2026-02-27_brainforge_x_movers_ai_solutions_discuss_d1fbe9e7

Meeting Title: Brainforge x Movers AI Solutions Discussion Date: 2026-02-27 Meeting participants: Luke Scorziell, Pranav Narahari, Luke’s Notetaker, Jeff MacDonald | Dir, Innovation and Technology

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WEBVTT

1 00:00:17.340 ⇒ 00:00:18.610 Pranav Narahari: Hello, hello.

2 00:00:18.880 ⇒ 00:00:19.720 Luke Scorziell: Ayy.

3 00:00:22.860 ⇒ 00:00:24.949 Pranav Narahari: I feel like every time you see me, I have a different background.

4 00:00:27.050 ⇒ 00:00:35.170 Luke Scorziell: There was a while when I was working on my own stuff, that I would be, like, just traveling, or, yeah, in different coffee shops and whatnot, like, every day, and…

5 00:00:35.720 ⇒ 00:00:39.990 Luke Scorziell: So, yeah, one of the people I was working with was like, dude, I feel like you’re always the different…

6 00:00:40.660 ⇒ 00:00:42.000 Luke Scorziell: spot.

7 00:00:43.290 ⇒ 00:00:44.210 Luke Scorziell: Oh.

8 00:00:45.050 ⇒ 00:00:45.840 Luke Scorziell: Yeah.

9 00:00:46.080 ⇒ 00:00:50.640 Luke Scorziell: This Brainforge background makes me feel like we have a nice… Right, office.

10 00:00:51.190 ⇒ 00:00:53.690 Pranav Narahari: No, I need to do that. I need to just set that up.

11 00:00:53.870 ⇒ 00:00:56.540 Luke Scorziell: It’s already in the Zoom, actually.

12 00:00:56.620 ⇒ 00:00:57.920 Pranav Narahari: Is it really?

13 00:00:57.920 ⇒ 00:01:03.279 Luke Scorziell: Yeah, because I didn’t even, I was, like… I asked Hannah to kind of give me…

14 00:01:03.770 ⇒ 00:01:10.829 Luke Scorziell: the backgrounds, and then she did, but then I went on to upload them, and then found that they were already in Zoom, so I think that’s true for everyone, but yeah.

15 00:01:11.230 ⇒ 00:01:15.620 Pranav Narahari: I’m not seeing it for me. For my backgrounds, I just see, like, the generic Zoom ones, but…

16 00:01:15.830 ⇒ 00:01:17.040 Pranav Narahari: I’ll look into it later.

17 00:01:17.850 ⇒ 00:01:19.250 Luke Scorziell: No worries.

18 00:01:19.940 ⇒ 00:01:22.109 Jeff MacDonald | Dir, Innovation and Technology: Oh, there we are. Hello.

19 00:01:22.110 ⇒ 00:01:23.690 Luke Scorziell: Hey, Jeff, how’s it going?

20 00:01:23.900 ⇒ 00:01:25.490 Jeff MacDonald | Dir, Innovation and Technology: Good, how are y’all doing today?

21 00:01:26.310 ⇒ 00:01:30.729 Luke Scorziell: Good to meet you, thanks for making the time to chat with us and let us pick your brain.

22 00:01:30.980 ⇒ 00:01:34.620 Jeff MacDonald | Dir, Innovation and Technology: Anytime, happy to do so! Happy to answer any questions you may have.

23 00:01:34.880 ⇒ 00:01:37.580 Luke Scorziell: Yeah, well, I don’t know how much…

24 00:01:37.890 ⇒ 00:01:48.710 Luke Scorziell: context John gave you, maybe it was just what was in the email. So I can, yeah, I guess, kind of introduce myself to you along those lines. So I’m,

25 00:01:49.160 ⇒ 00:01:51.770 Luke Scorziell: Yeah, dating one of his…

26 00:01:51.990 ⇒ 00:01:58.410 Luke Scorziell: family, friends, daughters. So we’ve… I’ve met him at church a few times, and we’ve gotten to hang out, and then…

27 00:01:58.830 ⇒ 00:02:01.390 Luke Scorziell: Kind of connected that we had,

28 00:02:01.690 ⇒ 00:02:04.990 Luke Scorziell: The agency stuff in common, so it’s been kind of a fun, like.

29 00:02:05.280 ⇒ 00:02:17.559 Luke Scorziell: yeah, way to just, get to connect and learn. So he’s had a lot more experience than I have, in the agency space, which is good. But then, yeah, then around,

30 00:02:17.910 ⇒ 00:02:22.069 Luke Scorziell: December last year, I started working with Brainforge, and we do…

31 00:02:22.360 ⇒ 00:02:28.870 Luke Scorziell: So prior to that, I’d been running my own marketing agency, and then stepped in with Brainforge, and we do,

32 00:02:29.200 ⇒ 00:02:44.459 Luke Scorziell: like, kind of help companies forge their brain, I guess, so… with, like, AI implementation, data infrastructure, and to make… make it so that all users get access to the information that they need to make decisions, kind of, like, on demand.

33 00:02:44.570 ⇒ 00:02:58.580 Luke Scorziell: So that’s been really fun, and then after a couple months, I was like, oh, it’d be kind of interesting to see how I could help, people on the agency space, and if we could build out custom solutions, because we work for

34 00:02:59.650 ⇒ 00:03:03.800 Luke Scorziell: Kind of like a more of a growth marketing agency, that Pranav led.

35 00:03:03.940 ⇒ 00:03:13.820 Luke Scorziell: led on. So, yeah, so we’ve had a couple of these conversations, and I guess we’re just curious, John mentioned that you were building out a lot of custom AI solutions in-house.

36 00:03:14.190 ⇒ 00:03:17.060 Luke Scorziell: For movers and shakers, so curious to kind of learn how that…

37 00:03:17.260 ⇒ 00:03:21.409 Luke Scorziell: process is going, and then I know, yeah, Pranav has more, like.

38 00:03:21.780 ⇒ 00:03:30.560 Luke Scorziell: just technical questions about, yeah, what that looks like, and what… yeah. So I’m interested in, like, the… what problems are you solving, and how is this helping the business, and then…

39 00:03:30.680 ⇒ 00:03:42.080 Luke Scorziell: I know, yeah, Pranav is, like, super gifted on the actual, using of the tools and whatnot. So that’s… that’s my overview, of… of where we’re coming from.

40 00:03:42.380 ⇒ 00:03:44.060 Jeff MacDonald | Dir, Innovation and Technology: Awesome, I’ll give them a quick…

41 00:03:44.230 ⇒ 00:03:58.710 Jeff MacDonald | Dir, Innovation and Technology: I can do this pretty quickly. So I came to Movers and Shakers 6 months ago as their first technical hire. In the past, they’ve never really hired anyone who’s the, like, implementation expert around tools and technology.

42 00:03:58.710 ⇒ 00:04:13.760 Jeff MacDonald | Dir, Innovation and Technology: So, when I was hired, I was hired as, like, part, yes, they want somebody to, like, help build out net new tools, but they’ve also just, like, never had a person who sat in between, like, the enterprise tools that our holding company has, which is Stagwell.

43 00:04:13.980 ⇒ 00:04:22.449 Jeff MacDonald | Dir, Innovation and Technology: So Stagwell invests lots of money and creates lots of their own tools, and, like, there’s a whole entire part of the company that is, like, buying and building tools.

44 00:04:22.700 ⇒ 00:04:23.700 Jeff MacDonald | Dir, Innovation and Technology: And…

45 00:04:23.770 ⇒ 00:04:46.689 Jeff MacDonald | Dir, Innovation and Technology: Movers and Shakers is a 60-person plus agency that creates social content, and they never have had anyone focused to say, like, oh, why would we want that stag wall offering? So, when I joined the company, I did a number of things. The first thing I did was a listening tour, where I went team by team, figuring out what they’re currently doing, what their pain points are, and what their tool stack looks like.

46 00:04:46.870 ⇒ 00:04:47.350 Luke Scorziell: Yeah.

47 00:04:47.350 ⇒ 00:04:58.479 Jeff MacDonald | Dir, Innovation and Technology: After doing that, I audited their tool stack and went and found other solutions for them to use. For the most part, Movers and Shakers was really using, like, what I consider, like, prosumer level

48 00:04:58.600 ⇒ 00:05:21.060 Jeff MacDonald | Dir, Innovation and Technology: tools, to put it in, like, a videography sense. Like, they were paying for, like, the monthly subscription to Hootsuite, the monthly subscription to Sprinklr. What I said… moved them into is enterprise-level subscriptions to tools. We moved them to Sprout Social for our social media management tool. We used to a… moved to a StagWill tool called IMAI, which is Influencer Marketing AI.

49 00:05:21.060 ⇒ 00:05:30.300 Jeff MacDonald | Dir, Innovation and Technology: for their influencer marketing tool, and we also, in all of those deals, requested API access, which we’ll get to the third pillar.

50 00:05:30.850 ⇒ 00:05:38.989 Jeff MacDonald | Dir, Innovation and Technology: The second pillar I worked on after implementing better tools for them at that part of the stack, the second pillar was AI and tech stack enablement.

51 00:05:38.990 ⇒ 00:05:53.709 Jeff MacDonald | Dir, Innovation and Technology: So started developing an education plan to help them become more educated about the tools that they have. For the most part, even if they have tools, most of the team at Movers and Shakers does everything still manually, or they use unauthorized tools.

52 00:05:53.750 ⇒ 00:06:08.500 Jeff MacDonald | Dir, Innovation and Technology: So, we’ve got strategists that really like perplexity, because perplexity doesn’t care about privacy, right? So it scrapes Reddit and Instagram. We’ve got strategists who are using their personal version of ChatGPT, because it’s got 3 years of their history saved.

53 00:06:08.510 ⇒ 00:06:11.600 Jeff MacDonald | Dir, Innovation and Technology: My role was to get them all onto Gemini.

54 00:06:11.600 ⇒ 00:06:29.560 Jeff MacDonald | Dir, Innovation and Technology: And from that perspective, for LLM, and then for generation of image and video content, and now audio, was to get them all onto Adobe Firefly. And we did that through enablement training. We did that through training, and showing them, this is how you can be using the tool, and this is how everything interoperates.

55 00:06:29.560 ⇒ 00:06:37.280 Jeff MacDonald | Dir, Innovation and Technology: Hence the API MCP portion of why I’m requiring all net new tools to have that access and capability.

56 00:06:38.450 ⇒ 00:06:51.309 Jeff MacDonald | Dir, Innovation and Technology: that’s the current work stream that’s taking up a lot of my time, is getting everybody trained up, and change management is part of that, which is, like, I know you know how to do it manually, but I need you to use the tool.

57 00:06:51.470 ⇒ 00:07:01.589 Jeff MacDonald | Dir, Innovation and Technology: Third pillar, my favorite pillar, thanks to Vibe coding, is the create net new tools, which is, okay.

58 00:07:01.920 ⇒ 00:07:12.500 Jeff MacDonald | Dir, Innovation and Technology: how cool would it be if we could create storyboards for our TikToks using NanoBanana Pro? And it also, when you were done creating the storyboard.

