Meeting Title: Brainforge AI General Catch-up Date: 2026-02-16 Meeting participants: Luke Scorziell, Neima Beizai
WEBVTT
1 00:00:14.890 ⇒ 00:00:16.129 Neima Beizai: What up, dude?
2 00:00:16.329 ⇒ 00:00:17.779 Luke Scorziell: Hey, man, how’s it going?
3 00:00:18.060 ⇒ 00:00:21.329 Neima Beizai: Another day, another dream, as it were. How about you?
4 00:00:21.500 ⇒ 00:00:24.519 Luke Scorziell: Nice, yeah, living the dream here, too, I guess.
5 00:00:24.520 ⇒ 00:00:26.630 Neima Beizai: Hell yeah, man.
6 00:00:26.630 ⇒ 00:00:28.340 Luke Scorziell: Raining out in LA, which is…
7 00:00:28.650 ⇒ 00:00:32.630 Neima Beizai: That’s different. I was gonna say, that’s different different.
8 00:00:32.630 ⇒ 00:00:36.640 Luke Scorziell: It’s always nice, though, when it does rain, because it’s like,
9 00:00:37.150 ⇒ 00:00:39.650 Luke Scorziell: like, breaks up the monotony of… I mean, it’s…
10 00:00:39.650 ⇒ 00:00:40.040 Neima Beizai: Yeah.
11 00:00:40.040 ⇒ 00:00:44.100 Luke Scorziell: like, easy, or probably hard to hear complaining from people who live in SoCal when you live.
12 00:00:44.100 ⇒ 00:00:44.640 Neima Beizai: Yeah.
13 00:00:44.640 ⇒ 00:00:49.890 Luke Scorziell: It’s actually cold, but it’s like, you know, it’s always so sunny that it’s, like, Sometimes, right?
14 00:00:50.310 ⇒ 00:00:57.039 Neima Beizai: Yeah, yeah, I mean, dude, there’s fucking snow on the floor in New York, so I’m just like, oh, okay. Where are you in New York?
15 00:00:57.450 ⇒ 00:01:12.710 Neima Beizai: I’m in the Lower East Side in Manhattan, so kind of in the mix of all that. I literally… you know what’s so funny is I literally walked through my door, and I was like, I gotta get on this call now. So I was, like, running… I was running all over all day today. I, I have a very interesting opportunity, so I had to make a pitch deck for it.
16 00:01:12.710 ⇒ 00:01:22.059 Neima Beizai: So I did that. Yeah, and then I asked a few of my friends who were kind of, like, in finance on that side to look at it, so I was meeting with one of them, and it went longer than I thought, and I was like, oh!
17 00:01:22.380 ⇒ 00:01:24.309 Neima Beizai: You know what I mean?
18 00:01:24.310 ⇒ 00:01:27.619 Luke Scorziell: Well, tell me, how’s… how’s the startup going, right?
19 00:01:27.620 ⇒ 00:01:29.480 Neima Beizai: Yeah, so I’m full-time on it, my guy.
20 00:01:29.780 ⇒ 00:01:30.440 Luke Scorziell: What’d you say?
21 00:01:30.440 ⇒ 00:01:33.079 Neima Beizai: I’m full-time on it now, bro. Nice, nice.
22 00:01:33.150 ⇒ 00:01:34.270 Luke Scorziell: Yeah, yeah, yeah.
23 00:01:34.270 ⇒ 00:01:45.709 Neima Beizai: Yeah, I took the leap, I quit my job, and I was like, let’s go full-time on this. So now, I also make go-to-market type and a salesman, so that’s pretty fun. I’m enjoying that. Yeah, yeah, so I’m just trying to drive adoption and whatnot.
24 00:01:45.810 ⇒ 00:01:58.849 Neima Beizai: My team is cool, we’re working on things too, we’re handling things, so on and so forth. We’re building another layer, actually, right now, as I kind of sell to businesses, which is for candidates. So say, for example, you wanted to sharpen your go-to-market skills.
25 00:01:58.860 ⇒ 00:02:06.799 Neima Beizai: Right? You can go to our platform, you can get, like, certification for specific things and go to market, like, let’s say market research, market understanding.
26 00:02:06.800 ⇒ 00:02:09.729 Luke Scorziell: Hold outreach, conversion, whatever it might be.
27 00:02:09.729 ⇒ 00:02:15.500 Neima Beizai: Right, you can kind of get certified for that, and we’d help you kind of, like, gain the skill sets you need for that. So we’re working on building that right now.
28 00:02:17.150 ⇒ 00:02:19.649 Luke Scorziell: Just using external platforms that can kind of, like.
29 00:02:19.650 ⇒ 00:02:23.999 Neima Beizai: No, we’re gonna build it internally ourselves, we’re gonna have our own version of it.
30 00:02:24.350 ⇒ 00:02:25.560 Luke Scorziell: Oh, really? Wow, so you’ll have your own.
31 00:02:25.560 ⇒ 00:02:25.920 Neima Beizai: Fair enough.
32 00:02:25.920 ⇒ 00:02:26.900 Luke Scorziell: communications and stuff.
