Meeting Title: Brainforge Internship Discussion Date: 2026-04-02 Meeting participants: Robert Tseng, Yi Heng Joshua Wu
WEBVTT
1 00:00:09.490 ⇒ 00:00:11.039 Yi Heng Joshua Wu: Robert, how’s it going?
2 00:00:11.040 ⇒ 00:00:13.219 Robert Tseng: Hey, Joshua. Good, how are you?
3 00:00:13.550 ⇒ 00:00:16.000 Yi Heng Joshua Wu: Doing good, doing good, thank you for hopping on the call.
4 00:00:16.000 ⇒ 00:00:19.509 Robert Tseng: Of course, yeah, so I was running a little late, I was running another call.
5 00:00:20.030 ⇒ 00:00:24.829 Yi Heng Joshua Wu: Oh, good. Yeah, I heard that you went to college with Billy?
6 00:00:24.890 ⇒ 00:00:34.579 Robert Tseng: Yeah, not at the same time, but yeah, we were part of the same, kind of college ministry, and then, when I lived in Hong Kong, he was somebody I met up with.
7 00:00:35.260 ⇒ 00:00:39.640 Yi Heng Joshua Wu: Oh, sweet, sweet. Do you happen to know Ving as well? I think he was also, like…
8 00:00:39.640 ⇒ 00:00:43.539 Robert Tseng: Of course, yeah, yeah, yeah. Oh, you know, you know, oh, because you were, you’re at Berkeley?
9 00:00:43.950 ⇒ 00:01:00.440 Yi Heng Joshua Wu: Yeah, so I was at Berkeley for undergrad, and Billy introduced me, and so we had kind of, like, started, like, a little small org back then. Yeah, so it was, I guess I followed his footsteps to become a Trojan afterwards. Yeah.
10 00:01:00.440 ⇒ 00:01:01.920 Robert Tseng: Wait, Bing went to USC too?
11 00:01:02.890 ⇒ 00:01:06.060 Yi Heng Joshua Wu: I don’t know if… no, sorry, I meant Billy.
12 00:01:06.060 ⇒ 00:01:07.049 Robert Tseng: Philly, going from the, okay.
13 00:01:07.050 ⇒ 00:01:13.230 Yi Heng Joshua Wu: Yeah, yeah, yeah. So, because he was like, yo, you know, you should be a Trojan, so I was like, okay, why not?
14 00:01:13.660 ⇒ 00:01:29.849 Yi Heng Joshua Wu: And so… Nice. Yeah. And I chatted with him, like, I think a couple weeks ago, and he was like, you know, you want to chat with Robin? I was like, okay. Yeah, I want to learn more about Brainforge, and, you know, it seems like a lot of the work, sounds very interesting on the apply side and data consulting, so…
15 00:01:29.850 ⇒ 00:01:35.270 Yi Heng Joshua Wu: if I decide to reach out. Yeah, so… Cool.
16 00:01:35.270 ⇒ 00:01:45.689 Robert Tseng: Yeah, appreciate… yeah, I mean, Billy, Billy, mentioned I should chat with you. Seems like you’re… you’re still in school until the end of this year, and then you’re looking for a full-time role after that?
17 00:01:46.260 ⇒ 00:01:53.009 Yi Heng Joshua Wu: Yeah, so it’s kind of flexible, like, the program, I just need to, like, move classes around. I can do either end of this year or end of spring.
18 00:01:53.010 ⇒ 00:02:11.720 Yi Heng Joshua Wu: But I think for now, mostly looking for internships, like, part-time during the school, so to kind of, get more, hands-on experience, you know, technology changes every day, and even working in the industry a couple years, just want to stay on top of the game. So I think, first of all, part-time, and then afterwards, full-time.
19 00:02:12.060 ⇒ 00:02:13.480 Yi Heng Joshua Wu: Yeah, that’s the current goal for now.
20 00:02:13.480 ⇒ 00:02:23.770 Robert Tseng: Okay, great. I remember… let me try to pull up your resume again, okay? I saw… come through,
21 00:02:24.230 ⇒ 00:02:33.540 Robert Tseng: Yeah, I guess, like, what stood out to me, couple things, yeah, I think being, like.
22 00:02:33.930 ⇒ 00:02:45.880 Robert Tseng: Seems like you have some consulting background, and also, I guess, you’re more data science focused, so maybe doing some sort of, like, predictive analysis is something that you’d be interested in.
23 00:02:46.380 ⇒ 00:02:48.959 Robert Tseng: Yeah, it seems like you also have some…
24 00:02:49.130 ⇒ 00:02:59.350 Robert Tseng: like, data engineering experience as well. Like, I see you doing stuff with, yeah, MongoDB, it seems like you use AWS and Python. Yeah, I mean.