59 00:07:12.500 ⇒ 00:07:23.349 Jeff MacDonald | Dir, Innovation and Technology: it went and checked the storyboard against past performance of other videos like that, because we’ve got the Sprout API kicking you back performance data in real time.

60 00:07:24.420 ⇒ 00:07:31.280 Jeff MacDonald | Dir, Innovation and Technology: So that’s, like, an example of what I’m building. I’m building a suite of strategy and creative tools that help tie in

61 00:07:31.330 ⇒ 00:07:50.939 Jeff MacDonald | Dir, Innovation and Technology: all of these APIs that we have access to, whether it be IMAI, Sprout, we also have tools that we can just only export CSV documents from, which is something we’re gonna fix by requiring API and MCP access from now on. But we’re pulling all that data in to make platforms that make it so it’s a single suite of

62 00:07:50.940 ⇒ 00:07:51.960 Jeff MacDonald | Dir, Innovation and Technology: tools.

63 00:07:52.020 ⇒ 00:07:59.510 Jeff MacDonald | Dir, Innovation and Technology: That access all of the available historical knowledge and new incoming signals from tools that we pay subscriptions for.

64 00:07:59.520 ⇒ 00:08:16.700 Jeff MacDonald | Dir, Innovation and Technology: That process is part going and asking people what they need, so a lot of user interviews, problems statement creation, then going and building unique MVPs, bringing those MVPs back to a single decision maker, normally the department lead.

65 00:08:16.750 ⇒ 00:08:21.610 Jeff MacDonald | Dir, Innovation and Technology: They’re the product owner that tells us when that product is good enough to ship.

66 00:08:21.920 ⇒ 00:08:26.460 Jeff MacDonald | Dir, Innovation and Technology: And normally we ship within one singular team. They provide feedback.

67 00:08:26.570 ⇒ 00:08:44.410 Jeff MacDonald | Dir, Innovation and Technology: We take that feedback in real time, create them as issues, assign a cloud code agent to it, fix the issues, you get the idea. And then eventually, hopefully in two months, we actually launch two platforms, one creative operating system platform, and one strategy platform we’re calling TrendSonar.

68 00:08:45.260 ⇒ 00:08:51.969 Jeff MacDonald | Dir, Innovation and Technology: I run all three pillars simultaneously, both managing the tools that we have access currently.

69 00:08:52.130 ⇒ 00:08:55.590 Jeff MacDonald | Dir, Innovation and Technology: And helping us find new tools that fit in the pay…

70 00:08:55.810 ⇒ 00:09:00.219 Jeff MacDonald | Dir, Innovation and Technology: Subscription category, training, and also creating new tools.

71 00:09:00.460 ⇒ 00:09:02.380 Jeff MacDonald | Dir, Innovation and Technology: That’s my job, that’s what I do.

72 00:09:04.500 ⇒ 00:09:06.420 Pranav Narahari: Great context, oh my gosh.

73 00:09:07.040 ⇒ 00:09:10.770 Luke Scorziell: I know, I’m like, yeah, we’re, we’re in the right place.

74 00:09:10.770 ⇒ 00:09:13.170 Pranav Narahari: Yeah, we’re in the right place.

75 00:09:13.580 ⇒ 00:09:18.540 Pranav Narahari: I have a ton of questions. A lot of you already gave me a lot of good context.

76 00:09:19.320 ⇒ 00:09:24.530 Pranav Narahari: I think the path that you’ve kind of built so far for the last 6 months is great, and it’s like…

77 00:09:25.720 ⇒ 00:09:32.829 Pranav Narahari: there’s a… and it’s crazy that you’re doing this, kind of, it seems like, as a one-man team.

78 00:09:33.210 ⇒ 00:09:35.589 Jeff MacDonald | Dir, Innovation and Technology: And a Quad Pro Max 6…

79 00:09:36.350 ⇒ 00:09:42.029 Pranav Narahari: Oh, yeah, yeah, no, we’re familiar with that here.

80 00:09:42.800 ⇒ 00:09:59.290 Pranav Narahari: How has the process of, like, building these platforms, kind of integrating all these tools into one single thing, and then deploying that into production, is that… is that, like, where you’re, like, seeing a bottleneck right now, or has that been, like, fine with, like, going from the vibe coding to then shipping into production?

81 00:10:00.250 ⇒ 00:10:04.419 Jeff MacDonald | Dir, Innovation and Technology: No, that’s not a bottleneck at all. The bottleneck is change management.

82 00:10:04.960 ⇒ 00:10:07.000 Luke Scorziell: The bottleneck is the people.

83 00:10:07.310 ⇒ 00:10:10.679 Pranav Narahari: Gotcha. Not to be, like, that guy.

84 00:10:10.690 ⇒ 00:10:13.760 Jeff MacDonald | Dir, Innovation and Technology: But, like, there’s so many days…

85 00:10:14.450 ⇒ 00:10:16.699 Jeff MacDonald | Dir, Innovation and Technology: off the record, where I’m just, like.

86 00:10:17.230 ⇒ 00:10:24.349 Jeff MacDonald | Dir, Innovation and Technology: I… how much time should I be spending trying to change the opinions of people versus, like.

87 00:10:24.470 ⇒ 00:10:42.400 Jeff MacDonald | Dir, Innovation and Technology: let’s just hire some AI-native people who get this, who are already using MCP tools, who already understand that the future of this is your Firefly talking to your Asana board in a single integration, allowing you to be able to, like.

88 00:10:42.540 ⇒ 00:10:46.540 Jeff MacDonald | Dir, Innovation and Technology: hold down the control key and say, hey, Claude.

89 00:10:46.640 ⇒ 00:11:03.280 Jeff MacDonald | Dir, Innovation and Technology: go to my Asana board. What images do I need to create? Create 3 ages to generate the first pass at, image mockups for those outstanding tasks. Like, that… I would have broken someone’s brain. They’d be like, I don’t even know what you just said, but.

90 00:11:03.280 ⇒ 00:11:03.720 Pranav Narahari: for, like.

91 00:11:03.720 ⇒ 00:11:16.730 Jeff MacDonald | Dir, Innovation and Technology: People like you on the call, you know what I… you know exactly why that is important, and why that’s the future of work. So, put that aside, my job is to make this agency efficient, but that’s the… that’s the issue, is, like.

92 00:11:17.460 ⇒ 00:11:18.420 Jeff MacDonald | Dir, Innovation and Technology: they…

93 00:11:18.600 ⇒ 00:11:30.890 Jeff MacDonald | Dir, Innovation and Technology: That is going to be the work, is the work is teaching them and convincing them that these workflows and tools will make them more efficient, because right now, they just don’t see it.

94 00:11:31.660 ⇒ 00:11:35.660 Pranav Narahari: Right. Yeah, and how we kind of think about that at Brainforge is, like.

95 00:11:35.780 ⇒ 00:11:40.770 Pranav Narahari: How do we build on top of the existing infrastructure so that it’s…

96 00:11:41.020 ⇒ 00:11:53.290 Pranav Narahari: so easy to adopt. We’re not trying to, in some cases, just, like, bring them to a bunch of different URLs where they have to completely change, like, their workflow. And so, like, a couple questions I have with that is, like.

97 00:11:53.290 ⇒ 00:12:02.509 Pranav Narahari: where have you integrated some of these tools into the existing workflow? Is there, like… are they already using, like, the Gemini chat, and you’re creating, like, MCP integrations there?

98 00:12:02.670 ⇒ 00:12:03.680 Pranav Narahari: Okay.

99 00:12:03.730 ⇒ 00:12:13.430 Jeff MacDonald | Dir, Innovation and Technology: The way we’re integrating it the most in their workflows, since we’re a Google agency, is we’re integrating it inside of GEMS.

100 00:12:13.640 ⇒ 00:12:29.299 Jeff MacDonald | Dir, Innovation and Technology: So we’re creating… we’re… that’s kind of, like, the very basic stuff that has nothing to do with, really, what my end goal is. But where we started is with custom gems. People like the gems. They like going to gemini.google.com, seeing the gems. Now they’re shared gems.

101 00:12:29.640 ⇒ 00:12:40.480 Jeff MacDonald | Dir, Innovation and Technology: Thank God. Took forever for them to launch shared gems. So now we’ve got organization-level gems, still no folders in Gemini.

102 00:12:40.730 ⇒ 00:12:43.460 Jeff MacDonald | Dir, Innovation and Technology: I mean, there’s just, like, a lot of issues that…

103 00:12:43.460 ⇒ 00:13:08.419 Pranav Narahari: They’re really basic. These custom GPTs, same problem, like, you have to use static data unless you want to deploy your own, like, like, knowledge base. I’m guessing these gems are pretty similar as well, and, like, I don’t know how useful having static data is going to be for you guys long-term. You probably want to have custom pulls coming from all of these different applications and tools that you’re talking about. You’re choosing these tools specifically because they have

104 00:13:08.420 ⇒ 00:13:15.069 Pranav Narahari: API access. If you’re having to manually, like, download CSVs and upload them on a daily, weekly basis, it’s like.

105 00:13:15.070 ⇒ 00:13:17.400 Pranav Narahari: That’s going to be a bottleneck down the line, too, that…

106 00:13:17.400 ⇒ 00:13:19.889 Pranav Narahari: you would rather fix right now, I’m assuming.

107 00:13:20.190 ⇒ 00:13:23.799 Jeff MacDonald | Dir, Innovation and Technology: We’ve gotten pretty good at the dynamic data part.

108 00:13:23.800 ⇒ 00:13:24.490 Pranav Narahari: Okay.

109 00:13:24.490 ⇒ 00:13:25.629 Jeff MacDonald | Dir, Innovation and Technology: Our teams…

110 00:13:25.930 ⇒ 00:13:35.639 Jeff MacDonald | Dir, Innovation and Technology: It’s just… again, it’s just, like, nothing is exactly where it needs to be for this, for most teams, but, like, we’ve gotten to a point where…

111 00:13:35.740 ⇒ 00:13:39.120 Jeff MacDonald | Dir, Innovation and Technology: because we’re… we’ve got the API set up.

112 00:13:40.010 ⇒ 00:13:48.549 Jeff MacDonald | Dir, Innovation and Technology: you know, as we start to deploy custom tools, they’re reading from a singular database. And, like, I’ll give you an example, like, we have a copywriting gym.

113 00:13:48.710 ⇒ 00:13:58.490 Jeff MacDonald | Dir, Innovation and Technology: and one of the first steps in the gym usage is it goes and it says, I need the spreadsheet link, and the spreadsheet is a…

114 00:13:59.020 ⇒ 00:14:10.730 Jeff MacDonald | Dir, Innovation and Technology: rundown of the most recent comments we’ve made. Again, this is, like, so stupid that we do it this way, but Gemini doesn’t have correct MCP access unless you use their stupid Vertex AI version of it.

