Meeting Title: Uttam_Harshit’s Personal Meeting Room Date: 2024-12-12 Meeting participants: Uttam Kumaran, Harshit Singh
WEBVTT
1 00:00:44.110 ⇒ 00:00:44.990 Uttam Kumaran: Hello!
2 00:00:54.100 ⇒ 00:00:55.040 Uttam Kumaran: Can you hear me?
3 00:01:03.031 ⇒ 00:01:05.200 Uttam Kumaran: I can’t hear you first.st Can you hear me?
4 00:01:05.699 ⇒ 00:01:08.730 Harshit Singh: Yeah, audible. I’m out, hey? Hi, how are you?
5 00:01:09.290 ⇒ 00:01:11.019 Harshit Singh: Yeah, I’m good. What about you?
6 00:01:11.300 ⇒ 00:01:15.429 Uttam Kumaran: Good. Thank you for taking the time. Sorry it’s it’s taken a while to get on the phone.
7 00:01:16.386 ⇒ 00:01:17.360 Harshit Singh: Noise, row.
8 00:01:18.750 ⇒ 00:01:20.320 Uttam Kumaran: How’s everything? How’s the week going.
9 00:01:21.455 ⇒ 00:01:24.459 Harshit Singh: Weeks been quite productive and quite hectic. So.
10 00:01:24.460 ⇒ 00:01:25.740 Uttam Kumaran: Hey? Tell me about it?
11 00:01:25.820 ⇒ 00:01:27.610 Uttam Kumaran: What’s the what’s the most hectic thing.
12 00:01:28.370 ⇒ 00:01:37.400 Harshit Singh: What’s the most active thing? Nothing. I was just building some few projects, working on some side projects or contributing to some open source projects so.
13 00:01:37.560 ⇒ 00:01:44.049 Harshit Singh: and some work. So that what? So that is what led to being? It’s a little bit more productive and hectic.
14 00:01:44.560 ⇒ 00:01:45.300 Uttam Kumaran: Okay.
15 00:01:45.870 ⇒ 00:01:50.459 Uttam Kumaran: Nice. Any plans for I don’t. Where are you based? By the way.
16 00:01:51.380 ⇒ 00:01:52.840 Harshit Singh: I’m based from India.
17 00:01:53.120 ⇒ 00:01:54.330 Uttam Kumaran: Where in India.
18 00:01:54.560 ⇒ 00:01:55.750 Harshit Singh: Delhi.
19 00:01:56.020 ⇒ 00:01:57.669 Uttam Kumaran: New Delhi. Yeah.
20 00:01:57.670 ⇒ 00:02:02.980 Uttam Kumaran: okay. All my family is in double knotted. But I grew up here in the Us.
21 00:02:03.100 ⇒ 00:02:05.529 Uttam Kumaran: My parents and family are here, but
22 00:02:05.560 ⇒ 00:02:08.940 Uttam Kumaran: I go there almost like every year, every other year, usually so.
23 00:02:10.370 ⇒ 00:02:11.450 Harshit Singh: Yes.
24 00:02:11.640 ⇒ 00:02:19.340 Uttam Kumaran: How’s the whole? How’s the year been? So tell me about like I don’t know. I guess we’ve been changing you know, emails. But I guess
25 00:02:19.620 ⇒ 00:02:38.300 Uttam Kumaran: I don’t know how, if you’ve taken a look at Brainforge. But I think we talked a little bit about back and forth. So you kind of know a little bit about what we do. I guess. Give me a sense of i 1 thank you for answering the questions. I really appreciated that. Tell me a little bit about like what you’re working on right now, and like what you’re interested in doing, and
26 00:02:38.570 ⇒ 00:02:42.849 Uttam Kumaran: would love to tell you about some of the projects we have, and see whether there’s opportunity to work together.
27 00:02:44.547 ⇒ 00:03:13.549 Harshit Singh: Currently, I’m building, currently, I’m working on building towards creating AI Chatbots and solutions. So recently, I did a project. So I’ll call it, basically personal project wherein I built a chatbot which helps you, you know, customize emails. And you know, make them a better prompt. I use the mixed on 8 x 7 b. Model, which is way better when compared to Gemini or Chatgpt for text integration.
