Meeting Title: AI Team Planning Date: 2025-06-30 Meeting participants: Miguel de Veyra, Mustafa Raja, Uttam Kumaran, Casie Aviles, Luke Daque


WEBVTT

1 00:00:32.259 00:00:33.470 Miguel de Veyra: Morning, everyone.

2 00:00:34.970 00:00:35.960 Mustafa Raja: Good morning!

3 00:00:37.340 00:00:38.310 Uttam Kumaran: Hello!

4 00:00:38.780 00:00:41.579 Miguel de Veyra: Utah, still in New York or back home.

5 00:01:17.040 00:01:17.950 Uttam Kumaran: And.

6 00:01:19.080 00:01:19.740 Mustafa Raja: A.

7 00:01:20.410 00:01:21.000 Uttam Kumaran: Hey!

8 00:01:21.850 00:01:23.580 Mustafa Raja: Yeah, how are you?

9 00:01:23.900 00:01:24.630 Uttam Kumaran: Good.

10 00:01:25.340 00:01:26.430 Mustafa Raja: How was your weekend.

11 00:01:27.090 00:01:28.329 Uttam Kumaran: Weekend was good.

12 00:01:29.110 00:01:30.960 Miguel de Veyra: Back in Texas, already.

13 00:01:31.930 00:01:33.700 Uttam Kumaran: No, I’m in New Hampshire.

14 00:01:35.060 00:01:36.430 Miguel de Veyra: Shit. Where’s that? Sorry? Wait.

15 00:01:36.430 00:01:36.865 Mustafa Raja: Yeah.

16 00:01:37.990 00:01:40.400 Uttam Kumaran: Is in the northeast.

17 00:01:41.250 00:01:42.480 Mustafa Raja: Easter.

18 00:01:42.480 00:01:43.210 Mustafa Raja: Okay.

19 00:01:43.660 00:01:45.689 Miguel de Veyra: Near New York, still.

20 00:01:46.100 00:01:48.050 Uttam Kumaran: Near New York. Kind of.

21 00:01:48.410 00:01:49.840 Miguel de Veyra: Oh, near Boston.

22 00:01:50.090 00:01:50.840 Uttam Kumaran: Yes.

23 00:01:51.750 00:01:55.752 Miguel de Veyra: Family no friends just here for

24 00:01:56.790 00:02:00.829 Uttam Kumaran: I go to a friend’s house for July 4th every year.

25 00:02:00.830 00:02:03.320 Miguel de Veyra: Oh, oh, yeah. Yeah. Independence Day. No.

26 00:02:03.320 00:02:04.250 Uttam Kumaran: Yes.

27 00:02:04.670 00:02:06.510 Miguel de Veyra: Independence from the Brits.

28 00:02:07.770 00:02:08.710 Uttam Kumaran: Yes.

29 00:02:08.710 00:02:10.629 Mustafa Raja: Oh, I didn’t know that.

30 00:02:13.570 00:02:17.420 Miguel de Veyra: What’s I’m not sure. Concord, Manchester.

31 00:02:18.060 00:02:18.890 Miguel de Veyra: Go over.

32 00:02:18.890 00:02:19.990 Uttam Kumaran: I’m in Dover.

33 00:02:20.513 00:02:21.560 Miguel de Veyra: Port city.

34 00:02:24.800 00:02:27.849 Uttam Kumaran: Like one of some oldest parts of the Us.

35 00:02:30.640 00:02:33.650 Miguel de Veyra: Portland, Rockland.

36 00:02:42.520 00:02:44.530 Miguel de Veyra: Does it snow there or not? Really?

37 00:02:44.670 00:02:45.660 Miguel de Veyra: Oh, it has to.

38 00:02:45.970 00:02:49.070 Uttam Kumaran: Yes, it does not right now, but in the winter.

39 00:02:49.760 00:02:51.610 Miguel de Veyra: Looks good. It’s like up north.

40 00:02:56.488 00:02:59.199 Miguel de Veyra: It’s a rainy season here in the Philippines.

41 00:03:04.130 00:03:05.100 Uttam Kumaran: Oh, really.

42 00:03:05.290 00:03:08.580 Miguel de Veyra: Yeah, like heavy rains. I think it’s flooding everywhere right now.

43 00:03:08.580 00:03:09.700 Uttam Kumaran: Oh, my! Gosh!

44 00:03:10.240 00:03:10.740 Mustafa Raja: Yeah.

45 00:03:10.740 00:03:12.220 Uttam Kumaran: Happens every year, right.

46 00:03:12.220 00:03:15.151 Miguel de Veyra: Yeah, since I was a child.

47 00:03:16.149 00:03:20.730 Mustafa Raja: It’s same in same over here in Pakistan. Also.

48 00:03:21.130 00:03:22.110 Uttam Kumaran: Oh, really.

49 00:03:22.590 00:03:22.980 Mustafa Raja: Yeah.

50 00:03:22.980 00:03:23.400 Uttam Kumaran: Raining.

51 00:03:23.400 00:03:26.380 Mustafa Raja: Heavy rains and floods, and all.

52 00:03:27.090 00:03:28.440 Uttam Kumaran: Oh, okay.

53 00:03:32.370 00:03:36.380 Uttam Kumaran: okay. Should we get started? Let me just get this up.

54 00:03:39.330 00:03:40.480 Miguel de Veyra: Yeah, okay.

55 00:03:41.260 00:03:43.970 Mustafa Raja: Yeah. And Trainer Bot is working good. Now.

56 00:03:44.610 00:03:45.689 Uttam Kumaran: Oh, really. Okay.

57 00:03:45.870 00:03:52.379 Mustafa Raja: Yeah, yeah, it’s able to add, it’s able to retain all of its formatting

58 00:03:52.790 00:03:57.980 Mustafa Raja: the table of contents and everything and Update the document in in a way we want.

59 00:03:58.300 00:03:58.940 Miguel de Veyra: Nice.

60 00:03:58.940 00:04:00.219 Uttam Kumaran: Hmm nice.

61 00:04:02.552 00:04:08.590 Mustafa Raja: Can add new content to the section and replace content if needed.

62 00:04:09.980 00:04:11.000 Uttam Kumaran: Oh, nice. Okay.

63 00:04:11.000 00:04:14.070 Mustafa Raja: I’m going to test it today with amber. I’ve asked her.

64 00:04:14.070 00:04:14.590 Uttam Kumaran: Okay.

65 00:04:14.590 00:04:15.759 Mustafa Raja: For some time.

66 00:04:16.470 00:04:17.640 Uttam Kumaran: Oh, great. Okay.

67 00:04:22.730 00:04:29.609 Mustafa Raja: Oh, one more thing. am I allowed to use Google Google chat, node

68 00:04:30.640 00:04:33.479 Mustafa Raja: gemini, 2.5 flash or pro.

69 00:04:36.970 00:04:40.679 Uttam Kumaran: I guess question for Mustafa. I mean question for Miguel.

70 00:04:41.490 00:04:42.649 Miguel de Veyra: I mean, why not.

71 00:04:43.530 00:04:46.610 Mustafa Raja: Yeah, okay.

72 00:04:47.360 00:04:48.330 Uttam Kumaran: Do you need a key?

73 00:04:48.330 00:04:49.030 Uttam Kumaran: Something.

74 00:04:49.030 00:04:51.960 Mustafa Raja: No, there was a key already configured.

75 00:04:51.960 00:04:54.010 Miguel de Veyra: I think his concern is the price.

76 00:04:54.390 00:04:56.260 Mustafa Raja: Yeah, yeah, yeah, yeah.

77 00:04:56.260 00:05:00.609 Miguel de Veyra: But I think it should be fine as long as we don’t. You know, backfill 2,000 records using that.

78 00:05:00.610 00:05:01.170 Uttam Kumaran: Yeah.

79 00:05:01.560 00:05:05.839 Mustafa Raja: Yeah, yeah, yeah, it’s only it’s only for tool calling. And

80 00:05:06.230 00:05:08.419 Mustafa Raja: yeah, it’s only for tool calling. Actually.

81 00:05:09.050 00:05:09.640 Uttam Kumaran: Okay.

