Imagine having an entire creative agency and
a personal assistant, even a full market research
firm, all working just for you, you know, 24
-7 and costing less than hiring a single freelancer.
It really does sound like something from, well,
the future. But this isn't science fiction anymore.
It's actually here. Yeah. Welcome, everyone,
to the Deep Dive. This is where we try to unpack
some pretty complex ideas and, you know, make
them accessible for you. Today we're diving into
something genuinely fascinating, a new guide
on building a specialized AI agent swarm. Basically,
a system that can automate your entire media
production. That's right. We'll explore exactly
how this AI army, as you could call it, functions.
Everything from creating really stunning visual
ads to doing deep market research. We're going
to look at some real world examples, peek under
the hood at its architecture, and yeah, even
break down the costs and the setup. Our goal
today really is to give you a shortcut, a way
to understand this powerful kind of game changing
tech without getting lost in the weeds. So let's
get into it. Okay, so this core concept we're
digging into today, it feels genuinely groundbreaking.
It's all about building this specialized AI agent
swarm, and it uses a tool called N8N. Now, for
those maybe not familiar, N8N is this really
powerful open source platform. Think of it like
a digital conductor, maybe, connecting different
services to automate complex stuff, often without
needing much code. Right. And when we say swarm,
we mean like a team of AI agents all working
together, coordinated. And like you said, this
isn't some five -year plan idea. People are building
and using this stuff right now. So what makes
this system so special compared to, say, other
automation tools people might already be using?
Well, the big thing I think is how it shatters
this barrier. You know, the one between the analytical
business stuff and the creative work. Traditionally,
automation was kind of stuck in silos. You'd
have one tool for data, another for design. Well,
they didn't talk much. The system, though, it
creates this integrated team. It really is like
having your own well -oiled creative agency all
connected. That's a great way to put it. A well
-oiled creative agency. So can you tell us a
bit more? What does this AI agency actually do?
What are the capabilities? Oh, absolutely. It
wears a lot of hats. First off, it's your personal
assistant. It can manage email. emails, your
calendar, even organize files in Google Drive.
Pretty handy. Then it's this creative powerhouse,
generating images completely from scratch, doing
complex edits like you'd see in Photoshop, even
creating full videos. It can take a boring static
image and turn it into a dynamic ad. It's also
a social media manager. It'll schedule and post
content automatically to X, TikTok, Instagram,
whatever you need. And beyond just making stuff,
it's a research analyst. It can scrape platforms
for trends, pull insights, and compile it all
into a professional Google Doc report. Wow, that's
quite... Yeah. And one cool detail. It's also
a meticulous account. It logs every single action,
every success, every failure, even the exact
token usage for each task. All in a detailed
log. But the real magic isn't just the list.
It's how seamlessly it all works together. You
can literally upload one image, say, make me
a VFX ad. That's visual effects, right? Motion
graphics. And just watch. It creates, edits,
and then publishes it across your platforms without
you needing to jump between five different apps.
That seamless flow, that sounds like the real
breakthrough here. What's the biggest sort of
aha moment people have when they see this working?
Why does it hit so hard? I think the biggest
aha. is seeing that integration in action, creative
and analytical automation finally working together.
Every campaign instantly becomes data informed.
Okay, let's walk through an example then. You
mentioned turning a basic product photo into
an ad campaign. Exactly. Think of like a creative
assembly line. So we started by sending a simple
image, just headphones through Telegram. And
right away, it wasn't just dumb storage. The
agent put it in the like Google Drive folder,
sure. But then it asked, hey, what should I name
this file? That's intelligent file management
from the get -go. Okay, so it's organizing intelligently,
not just storing. What's the next step after
it's filed? Precisely. From there, the image
went to the design studio agent. We gave it a
pretty simple creative brief, something like,
make this look like a studio shot. Give it energy.
Make it colorful. Capture the feeling of listening
to music. So the creative agent takes that and
figures out which tools to use, generates several
different stylistic options, and then shows you
low -res previews. You get to pick. The result
in our test. Three totally distinct professional
-looking headphone ads, different lighting, different
vibes, all delivered in just minutes. Minutes
for professional quality variations? That's impressive.
