Meeting Title: PM Daily Sync Date: 2025-04-01 Meeting participants: Aakash Tandel, Uttam Kumaran, Amber Lin
WEBVTT
1 00:01:06.450 ⇒ 00:01:07.350 Aakash Tandel: Hey! Amber.
2 00:01:08.050 ⇒ 00:01:09.130 Amber Lin: Hello!
3 00:01:10.280 ⇒ 00:01:10.970 Aakash Tandel: How’s it going
4 00:01:11.780 ⇒ 00:01:14.960 Amber Lin: Pretty good lots of meetings.
5 00:01:15.110 ⇒ 00:01:18.369 Amber Lin: So I just got off of a call from Annie.
6 00:01:18.980 ⇒ 00:01:20.720 Amber Lin: How’s it going for you?
7 00:01:21.940 ⇒ 00:01:25.830 Aakash Tandel: Good. I think. Yeah, busy.
8 00:01:25.990 ⇒ 00:01:27.150 Amber Lin: But I’ve
9 00:01:28.410 ⇒ 00:01:29.400 Aakash Tandel: Yeah.
10 00:01:29.510 ⇒ 00:01:32.189 Aakash Tandel: Lot of managing clients. I think.
11 00:01:33.370 ⇒ 00:01:36.640 Aakash Tandel: Lot of stuff going on. Yeah, not too bad.
12 00:01:39.025 ⇒ 00:01:42.540 Amber Lin: Let’s we can. I think we can make this
13 00:01:42.760 ⇒ 00:01:51.780 Amber Lin: pretty quick. So pretty good progress on all my teams. ABC, we’re starting to roll out. It’s good on track. So
14 00:01:52.295 ⇒ 00:02:01.440 Amber Lin: the client is reactive and able to give them tasks. And so we’re on track for that, and was onboarding Annie, so
15 00:02:01.530 ⇒ 00:02:27.526 Amber Lin: has also pretty good. She’ll have some more work that I don’t know how big the work will be, but we’re meeting with their internal data team. So we’ll have more stuff there for the internal AI team. Today, we did discovery call with the data team with Demo Day. So getting to know what their priorities are and what kind of is needed from there and then we’re on track of getting things set up so more
16 00:02:28.170 ⇒ 00:02:51.330 Amber Lin: So Casey and Miguel’s working on that of getting all the data information into a data lake. Essentially, that’s good. And for stack splits the clients. Just the client we’re working with the client data team and their data team is slow, so slow because I don’t have benchmarks on how fast things should move. So for me.
17 00:02:51.670 ⇒ 00:03:06.479 Amber Lin: Brain forge is my norm. I’m like, Okay, this is a pace. We work at it. Sometimes, I think, overcome too slow. But then I work with their data team. And the week later, last we met on last Tuesday, and we gave them an access permission to most stuff.
18 00:03:07.040 ⇒ 00:03:08.010 Amber Lin: And
19 00:03:08.170 ⇒ 00:03:17.919 Amber Lin: today they’re asking the same question on the same stuff, and I asked them, Do you guys have a roadmap, or do you even have a backlog? We have 0 items in a backlog?
20 00:03:18.330 ⇒ 00:03:26.549 Amber Lin: They’re not moving. And they’re like, Oh, I don’t think we need a backlog right now. We really need to work on this reconciliation stuff. So
21 00:03:27.270 ⇒ 00:03:35.400 Amber Lin: that’s that’s on them like there’s nothing we can do. We’re gonna talk to Mitch, the CEO or the product owner. But
22 00:03:35.720 ⇒ 00:03:38.950 Amber Lin: both all 3 are going pretty well. What about you
23 00:03:38.950 ⇒ 00:03:45.229 Aakash Tandel: Okay. Nice. Yeah. I’m Javi. We’re kind of
24 00:03:45.988 ⇒ 00:04:00.291 Aakash Tandel: limited at the moment with a wish being out. He’s out yesterday. 6. So trying to, I I shifted over some stuff to Witham so hopefully that’ll be good and then Eden
25 00:04:01.430 ⇒ 00:04:16.090 Aakash Tandel: like Josh put a kibosh on a lot of the work that we were originally doing, and then wants us focus. And now he wants us to bring that work back in so working with trying to figure out how to bring that work back in, and what the status of those existing things are. So that’s kind of where we’re at with those guys
26 00:04:16.899 ⇒ 00:04:21.379 Amber Lin: I see that’s good. Let’s see.
27 00:04:23.189 ⇒ 00:04:37.249 Amber Lin: is there anything for the Pm team that we’re currently working on? I think all our clients are going pretty well of. Is there any initiatives for the Pm. Team that we wanted to push on? I just don’t remember
28 00:04:37.810 ⇒ 00:04:40.139 Aakash Tandel: Yeah, I
29 00:04:40.240 ⇒ 00:04:49.230 Aakash Tandel: not that I know of at the moment. I think I would like us to eventually start doing like status updates and stuff. But I mean
30 00:04:50.201 ⇒ 00:05:04.380 Aakash Tandel: I think the 1st thing we should probably work on is like road mapping. So make sure that we have good roadmaps for all of our clients we. So we know what’s coming like the big initiatives so the one that we have for
31 00:05:04.910 ⇒ 00:05:12.659 Aakash Tandel: Javi is only up until 2 weeks from now, I think.
