2025-11-17_brainforge_x_cta_deeper_dive_c508fb71

Meeting Title: Brainforge x CTA: Deeper Dive Date: 2025-11-17 Meeting participants: Uttam Kumaran, Samuel Roberts, Katherine Bayless

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WEBVTT

1 00:00:44.940 ⇒ 00:00:47.379 Samuel Roberts: My headphones working this time? Yeah.

2 00:00:47.950 ⇒ 00:00:49.360 Samuel Roberts: Can you hear me?

3 00:00:51.400 ⇒ 00:00:52.180 Samuel Roberts: Cool.

4 00:00:52.720 ⇒ 00:00:54.229 Samuel Roberts: Oh, what was going on last time?

5 00:00:54.920 ⇒ 00:00:56.800 Samuel Roberts: Just decided they didn’t like it.

6 00:01:00.570 ⇒ 00:01:01.820 Samuel Roberts: Nope.

7 00:01:03.670 ⇒ 00:01:04.939 Uttam Kumaran: But I went well.

8 00:01:04.940 ⇒ 00:01:05.540 Samuel Roberts: Yeah.

9 00:01:07.540 ⇒ 00:01:16.270 Samuel Roberts: Yeah, I wasn’t sure what exactly the plan was with that other code. That was why I was a little, like… I knew it was the other shop, but I wasn’t sure, like.

10 00:01:16.570 ⇒ 00:01:21.860 Samuel Roberts: If they were getting it, and it seemed like there’s a combination of some of the stuff is coming, and some of the stuff is…

11 00:01:22.230 ⇒ 00:01:22.670 Uttam Kumaran: Yeah.

12 00:01:22.670 ⇒ 00:01:24.890 Samuel Roberts: Yeah, so that’ll be trying to figure out.

13 00:01:25.210 ⇒ 00:01:26.750 Uttam Kumaran: Yeah, I agree.

14 00:01:32.680 ⇒ 00:01:34.009 Katherine Bayless: Hello, hello, hello! Sorry.

15 00:01:34.010 ⇒ 00:01:40.110 Samuel Roberts: Zoom was kind of weird when I opened it. It was, like, fussing at me about authentication, so I don’t…

16 00:01:40.260 ⇒ 00:01:41.330 Uttam Kumaran: Oh, okay.

17 00:01:41.840 ⇒ 00:01:43.249 Uttam Kumaran: Strange thing. How’s everything?

18 00:01:43.680 ⇒ 00:01:44.440 Katherine Bayless: Sorry?

19 00:01:44.440 ⇒ 00:01:45.500 Uttam Kumaran: How’s everything?

20 00:01:46.320 ⇒ 00:01:49.620 Samuel Roberts: It was alright. Yeah, it’s been one hell of a Monday. I’m like…

21 00:01:50.240 ⇒ 00:01:54.170 Uttam Kumaran: Okay, sorry, we’re catching you at the tail end.

22 00:01:54.170 ⇒ 00:01:54.560 Katherine Bayless: Actually.

23 00:01:54.560 ⇒ 00:01:55.270 Uttam Kumaran: It’ll be loaded.

24 00:01:55.270 ⇒ 00:01:59.990 Samuel Roberts: Really, because it gave me, like, a, like, I got one more call, I gotta go.

25 00:02:01.770 ⇒ 00:02:04.140 Katherine Bayless: Yeah. So, what about you guys? How are you?

26 00:02:04.510 ⇒ 00:02:06.830 Uttam Kumaran: Good, it’s also kind of heavy Monday.

27 00:02:06.830 ⇒ 00:02:07.360 Samuel Roberts: Yeah.

28 00:02:07.570 ⇒ 00:02:13.670 Uttam Kumaran: We’re… yeah, we try to talk about every client every day, which is sometimes hard.

29 00:02:14.160 ⇒ 00:02:15.540 Uttam Kumaran: But…

30 00:02:15.710 ⇒ 00:02:16.800 Katherine Bayless: Good problem to have.

31 00:02:16.940 ⇒ 00:02:27.310 Uttam Kumaran: I don’t know, we’re just doing well, and, like, I’m pumped to kick off this project. I was telling Sam kind of all about it last week, too, and so… yeah, I’m just, like.

32 00:02:27.580 ⇒ 00:02:33.700 Uttam Kumaran: I’m just, like, ready to… to start on stuff, so I’m excited for tomorrow’s meeting. And yeah, maybe, Sam, I’ll let you give a brief introduction before I…

33 00:02:33.910 ⇒ 00:02:36.070 Uttam Kumaran: Start blobbing away.

34 00:02:36.070 ⇒ 00:02:36.510 Samuel Roberts: Yeah.

35 00:02:36.510 ⇒ 00:02:39.009 Uttam Kumaran: I’m just having my second coffee, so I’m just gonna, like…

36 00:02:39.010 ⇒ 00:02:39.690 Katherine Bayless: Right.

37 00:02:39.720 ⇒ 00:02:40.490 Samuel Roberts: mobile.

38 00:02:40.510 ⇒ 00:02:41.260 Katherine Bayless: Yeah.

39 00:02:41.320 ⇒ 00:02:51.490 Samuel Roberts: Yeah, so hi, I’m Sam. I’ve been at Brainforger since the summer, doing, a lot of AI automation side of things.

40 00:02:51.560 ⇒ 00:03:04.989 Samuel Roberts: But, learning a lot about data as well, because we do a lot of that. And so my background is more, startup stuff, product stuff, so I’ve been, you know, doing web development like that for years, and yeah, excited to work on this.

41 00:03:05.300 ⇒ 00:03:19.670 Katherine Bayless: Yeah, I mean, it makes sense, the AI angle, because I know I’ve talked a lot about how I’m like, we’re literally so behind, I think we could, like, leapfrog some of the stuff, you know? Like, why would I sit around and make a bunch of dashboards when we could just have talking to our data?

42 00:03:20.040 ⇒ 00:03:20.440 Samuel Roberts: Right.

43 00:03:20.440 ⇒ 00:03:21.710 Katherine Bayless: Yeah, yeah, yeah.

44 00:03:22.090 ⇒ 00:03:22.720 Samuel Roberts: Totally.

45 00:03:23.000 ⇒ 00:03:23.400 Katherine Bayless: life.

46 00:03:24.090 ⇒ 00:03:39.229 Uttam Kumaran: I feel really… I feel really similar. And that’s why it’s, like, been fun working with a lot of data people and AI full-stack people who are, like, also learning a lot of the data stuff, but they’re able to, like, question, like, oh, we could totally do this faster.

47 00:03:39.230 ⇒ 00:03:39.910 Katherine Bayless: Hmm.

48 00:03:39.910 ⇒ 00:03:54.619 Uttam Kumaran: That’s been great, so a lot of our clients are benefiting because we’re just… we’re able to move so much faster. And then also, we’re actually doing a spike for another client this week, which we’ll totally share with you, which is, like, chat with data, like, systems. And so.

49 00:03:54.620 ⇒ 00:03:56.540 Katherine Bayless: I think you mentioned, actually, yeah, we’re…

50 00:03:56.540 ⇒ 00:04:15.810 Uttam Kumaran: We’re evaluating, kind of, like… we did this, like, maybe 6 months ago, but we’re, like, evaluating the market of options. Like, we’ve done POCs with Omni and a few other tools, but we also want to demo Snowflake’s, like, latest, and sort of just get our opinion about, like, what works, given, like, how we architect things.

51 00:04:16.000 ⇒ 00:04:16.320 Katherine Bayless: Yeah.

52 00:04:16.749 ⇒ 00:04:19.689 Uttam Kumaran: That should also be really, really helpful for this, so…

53 00:04:20.620 ⇒ 00:04:23.749 Katherine Bayless: Yeah, it’s funny, I was actually just talking to,

54 00:04:23.980 ⇒ 00:04:39.820 Katherine Bayless: Jay, the VP of IT, about, like, you know, data and the AI apocalypse and all the things, and I was like, honestly, I was like, my job’s not going anywhere. It’s just gonna change from, like, data engineer pipeline builder to, like, digital librarian, like, I will curate.

55 00:04:39.820 ⇒ 00:04:40.860 Uttam Kumaran: Knowledge, meaning.

56 00:04:40.860 ⇒ 00:04:44.120 Katherine Bayless: content that the robots can use to answer your questions, right?

57 00:04:44.180 ⇒ 00:04:44.740 Samuel Roberts: Yeah. Like…

58 00:04:44.740 ⇒ 00:04:47.210 Katherine Bayless: Yeah, and also clean up all the stuff he breaks.

59 00:04:47.850 ⇒ 00:04:48.540 Uttam Kumaran: Exactly.

60 00:04:48.860 ⇒ 00:04:55.380 Katherine Bayless: He is pushed into the wild west of MCP in a way that I’m like, okay, buddy, have fun.

61 00:04:55.700 ⇒ 00:04:56.690 Samuel Roberts: Yeah.

62 00:04:56.690 ⇒ 00:05:01.680 Katherine Bayless: Right? And he’s like, I’ve got one that can edit our DNS records. And I’m like, I don’t think that you should build that.

63 00:05:01.680 ⇒ 00:05:02.780 Samuel Roberts: Yeah.

64 00:05:04.020 ⇒ 00:05:04.550 Katherine Bayless: Yeah.

65 00:05:05.100 ⇒ 00:05:23.629 Katherine Bayless: Yeah, yeah. So actually, speaking of, Jay, I think… so I wasn’t sure who all should get access to which thing, so I gave him your email address to add to AWS, at least, but then, Samuel, now that you’re here, and then I know I spoke with, I think.

66 00:05:24.790 ⇒ 00:05:25.500 Uttam Kumaran: Robert.

67 00:05:25.500 ⇒ 00:05:29.329 Katherine Bayless: Robert? Okay, I was like, I’m, like, not trusting myself, because, like, wait, your last name is Robert, so am I.

68 00:05:29.330 ⇒ 00:05:32.940 Uttam Kumaran: I just tried to log into Okta.

69 00:05:32.940 ⇒ 00:05:33.570 Katherine Bayless: Oh, okay.

70 00:05:33.570 ⇒ 00:05:39.660 Uttam Kumaran: OnePassword auto-filled a password, but then it didn’t save it, so I may need him to reset my account.

71 00:05:40.430 ⇒ 00:05:46.700 Katherine Bayless: Does it do that thing, like, 1Password, where you can, like, see, like, most recently generated passwords?

72 00:05:47.030 ⇒ 00:05:50.549 Uttam Kumaran: I don’t know, although I will…

73 00:05:50.550 ⇒ 00:05:51.040 Samuel Roberts: Somewhere.

74 00:05:51.040 ⇒ 00:05:56.950 Uttam Kumaran: Because this happens, like, But I guess I didn’t say… it didn’t save, it, like, autofilled, and then…

75 00:05:57.190 ⇒ 00:06:06.200 Uttam Kumaran: I would, like, went to go edit and put in the right vault, and then it, like, the extension, like, short-circuited, and then… it logged in anyways, and I was like…

76 00:06:06.200 ⇒ 00:06:16.859 Katherine Bayless: I’ve had the same, like, yeah, like, I’ll watch it, like, autofill, you know, your super secure, delightful password, and then you’re like, oh, wait, no, come back.

77 00:06:17.660 ⇒ 00:06:21.429 Uttam Kumaran: So, I don’t know. Let me see… Yeah, you’re looking at.

78 00:06:21.430 ⇒ 00:06:22.170 Katherine Bayless: way, you can.

79 00:06:22.170 ⇒ 00:06:24.220 Samuel Roberts: Yeah, there’s a history, it looks like.

80 00:06:24.770 ⇒ 00:06:25.690 Uttam Kumaran: Where is that?

81 00:06:26.190 ⇒ 00:06:29.780 Samuel Roberts: If you go to the… the key that says password generator.

82 00:06:30.200 ⇒ 00:06:33.429 Samuel Roberts: You should see at the bottom, password generator history.

83 00:06:33.820 ⇒ 00:06:35.719 Uttam Kumaran: Oh, there it is, wow!

84 00:06:35.720 ⇒ 00:06:38.230 Samuel Roberts: Oh yeah, I think, yeah, whether or not it’s even used, I think.

85 00:06:38.230 ⇒ 00:06:40.309 Uttam Kumaran: What kind of UI is this? Like, who…

86 00:06:40.310 ⇒ 00:06:41.190 Samuel Roberts: Yeah, right.

87 00:06:41.190 ⇒ 00:06:42.949 Uttam Kumaran: Clicking on the key button.

88 00:06:42.950 ⇒ 00:06:45.899 Katherine Bayless: Right. I’ve been clicking on his… alright, great.

89 00:06:45.900 ⇒ 00:06:48.739 Uttam Kumaran: Cool, let me just… let me just confirm that that works.

90 00:06:49.070 ⇒ 00:06:50.020 Katherine Bayless: Yeah.

91 00:06:50.020 ⇒ 00:06:50.610 Uttam Kumaran: Thank goodness.

92 00:06:50.610 ⇒ 00:06:51.570 Katherine Bayless: Because if it.

93 00:06:51.570 ⇒ 00:06:56.139 Uttam Kumaran: It just, like, changed everything. You know how much time I’ve wasted?

94 00:06:56.980 ⇒ 00:06:58.860 Katherine Bayless: No, I just saved my ass a few times.

95 00:06:58.860 ⇒ 00:07:01.270 Uttam Kumaran: Okay, awesome. Okay, never mind, then I’m fine there.

96 00:07:01.270 ⇒ 00:07:03.539 Katherine Bayless: Nice, okay.

97 00:07:03.670 ⇒ 00:07:12.150 Katherine Bayless: Okay, so actually, I’m curious, though, because he and I, admittedly, there are so few users in the AWS stuff, we couldn’t remember if…

98 00:07:12.400 ⇒ 00:07:22.369 Katherine Bayless: he gave you, like, admin access on the account. When you go into it, do you see the playground as well as the root account, or do I need to still, like.

99 00:07:23.010 ⇒ 00:07:27.000 Katherine Bayless: pull you the last step of the way to the actual Data Playground account.

100 00:07:27.330 ⇒ 00:07:31.320 Uttam Kumaran: Yeah, so let me… let’s… we can… let’s find out together.

101 00:07:36.610 ⇒ 00:07:37.500 Katherine Bayless: Yeah.

102 00:07:37.500 ⇒ 00:07:44.779 Uttam Kumaran: So, I don’t have… In Okta, it doesn’t look like I have AWS.

103 00:07:45.920 ⇒ 00:07:50.299 Katherine Bayless: You know, I think…

104 00:07:52.490 ⇒ 00:07:53.350 Uttam Kumaran: So…

105 00:07:53.710 ⇒ 00:07:54.490 Katherine Bayless: Yeah.

106 00:07:54.490 ⇒ 00:07:58.419 Uttam Kumaran: search for it. Oh, oh yeah, I can… it says I can add it.

107 00:07:58.730 ⇒ 00:07:59.820 Uttam Kumaran: I added it.

108 00:08:00.190 ⇒ 00:08:01.630 Katherine Bayless: Oh, you can add it? Okay.

109 00:08:02.270 ⇒ 00:08:10.140 Uttam Kumaran: Oh, but then it says, set up access, enter your username and password for the AWS console, password sign-in.

110 00:08:10.140 ⇒ 00:08:10.669 Katherine Bayless: Oh, recently.

111 00:08:10.670 ⇒ 00:08:12.380 Uttam Kumaran: contact, so you… yeah.

112 00:08:12.650 ⇒ 00:08:28.190 Katherine Bayless: Yeah, no, it’s, like, this happened with the other consulting team, too. There’s, like, we add you to the thing, and you do have access, but getting the tile to show up on your Okta dashboard is, like, a different thing. I sent you the link in Slack, I don’t know if you see if maybe you can…

113 00:08:28.190 ⇒ 00:08:29.149 Uttam Kumaran: Yeah, yeah, yeah, let me try.

114 00:08:29.150 ⇒ 00:08:30.090 Katherine Bayless: to it.

115 00:08:30.400 ⇒ 00:08:34.760 Katherine Bayless: Our Okta… Isn’t messing.

116 00:08:35.409 ⇒ 00:08:36.690 Katherine Bayless: It is a problem.

117 00:08:37.020 ⇒ 00:08:37.730 Katherine Bayless: It is broken.

118 00:08:38.340 ⇒ 00:08:45.939 Uttam Kumaran: We just did the migration from Active Directory to Entra over the weekend, apparently, so hopefully we’re getting a little better.

119 00:08:47.080 ⇒ 00:08:52.490 Katherine Bayless: If you’ve got anybody over there that’s good at Okta, it might not be a bad idea to send a proposal over.

120 00:08:52.640 ⇒ 00:08:54.480 Uttam Kumaran: Okay.

121 00:08:57.010 ⇒ 00:08:59.970 Uttam Kumaran: Okay, oh, signing with Okta FastPass, let’s see.

122 00:09:01.820 ⇒ 00:09:02.510 Uttam Kumaran: -Oh.

123 00:09:05.630 ⇒ 00:09:08.690 Uttam Kumaran: Yeah, I mean, it might be smart enough to still…

124 00:09:10.060 ⇒ 00:09:11.719 Katherine Bayless: Like, not let you through.

125 00:09:11.720 ⇒ 00:09:13.959 Uttam Kumaran: A user is not assigned to this application.

126 00:09:13.960 ⇒ 00:09:17.479 Katherine Bayless: Yeah, okay, okay, okay. I will let you know.

127 00:09:17.480 ⇒ 00:09:18.230 Uttam Kumaran: Okay.

128 00:09:20.000 ⇒ 00:09:20.780 Katherine Bayless: Yeah.

129 00:09:22.070 ⇒ 00:09:25.170 Katherine Bayless: Yeah. Yeah. Yeah. Yeah.

130 00:09:28.110 ⇒ 00:09:29.030 Katherine Bayless: Mondays.

