fakenerd.ai

ninja nerdingCody Schneider's marketing engineering crash course

Cody Schneider's marketing engineering crash course

Cody Schneider has done digital marketing for 15 years and co-founded Graphed. In 29 minutes he sets up Claude Code and runs a real marketing account from one chat: ads, keywords, leads, a blog post and a dashboard. The short of it: get your numbers into one place the agent can read, let it write back to the platforms, and read everything it tells you.

Jump to the loop, the eleven jobs and their prompts, or try it yourself.

The video

29 minutes, posted Oct 14, 2026, recorded the evening before. The chapters are his. Every timestamp on this page opens the video at that moment. From his YouTube channel, which puts out one marketing engineering video a week.

  1. 0:00 Intro
  2. 1:36 Why marketing engineering is exploding
  3. 2:39 What your coding agent needs: data pipeline + warehouse
  4. 7:35 Cloud server, storage, databases, cron jobs
  5. 10:26 The full marketing engineering stack
  6. 11:47 Install the Graphed CLI
  7. 12:37 Make a static ad with AI
  8. 13:47 Get a Facebook Ads API token
  9. 16:08 Graphed tools: the unified API
  10. 17:18 Upload the ad to Facebook Ads
  11. 19:14 Turn ads off from Claude Code
  12. 19:47 Ask questions across Facebook, GA4, Search Console
  13. 20:52 LinkedIn post engagers to emails
  14. 21:33 Keyword research for versus content
  15. 22:58 Find page-two keywords
  16. 24:08 Write and publish a blog post with the SEO plugin
  17. 25:03 Waterfall email enrichment
  18. 25:57 UGC ad scripts from Reddit pain points
  19. 26:32 Edit the dashboard
  20. 28:06 Wrap-up

Eight signals

The whole video in eight boxes. Each links to the part of this page that explains it.

  1. 010:15

    The agent does the middle work

    Copy, ad images, uploads, keyword research, lead lists, blog posts, dashboards. The work between the idea and the result moves to a coding agent. You still pick the idea and judge the result.

    How
  2. 022:59

    Data first, then tools

    Before the agent can market, it needs your numbers in one place: a pipeline that copies them in, and a warehouse that holds them. Everything else in the video sits on that.

    How
  3. 035:30

    Read from one place, write to many

    The agent reads from the warehouse. It only calls Facebook or Google directly to change something: upload an ad, pause one, move one. Results flow back into the warehouse. That's the loop.

    How
  4. 044:29

    One source can lie

    Ad platforms report their own wins. Follow the trail to signups and revenue in your own data before you trust a channel. On screen, his warehouse shows months of ad spend with zero signups.

    How
  5. 057:35

    Eleven pieces of plumbing

    Pipeline, warehouse, a server that's always on, file storage, databases, timers, a place to host pages, logins, share links, git, and access to many APIs. You can build it from open parts or buy it bundled.

    How
  6. 0614:53

    Keys live in a vault

    Give the agent a long-lasting ad token, but keep it in a secrets manager, not a file on your laptop. The agent uses it by name and never prints the value.

    How
  7. 0718:35

    Several jobs at once

    He starts a job, and while it runs he starts the next one in another chat. Once a job works, he moves it to the cloud on a timer so it runs without him.

    How
  8. 0816:15

    Read what comes back

    The agent swapped the image model, wrote ad copy he didn't ask for, flagged claims in its own ad scripts, and talked him out of 191 thin pages. All of it is in the replies.

    How

Words on this page

29 terms, in plain words. Skip this if you already run ads and use a coding agent.

