Will Sartorius's The 3-Part Framework That Tells You Exactly Which Ads to Make Next
FCo-host Will Sartorius chats with Andrew on a wide-ranging episode that opens with a hot-take roundup on the latest model drops (Claude Opus 4.8, Google Omni (Veo 3.4)), and why Google Flow's $200/month subscription might be the most slept-on deal in AI right now.
Will then shifts gears and dives into his full operational playbook. He breaks down how his agency uses AI to close more enterprise deals (a proposal workflow that litterally turns a sales call recording into 14 spec ads, a gap analysis, and a competitor breakdown that's delivered same day). He then outlines the three-piece framework his team uses to generate better creative: gap analysis, time series analysis, and social listening.
Andrew and will also get real about the messy details of AI and how tool costs can add-up fast, the danger of automating for automation's sake, and how to actually structure AI governance inside an agency. This episode closes with a four-bucket framework for how agencies and D2C brands should be thinking about AI as they move through 2026 and beyond.
Key Takeaways
The same-day proposal workflow Will is using to close enterprise deals faster and how you can too.
Why the gap analysis the first piece of the creative puzzle and what Will's AI tool actually shows you about your ad account.
What a time series analysis is for ad creative and how you can use the Meta API to tag every ad you've ever run by persona, angle, format, and emotion.
How social listening on these platforms will change the ads you prioritize.
How Google Flow's $200/month subscription actually stacks up vs. paying per-generation on SeaDance for high-volume video work.
Why Will decided to go back to having a human editor QC every AI-generated static before it goes live.
The TRUE cost of "playing around" with AI, and how to audit if your AI projects are actually generating revenue versus just burning tokens.
How the smartest agencies thinking about AI governance and what every agency needs to build out now
Products & Software Mentioned
Claude Opus 4.8 / Claude Sonnet 4.6 (Anthropic) — https://claude.ai (used for copywriting agents, tagging historical ads, and proposal workflows)
Claude Code — https://claude.ai/code (used for proposals, landing pages, and creative workflows)
Google Omni / Veo 3 (Google) — https://deepmind.google/technologies/veo/ (video generation model)
Google Flow — https://flow.google/ ($200/month subscription unlocking Nano Banana, Veo 3.1, Veo 3.2, Omni)
Nano Banana (Google) — Google's image generation model, accessible via Google Flow
C-Dance / Sea Dance (ByteDance) — Video generation model; comparable to Google Omni but priced per generation
GPT-4o Image Generation (OpenAI) — https://openai.com (referred to as "GPT-2" for image/static generation in context)
Read.ai — https://www.read.ai (AI meeting recording and transcription)
Granola — https://www.granola.so (AI meeting notes; mentioned as comparable to Read.ai)
11 Labs (ElevenLabs) — https://elevenlabs.io (voice AI; briefly mentioned)
Meta API — https://developers.facebook.com/docs/marketing-apis/ (used to pull historical ad data)
adlib.getskipper.ai — https://adlib.getskipper.ai (Will's free gap analysis tool — enter your brand, get persona/angle/emotion gaps)
Skipper — Will's product (social listening and creative intelligence platform; referenced throughout)
NFL.ai API — Used for generating static ad images directly into Claude Code workflow
Higgsfield — https://higgsfield.ai (AI video platform; mentioned as an alternative to Google Flow)
file.ai — Referenced as a platform team uses for video and static generation
Vercel — https://vercel.com (used for spinning up landing pages quickly)
GitHub — https://github.com (used in landing page/CRO workflow)
HQ — Project management tool for AI workflows (referenced as a way to organize Claude Code projects)
Codex (OpenAI) — https://platform.openai.com/docs/guides/code (mentioned as an alternative coding AI)
To connect with Andrew Foxwell reach him here Andrew@FoxwellDigital.com
To connect with Will Sartorious DM him here https://x.com/will_sartorius
To Connect mith Thomas Moen DM him here https://x.com/thomasmoen
To learn more about Foxwell Founders and conversations like this one, go here: www.foxwellfounders.com
Full Transcript:
(00:00) If you work in D2C and you use AI and you're wondering what the F is going on every week, this is your podcast. The AI D2C WTF podcast. Your home for tactical tips, strategies, and ideas that you can implement right now in your AI workflows to make your brand or agency more money. Welcome to a new episode of AI D2C WTF.