131 00:09:29.170 ⇒ 00:09:30.590 Katherine Bayless: Mondays, Mondays, Mondays.

132 00:09:33.150 ⇒ 00:09:35.059 Uttam Kumaran: So let me see where we left off.

133 00:09:36.000 ⇒ 00:09:43.009 Uttam Kumaran: the last time. I think we were just starting to talk about Identity stitching stuff…

134 00:09:43.530 ⇒ 00:09:45.540 Uttam Kumaran: Let me just take a look at my…

135 00:09:45.540 ⇒ 00:09:46.360 Katherine Bayless: Yeah.

136 00:09:48.120 ⇒ 00:09:53.529 Uttam Kumaran: Yeah, so we wanted to set up Slack, we have the SDG meeting tomorrow, we’re gonna… and then…

137 00:09:53.790 ⇒ 00:09:59.400 Uttam Kumaran: Yeah, I guess I was gonna ask you about Asana, or if you care if we do stuff in linear.

138 00:10:00.550 ⇒ 00:10:24.050 Katherine Bayless: Yeah, so we have Asana, same thing, I can have Jay add you to that one. Admittedly, we have not really built anything out, my team at least. Like, the previous data team that we kind of sort of inherited the, at least the budget headcount from, they had a pretty robust Asana board that they had built out with a whole bunch of stuff, and then the data engineer that was on my team briefly kind of, sort of translated it.

139 00:10:24.820 ⇒ 00:10:37.610 Katherine Bayless: I’m very content to start fresh. Asana is the project management tool that we have here, so, like, I will try to build it in Asana, but I’m more than happy to, like, you know, marry the structure that you guys use in linear, or…

140 00:10:37.610 ⇒ 00:10:51.020 Katherine Bayless: take, you know, advice. I tend to take a very light touch with Agile, right? I’m like, I don’t do the draconian writing of user stories. Honestly, MAC is usually more useful to me, right? Like, tell me how you will know it is done.

141 00:10:51.020 ⇒ 00:10:51.670 Samuel Roberts: Yeah, yeah.

142 00:10:51.670 ⇒ 00:10:52.899 Katherine Bayless: Yeah, yeah, exactly.

143 00:10:52.900 ⇒ 00:10:59.269 Uttam Kumaran: Yeah, we’re kind of the same way. I just mainly do it as, like, let’s just start building a backlog, and then…

144 00:10:59.410 ⇒ 00:11:05.500 Uttam Kumaran: That way, it just makes it easy. If anyone’s out, anyone, like, has stuff, they can, there’s a redundancy.

145 00:11:05.640 ⇒ 00:11:13.509 Uttam Kumaran: So we’re… we’re also not too heavy. We do, we do, like, what it takes to get the job done.

146 00:11:13.780 ⇒ 00:11:14.250 Katherine Bayless: Right.

147 00:11:14.250 ⇒ 00:11:19.220 Uttam Kumaran: I would like it, I would love to have everything have, like, perfect tickets and stuff, but it’s like, you know, it’s…

148 00:11:19.460 ⇒ 00:11:21.380 Uttam Kumaran: It’s a lot of work.

149 00:11:21.380 ⇒ 00:11:41.039 Katherine Bayless: It is, it really is. I mean, like, at my last place, we had a much, like, we had a… I mean, we had a pretty nice setup. Oh, great, okay. It was, like, I mean, it took a lot of work. It was basically, like, two people that were almost, you know, full-time, just to, like, keeping that pipeline together. But yeah, like, we had it all the way through from…

150 00:11:41.390 ⇒ 00:11:43.439 Katherine Bayless: What did we use? Zendesk?

151 00:11:43.820 ⇒ 00:11:44.190 Uttam Kumaran: Okay.

152 00:11:44.190 ⇒ 00:12:02.109 Katherine Bayless: Zendesk, and then we used Target Process, was our agile, like, software, which is a weird platform, and then we had it tied through to GitHub, so that, like, you would tie the Target Process story to the Zendesk ticket, to the pull request. Right, yeah, yeah, yeah. It was nice. I don’t intend to rebuild that, because I know better than to think I will maintain it.

153 00:12:02.110 ⇒ 00:12:03.060 Uttam Kumaran: Yeah, exactly.

154 00:12:03.060 ⇒ 00:12:03.889 Samuel Roberts: Exactly, exactly.

155 00:12:03.890 ⇒ 00:12:15.630 Katherine Bayless: But yeah, so I think in terms of project management, yeah, Asana, we do need to set up. Ticketing system just generally, we do need. I mean, that is part of the…

156 00:12:16.200 ⇒ 00:12:24.119 Katherine Bayless: annoyance with the, like, account provisioning stuff is, like, I’m literally just, like, sending Jay an email, being like, hey, can you add this person? But there isn’t, like.

157 00:12:24.120 ⇒ 00:12:33.219 Uttam Kumaran: I mean, if you’d like, like, we could also… we could… I could set up a sauna, like, we don’t… we have, like, a kind of an opinionated on swim lanes, but most of it is, like.

158 00:12:33.380 ⇒ 00:12:44.810 Uttam Kumaran: we have some stuff for backlog. For me, the main thing I usually want to see is, like, what’s, like, ready? What do we… what are we doing next week? And then, like, what are we focusing on this week?

159 00:12:45.110 ⇒ 00:12:58.619 Uttam Kumaran: that’s, like, the main thing, so that way you have a little bit of scheduling, even… not everything’s sitting in backlog, also not everything sitting in, like, the spring just rolls and rolls and rolls. So, that way we start Monday, we’re kind of like, what are we doing, and then…

160 00:12:58.720 ⇒ 00:13:07.769 Uttam Kumaran: in terms of in progress, yeah, we have, like, in progress block, then we do, like, internal review, client review, and then done.

161 00:13:08.170 ⇒ 00:13:21.030 Uttam Kumaran: And then that’s… that’s usually it. So I’m happy to set that up in Asana, and then ideally, I could think about some way where if we can mirror linear and Asana, that’s fine, or we can log in there, that’s also fine.

162 00:13:21.630 ⇒ 00:13:22.490 Katherine Bayless: Okay, okay.

163 00:13:22.490 ⇒ 00:13:26.369 Uttam Kumaran: But I’m happy to set that up and just, like, start to throw stuff in there.

164 00:13:26.480 ⇒ 00:13:27.770 Uttam Kumaran: Yep. Please.

165 00:13:28.420 ⇒ 00:13:38.229 Katherine Bayless: Okay, yeah. Yeah, yeah, I think, I think that would be good. I’m, like, looking over here, because I’m like, I do have, like, stuff on the wall that I had put up that is probably things I should translate into an Asana board.

166 00:13:39.140 ⇒ 00:13:44.119 Uttam Kumaran: Yeah, and we were gonna kind of also start on, like, a Gantt chart, of stuff.

167 00:13:44.120 ⇒ 00:13:44.680 Katherine Bayless: Hmm.

168 00:13:44.680 ⇒ 00:13:48.620 Uttam Kumaran: We started using this really nice tool called Instagant.

169 00:13:48.990 ⇒ 00:13:50.559 Katherine Bayless: Yeah, yeah, yeah, yeah.

170 00:13:50.560 ⇒ 00:13:51.470 Uttam Kumaran: loving.

171 00:13:51.470 ⇒ 00:13:51.810 Katherine Bayless: Yeah.

172 00:13:51.840 ⇒ 00:13:53.940 Uttam Kumaran: And…

173 00:13:54.370 ⇒ 00:14:02.179 Uttam Kumaran: I don’t have, like, an example up, but it’s just, like, it’s just been great to, like, to use that,

174 00:14:02.440 ⇒ 00:14:11.659 Uttam Kumaran: basically for client examples. So, I’ll just start to put in things that we see, that way we have, like, a good view of, like, the future.

175 00:14:11.790 ⇒ 00:14:13.940 Uttam Kumaran: And so I’m more than happy to do that as well.

176 00:14:14.260 ⇒ 00:14:17.260 Katherine Bayless: Okay, yeah, yeah. I mean, start with Asana, but…

177 00:14:17.260 ⇒ 00:14:18.149 Uttam Kumaran: Apple, okay.

178 00:14:18.150 ⇒ 00:14:20.410 Katherine Bayless: But yeah, I do, I do love a Gantt chart.

179 00:14:23.400 ⇒ 00:14:28.889 Uttam Kumaran: Yeah, and then I guess, you know, one thing we didn’t get to last time was sort of talking through…

180 00:14:29.050 ⇒ 00:14:35.720 Uttam Kumaran: Kind of, like, what needs to happen for the identity resolution?

181 00:14:35.720 ⇒ 00:14:38.279 Katherine Bayless: We talked about snowflake setup.

182 00:14:39.830 ⇒ 00:14:52.730 Uttam Kumaran: I know we… we kind of have our docs, and I could share that with you, but how we typically set up. So what we could do is, if we set up Asana and we have tickets for, like, dbt initialization, GitHub, I can link those

183 00:14:52.870 ⇒ 00:14:59.679 Uttam Kumaran: Like, sort of our docs on how we typically do that, and that way we can have a discussion before executing those.

184 00:14:59.830 ⇒ 00:15:02.060 Uttam Kumaran: But the DBT setup.

185 00:15:02.240 ⇒ 00:15:08.250 Uttam Kumaran: Probably, like, a week or two of work. Snowflake, so, like, a week or two of work, and then…

186 00:15:08.550 ⇒ 00:15:15.289 Uttam Kumaran: Once we have those set up, we can set up version control and some type of CICD for models.

187 00:15:15.590 ⇒ 00:15:22.879 Uttam Kumaran: But that’s, like, all on the, kind of, the setup side. Yeah. And then tomorrow, we’ll kind of inform a little bit of, probably about

188 00:15:23.050 ⇒ 00:15:24.629 Uttam Kumaran: Power BI stuff.

189 00:15:26.280 ⇒ 00:15:30.800 Katherine Bayless: So, about that, yeah, so on Friday afternoon.

190 00:15:30.900 ⇒ 00:15:37.530 Katherine Bayless: I did talk to the SDG team, because I was like, I mean…

191 00:15:37.680 ⇒ 00:15:54.609 Katherine Bayless: this is more just where it’s like my little chaos monkey brain, right, trying to play in structured brains. And so they’re a very traditional consulting shop, totally fine, part of why I wanted them on board as well, right? Like, I know they’ll give us the nice buttoned-up, you know, things that I can put in front of executives’ noses, but…

192 00:15:54.950 ⇒ 00:16:09.680 Katherine Bayless: they’re also like, we want to do stakeholder interviews, and I’m like, people will cry if I ask them to give you even 5 minutes of their time right now. It is bonkers here right now, right? And so, like, the Power BI stuff, I’m kind of like, okay, maybe… Okay. Maybe I’m moving them away from that. They’re still gonna do the prototypes and stuff.

193 00:16:09.680 ⇒ 00:16:18.650 Uttam Kumaran: But I was just like, okay, I need you guys to not go down the rabbit hole of, like, trying to understand all the Power BI things. I meant more just, like, look at it and see if there’s anything useful.

194 00:16:18.650 ⇒ 00:16:33.019 Katherine Bayless: So they are going to reprioritize a little bit and focus on some of the API integrations to the data lake, because that’s something that does not need stakeholders, and frankly, is probably a little bit more relevant. So I think they’re going to start with Cvent and Marketing Cloud,

195 00:16:33.990 ⇒ 00:16:40.589 Katherine Bayless: and EventPoint, which is the system that we use for our, like, speaker management for CES,

196 00:16:40.710 ⇒ 00:17:01.630 Katherine Bayless: And then there’s another one. Oh, Shopify. Shopify, I need to ask them if they can do that one, too. But anyway, so they’re gonna kind of start that direction. So… the Power BI stuff is less timely, but I know we also have the Snowflake blocker on this end. Jay did get the support from Snowflake to reach out and schedule a time for us to get back into the Bricked account.

197 00:17:02.750 ⇒ 00:17:26.819 Katherine Bayless: I think we probably, like, at the very least, need to pursue that so that we can shut it down if we don’t want to use it, but I, I wasn’t sure if the consensus was, do we want to wait and set up the Snowflake instance, like, once AWS ProServe is on and we have the new accounts, or do we want to build and figure if we’re doing a CICD and infrastructure as code, then, like, when we get the new accounts with AWS, we’ll just

198 00:17:27.010 ⇒ 00:17:29.629 Katherine Bayless: Recreate things over there.

199 00:17:29.810 ⇒ 00:17:47.400 Uttam Kumaran: Yeah, I would say we can go ahead and start, like, I think if I could just go ahead and once we’re in Asana, I can create the tickets, and it would give me the okay, and then, yeah, we can go ahead and do that. It’ll just be running great databases and stuff. I think the biggest thing is, like, I didn’t know if I asked…

200 00:17:47.940 ⇒ 00:17:53.539 Uttam Kumaran: On Friday, about, like, if you’re planning on… there already is an ETL tool, or, like, kind of how you’re thinking about

201 00:17:53.820 ⇒ 00:17:57.429 Uttam Kumaran: like, landing some of that data from Shopify or these other providers.

202 00:17:58.170 ⇒ 00:18:00.770 Uttam Kumaran: Another vendor that you’re sort of making a decision on?

203 00:18:01.230 ⇒ 00:18:26.090 Katherine Bayless: Yeah, I mean, open to suggestions. I’m trying to kind of keep as much as I can inside the walls of AWS. I used Glue at my last place. I mean, it’s a love-hate relationship, but, like, Glue is probably my thought for the direction we’re going, just because then it’s all in AWS, and we’re kind of, you know, consolidated billing, and finance sees that as, like, the infrastructure spend, you know, kind of thing, right?

204 00:18:26.090 ⇒ 00:18:37.349 Katherine Bayless: So I wasn’t thinking about pursuing, like, a Databricks or, you know, a Matillion or something, you know, like, as a, like, ETL platform as a service, but if you feel strongly about recommending one, I will entertain proposals.

205 00:18:37.740 ⇒ 00:18:50.489 Uttam Kumaran: Okay, yeah, probably the only reason, I mean, one, we could see if there’s existing AWS glue for, like, some of the common providers. It’s just… like…

206 00:18:50.490 ⇒ 00:18:52.260 Katherine Bayless: Yeah, yeah, yeah, totally.

207 00:18:52.260 ⇒ 00:19:00.710 Uttam Kumaran: Totally. It’s just, like, one click turn on, and then it’s, like, managed infre for ETL. I… there are, like, the common…

208 00:19:00.880 ⇒ 00:19:06.010 Uttam Kumaran: sort of characters, there also are some other providers that we’ve used that are great, so happy to…

209 00:19:06.330 ⇒ 00:19:08.819 Uttam Kumaran: Even do a proof of concept, and kind of…

210 00:19:08.920 ⇒ 00:19:22.669 Uttam Kumaran: In particular, like, I used to implement a lot of Fivetran for most of my career, and then recently we switched to using this company called Polytomic. Just, like, met the CEO, and the team was really great, and we have, like, 4 or 5 clients that

211 00:19:22.670 ⇒ 00:19:30.920 Uttam Kumaran: are using them, and we have a direct line to him via Slack. He’s built a lot of connectors… their team’s built a lot of connectors directly for us.

212 00:19:31.020 ⇒ 00:19:50.660 Uttam Kumaran: They power, like, the NFL, they power Okta, like, a bunch of big brands. They just do no marketing, which I think is, like, a complete shame, because they’re priced really well, and their support is great, but all their resources go to that. So, I, yeah, could be worth considering.

213 00:19:50.660 ⇒ 00:20:08.670 Katherine Bayless: Yeah, and it’s a good point about the speed, to be honest. I think some of it is my, like, association baggage, right, where I’m just so used to those sort of connector as a platform, or, you know, connections as a service platforms being, like, yeah, maybe, like, 3 out of your 50 systems are in there, kind of a thing.

214 00:20:08.670 ⇒ 00:20:09.340 Uttam Kumaran: Yeah, yeah.

215 00:20:09.340 ⇒ 00:20:11.500 Katherine Bayless: We have 54 systems, by the way.

216 00:20:11.500 ⇒ 00:20:12.150 Uttam Kumaran: Yeah.

217 00:20:12.150 ⇒ 00:20:22.910 Katherine Bayless: But here, there might be more things that are maybe connectable. Cvent, I would be surprised, because they’re… I think they still only have a set of soap. I don’t think they have REST endpoints.

218 00:20:22.910 ⇒ 00:20:36.240 Katherine Bayless: And Salesforce Marketing Cloud, I have learned, is weirdly often not an out-of-the-box connector, because the data model is so screwy and can be so individualized on the back end, which is surprising to me, but…

219 00:20:38.230 ⇒ 00:20:40.540 Katherine Bayless: Yeah, I mean, I could go back through the list.

220 00:20:40.540 ⇒ 00:20:47.199 Uttam Kumaran: If we do a mapping of the… if we do a mapping of the sources, then what we can do is we can look at, like, what exists.

221 00:20:48.100 ⇒ 00:20:51.010 Uttam Kumaran: again, for example, for Shopify, my…

222 00:20:51.010 ⇒ 00:20:52.099 Katherine Bayless: Yeah, I mean, that one, definitely.

223 00:20:52.100 ⇒ 00:20:54.819 Uttam Kumaran: Definitely, like, go with the vendor, because…

224 00:20:55.090 ⇒ 00:21:13.569 Uttam Kumaran: It’s a really standard model, and a lot… we actually have a lot of boilerplate Shopify code built on both Fivetran and Polyatomic landed schema, so it would just help us speed up really fast. And then for stuff like Cvent, again, if there are public or private-facing APIs, the reason

225 00:21:13.910 ⇒ 00:21:17.179 Uttam Kumaran: we like these guys, they’re just… they’ll go build it.

