Meeting Title: Brainforge Intro <> Joshua Michole Date: 2025-04-07 Meeting participants: Miguel De Veyra, Joshua Michole Solon


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1 00:02:40.220 00:02:41.389 Miguel de Veyra: Make a deal.

2 00:02:42.440 00:02:43.589 Miguel de Veyra: Hello, mate!

3 00:02:45.960 00:02:46.780 Joshua Michole Solon: You.

4 00:02:46.780 00:02:51.289 Miguel de Veyra: You wait. Let me just turn this camera on.

5 00:02:54.290 00:02:55.989 Joshua Michole Solon: Time I’ll see.

6 00:03:00.660 00:03:02.250 Miguel de Veyra: You go along.

7 00:03:06.030 00:03:08.099 Miguel de Veyra: There you go. That works.

8 00:03:10.320 00:03:15.049 Miguel de Veyra: Oh, so a bit of opener, though.

9 00:03:20.620 00:03:25.780 Miguel de Veyra: I think after you see you basically.

10 00:03:25.960 00:03:32.250 Miguel de Veyra: So I guess. Wait! Let me just pull up your she.

11 00:03:40.610 00:03:44.580 Miguel de Veyra: After autumn we brought the name terrible 1, 1 grizzly.

12 00:03:45.607 00:03:48.350 Joshua Michole Solon: We’ll see. Conversational AI analyst.

13 00:03:51.350 00:03:53.700 Miguel de Veyra: Oh, conversation data. Yeah.

14 00:03:54.420 00:03:56.430 Miguel de Veyra: So more on part of analytics, sir.

15 00:03:56.680 00:04:04.559 Joshua Michole Solon: No. Still, this, I think, still a bit the same as last time developing a chat bot, but more on dialog flow, cx

16 00:04:05.190 00:04:09.320 Joshua Michole Solon: pair, but it’s it’s not the same as you know.

17 00:04:10.030 00:04:13.360 Miguel de Veyra: Open. AI, it’s basically yeah, workflows.

18 00:04:13.700 00:04:17.060 Joshua Michole Solon: Yeah, so mix of automation. And AI, I think.

19 00:04:20.970 00:04:22.260 Miguel de Veyra: So it’s Google.

20 00:04:22.480 00:04:24.959 Joshua Michole Solon: Yeah, Google suite, or Google Cloud.

21 00:04:25.770 00:04:27.700 Miguel de Veyra: Also, you have experience in Google cloud.

22 00:04:28.030 00:04:29.610 Joshua Michole Solon: A bit. Yeah, with the.

23 00:04:29.610 00:04:33.570 Miguel de Veyra: Chatbots, because that’s where we’re fucking stuck. To be honest.

24 00:04:33.570 00:04:34.660 Joshua Michole Solon: Sorry. What was that?

25 00:04:34.660 00:04:35.986 Miguel de Veyra: Deploying Chatbots.

26 00:04:37.033 00:04:46.610 Joshua Michole Solon: That one not specifically on the deployment. That’s being handled by someone else. I’m more of like the design. And you know, creation of

27 00:04:46.890 00:04:53.579 Joshua Michole Solon: like, how conversations should flow with bots and basically training them as well.

28 00:04:54.940 00:04:55.650 Miguel de Veyra: Okay, so.

29 00:04:56.770 00:05:01.729 Joshua Michole Solon: So young intent. Classification, entity parameterization.

30 00:05:02.586 00:05:03.639 Joshua Michole Solon: You know.

31 00:05:03.640 00:05:04.020 Miguel de Veyra: Yeah.

32 00:05:04.400 00:05:22.864 Joshua Michole Solon: Like we receive. So basically, what what I do is I receive a bunch of messages from our customers, and I I check on them every day or no, every time I have, and then I try to analyze them like how many times you know these kinds of messages with the same meaning.

33 00:05:23.670 00:05:24.600 Miguel de Veyra: Partner, Classification.

