I think one of the most valuable people

in tech over the next 18 to 24 months is

going to be something called a marketing

engineer. Now some people call it a

forward deployed marketer and some other

people are calling it an AI growth

operator. I'm saying call it whatever

you want. The name is probably going to

change but the job won't. It's the

person who can do a whole marketing team

work with AI agents. And I think there's

going to be a ton of money to be made in

it. I actually think this becomes a

250k, 500k, a milliondoll job because

every company wants more leads. They

want faster experiments. They want

sharper positioning and they want to

read on their customers and they want

their just marketing to get smarter

every week with a smaller team than a

bigger team. Whoever can walk in and

just build that with AI agents are going

to get to name their price. So, if

you're a marketer, this is how you

become way more valuable. If you're a

founder, you know this. You don't just

want to vibe code something. You want

people using your product. So, you're

going to have a huge edge if you can use

AI agents to do your marketing for you.

By the end of this episode, you're going

to know what a marketing engineer

actually does. What do they build? What

the tool stack looks like? how to use

things like Grockbot and Claude and

Codeex and Hermes and creative models,

how they all play together within the

context of a marketing engineer, and the

exact 30-day plan I'd follow to learn

from scratch if marketing engineering is

interesting to you. Let's get into the

episode. I can't wait to see what you

[music] build.

So something I can't stop thinking about

is marketing keeps changing and having

been a part of multiple cycles. I've

started and sold three ventureback

companies. You know, one was in the web

era, one was in the social era, one was

in the mobile era. Every time the

technology changes, the most valuable

kind of marketer changes with it. So,

think about the traditional era of

marketing. I actually think about it as

like the Don Draper era where marketing

was about making people care through the

story, through the psychology, getting

your product in front of people on

whatever channels existed at the time.

Things like traditional print media and

radio. The best marketers at that time

understood what people wanted, what they

were insecure about, who they were

trying to become and how to package a

product so the market paid attention.

Obviously, that skill matters a lot. But

then the internet showed up and it

created the digital marketer. So it

evolved from traditional to digital.

Suddenly you had websites, email, SEO,

Google. In 2005, I think six, you had

Facebook ads, landing pages, pixels. The

best marketer became the person who

could acquire customers through channels

you could actually measure. And a lot of

people didn't know these were new

channels. So the the best marketers

understood funnels targeting these new

channels, analytics, things like Google

Analytics and the very practical

question about what happens after

someone clicks.

Then software created loops and then

growth hacking became a thing around if

I remember correctly 8 9 10 11 the best

growth uh hacker people were all about

activation referrals onboarding

retention pricing there was a guy by the

name of Dave Mccclure had this I think

it was called the R framework activation

and referral um that was the you know

the marquee er uh the the the symbol of

the time of the growth hacker era.

Basically, marketing moved closer to

product because the product itself could

become the growth engine. Now, we're

walking into the marketing engineering

era. And I feel like not a lot of people

have spoken about this. That's why I

want this to be the deacto episode about

this whole era. The marketing engineer

still needs all that old stuff. It still

needs, you know, customer understanding,

judgment, positioning, understanding

distribution, uh, taste. Um, if

anything, taste, you know, people talk

about this all the time, but taste

matters more now than ever because AI is

about to make average marketing

marketing just unbelievably cheap. The

new part is that the marketing engineer

also builds the system behind the

marketing. So the marketing engineer is

connecting uh customer data uh reading

the results uh shipping little landing

pages and uh you know calculators and

then turning raw customer signal into

content outbound positioning and product

ideas. So the way I think about it is

traditional marketing was about you know

making people care. Digital marketing

was acquiring customers through

measurable new channels. Growth hacking

was about using product and data to

build these loops. And marketing

engineering is about using AI, agents,

data, code, and taste to build a

marketing system that keeps learning.

Um, and the last phrase is an important

one because a marketing system that

keeps learning is now actually possible

in the agentic era. Now, most companies

already have pieces of this lying around

uh to their credit. So they've got, you

know, tools and dashboards, calls,

content, calendars, CRM, some SAS tools.

