1 00:00:00,080 --> 00:00:01,600 Speaker 1: I think the first thing is first, you can't you 2 00:00:01,639 --> 00:00:03,600 Speaker 1: can't get around this. You have to be good at 3 00:00:03,600 --> 00:00:07,880 Speaker 1: what you do, Like you have to invest in learning 4 00:00:07,960 --> 00:00:11,160 Speaker 1: what you're really good at and just doing that to 5 00:00:11,280 --> 00:00:13,720 Speaker 1: the best of your ability. Like that's the one thing 6 00:00:13,800 --> 00:00:16,079 Speaker 1: that that's the one impression that you're gonna make with 7 00:00:16,120 --> 00:00:18,720 Speaker 1: most people, They're gonna remember, did you say what you're 8 00:00:18,760 --> 00:00:20,960 Speaker 1: gonna do? You ran that of event and it went 9 00:00:21,000 --> 00:00:21,600 Speaker 1: really well. 10 00:00:22,040 --> 00:00:23,520 Speaker 2: You were, you know, on time. 11 00:00:23,680 --> 00:00:26,680 Speaker 1: You know, you communicate, Like just be a good whatever 12 00:00:26,680 --> 00:00:27,720 Speaker 1: you want to be in the world, Like, just be 13 00:00:27,800 --> 00:00:28,280 Speaker 1: good at that. 14 00:00:30,720 --> 00:00:35,160 Speaker 3: I'm will Lucas missus Black Tech, Green Money. I'm gonna 15 00:00:35,159 --> 00:00:37,000 Speaker 3: introduce you to some of the biggest names, some of 16 00:00:37,000 --> 00:00:39,160 Speaker 3: the brightest minds and brilliant ideas. 17 00:00:39,280 --> 00:00:39,960 Speaker 2: If you're black in. 18 00:00:40,040 --> 00:00:43,440 Speaker 3: Building, are simply using texta security you back, this podcast 19 00:00:43,479 --> 00:00:43,879 Speaker 3: is for you. 20 00:00:49,360 --> 00:00:51,920 Speaker 4: Jeroni Petty is founder and CEO at color. 21 00:00:51,680 --> 00:00:55,080 Speaker 3: Stack, the nonprofit Colici organization that helps black lots of 22 00:00:55,160 --> 00:00:56,800 Speaker 3: next computer science students. 23 00:00:56,520 --> 00:00:57,920 Speaker 4: Get degreed and hired. 24 00:00:58,520 --> 00:01:01,120 Speaker 3: When he was at Cornell, he worked as an intern 25 00:01:01,160 --> 00:01:03,640 Speaker 3: at Google and later turned him down for a full 26 00:01:03,680 --> 00:01:06,280 Speaker 3: time gig to start his own entrepreneurial journey. 27 00:01:07,200 --> 00:01:08,280 Speaker 4: We've had so many. 28 00:01:08,040 --> 00:01:11,440 Speaker 3: Conversations nationwide about the pipeline for black talent and tech. 29 00:01:12,000 --> 00:01:14,240 Speaker 4: I wanted to get an idea of its current state. 30 00:01:15,160 --> 00:01:18,000 Speaker 4: To Aran, who works on this issue every day, provides 31 00:01:18,120 --> 00:01:18,640 Speaker 4: enough date. 32 00:01:18,760 --> 00:01:21,160 Speaker 2: When you look at the data, it's about thirty percent. 33 00:01:21,800 --> 00:01:24,319 Speaker 1: You know, back in Latin next, computer science students or 34 00:01:24,360 --> 00:01:27,679 Speaker 1: people make up thirty percent of the population, twenty percent 35 00:01:27,680 --> 00:01:30,040 Speaker 1: of CS grads, and about. 36 00:01:29,760 --> 00:01:31,520 Speaker 2: Ten percent of the industry. 37 00:01:31,840 --> 00:01:34,280 Speaker 1: So there's drop offs at each level where you could 38 00:01:34,360 --> 00:01:37,760 Speaker 1: say not enough students are graduating with CS degrees to 39 00:01:37,760 --> 00:01:40,440 Speaker 1: begin with, but also from the ones that are, they're 40 00:01:40,440 --> 00:01:43,120 Speaker 1: not getting jobs in software right, they're maybe going into 41 00:01:43,160 --> 00:01:45,840 Speaker 1: it or becoming a teacher or doing something that they 42 00:01:45,880 --> 00:01:47,200 Speaker 1: weren't intending to do. 43 00:01:47,360 --> 00:01:49,040 Speaker 2: So we're trying to solve. 44 00:01:48,840 --> 00:01:54,320 Speaker 1: This like multi layered problem of like access to jobs, placement, retention, 45 00:01:54,560 --> 00:01:57,440 Speaker 1: and then even attraction to bring that twenty percent to 46 00:01:57,520 --> 00:02:00,160 Speaker 1: thirty percent right at the onset. 47 00:02:00,440 --> 00:02:04,600 Speaker 3: Do you see enough black students interested in computer science? 48 00:02:06,280 --> 00:02:08,760 Speaker 1: So I studied CS myself, right, So I was a 49 00:02:08,800 --> 00:02:12,280 Speaker 1: csgrad and so when I was on campus, the whole 50 00:02:12,320 --> 00:02:15,399 Speaker 1: reason I started doing this work was because I did 51 00:02:15,440 --> 00:02:17,880 Speaker 1: see that I did see the interest but what you 52 00:02:17,919 --> 00:02:21,360 Speaker 1: would find is that even in that intro course. At 53 00:02:21,360 --> 00:02:23,600 Speaker 1: a lot of these universities, the intro course is in 54 00:02:23,680 --> 00:02:26,400 Speaker 1: the intro course, you know, they kind of gotten so 55 00:02:26,720 --> 00:02:29,519 Speaker 1: used to these people that come in and have been 56 00:02:29,600 --> 00:02:32,720 Speaker 1: learning how to study, how to code and program from 57 00:02:32,760 --> 00:02:35,600 Speaker 1: when they were in middle school. So the professors, I 58 00:02:35,600 --> 00:02:38,880 Speaker 1: think have adapted for the wrong reasons and have now 59 00:02:39,000 --> 00:02:42,640 Speaker 1: expected so much prior knowledge where black students, Brown students 60 00:02:42,680 --> 00:02:46,520 Speaker 1: are going into these intro courses and they feel behind, 61 00:02:46,960 --> 00:02:50,320 Speaker 1: and once they get a backgrade on that first test 62 00:02:50,440 --> 00:02:52,960 Speaker 1: or project, they're dropping the class, They're dropping the major. 63 00:02:53,600 --> 00:02:53,799 Speaker 2: Yeah. 64 00:02:53,840 --> 00:02:56,080 Speaker 3: So I was reading something a different interview you were 65 00:02:56,080 --> 00:02:58,120 Speaker 3: doing it. You were talking about your personal mission that 66 00:02:58,160 --> 00:03:01,919 Speaker 3: you found many of your peers owner parts in these classes, 67 00:03:02,440 --> 00:03:07,200 Speaker 3: weren't doing well in these classes. And you talked about 68 00:03:07,240 --> 00:03:11,000 Speaker 3: this as pervasive and why is that pervasive? Like many 69 00:03:11,080 --> 00:03:13,840 Speaker 3: would say, we just aren't as talented or you know, 70 00:03:13,880 --> 00:03:16,040 Speaker 3: we don't have the proclivity for math and science. Well, 71 00:03:16,040 --> 00:03:18,280 Speaker 3: in your research and in your work, what have you 72 00:03:18,360 --> 00:03:21,680 Speaker 3: found to be the reasons why we are not ready 73 00:03:21,720 --> 00:03:23,640 Speaker 3: for these classes in so many respects? 74 00:03:24,200 --> 00:03:26,520 Speaker 1: Yeah, I think the first thing is definitely, you know 75 00:03:26,520 --> 00:03:28,560 Speaker 1: what I just mentioned about prior knowledge, like if you 76 00:03:28,560 --> 00:03:30,880 Speaker 1: didn't go to if you didn't go to that private school, 77 00:03:31,080 --> 00:03:35,160 Speaker 1: right that had CS one on one as a freshman, Right. 78 00:03:35,280 --> 00:03:37,560 Speaker 1: I think public education is just catching up to c 79 00:03:37,720 --> 00:03:41,600 Speaker 1: US education and baking that into the curriculum for high schools. 80 00:03:41,600 --> 00:03:43,920 Speaker 1: But if you either didn't if you didn't go to 81 00:03:43,960 --> 00:03:47,240 Speaker 1: a school that had the coursework, or you had a 82 00:03:47,240 --> 00:03:50,040 Speaker 1: family friend that just was able to expose you to 83 00:03:50,040 --> 00:03:52,680 Speaker 1: that at a young age, you are coming in at 84 00:03:52,720 --> 00:03:57,120 Speaker 1: a college level feeling so behind. So there's that there's 85 00:03:57,160 --> 00:03:59,400 Speaker 1: that mental kind of barrier where you just are not 86 00:03:59,440 --> 00:04:02,400 Speaker 1: as confident when you're going into your first intro course 87 00:04:02,560 --> 00:04:05,400 Speaker 1: and everybody else seems to know everything that's already like 88 00:04:05,440 --> 00:04:08,200 Speaker 1: from day one, you're already discouraged, right. 89 00:04:08,600 --> 00:04:09,360 Speaker 2: And then I think some. 90 00:04:09,400 --> 00:04:14,280 Speaker 1: Other areas within on the campus where students are kind 91 00:04:14,320 --> 00:04:17,880 Speaker 1: of selling themselves short is, for example, office hours. I 92 00:04:17,920 --> 00:04:21,000 Speaker 1: was a TA for a lot of the common CS 93 00:04:21,000 --> 00:04:25,960 Speaker 1: courses at qunell and for whatever reason, you know, a 94 00:04:25,960 --> 00:04:29,159 Speaker 1: lot of students wouldn't go to office hours, right. Maybe 95 00:04:29,200 --> 00:04:31,640 Speaker 1: it's because of the same issue they're facing in classes 96 00:04:31,640 --> 00:04:33,400 Speaker 1: where they feel like if they go to office hours, 97 00:04:33,560 --> 00:04:36,839 Speaker 1: they're just going to be you know, reinformed that they're 98 00:04:36,880 --> 00:04:40,160 Speaker 1: like behind or feel like they're dumb for asking questions. 