(00:27) We have Andrew and Will here. Andrew is working at 50% capacity because he's been going to the opera too often and taking stage and singing a little bit too much. Yeah, people don't know this, but I actually smoke a pack and a half a day and it's finally just affected me. You know, I'm also a part-time performing artist.
(00:48) You're a Marlboro Red guy, right? Big Marlboro Red guy. Yeah. And it's finally affected me. And the reality is I have a six-year-old and, you know, she licks my face, you know, or something. You know, it's like kids do gross stuff and that's what happens. So I'm sorry. Maybe some people like this. You know, maybe I'll have to like 11 labs and like keep this on because people are going to like the smokiness of it.
(01:12) You know, some people like a smoky me and some people like a smoky voice. And that's kind of what we're doing here. You're the most interesting man in marketing. Yeah, exactly. Exactly. Yeah, well, we're glad that you're here. Thank you for listening. There's been a lot of interesting new stuff that I would love to go through with you, Will.
(01:33) What's some of the newest stuff that's come out? I mean, there's so much. Claude came out with a new model, BT Dubs. What's your take on it? What can it do that the others can't thus far based on what you're seeing? Yeah. So, yeah, the two big drops this week or I guess over the past week and a half were Google I.O.
(01:53) , of course, which released Omni, which is their new video model. And then obviously Opus 4.8, which came out yesterday. So I can't say I have a clear sense of how much better it is than 4.7. What I can say is it uses a lot of tokens for commensurate tasks and compared to 4.7. So, for example, last night I was generating like 20 static ads for a client.
(02:19) They were just in Wirecutter. So we just wanted to spin up 20 ads with the Wirecutter branding. Just get that out there sort of ASAP Rocky. And I think it used like 850,000 tokens to write copy for 20 ads. Oh, my God. Which is pretty crazy. I will say, though, we have a pretty intricate process where we have 10 copywriting agents and each of the agents have to give the copy a score of 90 or higher or else it doesn't pass.
(02:48) And so historically, I think what was happening is it would just be like, ah, you know what? This is good enough. But I actually think I was on Opus 4.8 max at first and then I went down to extra and I found that actually the copy that it wrote, granted it took three hours, was very good. Like probably the best copy I've seen come out of Claude.
(03:07) And the other thing I found is that if you have a system with a handful of different skills marked on files, Opus 4.7, 4.6, they would skip a lot of steps and sort of say like, oh, you know what? I forgot that step. Let me go back and do it now that you've sort of called me out. What I found is that Opus 4.
(03:28) 8 doesn't necessarily skip as many steps. It's more intricate in reading your instructions, which is very, very helpful. And then on top of that, when you do slash goal, it very much, it feels like when you do slash goal and give it a specific end goal, it feels like it holds itself to a higher standard in the sense that like I need to do all these steps properly and not just like use my sort of human companion to bounce ideas off of.
(03:59) I candidly haven't been in Codex too much. I know everyone is telling me I should be doing more in Codex. I, you know, we use GPT-2 for image and static generation. I'm just like so, you know, embedded in Claude code at this point. And I just like Anthropic as a company more than OpenAI. So that's just like sort of like a morality thing.
(04:25) Maybe they're both sort of evil. But at the end of the day, yeah, I think 4.8 is better overall. I think the reasoning and the token usage are definitely correlated and they're definitely up. But overall, I would say from what I've seen thus far, the copywriting is, as it pertains to marketing, is superior than that of 4.7.
(04:48) Of course, you need to be giving it the right parameters to get good copy. I mean, what about this new Google thing that's out with the video? What do you think about that? Yeah. So Google Omni, this is like sort of Veo 3.4, I guess, technically. I think it's great. I think it's, again, probably on par with C-Dance, which is the ByteDance model.
(05:10) They're very, very similar. What I will say, though, is C-Dance gets pretty expensive pretty fast. If you wanted to do a full claymation Pixar ad, those things are all the rage these days. Or maybe they're gone. Who knows? It probably costs you $20 to $30. What's cool about Google is if you use Google Flow and just pay for a monthly subscription, I think it's like $200.
(05:35) You effectively get unlimited usage of their models. So you're getting $200 and you can use Nano Banana, Veo 3.1, Veo 3.2, up to Omni. And it just feels like that's a no-brainer. And I think that's just like a slept-on thing. People are probably just using Higgs field or file.ai or going directly to the interface.