226 00:21:17.680 ⇒ 00:21:34.820 Uttam Kumaran: So, like, I kind of just put it on them, and it’s not like… they don’t… they don’t, like, charge more. In fact, all of their connectors, they’ve sort of built for customers, and they’re good. Yeah, I don’t know, I mean, Fivetran right now… Fivetran has a… has a large swath of connectors, like, really mature, but, like, most expensive option.

227 00:21:35.840 ⇒ 00:21:36.820 Uttam Kumaran: Yeah.

228 00:21:36.820 ⇒ 00:21:37.530 Katherine Bayless: Yeah.

229 00:21:37.980 ⇒ 00:21:38.630 Uttam Kumaran: Yeah.

230 00:21:39.130 ⇒ 00:21:46.400 Katherine Bayless: Yeah, I was trying to see… I know I have this list of the systems somewhere here…

231 00:21:47.970 ⇒ 00:21:51.670 Katherine Bayless: Oh yeah, here we go. Systemsidentified.nd.

232 00:21:51.960 ⇒ 00:21:52.620 Uttam Kumaran: Great.

233 00:21:54.500 ⇒ 00:21:55.710 Katherine Bayless: Oh, okay.

234 00:21:55.850 ⇒ 00:21:58.810 Uttam Kumaran: 43 on this list. Okay.

235 00:21:58.850 ⇒ 00:21:59.849 Katherine Bayless: Alright, let’s see.

236 00:22:01.480 ⇒ 00:22:05.260 Katherine Bayless: I’ll just, for the moment, totally just gonna drop in the Zoom chat.

237 00:22:05.260 ⇒ 00:22:05.950 Uttam Kumaran: Okay.

238 00:22:09.490 ⇒ 00:22:14.469 Uttam Kumaran: Yeah, so, actually not a bad orientation, too, right? Okay, so…

239 00:22:14.900 ⇒ 00:22:20.260 Uttam Kumaran: Yeah, actually, let me, let me just, like, let me write, let me just put this in something, and then let’s just talk through it.

240 00:22:20.430 ⇒ 00:22:38.130 Katherine Bayless: Yeah. The big call-out, really, on this list is… so you see Salesforce at the top, it is… it is not… it is… it is not the, starting point that you would want it to be. The admin for that system has built a Rube Goldbergie and, sort of.

241 00:22:38.710 ⇒ 00:22:49.459 Katherine Bayless: automation thing, mostly with a personal Zapier account. And most processes in Salesforce are manual right now, and none of the integrations are working, and I’m gonna meet with her

242 00:22:49.520 ⇒ 00:23:03.050 Katherine Bayless: Tomorrow, and continue the conversation. Okay. But yeah, so yeah, not exactly the easy one, that I thought it would be when I was like, oh, great, we have Salesforce. Then Marketing Cloud, they do have APIs, yes, and I’ve…

243 00:23:03.450 ⇒ 00:23:13.259 Katherine Bayless: I mean, I’ve got, like, the tiniest proof-of-concept type code running for some of the things. That is one that I would like the SDG folks to kind of build out.

244 00:23:13.570 ⇒ 00:23:32.469 Katherine Bayless: Impexium, that is also remembers, is what they, like, rebranded to, so that’s our association management system. These are the people that we have the Snowflake data share agreement with that are continuing to pretend that Snowflake has a limitation of only being able to be deployed in one place, and I was like.

245 00:23:32.790 ⇒ 00:23:33.640 Katherine Bayless: Sorry.

246 00:23:34.070 ⇒ 00:23:42.119 Katherine Bayless: Expocad, this is another interesting one. So we had, right before this, actually, I had a meeting with this team.

247 00:23:42.800 ⇒ 00:23:50.620 Katherine Bayless: This is basically our, like, show floor management platform, right? So how we sell exhibit space, receptions, all the things,

248 00:23:51.380 ⇒ 00:24:00.689 Katherine Bayless: It is also probably the most hated piece of software at this organization. It is based on a form of CAD that, like, is out of support.

249 00:24:01.260 ⇒ 00:24:19.979 Katherine Bayless: there’s a lot to unpack on ExpoCAD. I think it’s mostly just gonna be, like, a we’ll get there later. Right now, I’m trying to do kind of, like, a needs assessment around the platform to figure out, like, okay, are there ways that we could maybe make this a little bit less draconian to deal with in the interim? It’s just a… it’s a bit of a mess. We could do a whole call on that one.

250 00:24:20.160 ⇒ 00:24:30.939 Katherine Bayless: Map Your Show is basically the same functionality, but with a little bit more feature added to it, and so we clone ExpoCAD into Map Your Show so that we can use some other features.

251 00:24:32.280 ⇒ 00:24:33.070 Katherine Bayless: It’s great.

252 00:24:33.400 ⇒ 00:24:56.929 Katherine Bayless: Cadmium has been replaced by OpenWater since the writing of this list. Open Water is, like a peer review platform, if you will, so it’s, like, used for a lot of, like, awards, grants, speaker submissions, that kind of stuff. It’s the ability for, like, you know, you solicit applications, hold onto them in the platform, and then solicit judges and have them, you know, do their whole thing and evaluate things against a rubric, etc, etc.

253 00:24:56.990 ⇒ 00:25:00.170 Katherine Bayless: We use it for our innovation awards,

254 00:25:01.250 ⇒ 00:25:16.700 Katherine Bayless: It was a bit of a disaster this year. Eventpoint, that’s the speaker management CMS. This system actually seems kind of nice. I’m interested in, like, not immediately, and not that I will say it out loud and scare my coworkers.

255 00:25:16.700 ⇒ 00:25:21.769 Katherine Bayless: But I’m actually curious if EventPoint could do a lot more than we currently have it doing.

256 00:25:22.320 ⇒ 00:25:32.730 Katherine Bayless: just not entirely sure, but it looks like a way better system in terms of being a potential CRM for CES than some of the other tools that we’ve got at play, so,

257 00:25:32.950 ⇒ 00:25:34.430 Katherine Bayless: Eyes on EventPoint.

258 00:25:34.830 ⇒ 00:25:43.119 Uttam Kumaran: Okay. Merits is the registration system for CES, so, like, everybody who registers.

259 00:25:43.740 ⇒ 00:25:51.129 Katherine Bayless: Asterisk goes through merits. Technically, speakers go through EventPoint, and exhibitors go through Map Your Show.

260 00:25:51.130 ⇒ 00:26:04.840 Katherine Bayless: Everything does eventually get back into merits, but it, it’s mostly, like, general attendee registrations that happen there. It takes 29 minutes and 36 seconds on average to complete registration.

261 00:26:05.300 ⇒ 00:26:05.960 Uttam Kumaran: Okay.

262 00:26:05.960 ⇒ 00:26:15.599 Katherine Bayless: oh, also, Map Your Show makes all of our vendors sign a form saying they won’t ping the API more than, like, so many times an hour.

263 00:26:16.190 ⇒ 00:26:27.759 Katherine Bayless: Yeah, yeah. It’s a really brittle little daisy chain between map your show… it’s like ExpoCAD to map your show to EventPoint and Mer… actually, no, EventPoint, I don’t know if it’s integrated at all, to Merits.

264 00:26:28.900 ⇒ 00:26:30.179 Katherine Bayless: Yeah, yeah.

265 00:26:30.180 ⇒ 00:26:34.239 Uttam Kumaran: And I guess while you’re going through this also, if there are internal owners.

266 00:26:34.540 ⇒ 00:26:36.519 Uttam Kumaran: I can note on their names.

267 00:26:37.450 ⇒ 00:26:41.290 Katherine Bayless: Yeah, I can, I can… yeah…

268 00:26:41.290 ⇒ 00:26:48.919 Uttam Kumaran: So after the fact, like, to give you context, for all of our clients, we just sort of spin up a little bit of, like, a documentation hub.

269 00:26:48.920 ⇒ 00:26:50.049 Katherine Bayless: Start to take.

270 00:26:50.050 ⇒ 00:26:51.150 Uttam Kumaran: notes are, like.

271 00:26:51.970 ⇒ 00:27:05.330 Uttam Kumaran: metrics or data tools, and so I’ll just kind of take notes here, and I can tag you here to just list the owners. Okay. That way, once we start ingesting, it’s clear, like, how it’s coming in, durations, and then all this…

272 00:27:05.510 ⇒ 00:27:11.790 Uttam Kumaran: I mean, ideally, we can either move this into wherever docs are easiest, or keep this in the repo, or keep this here.

273 00:27:13.340 ⇒ 00:27:23.290 Katherine Bayless: I like it. I think what I was gonna say was with the owners, like, I… so I have a table in our, little data warehouse where I’ve been tracking program owners for some of these things.

274 00:27:23.400 ⇒ 00:27:31.939 Katherine Bayless: the… this is more a question of preference. I always end up tying myself in knots, like, do I list the person or the team, right? Like…

275 00:27:33.370 ⇒ 00:27:38.730 Uttam Kumaran: I would probably list both. I could not answer, but, like.

276 00:27:38.730 ⇒ 00:27:39.670 Katherine Bayless: Yeah, yeah.

277 00:27:39.670 ⇒ 00:27:46.399 Uttam Kumaran: Because the person can leave, and then you’re like, okay, what is a functional team that’s relevant for this?

278 00:27:46.890 ⇒ 00:27:57.020 Uttam Kumaran: something I’ve done in the past. So usually, I put in… there’s, like, basically, I have, like, a, another table here that’s, like, stakeholders, and so…

279 00:27:57.270 ⇒ 00:28:04.380 Uttam Kumaran: It’s, like, that’s the relative… it pulls from this list, which is, like, who are the people, and then what are their teams, you know, so…

280 00:28:04.380 ⇒ 00:28:12.010 Katherine Bayless: Gotcha, gotcha, gotcha. Yeah, yeah, yeah, teams are probably more relevant at this point, but… yeah.

281 00:28:12.680 ⇒ 00:28:15.420 Katherine Bayless: Yeah, so in that case, then, yeah, like, Salesforce…

282 00:28:15.680 ⇒ 00:28:18.620 Katherine Bayless: That’s… obviously, it’s the sales team.

283 00:28:19.460 ⇒ 00:28:32.600 Katherine Bayless: there isn’t… yeah, because it’s, like, there’s, like, multiple people that would be the point of contact, depending on the system component in question, right? So, like, the international team uses Salesforce, that’s a different point of contact than the sales team uses Salesforce.

284 00:28:33.210 ⇒ 00:28:36.720 Katherine Bayless: I don’t know, yeah. Anyway, I’ll stay out of the nuts. Marketing Club.

285 00:28:36.720 ⇒ 00:28:42.059 Uttam Kumaran: Worst case, I’ll just put the team down, and if there’s not, like, a one person that’s, like, the best person, that’s fine.

286 00:28:42.060 ⇒ 00:28:54.759 Katherine Bayless: Yeah, that’s fair. Impexium is membership. Anna Rutter is, for the most part, the admin for that, but again, kind of shared responsibility, depending on exactly what corner you’re in.

287 00:28:55.220 ⇒ 00:29:02.740 Katherine Bayless: Expocad definitely has a person, his name is Tom Moshello. M-O-S-C-H-E-L-L-O.

288 00:29:02.990 ⇒ 00:29:08.760 Katherine Bayless: Map your show? Okay, so, okay, well, now it gets funny, because…

289 00:29:09.170 ⇒ 00:29:26.130 Katherine Bayless: Okay, I’ll do open water, and then I’ll put map your show. So Open Water currently doesn’t have a point of contact, but it is the operations team that manages the awards program. The person who was managing the awards this year has departed, and the position is open, if you know anybody who’s interested.

290 00:29:26.210 ⇒ 00:29:29.659 Katherine Bayless: So yeah, so that’s kind of like the ops team.

291 00:29:30.210 ⇒ 00:29:36.230 Katherine Bayless: So, event point, map your show, merits, decision point.

292 00:29:37.320 ⇒ 00:29:42.349 Katherine Bayless: I feel like there’s… I’m missing one or two. There’s event base, yeah.

293 00:29:42.740 ⇒ 00:29:49.140 Katherine Bayless: And Titan, who’s the security, yeah. Titan might just be on here, like, later. Yeah, it is, okay.

294 00:29:49.140 ⇒ 00:29:50.210 Samuel Roberts: Yeah, yeah.

295 00:29:50.210 ⇒ 00:30:06.700 Katherine Bayless: and pointer, yeah, okay. Anyway, so, like, these systems, they kind of form the CES tech stack, which does not currently really have an owner, so, like, the person that owns Map Your Show is the guy that works there, to a certain extent.

296 00:30:06.700 ⇒ 00:30:11.759 Katherine Bayless: Right? Like, there isn’t really a team or point of… we’re trying to figure this out, like, who should this.

297 00:30:11.760 ⇒ 00:30:14.949 Uttam Kumaran: That’s ex… that’s including ExpoCAF?

298 00:30:14.950 ⇒ 00:30:17.709 Katherine Bayless: No, Expo Guide is Tom, but Map Your Show…

299 00:30:17.710 ⇒ 00:30:20.679 Uttam Kumaran: Cadmium, Event Point, Merits, Decision Point.

300 00:30:20.680 ⇒ 00:30:38.149 Katherine Bayless: So, Open Water will be internal, we’re just recruiting for that one, but map your show, Event Point, Merits, Decision Point, and then some of the ones that are further in the list, Event Base, Titan, Pointer, Glean In, Turn Out Now, Mix Halo.

301 00:30:39.760 ⇒ 00:30:42.770 Katherine Bayless: Event co-pilot, which we have added.

302 00:30:43.160 ⇒ 00:30:50.600 Katherine Bayless: as a vendor since this list was created. Those are all the, like, CES tech stack things.

303 00:30:50.860 ⇒ 00:30:54.439 Katherine Bayless: And it’s mostly the vendors that are the point of contact on them.

304 00:30:55.200 ⇒ 00:31:00.049 Katherine Bayless: Yeah, yeah. Those are the Thursday calls that I want to get you guys on at some point.

305 00:31:00.370 ⇒ 00:31:15.439 Katherine Bayless: Cvent, since this list was created, we actually have 3 sites. So we have one for our GLA team, one for our events team, and then we have one that our international team uses for, Unveiled.

306 00:31:15.830 ⇒ 00:31:32.640 Katherine Bayless: Interestingly, even though Merits is the registration for CES, people sign up for tracks, like, session tracks via EventPoint, but then they also, would sign up for, like, receptions and lunches and forums and stuff like that, typically through individually configured Cvent sites.

307 00:31:32.700 ⇒ 00:31:44.739 Katherine Bayless: like, I’m helping our digital health team right now build out their Cvent registration site for events at CES, and so it’s like, the systems aren’t integrated. You have to be registered for CES to go to these things, but right now, they just kind of assume

308 00:31:44.950 ⇒ 00:31:48.660 Katherine Bayless: people will do the right thing. And I’m like, Have you met people?

309 00:31:48.660 ⇒ 00:31:51.420 Uttam Kumaran: There’s no gate, there’s no, like, gating, it’s just, like,

310 00:31:51.760 ⇒ 00:31:56.510 Uttam Kumaran: Or, it’s a URL, technically, but you can’t really… it’s not, like, indexed anywhere.

311 00:31:56.970 ⇒ 00:32:12.019 Katherine Bayless: No, so actually, you can gate it in Cvent, where what they do is, like, you set it up to be, like, an invitation-only or contactless-only event, and so, like, the person’s email address has to be manually allow listed in Cvent before they can get into the site, you know?

312 00:32:12.650 ⇒ 00:32:13.510 Uttam Kumaran: Yeah.

313 00:32:13.610 ⇒ 00:32:15.080 Katherine Bayless: You know, the pain.

314 00:32:15.740 ⇒ 00:32:22.119 Katherine Bayless: But I think there is a lot of interesting data in Cvent, potentially.

315 00:32:22.190 ⇒ 00:32:40.129 Katherine Bayless: Zoom, obviously, is our meetings platform. We do also do webinars and stuff like that, so, you know, a little bit of analytics around those things. Formstack has rebranded to IntelliStack, web forms, though, basically. We have, like, 600 or 700 of them, or something like that.

316 00:32:40.130 ⇒ 00:32:45.829 Katherine Bayless: We use Formstack a lot, as, like, a makeshift sort of CRM,

317 00:32:46.110 ⇒ 00:32:58.399 Katherine Bayless: its APIs are pretty good. I’ve built out, like, a couple little webhooks just to make my life easier, so, like, it’s pretty easy to interact with the platform. It’s just one of those, like, you know, any survey tool, right? It’s, like, a little too powerful, be dangerous.

318 00:32:59.130 ⇒ 00:32:59.870 Katherine Bayless: Yeah.

319 00:33:00.020 ⇒ 00:33:08.510 Katherine Bayless: Neverbounce, not Unbounce, we don’t no longer use them. That’s just email validation, right? So, check this email address, is it a spam drop? Yeah, yeah.

320 00:33:08.740 ⇒ 00:33:13.240 Katherine Bayless: That also, easy to automate. I have that piece done.

321 00:33:13.240 ⇒ 00:33:18.990 Uttam Kumaran: Are you guys use… you’re using that with… through the sign-up flow, or which… through marketing?

322 00:33:19.340 ⇒ 00:33:23.689 Katherine Bayless: Yeah, so right now, the sort of little… I mean, let’s not…

323 00:33:24.150 ⇒ 00:33:44.050 Katherine Bayless: oversell it and make it sound glamorous, but the little automation that I’ve built for the CES registration process basically ingests lists from a bunch of these different platforms, swirls them all together, checks for email addresses, runs them out to NeverBounce, brings the results back, and eventually puts together the 5 files that finally go into Marketing Cloud.

324 00:33:44.050 ⇒ 00:33:46.640 Uttam Kumaran: Where is that getting executed now, the automation?