99 00:04:41,080 --> 00:04:43,880 Speaker 1: But it's a lot of those small things. We're privileged 100 00:04:44,000 --> 00:04:47,479 Speaker 1: kind of in network. Students already know that like office hours, 101 00:04:47,640 --> 00:04:50,120 Speaker 1: office hours are there, I can go talk to the professor, 102 00:04:50,160 --> 00:04:51,320 Speaker 1: I can use these resources. 103 00:04:51,600 --> 00:04:53,240 Speaker 2: But when you feel so behind. 104 00:04:52,880 --> 00:04:55,920 Speaker 1: And when you're not kind of in these environments already, 105 00:04:56,240 --> 00:04:58,200 Speaker 1: you just don't feel like you can participate in the 106 00:04:58,240 --> 00:04:58,680 Speaker 1: same way. 107 00:05:01,040 --> 00:05:04,039 Speaker 3: With that response, then, is waiting until we get to 108 00:05:04,120 --> 00:05:07,400 Speaker 3: college too late to make sure that we're ready for 109 00:05:07,600 --> 00:05:10,760 Speaker 3: you know, actually getting internships to be able to get jobs. 110 00:05:11,640 --> 00:05:12,359 Speaker 2: I don't believe so. 111 00:05:12,560 --> 00:05:14,120 Speaker 1: I mean I think, you know, shout out to all 112 00:05:14,160 --> 00:05:17,440 Speaker 1: the orgs, Codination America on Tech that are doing that 113 00:05:17,480 --> 00:05:19,600 Speaker 1: are doing work at the high school level Black Girls Code. 114 00:05:19,720 --> 00:05:22,320 Speaker 1: I think it does. It is helpful to start earlier 115 00:05:22,360 --> 00:05:24,440 Speaker 1: and kind of get that exposure. But I don't think 116 00:05:24,480 --> 00:05:26,560 Speaker 1: it's too late. I think within when you're on a 117 00:05:26,600 --> 00:05:31,279 Speaker 1: campus that is already about discovery of oneself and really 118 00:05:31,320 --> 00:05:34,640 Speaker 1: just learning and expanding your horizons. I do think there 119 00:05:34,680 --> 00:05:39,000 Speaker 1: is hope where there are students who are still primed 120 00:05:39,200 --> 00:05:42,520 Speaker 1: for pushing their their limits and kind of expanding their 121 00:05:42,560 --> 00:05:47,400 Speaker 1: horizons and trying something new. But it does take intentional 122 00:05:47,440 --> 00:05:50,960 Speaker 1: effort at the earliest stage, that first fresh that freshman year, 123 00:05:50,960 --> 00:05:53,799 Speaker 1: because once you the way the curriculum and the major 124 00:05:53,880 --> 00:05:55,600 Speaker 1: system is set up at a lot of these schools 125 00:05:56,279 --> 00:05:58,400 Speaker 1: is you know, if you try to change your major 126 00:05:58,480 --> 00:06:02,560 Speaker 1: once you're a sophomore juniors, near impossible, right, And so 127 00:06:02,600 --> 00:06:04,760 Speaker 1: you really have to target and support those students at 128 00:06:04,760 --> 00:06:07,120 Speaker 1: the freshman level. And I'll even tell you this from 129 00:06:07,120 --> 00:06:09,240 Speaker 1: when I was at Cornell, when we were doing a 130 00:06:09,279 --> 00:06:14,960 Speaker 1: lot of work with underclassmen, we actually started doing events 131 00:06:15,120 --> 00:06:19,440 Speaker 1: that basically made other people who weren't cus feel jealous, right, 132 00:06:19,600 --> 00:06:21,560 Speaker 1: like oh, this is so cool, Like you know, all 133 00:06:21,560 --> 00:06:23,159 Speaker 1: my friends are doing this thing and they know how 134 00:06:23,240 --> 00:06:25,080 Speaker 1: to they know how Siri works, and they know how 135 00:06:25,080 --> 00:06:27,880 Speaker 1: the algorithms of YouTube and all these different social media work. 136 00:06:27,920 --> 00:06:31,120 Speaker 1: And they were like, Okay, I'll do a CS minor, right, 137 00:06:31,160 --> 00:06:32,960 Speaker 1: And that's happening at the college. All these are students 138 00:06:33,000 --> 00:06:36,239 Speaker 1: that were pre med, right, but now they're adding a 139 00:06:36,240 --> 00:06:37,000 Speaker 1: a CS minor. 140 00:06:37,040 --> 00:06:38,240 Speaker 2: So I don't think it's too late at all. 141 00:06:39,279 --> 00:06:42,200 Speaker 3: So as an entrepreneur, when you're going through your you 142 00:06:42,200 --> 00:06:44,560 Speaker 3: know idating process of the company. You're going to start, 143 00:06:44,560 --> 00:06:47,360 Speaker 3: the organization you're going to start. What was the decision 144 00:06:47,360 --> 00:06:49,279 Speaker 3: making process like for you when you said, you know, 145 00:06:49,360 --> 00:06:52,400 Speaker 3: I'm going to target those college students instead of building 146 00:06:52,440 --> 00:06:55,680 Speaker 3: an organization like a Black Girl's Code that actually gets 147 00:06:55,760 --> 00:06:58,280 Speaker 3: them younger, earlier in the process, so that they by 148 00:06:58,320 --> 00:07:00,560 Speaker 3: the time they get to college, they're more prepared. 149 00:07:01,839 --> 00:07:03,440 Speaker 1: That's a good question. I think this is the lesson 150 00:07:03,440 --> 00:07:05,680 Speaker 1: that I have for that I learned from myself but 151 00:07:05,920 --> 00:07:09,640 Speaker 1: also try to share with other entrepreneurs, is that, you know, 152 00:07:09,680 --> 00:07:13,160 Speaker 1: you don't want to think too much about what you're building. 153 00:07:13,240 --> 00:07:16,640 Speaker 1: I think incremental, like solving the problem in front of 154 00:07:16,640 --> 00:07:21,280 Speaker 1: you incrementally, you kind of just stumble upon a business, right. 155 00:07:21,280 --> 00:07:24,600 Speaker 1: That's what happened for me my freshman year, I was 156 00:07:25,480 --> 00:07:27,720 Speaker 1: I got an internship at two Sigma, had a really 157 00:07:27,720 --> 00:07:30,880 Speaker 1: great opportunity there. My sophomore year, I came back to 158 00:07:30,960 --> 00:07:34,400 Speaker 1: that internship feeling very discouraged because there weren't other you know, 159 00:07:34,480 --> 00:07:37,960 Speaker 1: black interns there, or I noticed that my friends on 160 00:07:38,000 --> 00:07:40,400 Speaker 1: campus didn't get internships that summer, or weren't doing well 161 00:07:40,400 --> 00:07:43,000 Speaker 1: in their classes or were considering dropping And so I 162 00:07:43,000 --> 00:07:45,160 Speaker 1: said Okay, how can I just solve that problem? How 163 00:07:45,160 --> 00:07:46,720 Speaker 1: can I just get my friends to come with me 164 00:07:47,080 --> 00:07:49,640 Speaker 1: on all these different opportunities you know that I have. 165 00:07:50,120 --> 00:07:51,760 Speaker 1: And so that was the problem that I solved, you know, 166 00:07:51,800 --> 00:07:54,320 Speaker 1: in twenty seventeen, and then twenty eighteen was I no 167 00:07:54,400 --> 00:07:57,160 Speaker 1: longer have enough time in the day to mentor all 168 00:07:57,160 --> 00:07:59,840 Speaker 1: these students, So how can I scale that by creating 169 00:08:00,080 --> 00:08:02,160 Speaker 1: a community of peer to peer support? Okay, that was 170 00:08:02,600 --> 00:08:04,600 Speaker 1: the problem I solved in twenty eighteen and twenty nineteen 171 00:08:04,640 --> 00:08:07,000 Speaker 1: by building the club, And then from twenty nineteen to 172 00:08:07,040 --> 00:08:09,800 Speaker 1: twenty twenty, it's like, okay, well, how can I provide 173 00:08:09,800 --> 00:08:12,160 Speaker 1: this value to more students on other campuses? 174 00:08:12,680 --> 00:08:12,880 Speaker 2: Right? 175 00:08:12,960 --> 00:08:16,559 Speaker 1: And so it was just me incrementally solving the problem 176 00:08:16,640 --> 00:08:18,720 Speaker 1: that was right in front of me. And I think 177 00:08:18,720 --> 00:08:21,000 Speaker 1: that's how everybody should approach, you know, you know, starting 178 00:08:21,000 --> 00:08:23,400 Speaker 1: a company, right, You don't have to build a Google tomorrow. 179 00:08:23,760 --> 00:08:26,000 Speaker 1: It's just what's the smallest version of that problem that 180 00:08:26,040 --> 00:08:26,800 Speaker 1: you can solve today. 181 00:08:27,560 --> 00:08:30,880 Speaker 3: And so to the idea that you know, not everybody specifically, 182 00:08:30,920 --> 00:08:33,240 Speaker 3: I'm talking about black people and brown people who come 183 00:08:33,240 --> 00:08:36,040 Speaker 3: into college aren't ready for the math courses and the 184 00:08:36,080 --> 00:08:39,400 Speaker 3: science courses, but what are some other barriers that keep 185 00:08:39,440 --> 00:08:42,679 Speaker 3: them from graduating? And then you know, then all went 186 00:08:42,720 --> 00:08:45,840 Speaker 3: in the opportunity to go get internships and jobs right 187 00:08:45,880 --> 00:08:46,480 Speaker 3: out of school. 