Meeting Title: Eden x Brainforge: Define Deliverables for Command Center Date: 2026-03-10 Meeting participants: Pranav Narahari, Daniel
WEBVTT
1 00:00:50.070 ⇒ 00:00:50.760 Pranav Narahari: Danny?
2 00:00:51.270 ⇒ 00:00:52.070 Daniel: What’s up, man?
3 00:00:52.860 ⇒ 00:00:54.559 Pranav Narahari: Nothing much. How’s your morning been?
4 00:00:55.890 ⇒ 00:00:56.280 Daniel: Good!
5 00:00:56.280 ⇒ 00:00:56.930 Pranav Narahari: Good.
6 00:00:57.240 ⇒ 00:00:58.180 Daniel: Kinda weird.
7 00:00:59.060 ⇒ 00:01:03.179 Pranav Narahari: Are you, are you based in Central, Eastern, Western?
8 00:01:03.180 ⇒ 00:01:08.799 Daniel: On Mountain in Denver. Oh, wow, the one that I missed, okay. You, East Coast with Robert?
9 00:01:08.800 ⇒ 00:01:10.749 Pranav Narahari: I’m East Coast, yeah, I’m in Massachusetts.
10 00:01:11.160 ⇒ 00:01:11.729 Daniel: Cool, man.
11 00:01:12.110 ⇒ 00:01:13.670 Pranav Narahari: Yeah. Yeah.
12 00:01:13.690 ⇒ 00:01:19.330 Daniel: I was, sorry, it’s been a busy morning, I didn’t get to respond to you until just, like, a few minutes ago.
13 00:01:19.520 ⇒ 00:01:26.740 Pranav Narahari: But, yeah, I was hopping in between meetings, was talking to Robert briefly, he’s, like, out of office this week.
14 00:01:26.740 ⇒ 00:01:27.700 Daniel: That’s what I figured.
15 00:01:27.700 ⇒ 00:01:32.900 Pranav Narahari: Yeah, yeah, so he hopped into a Slack with me, though, which was really helpful, kind of just, like.
16 00:01:33.360 ⇒ 00:01:42.819 Pranav Narahari: you know, just gave me a little bit more context, but I feel like I already kind of got the context, and we just looked through your presentation. Kind of wondering…
17 00:01:42.960 ⇒ 00:01:55.350 Pranav Narahari: I have, like, some ideas for how we can, like, structure the meeting a little bit, but, I know, like, you kind of wanted to set this up, like, is there something specifically, like, you wanted to refine on that, presentation, or how did you want to run things?
18 00:01:55.630 ⇒ 00:01:58.889 Daniel: I think… I think the overall impression
19 00:01:59.510 ⇒ 00:02:07.619 Daniel: is I’m putting together the business cases, right? So this is, like, things we could do with X, but I need help refining what that
20 00:02:07.880 ⇒ 00:02:12.610 Daniel: goal is, and I’m also trying to do some interpretation.
21 00:02:12.730 ⇒ 00:02:23.850 Daniel: My wife’s over at NVIDIA. They just launched this entire, like, augmented workflow. So I’m trying to, like, understand what… first of all, I know the art of the possible, and I know what that does.
22 00:02:24.390 ⇒ 00:02:28.899 Daniel: I don’t know technically what we need to do to build up the…
23 00:02:29.200 ⇒ 00:02:40.530 Daniel: data layers commensurate with opening these opportunities. So… From my basic understanding, If we build this… repository.
24 00:02:41.040 ⇒ 00:02:47.790 Daniel: Wherever it may be. Yep. If we have pre-cred… pre-credentialed access, that’s basically…
25 00:02:48.340 ⇒ 00:02:50.400 Daniel: taken care of by Google Workspace.
26 00:02:50.640 ⇒ 00:02:58.870 Daniel: So, I literally watch Sky at work, and what they do is they just go accept and install these tools, and then they get the access that they already had.
27 00:02:58.970 ⇒ 00:03:13.320 Daniel: through their typical IT administration. So, if they’re in the legal team, they would have access to legal files that the marketing team wouldn’t necessarily have access to, but the marketing team would have access to marketing contracts, so it sort of fits in these separate buckets.
28 00:03:13.910 ⇒ 00:03:15.380 Daniel: And then if you take all that.
29 00:03:15.610 ⇒ 00:03:18.170 Daniel: And you use, basically, a Gemini-based workflow.
30 00:03:18.770 ⇒ 00:03:23.370 Daniel: You can have pre-credentialed access, You log into Gemini.
31 00:03:24.130 ⇒ 00:03:29.569 Daniel: Log in with your company email. It opens up the world in terms of Google Workspace access.
32 00:03:30.270 ⇒ 00:03:36.379 Daniel: I already have that done for me. Like, I get to say, at Google Drive, pull the contract for whatever, right?
33 00:03:36.720 ⇒ 00:03:42.850 Daniel: But there’s a layer I’m missing there, which is access to our actual company data, which is coming from BQ.
34 00:03:43.180 ⇒ 00:03:46.650 Daniel: And from our biggest communication, which is Slack.
35 00:03:46.910 ⇒ 00:03:54.069 Pranav Narahari: Yeah. So the concept I’m really thinking about is how can we just build the foundational data layer that will allow us to put these UX tools on top of accessing that?
36 00:03:54.150 ⇒ 00:03:59.510 Daniel: primarily through leveraging, hopefully, a lot of the out-of-box Google Workspace functionality.
37 00:03:59.670 ⇒ 00:04:00.490 Pranav Narahari: Yep.
38 00:04:00.490 ⇒ 00:04:03.790 Daniel: And then if we did all of that, then I… getting the…
39 00:04:03.910 ⇒ 00:04:20.400 Daniel: you know, crazy thinking about opportunities and workflows we could use. Well, I mean, that would allow us access, if we have documented access points, that we could see who’s working with each other, who’s talking to each other. You can mind map this. I’ve been company… talking to a group called Worklytics that puts together these, like.
40 00:04:20.399 ⇒ 00:04:24.560 Daniel: Team functionality resourcing, and all of it is basically based off of
41 00:04:24.630 ⇒ 00:04:34.730 Daniel: okay, put any AI on top of your, you know, workspace, and you get this huge amount of exposure and functionality that’s unlocked. But I don’t know how to get to that
42 00:04:35.840 ⇒ 00:04:50.410 Daniel: basic foundational layers. That’s really what I wanted to talk through, because I don’t want to overcomplicate this, because we could make it way too difficult. We could start implementing bespoke tools, going far out of Google Workspace, and building out these, like, really complex data layers that are trying to.