Um, the problem is the learning is is

pretty scattered. Um, you know, sales

might hear one version of the market,

support hears another. Uh, product sees

the usage and marketing sees what got

clicks and the founder remembers, you

know, the one customer call that just

hit him emotionally that week and just

can't get that one customer call out of

his or her head. I know that happens to

me. Uh then everyone walks into the

growth meeting with a slightly different

version of reality. So the marketing

engineer's whole job is actually to pull

in these signals into one system and

turn them into growth. So the way I

define the role is this. uh a marketing

engineer's you know is a marketing

engineer is the person who turns market

signal into pipeline using AI agents

data code taste and that's really the

job um and I'm going to get you know

super tactical on how you can actually

do this soon um if I were a founder

right now uh the question I'd be asking

myself is who be who on my team would be

building the growth system for this

company now I am a founder my uh myself

so a lot lot of time I'm doing this

myself. Um, and I just hope that you

know if you're a founder listening here,

uh, either you hire someone or you do it

yourself. Um, and you know, because the

companies that are going to win in this

agentic era are going to learn the

market faster than anyone else. So, it's

kind of it's crucial to know. So if you

see the customer pain earlier, you spot

the winning language earlier, you're

testing more angles using fed uh

Facebook ads, shipping more surfaces,

lead magnets, and understand what's

working before the competitor even

notices things, you have this unfair

advantage. So the question I get asked a

lot is, okay, but what is the first

thing I would build? Okay, I want to

become a marketing engineer. I want to I

want to do more marketing engineering.

What do I build first? And the first

thing I would build is a growth repo.

Yeah, I know it sounds a little bit

nerdy. Um, but you know, even if you're

non-technical, I believe you can do it.

So, you're going to want to go and

create a GitHub repo. Um, or honestly

just a structured folder. Uh, you can

call it something like growth OS. And it

becomes a place where the company's

marketing memory is going to live. The

problem it's going to be solving is that

most people use AI in these random

chats. So they'll open up a chat GBT or

Claude Gemini. They'll ask for 10 posts

and maybe they'll copy and you know copy

one into a doc that they like and then

the work just disappears. Next week the

AI is starting from scratch again. Uh

when what it really needed was the

performance data and the founders voice

and the objection from the sales calls

and the language that actually created

replies. So the growth repo is going to

fix that. Um, and inside it, what we're

going to have is a customer truth

folder, and that's going to have our

sales calls notes or support tickets,

maybe some churn notes, interviews, um,

even uh, live product feedback can go in

there. So, you've got uh, a content

engine folder with the founder voice

guide with the winning hooks and the

scripts and notes on what performed

before. You've got an outbound engine

folder with the ICP, your ideal customer

profile. Uh the account research, the

trigger events, maybe some approved

angles could be good to have there. Even

actually ban uh band language is good to

have as well. Um because you know AI

outbound gets weird fast. If you let it

talk like an overexited SDR who just

discovered personalization, you know,

sometimes bad things could happen. So,

you've got a creative testing uh folder

for ad angles um and things like landing

page tests and hooks and offers and

results. And you've got an agents folder

where you define the jobs your AI

workers do. And that repo is the

difference between hey AI helped me make

a thing and AI is helping the whole

company get smarter. That's how a growth

or a marketing engineer uh you know is

thinking about it. And then the prompt

gets way better. So instead of hey you

know write me 10 LinkedIn posts, you say

you know read me read the customer truth

file, read the founder voice file, read

the last five uh posts that drove

qualified replies and draft five new

posts around Payne's buyers that were

actually mentioned this week. So, it's a

totally different level of output. Um,

because the agent is now having real

context. What tools do I need if I want

to become a marketing engineer? Well,

I'll tell you some of the most important

ones and how to think about, you know,

where all the tools fit uh and your tool

stack. So, you know, Grockbot is new,

but it's just an incredible uh product.

So I think of Grockbot as the growth

operating system that lives close to the

internet. So marketing is a living

system. The marketing is moving.

Competitors are moving. Culture is

changing. Customers are changing their

language. Uh creators are picking up new

formats. Um you know Grockbot is

especially useful in that world because

it is connected to the X ecosystem. If I

were setting this up as a founder, I'd

give it a few clear lanes. So, I'd say

one bot watches competitors and tells me

what changed. One is going to watch

customer language across X and Reddit.