82 00:05:12.360 00:05:15.820 Mustafa Raja: Because it has a lot a lot more, bigger context window.

83 00:05:16.010 00:05:17.699 Mustafa Raja: So it works better with it.

84 00:05:18.210 00:05:18.960 Uttam Kumaran: Okay.

85 00:05:25.600 00:05:26.470 Mustafa Raja: Hey, Casey?

86 00:05:27.630 00:05:31.240 Miguel de Veyra: Hey? Guys sorry better now, still know.

87 00:05:32.720 00:05:36.040 Casie Aviles: Just a little bit of cough, but I’m fine.

88 00:05:38.590 00:05:39.689 Mustafa Raja: How was your weekend.

89 00:05:40.690 00:05:45.259 Casie Aviles: I’m just, you know, I’m just yeah. I’m just laying in my bed.

90 00:05:45.660 00:05:47.742 Casie Aviles: I’m just sleeping all the time.

91 00:05:48.280 00:05:49.419 Uttam Kumaran: Oh, that sucks.

92 00:05:50.000 00:05:50.440 Casie Aviles: Yeah.

93 00:05:52.005 00:05:54.013 Miguel de Veyra: Oh, okay. Yeah.

94 00:05:56.060 00:05:57.916 Uttam Kumaran: Let’s take a look.

95 00:06:08.260 00:06:10.900 Uttam Kumaran: Well, so I’ll let Amber take care of that. Let’s start

96 00:06:11.030 00:06:14.249 Uttam Kumaran: here. So for pool parts. This is in progress.

97 00:06:14.250 00:06:15.140 Miguel de Veyra: Yeah, yeah.

98 00:06:16.020 00:06:18.029 Uttam Kumaran: I haven’t. They haven’t given me.

99 00:06:19.180 00:06:22.350 Uttam Kumaran: I guess I’m good. I’ll I’ll ping them again today.

100 00:06:22.640 00:06:26.019 Uttam Kumaran: But yeah, I guess I I sent you the notes from him.

101 00:06:26.020 00:06:34.040 Miguel de Veyra: Yeah, yeah, this one. I was a bit cautious, because, yeah, it’s book, like, you have to log in right? But the thing is it automatically books it

102 00:06:34.210 00:06:34.830 Miguel de Veyra: after you.

103 00:06:34.830 00:06:35.650 Uttam Kumaran: Yeah.

104 00:06:35.650 00:06:45.150 Miguel de Veyra: So I was like, Oh, shit, I probably have to coordinate. But yeah, I’ll continue this, because, as you mentioned, you know, they don’t want. We might. We don’t want to get them suspicious of what’s happening.

105 00:06:49.240 00:06:50.130 Uttam Kumaran: Okay, cool

106 00:06:58.180 00:07:01.170 Uttam Kumaran: one second. Let me just try to send them a note right now.

107 00:07:02.072 00:07:06.490 Uttam Kumaran: Okay. And then I want to include

108 00:07:29.220 00:07:31.179 Uttam Kumaran: So okay, cool.

109 00:07:33.710 00:07:36.139 Uttam Kumaran: It’s off. The record is fine.

110 00:07:39.000 00:07:41.379 Uttam Kumaran: Doesn’t seem like we’re we may.

111 00:07:41.930 00:07:50.970 Uttam Kumaran: Doesn’t seem like these are much of a priority right now. So I’m just gonna move these back here

112 00:07:53.990 00:07:56.490 Uttam Kumaran: as we’re working on the chat walrus stuff.

113 00:08:02.620 00:08:05.870 Uttam Kumaran: Okay, that’s fine.

114 00:08:10.306 00:08:11.160 Uttam Kumaran: Let’s see.

115 00:08:15.380 00:08:16.970 Miguel de Veyra: Data, platform, hey? Luke.

116 00:08:20.320 00:08:21.720 Luke Daque: Everyone. How’s it going.

117 00:08:21.720 00:08:24.650 Uttam Kumaran: A welcome.

118 00:08:29.170 00:08:31.550 Uttam Kumaran: Yeah, I’m just gonna clean some of these up.

119 00:08:55.700 00:08:58.209 Uttam Kumaran: Okay? So then for chat walrus.

120 00:08:59.289 00:09:02.520 Uttam Kumaran: yeah, I think case, you’re ready. Just probably handle

121 00:09:03.590 00:09:07.453 Uttam Kumaran: like all of these. Do you wanna talk about

122 00:09:08.480 00:09:09.190 Uttam Kumaran: Oh.

123 00:09:09.960 00:09:12.959 Miguel de Veyra: Is this a new client, or just from off the record.

124 00:09:13.530 00:09:14.900 Casie Aviles: Yeah. From? Craig.

125 00:09:15.600 00:09:16.330 Miguel de Veyra: See.

126 00:09:18.990 00:09:19.770 Uttam Kumaran: What?

127 00:09:25.340 00:09:27.079 Uttam Kumaran: Wait. What just happened?

128 00:09:38.270 00:09:41.929 Uttam Kumaran: Hold on just something up.

129 00:09:50.290 00:09:51.420 Uttam Kumaran: What?

130 00:10:31.840 00:10:32.640 Uttam Kumaran: Okay?

131 00:10:34.190 00:10:36.539 Uttam Kumaran: Yeah. Casey, how do you feel about all these.

132 00:10:38.577 00:10:44.489 Casie Aviles: Yeah, I can start working on this. I think the only thing I was thinking about was

133 00:10:45.680 00:10:49.312 Casie Aviles: in terms of like, yeah, the accounts.

134 00:10:50.270 00:10:58.139 Casie Aviles: so I might actually, we might need so like something like windmill for that, if if we’re gonna kind of replicate, the same

135 00:10:58.500 00:11:03.149 Casie Aviles: process that we have internally, so I think I’ll

136 00:11:03.560 00:11:07.279 Casie Aviles: do. Do I let them know to set up a windmill account as well?

137 00:11:08.110 00:11:12.810 Casie Aviles: Do you have a different like? Yeah.

138 00:11:16.540 00:11:21.980 Uttam Kumaran: Yeah, I would ask Adam to set up a windmill account.

139 00:11:23.600 00:11:24.290 Casie Aviles: Okay.

140 00:11:28.650 00:11:32.409 Uttam Kumaran: Yeah, that that would be best in case they don’t want to.

141 00:11:35.220 00:11:39.619 Uttam Kumaran: We can bill them for it. But yeah, I would rather them. Just.

142 00:11:39.750 00:11:41.429 Uttam Kumaran: we just create a windmill account.

143 00:11:42.870 00:11:45.999 Casie Aviles: Okay, okay, I’ll let them know. And I’ll also just

144 00:11:46.150 00:11:49.349 Casie Aviles: take a look at some Google stuff. Because

145 00:11:49.460 00:11:52.889 Casie Aviles: for our case, I had to use like a service account

146 00:11:53.305 00:11:58.489 Casie Aviles: for Google Cloud. I’ll just double check if I’ll I’ll need that with them as well.

147 00:11:59.120 00:11:59.630 Uttam Kumaran: Okay.

148 00:11:59.630 00:12:01.199 Casie Aviles: But yeah, okay.

149 00:12:04.570 00:12:05.550 Uttam Kumaran: Okay, great.

150 00:12:08.110 00:12:10.590 Uttam Kumaran: Cool. This one is done right?

151 00:12:14.030 00:12:16.557 Uttam Kumaran: Oh, this is a different one. This is like,

152 00:12:16.810 00:12:18.210 Miguel de Veyra: Yeah. Yeah. Different. One.

153 00:12:18.210 00:12:22.290 Uttam Kumaran: This AI demo site like,

154 00:12:32.030 00:12:39.349 Uttam Kumaran: Okay, let’s talk about stuff for AI internal. That’s in review.

155 00:12:49.170 00:12:53.670 Uttam Kumaran: okay, so I may. I’m just gonna move all these to done because I feel comfortable after seeing the demo.

156 00:12:58.604 00:13:00.429 Uttam Kumaran: This one is in review. Casey.

157 00:13:01.980 00:13:07.590 Casie Aviles: Yes, I think Hannah’s already. I’m not sure if Hannah gave it to Robert. But yeah, I

158 00:13:08.880 00:13:12.180 Casie Aviles: yeah, I believe it’s they’re using it already.