Marketing engineering
Marketing work done by telling a coding agent what you want, instead of clicking through each tool yourself.
GTM engineering
Go-to-market engineering. The same idea for sales: building lead lists, enriching them and sending outreach with code and agents.
Coding agent / harness
An AI that can run commands and edit files on a computer: Claude Code, Codex, Cursor, Hermes, a Grok bot. The harness is the app that runs it.
API
The door a service leaves open for programs. Facebook Ads, Google Ads and Search Console all have one.
Rate limit
The most calls an API will take in a given time. Go over it and you get blocked for a while, or worse.
Data pipeline
A tool that copies data from all your accounts (ads, analytics, CRM, payments) into one place, on a schedule.
Data warehouse
A database built to hold a lot of data and answer questions about it fast. The pipeline fills it; the agent asks it questions.
SQL
The language for asking a database questions. Coding agents write it well, so you don't have to.
Join
Lining up two tables by something they share, like a date or a campaign, so you can compare them.
Read vs write
Reading looks at data. Writing changes something: uploads an ad, pauses it, publishes a post.
Context window
How much text an AI can hold in mind at once. Millions of raw ad rows won't fit; a SQL answer will.
S3 bucket
Cheap online storage for files like images and videos. S3 is Amazon's; many others copy its format.
Postgres
A popular free database. Agents use small ones as notebooks: which ad used which prompt, which leads they found.
Cron job
A task that runs on a timer: every hour, every morning, every Monday.
Artifact
A page the agent builds for you, like a dashboard or a review board of ads, that lives at a link.
CLI
Command-line tool. A program you or your agent run by typing a command. Graphed's is installed with npm, the JavaScript package manager.
Secrets manager
A locked store for passwords and API keys. Programs fetch keys by name, so the key itself never sits in a file or a chat.
System user token
A Meta key that belongs to your business instead of a person. It can be set to never expire.
Ad set
A group of ads in Meta that share a budget, audience and schedule.
Pixel
A snippet on your site that tells Meta when someone who saw an ad signs up or buys.
GA4 / Search Console
Google Analytics 4 counts visits to your site. Search Console shows what people searched on Google before they found you.
Branded search
Someone searching your company's name. More of them usually means more people have heard of you.
Versus keywords
Searches like 'ClickHouse vs Postgres'. People typing these are choosing, which makes them good readers to reach.
Page-two keywords
Searches where you rank 11th to 20th on Google. Close to page one, so a little work can move them up.
Enrichment / waterfall
Enrichment fills in missing details like an email. A waterfall tries the cheapest provider first and only pays the next one for people still missing.
Email verifier
A service that checks an address will accept mail without sending one. Results: ok, catch-all (can't tell), or invalid.
UGC ad
User-generated-content style: a person talking to a phone camera about a product. Can be a real creator or an AI avatar.
Hook
The first line of an ad, meant to stop the scroll.
CMS
Content management system, where your blog posts live. His is Strapi.

Your coding agent does the middle work

Marketing engineering, in his words, is having your coding agent do the middle work you used to do by hand as a marketer. The idea and the judgment stay with you. The clicking, copying and uploading go to the agent. 0:15

Jobs anyone can hand over · three basic

His · shown in the video

Ten versions of one ad

Give it one headline, your brand colors and the words you can't use. It makes ten 1080×1080 images and saves them in a folder.

His · shown in the video

Pause an ad by name

Say which ad in which ad set. It finds it, pauses it, and tells you nothing else changed.

His · shown in the video

One question, three sources

How many signups came from Facebook this month, what did GA4 see from Facebook, and are people searching our name more?

Jobs once the data is wired · three advanced

FakeNerd example

Spend with no signups

An hourly job that checks every ad's spend against signups in the warehouse and messages you about any ad over a set amount with none. You decide what to pause.

FakeNerd example

Monday SEO list

Each week: page-two keywords from Search Console, bot traffic removed, top ten ranked, a draft post for the best one waiting in the CMS.

His · shown in the video

Complaint to ad

Pull what buyers complain about on Reddit, cluster it, write ten UGC scripts that each answer one complaint, then send them to an AI avatar.

Two ways to wire it · why he puts a warehouse in the middle 3:25

Before · the agent calls every API

Fast to try, breaks at scale

  • The agent calls Facebook, Google and GA4 directly every time it has a question.
  • Heavy reading hits rate limits. On Facebook Ads, he says, it can break the terms and get the ad account banned.
  • Matching data across sources happens inside the agent's head, and it makes things up.
  • Millions of rows don't fit in the context window.
  • Fine for one small account on one channel. Breaks once there's real volume.

After · read the warehouse, write to the APIs

His way

  • A pipeline copies every source into the warehouse on a timer. His syncs hourly.
  • The agent writes SQL against the warehouse. Joins happen in the database, not in the chat.
  • The answer that comes back is a few rows, not millions.
  • The agent only calls a platform's API to change something there.
  • The change shows up in the next sync, so the agent sees what its own change did.

