2026-03-10 Meeting participants: Kaela Gallagher, Rico Rejoso, Samuel Roberts, Demilade Agboola, Awaish Kumar, Amber Lin, Greg Stoutenburg, Uttam Kumaran, Pranav, Zoran Selinger
WEBVTT
1 00:00:28.510 ⇒ 00:00:31.320 Kaela Gallagher: Hello again, Rico. Hey, Sam.
2 00:00:31.320 ⇒ 00:00:32.250 Samuel Roberts: Ayy.
3 00:00:33.570 ⇒ 00:00:34.790 Samuel Roberts: There we go.
4 00:00:35.130 ⇒ 00:00:36.570 Kaela Gallagher: How’s it going? How are you doing today?
5 00:00:37.640 ⇒ 00:00:38.770 Kaela Gallagher: Good.
6 00:00:39.460 ⇒ 00:00:40.630 Kaela Gallagher: How about you?
7 00:00:41.760 ⇒ 00:00:47.909 Samuel Roberts: Yeah, doing alright. Doing alright. Fixed some GitHub stuff that wasn’t working right, so that’s nice.
8 00:00:48.320 ⇒ 00:00:49.700 Kaela Gallagher: Nice. How’s.
9 00:00:50.820 ⇒ 00:00:56.679 Samuel Roberts: It’s… it’s alright. It’s not bad. I have a bunch of stuff I gotta… my sister’s getting married next weekend.
10 00:00:56.680 ⇒ 00:00:57.500 Kaela Gallagher: Oh my god.
11 00:00:57.500 ⇒ 00:00:58.540 Samuel Roberts: negotiating.
12 00:00:58.540 ⇒ 00:00:59.470 Kaela Gallagher: Oh my god.
13 00:00:59.670 ⇒ 00:01:17.350 Samuel Roberts: I need to send forms in to New York City, and I thought I was just gonna mail it, but it needs to be notarized, and have a money order, and like, I was gonna run errands earlier, but then I needed some information from her, she’s not gonna get it till later, so now I’m like, all my errands are after work, which is good, but…
14 00:01:17.570 ⇒ 00:01:18.070 Kaela Gallagher: Oh my god.
15 00:01:18.070 ⇒ 00:01:19.399 Samuel Roberts: I dragged the kid around, too, so…
16 00:01:19.400 ⇒ 00:01:23.090 Kaela Gallagher: So does that mean you’re traveling to New York this weekend, too?
17 00:01:23.090 ⇒ 00:01:24.189 Samuel Roberts: Next weekend, yeah.
18 00:01:24.190 ⇒ 00:01:28.090 Kaela Gallagher: Next weekend, okay. Oh my gosh. Wow, that’s crazy! Yeah.
19 00:01:28.090 ⇒ 00:01:32.299 Samuel Roberts: We had, like, I think, like, 5 weddings in the first half of this year.
20 00:01:33.050 ⇒ 00:01:35.479 Samuel Roberts: And we’ve been to one so far, so…
21 00:01:35.930 ⇒ 00:01:42.809 Kaela Gallagher: Oh my gosh. Tis the season. I know, I have a couple that are, like, back-to-back weekends in June. I’m like, oh my gosh.
22 00:01:42.810 ⇒ 00:01:43.889 Samuel Roberts: Oh, yeah.
23 00:01:45.720 ⇒ 00:01:47.010 Kaela Gallagher: Fun times, though.
24 00:01:47.010 ⇒ 00:01:47.700 Samuel Roberts: Yeah.
25 00:01:48.440 ⇒ 00:01:50.130 Samuel Roberts: Yeah.
26 00:01:50.410 ⇒ 00:01:54.169 Samuel Roberts: I thought I was past the wedding season stuff, but not quite.
27 00:01:54.310 ⇒ 00:01:59.819 Kaela Gallagher: Yeah, it’s really, honestly, it’s starting for me, like… No. 6 months.
28 00:01:59.820 ⇒ 00:02:00.430 Samuel Roberts: You know?
29 00:02:00.430 ⇒ 00:02:00.810 Kaela Gallagher: Yeah.
30 00:02:00.810 ⇒ 00:02:02.100 Samuel Roberts: Yeah, yeah.
31 00:02:02.620 ⇒ 00:02:04.889 Kaela Gallagher: So, 10 more years of this.
32 00:02:05.170 ⇒ 00:02:06.310 Samuel Roberts: Yep.
33 00:02:08.639 ⇒ 00:02:09.470 Kaela Gallagher: Hmm.
34 00:02:12.230 ⇒ 00:02:20.190 Kaela Gallagher: And now people have, like, 4 events, so it’s not just the wedding that you travel for. There’s the engagement party and the bridal.
35 00:02:20.190 ⇒ 00:02:20.550 Samuel Roberts: Oh.
36 00:02:20.550 ⇒ 00:02:23.279 Kaela Gallagher: and The Bachelorette, and the wedding.
37 00:02:23.280 ⇒ 00:02:35.590 Samuel Roberts: Yeah, there were two Bachelor-bachelorette things happening as well. Fortunately, one of those, we were able to combine with a trip to visit my parents in Florida, so that saved one event out of the, like, seven or eight we’d have to travel to.
38 00:02:35.860 ⇒ 00:02:38.100 Samuel Roberts: But my sister is also…
39 00:02:38.330 ⇒ 00:02:50.459 Samuel Roberts: because she’s… she and her fiance are in New York City, and they realized pricing a wedding in New York City is, a lot, they’re doing, like, a smaller ceremony in New York, which is what’s happening next weekend.
40 00:02:50.690 ⇒ 00:02:56.940 Samuel Roberts: Okay. And then an event where I’m from in Boston, and where Fiance’s from in… Kentucky.
41 00:02:57.740 ⇒ 00:02:58.300 Samuel Roberts: And so…
42 00:02:58.300 ⇒ 00:02:59.099 Kaela Gallagher: Oh my gosh.
43 00:02:59.100 ⇒ 00:03:06.680 Samuel Roberts: That’s not till May, but I’m still kind of counting that as an event we have to travel to, so… I mean, that’s like 3 wedding events right there. Yeah, yeah.
44 00:03:07.120 ⇒ 00:03:07.440 Kaela Gallagher: Wow.
45 00:03:07.440 ⇒ 00:03:08.760 Samuel Roberts: Yeah.
46 00:03:10.120 ⇒ 00:03:10.740 Samuel Roberts: Crews.
47 00:03:13.590 ⇒ 00:03:16.930 Kaela Gallagher: Good morning, Amber, Awash, Dami.
48 00:03:18.730 ⇒ 00:03:19.280 Kaela Gallagher: Aye.
49 00:03:20.540 ⇒ 00:03:22.560 Kaela Gallagher: Okay.
50 00:03:24.820 ⇒ 00:03:29.170 Kaela Gallagher: I think we’re waiting on Utom, who’s having internet issues.
51 00:03:29.170 ⇒ 00:03:29.970 Samuel Roberts: Oh, no.
52 00:03:30.480 ⇒ 00:03:34.550 Kaela Gallagher: I’m trying to think if we’re missing anybody else. Pranav?
53 00:03:38.040 ⇒ 00:03:40.900 Kaela Gallagher: And Greg. Oh, there’s Greg. Morning, Greg.
54 00:03:41.310 ⇒ 00:03:46.859 Greg Stoutenburg: This will be my only time to eat anything today, so I’m gonna just go dark, but I will be active.
