Meeting Title: Brainforge Interview w- Amber Date: 2026-04-02 Meeting participants: Len Santiago (StudioLAB), Amber Lin
WEBVTT
1 00:00:32.930 ⇒ 00:00:34.410 Amber Lin: Hi there!
2 00:00:34.410 ⇒ 00:00:35.650 Len Santiago (StudioLAB): Hello?
3 00:00:36.030 ⇒ 00:00:36.810 Len Santiago (StudioLAB): Hi, Amber!
4 00:00:36.810 ⇒ 00:00:37.660 Amber Lin: Hmm.
5 00:00:37.790 ⇒ 00:00:38.919 Len Santiago (StudioLAB): Where are you?
6 00:00:38.920 ⇒ 00:00:42.020 Amber Lin: I’m doing well. Where are you based in?
7 00:00:42.020 ⇒ 00:00:44.699 Len Santiago (StudioLAB): West LA. West Hollywood, to be exact.
8 00:00:44.700 ⇒ 00:00:47.310 Amber Lin: Oh, wow, I’m in Culver City, so…
9 00:00:47.310 ⇒ 00:00:51.780 Len Santiago (StudioLAB): Oh, that’s awesome! Okay, yeah, that’s awesome. Yeah, fellow Angeleno.
10 00:00:51.780 ⇒ 00:00:54.450 Amber Lin: How long have you been in LA?
11 00:00:54.960 ⇒ 00:01:00.270 Len Santiago (StudioLAB): I’ve been out here for a few years. I’m originally from New York City, born and raised.
12 00:01:00.270 ⇒ 00:01:00.860 Amber Lin: Okay.
13 00:01:00.860 ⇒ 00:01:08.820 Len Santiago (StudioLAB): And, I came out here some years ago for Hollywood, I guess, you know, to work in the entertainment industry.
14 00:01:08.820 ⇒ 00:01:09.970 Amber Lin: Oh, really?
15 00:01:09.970 ⇒ 00:01:11.439 Len Santiago (StudioLAB): Yep, that’s great.
16 00:01:11.440 ⇒ 00:01:20.989 Amber Lin: Sounds good. Wow. I mean, how come… how come you were in entertainment, and now you want… you’re working or interviewing for this type of role?
17 00:01:20.990 ⇒ 00:01:32.600 Len Santiago (StudioLAB): That’s a really great question. So for the last few years, a couple of years to be exact, really, I’ve been with Walt Disney Studios in Burbank, it had, you know, the big studio down there.
18 00:01:33.530 ⇒ 00:01:43.859 Len Santiago (StudioLAB): within a unit or a business area called Studio Lab, which is the research and innovation
19 00:01:43.980 ⇒ 00:02:03.760 Len Santiago (StudioLAB): area for the studio, so we do a lot of Gen AI, filmic type of project we do for the studio. So, I’m on a contract. Disney contractors have a max term limit of 2 years, so that’s one reason.
20 00:02:04.100 ⇒ 00:02:09.869 Len Santiago (StudioLAB): To be truthful, the industry is going through massive change.
21 00:02:10.830 ⇒ 00:02:18.349 Len Santiago (StudioLAB): Yeah, as I’m sure you may have heard, the merging of Warner Bros. and Paramount, and we thought it was gonna be Netflix for a while.
22 00:02:19.730 ⇒ 00:02:32.020 Len Santiago (StudioLAB): And there are going to be some more significant changes, so as much as I love the work that I do and I’ve done, there’s been a lot of instability, and I have, you know, I have a mortgage to pay, you know?
23 00:02:32.020 ⇒ 00:02:33.110 Amber Lin: So…
24 00:02:33.110 ⇒ 00:02:43.620 Len Santiago (StudioLAB): with AI, it’s given me just a wonderful skill set to go out and really help transform the world from an automation standpoint.
25 00:02:44.060 ⇒ 00:02:59.269 Len Santiago (StudioLAB): this particular company that you’re with, Brainforge, really intrigues me, because there’s an opportunity to work with a multitude of clients, which is something that I’m very interested in hoping to learn more about from talking to you.
26 00:02:59.930 ⇒ 00:03:08.419 Amber Lin: Awesome. Okay, so how this interview would go is, I think you’ve already talked to Kayla. I think I was actually next to her while she talked to you.
27 00:03:08.420 ⇒ 00:03:08.820 Len Santiago (StudioLAB): Okay.
28 00:03:08.820 ⇒ 00:03:20.169 Amber Lin: So I know a little bit about your background, and you did a great intro, so I have some questions I would love to ask you, and I want to make sure at the end you have the time to ask me questions as well.
