Meeting Title: ABC | backlog grooming Date: 2025-08-20 Meeting participants: Casie Aviles, Mustafa Raja, Awaish Kumar, Amber Lin, Uttam Kumaran
WEBVTT
1 00:00:34.880 ⇒ 00:00:35.890 Mustafa Raja: Agency.
2 00:00:37.060 ⇒ 00:00:38.939 Casie Aviles: Hey, hey, how are you?
3 00:00:38.940 ⇒ 00:00:40.390 Mustafa Raja: Yeah, doing good, how are you?
4 00:00:42.260 ⇒ 00:00:45.889 Casie Aviles: Yeah, I’m just, … Thinking about the spike.
5 00:00:46.810 ⇒ 00:00:49.480 Mustafa Raja: No, for the automation one.
6 00:00:50.890 ⇒ 00:00:57.229 Casie Aviles: Yeah, yeah, for migrating… the spreadsheet to take it to Superbase, yeah.
7 00:00:57.230 ⇒ 00:01:03.000 Mustafa Raja: Oh, the other one… I thought you were talking about the insomnia one.
8 00:01:04.069 ⇒ 00:01:07.209 Casie Aviles: Oh, no, no, for ABC, for the ABC, I mean.
9 00:01:10.629 ⇒ 00:01:13.099 Casie Aviles: No, this is… this is ABC Grooming, right?
10 00:01:14.159 ⇒ 00:01:15.419 Casie Aviles: Yeah, I’ll be.
11 00:01:29.270 ⇒ 00:01:30.250 Amber Lin: Hello.
12 00:01:30.640 ⇒ 00:01:37.739 Amber Lin: Do we want everybody in this meeting? Thinking if someone needs some development work.
13 00:01:42.390 ⇒ 00:01:44.340 Uttam Kumaran: Who are we missing?
14 00:01:45.060 ⇒ 00:01:56.979 Amber Lin: I invited Sam, but it was a little bit last minute. I was thinking, because Mustafa’s not really… he’s mostly working on interlude and Default, maybe you can give me stuff time?
15 00:01:56.980 ⇒ 00:02:00.299 Uttam Kumaran: Yeah, that’s probably fine. I think as long as me…
16 00:02:00.560 ⇒ 00:02:03.129 Uttam Kumaran: and Casey are here, that’s probably fine.
17 00:02:04.010 ⇒ 00:02:08.460 Amber Lin: So, should Awish pop as well?
18 00:02:10.370 ⇒ 00:02:13.600 Uttam Kumaran: Yeah, up to him. I mean… Yeah, it’s….
19 00:02:13.600 ⇒ 00:02:18.489 Amber Lin: Okay. I mean, Utah, you’re already here, so I think we’ll be… we’ll be fine.
20 00:02:18.870 ⇒ 00:02:22.399 Uttam Kumaran: Okay, okay. Yeah, you guys can hop or stay and listen, whatever.
21 00:02:25.600 ⇒ 00:02:27.350 Amber Lin: Alright, getting started.
22 00:02:36.450 ⇒ 00:02:45.629 Amber Lin: So, just to quickly look over this, and then to have a few discussion points, I think right now, our current efforts are mostly…
23 00:02:45.880 ⇒ 00:03:02.720 Amber Lin: These are the triages. So, up to here, I’ve sent the instructions to these two departments, Lawn and Home Improvement. I think they’re working on creating the central dock right now, and once they do that, we can connect that to NIN and start testing.
24 00:03:02.880 ⇒ 00:03:06.509 Amber Lin: So, that’s, that’s in progress.
25 00:03:06.730 ⇒ 00:03:07.910 Amber Lin: And then…
26 00:03:08.500 ⇒ 00:03:27.610 Amber Lin: I think a big effort we’re doing now is to turn the spreadsheets into a database, and then eventually automate how the service managers update, say, the inspectors, technicians, automate that update process so that we can take Janice and Yvette out of the loop. That’s one of the main things.
27 00:03:27.950 ⇒ 00:03:31.810 Amber Lin: I think the second thing is the…
28 00:03:31.960 ⇒ 00:03:45.550 Amber Lin: AI, features, and also that we… we want to create a non-Google chat UI, and I know we just have a… we have a project plan for that already.
29 00:03:46.320 ⇒ 00:03:53.040 Amber Lin: On the other parts are more of adjustments we need to make based on the feedback.
30 00:03:53.200 ⇒ 00:04:01.149 Amber Lin: And then we should talk about that process, and so that Casey doesn’t have to spend most of his day on this.
31 00:04:04.370 ⇒ 00:04:04.930 Uttam Kumaran: Okay?
32 00:04:05.580 ⇒ 00:04:08.760 Amber Lin: Yeah, I think we can start, since…
33 00:04:09.770 ⇒ 00:04:14.959 Amber Lin: Casey, do we have a technical design document for the….
34 00:04:15.100 ⇒ 00:04:21.769 Casie Aviles: We have a… it’s not a TDD, it’s just a spike, really, so… I do have…
35 00:04:22.040 ⇒ 00:04:26.909 Casie Aviles: the Notion doc, I linked it to our thread, and it’s also in the ticket.
36 00:04:26.910 ⇒ 00:04:28.210 Amber Lin: Okay.
37 00:04:30.830 ⇒ 00:04:32.910 Casie Aviles: Yeah, it’s… yeah, it’s that one.
38 00:04:35.420 ⇒ 00:04:39.799 Amber Lin: Alright, actually, do you want to share a screen and walk us through it so we can talk.
