14:48Leveling Up with Eric Siu · Tutorial
AI Loops Are Useless Unless They Do This
A 14-minute breakdown of how to turn recurring AI workflows into compounding business systems, with a live AEO/SEO loop as the proof.
June 23rdThe argument in one line.
Coding agents replace most of a marketing team's headcount once they're wired into a shared data warehouse and API gateway, not just chatted with task by task.
Read if. Skip if.
READ IF YOU ARE…
- A marketing or agency operator who wants a concrete blueprint for wiring coding agents like Claude Code or Cursor into ad creative, SEO, and outbound instead of just chatting with them.
- A founder deciding whether to keep hiring for a marketing team or build the agent infrastructure that replaces most of that headcount.
- A performance marketer who wants real before/after numbers (cost per lead, cost per action, signup volume) from running Facebook, Google, SEO, and cold outbound through an agent.
- A technical operator curious what a production-grade stack looks like: data warehouse, cron jobs, API gateway, and database logging for a coding agent doing real work.
SKIP IF…
- You want a beginner explainer of what Claude Code or prompt engineering is. This assumes you already run coding agents regularly.
- You're looking for organic content or storytelling craft advice rather than paid-acquisition and outbound machinery.
The full version, fast.
Cody Schneider's six-person agency runs the ad-creative, SEO, and cold-outbound work of a 25-person marketing team by giving coding agents a shared data warehouse, API gateway, and recurring cron jobs instead of chatting with them task by task. Live on screen, he scrapes page-one SEO content and publishes a ranking article in under an hour, builds a LinkedIn-engager-to-cold-email funnel, and generates AI-avatar video ads with cloned voices. Documented results: Facebook cost per lead dropped from $70 to $16 in four weeks for one client, and another went from roughly 2,000 to over 20,000 monthly signups in three weeks.
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00:00 – 03:50
01 · Cold open: the AI intelligence amplifier
Eric Siu introduces Cody Schneider and frames AI as an intelligence amplifier for the episode's live build.
03:50 – 10:40
02 · What 'marketing engineering' actually means
Cody shares a Notion doc defining marketing engineering / GTM engineering as agents doing the 'middle work' of marketing.
10:40 – 15:41
03 · The nine-piece infrastructure stack agents need
Cody lists the data pipeline, warehouse, cloud server, media storage, databases, cron jobs, auth, git manager, and API gateway required to run agents on real marketing work.
15:41 – 20:34
04 · Audience poll and the 'go up or go out' framing
A live poll picks the demo order; Eric frames AI as both an intelligence amplifier and a truth revealer for marketing teams.
20:34 – 25:42
05 · Live demo: parasite SEO to page one in an hour
Cody scrapes page-one Google content, writes and publishes an article to LinkedIn Pulse, and pings it with Prime Indexer live on screen.
25:42 – 31:11
06 · Live demo: LinkedIn engagers into a cold-email funnel
Cody extracts LinkedIn post engagers via a scraping API, runs waterfall email enrichment, and uploads validated leads into an Instantly cold-email campaign.
31:11 – 36:19
07 · Cold-email infrastructure: tenants, deliverability, and HyperTide
Cody explains how HyperTide isolates sending domains into tenants to protect deliverability at scale, and compares it to InboxKit and Instantly's own warmed domains.
36:19 – 41:30
08 · Live demo: Seed Dance AI-avatar ad creative
Cody scrapes Reddit for pain points, writes 15 hook-and-pain-point ad scripts, and sends them to ElevenLabs and Higgsfield/Seed Dance to render AI-avatar video ads.
41:30 – 46:11
09 · The 85/90 rule: living inside the coding harness
Eric and Cody argue AI-native marketers should spend 85-90% of their time inside the agent harness, citing DaVinci Resolve's MCP for long-form video editing.
46:11 – 51:20
10 · TAM mapping and QA'ing signal-based outreach
A viewer question on QA'ing signal-based outreach leads into TAM mapping: tracking decision-makers and buying-intent signals like job changes.
51:20 – 56:49
11 · B2C creative volume and creator marketplaces
Cody points to a consumer brand running ~5,100 simultaneous Facebook ads and explains creator marketplaces like SideShift and Tribe for paid UGC production.
56:49 – 1:00:34
12 · Tool stack and the case against 'token maxing'
Cody describes his Cursor/Claude Code/Codex daily-driver mix and argues against 'token maxing' in favor of writing durable software instead of chatting for every task.
1:00:34 – 1:05:22
13 · Six people, 11,000 ads a month, and the brand-guide gate
Cody shares the agency's six-person headcount, ~11,000 ads published in a month, and the vision-model brand-style-guide gate creative must pass before publishing.
1:05:22 – 1:08:22
14 · Performance numbers, the 80/20 entropy rule, and close
Cody shares cost-per-lead and signup numbers from client accounts, explains the 80/20 rule for introducing creative entropy, and wraps with where to find him online.
Lines worth screenshotting.
- A coding harness plus a shared data warehouse lets one person do the outreach, ad-creative, and SEO work that used to take a 25-person marketing team.
- All marketing has effectively become code: an ad is a JSON payload to a generation API, a media buy is a database write, and a performance report is a SQL query.
- Parasite SEO articles published to a high-authority host and pinged with an indexing service can hit Google's page one for a target keyword in under an hour.
- The infrastructure a coding agent needs is a data pipeline, a data warehouse, a cloud server, media storage, a database for its own outputs, cron jobs, app authentication, and a git manager.
- Cold outbound built on comment-engagement signals outperforms cold lists: extracting the people who engaged with a relevant LinkedIn post gives a warmer, self-selected audience to enrich and email.
- Isolating email-sending domains into small tenant pools protects deliverability, so a single burned domain doesn't drag down the rest of a cold-email operation.
- AI avatar ad creative works best when the voice track's audio quality matches the avatar's environment; a studio-clean voice on an avatar sitting in a car breaks the illusion.
- Facebook's algorithm now targets largely off the ad creative itself, so narrow interest-based targeting is being replaced by creative written to speak directly to a specific buyer.
- The stated internal bar is that 85 to 90 percent of a marketer's time, and roughly 95 percent of an engineer's code, should come out of the AI harness, not be typed by hand.
- Pointing a browser-driving agent directly at a personal LinkedIn account for scraping risks account bans; routing the same task through a dedicated scraping API is the safer, more discreet path.
- TAM mapping plus signal stacking (a job change, a LinkedIn engagement, a site visit) turns cold outbound into timed outreach aimed at people actually entering a buying cycle.
- A single consumer brand running roughly 5,100 simultaneous active Facebook ads shows the ceiling for creative-testing volume once ad production is automated rather than hand-made.
- Creator marketplaces that pay per video, or a percentage of ad spend on winning creative only, shift UGC production cost from fixed headcount to pure performance.
- One agency's Facebook cost per lead dropped from $70 to $16, and Google cost per action from $82 to $35, in four weeks by running an agent to trim losing creative and promote winners daily.
- Roughly 20 to 30 percent of ad creative should be genuinely new each testing cycle to fight performance decay, once the current best-performing set starts to plateau.
The Infrastructure Behind AI-Native Marketing
MARKETING ENGINEERING STACK
A six-person team replaces the work of a 25-person marketing department by wiring coding agents into a shared data warehouse, API gateway, and recurring cron jobs instead of one-off chat sessions.
02What 'marketing engineering' actually means
- Marketing engineering and GTM engineering are the same discipline applied to acquisition and pipeline: building agents that do the ad-creative, outreach, and CRM 'middle work' a human used to do by hand.
- The workflow pattern is co-work a task manually with the agent once, then turn that session into a repeatable process the agent runs on a daily, weekly, or monthly cron schedule.
03The nine-piece infrastructure stack agents need
- A coding agent needs nine concrete pieces of infrastructure to do real marketing work: a data pipeline, data warehouse, cloud server, media storage, an outputs database, cron jobs, app authentication, a git manager, and an API gateway to every tool.
- Every generated asset, such as an ad's JSON or a script, gets saved back into a database so the agent can reference its own past work and tie it to downstream performance data.
04Audience poll and the 'go up or go out' framing
- Marketers who already build this way are becoming more in demand, not less; the people who don't adapt either move up into higher-leverage work or get replaced.
- AI is framed as both an intelligence amplifier and a truth revealer: it makes strong operators faster and exposes weak ones just as clearly.
05Live demo: parasite SEO to page one in an hour
- Parasite SEO means publishing agent-written content to a high-authority third-party host instead of your own low-authority domain, then paying an indexing service to get it crawled fast.
- The content strategy is literal: scrape what's already ranking on page one, feed it to the agent as source material, then layer in a founder's unique positioning from a recorded interview so the output isn't generic.
06Live demo: LinkedIn engagers into a cold-email funnel
- Cold outbound lists get built from LinkedIn post engagers, not purchased data: extract who liked or commented on a relevant post, then run waterfall email enrichment to find a verified address for each one.
- Never point a browser-automation agent directly at your primary LinkedIn account for scraping. Route it through a dedicated scraping API instead, or risk getting the account banned.
