From Prompt Engineer to AI Architect: Florian Litterst's Full Agency Playbook

Written By Andrew Foxwell | Co-Founder of Foxwell Digital

Florian Litterst, German paid social agency owner since 2012, joins the show to break down exactly how his team has wired AI into every corner of their operation. The conversation gets specific fast, from a Claude-powered agent that scrapes competitor ads from Meta's EU ad library and surfaces untested angles every 30 days, to a another that mines Trustpilot, TrustShops, and Amazon competitor reviews for creative ammunition.

Florian walks through his image generation workflow using krea.ai, why he now runs AI-ready photo shoots so every product can be "prompted into any situation," and how AI-generated B-roll is solving the impossible shot problem (think: socks on a runner's feet filmed from behind).

The episode closes with a forward-looking debate on where AI is taking agencies from execution focused shops toward data-connected consultancies and a unanimous take that experienced human taste is the one thing AI still can't replace.

Key Takeaways

  • What a real competitive intelligence AI agent looks like and how you can build one using Meta's ad library, Airtable, APFI, and Claude.

  • Why pulling competitor negative reviews from these places are one of the most underrated sources for ad angle discovery.

  • How the EU's ad transparency rule actually gives European agencies a data advantage over US-based media buyers. 

  • Why investing in "AI-ready photo shoot" is cheaper than repeatedly shooting new product content everytime

  • When AI-generated video becomes a liability instead of an asset

  • How this one site is being used to create scalable image and video workflows.

  • Why creative iterations are losing their value in Meta's algorithm, and what agencies should be doing with their production time instead.

Products & Software Mentioned

To learn more about Florian and his team at Ads Venture go here: adsventure.de

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. All right, welcome to another episode of AI D2C WTF.

(00:28) Glad to have Florian Litter's German legend on the show today to talk about all the things that he is doing with AI and in his business and agency. Florian, how's it going, by the way? It's good to have you. This must be the most complicated last name you've ever said, right? The German, my last name. No, sounds very complicated.

(00:48) Absolutely not. Yesterday, I had Marin, who is from Croatia, and he is a very well-known Croatian marketer, and his last name is Isch Dwan Tick. I had obviously been mispronouncing this for years, and I probably just did again. So it was tough, you guys. Thanks for having me, guys. Glad being here. Yeah, I'm Florian.

(01:16) I'll just do this very quickly. I run an agency here in Germany doing paid social since 2012-ish. So quite a long time. We know each other since, I don't know, 2000, what? I don't know, 15, maybe? So long. Long, long, long time ago. And yeah, playing around with lots of AI stuff in the agency to find new ways to navigate through this AI shift, basically, for our clients and for ourselves. Yeah.

(01:46) So Florian, like, what are you, how are you using AI now? What are the things that you're doing that you've seen the most impact on? For us, a big breakthrough actually started last year. We did a team workshop, and we discussed about how can we make use of AI? What's the best way? What's the best strategic way of using AI? And we stepped back a bit, and we thought about how can we think of AI, of using AI in different roles, in different departments, and different use cases.

(02:18) And that brought us to, okay, we have creative. In our agency, when you run paid social as a brand or as an agency, it doesn't matter. You do need creative strategy. You do need surely some kind of copywriting. You do need design and video editing. That's the biggest part you do. And analytics and reports. And in all of those roles, basically, we developed workflows, tools.

(02:43) We're using multiple tools for that, that help us with strategy for strategy. And quite lately, two weeks ago, maybe, we implemented some AI agents that helped us to find new ideas, basically, for creative strategy done in cloud. We have workflows for image generation, and we have workflows for video generation.

(03:05) And when it comes to creatives, I do believe the best case right now is like a hybrid case where you use real content and AI content and mix this together. That's basically a quick rundown of what we do in each department. Cool. So there's, I think there's a lot of interesting stuff there. But what I also heard a lot of agency owners say is that it's when they start to see kind of real value out of it.