His firm has done this for two years, he says, and companies keep arriving after trying the first way on a laptop and hitting these walls. Everything in marketing is now code, in his view, so the job is giving the agent what it needs to do marketing with code. 6:35

Is it a real job? 1:36

What he says

  • Searches for "marketing engineering" took off from 2024. The chart on screen shows about 2,400 a month, up 232% on the year.
  • Job listings are "skyrocketing".
  • "You can easily make $150,000 plus a year."
  • It's on the same path as GTM engineering, the sales version.

What we found

  • The same chart shows searches down 53% on the quarter. It comes from a browser add-on on top of Google Trends.
  • The Wall Street Journal (Sept 30, 2026): "marketing engineer" listings up 29% on LinkedIn, but only 173 people started such a job in the year to August.
  • Posted US salaries we found run about $127k to $296k, at funded tech companies. Fair for that slice, not for marketing jobs in general.
  • Growing fast from a small base. A skill to add, not yet a job title most companies hire for.

Source: The Wall Street Journal, Sept 30, 2026.

Eleven pieces, and everything he names

His list of what an agent needs before it can do marketing work. He names a do-it-yourself option for each, then uses Graphed, his own company, which bundles all eleven. 10:26

1Data pipelineCopies data from every account into one place.DIY: Airbyte (open source)2:59
2Data warehouseHolds it all and answers SQL fast.DIY: ClickHouse (open source)5:00
3Cloud serverA computer that's always on, so jobs run while your laptop is closed.FakeNerd note: Netlify hosts sites and short functions. For an always-on box, Railway, Render, Fly or a small VPS fit better.DIY: "Something like Netlify"7:35
4Media storageWhere the images and videos go.DIY: An S3 bucket7:56
5Databases for agentsSmall Postgres databases the agent makes when it needs to remember things.DIY: Railway8:25
6Recurring tasksTimers that start jobs.DIY: A cron job on the server8:58
7Artifact hostingA place for the dashboards and review pages the agent builds.DIY: Vercel9:17
8LoginsSo only your team can open those pages.DIY: A login database you set up9:28
9Share linksLinks to those pages that respect the logins.DIY: Same login database9:28
10Git managerLets several people change the same code without writing over each other.DIY: GitHub9:40
11API gatewayOne door to the many paid APIs: images, video, emails, scraping, keywords.DIY: "Subscriptions to the 40 different APIs"10:00

Where he types · any coding agent works

  • Coding agent

    Claude Code

    What he uses throughout, in the Claude desktop app with Opus 5.5 on high effort. He says Cursor, Codex, Hermes or a Grok bot work the same way.

    0:00 Site

  • Dictation

    Superwhisper

    He speaks most prompts instead of typing them. A friend's company, he says.

    11:56 Site

Where the data comes from

  • Ads · read and write

    Meta Ads (Facebook)

    Read through the warehouse. Written to through the Marketing API with a system user token: upload, pause, move ads.

    13:47 Site

  • Site visits · read

    Google Analytics 4

    Traffic by source. He asks how many visits came with Facebook as the referrer.

    19:59 Site

  • Search · read

    Google Search Console

    What people searched before they found you, and where you rank. Used for branded searches and page-two keywords.

    19:59 Site

  • Also piped in

    Google Ads, CRM, Stripe

    He names Google Ads, a CRM like Attio or HubSpot, and Stripe payments as sources, so ads can be traced to revenue.

    3:10

What the agent called, by job

  • Static ads

    GPT Image 2

    He asked for GPT Image 2.5, OpenAI's newest (Sept 2026). The reseller didn't support it yet, so the agent used GPT Image 2 and said so. Nano Banana is also on the list.

    16:15 Site

  • Model reseller

    Kie

    One credit-based API for many image and video models: GPT Image, Nano Banana, Seedance. The captions call it "Kai AI".

    16:08 Site

  • Video and AI avatars

    Seedance, HeyGen

    Seedance makes video clips. HeyGen makes a talking avatar read a script. For UGC-style ads.

    16:50 Site

  • Reddit research

    xAI API

    He says he runs the Reddit pain-point search through xAI's API (Grok). xAI's own tools are web search and X search; there's no Reddit-only one.

    17:53 Site

  • Keyword data

    DataForSEO

    Search volume, difficulty and cost per click. The versus-keyword run cost $2.57.