159 00:13:12.820 00:13:16.339 Casie Aviles: I guess the only thing here is that it’s not really a

160 00:13:16.630 00:13:21.830 Casie Aviles: a scheduled or a reoccurring scraping, so I did it like one time, so

161 00:13:22.300 00:13:27.299 Casie Aviles: I might have to build like a yeah, a scheduled one.

162 00:13:33.240 00:13:33.920 Uttam Kumaran: Okay.

163 00:13:43.930 00:13:45.889 Uttam Kumaran: okay, I’m gonna mark it as done.

164 00:13:47.580 00:13:49.249 Uttam Kumaran: I just sent him a note.

165 00:13:55.050 00:13:57.140 Uttam Kumaran: Okay, so this is done.

166 00:13:58.720 00:14:00.280 Uttam Kumaran: This is done.

167 00:14:03.990 00:14:06.279 Miguel de Veyra: I think everything here on my end is done.

168 00:14:07.180 00:14:07.820 Uttam Kumaran: Okay?

169 00:14:13.850 00:14:15.480 Uttam Kumaran: And then the contextual.

170 00:14:15.990 00:14:18.570 Miguel de Veyra: Yeah, that’s just okay. That’s just as fine.

171 00:14:18.570 00:14:19.370 Uttam Kumaran: Okay. Cool.

172 00:14:20.590 00:14:21.919 Uttam Kumaran: Oh, nice. Alright.

173 00:14:29.200 00:14:30.750 Uttam Kumaran: This is done.

174 00:14:34.540 00:14:43.663 Mustafa Raja: Yes. So the this was when when we changed the Ui, according to the design teams design

175 00:14:44.680 00:14:51.399 Mustafa Raja: the linear section and the email section didn’t have their components. So I added them back.

176 00:14:52.650 00:14:54.389 Mustafa Raja: This is for Miguel to review.

177 00:14:58.298 00:15:00.879 Miguel de Veyra: Okay, is there a Pr already for this other.

178 00:15:00.880 00:15:01.800 Mustafa Raja: Yeah.

179 00:15:01.800 00:15:03.110 Miguel de Veyra: Okay, let me.

180 00:15:04.600 00:15:06.579 Miguel de Veyra: I’m not sure. I’ll get back to you.

181 00:15:10.050 00:15:14.820 Miguel de Veyra: Trainforge web platform app. Okay. Here. Okay. I had to reload.

182 00:15:22.290 00:15:25.190 Uttam Kumaran: Okay? And then, how about

183 00:15:27.750 00:15:32.640 Miguel de Veyra: Sample Pdfs are done. I’ve already ingested it into contextual.

184 00:15:38.290 00:15:39.300 Uttam Kumaran: And this one.

185 00:15:39.723 00:15:46.560 Miguel de Veyra: I’ll just copy paste something there can. Let’s leave it, or do I just put it. Put it on a notion, Doc, and send it to you.

186 00:15:47.950 00:15:49.389 Uttam Kumaran: You can put it in here. That’s fine.

187 00:15:49.390 00:15:50.360 Miguel de Veyra: Okay. Okay.

188 00:15:56.940 00:16:05.192 Uttam Kumaran: Okay. I mean, I think we’re still a little bit ambitious on on the amount of things we’re gonna get done. So I feel like

189 00:16:06.450 00:16:08.990 Uttam Kumaran: Let me just take a look at the cycle.

190 00:16:17.110 00:16:17.950 Uttam Kumaran: Okay?

191 00:16:20.140 00:16:23.050 Uttam Kumaran: Oh, why is 71 tickets? Wait

192 00:16:24.830 00:16:27.600 Uttam Kumaran: 71 points in the cycle.

193 00:16:30.730 00:16:34.739 Uttam Kumaran: These are all done last cycle. I’m gonna get the credit back.

194 00:16:54.030 00:16:55.850 Uttam Kumaran: Okay? So.

195 00:17:05.790 00:17:07.109 Miguel de Veyra: I’ll be right back. Guys.

196 00:17:10.720 00:17:11.790 Uttam Kumaran: Yes.

197 00:17:20.869 00:17:21.810 Uttam Kumaran: Hmm.

198 00:17:52.000 00:17:56.809 Uttam Kumaran: okay. Alright. I feel better about this.

199 00:17:57.120 00:17:58.186 Uttam Kumaran: I think.

200 00:18:10.660 00:18:13.920 Uttam Kumaran: about stuff that’s moving. So let’s take a look at

201 00:18:15.790 00:18:20.520 Uttam Kumaran: couple of things that we want to do for this week.

202 00:18:32.280 00:18:41.760 Uttam Kumaran: So I think one of the bigger things that I wanted to try and prioritize is

203 00:18:46.957 00:18:52.209 Uttam Kumaran: I have a couple of asks Mustafa like for lists.

204 00:18:52.882 00:19:02.870 Uttam Kumaran: And I think I’m gonna see if you can work, probably with Ryan from marketing on this. But one of this is, I want to get a list of all the

205 00:19:03.230 00:19:10.370 Uttam Kumaran: I’ll put this here so this is like all mid level. Pm’s

206 00:19:10.670 00:19:14.369 Uttam Kumaran: in Austin with Big 4. Experience that this is

207 00:19:14.910 00:19:16.969 Uttam Kumaran: just a list to pull, probably

208 00:19:17.210 00:19:26.720 Uttam Kumaran: from clay or I think if you use work with Ryan, you can get this. So basically, we’re trying to bring on like a mid level project manager.

209 00:19:27.206 00:19:29.689 Uttam Kumaran: So I just want to get a list. So we can go.

210 00:19:30.010 00:19:34.230 Uttam Kumaran: DM, these folks on Linkedin ideally, we need their name.

211 00:19:35.790 00:19:48.470 Uttam Kumaran: And Linkedin and email Big 4 is like Accenture Deloitte, ui pwc,

212 00:19:51.370 00:19:53.640 Uttam Kumaran: But you can also look for like Bcg,

213 00:19:55.370 00:19:59.700 Uttam Kumaran: so basically, we want to try to see if we can get this list using clay.

214 00:20:00.780 00:20:01.440 Mustafa Raja: Mia.

215 00:20:03.570 00:20:05.320 Uttam Kumaran: So take a look at that one.

216 00:20:06.075 00:20:09.629 Uttam Kumaran: The other one is we also want to look for

217 00:20:12.970 00:20:17.070 Uttam Kumaran: amplitude, mixed panel segment solution. Architects in Austin.

218 00:20:17.856 00:20:19.930 Uttam Kumaran: So pretty similar to the other one.

219 00:20:23.320 00:20:27.770 Uttam Kumaran: But again, we want their name Linkedin email.

220 00:20:27.910 00:20:29.310 Mustafa Raja: Oh, okay.

221 00:20:35.350 00:20:36.829 Uttam Kumaran: The other thing is

222 00:20:37.399 00:20:45.539 Uttam Kumaran: I want. I’m I’m trying to see if I can bring on one more person eventually to help like tech lead

223 00:20:45.780 00:20:47.280 Uttam Kumaran: the AI team.

224 00:20:47.440 00:20:52.890 Uttam Kumaran: So I wanna try to start connecting with anyone with like any n experience in Austin.

225 00:20:54.294 00:20:56.550 Uttam Kumaran: That way, we can try to find.

226 00:20:57.700 00:20:59.999 Uttam Kumaran: See if I can find anybody that can

227 00:21:00.560 00:21:06.810 Uttam Kumaran: help, either with project management or with AI, because, currently, yeah, it’s gonna be rough. If I’m leading so

228 00:21:07.140 00:21:15.420 Uttam Kumaran: similar. So list of everyone with NAN parents in Austin.

229 00:21:23.600 00:21:29.569 Uttam Kumaran: and then the other thing is so Sid, on the sales side is working on setting up hubspot

230 00:21:30.988 00:21:41.179 Uttam Kumaran: but I I guess myself I was just gonna see like it would be great to think about as you’re you’re gonna be working through this gig radar integration with Hubspot.