(03:42) And it's, it's easier to grasp. When you guys had this team meeting, and you're kind of decided how to go into this, what was the first kind of things you started doing? And what kind of tools did you start playing around with? I mean, that was back in June last year. So in AI world, that's quite a long time ago, I would say.

(04:01) So we honestly, we started mostly using ChatGPT, using deep research for creative strategy, finding new ideas, new angles, new hooks. But we knew where in which direction we need to go, because we know which type of content performs on, on ads. So that's, that's where I started being like an architect for, for prompt.

(04:22) So I was more like a prompt engineer and engineered different prompts to help us, yeah, make use of ChatGPT to find new angles on the strategy side. And then we played around with lots of image generation tools. I mean, back then the first big breakthrough, I think, was the image generation of OpenAI, which was not so good from today's perspective.

(04:45) Then Google introduced Nano Banana and from there took off basically an image generation and what we can do in image generation. And with video, it's still kind of okay-ish, I would say. I honestly don't think there is already a big breakthrough in video generation. There are new models like Sea Dance, which came out two weeks ago, I think, which is quite good and quite strong.

(05:11) But video is like, it's hybrid. So we have real content with, made with content creators, and then we mix and match this with AI content, which helps us basically to produce stuff that we couldn't produce with content creators or that they basically forgot to produce. And this solves a big problem. Yeah. So let's, let's get into specifics on this.

(05:32) So of the things that you've built thus far right now with your agency, what are the things that are the most high leverage and, and specifically like exactly how, how did you set those up? You talked about agents. Is that maybe where you want to start? I would say, yeah, I would say. So how is, how are you building them with Cloud? Like how specifically are you setting them up? Like with, you know, what do they look like? What kind of tools are you using? I would say it's, it's the agents, um, which are quite new because they are more on autopilot right now.

(05:59) Up until then, it was like, we need to prompt something, we need to wait, and we need to guide it a bit more. And now it's way more on autopilot. What we did is we created a database in the backend using Airtable. And in Airtable, we have like different informations about our clients, about the brand, about the products. And based on this...

(06:19) And what kinds of stuff are you giving them in Airtable? You're giving it like the, the name, the vertical, the website, you're giving it like the persona. What else are you putting in there? Yeah. Persona. And it depends on the brand, but sometimes you need to go down on product levels.

(06:38) Sometimes you can just say on the brand level, depends on the brand and each case. And based on this, we've created, um, yeah, two different agents. One agent is, that's, I would say that's unique to the EU because in the EU, in Meta's ads library, you have a transparency guideline, which means in the EU, you can see how much reach an advertiser had on one ad or the other ad.

(07:04) That's unique in the EU compared to the US. And based on this, my idea was, um, why can't we create an agent that always, um, analyzes the ad library and checks for ads with the highest reach from up to five competitors, analyzes those, and then pushes back angle ideas that we might be missing. So we always like monitoring competitor brands from our clients.

(07:31) Their ads library, we always see which ads, uh, or we see based on the transparency, uh, rules and ads library, which of those ads get the highest reach. And I would say in most cases, not in all cases, but in most cases, the highest reach means the best performance, not in all cases, but in most, uh, and based on this, we, this, this information, so the ads, uh, scraped using APFI, which is like a tool for APIs, basically.

(07:59) Um, we're scraping data out of the ads library. We are also, um, uploading, um, the images into air table, and we are also pulling the videos. The videos is then, the videos then pushed to whisper from open AI, which is transcribing the video. And then we have everything that's set basically in the video in air table. And then Claude is going for everything and is ranking. Okay.

(08:20) This is a good angle. This is a good angle. That's my idea, uh, for you guys that you create this or that angle that you may be missing this or that, or this is good by done by whatever type of brand that's quite helpful. So you're having, so the, the agent or the agent goes through and you're continuing to feed it all this information.

(08:39) And other than the tools that you mentioned, you're using Claude as the one that's plugging in air table, APFI using whisper. Are there other things, other tools in there that are helping like pull it together? And if so, what are those? It's, it's pretty much that it's a Claude, which is like the architect and which is building my ideas.

