Meeting Title: ABC | Backlog Grooming Date: 2025-06-04 Meeting participants: Amber Lin, Casie Aviles
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1 00:00:23.590 ⇒ 00:00:24.590 Casie Aviles: Hey! Amber.
2 00:00:25.110 ⇒ 00:00:26.360 Amber Lin: Hello.
3 00:00:28.189 ⇒ 00:00:34.779 Amber Lin: I am looking at our linear, and I’m trying to figure out what we want to do for next cycle.
4 00:00:38.900 ⇒ 00:00:40.260 Amber Lin: Let’s see?
5 00:00:42.830 ⇒ 00:00:44.290 Amber Lin: That’s all of these.
6 00:00:44.570 ⇒ 00:00:45.460 Amber Lin: Yeah.
7 00:00:46.110 ⇒ 00:00:49.574 Amber Lin: And this is, gonna take a little bit longer.
8 00:00:53.380 ⇒ 00:01:00.630 Amber Lin: Okay, blah blah, that is, oh, oops!
9 00:01:10.340 ⇒ 00:01:13.250 Casie Aviles: Were you in a meeting with the client just before this.
10 00:01:14.640 ⇒ 00:01:18.829 Amber Lin: I wanted to. I stayed there. She did not come so. Oh, well.
11 00:01:19.140 ⇒ 00:01:19.620 Casie Aviles: Okay.
12 00:01:20.100 ⇒ 00:01:28.249 Amber Lin: It has been happening quite a few times like. And also I cause I was just in New York. And now I’m in Chicago, and I was like
13 00:01:28.680 ⇒ 00:01:39.380 Amber Lin: I have until 9, 30. And then I checked my phone. I was like, Oh, no, my meetings at 8 30. So I I literally climbed out of bed at 8 31,
14 00:01:39.520 ⇒ 00:01:45.205 Amber Lin: and then scrambled onto the meeting. And then she wasn’t there. I was like, Oh, never mind.
15 00:01:45.540 ⇒ 00:01:48.821 Casie Aviles: Yeah. Must be crazy. Constantly switching times.
16 00:01:49.290 ⇒ 00:01:50.390 Amber Lin: Know, I know, but
17 00:01:50.810 ⇒ 00:02:01.170 Amber Lin: this I haven’t traveled for 2 years. So this is this is what I wanted to do, but a little hard to manage to be very honest.
18 00:02:02.000 ⇒ 00:02:02.660 Casie Aviles: Yeah.
19 00:02:02.860 ⇒ 00:02:12.970 Amber Lin: Yeah, just checking on a few things.
20 00:02:13.799 ⇒ 00:02:20.370 Amber Lin: I know. Tim got back on the another trainer bought in the Google Workspace.
21 00:02:20.490 ⇒ 00:02:22.720 Amber Lin: What’s the update on that.
22 00:02:24.400 ⇒ 00:02:28.130 Casie Aviles: Yeah, I did send an email to him. And he did respond.
23 00:02:28.250 ⇒ 00:02:28.810 Amber Lin: Hmm.
24 00:02:29.277 ⇒ 00:02:33.479 Casie Aviles: But since then I he hasn’t replied yet.
25 00:02:33.480 ⇒ 00:02:39.190 Amber Lin: I see. So he, I think, he responded. I remember he was a little bit confused, and then he just.
26 00:02:39.190 ⇒ 00:02:39.580 Casie Aviles: Years.
27 00:02:39.580 ⇒ 00:02:42.449 Amber Lin: On it yet. Okay, sounds good.
28 00:02:43.660 ⇒ 00:02:53.055 Amber Lin: Oh, I think for today, for today. Oh, the input restrictions
29 00:02:53.720 ⇒ 00:03:01.569 Casie Aviles: Oh, okay, yeah. I’ll just. I’ll close this out today. I just didn’t finish my testing. But I did.
30 00:03:01.570 ⇒ 00:03:04.870 Amber Lin: Oh, oh, oh, awesome. Yeah, awesome.
31 00:03:05.480 ⇒ 00:03:06.520 Amber Lin: And
32 00:03:09.590 ⇒ 00:03:26.949 Amber Lin: yeah, with the oh, by the way, buttons, I know that so essentially 2 issues one, the main issue is that it doesn’t create anything right now. And then. Another nice thing that we can do is to link it to the central talk. So I don’t know if
33 00:03:27.777 ⇒ 00:03:31.510 Amber Lin: if we can finish this today, do you think we can do that?
34 00:03:31.810 ⇒ 00:03:37.659 Casie Aviles: I added some, I’m sorry. Yeah, I added some comments at the bottom.
35 00:03:38.310 ⇒ 00:03:39.665 Amber Lin: Hmm, yes.
36 00:03:41.110 ⇒ 00:03:49.990 Casie Aviles: Although I’m I’m I’m not sure what fixed it. I was just testing. And then it worked. But I need to investigate. I need to investigate. Why.
37 00:03:50.200 ⇒ 00:03:57.923 Amber Lin: Okay, okay, sounds good. You know. The other problem is that everything we do it gives a mosquito offer.
38 00:03:59.020 ⇒ 00:03:59.750 Casie Aviles: Oh!
39 00:03:59.750 ⇒ 00:04:03.690 Amber Lin: Yeah, like, I think I think
40 00:04:03.920 ⇒ 00:04:08.228 Amber Lin: it’s just I don’t. I don’t know. I’m just gonna note it down
41 00:04:12.340 ⇒ 00:04:14.999 Casie Aviles: Yeah, I, I’m using this prompt. So.
42 00:04:15.000 ⇒ 00:04:15.570 Amber Lin: Hmm.
43 00:04:15.570 ⇒ 00:04:19.750 Casie Aviles: Is this? Is this accurate? Is this the one that we’re going to use for? Now.
44 00:04:19.750 ⇒ 00:04:22.240 Amber Lin: Oh, let me check!
45 00:04:23.950 ⇒ 00:04:26.060 Casie Aviles: Like at least the the upsell options.
46 00:04:35.940 ⇒ 00:04:55.210 Amber Lin: I see. So the following cause, we have 2 places to create. Oh, by the ways, right? So there is a place to just do it in the message, and there is a place to do it in the button. Is this prompt? Where does it? Which place does it relate to.
47 00:04:56.188 ⇒ 00:04:57.780 Casie Aviles: It’s per the button. Yeah.
48 00:04:58.669 ⇒ 00:05:02.070 Amber Lin: But and
49 00:05:09.940 ⇒ 00:05:15.280 Amber Lin: I see, yeah, I mean.
50 00:05:15.780 ⇒ 00:05:22.139 Amber Lin: is this currently connected to somewhere in the in the central talk?
51 00:05:22.980 ⇒ 00:05:24.430 Amber Lin: Not yet. Right?
52 00:05:25.130 ⇒ 00:05:34.260 Casie Aviles: No, no, so so what’s what’s the goal, I guess. Do we want to read from the Central Doc for the oh, by the ways.
53 00:05:34.640 ⇒ 00:05:36.169 Amber Lin: I believe so. Yes.