34 00:05:24.600 00:05:33.990 Joshua Michole Solon: Yeah, they like they fall under a specific intent. And let’s say, if they, they keep on saying that I want to sell my card, and I put that in a

35 00:05:34.120 00:05:36.149 Joshua Michole Solon: you know intent where it says.

36 00:05:36.670 00:05:37.150 Miguel de Veyra: Salute.

37 00:05:37.150 00:05:41.699 Joshua Michole Solon: Customer wants to sell. Car. Yeah? And then I put that, as you know, one of the

38 00:05:41.920 00:06:02.299 Joshua Michole Solon: I I guess you could say blocks, because how dialog flow Cx works is like there’s like a big diagram, and you have to connect a bunch of I think it’s the same as voice flow before, but voice flow is more on interfacing and dialog flow. Cx. Is more on managing your yeah, basically managing your conversations through bubbles.

39 00:06:06.090 00:06:09.349 Miguel de Veyra: Before voice, flow, now.

40 00:06:09.820 00:06:17.589 Joshua Michole Solon: Yeah. But voice flow is not stuff independent, right? Like you have to connect it to a separate bot.

41 00:06:18.220 00:06:18.920 Miguel de Veyra: Yeah, yeah, yeah.

42 00:06:18.920 00:06:23.540 Joshua Michole Solon: Yeah. So this one, it’s all in dialogflow. Cx.

43 00:06:24.400 00:06:26.120 Miguel de Veyra: Llm. Provider.

44 00:06:26.574 00:06:35.059 Joshua Michole Solon: Actually, no, it like it has its own. I guess you would say machine or AI.

45 00:06:36.040 00:06:37.989 Miguel de Veyra: Okay, that makes sense. Then.

46 00:06:37.990 00:06:45.209 Joshua Michole Solon: But you could also, like, include generative AI into like, for example, in the responses I can have.

47 00:06:45.460 00:06:51.560 Joshua Michole Solon: you know, the bot. Say something generative that’s reliant on something like Gemini right?

48 00:06:52.600 00:07:05.850 Joshua Michole Solon: Or I could just force it like so like so if you remember, like in a in a previous role. There were like complications with people wanting like a fully scripted, but I think dialog flow. Cx. Is more suited

49 00:07:05.980 00:07:12.000 Joshua Michole Solon: for that kind of work, because I could structure the conversation. Flow, you know, as they are.

50 00:07:12.000 00:07:13.209 Miguel de Veyra: To help. Yeah.

51 00:07:13.460 00:07:15.009 Joshua Michole Solon: And I could also.

52 00:07:15.430 00:07:22.604 Joshua Michole Solon: yeah, I could also like upload knowledge base. I guess I mean they they’re they’re also like constantly updating as well, I think there’s like a new.

53 00:07:23.250 00:07:30.800 Joshua Michole Solon: I think they’re renaming it from dialog flow, cx. Into conversational agents. I think that’s more in line now with you know.

54 00:07:30.970 00:07:31.950 Miguel de Veyra: So- so it’s high.

55 00:07:31.950 00:07:32.370 Joshua Michole Solon: Before.

56 00:07:32.370 00:07:40.019 Miguel de Veyra: Are you familiar with Bland? Where there’s like conversational pathways like, Hey, here’s the start. Here’s where you diverges. Do they

57 00:07:40.020 00:07:42.680 Miguel de Veyra: basically resell or information.

58 00:07:43.190 00:08:08.200 Joshua Michole Solon: Like. That’s how that’s how everything is pre templated. I think we have, like a default, start, flow, and then I connect that with the next step of the conversation, or I could loop that to another flow like they could, like all flows, could interact with each other. They could be all interconnected, and you could also like capture or save parameters to send to. You know your database, your

59 00:08:08.500 00:08:11.559 Joshua Michole Solon: your panel, or whatever. So yeah.