39 00:04:39.800 ⇒ 00:04:42.090 Casie Aviles: Yeah, yeah, yeah, I can, I can share.
40 00:04:42.090 ⇒ 00:04:42.830 Amber Lin: Awesome.
41 00:04:46.010 ⇒ 00:04:47.220 Casie Aviles: Let me just….
42 00:04:51.380 ⇒ 00:04:52.630 Amber Lin: Welcome back, welcome back.
43 00:04:54.570 ⇒ 00:04:55.500 Casie Aviles: This one.
44 00:04:58.260 ⇒ 00:05:04.589 Casie Aviles: Alright, so basically the problem… so I’ll start with the problem.
45 00:05:05.410 ⇒ 00:05:12.040 Casie Aviles: Currently, we have multiple spreadsheets that we are adding into the AI’s context, so we have
46 00:05:12.540 ⇒ 00:05:15.110 Casie Aviles: the Master Inspector Sheet, we have…
47 00:05:15.920 ⇒ 00:05:19.149 Casie Aviles: Skills in zips, and we have the service areas.
48 00:05:20.940 ⇒ 00:05:28.909 Casie Aviles: Right now, one of the things that we’ve been… we’ve noticed is, you know, how we could keep this up to date. It’s very error-prone, you know, …
49 00:05:29.820 ⇒ 00:05:37.490 Casie Aviles: And so, our efforts to resolve that was to have it consolidated as a… Master Inspector Sheet.
50 00:05:38.730 ⇒ 00:05:45.879 Casie Aviles: But then we are also thinking if we have… if it would be better if we would migrate that into a database.
51 00:05:47.900 ⇒ 00:05:50.430 Casie Aviles: So, yeah, right now I’ve, I’ve, …
52 00:05:50.780 ⇒ 00:05:56.939 Casie Aviles: I’ve indicated here that the sheets currently are, you know, the formatting is not standardized.
53 00:05:57.050 ⇒ 00:05:59.399 Casie Aviles: We use lots of formulas.
54 00:05:59.660 ⇒ 00:06:01.669 Casie Aviles: To pull data into a master sheet.
55 00:06:03.760 ⇒ 00:06:06.860 Casie Aviles: And yeah, there’s, like, a lot of errors that could happen.
56 00:06:06.970 ⇒ 00:06:13.660 Casie Aviles: And ideally, we want to have just one source of truth, and that would be the database, which should reduce, like, you know, …
57 00:06:13.790 ⇒ 00:06:20.559 Casie Aviles: It should make it less messy and have, you know, stricter data validation, because there we can
58 00:06:20.690 ⇒ 00:06:25.099 Casie Aviles: We can… we have to type all the data that we insert there.
59 00:06:27.600 ⇒ 00:06:33.250 Casie Aviles: So another thing that I’ve… Checked out was…
60 00:06:33.400 ⇒ 00:06:36.090 Casie Aviles: Once we have the data there in…
61 00:06:36.960 ⇒ 00:06:39.350 Casie Aviles: Superbase, how do we query that?
62 00:06:40.860 ⇒ 00:06:46.080 Casie Aviles: And currently, we are just querying it… querying the spreadsheet directly.
63 00:06:47.530 ⇒ 00:06:56.380 Casie Aviles: This works mostly for just, zip code-related queries, like, who’s the inspector for 7123, something like that.
64 00:06:56.920 ⇒ 00:07:05.280 Casie Aviles: But, it’s not very… I don’t think that Google Streets is built for… … you know, …
65 00:07:05.600 ⇒ 00:07:13.080 Casie Aviles: For clearing, like… a table… a database table would still be ideal, so we could run, like, SQL queries.
66 00:07:13.240 ⇒ 00:07:20.090 Casie Aviles: So, my idea is to leverage something like, text to SQL querying agent.
67 00:07:23.080 ⇒ 00:07:29.270 Casie Aviles: Yeah, and then we could… we could implement that via Python using LamChain, or… Gamma index.
68 00:07:31.820 ⇒ 00:07:38.340 Casie Aviles: Yeah, and then I also listed some pros and cons here, and then I have a Python notebook and a Loom video showing
69 00:07:38.650 ⇒ 00:07:39.740 Casie Aviles: How it work.
70 00:07:40.360 ⇒ 00:07:43.439 Casie Aviles: How it could potentially work, once we have, like, the data.
71 00:07:44.300 ⇒ 00:07:46.060 Uttam Kumaran: In a database?
72 00:07:46.760 ⇒ 00:07:49.799 Casie Aviles: And so far, I think it works pretty well.
73 00:07:52.520 ⇒ 00:07:55.820 Casie Aviles: Yeah, so this basically lets us move away from
74 00:07:55.920 ⇒ 00:07:59.690 Casie Aviles: Google Spreadsheet. We’re able to do more complex queries.
75 00:08:00.250 ⇒ 00:08:01.430 Casie Aviles: And, yeah.
76 00:08:02.730 ⇒ 00:08:08.219 Casie Aviles: So, for, the updates, For automating the updates.
77 00:08:08.970 ⇒ 00:08:18.779 Casie Aviles: Some of the ideas that were floated was… using forms, although… I think… The issue there is…
78 00:08:19.940 ⇒ 00:08:24.089 Casie Aviles: with Google Forms, I mean, it’s, like, just a couple of fields.
79 00:08:24.190 ⇒ 00:08:31.320 Casie Aviles: And I guess maybe we could use… we could… it could work for, like, single edits, but what if we have to do, like, multiple edits?