54 00:05:36.820 ⇒ 00:05:45.549 Amber Lin: so I think we should create a specific section. Do you think that will make it really really slow? Should we make another spreadsheet.
55 00:05:46.980 ⇒ 00:05:48.520 Casie Aviles: I mean, I think.
56 00:05:49.600 ⇒ 00:06:00.950 Casie Aviles: Well, I guess there’s 2 things such as I’m thinking about, because I I would prefer if there’s like a separate list for the oh, by the way, that the bot will just get from.
57 00:06:01.140 ⇒ 00:06:02.439 Casie Aviles: But then
58 00:06:02.870 ⇒ 00:06:09.150 Casie Aviles: I guess we need to link it, consolidate it within their within the spreadsheet that they already have.
59 00:06:10.830 ⇒ 00:06:14.190 Casie Aviles: We don’t want the in the context to be scattered. It.
60 00:06:14.190 ⇒ 00:06:22.900 Amber Lin: Yeah. Yeah. I mean, we’re sourcing stuff from, you know the spreadsheet hub. They also have quite a I think.
61 00:06:24.420 ⇒ 00:06:27.610 Amber Lin: Do you think it’ll be better if we make this as a spreadsheet.
62 00:06:30.012 ⇒ 00:06:33.340 Casie Aviles: For the list of oh, by the ways the offers.
63 00:06:33.340 ⇒ 00:06:35.070 Amber Lin: Yeah, yeah, I think we.
64 00:06:35.070 ⇒ 00:06:36.630 Casie Aviles: We could try that. Yeah, we could.
65 00:06:36.630 ⇒ 00:06:40.590 Amber Lin: Okay, do you think? Then we have this.
66 00:06:40.770 ⇒ 00:06:52.550 Amber Lin: say, spreadsheet hub, maybe we just create another another one, because that’s also where the feedback goes to. So we create a separate spreadsheet in that document. Do you think that’s okay?
67 00:06:53.320 ⇒ 00:06:55.010 Casie Aviles: Yes, yes, I I can do that.
68 00:06:55.490 ⇒ 00:06:55.850 Amber Lin: Okay.
69 00:06:57.170 ⇒ 00:07:03.749 Casie Aviles: And then the list. We’ll get that still from the Central Doc to generate the offers.
70 00:07:06.170 ⇒ 00:07:08.280 Amber Lin: What do you mean by that.
71 00:07:08.750 ⇒ 00:07:10.749 Casie Aviles: Oh, I I mean like.
72 00:07:10.970 ⇒ 00:07:19.510 Casie Aviles: so I’m going to create a sheet right for the offers. And then where will I get that from the do I get that from the central dock like? Do I.
73 00:07:19.510 ⇒ 00:07:32.459 Amber Lin: Oh, I see they don’t have it in a central doc yet. It’s in everything. I think everything we have is in the oh, by the way, quick! Offer, Doc, that I attached in a linear ticket.
74 00:07:33.260 ⇒ 00:07:36.760 Casie Aviles: Oh, so okay, so that’s the same thing I’m using for the prompt.
75 00:07:37.300 ⇒ 00:07:43.759 Amber Lin: I think so. Yeah, I I think we just use like, for each line will be a different line in the
76 00:07:45.190 ⇒ 00:07:49.039 Amber Lin: like. Maybe a line in the spreadsheet. Perhaps.
77 00:07:49.740 ⇒ 00:07:50.579 Casie Aviles: Yes. Okay. Sure.
78 00:07:50.580 ⇒ 00:07:51.190 Amber Lin: Yeah.
79 00:07:51.970 ⇒ 00:07:53.780 Casie Aviles: And then they will just update that right.
80 00:07:53.780 ⇒ 00:07:55.210 Amber Lin: I think so. Yes.
81 00:07:55.930 ⇒ 00:07:56.959 Casie Aviles: Okay. Then, yeah.
82 00:07:58.020 ⇒ 00:08:06.270 Amber Lin: So I think right now we’re only dealing with the oh, oh, by the way, a button
83 00:08:10.620 ⇒ 00:08:21.360 Amber Lin: If you’re sure that it will work. I I would like to send a screenshot to the team, but I know we haven’t. I figured out what went wrong, so I would wait a little bit.
84 00:08:21.860 ⇒ 00:08:25.489 Casie Aviles: Yeah, I’ll I’ll try to. Yeah. I’ll I’ll figure it out first, st because.
85 00:08:25.490 ⇒ 00:08:26.110 Amber Lin: Hmm.
86 00:08:26.810 ⇒ 00:08:29.489 Casie Aviles: Yeah, if we give it to them, and then it doesn’t work. Then.
87 00:08:29.490 ⇒ 00:08:30.115 Amber Lin: Oops!
88 00:08:30.740 ⇒ 00:08:31.100 Casie Aviles: Yeah.
89 00:08:31.890 ⇒ 00:08:35.480 Amber Lin: Okay, okay, sounds good. So I think we’re.
90 00:08:36.260 ⇒ 00:08:40.020 Amber Lin: we’re going to link in spread.
91 00:08:41.270 ⇒ 00:08:42.480 Amber Lin: It’s.
92 00:08:43.570 ⇒ 00:08:44.920 Amber Lin: And so I think,
93 00:08:48.360 ⇒ 00:08:56.381 Amber Lin: yeah. And I, I can clarify with them if they want to show more than one, because right now it seems like they’re
94 00:08:57.490 ⇒ 00:09:00.820 Amber Lin: They’re only showing the mosquitoes.
95 00:09:03.120 ⇒ 00:09:03.780 Casie Aviles: Hmm, okay.
96 00:09:03.780 ⇒ 00:09:12.933 Amber Lin: Oh, probably because in our prompt we said it should only be related to the customer’s message, and the customer is asking about pest, and hence why, we
97 00:09:14.246 ⇒ 00:09:14.839 Casie Aviles: Yeah. Yeah.
98 00:09:14.840 ⇒ 00:09:15.180 Amber Lin: Yeah.
99 00:09:15.180 ⇒ 00:09:15.700 Casie Aviles: Yeah, that’s right.
100 00:09:15.700 ⇒ 00:09:20.369 Amber Lin: Offer mosquito, do you think? Because for the button like.
101 00:09:20.950 ⇒ 00:09:27.769 Amber Lin: do you think we should just generate a list of oh, by the ways like, just give them a list of current ones.
102 00:09:32.390 ⇒ 00:09:42.059 Casie Aviles: I think I mean, we could do that. I’m just not like I’m just thinking of, like, you know, the the readability. And maybe it’s gonna generate a long list.
103 00:09:46.810 ⇒ 00:09:53.989 Casie Aviles: That’s why I that’s why I was thinking it should be relevant to the prompt. But then, yeah, that’s a problem. If they just ask about that.
104 00:09:53.990 ⇒ 00:10:03.357 Amber Lin: Yeah, I I think when they I remember from my visit to them. So, for example, window and say,
105 00:10:04.150 ⇒ 00:10:05.425 Amber Lin: what is it
106 00:10:06.600 ⇒ 00:10:16.790 Amber Lin: like these window lawn, etc. It’s pretty basic. And it doesn’t really have to be related to what the customer is needing. It’s just.