60 00:08:12.820 00:08:19.299 Joshua Michole Solon: so like one of the things that I’ve helped develop. There was in like selling products.

61 00:08:19.420 00:08:31.100 Joshua Michole Solon: Sometimes we have buyers that will renege or, you know, not. Continue the sale with us, and we would classify that as a failed sale, but not a totally like

62 00:08:31.740 00:08:40.239 Joshua Michole Solon: cold case, I guess, and we would like set up a trigger or condition wherein it would fall under a recovery flow.

63 00:08:40.340 00:08:45.869 Joshua Michole Solon: We’re in. We have an automated text message being sent out to those customers, and then, you know.

64 00:08:45.870 00:08:46.320 Miguel de Veyra: So.

65 00:08:46.320 00:08:55.660 Joshua Michole Solon: We would say something like you know we still have your offer of this and that from last week. Are you still interested in, you know, pursuing that

66 00:08:55.820 00:09:03.099 Joshua Michole Solon: offer. So if they respond, then, you know, that’s already like the start of my conversational flow.

67 00:09:03.170 00:09:25.129 Joshua Michole Solon: we’re in. It will like try to categorize what their responses are. So if they say like the offer is too low. I would like direct it to a flow that is about, you know, pitching and a renegotiation. So if they say that, yeah, I wanna proceed. So there’s like another flow that’s more about acceptance. And then it will send a parameter to our panel.

68 00:09:25.150 00:09:34.879 Joshua Michole Solon: and then it will, you know, run something in the Api, or with a background, and then it will notify our live agents that you know this is an accepted sale. We need to schedule a pickup we need to schedule, you know.

69 00:09:34.880 00:09:35.760 Miguel de Veyra: Something. Yeah.

70 00:09:35.760 00:09:36.560 Joshua Michole Solon: Something like that.

71 00:09:37.520 00:09:43.639 Miguel de Veyra: Oh, okay, so more on, basically analytics, television and classification.

72 00:09:44.468 00:09:50.370 Joshua Michole Solon: Yeah, I guess so in in that sense. But they’re still like building the the flow itself.

73 00:09:50.900 00:09:54.339 Miguel de Veyra: Okay, let me show you something. Have you? Have you looked into anything.

74 00:09:54.340 00:09:58.020 Joshua Michole Solon: Yeah, I think, that’s 1

75 00:09:58.450 00:10:15.339 Joshua Michole Solon: the tools that I looked into where I was applying for other jobs. And they they showed me the N. 8. And I was like also this is like a mesh of automation now, and AI like it’s still like bubbling right like there’s flows that you can drag and drop. Yeah, something like that.

76 00:10:15.550 00:10:18.920 Miguel de Veyra: So this is basically one of our like bigger clients. Right now.

77 00:10:20.290 00:10:26.919 Miguel de Veyra: the conversational agent is because the way it works is there’s triggers. And then whatever you want to add it, of course.

78 00:10:28.450 00:10:32.010 Miguel de Veyra: and then you know the agent. And then this is basically.

79 00:10:32.310 00:10:34.180 Joshua Michole Solon: All without the Z period. Yeah.

80 00:10:34.180 00:10:40.319 Miguel de Veyra: Yeah, yeah, don’t, because it’s super expensive. And then basically, here’s the analytics that we built ourselves.

81 00:10:40.460 00:10:44.510 Joshua Michole Solon: So based on the out, the input and the output, you grade it right.

82 00:10:44.890 00:10:47.910 Miguel de Veyra: And then after that, you know, we

83 00:10:48.240 00:10:54.380 Miguel de Veyra: send it. If it’s an error, we log it into sheets. That’s what the client wants, and then we just send it to ourselves.

84 00:10:54.690 00:10:55.360 Joshua Michole Solon: Yeah.

85 00:10:55.360 00:11:04.990 Miguel de Veyra: So it’s basically honestly, a bit. SIM simple, like the Chatbot itself is simple. But what the complicated part is is because are you? Probably not.