80 00:08:32.270 ⇒ 00:08:33.959 Casie Aviles: Or, like, bulk edits.
81 00:08:34.510 ⇒ 00:08:37.250 Amber Lin: So, I don’t think that that would be the best.
82 00:08:37.330 ⇒ 00:08:38.260 Casie Aviles: Wei…
83 00:08:42.299 ⇒ 00:08:49.519 Casie Aviles: That… that part is actually still not super clear to me, like, how would the CSRs.
84 00:08:49.680 ⇒ 00:08:52.390 Amber Lin: Prefer updating it, like….
85 00:08:52.700 ⇒ 00:08:56.050 Casie Aviles: Because currently what they do is they update it
86 00:08:56.370 ⇒ 00:09:02.919 Casie Aviles: they update the spreadsheets, so that’s part of the options that I have indicated here, which is like a…
87 00:09:03.180 ⇒ 00:09:04.640 Casie Aviles: hybrid option.
88 00:09:05.110 ⇒ 00:09:06.090 Casie Aviles: Where…
89 00:09:06.440 ⇒ 00:09:16.029 Casie Aviles: similar to how we handle the central dock, where it’s… that’s where they make all the edits, right? The central dock. We basically have a script to…
90 00:09:16.350 ⇒ 00:09:24.130 Casie Aviles: or, like, I believe an NATN workflow that listens to updates being made on that file, and then it
91 00:09:25.010 ⇒ 00:09:28.339 Casie Aviles: syncs the database… the superbase table.
92 00:09:30.020 ⇒ 00:09:30.650 Amber Lin: That’s….
93 00:09:30.650 ⇒ 00:09:38.090 Casie Aviles: how… I believe we could also approach this, where we have, like, a spreadsheet Pass…
94 00:09:38.970 ⇒ 00:09:45.030 Casie Aviles: as just the UI for them to edit, and then we could sync it to Superbase.
95 00:09:47.810 ⇒ 00:09:53.280 Casie Aviles: Yeah, so I think that’s pretty much the gist of the spike that I have right now.
96 00:09:54.320 ⇒ 00:10:01.789 Casie Aviles: Yeah, I would love to get some feedback here, and if there are any things that I missed, or any potential issues with
97 00:10:03.950 ⇒ 00:10:06.860 Casie Aviles: Oh, I’m thinking of approaching this.
98 00:10:08.900 ⇒ 00:10:09.450 Uttam Kumaran: Okay.
99 00:10:10.160 ⇒ 00:10:20.750 Amber Lin: Utem, I’ll let you comment on the database set. I think for the updates automation, just an extra piece of information. When they get updates, so the service managers.
100 00:10:20.950 ⇒ 00:10:36.330 Amber Lin: update Yvette and Janice, say, hey, there’s this inspector, let’s add them from… and these zip codes, and they give a list of zip codes, and Yvette and Janice right now has to go into spreadsheets and manually find each one.
101 00:10:36.360 ⇒ 00:10:54.840 Amber Lin: So I’ve asked them to share the Google Form with me. She still haven’t sent it to me, I’ve bumped it a few times, so I don’t exactly know what the Google Form looks like, but I think it’s something that we can also create and just let them know to use the new one.
102 00:10:55.300 ⇒ 00:10:55.660 Uttam Kumaran: Okay.
103 00:10:55.660 ⇒ 00:10:57.389 Amber Lin: We’ve tried to go that route.
104 00:10:58.330 ⇒ 00:10:58.990 Casie Aviles: Okay.
105 00:10:59.270 ⇒ 00:11:01.610 Uttam Kumaran: Do we have that doc that they mentioned?
106 00:11:03.320 ⇒ 00:11:07.990 Amber Lin: … No, I asked. Okay. Have I reached?
107 00:11:07.990 ⇒ 00:11:08.910 Uttam Kumaran: Okay, okay.
108 00:11:09.170 ⇒ 00:11:09.970 Uttam Kumaran: Okay.
109 00:11:17.610 ⇒ 00:11:21.799 Uttam Kumaran: Okay, cool. Yeah, I… I need to sort of probably give comments on this async.
110 00:11:22.310 ⇒ 00:11:23.210 Uttam Kumaran: Good morning.
111 00:11:24.010 ⇒ 00:11:25.439 Uttam Kumaran: I’ll do a little bit more reading.
112 00:11:29.180 ⇒ 00:11:29.940 Casie Aviles: Sure, sure.
113 00:11:30.520 ⇒ 00:11:31.330 Amber Lin: Okay.
114 00:11:31.330 ⇒ 00:11:35.789 Uttam Kumaran: I feel pretty good about it, like, I feel… I feel… I think, like, ultimately…
115 00:11:36.030 ⇒ 00:11:42.780 Uttam Kumaran: I just want to make sure that this is worth us maintaining, and then, yeah, like, ideally, it sort of ends up in a…
116 00:11:42.930 ⇒ 00:11:45.790 Uttam Kumaran: we can start having this run Texas SQL, so….
117 00:11:50.280 ⇒ 00:11:50.900 Casie Aviles: Okay.
118 00:11:55.570 ⇒ 00:11:58.119 Casie Aviles: Okay, I’ll stop sharing now, then.
119 00:11:59.050 ⇒ 00:12:02.270 Casie Aviles: Yeah, I’ll just let you review that, Ace.
120 00:12:06.460 ⇒ 00:12:07.130 Amber Lin: Meaning.