29 00:03:20.930 ⇒ 00:03:21.930 Len Santiago (StudioLAB): Sounds good.
30 00:03:22.250 ⇒ 00:03:26.869 Amber Lin: Cool. So I think the first thing I want to…
31 00:03:27.230 ⇒ 00:03:33.599 Amber Lin: kind of align on is where you would fit in the company. I think we’re looking
32 00:03:34.010 ⇒ 00:03:38.060 Amber Lin: based on the track that… since you’re talking to me, I think we’re…
33 00:03:38.200 ⇒ 00:03:55.989 Amber Lin: we’re putting you on a track of the strategy, like a senior strategy role, and I believe from Kayla’s notes and from Utam’s notes, we wanted to see, how comfortable you are working, say, with,
34 00:03:56.300 ⇒ 00:04:00.119 Amber Lin: new AI tools, or… or what type of…
35 00:04:00.310 ⇒ 00:04:07.880 Amber Lin: case studies, in the past you’ve done with, say, the different tools and stuff. So…
36 00:04:08.570 ⇒ 00:04:10.690 Amber Lin: I guess, first question is.
37 00:04:11.280 ⇒ 00:04:22.989 Amber Lin: what… what do you want to do? Because you are doing a big industry shift, and you’ve done quite a lot of different things, so I kind of want to see, like, where you want to fit into.
38 00:04:22.990 ⇒ 00:04:34.520 Len Santiago (StudioLAB): Absolutely. That’s a great place to start. So, in my initial discussion with Kayla, she mentioned at the time, and this is maybe going back a month ago at this point.
39 00:04:34.910 ⇒ 00:04:47.700 Len Santiago (StudioLAB): The role that they were looking for was the strategy role, as you mentioned. And, after that conversation, I suppose she went back to your leadership, and they came back with
40 00:04:47.700 ⇒ 00:04:55.479 Len Santiago (StudioLAB): an evolved job description that was more delivery-centric, on execution.
41 00:04:55.480 ⇒ 00:05:08.960 Len Santiago (StudioLAB): Which I thought was actually perfect. I do a number of strategy function areas in my current role at Disney, and I’m very good at it. I’ve been a product, product manager, sorry, my allergies.
42 00:05:09.220 ⇒ 00:05:16.689 Len Santiago (StudioLAB): But I have been a working project program PMO lead in the past, so…
43 00:05:17.260 ⇒ 00:05:25.960 Len Santiago (StudioLAB): you know, that’s even more within my wheelhouse. So, to answer your question, I would love to, you know, hear more about
44 00:05:26.160 ⇒ 00:05:33.239 Len Santiago (StudioLAB): The company, from your perspective, what types of projects you’ve… or clients that you’re working on.
45 00:05:33.550 ⇒ 00:05:44.569 Len Santiago (StudioLAB): And understand, you know, and I have some questions and notes as well, that I put together based… I decoded the job description from Kayla.
46 00:05:45.280 ⇒ 00:05:52.939 Len Santiago (StudioLAB): And so, from what I gleaned was that you guys are looking to standardize delivery across the organization.
47 00:05:53.190 ⇒ 00:05:53.590 Amber Lin: Mom.
48 00:05:53.590 ⇒ 00:05:57.390 Len Santiago (StudioLAB): built a lightweight PMO, I would say.
49 00:05:57.450 ⇒ 00:06:15.130 Len Santiago (StudioLAB): Really, standardized communication and your client-facing maturity, you know, to really work on those communications, which are super important for customer success, accountability structures, and ultimately to scale delivery for the growth of your company.
50 00:06:15.410 ⇒ 00:06:20.569 Len Santiago (StudioLAB): Yeah, that’s what I took away from the email that I got from her. So…
51 00:06:20.820 ⇒ 00:06:29.290 Len Santiago (StudioLAB): I see myself as the head of delivery or execution, PMO, transformation within AI.
52 00:06:29.640 ⇒ 00:06:35.739 Len Santiago (StudioLAB): You know, it’s a senior role from what I understand, so that’s definitely on par with my background.
53 00:06:35.870 ⇒ 00:06:37.340 Len Santiago (StudioLAB): Yep, so…
54 00:06:38.870 ⇒ 00:06:41.740 Amber Lin: Cool. Sounds good. I think…
55 00:06:41.860 ⇒ 00:06:53.100 Amber Lin: right now, we have, say, immediate openings on, people on projects who would own the relationship with clients, and I think overall.
56 00:06:53.100 ⇒ 00:07:10.640 Amber Lin: they’re looking for someone who’s, because we’re a very AI-native company, for someone who’s very familiar with that, can set new standards of the way of work, and incorporating, like, new AI advancements or changes into our way of work.