55 00:03:48.120 ⇒ 00:03:53.279 Kaela Gallagher: Okay, I hope you enjoy whatever you’re eating. Is there something good on the menu?
56 00:03:58.290 ⇒ 00:04:00.520 Samuel Roberts: His mouth is already full, it must be very good.
57 00:04:00.650 ⇒ 00:04:03.570 Kaela Gallagher: That’s totally fine.
58 00:04:04.160 ⇒ 00:04:06.710 Kaela Gallagher: Well, I guess we can just…
59 00:04:06.710 ⇒ 00:04:31.519 Kaela Gallagher: start, and, like, Utam and, Pranav can join whenever they’re available, but wanted to just call a quick meeting together, because we’re very close to making some final decisions. We’ve obviously had a lot of interviews going on, the past couple weeks, so I wanted to just start off with, like, a couple updates on my end, and then really, like, open it up to you guys. Any feedback, any questions, like.
60 00:04:31.580 ⇒ 00:04:42.690 Kaela Gallagher: super happy to… to listen and adjust and, just appreciate your guys’, like, partnership through this whole process as we’re… as we’re growing. So,
61 00:04:42.890 ⇒ 00:04:48.200 Kaela Gallagher: I guess just, like, a couple things to start off with. Let me just share my…
62 00:04:48.530 ⇒ 00:04:54.000 Kaela Gallagher: screen quickly, because I feel like it’s helpful to have the visual of the Notion board.
63 00:04:54.910 ⇒ 00:04:57.410 Kaela Gallagher: Okay.
64 00:04:57.530 ⇒ 00:05:20.129 Kaela Gallagher: Cool. So a couple things to just review. I know you guys have been using it, and I’ve been, attaching it in the Slack message, but the interview scorecard is here. You’ll be able to find questions and rubrics for each of the positions, so if you’re, you know, doing stage one of the AI engineer, Sam, this is where you’re going. So everything should be here.
65 00:05:20.320 ⇒ 00:05:35.349 Kaela Gallagher: If you have any questions regarding that, let me know. But we’re not doing a weighted system anymore. Everything should just be pretty straightforward. Obviously, you’re grading in certain categories, but then it’s pass or fail at the end.
66 00:05:36.910 ⇒ 00:05:51.230 Kaela Gallagher: If, for example, you’re doing first round, Marcus Kahle passes your interview, I would just ask that you drag him over to the next move forward column. It makes it a little bit easier for me to…
67 00:05:51.230 ⇒ 00:06:00.280 Kaela Gallagher: get candidates moving quickly. So if you guys have somebody that passes, if you can just drag them over to that next column, that would be helpful.
68 00:06:00.280 ⇒ 00:06:12.500 Amber Lin: Oh, I also wanted to say, if you want… you can also change the state when you’re in someone’s notes. So, for people that’s not using this pipeline view, you can always click…
69 00:06:12.630 ⇒ 00:06:18.930 Amber Lin: First round move forward, second round move forward. I think that will be easier to remember to do.
70 00:06:19.030 ⇒ 00:06:23.330 Kaela Gallagher: Yes, exactly, so you can just change their status up top here.
71 00:06:23.700 ⇒ 00:06:30.180 Kaela Gallagher: Thank you for pointing that out, Amber. I live on this page, but not everybody does, so… Yeah, I haven’t seen that.
72 00:06:30.180 ⇒ 00:06:31.930 Samuel Roberts: page yet, I was just on the other ones.
73 00:06:31.930 ⇒ 00:06:46.470 Kaela Gallagher: Okay, okay, perfect. Yeah, I think this is, like, very helpful to kind of just get an overview of where we have people in… in the pipeline, and then there’s a calendar view here that’s nice as well, so, gives us a good overview.
74 00:06:46.720 ⇒ 00:06:50.450 Awaish Kumar: So, we are managing this in motion.
75 00:06:52.990 ⇒ 00:06:55.010 Kaela Gallagher: Sorry, I wish you were cutting out a little bit there.
76 00:06:55.010 ⇒ 00:06:57.140 Awaish Kumar: Like, I saw the similar recruiting…
77 00:06:58.590 ⇒ 00:07:08.919 Awaish Kumar: Yeah, I was born in linear as well, so just, like, confirming which is the one we should be looking at if we want to see anything.
78 00:07:09.740 ⇒ 00:07:27.450 Kaela Gallagher: Notion is our hub for everything recruiting right now, so this lives in the hiring and recruiting section of Notion, and if you scroll down, you can see our entire pipeline, click on candidates, profiles, so, another way that you can access besides my Slack messages.
79 00:07:28.860 ⇒ 00:07:30.370 Awaish Kumar: Okay, okay.
80 00:07:30.620 ⇒ 00:07:43.120 Kaela Gallagher: Okay, okay, perfect. Also, just helpful, like, if you do want to move somebody forward, if you have any feedback, questions, like, feel free to ping me on Slack at any point. It’ll help me just move things along quicker.
81 00:07:43.120 ⇒ 00:07:51.050 Kaela Gallagher: One thing I do want to call out, too, is, like, shout out to Utam, but he’s been going through the Loom videos pretty, like, thoroughly.
82 00:07:51.440 ⇒ 00:08:06.129 Kaela Gallagher: So, like, when you click into a candidate profile, let’s say you’re conducting the first round, I think it’s helpful to just drop down this little loom section here, and you can look at Utam’s notes, and sometimes he’s leaving comments like.
83 00:08:06.330 ⇒ 00:08:11.540 Kaela Gallagher: You know, would want to confirm his communication.
84 00:08:11.540 ⇒ 00:08:28.510 Kaela Gallagher: So it gives us an idea of, like, if you’re conducting the first round, this is something that we need to dig into deeper. Utam can’t ask questions to people live, but he might have some thoughts of, like, things that we need to look into a little bit more. So I would say, just helpful to give a glance at the loom notes.
85 00:08:28.510 ⇒ 00:08:38.889 Kaela Gallagher: And then if you’re doing, you know, a second or a final round, you can look at the notes from previous calls as well. So Greg’s talking to Garrett today, he can, you know, look at what Amber had to say.
86 00:08:38.960 ⇒ 00:08:40.070 Kaela Gallagher: Here.
87 00:08:40.559 ⇒ 00:08:55.149 Uttam Kumaran: Yeah, so if anyone has any feedback, I mean, basically, I sort of am, like, the first gatekeeper on if people are gonna move on to actually, like, spend time with our team. So I look for, like, are they generally taking the loom seriously?
88 00:08:55.289 ⇒ 00:08:58.859 Uttam Kumaran: Is it, like, 100% AI, or is it… are they actually, like…
89 00:08:58.899 ⇒ 00:09:06.919 Uttam Kumaran: do they show curiosity and interest in the stories that they’re telling? And then I’m basically judging about, like, their communication skills
90 00:09:06.939 ⇒ 00:09:17.759 Uttam Kumaran: And then ultimately, look, most of the people either skew so tech… super technical, or they skew non-technical at all. So then I usually am like, okay, great, the loom was really technical.
91 00:09:17.759 ⇒ 00:09:32.709 Uttam Kumaran: someone needs to understand… the next question should be, like, tell me about your team, tell me about working directly with stakeholders, versus if it’s super business-y, then I’m like, okay, you should ask, like, if this person actually knows some of the technical aspects. So some of those, I just jot down those notes.