33 00:02:27.180 ⇒ 00:02:36.180 Neima Beizai: Yeah, yeah, yeah. And so basically, you come in… yeah, so imagine you come into our platform as a candidate, you get certified, and now you’re searchable by companies looking for what you have certification in.
34 00:02:37.310 ⇒ 00:02:38.849 Luke Scorziell: That’s pretty cool.
35 00:02:38.850 ⇒ 00:02:44.780 Neima Beizai: Right? Yeah, yeah, yeah. Yeah, 9 out of 10 candidates prefer to apply the way I showed you, which I think is really cool.
36 00:02:44.830 ⇒ 00:02:59.669 Neima Beizai: I have some more data for you on this, actually. Interestingly enough, 8% of all candidates we’ve run through fall into our strong category, and people who fall into the strong category have a 30% interview rate and a 15% higher rate. The current higher rate is 1% across all applicants.
37 00:03:01.250 ⇒ 00:03:05.490 Luke Scorziell: I see that, so you’re, yeah, a lot higher than I… On the average…
38 00:03:05.490 ⇒ 00:03:06.960 Neima Beizai: And just a resume screen, right?
39 00:03:07.680 ⇒ 00:03:15.330 Neima Beizai: And… and we’re currently at 76 to 1 in terms of applicants to hire versus industry average of 200 to 1.
40 00:03:15.500 ⇒ 00:03:34.060 Neima Beizai: Which is a 62% reduction in time to fill. So, for example, let’s say you have a GDM assistant you want to hire, right? In the traditional process, you have to go through the meat grinder, you know, part of my language. Using our thing, you’d send all the people who apply and say, hey, look, just, I want to learn more about you, please go through this, you don’t have to. Whoever goes through it, you start there, start at the top, and work your way down.
41 00:03:34.940 ⇒ 00:03:35.520 Luke Scorziell: Yeah.
42 00:03:35.890 ⇒ 00:03:36.890 Luke Scorziell: Nice, nice.
43 00:03:36.940 ⇒ 00:03:38.479 Neima Beizai: Yeah, no, that’s cool.
44 00:03:40.240 ⇒ 00:03:45.920 Luke Scorziell: Yeah, well, I guess, so it… I got down to catch up, too, about their heritage and what you’re working on, but what’s,
45 00:03:46.040 ⇒ 00:03:48.920 Luke Scorziell: Yeah, is there any, I guess, prompt… just general catch-up?
46 00:03:48.920 ⇒ 00:03:57.260 Neima Beizai: Dude, literally, yeah, just general catch-up, dude. I saw you have a job at Brainforge AI, I was curious about that. You’re doing go-to-market, that’s really curious, you know? So literally, I just wanted to catch up, dude.
47 00:03:57.430 ⇒ 00:04:04.060 Luke Scorziell: Yeah, yeah, for sure. Yeah, it’s been dope. We, started… so I started in December,
48 00:04:04.310 ⇒ 00:04:06.770 Luke Scorziell: doing, like, consulting, and then January, I’ve just…
49 00:04:06.770 ⇒ 00:04:07.299 Neima Beizai: Kind of in, like.
50 00:04:07.300 ⇒ 00:04:09.489 Luke Scorziell: Launching content, for them.
51 00:04:09.720 ⇒ 00:04:15.140 Luke Scorziell: Kind of, like, more probably on the content and marketing side of the go-to-market than on the sales side.
52 00:04:15.140 ⇒ 00:04:19.449 Neima Beizai: Sure, so kind of like the marketing side of it, of how to, like, build a brand, let’s say, maybe.
53 00:04:19.450 ⇒ 00:04:21.830 Luke Scorziell: Yeah, exactly. So.
54 00:04:21.839 ⇒ 00:04:29.739 Neima Beizai: Yeah, because that was your lane, too. So when I… sorry, like, when I saw it, I knew you were kind of like a marketing guy, so I was like, oh, interesting, go to market. That’s, interesting to kind of get into.
55 00:04:30.010 ⇒ 00:04:39.510 Luke Scorziell: Yeah, yeah, I think it’s, it’s, you know, it’s, like, evolving, and it’s, like, 20 or 30 people at this point, and we’re just trying to see, like, what…
56 00:04:39.940 ⇒ 00:04:42.410 Luke Scorziell: Yeah, what works and what clicks.
57 00:04:42.570 ⇒ 00:04:52.100 Luke Scorziell: So, yeah, it’s been good, but, like, pretty dope to see some of the, like, AI solutions and stuff that we’ve been able to build. Which reminds me, your platform, too, is also…
58 00:04:52.470 ⇒ 00:04:54.070 Luke Scorziell: Was it pretty, urban?
59 00:04:54.400 ⇒ 00:04:55.740 Neima Beizai: Yeah, we’re AI-powered also.
60 00:04:56.170 ⇒ 00:04:58.520 Luke Scorziell: Oh, nice. What have you been using for that?
61 00:04:58.910 ⇒ 00:05:00.000 Neima Beizai: Our backend?