57 00:07:11.930 ⇒ 00:07:21.190 Amber Lin: And I think that’s why Kayla was specifically telling me about your background at Studio Labs with all the AI stuff that you guys have been doing.
58 00:07:21.950 ⇒ 00:07:22.720 Len Santiago (StudioLAB): Yeah.
59 00:07:24.010 ⇒ 00:07:28.689 Amber Lin: Cool. Let me pull up my questions.
60 00:07:31.240 ⇒ 00:07:31.810 Amber Lin: Cool.
61 00:07:31.990 ⇒ 00:07:37.499 Amber Lin: So… I think my next question’s more going to focus on,
62 00:07:37.740 ⇒ 00:07:48.510 Amber Lin: how you manage relationship with clients and stakeholders. Could you tell me about the type of stakeholders you previously worked with, and what the relationships was like?
63 00:07:48.700 ⇒ 00:08:05.849 Len Santiago (StudioLAB): Great question. So, when I think of stakeholders, I think of fostering really great relationships with folks to understand what their goals, what their priorities are, understand, any pain points that exist.
64 00:08:06.060 ⇒ 00:08:14.049 Len Santiago (StudioLAB): In their… line of business, whether it’s business or technology, so I’ve worked with
65 00:08:14.710 ⇒ 00:08:21.559 Len Santiago (StudioLAB): stakeholders from across the spectrum, from managers all the way up to C-level executives.
66 00:08:21.730 ⇒ 00:08:27.110 Len Santiago (StudioLAB): And, partnering with them to really understand
67 00:08:27.530 ⇒ 00:08:43.790 Len Santiago (StudioLAB): Again, the organizational mission of the company with respect to this project, and really, you know, working with their teams, because things kind of go down from, you know, chain of command from there, working with their respective teams to understand the impacts.
68 00:08:43.789 ⇒ 00:08:49.710 Len Santiago (StudioLAB): of, you know, the change or the project that’s being deployed, right?
69 00:08:49.750 ⇒ 00:09:07.890 Len Santiago (StudioLAB): you might be working on one digital marketing aspect piece, but there’s many back-end APIs that go there, and there’s chains back to enterprise, you know, ERP systems, and legal credit, this, that, the other, so it’s really important to understand
70 00:09:07.890 ⇒ 00:09:19.649 Len Santiago (StudioLAB): all the stakeholders that are involved, and most importantly, as a program PMO professional, to really understand the risk.
71 00:09:20.210 ⇒ 00:09:31.529 Len Santiago (StudioLAB): What are the risks? What are the issues? What are the dependencies? What are the assumptions that people are having across different impacted areas about this project?
72 00:09:32.730 ⇒ 00:09:48.130 Len Santiago (StudioLAB): Yeah, I have a lot to talk about assumptions, and it’s really important to document them, and I’ve actually found that some companies are resistant to want to talk about it, and, you know, fostering those relationships to get people to open up, because some people don’t want to admit that they
73 00:09:48.280 ⇒ 00:10:05.079 Len Santiago (StudioLAB): they’ve misunderstood a requirement, or, you know, or maybe they’re in denial of, you know, the change that’s coming, and that department is going to have to work really closely with another stakeholder and participate, so it just really…
74 00:10:05.300 ⇒ 00:10:21.600 Len Santiago (StudioLAB): At the end of the day, it’s about transparency and communication, and elevating all of the moving parts of a project, including its risk, to transparency, so that everyone is on the same page.
75 00:10:21.720 ⇒ 00:10:29.259 Len Santiago (StudioLAB): And we’re all… Aligning on the central goal of what this initiative is for.
76 00:10:30.960 ⇒ 00:10:31.610 Amber Lin: Cool.
77 00:10:31.950 ⇒ 00:10:49.370 Amber Lin: Sounds good. When I started with Brainforge, I also started in more of the, like, PMO project management side, and I eventually moved to more delivery-related work, so I resonate what you just said about managing the different relationships and expectations.
78 00:10:49.380 ⇒ 00:10:54.060 Amber Lin: I think the next question I have is, on…
79 00:10:54.590 ⇒ 00:11:14.480 Amber Lin: your relative experience. As you know, we’re a consulting company, and we do a lot of data work, some AI work, and some strategy work. I want to hear about what the types of work you’ve been doing. I know the industry, and I know you’ve worked with AI, but I’m trying to grasp
80 00:11:14.510 ⇒ 00:11:18.670 Amber Lin: Like, how that would relate or translate to the work we do.
81 00:11:19.680 ⇒ 00:11:32.379 Len Santiago (StudioLAB): That’s a really great question. So, the types of use cases that I have been working to bring to fruition, lie within, of course, the entertainment, right?