325 00:33:47.340 ⇒ 00:33:51.940 Katherine Bayless: Well… Different places, because…

326 00:33:52.030 ⇒ 00:34:07.509 Katherine Bayless: I built it piece by piece. So the webhook from Formstack to S3 is in Lambda, which I’m not proud of. And then some of the processing is happening in a SQL file that Glue calls and runs on a database, because I’m not proud of that either. And then,

327 00:34:07.510 ⇒ 00:34:18.910 Katherine Bayless: the last mile of the automation, I admit, I have not really solved for yet, because the Salesforce Marketing Cloud option for uploading these files is an FTP server, and…

328 00:34:19.139 ⇒ 00:34:19.779 Uttam Kumaran: Hmm, wow.

329 00:34:19.780 ⇒ 00:34:39.979 Katherine Bayless: I know how to hit those, right? But I also am like, I don’t really want to deal with this right now. I’m hoping that I can just start using the APIs to send the data to Marketing Cloud and just eliminate the FTP rather than adding it to the automation. I only have to survive until January this year, you know? So, yeah. Yeah, there’s a lot of.

330 00:34:39.989 ⇒ 00:34:44.429 Uttam Kumaran: Well, it’s just helpful for me to list these automations, too, because this is, of course.

331 00:34:44.559 ⇒ 00:34:54.759 Uttam Kumaran: something that you’ll want to get sourced from Martz, and then the reverse ETL or whatever happens at that point. Okay, I’m just gonna… I’m just noting those down.

332 00:34:54.989 ⇒ 00:35:04.389 Katherine Bayless: Yeah, yeah, and I think, I mean, the automation that I have built, it can absolutely all be torn down after we get through CES this year. The salient piece of it that will matter to a certain extent

333 00:35:04.389 ⇒ 00:35:16.719 Katherine Bayless: is the hierarchy of the assignments for the groups, because there are, I think it’s, like, 28 or 30 different types of registration for CES, and they’re, like, some are invites, some are GenPop, that kind of thing.

334 00:35:16.719 ⇒ 00:35:24.969 Katherine Bayless: And so we have to make sure that everybody gets invited once into the, you know, highest attendee tier, basically.

335 00:35:25.279 ⇒ 00:35:30.799 Katherine Bayless: That part, not so bad, but the rest of it is duct tape and boxfill sticks. I’m better than this.

336 00:35:30.999 ⇒ 00:35:37.219 Katherine Bayless: Forstra, we actually don’t use anymore, but we have some old survey data in,

337 00:35:37.379 ⇒ 00:35:43.259 Katherine Bayless: Quorum is… I don’t know if you guys ever come across it in the wild, but it’s basically like a…

338 00:35:44.739 ⇒ 00:35:58.449 Katherine Bayless: it’s a CRME kind of thing, but it’s specifically intended for, like, lobbying firms, and so one of their, like, value adds is that they’ll bring in, you know, the publicly available, like, government data, right? Like, who’s in what district, and what’s their staffer’s email, right? You know, that kind of stuff.

339 00:35:58.729 ⇒ 00:36:11.099 Katherine Bayless: it’s funny, they are also a startup from DC that I used to run into at, like, startup circles things when I was working with Lineup, and I can’t stand their people, I can’t stand their product, I think it’s garbage. And when I found out CTA has it, I was like, dang it.

340 00:36:11.229 ⇒ 00:36:13.619 Katherine Bayless: But it’s fine, I can get over myself.

341 00:36:13.749 ⇒ 00:36:28.299 Katherine Bayless: That seems pretty self-sufficient, the government affairs team. However, we are currently in just, like, a dizzying array of name changes and nonsense with the government reopening, and, like, all the LIT invites are just a mess right now, but we’ll get there.

342 00:36:28.570 ⇒ 00:36:36.090 Uttam Kumaran: Yeah, I guess also maybe even, like, one question I have, like, overarching, so you mentioned, you mentioned…

343 00:36:36.990 ⇒ 00:36:42.799 Uttam Kumaran: GLA, events, international, like, what are the core org structures.

344 00:36:42.800 ⇒ 00:36:43.290 Katherine Bayless: Hmm.

345 00:36:43.570 ⇒ 00:36:47.099 Uttam Kumaran: That, that exists within, CTA.

346 00:36:47.100 ⇒ 00:36:55.660 Katherine Bayless: That’s a good question. So we are primarily organized around I mean…

347 00:36:56.560 ⇒ 00:37:04.819 Katherine Bayless: Yeah, those are probably the big buckets. So there’s the sales team, which sells the exhibit space and receptions and sponsorships and all that stuff at CES.

348 00:37:05.070 ⇒ 00:37:19.540 Katherine Bayless: Then there is the membership team, and they do the, you know, sort of follow-on, like, also, if you’re a member, you get a discount, right? Right? So there’s two different sales processes and teams, those two. Then there is also the CES operations team.

349 00:37:19.540 ⇒ 00:37:25.100 Katherine Bayless: Which is, you know, the logistics and all of the actual magic that makes it happen.

350 00:37:25.890 ⇒ 00:37:41.530 Katherine Bayless: Then, outside of that, yeah, GLA, lobbying. We have a pretty extensive tech and standards team that I admit I have not had a ton of engagement with, but they’re the people that do, like, the cyber trust mark. And the… actually, we’re getting another Emmy, apparently.

351 00:37:41.530 ⇒ 00:37:53.069 Katherine Bayless: So, they’re pretty cool, that team. They use the system that’s on this list called Causeway, which is currently not playing nice with Impexium, and I have offered to help at some point.

352 00:37:53.500 ⇒ 00:37:55.830 Katherine Bayless: Causeway might not even be on this list, actually.

353 00:37:56.730 ⇒ 00:37:57.980 Katherine Bayless: Huh, yeah.

354 00:37:58.170 ⇒ 00:38:10.700 Katherine Bayless: Okay, add Causeway to the list. Okay, so there’s tech and standards, there’s the business intelligence team, which is mostly research, forecasting. We do some work with NASDAQ on some ETFs.

355 00:38:10.990 ⇒ 00:38:17.430 Katherine Bayless: As of course, you know, finance, admin, internal operations team, right? It.

356 00:38:19.320 ⇒ 00:38:20.849 Katherine Bayless: I think that’s everybody?

357 00:38:21.020 ⇒ 00:38:21.710 Uttam Kumaran: Okay.

358 00:38:24.500 ⇒ 00:38:26.430 Katherine Bayless: Marketing, obviously.

359 00:38:27.200 ⇒ 00:38:29.229 Katherine Bayless: Oh, and we have a library team.

360 00:38:29.430 ⇒ 00:38:31.769 Katherine Bayless: We have a physical library with stacks.

361 00:38:32.440 ⇒ 00:38:34.150 Uttam Kumaran: Oh, great! Wow.

362 00:38:35.120 ⇒ 00:38:40.639 Uttam Kumaran: I feel like, sort of, for, like, just, like, tech-related, consumer tech-related, like, what… okay.

363 00:38:40.900 ⇒ 00:38:59.419 Katherine Bayless: Yeah, yeah, we actually… I mean, truthfully, even though the site is a little funny at first, we have, like… I mean, we’ve been around 100 years, right? And so, like, we actually have, like, some of the only copies of, like, certain things from, you know, long ago, right? Like, from an archival standpoint, we are kind of important, it’s just…

364 00:39:00.810 ⇒ 00:39:04.170 Katherine Bayless: Right? You’re like, is this… is this library books? Right? Yeah.

365 00:39:05.380 ⇒ 00:39:16.369 Uttam Kumaran: Okay, cool. So that helps to just get a sense of… of those. And so, okay, so I guess in… I guess from… from your side, I assume it’s, like, sales, memberships, marketing…

366 00:39:16.920 ⇒ 00:39:18.059 Uttam Kumaran: like, core…

367 00:39:19.290 ⇒ 00:39:24.129 Uttam Kumaran: Or support, or tell me, like, kind of where your… where your head is in terms of core priority.

368 00:39:24.290 ⇒ 00:39:33.889 Katherine Bayless: Yeah, so initially, like, when I started, it was, yeah, like, sales, membership, marketing. It was like, okay, those are kind of the three legs of the stool that I can pursue that make the most sense.

369 00:39:34.350 ⇒ 00:39:42.370 Katherine Bayless: I’ve not ended up doing a ton of work with the sales team this year. I think probably after CES will be a chance to sort of

370 00:39:43.160 ⇒ 00:39:55.039 Katherine Bayless: help, see how I can help in that world. Truthfully, my thought is that knowing that we have two teams prospecting the same audience, I’m like, well, that’s my in, right? Like, that data needs to be synchronized.

371 00:39:55.040 ⇒ 00:40:14.479 Katherine Bayless: So… sales I haven’t worked with as much. Marketing, I’ve worked with really extensively. Membership is really eager to work with us, we’re just waiting on this data share thing. But beyond that, I would say the CES, like, ops team, like, the event logistics, getting registrations through all that kind of stuff, yeah, yeah.

372 00:40:14.810 ⇒ 00:40:34.340 Katherine Bayless: Also, our own finance and admin team could really use my help and love and assistance, but they are not the top of the, you know, pile, and so I’m like, I’m sorry, guys, I promise I’ll get to you, though. Oh, and we have a foundation, I guess I should mention that, too. He would like to work with us as well at some point, but same thing, not exactly top of the pile.

373 00:40:34.570 ⇒ 00:40:36.690 Uttam Kumaran: Okay, okay, great, that’s all.

374 00:40:37.210 ⇒ 00:40:37.890 Katherine Bayless: Yeah.

375 00:40:38.860 ⇒ 00:40:43.540 Uttam Kumaran: Okay, cool. Maybe back to… to sources. So…

376 00:40:44.380 ⇒ 00:40:47.930 Uttam Kumaran: Maybe let’s go to a couple that I do recognize.

377 00:40:47.930 ⇒ 00:40:50.200 Katherine Bayless: Sure. You also have SurveyMonkey?

378 00:40:50.900 ⇒ 00:40:54.920 Katherine Bayless: We don’t use SurveyMonkey anymore, so some of these we have data in, so, like.

379 00:40:54.920 ⇒ 00:40:57.719 Uttam Kumaran: And that’s for us to kind of get out and store, yeah. Okay, perfect.

380 00:40:57.720 ⇒ 00:41:01.780 Katherine Bayless: Yeah, so Qualtrics is who we’re currently using for surveying, yeah.

381 00:41:02.530 ⇒ 00:41:09.070 Katherine Bayless: Our surveys get, like, a less than 1% response rate. That team is very interested in working with me.

382 00:41:09.070 ⇒ 00:41:11.739 Uttam Kumaran: Is that in… is that sales, or is that,

383 00:41:12.460 ⇒ 00:41:15.640 Uttam Kumaran: I guess there’s a variety of people that probably use surveys, but okay.

384 00:41:15.640 ⇒ 00:41:19.760 Katherine Bayless: So actually, all surveying does go through the business intelligence team.

385 00:41:19.760 ⇒ 00:41:21.449 Uttam Kumaran: Okay, okay, great.

386 00:41:21.450 ⇒ 00:41:22.130 Katherine Bayless: Yeah.

387 00:41:23.610 ⇒ 00:41:28.690 Katherine Bayless: Yeah, massive opportunity to figure out how to engage that audience, because it’s.

388 00:41:28.690 ⇒ 00:41:29.160 Uttam Kumaran: Cool.

389 00:41:29.860 ⇒ 00:41:31.180 Katherine Bayless: Got nothing. Yeah.

390 00:41:31.180 ⇒ 00:41:44.530 Uttam Kumaran: I don’t like hearing low numbers, but I also like hearing that, because there’s also so much we could do, like, should go look at, like, all how surveys have been done, and there’s definitely, like, a quick analysis that we can turn around. So, okay.

391 00:41:44.950 ⇒ 00:41:49.859 Uttam Kumaran: So, SurveyMonkey, and then Qualtrics is on here somewhere.

392 00:41:50.710 ⇒ 00:41:52.310 Katherine Bayless: Yeah, kind of middle-ish.

393 00:41:53.140 ⇒ 00:41:53.840 Uttam Kumaran: Hello?

394 00:41:54.590 ⇒ 00:41:58.329 Uttam Kumaran: I know Okta is used for, like, auth.

395 00:41:59.840 ⇒ 00:42:11.459 Katherine Bayless: One thing that’s worth calling out with Okta is we do use it for, like, staff, but also for all of our external audience. So, like, in order to register for CGAS, you have to have an Okta account.

396 00:42:11.460 ⇒ 00:42:12.150 Uttam Kumaran: Really?

397 00:42:12.150 ⇒ 00:42:12.840 Katherine Bayless: Yeah.

398 00:42:13.320 ⇒ 00:42:14.310 Uttam Kumaran: Oh, wow.

399 00:42:14.310 ⇒ 00:42:16.359 Katherine Bayless: And I don’t think that any of us.

400 00:42:17.230 ⇒ 00:42:23.289 Uttam Kumaran: It’s gotta be an expensive contract. Right, right. But very secure. I mean…

401 00:42:24.020 ⇒ 00:42:34.100 Katherine Bayless: I mean, to a fault, right? Because obviously, you know, you register for an event once a year, and so nobody remembers that password, and so it just creates more headaches than it solves.

402 00:42:34.430 ⇒ 00:42:39.169 Uttam Kumaran: Yeah. Yeah. Okay. Oh, alright.

403 00:42:39.170 ⇒ 00:42:49.289 Katherine Bayless: 4J, like, he’s got, like, layers and layers and layers in his Okta setup that he’s just trying to unpack, and I’m like, dude, like, we probably just shouldn’t have used this for all 1 million.

404 00:42:49.290 ⇒ 00:42:55.470 Uttam Kumaran: Oh, but, you know, even again, like, what can the data team help with? Like, I’m sure he could go disable people that haven’t ever registered, or, like, your.

405 00:42:55.470 ⇒ 00:42:55.900 Katherine Bayless: Right.

406 00:42:55.900 ⇒ 00:42:58.230 Uttam Kumaran: Probably a bunch of low-hanging fruit there, too.

407 00:42:58.470 ⇒ 00:42:58.990 Katherine Bayless: Right.

408 00:42:58.990 ⇒ 00:43:00.630 Uttam Kumaran: M365.

409 00:43:00.630 ⇒ 00:43:01.830 Katherine Bayless: It’s just like…

410 00:43:02.410 ⇒ 00:43:04.599 Uttam Kumaran: The normal business suite of tools.

411 00:43:04.820 ⇒ 00:43:11.739 Katherine Bayless: Yeah, with the asterisk, I guess, that SharePoint is still our document management platform.

412 00:43:11.740 ⇒ 00:43:12.290 Uttam Kumaran: Okay.

413 00:43:12.570 ⇒ 00:43:13.930 Katherine Bayless: So, yeah.

414 00:43:14.120 ⇒ 00:43:19.769 Katherine Bayless: Yeah. Jay’s open to moving to Vox and piloting next year. I’ve been aggressive in my campaign.

415 00:43:19.770 ⇒ 00:43:28.089 Uttam Kumaran: I remember, after you mentioned it, now I kept… I told a bunch of people, I’m like, yeah, apparently Box is, like, not what you think it is.

416 00:43:30.040 ⇒ 00:43:37.289 Katherine Bayless: It’s cool! It’s really cool. But yeah, so M365 is, yeah, just Office software, but SharePoint-heavy here.

417 00:43:37.650 ⇒ 00:43:41.220 Uttam Kumaran: And then Concur is, what, for travel, like, expense management?

418 00:43:41.220 ⇒ 00:43:56.709 Katherine Bayless: Yeah, Concur… so, in fact, specifically, Ironclad and Concur are what the finance team would like me to help them integrate at some point. So, Ironclad is our contracting tool. I don’t know if any of the emails that you’ve got… yeah, yeah, yeah, okay, yeah. So, right now…

419 00:43:56.710 ⇒ 00:44:03.479 Katherine Bayless: Actually, I’ll use you guys as an example. When you eventually wind up submitting an invoice for payment, it will go into Concur.

420 00:44:03.550 ⇒ 00:44:11.760 Katherine Bayless: But those two systems aren’t integrated, so the finance team has to go manually find the contract in Ironclad to link it across, right, right, the whole thing.

421 00:44:11.900 ⇒ 00:44:13.419 Katherine Bayless: I think they want to use…

422 00:44:13.900 ⇒ 00:44:27.360 Katherine Bayless: purchase orders, the functionality in Concur to do this, even though they wouldn’t be purchase orders? I don’t know, they’ve got this whole thing kind of, like, imagined that I’m like, I think I’m gonna have a lot of questions before we do anything.

423 00:44:27.610 ⇒ 00:44:35.179 Uttam Kumaran: Yeah, we’re… I mean, we… we do this in our business all the time, so very familiar with this problem.

424 00:44:35.180 ⇒ 00:44:35.520 Katherine Bayless: Yeah.

425 00:44:35.520 ⇒ 00:44:39.399 Uttam Kumaran: Yeah, okay, great. So, cool, there’ll be something there.

426 00:44:40.020 ⇒ 00:44:41.240 Uttam Kumaran: SmartBrief?

427 00:44:41.730 ⇒ 00:44:55.369 Katherine Bayless: Yeah, I think you can ignore that one. I think… I thought it was a system, because it used to be, but it isn’t anymore, but I feel like every time I bring it up, I get a different answer, so I stopped asking. I don’t think it’s a system, as far as I can tell.

428 00:44:55.980 ⇒ 00:44:58.329 Uttam Kumaran: Alright, I’ll just put maybe ignore a question.

429 00:44:58.530 ⇒ 00:45:05.630 Uttam Kumaran: Zapier… is there… is Zapier just, like, plat… everybody in the company’s using it for stuff? Is there any, like…

430 00:45:06.220 ⇒ 00:45:11.080 Katherine Bayless: So, it is just the one person on the… Okay. Yeah. Okay, great. Awesome.