62 00:05:00.000 ⇒ 00:05:00.440 Luke Scorziell: Yeah.
63 00:05:00.440 ⇒ 00:05:03.769 Neima Beizai: Without getting too into it, one of the large LLMs, my friend.
64 00:05:04.180 ⇒ 00:05:05.070 Luke Scorziell: Okay.
65 00:05:05.360 ⇒ 00:05:07.269 Neima Beizai: Yeah. One thing…
66 00:05:07.450 ⇒ 00:05:12.859 Luke Scorziell: pretty high adoption? Or, like, what… or what, like, how’s the go-to-market process been, I guess, for you?
67 00:05:12.860 ⇒ 00:05:28.969 Neima Beizai: Oh my god, dude. It’s, well, I was constrained by literally having a full-time job for pretty much up until 2 weeks ago, so it was a lot of just chasing and not being able to really chase, because, like, for example, I’d hit up, like, enterprise people, and they’re like, alright, sick, let’s talk, I’d do a demo then, like, I had to chase them down, right?
68 00:05:29.120 ⇒ 00:05:41.269 Neima Beizai: First two weeks was just closed open business, which has been going okay, and now it’s just like, alright, new motion, start getting new people, so we’ll see. I feel pretty good, though, based on my pipeline stats. From cold, I convert about 5%.
69 00:05:41.450 ⇒ 00:05:47.920 Neima Beizai: From Enterprise, I convert 4%, and on SMB, I convert 10%. So I’m at about 8% between the two.
70 00:05:48.470 ⇒ 00:05:54.969 Neima Beizai: Nice. Yeah, and again, that’s part-time, right? That’s part-time, I never really did sales before, you know what I mean?
71 00:05:55.720 ⇒ 00:06:02.419 Luke Scorziell: Yeah, it’s brutal when you, getting out there. What are you doing for enterprise? Are you just cold outreach, or how are you…
72 00:06:02.420 ⇒ 00:06:13.719 Neima Beizai: I just… I know tons of people, bro. For example, if I wanted to work with Brainforge, I’d say, hey, Luke, you guys hiring? You’re like, oh, I don’t know, maybe. I’m like, well, I’d love to talk to your HR. And then it either goes or doesn’t go, and I have to chase you down. You know?
73 00:06:14.300 ⇒ 00:06:18.369 Luke Scorziell: Huh. No, that’s… that’s dope. Yeah, the network, I mean, we’re finding that, too. I think it’s, like.
74 00:06:18.640 ⇒ 00:06:20.500 Luke Scorziell: My network, the founder’s network.
75 00:06:20.500 ⇒ 00:06:21.160 Neima Beizai: Yeah.
76 00:06:21.160 ⇒ 00:06:23.940 Luke Scorziell: Just trying to see, like, however we can… Yeah. …get up.
77 00:06:24.580 ⇒ 00:06:27.470 Neima Beizai: Yeah, because if you think about it, right, in go-to-market in general.
78 00:06:27.470 ⇒ 00:06:27.850 Luke Scorziell: Hmm.
79 00:06:27.850 ⇒ 00:06:44.709 Neima Beizai: the people buy from people. Like, I can’t send you to my site, cold, and be like, Luke, go get this software. Like, what the fuck is this? You know? But people buy from people. Once you have enough scale where people know the person, then it’s a little different, right? It’s like, oh, I want to go on Netflix, you know Netflix, right? But at one point, Netflix was a company no one heard about.
80 00:06:45.000 ⇒ 00:06:51.870 Neima Beizai: You know what I mean? So, at one point, they had to go through that, like, people buy from people stage to get to the place where now you just, you build it and you give them your card.
81 00:06:53.250 ⇒ 00:06:59.170 Luke Scorziell: Yeah, no, that 100% makes sense. And are you… what are you aiming out of that mix?
82 00:06:59.990 ⇒ 00:07:02.860 Luke Scorziell: like, more enterprise, more SMB.
83 00:07:03.090 ⇒ 00:07:12.490 Neima Beizai: I think SMB has a better benefit to this than Enterprise does. My growth plan was go SMB, get a bunch of SMB, and then leverage that to get into Enterprise.
84 00:07:13.050 ⇒ 00:07:17.340 Luke Scorziell: What do you think has been stronger about the SMB segment?
85 00:07:17.340 ⇒ 00:07:28.849 Neima Beizai: faster decision cycles, and frankly, they have a higher need for what we offer than I think Enterprise does. Like, if I’m talking about, like, the Facebooks of the world, the Googles of the world, that’s a very long game until I get them.
86 00:07:28.990 ⇒ 00:07:31.040 Neima Beizai: Right? But if I’m talking about, like.
87 00:07:31.520 ⇒ 00:07:37.459 Neima Beizai: you know, let’s say your organization, my organization, any of these, like, others, like, startup organizations, it’s a much faster way to get to them.
88 00:07:37.720 ⇒ 00:07:39.560 Neima Beizai: I get it adopted, you know?
