Meeting Title: Henry:Robert Sync Date: 2025-10-16 Meeting participants: Robert Tseng, Henry Zhao
WEBVTT
1 00:03:03.350 ⇒ 00:03:05.480 Henry Zhao: Ugh, crazy day already, how are you doing?
2 00:03:06.510 ⇒ 00:03:09.740 Robert Tseng: I’m doing well. Hannah’s… Hannah’s in town.
3 00:03:09.890 ⇒ 00:03:11.419 Robert Tseng: So she.
4 00:03:11.420 ⇒ 00:03:12.660 Henry Zhao: Oh yeah, she’s coming.
5 00:03:13.160 ⇒ 00:03:21.069 Robert Tseng: Yeah, saw her this morning. She’s friends with my wife, actually, so they’re, it’s my wife’s birthday, and they’re going up to Boston, so…
6 00:03:21.330 ⇒ 00:03:27.460 Robert Tseng: Actually, like, I just… I got breakfast with them this morning, because then they already took off. So, yeah.
7 00:03:27.460 ⇒ 00:03:28.499 Henry Zhao: Oh, that’s really cool.
8 00:03:28.780 ⇒ 00:03:29.360 Robert Tseng: Yeah.
9 00:03:30.000 ⇒ 00:03:32.119 Henry Zhao: I still do a visit to Austin in December?
10 00:03:32.120 ⇒ 00:03:33.010 Robert Tseng: So yeah.
11 00:03:33.600 ⇒ 00:03:35.340 Henry Zhao: Yeah. Off-site?
12 00:03:35.820 ⇒ 00:03:41.349 Robert Tseng: I mean, yeah, so we… I mean, I think we’re gonna do a bigger off-site in Q1. I think that’s kind of the plan.
13 00:03:41.350 ⇒ 00:03:42.509 Henry Zhao: Like an actual company?
14 00:03:42.920 ⇒ 00:03:45.050 Robert Tseng: Yeah, I think… I think we can do it.
15 00:03:45.210 ⇒ 00:03:50.939 Robert Tseng: Yeah, we have cash in the bank now, so…
16 00:03:50.940 ⇒ 00:03:51.810 Henry Zhao: Awesome!
17 00:03:51.810 ⇒ 00:03:52.620 Robert Tseng: Yeah.
18 00:03:53.650 ⇒ 00:04:11.530 Robert Tseng: So we were bouncing ideas. Demolade’s in Malta, so I guess this is gonna be… he’s not gonna watch the recording, but we were thinking of maybe, seeing him before he makes his… he’s trying to move to the States, so maybe we can see… we, we meet there before he moves back to the States.
19 00:04:11.900 ⇒ 00:04:16.679 Henry Zhao: Oh, cool. I hope it’s early in January, because I am going to Australia the second half of January.
20 00:04:16.680 ⇒ 00:04:17.889 Robert Tseng: Oh, yeah? Okay.
21 00:04:18.230 ⇒ 00:04:26.239 Robert Tseng: Good to know. Yeah, we were thinking either early January, or it might actually be towards the end of Q1, so like, like March or something, so we’ll see.
22 00:04:26.540 ⇒ 00:04:27.220 Henry Zhao: Cool.
23 00:04:27.350 ⇒ 00:04:28.449 Henry Zhao: Alright.
24 00:04:29.330 ⇒ 00:04:36.829 Henry Zhao: So, pharmacy on-site. So, anything you need me to do on this document site, just read it over.
25 00:04:36.830 ⇒ 00:04:43.100 Robert Tseng: Yeah, yeah, I mean, I guess, sorry, it’s like GPT schlop, but, like, I’m glad that it actually showed up, so I think,
26 00:04:44.210 ⇒ 00:04:53.199 Robert Tseng: Yeah, I think I was kind of just organizing… I’ll just call out a few things. So, like, in the first section, right, I think it’s just good for you to be able to see, like.
27 00:04:53.420 ⇒ 00:05:11.449 Robert Tseng: when an order comes in, and then you just literally follow it around to kind of understand, like, where is it going to? Like, which system is it being passed through? Obviously, it’s coming in on… on BASC, but then it’s probably handed off to their internal system at the pharmacy, some sort of, like, WMS or whatever.
28 00:05:12.500 ⇒ 00:05:25.640 Robert Tseng: Yeah, so I mean, I think some of these details, like, it’s not obviously coming from a call center, so you can delete that, but just really being able to map out the fulfillment flow within the pharmacy specifically, I think is what the… one of the outcomes from… from that angle.
29 00:05:26.290 ⇒ 00:05:29.290 Robert Tseng: That way we can understand, like, you know, where the…
30 00:05:30.310 ⇒ 00:05:43.330 Robert Tseng: if… how many handoffs there are? Like, is it just, like, passing, like, the gen… the BASC order ID or whatever is… is, obviously is originating in BASC, it’s handed off to the WMS,
31 00:05:43.330 ⇒ 00:05:54.760 Robert Tseng: And then something… I mean, yeah, like… and then is… is that it? Does everything else kind of stay within that system? My guess is it’s not. They probably have multiple systems that they’re handing it off to before then.
32 00:05:54.880 ⇒ 00:06:13.520 Robert Tseng: So I think that’ll be important, right? Because if you think about the current capability, we have sent a pharmacy, and we know nothing about the order after that until it gets shipped out. So, like, we obviously are trying to, add more of those, to be able to get more tracking out of that, because that’s what the
33 00:06:13.520 ⇒ 00:06:16.930 Robert Tseng: team’s gonna need, as they do higher, higher volume. Yeah.
34 00:06:16.930 ⇒ 00:06:21.780 Henry Zhao: Do you know, also, when an order comes in, how does it get routed to a specific pharmacy?
35 00:06:22.720 ⇒ 00:06:29.810 Robert Tseng: Yeah, so I also, right now, I don’t know how they do that. I know how Basque chooses… Basque has basically been choosing it for them,
36 00:06:30.730 ⇒ 00:06:32.469 Robert Tseng: So, I guess…
37 00:06:32.780 ⇒ 00:06:36.290 Robert Tseng: I don’t know how relevant this is, if we’re going to be moving off BASC, but just for now.
38 00:06:36.290 ⇒ 00:06:56.000 Robert Tseng: They… they have… they’re able to set preferred pharmacies, and obviously they had, like, a big pharmacy blow up, recently, which is why they ended up… I forgot the name, so they moved off of it. But, so… so that… they would send it to those preferred pharmacies first. There was, like, maybe 3 options, it’s whatever is in my, my financial model.
39 00:06:56.420 ⇒ 00:07:14.989 Robert Tseng: Yeah, I forgot what the names were. And then afterwards, if they’re all at max capacity, then BASC has their own, like, closed-loop network of pharmacies that they fulfill orders for them. But it’s super expensive to do that, and that’s kind of where BASC makes a good chunk of their margin. So, the purpose of having this
40 00:07:15.160 ⇒ 00:07:19.369 Robert Tseng: you know, Albuquerque Pharmacy is… they want to be able to take on
41 00:07:19.430 ⇒ 00:07:23.069 Robert Tseng: well, actually, I’m not sure. Like, I think what percentage of…
42 00:07:23.070 ⇒ 00:07:42.310 Robert Tseng: their orders do they expect to be routing through them? Is this gonna be, like, the top priority, like, pharmacy? And, like, being able to really compare, like, their capabilities against, like, I guess, the Bass network? I think, obviously, you haven’t talked to BAS, you don’t really know what their benchmarks are. I, I, when I visited Bass, I kind of… I got a sense of
43 00:07:42.800 ⇒ 00:07:58.489 Robert Tseng: you know, it’s like 80% on-time shipment rate, I know what volume they’re able to process in their pharmacies, and stuff like that. So, I think once we’re able to get a sense of what that looks like in the Albuquerque one, then I’ll be able… we’ll be able to go back to Eden and be like, look.
