Meeting Title: SLs - Playbooks Date: 2026-04-15 Meeting participants: Brylle Girang, Samuel Roberts, Demilade Agboola, Awaish Kumar, Zoran Selinger, Jasmin Multani, Uttam Kumaran
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1 00:03:43.200 ⇒ 00:03:44.150 Brylle Girang: Hello?
2 00:03:45.730 ⇒ 00:03:48.099 Samuel Roberts: Hello! One sec.
3 00:03:49.790 ⇒ 00:03:52.459 Samuel Roberts: Zoom’s being a little… Iggy.
4 00:03:54.550 ⇒ 00:03:57.480 Samuel Roberts: There we go. There we go.
5 00:04:00.630 ⇒ 00:04:01.160 Brylle Girang: I think you’re.
6 00:04:01.160 ⇒ 00:04:01.569 Samuel Roberts: How are you doing?
7 00:04:01.570 ⇒ 00:04:04.210 Brylle Girang: You’re not using your… oh, you’re not using your boom mic.
8 00:04:04.700 ⇒ 00:04:08.750 Samuel Roberts: No, no, no, my… so, when it gets really warm out,
9 00:04:09.270 ⇒ 00:04:13.030 Samuel Roberts: The attic, where my office is gets really hot.
10 00:04:13.290 ⇒ 00:04:14.050 Brylle Girang: Oh, okay.
11 00:04:14.050 ⇒ 00:04:21.010 Samuel Roberts: So I haven’t put in the air conditioning units yet, so I’m down on the first floor, just on my laptop, until I get that sorted out.
12 00:04:21.010 ⇒ 00:04:22.979 Brylle Girang: It’s in an attic, that’s cool!
13 00:04:23.220 ⇒ 00:04:31.800 Samuel Roberts: Yeah, it’s not a bad workspace, it’s like a… like, it’s, you know, like, two and a half-story kind of house, so it’s like… it’s just the… but that means that when the sun’s shining, it bakes the roof.
14 00:04:31.800 ⇒ 00:04:33.040 Brylle Girang: Yeah, yeah, yeah.
15 00:04:33.040 ⇒ 00:04:38.560 Samuel Roberts: They just… the whole… like, it was, like, over 90 degrees Fahrenheit yesterday, which is quite warm.
16 00:04:38.930 ⇒ 00:04:44.779 Samuel Roberts: So I was… I was outside, I was down here on the first floor, and I gotta put the AC units in this weekend, hopefully.
17 00:04:46.450 ⇒ 00:04:47.010 Awaish Kumar: Bye!
18 00:04:48.090 ⇒ 00:04:48.780 Brylle Girang: Irish.
19 00:04:50.310 ⇒ 00:04:58.680 Awaish Kumar: Oh, you are… you have a… like, sunny day right now, grill.
20 00:04:58.680 ⇒ 00:05:16.419 Samuel Roberts: Yeah, yeah, the weather… the weather warmed up the last few days, and so when that happens, all the heat goes to the attic, and then the sun bakes the roof, and so by midday, it’s unbearable, so I’m just heading it off by working on just my laptop, which is a little… it’s nice to sometimes get away from my monitors and just work on the single screen.
21 00:05:16.500 ⇒ 00:05:20.289 Samuel Roberts: Make sure I can still do it without, all the supporting monitors.
22 00:05:21.070 ⇒ 00:05:21.730 Awaish Kumar: Yeah.
23 00:05:21.730 ⇒ 00:05:26.750 Brylle Girang: And this is, like, a virtual background, so I’m just trying to… Yeah, yeah, yeah.
24 00:05:26.750 ⇒ 00:05:28.609 Samuel Roberts: Yeah, no, it’s good, I like it, I like it.
25 00:05:29.150 ⇒ 00:05:30.960 Awaish Kumar: Yeah, but you are in a…
26 00:05:31.380 ⇒ 00:05:32.370 Brylle Girang: Oh, yes!
27 00:05:32.370 ⇒ 00:05:32.890 Awaish Kumar: I’ll listen.
28 00:05:32.890 ⇒ 00:05:33.500 Brylle Girang: it’s…
29 00:05:34.060 ⇒ 00:05:36.350 Awaish Kumar: Sure, so I thought it’s a hot…
30 00:05:37.020 ⇒ 00:05:38.690 Samuel Roberts: Oh, yeah, yeah, yeah.
31 00:05:38.690 ⇒ 00:05:39.150 Awaish Kumar: Pardon.
32 00:05:39.150 ⇒ 00:05:47.399 Brylle Girang: Yeah, during the day, it’s, like, 105 degrees Fahrenheit here, so it is, it is, it is burning hot.
33 00:05:47.600 ⇒ 00:05:52.440 Brylle Girang: We’re in the summer season here in the Philippines, and
34 00:05:52.620 ⇒ 00:06:04.829 Brylle Girang: Oh, you know, I hate it. It’s either, you know, we have two seasons here. It’s either it’s super hot, or it’s raining, but it’s still hot, and we’re currently the former.
35 00:06:06.130 ⇒ 00:06:08.860 Awaish Kumar: What about in winters? Is it… is it the same?
36 00:06:08.860 ⇒ 00:06:11.709 Brylle Girang: We don’t… we don’t have winter here.
37 00:06:11.810 ⇒ 00:06:17.329 Brylle Girang: So, we’re stuck, we’re stuck in the summer season, and then in the rainy season.
38 00:06:19.860 ⇒ 00:06:38.729 Brylle Girang: I do wish that we have winter here, but from all the people that I have talked to that are experiencing winter, they do not wish the same. I think most people despise winter, especially if it’s, you know, getting super cold, so I’m not sure. I think I just want to experience snow.
39 00:06:39.760 ⇒ 00:06:42.560 Samuel Roberts: I like winter… oh, go ahead, go ahead, Danny.