231 00:21:42.232 00:21:44.810 Uttam Kumaran: One of the things we wanna do is

232 00:21:45.170 00:21:55.969 Uttam Kumaran: like, make sure all emails and meeting activities are linked to each Hubspot lead.

233 00:21:56.610 00:22:02.240 Uttam Kumaran: So basically, it’s like, when a new lead is created.

234 00:22:03.860 00:22:12.899 Uttam Kumaran: we do several activities related to it, either meetings or emails.

235 00:22:15.020 00:22:22.609 Uttam Kumaran: Hubspot has a way to link all those like. I think it connects with my Gmail or something. But I just wanted to see if you can take a look at like

236 00:22:22.920 00:22:26.759 Uttam Kumaran: how we can make sure all activities are being tracked on each lead.

237 00:22:27.200 00:22:28.840 Mustafa Raja: Yeah, yeah, I can look at it.

238 00:22:49.990 00:22:50.600 Uttam Kumaran: Okay.

239 00:22:51.428 00:23:06.070 Uttam Kumaran: and then the last one I have sort of in this club thing. And this is looking for like integrations. People similar to like the Maga thing is like, I want to get a list of all amplitude, mix panel and segment. Snowflake and Dbt. Partners

240 00:23:06.670 00:23:08.830 Uttam Kumaran: with less than 5 employees.

241 00:23:09.490 00:23:10.100 Mustafa Raja: Yeah.

242 00:23:13.190 00:23:15.069 Uttam Kumaran: This is another one to take a look at.

243 00:23:16.280 00:23:20.100 Uttam Kumaran: I think those will be really really nice.

244 00:23:21.060 00:23:21.620 Mustafa Raja: Yeah.

245 00:23:21.620 00:23:22.830 Uttam Kumaran: Exercises.

246 00:23:23.010 00:23:23.510 Mustafa Raja: Yeah, I can.

247 00:23:23.510 00:23:28.180 Mustafa Raja: Isn’t try to teach them that, so that I can know which one to work on first.st

248 00:23:28.760 00:23:38.390 Uttam Kumaran: So the gig radar is still like important, probably the most important and then for this one

249 00:23:38.800 00:23:42.529 Uttam Kumaran: this is also very important.

250 00:23:43.810 00:23:45.490 Uttam Kumaran: This one is medium.

251 00:23:46.750 00:23:53.299 Uttam Kumaran: This is the lowest one, and then this is also a high one.

252 00:23:54.780 00:23:57.359 Uttam Kumaran: This one, I would say, is most more urgent.

253 00:23:59.365 00:24:00.160 Uttam Kumaran: Yeah.

254 00:24:01.920 00:24:04.890 Uttam Kumaran: And then what is this? This one.

255 00:24:05.250 00:24:10.429 Mustafa Raja: Yeah, this room is 35 min long. So I’d love some context over it.

256 00:24:10.880 00:24:17.460 Uttam Kumaran: Okay, okay, okay, yeah. Hi, this one. Maybe we should. Okay, I’m gonna

257 00:24:18.450 00:24:20.550 Uttam Kumaran: I’ll look and see if I can break it up.

258 00:24:21.060 00:24:29.759 Uttam Kumaran: Basically, this is like going through Robert’s process for one client. There’s probably like 5 or 6 different things we can automate in that. But I’ll take a look at this again.

259 00:24:30.160 00:24:30.800 Mustafa Raja: Okay.

260 00:24:41.324 00:24:41.790 Uttam Kumaran: Okay?

261 00:24:46.660 00:24:50.100 Uttam Kumaran: And then, Casey, you’re working on this one this week.

262 00:24:52.340 00:24:56.060 Casie Aviles: Yeah, I, yeah, I could work on this this week.

263 00:24:56.530 00:24:58.060 Uttam Kumaran: Okay, that’d be really great.

264 00:25:06.345 00:25:13.990 Casie Aviles: Yeah, this is related to. Yeah, I haven’t filled this out yet, but this is related to the scraping thing that I that was earlier.

265 00:25:14.600 00:25:15.330 Casie Aviles: Let me discuss.

266 00:25:15.683 00:25:16.390 Uttam Kumaran: I see!

267 00:25:21.380 00:25:25.220 Casie Aviles: I wonder which one that one is? Oh, yeah, definitely.

268 00:25:28.500 00:25:29.290 Uttam Kumaran: Okay.

269 00:25:40.050 00:25:42.300 Uttam Kumaran: this one is probably lower priority.

270 00:25:50.414 00:25:54.979 Uttam Kumaran: Okay, auto delete meeting recordings. Yeah, this is now getting to be a higher priority.

271 00:25:55.510 00:25:58.449 Casie Aviles: Okay, yeah, I’ll I’ll work on this this week.

272 00:25:58.960 00:25:59.580 Uttam Kumaran: Cool

273 00:26:04.510 00:26:08.220 Uttam Kumaran: and then we stopped the Google drive. Right?

274 00:26:08.890 00:26:09.880 Casie Aviles: Yes, yes.

275 00:26:10.220 00:26:10.820 Uttam Kumaran: Okay?

276 00:26:13.660 00:26:16.089 Uttam Kumaran: And then you did a pass of deleting a bunch.

277 00:26:18.109 00:26:22.939 Casie Aviles: You. You mean if I deleted the videos on Google drive.

278 00:26:23.230 00:26:23.980 Uttam Kumaran: Yes.

279 00:26:24.550 00:26:30.460 Casie Aviles: Yes, I’ve deleted some of them. I didn’t delete everything yet.

280 00:26:30.980 00:26:31.560 Uttam Kumaran: Okay.

281 00:26:38.161 00:26:40.969 Uttam Kumaran: Miguel, do you still want to investigate this one.

282 00:26:42.186 00:26:43.060 Miguel de Veyra: Oh, shit!

283 00:26:44.430 00:26:52.279 Miguel de Veyra: I think I’ll reopen because I haven’t really looked into this ticket. My bad.

284 00:26:52.920 00:26:53.540 Uttam Kumaran: Okay.

285 00:26:53.710 00:26:55.219 Miguel de Veyra: But you’re happy to investigate.

286 00:26:55.890 00:26:56.560 Uttam Kumaran: Okay.

287 00:26:59.390 00:27:01.379 Miguel de Veyra: By the way, is that your laptop logging.

288 00:27:02.620 00:27:07.770 Uttam Kumaran: I have an external monitor, and but I’m on a macbook air.

289 00:27:08.840 00:27:10.650 Uttam Kumaran: So it’s gonna lag.

290 00:27:11.370 00:27:14.410 Miguel de Veyra: Yeah, is it them, too? I have the same one. So.

291 00:27:14.410 00:27:16.680 Uttam Kumaran: m. 1 even worse.

292 00:27:16.680 00:27:18.050 Miguel de Veyra: And 8 GB, now.

293 00:27:18.850 00:27:21.690 Uttam Kumaran: It is 8 GB of RAM. This is pretty horrible.

294 00:27:21.850 00:27:22.820 Miguel de Veyra: Yeah, but.

295 00:27:22.820 00:27:31.406 Uttam Kumaran: But I haven’t. I have to. Everybody else gets upgraded 1st before me. So I I’m not gonna upgrade until everybody else gets better machines.

296 00:27:31.880 00:27:36.909 Miguel de Veyra: I’m I’m working on like getting a new laptop, because right now I’m glued to my PC.

297 00:27:38.630 00:27:43.550 Uttam Kumaran: Okay, okay, so this is all fine

298 00:27:47.360 00:27:48.280 Uttam Kumaran: pickle.

299 00:27:48.550 00:27:55.080 Uttam Kumaran: So this one would be really helpful to work on. Miguel.

300 00:27:55.550 00:27:58.810 Miguel de Veyra: Oh, yeah, yeah. Okay. Sure. Can we set this as high or something?

301 00:27:59.200 00:27:59.920 Uttam Kumaran: Yes.

302 00:28:10.270 00:28:11.790 Uttam Kumaran: and this one as well.

303 00:28:15.620 00:28:16.279 Miguel de Veyra: Okay, sure.

304 00:28:16.280 00:28:18.830 Uttam Kumaran: This one would be crazy if we can get it working.

305 00:28:18.830 00:28:20.690 Miguel de Veyra: Yeah, yeah, I’ll prioritize that.