44 00:07:58.490 ⇒ 00:08:05.129 Robert Tseng: you’re currently underperforming, like, against vast pharmacies by whatever percent.
45 00:08:05.140 ⇒ 00:08:20.459 Robert Tseng: It’ll probably take another 6 months to ramp up to get to their level of performance, so maybe they shouldn’t… you shouldn’t route most of your orders to the pharmacy, because everything’s gonna be late, or whatever. Like, I want to be able to give that type of, like, advice to them.
46 00:08:20.500 ⇒ 00:08:33.820 Robert Tseng: I’m sure, like, Rebecca has no idea, and she’s not going to be able to do that. She’s only… her only directive is to get that pharmacy up and running, so I think that’s… that’s the angle that we can come in to support them on.
47 00:08:34.169 ⇒ 00:08:34.849 Henry Zhao: Okay.
48 00:08:34.849 ⇒ 00:08:35.639 Robert Tseng: Yeah. Yeah.
49 00:08:36.669 ⇒ 00:08:41.589 Robert Tseng: That’s from, like, the order, like, the fulfillment journey. I think that’s kind of the purpose of that section.
50 00:08:41.919 ⇒ 00:08:47.169 Robert Tseng: And then, like, inventory kind of management, I was trying to thinking.
51 00:08:47.319 ⇒ 00:09:00.779 Robert Tseng: well, we don’t have that many SKUs, but obviously, like, there’s this manufacturing component there, where if this is a compounding pharmacy, they’re getting some sort of raw material, they have… I mean, I don’t know that much about chemical manufacturing, but, like.
52 00:09:01.769 ⇒ 00:09:10.569 Robert Tseng: They’re having to… I mean, there must be some, like, efficiency portion on, like.
53 00:09:10.699 ⇒ 00:09:13.559 Robert Tseng: There… there’s… there must be, like…
54 00:09:13.569 ⇒ 00:09:19.649 Robert Tseng: raw material does not… 100% raw material does not become 100% product, right? There’s, like, some waste
55 00:09:19.649 ⇒ 00:09:34.059 Robert Tseng: that happens, and, like, if you’re gonna do… we don’t… they don’t do supply forecasting right now, but if you were to do that, like, we don’t… I have no idea how to do supply forecasting right now. I don’t know, like, how much material, what substance to make in order to, like, actually, like, be, like.
56 00:09:34.059 ⇒ 00:09:35.649 Robert Tseng: you know, 10…
57 00:09:35.859 ⇒ 00:09:45.389 Robert Tseng: pounds… I don’t even know what the right measurement is, but, like, 10 pounds of this, chemical is going to give us, like, 6 pounds of
58 00:09:45.469 ⇒ 00:10:00.369 Robert Tseng: Of this truck, or whatever. Like, I don’t… I have no idea what that flow looks like currently. So, I do think that those assumptions we will need to get at some point if we are to be able to build out a supply forecast for that.
59 00:10:00.649 ⇒ 00:10:19.759 Robert Tseng: Yeah, and then obviously, I think it’s a good check for them, because in order to be a compliant pharmacy, they need to be able to perform cycle counts every week, so, like, they should be able to give you a tour of, like, their inventory, and be able to walk you through the manufacturing process, especially for, like, the higher,
60 00:10:19.969 ⇒ 00:10:26.249 Robert Tseng: like, a lot of high-volume products. So that’s… that, to me is a separate kind of, like, flow that I want…
61 00:10:26.359 ⇒ 00:10:28.239 Robert Tseng: I hope you that we can investigate.
62 00:10:31.449 ⇒ 00:10:40.749 Robert Tseng: Yeah, and then obviously, I’m sure it’s not shelf-stable, there’s probably some refrigeration, so, like, there’s a lot of things that complicate, like, I don’t know how much inventory they can keep on hand, and, like, what the…
63 00:10:40.799 ⇒ 00:10:57.419 Robert Tseng: like, how long it’ll take for them to go through, you know, their entire supply. So, I think just, you know, that… we can kind of get into more of the details of, like, what questions to ask there, but that’s kind of… yeah, that’s what I’ll say about the inventory part.
64 00:10:57.559 ⇒ 00:11:04.169 Robert Tseng: Systems is probably, like, that’s a bit more straightforward. Just, like, get to understand, like, all the systems they use.
65 00:11:04.539 ⇒ 00:11:06.589 Robert Tseng: I think…
66 00:11:07.109 ⇒ 00:11:19.419 Robert Tseng: I’m sure that they’re not a BASC-native pharmacy. This is, like, a 20-plus-year-old pharmacy. They probably have a really, like, antiquated system. Yeah, I think just wanting to understand
67 00:11:22.239 ⇒ 00:11:32.129 Robert Tseng: what they’re keying in manually there that ends up getting passed… that we would need to pass back to us, right? Those are types of the… those are the types of,
68 00:11:32.939 ⇒ 00:11:39.989 Robert Tseng: Risk, risking, or, like, high risk points if they have to manually key in anything.
69 00:11:40.459 ⇒ 00:11:47.579 Robert Tseng: So as much as they’re able to, obviously, use scans or, like, persist variables that they get from BASC, like.
70 00:11:49.109 ⇒ 00:11:52.959 Robert Tseng: About the… about the shipment, that’s probably better.
71 00:11:53.109 ⇒ 00:11:55.289 Robert Tseng: But yeah, I don’t…
72 00:11:55.959 ⇒ 00:12:03.219 Robert Tseng: I don’t really know what the… what the data flow is in and out of their system. So, I think that’s… that’s the other thing to investigate.
73 00:12:04.859 ⇒ 00:12:11.449 Robert Tseng: Lastly, yeah, I mean, the compounding and manufacturing controls piece,
74 00:12:12.289 ⇒ 00:12:26.109 Robert Tseng: Yeah, I mean, this is kind of the same idea as, like, the inventory material flow, except the inventory material flow, that’s more focused on the raw materials and kind of understanding, you know, before they end up…
75 00:12:26.229 ⇒ 00:12:30.779 Robert Tseng: And then… and then the compounding, like, ap… like, after it’s been…
76 00:12:31.009 ⇒ 00:12:32.629 Henry Zhao: compounded, like.
77 00:12:32.629 ⇒ 00:12:49.999 Robert Tseng: you know, there’s, like, a… like, how long do… how long does the product, like, sit there? Like, do we get it out within, like, 48 hours, or, like, whatever? Like, I think, that’s… that’s kind of just wanting us to have some sort of, like, digital paper trail on, like, the compounding activity. So…
78 00:12:53.029 ⇒ 00:13:03.929 Robert Tseng: Yeah, I think that one’s probably the least… I feel the least comfortable with. I have no idea how you compound drugs, so… but, like, I feel like the other three steps are all pretty standard for any sort of drug.