40 00:06:42.560 ⇒ 00:06:51.230 Demilade Agboola: I was gonna say, winter is only fun, like, the first time, first couple of days on your first time. After that, it’s an experience, you’re just like, I think it’s okay.
41 00:06:51.740 ⇒ 00:07:06.110 Samuel Roberts: I don’t mind it, as long as I don’t have to shovel too much. That’s really when I don’t like it, is when I have to get… like, I like looking at the snow, I enjoy the cold, I like the seasons changing, but I hate going out having to shovel in the cold and the snow and everything, so…
42 00:07:07.770 ⇒ 00:07:15.580 Brylle Girang: Yeah, I hope you guys get to visit the Philippines. I think the only thing fun here are the islands when it’s scorching hot.
43 00:07:15.940 ⇒ 00:07:16.960 Samuel Roberts: Oh, yeah.
44 00:07:17.250 ⇒ 00:07:35.339 Brylle Girang: Okay, yeah, anyways, so we’ll be talking about playbooks, so this is just a continuation of the road tools that we’re doing for SLs, and I just have this presentation here created using Visual Explainer that I’m going to, you know, mention again and again, just to make sure that we… we get to remember our skills. But,
45 00:07:35.340 ⇒ 00:07:46.010 Brylle Girang: our first two roadshows were about, you know, delivery source opportunities, and then the next one were about allocations for SLs, and then now, we’re talking about playbooks.
46 00:07:46.040 ⇒ 00:07:54.700 Brylle Girang: So this is just going to be, you know, shorter than the previous ones, since I know that a lot of us here, like, have
47 00:07:54.840 ⇒ 00:08:02.330 Brylle Girang: I’m pretty sure that it’s not 100% understanding, but at least we have, like, good understanding of what these playbooks are.
48 00:08:02.990 ⇒ 00:08:07.389 Brylle Girang: So, I’m going to start with what it is. So, playbooks are, you know.
49 00:08:07.830 ⇒ 00:08:26.800 Brylle Girang: our standards, our guides for our SLs and for our service lines. It is not a skill, because it’s not an actual workflow. It’s not something that you can trigger. It’s meant more like a path that the service lines can follow. It’s not a standard compared to,
50 00:08:26.950 ⇒ 00:08:34.830 Brylle Girang: contrary to what I mentioned earlier, but it is not a standard, because it is not authoritative, which means that, you know, it’s not prescriptive.
51 00:08:34.880 ⇒ 00:08:48.989 Brylle Girang: It can differ based on clients, but it’s something that can guide you on what to do per situation, per instance. And again, it is not a one-off project node. So this is not meant just to, you know, create once and then forget
52 00:08:48.990 ⇒ 00:08:57.400 Brylle Girang: Forever. This is meant for us to guide their service lines into what to actually do for a specific instance or for a specific situation.
53 00:08:58.160 ⇒ 00:09:00.709 Brylle Girang: Before I continue,
54 00:09:00.910 ⇒ 00:09:05.930 Brylle Girang: Does this give you, like, a clearer understanding of what the playbooks are? Or is there…
55 00:09:06.210 ⇒ 00:09:08.129 Brylle Girang: Or there’s some confusion around it?
56 00:09:09.110 ⇒ 00:09:16.780 Awaish Kumar: I’ve been searching, asking Khasher what is the difference between playbook and Skill, so… I, I have…
57 00:09:17.090 ⇒ 00:09:20.110 Awaish Kumar: Yeah, it’s good that I got that definition.
58 00:09:20.450 ⇒ 00:09:32.120 Brylle Girang: Yeah, I think, if I’m going to, like, explain it more, playbooks are a bigger umbrella, and then skills should be within those playbooks. So a playbook can have multiple skills, but a skill
59 00:09:32.320 ⇒ 00:09:35.009 Brylle Girang: Cannot have multiple playbooks under it.
60 00:09:35.340 ⇒ 00:09:37.530 Awaish Kumar: Yeah. Skill is atomic.
61 00:09:38.230 ⇒ 00:09:38.680 Brylle Girang: Exactly.
62 00:09:38.680 ⇒ 00:09:40.020 Awaish Kumar: Excluded.
63 00:09:40.400 ⇒ 00:09:42.029 Brylle Girang: An atomic unit, I like that.
64 00:09:42.780 ⇒ 00:10:01.800 Brylle Girang: So, I just have this cheesy code here that I wanted to insert, and I think this… this applies really well into what the playbooks are. So those who don’t learn from history are going to repeat it, which means that our playbooks are meant for us to understand what happened in the past, how can we make it better.
65 00:10:01.800 ⇒ 00:10:13.909 Brylle Girang: How can we make sure that, you know, our mistakes in the past do not get repeated again, and we get to provide a better experience to our clients and to our service lines in the future. So just remember this when we’re talking about playbooks.
66 00:10:15.030 ⇒ 00:10:29.870 Brylle Girang: So, this is a topic that I have had great insights from my conversation with Zoran, since Zoran was creating, like, this playbook around edge-to-activation. So, E2A is a fairly new service line that we have.
67 00:10:29.870 ⇒ 00:10:37.540 Brylle Girang: That we have launched for our clients, and right now, we only have Eden and, I’m gone.
68 00:10:37.780 ⇒ 00:10:38.310 Zoran Selinger: as often.
69 00:10:38.310 ⇒ 00:10:43.450 Brylle Girang: as our primary examples for the E2A service line.
70 00:10:44.080 ⇒ 00:10:53.970 Brylle Girang: And there have been many learnings from Zoran regarding what to do, what we could have done better, what we could have, you know, implemented better.
71 00:10:54.180 ⇒ 00:11:05.839 Brylle Girang: And the main problem that came there is how can we make sure that our playbooks are actually up-to-date? How can we make sure that our playbooks are evolving alongside Brainforge?