07Cold-email infrastructure: tenants, deliverability, and HyperTide
- Cold-email deliverability at scale depends on isolating sending domains into small 'tenant' pools, roughly two domains per tenant, so one burned domain doesn't take down the whole operation.
- A managed infrastructure provider can run roughly 10,000 cold emails a month for about $125, which scales to roughly $8,000 to send a million emails a month.
08Live demo: Seed Dance AI-avatar ad creative
- AI avatar ads need the voice track's audio character to match the avatar's visible environment. A studio-clean voice on someone shown sitting in a car breaks the illusion immediately.
- Ad scripts follow a fixed pattern: a proven hook line, then a pain-point-to-desired-outcome build, written at roughly a 12th-grade reading level and capped near 30 seconds.
09The 85/90 rule: living inside the coding harness
- The stated internal expectation is that AI-native marketers should spend 85 to 90 percent of their time working inside the coding harness, and engineers should have roughly 95 percent of their code written by AI.
- Long-form video editing, once considered too hands-on for AI, is now getting real results through DaVinci Resolve's MCP integration paired with an Astra subscription.
10TAM mapping and QA'ing signal-based outreach
- Signal-based outreach gets QA'd with an ICP-fit filter: the agent scores each engager against a markdown-defined ideal customer profile before it's allowed into the outbound list.
- TAM mapping means building a database of every company and decision-maker in the addressable market, then watching for buying-intent signals like a job change, since people are most likely to buy new tools right after switching companies.
11B2C creative volume and creator marketplaces
- The ceiling for creative-testing volume is real: one consumer brand cited in the demo was running roughly 5,100 simultaneous active Facebook ads.
- Creator marketplaces like SideShift and Tribe let a brand pay per UGC video, cited around $40 each, or a percentage of the ad spend a piece of creative goes on to win, instead of hiring a full-time creator-relations person.
12Tool stack and the case against 'token maxing'
- The daily driver stack is a mix of Cursor and Claude Code, with Codex brought in specifically for video-editing tasks and longer-time-horizon coding work.
- The stated contrarian position is against 'token maxing': the better move is writing durable, reusable software with its own thinking loop and live data stream, not defaulting to a chat agent for every small recurring task.
13Six people, 11,000 ads a month, and the brand-guide gate
- A six-person team, two founders, three to four deployed engineers, and one head of sales, published roughly 11,000 ads across client accounts in a single month.
- Creative has to clear a brand-style-guide gate before it can publish: a separate vision-model check flags issues like an incorrect font, and the fix gets sent back to image generation automatically.
14Performance numbers, the 80/20 entropy rule, and close
- Documented results from the demo: one client's Facebook cost per lead dropped from $70 to $16 and Google cost per action from $82 to $35 inside four weeks; another went from about 2,000 to over 20,000 monthly signups within roughly three weeks of full-stack setup.
- To fight creative fatigue, keep roughly 80 percent of spend on what's already proven to work and dedicate the other 20 to 30 percent to genuinely new creative once cost per action plateaus.
Terms worth knowing.
- Marketing engineering
- A discipline where marketers build and operate coding-agent infrastructure to run acquisition work (SEO, ads, outbound) instead of manually executing campaigns.
- GTM engineering
- The sales and CRM-side counterpart to marketing engineering; the same coding-agent-and-data-pipeline approach applied to pipeline generation and outbound.
- Parasite SEO
- Publishing content on a high-authority third-party domain, such as a LinkedIn Pulse article, to rank quickly instead of waiting for your own site's domain authority to build.
- Prime Indexer
- A paid indexing service that repeatedly pings a new URL to get Google to crawl and index it within minutes instead of days or weeks.
- TAM mapping
- Building a database of every company and decision-maker in an addressable market, then watching for buying-intent signals like a recent job change.
- Waterfall email enrichment
- Chaining multiple lead-data providers in sequence, falling through to the next provider whenever the first fails to find a verified email address.
- Seed Dance
- An AI video model that lip-syncs a cloned voice track onto an AI avatar to produce talking-head style ad creative without filming a real person.
- CBO campaign
- Facebook's Campaign Budget Optimization structure, where one shared budget is automatically distributed across many ad creatives inside a single campaign.
- Email tenant
- An isolated pool of sending domains inside Microsoft's email infrastructure; providers group domains into small tenants so one burned domain doesn't damage deliverability for the rest.
- Token maxing
- Defaulting to a chat-based AI assistant for every small recurring task instead of writing durable, reusable software that runs the work on its own.
- De-anonymization
- Identifying the specific company or person behind an otherwise anonymous website visit, using IP and firmographic matching tools.
- AEO (answer engine optimization)
- Optimizing content to be surfaced or cited by AI answer engines and chat-based search, the AI-era counterpart to classic SEO.
Things they pointed at.
10:40toolgraph.com (Cody's marketing engineering platform)
10:40toolAirbyte and Clickhouse (open-source data pipeline + warehouse)
20:34toolSERPR.dev (Google page-one scraping API)
20:34toolFirecrawl / xAI (content extraction)
20:34toolStrapi (CMS for blog publishing)
21:40toolPrime Indexer (URL indexing service)
25:42toolAppify / API Maestro (LinkedIn profile scraping)
26:40toolInstantly (cold email sending platform)
27:30toolMillion Verifier (email validation)
27:30toolLeadMagic and Heyreach
31:11toolHyperTide (managed cold-email infrastructure)
31:40toolInboxKit
36:19toolElevenLabs (Natasha voice clone)
36:19toolHiggsfield / Kai AI (Seed Dance video generation)
48:20toolLeadPipe (site-visitor de-anonymization)
51:20toolSideShift and Tribe (creator marketplaces)
56:40toolDaVinci Resolve MCP with an Astra subscription (AI-assisted long-form editing)
1:00:00toolP0.studio
Lines you could clip.
01:30
“It was like, I'd need 25 people, and now one person with a Claude Code Max subscription can basically function as that entire team.”
02:30
“If you're smart, you're 100 times smarter. If you're a dumbass, you're 100 times dumber, right now.”
10:10
“All marketing is now just turning into code.”
28:30
“Our running joke internally is friends don't let friends do N8N.”
41:30
“The future AI-native marketers are spending the vast majority of their time within the harness. It should probably be 85, 90 plus percent.”
57:40
“I'm against token maxing. I think it's really stupid... why am I paying Claude or Anthropic to schedule a social media post?”
1:05:55
“We took their cost per lead from $70 on Facebook down to about $16 in the span of four weeks doing this exact process.”
Word for word.
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metaphor
live. We're going to let some people come in for a second, but we got Cody Schneider today. We're going to be talking about the best AI workflows for business, for marketing, for sales.
Cody is a guy that, I mean, I'm sharing his links all the time with my team. Hey, we got to do this. We got to do this.
We got to do this over here. And I think there's going to be some awesome learnings today. We're going to go back and forth on some new tech as well and what's happening with Jev.
What are we doing with 5 .5 Opus? What are we doing with, you know, Jashibidi 6 Sol? There's just like new stuff coming out all the time.
I'm also going to go live over here on Instagram. You guys, before we get started in the next minute or two, tell us where you're coming from. Drop your questions in the chat.
Max is going to be piloting this stuff in the back end. And we'll just keep it going here. So we got Max welcoming people.
Tell us, guys, where are you coming from right now? What do you want to learn? I know we're talking about building an AI native marketing team, but I think there's much more than that.
But, Cody, I mean, before we get started, I know I kind of gave a long -winded intro for you, but do you want to add anything to your intro here? No, you're good, man. I think you hit a lot of it.
what we largely spend all of our time doing is figuring out like how to do all of the middle work is what we describe it as, um, that historically a marketer would do, whether that's like ad creative research, the generation of the ad creative, the media buying, you know, anything that you would, you would do historically for whatever channel it is that you're working on.
How do we get, uh, basically a coding harness to do that work for us and create out, outscaled outcomes that historically it's like, you know, and I, we're on a team like this. It was like, I'd need. 25 people and now one person with a cloud code max subscription or a code subscription can basically function as that entire team so oh my god dude there's a lot to talk about here so um but uh we got jay waters here driving from the beta la so drive safe um you know don't don't look at uh cody's good looking face too much but um and then we got stacy coming here uh thank you for that norcal we got yana we got cleveland ohio a lot of people from ohio you got the uk as well okay so here's what we're gonna do um i mean maybe that's a good place to start cody because you're gonna we're gonna screen share quite a bit here but um you know one of my i was actually just talking to my my um one of my podcast co -hosts uh one of my podcasts my podcast co -host neil right before this call and about how um ai is an right let's say if you're smart you're 100 times smarter if you're a dumbass you're 100 times done right now right and it's just it's amplified now and you can kind of see everything
and um it's what what we're just talking about from a high level not just from a marketing standpoint but from a mergers and acquisition standpoint is like there's just a lot of distressed agencies right now and you can probably pick them up um and for pennies on the dollar because There might have been a co -founder buyout and they can't afford it anymore, or they owe too much money to their government right now from a tax standpoint.