89 00:07:40.210 ⇒ 00:07:46.749 Luke Scorziell: Yeah, no, that’s super cool. Yeah, I mean, I’m, like, personally not hiring at the moment, but it would be interesting to see,
90 00:07:47.360 ⇒ 00:07:50.940 Luke Scorziell: Like, I’m sure… yeah, we’re… I know we’re hiring a lot on the engineering side.
91 00:07:51.030 ⇒ 00:07:58.649 Neima Beizai: Dude, for what it’s worth, Luke, our system is being used for two software engineers. I would love to help you guys out with one, honestly.
92 00:07:59.960 ⇒ 00:08:02.889 Luke Scorziell: Yeah, well, tell me a little more, too, about what.
93 00:08:03.250 ⇒ 00:08:04.550 Luke Scorziell: All worked again, because it’s been…
94 00:08:04.550 ⇒ 00:08:06.810 Neima Beizai: Yeah, dude, I’ll show you, bro. Dude, I’ll show you.
95 00:08:06.970 ⇒ 00:08:10.290 Neima Beizai: And you’re recording this, how perfect, you can literally show the team what it does.
96 00:08:10.290 ⇒ 00:08:11.260 Luke Scorziell: Yeah.
97 00:08:12.120 ⇒ 00:08:14.009 Neima Beizai: I know all of our stuff just.
98 00:08:14.150 ⇒ 00:08:17.629 Luke Scorziell: That’s, like, all… all… all… all the time recording.
99 00:08:18.100 ⇒ 00:08:30.090 Neima Beizai: Yo, my best friend, he’s like, that red light, it’s always on, dude. I’m like, you’re right, man, you’re right. Alright, here, let’s go to Brainforge.ai Careers, and let’s grab a job from here.
100 00:08:30.370 ⇒ 00:08:32.530 Neima Beizai: No… do you guys do it on Notion?
101 00:08:32.659 ⇒ 00:08:33.890 Neima Beizai: No, yeah?
102 00:08:34.240 ⇒ 00:08:35.660 Luke Scorziell: Yeah, I think we jumped
103 00:08:36.409 ⇒ 00:08:38.319 Luke Scorziell: I appreciate it. What’s up on it, Shin?
104 00:08:38.600 ⇒ 00:08:42.200 Neima Beizai: Alright, cool. Alright, sick. Let’s do, an automation engineer.
105 00:08:42.490 ⇒ 00:08:43.409 Neima Beizai: Amazing.
106 00:08:43.980 ⇒ 00:08:48.690 Neima Beizai: Let’s… What do we want, what do we want, what do we want?
107 00:08:49.980 ⇒ 00:08:51.280 Neima Beizai: Okay, let’s do this.
108 00:08:51.630 ⇒ 00:08:53.060 Neima Beizai: Oh, can I not copy it?
109 00:08:53.860 ⇒ 00:08:55.479 Neima Beizai: Alright, we’ll copy all of this.
110 00:08:57.440 ⇒ 00:09:02.559 Neima Beizai: So here, we’ll create a new job together right now, so I’ll drop in the job description…
111 00:09:02.970 ⇒ 00:09:08.690 Neima Beizai: And then here, I’ll grab this guy… The about… oh my god.
112 00:09:09.400 ⇒ 00:09:10.110 Luke Scorziell: That’s fair.
113 00:09:10.330 ⇒ 00:09:14.979 Neima Beizai: to think… to think Notion is a major, major site, and it has these things.
114 00:09:17.310 ⇒ 00:09:22.900 Neima Beizai: Alright, we’ll grab this, why join Brainforge… We’ll drop this.
115 00:09:22.900 ⇒ 00:09:29.779 Luke Scorziell: I mean, a lot of the applicants that we’re getting, too, are coming from, I guess, just DMs and our own networks, too.
116 00:09:30.240 ⇒ 00:09:30.700 Neima Beizai: Yeah.
117 00:09:30.700 ⇒ 00:09:31.169 Luke Scorziell: That is…
118 00:09:31.170 ⇒ 00:09:31.890 Neima Beizai: That’s something.
119 00:09:33.200 ⇒ 00:09:41.949 Neima Beizai: I mean, this is something you can send to anyone at any time, so even if you get DMs, right? And you still don’t… you still might not know if they can actually do the job or not. The point of this is to figure out, can they do the job?
120 00:09:42.470 ⇒ 00:09:44.829 Neima Beizai: So I’ll show you what I mean by this.
121 00:09:45.200 ⇒ 00:09:48.759 Neima Beizai: what was this? Automation Engineer? Is that right? Yeah, an automation engineer.
122 00:09:52.050 ⇒ 00:09:55.640 Neima Beizai: I’m assuming this is probably a mid-level hire? Mid-level to senior level?
123 00:09:55.830 ⇒ 00:09:56.150 Luke Scorziell: Yeah.
124 00:09:56.150 ⇒ 00:09:59.579 Neima Beizai: senior level, just in case. Industry will say artificial intelligence.
125 00:10:02.950 ⇒ 00:10:10.469 Neima Beizai: Then this is cool, you can either go general AI and Automation Engineer, or an expert in AI, because it’s slightly different. Let’s start in the middle here.