121 00:12:09.190 ⇒ 00:12:13.920 Uttam Kumaran: Anything else on the agenda? I just… I know I had sent some notes.
122 00:12:14.070 ⇒ 00:12:25.739 Amber Lin: Yeah, wanted to look at the non-chat UI, the non-Google chat UI project plan that you sent,
123 00:12:27.680 ⇒ 00:12:32.890 Amber Lin: I think we can present this to the clients tomorrow, but do we have… huh.
124 00:12:32.890 ⇒ 00:12:35.749 Uttam Kumaran: I don’t think we should present this tomorrow.
125 00:12:35.750 ⇒ 00:12:36.190 Amber Lin: I’d love to know.
126 00:12:36.190 ⇒ 00:12:37.599 Uttam Kumaran: Wrote it, like, today.
127 00:12:37.830 ⇒ 00:12:39.430 Amber Lin: Oh, okay.
128 00:12:40.230 ⇒ 00:12:45.659 Uttam Kumaran: Yeah, I just wrote this last night, so there’s nothing… I mean, I haven’t even gotten Sam’s feedback, so I….
129 00:12:45.660 ⇒ 00:12:46.430 Amber Lin: Okay.
130 00:12:46.690 ⇒ 00:12:51.089 Uttam Kumaran: I mean, I’m happy to share that we’re, like, working on it, but…
131 00:12:53.240 ⇒ 00:13:00.490 Uttam Kumaran: I would… what’s gonna be more important is that they see, like, a little bit of a UI. Sam’s working on that, so…
132 00:13:01.110 ⇒ 00:13:06.260 Uttam Kumaran: With that, we can… I don’t know if it’s gonna be tomorrow, though, I’m not sure yet.
133 00:13:06.550 ⇒ 00:13:07.140 Amber Lin: Yeah.
134 00:13:08.440 ⇒ 00:13:10.610 Amber Lin: Rising. Wow.
135 00:13:11.260 ⇒ 00:13:13.280 Amber Lin: Okay.
136 00:13:16.120 ⇒ 00:13:17.460 Amber Lin: Created.
137 00:13:17.720 ⇒ 00:13:18.910 Amber Lin: Alright.
138 00:13:20.260 ⇒ 00:13:21.580 Amber Lin: …
139 00:13:23.100 ⇒ 00:13:33.709 Amber Lin: Let’s see… the next on the list is how we’re gonna handle these triage, because I know, Casey, you’re spending a lot of time on this each day.
140 00:13:34.800 ⇒ 00:13:38.920 Casie Aviles: Yeah, so I gave a little bit of,
141 00:13:40.100 ⇒ 00:13:42.260 Casie Aviles: explanation earlier.
142 00:13:42.410 ⇒ 00:13:47.360 Casie Aviles: But… Basically, it’s only whenever I…
143 00:13:48.010 ⇒ 00:13:56.390 Casie Aviles: get around to working on the triage tickets that I… but yeah, usually I spend, like, 2 hours, but it’s not, like, every day, like.
144 00:13:56.630 ⇒ 00:14:03.350 Casie Aviles: Sometimes, depending on the day that I get, I’m able to work on the triage tickets that I…
145 00:14:03.740 ⇒ 00:14:04.780 Casie Aviles: I would.
146 00:14:04.930 ⇒ 00:14:08.180 Casie Aviles: Work on them, like, for 2 hours. But…
147 00:14:08.280 ⇒ 00:14:12.779 Casie Aviles: Yeah, I think it would be helpful if we could, like, set, like, …
148 00:14:13.060 ⇒ 00:14:18.689 Casie Aviles: When these, triage tickets should be done by, like, and then…
149 00:14:20.030 ⇒ 00:14:25.570 Casie Aviles: you know, the pri- I guess the priorities, I guess, if, like… Which ones need to be…
150 00:14:26.670 ⇒ 00:14:28.390 Casie Aviles: Which are more urgent.
151 00:14:28.410 ⇒ 00:14:30.759 Amber Lin: Those are definitely….
152 00:14:32.130 ⇒ 00:14:34.290 Casie Aviles: Yeah, helpful.
153 00:14:34.430 ⇒ 00:14:43.869 Amber Lin: I see. We did agree with them on 48 hours, even for the most urgent issues. So I would say
154 00:14:44.220 ⇒ 00:14:47.499 Amber Lin: How… should we carve out, maybe…
155 00:14:47.750 ⇒ 00:14:51.750 Amber Lin: a time… Monday, Wednesday, Friday, or should we….
156 00:14:51.750 ⇒ 00:15:00.169 Uttam Kumaran: Maybe I can give some feedback here. So one is, like, I just can’t have… we… I just want to… we can’t have Casey working on this 2 hours a day.
157 00:15:00.310 ⇒ 00:15:01.450 Uttam Kumaran: …
158 00:15:01.670 ⇒ 00:15:11.289 Uttam Kumaran: Especially when it’s not clear, like, what the priority tickets are. So one is, like, what is the… what’s the current process, like, once we triage these tickets? Are we assigning…
159 00:15:11.630 ⇒ 00:15:15.969 Uttam Kumaran: Like, priority on them? Or, like, what, like, how… what is the current….
160 00:15:16.360 ⇒ 00:15:18.280 Amber Lin: Triage process right now.
161 00:15:19.440 ⇒ 00:15:32.870 Amber Lin: Mostly, I can… I… right now, I help triage them, and then sometimes Janice’s tickets, she’ll look at it and then ask for help from us, and right now.
