Modern Creator
Why Modern Creator?
Greg Isenberg · YouTube

Claude Code & MCPs built my $145K marketing machine

A 54-minute live demo where Cody Schneider runs seven AI agents simultaneously to build a full GTM machine — ads, outreach, cold email, data analysis — with Greg Isenberg watching.

Posted
3 months ago
Duration
Format
Interview
educational
Views
90.5K
2.2K likes
Big Idea

The argument in one line.

Domain expertise is the real multiplier in AI-powered marketing — the vocabulary you bring from your field determines the ceiling of what agents can produce, and the first practitioners to internalize this will do the work of entire teams alone.

Who This Is For

Read if. Skip if.

READ IF YOU ARE…
  • You run paid ads manually and have spent hours uploading creative variations in Facebook Ads Manager.
  • You do cold outreach and want to automate the enrichment-to-send pipeline without hiring an SDR.
  • You are a solo founder or small team trying to replace fractional marketing hires with always-on agent workflows.
  • You buy SaaS tools primarily for their UI and are starting to wonder whether the API is what actually matters.
  • You want a concrete starting point for GTM engineering beyond prompting an LLM to write ad copy.
SKIP IF…
  • You are looking for a polished, step-by-step written tutorial — this is a live, sometimes messy screen-share demo.
  • You have no existing marketing stack with API access; the approach assumes you already subscribe to Instantly, Phantom Buster, and similar tools.
  • You need to understand underlying AI concepts before seeing applied use cases.
TL;DR

The full version, fast.

GTM engineering started as Clay-style data enrichment for outbound sales, but Claude Code has evolved it into full-stack agent orchestration where one person can replace a marketing team. The practical entry point is a single folder with an environment file holding every API key you already use, then spinning up parallel Claude Code instances. Cody demonstrates this across seven simultaneous agents: LinkedIn outreach, bulk Facebook ad creation at near-zero cost, cold email pipelines, Notion doc generation, and live ad performance analysis. The most durable insight is that domain vocabulary is the real multiplier — the more precisely you can describe what you need in your field language, the better the agent executes, and that advantage compounds.

Free for members

Chat with this breakdown — free.

Sign in and you get 23 free chat messages on us — ask for the hook, quote a framework, find the exact transcript moment, generate a markdown action plan. Bring your own key when you want unlimited.

Create a free account →
Voices

Who's talking.

00:00hostGreg Isenberg
00:51guestCody Schneider
Chapters

Where the time goes.

00:00 – 02:01

01 · Intro

Greg teases the episode promise: learn to build agents that handle marketing, sales, and growth 24/7.

02:02 – 05:11

02 · What Is GTM Engineering?

Cody traces the term from Clay.com data enrichment to full agent orchestration — passing all middle work to AI.

05:12 – 07:53

03 · Setting Up Your Agent Workspace

One folder, one .env file with all your API keys, Super Whisper for voice input, Claude Code front-end skill.

07:54 – 09:55

04 · Live Demo: LinkedIn Auto-Responder

Agent runs in background responding to LinkedIn post engagers who asked for a giveaway asset.

09:56 – 12:30

05 · Live Demo: Bulk Facebook Ad Generator

React components as 1080x1080 ad creative, HTML-to-Canvas for PNG export, Perplexity/Reddit for pain-point research.

12:31 – 14:46

06 · Live Demo: Cold Email Pipeline

Raphonic scrapes podcast host emails, Million Verifier validates, Instantly AI sends — entire pipeline built in one session.

14:47 – 16:44

07 · Live Demo: Notion Document Creator

Claude Code writes structured Notion docs using repo templates as style guides.

16:45 – 26:04

08 · Live Demo: Ad Creative at Scale

Walking through the bulk ad generator; Facebook Ads Library for competitor research; cost comparison with Nano Banana.

26:05 – 28:14

09 · Live Demo: LinkedIn Engagement Scraper

Slack slash-command triggers Phantom Buster, Apollo enriches profiles, Million Verifier validates, Instantly adds to campaign.

28:15 – 29:17

10 · Context Switching as a Skill

Cody reflects on managing 15 parallel agent windows; started with 2-3, expanded over 6 weeks.

29:18 – 35:00

11 · Live Demo: Bulk Facebook Ads API Upload and Dashboard

Bulk-uploading generated creatives as drafts into Facebook ad set; building a live clicks/CPC/spend dashboard.

35:01 – 38:47

12 · Live Demo: Ad Performance Analysis

Graphed MCP pulls live Facebook Ads data; Claude identifies highest-CPM losers; Facebook Ads API pauses them.

38:48 – 41:07

13 · Summary: The GTM Engineering Loop

Ideation, bulk creation, publish, analyze, optimize, kill losers, promote winners — the full cycle in one session.

41:08 – 44:47

14 · Deploying Agents to Railway

On-demand Postgres and server creation via Railway API; five-hour data analysis compressed to twenty minutes.

44:48 – 48:49

15 · The Dream of Autonomous Marketing

Winners: one-person businesses and small teams. Losers: entry-level marketing headcount. Real job displacement coming.

48:50 – 54:07

16 · API-First Products and Agent-Native Infrastructure

The API is now the product; SaaS UI is a nice-to-have; Graphed MCP as live data feed; domain vocabulary as competitive moat.

Atomic Insights

Lines worth screenshotting.

  • GTM engineering is no longer about data enrichment — it is about delegating every keyboard-touching task to an agent and polishing the output.
  • Your environment file is your power plant: one folder, one .env, every API key you already own, all accessible to every Claude Code instance at once.
  • Running ten Claude Code windows simultaneously is parallelized delegation, not chaos — the context-switching skill is learnable within weeks.
  • React components exported as PNGs produce bulk ad creative at near-zero token cost; test a thousand messaging variations before spending on polished visuals.
  • The Facebook Ads API pagination problem means you are likely only seeing 5% of your actual ad data when querying it through an MCP directly.
  • Domain vocabulary is the 10x multiplier: a graphic designer who can name a TV-static texture will one-shot what a generalist spends an hour iterating on.
  • The best-performing ads right now speak directly to pain points or desired outcomes — and Reddit gives you that language verbatim for free.
  • Deploying a Claude Code workflow to Railway turns a one-off agent session into a 24/7 autonomous process with zero additional prompt work.
  • On-demand databases: spin up Postgres for a data analysis task, use it, then spin it down — no persistent infrastructure overhead required.
  • API robustness now outweighs UX quality when choosing tools — if a critical action is not accessible via API, the workflow cannot be automated.
  • The middle work — everything between having an idea and a polished output — is being eliminated; humans become idea-generators and output-polishers.
  • Autonomous ad management as a closed loop is achievable today: generate, publish, analyze, kill losers, promote winners — no human in the middle.
Takeaway

Your vocabulary is your unfair advantage.