    21:43 Site

  • Find emails

    Apollo, LeadMagic

    People and company lookups. The waterfall tries the cheapest first.

    25:25 Site

  • Check emails

    MillionVerifier

    Checks a guessed or found address before you send to it.

    24:50 Site

  • Scraping and search

    Apify, ScrapeCreators, Serper

    Ad libraries, LinkedIn engagers, social profiles, Google results. The cheapest option per job is picked for you.

    16:35 Site

  • Blog (CMS)

    Strapi

    Where his blog posts are published. The SEO plugin uploads to it.

    15:34 Site

His product · one option, last

  • All eleven pieces in one

    Graphed

    The company he co-founded. Pipeline, warehouse (ClickHouse), storage, Postgres, agent runtime, hosting with logins, a secrets store and one API to 232 paid tools (he says about 250), used from a CLI. Tools are pay per call at 1¢ a credit.

    11:06 Site

Also named, not part of the setup

  • tldraw The whiteboard he draws the stack on.5:30
  • Looker Studio, Power BIDashboard tools he says a warehouse plus an agent can replace. Google renamed Looker Studio back to Data Studio in April 2026.18:15
  • Instantly Cold email tool. Its key sits in his secrets list; not used in the demo.15:34
  • HighLevel, Twilio, PostHogNamed as more data sources you can connect.12:15

The loop

Seven steps in a circle, plus five things the circle runs on. Darker boxes are the two steps that need you. Click any box to read it, or press Start and follow the ad he makes in the video.

The loop · read from one place, write to many · darker boxes need you

Beside the loop · what the loop runs on

Follow one ad through the loop

Nine beats, using the ad he makes in the video: from a prompt to an image, into an ad set, through the warehouse and back. Watch which boxes light up, and the one beat the video skips.

The loop · step 3 of 7 · Warehouse

Watch at 5:00

Warehouse holds the truth

Everything sits in one database built for big tables and fast questions. It's the source of truth the agent makes decisions on.

Why: Joins happen here, not in the agent's head. The agent gets back a small answer instead of millions of rows.

What you see

Tables named after each source: ad spend by day, sessions by referrer, search queries by week.

Watch out

Different sources name the same thing differently (campaign IDs, dates, time zones). Ask the agent to show the join it used.

He draws the first half of this on a whiteboard: sources into a warehouse, the warehouse into Claude Code, an arrow marked reading and one marked writing back to Facebook ads. The seven steps and their order are ours. 5:30

Eleven jobs, each with his prompt

Everything he runs in the video, grouped by area. Each has his prompt, as typed on screen or as said aloud (his are dictated, so they ramble), and a FakeNerd fill-in version that works with any tools. Then what came back, and what to watch.

Ads

Make a static ad

12:49

His · said aloud, from captions

Use the Graphed CLI. I want to make a static ad that's a 1080x1080 pixel ratio using the ChatGPT Image 2.5 API endpoint. And that ad, I want it to say something like "marketing engineering crash course". And go to graphed.com to see what the design style needs to be for this ad.

Fill-in version

Make a 1080x1080 static ad with [image model].
Headline: "[headline]".
Take the style (colors, fonts, tone) from [your website URL].
Rules: use only [brand colors]; never say [words you can't use].
Save it as a file and show it to me.
Then make [3] more that change only the headline.
If you can't use the model I named, stop and tell me which one you'd use instead.

What came back

One finished ad in his brand style, generated at 2048×2048 and scaled down. Made with GPT Image 2, because 2.5 wasn't available.

Watch out

Read the reply for swaps. The agent changed the model and said so; you only know if you read it.

Upload it to an ad set

17:18

His · typed, read off the screen

use graphed cli And I'm going to say upload the marketing engineering crash course ad to this ad set

https://adsmanager.facebook.com/adsmanager/manage/ads?act=…&selected_adset_ids=…

Fill-in version

Upload [file name] as a new ad in this ad set: [Ads Manager link].
Use the token stored as [secret name].
First, look at the ad set without changing anything and tell me what's in it.
Create the ad paused.
Headline: [headline]. Body: [body]. Button: [Learn More] to [link] with [UTM tags].
Don't change any other ad.

What came back

The ad, uploaded paused, with a headline, body and tracking link. The agent wrote the body copy itself because he only gave the image text. Its script skips the ad if run twice.

Watch out

Give it the copy, or read what it wrote before you turn the ad on.