306 00:28:21.510 00:28:25.085 Uttam Kumaran: The other one I wanted to maybe do related to this.

307 00:28:26.710 00:28:30.418 Uttam Kumaran: actually, I’ll come back to it in a sec because I wanna walk through it with

308 00:28:31.220 00:28:33.599 Uttam Kumaran: with Luke. Okay. So

309 00:28:42.020 00:28:49.069 Uttam Kumaran: okay. And this one also, let’s say so. It’s probably just gonna be a big like Hubspot week. I think.

310 00:28:51.500 00:28:52.280 Mustafa Raja: Okay.

311 00:29:19.170 00:29:19.750 Uttam Kumaran: Okay,

312 00:29:31.940 00:29:34.960 Uttam Kumaran: okay, so are you, gonna take a look at this bug, or did you already.

313 00:29:34.960 00:29:40.610 Casie Aviles: Oh, yeah, I made a different ticket, but only for the duplicate summaries.

314 00:29:40.920 00:29:46.580 Casie Aviles: I think the the wrong Channel thing will require a different fix.

315 00:29:47.150 00:29:47.760 Uttam Kumaran: Okay.

316 00:29:48.450 00:29:57.379 Casie Aviles: So for yeah, the duplicate summaries. I already made some changes, but I’m just monitoring if it will still do it.

317 00:29:57.860 00:29:58.890 Uttam Kumaran: Okay.

318 00:29:59.110 00:30:03.990 Casie Aviles: Did you guys notice anything if it’s still duplicated when I was out or not?

319 00:30:03.990 00:30:05.380 Uttam Kumaran: I didn’t see anything.

320 00:30:06.210 00:30:08.919 Casie Aviles: Okay, yeah, I guess it worked.

321 00:30:11.700 00:30:12.380 Casie Aviles: Oh.

322 00:30:15.670 00:30:21.849 Casie Aviles: so yeah, for for the wrong channels, I’ll I’ll likely implement a different logic for that. Now.

323 00:30:22.420 00:30:23.010 Uttam Kumaran: Okay?

324 00:30:28.850 00:30:36.070 Uttam Kumaran: And then, this is for adding more channels to the slack transformer.

325 00:30:38.980 00:30:41.389 Uttam Kumaran: Who on the team can take this? Or

326 00:30:42.380 00:30:44.799 Uttam Kumaran: yeah, who on the team wants to take this.

327 00:30:46.980 00:30:50.050 Mustafa Raja: This is in the dexter.

328 00:30:50.630 00:30:52.370 Uttam Kumaran: This is in Daxter. Yeah.

329 00:30:52.370 00:30:57.480 Mustafa Raja: Yeah, I guess it’s so. We only need to give it like a channel Id, or something like that.

330 00:30:57.910 00:31:04.180 Mustafa Raja: because we are we. We have our channels in the S. 3 already.

331 00:31:04.690 00:31:05.689 Mustafa Raja: Most of them.

332 00:31:06.350 00:31:09.410 Uttam Kumaran: But shouldn’t we add our internal channels to this too.

333 00:31:10.700 00:31:12.110 Mustafa Raja: Yeah. Yeah.

334 00:31:12.970 00:31:22.930 Mustafa Raja: I guess when we talked to wish or Casey checked last time the internal settings are also already in the s. 3, so we can add them here.

335 00:31:26.890 00:31:28.929 Uttam Kumaran: This is doing the filtering right.

336 00:31:29.170 00:31:33.449 Mustafa Raja: Yeah, this is we are putting them in super base. Right?

337 00:31:34.650 00:31:40.170 Uttam Kumaran: Yeah, so we definitely need to add like, add internal channels.

338 00:31:42.490 00:31:54.560 Uttam Kumaran: So this is sales project management, engineering data team, right?

339 00:31:54.920 00:32:04.620 Uttam Kumaran: AI team operations, brand motions.

340 00:32:08.950 00:32:11.880 Uttam Kumaran: And then we also have, like new clients.

341 00:32:12.970 00:32:20.819 Uttam Kumaran: So this is read me, pan stake default.

342 00:32:30.380 00:32:31.120 Uttam Kumaran: Okay.

343 00:32:34.670 00:32:38.170 Casie Aviles: Okay, I can try to take this one.

344 00:32:40.200 00:32:42.391 Uttam Kumaran: You can take this or

345 00:32:42.950 00:32:48.589 Uttam Kumaran: Yeah, okay, maybe. Well, actually, maybe I wanna assign this to Luke.

346 00:32:49.490 00:32:52.226 Uttam Kumaran: And I can try to talk a little bit about

347 00:32:53.140 00:32:55.289 Uttam Kumaran: couple of new things I want to add.

348 00:32:55.660 00:32:58.610 Uttam Kumaran: Given that he’s gonna have some availability.

349 00:32:59.692 00:33:03.650 Uttam Kumaran: Let me just double check. There’s anything else we want to bring on here.

350 00:33:12.750 00:33:13.665 Uttam Kumaran: okay,

351 00:33:18.130 00:33:24.136 Uttam Kumaran: okay, cool. So one of the things that I wanted to talk about was, I worked on

352 00:33:26.750 00:33:29.459 Uttam Kumaran: I worked on this document.

353 00:33:38.175 00:33:40.199 Uttam Kumaran: Called Project Leverage.

354 00:33:40.580 00:33:44.823 Uttam Kumaran: And yeah, it was just like

355 00:33:46.190 00:33:57.302 Uttam Kumaran: talking to Robert and a few people yesterday. And we’re really where this comes comes out of is

356 00:33:58.910 00:34:01.410 Uttam Kumaran: pretty much like historically.

357 00:34:02.170 00:34:13.850 Uttam Kumaran: I’ve like, especially in the last 3, 4 months. It’s getting kind of insane like like, how much continues to go through me. And so part of what I’m trying to do is one

358 00:34:14.030 00:34:16.290 Uttam Kumaran: really put constraints on

359 00:34:16.610 00:34:31.649 Uttam Kumaran: where my time is going, because I’m just finding really limited ability to work on the business like, I’m doing a lot of stuff in the business. And so basically I did some research and sort of wanted to put together a couple of tasks that I think is just gonna help us get more leverage.

360 00:34:32.260 00:34:39.979 Uttam Kumaran: Really, what that means is that I sort of broke down like, okay, we have like 9 to 5. And that’s like,

361 00:34:40.760 00:34:51.209 Uttam Kumaran: you know, like 80 30 min blocks right? And so one of the things that I want to just get a sense of is like, where is the time? Where is the time going?

362 00:34:51.878 00:34:54.460 Uttam Kumaran: And are we able to ensure that

363 00:34:55.040 00:34:58.559 Uttam Kumaran: that time is getting spent on the right priorities?

364 00:34:59.190 00:35:03.700 Uttam Kumaran: we’re doing some stuff on my side to sort of get things into other people’s hands.

365 00:35:03.860 00:35:12.019 Uttam Kumaran: Part part of this project is is a mix of understanding like, where are existing

366 00:35:12.530 00:35:14.719 Uttam Kumaran: like time is going as a company.

367 00:35:15.150 00:35:20.429 Uttam Kumaran: and then also helping me, and other leadership like get more leverage over

368 00:35:22.290 00:35:25.290 Uttam Kumaran: like in in the times that we we are working

369 00:35:25.995 00:35:29.580 Uttam Kumaran: and so the 1st sort of thing I wanted to work on is.

370 00:35:30.301 00:35:35.619 Uttam Kumaran: is a couple of things around meeting slack analytics

371 00:35:35.920 00:35:38.086 Uttam Kumaran: and sort of like a

372 00:35:39.020 00:35:54.469 Uttam Kumaran: like meeting scoring system. Basically so this is not in any order of like priority. But I want to talk about like calendar analytics. So basically, I want to be able to start to pull all Google Google Calendar events.

373 00:35:54.720 00:35:56.410 Luke Daque: Into s. 3.

374 00:35:57.655 00:36:02.230 Uttam Kumaran: Second is, I want to basically build an ability to classify

375 00:36:04.070 00:36:10.250 Uttam Kumaran: like those events like what type of an event it was. And then also see if it like.