188 00:08:47,880 --> 00:08:50,600 Speaker 1: Yeah, I think there's there's so many there's a whole 189 00:08:50,600 --> 00:08:53,120 Speaker 1: pocket episode on those barriers. But I think a couple 190 00:08:53,200 --> 00:08:57,160 Speaker 1: that I know, I knew already as a student myself, 191 00:08:57,200 --> 00:09:00,680 Speaker 1: but then I learned from building color stack. One it's 192 00:09:00,679 --> 00:09:05,679 Speaker 1: just financial, right, Like some students just you know, can't 193 00:09:05,960 --> 00:09:09,360 Speaker 1: well drops, you know, drop out of school or changed 194 00:09:09,480 --> 00:09:12,080 Speaker 1: from a four year to a two year or just 195 00:09:12,160 --> 00:09:17,000 Speaker 1: be you know, indefinitely on leave of absence just because 196 00:09:17,040 --> 00:09:17,600 Speaker 1: of money. 197 00:09:17,720 --> 00:09:17,920 Speaker 2: Right. 198 00:09:17,960 --> 00:09:20,520 Speaker 1: So I think there's there's definitely a conversation around the 199 00:09:20,640 --> 00:09:25,960 Speaker 1: afford affordability of school, especially these private institutions versus state schools, 200 00:09:26,240 --> 00:09:30,840 Speaker 1: where sometimes just money that prevents someone from continuing. The 201 00:09:30,880 --> 00:09:35,920 Speaker 1: second thing I think about a lot is no two 202 00:09:36,000 --> 00:09:38,800 Speaker 1: CS degrees are made equal, right, you know you would 203 00:09:38,880 --> 00:09:43,439 Speaker 1: think that, yes, from a Cornell or you know, a 204 00:09:43,520 --> 00:09:46,920 Speaker 1: Kannessas State or a Stony Book university, like they all 205 00:09:46,960 --> 00:09:48,959 Speaker 1: offer computer science. So no matter which one I pick, 206 00:09:49,240 --> 00:09:51,559 Speaker 1: I should be good. The truth of the matter is 207 00:09:51,840 --> 00:09:56,240 Speaker 1: that academia has not stayed on par with industry, and 208 00:09:56,280 --> 00:09:58,080 Speaker 1: so a lot of what it takes to become a 209 00:09:58,120 --> 00:10:00,959 Speaker 1: software engineer in industry is taught out side of the classroom. 210 00:10:01,360 --> 00:10:03,400 Speaker 1: And so there are two kind of sub reasons why 211 00:10:04,360 --> 00:10:08,360 Speaker 1: you know, students aren't able to keep up. One is 212 00:10:08,520 --> 00:10:11,760 Speaker 1: if you don't have the time right outside of a 213 00:10:11,760 --> 00:10:14,720 Speaker 1: class where you're a commuter student or you're working another 214 00:10:14,840 --> 00:10:17,640 Speaker 1: job to pay for school, and you think that you know, 215 00:10:17,679 --> 00:10:19,280 Speaker 1: you can just do your classes and do homework and 216 00:10:19,320 --> 00:10:22,360 Speaker 1: be done. You know you're going to be sol when 217 00:10:22,960 --> 00:10:25,080 Speaker 1: you find out that in order to really get that job, 218 00:10:25,120 --> 00:10:27,120 Speaker 1: you actually have to do your homework, get a good grade, 219 00:10:27,200 --> 00:10:29,520 Speaker 1: but then also learn how to become a software engineer. 220 00:10:29,960 --> 00:10:30,839 Speaker 2: And you know, when you're in. 221 00:10:30,760 --> 00:10:33,360 Speaker 1: A privileged position of just being on campus and just 222 00:10:33,360 --> 00:10:35,960 Speaker 1: focusing on school and all that's taken care of, you 223 00:10:36,080 --> 00:10:39,040 Speaker 1: have that time, but many of these students don't. And 224 00:10:39,040 --> 00:10:42,080 Speaker 1: then then on the other hand, you also don't have 225 00:10:42,280 --> 00:10:47,199 Speaker 1: the curriculum that is tied and kind of pegged two 226 00:10:47,440 --> 00:10:51,120 Speaker 1: industry standards, where a school like an MIT or Carnegie 227 00:10:51,160 --> 00:10:55,240 Speaker 1: melon they have partnerships with these companies to build curriculums. 228 00:10:55,200 --> 00:10:56,080 Speaker 2: That's relevant. 229 00:10:56,360 --> 00:10:58,560 Speaker 1: But if you're going to a local school, a small 230 00:10:58,679 --> 00:11:01,000 Speaker 1: CS department, you just might be out of date. 231 00:11:01,640 --> 00:11:03,480 Speaker 3: And so it's interesting to say that because I've had 232 00:11:03,520 --> 00:11:08,280 Speaker 3: these conversations about you know, industry and university is not 233 00:11:08,320 --> 00:11:10,160 Speaker 3: being able to stay on par or college is not 234 00:11:10,160 --> 00:11:12,280 Speaker 3: being able to stay on par with what they're educating, 235 00:11:12,320 --> 00:11:15,280 Speaker 3: and so often it comes back to hiring the professors 236 00:11:15,320 --> 00:11:17,520 Speaker 3: who can teach it because they those professors can go 237 00:11:17,559 --> 00:11:20,320 Speaker 3: to the industry and make more money than they would, you know, 238 00:11:20,840 --> 00:11:23,240 Speaker 3: working in a university or a college. And so I 239 00:11:23,280 --> 00:11:26,840 Speaker 3: wonder what your idea is on how much self directed 240 00:11:27,000 --> 00:11:29,160 Speaker 3: education we need to do, even if you're in school 241 00:11:29,200 --> 00:11:32,360 Speaker 3: for your CS degree, how much of this outside of 242 00:11:32,400 --> 00:11:34,480 Speaker 3: that to your you did talk a little bit about this, 243 00:11:34,559 --> 00:11:36,040 Speaker 3: and you know, you got a job and you got 244 00:11:36,080 --> 00:11:38,400 Speaker 3: other things to pay for the pay for that education. 245 00:11:39,080 --> 00:11:42,400 Speaker 3: How much of that self directed effort is required in 246 00:11:42,520 --> 00:11:46,160 Speaker 3: order to get the look from a big company or 247 00:11:46,160 --> 00:11:48,000 Speaker 3: a startup that you may be interested in. 248 00:11:49,400 --> 00:11:52,120 Speaker 1: Yeah, I think I think for the most part, when 249 00:11:52,120 --> 00:11:55,200 Speaker 1: you look at a big like, the bigger the company, 250 00:11:55,600 --> 00:11:59,080 Speaker 1: the more resources they have for learning and development. So 251 00:11:59,679 --> 00:12:02,160 Speaker 1: as as long as you can prove that you can code, 252 00:12:02,280 --> 00:12:05,160 Speaker 1: just generally a lot of the bigger companies with more 253 00:12:05,200 --> 00:12:08,400 Speaker 1: infrastructure for learning and development. Like, if you do well 254 00:12:08,400 --> 00:12:11,200 Speaker 1: in your classes and you can demonstrate a basic knowledge 255 00:12:11,200 --> 00:12:13,640 Speaker 1: of coding, you'll be able to kind of secure at 256 00:12:13,720 --> 00:12:16,880 Speaker 1: least beyond their radar and be competitive for roles at 257 00:12:16,880 --> 00:12:20,320 Speaker 1: bigger companies. If you're talking about mid sized company and 258 00:12:20,440 --> 00:12:23,120 Speaker 1: especially for a startup, they're going to expect you to 259 00:12:23,160 --> 00:12:25,520 Speaker 1: come and hit the ground running. So it's going to 260 00:12:25,640 --> 00:12:30,320 Speaker 1: require you to subscribe to certain newsletters so you know 261 00:12:30,360 --> 00:12:32,920 Speaker 1: what the newest tech tech is, Like JavaScript has a 262 00:12:32,920 --> 00:12:35,000 Speaker 1: new framework like every year, you need to know what 263 00:12:35,040 --> 00:12:37,839 Speaker 1: those are. Right, You're going to have to know how 264 00:12:37,880 --> 00:12:40,480 Speaker 1: to build an iOS app if you want to work 265 00:12:40,480 --> 00:12:43,120 Speaker 1: on a team that their only product is a mobile app. 266 00:12:43,280 --> 00:12:43,439 Speaker 2: Right. 