72 00:11:06.010 ⇒ 00:11:06.790 Brylle Girang: So…
73 00:11:06.900 ⇒ 00:11:25.889 Brylle Girang: the major signals here are, you know, our playbooks are no longer relevant to what our tools are, our playbooks are no longer relevant to what our deliveries are, and there’s no, you know, actual specific accountabilities around these playbooks. So these are the main problems, or the main signals that we need to watch out for.
74 00:11:27.650 ⇒ 00:11:37.649 Brylle Girang: And just to give you a better idea of what these playbooks are, I am listing here the example playbooks that we have per service line.
75 00:11:37.710 ⇒ 00:11:52.599 Brylle Girang: So instead of me just going around and telling you what playbooks are, I think a better way to better understand this is just by checking these playbooks from our service clients. So for the data service, I think this has the most playbooks as of the moment.
76 00:11:52.600 ⇒ 00:12:03.019 Brylle Girang: that Alwaysh and Otam have been creating in the past, so take a look at this. But also, I want to, like, give the floor to Awash, if that’s okay? To, like.
77 00:12:03.330 ⇒ 00:12:13.960 Brylle Girang: Can you… can you walk us through these playbooks, how it works, how you created it, and maybe what it is for, so that all the other SLs here have a better idea?
78 00:12:14.790 ⇒ 00:12:15.600 Awaish Kumar: Okay.
79 00:12:16.100 ⇒ 00:12:18.569 Awaish Kumar: So, I have created them while…
80 00:12:18.820 ⇒ 00:12:20.960 Awaish Kumar: while I have to work, or…
81 00:12:21.400 ⇒ 00:12:29.030 Awaish Kumar: Or, like, I got a task to create a snowbike, so while working on that, I figured that this is something
82 00:12:29.150 ⇒ 00:12:32.630 Awaish Kumar: That can be, repetitive.
83 00:12:32.740 ⇒ 00:12:39.010 Awaish Kumar: Like, the same path we have to follow for For creating snow pipes.
84 00:12:39.150 ⇒ 00:12:45.409 Awaish Kumar: Especially if we have, same… like, the source, S3.
85 00:12:45.720 ⇒ 00:12:53.150 Awaish Kumar: So… I went in to actually… to codify it, in a way, so that I don’t need to…
86 00:12:53.720 ⇒ 00:12:58.329 Awaish Kumar: Figure out what all the commands are, structures, and their syntax.
87 00:12:58.570 ⇒ 00:13:00.080 Awaish Kumar: So, yeah.
88 00:13:00.280 ⇒ 00:13:06.689 Awaish Kumar: So while I was working on that, like, the cutser have all the… Knowledge in that session.
89 00:13:06.850 ⇒ 00:13:13.200 Awaish Kumar: So, it makes it easier to create playbooks while you are work… working on something, really.
90 00:13:13.370 ⇒ 00:13:27.260 Awaish Kumar: So, when I’m creating snow pipes using cursor, and I’m giving the information and the commands and everything, once it has everything in that session, it has all that knowledge it needs to create a playbook.
91 00:13:27.500 ⇒ 00:13:43.639 Awaish Kumar: Then it made easier for me to ask Cursor to actually create a playbook. I just have to… I just had to enforce, like, a few things that I want… I don’t want it to run it automatically, so some gates on when to execute after my approval, and what are the user inputs.
92 00:13:43.800 ⇒ 00:13:49.199 Awaish Kumar: That needs to start, actually, Like, to start off.
93 00:13:49.340 ⇒ 00:13:53.780 Awaish Kumar: So, yeah, this is what is really needed while creating a playbook.
94 00:13:54.270 ⇒ 00:14:02.279 Brylle Girang: Yeah, I think one question that I also want us to tackle here is, why do you think are display books important for the data service line?
95 00:14:04.880 ⇒ 00:14:10.359 Awaish Kumar: Yeah, as I mentioned, like, these are important, like, for two things. Number one,
96 00:14:11.340 ⇒ 00:14:14.100 Awaish Kumar: For the quality, I had standardizing.
97 00:14:14.250 ⇒ 00:14:23.889 Awaish Kumar: The way we want to write a snowpipe, the way we want to, for example, give the names for our stages, pipes, so it basically standardizes your…
98 00:14:25.530 ⇒ 00:14:41.890 Awaish Kumar: centralize that part, and then second thing is it speeds up the development for the next time. So, for CTA, I have been creating snow pipes. I had to do it for multiple sources. I did it first
99 00:14:42.020 ⇒ 00:14:46.479 Awaish Kumar: Once, and I did it twice, and then I figured out, okay, this is something I have to do.
100 00:14:46.630 ⇒ 00:14:49.670 Awaish Kumar: repetitively, and I don’t want to spend,
101 00:14:49.860 ⇒ 00:14:56.920 Awaish Kumar: 2-3 hours doing that, so instead I created this, now I can do… create a new Oh, surviving,
102 00:14:57.270 ⇒ 00:14:58.929 Awaish Kumar: Maybe in 15 minutes.
103 00:15:00.660 ⇒ 00:15:10.979 Brylle Girang: Amazing. Great. So yeah, I wish he learned from history, and he didn’t want to repeat it. That’s amazing. Also, I think one… one main importance here is…
104 00:15:11.200 ⇒ 00:15:31.159 Brylle Girang: scalability, especially since Brainforge is growing. We want to make sure that, you know, everyone in our service lines are operating within the same baselines and within the same standards. And without playbooks, new hires or, you know, new people would need to explore everything from the ground up.
105 00:15:31.430 ⇒ 00:15:40.780 Brylle Girang: You as SLs, by creating display books, you are helping the newly hires to make sure that, you know, they understand what we’re doing.
