Claude Code marketing masterclass [from idea to making $$]

I sit down with Cody Schneider, growth engineer and co-founder of Graph, for a live, hands-on crash course in GTM (go-to-market) engineering powered by Claude Code. Cody walks through how he runs multiple AI agents simultaneously to handle everything from bulk Facebook ad creation and LinkedIn outreach to cold email campaigns and live data analysis — tasks that used to require a team of dozens. By the end of the episode, you'll have a full understanding of how to set up your own agent workflow, the specific tools involved, and why domain expertise paired with AI is the real competitive advantage right now. Cody’s GTM Toolkit: AI/Agent Tools: Claude Code, Perplexity API, OpenAI Codex Marketing & Outreach: Instantly AI (cold email), Phantom Buster (LinkedIn scraping/automation), Apollo API (data enrichment), Million Verifier (email verification), Raphonic (podcast host scraping): Advertising: Facebook Ads API, Facebook Ads Library (competitor research), Nano Banana Pro (AI image generation), Kai AI (bulk image generation), HeyGen API (UGC/video generation) Infrastructure & Deployment: Railway.com (servers, on-the-fly databases/Postgres), Vercel (deployment) Data & Analytics: Graphed / Graphed MCP (data warehouse, live data feeds), Google Analytics 4 CRM & Communication: Salesforce (mentioned as comparison), Intercom, SendGrid API, Slack, Cal.com API Productivity & Design: Notion, Super Whisper (voice transcription), Claude Code front-end design skill, HTML to Canvas (for converting React components to PNGs) Timestamps 00:00 – Intro 02:02 – What Is GTM Engineering? 05:12 – Setting Up Your Agent Workspace & Environment File 07:54 – Live Demo: LinkedIn Auto-Responder 09:56 – Live Demo: Bulk Facebook Ad Generator 12:31 – Live Demo: Cold Email Campaign Automation (Raphonic + Instantly) 14:47 – Live Demo: Creating Notion Documents via Claude Code 16:46 – Live Demo: Bulk Ad Creative Generator 26:05 – Live Demo: LinkedIn Engagement Scraper to Cold Email Pipeline 28:16 – Context Switching Across Tasks 29:19 – Live Demo: Bulk Ad Generator 31:41 – Live Demo: Data Analysis: Turning Off Low-Performing Ads 35:28 – Summary of GTM Engineering Workflow 37:48 – Deploying Agents and On-the-Fly Databases with Railway for Data Analysis 41:28 – The Dream of Autonomous Marketing 48:50 – Building API-First Products and Agent-Native Infrastructure Key Points GTM engineering has evolved from Clay-style data enrichment workflows into full-stack agent orchestration — where one person running multiple Claude Code agents can replace the output of a large team. The practical setup starts with a single folder containing your environment file (API keys for every tool in your stack), transcription software like Super Whisper, and Claude Code. Cody demonstrates running seven or more agents simultaneously across LinkedIn outreach, Facebook ad creation, cold email campaigns, Notion document generation, and live data dashboards. Code-generated ad creative (React components exported as PNGs) costs nearly nothing to produce at scale and allows rapid testing of messaging variations before investing in polished visuals. Deploying proven workflows to Railway turns one-off agent tasks into always-on, autonomous processes that run 24/7. Domain expertise is the real multiplier — the vocabulary you bring from your field determines the quality of output you can extract from these tools. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND CODY ON SOCIAL: Cody’s startup: https://www.graphed.com/ X/Twitter: https://x.com/codyschneiderxx Youtube: https://www.youtube.com/@codyschneiderx

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Greg Isenberg?

  How can you use AI agents, MCPs, and a bunch of different tools to make money on the internet? Today, we walk through it all. Yes, you can vibe code anything right now, and that's great. But how can you actually use AI agents to get you customers 24/7? Well, today, we live build it. We actually spun up 10 Claude code instances, and we show you how you can do it to help you get customers on repeat. I loved this episode. It's my friend Cody Schneider. He's an absolute legend when it comes to vibe marketing and growth marketing. This episode is saucy. And by the end of the episode, you're going to feel pretty confident you know what to do. You are in for a treat. Enjoy the episode, and I can't wait to see you in there.

• 0:51Greg Isenberg?

  Cody, by the end of this episode, what are we going to learn?

• 0:55Speaker 01

  You're going to learn how to build your first agents that allow for you to go and build personal software, to do marketing, sales, growth, customer experience for yourself. And by the end of this, you're going to come out of it with this whole new toolset that allows for you to do all of the middle work without touching a keyboard. You're just going to use your voice and have agents do work for you in the background, man. It's going to be crazy.

• 1:22Greg Isenberg?

  Okay, and can you list off a few of the tools and pieces of software we're going to use? Like?

• 1:27Speaker 01

  Yeah, absolutely. We're going to touch Phantom Buster. We're going to use Instantly AI. We're going to use Raphonic. We're going to use railway.com. We're also going to use a bunch of different other tooling that's in my go-to-market stack. So we're also just going to use like the Facebook Ads API as an example, as another just like way that we're going to interact via this agent harness Claude code.

• 1:56Greg Isenberg?

  All right, and we're going to live build it. And everyone, well, you're going to watch the whole thing. So let's get into it.

• 2:02Speaker 01

  Cool, sweet, man. So just to begin with, do you know like GTM engineering? Or like what it even means or like where it comes from?

• 2:10Greg Isenberg?

  No, honestly, I don't.

• 2:12Speaker 01

  It feels like a buzz. It's just a buzzword, right? So this is actually like made up by clay.com, which is hilarious. And they originally did it as like a way to explain somebody that like does basically like cascading workflows for like data enrichment to do outbound sales motions over email or Slack or, you know, it could be like cold calling. So that was kind of the origin of this was like, it was just basically this term that was given to it. But it's quickly evolving into something entirely different. And so let me screen share and I can just like show you like what we're seeing this work as now. But basically like what we're like seeing is that the, can you see this all right?