267 00:12:43,480 --> 00:12:46,880 Speaker 1: That's that's a perfect example of something that, like across 268 00:12:46,880 --> 00:12:50,000 Speaker 1: the board, is rarely taught in institutions. Right, Like you 269 00:12:50,080 --> 00:12:52,040 Speaker 1: might learn how to code in Python, you might learn 270 00:12:52,040 --> 00:12:54,800 Speaker 1: about databases, you might learn about machine learning, but even 271 00:12:54,840 --> 00:12:58,520 Speaker 1: something like iOS development isn't a thing that's typically taught 272 00:12:58,520 --> 00:13:04,000 Speaker 1: in schools because the professors do research and there isn't 273 00:13:04,040 --> 00:13:07,920 Speaker 1: much much research done on like mobile app development. It's 274 00:13:08,040 --> 00:13:11,640 Speaker 1: usually like database efficiency or machine learning or like programming 275 00:13:11,679 --> 00:13:16,960 Speaker 1: languages compilers, so things like iOS development, which is ubiquitous 276 00:13:17,000 --> 00:13:19,200 Speaker 1: in terms of its impact. Everybody uses their phone and 277 00:13:19,240 --> 00:13:22,480 Speaker 1: has apps. You're actually not even learning that on average 278 00:13:22,520 --> 00:13:23,920 Speaker 1: if you get a CS to be from any school 279 00:13:23,920 --> 00:13:25,840 Speaker 1: in the country, so you have to go out and 280 00:13:26,040 --> 00:13:28,400 Speaker 1: take a U to ME course or go on YouTube 281 00:13:28,480 --> 00:13:29,320 Speaker 1: or get a book. 282 00:13:29,520 --> 00:13:30,800 Speaker 2: You just have to know. 283 00:13:30,760 --> 00:13:34,000 Speaker 3: All that and so some other things that we talked about, 284 00:13:34,040 --> 00:13:37,440 Speaker 3: you know, with that are prohibitive for students to get 285 00:13:37,480 --> 00:13:40,720 Speaker 3: the degree and actually actually graduating. What are some of 286 00:13:40,720 --> 00:13:42,840 Speaker 3: those things that actually keep you from getting a job. 287 00:13:42,920 --> 00:13:45,840 Speaker 3: So let's say you've graduated, You've you went to a 288 00:13:45,920 --> 00:13:49,079 Speaker 3: mid level university, mid level college. You didn't go to Cornell. 289 00:13:49,559 --> 00:13:52,440 Speaker 3: Not everybody's as smart as you run. But let's say 290 00:13:52,720 --> 00:13:54,640 Speaker 3: you know, I went to a mid level school, I 291 00:13:54,640 --> 00:13:57,200 Speaker 3: got my degree, and I still can't get a job 292 00:13:57,240 --> 00:13:58,960 Speaker 3: at the company that I'm interested in. 293 00:13:59,000 --> 00:14:02,520 Speaker 4: What are some of those reasons why, other than racism? 294 00:14:02,920 --> 00:14:05,720 Speaker 1: Other than that, Yeah, yeah, let's start like that's already 295 00:14:05,760 --> 00:14:10,280 Speaker 1: that's the three requisite that's always there. Yeah, I think 296 00:14:10,360 --> 00:14:15,280 Speaker 1: I think you know, there's there's some there's some challenges 297 00:14:15,360 --> 00:14:19,080 Speaker 1: definitely when it comes to like exposure to companies. So, 298 00:14:19,200 --> 00:14:24,600 Speaker 1: for example, you know at certain schools, like at a 299 00:14:24,680 --> 00:14:27,640 Speaker 1: top level school, you're going to have companies flying out 300 00:14:27,720 --> 00:14:30,800 Speaker 1: to be at that career. Fair right, every company that 301 00:14:30,880 --> 00:14:33,360 Speaker 1: you know will go out and make sure they're at Cornell, 302 00:14:33,400 --> 00:14:36,200 Speaker 1: at MIT, whatever to get in front. 303 00:14:36,000 --> 00:14:36,680 Speaker 2: Of those students. 304 00:14:37,240 --> 00:14:39,680 Speaker 1: What I see at the mid level schools is that 305 00:14:39,880 --> 00:14:43,440 Speaker 1: it's usually like local companies, and if you're at a 306 00:14:43,480 --> 00:14:47,880 Speaker 1: small school in Michigan, there's no local tech company, right, 307 00:14:48,400 --> 00:14:53,480 Speaker 1: so your your access and your exposure to employment is 308 00:14:54,120 --> 00:14:59,160 Speaker 1: usually at best it right. At best you're learning about 309 00:14:59,160 --> 00:15:02,480 Speaker 1: some org that has a back office IT team that 310 00:15:02,560 --> 00:15:06,640 Speaker 1: you might be able to work for. You don't even know, 311 00:15:06,760 --> 00:15:09,920 Speaker 1: you aren't even talking to her. On the radar of 312 00:15:09,960 --> 00:15:13,760 Speaker 1: like pure tech pure software companies that are hiring software engineers, 313 00:15:13,880 --> 00:15:16,480 Speaker 1: which is what you study to be, right, So it's 314 00:15:16,480 --> 00:15:18,880 Speaker 1: not like, let's not confuse that you study to be that, 315 00:15:19,280 --> 00:15:22,320 Speaker 1: but the roles and the opportunities that are available to 316 00:15:22,360 --> 00:15:26,240 Speaker 1: you are more aligned for IT and other things that 317 00:15:26,280 --> 00:15:28,840 Speaker 1: are not coding. So that's one of the ways that 318 00:15:28,880 --> 00:15:31,400 Speaker 1: CLUTSA obviously bridges the gap. So no matter what schools 319 00:15:31,400 --> 00:15:33,240 Speaker 1: are going to your career for if you're a small 320 00:15:33,240 --> 00:15:35,080 Speaker 1: school in Michigan, Illinois. 321 00:15:35,120 --> 00:15:35,400 Speaker 2: Whatever. 322 00:15:36,080 --> 00:15:38,360 Speaker 1: I mean, we partner with fifty top tech tech companies 323 00:15:38,360 --> 00:15:40,560 Speaker 1: today where you can immediately get on their radar. But 324 00:15:40,600 --> 00:15:43,280 Speaker 1: that's like one of the bigger, bigger reasons. 325 00:15:43,000 --> 00:15:43,200 Speaker 2: You know. 326 00:15:43,320 --> 00:15:45,920 Speaker 3: I'm glad you bring up cover Stack in the way 327 00:15:45,920 --> 00:15:47,600 Speaker 3: that you have because I'm interested in you know, cover 328 00:15:47,640 --> 00:15:51,280 Speaker 3: Stack is a nonprofit Number one. What a lot of 329 00:15:51,320 --> 00:15:55,200 Speaker 3: people will ask, like, how do you make money doing this? 330 00:15:55,400 --> 00:15:57,840 Speaker 3: You know, because I mean, is this like purely altruistic 331 00:15:58,000 --> 00:15:59,960 Speaker 3: or are you attempting to like be like I want 332 00:16:00,120 --> 00:16:02,080 Speaker 3: build a billion dollar organization hot? 333 00:16:02,200 --> 00:16:04,040 Speaker 4: Like what's the motivation behind this? 334 00:16:04,240 --> 00:16:04,880 Speaker 2: Yeah? 335 00:16:05,080 --> 00:16:06,960 Speaker 1: Yeah, for sure, there's a lot of unpact there. So 336 00:16:07,040 --> 00:16:11,600 Speaker 1: for me, you know me personally, my passion and who 337 00:16:11,600 --> 00:16:14,080 Speaker 1: I am at heart is I like to help people. 338 00:16:14,280 --> 00:16:16,720 Speaker 1: I'm a servant leader, like I just want to help 339 00:16:17,200 --> 00:16:22,800 Speaker 1: people reach their full potential. So, you know, the decision 340 00:16:22,840 --> 00:16:24,680 Speaker 1: to start color Stack was easy for me because I 341 00:16:24,720 --> 00:16:26,400 Speaker 1: knew I'd be happy every day, Like every time a 342 00:16:26,400 --> 00:16:28,200 Speaker 1: student gets a job, even if they just get a 343 00:16:28,240 --> 00:16:32,360 Speaker 1: good grade on their homework assignment, I am just fired up, 344 00:16:32,480 --> 00:16:36,200 Speaker 1: like let's go, Like I'm so happy for you, and 345 00:16:36,280 --> 00:16:38,880 Speaker 1: it doesn't matter how big we get, I'll always kind 346 00:16:38,920 --> 00:16:41,520 Speaker 1: of have that local mindset of like, if we can 347 00:16:41,560 --> 00:16:44,560 Speaker 1: help one student, we're successful. So that's just me. That 348 00:16:44,640 --> 00:16:49,360 Speaker 1: was my motivation personally obviously. So I started color Stack 349 00:16:49,840 --> 00:16:53,000 Speaker 1: May twenty twenty, so this is beginning kind of peak 350 00:16:53,080 --> 00:16:56,760 Speaker 1: of the pandemic. And so for me, I mean I 351 00:16:56,800 --> 00:17:00,240 Speaker 1: still knew rationally speaking that like, I had to make 352 00:17:00,240 --> 00:17:03,800 Speaker 1: this work financially. I had an offer at Google that 353 00:17:03,840 --> 00:17:05,720 Speaker 1: I had accepted at the time. Actually so I was 354 00:17:05,760 --> 00:17:07,680 Speaker 1: heading to Google, was to be to be an associated 355 00:17:07,720 --> 00:17:13,239 Speaker 1: product manager. And basically my calculation internally was, hey, I 356 00:17:13,240 --> 00:17:14,639 Speaker 1: know I'm not going to make the same amount that 357 00:17:14,680 --> 00:17:17,400 Speaker 1: I would make if I was a product manager in industry, 358 00:17:18,000 --> 00:17:21,439 Speaker 1: but I want to be paid kind of respect, you know, 359 00:17:21,720 --> 00:17:26,400 Speaker 1: appropriately for my time and effort working on color Stack 360 00:17:26,480 --> 00:17:29,560 Speaker 1: full time. And so I first sought out to raise 361 00:17:29,720 --> 00:17:31,600 Speaker 1: enough money to do that. So my first goal was 362 00:17:31,640 --> 00:17:33,040 Speaker 1: raised enough money to do this full time for at 363 00:17:33,080 --> 00:17:35,240 Speaker 1: least a couple of years. So we got an incubation 364 00:17:35,400 --> 00:17:38,399 Speaker 1: deal with Triple Byte, and that's that was amazing. They 365 00:17:38,400 --> 00:17:41,760 Speaker 1: were so supportive they got us off the ground, and today, 366 00:17:41,960 --> 00:17:43,800 Speaker 1: I mean we have a full time team of six 367 00:17:43,960 --> 00:17:48,360 Speaker 1: two contractors, and we fund that mainly through corporate sponsorships. 