(05:58) But yeah, Google Flow is great. We just built an account and that's what our team uses when we're generating videos. So now we're saving money because we're not really using C-Dance anymore. We're able to utilize Omni within this channel. I will say, you know, one thing I've noticed is that our file.
(06:15) ai where we're generating videos and static bill has gone way up. It's not necessarily a bad thing because we're generating a lot more statics. And we can sort of get into that in another episode. But ultimately, yeah, the Omni model is great. It's super solid, I would say. Probably on par, if not the best video model right now.
(06:36) Like if you want to animate statics, it's ridiculously easy. Also, product fidelity, it does a really good job with. Generate the ad first in GPT-2 as an image. Use that as a reference. And then upload that to Omni. And you can get a pretty good video. The other thing that's sort of like top of mind right now is, was it June 9th? In New York, you're going to have to start disclosing if you're using AI creators.
(07:03) So that's just like something to be on folks' radar. You'll need a disclosure there. One thing, you know, I was on a sales call earlier and they were saying they're nervous. This is a, you know, a larger brand. And they're very nervous even about using like hands or feet for AI. So, you know, I did some deep dive in there.
(07:19) And I know, Andrew, you are, you know, you probably have more experience with law than me. But it seems like there's a lot of gray area in this thing where there isn't a lot of explicit language about certain use cases. So it's hard to say for sure, like what is going to consist of this sort of AI generated content.
(07:39) Like if you have an AI persona talking and applauding a product like that is going to be problematic. But if you're just showing a hand, like I can't see that necessarily being an issue. But invariably someone's going to get sued or I guess, and we'll have to sort of figure that out as we go. But yeah, June 9th, it's approaching quickly.
(07:57) Something just behind folks' radar. Good shout. The legality thing, I mean, we'll continue to see this, you know, change and evolve over time. I think there's a couple of things you never want to under, sorry, you never want to overestimate, which is the competency of Congress to actually legislate something, which they won't.
(08:15) And you also never want to underestimate the power of what lobbying can do, of which there will be an anthropic and others. It'll be, it'll go the way of meta and, you know, social networks. It's not going to be really legislated a lot. So I wouldn't necessarily think about it too much, but state law will become where the issues are.
(08:38) So you just have to kind of be aware of that, be ready for that. Any other major releases we want to talk about, Will? I think that is sort of the gist of it. All right, cool. Well, good wrap up and let's go ahead and get into the episode. Today, we're really talking about, Will, what you're doing with AI. I think the people know about you.
(09:00) They know that you do with AI creative, but, but like, let's get into the high level and then let's go really specific about what you think is the future of this and all that. But first of all, so like, what are you, what are you doing with AI right now in your company? Yeah, I would say AI. To sell. To sell. Okay.
(09:17) Yeah. To sell. Sure. To sell first, let's frame it up. Yeah. Okay. So great question. AI has made making sales proposals so much better. So when I get off of a sales call, what I've created is effectively a markdown file. So, you know, we use read.ai. It's the same thing as Granola, you know, AI recording. So what I do is after a sales call, I take the recording from the sales call.
(09:43) I upload that into a cloud folder that I attach to cloud code. And then I have a workflow in which it reviews the call. Then it goes to the brand's website, scripts products, scripts product descriptions, and, you know, fonts, colors, et cetera. It'll generate 14 spec ads sort of based on what we talked about in the call.
(10:06) Additionally, what it does is like does a bit of a very quick gap analysis, like what are your competitors are doing that you're not. And that way, like I have one candidly going on in the background right now from a sales call that we went on this morning. The full process probably takes five to seven hours, like doing sort of end to end.
(10:24) But what ends up happening is I get this beautiful looking proposal with 14 spec ads ready to go that I can deliver to them same day that has like everything that we discussed in the call embedded within the proposal. Insane. It's insane. So good. It's insane. And like we are now, I genuinely believe this, you know, just based on the way our proposals look, and I'm happy to sort of share this with, you know, believe this in the notes or whatever.
(10:52) Like I genuinely believe just based on how our proposals look, like we are closing enterprise deals at a higher clip because it just feels like this is, these people really care about polish. And yeah. And the other cool thing about this system is if you have the brand send over like brand guidelines, et cetera, you ingest that into your cloud code as well.