Turn an ad off

19:14

His · typed, read off the screen

In that ad set, turn the ad off that has this title gads_questions

Fill-in version

In ad set [name or link], pause the ad called [ad name].
Don't touch any other ad.
Tell me its status afterwards.

What came back

"I turned off gads_questions. Its status is now PAUSED." Meta showed it as in process for a few minutes.

Watch out

Say pause, not delete. A paused ad keeps its history and can come back.

Reddit complaints to UGC scripts

17:53

His · typed, read off the screen

Write some scripts for UGC, have the hooks be something like, okay, this is kind of crazy, or I wish I found this sooner, basically something like that. And then talk to one of the pain points in the outcomes. And again, this is an ad script that a UGC creator is going to read, write ten of these for me based off of the most impactful ideas.

Fill-in version

Step 1. Search Reddit for people who would buy [your kind of product].
Pull out their pain points, the outcomes they want, and their objections.
Group them and count how often each comes up. Quote real posts.

Step 2. Write [10] UGC ad scripts, 30 to 40 seconds each.
Hooks like "[hook 1]" or "[hook 2]".
Each script takes one pain point and one outcome.
Put B-roll and on-screen text in [brackets].
List every claim a script makes about the product, so I can check it.

What came back

Ten scripts, 30 to 40 seconds each, one pain point and outcome per script, stage notes in brackets. Before that, a Reddit report with clusters of pains, outcomes and objections.

Watch out

The agent warned that its counts were estimates and that some hooks made product claims to confirm before the ads go live.

Data

One question across three sources

19:47

His · typed, read off the screen

Look at my Facebook ads data, how many signups have happened from Facebook ads, what Facebook ads pixel is recording, also tell me how many signups are also tell me how much traffic is coming from Google Analytics 4 with referral as Facebook and tell me how many branded searches are happening. Like, are we seeing an increase in branded searches? Use the data source Google search console for this.

Fill-in version

From the warehouse, answer three things:
1. Signups from [ad platform] by month, and what its pixel recorded.
2. Traffic in [GA4] with [source] as the referrer, by month.
3. Are branded searches ([brand name] and its misspellings) going up in Search Console?
Show me the query behind each number.
Mark any month that's only partly over.
Flag anything that looks wrong.

What came back

A table of signups and spend by month. From April to August, no signups on almost $3k of Facebook spend.

Watch out

Ask what happened in the odd months. Broken tracking and a dead campaign look the same in this table.

Turn it into a dashboard

22:23

His · said aloud, from captions

Build a dashboard for me, an artifact that has all this data that we just pulled using the Graphed CLI.

Change the spend by month to a line chart instead of a bar chart.

Add a date range picker to the dashboard.

Fill-in version

Make a dashboard from the numbers we just pulled.
It should query the data live, not copy today's numbers in.
Make it private: only [your team] can open it.
Add a date range picker.
Open it in a browser and check it shows the right numbers before you send me the link.

What came back

A private page on Graphed Cloud that queries the warehouse live, caches for 10 minutes and has a refresh button. The agent said it hadn't opened the page to check it.

Watch out

Open it yourself before you share it, and check who can see it.

Leads

LinkedIn post engagers to emails

20:52

His · said aloud, from captions

[LinkedIn post URL]

Use the Graphed CLI, extract all of the engagers from this post and then use the get leads endpoint to find their emails.

Fill-in version

Get everyone who reacted to or commented on this post: [post URL].
Remove duplicates.
Find a work email for each with [enrichment tool].
Save a CSV: name, title, company, LinkedIn URL, email, where the email came from.
Tell me how many you found and what it cost.

What came back

A deduped list with emails where found and a verifier result for each. He says this one was poor; they usually find about half.

Watch out

Scraping LinkedIn is against its terms, and cold email has rules (CAN-SPAM in the US, GDPR in the EU). That's a FakeNerd note, not his.

Fill the gaps: waterfall, then guess

25:03

His · typed, read off the screen

44 people were not found Hey, those 44. Let's do a waterfall email enrichment now with whatever the cheapest provider is work down that for these other 44

And then also let's just guess the emails of the other 89 and use mill and verifier to see if they're actually real

Fill-in version

For the [N] people with no email:
try [provider 1] first, then [provider 2], cheapest first, and stop at the first hit.
For anyone still missing, try the common formats (first@, first.last@, flast@ and so on) at their company domain
and check each with [email verifier]. Keep only addresses that come back "ok".
Tell me the cost before you run it.

