Meeting Title: AI Team Weekly Planning Date: 2025-03-10 Meeting participants: Janna Wong, Uttam Kumaran, Amber Lin, Miguel De Veyra, Casie Aviles
WEBVTT
1 00:08:59.070 ⇒ 00:09:04.189 Amber Lin: Hello, okay. I just got back.
2 00:09:08.970 ⇒ 00:09:12.310 Amber Lin: We’ll wait a little bit for Miguel and.
3 00:09:21.325 ⇒ 00:09:23.160 Casie Aviles: Let me send him a message.
4 00:09:24.120 ⇒ 00:09:25.550 Amber Lin: Good morning!
5 00:09:29.670 ⇒ 00:09:30.640 Uttam Kumaran: Hey! Good morning!
6 00:09:33.740 ⇒ 00:09:34.949 Casie Aviles: Hey! Good morning!
7 00:10:12.230 ⇒ 00:10:13.050 Miguel de Veyra: Hey, guys.
8 00:10:20.620 ⇒ 00:10:21.220 Casie Aviles: Hey!
9 00:10:22.280 ⇒ 00:10:25.040 Miguel de Veyra: I was on a different meeting.
10 00:10:27.920 ⇒ 00:10:29.570 Amber Lin: Hello! Everyone.
11 00:10:31.990 ⇒ 00:10:32.940 Miguel de Veyra: Embarrassed.
12 00:10:36.590 ⇒ 00:10:38.229 Amber Lin: Oh! Can you all hear me?
13 00:10:38.230 ⇒ 00:10:38.930 Miguel de Veyra: Yep.
14 00:10:41.950 ⇒ 00:10:44.929 Amber Lin: Oh, I’m so sorry! I think I turned the sound off.
15 00:10:45.968 ⇒ 00:10:48.059 Amber Lin: Is my sound working now?
16 00:10:49.390 ⇒ 00:10:51.930 Amber Lin: Oh, perfect! There we go!
17 00:10:52.580 ⇒ 00:10:54.370 Amber Lin: Hello, everybody!
18 00:10:55.160 ⇒ 00:10:57.309 Amber Lin: They started to meet again.
19 00:10:57.790 ⇒ 00:10:58.710 Miguel de Veyra: Only morning.
20 00:10:59.426 ⇒ 00:11:00.559 Amber Lin: Good morning.
21 00:11:00.820 ⇒ 00:11:04.150 Amber Lin: It’s nighttime for you. We’re almost morning.
22 00:11:04.550 ⇒ 00:11:05.870 Miguel de Veyra: Almost. Morning. Yeah.
23 00:11:05.870 ⇒ 00:11:06.896 Amber Lin: I see.
24 00:11:07.900 ⇒ 00:11:16.469 Amber Lin: Okay, let’s make this quick. Let me share my screen. And then we can talk about that.
25 00:11:22.790 ⇒ 00:11:23.570 Amber Lin: Here.
26 00:11:24.510 ⇒ 00:11:31.400 Amber Lin: I have the weekly planning so
27 00:11:32.000 ⇒ 00:11:39.470 Amber Lin: based on the call last week, there was a few things that they suggested. So
28 00:11:39.900 ⇒ 00:11:48.818 Amber Lin: I haven’t looked at your guys’s comments yet. If you guys commented. But I would just like to get your guys thoughts on
29 00:11:49.430 ⇒ 00:11:53.619 Amber Lin: how? What do you think we should focus on, and
30 00:11:53.980 ⇒ 00:12:04.129 Amber Lin: how long or what priority? Each task is so right now I know that we’re working on
31 00:12:04.480 ⇒ 00:12:10.400 Amber Lin: the oh, by the way, and also working on the.
32 00:12:11.280 ⇒ 00:12:12.230 Casie Aviles: All right.
33 00:12:13.560 ⇒ 00:12:16.240 Amber Lin: Let’s see what things
34 00:12:16.693 ⇒ 00:12:26.400 Amber Lin: Miguel Casey and Jenna. Can you tell me what what we’re working on right now, based on your understanding? And I can think of what we can add to that.
35 00:12:27.330 ⇒ 00:12:29.590 Miguel de Veyra: Basically just polishing the.
36 00:12:30.280 ⇒ 00:12:32.000 Amber Lin: Oh, by the way, the.
37 00:12:32.610 ⇒ 00:12:39.130 Miguel de Veyra: Record. Prompt, I would say, and then the brain thrust. We’re still working on that.
38 00:12:40.060 ⇒ 00:12:41.110 Casie Aviles: Yeah. The evos.
39 00:12:41.110 ⇒ 00:12:42.250 Miguel de Veyra: The evils.
40 00:12:42.710 ⇒ 00:12:43.680 Amber Lin: Emails.
41 00:12:44.135 ⇒ 00:12:45.859 Miguel de Veyra: Brain thrust, and evils is the same thing.
42 00:12:45.860 ⇒ 00:12:48.720 Amber Lin: Oh, there we go! Let me try!
43 00:12:49.046 ⇒ 00:12:52.640 Miguel de Veyra: And then, what was I? What was I working on earlier?
44 00:12:53.630 ⇒ 00:12:55.479 Miguel de Veyra: We could also add.
45 00:12:57.010 ⇒ 00:13:00.240 Miguel de Veyra: The above sorry. Go
46 00:13:00.350 ⇒ 00:13:07.240 Miguel de Veyra: polishing. Oh, by the way, let’s just say here, instead of polishing, let’s just change it to improving the prompt.
47 00:13:07.520 ⇒ 00:13:31.189 Amber Lin: Improving. Oh, by the way, prompts, and I am meeting with Janine tomorrow to get either to get her to work on the Golden data set or to get more. Oh, by the way, prompts or hints, what would you guys prefer? So what would create the most impact, the golden data sheet, or the Oh, by the way, hints.
48 00:13:31.800 ⇒ 00:13:35.860 Miguel de Veyra: They affect very different parts of the
49 00:13:36.350 ⇒ 00:13:39.879 Miguel de Veyra: the process, basically. Because, oh, by the way.
50 00:13:40.530 ⇒ 00:13:48.220 Miguel de Veyra: affects how would you say this? It’s like, it’s like an upsell. Technically. So it’s yeah, the
51 00:13:49.120 ⇒ 00:13:55.070 Miguel de Veyra: actual user interface. They actually see it. The events is more for the back back end stuff.
52 00:13:55.380 ⇒ 00:13:58.609 Amber Lin: Yeah, I think I was asking, should I?
53 00:13:58.990 ⇒ 00:14:03.639 Amber Lin: I guess the Golden data set is related to the Evals, but it also.
54 00:14:03.640 ⇒ 00:14:04.650 Miguel de Veyra: Yeah, yeah, yeah.
55 00:14:05.060 ⇒ 00:14:09.359 Amber Lin: I could get that I could get her to maybe update
56 00:14:10.971 ⇒ 00:14:15.930 Amber Lin: Google drive or get. Oh, by the way, hints.
57 00:14:16.100 ⇒ 00:14:23.820 Amber Lin: yeah, I’ll see. I’ll see what we get to tomorrow. So would you like me to do this one or this one?
58 00:14:25.086 ⇒ 00:14:27.350 Miguel de Veyra: Both would be nice if you could spend half half.
59 00:14:28.480 ⇒ 00:14:31.289 Amber Lin: Okay, I might not get it totally done, though we.
60 00:14:31.290 ⇒ 00:14:32.976 Miguel de Veyra: Yeah, yeah.
61 00:14:33.820 ⇒ 00:14:34.660 Amber Lin: Oh, okay.
62 00:14:36.023 ⇒ 00:15:01.089 Amber Lin: that she also mentioned that. Well, Scott also mentioned, and they agree that we should have a feedback system system after calls, especially since we are testing it with the Csrs. If we have a feedback system that they just can, they, they can just click kind of like our bots in our AI testing channel of oh, rate this rate, this call. Do we have that in place.