(11:15) And so like it's you effectively are creating an agent to QC against brand guidelines. So when you deliver those assets for a brand that really cares, everything's pixel perfect, you're going to sort of hit the mark right off the bat. I mean, it's so it's so great. Like it's it's such an easy thing to do. But what I was really asking was like, you guys make ads for people utilizing AI, right? But you also wrap in customer personas.
(11:39) And like, that's the that's a big, deep part of what you do, right? Yeah, of course, the ad creation is like, it's the last piece of the puzzle, right? Like, I think I talk about this on most of my sales calls. So and we may have talked about this in the podcast before, so I'll keep it brief. But I think there's like sort of three pieces of the puzzle to generate great ads.
(12:00) You know, the first piece of the puzzle is a gap analysis. You know, I've built a free tool adlib.skipper.ai, adlib.getskipper.ai, where you can put in your brand, it will show you like, these are the personas, formats, angles and emotions that you're not focused on that you should be focusing on. And I'll give you 10 recommendations on ads to build.
(12:18) That's sort of piece one. So it's like, you are focusing on these personas. And like, especially for folks that are struggling with CAC. And it's like, you know, we can't get new customers or CAC keeps flying. But the issue is you probably keep targeting the same people again and again. So you've trained your pixel to just like look for the same type of person, right? Like you need to be training people.
(12:38) You need to be training Meta's pixel to be looking for new audiences. So sort of the gap analysis is one. And I'll add to that in a moment. The second piece of the puzzle is time series analysis. I think the antiquated way of thinking about things is, oh, you know, we had that great ad in January. Like, why didn't we ever do anything more like that? Why didn't we ever hit up that creator again? Or like, oh, we had that, you know, static that did really well.
(13:04) Like, why did we turn that off? Like, this is how agencies and brands talk. And it's just like, it feels like the stone ages. Because like what you can do at this point is using the Meta API, I would say use the Meta API. Don't use MCP. The MCP sort of breaks. Even the Meta API sort of sucks, but it's better than the MCP.
(13:22) What you can do is you can pull all of your ads that you've ever run. You can use Cloud Sonnet 4.6. And you can tag every ad you've ever created with persona, angle, format, emotion, and ad type. And then you can correlate that to performance. And so you can say like, okay, for the past five years, like these combinations have been my winning formulas.
(13:43) And like, here are the ads to back that up. So if you're creating a system where you are never losing learnings, like every learning is compounding on one another. And that's like also why like creative velocity is so important, right? Like the more ads you're putting into the system. And like, I know this is like a controversial take.
(14:01) I'm of the opinion, like for every $1,000 you're spending, you need to be testing a net new creative. And I don't mean an iteration. I don't mean a new hook. I mean like a net new creative, right? Even if it doesn't get enough spin, you'll still get signals that will go into that time series analysis that will tell you, you know, this persona, angle, emotion had a great CTR.
(14:18) So like maybe there's a CRO optimization you can do. So anyway, so we have the gap analysis, the time series analysis, and then the third piece of the puzzle, and this is what we're building with Skipper, is social listening. You know, looking at what folks are saying in your reviews, what folks are saying on Reddit, on Trustpilot, on Quora, on Amazon, and saying, okay, these are like my core eight to 12 personas.
(14:38) This is what they care about the most with a product. Like these are the angles that they care about the most. And then what you do is with the social listening, the time series, the gap analysis, you put that together and you have this really nice Venn diagram of like, here's what the gap analysis is telling me to do.
(14:57) Here's what my time series analysis is telling me to do. Here's what people talking about my brand are telling me to do. Where's the overlap? Okay, great. Here's the overlap. Here are the ads we should be creating. And so like, when we now have an AI, we call it AI creative only team, but there are eight people on it, right? Like the whole idea is like, there's humans in the loop every step of the way.
(15:17) Like we are not at the point, and I cannot reiterate this enough because I get this question almost every day. We are not at the point yet where you can get 10 out of 10 perfect ads using AI alone. You may get really good ones. Maybe nine out of 10 are really, really good. But maybe a few won't have the safe zone or whatever it is, right? So when we have the center of that Venn diagram, right? We can give that to a creative strategist.
(15:43) The model will say, hey, you know, this is what I'd recommend putting together based on those three things outlined. And the creative strategist will say, great, give me 20 ads, 20 pieces of copy. It'll spit out the copy. Creative strategist will review the copy. Great. If they like it, great. If not, you know, not so good.