43 00:04:50.410 ⇒ 00:04:51.070 Pranav Narahari: public.
44 00:04:51.070 ⇒ 00:04:56.090 Daniel: pre-think the data, and I don’t want to pre-think the data, I just want to have, basically, really.
45 00:04:56.200 ⇒ 00:05:02.720 Daniel: well-put-together documented data repositories and connectors that allow us to have this type of UX on top of it.
46 00:05:03.030 ⇒ 00:05:10.459 Pranav Narahari: Yeah, I mean, you’re bringing up all the same things that I wanted to talk about as well, and it’s essentially these…
47 00:05:10.730 ⇒ 00:05:19.470 Pranav Narahari: you’re right, like, the possibilities are endless after you have this layer about just building those, like, UX tools,
48 00:05:19.720 ⇒ 00:05:26.600 Pranav Narahari: I think what would be good here is, like, let’s define, like… because… and the possibilities are endless, honestly, at that point.
49 00:05:26.710 ⇒ 00:05:37.060 Pranav Narahari: But we shouldn’t go in thinking we want to build those endless tools. We should go in thinking about, let’s build the one that’s going to, like, really be the biggest value add.
50 00:05:37.180 ⇒ 00:05:42.280 Pranav Narahari: Or just, like, which one of these, and I know you mentioned a few, like, on this presentation,
51 00:05:42.630 ⇒ 00:05:49.969 Pranav Narahari: let’s, like… that layer’s gonna need to be built, so that we can build all the additional, like, UX workflows after.
52 00:05:50.200 ⇒ 00:05:54.299 Pranav Narahari: however, like, Now, let’s think about…
53 00:05:54.580 ⇒ 00:06:06.099 Pranav Narahari: what are the actual deliverables, what are the actual insights that it’s going to be giving? We talked a little bit about, like, a scheduled, like, every Friday or every, like, once a week type of insight.
54 00:06:06.520 ⇒ 00:06:14.139 Pranav Narahari: That sounds great. Why that sounds great is because, the connectors that we were talking about, where the data would be coming from, and you put it
55 00:06:14.370 ⇒ 00:06:23.869 Pranav Narahari: you, like, showed it pretty well, like, on this slide. Just, like, the augmented employee command center. So, like, the Google Suite, right? So, Gmail, Calendar, Google Docs,
56 00:06:24.440 ⇒ 00:06:34.150 Pranav Narahari: that all comes from Google. And then, yeah, BQ, and then Slack. I think bringing in all of that data, and then using that to then…
57 00:06:34.300 ⇒ 00:06:40.840 Pranav Narahari: drive some type of deliverable on a per-week basis, so we talked about… and I have it up right here…
58 00:06:43.290 ⇒ 00:06:52.690 Daniel: And I know I was pre-thinking some of that with the original command center. Obviously, this has, you know, iterated since as I start to understand the possibilities. The real goal, I think.
59 00:06:53.030 ⇒ 00:06:53.540 Pranav Narahari: Yeah.
60 00:06:53.540 ⇒ 00:06:56.199 Daniel: would be, I’m an administrator on everything, right?
61 00:06:57.800 ⇒ 00:06:59.730 Daniel: I have unlimited access.
62 00:06:59.940 ⇒ 00:07:00.470 Pranav Narahari: Yes.
63 00:07:00.470 ⇒ 00:07:08.039 Daniel: Theoretically So if all the data was in this place, where I had unlimited access to all these tools.
64 00:07:08.220 ⇒ 00:07:11.060 Daniel: I should be able to go in and ask, Hey!
65 00:07:11.280 ⇒ 00:07:17.099 Daniel: who is Ryan working with the most? Now, I know there’s anonymization, all this kind of… but conceptually, I should be able to do that.
66 00:07:17.100 ⇒ 00:07:18.739 Pranav Narahari: Right. You should recognize.
67 00:07:18.740 ⇒ 00:07:25.220 Daniel: Slack, and… Yeah, maybe even up to Figma on Monday, or whatever it is, right? And say, okay, well…
68 00:07:25.460 ⇒ 00:07:41.690 Daniel: you know, these are the types of interactions that group has, because if I can get to that myopic insight, then we can build out these really useful tools around the way of working premise, around data access. So before I get to any employee UX stuff, I mean, I’d love to just take my account and see, like.
69 00:07:42.030 ⇒ 00:07:55.539 Daniel: How could we experiment? Can I just ask Gemini, and it will pull up recent Slack messages, interacting with Google Docs, you know, feedback? It’ll think through all of that. I already know it will, because it does it for me, right?
70 00:07:55.590 ⇒ 00:08:03.169 Daniel: It’ll think through all of that if I just have all of the data in there. And so I think the first step here is, like, connecting our tools.
71 00:08:03.170 ⇒ 00:08:03.920 Pranav Narahari: Yes, yeah.
72 00:08:03.920 ⇒ 00:08:09.610 Daniel: So, so really, this discussion is more about how do we connect Slack
73 00:08:09.800 ⇒ 00:08:12.979 Daniel: and Zendesk into a repository, right?
74 00:08:13.170 ⇒ 00:08:24.670 Pranav Narahari: And so, yeah, so Zendesk is one that we didn’t talk about before, and I just want to make sure, like, for you, like, okay, is that, like, the biggest… is, like, that super important? Because…
75 00:08:24.670 ⇒ 00:08:34.810 Daniel: I don’t know, not really for me, necessarily, but as I think through, like, these big tools… so we use, like, Monday.com. It’s interesting, people kind of use it, I think…
76 00:08:34.990 ⇒ 00:08:53.289 Daniel: But I don’t trust it. It’s not updated enough. It’s all based on manual, right? So the one thing I like about Google Workspace is it’s got this really automated functionality. I can see meeting notes related to a meeting, and then you can tie it from a timestamp direct into a Google Doc being submitted for a project plan, and it does that automatically for me, even.
77 00:08:53.290 ⇒ 00:08:54.240 Pranav Narahari: Yeah.
78 00:08:54.240 ⇒ 00:09:09.379 Daniel: I can ask it, like, what meetings am I most productive in? And it’ll go analyze my Google Drive folders and say, well, from this meeting you created this. Based on the meeting notes that we automatically took in, you had X amount of emails that were sent out as a result. Like, it’ll go to that in-depth analysis.