25 00:02:59.610 ⇒ 00:03:09.510 Robert Tseng: I don’t know how much you know about Brainforge, but do you want to try to, like, give me your, like, few-sentence kind of summary of your journey and what you’re looking for?
26 00:03:09.990 ⇒ 00:03:34.050 Yi Heng Joshua Wu: Yeah, so I think, like, start… I guess I started off journey kind of in school, did a background in data science and econ, really interested in combining both the technical side and business side things. I don’t want to, you know, just focus on classroom theory, but really apply, all the stuff that I learned to help business solve challenges. And so, ultimately, I did a couple internships, ranging from BI consulting to, kind of, data science on the back end.
27 00:03:34.050 ⇒ 00:03:43.230 Yi Heng Joshua Wu: And finally, kind of consulting that combines all the above, so kind of end-to-end pipeline, from, you know, the raw data into how to drive value for a client.
28 00:03:43.230 ⇒ 00:03:45.859 Yi Heng Joshua Wu: I think my goal is really being able to.
29 00:03:45.860 ⇒ 00:03:46.330 Robert Tseng: Anything?
30 00:03:46.330 ⇒ 00:04:11.259 Yi Heng Joshua Wu: deliver value, ultimately, and I thought that Brainforge is really at the forefront of helping all these, industries with maybe enterprise, but perhaps legacy, database and infrastructure, and help them drive value, because ultimately, that kind of transformation process is probably the hardest part that, you know, even AI probably couldn’t solve right away. And so I think that first step and what Brainforge is doing is really interesting.
31 00:04:11.260 ⇒ 00:04:18.300 Yi Heng Joshua Wu: And with this newest development, I think it’s the right place to be, and to expose myself more, to the work like that, so…
32 00:04:18.300 ⇒ 00:04:20.509 Yi Heng Joshua Wu: Here I am, trying to learn from my company.
33 00:04:20.850 ⇒ 00:04:37.410 Robert Tseng: Nice, yeah, I mean, I guess I’d like to hear more about, when you say end-to-end experience, can you walk me through, like, how you… what’s your role on a client engagement? Like, you know, how long were the projects? Kind of like, yeah, what was your role in it? And…
34 00:04:37.570 ⇒ 00:04:39.310 Robert Tseng: Yeah, maybe we’ll just start with that.
35 00:04:39.730 ⇒ 00:04:56.760 Yi Heng Joshua Wu: Yeah, sounds good. I think, typically projects last from, 6 months to a year, and so they are more, sort of, long-term engagement, and so sometimes we work with… I guess one example of a project would be working with a pharmaceutical or healthcare client where your data is often messy, and
36 00:04:56.760 ⇒ 00:05:00.570 Yi Heng Joshua Wu: Lots of compliance reasons, they’re kind of, like, in different spaces.
37 00:05:00.570 ⇒ 00:05:25.549 Yi Heng Joshua Wu: And so, ultimately, we try to make a unified view of, kind of how well they’re doing, overall in the healthcare setting, using their defined KPIs, and also, just general, let’s say, marketing performance, financial performance, and forecasting. We basically have to talk to all the individual data owners, try to figure out what the data definition means, whether they’re, like, duplicate, you know, different metrics that mean
38 00:05:25.550 ⇒ 00:05:42.800 Yi Heng Joshua Wu: kind of the same thing, or whether they are, you know, all have different arguments that we try to have to make sure everything is standardized. And so, after having that sort of conversation, you’re able to build, sort of process or pipeline, working with data engineers and all the product
39 00:05:42.800 ⇒ 00:05:54.679 Yi Heng Joshua Wu: Team to develop, sort of, like, automated pipeline to essentially, have an incremental update that allows them to say, hey, Xantha team, here are your monthly results, quarterly results.
40 00:05:54.680 ⇒ 00:05:55.370 Robert Tseng: Annual.
41 00:05:55.370 ⇒ 00:05:57.489 Yi Heng Joshua Wu: results. This is what is useful.
42 00:05:57.490 ⇒ 00:05:57.870 Robert Tseng: Nope.
43 00:05:57.870 ⇒ 00:06:18.419 Yi Heng Joshua Wu: For you guys, here’s what you guys should do based on these, APIs. And so you kind of, like, set up that whole infrastructure for them so that they can run, whatever analysis they want, whenever they want, but essentially help train the team and guide them on the best processes and how to move forward, from a legacy structure into something that’s more stable and more mature.
44 00:06:18.960 ⇒ 00:06:23.160 Yi Heng Joshua Wu: So my role is kind of, like, coordinating, and also when there’s a,
45 00:06:23.160 ⇒ 00:06:23.680 Robert Tseng: you know, but…
46 00:06:23.680 ⇒ 00:06:31.109 Yi Heng Joshua Wu: locker up, basically go into it and try to troubleshoot what’s happening, because I have the technical background, but also the business context. So, essentially.