63 00:15:03.000 ⇒ 00:15:06.919 Miguel de Veyra: Wait. Sorry is this. Is this a feedback on the reply of the bot.
64 00:15:07.680 ⇒ 00:15:08.620 Casie Aviles: Don’t think we have.
65 00:15:09.400 ⇒ 00:15:10.733 Amber Lin: Oh, okay,
66 00:15:12.480 ⇒ 00:15:23.320 Amber Lin: So this is kind of the Csr’s use our bot and the at end of their usage they click, they rate it on the scale of 10 and then send some feedback.
67 00:15:24.090 ⇒ 00:15:31.269 Amber Lin: so we can know how we did not just based on the golden data set, but also based on the Csrs.
68 00:15:31.510 ⇒ 00:15:32.780 Miguel de Veyra: Yeah, let’s.
69 00:15:34.160 ⇒ 00:15:36.460 Casie Aviles: Do a thumbs up right or thumbs down something.
70 00:15:36.460 ⇒ 00:15:41.230 Miguel de Veyra: No, I think they’re looking for something more specific, though, like, Hey, how did this go?
71 00:15:41.420 ⇒ 00:15:47.080 Miguel de Veyra: I just think. But the thing is, the conversation never really ends. So it’s a bit hard.
72 00:15:47.570 ⇒ 00:15:52.960 Miguel de Veyra: right? Because it’s an ongoing conversation. They can just keep going back. So I guess what we do.
73 00:15:52.960 ⇒ 00:15:57.839 Amber Lin: We could do it like Chatgpt. You know the the each answer you could
74 00:15:58.020 ⇒ 00:16:00.410 Amber Lin: give a thumbs up, thumbs down. Do you think.
75 00:16:02.030 ⇒ 00:16:07.749 Miguel de Veyra: I mean case can. Do you think we can do that on Google Chat? I I know we can do it on.
76 00:16:08.060 ⇒ 00:16:13.200 Casie Aviles: I think we could read like the reactions. So we could start with reactions.
77 00:16:13.790 ⇒ 00:16:17.790 Miguel de Veyra: Yeah, let’s well, this is more of a spike, I would say amber like.
78 00:16:17.790 ⇒ 00:16:18.170 Amber Lin: Okay.
79 00:16:18.170 ⇒ 00:16:19.029 Miguel de Veyra: If it’ll work.
80 00:16:19.580 ⇒ 00:16:30.030 Amber Lin: Okay, let’s see, 4 business like.
81 00:16:30.650 ⇒ 00:16:33.969 Amber Lin: yeah, I think, how long do you guys estimate this would take.
82 00:16:34.618 ⇒ 00:16:36.649 Miguel de Veyra: Spike would probably be a day.
83 00:16:37.647 ⇒ 00:16:40.749 Miguel de Veyra: Is this very? Is this very time consuming?
84 00:16:42.390 ⇒ 00:16:46.040 Miguel de Veyra: Oh, we can’t say I. We can say, probably after the spike.
85 00:16:46.610 ⇒ 00:16:46.950 Amber Lin: Okay.
86 00:16:46.950 ⇒ 00:16:48.229 Miguel de Veyra: Like, tomorrow. Yeah.
87 00:16:48.780 ⇒ 00:16:50.750 Amber Lin: Oh, what are we doing tomorrow?
88 00:16:52.330 ⇒ 00:17:01.240 Miguel de Veyra: I know, for spikes are, you know, designed to to basically research it. So we can be more accurate and how long it will develop. I mean.
89 00:17:02.350 ⇒ 00:17:06.250 Amber Lin: We can can we research? We could research that today.
90 00:17:06.869 ⇒ 00:17:07.669 Miguel de Veyra: Yeah, yeah.
91 00:17:07.810 ⇒ 00:17:11.369 Amber Lin: Monday, and then decide time.
92 00:17:12.119 ⇒ 00:17:12.699 Miguel de Veyra: Timeframe. Yeah.
93 00:17:14.250 ⇒ 00:17:23.202 Amber Lin: Meeting perfect. And then they also brought up in the meeting.
94 00:17:24.300 ⇒ 00:17:39.680 Amber Lin: cause. We were talking about the ex essentially Google sheets of all their services. I think Janine was talking about sorry Yvette was talking about. Oh, the answers are not granular enough.
95 00:17:39.870 ⇒ 00:17:54.940 Amber Lin: which I’m not sure which version she has been using, or if she has used it recently. But they did bring up, and Spot did bring up that. We do want to scrape their websites again, and I confirm with them which ones
96 00:17:55.596 ⇒ 00:18:03.689 Amber Lin: they want us to scrape. And it was the ABC pest site, the Chem free, and then
97 00:18:04.440 ⇒ 00:18:05.669 Amber Lin: and then the.
98 00:18:07.500 ⇒ 00:18:08.250 Miguel de Veyra: Yeah.
99 00:18:08.250 ⇒ 00:18:08.640 Amber Lin: So.
100 00:18:08.640 ⇒ 00:18:16.890 Miguel de Veyra: I I guess, for this one amber. What we can do is we can probably escape. Because if you go to one of those sites, let’s see.
101 00:18:16.890 ⇒ 00:18:17.640 Amber Lin: Yeah, yeah.
102 00:18:17.640 ⇒ 00:18:20.369 Miguel de Veyra: So I actually haven’t really checked this as much.
103 00:18:20.640 ⇒ 00:18:21.819 Amber Lin: No, don’t worry.
104 00:18:22.910 ⇒ 00:18:25.210 Amber Lin: Say, this side.
105 00:18:25.470 ⇒ 00:18:29.650 Amber Lin: Yeah, let me. I need to share a different screen.
106 00:18:30.380 ⇒ 00:18:32.090 Amber Lin: And here.
107 00:18:33.530 ⇒ 00:18:39.750 Amber Lin: see, this is the other side. I bet you guys have looked at the ABC side. This is their other site
108 00:18:40.100 ⇒ 00:18:40.800 Amber Lin: through.
109 00:18:40.800 ⇒ 00:18:43.070 Miguel de Veyra: I mean others.
110 00:18:43.070 ⇒ 00:18:46.489 Amber Lin: If we can find their services.
111 00:18:46.490 ⇒ 00:18:53.060 Miguel de Veyra: It’s probably on. Yeah, this is the thing, though, like, do we like, what info from this side do we need to scrape.
112 00:18:53.580 ⇒ 00:18:54.500 Amber Lin: Yeah.
113 00:18:54.930 ⇒ 00:19:05.649 Amber Lin: I’m not. I’m not 100% sure. I think they just got really excited about oh, we’re gonna scrape the website. And I know during the meeting would almost like, Oh, we have a
114 00:19:06.275 ⇒ 00:19:18.699 Amber Lin: we already have a scraper that it will be quite easy, but I spent some time in the weekend learning squarep and trying to do it myself, and I don’t know what we’re trying to get here.
115 00:19:19.040 ⇒ 00:19:23.459 Miguel de Veyra: Basically, it’s just the the info, like their services, their products and stuff.
116 00:19:23.460 ⇒ 00:19:29.570 Amber Lin: Yeah, I just for this site, specifically for one service.
117 00:19:29.990 ⇒ 00:19:44.579 Miguel de Veyra: Because, for example, for this one, it’s our bot is designed for, you know. Csrs, so it’s not really, if you see above, it’s there for become an installer or something, so I don’t know. Maybe we should ask them, hey? Which you know.
118 00:19:44.580 ⇒ 00:19:50.727 Amber Lin: Oh, let me, con! That’s great! I will check what info on.
119 00:19:51.200 ⇒ 00:19:55.690 Miguel de Veyra: Yeah, because this this will have to be added to Central Doc.
120 00:19:56.290 ⇒ 00:20:00.290 Amber Lin: Okay, this will have to be.