(08:58) Um, air table, um, APFI and whisper. Yeah, that's it for that case. We also have another case where we, so this is like the, um, the ad library agent and we, we have kind of the same idea. We had kind of the same idea with customer reviews and we are not pulling customer reviews from our clients. We are pulling the reviews from their competitors, which means we always see the top three positive and top three negative comments from the competitors, from our clients, which is kind of the same idea.

(09:33) We are, we always get ideas for like, okay, these are angles you're missing. These are angles that are maybe like a anti pitch angle, whatever, because they are lacking in quality here or there. You could go into that direction as an angle with, with, uh, for your client and, uh, basically, yeah, uh, get this information out of Trustpilot, TrustShops and Amazon.

(09:58) Also done with APFI and Claude and air table in the background. Just a follow up. Um, um, a lot of people I talked to today use Superbase versus, uh, air table. Um, I know they both do the same things. Uh, but what I'm interested in trying to understand is, um, um, what are you doing then with all the learnings and the data clock gives you based on what it's analyzing? How, how do you, how do you use that? So right now it's right now it's basically pushing, uh, the idea.

(10:28) So it's pulling this data every 30 days for each of our clients, not daily every 30 days, because you need new data that needs to be analyzed. And that's why we decided to go with every 30 days. And then it's pushing like a message into the Slack channel. Basically we have a Slack channel for each client, uh, in our agency and there, our agent is pushing a message with, I analyzed whatever 50 ads here, the top ads.

(10:54) I think this is good. This is good. So I asked Claude to score those ads or to score the reviews. Uh, and based on the scoring, it's basically sending us the ideas. And then we have a set of ideas and a set of ads that we might be, uh, producing. Are you then kind of looping back what is created in terms of how it delivers? I mean, is it like a feedback loop of, was it actually a good idea? This did this ad perform or is that maybe kind of maybe the next level of what you guys are thinking on? This is not done by AI yet. Um, this is

(11:28) done by our creative strategist. Um, and I think a creative strategist, a good creative strategist is always looking what worked in the past and is always looking into like what might work in the future. And this is basically just at the end, it's just in another angle that we're testing, but the idea is coming from AI and we save lots of time, uh, in research here. Yeah.

(11:52) So you have, so you have the, this agent set up. So the other stuff you have in terms of, uh, image generation and video generation, talk through those and how those are set up and, um, yeah. And what kinds of things they're, they're doing and what they're built on. Well, we played so much with different models and different tools out there.

(12:14) And we came to the conclusion that, okay, the most important thing is having good raw material, a good kind of imagery from each product to basically train a model or to basically use an image as, as a reference image, for example. That's why we started, um, a month ago, uh, doing photo shootings, AI ready photo shootings in a studio, which basically means we get the product and we, um, create images of a product in each angle with perfect light.

(12:46) Um, so we can use this image, this product image to train models or to use it as a reference image. That's where we are right now. Um, and then the tool we're using or the platform we're using is called, uh, kreia.ai. That's what we use, uh, kreia.ai with K, not C, not C, kreia.ai. AI. And in, in that, uh, that's like Higgs field, for example, it's pretty similar to Higgs field.

(13:14) Basically it's a, it's a wrapper. It's a kind of a wrapper, which, uh, um, is plugged into, uh, every model through the API. And in CREA, we can basically create images with nano banana, nano banana 2, uh, whatever, every, every version of nano banana, every version of, uh, the latest video models like C dance, for example.

(13:39) And then in CREA, we built, or we're building workflows in a way that we say, okay, we do know which type of imagery works as a performance ad. So for example, product enhance is classic one. Uh, each product shot in a hand from like a eco perspective is usually a top performing image ad. Um, and we created a workflow just to create multiple images of a product in different hands, basically different settings, different hands.

(14:07) So that's a workflow for us where we basically upload the imagery from different products. It's always the same workflow. And then it creates different images that are from our, that we know perform as an ad. So it's like the workflow is built on, built, uh, built in a way that we created each, uh, different workflows for each use case where we know, okay, this type of imagery works.