Because if you're international, maybe your interest rates are a lot higher. So there's a lot of meta behind this, and we can talk about that. But Cody, maybe...
your most exciting workflow right now because you have a lot of stuff you're sharing around sales backlinks like you know running using cursor to run your google ads like where do you want to start first let's just go there yeah yeah i think i mean whenever i'm doing these conversations i'm like first off what even is this and i i think that helps people understand like the market that we're entering into um and so i i think starting there is probably the best part like basically this is being called marketing engineering this is this like new role it's also called gtm engineering if you cross over into like sales or anything that's touching a crm but they kind of live in the same you know category at this point a lot of a lot of similar work and they they use a lot of similar tools right if like you're doing a link building outreach campaign right um you're using a cold email sending platform like instantly if you're doing cold email you know just for lead generation it's using the same infrastructure so i i think this start there and i i actually have a notion document let me share and i can talk through this of like
how we view and think about this like new kind of world that we're living in um and like what this means in relationship to like you know basically where is this going for uh uh agency owners really any business owner if you get leads online like this is going to become a part of this so can you see this all right eric Sorry about that.
I froze out, but I'm still here. No worries, no worries. Can you see this all right?
Yeah, I can see it. Cool. So just first off, what is marketing engineering?
It's basically this new category that I was describing where people are basically doing all the middle work. So to be able to do this and how we basically approach this, you can do this locally on your machine, but the more effective way is actually deploy these workflows with these agents into the cloud. And so what you need is to basically build the infrastructure to be able to facilitate all of the work that this coding agent is going to be doing you for you on your behalf you're basically giving it all the tools that it needs to do that so over the last 18 months this is what we found is necessary to accomplish that you basically need to build a data pipeline data warehouse a cloud server to like run code on media storage to store images and videos for example for ad creative databases that the coding agent can spin up so it can report on its activities so for example if it goes and it creates a you know piece of media like a uh static image uh it can save literally that json that it used to generate that image into a database so that you can come back and reference that and actually tie it to your facebook ads data as an example you need to be able to do recurring tasks or cron jobs and then also have some type of application authentication so if you want to share a dashboard as an example or an artifact as an example with your team so that you know that doesn't get published publicly
it's not public to the web and then also a git manager so that this is multiplayer and so that multiple team members can be working on this like you know infrastructure simultaneously and then the last piece of this which is like the biggest unlock is this an api gateway of like all of the different uh tools that are necessary or that you need basically to do this work right so um everything that i just described You can do this open source, like for example, data pipeline, data warehouse.
You can use a company called Airbyte, another one called Clickhouse for the data warehouse. And you basically just stack all of these pieces together. But fundamentally under the hood, what you're trying to do is give your coding agent access to all of this.
And then you're going to, through these APIs, through the data that you're pulling back from that data pipeline, data warehouse. And then all of this other tooling, you're basically capable of getting your agent to basically do any amount of marketing or any work that you're doing. And a lot of the times how I describe this for people, like when I'm initially like trying to get them to kind of wrap their mind around it, it's like, I'm going to take a task that I'm doing manually right now.
I'm going to co -work with Cloud Code to be like, cool. Like I get the outcome that I get out of that. And then once I built that kind of like log session of me having that chat, I'm then trying to turn that into a repeatable process.
that i deploy into a cloud that's running on some type of occurrence whether it's daily weekly monthly if doing some type of activity a really you know perfect a perfect example to describe this is uh like for seo um you like research a list of target keywords uh you scrape what's ranking page one of google um you put that into the context window you write an article based off of that uh you add your own like brand style voice based off of the transcript that you provide to it publish that to your site via your CMS's API.
So we use Strapi for our blog post hosting. And then that process that I just did, and what I would do then is like refresh it on the 30 -day cadence based off of the live data stream. But that process that I just described, I would then take that and I would say, hey, every day, here's this list of keywords.
I want you to research, write, and publish this new blog post. every day on a cadence and have that automatically run. And then our job as marketers is we're basically stacking all of these things on top of each other.
So suddenly we're publishing 30 new pieces of ad creative per week to Facebook. We're publishing 20 new pieces of ad creative to LinkedIn. We're automatically like optimizing Google ads in the background continuously based off of the live data stream.
And we can do this and we can have confidence that it's actually working because we can unify the data. to understand, hey, I bid on this Google search term. I can connect my Google ads to my Google analytics, to my postdoc, to my CRM, to my payment processor.
And we can know this search term when I spend money on it, it has a greater likelihood of a higher customer lifetime value. And that's like kind of the whole piece. And everything that we're doing today is built on top of that infrastructure.
But I always just try to start there to kind of give people like a frame of context to think about this. Got it. that's really good and just just to confirm here i mean it sounds like that this this is very much the foundational piece of what you need to do this go to market engineering right so anybody that you hire like they should be running through this infrastructure so this this uh let's call it a marketing brain this marketing brain continues to compound right and so this and this is this is um you guys have all this within graph .com is that what it is yeah yeah so we built this platform for this and then how we work with companies is we basically like we'll forward deploy software engineers to do these implementations but then other people can go and basically like use all this infrastructure and like everything that i'm doing today is on top of that again you can do this open source like you can go and burn 20 grand in fable tokens literally just hand it this transcript and that the notion doc that we're going to provide you and you can go and build this yourself um and but you know again fundamentally it's the same ideas we're just
all the infrastructure that is needed for the agent to do this marketing work for us. And the last thing to like piggyback on top of this with is what our thesis and like how we see the world like evolving is like all marketing is now just going, it's turning into code, right? And like when you think about a seed dance video, like we're going to generate these today.
What is that? It's literally a JSON file that's being sent to an API that's running on some GPU that's being sent back, right? When I upload that ad into Facebook, like that is just a...
piece of software that is basically like publishing that that content that i just generated up into the platform when i am analyzing the data that's just an sql query that's happening under the hood that the coding agent is writing for us hitting the data warehouse pulling the necessary information that it needs just in time to do the action to do the analysis that you know i'm basically asking it to do and so when you like you know where does this all go and where's the puck going to right and how do we skate to that it's basically this is where this is is evolving to and every company that we're talking to okay how do i do how do i build this how do i teach my team to do this etc yep yeah and let's talk about that so by the way i'm going to launch a poll real quick because um cody actually shared the things that he's excited about so i'm going to share this poll in terms of what is most interesting to you so there's this little poll on the side if you guys can click that i'll maybe end it once i have enough answers here but the thing that we're we're seeing is this right and so
um if you're a good marketer you now have everything in your hands you can build anything that you want right and and you can also just because you can build anything just doesn't mean you should you can just you can build anything just on everything right um but having this type of infrastructure is important because when we get people that come to us and they're looking for help they're like well well eric we can we can build all this like why do we need you guys right well then i then i look at them and i'm like well, who's going to maintain it and what, who's going to optimize it and who's going to upgrade it for you?
And they're like, oh yeah, you're right. Like, we don't want to deal with that. Right.
And so like, I think any of you that are on this call right now, and you're in services or you're, you're on a marketing team, just keep in mind, if you're really good at what you do, you're always going to be in demand. Um, if not more now on the flip side of that, I'll say this, right. I look at the work that we've been doing with my YouTube channel, right?
I'm like, dude. it takes forever to get an edit done okay and even when the edit comes out it's not that good and then it takes forever to get a thumbnail out and it takes forever to post that even when we post it there's issues with that too and i'm just like you know a part of my language but i'm like what the like why don't i just run it through all these skills and literally i create i ripped out three videos over saturday i'm just so pissed off now right and i think the week before i did the same thing too And then people show up to the call.
I know one of the people is on the call watching this right now, right? But I show up to the call with the brand team and they're all scared. And I'm like, don't be scared.
If you're doing this stuff, you're working in this way, like how Cody's talking about right now, you're good, right? If you're not working this way, it's going to go two ways. You're going to go up or you're going to go out, right?
And again, I like to say again, AI is an intelligence amplifier. It's also a too. I mean, maybe, Cody, it's a good place to start, I think, with maybe the Seed Dance part in terms of just giving people ideas on how marketers actually work today because that one has the most uploads.
Number two, okay, let me just give it to you. Seed Dance is 33%. FB ad library mapping for entire category, that's number two.
Tied with LinkedIn post to cold email DM, that's number three. And then link building with cold email naturally is last because not everyone has an SEO background, so that makes sense. i love it yeah that'll make sense all right cool um yeah we'll just jump into it and i'll start screen sharing and just jump it through but uh just to begin just a quick uh this is a test that we're running right now and i think it's hilarious and i'm just going to give you all a bunch of free sauce of something that we found recently so this was published literally yesterday this we're going to do a parasite seo strategy So this is Facebook ads for Odontis.
We're doing a campaign for this right now. Do you want to explain Parasite SEO real quick? Yeah, absolutely.
So Parasite SEO is basically using the domain authority of a separate website to get an article or a piece of content to rank. So this piece of content that I'm showing you right here was... research written and like you know published by ai to our facebook uh sorry to our linkedin ad page it's a pulse article and i'm literally going to show you how to do this right now and within the time that this live call like is is done like this we'll have written an article, published it, and have it on page one of Google for the target keyword.