47 00:06:31.590 ⇒ 00:06:43.250 Yi Heng Joshua Wu: slide myself in, and I think somewhere in a startup where you’re able to wear multiple hats is where I want to be to keep my skills sharp and keep all my muscles kind of, like, working. Okay. Yeah. Cool, yeah.
48 00:06:43.250 ⇒ 00:07:04.579 Robert Tseng: I’ll, like, try to, like, match some of your experience, kind of put it in the brainwash, like, kind of world. So our average contract is probably, like, 3 to 6 months, so a little bit on the shorter side compared to what you deal with. We have, like, some longer-term contracts we have clients that we’re working with for over a year and a half, and we just signed, like, a year-long deal, so we do kind of see ourselves, especially as we move
49 00:07:04.580 ⇒ 00:07:08.550 Robert Tseng: Upmarket to be doing these 6-month-plus contracts.
50 00:07:08.550 ⇒ 00:07:31.160 Robert Tseng: But yeah, I think, like, one of the biggest needs is, like, somebody to come in and be able to do discovery. So, like, I think, like you said, walking into kind of a mess, messy situation to make sense of it, and to basically build a roadmap, and to… and also make a recommendation for a quick win. So, yeah, I think, like, you know, there’s different…
51 00:07:31.400 ⇒ 00:07:35.190 Robert Tseng: We’re hiring for different types of,
52 00:07:35.390 ⇒ 00:07:40.440 Robert Tseng: data people. I mean, there’s, like, we’re hiring for data engineers, so you could just straight up just be doing, like.
53 00:07:40.550 ⇒ 00:07:45.479 Robert Tseng: building custom NetSuite connectors and, like, doing…
54 00:07:45.600 ⇒ 00:08:00.509 Robert Tseng: yeah, like, manage the ETL on, like, a big client, or if you wanted to do that. We have analytics engineers, you know, dbt modeling, which I think is really interesting, because with the advancements in AI, like, 30% of our dbt tickets are executed with AI, so…
55 00:08:00.970 ⇒ 00:08:06.130 Robert Tseng: The way that we’ve, we’ve set it up is, every…
56 00:08:06.710 ⇒ 00:08:13.060 Robert Tseng: Like, all… we have a pretty wide range of context.
57 00:08:13.500 ⇒ 00:08:20.000 Robert Tseng: All the calls, transcripts, Slack messages, emails, requirements that we get, basically unstructured requirements we get from the clients.
58 00:08:20.020 ⇒ 00:08:33.559 Robert Tseng: They get run through, kind of, like, we’ve set up a bunch of cloud agents that help do project planning. There’s a human review process, where typically the lead on a client will basically make sure that that’s the right sequence, the objectives seem right.
59 00:08:33.870 ⇒ 00:08:49.109 Robert Tseng: And then that gets broken out into tickets, and linear, specifically. And then we’ll run it through Codex and Claude, whichever model thinks it can pick up the ticket, if it has more than 85% context, AI will just execute it. And so…
60 00:08:49.430 ⇒ 00:09:01.480 Robert Tseng: That’s the world we see. Like, analytics engineering is gonna become more and more automated, like, I think that this will probably be… I mean, our goal is, like, 40% automation for that, for those tickets by the end of the…
61 00:09:01.480 ⇒ 00:09:13.739 Robert Tseng: So, I think it’s interesting that it’s like, okay, if you were really passionate about data modeling, then you can come in, you’re basically, like, more like a product manager, trying to, like, help us hit that, goal of, like, 40% automation on
62 00:09:14.160 ⇒ 00:09:15.490 Robert Tseng: analytics engineering work.
63 00:09:15.490 ⇒ 00:09:16.930 Yi Heng Joshua Wu: Oh, that’s very exciting.
64 00:09:16.930 ⇒ 00:09:29.919 Robert Tseng: Yeah, so that’s… that’s an interesting kind of… that’s another direction you could go if you wanted to. And then, I think where there’s the most upside, in terms of, like, career growth, highest comp, is, like, if you come in and be a data strategist for us.
65 00:09:30.320 ⇒ 00:09:44.229 Robert Tseng: case we have, like, two different tracks. We have one where we call client success owner, where you’re client-facing. You’re basically presenting to VP-level, C-level, folks, like, representing Brainforge, the work that we’re doing.
66 00:09:44.230 ⇒ 00:09:54.739 Robert Tseng: And yeah, you’re… it’s more of, like, pushing towards, like, an account management track. Right, right. But the exciting part there is, yeah, you know, you… you help us, like.
67 00:09:55.020 ⇒ 00:09:57.439 Robert Tseng: You know, stay… maintain good relationships.
68 00:09:57.440 ⇒ 00:09:57.830 Yi Heng Joshua Wu: Yeah.
69 00:09:57.830 ⇒ 00:10:01.659 Robert Tseng: So there’s a bit of travel, because sometimes they have to go on-site to go.
