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If you are a marketer in sales or in go to market and you truly want to call yourself AI native,

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you need to watch this episode. On this episode of Human in the Loop, the most actionable AI show on the Internet, I talked to Cody Schneider who truly is a 100 x marketer, and he shows you his systems,

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his process,

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and everything that goes into him being probably the most effective and AI native marketer I've ever met and what the future of growth marketing looks like because of AI. Let's hop into it.

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Okay. So we I'm gonna start

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with a tweet that you put out

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that blew up. It's what got us connected to do this.

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So you said,

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I don't think you understand what is happening in GTM engineering right now. I want to try to explain this to you. What someone can do in a day with Claude code, plus APIs, plus plus n eight n, plus railway.com,

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plus GitHub repo, plus Skill MD files is what a Fortune 500 would do in a year. Today, I made 40 Facebook ads, a 100 landing pages, wrote three guest blog posts for backlinks,

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booked myself on four podcasts with a cold email automation,

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wrote five help desk articles, added two vlog vlog videos, scheduled 25 tweets across accounts, wrote two pieces of scripting software to give away as LinkedIn lead maggots

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maggots. Magnets, and baked bread from scratch and made katsu sandos with my chief of fiance.

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As I write this, I still have four hours left in my day. I don't think you understand what is happening in GTM engineering right now. And as of recording this, it has 315,000

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views. Now, I will say,

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once we schedule this and people I think had a lot of feelings around your tweet, there I I think you told me this. There was actually a a Polymarket or call sheet bet around if Yeah. I'm wondering if this was like possible to do or not basically. Which I thought Basically curious. So So for the for the for the people who read this and say, Cody has to be a fraud,

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what is your response to them? I'm just doing I don't know, man. Like, with everything that I'm doing, it's like, this is what I'm with

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and seeing work right now, and I just share it in public.

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It's I think for a lot of people that have never interacted with my content, they're like, oh, it's a bunch of just cap, like, full stop or like, yeah.

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Again, this is just what's working for me. Like, I just kind of live tweet, like, here are the things that are being successful based on my go to market strategies, like, with my company and with what I'm seeing with friends companies who I talk to. So anyway, yeah, hopefully today,

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what like give you all the tooling you need to be able to do this yourself. It's totally possible. Everybody that is on this call will be able can do this. Like, it's not you don't have to have any specialties or like any like, you know, specific knowledge to get started on what I'm talking about today. And before we hop into it, like,

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how,

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like, how profound is what's happening in

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go to market and go to market engineering right now? Like, what is the impact this can have on someone's career or their business if they get this system right? I mean, this is one of the most searched for roles right now. Like, I've gotten five

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messages in the last, like, seven days from founders that are like, yo, I'm trying I like I saw this tweet. I'm trying to hire this person. Like, who can you intro me to? Right? Basically, like looking for these skill sets.

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Just to give you context, like I've worked in startups for a long time. Early stage is what I specialize in. Like, to do this type of work, like, I would have had traditionally to go out and hire a team of like, you know, whatever 20 people to

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execute on this.

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In contrast, it's just like it's just me now. Right? Like, this is the difference that this has evolved into. And, like, this is how companies are starting to, like, leverage all of these tools is to be able to basically compound their skill sets. I'm like, your domain knowledge that you have combined with this is where the real magic is. Like, if you have a deep expertise in one thing and you can you understand the systems and the processes for that, and you can translate that into code, which is, like, literally what we're doing, and then use this as a system, like, to go and do activities for you. Like, that's where the real, like, power of this comes from. So I I I

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I don't really have words for it. Like, I'm actually losing sleep. To be totally honest, like, I woke up at 4AM this morning. I was like, shit. I think I can do this, like, this totally, like, different thing.

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I my friends are, like, also like this. Like, you know, the the people I talk to on a weekly basis that are in growth that we just share, like, what is working? Like, what's happening right now? What's the meta that exists, like, currently in the market? They're all just freaking out basically because the amount it's like, I I was selling you off this call, like, before we started, Alex. Like, I I have a friend. He works at a start up. Like, they're being too slow on shipping what he's doing at the company. So he's basically in this waiting period. He's picked up, like, three side gigs doing growth consulting for them, and he's shipping more using this type of system than what he's doing at his day job. Like, that's how, like, the

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velocity that you can go at. And I know there's, a ton of people that are like, oh, it's all slop. It's all it's all you can do this really effectively and we're gonna like talk to that I know on the like beginning of the conversation. But

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Two two

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things before we hop into it. One is, are people going to know how to make killer katsu sandwiches by the end of this? I can give you the recipe. I mean, it's super simple. It's basically just like get good chicken from a butcher,

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Yukus Paco,

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and then just make like a tonkatsu sauce to put on the top of it. So Mike Love it. My fiancee's

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family is Japanese American so we get we kinda get hooked up in that that neighborhood. Got Cody is a renaissance man. Or as someone in the chat put it, the the Ehrlich Bachman of growth.

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I love you. I'm sorry.

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So good.

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I'm gonna stop talking. Let's fire this thing up. Where do you wanna start? Yeah. I think I think just to begin with, like, just a quick history of what is GTM engineering for the uninitiated.

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So this really kind of started to happen in, 2023.

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Originally,

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it was just like for outbound motions. Right? So Clay really kind of solidified this as a job function. And it was really focused on like, rather than thinking about can't

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the work that I'm doing to do distribution as campaigns, let's think about it as like systems and processes that are directly, you know, trackable, attributable, and treating this almost as like what a software engineering function would be where it's like, hey. We do week long sprints. We look at the data. We analyze what's working, and then we re repeat those processes.

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In the last couple of months, it's

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totally had an evolution. So now it's not just outbound. It's everything. Like, you know, it's it's inbound. It's paid ads. It's organic SEO. It's like organic content. It's you you you name it and there's not a thing that it's not touching. And this has really become kind of the foundation for, like, how these, like, early stage companies are doing really effective distribution and growth strategies

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is trying

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to build out these systems and processes. And then, like I mean, I'm seeing people incorporate these into their code bases as well, right, where it's like, okay. I built this side project thing.

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It's now running the entire, like, you know, blog, like, organic content strategy.

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And now we're gonna build this into their core code base of the company, the entity, you know,

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and then it's it lives on in perpetuity. It's like this agent that's just kinda working continuously in the background that's in the core code base. So that's And and so you do you think do you think the phrase GTM engineering is a useful or valuable phrase anymore given that now to your point? Like, it started as

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treating

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outbound sales like software engineering, treating it more like a science than an art. Now you're basically saying it touches sales,

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it touches marketing,

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and now even, like, if you look at other companies, they're hiring. Like,

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yeah. Now it touches like basically, I've heard GTM engineers refer to as people who just like are truffle pigs of inefficiency in a business, and they build

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agents and things for any function of the business. So do you think that phrase even has value anymore? Yeah. I think it's just the the same names, the exact same person that's always existed for the last 10 or twenty years. Like, it was a growth hacker. Was a head of growth, and now it's a GTM engineer. It's just the tooling and, like, the activities they're doing here are the exact same. Like, if I look at my day to day, like, if I was to zoom out, like, I'm doing the exact same type of work. Right? It's like I'm basically trying to find marketing and distribution arbitrage within the system, like figure out the positioning for my company so that the audience is receptive to it. And then I'm going to go and basically, like, build out processes to go execute on that and then, you know, have some type of data analysis over the top of it to actually track what I'm doing. It's not exact same thing. I'm just saying changing the underlying tooling.

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So

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I don't know if it like, GTM engineering really, like, encapsulates everything that you can do. I just think that that is like how people are talking about it and describing it. And it's also just like one of those buzzwords that are for for currently. But if you're in any role that, like, gets people to buy things,

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you can do these exact same strategies. Like, whether that's sales, whether that's marketing, whether that's customer experience, whether what whatever it is, like, whether that's rev ops, it doesn't matter. You can all, like, use basically these this foundation as a way to, like, do your work, you know, more quickly. Well, let's now that people have a foundation of what GTM engineering is, let's let's give people the sauce. Where do you start? Yeah. So to begin with, like, how I structure it,

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Cool. So to begin with, like, what I've done is I just have this

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file that is on my local machine that's in documents that's literally just like, this is what I live out of now.

