Meeting Title: ABC Standup Date: 2025-07-15 Meeting participants: Casie Aviles, Awaish Kumar, Amber Lin, Mustafa Raja, Luke Daque, Annie Yu
WEBVTT
1 00:02:26.470 ⇒ 00:02:27.700 Amber Lin: Hello!
2 00:02:29.990 ⇒ 00:02:31.609 Casie Aviles: Hey! Hey! Amber.
3 00:02:32.940 ⇒ 00:02:39.610 Amber Lin: Hi! Waiting for Luke to be here. I’ll just we can. We can talk about
4 00:02:40.600 ⇒ 00:02:43.350 Amber Lin: the other stuff for now.
5 00:02:45.386 ⇒ 00:02:47.240 Amber Lin: Hi! Mustafa!
6 00:02:48.490 ⇒ 00:02:49.559 Mustafa Raja: Hey! How are you?
7 00:02:50.050 ⇒ 00:02:51.099 Amber Lin: Oh, good.
8 00:02:52.100 ⇒ 00:02:56.739 Amber Lin: Here, linear ABC current.
9 00:02:57.959 ⇒ 00:03:01.230 Amber Lin: Okay, let’s look at
10 00:03:06.430 ⇒ 00:03:12.350 Amber Lin: here. So Tim said, he’s getting back to us on the transcripts.
11 00:03:12.500 ⇒ 00:03:18.579 Amber Lin: So just a heads up that once we get the transcripts, we wish we might need your help
12 00:03:18.920 ⇒ 00:03:22.573 Amber Lin: to just quickly set up. Set that up.
13 00:03:24.260 ⇒ 00:03:30.189 Amber Lin: Any progress on this one, Casey, returning Urls from Andy’s answers.
14 00:03:30.570 ⇒ 00:03:35.440 Casie Aviles: Oh, this is currently in progress. I just started work on this.
15 00:03:35.840 ⇒ 00:03:51.670 Amber Lin: Yeah, no worries. I think today, when I work with the Csrs, we’re gonna add some more urls. So when I add it, I’ll sort of screenshot and tell you where it is. So when you’re in testing, you know what to test for cause. I don’t think there’s too much Urls in there yet.
16 00:03:52.952 ⇒ 00:03:53.637 Casie Aviles: Yes, sure!
17 00:03:53.980 ⇒ 00:03:54.360 Amber Lin: Okay.
18 00:03:54.360 ⇒ 00:03:56.879 Casie Aviles: That also helps with adding test cases.
19 00:03:57.420 ⇒ 00:04:08.429 Amber Lin: Okay, awesome. So for this one, the service areas, I think a consistent issue is that sometimes it doesn’t. It returns technicians
20 00:04:10.120 ⇒ 00:04:14.349 Amber Lin: routing to spreadsheets. So
21 00:04:19.970 ⇒ 00:04:24.300 Amber Lin: I think that’s something that we’ll need to tackle
22 00:04:24.640 ⇒ 00:04:29.680 Amber Lin: soon. As we add more as we add more of the
23 00:04:31.350 ⇒ 00:04:32.090 Casie Aviles: Okay.
24 00:04:32.520 ⇒ 00:04:39.009 Amber Lin: Yeah. So if we look at adding the service area spreadsheet, then we’ll need to be
25 00:04:39.710 ⇒ 00:04:42.769 Amber Lin: careful on what to route to.
26 00:04:43.410 ⇒ 00:04:49.790 Amber Lin: So I think there was still an error last time I checked with the I checked with the Csr. So
27 00:04:50.020 ⇒ 00:04:52.400 Amber Lin: we might need to look into that again.
28 00:04:53.340 ⇒ 00:04:54.670 Casie Aviles: I see. I see. Okay.
29 00:04:55.750 ⇒ 00:04:56.070 Amber Lin: Yeah.
30 00:04:56.070 ⇒ 00:04:56.420 Casie Aviles: Yeah.
31 00:04:57.100 ⇒ 00:05:00.060 Amber Lin: Musafa, how is?
32 00:05:00.710 ⇒ 00:05:01.800 Amber Lin: How is this one.
33 00:05:02.401 ⇒ 00:05:11.409 Mustafa Raja: Yeah. So I’m I I couldn’t work on this yesterday. I’m what I’m going to today do is I’m going to ready the spreadsheet.