32 00:05:12.860 ⇒ 00:05:16.460 Aakash Tandel: But let me send it to you. I don’t know if you’ve already seen this
33 00:05:22.980 ⇒ 00:05:24.520 Aakash Tandel: but this one’s already
34 00:05:28.990 ⇒ 00:05:31.501 Aakash Tandel: kind of in progress.
35 00:05:32.330 ⇒ 00:05:34.490 Aakash Tandel: So this one’s looking good.
36 00:05:38.100 ⇒ 00:05:40.059 Aakash Tandel: I don’t know if you ever would real open
37 00:06:26.760 ⇒ 00:06:28.440 Aakash Tandel: were you able to open the file
38 00:06:29.572 ⇒ 00:06:31.659 Amber Lin: Would let me see.
39 00:06:34.320 ⇒ 00:06:39.299 Amber Lin: Hmm, yes, yeah. I see that
40 00:06:39.820 ⇒ 00:06:44.189 Aakash Tandel: Cool. Yeah, I would like to get this, basically, for all of our clients kind of like
41 00:06:44.190 ⇒ 00:06:44.770 Amber Lin: Thank you.
42 00:06:44.770 ⇒ 00:06:45.500 Aakash Tandel: Air
43 00:06:45.660 ⇒ 00:06:57.800 Aakash Tandel: month, 2 month roadmap. I’m going to be working with Robert to get that same thing for Eden, and then we’ll go from there. But yeah, this is, I think, what we should have, basically for all the clients, you know.
44 00:06:57.990 ⇒ 00:07:00.240 Aakash Tandel: I think the total for this
45 00:07:03.390 ⇒ 00:07:04.360 Aakash Tandel: is
46 00:07:04.360 ⇒ 00:07:07.019 Amber Lin: Walk me through each column.
47 00:07:08.440 ⇒ 00:07:11.599 Aakash Tandel: Sure. So the effort is the actual work.
48 00:07:12.180 ⇒ 00:07:17.910 Aakash Tandel: Oh, yeah, good question.
49 00:07:18.350 ⇒ 00:07:19.669 Amber Lin: No no go ahead.
50 00:07:19.670 ⇒ 00:07:47.070 Aakash Tandel: Yeah, the type is gonna be either data analysis. So it’s gonna be analysts or engineering. We have the Max episode estimate, it should take we have the actuals after the works completed. So that’s being filled in timeline. If we have that available, that’s kind of what we are doing. Some of these don’t have timeline, because they’re like thoroughly blocked. So like this one’s pretty blocked.
51 00:07:47.280 ⇒ 00:07:52.885 Aakash Tandel: This one’s pretty blocked this one’s not really a thing.
52 00:07:53.830 ⇒ 00:07:58.090 Aakash Tandel: we have notes, and then we have the linear tickets for the linear tickets that’s available
53 00:07:58.990 ⇒ 00:08:00.090 Aakash Tandel: That’s basically it.
54 00:08:00.280 ⇒ 00:08:17.450 Amber Lin: I stay. Yeah, I think my question is, when I think of roadmap I think of oh, this is an initiative we’re working on. And down there we have different little projects. And down from a project we have different tickets, which essentially is the effort we have there. So my question is, how
55 00:08:18.050 ⇒ 00:08:47.260 Amber Lin: granular or how inclusive should the efforts be? Should I also note that this belongs to that project? Because for ABC. Maybe some of it is related to the rollout for the Csr boss. Some of this related to another bot which are separate projects of how are we gonna track that in the roadmap? Or is this just mostly? Is this more of a summary of tickets? Or is it more of a project breakdown like I? I just wanna understand that
56 00:08:47.530 ⇒ 00:08:59.030 Aakash Tandel: Yeah, it should be pretty high level. So a lot of these are like the beginning tickets of the thing. But there’s gonna be subsequent tickets related to it’s not going to be just one ticket for the whole, this whole effort. It’s gonna take multiple tickets. So
57 00:08:59.810 ⇒ 00:09:18.590 Aakash Tandel: Those aren’t fully representative of the stuff. And it’s just it’s a high level, like goal of like what we’re trying to do. So it’s not anything too detailed like here. It’s analyst handoff. So I don’t have all of the different tickets and all the different trainings we’re going to go through, but we just have the general idea of what they need here.
58 00:09:19.220 ⇒ 00:09:24.120 Amber Lin: I see so essentially, these are all projects, right?
59 00:09:24.730 ⇒ 00:09:26.000 Aakash Tandel: In linear.
60 00:09:26.170 ⇒ 00:09:30.879 Amber Lin: No like like these are all small projects on their own that we’re thinking of.