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This isn't organized, and I know there's an engineer that's gonna see this and be like, this is disgusting. I totally agree. It doesn't matter. It works for me. So, basically, what I've done here is I've

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like, you can start with an empty file, and this is how you begin this whole process. It's basically make a file that you're going to live out of. And the first thing that you're going to do is create an environment

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file.

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It is called an EMV file. This is where all of your API keys are stored, and this is how you're going to go and interact with all of the tools that you use within your stack. And this is what I'm about to show today. So what I've done now is I've CD'd or I basically moved into this directory. So

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documents forward slash graphs growth agents, and then I'm gonna start Claude. I'm just gonna assume that you know how to, like, install Claude code onto your your

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your applicate or, you know, onto your local machine. If you don't know how, there's tons of tutorials how to do this so we're gonna skip over that basically. Cool. And can you just zoom in a bit just Absolutely. No problem. Yeah. So Thanks. So now that I'm in this folder and I've got Claude open, this is basically where my work starts from and this is how, like, I go about my process of, you know, whatever it is that I'm doing. So a lot of the times how I'm doing this is I'm spinning up multiple Claude agents

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and I'm putting them in different desktops. And then I'm just moving between those desktops

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as I'm do as I'm doing work other work in the background. So, like, for example, for the Facebook ads,

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the first you know, one of the campaigns that I'm running right now is basically a before and after. So I'm just gonna bring up

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this,

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like, software that we wrote for this. So give me a second. I just gotta remember the name of what it is, but I just actually gonna transcribe. So it's the Facebook ad software for the static ads before and after. Can you start this and run it locally?

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So what I just did there is I used a transcription software called Super Whisper to transcribe that out. I'm now gonna tell Clogcode to basically open up this software.

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What it understands

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is the file structure, everything that I've done previously so it can basically go and bring this up for us. And so this will be like the first thing that we do today is basically

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we're gonna I'm gonna show you how I built out this template

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that is for ad creation

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and then show you how I'm basically using this to go and then do bulk ad generation. I'm just gonna walk you through this entire process

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and then show you how I would, like, set up an AI data analyst to basically watch this campaign that I'm doing for testing and what I would use for measurements of success. So this whole thing here that you see is entirely,

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like, AI generated.

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This is actually components. So if I was, to zoom in on this in Hubbard, this is, like, React components. So this is code. So this came from an epiphany I had that, like, all design is actually just code on the under like, if you go into Figma and you're doing any design, it's just code that's under the hood. So why can't I just make these outputs using

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React components?

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And then I use this library called HTML

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to Canvas.

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And this library is basically a way to export

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that

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React component as a downloadable PNG.

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So built this template out, basically go back and forth with Clog to, like, create that template. Once I've done that, I can then use this to do bulk iterations. So then I created the sec or, you know, the separate function

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that enables me to go and bulk generate as many different variations.

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So it's just text variation changes. But why would I be doing this? I'm basically trying to

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test different angles that I can talk about the same product from to understand the positioning.

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So how would I go about this process to actually,

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like, you know, create that output?

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So just for, again, today, we're gonna be using my company, Craft, as, like, the the the company that we'd go about this for. So what I would go and look for is I'd use Perplexity to help me identify I I've now built this into Claude. Like, I have an a file talking about my MCP, but just to zero to one this process, this is what I would do is I would basically go and I would search something like,

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what are the pain points

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that's an

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AI

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data analyst

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for GTM

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teams?

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Do something like what are the pain points that an idea is would solve,

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and then what are the outcomes?

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Actually, I'll just do this transcription. So what are the outcomes

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that an AI data analyst for GTN teams like, what would that GTN team want? What would be the outcome that they would want?

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And I'm gonna use this as source material for the ads that I'm going to create. So I'm then gonna put this like tag to like search Reddit for this

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to pull in actual customer conversations.

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So what I found is that when I do this, I'm using the language of my target customer. Like here's their actual pain points

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and the actual,

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you know, outcomes that they're looking for that I'm then going to go incorporate into the bulk production of this ad creative content. So I'm talking in the language that's going to be most receptive to them. At that at this point, I would pull this out. Again, you could use a you know, you could use Claude. You could use ChatGPT for this. This is just what my workflow looks like. I would then go to Claude, and I would say,

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you know, actually, honestly, I'd probably just drop this into

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this chat now. So I'd drop this in as context, and then I would say

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brainstorm

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we'll say 40 ad

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titles

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and

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supporting paragraphs

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based on the source material.

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And then it's basically going to take that into context. It understands that it's interacting with this code that I have written or that we've created.

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And then it knows, okay, this is what we're trying to basically like change within this.

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It's gonna create those

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title and subject or title and supporting paragraph variations, and then I can just say go and do the bulk creation of these ad creatives.

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At that point, it's gonna make the zip file for me of all those variations and then I can upload that into Facebook ads.

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This is something I'm like actively building out right now is basically that connector. Like, I don't have this built yet. It's halfway done. I was trying to have it ready for today, but it's not.

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So I'm you're just basically going to then

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like, within Cloud Code, I could basically say, hey. I wanna upload this zip file or upload all of these images into this specific

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campaign so you can drop in this campaign URL.

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That uploads them in.

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And then,

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basically, what it allows for is you to, like it puts them into a draft. I can change all of the

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URLs,

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like, that scale that they're sending to change the subject lines. So it's written these. Right? And at this point, can say, okay.

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Now use

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okay. Now use the bulk

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generation for the ads to create ad variations of each of these

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and hit send. So while this is working, at this point, I would spin up another workspace.

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So I'd go then to documents again

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and go to graft agents,

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and I'm gonna start Claude again.

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And I would move this over to Can we just course. For

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one sec, can we just pause for a sec? Because you're like, you've covered so much good stuff, and I just wanna make sure that

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I'm on the same page with everything.

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Okay. So basically, what you've done like, the whole goal here is you're running a ton of meta ads for your business, and your bullet your whole thing is, like, the bottleneck historically

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was getting enough good creative to test and rotate in when you're running

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paid marketing.

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But now, basically,

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you have the ability to,

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one, do research into

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your

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ICP

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for your business and see, like, what are actual problems or pain points that kind of, like, the the end buyer for the AI data analyst

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for GTM.

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What are the pain points they've actually talked about online, which is why you searched Reddit? You then use that output from Claude

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or for sorry. From Perplexity,

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but you could do with any LLM.

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You feed it into Claude where you then have Claude create kind of, like, the

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the h one and any of the copy for the ad,

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and then you use all that plus this this piece of software you've already built to basically build 40 variations

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of the existing ad you have. It's not connected yet, but ultimately, you're gonna have org connects where those 40 ads just get uploaded

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into your ads manager and meta. You can go through and decide which ones you wanna set versus not.

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Yeah. Aria, I can just have AI tell me which ones are the best like performing. Right? So Yep. This is And like and a few people have had a question here which is like well, there's been a bunch of questions, but the process so you already have this thing built. Yeah. That is building the ads for you. I think people maybe have question like how hard is that? Like could anyone Do that in about twenty minutes to just give context. I basically was like, build me like an bulk ad generator.

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Like, so this this I built this first to visualize it and it like has base so I gave it an example of an ad that I had seen previously. I was like, hey. I want you to make a template based off of this. And then I just went back and forth with Claude. So install the Claude code skill that's called UI design.

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If you just Google it, that will come up.

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And this will just, like, help with the outputs,

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like, from a quality standpoint, just from, a design standpoint.

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But this this whole thing that you're seeing right here, like, this whole interactive thing, this was, like, two prompts basically to get this live.

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And then

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the bulk generator

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took a little bit more, but it was just going back and forth, basically explaining the outcome that I was anticipating.

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And this whole build was about twenty minutes to build this infrastructure.

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Awesome. Cool.

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Okay. So I've now created all those variations.

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And I I just wanna zoom out to you like why are we even doing this? Like, why am I making all these variations? I I don't know what's going to work on Facebook ads. Right? I have,

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like, gut intuition on what I think is going to, but how

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like, what the audience or my audience is going to be most receptive to, I I the only way that I can identify that is through testing. And so by doing all these testing variations,

00:20:25.485 --> 00:20:42.890
that is, like, why that's how I'm going to see, like, what the audience is most receptive to from a positioning standpoint. Once I find the those winners. Right? And I just have, like, examples in here to show you this. Right? So, like, this is the CPC's 30¢ on this one in comparison to 53 and 85 on these other other examples.