121 00:20:09.050 ⇒ 00:20:09.590 Amber Lin: Have you seen.
122 00:20:09.590 ⇒ 00:20:11.730 Miguel de Veyra: Spend time on the Central Doc. By the way.
123 00:20:12.269 ⇒ 00:20:22.800 Amber Lin: I have looked at it, and I know it’s it’s very long, but I don’t exactly know what to look at, because it’s so long. So I just know that kinda it’s there.
124 00:20:22.800 ⇒ 00:20:27.899 Miguel de Veyra: Yup Yup is the scraped stuff will most probably have to go there.
125 00:20:29.180 ⇒ 00:20:30.110 Miguel de Veyra: But the thing is.
126 00:20:30.110 ⇒ 00:20:34.709 Amber Lin: Have a craper in place, or do we have to spend time developing it.
127 00:20:35.100 ⇒ 00:20:41.350 Miguel de Veyra: Honestly, we’ll just copy, paste everything. It’s much easier cause we only need the content. Anyways.
128 00:20:42.158 ⇒ 00:20:46.989 Miguel de Veyra: we don’t. We don’t need to develop anything. I’ll just copy, paste it. Post it to Gpt. Hey?
129 00:20:47.350 ⇒ 00:20:48.060 Amber Lin: Oh, okay.
130 00:20:48.060 ⇒ 00:20:51.560 Miguel de Veyra: Clean this up a bit. That’s it. Yeah, that’s why we need to know the pages.
131 00:20:51.680 ⇒ 00:20:53.099 Miguel de Veyra: What info did they need.
132 00:20:53.100 ⇒ 00:21:01.930 Amber Lin: See? Oh, that’s so helpful. Okay? Need to know what pages? Well, I’m gonna I’m not gonna tell them that we’re should I tell them that we’re gonna copy and paste everything.
133 00:21:01.930 ⇒ 00:21:02.700 Miguel de Veyra: No, no, no.
134 00:21:02.700 ⇒ 00:21:05.300 Amber Lin: That’s cool. Okay, we’re gonna everything.
135 00:21:05.300 ⇒ 00:21:06.520 Miguel de Veyra: Clean the data.
136 00:21:06.800 ⇒ 00:21:09.070 Amber Lin: Yes, don’t tell quiet.
137 00:21:09.940 ⇒ 00:21:16.630 Amber Lin: I have the problem. I I know I I be too honest. Sometimes I need to know that. So I don’t tell them.
138 00:21:18.390 ⇒ 00:21:22.100 Amber Lin: Okay, that’s good. That saves a lot on our end. Well, let’s.
139 00:21:22.100 ⇒ 00:21:22.490 Miguel de Veyra: Yes.
140 00:21:22.490 ⇒ 00:21:27.090 Amber Lin: Do that. That’s done, I will take care of it, and then.
141 00:21:27.090 ⇒ 00:21:33.130 Miguel de Veyra: And then, yeah, you mentioned earlier. The replies are not too granular, is it?
142 00:21:33.130 ⇒ 00:21:35.980 Amber Lin: Yeah, I think she wants it specifically of
143 00:21:36.670 ⇒ 00:21:39.459 Amber Lin: where the postal code it is
144 00:21:39.790 ⇒ 00:21:52.460 Amber Lin: like, I think, sh! Right now she’s saying that it just gives what the service is, not what area, not specifically what city, not not down to that level.
145 00:21:52.820 ⇒ 00:21:53.809 Miguel de Veyra: Only a bit.
146 00:21:53.810 ⇒ 00:21:56.889 Miguel de Veyra: Well, that’s what the golden data is for, to be honest.
147 00:21:56.890 ⇒ 00:21:59.439 Amber Lin: Oh, okay, let me tell her this is.
148 00:21:59.440 ⇒ 00:22:08.600 Miguel de Veyra: Yeah. Like, for example, if I don’t know, maybe, what services are you? Who’s the people on what services is there on a certain postal code.
149 00:22:08.740 ⇒ 00:22:13.730 Miguel de Veyra: Maybe, if you know, hey, here’s the mosquito text and stuff like that. But yeah.
150 00:22:14.240 ⇒ 00:22:22.099 Miguel de Veyra: we’ll ask them, what’s the ideal reply of the boss? I did ask them multiple times. But yeah, maybe it’s you’ll have a better long.
151 00:22:22.790 ⇒ 00:22:35.230 Amber Lin: Okay, I think we just need to try it many, many times until we get it right. It’s like someone’s working with a client. It’s like working with a model, and you just poke it and poke it and poke it, and then they’ll be.
152 00:22:37.515 ⇒ 00:22:40.870 Miguel de Veyra: Yeah, I think the other thing we can do is
153 00:22:41.350 ⇒ 00:22:46.449 Miguel de Veyra: ask them, amber. If, by the way, you’re not, we’re not seeing any of your screen.
154 00:22:46.450 ⇒ 00:22:52.039 Amber Lin: Oh, I’m sorry! Let me change the change it back to here, there we go.
155 00:22:52.040 ⇒ 00:22:58.369 Miguel de Veyra: Yeah, maybe if they like, maybe you can ask them if there’s like a certain format that they wanted to.
156 00:22:58.550 ⇒ 00:23:09.560 Amber Lin: Oh, yeah, yeah, totally. I was thinking about that. I didn’t bring that up in the client meeting, because I think they already got overstep. But I can ask Janine, and I would just
157 00:23:11.720 ⇒ 00:23:15.509 Amber Lin: I’ll just incorporate that into the golden data sheet.
158 00:23:16.540 ⇒ 00:23:18.740 Amber Lin: Yes, perfect.
159 00:23:20.160 ⇒ 00:23:32.890 Amber Lin: I think that’s that’s that. This is mostly on my end. I’ll push it from them, and I’ll get back to you guys. It’s before it’s before our meeting, so I’ll meet with them. Now we’ll meet together. I’ll see. We’ll see how it goes.
160 00:23:32.890 ⇒ 00:23:34.880 Miguel de Veyra: Okay, and.
161 00:23:35.010 ⇒ 00:23:40.429 Amber Lin: Last few parts. Just the Cs, but Csr testing.
162 00:23:40.830 ⇒ 00:23:45.379 Amber Lin: how is it with the with Shannon Grace.
163 00:23:46.260 ⇒ 00:23:49.409 Miguel de Veyra: I haven’t met. This is the 1st time we’re gonna be talking with them.
164 00:23:49.410 ⇒ 00:23:55.699 Amber Lin: Okay, okay, we have their emails. I’ll amber. Look.
165 00:23:56.090 ⇒ 00:24:05.089 Amber Lin: what is the steps to onboarding? Because I’ll take it from here. But I don’t. I don’t exactly know the technicals of how to onboard them
166 00:24:05.260 ⇒ 00:24:06.350 Amber Lin: exactly.
167 00:24:09.242 ⇒ 00:24:11.430 Miguel de Veyra: On board them to use the app.
168 00:24:11.430 ⇒ 00:24:15.019 Amber Lin: Yeah, yeah. Cause I I imagine we haven’t done that yet.
169 00:24:15.910 ⇒ 00:24:19.030 Miguel de Veyra: No, we haven’t done that yet, but I think it would be
170 00:24:20.030 ⇒ 00:24:25.400 Miguel de Veyra: it they they have to give their email to Tim right? So he can add them. Casey, Jenna.
171 00:24:27.920 ⇒ 00:24:31.309 Janna Wong: Yes, they all need to be added under Tim’s.
172 00:24:32.165 ⇒ 00:24:33.920 Miguel de Veyra: Deal. List. Yeah.
173 00:24:35.580 ⇒ 00:24:40.060 Amber Lin: To add it under Tim’s Gmail
174 00:24:40.600 ⇒ 00:24:49.710 Amber Lin: list. Okay, I will get in touch with them to get them to do that. I guess I can contact Tim directly? Or should I just contact?