61 00:09:31.900 ⇒ 00:09:37.419 Amber Lin: I see. And maybe they have a project or a bigger ticket ticket with sub issues in linear.
62 00:09:37.590 ⇒ 00:09:40.519 Amber Lin: Okay, I see that makes that makes more sense.
63 00:09:40.770 ⇒ 00:09:47.590 Amber Lin: And then I know there’s another tab called Brainforge proposal. How are those different
64 00:09:47.770 ⇒ 00:09:50.100 Aakash Tandel: I don’t actually know what’s on this tab. I’m not sure
65 00:09:50.645 ⇒ 00:09:51.190 Amber Lin: Okay.
66 00:09:51.190 ⇒ 00:09:52.790 Aakash Tandel: Staggerty, Rhode Island. Yeah.
67 00:09:54.140 ⇒ 00:09:55.000 Amber Lin: I see
68 00:09:58.610 ⇒ 00:09:59.520 Amber Lin: cool.
69 00:09:59.740 ⇒ 00:10:06.409 Aakash Tandel: Alright, yeah, we don’t need a I’m assuming is busy. So it’s not a big deal. But yeah.
70 00:10:07.050 ⇒ 00:10:11.039 Amber Lin: Yeah, that’s all the questions I had on my side. I will. I think
71 00:10:11.250 ⇒ 00:10:18.209 Amber Lin: I’ll make a ticket in our project management part to create that for each client, and I will do that
72 00:10:21.230 ⇒ 00:10:25.070 Aakash Tandel: Yeah, that’s all from my side, sweet
73 00:10:25.290 ⇒ 00:10:28.449 Amber Lin: Hmm, okay. Thanks for meeting Ohio, Tom.
74 00:10:29.360 ⇒ 00:10:31.109 Uttam Kumaran: Hey, guys? Sorry for the delay.
75 00:10:31.550 ⇒ 00:10:41.190 Aakash Tandel: No worries. We just kind of went through kind of the projects. And I explain like the 1st thing I think we should have for all of our clients is the roadmap for what we’re doing next month or 2.
76 00:10:42.460 ⇒ 00:10:55.639 Aakash Tandel: So I’m basically gonna be creating that with Robert today and running it by our client tomorrow. So running by Josh tomorrow. So we’ve done that with Jabby. I think it’s been helpful just need to get the ball moving
77 00:10:56.580 ⇒ 00:11:08.490 Amber Lin: Let’s see, we kind of have this for the different class in notion. So do you want to keep it there, or should does this format help us track a little bit better?
78 00:11:08.750 ⇒ 00:11:16.600 Amber Lin: Or can we also have it in like, how is this different from linear? Or how is it different from notion
79 00:11:17.110 ⇒ 00:11:19.020 Amber Lin: of how we’re gonna use this
80 00:11:19.580 ⇒ 00:11:23.219 Aakash Tandel: Yeah, I don’t know if it’s already a notion, and if it is
81 00:11:23.630 ⇒ 00:11:28.291 Aakash Tandel: the Javi one is most up to date in the spreadsheet that we we went through just now.
82 00:11:28.740 ⇒ 00:11:29.420 Amber Lin: Okay.
83 00:11:30.261 ⇒ 00:11:33.279 Aakash Tandel: How is it different than linear linear is? Gonna be
84 00:11:33.770 ⇒ 00:11:44.279 Aakash Tandel: the individual tasks that need to be accomplished to fulfill the broader initiative? The roadmap should be like, Hey, we want Tiktok shop data
85 00:11:44.710 ⇒ 00:11:51.610 Aakash Tandel: working. And whatever right like that, that should be like the basic item in the roadmap and then the
86 00:11:52.060 ⇒ 00:12:00.109 Aakash Tandel: the linear tickets will be significantly more detailed, and they’ll be broken up into steps and stuff like that. So there’ll be a lot more detail there
87 00:12:00.630 ⇒ 00:12:01.909 Amber Lin: Okay, sounds good.
88 00:12:02.574 ⇒ 00:12:07.740 Amber Lin: And we want this for a month or 2 months. What’s the timeline for that?
89 00:12:08.240 ⇒ 00:12:18.940 Aakash Tandel: Yeah, I mean, I would say, like month is good. I would like to do 2 months. A 2 month roadmap for a lot of our clients, I think, would be awesome. I don’t know if we can get that deep that far out, but that would be great
90 00:12:19.527 ⇒ 00:12:25.100 Amber Lin: I see, okay, sounds good. I’ll make a ticket for myself, in our Pm, space
91 00:12:26.050 ⇒ 00:12:26.690 Aakash Tandel: Cool.
92 00:12:26.890 ⇒ 00:12:27.570 Amber Lin: Yeah, okay.
93 00:12:27.570 ⇒ 00:12:36.170 Uttam Kumaran: I guess a couple of things from my side. So one I saw like James is still working on stuff, can I? Can I? Can I give him a call today? Do we still need him
94 00:12:36.980 ⇒ 00:12:49.049 Aakash Tandel: Yeah, I I wasn’t sure if you had a conversation or not. Yeah, that I don’t know what’s taking as long as it’s taking. So I think at this point like
95 00:12:49.300 ⇒ 00:12:51.516 Aakash Tandel: that dashboard should be shipped.