82 00:11:32.880 ⇒ 00:11:44.779 Len Santiago (StudioLAB): solutions that would exist within a film studio. So, two of the big programs that I’ve worked on over the last couple of years was visual effects in the area of…
83 00:11:44.840 ⇒ 00:11:46.680 Len Santiago (StudioLAB): Object removal.
84 00:11:46.680 ⇒ 00:12:09.600 Len Santiago (StudioLAB): and screen replacement. So, one of our studios is Marvel Cinematic Universe, and they’re superheroes, it’s a fast, high-paced action movie type of environment, and they’re literally superheroes flying around, you know, in the… in… all over the place, in the film scene, right? And so, very often, they’re rigged up to wires.
85 00:12:09.690 ⇒ 00:12:21.780 Len Santiago (StudioLAB): And those wires are attached to other rigs that manipulate them and move them around, and it appears that they’re flying. So, the old… the previous process, which has been
86 00:12:22.510 ⇒ 00:12:34.639 Len Santiago (StudioLAB): doing for years and years is to actually hand-paint, do what they call an in-painting process to remove the wires so that it looks real, and it’s believable, by hand.
87 00:12:34.670 ⇒ 00:12:50.729 Len Santiago (StudioLAB): And that’s a very time-consuming and very, very expensive to do. So, there have been technologies, and because of generative AI and advancements, we were able to really effectively
88 00:12:50.910 ⇒ 00:12:52.120 Len Santiago (StudioLAB): remove.
89 00:12:52.450 ⇒ 00:12:55.989 Len Santiago (StudioLAB): The wires from those film frames with
90 00:12:56.850 ⇒ 00:13:01.330 Len Santiago (StudioLAB): Through machine learning, enablement, essentially.
91 00:13:01.610 ⇒ 00:13:08.259 Len Santiago (StudioLAB): We did a similar thing for screen replacement. So, let’s say an actor’s in a movie, and
92 00:13:08.260 ⇒ 00:13:23.930 Len Santiago (StudioLAB): they pull out their cell phone, right? Their cell phone’s gonna be black when they’re filming it, but there’s a way to do compositing and actually superimpose, like, let’s say a text image or anything else, any other kind of image, onto that device so that it appears that
93 00:13:24.010 ⇒ 00:13:33.230 Len Santiago (StudioLAB): that content is actually there, but it’s really not. And again, that’s the second use case that we had for Marvel, and
94 00:13:33.340 ⇒ 00:13:36.150 Len Santiago (StudioLAB): you know, I think the common denominator
95 00:13:36.510 ⇒ 00:13:39.290 Len Santiago (StudioLAB): Between, let’s say, that project and…
96 00:13:39.420 ⇒ 00:13:53.160 Len Santiago (StudioLAB): let me actually pause there. The second project I worked on was automated localization, which we delivered into a full productionized environment. Localization is the enablement of foreign languages.
97 00:13:53.210 ⇒ 00:14:00.179 Len Santiago (StudioLAB): of English to be translated to foreign languages for subtitling, dubbing.
98 00:14:00.250 ⇒ 00:14:08.719 Len Santiago (StudioLAB): For multiple languages, including, what, something called AD, which I won’t get into. It’s another subset of localization.
99 00:14:08.720 ⇒ 00:14:21.220 Len Santiago (StudioLAB): So, there’s something like 13 main languages in the world, so by using voice synthesis and text-to-speech and text-to-text and some other enablements.
100 00:14:21.220 ⇒ 00:14:26.360 Len Santiago (StudioLAB): We have been able to effectively use automation
101 00:14:26.610 ⇒ 00:14:40.429 Len Santiago (StudioLAB): Whereas previously, we were… we were using 100% human beings to do the direct translation in all of those foreign languages around the world. And so…
102 00:14:40.480 ⇒ 00:14:59.540 Len Santiago (StudioLAB): this is a big movement that’s happening in technology, so that’s the second major initiative I’m very proud of. Now, the common denominator with those two programs is that I have implemented a governance around how to successfully deliver that in partnership with our stakeholders.
103 00:15:00.420 ⇒ 00:15:03.220 Len Santiago (StudioLAB): So there’s a governance framework.
104 00:15:03.460 ⇒ 00:15:07.860 Len Santiago (StudioLAB): out there called PMI, CPMAI, which is the global…
105 00:15:07.940 ⇒ 00:15:14.350 Len Santiago (StudioLAB): governance model for working on AI projects, and essentially, it identifies six
106 00:15:14.420 ⇒ 00:15:28.350 Len Santiago (StudioLAB): phases. Business understanding. You want to be totally in aligned with your stakeholders that are paying for this project, that are ultimately going to sign off on it, on the use case, understanding, you know.