86 00:11:05.200 00:11:10.540 Miguel de Veyra: But the real data. This one is the one we use for basically visualizing everything

87 00:11:11.690 00:11:16.540 Miguel de Veyra: because canvas dash. I’m not sure even if it if it’s done or not yet.

88 00:11:18.140 00:11:19.580 Miguel de Veyra: and let me just show.

89 00:11:19.580 00:11:20.959 Joshua Michole Solon: So like the reporting dashboards.

90 00:11:20.960 00:11:21.800 Joshua Michole Solon: Yes, yeah.

91 00:11:22.140 00:11:33.879 Miguel de Veyra: So we have like a data engineer that works with us. So how many thumbs up? Because this is deployed in Google chat? Right? So it thumbs up, thumbs down, and then what’s the average execution time before they get to reply, and then.

92 00:11:33.880 00:11:34.260 Joshua Michole Solon: Yeah.

93 00:11:34.260 00:11:41.501 Miguel de Veyra: How many errors. So this is the the way we’re the one we’re tracking a lot. And this is all automated. We don’t. Wanna you know.

94 00:11:41.780 00:11:44.562 Joshua Michole Solon: Same for for us. But we’re using SQL,

95 00:11:45.350 00:11:55.620 Joshua Michole Solon: you know. Fancy reporting dashboard. So I got tableau, and then it would send me like reports about how many messages of this type have come in, how many you know.

96 00:11:56.050 00:12:00.600 Joshua Michole Solon: how many parameters have not been recorded or failed or not match.

97 00:12:01.010 00:12:10.940 Miguel de Veyra: Oh, yeah, actually, this is also in sequel. So one of the things we want to add is basically cause there’s like, for example, a client asks for termite shit

98 00:12:11.499 00:12:17.280 Miguel de Veyra: like, hey? If you have a termite problem, you know, you could also try this product. They call it upselling.

99 00:12:17.520 00:12:29.359 Miguel de Veyra: So that’s that’s basically we. One thing we want to track also because it’s what it’s a way for us to earn money basically is how many upsells we did right the what helped them.

100 00:12:29.690 00:12:32.280 Miguel de Veyra: But the thing is only some problem. Again, the details.

101 00:12:32.590 00:12:40.070 Miguel de Veyra: It’s not the users that are actually talking. It’s like my customer support. It’s just assisting them, basically being them a bit better.

102 00:12:41.010 00:12:43.749 Miguel de Veyra: So it’s it’s not really changing them right.

103 00:12:44.710 00:12:45.370 Joshua Michole Solon: Yeah.

104 00:12:45.370 00:12:51.659 Miguel de Veyra: So yeah, that’s basically it. I think it would be a good fit, especially the background you have.

105 00:12:56.000 00:12:56.849 Joshua Michole Solon: No nda.

106 00:12:57.010 00:12:58.410 Miguel de Veyra: And sample work.

107 00:12:59.300 00:13:04.259 Joshua Michole Solon: Yeah, company. And also, like everything is customized to their end. So I can’t really.

108 00:13:04.590 00:13:06.590 Miguel de Veyra: Yeah, yeah, okay, yeah, that’s fine.

109 00:13:07.220 00:13:11.670 Joshua Michole Solon: Like they have their own panels. They have their own website. And it’s a software using.

110 00:13:12.000 00:13:16.809 Miguel de Veyra: Okay. Okay? So I, honestly, we only have because there’s 2 parts of the business

111 00:13:16.940 00:13:32.420 Miguel de Veyra: data, which is the main part. There’s like 6 or 7 clients there that pay a lot of money like they’re all. I think they’re like tens of thousands monthly. So no, no, it’s 1 client per person.

112 00:13:33.420 00:13:34.390 Miguel de Veyra: So it’s good.