96 00:12:52.300 ⇒ 00:12:54.130 Aakash Tandel: but it’s not so. I think
97 00:12:54.800 ⇒ 00:13:05.910 Aakash Tandel: we need to move that either to someone else to finish up or yeah, get Robert to. Maybe I don’t even know can I do something there? But yeah.
98 00:13:05.910 ⇒ 00:13:06.520 Uttam Kumaran: Cool.
99 00:13:06.520 ⇒ 00:13:07.750 Aakash Tandel: Yeah, that should be it. Ending
100 00:13:07.750 ⇒ 00:13:13.290 Uttam Kumaran: And then and then like, how did it go with like time? Allocation, and stuff, I mean
101 00:13:13.520 ⇒ 00:13:25.040 Uttam Kumaran: like, are people respecting that? Do you know, if like, that’s fine, the kind of the my biggest concern is that like I, I just went through and looked at basically all expenses for past 2 months.
102 00:13:25.180 ⇒ 00:13:34.869 Uttam Kumaran: So I just want to confirm that we’re basically whatever we did on last week to just set allocations like people are adhering to that, not billing more hours
103 00:13:35.530 ⇒ 00:13:42.109 Aakash Tandel: Yeah, I guess we don’t. We haven’t done like a reconciliation on that. I don’t know if there’s a way we can
104 00:13:43.080 ⇒ 00:13:44.830 Aakash Tandel: automate that
105 00:13:45.040 ⇒ 00:13:45.720 Uttam Kumaran: Okay.
106 00:13:46.880 ⇒ 00:13:55.120 Uttam Kumaran: yeah, I guess my point is that like, are you guys seeing that slow like, you should be seeing it in like, slow down, or
107 00:13:55.260 ⇒ 00:14:05.369 Uttam Kumaran: sort of like, what do we like short term before that like? Where can we see that? I mean, I can. I can send you or show you and clockify where you can go. Look at your team’s hours
108 00:14:06.050 ⇒ 00:14:07.550 Uttam Kumaran: as it’s being booked
109 00:14:07.550 ⇒ 00:14:32.640 Amber Lin: Yeah, I think we know where to look. I don’t. I haven’t been looking at it yet. I think I just made a ticket to remind myself to do that. I think daily. If we look at it, clock, if I’ll be a good measure, and then weekly to have that reconciliation meeting at the end to say, Hey, this is how much it worked on this week. That’s it. And this is what we agreed on
110 00:14:34.580 ⇒ 00:14:37.119 Aakash Tandel: Yeah, we’re not gonna be able to look at this daily. That’s gonna be way too much
111 00:14:37.120 ⇒ 00:14:37.670 Uttam Kumaran: Yeah.
112 00:14:37.670 ⇒ 00:14:39.200 Amber Lin: I see then how
113 00:14:39.200 ⇒ 00:14:40.479 Uttam Kumaran: Yeah. Weekly is fine.
114 00:14:40.983 ⇒ 00:14:41.990 Amber Lin: I see.
115 00:14:42.900 ⇒ 00:15:03.630 Amber Lin: And I also answered this question from Annie, and she was asking, Hey, did do I still need to track my time. If I’m full time, it’s like, Yes, it helps in different things. And I and would I would really like our Ops team to announce that in the main channel of giving some guidelines into how to track time.
116 00:15:04.090 ⇒ 00:15:07.240 Amber Lin: Because I think it’s a company wide thing, not just
117 00:15:07.240 ⇒ 00:15:09.186 Uttam Kumaran: Can you just ping them to do that?
118 00:15:10.240 ⇒ 00:15:20.020 Uttam Kumaran: yeah, if there’s still people asking, you guys just direct, just tell the Ops team that like they have to announce something, or send something about how to track time and clock. If they have all the documentation
119 00:15:20.130 ⇒ 00:15:21.550 Uttam Kumaran: and stuff like that
120 00:15:21.920 ⇒ 00:15:23.489 Amber Lin: Okay, let me send that message.
121 00:15:23.490 ⇒ 00:15:26.920 Uttam Kumaran: Yeah, I would just like I would literally just directly send it to them.
122 00:15:27.450 ⇒ 00:15:30.549 Uttam Kumaran: Like on. I would just send it to them directly in the operations channel
123 00:15:30.550 ⇒ 00:15:30.930 Amber Lin: Yeah.
124 00:15:30.930 ⇒ 00:15:33.790 Uttam Kumaran: Just tell them what you need. Yeah, don’t hesitate
125 00:15:35.680 ⇒ 00:15:41.050 Aakash Tandel: Yeah, maybe there’s also a thing that they can generate
126 00:15:41.280 ⇒ 00:15:43.689 Aakash Tandel: from clock if I cause right now I’m
127 00:15:43.870 ⇒ 00:15:47.080 Aakash Tandel: how do I aggregate? Maybe let me just share my screen. Maybe
128 00:15:53.770 ⇒ 00:15:58.409 Uttam Kumaran: Yeah. So if you go to like, I think if you go to like Summary or something, and then you
129 00:15:58.550 ⇒ 00:16:03.010 Uttam Kumaran: you can filter to just the project that whatever?