126 00:10:10.580 ⇒ 00:10:17.410 Neima Beizai: Candidate fit, strong is 8% of all applicants. Good includes strong, and that’ll be 76% of all applicants.
127 00:10:17.480 ⇒ 00:10:36.919 Neima Beizai: So let’s say good for this one. Require resume is purely just optional, we don’t need it. It doesn’t affect anything, it’s just for convenience. Same with this label. You can choose between 1 and 10 questions, so let’s just say 4. You can even do a custom question here, and type it in. So, software engineer, last one that was hired, they had 6 custom questions input for their, hiring.
128 00:10:37.120 ⇒ 00:10:43.479 Neima Beizai: For their questions. So, you hit submit, and now the job is live here. So you have AI and Automation Engineer here.
129 00:10:43.670 ⇒ 00:11:02.059 Neima Beizai: You can copy this link, so back to your point, let’s say someone DMs you on LinkedIn, right? Hey, Luke, I saw your AI and automation engineer job, I’m really interested. I DM you, right? Say, alright, sure, Nima, no problem. Here, take this assessment, you know, fill out this application, fill out this assessment, fill out whatever, right? When they say, I get it, I click on the link, hey, we just want to learn more about you.
130 00:11:02.510 ⇒ 00:11:03.550 Neima Beizai: Let me hit start.
131 00:11:05.100 ⇒ 00:11:08.809 Luke Scorziell: And do you white-label the software to where, like, it can have Brainforge’s branding on it?
132 00:11:09.560 ⇒ 00:11:11.960 Neima Beizai: We’re working on an API, so yes.
133 00:11:12.310 ⇒ 00:11:12.940 Luke Scorziell: Nice.
134 00:11:13.300 ⇒ 00:11:21.280 Neima Beizai: Yeah, that’s further down the, roadmap, but yes, if you want to talk about that, I’m open to talk about that, but I would like to also help you guys out with your searches, because that’s kind of our core business.
135 00:11:21.370 ⇒ 00:11:22.490 Luke Scorziell: Yeah.
136 00:11:22.710 ⇒ 00:11:30.770 Neima Beizai: So, here’s an example, right? Imagine you’re tasked with developing a new LLM-based feature, but midway through, you encounter unexpected technical challenges that hinder progress.
137 00:11:30.950 ⇒ 00:11:36.379 Neima Beizai: Sure. How would you approach resolving these issues while keeping stakeholders informed and ensuring alignment with the project timeline?
138 00:11:36.720 ⇒ 00:11:42.970 Neima Beizai: I’d figure out what the, technical… Challenges.
139 00:11:43.120 ⇒ 00:11:49.500 Neima Beizai: Are driven by, and then create a plan to address them.
140 00:11:49.620 ⇒ 00:11:54.369 Neima Beizai: If need be, I’d… Consult with experts.
141 00:11:55.560 ⇒ 00:11:58.159 Neima Beizai: Once… res… one set…
142 00:11:58.330 ⇒ 00:12:04.959 Neima Beizai: I’d hold a meeting for the team to keep them in the loop, let’s just say.
143 00:12:05.400 ⇒ 00:12:14.899 Neima Beizai: You receive feedback from a user that the current optimization of embeddings is not meeting their needs. Describe how you would handle this feedback, including how you would iterate on design and communicate changes to the team and the user.
144 00:12:15.550 ⇒ 00:12:22.249 Neima Beizai: Okay, optimization of embeddings. That means, for what it’s worth, Luke, I’m not an AI and automation engineer, so forgive me.
145 00:12:22.860 ⇒ 00:12:23.929 Neima Beizai: I’m gonna do…
146 00:12:23.930 ⇒ 00:12:24.260 Luke Scorziell: Oh my god.
147 00:12:24.260 ⇒ 00:12:31.770 Neima Beizai: though, I’m assuming this means… and just so you know, let’s say I went to ChatGPT, right? One, I can’t… I can try copying this, right?
148 00:12:31.900 ⇒ 00:12:35.030 Neima Beizai: But we don’t allow it, and you also can’t paste in the box.
149 00:12:35.580 ⇒ 00:12:36.600 Luke Scorziell: Oh, really? Huh.
150 00:12:36.600 ⇒ 00:12:42.799 Neima Beizai: Yeah, and we limit you to 350 words, and on our other side, we track how many… or how much time, sorry, someone spent on it.
151 00:12:42.800 ⇒ 00:12:58.960 Neima Beizai: So it’s not time-bound to you, the candidate, but on our end, we’ll track how much time it took. So you can see, if you have a cluster of, let’s say, 10 people, right, and 9 of them took 30 minutes, and 1 took 2 hours, like, okay, this 2-hour person took a lot longer, why? And you can look at their answers and say, oh, these look AI-generated, I don’t want to talk to them, I want to talk to the other ones.
152 00:12:58.980 ⇒ 00:13:01.439 Neima Beizai: It’s kind of part of our, like, anti-cheating measures.
153 00:13:01.580 ⇒ 00:13:08.269 Neima Beizai: Okay, I’m gonna say I’m not sure I did finance, not AI.