70 00:10:01.660 ⇒ 00:10:02.290 Yi Heng Joshua Wu: Finally.
71 00:10:02.290 ⇒ 00:10:02.770 Robert Tseng: and keep.
72 00:10:02.770 ⇒ 00:10:03.150 Yi Heng Joshua Wu: Corporation.
73 00:10:03.150 ⇒ 00:10:06.000 Robert Tseng: and also discovering new opportunities, which.
74 00:10:06.000 ⇒ 00:10:06.400 Yi Heng Joshua Wu: ending as.
75 00:10:06.400 ⇒ 00:10:07.860 Robert Tseng: where the upside is, if you…
76 00:10:07.860 ⇒ 00:10:08.190 Yi Heng Joshua Wu: Right.
77 00:10:08.190 ⇒ 00:10:25.909 Robert Tseng: renewal, you expand the contract by trying to, you know, you scope a new workstream that, like, we weren’t working on before, and we’re able to tack that on to our contract. You get a cut of that. So that’s, like, that track. And the other track is just being more of a specialist, where we call it service lead.
78 00:10:25.910 ⇒ 00:10:35.129 Robert Tseng: Where you own a particular domain, and any work related to that work from clients comes to you, and you’re basically the main, like, architect for that work stream.
79 00:10:35.130 ⇒ 00:10:49.000 Robert Tseng: And so, like, other colleagues will come to you, be like, hey, this client wants to… has some challenges with product analytics, they’re talking to the product analytics service lead, and he’s helping them… he’s basically consulting them to, like, help.
80 00:10:49.000 ⇒ 00:10:49.420 Yi Heng Joshua Wu: For real.
81 00:10:49.420 ⇒ 00:10:50.000 Robert Tseng: their.
82 00:10:50.000 ⇒ 00:10:51.389 Yi Heng Joshua Wu: Kind of internal, right.
83 00:10:51.390 ⇒ 00:10:51.830 Robert Tseng: Yeah.
84 00:10:51.830 ⇒ 00:10:52.920 Yi Heng Joshua Wu: Gotcha, gotcha.
85 00:10:53.110 ⇒ 00:10:56.710 Robert Tseng: Yeah, I’ll just pause there. I know that’s a lot, kind of trying to take
86 00:10:56.770 ⇒ 00:11:14.580 Robert Tseng: like, overall, like, how we engage with clients versus… and the delivery structure that we… that we run for, like, where, you know, where you could possibly fit in. Kind of given that, like, what, you know, any… any, like, initial reactions, like, what sticks out to you, like, any of those roles you felt like, you want to be more.
87 00:11:14.580 ⇒ 00:11:27.569 Yi Heng Joshua Wu: Yeah, I think… I think the last two are definitely, like, something worth considering, given my background. I think dimensional modeling, as you said, you know, is even… is interesting, but in that I think there’s definitely a lot of automation going on, so a lot of changes.
88 00:11:27.570 ⇒ 00:11:45.239 Yi Heng Joshua Wu: Now, I think definitely kind of like a hybrid product manager, and also sort of specialist, where you have a domain knowledge, and also understand, kind of, what are the problems. Being able to, kind of, stay hybrid on both… both sides, I think that would be great, but I think I would have to learn more about it as, as I go along.
89 00:11:45.240 ⇒ 00:11:55.999 Yi Heng Joshua Wu: Definitely, I think, being able to client-facing, you kind of keep the revenue coming, and also, understand what is the state of the art, what is the latest challenge. Being a product manager, you’re able to kind of
90 00:11:56.000 ⇒ 00:12:20.969 Yi Heng Joshua Wu: scale the product and try to make sure that you’re going towards that, North Star, having AI automate most of the work, or at least the analytics and engineering part. So, I think those two are definitely my top interests for now. But yeah, definitely would like to learn more about it. Man, it seems like it’s mostly… the work streams, if I understand, for the website, is data engineering, kind of marketing attribution and measurement, and also
91 00:12:20.970 ⇒ 00:12:23.279 Yi Heng Joshua Wu: AI automation, what do you say that’s like…
92 00:12:23.280 ⇒ 00:12:25.060 Yi Heng Joshua Wu: The key word streams for the special?
93 00:12:25.060 ⇒ 00:12:28.969 Robert Tseng: So I would say those are the core, like, engineering work streams,
94 00:12:29.200 ⇒ 00:12:33.849 Robert Tseng: Yeah, I think there’s more… I mean, I think there’s more that I’m trying to add.
95 00:12:33.850 ⇒ 00:12:35.290 Yi Heng Joshua Wu: Did that? No.