368 00:17:48,400 --> 00:17:50,879 Speaker 1: So similar to you know, even Afrotech. How you know, 369 00:17:50,920 --> 00:17:52,880 Speaker 1: you guys do an event, you have all these sponsors, 370 00:17:52,920 --> 00:17:54,920 Speaker 1: they come in and kind of try to attract talent. 371 00:17:54,960 --> 00:17:57,440 Speaker 1: We're doing the same thing kind of all year round 372 00:17:57,520 --> 00:18:00,439 Speaker 1: through events and engagement with our students and companies budget 373 00:18:00,480 --> 00:18:03,920 Speaker 1: for it. Like we're becoming a line item in university 374 00:18:03,960 --> 00:18:06,120 Speaker 1: recruiting budgets where they're like, hey, all right, we're doing 375 00:18:06,119 --> 00:18:08,200 Speaker 1: a new strategy for twenty twenty three. We got to 376 00:18:08,240 --> 00:18:10,359 Speaker 1: hit Aprotech, we gotta hit Grace Hopper, and we got 377 00:18:10,400 --> 00:18:10,920 Speaker 1: a partner. 378 00:18:10,720 --> 00:18:11,320 Speaker 2: With color Stack. 379 00:18:12,440 --> 00:18:12,919 Speaker 4: I love that. 380 00:18:13,200 --> 00:18:15,399 Speaker 3: But when you go to a company and you say, look, 381 00:18:16,000 --> 00:18:19,480 Speaker 3: I'm going to help you with your black talent, there's 382 00:18:19,760 --> 00:18:22,240 Speaker 3: ninety nine people who came before you who said I 383 00:18:22,240 --> 00:18:24,919 Speaker 3: can do that, and one hundred and nine coming after 384 00:18:24,960 --> 00:18:25,920 Speaker 3: you who. 385 00:18:25,720 --> 00:18:26,479 Speaker 4: Said I can do that. 386 00:18:26,560 --> 00:18:28,840 Speaker 3: Like what is what is it that got them to 387 00:18:28,880 --> 00:18:31,440 Speaker 3: believe that Yo Jeran and what he's doing with color Stack, 388 00:18:31,840 --> 00:18:33,760 Speaker 3: these are who we need to be working with. 389 00:18:34,600 --> 00:18:35,160 Speaker 2: Yeah, for sure. 390 00:18:35,160 --> 00:18:36,879 Speaker 1: I mean I think the first of a couple of 391 00:18:36,920 --> 00:18:40,000 Speaker 1: early things that I did strategically or I under saying 392 00:18:40,320 --> 00:18:42,560 Speaker 1: do them intentionally, but they happened that they were strategic. 393 00:18:43,400 --> 00:18:44,600 Speaker 2: The first thing was. 394 00:18:46,000 --> 00:18:53,119 Speaker 1: Being a CS student myself. The transition from this recruiter 395 00:18:53,359 --> 00:18:56,840 Speaker 1: was trying to recruit me for their company to hey, 396 00:18:56,880 --> 00:18:58,959 Speaker 1: I'm not running a nonprofit that you can benefit like 397 00:18:59,119 --> 00:19:02,880 Speaker 1: that was such a small transition because you know, these 398 00:19:03,040 --> 00:19:05,920 Speaker 1: these recruiters were like trying to literally trying to hire 399 00:19:05,920 --> 00:19:08,480 Speaker 1: me for the new new GRAP programs, and you know, 400 00:19:08,560 --> 00:19:10,080 Speaker 1: unfortunately I said notes a lot of them have to 401 00:19:10,080 --> 00:19:13,000 Speaker 1: pick one. But it was so easy to like reach 402 00:19:13,040 --> 00:19:14,960 Speaker 1: out to them because they were already excited about me 403 00:19:15,000 --> 00:19:17,040 Speaker 1: as a candidate, to be like, hey, well I'm doing 404 00:19:17,080 --> 00:19:19,639 Speaker 1: this other thing that's going to help you and ideally 405 00:19:19,680 --> 00:19:22,440 Speaker 1: find hundreds of more knees out there in the world. 406 00:19:22,480 --> 00:19:23,920 Speaker 2: And they were like immediately on. 407 00:19:23,920 --> 00:19:26,320 Speaker 1: Board because I had built that trust and they already 408 00:19:26,320 --> 00:19:29,000 Speaker 1: respected me for you know, a different reason but related. 409 00:19:29,400 --> 00:19:32,320 Speaker 1: So I had tons of relationships like dual Lingo is 410 00:19:32,359 --> 00:19:34,720 Speaker 1: a good example, Square Space, some of our silver partners, 411 00:19:34,720 --> 00:19:37,040 Speaker 1: like those recruiters, I was in their pipeline. They were 412 00:19:37,080 --> 00:19:38,760 Speaker 1: trying to hire me, right, so it was easy to 413 00:19:38,840 --> 00:19:42,359 Speaker 1: kind of leverage those relationships. And then the second thing 414 00:19:42,400 --> 00:19:47,399 Speaker 1: I connected with He's on my board now Wahabhaba Lobby. 415 00:19:47,440 --> 00:19:50,200 Speaker 1: He's the founder of a community called u RX, which 416 00:19:50,200 --> 00:19:53,040 Speaker 1: is a community of university recruiters and so we connected, 417 00:19:53,119 --> 00:19:55,239 Speaker 1: we hit it off. I asked him to join through 418 00:19:55,320 --> 00:19:59,040 Speaker 1: my board and like the brand, equity and trust just 419 00:19:59,040 --> 00:20:01,000 Speaker 1: built from that as well, all the intros from. 420 00:20:00,920 --> 00:20:02,840 Speaker 2: That as well, Like that just all helped out. 421 00:20:03,240 --> 00:20:07,000 Speaker 1: Where a lot of the early sales I didn't have much, 422 00:20:07,040 --> 00:20:09,800 Speaker 1: but they just because of my background, because of the 423 00:20:09,800 --> 00:20:11,800 Speaker 1: people I was associated with, were able to give me 424 00:20:11,840 --> 00:20:14,200 Speaker 1: a chance, and you know, they were rewarded and long. 425 00:20:15,119 --> 00:20:19,400 Speaker 3: You know, from from your perspective, when a company doesn't 426 00:20:19,480 --> 00:20:23,840 Speaker 3: have black talent at the levels it should, what are 427 00:20:23,520 --> 00:20:25,800 Speaker 3: they What are they missing out on? Because we often 428 00:20:25,800 --> 00:20:29,119 Speaker 3: talk about this from a justice perspective, like equality and 429 00:20:29,160 --> 00:20:32,439 Speaker 3: you know, having diversity, But what are they actually missing 430 00:20:32,480 --> 00:20:36,280 Speaker 3: out on? And I'm talking about even from financially. Are 431 00:20:36,320 --> 00:20:40,800 Speaker 3: they missing out on the revenue opportunity for having black candidates, 432 00:20:41,240 --> 00:20:43,119 Speaker 3: black talent on their teams? 433 00:20:43,720 --> 00:20:46,679 Speaker 1: Yeah, for sure. I mean I think I think you 434 00:20:46,720 --> 00:20:49,479 Speaker 1: can you can be specific about black talent, but this 435 00:20:49,560 --> 00:20:54,240 Speaker 1: applies to all kind of intersectional identities out there. I 436 00:20:54,280 --> 00:20:59,320 Speaker 1: think the more homogeneous, right, a team is the more 437 00:20:59,320 --> 00:21:02,760 Speaker 1: blind side you have blind spots you have where you 438 00:21:02,760 --> 00:21:05,880 Speaker 1: know you're thinking the same way, right, you have very 439 00:21:05,880 --> 00:21:10,480 Speaker 1: similar experiences. You just view you view the world in 440 00:21:10,560 --> 00:21:13,960 Speaker 1: a certain way, and you're not able to really bring 441 00:21:14,000 --> 00:21:17,960 Speaker 1: in new insight and get truly creative on new product 442 00:21:18,000 --> 00:21:20,800 Speaker 1: innovation or even just how your team should operate, or 443 00:21:20,800 --> 00:21:22,800 Speaker 1: even just lessons learned. I mean there's a lot of 444 00:21:23,080 --> 00:21:26,560 Speaker 1: you know, not every you know, black student is necessarily 445 00:21:26,560 --> 00:21:30,919 Speaker 1: low income, but there are lessons learned from being, you know, 446 00:21:30,960 --> 00:21:34,400 Speaker 1: in certain situations and growing up in certain circumstances that 447 00:21:34,840 --> 00:21:37,320 Speaker 1: could help when when companies have to cut budget and 448 00:21:37,400 --> 00:21:39,840 Speaker 1: figure out, you know, innovative ways to get the profitability. 