79 00:13:03.929 ⇒ 00:13:05.559 Henry Zhao: Mike Warehouse.
80 00:13:05.559 ⇒ 00:13:07.709 Robert Tseng: kind of investigation, so…
81 00:13:08.519 ⇒ 00:13:14.689 Robert Tseng: Yeah, I mean, we can keep, like I said, we can keep working through the stock to make it a bit more… a bit clearer.
82 00:13:14.690 ⇒ 00:13:15.260 Henry Zhao: Okay.
83 00:13:15.260 ⇒ 00:13:15.880 Robert Tseng: Yeah.
84 00:13:16.110 ⇒ 00:13:25.240 Henry Zhao: But ultimately, okay, so this is what I was gonna ask you, is like, what should I walk away with, and what should our recommendation, like, what kind of recommendation are we looking for to give out of this visit?
85 00:13:26.260 ⇒ 00:13:35.039 Robert Tseng: Yeah, so I think I gave you the recommendation on the first one with, from the order to shipment, like, kind of, you need to be able to kind of tell them, like.
86 00:13:35.100 ⇒ 00:13:49.269 Robert Tseng: how… is this pharmacy ready to use? Can it handle the volume? How does it perform against, like, the other pharmacies that you already currently use? And then also the second piece is, like, these are all the different, kind of.
87 00:13:49.990 ⇒ 00:13:54.920 Robert Tseng: Events that we should be able to track within
88 00:13:55.080 ⇒ 00:14:08.989 Robert Tseng: Within the pharmacy workflow, because, you know, right now, it’s just sent to pharmacy, and then when it gets shipped out, so we have to, like, kind of decide, like, what are those other, kind of points that we want to be able to track, so be able to give advice there.
89 00:14:09.320 ⇒ 00:14:10.550 Robert Tseng: And then…
90 00:14:10.580 ⇒ 00:14:17.319 Robert Tseng: like, I think the third tickets… I don’t know how much you’ll… I think if you could get those two things done in a day, like, that would be great.
91 00:14:17.340 ⇒ 00:14:41.360 Robert Tseng: But it’s like, as you’re kind of investigating, I would like to know some of the assumptions so we can start to, like, plan, like, a supply forecast on the inventory side, and then, like, I mean, I just don’t know anything about compounding, so it’s hard for me to kind of visualize, like, what kind of output we’re going to give them there. I think I just want to understand, like, what are the… like, are there any other risks in, kind of, like.
92 00:14:41.360 ⇒ 00:14:48.150 Robert Tseng: They’re set up where there’s manual transcription of any kind that’s happening that we just want to be able to flag to them.
93 00:14:48.580 ⇒ 00:15:00.410 Henry Zhao: And is our ultimate goal, as Brainforge, do we want to just find more meaningful work, or do we want to upsell them and say, like, we need a higher contract, because now we’re going to do this much additional work for the pharmacy?
94 00:15:00.580 ⇒ 00:15:19.329 Robert Tseng: Yeah, so I do think it’s gonna be both, like, we’re gonna… there’s obviously data work to do here, like, the telemetry, capturing, storing it, being able to bring it into reporting, that’s all on us, but as far as, like, building the systems to be able to integrate them, whatever systems they’re using, into, like, their current stack.
95 00:15:19.710 ⇒ 00:15:29.830 Robert Tseng: That’s not us. That’s gonna be… we already have Surf kind of helping us on the remote side, but they’re gonna… they know that they’re gonna have to build out an engineering team, so we can, like, just being able to…
96 00:15:29.870 ⇒ 00:15:44.129 Robert Tseng: get… gather enough… build up enough of a roadmap that we can go back and, we’re not going to take on that work with our team, but we may contract it out to… subcontract it out to SURF or, some other engineering firm partner that we have.
97 00:15:44.760 ⇒ 00:15:48.280 Robert Tseng: Okay. Yeah. And then who do I… so you think one day there should be fine?
98 00:15:48.790 ⇒ 00:16:01.369 Robert Tseng: Yeah, I think that’s a lot to cover in a day, to be honest. I think if you just covered the first two things I said, that’d probably be enough, but it’s… I mean, if you’re gonna be able to spend the whole day there, I mean, I think, you know, CC as much as you can.
99 00:16:01.370 ⇒ 00:16:05.630 Henry Zhao: Yeah, I can do more than one day, but I was just curious how many days you think would need for all of this.
100 00:16:07.260 ⇒ 00:16:10.830 Henry Zhao: Do I book my travel with Rebecca, or how does that work?
101 00:16:10.830 ⇒ 00:16:20.039 Robert Tseng: Yeah, so it’s gonna come out of Rebecca’s budget. I mean, we’re in a group chat, so I guess once we get this doc finalized, maybe we’ll kind of finalize it over the weekend.
102 00:16:20.090 ⇒ 00:16:36.639 Robert Tseng: we’ll send it to her, and kind of just show… show her, like, what the… what the plan is, tell her that she… we want a date, we would pick a date, and then, she knows it’s coming out of her budget, so then she would… I guess, it’ll probably be you book on your own, and then you’ll get reimbursement from her, or something like that.
103 00:16:36.850 ⇒ 00:16:39.909 Henry Zhao: Okay, do I ask Rebecca about all that, or we just talk about that next week?
104 00:16:39.910 ⇒ 00:16:55.980 Robert Tseng: Yeah, well, it’s just not gonna be her decision, so, like, we can… we can just… once… once we’re… once we tell her what the plan is, and she thinks it’s good, like, yeah, like, we’ll… we’ll… we’ll get… we’ll get… you’ll be able to probably… I’m expecting you to be able to book your… book your tickets or whatever next week.
105 00:16:55.980 ⇒ 00:16:56.590 Henry Zhao: Okay.
106 00:16:56.920 ⇒ 00:16:57.360 Robert Tseng: Yeah.
107 00:16:57.990 ⇒ 00:17:05.380 Henry Zhao: Yeah, the next thing is the Catalyst Eden update, so I already gave a little bit of update on that in the stand-up, but my question for you is on this.
108 00:17:06.060 ⇒ 00:17:09.090 Henry Zhao: This delay that you talked about.
109 00:17:09.589 ⇒ 00:17:11.239 Robert Tseng: Yeah, the 10 to 14 days.
110 00:17:11.440 ⇒ 00:17:12.220 Henry Zhao: Yes.
111 00:17:12.220 ⇒ 00:17:19.890 Robert Tseng: Yeah, I know that the trans… The transaction ID doesn’t get passed through the order update, it never has, and I don’t know, yeah.
112 00:17:20.130 ⇒ 00:17:20.930 Robert Tseng: I guess…
113 00:17:20.930 ⇒ 00:17:22.430 Henry Zhao: Okay.
114 00:17:22.640 ⇒ 00:17:30.909 Henry Zhao: But Ryan was asking, like, is this because that the customers sometimes take that long to fill out the questionnaire, or is there just a delay from the order updated being…
115 00:17:31.550 ⇒ 00:17:37.679 Robert Tseng: Yeah, just delay from the order updated. Basque has told me that most of their… it’s… it’s…
116 00:17:37.860 ⇒ 00:17:45.930 Robert Tseng: I mean, Dan Milate and I have, like, kind of… I can show you the old analysis that we did, but it was something like,
117 00:17:46.380 ⇒ 00:17:53.210 Robert Tseng: 50 or 60% of orders don’t get their…
118 00:17:55.640 ⇒ 00:18:03.579 Robert Tseng: it may show, like, it’s been updated in the BAS UI, but we don’t get the actual webhook into our
119 00:18:03.620 ⇒ 00:18:17.560 Robert Tseng: into our data warehouse at the same time. So, there is some, like, delay, and that delay comes… it’s… most of them that get settled within the same day, so it’s not that big of a deal, but some of them do go all the way up to 10 to 14 days.