So in 20 minutes, this went to page one, position one for this target keyword phrase yesterday. You can see it was published 17 hours ago. So anyways, I'm going to just begin here.
And you're basically going to be co -working with me today because I was in 30 hours of calls last week and got nothing done. And there's a ton of things that I need to get done on the actual... go to market for our side of our company.
And I'm going to walk you through and teach you, you know, everything that we do for that. But okay, for this first one. So how do you actually do this?
So I'm going to do it for this keyword here. Facebook ads for kitchen remodeling. So what we find working right now for SEO is basically scrape what's ranking on page one of Google currently, you extract that content, put it into the context window.
and then you write an article based off of that um and then you can modify it for your own you know uh uh brands you know based off of what you're seeing but like for example we're running this campaign facebook ads for like x business type so facebook ads for pet grooming This article was research written, published, and is refreshed continually by an agent in the background.
And then we have call to actions that are scattered throughout the page, basically, for different levels of commitment into the product. So how do we actually do this? I'm going to start this process right now.
So I'm literally like I normally have an agent go and do this, but I'm going to show you the manual side just to begin. You go and extract all the content from page one. I'm just going to open up Claude and I'm going to paste that in.
And again, we'll just go through each of these individually. How I would normally do this is I would use a tool called SERPR .dev. And it has an API that enables me to scrape the front page of Google to extract out what is ranking currently.
And then I would use XAI or Firecrawl to basically go and pull this out. Oh, sorry, you can't see my cloud code. So let me reshare with the correct full screen.
So one second. Awesome. all right um so i'm basically just pulling in all of uh the content from uh these articles that are currently ranking and why are we doing this it's because google is already signaling to us that this content is what it's looking for um by you know it being in the search results we basically know the shape of content that it's looking for right How you would modify this when you actually publish it for a brand that you're working with is you would record a conversation with the founder of the company about their unique positioning.
How do they fit into the market? What's their unique thesis? 30 minute conversation.
Give that transcript. You basically take what is ranking currently, what we just extracted. You provide both what is ranking currently, their unique point of view on the industry.
And then that will basically make this like. qual this article that meets the uh basically what google is looking for and also uh um you know talk about the brand that you're trying to position there's a lot of stuff that you can do here with like iterative loops for like you know you're trying to for example there's a plugin called like no ai slap if you're trying to like remove the the things that it does regularly but anyways coming back up to this um i'm going to now go and have it write this article so i'm going to say uh write an article uh for the target or for the target keyword Sorry, I need to start using transcription so we can move faster.
Give me one second and I will do that for the target keyword. What did we decide that we're actually doing today? Hilario says it's disconnecting repeatedly.
So I'm not seeing that on my side. If anybody else is having issues, you can drop it in the chat, but I don't, yeah. But anyway, just so everyone knows, Cody here, it looks like Stacey might be a little confused.
I think what Cody is showing here is how do you rank number one quickly with the content that you're publishing? from an SEO, AEO standpoint. And that's very valuable.
This is largely just the very bottom of Funnel Tactic. I'm going to immediately go into Seedance after this. All of this is going to happen in parallel.
So I'm just starting the initial and then we're going to be bouncing between multiple chats basically to push this all along. So write an article for the target keyword, Facebook ads for kitchen remodeling based off of the following source text. Oh, and Cody, Karina says, can we zoom in a little bit?
Yeah, absolutely. Happy to. Following source text.
And again, that source text that we scraped is below. So I'm going to start that writing. And then now we're going to go and we're going to start the seed dance chat.
So again, everything that I have already, or that I talked about, all of the unified APIs, all the data that is necessary, that is already connected into my cloud code. Again, I'm just using the graph CLI for this. But again, you can build this yourself, you know, basically patching all of this together.
So I'm going to say, okay. We're going to start making ads for Seed Dance. We're going to use the AI avatars that we have saved that are in the kitchen.
Cool. So I'm going to get that to start running. So to begin how we actually go and make good quality outputs and what we're trying to get, it's really three things that we need to have happening.
We need to have a voice that sounds realistic. we need to have an avatar that basically matches uh uh like the voice and the environment that they're in this is actually the hardest part is basically like if somebody is in a car right we need an audio track that basically sounds like they're in a car it can't be studio level quality otherwise it has this like like discrepancy and so today what i'm doing is i have found this voice on 11 labs called natasha that's what we're going to be using and then what we're going to be doing as well is basically using the uh these ai avatars I'll show you those real quick.
So I have a five different avatars that are different age demographics and different ethnicities. And the reason for this is because Andromeda now how it's targeting functions is it's basically based off of the ad creative. And so the script that we give it and also the avatar that we use is going to basically define who it's going to show the ad to in front of them.
And so this is a way for us to like. with all of our campaigns that we're running for clients at this point, unless we're doing account -based marketing, we are targeting all of Facebook and then we're making the creative basically be the positioning element. So historically you would do interest -based targeting, right?
So say you wanted to market to people who have a mountain biking interest because they're trying to sell pedals to them. Instead of doing that now, what you would do is you would make the creative so that it's speaking directly to them. So this workflow that I'm going to show you right now is what we're using for software companies.
The outcomes, just to kind of, show you what that is created. So this is an example of a company.
This is demo requests booked using this exact strategy, basically. So this is them over the last, whatever, 12 or three months. So, okay, going into this, to actually pull the scripts and make the scripts, what we're going to do is we're going to scrape Reddit for the pain points and desired outcomes that people have in relation, in relationship to whatever the product is that we're trying to sell.
So we're going to do this just for graph today for the ease of it. So I'm going to say, Use the Exa AI API key to scrape Reddit for the pain points and desired outcomes that somebody would want to buy an AI agent that runs their Google ads for them.
Maybe they dislike their agency or they feel that the agency isn't doing anything unique or different. But again, just source from any of the Reddit threads that you can find in relationship to this. So I'm going to let that start running.
And in the background, we're going to come back to the article that it wrote. So I'm going to say, just return the text here within the chat. And then we're going to take that and actually go get that index.
So this is how I'm working continuously in the background now is basically all of these things are happening simultaneously. And once I figured out the system, like the seed dance system that we have done today. what we're actually going to go do is we can then go and publish that.
So it's happening on a cadence. So every day, for example, I can have 10 new pieces of ad creative get uploaded into a CBO level campaign and Facebook ads. And those automatically get generated, uploaded.
And then I can also create a feedback loop on top of that, where it's basically looking at the conversion data and it's making new creative like the ones that are winning. And we know which creative that is winning because we've already saved that JSON. We've saved all that work into that database for all of the actions that we're basically doing or working on.
Use the graph, sorry. Use the graph CLI for this extraction.
And coming back to this Facebook piece, let's copy this over. And now I'm going to go back to LinkedIn and I'm going to just publish this to, we'll just go to graphs just to show you how crazy this is. I'm obsessed with this right now.
So this is why I'm showing it. And I'm just trying to give you free arbitrage that exists in the market currently. So we're going to go create a post and the post that we're going to do is write an article.
I'm going to paste in that article that we just wrote. Have the keyword phrase be the exact title because then that will come out as the URL. And then I'm going to take this first intro section and I'm going to add that to the post here and hit publish.
Now, once this is published, we can then take the URL that it provides. You can see here it says Facebook ads kitchen remodeling. And I can take that URL and I'm going to go and use a tool called Prime Indexer.
And Prime Indexer basically does a drip ping to this that enables these to get seen. Do not do this for your core website. You can only do this for your basically external, these parasite sites.
But this is this way. And again, I'm going to show you this right now. This should go to page one.
We'll see what happens. Actually, always live. It's, you know, who knows what's going to go on.
But you can see this is not indexed by Google currently. But through this process, it basically should get it indexed and we should show up in the search results. So coming back to Clog Code, on the CDN side, it's still doing that scrape for Reddit.
So it's pulling out that information. Cody, what's the indexing tool again? It's called Prime Indexer is the tool.
And they have an API that's accessible for this as well. So you could hypothetically publish. Yep.
That's really important because one of our workflows right now, the challenge is they're not getting indexed. And even if you use GSC, there's no clear API with that. So I think this is really important to have in the workflow.
But continue, please. Yeah, yeah, totally. So just to expand on what's happening here in the background, like why do I even, why am I even talking about this?
You can make LinkedIn pages for free and you can publish this content to those LinkedIn pages. And if it's optimized appropriately and it's targeting the correct keywords, you can get this to literally show up and we'll see this like within minutes will be like, it will be indexed at least by Google. and hypothetically on page one and we've done this a couple of times you can see a handful of these here and i'll show you those but all right um coming back uh to seed dance um so this is still pulling or scraping from reddit so what was the next one uh eric that they wanted to start have a start on yeah so the next one okay so it is a tie you can choose here cody so it can be uh linkedin post to call email dm which i think is probably a good one um so let's just go with that one then i'll tell you the third one yeah awesome yeah so So LinkedIn posts to Coldium, how we use these is typically to extract the engagers from influencers that are in the product category that we are in, right?
So what does that look like actually in practice? Let me just go into like AI, like Facebook ads. Let's see what comes up.