175 00:24:50.020 ⇒ 00:24:52.560 Amber Lin: We have Tim’s email right?
176 00:24:52.700 ⇒ 00:25:07.119 Miguel de Veyra: Yeah, yeah, I think he’s on the he’s on the thread, the email thread. What do you? What do you? I think what you can do is, hey? We’re gonna be onboarding the 2 people. And then here’s their emails. If you could give them access to the bot, he would know what to do.
177 00:25:07.380 ⇒ 00:25:14.500 Amber Lin: Okay ask him to give access, and then from there, I guess.
178 00:25:15.130 ⇒ 00:25:21.459 Amber Lin: do we have, like a guide document that we can send them? Or do we have to tell them in person.
179 00:25:21.840 ⇒ 00:25:25.249 Miguel de Veyra: We don’t have a standard. This is the 1st time.
180 00:25:25.250 ⇒ 00:25:33.319 Amber Lin: That’s good. We can try creating that because it will be helpful for the people. We’ll probably have to produce that eventually.
181 00:25:34.630 ⇒ 00:25:41.499 Amber Lin: So what would be the 1st step after they’re edit, added. I just want to know one step after that.
182 00:25:42.640 ⇒ 00:25:45.459 Miguel de Veyra: Hmm, I think the 1st step is, we should probably
183 00:25:45.690 ⇒ 00:25:49.929 Miguel de Veyra: well, not really first, st but we should probably create a loom video on how to access the bot.
184 00:25:49.930 ⇒ 00:25:53.399 Amber Lin: Hmm, hmm, hey? That’s a really good idea.
185 00:25:53.550 ⇒ 00:25:56.090 Amber Lin: Video on how to.
186 00:25:56.600 ⇒ 00:26:01.549 Amber Lin: And I will. Also. I will also appreciate that, too, because I don’t know either.
187 00:26:01.550 ⇒ 00:26:02.830 Miguel de Veyra: Okay, okay, yeah.
188 00:26:03.010 ⇒ 00:26:12.110 Miguel de Veyra: The fun accessible. Yeah. And then from there. What’s like the sample questions you can ask right? And.
189 00:26:12.110 ⇒ 00:26:18.540 Amber Lin: Yeah, a sample questions we can ask, and then we’ll let them play around with it.
190 00:26:18.540 ⇒ 00:26:29.499 Miguel de Veyra: Yeah. And then I think the important part there is we can show. We have to tell them like this, bot has access to this documents and then share them. The Central Doc.
191 00:26:30.670 ⇒ 00:26:34.520 Amber Lin: Oh, okay. Share. Central.
192 00:26:34.520 ⇒ 00:26:39.270 Miguel de Veyra: Though I’m not sure if no, I think they have access to it. Cause yeah, yeah, never mind.
193 00:26:40.750 ⇒ 00:26:41.420 Miguel de Veyra: little dog.
194 00:26:41.560 ⇒ 00:26:47.790 Amber Lin: Okay, perfect. So I think this is just a essentially all the titles in the Central Doc List.
195 00:26:47.790 ⇒ 00:26:48.540 Miguel de Veyra: Yeah. That was.
196 00:26:48.540 ⇒ 00:26:49.350 Amber Lin: It’s easy.
197 00:26:49.560 ⇒ 00:26:52.070 Amber Lin: All headings in central.
198 00:26:52.780 ⇒ 00:26:53.350 Amber Lin: Yeah.
199 00:26:53.780 ⇒ 00:26:57.179 Miguel de Veyra: How is it? Are they gonna be actually taking live phone calls.
200 00:26:58.320 ⇒ 00:27:00.910 Amber Lin: I think so. I think I think
201 00:27:01.330 ⇒ 00:27:10.629 Amber Lin: that’s the idea. So they would be. They would play around with it a little bit, has some sample questions, and they will probably try to use it during their calls.
202 00:27:11.250 ⇒ 00:27:14.619 Miguel de Veyra: But aren’t most of the data outdated that they gave us.
203 00:27:15.046 ⇒ 00:27:20.163 Amber Lin: I see I will bring that. I will bring that up to
204 00:27:20.590 ⇒ 00:27:24.860 Miguel de Veyra: Yeah, cause we might end up getting blamed for, hey? Your bot performed wrong.
205 00:27:24.860 ⇒ 00:27:33.680 Amber Lin: I know. Tell Janine that the data. Okay, I think then this week, until they update it, we’re just gonna let the Csrs play around and get familiar with that.
206 00:27:34.050 ⇒ 00:27:41.070 Miguel de Veyra: Yeah, they probably have a questionnaire like a test stuff. And then they’re probably gonna use the bot to try and pass that thing.
207 00:27:41.070 ⇒ 00:27:42.130 Amber Lin: Yeah, yeah.
208 00:27:42.130 ⇒ 00:27:45.800 Miguel de Veyra: That’s probably how it’ll go. I doubt they’re gonna cause I think their train is. They’re fairly new
209 00:27:46.160 ⇒ 00:27:48.740 Miguel de Veyra: there. I think. There, that’s the 1st round of trainees.
210 00:27:48.740 ⇒ 00:27:56.019 Amber Lin: Check if they if Shannon and Grace is new or not, how experienced.
211 00:27:56.220 ⇒ 00:27:58.029 Amber Lin: Okay, that’s good.
212 00:27:58.300 ⇒ 00:28:00.869 Amber Lin: Can’t provide that.
213 00:28:01.010 ⇒ 00:28:09.559 Amber Lin: Yeah, I will tell that to Janine, so that we are not blamed for inaccuracy.
214 00:28:09.560 ⇒ 00:28:12.099 Miguel de Veyra: Yes, yes, because we can’t do anything about that.
215 00:28:12.320 ⇒ 00:28:23.640 Amber Lin: Yes, I will highlight this, these 2. So I’ll do that today. I think these things we can. We can wait later. But sometime in the early early this week.
216 00:28:23.970 ⇒ 00:28:27.249 Amber Lin: Monday to Wednesday, probably.
217 00:28:28.000 ⇒ 00:28:32.020 Amber Lin: And yeah, let me.
218 00:28:32.210 ⇒ 00:28:34.140 Amber Lin: That’s for me.
219 00:28:34.820 ⇒ 00:28:39.330 Amber Lin: And then this is this is kind of what you guys are working on right.
220 00:28:40.312 ⇒ 00:28:43.690 Miguel de Veyra: Improve speed and accuracy. I think we are.
221 00:28:43.850 ⇒ 00:28:49.679 Miguel de Veyra: Casey. Correct me if I’m wrong, but I think that we are at the maximum right cause. We are at around 5 to 10 seconds.
222 00:28:50.440 ⇒ 00:28:53.720 Casie Aviles: Yeah, yeah, we did improvements last week.
223 00:28:54.670 ⇒ 00:29:17.699 Miguel de Veyra: 3 to 5 seconds is gonna be pretty tough, because, like there’s so much platforms, it’s going. But the Steve, I think the C. I’m not sure what, Steve, but I think he’s the highest ranked person we’ve talked to, he said, like 10 seconds is like the goal. I think we’re below that around 3, I think some replies. Take 3 seconds, some take 8. The worst I’ve seen is like 11. So I think we’re pretty safe.
224 00:29:18.470 ⇒ 00:29:19.230 Amber Lin: Okay, so.
225 00:29:19.230 ⇒ 00:29:24.749 Casie Aviles: Average. Yeah, based on my tests. We had an average of 7 seconds.
226 00:29:26.160 ⇒ 00:29:30.389 Miguel de Veyra: So I think this one is like we want would probably be working on this.
227 00:29:30.390 ⇒ 00:29:31.770 Amber Lin: Yeah, okay.