92 00:09:32.709 ⇒ 00:09:49.029 Uttam Kumaran: And then, for the most part, I’m trying to push candidates through that I feel like have a chance at making it to the end. Like, I’m… I’m not… there are some people that are on the line, and I’d rather say no, because I don’t want to waste, you know, we’re gonna spend 5 or 10 hours for each candidate, so…
93 00:09:49.109 ⇒ 00:09:53.379 Uttam Kumaran: I’m trying to push people through that I feel like could have a chance to make it to the end, for the most part.
94 00:09:54.100 ⇒ 00:09:54.990 Kaela Gallagher: Perfect.
95 00:09:55.050 ⇒ 00:10:01.010 Kaela Gallagher: One other thing that I want to call out is if you’re ever doing an interview, and you feel like.
96 00:10:01.010 ⇒ 00:10:24.689 Kaela Gallagher: I’m not the right person that should be interviewing this candidate. Utam and I are doing our best in the beginning to funnel people into, you know, the correct position we think they would be a fit for, and, you know, the correct track, whether that’s data or AI or strategy. But if you’re like, oh my gosh, this person needs to be talking to a strategy person instead, like, please flag that, please let me know, and we can adjust.
97 00:10:24.790 ⇒ 00:10:33.209 Kaela Gallagher: you know, where this person goes in the interview track. I know we’ve ran into a couple of those situations recently, but please just continue to call that out to me.
98 00:10:35.140 ⇒ 00:10:55.840 Kaela Gallagher: One other thing I want to highlight for first rounds that I think is important for us to ask, because we’re not understanding this in Loom videos, is, like, why… why is this person on the market? I always like to open up my interviews with this, like, oh, what’s putting you on the market? Like, why are you looking for a new role? Like, understand their motivation, and understand if, like.
99 00:10:55.840 ⇒ 00:11:00.010 Kaela Gallagher: They could seriously accept an offer from us in 2 weeks.
100 00:11:00.010 ⇒ 00:11:05.420 Kaela Gallagher: We’re looking to move quickly, and we only want to move people forward. That can kind of work with our
101 00:11:05.420 ⇒ 00:11:15.000 Kaela Gallagher: timeline on that. So, if you’re doing a first round, I would just ask that you… you add that question, and I can add it to the question rubrics as well.
102 00:11:15.200 ⇒ 00:11:17.830 Kaela Gallagher: Cool.
103 00:11:18.360 ⇒ 00:11:33.080 Kaela Gallagher: Just for some hiring updates right now, just for visibility, and I can do a better job about, like, sending this out in Slack as well, our current openings is a data engineer, an analytics engineer, an AI engineer.
104 00:11:33.080 ⇒ 00:11:47.230 Kaela Gallagher: And somebody that’s, like, very kind of senior on the strategy side. So those are, like, our hottest needs right now, so just wanted to call those out for visibility to everybody, in terms of, like, what we’re looking for.
105 00:11:47.580 ⇒ 00:11:53.530 Kaela Gallagher: Utam, anything to add to, like, Those roles or our requirements.
106 00:11:56.570 ⇒ 00:11:58.950 Uttam Kumaran: Nothing on my end, no. That’s perfect.
107 00:11:59.250 ⇒ 00:11:59.910 Kaela Gallagher: Okay.
108 00:12:00.240 ⇒ 00:12:12.280 Kaela Gallagher: Okay, and then Utam, I know you also wanted to talk about potentially, like, fast-tracking people and, you know, that our needs could be very soon for some of these candidates?
109 00:12:13.730 ⇒ 00:12:21.380 Uttam Kumaran: Yeah, I think the main thing for me is that, like, if we spot a candidate at any point in the pipeline that you’re like, oh my god, this person’s awesome, like.
110 00:12:21.530 ⇒ 00:12:25.300 Uttam Kumaran: I want to find those people, and I want to move them quickly through the process.
111 00:12:25.500 ⇒ 00:12:34.589 Uttam Kumaran: So there’s even some people that I had reviewed their looms, and I flagged to Kayla, like, hey, these people, I have a strong feeling they’re gonna make it.
112 00:12:34.730 ⇒ 00:12:50.200 Uttam Kumaran: So, let’s just try to advance them forward. So if you feel like… like that, it’s like, I almost want to think about it, like, I don’t know, Kayla, if other places do this, but, like, maybe there’s some way for people to just have, like, okay, this person needs, like, a golden ticket, basically, like, they’re good.
113 00:12:50.330 ⇒ 00:12:57.759 Uttam Kumaran: I feel like we all have that feeling sometimes about people, and as you interview, if you’re new to interviewing, you’ll get this sense as you go.
114 00:12:58.340 ⇒ 00:13:08.839 Uttam Kumaran: That if you spot someone that you’re like, oh my god, we need them, you should just flag that. Like, we don’t need to wait for the whole process, like, we can move them to the end.
115 00:13:09.190 ⇒ 00:13:26.229 Uttam Kumaran: And so I think that’s just something that I want to flag to everyone as you’re interviewing people. If someone you’re interviewing with is like, hell yes, I would love to work with this person, we really want to hear about it, so that we can move them quickly through the process. Otherwise, we’re going to try our best to wait to get a mix of people to make a decision on,
116 00:13:27.000 ⇒ 00:13:33.820 Uttam Kumaran: Another way, also, is if you’re… if you’re on a team and you feel like… if you feel like you met somebody that,
117 00:13:34.310 ⇒ 00:13:42.340 Uttam Kumaran: you know, you really appreciate and you want to work with, you can also say, like, this person’s good, like, let’s move them forward. So, I just want to say there’s, like, a lot of latitude, like.
118 00:13:42.470 ⇒ 00:13:45.749 Uttam Kumaran: To make these decisions, you know?
119 00:13:46.140 ⇒ 00:14:00.810 Kaela Gallagher: Yeah. We actually have a, like, a feature, too, that I can add to profiles, that assigns them, like, a priority. So if we have… I call them, like, hot candidates, but, like, very high potential, exciting candidates.
120 00:14:00.810 ⇒ 00:14:17.349 Kaela Gallagher: I can… I can assign them, like, a high priority. So the ones that Utom called out the other day that had just, like, amazing Loom videos, I labeled them as high priority in the system, and, we can do our best to, like, adjust our schedules and really try to get them through the process quickly.
121 00:14:20.430 ⇒ 00:14:21.200 Uttam Kumaran: Sorry.
122 00:14:23.810 ⇒ 00:14:26.630 Kaela Gallagher: Oh, Utam, you might be cutting out again, sorry.
123 00:14:26.630 ⇒ 00:14:28.499 Uttam Kumaran: Sorry, sorry, no, nothing else on my end.
124 00:14:28.500 ⇒ 00:14:46.979 Kaela Gallagher: Okay, okay, cool. Yeah, I’d love to just, like, use the rest of our time, to just ask for any feedback that you guys might have. I’ve been trying to make adjustments, like, as you guys have been letting me know things, but yeah, just curious, like, overall, if anybody has, feedback on the interview process.
125 00:14:55.140 ⇒ 00:14:55.780 Pranav: Should we have…
126 00:14:55.780 ⇒ 00:14:58.849 Kaela Gallagher: Everything’s just perfect? Okay, go ahead.
127 00:14:58.850 ⇒ 00:15:07.709 Pranav: I think Sam and I, like, indirectly have kind of, like, talked about, like, some, like, applicants. Not really applicants, but just, like, the interviews in general.
128 00:15:07.740 ⇒ 00:15:12.160 Kaela Gallagher: Sometimes after the fact, like, after I interviewed them, like we’ve kind of discussed.
