Meeting Title: ABC | backlog grooming Date: 2025-08-06 Meeting participants: Uttam Kumaran, Mustafa Raja, Sam Roberts, Casie Aviles, Amber Lin
WEBVTT
1 00:01:10.100 ⇒ 00:01:11.020 Mustafa Raja: Hey!
2 00:01:11.750 ⇒ 00:01:12.899 Uttam Kumaran: Hey! How are you?
3 00:01:13.770 ⇒ 00:01:15.310 Mustafa Raja: Super good! How are you?
4 00:01:16.290 ⇒ 00:01:20.760 Uttam Kumaran: Good dude this document, by the way.
5 00:01:21.070 ⇒ 00:01:24.990 Mustafa Raja: Yeah, yeah, yeah. I looked at it. Very well written.
6 00:01:24.990 ⇒ 00:01:26.309 Uttam Kumaran: Yeah, it was really great.
7 00:01:27.100 ⇒ 00:01:27.710 Uttam Kumaran: Hey, Sam?
8 00:01:27.710 ⇒ 00:01:31.099 Mustafa Raja: I need to. I need to learn this from Casey.
9 00:01:31.660 ⇒ 00:01:34.767 Uttam Kumaran: No, I know I’m really impressed. Like I I don’t know. I feel like
10 00:01:36.760 ⇒ 00:01:39.120 Uttam Kumaran: not a lot of engineering teams do like
11 00:01:39.290 ⇒ 00:01:42.079 Uttam Kumaran: sort of triage and investigative docs. But I,
12 00:01:42.370 ⇒ 00:01:46.120 Uttam Kumaran: if it’s like the perfect format for finding out problems like this.
13 00:01:46.120 ⇒ 00:01:46.870 Mustafa Raja: Yeah, yeah.
14 00:01:46.870 ⇒ 00:01:52.199 Uttam Kumaran: So I’m glad everybody’s actually like, really great, really positive around it, you know.
15 00:01:52.560 ⇒ 00:01:53.220 Mustafa Raja: Yeah.
16 00:01:59.750 ⇒ 00:02:01.829 Mustafa Raja: The plan Medicare meeting was good.
17 00:02:02.640 ⇒ 00:02:06.335 Uttam Kumaran: Yeah, it’s good. They’re kind of that guy’s kind of a character, right?
18 00:02:06.620 ⇒ 00:02:08.461 Mustafa Raja: Yeah, yeah, I love him.
19 00:02:11.270 ⇒ 00:02:16.109 Uttam Kumaran: Dude. This is what I’m saying. Yeah. Do you know, I don’t know if you want to deal with clients like that
20 00:02:17.520 ⇒ 00:02:20.150 Uttam Kumaran: some at some point I was like. Is he mad at me, or who is he mad at.
21 00:02:20.150 ⇒ 00:02:27.829 Mustafa Raja: Oh, yeah, I I thought, because his tone was like he he was really. He looked really frustrated, but he wasn’t frustrated.
22 00:02:27.830 ⇒ 00:02:31.390 Uttam Kumaran: No, no, he wasn’t mad at me. In fact, he was like we needed. You guys, you know.
23 00:02:31.390 ⇒ 00:02:32.130 Mustafa Raja: Yeah.
24 00:02:33.480 ⇒ 00:02:34.489 Sam Roberts: What was this one.
25 00:02:35.820 ⇒ 00:02:38.849 Mustafa Raja: The Plan Medicare Client Meeting.
26 00:02:39.570 ⇒ 00:02:40.250 Sam Roberts: Got it.
27 00:02:42.656 ⇒ 00:02:46.310 Mustafa Raja: It was just before this. Half hour ago.
28 00:02:48.735 ⇒ 00:02:49.140 Sam Roberts: Okay.
29 00:02:50.750 ⇒ 00:02:51.519 Mustafa Raja: How are you?
30 00:02:54.270 ⇒ 00:02:54.940 Sam Roberts: Me!
31 00:02:55.440 ⇒ 00:02:56.130 Mustafa Raja: Yeah, how are you?
32 00:02:56.130 ⇒ 00:02:57.223 Sam Roberts: Yeah, yeah.
33 00:02:59.670 ⇒ 00:03:07.229 Sam Roberts: I’ll say the space part. I mute myself. But then I wasn’t. Didn’t have it open. Yeah, no. Things are going all right. I was digging into some of the co-pilot kit stuff
34 00:03:07.890 ⇒ 00:03:09.390 Sam Roberts: right up a spike for that.
35 00:03:11.710 ⇒ 00:03:12.410 Sam Roberts: Yeah.
36 00:03:13.490 ⇒ 00:03:14.060 Amber Lin: So.
37 00:03:14.400 ⇒ 00:03:14.940 Mustafa Raja: And.
38 00:03:14.940 ⇒ 00:03:15.540 Sam Roberts: So.
39 00:03:16.620 ⇒ 00:03:29.109 Amber Lin: Hi, so this meeting mainly want to talk about the inspector sheet I will talk about what the causes are, and if we get any time left over? We can talk about
40 00:03:29.330 ⇒ 00:03:31.399 Amber Lin: how we’re going to scale
41 00:03:31.640 ⇒ 00:03:50.350 Amber Lin: to talk about evals and then talk about if we can scale how the scalable is our current, Chatbot, because we’re adding a lot of new departments. But let’s start with the inspector sheet. I know, Casey, you’ve had a document. Would you mind sharing the link in the chat.
42 00:03:50.350 ⇒ 00:03:55.139 Uttam Kumaran: Did did everyone have a chance to read it? Or, if not, take, take 90 seconds? It’s pretty quick.
43 00:03:55.750 ⇒ 00:03:56.295 Amber Lin: Yeah.
44 00:03:57.370 ⇒ 00:04:06.430 Sam Roberts: Can I actually get like a quick intro to this in general, because I was reading this? But I realized I didn’t really have the context of you know, I knew what was going wrong here, but I don’t know what the.
45 00:04:06.430 ⇒ 00:04:07.140 Amber Lin: Yeah, to.
46 00:04:07.140 ⇒ 00:04:08.220 Sam Roberts: Full. Context is.
47 00:04:08.420 ⇒ 00:04:29.450 Amber Lin: So this client, we are helping their customer service Department to create a top chat bot for them so mainly. This connects to a lot of their internal documentation and then the chat Bot provides information when when asked. Essentially so, the current issue is with a spreadsheet that has
48 00:04:30.330 ⇒ 00:04:36.169 Amber Lin: the different inspectors for the different zip codes.
49 00:04:36.380 ⇒ 00:04:44.200 Amber Lin: And so I will also share the link to the sheet. So you can have context of what it looks like.
50 00:04:46.520 ⇒ 00:04:48.590 Sam Roberts: Alright. Yeah, I think I got it here off the triage.
51 00:04:48.820 ⇒ 00:04:54.540 Uttam Kumaran: Yes, Sam, are you did, Amory, Sam know ABC, and like kind of what we’re working on for them.
52 00:04:55.350 ⇒ 00:04:56.510 Amber Lin: No Jenna.
53 00:04:57.440 ⇒ 00:05:01.259 Uttam Kumaran: Well, then, I don’t think we’re gonna have time to go go through that. Probably today.
54 00:05:01.260 ⇒ 00:05:03.930 Sam Roberts: No, that’s fine. I see that that’s enough context for me to at least understand a little.
55 00:05:03.930 ⇒ 00:05:08.819 Uttam Kumaran: Okay, basically, you’re building a chat bot for this company. One of the inputs is the spreadsheet
56 00:05:08.940 ⇒ 00:05:18.179 Uttam Kumaran: and part of the spreadsheets, basically a lookup spreadsheet. For I don’t, Casey, do you want to share? Maybe we can just go through some of these artifacts
57 00:05:18.380 ⇒ 00:05:22.610 Uttam Kumaran: and we can. Just I read the doc? I,
58 00:05:22.770 ⇒ 00:05:29.120 Uttam Kumaran: yeah, basically, there’s a spreadsheet with a lookup on inspectors. And basically our job is to
59 00:05:29.580 ⇒ 00:05:31.650 Uttam Kumaran: we’re trying to figure out why, that’s not
60 00:05:31.950 ⇒ 00:05:40.440 Uttam Kumaran: the Chatbot is not pulling from that accurately or like they. They basically said, Hey, some of the data it’s giving is is not accurate. So that’s what we’re figuring.
61 00:05:40.790 ⇒ 00:05:46.140 Casie Aviles: Yes, yeah. So we have this. Wait, let me.
62 00:05:46.880 ⇒ 00:05:50.830 Casie Aviles: We have this Consolidated spreadsheet.
63 00:05:50.940 ⇒ 00:05:53.410 Casie Aviles: So it’s like a let me hide this.
64 00:05:54.040 ⇒ 00:06:01.960 Casie Aviles: So it’s like a master spreadsheet that we have that should contain, like the inspectors for all the
65 00:06:02.340 ⇒ 00:06:07.460 Casie Aviles: all these residential pest, etcetera. And then the zip code.
66 00:06:07.890 ⇒ 00:06:12.619 Casie Aviles: So we are getting this via a
67 00:06:12.790 ⇒ 00:06:17.810 Casie Aviles: Via from N. 8 n, so we’re we just have like a tool that reads this.
68 00:06:18.880 ⇒ 00:06:26.859 Casie Aviles: And then we have a separate workflow that takes all of this into context and then returns like a response based on the query.
69 00:06:28.660 ⇒ 00:06:31.190 Casie Aviles: So, for example, if we ask, like
70 00:06:31.924 ⇒ 00:06:41.680 Casie Aviles: Inspectors, ABC, 7, 8, 7, 5, 1. It’s gonna return a list of people from from here.
71 00:06:42.020 ⇒ 00:06:45.409 Casie Aviles: So for example, 7, 8, 7, 5, 1.
72 00:06:46.180 ⇒ 00:06:50.359 Casie Aviles: So yeah, over here. So like, these are the people. And it should return that.