228 00:29:31.770 ⇒ 00:29:33.590 Miguel de Veyra: This is the lowest priority.
229 00:29:33.590 ⇒ 00:29:37.270 Amber Lin: Okay, Lois, what about accuracy?
230 00:29:37.640 ⇒ 00:29:39.140 Miguel de Veyra: After that, see is.
231 00:29:39.140 ⇒ 00:29:39.720 Amber Lin: A dog.
232 00:29:39.720 ⇒ 00:29:41.199 Miguel de Veyra: Based on them. Yeah.
233 00:29:41.380 ⇒ 00:29:53.530 Amber Lin: Oh, okay, but I remember last time we said, it’s 40% accuracy for the golden data set is the golden data set up to date, or is it not up to date as well.
234 00:29:53.530 ⇒ 00:29:57.690 Miguel de Veyra: With the Golden data set is it’s not complete. So it can’t really be used to. You know.
235 00:29:57.690 ⇒ 00:29:58.839 Amber Lin: Oh no!
236 00:29:59.750 ⇒ 00:30:03.610 Miguel de Veyra: It like there’s nothing there’s technically nothing in there.
237 00:30:03.770 ⇒ 00:30:06.460 Miguel de Veyra: So it can’t really be used to be.
238 00:30:06.720 ⇒ 00:30:07.280 Amber Lin: Oh!
239 00:30:07.280 ⇒ 00:30:08.140 Miguel de Veyra: Answered.
240 00:30:08.920 ⇒ 00:30:10.022 Amber Lin: Okay, I see.
241 00:30:12.530 ⇒ 00:30:14.070 Amber Lin: There we go.
242 00:30:14.350 ⇒ 00:30:15.690 Amber Lin: And
243 00:30:16.070 ⇒ 00:30:25.070 Amber Lin: so I’ll put this as lower priority. I think if I get more of the golden data set. We can put something on that.
244 00:30:25.070 ⇒ 00:30:32.269 Miguel de Veyra: Yeah, can you add a task under the golden data set for me, please? It’s just add the Faqs into the bot.
245 00:30:34.600 ⇒ 00:30:36.090 Amber Lin: FAQ.
246 00:30:36.090 ⇒ 00:30:37.470 Miguel de Veyra: Yeah, for the bottom.
247 00:30:37.470 ⇒ 00:30:39.440 Amber Lin: Into the thought, What’s that for.
248 00:30:40.429 ⇒ 00:30:44.169 Miguel de Veyra: Cause. I think some of the Faqs weren’t on the bot
249 00:30:44.600 ⇒ 00:30:52.420 Miguel de Veyra: like we don’t have access to it. It’s just now ideal is. We’ve added it to the golden data set. But it’s not on the bot. So I actually have to put that on the bot.
250 00:30:53.020 ⇒ 00:30:55.940 Amber Lin: Oh, okay, okay, I think.
251 00:30:56.800 ⇒ 00:31:07.280 Amber Lin: yeah, this time, this time around, I’m also gonna confirm with Janine what are the most frequent questions in the media. We brought up something that’s.
252 00:31:07.280 ⇒ 00:31:08.589 Miguel de Veyra: It’s they gave it to us.
253 00:31:09.060 ⇒ 00:31:18.739 Amber Lin: Yeah, the service availability. They said that was the most important aspect. So I’m gonna have them mark which one it is. If they have.
254 00:31:18.740 ⇒ 00:31:22.209 Miguel de Veyra: Do. Sorry. Do you have access to the
255 00:31:22.980 ⇒ 00:31:28.090 Miguel de Veyra: the gold ether email? The brain forge at gold ether? No.
256 00:31:28.800 ⇒ 00:31:30.480 Amber Lin: Rainforge, at.
257 00:31:30.620 ⇒ 00:31:32.599 Miguel de Veyra: Goat eater! Wait! Let me.
258 00:31:32.600 ⇒ 00:31:33.870 Amber Lin: I do not.
259 00:31:34.590 ⇒ 00:31:37.920 Miguel de Veyra: Yeah, cause you need access to that. Wait, let me try to get.
260 00:31:38.190 ⇒ 00:31:39.910 Miguel de Veyra: I don’t have the password.
261 00:31:40.270 ⇒ 00:31:40.990 Amber Lin: In slack.
262 00:31:41.420 ⇒ 00:31:46.340 Miguel de Veyra: No, no, it’s a it’s a Gmail account. It’s where they should wait. Let me try to get it.
263 00:31:46.590 ⇒ 00:31:47.370 Amber Lin: Okay.
264 00:31:48.040 ⇒ 00:31:50.830 Miguel de Veyra: The password manager, Gmail.
265 00:31:58.730 ⇒ 00:32:06.750 Amber Lin: I think, while you work work on that Casey and Jenna, what do you think we can progress on the trainer? Assistive bot?
266 00:32:06.920 ⇒ 00:32:12.970 Amber Lin: So so by next Friday, what do you guys think our progress would be.
267 00:32:14.890 ⇒ 00:32:23.410 Casie Aviles: Oh, for, like internally, we actually have, like a pending task that I think it’s an ad hoc task for sales that
268 00:32:25.139 ⇒ 00:32:35.019 Casie Aviles: we want. We need to create like a a automated lead list builder for Robert, like he was asking that from last week. So that’s also something we plan to
269 00:32:35.290 ⇒ 00:32:37.359 Casie Aviles: spend some time working on this week.
270 00:32:38.243 ⇒ 00:32:39.330 Amber Lin: Let me.
271 00:32:39.916 ⇒ 00:32:41.819 Amber Lin: That’s really nice, too.
272 00:32:42.080 ⇒ 00:32:44.130 Amber Lin: I will note that down.
273 00:32:44.660 ⇒ 00:32:45.830 Amber Lin: Second one.
274 00:32:46.140 ⇒ 00:32:51.191 Amber Lin: Okay, that will spend. Oh, I see. That will take some time.
275 00:32:52.870 ⇒ 00:32:56.210 Amber Lin: What about how long do you think that would take.
276 00:32:58.840 ⇒ 00:32:59.820 Casie Aviles: Hmm!
277 00:33:00.740 ⇒ 00:33:05.589 Casie Aviles: I think maybe until I guess Wednesday or Thursday.
278 00:33:07.100 ⇒ 00:33:08.299 Amber Lin: That’s good to know.
279 00:33:08.840 ⇒ 00:33:23.159 Amber Lin: And let’s see. So I think this week I can be pushing on my end to get their data here, and then we also want to have a few things that we can present to them to say, hey, we worked on these things on Friday.
280 00:33:23.230 ⇒ 00:33:40.000 Amber Lin: So I think eval evals is great for our end, and I think they also want to see something improving on the bot’s performance, because that’s how they that’s they. That’s how they feel. When they interact with the bot. Right? So.
281 00:33:40.000 ⇒ 00:33:43.360 Miguel de Veyra: Did you present the speed last Friday or not? Really.
282 00:33:43.360 ⇒ 00:33:47.010 Amber Lin: Yeah, I did I? I showed them the difference. I showed them.
283 00:33:47.010 ⇒ 00:33:47.560 Miguel de Veyra: Council.
284 00:33:47.560 ⇒ 00:33:56.150 Amber Lin: Screenshots from before. That was like almost 40 something seconds. And I showed them the around lower than 10 seconds, and they were quite impressed.
285 00:34:00.880 ⇒ 00:34:01.989 Amber Lin: Yeah, I think.
286 00:34:03.810 ⇒ 00:34:06.329 Miguel de Veyra: Or let me send this to you. Amber, real quick.
287 00:34:06.692 ⇒ 00:34:09.588 Amber Lin: On slack, please, so that it doesn’t disappear.
288 00:34:12.429 ⇒ 00:34:13.630 Miguel de Veyra: Or something like that.
289 00:34:19.239 ⇒ 00:34:22.140 Miguel de Veyra: There you go. Yeah, cause I need to add the security.