What about adding motion? Video? Right. The final
stop was the VFX studio. The command was pretty
straightforward. Take that first preview image
and make it a video ad. Add music, make light
sync to the beat, you know, typical ad stuff.
And the agent did this two ways. First, image
to video. It took our edited headphone shot and
brought it to life with dynamic lighting that
pulsed with the music. Second, text -to -video.
It generated completely new B -roll footage from
scratch, just based on the prompt. Both versions
had professional -grade VFX, lights perfectly
synced. Whoa! I mean, just imagine the possibilities
there. Creating ads with synchronized effects
in minutes, not days or weeks. It's like having
a Hollywood effects team in your browser. Thinking
back to when I first started creating content,
this would have been, well, pure science fiction.
Hours, maybe days of work, just gone. Automated.
That is genuinely astonishing. So with all this
production automated, how does this free up a
creator? What does it allow them to focus on
instead? The bigger picture. By automating all
that production work, creators are basically
freed up. They can focus on the high -level strategy,
the vision, not just the execution grind. They
become architects, not just builders. Makes sense.
We've talked a lot about the creation side, but
you mentioned it's also a research tool. Transforming
a creator into more of a data -driven strategist
with this market intelligence function. How does
that part work? Exactly. So we give the system
a mission. Pretty simple one. Find me two high
-performing videos about NAN on TikTok, Instagram,
and YouTube. And what happened next was pretty
cool. Parallel processing. The social media agent
didn't just check TikTok, then Instagram, then
YouTube. No, it deployed Epify scrapers, which
are like automated browsers that grab data to
all three platforms at the same time. It pulled
view counts, likes, comments, info about the
creators and key insights. You know, what formats
work, what hooks grab attention. OK, so it gathers
all this intel simultaneously. What happens with
that raw data then? How does it become useful?
Right, so once the scraping was done, the AI
agent compiled everything, all the findings from
the different platforms into one single professional
-looking report in a Google Doc, like an intelligence
briefing. And this report had really actionable
stuff. Like on TikTok, it found short, punchy
tutorials were killing it. On YouTube, it broke
down why a specific, longer tutorial was so successful.
For Instagram, it analyzed visual styles and
caption strategies that got engagement. The most
impressive part, this whole... Multi -platform
research task done in minutes. Not the hours
and hours of manual scrolling and note -taking
it would normally take. You'd usually need a
team or at least a dedicated afternoon. That
speed and depth is a huge advantage. Now, you
mentioned earlier this isn't just one big AI
brain. Can you unpack that agent swarm idea a
bit more? How is this whole thing structured?
What's the architecture? Yeah, absolutely. It's
key to understanding why it works so well. It's
not monolithic. It's structured more like a military
unit or maybe a well -run company. There's a
clear hierarchy. At the top, you've got the main
agent. Think of it as the general or the CEO.
It's usually powered by something cost -effective
like GPT -40 mini, maybe through a service like
OpenRouter to optimize costs and performance.
And its main job, delegate. It doesn't do the
work itself. It assigns tasks to the specialists.
It also keeps track of the conversation, the
short -term memory, so it understands multi -step
requests. Okay, so the general delegates. Who
are the troops? The specialists. Exactly. Below
the general are the special forces units. These
are specialized AI agents, each an expert in
one area. You've got the creative division. That
includes the creative agent, the artist doing
image creation, editing, VFX, video. And the
posting agent, the publisher, getting content
out. Then there's the intelligence and operations
division, the social media agent, your spy scraping
platforms, and the web agent, a general scout
for web searches. And finally, an administrative
division, the Google Drive agent, sort of the
digital quartermaster managing files, and a comms
team handling email, calendar, contacts, that
sort of thing. That hierarchy sounds, well, complex,
like building a real org chart. But does that
specialization actually make the system more
robust, more reliable? Yes, absolutely. That
specialization is what makes it robust, reliable,
and actually easier to expand later. Each agent
just focuses on what it does best. Okay, let's
dive deeper into that creative agent then, the
secret sauce, you called it. It's workshop. How
exactly does it menu image and video stuff? Right,
the digital easel handles the static images.