120 00:18:18.470 ⇒ 00:18:19.540 Henry Zhao: Okay.
121 00:18:19.700 ⇒ 00:18:23.149 Henry Zhao: Because let me see my ticket that I had for Eden 1004.
122 00:18:31.950 ⇒ 00:18:33.339 Henry Zhao: So much stuff here.
123 00:18:33.340 ⇒ 00:18:35.779 Robert Tseng: Okay, I’m looking for it as well.
124 00:18:36.220 ⇒ 00:18:39.569 Henry Zhao: No, no, it’s a different one, it’s different. So I, basically, I tested it.
125 00:18:40.860 ⇒ 00:18:48.060 Henry Zhao: Okay, never mind. That’s something else. So don’t worry about that. Okay, so don’t worry about that. I’ll tell Demila… I’ll tell Awash, like, we need to either deal with that or talk to Basque.
126 00:18:48.360 ⇒ 00:18:49.270 Robert Tseng: Yeah.
127 00:18:49.270 ⇒ 00:18:53.460 Henry Zhao: Because we can’t use the webhook if there’s a delay, right? So… or we find another solution.
128 00:18:55.920 ⇒ 00:19:00.770 Henry Zhao: I mean, it’s not a bad thing that we pay Catalyst less, right? Or we’ll just pay those next month.
129 00:19:01.260 ⇒ 00:19:02.990 Robert Tseng: Yeah, I don’t think it’s a… I don’t think it’s that…
130 00:19:02.990 ⇒ 00:19:07.810 Henry Zhao: Okay, cool. So the next one is the HIPAA chart. I try to just keep it simple.
131 00:19:07.810 ⇒ 00:19:08.490 Robert Tseng: Great, yeah.
132 00:19:08.490 ⇒ 00:19:10.560 Henry Zhao: I don’t know if you wanted more complex than this, but…
133 00:19:10.790 ⇒ 00:19:22.090 Henry Zhao: Basically, the only thing that I think Jonah and Josh would care about is that the edge layer is this stuff, the Cloudflare stuff that, Zoran implemented. The edge layer data that we capture by Cloudflare, there’s no PII, the IPs are hash.
134 00:19:22.220 ⇒ 00:19:29.070 Henry Zhao: Like, you can’t recognize the user ID, it’s like a jumble of letters and numbers, like, there shouldn’t be anything that violates HIPAA.
135 00:19:29.070 ⇒ 00:19:29.630 Robert Tseng: Yeah.
136 00:19:29.730 ⇒ 00:19:34.009 Henry Zhao: Annotice data gets sent to the data warehouse. Oh, I just need another arrow here.
137 00:19:35.180 ⇒ 00:19:36.489 Henry Zhao: Where did my arrows go?
138 00:19:39.630 ⇒ 00:19:41.160 Henry Zhao: Is this Figma?
139 00:19:41.350 ⇒ 00:19:42.050 Henry Zhao: Yeah.
140 00:19:43.310 ⇒ 00:19:46.670 Robert Tseng: You’re, like, using a different version. I’ve never seen it in this version before.
141 00:19:47.420 ⇒ 00:19:48.820 Henry Zhao: Oh, it’s because it’s the dev version.
142 00:19:49.210 ⇒ 00:19:50.560 Robert Tseng: Oh, interesting.
143 00:19:51.560 ⇒ 00:19:53.139 Henry Zhao: I guess that I changed the prod ator?
144 00:19:55.120 ⇒ 00:19:56.519 Henry Zhao: I’m just guessing us,
145 00:19:57.940 ⇒ 00:19:58.650 Robert Tseng: Oh, yeah.
146 00:20:00.570 ⇒ 00:20:07.779 Henry Zhao: So I’m just saying, like, Google Tag Manager goes here, Segment goes here, it’s all HIPAA eligible, Catalyst goes directly to Catalyst.
147 00:20:08.110 ⇒ 00:20:12.780 Henry Zhao: And then we send this data to MixedPanel, Customer I.O, Tableau, Northbeam, Spanish Budget.
148 00:20:14.990 ⇒ 00:20:15.660 Robert Tseng: Yeah.
149 00:20:22.070 ⇒ 00:20:28.740 Robert Tseng: I mean, yeah, we’re already hashing everything at second… or, like, yeah, like, before it even gets to Google BigQuery, we can’t even… we don’t even know who they are, so…
150 00:20:28.740 ⇒ 00:20:30.950 Henry Zhao: And then here’s HIPAA eligible. So, like, here is where, like.
151 00:20:31.320 ⇒ 00:20:37.679 Henry Zhao: I could essentially… I could download everyone’s health data and spam… send it on the internet, so I didn’t put anything here, but we’re not gonna do that.
152 00:20:37.680 ⇒ 00:20:46.059 Robert Tseng: They said that they signed a BAA with BigQuery, which I have not seen the contract, I don’t believe them, like, our other clients have never been able to get Google to sign one, so…
153 00:20:46.060 ⇒ 00:20:48.780 Henry Zhao: So I think you can present it and just talk about that, like, on Twitter.
154 00:20:48.780 ⇒ 00:20:50.689 Robert Tseng: No, I think, I think this makes sense. Yeah.
155 00:20:50.690 ⇒ 00:20:55.270 Henry Zhao: Okay, I can add anything, I shared it with you, and I can add it to the linear after this.
156 00:20:55.600 ⇒ 00:20:56.170 Robert Tseng: Okay.
157 00:20:57.180 ⇒ 00:20:57.810 Robert Tseng: Cool.
158 00:20:58.190 ⇒ 00:21:01.839 Henry Zhao: Okay, read me outline, and then my question on proxy downgrade.
159 00:21:02.110 ⇒ 00:21:03.470 Henry Zhao: As in why we need that.
160 00:21:03.470 ⇒ 00:21:04.570 Robert Tseng: Yeah.
161 00:21:04.570 ⇒ 00:21:26.610 Henry Zhao: So right now, I just basically took the pricing analytics doc, I watched, kind of, the 30-minute video you did of, like, that was kind of cool to see how you put ChatGPT side-by-side and just, like, copy-pasted and, like, added your own twist to it. Yeah. I basically just organized my thoughts here on, like, what we would need step-by-step to get the project done, and what kind of questions we want to answer. So, from this call, the remaining time we have, maybe let’s just go through…
162 00:21:26.610 ⇒ 00:21:30.930 Henry Zhao: what questions you want to focus on for this first round, so I can add it to that notion?
163 00:21:32.520 ⇒ 00:21:36.799 Henry Zhao: skeleton that, you, Tom, shared at the end of this call just now.
164 00:21:37.090 ⇒ 00:21:49.180 Henry Zhao: Okay. So, first step, right, is first step, I’m understanding the MongoDB data and schema and what data we have, because we need to reconcile that data with the amplitude data. Correct. The reason I put this first is I want to understand, kind of, all of our data sources.