00:20:43.530 --> 00:20:47.610
I can then say, okay. Well, what does that what is that messaging on that specific ad?

00:20:47.850 --> 00:21:03.825
How do I go and remix that messaging across different formats? So I would then take this this messaging from this ad, and I would go and I would bulk generate, for example, maybe UGCs to to do a different ad format. So this is again something that I'm building out actively right now. It's basically

00:21:04.305 --> 00:21:06.545
like plugging into the HeyGen API

00:21:06.800 --> 00:21:08.960
so that I can then go and

00:21:09.120 --> 00:21:10.960
bulk create creative

00:21:11.280 --> 00:21:11.920
for

00:21:12.320 --> 00:21:12.960
the

00:21:13.920 --> 00:21:32.095
like, based off of those winning formats. And, like, I've already I'm already doing variations of this, like thousands of them. Right? Like, if I could just continue to scroll. So all I'm doing is taking the workflows that are already working for me, and I'm just trying to automate as much of those as I can, right, by using this tooling so that it's in the background basically,

00:21:32.175 --> 00:21:39.650
you know, functioning on this. So alright. So it's completed that. Right? At this point, I would go back. I would go to that bulk section.

00:21:39.890 --> 00:21:45.010
I could download those those files. I don't know if it updated this. Maybe it's only showing the first five.

00:21:45.650 --> 00:21:48.475
Or yeah. It's only gonna do these five. But, anyways, this is

00:21:49.355 --> 00:21:55.835
we could go back and forth basically to be like, okay. This oh, so this zip folder is in bulk ads comparison at zips.

00:21:57.515 --> 00:21:58.635
Add these

00:21:59.595 --> 00:22:00.875
to the bulk page.

00:22:01.710 --> 00:22:03.630
Just say forward slash bulk

00:22:04.270 --> 00:22:06.510
dot html so I can download.

00:22:07.950 --> 00:22:13.630
And then while that's working on this, this is where this starts to compound is I would go and I would start on another process.

00:22:14.185 --> 00:22:15.385
So I

00:22:15.385 --> 00:22:24.345
found a winning ad format that's working for me. Cool. Now what I wanna go do is I wanna go spin up landing pages that are dedicated to those winning ad formats. So

00:22:24.745 --> 00:22:28.985
what I how we've structured this is I use this software called Strapi.

00:22:29.380 --> 00:22:35.780
So Strapi is an open source CMS. You can run this. This is like actually how we've built this on graph.com.

00:22:36.580 --> 00:22:49.635
So we use Strapi. It has an API endpoint that I can hit, and this allows for me to go and create, upload and create blog content, landing page content, and whatever other content formats that I want. So you basically create

00:22:49.875 --> 00:22:52.115
a content format within Strapi,

00:22:52.195 --> 00:23:17.485
and then I'm going and interacting with that through Cloud Code. You could do this with any CMS. Like, you could do this with WordPress. You could do we just use Strapi because it's, like, infinitely scalable and we can self host it in the long term. So if I have a 100,000 blog posts that are on the site, like, this is a way that, like, I can do this at that scale at a super cheap cost. So for these landing pages, I already have a template that that exists.

00:23:18.205 --> 00:23:22.045
And all I wanna do is change the the the title and the

00:23:22.510 --> 00:23:30.670
the it's basically the homepage of the website that is just like built into a templated format. So it has this, like, h one and it has this supporting.

00:23:30.750 --> 00:23:33.950
So say I find a, like, Facebook ads

00:23:35.310 --> 00:23:39.495
angle that is working. I could then go and bulk generate those

00:23:39.655 --> 00:23:40.695
landing pages.

00:23:40.855 --> 00:24:00.870
So this is one way that I would do this with Facebook ads. The other way that I would do this is I would actually extract the keywords that are converting from Google Ads. So what's actually creating the sign up action or the payment action, and then I would go and build these landing pages out at scale. I used to do this manually. I now, like, just use clog codes to do this. Right? So what I'm gonna do is, like,

00:24:01.270 --> 00:24:02.150
open

00:24:02.630 --> 00:24:03.910
the landing page.

00:24:04.885 --> 00:24:10.005
First, let's just do this. Open the landing page directory. We're gonna build some landing pages together.

00:24:11.205 --> 00:24:14.085
And we'll get that started. As you're as you're doing this,

00:24:14.405 --> 00:24:16.405
one question I saw from folks

00:24:16.965 --> 00:24:17.605
is

00:24:18.220 --> 00:24:26.700
how much do you have to spend? Like, much are you spending on meta to feel confident in these tests you're running before you kind of double down on winning creative?

00:24:26.940 --> 00:24:35.535
Yeah. So, like, we haven't spent a ton to be fully transparent. Like, we're super early stage. I, like, literally figured out the positioning for this brands like

00:24:35.615 --> 00:24:36.655
two weeks ago.

00:24:37.455 --> 00:24:57.680
Like, we we started out as really broad. Like, we're this AI, you know, business intelligence software. And then we funneled down into, no. We're AI data like an AI data analyst for GTM teams because we found this to be a massive pain point when they're in the market. Or it's like, hey. You're like, you have 10 to 50 people and you don't wanna hire a data engineer, but you need a way to unify your data. We're the solution for that basically.

00:24:58.720 --> 00:25:04.975
So it it really like, how I approach the structure of my, like, Facebook ads campaigns,

00:25:04.975 --> 00:25:12.495
well, this is just how I do it. There's a million ways to do it. This is how I structure it. So I'll test all the ad creative against each other in a click campaign,

00:25:13.070 --> 00:25:15.870
and then I'll look at what has the cheapest CPC.

00:25:16.110 --> 00:25:30.515
And I can run, you know, we'll do like a $100 over a three day period to see which gets the cheapest CPC. At that point, I'll take those winners that have the cheapest cost per click, which is typically an a leading indicator that once I move them into a conversion campaign,

00:25:30.835 --> 00:25:35.155
I'm gonna get a cheaper cost per action. Like, this is just the what I've seen historically.

00:25:35.315 --> 00:25:44.050
So I take I test them basically in a CPC campaign against each other. I take those winners. I spin those out into their own conversion campaign,

00:25:44.210 --> 00:25:47.490
and then I give them their own dedicated budget that they're running against.

00:25:47.730 --> 00:26:17.520
And this is how like a way that you can basically test creative. Like, you know, imagine testing 200 different pieces of creative on a monthly cadence to find those winners so that you're always refreshing the creative that you're, like, adding to your your your ads platform that you're using. Same style, some functions with Google Ads as well. It's basically like I'm just constantly looking at the keywords that are creating conversions or like getting the cheapest CPC in relation to Yeah. It's it's kind of like this is the paid marketing equivalent of,

00:26:17.920 --> 00:26:18.480
you know,

00:26:18.960 --> 00:26:27.855
I know Gary Vee talks about this a lot or even if you look you think about like some of the best non fiction authors say, like, even think about, like, Morgan Housel or, like,

00:26:28.895 --> 00:26:30.255
Malcolm Gladwell.

00:26:30.335 --> 00:26:32.735
The way they didn't start with books.

00:26:33.055 --> 00:26:35.295
What they actually started with was a tweet

00:26:35.380 --> 00:26:39.860
that performed well. That tweet that performed well, they turned into a blog post.

00:26:40.180 --> 00:26:44.260
That blog post that performed well, they repurposed a bunch of ways.

00:26:44.500 --> 00:26:47.940
And then ultimately, like Malcolm Gladwell's book

00:26:48.745 --> 00:27:00.025
I can't remember. Was David and Glide or another one. Literally, it's just a article from The Atlantic or The New York Times that performed exceptionally well that he turned into a book. Morgan Housel's book, Psychology of Money, is just a repurposing

00:27:00.025 --> 00:27:07.070
of his best performing blog post. But it's the same concept of how do you, as low resources humanly possible,

00:27:07.230 --> 00:27:09.710
test something before you know that it works,

00:27:09.950 --> 00:27:15.550
and then put more resource into it. And so the point we're at now is, like, you've run all these different

00:27:15.790 --> 00:27:16.750
derivatives

00:27:16.750 --> 00:27:26.355
of ad creative and meta. You see what works well. And then once you know what works well, then you start putting more resource into how that messaging shows up in other parts of the funnel.