96 00:12:35.290 ⇒ 00:12:39.050 Robert Tseng: Clients are always asking us for more stuff that, like, I don’t necessarily think we can sort
97 00:12:39.380 ⇒ 00:12:54.100 Robert Tseng: So, yeah, I am trying to bring in more people to kind of diversify it. Like, one example is, like, forecasting is a work stream that nobody owns right now. Like, I have some background on the business side, so I built some
98 00:12:54.100 ⇒ 00:13:02.109 Robert Tseng: forecast for our clients, but, like, I’m not really able to kind of keep that going, so I’m, like, trying to find a service lead who’s just going to be doing, like.
99 00:13:02.600 ⇒ 00:13:05.370 Yi Heng Joshua Wu: Forecasting, right? Kind of, like, specialize in that.
100 00:13:07.430 ⇒ 00:13:08.260 Yi Heng Joshua Wu: Oops.
101 00:13:08.590 ⇒ 00:13:11.559 Yi Heng Joshua Wu: Seems like it’s lagging.
102 00:13:19.270 ⇒ 00:13:19.890 Robert Tseng: Oh.
103 00:13:20.830 ⇒ 00:13:21.870 Yi Heng Joshua Wu: Sorry to hear him.
104 00:13:21.870 ⇒ 00:13:23.149 Robert Tseng: Yeah, yeah, I can hear you. Oh, sorry.
105 00:13:23.150 ⇒ 00:13:26.520 Yi Heng Joshua Wu: Okay, perfect. No, no worries. Yeah, I just froze for a sec.
106 00:13:26.520 ⇒ 00:13:26.909 Robert Tseng: No worries.
107 00:13:26.910 ⇒ 00:13:29.989 Yi Heng Joshua Wu: understand. Yeah, go ahead.
108 00:13:30.240 ⇒ 00:13:43.810 Robert Tseng: Yeah, I… I’m not sure where I got cut off, so, I think I was just basically saying there are a couple other service leads that I’m… like, specific specialties that I’m… I’m looking to fill. But yeah, I think that’s a good overview of, like, kind of the areas that we work in.
109 00:13:45.760 ⇒ 00:13:47.709 Robert Tseng: Yeah, I think,
110 00:13:48.580 ⇒ 00:13:53.400 Robert Tseng: I mean, it seems like you… I mean, I think… I think you’re a good, I’m…
111 00:13:53.740 ⇒ 00:13:55.710 Robert Tseng: Good communicator, so that goes a long.
112 00:13:55.710 ⇒ 00:13:58.260 Yi Heng Joshua Wu: This business is, like…
113 00:13:58.260 ⇒ 00:14:11.769 Robert Tseng: at least 50% communication, so… For sure. Yeah. And I think as far as, like, next steps for us, like, if you’re interested in exploring this further, like, I’ll basically pass you off to Kayla. I don’t know if she reached out to you. She’s our recruiter.
114 00:14:11.770 ⇒ 00:14:12.110 Yi Heng Joshua Wu: Social.
115 00:14:12.110 ⇒ 00:14:17.709 Robert Tseng: to tell you… probably have you go through a couple rounds. One will be, like, more of, like, a technical screening.
116 00:14:17.890 ⇒ 00:14:18.330 Yi Heng Joshua Wu: Right.
117 00:14:18.330 ⇒ 00:14:25.329 Robert Tseng: And then one will be more, like, kind of a case study, where you kind of put together a deck, and, like, you present it.
118 00:14:25.330 ⇒ 00:14:25.940 Yi Heng Joshua Wu: Alright.
119 00:14:25.940 ⇒ 00:14:33.249 Robert Tseng: And I think if all that goes well, then we can definitely, fit you into… fit you into the team.
120 00:14:33.250 ⇒ 00:14:34.570 Yi Heng Joshua Wu: Yep. So yeah, I think that’s…
121 00:14:34.570 ⇒ 00:14:36.230 Robert Tseng: Kind of what the process would be.
122 00:14:36.640 ⇒ 00:14:45.119 Robert Tseng: I guess, do you have any other kind of questions about the Brain Forge, or anything in general? Like, happy to kind of just step out of the interview mode.
123 00:14:45.120 ⇒ 00:14:46.649 Yi Heng Joshua Wu: Yeah, yeah, no, no, no, for sure.
124 00:14:46.840 ⇒ 00:14:47.390 Robert Tseng: Yeah.
125 00:14:47.390 ⇒ 00:14:58.300 Yi Heng Joshua Wu: Yeah, I guess curious, from your perspective, you know, over the years in the industry, what would you say is, like, the biggest change, and if there’s, like, anything that actually got harder after AI kind of came along?
126 00:14:59.100 ⇒ 00:15:00.030 Robert Tseng: Pardon me.