WHAT TO LEARN

The bottleneck in AI-powered marketing is no longer access to tools — it is the precision with which you can describe what you need.

02What Is GTM Engineering?
  • GTM engineering evolved from Clay-style outbound data enrichment into a framework for delegating all middle work — anything that required touching a keyboard — to AI agents.
03Setting Up Your Agent Workspace
  • A single folder with one .env file holding every API key in your stack is the complete infrastructure required to start; voice transcription software removes the keyboard from the prompting loop entirely.
05Live Demo: Bulk Facebook Ad Generator
  • React components rendered to PNG via HTML-to-Canvas produce ad creative at near-zero cost, enabling hundreds of messaging variations to be tested before committing budget to polished image generation tools.
  • Pain-point language sourced from Reddit via the Perplexity API gives ad copy the specificity that converts — it is the language real customers already use to describe their problems.
06Live Demo: Cold Email Pipeline
  • A complete podcast outreach pipeline — scrape hosts, verify emails, add to campaign — can be built and running inside a single Claude Code session by chaining three existing API services together.
10Context Switching as a Skill
  • Managing ten to fifteen parallel agent windows is a learnable skill that expands with practice; Cody went from two or three concurrent sessions to fifteen over six weeks of daily use.
12Live Demo: Ad Performance Analysis
  • Live Facebook Ads data pulled through a data warehouse MCP lets Claude identify and pause high-CPM losers in a single prompt — closing the ideation-to-optimization loop without touching the Ads Manager UI.
  • Direct MCP-to-Facebook-API connections have a pagination problem that limits data visibility to roughly 5% of actual ad performance; routing through a data warehouse eliminates this.
14Deploying Agents to Railway
  • On-demand Postgres databases created via the Railway API let you run analysis tasks against structured data and then tear down the database when done — no persistent infrastructure to maintain.
  • Data analysis that historically took five hours in Excel can be completed in twenty minutes by loading raw data into a temporary database and analyzing it conversationally with Claude.
15The Dream of Autonomous Marketing
  • The near-term winners of AI-powered marketing are one-person businesses and small teams who can now do the output of a large marketing org; the losers are entry-level marketing roles consisting primarily of middle work.
  • Domain expertise is the real moat — the vocabulary gap between a domain expert and a generalist determines the quality ceiling of what either person can extract from the same AI tools.
16API-First Products and Agent-Native Infrastructure
  • When your primary interface to software is an LLM agent rather than a browser, API robustness replaces UX quality as the most important product attribute.
  • The goal for any tool or service is to be callable from any LLM harness so that domain-expert users can integrate it wherever they already work.
Glossary

Terms worth knowing.

GTM engineering
Go-to-market engineering: originally Clay-style data enrichment for outbound sales, now broadly used to describe any technical workflow that automates marketing, sales, or growth tasks using APIs and AI agents.
Environment file (.env)
A plain-text file storing API keys and credentials as key-value pairs, used by Claude Code and other tools to authenticate with external services without hardcoding secrets in scripts.
Agent harness
A software environment like Claude Code that gives an AI agent the ability to read files, run code, call APIs, and execute multi-step workflows autonomously based on a single natural-language prompt.
Graphed MCP
An MCP server built by Graphed that exposes live data warehouse feeds — Google Ads, Facebook Ads, GA4 — as queryable endpoints that any LLM harness can call in real time.
Phantom Buster
A LinkedIn automation tool with an API that can extract profile data, post engagers, and other social data at scale without manual browser interaction.
Instantly AI
A cold email sequencing platform with an API for programmatically creating campaigns, adding leads, and managing outreach sequences.
Million Verifier
An email validation API that checks whether an email address is deliverable before adding it to an outreach campaign, reducing bounce rates.
Railway
A cloud infrastructure platform with an API that allows programmatic creation of Postgres databases and server deployments, enabling on-demand infrastructure that can be spun up and torn down per task.
HTML to Canvas
A JavaScript library that converts rendered HTML including React components to a PNG image, enabling code-generated ad creative to be exported as downloadable image files.
Resources

Things they pointed at.

01:15toolClaude Code ↗
02:12toolPhantom Buster ↗
02:12toolInstantly AI ↗
04:19toolRaphonic
06:01toolrailway.com ↗
07:30toolFacebook Ads API ↗
07:30toolMillion Verifier ↗
07:43toolSuper Whisper ↗
10:17toolPerplexity API ↗
17:55toolNano Banana Pro
20:10toolKai AI ↗
23:12toolHeyGen API ↗
25:56toolApollo API ↗
36:37toolGraphed / Graphed MCP ↗
51:11linkGTM Engineering Course (free) ↗
Quotables

Lines you could clip.

03:06
“Everything that I would do to touch the keyboard, I am now passing it on to some type of agent harness.”
Clean one-liner that defines the whole GTM engineering shift→ TikTok hook↗ Tweet quote
20:36
“This costs me nothing. Like, it is literally maybe a thousand tokens to do all of these generations.”
Concrete cost claim that challenges the assumption that quality creative is expensive→ IG reel cold open↗ Tweet quote
27:00
“I am just jockeying agents.”
Three words that reframe the job of a modern marketer→ newsletter pull-quote↗ Tweet quote
40:41
“On the fly UIs, on the fly databases, on the fly software is going to become the standard for these people working at the forefront of this.”
Thesis statement for the post-SaaS era of software→ TikTok hook↗ Tweet quote
44:45
“I have a friend who runs a startup and he texted me yesterday — he is like, I think I am gonna fire 50 people. And that is like 70% of his team.”
Concrete alarming anecdote that grounds the job displacement argument→ IG reel cold open↗ Tweet quote
47:09
“If you can figure out how to do all these things, you could make the case — hey, triple my salary.”
Optimistic counterpoint to the job displacement argument→ newsletter pull-quote↗ Tweet quote
Topic Map

Where the conversation goes.

00:00 – 05:12steadyGTM engineering definition and context
05:12 – 10:00denseWorkspace setup and tooling philosophy
10:00 – 35:00denseLive demos: LinkedIn, ads, email, Notion
35:00 – 41:30denseDeploying agents and Railway infrastructure
41:30 – 48:50steadyJob displacement and winners vs. losers
48:50 – 54:07denseAPI-first products and domain vocabulary moat
The Script

Word for word.