129 00:15:14.600 ⇒ 00:15:21.130 Pranav: But I think that might just… I’m just thinking out loud, like, I think that might just be kind of solved with, like, the whole page of, like…
130 00:15:23.880 ⇒ 00:15:30.990 Pranav: just, like, the notion, like, you can kind of see, like, the BF chat, and then you can see the first round, and, like, for me, like, getting context for the second round. Yeah.
131 00:15:31.180 ⇒ 00:15:41.339 Pranav: I’m wondering, and honestly, this might be good enough, like, how we have it right now, like, is there another system where we can get that additional context, maybe even refine the specific…
132 00:15:41.570 ⇒ 00:15:57.010 Pranav: questions that we ask for our interview. Like Utam said, like, sometimes he has a really technical chat, maybe then we should have an even more refined technical chat for, like, that second round, or vice versa, like, if he’s having a more business-y chat, then maybe Sam can have, like, a…
133 00:15:57.620 ⇒ 00:16:03.150 Pranav: More refined, like, kind of business, like, just kind of… like,
134 00:16:03.560 ⇒ 00:16:07.710 Pranav: the questions that he’s asking can be more refined? Does that… does that kind of make sense?
135 00:16:08.630 ⇒ 00:16:14.519 Kaela Gallagher: Yeah, yeah, I think so. Yeah, I think that can be…
136 00:16:14.610 ⇒ 00:16:35.199 Kaela Gallagher: kind of adjusted, like, based on your communication, like, if you’re looking at Sam’s notes, and, like, I love that you and Sam are talking throughout the process, because I feel like you are able to, you know, maybe give Sam some feedback, like, oh, maybe we should have caught this thing in round one, and, vice versa, so I love that you guys are, like, chatting throughout the process.
137 00:16:35.200 ⇒ 00:16:38.200 Kaela Gallagher: The questions are there just as, like.
138 00:16:39.550 ⇒ 00:16:46.270 Kaela Gallagher: suggestions. Obviously, we want to be, like, evaluating the 4 or 5 categories that we have set out in each round.
139 00:16:46.270 ⇒ 00:17:03.530 Kaela Gallagher: But how you do that is kind of up to you. Like, if you’re going through an interview and you’re like, oh, I really need to dive deeper on technical things with this candidate, like, ask whatever questions you feel like you need to ask in order to, like, really evaluate their technical abilities.
140 00:17:03.530 ⇒ 00:17:06.169 Kaela Gallagher: And then if you have suggestions to, like.
141 00:17:06.170 ⇒ 00:17:20.559 Kaela Gallagher: the questions we have listed out and want to change them, like, we can do that as well, but, want to give you the ability to, like, have your own interviewing style and, you know, make it a conversation and feel like you can dive in deeper wherever you need to.
142 00:17:23.589 ⇒ 00:17:29.929 Amber Lin: I think, bring up a good point, and I… I think as a first-round interviewer, I would like to hear
143 00:17:29.939 ⇒ 00:17:45.269 Amber Lin: feedback from later in the loop. For example, say if Greg interviewed someone that I interviewed, did I give you enough notes, or would you like to hear more comments on this side? I think that helps me tweak how I interview.
144 00:17:46.259 ⇒ 00:17:50.259 Amber Lin: And also, I think, for…
145 00:17:50.509 ⇒ 00:18:10.119 Amber Lin: me and Greg, or at least I haven’t looked at our technical case study yet, so I go on the panel interview, and I… and I have, like, a little bit more context than the candidate, which is not helpful. So, I think having more visibility in the practice tests.
146 00:18:10.279 ⇒ 00:18:17.669 Amber Lin: Or, say, what we’re looking out of, to get out of the practice test would be helpful for the final panel interview.
147 00:18:18.060 ⇒ 00:18:21.379 Kaela Gallagher: Okay. Yeah, I know Robert,
148 00:18:21.390 ⇒ 00:18:35.139 Kaela Gallagher: built out that… that exam. And he even has, like, some sample answers on the… the page, that might be helpful for, like, you and Greg to… to review ahead of the panel.
149 00:18:35.140 ⇒ 00:18:49.549 Kaela Gallagher: Just showing you quickly here in Notion, where all of our practice, or all of our final challenges can be found. On the Hiring and Recruitment page, if you go here to Interview Exercises, and click in.
150 00:18:49.980 ⇒ 00:19:09.979 Kaela Gallagher: This data analyst case study is what we’re using for basically, like, all of our strategy roles right now, so you can click into that. And here there’s, like, you know, do not share with candidates sample answers, so you can open some of these docs, and it might give you some ideas for the final two.
151 00:19:10.840 ⇒ 00:19:12.739 Kaela Gallagher: But I can also share the link.
152 00:19:12.740 ⇒ 00:19:16.960 Amber Lin: Okay, very helpful. I… I got there already, so this is great.
153 00:19:17.210 ⇒ 00:19:19.230 Kaela Gallagher: Okay, perfect. Awesome.
154 00:19:19.860 ⇒ 00:19:24.669 Kaela Gallagher: Any other questions or qualms or suggestions?
155 00:19:25.420 ⇒ 00:19:37.229 Uttam Kumaran: Yeah, maybe the next record we do can be about candidates that, like, made it to the final round, but then didn’t make it, so we can look at, like, how we could have streamed them out faster in the process, you know?
156 00:19:37.550 ⇒ 00:19:41.920 Uttam Kumaran: Ultimately, as candidates get further down the pipe, it’s more expensive
157 00:19:42.070 ⇒ 00:19:59.660 Uttam Kumaran: For us, in general, and the amount of time, and the effort. And so, like, really, we want candidates to end up… I want… and I’ve sort of mentioned this before, like, I want actually not… there shouldn’t be many people as a percentage of our total pipeline that make it to the end. And so I think it’s always helpful for us to look at, like.
158 00:19:59.710 ⇒ 00:20:02.140 Uttam Kumaran: Who made it and didn’t make it through?
159 00:20:02.390 ⇒ 00:20:04.889 Kaela Gallagher: Yeah. And they’d be like, is there… was there a way we could’ve…
160 00:20:04.890 ⇒ 00:20:08.649 Uttam Kumaran: stream this earlier. Sometimes we… we may not have, but…
161 00:20:08.770 ⇒ 00:20:10.640 Uttam Kumaran: That could be good for another retro.
162 00:20:10.940 ⇒ 00:20:27.630 Kaela Gallagher: Yeah, 100%, yeah, we can make this monthly and kind of go through that next time, but yeah, I feel like we should be hiring, like, 50% of the people that make it to finals for the sake of our time, for the sake of the candidate experience, like, that’s why, you know, Pranav and Sam, I was, like, having you guys partner on
163 00:20:27.860 ⇒ 00:20:38.130 Kaela Gallagher: you know, we shouldn’t be sending, everybody to the final rounds, just for the sake of everyone’s time. So, yeah, good call out there, Utong.
164 00:20:41.970 ⇒ 00:20:49.780 Demilade Agboola: That… that does feel a bit good to hear, because sometimes I feel like I’m being a bit strict before sending people to the final round, but…
165 00:20:50.040 ⇒ 00:20:51.739 Kaela Gallagher: No, be strict.
166 00:20:52.580 ⇒ 00:21:00.480 Uttam Kumaran: Yeah, no, like, I really am serious, like, the people who make it to working with us, all of you on the call need to be like, I can’t wait to work with this.