127 00:15:00.030 ⇒ 00:15:01.680 Yi Heng Joshua Wu: you know, word perspective, so…
128 00:15:01.680 ⇒ 00:15:04.730 Robert Tseng: Yeah, definitely. I think…
129 00:15:05.000 ⇒ 00:15:18.429 Robert Tseng: on the… both on the supply side and demand side. On the supply side, it’s much harder to find people who, like… there’s just a lot of noise in, like, AI-generated output, and we are a very AI-forward team, so…
130 00:15:18.550 ⇒ 00:15:33.930 Robert Tseng: And it’s… it’s kind of the trade-off that you make, where everybody is kind of using, like, our internal tools to help speed up their work, but the quality doesn’t, like, kind of… if not managed well, it doesn’t… it doesn’t stay. It could, like, become slopp, right?
131 00:15:34.070 ⇒ 00:15:40.430 Robert Tseng: So yeah, I feel like we’ve had to be a lot more thoughtful about the guardrails that we put in place.
132 00:15:40.830 ⇒ 00:16:00.269 Robert Tseng: both, not just from, like, AI-generated code, but also, you know, we use it to generate, like, like, briefs that we write, like, scopes of work, like, all this content that we put out in front of clients, too, but it still needs to hit a very high bar. So, I think finding people who are able to, like, who are very opinionated, about what
133 00:16:00.270 ⇒ 00:16:01.330 Robert Tseng: Good looks like.
134 00:16:01.470 ⇒ 00:16:07.440 Robert Tseng: And, like, we’re able to, like, build things up from a first principles perspective, rather than just, like.
135 00:16:07.580 ⇒ 00:16:16.659 Robert Tseng: I think a very junior person who doesn’t really think too critically will just take AI’s output and start to edit it down, which is, like.
136 00:16:16.770 ⇒ 00:16:31.940 Robert Tseng: it’s… if it’s built fundamentally in an inefficient or, like, an incomplete way, you editing it down is still gonna be, like, messy. You’re just like, yeah, it’s not gonna be that great. So, I think that shows up pretty clearly, when…
137 00:16:31.940 ⇒ 00:16:45.640 Robert Tseng: you know, and the work on the supply side. Now, on the demand side, yeah, clients feel like they understand our work. You know, they just throw everything into ChatGPT or Quad first, and then they’ll try to tell us, like, hey, why don’t you do it this way? And so.
138 00:16:46.090 ⇒ 00:16:59.150 Robert Tseng: being able to defend against that, and yeah, I think there’s more skepticism in the market now. It’s put a lot more pressure on consultants to be, like, really clear in their communication and establishing expertise.
139 00:17:00.320 ⇒ 00:17:03.860 Robert Tseng: Yeah, like, I just feel like a lot of our clients try to tell us how to do our job now.
140 00:17:03.860 ⇒ 00:17:06.230 Yi Heng Joshua Wu: And.
141 00:17:06.230 ⇒ 00:17:16.739 Robert Tseng: You know, sometimes they’re right, and sometimes I’m like, shoot, like, they’re exposing our team for, like, not doing a good job. Like, sometimes it actually… their AI-generated thing is better than what the team predicted.
142 00:17:16.740 ⇒ 00:17:17.520 Yi Heng Joshua Wu: Wow.
143 00:17:17.520 ⇒ 00:17:23.130 Robert Tseng: Which is good, because it forces us to kind of think about, like, why did we not get to that bar?
144 00:17:23.130 ⇒ 00:17:24.000 Yi Heng Joshua Wu: Like, how…
145 00:17:24.000 ⇒ 00:17:24.740 Robert Tseng: And how do we keep pushing?
146 00:17:24.740 ⇒ 00:17:28.079 Yi Heng Joshua Wu: Wow. Okay, I did not think of that, yeah.
147 00:17:28.089 ⇒ 00:17:34.719 Robert Tseng: Yeah, so I think everybody… nobody’s a real… real expert in this space, in terms of, like, the how to do it. I think, like.
148 00:17:35.090 ⇒ 00:17:45.300 Robert Tseng: grounded in, like, you know, in your domain, and not, like, getting lost in the what models to use, like.
149 00:17:45.300 ⇒ 00:17:45.750 Yi Heng Joshua Wu: Very long.
150 00:17:45.750 ⇒ 00:17:47.200 Robert Tseng: prompt engineering, like, all of that.
151 00:17:47.200 ⇒ 00:17:47.710 Yi Heng Joshua Wu: Right.
152 00:17:47.710 ⇒ 00:18:00.109 Robert Tseng: stuff, like, we… we don’t worry about too much. Like, the models get better every 6 months anyway, so… Right, exactly. Yeah, like, I… and we have an internal engineering team that basically is helping to
153 00:18:00.740 ⇒ 00:18:02.960 Robert Tseng: Create the tools that we need, but…
154 00:18:02.960 ⇒ 00:18:03.290 Yi Heng Joshua Wu: I think.
155 00:18:03.290 ⇒ 00:18:09.779 Robert Tseng: The people who are in client-facing roles, like, they’re… they just need to stay focused on, like, how to deliver… deliver the value.