130 00:16:04.360 ⇒ 00:16:06.450 Uttam Kumaran: yeah, you filter to just the client
131 00:16:06.770 ⇒ 00:16:10.870 Uttam Kumaran: that you want, and then you can do detailed, and you’ll see the people
132 00:16:11.700 ⇒ 00:16:16.980 Uttam Kumaran: or or yeah. So this so detail will give you all the times. If you go to back to summary
133 00:16:19.260 ⇒ 00:16:23.459 Uttam Kumaran: underneath group by, you’ll also be able to group by person
134 00:16:23.860 ⇒ 00:16:26.079 Amber Lin: It’s towards the bottom left
135 00:16:28.500 ⇒ 00:16:29.579 Uttam Kumaran: Thank you.
136 00:16:29.930 ⇒ 00:16:30.820 Uttam Kumaran: Yeah.
137 00:16:32.620 ⇒ 00:16:38.130 Aakash Tandel: Okay, perfect. Okay, this is what I was looking for. Okay, yeah, this is something we should probably
138 00:16:38.290 ⇒ 00:16:43.099 Aakash Tandel: look. This is, I think, the view that we need weekly to say, Hey, you know.
139 00:16:43.450 ⇒ 00:16:48.399 Aakash Tandel: last week we and I guess. Is there a place in like operating
140 00:16:49.790 ⇒ 00:17:19.650 Uttam Kumaran: Yeah. So we’re gonna we’re gonna start to bring this into operating where basically, we’ll be able to see the differences like in what we did this this week first, st last week. But I think roughly, for just their clients to just have in your head, like, okay, we we roughly have, like 20 weeks, or we roughly have 20 h. Or if you have 40 h, and basically, I think just looking at that view and matching it towards the messages you guys sent before. It’s probably the best way. I think in a few weeks we’ll have it. So we’ll get a report out, basically on a weekly basis.
141 00:17:20.099 ⇒ 00:17:25.079 Aakash Tandel: Okay, that sounds good. Yeah, I think, for now I guess we’ll just have to stick with
142 00:17:27.039 ⇒ 00:17:29.289 Aakash Tandel: like, yeah, reconciling the 2
143 00:17:29.659 ⇒ 00:17:35.749 Aakash Tandel: like visually. And then, yeah, eventually, we can automate that. Okay, that sounds good. Why is this? Okay?
144 00:17:35.750 ⇒ 00:17:44.300 Uttam Kumaran: Yeah. So so for me, like what I’ll try to look at, or maybe we could do this on Fridays is we just go through and look to see. Okay, what did everyone, Bill? And
145 00:17:44.460 ⇒ 00:17:46.930 Uttam Kumaran: and is it in line with what we expect?
146 00:17:47.310 ⇒ 00:17:50.240 Uttam Kumaran: Okay.
147 00:17:50.910 ⇒ 00:17:54.550 Aakash Tandel: Well, maybe we should put like a little slack bot or something together to
148 00:17:55.090 ⇒ 00:17:57.673 Amber Lin: Oh, that would be helpful.
149 00:17:58.860 ⇒ 00:18:01.949 Uttam Kumaran: Yeah, just to like remind people to do that. Yeah.
150 00:18:03.570 ⇒ 00:18:10.139 Aakash Tandel: Okay, that sounds good. I will do the numbers match just
151 00:18:10.140 ⇒ 00:18:24.330 Uttam Kumaran: Poke. Yeah, just poke around at it just for the 2, and then just we can all chat in our channel about like what we see I think same thing, probably amber. You could just take a look at your clients, filter, and just just look at what everybody’s billing, and then
152 00:18:24.756 ⇒ 00:18:35.429 Uttam Kumaran: again. We just wanna make sure it’s in line with what we expect. The other thing I’ll start probably being more as we sort of as we get better at tracking kind of a couple of things. So one
153 00:18:35.830 ⇒ 00:18:45.709 Uttam Kumaran: we’ll be able to flag any we’ll be able to flag any times that don’t have like a description, basically, or any like long blocks of time, like, basically, any time that’s like
154 00:18:45.920 ⇒ 00:18:48.000 Uttam Kumaran: more than 4 h
155 00:18:48.420 ⇒ 00:18:48.809 Amber Lin: That’s just like
156 00:18:48.810 ⇒ 00:18:54.575 Uttam Kumaran: One block. I probably will flag as like, Hey, this needs to be broken down.
157 00:18:55.280 ⇒ 00:19:09.040 Uttam Kumaran: so that’s 1 piece. And then, yeah, I’m I’m basically just getting a little bit tighter on looking at everybody’s expenses. The other piece I have is like, sort of thinking through how we’re gonna leverage, Annie, I mean, basically, I want Annie to start taking on any.