165 00:21:49.580 ⇒ 00:21:51.680 Henry Zhao: And where we want to get our data from, okay?
166 00:21:51.680 ⇒ 00:21:52.320 Robert Tseng: Yep.
167 00:21:52.320 ⇒ 00:21:58.639 Henry Zhao: So, some things I thought of as, like, number of users by tier, upgrades and downgrades, and that’s pretty much it. I think if we have that data.
168 00:21:58.830 ⇒ 00:21:59.430 Robert Tseng: Yep.
169 00:21:59.430 ⇒ 00:22:03.829 Henry Zhao: Then the amplitude data should be fine as long as they’re firing, which would be step 3, which you’ll see later.
170 00:22:04.180 ⇒ 00:22:04.980 Robert Tseng: Yep.
171 00:22:05.150 ⇒ 00:22:12.370 Henry Zhao: So then… oh, step two, actually. So ensure that amplitude events are firing for all the analysis we need. So the only ones I care about right now are sign-ups.
172 00:22:12.550 ⇒ 00:22:24.159 Henry Zhao: Project created, upgrades, and launches product, projects, so that’s… we already have that, of course. Downgrades, I don’t know what we need there, because we already have plan change. I don’t understand why downgrades are not.
173 00:22:25.820 ⇒ 00:22:27.190 Robert Tseng: Yeah, so…
174 00:22:27.330 ⇒ 00:22:36.819 Robert Tseng: I guess, so this is, like, where I needed that extra feature from them, the computations. So, like, when you do a plan change event,
175 00:22:36.970 ⇒ 00:22:44.179 Robert Tseng: Yeah, I mean, if you look through the event stream, you know what the plan they had was before, and you know what the plan is afterwards, but there.
176 00:22:44.180 ⇒ 00:22:44.550 Henry Zhao: Is it…
177 00:22:44.550 ⇒ 00:22:54.079 Robert Tseng: something else that captures, like, this was a downgrade, or this was an upgrade. So, like, I think I would… I wanted to be able to compute
178 00:22:54.080 ⇒ 00:23:07.889 Robert Tseng: an additional property on the profile that’s calculated from when there is a change in value in the plan to, like, mark if it’s, like, directionally, if it’s an upgrade or downgrade.
179 00:23:08.250 ⇒ 00:23:11.099 Henry Zhao: Okay, I think this is free in MixedPanel, so I got confused. I didn’t know that.
180 00:23:11.100 ⇒ 00:23:15.770 Robert Tseng: It is free in Mixpanel, yeah, so it is kind of annoying that you can’t do it without this, yeah.
181 00:23:15.960 ⇒ 00:23:18.649 Henry Zhao: Okay, gotcha, gotcha, gotcha, gotcha, okay. Yeah.
182 00:23:19.750 ⇒ 00:23:21.130 Henry Zhao: Oh, that makes so much sense
183 00:23:21.560 ⇒ 00:23:33.350 Henry Zhao: Alright, and then the actions within the project, and then if they see an upsell, because later we want to look at upsells versus self-serve versus trial, right? Correct. And then there’s just the features, so, like, recipes, etc.
184 00:23:33.860 ⇒ 00:23:39.139 Henry Zhao: I know a lot of these features are not tracked, so I just did some testing yesterday, and a lot of them are not tracked.
185 00:23:39.290 ⇒ 00:23:41.490 Henry Zhao: So I guess we need to track those.
186 00:23:41.690 ⇒ 00:23:44.789 Henry Zhao: But I didn’t see a trial feature, so what… when you.
187 00:23:44.790 ⇒ 00:23:48.399 Robert Tseng: Yeah, there isn’t a feature. It’s, yeah, we…
188 00:23:48.540 ⇒ 00:23:53.209 Henry Zhao: They say that new users that are…
189 00:23:53.470 ⇒ 00:24:07.290 Robert Tseng: within 14 days, like, on their 14th day, they’re basically pushed out of trial. Like, they have to… they have to downgrade to free, or they, have to basically put a credit card in in order to stay on the product. So…
190 00:24:07.290 ⇒ 00:24:09.009 Henry Zhao: Oh, right now I have a full version?
191 00:24:09.950 ⇒ 00:24:18.699 Robert Tseng: Yeah, if you’re… this is your version? Yeah. Yeah, you have the full version then. I’m assuming it hasn’t been 14 days yet. You probably are on business or something.
192 00:24:21.080 ⇒ 00:24:22.700 Henry Zhao: Okay, didn’t know that, okay.
193 00:24:23.280 ⇒ 00:24:25.290 Henry Zhao: So, not formal.
194 00:24:26.390 ⇒ 00:24:30.039 Henry Zhao: But 14 days trial, everyone is given.
195 00:24:30.420 ⇒ 00:24:31.180 Robert Tseng: Yeah.
196 00:24:31.180 ⇒ 00:24:34.780 Henry Zhao: then need card, or a Or free.
197 00:24:35.360 ⇒ 00:24:35.970 Robert Tseng: Yeah.
198 00:24:36.980 ⇒ 00:24:38.739 Henry Zhao: Okay, that’s good to know.
199 00:24:38.920 ⇒ 00:24:46.220 Henry Zhao: So then we need also to make sure that we have the right user properties and amplitude, so unlike default, we don’t have, like, teams or anything like that, so we just have…
200 00:24:46.220 ⇒ 00:24:51.170 Robert Tseng: Yeah, so actually a couple things here. Plan type, I think, is not firing correctly, because there’s so many…
201 00:24:51.360 ⇒ 00:25:06.569 Robert Tseng: people that have plan type, none. So, like, I think this is also part of the… when you’re reconciling with amplitude data, number of users by tier, I would be curious, yeah, like, what the plan type distribution actually is in Mongo compared to…
202 00:25:06.570 ⇒ 00:25:12.500 Henry Zhao: In MongoDB, I saw 12 Enterprise, and in NPL, I saw 2,000, so I don’t know how many enterprise we actually have.
203 00:25:13.790 ⇒ 00:25:14.730 Robert Tseng: Oh, wow.
204 00:25:15.430 ⇒ 00:25:17.799 Henry Zhao: Oh, I haven’t looked at what the engineer sent me yet, so maybe at that number.
205 00:25:17.800 ⇒ 00:25:18.450 Robert Tseng: Yeah.
206 00:25:18.450 ⇒ 00:25:25.439 Henry Zhao: But I’m just saying, like, on day one, I was like, what do I even do, right? I was at loss, because I was like, I don’t even know if I’m in the right…
207 00:25:26.220 ⇒ 00:25:28.149 Henry Zhao: zone of data, right? So…
208 00:25:28.150 ⇒ 00:25:28.930 Robert Tseng: Yeah.
209 00:25:28.930 ⇒ 00:25:33.449 Henry Zhao: That’s what I meant by why I needed to talk to a programmer, just to get an understanding.
210 00:25:33.570 ⇒ 00:25:43.860 Henry Zhao: Just to have some guidance. And then I was wondering if Alicia cares about any other, like, demographic or device information? Like, does she care about it by country, by, like, device type?
211 00:25:44.030 ⇒ 00:25:47.320 Henry Zhao: whether it’s… Apple or whatever, right?