• 2:58Greg Isenberg?

  Yeah.

• 2:59Speaker 01

  Cool. So how I'm thinking about it now is like basically everything that used to be the middle work that we would do, like all of anything that I would do to touch the keyboard, I'm now passing it on to some type of agent harness, whether it's Claude code or it's Codex or any of these tools. And so my job suddenly turns into like, I have ideas, I pass them on to Claude code. And then I'm basically polishing the end product and it enables me to do like things at scale that that were just previously impossible. And just to give you like a taste of like what I'm talking about, and we're going to do this today. Like build a hundred Facebook ads, publish them to Facebook, build a dashboard to track that,

• 3:41Speaker 01

  analyze the data within Claude code, have it turn off the Facebook ads that are the low performers, have it bump up the Facebook ads that are the best performers to a new ad set with its own dedicated budget. And everything that I just described, that happening in like literally, you know, 30 minutes. So anyways, again, not really sleeping. So this is kind of where it's at now, and I'm going to talk through like this whole setup process and actually how to do this. And then I'm going to talk about where it's going, like how agents are the natural evolution from this. Basically, as soon as you like start, you have this epiphany level, like I can get this thing to do work for me. Then you suddenly have this like you come to come to Jesus moment of like, oh, I can just deploy

• 4:24Speaker 01

  this onto a server and now it's doing this task for me in the background and I'm building out this personal software for myself, for my job, for my, my, you know, tasks, et cetera. And this isn't some like hype thing of like, go do open claw and give it access to everything. I'm talking about like specific like jobs to be done workflows that are custom made for how you want to operate in your day to day. So that's kind of the high level, man. Any questions I can try to answer? Have to go deeper on anything.

• 4:53Greg Isenberg?

  No, um, if you can teach me this by the end of that episode, I mean, that's sort of the, that's, I think the question that a lot of people have in their heads right now. Like, how do I, how can I do that? Right? Cause that's going to be an unfair advantage. So yeah, let's, let's go, let's go through it.

• 5:09Speaker 01

  Perfect. Let's jump into it, man. All right. So first off, what you need to do, if you're watching right now is I want you to go and I need you to create a folder that you're going to start living out of. So the one I live out of is called graph, uh, graph growth agents. So everything I do now where I start my work, it all exists within here. And the first thing that I'm going to have you do is you're going to set up an environment file. And this environment file, it just holds all of your API keys that you're basically going to be working with. So what I'm doing is I'm basically having, and I'm just not going to show this just because it has literally all of our API keys for everything, but it

• 5:50Speaker 01

  has, uh, I can open up this example one. Um, so it has, uh, like intercom, it has our send grid API, my hub spot API, my cal.com API, my perplexity API, my Facebook ads API, uh, in a million verifier instantly, everything that I live on top of that is a part of my day to day growth stack. This is like what I'm working with basically. And so what this translates into or like why I am, I'm, why you start here is you're basically starting to interact with everything that you do on a daily basis via the APIs. And this is actually how I'm thinking about everything I do now and like how I buy software in particular is how robust the API is. It's funny. I was talking to a friend

• 6:35Speaker 01

  recently and he's like, if you're looking at Salesforce versus HubSpot right now, Salesforce, even though it's like historically a more clunk, like clunky CRM, it's actually the better product for this AI foundation because it has a more robust API. So you can do more with it, basically. And this is what this like turns into is your, all of the work that you're doing, and we're going to do this together today, is going to be happening from this, this like repository. When I say repo, all I mean is just this like folder that we're living in that has all of these files. And I'm going to be using Claude code like throughout the rest of the session to basically be building out this personal software and be building out, you know, actually doing work, if that makes sense.

• 7:19Speaker 01

  So that's kind of one component of it. The last piece is then I would strongly suggest, suggest getting something like a Super Whisper or any of these other transcription softwares, because it enables you to just so quickly go through the process of building out like what you're trying to do on the distribution side. And then optional is just installing the Claude code front end design skill. I've just found this to be like one of those things that it, you know, if we're going to generate a UI, it's nice to have it look pretty. So, all right, that is kind of the foundational pieces. Now it's actually like, great, that's cool. You've just built this. What do you actually do to go get started on this? So the first thing that I'm going to do to get started is I'm going to go and I'm going

• 8:00Speaker 01

  to have Claude code start responding to people on LinkedIn for me that have asked for an asset. So I've been doing all of these like giveaways, basically. Here's one that's an email triage. I wrote this giveaway doc, you know, motion document. I'm now going to go in and I'm going to get this agent to start running for me in the background while I have other work going on. So I've got the Claude code or sorry, I've got the Claude. Chrome extension installed. And I'm gonna go and I'm gonna say, um, so I'm working out of this, uh, that directory, right? That I've already been in. And I already have built this, uh, basically skill and it's a piece of software that will go and comment on everybody that asked for this asset.

• 8:43Speaker 01

  So I'm gonna say this right now, I'm gonna say, uh, uh, let's run, or we're gonna transcribe it. So let's run the LinkedIn, uh, respond, uh, uh, software. Uh, the, uh, keyword that you're looking for is triage. I'm gonna provide the Notion documents and the LinkedIn post URL.

• 9:02Speaker 01

  And then I'm gonna select the, uh, post URL and I'm gonna put that in. And then I'm also gonna select, uh, the Notion document that I wanted to do as well. So I'm gonna give it that, uh, it's gonna start running. So what it's gonna do right now is it's gonna basically open this up. I'm gonna babysit it for a moment while it, while it starts this process.

• 9:22Speaker 01

  And just make sure that it starts on the right path. And then once it's on the right path, then I'm gonna go and basically start on the other things. And actually, while it's thinking, let's just go to these other, uh, places. So the next thing I'm gonna do, uh, is I'm going to, uh, go, or sorry, that just opened the LinkedIn profile. Let's bring that back over here. Um, so this is now running, uh, perfect. And so this should now start commenting on those responding back to those people. I'm just gonna change this to most recent, just so that it works backwards on this. And then we're gonna just let that run in the background. So while that's happening, um, what I'm going to do now is we're gonna build a Facebook ads generator. So, um, I've been doing this where it's basically a, and I'll show you an example of what this looks like.