28 00:03:13.690 ⇒ 00:03:39.100 Harshit Singh: And and in that, when you are when you give a prompt such as passing through an email and say that make it a little bit more casual, or you know, do it like, make it a little, make it a little bit more formal. It does it very efficiently. It does it very smoothly, so I am working towards making such such solution, wherein I, wherein that could actually help people out there.
29 00:03:39.150 ⇒ 00:03:50.809 Harshit Singh: And, as you know, there’s a boom right now in the market leading to every AI solution leading to. And that is what excited me about the the idea of brain brain forge is
30 00:03:50.820 ⇒ 00:03:52.110 Harshit Singh: is working towards.
31 00:03:52.836 ⇒ 00:04:00.249 Harshit Singh: So yeah, I’m currently working and building in more full stack. And the AI solutions.
32 00:04:00.440 ⇒ 00:04:02.620 Harshit Singh: If that makes sense.
33 00:04:02.890 ⇒ 00:04:09.610 Uttam Kumaran: Yeah, that makes sense. So are you? I just I saw on your linkedin. So you Gra, you just graduated this past. This past may.
34 00:04:11.210 ⇒ 00:04:11.770 Harshit Singh: Yeah.
35 00:04:12.130 ⇒ 00:04:19.009 Uttam Kumaran: Okay, okay, are you? And are you just? You’re currently in like internships, or where are you right now? In terms of like job search and everything. You’re just not.
36 00:04:19.019 ⇒ 00:04:19.589 Harshit Singh: Okay.
37 00:04:19.589 ⇒ 00:04:20.299 Uttam Kumaran: Full time.
38 00:04:21.357 ⇒ 00:04:31.779 Harshit Singh: Yes, I am looking for full time, but I do actually contribute to some open source projects and make projects up on the side. But I do looking for like a full time job.
39 00:04:32.210 ⇒ 00:04:48.029 Uttam Kumaran: Okay, cool. Yeah. So we so we have a couple of different sort of angles for AI work that we do. So we have both internal operations and automations work, and then we also do customer facing so customer facing. You’ll think of like chat boss and voice agents.
40 00:04:48.030 ⇒ 00:05:02.610 Uttam Kumaran: and then for internal you can think of like AI copilots, knowledge, base rag things like that. Is there any particular sort of like AI solution that’s interesting to you out of the others like again, we do everything from
41 00:05:02.610 ⇒ 00:05:19.829 Uttam Kumaran: using, like Zapier to slack to Openai for automations. We do a lot of rag related stuff, a ton of rag related work using, make that sort of stuff using relevance. Is there? We’re starting to do some stuff in voice.
42 00:05:19.830 ⇒ 00:05:37.939 Uttam Kumaran: Is there anything in particular, that, like you’re super interested in within, like the broad, like AI sort of like set of capabilities. And to give you deeper question, like, of course, you know, like the full stack. AI, so you have, like your base language models, you could do fine tuning.
43 00:05:37.940 ⇒ 00:05:55.630 Uttam Kumaran: You have actually, like knowledge, retrieval embeddings, vector databases you then almost have, like Ui for AI, which is like, how do you actually chat and interact? There’s building agents. There’s also building tools. So tell me, like, what part of the stack you’re like most interested in in working in.
44 00:05:56.981 ⇒ 00:06:22.070 Harshit Singh: I’m definitely more interested in working towards the Zapier slack, or you can see the open AI, mainly because you know, that is where you can see the actual stuff happening as as using Zapier, the one could get more leads. And you know, those leads could actually turn into customers that could that could eventually help the business. So I’m more interested in working towards the Zapier, the slack, and especially the especially the open AI
45 00:06:22.080 ⇒ 00:06:35.400 Harshit Singh: Openai, mainly due to the fact that since it is, you know, on the boom, and since it is launching new models every time and using, Openai would eventually make the Chatbot more feel more natural
46 00:06:35.440 ⇒ 00:06:40.710 Harshit Singh: and not feel a very automated chat board through which no one would like to talk
47 00:06:40.730 ⇒ 00:06:49.459 Harshit Singh: so definitely. These are the 3 section. I am very interested, but I am also open to voice in the in the future, and rag.
48 00:06:50.700 ⇒ 00:06:55.930 Uttam Kumaran: And so you you mainly did work. So your past work has all been like front end related right? Like, what sort of skills
49 00:06:55.950 ⇒ 00:07:00.549 Uttam Kumaran: did you use in front end, like, what sort of programming languages and frameworks are you familiar with.