167 00:21:00.480 ⇒ 00:21:00.850 Samuel Roberts: 100%.
168 00:21:01.190 ⇒ 00:21:01.680 Kaela Gallagher: Yes.
169 00:21:01.680 ⇒ 00:21:14.760 Uttam Kumaran: And so that’s why when you hear me ask you, like, I’m gonna ask, like, is this person someone that you, like, can’t wait for them to be on your team? Or is it someone that you’re like, yeah, I think it’d be great, because we are, like, slammed, we need people.
170 00:21:14.760 ⇒ 00:21:30.309 Uttam Kumaran: ultimately, like, I’ll make the call on, like, look, sometimes we just need to bring on people, but as much as possible, we want everybody to be, like, a hell yes or a no. Like, if it’s a mild yes, or, like, I could see this person figuring it out, like.
171 00:21:30.630 ⇒ 00:21:38.830 Uttam Kumaran: we all should be like, that’s a no, you know? And each of us has to push back, because when you guys know when you’re on a team.
172 00:21:38.970 ⇒ 00:21:42.829 Uttam Kumaran: And you’re currently, like, in the mix, and you’re really stressed.
173 00:21:42.870 ⇒ 00:21:57.829 Uttam Kumaran: you start to make sacrifices, and you may say, like, well, I just need whoever we got. I do this… I’m like… I do this all the time. And so it’s up to this panel for us to each be like, actually, no, this… I don’t think this person is, like, up to our caliber.
174 00:21:57.860 ⇒ 00:22:15.500 Uttam Kumaran: Because what you’ll find is if we let in people who aren’t as great, and ideally better than we are, the quality of the way we work together, the quality of the service we provide to clients is going to go down. And so, ultimately, like, your goal should be to bring on people that make you feel intimidated.
175 00:22:16.010 ⇒ 00:22:26.360 Uttam Kumaran: And there’s no risk to anyone’s job here, but, like, that’s what I want to promote, you know? And I want to say that out loud, because I feel like it’s rarely, sort of, expressed that way. So, yeah, great point, Demi.
176 00:22:26.730 ⇒ 00:22:40.829 Kaela Gallagher: Yeah, people that you’re, you know, excited about, that are gonna level you up, that are going to, you know, fill a gap on the team and bring us more knowledge in that gap, like, yeah, we should be really excited about the people that we’re moving forward each round.
177 00:22:45.780 ⇒ 00:23:00.799 Demilade Agboola: And also, just to be, like, so that maybe part of… I can get feedback on how I also, like, judge people. I look at the technical side, obviously. I want someone who can come in and hit the ground
178 00:23:01.060 ⇒ 00:23:02.719 Demilade Agboola: Running, technically? Yeah.
179 00:23:02.880 ⇒ 00:23:13.310 Demilade Agboola: But I also, like, look at it from a potential client-facing perspective as well. So some people, I have said, to be honest, if you look at some of my notes, I’ve said some people are, like, good technically.
180 00:23:13.610 ⇒ 00:23:27.670 Demilade Agboola: But, honestly, I… like, if this person was to face a client, or, like, to have conversations with the client, it could go south real quick, or it could just, like… they might struggle to convey their ideas to the client, and that was…
181 00:23:27.830 ⇒ 00:23:32.319 Demilade Agboola: largely my reason for, like, rejecting a particular candidate.
182 00:23:32.320 ⇒ 00:23:32.970 Kaela Gallagher: Okay.
183 00:23:33.720 ⇒ 00:23:44.149 Demilade Agboola: So, was I being too strict, or is that… is that something, like, that we should also try and balance? Like, try and find that balance between, hey, this person is probably, like, pretty good, but we also need someone who
184 00:23:44.640 ⇒ 00:23:50.840 Demilade Agboola: can interact with the client, or are we fine having people who are just, like, non-client facing.
185 00:23:51.510 ⇒ 00:24:05.680 Kaela Gallagher: Yeah, I mean, the purpose of the first round is kind of that, like, cultural fit and, you know, communication skills and being able to put people in front of clients, so I think that’s really good feedback for, you know.
186 00:24:05.970 ⇒ 00:24:09.910 Kaela Gallagher: the first round, like, interviewer in this case, of, like.
187 00:24:09.910 ⇒ 00:24:32.489 Kaela Gallagher: by the time they get to you, Dami, they should be very solid in terms of, like, yes, we can put them in front of a candidate, yes, they have great communication skills, and yes, they would get along with the team really well. And then, like, it’s kind of up to you to, you know, dive in deeper on the technical side. So, appreciate you catching the client side in that case, but, probably something we could have caught sooner.
188 00:24:32.490 ⇒ 00:24:33.670 Kaela Gallagher: On that candidate.
189 00:24:39.540 ⇒ 00:24:52.100 Samuel Roberts: I have a question about the, like, technical, exercises, or the interview. Like, I see… I was just looking at the AI automation one, and it said not started, and I see we have the old one. Is that what we’re looking to use still?
190 00:24:53.060 ⇒ 00:24:58.570 Kaela Gallagher: Yes, the AI one, I believe you guys developed before I got here.
191 00:24:58.570 ⇒ 00:25:00.859 Samuel Roberts: Yeah, I just didn’t know if that was still what we were… okay.
192 00:25:00.860 ⇒ 00:25:08.069 Kaela Gallagher: Yes, and then we recently developed, a data one, and then an analytics one as well, so, you have those three that we’re using.
193 00:25:08.070 ⇒ 00:25:09.840 Samuel Roberts: Okay, cool, cool. Just making sure I…
194 00:25:09.960 ⇒ 00:25:15.400 Samuel Roberts: was sort of telling candidates… I wasn’t explaining what was coming, but I was letting them know it was, and I’m making sure that we had that.
195 00:25:15.830 ⇒ 00:25:19.370 Kaela Gallagher: Awesome. Cool. Okay. Cool. It was another thought.
196 00:25:20.400 ⇒ 00:25:21.440 Samuel Roberts: I don’t know right now.
197 00:25:24.350 ⇒ 00:25:29.369 Kaela Gallagher: Also, if you think of it, feel free to hop in, but I did want to say, like.
198 00:25:29.440 ⇒ 00:25:47.640 Kaela Gallagher: You know, we’re all, like, learning through this process together. I think this, like, structured interview process is probably something that’s pretty new to everybody here. So feel free to, like, share feedback at all points. Feel free to share feedback with the person who interviewed before you, and say, you know, you should have caught this.
199 00:25:47.640 ⇒ 00:26:00.950 Kaela Gallagher: I’m happy to share that feedback with people as well, like, we’re all learning. Please share feedback with me, let me know what I can do to make your lives easier. Yeah, just appreciate, like, all of your collaboration in this process.
200 00:26:04.020 ⇒ 00:26:07.069 Samuel Roberts: Oh, and yeah, I… so I was,
201 00:26:07.720 ⇒ 00:26:15.719 Samuel Roberts: I don’t want to say struggling with a little bit, but, like, I wasn’t sure how technical to get, kind of, in that first round. There were a couple candidates where I was able to see…
202 00:26:15.950 ⇒ 00:26:21.969 Samuel Roberts: Okay, they’re rambling, I’m not really sure where they’re going, their communication skills, or,
203 00:26:22.190 ⇒ 00:26:30.759 Samuel Roberts: they’re just kind of basically answering the questions short and not really much. I was able to kind of see a little bit of that, get the feel for them, but then I’m not sure how…
204 00:26:30.970 ⇒ 00:26:33.899 Samuel Roberts: deep to go, or if I should just be saying, like.