• 10:07Speaker 01

  Let's just go over to, uh, LinkedIn and I can give you an example of the output that we're going to actually create today. So it's basically a bulk generator of ad creative. We're gonna create this template and then I'm gonna go and do research based off of, uh, Reddit, um, and other social media posts for the pain points that people experience. And then we're gonna go and bulk generate all these variations. So let's get that started right now. So I've got, again, those API keys are stored within here. And I've also made that, uh, that skill. So I'm gonna tell it right now, um, I want you. I want you to create a bulk Facebook ad generator. It's going to be a 1080 by 1080 pixel image.

• 10:51Speaker 01

  What's going to happen is I'll give you an example of what one of these ads looks like. And then we're going to go and build a template around that. And then I'll basically create a, or give you variations of text, both titles and paragraphs that I want to be generated. It'll be a zip file that we download for the beginning. Can you make this into a UI as well so that we can visually see the creative? The first thing I just want to be able to see is like what the actual creative will look like. For this, you're going to use just React components. So I don't want you, or like, just purely build it with React components.

• 11:35Speaker 01

  And then also to actually change this React components into a PNG that's downloadable, we're going to use HTML to canvas. It's just a, you know, resource that you have available for you on that. Ask questions if you need. So I've just transcribed that. I'm now going to put Claude into plan mode and I'm just going to let that start running in the background. All right. So while that's running in the background, let's come back here and let's see the work that it's doing. So it's going through these and I believe it's now commenting. So that's happening. So we'll just let that run in perpetuity, respond back to them. All right. So next, I'm just going to just click through this quickly. I'll share it now.

• 12:20Speaker 01

  I'll share it, I'll share it after setup. And then input method, form-based UI, let's do both. And then I'm going to hit submit. All right. So now that's working on that in the background. I'm going to open up another folder and I'm going to start Claude code again within an entirely another, or another window. So I'm going to do documents, forward slash graphs. Let's go to agents and then demo.

• 12:50Speaker 01

  All right. So the next thing that I want to build as an example is I'm going to basically pull information for so I just I just did this actually so we could like talk through and about what this ends up looking like but basically scraped all of the podcasts that were within the marketing category and then built a workflow that goes and cold emails them and then an agent that responds back to book me on the podcast this ends up turning into way better performing than I expected.

• 13:23Greg Isenberg?

  That's crazy. Sorry. What is Instantly?

• 13:26Speaker 01

  Yeah, so Instantly is a cold email software. And so this is just a part of my stack. So it's one of the things that like is within that environment file that allows for me to build on top of. And so what I'm like, how how I can think about this like on the is basically like my manual workflows that I would do previously were just like daisy chaining those together like using this software. So I'm going to bring this into a new desktop and let's just rebuild that whole thing. I'm going to say you have the Raphonic API key. I want you to build a software that scrapes podcast host emails from Raphonic. It then

• 14:06Speaker 01

  sends it to a million verifier to verify the emails and then it also will then send it to an Instantly campaign. I'll provide the Instantly campaign that I want it to send to.

• 14:21Speaker 01

  All right, so I've got that now. I'm going to put that in the plan mode and let that run as well. And then we have that as its own window. And so while these two are working again in the background, well, we can then go and actually do like some other work. So let me get this going and I'll just say, cool. So that's a plan. All right. So now this is my we're in this folder. This is like my demo folder, which I just like every time I give this presentation, I just nuke. This is kind of to show you like how to start it from zero to one. This folder that we're in now is my actual folder that I live out of.

• 15:02Speaker 01

  And I'm just going to show you some of the things that are capable with this. So for example, I have it attached to Notion and I've basically given it a an example of like, how do we write a like a Notion giveaway, right? So I'm going to go and we're going to create one of these together right now because I need to actually accomplish this. So I'm going to take this URL and then copy this over. And I'm going to say, okay, write a or create a Notion document. Based off-

• 15:37Greg Isenberg?

  Look at you typing with your hands.

• 15:39Speaker 01

  I know, the problem is we can do it in the transcription of so. Create a Notion document based off of our like current or you know, our structure. Look for the skill that has this. I'm going to provide context on what that should include. You should incorporate stuff that we haven't within the repo, like the documentation that I have in the repo on how to do this. All right, and so I'm going to copy this over. Let that run and now it's going to go and create me a Notion document, just like the one that we have being sent in the background here currently. All right, so in that folder, I've already created the bulk ad generator.

• 16:20Speaker 01

  So I'm just going to go in there just to show you like what you can do with this. Once that it's like you've actually gone through this process of like zero to one making this. So this is the bulk, the creator as an example. So that's going to continue working on that bulk Facebook ad generator in the background. While that's happening, let's go to graphs, growth agents. And then I'm going to start Claude code within there. And now I'm going to start locally the bulk Facebook ad generator. I just want to bring that up within my local so that I can create some ads.

• 17:02Speaker 01

  So again, it's already created the software for me. I'm now coming back to it and I'm going to talk through the whole process of the actual creation of this because it'll just like make more sense momentarily. But the goal here is basically what we're trying to do is I'm trying to create as many different variations of these ads as possible. So how did I make this ad? This is entirely code and I think this is something to like double click on. Everything in here is just, it's just React components like that. This is, this is just a React component and entirely built by code. And so I can make an infinite amount of these at scale and I've done this already.

• 17:43Speaker 01

  So you can see this bulk forward slash or forward slash bulk forward slash HTML. So we're going to go through this together though. How do we actually like do this process? So I, I would go and I would give it an example and we'll do this over here while this one is like working on it. We'll come back to that. But I would give it an example of what like ad I'm trying to build. A way to do this is if you don't know where to start, go to Facebook Ads Library and you can see what your like competitors or other software companies are doing in your category. This is actually how I made this initial one was I found like this before and after format. And then I basically had it build off of that before and after.