(16:02) Again, like I said, 4.7, we were rewriting a lot of the copy. I just did this wire cutter ads for this client today. And the copy is really good. And so I think Opus 4.8 really, you know, helped out with that. Granted it took like three, four hours. And then the ads are generated. We're just using an NFL.ai API.
(16:23) So it lands directly in our Cloud Code folder. Of course, you can use Higgs field as well. And then I think where I was being really too stubborn for too long was I was saying like, we don't need to necessarily have an editor touch these up. But as we have been now selling this workflow to enterprise, that's just like not, you know, you sort of need to have that.
(16:46) So we... Looking at it, yeah. Yeah. So we have, you know, three people in the U.S. that are generating statics with AI. And then they go to our editing team. We have a 24-hour SLA. And what the editing team effectively is, they're just like brand guideline Nazis. They're just ensuring that, you know, the fonts are perfect.
(17:09) The colors are perfect. The product looks right. Everything's in the safe zone. And that's their job. So, all right, it's just like a QC team. Because when we're at the scale now that we're generating so many creatives, it's hard to be like, is that, you know, is that going to get cut off by Meta's UI? Like we just like needed a dedicated team to do that.
(17:27) And AI will get you very, very close. I would say of all the AI statics we're creating, 90... We're getting to 90 to 95% of the way there. It's just like those like sort of final touches, right? And especially for the brands that really care about pixel perfection. Like if the logo's size is like two pixels off, they're going to be like, that's wrong.
(17:51) So that's where having an editor come into play really makes a big difference at the end game. Yeah. So this is how you've built what you're doing and selling now. And hopefully those of you that are listening can take pieces of that and maybe even think about it in your own agency. So like, how are you as a creative agency utilizing AI within your creative systems? And also like, what is your creative system? Because honestly, you talked through some of it, right? You're going through the process of that's for each client.
(18:29) But how are you utilizing AI in the business to make more money or have more time or, you know, be really like be making great stuff for these folks? Yeah. Again, it's a good question. Some part of me, I feel like since, I don't know what we're calling it. We call it the industrial revolution. Are we calling this AI revolution? I don't know.
(18:51) Some part of it, I think I'm working more hours than I ever have in my life right now, I would say. And I think from folks that are sort of doing similar things, like I have one client that is, he says he works 18 hours a day in Cloud Code. He's just like addicted to it, right? And there is, I feel like a bit of a paradox where you feel like you're putting in more work, but you're getting less out of it.
(19:13) So you really need to sort of figure out which swim lanes make sense. I would say the biggest ROI I've found, one, the proposal game has never been better. Two, CRO. We never did landing pages. You know, we never did landing pages. Landing pages took us like three, four weeks. They were such a pain in the ass to put together.
(19:34) If you had edits, like it would take a designer, you know, four or five days to get edits back. Like now with like Vercel, Cloud Code, GitHub, like spinning up landing pages has never been easier. So in our workflow, like again, if we see an angle pop off for a specific brand, we just spin up a landing page within the next 24 to 48 hours and start driving traffic to that instead.
(19:56) Right? Like it's work, but like the more one-to-one you can go from ads to landing pages, obviously the better. We've talked about this ad nauseum on the Cody podcast. And I don't want to, you know, beat a dead horse here. Like from an operational perspective, I would say at first I was like, we probably don't need to have a project manager anymore.
(20:13) I was wrong. I think having a project manager is actually exceedingly helpful. I like definitely had a bit of whiplash where I was like, I can just sort of automate everything. And I think everyone sort of goes through that period. And then you sort of come back to reality and you realize like the solution is somewhere in the middle.
(20:29) So it's AI plus humans in the loop, which I've always been a proponent of. And especially with generating ads, I will say like from an ad perspective and like an analytics perspective, that is undoubtedly changed forever until token prices like increase astronomically. But like the ability to be able to track how certain personas or how certain angles are performing over time is crazy.
(20:56) It's so cool. Like we just have a graph where I can just like pull up a client. It's like, you know, how is, you know, a mom of 24 to 35, how has she been performing, you know, recently? Maybe she like is an urban mom, right? Like how has that been performing, right? So effectively, we've created a system where when our creative strategists come sign on for the day to start making their ads, they already have a swim lane.