290 00:34:27.650 ⇒ 00:34:31.519 Miguel de Veyra: Oh, what happened to the Okrs? By the way.
291 00:34:33.510 ⇒ 00:34:34.010 Amber Lin: So.
292 00:34:34.010 ⇒ 00:34:38.650 Casie Aviles: For the okrs. We did like a didn’t we pause last week for that.
293 00:34:39.500 ⇒ 00:34:45.109 Miguel de Veyra: Yeah. But is it like, is it just for that week, or are we like to evaluating everything?
294 00:34:47.719 ⇒ 00:34:50.659 Miguel de Veyra: Okay, ours are in notion. It’s like the
295 00:34:51.989 ⇒ 00:34:54.350 Miguel de Veyra: what’s the definition of Opr again? PC, sorry.
296 00:34:54.570 ⇒ 00:35:00.750 Casie Aviles: It’s a objectives and key responsibilities, key results, key results. I’m sorry.
297 00:35:00.750 ⇒ 00:35:02.650 Amber Lin: Yeah. Oh, oh, yeah, okay, yeah.
298 00:35:02.820 ⇒ 00:35:08.259 Amber Lin: I know that we’re trying to decrease your 1st call resolution.
299 00:35:08.460 ⇒ 00:35:11.939 Amber Lin: But we can’t really get that before we actually have them call.
300 00:35:12.297 ⇒ 00:35:15.160 Miguel de Veyra: No, no, there’s like a different company. Okr.
301 00:35:15.510 ⇒ 00:35:16.180 Amber Lin: Oh! That!
302 00:35:16.180 ⇒ 00:35:18.650 Casie Aviles: That’s the junior Pm. Stuff.
303 00:35:19.070 ⇒ 00:35:24.550 Miguel de Veyra: Yeah, yeah, I’m I’m not sure, though. Are we gonna stop that completely, or are we gonna proceed with.
304 00:35:24.990 ⇒ 00:35:34.419 Casie Aviles: Well, the thing is for okrs, like, before I switched over to work on ABC, I was working on the Okr, so I was owning that
305 00:35:35.387 ⇒ 00:35:40.450 Casie Aviles: but yeah, since last week, like I started to also pair with you on
306 00:35:40.840 ⇒ 00:35:43.770 Casie Aviles: ABC stuff, right? So that’s why it was paused.
307 00:35:44.860 ⇒ 00:35:45.270 Amber Lin: Let’s see.
308 00:35:45.270 ⇒ 00:35:46.090 Casie Aviles: So
309 00:35:47.260 ⇒ 00:36:04.990 Amber Lin: I believe, for the Junior Pm. Stuff. The Pm. Team is having a meeting, and I know that it’s really hard to push on creating a bot or something for the Pm. Stuff when we don’t know the processes in the Pm, so in different teams. So I am gonna
310 00:36:05.030 ⇒ 00:36:26.519 Amber Lin: meet later today, and they’ll probably meet with different teams to get their processes and then get that part going. So Casey, I’ll probably talk to you or talk if what whoever is working on that okay are, I will talk to you guys to gather what kind of stuff you guys need and then I will.
311 00:36:26.830 ⇒ 00:36:30.640 Amber Lin: but that I’ll keep that in mind when I meet with the different people.
312 00:36:31.920 ⇒ 00:36:33.029 Casie Aviles: Yes, sounds good.
313 00:36:33.260 ⇒ 00:36:39.639 Amber Lin: Okay, do you guys know what you would need? Or should I just get a overview of the process first.st
314 00:36:39.850 ⇒ 00:36:44.500 Miguel de Veyra: Oh, wait! We should probably send her the mural.
315 00:36:44.670 ⇒ 00:36:46.539 Miguel de Veyra: I mean, it’s all over the place, but.
316 00:36:46.540 ⇒ 00:36:47.620 Casie Aviles: Okay. Yeah.
317 00:36:47.620 ⇒ 00:36:49.070 Miguel de Veyra: It’s something. It’s.
318 00:36:49.964 ⇒ 00:36:58.669 Amber Lin: Maybe I already have access to that. I don’t know. Maybe that’s for the ABC. Client. Oh, I only have the Miro for the ABC. Client.
319 00:36:58.880 ⇒ 00:37:02.150 Miguel de Veyra: Yeah, it’s this one let me know if you can access it.
320 00:37:05.290 ⇒ 00:37:07.940 Amber Lin: Which it’s the same one for the ABC.
321 00:37:09.280 ⇒ 00:37:10.840 Miguel de Veyra: No, I send it to you via Pm.
322 00:37:10.840 ⇒ 00:37:13.210 Amber Lin: Oh, okay, okay, let me check.
323 00:37:14.870 ⇒ 00:37:15.540 Amber Lin: Okay.
324 00:37:16.040 ⇒ 00:37:16.830 Amber Lin: Oh.
325 00:37:21.480 ⇒ 00:37:24.087 Amber Lin: yeah, I have access to it. Great.
326 00:37:24.600 ⇒ 00:37:30.390 Amber Lin: I will. I will dig deeper. I’ll take a look I won’t take up your guys’s time on that. Just
327 00:37:31.340 ⇒ 00:37:33.290 Amber Lin: yeah. And.
328 00:37:35.160 ⇒ 00:37:36.829 Casie Aviles: We have a bunch of like.
329 00:37:37.737 ⇒ 00:37:41.210 Casie Aviles: bullet points here, like what we’re trying to build. But
330 00:37:41.530 ⇒ 00:37:52.350 Casie Aviles: yeah, maybe it’s I guess the the issue is that maybe it’s not like what the team needs right now or like, maybe we’re kind of out of touch with, you know, the whole process thing. Since.
331 00:37:52.420 ⇒ 00:37:53.030 Amber Lin: You know.
332 00:37:53.240 ⇒ 00:37:55.039 Miguel de Veyra: And I know we’re gonna switch like a
333 00:37:55.620 ⇒ 00:38:03.189 Miguel de Veyra: do something like linear. Or I don’t know. Right? So that’s I think that’s why this is why this was possible. In the 1st place.
334 00:38:03.190 ⇒ 00:38:15.350 Amber Lin: Yeah, this week we are starting to set up the Pm stuff. So it’s great. I will get back to you guys, especially since we are meeting so often every day. So I’ll I’ll keep you guys posted. This is great.
335 00:38:15.350 ⇒ 00:38:16.650 Miguel de Veyra: That’s why this was paused.
336 00:38:17.190 ⇒ 00:38:17.525 Amber Lin: Yeah.
337 00:38:17.860 ⇒ 00:38:23.520 Miguel de Veyra: Okay, okay, let’s see, let’s continue it getting past. Then. Let’s work on this stuff for
338 00:38:23.900 ⇒ 00:38:25.790 Miguel de Veyra: for Robert. 1st I would say.
339 00:38:25.790 ⇒ 00:38:42.969 Amber Lin: Okay, okay, so that’s for for Robert. First, st I just wanna just before we end the meeting. I just wanna get an idea of how the bot is gonna progress. So are we gonna be able to add any features this week? Maybe after the thing we’re done with Robert, I just want something to present on Friday.
340 00:38:43.140 ⇒ 00:38:46.459 Miguel de Veyra: Oh, working on the tailor system! But.
341 00:38:47.752 ⇒ 00:38:50.329 Miguel de Veyra: What does the trainer system is this like.
342 00:38:50.930 ⇒ 00:38:52.999 Amber Lin: That is the updated information. I’m gonna.
343 00:38:53.000 ⇒ 00:38:55.390 Miguel de Veyra: Add a documentation agent. Okay?
344 00:38:55.390 ⇒ 00:38:57.280 Amber Lin: Human update.
345 00:38:57.530 ⇒ 00:39:02.240 Miguel de Veyra: Okay. Yeah, I guess this one is just because.