What came back

Before he asked, the agent offered to run LeadMagic on the people with no email, for about $4.60 for 133 people.

Watch out

"Catch-all" means the server accepts everything, so the address may still bounce. Treat it as unknown.

SEO

Find versus keywords

21:33

His · typed, read off the screen

use the graphed CLI for this

Use the data for SEO API. I want you to find all of the versus content for customer data platforms. I'm thinking like, "high touch vs x, click house vs x." Anything that would be in this stack, we're going to write some blog posts about this, but just find me all those keywords

Fill-in version

Use [keyword data tool].
Find every "[X] vs [Y]" search where both sides are tools in [your category], like [tool A] vs [tool B].
Merge "A vs B" with "B vs A".
Give me US monthly volume, difficulty and cost per click.
Save a CSV and tell me what the calls cost.

What came back

765 X-vs-Y pairs from 2,599 variants, both sides real tools, A-vs-B merged. The keyword calls cost $2.57.

Watch out

Say which country. Volumes on screen were US only.

Find page-two keywords

22:58

His · said aloud, from captions

Find all the keywords that we're ranking for organically on page two of the search results for Google. Use the Google Search Console data source and the Graphed CLI data warehouse to source this data and this information for us. I'm basically looking for high impact keywords, keywords that we could potentially rank for really easily if we just write some content or designate some content to it.

Fill-in version

From Search Console, list the queries where our average position is 11 to 20
and we had [100]+ impressions in the last 90 days.
Group them by the page that ranks.
Flag anything that looks like bots: lots of impressions, no clicks.
Rank the top 10 to work on, and say why for each.

What came back

398 keywords on page two. The agent set aside one group with 8,300 impressions and zero clicks as automated queries, not people.

Watch out

When he asked for one post per industry, the agent checked 191 industries and found almost no searches. It suggested one big page instead.

Write and publish a post

24:08

His · typed, read off the screen

Use the graph CLI use the SEO plugin that we have installed and I want you to write a blog post and publish it to the graph blog for this target keyword:

clickhouse vs postgres

Fill-in version

Write a blog post for the keyword "[keyword]".
First read the top results on Google for it and tell me what they all cover and what they miss.
Then write a better one in our voice; here's a post we like: [link].
Save it as a draft in [CMS] and send me the link. Don't publish.

What came back

His SEO plugin reads page one of Google, writes the post with Claude Sonnet and uploads it to his CMS. By the end of the video it's published.

Watch out

He publishes straight away. Start with drafts until you trust the voice and the facts.

His one plugin · SEO 24:08

What it does, in order

  1. 1Reads what ranks on page one of Google for the keyword.
  2. 2Writes the post with Claude Sonnet.
  3. 3Uploads it to your blog (his runs on Strapi).
  4. 4Hands back the link.

To set it up he'd say “install the Graphed SEO plugin, help me set it up to my CMS”. You can change it however you want, he says. Later he calls it as a slash command, /seo-blog.

Watch out

  • It publishes, not drafts, in his setup. Point it at drafts first.
  • Page one tells you what to cover, not what's true. Check the facts in versus posts about other companies' products.
  • The plugin's source isn't public that we found. The steps above are from what he says and what the agent printed.

The Facebook Ads token, step by step

The agent needs a key to make changes in your ad account. He uses a Meta system user token, which belongs to the business and doesn't expire. About 10 minutes, he says. 13:47

  1. 01he says

    Make a developer app

    In Meta Business Settings, add an app. Name it anything.

  2. 02he says

    Pick the ad use cases

    Create and manage ads with the Marketing API, and with Meta Ads Manager.

  3. 03he says

    Connect your business

    Link the app to your business portfolio, confirm, create. Add a privacy policy link. About 10 minutes, he says.

  4. 04he says

    Add a system user

    A user that belongs to the business, not to a person. This is what makes the token last.

  5. 05he says

    Give it only what it needs

    Assign the ad accounts (and pages) it may touch. Nothing else.

  6. 06his guide + Meta docs

    Generate the token

    His guide sets it to never expire, with every permission ticked. Meta allows that, but calls expiring tokens best practice. Tick only the ad permissions you need.