One watches the creators in the niche

and finds formats worth testing. And one

watches ads and landing pages. Um, you

know, [clears throat] basically wherever

there's a connection to the internet,

you know, Grockbot is going to be extra

good there. That doesn't mean you can't

use Grockbot to do everything. You

totally can. Um, and I think, uh, you

know, I'm one of those people that, you

know, say like, you know, basically, you

know, pick an ecosystem that you like,

that you feel comfortable with. If

Grockbot feels good for you, you know,

just do everything in there as well. The

way I think about it, this is just the

way I'm thinking about it. So, uh, hope

it gets the creative juices flowing. You

know, for me, I use Claude and Codeex

and products like that in in a different

part of the system. So, they're going to

help me build the repo and generate the

landing pages, writing scripts, building

the little internal tools that I was

talking about. Um, and then, you know,

turn that repeatable work into something

durable. Um, you know, I've talked on

this channel about Hermes before. Hermes

style workflows are still extremely

valuable, uh, especially when you want

scheduled operations with memory and

approval. So something like every Monday

morning build me a market brief or every

Friday afternoon review the experiments.

Um every time a fresh batch of sales

calls land, you know, maybe put it in a

folder and then pull the objections and

update the positioning file. Then you

have creative models. Then they're going

to help you move faster on ads,

thumbnails, mockups, and video concepts.

Um there's a bunch of those that exist.

There's foul AI, there's Higsfield,

there's a bunch of them. And local AI

matters when the data is, you know,

particularly sensitive or there's p

private customer transcripts or

regulated notes, pricing plans,

basically anything a company would feel

weird sending into a cloud tool. Um,

also things that are expense, too

expensive to do into a cloud tool. I'm

going to do a whole separate episode on

local AI. So, so stay tuned for that

over the next one or two weeks, you

know, and subscribe. Uh, so that comes

into your feed. The tools are going to

keep changing, but the workflow is the

thing to actually learn. So, where it

gets really interesting is when the

agent connects to live business data and

the tools obviously to actually do the

work. So, take SEO content. The beginner

version is asking an AI to write a blog

post about a keyword. So, a marketing

engineer isn't going to do that. A

marketing engineer is going to check

Google Search Console, pulling, you

know, keyword data from Hrefs or or SEM

Rush, look inside this CMS to see, you

know, if it already exists. It's going

to rank opportunities by volume and by

buyer intent and it's going to research

what's already ranking uh in you know

hopefully adding the founders's point of

view and draft the post write the

metatitle suggest internal links and

just send the whole thing for approval.

Um that's a pretty big jump but you know

the agent has a job the job has inputs

and the inputs come from the business

and the output goes somewhere useful.

So, every agent is going to need a real

job spec. And I'd write it out almost

like I was hiring a person. Here's the

data sp here's the data source. Here's

when you run it. Uh here's what you

filter out. Here's the output I expect.

Like here's what good looks like. Here's

what's going to need human approval.

Here's the metric that matters. And

here's what you write the result so the

system gets smarter next time. So for

you know maybe a competitor engager

agent that might be every weekday

morning check these 20 LinkedIn accounts

and pull the people who commented on new

post enrich them drop the drop the bad

fit leads and draft 10 messages tied to

a specific post they engaged with. Oh

and then obviously write that write the

results to a file for approval. The

metric is going to be positive replies

from qualified accounts because a

marketing engineer cares about business

results, right? Not activity counts. Uh

messages sent is activity. Quality

qualified replies is going to be your

signal. And the whole point the

marketing engineer is trying to do is to

generate pipeline demand. And you train

these agents the same way you train a

new hire. You start with small tasks.

You watch it work. You correct the

mistakes. You add the correction to

memory because now we have memory and

then you expand the scope as you

increase your comfort level. If the

outbound agent writes a first line that

sounds like fake, for example, you got

to add the rule to the repo. And if the

content agent keeps writing these

generic intros that sound like generic

AI, you give it three good examples and

three bad ones. If the customer truth

agent makes a claim with no evidence,

you know, we got a problem here. You got

to add the rule to that. Every insight

needs a quote or a link or a source.

Every correction becomes part of this

operating system, this growth, you know,

marketing engineering uh uh system. And

that's how this whole thing compounds.

And going back to like how does a, you

know, marketing engineer make a million

a year or $500,000 a year or $1.5

million a year for their own startup.