79 00:09:09.380 ⇒ 00:09:14.590 Daniel: I’m just missing visibility on a couple of tools, Slack being the primary tool.
80 00:09:14.590 ⇒ 00:09:26.380 Pranav Narahari: Yeah. I think that’s what we do. I think, you know, you talked about how, like, for your own assistant, kind of that you have, like, or your own workflow that you set up, you have, like, the Google Suite. Yeah. Let’s add Slack, let’s add BigQuery.
81 00:09:26.380 ⇒ 00:09:38.749 Pranav Narahari: And then let’s just, like, knock those two out of the park, because part of this is, like, the data connection, but then it’s also, like, how do we use that context properly? And so, like, bringing in all these connections is not as simple as just, like.
82 00:09:38.750 ⇒ 00:09:48.150 Pranav Narahari: Okay, just piping in the data, like, we need to know, like, what data are we bringing, how are we gonna use this properly as additional context, or else it’s just going to… it’s just gonna muddle the pot.
83 00:09:48.150 ⇒ 00:09:59.350 Pranav Narahari: And that’s not what we want. And that’s, like, the fear of, like, bringing in too many different connections and not allocating enough time to using that data properly.
84 00:09:59.350 ⇒ 00:10:09.580 Pranav Narahari: And so, I think you mentioned how Slack is, like, that’s where all the comms are happening. Most companies are the same way. Let’s knock that one out of the park, and I feel like that’s going to drive
85 00:10:09.840 ⇒ 00:10:26.210 Pranav Narahari: the majority of the insights that the final deliverable is going to have anyways. Down the line, you know, integrating Zendesk properly, giving it the proper allocation of, like, weight as well, maybe is beneficial, but it seems like Slack is the main one, right? So let’s…
86 00:10:26.260 ⇒ 00:10:31.680 Daniel: It also seems to me that it will simplify if we just think about me, and we think about my job.
87 00:10:32.160 ⇒ 00:10:32.650 Pranav Narahari: Mmm.
88 00:10:32.650 ⇒ 00:10:41.359 Daniel: What we can do from there is use the learnings through that process to enhance other workflows. That’s where I really want to go. I really do want to redefine, like, I would love…
89 00:10:41.760 ⇒ 00:10:50.139 Daniel: future state for this is my employees open up an Eden OS command center that has all the connected tools.
90 00:10:50.140 ⇒ 00:11:06.489 Daniel: It integrates my project management tools, does meeting assessments, it’ll recognize, hey, you have a meeting with Adam coming up in 30 minutes. I’ve pulled up the notes from your last weekly and, you know, redefined, here’s your current progress based on these workflows. That is possible, and I know it’s possible because I’m doing it right now.
91 00:11:06.490 ⇒ 00:11:09.279 Daniel: I just don’t have exposure to the Slack comms.
92 00:11:09.460 ⇒ 00:11:22.170 Pranav Narahari: Right. Yeah, I mean, I like that. Like, in terms of progression, too, like, we should definitely just focus on your workflows, especially since, like, you also know, like, what you’re getting right now. And so, like, bringing in Slack, bringing in BigQuery, like.
93 00:11:22.170 ⇒ 00:11:29.960 Pranav Narahari: you’ll be able to say, like, okay, is this actually adding any benefit? And then that just kind of, like, cycle of, like, okay, you were helping us, like.
94 00:11:29.960 ⇒ 00:11:38.609 Pranav Narahari: telling us, like, okay, this is what the output is looking like. We’ll also have our own internal QA, of course, but then from you, like, as a final pass to see, like, okay.
95 00:11:38.610 ⇒ 00:11:54.279 Pranav Narahari: are we properly getting the context from Slack? You can kind of give us, like, that high-level, understanding. And it’s just, like, I like that better than, like, someone that has, like, working kind of just super manually, across all of these different, integrations, and then now we’re adding
96 00:11:54.740 ⇒ 00:12:10.330 Pranav Narahari: you know, we’re just adding all this context, you’re gonna get some insight, but I think for you, you’re gonna be able to really be particular about the insights that we’re creating, and then when we, like, ship it across the country, create that OS, company, I said country, not country.
97 00:12:10.330 ⇒ 00:12:19.120 Pranav Narahari: Across the company, we’ll be able to really, like, be proud of, like, the product that we’re creating, and it’ll really, save a lot of time.
98 00:12:19.290 ⇒ 00:12:27.749 Pranav Narahari: So I like that, like, yeah, let’s, let’s focus on Slack and BigQuery to start off with, in terms of your workflow.
99 00:12:27.960 ⇒ 00:12:36.469 Pranav Narahari: Now, kind of, like, going deeper into this presentation, yeah, the workflow’s in action.
100 00:12:39.470 ⇒ 00:12:42.959 Pranav Narahari: So, one of them was, like, a meeting prep.
101 00:12:44.510 ⇒ 00:12:49.149 Daniel: That’s an example of it, right? And so, I’m just live sharing, like.
102 00:12:50.300 ⇒ 00:12:52.750 Daniel: Hold on here, how do I…
103 00:12:53.640 ⇒ 00:13:03.640 Daniel: My desktop, there we go. So, just for context, it seems like an LLM, and so… I can’t get… can you… do you see the zoom thing? How do I move this?
104 00:13:04.150 ⇒ 00:13:05.390 Pranav Narahari: No, I don’t see that.
105 00:13:05.410 ⇒ 00:13:06.120 Daniel: Huh.
106 00:13:06.530 ⇒ 00:13:13.840 Daniel: Alright, so I just said, I have a meeting coming up at 1PM today, can you look at what the meeting is, providing past notes and emails to give me full context?
107 00:13:14.250 ⇒ 00:13:22.229 Daniel: Identifies this leadership meeting, gives me the most recent updates, you know, revenue hits 600, highest run rate,
108 00:13:22.390 ⇒ 00:13:25.770 Daniel: I ask it, as COO, provide me an update.
109 00:13:26.250 ⇒ 00:13:30.959 Daniel: You should ask these questions. Where are the picks with their exams? What’s the financial burn?
110 00:13:32.280 ⇒ 00:13:37.620 Daniel: like… This workflow seems really simple.
111 00:13:38.530 ⇒ 00:13:45.079 Daniel: But if this pulls in… this pulls in my emails, right, and everything else, to give me highest, best context.
112 00:13:45.240 ⇒ 00:13:47.060 Daniel: And it’s… good.
113 00:13:47.600 ⇒ 00:13:49.030 Pranav Narahari: Yeah, that’s good.