(21:20) They know like I need to be generating ads for this persona, this angle, this emotion. The question is just like, what's the best copy for it and what's the best format to do that in? The AI can guide you, but, and I've said this to my team, again, at Nage, I'm like, the differentiator is taste. Like humans have really good taste.
(21:38) AI doesn't have any taste. There's something soulless about a lot of AI ads that I found. And that's why having people in the loop throughout the process is essential. I think it's, you know, one is I think from the workflow standpoint, and some of you listening to this may really identify with it, which is I think you were doing a certain amount of work because I feel like I'm working more as well.
(21:59) And then you sort of see what's possible. And then you were able to take on these things that you never thought you'd be able to tackle, right? Like, I mean, and that can mean anything. It can mean your creative system based on hooks like you're talking about. It can be creative cohort analysis. It can be, you know, what ads have driven the most net new customers.
(22:19) It could be, I mean, it can be any of that. And the volume of work, you know, I feel like I'm doing the volume of work of like three people now because I'm able to do all this stuff that just was unaccessible before. It just was like, this would take me forever to go through this. And now it's like, boom, boom, boom.
(22:36) We got to do this, got to do this, got to do this. You know, like I built like four landing pages for our own shit like last week. And now I've got to tell people about it. I got to promote about it. And then I'm using AI to write, you know, this and that. So, you know, I think it's big. And we're actually working on a statement about AI now in our organization about like, here's what we believe.
(22:58) Like we need to be transparent. AI augments our work, you know, et cetera, et cetera. It needs to be transparent when we're using it. Because I think we're all sort of in this like rush, gold rush moment. But it's also, we're going to need to come up with some standards in the industry of what it really means, the changes.
(23:13) I think from a creative strategy, or sorry, from a creative systems standpoint, you know, the fact that you're able to do deep analysis is massive. And if you are an organization that's making creative, you know, I think one of the biggest things that you want to always be looking at is not thinking about volume.
(23:32) It's not just about making a bunch of ads. And I think we know this. But it's about making enough of the right ads. And then figuring out what our expectation is as it relates to testing those. And it's also not every ad that you have in your, in the community, like in the ad account, right? It can't be all AI.
(23:52) It can't be all founder videos. It can't, you know, you know that to be successful, we need a mix. And this is what that creative like sort of analysis and systems can be built. I think that what this is allowing, or like can do for us, I think that what it's allowing us to do is build better ads over time and build better like way to categorize and understand where opportunities lie.
(24:20) And it can help you scale faster. If, you know, and that's, and I do think that to your point, a person running project management or CLO type of thing or type of role is absolutely the most critical as it relates to this right now. Because what I see in organizations and that the places that I'm coaching and stuff is like, people are doing this stuff, which is cool, but it's all running around like with their heads cut off.
(24:45) And, and you can have a tool like HQ, which is cool and puts all these projects together and you can see what they built or what you built and you can utilize those projects together, etc. But that is not going to solve for the why in each of this, right? Or in all this, like it's not going to solve for like, what's the incremental progress that we are making? And, and also the incremental revenue that we are making.
(25:12) Yes. And so I think you like, it has to be looked through that lens. And I understand that there's an excitement and like all this, but right now it's very much a noise perspective, you know? And it's not necessarily like moving the needle as much as it possibly could. I was talking to somebody the other day and I said, it's sort of akin to like, I mean, a little microcosm of like when like online messaging became available in the works.
(25:37) Like, you know, like you could tell this person you're going to be five minutes late or like, you know, all these little things. But then it like brought it to a whole different place. And then you're like, wait, where was that? They told me this over here. And so it's like, you have to make sure that you are understanding what the true incremental impact is in the business.
(25:56) And like over the incremental impact that you want to make and that all of these things are aligning towards that goal. And like, that's what we're trying to do. And also, I mean, we're at the point of it too, where having free thought is useful and messing around with it is useful. And that's good too. And some of that can be, we want to be a leader in AI as it relates to our agency.
(26:16) And by doing that, or in order to achieve that goal, we have to just be messing around a whole bunch. Right? Like, how do you enable your employees to sort of think through that will? Like, are you like, look, we want to be putting out 20 new proposals, net new. How are we achieving that? And also, are you taking like every employee takes an hour and a half every day to fuck around? Like, how do you sort of think about this? Yeah, it's a really tough one.