So I would find posts. All these are kind of garbage. Let me go to the homepage.
And by the way, Cody, do you mind if I add in for the last one as you pull this up? um the thing that cody is doing really with the last one is he's getting a post up and it's going on linkedin and it goes to public and then google can index that but linkedin site is very strong from a domain authority standpoint which is why it's going to rank better than your main site for the most part but that's not to say that you can't test it on your main site cody's not saying that I, yeah, you can do, you can write that article and publish it in the exact same way.
The only difference is that do not use prime indexer on your core site. And the reason for that is this is basically doing a drip ping to that, that, that link. You don't want to do that to your main site.
It just can have like negative effects. You want to only do this bit to a large site. This is also effective if you're building listings for SMB.
Like, so for example, if you're trying to rank within the map pack for like, say like you know commercial cleaning sf as an example right um if you're trying to rank within this map pack um how do you actually do that um it's basically you want to take the name address and phone number and put it on as many directory websites as you can for example like mapquest like foursquare etc but the problem with that is that these sites are massive there's literally you know hundreds of thousands of pages so how do you get google to actually see those pages That's where you can use, again, something like a prime indexer to actually do the strip ping to it.
LinkedIn is just another example of like this site that you can publish to that you can link from. So, all right, coming back. Oh my God, MapQuest is trying to nuke my RAM.
Right. Coming back to LinkedIn to show that process. So I'm going to see if I can find something that's about AI for marketing.
Potentially clay. So like anybody that interacts with this, that could be one. So I could put that up as an observer.
But the strategy here that we're going to actually illustrate is I'm going to find, for example, 10 different profiles on LinkedIn. You know, imagine this is 10 of them. And every day they're going to do a new post, right?
So they're going to do a new post, each of them individually. And then from those new posts, I'm going to extract, you know, the 100 engagers, the 50 engagers that are coming out of them. And then once I have their LinkedIn profiles, it gets game over.
I can cold LinkedIn them using something like Heyreach. Or I can do a waterfall email enrichment to find their emails and actually cold email them as well. So again, just to talk through that process, I'm basically setting up a listener that daily checks for net new posts.
And this is exactly what I'm going to tell the agent and tell it to use Appify to do this. And then I'm going to extract the actual engagers from the posts. And then I'm going to find the emails and we're going to add those emails into the Instantly AI.
And everything I just described, we're going to walk through this right now. How do we actually do this? I'm just going to use my own profile for this just because it's going to make this like fast right now.
So we'll say, okay, everybody that, you know, is engaged with this, I will just give my profile into Cloud Currently. And again, I have that Appify endpoint already established to extract the LinkedIn profiles. The Appify that we like is this guy named API Maestro.
He has the best LinkedIn ones in our opinion. Shout out to him. He's a great partner.
So we always try to show him as much as we can. And we're using basically this LinkedIn profile extraction. And the reason that we're doing this is that we're trying to not have our core account basically like doing all of these requests to LinkedIn.
And so this is this way to basically navigate around this. He is handling all the proxies. He's handling all the scraping.
So I'm going to say this now. And just a heads up. Oh, sorry.
Yeah. the um just so everyone knows the reason you don't want to hit your your main linkedin account is because that's this type of shit that can get you banned so that's what cody's saying totally yeah and it's i see this happen a lot where people like give agents like they're you know basically like uh browser use and then they have to go to these automations i am just warrant like do not do that you are just asking for something to go wrong like the best way to do this there's there's there's a boundary of basically like you know white gray hat right like where you want to live in and everything i'm describing today is like again we have found that this works over all of the clients the companies that we're working with and also our own personal stuff and everybody that's on the platform that's using it so i'm going to say all right we're going to use the appify api to the graph cli uh to extract all the posts uh from this user from the last seven days and then i want to extract the linkedin profile urls of those individuals and then uh
Get leads to do a waterfall email enrichment. If you need to go to lead magic or just guest their email as well, feel free to do that. Validate the email with million verifier.
And then I'm going to give you an instantly campaign to upload those emails into so that we can do cold outbound to them. So again, I'm just using super whisper to transcribe that workflow that I just described. historically if i wanted to go do this right like i am going to go and hog wrestle n8n or you know zapier to basically make this work workflow do not do that uh you know our running joke internally is friends don't let friends do n8n the better way to do this is go straight to code and the reason that you want that is one it's more discreet but second it's also more flexible so you can modify these workflows at any point in time so i'm gonna get that fired off and we're gonna come back to seed dance now You know what's funny, Cody?
We tell people during the interview process, we tell them afterwards, and it's like, oh, well, why aren't we moving forward? It's because you listed NNN. That's so funny.
And this is taking forever for some reasons. I'm just going to speed this up and just use perplexity. I'm going to say scrape Reddit for the pain points and desired outcomes of why somebody would buy an AI agent that runs their Google Ads automatically for them.
All right. We're going to get that to fire off. And then I'm just going to give that source material as the source material for the scripts that we are about to go and write those scripts.
We're going to create an MP3 file first. And then that MP3 file, we're going to send that to C dance and have it lip sync using the AI avatars that we like showed previously. And again, I'm going to walk you through that whole process, but I'm just going to wait for that as it comes out.
So while that's going on, let's come back to prime index for now. Let's see if it got indexed. All right, cool.
So it did get it indexed. See if it's live. It hasn't hit yet.
So we'll keep refreshing this to see when this basically gets seen by Google. So typically it takes like a minute or two after this. All right, coming back.
So we got the user post. So this is working in the background. It's scraping the reactions and comments and it's adding it to a CSV.
You can see all the tool calls that it's basically making for me. And then while that's happening, let me just log into instantly real quick. I'm actually going to just...
Stop screen share for a second so I don't show an API key or potentially - No API keys, yep. Exactly. All right.
I just want to make sure I'm in the correct account. Okay, perfect. All right.
So I'm in the correct account. And so I'm in instantly. And I've got, I think, 1 ,000 inboxes that I've got connected here.
The inboxes that I'm using, they are through a partner called HyperTide that we love working with. You can basically send about 10 ,000 cold emails a month on top of their infrastructure for about $125 in infrastructure costs. And so if you translate that, you could send a million cold emails a month for, you know, about eight grand is what this turns into.
This is a whole other rabbit hole we can go down, Eric. We are thinking about cold email now as like a one -to -one marketing channel. Yeah, same here.
Cody, the question is, so they seem like they're managed service, right? HyperTide? um and you just pay them to manage it right and my whole thing is like with with our infrastructure internally right now um this was set up like a couple months ago but we had her me set it all up um but you know at the same time though you at the same time we have to manage it right but it's not that big of a pain in the butt on our end but hypertype you say it was like 120 bucks for how many emails 120 you can send about 10 000 cold emails a month why we like them is they manage all of the microsoft uh like entre infrastructure um what does that mean is it they basically isolate uh the domains that it's called a tenant But Microsoft, if you get put into a bad tenant pool, your deliverability is terrible.
And so what they basically handle is the tenant management. So imagine we buy 20 domains and we're spinning up, I think how they do it is like 100 inboxes per domain. They put two domains per tenant.
And so it creates this like isolation so that if a tenant does get burned or a domain does get burned, it doesn't affect the entire infrastructure that you're running on. So anyways, we just worked with them. There's tons of these.
InboxKit is another one. There's, and it's more like self -service. They're more like, they serve a lot of like agencies and partners, like the stuff, the work that we do.
But anyways, just, you know, service providers that we see. Instantly also offers these like pre -warmed domains as well. And you can buy these from them.
They actually have great deliverability. The only problem is they're not branded to your, it's not like a burner domain that you're sending from. So it's just.
Depends on what you're trying to do. But anyway, all right. So we've got those domains.
They've been warmed. They're ready to send. So I'm going to create a new campaign and I'm just going to call it like LinkedIn Engagers.
And let me continue. And at this point, I'm going to take this URL. And because it already has the instantly API key, it knows it can automatically upload these leads.
So I'll say. When you're done with the email validation, upload the leads into this instantly campaign.
And then while that's happening, I can also start working on the copy for that instantly campaign. So I can say something like, I want to create a two email sequence. So for this instantly campaign, email one, the subject line, have it be LinkedIn.
or saw your comment on my LinkedIn as the subject line and then have the text be something like, hey, name, saw you commented on my LinkedIn post, took a look at your Google ads or your Facebook ads library and saw that you were only running a handful of creative. If we could ship 80 new pieces of creative a month for you.
automatically and have a learning loop where an agent is running the media buying of the account, would this be interesting to you and worth a call? Some variations of that make it extremely concise. And I want you to focus on the economy of words with the writing that you're doing for these emails.
Got it. And Cody, are you trying to share your cloud dashboard? Oh, sorry.
Yeah, I apologize. Let me, that was sharing the window. So I am back now on the Claude dashboard and that transcription that I just did.
So again, I added into that the user post. Let me just shoot this off first so that it's going. So it's going to create that email campaign.