107 00:10:16.790 ⇒ 00:10:17.370 Casie Aviles: Is.
108 00:10:17.370 ⇒ 00:10:20.960 Amber Lin: Most people would need it. And so
109 00:10:21.440 ⇒ 00:10:30.920 Amber Lin: maybe we can. I don’t know how difficult it would be for our site, but if we have the spreadsheet. We can just change your prompt to say, like, just
110 00:10:31.330 ⇒ 00:10:38.049 Amber Lin: list out everything, but just format it nicely. But we can still list out everything like. If we.
111 00:10:38.510 ⇒ 00:10:41.460 Amber Lin: if we remove the restrictions.
112 00:10:42.430 ⇒ 00:10:43.230 Casie Aviles: Okay. Yeah.
113 00:10:43.230 ⇒ 00:10:48.859 Amber Lin: Like maybe we can pick like I don’t know. Like 3.
114 00:10:49.840 ⇒ 00:10:52.650 Casie Aviles: Yeah, yeah, that makes sense. We can start with that. So.
115 00:10:52.650 ⇒ 00:10:56.259 Amber Lin: Yeah. Okay, pick 3.
116 00:10:57.380 ⇒ 00:10:58.760 Amber Lin: Oh.
117 00:11:09.074 ⇒ 00:11:10.289 Amber Lin: there you go.
118 00:11:11.340 ⇒ 00:11:13.229 Amber Lin: Sorry noting it down.
119 00:11:16.320 ⇒ 00:11:19.040 Amber Lin: Okay, sounds good.
120 00:11:20.280 ⇒ 00:11:23.860 Amber Lin: And then so that’s in progress.
121 00:11:30.470 ⇒ 00:11:33.480 Amber Lin: alright anything.
122 00:11:33.970 ⇒ 00:11:38.639 Amber Lin: Okay? Let’s see, looking at the to-dos and cycle.
123 00:11:39.820 ⇒ 00:11:41.189 Amber Lin: Okay, I think we’re.
124 00:11:41.540 ⇒ 00:11:46.249 Amber Lin: I think we’re fine. With that I need to do the reformatting for the Central Doc Oops.
125 00:11:46.800 ⇒ 00:11:48.750 Amber Lin: but I haven’t done that yet.
126 00:11:50.306 ⇒ 00:11:53.610 Amber Lin: Next ready for development.
127 00:11:57.230 ⇒ 00:12:00.440 Amber Lin: Oh, I think
128 00:12:02.250 ⇒ 00:12:09.570 Amber Lin: I think doing that will change. Let me just share. Oh, I mean, I am sharing my screen. I think that will just change this
129 00:12:10.250 ⇒ 00:12:11.130 Amber Lin: right.
130 00:12:13.958 ⇒ 00:12:19.439 Casie Aviles: Yes, so this would be the the, I guess. This also. This also related to that previous ticket. Then.
131 00:12:22.700 ⇒ 00:12:24.890 Amber Lin: Over the offers.
132 00:12:26.950 ⇒ 00:12:36.020 Amber Lin: I’m just gonna change to ticket, yeah, let me say.
133 00:12:36.980 ⇒ 00:12:44.019 Amber Lin: I think this is just relate because there’s 2 things right? There’s the old button. And this is in the response
134 00:12:47.120 ⇒ 00:12:51.870 Amber Lin: and think, phone.
135 00:12:53.460 ⇒ 00:12:55.969 Amber Lin: Let me copy that over.
136 00:13:01.960 ⇒ 00:13:03.240 Amber Lin: Oh.
137 00:13:09.310 ⇒ 00:13:10.165 Amber Lin: yeah,
138 00:13:11.580 ⇒ 00:13:19.409 Amber Lin: When I was looking, because this one. We have 2 things right? So we have related, or to other services.
139 00:13:19.980 ⇒ 00:13:31.000 Amber Lin: and offers alright. And then, do you see everything it says? It just says Mosquito, and
140 00:13:31.630 ⇒ 00:13:36.100 Amber Lin: I don’t think this is. I think this is for next cycle. But I was just thinking about
141 00:13:37.980 ⇒ 00:13:40.180 Amber Lin: no worries. Where’s the other ticket
142 00:13:43.170 ⇒ 00:13:49.090 Amber Lin: like these are the current services I think they have, and
143 00:13:50.490 ⇒ 00:13:52.700 Amber Lin: think it’ll be nice if we
144 00:14:00.720 ⇒ 00:14:12.189 Amber Lin: say these services right are like all possible. I guess all possible things that they can.
145 00:14:12.520 ⇒ 00:14:13.930 Amber Lin: They can do.
146 00:14:15.955 ⇒ 00:14:21.200 Casie Aviles: Okay, so so these are things that.
147 00:14:21.940 ⇒ 00:14:22.430 Amber Lin: Yeah.
148 00:14:22.430 ⇒ 00:14:23.790 Casie Aviles: We want to generate.
149 00:14:24.190 ⇒ 00:14:24.980 Amber Lin: You should do it.
150 00:14:24.980 ⇒ 00:14:25.580 Casie Aviles: Degenerate.
151 00:14:25.580 ⇒ 00:14:26.870 Amber Lin: Don’t really know what.
152 00:14:27.380 ⇒ 00:14:29.789 Amber Lin: I just looked at it closely.
153 00:14:29.900 ⇒ 00:14:34.209 Amber Lin: I don’t really know what this is. Give me a second
154 00:14:34.880 ⇒ 00:14:41.300 Amber Lin: like this is somewhat related, but it’s not completely related, because I think my point was that
155 00:14:42.590 ⇒ 00:14:48.289 Amber Lin: the oh, by the way, categories have offers, which in other
156 00:14:48.480 ⇒ 00:14:52.370 Amber Lin: this is this is what we’re doing with what they
157 00:14:52.950 ⇒ 00:15:04.210 Amber Lin: gave us. Right? This is in this and then potential. Other services will include all other
158 00:15:05.740 ⇒ 00:15:09.960 Amber Lin: ABC and come free services.
159 00:15:10.930 ⇒ 00:15:12.210 Amber Lin: Right? So.
160 00:15:15.590 ⇒ 00:15:16.900 Amber Lin: Does this make sense?
161 00:15:17.070 ⇒ 00:15:20.380 Amber Lin: And so I think, when we generate it in here.
162 00:15:21.120 ⇒ 00:15:30.580 Amber Lin: instead of only doing pest, I think we should have it logically relate to other things. So say.
163 00:15:34.130 ⇒ 00:15:37.550 Amber Lin: we should probably give it a list of.
164 00:15:38.310 ⇒ 00:15:48.199 Amber Lin: I guess we should list all ABC kind of the service areas
165 00:15:48.930 ⇒ 00:15:53.610 Amber Lin: list, all offers currently, which is done.
166 00:16:02.120 ⇒ 00:16:07.949 Amber Lin: and then we define logic when it should appear.
167 00:16:09.500 ⇒ 00:16:10.889 Amber Lin: And then
168 00:16:17.260 ⇒ 00:16:18.420 Amber Lin: and then
169 00:16:25.710 ⇒ 00:16:33.500 Amber Lin: so yeah, and then we should just test it.