212 00:25:47.890 ⇒ 00:25:52.390 Robert Tseng: I mean, I looked through all of those on amplitude, none of those are reliable, so…
213 00:25:53.330 ⇒ 00:25:58.989 Robert Tseng: I mean, it’s… those are nice to have, but, like, yeah, I don’t think they’re being properly tracked right there.
214 00:25:59.230 ⇒ 00:26:03.759 Henry Zhao: So is their board, or does Elisa care about these things? Do they want to eventually have this data?
215 00:26:04.450 ⇒ 00:26:07.689 Robert Tseng: I think they do, but more… more… I think…
216 00:26:07.880 ⇒ 00:26:14.980 Robert Tseng: it’s… it’s more… yeah, I don’t think it’s gonna be urgent. They’re only looking at behavioral stuff right now.
217 00:26:14.980 ⇒ 00:26:15.760 Henry Zhao: Okay.
218 00:26:15.760 ⇒ 00:26:16.290 Robert Tseng: Yeah.
219 00:26:16.290 ⇒ 00:26:18.259 Henry Zhao: Eventually, we want this, but not urgent.
220 00:26:18.260 ⇒ 00:26:18.850 Robert Tseng: Yeah.
221 00:26:19.820 ⇒ 00:26:23.560 Henry Zhao: just behavioral stuff.
222 00:26:23.560 ⇒ 00:26:38.440 Robert Tseng: Yeah, I think they’re most interested in tying, like, feature engagement to revenue, and they’re just trying to, like, understand what, of all the random features they’ve shipped, like, what’s really, like, kind of driving conversions, and I just think that’s… that’s what they’re trying to get at with all.
223 00:26:38.440 ⇒ 00:26:44.410 Henry Zhao: Yes, because that was my concern… that was my concern initially when I first started looking at README.
224 00:26:44.550 ⇒ 00:26:45.750 Henry Zhao: is…
225 00:26:46.750 ⇒ 00:26:53.189 Henry Zhao: One of my favorite marketing concepts I learned in business school was KISS, right? Keep it short and simple.
226 00:26:53.190 ⇒ 00:26:53.990 Robert Tseng: Yeah.
227 00:26:54.210 ⇒ 00:26:59.329 Henry Zhao: And then we learned something called the cheese pizza principle, which is my favorite principle ever, which is, like, if you have…
228 00:26:59.930 ⇒ 00:27:06.599 Henry Zhao: People, like, order cheese pizza at company parties, and nobody ends up eating it, because cheese pizza is, like, trying to please everyone.
229 00:27:06.890 ⇒ 00:27:08.970 Robert Tseng: That’s a combo. Yeah.
230 00:27:08.970 ⇒ 00:27:12.059 Henry Zhao: Basically, all I’m trying to say is, when you go to this.
231 00:27:12.350 ⇒ 00:27:13.009 Robert Tseng: Huh.
232 00:27:13.010 ⇒ 00:27:13.790 Henry Zhao: Stuff.
233 00:27:14.980 ⇒ 00:27:18.310 Henry Zhao: where I feel like we’re losing people because…
234 00:27:18.930 ⇒ 00:27:21.639 Henry Zhao: You’re targeting, kind of, like, all these things.
235 00:27:22.750 ⇒ 00:27:23.270 Robert Tseng: Yeah.
236 00:27:23.450 ⇒ 00:27:26.630 Henry Zhao: I don’t know if they’re irrelevant, so… I might not have enough…
237 00:27:27.370 ⇒ 00:27:36.489 Robert Tseng: I think, like, the user is a tech… like, who’s gonna be building technical DOS, right? It’s gonna be, like, some, like, indie, like, developer or whatever.
238 00:27:37.090 ⇒ 00:27:43.139 Robert Tseng: I mean, yeah, whoever that persona is, like, they have to be speaking to that. I don’t think they’re very clear on it,
239 00:27:43.580 ⇒ 00:27:56.660 Robert Tseng: So… but yeah, I mean, I don’t know. I would expect someone who’s, like, a more technical user wants to see a longer list of the features, rather than, like, I don’t know, like, obviously, if you’re selling to an, like, a less…
240 00:27:56.770 ⇒ 00:28:00.980 Robert Tseng: Technical person, they’d probably only want to see, like, 5 things, or whatever.
241 00:28:00.980 ⇒ 00:28:12.289 Henry Zhao: Right, but if we’re up… yeah, if we’re upgrading on these four features, like, I don’t know that we want… we either want to put these higher up, or we want to, like, just have these four, and then say, plus 48 other, like, document integrations, right?
242 00:28:12.290 ⇒ 00:28:19.070 Robert Tseng: Oh, totally, yeah, they should know which features are the ones that are the high… most int… like, that their users will care about the most, yeah.
243 00:28:19.070 ⇒ 00:28:28.470 Henry Zhao: Exactly, because if they care about managed onboarding implementation, nobody is scrolling all the way down to this. They’re, like, get lost halfway through scrolling, right? That’s what all I’m trying to say with this.
244 00:28:28.470 ⇒ 00:28:29.820 Robert Tseng: Yeah.
245 00:28:29.820 ⇒ 00:28:31.010 Henry Zhao: I’m saying, Liz, like.
246 00:28:31.160 ⇒ 00:28:36.160 Henry Zhao: it’s good that you are telling me this, so now I know where to focus, right?
247 00:28:36.160 ⇒ 00:28:36.580 Robert Tseng: Yeah.
248 00:28:36.580 ⇒ 00:28:49.829 Henry Zhao: Look at feature user behavior, and then also upgrade type. So, are they upgrading based on the end of trial now, I know, or based on an upsell that they see, or self-serve? So they used it for a while, they got value out of it, and they upgraded, right? Yep.
249 00:28:50.070 ⇒ 00:29:02.830 Henry Zhao: So then cohorts, I need to build this out a little bit more, but, like, what cohorts should we build in Amplitude? So, like, first project created has upgraded, and then I’m sure we’ll have cohorts, like, used AI features, right?
250 00:29:03.990 ⇒ 00:29:07.720 Henry Zhao: And then maybe we’ll say, like, top 4 features identified.
251 00:29:08.030 ⇒ 00:29:14.070 Robert Tseng: Yeah, I built the Use AI features cohort, so right… we do have a limit on cohorts right now. We can only build
252 00:29:14.370 ⇒ 00:29:17.800 Robert Tseng: Like, 5, because of the current plan.
253 00:29:18.110 ⇒ 00:29:20.040 Henry Zhao: How to identify what the horse we want to build, yeah.
254 00:29:20.040 ⇒ 00:29:20.560 Robert Tseng: Yes.
255 00:29:20.560 ⇒ 00:29:28.080 Henry Zhao: And once I know, I will be able to say, like, this cohort versus the rest of your cohorts, like, there’s this much more upgrading, there’s this much more retention, so when you.
256 00:29:28.080 ⇒ 00:29:28.600 Robert Tseng: Beautiful.
257 00:29:28.600 ⇒ 00:29:30.090 Henry Zhao: From these people, or maybe.
258 00:29:30.090 ⇒ 00:29:31.590 Robert Tseng: Exactly. Yeah.
259 00:29:32.110 ⇒ 00:29:46.599 Henry Zhao: So that’s that. Okay, and then the questions we want to answer, some of these I just copied from our discussion yesterday, but what is the current conversion at each step of the funnel? This is pretty obvious. Breakdown funnel by product features, so this will help us dive deeper into, like, what are the top few? Are there any, like, co…
260 00:29:46.970 ⇒ 00:29:49.249 Henry Zhao: Co-effects, right? Like, people that use.