But I added the, sorry, I didn't actually add it to this one, but I'm going to say, uh add the leads to this campaign uh once you're done with million verifier by the way as cody's doing this right now i think it's really important to emphasize that the future like ai native marketers are spending the vast majority of their time within the harness like it should probably be 85 90 plus if i'm being honest and the work that we expect people to do like if you're an engineer 95 of your code should probably be written by ai um and then if it's like if you're not you're not an engineer our expectation is that 70 of your work is done by ai uh that's just how we are cody i'm not sure how you guys think about that we're like literally anything that touches a keyboard at this point like if you use the computer for the work like you should be trying to figure out can i get an agent to do this um and there's things that are still on the like the like the early days like for example long form video editing but like
I am getting incredible results right now with DaVinci Resolves MCP and an Astra subscription. It is ridiculous the outputs that you can get out of there. It's absolutely insane.
Even for long -form editing now, I just think there's no more excuses. Yeah, but please continue. Totally, totally.
No, no, no, please. I'm happy to talk to me in the background too. Feel free to.
So I'm going to say here's the source material. So this is, again, I'm just, I don't know. It got in this thinking loop and I'm not going to try to solve it right now.
I basically, again, I'm scraping through social, the conversations that people have had that have basically, they've shown like, again, their pain or the desired outcomes that they have in relationship to the product that your product can solve for them or your service can solve for them. So here's the source material. And I'm going to say, I want you, actually, I'm just going to have to save it just for now.
We're going to write the scripts next. We're going to write the scripts next.
We're going to, there we go. And what I'm going to go do, I don't have this saved here. So I'm just going to go to my Twitter to extract this.
So I have a list of Cody Schneider posts, list of Facebook ads hooks.
I'm just going to, we found it's like 10 Facebook ad hooks that works really effectively for like software, but they also can be translated to other companies or other business categories. We're actually finding them work like really well for local service businesses right now too. But we'll take those hooks and then we're going to basically do a hook and then a desired outcome, like pain point structure.
And I'm going to show you what that looks like. So here's these hooks from a post that I wrote previously. I'm then going to go and I'm going to drop this in and I'm going to say, Let's do 15.
Write 15 add script variations, use the hooks below, and then use the source material above that I just provided as for the rest of the script. The script needs to be 30 seconds long and use super simple language. Again, think on the economy of words.
I wanted that like a... 12th grade reading level um for this and then um the format is going to be hook and then you know desired outcome pain point combination so all right so i'm going to have it write the scripts now once i have those scripts and then i'm then going to send those scripts to 11 labs once i have the mp3 files back from 11 labs i'm going to send that to We're using right now Kai AI or Seed Dance, or sorry, Kai AI or Higgs Field for Seed Dance.
Higgs Field is what we're finding. We can get a 30 -second video out of Higgs Field right now for about $2 .50 with like the basic pricing that we've got locked in with them. And then we will generate these videos.
So I'm going to send the MP3 file and the avatar screenshot that I showed previously. And we'll bring those up again in a second. We're going to send those all to...
uh seed dance like takai ai which is hosting the seed dance model for us and then that will basically uh we'll have that final media once we have that final media we'll actually go and upload that into facebook ads and we can show you that whole process there so cool i've got these email variations let's take a look at these Notice that Cody's doing multiple jobs at the same time right now.
He's doing SEO. He's doing signal -based outreach. He's getting ads up at the same time.
This is like many, many, many jobs at once. Totally, totally. And again, this is not anything that a human wasn't doing previously.
We are just taking the human process that used to occur, like a media buyer. What was a media buyer doing, right? They were publishing new ads to Facebook.
They were trimming the losers. They were promoting the winners. And then they were creating a feedback loop of what does the winning content look like?
How do I go and make more of that winning content? We're doing the exact same process. But again, all of that middle work.
We're getting the coding agent to do that work for us because it has access to all of these tools, all of this infrastructure. And then once we have done that system, like I just wrote this, like we just did this process, right? Or sorry, this one here, this email enrichment process that it's still going through.
Once we've done this process, I can say, okay, I want to turn this into a piece of software. And I want you to deploy this into my cloud, right? Like into, again, I'm just using the Graph Cloud, but this would be basically stored on a server.
And then I can have it, or again, daily. I give it a list of 10 different creators. It's extracting those posts, extracting the engagers from the net new posts, doing this whole enrichment.
And so in the background, I'm just constantly feeding my system new leads that it's doing this outbound to. All right, cool. So it wrote the script files.
Let's take a look at those real fast just to kind of see. I'll pull you guys over here so you're not in the way. okay, I didn't think this would actually work.
I paid an agency to run my Google ads. They checked it once a month. The rest of the month, my money went to junk searches and cheap leads that never bought.
Now an AI agent watches my account every day. This is great. Cool.
Awesome. I just kind of gut check those again. We've done this enough now that it's like, I don't even really look at these anymore.
I just create a walled garden for my agent to work within. And then I just let it go and figure it out for me, right? I'm letting it do all of that middle work.
And this is very uncomfortable to large companies, by the way, like we're working with a large software company right now. And it's like to convince the team internally that this is the way to win, especially for account -based marketing, where like add creative velocity is the challenge. This is something, you know, a very large, yeah, yeah.
Well, now you have Jeff, right? You have a classifier and the evaluator at scale and it's so cheap that like... You know what I mean?
And the reality too is like we, you know, this is, we're doing a zero to one right now, but in reality, like I have creative most of the time that I am remixing because I already have signal, right? Like that, you know, again, this outcome that I was talking about, we've shipped, you know, thousands of ads for this company at this point.
We have very strong signal knowing what's actually working for them, right? This is just, again, that zero to one. So we've done that.
Now I'm going to say, I'm trying to think what the name is. Use the Natasha voice.
We're going to send those scripts to 11 Labs via the 11 Labs API. If you need the Natasha voice ID, let me know. It should be stored somewhere within the file that I can specify where it is if necessary.
All right, so that's continuing on. I've got these emails. I'll just say, cool, are these added to that Instantly campaign?
and the cold emails again still running in the background i'm just going to ask it give me a status report and then we're going to come back and we're going to check on this seo strategy that's going on in the background so let's check that again now um where it was prime indexer cool so we got the url let's see if that's online currently cool so it still hasn't indexed which again, this is what it takes.
Sometimes when you're doing it live, things don't work. But the, again, just to kind of show you like what can happen with this. So we did this exact same thing for like Facebook ads for pet grooming.
It should be, I think that dropped off on the LinkedIn side.
Maybe it's pulling it. Oh, sorry. It's right here.
So Facebook ads for pet grooming, exact same strategy. Facebook ads for orthodontists. Mike is getting the same thing.
Orthodontists. And then we'll see. Let me see if it's actually just not showing on the index, but it's showing up for the remodel.
Cool, we'll keep an eye on that while it's running in the background. And actually, I might actually start another one because I'm just curious to see if we can do it while we're waiting for this other stuff.
And Cody, just to confirm, right now you have the SEO piece, you have the ads piece, you have the signal -based outreach, like the DMs as well. Those are the three things you're cooking right now on the screen? Yep, those are the three things that I'm cooking right now.
So I've got... I've got a question. Yeah, please.
Yeah, so on the signal -based Q8, so it's like... You know, this is coming from my team, by the way. So on personalization, right?
So let's say you're... you get an Instagram or a, sorry, a LinkedIn post out there. It gets like a thousand comments or whatever.
Right. And then you're looking for people that are ICP fit and you're reaching out to these people. So one of the questions for our team was like, how do you QA signal based content at scale?
You know, are you spot checking? Is there anything, is there something that filters? And I have an answer in mind, but maybe you're, you're doing something.
Yeah, yeah, totally. I mean, we, you can do an ICP filter, like basically on the content that it's being, like you can pull the LinkedIn content itself. that and basically extract the text to be like okay i want you to rank this you know one to ten does this match this icp fit that i you know have defined in a markdown file and then basically you know it it kind of qualifies them on the front end for that um that is a way to do this uh the other uh way um that we've seen most creators like it's it's a lot of it comes down to the creator selection that you're observing most of the creators are talking about the exact same thing like they found a category that's how they're basically like you know gaming the for you page algorithm is they found a niche um that's working for them so they're not really like you know straying away from that to say that yeah so and do you have like a rule set here where it's like hey you know if they're if they're icp fit and they've engaged with you three times in the last you know 30 days are they like tier one versus somebody else like how do you think about that you could absolutely do that yeah i mean we're doing a lot more of this um just getting into the weeds but it's like called a tam mapping right so like total addressable market mapping
What this enables you to do is you basically can go. That's funny. What this basically enables you to do is you can go and find everybody that's in your target audience that you're trying to sell to.
Also, this is like what the best companies in software startups have been doing for years now. It's just now proliferating. It's had it before you'd have to be incredibly technical to be able to actually accomplish this, accomplish this.
But it's basically finding all the companies that you would want to sell to within your industry. You find the firmographics, the company size, how many employees they have, etc. And then you find the decision maker at that company.