156 00:18:09.780 ⇒ 00:18:10.250 Yi Heng Joshua Wu: Right.
157 00:18:10.250 ⇒ 00:18:10.630 Robert Tseng: to.
158 00:18:10.630 ⇒ 00:18:11.460 Yi Heng Joshua Wu: Go to trust.
159 00:18:11.460 ⇒ 00:18:18.359 Robert Tseng: So, I don’t think… I think that part hasn’t changed, in, in, in, in consulting, so… Right.
160 00:18:18.700 ⇒ 00:18:38.389 Yi Heng Joshua Wu: Gotcha. Okay, no, thank you for sharing that, because I think I’ve been seeing a lot, definitely see, you know, like, the power of AI in kind of generating all these ideas, but definitely, as you said, you know, with the experts and kind of how to, you know, showcase that expertise, I think that’s definitely, like, the harder part now, now that everyone can basically challenge what you say, and…
161 00:18:38.390 ⇒ 00:18:46.879 Yi Heng Joshua Wu: Yeah. I never want to have access to that very easily, so, thank you for sharing that perspective. I think that’s, like, very helpful to know. I think that’s…
162 00:18:46.880 ⇒ 00:18:58.009 Yi Heng Joshua Wu: Yeah, I don’t know if anyone has a solution, but it seems like that’s gonna be, you know, trying to parse the signal from a noise. I think that’s probably the hardest part, for everyone. Yeah. So…
163 00:18:58.760 ⇒ 00:19:11.999 Yi Heng Joshua Wu: Yeah, no, I think… I think that’s mostly a question. I think you’ve pretty much explained, what a work stream and how it maps, so definitely would love to learn more. I’ll reach out, to, is it, Kane?
164 00:19:12.000 ⇒ 00:19:13.670 Robert Tseng: Kayla, yeah.
165 00:19:13.670 ⇒ 00:19:23.449 Yi Heng Joshua Wu: Yeah, Kayla, yeah, so, I’ll reach out, but yeah, I think definitely would love to learn more about the role, and, yeah, happy to help on the interview process, too, so…
166 00:19:23.450 ⇒ 00:19:24.170 Robert Tseng: I appreciate it.
167 00:19:24.170 ⇒ 00:19:29.969 Yi Heng Joshua Wu: it, the call-in. Show me how… what it’s like, latest in industry.
168 00:19:30.450 ⇒ 00:19:45.479 Robert Tseng: Yeah, of course. I’ll be in LA in, like, a month, so I usually… Oh, shoot? It’s usually for work, because we have… we actually have, like, a team of, like, 6 people in LA. I mean, soon to be 7, 7 starting next week, but, yeah, I mean, as LA team grows.
169 00:19:45.480 ⇒ 00:19:47.150 Yi Heng Joshua Wu: Love to catch up if you’re here, yeah.
170 00:19:47.150 ⇒ 00:19:51.460 Robert Tseng: I’d love you to kind of come meet the team, and we can meet in person.
171 00:19:51.460 ⇒ 00:19:51.909 Yi Heng Joshua Wu: For sure.
172 00:19:51.910 ⇒ 00:19:54.499 Robert Tseng: Yeah, my wife and I live in New York right now, but we’re considering.
173 00:19:54.500 ⇒ 00:19:54.880 Yi Heng Joshua Wu: Okay.
174 00:19:54.880 ⇒ 00:19:59.190 Robert Tseng: back to LA because, things are kind of starting to pick up, and I might.
175 00:19:59.190 ⇒ 00:19:59.590 Yi Heng Joshua Wu: Yeah.
176 00:19:59.590 ⇒ 00:20:03.259 Robert Tseng: Just be there to… to run an office or something.
177 00:20:03.260 ⇒ 00:20:06.459 Yi Heng Joshua Wu: Housing is probably better here, too, in the wetter. It is.
178 00:20:06.460 ⇒ 00:20:09.509 Robert Tseng: It is, yeah, much bigger, and get a better space, yeah.
179 00:20:10.250 ⇒ 00:20:17.499 Yi Heng Joshua Wu: Wow, I’m glad. Yeah, definitely let me know, I’d love to hit you up, and yeah, grab your coffee or a meal or something, so… yeah.
180 00:20:17.700 ⇒ 00:20:22.560 Robert Tseng: Cool, I appreciate it. I guess, what else are you involved in at USC?
181 00:20:23.040 ⇒ 00:20:40.540 Yi Heng Joshua Wu: Yeah, so, so far, I think mostly just, trying to recruit. I think the first year, it’s, mostly just school and recruiting. Hopefully, you know, we’ll get something, can kind of relax, next semester, and then I’ll probably join some clubs. I think one of my friends recommended, you should join, like, a rowing club or something. They wake up, like, 5 a.m. in the morning.