115 00:14:10.730 ⇒ 00:14:12.339 Pranav Narahari: It’s so…

116 00:14:12.340 ⇒ 00:14:23.640 Jeff MacDonald | Dir, Innovation and Technology: So, that’s how we’re doing it. The end goal, ultimately, would be that’s what TrendSonar would be for. They’d pop into TrendSonar, and there, that’s where they could do their, like.

117 00:14:23.980 ⇒ 00:14:42.439 Jeff MacDonald | Dir, Innovation and Technology: helping figure out what comments to respond with, and similarly, in the Creative OS, they would have access to the same data. But building where they do the work, I agree, that’s always been the philosophy I had. That’s, like, when we first started working on these tools, my first MVPs were basically as Chrome extensions, and using, like.

118 00:14:42.440 ⇒ 00:14:47.269 Jeff MacDonald | Dir, Innovation and Technology: the… the Google Workspace, like, sidebar extension capabilities? Yeah.

119 00:14:47.990 ⇒ 00:14:56.720 Jeff MacDonald | Dir, Innovation and Technology: But just, like, the vision of our C-suite is a little different, because, like, a sidebar that is an extension inside of Google Sheets and Google Slides.

120 00:14:57.140 ⇒ 00:15:11.330 Jeff MacDonald | Dir, Innovation and Technology: isn’t very screen… doesn’t screenshot very well, and so they wanted, like, a full-on, like, web app experience that, like, was sexy, and they wanted, like, IP, like, trademarkable terms, like virality score, and things like that.

121 00:15:11.330 ⇒ 00:15:20.549 Jeff MacDonald | Dir, Innovation and Technology: And so I built that. But it’s funny, like, I’ll tell you this, like, a lot of what I do is I make the sexy-looking screenshottable web app.

122 00:15:20.550 ⇒ 00:15:37.850 Jeff MacDonald | Dir, Innovation and Technology: And then hidden in there is the feature request from the user. So, like, we have a… we have a tool, the video audit tool, that audits your videos, and it checks for a virality score, but the thing that it does when you actually scroll down the page is it checks to make sure that you didn’t misspell any words in the captions.

123 00:15:37.940 ⇒ 00:15:45.600 Jeff MacDonald | Dir, Innovation and Technology: And that was, like, the number one user request, because Adobe Premiere doesn’t have, spill check, spell check.

124 00:15:45.810 ⇒ 00:15:55.419 Luke Scorziell: Wow, okay. Yeah. Well, that… yeah, that’s so interesting. And such a brand and ad agency thing to have all the trademarked,

125 00:15:55.610 ⇒ 00:15:59.390 Luke Scorziell: For when I want to have all the words, which I guess I like, but…

126 00:15:59.390 ⇒ 00:16:06.159 Jeff MacDonald | Dir, Innovation and Technology: Because you go… because our, you know, like, at the end of the day, we’re selling to the C-suite at our clients.

127 00:16:06.620 ⇒ 00:16:07.200 Luke Scorziell: Yeah.

128 00:16:07.200 ⇒ 00:16:22.590 Jeff MacDonald | Dir, Innovation and Technology: We at our clients read the McKinsey and the CNBC article, and their CEO is telling them that they need to become more AI-native and more efficient with AI, so we need to bring the sexy names for AI tools.

129 00:16:22.690 ⇒ 00:16:29.990 Jeff MacDonald | Dir, Innovation and Technology: But at the end of the day, I also have to build tools that actually make efficient workflows, and so it’s… that’s the balancing act.

130 00:16:30.310 ⇒ 00:16:30.810 Jeff MacDonald | Dir, Innovation and Technology: Yeah.

131 00:16:30.810 ⇒ 00:16:34.310 Luke Scorziell: Yeah. Well, I’m curious, too, so it sounds like there are a couple different

132 00:16:34.620 ⇒ 00:16:40.950 Luke Scorziell: I guess, like, stakeholders that you’re behooving to, or behooving to, so there’s… it sounds like your C-suite.

133 00:16:41.220 ⇒ 00:16:46.059 Luke Scorziell: And then the client… or, like, I guess, yeah, what is your mandate? Like, where is the…

134 00:16:46.690 ⇒ 00:16:49.510 Jeff MacDonald | Dir, Innovation and Technology: Well, my mandate is internal. I…

135 00:16:49.510 ⇒ 00:17:07.760 Jeff MacDonald | Dir, Innovation and Technology: thankfully, for the most part, don’t meet with clients anymore, which is, like, a great change in my 15-year career so far. So I… my job is just to make sure everyone at Movers and Shakers is happy, but yeah, like, my day-to-day boss is the C-suite to make sure that I’m making a more efficient staff.

136 00:17:07.940 ⇒ 00:17:17.399 Jeff MacDonald | Dir, Innovation and Technology: And, like, increasing speed to insight for strategists, increasing speed to concept for creatives, and we measure that through

137 00:17:17.819 ⇒ 00:17:23.990 Jeff MacDonald | Dir, Innovation and Technology: Are we… and literally, we’re going to get to this point, hopefully, is are we spending less time per scope?

138 00:17:24.730 ⇒ 00:17:28.110 Jeff MacDonald | Dir, Innovation and Technology: Man hours, but charging the same amount of money.

139 00:17:28.270 ⇒ 00:17:29.360 Jeff MacDonald | Dir, Innovation and Technology: Yeah.

140 00:17:30.050 ⇒ 00:17:32.680 Jeff MacDonald | Dir, Innovation and Technology: Because, in actuality.

141 00:17:32.830 ⇒ 00:17:44.380 Jeff MacDonald | Dir, Innovation and Technology: It’s the… it’s the inverse most of the time, is what… using these tools are taking more time because they’re learning something, and our clients are demanding less and less fee.

142 00:17:44.730 ⇒ 00:17:45.360 Luke Scorziell: Yeah.

143 00:17:45.360 ⇒ 00:17:47.939 Jeff MacDonald | Dir, Innovation and Technology: Because there, CNBC told them they should.

144 00:17:48.760 ⇒ 00:17:59.299 Luke Scorziell: No, I get it. I mean, that’s kind of the thing with agencies, and we kind of operate in many ways… I mean, I think Brainforge is fortunate to have started

145 00:17:59.430 ⇒ 00:18:03.629 Luke Scorziell: Within the last few years, so we didn’t fully have the hourly…

146 00:18:03.770 ⇒ 00:18:09.750 Luke Scorziell: like, system baked into how… how we work. We’re able to do more value-based pricing.

147 00:18:09.750 ⇒ 00:18:10.770 Jeff MacDonald | Dir, Innovation and Technology: Yes.

148 00:18:10.770 ⇒ 00:18:11.590 Luke Scorziell: But…

149 00:18:11.700 ⇒ 00:18:26.419 Luke Scorziell: Yeah, I mean, totally, like, agencies that run on margin, people get burned out, like, it’s… it’s as much work as you can crank out in as little time as possible. And I think, like, the interesting problem that I’m thinking about is, like, Pranam and I kind of do… have these conversations is.

150 00:18:26.910 ⇒ 00:18:28.240 Luke Scorziell: You know, how…

151 00:18:28.860 ⇒ 00:18:36.669 Luke Scorziell: like, just from a quality of life standpoint, too, how can AI and AI tooling help the people within agencies

152 00:18:37.230 ⇒ 00:18:42.549 Luke Scorziell: You know, feel better and be able to do their work more efficiently without just these, like.

153 00:18:42.770 ⇒ 00:18:55.890 Luke Scorziell: strenuous, demands that just get, you know, it’s like working with a client that needs their stuff done immediately, and then needs another project, then you have another project and a different client. It’s like, AI could enable you to do that

154 00:18:56.050 ⇒ 00:18:58.590 Luke Scorziell: Like, increase their throughput, you know.

155 00:18:59.070 ⇒ 00:19:03.639 Luke Scorziell: significantly. We had an agency that, like, they 3X’d the number of briefs

156 00:19:03.860 ⇒ 00:19:08.469 Luke Scorziell: That they were able to do through, like, a brief generator that we made them. So it’s like…

157 00:19:08.880 ⇒ 00:19:16.820 Jeff MacDonald | Dir, Innovation and Technology: That’s, like, a great example where it’s, like, the… Big drawback.

158 00:19:19.090 ⇒ 00:19:28.219 Jeff MacDonald | Dir, Innovation and Technology: that I’ve had is I know the successful answer to a lot of the, like, questions about finding efficiencies, but it’s not scalable, which is…

159 00:19:28.700 ⇒ 00:19:30.499 Jeff MacDonald | Dir, Innovation and Technology: I sit with a person.

160 00:19:30.850 ⇒ 00:19:33.159 Jeff MacDonald | Dir, Innovation and Technology: They show me what their job looks like.

161 00:19:33.380 ⇒ 00:19:37.139 Jeff MacDonald | Dir, Innovation and Technology: And then I write them a plan that says, like.

162 00:19:38.170 ⇒ 00:19:44.430 Jeff MacDonald | Dir, Innovation and Technology: Have you… like, a great example of, like, just human…

163 00:19:46.590 ⇒ 00:19:58.970 Jeff MacDonald | Dir, Innovation and Technology: like, desire and need for, like, having something that’s a repeatable process versus breaking that repeatable process that they’ve come to understand by searching for innovation is, like.

164 00:19:59.420 ⇒ 00:20:09.859 Jeff MacDonald | Dir, Innovation and Technology: I’ll sit with someone, and they’ll show me a task that they do, and they’re like… and then I’ll copy and paste from Asana to Google Sheets. And I was like, have you ever Googled if there’s an extension for Asana in Google Sheets? And they were like.

165 00:20:10.180 ⇒ 00:20:11.170 Jeff MacDonald | Dir, Innovation and Technology: No, I’ve…

166 00:20:11.580 ⇒ 00:20:24.700 Jeff MacDonald | Dir, Innovation and Technology: I don’t know why that would be… and I was just like, that’s just, like, the easiest thing, like, just go look at your day. If there’s a task where you go from one software to another, go see if there’s, like, an interconnection. Like, Google, like…

167 00:20:24.700 ⇒ 00:20:40.619 Jeff MacDonald | Dir, Innovation and Technology: for Gemini not having very many connections, the one it does have is for Asana. Like, you click one click, and all of a sudden, you can chat with Asana via Gemini, like it was a tried-and-true MCP connection. And, like, that’s just, like, again, like.

168 00:20:40.620 ⇒ 00:20:41.820 Jeff MacDonald | Dir, Innovation and Technology: people…

169 00:20:41.820 ⇒ 00:20:54.379 Jeff MacDonald | Dir, Innovation and Technology: unless they’re wired that way to search for how technology can make them more efficient, they don’t do it. And so what I do a lot at times is I just, like, sit with people and learn about what their day-to-day life

170 00:20:54.380 ⇒ 00:21:03.040 Jeff MacDonald | Dir, Innovation and Technology: and job looks like, and help find efficiencies. What I… what I always tell people, and this is the problem with, like, our training model, really.

171 00:21:03.040 ⇒ 00:21:03.960 Jeff MacDonald | Dir, Innovation and Technology: is…

172 00:21:04.870 ⇒ 00:21:10.320 Jeff MacDonald | Dir, Innovation and Technology: if you just do, like, an agency all, like, here’s how we’re gonna start using Notebook LM, which we just did.