449 00:21:40,320 --> 00:21:41,879 Speaker 1: But I'm sure if you're if you're a bunch of 450 00:21:41,880 --> 00:21:44,280 Speaker 1: people who never had to deal with never to think 451 00:21:44,320 --> 00:21:46,480 Speaker 1: about money, you probably don't know what you're doing right now. 452 00:21:46,560 --> 00:21:48,720 Speaker 1: You probably you probably are trying to figure that out. 453 00:21:49,920 --> 00:21:52,399 Speaker 1: And that's just an example, right, But I think you 454 00:21:52,440 --> 00:21:57,040 Speaker 1: know that I've even learned within the space of building 455 00:21:57,040 --> 00:21:59,840 Speaker 1: a team that's primarily black, Like, there's a lot of 456 00:21:59,880 --> 00:22:03,800 Speaker 1: inter sectional value from the intersectionality where people are bringing 457 00:22:03,800 --> 00:22:06,159 Speaker 1: different to the table. That I just would never have 458 00:22:06,240 --> 00:22:09,320 Speaker 1: thought of, and that leads to better outcomes, better products, 459 00:22:09,320 --> 00:22:11,880 Speaker 1: better solutions, and better returns at the end of the day. 460 00:22:12,600 --> 00:22:15,840 Speaker 3: You know, we've had these stats that come out that 461 00:22:15,920 --> 00:22:19,280 Speaker 3: talk about you know, ten percent of Google's national workforce 462 00:22:19,400 --> 00:22:23,280 Speaker 3: is black or Latin X or you know, talk about Apple, 463 00:22:23,400 --> 00:22:26,480 Speaker 3: you know where I think it's like a nearly half 464 00:22:26,560 --> 00:22:29,359 Speaker 3: of their global team is all white people, right, And 465 00:22:30,040 --> 00:22:33,240 Speaker 3: you know, I have the perspective that you know, I'm 466 00:22:33,240 --> 00:22:35,480 Speaker 3: not interested in asking for us he did the table, 467 00:22:35,640 --> 00:22:38,960 Speaker 3: That's just me. I'm interested in building my own tables. 468 00:22:39,280 --> 00:22:41,480 Speaker 3: And so I wonder what your take is on these 469 00:22:42,560 --> 00:22:46,119 Speaker 3: not necessarily competing approaches, But what is your take on 470 00:22:46,400 --> 00:22:48,680 Speaker 3: You're like, look, we're going to continue to beat down 471 00:22:48,720 --> 00:22:50,159 Speaker 3: the door of Google and say you need to be 472 00:22:50,240 --> 00:22:53,520 Speaker 3: hiring us, versus we're going to go build the next Google. 473 00:22:54,320 --> 00:22:55,080 Speaker 2: Yeah, no, for sure. 474 00:22:55,240 --> 00:22:57,240 Speaker 1: I'm so happy you brought this up because that I 475 00:22:57,320 --> 00:23:00,080 Speaker 1: have the same thesis. Like we we partner with company, 476 00:23:00,240 --> 00:23:03,640 Speaker 1: and you know, we were happy to help these students 477 00:23:03,640 --> 00:23:07,280 Speaker 1: get jobs. But my ultimate mission and our ultimate mission 478 00:23:07,280 --> 00:23:11,679 Speaker 1: at color Stack, is to give these students agency. I 479 00:23:11,720 --> 00:23:13,960 Speaker 1: had a really close friend, a mentee that became a 480 00:23:13,960 --> 00:23:16,640 Speaker 1: close friend of mine, and she a black woman from 481 00:23:16,720 --> 00:23:20,879 Speaker 1: New York and she had a terrible experience interning at 482 00:23:21,119 --> 00:23:23,600 Speaker 1: Google with me, Right, we had to take walks like 483 00:23:23,680 --> 00:23:25,000 Speaker 1: almost every day kind of. 484 00:23:24,880 --> 00:23:27,320 Speaker 2: She was crying, like there's a really bad experience. 485 00:23:27,400 --> 00:23:30,080 Speaker 1: Right, And you know, I could have went to you know, 486 00:23:30,160 --> 00:23:32,440 Speaker 1: the manager or talked to someone on the team be like, hey, 487 00:23:32,520 --> 00:23:34,399 Speaker 1: you guy should do this differently, or here's the impact 488 00:23:34,440 --> 00:23:36,680 Speaker 1: of this, and bla blah blah blah, but I focused 489 00:23:36,680 --> 00:23:39,240 Speaker 1: more on just investing in her. The next summer, she 490 00:23:39,320 --> 00:23:44,600 Speaker 1: worked at a company, a startup that was building a 491 00:23:44,640 --> 00:23:47,960 Speaker 1: woman coaching an empowerment platform, and obviously the team was 492 00:23:48,040 --> 00:23:49,840 Speaker 1: all woman and she had the best time of her life. 493 00:23:49,880 --> 00:23:52,040 Speaker 1: And now she's over there working at Fingla having a 494 00:23:52,080 --> 00:23:56,280 Speaker 1: great career, you know, careers, early career experience. And so 495 00:23:56,359 --> 00:23:58,160 Speaker 1: for me, it's all about agency, Like I just want 496 00:23:58,200 --> 00:24:00,880 Speaker 1: to help these students, right, I want them to become 497 00:24:00,880 --> 00:24:03,480 Speaker 1: the strongest engineers in the world so that they can 498 00:24:03,640 --> 00:24:04,680 Speaker 1: chart their own path. 499 00:24:05,240 --> 00:24:07,360 Speaker 2: Right. Because when you to your point, if we just. 500 00:24:07,280 --> 00:24:11,159 Speaker 1: Focused on like trying to like make these companies less biased, 501 00:24:11,240 --> 00:24:15,200 Speaker 1: less racistless whatever, that's just gonna be an endless that's 502 00:24:15,400 --> 00:24:17,160 Speaker 1: that's how we got to the point where we're still 503 00:24:17,240 --> 00:24:19,720 Speaker 1: talking about this ten to fifteen, twenty years later. I'm 504 00:24:19,720 --> 00:24:22,000 Speaker 1: not focused on that they can do that day. I'm 505 00:24:22,000 --> 00:24:23,680 Speaker 1: trying to help the students just become the best. 506 00:24:24,160 --> 00:24:24,800 Speaker 4: I love that. 507 00:24:24,920 --> 00:24:27,840 Speaker 3: And one of the conversations that we were talking about 508 00:24:27,840 --> 00:24:29,800 Speaker 3: in afro tech was, you know, we often talk about 509 00:24:30,200 --> 00:24:32,639 Speaker 3: getting black people into tech, but it's another thing to 510 00:24:32,760 --> 00:24:36,719 Speaker 3: keep us in tech because we don't necessarily have ecosystem everywhere, 511 00:24:36,760 --> 00:24:38,840 Speaker 3: which is why color tech is important, which is why 512 00:24:38,920 --> 00:24:42,560 Speaker 3: afro tech is important. What are some interesting ways you've 513 00:24:42,640 --> 00:24:45,400 Speaker 3: found to help those who might be in the ecosystem 514 00:24:45,440 --> 00:24:48,320 Speaker 3: but might be disengaged from the ecosystem, so we don't 515 00:24:48,400 --> 00:24:51,600 Speaker 3: lose talent that you know, could have opportunity here but 516 00:24:51,920 --> 00:24:53,040 Speaker 3: they don't see themselves. 517 00:24:54,240 --> 00:24:54,840 Speaker 2: Yeah, for sure. 518 00:24:54,840 --> 00:24:57,080 Speaker 1: I mean there was some study done that said something 519 00:24:57,240 --> 00:25:01,159 Speaker 1: like one of there's like a predict of retention that 520 00:25:01,280 --> 00:25:02,960 Speaker 1: has to do with like com many friends you make 521 00:25:02,960 --> 00:25:05,200 Speaker 1: in the workplace, Like if you don't make like two 522 00:25:05,320 --> 00:25:07,520 Speaker 1: or three, then you're very likely to leave that company. 523 00:25:07,960 --> 00:25:11,840 Speaker 2: And I think you know that applies here as well, where. 524 00:25:13,119 --> 00:25:15,679 Speaker 1: At the very least you need community, which is a 525 00:25:15,760 --> 00:25:17,600 Speaker 1: thing that Afrotech does, Like you said, this is a 526 00:25:17,640 --> 00:25:19,760 Speaker 1: thing that color Stack does. All these events and all 527 00:25:19,800 --> 00:25:21,919 Speaker 1: these ways for you to connect with other folks that 528 00:25:22,000 --> 00:25:23,600 Speaker 1: may not be at your company, because we know what 529 00:25:23,640 --> 00:25:26,359 Speaker 1: the numbers look like. But at least you notice someone 530 00:25:26,400 --> 00:25:29,240 Speaker 1: in your same role in the industry, and that leads 531 00:25:29,280 --> 00:25:32,080 Speaker 1: to further retention because you at least have that support system. 532 00:25:32,160 --> 00:25:32,320 Speaker 2: Right. 533 00:25:32,359 --> 00:25:34,840 Speaker 1: So, like, that's one thing that I think is important, 534 00:25:35,000 --> 00:25:37,360 Speaker 1: and I think people need to know about that. Even 535 00:25:37,359 --> 00:25:39,800 Speaker 1: if your company may not be the most ideal situation 536 00:25:40,280 --> 00:25:42,119 Speaker 1: and you can't build community, at least you can do 537 00:25:42,160 --> 00:25:46,199 Speaker 1: that across different companies through you know, company agnostic communities. 538 00:25:47,119 --> 00:25:49,840 Speaker 1: And I think the other thing that is missing a 539 00:25:49,880 --> 00:25:56,600 Speaker 1: lot is understanding what it takes to progress. I think 540 00:25:56,640 --> 00:25:59,760 Speaker 1: what happens is a lot of a lot of recent 541 00:26:00,359 --> 00:26:03,440 Speaker 1: and early career professionals stay in that entry level role, 542 00:26:03,520 --> 00:26:06,800 Speaker 1: that junior role for too long. And one is the 543 00:26:06,840 --> 00:26:08,800 Speaker 1: fault of the manager. But like we just talked about, 544 00:26:08,840 --> 00:26:11,480 Speaker 1: I'm not trying to convince a manager to be less 545 00:26:11,480 --> 00:26:17,040 Speaker 1: biased and whatever. Let's just focus on really educating our junient, 546 00:26:17,080 --> 00:26:19,240 Speaker 1: like art from our community people who are in that 547 00:26:19,320 --> 00:26:22,520 Speaker 1: junior level. Like here's what it really takes to become 548 00:26:22,560 --> 00:26:26,440 Speaker 1: that level two, level three, that senior level, that manager level. 