162 00:15:33.810 ⇒ 00:15:34.920 Amber Lin: …
163 00:15:35.870 ⇒ 00:15:49.230 Amber Lin: most of it is non-urgent, most of it is issues that can wait 48 hours or more. I think Casey’s just very, very diligent, and I think we just have to…
164 00:15:49.410 ⇒ 00:16:00.999 Amber Lin: let down the… the pressure a little bit, and internally know that we can wait 48 hours, because I know that sometimes I work on those tickets as well.
165 00:16:01.100 ⇒ 00:16:01.649 Amber Lin: I think it’s.
166 00:16:01.650 ⇒ 00:16:02.350 Uttam Kumaran: That’s where you….
167 00:16:03.640 ⇒ 00:16:07.939 Uttam Kumaran: Yeah, it’s gonna be attractive because you can get it done quickly, but it’s…
168 00:16:08.080 ⇒ 00:16:17.269 Uttam Kumaran: like, not useful, I promise you. So, one of the things that maybe I would recommend is, one, as part of the triage process, can we use the priority.
169 00:16:17.630 ⇒ 00:16:18.640 Amber Lin: Yeah, totally.
170 00:16:19.110 ⇒ 00:16:19.750 Uttam Kumaran: Yeah, it’s re….
171 00:16:19.750 ⇒ 00:16:22.500 Amber Lin: required, actually to….
172 00:16:22.500 ⇒ 00:16:23.240 Uttam Kumaran: Okay.
173 00:16:23.530 ⇒ 00:16:24.560 Amber Lin: ….
174 00:16:25.270 ⇒ 00:16:26.669 Uttam Kumaran: To move into the shrint.
175 00:16:27.200 ⇒ 00:16:30.470 Amber Lin: Yeah, I think so. I had it…
176 00:16:31.020 ⇒ 00:16:32.930 Amber Lin: Sorry, I had it in May.
177 00:16:32.930 ⇒ 00:16:36.040 Uttam Kumaran: Ideally, we use a priority, and then we set the due dates.
178 00:16:36.860 ⇒ 00:16:44.130 Amber Lin: But for me, what I… 48 hours SLA on the most urgent things. So ideally, like.
179 00:16:44.240 ⇒ 00:16:50.969 Uttam Kumaran: we want to set things up to be due on Friday, or, like, during the sprint, for things that are non-urgent.
180 00:16:50.970 ⇒ 00:16:52.299 Amber Lin: I see.
181 00:16:52.300 ⇒ 00:16:56.059 Uttam Kumaran: Right? Because I want to, like, if we think about…
182 00:16:56.330 ⇒ 00:17:14.909 Uttam Kumaran: we have other priority items across a few other clients, and internally that we can work on, so I just want to make sure that if we can batch this, if Casey can batch this, or at least we’re just, like, not talking about it every day, because it’s gonna continue to grow like this, and we can’t sort of support this.
183 00:17:14.910 ⇒ 00:17:33.659 Amber Lin: Totally. Yeah, I think due dates and priorities are a great suggestion. I think it’s easier for us to understand, what needs to get done. Whatever’s assigned to Janiece, I can, I can let her figure out the due dates, but whatever’s assigned to us will have stricter due dates and
184 00:17:33.930 ⇒ 00:17:35.970 Amber Lin: Less pressure on them.
185 00:17:36.400 ⇒ 00:17:37.130 Uttam Kumaran: Okay.
186 00:17:38.010 ⇒ 00:17:38.620 Amber Lin: Nope.
187 00:17:38.840 ⇒ 00:17:39.840 Amber Lin: Okay.
188 00:17:40.090 ⇒ 00:17:42.920 Amber Lin: Let’s check the agenda…
189 00:17:46.410 ⇒ 00:18:00.500 Amber Lin: Yeah, and then training Janice on triage, I was gonna write a SOP for it, but then I… then I looked at a triage, there’s no tickets there for now. When something comes in.
190 00:18:00.840 ⇒ 00:18:11.829 Amber Lin: Or I can… I can walk them through this, this afternoon, because I’m meeting with Janiece and Tara, and then maybe I record that meeting, and then add it to the…
191 00:18:12.300 ⇒ 00:18:15.370 Amber Lin: … The training guidelines for them.
192 00:18:15.800 ⇒ 00:18:16.580 Uttam Kumaran: Okay.
193 00:18:16.900 ⇒ 00:18:17.450 Amber Lin: Yep.
194 00:18:24.980 ⇒ 00:18:32.890 Amber Lin: I’ll eat for the one. Okay. … I mean…
195 00:18:33.330 ⇒ 00:18:41.970 Amber Lin: we could use this time… I’ve realized the tickets here are not the most groomed, they do not have due dates.
196 00:18:42.080 ⇒ 00:18:49.909 Amber Lin: Because a lot of them just come up. I did not have time to groom this. … I can…
197 00:18:50.430 ⇒ 00:18:59.909 Amber Lin: Well, let’s see… … Just gonna spend the rest of the time to go through these
198 00:19:00.540 ⇒ 00:19:09.040 Amber Lin: tickets, and then we probably can skip the ABC stand-up, but I’ll probably still need to meet on Essonya later in the day.
199 00:19:09.140 ⇒ 00:19:09.900 Amber Lin: Okay.
200 00:19:10.720 ⇒ 00:19:15.679 Amber Lin: So… We decided on… we finished this spike.