431 00:45:11.560 ⇒ 00:45:18.829 Katherine Bayless: Yeah, and we are trying to figure out how to gently Indiana Jones the account, because it’s on her personal.

432 00:45:19.290 ⇒ 00:45:20.279 Uttam Kumaran: Okay, okay.

433 00:45:20.280 ⇒ 00:45:22.479 Katherine Bayless: Yeah. Yeah. Yeah.

434 00:45:23.770 ⇒ 00:45:28.160 Uttam Kumaran: Cool, and then… I know Gleene, like, the new company, Gleene.

435 00:45:28.510 ⇒ 00:45:31.570 Katherine Bayless: Yeah, yeah, the AI, like, corporate knowledge tool, yeah.

436 00:45:31.570 ⇒ 00:45:32.859 Uttam Kumaran: Still working for you guys?

437 00:45:34.120 ⇒ 00:45:39.429 Uttam Kumaran: I just, I was on the phone with somebody two weeks ago, and they’re like.

438 00:45:39.580 ⇒ 00:45:47.570 Uttam Kumaran: Have you heard about Glean recently? I was like, no, but there were the Rays for a while, and then he was like, yeah, it’s not… nope, it’s not worked at all.

439 00:45:47.570 ⇒ 00:45:48.160 Katherine Bayless: -

440 00:45:48.160 ⇒ 00:45:50.259 Uttam Kumaran: But they, like, go through PSCs, and it…

441 00:45:50.650 ⇒ 00:45:53.659 Uttam Kumaran: And, yeah, so, okay, that sucks.

442 00:45:53.660 ⇒ 00:45:55.849 Katherine Bayless: Yeah. I would love to see…

443 00:45:55.870 ⇒ 00:45:58.789 Uttam Kumaran: How… how it doesn’t work at some point, but okay.

444 00:45:58.790 ⇒ 00:46:10.779 Katherine Bayless: Truthfully, like, the one thing that Glean decided that just drives me personally crazy is they call their, like, their equivalent of, like, a custom GPT, they call it an agent.

445 00:46:11.340 ⇒ 00:46:16.910 Uttam Kumaran: And it drives me insane, because it means I have to talk to all of my coworkers about agents that are not agents, right?

446 00:46:16.910 ⇒ 00:46:22.300 Katherine Bayless: They are scripted conversations with AI over our garbage, like, SharePoint deployment, right?

447 00:46:22.430 ⇒ 00:46:22.950 Uttam Kumaran: Yeah.

448 00:46:22.950 ⇒ 00:46:38.420 Katherine Bayless: And truthfully, I think that is why, like, I’m, like, I’m pushing so hard with Box, because, like, what that company is trying to do is figure out, like, okay, what is the actual semantic, ontological relationship of your information so that we can use it? Whereas Lean is just like, what if you could ask a question of every version?

449 00:46:38.420 ⇒ 00:46:40.920 Uttam Kumaran: Like, out of the box?

450 00:46:40.920 ⇒ 00:46:41.670 Katherine Bayless: I’m sorry?

451 00:46:41.670 ⇒ 00:46:45.559 Uttam Kumaran: Does Box have MCPs, like, out of the box, like, they provide, or…

452 00:46:45.560 ⇒ 00:47:00.859 Katherine Bayless: They do… I think… don’t quote me off the top of my head, but I do think that they did that kind of, like, annoying thing where they, like, invented a new super enterprise tier, if you want MCP or something, because I feel like I’ve had a few friends complain about, like, we… turned out we didn’t have the box we thought we did, kind of thing.

453 00:47:00.860 ⇒ 00:47:01.699 Uttam Kumaran: Yeah, I know.

454 00:47:01.990 ⇒ 00:47:17.309 Uttam Kumaran: Yeah, we have a similar thing, you know, I always go back and forth. At this point, like, I’m almost at the point, and Sam knows this, where I’m like, let’s just have everything in GitHub, and as much as we can, MCP’d into my linear… into my cursor.

455 00:47:17.570 ⇒ 00:47:21.009 Uttam Kumaran: Because then that’s, like, kind of the route.

456 00:47:22.210 ⇒ 00:47:24.890 Katherine Bayless: I like watching Sam sit back as you said that.

457 00:47:24.890 ⇒ 00:47:28.610 Samuel Roberts: Yeah. Yeah, I was like, oh boy, oh yeah!

458 00:47:28.730 ⇒ 00:47:33.369 Uttam Kumaran: Because I, yeah, I just, like, I know too much, because I’m also an engineer.

459 00:47:33.540 ⇒ 00:47:34.189 Katherine Bayless: But bye.

460 00:47:34.190 ⇒ 00:47:38.779 Uttam Kumaran: Do all these business things all day, and… so painful.

461 00:47:38.990 ⇒ 00:47:44.009 Uttam Kumaran: that, like, I have to write, like, I have to write raw in a Google Doc, and I’m like.

462 00:47:44.100 ⇒ 00:47:46.870 Uttam Kumaran: Finding all these ways of getting around that.

463 00:47:46.930 ⇒ 00:48:00.159 Uttam Kumaran: But truly, like, a cursor interface on, like, whatever I’m… like, you… people should be using cursor more often for writing, like, even in this example, like, if it’s just us that are gonna access this docs, I’m gonna move this to… to our repo.

464 00:48:00.160 ⇒ 00:48:10.489 Uttam Kumaran: And I will make tables and markdown, and so you can interact with those. So, for some clients, like, that’s never gonna happen, they’re never gonna get there, so we sort of have to, like.

465 00:48:11.040 ⇒ 00:48:11.420 Katherine Bayless: Damn.

466 00:48:11.420 ⇒ 00:48:21.679 Uttam Kumaran: these docs that may or may not end up stale, but I want everything in a… to be accessed right where our logic is, because that’s all the context, you know? Yeah.

467 00:48:21.990 ⇒ 00:48:22.640 Katherine Bayless: Right?

468 00:48:22.640 ⇒ 00:48:23.040 Samuel Roberts: Yeah.

469 00:48:23.040 ⇒ 00:48:35.350 Uttam Kumaran: Yeah. Yeah. Yeah, that’s what I think, and then… and then the more people that are using Cursor to write docs, or you can then ask questions and… over the repo, and stuff like that is a lot better, you know, so…

470 00:48:35.350 ⇒ 00:48:45.810 Katherine Bayless: Yeah, like, I would love to figure out, like, doc classification in, like, a streaming context. Like, everything you touch all the time is just being autosaved into.

471 00:48:45.810 ⇒ 00:48:46.240 Uttam Kumaran: Yes.

472 00:48:46.240 ⇒ 00:48:48.909 Katherine Bayless: And it’s deciding, in the moment, what’s in the document.

473 00:48:48.910 ⇒ 00:48:51.869 Uttam Kumaran: Yeah, we use Notion for a lot of stuff, and…

474 00:48:52.030 ⇒ 00:48:56.799 Uttam Kumaran: I don’t know, I’m starting to, like, regret the decision, but I also don’t know what the alternative is, like…

475 00:48:56.920 ⇒ 00:49:00.029 Uttam Kumaran: not everyone in the company is, like, technical enough to use, like, Obsidian.

476 00:49:00.600 ⇒ 00:49:00.940 Katherine Bayless: Yeah.

477 00:49:00.940 ⇒ 00:49:03.719 Uttam Kumaran: And, like, we have to do a lot of external sharing.

478 00:49:04.800 ⇒ 00:49:23.260 Uttam Kumaran: But, like, if it was up to me, like, the whole company, I would run on… I would just run out of repos, and I’d be like… I would just mix… we… I would just say you can only use… mainly, for the most part, until recently, we were using Google Drive just for, like, PDFs and contracts. Like, we never use Google Docs, but Notion is, like, kind of tough to get stuff out.

479 00:49:23.540 ⇒ 00:49:30.910 Uttam Kumaran: it’s nice, it’s all marked down, but it’s, like, they don’t… the APIs kind of suck, so we’re using some, like, off-market API for stuff.

480 00:49:31.970 ⇒ 00:49:35.360 Katherine Bayless: That’s funny, one of the guys in the car gang actually works for Notion.

481 00:49:35.360 ⇒ 00:49:36.010 Uttam Kumaran: Oh, great.

482 00:49:36.010 ⇒ 00:49:39.360 Katherine Bayless: Shit. I’m like, I didn’t realize they don’t have great APIs. I would have assumed.

483 00:49:39.360 ⇒ 00:49:46.670 Uttam Kumaran: Yeah, the API stuff, you can tell them. It took them years to release offline, so before you open your laptop and you couldn’t…

484 00:49:46.670 ⇒ 00:49:47.240 Samuel Roberts: Oh, yeah.

485 00:49:47.240 ⇒ 00:49:48.950 Uttam Kumaran: Product, like, on a plane.

486 00:49:49.260 ⇒ 00:50:00.459 Uttam Kumaran: That’s, like, a use case for writing, and… Right. They’ve just, like, been really slow, and their AI product is another, like, 20, 30 bucks a user on top of their additional…

487 00:50:00.850 ⇒ 00:50:03.039 Uttam Kumaran: 20, 30 bucks a user, and so…

488 00:50:03.490 ⇒ 00:50:04.290 Katherine Bayless: Yeah.

489 00:50:04.510 ⇒ 00:50:06.010 Katherine Bayless: Yeah.

490 00:50:08.280 ⇒ 00:50:11.340 Uttam Kumaran: Okay, so Glean is… who is… who owns that?

491 00:50:11.340 ⇒ 00:50:28.109 Katherine Bayless: Okay, so Glean, in that case, there is an owner in terms of, like, administering it as a platform. There is definitely no ownership of the thing it sits on top of, right? But, Jay from IT, right? So he, owns and administers Glean, yeah.

492 00:50:28.990 ⇒ 00:50:45.149 Katherine Bayless: Yeah. And actually, I guess I should say now, too, on this list, it’s not present, but we do also have Enterprise, ChatGPT, and then Anthropic Claude, so… he… technically, I’m kinda sorta the owner for Claude, but mostly just because I was the one who put in the budget request, but…

493 00:50:45.150 ⇒ 00:50:51.039 Katherine Bayless: he’s at least the admin for the OpenAI side, and I think increasingly, probably, we’ll take over, like.

494 00:50:51.250 ⇒ 00:50:53.859 Katherine Bayless: provisioning of users and stuff like that for Claude.

495 00:50:54.420 ⇒ 00:50:58.180 Uttam Kumaran: Okay, great. Any reason you have both, just to, like, add different models?

496 00:50:58.180 ⇒ 00:51:11.579 Katherine Bayless: I mean, I think, honestly, it’s mostly just because I’m a brat, because when I got here and tried Glean, I was like, this is not gonna work for me. And they were like, well, we have ChatGPT, and I was like, yeah, I like Claude better, though, because I’m a developer type.

497 00:51:11.810 ⇒ 00:51:12.600 Katherine Bayless: So, yeah.

498 00:51:12.600 ⇒ 00:51:21.710 Uttam Kumaran: We have everything. I… we just ended up centralizing a lot, because we’re… we… we ended up with a bunch of Azure credits, so I’m like, okay, everything’s GPT.

499 00:51:22.050 ⇒ 00:51:30.639 Katherine Bayless: Yeah, yeah, yeah. And I mean, truthfully, I was telling our AWS account rep, when I talked to him a week or so ago, I was like, that’s really kind of just like to disintermediate the platforms, right?

500 00:51:30.640 ⇒ 00:51:31.420 Uttam Kumaran: Yeah, yeah.

501 00:51:31.420 ⇒ 00:51:33.310 Katherine Bayless: Yeah, yeah. I mean, so I have a Wi-Fi.

502 00:51:33.310 ⇒ 00:51:45.619 Uttam Kumaran: You know, I said, we’re not gonna be married, because who knows, and like, I don’t really care who wins. Right. I want us to win. Whoever we… whoever’s the flavor of the month this month, we can be easily swappable, you know?

503 00:51:46.100 ⇒ 00:51:51.409 Katherine Bayless: Exactly, exactly. And so, I’ve done a little wiring of it up in Bedrock, but…

504 00:51:51.750 ⇒ 00:51:52.120 Uttam Kumaran: Cool.

505 00:51:52.120 ⇒ 00:51:53.250 Katherine Bayless: Time is the enemy.

506 00:51:54.360 ⇒ 00:51:56.770 Uttam Kumaran: Okay, Decipher?

507 00:51:56.990 ⇒ 00:52:00.939 Katherine Bayless: Another former survey tool, not currently in use.

508 00:52:01.780 ⇒ 00:52:05.830 Uttam Kumaran: Okay, I’ll just go… Umbraco? Umbraco?

509 00:52:05.830 ⇒ 00:52:22.189 Katherine Bayless: So that’s our web, so instead of, like, like Drupal, right, or Sitefinity, whatever, like, we’re on an Umbraco platform. This has been an absolute nightmare this year, that I’m, like, a couple degrees removed from, fortunately. Apparently, our hosting vendor, not great.

510 00:52:22.290 ⇒ 00:52:27.999 Katherine Bayless: Web support, we don’t really have somebody on staff to do it, and so, like, we’ve got a web dev…

511 00:52:28.130 ⇒ 00:52:36.390 Katherine Bayless: on the IT team who handles, like, code updates, but I’m like, I don’t, like, what code updates are we making on our website on a day-to-day basis?

512 00:52:37.010 ⇒ 00:52:51.479 Katherine Bayless: I have a lot of questions that I don’t ask about the website, but I also apparently am made to understand that Umbraco made it very difficult for us to find vendors that would work with us, because it is one of the, like, closed-source platforms, and people don’t like those.

513 00:52:52.920 ⇒ 00:52:53.530 Uttam Kumaran: Yeah.

514 00:52:54.210 ⇒ 00:52:55.609 Katherine Bayless: Yeah. Litness?

515 00:52:56.300 ⇒ 00:52:58.810 Katherine Bayless: I don’t know.

516 00:52:59.250 ⇒ 00:53:04.269 Katherine Bayless: I don’t know. I don’t know. I wrote that one down, but I don’t have any recollection of where I picked that one up.

517 00:53:04.920 ⇒ 00:53:08.500 Uttam Kumaran: I assume GA is just on the site itself for analytics?

518 00:53:08.730 ⇒ 00:53:32.360 Katherine Bayless: Yeah, we actually have a pretty dope Google Analytics deployment. So we work with this firm called Orange Spark, and they’ve set up BigQuery and Looker Studio for our dashboards, and, like, it’s nice. It’s a nice setup in there. Where we fall short is, I think most companies, the same kind of thing, like, we just don’t really use the information a lot. I think folks here don’t really understand how to connect.

519 00:53:32.920 ⇒ 00:53:33.300 Uttam Kumaran: Yeah.

520 00:53:33.300 ⇒ 00:53:38.799 Katherine Bayless: Right, so I’m… I’m like, I will help, I will help bring them along on this journey. But the setup’s pretty nice.

521 00:53:39.040 ⇒ 00:53:56.859 Katherine Bayless: at the moment, and this… I take some of the blame, because I should have known better, the person who was the owner of the Google Analytics and BigQuery accounts, she has left. And, I didn’t realize I have, like, data editor admin access, but not admin admin, and so I can’t manage users.

522 00:53:56.860 ⇒ 00:54:03.079 Katherine Bayless: And so I am trying to convince Google Cloud to, you know, Give her account back.

523 00:54:03.340 ⇒ 00:54:04.069 Uttam Kumaran: Yeah, yeah.

524 00:54:05.330 ⇒ 00:54:07.999 Katherine Bayless: Yeah, I’m not proud of myself on that one.

525 00:54:08.640 ⇒ 00:54:09.200 Katherine Bayless: Yeah.

526 00:54:09.580 ⇒ 00:54:13.230 Uttam Kumaran: So, we talked… so, Presto and Event Base.

527 00:54:14.270 ⇒ 00:54:17.880 Katherine Bayless: Presto is.

528 00:54:19.120 ⇒ 00:54:20.430 Uttam Kumaran: That’s what I’m thinking about?

529 00:54:21.230 ⇒ 00:54:23.490 Katherine Bayless: It’s like, oh, it’s not press…

530 00:54:23.900 ⇒ 00:54:26.549 Uttam Kumaran: Got it. It’s not like AWS, presto.

531 00:54:26.550 ⇒ 00:54:30.010 Katherine Bayless: No, it’s not… yeah, yeah, it’s not that one. It’s like,

532 00:54:30.680 ⇒ 00:54:41.729 Katherine Bayless: it’s like a, like a news service, kind of a thing. And so it’s our library team uses it for, like, press releases, but not outbound…

533 00:54:42.600 ⇒ 00:54:43.400 Uttam Kumaran: Oh, okay.

534 00:54:43.400 ⇒ 00:54:44.890 Katherine Bayless: Let me see if I can…

535 00:54:50.980 ⇒ 00:54:52.000 Katherine Bayless: Hmm.

536 00:54:57.040 ⇒ 00:54:59.070 Uttam Kumaran: Presto, oh.

537 00:55:00.310 ⇒ 00:55:02.430 Katherine Bayless: I don’t know. I’d have to…

538 00:55:03.000 ⇒ 00:55:04.350 Uttam Kumaran: We can find out.

539 00:55:05.190 ⇒ 00:55:12.269 Katherine Bayless: Yeah, because it’s not one of the systems that… here we go. Oh, you know what, actually, maybe it is the AWS thing, now that I’m saying this.

540 00:55:13.900 ⇒ 00:55:14.899 Katherine Bayless: Hey, here, I’ll share my screen.

541 00:55:14.900 ⇒ 00:55:15.780 Uttam Kumaran: It’s just like…

542 00:55:17.150 ⇒ 00:55:19.480 Katherine Bayless: It’s whatever this is.

543 00:55:24.120 ⇒ 00:55:26.749 Katherine Bayless: Today might actually be presto.

544 00:55:27.730 ⇒ 00:55:28.890 Katherine Bayless: the database.