549 00:26:26,480 --> 00:26:27,920 Speaker 1: Like what's the next step? 550 00:26:28,040 --> 00:26:28,200 Speaker 2: Right? 551 00:26:28,240 --> 00:26:31,520 Speaker 1: I think the breaking into the industry and that content 552 00:26:31,600 --> 00:26:34,159 Speaker 1: is great, but I really want to see over the 553 00:26:34,240 --> 00:26:39,280 Speaker 1: next five years more content and support around. Once you 554 00:26:39,400 --> 00:26:41,560 Speaker 1: get there, how do you grow? How do you continue 555 00:26:41,600 --> 00:26:42,200 Speaker 1: to progress? 556 00:26:42,560 --> 00:26:43,800 Speaker 2: Right? Yeah? 557 00:26:44,240 --> 00:26:46,960 Speaker 3: You know, I'm still thinking about how you got these 558 00:26:47,000 --> 00:26:48,760 Speaker 3: deals versus the people who came before you and the 559 00:26:48,760 --> 00:26:51,439 Speaker 3: people who were in line after you, and so because 560 00:26:51,520 --> 00:26:53,880 Speaker 3: a lot of it has to come down to you, 561 00:26:53,880 --> 00:26:57,240 Speaker 3: you know, like what did you learn through your journey, 562 00:26:57,320 --> 00:26:59,800 Speaker 3: whether it was in school or just upbringing, about how 563 00:26:59,840 --> 00:27:03,000 Speaker 3: to make yourself valuable while you're still in school, Like 564 00:27:03,359 --> 00:27:06,520 Speaker 3: what kind of things make you more attractive as a person, 565 00:27:07,320 --> 00:27:11,159 Speaker 3: as a professional, even that aside from turning down a 566 00:27:11,240 --> 00:27:14,840 Speaker 3: role at Google, and aside from going to Cornell and 567 00:27:14,880 --> 00:27:18,080 Speaker 3: getting accepted into Cornell and getting at getting job offered 568 00:27:18,080 --> 00:27:20,520 Speaker 3: from Google, Like what aside from those things, Like what 569 00:27:21,000 --> 00:27:24,440 Speaker 3: would you admonish other students to do to make themselves 570 00:27:25,000 --> 00:27:32,239 Speaker 3: more not just hireable, but attractive as partners to these organizations? 571 00:27:32,800 --> 00:27:33,840 Speaker 2: Yeah? Yeah, for sure. 572 00:27:33,800 --> 00:27:35,439 Speaker 1: I think the first thing is first, you can't you 573 00:27:35,480 --> 00:27:37,439 Speaker 1: can't get around this. You have to be good at 574 00:27:37,440 --> 00:27:42,639 Speaker 1: what you do, Like you have to invest in learning 575 00:27:42,720 --> 00:27:45,919 Speaker 1: what you're really good at and just doing that to 576 00:27:46,000 --> 00:27:48,440 Speaker 1: the best of your ability. Like that's the one thing 577 00:27:48,520 --> 00:27:51,760 Speaker 1: that you know, people are gonna that's the one impression 578 00:27:51,760 --> 00:27:54,720 Speaker 1: that you're gonna make with most people, they're gonna remember, like, 579 00:27:56,440 --> 00:27:59,240 Speaker 1: you know, did you say what you're gonna do? You 580 00:27:59,359 --> 00:28:01,840 Speaker 1: ran that of that and it went really well. You were, 581 00:28:02,040 --> 00:28:04,960 Speaker 1: you know, on time, you know, you communicate, Like just 582 00:28:05,040 --> 00:28:06,960 Speaker 1: be a good whatever you want to be in the world, Like, 583 00:28:07,000 --> 00:28:09,360 Speaker 1: just be good at that, right. I think that's where 584 00:28:09,359 --> 00:28:11,480 Speaker 1: I started. I started Cornell by just trying to be 585 00:28:11,520 --> 00:28:15,080 Speaker 1: the best CS student I can be. The second level 586 00:28:15,680 --> 00:28:20,679 Speaker 1: is about kind of networking. I hate to say networking 587 00:28:20,680 --> 00:28:22,800 Speaker 1: because sometimes it's just like people think it's like super 588 00:28:22,840 --> 00:28:26,040 Speaker 1: professional and boring and like proper, but it's really just 589 00:28:26,080 --> 00:28:28,800 Speaker 1: putting yourself out there. Within my sophomore year, I started 590 00:28:28,840 --> 00:28:31,520 Speaker 1: to like post on LinkedIn and even little things like 591 00:28:31,520 --> 00:28:33,359 Speaker 1: oh I just watched Black Panther and I just really, 592 00:28:33,640 --> 00:28:35,959 Speaker 1: you know, love the representation. It was a little article 593 00:28:36,160 --> 00:28:38,160 Speaker 1: kind of just a couple of words, but I started 594 00:28:38,160 --> 00:28:41,800 Speaker 1: to build this brand on social media based on my 595 00:28:41,880 --> 00:28:45,120 Speaker 1: interests and my accolades, that people you know, started to 596 00:28:45,160 --> 00:28:48,960 Speaker 1: recognize and understand about me and build that personal brand 597 00:28:49,000 --> 00:28:50,880 Speaker 1: so that when they think of certain opportunities, they were 598 00:28:50,880 --> 00:28:51,640 Speaker 1: able to think of me. 599 00:28:52,320 --> 00:28:52,520 Speaker 2: Right. 600 00:28:52,600 --> 00:28:56,160 Speaker 1: And so once you already build that skill set right 601 00:28:56,240 --> 00:29:00,480 Speaker 1: that nobody can debate, you start putting yourself out there 602 00:29:00,520 --> 00:29:03,520 Speaker 1: so that people the right person can find you, see 603 00:29:03,560 --> 00:29:07,640 Speaker 1: that and promote, you know, refer you to an opportunity 604 00:29:07,680 --> 00:29:09,680 Speaker 1: or select you for an opportunity. So I think it's like, 605 00:29:09,800 --> 00:29:12,000 Speaker 1: those are the two things that I would say, for 606 00:29:12,040 --> 00:29:13,960 Speaker 1: the most part that you got to do. And I 607 00:29:13,960 --> 00:29:16,720 Speaker 1: think the last thing is like once you get the opportunity, 608 00:29:17,280 --> 00:29:20,440 Speaker 1: it's just like doing what you say you're going to do, 609 00:29:20,800 --> 00:29:23,200 Speaker 1: following up and just seeing things through. I think the 610 00:29:24,240 --> 00:29:26,520 Speaker 1: biggest thing that students aren't doing right now, we deal 611 00:29:26,560 --> 00:29:28,680 Speaker 1: with this a lot of close stack is just they 612 00:29:28,720 --> 00:29:31,880 Speaker 1: don't close like they'll apply to this thing that we have. 613 00:29:32,040 --> 00:29:34,720 Speaker 1: They'll show up to the first event, but then three 614 00:29:34,720 --> 00:29:37,240 Speaker 1: weeks later it's like, oh hey, like I'm they're either 615 00:29:37,240 --> 00:29:40,480 Speaker 1: ghosting us or like oh hey I got busy or whatever, 616 00:29:40,560 --> 00:29:42,520 Speaker 1: and they're not kind of following through like just. 617 00:29:42,520 --> 00:29:45,920 Speaker 3: Close you know, Yeah, it's interesting you started off talking 618 00:29:45,920 --> 00:29:47,920 Speaker 3: about you know, actually doing what you said you were 619 00:29:47,960 --> 00:29:50,960 Speaker 3: going to do and then being good at what you 620 00:29:51,120 --> 00:29:53,160 Speaker 3: actually are you know, supposed to be doing, because I 621 00:29:53,400 --> 00:29:57,320 Speaker 3: have had I had this conversation with several different people 622 00:29:57,320 --> 00:29:59,760 Speaker 3: on this podcast about you know, it's sometimes it can 623 00:29:59,840 --> 00:30:02,800 Speaker 3: be a faux pod or walk into a job too 624 00:30:02,840 --> 00:30:05,800 Speaker 3: early and talking about diversity and equity and include like 625 00:30:05,800 --> 00:30:07,160 Speaker 3: you need to hire more of us. And you just 626 00:30:07,200 --> 00:30:10,240 Speaker 3: got hired last week, bro, Like we and we hired 627 00:30:10,280 --> 00:30:13,040 Speaker 3: you the code and now now you've got your black 628 00:30:13,080 --> 00:30:15,719 Speaker 3: panther shirt on. And I mean, you know, like come on, 629 00:30:15,840 --> 00:30:19,200 Speaker 3: like actually be good at the job. And then as 630 00:30:19,240 --> 00:30:22,400 Speaker 3: you build that credibility, then you can start speaking up 631 00:30:22,400 --> 00:30:24,560 Speaker 3: on certain things. So I wonder there and there's a 632 00:30:24,600 --> 00:30:27,360 Speaker 3: balance there and and I'm sensitive to the balance of 633 00:30:27,400 --> 00:30:30,480 Speaker 3: like when you see injustice, obviously you've got to you 634 00:30:30,560 --> 00:30:33,400 Speaker 3: gotta address things appropriate least, but I think about the 635 00:30:33,440 --> 00:30:37,600 Speaker 3: ways that we want to be, you know, brother Umar Johnson. 