Read-along

Don't just watch it. Burn it in.

See every word as it's spoken — crank it to 2× and still catch all of it. The same dual-channel trick behind Amazon's Kindle + Audible.

00:00How 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.
00:09You can vibe code anything and right now, and that's great. But how can you actually use AI agents to get you customers twenty four seven? Well, today we live build it.
00:19We actually spun up 10 Cloud 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.
00:29He'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 gonna feel pretty confident you know what to do.
00:39You are in for a treat. Enjoy the episode, and I can't wait to see you in there.
00:51Cody, by the end of this episode,
00:54what are we gonna learn? You're gonna 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 gonna come out of it with this whole new tool set that allows for you to do all of the middle work without touching a keyboard.
01:16You're just gonna use your voice and have agents do work for you in the background, man. It's gonna be crazy. Okay.
01:22And can you list off a few of the piece tools and pieces of software we're gonna use? Like
01:27Yeah. Absolutely. We're gonna touch Phantom Buster.
01:30We're gonna use Instantly AI. We're going to use Vraphonic. We're going to use railway.com.
01:38We're also going to use a bunch of different other tooling that's in my go to market stack. So we're also just gonna use, like, the Facebook Ads API as an example, as another just, like, you know, way that we're gonna interact via this this agent harness clog code.
01:56Alright. And we're gonna live build it and everyone well, you're gonna watch you're gonna watch the whole thing, so let's get into it.
02:02Cool. Sweet, man. So just to begin with, do do you know, like, GTM engineering or, like, what it even means or, like, where it comes from?
02:11No. Honestly, I don't. That's why I'm like a buzz it's just a buzzword.
02:14Right? So this is it's actually, like, made up by clay.com, which is hilarious.
02:19And they originally did it as, like, a 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.
02:35So 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.
02:46And 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 alright? Yeah.
02:59Cool. 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 hardest, whether it's Clogcode or it's Codex or any of these tools.
03:17And so my job suddenly turns into, like, I have ideas. I pass them on to Clogcode, and then I'm basically polishing the end product.
03:26And it 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, we're gonna do this today. Like, build a 100 Facebook ads, publish them to Facebook, build a dashboard to track that, analyze the data within Clogcode, have it turn off the Facebook ads that are the low performers, have it bump up the Facebook ads that are 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, thirty minutes.
03:59I'm anyways, again, not really sleeping. So this is kinda where it's at now, and I'm gonna talk through, like, this whole setup process and actually how to do this. And then I'm gonna talk about where it's going, like, how agents are the natural evolution from this.
04:13Basically, as soon as you, like, start you have this epiphany of, 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 this onto a server, and now it's doing this task for me in the background.
04:28And I'm building out this personal software for myself, for my job, for my my, you know, tasks, etcetera. And this isn't some, like, hype thing of, like, go do OpenCLAW and give it access to everything.
04:40I'm talking about, like, specific, like, jobs to be done workflows that are custom made for how you wanna operate in your day to day.
04:49So that's kind of the high level, man. Any questions I can try to answer? Happy to go deeper on anything.
04:53No.
04:54I'm 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?
05:04Right? Because that's gonna be an unfair advantage.
05:07So, yeah, let's let's go let's go through it. Perfect. Let's jump into it, man.
05:11Alright. 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 gonna start living out of. So the one I live out of is called graft graft growth agents.
05:24So everything I do now where I start my work, it all exists within here. And the first thing that I'm gonna have you do is you're gonna 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.
05:43So what I'm doing is I'm basically having and I'm just not gonna show this just because it has literally all of our API keys for everything, but it has I can open up this example one. So it has, like, Intercom.
05:56It has our SendGrid API, my HubSpot API, my cal.com API, my Perplexity API, my Facebook Ads API, in million verifier, instantly.
06:06Everything 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 what this translates into or, like, why I'm 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.
06:27And 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 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.
06:53And this is what this, like, turns into is your all of the work that you're doing, and we're gonna do this together today, is going to be happening from this this, like, repository. When when I say repo, all I mean is just this, like, folder that we're living in that has all of these files.
07:08I'm gonna 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. So that's kind of one component of it.
07:21The last piece is then I would strongly suggest get suggest getting something like a SuperWhisper 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.
07:37And 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 gonna generate a UI, it's nice to have it look pretty. So alright.
07:49That is kinda the foundational pieces. Now let's actually like, great. That's cool.
07:53You've just built this. What do you actually do to go get started on this? So the first thing that I'm gonna do to get started is I'm going to go, and I'm gonna have Clog Code start responding to people on LinkedIn for me that have asked for an asset.
08:07So 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, Notion document.
08:16I'm now gonna go in, and I'm gonna 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.
08:27And I'm gonna go and I'm gonna say so I'm working out of this that directory, right, that I've already been in. And I already have built this basically skill, and it's a piece of software that will go and comment on everybody that asked for this asset.
08:43So I'm gonna say this right now. I'm gonna say, let's run or we're gonna transcribe it.
08:48So let's run the LinkedIn respond software.
08:53The keyword that you're looking for is triage. I'm gonna provide the Notion documents and the LinkedIn post URL.
09:02And then I'm gonna select the post URL and I'm gonna put that in. And then I'm also gonna select the Notion document that I want it to do as well.
09:11So I'm gonna give it that. It's gonna start running. So what it's gonna do right now is it's gonna basically open this up.
09:17I'm gonna babysit it for a moment while it while it starts this process 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.
09:28And, actually, while it's thinking, let's just go to these other places. So next thing I'm gonna do is I'm going to go or sorry. That just opened the LinkedIn profile.
09:37Let's bring that back over here. So this is now running. Perfect.
09:43And 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.
09:55So while that's happening, what I'm going to do now is we're gonna build a Facebook ads generator. So I've been doing this where it's basically a and I'll show you an example of what this looks like.
10:07Let's just go over to LinkedIn, and I can give you an example of the output that you we're going to actually create today. So it's basically a bulk generator of ad creative.