(14:29) Um, and, uh, yeah, that's for image and for video. It's basically my experience with video is like so-and-so sometimes it's quite good. Sometimes it's, um, slop, AI slop. And, uh, for our customers, um, I'm trying to not create AI slop. Um, that's why we started, uh, in a way that we try to, um, try to widen in a way, our B-roll library for video content in a way that we create content that we haven't created before with videos.

(15:00) And this is done kind of like an art director, I would, uh, art director, I would say. So we create different, um, different images based on the images, uh, the photos we've created, and then those images, we animate those. And then based on this, it's like a sketchbook, I don't know. Right. So we have different images, different images getting animated, and then we have five different B-rolls and these five different B-rolls are then fed into the video team and mix and matched with our existing content.

(15:31) That's, uh, what we do there. So, and so basically a client signs with you and they come and say, these are our products and you're, you look at the top products and then you make sure to load those into the like static workflows that you have, which is a product holding in hand. And they're the things that you have seen that have worked before.

(15:48) And then with the video, basically taking like animated gifs essentially. And then you're building those into the preexisting video assets that you have is like the hook. Is that essentially kind of what it is? Exactly. Exactly. Yeah. Exactly. Yeah. And, and you're going through, so when you're building these out and you're, you know, starting to build them new creatives and new creative direction and stuff like is, is there, there's the research phase that's taking place that we talked about before with the agent and that's then spitting

(16:20) out as well, some ideas for just the creative strategist or does the client also see those or like what's, you know, cause the innovation on not finding new personas and stuff, I assume maybe you're telling the client as well, but so maybe some of that's internal. I'm just curious. So what I'm trying to build is, uh, I would say for most processes, it's still human in the loop, which means we are still screening the ideas and we still say, okay, that's a good idea.

(16:46) That's a bad idea. Even with designs or with images that are created based out of those workflows, we always need to make sure that there's a good, like a mood board, um, at the beginning, which is like style trading for the AI, I would say done by human. And we always make sure that the output is basically, um, uh, controlled by human, um, to really make sure that this is on brand and this is not sloppy in a way. Be really clear.

(17:14) Sorry. One more question. So you're, you're taking the, let's say that you did that with video. So you take some of this stuff that the agent has learned, the mood board, you then take it to this software that you mentioned, or the one, I forgot what the name of that one is. That is kreia.ai. KREA.

(17:35) And then you say to, to kreia, Hey, this is all of the stuff that we know. Here's a, here's a preexisting video asset that we want to be added or want to be like included in this. Create the, a 30 second version of this for me. Or like, what are you telling kreia to do? You, you're speaking about videos, right? Yeah. Yeah. Yeah. Okay. It's like kreia is basically, it's no difference in using Google V or free or for whatever, or kreia.

(18:04) It's, it's basically the same model. Um, what we do is we, we, we create for videos, we create like a sketch board. So it's like having someone who's thinking of the video, we, which scenes do we need in a video? And we create images for each scene. This is based on the idea. And then based on this, we say, okay, we think C-Dance 2 is the best model to animate this scene.

(18:27) And then we have 10 different scenes. And those 10 different scenes is additional B-roll footage for our video team. That's how we, how we think about this. And the, the, the 10 different scenes are being sketched out by what you're learning from the agent. In some ways, yes. In some way it's still made by, by us, by our creative strategies.

(18:43) It's by you're just saying, okay, actually this is what we know. This is what the client says. And then like, here's the scenes and there, and these little scenes. I do have one good example, which is quite hard to, how to shoot as a video actually. So usually we, we, we still do lots of videos with content creators out there.

(19:02) We have roughly 300 that are working with us. Um, and we have a client that's selling socks, sports socks. The issue with sports socks is it's really hard to, as a content creator, it's really hard to shoot a video, wearing your socks, running and shooting a video from, from the back, uh, basically recording yourself running. That's very, very hard.

(19:23) So you definitely need a video team or someone else, uh, recording that person, which is expensive, which, um, makes costs going up. And what you can do is you can create this scenes or multiple scenes where a person is wearing socks and it's running basically. And the, video is, uh, recording this person from the back, from the side, whatever.