170 00:16:36.100 ⇒ 00:16:39.149 Amber Lin: How does this sound like? Does this make sense.
171 00:16:41.409 ⇒ 00:16:43.999 Casie Aviles: I think I just. I guess I just need like.
172 00:16:44.790 ⇒ 00:16:49.319 Casie Aviles: And I guess an example like, how does it look like I’m I’m trying.
173 00:16:49.320 ⇒ 00:16:56.620 Amber Lin: I see I see it. Let me per example handful.
174 00:16:57.190 ⇒ 00:16:58.440 Amber Lin: So
175 00:17:02.890 ⇒ 00:17:13.000 Amber Lin: I guess they say we ask ask do we treat wasps?
176 00:17:13.520 ⇒ 00:17:22.460 Amber Lin: And he says, Yes, blah, blah, blah, blah blah separate line separate line. We’d say.
177 00:17:22.735 ⇒ 00:17:22.990 Casie Aviles: Yeah.
178 00:17:23.970 ⇒ 00:17:34.150 Amber Lin: Oh, by the way, since you, it’s somewhat like since you have, was, you might one
179 00:17:34.730 ⇒ 00:17:42.409 Amber Lin: to to. I don’t know. You might. It might be caused by you might need tree cleaning like we can give them some reason.
180 00:17:44.182 ⇒ 00:17:52.920 Amber Lin: We might want to do tree no like free cleaning.
181 00:17:53.640 ⇒ 00:17:54.850 Casie Aviles: Okay. Okay.
182 00:17:54.850 ⇒ 00:18:10.840 Amber Lin: Or gutter we need, because was those that causes pests and rodents
183 00:18:11.020 ⇒ 00:18:17.960 Amber Lin: like something like that. This is not. This is very poorly formatted. I bet AI will have something better to say.
184 00:18:18.110 ⇒ 00:18:24.610 Amber Lin: But essentially it’s you have this problem. It might be related to this, some other problem.
185 00:18:27.500 ⇒ 00:18:36.249 Amber Lin: Or like this is, let me let me categorize this. This is like logically related number one, right?
186 00:18:36.560 ⇒ 00:18:45.900 Amber Lin: A. G, you have passed test. Live in tree, clean tree.
187 00:18:46.110 ⇒ 00:18:54.830 Amber Lin: Okay. And then the second one would just be currently on sale promotion.
188 00:18:55.530 ⇒ 00:19:01.259 Amber Lin: And hence that would just be the list that they provided.
189 00:19:02.310 ⇒ 00:19:04.819 Amber Lin: I think there’s a like a march.
190 00:19:05.400 ⇒ 00:19:10.619 Amber Lin: Our offer list in somewhere. Let me go. I’ll go find that.
191 00:19:13.630 ⇒ 00:19:15.100 Amber Lin: Where is it?
192 00:19:15.910 ⇒ 00:19:16.820 Amber Lin: Test?
193 00:19:20.050 ⇒ 00:19:23.940 Amber Lin: So it’s all over the place.
194 00:19:28.556 ⇒ 00:19:30.840 Amber Lin: This clears things up, though.
195 00:19:30.840 ⇒ 00:19:32.770 Amber Lin: Yeah, yeah, I should have done this sooner.
196 00:19:35.690 ⇒ 00:19:41.860 Amber Lin: Amber find ABC offers.
197 00:19:43.170 ⇒ 00:19:58.370 Amber Lin: And then just common flea of sold services. Agency window cleaning is the
198 00:20:01.420 ⇒ 00:20:04.690 Amber Lin: regardless of what the customer.
199 00:20:06.500 ⇒ 00:20:16.920 Amber Lin: I think these are the main 3 categories that come across and.
200 00:20:16.920 ⇒ 00:20:17.310 Casie Aviles: Okay.
201 00:20:17.310 ⇒ 00:20:20.829 Amber Lin: Like I I guess we pick and choose. But
202 00:20:21.060 ⇒ 00:20:29.036 Amber Lin: at this moment I think if we just have at least have these, don’t I mean
203 00:20:30.140 ⇒ 00:20:36.959 Amber Lin: ask any questions if you need, and I will go ask the client. So just let me know what’s unclear. I will go clarify that.
204 00:20:38.020 ⇒ 00:20:39.620 Amber Lin: Yeah. So.
205 00:20:39.620 ⇒ 00:20:40.200 Casie Aviles: This.
206 00:20:40.940 ⇒ 00:20:46.539 Amber Lin: Yeah. Comment there, just tag. Ask me in slack. That will. Everything will be fine.
207 00:20:47.248 ⇒ 00:20:49.289 Amber Lin: So I think that’s for
208 00:20:49.860 ⇒ 00:20:55.649 Amber Lin: I have it for next cycle, cause it’s I think we do have a bit.
209 00:20:56.530 ⇒ 00:20:58.730 Amber Lin: We have this acronym wine
210 00:21:01.450 ⇒ 00:21:10.540 Amber Lin: We need to reformat it ideally. Put that in a workspace. I think we have decent amount for
211 00:21:11.280 ⇒ 00:21:15.259 Amber Lin: these 2 cycles. But definitely, this is something that’s coming up.
212 00:21:15.910 ⇒ 00:21:19.519 Amber Lin: I don’t know if we’re are we going to do this.
213 00:21:21.495 ⇒ 00:21:22.560 Casie Aviles: For next cycle.
214 00:21:22.820 ⇒ 00:21:23.690 Amber Lin: Yeah.
215 00:21:26.240 ⇒ 00:21:26.920 Casie Aviles: Hmm!
216 00:21:27.280 ⇒ 00:21:30.479 Casie Aviles: I think we can. We can do this. This is.
217 00:21:30.480 ⇒ 00:21:36.439 Amber Lin: It’s a. It’s a bit of work, though, if we do that for next cycle, I think that’s everything we’re gonna do for next cycle.
218 00:21:37.180 ⇒ 00:21:38.250 Casie Aviles: Oh!
219 00:21:38.410 ⇒ 00:21:44.470 Amber Lin: Right cause I like. I don’t know how long this would take you. This one, like, I think, currently.
220 00:21:44.470 ⇒ 00:21:44.910 Casie Aviles: Okay.
221 00:21:44.910 ⇒ 00:21:47.529 Amber Lin: We’re looking at this rate, let me know.
222 00:21:51.480 ⇒ 00:21:52.060 Amber Lin: Not good.
223 00:21:52.060 ⇒ 00:21:52.410 Casie Aviles: Yeah.
224 00:21:52.410 ⇒ 00:21:56.529 Amber Lin: We have it all list. Then we just adjust the prompting.
225 00:21:57.080 ⇒ 00:22:03.750 Casie Aviles: Yeah, I think it. It’s going to be mostly prompting and then just testing. So maybe.
226 00:22:03.750 ⇒ 00:22:04.420 Amber Lin: Hmm.
227 00:22:04.420 ⇒ 00:22:07.569 Casie Aviles: Yeah, as long as I have, like the the information that I need.
228 00:22:07.980 ⇒ 00:22:09.170 Casie Aviles: For for the bot.