545 00:55:30.350 ⇒ 00:55:31.070 Uttam Kumaran: Okay.

546 00:55:31.610 ⇒ 00:55:37.040 Katherine Bayless: But yeah, it’s like, news archiving.

547 00:55:37.040 ⇒ 00:55:40.400 Uttam Kumaran: Oh, it looks like some type of, like, PR Newswire type thing, maybe?

548 00:55:40.400 ⇒ 00:55:52.950 Katherine Bayless: Yeah, yeah, and so, like, it’s funny, I was assuming that it is a product that we have purchased, but my inability to Google the thing and find out anything about it tells me that it maybe is something we had built? I don’t know.

549 00:55:53.370 ⇒ 00:55:59.090 Uttam Kumaran: Oh, it looks like a CTA, it looks kind of like a CTA thing. Okay, so… Alright, there’s nothing.

550 00:56:00.160 ⇒ 00:56:02.279 Katherine Bayless: Alright, well now I have questions, but yeah.

551 00:56:02.730 ⇒ 00:56:07.320 Uttam Kumaran: Yeah, so that’s what Presto is. So maybe it is the AWS thing. Okay.

552 00:56:07.320 ⇒ 00:56:10.510 Katherine Bayless: Eventbase is our mobile app,

553 00:56:10.630 ⇒ 00:56:20.789 Katherine Bayless: they are, not anybody’s, like, favorite favorite, but they’re decent, and so I think everybody’s, like, you know, willing to put up with

554 00:56:20.930 ⇒ 00:56:23.830 Katherine Bayless: Written in ColdFusion, in case you’re curious.

555 00:56:24.360 ⇒ 00:56:25.000 Uttam Kumaran: Okay.

556 00:56:25.000 ⇒ 00:56:38.140 Katherine Bayless: Great. Sonic was gonna help us add AI to CES, and when I told their AI lead that we use a cold fusion backend for our mobile app, she laughed at me, and I was like, that’s the right response. That’s the right response.

557 00:56:39.230 ⇒ 00:56:44.659 Uttam Kumaran: Yeah, very interesting. Oh, wait, I just googled it, they said Cold Fusion Builder End of Life.

558 00:56:47.340 ⇒ 00:56:52.199 Katherine Bayless: she’s like, have you heard of Flutter? And I was like, I have definitely heard of Flutter, yes.

559 00:56:55.130 ⇒ 00:57:01.989 Katherine Bayless: Yeah, so I think… I think Fedbase might be on a two-year contract at present, so, like, I think we might be stuck with them for a little longer, but the.

560 00:57:01.990 ⇒ 00:57:02.389 Samuel Roberts: I don’t know.

561 00:57:02.390 ⇒ 00:57:05.750 Katherine Bayless: I think there’s a lot of willingness to go to Flutter.

562 00:57:06.430 ⇒ 00:57:07.210 Samuel Roberts: Yeah.

563 00:57:08.220 ⇒ 00:57:18.160 Katherine Bayless: There’s also something squirrely with our Apple developer account that I don’t understand. Like, I think we have, like, a shitty tier of it or so? I don’t know. That’s a question for Jay.

564 00:57:18.160 ⇒ 00:57:20.099 Uttam Kumaran: Do you guys have analytics on the app?

565 00:57:21.070 ⇒ 00:57:23.390 Katherine Bayless: Not that I know of. I haven’t seen any.

566 00:57:23.510 ⇒ 00:57:24.360 Katherine Bayless: Yeah.

567 00:57:24.520 ⇒ 00:57:27.350 Katherine Bayless: Yeah. I’m sure they’re somewhere, maybe?

568 00:57:27.820 ⇒ 00:57:28.280 Uttam Kumaran: Okay.

569 00:57:28.280 ⇒ 00:57:29.000 Katherine Bayless: Beebeep.

570 00:57:29.350 ⇒ 00:57:30.290 Katherine Bayless: Baby.

571 00:57:30.640 ⇒ 00:57:33.500 Uttam Kumaran: And then what is Shopify use for just checkout?

572 00:57:34.930 ⇒ 00:57:35.940 Katherine Bayless: You know…

573 00:57:36.460 ⇒ 00:57:49.020 Katherine Bayless: So Shopify, as far as I understand, we brought it on to replace… so Impexium, remembers, has, like, a store component, so members can purchase, like, research and that kind of stuff.

574 00:57:50.090 ⇒ 00:58:01.239 Katherine Bayless: I think the idea was that that interface was not great, and also we sometimes want people who are not members to be able to buy stuff, but not give them the annoyance of creating the Impexium account, and so we brought Shopify in.

575 00:58:01.400 ⇒ 00:58:17.500 Katherine Bayless: I am unclear on whether or not Shopify is essentially, like, just front-ending for the Impexium store, but I see hundreds and hundreds and hundreds of failed API calls a day on Impexium’s side, looking up products, and I’m like, well, we don’t even use your store, so…

576 00:58:17.890 ⇒ 00:58:36.899 Katherine Bayless: in defense, the team that, manages Shopify has been begging me to help them, and I’m just like, I just haven’t had a chance yet. But yeah, so there’s something… something funky with our Shopify, and I think we also have a challenge where, like, people can check out, but then the downloads aren’t always working. I don’t know.

577 00:58:36.900 ⇒ 00:58:40.289 Uttam Kumaran: I’m curious if Shopify… I’ll use that for BI, then?

578 00:58:41.400 ⇒ 00:58:42.829 Uttam Kumaran: that owns Shopify.

579 00:58:43.230 ⇒ 00:58:49.760 Katherine Bayless: So finance, kinda, sorta, and then IT, kinda, sorta, and then membership, kinda, sorta.

580 00:58:50.830 ⇒ 00:58:51.399 Uttam Kumaran: Yeah, we…

581 00:58:51.400 ⇒ 00:58:51.920 Katherine Bayless: There is…

582 00:58:51.920 ⇒ 00:58:54.089 Uttam Kumaran: We do a lot of Shopify work.

583 00:58:54.520 ⇒ 00:58:55.010 Uttam Kumaran: arms.

584 00:58:55.010 ⇒ 00:58:55.610 Katherine Bayless: Yay.

585 00:58:55.610 ⇒ 00:58:55.990 Uttam Kumaran: Oh.

586 00:58:55.990 ⇒ 00:59:11.139 Katherine Bayless: I mean, like, there’s no BI coming out of it. Like, the finance team, like, has nothing, but I also don’t think we do a lot of sales, right? So it’s like, it’s not the thing to, like, go towards, like, first first, right? I mean, it needs the attention, but it’s like…

587 00:59:11.830 ⇒ 00:59:17.579 Katherine Bayless: Great, here’s your sales report on $10,000outofour$120 million that we need this year, right?

588 00:59:17.580 ⇒ 00:59:19.149 Uttam Kumaran: Yeah, yeah, yeah, yeah, okay.

589 00:59:19.320 ⇒ 00:59:19.950 Katherine Bayless: Yeah.

590 00:59:20.170 ⇒ 00:59:20.750 Uttam Kumaran: And then.

591 00:59:20.750 ⇒ 00:59:23.120 Katherine Bayless: curious if we could expand how we use Shopify.

592 00:59:23.120 ⇒ 00:59:23.500 Uttam Kumaran: Yeah.

593 00:59:23.500 ⇒ 00:59:28.660 Katherine Bayless: You have a lot of external data sharing, and, like, part of me is like, hmm…

594 00:59:29.060 ⇒ 00:59:35.780 Katherine Bayless: I wonder if that platform would be an interesting way to handle that, versus right now, Catherine Mills a SharePoint site.

595 00:59:36.720 ⇒ 00:59:37.360 Uttam Kumaran: Yeah.

596 00:59:37.940 ⇒ 00:59:38.760 Katherine Bayless: Yeah.

597 00:59:38.990 ⇒ 00:59:39.800 Katherine Bayless: Anyway.

598 00:59:40.200 ⇒ 00:59:46.429 Uttam Kumaran: And then Zoom is for, like, are you guys billing or running webinars and stuff through Zoom, or you mentioned in the beginning of the call.

599 00:59:46.610 ⇒ 00:59:49.980 Katherine Bayless: Yeah, so it’s mostly internal meetings, to be honest.

600 00:59:49.980 ⇒ 01:00:13.569 Katherine Bayless: we do do some webinars. To my knowledge, I don’t think we charge for them, and if we do, we probably do it stupidly and charge somewhere else, honestly. What I’m actually very interested in, to a certain extent with Zoom, is our teams use it for, like, sales calls, like prospecting and stuff like that. And so, right now, there’s no visibility into the unstructured data of all those sales notes,

601 01:00:13.610 ⇒ 01:00:22.500 Katherine Bayless: I would like to fix that fast, but also, I mean, those Zoom calls, right? At least transcripts, if not, like, recording, stuff like that, you know? So, yeah.

602 01:00:22.500 ⇒ 01:00:23.360 Uttam Kumaran: Yeah.

603 01:00:24.320 ⇒ 01:00:29.859 Katherine Bayless: Also, I know it is 5.30, I’m totally fine to keep going, but I don’t want to, like, trap you guys if you got stuff.

604 01:00:30.150 ⇒ 01:00:31.949 Uttam Kumaran: Dan, what do you think? I’m down to get going.

605 01:00:32.570 ⇒ 01:00:34.059 Samuel Roberts: Yeah, I’d probably go a little longer.

606 01:00:34.060 ⇒ 01:00:34.700 Uttam Kumaran: Okay.

607 01:00:35.460 ⇒ 01:00:41.040 Uttam Kumaran: Yeah, we probably have, like, 6 or 7, so let’s talk about Leopatra.

608 01:00:41.730 ⇒ 01:00:45.670 Uttam Kumaran: Cleopatra Profix… and Great Plains.

609 01:00:46.050 ⇒ 01:00:51.420 Katherine Bayless: Yeah, Cleopatra, I forget what that one is, similar to Presto.

610 01:00:51.810 ⇒ 01:00:52.530 Uttam Kumaran: Okay.

611 01:00:52.710 ⇒ 01:00:53.710 Katherine Bayless: Yeah.

612 01:00:54.270 ⇒ 01:00:58.930 Uttam Kumaran: That’s fine. We’re… this is a lot. Like, these are, like, this is a lot of stuff, so… Yeah, right.

613 01:00:59.150 ⇒ 01:01:21.289 Katherine Bayless: Profix, though, so that is our budget system. We started using it, I think, last year was the first year, this year was the second. I will say, based on my experience, trying to use it as an end user putting in their budget, I do not look forward to trying to consume that data, because that is an interesting, awful platform. Either that, or maybe we’ve, like, configured it poorly? I’m unclear.

614 01:01:21.290 ⇒ 01:01:25.050 Katherine Bayless: But yeah, it’s like budgeting software, and it sucks.

615 01:01:25.680 ⇒ 01:01:26.590 Uttam Kumaran: Oh, okay.

616 01:01:26.590 ⇒ 01:01:34.600 Katherine Bayless: And then we were on Great Plains, we just completed in September the move to Sage, so that’s our,

617 01:01:35.850 ⇒ 01:01:39.190 Katherine Bayless: what do you call it? Like, dynamics?

618 01:01:39.750 ⇒ 01:01:40.750 Katherine Bayless: ERP?

619 01:01:41.600 ⇒ 01:01:43.559 Uttam Kumaran: Yeah, yeah, yeah.

620 01:01:48.210 ⇒ 01:01:48.880 Uttam Kumaran: Okay.

621 01:01:50.310 ⇒ 01:01:54.850 Katherine Bayless: And then Microsoft Forms, sadly,

622 01:01:54.860 ⇒ 01:02:12.740 Katherine Bayless: finance and HR tend to be the primary users of Microsoft Forms. Yeah, I know, yeah, exactly. Those eyebrows say that. Yeah, right? Yeah, they asked me to do my, like, 6-month, like, you know, employee check-in in a Microsoft Form. I was like, I’m just tired of putting my data in places it shouldn’t be.

623 01:02:13.780 ⇒ 01:02:18.649 Katherine Bayless: Yeah, yeah, yeah. And then Whitfly is an accounting firm?

624 01:02:18.730 ⇒ 01:02:34.879 Katherine Bayless: But they also do some, like, connector-type work, and so we are using Wipley maybe for accounting services, but also for the connector… I’m not sure, honestly, what things they are connectoring.

625 01:02:34.880 ⇒ 01:02:39.100 Katherine Bayless: But something in the finance department is connected via Whipley.

626 01:02:39.100 ⇒ 01:02:40.600 Uttam Kumaran: Okay, okay.

627 01:02:40.770 ⇒ 01:02:41.330 Katherine Bayless: Yeah.

628 01:02:44.760 ⇒ 01:02:47.630 Uttam Kumaran: Some type of managed software service or something, but…

629 01:02:48.130 ⇒ 01:02:59.250 Katherine Bayless: Yeah, like, it might be that Whipley is connecting Sage to Concur, and that’s why they’re like, they can’t get Ironclad to concur, is that, like, next mile sort of step. Yeah.

630 01:03:00.380 ⇒ 01:03:03.639 Uttam Kumaran: Okay, so I think we’ve kind of gone through…

631 01:03:05.260 ⇒ 01:03:10.199 Uttam Kumaran: I don’t miss any? I’m just, like, looking through our list. I feel like I’m looking through everything.

632 01:03:11.290 ⇒ 01:03:12.849 Uttam Kumaran: Leadership Connect.

633 01:03:13.230 ⇒ 01:03:13.860 Samuel Roberts: Yeah…

634 01:03:13.860 ⇒ 01:03:20.690 Katherine Bayless: Leadership Connect is kind of cool. That’s our library team that uses it. They… so it’s like,

635 01:03:22.220 ⇒ 01:03:30.859 Katherine Bayless: It’s kind of LinkedIn-y, but meets ZoomInfo-y, meets, like, publicly available information, so it’s a little creepy, but it’ll tell you that, like.

636 01:03:30.860 ⇒ 01:03:44.650 Katherine Bayless: such and such board member at Facebook actually used to be a junior senator from Nebraska, or vice versa, right? Whatever. And so it’s like the, like, politics to big tech connection, and I’m like, there’s something interesting in here.

637 01:03:44.650 ⇒ 01:03:45.200 Uttam Kumaran: Yeah, man.

638 01:03:45.200 ⇒ 01:03:46.170 Katherine Bayless: Yeah, yeah.

639 01:03:46.170 ⇒ 01:03:52.639 Uttam Kumaran: Nice, that’s cool. And yeah, we’ve done a lot of work with all the major enrichment providers.

640 01:03:54.120 ⇒ 01:04:01.609 Katherine Bayless: Yeah, I do think… sorry, I was just seeing if there’s anything else written on my board that isn’t on here. I think Causeway is the only one.

641 01:04:02.120 ⇒ 01:04:15.500 Katherine Bayless: I think Causeway’s the only one. Yeah, the enrichment stuff, I know we talked about it a little bit on Friday, too, but, like, definitely an area of opportunity, I think, for us. I think the cost is going to be the limiting factor in that case.

642 01:04:15.500 ⇒ 01:04:28.530 Uttam Kumaran: I mean, you’d be surprised, like, the… what we found is that there’s starting to be, like, a plateauing of, like, quality across, because they’re all sourcing from a lot of the same places. Instead, what’s… what we’re finding the differences are

643 01:04:28.820 ⇒ 01:04:39.719 Uttam Kumaran: is actually, like, the uniqueness of the signals. Like, can you look at, like, sales team growth, or job changes, like, interesting signals like that, versus just, like.

644 01:04:39.940 ⇒ 01:04:43.620 Katherine Bayless: Yeah. …or can work at this company, and for how long, so…

645 01:04:43.630 ⇒ 01:04:57.910 Uttam Kumaran: Yeah, we can… and then also this, like, consolidation. And the last piece is also, like, do you have, sort of, like, a go-to-market, like, automation tool? Like, for example, we’ve done a lot of work with clay, like, we use clay internally. People build, like, waterfall enrichments.

646 01:04:59.500 ⇒ 01:05:13.109 Uttam Kumaran: And it actually takes a lot of load off, like, what you would typically have to build in dbt. You can actually have your sales team leverage it there, and then write it back to, like, the CRM. So there’s some interesting new players in go-to-market automation.

647 01:05:13.930 ⇒ 01:05:17.760 Katherine Bayless: So, what is a go-to-market automation?

648 01:05:17.760 ⇒ 01:05:26.599 Uttam Kumaran: Sort of go-to-market automation, you can think of it like, Zapier, but very focused on, like, sales and marketing-related outcomes.

649 01:05:26.600 ⇒ 01:05:35.959 Uttam Kumaran: So Zapier is, like, connected, and I think this is really focused on… and I can share some examples. Like, I mean, a good example is, like, it’s like, it’s basically like a workbook, like an Excel workbook.

650 01:05:35.960 ⇒ 01:05:51.179 Uttam Kumaran: And each column is, like, a step in a workflow. So you can have, like, waterfall enrichment, you can have a prompt take an input from one cell and output another, you can have external-facing HTTP requests.

651 01:05:51.580 ⇒ 01:05:58.660 Uttam Kumaran: connect to other integrations, but sort of the… the theme of why Clay kind of became big is, like, it’s all…

652 01:05:58.810 ⇒ 01:06:14.859 Uttam Kumaran: it’s sort of like what Airtable failed to do, which is, like, build something that is not just, like, Google Sheets, where you can actually call externally in each cell. And so, it’s just really nice, and it’s a nice, like, user interface for folks that are used to, like, that environment, but you can, like.

653 01:06:14.930 ⇒ 01:06:30.650 Uttam Kumaran: do really common sales or marketing-related workflows. Enrichment is one, copy generation is another, lead scoring is another. You can call things like Unbounce or NeverBounce, directly in there.