205 00:26:34.090 ⇒ 00:26:51.880 Samuel Roberts: okay, they clearly can talk about it, but I don’t know what their actual skills are like, and so I’m not sure… it’s a little… maybe this is just a me, I’m not used to doing maybe less technical stuff, interview-wise, but I guess I’m kind of trying to figure where that balance is for the first round, because I don’t want to say someone, like, can talk a good game and then pass them on, and they’re just…
206 00:26:52.230 ⇒ 00:26:55.580 Uttam Kumaran: Yeah, I also have this question, too,
207 00:26:55.700 ⇒ 00:27:13.180 Uttam Kumaran: in that, like, should… should each round focus on everything? Because I actually think it’s sometimes helpful for someone to just check the box that this person is technical, so that, like, I don’t… you don’t have to do that again. But I also can see both points, that if you’re like, this person’s technical, but there’s, like.
208 00:27:13.360 ⇒ 00:27:15.470 Uttam Kumaran: They can’t hold a conversation.
209 00:27:15.470 ⇒ 00:27:16.010 Samuel Roberts: Yeah.
210 00:27:16.010 ⇒ 00:27:18.119 Uttam Kumaran: then you might… then I would say…
211 00:27:18.340 ⇒ 00:27:23.709 Uttam Kumaran: My thought is, like, you just mixed them right there, but I don’t know, like, sort of open the thoughts.
212 00:27:23.710 ⇒ 00:27:34.770 Samuel Roberts: Well, yeah, I think my thing is kind of the other way, where I’m able to hold a conversation with them, and they’re able to talk about the field and stuff going on, and explain some of their projects, but it’s not… we’re not going deep, and so I don’t know, you know.
213 00:27:34.770 ⇒ 00:27:35.430 Kaela Gallagher: Yes.
214 00:27:35.680 ⇒ 00:27:37.280 Samuel Roberts: And that’s why I’m just not sure…
215 00:27:37.420 ⇒ 00:27:49.360 Samuel Roberts: should… maybe the question is, like, should I get more technical earlier? Should we do more technical first, and, like, weed people out that just can’t do the work, and then… like, I guess, you know, where the filtering happens, maybe, is my question. Like, which order…
216 00:27:49.360 ⇒ 00:27:49.910 Kaela Gallagher: Yeah.
217 00:27:49.910 ⇒ 00:27:51.789 Samuel Roberts: Or how deep to go.
218 00:27:51.790 ⇒ 00:27:52.240 Kaela Gallagher: Yeah.
219 00:27:52.240 ⇒ 00:27:55.949 Samuel Roberts: Until we go even deeper on a more technical, focused one.
220 00:27:55.950 ⇒ 00:27:56.790 Kaela Gallagher: Yeah.
221 00:27:57.130 ⇒ 00:28:02.960 Kaela Gallagher: From my, like, initial conversations with all of you guys, and kind of looking at, like.
222 00:28:03.160 ⇒ 00:28:10.199 Kaela Gallagher: our pipeline and what’s been hardest to find in these candidates, the feedback that I received was, like.
223 00:28:10.900 ⇒ 00:28:29.200 Kaela Gallagher: most of the time, the candidates have the technical ability, and being able to put them in front of clients, and having the good communication skills, and, like, really collaborating with the team is the harder thing to find. So, to me, that’s why that is the first round right now, because we want the first round to be, like.
224 00:28:30.380 ⇒ 00:28:42.419 Kaela Gallagher: kind of, testing for the thing that’s hardest to find. We want to dequeue people as early in the process as possible. Okay. So that’s why it’s set up the way that it is right now.
225 00:28:42.560 ⇒ 00:28:44.330 Kaela Gallagher: Sam, I wouldn’t, like…
226 00:28:44.680 ⇒ 00:28:54.190 Kaela Gallagher: ask you to get into technical things in the first round, because I want you to feel, like, really confident about the cultural and communication side of things.
227 00:28:54.540 ⇒ 00:28:58.590 Kaela Gallagher: If you feel like, oh my gosh, this person’s amazing, and they totally.
228 00:28:58.590 ⇒ 00:28:59.360 Samuel Roberts: Right.
229 00:28:59.360 ⇒ 00:29:11.309 Kaela Gallagher: got fives in every category for communication and culture and all these things, and you have 15 minutes left, like, okay, sure, like, ask some technical questions, but, like, I don’t want to put that all on you round one.
230 00:29:11.310 ⇒ 00:29:15.009 Samuel Roberts: Okay, yeah, no, that’s fine. I just kind of… that’s exactly kind of what I was thinking. I didn’t know…
231 00:29:15.010 ⇒ 00:29:15.560 Kaela Gallagher: Ren.
232 00:29:15.780 ⇒ 00:29:29.089 Samuel Roberts: if… if this is the thing to filter on first, because it’s easier to find people that can do the work, but maybe can’t talk, like, that’s… that works for me then. I just kind of want to make sure I’m not just, you know, passing people that sound good, but can’t do the work kind of thing.
233 00:29:29.520 ⇒ 00:29:33.830 Uttam Kumaran: No, ultimately, guys, we’re looking for folks, we’re looking for folks like us, who are hard.
234 00:29:33.830 ⇒ 00:29:34.749 Samuel Roberts: Kind of what I have.
235 00:29:35.130 ⇒ 00:29:39.450 Uttam Kumaran: were very hard to find, so it’s almost hard for me to say one or the other.
236 00:29:39.570 ⇒ 00:29:45.769 Uttam Kumaran: I find whatever the things… I would say, if you’re nervous about something, build… dig into that first.
237 00:29:45.770 ⇒ 00:29:46.430 Samuel Roberts: F.
238 00:29:46.430 ⇒ 00:29:57.000 Uttam Kumaran: Like, in the 5 minutes, you’re like, great, this person’s awesome, they can talk, but, like, I don’t know if they can do any work, then switch and focus on that. Your job is to DQ.
239 00:29:57.000 ⇒ 00:29:57.680 Samuel Roberts: Right.
240 00:29:57.680 ⇒ 00:30:05.950 Uttam Kumaran: Like, I don’t… I mean, look, I think we’re all gonna have a mix of styles. Like, I already know that Demi is a hard interviewer. I have nothing… I have no problem with that.
241 00:30:06.090 ⇒ 00:30:21.069 Uttam Kumaran: I’ve been through… I think there’s… I think that we need to have a mix of people for, like, a true panel to work, right? And just because… just because Demi interviews hard, I know he’s also really gracious, and so he’ll say, like, I’m a hard interviewer. So.
242 00:30:21.090 ⇒ 00:30:23.479 Samuel Roberts: That’s why there needs to be a mix of…
243 00:30:23.510 ⇒ 00:30:29.490 Uttam Kumaran: ways that we interview, but ultimately, you’re… I think… if you find… you’re trying to find a weak spot.
244 00:30:29.640 ⇒ 00:30:31.860 Uttam Kumaran: So that, like, that can be documented.
245 00:30:32.150 ⇒ 00:30:40.149 Uttam Kumaran: And then we can have a discussion about it. So, like, if you feel like 10 minutes in, a candidate’s doing great on technical, then switch, you know?
246 00:30:40.150 ⇒ 00:30:40.770 Samuel Roberts: Okay.
247 00:30:40.990 ⇒ 00:30:42.360 Samuel Roberts: That makes sense.
248 00:30:43.390 ⇒ 00:30:44.060 Kaela Gallagher: Cool.