00:27:26.835 --> 00:27:38.500
Totally. And I I also think that like the creative doesn't have to be perfect to begin with as well. Right? Like, we have these 40 variations that we just generated. Right? I'd go. I hit download. But the variations

00:27:38.740 --> 00:27:43.620
like, I'm just gonna go back to the core of this while that's running in the background.

00:27:44.020 --> 00:27:45.140
The variations,

00:27:45.140 --> 00:28:07.600
like, once I find a winner, I can always come back to this and have a human touch this up and improve it. Right? Like, people, for some reason, they get stuck on, like, oh, this isn't malleable and, like, the Internet, you can't just, like, iterate on top of this. This is how software engineering has, like, functioned for the last, yeah, I just if we're since the dawn of everybody doing, like, what we're doing within software. Right? You

00:28:07.840 --> 00:28:34.260
gotta think about it in that capacity. We now have like, for example, I see this with AI avatar UGC ads all the time where they're like, oh, I can tell that it's AI avatar I'm like, great. You can tell. Some of the best performing ads that I've seen have been AI avatar ads. And then you know what works what's even, like, more interesting is when we take that ad and then we go and we use, like, v o three. So what my process as an example is I would go and I would ball crate ads with HeyGen,

00:28:34.260 --> 00:28:44.100
and then I would test them. I would find a winner. I would take that winner. I go to v o three, and I try to make a better version of that winner with that same ad script. The concept is what you're testing.

00:28:44.420 --> 00:28:45.940
The the the medium

00:28:47.505 --> 00:28:54.305
platform that you put it on to put it out in the public can can evolve and can change. But what I'm trying to get to is the messaging component,

00:28:54.305 --> 00:29:22.785
and this is a way that at scale I can do that. And then, okay, I find that the v o three one, that's not performing as well as I think a human could do it. Then at that point, I can go hire a human. They read the ad script and we turn that into an ad. But what I'm seeing a lot of the times is that the iteration that I can do, I can get a better I can move faster than what I can do when I incorporate a human into that process. Because I have to wait on them. I have to, like, you know, give them feedback on how they're doing the script read, etcetera. And I can get an output

00:29:22.945 --> 00:29:44.160
that is I I can just move so much faster than what that human in the loop ends up looking like. And if I can move faster, a lot of the times I can win. So, again, I'm talking about startups, though, too. Like, we're an early stage company. This is way different when you're at a larger organization. But there's ways to incorporate this into your workflows that I I I think people don't like, if you just start to think in this way, you you you can compound

00:29:44.715 --> 00:30:10.840
the experience that you have. Like, you you're you're no longer like a purse like a single person that's joining a company. Like, you're a person with 30 agents behind you, and you have all this personal software that you've written that you're now bringing to the table. Okay. What levers does that give you to negotiate from a salary standpoint? Like, not just hiring me. You're also hiring my system that I've developed and that I'm going to bring into this organization while I come. So anyway, I don't know if there's questions around that I can try to answer. But

00:30:11.515 --> 00:30:14.395
Yeah. What percent more productive

00:30:14.395 --> 00:30:18.315
would you say you are given your use of these tools versus old Cody?

00:30:18.475 --> 00:30:20.635
I've done I've done probably

00:30:20.955 --> 00:30:25.275
more work in the last two weeks than I had done since October

00:30:25.275 --> 00:30:25.755
probably.

00:30:27.310 --> 00:30:28.190
Like,

00:30:28.270 --> 00:30:44.625
I I can't even put a number on like, it's it's it's infinite. The the problem now is no longer like the things that can be done. Right? Like, I can I can we could be in here right now and be like, here, we'll just do this? I'll just be like, go and make landing pages. Like, I'm gonna do AI dashboard generator.

00:30:44.865 --> 00:30:47.905
Right? And then I'm gonna use this tool called Keywords Everywhere,

00:30:48.225 --> 00:30:59.250
and it's gonna help me find all the long tail keywords related to AI dashboard generator. So it's gonna pull all of these out. It's gonna extract these. Right? I can take every one of these keywords. I'm gonna download them right now.

00:31:01.090 --> 00:31:05.810
I'm gonna copy them. I'm gonna go over to Klon, and I'm gonna say make a landing page

00:31:06.450 --> 00:31:07.330
for each of these.

00:31:10.005 --> 00:31:13.685
Someone saying that you're in crisis after understanding what is possible.

00:31:13.845 --> 00:31:16.645
Yes. This is literally what it comes into because you you you the

00:31:18.085 --> 00:31:31.250
I'm I'm like losing sleep over this to the because of what you can do. Like, feels like you're at this, like, tipping point. Again, with the domain knowledge that I have, like, have experience in what you know, these aspects, like, these deep understandings.

00:31:31.250 --> 00:31:39.650
If I can go and apply this to that, right, it creates this compounding effect in the work that I can do that's just at a ridiculous level, basically.

00:31:40.235 --> 00:32:03.150
And so cool. It just said, like, it just set this up. Seven new pages are being created now. It's gonna give me the URLs for those pages. I can take a look at them in a draft mode, and I can hit publish. Or I can just say, hey. Just hit publish, and let's go, like, right into the pro. And to create those pages, because I'm sure like I I had a similar question as you were creating the bulk Facebook ads. Like, what's actually creating the design there? Like,

00:32:03.550 --> 00:32:04.430
what what's

00:32:04.830 --> 00:32:19.145
yeah. Yeah. It's just the template of the homepage. So all I've done is like forward slash like page. Right? And I'm just gonna go to this test page integration. Right? Yep. It's just this. It's basically the exact same thing of the homepage. Only the title

00:32:19.305 --> 00:32:50.375
and the p one in the hero section is being changed. The reason that we do this is because when we see that when we align the ad and the landing page that we're sending them to, we can increase the conversion rate that's happening there. Like, this is why you build you know, this is why there's, like, thousands of landing page builders. Right? Like you could you go for hours talking about like Leadpages or like Yep. You know, any of these. The whole idea is I'm trying to like optimize that funnel so that it feels cohesive to the user that's coming from an ad to the page that they're landing on.

00:32:51.620 --> 00:33:01.940
What I'm how I'm thinking about this now is like, okay. Well, this is just a single landing page format. I can go and make as many different variations of landing page formats

00:33:01.940 --> 00:33:04.980
and then go and test those against each other as well. Like,

00:33:06.105 --> 00:33:09.625
expands kind of infinitely in whatever direction that you can imagine.

00:33:09.945 --> 00:33:18.505
And and I'm also not, like, hindered by any engineering resources with everything that I'm doing here. Right? Like, I I'm having Claude set up this infrastructure.

00:33:19.450 --> 00:33:27.290
I'm then having Claude do the work for me of, like, you know, page by page building out landing pages for every one of these. Right?

00:33:27.530 --> 00:33:38.295
And then I'm basically deploying those. I I what this turns into from here too is like, Now I want to go and I wanna submit these to Google Search Console so that they get indexed.

00:33:38.535 --> 00:33:46.455
I, like, ask Claude, okay. What's the sitemap that these are under? I then say, okay. Hit the Search Console API to submit these so that they get seen

00:33:46.775 --> 00:33:48.855
or by so that this

00:33:49.270 --> 00:33:57.190
sitemap starts to get indexed by Search Console. I see that those pages aren't actually getting indexed. I can hit the web indexing API from Google's

00:33:57.510 --> 00:34:01.990
that Google provides to basically do like a manual ask for the indexing of that page.

00:34:02.825 --> 00:34:04.185
The the like,

00:34:04.425 --> 00:34:07.225
it's basically the exact same work that you're doing,

00:34:07.545 --> 00:34:10.665
but just employing the Cody, you're you're you're

00:34:10.665 --> 00:34:13.225
you're you're frozen for a second. I think your

00:34:13.385 --> 00:34:24.200
your computer is like about to take flight. They're like they're like, I'm trying to match Cody's energy right now, and it is not possible. I'm simply a robot. But but I think

00:34:24.520 --> 00:34:26.840
the I think the the gist of it is, like,

00:34:27.640 --> 00:34:33.320
you you're able to create at such abundance now. I guess my question for you is is, like, what is

00:34:33.775 --> 00:34:41.055
what is the biggest bottleneck in a marketer or head of growth's job now if you're functioning like a go to market engineer?