• 18:23Speaker 01

  But this whole thing, like everything you see here is just code. It's entirely code. The other way you can do this is with something like Nano Banana where you're like going and bulk generating these, right? But once I found and I built that template, I can now make all those variations. So let's go back to Claude code and let's say, okay, I want you to use the Facebook Ads API and I want you to go and scrape the pain points that you see, or sorry, actually let's restart that. I want you to use the perplexity API and go and scrape Reddit for the pain points and the outcomes that growth marketers wish they could have from like something like a Looker

• 19:08Speaker 01

  Studio or any of these other business intelligence softwares that they're using. We be focusing on like the data analyst component of it of how they can't get bandwidth or it's too complicated to get started or they can't unify their data all into one location. You can also source from YouTube. You can also source from Twitter if necessary. So I'm gonna have it go do research and deal with those pain points.

• 19:34Greg Isenberg?

  For the ad, sorry, for the ad itself, wouldn't we want to use Nano Banana Pro? Like the best image model that exists? Like, why are we using code when, you know, when we could?

• 19:44Speaker 01

  Yeah, I'm just doing this purely like this was just a way I thought about doing it. Like absolutely the Nano Banana thing. The only thing I've found with like Nano Banana is that I sometimes have trouble like getting it to stay on brand. And if I'm trying to just like figure out the messaging variations that I'm trying to go after, this can be a faster way to do that. Again, there's like a million different ways to do this exact same thing. I think, yeah, if you're going to use Nano Banana, you should look at something like, I think it's like Kai AI, I believe.

• 20:23Speaker 01

  Or, yeah, Kai.ai. And you can just like, basically it's one of these bulk buys. But we've been using that for these bulk generations. This that I'm doing costs me nothing. Like, it's literally, you know, maybe a thousand tokens to do all of these, like, these generations. And so this, that's a reason for it. So it's like, I can go, we could go and create a thousand ad variations right now, G, and like, this literally costs nothing.

• 20:54Speaker 01

  But again,

• 20:56Greg Isenberg?

  Well, that's, that's a part of it too, right? It's like your goal is going to be come up with the best ad creative that's going to actually, you know, you put in a dollar, you get $3 out. Once you get that, you can make it. Well, there's, there's two schools of thought. One school of thought is you need the best creative. So you need to send it to Nano Banana Pro to get scroll stopping creative. Another school of thought is like, well, you actually have some pretty quote unquote ugly ads that just speak to the pain points that you can kind of get a good understanding of this is going to bring you $1.50 when you put in a dollar. And then you can get it from $1.50 to $3 once you figure out the ad.

• 21:39Greg Isenberg?

  So you're kind of saying, maybe it's best to like, get as many ads as possible. Start using those, figure out the one or two or three creative that actually crushes. And then go ahead and go crazy with spending tokens.

• 21:55Speaker 01

  Totally like this, I guess a different like, I'm just trying to find like the, the format or the angle that's going to be most receptive. I'm going to remix that a thousand times, you know, after it. The, this is like the big piece of this, especially with like, how much we can do on the like, the, the, anybody can go and generate as many of these as they want, right? Like it's literally infinite, but identifying those winners like you're talking about now becomes the challenge that you're going to face with all of this. And like, we're going to get to that in a second, but the, the, the, the main thing I want to emphasize with it is like, this is malleable and flexible and the spit, the pace, like just think about

• 22:39Speaker 01

  you manually having to go create 50 advertisements in Figma. And like, you could just now make those and get those live and test those. And as soon as I find a winning like format from a, a, a language that's being said perspective, I can then go and remix that into all these other different templates. I can go and find like, what are different winning ad formats? That I can now port this to, but this is a way to just like start immediately and then get that basically out in the in in in public. I also think that like the same ideas can go into different formats like we're all, you know, already seeing this where it's like, cool.

• 23:16Speaker 01

  I made, you know, a static format. I'm now going to port that over to a UGC format and I'm sending that to the HeyGen API to pull in that. You know, like to make that creative, like pull in, pull it in as a video and then bulk upload that to Facebook, if that makes sense. So I, I like where I'm going with this or where I'm seeing this head personally is like, I'm going to build these tools. That an agent is going to have, and then it's going to be able to run this process in the background where it's basically has the ability to make new creative. It can publish that creative to directly to Facebook, which I'm going to show you in a second. It's going to then analyze what is working and then it's going to like basically turn off what isn't and promote what is right.

• 24:01Speaker 01

  And this is like, everything I'm going to show you today is at like a small scale, like this is literally like weeks of realization that's starting to happen like with this. But I just, again, I want to plant the seed of like, what is possible using this tooling to like do your, again, that middle work that historically like you wouldn't be able to to do. So yeah, is there questions about that I can try to answer?

• 24:23Greg Isenberg?

  No, let's, let's keep cooking.

• 24:27Speaker 01

  Awesome. All right. So this keeps like trying to scrape things. I'm just going to be like, um. Instead, I want you to just brainstorm, uh, pain points that people have, uh, with data reporting, specifically, uh, the unification of the data into multiple locations.

• 24:43Speaker 01

  Cool. So we're going to do that. Um, once I have all those variations, I can then say, okay, now go bulk generate every one of those. And then at that point, I can download these as a CSV. And what I will do is just wait for that to, while that's happening, we'll just get this to start downloading. And that Facebook Ads API is going to allow for us to bulk upload all of those pieces of creative that we just downloaded. So here's all those variations. I'm going to say now, okay, now, uh, use the bulk or let's do the transcription. Okay. Now use the bulk, uh, Facebook Ads generator, uh, to go and create these variations.

• 25:25Speaker 01

  Put them in the forward slash bulk, bulk.html page when you're done with this. So this is now happening. I'm going to go back over to see what the other things are going off of. All right. So let's see this document based off of the current. We'll continue to let that happen.