(19:45) This can be perfectly done by AI. And then you can basically mix and match the scene of whatever the content creator who's talking about the product with this B-roll footage. So that's quite a, quite a good example, I think. But, but, but, but then again, which I think is really interesting is that you're using that so your experienced team can, can make the decision if it's good enough or good enough and give feedback.

(20:10) So it's, it's, it's just like you're working with a AI photographer, uh, and the rest of the workflow is pretty much the same that it's always been. Is that kind of correct or? Kind of. I do think that human taste is still super important. Um, but everything else should be enabled and enhanced by, by AI.

(20:32) And, uh, that that's how we think about this. Yeah. I also built another quite fun workflow, something else I did. I did build quite a fun workflow, which is pulling the best performing image ad out of the ad account and creating iterations based of this best performing image ad, which is quite easy for AI. So it's basically downloading the best performing image ad, uploading the best performing image ad into Google drive done in cloud.

(20:57) Uh, then it's sending the image into cloud cloud is a reading basically what's on the image. It's creating new hooks basically. So text overlays for the image. This is then again, double checked by another, uh, um, prompt basically, because sometimes the grammar was wrong or the spelling was wrong. And then basically it's creating three different versions of the same image with different hooks and overlays.

(21:22) This is end to end automation of, of creatives. But from all what we guys probably know is that iterations are not like the thing where you should spend too much time on because of meta andromeda and that are there creative diversification. So I would not spend too much time on this. That's why I thought, okay, it might be a good idea to automate this end to end.

(21:42) That's, that's what you do with, with image ads and iterations. Yeah. It's pretty cool. And, and, um, are, are the, are these versions, um, performing well when you're testing them? Like the, the flow is working, but it is giving good quality as well. It's, it's working. We still double check every output because I mean, I would not upload random stuff into ads manager, at least not when I'm the one who's responsible, uh, for our clients.

(22:09) So I always want to have someone double checking this. Um, and yeah, their output is good, but, um, from everything we see before this cloud transition and AI shift, iterations are not the thing that are driving performance in ads manager that much, at least sometimes yes, sometimes no. That's why we, before we had this workflow, we decided, okay, we don't put, put much effort into iterations just because of that shift on meta side.

(22:33) And we spent more time finding new concepts. And that's why I thought it might be a good idea to have to still like autopilot in the background who's creating animations, but we don't spend human time on this. Yeah. Yeah. And how are the clients reacting to, to this kind of shift? Do they, do they know, do they care about it being more AI in the picture? How, how are, how are they feeling? One year ago, I would have been afraid, honestly.

(23:03) Um, and I thought, um, that, um, that maybe clients don't, um, at least for, I'm speaking now for the German speaking market, which might be different to the international market, just to be, just to have this disclaimer here. And looking at the German market, I thought that, uh, most people think that we basically spend less time managing their things, which is not true at the end.

(23:27) And, uh, then our, the perceived value of what we do as an agency is going down. That was my, uh, very, to be honest, but turns out it's completely different. People really love when we do this. People are really open. Uh, people, all clients always, uh, yeah, they, they, they're super happy when we create new stuff.

(23:49) For example, another thing we do, and all of our clients are, are really loving, loving this is we, we create CGI type of content, which is basically you take the product and you put it somewhere in front of, I don't know, the Empire State Building, for example, that's trademarked, would not do this, but it's possible technically with AI.

(24:09) So you take your product and you put it somewhere on a monument, someplace that most people know. And this is the CGI type of stuff, which is quite cool. It's still on brand and people love this when we do this. That's one example where we understood that our clients really like AI stuff. Before I was hesitant and I was skeptical, but right now I'm all in.

(24:34) I'm going all in into this and I'm pushing this really hard, um, to the team and the team is really open. Um, our clients are super open. We do lots of content around this and we are very, very open to our clients that we use AI in different scenarios. They trust us that we are not creating AI slop. Uh, and I take care that we are not doing this.