114 00:13:49.760 ⇒ 00:13:52.720 Daniel: Like, these are the questions I should be asking.
115 00:13:54.430 ⇒ 00:13:57.699 Daniel: And so, what I really want to do is be able to take this insight.
116 00:13:58.010 ⇒ 00:14:02.870 Daniel: Include it with the Slack comms. For example, I know there’s a mess. We hired this business development director.
117 00:14:03.060 ⇒ 00:14:12.810 Daniel: I just don’t have an email reflecting that hiring. Instead, I have Slack notes saying Jason onboarded, he started… you see what I’m saying? I’m just missing that final mile of context.
118 00:14:13.070 ⇒ 00:14:13.430 Pranav Narahari: That’s right.
119 00:14:13.430 ⇒ 00:14:17.880 Daniel: It’s, like, perfect, because ultimately what I can do is just, you know, can you put
120 00:14:25.790 ⇒ 00:14:37.020 Daniel: I mean, this’ll rock the whole agenda, and it makes it really easy workflow for prep. And, if we get better at it, we train the Gemini bot that sends this to me 15 minutes before my meeting.
121 00:14:37.310 ⇒ 00:14:38.000 Pranav Narahari: Right.
122 00:14:38.160 ⇒ 00:14:49.729 Daniel: if I have an interview, it’ll pull out the resume and submit that as part of that. Like, that’s the detail we can go to from a workflow perspective, and if I can do that, then I know we can start talking about the concept that other employees could do that, too.
123 00:14:51.460 ⇒ 00:14:52.240 Pranav Narahari: Yeah.
124 00:14:53.830 ⇒ 00:15:08.170 Pranav Narahari: So, okay, this seems great, and it’s like, yeah, it’s specific to just, like, the Slack channel, to the Gmail. It’s a little bit different in terms of, like, how we thought about, like, a weekly report, because this could be, like, more ad hoc.
125 00:15:08.280 ⇒ 00:15:14.030 Pranav Narahari: Right? And so, the architecture would be a little bit different.
126 00:15:14.930 ⇒ 00:15:19.219 Pranav Narahari: But, you know, also not as complex as…
127 00:15:20.930 ⇒ 00:15:27.340 Pranav Narahari: like, in terms of just adding on, like, Slack context to this, of course, like, we need to figure out…
128 00:15:28.240 ⇒ 00:15:36.040 Pranav Narahari: like, Gemini’s doing a bunch of these, like, tool calls on the backend for properly getting the context of emails, of calendar.
129 00:15:36.570 ⇒ 00:15:40.999 Pranav Narahari: Okay, this is good to know. Let’s also talk about,
130 00:15:41.960 ⇒ 00:15:47.490 Pranav Narahari: each of these probably, like, workflows in action. So, like, the next one I see here…
131 00:15:48.800 ⇒ 00:15:51.309 Pranav Narahari: Oh my gosh, I can’t type through this. Let’s see.
132 00:15:52.390 ⇒ 00:15:58.779 Pranav Narahari: Yeah, the monthly KPI and performance reporting, I think this is more kind of, like, what we were talking about.
133 00:15:58.780 ⇒ 00:16:00.680 Daniel: This is that meeting prep.
134 00:16:02.660 ⇒ 00:16:04.080 Pranav Narahari: Right after meeting prep.
135 00:16:05.120 ⇒ 00:16:06.330 Pranav Narahari: the movie.
136 00:16:06.330 ⇒ 00:16:11.370 Daniel: This… oh, this is the, the sort of looking around corners, trying to prep that.
137 00:16:11.590 ⇒ 00:16:15.220 Daniel: That’s basically what it’s doing. It’s saying monthly KPIs. I mean, technically.
138 00:16:15.360 ⇒ 00:16:25.500 Daniel: there is full access to BQ. If you’re credential on that, you should be able to pull out a KPI report based on some functionality and ultimately job description, right? That’s how detailed it can get, like.
139 00:16:25.500 ⇒ 00:16:25.980 Pranav Narahari: Yeah.
140 00:16:25.980 ⇒ 00:16:31.639 Daniel: Paycom data, and they see a job description for this person, they will drive to those same results. It’s kind of the concept.
141 00:16:31.870 ⇒ 00:16:32.490 Pranav Narahari: Yeah.
142 00:16:32.950 ⇒ 00:16:42.220 Daniel: Now, that has an additional layer of the Paycom functionality, which I don’t want to tackle yet. I don’t want to deal with employee segmentation, that’s why I just want to focus on my workflows.
143 00:16:42.840 ⇒ 00:16:45.610 Daniel: Because if I can do some of these things.
144 00:16:46.520 ⇒ 00:16:49.890 Daniel: That shows me that the context and the data is all there.
145 00:16:50.330 ⇒ 00:16:52.950 Daniel: And then we can segment it for employees, or do whatever.
146 00:16:53.500 ⇒ 00:17:00.500 Pranav Narahari: Gotcha. And so, how this would run is, like, on some type of scheduled cadence, right? Like… Wow.
147 00:17:00.590 ⇒ 00:17:04.859 Daniel: No, it actually… it actually run based on the calendar of that employee.
148 00:17:05.150 ⇒ 00:17:06.299 Pranav Narahari: I see. Okay.
149 00:17:06.300 ⇒ 00:17:08.060 Daniel: So, it will tell me…
150 00:17:08.310 ⇒ 00:17:23.520 Daniel: and proactively take that step. Now, that’s a little more challenging, because there’s no prompt in there, right? So we’d have to build out a prompt mechanism, but I should be able to say, hey, can you send me the notes for all my meetings today, and it’ll do it.
151 00:17:25.020 ⇒ 00:17:26.819 Pranav Narahari: Gotcha. I’ll show you that.
152 00:17:31.550 ⇒ 00:17:32.659 Pranav Narahari: Yeah, that would be great.
153 00:17:38.890 ⇒ 00:17:44.099 Daniel: It’s a rad… Concept, if it can just have all of the context.
154 00:17:50.890 ⇒ 00:17:54.900 Daniel: This’ll probably take a second, because I have… Using the pro here.
155 00:17:56.150 ⇒ 00:17:58.299 Daniel: Actually, I’m not sure why I’m using Pro.
156 00:18:12.550 ⇒ 00:18:15.230 Daniel: I mean, this is obviously pretty light, but…
157 00:18:23.520 ⇒ 00:18:25.830 Daniel: It’s, like, a pretty powerful tool.