And then you basically can observe that decision maker. Are they engaging with this content? You can do de -anonymization of them to the website as well, using something like a lead pipe, where it's basically as they hit the site, you can see that they're coming to it.
um again there's a lot of like levers that you can pull here but basically what you're trying to trigger is you're looking for a signal or for example like this person changed their job they went from you know company a to company b strong signal that they are you know about to go into a buying cycle everybody always buys new when they join another company um and so uh you're basically stacking all these signals together and then uh From that TAM map that you've created, when a person lights up from one of those signals, you then can go and do that cold outbound motion to them.
Yeah. And I hate to keep mentioning Jeff, but I'm just like, dude, now you can classify these things. Did they actually engage?
Are they ICP fit? Were they active in the last 30 days? All these things that are impossible for a human, you can do it all now.
And I'm not a salesperson for Jeff, by the way. No, no, no. Yeah, I think there is a lot of use.
I mean, what we're excited about with Jeff is like, you know. We can do a TAM mapping of the entire, like all the ads in the United States for like a category and like pull those and understand what is in them like pretty effectively using this. So for example, like we just did this recently for car detailing because we're like doing an initiative around that.
know business category for some of our work um so we found like all the ads that were basically running for car detailing and then had a vision model and that's multi -modal so it can look at the image and then also look at the video basically extract okay what is in the video writes that out and within text and then from that we can basically source like what are the commonalities between ads that are people are running which is the signal of what's working if they're running you know a lot of people are running similar ads there's you know within different geography a strong signal that those ads are probably you know being for them on a lead generation standpoint.
So yeah, other questions. I see the chat kind of blown up. Yeah.
So I'll get Syed and Steve have a question around what about B2C workflows or are your workflows only for B2B? Yeah, B2C is the kind of same strategy. I think the biggest thing on the B2C side that we found to be successful, depending on the company type, we've only really worked with like mobile applications that are on the consumer side, but add creative volume is like, I mean, if you go and you look at like Rye's Superfoods as an example at this point, Let me go to their Facebook ads library.
I think they have, it's something in the range of like 5 ,000 pieces of like active creative that they're testing simultaneously. This is what the best companies in the world are doing right now is they're basically like testing a ridiculous amount of creative. Yeah, they have 5 ,100, right?
This is 5 ,100 active ads. that they are running in parallel currently. How do you think they're doing this?
They are 100 % using AI. You can see the creative production here. It's literally an animation that they're doing.
They have a team of creatives that are pumping these out. They also are doing partnerships with creators using something like a side shift or tribe. SideShift and Tribe basically are like creator marketplaces where you can pay them on a per video that they produce.
So for example, like we're running a campaign right now for a company where we pay $40 per UGC content that they generate. You can also structure it in ways though where it's like you pay them on a percentage of the media that is spent. on the ad credit that they produce for you.
So like, you know, say deploy grants, and you pay them, for example, like 3 % of that $1 ,000 for, you know, the video that they make. So only the videos that win, basically, you're paying them for so, but side shift tribe is another one. And again, I'm just, I was just at a dinner in San Francisco, like two weeks ago, and a huge company, same, I cannot say.
um very fast growing startup uh they are doing an absolutely a massive amount of content production using these uh these creator networks um like tribe like side shifts um and then to manage these networks how they're actually doing this is all like everything that we've been talking about today we're using your coding harness SideShift has an API.
You can basically manage these campaigns. You used to have to have a full -time person focusing on this. That was managing the creator production pipeline, answering their questions, actually looking at the creative to see if it matches the requirements for the campaign.
You can have literally a vision model with agents and through the API do that entire management process. I got a question. Cody, are you primarily using CloudCode or are you using any other harnesses and are using any autonomous agents to help you?
Yeah, yeah, yeah. So the company works out of Cursor and their cloud agent infrastructure is really good. So that's why we've done it.
My daily driver is like a combination of Cursor and CloudCode. A lot of the times I have both open. And then I'm just starting to use Codex again because, again, for the video editing capabilities and some of the...
coding like long time horizons i'm pretty agnostic to this i think the biggest thing that i'm trying to like do is basically use cloud agents more and like how do i basically get those cloud agents to work in the background um we don't really use we had experimented with hermes and like with these other i would call them like almost co -worker style agents um and like getting them in slack and that thing but we just found that they're this is probably a contradictory take but I'm like against token maxing.
I think it's really stupid. I think that's a good take. Yeah, I'm with you.
But I think it's against like what, everybody's like token max, like you should be burnt. I think it's the dumbest thing. Like, why am I paying, like, why am I playing Claude or Anthropic to schedule a, like social media posts, you know, every time that I'm trying to, or like to write a blog, like what I should be doing is I should be using my coding harness to write software that's discreet.
and when i say like a marketing agent right like a google ads like marketing agent which is like one of the ones that we have that we like deploy very often for companies that agent is just software with a thinking loop with a live data stream right it's not like god in a box is managing a google ads account we actually found that when you hook hermes up to like god you know to all this and tell it go do work it's kind of at it actually and like it's what is actually better is basically getting it to write software that is an algorithm that it's running and when you when you kind of take a step back it's it's it's a lot of what we found in the past right like how do you do the operations at your agency currently you have a human that's running an s like a standard operating procedure we're just taking that standard operating procedure we're translating it into code and then we're giving the agent like giving the coding agent all the data it needs so that it can write better code for that that process so got it i got two two questions before you kind of share what else we have and then uh maybe we can wrap it up with questions so um the
So right now, I mean, you mentioned like you don't necessarily need a ton of headcount, right? So I'm curious, the majority of your company is working like how you work right now. Like what is your headcount right now?
Yeah, we are six people. So it's my co -founder and I, we've got three, four deployed engineers and we have a head of sales. So that's kind of the structure.
Yeah, but look at how you guys are working. Like that's crazy to me, right? It's like - We can do a lot of work.
It's the amount that you can do now. Yeah, exactly. We, I mean, anecdotally, like, what is this?
It's September. I think it was in July. We published in the range.
I think it was like 11 ,000 ads across all the companies that we're working with. And this is not like, when I say that people are like, oh, it's slop. And I'm like, no, this is like brand style guides with iterative loops that it doesn't, it has like a gate basically where the creative can't pass through the gate unless it meets the brand style guides.
Right. So. We also, you can like get human in the loops for this.
This is actually something just to add to this. We have found that humans are actually, they need to get out of the way for all this work. Humans like want this oversight to begin with and then they become the bottleneck.
They're like, I can't prove 20 new pieces of ad creative per day, right? But an agent can happily do that and at a quality bar that is 99 .9 % of the way there when you give it the right infrastructure, right? When you say, okay, again, here's this brand style guide, make the ad.
look at the ad like with a different like vision model like does this meet the brand style guides oh you're using a font that's incorrect cool send that back to the chat gpt image 2 .5 make that you know make that change so yeah and cody second question here um Cody, before we go back to the screen share and then maybe more questions, you kind of shared some performance numbers, right?
So I think it was like on a hundred grand in spend, you're able to book like, I don't know, 500 meetings or something. And the cost per book meeting was 200. Like, do you have any other performance numbers you can share around this stuff just so people can really grasp that this shit works?
Yeah. I mean, so working with the company, They're in the wellness space.
They're in a franchise. We're working at the corporate level with them. We took their cost per lead from $70 on Facebook down to about $16 in the span of four weeks doing this exact process.
We're now basically having somebody, we're jokingly saying they're for this company. Um, they, uh, Google ads say like similar outcomes where it was like, I think it was like $82 and we got it down to like 35 in the same period. Um, so that's on the like, you know, regional business side, uh, for software companies, um, you know, book demos, uh, we like trying to think about some of the other outcomes on the paid ad side, just off the top of my head.
The biggest one that comes to mind is the one I showed you. Um, we're also working with a prosumer application, uh, where we basically started. We zero to one their entire Facebook ads strategy and took it from zero to, I think they did, it was in the range of 20 ,000 signups across.
We did Facebook ads, Google ads, SEO, cold email, LinkedIn DMs. We basically did that whole stack and had it out the door for them in three weeks. I think when we started with them, it was June.
I think they did about 2 ,000 signups in that month. Again, on that. scaling they're doubling basically month over month since we started with them is what it looks like so this is the um yeah on the linkedin cold dms like what kind of performance are you seeing there in terms of like hey you send like a thousand messages and like x amount of people book like do you have any numbers like that yeah yeah it really depends on so what we have found is that the with cold outbound the only way this may you make this work right now is you have to have an offer that the market wants so the the strategy that we found to work is you find an influencer in your category You record a live class with them.
And then you use that within the outbound motion where you're like, hey, name. Again, saw you commented on X post. Reaching out because we recorded a live class with Y influencer.
And it's about one, two, three, four, five. Thought you might be interested. Do you want me to send over the recording?
The recording is literally, they say, yes. It's literally just like a demo in disguise of your product. We found that to be very good on the performance side, on the response rate.
I actually have a podcast with my friend, Nick Abraham. Let me see if I can have the podcast. Where it basically, he talks through his, he's sending like a quarter million LinkedIn DMs a month.
And he explains exactly how he's doing it and how the outcomes that they're getting are more performant than literally any other. channel that he's doing called Outbound Slide. So anyways, if that's what somebody wants to go deeper on that, that's available there.