261 00:29:49.250 ⇒ 00:29:49.880 Robert Tseng: Yeah.
262 00:29:49.880 ⇒ 00:29:51.109 Henry Zhao: It’s also use…
263 00:29:51.130 ⇒ 00:30:02.439 Henry Zhao: API features, right? Yeah. But, you know what I mean. People that use MDX, they also probably use, guides, right? Yeah. And then that, I just said, we want cohorts on these.
264 00:30:02.440 ⇒ 00:30:17.730 Henry Zhao: Where are the highest drop-offs? So, do people that start out using a specific feature drop off more likely? What features are the highest retention by plan? We just talked about this. Is self-serve conversion improving? Are AI features driving users to higher dollar amounts overall? We can just look at the plan.
265 00:30:17.880 ⇒ 00:30:22.960 Henry Zhao: Breakdowns, and then what’s a standardized way of evaluating the engagement from a new feature set?
266 00:30:23.920 ⇒ 00:30:25.830 Henry Zhao: So when they launch new features.
267 00:30:26.260 ⇒ 00:30:33.630 Henry Zhao: How do we evaluate the engagement? And then do we need to store, like, a feature launch date somewhere, you know? Yeah.
268 00:30:35.230 ⇒ 00:30:42.160 Henry Zhao: And then we need to select the milestone events that need to move from client-side to server-side. I don’t know what this is, but I put it here as, like, a future…
269 00:30:43.480 ⇒ 00:30:52.000 Robert Tseng: So this is like, okay, let’s say that, Amplitude and Mongo are, like, wildly off. Well, we’re gonna have to push some data from Mongo into Amplitude then, so…
270 00:30:52.110 ⇒ 00:30:56.610 Henry Zhao: So that’s the last, like, we can deal with that when we… when we need to.
271 00:30:56.920 ⇒ 00:30:57.620 Robert Tseng: Okay.
272 00:30:57.620 ⇒ 00:31:04.639 Henry Zhao: But we just figure out what tool we need to use to send, and how do we reconcile the data, like, make sure in the future the data still matches, set some sort of cadence there.
273 00:31:05.830 ⇒ 00:31:18.980 Robert Tseng: Okay, cool. Also, I’ll kind of do a little bit of a readout of, like, the reporting stuff that I actually kind of worked on the past week to Alicia, and then I’m sure she’s going to want to ask, like, why do we need to upgrade our plan? And I think kind of your outline helps illustrate that.
274 00:31:18.980 ⇒ 00:31:33.479 Robert Tseng: So I’ll talk about, like, we’re… we only have 5 cohorts, we can’t do these, like, yeah, we don’t have computation, so we can’t do this kind of, like, upgrade-downgrade signaling, whatever. It’s hard to create proxy events. And then, like, you have, like, on your outline.
275 00:31:33.480 ⇒ 00:31:40.620 Robert Tseng: Well, we really need to be able to look at all these different cohorts so that we can start to look at kind of, like, co-affecting
276 00:31:40.640 ⇒ 00:31:49.620 Robert Tseng: Like, features, and be able to do, yeah, basically do more drill downs on, on, users by different types of
277 00:31:49.690 ⇒ 00:31:59.250 Robert Tseng: kind of different groups of behaviors. So, like, I think, you know, maybe that’s an opportunity to kind of push it to you, and you can walk through some of the things that you’ve been thinking about and getting her feedback.
278 00:32:00.300 ⇒ 00:32:01.060 Henry Zhao: Okay, cool.
279 00:32:01.060 ⇒ 00:32:04.089 Robert Tseng: Okay, so all… I think that’s how we’ll structure the,
280 00:32:04.090 ⇒ 00:32:04.510 Henry Zhao: Awesome.
281 00:32:04.510 ⇒ 00:32:05.459 Robert Tseng: the golf theater.
282 00:32:05.460 ⇒ 00:32:18.820 Henry Zhao: So, during the call, I’m just gonna take notes and understand, kind of, where Lisa’s at, and then after that, I will throw all this, plus the additional notes, into a chat GPT to summarize, then I’ll build the Notions project plan that we’ve shared tomorrow, and we’ll just go over that tomorrow.
283 00:32:19.160 ⇒ 00:32:20.959 Robert Tseng: Okay, yeah, that sounds good.
284 00:32:21.350 ⇒ 00:32:27.599 Henry Zhao: Okay, and then just one last quick, just, housekeeping question is, like, a one-on-one like we just had right now, like, we have talked about Eden, half talked about…
285 00:32:28.090 ⇒ 00:32:33.479 Henry Zhao: README for Clockify, like, I don’t want to spend too much time, like, fine-tuning Clockify.
286 00:32:33.480 ⇒ 00:32:33.870 Robert Tseng: Yeah.
287 00:32:33.870 ⇒ 00:32:38.050 Henry Zhao: One-on-one as just, like, all one-on-ones, just to, like, save time.
288 00:32:38.240 ⇒ 00:32:38.860 Robert Tseng: Yeah.
289 00:32:39.870 ⇒ 00:32:47.179 Henry Zhao: I was thinking about that, because I was like, I don’t want to overbill, like, README or Eden, but, like, if they’re fixed contracts, we’re still… you guys are still paying me, it doesn’t matter, like…
290 00:32:47.180 ⇒ 00:32:51.610 Robert Tseng: Yeah, yeah, yeah. I mean, you should be able to create a separate project
291 00:32:51.740 ⇒ 00:32:57.360 Robert Tseng: I mean, now that you’re full-time, I don’t really care. Not all of your time has to be billed on a client, so I wouldn’t consider this time billed on a client.
292 00:32:58.450 ⇒ 00:32:59.170 Henry Zhao: Right.
293 00:32:59.170 ⇒ 00:32:59.700 Robert Tseng: Yeah.
294 00:32:59.700 ⇒ 00:33:05.429 Henry Zhao: But I also was thinking… but that’s why I was… I was, like, asking Uptam yesterday about, like, the project management stuff, because…
295 00:33:05.800 ⇒ 00:33:12.339 Henry Zhao: if this is going into his data analysis, I still want it to be… so, a little bit about me, right? I’m very OCD, and I’m, like, very, like…
296 00:33:13.380 ⇒ 00:33:18.709 Henry Zhao: I need the data to be exact, even though, like, business-wise, we don’t need it to be that exact. Yeah.
297 00:33:18.710 ⇒ 00:33:25.589 Robert Tseng: But it bothers me when things are not exact, so, like, if I’m doing analysis on this, I want him to have as many good data points as possible.
298 00:33:25.590 ⇒ 00:33:31.920 Henry Zhao: Sure. So when I’m busy and I have an hour where I’m, like, juggling README stuff and eating, I don’t want to have to be, like.
299 00:33:32.230 ⇒ 00:33:34.299 Henry Zhao: Switching Clockify all the time, right? So…
300 00:33:34.300 ⇒ 00:33:35.160 Robert Tseng: Yeah, totally.
301 00:33:35.500 ⇒ 00:33:39.729 Robert Tseng: So you’re saying you just want to dump it in one place? Or you just want to log it in one place?