10:19We're gonna create this template, and then I'm gonna go and do research based off of Reddit and other social media posts for the pain points that people experience. And then we're gonna go and bulk generate all these variations.
10:31So 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 that skill.
10:41So I'm gonna tell it right now. I want you I want you to create a bulk Facebook ad generator.
10:48It's gonna be a ten eighty by ten eighty pixel image. What's gonna happen is I'll give you an example of what one of these ads looks like, and then we're gonna go and build a template around that.
11:01And then we'll I'll basically create a or give you variations of text, both titles and paragraphs that we I want to be generated.
11:10It'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?
11:21For the first thing I would just wanna be able to see is, like, what the actual creative will look like. For this, you're going to use just React components.
11:30So I don't want you or, like, I just purely build it with React components. And then also to actually change those React components into a PNG that's downloadable, we're going to use HTML to Canvas.
11:44It's just a, you know, resource that you have available for you on that. Ask questions if you need.
11:51So I've just transcribed that. I'm now going to put Claude into plan mode, and I'm just gonna let that start running in the background.
12:00Alright. 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.
12:08So that's happening. So we'll just let that run-in perpetuity, respond back to them.
12:14Alright. So next, I'm just gonna just click through this quickly. I'll share it now.
12:20I'll share it I'll share it after setup. And then input method, form based UI.
12:27Let's do both, and then I'm gonna hit submit. Alright. So now that's working on that in the background.
12:31I'm gonna open up another folder, and I'm going to start Clog code again within an entirely another diff or another window.
12:40So I'm gonna do documents forward slash grafts. Let's go to agents and then demo.
12:50Alright. So the next thing that I wanna build as an example is I'm going to basically pull information for so I just I I just did this actually so we could, like, talk through and about what this ends up looking like.
13:07But 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.
13:23Is what my week looks crazy. Sorry. What is Instantly?
13:26Yeah. So Instantly is a cold email software. Okay.
13:29And 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 is basically, like, my manual workflows that I would do previously.
13:47We're just, like, daisy chaining those together, like, using this software. So I'm gonna bring this into a new desktop, and let's just rebuild that whole thing. I'm gonna say you have the Refonic API key.
13:59I want you to build a software that scrapes podcast host emails from Refonic.
14:05It then sends it to Million Verifier to verify the emails, and then it also will then send it to an instantly campaign.
14:16I'll provide the instantly campaign that I want it to send to.
14:21Alright. So I've got that now. I'm gonna put that into plan mode and let that run as well.
14:28And then we have that as its own window. And so while these two are working again in the background, we'll we can then go and actually do, like, some other work.
14:40So let me get this going, and I'll just say, cool. So that's in plan.
14:46Alright. 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 kinda to show you, like, how to start it from zero to one.
14:58This folder that we're in now is my actual folder that I live out of. And I'm just gonna show you some of the things that, like, are, like, 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, like, giveaway.
15:18Right? So I'm gonna go, and we're gonna create one of these together right now because I need to actually accomplish this. So I'm gonna give take this URL and then copy this over.
15:28And I'm gonna say, okay. Write a or create a Notion document based off Look you typing with your hands.
15:39I know. The problem here, we can do it in the the transcription. So create a Notion document based off of our, like, current or, you know, our our structure.
15:48Look for the skill that has this. I'm gonna provide context on what that should include. You should incorporate stuff that we we haven't within the repo, like the documentation that I have in the repo on how to do this.
16:03Alright. And so I'm gonna copy this over and let that run.
16:07And now it's gonna go and create me a Notion document just like the one that we have being sent in the background here currently. Alright. Um, so in that folder, I've already created the, uh, bulk ad generator.
16:21So I'm just gonna go in there just to show you, like, what you can do with this once that it's 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.
16:33So that's gonna continue working on that bulk Facebook ad generator in the background. While that's happening, let's go to graphs, uh, growth agents, and then I'm gonna start clog code within there.
16:47And now I'm going to, uh, start locally the bulk Facebook ad generator. Uh, I just wanna, uh, bring that up within my local so that I can create some ads.
17:02So, again, it's already created the software for me. I'm now coming back to it. And I'm gonna talk through the whole process of the actual creation of this because it'll just, like, make more sense momentarily.
17:12But 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.
17:22So how did I make this ad? This is entirely code, and I think this is something to, like, double click on.
17:29Everything in here is just it's just React components like that. This is this is just a React component and entirely built by code.
17:36And so I can make an infinite amount of these at scale, and I've done this already.
17:43So you can see this bulk forward slash or forward slash bulk forward slash a h t m l. So we're gonna go through this together, though. How do we actually, like, do this process?
17:51So 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.
18:02A 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.
18:13This 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. But this whole thing, like, everything you see here is just code.
18:29It'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?
18:37But once I found and I built that template, I can now make all those variations. So let's go back to Cloud Code, and let's say, okay.
18:47I 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.
18:57I 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, uh, from, like, something like a Looker Studio, um, or any of these other business intelligence softwares that, uh, they're using.
19:14We've been focusing on, like, the the the 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.
19:25You can also source from YouTube. You can also source from Twitter if necessary. So I'm gonna have it go do research and those pain points.
19:34For the ad sorry. For the ad itself,
19:37wouldn't we wanna use Nana Banana Pro, like, the best image model that exists? Like, why are we using code when, you know, when we couldn't I'm just doing this purely like, this was just a way I thought about doing it. Like, the Nano Banana thing.
19:51The 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.
20:06Again, there's, like, a million different ways to do this exact same thing. I think, yeah, if you're going to use nana Nano and Banana, you should look at something like I think it's like Kai AI, I believe.
20:20Nano Banana.
20:23Or, yeah, kai.ai. And you can just, like, base baits one of these bulk buys, but we've been using that for these bulk generations.
20:33This that I'm doing cost 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.
20:44So it's like, I can go we could go and create a thousand ad variations right now, g, and, like, this literally costs nothing.
20:55Yeah. But again Well, that's that's a part of it too. Right?
20:58It'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.
21:07Once you get that, uh, 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 nana banana pro to get scroll stopping creative.