106 00:15:40.840 ⇒ 00:15:58.640 Brylle Girang: from day one. They understand what the guidelines are, and they are guided from what they need to do for each specific instance from day one. So it helps you by not taking too much of your time. Our new hires would not need to, like, call you to understand what we’re doing.
107 00:15:58.640 ⇒ 00:16:04.429 Brylle Girang: how we’re… how we’re, how we’re approaching things, etc. So I think that’s also one of the main importance for this.
108 00:16:04.790 ⇒ 00:16:07.840 Brylle Girang: So that’s for the data service. Thank you, Oish, again.
109 00:16:07.970 ⇒ 00:16:14.019 Brylle Girang: six, you know, you, you collaborating with Utam with creating these, these playbooks, and social…
110 00:16:14.020 ⇒ 00:16:26.989 Uttam Kumaran: It’s mostly Awash, it’s not… it’s not… it’s not as much as me. Some of these are old. I think Awash’s point, though, in that, like, right at the end of when you just did a thing, being like, create a playbook.
111 00:16:27.060 ⇒ 00:16:37.129 Uttam Kumaran: is, like, the… I have not found an easier way. We’re all busy, it’s hard to, like, sit down and write the playbooks. It’s very easy, though, right at the end, to be like.
112 00:16:37.400 ⇒ 00:16:42.619 Uttam Kumaran: hey, like, I just did a chunk of work that is, like, pretty reproducible.
113 00:16:42.890 ⇒ 00:17:01.949 Uttam Kumaran: A good example is I wrote something to help default connect SuperBase to S3 with a GitHub action. Very, like, specific piece of work that I’m like, maybe sometime in the future, we end up doing that again. Let me just write a playbook for how to do this, and then I shipped it.
114 00:17:02.140 ⇒ 00:17:15.859 Uttam Kumaran: Part of this, though, is just getting in the habit of that, and you’re gonna see that the amount of playbooks you create, it’s very similar to skill creation. So, one thing that I’m gonna try to do, and in the way that, on the platform team, you should see that
115 00:17:15.930 ⇒ 00:17:22.360 Uttam Kumaran: Cursor and your tools will ask you, do you want to create this as a playbook? Do you want to create a skill for this?
116 00:17:22.440 ⇒ 00:17:24.259 Uttam Kumaran: But ultimately, I think…
117 00:17:25.000 ⇒ 00:17:33.929 Uttam Kumaran: being able to just look back at the work you did for the week, and do that. So whether that’s, like, right at the end of the chat, or whether that’s at the end of the week, you’re looking at all past chats.
118 00:17:34.040 ⇒ 00:17:35.699 Uttam Kumaran: What are some opportunities?
119 00:17:36.290 ⇒ 00:17:38.460 Uttam Kumaran: Like, I just wanted to double down on that.
120 00:17:42.210 ⇒ 00:18:01.310 Brylle Girang: Yeah, thank you. Again, shout out to OH. These are amazing. Yeah, so some, some few examples, too. So, for strategy and analytics, one thing that I have seen is the playbook revolving around dashboard specifications. So, similar to OASH, can you walk us through, like, how you did this, why you did this, and what it is for?
121 00:18:01.450 ⇒ 00:18:09.000 Uttam Kumaran: Yes, let me see if I can even find the chat, because it’s gonna be helpful for everybody to just, like…
122 00:18:09.820 ⇒ 00:18:11.949 Uttam Kumaran: B, how I got here.
123 00:18:12.250 ⇒ 00:18:17.630 Uttam Kumaran: Let’s see if I can… find it.
124 00:18:32.220 ⇒ 00:18:35.230 Uttam Kumaran: Okay, I may not have the exact…
125 00:18:36.950 ⇒ 00:18:43.100 Uttam Kumaran: Chad. But basically, the way… the way, I was looking at this…
126 00:18:49.080 ⇒ 00:18:59.449 Uttam Kumaran: Yeah, I don’t think I have the perfect one, but basically what this was, was that for Element, we were continuing to struggle to set standards for dashboards.
127 00:18:59.760 ⇒ 00:19:17.419 Uttam Kumaran: And so, like, Greg was like, hey, I’m putting, like, multiple formats in front of the client. I was seeing other clients using multiple formats for dashboards. So what I did is I took the existing dashboard requirements, and I went into Kirscher, and I said, hey, today I want to work on a dashboard spec.
128 00:19:18.240 ⇒ 00:19:32.460 Uttam Kumaran: I, beforehand, wrote down all the things that I expect in a dashboard spec, as someone that’s built a lot of dashboards. I then said, here’s a couple of specs that we’ve done for clients. As you can see, there is, like, misalignment.
129 00:19:32.770 ⇒ 00:19:35.499 Uttam Kumaran: And the formatting of those specs.
130 00:19:35.610 ⇒ 00:19:37.240 Uttam Kumaran: Today, I want your help.
131 00:19:37.440 ⇒ 00:19:40.140 Uttam Kumaran: Not only working on the new spec.
132 00:19:40.310 ⇒ 00:19:48.600 Uttam Kumaran: but also working on, yeah, basically, I started this. I was like, hey, I’m just gonna brain dump everything.
133 00:19:48.920 ⇒ 00:19:49.610 Uttam Kumaran: What?
134 00:19:49.800 ⇒ 00:19:52.709 Uttam Kumaran: what I’ve learned in 10 years of writing dashboards.
135 00:19:52.910 ⇒ 00:20:05.939 Uttam Kumaran: I’m just gonna write it all down, I’m gonna see if anyone else has a sec to comment. What I did is I copied all this, I copied the specs, and I told AI, hey, I wanna write a new dashboard spec. But I also said, at the end of this, I want to…
136 00:20:06.100 ⇒ 00:20:09.750 Uttam Kumaran: end up with not only a dashboard spec, I want to migrate
137 00:20:10.700 ⇒ 00:20:14.520 Uttam Kumaran: this existing spec to this, so I can get feedback.