654 01:06:30.770 ⇒ 01:06:41.819 Uttam Kumaran: That way you can kind of… you kind of don’t need to go to Glue and to several other tools to build that, and it’s something that, like, someone in sales and marketing can build. So, there’s a couple of those tools.

655 01:06:42.430 ⇒ 01:07:01.009 Katherine Bayless: Right now, if sales wants to send an email, they export a CSV from Salesforce, and then somebody chops it into 6 other CSVs, and then those 6 people get together and make sure that their data doesn’t overlap, which is very funny to me. And then they take those 6 CSVs and they upload them via the FTP into Marketing Cloud.

656 01:07:01.200 ⇒ 01:07:07.060 Katherine Bayless: And then they send an email out. We started using Journeys this year. We have one email, Journeys.

657 01:07:07.520 ⇒ 01:07:11.559 Katherine Bayless: Literally a journey that’s like, you exist, here’s an email, we’re done.

658 01:07:11.870 ⇒ 01:07:13.390 Uttam Kumaran: That’s crazy.

659 01:07:14.690 ⇒ 01:07:15.530 Uttam Kumaran: Yeah.

660 01:07:16.490 ⇒ 01:07:19.779 Uttam Kumaran: There should be some more drip, some more, like, some gold marketing.

661 01:07:21.990 ⇒ 01:07:24.839 Uttam Kumaran: It’s so funny, because we have… we have some clients that are, like.

662 01:07:25.250 ⇒ 01:07:34.619 Uttam Kumaran: so advanced in the email signals, they’re like, the moment this activity happens, the fourth step of this thing takes them down a tree, and, like, we’ve done analysis where, like.

663 01:07:34.790 ⇒ 01:07:46.549 Uttam Kumaran: okay, you need to send emails, like, at this hour and, like, this thing to get them to, like, do this activity, which increases their LTV, and it’s like, we just probably should just send more emails in general.

664 01:07:47.520 ⇒ 01:07:54.909 Katherine Bayless: Yeah, we had an 8% opt-out on one of our emails a week or so ago, yeah, yeah, yeah.

665 01:07:54.970 ⇒ 01:07:55.970 Uttam Kumaran: Yeah.

666 01:07:55.970 ⇒ 01:07:56.870 Katherine Bayless: Yeah.

667 01:07:57.090 ⇒ 01:07:57.790 Katherine Bayless: Yeah.

668 01:08:00.750 ⇒ 01:08:08.010 Katherine Bayless: I mean, it really… it’s like, there’s so much room, and the people are lovely, there’s all the potential, but it is sometimes I’m just like, really, guys?

669 01:08:10.610 ⇒ 01:08:18.819 Uttam Kumaran: So also, I guess, like, this is a good point to, like, tell me, like, kind of how you’re… like, how are you finding focus across all of these? Like…

670 01:08:19.040 ⇒ 01:08:31.529 Uttam Kumaran: you know, are you seeing… are you seeing yourself more as, like, okay, I’m gonna make… I’m gonna land all the data, and then enable, like, more of an automation or action layer that is sourced from someplace?

671 01:08:31.779 ⇒ 01:08:39.510 Uttam Kumaran: Do you find that you’ll eventually be the owner of, like, the activation of this data as well? Like, how are you thinking about things?

672 01:08:39.790 ⇒ 01:09:01.790 Katherine Bayless: Yeah, so, fabulous question, because, yeah, I mean, like, all of my usual bag of tricks, right, coming into a new place, just, I mean, I have an ocean to boil, right? And so I turned to… I’m a big fan of Rommelt and his, like, few points on strategy, and so, you know, the whole idea, right, is, like, what is the problem?

673 01:09:02.020 ⇒ 01:09:19.740 Katherine Bayless: what are the ins and outs of bounds, and then what are we going to do about it, right? And so, my diagnosis of the organization, insofar as my data lane is concerned, is that the siloing of information is preventing people from having the knowledge they need to do their jobs, and do their jobs better, right? Like, I mean, we just…

674 01:09:19.770 ⇒ 01:09:35.040 Katherine Bayless: people can’t come up with a better way to do stuff, because by the time you’ve talked to 8 people to get your spreadsheet so that you can do the thing, you’re exhausted, right? And so, my first pass at this is unblock knowledge. I don’t know how much you guys can see my whiteboard behind me, but…

675 01:09:35.040 ⇒ 01:09:44.319 Katherine Bayless: it’s the, you know, sort of classic, data-to-wisdom continuum, right? But envisioned as, like, an actual system, right? And so I’m like, okay, we have a lot of

676 01:09:44.319 ⇒ 01:09:54.440 Katherine Bayless: data in this stock, sure, but it’s not going anywhere. It’s not becoming information or knowledge, let alone wisdom, right? And so I’m like, I want to prioritize anything

677 01:09:54.440 ⇒ 01:10:03.900 Katherine Bayless: that accelerates the conversion from data to knowledge. I want to just get this information into the hands of my colleagues so that they can start using it. I do think

678 01:10:04.030 ⇒ 01:10:18.040 Katherine Bayless: I will need to be the activation layer in a lot of cases, and I also think we’ll probably, hopefully quickly run out of the, like, you know, low-hanging fruit stuff. Like, as soon as people can start answering all of the basic questions, I’m hoping they will have really deep.

679 01:10:18.040 ⇒ 01:10:33.370 Katherine Bayless: difficult ones, right? And at that point, then we get to finally kind of be data people and be like, aha, let me push my glasses up and make you a model, or, you know, whatever, right? But, like, right now, it’s just, I mean, it’s a knowledge gap. That’s the biggest thing that we’re dealing with.

680 01:10:33.570 ⇒ 01:10:39.499 Uttam Kumaran: Cool. Okay, makes sense. Yeah. So, the next step, I mean, we have our call… I guess…

681 01:10:39.740 ⇒ 01:10:42.530 Uttam Kumaran: Or we’re still doing the call tomorrow with SCG.

682 01:10:43.440 ⇒ 01:10:57.580 Katherine Bayless: Yeah, I need to… I was thinking about this earlier. I was like, I need to actually make sure that everybody’s on the same page for that. So it might wind up being a Wednesday thing, because I think I might have forgotten to close a loop with Greta, which is totally my fault.

683 01:10:57.890 ⇒ 01:10:58.870 Katherine Bayless: But yeah.

684 01:10:59.270 ⇒ 01:11:16.339 Katherine Bayless: We can still meet tomorrow, if you want, even if I have failed to secure the SVG, folks. Okay, this is, like, totally my bad habit of, like, well, but they’re… they’re… they’re here for whatever I need them for, so if I tell them there’s a call in 10 minutes, can’t they just join it? And, like, that’s not nice. That’s not how we treat humans, Catherine.

685 01:11:16.340 ⇒ 01:11:18.530 Uttam Kumaran: Yeah, but I mean, I don’t know, I feel like…

686 01:11:19.020 ⇒ 01:11:21.349 Uttam Kumaran: work for you, so we’ll be there. I don’t…

687 01:11:21.670 ⇒ 01:11:23.370 Katherine Bayless: I’ll do better.

688 01:11:23.370 ⇒ 01:11:26.460 Uttam Kumaran: Or if I can’t be there, someone from Frame Forge will be there.

689 01:11:26.460 ⇒ 01:11:26.990 Samuel Roberts: Yeah.

690 01:11:26.990 ⇒ 01:11:41.219 Uttam Kumaran: Yeah, so, okay, I think, yeah, maybe, like, if not tomorrow, I think we probably need at least a day. A couple things that I want to do, is one, I want to start, Sam, we’ve done this before, is I just want to start

691 01:11:41.830 ⇒ 01:11:45.429 Uttam Kumaran: Building a visual diagram of the data platform.

692 01:11:45.640 ⇒ 01:12:03.660 Uttam Kumaran: So the first place we’ll start all the way on the left is, like, map these sources. Some of these are legacy, so mainly we’re getting stale data, landed. We’re also looking at some active. I want to start to organize and just be like, cool, this is the… this is the state of, like, data ingestion. At that point.

693 01:12:03.720 ⇒ 01:12:07.549 Uttam Kumaran: We can then start discussing, like, how to ingest.

694 01:12:08.600 ⇒ 01:12:16.630 Uttam Kumaran: if you want, like, we can go ahead and start Snowflake, like, if you think the risk is… is, like, hey, it’s gonna…

695 01:12:16.870 ⇒ 01:12:20.989 Uttam Kumaran: well, I don’t know what’s gonna happen with AWS. The nice thing is, like, I guess…

696 01:12:23.780 ⇒ 01:12:34.549 Uttam Kumaran: if it’s… we’ll just make sure it’s on the AWS cluster, and then… I guess we’ll have to see when they… maybe when we talk to them what they want to do eventually, but I would like to have that going, and then…

697 01:12:35.010 ⇒ 01:12:42.010 Uttam Kumaran: whatever happens, we can send data to the next place, set it up again if needed. It’s not, like, tons of work, so…

698 01:12:42.270 ⇒ 01:12:42.740 Katherine Bayless: Yeah.

699 01:12:42.740 ⇒ 01:12:48.109 Uttam Kumaran: And for a short term is just to get a snowflake up and running and going, then start there.

700 01:12:48.680 ⇒ 01:12:53.509 Katherine Bayless: Yeah, I mean, I’m totally on board with that. I think…

701 01:12:54.880 ⇒ 01:13:11.660 Katherine Bayless: if we were move… if there was more, like, stuff already, then I’d be like, yeah, like, let’s not just create a bunch of tech debt right out the gate, but in this case, I think it is actually worth the, like, moving fast, even if we do have to repeat some of the steps when we get the new AWS accounts.

702 01:13:11.660 ⇒ 01:13:17.440 Katherine Bayless: There is also still the chance that we wind up just keeping this one, like…

703 01:13:17.490 ⇒ 01:13:31.260 Katherine Bayless: you know, we were kind of like, well, we could either set up an entirely new landing zone control tower, all the things, then just cut over, or, you know, kind of migrate these in as legacy accounts and slowly transition, you know, right, all the options. But…

704 01:13:31.260 ⇒ 01:13:37.729 Katherine Bayless: I have no qualms with, like, yeah, getting started, rather than waiting to see when that comes through.

705 01:13:37.860 ⇒ 01:13:44.920 Uttam Kumaran: Okay. Yeah, the other piece is, like, we can also kind of hedge a little bit by landing everything in S3 first.

706 01:13:44.920 ⇒ 01:13:46.240 Katherine Bayless: That’s where it is now, yeah.

707 01:13:46.240 ⇒ 01:13:46.870 Uttam Kumaran: Okay.

708 01:13:46.870 ⇒ 01:14:05.169 Katherine Bayless: Yeah. Yeah, so the Snowflake account that Jay bricked, which maybe we will get back into, maybe we won’t, either way, like, what I had done was I took the old marketing SQL Server data warehouse, right, and dumped it into CSV and Parquet files in S3, and then I connected the S3 stage to Snowflake.

709 01:14:05.170 ⇒ 01:14:10.429 Katherine Bayless: So that I could query against it. That was about as far as I got, but it was all…

710 01:14:10.500 ⇒ 01:14:12.580 Katherine Bayless: Pretty easy to do, honestly.

711 01:14:12.580 ⇒ 01:14:17.340 Uttam Kumaran: So that’ll all be provisioned through that… Console access.

712 01:14:18.670 ⇒ 01:14:21.570 Katherine Bayless: Yeah,

713 01:14:21.810 ⇒ 01:14:22.450 Uttam Kumaran: Okay.

714 01:14:24.760 ⇒ 01:14:32.119 Katherine Bayless: I guess since the Snowflake got bricked as part of setting up the SAML and SCIM, in theory, it should…

715 01:14:32.250 ⇒ 01:14:34.000 Katherine Bayless: If we fix it, then…

716 01:14:34.310 ⇒ 01:14:39.130 Katherine Bayless: it would flow through. I honestly, part of me is like, I think we should probably just open another instance, right?

717 01:14:39.130 ⇒ 01:14:42.620 Uttam Kumaran: I mean, that’s what the sales guy’s gonna probably tell you, too, because he’s gonna be like.

718 01:14:43.430 ⇒ 01:14:58.790 Uttam Kumaran: support won’t get back to us, or whatever, so… Right, right. Like, I set it all up in the console. I think I did create a CloudFormation template, but then I ended up doing it in console. There was some wrinkle I ran into where it was getting annoying, or it was kind of annoying to set up the…

719 01:14:59.330 ⇒ 01:15:00.410 Katherine Bayless: I am.

720 01:15:00.410 ⇒ 01:15:04.559 Uttam Kumaran: annoying steps on, I forgot, like, what part it, like…

721 01:15:05.970 ⇒ 01:15:09.349 Uttam Kumaran: some passkey or something. It’s, like, a little bit annoying.

722 01:15:09.520 ⇒ 01:15:20.830 Katherine Bayless: Yeah, like, there was some part of setting up the role, and the trust policy, and the permit. Like, there’s always, like, some IAM permission that you need that you’re like, why would I need that one, though? And how was I supposed to know?

723 01:15:20.830 ⇒ 01:15:24.880 Uttam Kumaran: Well, it’s like, you have to do, like, a storage integration, and then a share, like, a…

724 01:15:25.010 ⇒ 01:15:30.220 Uttam Kumaran: And then, if you wanted to have a recurring sink, then you need to do snowpipe.

725 01:15:31.740 ⇒ 01:15:38.570 Uttam Kumaran: Okay, so… so I think, like, this week, I would love, maybe we can make a dent into that, so I assume for that, we’ll just create it using our…

726 01:15:38.700 ⇒ 01:15:42.610 Uttam Kumaran: Should I just, like, how would you want to handle it? Should we just go ahead and create it?

727 01:15:43.300 ⇒ 01:15:48.179 Uttam Kumaran: with our Brainforge domain, or do you think it’s best to try to get provisioned.

728 01:15:49.100 ⇒ 01:15:59.740 Katherine Bayless: Yeah, no, we can… I’ll ask Jay if he can add the AWS app to your Okta thing so you can actually get into it, but once you’re in there, we can just open a new account via the marketplace, yeah, yeah, yeah.

729 01:15:59.970 ⇒ 01:16:00.760 Uttam Kumaran: Right.

730 01:16:00.760 ⇒ 01:16:01.360 Katherine Bayless: Yeah.

731 01:16:01.680 ⇒ 01:16:02.510 Katherine Bayless: Yeah.

732 01:16:03.150 ⇒ 01:16:05.480 Katherine Bayless: I assume that since there’s already one…

733 01:16:05.720 ⇒ 01:16:10.009 Katherine Bayless: instance open, it wouldn’t prevent you from opening another one through the marketplace?

734 01:16:10.970 ⇒ 01:16:12.309 Katherine Bayless: Let me just go take a look.

735 01:16:12.500 ⇒ 01:16:14.450 Uttam Kumaran: Yeah, we’ll find out.

736 01:16:14.740 ⇒ 01:16:21.279 Uttam Kumaran: Okay, so then, yeah, we’ll start… we’ll start on that. We’ll… once we have all the…

737 01:16:21.600 ⇒ 01:16:35.379 Uttam Kumaran: sort of sources listed, we can then… you could kind of give us the, okay, let’s go after these first, and then we’ll sort of take those off. I think, yeah, also, now that we have these listed, this could help us understand

738 01:16:35.860 ⇒ 01:16:48.740 Uttam Kumaran: shop around on, like, what we want to do on ETL. You know, of course, it’s going to be a little bit volume-dependent, but also, if we have the priority ones, like, if there’s, like, 5 to 10 that are the priority.

739 01:16:49.860 ⇒ 01:16:55.599 Uttam Kumaran: If member attendance and, like, CRM are the priority, then we just select those, and…

740 01:16:55.740 ⇒ 01:17:04.659 Uttam Kumaran: we can go get some quotes, and also kind of look at what it would take for us to build it. Because again, if it’s… if it is a single endpoint, and it’s like, call it and move the data.

741 01:17:04.850 ⇒ 01:17:11.920 Uttam Kumaran: I don’t, like, not worried about that, but in situations like Shopify, where there’s, like, almost 15 or 20 different objects.

742 01:17:11.990 ⇒ 01:17:13.589 Katherine Bayless: And it’s a lot of data.

743 01:17:14.210 ⇒ 01:17:14.800 Katherine Bayless: Yeah.

744 01:17:14.900 ⇒ 01:17:22.350 Uttam Kumaran: it’s, like, an adult project for us to build just that, so that’s where push should be, like, we should consider. So…

745 01:17:23.510 ⇒ 01:17:35.110 Katherine Bayless: I mean, and actually, so it’s funny, because yes, registration, definitely one of the core sources. So, Impexium, if we can get this Snowflake data share, that’ll make it way easier than writing the API calls for that.

746 01:17:35.300 ⇒ 01:17:43.939 Katherine Bayless: Yeah, I definitely don’t want to get into there. Salesforce Marketing Cloud, those are the two, sort of, like, biggest ones. Merits does not have APIs.

747 01:17:44.250 ⇒ 01:18:00.740 Katherine Bayless: I mean, they kind of do, but not really, like, and they won’t let us use them because they’re not resilient enough for me to ping them in addition to the other vendors, which is fascinating. So Merits, we are right now on an FTP with them as well, but yeah, kind of sucks.

748 01:18:01.700 ⇒ 01:18:12.629 Katherine Bayless: I think the event point data is another one to focus on, though, because it’s just, it’s a good, like, platform, and then this event thing, which, yeah, kind of crappy, but…

749 01:18:12.850 ⇒ 01:18:17.130 Katherine Bayless: Yeah, Impexium Marketing Cloud… Cvent.

750 01:18:18.340 ⇒ 01:18:21.760 Katherine Bayless: I mean, Formstack I’ve already kind of done, but it wouldn’t hurt to do better.

751 01:18:22.830 ⇒ 01:18:23.410 Uttam Kumaran: Okay.