201 00:19:15.800 ⇒ 00:19:21.319 Amber Lin: What is our next steps? Are we making the database? How… how much would that be?
202 00:19:21.780 ⇒ 00:19:25.320 Uttam Kumaran: No, no, like, spikes have to get reviewed, approved.
203 00:19:25.610 ⇒ 00:19:31.519 Uttam Kumaran: and then ticketed out. So, like, I… we… the first time I’ve talked about this is in this meeting, so…
204 00:19:31.900 ⇒ 00:19:35.860 Uttam Kumaran: We can’t move this ahead until, like, it gets approved by me and Sam.
205 00:19:36.430 ⇒ 00:19:37.160 Amber Lin: Okay.
206 00:19:37.390 ⇒ 00:19:41.320 Uttam Kumaran: … Similarly with the other project plans, so…
207 00:19:41.560 ⇒ 00:19:50.199 Uttam Kumaran: we… I think the step we’ve accomplished is, like, getting things written down, but it needs to get reviewed and then actually, like, approved for development, so….
208 00:19:54.050 ⇒ 00:19:55.240 Amber Lin: Great.
209 00:19:56.230 ⇒ 00:20:05.330 Amber Lin: … Internal review… And then…
210 00:20:08.220 ⇒ 00:20:15.000 Amber Lin: Joseph, I know you were working on normalizing the first page of the skills and zip sheet. How’s that?
211 00:20:15.360 ⇒ 00:20:19.359 Mustafa Raja: Yeah, I didn’t, really didn’t, get the chance to get into it.
212 00:20:19.620 ⇒ 00:20:26.670 Mustafa Raja: But, the interlude and default work is going, going to be a little lighter.
213 00:20:26.790 ⇒ 00:20:30.229 Mustafa Raja: Going ahead, I feel, so I should be able to take it.
214 00:20:30.700 ⇒ 00:20:34.480 Amber Lin: Okay, what’s the point estimate for this?
215 00:20:35.750 ⇒ 00:20:37.479 Mustafa Raja: Let’s do two.
216 00:20:41.500 ⇒ 00:20:46.200 Amber Lin: … And Casey, how many points would this be?
217 00:20:47.230 ⇒ 00:20:51.729 Casie Aviles: Did we change, like, the point system? I think this should be zero, right?
218 00:20:51.940 ⇒ 00:20:53.979 Casie Aviles: If it’s, like, less than 1 hour.
219 00:20:54.840 ⇒ 00:20:55.820 Amber Lin: Yeah, okay.
220 00:20:57.600 ⇒ 00:20:59.660 Amber Lin: No formulas…
221 00:21:40.850 ⇒ 00:21:41.600 Amber Lin: Okay.
222 00:21:42.390 ⇒ 00:21:51.099 Amber Lin: … Alright, and then… Cleaning up the spreadsheet hub, I think once we…
223 00:21:51.570 ⇒ 00:22:03.509 Amber Lin: Once we connect the new inspector sheet, I think we should hide all the not-relevant spreadsheets, because right now there’s just a lot, and we know where to go, but I don’t think
224 00:22:04.270 ⇒ 00:22:10.809 Amber Lin: Clients who… or whoever needs to access those sheets can have a clear idea of where to go.
225 00:22:11.930 ⇒ 00:22:16.430 Amber Lin: How many points would this be? Is it, like, 1 point?
226 00:22:16.430 ⇒ 00:22:19.100 Casie Aviles: it’s… Yeah, let’s do….
227 00:22:20.570 ⇒ 00:22:21.190 Amber Lin: Okay.
228 00:22:21.620 ⇒ 00:22:24.470 Amber Lin: Sounds good. And then…
229 00:22:29.400 ⇒ 00:22:38.049 Amber Lin: … Let me just… Cancel this… And then… okay.
230 00:22:40.560 ⇒ 00:22:42.979 Amber Lin: That’s gonna get done today.
231 00:22:43.450 ⇒ 00:22:47.889 Amber Lin: How’s progress on this? I know you had an initial idea.
232 00:22:48.980 ⇒ 00:22:53.190 Casie Aviles: Yeah, yeah, there’s no… No, I haven’t implemented this yet.
233 00:22:57.200 ⇒ 00:23:01.040 Amber Lin: Could you add the plan in this ticket?
234 00:23:02.430 ⇒ 00:23:03.140 Casie Aviles: Okay.
235 00:23:03.490 ⇒ 00:23:04.100 Amber Lin: Great.
236 00:23:04.100 ⇒ 00:23:04.939 Casie Aviles: Write that down.
237 00:23:09.460 ⇒ 00:23:10.840 Amber Lin: All right
238 00:23:17.790 ⇒ 00:23:23.139 Amber Lin: And then, I think last time we met with Yvette, we had a…
239 00:23:23.280 ⇒ 00:23:26.790 Amber Lin: We talked about integrating with 8x8.
240 00:23:27.090 ⇒ 00:23:32.509 Amber Lin: … I don’t think I’ve received the documents yet.
241 00:23:34.470 ⇒ 00:23:35.390 Amber Lin: Okay.
242 00:23:35.390 ⇒ 00:23:38.289 Uttam Kumaran: Yeah, I think for the 8x8 stuff, ….
243 00:23:40.050 ⇒ 00:23:48.650 Uttam Kumaran: I haven’t got anything yet. Maybe my ask is, like, we just have them connect to whoever is there, or they can give us access?
244 00:23:48.910 ⇒ 00:23:49.570 Amber Lin: Yeah.