229 00:22:09.730 ⇒ 00:22:11.730 Casie Aviles: So maybe around 3.
230 00:22:12.070 ⇒ 00:22:15.620 Amber Lin: Okay, let me go.
231 00:22:16.320 ⇒ 00:22:19.789 Amber Lin: Yeah, I’ll go grab those information.
232 00:22:20.300 ⇒ 00:22:21.749 Amber Lin: Let me note that down.
233 00:22:22.840 ⇒ 00:22:24.190 Amber Lin: Oh, crap!
234 00:22:29.270 ⇒ 00:22:30.100 Amber Lin: Great
235 00:22:32.540 ⇒ 00:22:43.960 Amber Lin: I think another one is really important. Not for this cycle. I incorporate other spreadsheets from chest.
236 00:22:44.320 ⇒ 00:22:51.500 Amber Lin: because you know the the pest department. Currently we only have one spreadsheet. We’re linking to right.
237 00:22:53.140 ⇒ 00:22:53.880 Casie Aviles: Yes.
238 00:22:54.120 ⇒ 00:22:58.710 Amber Lin: Yeah, it seems like when I visited, they have 3.
239 00:22:59.100 ⇒ 00:23:03.660 Amber Lin: Do you think we can manage having 3 spreadsheets linked to it?
240 00:23:05.610 ⇒ 00:23:12.506 Casie Aviles: To the bot. I guess I I want to see the spreadsheets first, st
241 00:23:13.930 ⇒ 00:23:16.880 Casie Aviles: I see. So it’s kind of similar to the one we have.
242 00:23:17.880 ⇒ 00:23:25.879 Amber Lin: And like the technician one, it’s it’s also multiple tabs. A little bit, not very clean
243 00:23:26.660 ⇒ 00:23:36.740 Amber Lin: and probably similar in size. And they’re kind of related. So they check one. They go to the other and then go check back, and they go check involved, and then they go check this.
244 00:23:37.540 ⇒ 00:23:40.859 Casie Aviles: Hmm, yeah, that’s gonna take some work.
245 00:23:40.860 ⇒ 00:23:51.080 Amber Lin: Yeah, okay, let me let me say this, gather spreadsheets and
246 00:23:52.485 ⇒ 00:23:55.889 Amber Lin: link, and I don’t know what’s gonna happen.
247 00:23:56.060 ⇒ 00:23:56.889 Casie Aviles: I need the money.
248 00:23:56.890 ⇒ 00:23:57.570 Casie Aviles: If I’d
249 00:23:58.360 ⇒ 00:24:06.200 Casie Aviles: I need to modify the workflow. So it takes from these spreadsheets. And then, of course, testing. I think those are the at the top of my head.
250 00:24:09.140 ⇒ 00:24:10.890 Amber Lin: Interesting.
251 00:24:12.862 ⇒ 00:24:16.450 Amber Lin: I think I also need to gather.
252 00:24:16.720 ⇒ 00:24:22.330 Amber Lin: Gather how crs use these spreadsheets?
253 00:24:24.328 ⇒ 00:24:27.401 Amber Lin: Let me try and get to this.
254 00:24:28.130 ⇒ 00:24:33.500 Amber Lin: this cycle so that you can at least look at them and know what you need to do.
255 00:24:33.640 ⇒ 00:24:39.099 Amber Lin: There it was, think, oh, gosh! Next cycle seems pretty tense.
256 00:24:39.870 ⇒ 00:24:40.980 Casie Aviles: Okay.
257 00:24:42.210 ⇒ 00:24:44.789 Amber Lin: What if we? I feel like because we have
258 00:24:45.980 ⇒ 00:24:53.139 Amber Lin: 1, 2, 3, like, do you think we should put something into this cycle? And this cycle is this 2 weeks?
259 00:24:53.390 ⇒ 00:24:55.250 Amber Lin: So should we.
260 00:24:55.250 ⇒ 00:24:56.370 Casie Aviles: Until next week, right.
261 00:24:57.170 ⇒ 00:25:03.980 Amber Lin: Yeah, yeah, this week and next week. So do you think we should like squeeze something in so that
262 00:25:05.000 ⇒ 00:25:08.770 Amber Lin: oh, like, let me go to the current cycle
263 00:25:15.910 ⇒ 00:25:17.380 Amber Lin: like these are.
264 00:25:19.200 ⇒ 00:25:20.930 Amber Lin: These are the ones we have.
265 00:25:21.550 ⇒ 00:25:24.360 Casie Aviles: I don’t. I don’t think I think we can.
266 00:25:24.530 ⇒ 00:25:28.169 Amber Lin: Like this probably is good for this week, right?
267 00:25:28.960 ⇒ 00:25:31.370 Amber Lin: Or I don’t know how much time you have.
268 00:25:32.960 ⇒ 00:25:36.169 Amber Lin: cause that’s pretty much done. That’s that’s pretty much done.
269 00:25:36.990 ⇒ 00:25:41.153 Amber Lin: Oh, never mind, I just I just saw this, my bad.
270 00:25:41.910 ⇒ 00:25:53.860 Amber Lin: So there’s oh, by the way, button 300 bucks yeah, for now.
271 00:25:53.860 ⇒ 00:25:56.540 Casie Aviles: Next week I’ll be working mostly on the trainer, but.
272 00:25:56.950 ⇒ 00:25:57.600 Amber Lin: Hmm.
273 00:26:00.540 ⇒ 00:26:03.930 Casie Aviles: And so I’m not sure if this yeah, speaking squeeze.
274 00:26:03.930 ⇒ 00:26:06.060 Amber Lin: Okay, that’s fine. That’s fine. Then
275 00:26:07.410 ⇒ 00:26:13.460 Amber Lin: I mean, we only have one developer on this. It’s not. It’s not your fault that we don’t have that much capacity.
276 00:26:13.680 ⇒ 00:26:26.340 Amber Lin: I can also ask Utah like what he thinks, because the other part of your time is going to the AI team like if he’s willing to sacrifice some of that. Then we have more time on here, so don’t worry. We’ll not make you
277 00:26:26.830 ⇒ 00:26:30.750 Amber Lin: work extra hours. It’s not worth it.
278 00:26:34.490 ⇒ 00:26:37.349 Amber Lin: Okay, corporate registration test.
279 00:26:38.200 ⇒ 00:26:39.630 Amber Lin: This is
280 00:26:42.920 ⇒ 00:26:48.780 Amber Lin: okay. Let me say, yeah, they’re out there.
281 00:26:50.180 ⇒ 00:26:51.700 Amber Lin: Documents.
282 00:26:52.540 ⇒ 00:26:53.340 Amber Lin: Wow.
283 00:26:54.700 ⇒ 00:26:58.500 Amber Lin: Spreadsheets from past departments.
284 00:26:59.644 ⇒ 00:27:06.930 Amber Lin: Oh, by the way, our offers line of ABC service
285 00:27:08.170 ⇒ 00:27:11.190 Amber Lin: any any other documents you needed?
286 00:27:11.410 ⇒ 00:27:14.280 Amber Lin: I’m just gonna do this so that you have everything.