752 01:18:23.410 ⇒ 01:18:24.290 Katherine Bayless: But yeah…

753 01:18:24.890 ⇒ 01:18:31.970 Uttam Kumaran: And then I just want to probably get a one-time sync of all the other data from all the sources that are no longer, and land all.

754 01:18:31.970 ⇒ 01:18:32.370 Katherine Bayless: Honda.

755 01:18:32.760 ⇒ 01:18:34.880 Uttam Kumaran: You know, so that’s… that’s kind of how…

756 01:18:35.050 ⇒ 01:18:45.240 Uttam Kumaran: if we… once, like, probably by Thursday, I feel like we’ll have all these sources mapped, and then we can start to map out what to go after. So that’s kind of, like, my objective for… for this week.

757 01:18:45.490 ⇒ 01:18:53.519 Katherine Bayless: Yeah, okay, so then probably, too, what we’ll want to do is maybe add a column or a note to, like, which tools, like.

758 01:18:53.680 ⇒ 01:19:03.669 Katherine Bayless: do we have access to… so, so, so, like, the Qualtrics stuff, like, I don’t have access to Qualtrics, and I don’t have access to any of the historical survey information that was collected.

759 01:19:03.770 ⇒ 01:19:11.319 Katherine Bayless: I’m hoping that we can encourage our colleagues to share, but they have their own set of 12 SQL servers that they are using.

760 01:19:11.320 ⇒ 01:19:13.349 Uttam Kumaran: Yeah, I guess my question would be…

761 01:19:13.350 ⇒ 01:19:13.790 Katherine Bayless: Yeah.

762 01:19:13.790 ⇒ 01:19:15.859 Uttam Kumaran: It’s like, do you have access? And…

763 01:19:16.120 ⇒ 01:19:19.499 Uttam Kumaran: If not, do you think it’s worth going after now?

764 01:19:19.650 ⇒ 01:19:21.469 Katherine Bayless: Right, right, yeah, exactly.

765 01:19:21.470 ⇒ 01:19:28.870 Uttam Kumaran: I’m just gonna literally write those as I said it, and so you can go ahead and check which one. Yeah, perfect.

766 01:19:28.870 ⇒ 01:19:29.490 Katherine Bayless: Perfect.

767 01:19:29.490 ⇒ 01:19:32.720 Uttam Kumaran: I’ll just put, does, does Kay have access?

768 01:19:32.870 ⇒ 01:19:34.109 Katherine Bayless: I like it, yeah.

769 01:19:34.110 ⇒ 01:19:34.770 Uttam Kumaran: Huh.

770 01:19:34.770 ⇒ 01:19:41.980 Katherine Bayless: Yeah, because, like, a lot of the stuff that’s on the business intelligence team, I’m hoping that they, like, that I can entice them with Snowflake.

771 01:19:42.010 ⇒ 01:19:45.510 Uttam Kumaran: Totally, I know, I totally see where you… what the game… I know what the game is, so you…

772 01:19:45.510 ⇒ 01:20:02.829 Katherine Bayless: Yeah, exactly. Oh, actually, also, I don’t think I mentioned this on Friday, if I’m repeating myself, then at least Sam gets some information. So they’ve hired the guy who will be the Senior Director of Business Intelligence. It was very interesting being in those interviews, because the

773 01:20:02.830 ⇒ 01:20:17.560 Katherine Bayless: candidate was like, wait, your title is my title. I’m like, well, technically this organization thinks we do different things. But he’s this guy who had, like, a startup that MasterCard acquired 20 years ago, and he’s been at MasterCard ever since, and then he was kind of, like, burnt out, and so he was like, I’m gonna consult, and he’s like, consulting sucks.

774 01:20:17.690 ⇒ 01:20:25.410 Uttam Kumaran: I need somebody else to be in charge of my payroll. And so he’s coming on board here. I don’t know when he starts, but, like, he’s…

775 01:20:25.520 ⇒ 01:20:28.200 Katherine Bayless: He’s an interesting, like, force.

776 01:20:28.200 ⇒ 01:20:33.420 Uttam Kumaran: Okay. And so I’m hoping that, like, he’ll be a good ally and partner and, like.

777 01:20:33.420 ⇒ 01:20:39.139 Katherine Bayless: a lot of the questions he had for me in the interviews, he was talking about, like, you know, like, what are your tools? And I was like, Excel and SharePoint.

778 01:20:39.920 ⇒ 01:20:43.869 Katherine Bayless: And so I’m like, if by the time he starts, I’m like, now it is, right?

779 01:20:43.870 ⇒ 01:20:44.509 Uttam Kumaran: Oh, yeah, yeah.

780 01:20:44.510 ⇒ 01:20:45.210 Katherine Bayless: Yeah, yeah.

781 01:20:45.210 ⇒ 01:20:46.070 Uttam Kumaran: Right.

782 01:20:47.260 ⇒ 01:20:48.740 Uttam Kumaran: Okay, awesome.

783 01:20:48.740 ⇒ 01:20:50.300 Katherine Bayless: Like, a social engineer, in addition.

784 01:20:50.300 ⇒ 01:20:51.545 Uttam Kumaran: Yes.

785 01:20:54.570 ⇒ 01:20:55.520 Katherine Bayless: It’s terrible.

786 01:20:55.920 ⇒ 01:21:01.579 Uttam Kumaran: And then, if it’s easy to… if you want to include Jay in that Slack, also feel free to.

787 01:21:02.130 ⇒ 01:21:08.019 Katherine Bayless: I think I will. I think you guys would honestly really get along, and I mean, I like him a lot. He just… he’s so, like.

788 01:21:08.020 ⇒ 01:21:16.270 Uttam Kumaran: No, I love IT people, I like, like, we’re also… we do a lot of that type of work, so we just want to be a friend to him and take these…

789 01:21:16.820 ⇒ 01:21:18.620 Uttam Kumaran: Takes a lot of his plate.

790 01:21:18.620 ⇒ 01:21:23.770 Katherine Bayless: And he’s been here, like, 20 years, and he’s got a lot of institutional knowledge, like, he knows where all the bodies are buried.

791 01:21:23.770 ⇒ 01:21:31.849 Uttam Kumaran: Yeah, like, I would like him to validate stuff, and… I mean, the next 2 weeks is gonna be a lot of access. Yeah. So…

792 01:21:31.850 ⇒ 01:21:32.360 Katherine Bayless: Yeah.

793 01:21:32.460 ⇒ 01:21:36.430 Uttam Kumaran: For us, we think a lot about, like, how do we just make the right friends?

794 01:21:36.430 ⇒ 01:21:40.409 Katherine Bayless: exactly, exactly, exactly.

795 01:21:40.670 ⇒ 01:21:41.910 Uttam Kumaran: Cool.

796 01:21:43.600 ⇒ 01:21:46.010 Katherine Bayless: Okay, cool.

797 01:21:46.010 ⇒ 01:22:02.359 Uttam Kumaran: Yeah, anything else? I guess we didn’t really get to talk a lot about, like, the end state. I briefed Sam a lot about, like, sort of what we talked about in terms of consolidated member lists, and identity resolution. I don’t know, I don’t think it’s worth

798 01:22:02.710 ⇒ 01:22:09.230 Uttam Kumaran: spending more time on that now until we even have some landed data, because then we can start to stitch and then append to that.

799 01:22:09.520 ⇒ 01:22:17.559 Uttam Kumaran: But the real thing I’m driving for is, instead of Snowflake is… oh, I guess the other question is, like, if you guys are on GitHub already.

800 01:22:18.290 ⇒ 01:22:19.000 Uttam Kumaran: Okay.

801 01:22:19.000 ⇒ 01:22:29.719 Katherine Bayless: Yeah, I need to invite you, or, well, have Jay invite you, yeah, yeah, yeah. But yeah, I have a repo set up where I’ve been putting my stuff. I mean, you know, be gentle, be gentle on me.

802 01:22:29.830 ⇒ 01:22:36.359 Uttam Kumaran: So we, I mean, we’ll just set up dbt Core and at least start, and then you can decide if you want to end up doing dbt Cloud.

803 01:22:37.230 ⇒ 01:22:43.029 Katherine Bayless: Yeah, I mean, I… so, based on my, like, looking into it, I mean, I feel like core looks good to me, I mean, the…

804 01:22:43.030 ⇒ 01:22:43.510 Uttam Kumaran: we…

805 01:22:43.510 ⇒ 01:22:46.000 Katherine Bayless: Say the cloud doesn’t have interesting features, but yeah.

806 01:22:46.000 ⇒ 01:22:57.940 Uttam Kumaran: No, I mean, everybody on our team uses Cursor for stuff, so the main reason is some people, they find it easy to orchestrate stuff there, but we orchestrate stuff directly as GitHub Actions, or we can set up functions in AWS, so that’s fine.

807 01:22:58.590 ⇒ 01:23:15.289 Katherine Bayless: Yeah, I do have the little bit of GitHub action set up so that, like, you know, one push, it’ll copy everything up to S3 and package my Lambda functions for me and, you know, just some of those bits, but, happy to expand that, and do more. And I think Jay’s kind of interested in Terraform, which I was like.

808 01:23:15.290 ⇒ 01:23:15.680 Uttam Kumaran: Nice.

809 01:23:15.680 ⇒ 01:23:18.869 Katherine Bayless: Yeah. I’ve worked with Terraform in the past, I think it’s fine.

810 01:23:19.040 ⇒ 01:23:22.779 Uttam Kumaran: Yeah, but for, for, like, setting up apps and stuff?

811 01:23:23.240 ⇒ 01:23:30.309 Katherine Bayless: Yeah, I don’t know. I think he wants to use it for setting up, like, Okta rules and deploying them.

812 01:23:30.440 ⇒ 01:23:31.330 Uttam Kumaran: Hmm.

813 01:23:31.330 ⇒ 01:23:32.050 Katherine Bayless: Yeah.

814 01:23:32.650 ⇒ 01:23:33.510 Katherine Bayless: Yeah.

815 01:23:33.680 ⇒ 01:23:34.520 Uttam Kumaran: Interesting.

816 01:23:34.520 ⇒ 01:23:35.300 Katherine Bayless: Yeah.

817 01:23:38.830 ⇒ 01:23:46.739 Uttam Kumaran: I also… I’m gonna start… I’m gonna do some research on a lot of these event platforms, too, and talk to a couple friends I know in the event world about some of these.

818 01:23:46.890 ⇒ 01:23:49.019 Uttam Kumaran: Do what they think, but.

819 01:23:49.420 ⇒ 01:24:01.500 Katherine Bayless: Yeah, I mean, I… yeah, I mean, any… I’m kind of doing the same with my network, because there’s this open question right now of, like, who should own these things? And I’m like, if it’s just a cat herding job of vendor management, then, like, dear God, don’t give it to me, I will just get.

820 01:24:01.500 ⇒ 01:24:01.980 Uttam Kumaran: Right.

821 01:24:01.980 ⇒ 01:24:12.810 Katherine Bayless: I am not good at that kind of work, right? But if it’s like, how do we want to deliver a digital experience to 150,000 people for four days in Las Vegas? Yeah. I’ll take that. I’ll take that.

822 01:24:13.160 ⇒ 01:24:13.890 Uttam Kumaran: Yeah.

823 01:24:14.900 ⇒ 01:24:16.140 Katherine Bayless: Yeah.

824 01:24:16.510 ⇒ 01:24:30.339 Uttam Kumaran: Awesome. Well, yeah, now that we have Slack, I feel like just get us if you need anything, like, yeah, let me know if tomorrow’s gonna end up happening. Otherwise, like, yeah, maybe we’ll… I’ll plan… we can aim for Thursday. If we make progress by Wednesday, I think we end up doing Wednesday.

825 01:24:30.460 ⇒ 01:24:39.970 Uttam Kumaran: And we’ll just try to stream… livestream as we start to… to do some damage. And then I’ll send a summary of, like, the immediate next, like, access request directly in Slack, so…

826 01:24:40.240 ⇒ 01:24:47.590 Katherine Bayless: Okay, okay. And I think once you have the dbt stuff set up, too, like, even though I haven’t got it much, I’ve never used it, so a little training and tour.

827 01:24:47.590 ⇒ 01:24:59.090 Uttam Kumaran: Oh, yeah, 100%, yeah, we’ll make sure, and also now, again, like, we’ll put all the docs and, like, how we set up projects, profiles, naming conventions, everything, we’ll leave in there as well.

828 01:24:59.090 ⇒ 01:25:13.339 Katherine Bayless: Yeah, actually, I should share that file… I mean, it’s in the repo, too, but I do have, like, a naming conventions, like, file, basically, that I found very helpful with Claude Code, right? Instead of it giving me whatever it thinks I should call stuff, right? It’s like, here are my naming conventions.

829 01:25:13.340 ⇒ 01:25:17.599 Uttam Kumaran: Yeah, we set up an agent’s MD file and the cursor rule, so we’ll just, like.

830 01:25:17.600 ⇒ 01:25:18.130 Katherine Bayless: Nice.

831 01:25:18.310 ⇒ 01:25:19.230 Uttam Kumaran: Do all that.

832 01:25:19.300 ⇒ 01:25:20.950 Katherine Bayless: Nice, nice, awesome.

833 01:25:22.220 ⇒ 01:25:22.580 Katherine Bayless: Cool.

834 01:25:22.580 ⇒ 01:25:23.210 Uttam Kumaran: Whoa.

835 01:25:23.590 ⇒ 01:25:30.270 Uttam Kumaran: Okay, awesome. I love this. This is, like, this is just, like, the kickoff to, like, a lot of stuff, so… yeah, it’s great.

836 01:25:30.660 ⇒ 01:25:38.779 Katherine Bayless: I’m genuinely, I’m really excited. It’s overwhelming, and increasingly the people here are just, like, freaking out all the time, but…

837 01:25:38.780 ⇒ 01:25:45.069 Uttam Kumaran: Yeah. Well, we’re gonna… that’s why I want to drive towards a win that you can usually… can definitely use to build more…

838 01:25:45.300 ⇒ 01:25:47.619 Uttam Kumaran: Cloud with internally, you know, so…

839 01:25:48.280 ⇒ 01:25:49.099 Uttam Kumaran: You can do that.

840 01:25:49.710 ⇒ 01:26:00.720 Katherine Bayless: Yeah, I think if people can start asking the basic questions way more easily, it’ll be a big win. And then, you know, the other day, my boss was asking me if it was possible to, like.

841 01:26:02.530 ⇒ 01:26:15.790 Katherine Bayless: we… our attendance numbers were very down, and so we moved a bunch of paid marketing up, which meant we got more free registrants, because it was before the deadline for free reg, and so she was like, is it possible to have a model that could have helped us make that decision? I was like, yes!

842 01:26:16.130 ⇒ 01:26:17.040 Uttam Kumaran: Yes.

843 01:26:17.500 ⇒ 01:26:23.340 Uttam Kumaran: Yeah. It is. That’s… it is, at some point.

844 01:26:23.340 ⇒ 01:26:25.380 Katherine Bayless: The goal is decision-making support.

845 01:26:25.380 ⇒ 01:26:25.810 Uttam Kumaran: Yeah.

846 01:26:25.810 ⇒ 01:26:31.300 Katherine Bayless: needs decision support. Have you seen Ontopia?

847 01:26:32.020 ⇒ 01:26:32.680 Uttam Kumaran: No.

848 01:26:32.680 ⇒ 01:26:40.829 Katherine Bayless: Okay, I haven’t yet either. My homework is to play with it tonight before I have a conversation with a friend tomorrow, but it’s a… I think it’s like a… like a semantic modeling.

849 01:26:40.830 ⇒ 01:26:42.530 Uttam Kumaran: Oh, interesting.

850 01:26:42.530 ⇒ 01:26:43.720 Katherine Bayless: Sort of a thing.

851 01:26:43.720 ⇒ 01:26:46.150 Uttam Kumaran: I feel like, Sam, you would like Octopia.

852 01:26:46.870 ⇒ 01:26:49.079 Samuel Roberts: Yeah. Well, like, taxonomy.

853 01:26:49.080 ⇒ 01:26:49.640 Katherine Bayless: -

854 01:26:49.640 ⇒ 01:26:53.359 Uttam Kumaran: And what’s the… yeah, I feel we, we talk, we talk a lot about it.

855 01:26:53.610 ⇒ 01:26:59.239 Uttam Kumaran: I mean, it’s a shame none of our clients really care. We try to do a lot of great naming convention and, like, taxonomy work.

856 01:26:59.990 ⇒ 01:27:12.480 Katherine Bayless: I mean, it really matters, right? And I think especially with, like, the, the way that, like, the semantic model is totally the make-or-break piece of a rag layer, like… Yes. Yeah. Yeah. Yeah.

857 01:27:12.600 ⇒ 01:27:13.360 Katherine Bayless: Yeah.

858 01:27:14.120 ⇒ 01:27:16.000 Uttam Kumaran: Okay, I’m gonna look at Ontopia, too.

859 01:27:19.380 ⇒ 01:27:21.450 Katherine Bayless: I am gonna go turn my brain off and sit on the bed.

860 01:27:21.450 ⇒ 01:27:23.130 Uttam Kumaran: Alright.

861 01:27:24.880 ⇒ 01:27:28.439 Katherine Bayless: Thank you guys so much, and I’m sorry we didn’t actually get you access all the way, but I’ll…

862 01:27:28.440 ⇒ 01:27:32.470 Uttam Kumaran: No, no, this is just the start, so it’ll happen in due time.

863 01:27:33.180 ⇒ 01:27:35.230 Uttam Kumaran: Okay, alright, thank you both.

864 01:27:35.350 ⇒ 01:27:36.570 Katherine Bayless: Alright, see you.

865 01:27:36.570 ⇒ 01:27:37.760 Samuel Roberts: Scrumity, bye.

866 01:27:37.760 ⇒ 01:27:38.750 Katherine Bayless: Nice to meet you, too.