73 00:06:54.100 ⇒ 00:06:59.280 Casie Aviles: So I guess. Yeah, the problem sometimes is that these are incomplete, or
74 00:06:59.950 ⇒ 00:07:02.865 Casie Aviles: there are missing data. So I think it’s
75 00:07:03.900 ⇒ 00:07:10.540 Casie Aviles: it’s 1 1. My my hypothesis is there might be some discrepancies here. And since
76 00:07:10.730 ⇒ 00:07:19.199 Casie Aviles: we created this table kind of we we? This is like, let me show you the original tables.
77 00:07:19.400 ⇒ 00:07:21.020 Casie Aviles: So they look like this.
78 00:07:25.790 ⇒ 00:07:27.980 Casie Aviles: I’m sorry it’s it’s loading. But
79 00:07:29.950 ⇒ 00:07:33.726 Casie Aviles: yeah, so so like this. So we had to kind of
80 00:07:34.490 ⇒ 00:07:40.870 Casie Aviles: Standardize this because it’s they have their own kind of layout here or format.
81 00:07:41.220 ⇒ 00:07:46.540 Casie Aviles: So we wanted to flatten that and make it easier for us to get
82 00:07:47.400 ⇒ 00:07:52.110 Casie Aviles: like the the stuff that we need, the info that we need to the AI,
83 00:07:52.780 ⇒ 00:08:02.700 Casie Aviles: and I guess the the pro. My, yeah, my my hypothesis is that there might be some discrepancies from getting the stuff here and into here.
84 00:08:04.590 ⇒ 00:08:06.099 Casie Aviles: So that’s 1
85 00:08:06.450 ⇒ 00:08:18.399 Casie Aviles: probable cause for the discrepancy. So because there’s also a lot of things here that maybe we did not catch. And we don’t have, like the proper domain like us from
86 00:08:18.890 ⇒ 00:08:23.509 Casie Aviles: the brain forge team side like there are things we might have overlooked here like.
87 00:08:24.277 ⇒ 00:08:30.949 Casie Aviles: you know, there are a lot of stuff here that that’s domain specific. So and we don’t necessarily have, like the
88 00:08:31.830 ⇒ 00:08:39.429 Casie Aviles: alright contact. So maybe there are some. There’s those there are those alright. And then, if you can see, we have all these
89 00:08:40.620 ⇒ 00:08:44.880 Casie Aviles: formula. So we’re getting it from like flattened tables.
90 00:08:47.380 ⇒ 00:08:49.719 Casie Aviles: For example, here, what we did.
91 00:08:51.310 ⇒ 00:08:54.879 Casie Aviles: We created. We kind of flattened each sheet
92 00:08:55.580 ⇒ 00:08:59.989 Casie Aviles: this way, and we are using the formulas to draw from this.
93 00:09:00.760 ⇒ 00:09:06.589 Casie Aviles: Pretty much so those are. That’s how we do it.
94 00:09:09.960 ⇒ 00:09:11.970 Casie Aviles: Yeah. And then I guess another.
95 00:09:13.300 ⇒ 00:09:17.240 Casie Aviles: It’s also possible, although I haven’t fully
96 00:09:17.998 ⇒ 00:09:25.740 Casie Aviles: investigated yet is if the actual tool or workflow that we have maybe flawed as well.
97 00:09:27.814 ⇒ 00:09:31.470 Casie Aviles: Maybe it’s not getting even if the the data is correct on
98 00:09:31.880 ⇒ 00:09:39.950 Casie Aviles: the inspector spreadsheet. Maybe it’s not getting everything. But I haven’t really investigated that fully, and that’s also another
99 00:09:40.090 ⇒ 00:09:42.080 Casie Aviles: possible cause.
100 00:09:44.006 ⇒ 00:09:49.129 Casie Aviles: Yeah, I I’ll stop there. And you know, if you have any questions.
101 00:09:50.980 ⇒ 00:09:56.639 Uttam Kumaran: Yeah, maybe I I go to Mustafa first.st Since you’re the other. You know you’re on the client. What do you think.
102 00:09:58.220 ⇒ 00:10:12.789 Mustafa Raja: Yeah. So the workflow that we have for inspector sheet the tool. We can now update it also, because, prior, when we when we created this to only fetch data for the
103 00:10:13.244 ⇒ 00:10:36.439 Mustafa Raja: Zip code the Google sheets. No, did not have filters available. We recently updated our Internet and instance, we now have filters for Google sheets. So we can add the filters, and for the zip codes, we need to see if we are getting the correct
104 00:10:37.062 ⇒ 00:10:40.010 Mustafa Raja: data for the Zip code.
105 00:10:41.830 ⇒ 00:10:52.710 Uttam Kumaran: But I guess, like maybe my 1st question is, if we look at the question that they tried to get answered, and they flagged as, Hey, it’s incorrect. Do you have that, Casey?
106 00:10:52.710 ⇒ 00:10:54.190 Mustafa Raja: Yeah, we have those.
107 00:10:54.190 ⇒ 00:10:55.190 Casie Aviles: Yes.
108 00:10:55.695 ⇒ 00:10:57.210 Casie Aviles: Abc, logs. Channel.
109 00:10:58.210 ⇒ 00:11:00.699 Casie Aviles: Yeah. We also have no. We also have a spreadsheet.
110 00:11:01.080 ⇒ 00:11:02.220 Amber Lin: Go ahead, sorry.
111 00:11:03.220 ⇒ 00:11:08.526 Casie Aviles: Oh, yeah, we also have this sheet. So it’s also routing all the
112 00:11:09.130 ⇒ 00:11:11.920 Casie Aviles: feedback the thumbs down feedback that we get.
113 00:11:12.750 ⇒ 00:11:14.730 Casie Aviles: And you can see here that
114 00:11:15.040 ⇒ 00:11:18.740 Casie Aviles: yeah. So I’ve dug which ones are for the inspector sheet.
115 00:11:19.640 ⇒ 00:11:21.680 Casie Aviles: And these are the kinds of questions.
116 00:11:21.860 ⇒ 00:11:23.950 Uttam Kumaran: So let’s take one example.
117 00:11:24.380 ⇒ 00:11:26.529 Uttam Kumaran: So I guess my point is that
118 00:11:26.690 ⇒ 00:11:35.690 Uttam Kumaran: is the inaccuracy on the on their side, or is the inaccuracy happening, because our sheet is not up to date with the latest.
119 00:11:36.510 ⇒ 00:11:44.940 Amber Lin: I think, is with the translation of the original sheet to our current sheet, because I think it was this.
120 00:11:45.080 ⇒ 00:11:50.730 Amber Lin: Spreadsheets and so many formulas like it. Just wasn’t that accurate.
121 00:11:51.000 ⇒ 00:11:58.690 Uttam Kumaran: So can you, so can you pull up? Can we literally go to this cell, in this in their master sheet? And then the cell in our sheet.
122 00:11:58.860 ⇒ 00:12:00.499 Uttam Kumaran: For this value.
123 00:12:00.880 ⇒ 00:12:02.006 Amber Lin: Yeah, totally.
124 00:12:03.000 ⇒ 00:12:04.730 Amber Lin: Let’s go.
125 00:12:05.870 ⇒ 00:12:07.700 Uttam Kumaran: But I just wanna confirm like
126 00:12:08.070 ⇒ 00:12:16.060 Uttam Kumaran: the mechanism aside. I just want to get down to like, Okay, what is is it? Literally not there, or what’s the difference, you know.
127 00:12:21.490 ⇒ 00:12:23.979 Casie Aviles: 9, 7, 8, 6, 6, 5.
128 00:12:37.390 ⇒ 00:12:38.690 Casie Aviles: It’s here.
129 00:12:40.580 ⇒ 00:12:48.360 Casie Aviles: So they asked, so when was this? Let me check the date.
130 00:12:50.730 ⇒ 00:12:57.070 Casie Aviles: Okay, so one of the problems here is this is actually getting from the technicians.
131 00:12:57.980 ⇒ 00:13:08.510 Casie Aviles: So it’s not so. It’s a routing issue here in this particular error in this particular row.
132 00:13:08.720 ⇒ 00:13:15.840 Casie Aviles: because these are when when we have these A rodents. B rodents, these are for the technician sheet.
133 00:13:16.450 ⇒ 00:13:22.400 Casie Aviles: And it’s asking from Inspector. So that’s 1 pro one of the issues.
134 00:13:22.770 ⇒ 00:13:33.890 Amber Lin: Did the estimate. I think in that case the word estimate confused because it sounds like in the next one row, 5, where it asked for, wrote an estimate.
135 00:13:34.110 ⇒ 00:13:36.710 Amber Lin: It also gave the technician sheet.
136 00:13:40.550 ⇒ 00:13:44.339 Casie Aviles: Okay. So for the 4th one, let me check this.
137 00:13:44.340 ⇒ 00:13:53.130 Amber Lin: Yeah, the inspectors are the right inspectors. I know, we asked to
138 00:13:54.300 ⇒ 00:14:05.789 Amber Lin: add. Routing based on the wording, because inspectors, estimates, bids did all route to the Inspector Sheet, were we able to add that in the system prompt.
139 00:14:08.118 ⇒ 00:14:09.970 Casie Aviles: Yeah, I did add it, although.
140 00:14:09.970 ⇒ 00:14:10.750 Amber Lin: Hmm.
141 00:14:10.750 ⇒ 00:14:13.969 Casie Aviles: Yeah, that’s 1 of the yeah, these are.
142 00:14:13.970 ⇒ 00:14:21.819 Uttam Kumaran: Let’s okay. So let’s just take this. Let’s just take line 22, right? So they said, Res pest, inspector, 7, 8, 6, 20.
143 00:14:22.490 ⇒ 00:14:26.750 Uttam Kumaran: And what? And then the answer is.
144 00:14:26.920 ⇒ 00:14:31.189 Uttam Kumaran: there is no inspector listed for residential pest control.
145 00:14:32.030 ⇒ 00:14:35.059 Uttam Kumaran: so can we confirm that that is true.
146 00:14:35.640 ⇒ 00:14:37.619 Amber Lin: Yeah, let me 7, 8.