00:34:41.535 --> 00:34:50.210
Yeah. The the the biggest challenge that you're gonna be facing is the amount of data that you can produce is at a scale that you just, like, never could previously.

00:34:50.450 --> 00:34:52.770
Right? And this is actually, like, the whole origin

00:34:52.850 --> 00:35:27.070
of the company that I'm building. Right? It's like everybody right now can go and build a thousand Facebook ads. Right? Like, I just literally showed you how to do this. But how do I understand what's actually working? Like, what is actually happening within that data at the scale that I'm at? Like, this is this is the challenge that all of these companies are going to be facing. And this is, like, exact so we tried to solve this too. Like, I initially tried to build this with like an MCP or just like hitting an API endpoint to pull in the data. Like, Facebook ads alone for like one of our customers creates 25,000,000 rows of data a month. Right? Like at the scale that they're at. They're deploying about a $180

00:35:27.070 --> 00:35:31.285
of like spend a month. The there is no way through an MCP

00:35:31.525 --> 00:35:45.410
or through the Facebook API that you could basically hit that. So be before we get even get into that, though, like, I'd love to do an actual build just to, like, show people the pro Let's do it. Where it's like, hey. We're gonna scrape LinkedIn comments and, like, people that have engaged with profiles.

00:35:45.490 --> 00:36:00.975
We're gonna use this tool called Phantom Buster to basically, like, pull all that out. We're gonna send that to Apollo, and then we're gonna send that to Instantly AI to actually, like, cold email these people. Just to show people Yeah. Well, let's let's do it. Looks like. So And if you're Wadi and you're at LinkedIn, I apologize,

00:36:00.975 --> 00:36:02.255
but this is gonna be awesome.

00:36:03.215 --> 00:36:05.615
Watch my decal's gonna get nuked after this.

00:36:05.935 --> 00:36:07.295
Give me one second. But

00:36:08.870 --> 00:36:20.870
but I just wanna show people, like, what this process, like, actually looks like when you're starting from zero just so that they can understand. So I'm gonna start an entirely new window. So I'm gonna go into terminal. And, again, I'm gonna go into that documents folder.

00:36:22.055 --> 00:36:28.615
I'm gonna go into that agents folder, and then I'm gonna start Claude, and we're gonna start from scratch. I'm gonna say,

00:36:29.255 --> 00:36:33.175
okay. I wanna build a new workflow that basically will take the engagers

00:36:33.175 --> 00:36:36.135
from a

00:36:35.370 --> 00:36:36.410
LinkedIn profile

00:36:36.810 --> 00:36:43.770
sorry, from a LinkedIn post that I find, and it will then go and use the Apollo API to enrich those individuals.

00:36:44.010 --> 00:36:46.090
It's gonna pull out the emails of those people,

00:36:46.410 --> 00:36:54.935
look for the Apollo API key within the environment file. All this should be in within the environment file already. Ask me for any API keys if you need them.

00:36:55.575 --> 00:37:01.495
And then I want you to then go to the million verifier and validate that email and then add it to an instantly

00:37:01.655 --> 00:37:05.310
AI campaign. Let me know if you have any questions. So at this point,

00:37:06.270 --> 00:37:08.190
I'm then gonna turn it into

00:37:08.350 --> 00:37:09.470
plan mode

00:37:09.870 --> 00:37:11.550
and have it basically

00:37:11.710 --> 00:37:20.365
walk through the process of like, what do you need from me to get this output that I just asked you for? That is literally the origin of this. And twenty minutes later,

00:37:21.245 --> 00:37:23.565
you're gonna have that whole workflow built.

00:37:23.965 --> 00:37:31.690
Like, you're just basically providing it what it needs to do this activity for you. This is like how simple this is, and this is how. Yeah.

00:37:32.090 --> 00:37:36.410
I mean, I was building a similar I was building a similar thing yesterday where

00:37:36.810 --> 00:37:39.930
I want to I've noticed there are more go to market engineer,

00:37:39.930 --> 00:38:02.260
chief AI officer, head of AI roles. And to me, those companies that post those jobs are great potential customer for 10 x. And so basically, I just similarly to you, and we have like a certain planning prompts at 10 x, but you can, you know, quads plan mode is is more than sufficient. I basically was like, build me something that every day,

00:38:02.900 --> 00:38:05.060
uh, goes through and searches

00:38:05.060 --> 00:38:09.540
LinkedIn jobs that have these three titles or titles like them at companies that have

00:38:10.275 --> 00:38:12.035
more than 200 employees.

00:38:12.355 --> 00:38:17.715
If you can't get it directly from LinkedIn, use Exa because I know Exa has basically scraped all of LinkedIn,

00:38:17.875 --> 00:38:22.115
enrich the data so that you know which of these companies actually have more than 200 employees,

00:38:22.560 --> 00:38:37.200
and then set up a Slack integration where every day in Slack, we get a message with at least 15 jobs that have these titles at companies of this size that we can send DMs to. That's where it's at now. We can take it a step further, obviously, and actually, like, automate the drafting and DM process.

00:38:37.795 --> 00:38:41.155
Exactly. This is the whole like, so what

00:38:41.635 --> 00:38:43.475
you just described is

00:38:43.635 --> 00:38:51.235
where all of my time is spent now is figuring out, like, what is that arbitrage. Right? And then how do I go and basically,

00:38:51.395 --> 00:38:51.555
like,

00:38:52.490 --> 00:38:55.290
and this is the game now. Right? Like, you're you're competing

00:38:55.850 --> 00:39:09.295
against, like, people like me, like you, like, you know, our friends that are all doing this type of work. Like, this is how sophisticated it's starting to become. And, like, I I I'm, like, honestly just, like, afraid.

00:39:09.695 --> 00:39:19.535
Right? For, like, I I, you know, I I know people that are in these roles that, like, aren't, like, adopting this or their or their jobs won't let them this yet. There's just this huge opportunity cost basically

00:39:19.615 --> 00:39:20.895
to, like, not, like,

00:39:21.900 --> 00:39:23.500
start doing this immediately.

00:39:23.660 --> 00:39:38.475
I and I would like the other the other piece of it is, like, how do you communicate this and, like, show this internally of, like, the activities that you're doing? And, again, like, the with the system that we're like, just to show you an example of this. Right? So, okay, I I spun up this campaign

00:39:38.635 --> 00:39:41.275
and I'm gonna go and I'm going to extract

00:39:41.435 --> 00:39:45.675
the ad set ID. Okay? And then I go over to graft and I'm like, cool.

00:39:46.235 --> 00:39:47.755
Like, make a dashboard

00:39:48.635 --> 00:39:50.475
about this ad set.

00:39:51.550 --> 00:39:54.030
So I've selected like the

00:39:54.190 --> 00:39:57.310
like Facebook ads and then I'm gonna hit send message.

00:39:58.030 --> 00:40:16.585
So this is gonna go and make a dashboard for me about this campaign that I just spun up. While it's working on that, in the background, I'm just over here doing whatever it is that I'm working on with Claude Code. Yeah. Yeah. So let's keep let's keep this let's keep this LinkedIn thing going. I think it'll be awesome for people to say. So I built this pipeline already. So what I'm gonna say is build

00:40:16.905 --> 00:40:19.225
like something else. I'm gonna be like, do it from scratch.

00:40:22.250 --> 00:40:23.690
To show the process.

00:40:25.610 --> 00:40:28.170
So gave it the output, the outcome that I want.

00:40:28.490 --> 00:40:29.050
It

00:40:29.610 --> 00:40:33.210
so it just read my code base and understands, hey. You already have something like this.

00:40:34.225 --> 00:41:02.320
Like, are you sure you wanna basically do this, or do you wanna do it a different way? So now what it's going to do is basically go and design this whole system for me of what I just described. And this will have some back and forth that's necessary where it's basically gonna ask me, hey. Like, I need these API keys. Like, here's where to it'll walk you through step by step. Like, here's exactly where you need to go to basically get those API keys that are necessary for me. Here's the permissions that I need. It's crazy, man. Like, on Facebook ads in particular, traditionally

00:41:02.320 --> 00:41:06.245
a very, like, challenging API to interact with.

00:41:06.885 --> 00:41:08.085
It is so

00:41:08.245 --> 00:41:13.925
it it understands the API so deeply. Like, it it from a Totally. It's

00:41:14.085 --> 00:41:21.600
it's honestly like, I I can't even find good documentation on Facebook alone, like, about the API to, like, if I was trying to do this myself.