(24:54) Um, and that's why I think it works quite well. So if it's done right, AI basically makes the work that you're doing more effective because you're able to give the client more creative options and therefore more scale, right? Because scaling is so much dependent upon persona development and the expansion of matching personas into that.

(25:23) Um, what do you think in terms of places you're spending your time and what you're seeing and hearing from other leaders? I think there's, there's a lot of people throwing shit against the wall right now, but what is your opinion about the future of this moving forward and where you are spending time and where you'd recommend others spending time? Because I think a lot of us initially with this have gone into better agency owners have gone into spending time on reporting and automating the reporting and spending time on creative iterations and

(25:57) obviously building up more iterations and workflow and processes around that. The next phase of this to my opinion, I will, I won't poison the well. So I have an idea of like what I think is going to happen with this, but I'm curious of your opinion of where it's, where it's headed and where people should be spending their time.

(26:14) Um, you, uh, you mean spending time as an agency or in general in, in this digital market? As a marketer, let's just say, as an agency, you could, you could certainly answer it any way you'd like. Um, I do think, I mean, there's a, there's a saying, and this is quite common that the person using AI is definitely outperforming the person not using AI.

(26:33) So there's no way not using AI definitely. And I would be curious. I would be open. Um, um, and I would, I mean, at the end I, I would spend time thinking about what's actually a good system and how can I connect together multiple, multiple things, databases, tools, whatever, to find a good and effective workflow.

(26:57) So being more like an architect being more like, uh, I mean, pretty clear, you need to move from, uh, the day to day work more to a strategic work. I mean, that's nothing new that happened already with media buying five, six, seven years ago with iOS and every, every change there. Um, this is, this is, um, accelerated by AI and you need to, you need to be the one who's really connecting multiple dots and maybe multiple channels insights from multiple channels.

(27:25) For us, this means we, we are, we evolve more into like a consultancy, which is also doing agency stuff basically for our clients. So we help with multi-touch attribution, cross-channel, branding, upper funnel, I don't know what else, which is usually that's not what we do, but we know this stuff and we can help with this stuff and we really, I think with AI as an agency, you have the option to really cut down costs for your clients.

(27:58) Um, and that's what we try to do with the photo shoots we do. This is a photo shoot you do once, and then you have perfect imagery for endless AI creations of your, of your product. Um, and that's how we try to help being more agile in terms of content creation. Um, which basically means you can prompt your, your product into every, every situation.

(28:22) And before you are, you would need to create a photo shooting. Um, that, that, that's how I think about this in general, I would be interested in your take, uh, because I mean, the end goal of, I would say every ad platform and also meta clearly is to automate ad creatives and to basically give us your money. We do everything for you.

(28:41) What do you guys think? Do you think that's, that's happening and when would it happen? What do you think? What's your take on this? You started the loop. So you just, just, uh, what's, what's the next phase and also specifically around these platforms and automating everything? Yeah. So I think there's a couple of different pieces of this.

(29:08) One is as it relates to the way you'll use it as a marketer right now, it's been used in silos. So we've been utilizing it in creative because that's where so much of us spend our time in terms of scaling an account. I think that it'll continue to expand into utilizing it for full funnel. So one of the most powerful things that we can do is build a better offer as build better landing pages that match personas.

(29:28) And then the ads match those personas too. So that it's a full thing where if you have a particularly, and then you, and then you cross reference this with financials. So you have a product that if you're selling water bottles that has a better margin than a product that if you're selling microphones and looking at things on my desk, um, then you're going to push a, the water bottle more and AI will say, Hey, look, your margins are better on this product and you have more of this in stock and your new customer acquisition on this particular

(29:56) product or this particular funnel is X over the last 50, 60 days. I recommend that you start doing more creative for this and it will then spool up persona development that's around the water bottle angles that you have in the markets. And then it'll have corresponding landing pages or corresponding advertorials that are built and you'll be able to say, yes, try this idea.