158 00:19:09.290 ⇒ 00:19:25.089 Uttam Kumaran: Basically, all analysts related tasks on Eden and and Javi and as well as on ABC, so I guess, like, how do you guys feel about that like? And how far away from that are we
159 00:19:26.270 ⇒ 00:19:49.200 Amber Lin: Well, well, we’re meeting with ABC Internal, so she will learn about her tasks more during that meeting. I don’t know how much task there are is sounds more like a 1 time thing, because we also have their internal analysts so they can do some work as well. So I think ABC is gonna be not that heavy for every for Annie. But we’ll need to make sure
160 00:19:50.110 ⇒ 00:19:56.439 Uttam Kumaran: Yeah, I mean, basically on ABC side, like anything data related should go through her like, I don’t want Casey to work on
161 00:19:56.800 ⇒ 00:19:59.540 Uttam Kumaran: sports, or she should take all the real work
162 00:19:59.830 ⇒ 00:20:06.429 Uttam Kumaran: so that there’s no current like. There’s no existing real work right now until, like probably after this meeting, right
163 00:20:08.570 ⇒ 00:20:30.559 Amber Lin: yeah, I gave her a task because I asked her, do you know how real works she’s like? No so I asked her to at least set it up on her desktop. No, go through some tutorials and know how it works. And then I asked her to specifically look at the canvas, because I think that’s something we want for the client as well. Right
164 00:20:31.650 ⇒ 00:20:39.530 Uttam Kumaran: Yeah, I mean. And and even for that, like, you should time box those things. So otherwise she’s gonna spend 3 days and like.
165 00:20:39.740 ⇒ 00:20:45.959 Uttam Kumaran: however, much time just doing that. So this is where I was like learning how to do something is not
166 00:20:46.010 ⇒ 00:21:05.189 Uttam Kumaran: a great ticket like it’s it needs to have a end date. So whether it’s like you can either learn by saying, Hey, go, take this task, and while you’re doing it, learn the tool, or you have to. You have to give her an assignment right? This is the same problem we had with Kaya, where, if you just people, they’re Gonna say, oh, I need time to learn this. That’s not. That’s like an open, ended thing.
167 00:21:05.210 ⇒ 00:21:23.610 Uttam Kumaran: So you can spend your whole life like learning the things. So what I would suggest is, you give her a task, and while she executes that task there will be a time where she has to learn the tool, and the task will take longer, but as long as it’s attached to some deliverable, open-ended learning, things
168 00:21:23.610 ⇒ 00:21:23.960 Amber Lin: Okay.
169 00:21:23.960 ⇒ 00:21:25.530 Uttam Kumaran: It’s gonna be too hard
170 00:21:25.530 ⇒ 00:21:29.019 Amber Lin: I will ask her to do a real canvas for ABC data
171 00:21:29.270 ⇒ 00:21:39.950 Uttam Kumaran: Okay, perfect. Yeah. And then just just say, like, have something ready by. Just just ask her to agree on a date, and then you can tell her. Like to go meet with Casey. She can go meet with anybody on the data team
172 00:21:39.950 ⇒ 00:21:44.120 Amber Lin: Yeah, I put a also a ticket for her to book a call with Casey
173 00:21:44.690 ⇒ 00:21:57.569 Uttam Kumaran: Okay, perfect. Yeah. So that’s a perfect way, because engineers will do this where they’ll be like, I need to go learn this thing. But we learned from the Kyle example, which is like, can’t we? Can’t let anything be open ended like tasks will take.
174 00:21:57.880 ⇒ 00:22:18.830 Uttam Kumaran: The principle for me is like tasks will take up the volume of time you give it. So, even if you said a week, it would take a week. If you said 2 days, it’ll take 2 days. So set. Try to set a due date for every single item that we do and like really try to push on, making sure that things get done. You know.
175 00:22:19.540 ⇒ 00:22:29.450 Uttam Kumaran: And then. So I guess, for for Eden and Javi do we like? Do we feel like she can start taking on more stuff there and take stuff off Sahana’s plate. Basically
176 00:22:29.610 ⇒ 00:22:36.640 Aakash Tandel: Yeah, that’s what I was Gonna ask, is the idea to take tasks off of Sahana’s plate? Is that the primary
177 00:22:36.950 ⇒ 00:22:37.760 Uttam Kumaran: Yes.
178 00:22:38.030 ⇒ 00:22:39.376 Aakash Tandel: Okay. Yeah.
179 00:22:41.050 ⇒ 00:22:55.790 Uttam Kumaran: I mean, there’s kind of 2 things here. So one is like, I want her to start taking items herself. There may be a transition period. So I’ll let you sort of decide like what is best. But I want her to start to take
180 00:22:55.910 ⇒ 00:23:00.709 Uttam Kumaran: take items off of Sahana’s plate, or basically they, they start to split the workload
181 00:23:01.063 ⇒ 00:23:30.009 Uttam Kumaran: and then I ideally like a majority of tasks, go to her. And you can let if there’s questions from Sahana about like, what am I working on? Blah blah! You can direct all that to me. Don’t worry about that. But for you I would say the directive is to try to. I want Annie to sort of be lead analyst there, on that and on on Javi. I would say. Robert is probably the one on Javi who’s taking on a lot of stuff so ideally hit any of his work can go to to Annie. And similarly, so.