00:41:21.840 --> 00:41:40.815
But by it going and interacting with the API, it knows what it needs to like, it it can guide me through this process, basically. Yeah. It sounds ridiculous. It seems almost like you're a vessel for what it needs from you to do the activity that it kind I mean, that that is exactly what it is. Like, I think it's really important for people to realize that with Claude code,

00:41:41.535 --> 00:41:47.140
it's it's one of those things where you you really do not have to understand software engineering.

00:41:47.380 --> 00:41:56.660
You just have to be a clear enough thinker. But, honestly, ClaudeCode is getting better at even if you're not a clear thinker, you're a disorganized thinker because it's really good at inferring

00:41:56.660 --> 00:42:18.820
what you want. And anytime you don't know something so if it's like I don't know. Using the example of what I built, like, hey. I wanna scrape for these things from Exa. If it's like, oh, you need to go grab the sign in for an Exa account and grab the Exa API. Let's just say I didn't know what the Exa API was. I could just ask it, how do I what is an API? Or how do I go grab the AXA API? And it gives me the act exact

00:42:19.620 --> 00:42:20.420
directions.

00:42:20.900 --> 00:42:38.765
So and to the point Cody made, it's like because Claude code and these tools can now just build software from scratch, It's using, like, people as a vessel to get all the information that it needs to build these things, and we are just a conduit for giving the information it needs to basically build software from scratch.

00:42:39.005 --> 00:42:45.900
Totally. I think the other thing just to piggyback on, like, we had this conversation two weeks ago, I would have had, like, n and n within this workflow.

00:42:46.140 --> 00:42:49.900
And, like, what I found is that I'm actually now just going directly to,

00:42:50.620 --> 00:42:57.505
like, code. Like, I I just skipping n and n as, like, within my stack and just going like immediately

00:42:57.825 --> 00:42:59.505
to like writing.

00:42:59.505 --> 00:43:02.865
So for example, like I I needed to set up a

00:43:03.505 --> 00:43:09.265
basically like after a sales call, wanna give a Notion document of the recordings that it writes an email draft

00:43:09.870 --> 00:43:11.150
for me and

00:43:11.790 --> 00:43:15.470
based off of like what the follow-up steps are for from the onboarding call.

00:43:16.110 --> 00:43:25.025
I needed a server to be able to have this run-in in perpetuity in the background all the time so I could like send a Slack message and have it run. So I gave,

00:43:25.905 --> 00:43:35.505
like By the way, so so you guys know because I think, like, you may be watching Cody right now and you're like, holy hell. This guy is frenetic and, like, he's context switching to all these different things.

00:43:36.400 --> 00:43:41.840
It's one of my theories that, like, multitasking has always been, like, a frowned upon thing.

00:43:42.080 --> 00:43:44.560
But what he is doing is actually not multitasking.

00:43:44.560 --> 00:43:45.680
It's multithreaded

00:43:45.680 --> 00:43:53.585
work is the way I view it, where it's now as things can run-in parallel, the only way to work is going to be working on multiple things in parallel

00:43:53.745 --> 00:43:54.465
because

00:43:54.705 --> 00:44:06.990
the cost of not doing so is someone else who is able to do so because you actually don't have to divert your attention across many things because another coding agent or another Claude is going to have all of its attention focused on that one task.

00:44:07.310 --> 00:44:08.670
Yes. And, like, this

00:44:09.390 --> 00:44:10.750
again, I'm

00:44:10.750 --> 00:44:28.065
I'm just basically jockeying these agents is how I think about it. Right? Like, I'm just going back and forth between them and it's like guiding them or doing what they need from me. And just to come back to this, so, like, I needed a server and so that this software could run-in perpetuity in the background. Right? So, like, basically

00:44:28.065 --> 00:44:30.705
always beyond, not just using the CPU on my machine.

00:44:31.800 --> 00:44:34.600
So I gave it my Railway API key,

00:44:35.080 --> 00:44:44.135
and I'm like, cool. Set up, you know, a types you know, set up the the server that I need. It was just like a Node Express server. It set that up for me. It launched the software on It pushed the the

00:44:44.455 --> 00:44:57.095
the repo to GitHub to be able to do this. Like, all of this, it it handled on its own. Again, while I'm working on these other activities, whether it's like creating dashboards or analyzing the data or building out a new workflow

00:44:57.750 --> 00:45:09.270
for whatever like opportunity that I see within the distribution stack that I'm going after. So anyway Totally. I don't know if there's other questions on your Friday. Where are we no. No. So where are we in the the LinkedIn build?

00:45:09.510 --> 00:45:11.350
Yeah. So in the LinkedIn build,

00:45:11.670 --> 00:45:12.805
it's currently

00:45:14.165 --> 00:45:20.805
like, you're it basically created this action plan, and it's now going to go and, like, implement what I just described. So

00:45:21.765 --> 00:45:28.170
Cool. And ultimately, what you would have to do for this to be, like, fully built is you're gonna need, like, an API key for

00:45:28.410 --> 00:45:40.410
the thing that scraped from LinkedIn. You're gonna need an API key from Apollo, which is gonna enrich those leads from LinkedIn. You're gonna need an API key for Instantly, which is the thing that sends, um, cold, uh, outbound emails.

00:45:41.015 --> 00:45:44.055
And there's one other API key. What's Million Verifier?

00:45:44.055 --> 00:46:08.850
Million Verifier is just a email validation software to check that the email is, like, actually valid so you don't nuke the cold email can't like, domain Yep. That you're sending from. So Yeah. So basically, what's gonna end up happening probably is that the only work you're gonna have to do is get these API keys from these different sites. If you don't didn't know how to, you could just ask Claude how to do it. You're gonna feed it to Claude. And then once it's done and you test this out, if it works, amazing.

00:46:09.335 --> 00:46:16.215
If it doesn't work, you just feed the error back to Claude and tell it fit figure out how to fix this for me. Exactly.

00:46:16.455 --> 00:46:25.670
Honestly, it'll just do that recursive loop for you. And this is like why it's so powerful. It's like if it sees the error that's occurring, like for example, we had this railway when I was deploying the server.

00:46:25.910 --> 00:46:32.630
Like, there was some bug that was occurring. I just looked at the logs to see what was happening and then fixed it so that it could do the deploy.

00:46:32.790 --> 00:46:36.390
So this is now completed. Right? Like, it's now done this basically.

00:46:37.915 --> 00:46:48.475
I can now just drop in a LinkedIn URL here. Like, what how I'm going to extend this, like, just to communicate it. It's like, I'm gonna build this as a Slack function. So I do, like, forward slash LinkedIn

00:46:48.715 --> 00:47:12.045
enrichment. Right? I drop in a LinkedIn post URL, and that will just fire this whole thing off and that automatically gets added to the Instant Lead like AI like campaign that I'm running that cold outbound strategy from for people that engage. So as I'm scrolling LinkedIn on my mobile, right, I find a post that's relevant to the software or the product that I'm building. People that interact with that post, they're valuable to the company.

00:47:12.525 --> 00:47:32.860
I taped that post link, I dropped that into Slack, and this whole thing fires in the background. So I this is this is the compounding effect that can happen. You could also just provide this as a tool to your whole team as well. So they can just, like, feed this into it, or you can have it where it's, like, automatically scraping for these posts using something like Appify or Rapid API to go and extract

00:47:33.475 --> 00:47:34.035
the,

00:47:34.355 --> 00:47:36.595
like, most viral pieces of content

00:47:36.755 --> 00:47:41.715
within the category that you're in. Or if you know that specific creators make content that is super

00:47:42.355 --> 00:47:56.330
that is like, they do that on a consistent basis that your ICP interacts with, you can go and follow them. So, like, this is something I'm building right now is I'm basically taking, like, all the incumbent competitors, CEOs, LinkedIn profiles. I'm looking at their their content to see who engaged.

00:47:56.490 --> 00:48:15.265
And then that typically is a great signal that they're, like, in a buying motion with that company. I then take that and then go and reach out to them. So these are the like the levels of the game that you can play with this basically. So And anything so we have about ten minutes left. Is there anything else you wanna show in kind of your build before we hop into questions?