636 00:30:38,640 --> 00:30:41,640 Speaker 3: And that's no shade on him. So early in the 637 00:30:41,760 --> 00:30:44,360 Speaker 3: journey of a professional career, when you when you haven't 638 00:30:44,440 --> 00:30:46,400 Speaker 3: proven yourself to be good at the role that they 639 00:30:46,480 --> 00:30:47,960 Speaker 3: hired you for, you speak on that. 640 00:30:48,040 --> 00:30:51,680 Speaker 1: Yeah, it's tough, Like you said, there's a balance, right, 641 00:30:51,800 --> 00:30:54,520 Speaker 1: but I think and I want to preface that also 642 00:30:54,560 --> 00:30:58,200 Speaker 1: by saying preface is also by saying like, you know, 643 00:30:58,240 --> 00:31:02,920 Speaker 1: we we know that the current circumstances aren't right, Like 644 00:31:02,960 --> 00:31:07,400 Speaker 1: we can't change today what happened right over the past 645 00:31:07,480 --> 00:31:09,640 Speaker 1: hundreds of years. We are here today and there are 646 00:31:09,640 --> 00:31:12,479 Speaker 1: certain circumstances. So these are just ways that we can 647 00:31:12,560 --> 00:31:14,880 Speaker 1: kind of get around that. But we know, Like I 648 00:31:15,720 --> 00:31:17,760 Speaker 1: have these conversations with students all the time where it's like, 649 00:31:18,520 --> 00:31:21,080 Speaker 1: do you want to be that pioneer. I don't think 650 00:31:21,120 --> 00:31:22,760 Speaker 1: you have to be, and I don't think you deserve 651 00:31:22,880 --> 00:31:25,400 Speaker 1: to be, but someone needs to be the first black 652 00:31:25,440 --> 00:31:28,560 Speaker 1: employee at a certain company if that company is. 653 00:31:28,520 --> 00:31:30,640 Speaker 2: Going to increase and kind of be more diverse over time. 654 00:31:30,680 --> 00:31:36,000 Speaker 1: And so to your point, I think, you know, being 655 00:31:36,400 --> 00:31:39,040 Speaker 1: good at what you do the best as best you 656 00:31:39,120 --> 00:31:44,720 Speaker 1: can kind of just reduces any evidence, right, any unsaid 657 00:31:44,880 --> 00:31:48,920 Speaker 1: or kind of flaky evidence for not promoting you, letting 658 00:31:48,920 --> 00:31:50,560 Speaker 1: you go, like all these different things, and that still 659 00:31:50,640 --> 00:31:53,400 Speaker 1: might happen just because of racism and bias. But the 660 00:31:53,400 --> 00:31:55,600 Speaker 1: best thing that you can do for your own agency 661 00:31:55,640 --> 00:31:59,520 Speaker 1: and your career is just do the work right, because 662 00:31:59,520 --> 00:32:02,240 Speaker 1: at the end the day, as much as all this 663 00:32:02,280 --> 00:32:07,080 Speaker 1: other social stuff is present, companies want to be profitable, 664 00:32:08,040 --> 00:32:11,120 Speaker 1: do better, do better work for their customers, make great experiences, 665 00:32:11,160 --> 00:32:13,600 Speaker 1: and reward their investors. So if you can just take 666 00:32:13,640 --> 00:32:16,240 Speaker 1: care of that, right, if you can just write that code, 667 00:32:16,320 --> 00:32:19,720 Speaker 1: push that product, do the things, you have so much 668 00:32:19,760 --> 00:32:23,680 Speaker 1: more agency to add anything on top of that, to 669 00:32:23,720 --> 00:32:26,520 Speaker 1: start adding new initiatives because of that respect that you have, 670 00:32:26,960 --> 00:32:30,040 Speaker 1: that you have kind of solidified, right. 671 00:32:30,520 --> 00:32:33,600 Speaker 3: No, I love that. I was reading an interview another interview. 672 00:32:33,640 --> 00:32:36,720 Speaker 3: You were talking about the paraphrase a statement that you 673 00:32:36,760 --> 00:32:38,680 Speaker 3: had here, and it says, you know, being a computer 674 00:32:38,760 --> 00:32:41,360 Speaker 3: science major actually forces you to think about things in 675 00:32:41,400 --> 00:32:45,120 Speaker 3: the same way an entrepreneur thinks about things. If you 676 00:32:45,160 --> 00:32:47,800 Speaker 3: remember saying that, can you speak on that and elaborate? 677 00:32:48,840 --> 00:32:52,680 Speaker 2: Yeah? I think so. 678 00:32:52,880 --> 00:32:55,800 Speaker 1: When I started learning how to how to code, and 679 00:32:55,880 --> 00:32:58,200 Speaker 1: friend Mady who hasn't learned how to code, it, really 680 00:32:58,360 --> 00:33:01,600 Speaker 1: you're you're trying to tell the computer what to do 681 00:33:01,680 --> 00:33:03,960 Speaker 1: at the end of the day, right, You're using this 682 00:33:04,040 --> 00:33:08,800 Speaker 1: coding language which boils down into language that the machine 683 00:33:09,280 --> 00:33:12,720 Speaker 1: that you're coding on can understand to perform some level 684 00:33:12,800 --> 00:33:17,520 Speaker 1: of computation or render a website or whatever the case 685 00:33:17,560 --> 00:33:20,680 Speaker 1: may be, right, And what I started to learn early 686 00:33:20,720 --> 00:33:23,560 Speaker 1: on is that like you have to be so detailed 687 00:33:23,800 --> 00:33:25,800 Speaker 1: to write code, Like you have to think about so 688 00:33:25,880 --> 00:33:29,480 Speaker 1: many different cases, if else, for loops, like all these 689 00:33:29,480 --> 00:33:36,280 Speaker 1: different things that boiled down to solve some basic problem 690 00:33:36,360 --> 00:33:39,600 Speaker 1: like adding two numbers. Like if you've ever written code, 691 00:33:39,600 --> 00:33:41,760 Speaker 1: you know that adding two numbers isn't like some super 692 00:33:41,760 --> 00:33:44,160 Speaker 1: trivial things like you actually have to think about a 693 00:33:44,200 --> 00:33:47,800 Speaker 1: lot of like edge cases and math that you didn't 694 00:33:47,840 --> 00:33:49,960 Speaker 1: think about before. And so I remember on this part, 695 00:33:49,960 --> 00:33:51,440 Speaker 1: I think it might've been the same podcast. I was 696 00:33:51,440 --> 00:33:54,280 Speaker 1: telling them, like, explain to me how you would how 697 00:33:54,320 --> 00:33:56,840 Speaker 1: you would you know how to make a peanut butter 698 00:33:56,840 --> 00:34:00,320 Speaker 1: and jelly sandwich. And they realized how many stings they 699 00:34:00,400 --> 00:34:02,960 Speaker 1: take for granted. And I was like, well, as a 700 00:34:03,000 --> 00:34:06,280 Speaker 1: business leader, right, as a founder, if you want to 701 00:34:06,320 --> 00:34:09,640 Speaker 1: go and build a nonprofit that supports black and LATINX 702 00:34:09,680 --> 00:34:11,879 Speaker 1: computer science students, and you tell me, and I ask 703 00:34:11,920 --> 00:34:13,680 Speaker 1: you how you're gonna do that, and you'd tell me, Oh, 704 00:34:13,680 --> 00:34:16,240 Speaker 1: we're gonna do events and we're gonna run a slack 705 00:34:16,280 --> 00:34:20,600 Speaker 1: and we're gonna get sponsors. Well, okay, let's break that 706 00:34:20,760 --> 00:34:23,120 Speaker 1: down into how you're gonna do those individual things. You 707 00:34:23,120 --> 00:34:24,840 Speaker 1: have to break those things down. You need to continue 708 00:34:24,880 --> 00:34:26,879 Speaker 1: to do that. And it just reminded me so much 709 00:34:26,880 --> 00:34:28,759 Speaker 1: of what I learned when I wrote code. So when 710 00:34:28,760 --> 00:34:31,280 Speaker 1: I come in and think about how to build a company, 711 00:34:31,760 --> 00:34:35,919 Speaker 1: I'm starting from this basis of like I've already learned 712 00:34:35,960 --> 00:34:37,960 Speaker 1: and been trained on how to be so detailed in 713 00:34:38,000 --> 00:34:42,080 Speaker 1: my solutions that I'm applying that here in the same 714 00:34:42,200 --> 00:34:44,120 Speaker 1: use case of like starting a company, where I'm thinking 715 00:34:44,160 --> 00:34:47,400 Speaker 1: about each step, each edge case, boiling it all down 716 00:34:47,719 --> 00:34:50,680 Speaker 1: to its fundamental kind of basic. 717 00:34:50,560 --> 00:34:51,400 Speaker 2: Parts of the solution. 718 00:35:05,400 --> 00:35:07,920 Speaker 4: Black Tech Green Money is a production of Blavity. 719 00:35:07,520 --> 00:35:10,800 Speaker 3: Afrotech going to Black Effect Podcast Network. 720 00:35:10,400 --> 00:35:13,200 Speaker 4: And night Hire Media. It's produced by Morgan Debonne and me. 721 00:35:13,600 --> 00:35:19,120 Speaker 3: Well Lucas, with additional production support by Sarah Ragan, Enrolse McLucas. 722 00:35:19,120 --> 00:35:20,440 Speaker 4: Special thanking to Michael Davis. 723 00:35:20,440 --> 00:35:23,080 Speaker 3: Something that's a surruno learn more about my guess The 724 00:35:23,120 --> 00:35:26,000 Speaker 3: Other Tech The Trut is an innovators to afrotech dot com. 725 00:35:26,640 --> 00:35:29,800 Speaker 3: Join your Black Tech Green Money, share this with somebody, 726 00:35:31,680 --> 00:35:33,239 Speaker 3: Go get your money. 727 00:35:33,840 --> 00:35:34,480 Speaker 4: Peace and love.