107 00:15:28.630 ⇒ 00:15:35.449 Len Santiago (StudioLAB): would we, could we, and should we, right? So, not all things are…
108 00:15:35.560 ⇒ 00:15:42.590 Len Santiago (StudioLAB): you want to work on. There could be financial risk, legal risk, and maybe we shouldn’t do it.
109 00:15:42.770 ⇒ 00:16:00.730 Len Santiago (StudioLAB): So that’s the business understanding. And then, of course, the greatest challenge of any AI project is the data. It’s like, you know, the big monster in the room. Everything points back to data. The data understanding, the data preparation, and then, ultimately, the model development.
110 00:16:00.730 ⇒ 00:16:12.080 Len Santiago (StudioLAB): the evaluation of those models, and then, of course, the opera… oper… operationalization? I can’t say that today, the deployment will make it easy.
111 00:16:12.080 ⇒ 00:16:29.150 Len Santiago (StudioLAB): And then, you know, beyond that, models change as new data comes in. There’s model drift, there’s data drift, so there’s a forever maintenance to ensure that these automations are accurate in the world of machine learning.
112 00:16:30.570 ⇒ 00:16:39.299 Len Santiago (StudioLAB): I think that… so that’s kind of the execution framework that I bring, and then there’s a whole bunch of other endpoints.
113 00:16:39.780 ⇒ 00:16:40.270 Len Santiago (StudioLAB): You know.
114 00:16:40.270 ⇒ 00:16:41.369 Amber Lin: That’s cool.
115 00:16:41.630 ⇒ 00:16:42.020 Len Santiago (StudioLAB): Yeah.
116 00:16:42.020 ⇒ 00:16:53.460 Amber Lin: Okay, so how long were those projects for? You mentioned you worked, at Werner Bros for about 2 years. Were… were those both, like, 2-year-long projects, or month-long projects?
117 00:16:53.460 ⇒ 00:17:07.589 Len Santiago (StudioLAB): Automated localization started the day that I started in June of 2024, and it’s going to go, we deployed our first, soft test phase,
118 00:17:08.510 ⇒ 00:17:24.140 Len Santiago (StudioLAB): you know, in a kind of sandbox environment, it’s working for Marvel Studios, but it’s going to continue. So the idea is that this is going to be accepted and implemented throughout all the different divisions, so, like, Lucasfilm, ILM, Walt Disney Animation.
119 00:17:24.280 ⇒ 00:17:39.509 Len Santiago (StudioLAB): We’re doing a soft phase, a soft phased approach, but 2 years, 2 years plus, and then the VFX project, was about a solid year. We’ve wrapped that up in January of this year.
120 00:17:39.510 ⇒ 00:17:46.160 Len Santiago (StudioLAB): And prior to that, there was about 6 months of stakeholder alignment on understanding, like.
121 00:17:46.650 ⇒ 00:18:04.259 Len Santiago (StudioLAB): you know, could we, should we, and those parts, right? Understanding the funding, doing the evaluation with existing LLMs out there, multi-model systems that exist, you know, could we build it in-house? So, you know, we really did our due diligence on that.
122 00:18:04.480 ⇒ 00:18:17.299 Len Santiago (StudioLAB): Yeah, so I just want to say I have a hard stop at 1.30, that I can’t… I could not get out of. So, hopefully we can accomplish what we… what we set up for.
123 00:18:17.300 ⇒ 00:18:23.409 Amber Lin: I’ll make sure that there’s time for you to ask questions as well. I’m just very curious about your experiences.
124 00:18:23.410 ⇒ 00:18:25.020 Len Santiago (StudioLAB): Absolutely!
125 00:18:25.300 ⇒ 00:18:35.570 Amber Lin: Yeah, I think the follow-up question on the project you described, you mentioned you were playing the more project management role on these projects.
126 00:18:35.660 ⇒ 00:18:45.989 Amber Lin: Who would you collaborate with with, say, the architecture of… what was the ownership like on those projects, and what did you own and what did you not own?
127 00:18:48.660 ⇒ 00:19:08.239 Len Santiago (StudioLAB): my ownership was the delivery and acceptance of these solutions. So, my team is made up of a machine learning team with a data scientist, a data analyst, and about 7 or 8 machine learning engineers that are globally distributed.
128 00:19:08.490 ⇒ 00:19:19.030 Len Santiago (StudioLAB): I have a ML manager, machine learning manager, that really works to kind of orchestrate on the technical level with that team. That’s the direct report.