It's because they're building this and

it's so darn valuable. But let's let's

actually get into a concrete example so

that just this gets solidified into your

head. So imagine a vertical SAS startup

selling software to commercial HVAC

contractors. These are companies

managing technicians and service calls

and maintenance contracts

uh and and dispatch. So, it's a real,

you know, B2B market. Um, the buyer has

a lot of money. The workflows are messy

and the language is specific, which is

why I wanted to use this uh example. The

marketing problem for that company is

usually a little bit more sharper than,

hey, we need some more content. Um, the

real problem that they're facing is

usually something like which pain gets

the owner to take a a demo. Uh, maybe

it's dispatch chaos, or maybe it's late

invoices. Maybe it's that the owner has

no idea which jobs were profitable until

the month is over. Or maybe it's

actually that the technician finishes a

service call, spots a replacement

opportunity, and the follow-up quote

just never gets sent. Um, that's

interesting just because it's really

specific. So, when you have something

specific, you know, it's it's just

interesting.

you know, my bunny ears go up. Stop

losing replacement revenue after every

service call is obviously a much sharper

angle than run your HVAC business

better. So, this is where your marketing

engineer is going to earn their keep,

right? It's going to start with the

customer truth system. That first system

is going to be the customer truth

system. And every startup says they

understand the customer and you talk to

five people and they get five different

results. We talked about that. But the

marketing engineer is going to pull

those signals into one place. The output

is a file called what the market is

telling us.md. I tweeted about this

idea. It went viral. I'm glad people

liked it. It's basically this a markdown

file which updates every morning or

every week depending on how much signal

the c uh the company is going to have.

And it's reading the sales calls and

support tickets and churn notes. Uh even

stripe movement. Um, oh, CRM notes is a

good one. Uh, and also social data,

especially if it's more consumerry, and

its whole job is to show what's changed.

So, maybe the buyers are using a

different phrase than they were you

using a month ago, or maybe the trial

users keep getting stuck before they

invite a teammate. You're just going to

get some insight

and you're going to ask the agent to

show quote snippets, uh, ticket links,

event counts. Um, what you don't want is

obviously a vague summary, which a I've

seen a lot of people do this. They just

get these summaries and it's pretty

vague. Like in this case, you'd get

something like u customers want better

collaboration.

You want something way more sharp than

that. I want the thing that's going to

make the business, you know, harder to

lie to. So, for the HVAC company, you

know, good memo might be something like

five sales calls this week mentioned

emergency dispatch, but the calls that

actually converted all talked about

missed follow-up quotes after the tech

left. Um, just a lot sharper.

The second system is the founder content

engine. So, a lot of companies have uh

raw material, great raw material, like

the founder has opinions. Um, and you

got customer stories. Um, but you know,

you're not really capturing all the

stuff. So, the marketing engineer could

build the loop. So, you can record

founder founder talking to customers.

You can pull from podcasts, extract the

strongest ideas, and then have the

system watch what performs. you know

which hooks you know people keep

watching because you have this data

right and then you create uh content out

of that for the HVAC company um imagine

something like the loss replacement

revenue insight becoming you know five

things a founder post about the hidden

revenue leak in service businesses a

short video on why contractors lose

money after the first visit a landing

page line that says every completed job

uh should create the next quote a cold

email angle could be good and a simple

calculator that estimates the loss

revenue. Um, so the system here is

learning the the third system is the

outbound signal engine. So bad outbound

uh usually starts with a spreadsheet a

spreadsheet full of names. But good

outbound starts with timing. So, who

just raised money? Who's hiring for the

exact problem you solve? Who posted

publicly about, you know, a pain point?

Um, and then who fits your ICP and has a

real reason to care this week. You know,

these people are, you know, they they've

got the pain. You're selling

painkillers, not vitamins with with when

timing uh hurts.

So having an agent watching those

signals, researching accounts, uh

drafting specific angles and sending to

human for approvals, that's the type of

thing that for the HVAC company would be

awesome. So like watching for

contractors, hiring dispatchers or

opening new locations, getting bad

reviews, and then having the agent

actually go and reach out outbound uh is

going to be huge. The fourth is the

creative testing engine.

So, uh, you know, taking one offer and

spinning up 20 hooks, 10 ad angles,

recording the results, and testing them.

So, a lot of people say like, "Facebook

ads don't work for me." Uh,

yeah, maybe. Or maybe the creative,

you're just not testing enough creative

with the right angle. So, a good uh

marketing engineer, you know, could

create thousands of pieces of creative

uh based on, you know, your positioning.