245 00:23:51.220 ⇒ 00:23:52.100 Amber Lin: Okay.
246 00:23:53.670 ⇒ 00:23:59.400 Amber Lin: … The next… Friday.
247 00:24:15.490 ⇒ 00:24:16.630 Amber Lin: Alright.
248 00:24:17.240 ⇒ 00:24:23.770 Amber Lin: … I will do… I won’t do that.
249 00:24:24.740 ⇒ 00:24:25.880 Amber Lin: Amber…
250 00:24:40.320 ⇒ 00:24:46.380 Amber Lin: Alright, and then we have, … Exploring the transcript data.
251 00:24:48.110 ⇒ 00:24:51.909 Amber Lin: So, I know the data’s in this suite, but….
252 00:24:53.060 ⇒ 00:24:59.729 Casie Aviles: I don’t think it was in S3, because I checked last time in the… It’s not running at all.
253 00:25:00.220 ⇒ 00:25:03.620 Casie Aviles: already being… Wash the… for this….
254 00:25:03.620 ⇒ 00:25:04.300 Amber Lin: Huh.
255 00:25:06.410 ⇒ 00:25:10.929 Amber Lin: Okay, I see. I will… I will…
256 00:25:11.370 ⇒ 00:25:13.269 Amber Lin: Keep a close eye on this.
257 00:25:13.520 ⇒ 00:25:19.660 Amber Lin: on the transcript… Let’s see… Okay.
258 00:25:20.980 ⇒ 00:25:26.180 Amber Lin: … I’m gonna assign this to our stuff.
259 00:25:39.740 ⇒ 00:25:41.670 Amber Lin: I didn’t know, this is how we’re going.
260 00:25:45.150 ⇒ 00:25:46.020 Amber Lin: Alright.
261 00:25:46.670 ⇒ 00:25:47.700 Amber Lin: Honestly.
262 00:25:49.800 ⇒ 00:25:51.080 Amber Lin: And then…
263 00:25:53.010 ⇒ 00:26:00.880 Amber Lin: On the dashboarding side, we wanted to create a document on what types of analysis is available.
264 00:26:01.640 ⇒ 00:26:13.110 Amber Lin: I haven’t got around to do that. I think I’m gonna ask AI to do an initial list of questions and do an initial… and do an internal review on that.
265 00:26:13.110 ⇒ 00:26:16.449 Uttam Kumaran: Okay. Yeah, I can… I can add feedback once that’s there.
266 00:26:16.450 ⇒ 00:26:20.139 Amber Lin: I’ll aim for it today, because I’m gonna be out tomorrow.
267 00:26:20.570 ⇒ 00:26:22.149 Amber Lin: That is not today.
268 00:26:23.700 ⇒ 00:26:24.470 Amber Lin: Okay.
269 00:26:25.040 ⇒ 00:26:34.469 Amber Lin: And then, on the dashboard, you say, I think it’s just part of this analysis, I’ll include it in the plan, but originally I do want to see…
270 00:26:34.640 ⇒ 00:26:39.179 Amber Lin: overall what type of questions they’re asking, but I’ll include it in this plan.
271 00:26:40.250 ⇒ 00:26:53.400 Amber Lin: So, … want to add due dates to these, thinking that hopefully these get reviewed Thursday or Friday.
272 00:26:53.680 ⇒ 00:26:54.390 Uttam Kumaran: Okay.
273 00:26:54.690 ⇒ 00:27:00.399 Amber Lin: And then we can set out plans for next sprint on how we can develop that.
274 00:27:01.130 ⇒ 00:27:08.509 Amber Lin: And… Mustafa, when do you think you have capacity to normalize the tab?
275 00:27:09.080 ⇒ 00:27:14.730 Mustafa Raja: … Let’s do, end of week.
276 00:27:14.980 ⇒ 00:27:15.710 Amber Lin: Okay.
277 00:27:17.430 ⇒ 00:27:24.200 Amber Lin: This week… Casey, for these two tasks, when is a reasonable time?
278 00:27:26.880 ⇒ 00:27:32.370 Casie Aviles: for these two tasks, yeah, I can do this today, yeah. These are very quick.
279 00:27:33.540 ⇒ 00:27:34.170 Amber Lin: Okay.
280 00:27:41.390 ⇒ 00:27:46.090 Amber Lin: Alright. I guess Sam is also reviewing this one.
281 00:27:46.870 ⇒ 00:27:54.690 Amber Lin: And… … I’ll say… End of week.
282 00:27:56.220 ⇒ 00:28:00.220 Amber Lin: And then, trained needs to triage today.
283 00:28:02.790 ⇒ 00:28:08.330 Amber Lin: And then… I’m trying to use it.
284 00:28:11.910 ⇒ 00:28:12.720 Amber Lin: Okay.
285 00:28:13.350 ⇒ 00:28:15.270 Amber Lin: Also do this today.
286 00:28:18.800 ⇒ 00:28:19.660 Amber Lin: Alright.
287 00:28:19.810 ⇒ 00:28:27.370 Amber Lin: And then this will probably… We’ll ask for access, but this will be blocked for a bit.
288 00:28:27.570 ⇒ 00:28:30.109 Amber Lin: I’ll assign it to me so I can keep track.
289 00:28:30.800 ⇒ 00:28:34.070 Amber Lin: … Alright.
290 00:28:38.790 ⇒ 00:28:40.050 Amber Lin: Sounds good.
291 00:28:41.490 ⇒ 00:28:42.600 Amber Lin: Dang.