287 00:27:17.910 ⇒ 00:27:24.686 Casie Aviles: Spreadsheet. So, by the way, line of ABC service, I think that’s that’s it, for now.
288 00:27:25.360 ⇒ 00:27:25.900 Amber Lin: Okay.
289 00:27:27.920 ⇒ 00:27:29.120 Casie Aviles: Okay.
290 00:27:29.677 ⇒ 00:27:34.029 Amber Lin: And then let’s look at this, I mean the
291 00:27:34.190 ⇒ 00:27:37.640 Amber Lin: is that possible, like we have 5 points on it.
292 00:27:37.750 ⇒ 00:27:42.400 Amber Lin: if it’s not possible, we’ll just say, oh.
293 00:27:44.060 ⇒ 00:27:47.219 Casie Aviles: No, I haven’t. I haven’t done like an an investigation on this.
294 00:27:47.220 ⇒ 00:27:52.019 Amber Lin: Oh, that’s fine! We don’t say he would. He never did, because he’s too busy.
295 00:27:52.020 ⇒ 00:27:52.630 Casie Aviles: Yeah.
296 00:27:53.060 ⇒ 00:27:54.780 Amber Lin: Alright, I’ll leave it.
297 00:27:57.646 ⇒ 00:27:59.420 Amber Lin: Improve accuracy!
298 00:27:59.940 ⇒ 00:28:05.439 Amber Lin: They won’t do this. How’s our? How’s our accuracy? Score right now? Like, is it.
299 00:28:07.040 ⇒ 00:28:10.090 Casie Aviles: I mean, it’s still it’s still 8, I believe.
300 00:28:10.460 ⇒ 00:28:15.180 Casie Aviles: So. I still want to make sure that.
301 00:28:15.440 ⇒ 00:28:16.020 Amber Lin: Hmm.
302 00:28:16.020 ⇒ 00:28:17.749 Casie Aviles: It’s actually accurate and.
303 00:28:17.750 ⇒ 00:28:18.199 Amber Lin: I see.
304 00:28:18.200 ⇒ 00:28:25.829 Casie Aviles: Yeah, yeah, the thing is, we’re we’re we’re also having, like, more and more questions. So we, the the golden data set, would
305 00:28:26.889 ⇒ 00:28:30.680 Casie Aviles: you know it would inflate, because there’s more questions. So.
306 00:28:31.130 ⇒ 00:28:36.690 Amber Lin: I see. So have we. Did we expand the golden data set.
307 00:28:37.440 ⇒ 00:28:41.100 Casie Aviles: Not yet. No, I haven’t put any work on to that yet.
308 00:28:41.100 ⇒ 00:28:45.979 Amber Lin: I see. No, it’s fine. I just wanted to know where we’re at, so I think it seems like we should
309 00:28:46.960 ⇒ 00:28:52.649 Amber Lin: alright, expand, fold, then data set.
310 00:28:53.850 ⇒ 00:29:00.670 Amber Lin: Well, it’s also I think it is also hard, because we don’t know like
311 00:29:01.490 ⇒ 00:29:05.900 Amber Lin: what we know is correct or wrong. So I guess the only the only way.
312 00:29:05.900 ⇒ 00:29:06.350 Casie Aviles: Yes.
313 00:29:06.350 ⇒ 00:29:10.570 Amber Lin: Incorporate. There’s some thumbs up feedback and.
314 00:29:12.383 ⇒ 00:29:13.250 Casie Aviles: Yes! Yes!
315 00:29:13.250 ⇒ 00:29:17.029 Amber Lin: Have you done the Pr review? How does it look? Currently?
316 00:29:17.810 ⇒ 00:29:20.819 Amber Lin: Oh, I I did approve Utam, and I approved it.
317 00:29:20.820 ⇒ 00:29:21.540 Amber Lin: Oh, great!
318 00:29:23.050 ⇒ 00:29:26.340 Amber Lin: And so I will say that it’s all over here.
319 00:29:26.340 ⇒ 00:29:28.240 Casie Aviles: Like, yeah, and you can.
320 00:29:28.580 ⇒ 00:29:33.129 Amber Lin: Yeah, let me. Oh, should we tell Annie to merge it now?
321 00:29:35.670 ⇒ 00:29:36.120 Casie Aviles: Yeah.
322 00:29:36.120 ⇒ 00:29:36.720 Amber Lin: All right
323 00:29:43.880 ⇒ 00:29:44.880 Amber Lin: sounds great.
324 00:29:46.160 ⇒ 00:29:55.550 Amber Lin: And then I think after that we can check how the quality score is going. I think it’s really I don’t. I just think it’s really hard for us to measure the quality score?
325 00:29:57.260 ⇒ 00:29:58.470 Casie Aviles: Yeah, because we don’t.
326 00:29:58.470 ⇒ 00:30:00.605 Amber Lin: Yeah, we just we just don’t know.
327 00:30:04.670 ⇒ 00:30:06.990 Amber Lin: Yeah, I don’t know how we’re gonna do this.
328 00:30:17.990 ⇒ 00:30:22.269 Amber Lin: currently, I have a question, currently does Andy ask, follow up questions.
329 00:30:24.780 ⇒ 00:30:31.630 Casie Aviles: I I think I haven’t. I? Yeah, actually, yeah, it does. It does. Yeah, I’m just trying to remember.
330 00:30:31.926 ⇒ 00:30:33.999 Amber Lin: What type of questions does it ask?
331 00:30:36.175 ⇒ 00:30:40.324 Casie Aviles: Like, for example, like, for example, I was just testing earlier
332 00:30:41.910 ⇒ 00:30:47.540 Casie Aviles: Like, I just test. I just entered mosquito suppression. And then it’s going to ask like
333 00:30:48.031 ⇒ 00:30:55.430 Casie Aviles: Do you have the customer’s address or the name of the specific technician. You’d like to check availability for ask something like that.
334 00:30:56.120 ⇒ 00:30:57.150 Amber Lin: Oh!
335 00:30:58.590 ⇒ 00:30:59.425 Casie Aviles: Maybe.
336 00:31:00.260 ⇒ 00:31:06.019 Casie Aviles: Some of yeah. Some of the Csrs have noted that it asked. Follow up questions, but then it says it doesn’t know.
337 00:31:08.260 ⇒ 00:31:12.779 Amber Lin: So should we make it ask? Follow up questions based on like, how do we improve that?
338 00:31:13.040 ⇒ 00:31:17.779 Amber Lin: So if they ask all our questions based on what we actually have or.
339 00:31:19.490 ⇒ 00:31:26.510 Casie Aviles: Yeah, we’re just gonna we’ll need to prompt the the bot much better. So you just need to
340 00:31:29.490 ⇒ 00:31:31.080 Casie Aviles: like, yeah.
341 00:31:37.580 ⇒ 00:31:38.080 Amber Lin: Right.
342 00:31:42.070 ⇒ 00:31:46.849 Amber Lin: Oh, alright! I think that’s something that
343 00:31:47.390 ⇒ 00:31:53.370 Amber Lin: I will. I’ll think about. I’ll make the oh, we have something here.
344 00:31:58.070 ⇒ 00:32:05.100 Amber Lin: yeah, I think this is related to this is, relate to a free aviations.