129 00:19:19.170 ⇒ 00:19:25.710 Len Santiago (StudioLAB): But on a product level, I run, like, the scope and all of that, so…
130 00:19:25.760 ⇒ 00:19:38.609 Len Santiago (StudioLAB): it’s a mix of product and project management, and then outside of that, there are the stakeholders on multiple fronts. There’s the ultimate stakeholder that is, like, the…
131 00:19:38.610 ⇒ 00:20:01.190 Len Santiago (StudioLAB): the director of the film, the executive over that post-production wing or department, and then there are some others. And actually, the projects that I just described were featured by Bob Iger twice in the last couple of months. We had our annual shareholders meeting before he left the company after many years, and
132 00:20:01.240 ⇒ 00:20:04.990 Len Santiago (StudioLAB): He showcased our projects in that worldwide meeting.
133 00:20:04.990 ⇒ 00:20:29.990 Len Santiago (StudioLAB): And then we were also showcased in our AI summit. We had, like, a thousand executives fly in from all over the world, and we’re just so proud. I will say that my team… there’s a lot of AI going around, experimentation, right, in the company, but my team is consistently delivering real, tangible products that are being accepted and used day-to-day in our operations.
134 00:20:29.990 ⇒ 00:20:32.040 Len Santiago (StudioLAB): So I feel really, really lucky.
135 00:20:33.220 ⇒ 00:20:34.040 Len Santiago (StudioLAB): Yeah.
136 00:20:35.020 ⇒ 00:20:38.060 Amber Lin: Awesome. We have 10 minutes left, so…
137 00:20:38.060 ⇒ 00:20:39.830 Len Santiago (StudioLAB): I want to get the time to use it.
138 00:20:39.830 ⇒ 00:20:41.020 Amber Lin: Ask me questions.
139 00:20:41.020 ⇒ 00:20:41.850 Len Santiago (StudioLAB): I’m happy to…
140 00:20:41.850 ⇒ 00:20:43.880 Amber Lin: more questions, but I’ll put them down the.
141 00:20:43.880 ⇒ 00:20:46.960 Len Santiago (StudioLAB): I’m happy to meet with you again, as well, if you’d like.
142 00:20:48.490 ⇒ 00:20:51.289 Amber Lin: Of course, but feel free to ask away.
143 00:20:51.290 ⇒ 00:20:52.050 Len Santiago (StudioLAB): Okay.
144 00:20:52.400 ⇒ 00:20:54.570 Len Santiago (StudioLAB): Let’s see here,
145 00:20:58.330 ⇒ 00:21:03.959 Len Santiago (StudioLAB): So, who would be… my hiring manager. Who’s… who’s my boss?
146 00:21:04.850 ⇒ 00:21:12.089 Amber Lin: I think your boss would… be either the strategy lead, or whatever
147 00:21:12.250 ⇒ 00:21:22.560 Amber Lin: Sorry. To… to clarify, I just asked Kayla, I want to confirm what role are we hiring you for? So, to clarify, we’re… we are hiring you for
148 00:21:22.560 ⇒ 00:21:35.600 Amber Lin: A client success owner, which I think I described earlier, someone that owns a relationship with the clients, and also essentially helps scope out the project, make sure things get delivered. So, very similar to
149 00:21:35.600 ⇒ 00:21:42.529 Amber Lin: your ownership before, and I think you would directly report to our CEO.
150 00:21:42.810 ⇒ 00:21:45.759 Len Santiago (StudioLAB): Okay, that’s what I thought.
151 00:21:45.900 ⇒ 00:21:50.740 Len Santiago (StudioLAB): Who does the role directly… or indirectly manage.
152 00:21:51.340 ⇒ 00:21:58.019 Amber Lin: So, this is based on projects, so you will manage the team,
153 00:21:58.330 ⇒ 00:22:16.260 Amber Lin: on that client. And so that would include, depending on what type of the project is, engineers, we’re analysts, so whoever’s on that project, usually between, 2 to 5 people would be under your management.
154 00:22:16.400 ⇒ 00:22:24.420 Len Santiago (StudioLAB): Okay, thanks. And how long would you say the average project or initiative lasts with any one of your clients?
155 00:22:24.710 ⇒ 00:22:40.050 Amber Lin: Cool. So, usually our clients start out… when we first acquire the clients, it’s usually a slightly smaller and shorter discovery project, which usually lasts about a month, two months, and then we sign the full-on project, which usually
156 00:22:40.050 ⇒ 00:22:46.250 Amber Lin: Last 6 months to, maybe 9 or 12 months, but 6 months is the standard.