292 00:28:43.020 ⇒ 00:28:44.100 Amber Lin: How about?
293 00:28:56.190 ⇒ 00:28:57.200 Amber Lin: That’s good.
294 00:28:57.320 ⇒ 00:28:58.250 Amber Lin: Alrighty.
295 00:28:58.720 ⇒ 00:29:00.370 Amber Lin: Any other questions?
296 00:29:07.440 ⇒ 00:29:22.120 Uttam Kumaran: Yeah, I think next week, I think the biggest thing is just want to see if we can get Casey out of, sort of, having to deal with this stuff every day, and then… yeah, I think probably something that I’ll… I can ask in the PM channel is just to start to look at, …
297 00:29:22.660 ⇒ 00:29:26.880 Uttam Kumaran: sort of points by team. I think that’s something that now we have the data to look at.
298 00:29:27.140 ⇒ 00:29:31.470 Uttam Kumaran: So maybe in our next allocation meeting, we can start to look at, okay, like.
299 00:29:31.840 ⇒ 00:29:36.270 Uttam Kumaran: How many points are we taking on per team, and anywhere we’re overweighted or underweighted?
300 00:29:36.400 ⇒ 00:29:37.230 Uttam Kumaran: Yep.
301 00:29:37.230 ⇒ 00:29:37.880 Amber Lin: Sounds good.
302 00:29:37.880 ⇒ 00:29:39.830 Uttam Kumaran: Yeah, so we can talk about that on Tuesday.
303 00:29:40.110 ⇒ 00:29:41.600 Amber Lin: Yeah. …
304 00:29:41.760 ⇒ 00:29:53.679 Amber Lin: I think, overall, Eden’s around 100, Urban Stems is around 80. Abc, if you exclude Janice, we’re probably around 60-ish.
305 00:29:54.040 ⇒ 00:29:55.170 Amber Lin: …
306 00:29:55.610 ⇒ 00:30:02.509 Amber Lin: That’s for my teams, but let’s… we can create a view for that. I know we have some… I have the linear dashboard, too.
307 00:30:03.060 ⇒ 00:30:03.940 Uttam Kumaran: Okay, okay.
308 00:30:04.180 ⇒ 00:30:04.830 Amber Lin: Yeah.
309 00:30:05.700 ⇒ 00:30:06.900 Amber Lin: Alrighty.
310 00:30:07.250 ⇒ 00:30:12.869 Amber Lin: Thanks a lot, and Casey, I’ll try to triage and add due dates to all of them, and …
311 00:30:13.320 ⇒ 00:30:16.740 Amber Lin: Also, you can do that as well.
312 00:30:17.800 ⇒ 00:30:24.759 Casie Aviles: For… just later for… to later stand up. I’m not sure if I can make it at that time. We have, like, a….
313 00:30:24.760 ⇒ 00:30:25.330 Amber Lin: I see.
314 00:30:25.330 ⇒ 00:30:30.250 Casie Aviles: a demo with… like, evals for AI.
315 00:30:30.250 ⇒ 00:30:31.029 Amber Lin: Yeah, okay.
316 00:30:31.140 ⇒ 00:30:41.050 Amber Lin: It’s mostly insomnia Cookies items. We can do it async, I can send the updates we need async, so we’ll skip that one.
317 00:30:41.600 ⇒ 00:30:47.669 Casie Aviles: Yeah, I also just replied to your stuff for, like, the updates on the spike.
318 00:30:48.390 ⇒ 00:30:49.920 Amber Lin: Okay.
319 00:30:50.070 ⇒ 00:30:56.579 Amber Lin: Awesome. And then for the data platform, Utam, are you taking the remaining dashboard? I saw you had some adjustments.
320 00:30:56.580 ⇒ 00:31:02.930 Uttam Kumaran: I’m gonna take… I’m gonna take some of those, and then… or, yeah, I’m probably gonna end up taking it.
321 00:31:03.700 ⇒ 00:31:04.590 Amber Lin: Okay, I see.
322 00:31:04.590 ⇒ 00:31:11.670 Uttam Kumaran: But, like, the data platform stuff, I think we made a pretty good push. The things I want to see is, like, I want to get the calendar data in there.
323 00:31:12.190 ⇒ 00:31:17.910 Uttam Kumaran: I want to make sure that these Daxter issues are starting to get resolved. All the other stuff.
324 00:31:18.270 ⇒ 00:31:20.040 Uttam Kumaran: Yeah, it’s easier for me to do.
325 00:31:20.290 ⇒ 00:31:23.359 Amber Lin: Okay, so I had a ticket about the…
326 00:31:23.890 ⇒ 00:31:29.189 Amber Lin: So there’s the financial data and the calendar data, so I’ll make a ticket for that.
327 00:31:30.870 ⇒ 00:31:31.620 Uttam Kumaran: Okay.
328 00:31:32.730 ⇒ 00:31:34.030 Amber Lin: And…
329 00:31:37.230 ⇒ 00:31:38.060 Amber Lin: Okay.
330 00:31:38.480 ⇒ 00:31:42.200 Amber Lin: Thanks, both. Thanks everyone. I’ll cancel the other stand-up.
331 00:31:42.580 ⇒ 00:31:43.180 Amber Lin: Okay.
332 00:31:43.490 ⇒ 00:31:44.070 Casie Aviles: Thank you.
333 00:31:44.070 ⇒ 00:31:45.420 Mustafa Raja: Thank you. Thank you.