158 00:18:30.570 ⇒ 00:18:32.300 Pranav Narahari: Yeah, and that integration’s great.
159 00:18:33.250 ⇒ 00:18:42.739 Daniel: So, I think if this just included Slack context, we could see, okay, out of the box, there’s gonna be some enhanced functionality here. I don’t know how Gemini crawls it, right?
160 00:18:42.970 ⇒ 00:18:54.630 Daniel: is the BQ instance, and in essence, it tells it that that’s where Slack lives. Is there a direct connection that we can do into Google Workspace that gives it that live view? That’s really my question, is like…
161 00:18:55.470 ⇒ 00:18:55.930 Pranav Narahari: Yeah.
162 00:18:55.930 ⇒ 00:18:59.239 Daniel: Create this as an access point for our employees.
163 00:19:00.030 ⇒ 00:19:10.620 Pranav Narahari: Right, right. So, it’s… essentially just… Doing, like, a… a SQL query, is my… And so…
164 00:19:11.400 ⇒ 00:19:16.769 Pranav Narahari: How, like, how… why these tools work so well is because they have very,
165 00:19:17.020 ⇒ 00:19:28.380 Pranav Narahari: they add a lot of definition where they can. So, like, a SQL query is going to be very deterministic, and then they use that as context, so they’re not just like, oh, pull me the relevant data.
166 00:19:29.580 ⇒ 00:19:34.380 Pranav Narahari: Using that SQL query is probably the way they would do it, the way that we would do it, too.
167 00:19:34.970 ⇒ 00:19:41.430 Daniel: And in essence, you can see the workspace connection is live. It’s crawling, searching. H Street Digital is like a…
168 00:19:41.810 ⇒ 00:19:42.530 Daniel: you know.
169 00:19:44.310 ⇒ 00:19:51.200 Daniel: this is somebody we’re not even working with, it was just a random proposal, and I can pull up all the details on that.
170 00:19:51.560 ⇒ 00:19:52.280 Pranav Narahari: Nice.
171 00:19:53.690 ⇒ 00:19:56.659 Daniel: Actually, it didn’t pull up all the details on it, that’s interesting.
172 00:19:57.130 ⇒ 00:20:00.060 Daniel: And I know why. It’s because their proposal was a link.
173 00:20:00.260 ⇒ 00:20:02.669 Daniel: Not a document. Interesting.
174 00:20:03.540 ⇒ 00:20:04.210 Daniel: Either way.
175 00:20:04.510 ⇒ 00:20:07.059 Daniel: Like, the power is there.
176 00:20:07.060 ⇒ 00:20:07.910 Pranav Narahari: 100%.
177 00:20:08.420 ⇒ 00:20:13.899 Daniel: So, if I can get… if we can sort of set an objective where… get Slack context.
178 00:20:14.870 ⇒ 00:20:21.620 Daniel: Then we’ve got Google Workspace and Slack, which are my main tools, and I… at that point, I should be able to be, like.
179 00:20:21.810 ⇒ 00:20:25.219 Daniel: I should be able to ask at context about how my teams work together.
180 00:20:26.090 ⇒ 00:20:28.659 Pranav Narahari: Yeah. Yeah, and
181 00:20:28.970 ⇒ 00:20:45.229 Pranav Narahari: like, a list of, like, those questions, you probably just… a bunch would come to mind. Like, let’s, like, define some of those so, like, we know, like, okay, if we’re able to get that Slack contact, we should be able to hit these questions out of the park. And right now, like, with the current setup, like, there’s certain gaps.
182 00:20:45.230 ⇒ 00:20:45.610 Daniel: Yeah.
183 00:20:45.610 ⇒ 00:20:51.110 Pranav Narahari: That’s gonna help a lot for the development process, because it’s like, we need something to test against,
184 00:20:51.550 ⇒ 00:20:52.060 Pranav Narahari: Yeah.
185 00:20:52.060 ⇒ 00:21:01.240 Daniel: So, I need to basically go through and ask a series of questions related to, okay, if I had Slack in here, and if it had full admin access.
186 00:21:03.050 ⇒ 00:21:09.879 Daniel: It’s like, this is talking about me, right? This is everything about me, it’s not giving me company context. Maybe that’s another piece.
187 00:21:10.200 ⇒ 00:21:11.990 Daniel: That I need to consider, right?
188 00:21:12.150 ⇒ 00:21:16.540 Daniel: So, Gemini is gonna focus on my frequent communicators.
189 00:21:17.000 ⇒ 00:21:17.700 Pranav Narahari: Right.
190 00:21:20.630 ⇒ 00:21:33.310 Pranav Narahari: Yeah, if it’s integrated through directly into this. Now, if you did a more org-scoped, right, we’re seeing every single direct message, every channel you’re not a part of, and I think
191 00:21:34.690 ⇒ 00:21:48.360 Pranav Narahari: for, like, that idea of, like, a… like, a COO trying to, like, just understand where the company is at, that’s what’s most important, right? They don’t care about their direct communications. They’re… they’re caring, like, what’s… what’s happening, like.
192 00:21:48.490 ⇒ 00:21:51.060 Pranav Narahari: In, like, every corner of the company.
193 00:21:51.060 ⇒ 00:21:57.350 Daniel: Yeah, you’re right. Okay, this conversation is helping me. So, so this is the issue. There’s no backdoor, right, into this.
194 00:21:57.510 ⇒ 00:22:05.020 Daniel: So that’s part of the challenge. So number one is, can we get context beyond just my… workflows
195 00:22:05.230 ⇒ 00:22:07.459 Daniel: But then, my workflows…
196 00:22:07.600 ⇒ 00:22:22.849 Daniel: that’s super valuable, like, that’s almost at the finish line. So maybe what we can do is just start on enhancing our individual workflows as a company, and then we can work on leveraging that data for insights in terms of how, you know, everybody works together, but that starts with
197 00:22:23.300 ⇒ 00:22:34.559 Daniel: basically a big bucket of all this information that just lives in a BQ instance or something, and when you pull it, it’s full exposure, and there’s credentialed access to that or something, right?
198 00:22:35.420 ⇒ 00:22:37.029 Pranav Narahari: Yeah, yeah.
199 00:22:38.200 ⇒ 00:22:43.439 Pranav Narahari: It’s all about just, like, role scope and then org scope, like, that’s how all of these, like…
200 00:22:43.900 ⇒ 00:22:45.369 Pranav Narahari: That’s how, like, there is.