346 00:39:03.890 ⇒ 00:39:05.880 Miguel de Veyra: yeah, we can start looking into this.
347 00:39:06.650 ⇒ 00:39:07.190 Amber Lin: Oh! But.
348 00:39:07.190 ⇒ 00:39:08.699 Miguel de Veyra: I guess that’s like a task here.
349 00:39:09.050 ⇒ 00:39:10.550 Amber Lin: Yeah, let me.
350 00:39:10.550 ⇒ 00:39:13.029 Miguel de Veyra: I’ll create. Yeah, I’ll create the specs later.
351 00:39:14.520 ⇒ 00:39:15.690 Amber Lin: This next.
352 00:39:16.180 ⇒ 00:39:20.950 Miguel de Veyra: Yeah, that’s per, basically on what needs to be done from.
353 00:39:21.210 ⇒ 00:39:24.066 Amber Lin: On the bot there.
354 00:39:26.859 ⇒ 00:39:35.209 Amber Lin: Do you want to do that earlier this week? Because this the specs shouldn’t take that long right? It would just take an hour or so.
355 00:39:35.720 ⇒ 00:39:40.319 Miguel de Veyra: Oh, yeah, yeah, I’ll probably finish it today. To be honest, then I’ll con I’ll convene with case.
356 00:39:40.760 ⇒ 00:39:44.570 Amber Lin: Yeah, okay, let me also highlight this.
357 00:39:44.990 ⇒ 00:39:51.160 Amber Lin: I think this is some team that’s working this plastic.
358 00:39:54.550 ⇒ 00:39:57.910 Amber Lin: Okay? And then evals with.
359 00:39:57.910 ⇒ 00:39:58.530 Miguel de Veyra: Rainforce.
360 00:39:58.837 ⇒ 00:40:04.370 Amber Lin: I know we already set up the account, but I know we also are not using them yet.
361 00:40:06.750 ⇒ 00:40:08.510 Miguel de Veyra: Casey, do you want to take over here.
362 00:40:08.820 ⇒ 00:40:14.199 Casie Aviles: No, we’re using. We’re using the account. But there’s just, you know, some code stuff that we haven’t done yet.
363 00:40:14.860 ⇒ 00:40:15.480 Amber Lin: Hmm.
364 00:40:15.790 ⇒ 00:40:20.499 Miguel de Veyra: Basically implementing it to Google, how are we done implementing it to Google or not yet.
365 00:40:20.700 ⇒ 00:40:21.290 Casie Aviles: Nope.
366 00:40:21.730 ⇒ 00:40:22.840 Miguel de Veyra: Yeah, yeah, that one.
367 00:40:24.760 ⇒ 00:40:30.569 Amber Lin: Oh, okay, okay, this is more back end stuff. So I don’t think the client would notice or care. So I I think we can.
368 00:40:30.570 ⇒ 00:40:32.209 Miguel de Veyra: Do they have access to this or no?
369 00:40:32.620 ⇒ 00:40:33.700 Amber Lin: Do they.
370 00:40:34.260 ⇒ 00:40:36.079 Miguel de Veyra: To this, Doc or no. The client.
371 00:40:36.340 ⇒ 00:40:39.620 Amber Lin: This one. This is. This is in my private one. So I.
372 00:40:39.620 ⇒ 00:40:40.529 Miguel de Veyra: Oh, okay. Okay.
373 00:40:40.530 ⇒ 00:40:45.080 Amber Lin: Guys, I will share our stuff with you guys later. But this is just for us.
374 00:40:45.080 ⇒ 00:40:49.909 Miguel de Veyra: Okay. Okay, okay, okay, yeah. I think that’s pretty much it.
375 00:40:50.090 ⇒ 00:40:56.450 Amber Lin: Okay, you guys also told me that we wanna update the code, send the new code to the client.
376 00:40:57.698 ⇒ 00:41:01.879 Miguel de Veyra: Yeah, that’s that’s the using Google, but need to implement with code.
377 00:41:02.680 ⇒ 00:41:03.840 Amber Lin: Oh!
378 00:41:03.840 ⇒ 00:41:11.590 Miguel de Veyra: So we’re still implementing it into our own. We’re trying to implement it into our own Google, 1st to make sure it’s working, and then we’ll send it to the client.
379 00:41:15.570 ⇒ 00:41:19.440 Amber Lin: How long? When do you guys estimate? We can have that by.
380 00:41:20.570 ⇒ 00:41:23.150 Miguel de Veyra: Can we do that by end of day? Case here? Not yet.
381 00:41:24.230 ⇒ 00:41:25.440 Amber Lin: Hmm sorry.
382 00:41:27.940 ⇒ 00:41:28.910 Casie Aviles: End of day.
383 00:41:29.070 ⇒ 00:41:32.780 Miguel de Veyra: Maybe not. No, no, sorry I’m I’m asking Casey.
384 00:41:33.060 ⇒ 00:41:33.840 Amber Lin: Okay.
385 00:41:35.720 ⇒ 00:41:37.840 Casie Aviles: I mean. Yeah, I guess I’ll
386 00:41:38.050 ⇒ 00:41:45.410 Casie Aviles: work on. I’m just a little like I’m not. I’m not. Which. Which should I work on first, st like. There’s also Robert stuff and.
387 00:41:45.580 ⇒ 00:41:51.569 Miguel de Veyra: Yeah, why can’t we pass there, Robert? Cause for China? Because technically, that’s the internal team, right?
388 00:41:53.050 ⇒ 00:41:56.509 Casie Aviles: Hmm, yeah, yeah, that’s for us, for Brainforge.
389 00:41:57.150 ⇒ 00:41:57.990 Miguel de Veyra: Yeah.
390 00:41:57.990 ⇒ 00:41:59.380 Amber Lin: Who’s gonna work on it?
391 00:42:03.120 ⇒ 00:42:04.829 Miguel de Veyra: I think what we can do is
392 00:42:05.610 ⇒ 00:42:08.810 Miguel de Veyra: have you built something like the one room
393 00:42:09.090 ⇒ 00:42:11.229 Miguel de Veyra: Robert is asking Casey. You’re not there.
394 00:42:12.345 ⇒ 00:42:19.200 Casie Aviles: Just not entirely. Because, you know, I I need to do some scraping there like an automated scraper.
395 00:42:21.080 ⇒ 00:42:22.770 Miguel de Veyra: Okay, I think for this.
396 00:42:24.050 ⇒ 00:42:28.399 Miguel de Veyra: Yeah, let’s just move Jana. So we can. She can start working on the internal stuff.
397 00:42:28.610 ⇒ 00:42:30.889 Miguel de Veyra: And then we can focus on the client stuff.
398 00:42:33.400 ⇒ 00:42:35.020 Casie Aviles: Because that was the plan.
399 00:42:35.410 ⇒ 00:42:39.790 Miguel de Veyra: Yeah, yeah, that was, yeah. That was the original plan with uten.
400 00:42:40.570 ⇒ 00:42:41.525 Amber Lin: Okay.
401 00:42:42.920 ⇒ 00:42:43.250 Casie Aviles: So.
402 00:42:43.650 ⇒ 00:42:50.829 Amber Lin: So I can have you guys work on the I’ll have Casey and Miguel work on the client stuff.
403 00:42:51.350 ⇒ 00:42:58.550 Amber Lin: So push this a little bit, because since the Csr bot is so dependent on them, I think
404 00:42:58.930 ⇒ 00:43:09.090 Amber Lin: for us to present something for the client to feel like, oh, we’re gonna continue working with them. We probably need to push a little bit more on the document update.
405 00:43:09.710 ⇒ 00:43:10.220 Miguel de Veyra: Yeah.
406 00:43:10.220 ⇒ 00:43:11.650 Amber Lin: Something to show them.
407 00:43:12.140 ⇒ 00:43:19.700 Amber Lin: So I will say that we can have this, not that one and anything else.