157 00:22:46.790 ⇒ 00:22:49.479 Len Santiago (StudioLAB): Okay, that’s, that’s great, thanks for that.
158 00:22:49.880 ⇒ 00:22:55.830 Len Santiago (StudioLAB): Could you describe some of the delivery breakdowns that happened today?
159 00:22:56.090 ⇒ 00:23:01.940 Len Santiago (StudioLAB): Have there been any client issues that… You’re looking to improve.
160 00:23:02.050 ⇒ 00:23:06.939 Len Santiago (StudioLAB): For that success, That we’re all looking for?
161 00:23:07.630 ⇒ 00:23:23.550 Amber Lin: Gotcha. I think the… you’re kind of looking for where the brave points are, kind of where… were challenged the most right now. Yeah. I think our main challenge is, as we take on bigger clients, as we’ve grown a lot in the past year.
162 00:23:23.690 ⇒ 00:23:43.230 Amber Lin: we want to be more polished in our delivery. We want to have… since the projects are bigger, the stakes are higher, and the client has more expectations, because they’re paying more money, of how work is delivered, when work, and what work is delivered. I think we always deliver good work.
163 00:23:43.320 ⇒ 00:24:02.369 Amber Lin: But in terms of having proper alignment, having things polished, and having clear communication checkpoints every step of the way, those are things that significantly improve how the clients feel and perceive us.
164 00:24:02.490 ⇒ 00:24:08.519 Amber Lin: And… That they’re easy wins that we have yet to do.
165 00:24:10.080 ⇒ 00:24:19.139 Len Santiago (StudioLAB): Great. Makes a lot of sense. I could see, absolutely see why. That’s, like, the common thread. People want to keep their customers happy, they want to deliver on time.
166 00:24:19.260 ⇒ 00:24:25.919 Len Santiago (StudioLAB): At the budget that they agreed to, right? And ultimately solve the problem, deliver the solution.
167 00:24:29.150 ⇒ 00:24:33.699 Len Santiago (StudioLAB): what types of AI solutions would you say
168 00:24:34.260 ⇒ 00:24:46.969 Len Santiago (StudioLAB): Brainforge is known for? Like, what are the one, two, or three number one type of product deliveries that you guys are doing? Maybe you can give me an example with a specific customer that you have.
169 00:24:47.360 ⇒ 00:25:04.290 Amber Lin: I see. Ai is one of our branches. Ultimately, we’re not a product company, we’re a service company, so if we do deliver any products, it’s product as a service, so it’s very tailored to this customer, and we…
170 00:25:04.460 ⇒ 00:25:15.250 Amber Lin: We won’t sell… the product, say, as a SaaS. So, for example, on our AI branch, there’s…
171 00:25:15.420 ⇒ 00:25:17.269 Amber Lin: A group of clients that
172 00:25:17.460 ⇒ 00:25:32.669 Amber Lin: overlap with the data client. So we’ve set up the data system for them, set up the data models, and now they want to have AI dashboarding. They want to have the ability to ask AI questions about their data. So parts of that is
173 00:25:32.770 ⇒ 00:25:42.299 Amber Lin: Helping them set up AI dashboarding tools, helping them, create AI context based on their models. So that’s very data-related AI work.
174 00:25:42.560 ⇒ 00:25:50.860 Amber Lin: And then there’s a separate, more traditional AI product, like, AI work, which is, for example.
175 00:25:51.320 ⇒ 00:25:55.610 Amber Lin: Based on a client’s knowledge base, creating a…
176 00:25:55.850 ⇒ 00:26:13.779 Amber Lin: chatbot or AI interface that can answer questions while their customer representatives are on call, or help them look at, unify their scattered internal information, and help them look up things by just asking questions.
177 00:26:13.780 ⇒ 00:26:14.210 Len Santiago (StudioLAB): Sure.
178 00:26:14.210 ⇒ 00:26:28.959 Amber Lin: So, a lot of our work… yes, a lot of our work overlaps with our data work, because that’s our… I think that’s our competitive advantage, because we know how to work the data for AI. So, I think a lot of the work that you do
179 00:26:29.260 ⇒ 00:26:32.270 Amber Lin: Would still overlap with the data side.
180 00:26:32.620 ⇒ 00:26:34.440 Len Santiago (StudioLAB): Sure, absolutely.
181 00:26:34.630 ⇒ 00:26:42.350 Len Santiago (StudioLAB): as I mentioned, data is, like, half of the problem, right, with AI. The modeling is the…
182 00:26:42.390 ⇒ 00:26:59.639 Len Santiago (StudioLAB): easy part, you know, it’s still complex and needs to be evaluated, but it’s all about the data gathering, right? Getting the right data, and then the data preparation is absolutely key. Without that, you don’t really… you’re gonna end up with a very weak model and output that’s a waste of time, you know?