173 00:21:10.550 ⇒ 00:21:18.729 Jeff MacDonald | Dir, Innovation and Technology: when you do that, it’s so broad, no one sees that’s how it’s applicable to them, because they’re like, I don’t collect a bunch of PDFs every day.

174 00:21:19.120 ⇒ 00:21:34.290 Jeff MacDonald | Dir, Innovation and Technology: I collect a bunch of images, but I don’t collect a bunch of PDFs, and then I don’t need a podcast version of the PDF to get me ready for my media meeting. So what you have to do is you have to go person by person, almost, like, literally person by person, and go.

175 00:21:34.520 ⇒ 00:21:47.540 Jeff MacDonald | Dir, Innovation and Technology: tell me what your day looks like, this is how you can be using Notebook LM, or Gemini, or whatever. And then it clicks for them. They’re like, oh, that one task that I do every day, that’s the thing I need automated with this tool.

176 00:21:47.550 ⇒ 00:22:01.529 Jeff MacDonald | Dir, Innovation and Technology: And so you have to really individualize the training, and then you can… and so what we try to do is we have that. I have weekly office hours for 3 hours, where I do it on an individual basis when people self-select to do it. But I also have, like.

177 00:22:01.560 ⇒ 00:22:10.019 Jeff MacDonald | Dir, Innovation and Technology: team-based trainings that I do with just… and our teams are small enough where it’s almost individual. Like, I just did it recently with our content creators.

178 00:22:10.020 ⇒ 00:22:22.159 Jeff MacDonald | Dir, Innovation and Technology: And I showed them how, inside of Adobe Firefly Boards, is hidden the Topaz Upscaler, where they can use it to upscale images and video. And that, to them, made the 30-minute meeting.

179 00:22:22.450 ⇒ 00:22:34.079 Jeff MacDonald | Dir, Innovation and Technology: Like, worth it. They were like, oh, I knew how to do everything else, Jeff, but I just didn’t know where to go upscale images in Adobe Firefly, and I was like, they should just have an upscale button, it’s stupid.

180 00:22:34.250 ⇒ 00:22:39.009 Luke Scorziell: Yeah, no, it’s… I mean, our whole company is…

181 00:22:39.470 ⇒ 00:22:54.180 Luke Scorziell: On cursor right now, and it’s… it was, like, a big lift for me to get on, because, like, I would GitHub, like, I’m just, like, allergic to that, those kind of words, you know? And then, but then I, like, realized, like, oh, wow, this is, like.

182 00:22:54.680 ⇒ 00:23:08.789 Luke Scorziell: I don’t have to give it prompts, like, super long prompts every time, because it just references knowledge files, and I can pull meeting transcripts that our founder had with a client, to figure out messaging. You know, so it’s just like…

183 00:23:09.260 ⇒ 00:23:19.359 Luke Scorziell: Yeah, but it takes that little kind of moment where you’re like, oh, this is how it could work for me, to then be like, oh, I wonder, like, what else it could do.

184 00:23:19.600 ⇒ 00:23:28.759 Jeff MacDonald | Dir, Innovation and Technology: That’s, like, the biggest drawback, too, that I’ve been having, is, like, everyone wants there to be one tool that can do it all. Like, we want it to be Gemini and Firefly.

185 00:23:29.060 ⇒ 00:23:39.119 Jeff MacDonald | Dir, Innovation and Technology: But that’s just not realistic. Like, unfortunately, every tool does have its best use, and I think Claude is a perfect example where 3…

186 00:23:39.480 ⇒ 00:23:58.120 Jeff MacDonald | Dir, Innovation and Technology: weeks ago, even, maybe a month ago, we wouldn’t have considered Claude for the organization, but Claude co-work is such a great, like, abstraction of what Claude code is doing that it’s hard to ignore. Like, we had a finance ask where we had 17 spreadsheets

187 00:23:58.120 ⇒ 00:24:00.220 Jeff MacDonald | Dir, Innovation and Technology: Each within the spreadsheet, there’s…

188 00:24:00.580 ⇒ 00:24:13.390 Jeff MacDonald | Dir, Innovation and Technology: 15 sheets within the spreadsheet, and each one of them has hundreds of columns of data. One of the sheets within the spreadsheet has staff and total number of hours sold.

189 00:24:13.570 ⇒ 00:24:19.500 Jeff MacDonald | Dir, Innovation and Technology: but several times, because each pod is for a different ask. We needed all of the pods equaled.

190 00:24:20.830 ⇒ 00:24:25.670 Jeff MacDonald | Dir, Innovation and Technology: On that one sheet for total hours sold, and then we needed all of that

191 00:24:26.260 ⇒ 00:24:41.990 Jeff MacDonald | Dir, Innovation and Technology: summed against the 17 sheets of the projects we sold through in 2025, so we could see how many hours we sold per roll, and compare that against the hours we charge, or whatever. I don’t even know what they ended up doing with the data, I don’t care.

192 00:24:42.090 ⇒ 00:24:46.940 Jeff MacDonald | Dir, Innovation and Technology: I threw it against Gemini, I threw it against ChatGPT,

193 00:24:47.280 ⇒ 00:24:49.400 Jeff MacDonald | Dir, Innovation and Technology: And the issue was, is I…

194 00:24:50.130 ⇒ 00:25:00.260 Jeff MacDonald | Dir, Innovation and Technology: Both of those were web-based prompt requests. I downloaded the spreadsheets, threw them in a folder, and pointed Claude Co-Work at the folder.

195 00:25:00.590 ⇒ 00:25:07.710 Jeff MacDonald | Dir, Innovation and Technology: It did it in 50 seconds. No reprompting. It created a spreadsheet as an XLX, SLX file.

196 00:25:08.350 ⇒ 00:25:20.139 Jeff MacDonald | Dir, Innovation and Technology: opened up the spreadsheet, it was perfect. It had the summary sheet, and it even created a second sheet where I could go and audit it, and I could go sum my own values to make sure that it hadn’t hallucinated. Threw it into anti-gravity.

197 00:25:20.210 ⇒ 00:25:35.399 Jeff MacDonald | Dir, Innovation and Technology: Same thing, worked in 50 seconds, first prompt, threw it in codex, pointed it. So the issue then was like, oh, for really, really complex tasks, how am I gonna train people to start using these, what we are for coding.

198 00:25:36.260 ⇒ 00:25:54.720 Jeff MacDonald | Dir, Innovation and Technology: But actually, the power of them is the ability to take on really complex tasks that require more context than is available in the web version of the apps to be able to read 3 folders worth of information, 17 spreadsheets worth of data. So that’s, like, that’s where I get these moments where I’m like.

199 00:25:55.810 ⇒ 00:26:00.459 Jeff MacDonald | Dir, Innovation and Technology: It’s gonna be a challenge. And I don’t know what the answer is, because, like, right now.

200 00:26:01.580 ⇒ 00:26:07.470 Jeff MacDonald | Dir, Innovation and Technology: I… I would… like, I don’t know how I would explain to the average person I work with how to do that.

201 00:26:07.740 ⇒ 00:26:20.550 Jeff MacDonald | Dir, Innovation and Technology: And how cloud code works is the same thing as Cursor, but you just, like, just… you have to ask, don’t code me a website. I’m just using you because you have your agentic capabilities that the web tools don’t have yet.

202 00:26:22.810 ⇒ 00:26:25.119 Pranav Narahari: what a lot of these, I think…

203 00:26:25.230 ⇒ 00:26:44.670 Pranav Narahari: a lot of our clients, what they’ve been asking for that is kind of in the same vein is just having a knowledge base to use as reference of, okay, what does the truth look like? What should we be using as context? And then, also, using, like, the API version instead of the web version, like, gives you more,

204 00:26:44.890 ⇒ 00:26:46.629 Pranav Narahari: granular… or,

205 00:26:46.680 ⇒ 00:26:59.279 Pranav Narahari: It allows you to modulate the number of tokens you’re using as well. We use, like, the Vercel AI SDK, which really lets you change everything. You can modify temperature, tokens, thinking budget.

206 00:26:59.280 ⇒ 00:27:08.549 Pranav Narahari: we can really curate something that is, like, perfect for, like, a use case, whereas, you know, ChatGPT gives you three options. Thinking, Instant, or auto.

207 00:27:08.550 ⇒ 00:27:09.300 Jeff MacDonald | Dir, Innovation and Technology: Oh, yup.

208 00:27:09.300 ⇒ 00:27:20.380 Pranav Narahari: And so it’s like, that’s where I think, once you define, like, what your workflow is, then kind of really refining each one of these parameters, I think that’s what takes you to the next level.

209 00:27:20.460 ⇒ 00:27:37.569 Pranav Narahari: MCP servers is a huge win, which I feel like you’ve already kind of figured out. I have a few more questions there, which is, like, how has that been going? Have you guys been having, like, data issues there? Maybe we can talk about that in another call if, like, that’s interesting.

210 00:27:37.750 ⇒ 00:27:41.469 Pranav Narahari: But then, yeah, knowledge base is another one, like, how has…

211 00:27:41.580 ⇒ 00:27:48.170 Pranav Narahari: Have you guys thought about creating knowledge bases, integrating that with tools, basically creating, like, a RAG application?

212 00:27:48.590 ⇒ 00:27:54.240 Jeff MacDonald | Dir, Innovation and Technology: Yes, we’ve done that a couple of times. We do it at an individual application.

213 00:27:54.580 ⇒ 00:27:58.690 Jeff MacDonald | Dir, Innovation and Technology: level now. Yeah. So our tool, TrendSonar, right now.

214 00:27:58.920 ⇒ 00:28:05.739 Jeff MacDonald | Dir, Innovation and Technology: Every single time you have it do a pull of, like, one of the features of Transonar is a feature called Neighborhood Watch.

215 00:28:05.860 ⇒ 00:28:24.320 Jeff MacDonald | Dir, Innovation and Technology: And what Neighborhood Watch does is you create a pod of creators on TikTok that you want to keep daily listeners on. And so it uses an API, and every day, it goes out and it hits those… that API, and it sees any net new content those creators has made. If they’ve created net new content.

216 00:28:24.320 ⇒ 00:28:47.250 Jeff MacDonald | Dir, Innovation and Technology: our… the API provides the transcript, so we don’t have to do any funny things there. Sends the transcript over, we throw the transcript into Firestore, same thing with the comment section. We scrape the comments section, and we throw that into a Firestore, and that gets re-indexed every single time net new content gets added, so that way then the search function that’s built inside of Neighborhood Watch, which is also what is…

217 00:28:47.250 ⇒ 00:28:48.799 Jeff MacDonald | Dir, Innovation and Technology: Which is… well, they’re separate.

218 00:28:48.800 ⇒ 00:28:57.999 Jeff MacDonald | Dir, Innovation and Technology: It creates the summary of what’s net new, and then now the search function, when you ask a question, or search function, chat function, now has the net new knowledge.

219 00:28:58.250 ⇒ 00:28:58.920 Pranav Narahari: Right.