154 00:13:08.840 ⇒ 00:13:18.400 Neima Beizai: During collaboration with a cross-functional team, you notice a significant misalignment of priorities among team members regarding LLM feature development. Okay, for sure, I get this. How do you…
155 00:13:19.760 ⇒ 00:13:26.359 Neima Beizai: I’d basically have the team openly discuss why one feature
156 00:13:26.520 ⇒ 00:13:34.009 Neima Beizai: Should come ahead of the other, and help us get to an aligned roadmap.
157 00:13:34.200 ⇒ 00:13:40.849 Neima Beizai: If it’s not possible to, I’d suggest running the features
158 00:13:41.680 ⇒ 00:13:52.509 Neima Beizai: In parallel to see which one is going to actually drive the product forward, let’s just say.
159 00:13:53.660 ⇒ 00:14:03.209 Neima Beizai: Your attribute and evaluation framework for AI features seems outdated. Okay, for sure. How would you take… what steps would you take to assess its relevance, and how would you incorporate new trends in LLMs?
160 00:14:03.910 ⇒ 00:14:08.760 Neima Beizai: I’d figure out what the latest AI.
161 00:14:08.910 ⇒ 00:14:13.130 Neima Beizai: Frameworks are, and then compare against that.
162 00:14:13.860 ⇒ 00:14:20.759 Neima Beizai: Seeing where the gaps are… And then creating a plan to execute.
163 00:14:21.010 ⇒ 00:14:27.000 Neima Beizai: on, and fill those gaps in. Alrighty, dude. I did my best.
164 00:14:27.200 ⇒ 00:14:28.940 Luke Scorziell: Yeah, I know, it’s fine, we don’t have to…
165 00:14:30.160 ⇒ 00:14:32.750 Luke Scorziell: And what’s the, like, price points right now?
166 00:14:33.270 ⇒ 00:14:50.720 Neima Beizai: I got you, bro. It is, for a lot of volume, $500 per user a month. So let’s say you guys get, like, thousands of people coming into you, that would make sense. If not, dollar per completion. So let’s say you guys have, like, you know, the occasional 5-10 people who come through, dollar per completion, which I think would be very beneficial, personally.
167 00:14:51.060 ⇒ 00:14:56.350 Luke Scorziell: Like, like… If 5 to 10 people submit it, it’s 10.
168 00:14:56.600 ⇒ 00:15:12.859 Neima Beizai: Literally. Literally. Yeah. The reason why… yeah, the reason why I went there is because I thought about my dad, who was a small business owner. I was like, he would not be able to afford a $500 a month solution, and the fundamental goal behind this business is to increase access to opportunity, so I wasn’t gonna let money cause that.
169 00:15:13.200 ⇒ 00:15:13.670 Luke Scorziell: Yeah.
170 00:15:13.670 ⇒ 00:15:14.240 Neima Beizai: Fair enough.
171 00:15:14.720 ⇒ 00:15:17.760 Neima Beizai: So… No surprise, I’m not qualified.
172 00:15:17.970 ⇒ 00:15:21.799 Neima Beizai: So we click on Qualified Applicants. We start with qualified, but you can see everyone.
173 00:15:22.010 ⇒ 00:15:33.440 Neima Beizai: Right? So you have NEMA, email, candidate fit, we say low fit, role fit, growth potential, and skill gap, which I’ll explain in a minute. Duration, this is kind of what I was saying a little earlier, we track time on the back end to see how much someone actually spent.
174 00:15:33.600 ⇒ 00:15:39.219 Neima Beizai: You click on this report, we’ll give you an interview recommendation, we’ll give you candidate strengths we identified.
175 00:15:39.340 ⇒ 00:15:41.269 Neima Beizai: Candidate areas for improvement?
176 00:15:42.170 ⇒ 00:15:44.599 Neima Beizai: How the candidate will fit into the role long-term.
177 00:15:44.720 ⇒ 00:15:46.670 Neima Beizai: How to onboard the candidate.
178 00:15:46.930 ⇒ 00:16:03.759 Neima Beizai: Things to ask about during the interview process. So before you even start, we’ll, like, give you a read, and I’ll say once you interview them, these are things to ask about. So back to this candidate matching index. Role fit, the higher this percentage, the more likely the candidate is to do the job. Growth potential, the higher this percentage, the more likely the candidate is to be able to grow into the job.
179 00:16:03.890 ⇒ 00:16:13.579 Neima Beizai: Skill gap risk, the lower this is, the more likely the candidate is to have the skills for the job. Decision rationale is why the candidate was given the feedback they were given. And then we also show…
180 00:16:13.770 ⇒ 00:16:14.130 Luke Scorziell: So what the.
181 00:16:14.130 ⇒ 00:16:14.610 Neima Beizai: Listen.
182 00:16:14.610 ⇒ 00:16:16.299 Luke Scorziell: Fuel gap assessment.
183 00:16:16.640 ⇒ 00:16:20.450 Luke Scorziell: Sorry. 15% meaning that… You have 15%.