For creating a new image, you give it a detailed
prompt, a name, it uses an API like OpenAI's,
and bam, delivers a preview to Telegram and saves
the high -res version to Google Drive. The editing
workflow is even smarter, I think. You give an
existing image and instructions. Instead of just
making one final version, it generates multiple
low -res previews first. You look at them, pick
the one you like, then it renders the final high
-res image. Ah, that makes sense. Saves time
and compute costs if the first try isn't quite
right. What about video? Yeah, exactly. Then
there's the editing bay. For video. For text
-to -video, you give it a text prompt. It uses
a model, maybe something fast and efficient,
like Google's VO3 Fast, and generates original
B -roll footage. It uses this smart polling thing
to know when the video's ready. And for image
-to -video, like in the demo we talked about,
it takes your image and adds those cool VFX,
like the lights pulsing in time with the music,
adds the audio track too. So it's not just executing
commands, it's actively trying to improve the
output. Precisely. The creative agent also has
this built -in artistic philosophy. Its core
instructions, its system prompt tells it to be
an optimizer, not just a blind follower. So when
you give it a simple idea, its first move is
often to rewrite that idea into a more detailed,
more stylized prompt internally. It's trying
to engineer a better prompt before it even calls
the image or video model. It acts like a creative
director. You know, I still wrestle with prompt
just... myself sometimes that's when the ai kind
of wanders from your original intent over iterations
so having an ai agent basically refining the
prompt for you that's pretty awesome that is
a huge help yeah boosting quality automatically
okay so you've created this amazing content but
it's not much use sitting on a hard drive how
does the system handle publishing Getting it
out there. All right, this is where the posting
agent comes in. And the whole posting system
is built on this really elegant four -step modular
process. Think of it like a standard shipping
container for your content. Makes things predictable.
First step, file prep. Making sure the final
image or video in Google Drive has the right
public sharing permissions so the posting tool
can grab it. Second, platform optimization. The
system automatically tweets things like caption
length, hashtags for whatever platform you're
targeting. X needs different stuff than TikTok,
right? Third, the delivery. It uses a reliable
third -party tool, something like Blotato or
Buffers API, to actually do the posting. These
tools are built for robust delivery. And finally,
Confirmation. It gives you back a submission
ID so you can track that the post went through
successfully. That modular approach sounds incredibly
efficient. Does that really make it easier to
add new platforms later on, say, if a new social
network pops up? Absolutely. That's the beauty
of it. The actual N8N workflows for posting to
X, TikTok, and Instagram, they're almost identical.
The only thing that really changes is the final
destination setting. This makes the whole posting
system super easy to maintain and expand. Adding
support for, I don't know, LinkedIn or threads,
it's basically duplicating an existing workflow
and changing one or two nodes. Really straightforward.
Mid -roll sponsor read. Welcome back to the Deep
Dive. We've just gone through the amazing capabilities
of this AI media agent swarm. Now, the crucial
question, how do you tailor it? How do you make
it work for your specific brand, your workflow?
Where does customization begin? Yeah, this is
the calibration bay, essentially. And it's designed
to be flexible. You can really define your brand's
unique style by tweaking the system prompts within
those creative sub -workflows. That means you
can adjust the default image and video prompts
to match your visual aesthetic. You want minimalist
and clean. Tell it that. Bold and vibrant. Tell
it that. You can also tune quality settings to
balance how it looks versus the cost. Okay, so
you can tune the creative output. What about
the research side or the social media activity?
Same idea. For the social media agent, you're
basically giving your spy its mission parameters.
You can figure the scraping settings, focus on
a specific niche, track certain competitors.
You can also customize posting schedules. Maybe
your audience is active at specific times. And
fine -tune the default captions and hashtags
to always match your brand voice. and for the
research agent you refine its focus adjust the
search terms limit the number of results it pulls
so you don't get overwhelmed customize the Google
Doc templates so reports look exactly how you
want them it's all about tuning its brain right
now let's talk about the operators manual specifically
costs and transparency what are the real numbers
involved in running something like this what
should someone expect Good question. There are
basically three main cost areas to think about.
First is token usage. That's your primary variable
cost, kind of like the fuel for the AI models.
The system smartly uses cost -effective models
like GPT -40 mini for most things. But sometimes,
for trickier tasks, specialized agents might
strategically use a more powerful, slightly pricier
model like Claude or maybe GPT -4 when deep reasoning
is really needed. Second is media generation,
the actual cost of creating the images and videos.