Um, it's basically like having

uh creative becoming this like learning

system, not really a treadmill that you

actually have to do, you know, have to

do. You're going to have it on repeat,

having these agents go and create

creative based on uh just how the world

is changing and how that data is is

changing too. And again like another

like huge insight around like wow this

is like a new way of doing marketing

marketing engineer. The fifth system is

AI search visibilities. So, you know,

you now have billion I mean there's a

billion plus people using chat GPT

asking ju just chat GPT. I'm not talking

about Google AI uh AI overviews or or

Gemini or Perplexity or Claude. Uh I

just saw Sam Alman said they have a

billion users. It's insane. So you got

to think about whether your company is

even understandable to those systems and

then having agents actually go pull in

that data and actually create content

and optimize your website such that

you're you know ranking high there.

Getting cited by AI is like such a huge

opportunity and something that a

marketing engineer is thinking about. Of

course the sixth system is the growth

cockpit. So you know this is like a

weekly view that tells the team what has

changed and what to do about it. What's

con what content has worked? What

campaign created real conversations?

Which objection came up again? What test

won? How many tests won? What percentage

of tests won? What competitors moved? Uh

what customer pain is getting louder and

what to test next. You know, for the

HVAC company, the cockpit might say

something like, "Hey, you know, this

week the lost uh replacement revenue

angle drove fewer clicks than the

dispatch angle, but twice as many demo

requests from owners with more than 20

tech. So, that's the kind of memo that

if you're an executive, you want to wake

up to that. Um, and that's super super

valuable. So, if you've gotten this far,

what are some ideas on how you've

actually could get can make money with

marketing engineering? And you know, I

think there's a few ways that you can do

it. The first is becoming the person

inside the company. So, if you're

already a marketer or a RevOps person, a

growth person, a creator, um or just

honestly like a curious

um marketing-minded person, this is one

of the clearest ways to become way more

valuable uh because this work sits

directly next to uh revenue. All the

ideas that we talked about, all the

systems that we talked about is things

around creating pipeline, lifting

conversion, uh cutting wasted spend is

huge with things like uh these marketing

agents. And you've got this direct line

to business value. And that's how

someone becomes a $500,000 hire because

they look at it and they're like, "Well,

if I'm going to save $2 million and I'm

going to increase revenue uh this this

amount this much and I'm going to double

the conversion rate, uh that's a huge

huge like it's it's a win-win

situation." Um so you know why in the

original I said I think that there's

going to be people make a million

dollars doing this and I actually think

that's conservative. I think there will

be versions of that of the best

marketing engineers

uh making millions of dollars a year is

because

uh they're going to be just driving

insane amounts of value uh in the same

way that forward deploy engineers are

driving insane amounts of value for

companies right now. The second way is

just do consulting. So you embed, you

know, you create an offer, you embed

with a founder company, maybe it's 30,

60, 90 days. Uh you build one growth

system and then you sell the outcome. So

hey, we'll build your customer true

system and turn it into weekly campaigns

or we'll build your founder content

engine or we'll build your outbound

signal engine. some of these ideas that

we talked about, you just embed

yourself, you build it, uh, and you

charge, you know, 5, 10, $30,000

a month depending on what you're

actually building. The third, uh,

somewhat less talked about is

productized services. So, you can pick

one, uh, one wedge and then repeat it.

So, for example, outbound signal engines

for vertical SAS, it's what you focus

on, or founder content engine for B2B

CEOs.

uh customer truth repos for seedstage

startups before they hire a a full

marketing team. So the tighter the

wedge, the easier it is to sell, deliver

and repeat. And that's like the only

thing that you focus on. That's why it's

called productized service services

because it's not like you're doing

services custom things for everyone.

There's this one thing you do for this

one niche and you charge x amount of

dollars for it. The fourth is software.

Um, I think the biggest outcomes are

going to come from this, but I do think

that I would start with services first.

So, you do the work by hand, you build

the same system for five companies, 10

companies, and you notice the pain that

repeats, and then that's when you turn

it into software. Um, that's and that's

also how you avoid building something

that nobody wants. Uh, the fun part is

all these ideas actually stack together.