345 00:32:05.610 ⇒ 00:32:09.229 Amber Lin: And then I think now that we
346 00:32:10.553 ⇒ 00:32:17.200 Amber Lin: change the 2 word limited, the input I think that will help, but.
347 00:32:17.200 ⇒ 00:32:17.840 Casie Aviles: Yes.
348 00:32:17.840 ⇒ 00:32:18.740 Amber Lin: Yeah.
349 00:32:25.040 ⇒ 00:32:26.670 Amber Lin: is this something that?
350 00:32:28.010 ⇒ 00:32:28.930 Amber Lin: Oh.
351 00:32:30.210 ⇒ 00:32:32.359 Casie Aviles: Wait. This is not. I’m not sure what this is.
352 00:32:32.510 ⇒ 00:32:35.485 Amber Lin: Yeah, so this is so.
353 00:32:36.640 ⇒ 00:32:47.979 Amber Lin: I think when we talked about the trainer trainer bought right? So we talked about how to. We have a lot of different documents, and we kind of want to. We wanted to originally
354 00:32:48.290 ⇒ 00:32:51.200 Amber Lin: tag each one with different tags.
355 00:32:51.661 ⇒ 00:32:56.959 Amber Lin: So, for example, like this is about service lines. This is about workflow policies, etc.
356 00:32:57.760 ⇒ 00:33:05.000 Amber Lin: and then tag them so it’s more easily searchable if that makes sense.
357 00:33:07.559 ⇒ 00:33:13.400 Casie Aviles: So it’s it’s like just adding keywords to the central dock right.
358 00:33:13.790 ⇒ 00:33:14.869 Amber Lin: Kind of yeah.
359 00:33:15.600 ⇒ 00:33:19.910 Amber Lin: Do you think that would help the help us?
360 00:33:20.950 ⇒ 00:33:23.059 Amber Lin: Yeah, I hope the bot search it.
361 00:33:24.190 ⇒ 00:33:31.610 Casie Aviles: Yeah, I think, yeah, it it helps like, especially if we we have like question and answer formats like.
362 00:33:33.770 ⇒ 00:33:36.949 Casie Aviles: Yeah, that that’s going to help or like adding, just adding
363 00:33:37.360 ⇒ 00:33:41.979 Casie Aviles: keywords in general could also help the bot. Just look for the correct context.
364 00:33:41.980 ⇒ 00:33:42.910 Amber Lin: Hmm!
365 00:33:44.420 ⇒ 00:33:49.039 Amber Lin: I see. So this is some like the 1st step, we should say.
366 00:33:50.030 ⇒ 00:33:55.790 Amber Lin: add keywords. What other things would help the bot search it.
367 00:34:00.510 ⇒ 00:34:01.999 Amber Lin: Sorry you were saying.
368 00:34:03.040 ⇒ 00:34:07.450 Casie Aviles: Sorry. No, no, I was just thinking. I was reading through the ticket.
369 00:34:07.710 ⇒ 00:34:08.270 Amber Lin: Hmm.
370 00:34:12.880 ⇒ 00:34:18.999 Casie Aviles: I mean, I think these suggestions here in the ticket are
371 00:34:19.389 ⇒ 00:34:24.259 Casie Aviles: are fine, for now. This is the one that comes to mind immediately, like keywords or.
372 00:34:24.260 ⇒ 00:34:24.850 Amber Lin: Hmm.
373 00:34:26.190 ⇒ 00:34:32.734 Casie Aviles: You know, introducing Q&A formats like, for example, like, there’s a section in
374 00:34:34.639 ⇒ 00:34:38.480 Casie Aviles: yeah, like in in the central dock, you could add like
375 00:34:39.300 ⇒ 00:34:50.609 Casie Aviles: questions that this section would answer. So if they wrote something about pest pet poisoning? Then I could add questions, there like these are the answerable questions
376 00:34:51.600 ⇒ 00:34:53.149 Casie Aviles: from the user. Right?
377 00:34:53.650 ⇒ 00:34:54.190 Amber Lin: I see.
378 00:34:54.190 ⇒ 00:34:55.270 Casie Aviles: Something like that.
379 00:34:55.630 ⇒ 00:34:56.429 Amber Lin: Wow!
380 00:34:57.560 ⇒ 00:34:58.470 Amber Lin: Search.
381 00:35:00.740 ⇒ 00:35:07.310 Amber Lin: I think I’ll implement that while I’m doing the formatting changes, I’ll do at least a part of it today.
382 00:35:07.720 ⇒ 00:35:16.099 Amber Lin: and like. I don’t know how hard it is to do a knowledge graph.
383 00:35:16.620 ⇒ 00:35:20.079 Amber Lin: Let me find a image about Polish graphs.
384 00:35:30.630 ⇒ 00:35:31.599 Amber Lin: I think
385 00:35:37.900 ⇒ 00:35:40.119 Amber Lin: the knowledge graph looks like this.
386 00:35:41.930 ⇒ 00:35:44.549 Casie Aviles: I haven’t done anything like that.
387 00:35:44.550 ⇒ 00:35:47.466 Amber Lin: I know me neither.
388 00:35:48.765 ⇒ 00:35:50.989 Amber Lin: I think it’s mostly just
389 00:35:51.260 ⇒ 00:36:00.180 Amber Lin: this is linked in other. This is mentioned in other documents, you know, like how notion works right, or
390 00:36:01.550 ⇒ 00:36:12.029 Amber Lin: let me. Here, let me see if I can show you my oh, my knowledge graph desktop share.
391 00:36:12.390 ⇒ 00:36:13.340 Amber Lin: So
392 00:36:14.330 ⇒ 00:36:21.489 Amber Lin: I write. I don’t know what kind of personal information is going to come up here. So this is my knowledge
393 00:36:21.670 ⇒ 00:36:25.300 Amber Lin: base that I write my own reflections in.
394 00:36:25.930 ⇒ 00:36:27.120 Casie Aviles: Oh, this is obsidian.
395 00:36:27.120 ⇒ 00:36:30.180 Amber Lin: Yeah, this is obsidian. So if you have.
396 00:36:30.730 ⇒ 00:36:38.880 Amber Lin: if you have this right, if it’s mentioned in here, I tag it, I tag here, and so.
397 00:36:39.470 ⇒ 00:36:41.160 Amber Lin: whatever’s tagged.
398 00:36:41.500 ⇒ 00:36:47.120 Amber Lin: So every one of this, these lines are just this was mentioned once
399 00:36:47.500 ⇒ 00:36:56.419 Amber Lin: in this document. Right? So this is essentially just mentions, like I may. I mentioned.
400 00:36:56.790 ⇒ 00:37:04.190 Amber Lin: I have this, and I mentioned it was mentioned in this big document that that.
401 00:37:05.200 ⇒ 00:37:05.530 Casie Aviles: Okay.
402 00:37:05.530 ⇒ 00:37:06.430 Amber Lin: Yeah.
403 00:37:06.610 ⇒ 00:37:16.530 Amber Lin: So if I have oh, so if I have oh, gosh! What is this?