• 25:44Speaker 01

  Build this up. Perfect. We're going to let that go as well. So I'm looking at the scaffolding to build the bulk add generator. And we'll check in on this one to see where it's like basically added in its process of responding. And it might have completed and it did complete. So that's done. It ran for 15 minutes on its own in the background. And these are coming back. So while these are all happening and I'm waiting on them or they're waiting on me, I can then open up another one of these. I'll just click through this to just kind of get it moving. But I would then open up another one of these tabs and I would start on the next project. So the next thing that I want to do is I want to build a LinkedIn engagement scraper. So I'm going, so basically at people that engage on the LinkedIn

• 26:30Speaker 01

  or the LinkedIn posts, I'm going to pull them out and then send them to a basically add them into instantly. So we're going to go, we're going to find their LinkedIn profile using Phantom Buster. We're then going to, you know, do that whole flow. So I'll, I'll do that in a second. Let me just get this up. Give that its own section.

• 26:51Greg Isenberg?

  By the end of this podcast, you have like a hundred.

• 26:54Speaker 01

  This is literally how I'm working now. This is like, I'm just jockeying agents across. And then if I can automate them and get them to do like, like if I can figure out, okay, this is the specific lane that you can focus on. Then I'm spinning that up onto a server on Railway and I'll talk about that in a second. On like how you can on demand create databases and on demand create the servers that this software starts running in perpetuity. So we're going to do this demo one. Alright, so I want to make a workflow where it's a, basically within Slack, you'll do forward slash LinkedIn post and anybody in Slack will be able to just drop in a LinkedIn

• 27:37Speaker 01

  post that they think is a good fit. And then that's going to go and it's going to use the Phantom Buster API to extract all of the engagers and then it's going to take those LinkedIn profiles. We're going to go and enrich those with the Apollo API. And then from there, we're going to send it to the Million Verifier API. And then finally, we're going to add them to an instantly campaign. Ask me questions if you need. Alright, so I'm going to turn on plan mode for that. Let that start running in the background as well. We'll come back to these. Let them continue to cook. Publish the landing page. Let me get context on what this one is again.

• 28:16Greg Isenberg?

  This is the craziest part when you're going from screen like screen to screen and realizing that you're an agent jockey and that you're trying to get context on each one. You're like, okay, what was this one doing again? And I find that the context switching is actually difficult.

• 28:34Speaker 01

  I did as well, but now it's like, now it feels like I like that has expanded. Like, and again, this is just how I've been working for the last like six weeks. And it was like, maybe I could have like two or three of them in the beginning. And now it's like, I'm comfortable with like, we could have 15 windows open. I'm about to literally go buy a new computer because I'm like, I need more RAM. I need more like ability to do this in the background.

• 29:00Greg Isenberg?

  Totally. Yeah. Like, like and comment this video so that, you know, I could send some YouTube AdSense revenue to Cody. We can get some more RAM.

• 29:12Speaker 01

  It's all ridiculous.

• 29:13Greg Isenberg?

  This guy needs some RAM.

• 29:14Speaker 01

  No, man, we, it's like, I'm just realizing like what this turns into. So, okay, we bet, we made all those pieces of ad creative, right? Got those variations and it's just text variations. Alright, so now I'm going to go back to Claude and I'm going to be like, I want, now I want to buckle a bulk upload all of these ads as drafts into a Facebook ad set. Here is the, or here's where the folder is locally for the creative and I'm going to provide the Facebook ads, ad set URL to you in a second.

• 29:53Speaker 01

  Alright, so I'm now going to go back to Finder. And I'm going to copy this. Paste that in.

• 30:04Speaker 01

  And then let's go back to Facebook. And I have this ad set that I've already created for this demo. It's basically just here. And I'm just going to paste in this URL. And so now here's that URL. It's going to basically bulk upload all of those pieces of creative into that ad set. So while that's happening, I'm now going to go and I'm going to create a dashboard about this. So let's just pull out the ad set ID. Let's do the ad set ID. And I'm going to go over to Graft and I'm going to be pull up Facebook Ads as the data source.

• 30:49Speaker 01

  And then I'm going to be say, this is the ad set ID.

• 30:58Speaker 01

  Make a dashboard showing clicks over time. Also have a scorecard that, or sorry, I didn't do the transcription. Make a dashboard showing clicks over time as a line chart. Also, within that line chart, can you include the cost and the CPC as lines as well? And then add a scorecard also that has total spend, total traffic or total clicks as another scorecard. So those are two separate ones. And then I want you to also show demographic data as a bar chart of showing the ages. So that's its own separate chart. That's a bar chart basically showing the impressions by the age categories. So I'm going to let that run in the background.

• 31:44Speaker 01

  We'll come back to that in a second. But now that I'm have this campaign that's running. And I'm trying to track what's happening within it. I can basically go and like build out a tracking dashboard for this. The other thing that I can do, so once it's got the ad set with destination URL, would you like just put them as a draft? So. While that's working, I can also analyze what is happening in that specific ad campaign. And I can turn off the losers of that ad campaign. So I'm going to show you how to do that. So I do documents forward slash graft forward slash growth agents.

• 32:30Speaker 01

  And then Claude. And then I'm going to get that URL again. And I'm going to say,

• 32:38Speaker 01

  use the graft MCP to pull in the data for this ad set that I'm about to provide from Facebook ads. I want to look at the CPM data to see which ones are the lowest performing, like the highest CPM price.

• 32:55Speaker 01

  All right. And then let's provide the ad set URL again. Let's go ad sets. And then while that's happening, we can come in and check on the other ones. All right. So it's now built that entire bulk Facebook ad generator. Or sorry, which one is this? This is the local one. Okay. So it's made the updates to these ads. These are an entirely new ad set that it's basically pulling in. So I already did this, right of like downloading these as a zip and bulk uploading them. So we won't go through that process again, but this is how easy it is to basically make those variations.