34 00:05:12.001 ⇒ 00:05:21.000 Mustafa Raja: With the templates. And then tomorrow I’d be working on Andy Andy’s agent to add this as a tool.
35 00:05:21.670 ⇒ 00:05:23.789 Amber Lin: Okay, awesome. So
36 00:05:24.070 ⇒ 00:05:31.869 Amber Lin: I guess for both of these, could I have something for Thursday? So I can show them at my presentation.
37 00:05:31.870 ⇒ 00:05:32.460 Mustafa Raja: Yeah.
38 00:05:32.980 ⇒ 00:05:36.600 Amber Lin: Okay, that will be awesome Thursday.
39 00:05:38.470 ⇒ 00:05:46.459 Amber Lin: That’s that. And then let’s look at this, Luke. How is how are these.
40 00:05:47.890 ⇒ 00:06:00.649 Luke Daque: For the spike timestamp. I’m yeah. And I just messaged away last earlier. This, like I need, I might need help with this, because I can’t figure out like, why we are not getting timestamps. But
41 00:06:00.850 ⇒ 00:06:06.402 Luke Daque: so yeah, we’ll be working on that one, and we might need to bear on that I still don’t
42 00:06:07.670 ⇒ 00:06:08.450 Luke Daque: anything.
43 00:06:09.490 ⇒ 00:06:12.080 Amber Lin: Is there Timestamps in the Api. Doc?
44 00:06:12.080 ⇒ 00:06:12.580 Amber Lin: I’ll share.
45 00:06:14.280 ⇒ 00:06:15.860 Amber Lin: Sorry I wish. Go ahead.
46 00:06:16.080 ⇒ 00:06:16.770 Awaish Kumar: What
47 00:06:17.310 ⇒ 00:06:23.559 Awaish Kumar: like, what kind of documentation timestamp we need like. I see the start, date and End date column should be there.
48 00:06:24.750 ⇒ 00:06:32.560 Luke Daque: Yeah, but it looks like they are in date format. And they don’t have the time like hour. And
49 00:06:32.560 ⇒ 00:06:36.490 Luke Daque: and I think, yeah, and he needs the the timestamp.
50 00:06:36.490 ⇒ 00:06:44.207 Awaish Kumar: But yeah, but like, can you just convert this in the Api?
51 00:06:45.040 ⇒ 00:06:51.010 Awaish Kumar: we are getting these date fields. Just convert them to Timestamps and add, like 2 extra fields
52 00:06:51.540 ⇒ 00:06:53.900 Awaish Kumar: at the start and end timestamp.
53 00:06:54.190 ⇒ 00:06:56.030 Luke Daque: I haven’t really.
54 00:06:56.290 ⇒ 00:06:57.130 Amber Lin: Oh!
55 00:06:57.130 ⇒ 00:07:01.099 Luke Daque: And deeply into the python script yet, so I’ll take a look at that.
56 00:07:02.130 ⇒ 00:07:07.012 Awaish Kumar: Yeah. So it’s just like, we are not getting it from Api. But we can just
57 00:07:09.790 ⇒ 00:07:12.219 Amber Lin: I wish. I don’t know if that would work, though.
58 00:07:12.400 ⇒ 00:07:41.280 Amber Lin: cause I I think the reason we need it is because we want to join the call logs to our bot logs, and the way we did that was we got the names of the Csrs and the exact time when they had the call and compared to the exact time that they asked asked Andy the question. And because they might have multiple multiple calls a day if it’s only a date field and then we fill out the rest. It might not.
59 00:07:41.280 ⇒ 00:07:42.939 Awaish Kumar: Yeah, these are summary reports.
60 00:07:44.760 ⇒ 00:07:45.690 Awaish Kumar: The kind of.
61 00:07:45.890 ⇒ 00:07:50.860 Awaish Kumar: So the kind of request I got initially to get the summary data. Summary reports.
62 00:07:51.410 ⇒ 00:07:53.810 Awaish Kumar: Historical summary reports. Basically.
63 00:07:54.510 ⇒ 00:08:00.790 Awaish Kumar: So. So now, the data we are getting these are called. These are summary reports. They are not like.
64 00:08:00.790 ⇒ 00:08:01.220 Amber Lin: Ha!
65 00:08:01.220 ⇒ 00:08:03.510 Awaish Kumar: Data of each agent.