408 00:43:21.182 ⇒ 00:43:30.699 Amber Lin: Oh, yeah, we’ll push this spot a little bit, and then we will need to send a new code to the client.
409 00:43:30.970 ⇒ 00:43:41.619 Amber Lin: because what they care about is what they see. So for the internal evals that’s for us. But they want to see. Oh, you have new code. Oh, you have this new thing. So
410 00:43:41.860 ⇒ 00:43:42.350 Amber Lin: okay.
411 00:43:42.685 ⇒ 00:43:49.729 Miguel de Veyra: We’ll probably have the document update, like as an initial version of it. By by Friday I’ll I’ll start with it.
412 00:43:50.890 ⇒ 00:43:51.770 Amber Lin: You mean.
413 00:43:51.770 ⇒ 00:43:53.400 Miguel de Veyra: The document update bar.
414 00:43:54.030 ⇒ 00:43:54.570 Amber Lin: Okay.
415 00:43:54.570 ⇒ 00:43:59.339 Miguel de Veyra: We could probably present, so I not really present, but show what we can do. On Friday.
416 00:43:59.340 ⇒ 00:44:10.540 Amber Lin: Yeah, yeah, totally. That is awesome. That’s awesome. And we will have. Oh, sorry. Not that show, right?
417 00:44:12.470 ⇒ 00:44:17.689 Amber Lin: And what about the this new code is for the Csr bots right?
418 00:44:19.510 ⇒ 00:44:28.079 Miguel de Veyra: Yeah, yeah, we’ll probably see, yeah, we basically have. We’ll end up having to send them 2 codes, one for the Csr and one for the update.
419 00:44:29.840 ⇒ 00:44:40.229 Amber Lin: And send send code on Friday, Thursday. Question mark
420 00:44:41.205 ⇒ 00:44:47.819 Amber Lin: we or we can just show them on Friday. We might not even have to send them the code that on before that meeting.
421 00:44:47.960 ⇒ 00:44:59.169 Miguel de Veyra: Yeah, yeah, we’ll never show the code on meeting. It’s just we have to email it to them. So Shannon and I forgot the other girl’s name. They can. They can play around with it.
422 00:44:59.170 ⇒ 00:45:07.590 Amber Lin: Yeah, Shannon and Grace. So okay, I think this update bot is for your vet and janine. So the the managers can Update a Doc.
423 00:45:07.960 ⇒ 00:45:08.610 Miguel de Veyra: Yeah.
424 00:45:08.610 ⇒ 00:45:26.029 Amber Lin: Same thing. Same thing. Okay? I think that’s that’s all. Send new posted client. We can send that. I will push on. I’ll remind you guys or ask you guys about when we have implemented to Google.
425 00:45:26.460 ⇒ 00:45:36.416 Amber Lin: And so right now, let’s look at all the tasks. I know that I’m gonna meet with Janine. I’m gonna get the questions about the golden data set.
426 00:45:36.950 ⇒ 00:45:45.350 Amber Lin: and oh, I’m gonna push on that. And then for the team we have
427 00:45:45.740 ⇒ 00:45:52.500 Amber Lin: Miguel and Casey working on the client stuff, and Jenna is working on the task for Robert
428 00:45:53.290 ⇒ 00:46:03.139 Amber Lin: and for the client staff. We should research the feedback system, we should create a loom video.
429 00:46:03.930 ⇒ 00:46:13.100 Amber Lin: And and then this, I don’t know when you want to do it.
430 00:46:13.480 ⇒ 00:46:16.000 Amber Lin: You wanna do it today, or a different.
431 00:46:16.000 ⇒ 00:46:18.859 Miguel de Veyra: Yeah, that’s gonna be that’s gonna be fast. I’ll just add it.
432 00:46:19.120 ⇒ 00:46:24.579 Amber Lin: Okay, okay, sounds good, that. And then implementing the cs.
433 00:46:24.810 ⇒ 00:46:29.439 Amber Lin: the bot, I don’t know what what this is for implementing what to our own Google.
434 00:46:30.207 ⇒ 00:46:32.079 Miguel de Veyra: Basically, we wanna test
435 00:46:32.190 ⇒ 00:46:45.070 Miguel de Veyra: the implementation of, you know, the new, basically the brain trust code that connects it to the Google chat into our for into our Google cloud platform, basically.
436 00:46:45.070 ⇒ 00:46:45.420 Amber Lin: Okay.
437 00:46:45.420 ⇒ 00:46:48.100 Miguel de Veyra: So we can test it 1st before we hand it off to them.
438 00:46:48.370 ⇒ 00:46:50.580 Amber Lin: Yeah, can we do that today?
439 00:46:51.300 ⇒ 00:46:55.199 Miguel de Veyra: No cause. Brain trust isn’t done. This is dependent on brain trust.
440 00:46:55.200 ⇒ 00:46:59.680 Amber Lin: Okay, okay, set up right?
441 00:47:00.090 ⇒ 00:47:02.549 Amber Lin: Trust this, we can do today.
442 00:47:03.090 ⇒ 00:47:06.130 Amber Lin: Okay, that I will change that.
443 00:47:06.980 ⇒ 00:47:14.580 Amber Lin: And we’ll, I will say, have this neglected.
444 00:47:16.939 ⇒ 00:47:24.020 Amber Lin: Okay, okay, so I think today, we know what we need to do.
445 00:47:25.350 ⇒ 00:47:30.699 Amber Lin: And Jana, do you? Are you
446 00:47:30.910 ⇒ 00:47:33.999 Amber Lin: sure of what you would need to do today?
447 00:47:36.154 ⇒ 00:47:40.759 Casie Aviles: I’m going to help Jana with that, like, I’ll give her the details.
448 00:47:41.960 ⇒ 00:47:43.689 Casie Aviles: And yeah, the requirements.
449 00:47:44.640 ⇒ 00:47:45.690 Amber Lin: Fantastic.
450 00:47:46.100 ⇒ 00:47:57.543 Amber Lin: Can I also? Can you also just drop me a copy of that? I’m very interested in what that is because I spent the weekend scraping, and it is so hard it is so hard.
451 00:47:58.125 ⇒ 00:48:00.165 Casie Aviles: Yeah, it is. I got. I got blocked.
452 00:48:00.420 ⇒ 00:48:01.390 Amber Lin: Auditions.
453 00:48:04.620 ⇒ 00:48:09.519 Amber Lin: Okay, is that enough to work on today or too much to work on today, I just wanna check.
454 00:48:14.800 ⇒ 00:48:15.490 Miguel de Veyra: Think it’s fine.
455 00:48:16.290 ⇒ 00:48:17.170 Casie Aviles: Okay. Very neat.
456 00:48:17.390 ⇒ 00:48:17.770 Miguel de Veyra: Yeah.
457 00:48:18.150 ⇒ 00:48:25.630 Amber Lin: I will, I will summarize this. I’ll send this into our chat, and then I will
458 00:48:25.990 ⇒ 00:48:29.359 Amber Lin: type out the assigned tasks. So you guys can have a reference.
459 00:48:29.660 ⇒ 00:48:30.340 Miguel de Veyra: Something.
460 00:48:30.630 ⇒ 00:48:31.580 Amber Lin: Awesome.
461 00:48:31.960 ⇒ 00:48:32.639 Miguel de Veyra: Thank you. Guys.
462 00:48:32.640 ⇒ 00:48:33.809 Miguel de Veyra: Everyone have a good day.
463 00:48:35.380 ⇒ 00:48:38.420 Amber Lin: I’ll see you guys soon. We have another company.
464 00:48:38.710 ⇒ 00:48:39.870 Miguel de Veyra: Yeah, in 20 min.
465 00:48:40.950 ⇒ 00:48:43.210 Amber Lin: Okay, see, you guys, bye-bye.