249 00:30:44.350 ⇒ 00:30:44.890 Kaela Gallagher: Amber?
250 00:30:44.890 ⇒ 00:31:00.420 Uttam Kumaran: But this should be a little bit… like, I just want to say this should be a little bit heartbreaking, like, meaning not everybody is as good at doing both as this crew is. Like, and you guys know from working in the industry that, like, folks like us are really hard to come by.
251 00:31:00.500 ⇒ 00:31:07.360 Uttam Kumaran: And it’s not like… I mean, we are recruiting, we’re doing our best to recruit great people, but ultimately, our hit rate should be low.
252 00:31:07.690 ⇒ 00:31:12.689 Uttam Kumaran: So just, like, keep that in mind. It’s, like, emotional process, but just keep that in mind.
253 00:31:15.260 ⇒ 00:31:15.910 Kaela Gallagher: Oh.
254 00:31:15.910 ⇒ 00:31:27.180 Amber Lin: I know we’re at time, so very quick question, also on the first round. I kind of do the same thing, but I try to find where the…
255 00:31:27.270 ⇒ 00:31:39.270 Amber Lin: weak spot is, but when it comes to, say, judging cultural fit, judging personality, I’m sometimes worried that I have my subjective judgment and subjective
256 00:31:39.270 ⇒ 00:31:51.780 Amber Lin: preferences of people, because we… we like people who’s more similar to us, and people who are a little bit different. Sometimes we have internal fears or inversions. I… I worry about
257 00:31:51.870 ⇒ 00:31:57.190 Amber Lin: my judgment there in the interview process? Well, I… well, I think
258 00:31:57.430 ⇒ 00:32:02.280 Amber Lin: I look for certain qualities that will fit the team, but
259 00:32:02.900 ⇒ 00:32:09.149 Amber Lin: I also fear that it’s too limited on my personal preferences. I sometimes worry that maybe this is
260 00:32:09.330 ⇒ 00:32:20.270 Amber Lin: Our old direction, and we’re heading in different ways, so what’s your guys’ comments on, like, personality fit, not just, say, the communication skills?
261 00:32:23.240 ⇒ 00:32:23.920 Kaela Gallagher: Hmm.
262 00:32:24.510 ⇒ 00:32:26.690 Kaela Gallagher: That’s a good point. That’s a good point.
263 00:32:26.900 ⇒ 00:32:28.880 Kaela Gallagher: I think it’s…
264 00:32:29.270 ⇒ 00:32:45.970 Kaela Gallagher: natural for, like, us to have biases in interviews. I think that happens in any interview process, no matter how much you try to maybe train against it, but I think it’s, like, really good that you kind of recognize, like, oh, I might have biases in certain areas. I think…
265 00:32:46.360 ⇒ 00:33:04.769 Kaela Gallagher: the fact that there’s multiple people in the interview process is, like, one of the methods that we use to counter that. Like, multiple people have to sign up… sign off on this person for them to be hired. But then I would say, like, the other way to maybe counter that is, like, using
266 00:33:05.300 ⇒ 00:33:24.720 Kaela Gallagher: facts in your review of the person, in your notes of the person, rather than, like, opinions. Like, oh, seems nice. Like, you know, that wouldn’t be something that we want to use to, like, push somebody forward to the next round. But, like, oh, clearly articulates their answers to questions.
267 00:33:24.720 ⇒ 00:33:37.329 Kaela Gallagher: And would be able to use that to communicate with a client well, that might… that’s more of, like, a fact and something that we could use to push somebody forward. But I’m curious if anybody else, like, has thoughts on this.
268 00:33:39.660 ⇒ 00:33:43.449 Demilade Agboola: So, personally, what I do is for…
269 00:33:43.720 ⇒ 00:33:46.799 Demilade Agboola: What I have done for different clients is I have…
270 00:33:47.120 ⇒ 00:33:51.009 Demilade Agboola: I first off do my review on, like, the score system.
271 00:33:51.620 ⇒ 00:33:57.779 Demilade Agboola: And I have my pass or fail, right? And then I take the interview transcript, and I pass it through cursor.
272 00:33:57.890 ⇒ 00:34:13.899 Demilade Agboola: And I just go, like, score this using the same criteria. Now, I look at the numbers, usually they’re around the same, so there are very few times I would say this was a 1, for instance, and Crystal will say, no, that’s a 5. No. It’s usually, like, 2, 1, like, it’s very close.
273 00:34:14.060 ⇒ 00:34:19.540 Demilade Agboola: But it does give me some feedback to make me have an idea of if I’m being so far off.
274 00:34:20.020 ⇒ 00:34:22.880 Demilade Agboola: And if I’m just so, like.
275 00:34:23.400 ⇒ 00:34:26.030 Demilade Agboola: Locked in my bias of, like.
276 00:34:26.500 ⇒ 00:34:32.520 Demilade Agboola: how I think a candidate should be. So I think kind of why I do that is so I just want to know if, hey.
277 00:34:33.230 ⇒ 00:34:48.689 Demilade Agboola: am I potentially rating a candidate lowly or highly when, objectively, they shouldn’t be that high? Because that then forces me to look again or think again about the conversation, and what was I missing? What did I,
278 00:34:48.870 ⇒ 00:34:51.089 Demilade Agboola: Overlook, that kind of thing.
279 00:34:51.090 ⇒ 00:34:54.590 Kaela Gallagher: Yeah, that’s a really great point. I love that you’re, like.
280 00:34:55.010 ⇒ 00:35:05.389 Kaela Gallagher: Putting your own ideas down first, jotting those down first, and then, like, using something to kind of, like, check you and make… maybe make you reconsider certain things.
281 00:35:06.420 ⇒ 00:35:07.509 Kaela Gallagher: I like that.
282 00:35:07.510 ⇒ 00:35:20.830 Amber Lin: I think… I think that sounds helpful. Like, should I be screening for, say, personality fit, or is that too much of a subjective judgment? Should I… maybe it should just be a.
283 00:35:20.830 ⇒ 00:35:23.459 Uttam Kumaran: Well, describe to me what personality fit means to you.
284 00:35:23.460 ⇒ 00:35:28.890 Amber Lin: sometimes I don’t… I don’t like people who’s too salesy or too intense.
285 00:35:28.890 ⇒ 00:35:29.650 Uttam Kumaran: Fair, fair.
286 00:35:29.650 ⇒ 00:35:33.869 Amber Lin: personal bias, but maybe we need a position that has someone like.
287 00:35:33.870 ⇒ 00:35:42.860 Uttam Kumaran: But I think, I think what you should do is, you should, if you’re able to identify that, I think you should put, hey, I felt like this person was a little bit too salesy.
288 00:35:43.150 ⇒ 00:35:55.030 Uttam Kumaran: And for that… and for that reason, I’m rating them low here. Because ultimately, at the end of it, someone will look at all the scores and be like, actually, this role needs to be salesy, so that’s okay. Like, I… I would rather you…
289 00:35:55.030 ⇒ 00:36:06.889 Uttam Kumaran: If it’s so much that you’re like, there’s no way this person, like, this person would survive here, then you can DQ. But if you’re like, look, they did well, but they’re also, like, kind of, like, salesy.
290 00:36:06.890 ⇒ 00:36:16.289 Uttam Kumaran: And maybe, like, I feel like I don’t… I wouldn’t be best friends with them, but I think they could probably crush here. You should just write that down, like, write the… write the bias down.