66 00:08:04.900 ⇒ 00:08:05.750 Amber Lin: I see
67 00:08:07.090 ⇒ 00:08:07.660 Awaish Kumar: If you.
68 00:08:07.660 ⇒ 00:08:08.710 Amber Lin: So, if.
69 00:08:08.710 ⇒ 00:08:11.859 Awaish Kumar: If you want more granular, granular, detailed.
70 00:08:13.190 ⇒ 00:08:16.469 Awaish Kumar: if you need, if we need more granular detailed reports.
71 00:08:17.390 ⇒ 00:08:19.779 Awaish Kumar: Like, like, who can add about.
72 00:08:23.740 ⇒ 00:08:31.420 Amber Lin: Yeah, I I think we had. I guess my question is that does this current Api give us the requirements
73 00:08:31.600 ⇒ 00:08:34.849 Amber Lin: and needs because we can also
74 00:08:37.340 ⇒ 00:08:48.669 Amber Lin: because we also have one other Api that we have access to. I guess my question yesterday was that for Luke to check the api documentation to see if
75 00:08:49.350 ⇒ 00:08:55.439 Amber Lin: they we actually can. If it’s possible to get the level of granularity.
76 00:08:57.160 ⇒ 00:08:58.830 Awaish Kumar: Sorry like are you?
77 00:08:59.050 ⇒ 00:09:00.589 Awaish Kumar: Did you lost me, or.
78 00:09:01.694 ⇒ 00:09:03.169 Amber Lin: I can still hear you.
79 00:09:06.840 ⇒ 00:09:11.509 Awaish Kumar: Okay, no, I mean, like, I don’t know when my connection got disconnected.
80 00:09:12.000 ⇒ 00:09:15.139 Amber Lin: Oh, okay, yeah. So to repeat what I said.
81 00:09:15.760 ⇒ 00:09:23.700 Amber Lin: I think what we wanted to check yesterday was, that does all these Apis? Is it even possible to get
82 00:09:24.070 ⇒ 00:09:29.250 Amber Lin: the granular Timestamps from the Apis? We have access to.
83 00:09:30.245 ⇒ 00:09:31.960 Amber Lin: Luke, did you check on the.
84 00:09:31.960 ⇒ 00:09:32.280 Awaish Kumar: John.
85 00:09:32.280 ⇒ 00:09:34.020 Amber Lin: Was it possible?
86 00:09:34.390 ⇒ 00:09:37.350 Awaish Kumar: Can I? Yeah, I can like.
87 00:09:37.550 ⇒ 00:09:40.100 Awaish Kumar: guide the look on where to go, like.
88 00:09:40.100 ⇒ 00:09:40.490 Amber Lin: Okay.
89 00:09:40.490 ⇒ 00:09:47.840 Awaish Kumar: So okay on the report types, endpoint that you like.
90 00:09:48.330 ⇒ 00:10:03.400 Awaish Kumar: Got all these summary reports from like in those in that report types. We also have some reports which are not summary reports. They mentioned word like detailed reports, or something like that.
91 00:10:04.330 ⇒ 00:10:11.249 Awaish Kumar: So right now, the I think, the kind of reports. We are extract extracting the data from our
92 00:10:11.970 ⇒ 00:10:13.230 Awaish Kumar: summary report.
93 00:10:13.350 ⇒ 00:10:17.719 Awaish Kumar: I think. Like, look if you can explore those detailed reports
94 00:10:18.160 ⇒ 00:10:24.099 Awaish Kumar: and see like what kind of data we are getting from those that might be helpful.
95 00:10:27.210 ⇒ 00:10:30.969 Luke Daque: Okay, I’ll see if yeah, I can check.
96 00:10:31.660 ⇒ 00:10:32.630 Luke Daque: So that’s yeah.
97 00:10:32.630 ⇒ 00:10:37.763 Amber Lin: Yeah, I mean, this is the this is the Api that we’re currently using.
98 00:10:38.310 ⇒ 00:10:46.610 Amber Lin: I looked at it. I don’t think any of these mentioned like a specific start time and end time.
99 00:10:48.430 ⇒ 00:10:54.139 Amber Lin: I think that was the problem is, I don’t. I don’t know if this Api lets us do
100 00:10:54.600 ⇒ 00:10:57.100 Amber Lin: like. If I don’t, I don’t find start time.
101 00:10:57.260 ⇒ 00:11:07.290 Awaish Kumar: So if if the requirement is to find, like the wrap up time, or things like that, based on like daily, weekly, monthly, we can do from existing data.