201 00:22:45.580 ⇒ 00:22:50.640 Pranav Narahari: the Slack API is gonna work, that’s how, like, the BigQuery’s gonna work as well, like…
202 00:22:51.360 ⇒ 00:23:05.939 Daniel: So, so based on these contexts, do you think it’s easier to start with the… the super admin view on this, or is it easier to start with individual workflows and just making sure Slack’s connected, and then my team can just get credentialed into it?
203 00:23:07.400 ⇒ 00:23:10.700 Pranav Narahari: Easy in the sense…
204 00:23:11.950 ⇒ 00:23:18.450 Daniel: Based on our current data setup. Like, what gives you guys the fastest, like, launch there? It would be my curiosity.
205 00:23:18.450 ⇒ 00:23:24.239 Pranav Narahari: Yeah, so, of course, like, doing it on an individual basis would be faster, but it won’t just be as powerful.
206 00:23:24.580 ⇒ 00:23:31.950 Pranav Narahari: Right. We’re talking about how you’re just going to have access to, like, your specific threads, and…
207 00:23:31.950 ⇒ 00:23:38.439 Daniel: If we do that data right, I mean, shouldn’t technically we be able to say, okay, use Gemini as an access point to all of your Google tools and Slack?
208 00:23:39.760 ⇒ 00:23:42.360 Pranav Narahari: Yeah, how you would set it up is going to be…
209 00:23:42.440 ⇒ 00:23:56.620 Pranav Narahari: a little bit different, I think. You would have, like, a data warehouse that pulls it directly, not based on… like, so it wouldn’t be based on, like, one person, authenticating in. It would just be like, okay, we’re just gonna pull in all of the organization’s data.
210 00:23:56.620 ⇒ 00:24:04.110 Pranav Narahari: And we would do it that. We would do it that way. It’s not like, oh, as each person, like, authenticates in, we’re getting more and more data.
211 00:24:04.150 ⇒ 00:24:11.359 Pranav Narahari: It wouldn’t… That, by design, would just be a lot more difficult.
212 00:24:12.020 ⇒ 00:24:15.170 Daniel: So let me re-ask the question a different way, then. So…
213 00:24:15.990 ⇒ 00:24:22.710 Daniel: I already have Google Workspace set up, right? We’re, like, 6-70% of the way there because I’m just missing Slack.
214 00:24:22.970 ⇒ 00:24:32.249 Daniel: So I’m trying to break it off. Could I integrate Slack into this contextually, and then just onboard all of my employees and show them how to credential into Gemini, right?
215 00:24:32.600 ⇒ 00:24:43.519 Daniel: Yeah, that’s a pretty sweet light lift if it has access to Slack contacts. If it doesn’t, it’s worthless, because it’s going to miss the 30% of the information, which is just going to be the most relevant, right?
216 00:24:43.520 ⇒ 00:24:44.939 Pranav Narahari: Yeah, so what you’re saying is budget.
217 00:24:44.940 ⇒ 00:24:55.250 Daniel: and Slack, then I could take the first project being, hey everybody, you have access to Gemini now, here’s how to authenticate it, use it to your heart’s content, it’s already linked in with your Slack.
218 00:24:56.240 ⇒ 00:24:57.820 Pranav Narahari: Right, yeah, so…
219 00:24:58.130 ⇒ 00:25:09.110 Pranav Narahari: I like that a lot. I think if… and I just want to make sure we’re clear, though, like, with Slack, how we’d add that as context is by getting the organizational context, or are you saying…
220 00:25:09.110 ⇒ 00:25:10.740 Daniel: Everybody would have access to everything?
221 00:25:13.040 ⇒ 00:25:18.209 Pranav Narahari: We could also… we could… we… so…
222 00:25:18.490 ⇒ 00:25:36.050 Pranav Narahari: Now, we can add granularity to that, right? We can say, like, Danny, for you, since you’re an admin on everything, like, you can get access to everything. We can also add just specific roles for, like, okay, you can only get access to threads and channels and, DMs that you have been a part of.
223 00:25:36.050 ⇒ 00:25:36.770 Daniel: Okay.
224 00:25:37.090 ⇒ 00:25:37.770 Pranav Narahari: Yeah.
225 00:25:39.110 ⇒ 00:25:43.800 Daniel: So that would be an interesting first project, because first of all, I believe it would just enhance workflows a lot.
226 00:25:43.800 ⇒ 00:25:44.750 Pranav Narahari: Yeah.
227 00:25:45.010 ⇒ 00:25:51.449 Daniel: So… so that’s interesting to me, and I could just walk everybody through onboarding onto Gemini, which is kind of fun.
228 00:25:51.460 ⇒ 00:25:52.590 Pranav Narahari: Yeah.
229 00:25:52.620 ⇒ 00:25:56.190 Daniel: So… Interesting. Okay.
230 00:25:58.320 ⇒ 00:26:06.499 Daniel: That might be an easier lift than trying to get the full bird’s-eye view, but what you’re telling me is basically the data’s gonna be the same, because of the way you guys are gonna have to do Slack.
231 00:26:10.500 ⇒ 00:26:16.230 Daniel: Am I confusing this more than it should be? I feel like I walked in here pretty clear on what I wanted, now I’m a little more confused.
232 00:26:16.920 ⇒ 00:26:20.930 Pranav Narahari: I, I feel…
233 00:26:20.930 ⇒ 00:26:22.489 Daniel: Let’s start with Juan, right?
234 00:26:22.780 ⇒ 00:26:25.650 Pranav Narahari: Yes, and so that’s what I wanted to come in saying, too, like.
235 00:26:25.880 ⇒ 00:26:42.029 Pranav Narahari: every connection that we add, it does increase, time spent in order to get it done right. And what I mean by that is, like, we’re bringing in new data, we should re-evaluate that we’re pulling in better context, significantly better, and it’s
236 00:26:42.390 ⇒ 00:26:53.899 Pranav Narahari: we’re actually… like, it would be an issue if, like, in that Gemini chat, you know something exists in Gemini, but it isn’t pulling that information and providing it to you.
237 00:26:54.070 ⇒ 00:27:03.890 Pranav Narahari: The only reason why, like, for that one candidate that already got hired, that you weren’t concerned is because you know that comm doesn’t exist in email.
238 00:27:03.890 ⇒ 00:27:05.009 Daniel: only in Slack.