21:19Another school of of thought is like, well, you actually have some pretty, quote unquote, ugly ads that just speak to the ice the pain points that you can kinda get a good understanding of this is gonna bring you a dollar 50, uh, when you put in a dollar, and then you can get it from a dollar 50 to $3 once you figure out the ad.
21:39So you're kinda saying, maybe it's best to, like, get as many ads as possible, start using the those, figure out the one or two or three creative that actually crushes, and then go ahead and go crazy with spending tokens.
21:55Totally. Like, the the 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.
22:04I'm gonna 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.
22:22Right? 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.
22:29And, like, we're gonna get to that in a second. But the the the the main thing I wanna emphasize with it is, like, this is malleable and flexible and the spit the pace. Like, just think about you manually having to go create 50 ad variations in Figma.
22:44And, 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 language that's being said perspective, I can then go and remix that into all these other different templates.
23:00I 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.
23:11I 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. I made, you know, a static format.
23:18I'm now gonna 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 gonna build these tools that an agent is going to have, and then it's gonna be able to run this process in the background where it's basically has the ability to make new creative.
23:50It can publish that creative to directly to Facebook, which I'm gonna show you in a second. It's gonna then analyze what is working, and then it's gonna, like, basically turn off what isn't and promote what is. Right?
24:01And this is, everything I'm gonna 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.
24:09But I just again, I I wanna 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?
24:23No. Let's
24:25let's keep cooking.
24:27Awesome. Alright. So this keeps, like, trying to scrape things.
24:30I'm just gonna be like, instead, I want you to just brainstorm pain points that people have with data reporting, specifically the unification of the data into multiple locations.
24:43Cool. So we're gonna do that. Once I have all those variations, I can then say, okay.
24:48Now go bulk generate every one of those. And then at that point, I can download these as a CSV.
24:57And 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 gonna allow for us to bulk upload all of those pieces of creative that we just downloaded.
25:11So here's all those variations. I'm gonna say now, okay, now use the bulk or let's do the transcription.
25:19Okay. Now use the bulk Facebook ads generator to go and create these variations.
25:25Put them in the forward /bulk.html page when you're done with this. So this is now happening.
25:32I'm gonna go back over to see what the other things are going off of. Alright. So let's see.
25:38This notion document based off of the current, we'll continue to let that happen. I wanna build this up. Perfect.
25:46We're gonna let that go as well. So I'm looking at the scaffolding to build the bulk ad generator, and we'll check-in on this one to see where it's, like, basically at in its process of responding.
25:57And it might have completed, and it did complete. So that's done.
26:01It ran for fifteen minutes, uh, on its own in the background. 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.
26:12So I'll just click through this to just kinda 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 wanna do is I wanna build a LinkedIn engagement scraper.
26:26So I'm going so, basically, at people that engage on the LinkedIn pro or the LinkedIn post, I wanna pull them out and then send them to a basically, add them into Instantly. So we're gonna go we're gonna find their LinkedIn profile using Phantom Buster.
26:42We'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 and Give that its own section.
26:51By the end of this podcast, you're gonna have, like,
26:53a 100 This is literally how I'm working now. This is like, I'm just jockeying agents across.
27:01And 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 so that this software starts running in perpetuity.
27:23So we're gonna do this demo one. Alright.
27:26So I wanna 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 post that they think is a good fit.
27:39And then that's gonna go, and it's gonna use the Phantom Buster API to extract all of the engagers. And then it's gonna take those LinkedIn profiles.
27:48We're gonna go and enrich those with the Apollo API. And then from there, we're gonna send it to the Million Verifier API. And then finally, we're gonna add them to an instantly campaign.
28:00Ask me questions if you need. Alright. So I'm gonna turn on plan mode for that.
28:05Let that start running in the background as well. We'll come back to these. Let them continue to cook.
28:11Publish the landing page. Well, let me get context on what this one is again.
28:16This is the craziest part when you're going from screen like, screen to screen and realizing that you're an agent jockey Yep.
28:25And that you're trying to get context on each one. Yep. You're like, okay.
28:28What was this one doing again? And I find that the context switching is actually difficult.
28:33I I did as well, but now it's like now it feels like I I'd like, that has expanded. Like and again, this is just how I've been working for the last, like, six weeks.
28:44And 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, which just sounds so stupid.
29:01Yeah.
29:04Like like and comment this video so that, you know, I could send some YouTube AdSense revenue to CardiZoom. Yeah. Me too.
29:10We can get some more RAM. It's all ridiculous. This guy needs some RAM.
29:14No, man. We I it's like I'm just realizing, like, what this turns into. So okay.
29:19We bit we made all those pieces of ad creative. Right?
29:23We've got those variations, and it's just text variations. Alright. So now I'm gonna go back to Claude, and I'm gonna be like, I want now I wanna buckle bulk upload all of these ads as drafts into a Facebook ad set.
29:41Here is the u or here's where the folder is locally for the creative, and I'm gonna provide the Facebook ads ad set URL to you in a second.
29:53Alright. So I'm now going to go back to Finder, and I'm going to copy this, paste that in, and then let's go back to Facebook.
30:07And I have this ad set that I've already created for this demo. It's basically just here.
30:15And I'm just gonna paste in this URL. And so now here's that URL.
30:22It's gonna, uh, basically, uh, bulk upload all of those pieces of creative into that ad set.
30:29Um, so while that's happening, I'm now gonna go and I'm gonna create a dashboard about this. Um, so let's just pull out the ad set ID.
30:39Let's do the ad set ID, and I'm gonna go over to graft, and I'm gonna be, uh, pull up Facebook ads as the data source.
30:49And then I'm gonna be say, this is the ad set ID.
30:58Make a dashboard showing clicks over time. Also, have a scorecard that or sorry.
31:04I didn't do the transcription. Make a dashboard showing clicks over time, uh, as a line chart. Also, uh, within that line chart, can you include, uh, um, the cost and the CPC as lines as well?
31:17And 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.
31:33So that that's its own separate chart. That's a bar chart basically showing the impressions by the age categories.
31:41So I'm gonna let that run-in the background. 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.
31:59The other thing that I can do so once it's, uh, got the ad set with destination URL, would you like, um, just put them, uh, as a draft. So, uh, 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.