(26:41) And it's a hard solve because I think anyone that's doing this will immediately say like, well, I can just do it myself. Like, it'll be much faster. Like, I've built these systems around myself. Like, I know how my brain works. And that's where I was for a while. Like, I was the one, you know, generating all of the static ads for our clients for a bit because like, I'm neurotic and I can be a bit of a control freak when it comes to our standards.
(27:08) And then I just like found someone that I was able to sort of just like download all of my brain onto. And then she just like took that and like sort of going in her own way. And so like now what I've started to do, and, you know, we just brought in another person to sort of help generate statics as well. Is I sort of say like, hey, here's my framework of how I go about generating ads.
(27:31) This is just like one example, you know, ads as an example. Here's like the step-by-step process. Like, here are all the markdown files I utilize. We're going to send you a website that sort of goes through our whole process. But like, I don't want you to follow this exactly. I need people at the end of the day that are going to, this is like the most cliche line in the world, but sort of like think outside the box, color outside the lines, right? I think I read something the other day, like, I can't remember who it was.
(27:57) Maybe it was like Marc Andreessen was to like people that are going to be most successful in AI are just the people that are just like super unorganized and just like want to be testing a lot of different things, right? Like, and they're just like Renaissance people, right? Jack of all trades, maybe even a master of none.
(28:12) And so like, I think giving people, leading the horse to water in a sense, but then letting people have that like aha moment themselves, for me at least has been the sort of the critical unlock. Because before we were just like saying like, run these steps in a row and you'll get good ads. And people were doing that and they'd get good ads and they didn't really understand why they were getting good ads.
(28:35) Like, I don't necessarily need someone to just like run an energetic flow. Like, I can have AI run an energetic flow. But if I have someone that is building their own flow based on our foundation and comes up with like, oh my God, we should create this agent, right? This would fit really well after agent three and five or whatever it is.
(28:52) Like, that is what I want. And, you know, people talk about critical thinking all the time. Like, there are really two ends of the barbell. Like, and I'm sure everyone has seen it. There are people that are like respond in Slack with ChatGPT or respond in emails with Claude, which is fine. And then there are copywriters who are writing their copy with Claude or ChatGPT, which is fine.
(29:14) And those are the people that are on one end of the dumbbell. You know, they're sort of effectively replacing their work with AI, which is like useless. Because like, who wants to be in the middle of the bell curve? Then the other people are the people that are like actually critically thinking and pushing back every second on what the AI is giving them.
(29:30) And saying like, this is how you do it better. Like effectively training a junior employee. You know, this is how you write better copy. This is how, you know, you generate better ads. This is how you think about these things better. So, yeah, I think, you know, sort of like the token maxing era is like slowly dying.
(29:45) And now it's like, how can we actually utilize these things to create ROI? Like, we've had our fun. We've been in the playground. We've fucked around. We've made a lot of cool things. But now exactly to your point, Andrew, like, where's the ROI? And the ROI for us has been being able to build landing pages for CRO, being able to bulk create a lot of static ads with editors and strategists in the loop, and generating really, really strong proposals.
(30:09) And those have been the three pieces that I've utilized for AI that have really, really leveled up our organization. Everything else is pretty much the exact same as it was before. Yeah. I mean, I think, you know, this makes me think about, you know, there's going to be these phases of it that will impact all of it.
(30:26) If you look across our businesses or you look across D2C businesses that we work on, you know, I think there's going to be, we're going to have to establish a bunch of different buckets as it relates to AI. One is there's a governance bucket. And the governance bucket is putting out a thing of what do we believe? How are we securing this data within our brand or our agency? And how are we, you know, sort of utilizing AI in our organization? And this is what it means for us to utilize it.
(30:58) Hey, employees, this is what it is. Okay. And who is going to be the captain of this? Right. There needs to be a person or a group of people that are a counsel in an agency or whatever, you know, that sort of says, because this stuff's going to keep evolving. So it can't just be on the founder. And it can't, it shouldn't just be on the founder.
(31:17) Right. Like it has to be on a group of employees that care and contractors. I mean, for what, you know what I mean? That's like a governance thing. Like, this is what we do. This is where we stand and how we use it. And then this is, you know, kind of the way that we think about it. And that, then the next piece of it is revenue enablement, like we were just talking about, which is what are the challenges we face in business? And whether that's unlocking new personas for scale in any D2C business, unlocking new landers for scale.