• 33:39Greg Isenberg?

  So and not just variations, these are variations based on pain points that people have said publicly.

• 33:45Speaker 01

  Yes, exactly. So it has pulled in basically the social dialogue that's happened. So the best ads that I'm seeing perform right now are basically you're selling outcomes or you're talking to the pain points, right? And so I'm just guiding it to focus on those things, pull me that information and then build the ad sets around those. So while that just happens, this in the background just used the graft MCP to pull in all of the low performers. So these are the, let's look at the ones that have the highest CPM. So these all have high CPM. So I'm just going to tell it, turn these off. I'm going to say, use the Facebook Ads API to turn off these ads with this ad name.

• 34:32Speaker 01

  And so now it's just pulled in this live data from my data warehouse. And this isn't an MCP that's interacting with the Facebook Ads API. I just want to like emphasize this. So it's not have, you're not running into rate limits. Like again, if you go and publish like a thousand ads and are running those variations, there is literally no way, like if you're spending enough, like there is literally no way that you're going to be able to analyze this data without a data pipeline and a data warehouse. And so this is like what we've built right at Graft. So anyways, just to get back to the MCP thing, there's like this Page Nation problem. So like we see this all the time where people are like, yeah, I plugged into Facebook Ads MCP. I'm interacting with it.

• 35:15Speaker 01

  And then I realized that I'm only seeing like 5% of the data that I think I'm actually seeing. Right? But so coming back to this, I've now said, hey, turn these off. So it went and it paused those ads for me. And so it's just, just to walk through what we just did, just kind of reiterate this. We just did ideation. We just did bulk ad creation.

• 35:38Speaker 01

  We just analyzed the data for the performers. We just turned those off and on based on that.

• 35:45Speaker 01

  And at this point, you're probably starting to have the epiphany like, oh, I can just turn this into a repeatable process. And this is where I see all of this going, basically, is you're going to be going to have these agents that are running on top of your live data. They're analyzing it, making decisions based off of like the, the model. So like, for example, how I would run this is I would have a test campaign where I'm basically testing new creative constantly. I would have a cron job that's on a daily basis, basically going and turning off the low performers. And then the high performers, they get bumped up into their own ad sets with their own dedicated ad budget for CPA action. And then that whole thing could just run automatically in the background.

• 36:29Speaker 01

  And then to track that, I'd build out a dashboard that basically is showing me, you know, that information so I can come back to that like later on and see what's occurring there. And then the other thing that I would then go do is like potentially have a conversation in the morning, say, for example, so I've got the graph MCP in my Claude, I like chat. So this is also technically on my phone. So like in the morning, I'll wake up and be like, how much traffic, let's just do this, how much traffic went to the, or how many new users went to the homepage of the website yesterday? And I'll just say, use

• 37:11Speaker 01

  the graph MCP and Google Analytics four.

• 37:16Speaker 01

  And we'll let that run. And so I can basically get a brief each morning, whatever those KPI metrics are that I care about and have a conversation like with my data that's live and being seen continuously within the background. And you can give this to your whole team as well, so that everybody on your team also has access to this, both from within Claude code, within their, like, whatever their harnesses that they use, whether that's chat TBT or Claude, and then also the ability to like do that tracking within like dash boardings or conversations. Now, coming back to all of this, right, we've just built out basically this whole like cycle of funnel. How would I now go deploy this? So this is where it gets like the most interesting. So what I'm doing right now, say, I wanted to turn this

• 38:01Speaker 01

  into an agent. I'm using Railway for this. And the only reason is just because I saw a tutorial and that's how I've like figured out how to do this. So Railway has a really robust API key. And say I wanted to spin up, for example, this bulk ad generator, so that my other team members could use this, right? They could come back and basically like use this software that I've created. I can just tell Railway via Claude code, hey, spin this up into a

• 38:33Speaker 01

  like a server that I can access, or I can just deploy this directly to Vercel, or any of these workflows that I have. So say, for example, we were talking about that LinkedIn funnel. Let's go see which one of this it is.

• 38:50Speaker 01

  Alright, so this is the podcast software.

• 38:55Speaker 01

  This is the image generator. This is the LinkedIn. So, say I want this to be accessible in perpetuity in the background. I can then take the software that I co-work on with Claude. And I say, "Okay, deploy this to a server on Railway." So that my whole team can basically use this action or always be adding. Like whenever they come across a LinkedIn post, as an example. They could be adding that into the queue so that it just automatically goes into the email. Like filtering. Sorry, the email, like cold email process. And this even goes further. So like, how I'm starting to use this G and I'm curious like to get your thoughts on this.

• 39:39Speaker 01

  So basically like, I had to do some data analysis work the other day. Historically, I would have like downloaded the information, put it into Excel, and then I do a bunch of pivot tables. Now, instead, what I did was I went directly to the URL. I had to push it into a Postgres database that I on the fly created using the Railway API. It just pumped everything in there. I then did the analysis together with Claude. And then at that point, I basically pushed from that Postgres database. The outputs to the location that I wanted. What have used it would have, it would have taken me probably five hours historically to like clean the data appropriately. And I smashed that out in like probably 20 to 30 minutes.

• 40:23Speaker 01

  And then as soon as I got done with that database, I just spun it down.

• 40:29Speaker 01

  And this was the most like interesting part of this was that like, it was basically like on the fly UI. On the fly, or the epiphany I had was like on the fly UIs, on the fly databases, like on the fly software is going to become the standard for these people that are like, you know, working at the forefront of this. So, um, yeah, man, I, we could probably, you know. Sit here and watch me work for hours if you wanted, but that's kind of everything I had that I wanted to show you today. The only other thing I'm just like, keep getting asked, like, how do I do this? How like, show me more technical details. I bought the domain GTM Engineering Course.com. I'm going to give this thing away for free to everybody who wants it.