32:21So I'm gonna show you how to do that. So I do documents forward slash graft forward slash growth agents and then Claude.
32:32And then I'm gonna get that URL again, and I'm gonna say, use the graphed MCP to pull in the data for this ad set that I'm about to provide from Facebook ads.
32:45I wanna look at the CPM data to see which ones are the lowest performing, like the highest CPM price. Alright.
32:56Um, and then let's provide the ad set URL. Again, uh, let's go ad set.
33:03And then while that's happening, we can come in and check on the other ones. Alright. So it's now built that entire bulk Facebook ad generator.
33:13Or sorry. Which one is this? This is the Look one.
33:17Okay. So it's made the updates to these ads.
33:21These are an entirely new ad set that it's basically pulling in. So instead I already did this, right, of, like, bulk 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.
33:39So And not just variations. These are variations based on pain points that people have said publicly.
33:45Yes. Exactly. So it has pulled in basically the social dialogue that's happened.
33:52So the best ads that I'm seeing perform right now are basically you're selling outcomes or you're you're talking to the pain points. Right? So I'm I'm just guiding it to focus on those things, pull me that information, and then build the ad sets around those.
34:07So while that just happens, this in the background just use the graphed MCP to pull in all of the low performers.
34:15So these are the let's look at the ones that have the highest CPM. So these all have high CPM.
34:20So I'm just gonna tell it turn these off. I'm gonna say use the Facebook Ads API to turn off these ads with the this ad name.
34:32And so now it's just pulled in this live data from my data warehouse.
34:37And this isn't an MCP that's interacting with the Facebook Ads API. I just wanna, like, emphasize this. So it's not have you're not running in the rate limits.
34:46Like, again Mhmm. 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 gonna be able to analyze this data without a data pipeline and a data warehouse.
35:01And so this is, like, what we've built, right, at Graft. So anyways, the just to get back to the MCP thing, there's, like, this page nation problem.
35:11So, like, we see this all the time where people are like, yeah. I plugged into Facebook Ads, MCP, I'm interacting with it, and then I realize that I'm only seeing, like, 5% of the data that I think I'm actually seeing. Right?
35:21But so coming back to this, I've now said, hey. Turn these off.
35:26So it went and it paused those ads for me. And so it just just to walk through what we just did, just kinda reiterate this. We just did ideation.
35:34We just did bulk ad creation. We just analyzed the data for the performers. We just turned those off and on based on that.
35:45And at this point, you're probably starting to have the epiphany like, oh, I can just turn this in a into a repeatable process. And this is where I see all of this going, basically, is you're going to you're going to have these agents that are running on top of your live data.
36:02They're analyzing it, making decisions based off of, like, the the model.
36:08So, 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 a CPA action.
36:26And then that whole thing could just run automatically in the background. 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.
36:38And then the other thing that I would then go do is, like, potentially have a conversation in the morning.
36:46Say, for example so I've got the graft MCP in my Claude I like, chat.
36:54So 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.
37:01How much traffic went to the or how many new users went to the homepage of the website yesterday? And I'll just say use the graphed MCP and Google Analytics four.
37:16And 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 synced continuously within the background.
37:29And 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 Shats, VBT, or Claude, and then also the ability to, like, do that tracking within, like, dashboardings or conversations.
37:48Now coming back to all of this. Right? We've just built out basically this whole, like, cycle of funnel.
37:54How 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 into an agent.
38:02I'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.
38:20Right? They could come back and basically, like, use this software that I've created. I can just tell Railway via Clogcode, hey.
38:28Spin this up into a, like, a a server that I can access, or I can just deploy this directly to Vercel or any of these workflows that I have.
38:41So say, for example, we were talking about that LinkedIn funnel. Let's go see which one of this it is.
38:50Alright. So this is the podcast software.
38:55This is the image generator. This is the LinkedIn. So say I want it I want this to be accessible in perpetuity in the background.
39:06I 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 it just automatically goes into the email filtering.
39:29Or sorry, the email like, cold email process. And this even goes further. So, like, how I'm starting to use this, Jean, I'm curious, like, to get your thoughts on this.
39:39Basically, 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 down I went directly to the URL.
39:52I had it push it into a Postgres database that I, on the fly, created using the Railway API. It just pumped everything in there.
40:00I then did the analysis together with Claude. And then at that point, I basically pushed from that Postgres database the outputs to the to the location that I wanted.
40:13What I've used to would've it would've taken me probably five hours historically to, like, clean the data appropriately, and I smashed that out in probably twenty to thirty minutes. And then as soon as I got done with that database, I just spun it down.
40:29And this was the most interesting part of this was that it was basically on the fly UI, on the fly or the epiphany I had was on the fly UIs, on the fly databases, on the fly software is going to become the standard for these people that are working at the forefront of this.
40:49So, yeah, man. I I we could probably 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.
40:59The only other thing I'm just, like, keep getting asked, like, how do I do this? How like, show me more technical details.
41:07I bought the domain gtmengineeringcourse.com. I'm gonna give this thing away for free to everybody who wants it. It'll be entirely public.
41:16I've already got a wait list of a 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 gonna document into one place. But, anyways, just throwing that out there as the last thing.
41:27But 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.
41:35Like, how you defend against this, like, with your job?
41:39Or do you is it just like, you need to learn this now? And, like, I wanna hear your thoughts because I'm you're seeing way more than I am with everything.
41:46I'll tell you my I'll answer your question, but I wanna start by saying, like, my biggest takeaway from all of this. Yeah. So my biggest takeaway of all this is when you connected it with Railway.
41:58And I I it's a glimpse into the future of autonomous marketing. So marketing, you know, all you you basically what you've done, like, all those sort of jobs to be done were jobs to be done that were literally done by human beings.
42:15Right? And then you kinda stitched together. You know, if you've ever run ad campaigns before, you know how painful some of these things are.
42:26Like Just uploading the ads alone? I was just Like that.
42:29I was like, I have literally spent, like I I mean, I'm just imagining uploading a thousand ad variations.
42:37Like Dude.
42:40Like, it just Don't give me PTSD on the pod. Straight. You know?
42:43Like Yeah. I I did this early in my career. It was absolutely painful.
42:47It was painful. Right? It was painful, and and it's not fun.
42:50It's not fun at all. Removing and figuring out low performers, ad creative, not fun.