102 00:11:08.280 ⇒ 00:11:14.909 Awaish Kumar: Is it more granular like? Well, if you want to know when a agent received a call
103 00:11:15.170 ⇒ 00:11:20.629 Awaish Kumar: in a day, if that’s if if that’s really needed, we can explore that.
104 00:11:20.890 ⇒ 00:11:23.050 Awaish Kumar: But that’s a question for you.
105 00:11:23.930 ⇒ 00:11:31.370 Amber Lin: Yeah, that’s what that’s what we need to join the join the 2 logs, or else it it doesn’t. It doesn’t work.
106 00:11:35.520 ⇒ 00:11:41.049 Awaish Kumar: Yeah. But is that really the requirement from the client like, because this sheet Google Sheet, does not
107 00:11:41.890 ⇒ 00:11:45.989 Awaish Kumar: any such detail of getting the granular data.
108 00:11:49.110 ⇒ 00:11:51.139 Amber Lin: Well, this is what we
109 00:11:51.390 ⇒ 00:12:00.009 Amber Lin: I guess this goes back in time. When we asked for this api this was what we asked for because the 1st one that we checked
110 00:12:00.848 ⇒ 00:12:03.759 Amber Lin: this one didn’t have.
111 00:12:04.110 ⇒ 00:12:07.659 Amber Lin: I guess the details we need.
112 00:12:08.360 ⇒ 00:12:29.620 Amber Lin: So probably it goes back to when we didn’t have it technically, and we’re still fumbling through the stuff. I do think I shared this yesterday. I don’t know, Luca, if you had a chance to check this yet this one probably would have the timestamps, and we do already have access to this. So if you can, I think here there’s already a
113 00:12:30.010 ⇒ 00:12:32.490 Amber Lin: see like, accept timestamp.
114 00:12:33.380 ⇒ 00:12:45.830 Amber Lin: finish timestamp. I think this is what we need, and then combine that with the historical actions. So we’ll have a lot of data from there. I just don’t know if you had a chance to look at this one yet.
115 00:12:47.080 ⇒ 00:12:55.790 Luke Daque: Yeah, I did. But it doesn’t. It’s very different from what we had in the Google sheet, right? Just like it has different columns and stuff.
116 00:12:55.790 ⇒ 00:12:57.810 Amber Lin: Yeah, it’s a different Api.
117 00:12:59.250 ⇒ 00:13:07.430 Luke Daque: So that I guess that’s and yeah, I don’t know. How is that the same you have.
118 00:13:07.430 ⇒ 00:13:16.680 Awaish Kumar: Yeah, so like, can we like having to divide this? Ask in 2 different tasks.
119 00:13:17.400 ⇒ 00:13:17.760 Amber Lin: Totally.
120 00:13:17.760 ⇒ 00:13:18.180 Awaish Kumar: I’m.
121 00:13:18.760 ⇒ 00:13:20.009 Amber Lin: Task would be
122 00:13:20.950 ⇒ 00:13:27.900 Awaish Kumar: My 1st task like I would like, look to explore in the current existing Api.
123 00:13:28.240 ⇒ 00:13:33.029 Awaish Kumar: We already have some detailed report. Times I would love to
124 00:13:33.360 ⇒ 00:13:42.179 Awaish Kumar: load those first.st It’s possible that we might get our required data from that like, spend a few hours and see like, if you are getting more granular data or not.
125 00:13:42.420 ⇒ 00:13:50.149 Awaish Kumar: Don’t develop it. Just send a request, get the data and see if it has the details we need.
126 00:13:50.410 ⇒ 00:13:53.379 Awaish Kumar: And similarly, this is the task one.
127 00:13:53.890 ⇒ 00:13:59.730 Awaish Kumar: and then we’ll have Task 2. The Api which you are sharing Ambo.
128 00:13:59.910 ⇒ 00:14:05.829 Awaish Kumar: Then we can move forward to other Api. If this current Api does not fill our fulfill our request.
129 00:14:23.280 ⇒ 00:14:24.130 Amber Lin: Okay.
130 00:14:24.886 ⇒ 00:14:31.489 Amber Lin: can we time box? This, please? Cause I, I know this has been taking a bit time, already.
131 00:14:39.070 ⇒ 00:14:42.820 Amber Lin: I wish what is a good timeframe to explore this 1st one.