But yeah, coming back to this. So again, emails have been found. They are now in the Instantly accounts.
Let's see if the leads are there. Cool. Leads are there.
The sequences have been written. Everything has been mapped so that it will work appropriately. The inboxes are set up.
That can literally start sending. on the seed dance side we'll see if these will generate in time uh the scripts are have been written the mp3 files have been completed uh it's now just with kai for the seed dance renders so we'll see if that you know how that works coming back and then uh looking at uh let's come back to this uh see if the seo thing ended up happening curious if we ended up getting it to work live um Yep.
So that is now indexed by Google. And let's go see where it's ranking. So yeah, it's ranking position one.
This went live 38 minutes ago. So anyways, that's it, man. Any questions I can try to answer?
Happy to dive deeper on anything. Yeah, let's hit a few questions here and then we'll get Cody on his way. This has been phenomenal, man.
So we got a question here from Syed. We'll pop it up over here. So are you deploying these systems inside the companies, for example, the ads, or are you guys running everything through your own systems?
Yeah, so for the companies that we are working with, we basically like. function as a platform that we build these systems on top of our platform for them um at any point like you know we forward deploy the engineers so that uh they we can basically get these out the door as fast as possible because it's just like there's a huge gap in knowledge between this like you basically have to find somebody who's like has enough software engineering knowledge and also has enough marketing knowledge and it's just like a very rare person to almost impossible yeah it's very hard what we're finding works and this might be interesting for you eric is um it's these like 22 year olds that have like ran an ai consulting agency and they're like they have ran into these problems and they're looking for like a place to basically like anyways they're we're finding them to be that that's that's where we see this all going but um yeah so deploying onto the platform um you could build the platform yourself we just don't work with companies like that because it's like literally we've spent the last 18 months and so much money right to basically
you build out this infrastructure layer um but for the companies the things that we build on top uh build for them on top of us uh at any point they can be like cool we don't need the four deployed engineer anymore we just want this like virtual employee to continue to run on and it just lives on on top of the infrastructure and we just like then it just becomes usage based where it's like how many rows do you need synced what's the you know credits that you need uh you know for email enrichments for ad creative production etc so peyton has a really good question that i'm about to pull up but the the way i see this too is um you know we're all just agent managers at the end of the day now and our edge cody is living on the edge and people are always going to need that and so i remember there's someone listening to the the marketing school pod and they're like we just built this all ourselves and we realized that we just can't keep up with you and so like therefore if you're on top of this stuff people are always going to need you this agency stuff services stuff is not going away but let me come to payton's question over here so um payton asked how much budget have you seen be useful to test creative on this scale
Yeah, it's great. It depends on the cost per action, but we work with a lot of software companies where, you know, their cost per demo ranges from like 50 to $200, depending on the industry that they're in. We typically start with like a hundred dollars a day on Facebook ads and Google ads.
And, you know, anecdotally by week six, like we are very confident on like. with the data. We've had it as fast as like literally a week.
We have enough, you can do creative loops now where it's like, you know, every week I can do two to three creative loops where I'm like a tested piece, you know, a group of ads. I see what works. I go, you know, remix this.
We're actually doing this for this company right now. I don't think it'll care if I share it actually. Yeah.
It's called a void. They basically like get physical, like people, if you're like, I want people like. to discover my cafe or my local business like walk -ins to happen they like get people to go to your physical store and discover you like you pay 25 and a human shows up and they like literally take a photo of themselves there and like it's you know buy a coffee etc right um it's a super fascinating business model but for them it's like been this positioning uh uh like we've been helping them on that and go going through those iterative cycles of like how do we like position you know the company basically cool anyways um the uh That's kind of the scale.
Once you have that number, then it's just a CAC to lifetime value ratio. And if you're in an e -com company and you're listening to this, you know the game. It's just ROAS, right?
But what this ends up being is you start to see signal, and then you just chase it, and then you just continue to double down. The problem that we face is everything has a half -life now. And so there is some type of decay that happens.
You have to think about entropy, like how do I introduce new DNA to the system? The ways that we're doing that is we're basically scraping social. within our category.
And we're finding organic social posts that like go viral within, you know, whatever marketing and that then basically introduces that new DNA. So. Cool.
That's great. We'll cover one last point here. But Jay, Jay had some sauce to share.
I'm just going to put this on the screen. So I've never heard about P zero dot studio. I'm just going to share this with people.
I haven't tried it myself. I'm, I don't know if Cody has, but it's amazing.
Yeah, 70 % less than Higgs field API MCP X402 for payments as well. That's cool. Okay, one last thing that I think we could touch on before we get out of here.
Actually, Peyton has a good question here for you. So what percentage mix do you introduce entropy?
That's a good question. We don't have probably a very solid formula for this yet.
And largely what we'll see is that the CPA action will get to a threshold where we're like, okay, we think we can get cheaper. And then at that point we start to introduce, maybe it's like 20 to 30 % of the creative is like totally net new. And then as soon as, once we find like that net new that is working, like all, you know, how we built this is like, we just chase that signal, right?
So we're like sprinting towards that. But I would say it's probably in that range. It's typically like an 80, 20.
Like I'm always just trying to think about like, how am I? and 80 is what i know is working 20 is always testing constantly everything that i'm doing is that that's big and i think that's a good place to end uh before so the key takeaway here um is this so with the engineers i have to constantly remind them on the team hey guys like it's cool to build but the challenge is if you just keep build build build you're not going to go anywhere right the good thing about marketers we know how to we know how to fail really really well so it's build measure iterate which is what cody's talking about like once you find the signal all in right and then once the signal starts to decrease okay onto something else over and over and over again that game never ends but that's what makes it fun right um but cody this has been amazing what's the best way for for people to find you online yeah yeah thanks for having me eric uh i'm pretty active on twitter and linkedin those are kind of the two socials i and then youtube and uh as well actually i'm like we're just about to go into another sprint there um and i'm literally going to be teaching like
everything that I just described in way more detail when it's not in a live setting and you'll get like step -by -step because we can actually do edits and we don't have to wait to watch the prints occur. But yeah, those are the best places.
The Hook
The bait, then the rug-pull.
Eric Siu opens promising 'the best AI workflows for business, for marketing, for sales,' then hands the screen to Cody Schneider, who spends the next hour live-building the SEO, ad-creative, and cold-outbound infrastructure most marketing teams still run by hand.
Named ideas worth stealing.
10:40model
Marketing engineering infrastructure stack
- Data pipeline
- Data warehouse
- Cloud server to run code
- Media storage
- Databases for agent-generated outputs
- Cron jobs / recurring tasks
- App authentication
- Git manager
- API gateway to every marketing tool
The nine-piece infrastructure layer Cody's team spent 18 months building so a coding agent has everything it needs to run marketing work end-to-end instead of one-off chat sessions.
Steal forany team wiring Claude Code or Cursor into recurring marketing or sales operations
20:34list
Parasite SEO publish-and-index loop
- Scrape what's ranking on page one for the target keyword
- Feed that content into the agent's context window
- Write a new article in brand voice, informed by a founder interview transcript
- Publish to a high-authority third-party host, never the core site
- Ping the URL with an indexing service like Prime Indexer
- Add CTAs at different commitment levels throughout the page
How Cody's team gets a new keyword to Google page one in under an hour without waiting on their own site's domain authority.
Steal forbottom-of-funnel SEO for a new or low-authority site
25:42list
LinkedIn engager-to-cold-email funnel
- Daily listener checks target creator profiles for new posts
- Extract engagers (likers/commenters) via a scraping API
- Waterfall email enrichment across providers until a verified email is found
- Validate every email before sending
- Auto-upload into a cold-email campaign referencing the post they engaged with
Turns organic engagement on other people's content into a warm, targeted cold-outbound list instead of buying or scraping cold data.
Steal forB2B outbound that wants warmer opening lines than a generic cold email
36:19list
AI avatar ad creative pipeline
- Scrape Reddit/social for pain points and desired outcomes
- Write hook + pain-point scripts at a 12th-grade reading level
- Generate voice audio with a cloned ElevenLabs voice matched to the avatar's setting
- Lip-sync the voice onto a demographic-matched AI avatar via Higgsfield/Seed Dance
- Auto-upload the finished creative into a CBO Facebook campaign
- Feed conversion data back in to remix whichever creative is winning
An end-to-end loop for producing and testing UGC-style video ads without filming a person, at roughly $2.50 per 30-second render.
Steal forpaid-social teams that need high ad-creative velocity without a production crew
46:11concept
TAM mapping + signal stacking
Build a database of every company and decision-maker in the addressable market, then watch for buying-intent signals (job change, content engagement, site visit) to time outbound at the moment someone is entering a buying cycle.
Steal foraccount-based marketing and enterprise outbound
51:20concept
80/20 creative entropy rule
Once cost per action plateaus, roughly 20 to 30 percent of new creative should be genuinely novel to introduce fresh signal, while the rest stays anchored to what's already proven to work.
Steal forpaid-media teams fighting ad fatigue and performance decay
Visual structure at a glance.