(30:20) Um, and then it basically builds from there looking at, you know, competitive analysis and continues to like go on the things that you've been talking about. So I think it'll become a more full funnel play. And I think that that also extends to agencies. I think that where it comes with agencies is really going to be, how are you making the case for AI with your clients in agencies to say, look, this isn't just me messing around, right? And Florian, you talked about AI slop.

(30:45) This isn't just us trying things. And I think to some degree in agencies, this is actually people messing around. But I think right now, what you want to try to go forth with is look, we're going to, this is allowing us to go into deep research with more ideas, and it's allowing us to build our process better so that we get to spend more time effectively analyzing data for you and doing and being a better advertiser.

(31:07) It's not just advertising all products and saying you have a four row as it's like looking at them by category, looking at them by contribution margin, looking, you know, looking at sort of the results in relation to the financial metrics and calculations. And if you're able to do that, utilizing AI as an agency moving forward, you become a true marketing partner.

(31:27) You're not just one person that's building the meta ads, right? You're doing a lot of other things. This could even go into things like building incremental channels, right? Where, look, we have this idea, we're going to launch connected TV now, and this is how we're going to be able to do that. So, you know, I think this is, it's headed in the direction of making it more effective with more people and, or with less people involved, I think.

(31:52) But with the people that you have, it's going to be more data that's going to really actually be able to really help folks. So that's kind of what I think. I don't know. Thomas, what do you think? I agree. And I think that, which I also feel like Florian's point in this whole conversation is around that you're still going to need real people with real experience, understanding the data, understanding the workflows and communicating it clearly to the clients.

(32:24) So I think that people will be more and more valuable, and at least people who have experience in this industry from before. And I also think that it's going to be harder and harder for younger people to kind of get up to a certain level and get that gut feeling experience because, you know, younger people are just agreeing to whatever AI is telling them more than us grumpy old farts who are just like challenging and no, not that way.

(32:55) And you think like this and, you know, all that stuff. So I definitely think it's going to be more of the whole funnel. And I think that Meta, Google, everyone is going to try to build that platform. But I think that the more the agencies can take ownership to creating their own software and their own platform and plug into the different APIs, I think that's the one who can do the best job for their clients going forward.

(33:25) It's quite funny because I was playing around with Cloud, which is basically, it's pretty easy to duplicate product detail pages using Cloud and then change something and messaging on a product detail page or any landing page. So it's pretty easy to spit that out because I had the same idea in like, okay, we have the messaging on the creative, but it's not really, really matching the landing page.

(33:49) And the idea was to basically create a system that's that's using the existing page and changing the headline, changing the image to, to have a better match with, with ad creatives, which could be done quite easily using Cloud, honestly, and Netlify. But yeah, that's a different story. Yeah, I mean, so much of it is just like trying and testing and I'm thinking about it, but I think you have to make sure that you're trying and testing things in a strategic framework that add into the greater whole.

(34:20) So it's not just like, oh, it's like, you know, so much of this is like, you see this on X, oh shit, I got to try that. You see this on X, I got to try this, I got to try this. And it's like, you can try it if it's, but you also have to have a destination because otherwise, you're just taking all these side journeys that aren't necessarily improving the overall things.

(34:34) It's like, where are the hard costs of our agency? Where are the hard times that were, or where are the hard costs of working with a particular client? You know, is it client communications? What are the things that we can do to make that more efficient and effective and saving money there? So I think it's like, if that contributes to that goal, then absolutely. Right.

(34:52) But yeah, Florian, I appreciate you joining us. Florian will be able to answer any questions. If you have them, you can email me andrew at foxwelldigital.com. And all of his details and notes, if you want to follow Florian, are going to be in the show notes. But thanks. Thank you for being here. Thanks for having me guys.

(35:08) Bye. Healthy options. ある程度 最初 使用

Andrew Foxwell | Co-Founder of Foxwell Digital

Co-Founder of Foxwell Digital, a social media advisory firm focused on honesty and transparency across paid social. Through its membership offerings, online courses, account management, and consulting services, Foxwell Digital helps brands and agencies make better decisions and scale sustainably.

https://foxwellfounders.com/
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