  7. 07he says

    Put it in the vault

    Store it in a secrets manager and tell the agent its name. He pastes it into Claude Code and asks it to add it to his secrets.

Where the key lives 14:53

You can keep the token in a file on your laptop, he says, but he wouldn't: it's a security hole. He puts it in a secrets manager. Asked to list his secrets, the agent printed names only, grouped by project, and no values.

FakeNerd note

A token that never expires, with every permission, is a key to your ad spend. Give it only the ad account and ad permissions it needs. Add it to the vault yourself rather than pasting it into a chat, where it stays in the log.

His full walkthrough, with screenshots: Create a Facebook Ads developer token. Meta's own pages: system users and generating their tokens.

Read the replies

The video moves fast and the narration skips most of what the agent says back. Read off the screen, these replies are the best lessons in it.

  1. 116:15

    It swapped the image model, and said so

    Asked for GPT Image 2.5. The provider said "model not supported" to every name it tried, so it used GPT Image 2 and explained why. The narration still says 2.5.

  2. 218:08

    It looked before it touched

    Before uploading, it said: "First I'll check the ad set without changing anything." It created the ad paused, and its script won't upload the same ad twice.

  3. 322:10

    It found money with nothing to show

    April to August: no Facebook signups on almost $3k of spend. It's in the answer, and the video moves on without a word.

  4. 426:30

    It flagged its own ad claims

    "The counts are estimates… Some hooks make claims about the product… Confirm the product really does each of these before the ads go live." It also fixed one: daily sync to hourly.

  5. 528:00

    It talked him out of 191 pages

    He wanted "Google Ads vs Facebook Ads for [industry]" posts. It checked 573 versions across 191 industries; six had any searches. It suggested one page for the main query instead.

  6. 626:50

    It said what it hadn't checked

    "I did not open the page in a browser, so I have not seen how it renders." Honest, and a reminder to look yourself.

FakeNerd starter · add to your agent's rules file

## Marketing changes
- Before changing anything in an ad account, look first and tell me what's there.
- Create new ads and posts paused or as drafts. I turn them on.
- If you can't use the model or tool I named, stop and say what you'd use instead.
- List every claim an ad makes about the product, so I can check it.
- Before any paid run over [$5], tell me the cost and wait.
- Say what you didn't check (for example, "I didn't open the page").

What it cost

Prices the agent showed on screen. Graphed sells credits; its tools page puts one credit at 1¢, which matches the agent's own quote. Dollar figures marked “≈” are our math.

765 versus-keyword pairs (DataForSEO)$2.57Agent's reply, on screen
Email lookup for 133 people (LeadMagic)≈ $4.60Agent's quote before running
One GPT Image 2 image3.45 credits≈ 3.5¢ by our math
One email check (MillionVerifier)0.046 creditsUnder a tenth of a cent
HeyGen Avatar III video1.92 credits / sec≈ $0.58 for a 30-second read
Seedance video36 credits / sec≈ $3.60 for 10 seconds
Getting started on Graphed$10Said. Graphed's agent setup notes say the CLI needs a paid plan

Cheap per call, but an agent on a timer makes a lot of calls. The agent you use (Claude Code, Codex) is a separate bill. He says Graphed is free to start; Graphed's setup notes for agents say the CLI needs a paid plan. Check before you plan around it.

Try it, smallest version first

Seven steps, cheapest first. Steps 1 to 4 cost nothing beyond the agent you already pay for and change nothing in your accounts. Works in Claude Code, Codex, Cloudroom or bb.

  1. 01

    Pick one question you answer by hand

    The one you dread on Mondays. Did last week's ads make money? Which posts are close to page one? Write it down in one sentence.

  2. 02

    Export the data yourself, once

    Download CSVs from Search Console (Performance → Export), GA4 and your ad account. Put them in one folder. No pipeline yet.

    Search Console export help
  3. 03

    Open an agent in that folder and ask

    Claude Code, Codex, Cloudroom or bb. Paste the starter below. This is the read half of the loop, for free.

    bb
  4. 04

    Make the folder a tiny warehouse

    Ask the agent to load the CSVs into DuckDB, a free database that's one file on your laptop, and answer with SQL from now on. Same idea as his warehouse, smaller. This step is our suggestion, not his.