182 00:23:30.452 ⇒ 00:23:38.339 Uttam Kumaran: yeah, I think that’s that’s the goal. And so that’s sort of what I want to start to see is that her time is basically fully booked with between those
183 00:23:38.460 ⇒ 00:23:40.095 Uttam Kumaran: those 3 clients.
184 00:23:40.640 ⇒ 00:23:50.130 Aakash Tandel: Yeah, yeah, I think the joby and Ian, we’re coming up against the thing where I think, like the Institutional knowledge people mostly. Robert in a waysh are
185 00:23:50.260 ⇒ 00:24:01.060 Aakash Tandel: over utilized and everyone else under utilized, because no one else has the full context of stuff. So it always comes back. Those 2 people. So I’m
186 00:24:01.360 ⇒ 00:24:10.999 Aakash Tandel: trying to figure out a way around that by like getting Annie to do the trainings that you know. If she has to teach the dashboards hopefully, she’ll
187 00:24:11.000 ⇒ 00:24:11.840 Uttam Kumaran: Yes.
188 00:24:11.840 ⇒ 00:24:14.959 Aakash Tandel: And see. Oh, yeah, I don’t know this. I’ll ask the question
189 00:24:14.960 ⇒ 00:24:15.480 Uttam Kumaran: Yes.
190 00:24:15.480 ⇒ 00:24:31.770 Aakash Tandel: There’s other things like that with like Demo a day. I’m giving him a lot of tasks that are touching different pieces, so that maybe he’ll go, and like he’ll ask away about Hey, Xyz but we’re still at a point where, like Robert and a waste are still like so pivotal to both those projects that they
191 00:24:34.180 ⇒ 00:24:40.480 Uttam Kumaran: So that makes sense. I mean the the one suggestion I have is there’s there can be a difference in who’s like primary versus
192 00:24:40.610 ⇒ 00:24:55.409 Uttam Kumaran: who is secondary, right? So there will be some stuff where it’s like this needs to get done tomorrow, sure. But for all other tasks I would. And and again, Robert, and await. They may push back on this, but Annie and Dev a lot of should be primary, and they can go get help.
193 00:24:55.490 ⇒ 00:25:16.409 Uttam Kumaran: but ultimately they should own the deliverable and and understanding. Otherwise, there’s no way there’s just gonna be. We’re gonna be in the same spot next month. So you just have to force it, you just have to say, and he’s gonna take this if it we can afford for this to take twice as long or or whatever 50% longer, and
194 00:25:16.740 ⇒ 00:25:31.620 Uttam Kumaran: and then she she owns the ultimate deliverable as long as the things are clear, and then then she can start to gain that. It just has to be a hard cut on some of the items. You know, it’s otherwise. It’s gonna be very, very hard for us to start to separate people.
195 00:25:32.340 ⇒ 00:25:32.890 Aakash Tandel: Yeah.
196 00:25:34.455 ⇒ 00:25:35.250 Uttam Kumaran: Okay.
197 00:25:36.050 ⇒ 00:25:36.645 Uttam Kumaran: Alright.
198 00:25:37.640 ⇒ 00:25:38.120 Uttam Kumaran: Okay.
199 00:25:38.120 ⇒ 00:25:39.140 Aakash Tandel: So cool.
200 00:25:39.620 ⇒ 00:25:40.230 Uttam Kumaran: That’s all I had
201 00:25:41.050 ⇒ 00:25:50.019 Aakash Tandel: Cool. I oops. I’m not sure this don’t not share trying to share this with you guys
202 00:25:52.440 ⇒ 00:25:59.430 Aakash Tandel: and add, you guys, I know we’re dumping.
203 00:26:03.760 ⇒ 00:26:08.680 Aakash Tandel: I’m gonna I I can produce the 1st like version of this goddammit.
204 00:26:09.740 ⇒ 00:26:10.950 Aakash Tandel: So many tabs
205 00:26:11.650 ⇒ 00:26:18.260 Aakash Tandel: of this spreadsheet to do like reconciliation. I just threw at the bottom. I threw tabs for Jabby Eden.
206 00:26:18.689 ⇒ 00:26:23.949 Aakash Tandel: We want do one for ABC. I’ll work on the format and then we can.
207 00:26:26.010 ⇒ 00:26:29.029 Aakash Tandel: Oh, yep. I worked on Eden. First, st that’s fine. Okay.
208 00:26:29.030 ⇒ 00:26:29.750 Amber Lin: Yeah, guys, I will
209 00:26:30.350 ⇒ 00:26:48.839 Amber Lin: show something that we did with the cause. I’m creating a documentation to onboard, Annie, and our ABC bot that we our team made is so helpful. I essentially passed our Pm. Onboarding document to it with all the questions, and then it gave me
210 00:26:49.700 ⇒ 00:26:58.249 Amber Lin: almost all the answers I need. So I didn’t have to write this. I didn’t even have to speak to it. I passed it through the bot.