50 00:07:01.730 ⇒ 00:07:12.790 Harshit Singh: Right. So so all parts of my work has been a both front end and full stack where in I have been involved using react.
51 00:07:12.910 ⇒ 00:07:25.039 Harshit Singh: And and I did a lot of site stuff in in it, and I also use a little bit of pi so my last last internship. I had to make a 1 chat board for the company wherein I had to turn in leads.
52 00:07:25.090 ⇒ 00:07:41.360 Harshit Singh: And the chat was what was basically that any user that would come onto it would like to say that I want to search up these these products and that and that products will be shown related. And consider that as a
53 00:07:41.370 ⇒ 00:07:47.470 Harshit Singh: Amazon database wherein you wherein you search for a thing, and there are related things like showing up.
54 00:07:47.720 ⇒ 00:07:55.649 Harshit Singh: So I had to make a chatbot for that cus, make it mobile, friendly, and do the all, and do all the front end things along with making it a Chatbot.
55 00:07:55.850 ⇒ 00:08:04.799 Harshit Singh: So all my past experience has been has been a mix of front end full stack, a little bit of back end, a platform. AI also.
56 00:08:04.920 ⇒ 00:08:05.770 Harshit Singh: So yeah.
57 00:08:06.330 ⇒ 00:08:11.520 Uttam Kumaran: Are you more interested in back end, over front, end, or like? Where do you think your your interest is?
58 00:08:11.550 ⇒ 00:08:25.790 Uttam Kumaran: Because for our work, you know, I think we’re gonna need a lot more. We need people, we need basically like application development on like AI stuff. So actually building on building agents and building workflows. But you also need some back and help basically like, where do we host
59 00:08:26.088 ⇒ 00:08:40.869 Uttam Kumaran: like a vector stores? Where do we host back end databases for some of applications. I saw that you had done, you know, work with Docker. And some of these, like, you know, basically a lot of like back end sort of container work like, where where are you? Kind of like most interested in.
60 00:08:42.453 ⇒ 00:09:00.670 Harshit Singh: If I would have to say I would say I am. In the range of 50, 50, or 60, 40, you would say, I would definitely pick front end 1st if I was given the opportunity. But I am very comfortable with backend, too, because back end is back end is what makes the front end work.
61 00:09:00.690 ⇒ 00:09:05.859 Harshit Singh: So I’m def. So I’m definitely more more comfortable with both front end and back end.
62 00:09:06.160 ⇒ 00:09:07.510 Harshit Singh: And yeah.
63 00:09:08.780 ⇒ 00:09:23.579 Uttam Kumaran: And so even on your site, you know the the work you did with everything is like kind of hosted on vercel. And like, you know, I kind of clicked around a lot of them. So you designed the app. You designed all the apps. And then you also implemented basically everything in full stack.
64 00:09:24.430 ⇒ 00:09:25.290 Harshit Singh: Right.
65 00:09:26.070 ⇒ 00:09:26.900 Uttam Kumaran: Okay, okay.
66 00:09:27.720 ⇒ 00:09:51.239 Uttam Kumaran: okay, okay, great. So one of the things like we, we’re starting to interview, you know, for more AI engineers. Currently, we have a couple of other people that are in pipeline. We do have like a technical interview process that we usually ask folks to go through. I know I I wanted to connect you with our head of AI engineering. He’s just been really busy, literally in the last 3 weeks. We just have a bunch of clients that we’re working on
67 00:09:51.530 ⇒ 00:10:13.629 Uttam Kumaran: So how about i? 1 thing, I wanna I wanna we’re just finalizing our job description and our interview process for that role. I would love to kind of give you a chance to take a crack at that interview process. And kind of see where you’re most interested. The kind of the key areas we have a lot of we need a lot more help in is one is definitely on like building basic front ends. So again, we
68 00:10:14.040 ⇒ 00:10:27.949 Uttam Kumaran: we’re not. We’re not gonna be using for a lot of these apps. The actual chat bots that come out of the box. We’ll be developing our own front end as well as back end, and then we provide the actual Apis for the agents to discuss. So we do need some help.