182 00:20:40.540 ⇒ 00:20:40.920 Robert Tseng: Yeah, yeah.
183 00:20:40.920 ⇒ 00:20:41.650 Yi Heng Joshua Wu: Palm Beach.
184 00:20:41.650 ⇒ 00:21:01.549 Yi Heng Joshua Wu: And do it every single day for, like, I don’t know, 8 weeks or something, and I was like, that sounds crazy, but it also sounds very fun, so… Yeah. So maybe that, and then a couple, kind of, like, I’m just hopping around different churches and see, you know, because I think there’s just, like, kind of a fit. I think I… I went, initially went to crew, but it, you know, it’s…
185 00:21:01.820 ⇒ 00:21:10.510 Yi Heng Joshua Wu: I think the values are kind of different, compared to, let’s see, I personally prefer, like, an Asian fellowship, and so, sure.
186 00:21:10.510 ⇒ 00:21:19.530 Yi Heng Joshua Wu: Yeah, that’s… that’s the one kind of, like, still exploration stage. Been talking to Billy Moore, now that he’s in UK. I think back then he was in Hong Kong for a while, and…
187 00:21:19.530 ⇒ 00:21:32.990 Yi Heng Joshua Wu: I think there is now more kind of, like, commonality, kind of moving away, home away from home sort of idea, and so for him, it’s kind of like, he watches growing older. I think I first met him when I was in, like.
188 00:21:32.990 ⇒ 00:21:33.730 Robert Tseng: Email.
189 00:21:33.730 ⇒ 00:21:48.769 Yi Heng Joshua Wu: for 10th grade, or something like that, and so back then, he was, like, the adult, like, the leader of the group. Now we’re all kind of, like, in similar stages and adults, so it was really cool to kind of see that, and, you know, have kind of calm conversations, like, oh, gas is so expensive, like, why is, like, all these.
190 00:21:48.770 ⇒ 00:21:49.420 Robert Tseng: Politicians.
191 00:21:49.420 ⇒ 00:22:10.750 Yi Heng Joshua Wu: so, you know, crazy. But, yeah, so it’s really nice, just to kind of have that buffer time, especially now, with technology changing so much, I don’t think I can even recognize what the kind of workplace is like in some way, but also the excitement here that, you know, building that, developing value and building that trust, the relationship is still, the crucial part, so…
192 00:22:10.750 ⇒ 00:22:15.959 Yi Heng Joshua Wu: I’m trying to… stay ahead of the game, and yeah, keep my skills sharp, and yeah.
193 00:22:15.960 ⇒ 00:22:16.640 Robert Tseng: Just…
194 00:22:16.640 ⇒ 00:22:27.419 Yi Heng Joshua Wu: being open to different opportunities and learn more, and try to network as much as possible while I’m at C, because I heard that’s probably the strongest suit, from the school, so… Yeah.
195 00:22:27.420 ⇒ 00:22:41.120 Yi Heng Joshua Wu: yeah, trying to put my best foot forward, going to networking events, and just co-reached out to many different alumni, which are… I’m very happy that many of them are willing to help, and that’s not really the case, in other places, so…
196 00:22:41.120 ⇒ 00:22:41.570 Robert Tseng: Yeah.
197 00:22:41.570 ⇒ 00:22:46.289 Yi Heng Joshua Wu: Yeah, so it’s exciting times, personally, yeah.
198 00:22:46.290 ⇒ 00:22:51.389 Robert Tseng: Yeah, I mean, I love hiring alumni. I think, like, half our LA team is from USC.
199 00:22:51.390 ⇒ 00:22:54.480 Yi Heng Joshua Wu: Fight on. Yeah.
200 00:22:54.480 ⇒ 00:22:54.850 Robert Tseng: Yeah, yeah.
201 00:22:55.090 ⇒ 00:22:55.920 Yi Heng Joshua Wu: Yeah.
202 00:22:56.310 ⇒ 00:22:57.250 Yi Heng Joshua Wu: Cool.
203 00:22:57.400 ⇒ 00:23:15.460 Yi Heng Joshua Wu: Yeah, yeah, I want to be mindful of your time, really appreciate it. I know, you know, super busy, so I’m really grateful that you take the time to kind of walk me through our work stream and how everything maps, so I look forward to chatting more with Kayla and learning more about her role, and definitely let me know if you come in town. Love to take you out, so…
204 00:23:15.460 ⇒ 00:23:17.710 Robert Tseng: Okay, sounds good. Thanks, Joshua.
205 00:23:17.940 ⇒ 00:23:19.210 Yi Heng Joshua Wu: Alright, thanks, Robin. Have a good one.
206 00:23:19.210 ⇒ 00:23:19.630 Robert Tseng: Luckily.
207 00:23:20.040 ⇒ 00:23:20.550 Yi Heng Joshua Wu: Okay.