147 00:14:37.620 ⇒ 00:14:38.150 Casie Aviles: Perspective.
148 00:14:38.150 ⇒ 00:14:39.370 Amber Lin: 2 0.
149 00:14:46.340 ⇒ 00:14:50.309 Uttam Kumaran: So it looks like there is residential pest.
150 00:14:52.550 ⇒ 00:14:53.430 Uttam Kumaran: Alright.
151 00:14:54.320 ⇒ 00:14:59.580 Amber Lin: there.
152 00:15:04.030 ⇒ 00:15:04.990 Amber Lin: yeah.
153 00:15:08.230 ⇒ 00:15:15.770 Amber Lin: that’s so strange, it, okay, cool.
154 00:15:21.300 ⇒ 00:15:22.360 Amber Lin: Yeah.
155 00:15:31.710 ⇒ 00:15:38.823 Amber Lin: So strange there, is most of most of it, we have for respest.
156 00:15:39.580 ⇒ 00:15:47.559 Amber Lin: we could further flatten this table cause maybe cause right now.
157 00:15:47.560 ⇒ 00:15:55.849 Uttam Kumaran: I just want to answer. I just want to answer the most basic like, let’s don’t solution at all. I just want to know, like, is our, was our reply. Wrong.
158 00:15:57.300 ⇒ 00:16:00.830 Amber Lin: Yeah, it’s wrong. We don’t have. We have. We didn’t show it.
159 00:16:01.290 ⇒ 00:16:07.429 Uttam Kumaran: So can we like? Can we isolate like, I guess, Casey, for Casey and Mustafa the goal is like.
160 00:16:07.680 ⇒ 00:16:10.390 Uttam Kumaran: why did the AI not
161 00:16:11.350 ⇒ 00:16:18.869 Uttam Kumaran: provide that answer like, what did it end up pulling from the Google sheets into context? And can you replicate
162 00:16:19.080 ⇒ 00:16:21.870 Uttam Kumaran: the answer that we gave.
163 00:16:24.010 ⇒ 00:16:24.590 Casie Aviles: Okay.
164 00:16:25.340 ⇒ 00:16:25.740 Uttam Kumaran: Right.
165 00:16:25.740 ⇒ 00:16:27.030 Casie Aviles: Test, this right now.
166 00:16:29.590 ⇒ 00:16:32.569 Uttam Kumaran: So my, that’s gonna be my 1st question is just like.
167 00:16:37.240 ⇒ 00:16:38.110 Mustafa Raja: Yeah.
168 00:16:47.920 ⇒ 00:16:48.760 Uttam Kumaran: Okay.
169 00:16:49.840 ⇒ 00:16:50.480 Mustafa Raja: So.
170 00:16:53.890 ⇒ 00:16:55.020 Casie Aviles: Oh, wait! Sorry!
171 00:16:55.420 ⇒ 00:16:56.700 Uttam Kumaran: Yeah, so that’s fine.
172 00:16:56.700 ⇒ 00:16:58.419 Uttam Kumaran: I’m not sure what is happening.
173 00:16:59.900 ⇒ 00:17:01.000 Casie Aviles: Yeah, this is.
174 00:17:01.870 ⇒ 00:17:03.250 Uttam Kumaran: Accurate, right, now.
175 00:17:03.250 ⇒ 00:17:04.170 Casie Aviles: These are so. Then she.
176 00:17:04.170 ⇒ 00:17:06.909 Uttam Kumaran: Can you? Right? Can you? Right click on that cell?
177 00:17:08.700 ⇒ 00:17:09.450 Casie Aviles: I’m sure.
178 00:17:10.280 ⇒ 00:17:12.470 Uttam Kumaran: And can you do show edit history?
179 00:17:18.650 ⇒ 00:17:20.260 Uttam Kumaran: Okay? Alright, cool.
180 00:17:25.690 ⇒ 00:17:29.280 Uttam Kumaran: So it’s not like this was updated right? Recently.
181 00:17:30.560 ⇒ 00:17:31.010 Amber Lin: No.
182 00:17:32.610 ⇒ 00:17:37.439 Sam Roberts: What kind of like logs do we have of their queries? Besides that thumbs up thumbs down
183 00:17:38.060 ⇒ 00:17:42.089 Sam Roberts: results like, is there any way to see the data that was actually like.
184 00:17:42.090 ⇒ 00:17:44.800 Uttam Kumaran: Yeah. Can you go run for this.
185 00:17:44.800 ⇒ 00:17:47.440 Sam Roberts: Yeah, is, that is, are we able to find that easily.
186 00:17:48.462 ⇒ 00:17:51.347 Mustafa Raja: Yeah, we can find the answer.
187 00:17:56.080 ⇒ 00:18:00.430 Mustafa Raja: the most recent one for 7, 8, 6, 3, 3. The
188 00:18:02.520 ⇒ 00:18:13.849 Mustafa Raja: the feedback is, we are missing residential tree for for that zip code, but I see that in the in the sheet we do not have
189 00:18:14.481 ⇒ 00:18:16.989 Mustafa Raja: any for the residential tree
190 00:18:18.770 ⇒ 00:18:20.340 Mustafa Raja: in the inspector sheet at all.
191 00:18:21.880 ⇒ 00:18:23.400 Casie Aviles: This was the question.
192 00:18:23.400 ⇒ 00:18:25.660 Sam Roberts: Okay. So this, this is is this the one that
193 00:18:27.700 ⇒ 00:18:29.819 Sam Roberts: that’s something that just ran right.
194 00:18:30.510 ⇒ 00:18:34.229 Casie Aviles: Yes, and this is this is the response.
195 00:18:34.760 ⇒ 00:18:38.569 Sam Roberts: Okay, so, but this is the one that we know. Work. Is there a way to see
196 00:18:39.000 ⇒ 00:18:42.980 Sam Roberts: like, do we have the the date and time of that bad request.
197 00:18:48.670 ⇒ 00:18:52.110 Casie Aviles: Take time, date and time.
198 00:18:52.110 ⇒ 00:18:53.430 Sam Roberts: Like, if you go back to the.
199 00:18:53.670 ⇒ 00:18:54.390 Casie Aviles: You mean this.
200 00:18:54.950 ⇒ 00:19:00.180 Sam Roberts: Well, I I guess I just don’t know like how long these are all stored for, like what kind of logs we have going back.
201 00:19:02.170 ⇒ 00:19:05.080 Mustafa Raja: The execution. Logs are stored for 30 days.
202 00:19:05.570 ⇒ 00:19:08.660 Sam Roberts: Okay, so can we see
203 00:19:09.210 ⇒ 00:19:16.180 Sam Roberts: specifically for that one we’ve been looking at that we just tried and worked the bad one that they, you know, had the issue with.
204 00:19:18.500 ⇒ 00:19:22.420 Casie Aviles: Going to be too far back already.
205 00:19:22.420 ⇒ 00:19:26.512 Sam Roberts: Yeah. So I just didn’t know how how. Well, you know, we can filter all that stuff through.
206 00:19:29.300 ⇒ 00:19:34.549 Casie Aviles: I think they should be able you, should we? Should. We have these? Execution starts soon.
207 00:19:35.180 ⇒ 00:19:44.550 Sam Roberts: Okay, yeah. So so, oh, yeah, that might be. That might be just a lot to sift through there.
208 00:19:45.070 ⇒ 00:19:46.700 Casie Aviles: Yeah, it’s going to be a lot.
209 00:19:47.790 ⇒ 00:19:48.380 Sam Roberts: Okay.
210 00:20:02.310 ⇒ 00:20:07.450 Casie Aviles: Okay, yeah.
211 00:20:07.870 ⇒ 00:20:08.630 Casie Aviles: So
212 00:20:11.900 ⇒ 00:20:14.116 Sam Roberts: So I’m just saying, Don’t don’t mind me
213 00:20:14.670 ⇒ 00:20:15.320 Casie Aviles: Okay.
214 00:20:21.580 ⇒ 00:20:22.839 Casie Aviles: I’m going to do that.
215 00:20:22.990 ⇒ 00:20:24.520 Casie Aviles: Look for others
216 00:20:37.315 ⇒ 00:20:37.800 Casie Aviles: here.
217 00:20:38.180 ⇒ 00:20:42.380 Casie Aviles: So Tree Inspector.
218 00:21:04.300 ⇒ 00:21:06.583 Casie Aviles: So they noted here that
219 00:21:09.190 ⇒ 00:21:12.799 Casie Aviles: Brad P is listed as the residential tree inspector.
220 00:21:17.620 ⇒ 00:21:20.160 Casie Aviles: It’s returning, Jesse Warrior. So
221 00:21:25.200 ⇒ 00:21:27.270 Casie Aviles: we do have this. But
222 00:21:30.330 ⇒ 00:21:31.760 Casie Aviles: let me check here.
223 00:21:36.270 ⇒ 00:21:38.700 Casie Aviles: 7, 8, 7, 3, 3.
224 00:21:42.600 ⇒ 00:21:43.470 Casie Aviles: Okay.
225 00:21:48.480 ⇒ 00:21:49.900 Uttam Kumaran: It’s a it’s correct, right?
226 00:21:53.700 ⇒ 00:21:54.420 Casie Aviles: Hmm!
227 00:21:55.050 ⇒ 00:21:57.732 Casie Aviles: This is their 3 inspectors and
228 00:21:58.630 ⇒ 00:22:00.189 Uttam Kumaran: But like scroll left.
229 00:22:00.910 ⇒ 00:22:02.279 Uttam Kumaran: So you can see the Zip
230 00:22:02.910 ⇒ 00:22:08.020 Uttam Kumaran: 7, 8, 3, 3. 0, it is. It isn’t okay.
231 00:22:08.270 ⇒ 00:22:15.099 Uttam Kumaran: So I guess my question is like, how so? Okay? So right now, it looks like it’s this person, Hunter Brad Paxton. Right?
232 00:22:15.870 ⇒ 00:22:19.500 Uttam Kumaran: So let’s let’s go back to our spreadsheet.