• 41:14Speaker 01

  It'll be entirely public. I've already got a waitlist of 100, but basically I'm just in the process of building this out with like step by step. And it's everything that I do, I'm just going to document it to one place. But anyways, just throwing that out there as a last thing. But any, I'd be curious, I'm like, okay, you see, you just watched this and you're in like a role at some company.

• 41:36Speaker 01

  How do you defend against this, like with your job? Or do you, is it just like, you need to learn this now? And like, I want to hear your thoughts because you're seeing way more than I am with everything.

• 41:46Greg Isenberg?

  I'll tell you my, I'll answer your question, but I want to start by saying like my biggest takeaway from all of this.

• 41:51Speaker 01

  Yeah.

• 41:52Greg Isenberg?

  So my biggest takeaway of all this is when you connected it with Railway. And I, it's a glimpse into the future of autonomous marketing. So marketing, you know, all you basically, what you've done, like all those sort of

• 42:11Greg Isenberg?

  jobs to be done, were jobs to be done that were literally done by human beings, right?

• 42:17Greg Isenberg?

  And then you kind of stitched it together, you know? If you've ever run ad campaigns before, you know how painful some of these things are.

• 42:26Speaker 01

  Like just uploading the ads alone. I was like, I have literally spent like, I mean, I'm just imagining uploading a thousand ad variations. Like dude.

• 42:40Speaker 01

  Like it just.

• 42:40Greg Isenberg?

  Don't give me PTSD on the pod.

• 42:44Speaker 01

  I did this early in my career, it was absolutely painful.

• 42:47Greg Isenberg?

  It was painful, right? It was painful and, and it's not fun. It's not fun at all. Removing and figuring out low performers at a creative, not fun, not fun. And you need to be on it.

• 43:01Greg Isenberg?

  So the idea that you can, you know, make this an agent that's working 24/7 and that's managing all these different things is the dream. It is absolutely the dream, autonomous marketing, the dream. I think.

• 43:17Greg Isenberg?

  Who are the winners and who are the losers of this? The winners are gonna be, you know, one-person businesses, small teams.

• 43:29Greg Isenberg?

  And then maybe you're, you're head of marketing that currently are getting paid $100,000 a year. Now, all of a sudden, if you can figure out how to do all these things, and this is where I'm answering your question. If you can figure out how to do all these things, you know, you could make the case like, hey, triple, you know, triple my salary.

• 43:48Speaker 01

  Easily.

• 43:48Greg Isenberg?

  Right? Like, from a value perspective, like, if you can do all these jobs to be done, you're one person instead of 10. There is a case to be made that you've made, you know, you've added a tremendous amount of value to, to your role. So I think, and then the unfortunate thing is, I think a lot of, a lot of these jobs to be done, and this is where I disagree with a lot of people, is I think that there is gonna be a lot of job loss, real job loss. Like, it just, who, anyone who just walks-

• 44:18Speaker 01

  I think it's going to be extremely rapid job loss. And then, like, I'm just thinking about, like, the early days of, like, what we saw, you know, in the Industrial Revolution and, like, the United Kingdom. Like, they, I mean, you basically have this displacement and then new roles get created. But like, in that interim, still, a lot of turmoil happens.

• 44:38Greg Isenberg?

  It's gonna be chaos.

• 44:39Speaker 01

  It's gonna be chaos. And I, like, I have a friend who runs a startup and he texted me yesterday and he's like, I think I'm gonna fire 50 people. And that's like 70% of his team, right? And I'm just over here and I'm like, how, why, what, you know, tell me the reason. He's like, I think I can automate all of their jobs right now with, like, agent swarms. And I'm like, okay, what's an agent swarm? You know, because that's just this, like, throw, like, term that gets thrown around right now. And he's like, oh, it's just an agent that does, like, a specific thing? And then there's an agent that manages, like, that whole system? And then, like, imagine, like, five pillars under, like, another agent? And I'm like, oh, I've built that. That's what an agent swarm is.

• 45:20Speaker 01

  And I think that this is the thing that, like, people aren't real, because now it just runs in the background. See, like, I have one that's just, like, crawling LinkedIn, like, as we speak. And it's, like, looking for, like, ICP. And then it enriches them, it writes a personalized email and it cold emails them.

• 45:36Greg Isenberg?

  Yeah.

• 45:36Speaker 01

  And like- I don't think people understand like what's about to happen in like the next 12 months. So, and I'm excited about it because I think there's like, again, if you can build, like it is incredible. Like you're so capable right now, especially if you have domain knowledge. The other thing that I'm finding is like, just because you can, like it can be built, doesn't mean that you can build it because you don't have the vocabulary. Like when I look at like my co-founder Max, right? And his technical vocabulary, how he can describe the problem to a coding agent is so much more sophisticated than I'll ever be able to do it. And so the output quality that he can get from this is at like a level that's in the top 10, top 1%.

• 46:19Speaker 01

  So if we translate that to something else, like say you studied graphic design for 20 years and like you've been working in the industry for 20 years. The vocabulary you have to describe something is going to be so much more sophisticated than what I have. So I'm like, this happened the other day where I'm like, I wanted to put texture on the back of an ad. And I was like, how the fuck do I do that in the background? I tried trying to describe it, it came out terrible. And then I found this like person giving a description of like, how do you make it have a TV type texture? Right? And it was like all of these, you know, specific, like it was like a specific lexicon to describe it. To call it, literally one shots it, you know, immediately like what I was looking for after that. And I had, you have that realization that this actually becomes like the superpower.

• 47:00Speaker 01

  If you can incorporate these tools into what you're doing for work and have that domain expertise, that knowledge that's like on top of that. That actually is what makes you like incredible. And so it's the same thing that we've always seen where it's like, oh, you have one or two skills with like a deep tea. And then you like, that was makes you valuable. This is like that, but like, you know, times a thousand, where it's like, if you have the vocabulary, you know, and six things. And you come to the, this tooling and can basically express and explain like what you're needing or what you're looking for. It changes the entire system in my mind, but I, again, I would love to hear your thoughts on like where you like. And also just like what you're seeing within your own companies that you own and all like, you know, within the market as well.