291 00:36:16.290 ⇒ 00:36:30.290 Uttam Kumaran: So that at the end, what we’re gonna do is we’re gonna look across candidates. So ultimately, if we have two candidates, and the role is not salesy, and one person is really over the top, then maybe the other person gets it, and that’s… that’s the context we would have needed in the doc.
292 00:36:30.730 ⇒ 00:36:45.219 Amber Lin: Okay, so based on your guys’ comments, I think I’ll put it as a note, and I’ll use it… I don’t usually use it to de-qualify people, but it’s something that I’ll note for the next round interviewer, so that’s helpful.
293 00:36:45.220 ⇒ 00:36:52.269 Kaela Gallagher: And maybe it affects the score in, like, one of the categories, but Amber, I know what candidate made you think of this.
294 00:36:53.600 ⇒ 00:36:56.209 Kaela Gallagher: And you did, you put it in the notes.
295 00:36:56.210 ⇒ 00:36:58.059 Amber Lin: And I did tell you, I, like, I…
296 00:36:58.060 ⇒ 00:36:58.410 Kaela Gallagher: Yes.
297 00:36:58.410 ⇒ 00:37:04.640 Amber Lin: I know he’s strong, I just personally felt very, it was very intense.
298 00:37:04.640 ⇒ 00:37:24.259 Kaela Gallagher: Yes, and so that section of the notes where you were like, oh, I would like to see more grace and empathy for clients, and very salesy, I went in and I bolded that, and so when Greg talks to him tomorrow, hopefully that’s, you know, what Greg sees before he goes into that interview and can dig in a little bit deeper and, you know, see if he agrees with you or sees anything.
299 00:37:24.260 ⇒ 00:37:24.740 Amber Lin: Okay.
300 00:37:24.740 ⇒ 00:37:25.520 Kaela Gallagher: a flag.
301 00:37:25.680 ⇒ 00:37:26.830 Amber Lin: Sounds good.
302 00:37:26.830 ⇒ 00:37:27.979 Samuel Roberts: I’d also say, like.
303 00:37:28.200 ⇒ 00:37:45.739 Samuel Roberts: I don’t know, I have kind of mixed feelings about this, having gone through hiring processes and been on the other side, and gone back and forth, but, like, these are people you’re gonna wanna be working with, you know? Like, there’s something to be said for, like, this person rubs me the wrong way, I don’t know what it is, but, like, flagging that is good in some way. Whether or not it’s… it’s…
304 00:37:46.190 ⇒ 00:37:51.879 Samuel Roberts: the determining factor, but, you know, if he rips you the wrong way, he might rip someone else the wrong way, he might.
305 00:37:51.880 ⇒ 00:37:52.360 Uttam Kumaran: Totally.
306 00:37:52.360 ⇒ 00:37:54.730 Samuel Roberts: Other people internally the wrong way, or externally the wrong…
307 00:37:55.310 ⇒ 00:38:02.370 Samuel Roberts: It could be something you miss completely because you get along with someone and someone else might flag it, but I think noting it down is well worth it.
308 00:38:03.430 ⇒ 00:38:04.739 Amber Lin: I see. Cool.
309 00:38:05.360 ⇒ 00:38:06.000 Kaela Gallagher: Yeah.
310 00:38:07.860 ⇒ 00:38:12.700 Amber Lin: Alright, that was all my questions. This was… this is a really cool call. I hope we keep doing this.
311 00:38:12.700 ⇒ 00:38:14.600 Kaela Gallagher: Okay, yay, I’m glad you guys found it valuable.
312 00:38:14.600 ⇒ 00:38:27.779 Uttam Kumaran: Yeah, I’m so glad, because I interviewed all of you, and it’s so nerve-wrecking, and, you know, like, I feel so lucky to have gotten lucky to have you guys on the team, but you’ve also made
313 00:38:27.900 ⇒ 00:38:33.569 Uttam Kumaran: I would say, like, whenever someone doesn’t work out at our company, I blame us, and, like, our process, and, like.
314 00:38:33.620 ⇒ 00:38:39.120 Uttam Kumaran: ultimately, like, there’s folks that will work out at another company. Our company is very unique.
315 00:38:39.160 ⇒ 00:38:56.309 Uttam Kumaran: And so we’re just trying to keep a super, super high bar of talent, because all these people are gonna be working under you guys very soon. And so, really think about, in any doubt, think about, would I want this person on my team? Like, would I be pumped to talk to this person at 8am every morning, or, like, 8pm every night?
316 00:38:56.740 ⇒ 00:39:01.670 Uttam Kumaran: Right? And if it’s a no, then no, then just say no. That’s fine. Like… Right.
317 00:39:01.670 ⇒ 00:39:02.290 Kaela Gallagher: Right.
318 00:39:02.430 ⇒ 00:39:03.200 Uttam Kumaran: Yeah.
319 00:39:04.850 ⇒ 00:39:05.490 Kaela Gallagher: Perfect.
320 00:39:05.490 ⇒ 00:39:06.330 Samuel Roberts: Yeah, that’s good.
321 00:39:07.130 ⇒ 00:39:27.509 Kaela Gallagher: Cool, guys. Well, I will try to make this, like, a monthly thing, and just, you know, we can come together, talk about our findings, talk about candidates that made it to the final that maybe shouldn’t have. We can always, like, dig in deeper to our processes, but really appreciate, like, all of your guys’ feedback here, and, I think it’s gonna make us all better moving forward, so…
322 00:39:27.510 ⇒ 00:39:32.370 Kaela Gallagher: Thank you guys for your time, and yeah, I’m always ears if you guys have anything else.
323 00:39:33.710 ⇒ 00:39:37.619 Amber Lin: Awesome, yeah, and thank you, Kala, for making this so much easier. I feel like…
324 00:39:37.620 ⇒ 00:39:38.190 Uttam Kumaran: Yes.
325 00:39:38.190 ⇒ 00:39:40.649 Amber Lin: It’s gotten so much better since you joined.
326 00:39:40.940 ⇒ 00:39:42.580 Uttam Kumaran: Look at that, man! That’s…
327 00:39:43.110 ⇒ 00:39:50.490 Amber Lin: I get reminders that I have an interview at least a day before, so I don’t read their notes 5 minutes.
328 00:39:50.490 ⇒ 00:39:50.910 Uttam Kumaran: I was in trouble.
329 00:39:51.310 ⇒ 00:39:52.020 Uttam Kumaran: Laura, yes.
330 00:39:52.020 ⇒ 00:39:52.860 Samuel Roberts: Yeah, yeah.
331 00:39:52.860 ⇒ 00:39:54.870 Uttam Kumaran: at all, and I had to…
332 00:39:54.870 ⇒ 00:39:55.340 Kaela Gallagher: I won’.
333 00:39:55.340 ⇒ 00:39:59.140 Uttam Kumaran: I’m also so… I’m also so happy. This is, like, such a better process.
334 00:39:59.140 ⇒ 00:40:01.070 Kaela Gallagher: Aw, awesome. Glad to hear it.
335 00:40:01.890 ⇒ 00:40:04.669 Kaela Gallagher: Cool. Well, I hope everyone has a great Tuesday.
336 00:40:04.880 ⇒ 00:40:05.590 Uttam Kumaran: Thank you, everyone.
337 00:40:05.590 ⇒ 00:40:06.130 Samuel Roberts: Awesome.
338 00:40:06.590 ⇒ 00:40:07.350 Samuel Roberts: Thanks! Bye!