233 00:22:22.970 ⇒ 00:22:24.909 Uttam Kumaran: and then let’s go find
234 00:22:25.220 ⇒ 00:22:31.610 Uttam Kumaran: like. So right now, this is a V lookup right on the commercial inspectors table. So let’s go to that.
235 00:22:32.100 ⇒ 00:22:36.630 Uttam Kumaran: Let’s go to that sheet within this spreadsheet.
236 00:22:40.450 ⇒ 00:22:45.699 Uttam Kumaran: and then scroll right? Find that? Yeah, to find this. What is it? 7, 8, 3. Something.
237 00:22:49.207 ⇒ 00:22:50.759 Uttam Kumaran: What was the zip.
238 00:22:53.900 ⇒ 00:22:55.950 Casie Aviles: 7, 8, 7, 3, 3.
239 00:23:06.630 ⇒ 00:23:09.880 Uttam Kumaran: I guess. Like, can you find in the yeah. See if you can see it in the top here?
240 00:23:10.200 ⇒ 00:23:11.929 Uttam Kumaran: 7, 8, 7, 3, 3. Right here.
241 00:23:14.370 ⇒ 00:23:15.630 Casie Aviles: That’s a nice one.
242 00:23:16.990 ⇒ 00:23:17.690 Casie Aviles: Yeah, it’s Fred.
243 00:23:17.690 ⇒ 00:23:18.009 Uttam Kumaran: Got it.
244 00:23:18.010 ⇒ 00:23:18.650 Casie Aviles: Come here!
245 00:23:19.780 ⇒ 00:23:20.830 Uttam Kumaran: So.
246 00:23:21.370 ⇒ 00:23:28.499 Uttam Kumaran: But go back to the the master sheet. Why was why was this saying.
247 00:23:35.330 ⇒ 00:23:37.620 Uttam Kumaran: yeah, keep keep going, keep going down.
248 00:23:43.050 ⇒ 00:23:45.530 Uttam Kumaran: So why was it saying, Brad
249 00:23:46.350 ⇒ 00:23:50.470 Uttam Kumaran: Brad Paxton? But go. So now go back to the like. The 1st sheet we were on
250 00:23:51.600 ⇒ 00:23:54.290 Uttam Kumaran: where it said, Jesse.
251 00:23:54.750 ⇒ 00:23:56.780 Uttam Kumaran: Okay, why, why is this happening?
252 00:23:59.530 ⇒ 00:24:04.070 Uttam Kumaran: Click, click on the click on the formula, or, what is a formula.
253 00:24:05.500 ⇒ 00:24:07.839 Casie Aviles: Okay, there is no formula here.
254 00:24:08.410 ⇒ 00:24:09.540 Uttam Kumaran: Oh, shit.
255 00:24:11.910 ⇒ 00:24:16.630 Uttam Kumaran: Okay. Well, there you go, can you? When were these edited?
256 00:24:26.720 ⇒ 00:24:27.440 Uttam Kumaran: What.
257 00:24:29.370 ⇒ 00:24:31.309 Casie Aviles: Yeah, this might be me.
258 00:24:31.920 ⇒ 00:24:33.190 Uttam Kumaran: Oh, okay. Okay.
259 00:24:35.180 ⇒ 00:24:37.270 Casie Aviles: Yeah, there was like a formula here.
260 00:24:37.570 ⇒ 00:24:41.599 Uttam Kumaran: Well, I guess what like. Let’s go back to what happened on July 24.th
261 00:24:47.530 ⇒ 00:24:52.310 Uttam Kumaran: My guess is like, was there can. Yeah, I guess.
262 00:24:52.850 ⇒ 00:24:55.600 Uttam Kumaran: Do you remember making a change on July 24.th
263 00:24:57.170 ⇒ 00:24:59.550 Casie Aviles: Not necessarily.
264 00:25:01.610 ⇒ 00:25:02.110 Uttam Kumaran: Was there.
265 00:25:02.110 ⇒ 00:25:03.490 Casie Aviles: I think I did.
266 00:25:03.490 ⇒ 00:25:07.050 Uttam Kumaran: Someone released a did someone give some feedback? And
267 00:25:07.630 ⇒ 00:25:10.009 Uttam Kumaran: we we did a manual change or something.
268 00:25:12.110 ⇒ 00:25:12.999 Casie Aviles: Let me check.
269 00:25:13.610 ⇒ 00:25:14.400 Casie Aviles: Sure
270 00:25:22.600 ⇒ 00:25:29.210 Casie Aviles: item, I don’t remember, but I’m I think I’m the only one using it so.
271 00:25:30.130 ⇒ 00:25:33.320 Casie Aviles: But I don’t remember making the change here
272 00:25:42.560 ⇒ 00:25:45.769 Casie Aviles: since I we we did set it up to have, like
273 00:25:46.000 ⇒ 00:25:48.339 Casie Aviles: the formulas, as you can see here.
274 00:26:03.770 ⇒ 00:26:10.059 Uttam Kumaran: So I think so. One can we? Can you replace those with the formula and see whether we get the?
275 00:26:10.940 ⇒ 00:26:12.480 Uttam Kumaran: We get the right answer.
276 00:26:15.640 ⇒ 00:26:16.310 Casie Aviles: Okay.
277 00:26:17.390 ⇒ 00:26:19.630 Uttam Kumaran: But this would be, Yeah.
278 00:26:28.520 ⇒ 00:26:29.180 Casie Aviles: Hmm.
279 00:26:35.120 ⇒ 00:26:35.880 Uttam Kumaran: Hmm.
280 00:26:36.500 ⇒ 00:26:38.009 Casie Aviles: I don’t think it’s getting it.
281 00:26:39.650 ⇒ 00:26:41.979 Uttam Kumaran: Okay? So this is what we need to figure out.
282 00:26:49.100 ⇒ 00:26:52.040 Uttam Kumaran: where does it say tree here?
283 00:26:59.330 ⇒ 00:27:02.269 Uttam Kumaran: Right? Because it’s doing a vlookup on tree right?
284 00:27:03.460 ⇒ 00:27:04.200 Casie Aviles: Yes.
285 00:27:11.790 ⇒ 00:27:13.510 Casie Aviles: Residential tree.
286 00:27:17.780 ⇒ 00:27:24.000 Uttam Kumaran: And this is in master. Inspect table cockpitch.
287 00:27:31.360 ⇒ 00:27:36.970 Uttam Kumaran: commercial tree, residential 3. And then this is 7, 8, 7, 3, 3.
288 00:27:43.690 ⇒ 00:27:57.730 Uttam Kumaran: But I guess my question is, it looks like there’s no but well, it should be Brad.
289 00:27:58.340 ⇒ 00:28:01.730 Uttam Kumaran: So okay, let’s look at. Let’s just let’s test out this formula. Right?
290 00:28:01.900 ⇒ 00:28:05.399 Uttam Kumaran: Let’s just look at. Let’s just look through the formula. So.
291 00:28:05.940 ⇒ 00:28:08.950 Sam Roberts: I didn’t know if I was muted. I’m sorry I was just saying the same thing. Yeah.
292 00:28:08.950 ⇒ 00:28:10.069 Uttam Kumaran: Oh, you’re good. Yeah, it’s.
293 00:28:10.301 ⇒ 00:28:12.620 Sam Roberts: Realize we’re on a different different one than the original.
294 00:28:12.620 ⇒ 00:28:21.879 Uttam Kumaran: No, you could. Just you could. You could also try the next cell over. It’s basically gonna be this looks like it’s gonna be the same thing, but it’s a vlookup on a 1, 91. So a 1, 91 is
295 00:28:24.180 ⇒ 00:28:26.349 Uttam Kumaran: well, what is a 1? 91
296 00:28:27.410 ⇒ 00:28:30.520 Uttam Kumaran: oh, 8, 2, 1, okay, 8, 2, 1, 9.
297 00:28:31.230 ⇒ 00:28:33.420 Sam Roberts: It’s good. Yeah, that’s good.
298 00:28:33.630 ⇒ 00:28:38.089 Uttam Kumaran: 7, 8, 7, 3, 3 tree table.
299 00:28:39.450 ⇒ 00:28:40.479 Uttam Kumaran: What is that?
300 00:28:42.830 ⇒ 00:28:43.960 Casie Aviles: Should be this table.
301 00:28:44.264 ⇒ 00:28:45.480 Uttam Kumaran: I see. Okay, okay.
302 00:28:46.680 ⇒ 00:28:54.860 Uttam Kumaran: Pre, table match y, 4 to the tree table headers.
303 00:28:55.400 ⇒ 00:28:57.779 Uttam Kumaran: Okay, so press enter. What would we get?
304 00:29:00.780 ⇒ 00:29:08.590 Uttam Kumaran: Hmm, okay. So another thing is, let’s try to dissect.
305 00:29:08.920 ⇒ 00:29:11.413 Uttam Kumaran: So the goal is here is to dissect this
306 00:29:14.550 ⇒ 00:29:18.370 Uttam Kumaran: So kind of so to tell you how I typically debug stuff like this is
307 00:29:18.540 ⇒ 00:29:21.940 Uttam Kumaran: what I’ve done in the past is, I go into Chat Gbt, and I basically say that
308 00:29:22.230 ⇒ 00:29:26.549 Uttam Kumaran: I’m trying to debug this formula like, let’s break it down. Because
309 00:29:26.650 ⇒ 00:29:29.880 Uttam Kumaran: 1st we want to look at what’s failing. Right? So
310 00:29:30.000 ⇒ 00:29:41.300 Uttam Kumaran: can you? Can you look, can you just try to run like the match function. But let’s actually look at. Let’s go through the debug together. Yeah. So paste it in and say, I need say, your your Google sheets expert. I need help
311 00:29:42.130 ⇒ 00:29:45.680 Uttam Kumaran: debugging this formula. What are the steps? I should take?
312 00:29:45.840 ⇒ 00:29:52.409 Uttam Kumaran: What it’s probably going to tell you is okay. Start with the match, then start with the next piece. And this is a great way to debug these spreadsheets.