42:57Not fun. And you need to be on it. Um, so the idea that you can, you know, make this an agent that's working twenty four seven and that's managing all these different things is the dream.
43:11It is absolutely the dream. Autonomous marketing, the dream. I think, who are the winners and who are the losers of this?
43:20The winners are gonna be, you know, one person businesses, small teams.
43:29And then maybe your your head of marketing that currently are getting paid a $100,000 a year.
43:37Now 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. Easily.
43:48Right? Like, from a value perspective, like, 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.
44:02So 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 are is gonna be a lot of job loss, real job loss.
44:15Like, it just
44:17who anyone who gets 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 in, like, United Kingdom.
44:29Like, they I mean, you basically have this displacement, and then new roles get created. But, like, in that interim, still a lot of turmoil.
44:38It's gonna be chaos. It's gonna be chaos. And I Yeah.
44:41Like, 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.
44:48Right? And I'm just over here, and I'm like, how?
44:52Why? What? You know?
44:52Tell 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.
44:59What's an agent swarm? You know? Because that's just this, like, throw like, term that gets thrown around right now.
45:04And he's like, oh, it's just an agent that does, 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.
45:17That's what an agent's form is. 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.
45:28And it's, like, looking for, like, ICP. And then it enriches them. It writes a personalized email, and it cold emails them.
45:36Yeah. And, like, I don't think people understand, like, what's about to happen in, like, the next twelve months.
45:43So and I'm excited about it because I think there's, like again, what if you can build, like, it is incredible. Like, you're so capable right now.
45:52Especially if you have domain knowledge is the other thing that I'm finding is, like, just because you can like, it 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 cofounder 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.
46:13And so the output quality that he can get from this is at a, like, a level that's in the top 10, top 1%. So if we translate that to something else, like, say you studied graphic design for twenty years and, like, you've been working in the industry for twenty years, the vocabulary you have to describe something is gonna be so much more sophisticated than what I have.
46:30So 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.
46:38It 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?
46:45Right? And it was like all of these, you know, specific like, it was like a specific lexicon to describe the to call it. Literally one shots it, you know, immediately, like, what I was looking for after that.
46:56And I you have that realization that this actually becomes, like, the superpower. 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 what makes you valuable.
47:17This is like that, but, like, you know, times a thousand where it's like, 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.
47:34But I I I again, I would I'd 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.
47:43Well, I 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.
47:55Now I think that the tools are gonna get so good that the UX is gonna 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,
48:13no, more, 20 tools. I'll include some of those in the show notes. Yeah.
48:17I'll read the list of them so that you can pass them on. Phantom
48:20Blaster instantly. Like, I'm not even talking about, like, Cloud Code and stuff like that. You you, like, you've done your research.
48:27You'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.
48:48But, 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.
49:00So, like, in the old way in the old way of, like, SaaS tools and stuff like that, you you didn't. I mean, was nice an API was a nice to have.
49:09You know? It was about how good is the software that you're using. Um, how good is the UX?
49:14How good is the brand? How good is you know, when you press this feature, how quick is it? How instant is it?
49:20But now, when you're living in a terminal, for example, and you're using MCPs to talk to LMs, you kinda you know, the nice to have is actually the the the UI.
49:33The nice to have is the SaaS. The nice to have is going to this website and and look pretty. Ultimately, what you care about is the output, and the thing is running the agents are running, you know, twenty four seven.
49:44They aren't, you know, hogging tokens. The output is high quality. It's doing the thing that it's says it, you know, it should do.
49:54And I think Sam Altman said recently something about APIs. I think he said the every company is gonna be an API company.
50:02Totally. I align with this. Like, now doing this, like, I there's a software.
50:07Like, 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 Mhmm. Critical for me.
50:18And 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 gonna be companies that are entirely just like like, what what it I mean, we literally had this conversation internally.
50:35Like, do we build an a like, a UI? Like, is 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?
50:44And I think that, like, you know, we had to come you know, have a come to Jesus moment of, 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.
51:02But, like, I mean, it's very clear. Right? Like, for example, like, with the graph MCP, that's a live data feed.
51:08So 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.
51:15It'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.
51:27And I'm like, okay. Well, I'll let let's just go build a custom dashboard, like, for what we need.
51:34But 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.
51:47So whether you're working from Cloud iOS or ChatGPT desktop or Cloud Code on you know, in your terminal or, like, Cursor or, you know, even the UI, it's unified across that.
51:58And 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 kinda moving forward. And I think it again, what it comes down to, though, is like everything that like, we're talking about this tooling piece.
52:14Like, unless you know what to do, it's very hard to get it to like, if I if I didn't know these these exact tool sets 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.
52:29It's totally possible. It can. It's just, like, gonna take longer.
52:32And 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 I'm finding myself doing this where I'm like, I have this vision of a workflow, and I'm starting with the final product.
52:49And then I'm working back and basically piecing together how does this work and then having the agent go and build that for me.
52:56And so then this comes back to how do agents discover the necessary infrastructure for and, like, how do you be the thing that it picks when it's going to build, you know, x y z thing?
53:08And, like, again, these are the things I'm losing sleep over now as we're, like, getting deeper and deeper into this. Well, Cody, I appreciate you being so saucy with with sharing all this stuff with us. We do appreciate it.
53:19I 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 we'd love to have you.
53:31Have a ton of them, man. You can go for days about Chrome extensions right now. You can literally have Clog Code One shot them and just turn on Facebook ads in the background automatically.
53:40Also had 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.
53:46So
53:47So 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.
53:56Share ideas. You get you definitely get my creative juices flowing, so I appreciate you so much. And Appreciate it, g.
54:02Thanks for for your time as always, man. I always love coming on. Thank you.
The Hook