184 00:16:20.450 ⇒ 00:16:34.889 Neima Beizai: Yeah, all the way around. It means that I have some of the skills, but there’s still stuff to develop, right? So, like, I understand… for example, like, I’m an AI CEO, right? Like, I understand AI to an extent. I don’t understand LLMs like that, but I understand it to an extent.
185 00:16:34.980 ⇒ 00:16:35.969 Luke Scorziell: You know what I mean?
186 00:16:35.970 ⇒ 00:16:51.190 Neima Beizai: And, like, I coded the assessment layer that’s within this product, so, like, I understand that part, right? So it’s not like I don’t, it’s just, like, when you get into, like, the in-depth, like, how do you make an LLM, how do you do the neural layer processing or neural language processing, whatever it is, like, that’s when I’m like, alright, guys, you’re starting to lose me a little bit.
187 00:16:52.970 ⇒ 00:16:57.570 Neima Beizai: And then you can also see the assessment here, to kind of get a sense of what the candidate said.
188 00:16:57.780 ⇒ 00:17:00.839 Neima Beizai: You can click this button to download it, and then this button’s just a fiss.
189 00:17:01.970 ⇒ 00:17:04.629 Neima Beizai: That’s pretty much it, dude. Yeah, that’s how tech works.
190 00:17:05.069 ⇒ 00:17:10.799 Luke Scorziell: No, that’s dope. Yeah, well, I’ll… I’ll… I’ll definitely message,
191 00:17:11.819 ⇒ 00:17:14.579 Luke Scorziell: our founders and just see what, what,
192 00:17:15.079 ⇒ 00:17:18.709 Luke Scorziell: Like, the appetite is, and yeah, obviously now I have this video so I can show.
193 00:17:18.839 ⇒ 00:17:20.009 Luke Scorziell: Yeah.
194 00:17:20.719 ⇒ 00:17:27.889 Luke Scorziell: But, yeah, no, that looks great. And then, because I think, like, we had a job posting that went viral.
195 00:17:27.890 ⇒ 00:17:28.300 Neima Beizai: Oh, cool.
196 00:17:28.300 ⇒ 00:17:32.570 Luke Scorziell: For us, at least, like, a couple weeks down, we got, like, 50 or 60 people.
197 00:17:32.780 ⇒ 00:17:34.419 Luke Scorziell: It’s like…
198 00:17:34.420 ⇒ 00:17:34.989 Neima Beizai: right there.
199 00:17:34.990 ⇒ 00:17:38.479 Luke Scorziell: We don’t really have time, to go through all of them.
200 00:17:38.480 ⇒ 00:17:56.770 Neima Beizai: Yeah, dude, Luke, imagine, right? Imagine you send out 50 just messages to all of them, right? Here you go, here’s 50 assessments, you know, please take it if you’d like. If not, no worries, right? You don’t force them into it. And the ones who do opt-in, they’ll give you the best quality signal you can get on a candidate, ever. Because think about it this way.
201 00:17:56.850 ⇒ 00:18:01.600 Neima Beizai: If someone goes into an interview on a video, for example, Here’s a great one, right?
202 00:18:01.900 ⇒ 00:18:15.229 Neima Beizai: Hi, Luke. Thank you for taking the time to interview with me. Please tell me about yourself. That’s AI interviews for you. Even if AI interview was, like, us trying to talk like this, it’s still judging you based on the way you look, the way you act, the way you deliver things.
203 00:18:15.230 ⇒ 00:18:26.189 Neima Beizai: So, and it creates awkwardness, right? It’s just super awkward. So that, that, out the window. Resumes, with all due respect, ChatGPT and Cloud can write them. With this, a candidate goes in, super calm.
204 00:18:26.190 ⇒ 00:18:37.709 Neima Beizai: super collected, and like, oh, wow, like, this is fun. Like, dude, 9 out of 10 people would rather apply this way. And I’ve seen with my own eyes, dude, so many people get locked in as soon as they start answering the questions.
205 00:18:38.920 ⇒ 00:18:43.470 Luke Scorziell: Yeah, huh? No, that’s cool. I appreciate you showing up.
206 00:18:43.470 ⇒ 00:18:45.070 Neima Beizai: Yeah, of course, dude, my pleasure.
207 00:18:46.740 ⇒ 00:18:53.990 Luke Scorziell: Yeah, well, sweet. I don’t… yeah, I don’t have too much else, I guess, unless you want to connect me with other, other people in your space.
208 00:18:53.990 ⇒ 00:18:58.109 Neima Beizai: Yeah, dude, honestly, I will. What do you guys do? You guys do, like, automation tools?
209 00:18:58.110 ⇒ 00:19:11.210 Luke Scorziell: Yeah, we’re doing, like, AI and data implementation… implementation, so we work with, like, on the one… we have a lot of data engineers, so that’s kind of core to our value proposition, is that we’re not just, like, a bunch of people vibe coding.
210 00:19:11.740 ⇒ 00:19:13.040 Neima Beizai: The actual engineers.