    Load every CSV in this folder into a DuckDB file called marketing.duckdb, one table per file.
    From now on, answer my questions with SQL against it and show me the query.
    DuckDB
  5. 05

    Add one write, and make it a pause

    Make a Meta system user token for one ad account, put it in a secrets manager, and let the agent pause ads by name. Pausing can be undone, which makes it the safe first write.

    The token, step by step
  6. 06

    Put the copying and the question on a timer

    A pipeline (Airbyte is the open-source one he names) fills a warehouse every hour, and your question runs every morning on a schedule. Cloudroom and bb have scheduled automations; a cron job on a server works too.

    Airbyte
  7. 07

    Or buy the whole stack

    His Graphed CLI bundles all eleven pieces. He gives Claude Code the npm page and says "install this". He calls it free to start; Graphed's own setup notes for agents say the CLI needs a paid plan, so check first. The SEO plugin is one more command.

    npm install -g @graphed-inc/cli
    graphed login
    graphed plugins add seo
    @graphed-inc/cli on npm

FakeNerd starter · paste this for step 3

You're my marketing analyst. The CSV files in this folder are exports from:
- [Search Console: queries and pages]
- [GA4: sessions by source]
- [ad platform: spend and results by ad, by day]

Answer this: [your one question].

Rules:
- Read the files; don't guess. Say which file and columns each number comes from.
- Mark any period that's only partly in the data.
- If the sources disagree, show both numbers and say which you'd trust and why.
- Finish with the 3 changes you'd make, the one you'd do first, and what you'd need from me.
- Don't contact any platform or change anything. Read only.

Next to the others

Other pages on this site that cover the same ground from a different side.

Greg Isenberg: marketing engineers Big idea: One brain folder, six agentsReads: Docs and notes in a folderGreg says what to build: the brain and the six agents. Cody shows the plumbing under them: a warehouse to read, APIs to write. Read Greg first, then Cody.
Nicolas Cole: write it once Big idea: Approved language, no slopReads: Your own past writingCody's SEO plugin writes and publishes posts. Cole is how you keep those posts sounding like you.
Nate B. Jones: ChatGPT Work Big idea: Give it a job, not a questionReads: Files and connected appsThe no-terminal version: spreadsheets, research and quiet monitors in ChatGPT. Good if a coding agent feels like too much.
David Ondrej: mini software factory Big idea: Loops on timersReads: Your repoCody builds a job by hand, then puts it in the cloud on a timer. Ondrej's page is how to run those loops so they check their own work.

FakeNerd's take

The warehouse idea is the lesson

Read from one place, write to the platforms, let the results flow back. That holds whatever tools you buy, and it's the part most "Claude runs my ads" demos skip.

It's a product demo, and it says so

Cody runs Graphed and every job goes through its CLI. The demo is real and useful, but the eleven-piece list is also the sales pitch. Each piece has a free or open option; start with those until you know what you need.

The replies are the best part

The agent swapped models, flagged its own claims, found months of wasted spend and argued him out of 191 pages. Read every reply. That's where you're still the marketer.

Draft before you publish

Uploading ads paused is the right default. Publishing posts and emailing scraped lists without a look is not. Add a review step until it's earned your trust.

Attribution

  • Cody Schneider, “Marketing Engineering Crash Course with Claude Code” (posted Oct 14, 2026). The idea, the eleven-piece stack, the jobs and his prompts are his, retold in our words. Prompts marked as typed are read off the screen; the rest are from the captions. Numbers in “what came back” are read off the screen.
  • Disclosure: the video is sponsored by Graphed, and Cody co-founded Graphed (per his LinkedIn). He calls it the sponsor on camera but doesn't say it's his. Every job in the demo runs through Graphed. Claims about Graphed's features, prices and results are his and Graphed's; nobody has checked them. See graphed.com/platform.
  • Where screen and captions disagree, the screen won: the ad was made with GPT Image 2, not 2.5; Graphed's page says 750+ data sources, not 800+; its tools page says 232 tools, not about 250.
  • His Facebook token guide is Graphed's, summarized. Meta's token rules are from Meta's developer docs.
  • The seven-step loop, the nine-beat walkthrough, every fill-in prompt and starter, the job-market check, the dollar math, the setup order and the takes are FakeNerd's. Not sponsored by anyone on this page.
↑↓ move enter openBrowse every card