00:48:16.330 --> 00:48:23.850
No. I I I think the only, like, again, the only thing that I think is going to hinder people is, like, thinking about

00:48:26.090 --> 00:48:49.810
you can do anything now. So, like, what should you do? And, again, like, going back to those, like, the data is going to drive all of your activities. Like you have to have a solution for whatever it is that you're like just going like I I see these like tutorials all the time that are like, here's how to do like you know this this action where it's like for example, like I'm gonna make a thousand Facebook ads. Like if you don't have like an outcome

00:48:50.290 --> 00:48:58.095
that you're moving towards or a way to measure this, there's no point of what you're doing. Like all the AI slop tooling in the world will,

00:48:58.575 --> 00:49:01.135
again, will enable you to to

00:49:01.615 --> 00:49:08.655
create as much content as you want. But unless you can actually analyze that information, that's that's the only way that you're gonna be able to, like,

00:49:09.215 --> 00:49:11.935
scale with this. So anyways, that's my only thought.

00:49:12.700 --> 00:49:35.355
And two two other things here. One is we're gonna do questions now. If you have questions, put them in the q and a part of the chat so that it doesn't get drowned out by, honestly, the amazing conversation that's going on here. There's literally conversation in this chat about people setting up a go to market engineering WhatsApp group to keep the conversation around this going. But, yeah, drop questions in the q and a. I'll take a look at those.

00:49:36.475 --> 00:49:39.435
And in the meantime, I got this question. So

00:49:39.675 --> 00:49:41.035
we purposefully

00:49:41.290 --> 00:49:42.890
make these conversations,

00:49:42.970 --> 00:49:43.850
I would say,

00:49:45.930 --> 00:49:50.570
technical ish. Like, not technical at the at the level of engineering,

00:49:50.570 --> 00:49:53.370
but technical where you are for sure gonna hear terms

00:49:53.855 --> 00:49:56.335
that you haven't heard before if you're nontechnical.

00:49:56.575 --> 00:50:15.310
And that is purposeful. And and it's purposeful because our belief is that really high agency people who are joining this conversation and wanna stay in the frontier of this technology are going to do the work to get those questions answered. So I saw someone say like, I don't even know how to get a repo on GitHub. I don't know what, like, you know,

00:50:16.110 --> 00:50:36.480
exactly how an IDE works and what a CLI is and all these things. So I didn't know what any of these things were ten months ago. I literally did not know any of them. But if you, one, spend time in this sort of conversation with people also looking for the answers, and honestly with Claude Code, there actually is just no excuse now for for not finding the answer to all these Everything.

00:50:37.120 --> 00:50:41.840
Everything I talked about today, you can literally be like, I don't know how to do that.

00:50:42.160 --> 00:50:49.455
Like, tell me how to do this, and then we'll walk you through every part of that process. So Yep. Cool. Okay. So we're gonna hop in some questions.

00:50:50.815 --> 00:50:53.535
First question from Tom Babb.

00:50:53.615 --> 00:50:58.255
Tom said you listed about 20 tools. How are you discovering them? Google, AI,

00:50:58.815 --> 00:51:02.720
like where are you finding the tools that you use? Yeah. I I honestly,

00:51:02.720 --> 00:51:08.880
it's like I've been doing this this is a terrible answer, but I've been doing this so long. I just know where these things are.

00:51:09.760 --> 00:51:21.665
The like, Twitter is Twitter and YouTube is where all of this is happening right now. Full stop. It's so funny because, like, I'm not really active on LinkedIn. Like, I'm I'm it's a it's a channel that I'm really bad at. I'm just, like, not good

00:51:22.065 --> 00:51:25.025
not really built for the content that's, like, works there.

00:51:25.905 --> 00:51:29.665
I'll see stuff that went viral, like, six months ago on Twitter,

00:51:30.170 --> 00:51:40.570
And, like, that, like, has already been adopted and implemented and, like, basically, like, the arbitrage has been exhausted, and it will show up on LinkedIn. And it's just hilarious. So, like, it it's it's kind of assess pool,

00:51:40.810 --> 00:51:42.330
like, full, like, full warning.

00:51:42.845 --> 00:52:21.305
But, like, that like, where all this is happening is largely on Twitter and, like, YouTube. With that said, though, honestly, like, using a like, if you're trying to solve a problem, like, okay. How do I extract, like, engagers out of, you know, like, LinkedIn posts? Right? Like, if you just go to Perplexity and be like, what are the five best, like, tools for this? It's gonna give you examples of each of those, and then you'll be able to go and implement those. And, honestly, I've had Cloud Code, like, share stuff with me where I was like, oh, I didn't even realize that this was the solution that would, like, be a better like, for the outcome that I'm looking for. So I I think just, like, there's no there's no rule book with this right now. There's no, like, good educational

00:52:21.305 --> 00:52:32.460
material. It's all just kind of happening in real time. Like, everything that I just showed you is, like, transpired over the last two weeks. Right? Like, that's how that's the velocity that this is basically moving at, like, with currently.

00:52:32.460 --> 00:52:37.385
Okay. We have a ton of questions in the chat. I can just keep them rolling. Yeah. Will said try be quick. Everything

00:52:37.385 --> 00:52:50.825
you've talked about today seems like a tool for just you to use. How do you think about deploying these tools to a team for them to use as well? Yeah. So what I just showed, like, that can be a shared like, a a piece of shared software. Right? So for example, like the bulk ad generator.

00:52:51.080 --> 00:52:52.600
You could just deploy that.

00:52:53.080 --> 00:53:11.865
Like, you could just literally put that on a URL and then provide that to your entire team. Or like how I see, like, more sophisticated teams doing this is they're, like, having shared GitHub repo, And they're basically, like, as they make changes to the code base, they, like, merge that to the GitHub repo so everybody's working on the same instance.

00:53:12.425 --> 00:53:23.560
There's multiple different ways that you could go about that. It just depends on, like, how sophisticated you wanna be, like, treating this as, a software engineering activity or as like a I'm just building internal tools and sharing them with my team.

00:53:23.960 --> 00:53:35.375
And and again, you don't need to know how to get your repo on GitHub or how to merge a PR. You can literally just say, I wanna share this with my team. What's the best way to share it? It Cool. Google Right?

00:53:35.375 --> 00:53:42.335
Yeah. Exactly. It's like cool. Here's this URL that it can now go to and you just deploy it onto Vercel. You don't even know what Vercel is. Right? But it's Exactly.

00:53:42.895 --> 00:53:51.820
Can access it. So Okay. Next question from Kate. Do you use this post on your owned channels or do you just test on satellite accounts

00:53:51.980 --> 00:54:10.265
and paid ads? How do you think about quality control at scale? So basically, it's like if you're testing all these different ads, do you worry about knowing they're gonna be bad ones that you're testing on like your core channel? You could totally have that separation. And then like basically, like, the the the the paid ad spend for the winner is the the

00:54:10.585 --> 00:54:15.465
basically, the the lens that you, you know, that you sift through to then move to your main.

00:54:16.130 --> 00:54:25.570
We do this a lot with organic social where it's like I have burner accounts that we're posting ideas to. And then once we find, like, banger ideas, we'll then pull those over and then put them onto mains.

00:54:25.810 --> 00:54:27.250
It just depends on again,

00:54:27.970 --> 00:54:34.175
the it it it depends on the situation of the organization that you're in and how flexible they are with, like, this type of

00:54:34.575 --> 00:54:48.800
this type of testing. But I think if you go to them and you're like, we can create better outputs. Like, I need to be able to do this. Like, there's the conversation that you can have. And then proving that to them, like, here's this KPI dashboard that is showing you that I just decreased, like, our CPA

00:54:48.880 --> 00:54:54.000
by 20% because I'm now doing this, like, you know, ad velocity testing that we're talking about. So

00:54:54.640 --> 00:55:09.735
Yep. Love it. Eduardo asked, I'm sure other people are wondering, can you share again what is the process you use in order to get the meta ad creative done? So can you just, like, almost just go, like, step one through whatever step of how you do that bulk upload? Yeah. Totally. So so step one,

00:55:10.215 --> 00:55:16.040
I would go to Claude and, like, I I would basically be like, I wanna build an bulk ad generator.

00:55:16.360 --> 00:55:21.560
Here's an example of an ad, like, you know, square format that I want to create.