220 00:28:58.920 ⇒ 00:28:59.670 Jeff MacDonald | Dir, Innovation and Technology: Vision!

221 00:28:59.880 ⇒ 00:29:00.550 Pranav Narahari: Yeah.

222 00:29:00.770 ⇒ 00:29:06.780 Jeff MacDonald | Dir, Innovation and Technology: We have a vision, which is to not be application-specific.

223 00:29:07.470 ⇒ 00:29:11.309 Jeff MacDonald | Dir, Innovation and Technology: And this was actually what I originally proposed when I took the job.

224 00:29:11.870 ⇒ 00:29:16.750 Jeff MacDonald | Dir, Innovation and Technology: We’re gonna create two data layers. One is called Currents.

225 00:29:16.990 ⇒ 00:29:29.559 Jeff MacDonald | Dir, Innovation and Technology: And the other is called Signals. Currents is under your feet, signals is above you. Currents is the data that is our own data that we generate by posting content on social.

226 00:29:29.670 ⇒ 00:29:45.040 Jeff MacDonald | Dir, Innovation and Technology: So, it is the influencer campaigns we’re running. It is the owned asset creation and the performance of that asset on social platforms. It’s the social chatter… well, no, that one doesn’t count, but it’s… there’s… so there’s… and then it’s also… oh, I know it’s under currents. It’s…

227 00:29:45.040 ⇒ 00:29:50.990 Jeff MacDonald | Dir, Innovation and Technology: our Google Drive data, basically. It’s like, any of, like, the briefs, the client-provided documents.

228 00:29:50.990 ⇒ 00:29:57.169 Jeff MacDonald | Dir, Innovation and Technology: That’s under current, so, like, that’s our owned data. Signals is what we receive mostly from APIs.

229 00:29:57.170 ⇒ 00:30:04.610 Jeff MacDonald | Dir, Innovation and Technology: Which is things like Neighborhood Watch, it’s the social listening data, it’s Google Trends data.

230 00:30:04.730 ⇒ 00:30:13.610 Jeff MacDonald | Dir, Innovation and Technology: And whatever else we can borrow and steal. And then make it so that now we’ve got signals, we’ve got currents.

231 00:30:13.760 ⇒ 00:30:17.729 Jeff MacDonald | Dir, Innovation and Technology: what do you want to build? And we can just say, like, oh, like.

232 00:30:17.800 ⇒ 00:30:33.170 Jeff MacDonald | Dir, Innovation and Technology: Staples wants us to spin up a really quick dashboard for an influencer that just went viral for Staples? Great. This is a real-world example. I already have everything already set up in TrendSonar, or TrendSonar, which is just built upon signals and currents.

233 00:30:33.170 ⇒ 00:30:40.430 Jeff MacDonald | Dir, Innovation and Technology: So I know… so I just go to Cloud Code, using Signals and Currents API, which you have documented so well.

234 00:30:40.490 ⇒ 00:30:55.579 Jeff MacDonald | Dir, Innovation and Technology: Build the Staples dashboard! So that’s the vision, is that signals and currents will be the data sources that all… those are, like, our owned APIs, which are just amalgamations of the MCPs and APIs we have, and data layers, which will be the RAG databases we generated.

235 00:30:55.780 ⇒ 00:30:57.430 Jeff MacDonald | Dir, Innovation and Technology: And we’ll just build upon that.

236 00:30:58.430 ⇒ 00:31:00.080 Pranav Narahari: Gotcha. And so…

237 00:31:00.350 ⇒ 00:31:09.929 Pranav Narahari: it looks like you’re… I mean, I heard you mention transcripts specifically. Are you guys using any other part of, like, the creative, like the… the images, or videos, or anything like that?

238 00:31:10.210 ⇒ 00:31:20.260 Jeff MacDonald | Dir, Innovation and Technology: No, we haven’t gotten there. We’re gonna be doing that on the creative tool. The video audit tool is using Gemini, and so it creates the best

239 00:31:20.340 ⇒ 00:31:31.700 Jeff MacDonald | Dir, Innovation and Technology: visual overview of what’s in the content, but in terms of the process of actually scraping videos off of TikTok, and then maintaining the video assets on our side.

240 00:31:31.700 ⇒ 00:31:33.329 Pranav Narahari: We’re getting embeddings based on that.

241 00:31:33.330 ⇒ 00:31:42.929 Jeff MacDonald | Dir, Innovation and Technology: Yeah, we haven’t done that. It’s just… I know how to do it, I know what we would do to do it. I don’t… I haven’t seen, like, what the…

242 00:31:43.930 ⇒ 00:31:57.719 Jeff MacDonald | Dir, Innovation and Technology: long-term benefit would be, but where it has come up is when we do create neighborhoods for Neighborhood Watch, our big… my biggest caveat is to make sure that the creators in Neighborhood Watch talk in their videos.

243 00:31:57.720 ⇒ 00:32:03.990 Jeff MacDonald | Dir, Innovation and Technology: And as you can imagine, there’s no transcript if it’s just them showing their favorite ramen noodle shops in San Francisco.

244 00:32:03.990 ⇒ 00:32:04.480 Pranav Narahari: Right.

245 00:32:04.480 ⇒ 00:32:06.409 Jeff MacDonald | Dir, Innovation and Technology: You need to say it!

246 00:32:08.330 ⇒ 00:32:20.879 Luke Scorziell: Well, I know we’re a little past what we’d booked for. Maybe it’s Friday. Yeah, I mean, we could keep going, but… Yeah, I guess I’m curious,

247 00:32:22.110 ⇒ 00:32:24.140 Luke Scorziell: Well, yeah, I guess.

248 00:32:24.420 ⇒ 00:32:30.829 Luke Scorziell: Two things, like, did… did they give you a budget when… with working out those tools, or are you just kind of, like.

249 00:32:31.010 ⇒ 00:32:33.870 Luke Scorziell: Scrape, like, what does that look like on your end?

250 00:32:35.250 ⇒ 00:32:36.880 Jeff MacDonald | Dir, Innovation and Technology: Did they give me a budget?

251 00:32:37.250 ⇒ 00:32:39.980 Luke Scorziell: Yeah, or I guess, like, what kind of… what are you working with?

252 00:32:41.310 ⇒ 00:32:49.930 Jeff MacDonald | Dir, Innovation and Technology: No, they didn’t give me a budget, they just said start. And I told them I’d let them know how much it started to cost as I went.

253 00:32:50.080 ⇒ 00:32:57.269 Jeff MacDonald | Dir, Innovation and Technology: the… The biggest budget item was I started asking for API access to every tool.

254 00:32:58.520 ⇒ 00:33:08.380 Jeff MacDonald | Dir, Innovation and Technology: And so that was… so they kind of, like, started figuring that out. By the start of 2026, I gave them a number and just said, like, buffer me for the year for this amount.

255 00:33:09.080 ⇒ 00:33:20.460 Jeff MacDonald | Dir, Innovation and Technology: And it was inclusive of API access, Google Cloud, costs… So, GCP costs, and,

256 00:33:21.250 ⇒ 00:33:29.030 Jeff MacDonald | Dir, Innovation and Technology: my Claudeback subscription now. Which I don’t know if they knew that was coming, but they were happy to hear that

257 00:33:29.740 ⇒ 00:33:32.620 Jeff MacDonald | Dir, Innovation and Technology: It allowed me to never stop coding.

258 00:33:32.800 ⇒ 00:33:41.749 Jeff MacDonald | Dir, Innovation and Technology: Yeah, I love that. Because I was like, yeah, I hit my limit again, and they were like, oh, that’s not affordable. Yeah, or that’s not useful. You go get that Mac subscription.

259 00:33:41.750 ⇒ 00:33:42.680 Luke Scorziell: Yay.

260 00:33:42.680 ⇒ 00:33:53.629 Pranav Narahari: I think now they even have, like, a plus when you’re on top of Max, like, you can add, like, 50%, like, $50 per month or something like that, and they’ll literally never throttle you. It’s insane. Yeah.

261 00:33:53.630 ⇒ 00:34:12.929 Jeff MacDonald | Dir, Innovation and Technology: I just switched from the Pro, which was the $20,tothe$200 max with the 20X. I’m using this tool called Open Usage that allows you to keep track of all of your model’s limits. I’ve never gotten less than 80% in my

262 00:34:13.090 ⇒ 00:34:28.619 Jeff MacDonald | Dir, Innovation and Technology: 4-hour, 5-hour window, which is insane. But, so I’m fine with my… I might even try, although I’m tempted never to just bring it up, but I might even try the 5X, $100 a month, because I might be okay with just 5X and not need 20X.

263 00:34:28.659 ⇒ 00:34:29.409 Pranav Narahari: Yeah.

264 00:34:29.510 ⇒ 00:34:30.350 Jeff MacDonald | Dir, Innovation and Technology: Yeah.

265 00:34:31.030 ⇒ 00:34:33.730 Pranav Narahari: You never know, maybe as things scale up.

266 00:34:33.739 ⇒ 00:34:36.629 Jeff MacDonald | Dir, Innovation and Technology: Maybe if things scale up, that would be awesome.

267 00:34:36.630 ⇒ 00:34:37.320 Pranav Narahari: Yeah.

268 00:34:38.159 ⇒ 00:34:42.599 Pranav Narahari: I guess… One other question I just have is, like, you’ve…

269 00:34:42.900 ⇒ 00:34:47.939 Pranav Narahari: Talk to, like, a lot of people in your office hours to understand the individual workflows of everybody on your team.

270 00:34:48.150 ⇒ 00:34:49.750 Pranav Narahari: Where do you feel like…

271 00:34:50.040 ⇒ 00:35:04.140 Pranav Narahari: some… and this is a common problem that a lot of people have when they’re building AI solutions, is that they go from 0 to, like, 70%, but that 70% to 100% is where, like, they kind of get stuck, things start breaking, and then it’s just, like, they can’t…

272 00:35:04.250 ⇒ 00:35:23.649 Pranav Narahari: they can’t get over that hump. Is that something that you’re facing with, like, a few of the automations that you’ve built, or the agents that you’ve built? Like, where do you see, like, small rooms of improvement? Maybe things that are just, like, in your backlog, they’re just like, I get to it eventually, like, there’s a ton of stuff on your plate, it sounds like. What is, like, something that comes to mind when I mention this?

273 00:35:25.530 ⇒ 00:35:36.639 Jeff MacDonald | Dir, Innovation and Technology: The biggest… 70 to 100… like, I would say the 0 to 70… Example would be, like.

274 00:35:37.750 ⇒ 00:35:52.070 Jeff MacDonald | Dir, Innovation and Technology: to… yesterday, I showed somebody that there’s Reddit answers. That was 0 to 70 for that person. They were like, oh my gosh, I didn’t even know that I could go to Reddit answers, and I could chat with Reddit.

275 00:35:52.070 ⇒ 00:35:55.809 Luke Scorziell: And, like, ask for, like, what’s big in travel today?

276 00:35:55.810 ⇒ 00:36:03.900 Jeff MacDonald | Dir, Innovation and Technology: And they were like, you know how much time this is gonna save me? And I was like, yeah, okay, there’s one down. The 70 to 100 is, like.