(31:48) I mean, you could, you know, go specific, like I'll keep it high level. Unlocking and understanding unit economics. Great thing that AI can help you with. Understanding and going through, you know, inventory planning. As inventory relates to how much money you have in the bank any given day that you could spend on ads.
(32:09) I mean, and if you're a subscription brand, there's even more of this. Okay. So like, it's sort of what is the revenue enablement that we can utilize. Right. Right. And it's, we're going to go from, from piecemeal project based stuff of like, add this, add this. Oh yeah. And then I made this landing page or whatever.
(32:24) And it's going to be more like, it's going to have to go under an umbrella of, is this making us more money? And then the third bucket or a third bucket on this is employee enablement. So what are the things that you are already doing that you could replace? That's one. And that's where a lot of people sit now.
(32:42) The next one is, what are things you've always wanted to do that you believe would have an impact on the second bucket or on your own time that would give you time back that will enable you to be better at your job and have you as one employee be three employees. Right. And if, and under that bucket is incentivization.
(33:03) How are you incentivized to do this? If you do better with this and you, and you save four hours of time every day, that's great for you. And you save the company 20%, you should get a 10% bonus or whatever. Right. Like, how are you incentivizing that underemployee AI engagement and whatever. And I think those are kind of like some of the main pieces of how it will do that.
(33:27) I mean, I would say the fourth bucket is probably like a partner bucket of like, how are you communicating and working with partners in your, is you in your agency? Or in your e-com business? Right. Like, what are the things that you know from previous conversations that you don't have to repeat yourself? What do you know from previous things that, you know, are in Slack that you can say, like, I know I talked to Julie about this three years ago or three months ago.
(33:50) What should you say about pricing per pound on tea then or whatever? You know what I mean? It's like, and like bringing that together and how can you make partner relationships 20, sorry, 2x, like 200% more effective. Um, because that is going to make your life easier as well and will allow you to scale a lot faster.
(34:09) Um, and I think, you know, it's like you can talk about media buying, of course, which all of us are media buyers ultimately. And like, I mean, that goes under bucket two, right? Which is like, how do we make more money from this baby? Um, as well. So anyway, that's kind of like, I've been thinking about how we go through this and what those buckets look like.
(34:25) I don't know what you think, but that's, that's been my take. Yeah, I think that's a really sound take. Um, I think it's a really, really sound take. It's, uh, uh, which company was it? Maybe Uber release, uh, you know, this is how much we're spending on tokens. And like, this has been our ROI and it's like, you know, 80% versus 20%.
(34:44) Uh, so I think, you know, at the end of the day, it really comes back to like, what is revenue generating for you? And I think, and this was a reality check for me. Like, I just needed to look in the mirror. I was spending way too much time generating shit that we just didn't need, but I thought was like, cool.
(34:59) Uh, and I was like, I'm, you know, I should be spending this time with my kid. Like, what am I doing? Like, you know, uh, and so figure out what lanes you need to be focused on. It's going to be probably different for everyone. And just go in that direction. Like, try to correlate the projects that you've created with cloud code, codex, whatever it is, to revenue generated.
(35:22) And what was your costs? And like, what, how much revenue? And like, what was your margin? Like, I'm looking at the amount of status that we're creating right now. And like, we probably spent like seven or eight grand this month, just like using AI tooling. Like, that's a lot of money. And I'm like, oof, you know, that feels like a lot, you know? And, you know, we're still have the same headcount.
(35:42) We actually added people, but like an extra 7k a month to generate ads that we were using editors for before. Obviously, we're doing a lot more. So, you know, it's, it's sort of six, one half a dozen, but like, just like be super conscious about that stuff. Because it's so easy to get taken away, you know, just, yeah, be taken away by all of this.
(35:59) And be like, this is amazing, especially if you're using an API. Because like, you don't see the costs like upfront in cloud code. Or using an MCP, you don't see the costs upfront. So, yeah, I appreciate it. Thank you for listening, everyone. Hopefully, this is helpful to you of our ranting and talking about all this different stuff.
(36:16) And we appreciate you being here. And if you have any thoughts or anything, always email me, andrew at flexibledigital.com. And we look forward to hearing from you next time. Thank you, guys. Thank you. Thank you. I appreciate it.