132 00:14:43.370 ⇒ 00:14:46.659 Awaish Kumar: I would spend like 2, 3 h on this. But like.
133 00:14:47.380 ⇒ 00:14:49.770 Awaish Kumar: yeah, but for the due dates you can
134 00:14:50.820 ⇒ 00:14:54.370 Awaish Kumar: decide. Based on what Luke already has on his plate.
135 00:14:55.680 ⇒ 00:15:02.130 Amber Lin: I think this is the most important thing. So let me let me add both of these to the cycle, and then we can look at
136 00:15:02.260 ⇒ 00:15:04.830 Amber Lin: what’s currently to do.
137 00:15:05.340 ⇒ 00:15:10.860 Amber Lin: So sub issues.
138 00:15:27.160 ⇒ 00:15:28.000 Amber Lin: Okay.
139 00:15:28.280 ⇒ 00:15:30.879 Amber Lin: So looking at here.
140 00:15:32.450 ⇒ 00:15:38.050 Amber Lin: I don’t think we need to set up Dbt, if we don’t have the other 2 done
141 00:15:38.270 ⇒ 00:15:47.369 Amber Lin: think this is the most important thing. So the other things can wait. And let’s focus and get this done.
142 00:15:49.960 ⇒ 00:15:50.670 Amber Lin: Oops.
143 00:15:53.330 ⇒ 00:15:59.280 Amber Lin: So, Luke, what do you think would be a good estimate to get the 1st
144 00:16:00.172 ⇒ 00:16:05.269 Amber Lin: check the 1st Api, and then look at the other. Api.
145 00:16:06.054 ⇒ 00:16:08.739 Awaish Kumar: So the 5, 3, 1 should be the 1st one right.
146 00:16:09.170 ⇒ 00:16:11.880 Awaish Kumar: The existing. Yeah, this should be the highest.
147 00:16:17.640 ⇒ 00:16:21.200 Amber Lin: Okay, can I expect that by tomorrow?
148 00:16:22.450 ⇒ 00:16:24.619 Amber Lin: Tomorrow is already Wednesday? Okay.
149 00:16:24.620 ⇒ 00:16:25.930 Luke Daque: Work on that today.
150 00:16:26.680 ⇒ 00:16:47.169 Amber Lin: Awesome. And then if you get extra time, or if you, if you’re able to figure out that the 1st one doesn’t allow for the Timestamps. Can you do a quick? Read of the other documents and tell us what we need? Because I expect that we probably I don’t know if we connected yet yet basically, do we ever connect to that Api.
151 00:16:48.480 ⇒ 00:16:50.299 Casie Aviles: Oh, which Api were we referring.
152 00:16:50.682 ⇒ 00:16:56.850 Amber Lin: The one that you shared for the contact center to the east, reporting.
153 00:16:57.620 ⇒ 00:17:03.170 Casie Aviles: We were able to connect with that. But like we don’t have like a pipeline to pull from that.
154 00:17:03.380 ⇒ 00:17:03.800 Amber Lin: You know.
155 00:17:03.960 ⇒ 00:17:06.790 Casie Aviles: Because it was just more of a investigatory.
156 00:17:07.670 ⇒ 00:17:08.390 Amber Lin: Okay.
157 00:17:11.560 ⇒ 00:17:13.620 Amber Lin: okay, let me copy that.
158 00:17:25.220 ⇒ 00:17:34.189 Amber Lin: Okay, so let’s finish up the 1st task fast so that we can, we can have time to connect it to make a pipeline if we need.
159 00:17:34.960 ⇒ 00:17:35.800 Amber Lin: Okay.
160 00:17:35.990 ⇒ 00:17:42.339 Amber Lin: I think that’s all for today. And then Annie’s work is still blocked until we figure that one out.
161 00:17:42.510 ⇒ 00:17:44.840 Amber Lin: so not much. We can do
162 00:17:48.810 ⇒ 00:17:52.019 Amber Lin: alright. Thanks, everybody. I gotta hop to an interview.
163 00:17:53.540 ⇒ 00:17:54.000 Mustafa Raja: Thank you.
164 00:17:54.000 ⇒ 00:17:55.430 Mustafa Raja: Sounds good. Thanks. Bye.
165 00:17:55.430 ⇒ 00:17:57.149 Amber Lin: Thanks everyone, bye.