138 00:20:14.650 ⇒ 00:20:16.780 Uttam Kumaran: And so what I did is I…
139 00:20:17.360 ⇒ 00:20:31.179 Uttam Kumaran: I… I did exactly that. I wrote this… the spec. I felt okay with it. I published it to the Element team. They came back and were like, okay, I think this doesn’t make sense, this doesn’t make sense. Ultimately, I actually was the one giving most of the feedback.
140 00:20:31.320 ⇒ 00:20:35.350 Uttam Kumaran: Then I, like, took all… I used the GWS DLI,
141 00:20:35.470 ⇒ 00:20:41.550 Uttam Kumaran: which I can scan through your Google Doc, took all my comments, redid another version of the spec.
142 00:20:41.760 ⇒ 00:20:47.070 Uttam Kumaran: And then I said, perfect. Beck is in, like, a good spot, at least for Jasmine to take it from here.
143 00:20:47.230 ⇒ 00:21:01.460 Uttam Kumaran: Then I said, I want to create a skill that helps people create specs for dashboards. Ultimately, what I wanted it to do is, you can say, I want to make a new dashboard spec. It will ask you questions about what’s in the dashboard.
144 00:21:01.970 ⇒ 00:21:04.149 Uttam Kumaran: And then it’ll write the spec out for you.
145 00:21:05.640 ⇒ 00:21:17.160 Uttam Kumaran: And that’s basically the entirety of the PR. What this helps, right, is now Greg and other people don’t have to think about, like, what is in a spec.
146 00:21:17.500 ⇒ 00:21:20.930 Uttam Kumaran: They think about writing, like, completing the spec.
147 00:21:21.180 ⇒ 00:21:32.309 Uttam Kumaran: Right? So I’ve… I’ve removed that decision from them, which is great. Like, we’ve removed that from… from their, like, need to think about the formatting. They need to come with a context.
148 00:21:32.540 ⇒ 00:21:37.969 Uttam Kumaran: Right? And so that’s… that’s sort of, like, what I did here. I… it took maybe, like, 30-40 minutes.
149 00:21:40.020 ⇒ 00:21:52.670 Uttam Kumaran: But, like, this is, I think, like, the way I want to see people jump on opportunities to make more specs and make more playbooks. Like, if you’re seeing a piece of work happen, and it’s happening often,
150 00:21:52.890 ⇒ 00:22:00.099 Uttam Kumaran: It’s a great opportunity to just say, like, to tell that person, make a playbook, or you just take their work.
151 00:22:00.150 ⇒ 00:22:13.419 Uttam Kumaran: And make a playbook out of it. And then next time you see it done, you can let them know, use the playbook. And then, it’s sort of like onboarding materials, like, hey, once you go through onboarding, leave any comments on anything that was wrong, you know?
152 00:22:17.730 ⇒ 00:22:22.290 Brylle Girang: And how many hours do you think that this will save, like, the strategy team.
153 00:22:23.650 ⇒ 00:22:32.209 Uttam Kumaran: No, I think a lot of people are doing work with, like, are doing actual work that could have been in playbooks, where we’ve done the work before.
154 00:22:32.510 ⇒ 00:22:36.530 Uttam Kumaran: And instead, they’re relying on just, like, their intuition in the moment.
155 00:22:36.530 ⇒ 00:22:36.890 Brylle Girang: Yeah.
156 00:22:36.890 ⇒ 00:22:40.129 Uttam Kumaran: Versus, like, hey, Brainforge has actually done this type of work before.
157 00:22:43.490 ⇒ 00:22:50.490 Uttam Kumaran: So, like, I mean, I think there’s… I think this is… this is where, when I talk about, like, defects coming in the system, typically when people are not
158 00:22:50.670 ⇒ 00:23:07.999 Uttam Kumaran: following a playbook or an approved process is when… for us, we’re good. We’ve done a lot of this stuff for a while. It’s everybody else, right? And what you’re gonna find is leverage for us as service leads is, in one way, can everybody else start to think like us?
159 00:23:08.270 ⇒ 00:23:20.669 Uttam Kumaran: Right? Before, right, how do you impact that leverage? You have to teach, you have to have, like, check-ins, you have to, like, have review processes. With AI, you can actually disperse the knowledge
160 00:23:20.820 ⇒ 00:23:26.509 Uttam Kumaran: Way faster, and in a way that actually is, like, right alongside people’s work.
161 00:23:26.980 ⇒ 00:23:34.649 Uttam Kumaran: It’s not like they have to, like, read a manual. They literally can go into Cursor and say, hey, take… give me the playbook for setting up Cloudflare.
162 00:23:34.830 ⇒ 00:23:36.339 Uttam Kumaran: What should I do next?
163 00:23:36.860 ⇒ 00:23:39.730 Uttam Kumaran: See what I mean? It, like, it really de-risks.
164 00:23:40.540 ⇒ 00:23:43.050 Uttam Kumaran: And so that’s what we’re trying to do.
165 00:23:43.500 ⇒ 00:23:53.809 Uttam Kumaran: And so this is where, like, the leverage creation, I think, is really, really important here, but you’re gonna find that, like, just by telling people, hey, I already wrote a playbook for this, just follow that.
166 00:23:54.110 ⇒ 00:24:05.309 Uttam Kumaran: you’re gonna save so much time, and, like, so much time identifying where the defect is. Instead, if the playbook is wrong, you guys… you can be critical about the playbook and change that. That’s actually great.
167 00:24:05.340 ⇒ 00:24:18.619 Uttam Kumaran: Right? So a lot of this is standard in SOP setting, but you’re gonna find it’s different than what would be in a traditional organization, where you’re like, write a runbook, and then nobody looks at that ever. Right? Like, this is literally where everybody works.