239 00:27:05.010 ⇒ 00:27:21.199 Pranav Narahari: Since it was only a Slack. So that’s why, okay, it’s performing as promised. The issue would be, like, if you have Slack integrated, and we’re not pulling in that information, then we have a bigger problem. And so that’s why, with each additional connection, we need to make sure that we are pulling in the right information.
240 00:27:21.740 ⇒ 00:27:39.339 Daniel: You can use me as an experiment to run through that. I’ll just try and integrate it into workflow, and I’ll look for the QA on that side. But that’s exactly where my head’s at. This is doing what I would expect Gemini to do with the information it has access to today. Yes. If we onboard something like Slack, I’m just going to use it for all of those purposes.
241 00:27:39.480 ⇒ 00:27:46.569 Pranav Narahari: And since you’ve already used it so much for, like, the Google Workspace, like, you’ll have better clarity about, like, hey, I know this isn’t Slack, you know?
242 00:27:47.390 ⇒ 00:28:03.489 Daniel: And if it works for me, I experiment with it for a few days, it’s good enough, we see, you know, I try and get access to something I shouldn’t have access to, which, that’ll be a little… maybe… maybe I’ll find a peer, to run this through, too. Yeah. And ultimately, that should…
243 00:28:03.700 ⇒ 00:28:07.860 Daniel: be enough for telehealth specifically, right? Okay.
244 00:28:08.080 ⇒ 00:28:13.650 Daniel: That seems like a good start to the project, is let’s figure out if we can get Slack into Danny’s Gemini.
245 00:28:14.570 ⇒ 00:28:15.290 Pranav Narahari: Perfect.
246 00:28:15.820 ⇒ 00:28:16.700 Pranav Narahari: Yeah.
247 00:28:17.140 ⇒ 00:28:17.990 Daniel: I like this.
248 00:28:18.850 ⇒ 00:28:26.190 Daniel: I think I’m pretty on base with how the way of working is gonna change, I just don’t… I’m not a data guy, so I don’t quite understand how that all works.
249 00:28:26.680 ⇒ 00:28:43.949 Daniel: when I was trying to Gemini this project and, you know, have it talk to me, it was basically, okay, use a Vertex AI layer and do, like, a, you know, refresh and get Slack basically piping into that layer for… and then it’ll open up this Google Workspace access.
250 00:28:44.030 ⇒ 00:28:49.310 Pranav Narahari: So I don’t know if that’s helpful context, but it was really clear that, like, if you just get that vertex layer in.
251 00:28:50.200 ⇒ 00:28:52.899 Daniel: This will already be integrated.
252 00:28:53.030 ⇒ 00:28:53.540 Daniel: It’s kind of.
253 00:28:53.540 ⇒ 00:29:12.989 Pranav Narahari: Yeah, I think Gemini’s going to push, like, Vertex. I don’t, like, we’ve had a couple different, like, projects internally, like, use Vertex, and I… I think what we would do is, like, we would spike to see, like, you know, yeah, you are using it within the Gemini, chat, right? So, like, if that is…
254 00:29:13.600 ⇒ 00:29:21.979 Pranav Narahari: that’s a pro for Vertex, since it’s in the same, like, environment, ecosystem, I should say.
255 00:29:22.360 ⇒ 00:29:32.040 Pranav Narahari: But basically, what I’ll do is I’ll spike on all the tools. Like, we’ll use Vertex, we’ll also look at, we’ll look at Mastro, we’ll look at a bunch of different other things.
256 00:29:32.040 ⇒ 00:29:40.599 Daniel: I would like them to be as uniform in that connection as we can, meaning in Google Workspace. I’m not a Google Workspace fanatic.
257 00:29:40.600 ⇒ 00:29:42.629 Pranav Narahari: I just know if everything…
258 00:29:42.720 ⇒ 00:29:56.819 Daniel: is in Google Workspace, we get to take advantage of all of their new implemented tools and features, versus if we’re collabing and building out these band-aids to other systems, we don’t just… we don’t just rise with the tide because we’re on Google Workspace, and I want that effect.
259 00:29:57.080 ⇒ 00:29:58.310 Pranav Narahari: Yes. Yes.
260 00:29:58.310 ⇒ 00:30:06.819 Daniel: Because Google’s implementing this stuff live all the time. I just… this Drive connection came out, like, what, 2 months ago?
261 00:30:07.260 ⇒ 00:30:07.670 Pranav Narahari: Yeah.
262 00:30:07.670 ⇒ 00:30:16.160 Daniel: all of a sudden, we have this new access point that we did nothing for other than pay for a license to Google Workspace. So I’d love to be able to take advantage of all of those features.
263 00:30:16.450 ⇒ 00:30:21.789 Pranav Narahari: Definitely, yeah. That’s why when we choose tooling too, we want to make sure, like.
264 00:30:22.280 ⇒ 00:30:26.250 Pranav Narahari: Either, like, we know… like, sometimes with some of our partners, too, like, we, like…
265 00:30:26.360 ⇒ 00:30:30.299 Pranav Narahari: They’ll just, like, make features for us because they know, like.
266 00:30:30.640 ⇒ 00:30:42.860 Pranav Narahari: you know, our clients want them. And so we can drive it even that closely. Of course, for Google, it’s not like that, but we make decisions based on, like, okay, is this going to, like… are these… are there features, like.
267 00:30:43.120 ⇒ 00:30:55.759 Pranav Narahari: like, something like that that are gonna be down the pipeline? Is this, like, a tool that’s kind of, like, broken, and it’s, like, people are… it’s just kind of on its last legs? Gemini is, of course, not like that. They’re shipping new things all the time. Those tools…
268 00:30:55.760 ⇒ 00:31:11.119 Daniel: I even almost get a little worried with the Omni, you know, AI context, like, they’re good, right? But I’m like, fuck, I’m gonna be able to pull this stuff direct from Gemini through BQ pretty soon here. Like, it’s gonna be so linked that, like, I will just ask it for my own dashboard whenever I want it.
269 00:31:11.330 ⇒ 00:31:15.179 Daniel: But I know that’s probably, like, a year away. So…
270 00:31:15.180 ⇒ 00:31:15.570 Pranav Narahari: Yeah.
271 00:31:15.570 ⇒ 00:31:20.539 Daniel: So with that in mind, like, you know, we gotta make some decisions based on… on that, but…
272 00:31:21.130 ⇒ 00:31:27.790 Pranav Narahari: Yeah, it’s really hard to say, like, all these companies, too, they just pivot randomly, like,
273 00:31:27.950 ⇒ 00:31:42.390 Pranav Narahari: like, ChatGPT, just, like, coming up with, like, a bunch of apps, you know, like, it’s just… it’s all random. And then what we do is we just, like, okay, we see, like, the news that happened last night, and then we’re like, okay, let’s reassess. Let’s figure out what we did.