• 47:43Greg Isenberg?

  Well, I, I think the reality is there's a lot of people, even if they have a ton of domain expertise. They don't know the tools and how to use the tools optimally yet. Now I think that the tools are going to get so good that the UX is going to be so easy at some point. But for right now, like for example, if we, if we. Counted off all the tools that you mentioned in this, in this podcast. You probably mentioned 17, no more, 20 tools. I'll include some of those in the show notes. Yeah, I'll give you the list of them so that you can pass them on. Phantom Blaster instantly, like, I'm not even talking about like Claude Code and stuff like that.

• 48:25Greg Isenberg?

  You, you, like, you've done your research, you've found the tools and, you know, I think that's why a lot of people listen to this podcast. They try to, you know, it's a way to, for them to learn a lot of that stuff. But the point is, I have a lot of respect for the people that understand they have domain knowledge, know that that domain knowledge is super valuable and who are going out there and trying things. But yeah, this, you know, the other sort of takeaway I have from this podcast is your insight around APIs, which I thought was really interesting. So like, in the old way, in the old way of like SaaS tools and stuff like that, you, you didn't, I mean, it was nice. An API was a nice to have, you know?

• 49:10Greg Isenberg?

  It was about how good is the software that you're using? How good is the UX? How good is the brand? How good is, you know, when you press this feature? How quick is it? How instant is it? But now, when you're living in a terminal, for example, and you're using MCPs to talk to LLMs, you kinda, you know, the nice to have is actually the, the UI. The nice to have is the SaaS. The nice to have is going to this website and looking pretty. Ultimately, what you care about is the output and the thing is running, the agents are running, you know, 24/7. They aren't, you know, hogging tokens. The output is high quality. It's doing the thing that it's, says that, you know, it should do.

• 49:53Greg Isenberg?

  And I think Sam Altman said recently something about APIs. I think he said, The every company is going to be an API company.

• 50:02Speaker 01

  Totally. I align with this. Like now doing this, like I, there's a software, like I just won't put them on blast because I know how big your audience is. But like, like there's a thing you can do in their UI. I can't do in their API and I'm literally about to churn because I'm just like, this is critical for me. And now it feels archaic for me to go and interact with your fucking A, you like UI to do this outcome, like output that I'm, that I'm like, I need. And I think that this is going to be, like, I think there's going to be companies that are entirely just like, like what, what it, I mean, we literally had this conversation internally, like, do we build an A, like a UI? Because that even a thing that we do, or do we just build the tooling that enables you to see like where we see the puck going? And I think that like,

• 50:46Speaker 01

  you know, I, we had to come, you know, have a come to Jesus moment of like, oh, this is a, like where we know the puck is going is entirely different than like where the normie like is right now and like the adoption cycle of this. And so like having to like meet there to ride this, but like, I mean, it's very clear, right? Like, for example, like with the graph MCP, that's a live data feed. So I may, I'm like, when I'm like, show me my Google ads and Facebook ads, paid ad spend, right? That's a live data feed that's happening underneath the hood. It's like a, it's like an endpoint that I'm hitting. It's literally on the fly, generating a live data endpoint that I can pull from my data warehouse from. So with that, I can basically build whatever I want on top of that.

• 51:28Speaker 01

  And I'm like, okay, well, let's just go build a custom dashboard like for what we need. But what we're finding is that like, there's like kind of different use cases, like the, I guess what I'm trying to say is like, you're basically making your agent so that, or whatever it is your tooling is, so that it fits into any harness. So whether you're working from Claude iOS or ChatGPT desktop or Claude code on, you know, in your terminal or like cursor or, you know, even the UI, it's unified across that. And people can basically take that wherever they want and get the same outputs. And so from a product standpoint, this is how we're like, you know, focused on it and kind of moving forward. And I think it. Again, what it comes down to though is like everything that like we're talking about this tooling

• 52:13Speaker 01

  piece like unless you know what to do, it's very hard to get it to like if I if I didn't know this these exact toolsets to use to like go and do these actions like here's how to do this LinkedIn thing as an example, there would be like a very low chance that it would be able to figure this out. It's totally possible. It can. It's just like gonna take longer. And you can do this now with like Claude and with perplexity where you're like, I'm trying to do X, list five APIs that can help me do that. But I think this is how people are gonna start building this. And like, I'm finding myself doing this. Where I'm like, I have this like vision of a workflow, and I'm starting with the final product. And then I'm like, working back and like, you know, basically piecing together, how does this work? And then having the agent go and build that for me. And so then, this comes

• 52:57Speaker 01

  back to like, how do agents discover the the necessary infrastructure for and like, how do you be the thing that it picks when it's going to build, you know, XYZ thing? And like, again, these are the things I'm losing sleep over now as we're like, getting deeper and deeper into this.

• 53:13Greg Isenberg?

  Well, Cody, I appreciate you being so saucy with with sharing all the stuff with us. We do appreciate it. I need, you know, it's been too long. It's been too long. You need to come back on again. And and share some ideas and stuff like that. So would love to have you. And

• 53:31Speaker 01

  Have a ton of them, man. You can go for days about Chrome extensions right now. You can literally have Claude code one shot them and just turn on Facebook ads in the background automatically. I also have an agent that was running an Etsy shop for a little bit. That was crazy. It just got banned two days ago, which was hilarious. So.

• 53:47Greg Isenberg?

  So people, please, you know, let's beg Cody to come back on the pod and have him on soon. This is an open invite, Cody. You can come on whenever you'd like. Share ideas. You get you definitely get my creative juices flowing. So I appreciate you so much. And

• 54:01Speaker 01

  Appreciate it, G. Thanks for your time as always, man. I always love coming on.

• 54:05Greg Isenberg?

  Thank you.