The bait, then the rug-pull.

The title promises a marketing machine built by AI. What the episode delivers is something more useful: a 54-minute window into how a growth engineer actually works in 2026 — seven terminal windows open, agents firing in parallel, and the only thing slowing him down is needing more RAM.

CTA Breakdown

How they asked for the click.

MENTIONED ON CAMERA
01:15toolClaude Code ↗
02:12toolPhantom Buster ↗
02:12toolInstantly AI ↗
06:01toolrailway.com ↗
07:30toolFacebook Ads API ↗
07:30toolMillion Verifier ↗
07:43toolSuper Whisper ↗
10:17toolPerplexity API ↗
20:10toolKai AI ↗
23:12toolHeyGen API ↗
25:56toolApollo API ↗
36:37toolGraphed / Graphed MCP ↗
51:11linkGTM Engineering Course (free) ↗
FROM THE DESCRIPTION
PRIMARY CTAWhere the creator wants you to go next.
OTHER LINKSAlso linked in the description.
Frame Gallery

Visual moments.

Frame at 00:00 from Claude Code & MCPs built my $145K marketing machine00:00Frame at 01:07 from Claude Code & MCPs built my $145K marketing machine01:07Frame at 01:21 from Claude Code & MCPs built my $145K marketing machine01:21Frame at 02:15 from Claude Code & MCPs built my $145K marketing machine02:15Frame at 02:58 from Claude Code & MCPs built my $145K marketing machine02:58Frame at 03:37 from Claude Code & MCPs built my $145K marketing machine03:37
Frame at 00:00 from Claude Code & MCPs built my $145K marketing machine00:00Frame at 01:07 from Claude Code & MCPs built my $145K marketing machine01:07Frame at 01:21 from Claude Code & MCPs built my $145K marketing machine01:21Frame at 02:15 from Claude Code & MCPs built my $145K marketing machine02:15Frame at 02:58 from Claude Code & MCPs built my $145K marketing machine02:58Frame at 03:37 from Claude Code & MCPs built my $145K marketing machine03:37Frame at 04:15 from Claude Code & MCPs built my $145K marketing machine04:15Frame at 04:50 from Claude Code & MCPs built my $145K marketing machine04:50Frame at 05:12 from Claude Code & MCPs built my $145K marketing machine05:12Frame at 06:12 from Claude Code & MCPs built my $145K marketing machine06:12Frame at 06:53 from Claude Code & MCPs built my $145K marketing machine06:53Frame at 07:33 from Claude Code & MCPs built my $145K marketing machine07:33Frame at 07:56 from Claude Code & MCPs built my $145K marketing machine07:56Frame at 09:07 from Claude Code & MCPs built my $145K marketing machine09:07Frame at 09:28 from Claude Code & MCPs built my $145K marketing machine09:28Frame at 10:05 from Claude Code & MCPs built my $145K marketing machine10:05Frame at 10:54 from Claude Code & MCPs built my $145K marketing machine10:54Frame at 11:32 from Claude Code & MCPs built my $145K marketing machine11:32Frame at 12:09 from Claude Code & MCPs built my $145K marketing machine12:09Frame at 13:06 from Claude Code & MCPs built my $145K marketing machine13:06Frame at 13:19 from Claude Code & MCPs built my $145K marketing machine13:19Frame at 14:26 from Claude Code & MCPs built my $145K marketing machine14:26Frame at 14:47 from Claude Code & MCPs built my $145K marketing machine14:47Frame at 16:05 from Claude Code & MCPs built my $145K marketing machine16:05Frame at 16:10 from Claude Code & MCPs built my $145K marketing machine16:10Frame at 16:46 from Claude Code & MCPs built my $145K marketing machine16:46Frame at 17:50 from Claude Code & MCPs built my $145K marketing machine17:50Frame at 18:13 from Claude Code & MCPs built my $145K marketing machine18:13Frame at 19:16 from Claude Code & MCPs built my $145K marketing machine19:16Frame at 19:59 from Claude Code & MCPs built my $145K marketing machine19:59Frame at 20:42 from Claude Code & MCPs built my $145K marketing machine20:42Frame at 21:25 from Claude Code & MCPs built my $145K marketing machine21:25Frame at 22:08 from Claude Code & MCPs built my $145K marketing machine22:08Frame at 22:51 from Claude Code & MCPs built my $145K marketing machine22:51Frame at 23:34 from Claude Code & MCPs built my $145K marketing machine23:34Frame at 24:17 from Claude Code & MCPs built my $145K marketing machine24:17Frame at 25:00 from Claude Code & MCPs built my $145K marketing machine25:00Frame at 25:50 from Claude Code & MCPs built my $145K marketing machine25:50Frame at 26:48 from Claude Code & MCPs built my $145K marketing machine26:48Frame at 27:10 from Claude Code & MCPs built my $145K marketing machine27:10Frame at 28:06 from Claude Code & MCPs built my $145K marketing machine28:06Frame at 28:26 from Claude Code & MCPs built my $145K marketing machine28:26Frame at 28:47 from Claude Code & MCPs built my $145K marketing machine28:47Frame at 29:08 from Claude Code & MCPs built my $145K marketing machine29:08Frame at 29:30 from Claude Code & MCPs built my $145K marketing machine29:30Frame at 30:16 from Claude Code & MCPs built my $145K marketing machine30:16Frame at 31:17 from Claude Code & MCPs built my $145K marketing machine31:17Frame at 31:47 from Claude Code & MCPs built my $145K marketing machine31:47Frame at 32:33 from Claude Code & MCPs built my $145K marketing machine32:33Frame at 33:02 from Claude Code & MCPs built my $145K marketing machine33:02Frame at 33:53 from Claude Code & MCPs built my $145K marketing machine33:53Frame at 34:31 from Claude Code & MCPs built my $145K marketing machine34:31Frame at 35:09 from Claude Code & MCPs built my $145K marketing machine35:09Frame at 35:51 from Claude Code & MCPs built my $145K marketing machine35:51Frame at 36:38 from Claude Code & MCPs built my $145K marketing machine36:38Frame at 37:24 from Claude Code & MCPs built my $145K marketing machine37:24Frame at 38:10 from Claude Code & MCPs built my $145K marketing machine38:10Frame at 38:57 from Claude Code & MCPs built my $145K marketing machine38:57Frame at 39:38 from Claude Code & MCPs built my $145K marketing machine39:38Frame at 40:22 from Claude Code & MCPs built my $145K marketing machine40:22Frame at 40:52 from Claude Code & MCPs built my $145K marketing machine40:52Frame at 41:45 from Claude Code & MCPs built my $145K marketing machine41:45Frame at 42:25 from Claude Code & MCPs built my $145K marketing machine42:25Frame at 43:08 from Claude Code & MCPs built my $145K marketing machine43:08Frame at 43:48 from Claude Code & MCPs built my $145K marketing machine43:48Frame at 44:17 from Claude Code & MCPs built my $145K marketing machine44:17Frame at 44:50 from Claude Code & MCPs built my $145K marketing machine44:50Frame at 45:49 from Claude Code & MCPs built my $145K marketing machine45:49Frame at 46:29 from Claude Code & MCPs built my $145K marketing machine46:29Frame at 47:09 from Claude Code & MCPs built my $145K marketing machine47:09Frame at 47:43 from Claude Code & MCPs built my $145K marketing machine47:43Frame at 48:15 from Claude Code & MCPs built my $145K marketing machine48:15Frame at 49:09 from Claude Code & MCPs built my $145K marketing machine49:09Frame at 50:01 from Claude Code & MCPs built my $145K marketing machine50:01Frame at 50:29 from Claude Code & MCPs built my $145K marketing machine50:29Frame at 51:08 from Claude Code & MCPs built my $145K marketing machine51:08Frame at 51:48 from Claude Code & MCPs built my $145K marketing machine51:48Frame at 52:27 from Claude Code & MCPs built my $145K marketing machine52:27Frame at 53:13 from Claude Code & MCPs built my $145K marketing machine53:13Frame at 53:31 from Claude Code & MCPs built my $145K marketing machine53:31
Watch next

More from this channel + related breakdowns.

Chat about this