You can start by consulting to learn

what actually works. You can notice the

same system every client needs. You

productize it. You eventually turn it

into software like you know set of

agents. Um if I were doing this uh

tomorrow morning, I would keep the first

version almost painfully simple. You

know, I would, you know, build that

growth OS folder. I'd have five of those

files. customer truth, founder voice,

uh, experiments, agent jobs, and then I

would paste 20 real customer notes, um,

or or call call summaries, and then I

would ask the agent to do one job. I'd

say, tell me what's changed, show me the

receipts, suggest one marketing test

that could create pipeline this week,

not next week, not a month from now. And

then build one thing from that output.

you know, for that HVAC company I was

talking about. Maybe it's the loss

replacement revenue calculator

um or something like that. The first

goal is just to prove the system can

turn this messy market data into one

useful uh action. So, if you listen to

this and you're like, "Wow, being a

marketing engineer sounds really cool. I

want to go hone my skills in the next 30

days to become a marketing engineer. Be

it as an employee, as a founder,

whatever it is. Here's the plan that I

would run. Week one, I would do an

audit. So, I'd pick one real company. It

could be yours, a friends, uh, whatever

you can get access to. I would study the

website, the offer, the ICP, uh, the

founders content if there is any. Um,

oh, sales calls and support tickets if

you can get them obviously. Um, and then

you output, you know, a market map.

Who's the customer? What pain do they

describe? What words do they use? And

what would you test first? Uh, what are

they buying instead of your product or

this product? Where's the funnel leak?

And what would you test first? So, what

week one is just studying all that

stuff. Um, week two is the growth repo.

So create it, add the folders and build

your first what is the market telling us

uh markdown file. Uh you can use

whatever tools you like. Could be claw

chat chat gbt grockbot uh gemini local

models whatever it is. Uh the tools

actually matter less than the workflow

here. The goal is to basically just to

turn that scattered signal into the meta

with real receipts and actually just

start uh you know feeling like a re a

true marketing engineer. Week three is

your first machine. So you can pick one

system and actually build it. You know,

it could be the content engine, the

outbound signal engine, a landing page

tester. Obviously, this is going to vary

depending on what the company needs and

wants, but just pick one because you

know you're going to get better outcome

with one uh and one working system is

going to beat five like half-built ones.

And then week four, week four is just

all about results. Like what what

changed? Okay, you did this thing. Did

replies improve? Did meetings get

booked? Did any conversion lift? Uh, did

the founder sound sharper? You know, did

the founder like the post? Um, at the

end of your month, you should have a

case study that sounds something like,

you know, I audited this audited this

company's growth. We built this customer

truth repo I found was like one high

intent pain that they didn't know about

and I turned it into an outbound signal

engine which shipped you know 75

targeted messages got nine warm replies

booked three calls and I documented

everything what I learned um and then

you're showing like a real business

result tangible value um and that's how

you get hired that's how you get clients

and that's how you become credible I

think the Best marketing engineers are

going to feel like part marketer, part

product person, part revops, part data

analyst, part creator, and part

engineer. So they can talk to a

customer, they can build the workflow

that uses that insight. They can write

the positioning. They can wire the

automation. And they can make the

landing page. And they can read the

conversion. And they can set the

outbound agent. And they know when

personalization sounds fake. And they

can use AI to make more. And they've got

the judgment and taste to know what

should exist in the first place. The

agents are going to be a commodity at

some point. Your judgment about what to

point them to is the moat. And that's

the job of the marketing engineer

really. And I think it's going to be one

of the most valuable jobs out there. Um,

if this is if you're a marketer, uh,

this is how you become the person your

company literally cannot run without.

And if you're a founder, this is how you

get agents running your marketing for

you. Um, I think there's a real edge

that uh you can have when you're

actually using marketing agents to

actually grow your startup ideas because

people are still stuck in the old growth

hacker or even even worse digital

marketing era of marketing. I think this

window is open right now. I think a lot

of people haven't built the machine and

I wanted to give you the sauce so that

you can uh internalize it so you can

process it so you get your hands dirty

around building some of these agents,

some of these marketing agents because

it's all about increasing your

probability of success when it comes to

building your own startup. And I thought

that that, you know, hey, if you can get

a promotion, if you can, if you can, you

know, have more fun being an employee

working within uh an organization, why

not? Why not do this? Um, so hope this

has been helpful. Obviously, I could

have gone deeper in so many parts of

this episode. There just wasn't enough

time. Um, but do let me know what you

want me to go deeper in. Is it the

Grockbot point, you know, part? Is it,

you know, different uh, you know, the

markdown files, skills? Uh, you let me

know. I live to serve. I'm here to just

give that information to you. Hopefully,

uh, you enjoy it. Hopefully,

um, it gets your creative juices

flowing. And if you haven't liked,

comment, and subscribed

at this point, I don't know what you're

doing. H, hook it up. You're hooking

yourself up. you're getting more quality

content in your feed, less slop. So, uh,

thank you for giving me your time. Hope

it's been helpful, and I'll see you next

time.