168 00:24:18.740 ⇒ 00:24:24.289 Uttam Kumaran: it’s going to be very hard to be working on Cloudflare, and the AI’s gonna tell you.
169 00:24:24.460 ⇒ 00:24:32.100 Uttam Kumaran: hey, there’s a playbook for this. Like, you should use that. Right? And that’s my job on the platform team, but, like, that’s what you could expect.
170 00:24:34.920 ⇒ 00:24:39.539 Samuel Roberts: I was gonna ask, are the playbooks discoverable the same way skills are? So, like, cursor just…
171 00:24:39.690 ⇒ 00:24:43.140 Samuel Roberts: Will know the metadata there, and… or does it have to look at.
172 00:24:43.140 ⇒ 00:24:44.520 Uttam Kumaran: Not as much, but.
173 00:24:44.520 ⇒ 00:24:44.990 Samuel Roberts: Okay.
174 00:24:44.990 ⇒ 00:24:49.110 Uttam Kumaran: When we kind of moved to… Like, the work platform.
175 00:24:49.110 ⇒ 00:24:50.100 Samuel Roberts: That’s what I was hoping.
176 00:24:50.100 ⇒ 00:25:03.969 Uttam Kumaran: some other surfaces, it… we’ll be able to customize how some of these Brainforge-type artifacts work. Skills, though, but again, what you should coach the people on your team to do is, when they’re taking a piece of work, to just say, are there playbooks for this?
177 00:25:03.970 ⇒ 00:25:05.010 Samuel Roberts: Yeah.
178 00:25:05.010 ⇒ 00:25:10.510 Uttam Kumaran: the behavior change that I seize, and everybody need to… Start to do.
179 00:25:10.640 ⇒ 00:25:16.309 Uttam Kumaran: But that’s what I’m like, we’re gonna start to push that, where people should come and say, I have this task today.
180 00:25:16.950 ⇒ 00:25:19.350 Uttam Kumaran: Give me… how should I execute it?
181 00:25:19.490 ⇒ 00:25:27.370 Uttam Kumaran: skills, playbooks, maybe there’s a subject matter expert, there’s a transcript that’s relevant. The platform will sort of give you all the relevant context.
182 00:25:28.000 ⇒ 00:25:28.540 Samuel Roberts: Perfect.
183 00:25:28.990 ⇒ 00:25:29.540 Uttam Kumaran: Yeah.
184 00:25:34.580 ⇒ 00:25:38.450 Brylle Girang: Yeah, I guess, any more questions regarding… Playbooks?
185 00:25:43.090 ⇒ 00:25:58.240 Uttam Kumaran: So even… even if, yeah, one… maybe one more thing, sorry, even if it’s helpful for, like, this week, if you’re like, hey, let’s just spend 30 minutes, because I have, like, 100 playbooks in the back of my head I want to write, if it’s helpful for us to all just, like, blind doing that, we could do that.
186 00:25:58.530 ⇒ 00:26:03.610 Uttam Kumaran: like, for example, I have a bunch of, like, dbt playbooks I want to run, I have some, like.
187 00:26:03.950 ⇒ 00:26:07.380 Uttam Kumaran: platform-related playbooks I want to create, so…
188 00:26:07.540 ⇒ 00:26:11.150 Uttam Kumaran: Happy to… to do that. Sorry, go ahead, Demi.
189 00:26:12.340 ⇒ 00:26:15.829 Demilade Agboola: I was just saying, if there’s a way we can organize it such that…
190 00:26:16.400 ⇒ 00:26:21.400 Demilade Agboola: We can easily find the playbooks, that could also be very helpful.
191 00:26:22.810 ⇒ 00:26:23.440 Uttam Kumaran: Okay.
192 00:26:23.550 ⇒ 00:26:33.110 Uttam Kumaran: Yeah, right now, in the platform, under knowledge, there… we’re… I’m trying to organize the playbooks by service line, or by subservice.
193 00:26:33.720 ⇒ 00:26:39.329 Demilade Agboola: So what I mean by that is, like, If we have, like.
194 00:26:40.110 ⇒ 00:26:46.039 Demilade Agboola: like, for the data team, for instance, like, in Slack, we can have it pinned, like, the list of playbooks.
195 00:26:46.040 ⇒ 00:26:46.930 Uttam Kumaran: I see, I see.
196 00:26:46.930 ⇒ 00:26:49.670 Demilade Agboola: Like, a link to the playbooks, or, you know…
197 00:26:49.790 ⇒ 00:27:00.820 Demilade Agboola: in the, like, the AI team, they can also have, like, a link to their list of playbooks and stuff, so that way it’s very easily accessible, and it’s easy to be top of mind when you’re trying to start a new task.
198 00:27:07.470 ⇒ 00:27:08.799 Uttam Kumaran: Okay, I can take that on.
199 00:27:16.700 ⇒ 00:27:17.240 Demilade Agboola: Also.
200 00:27:17.660 ⇒ 00:27:18.600 Demilade Agboola: Oh, M.
201 00:27:19.190 ⇒ 00:27:26.840 Demilade Agboola: The same way, like, I had, like, conversations with Bryl, and we talked about how… Being able to…
202 00:27:27.300 ⇒ 00:27:30.140 Demilade Agboola: Put the different skills into different buckets.
203 00:27:30.270 ⇒ 00:27:33.499 Demilade Agboola: That’s kind of like this, in the sense that, like.
204 00:27:34.850 ⇒ 00:27:38.930 Demilade Agboola: They can be, like, general core, like, playbooks. Yeah.
205 00:27:39.150 ⇒ 00:27:41.160 Demilade Agboola: But being able to, like.
206 00:27:42.830 ⇒ 00:27:51.579 Demilade Agboola: Point to different teams when certain playbooks are being created, and just be like, hey, platform team, this playbook has just been created, so instead of doing this all the time.