211 00:19:13.040 ⇒ 00:19:24.329 Luke Scorziell: Yeah, we have actual engineers who structure the data layer to make sure that it, like, is readable and indexable by an LLM, and then we build out, like, knowledge bases for customers, we work with
212 00:19:24.500 ⇒ 00:19:31.290 Luke Scorziell: Like, we have a very large home services client, working, like, the… health,
213 00:19:31.400 ⇒ 00:19:33.910 Luke Scorziell: Yeah, we have a health services client.
214 00:19:33.910 ⇒ 00:19:41.919 Neima Beizai: So, look, if I’m understanding correctly, like, when you say knowledge base, for example, within my business, you build out, like, a bunch of data about candidates and jobs, let’s say.
215 00:19:42.350 ⇒ 00:19:48.719 Luke Scorziell: Yeah, like, okay, so, like, an example right now is we’re launching, like, an agency… or I just launched, like, an agency white paper, and so…
216 00:19:48.720 ⇒ 00:19:49.100 Neima Beizai: Okay.
217 00:19:49.100 ⇒ 00:19:52.300 Luke Scorziell: Basically, what we talk about is, like, for one of our agency clients.
218 00:19:52.380 ⇒ 00:20:11.210 Luke Scorziell: they have individual meetings with clients, need to do, like, weekly reporting on each of those clients, like, how ads are performing, need to do, like, create briefs, maybe multiple… so we can pull transcripts automatically from the calls, and then put them into a knowledge base that then allows, like.
219 00:20:11.350 ⇒ 00:20:14.640 Luke Scorziell: People at the agency to then query the,
220 00:20:14.640 ⇒ 00:20:16.680 Neima Beizai: Nice. He’s very nice.
221 00:20:16.680 ⇒ 00:20:20.799 Luke Scorziell: Yeah, to see, like, oh, like, what were the priorities for last week? Can you help me to organize?
222 00:20:20.800 ⇒ 00:20:21.320 Neima Beizai: I don’t know.
223 00:20:21.320 ⇒ 00:20:25.269 Luke Scorziell: set up, like, an automated Slack that goes out every week.
224 00:20:25.270 ⇒ 00:20:34.220 Neima Beizai: That’s cool. That’s actually really cool, I love that, because, you know, a lot of companies, what they struggle with is that central core. So if you guys create the central core that’s queryable, that’s amazing.
225 00:20:34.220 ⇒ 00:20:35.289 Luke Scorziell: Yeah, and then, so the.
226 00:20:35.290 ⇒ 00:20:37.970 Neima Beizai: That’s a really cool business, dude. That’s a really cool business.
227 00:20:37.970 ⇒ 00:20:50.430 Luke Scorziell: Yeah, we can pull the, like, data layer, like, working with, like, Snowflake and other, data warehouses to just make sure that the data’s all in the right place, and then we can build on top of that, too. So, yeah, anyone that’s saying, like.
228 00:20:51.450 ⇒ 00:20:58.759 Luke Scorziell: Probably… Yeah, I need to get the ad numbers specifically, but, like, agencies, people who are spending…
229 00:20:58.960 ⇒ 00:21:02.139 Luke Scorziell: I think it’s, like, 20,000 maybe a month or so.
230 00:21:02.140 ⇒ 00:21:02.599 Neima Beizai: I appreciate it.
231 00:21:02.600 ⇒ 00:21:05.850 Luke Scorziell: Attribution layer tracking on… on,
232 00:21:06.220 ⇒ 00:21:10.110 Luke Scorziell: Like, yeah, because it’s just with cookies and all the blockers and stuff, it’s like…
233 00:21:10.110 ⇒ 00:21:11.390 Neima Beizai: Yeah, yeah, seriously.
234 00:21:11.390 ⇒ 00:21:17.310 Luke Scorziell: accuracy that you get. So, yeah, I don’t know if that sparks any, dude.
235 00:21:17.310 ⇒ 00:21:24.610 Neima Beizai: I talk to a zillion people a day, so I got you. Anyone who needs help with data structuring, I’ll send your way.
236 00:21:24.960 ⇒ 00:21:36.080 Luke Scorziell: Yeah, no, that’d be… that’d be dope. So, yeah, and then we’ll be… like, I’m gonna be posting more regularly, too, on my LinkedIn, so I’ll kind of have some more insights into what we’re doing.
237 00:21:36.080 ⇒ 00:21:44.000 Neima Beizai: Dude, I’ll interact, no problem, and then I’ll chase you down, I’ll follow up with you in a few days to see if y’all want to use it. And honestly, bro, I would love to help you guys out with your searches. I’d love nothing more, yeah?
238 00:21:44.000 ⇒ 00:21:47.200 Luke Scorziell: Sweet. Yeah, yeah. Well, I’ll pass along, so…
239 00:21:47.200 ⇒ 00:21:48.740 Neima Beizai: Cool. Thanks, man, appreciate it.
240 00:21:48.740 ⇒ 00:21:49.859 Luke Scorziell: Yeah, good to tell you.
241 00:21:49.860 ⇒ 00:21:51.260 Neima Beizai: Alright, likewise, we’ll talk soon. Bye.
242 00:21:51.260 ⇒ 00:21:51.830 Luke Scorziell: Yep.