00:55:22.520 --> 00:55:24.840
Like, help me do this. It'll

00:55:25.480 --> 00:55:33.975
put it in plan mode. It'll literally make a plan to execute this. It'll ask you questions on, like, how, like, variable do you want the generator to be.

00:55:34.455 --> 00:55:43.780
And then you like, literally, that walks through. Imagine, like, ten minutes of you going back and forth with it describing it. You hit go. It will make that box generator.

00:55:44.340 --> 00:55:46.260
And then to redesign

00:55:46.340 --> 00:55:47.700
that that,

00:55:48.580 --> 00:55:49.540
like, piece of

00:55:49.780 --> 00:55:52.740
that, like, ad creative. So, like, this is something where

00:55:53.220 --> 00:55:53.860
we

00:55:54.735 --> 00:56:02.895
having the language to describe the thing that you're trying to describe is the hardest part of this now. So for to give you an example, I have a cofounder,

00:56:03.055 --> 00:56:10.255
super technical. Like, the depth of knowledge he has and the language and the vocabulary that he can use to describe the outcome that he's looking for

00:56:10.740 --> 00:56:39.130
is like so much deeper than I can. Right? So and to get to to to zoom this out, to give an example, if I go to Claude and I'm like, write a blog post about x. Right? It's gonna write the most average thing that you've ever seen. But in contrast, if I interview myself, say I'm an expert about whatever this topic is, I'm gonna like do a transcription where I talk for ten minutes. Like, I just monologue about the topic, my opinions, my views. I use that as source material. Then I also go scrape what's ranking on page one of Google,

00:56:39.370 --> 00:56:47.450
and I bring that in as source material as well. I put both of those into context and then I'm right, okay. Now write a blog post about this based off of the content that I provided.

00:56:47.690 --> 00:56:50.650
Use the source material as you need. Use the vocabulary

00:56:51.335 --> 00:56:53.575
from the transcript that I provided.

00:56:53.975 --> 00:57:10.430
The output quality that I'm gonna get from that is gonna be, like, top, you know, 10 to, like, 10 to 1%. Right? Like, you're gonna be finally in that, and and it's the same idea here. So when you're this is the actual the hardest part. Like, I I'm act I'm actively doing this right now. I don't have the design language to describe

00:57:10.590 --> 00:57:13.150
what I'm trying to do with the creative

00:57:13.550 --> 00:57:21.175
to create the out like, the the visual that I'm looking for. So, like, something I just learned yesterday was like, oh, you can talk about a grain opacity.

00:57:21.175 --> 00:57:47.350
So you basically, like, overlay a grain, like SVG over the top of the background, and then I can put the opacity levels at a different size to basically create this almost like effect where it feels like there's like texture to it. And I was trying to tell it, like, make texture. Right? Like, I I don't have the language. And this is this is the actual, like, hardest part of this is the acquiring of that, like, domain knowledge. And this is why people that already have that domain knowledge that implement this are so much more effective at using this tooling. So

00:57:48.135 --> 00:57:52.775
Totally. And so just the to complete the steps. The step was basically

00:57:52.855 --> 00:57:57.495
you have Cloud Code build the bulk ad generator. Yep. You give it an ad that

00:57:57.735 --> 00:58:00.295
you want to be kind of the source material.

00:58:00.615 --> 00:58:22.535
Then what's the next step after that? Yeah. So give it the ad you want it to be the source material. It's gonna go and make a variation of that ad. You then go back and forth with Claude with the changes that you want. And you can just ask it. Be like, hey, this doesn't feel super cohesive. The first version that it did, for example, purple, black, brown, like, very like, it looked terrible. Like, tons of colors that weren't on brand. I'm like, cool. Here's our brand style guides.

00:58:22.855 --> 00:58:34.090
I want you to, like, you know, mimic this as much as you can. How can we make changes to the ads so that it fits this? I want I go down that texture rabbit hole because I'm trying to make it have, like, this feeling of depth. So once I get that that

00:58:34.810 --> 00:58:46.585
the image to the quality that, like, I want, like, the template to the quality either to the outcome that or the the the template to the level that I want. At that point, then I can say, okay. Now I wanna, like, add a bulk generator to this.

00:58:46.905 --> 00:58:51.545
I'm gonna basically we're gonna change the title. We're gonna change the the the paragraph.

00:58:52.265 --> 00:59:03.110
Help me brainstorm those ideas of like what should be in here. Again, I showed you how to do that with Perplexity and using Claude. You could do that all within Claude code. I was just, you know, showing you a different way to do the same outcome.

00:59:03.270 --> 00:59:08.390
It's gonna generate those ideas. You can select the ones that you think are the best, and then you go and do that bulk generation.

00:59:09.195 --> 00:59:12.315
That whole process again, like that's like 30

00:59:12.315 --> 00:59:18.955
of time to get that thing set up that I just showed you how to do. Love it. Last question for you. What are,

00:59:19.275 --> 00:59:25.670
let's call it the top five most important tools you use in your stack for doing what you do today?

00:59:26.230 --> 00:59:27.350
Yeah. I think

00:59:28.790 --> 00:59:32.390
it's it's it's I just try to keep it simple, and it's like literally,

00:59:32.390 --> 00:59:32.870
like,

00:59:33.750 --> 00:59:38.870
on the most slept on okay. So just to take a step back. I think the ability to email,

00:59:39.495 --> 00:59:49.175
like, cold email people is so underrated. Like, I don't think people understand. Like, I can the the amount of information that I can just, like, scrape from the Internet and then

00:59:49.575 --> 01:00:00.100
do bulk email that's customized at scale. Like, just having, like, a ton of domains sorry, a ton of inboxes that are in instantly. So we I, for example, I use HyperTite. For all of my domain infrastructure.

01:00:00.180 --> 01:00:05.940
They basically set up I have 2,000 inboxes that I'm sending from that I put into instantly.

01:00:05.940 --> 01:00:12.815
And then I'm just running like multiple campaigns out of out of instantly for whatever activities that I'm trying to do. Right now we're pitching me to go on podcasts.

01:00:12.975 --> 01:00:21.695
I'm pitching YouTubers to basically like, you know, do influencer marketing or creator led marketing for us. And then I'm also doing like traditional cold email to our ICP.

01:00:22.380 --> 01:00:30.620
I think that that is something, like, having that ability to just tap into that with, like, whatever out out, you know, outbound you're trying to do, that's something that's super powerful.

01:00:31.340 --> 01:00:46.625
Like, again, this clog code, like, piece, like, I still do use cursor some just for, like, small pieces, but my stack is basically clog code. All of the all of the APIs that I work with on a daily basis, I have that in that environment file. And then I'm, like, living out of graph.com,

01:00:46.625 --> 01:00:54.410
which is my company for, like, all of the analytics. And so, like Got it. For example, just to show people like what this ends up looking like. So we just started that campaign,

01:00:54.730 --> 01:00:57.690
right, of like we're trying to go and basically

01:00:58.170 --> 01:01:12.615
like track the outcomes of this like ad creative that we just generated. I basically was like build me a dashboard about the ad set with this ad set number and I now have like spend. I have breakdown by the conversions. I have like where it's actually being shown on platform.

01:01:12.855 --> 01:01:20.440
If I wanna modify this or change this in any way, I just chat with the dashboard. If I wanna change the chart style where I'm like change this to a bar chart,

01:01:21.480 --> 01:01:57.030
it does this. And then I can share this internally with my team so that I can actually create like, you know, basically buy in from the organization that I'm working on with. Here's this KPI dashboard that's actually showing the outcomes that I'm doing based off of this work that I'm doing. So anyways, man, that's that's really it. I've try to keep it as simple as possible. I think people get obsessed with the tools, get obsessed with the outcomes. The tools are it doesn't matter anymore. Like, there's no limitation on the tools and what you can get them to do. It's the hardest part is knowing like what should I be doing and then like how do I polish that and measure like what is actually working for my company. So Love it. Cody,

01:01:57.455 --> 01:02:00.015
this was awesome. Appreciate the time and

01:02:00.095 --> 01:02:04.335
look forward to having you on again in the future but I thank Thanks for having me. Truly on sales channel. Everyone

01:02:04.895 --> 01:02:06.815
learned a ton. Cheers.

01:02:07.055 --> 01:02:08.975
Cool man. Thanks everyone. Yeah. Thank you.