277 00:36:04.310 ⇒ 00:36:06.200 Jeff MacDonald | Dir, Innovation and Technology: Operationalizing that.

278 00:36:06.600 ⇒ 00:36:07.210 Pranav Narahari: Okay.

279 00:36:07.380 ⇒ 00:36:13.069 Jeff MacDonald | Dir, Innovation and Technology: like, how do I now make it so that 65 employees at Movers and Shakers

280 00:36:13.970 ⇒ 00:36:25.349 Jeff MacDonald | Dir, Innovation and Technology: have a prompt library, like, that’s… I’m a bad example. Prompt library that they can go into Reddit answers and use daily to skim insights.

281 00:36:25.990 ⇒ 00:36:26.670 Pranav Narahari: Yeah.

282 00:36:26.800 ⇒ 00:36:31.979 Jeff MacDonald | Dir, Innovation and Technology: So that way it is a repeatable process that we can then start to measure

283 00:36:32.170 ⇒ 00:36:34.580 Jeff MacDonald | Dir, Innovation and Technology: How it is impacting their workload.

284 00:36:34.830 ⇒ 00:36:38.140 Jeff MacDonald | Dir, Innovation and Technology: That’s the… job I have.

285 00:36:38.470 ⇒ 00:36:57.529 Jeff MacDonald | Dir, Innovation and Technology: That’s what they want… that’s what they technically pay. They don’t pay me to go around and teach people how to use Adobe Firefly and teach… well, they do, and… but, like, that’s not, like, the end goal is, like, finding these, like, little efficient flows. They want me to, like, operationalize and measure and sell as net new product. And that’s the struggle.

286 00:36:58.970 ⇒ 00:37:13.029 Pranav Narahari: That’s interesting, because a lot of what we do here at Brainforge, too, is, like, that product design as well. Kind of figuring out, like, okay, going from 70 to 100, like, how do we get wide adoption? How can we get it so that it’s in the hands of everybody to use all the time?

287 00:37:13.030 ⇒ 00:37:20.249 Pranav Narahari: So, like, one thing that Luke and I have talked about, and what I’ve worked on with clients, like, building Slack bots, building Teams bots.

288 00:37:20.250 ⇒ 00:37:27.549 Pranav Narahari: whatever you guys are using, honestly, we can create bots integrated to that, like, where the work is actually happening.

289 00:37:27.640 ⇒ 00:37:42.780 Pranav Narahari: having them send on, like, schedule, things of that nature, sometimes that can help to get to the… to the 100%, like, if you can just, within Slack, do, like, a slash my bot name, get it, and then ask it a specific question, and then that’s.

290 00:37:42.780 ⇒ 00:37:54.799 Luke Scorziell: Yeah, we’ve been sending, like, daily Reddit reports on those prompts that you were thinking about? That’s kind of interesting. Like, if there was an insights channel on it every morning, it just chatted like a…

291 00:37:54.990 ⇒ 00:38:00.410 Luke Scorziell: Here’s what’s trending on Reddit today. I don’t know if that’s kind of what you were thinking about, too, for now.

292 00:38:00.410 ⇒ 00:38:01.750 Pranav Narahari: Yeah.

293 00:38:02.780 ⇒ 00:38:22.280 Jeff MacDonald | Dir, Innovation and Technology: Yeah, that’s, like, a great example. We’ve been trying to get more into, like, automating some of our Slack notifications and workflows. Like, I use a Slack bot for project management. I use Linear, and when anybody gives a product request, I don’t… I just go, at Linear, read the product request.

294 00:38:23.960 ⇒ 00:38:30.890 Luke Scorziell: I was like, what the heck is this linear thing? And now I’m, like, also at linear, create a task for me.

295 00:38:30.890 ⇒ 00:38:31.970 Jeff MacDonald | Dir, Innovation and Technology: Yeah, yeah.

296 00:38:32.240 ⇒ 00:38:32.760 Luke Scorziell: So…

297 00:38:32.760 ⇒ 00:38:34.920 Jeff MacDonald | Dir, Innovation and Technology: But that’s, like, a good example of, like.

298 00:38:35.350 ⇒ 00:38:38.390 Jeff MacDonald | Dir, Innovation and Technology: Yeah, that’s the kind of stuff we’re looking for.

299 00:38:38.520 ⇒ 00:38:46.110 Jeff MacDonald | Dir, Innovation and Technology: I think the big thing for us is Two is… we…

300 00:38:46.260 ⇒ 00:39:01.130 Jeff MacDonald | Dir, Innovation and Technology: need to find, like, efficiencies and automations and workflows and stuff, but we also need to make it so that it feels like the humans drove the insights still, and, like, drove the creative selection. So a lot of what I’ve been trying to build is tools that, like.

301 00:39:01.680 ⇒ 00:39:14.829 Jeff MacDonald | Dir, Innovation and Technology: offer up choices. And so it’s like, if that Reddit tool pulled in the top 15 Reddit topics around travel, and then it allowed the human to curate and add their own unique little

302 00:39:14.830 ⇒ 00:39:23.509 Jeff MacDonald | Dir, Innovation and Technology: tool and topic, and be like, oh, yeah, these are 15. These 4 are actionable, based on the clients that we have, and then it allowed them to, like.

303 00:39:23.660 ⇒ 00:39:32.459 Jeff MacDonald | Dir, Innovation and Technology: supplement and say, like, Jeff’s take, Jeff’s take, underneath each of the AI-driven insights from the Reddit.

304 00:39:32.830 ⇒ 00:39:33.450 Luke Scorziell: Hmm.

305 00:39:33.450 ⇒ 00:39:35.840 Jeff MacDonald | Dir, Innovation and Technology: But I don’t know, yeah, that’d be really cool.

306 00:39:36.420 ⇒ 00:39:44.489 Pranav Narahari: Yeah, I think with the… like, I mentioned the versatile AI SDK that we’ve worked on with, like, a ton of different clients is, like.

307 00:39:44.750 ⇒ 00:39:48.879 Pranav Narahari: We can use those parameters and then map them to, like.

308 00:39:49.040 ⇒ 00:40:05.720 Pranav Narahari: individual changes that they’ll have on the prompt, and that can be, like, something that, let’s say we work together on a project, how does that affect the output? And then we can turn those into certain buckets. Like, let’s say for, like, the nanobanana tool that you’re talking about, we want very low temperature on something like that, because we don’t want it to be acting too freely.

309 00:40:05.730 ⇒ 00:40:21.850 Pranav Narahari: However, for… maybe for asking for, like, a very… you gave, like, the Excel example, where it has to, like, look at all of these different documents, and then really use, like, deep thinking to understand, like, and do maybe some calculations to get a final output.

310 00:40:21.940 ⇒ 00:40:27.989 Pranav Narahari: That requires a lot of thinking, and requires a certain level of creativity, especially if…

311 00:40:28.100 ⇒ 00:40:41.510 Pranav Narahari: the questions being asked can be very dynamic, and so then, that’s an example where, yeah, you probably want to increase thinking budget, and you also want to have the temperature be a little bit higher. So things of that nature is, like.

312 00:40:41.670 ⇒ 00:40:45.379 Pranav Narahari: I feel like gets you to that 100%, where you’re seeing, like, the peak…

313 00:40:46.050 ⇒ 00:40:56.300 Pranav Narahari: you’re getting the most out of this AI. And also not getting a bunch of garbage along the way, too. That’s a big problem with a lot of

314 00:40:56.910 ⇒ 00:41:01.020 Pranav Narahari: a lot of, like, solutions that I just see, like, out there,

315 00:41:01.510 ⇒ 00:41:13.119 Pranav Narahari: high promises, but they’re just not built properly in a way where, like, the outcome is actually what you’re looking for. Like, 70% of the time, sure, you get some good output. 30% of the time, you’re like, okay, gotta go back to the manual workflow. This is not doing it for me.

316 00:41:13.750 ⇒ 00:41:27.330 Jeff MacDonald | Dir, Innovation and Technology: Yeah, exactly. That’s, like, the biggest hurdle that you just described, is, like, if the first time they use it, and it didn’t do it faster than the way they do it manually, they never come back.

317 00:41:27.710 ⇒ 00:41:39.259 Pranav Narahari: Makes sense. I operate the same way in my own life, you know? Like, if someone’s trying to make me do something, I try it once, I’ll give it a fair shot, usually, and then if I… if it doesn’t work for me, I’m just not gonna… just not gonna adopt it.

318 00:41:39.500 ⇒ 00:41:43.569 Jeff MacDonald | Dir, Innovation and Technology: That’s the hardest thing around what I do around…

319 00:41:43.900 ⇒ 00:41:59.460 Jeff MacDonald | Dir, Innovation and Technology: like, if my job was helping a bunch of people who make banner ads for a living, I’d be shooting fish in a barrel, because there’s hundreds of tools that can help speed that up. But my job is to help a bunch of really wired-in social strategists and content creators

320 00:41:59.460 ⇒ 00:42:15.790 Jeff MacDonald | Dir, Innovation and Technology: who kind of already know the trend, because they’re chronically online. Right. And they’re just looking for data that helps support what they already know. Yeah. But then they come to me and say, well, how come the tool didn’t show me that this is trending right now? I know it’s trending, why doesn’t the tool? And it’s like, because it’s…

321 00:42:15.810 ⇒ 00:42:20.679 Jeff MacDonald | Dir, Innovation and Technology: there’s no API for what are the trends?

322 00:42:20.680 ⇒ 00:42:21.660 Pranav Narahari: Right, right.

323 00:42:21.660 ⇒ 00:42:24.250 Jeff MacDonald | Dir, Innovation and Technology: That’s not an endpoint. Yeah.

324 00:42:24.660 ⇒ 00:42:29.809 Pranav Narahari: It’s not as simple as an endpoint, but sometimes when you can create a knowledge base, that’s when it starts looking like.

325 00:42:30.000 ⇒ 00:42:34.649 Pranav Narahari: wow, like, it actually is operating more and more closely to what I’m thinking in my head.

326 00:42:34.650 ⇒ 00:42:35.220 Jeff MacDonald | Dir, Innovation and Technology: Yeah, exactly.

327 00:42:35.220 ⇒ 00:42:49.639 Pranav Narahari: It’s not as simple as just, like you said, like a MCP server that’s enabled, or just, like, one API, two APIs that are integrated. Like, you need to get a huge sum of data from, like, all these different sources for it to really drive that insight that you’re looking for.

328 00:42:50.060 ⇒ 00:43:02.380 Jeff MacDonald | Dir, Innovation and Technology: like, one of the things I did when I… last time I was in New York, and I came back from the meeting, was I was listening to somebody on MasterClass that does, like, trend and insight analysis, and they said, like.

329 00:43:02.910 ⇒ 00:43:09.950 Jeff MacDonald | Dir, Innovation and Technology: The way our team operates is we make a binary yes-no bet on the future.