211 00:26:58.780 ⇒ 00:27:02.359 Amber Lin: and then they gave all the answers.
212 00:27:02.490 ⇒ 00:27:04.609 Amber Lin: and they’re pretty much accurate and up to date.
213 00:27:05.830 ⇒ 00:27:06.510 Amber Lin: So I
214 00:27:06.510 ⇒ 00:27:07.050 Uttam Kumaran: Nice
215 00:27:07.050 ⇒ 00:27:14.380 Amber Lin: Really recommend us having this for especially the clients that struggling, or we have new people.
216 00:27:14.710 ⇒ 00:27:17.349 Amber Lin: because that’s all we, that’s all we needed, and
217 00:27:17.350 ⇒ 00:27:27.489 Uttam Kumaran: I mean so. But then this is where it’s like. If you see it, then you should just tell the team to start pinging the Javi Bot, but I guess this is part of the AI steam thing is, many people don’t know that this exists
218 00:27:27.640 ⇒ 00:27:28.730 Amber Lin: Yeah, I will put
219 00:27:28.730 ⇒ 00:27:29.350 Uttam Kumaran: Awesome.
220 00:27:29.350 ⇒ 00:27:33.539 Amber Lin: I’ll post this in our Brainforge team, I’ll say like, this is what the bot did
221 00:27:34.510 ⇒ 00:27:38.929 Uttam Kumaran: Yeah, I think even one step further is, you probably just need to
222 00:27:39.250 ⇒ 00:27:53.690 Uttam Kumaran: like either. We we could do this on Friday. But like every team needs to know that this is available like. So that that’s the thing. I don’t know whether the Javi bot and all the different client bots are this good. So
223 00:27:53.920 ⇒ 00:27:55.979 Amber Lin: We only have Joby and ABC.
224 00:27:56.380 ⇒ 00:28:02.920 Uttam Kumaran: So, yeah, but is, I don’t know whether the Javi bot is this good? Because if people try it and it’s not, it doesn’t give the answer. Then they’re gonna
225 00:28:03.320 ⇒ 00:28:05.539 Uttam Kumaran: they’re never going to use it again. So
226 00:28:06.010 ⇒ 00:28:10.889 Uttam Kumaran: I would wait until you’re confident that it’s actually gonna work for whatever they need to do
227 00:28:13.280 ⇒ 00:28:20.499 Uttam Kumaran: That’d be my perspective. Because if people tried, and it’s like, not good enough, or it hallucinates, then they may not use it again.
228 00:28:21.360 ⇒ 00:28:22.170 Uttam Kumaran: Yeah, okay.
229 00:28:22.170 ⇒ 00:28:31.369 Uttam Kumaran: We tried to push it. Once we send a message, I think people are trying it here and there, but even for me, I’m not confident. It’s like 100 works for most use cases. So
230 00:28:31.770 ⇒ 00:28:37.270 Uttam Kumaran: I think this is something to ask the data team, or whoever you all are partnering with there on how we can promote this
231 00:28:37.270 ⇒ 00:28:40.420 Amber Lin: Yeah, that’s a that’s that’s essentially
232 00:28:40.550 ⇒ 00:28:43.539 Amber Lin: metrics. Right? That’s what we’re doing for the ABC team. So
233 00:28:43.540 ⇒ 00:28:44.270 Uttam Kumaran: Yes.
234 00:28:44.270 ⇒ 00:28:51.709 Amber Lin: Errors and getting testing data to get it more accurate. I think that’s that’ll just be something on the AI team’s backlog
235 00:28:51.710 ⇒ 00:28:55.680 Uttam Kumaran: Yeah, exactly like ideally, you guys should build another an Eval set
236 00:28:56.220 ⇒ 00:29:04.470 Uttam Kumaran: And work with whoever to get those what those questions are. And then we can basically make sure that at any moment the bot is able to answer it.
237 00:29:06.810 ⇒ 00:29:07.759 Uttam Kumaran: you know.
238 00:29:10.530 ⇒ 00:29:14.360 Amber Lin: With sample questions to verify.
239 00:29:17.440 ⇒ 00:29:19.170 Amber Lin: Yeah, right?
240 00:29:19.900 ⇒ 00:29:22.309 Amber Lin: I will put that in our backlog
241 00:29:23.170 ⇒ 00:29:23.880 Uttam Kumaran: Okay.
242 00:29:28.160 ⇒ 00:29:29.120 Aakash Tandel: How are y’all
243 00:29:30.070 ⇒ 00:29:32.460 Uttam Kumaran: Thanks for the meeting. Okay, thank you.
244 00:29:32.600 ⇒ 00:29:33.000 Amber Lin: Bye, bye.
245 00:29:33.000 ⇒ 00:29:33.530 Aakash Tandel: Deal