113 00:13:34.550 00:13:44.559 Miguel de Veyra: But the thing is what what we do is we also treat, because basically, Oh, Casey, and there’s another girl. See, Jana, but I don’t know if she’s still with us to be honest, but she’s on and off.

114 00:13:46.490 00:13:58.439 Miguel de Veyra: The thing is right. Now. I’m basically writing the technical components in charge of recruiting and everything. And then Case is basically alone in the development I tried to help out. But you know, they don’t want me to develop anymore.

115 00:13:58.870 00:13:59.880 Miguel de Veyra: The thing is.

116 00:14:00.070 00:14:11.130 Miguel de Veyra: there’s clients for for like company clients. And then there’s internal clients. So the marketing team sales team data team. We also want to build AI stuff for them. But since you know.

117 00:14:12.260 00:14:20.210 Miguel de Veyra: that’s why we said told me like, you know, let’s keep hiring. Let’s keep looking for people. And then Casey recommended. Hey? Why not, Josh? Right?

118 00:14:20.700 00:14:23.810 Miguel de Veyra: And then he told me that they’re looking for another job. So.

119 00:14:24.670 00:14:27.270 Joshua Michole Solon: Oh, yeah, a lot of them coming up.

120 00:14:27.740 00:14:29.030 Joshua Michole Solon: Rpg, on.

121 00:14:29.540 00:14:33.030 Miguel de Veyra: Oh, okay, okay, you play. You play game. Is that.

122 00:14:33.030 00:14:33.820 Joshua Michole Solon: Getty.

123 00:14:34.440 00:14:36.500 Miguel de Veyra: No, no! You play another Warhammer game.

124 00:14:37.168 00:14:38.959 Joshua Michole Solon: Space. Marines, you mean.

125 00:14:38.960 00:14:41.240 Miguel de Veyra: No, no. You play another one wrong trailer.

126 00:14:41.522 00:14:42.650 Miguel de Veyra: Rogue trader. Yeah, yeah.

127 00:14:42.650 00:14:48.890 Miguel de Veyra: yeah. Yeah. That one. So I was like, Oh, yeah, yeah. Why not? Let’s invite them like after work hours?

128 00:14:49.180 00:14:51.960 Miguel de Veyra: Oh, why not.

129 00:14:51.960 00:14:53.589 Joshua Michole Solon: Nagaro, trader Cayo.

130 00:14:53.590 00:14:58.329 Miguel de Veyra: In the space. No use that.

131 00:15:00.400 00:15:04.840 Joshua Michole Solon: I think twice now after, like the Dlc.

132 00:15:04.840 00:15:05.540 Miguel de Veyra: Which one.

133 00:15:05.690 00:15:10.120 Joshua Michole Solon: The void void Walkers, Dlc. Or something.

134 00:15:10.120 00:15:11.170 Miguel de Veyra: Oh, okay.

135 00:15:11.340 00:15:15.481 Joshua Michole Solon: I think there’s like an upcoming Dlc. As well. I’ll I’ll probably like replay it again.

136 00:15:15.740 00:15:18.939 Miguel de Veyra: Yeah, I started collecting, you know. Are you familiar with this stuff?

137 00:15:19.580 00:15:20.500 Joshua Michole Solon: Yeah. Figurines.

138 00:15:20.500 00:15:24.669 Miguel de Veyra: Yeah, yeah, I have like, did you paint that yourself?

139 00:15:24.670 00:15:26.860 Miguel de Veyra: No, no, the paintings are there. These are Joy toys.

140 00:15:26.860 00:15:27.540 Joshua Michole Solon: Oh!

141 00:15:28.160 00:15:29.240 Miguel de Veyra: I can’t show the face there.

142 00:15:29.240 00:15:29.640 Joshua Michole Solon: Okay.

143 00:15:29.640 00:15:30.850 Miguel de Veyra: There you go right.

144 00:15:30.970 00:15:33.119 Miguel de Veyra: This is my favorite one by far.