376 00:36:10.970 00:36:13.996 Uttam Kumaran: basically try to get a sense of like, is this,

377 00:36:14.670 00:36:24.330 Uttam Kumaran: was this a good meeting, and then also start to and start show visualizations against that. So I think this is all stuff we can do in real if we just get everything into S. 3

378 00:36:26.080 00:36:32.549 Uttam Kumaran: but that’s like the 1st set of projects. I think ideally, we’ll start with my calendar, and then we can

379 00:36:32.760 00:36:37.924 Uttam Kumaran: move on to bringing in everybody’s. And so we can kind of get a sense of how many meetings are happening in the company.

380 00:36:38.796 00:36:48.219 Uttam Kumaran: And then, like, basically get an understanding of like, if the meetings are are good. The second thing, this is probably honestly more important.

381 00:36:49.131 00:36:50.939 Uttam Kumaran: Because this is sort of like

382 00:36:51.780 00:36:57.849 Uttam Kumaran: kind of like, have. It’s a big like love, hate relationship with with slack overall. Right now

383 00:36:58.170 00:37:01.619 Uttam Kumaran: in that I get tagged in a lot of things.

384 00:37:02.326 00:37:04.960 Uttam Kumaran: And it’s incredibly hard for me to

385 00:37:05.460 00:37:09.893 Uttam Kumaran: just focus and get couple of things that we need done for the company.

386 00:37:10.658 00:37:21.349 Uttam Kumaran: And so one of the things that I’m trying to would love to work on. And again, this is something that I think would work for me, and then easily, I think, from people that are also

387 00:37:22.090 00:37:24.420 Uttam Kumaran: for people that are also working on a lot of

388 00:37:24.580 00:37:28.949 Uttam Kumaran: clients are in a leadership position. I think this will immediately go to help them.

389 00:37:29.190 00:37:35.059 Uttam Kumaran: The one is like, I wanna start by making sure we get all the slack messages from channels.

390 00:37:36.680 00:37:42.749 Uttam Kumaran: So that’s 1. If we can get stuff from Dms like we could try. I just don’t know what’s possible.

391 00:37:43.290 00:37:47.950 Uttam Kumaran: Second is like, I want to calculate these metrics.

392 00:37:48.270 00:37:51.969 Uttam Kumaran: The number of mentions number of replies by me.

393 00:37:52.440 00:38:00.249 Uttam Kumaran: a number of distinct threads that, like I posted in and the number of the unique senders that are tagged.

394 00:38:01.770 00:38:08.799 Uttam Kumaran: this will get a sense of like, okay, when am I getting hit for messages, and like this will allow us to start to measure this.

395 00:38:09.351 00:38:17.779 Uttam Kumaran: Then I want to start to have an Llm. Sort of understand and classify the message like, is this something that could have been answered by someone else

396 00:38:18.220 00:38:25.289 Uttam Kumaran: was, did I? Was I absolutely necessary and like could have been delegated, and then could start to look at like black burden.

397 00:38:26.653 00:38:35.309 Uttam Kumaran: To give you guys a sense. I mean, I I’m excited to see the numbers, but I probably get hit up in slack like a hundred times a day, maybe like 100 to 150

398 00:38:35.560 00:38:37.890 Uttam Kumaran: like I’m guessing.

399 00:38:38.930 00:38:43.467 Uttam Kumaran: And that makes my job like incredibly hard to do.

400 00:38:44.240 00:38:51.098 Uttam Kumaran: So I do think that this is something that will be really interesting. And this is something that we’ll we’ll work on

401 00:38:51.660 00:38:52.620 Uttam Kumaran: after.

402 00:38:54.090 00:39:03.009 Uttam Kumaran: But I think these 2 are really the most important. And then the the meeting scoring system. I think this is something that we should start doing for all meetings is like

403 00:39:03.631 00:39:08.569 Uttam Kumaran: similar to the summary step. We should just have a a score step.

404 00:39:10.310 00:39:20.400 Uttam Kumaran: Right? So this takes in the meeting transcripts, and then uses uses Llm

405 00:39:21.350 00:39:26.340 Uttam Kumaran: to score based on these dimensions focus. This is making owner clarity value and redundancy.

406 00:39:26.740 00:39:30.280 Uttam Kumaran: And then, yeah, basically writes the score somewhere.

407 00:39:30.530 00:39:35.750 Uttam Kumaran: And then I want to start measuring how good our meetings are.

408 00:39:38.720 00:39:44.569 Uttam Kumaran: So this is sort of a couple of things in this sort of like what I’m what I basically am describing is like

409 00:39:44.970 00:39:46.680 Uttam Kumaran: project leverage.

410 00:39:47.319 00:39:53.560 Uttam Kumaran: One other thing that I want to work on is this which is

411 00:39:56.030 00:39:58.400 Uttam Kumaran: basically a summary of like

412 00:39:59.070 00:40:04.229 Uttam Kumaran: cause. What 1 1 of the changes I’m gonna do is I’m I’m gonna start to be off slack.

413 00:40:04.580 00:40:08.909 Uttam Kumaran: or like at least one or 2 h per day.

414 00:40:11.180 00:40:16.230 Uttam Kumaran: because I just I can’t get any work done during the day if it’s if I see it.

415 00:40:16.732 00:40:20.550 Uttam Kumaran: But one thing that I want help on is like, I want to know.

416 00:40:21.160 00:40:27.849 Uttam Kumaran: like, let’s say, I log back on at the end of the day. I want to get an understanding of what are all the things I need to go back through and respond to?

417 00:40:29.710 00:40:30.810 Uttam Kumaran: And so

418 00:40:30.920 00:40:46.259 Uttam Kumaran: this is just an ability to to do that. So how can we sort of enable someone like me to get a summary of all the things they’ve been tagged in. This is actually very similar to the ticket that Miguel is taking on, which is

419 00:40:46.930 00:40:50.309 Uttam Kumaran: reminder messages that haven’t been responded to.

420 00:40:50.710 00:40:52.862 Uttam Kumaran: It’s almost like a

421 00:40:54.160 00:40:57.820 Uttam Kumaran: It’s almost like this would only be for one person.

422 00:40:58.060 00:41:00.480 Uttam Kumaran: And the way you can see this working is like

423 00:41:00.900 00:41:12.119 Uttam Kumaran: part of what’s happening here is like some in in linear, in notion and in slack and in email, we all have things asks that are coming our way.

424 00:41:12.310 00:41:23.869 Uttam Kumaran: And we need some ability to prioritize. Right? Typically, this is like what a project manager does right, but almost I want to give every single person their own like Project manager

425 00:41:24.230 00:41:29.140 Uttam Kumaran: where it will have like. Hey, here’s all the things that you’ve been tagged in today.

426 00:41:29.490 00:41:40.340 Uttam Kumaran: and that way I can look at that at the end of the day and go through it, or like if something drops through the funnel I can go through at the end of the day, and then this something will roll out to everybody in the company

427 00:41:40.710 00:41:42.979 Uttam Kumaran: after it starts working for me.

428 00:41:43.562 00:41:51.160 Uttam Kumaran: So that people are confident that they’re not missing things, that there’s not things dropping, and also people can log off slack for a little bit and be okay.

429 00:41:51.260 00:41:58.010 Uttam Kumaran: Because Slack doesn’t give you any ability to do prioritization.

430 00:41:58.190 00:42:11.609 Uttam Kumaran: It doesn’t give you any ability to delay notifications. It’s really, really kind of corrupt like in terms of like it. Feeling like context, time and context switching. So I kind of really want to attack that.

431 00:42:15.720 00:42:19.770 Uttam Kumaran: So stop there like any thoughts.

432 00:42:22.350 00:42:25.092 Luke Daque: Yeah, just one quick question is,

433 00:42:26.800 00:42:29.370 Luke Daque: just to clarify the goal for this

434 00:42:29.770 00:42:37.889 Luke Daque: specific project, like, at least for from my end. Is it like the data integration piece to integrate slack

435 00:42:38.860 00:42:41.709 Luke Daque: to S 3 and stuff like that? I guess.