313 00:29:57.340 ⇒ 00:29:59.069 Uttam Kumaran: Yeah, this is perfect.
314 00:30:02.170 ⇒ 00:30:03.060 Uttam Kumaran: Yes.
315 00:30:04.440 ⇒ 00:30:06.898 Uttam Kumaran: So let’s walk through these steps perfect.
316 00:30:14.230 ⇒ 00:30:19.023 Casie Aviles: Hmm should exist.
317 00:30:20.350 ⇒ 00:30:24.969 Uttam Kumaran: So yeah, let’s so let’s start with just doing the 2, 1 9,
318 00:30:25.160 ⇒ 00:30:28.719 Uttam Kumaran: meaning like, just do just do equal star 2, 1, 9.
319 00:30:32.770 ⇒ 00:30:40.579 Uttam Kumaran: It’s gonna be painful or sorry. A yeah, perfect. Okay, great. And then what does it say to do next? Say that probably to test the match function right?
320 00:30:42.370 ⇒ 00:30:44.430 Casie Aviles: Verify Table Range.
321 00:30:45.970 ⇒ 00:30:50.640 Uttam Kumaran: Yeah. So so see if you can do equals. See if you can. Just
322 00:30:51.260 ⇒ 00:30:54.849 Uttam Kumaran: if tree table is, the is actually something you can reference.
323 00:31:35.400 ⇒ 00:31:36.040 Casie Aviles: Hmm.
324 00:31:44.250 ⇒ 00:31:45.859 Sam Roberts: Yeah, there’s an error. Okay.
325 00:31:50.470 ⇒ 00:31:51.330 Casie Aviles: No this!
326 00:31:51.960 ⇒ 00:31:53.600 Uttam Kumaran: Yeah, so, but yeah.
327 00:31:53.600 ⇒ 00:31:55.319 Sam Roberts: Tree tables is the issue. Yeah.
328 00:31:55.780 ⇒ 00:31:57.289 Uttam Kumaran: It’s a treat. Oh, really.
329 00:31:57.740 ⇒ 00:32:02.249 Uttam Kumaran: yeah. Well, cause I realized it was wrapped in a is na. Otherwise it’s gonna be blank.
330 00:32:02.250 ⇒ 00:32:03.150 Sam Roberts: Yeah, so, so.
331 00:32:03.150 ⇒ 00:32:04.010 Uttam Kumaran: So it’s default.
332 00:32:04.550 ⇒ 00:32:09.990 Sam Roberts: And if you go to data named ranges, there is no named range
333 00:32:10.950 ⇒ 00:32:13.300 Sam Roberts: tree tables. So something was to happen to it.
334 00:32:19.470 ⇒ 00:32:24.859 Sam Roberts: Yeah, what it’s like it says, Yeah, define a named range. There is no one called tree table.
335 00:32:24.860 ⇒ 00:32:30.920 Uttam Kumaran: Yeah, like, that’s the thing I didn’t even I don’t think you can do what you’re doing, which is select from
336 00:32:31.110 ⇒ 00:32:33.990 Uttam Kumaran: tree table, because typically.
337 00:32:36.140 ⇒ 00:32:38.430 Sam Roberts: You. I think you could if it was named.
338 00:32:38.430 ⇒ 00:32:40.340 Uttam Kumaran: You have to create a name range. But like typically
339 00:32:40.850 ⇒ 00:32:43.849 Uttam Kumaran: so, a name range is equivalent to just a new sheet.
340 00:32:44.190 ⇒ 00:32:45.060 Uttam Kumaran: Right?
341 00:32:46.100 ⇒ 00:32:50.149 Uttam Kumaran: So I guess my point is, let’s see if you
342 00:32:50.640 ⇒ 00:32:55.049 Uttam Kumaran: yeah, just see if you can just select anything from tree table, or if you can run the match
343 00:32:55.870 ⇒ 00:32:56.850 Uttam Kumaran: command.
344 00:33:00.540 ⇒ 00:33:03.109 Uttam Kumaran: Yeah, see if you can run that.
345 00:33:10.330 ⇒ 00:33:11.129 Casie Aviles: Let me see.
346 00:33:18.170 ⇒ 00:33:22.870 Uttam Kumaran: Okay, so something’s there.
347 00:33:25.790 ⇒ 00:33:29.359 Uttam Kumaran: So what is? So what is what is 6 supposed to be?
348 00:33:30.210 ⇒ 00:33:32.400 Uttam Kumaran: 6 is like, yeah, what is this?
349 00:33:41.780 ⇒ 00:33:43.080 Uttam Kumaran: Yeah. Good question.
350 00:33:47.460 ⇒ 00:33:51.770 Uttam Kumaran: 6 calls, etc. So let’s go. Let’s go. Confirm that
351 00:33:52.920 ⇒ 00:33:56.559 Uttam Kumaran: the 1, 2, 3, 4. That’s not that.
352 00:33:56.780 ⇒ 00:33:58.110 Uttam Kumaran: So go into notes
353 00:34:01.150 ⇒ 00:34:02.040 Uttam Kumaran: right?
354 00:34:06.020 ⇒ 00:34:06.810 Casie Aviles: Yeah.
355 00:34:10.330 ⇒ 00:34:13.140 Uttam Kumaran: So let’s go back to the match function.
356 00:34:21.520 ⇒ 00:34:25.010 Uttam Kumaran: No, that’s weird.
357 00:34:26.440 ⇒ 00:34:27.700 Uttam Kumaran: Okay. Well, go.
358 00:34:28.850 ⇒ 00:34:37.420 Uttam Kumaran: Can you ask? Chat Wt, how you can get the value of the column. Not just the the position.
359 00:34:44.630 ⇒ 00:34:46.109 Uttam Kumaran: Okay, yeah. Try this.
360 00:35:11.550 ⇒ 00:35:14.919 Casie Aviles: Hmm, wait. Okay, let’s I’m just trying this.
361 00:35:17.960 ⇒ 00:35:21.550 Uttam Kumaran: I think you’re you’ll have to
362 00:35:22.170 ⇒ 00:35:24.119 Uttam Kumaran: people headers. Thing that. Yeah, yeah.
363 00:35:36.030 ⇒ 00:35:38.740 Uttam Kumaran: what is row number with that?
364 00:35:41.800 ⇒ 00:35:44.960 Uttam Kumaran: So here, one way, one way to look at the formula.
365 00:35:45.230 ⇒ 00:35:47.639 Uttam Kumaran: I can show you, Casey. If you go back.
366 00:35:50.468 ⇒ 00:35:53.099 Uttam Kumaran: is, you can just click here.
367 00:35:56.290 ⇒ 00:36:03.880 Uttam Kumaran: And yeah, Yup, or just like, just literally click. Don’t highlight.
368 00:36:06.727 ⇒ 00:36:12.470 Uttam Kumaran: You should. It should give you like a dropdown explanation of how this function works like, click in here. Maybe.
369 00:36:16.130 ⇒ 00:36:18.010 Uttam Kumaran: Yeah. So click, yeah.
370 00:36:18.510 ⇒ 00:36:24.729 Uttam Kumaran: So index reference row column. So reference is the array of cells.
371 00:36:24.930 ⇒ 00:36:28.069 Uttam Kumaran: So I don’t think you need row number.
372 00:36:37.430 ⇒ 00:36:38.180 Uttam Kumaran: Hmm.
373 00:36:47.950 ⇒ 00:36:53.249 Uttam Kumaran: yeah, we don’t want to override it. So so try this in a try this in a new sheet, or
374 00:36:55.247 ⇒ 00:36:59.172 Uttam Kumaran: I’m trying to think like, what’s the easiest thing to do here?
375 00:37:00.290 ⇒ 00:37:08.949 Uttam Kumaran: yeah, do this. And what what I guess what you can do is click on it. Replace y 4 with the string residential tree.
376 00:37:12.030 ⇒ 00:37:13.600 Casie Aviles: Oh, residential.
377 00:37:13.600 ⇒ 00:37:14.310 Uttam Kumaran: Yeah.
378 00:37:17.760 ⇒ 00:37:18.500 Uttam Kumaran: sure.
379 00:37:20.585 ⇒ 00:37:22.760 Casie Aviles: So quotes, yeah.
380 00:37:22.760 ⇒ 00:37:27.199 Sam Roberts: Okay. So I just, oh, yeah, I did. I just pasted, yeah, I did the same. I’m just yeah.
381 00:37:27.862 ⇒ 00:37:28.828 Sam Roberts: You got it.
382 00:37:29.150 ⇒ 00:37:33.470 Uttam Kumaran: So what does this tell us.
383 00:37:35.900 ⇒ 00:37:37.109 Sam Roberts: This is doing.
384 00:37:38.340 ⇒ 00:37:41.299 Casie Aviles: I think these are the contents of the row.
385 00:37:43.030 ⇒ 00:37:43.810 Sam Roberts: Yes.
386 00:37:44.240 ⇒ 00:37:45.090 Uttam Kumaran: Or what.
387 00:37:45.090 ⇒ 00:37:45.680 Casie Aviles: Even.
388 00:38:01.060 ⇒ 00:38:01.950 Casie Aviles: Hmm.
389 00:38:04.880 ⇒ 00:38:06.770 Casie Aviles: 7, 8, 6, 1, 3.
390 00:38:07.440 ⇒ 00:38:09.356 Uttam Kumaran: But I guess I’m confused with like.
391 00:38:10.740 ⇒ 00:38:14.230 Uttam Kumaran: why is it not giving me the giving us the column name?
392 00:38:14.753 ⇒ 00:38:18.630 Sam Roberts: Is it so match is doing?
393 00:38:20.400 ⇒ 00:38:22.680 Sam Roberts: Max comes to 6 right?
394 00:38:22.800 ⇒ 00:38:25.710 Sam Roberts: And is that giving them?
395 00:39:05.380 ⇒ 00:39:06.400 Sam Roberts: Oh, I see.
396 00:39:55.110 ⇒ 00:39:56.310 Sam Roberts: Oh.