145 00:15:33.120 00:15:35.389 Joshua Michole Solon: You’re a custodians, Fan. Then.

146 00:15:35.390 00:15:37.519 Miguel de Veyra: I know this is Dante blood angels.

147 00:15:37.520 00:15:40.670 Joshua Michole Solon: Oh, okay, I thought, you know, the gold is not really clear.

148 00:15:40.670 00:15:41.250 Miguel de Veyra: Yeah, yeah.

149 00:15:41.250 00:15:41.930 Joshua Michole Solon: Okay.

150 00:15:42.160 00:15:42.900 Miguel de Veyra: This one.

151 00:15:43.550 00:15:46.990 Miguel de Veyra: But yeah, I mean, I think it’s definitely a good fit

152 00:15:47.160 00:15:54.000 Miguel de Veyra: in terms of not to mention in terms of rate and hours, actually.

153 00:15:56.505 00:15:56.960 Joshua Michole Solon: Hello!

154 00:15:58.450 00:16:03.850 Miguel de Veyra: I’ll I’ll chat you on discord with oh.

155 00:16:15.130 00:16:16.670 Joshua Michole Solon: I think you already.

156 00:16:16.920 00:16:21.070 Miguel de Veyra: Oh, yeah, yeah, okay, just just to make sure just to make sure.

157 00:16:21.870 00:16:28.989 Miguel de Veyra: But yeah, I think for rate. And then we use clockify. It’s a time tracking tool.

158 00:16:29.637 00:16:30.500 Joshua Michole Solon: What was that?

159 00:16:30.500 00:16:32.270 Miguel de Veyra: Clock. If I it’s a time timing tool.

160 00:16:32.270 00:16:32.630 Joshua Michole Solon: Bye.

161 00:16:32.630 00:16:42.740 Miguel de Veyra: Though well on screen recording, because I wouldn’t do it like no one else in the company would do it. It’s just to know, basically because they’re very, they’re very like because data company, like they, they want to know where the errors are going and stuff.

162 00:16:42.740 00:16:45.570 Joshua Michole Solon: Time and motion studies. Yeah, before.

163 00:16:45.970 00:16:46.609 Miguel de Veyra: But basically.

164 00:16:46.610 00:16:56.889 Miguel de Veyra: what they do is Internet. Because, honestly, you don’t have to log what you did. It’s just to which client you’re working on. So they know, because the numbers came in the end right.

165 00:16:56.890 00:17:00.040 Joshua Michole Solon: Are? Are your working hours like flexible.

166 00:17:01.036 00:17:05.559 Miguel de Veyra: Yeah, it’s flexible. But usually we usually work this like the way.

167 00:17:06.786 00:17:08.280 Joshua Michole Solon: Based today.

168 00:17:08.700 00:17:16.709 Miguel de Veyra: And then, you know, I tried to be on them because me and Casey, we basically every day hop on like an hour or 2 about work and shit.

169 00:17:16.890 00:17:20.460 Joshua Michole Solon: Oh, okay, I thought it was like a regular 9 to 5.

170 00:17:21.341 00:17:26.779 Miguel de Veyra: We try to be as a sync as possible, though there’s like meetings around 9 to 19 to 11.

171 00:17:27.019 00:17:43.069 Miguel de Veyra: But I tried to tell them. I tried to tell her now, you know, for most of the stuff I don’t think need number, so they can focus on their things, just me, and then I’ll just relay them to the team. So not 4 h, basically as a meeting total time, right? Waste of money.

172 00:17:43.620 00:17:44.290 Joshua Michole Solon: All right.

173 00:17:44.680 00:17:47.800 Miguel de Veyra: But yeah, as for the rate what are you looking for?

174 00:17:48.590 00:17:51.930 Joshua Michole Solon: Actually something similar to like my current role.

175 00:17:52.520 00:17:58.420 Joshua Michole Solon: But you know I’m I’m fine with I think the rate we had before.