207 00:27:51.860 ⇒ 00:27:53.980 Demilade Agboola: You can use this instead.
208 00:27:54.170 ⇒ 00:27:58.769 Demilade Agboola: Same thing with, like, the modeling team here, instead of just, like…
209 00:27:59.360 ⇒ 00:28:02.030 Demilade Agboola: Modeling the same thing every single time.
210 00:28:02.140 ⇒ 00:28:05.020 Demilade Agboola: This is a playbook that helps you do it much faster.
211 00:28:05.560 ⇒ 00:28:07.330 Demilade Agboola: Same thing with, like…
212 00:28:07.550 ⇒ 00:28:13.499 Demilade Agboola: whichever team, basically. So that way, everyone’s also aware of, like, the new stuff that’s coming out.
213 00:28:13.760 ⇒ 00:28:23.019 Demilade Agboola: And even then, it’s much easier to get feedback on things that are taking quite a bit of time, because then it can be more interactive, and so you can say, hey, like.
214 00:28:23.190 ⇒ 00:28:27.460 Demilade Agboola: what’s taking you the most time now? Is there a playbook we can create that can
215 00:28:27.630 ⇒ 00:28:32.610 Demilade Agboola: Even if it’s half the time that you’re currently using on it, that would also be very helpful, so…
216 00:28:32.830 ⇒ 00:28:35.130 Demilade Agboola: I guess, playbooks.
217 00:28:35.610 ⇒ 00:28:40.910 Demilade Agboola: That would also drive, like, the utilization of those playbooks, because if it’s stuff that people are actively…
218 00:28:41.200 ⇒ 00:28:48.909 Demilade Agboola: struggling with, or, like, it takes a lot of time in their current process, they will be excited to use it, because they also want to
219 00:28:49.330 ⇒ 00:28:53.029 Demilade Agboola: You know, speed up that process, and it’s something that’s an active pain.
220 00:28:54.560 ⇒ 00:29:09.059 Uttam Kumaran: Yeah, so what’s helpful for me is as soon as you guys start creating these, and start telling people to use them, there’s gonna be some of these paper cuts. That’s where I want to be helpful in solving that. So that’s why the faster that you guys can start to create and push your team to start using them.
221 00:29:09.290 ⇒ 00:29:20.239 Uttam Kumaran: then it’s like, okay, they need to be more discoverable. Perfect, I can take that. Or, hey, like, I want… I want AI to automatically suggest people playbooks more, like.
222 00:29:20.730 ⇒ 00:29:25.980 Uttam Kumaran: like… in a more annoying way, I can solve that, right? So…
223 00:29:31.060 ⇒ 00:29:33.500 Awaish Kumar: Is it possible to run,
224 00:29:34.110 ⇒ 00:29:41.100 Awaish Kumar: For every chat prompt that you send, is it possible to run anything in the backend for the cursor? So it can look…
225 00:29:41.550 ⇒ 00:29:42.020 Awaish Kumar: Automatic.
226 00:29:42.020 ⇒ 00:29:43.060 Uttam Kumaran: Yeah, so…
227 00:29:43.620 ⇒ 00:30:00.549 Uttam Kumaran: Yeah, I mean, I had this idea, the problem is we don’t have Cursor Enterprise, and so we don’t have access to logs. So part of the reason I’m gonna be talking to some people on the team today about moving to a little bit of a new platform is for me to start to see some of the logs.
228 00:30:00.600 ⇒ 00:30:04.329 Uttam Kumaran: And build on top of that, effectively. So…
229 00:30:05.330 ⇒ 00:30:11.330 Uttam Kumaran: TBD. But yes, that’s on the roadmap to basically scan for…
230 00:30:12.010 ⇒ 00:30:17.959 Uttam Kumaran: Prompt scan for playbook creation, skill creation, using all the chats that are happening.
231 00:30:20.890 ⇒ 00:30:27.640 Awaish Kumar: Yeah, my point was more, like, in the real time, that a process runs and suggests, like, based on your brand, you can use
232 00:30:27.780 ⇒ 00:30:31.539 Awaish Kumar: There are 2-3 playbooks that might be useful for you.
233 00:30:32.500 ⇒ 00:30:39.570 Uttam Kumaran: Yeah, so there is… there is this, like, skill that I created called, like, cursor history.
234 00:30:40.050 ⇒ 00:30:45.629 Uttam Kumaran: maybe give it a shot on your machine, because I built it because I wanted to start to, like.
235 00:30:45.740 ⇒ 00:30:49.050 Uttam Kumaran: Push my chats into the platform.
236 00:30:49.730 ⇒ 00:30:54.889 Uttam Kumaran: I would be interested if you can string that with the… Playbook Creator.
237 00:30:55.390 ⇒ 00:31:01.200 Uttam Kumaran: or have it look through that and see, and tell you if there’s any playbooks to create. I haven’t tried that yet.
238 00:31:01.730 ⇒ 00:31:07.849 Uttam Kumaran: This is something that I was, like, trying to figure this out, but then… because… well… yeah.
239 00:31:07.990 ⇒ 00:31:09.960 Uttam Kumaran: There’s gonna be some… we’ll be…
240 00:31:10.070 ⇒ 00:31:14.099 Uttam Kumaran: Moving to a few other oper… like, ways to solve this problem, so…
241 00:31:14.430 ⇒ 00:31:16.180 Uttam Kumaran: But that… that’s helpful to hear.
242 00:31:16.900 ⇒ 00:31:24.820 Samuel Roberts: By the way, are you wondering more about, like, an HSMD that would specifically try to call out, oh, it looks like you’re doing this task, there’s a playbook for it?
243 00:31:25.870 ⇒ 00:31:26.569 Awaish Kumar: Yeah, yeah.
244 00:31:27.010 ⇒ 00:31:28.160 Uttam Kumaran: Okay, okay.