302 00:33:40.030 ⇒ 00:33:52.269 Henry Zhao: What I might do is I might log in in one place, and just on, like, a notepad somewhere, just say, like, this one-on-one was roughly 50% readme 50% Eden, so when Utam needs to do that analysis, I can say.
303 00:33:53.080 ⇒ 00:33:55.330 Robert Tseng: Like, this is where the time is getting spent.
304 00:33:55.540 ⇒ 00:34:04.709 Henry Zhao: But this wasn’t even an issue until yesterday, because I thought we were good in terms of Eden utilization. Because remember, I was supposed to be at 30 hours for Eden?
305 00:34:04.710 ⇒ 00:34:12.160 Robert Tseng: I think we are, like, it’s just… it’s… I mean, sorry, I don’t… I don’t… except I don’t see eye to eye on this entirely, so… Okay.
306 00:34:12.159 ⇒ 00:34:16.229 Henry Zhao: Yeah. Because you said I had 30 hours with Eden, I’ve never spent 30 hours on Eden.
307 00:34:16.360 ⇒ 00:34:16.780 Robert Tseng: Yeah.
308 00:34:16.780 ⇒ 00:34:33.169 Henry Zhao: I might go a little bit over, but I’ve been at, like, 12, 16 hours with Eden, so I don’t know how our utilization is going over. And I also don’t want to make sure that Amber’s not getting blamed on any of this, because she’s been doing a great job of, like, pushing things, making sure we say no, and, like, getting everything clear. So I want to be clear that Amber’s doing a great job.
309 00:34:33.170 ⇒ 00:34:48.710 Robert Tseng: No, yeah, the problem is with Zoran’s 15 hours a week coming in, like, that was unexpected from what… for the budget that we have from UDID, and then, you know, that just… that just ended up making everybody else’s hours have to go down. And, like, Amber didn’t necessarily manage that, it was just…
310 00:34:48.719 ⇒ 00:34:50.689 Henry Zhao: But he’s also doing alien stuff like that, right?
311 00:34:51.690 ⇒ 00:34:56.179 Robert Tseng: Yeah, but, like, 15… like, you know, we…
312 00:34:57.410 ⇒ 00:35:10.510 Robert Tseng: like, the allocation that we have was not including his additional 15 hours a week on Eden. So, now that he came in, like, that just, like, you know, that just obviously impacted our margins, so…
313 00:35:10.510 ⇒ 00:35:28.940 Henry Zhao: Okay, tell my part, this week, I only used him for one hour, and it was a very useful hour. I needed the tracking join for attribution, and I needed to help on the JavaScript today. I only needed one hour, so we need to figure out what the other 14 hours are, but for, like, the Eden stuff, I only needed his one hour today, okay? The rest of attribution, I’m doing on my time, so just as context to you.
314 00:35:28.940 ⇒ 00:35:29.600 Robert Tseng: Okay.
315 00:35:29.600 ⇒ 00:35:31.110 Henry Zhao: Take that as information, yeah.
316 00:35:31.110 ⇒ 00:35:31.870 Robert Tseng: Yeah, okay.
317 00:35:31.870 ⇒ 00:35:36.389 Henry Zhao: information from me on, like, how the time is being used, because I can’t have a grasp of that right now.
318 00:35:36.390 ⇒ 00:35:49.049 Robert Tseng: Okay. No, that’s helpful to know. I mean, I kept asking, like, how long is Zoran spending? Like, you know, Andrew was pretty consistent. He was, like, 5 to 10 hours, and he was like, okay, we did it for 4 weeks, and then we shut him off. But, like, Zoran, it’s like…
319 00:35:49.050 ⇒ 00:36:04.519 Robert Tseng: I understand that he’s doing… I know there’s budget to get from Eden, because Andrew and Zoran’s work has replaced their fractional CTO. I want to get that budget for us, like, I don’t mind having… I don’t mind having Zoran on for longer, and just, like, kind of jumping in, doing random things, whatever.
320 00:36:04.520 ⇒ 00:36:13.109 Robert Tseng: I don’t care, like, that should just be budgeted separately for him, like, but that shouldn’t eat into the rest of the budget that the team, is… is kind of…
321 00:36:13.560 ⇒ 00:36:19.790 Robert Tseng: like, is basically pulling from. So, yeah, that’s, that’s all I’m saying.
322 00:36:20.070 ⇒ 00:36:31.740 Henry Zhao: I feel better about REME now, and I feel better about, this… this Eden stuff, because this was, like, sitting on my mind all of last weekend… the REA stuff last weekend, and then the Zoran stuff yesterday… the Eden stuff yesterday, so…
323 00:36:31.740 ⇒ 00:36:32.160 Robert Tseng: Okay.
324 00:36:32.160 ⇒ 00:36:36.460 Henry Zhao: We kind of… Feel better about these things that were kind of on my mind.
325 00:36:36.460 ⇒ 00:36:43.809 Robert Tseng: Okay, great. Yeah, no, thanks for bringing it up. I mean, we’re… we’re fine. Like, it’s not, like, that big of a deal, but, like, yeah, I think it’s…
326 00:36:44.490 ⇒ 00:36:54.179 Robert Tseng: you know, when we do have to bring… pull in different people to support the team, like, the budget needs to be adjusted for that. And, like, in order for me to do that.
327 00:36:54.310 ⇒ 00:37:05.899 Robert Tseng: like, yeah, I can… I can preemptively just go and, like, bring in Zoran, and then I have to basically tell Eden, like, later on to adjust for it. I’m okay having those conversations, like, I was doing that before. That’s how we expanded from, like, a…
328 00:37:05.900 ⇒ 00:37:16.060 Robert Tseng: 5K a month mixed panel contract, or whatever the heck we have now. So, I guess it’s just, you know, things are… things are flexible. The con… like, the constraints are not, like.
329 00:37:16.060 ⇒ 00:37:18.570 Robert Tseng: As… they’re not, like… it’s not…
330 00:37:18.750 ⇒ 00:37:28.760 Robert Tseng: it’s not like we have to deliver crappy work in order to, like, meet the constraints. Like, if it is really taking that much time, I will get… I will go get that, time and budget from
331 00:37:28.760 ⇒ 00:37:39.999 Robert Tseng: From the client. So, yeah, that’s kind of… obviously, you’re kind of day-to-day closer to the people working with them, so I need the information from you in order to be able to go in and get the budget.
332 00:37:40.000 ⇒ 00:37:49.180 Henry Zhao: But that’s kind of also why I asked you in New York, like, do they have an engineering team, and is Andrew slash Laurent supposed to replace them? Because if so, we should be getting that budget, like…
333 00:37:49.180 ⇒ 00:37:50.100 Robert Tseng: Yeah, totally.
334 00:37:50.100 ⇒ 00:37:51.829 Henry Zhao: Yeah, that’s why I asked that question, yeah.
335 00:37:51.990 ⇒ 00:37:52.660 Robert Tseng: Yeah.
336 00:37:52.660 ⇒ 00:37:54.899 Henry Zhao: Yeah, cool. Okay, that makes sense now, and I feel better.
337 00:37:55.050 ⇒ 00:37:56.480 Robert Tseng: Okay, great.
338 00:37:56.480 ⇒ 00:37:58.000 Henry Zhao: Cool. Thanks. Thanks, Robert.
339 00:37:58.000 ⇒ 00:38:00.150 Robert Tseng: Yeah, alright. Thanks, Henry. See ya.