330 00:43:10.280 ⇒ 00:43:18.869 Jeff MacDonald | Dir, Innovation and Technology: And we say, you know, wireless charging will happen

331 00:43:19.910 ⇒ 00:43:36.759 Jeff MacDonald | Dir, Innovation and Technology: to be… will become the next… or wireless charging for EV vehicles will also become the next place that people, like, watch movies or something. Yes or no. And then when they… and then they’ll make that decision and say, yes, it will happen, and these are the win criteria that it takes for it to win.

332 00:43:37.340 ⇒ 00:43:40.940 Jeff MacDonald | Dir, Innovation and Technology: And then what they do is they then build a listening map.

333 00:43:42.180 ⇒ 00:43:44.029 Jeff MacDonald | Dir, Innovation and Technology: So that they can measure

334 00:43:44.780 ⇒ 00:44:01.940 Jeff MacDonald | Dir, Innovation and Technology: as time goes on, what percentage correct they’re becoming. It’s like, oh, okay, so wireless charging is rolling out. That’s win criteria 1. I’m now 25% of the way more in the right direction of correct. Or the opposite will happen. It’s like, the indicators will say, I’m not even close.

335 00:44:02.160 ⇒ 00:44:05.859 Jeff MacDonald | Dir, Innovation and Technology: And… They use this as a way to build a map.

336 00:44:06.180 ⇒ 00:44:13.499 Jeff MacDonald | Dir, Innovation and Technology: of trend prediction. They’ll say, like, okay, like, what we notice is that these following

337 00:44:13.920 ⇒ 00:44:24.079 Jeff MacDonald | Dir, Innovation and Technology: things in society, in policy, and buying behavior, etc, have to change in order for this to become true. And so what I built

338 00:44:24.080 ⇒ 00:44:43.180 Jeff MacDonald | Dir, Innovation and Technology: in TrendSonar that never got launched, because I can’t… people don’t understand what I’m trying to explain right now to you, and so maybe you understand, is I wanted to do the same thing with trend analysis. I wanted my social strategists, who are super aware of what trends are happening in travel, to write out a prediction. I believe that

339 00:44:43.300 ⇒ 00:44:52.919 Jeff MacDonald | Dir, Innovation and Technology: this year, this summer, we’ll see much more Gen Z international travel than before, because people are having an identity crisis of their country.

340 00:44:53.210 ⇒ 00:45:10.279 Jeff MacDonald | Dir, Innovation and Technology: Okay, what is the win… then they… that’s all they have to write. AI will write the win parameters. So what needs to happen? We need to see a rise in Gen Z Google search for destinations outside of the U.S. Okay, that’s a measurable metric. We have Google search data that can prove that.

341 00:45:10.490 ⇒ 00:45:24.470 Jeff MacDonald | Dir, Innovation and Technology: Okay, we need to see more of the content creators that Delta cares about creating international travel itineraries and posting them on TikTok. Great, we have an API that can measure that. And then make… it’ll work back.

342 00:45:24.800 ⇒ 00:45:36.969 Jeff MacDonald | Dir, Innovation and Technology: it’ll be able to measure how successful that specific strategist is at predicting trends, but it also uses that data for it to get smarter at predicting trends. Because it goes…

343 00:45:37.130 ⇒ 00:45:43.219 Jeff MacDonald | Dir, Innovation and Technology: Oh, this is how I should be using my tools to predict trends. Thank you, so-and-so.

344 00:45:43.340 ⇒ 00:45:44.889 Jeff MacDonald | Dir, Innovation and Technology: I will…

345 00:45:45.340 ⇒ 00:45:59.029 Jeff MacDonald | Dir, Innovation and Technology: take the over-under on this trend, then, based on what you just taught me. Right. And that’s the vision, is that the trend maps that are created by a strategist inform the automation of creating trend sonar.

346 00:46:00.240 ⇒ 00:46:01.740 Jeff MacDonald | Dir, Innovation and Technology: You get it.

347 00:46:01.740 ⇒ 00:46:13.040 Pranav Narahari: Absolutely. It’s basically… and that’s how it learns and improves. It’s not… it’s not… you’re not training a model, per se, but it’s… it’s… you’re still training the… the application itself.

348 00:46:14.680 ⇒ 00:46:25.140 Pranav Narahari: Yeah, these are, like, all, like, pretty big, like, projects, you know? And it’s just crazy that, like, Jeff, you’re, like, the only one, like, that sounds like is, like, forefronting this.

349 00:46:25.410 ⇒ 00:46:26.020 Jeff MacDonald | Dir, Innovation and Technology: Yeah.

350 00:46:26.300 ⇒ 00:46:28.229 Pranav Narahari: That’s why I was kind of asking before, like.

351 00:46:28.350 ⇒ 00:46:36.810 Pranav Narahari: Is the bottleneck really only just getting people to adopt the tool, or is it, like, do you have these ideas in your head where it’s just, like, they’re just kind of in your head, and you can’t, like.

352 00:46:37.550 ⇒ 00:46:46.990 Pranav Narahari: put it on paper. Is it also, like, some of this product stuff, where it’s, like, there’s a lot of these people that are just, like, deep in the weeds in what they… what they’re doing, and…

353 00:46:47.030 ⇒ 00:47:03.410 Pranav Narahari: kind of being able to, like, define the exact product that would be most useful for them, and, like, also not having that issue of, like, they try it once, it doesn’t work perfectly, and then they’re just, like, not willing to adopt it in the future. Is that another thing that you feel like could be helpful as, like, a partnership?

354 00:47:03.670 ⇒ 00:47:12.320 Jeff MacDonald | Dir, Innovation and Technology: I just… yeah, I mean, I think it’s more the… it’s closer to the… it just doesn’t parody what they do manually any better yet.

355 00:47:12.670 ⇒ 00:47:13.280 Pranav Narahari: Yeah.

356 00:47:13.540 ⇒ 00:47:19.169 Jeff MacDonald | Dir, Innovation and Technology: So there… and that’s just because I don’t have enough use cases to make it better. Like, I literally have one…

357 00:47:19.560 ⇒ 00:47:22.519 Pranav Narahari: person I’m really testing TrinSonar out with.

358 00:47:22.670 ⇒ 00:47:24.890 Pranav Narahari: Which is our strategy tool.

359 00:47:24.990 ⇒ 00:47:37.929 Jeff MacDonald | Dir, Innovation and Technology: And she… and her, I just taught her how to use Reddit Answers. So how am I gonna compete? Reddit Answers… Reddit’s not an API, so, like, that I can create into my tool. So, like, I’m never gonna beat Reddit Answers.

360 00:47:38.140 ⇒ 00:47:38.850 Pranav Narahari: Yeah.

361 00:47:38.850 ⇒ 00:47:46.830 Jeff MacDonald | Dir, Innovation and Technology: So now, that’s what I’m competing against, or I’m never gonna beat the search button inside of TikTok on her phone.

362 00:47:47.270 ⇒ 00:47:48.499 Pranav Narahari: Right, right, right.

363 00:47:48.500 ⇒ 00:47:56.959 Jeff MacDonald | Dir, Innovation and Technology: So that’s… that’s what I compete the most against, is, like, they get the vision, and they understand it could be more useful, but

364 00:47:57.270 ⇒ 00:48:06.819 Jeff MacDonald | Dir, Innovation and Technology: when they’re logging in to Slack, and they get a notification that says, clients are freaking out, all of a sudden, college dorm buyers are talking about

365 00:48:08.150 ⇒ 00:48:23.150 Jeff MacDonald | Dir, Innovation and Technology: printers are in. How do we make a Staples post about printers? They’re not gonna go, oh, what if I went and created a neighborhood watch inside of TrendSonar and watched all content creators around dorm content? Like, they’re just like.

366 00:48:24.120 ⇒ 00:48:33.309 Jeff MacDonald | Dir, Innovation and Technology: I’m gonna Google search, why is printers trending? I’m going to go to TikTok and type in printers. I’m gonna start screenshotting on my phone and dragging into the Google Slides.

367 00:48:33.310 ⇒ 00:48:36.519 Pranav Narahari: Yeah. And they’re probably super efficient at that too, right?

368 00:48:36.520 ⇒ 00:48:39.720 Jeff MacDonald | Dir, Innovation and Technology: Just because that’s how they’ve operated for years, is without tools.

369 00:48:39.720 ⇒ 00:48:41.260 Pranav Narahari: Yeah. Yep.

370 00:48:41.680 ⇒ 00:48:50.460 Luke Scorziell: Yeah, well, I mean, I don’t know if it’d be interesting, to you, Jeff, to, like, to have another conversation, too. I know, like, a lot of what we’ve done

371 00:48:50.810 ⇒ 00:49:10.380 Luke Scorziell: we just finished with another client, we just did, like, discovery to kind of learn more. I mean, also, like, I feel like we’ve learned a lot, so also if the relationship ends here, that’s okay, too. But, yeah, I mean, if it would be interesting to you to, like, have another call or, like, kind of see

372 00:49:10.530 ⇒ 00:49:14.419 Luke Scorziell: more of what we do, I’d be happy to schedule one.

373 00:49:14.590 ⇒ 00:49:25.769 Luke Scorziell: I know… yeah, like, the thing… we’re kind of, like, coming in as consultants, and then also just the more we learn about a process… processes within an organization.

374 00:49:25.850 ⇒ 00:49:29.109 Luke Scorziell: And the people within it, too, then, like, the more we can build.

375 00:49:29.150 ⇒ 00:49:49.100 Luke Scorziell: with you, so it sounds like, like, I’m, like, listening to you guys talk, I’m like, oh, wow, this is a… yeah, you need some… you are the… you are the me equivalent within Brainforge, I think, where, just I’m the… I’m the creative surrounded by engineers, and you’re the more, technical mind surrounded by creatives.

376 00:49:49.100 ⇒ 00:49:54.110 Jeff MacDonald | Dir, Innovation and Technology: I think that’s a good way to look at it. Yeah, I mean, I like these kinds of talks because…

377 00:49:55.360 ⇒ 00:50:09.369 Jeff MacDonald | Dir, Innovation and Technology: kind of the see one, do one, teach one method, like, me saying it out loud sometimes gives me ideas. So I love talking about it. I think what might be helpful is, like, if you want, we can schedule something in, like, 2 weeks to 4 weeks.

378 00:50:10.090 ⇒ 00:50:14.590 Jeff MacDonald | Dir, Innovation and Technology: A lot will have happened on my end, because we’re actively

379 00:50:15.340 ⇒ 00:50:19.300 Jeff MacDonald | Dir, Innovation and Technology: Developing these things, turning these things on, making them work.

380 00:50:20.390 ⇒ 00:50:27.909 Jeff MacDonald | Dir, Innovation and Technology: And so, every day, we’re trying to make the tools that we have more useful and successful for our teams. And so, in 4 weeks.

381 00:50:28.760 ⇒ 00:50:41.150 Jeff MacDonald | Dir, Innovation and Technology: you know, in theory, in 4 weeks, actually, by our milestones, we should have launched in the agency. So I’ll have been able to provide you a lot of details about how things are going and where we’re short… coming in short.