274 00:31:42.390 ⇒ 00:31:56.310 Daniel: And we’re gonna have to do that, but I get a little worried about, like, like, Gemini’s not my favorite tool right now. Like, I’m using Claude, but 3 months ago, Gemini was kind of, like, you know, better in that instance, right? So I’m like, I would rather let not debate on that.
275 00:31:56.440 ⇒ 00:32:01.280 Daniel: Yeah. And just pick a tool and integrate it into the tool, because it’s gonna get better around us.
276 00:32:01.590 ⇒ 00:32:19.309 Pranav Narahari: That’s the thing, too, so, like, whatever system we build to create that, like, AI brain, that context graph, it should be plug-and-play wherever, you know? Like, it shouldn’t just be, like, dependent on that chat interface within Gemini. Like, if we need to build a standalone app, if we wanted to build an integration with Slack,
277 00:32:19.320 ⇒ 00:32:27.100 Pranav Narahari: that isn’t going to require a complete revamp of the application. It’s really… it just is, like, another module that we need to develop.
278 00:32:28.610 ⇒ 00:32:42.900 Daniel: Yeah, and again, also, I’m thinking in my head, well, if I get everybody using Gemini, then I’m only paying for one license that I’m already paying for. So the more I can push that, the better, because people have, like, ChatGPT licenses out there that aren’t connected to any tools, like, this will be way more enhanced.
279 00:32:43.090 ⇒ 00:32:44.520 Pranav Narahari: Yeah, yeah.
280 00:32:44.520 ⇒ 00:32:55.569 Daniel: So I think… I think we start with that. Why don’t we start with getting me access to Slack, and me testing that, and seeing if we can launch this as a tool just generally across the company, because it should be pretty quick.
281 00:32:55.610 ⇒ 00:32:56.520 Pranav Narahari: If…
282 00:32:57.230 ⇒ 00:33:08.019 Daniel: we work on that credentialing, and people have access to basically what they should have access to, which is why I liked the context, the… I liked the theory of what I was seeing in terms of the Vertex AI build-out.
283 00:33:08.650 ⇒ 00:33:10.989 Pranav Narahari: Yeah, okay. That sounds good to me.
284 00:33:11.290 ⇒ 00:33:15.310 Pranav Narahari: But maybe, maybe that pulls from BQ, I don’t know all the background there.
285 00:33:15.310 ⇒ 00:33:20.940 Daniel: But we’d want, basically, full visibility into anything I have access to in Workspace and Slack.
286 00:33:21.700 ⇒ 00:33:22.800 Pranav Narahari: Yes, right.
287 00:33:23.700 ⇒ 00:33:24.440 Daniel: That’d be sweet.
288 00:33:24.770 ⇒ 00:33:30.690 Pranav Narahari: That sounds great, yeah. Cool. That seems like, that seems, like, very targeted as well, which I like, you know?
289 00:33:30.690 ⇒ 00:33:37.730 Daniel: Yeah, I like that too, and then, you know, Josh and Adam can grab that access really easily, and we can, you know, experiment on that, and then we can roll it out.
290 00:33:38.100 ⇒ 00:33:38.969 Daniel: Yep.
291 00:33:39.510 ⇒ 00:33:51.709 Daniel: And then from there, we can work on back-end tooling, you know, super exposure, so I can do what I really want to do, which is look at, like, how does my team work together? Where are the interactions? Where are the blockers and roadmaps that are happening?
292 00:33:51.710 ⇒ 00:34:06.950 Daniel: Gemini will be able to assess that and be like, hey, this meeting’s been on the books with no progress for, like, you know, 4 months, like, something’s not working here, nobody’s creating any documents, nobody’s talking about it after the meeting, they’re just sitting on it so I can go can that meeting, right? That’s kind of the insight I’m looking towards.
293 00:34:07.370 ⇒ 00:34:11.189 Pranav Narahari: Yeah, that phased approach is, like, the best way, I think, for both
294 00:34:11.420 ⇒ 00:34:17.760 Pranav Narahari: you, like, for you and for me, you know? Just, you can consistently see, like,
295 00:34:17.940 ⇒ 00:34:37.459 Pranav Narahari: additional insights and, like, workflow enhancements, while I am not working on a ton of stuff and then pressing, like, after months and months and months, pressing go and just seeing if everything works. You know, I like to be, like, that feedback, kind of coming back and forth. And then it also allows us to, like, ship quicker.
296 00:34:37.830 ⇒ 00:34:48.559 Daniel: That’s what I like, because we may as well take advantage of this stuff. I like this plan, so let’s get… let’s get me just basic access to my Slack and see if… see where Gemini does, you know, what it does from there.
297 00:34:48.850 ⇒ 00:34:50.239 Pranav Narahari: Yeah, that sounds good.
298 00:34:50.679 ⇒ 00:34:51.239 Daniel: Cool.
299 00:34:51.440 ⇒ 00:34:51.980 Pranav Narahari: Cool.
300 00:34:53.209 ⇒ 00:35:01.069 Daniel: You’re probably gonna need credentials or something, or who knows, so just tell me whatever you need to get access to these things.
301 00:35:01.620 ⇒ 00:35:03.210 Pranav Narahari: Yeah,
302 00:35:04.700 ⇒ 00:35:12.469 Pranav Narahari: I will… I will work with Robert on that as well, just to figure out exactly, the next steps.
303 00:35:12.780 ⇒ 00:35:18.790 Pranav Narahari: And so, and then, yeah, since we’re on Slack too, that’s perfect. I’ll create a thread for the three of us.
304 00:35:18.790 ⇒ 00:35:22.319 Daniel: Okay, and yeah, whatever you guys need to get access, full exposure.
305 00:35:22.640 ⇒ 00:35:27.110 Daniel: I think we start there. I think we start with… with my Slack access.
306 00:35:27.580 ⇒ 00:35:29.240 Pranav Narahari: Yeah. That sounds great.
307 00:35:29.530 ⇒ 00:35:32.189 Daniel: Cool. This is awesome. Thanks for jumping on, Rav.
308 00:35:32.550 ⇒ 00:35:34.799 Daniel: Yeah, thank you so much. Talk soon.
309 00:35:34.840 ⇒ 00:35:35.560 Pranav Narahari: Tip.