397 00:40:13.090 ⇒ 00:40:14.120 Sam Roberts: yeah, so that
398 00:40:33.880 ⇒ 00:40:41.700 Sam Roberts: think the that indexes the row and column might be switched.
399 00:40:44.390 ⇒ 00:40:45.380 Uttam Kumaran: Oh!
400 00:40:45.960 ⇒ 00:40:51.519 Sam Roberts: So it’s matching the title residential tree to the tree table. Header.
401 00:40:52.230 ⇒ 00:41:01.849 Sam Roberts: Right? That’s what we’re getting. That match is giving us a number. And then that’s going in the row entry of the index instead of the column entry.
402 00:41:01.850 ⇒ 00:41:07.400 Uttam Kumaran: Oh, okay, go back to the spreadsheet. Then see if you can.
403 00:41:07.400 ⇒ 00:41:08.010 Sam Roberts: So.
404 00:41:08.010 ⇒ 00:41:09.369 Uttam Kumaran: Yeah, yeah, go ahead. Go ahead.
405 00:41:09.370 ⇒ 00:41:15.769 Sam Roberts: Yeah, I was just gonna yeah, go back to there and just edit that one.
406 00:41:16.270 ⇒ 00:41:19.769 Sam Roberts: And just so see that 0 at the end.
407 00:41:22.220 ⇒ 00:41:26.170 Sam Roberts: That should. So that’s within the match.
408 00:41:26.920 ⇒ 00:41:30.180 Sam Roberts: Oh, so there needs to be another 0 at the end or in front of Matt.
409 00:41:30.670 ⇒ 00:41:38.129 Uttam Kumaran: Paste in the paste in the larger formula, again, like the Og, one.
410 00:41:39.350 ⇒ 00:41:40.070 Sam Roberts: Oh, yeah.
411 00:41:42.150 ⇒ 00:41:44.799 Uttam Kumaran: This is, that’s the Og one. Right? Okay? So.
412 00:41:44.800 ⇒ 00:41:46.810 Sam Roberts: It just doesn’t have the na in front of it, but.
413 00:41:47.470 ⇒ 00:41:54.050 Uttam Kumaran: Yeah, yeah. So in this one, you’re saying, we need to swap.
414 00:41:55.100 ⇒ 00:41:59.259 Sam Roberts: Oh, maybe maybe I was doing something different down here. I had to wait. Where’s index? There’s no index in that one.
415 00:42:03.710 ⇒ 00:42:07.890 Sam Roberts: Hold on! I was looking at something else here, if any of you look up. Oh, I have something different. Never mind.
416 00:42:08.690 ⇒ 00:42:09.180 Uttam Kumaran: So.
417 00:42:09.180 ⇒ 00:42:09.880 Sam Roberts: Let me dig into.
418 00:42:09.880 ⇒ 00:42:11.850 Sam Roberts: Now. I was looking for something slightly different.
419 00:42:15.460 ⇒ 00:42:22.960 Uttam Kumaran: Basically that what this is function is doing is it’s saying, cool, give me 7, 8, 7, 3, 3, and column 4 of tree table.
420 00:42:25.750 ⇒ 00:42:29.889 Uttam Kumaran: But match tree table headers is doing 6.
421 00:42:34.050 ⇒ 00:42:34.920 Sam Roberts: Right.
422 00:42:38.500 ⇒ 00:42:42.410 Sam Roberts: and that’s let’s go on 1st time.
423 00:42:42.410 ⇒ 00:42:45.380 Uttam Kumaran: Like, why is this giving? Why is this giving 6?
424 00:42:46.120 ⇒ 00:42:51.300 Uttam Kumaran: Can you? Can you? Can you open this whole formula, Casey, like, Go back there and just hit the dropdown
425 00:42:52.790 ⇒ 00:43:02.979 Uttam Kumaran: like if you click on this and then just hit escape and then click back here.
426 00:43:05.490 ⇒ 00:43:09.290 Uttam Kumaran: and then I think you can see it here if you like. Click into the formula.
427 00:43:11.860 ⇒ 00:43:13.400 Uttam Kumaran: Is there a way to like
428 00:43:14.330 ⇒ 00:43:16.060 Uttam Kumaran: you just had it? I think.
429 00:43:17.060 ⇒ 00:43:18.590 Uttam Kumaran: Yeah. So booked out.
430 00:43:19.820 ⇒ 00:43:25.480 Uttam Kumaran: So match Sunday, the range and then the search type. So scroll down to search type.
431 00:43:33.650 ⇒ 00:43:36.230 Uttam Kumaran: can you do 0 the search type?
432 00:43:38.840 ⇒ 00:43:39.580 Uttam Kumaran: Yeah.
433 00:43:40.404 ⇒ 00:43:40.859 Sam Roberts: Yep.
434 00:43:42.010 ⇒ 00:43:42.650 Casie Aviles: Oh!
435 00:43:42.650 ⇒ 00:43:43.490 Uttam Kumaran: That’s it.
436 00:43:45.260 ⇒ 00:43:51.140 Sam Roberts: What does it default? The search type to one finds the largest value less than or equal to the key? Wow!
437 00:43:51.140 ⇒ 00:43:52.440 Uttam Kumaran: What does that even mean?
438 00:43:53.775 ⇒ 00:43:59.679 Sam Roberts: I mean, I imagine if you’re doing numbers, it’s not the same as matching text, but who know? I know
439 00:44:00.040 ⇒ 00:44:01.019 Sam Roberts: sheets is following the lead
440 00:44:01.020 ⇒ 00:44:08.929 Sam Roberts: excel does stuff. It’s like text is, you know, compared in different ways. And yeah, 0, there is important.
441 00:44:08.930 ⇒ 00:44:14.780 Uttam Kumaran: But let’s try. Let’s try this. Let’s try with this. Try it. Try to build the vlookup with the 0.
442 00:44:17.080 ⇒ 00:44:18.750 Uttam Kumaran: But is that already? What we had.
443 00:44:20.420 ⇒ 00:44:22.600 Casie Aviles: It’s the same one we had before.
444 00:44:23.310 ⇒ 00:44:24.120 Sam Roberts: Okay, so let’s.
445 00:44:24.120 ⇒ 00:44:24.730 Casie Aviles: Here.
446 00:44:24.730 ⇒ 00:44:26.689 Sam Roberts: Gives you the 4 right?
447 00:44:27.690 ⇒ 00:44:28.530 Sam Roberts: That’s.
448 00:44:32.910 ⇒ 00:44:34.679 Uttam Kumaran: And what is the error code here?
449 00:44:35.240 ⇒ 00:44:37.250 Uttam Kumaran: But what is this? What is this error.
450 00:44:37.880 ⇒ 00:44:43.289 Sam Roberts: That was, that’s just I just removed the is na that wrapped this whole thing.
451 00:44:43.580 ⇒ 00:44:48.569 Uttam Kumaran: So can you. Can you take this and just put this in here and let’s try with the 7, 8, 7, 3, 3.
452 00:44:48.570 ⇒ 00:44:49.270 Sam Roberts: Yeah.
453 00:44:56.780 ⇒ 00:44:58.810 Uttam Kumaran: And just change to 2, 1, 9.
454 00:45:02.350 ⇒ 00:45:04.590 Sam Roberts: Still an error. Wrapping this Vlook up.
455 00:45:05.000 ⇒ 00:45:08.190 Uttam Kumaran: Well could not find value in the Vlookup evaluation.
456 00:45:08.190 ⇒ 00:45:12.739 Sam Roberts: Yeah, we’re searching for that.
457 00:45:13.360 ⇒ 00:45:17.779 Sam Roberts: The range that index.
458 00:45:18.070 ⇒ 00:45:22.269 Uttam Kumaran: So can you? Can you go back? Can you go to sheet? Can you copy this into sheet 40? This formula.
459 00:45:22.970 ⇒ 00:45:31.109 Uttam Kumaran: So now that we fix. Now, we know, like one thing. So let’s go back to sheet 40 in a new cell, just price it in and replace this match with 4.
460 00:45:31.710 ⇒ 00:45:36.130 Uttam Kumaran: Now that we know like that solved, we can get for like to replace the whole match
461 00:45:43.660 ⇒ 00:45:46.720 Uttam Kumaran: and then replace 2 0. 9 with our Zip code.
462 00:45:48.120 ⇒ 00:45:49.600 Uttam Kumaran: But the string
463 00:45:53.230 ⇒ 00:45:55.030 Uttam Kumaran: you need, you’ll need quotes.
464 00:46:01.770 ⇒ 00:46:07.810 Uttam Kumaran: And can you go to the value in the other table? 4, 7, 8, 7, 3, 3.
465 00:46:11.500 ⇒ 00:46:12.220 Casie Aviles: Okay.
466 00:46:20.530 ⇒ 00:46:23.820 Casie Aviles: we have multiple 7, 8, 7, 3, 3.
467 00:46:25.110 ⇒ 00:46:26.170 Casie Aviles: Looks like.
468 00:46:27.350 ⇒ 00:46:32.840 Uttam Kumaran: Yeah, but but 7, 8, 7. So go back to sheet 40.
469 00:46:39.400 ⇒ 00:46:41.720 Uttam Kumaran: Can you type in 2 instead of 4?
470 00:46:52.660 ⇒ 00:46:54.780 Uttam Kumaran: But tree table.
471 00:46:58.190 ⇒ 00:46:59.500 Uttam Kumaran: can you tell me one?
472 00:47:03.520 ⇒ 00:47:07.410 Uttam Kumaran: But this formula is not right. Right? What is this? This is not a range
473 00:47:12.290 ⇒ 00:47:13.020 Uttam Kumaran: or.
474 00:47:17.060 ⇒ 00:47:18.039 Sam Roberts: Not being found in.
475 00:47:19.240 ⇒ 00:47:20.070 Sam Roberts: Hmm?
476 00:47:26.730 ⇒ 00:47:32.600 Sam Roberts: Oh, so it’s looking at the treat table right?
477 00:47:33.000 ⇒ 00:47:35.290 Sam Roberts: The 1st is it it’s doing
478 00:47:36.610 ⇒ 00:47:38.310 Sam Roberts: is that? Hold on! I got my name.