245 00:31:28.560 ⇒ 00:31:30.770 Uttam Kumaran: Okay, that’s something I can also…
246 00:31:31.250 ⇒ 00:31:33.180 Uttam Kumaran: I can take, and I’ll put a ticket.
247 00:31:33.290 ⇒ 00:31:34.970 Uttam Kumaran: This week, to take on.
248 00:31:35.710 ⇒ 00:31:36.930 Uttam Kumaran: Okay, makes sense.
249 00:31:43.740 ⇒ 00:31:45.110 Brylle Girang: Okay,
250 00:31:46.020 ⇒ 00:32:04.859 Brylle Girang: this is not, like, this is not a prescription, but this is what AI has given me when I was asking for, like, ideas of playbooks that we can create. So, for AI data strategy, again, this is not a prescription, the expertise is with you, but if you want to, like, get some ideas on which to prioritize, this might help.
251 00:32:06.060 ⇒ 00:32:22.289 Brylle Girang: I think, data, we have pretty much, you know, six playbooks. Strategy, we have one, AI, I would challenge you some to, like, create more playbooks around AI, revolving around AI, so that Case and Mustafa could also have, like, you know, a smoother run when it comes to
252 00:32:22.480 ⇒ 00:32:23.930 Brylle Girang: the workflows.
253 00:32:24.990 ⇒ 00:32:34.219 Brylle Girang: E2A, I know, Zaran, that you are already creating one. Sorry, I forgot to add it here, but I know that you are in the process of, like, polishing the E2A playbooks too.
254 00:32:35.230 ⇒ 00:32:45.309 Brylle Girang: So again, just to recap, so the SL owns, you know, basically the playbooks. The accuracy of it, the priority of each playbook to create.
255 00:32:45.340 ⇒ 00:32:51.229 Brylle Girang: But the links and the relevant resources, as well as the adoption for your service line’s IECs.
256 00:32:51.240 ⇒ 00:33:07.969 Brylle Girang: So your main responsibility here, I would argue that your main responsibility is not just to create playbooks, but to make sure that your people actually uses those playbooks. Because if you create these playbooks and then no one adopts it, it will be pretty much useless in the long run.
257 00:33:10.160 ⇒ 00:33:11.680 Brylle Girang: And yeah,
258 00:33:12.480 ⇒ 00:33:31.270 Brylle Girang: Those are everything. I guess one assignment that we would need here. By Monday, we would love to see, like, one playbook created for each service line at the minimum. So we want to see, you know, we want to gather more feedback. We want to make sure that we move fast when it comes to making our processes more scalable in the long term.
259 00:33:35.220 ⇒ 00:33:37.289 Brylle Girang: Utam, anything that you want to add?
260 00:33:38.580 ⇒ 00:33:51.590 Uttam Kumaran: No, I think that’s it. I think this is a great opportunity, guys, for you to just start to set some standards, you know, and then any… and then, like, a good example is, like, Zoran, your work, although you need analytics engineers, is a little bit specific, right?
261 00:33:51.710 ⇒ 00:34:00.499 Uttam Kumaran: So that path of getting people who have, like, a generalized knowledge to your thing, this is a perfect way to do that, you know?
262 00:34:00.500 ⇒ 00:34:01.010 Zoran Selinger: No.
263 00:34:01.010 ⇒ 00:34:04.249 Uttam Kumaran: So, think about Kayla’s perspective as, like, okay.
264 00:34:04.360 ⇒ 00:34:09.630 Uttam Kumaran: If Kayla wants to hire, now she can look at a wider audience, because people can just do your playbooks.
265 00:34:09.880 ⇒ 00:34:13.310 Uttam Kumaran: To take this to, like, the nth degree.
266 00:34:13.639 ⇒ 00:34:17.430 Uttam Kumaran: Brainforge is just a team of really smart engineers.
267 00:34:17.719 ⇒ 00:34:32.930 Uttam Kumaran: people should be able to, like, move across service lines, right? Effectively. Maybe you have expertise, but we want the playbooks to start to level out, like, knowledge across the company, because I don’t… otherwise, what we’re gonna have is
268 00:34:33.159 ⇒ 00:34:39.229 Uttam Kumaran: someone can’t work over here. Instead, we want to be a group of, like, mercenaries, almost, right? So you pick the people for the job.
269 00:34:39.440 ⇒ 00:34:44.410 Uttam Kumaran: But ultimately, we have playbooks, so, like, worst case, you can rely on, like, the handbook.
270 00:34:44.650 ⇒ 00:34:48.209 Uttam Kumaran: For how to take on, you know, a certain challenge.
271 00:34:48.780 ⇒ 00:34:56.080 Uttam Kumaran: That’s… Further down the vision, but that’s… hopefully this is, like, what is starting to normalize,
272 00:34:56.360 ⇒ 00:34:59.199 Uttam Kumaran: You know, knowledge across… across areas, so…
273 00:35:01.290 ⇒ 00:35:02.510 Zoran Selinger: Yeah, that makes sense.
274 00:35:06.950 ⇒ 00:35:07.550 Uttam Kumaran: Okay.
275 00:35:07.850 ⇒ 00:35:08.590 Uttam Kumaran: Great.
276 00:35:09.240 ⇒ 00:35:11.710 Uttam Kumaran: Thanks, B, appreciate it. Great presentation.
277 00:35:11.790 ⇒ 00:35:12.310 Samuel Roberts: Yeah.
278 00:35:12.310 ⇒ 00:35:13.270 Brylle Girang: Yeah, everyone.
279 00:35:13.470 ⇒ 00:35:14.620 Zoran Selinger: Thanks, buddy.
280 00:35:14.880 ⇒ 00:35:15.660 Brylle Girang: Okay. Bye.
281 00:35:15.660 ⇒ 00:35:16.260 Uttam Kumaran: Bye.