436 00:42:42.490 00:42:49.969 Uttam Kumaran: Yeah. So I do think that Luke, where you’re most leverage is in here. And then in the in getting this into real

437 00:42:51.063 00:42:56.570 Uttam Kumaran: the AI team will help you do any of these like classifications, if necessary.

438 00:42:58.780 00:43:01.420 Uttam Kumaran: And they can work with you on setting that up.

439 00:43:01.900 00:43:08.260 Uttam Kumaran: We already also have some of these set up, so I think it would be great for you to meet with

440 00:43:08.520 00:43:13.209 Uttam Kumaran: the AI team to understand how we’re currently moving slack into S. 3.

441 00:43:13.720 00:43:15.310 Luke Daque: And then how.

442 00:43:15.930 00:43:18.560 Uttam Kumaran: They can facilitate some of these asks,

443 00:43:21.010 00:43:28.540 Uttam Kumaran: so let me know like how I want. Maybe I’ll let you sort of take a look at this ticket, and if you could own breaking it down.

444 00:43:29.397 00:43:37.660 Uttam Kumaran: maybe it is one ticket per section. But I do think that I I don’t want to. I want you to sort of under because you’re

445 00:43:37.960 00:43:46.740 Uttam Kumaran: next to me. You’re the next resident data expert. And so anything that is like sort of data movement. I want you to sort of have a good understanding of.

446 00:43:46.890 00:43:53.299 Uttam Kumaran: They’re running, you know. We’re running stuff in Daxter to pull these, but it’d be good for you to sort of get an understanding of that.

447 00:43:53.430 00:43:54.030 Uttam Kumaran: I think.

448 00:43:54.030 00:43:54.360 Luke Daque: Okay.

449 00:43:54.360 00:44:00.030 Uttam Kumaran: If you meet with I think everybody on this team sort of has a good understanding of of how this is working.

450 00:44:00.687 00:44:11.140 Uttam Kumaran: But that would be very helpful, and then I would say, the classification stuff is helpful, but you know you can work on some of the viz. Even before you have this. Right? So

451 00:44:12.560 00:44:17.329 Uttam Kumaran: ideally, I think the slack analytics is the number one priority.

452 00:44:17.620 00:44:20.919 Uttam Kumaran: So slack analytics and then meeting analytics.

453 00:44:22.300 00:44:23.300 Luke Daque: Gotcha.

454 00:44:24.510 00:44:26.032 Luke Daque: Okay. Sounds good.

455 00:44:27.000 00:44:31.510 Luke Daque: But you mentioned we already have slack integrated to Sv. At the moment.

456 00:44:31.880 00:44:32.290 Uttam Kumaran: We do?

457 00:44:32.290 00:44:34.950 Luke Daque: Or oh, nice!

458 00:44:41.770 00:44:44.669 Uttam Kumaran: So I’m just gonna create a couple of spike tickets.

459 00:44:52.470 00:44:54.689 Uttam Kumaran: And let me just edit this.

460 00:45:11.330 00:45:15.239 Uttam Kumaran: Yeah. And then once it scales to me, I’m gonna have it scale to sort of all managers

461 00:45:15.390 00:45:17.070 Uttam Kumaran: think that would be really, really great.

462 00:45:41.960 00:45:46.339 Uttam Kumaran: Okay, those 2 spikes. And then

463 00:45:49.290 00:45:54.109 Uttam Kumaran: this meeting scoring system. I think, Casey, I’ll let you think about it this week.

464 00:45:55.080 00:45:55.720 Casie Aviles: Okay.

465 00:45:57.590 00:45:58.950 Uttam Kumaran: Anyone else is interested.

466 00:45:59.540 00:46:06.290 Miguel de Veyra: For that meeting, scoring. I think we can do that, and we can also display that on the dashboard. No.

467 00:46:06.290 00:46:07.010 Uttam Kumaran: Yes.

468 00:46:07.310 00:46:11.390 Miguel de Veyra: So kind of backfill. And then, yeah, I’ll coordinate with Casey.

469 00:46:14.200 00:46:19.829 Uttam Kumaran: Yeah, because Casey has all the understanding of, like the Zoom transcript flow.

470 00:46:19.830 00:46:20.240 Miguel de Veyra: Yeah.

471 00:46:20.240 00:46:29.560 Uttam Kumaran: I feel like this could be convenient. But I honestly think, like Casey, you should work with Miguel, or, yeah, maybe work with Miguel, because I think the stuff has a bunch on his plate.

472 00:46:29.780 00:46:31.660 Uttam Kumaran: Just talk through this and like.

473 00:46:32.020 00:46:34.669 Uttam Kumaran: get a sense of like if this is gonna work.

474 00:46:39.440 00:46:43.999 Uttam Kumaran: And then. Yes, I want to start displaying basically scores of of the meetings.

475 00:46:44.000 00:46:44.380 Miguel de Veyra: Yep.

476 00:46:44.380 00:46:51.399 Uttam Kumaran: Because also, that’s gonna help us basically say, cool. Let’s look at all the worst meetings and then see what happened there, you know or like, how we can improve.

477 00:46:51.900 00:47:00.040 Miguel de Veyra: Yeah, I think that’s the 1st thing we can add other than the chat bot and the list of meetings in the dashboard is there, like, you know, the worst meetings.

478 00:47:00.290 00:47:00.690 Luke Daque: Yeah.

479 00:47:04.460 00:47:07.109 Miguel de Veyra: Top 5. Worst 3 meetings. Okay.

480 00:47:09.780 00:47:10.679 Luke Daque: By the way, we’ll talk.

481 00:47:10.680 00:47:14.150 Luke Daque: Can you add me to the linear? Let the team.

482 00:47:14.150 00:47:15.060 Uttam Kumaran: Oh, yeah.

483 00:47:15.230 00:47:17.329 Luke Daque: So yeah, I can’t see them

484 00:47:23.110 00:47:24.770 Luke Daque: cool. Thanks.

485 00:47:31.250 00:47:35.170 Uttam Kumaran: Okay, how do we feel? Guys?

486 00:47:36.230 00:47:37.840 Uttam Kumaran: Kind of a lot of tickets.

487 00:47:41.150 00:47:41.570 Mustafa Raja: Actually.

488 00:47:42.590 00:47:44.120 Casie Aviles: Yeah, this looks good to me.

489 00:47:46.040 00:47:48.440 Uttam Kumaran: 30 tickets. I mean, it’s not the worst.

490 00:47:51.070 00:47:55.490 Uttam Kumaran: I would say, Mustafa, it’s gonna I think you have, like maybe 5 or 6.

491 00:47:56.210 00:47:59.060 Uttam Kumaran: And then, Casey, some of yours like

492 00:48:00.160 00:48:02.370 Uttam Kumaran: after Chat Wallace, I think you’ll be able to get to.

493 00:48:02.780 00:48:05.400 Uttam Kumaran: But, Mustafa, you currently have the most right now.

494 00:48:06.290 00:48:13.129 Mustafa Raja: Yeah, it’s mostly hubspot. So they must all be linked to each other so it wouldn’t be a problem. I feel.

495 00:48:13.130 00:48:16.090 Uttam Kumaran: Okay, okay?

496 00:48:23.360 00:48:27.040 Uttam Kumaran: And then, Miguel, this one would be like, incredible.

497 00:48:27.040 00:48:27.710 Miguel de Veyra: Yeah.

498 00:48:29.854 00:48:31.979 Uttam Kumaran: How are you thinking about this

499 00:48:33.960 00:48:36.799 Uttam Kumaran: like is this gonna show up in?

500 00:48:38.520 00:48:41.479 Uttam Kumaran: Is this gonna show up in slack or like.

501 00:48:43.350 00:48:45.157 Miguel de Veyra: This is a

502 00:48:48.710 00:48:53.130 Miguel de Veyra: Probably the best would be slack first, st like on the specific team. No.

503 00:48:55.820 00:48:56.706 Uttam Kumaran: I guess.

504 00:49:00.620 00:49:03.430 Uttam Kumaran: Well, this is a this is an interesting one.

505 00:49:05.160 00:49:07.240 Uttam Kumaran: right? This is almost like a part 2.

506 00:49:07.360 00:49:08.780 Miguel de Veyra: Yeah, I agree.