479 00:47:39.570 ⇒ 00:47:45.020 Uttam Kumaran: The value to search for. For example, 42. Okay, so 7, 8, 7, 3, 3. The range.
480 00:47:56.360 ⇒ 00:48:00.130 Sam Roberts: Oh, okay, I think it’s because Vlookup says it
481 00:48:00.250 ⇒ 00:48:03.090 Sam Roberts: searches down the 1st column of a range.
482 00:48:03.930 ⇒ 00:48:11.060 Sam Roberts: and the 1st column of this is not the zip. It’s the branch of tree table.
483 00:48:17.290 ⇒ 00:48:18.069 Uttam Kumaran: I guess.
484 00:48:23.770 ⇒ 00:48:24.670 Uttam Kumaran: wow.
485 00:48:54.550 ⇒ 00:48:56.510 Sam Roberts: Like, just take that zip 7, 8,
486 00:48:56.730 ⇒ 00:48:59.220 Sam Roberts: 7, 3, 3, and replace it in.
487 00:48:59.890 ⇒ 00:49:01.209 Sam Roberts: Sell to the left.
488 00:49:01.580 ⇒ 00:49:06.540 Sam Roberts: See if that just makes it work, because I think Vlookup only looks in that 1st column.
489 00:49:10.125 ⇒ 00:49:11.770 Casie Aviles: Sorry. What do I need to do.
490 00:49:12.040 ⇒ 00:49:16.150 Sam Roberts: So I was just saying, just replace Austin in a 3 0 5 with that zip.
491 00:49:17.800 ⇒ 00:49:18.580 Casie Aviles: Okay.
492 00:49:18.720 ⇒ 00:49:21.780 Sam Roberts: And just see if that makes the formula work in the other page.
493 00:49:34.880 ⇒ 00:49:37.580 Sam Roberts: Oh, it’s a string. It’s not a number anything.
494 00:49:51.730 ⇒ 00:49:52.440 Sam Roberts: Yeah.
495 00:49:53.780 ⇒ 00:49:56.160 Sam Roberts: Go back to your test cell. Real quick.
496 00:50:00.610 ⇒ 00:50:01.456 Casie Aviles: Oh, that’s
497 00:50:02.100 ⇒ 00:50:03.180 Sam Roberts: Yeah, just.
498 00:50:03.180 ⇒ 00:50:03.890 Casie Aviles: This one.
499 00:50:04.100 ⇒ 00:50:08.230 Sam Roberts: No, no, no! Go back to the one where we so we did that. And then where are you confirming how that would work?
500 00:50:08.690 ⇒ 00:50:16.420 Sam Roberts: Yeah. Get rid of the quotes around 7, 8, 7, 3, 2, yeah. There you go.
501 00:50:17.000 ⇒ 00:50:18.070 Uttam Kumaran: Okay.
502 00:50:18.800 ⇒ 00:50:26.339 Sam Roberts: So I think the issue here is well, one. There is a blank cell there, so that is returning correct, because if you go over to
503 00:50:26.510 ⇒ 00:50:28.529 Sam Roberts: in row 3 0, 5, right
504 00:50:28.710 ⇒ 00:50:31.059 Sam Roberts: under residential tree. Is that empty.
505 00:50:34.150 ⇒ 00:50:35.240 Uttam Kumaran: Shouldn’t be.
506 00:50:35.570 ⇒ 00:50:36.320 Sam Roberts: Hmm.
507 00:50:36.700 ⇒ 00:50:37.650 Uttam Kumaran: Well.
508 00:50:37.650 ⇒ 00:50:38.970 Sam Roberts: Office, commercial.
509 00:50:38.970 ⇒ 00:50:44.869 Uttam Kumaran: No, no, but those are. Those are not. Those are. Those are not the right headers like, I’m gonna unfreeze these headers.
510 00:50:45.000 ⇒ 00:50:45.760 Uttam Kumaran: or like.
511 00:50:45.760 ⇒ 00:50:46.479 Sam Roberts: Oh, interesting!
512 00:50:46.480 ⇒ 00:50:48.290 Uttam Kumaran: Those headers are not accurate.
513 00:50:48.860 ⇒ 00:50:53.889 Sam Roberts: Okay, okay, that’s that’s but yeah, I think the issue here is that Vlookup is doing.
514 00:50:54.020 ⇒ 00:51:02.129 Sam Roberts: I’ll look up through that list of branches because it does. If you see vertical, look up, searches down the 1st column of a range.
515 00:51:03.830 ⇒ 00:51:05.999 Sam Roberts: So if you go back to the tree table.
516 00:51:06.250 ⇒ 00:51:10.399 Uttam Kumaran: Oh, well, there’s multiple records for 7, 8, 7, 3, 3.
517 00:51:11.000 ⇒ 00:51:12.819 Uttam Kumaran: That’s the problem. Right?
518 00:51:14.780 ⇒ 00:51:21.540 Sam Roberts: no, I think the problem. Well, that’s that’s another problem. I think the 1st problem here is that it’s searching down this column column a
519 00:51:22.730 ⇒ 00:51:27.799 Sam Roberts: where. It’s just Austin. So I think if you can make the Zip codes the 1st column of tree table.
520 00:51:28.040 ⇒ 00:51:30.918 Uttam Kumaran: Well, this is what I if you go to. If you go to
521 00:51:32.320 ⇒ 00:51:36.520 Uttam Kumaran: what I just did in my cell, you can see it. What I fix.
522 00:51:36.520 ⇒ 00:51:37.889 Sam Roberts: Yeah, where are you?
523 00:51:37.890 ⇒ 00:51:43.080 Sam Roberts: But what this is looking for now is 7, 8, 7, 7, 8, 7, 3, 3.
524 00:51:44.088 ⇒ 00:51:46.179 Uttam Kumaran: And this is looking for
525 00:51:48.942 ⇒ 00:51:53.330 Uttam Kumaran: commercial tree, because it’s column 3
526 00:51:54.320 ⇒ 00:52:07.709 Uttam Kumaran: right? So click in that. So see 3. So so if I was to go change this to 4. Now, the problem you’re gonna have is, there is no value for the 1st record of 7, 8, 7, 3, 3, column 4 is empty. So this is accurate.
527 00:52:08.030 ⇒ 00:52:17.249 Uttam Kumaran: So what what we need to do is we need to find a way for it to get to basically get all values for 7, 8, 7, 3, 3,
528 00:52:17.650 ⇒ 00:52:21.910 Uttam Kumaran: and then make comma separate them right into an array.
529 00:52:24.560 ⇒ 00:52:27.189 Uttam Kumaran: It’s empty because the first.st
530 00:52:27.190 ⇒ 00:52:29.060 Sam Roberts: Yeah, there.
531 00:52:29.060 ⇒ 00:52:30.640 Uttam Kumaran: And it is empty.
532 00:52:31.530 ⇒ 00:52:32.799 Sam Roberts: Want, something like built in.
533 00:52:32.800 ⇒ 00:52:39.819 Uttam Kumaran: There are multiple values for 7, 8, 7, 3, 3. And
534 00:52:40.320 ⇒ 00:52:45.969 Uttam Kumaran: there are multiple rows for 7, 8, 7, 3, 3 rows, 4, 7, 8, 7, 3, 3.
535 00:52:48.500 ⇒ 00:52:49.450 Uttam Kumaran: See?
536 00:52:51.010 ⇒ 00:52:56.940 Uttam Kumaran: 3. K, this not. Michelle’s below.
537 00:53:02.640 ⇒ 00:53:04.939 Uttam Kumaran: Okay, let’s see what it says to do.
538 00:53:08.850 ⇒ 00:53:10.330 Uttam Kumaran: Okay.
539 00:53:28.140 ⇒ 00:53:28.930 Sam Roberts: Understand?
540 00:53:35.990 ⇒ 00:53:36.950 Sam Roberts: Yeah.
541 00:53:39.810 ⇒ 00:53:42.699 Uttam Kumaran: And yeah, so you’re close.
542 00:53:43.700 ⇒ 00:53:48.970 Sam Roberts: And then we want to get just which row here. The to the Jonathan Hurst, Jonathan Hurst, Brad Paxton, list.
543 00:53:48.970 ⇒ 00:53:52.679 Uttam Kumaran: Well, but look at, look at my function in 8. I think this is.
544 00:53:53.590 ⇒ 00:53:58.200 Sam Roberts: Yes, there you go. Okay, yep. Yep, yep. Yep. Yeah. Sorry
545 00:53:58.910 ⇒ 00:54:00.259 Uttam Kumaran: No, that’s fine. So basically.
546 00:54:00.260 ⇒ 00:54:01.219 Sam Roberts: It’s not.
547 00:54:01.220 ⇒ 00:54:01.800 Uttam Kumaran: Yeah.
548 00:54:01.800 ⇒ 00:54:05.940 Sam Roberts: It’s only giving Brad Paxton right.
549 00:54:05.940 ⇒ 00:54:07.400 Uttam Kumaran: That’s right, though.
550 00:54:07.730 ⇒ 00:54:11.869 Sam Roberts: Oh, we don’t want Jonathan. Oh, cause he’s in that column. Sorry I was looking at the wrong column. You’re good.
551 00:54:11.870 ⇒ 00:54:19.719 Uttam Kumaran: Yeah, right? So your data shows that we only want Brad. But, for example, if I was to change this to a commercial tree.
552 00:54:22.650 ⇒ 00:54:24.309 Uttam Kumaran: we should get all 3.
553 00:54:24.490 ⇒ 00:54:25.330 Sam Roberts: Boom, yep.
554 00:54:25.330 ⇒ 00:54:29.000 Uttam Kumaran: But the problem here is, these are all coming in. Oh, yeah, yeah, yeah. So.
555 00:54:29.000 ⇒ 00:54:32.750 Sam Roberts: You may. Wanna, yeah.
556 00:54:33.790 ⇒ 00:54:41.520 Uttam Kumaran: Okay, so let’s talk about what the solution is for the master inspectorship. So one is these.