Using OpenAI for images, you're looking at at
maybe $0 .04 per medium -quality image. For video,
using something like Fel .ai with VO3, it might
be around $3 .75 for a high -quality 8 -second
clip with synced audio. Those costs per asset
seem surprisingly low, actually, for that kind
of output. What about fixed costs? Subscriptions?
Yeah, the per -asset cost is pretty manageable.
Then you have the monthly subscriptions, your
overhead, a solid social media posting tool like
Blowdado. Maybe around $29 a month to start.
apify for the web scraping has flexible pricing
and honestly their free tier is pretty generous
for getting started or for moderate use at a
pro tip here always hunt around for special deals
or extended trials lots of these sauce tools
offer them for new users okay and you mentioned
a crucial piece earlier the black box recorder
how does that fit into understanding costs and
performance ah yes the black box recorder This
is absolutely critical, in my opinion. It gives
you a complete, unchangeable audit trail. Proof
of everything your AI army does. How it works
is, it logs all the execution details, timestamp,
which workflow ran, the inputs, the outputs,
the token usage breakdown, success or failure
status, any errors, all in real time to a dedicated
Google Sheet. Why is this so critical? Well,
for rapid debugging, if something goes wrong.
For a smart cost optimization, you can see exactly
where your tokens are going. For full accountability,
and ultimately for a data -driven improvement,
you can actually see what's working and optimize,
just like managing a human team, but with perfect
data. That level of logging sounds invaluable.
Okay, so for someone listening who's thinking,
right, I'm ready to build my own media empire.
What's the assembly manual? What are the practical
first steps? All right. Step one is acquiring
the schematics. You need the NAN workflow files.
You can usually find these shared in online automation
communities, often bundled as a ZIP file. These
files are the blueprints. There are about nine
essential ones. The main agent, edit image, create
image, image to video, create video, the posting
workflows for X, TikTok, Instagram, and the Google
Doc creation workflow. Got it. Download the blueprints,
then comes the assembly part. Then comes the
assembly. This needs some careful, focused work.
First, you import all those workflow files into
your NEN setup. The absolutely critical part
here is linking the tool nodes in the main agent
to the correct sub -workflows. The names must
match exactly for the delegation to work. Second,
set up your Google environment. Create the specific
folders in Google Drive like media and media
analysis where it will store assets and reports.
Set up the Google Sheet using the provided logging
template. Third, API integration. You've got
to gather all your API keys, OpenAI, Google,
Telegram, Apify, your social posting tool, and
add them securely into the NAN credentials section.
Okay, that sounds methodical. What would you
say is the biggest potential snag or hurdle someone
might hit during that initial setup? The place
to be extra careful. Honestly. linking all those
workflows correctly in the main agent, making
sure every connection is right, every name matches.
It really requires attention to detail. It's
like Lego blocks one piece in the wrong spot
and the whole thing might not work as expected.
Right. Attention to detail is key there. So let's
try and bring this all together. This system,
it feels like more than just automation, doesn't
it? It seems like a complete paradigm shift.
You're moving from being just the artist, the
creator, to being the director of an entire automated
creative studio. Not just saving time, you're
genuinely multiplying your creative output. Totally.
And look, let's be real. This isn't a five minute
setup. You definitely need to plan for, you know,
maybe a few hours of careful, focused configuration
initially to get everything wired up right. But
once it is running, you have this absolute creative
powerhouse working for you. Something that if
you try to replicate it with traditional tools
and freelancers would easily cost thousands of
dollars every single month. It's a massive competitive
advantage. It really feels like the AI revolution
in creative work isn't some future event. It's
actually here now. And it's surprisingly accessible
if you're willing to put in that initial effort
to build the system. This media agent army concept
gives individuals and small teams the power to
compete with much larger agencies, potentially
even working solo. So the final thought perhaps
is stop just dreaming about automating your creativity.
The tools and the blueprints are out there. It's
time to start building it. Yeah, and remember,
there are dedicated online communities, even
advanced courses, if you really want to dive
deep and achieve true mastery. Think about how
these ideas, this capability, could fundamentally
change how you approach content creation and
marketing. It really opens up a whole new world.
Well, thank you for joining us on this deep dive
today. It's been fascinating. We'll be back soon
with more insights to unpack. Out to your own
music.