507 00:49:09.700 00:49:12.720 Uttam Kumaran: But then this one should really be like this is like

508 00:49:14.080 00:49:17.209 Uttam Kumaran: in a slack channel or in a notion, Doc. I don’t know.

509 00:49:18.040 00:49:27.030 Uttam Kumaran: I guess in a slack channel you can look at like, look at all tickets in current cycle and

510 00:49:27.420 00:49:34.720 Uttam Kumaran: current cycle run. If that run basically like the evaluator.

511 00:49:34.720 00:49:38.130 Miguel de Veyra: Like a front job that it runs on Mondays or every day.

512 00:49:38.500 00:49:43.949 Uttam Kumaran: Yeah, run evaluator and then send tickets that don’t.

513 00:49:45.370 00:49:46.224 Miguel de Veyra: Not very bad.

514 00:49:46.670 00:49:49.260 Uttam Kumaran: Are bad to slack.

515 00:49:49.600 00:49:50.190 Miguel de Veyra: Yeah, something.

516 00:49:50.190 00:49:52.899 Uttam Kumaran: Right now. Just send it to the test channel and see what happens.

517 00:49:52.900 00:49:53.460 Miguel de Veyra: Sure.

518 00:49:55.400 00:49:59.760 Uttam Kumaran: Basically, we want to make sure that any ticket in cycle

519 00:50:00.773 00:50:02.900 Uttam Kumaran: is good. And I think you can.

520 00:50:03.400 00:50:06.138 Uttam Kumaran: I think, in terms of doing like

521 00:50:06.980 00:50:10.790 Uttam Kumaran: Well, I would say, ask in Pm.

522 00:50:11.120 00:50:19.750 Uttam Kumaran: Panel for their guidance on what constitutes all good together.

523 00:50:19.750 00:50:23.000 Miguel de Veyra: Okay, could I do the AI theme first? st

524 00:50:23.690 00:50:24.400 Uttam Kumaran: Yes.

525 00:50:24.810 00:50:26.270 Uttam Kumaran: Oh, yeah, that’d be great. Yeah.

526 00:50:26.270 00:50:28.040 Miguel de Veyra: Should we do a client instead.

527 00:50:30.360 00:50:34.430 Uttam Kumaran: I don’t care either way for me. It’s more of functionality. I just care about the functionality.

528 00:50:34.430 00:50:35.510 Miguel de Veyra: Okay. Okay. Sure.

529 00:50:46.830 00:50:52.279 Uttam Kumaran: Okay. So yeah, I mean, I, I think that we’re a lot of stuff is going on this week, I think.

530 00:50:52.570 00:50:55.361 Uttam Kumaran: for the platform side. I feel good.

531 00:50:56.430 00:50:59.549 Uttam Kumaran: I think the biggest sort of open question

532 00:51:03.720 00:51:11.040 Uttam Kumaran: is just like making sure we can add all clients. So I’m I’m I’m rico is starting as on operations.

533 00:51:11.718 00:51:17.359 Uttam Kumaran: And so I’m kind of helping him sort of work through, so he’ll he’ll be owning like creating new clients there.

534 00:51:17.590 00:51:20.270 Uttam Kumaran: and things like that. I think the only other piece

535 00:51:21.105 00:51:25.680 Uttam Kumaran: that we wanted to work on. And I don’t. This is gonna be honestly based on

536 00:51:25.860 00:51:30.987 Uttam Kumaran: Mustafa’s work in Hubspot is eventually we want

537 00:51:32.820 00:51:33.720 Uttam Kumaran: Oh.

538 00:51:39.080 00:51:41.210 Uttam Kumaran: wait! What is the what is the thing again?

539 00:51:44.920 00:51:47.419 Uttam Kumaran: What’s the URL again? Oh, this is

540 00:51:48.041 00:51:50.840 Uttam Kumaran: we’re gonna wanna get all the leads in here.

541 00:51:52.320 00:51:55.940 Uttam Kumaran: So for any new lead that gets created in Hubspot.

542 00:51:56.530 00:52:01.120 Uttam Kumaran: we’re gonna create a matching record and super base

543 00:52:01.480 00:52:04.980 Uttam Kumaran: so that you can go chat with all the activities related to a lead.

544 00:52:05.650 00:52:10.639 Uttam Kumaran: But that’s sort of like the downstream impact myself of making sure all those activities are there

545 00:52:10.800 00:52:13.210 Uttam Kumaran: is that eventually we’ll make it available here.

546 00:52:13.430 00:52:18.670 Uttam Kumaran: And then for this stuff, like, for example, departments. This is where sales and everything is gonna go right. So.

547 00:52:21.150 00:52:21.770 Mustafa Raja: Yeah.

548 00:52:23.730 00:52:27.330 Uttam Kumaran: So the downstream implications of getting Hubspot working is

549 00:52:27.450 00:52:31.350 Uttam Kumaran: ideally I don’t want to. We won’t be spending a ton of time in Hubspot.

550 00:52:31.470 00:52:35.300 Uttam Kumaran: but we want to be able to chat similarly, how we chat with all the

551 00:52:35.530 00:52:40.009 Uttam Kumaran: activities related to a client. We’re gonna chat with all the activities related to bleed.

552 00:52:40.680 00:52:41.390 Mustafa Raja: Yeah.

553 00:52:47.710 00:52:54.479 Uttam Kumaran: Okay, cool another productive week. Anything else. I’m gonna be out

554 00:52:54.750 00:52:56.080 Uttam Kumaran: towards the end of the week.

555 00:52:56.390 00:53:00.650 Uttam Kumaran: I’ll try my best to get everybody, everything they need. By Wednesday.

556 00:53:03.610 00:53:07.236 Mustafa Raja: Okay? Then I then I’ll work on the

557 00:53:07.850 00:53:15.509 Mustafa Raja: hubspot to get rid our thing because I feel there. I might need a few things from you.

558 00:53:15.980 00:53:16.620 Uttam Kumaran: Okay.

559 00:53:18.520 00:53:26.049 Miguel de Veyra: As for me, I’ll just finish the contextual stuff, and then the one for this for the CEO of pool.

560 00:53:27.030 00:53:32.619 Miguel de Veyra: And then, yeah, Putin, by the way, do you mind if I like? Take like a 2 to maybe 3 h break? I’m I’m not.

561 00:53:32.620 00:53:33.270 Uttam Kumaran: Yeah, yeah, yeah.

562 00:53:35.590 00:53:37.059 Miguel de Veyra: I’ll keep you guys posted.

563 00:53:37.190 00:53:38.390 Miguel de Veyra: Thank you. Everyone.

564 00:53:39.320 00:53:53.540 Uttam Kumaran: Okay, thank you. Guys, welcome, Luke. And then, yeah, I think, Luke, probably biggest thing is for you to just learn about the slack process, and then it’s already in s. 3. So I think you can bring a lot of that into into real sorry, internal, real. So feel free to rip it.

565 00:53:53.780 00:53:56.629 Luke Daque: Do we have it in snowflake branding, or just just.

566 00:53:56.630 00:53:58.999 Uttam Kumaran: You can connect real directly to S. 3.

567 00:53:59.190 00:54:01.910 Uttam Kumaran: Oh, really, I didn’t know that cool nice.

568 00:54:02.440 00:54:08.149 Uttam Kumaran: so that actually may save us some processing time, and then you can do any basic modeling in real.

569 00:54:08.430 00:54:14.629 Luke Daque: Right? So yeah, okay, yeah, I’ll do that. I’ll that’s what I’m gonna do for the spike. Then.

570 00:54:15.060 00:54:15.960 Uttam Kumaran: Okay, okay?

571 00:54:16.540 00:54:20.879 Uttam Kumaran: And then, yeah, the if you have any questions hit in the AI team, everybody can help answer.

572 00:54:21.620 00:54:23.020 Luke Daque: Sounds, good thanks.

573 00:54:23.020 00:54:25.530 Uttam Kumaran: Okay, thank you. Guys appreciate it.

574 00:54:25.530 00:54:26.520 Mustafa Raja: Thank you.

575 00:54:26.930 00:54:27.660 Uttam Kumaran: Bye.

576 00:54:27.840 00:54:28.255 Mustafa Raja: Bye.