557 00:54:43.240 ⇒ 00:54:50.270 Uttam Kumaran: we need to edit these V lookups because what you’re probably getting now is you’re just you’re actually just gonna get the 1st
558 00:54:51.890 ⇒ 00:54:52.880 Uttam Kumaran: value.
559 00:54:53.160 ⇒ 00:54:54.970 Uttam Kumaran: So Casey, can I share.
560 00:54:54.970 ⇒ 00:54:55.410 Casie Aviles: Okay.
561 00:54:55.410 ⇒ 00:55:00.649 Uttam Kumaran: I’ll just maybe see how we can close this out. So
562 00:55:02.183 ⇒ 00:55:06.820 Uttam Kumaran: like, let’s go back to 7, 8, 7, 3, 3.
563 00:55:07.150 ⇒ 00:55:14.280 Uttam Kumaran: Let’s talk about residential residential tree.
564 00:55:14.500 ⇒ 00:55:15.520 Uttam Kumaran: Great.
565 00:55:15.780 ⇒ 00:55:24.280 Uttam Kumaran: So let’s so all of these seem to be manual. So what we’re gonna find is
566 00:55:25.100 ⇒ 00:55:30.479 Uttam Kumaran: for residential tree for 7, 8, 7, 3, 3. What we actually want?
567 00:55:32.150 ⇒ 00:55:36.560 Uttam Kumaran: Is something like.
568 00:55:41.410 ⇒ 00:55:45.940 Uttam Kumaran: okay. So I guess, let me see how I can best make this work. So
569 00:55:47.500 ⇒ 00:55:52.810 Uttam Kumaran: I’m trying to think about like how I can build this filter using the this. Now you know.
570 00:55:53.374 ⇒ 00:55:57.289 Sam Roberts: Yeah. What do you hold on trying to remember that? So you wanted to put in
571 00:55:59.651 ⇒ 00:56:05.110 Sam Roberts: table commercial? Oh, that’s what the match was for. Maybe you aren’t able to build that name.
572 00:56:05.110 ⇒ 00:56:06.379 Uttam Kumaran: Oh, okay. Okay.
573 00:56:06.380 ⇒ 00:56:08.220 Sam Roberts: That’s why you have to have the match.
574 00:56:08.740 ⇒ 00:56:13.760 Sam Roberts: But no, we’re using filter now. So that’s a different range, though, and.
575 00:56:14.940 ⇒ 00:56:17.880 Uttam Kumaran: Yeah, let me let me ask chat. Let’s see.
576 00:56:17.880 ⇒ 00:56:24.779 Sam Roberts: Yeah, it’s gotta be another. Because I I with the named ranges. It’s fine. But if we try to build that name range I don’t know how that works
577 00:56:24.960 ⇒ 00:56:25.790 Sam Roberts: to the app.
578 00:56:26.190 ⇒ 00:56:27.030 Sam Roberts: We’ll chat.
579 00:56:32.300 ⇒ 00:56:33.970 Uttam Kumaran: Okay. So
580 00:56:43.240 ⇒ 00:56:44.289 Uttam Kumaran: if we try.
581 00:56:44.290 ⇒ 00:56:48.470 Sam Roberts: Oh, okay, I guess. What was the original intention. Yeah.
582 00:56:58.720 ⇒ 00:57:02.080 Uttam Kumaran: Okay. Well, this is accurate, but it’s
583 00:57:05.460 ⇒ 00:57:08.719 Sam Roberts: Well, that’s residential, not you’re looking for residential.
584 00:57:08.720 ⇒ 00:57:10.780 Uttam Kumaran: Oh, yeah, so.
585 00:57:21.940 ⇒ 00:57:29.719 Uttam Kumaran: okay, so this is working. Now, I mean, my, probably my only thing is that commercial tree here
586 00:57:30.330 ⇒ 00:57:35.459 Uttam Kumaran: still doesn’t have anybody. Because, oh, this one!
587 00:57:39.130 ⇒ 00:57:48.670 Uttam Kumaran: Wait! What commercial tree like! Why is this one?
588 00:57:49.090 ⇒ 00:57:51.559 Uttam Kumaran: Oh, coast company, commercial!
589 00:57:52.890 ⇒ 00:57:58.470 Uttam Kumaran: Wait! This is pulling from the commercial inspectors table. And this was pulling from the residential tree.
590 00:57:58.680 ⇒ 00:58:03.800 Uttam Kumaran: Oh, but the residential tree! There are commercials. Oh, wait! What?
591 00:58:05.940 ⇒ 00:58:11.190 Uttam Kumaran: So? Where does Brad? Where does someone like Jonathan Hurst end up here?
592 00:58:12.900 ⇒ 00:58:16.630 Sam Roberts: Jonathan Hirst should be on the commercial tree list.
593 00:58:16.630 ⇒ 00:58:17.060 Casie Aviles: Yes. Okay.
594 00:58:17.060 ⇒ 00:58:18.909 Sam Roberts: According to the tree table. If you.
595 00:58:18.910 ⇒ 00:58:19.280 Uttam Kumaran: There!
596 00:58:19.280 ⇒ 00:58:20.529 Sam Roberts: Commercial tree list.
597 00:58:21.960 ⇒ 00:58:25.079 Sam Roberts: No, according to the tree table on the other sheet.
598 00:58:25.080 ⇒ 00:58:25.540 Sam Roberts: Yes.
599 00:58:25.540 ⇒ 00:58:34.999 Sam Roberts: doing the look up so he should be listed on that commercial tree. But I don’t know what that other yeah. But what is that other? What is what are these other named ranges here? Commercial inspectors table?
600 00:58:37.610 ⇒ 00:58:40.290 Sam Roberts: Where’s that one leave? Is that.
601 00:58:40.290 ⇒ 00:58:44.349 Uttam Kumaran: What is commercial inspectors table. And then what is this one, this tree table.
602 00:58:48.353 ⇒ 00:58:58.719 Casie Aviles: Commercial inspectors table. I think this is yeah. This is for commercial only, like I I think this is all, all of the inspectors. But under commercial.
603 00:59:02.440 ⇒ 00:59:06.379 Uttam Kumaran: But the other. The tree table also has commercial.
604 00:59:07.380 ⇒ 00:59:10.370 Casie Aviles: Yeah, I think that’s that’s how they formatted it.
605 00:59:12.000 ⇒ 00:59:15.420 Uttam Kumaran: But what we’re seeing is that there’s nobody like.
606 00:59:15.990 ⇒ 00:59:19.900 Uttam Kumaran: Jonathan Hurst is a commercial and person.
607 00:59:20.550 ⇒ 00:59:21.530 Uttam Kumaran: But
608 00:59:22.060 ⇒ 00:59:28.729 Uttam Kumaran: he’s not in this list. Okay, that’s maybe something to think about. But let’s, I’ll just move past that for now solve this.
609 00:59:29.370 ⇒ 00:59:34.499 Uttam Kumaran: So it’s my only point is that.
610 00:59:35.590 ⇒ 00:59:37.999 Sam Roberts: Oh, it’s a different to be able to.
611 00:59:40.570 ⇒ 00:59:43.240 Sam Roberts: And tree. Oh, okay.
612 01:00:24.230 ⇒ 01:00:32.599 Casie Aviles: Yeah, that’s that’s what is a bit confusing from the original ones, because they have, like a dedicated commercial sheet
613 01:00:34.270 ⇒ 01:00:40.249 Casie Aviles: which should contain all the commercial, the the inspectors under commercial. But then they have
614 01:00:41.379 ⇒ 01:00:46.550 Casie Aviles: a a sheet, a tree sheet, and it has both residential and commercial people.
615 01:00:48.550 ⇒ 01:00:52.800 Uttam Kumaran: Okay, yeah, I can ask them about that. I guess I think I’ve got it. So
616 01:00:53.010 ⇒ 01:00:54.801 Uttam Kumaran: if we go to
617 01:00:59.870 ⇒ 01:01:04.360 Uttam Kumaran: like Jesse Boyer is not even in the tree page.
618 01:01:06.700 ⇒ 01:01:07.420 Casie Aviles: Yeah.
619 01:01:07.980 ⇒ 01:01:09.710 Sam Roberts: Yeah, somehow, that just got overwritten.
620 01:01:09.860 ⇒ 01:01:12.055 Uttam Kumaran: So if like, for example, if I’m too.
621 01:01:13.890 ⇒ 01:01:16.339 Uttam Kumaran: this is this seems more accurate.
622 01:01:17.650 ⇒ 01:01:19.609 Sam Roberts: Yeah, you might just want to wrap it with the.
623 01:01:20.070 ⇒ 01:01:23.806 Uttam Kumaran: Yeah, so let’s wrap. Let’s wrap it with the Fna.
624 01:01:44.800 ⇒ 01:01:49.020 Uttam Kumaran: okay, so I’m gonna drag this. Can you guys verify a couple more of these.
625 01:01:51.820 ⇒ 01:01:53.619 Uttam Kumaran: and just pick any random one and.
626 01:01:53.620 ⇒ 01:01:54.490 Sam Roberts: But yeah.
627 01:01:55.810 ⇒ 01:01:59.401 Mustafa Raja: Yeah. The one more issue is that
628 01:01:59.850 ⇒ 01:02:00.430 Amber Lin: Sorry.
629 01:02:00.430 ⇒ 01:02:01.100 Mustafa Raja: And.
630 01:02:01.390 ⇒ 01:02:06.139 Amber Lin: Can I use this meeting? Link? I have eaten grooming.
631 01:02:06.380 ⇒ 01:02:07.600 Uttam Kumaran: Oh, yeah. Yeah. Yeah. Yeah.
632 01:02:07.800 ⇒ 01:02:08.470 Amber Lin: They’re one.
633 01:02:08.470 ⇒ 01:02:09.699 Uttam Kumaran: I’ll send another one.
634 01:02:09.700 ⇒ 01:02:11.269 Amber Lin: Okay, I appreciate it.
635 01:02:11.270 ⇒ 01:02:12.090 Uttam Kumaran: Okay. Alright. Thanks.