69 00:10:28.328 ⇒ 00:10:44.079 Uttam Kumaran: There. The other thing that we need. You know, some more help on is people to learn more stuff around knowledge, retrieval rag, and like embedding and and vector, indexing. So that’s where we we need a lot more help.
70 00:10:44.338 ⇒ 00:10:58.060 Uttam Kumaran: So that seems interesting to you. I can. I’m happy to, you know, sort of move you to the next phase and kind of give you a chance at the technical interview. And maybe you can take a crack at that. We don’t need a you know. We’re not building
71 00:10:58.060 ⇒ 00:11:14.949 Uttam Kumaran: in some sense, we’re not building like a lot of full stack apps. So really, we may need some help more on the AI, and then the front end side. Really but all these apps. We want to host either heroku or vercel and make available like we probably have to include off and stuff like that. For some of our clients. So.
72 00:11:17.350 ⇒ 00:11:20.129 Harshit Singh: Yeah, that sounds perfect. I would like to be a part of it.
73 00:11:20.460 ⇒ 00:11:45.849 Uttam Kumaran: Okay, cool. So how about so right now, it’s we’re kind of in a very busy period. So give me like a week or 2 to kind of follow up with a technical interview. But again, I really appreciate. You know, your initial email and the persistence. So I know it’s hard to find a job right now in engineering. So again, hopefully, you know it works out here. But however, I could be helpful otherwise, please let me know.
74 00:11:46.740 ⇒ 00:11:55.399 Harshit Singh: Yeah, gladly. I mean, I mean, I saw what the company was doing, and I was passionate. So I went up and saw and through an email. And gladly you replied.
75 00:11:55.600 ⇒ 00:11:56.600 Harshit Singh: so yeah.
76 00:11:57.140 ⇒ 00:12:02.480 Uttam Kumaran: Totally. And then is there any questions you have? For me? While we have some more time.
77 00:12:03.710 ⇒ 00:12:15.329 Harshit Singh: Yes, in fact, I was reading. I was reading and studying about the company, so I would definitely want to know, like, what is the one or 2 year end goal, like by the like. What is the future? Goals.
78 00:12:16.970 ⇒ 00:12:26.745 Uttam Kumaran: Yeah, it’s a good question. So for us, really, the we’re going. We’re moving from a phase of, you know, I was working on a lot of projects. We’ve hired a good amount of people right now, we’re scaling up
79 00:12:27.230 ⇒ 00:12:32.680 Uttam Kumaran: we’re hiring more engineers, and we’re actually implementing a lot more process. So how do we actually run
80 00:12:32.720 ⇒ 00:12:48.542 Uttam Kumaran: an AI team? How do we run a data team? How do we run an engineering organization? And then also, how do we? How do we improve the ability for us to take on more clients? So we have strict project management guidelines. So that’s really the phase we’re in right now is we basically wanna almost
81 00:12:49.250 ⇒ 00:13:12.850 Uttam Kumaran: 2 or 3 x our revenue next year. And basically to do that, we need to rely a lot more on process and standardization right now. It’s a little bit crazy. And you know, we’re only like a 2 year old company, almost. So we’re starting to standardize a lot more, have clear requirements about when we take on work, and then the work is executed and also build like an engineering culture. So those are like our probably key, like short term
82 00:13:13.060 ⇒ 00:13:14.040 Uttam Kumaran: goals.
83 00:13:16.320 ⇒ 00:13:18.729 Harshit Singh: Makes sense, makes sense, it clears it out.
84 00:13:20.170 ⇒ 00:13:20.860 Uttam Kumaran: Cool.
85 00:13:21.030 ⇒ 00:13:38.359 Uttam Kumaran: Okay? All right. Well, if no other questions, then yeah, let me follow up with you sometime in the next 2 weeks, and we’ll kind of get you over an interview process. We’re just working on that now. So thanks for the patience. And yeah, I really appreciate the time and the and the, you know, listening to the spiel about Brainforge. So.
86 00:13:39.180 ⇒ 00:13:41.070 Harshit Singh: Yeah, no. Issue, yeah.
87 00:13:41.460 ⇒ 00:13:43.120 Uttam Kumaran: Alright. Thank you so much.
88 00:13:43.610 ⇒ 00:13:44.800 Harshit Singh: Thank you. Bye-bye.