404 00:37:17.220 ⇒ 00:37:19.580 Amber Lin: And here’s something.
405 00:37:23.670 ⇒ 00:37:25.780 Amber Lin: Oh, huh!
406 00:37:26.750 ⇒ 00:37:30.569 Amber Lin: Anyways, I think you get the point, and, like each of these, have mentioned
407 00:37:30.760 ⇒ 00:37:35.049 Amber Lin: other documents, and hence why the link is established.
408 00:37:35.490 ⇒ 00:37:40.710 Amber Lin: I don’t exactly know if we need to do that, or if we should
409 00:37:41.290 ⇒ 00:37:45.150 Amber Lin: do that, and how searchable is, gonna make things
410 00:37:46.330 ⇒ 00:37:50.009 Casie Aviles: So this this will be for the Bot or for the Csrs, because.
411 00:37:51.290 ⇒ 00:37:59.309 Casie Aviles: I’m not sure if we I mean I I know that there are some ways that we could implement knowledge graphs for for bots, but
412 00:37:59.430 ⇒ 00:38:06.750 Casie Aviles: it’s very experimental, and I’m not sure if it’s it’s gonna it’s gonna result in any positive.
413 00:38:06.750 ⇒ 00:38:07.540 Amber Lin: Yeah, yeah.
414 00:38:07.770 ⇒ 00:38:08.710 Casie Aviles: Yeah.
415 00:38:09.840 ⇒ 00:38:17.550 Casie Aviles: I’m not sure, because I I haven’t really done it for the bot. But if it’s for a visual interface for the Csrs, that’s another thing.
416 00:38:17.810 ⇒ 00:38:20.120 Amber Lin: Like obsidian, but.
417 00:38:20.560 ⇒ 00:38:30.490 Casie Aviles: Yeah, I I guess, like, the question is, how how do we do? We need to implement it for the Csrs or and and how do we implement it for the Csrs? I don’t. I don’t know yet exactly.
418 00:38:30.490 ⇒ 00:38:41.150 Amber Lin: I see I see you’re you’re very right. You bring up a good point, because ultimately we want the Csrs to go into the central dock right? And I guess to that point.
419 00:38:42.470 ⇒ 00:38:42.940 Casie Aviles: Yeah.
420 00:38:42.940 ⇒ 00:38:49.609 Amber Lin: Maybe all we need to do cause this is gonna take some time. I guess all we need to do is to just
421 00:38:49.850 ⇒ 00:38:54.179 Amber Lin: organize the Central Doc and give it like a certain hierarchy.
422 00:38:54.480 ⇒ 00:38:58.390 Amber Lin: like a certain organization, and that will be all we need. I guess.
423 00:38:58.630 ⇒ 00:39:00.780 Casie Aviles: Yeah, the minimum we could start with that.
424 00:39:02.950 ⇒ 00:39:04.029 Casie Aviles: So it’s just yeah.
425 00:39:04.520 ⇒ 00:39:05.010 Amber Lin: Nice?
426 00:39:05.010 ⇒ 00:39:07.149 Casie Aviles: More on structuring and formatting the.
427 00:39:07.740 ⇒ 00:39:08.410 Casie Aviles: Oh!
428 00:39:10.690 ⇒ 00:39:12.099 Amber Lin: Yeah, let me.
429 00:39:18.210 ⇒ 00:39:20.760 Amber Lin: Yeah, I think let’s move this backlog.
430 00:39:24.050 ⇒ 00:39:31.829 Amber Lin: Oh, we have this right, Andy just says we. I don’t know sometimes.
431 00:39:32.900 ⇒ 00:39:36.950 Amber Lin: but we don’t have. Oh, okay, we don’t have past hallucination pairs.
432 00:39:37.730 ⇒ 00:39:43.860 Casie Aviles: Yeah, we we didn’t identify like, okay, which responses to investigate.
433 00:39:44.423 ⇒ 00:39:45.550 Amber Lin: Sounds good.
434 00:39:52.000 ⇒ 00:40:03.789 Amber Lin: yeah, I will go search in the feedback feedback. Pub sheet, and that will come up
435 00:40:04.830 ⇒ 00:40:07.200 Amber Lin: alright. Conversation. Log.
436 00:40:07.310 ⇒ 00:40:20.100 Amber Lin: Oh, think! Looking at these, this is for later, I think one last thing is that like.
437 00:40:21.360 ⇒ 00:40:26.680 Amber Lin: do we want to enable direct updates to central talk via Trainerva ui.
438 00:40:27.130 ⇒ 00:40:30.789 Amber Lin: The problem is that I don’t think they’re even using that trainer bot yet.
439 00:40:31.080 ⇒ 00:40:31.790 Amber Lin: So.
440 00:40:32.930 ⇒ 00:40:37.049 Casie Aviles: Hmm, yeah, and we haven’t figured out. I think this was the.
441 00:40:37.260 ⇒ 00:40:38.830 Amber Lin: Yeah, this is hard.
442 00:40:39.390 ⇒ 00:40:43.500 Casie Aviles: Yeah, this was the problem that also Miguel faced with the trainer. Bot.
443 00:40:43.930 ⇒ 00:40:44.650 Amber Lin: Hmm.
444 00:40:44.650 ⇒ 00:40:47.499 Casie Aviles: Which is why we didn’t do the direct updates.
445 00:40:47.670 ⇒ 00:40:48.620 Amber Lin: I see
446 00:40:53.640 ⇒ 00:40:55.949 Casie Aviles: So I’m I’m not sure if they they need this.
447 00:40:56.670 ⇒ 00:40:58.870 Casie Aviles: This, yeah, the trainers.
448 00:40:58.870 ⇒ 00:41:05.020 Amber Lin: I see I don’t think they need it. It was something really, really nice that they can have
449 00:41:05.300 ⇒ 00:41:21.509 Amber Lin: cause already. They’re not really using. They? They’re not really using the trainer. But I think, as a 1st step, let’s put it in Google, like, put it in Google Workspace, and think that will make them use it a little bit more, and then we can think about this this one later.
450 00:41:22.690 ⇒ 00:41:23.710 Casie Aviles: Yeah, sure.
451 00:41:24.200 ⇒ 00:41:24.820 Amber Lin: Okay.
452 00:41:26.248 ⇒ 00:41:31.440 Amber Lin: let me groom these tickets a little bit more, I think, at least for next cycle we have.
453 00:41:33.080 ⇒ 00:41:38.780 Amber Lin: we have quite a bit, and this is also you. So I don’t know if you have all the time to do that.
454 00:41:38.950 ⇒ 00:41:40.580 Amber Lin: but I think that’s good.
455 00:41:41.940 ⇒ 00:41:42.520 Casie Aviles: Okay.
456 00:41:42.520 ⇒ 00:41:45.899 Amber Lin: Yeah, thank you so much.
457 00:41:47.320 ⇒ 00:41:49.210 Casie Aviles: Okay. Yeah. Thanks. Thanks. Amber.
458 00:41:49.210 ⇒ 00:41:53.560 Amber Lin: Yeah, alrighty. Bye-bye.
459 00:41:54.310 ⇒ 00:41:54.980 Casie Aviles: Bye.