183 00:26:59.660 ⇒ 00:27:05.040 Len Santiago (StudioLAB): Okay, great. That’s, that certainly helps. Awesome.
184 00:27:05.040 ⇒ 00:27:06.259 Amber Lin: I have one last question.
185 00:27:06.650 ⇒ 00:27:26.409 Amber Lin: That’s not real… not complete, like, interview-related, but I like to ask this on every call with people, is, is there something outside of work that you stuck with, like, something not related to professional life that gives you energy, or something that you kept doing for many years?
186 00:27:27.090 ⇒ 00:27:34.859 Len Santiago (StudioLAB): I would absolutely say… fitness is super important to me. I…
187 00:27:35.420 ⇒ 00:27:46.479 Len Santiago (StudioLAB): I, you know, I’m at the gym, or I’m doing yoga, or I’m running, or I’m hiking, you know, I just… I love to be active.
188 00:27:46.480 ⇒ 00:27:55.530 Len Santiago (StudioLAB): So that’s something that I have done, I mean, since I was, like, a kid in school, you know, teenager in college, high school, all of that.
189 00:27:55.910 ⇒ 00:28:08.509 Len Santiago (StudioLAB): Yeah, it’s a big part of my life, it’s a part of my well-being. I think why I’ve been successful, is, you know, just having a clear mind and energy, running, all of that. I absolutely love to travel the world.
190 00:28:09.250 ⇒ 00:28:12.619 Len Santiago (StudioLAB): I’ve been to about 30 different countries.
191 00:28:12.900 ⇒ 00:28:17.099 Len Santiago (StudioLAB): Mostly in Europe and Latin America. I speak Spanish, I’m bilingual.
192 00:28:17.530 ⇒ 00:28:24.910 Len Santiago (StudioLAB): And, yeah, just… I mean, with that comes…
193 00:28:25.570 ⇒ 00:28:30.549 Len Santiago (StudioLAB): food. I’m a big foodie. Big foodie.
194 00:28:30.550 ⇒ 00:28:31.390 Amber Lin: Huh.
195 00:28:31.390 ⇒ 00:28:35.259 Len Santiago (StudioLAB): As I travel, and I actually do quite a bit of cooking when I have time, and, you know.
196 00:28:35.260 ⇒ 00:28:36.570 Amber Lin: Oh, awesome.
197 00:28:36.910 ⇒ 00:28:41.669 Amber Lin: You’ll, you’ll… if you were to join us, you’ll find out, half of the company.
198 00:28:41.670 ⇒ 00:28:42.070 Len Santiago (StudioLAB): Yeah.
199 00:28:42.070 ⇒ 00:28:44.490 Amber Lin: cooking analogies. It’s very, it’s very funny.
200 00:28:44.490 ⇒ 00:28:51.130 Len Santiago (StudioLAB): Oh, that’s great. I love it. I love it. Yeah, I was obsessed with Food Network at one point, you know.
201 00:28:51.130 ⇒ 00:28:51.520 Amber Lin: Oh.
202 00:28:51.520 ⇒ 00:29:06.130 Len Santiago (StudioLAB): A long time ago. And I actually learned a lot, I have to say, from, you know, watching a lot of it back, you know, maybe, like, 10, 15 years ago. I used to love Rachel Ray and, like, the Barefoot Contessa, Ina Gardner, and…
203 00:29:06.130 ⇒ 00:29:06.810 Amber Lin: Oh, okay.
204 00:29:06.810 ⇒ 00:29:10.070 Len Santiago (StudioLAB): But, yeah, that’s… that’s a little bit about me.
205 00:29:10.070 ⇒ 00:29:26.270 Amber Lin: Alright, we’re perfectly at time, so thank you for coming to the call today. I enjoyed learning about your experience, and the operations team will reach out, and they’re pretty fast, so one week max, two weeks, no matter what the decision is, so you’ll hear back from us soon.
206 00:29:26.510 ⇒ 00:29:32.990 Len Santiago (StudioLAB): Thank you, Amber. Really enjoyed the conversation, have a great weekend, and I definitely look forward to keeping the conversation going.
207 00:29:32.990 ⇒ 00:29:34.650 Amber Lin: Alright, have a good afternoon.
208 00:29:34.650 ⇒ 00:29:35.380 Len Santiago (StudioLAB): Thanks so much.
209 00:29:35.380 ⇒ 00:29:36.100 Amber Lin: Bye!
210 00:29:36.100 ⇒ 00:29:36.780 Len Santiago (StudioLAB): Bye-bye.