176 00:17:58.900 00:18:04.370 Joshua Michole Solon: But currently like, if I just share it to you, my salary current salary right now, it’s also

177 00:18:04.500 00:18:07.160 Joshua Michole Solon: build like monthly.

178 00:18:08.085 00:18:11.179 Miguel de Veyra: We’re billed monthly. They use wiser.

179 00:18:11.180 00:18:12.690 Joshua Michole Solon: Yeah, same same as.

180 00:18:12.690 00:18:14.250 Miguel de Veyra: Cisco is annoying as hell, though.

181 00:18:15.321 00:18:26.720 Joshua Michole Solon: Well, they they use actually paypal, or if it, if not, if it’s not working, then it’s wise as well. So I think the current salary expectation would be like 7 bucks an hour.

182 00:18:28.050 00:18:32.810 Miguel de Veyra: Okay? Yeah. Sure. I think that works a lot in your favor. Because one guy interviewed is like

183 00:18:32.940 00:18:36.004 Miguel de Veyra: he was asking for 25 mate. I don’t even make that much.

184 00:18:36.240 00:18:36.730 Joshua Michole Solon: Yeah.

185 00:18:36.730 00:18:44.640 Miguel de Veyra: Me and Casey combined don’t make that much so. But yeah, I think that definitely a good point. And then working hours. I don’t think you have a problem. Anyways.

186 00:18:45.500 00:18:49.369 Joshua Michole Solon: Yeah, I’m I’m really. I really need to do something else.

187 00:18:49.370 00:19:05.769 Miguel de Veyra: Yeah. And then the the good thing is that they actually push you to be a lot technical. It’s more on the quality. And then eventually, you learn about data. We have to learn about data.

188 00:19:06.050 00:19:10.910 Joshua Michole Solon: Yeah, yeah, so it’s good, technically good for resuming. So yeah, I’ll recommend you definitely.

189 00:19:11.910 00:19:14.380 Joshua Michole Solon: okay. And then when can you start?

190 00:19:15.770 00:19:21.209 Joshua Michole Solon: I would say, like the the normal 2 weeks time. But I’m also like, really free.

191 00:19:21.370 00:19:24.359 Joshua Michole Solon: if if I’m allowed to even say that. So yeah.

192 00:19:24.620 00:19:26.169 Miguel de Veyra: Yeah. Yeah. Next.

193 00:19:27.170 00:19:32.420 Miguel de Veyra: let’s say as soon as possible. So ideally next week, if cam or if I don’t know if you celebrate holidays.

194 00:19:32.980 00:19:38.929 Joshua Michole Solon: I mean, yeah, if you you’d send me like the official job offer and stuff like that, I’d be.

195 00:19:38.930 00:19:39.250 Miguel de Veyra: For.

196 00:19:39.250 00:19:40.290 Joshua Michole Solon: Happy to look into it.

197 00:19:40.500 00:19:49.879 Miguel de Veyra: Okay, yeah. And then the way it works, I think I’m not sure if I got full time, because the way usually it works is, we hire someone part time for the first, st like month or so, just.

198 00:19:49.880 00:19:50.660 Joshua Michole Solon: Trial.

199 00:19:50.860 00:19:53.069 Miguel de Veyra: Yeah, yeah, that. But of course, paid, of course.

200 00:19:53.630 00:19:58.170 Miguel de Veyra: Yeah. And then we’ll test it out. Casey took a week before she working full time or 2 weeks.

201 00:19:59.080 00:20:10.249 Miguel de Veyra: So, but yeah, I think definitely a good fit. I will convene with them after this call. And then, yeah, thanks, Josh. I will hop off now.

202 00:20:10.480 00:20:11.850 Miguel de Veyra: Okay, thank you.

203 00:20:11.850 00:20:12.389 Miguel de Veyra: Have a good one.

204 00:20:12.390 00:20:13.930 Joshua Michole Solon: Nice seeing you. Bye-bye.