382 00:50:41.150 ⇒ 00:50:55.790 Luke Scorziell: Yeah, okay. I mean, yeah, I mean, the cool thing, too, is, like, we… we’re finding that we can move super quick, too, so it’s, like, some of our project turnaround times right now are 4 weeks. Yeah. But, yeah, why don’t… I could… we could set a time…

383 00:50:56.460 ⇒ 00:51:02.300 Luke Scorziell: I guess now, if I… Four weeks from now is what?

384 00:51:02.410 ⇒ 00:51:03.490 Luke Scorziell: March.

385 00:51:03.940 ⇒ 00:51:09.689 Luke Scorziell: End of March, yeah, I would just like the…

386 00:51:10.150 ⇒ 00:51:12.689 Luke Scorziell: 20th, 27th work for you, one of those days?

387 00:51:13.700 ⇒ 00:51:18.090 Luke Scorziell: When would be… when would you have the context that you feel like you’d want?

388 00:51:23.330 ⇒ 00:51:25.740 Jeff MacDonald | Dir, Innovation and Technology: Yeah, the 25th?

389 00:51:26.350 ⇒ 00:51:27.870 Jeff MacDonald | Dir, Innovation and Technology: is pretty open.

390 00:51:28.440 ⇒ 00:51:29.120 Luke Scorziell: Okay.

391 00:51:31.990 ⇒ 00:51:38.260 Jeff MacDonald | Dir, Innovation and Technology: We could do the same time the 20… well, not the… yeah, we could do 2.30.

392 00:51:38.260 ⇒ 00:51:39.809 Luke Scorziell: 2.30 on the 25th.

393 00:51:39.810 ⇒ 00:51:40.500 Jeff MacDonald | Dir, Innovation and Technology: Yeah.

394 00:51:41.160 ⇒ 00:51:41.810 Pranav Narahari: Perfect.

395 00:51:42.540 ⇒ 00:51:45.229 Luke Scorziell: Well, should I… I can book 45 minutes?

396 00:51:45.420 ⇒ 00:51:47.030 Jeff MacDonald | Dir, Innovation and Technology: Yeah, go for it, go for an hour.

397 00:51:47.030 ⇒ 00:51:47.650 Luke Scorziell: Okay.

398 00:51:49.990 ⇒ 00:51:52.020 Jeff MacDonald | Dir, Innovation and Technology: I’ll let you know how things are going, and…

399 00:51:52.660 ⇒ 00:51:55.670 Jeff MacDonald | Dir, Innovation and Technology: Yeah, we’re… we’re… we’re doing a lot of things.

400 00:51:56.280 ⇒ 00:51:59.310 Jeff MacDonald | Dir, Innovation and Technology: All at the same time, which is really fun. But,

401 00:52:00.160 ⇒ 00:52:04.920 Jeff MacDonald | Dir, Innovation and Technology: Yeah, there is a little bit of the bottleneck of me being the sole person.

402 00:52:05.180 ⇒ 00:52:13.220 Jeff MacDonald | Dir, Innovation and Technology: developing all these things, so we are hiring a 3-6 month contract on as creative technologist, me.

403 00:52:13.450 ⇒ 00:52:20.170 Jeff MacDonald | Dir, Innovation and Technology: That would help start leading the creative operating system, because I’m very focused on the strategic tool.

404 00:52:21.410 ⇒ 00:52:25.319 Luke Scorziell: Yeah, how much are you… or what are you budgeting for that position?

405 00:52:25.320 ⇒ 00:52:25.990 Jeff MacDonald | Dir, Innovation and Technology: I don’t know.

406 00:52:27.410 ⇒ 00:52:32.969 Jeff MacDonald | Dir, Innovation and Technology: I was only told to do the interviews, I wasn’t told how much they’re gonna spend on it.

407 00:52:32.970 ⇒ 00:52:38.139 Luke Scorziell: Yeah, okay. I mean… Yeah, we’d love to chat. I mean, also, yeah, if it makes…

408 00:52:38.330 ⇒ 00:52:41.339 Luke Scorziell: Like, if it makes sense to chess, Unity can always…

409 00:52:41.630 ⇒ 00:52:43.869 Luke Scorziell: Let me know, but yeah, it’d be interesting to…

410 00:52:44.110 ⇒ 00:52:47.129 Luke Scorziell: Because I think what we find at a couple pinpoints is, like.

411 00:52:47.270 ⇒ 00:52:52.630 Luke Scorziell: We’re helping cut down on, like, SaaS sprawl, and then we’re kind of able to build in systems that

412 00:52:52.900 ⇒ 00:53:01.780 Luke Scorziell: new people can use, and then we have kind of a whole engineering team that embeds, so it’s, like, a lot to put on, you know, that we’re able to move, kind of.

413 00:53:02.490 ⇒ 00:53:21.280 Jeff MacDonald | Dir, Innovation and Technology: Yeah, that’s interesting to me. I mean, especially because you already said you use linear. It’s interesting to me, like, rather than just hiring a single person for a contract for 3 to 6 months, like, working more with, like, a team that can maybe work more agilely in the same amount of budget in 4 weeks…

414 00:53:22.310 ⇒ 00:53:22.920 Luke Scorziell: Yeah.

415 00:53:23.550 ⇒ 00:53:28.770 Jeff MacDonald | Dir, Innovation and Technology: just using linear and GitHub. It just knocked the thing out.

416 00:53:28.770 ⇒ 00:53:42.889 Luke Scorziell: Yeah, I mean, literally, we do… we also do data stuff, but we did a migration from a legacy BI tool to a new tool in two weeks for someone, because they… which was insane that we did this, so it’s, like, the speed that we’re moving is…

417 00:53:42.940 ⇒ 00:53:54.440 Luke Scorziell: crazy with the other agency we worked with, we propped up stuff within, I think it was, like, 2 weeks. They had, like, some… 2 or 3 weeks, they had some minimum viable, like, products that they could work with, and so…

418 00:53:54.630 ⇒ 00:53:57.390 Luke Scorziell: And then the other thing, too, is, yeah, like, this is…

419 00:53:57.550 ⇒ 00:54:01.570 Luke Scorziell: all we do. Yeah. So, we’re like…

420 00:54:01.740 ⇒ 00:54:05.109 Luke Scorziell: Three engineers all on Clodmax, you know? Yeah, I had…

421 00:54:05.110 ⇒ 00:54:15.190 Jeff MacDonald | Dir, Innovation and Technology: You mean you don’t have to go and now take a meeting, with the Stagwell agency about how to onboard your team to Adobe Learning Management Software?

422 00:54:15.190 ⇒ 00:54:32.260 Luke Scorziell: Yeah, well, so… and then that… so, yeah, the… that’s… like, we… there was a post yesterday that was like, I feel like I need a full… I need to be unemployed to be able to learn about how to become AI native, and I sent that in Slack, and I was like, I think they just need to work at Brainforge, because it’s like.

423 00:54:32.370 ⇒ 00:54:33.970 Luke Scorziell: All we’re doing.

424 00:54:34.120 ⇒ 00:54:41.080 Luke Scorziell: But, yeah, so I would love to check in too, but then I’m also curious, like, if there’s anyone else that you think would be, like.

425 00:54:41.540 ⇒ 00:54:49.259 Luke Scorziell: interesting to talk to, like, I’ve… a couple of these conversations people have brought up, like, the parent companies, I don’t even… I don’t know how that…

426 00:54:49.520 ⇒ 00:54:51.579 Luke Scorziell: Structure works with them, but…

427 00:54:51.580 ⇒ 00:54:53.500 Jeff MacDonald | Dir, Innovation and Technology: I don’t know how that structure works.

428 00:54:53.500 ⇒ 00:54:58.009 Luke Scorziell: Yeah, or other people that you know at agencies that are maybe in your position. I’m kind of…

429 00:54:58.010 ⇒ 00:55:02.210 Jeff MacDonald | Dir, Innovation and Technology: I wish I knew more people at other agencies in my position, I’d hire them.

430 00:55:02.990 ⇒ 00:55:05.990 Jeff MacDonald | Dir, Innovation and Technology: No, I don’t… I’m… I… I know…

431 00:55:06.450 ⇒ 00:55:11.679 Jeff MacDonald | Dir, Innovation and Technology: Yeah, I don’t know anyone else or anybody at the Stagwell level, unfortunately, in what they’re doing.

432 00:55:12.000 ⇒ 00:55:13.479 Jeff MacDonald | Dir, Innovation and Technology: To me, they’re working…

433 00:55:14.030 ⇒ 00:55:24.490 Jeff MacDonald | Dir, Innovation and Technology: slow and in legacy systems. Like, I don’t know, like, I, every single time I do a demo of a SaaS product over at Stagwell, I’m like, I could build that.

434 00:55:24.490 ⇒ 00:55:25.080 Luke Scorziell: Yeah.

435 00:55:25.080 ⇒ 00:55:27.050 Jeff MacDonald | Dir, Innovation and Technology: I’m gonna pay you per month for that.

436 00:55:27.460 ⇒ 00:55:28.900 Luke Scorziell: Yeah, exactly.

437 00:55:29.310 ⇒ 00:55:33.939 Jeff MacDonald | Dir, Innovation and Technology: Anyways, yeah, I don’t know, I don’t have any other contacts, but if I think of anybody, I will let you know.

438 00:55:34.140 ⇒ 00:55:37.600 Luke Scorziell: Cool. Well, this was so fun. Thank you for making the time.

439 00:55:37.820 ⇒ 00:55:52.519 Jeff MacDonald | Dir, Innovation and Technology: It is fun! I’m so excited for chatting with you all, and yeah, hopefully I can, like, make some progress on some stuff, so our next meeting, I can give you a status update and figure out maybe how we can partner, especially around… I’m very interested in, like.

440 00:55:52.910 ⇒ 00:56:02.290 Jeff MacDonald | Dir, Innovation and Technology: Once we start figuring out what the ask is actually for this 3-6 month contract for this creative technologist, and comparing it to what we could get just with contracting.

441 00:56:02.930 ⇒ 00:56:06.290 Jeff MacDonald | Dir, Innovation and Technology: with the company, like, I’d be interested, because…

442 00:56:06.570 ⇒ 00:56:13.680 Jeff MacDonald | Dir, Innovation and Technology: Yeah. Three engineers with Cloud Pro Max accounts that do this, versus, like, a single contract person with 1 Cloud Pro Max account.

443 00:56:17.390 ⇒ 00:56:18.100 Jeff MacDonald | Dir, Innovation and Technology: Oh.

444 00:56:18.310 ⇒ 00:56:21.470 Jeff MacDonald | Dir, Innovation and Technology: Cool. Well, we’ll check in in about a month.

445 00:56:21.730 ⇒ 00:56:23.899 Luke Scorziell: Will do. We’ll talk again soon. Alright.

446 00:56:23.900 ⇒ 00:56:24.580 Pranav Narahari: It’s awesome.

447 00:56:24.990 ⇒ 00:56:26.350 Jeff MacDonald | Dir, Innovation and Technology: Great talking. Bye.

448 00:56:26.350 ⇒ 00:56:26.920 Luke Scorziell: But…